Citation
Hybrid multi-level agent-based decision support system for modeling and simulation of crowd and traffic dynamics

Material Information

Title:
Hybrid multi-level agent-based decision support system for modeling and simulation of crowd and traffic dynamics
Creator:
Alqurashi, Raghda
Place of Publication:
Denver, CO
Publisher:
University of Colorado Denver
Publication Date:
Language:
English

Thesis/Dissertation Information

Degree:
Doctorate ( Doctor of philosophy)
Degree Grantor:
University of Colorado Denver
Degree Divisions:
Department of Computer Science and Engineering, CU Denver
Degree Disciplines:
Computer science and information systems
Committee Chair:
Alaghband, Gita
Committee Members:
Altman, Tom
Mannino, Michael
Biswas, Ashiss Kumer
He, Liang

Notes

Abstract:
Agent-based model (ABM) simulation is a bottom–up approach that can describe the phenomena generated from actions and interactions within a multiagent system. An ABM is an improvement over model simulations which only describe the global behavior of a system. Therefore, it is an appropriate technology to analyze emergent phenomena in social sciences and complex adaptive systems such as pedestrian crowds and vehicular traffic. In this dissertation, a hybrid agent-based modeling framework designed to automate decision-making processes of evacuation during an emergency and during traffic congestion is proposed. The model provides system individuals with real-time alternative routes, computed via a decentralized multi-agent model, that tries to achieve a system-optimal distribution within an entire system, thus reducing the total travel time of all the individuals to reach their goals. The presented work explores a decentralized ABM technique on an autonomous microgrid that is represented through cellular automata (CA). The proposed model was applied to high-density crowd events, such as emergency evacuations, massive gatherings, and traffic congestion events, e.g., car accidents or lane closures, and its effectiveness was analyzed. The experimental results confirm the efficiency of the proposed model in not only accurately simulating the drivers/pedestrian behaviors and improving flows of crowd and vehicular traffic during congestion but also by suggesting changes to crowd/traffic dynamics during the simulations, such as avoiding obstacles and high-density areas and then selecting the best alternative routes. The simulation results validate the ability of the proposed model and the included decision-making sub-models to both predict and improve the behaviors and intended actions of the agents.

Record Information

Source Institution:
University of Colorado Denver
Holding Location:
Auraria Library
Rights Management:
Copyright Raghda Alqurashi. Permission granted to University of Colorado Denver to digitize and display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.

Downloads

This item has the following downloads:


Full Text
HYBRID MULTI-LEVEL AGENT-BASED DECISION SUPPORT SYSTEM FOR
MODELING AND SIMULATION OF CROWD AND TRAFFIC DYNAMICS
by
RAGHDA ALQURASHI B.S., Umm Al-qura University, 2006 M.S., University of Colorado Denver, 2013
A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy
Computer Science and Information Systems Program
2019


This thesis for the Doctor of Philosophy degree by Raghda Alqurashi has been approved for the
Computer Science and Information Systems Program
by
Gita Alaghband, Chair Tom Altman, Advisor Michael Mannino Ashis Kumer Biswas Liang He
Date: November 14, 2019


Ill
Alqurashi, Raghda (Ph.D., Computer Science and Information Systems)
Hybrid Multi-Level Agent-Based Decision Support System for Modeling and Simulation of
Crowd and Traffic Dynamics
Thesis directed by Professor Tom Altman
ABSTRACT
Agent-based model (ABM) simulation is a bottom-up approach that can describe the phenomena generated from actions and interactions within a multiagent system. An ABM is an improvement over model simulations which only describe the global behavior of a system. Therefore, it is an appropriate technology to analyze emergent phenomena in social sciences and complex adaptive systems such as pedestrian crowds and vehicular traffic. In this dissertation, a hybrid agent-based modeling framework designed to automate decision-making processes of evacuation during an emergency and during traffic congestion is proposed. The model provides system individuals with real-time alternative routes, computed via a decentralized multi-agent model, that tries to achieve a system-optimal distribution within an entire system, thus reducing the total travel time of all the individuals to reach their goals. The presented work explores a decentralized ABM technique on an autonomous microgrid that is represented through cellular automata (CA). The proposed model was applied to high-density crowd events, such as emergency evacuations, massive gatherings, and traffic congestion events, e.g., car accidents or lane closures, and its effectiveness was analyzed. The experimental results confirm the efficiency of the proposed model in not only accurately simulating the drivers/pedestrian behaviors and improving flows of crowd and vehicular traffic during congestion but also by suggesting changes to crowd/traffic dynamics during the simulations, such as avoiding obstacles and high-density areas and then selecting the best alternative routes. The simulation results validate the ability of


the proposed model and the included decision-making sub-models to both predict and improve the behaviors and intended actions of the agents.
The form and content of this abstract are approved. I recommend its publication.
Approved: Tom Altman


V
DEDICATION
This work is dedicated to my life’s partner, Dr. Mohammed Alqurashi, without whom my achievements would be limited, my horizons bounded, my vision vague, and the dissertation that follows would not be possible.


VI
ACKNOWLEDGEMENTS
First and foremost, all my sincere gratitude to my god (Allah), the most gracious and most merciful for enabling and helping me to successfully complete my doctorate.
This doctorate has been a really long journey which made me grow up as a person and as a researcher. At the end of my journey, I would like to express my sincere thanks to those who helped me to achieve my dream.
I would like to express my gratitude to my thesis advisor, Dr. Tom Altman, who has encouraged me through my research. He has been such a helpful advisor, and this thesis has benefited from his guidance and support throughout my graduate studies. I would also like to thank Dr. Altman for giving me great patience and support to explore many different ideas and research topics. His constructive criticism has greatly improved my skills as a researcher and technical writer.
I would also like to thank the other members of my committee, Dr. Gita Alaghband, Dr. Ashis Kumer Biswas, Dr. Liang He, and Dr. Michael Mannino for their valuable feedback and expertise. Especially, I am grateful to Dr. Alaghband for her encouraging words throughout my Ph.D. study. I will not forget how she always pushed me during the tough times of my journey, and I will always remember when she once told me, “Don’t give up!”.
I am eternally grateful and indebted to my Mother, Naimah, and my Father, Mutair, for raising me in an intellectually stimulating environment, for always encouraging me to pursue my passion, for their endless love and encouragement, and for their patience while I was pursuing my studies far away from them. I have never felt the need to ask for their help because they have always been there before I even had to ask. The successful completion of my dissertation would


vii
probably not have been possible without their support. There are no proper words to convey my gratefulness for their prayers for me. My deepest appreciation and sincere gratitude go to them.
I would like to express my sincerest gratitude to my dear brothers, and my darling sister, Hanadi, for their unwavering and unconditional support throughout my academic career. They have been always supportive especially during the tough days of this journey. Special thanks to my little brother, Habeeb, for teaching me designing on AutoCAD.
I am thankful to my precious sons, Ahmed and Albara, for their love that is the most selfless shelter to me and is also the resource where the sense of responsibility and motivation come from. Special thanks to them for their patience, time, and help through all the phases of my graduate study. Also, I am grateful to my parents-in-law for their encouragement, support, and prayers.
I must also acknowledge my honest friends, who were with me in moments of joy and in moments of sadness, with whom I shared my journey in graduate school, and who have helped me over these years to recognize the beauty of life.
I would like to thank my government, and Umm Al-Quraa University for giving me the opportunity to receive a scholarship and complete my Ph.D. study.
Finally, I would like to express my deepest gratitude to my loving husband, Dr. Mohammed Alqurashi, for his constant generous and unconditional support and encouragement during the years, and for him believing that I could reach this point. He brought me through the inevitable periods of frustration and doubt that accompany my doctoral journey. He always stands behind me and his words always brighten my path. There are no proper words to convey my heartfelt appreciation and gratefulness for him. This dissertation is as much his achievement
as it is mine.


Vlll
TABLE OF CONTENTS
CHAPTER
I. INTRODUCTION........................................................... 1
Motivation...............................................................6
Research Contributions...................................................7
Structure of the Dissertation...........................................10
II. BACKGROUND AM) RELATED WORK........................................... 11
Modeling of Complex Systems............................................ 11
Agent-based Modeling and Simulation Approach............................12
Agent-based model development........................................18
Applications of agent-based modeling.................................19
Cellular Automata.......................................................21
Crowd Modeling..........................................................24
Scales of Crowd Modeling.........................................26
Levels of Crowd Modeling.........................................27
Traffic Modeling........................................................27
III. MODEL DESCRIPTION.....................................................3 I
Environment Configuration in the Model..................................33
Agent Configuration in the Model........................................35
Target-Driven Decision-Making Model.....................................39
Transition Decision-Making Model........................................40
Agent Status Upgrading Model............................................43
Evaluation of Trustworthiness Model
47


IX
Model Validation............................................................51
Implementation Set-up...................................................52
The ODD Protocol........................................................53
IV. DECISION SUPPORT SYSTEM FOR SIMULATING AND MODELING OF CROWD
DYNAMICS AND EVACUATION.....................................................54
Introduction................................................................54
Model Description...........................................................57
Environment Configuration in the Model..................................58
Experimentation and Analysis................................................58
Results and Discussion......................................................63
Application of MLMS-ABM Model in last Floor of Al- Haram Al-Sharif in Makkah .. 76 Results and Discussion......................................................77
V. DECISION SUPPORT SYSTEM FOR SIMULATING AND MODELING OF
TRAFFIC DYNAMICS............................................................81
Introduction................................................................81
Intelligent Transportation Systems...................................83
Decentralized Techniques.............................................84
The Decentralized Architectures and Multi-Agent Systems..............85
Centralized / Decentralized Techniques...............................87
Related Work................................................................87
Model Description...........................................................89
Agent Configuration in the Model........................................90
Environment Configuration in the Model......................................91


X
Agent Status Upgrading Model.........................................92
Experimentation and Analysis............................................95
Results and Discussion..................................................99
VI. CONCLUSION AM) FUTURE WORK......................................... 112
REFERENCES............................................................... 121
APPENDIX
A. Simulating and Modeling of Crowd Dynamics Python Code................. 136
B. Simulating and Modeling of Traffic Dynamics Python Code............... 152


XI
LIST OF TABLES
TABLE
1. Agents movement speed..............................................................38
2. Total reroute time vs. method with different arterial load for the hypothetical road
network..............................................................................102
3. Total reroute time vs. method with different arterial load for the real-world road
network..............................................................................107
4. Comparing the total travel time for the hypothetical road network and the 1-25 road
network..............................................................................110
5. Comparing flow rates for the hypothetical road network and the 1-25 road network. Ill
6. Comparing the vehicles’ average speed for the hypothetical road network and the 1-25 road
network..............................................................................Ill


xii
LIST OF FIGURES
FIGURE
1. Multi-level multi-stage agent-based model (MLMS-ABM) system overview.............32
2. The two layers of MLMS-ABM model.................................................33
3. A finite state machine (FSM) representation corresponding to state transition of the agent’s
behavior........................................................................37
4. Decision tree with n neighbor agents.............................................48
5. The overall modeling framework...................................................50
6. The next time-stamp target cells.................................................58
7. Configured simulation environments...............................................60
8. Screenshot of the simulation environment.........................................60
9. Scenarios targets’ floor field (TFF).............................................62
10. Total travel time to evacuate...................................................65
11. Total travel time to evacuate the same agent during the three cases.............67
12. Cumulative flow of agents.......................................................69
13. Agents’ average speed...........................................................70
14. Changes in population size overtime in different evacuation scenarios...........72
15. Testing dynamics of upgrading model through evacuation total time...............73
16. Testing dynamics of upgrading model through pedestrian’ average speed...........74
17. Comparing evacuation total time when the environment is dynamic vs. static......75
18. Comparing system throughput when the environment is dynamic vs. static..........75
19. The variation of density to each exit’s target floor field (TFF)................77
20. Cumulative flow of agents to evacuate...........................................78
21. Average speed of agents.........................................................79


Xlll
22. Total travel time to evacuate...........................................................80
23. The next time-stamp target cells for a vehicle..........................................92
24. Traffic dynamic modeling layers.........................................................94
25. Basic hypothetical road network.........................................................97
26. The segment of the real road network in Denver County...................................98
27. Screenshot of the simulation environment of the hypothetical road network..............100
28. Total travel time for rerouting around accident with different arterial loads..........101
29. Total travel time to reroute around accident for the same vehicle during variety of arterial loads
(hypothetical road network).............................................................102
30. Traffic flow during simulation time (hypothetical network).............................103
31. Total travel time for rerouting around accident during different traffic volumes with different
arterial loads..........................................................................104
32. Traffic throughput during simulation with different arterial loads.....................105
33. Average vehicle speeds with different arterial loads (hypothetical road network).......106
34. Total travel time through the 1-25 freeway in different methods with different traffic
loads...................................................................................107
35. Total travel time to reroute around incident for the same vehicle during variety of arterial loads
(real-world network)....................................................................108
36. Traffic flow during simulation time (real-world network)...............................109
37. Vehicle’s average speed with different arterial loads (real-world network).............110


XIV
LIST OF PUBLICATIONS
• R. Alqurashi, and T. Altman, “Hierarchical Agent-Based Modeling for Improved Traffic Routing,” Applied Sciences, vol. 9, (20):4376, 2019.
• R. Alqurashi, and T. Altman, “Multi-Level Multi-Stage Agent-Based Simulation Model of Crowd Dynamics in Upper Floor of Al- Haram Al-Sharif,” in Proceedings of the 19th Scientific Forum for Hajj, Umrah and Madinah Visit Research, pp. 159-167, 2019.
• R. Alqurashi, and T. Altman, “Multi-level multi-stage agent-based decision support system for simulation of crowd dynamics,” in Proceedings of the 23rd International Conference on Engineering of Complex Computer Systems (ICECCS 2018), pp. 82-92, 2018.
• R. Alqurashi, and T. Altman, “Multi-class agent-based model of crowd dynamics,” in Proceedings of the 2017 International Conference on Computational Science and Computational Intelligence, pp. 1801-1802, 2017.
• H. Alsultaan, R. Alqurashi, M. Greene, and T. Altman, “Agent-based models predicting collective behaviors,” in Proceedings of the 2017 International Conference on Computational Science and Computational Intelligence, pp. 297-302, 2017.


1
CHAPTER I INTRODUCTION
Modeling and simulation are means for developing a deep understanding of both complex systems and complex adaptive systems behaviors. Computational simulations have long been accurate predictors of complex social systems. They are now seen as powerful tools in studies of those systems’ dynamics [1, 2], One particularly effective computational simulation method is agent-based modeling (ABM) [3-6], ABM considers the complex system as a decentralized, multi-agent system (MAS) [3-11], where each agent can communicate only with its immediate neighboring agents. The ABM approach is a form of optimization of individual solutions, and it applies to systems of interacting, autonomous, and individual agents. The ABM is used to model and simulate complex systems ranging across various contexts, including biological and social systems [7], Because of the emergent phenomena of complex systems, the ABM is an effective approach to address the question of how a system’s behavior connects to the behaviors and characteristics of its individual components. The agents in the decentralized system have no direct information about their global position. However, they have information about their nearby neighbors and their environment locally [9, 11], They can use this local knowledge to collectively construct a coordinate system. In ABM, the agents are described as unique and autonomous entities that embody the origin of the coordinate system [12], Instead of describing the state of whole systems, the ABM represents the systems’ individual components and their behaviors. Also, their generalized nature is able to capture complex dynamics and structures [10], It can be observed in the literature that both ABM and complex networks are based on the complexity theory. The ABM approach has been successfully applied to a wide range of scenarios including military training, building evacuation and analysis of digital games [13, 14],


2
The implementation of agent-based frameworks for the analysis of other complex social systems, including crowd dynamics, has now become more common [8], Spatial-temporal processes, such as crowd dynamics and traffic congestion, typically require complex models. Two technologies used to construct these models are ABM and cellular automata (CA) [15-20], Each has the ability to explain the status changes that take place within the spatial cells step-by-step. These methods are capable of reflecting the emergent and complex characteristics associated with the complex phenomenon [20],
This dissertation presents a novel multi-component, agent-based modeling framework that simulates the components, behaviors, and phenomena of complex systems. A decentralized multi-agent control strategy is proposed and investigated on an autonomous microgrid. Communication restrictions allow each agent to communicate only with its neighboring agents. The modeling framework is used to develop a decision support system which aids in the understanding of crowd and traffic dynamics under panic and risk conditions. The proposed modeling system employs a hybrid, decentralized approach to assist the individual agents with their decision-making. Hence, the system will be more robust. In a multi-agent complex system, agents adjust their behavior according to their current states, to other agents’ states, and to their environment. Agent-based model simulation is a bottom-up approach describing only the phenomenon that is generated from the actions and interactions of the multiagent system.
Because it does not describe the global phenomenon of the system, ABM is an appropriate technology to analyze emergent phenomena in social sciences and complex adaptive systems such as traffic, crowds, and transportation hubs. The proposed model is a computational discretetime simulation scheme. The support system is outlined with finite-state machines and uses a


3
genetic algorithm to optimize the selections and decisions taken by individuals. The model was built to explain and predict observed interactions among real agents.
This dissertation represents an egress model through the application of agent-based model and Cellular Automata. The predictive model results will enable us to test and evaluate the conditions that might occur within the network and improve our understanding of which assumptions and future developments could have the most impact on managing the system flow.
This work represents a strongly predictive simulation model for dynamic decisionmaking in a multi-agent system. The model permits direct insight into observed dynamic processes in complex systems. The proposed framework can help predict system behaviors when given behavior information of agents in the network. The simulation model mimics the movement behavior of multi-agent systems, ranging in size from hundreds to thousands of agents, in an environment undergoing dynamic changes. The presented model can be used to predict individual behavior in highly congested areas, thereby anticipating and preventing events such as panic stampedes in crowds and traffic accidents in traffic jams. The methodology presented here will support a wide range of crowd and traffic simulation research studies. Also, the model’s ability to derive the underlying decision models for multi-agent systems is demonstrated.
The developed versatile agent-based framework encompasses fundamental principles of modeling as they are commonly applied to multi-agent systems dynamics. To this agent-based framework, an adjustable approach was introduced for simulating human perception and decision-making in dangerous scenarios. The framework focuses on two social science scenarios: evacuation scenarios [21, 22] and traffic simulation scenarios [23], The goal of this work is to create a model to simulate varying individual behaviors within these two scenarios in which


4
agents interact with an unfamiliar, dynamic, and stochastic environment with the goal of optimizing their long-term performance. The dynamic decision-making modeling is organized into three levels: (1) strategic, (2) tactical and (3) operational [24-28], The formulation of a plan and its final objective is drawn at the strategic level. At this level, no information is provided about the real circumstances [25], At the tactical level, all activities are computed and performed to facilitate the formulated plan [27] and address short-term decisions like avoiding obstacles or changing plans based on new information. Additional information about the multi-agent system such as the flow of agents is available at this level [26], The operational level addresses the physical actions and activities developed at the tactical level [28], The operational level represents the agents’ movement that includes the connection between agents. The goal is to be able to mimic intelligent, self-organizational behaviors and gain reliable results. The two main model components are the environment, where the simulation takes place, and the agents, whose autonomous behavior will impact the entire system.
The simulation model consists of multiple sub-models, as shown by the system overview in Chapter III, Figure 1. It begins by modeling how the agent selects its goals. The act of avoiding obstacles and collisions with nearby agents are then modeled. The hybrid version of the agent-based model includes simulating the leading and following behaviors of agents after dynamically upgrading certain agents to the “intelligent” level and enabling them to perform some sort of guidance behavior, as detailed in Chapter III. Besides avoiding collisions with neighboring agents, the framework includes a model of avoiding high density areas in order to reduce the overall travel time.
Complex and dynamic multi-agent system was modeled and simulated at both microscopic and macroscopic levels, as shown in Chapter III, Figure 2. The highest layer


5
represents the macroscopic phenomena of the multi-agent systems that would be difficult to model in CA frames. This layer detects the collective behavior of the agents, which involves some form of guidance, e.g., intelligent agents to enhance the decisions for the whole system as described in Chapter III. The base layer representing the microscopic phenomena utilized a CA model. It incorporates system motion features and interconnections between individuals, and it provides fine details of the simulation and insight regarding the network flow.
This research is driven by the application of a novel, self-adaptive model, designed and developed with an agent-based computing approach for optimizing the flow of agents. The purpose is to provide evidence for overall system behavior changes within dynamically changing environments/networks. These networks involve topology changes and other external stimuli such as fires, stampedes resulting from panic, or congestion (i.e., the state of being overcrowded, especially with traffic or people). The proposed model has the ability to predict the change of agents’ behaviors when the structure of the complex system changes. Therefore, it answers questions about communication between an agent and its immediate neighboring agents and the global system information exchange between decentralized agents.
The proposed hybrid, multi-scaled, agent-based framework demonstrates how decisionmaking processes occur during crowd events, such as natural disaster evacuations, rush-hour traffic, and organizing large gatherings. The simulation model provides a tangible example of one way to construct a decision-making system for supporting massive crowd and traffic management. The scalability of the proposed approach is demonstrated on large-scale scenarios, as illustrated in Chapter IV and V.
The simulation was ran in more complex environments to examine the model and to increase its robustness. The experiments include more complex evacuation processes, such as


6
more complex settings of building interiors, additional environmental obstacles, and fewer numbers of targets. These settings will help validate the proposed model and test its ability to address complex evacuation cases. In order to show the potential of the proposed model, the evacuation in a hypothetical scenario will be simulated with incoming flow of people. An important feature of the scenario will be the asymmetrical configuration of the environment. In addition to simulating crowd dynamics, the environment’s external settings include controlling traffic during congestions. The proposed model will address collision detection and avoidance in vehicular traffic networks.
Different hypothetical scenarios were designed with varying complexity and features for each of the considered real-world scenarios. In order to show the potential of the proposed model, particular emergent actions, such as evacuation and car accidents, were simulated with incoming flow of people in each of the hypothetical scenarios. The model was experimented in each scenario to show its efficiency in the simulated situations while conserving reasonable dynamics and flow of the crowd/traffic that includes congestion avoidance and overall shorter travel times. To perform the analysis, a representative environment for each scenario was constructed. For example, a representative road network will be created to analyze the traffic control model.
Motivation
In general, crowd and traffic dynamics simulation is relatively difficult to carry out because of the behavior-influencing factors that come from internal as well as external forces exerted on the system [29], Such systems are typically challenging to accurately model since doing so requires considering the interdependence of each component [30], Additionally, it is


7
practically impossible to implement and test all scenarios for large-scale and complex networks
[31]-
The aim was to accurately simulate the agent behaviors and phenomena in multi-agent systems, thereby improving decisions. The effectiveness and robustness of the proposed model in supporting crowd and traffic management decisions have been ensured through a novel, multi-component, agent-based modeling framework designed to support the management decisions by elaborating on “what-if ’ scenarios. Also, the proposed model aims to support event planners’ and building designers’ decisions.
The importance of this research in providing promising solutions for facilitating crowd management involving large numbers of individuals will be furthered to include improvements in its practical applicability in more complex scenarios, modeling additional phenomena and practical environmental infrastructures. Specifically, the framework was applied to different crowd and traffic dynamics in different real-world scenarios and analyze its effectiveness in the case of a high-density multi-agent systems. This research hypothesizes that the agent-based simulation model is more suitable than previous methods that are restricted to controlled and predefined goals, paths, and rules among agents. Furthermore, the methods described here are scalable enough to support everyday activities of decision-makers in various domains, such as designers, crowd managers and organizers of events in large constrained areas.
Research Contributions
This dissertation provides a novel framework for modeling crowd and traffic management decision support systems in a collective environment. The key contribution is using multi-level, multi-stage, agent-based computing technology to model complex systems to ensure capturing all factors that impact the complex dynamics and structures of a system. In that way,


8
the proposed hybrid agent-based framework is able to model complex autonomous systems. Compared to the proposed model, previous works used conventional ABM to model individual agents’ behaviors. They have not modeled an entire complex system using multiple layers of modeling while simultaneously incorporating multiple levels containing multiple stages and using agent-based and cellular automata computing approaches, as was done here. By reconceptualizing an existing agent-based modeling approach, the crowd/traffic modeling levels and layers (scales) were integrated to ensure the ability and robustness of the proposed model to capture all crowd/traffic phenomenon during risk and panic situations.
Employing the adjustable ABM approach helps to simulate human perception and decision-making in complex scenarios. Therefore, the proposed agent-based model is able to accurately simulate the agents’ behaviors and phenomena, allowing for improved decisions taken to enhance the whole complex systems. In addition, the presented model is distinct from all previous works in its novelty and effectiveness in simulating large-size heterogeneous complex traffic networks based on both CA and hybrid, multicomponent ABM techniques.
One specific contribution is combining the dynamic agents’ status updating, by relying on behavioral factors, with the complex system modeling. This approach offers a significant improvement over the existing surveyed works. Previous works specify the agents’ roles prior to the simulation beginning without considering the dynamic environmental events that could occur after the simulation begins, in contrast, the proposed model updates and expands the agent’s status dynamically, making it more specific to the agents’ surrounding environmental situations. The significance of the agent status being continuously and dynamically updated throughout the entire simulation is that the model is generalized. Also, as various levels of intelligence are possible for the agents. Other levels of the proposed multi-level, multi-stage, agent-based


decision support system were modified according to the improvement in the agents’ status upgrading model.
9
The presented work offers another contribution to the discourse in that the first level of modeling of the system dynamics, the target-driven decision-making model, investigates gene expression programming and automatically integrates decision rules extraction into the model. This re-contextualization allows us to extract the rules for determining/selecting the goal, which is the first level of dynamical modeling. A thorough search of the relevant literature did not uncover crowd and traffic research that involves an automatic decision rules extraction model for specifying the goal (decision) into this modeling technology.
In contrast to existing models, the proposed transition decision-making model takes into account all factors that impact the transition of agents through the environment. These include distance to the goal, need to avoid collisions, density, and obstacle avoidance, just to mention a few. Implementing these uses an algorithm for finding the best path to the goal that considers not only shortness of distance, but also the obstacle-repulsion natural behavior of the agents. By applying the A * algorithm to find the distance to the goal, rather than the common methods used by other researches, this model is applicable to the shortest path with the presence of arbitrary obstacles. The transition decision-making model, in which two types of floor field approaches were investigated (static and dynamic) ensures capturing all factors that impact the agent’s transition through the environment. The dynamic floor field is modified according to its diffusion and decay rules previously investigated in [65, 72],
Moreover, in contrast to the conventional ABM, the presented model provides a new solution to the problem of trustworthiness by incorporating a trustworthiness evaluation tool in modeling the communication and information exchange between agents. One of the


10
shortcomings of the previous complex network approaches was that they did not include a communication model based on trustworthiness between agents. Such an assessment improves the accuracy of agents’ decisions in the complex system, thereby improving the overall system’s performance. The need to perform a trustworthiness evaluation between an agent and its neighbors is critical, since it allows the agents to adjust their behaviors or their social links, which induces changes in the social network where they are embedded.
Structure of the Dissertation
Following this introduction, related works and introduction to agent-based modeling and simulation (ABMS) are described in Chapter II. Also, Chapter II presents the concepts of complex systems and Cellular Automata. Furthermore, this chapter describes the literature review about crowd dynamics including evacuation simulations. Chapter III describes the hierarchy of the multi-stage, multi-level, agent-based framework and presents how the simulation and analysis were done. In order to illustrate the benefits of using ABMS, this dissertation focused on several aspects of a well-known area related to simulation of complex systems, namely crowd and traffic. In Chapter IV, the first implementation of a simulated evacuation model is presented. In Chapter V, the implementation of the proposed model of the traffic network is discussed. Chapter VI, the discussion and conclusion, contains the investigated problems and approaches used. At the end, a brief look into future study and research is provided.


11
CHAPTER II
BACKGROUND AND RELATED WORK
Modeling of Complex Systems
A model is a purposeful illustration of a real system made to either answer questions about a specific system or simply to solve problems [29], To create a model means to design its algorithms and concepts using computational methods. This approach offers advantages over others that are either too complex to build, too expensive to construct, or would take too long in the experiment phase [30], For instance, it would be challenging and time-consuming to comprehend how cities and land formations undergo change just by relying on experiments. In an attempt to get a better understanding of something large or complex, we created a simple version of the system with the aid of computer programs and mathematical equations that we can edit and experiment on in silico [31],
Modeling and simulation are integral tools in modern science. They enable explanation and prediction of specific conditions that may not have been otherwise possible. The process by which a model is executed and experimented on is known as simulation [29, 31], This process takes the model through continuous or discrete changes of state over time [30], Usually, for difficult problems where time and cost are crucial variables, a simulation offers a high return of information while also enhancing the quality of the product along the development stage.
To carry out the simulation of a complex process, various data about the element(s) to be analyzed need to be gathered or inferred. Parameters such as the characteristics of the element(s) need to be arranged in a uniform manner and with a schematic representation, e.g., geometry computer-aided design (CAD) data. Also, to simulate a complex process, boundary conditions of


12
the element under consideration is needed for data describing the behavior of subsystems adjacent to the subsystem studied, and inferring how those systems interact and influence each other [32],
Many challenges arise during the development of simulation models for the design of complex systems. Those challenges include incorporating multiple perspectives that occur within the system, such as the overall system and the individual basic parts. An additional challenge is in determining the amount and complexity of detail and information that should be included in the model. One approach to a complex model is to distill the complex system into subsystems. Each have specific roles and are subsequently utilized as building blocks that possess their own characteristics [32],
Modularization is a method that considers the complex system as a part of other subsystems having specific roles that contribute to the design information in behavior and function. Modularization is vital for managing complexity, and it has been adopted in various methods that rely on model-based systems engineering (MBSE). The MBSE is a distinct approach to system modeling methods and frameworks that supports complex system designs. It is a vast methodology that oversees other aspects of engineering designs, such as the functions, behaviors, requirements and structures of the product using the models [33],
Agent-based Modeling and Simulation Approach
A considerable percentage of data available for consumption is generated by interactive systems that do not involve humans. In order to ensure a solid mechanism, it is essential to determine the possible agent behaviors beforehand. When there is a possibility to predict agent behaviors effectively, the platform will be able to optimize the performance [34], With the help of machine learning, it is possible to predict the behavior of dynamic systems that exist in the


13
real world [35], For example, how people will work in a crowdsourced project or how a marketing campaign might deliver positive results can easily be determined with the assistance of machine learning [36],
The initial data required to build a model of these systems are obtained by observations of live agents and their behavior [37-40], These systems can be optimized through the continual input of additional data sets. As a result, the model will improve with time. In the meantime, agents will be observing all changes that take place within the system and will respond to the specific changes through their behaviors. This is how behavioral data evolves over time; they are not independently and identically distributed [39, 40], The theories behind machine learning have come across some significant theoretical challenges [35, 37] that can be mitigated with the assistance of Markov Chain in random environments (MCRE) which can determine behavioral data. MCRE functions by conducting generalization analysis of the algorithms used in machine learning. MCRE is associated with a one-step transition; thus, the outcome is dependent on the random environment as well as the previous state, explaining why traditional techniques cannot be applied in this situation. In order to address this issue, MCRE should be transformed into a time homogeneous Markov chain, which is located in a higher dimension. Even though it utilizes a higher number of variables, the platform will be regular and the result more interpretable.
When the time is set to infinity, the Markov chain will converge. This can be used to prove generalization with machine learning algorithms when they are used along with data generated via a Markov chain. Hence, it is the most effective generalization analysis method, one which can be used to model dynamic systems in the real world [41],
Several theories are used when modeling the spatio-temporal processes. Among those theories, agent-based models (ABM) [5, 7-11, 13, 24-28, 42-54] and cellular automata (CA) [15-


14
20, 55-57], They are the most prominent and are capable of reflecting the emergent and complex characteristics associated with complex phenomenon. Both ABM and CA are considered bottom-up approaches [3, 54], This is due to their ability to explain the status changes that take place within the spatial cells step-by-step [37, 55],
Prior to execution of a model, it is critical to understand the details of the agents, their behaviors and their attributes in addition to the relationships of agents, along with their interaction methods, to be able to predict how the model will perform and behave [39, 42], Understanding the environment with which the agents reside and interact is also critical to successfully simulate an agent-based model, as it is important to critically evaluate the parameters controlling the interactions and behaviors of the agents [9-11, 42-44],
Agent-based modeling and simulation (ABMS) can effectively be used to model systems that are made out of interacting, autonomous and individual agents [9, 10], ABMS is considered the computational framework used to simulate diverse processes involving autonomous agents [3, 11], In this scenario, each agent will have its own behaviors and characteristics. Agents will also have their own inherent attributes and properties; for example, an agent can be self-directed and autonomous [39, 49], It is possible for an agent to function independently within the environment, and the interactions (often nonlinear) with other agents can also be done in an independent manner [43], The behavior of an agent is related to the information that an agent would sense from the environment in which it is living; these pieces of information will trigger actions as well as decisions [44],
Agent-based modeling represents the individual components of a system. In addition, behaviors of the system are also determined and represented. Hence, the system will not be described through the use of variables. Instead, individual agents will be used in order to model


15
the entire system [3, 11, 42, 44], For this reason, it is possible to come to a conclusion that agents represent the individual components of a system. Agents are individual and unique components [49] in terms of their location, size, history and resource reserves and will not interact with all other agents in the system; instead, they will limit the interactions to the agents in the neighborhood [58],
Due to the above-mentioned reasons, agents exhibit adaptive behavior which is applied to both their current state and the overall environment [29, 59-63], Through agent-based modeling, it is possible to solve some of the common issues associated with emergence, which include system dynamics and the way each agent responds to the environment [59, 61, 63],
Because of the versatility of ABM in modeling and simulating complex systems which span across various contexts [59-87], it has been identified as the most suitable approach available when studying a system that requires adaptive behavior, such as in social systems [77], When cognitive ABM is used to represent cognition ability in humans, it models the organizational behavior, social behavior and decision-making of individuals [6, 7, 88-90], Cognitive ABM is applied to construct complex and dynamic models of human decision-making in simulations of crowd and evacuation dynamics [14, 85, 86, 89, 90, 57], Previous studies have shown that the behavior of each individual tends to be independent from other individuals in a connected environment [10, 37], In contrast, in social environments, the choices often reflect a group-based decision, such as swarm systems, based on behavior trends [64-71], In order to predict agent behaviors in an effective manner, it is important to use a dynamic simulation method on a social structure [35], Social structure and group decision-making schemes are highly influential factors during human behavior. Thus, they are critical variables to include during the construction of simulations of behavior such as crowd evacuation [89, 90], The main


16
objective of agent-based simulation is to determine how the agents behave in environments that include other agents, recognizing that agents make decisions in a unique manner. When analyzing the way agents make decisions, a possibility presents itself as a way to figure out two dimensions that define agent architectures: the social and the cognitive levels [54], The social level of the agents is determined by their ability to distinguish social network relations. In addition, the level of communication that the agents are capable of is also determined. Some agents are capable of managing complex social projects. The cognitive level of the agents determines whether or not they are entirely reactive [6, 45], However, the simple cognitive components and forms of deliberation of the agents are also determined through this approach
[7].
When looking at the collective behavior of agents that exist within a social network environment, it is possible to see that consequences are based upon the aggregation of individual behaviors [9,11, 54], However, within a connected environment, the behaviors of individual agents tend to be independent. In other words, the agents are capable of moving forward with their work without any dependencies on each other, although they are influenced by the behavioral trends.
The behaviors of individual agents are then determined independently of other agents, all of which have their own inherent attributes and properties [3-13], For example, an agent can be self-directed and autonomous. The behavior of an agent is also related to the information they would sense from the surrounding environment. These pieces of information will influence actions as well as decisions [35], Modularity can be considered as another prominent attribute among agents [32], As a result, there is a possibility to identify an agent, uniquely and discretely, with a set of characteristics, decision-making capabilities, behaviors, and attributes [34, 36],


17
Sociality [3] is identified as an attribute of the agents as they are being socialized along with other agents and will exchange information with each other through specific communication methods that uniquely identify the other agents and send them appropriate messages. Agent-to-agent interactions are determined by common topologies [3], as follows:
• Soup - Anon-spatial model, which determines the agents that do not have locational attributes.
• Grid - The interactional patterns of agents.
• Euclidean space - The ability to roam around in two-dimensional and three-dimensional spaces; the overall space is called the Euclidean space.
• Geographical information system - Agents tend to move and interact with geo spatial landscapes.
• Networks - Networks can either be dynamic or static. The location of an agent is relative to the location node of the network.
Regardless of these common topologies, what is important is the ability of the agents to interact at any given time along with other agents in the population [72], This interaction can be done via the definition of a local neighborhood that will be stored within the same network.
The final attribute of agents is conditionality [3], All agents are equipped with a specific state that can vary along with time and contains a subset of behaviors and attributes of an agent. The state of the environment is created from all the states of agents. The process of learning will describe the ultimate behavior of agents.
Agent-based modeling can be done in two steps [3], The first step is to determine the classes or types of agents which should be done along with determining the attributes of the agents. The


18
second step is specifying agent’s behaviors [9, 13], The theory of agent’s behavior should be used as the basis for modeling agent behavior. It is also possible to start with a generic behavioral heuristic and a bounded rationality model [10], This will determine the way agents interact in their relationships with other agents.
While analyzing agent-based modeling, it is important to take cognitive agent-based computing into account, as the primary objective of cognitive agent-based computing is to identify complex systems in the real world and transform them into suitable models [6, 7, 60], During this process, appropriate modeling levels need to be selected. Along with the assistance of an appropriate ABM framework, there exists a possibility to validate a large-scale system, which is made out of multiple agents [71], This will not be possible without the use of cognitive agent-based computing.
Another prominent benefit that can be experienced through ABM is that it has the ability to contribute to the buildup of models [3, 13, 59, 46], In fact, models can be developed without any understanding of the global inter-dependencies, and there is no need to know about how things will create an impact on each other while developing an agent-based model. Nor is it important to have an understanding of the sequence of operation [35, 49], A basic understanding of the individual participants and how the overall process would behave is critical to develop the local behavior, which ultimately contributes to global behavior [42],
Agent-based model development
Agent-based systems are used in a large number of applications in global systems [58-75], In order to manage this kind of system effectively, the individual components and the way they interact with each other must be determined. These interactions have their own parameters and rules; thus, when modeling a system using agent-based models, it is important to specify the


19
exact relationships that exist between individual agents [3, 5, 11, 37, 54], The interaction between agents should be located within the environment; otherwise, there is no possibility to establish the relationships between them. A variety of methods are available to establish relationships [45, 83], such as goal-directed relationships and simple reactive relationships. In addition, the specific environment that can facilitate the interactions that take place within the system should be determined. While the interactions are simulated within an environment, there is a possibility to represent them within a continuous or discrete field [43, 59],
In order to predict agent behavior, specifically human behavior, in an effective manner, a dynamic simulation method on a social structure is needed [24, 28, 42], Agent-based models can be built using two approaches: discrete event modeling or existing system dynamics [3, 37, 54], The discrete agent-based model can be enhanced with the objective of capturing dependencies and more complex behavior.
Micro simulation, which is another important aspect of the agent-based model, becomes critically important when agent-based modeling is applied to practical scenarios [46], The modeler who defines the agent-based model should be in a position to identify all variables, including agents, active entities, cities, vehicles, assets, projects and companies, in addition to defining agent behaviors [45, 47, 59], Once these components are placed within a specific environment, connections will be established. Individual behaviors of agents can contribute to the global behavior of the overall system. Hence, micro simulation can be considered as the building block of a system.
Applications of agent-based modeling
The applications of ABM span across a diverse range of domains [24-28, 33-37, 42-54, 59-90], from physical, cultural, behavioral, and social to biological systems and include


20
determining the success of promotional campaigns, identifying the chains within stock markets [36] and projecting the upcoming requirements of healthcare systems. One of the initial applications of agent-based modeling was used to predict the spread of AIDS [83], It has also been used successfully in applications including economics [36], public policy, management of ecosystems [37], insurgency, crime proliferation, tax evasion, technology adaptation, traffic patterns [84-86], and crowd dynamics [91-101], Applications of agent-based modeling have also been used to study human learning and cognition [60, 76, 78],
Recently, agent-based models have been used to model the demand for and availability of water [14] as part of risk management during a disaster. Using this model, it was possible to come up with effective flood management procedures [14] and, on a grander scale, Tsunami evacuations [134],
Agent-based modeling is regarded as the most suitable approach to study complex adaptive systems (CAS) [29, 59, 61, 63] because of its ability to accommodate complex dynamics and structures in an effective manner. Recently, multi-agent systems were used to manage the carbon footprint within a corporate environment. This was done with the participation of a heterogeneous system and cognitive agent-based computing [60, 71],
Multi-agent systems are reactive techniques that are typically used to study the behavior and the emergent patterns of swarm systems such as ant colonies and animal flocks. The complex behavior of flocking birds, for example, employ three simple reactive rules to create the overall flocking behavior: attraction, cohesion, and repulsion [64], A number of studies [64-71] utilize agent-based models to study the effects of animals’ environments on the swarm systems’ foraging strategies. The multiple aspects of animal behavior make it an ideal subject of study using ABM approaches. Whereas decentralized and self-organized natural systems are known for


21
their collective behaviors, which include collective decision-making, a group of animals can make optimal choices without perfect environment knowledge or leadership [64, 67], For instance, social insect colonies such as ants have an ability to choose the best among several routes of action; a choice which is based on the knowledge gained among all individuals [66-71], Each ant has limited local information and a set of rules to make decisions and uses individual memory and pheromone communication to achieve collective foraging behavior. Ant colonies operate without central control, ranging their behavior through local interactions with each other [69], The local information known by each ant is based on positive feedback, in the form of pheromones, which are deposited on its way back to the colony after it finds food [64, 66], This pattern of behavior is easily modeled using ABM and can ultimately lead to a prediction of the behavior of the ant colony. Previous research [64] has implemented ants’ foraging strategies as distributed search algorithms in robotic swarms. In our work [102], we presented a predictive interactive agent-based model to simulate the ant colony complex system and individual ant’s decision-making and foraging behaviors. The simulation model provides the ability to generate customized complex ant environments and to explore the interaction between the ants’ environment features and their behaviors.
The benefits of agent-based models are such that they are used in various applications. After the creation of an agent-based model, it is possible to explore new dimensions of prominent applications of ABMs in the future. It is also possible to combine agent-based models along with other similar models.
Cellular Automata
Numerous studies have been aimed at optimizing the use of cellular automata (CA) [15-20, 55, 104-122], CA has spatial structure as its first important principle and local interaction as


22
the second important principle [15, 19], Using an example of a checkerboard, every cell can be called an individual (the first principle), an individual checker, and we know that every cell will have neighbors, the other checkers on the board, with which it can interact (the second principle) [16, 104, 121], It is important to know that local interaction means that the interaction is limited to its nearby cells. This type of neighborhood can be considered if cell communication is limited to only four of its neighbors. But the type and range of the neighborhood can be changed, and it can be increased depending on different factors [115, 118, 122], These changes will bring changes to the results of the CA structure; hence, an even more result-oriented study can be carried out. One parameter that defines the working patterns of the cellular automata is the dynamic or static state of the cell [105, 119], Cells can change their states and/or location. If one of these things change, the structure of the spatial structure (the checkerboard) will change and the interaction will be affected [18, 20, 24], hence increasing the result-oriented nature of CA as a research tool in a number of scenarios involving heavily crowded locations, such as football matches and airports, or even traffic conditions that force drivers to change lanes [15-20, 55,
115, 123, 124],
The cellular automata models are widely used when analyzing complex systems [111, 124, 134, 135], If there is an application that reflects complex changes in the aspects, and if it needs to be simulated, cellular automata modeling is a preferred approach [15, 20], CA allows many mathematical and theoretical models to successfully elucidate information about a number of complex systems [104], ranging from the effects on the animal kingdom to the changes in the human body on a cellular level. Without the presence of CA, modeling of complex collective systems would be difficult [19, 24], A large number of studies have clearly indicated how the


23
paradigm can be applied to find answers to a large number of questions raised within complex collective systems.
Cellular automata have been applied to study forest fires [81, 94, 107, 111, 120], The findings explicating the increased frequency of drought and fires provides crucial information on predicting catastrophic wildfire events. In research conducted by Georgoudas et al. [120], the spread of wildfire was observed through parallel CA method. Cellular automata can also be used to explain the principles of cloud computing [15], When it comes to large-scale cloud computing platforms, the CA model is effective in achieving a perfect balance between computational nodes.
The floor field (FF) model, based on CA, is a highly effective method for simulation of agents’ dynamics [96, 109, 112, 116, 125-127], This method involves agents moving stochastically on latticed cells [112], One of the advantages of the FF model is simplicity, as its approach is based within the fundamentals of CA and is constructed in a discreet and microscopic form [125, 127], Implications of this format include the movement of a specific cell being directly proportional to the movement of the neighboring cells. At its core, a floor field is composed of a group of superimposed cells [96, 126], Quantification of the dynamics in this model are the spreads observed by each individual cell within the grid, referred to as path fields [112, 125], Overall observation of all path fields in the grid can be used to explain such phenomena as the navigation of pedestrians as the density fields highlight crowded areas in the environment. Two types of floor fields, dynamic and static, are commonly used [127], The static floor field does not change the status during the stimulation, whereas the dynamic floor field changes throughout the simulation process. The static fields describe the attractiveness: e.g., if the cell is closer to the exit point, it has a higher force of attraction. The dynamic floor fields


24
indicate the virtual trace that agents leave [122], The floor field values can be considered as the spread that can be found in the grid, and the gradient of this grid can be used to explain phenomena such as navigation of pedestrians [111]. With the path fields, the shortest available path to a given destination is obtained, and the density fields highlight crowded areas in the environment. The floor field based on CA is constructed in discrete and microscopic form [125], In a pedestrian simulation, individuals are provided with the ability to move and interact along with the neighboring cells. Every step of the cells is determined with the assistance of a given set of rules.
Crowd Modeling
Research on crowd dynamics has been extensively studied [86, 91-101, 104-106, 108, 115-120, 125, 128-135], Studying crowds has proven successful in avoiding some scenarios that could have been prevented had there been an earlier anticipation [91, 115], Crowds exhibit pronounced characteristics, including the tendency to move from instances of disorganized forms to being organized when a common purpose is being pursued [110], In such a case, crowds are observed to march towards exits in a sort of a herd. This behavior can be observed and modeled using the approaches described above.
Modeling crowd dynamics is complicated by the behavior of individuals while in a state of panic [129, 127, 134, 135], For example, individuals will move towards their own goal rather than the collective goal of the crowd. This is thought to occur because personal memory is mostly used to find the shortest escape routes in emergency situations [14, 24, 128-135], This demonstrates a scenario where the self and collective behaviors are both crucial for consideration
in simulation modeling for evacuations.


25
There are different forms of crowds that any model seeks to simulate, such as pedestrians, demonstrations and social gatherings [16, 19, 24, 86, 93, 98], In managing pedestrian behavior, various factors are involved, such as goal attraction, which constitutes what the pedestrian may want and possible alternate routes that they might entertain along the way [108, 115, 117], Considering all of these factors mark the beginning of a seemingly identifiable simulation to normal pedestrian movement and eventually predicts a crowd movement [17, 28], These crowd models are used as formal computational models to predict crowd dynamics. These dynamics can be tackled from a pedestrian point of view [92]:
1) Physical approach.
In the physical approach, a pedestrian is equated to particles that are subject to various forces that can either be attraction or repulsive [29], Whichever the force, the pedestrians get distracted, which is why it is important to include “distractions” in modeling solutions.
2) Cellular automata approach.
This is a biological analogy wherein an agent is equated to occupy the environment just as cells do in living organisms. The interactions that pedestrians engage in are classified according to a method referred to as floor field, which ensues instances of virtual traces that influence the transitional and movement dynamics of pedestrians. This model is limited, as it can only offer separate paths of the pedestrians. However, other important aspects, such as flows and densities, can be computed using this model and the behavior patterns which tend to be complex in socially-induced forces.
3) Agent-based approach.


26
Here, pedestrians are heterogeneous and autonomous entities that move as influenced by rules of behavior and the parameters applied to the system. As such, a utility-based agent would represent a simulation of pedestrians based on a computational-discrete model.
Agent-based simulations have gained prominence in recent years due to their autonomy aspect and the efficiency of their ability to mimic human behavior by using simple rules and heuristics [48], In ABM, there are rules that have to be utilized to allow for these models to be used in modeling crowd evacuations. Therefore, it is crucial to facilitate testing in appropriate environments. These rules are as follows:
i) The ABM must properly represent cognition ability in humans [6, 7],
ii) They must capture daily complex human movements and interactions in cities.
iii) They should be able to revert behaviors as human perception while providing warnings for potential risks and threats.
Applications of agent-based systems in testing evacuations of widespread disasters such as floods have been ubiquitously applied [14, 134], The results of these studies have proven feasible and hence, provide a powerful tool in planning for risk management [101], Specifically, these methods can help in determining evacuation patterns, identifying critical infrastructure and identifying need for improving current emergency resources. The potential of ABM is limitless, as different strategies of communication can be tested in the event of an anticipated disaster.
Scales of Crowd Modeling
1) Macroscopic scale - Successfully managing urban crowds in complicated disasters is challenging as processes usually occur at different temporal and spatial scales. The macroscopic model seeks to overcome these extensively spread-out risks by considering subjects from a perspective that includes all processes [92], The model of macroscopic scales is derived from a


27
macroscopic process which maps to the fact that models on this scale focus on accumulation of value rather than singular entities equivalent to a single pedestrian.
2) Microscopic scale - This scale is responsible for the definition of the intricate fine details of a pedestrian’s movements [93], These dynamics are based on cellular automata wherein a pedestrian is a single discrete object. The movements of pedestrians are simulated on a 2D cellular grid. Rules are defined to influence the movements of the discrete objects that form the crowd.
Levels of Crowd Modeling
1) Strategic level - The formulation of a plan and the final objectives are drawn in this level [25],
2) Tactical level - Here, activities which facilitate the plan are computed and scheduled [27],
3) Operational level - This level allows for physical execution of the activities laid out, such as the movement of a person from one point to another in a particular environment [26],
Traffic Modeling
Traffic flow creates a dynamically complex system since it involves a nonlinear interaction of many independent vehicles with largely autonomous behavior [85, 115, 123, 124], These interactions can lead to emergent behaviors that produce different kinds of traffic problems. For example, “traffic jams” of vehicles can be formed when a group of vehicles is stuck behind one driving slowly. A large number of models have been developed and applied to simulate the process of vehicular dynamics. These studies also effectively simulate the complex behaviors of traffic and people in outdoor or indoor scenarios. The results of these studies can help researchers to develop new ways to integrate and incorporate the increasing availability of autonomous vehicles and the virtual data [85, 115, 124], One particularly effective


28
computational simulation method is a decentralized multi-agent system (MAS), where each agent can only communicate with its immediate neighboring agents. The ABM approach is a form of optimization of individual solutions and applies to systems of interacting, autonomous, and individual agents. The agents in the decentralized system have no direct information about their global position but do have information about their nearby neighbors and their environment locally [3, 9], However, they can only use this local knowledge to collectively construct a coordinate system. In ABM, the agents are described as unique and autonomous entities that embody the origin of the coordinate system [130, 131], Instead of describing the state of whole systems, ABM represents the systems’ individual components, and their behaviors and their generalized nature, which is able to capture complex dynamics and structures [143, 131, 132], It can be observed in the literature that both ABM and complex networks are based on complexity theory. The ABM approach has been successfully applied to a wide range of scenarios including military training, building evacuation, and analysis of digital games [130, 132], The implementation of agent-based framework for the analysis of other complex social systems, including traffic dynamics, has now become more common [85, 143, 131], These two different approaches make a significant impact on the determination of optimum traffic flows. With this kind of a framework, it is also possible to model and simulate the complex interactions that take place between homogeneous agents and vehicles in road traffic [132, 121],
Several mathematical models are available to simulate traffic jams and get a clear understanding about their occurrence and consequences [93], The ones based upon the principles of CA have received a lot of attention [98, 115, 124, 177], One of the practical applications of Cellular Automata is in the simulation of street traffic control. The CA model is an effective
approach to explain the principles of traffic jams, while building the theory from fundamentals.


29
Cellular Automata simulations of complex network dynamics provide excellent assistance and add a higher level of efficiency into the design of transportation facilities. The CA model is a sufficiently advanced and complex model. It has been widely used as a mathematical tool to study a system wherein there are high numbers of agents that are constantly changing their states [93, 98], An example of such a scenario is traffic on highways or a location where there are too many vehicles present, which limits their movement, thus, changing their states [115], In addition, the CA modeling approach has proven useful when the rate of change in a system begins slowly and then increases over time [124], e.g., when drivers apply the brakes and cause a chain-reaction slowdown of traffic behind them.
A large number of studies were conducted in order to get a clear understanding of the dynamic routing-problem, which is referred to as online or real-time Vehicle Routing Problem (VRP) [185], The problem has been analyzed from many different angles to determine if a solution can be derived. One of the most significant decisions in the dynamic routing solution is to understand how certain decisions will be made and the impact of those decisions [88, 177], The primary objective of understanding the decision impact is to provide context-sensitive data and information to the drivers when they are traveling on the roads (e.g., through mobile phones and global positioning systems). Then, the drivers will be able to prevent delays that they would otherwise experience due to a traffic congestion.
During an accident, most drivers tend to look for alternative routes. At the time the driver seeks to select an alternative route, having a clear understanding of the existing traffic conditions on the road is extremely useful [93, 115, 173, 176], Most drivers seek the shortest route, and the available GPS navigation applications and systems provide excellent assistance. However, during times of heavy congestion when drivers are using the same GPS navigation systems, their usefulness is


30
mitigated because everyone will be following the same detour, which results in transferring the traffic congestion [3, 6, 8], To prevent this, drivers need to be alerted about alternative routes by the exchange of data among the other drivers involved. So, the decision on where the vehicle should reroute needs to be made with data gathered from the existing network through sensors.
Assisting drivers in finding the shortest possible alternative routes after an accident is just one of many objectives of traffic information systems. When the required information is made available, the drivers have an easier task deciding the most efficient route to take because they collaboratively look for alternative routes. When collaborating with each other through the same system, the group will not be directed to just one specific route as an ordinary GPS system does. This routing method, called dynamic or distributed routing [98], has been explored through a number of papers [9, 84, 92, 98, 115, 123, 124, 133], It is an agent-based approach for modeling complex transportation networks in a manner permitting vehicles to communicate with other vehicles to gain a better assessment of the current state of nearby road networks. This communication provides drivers with real-time road data, and an enhanced awareness of the road network to help them seek efficient alternative routes, thus reducing congestion [115],


31
CHAPTER III
MODEL DESCRIPTION
In this dissertation, the multi-level multi-stage agent-based model (MLMS-ABM) is presented, where the ABM approach and the non-homogeneous CA have been exploited [21-23] to provide a multi-layered decision support system in cases of crowd/traffic congestions during dangerous cases. The presented work introduces a multi-leveled model where crowd/traffic dynamics are divided into three main levels of decision making: (1) strategic, (2) tactical, and (3) operational. The planning for pre-trip of the route and the final destination is designed at the strategic level. During strategic process, no information is provided about the real circumstances. Decisions for the short term, like avoiding obstacles or changing routes depending on the real situation, are addressed at the tactical level. Additional information about the network such as the flow of agents is available at this point. The operational level represents the agents’ movement that includes the connections with other agents.
The MLMS-ABM model consists of multiple sub-models, as it is shown in the system overview in Figure 1, starting with the model of how the agent selects its goal destination. Then, the acts of avoiding obstacles and collision with neighbored agents are modeled. Also, the hybrid version of the agent-based model includes simulating the leading and following behaviors of agents after dynamically upgrading certain agents to the intelligent level and enabling them to perform some sort of guidance behavior, as detailed below. Besides avoiding collisions with neighboring agents, the framework also includes a model of avoiding high density areas in order to reduce the overall travel time.
The work represents an approach for modeling and simulating complex and dynamic systems, both at microscopic and macroscopic levels. The highest layer represents the


32
macroscopic phenomena of the complex network that would be difficult to model in C A frames. This layer represents the connections between intelligent guide agents that enhance the decisions for the whole system as it will be described below. Instead of considering discrete and singular objects, modeling on the macroscopic scale considers accumulated values. For instance, in macroscopic scale, a cumulated number of pedestrians are modeled in the form of density and a simplified one-dimensional network. Macroscopic models are highly computational and effective with a low level of detail. Thus, modeling on a macroscopic scale is useful for simulating the traffic and crowd on large scale scenarios. The base layer is composed of a high determination CA framework for every open space, which shows how the agents’ neighborhood moves as well as how the development of decision-making at the microscopic level of the system is created. From a macroscopic point of view, the agents move from a starting point to a destination point in a short time. From a microscopic point of view, agents perform complex behaviors during the transition process from one point to the other. Those complex behaviors are strongly affected by surrounding agents’ behaviors, obstacles and conditions of local environment. As a result, agents
may change their paths or intermediate transition behaviors according to those factors. Figure 2 demonstrates the two-layered structure of the proposed system.
Strategic Level
Tactical Level
Environment
Evaluation
Transition
decision-making
model
Floor Fields
Agent Status Upgrading
Behavior Factors
Intelligent Agents
1—*—i—
Other Agents
Rank 1
Communication
Rankn
Final Choice decision-making model
Trustworthiness
Evaluation
Operational Level
Figure 1. Multi-level multi-stage agent-based model (MLMS-ABM) system overview.


33
Figure 2. The two layers of MLMS-ABM model.
The two main managed components of the model are the environment, where the simulation takes place, and the agents, whose autonomous behavior will impact the whole system. ABMs are composed of agents, environments and interactions between them. In the proposed model, space and time are discretized in a way that allows real-time system behavior feedback.
Environment Configuration in the Model
The first step in creating a dynamic simulation is the configuration of the simulation environment. The environment component of this ABM model defines the elements of the physical space, such as a city, building, or roads, etc. where the agents behave and interact. This section describes how agents interact with the environment. This stage also includes introduction of the following components: representation of the environment, environment’s components, and


34
potential floor fields. The environment area is represented using a CA layer, where the area is divided into equal cells. The simulation environment is presented as a grid, which is a two-dimensional array of n*n cells. It is assumed that each cell is of square shape and of a size that can be occupied by only one agent (vehicle or pedestrian).
Three specific types of cells have been designated in a lattice [112] of a non-homogeneous cellular automaton: obstacle cells, which are unreachable; target cells, which represent exits in the evacuation scenarios; and reachable cells, which are considered as the movement space. Only cells belonging to the last two types can be accessed by the agents. The lattice is surrounded by obstacle cells except for a number of target cells where agents can only evacuate the building through these cells.
In the proposed model, three different types of floor fields are considered [109, 119, 131], The first includes both the target fields that are restricted to a specific area and the distance from the destination [131], The second is made out of obstacle fields, which are considered a repulsive force [119], These two floor fields are static. The last type of floor field is the density field, which is dynamic [109], It gives an indication of how the occupancy of every single cell surrounding the agent will change along with time in order to avoid collisions. In addition to the advantage of observing agents’ movement through floor fields, scene structure— the flow of a complex network— can clearly be explained in the context of a specific environment. The preferred movement direction of the people can be examined clearly with the assistance of long ranged forces [122], In fact, a long-range force that represents an individual can give a better understanding of the way crowd/traffic would move towards a target. This represents the local force, which would increase the instantaneous probability of moving in a given direction.


35
In this model, target floor field (IFF) is used to indicate the distances to a destination for every agent in the environment. TFF value is assigned to every cell to describe the distance to the earliest chosen target. That means one floor field is computed for each agent to each target destination. Thus, to move towards a target, the agent should follow the static floor field towards that specific target. We use the well-known heuristic path-finding A* algorithm [136] and Manhattan metrics to compute the static weight of cells in a cellular environment. Manhattan and Dijkstra [137] metrics are used for the area that contain obstacles. However, using Dijkstra algorithm to construct a static floor field may consume considerable time in large environments. In the model, we apply A*metric, which works as well as Dijkstra metric but is easier and faster to compute in order to determine the shortest path out of many possibilities between each cell to a target with the presence of arbitrary obstacles. To calculate the A*metric, a visibility graph is constructed; then, by using A * algorithm, the shortest path is specified. Algorithm A * calculates the explicit values of static floor field SFF for each target in the environment. This means that the strength of the SFF depends on the shortest distance to a target. Inside the field, an agent moves through the gradient of potential field values propagated from the predefined target. In other words, the agents move towards the direction of greater target field values. We represent this phenomenon as follows: let d be the distance to the target T located at point (x, y), where it is calculated based on the Manhattan scheme:
d(x,y) = |x0 - x| + |y0 - y|, (1)
Agent Configuration in the Model
All agents in the environment are considered to be able to learn and adapt. Agents are described in the model by means of their state and behavior. Agent behavior was modeled as a discrete process where agents alternate between states. In a single simulation, the agent behavior


36
is described in five states as a finite state machine (FSM), as shown in Figure 3: environment perception, environment evaluation, status upgrading, communication, and action. The FSM is a set of actions that an agent performs by using a prescribed set of states and actions. The transitions between those states are either temporal or spatial. Each of these states will be described in detail in the following sections.
Each state in the finite state machine (FSM) represents a sub-model (stage) of the MLMS-ABM model, as shown in Figure 3. Each sub-model inside the model represents a particular behavior which is considered as a general-purpose action or set of actions that an agent performs. The sub-model is described using a prescribed set of states and actions. An example of a general type behavior would be “Follow the neighbor agent” or “Follow the fastest route.” The information from one state in the FSM can affect the transition to another state. The decision to move from one state to another in the FSM is based on the status of the neighbor agents and the local environment data. The hierarchical state is decomposed into the sub states or stages, as represented in Figure 1. Levels in the MLMS-ABM model are special types of behaviors specifically designed to perform a sequence of actions or behaviors. Each level performs a decision-making process based on constraints forced by the local environment and the states (characteristics) of neighbor agents. Those constraints determine how to transit between various sub-models within each level. The constraints can be constant values, such as vehicle maximum speed, or dynamic data such as current velocity at a specific location.


37
Figure 3. A finite state machine (FSM) representation corresponding to state transition of the agent’s behavior.
In this model, the agents are able to learn from the environment (task follow, neighborhood configuration, interactive information, etc.) and accordingly adjust the network. In order to perform the task effectively, each agent reorganizes its neighborhood in a distributed way with only local available information. The agents are provided with the ability to move and interact along with the neighboring cells. Every movement is determined with the assistance of a given set of rules. To promote the practicality of the simulation, the model takes into account the heterogeneity of the agents’ movement speed is not constant. Instead, the movement is modeled as a continuously dynamic variable influenced by the surrounding density, the behavioral characteristics of the agents, and the environment’s structure. Thus, the movement speed is modeled to be adapted on the agent’s current condition at each simulation step. In other words, the agent can move with maximum speed if all intermediate cells between the current location and the destination cell are not occupied by other agents or obstacles. In this model, three different speed levels are proposed, as shown in Table 1. As a result, the dimension of the Moore


38
neighborhood [122] is expanded from 3x3 to 7x7. This means that at one time-stamp, the agent can move at the highest speed, which is the highest, or third, level of the Moore neighborhood. At the same time-stamp, other agents might move with the lowest speed if the current density around the agent is at the highest value. The maximum speed of agents is set to be s = lm/s: about 3 cells/time-stamp. The speed will be kept in the maximum speed until the density value around the agent becomes equal to 1. A collision is considered as maximum density, which is recorded when all the adjacent cells of an agent are full, and the location cannot be updated. In the case where some or all of the intermediate cells are occupied by another agent or obstacle, the agent’s speed will be dynamically adjusted to a lower speed proportional to the distance to that barrier.
Table 1. Agents movement speed.
Speed Steps
0.33 m/s 1 cell per time-stamp
0.67 m/s 2 cells per time-stamp
1.00 m/s 3 cells per time-stamp
The agents in the proposed model are randomly assigned with objective and subjective parameters at the beginning of the simulation. The individuals’ characteristics, or subject parameters, include awareness of the environment, cooperativity, adaptability, flexibility, perception of potential risks, acceptance to follow orders, and ability to access global information about the environment. On the other hand, drivers’ objective characteristics include age, health status, and communication capability.
Agents are loaded into the environment area based on a predefined demand-loading pattern specified by the user. Upon starting the simulation, the goal of each agent is to approach the congestion-free point and to be as close as possible to the destination (goal). The shortest


39
travel time path between the origin and the selected destination is determined by the transition decision-making model as described below.
Target-Driven Decision-Making Model
The first stage of the multi-staged agent-based crowd modelling system is the design of the rules that govern the decision-making process for agents to choose a target (i.e., an exit). Many studies design decision rules empirically based on domain known experiences [138], The proposed system automates the process of extracting decision rules by adapting gene expression programming [139] to find optimal decision rules from objective behaviors. First, the problem of finding optimal decision rules from the prescribed objective behaviors was formulated as a symbolic regression problem. Then, the gene expression programming is applied to solve the problem. So, by using the extracted decision rules, the model will be able to reproduce specific objective behaviors. That means in this stage of the proposed model, decision making of the agents, i.e., choosing a target, is determined by the extracted decision rules.
The optimal initial target decision is impacted by different factors that the agents perceive from the environment. The model involves four important factors: the distance to a target, the width of the target (exit), the speed of the agent, and the density at the target. For each agent a, the initial target decision (ITD) function is calculated to assign a specific target, which has the minimum ITD value, to agent a. For j targets in the environment, the ITD function is calculated as follows:
ITD (a) = min(^+^), (2)
sa wj
where: •
• dj is the distance to a target j,


40
• sa is the speed of the agent,
• tdj is the density (congestion) at that specific target j,
• Wj is the width of the target j.
The distance to the target j located at point (x0, y0), is calculated based on the Euclidean scheme [44]:
d(x, y) = 7(x0 -x)2 + (y0 - y)2 . (3)
Transition Decision-Making Model
Every agent's decision about the optimal route is based on the desired travel time to reach the desired destination. At every time-stamp and for each agent, a new target cell is selected from the eight candidate cells in the Moore neighborhood to define the travelling trajectory. This choice is based on the probabilistic calculation performed on each candidate cell, and the agent will select to move to the cell with the largest probability. The transition probability is largely affected by the static target floor field, (TFF). Also, interaction between agents has a major influence on the decision for choosing the subsequent cell. Altogether, transition probability, P(x,y), is determined by four factors: (1) dynamic floor field, (2) target floor field, (3) obstacles floor field, and (4) the density around the next target cell.
TFF value is specified based on the computation of A* algorithm [136] that calculates the distance from the origin point to the destination. Applying A* algorithm only as a routing technique neither specifies where the processing for the routes exists nor captures the varying conditions of congestions at any point in time. The agent a will move to the target cell, the neighbor empty cell with the highest probability among Moore neighborhood cells in the next


time-stamp. The transition probability, P(x,y), to move to an unoccupied neighbor cell is on floor fields of the cell (x,y).
41
In each time-stamp, the dynamic floor field Di;- decays with some probability and diffuses with some probability to one of its eight neighbor cells. In order to calculate the
the model calculated the dynamic floor field (DFF) according to decay and diffusion as follows:
where a is the diffusion probability that represents the randomness of an agent’s movement, and 8 is the decay probability that reflects the agent’s visible range.
In the model, it is expected that people usually avoid walking close to walls and obstacles. Many studies have observed high density areas around obstacles and corners in simulations that do not include wall potentials [57, 121, 135], This occurs since everybody tries to evacuate along the minimum path length. The introduction of a repulsive obstacle potential in the proposed model, which is achieved by the generation of virtual fields around obstacles, prevents movement close to obstacles. The repulsive obstacle potential is inversely proportional to the distance from the obstacles. The obstacles’ effect disappears for distances greater than a certain threshold. Thus, the impact of the target static potential field is affected by the obstacles’ floor field (OFF). The values for the cells occupied by obstacles are set to be the highest values of the cells in the environment. The obstacles’ static potential field is calculated as follows:
dynamic floor field, first, all the cells are initialized to 0, i.e., at t = 0, Dfj = 0 for all cells. Then,
(4)
OFF(x,y) = min(Dmax ,dx,y) ,
max f
(5)


42
where d represents the minimum distance from the obstacles, and Dmax is the maximum distance at which people feel the obstacles.
One of the key elements of the model is the collision avoidance sub model. It provides the ability to calculate potential interactions between agents and the density around each cell. It is measured based on the number of agents within the specified space of range r. It insures avoiding collision during calculation and the best trajectory to take for each agent. Therefore, the model provides the awareness of when the possible interaction between agents can or will occur during travel, and it enables each agent to be aware of potential interactions with other agents.
For each agent a, we calculate the transition probability to each empty cell (x, y) in its Moore neighborhood as follows:
P(x,y) = N exp{—kT TFF(x,y) + kDDFF{x,y) + k0OFF{x,y) + kdenDen(x,y) +
kjl), (6)
where:
• N is the normalization coefficient,
• TFF(x, y) is the target static potential field value,
• DFF(x, y) is the value of the dynamic floor field,
• OFF(x, y) is the obstacles floor field value,
• Den(x, y) is the value of the density field,
• / is the inertia parameter,
• kT, k0, kD, and kden G [0, go) are weight sensitivity parameters of target, obstacles, dynamic, and density floor fields, respectively,
• k, is weight sensitivity parameter of the inertia.


43
To solve a conflict, such as when more than one agent moves to the same cell, one agent is randomly chosen with equal probability and succeeds to proceed, whereas, the other remains at his/her cell. If no movement is possible in any of the adjacent cells, the cell state will not change, and the agent remains motionless.
Applying this transition decision-making model ensures the shortest path that avoids obstacles and congested spots along the agent’s route. This transition function enables the agents’ projected path to be updated to alleviate collision, and thus improve cooperation between agents. Also, this sub-model will help each agent to check for possible interactions with other agents.
Agent Status Upgrading Model
The third stage in the MLMS-ABM simulation classifies different types of agents in the environment. The agent-based model here represents two sets of agents: the first set is familiar with the environment, and the other one is not. In the proposed model, this is a major stage when the agents’ expected behaviors are examined. The expectation is dependent on the intelligence level during different situations and scenarios. Allocating guidance tasks and intelligent status to the right agents is important in multi-agent systems. Here, a novel allocation algorithm is proposed that is based on dynamically changing structures. The classification is done based on subjective and objective characteristics of the individual agents, as mentioned above.
In the proposed ABM implementation, the environment CA grid is evenly divided into square regions to estimate the density at each region (if it is more than a predefined threshold). The regional density is measured by counting all agents in the region and then dividing by the region area. At the regions with high density, the objective and subjective parameters are examined for each agent in that region. If these two parameters meet the condition for an


44
intelligent agent, based on a predefined threshold, then that agent’s status is upgraded to that of an intelligent agent, as shown in Algorithm (1). The intelligent agents in MLMS-ABM model are considered as the decision makers because they are able to evaluate the exchanged information and make decisions about their current route in order to improve the total travel time, while reducing congestion. Being an intelligent agent means that the agent is relied upon during the decision-making processes by other agents. Once an intelligent agent is assigned in a specific region, the neighboring agents adapt their moving attributes to the intelligent agent. MLMS-ABM model maps the decision space of followers into the intelligent agent’s decision space, after which the followers decide upon the decision variables that optimize his objective function.
All agents are looking for faster routes, while concurrently following the intelligent agent in a group of other agents. At the same time, they are ensuring that they stay away from high density/congestion within the surrounding neighborhood, which could potentially decrease travel time. Particularly, unfamiliar agents apply only the operational level by following or mimicking intelligent agents’ movements, thus maintaining the collective pattern.
In the proposed model, the number of intelligent agents is not constant, and it depends on the density of the crowd /traffic. Also, the position of the intelligent agents could be in front of follower agents, as in the crowd and traffic modeling, or lateral (left, right, center) as in traffic modeling.
In the MLMS-ABM model, the upgrading stage is dynamic, i.e., the status of the agents changes throughout the simulation. The status alteration depends on changes in the surroundings or changes in the agent’s objective parameters. The status of an agent could change, either up to intelligence layer or down to a normal layer, during the simulation. An upgrading/downgrading procedure enables the proposed model to cover all the individuals’ behaviors under all situations.


45
For example, partway through the simulation, intelligent agents could be changed back to normal status. So, the upgrading model is dynamically run several times for each agent during the simulation.
ALGORITHM 1: Dynamical Status Upgrade for each agent a in the simulation environment do a.Objective-Parameter = Random [0,1]; a.Subjective-Parameter = Random [0,1]; end
Divide the environment space into equal regions; for every k timestamp do
for each environment region do
if (Density > Density-Threshold) then for each agent a in the region do
if (a.Objective-Parameter > Objective-Thresholdjand (a.Subjective-Parameter > Subjective-Threshold) then if (a.Status = Follower) then a. Status = Intelligent; a.MooreNeighbors.Status = Follower; end else
for each agent a in the region do a.Status = solitary;
end


46
end
end
The proposed model is generalized by increasing the variety in the statuses/rankings of intelligence possible for the agents instead of having only two levels of agents. The classification is based on the subjective parameter of intelligent agents. The interactions and communication behaviors between agents is based on intelligence ranking. For instance, if two agents with different intelligence rankings meet at the same point and have different decisions, then the lower-ranked agent follows the higher-ranked one. Algorithm (2) illustrates the classification of intelligence ranks based on the subjective parameter that is assigned to agents at the beginning of the simulation.
ALGORITHM 2: Multiple Levels of Intelligence for each Intelligent in the simulation environment do
if (p.Subjective-Parameter > Subjective-Threshold 1) then p.Rank = 1;
else
if (p.Subjective-Parameter > Subjective-Threshold 2) then p.Rank = 2;
else
if (p.Subjective-Parameter > Subjective-Threshold n) then p.Rank = n; end
MLMS-ABM robust distributed algorithm is able to detect dynamical changes in task requirements and is able to react to them quickly. The adaptive network mechanism explored in


47
this chapter enables the intelligent agents to aggregate historical information and adjust the intermediate targets continuously to keep up with the task requirements.
Evaluation of Trustworthiness Model
Trust as a computational concept [140-159] is important in understanding the thought process with regard to choices, options, and the decision-making process during human interactions, especially in situations where there is a risk. The term trust [142] is commonly used in multi-agent systems since these systems usually contain uncertain, incomplete, or incorrect knowledge from various information sources [140, 141, 145-147, 149], Trust between agents is defined as the agent’s expectation about another’s perspectives [150], In the model, a trust evaluation algorithm was investigated for agents in a multi-agent system based on the trustworthiness of related intelligent agents. The term trustworthiness is used here to measure the trust level a follower agent has in the intelligent agent to make a correct decision about the next target.
It is mentioned previously that agents are divided into two groups in their environmental perspective: one familiar and one unfamiliar with the current environment. Unfamiliar agents build their local perspectives based on the quality of the incoming information sources. Intelligent agents in the model play the role of information sources for others. Here, the trust concept is introduced as the agent’s confidence in the ability of a related intelligent agent (information source) to deliver accurate information. An agent is considered to be trustworthy if it has a high probability of performing a particular action which, in my context, is to make a trustworthy correct decision about the final target. The amount of trustworthiness of an intelligent agent is built through other neighboring agents.


48
Before agent a can make a decision to follow the actions taken by intelligent agent p, agent a needs to evaluate the trustworthiness of agent p. Particularly, the probability that a following agent would approve of an intelligent agent’s opinion on a specific target is dependent on the approval of the neighboring agents about the decision taken by the intelligent agent.
To illustrate, suppose an intelligent agent p provides knowledge, or decision q to agent a. Suppose n neighboring agents have contributed to the current decision q. The parent nodes of the decision tree consist of a combination of the neighboring agents’ decisions, including the intelligent agent who is one of the neighbors. Figure 4 shows the resulting decision tree.
Figure 4. Decision tree with n neighbor agents.
After the decision tree has been built, the certainty value agent a has on decision (knowledge) q can be calculated from propagating probabilities in the tree. The trustworthiness probability about the decision q is calculated as follows:
P(.q) = S If=iIy=i^(?|a/)P(a/), (7)
where:
• is the normalizing factor,


49
• P(q|cq ) is the certainty factor that an agent aL has on decision q. That means an agent aL thinks q is correct with probability P(q\at ),
• P(a{) is the reliability factor of an agent aL .
Therefore, the agent’s probability of following a decision process is based on the greatest certainty value of P(q). In other words, agent a trusts intelligent agent p only if trustworthiness probability value is greater than or equal to a predefined threshold.
All proposed stages and sub-models of the three levels of the MLMS-ABM model are performed in the microscopic layer as they are implementation components of the layer. However, when the agent status upgrading sub-model is performed, the intelligent agents are generated, and the macroscopic layer is generated as a result. The communication and trustworthiness evaluation stage is performed in both the microscopic and macroscopic layers.
Figure 5 shows the overall modeling framework that consists of three main modules: input, simulator and output. The input module processes the input data which includes: (a) geometries of the environment, (b) agent configurations, and (c) simulation parameters. The geometries description includes defining the environment shapes with their dimensions and spaces and illustrates how the environmental space will be changed during the simulation. It also provides the locations of all obstacles and gates inside facilities. This information is typically extracted from CAD files. Agent configuration input specifies the number of agents entering the simulation environment from different starting points in the different time intervals. In addition, the major behaviors expected during simulation, and the percentage of agents who follow these behaviors are assumed given. Also, the agents’ moving maximum speed is delineated, which defines the average distance an agent can move per unit of time when allowed to move freely in the area. The speed attribute is assigned to the agents based on surrounding congestion and


50
density. During the simulation, the speed values change over time. Simulation parameters determine the general following behaviors of the agents: deterministic, non-deterministic, and non-intelligent. First, for deterministic behaviors, the MLMS-ABM model is applied where all agents should follow the intelligent agent in their region. Thus, no implementation of the trustworthiness sub-model is needed. Second, in the non-deterministic technique, where agents in a region have a choice to follow or not follow the intelligent agent in that region, some of the agents are in the solitary case, meaning that the proposed model isn’t applied to them. Finally, or non-MLMS-ABM behavior is implemented as a baseline of the experiments, where only the traditional agent-based simulation is implemented without involving the strategic and tactical levels.
Input
Environmental
configurations
Obstacles
Goals
Open spaces Dynamical changes
Agent
configurations
Demand loading pattern
Spatial Distribution Behavioral rules Agent characteristics
Simulation Parameters
Following behavior Intelligent/ Non- Intelligent Deterministic/ Non- deterministic
Simulator
Behavioral rules
Goal selection Communication Follow neighbor Route choice Collision avoidance Agents' movement
l
Output
Visualization interface Statistical datasets
Figure 5. The overall modeling framework.


51
Model Validation
The simulation output can be observed in the form of real-time visualization, and it is saved as data in spreadsheet files for later analysis and evaluation of the model. The model results enable us to evaluate the conditions that would need to occur in the network and improves the understanding of which assumptions and future developments could have the most impact. Evaluating the predictive model shows how this model can be useful in managing crowd flow. In addition, MLMS-ABM model provides output statistics that enable users to store data from many simulations and do comparisons between multiple findings. Comparing between different scenarios also enables the user to get the average of many runs. In order to validate the proposed model, implementation was performed using a custom imperative programming approach; a Python module.
A required step for validating and analyzing the model is performing a sensitivity analysis. A sensitivity analysis, or what-if analysis, is a technique used to understand the effect of different values of an independent variable on a dependent variable under certain specific conditions and assumptions. It can involve changing some attributes of the data to create a specific scenario. Running over the possible range of values will allow us to know which parameters of the model are most critical to control. The sensitivity analysis can help discover the likely reasons for differing data, giving us valuable information about which parts of the model need extra analysis and possible change. In addition to sensitivity analysis, scenario analysis is performed where all the variables that would affect a specific scenario are identified and then manipulate them to understand the full range of outcomes. In the scenario analysis, it is possible to create a number of scenarios, based on different objectives, to provide insight into the effects of each decision. By applying the scenario analysis, a comprehensive image of the model


52
is developed, thus gaining knowledge of the full range of outcomes, given a specific set of variables defined by real-life scenarios.
To analyze the proposed model for crowd management, many simulations that exhibit actions, such as incidents and evacuations, are created. The key metric used for performance evaluation in the proposed model is the total travel time needed for agents to reach their individual goals. In other words, the shortest possible trip time for the agents in reaching their destinations should be ensured. The fastest paths are updated regularly as networks can change rapidly. In addition, the crowd flow measurement is used as a metric for model performance evaluation, as one of the main goals of crowd and traffic management is improving the flow and the travel time. The flow data is used to estimate the parameters of the model, which enables us to objectively optimize and evaluate the model. Also, to check the validity of the proposed model in the vehicle-vehicle interactions scenario, the vehicular delay is observed in addition to the flow of vehicles. In addition to measuring the system flow, simulations for the hypothetical scenarios will be performed to capture these travel times:
a. The individuals to reach their final destinations (i.e., exits) with congestion avoidance in the indoor settings evacuation scenario.
b. The individuals to reach their final destinations with congestion avoidance.
c. The vehicles to reroute around the incident and reach their destinations without colliding with other vehicles in vehicle-vehicle congestions scenario.
Implementation Set-up
The proposed model is facilitated through computational tools; for example, AutoCAD is used to model the simulation environment (space), while the spatial semantics, agents’ behaviors, algorithms and sub-models are scripted using Python programming language. The


53
running time of the simulation model varies by the loading scenario and by how many agents are in the system at the same time. It runs on a macOS Mojave computer (version 10.14.4) with a processor Intel Core i5 CPU @ 2.6 GHz and Memory 8 GB 1600 MHz DDR3. The code size is about 30 KB.
The ODD Protocol
The structure the information and description of the ABM model is based on the standard protocol, ODD [160, 161], This protocol consists of seven elements that can be grouped in three blocks (Overview, Design Concepts, and Details). The Overview consists of three elements (purpose, state variables and scales and process overview, and scheduling). In the Overview, the overall purpose and structure of the model is presented as it is presented in this Chapter, where the idea of the model’s focus, resolution and complexity is given. Also, this Chapter includes the declaration of all objects (classes) describing the model’s entities (different types of individuals (agents) and their behaviors and environments) and the scheduling of the model’s processes. The design concepts provide a common framework for designing and communicating ABMs, which describes the general concepts underlying the design of the model. These concepts include questions about the theoretical and empirical background, individual decision-making, learning, individual sensing and prediction, interaction, collectives, heterogeneity, stochasticity, and observation. The design concepts of the proposed model are detailed in Chapters IV and V. The third part of ODD, Details, includes four elements (implementation details, initialization, input, sub-models). The technical information, such as the model implementation and the programming language, are delivered in this Chapter. The experiments and the information required to reimplement the model and run the baseline simulations are provided in Chapters IV and V.


54
CHAPTER IV
DECISION SUPPORT SYSTEM FOR SIMULATING AND MODELING OF CROWD DYNAMICS AND EVACUATION
Introduction
A crowd evacuation system is a complex system with multiple interacting agents such as people, vehicles, communication systems, disaster management authorities, etc. The events that occur during a crowd evacuation have far-reaching implications for the safety of individuals involved [94], Studies concerned with characterizing, describing, and predicting the collective behaviors and movement dynamics of pedestrians in public facilities have been conducted for decades in order to assess potential evacuation risks and suggest countermeasures [80, 87, 121, 126, 127, 135-141], Findings from these studies have contributed to the prevention of crises by influencing building design and crowd management strategies. Studying crowd behaviors in normal and emergency situations has been facilitated by various agent-based pedestrian models [162-170], Different assumptions have been considered when building the models that represent or mimic reality, and verifying those assumptions by using existing datasets is one of the key challenges in pedestrian modeling.
Crowds tend to move from disorganized to organized forms when a common goal such as evacuating an enclosed space, is being pursued. For example, during any kind of evacuation, crowds are observed to form the shape of a flock as they move in unison towards exits. In the model, the search algorithm employed by individuals within the crowd is derived from our previous work that used an agent-based modeling approach (ABM) to replicate foraging behaviors of ants [102], Most parameters from the ant model are duplicated in the crowd agents.


55
The crowd agents’ movement during undirected movement replicates the correlated random walk of virtual ants [102], Thus, the ABM was exploited to model and simulate the crowd dynamics since the ABM technique is typically employed by most animal behavior, including flocking birds. We developed a modeling framework [142, 143] for crowd dynamics in dense areas and large facilities using the ABM combined with non-homogeneous cellular automata (CA). The modeling framework [143] is used to develop a decision support system which aids in the understanding of crowd dynamics, specifically under risk conditions during evacuations.
The proposed model [21, 22] simulates the complex behaviors of crowds during panic situations by utilizing a hybrid, multi-stage, agent-based approach. A self-adaptive architecture was modeled for managing crowd behaviors using a heterogeneous multi-agent system. The focus was on studying crowd domain because pedestrian dynamics have not been studied as extensively as vehicular traffic, particularly using a CA, which could be due to its generically two-dimensional nature.
The developed versatile agent-based framework encompasses the fundamental principles of crowd dynamics commonly applied to building evacuations. To this framework, an adjustable approach is introduced for simulating human perception and decision-making in dangerous scenarios as the goal of this work is to create a model that is able to simulate varying individual behaviors. The crowd dynamics decision-making modeling has been branched into three levels: strategic, tactical, and operational. The formulation of a plan and the final objectives, such as deciding on an exit to move towards, are drawn in the strategic level. At the tactical level, all activities are computed and performed to facilitate the formulated plan. The operational level includes the physical executions and procedures of the activities developed in the tactical level. An example of operational level behavior would be the movement of a person from one point to


56
another. The goal is to be able to mimic intelligent and self-organizational behaviors and gain reliable results. The two main components of the proposed model are the environment in which the simulation takes place and the agents, whose autonomous behavior will impact the whole system. The relationship among all the elements of a crowd is essential because the dynamic of this interaction influences the dynamics of the entire system.
The previous chapter mentions the major contributions of this dissertation. It describes the multi-level multi-stage agent-based decision support system for crowd dynamics during an evacuation process [101], ABM, combined with CA and floor field approaches, was applied to model pedestrian behavior and crowd phenomena. The proposed framework includes multiple dynamic decision-making stages to improve the complex process of evacuation during an emergency. Both the macroscopic and microscopic points of view of crowd flow inside constrained environments were examined. The framework also introduces several interconnection rules between individuals inside of the system as well as between these individuals and their environment. The macroscopic layer represents the connections between intelligent guide agents and their capability to enhance the decisions for the whole system. The microscopic view is composed of a high determination CA framework for every open space. It shows how an agent’s neighborhood moves, as well as how decision-making develops at the microscopic level of the system. The two main layers, macro- and microscopic, are modeled in three levels using multiple sub-models. At the strategic level, a model was introduced in which decision rules were automatically extracted. The aim of this approach is to acquire environmental perception and optimized objective selection. At the tactical level, decisions for intermediate goal selection, upgrades of an agent’s guidance status, and trustworthiness assessment of related


57
intelligent agents were examined. The agents’ physical behavior, which included the connection with other individuals, was modeled in the operational level.
The aim of the model is to accurately simulate the real crowd behaviors and phenomena, allowing for improved decisions taken to enhance the complex process of crowd management under various evacuation scenarios, as it provides tools to analyze the effects of architectural changes on evacuation plans. It can be used to assist decision-makers in solving logistic and organizational challenges. In this chapter, the movement times of evacuation from large facilities were modeled, such as supermarket and multi-store buildings, on the microscopic, ABM and CA, and macroscopic base.
Model Description
In this proposed model, the ABM approach and the non-homogeneous CA are exploited and a new simulation method is developed to provide a multi-layered decision support system in cases of crowd evacuation. The work aims to understand the movement of large crowds during evacuations from buildings.
The MLMS-ABM model was adapted for mass evacuation scenarios by using a concept of static and dynamic floor field as well as a prosperity of transition function of agent movement. The model’s second stage (transition decision-making), which is developed according to specific representation of individuals, corresponds to deciding the cells that are expected to be occupied by each agent in the following time-stamp. Those cells are mostly determined by using the SFF since pedestrians are mostly expected to move toward the destination or exit in the shortest way. Thus, it has been assumed that pedestrians walk along to the gradient of the SFF.


58
Environment Configuration in the Model
To represent the severe congestion scenarios that are usually observed in the evacuation locations, an average cell dimension of 40 centimeters is considered. The model uses CA as a detailed representation of the simulation space, where a pedestrian is represented in CA crowd models as a state of 40cm x 40cm square cell. The cell dimension is considered such that a maximum density of about 7-8 pedestrians/m2 is usually observed during very crowded situations. Initially, every agent had been assigned to a specific cell, and the agent’s center corresponds with the center of the cell. An agent can transfer to another cell in the Moore neighborhood of radius 1 (±45, ±90, and ±135 degrees), as represented in Figure 6. For each cell in the area, the set of non-occupied adjacent cells is determined.
Figure 6. The next time-stamp target cells.
Experimentation and Analysis
To cover the whole range of densities, a number of simulations with variable population sizes have been conducted. The experiments in which the size of the crowds is scaled up, the number of obstacles in the environment, and the size of the area in which the virtual agents navigates were done with changes happening in the environment, such as a falling wall or a closing path.
P-1,1 o' CL Pi,i
P-1,0 "0 o o Pi,o
P-1,-1 "O 0 1 Pi,-1


59
To investigate the performance of the proposed model, three different scenarios with different sizes, number of targets, and complexity were designed. The crowd behavior is more complicated in the third scenario than those in the first and second ones through the introduction of more obstacles and the removal of a number of targets (exits) available in the environment. The first scenario is 20m x 10m with six exits, the second scenario is 30m x 30m with four targets, and the third scenario is 30m x 50m with three targets as well as more complex interior walls as shown in Figure 7. A snapshot of the simulation is given in Figure 8 illustrating crowd movements filling the space. The black dots represent agents in the facility. The blue, lime, and magenta dots represent intelligent agents with different ranking.
E6
E1 E5
E4
E2 E3
(a) First scenario.
E4
E1
E2
E3
(b) Second scenario.


60
Figure 7. Configured simulation environments.
0
20
40
60
80
LOO
0 10 20 30 40 50 60 70 80
Timestamp: 10
Figure 8. Screenshot of the simulation environment (Third scenario).


61
Figure 9 shows the variation of density to each target’s static floor field (TFF) in each scenario. The distribution of agents is random throughout the environment at the beginning of the simulation. Each agent is assigned to one cell in the environment. If a pedestrian already exists in the cell, a new pedestrian does not appear. Thus, they were permitted to stop only if they cannot avoid collisions. When an agent reaches its target, it is considered evacuated from the environment and removed from the simulation. The above modeling framework is executed independently ten times in three different cases. The first case is deterministic, where all agents should follow the intelligent agent in their region; thus, there is no implementation of trustworthiness model. The second case is non-deterministic, where agents in a region have a choice to follow or not follow the intelligent agent in that region. In the third case, Non-MLMS-ABM, agent-based simulation was implemented without involving the tactical level which means there is no existence of intelligent agents in the simulation and no application of trustworthiness. In this case, pedestrians move naturally without any instructions. For each simulation scenario, the evacuation of the crowd is modeled using different loading values (different population sizes) to cover the whole range of densities. In each simulation, six different loads of crowds are considered, ranging from small crowd, average crowd, to large crowd. In Figure 9, the blue radiance represents the higher force of attraction of the TFF value. The yellow radiance illustrates avoiding areas that prevent or delay agents from reaching their exit.


62
0 50 100 150 200
(a) First scenario.
(b) Second scenario.
0 10 20 30 40 50 60 70 80
(b) Third scenario.
Figure 9. Scenarios targets’ floor field (TFF).


63
Results and Discussion
The ultimate aim of the work of this chapter is to test the capability of the presented model in improving crowd behaviors during evacuations. Because one of the main criteria for the performance evaluation of the crowd simulation model is the total travel time needed for the agents to reach their individual goals, the shortest possible trip time for the agents to reach their destinations was ensured. The model uses the evacuation time of the individuals as the evaluation metric. If an exit is overcrowded and congested, the agents will determine whether to select a farther exit for escape, and by selecting the optimal exit and avoiding congestion, the evacuation efficiency can be improved. Different attributes of the crowd have been considered in the implementation of the model. This includes, but is not limited to, the individual characteristics of the agents, such as language, culture, and age as well as environment obstacles that could be caused by external events or the agents themselves.
The first result is related to demonstrating the model’s efficiency in promoting the overall travel time of the crowd during evacuation for different population sizes for the three scenarios. The values of the sensitivity parameters in the runs for this experience were as follows: kT = 2.0, kden = 0.5, k0 = 0.3, kD= 1, k[ = 3.0, and Dmax = 10. Specifically, it was observed in the first two cases of the three scenarios that all agents in the environment have been evacuated in a short and reasonable time. However, it took the agents a longer travel time to evacuate in the last case, the Non-MLMS-ABM, as shown in Figure 10. In the first scenario, the agents spent the longest time to evacuate in the Non-MLMS-ABM case, and then the deterministic condition and non-deterministic follows. This qualitative tendency is significant for all the crowd loads except for the small crowd load of 500 agents. The same tendency was observed in the second scenario. In the third scenario, however, the pedestrians took the longest time to evacuate in the Non-MLMS-


64
ABM case, yet, they were evacuated faster in the deterministic condition than in non-deterministic. This tendency should be considered as general characteristics of pedestrians while this result confirms the benefit of relying on an intelligent agent to improve the evacuation overall travel time.
180
160
500 1 000 1 50 0 2 00 0 2 50 0 3 000
Number of agents
â–  MLMS-ABM (Deterministic) â–  MLMS-ABM (Non-Deterministic) â–  Non_MLMS-ABM
(a) First scenario.
450
— 400
Q.
1 3“
in
dj1 300 E
— 250 £ 200 g 150
CO
~ 100
CO
£ 50
0
â–  MLMS-ABM (Deterministic) â–  MLMS-ABM (Non-Deterministic) I Non MLMS-ABM
500 lOOO 1500 2000 2500 3000
Number of agents
(b) Second scenario.


65
(c) Third scenario.
Figure 10. Total travel time to evacuate.
In addition, the travel time histogram shown in Figure 11 supports the results in Figure 10 as it illustrates the travel time for the same agent from the same starting point in the simulation environment to reach the destination and to evacuate from the building. In this experiment, the travel time was compared between the two cases of the proposed MLMS-ABM and the Non-MLMS-ABM models during three crowd loads. This result validates that the MLMS-ABM model provides quicker evacuation times than the Non-MLMS-ABM regardless the number of
agents.


66
(b) Second scenario.


67
The second finding illustrates the model’s capability of improving the crowd flow pattern. The values of the sensitivity parameters of the floor fields in the runs that represents individual's radius for this experience were set as follows: kT=3.0, k0= 0.8, kD = 0.8, kden= 0.3, k,= 1, and Dmax = 10. Figure 12 shows that agents’ flow rate is the highest in the non-deterministic case, followed by the deterministic case in the second scenario, whereas it is almost the same between these two cases in the second scenario and the flow rate is the highest in the deterministic case in the third scenario. In contrast, the lowest flow rate is in the Non-MLMS-ABM case in all scenarios. In general, the crowd is evacuated quickly at the beginning of the simulation and gradually becomes slower as the evacuation proceeds, indicating the ability of proposed model to improve the overall crowd flow during evacuation.


68
0.9
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69
Simulation time-stamps
MLMS-ABM (Deterministic) — — -MLMS-ABM (Non-Deterministic) ••••Non_MLMS-ABM
(a) First scenario.
0.9
— 0.8
(/>
E 0.7 c
nj 0.6
0.5
0.4
0)
â– O
OJ
Q.
0)
^ 0.3
nj
l.
5 0.2 o
0.1
0
Simulation time-stamps
— MLMS-ABM (Deterministic) —— MLMS-ABM (IMon-Deterministic) • • • • Non_MLMS-ABM
(b) Second scenario.


69
Figure 12. Cumulative flow of agents.
The speed of the agents’ movement to evacuate was measured by tracking the same agent during the simulation under different conditions and different crowd loads. It can be noticed from Figure 13 that the non-deterministic MLMS-ABM model has obvious advantages over other two models in the first and second scenarios, whereas it has no advantage in the two MLMS-ABM cases in the last scenario as the crowd evacuated more quickly than in the Non-MLMS-ABM model. The sensitivity parameters for this experiment are as follows: kT=2.0, k0= 0.3, kp 1, k^en 0.5, kj 0.8, and Dmax 10.


70
“O
Q.
V)
M
H3
>
03
C
bD
<
4
3.5 3
2.5 2
1.5 1
0.5
0
1000 2000 3000
Number of pedestrian
----MLMS-ABM (Deterministic)-------MLMS-ABM (Non-Deterministic) -------Non_MLMS-ABM
(a) First scenario.
Figure 13. Agents’ average speed.


71
Figure 14 shows the change of pedestrian number who evacuated from the simulated facility. Figure 14 shows the change in the number of 1000 agents in the scene of (a) six exits,
(b) four exits, and (c) three exits. The histogram shows that the number of evacuees between the MLMS-ABM model and the Non-MLMS-ABM model is distinguishable at the beginning of the simulation in the first and second scenarios. On the other hand, it is difficult to distinguish between the number of evacuees in the third scenario, which is more complicated with more obstacles.
(a) First scenario.


72
(c) Third scenario.
Figure 14. Changes in population size over time in different evacuation scenarios.
In addition, the following experiment shows the model’s efficiency in upgrading the agent’s status dynamically, i.e., the status of the agent’s changes throughout the simulation. The status alteration depends on changes in the surroundings or changes in the agent’s objective parameters. The experiment was conducted on the third scenario and the number of agents was


73
1000. The values of the sensitivity parameters in the runs for this experience were as follows: kT = 1.8, kden= 0.5, k0= 0.3, kD= 1, k,= 3.0, and Dmax= 10.
Figure 15 shows that all evacuees in the environment have been evacuated in a short and reasonable time when applying the proposed model, while it took them a longer travel time to evacuate when the intelligent agents were assigned once at the beginning of the simulation. Also, the speed of the agents’ movement to evacuate was higher when the upgrading model was dynamically run several times for each agent during the simulation than when the upgrading model was executed once (see Figure 16). This result confirms the generalization feature of the proposed model.
400
343
Dynamical upgrading of One_time upgrading of
Intelligent agents Intelligent agents
Figure 15. Testing dynamics of upgrading model through evacuation total time.


74
1.6
ro 0.6
S 0.4 00 <
0.2
0
0 20 4 0 6 0 80 1 00 1 20 140
Simulation time-stamps
• Dynamical upgrading of Intelligent agents • Onetime upgrading of Intelligent agents
Figure 16. Testing dynamics of upgrading model through pedestrian’ average speed.
Figure 17 shows the crowd’s overall travel time during evacuation when the environment is dynamically changing compared to when the environment is static. Also, Figure 18 illustrates the system throughput when the environment is dynamic compared to the static version. These results are due to the dynamical selection of the targets (exits) by the intelligent agents. Every predefined duration, the intelligent agents reselect the best target to evacuate based on the environmental factors as calculated in the target-driven sub-model. That means, when the environment changes, such as a falling wall or a closing path, the intelligent agents reselect new targets based on the environment situation at a moment. Thus, the model performance is not affected by the environment undergoing dynamic changes.


75
Figure 17. Comparing evacuation total time when the environment is dynamic vs. static.
----Dynamical environment ------Static environment
Figure 18. Comparing system throughput when the environment is dynamic vs. static.
The results, in general, show that the first case of the proposed model, the deterministic
case, performs better than the other two cases. However, the difference between the first and
second case results is insignificant when considering the agents’ travel time and their speed. In
addition, from my observations, it was found that, by applying A * algorithm, the model was able to simulate the case of movement in a blocked (or non-exit) area. The results show that in the last scenario, which is the most complex environment with more obstacles and less exists, the two cases of MLMS-ABM model (deterministic and non-deterministic) always overcome the Non-MLMS-ABM model under all experiments with more benefits of the deterministic over non-
deterministic case.


76
Application of MLMS-ABM Model in Last Floor of Al- Haram Al-Sharif in Makkah
To demonstrate the scalability of the proposed approach, here the model is examined for modeling crowd behavior and dynamics in a specific large-scale scenario [170], The novel multi-component agent-based modeling framework is applied to simulate the components of varying individual behaviors and phenomena of complex systems within the massive crowd that represents the pilgrims attending prayers in the Al- Haram Al-Sharif Mosque (Masjid Al-Haram) [171], The Masjid Al-Haram, in the City of Mecca in Saudi Arabia, was selected as the case study as it accommodates millions of pilgrims to perform their prayer ritual at a specific time and place. In this application of the model, the focus was on the inside area of the mosque, specifically the upper level, during evacuation. To the best of my knowledge, no research has been conducted to study the behavior of a crowd inside a mosque.
Pilgrims create crowd congestions that could lead to chaos, panic, and injuries. Pilgrims are unique in that they come from different countries, and the cultural and geographical diversity affects the management of the pilgrims as well as their behavior. As mentioned by Al-Kodmany [2], foreign pilgrims have little awareness of the physical infrastructure of the Masjid Al-Haram facility or the entrances and exits of this facility. Because of the unfamiliarity with the environment and the exhausting performance of certain activities pilgrims are not always fully aware of their exact location within the building. Krausz and Bauckhage [183] describe the crowd densities that create a pattern of movement as a “stop-and-go wave.” This pattern indicates dangerous overcrowding that could be difficult to manage. When this pattern appears, people in this wave move in all directions, and they may push each other, causing some to fall.
The huge crowd of up to 30,000 pilgrims in the Masjid Al-Haram area cannot easily be simulated. From the surveyed papers, several crowd simulation models are available for the


77
simulation of evacuation and movements of the crowd, but these models can only handle relatively small crowds and are not able to simulate the very large crowd (such as pilgrims) with accuracy and details. The proposed model can simulate, on a single personal computer, a crowd of tens of thousands inside the area of the upper level of the Masjid Al-Haram with considerable amount of details.
Results and Discussion
The crowd loading in this simulation experiments was acquired from The Center of
Research Excellence in Hajj and Umrah and the Custodian of the Two Holy Mosques Institute of
Hajj Research at Umm Al-Qura University in Makkah, Saudi Arabia, both of which regularly
collect and analyze data about the Two Holy Mosques in Makkah and Al-Madinah [180], The
population size of this experiment was 10,000 pedestrians. Figure 19 shows the variation of
density to each exit’s target floor field (IFF). o
50 100 150 200 250
Figure 19. The variation of density to each exit’s target floor field (TFF).


78
The first finding illustrates the model’s capability of improving the crowd flow pattern. Figure 20 shows that agents’ flow rate was higher in the proposed model than the traditional ABM application. That indicates the ability of the model to improve the overall crowd flow during evacuation. It was also found that the agents’ average speed during the simulation was higher in the proposed model. Figure 21 shows the estimation of the average speed of 10,000 agents during the simulation.
Figure 20. Cumulative flow of agents to evacuate.


79
3.5
E, T3 3
!/> 0) 00 2
2 1.5
ro "in *-> 1
c 01 00 in d
< 0

r^ma^i^rHrvma>LnrHr>*pna»ir)rH
r^cr>org^-inp^ooo*NroLnvDooo
HHNNNNNNfOMMPOfOM^
Agents
MLMS-ABM
Non-MLMS-ABM
Figure 21. Average speed of agents.
The second result is related to demonstrating the model’s efficiency in promoting the crowd’s overall travel time during evacuation. Specifically, it is observed that all agents in the environment have been evacuated in a shorter time, while it took the agents a longer time to evacuate in the traditional ABM model, as shown in Figure 22, which shows the total travel time for 200 agents in both cases. This result demonstrates the benefit of relying on an intelligent agent to improve the evacuation overall travel time and the efficiency of the models in accurately simulating the events during crowd evacuations. Significant improvement of crowd flows was observed during simulations compared to crowd flows observed during simulations using traditional applications of ABM. These observations could influence multiple aspects of how evacuations are planned such as the placement of exits in buildings, and the training of how to behave during an evacuation. Taken together, the results show that the proposed multi-leveled multi-staged agent-based model outperforms the traditional ABM approach in improving the crowd dynamics during evacuation in a high-density simulation logic.


80
The aim of the model in such cases is to help Hajj and Umrah crowd management authorities build successful schemas by predicting crowd behavior. The proposed ABM model is able to improve crowd management solutions by considering the diversity of pilgrims and their individual characteristics, and the results show the ability of the model to support the heterogeneity and high density observed among the massive numbers of pilgrims by using small time steps in order to consider different pedestrian speeds and reduced mobility of some of them, e.g., elderlies. The results of this model, showing the improved actions and movements of a massive number of pilgrims carrying out the evacuation movements in a case of dangerous events, includes new rules and higher accuracy and flexibility compared to the existing models. The model integrates a discrete-event actions model into the large crowd simulation, and the simulation of actions and movements of individual pilgrims gives us insight into the emergent behaviors of the crowd. The experimental results provide evidence that the hybrid, multi-layered approach can be successfully applied to efficiently simulate agent behaviors in intensive crowd
environments.


81
CHAPTER V
DECISION SUPPORT SYSTEM FOR SIMULATING AND MODELING
OF TRAFFIC DYNAMICS
Introduction
A significant amount of research has addressed ways of incorporating technology to help avoid vehicle collisions and reduce road accidents [172-176], It has become extremely important to develop effective transportation strategies that will not only enhance the quality of life of individuals who use public transportation but can also contribute to the safety of the general public [172, 175], While implementing such strategies can lead to the prevention of accidents, those strategies come with some negative consequences [172, 173], Therefore, it is important to understand how to produce the most effective ones [174, 175],
Traffic congestion and environmental pollution have been identified as two of the most common issues that are linked with everyday urban traffic [174], Traffic congestion takes place when the road system capacity is insufficient to handle the traffic flow and/or when drivers fail to communicate with each other collectively in real time. Current solutions brought in to improve traffic conditions often make life easier for a small percentage of the population while making life more difficult for others [173, 175], such as when considerable amounts of vehicular emissions contribute to air pollution in urban networks [176], The high frequency of starting and stopping at traffic signals and intersections contributes to a higher volume of fuel consumption during rush hours as well as uncongested times when the flow of vehicles is interrupted by cyclists and pedestrians. Therefore, waiting time is created in all traffic scenarios and this plays a crucial role in any flow analysis.


82
Road authorities in urban areas interested in reducing emissions need to be aware of evaluate the overall total time that people are spending on the road and the optimum speed at which the traffic should flow [174-176], A reduction in emissions occurs when the number of accelerations and decelerations decreases, and the emissions that take place in urban areas are heavily impacted by these two factors (accelerations and decelerations). Therefore, they both need to be reduced and evaluated [84, 174],
Traffic flow creates a dynamically complex system since it involves a nonlinear interaction of many independent vehicles with largely autonomous behavior. These interactions can lead to situations that produce different kinds of traffic problems. For example, traffic jams can occur when a group of vehicles are stuck behind one driving particularly slowly. A number of models have been developed and applied to simulate the process of vehicular dynamics causing traffic jams caused by slow-moving vehicles [85, 115, 123, 124], The results of these studies help researchers develop new ways to integrate and incorporate the increasing availability of vehicles [7-10], One particularly effective computational simulation method is a decentralized, multi-agent system (MAS), where each agent can communicate only with its immediate neighboring agents.
The essential contribution of this chapter is applying the developed distributed architectures to the distributed vehicle routing-problem. The MLMS-ABM framework provides a decentralized processing approach where the keys to distributed vehicle routing are the underlying interaction relationships of the vehicles themselves. The MAS contains communication constraints, where agents can communicate only with their immediate neighboring agents. The vehicles share information with the other vehicles within their neighborhood. Such communication between vehicles combines the effectiveness of the


83
macroscopic and microscopic modeling layers with the involved stages in the proposed hybrid model. As vehicles in the presented model interact and share data with one another, they choose their routes based on the selected routes of the other vehicles. By knowing the decisions of surrounding drivers, a driver will gain better situational awareness and make a more accurate decision, thereby reducing traffic congestion impact on alternative routes while improving the overall travel time. The enhanced driver awareness improves decision-making about the best alternative road to take, and thus ensuring fewer routing delays as a result of traffic congestion. As mentioned earlier, the primary objective here is to make sure that all the drivers are not taking the same alternative route.
This chapter discusses hybrid decentralized approaches in detail and explains the benefits of applying them to determine a viable solution to the traffic routing problem. The proposed technology will be analyzed in detail and evaluated. Different cases of the decentralized approach will be tested to study their ability to reduce overall congestion within the traffic network. Only then it will be possible to understand the differences that exist between the proposed models and examine the one that is capable of delivering the best possible results.
Also, the MLMS-ABM model will address collision detection and avoidance in vehicular traffic networks. To validate and evaluate the proposed model, both hypothetical and real-road data base simulations will be performed.
Intelligent Transportation Systems
Along with the development of technology, intelligent transportation systems (ITS) have received a lot of attention [172, 173, 178, 179], The sophistication of the technology behind intelligent transportation systems is ever improving. The advancements in processing capabilities, communication technology, and sensors now provide vehicles and drivers with the


84
opportunity to figure out the conditions that exist on the road [172, 173], As a result, there is a high possibility of increasing efficiency of the system. For example, drivers are given the opportunity to determine the best route available to reach their destination in minimum time. However, traffic congestions are extremely dynamic. For instance, even a small accident suffices to instantly create significant traffic congestion on the road. But if the vehicles are provided with the technology to gather relevant data and process them in real time, drivers will be able to immediately determine the congestion and look for alternative routes while still on the road.
The connectivity that exists between vehicles benefits the intelligent transportation systems [173, 178, 179], Acquisition of data can be considered as one of the principal requirements behind intelligent transportation systems. Data, when processed properly, provides the resource that is needed to make intelligent decisions. Imagine that an intelligent transportation system is assisting drivers in taking the best route. One aspect that could be considered is the “greedy-routing issue” that can be solved with the assistance of centralized architecture. In contrast to a decentralized system, where all the information is being gathered locally, the necessary data are gathered by sensors that are located on the road in the centralized architecture. Then, the data is processed centrally, and the resulting information is provided in a meaningful manner [172, 173, 178],
Decentralized Techniques
Among the methods that can be used to tackle the distributed vehicle routing-problem, the solutions based on distributed architecture have received a lot of attention [172, 180] because when a decentralized network is implemented, it is possible to achieve distinct advantages over a centralized one. For example, all the vehicles that are located in a specific neighborhood work as sensors on their own, and this eventually benefits a system of sensors and data-aggregators [180],


85
In addition, they work as independent traffic-management centers. Moreover, all the vehicles are provided with the technology to access data, which they need to refer to in order to make meaningful decisions. As a result, interfacing issues can be eliminated effectively. However, the process of making decisions can be quite challenging because the vehicles are provided with the responsibility of processing data as soon as it arrives in an asynchronous manner [178, 180],
The Decentralized Architectures and Multi-Agent Systems
In decentralized architectures and multi-agent systems, each vehicle is considered a processing unit of its own [180], The term “agent” is used to determine the intelligent actor who is interacting with the environment via an actuator or a sensor. Therefore, a multi-agent system is a product composed of multiple agents interacting via this network to communicate with one another. Using a multi-agent approach within a distributed architecture is viable; however, it must have a unique combination of actions in order to solve a problem. In other words, the specific solutions used for particular issues need to be understood. However, it is not possible to compute a general solution that keeps agents who are interacting with other agents away from performing a specific task [173, 180], This framework defines a method which can be used to perform the actions and account for the unplanned conditions. This unique method of communication is usually considered a vehicle-to-vehicle communication method [116, 172, 173], It has an ad hoc structure which ensures the direct communication among vehicles.
Traffic networks usually fit into a multi-agent paradigm. With the ABM method, it is possible to understand a set of rules which determine the behavior of a specific agent. This process is called “mapping” of all the sensory inputs that can achieve a task [172, 173, 178, 180],
Multi-agent systems use several different states. All states are designed to work in the sequence of sensing, planning, and acting [3,9, 130], The agent first needs to gather information


86
about the environment with the assistance of sensors, and the data collected by the sensors is used to create a model environment. Once the agent is familiar with the environment, it then develops an action plan that can be used to achieve a specific goal, which is made from multiple, smaller, sequential methods, that is used to complete the desired task [3, 130], When using the multi-agent approach, every vehicle acts as an agent. This way, the network is able to receive comprehensive information which is used to make a better decision. These agents are positioned to create a vehicular ad-hoc network (VANET) [130], VANETs are made from a cluster of agents who are continually moving. With the assistance of a distributed architecture method, modeling vehicles as agents to exhibit behaviors in a trend can be described in detail. However, a distributed architecture approach cannot differentiate among individual vehicles.
Inside the VANET, the agents are provided with the task of reacting according to changing conditions. To do that, they need to use behaviors that exhibit the right approach. However, behaviors in nature are usually quite reactive when the timing of the changes is unknown to agents. One of the biggest challenges that exists here is how to deal with the information in real time and process it inside the vehicle. Traditionally, an event-looping programming paradigm processes data that are being received by the observer [130], Using this system, the observer pattern is used with event-handling. As a result, the object maintains a list of dependents who are acting as observers. They are sent out with automatic notifications of the changes in status. It follows that the complexity of the system increases when it is covering larger geographical boundaries with additional agents.
In a decentralized network, data are captured from the vehicles that share information in the same local range. The exchanged data among agents include but are not limited to: Current position, route, velocity, and type [172, 178, 180], The data are locally processed by the vehicles.


Full Text

PAGE 1

! ! ! "#$%&'!()*+& , *-.-*!/0-1+ , $/2-'!'-3&2&41!2)554%+!2#2+-(!64%! (4'-*&10!/1'!2&()*/+&41!46!3%47'!/1'!+%/66&3!'#1/(&32 ! 89 ! %/0"'/!/*:)%/2"& ! $;2; , ?@AB! )CDEFAGDH9LABNL!'FCEFA H9!L M!HQF!0ABN@BHF!2RQLL>!LM!HQF ! )CDEFAGDH9!LM!3L>LABNL!DC!SBAHDB>!M@>MD>>=FCH ! LM!HQF!AF?@DAF=FCHG!MLA!HQF!NFTAFF!LM ! 'LRHLA!LM!5QD>LGLSQ9! ! 3L=S@HFA!2RDFCRF!BCN!&CMLA=BHDLC!29GHF=G!5ALTAB=! ! IJO U !

PAGE 2

DD ! ! ! ! ! ! +QDG!HQFGDG!MLA!HQF!'LRHLA!LM!5QD>LG LSQ9!NFTAFF!89 ! %BTQNB!/>?@ ABGQD ! QBG!8FFC!BSSALEFN!MLA!HQF ! 3L=S@HFA!2RDFCRF!BCN!&CMLA=BHDLC!29GHF=G!5ALTAB=! ! 8 9 ! ! ! ! 0DHB!/>BTQ8BCNH=BC!(BCCDCL ! /GQDG!V@=FA!$DGWBG! ! *DBCT!"F! ! ! ! 'BHFX ! 1LEF=8FA!OY
PAGE 3

DDD ! ! />?@ABGQDHD , *FEF>!/TFCH , $BGFN!'FRDGDLC!2@SSLAH!29GHF=!MLA!(LNF>DCT! B CN!2D=@>BHDLC!LM! 3ALWN!BCN!+ABMMDR!'9CB=DRG ! +QFGDG!NDAFRHFN!89!5ALMFGGLA!+L=!/>H=BC ! !"#$%!&$ ! /TFCH , 8BGFN!=LNF>!Z/$([!GD =@>BHDLC!DG!B!8LHHL= \ @S!BSSALBRQ!HQBH!RBC!NFGRAD8F! HQF! SQFCL=FCB!TFCFABHFN!MAL=!BRHDLCG!BCN!DCHFABRHDLCG!WDHQDC!B!=@>HDBTFCH!G9GHF=;!/C!/$(!DG!BC! D=SALEF=FCH!LEFA!=LNF>!GD=@>BHDLCG!WQDRQ!LC>9!NFGRAD8F!HQF!T>L8B>!8FQBEDLA!LM!B!G9GHF=;! +QFAFMLAFLT9!HL!BCB>9]F!F=FATFCH!SQFCL=FCB! DC!GLRDB>!GRDFCRFG!BCN! RL=S>F^!BNBSHDEF!G9GHF=G!G@RQ!BG!SFNFGHADBC!RALWNG!BCN!EFQDR@>BA!HABMMDR;!&C!HQDG! NDGGFAHBHDLC DCT!MAB=FWLA_!NFGDTCFN!HL!B@HL=BHF!NFRDGDLC , =B_DCT!SALRFGGFG ! LM! FEBR@BHDLC!N@ADCT!BC!F=FATFCR9 ! BCN! N@ADCT ! HABMM DR!RLCTFGHDLC!DG!SALSLGFN;!+QF!=LNF>!SALEDNFG ! G9GHF= ! DCNDEDN@B>G ! WDHQ!AFB> , HD=F!B>HFACBHDEF!AL@HFGD]FN!=@>HD , BTFCH! =LNF>!NDGHAD8@HDLC!WDHQD C!BC!FCHDAF!G9GHF=!HABEF>! HD=F!LM!B>>!HQF! DCNDEDN@B>G!HL!AFBRQ!HQFDA!TLB>G ; ! +QF!SAFGFCHFN!WLA_!F^S>LAFG!B! NFRFCHAB>D]FN!/$(!HFRQCD?@F!LC!BC!B@HLCL=L@G!=DRALTADN!HQBH!DG!AFSAFGFCHFN!HQAL@TQ!RF>>@>BA! B@HL=BHB!Z3/[;!+QF!SALSLGFN!=LNF> ! WBG!BSS>DFN!HL!QDTQ , NFCGDH9 ! RALWN!FEFCHGBCF!R>LG@AFG9]FN;!+QF!F^SFAD=FCHB>!AFG@>HG!RLCMDA=!HQF!FMMDRDFCR9! LM!HQF!SALSLGFN!=LNF>!DC!CLH!LC>9!BRR@ABHF>9!GD=@>BHDCT!HQF! NADEFA G`SFNFGHADBC ! 8FQBEDLAG!BCN! D=SALEDCT!M>LWG ! LM!RALWN!BCN!EFQDR@>BA!HABMMDR ! N@ADCT!RLCTFGHDLC!8@H!B>GL!89!G@TTFGHDCT!RQBCTFG! HL! RALWN` HABMMDR!N9CB=DRG!N@ADCT!HQF!GD=@>BHDLCGFG!BCN!QDTQ , NFCGDH9! BAFBG!BCN!HQFC!GF>FRHDCT!HQF!8FGH ! B>HFACBHDEF!AL@HFG;!+QF!GD=@>BHDLC!AFG@>HG!EB>DNBHF!HQF!B8D>DH9!LM!

PAGE 4

DE ! ! HQF!SALSLGF N!=LNF>!BCN!HQF!DCR>@NFN!NFRDGDLC , =B_DCT!G@8 , =LNF>G!HL!8LHQ!SAFNDRH!BCN!D=SALEF! HQF!8FQBEDLAG!BCN!DCHFCNFN!BRHDLCG!LM!HQF!BTFCHG;! ! +QF!MLA=!BCN!RLCHFCH!LM!HQDG!B8GHABRH!BAF!BSSA LEFN;!&!AFRL==FCN!DHG!S@8>DRBHDLC;! ! /SSALEFNX!+L=!/>H=BC ! !

PAGE 5

E ! ! '(')&!$)*+ , This work is dedicated to my life's partner, Dr. Mohammed Alqurashi, without whom my achievements would be limited, my horizons bounded, my vision vague, and the dissertation that follow s would not be possible. !

PAGE 6

ED ! ! !&-+*./('0(1(+$# , 6DAGH!BCN!MLAF=LGH>!=9!GDCRFAF!TABHDH@NF!HL!=9!TLN!Z/>>BQ[!MLA!FCB8>DCT!BCN!QF>SDCT!=F!HL!G@RRFGGM@>>9!RL=S>FHF!=9!NLRHLABHF;! ! +QDG!NLRHLABHF!QBG!8FFC!B!AFB>>9!>LCT!aL@ACF9 ! WQDRQ!=BNF!=F!TALW!@S!BG!B!SFAGLC!BCN!BG! B ! AFGFBARQFA;!/H!HQF!FCN!LM!=9!a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aL@ACF9>! B>WB9G ! AF=F=8FA!WQFC!GQF!LCRF!HL>N!=F>9!TABHFM@>!BCN!DCNF8HFN!HL!=9!(LHQFA>FRH@B>>9!GHD=@>BHDCT!FCEDALC=FCHWB9G!FCRL@ABTDCT!=F!HL!S@AG@F!=9! SBGGDLC FGG!>LEF!BCN!FCRL@ABTF=FCHF!&!WBG!S@AG@DCT! =9!GH@NDFG!MBA!BWB9!MAL=!HQF=;!&!QBEF!CFEFA!MF>H!HQF!CFFN!HL!BG_!MLA!HQFDA!QF>S!8FRB@GF!HQF9!QBEF! B>WB9G!8FFC!HQFAF!8FMLAF!&!FEFC!QBN!HL!BG_; ! +QF!G@RRFGGM@>!RL=S>FHDLC!LM!=9!NDGGFAHBHD LC!WL@>N!

PAGE 7

EDD ! ! SAL8B8>9!CLH!QBEF ! 8FFC!SLGGD8>F!WD HQL@H!HQFDA! G@SSLAH; ! +QFAF!BAF!CL!SALSFA!WLANG!HL!RLCEF9!=9! TABHFM@>CFGG! MLA!HQFDA! SAB9FAG ! MLA!=F ;! (9!NFFSFGH!BSSAFRDBHDLC!BCN!GDCRFAF!TABHDH@NF!TL!HL!HQF=; ! ! &!WL@>N!>D_F!HL!F^SAFGG!=9!GDCRFAFGH!TABHDH@NF!HL!=9!NF BA!8ALHQFAG DCT!GDGHFA!G@SSLAH!HQAL@TQL@H!=9!BRBNF=DR!RBAFFA;!+QF9! QBEF!8FFC!B>WB9G!G@SSLAHDEF!FGSFRDB>>9!N@ADCT!HQF!HL@TQ!NB9G!LM!HQDG!a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aL@ACF9;!"F!B>WB9G! GHBCNG!8FQDCN!=F!BCN!QDG!WLANG!B>WB9G!8ADTQHFC!=9!SBHQ;!+QFAF!BAF!CL!SALSFA!WLANG!HL!RLCEF9! =9!QFBAHMF>H!BSSAFRDBHDLC!BCN!TABHFM @>CFGG!MLA!QD=;!+QDG!NDGGFAHBHDLC ! DG!BG!=@RQ!QDG!BRQDFEF=FCH! BG!DH!DG!=DCF; ! !

PAGE 8

EDDD ! ! $!"/(,*2,&*+$(+$# , 3"/5+-%! ! &; ! &1+%4')3+&41!fff;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!O ! (LHDEBHDLC ! ;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!K ! %FGFBARQ! 3LCHAD8@HDLCG ! f;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!g ! 2HA@RH@AF!LM!HQF!'DGGFAHBHDLC ! ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!OJ! ! &&; ! $/3V0%4)1'!/1'!%-*/+-'!74%V! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!O O ! !!!!!! (LNF>DCT!LM!3L=S>F^!29GHF=G! ;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;!O O ! /TFCH , 8BGFN!(LNF>DCT!BCN!2D=@>BHDLC!/SSALBRQ ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!O I ! /TFCH , 8BGFN!=LNF>!NFEF>LS=FCH! ;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;! Oh ! /SS>DRBHDLCG!LM!BTFCH , 8BGFN!=LNF>DCT ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! OU ! 3F>>@>BA!/@HL=BHB ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;!I O ! 3ALWN!(LNF>DCT ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! I Y ! 2RB>FG!LM!3ALWN!(LNF>DCT ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!I K ! *FEF>G!LM!3ALWN!(LNF>DCT ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!I g ! +ABMMDR!(LNF>DCT! ;;;;;;;;;;; ;;;;; ;; ;;;;;;;;;;;;; ;; ;;;;;;;;;;;;; ;; ;;;;;;;;;;;; ; ;;;;;;;;;;;; ;;;;;; ;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;; , Ig ! &&&; ! (4'-*!'-23%&5 +&41 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!PO! ! -CEDALC=FCH!3LCMDT@ABHDLC!DC!HQF!(LNF> ;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!PP! ! / TFCH!3LCMDT@ABHDLC!DC!HQF!(LNF> ! ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!Pi ! +BATFH , 'ADEFC!'FRDGDLC , (B_DCT!(LNF> ! ;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!PU ! +ABCGDHDLC!'FRDGDLC , (B_DCT!(LNF> ! ;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!YJ ! /TFCH!2HBH@G!)STABNDCT!(LNF>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!YP ! -EB>@BHDLC!LM!+A@GHWLAHQDCFGG!(LNF>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!Y g !

PAGE 9

D^ ! ! (LNF>!.B>DNBHDLC! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!i O ! !!!!!!! &=S>F=FCHBHDLC!2FH , @S! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!iI ! !!!!!!! +QF!4''!5ALHLRL>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!i P ! &.; ! '-3&2&41!2)554%+!2#2+-(!64%!2& ()*/+&10!/1'!(4'-*&10!46!3%47'! '#1/(&32!/1'!-./3)/+&4 1! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!iY ! &CHALN@RHDLC!;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;!iY ! (LNF>!'FGRADSHDLC! ;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!ig ! !!!!!!!! -CEDALC=FCH!3LCMDT@ABHDLC!DC!HQF!(LNF>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;!i h ! !!!!! ! -^SFAD=FCHBHDLC!BCN!/CB>9GDG! ;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!ih ! %FG@>HG!BCN!'DGR@GGDLC! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!K P ! /SS>DRBHDLC!LM!(*(2 , /$(!(LNF>!DC!>BGH!6>LLA!LM!/> , ! "BAB=!/> , 2QBADM!DC!(B__BQ!;;!g K ! ! !!!!!!!!!!!!!! %FG@>HG!BCN!'DGR@GGDLC! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!g g ! .; ! '-3&2&41!2)554%+!2#2+-(!64%!2&()*/+&10!/1'!(4'-*&10!46! +%/66&3!'#1/(&32! ;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!hO ! &CHALN@RHDLC ;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!hO ! &CHF>>DTFCH!+ABCGSLAHBHDLC!29GHF=G ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!hP ! 'FRFCHAB>D]FN! +FRQCD?@FG ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!hY ! +QF!'FRFCHAB>D]FN!/ARQDHFRH@AFG!BCN!(@>HD , /TFCH!29GHF=G ;;;;;;;;;;; ;; ;;;;;;;;;; ;;;;;;;;;!hi ! 3FCHAB>D]FN!`!'FRFCHAB>D]FN!+FRQCD?@FG ;;;;;;;;;;; ;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;!hg ! %F>BHFN!7LA_ ! ;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;; ! hg ! (LNF>!'FGRADSHDLC ! ;;;;;;;;;;;;;;;;;;;; ;;;;;;;;; ;; ;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! hU ! !!!!!!! /TFCH!3LCMDT@ABHDLC!DC!HQF!(LNF>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!UJ ! -CE DALC=FCH!3LCMDT@ABHDLC!DC!HQF!(LNF> ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!U O !

PAGE 10

^ ! ! /TFCH!2HBH@G!)STABNDCT!(LNF>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!UI ! -^SFAD=FCHBHDLC!BCN!/C B>9GDG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;; ; ;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!U i ! %FG@>HG!BCN!'DGR@GGDLC! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;; ;;;;;;;;;! UU ! .&; ! 3413*)2&41!/1'! 6)+)%-!74%V ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!OO I ! %-6-%-13-2! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!OI O ! /55-1'&j! ! /;!2D=@>BHDCT!BCN!(LN F>DCT!LM! 3ALWN ! '9CB=DRG!59HQLC!3LNF!;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;!OP K ! ! $;!2D=@>BHDCT!BCN!(LNF>DCT!LM!+ABMMDR!'9CB=DRG!59HQLC!3LNF ! ;;;;;;;;;;;;;;;;;;; ;; ;;;;;;;;;;;;;;;;;;;;;;;;;;! Oi I ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! , ,

PAGE 11

^D ! ! /)#$,*2, $!"/(# ! +/$*-! ! O;! /TFCHG!=LEF=FCH ! GSFFN ! ;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;; ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;!Ph ! ! I; ! +LHB>!AFAL@HF!HD=F!EG;!=FHQLN!WDHQ!NDMMFAFCH!BAHFADB>!>LBN!MLA!HQF!Q9SLHQFHDRB>!ALBN ! CFHWLA_ ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;; ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ! OJ I ! P;!+LHB>!AFAL@HF!HD=F! EG;!=FHQLN!WDHQ!NDMMFAFCH!BAHFADB>!>LBN!MLA!HQF!AFB> , WLA>N!ALBN! CFHWLA _ ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;; ; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!OJ g ! Y;!3L=SBADCT!HQF!HLHB>!HABEF>!HD=F!MLA!HQF!Q 9SLHQFHDRB>!ALBN!CFHWLA_!BCN!HQF!& , Ii!ALBN! CFHWLA_; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ; ;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!OO J ! i;!3L=SBADCT!M>LW!ABHFG!MLA!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_!BCN! HQF!& , Ii!ALBN!CFHWLA_!f ;; ff!OO O ! ! K;!3L=SBADCT!HQF!EFQDR>FGc!BEFABTF!GSFFN!MLA!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_!BCN!HQF!& , Ii!ALBN! CFHWLA_; ;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;; ;;;;;;;;;;;;; ! OO O ! ! ! ! , , , , , , , , , , , , , , , , , ,

PAGE 12

^DD ! ! /)#$,*2,2)03%(# , 6&0)%-! ! O; ! (@>HD , >FEF>!=@>HD , GHBTF!BTFCH , 8BGFN!=LNF>!Z(*(2 , /$([!G9GHF=!LEFAEDFW! ;;;;; ;;;;;;;;;;;;;;;;;!P I ! ! I; ! +QF!HWL!>B9FAG!LM!(*(2 , /$(!=LNF>! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!PP ! P; ! /!MDCDHF!GHBHF!=BRQDCF!Z62([!AFSAFGFCHBHDLC!RLAAFGSLCNDCT!HL!GHBHF!HABCGDHDLC!LM!HQF!BTFCHcG! 8FQBEDLA ! ;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!Pg ! Y; ! 'FRDGDLC!HAFF!WDHQ! ! ! CFDTQ8LA!BTFCHG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;!Yh ! i; ! +QF!LEF AB>>!=LNF>DCT!MAB=FWLA_! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! iJ ! K; ! +QF!CF^H!HD=F , GHB=S!HBATFH!RF>>G! ;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;!ih ! g; ! 3LCMDT @AFN!GD=@>BHDLC!FCEDALC=FCHG ! ;;;;;; ;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;! KJ ! h; ! 2RAFFCGQLH!LM!HQF!GD=@>BHDLC!FCEDALC=FCH ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! KJ ! U; ! 2RFCBADLG!HBAT FHGc!M>LLA!MDF>N!Z "## [!;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! K I ! OJ; ! +LHB>!HABEF>!HD=F!HL!FEBR@BHF! ;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;!K i ! OO; ! +LHB>!H ABEF>!HD=F!HL!FEBR@BHF!HQF!GB=F!BTFCH!N@ADCT!HQF!HQAFF!RBGFG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;!K g ! OI; ! 3@=@>BHDEF!M>LW!LM!BTFCHG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;!K U ! OP; ! /TFCHGc!BEFABTF!GSFF N! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;!gJ ! OY; ! 3QBCTFG!DC!SLS@>BHDLC!GD]F!LEFA!HD=F!DC!NDMMF AFCH!FEBR@BHDLC!GRFCBADLG ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;!g I ! Oi; ! +FGHDCT!N9CB=DRG!LM!@STABNDCT!=LNF >!HQAL@TQ!FEBR@BHDLC!HLHB>!HD=F! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! g P ! OK; ! +FGHDCT!N9CB=DRG!LM!@STABNDCT!=LNF>!HQAL@TQ!SFNFGHADBCc!BEFABTF!GSFFN ! ;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;! g Y ! Og; ! 3L=SBADCT , FEBR@BHDLC!HLHB>!HD=F!WQFC!HQF!FCEDALC=FCH!DG!N9CB=DR!EG;!GHBHDR!ff;;ff f;!g i ! Oh; ! 3L=SBADCT , G9GHF=!HQAL@TQS@H!WQFC!HQF!FCEDALC=FCH!DG!N9CB=DR!EG;!GHBHDR! ;;;;;;;;;;;;;;;;;;;;;;;;;; ! g i ! OU; ! +QF!EBADBHDLC!LM!NFCGDH9!HL!FBRQ!F^DHcG!HBATFH!M>LLA ! MDF>N!Z "## [ ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! gg ! IJ; ! 3@=@>BHDEF!M>LW!LM!BTFCHG!HL!FEBR @BHF! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! gh ! IO; ! /EFABTF!GSFFN!LM!BTFCHG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;!g U !

PAGE 13

^DDD ! ! II; ! +LHB>!HABEF>!HD=F!HL!FEBR@BHF ! ;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;! hJ ! IP; ! +QF!CF^H!HD=F , GHB=S!HBATFH!RF>>G!MLA!B!EFQDR>F! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;!UI ! IY; ! +ABMMDR!N9CB=DR!=LNF>DCT!>B9 FAG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;!U Y ! Ii; ! $BGDR!Q9SLHQFHDRB>!ALBN!CFHWLA_! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;!U g ! IK; ! +QF!GFT=FCH!LM!HQF!AFB>!ALB N!CFHWLA_!DC!'FCEFA!3L@CH9! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ! U h ! Ig; ! 2RAFFCGQLH!LM!HQF!GD=@>BHDLC!FCEDALC=FCH!LM!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_ ! ;;;;;;;;;;;;;;;;;;;;;;;; ! OJ J ! Ih; ! +LHB>!HABEF>!HD=F!MLA!AFAL@HDCT!BAL@CN ! BRRDNFCH!WDHQ!NDMMFAFCH!BAH FADB>!>LBNG! ;;;;;;;;;;;;;;;;;;;;;;;;;! OJ O ! IU; ! +LHB>!HABEF>!HD=F!HL!AFAL@HF!BAL@CN! BRRDNFCH! MLA!HQF!GB=F!EFQDR>F!N@ADCT!EBADFH9!LM!BAHFADB>!>LBNG! ZQ9SLHQFHDRB>!ALBN!CFHWLA_[! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;; ;;;;;;;;;;;; ;;;;;;;;;;;!OJ I ! PJ; ! +ABMMDR!M>LW!N@ADCT!GD=@>BHDLC!HD=F!ZQ9SLHQFHDRB>!CFHWLA_[! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ! OJ P ! PO; ! +LHB>!HABEF>!HD=F!MLA!AFAL@HDCT!BAL@CN!BRRDNFCH!N@ADCT!NDMMFAFCH!HABMMDR!EL>@=FG!WDHQ!NDMMFAFCH! BAH FADB>!>LBNG!;; ;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;!OJ Y ! PI; ! +ABMMDR!HQAL@TQS@H!N@ADCT!GD=@>BHDLC!WDHQ!NDMMFAFCH!BAHFADB>!>LBNG! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;! OJ i ! PP; ! /EFABTF!EFQDR>F!GSFFNG!WDHQ!NDMMFA FCH!BAHFADB>!>LBNG!ZQ9SLHQFHDRB>!ALBN!CFHWLA_[ ! ff;;;f;!OJ K ! PY; ! +LHB>!HABEF>!HD=F!HQAL@TQ!HQF!& , Ii!MAFFWB9!DC!NDMMFAFCH!=FHQLNG!WDHQ!NDMMFAFCH!HABMMDR! >LBNGff ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;; ;;;;;;;;;;;;;;; ! OJ g ! Pi; ! +LHB>!HABEF>!HD=F!HL!AFAL@HF!BAL@CN!DCRDNFCH!MLA!HQF!GB=F!EFQDR>F!N@ADCT!EBADFH9!LM!BAHFADB>!>LBNG! ZAFB> , WLA>N!CFHWLA_[! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;;;;;;; ;;;;;;;;;;;;;;;;;;;;;;;;;; ;!OJ h ! PK; ! +ABMMDR!M>LW!N@ADCT!GD=@>BHDLC!HD=F!ZAFB> , WLA>N!CFHWLA_[ ! ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ! O JU ! Pg; ! .FQDR>FcG!BEFABTF!GSFFN!WDHQ!NDMMFAFCH!BAHFADB>!>LBNG!ZAFB> , WLA>N!CFHWLA_[! ;;;;;;;;;;;;;;;;;;;;;;;;;; ! OO J ! , , ,

PAGE 14

^DE ! ! /)#$,*2,43"/)&!$)*+# , • ! %;!/>? @ABGQDH=BC< ! b"DFABARQDRB>!/TFCH , $BGFN!(LNF>DCT!MLA!&=SALEFN!+ABMMDR! %L@HDCT;!U< ! /0123 4567 ?@ABGQDH=BC< ! b (@>HD , *FEF>!(@>HD , 2HBTF!/TFCH , $BGFN!2D=@>BHDLC!(LNF>! LM! 3ALWN!'9CB=DRG!DC!)SSFA!6>LLA!LM!/> , ! "BAB=!/> , 2QBADM ! ( ! ?@=> * +,'(!='<',*#:9AB*<:9*CDEE.*FB9D>*D!)*GD)'!D>*H'-'=*I(-(D9,> < ! SS;!OiU , OKg?@ABGQDH=BC< ! b(@>HD , >FEF>!=@>HD , GHBTF!BTFCH , 8BGFN!NFRDGDLC!G@SSLAH! G9GHF=!MLA ! GD=@>BHDLC!LM!RALWN!N9CB=DRG(*059)*J!=(9!D=':!D&* K:!<(9(!,(*:!*L!;'!((9'!;*:<*K:B%&(M*K:B%A=(9*+N-=(B-*/JKLKK+*01?O2 ?@ABGQDH=BC< ! b(@>HD , R>BGG!BTFCH , 8BGFN!=LNF>!LM!RALWN!N9CB=DRG(*01?6*J!=(9!D=':!D&*K:!<(9(!,(*: !*K:B%A=D=':!D&*+,'(!,(*D!)* K:B%A=D=':!D&*J!=(&&';(!,(. ! SS;!OhJO , OhJIG@>HBBC?@ABGQDH=BC< ! b/TFCH , 8BGFN!=LNF>G!SAFNDRHDCT! RL>>FRHDEF!8FQBEDLAG( * 01?6*J!=(9!D=':!D&*K:!<(9(!,(*:!* K:B%A=D=':!D&*+, '(!,(*D!)*K:B%A=D=':!D&*J!=(&&';(!,(. ! SS;!IUg , PJI
PAGE 15

O ! ! &5!4$(%,) , )+$%*'3&$)*+ , (LNF>DCT!BCN!GD=@>BHDLC!BAF!=FBCG!MLA!NFEF>LSDCT!B!NFFS!@CNFAGHBCNDCT!LM!8LHQ!RL=S>F^! G9GHF=G!BCN!RL=S>F^!BNBSHDEF!G9GHF=G!8FQBEDLAG;! 3L=S@HBHDLCB>!GD=@>BHDLCG!QBEF!>LCT!8FFC! BRR@ABHF!SAFNDRHLAG!LM!RL=S>F^!GLRDB>!G9GHF=G ; ! +QF9 ! BAF!CLW!GFFC!BG!SLWFAM@>!HLL>G!DC!GH@NDFG!LM! HQLGF!G9GHF=Gc!N9CB=DRG!kOBA>9!FMMFRHDEF!RL=S@HBHDLCB>!GD=@>BHDLC!=FHQLN!DG! BTFCH , 8BGFN!=LNF>DCT ! Z/$([ ! k P , K l ; ! /$(! RLCGDNFAG!HQF!RL=S>F^!G9GHF =!BG!B!NFRFCHAB>D]FNHD , BTFCH!G9GHF=!Z(/2[!k P , O O l9!WDHQ!DHG!D==FNDBHF ! CFDTQ8LADCT!BTFCHG;!+QF!/$(!BSSALBRQ!DG!B!MLA=!LM!LSHD=D]BHDLC!LM!DCNDEDN@B>!GL>@HDLCGDFG!HL!G9GHF=G!LM!DCHFABRHDCT!BTFCHG;!+QF!/$(!DG!@GFN!HL!=LNF>! BCN!G D=@>BHF!RL=S>F^!G9GHF=G!ABCTDCT!BRALGG!EBADL@G!RLCHF^HG@NDCT!8DL>LTDRB>!BCN!GLRDB>! G9GHF=G!kgl; ! $FRB@GF!LM!HQF!F=FATFCH!SQFCL=FCB!LM!RL=S>F^!G9GHF=G!RL=SLCFCHG; ! +QF!BTFCHG!DC!HQF!NFRFCHAB>D]FN!G9GHF=!QBEF!CL! NDAFRH!DCMLA=BHDLC!B8L@H!HQFDA!T>L8B>!SLGDHDLC ; ! "LWFEFA< ! HQF9 ! QBEF!DCMLA=BHDLC!B8L@H!HQFDA! CFBA89! CFDTQ8LAG!BCN!HQFDA!FCEDALC=FCH!>LRB>>9!kULRB>!_CLW>FNTF!HL! RL>>FRHDEF>9!RLCGHA@RH!B!RLLANDCBHF!G9GHF=;!&C!/$(F!G9GHF=G!RL=SLCFCHG!BCN!HQFDA! 8FQBEDLAG ; ! />GL< ! HQFDA!TFCFAB>D]FN!CBH@AF!DG!B8>F!HL!RBSH@AF!RL=S>F^!N9CB=DRG!BCN!GHA@RH@AFG! kOJl;!&H!RBC!8F!L8GFAEFN!DC!HQF!>DHFABH@AF!HQBH!8LHQ!/ $(!BCN!RL=S>F^!CFHWLA_G!BAF!8BGFN!LC! HQF! RL=S>F^DH9 ! HQFLA9;!+QF!/$(!BSSALBRQ!QBG!8FFC!G@RRFGGM@>>9!BSS>DFN!HL!B!WDNF!ABCTF!LM! GRFCBADLG!DCR>@NDCT!=D>DHBA9!HABDCDCTNDCT!FEBR@BHDLC!BCN!BCB>9GDG!LM!NDTDHB>!TB=FG!kOP
PAGE 16

I ! ! +QF!D=S>F=FCHBHDLC!LM!BTFCH , 8BG FN!MAB=FWLA_G!MLA!HQF!BCB>9GDG!LM!LHQFA!RL=S>F^!GLR DB>!G9GHF=G@NDCT!RALWN!N9CB=DRG , HF=SLAB>!SALRFGGFG>9!AF?@DAF!RL=S>F^!=LNF>G;!+WL!HFRQCL>LTDFG! @GFN!HL! RLCGHA@RH!HQFGF!=LNF>G!BAF!/$(!BCN!RF>>@>BA! B@HL=BHB!Z3/[!kOi , I J l ; ! BRQ!QBG!HQF!B8D>DH9! HL!F^S>BDC!HQF!GHBH@G!RQBCTFG!HQBH!HB_F!S>BRF!WDHQDC!HQF!GSBHDB>!RF>>G!GHFS , 89 , GHFS;!+QFGF!=FHQLNG! BAF!RBSB8>F!LM!AFM>FRHDCT ! HQF!F=FATFCH!BCN!RL=S>F^!RQBABRHFADGHDRG!BG GLRDBHFN!WDHQ!HQF!RL=S>F^! SQFCL=FCLC!kIJl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

PAGE 17

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cG!B8D>DH9!HL!NFADEF!HQF!@CNFA>9DCT!NFRDGDLC!=LNF>G!MLA!=@>HD , BTFCH!G9 GHF=G ! DG! NF=LCGHABHF N ; ! +QF! NFEF>LSFN! EFAGBHD>F!BTFCH , 8BGFN!MAB=FWLA_!FCRL=SBGGFG!M@CNB=FCHB>!SADCRDS>FG!LM! =LNF>DCT!BG!HQF9!BAF!RL==LC>9!BSS>DFN!HL!=@>HD , BTFCH!G9GHF=G!N9CB=DRG ;!+L!HQDG!BTFCH , 8BGFN! MAB=FWLA_F!BSSALBRQ! WBG! DCHALN@RF N ! MLA!GD=@> BHDCT!Q@=BC!SFARFSHDLC!BCN! NFRDGDLC , =B_DCT!DC!NBCTFAL@G!GRFCBADLG;!+QF!MAB=FWLA_!MLR@GFG!LC!HWL!GLRDB>!GRDFCRF!GRFCBADLGX! FEBR@BHDLC!GRFCBADLG ! k IOBHDLC!G RFCBADLG ! k IP l ;!+QF!TLB>!LM!HQDG!WLA_!DG!HL! RAFBHF!B!=LNF>!HL!GD=@>BHF!EBA9DCT!DC NDEDN@B>!8FQBEDLAG!WDHQDC!HQFGF!HWL!GRFCBADLG!DC!WQDRQ!

PAGE 18

Y ! ! BTFCHG!DCHFABRH!WDHQ!BC!@CMB=D>DBA!LM! LSHD=D]DCT!HQFDA!>LCT , HFA=!SFAML A=BCRF;!+QF!N9CB=DR!NFRDGDLC , =B_DCT!=LNF>DCT!DG!LATBCD]FN! DCHL!HQAFF!>FEF>GX! ZO[ ! GHABHFTDR!BCN! ZP[! LSFABHDLCB>!kI Y , Ihl;!+QF!MLA=@>BHDLC!LM!B!S>BC! BCN!DHG!MDCB>!L8aFRHDEF!DG!NABWC!BH!HQF!GHABHFTDR!>FEF>;!/H!HQDG!>FEF>!RDAR@=GHBCRFG!kIil;!/H!HQF!HBRHDRB>!>FEF>>!BRHDEDHDFG ! BAF! RL=S@HF N ! BCN!SFAMLA= FN ! HL!MBRD>DHBHF!HQF!MLA=@>BHFN!S>BC!kIgl!BCN!BNNAFGG!GQLAH , HFA=!NFRDGDLCG!>D_F!BELDNDCT!L8GHBR>FG!LA! RQBCTDCT!S>BCG!8BGFN!LC!CFW!DCMLA=BHDLC;!/NNDHDLCB>!DC MLA=BHDLC!B8L@H!HQF!=@>HD , BTFCH!G9GHF=! G@RQ!BG!HQF!M>LW!LM!BTFCHG!DG!BEBD>B8>F!B H!HQDG!>FEF>!kIKl;!+QF!LSFABHDLCB>!>FEF>!BNNAFGGFG!HQF! SQ9GDRB>!BRHDLCG!BCN!BRHDEDHDFG!NFEF>LSFN!BH!HQF!HBRHDRB>!>FEF>!kIhl;! +QF!LSFABHDLCB>!>FEF>! AFSAFGFCHG!HQF!BTFCHGc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bDCHF>>DTFCHe! >FEF>!BCN!FCB8>DCT!HQF=!HL!SFAMLA=! GL=F!GLAH!LM!T@DNBCRF!8FQBEDLAFN!DC! 3QBSHFA! &&& ;! $FGDNFG!BELDNDCT!RL>>D GDLCG!WDHQ! CFDTQ8LADCT! BTFCHG@NFG!B!=LNF>!LM!BELDNDCT!QDTQ!NFCGDH9!BAFBG!DC!LANFA!HL! AFN@RF!HQF!LEFAB>>!HABEF>!HD=F; ! 3 L =S>F^!BCN!N9CB=DR!=@>HD , BTFCH!G9GHF= ! WBG! =LNF> FN ! BCN!GD=@>BHF N ! BH!8LHQ! =DRALGRLSDR!BCN!=BRALGRLSDR!>FEF>GB9FA!

PAGE 19

i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`CFHWLA_G;!+QFGF!CFHWLA_G!DCEL >EF!HLSL>LT9!RQBCTFG!BCN!LHQFA!F^HFACB>!GHD=@>D! G@RQ!BG!MDAFGHDCT!MAL=!SBCDR >9!WDHQ!HABMMDR!LA!SFLS>F [ ;! + QF!SALSLGFN!=LNF>!QBG!HQF!B8D>DH9!HL!SAFNDRH!HQF!RQBCTF!LM! BTFCHGc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
PAGE 20

K ! ! =LAF!RL=S>F^!GFHHDCTG!LM!8@D>NDCT!DCHFADLAG!FCEDALC=FCHB>!L8GHBR>FG>!QF>S!EB>DNBHF!HQF!SALSLGFN!=LNF>!BCN!HFGH!DHG!B8D>DH9!HL! BNNAFGG!RL=S>F^!FEBR@BHDLC!RBGFG;!&C!LANFA!HL!GQLW!HQF!SLH FCHDB>!LM!HQF!SALSLGFN!=LNF>!GRFCBADL!WD>>!8F!GD=@>BHFN!WDHQ!DCRL=DCT!M>LW!LM!SFLS>F;!/C! D=SL AHBCH!MFBH@AF!LM!HQF!GRFCBADL!WD>>!8F!HQF!BG9==FHADRB>!RLCMDT@ABHDLC!LM!HQF!FCEDALC=FCH; ! &C! BNNDHDLC!HL!GD=@>BHDCT!RALWN!N9CB=DRG !GFHHDCTG!DCR>@NF!RLCHAL>>DCT! HABMMDR!N@ADCT!RLCTFGHDLCG;!+QF!SALSLGFN!=LNF>!WD>>!BNNAFGG!RL>>DGDLC ! NFHFRHDLC!BCN!BELDNBCRF!DC! EFQDR@>BA!HABMMDR!CFHWLA_G; ! ' DMMFAFCH!Q9SLHQFHDRB>!GRFCBADLG! WFAF! NFGDTCFN! WDHQ!EBA9DCT!RL=S>F^DH9!BC N!MFBH@AFG!MLA! FBRQ!LM!HQF!RLCGDNFAFN!AFB> , WLA>N!GRFCBADLG;!&C!LANFA!HL!GQLW!HQF!SLHFCHDB>!LM!HQF!SALSLGFN! =LNF>BA!F= FATFCH!BRHDLCGBHFN!WDHQ! DCRL=DCT!M>LW!LM!SFLS>F!DC!FBRQ!LM!HQF!Q9SLHQFHDRB>!GRF CBADLG;!+QF!=LNF>!WBG!F^SFAD=FCHFN!DC! FBRQ!GRFCBADL!HL!GQLW!DHG!FMMDRDFCR9!DC!HQF!GD=@>BHFN!GDH@BHDLCG!WQD>F!RLCGFAEDCT!AFBGLCB 8>F! N9CB=DRG!BCN!M>LW!LM!HQF!RALWN`HABMMDR!HQBH!DCR>@NFG!RLCTFGHDLC!BELDNBCRF!BCN!LEFAB>>!GQLAHFA! HABEF>!HD=FG;!+L!SFAMLA=!HQF!BC B>9GDGF>!8F!RAFB HFN!HL!BCB>9]F!HQF!HABMMDR! RLCHAL>!=LNF>; ! 16789:786; , &C!TFCFAB>BHDLC!DG!AF>BHDEF>9!NDMMDR@>H!HL ! RBAA9!L@H! 8FRB@GF!LM!HQF!8FQBEDLA , DCM>@FCRDCT!MBRHLAG!HQBH!RL=F!MAL=!DCHFACB>!BG!WF>>!BG!F^HFACB>!MLARFG! F^FAHFN!LC!HQF!G9GHF=!kIUl;!2@RQ!G9GHF=G!BAF!H9SDRB>>9! RQB>>FCTDCT ! HL!BRR@ ABHF>9!=LNF>!GDCRF! NLDCT!GL!AF?@DAFG!RLCGDNFADCT!HQF!DCHFANFSFCNFCRF!LM!FBRQ ! RL=SLCFCH!kPJl;!/NNDHDLCB>>9
PAGE 21

g ! ! SABRHDRB>>9!D=SLGGD8>F!HL!D=S>F=FCH!BCN!HFGH!B>>!GRFCBADLG!MLA!>BATF , GRB>F!BCN!RL=S>F^!CFHWLA_G! kPOl; ! +QF ! BD=! WBG! HL!BRR@ABHF>9!GD=@>BHF!HQF!BT FCH!8FQBEDLAG!BCN!SQFCL=FCB!DC!=@>HD , BTFCH! G9GHF=G ! DC! G@SSLAHDCT!RALWN!BCN!HABMMDR!=BCBTF=FCH!NFRDGDLCG!QBEF!8FFC!FCG@AFN!HQAL@TQ!B!CLEF>HD , RL=SLCFCHDCT!MAB=FWLA_!NFGDTCFN!HL ! G@SSLAH!HQF!=BCBTF=FCH!NFRDGDLCG!89! F>B8LABHDCT! LC! bWQBH , DMe!GRFCBADLG;!/>GL!BD=G!HL!G@SSLAH!FEFCH!S>BCCFAGc! BCN!8@D>NDCT!NFGDTCFAGc!NFRDGDLCG; ! +QF!D=SLAHBCRF!LM!HQDG!AFGFBARQ!DC!SALEDNDCT!SAL=DGDCT!GL>@HDLCG ! MLA!MBRD>DHBHDCT!RALWN! =BCBTF=FCH!DCEL>EDCT!>BATF!C@=8FAG!LM!DCNDEDN@B>G!WD >>!8F!M@AHQFAFN!HL!DCR>@NF!D=SALEF=FCHG! DC!DHG!SABRHDRB>!BSS>DRB8D>DH9!DC!=LAF!RL=S>F^!GRFCBADLGDCT!BNNDHDLCB>!SQFCL=FCB!BCN! SABRHDRB>!FCEDALC=FCHB>!DCMABGHA@RH@AFG;!2SFRDMD RB>>9DFN! HL!NDMMFAFCH! RALWN ! BCN!HABMMDR ! N9CB=DRG!DC! NDMMFAFCH!AFB> , WLA>N!GRFCBADLG!BCN!BCB>9]F!DHG!FMMFRHDEFCFGG!DC!HQF! RBGF!LM!B!QDTQ , NFCGDH9!=@>HD , BTFCH!G9GHF=G;! +QDG!AFGFBARQ ! Q9SLHQFGD]F G ! HQBH! HQF ! BTFCH , 8BGFN! GD=@>BHDLC!=LNF>!DG! =LAF!G@DHB8>F!HQBC!SAFEDL@G!=FHQLNG!HQBH!BAF!AFGHADRHFN!HL!RLCHAL>>FN!BCN! SA FNFMDCFN!TLB>GFG!B=LCT!BTFCHG;!6@AHQFA=LAFB8>F!FCL@TQ!HL!G@SSLAH!FEFA9NB9!BRHDEDHDFG!LM!NFRDGDLC , =B_FAG!DC!EBADL@G!NL=BDCGBATF!RLCGHABDCFN ! BAFBG;! ! %<=<:>?@, &6;7>8AB786;= , +QDG!NDGGFAHBHDLC!SALEDNFG!B!CLEF>!MAB=FWLA_!MLA!=LNF>DCT!RALWN!BCN!HABMMDR! =BCBTF=FCH!NFRDGDLC!G@SSLAH!G9GHF=G!DC!B!RL>>FRHDEF!FCEDALC=FCH;!+QF!_F9!RLCHAD8@HDLC!DG!@GDCT! =@>HD , >FEF>HD , GHBTFLT9!HL!=LNF>!RL=S>F^!G9GHF=G!H L!FCG@AF! RBSH@ADCT!B>>!MBRHLAG!HQBH!D=SBRH!HQF!RL=S>F^!N9CB=DRG!BCN!GHA@RH@AFG!LM!B!G9GHF=;!&C!HQBH!WB9
PAGE 22

h ! ! HQF!SALSLGFN!Q98ADN!BTFCH , 8BGFN!MAB=FWLA_!DG!B8>F!HL!=LNF>!RL=S>F^!B@HLCL=L@G!G9GHF=G; ! 3L=SBAFN!HL!HQF!SALSLGFN!=LNF> ! /$(!HL!=LNF>!DCNDEDN@B>! BTFCHGc!8FQBEDLAG;!+QF9!QBEF!CLH!=LNF>FN!BC!FCHDAF!RL=S>F^!G9GHF=!@GDCT!=@>HDS>F!>B9FAG!LM! =LNF>DCT!WQD>F!GD=@>HBCFL@G>9!DCRLASLABHDCT!=@>HDS>F!>FEF>G!RLCHBDCDCT!=@>HDS>F!GHBTFG!BCN! @GDCT!BTFCH , 8BGFN ! BCN!RF>>@>BA!B@HL=BHB!RL=S@HDCT ! BSSALBRQFGD]DCT!BC!F^DGHDCT!BTFCH , 8BGFN!=LNF>DCT!BSSALBRQDCT!>FEF>G! BCN!>B9FAG!ZGRB>FG[!WFAF!DCHFTABHFN!HL!FCG@AF!HQF!B8D>DH9!BCN!AL8@GHCFGG!LM!HQF!SALSLGFN!=LNF> ! HL! RBSH@AF!B>>!RALWN`HABMMDR!SQ FCL=FCLC!N@ADCT!ADG_!BCN!SBCDR!GDH@BHDLCG; ! -=S>L9DCT!HQF!BNa@GHB8>F!/$(!BSSALBRQ!QF>SG!HL!GD=@>BHF!Q@=BC!SFARFSHDLC!BCN! NFRDGDLC , =B_DCT!DC!RL=S>F^!GRFCBADLG;!+QFAFMLAF!DG!B8>F!HL! BRR@ABHF>9!GD =@>BHF!HQF!BTFCHGc! 8FQBEDLAG!BCN!SQFCL=FCB>LWDCT!MLA!D=SALEFN!NFRDGDLCG!HB_FC! HL!FCQBCRF!HQF!WQL>F!RL=S>F^!G9GHF=G;!&C!BNNDHDLC!DG!NDGHDCRH!MAL=!B>>! SAFEDL@G!WLA_G!DC!DHG!CLEF>H9!BCN!FMMFRHDEFCFGG!DC!GD=@>BHDCT!>BATF , GD]F!QFHFALTFC FL@G!RL=S>F^! HABMMD R!CFHWLA_G!8BGFN!LC!8LHQ!3/!BCN!Q98ADNHDRL=SLCFCH!/$(!HFRQCD?@FG; ! 4CF!GSFRDMDR!RLCHAD8@HDLC!DG!RL=8DCDCT!HQF!N9CB=DR!BTFCHGc!GHBH@G!@SNBHDCT9DCT! LC ! 8FQBEDLAB>!MBRHLAGF^!G9GHF=!=LNF>DCT;!+QDG!BSSALBRQ!LMMFAG!B ! GDTCDMDRBCH! D=SALE F=FCH!LEFA!HQF!F^DGHDCT!G@AEF9FN!WLA_G;! 5AFEDL@G!WLA_G ! GSFRDM 9 ! HQF!BTFCHGc!AL>FG!SADLA!HL! HQF!GD=@>BHDLC!8FTDCCDCT! WDHQL@H!RLCGDNFADCT! HQF!N9CB=DR!FCEDALC=FCHB>!FEFCHG!HQBH!RL@>N!LRR@A! BMHFA!HQF!GD=@>BHDLC!8FTDCG;! DC!RLCHABGH! @SNBHFG!BC N!F^SBCNG!HQF!BTFCHcG! GHBH@G!N9CB=DRB>>9< ! =B_DCT!DH!=LAF!GSFRDMDR!HL!HQF!BTFCHGc!G@AAL@CNDCT!FCEDALC=FCHB>!GDH@BHDLCG;! +QF!GDTCDMDRBCRF!LM ! HQF!BTFCH!GHBH@G!8FDCT!RLCHDC@L@G>9!BCN!N9CB=DRB>>9!@SNBHFN!HQAL@TQL@H!HQF! FCHDAF!GD=@>BHDLC!DG ! HQ BH!HQF!=LNF>!DG!TFC FAB>D]FN;!/>GLFEF>G!LM!DCHF>>DTFCRF!BAF! SLGGD8>F!MLA!HQF ! BTFCHG;!4HQFA!>FEF>G!LM!HQF!SALSLGFN!=@>HD , >FEF>HD , GHBTF
PAGE 23

U ! ! NFRDGDLC!G@SSLAH!G9GHF=!WFAF!=LNDMDFN!BRRLANDCT!HL!HQF!D=SALEF=FCH!DC!HQF!BTFCHGc!GHBH@G! @S TABNDCT!=LNF>; ! +QF! SAFGFCHFN!WLA_!LMMFAG!BCLHQFA!RLCHAD8@HDLC!HL!HQF!NDGRL@AGF!DC!HQBH!HQF!MDAGH!>FEF>!LM ! =LNF>DCT!LM!HQF!G9GHF=!N9CB=DRG>9!DCHFTABHFG!NFRDGD LC!A@>FG!F^HABRHDLC ! DCHL!HQF!=LNF>; ! +QDG!AF , RLCHF^H@B>D]BHDLC!B>>LWG!@G!HL!F^HABRH!HQF!A@>FG!MLA!NFHFA=DCDCT`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cG! HABCGDHDLC!HQAL@TQ!HQF!FCEDALC= FCH;!+QF!N9CB=DR!M> LLA!MDF>N!DG!=LNDMDFN!BRRLANDCT!HL!DHG!NDMM@GDLC! BCN!NFRB9!A@>FG!SAFEDL@G>9!DCEFGHDTBHFN!DC! kKi!/$(!SALEDNFG!B!CFW ! GL>@HDLC!HL!HQF!SAL8>F=!LM!HA@GHWLAHQDCFGG!89!DCRLASL ABHDCT!B!HA@GHWLAHQ DCFGG!FEB>@BHDLC!HLL>!DC ! =LNF>DCT!HQF!RL==@CDRBHDLC!BCN!DCMLA=BHDLC!F^RQBCTF!8FHWFFC!BTFCHG;!4CF!LM!HQF!

PAGE 24

OJ ! ! GQLAHRL=DCTG!LM!HQF!SAFEDL@G!RL=S>F^!CFHWLA_!BSSALBRQFG!WBG!HQBH!HQF9!NDN!CLH!DCR>@NF!B! RL==@CDRBHDLC!=LNF>!8BGFN!LC!HA@GHWLAHQDCFGG! 8FHWFFC!BTFCHG;!2@R Q!BC!BGGFGG=FCH!D=SALEFG! HQF!BRR@ABR9!LM!BTFCHGc!NFRDGDLCG!DC!HQF!RL=S>F^!G9GHF=>!G9GHF=cG! SFAMLA=BCRF;!+QF!CFFN!HL!SFAMLA=!B!HA@GHWLAHQDCFGG!FEB>@BHDLC!8FHWFFC!BC!BTFCH!BCN!DHG! CFDTQ8LAG!DG!RADHDRB>>LWG!HQF!BTFCH G!HL!BNa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

PAGE 25

OO ! ! &5!4$(%, )) , "!&0%*3+',!+', %(/!$(',.*%, 16D!DG!B!S@ASLGFM@>!D>>@GHABHDL C!LM!B!AFB>!G9GHF=!=BNF!HL!FDHQFA!BCGWFA!?@FGHDLCG! B8L@H!B!GSFRDMDR!G9GHF=!LA!GD=S>9!HL!GL>EF!SAL8>F=G!kIUl;!+L!RAFBHF!B!=LNF>!=FBCG!HL!NFGDTC!DHG! B>TLADHQ=G!BCN! RLCRFSHG!@GDCT!RL=S@HBHDLCB>!=FHQLNG ; ! + QDG!BSSALBRQ!LMMFAG ! BNEBCHBTFG!LEFA! LHQFAG!HQBH!BAF!FDH QFA!HLL!RL=S>F^!HL!8@D>NN!HB_F!HLL!>LCT ! DC! HQF ! F^SFAD=FCH! SQBGF ! kPJl;!6LA!DCGHBCRFN!8F ! RQB>>FCTDCT!BCN!HD=F , RLCG@=DC T ! HL! RL=SAFQFCN!QLW!RDHDFG!BCN!>BCN!MLA=BHDLCG ! @CNFATL!RQBCTF!a@GH!89!AF>9DCT!LC ! F^SFAD=FCHG; ! &C! BC!BHHF=SH!HL!TFH!B!8FHHFA!@CNFAGHBCNDCT!LM!GL=FHQDCT!>BATF!LA!RL=S>F^F! EFAGDLC!LM!HQF!G9GHF=!WDHQ!HQF!BDN!LM!RL=S@HFA!SALTAB=G!BCN ! =BHQF=B HDRB>!F?@BHDLCG!HQBH! WF ! RBC! FNDH!BCN!F^SFAD=FCH!LC!DC!GD>DRL!kPOl; ! (LNF>DCT!BCN!GD=@>BHDLC!BAF ! DCHFTAB>!HLL>G!DC!=LNFAC!GRDFCRF ; ! + QF9!FCB8>F!F^S>BCBHDLC! BCN!SAFNDRHDLC!LM!GSFRDMDR!RLCNDHDLCG!HQBH!=B9!CLH!QBEF!8FFC!LHQFAWDGF!SLGGD8>F;!+QF!SALRFGG!89! WQDRQ!B ! =LNF>!DG!F^FR@HFN!BCN!F^SFAD=FCHFN!LC!DG!_CLWC!BG!GD=@>BHDLC!kIU!HQAL@TQ!RLCHDC@L@G!LA!NDGRAFHF!RQBCTFG!LM!GHBHF!LEFA!HD=F!kPJl;!)G@B>>9H!SAL8>F=G!WQFAF!HD=F!BCN!RLGH!BAF!RA@RDB>!EBADB8>FGBHDLC!LMM FAG ! B!QDTQ!AFH@AC!LM! DCMLA=BHDLC!WQD>F!B>GL!FCQBCRDCT!HQF!?@B>DH9!LM!HQF!SALN@RH!B>LCT!HQF!NFE F>LS=FCH!GHBTF; ! +L!RBAA9!L@H!HQF!GD=@>BHDLC!LM!B!RL=S>F^!SALRFGGF=FCHZG[!HL!8F! BCB>9]FN!CFFN!HL!8F!TBHQFAFN!LA!DCMFAAFN;!5BAB=FHFAG!G@R Q!BG!HQF!RQBABRHFADGHDRG!LM!HQF!F>F=FCHZG[! CFFN!HL!8F!BAABCTFN!DC!B!@CDMLA=!=BCCFA!BCN!WDHQ!B! GRQF=BHDR!AFSAFGFCHBHDLCGLBHF!B!RL=S>F^!SALRFGG
PAGE 26

OI ! ! HQF!F>F=FCH!@CNFA!RLCGDNFAB HDLC! DG ! CFFNFN!MLA ! NBHB ! NFGRAD8DCT!HQF!8FQBEDLA!LM!G@8G9GHF=G! BNaBRFCH!HL!HQF!G@8G9GHF=!GH@NDF N < ! BCN!DCMFAADCT!QLW!HQLGF!G9GHF=G!DCHFABRH!BCN!DCM>@FCRF!FBRQ! LHQFA ! kPIl; ! (BC9!RQB>>FCTFG!BADGF!N@ADCT!HQF!NFEF>LS=FCH!LM!GD=@>BHDLC!=LNF>G!MLA!HQF!NFGDTC!LM! RL=S>F^!G9GHF=G;!+QLGF!RQB>>FCTFG!DCR>@NF!DCRLASLABHDCT!=@>HDS>F!SFAGSFRHDEFG!HQBH!LRR@A!WDHQDC! H QF!G9GHF=>!G9GHF= ! BCN!HQF!DCNDEDN@B>!8BGDR!SBAHG;!/C!BNNDHDLCB>!RQB>>FCTF!DG! DC!NFHFA=DCDCT!HQF!B=L@CH!BCN!RL=S>F^DH9!LM!NFHBD>!BCN!DCMLA=B HDLC!HQBH!GQL@>N!8F!DCR>@NFN!DC! HQF!=LNF>; ! 4CF!BSSALBRQ!HL ! B!RL=S>F^!=LNF>!DG!HL!NDGHD>>!HQF!RL=S >F^!G9GHF= ! DCHL!G@8G9GHF=G ; ! -BRQ ! QBEF!GSFRDMDR!AL>FG!BCN ! BAF!G@8GF?@FCH>9!@HD>D]FN!BG!8@D>NDCT!8>LR_G!HQBH!SLGGFGG!HQFDA!LWC! RQBABRHFADGHDRG!kPIl; ! (LN@>BAD]BHD LC!DG!B!=FHQLN!HQBH!RLCGDNFAG!HQF!RL=S>F^!G9GHF=!BG!B!SBAH!LM!LHQFA! G@8G9GHF=G ! QBEDCT!GSFRDMDR!AL >FG!HQBH ! RLCHAD8@HF!HL!HQF!NFGDTC!DCMLA=BHDLC!DC!8FQBEDLA!BCN! M@CRHDLC;!(LN@>BAD]BHDLC!DG!EDHB>!MLA!=BCBTDCT!RL=S>F^DH99!LC!=LNF> , 8BGFN!G9GHF=G!FCTDCFFADCT!Z($2-[;!+QF!($2! DG!B! NDGHDCRH! BSSALBRQ!HL ! G9GH F=!=LNF>DCT!=FHQLNG!BCN!MAB=FWLA_G ! HQBH!G@SSLAHG!RL=S>F^!G9GHF=!NFGDTCG ;!&H ! DG!B ! EBGH!=FHQLNL>LT9!HQBH!LEFAGFFG!LHQFA!BGSFRHG!LM!FCTDCFFADCT!NFGDTCGG!kPPl; ! !F<;7 K A:=6:?@ , /!RLCGDNFAB8>F!SFARFCHBTF!LM!NBHB!BEBD>B8>F!MLA!RLCG@=SHDLC!DG!TFCFABHFN!89!DCHFABRHDEF! G9GHF=G!HQBH!NL!CLH!DCEL>EF ! Q@=B CG; ! &C!LANFA!HL!FCG@AF!B!GL>DN!=FRQBCDG=!HL! NFHFA=DCF!HQF!SLGGD8>F!BTFCH!8FQBEDL AG!8FMLAFQBCN;!7QFC ! HQFAF!DG!B!SLGGD8D>DH9!HL!SAFNDRH!BTFCH! 8FQBEDLAG!FMMFRHDEF>9BHMLA=!WD>>!8F!B8>F!HL!LSHD=D]F!HQF!SFAMLA=BCRF!kPYl;!7DHQ!HQF!QF>S! LM ! =BRQDCF!>FBACDCTF!HL!SAFNDRH!HQF!8FQBEDLA!LM!N9CB=DR!G9GHF=G!HQBH!F^DGH!DC!HQF!

PAGE 27

OP ! ! AF B>!WLA>N!kPil;!6LA!F^B=S>FF!WD>>!WLA_!DC!B!RALWNGL@ARFN!SALaFRH!LA ! QLW!B! =BA_FHDCT!RB=SBDTC!=DTQH!NF>DEFA!SLGDHDEF!AFG@>HG!RBC!FBGD>9!8F!NFHFA=DCFN! WDHQ!HQF!BGGDGHBCRF! LM!=BRQDCF!>FBACDCT ! kPKl; ! +QF!DCDHDB>!NBHB!AF?@DAFN!HL!8@D>N!B!=LNF>!LM!HQFGF ! G9GHF=G!BAF!L8HBDCFN!89!L8GFAEBHDLCG! LM!>DEF!BTFCHG!BCN!HQFDA!8FQBEDLA!kPg , YJl;!+QFGF!G9GHF=G!RBC!8F!LSHD=D]FN!HQAL@TQ!HQF!RLCHDC@B>! DCS@H!LM!BNNDHDLCB>!NBHB! GFHG;!/G!B!AFG@>H!WD>>!D=SALEF!WDHQ!HD=F;!&C!HQF!=FBCHD=F>!8F!L8GFAEDCT!B> >!RQBCTFG!HQBH!HB_F!S>BRF!WDHQDC!HQF!G9GHF=!BCN!WD>>!AFGSLCN!HL!HQF! GSFRDMDR!RQBCTFG!HQAL@TQ!HQFDA!8FQBEDLAG;!+QDG!DG!QLW ! 8FQBEDLAB>!NBHB!FEL>EF G ! LEFA!HD=Fm!HQF9!BAF! CLH!DCNFSFCNFCH>9!BCN!DNFCHDRB>>9!NDGHAD8@HFN!kPUFBACD CT! QBEF!RL=F!BRALGG!GL=F!GDTCDMDRBCH!HQFLAFHDRB>!RQB>>FCTFG!kPi! NBHB;!(3%-!M@CRHDLCG!89!RLCN@RHDCT!TFCFAB>D]BHDLC!BCB>9GDG!LM!HQF!B> TLADHQ=G!@GFN!DC!=BRQDCF! >FBACDCT;!(3%-!DG!BGGLRDBHFN!WDHQ!B!LCF , GHFS!HABCGDHDLCm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kYOl; ! 2FEFAB>!HQFLADFG!BAF!@GFN!WQFC!=LNF>DCT!HQF!GSBHDL , HF=SLAB>!SALRFGGFG;!/= LCT!HQLGF! HQFLADFGG!Z/$([!ki>@>BA!B@HL=BHB!Z3/[!kOi ,

PAGE 28

OY ! ! I J F!LM!AFM>FRHDCT!HQF!F=FATFCH!BCN!RL=S>F^! RQBABRHFADGHDRG!BGGLRDBHFN!WDHQ!RL=S>F^!SQFCL=FCLC;!$LHQ! /$(!BCN!3/!BAF!RLCGDNFAFN ! 8LHHL= , @S!BSSALBRQFG!k P DH9!HL!F^S>BDC!HQF!GHBH@G!RQBC TFG!HQBH!HB_F!S>BRF! WDHQDC!HQF!GSBHDB>!RF>>G!GHFS , 89 , GHFS!kPg ! HL!@CNFAGHBCN!HQF!NFHBD>G!LM!HQ F!BTFCHGBHDLCGQDSG!LM!BTFCHGLCT!WDHQ!HQFDA! DCH FABRHDLC!=FHQLNGF!HL!SAFNDRH!QLW!HQF!=LNF>!WD>>!SFAMLA=!BCN!8FQBEF!kPUGL!RADHDRB>!HL! G@RRFGGM@>>9!GD=@>BHF!BC!BTFCH , 8BGFN!=LNF>>9 ! FEB>@BHF!HQF! SBAB=FHFAG!RLCHAL>>DCT!HQF!DCHFABRHDLCG!BCN!8FQBEDLAG!LM!HQF!BTFCHG!kU , OODCT!BCN!GD=@>BHDLC!Z/$(2[! RBC!FMMFRHDEF>9!8F!@GFN ! HL!=LNF>!G9GHF=G! HQBH!BAF!=BNF!L@H!LM!DCHFABRHDCT!BTFCHG!kU!MAB=FWLA_ ! @GFN!HL!GD=@>BHF!NDEFAGF!SALRFGGFG!DCEL>EDCT!B@HLCL=L@G!BTFCHG! k P >!QBEF!DHG!LWC!8FQBEDLAG!BCN!RQBABRHFADGHDRG;!/TFCHG!WD>>! B>GL!QBEF!HQFDA!LWC!DCQFAFCH!BHHAD8@HFG!BCN!SA LSFAHDFGm!MLA!F^B=S>FM , NDAFRHFN! BCN!B@HLCL=L@G!kPUF!MLA!BC!BTFCH!HL!M@CRHDLC!DCNFSFCNFCH>9!WDHQDC!H QF! FCEDALC=FCHDCFBA[!WDHQ!LHQFA!BTFCHG!RBC!B>GL!8F!NLCF!DC!BC! DCNFSFCNFCH!=BCCFA!k YPl;!+QF!8FQBEDLA!LM!BC!BTFCH!DG!AF>BHFN!HL!HQF!DCMLA=BHDLC!HQBH!BC!BTFCH! WL@>N!GFCGF!MAL=!HQF!FCEDALC=FCH!DC!WQDRQ!DH!DG!>DEDCTm!HQFGF!SDFR FG!LM!DCMLA=BHDLC!WD>>!HADTTFA! BRHDLCG!BG!WF>>!BG!NFRDGDLCG!kYYl; ! /TFCH , 8BGFN!=LNF>DCT!AFSAFGFCHG!HQF!DCNDEDN@B>!RL= SLCFCHG!LM!B!G9GHF=;!&C!BNNDHDLCGL!NFHFA=DCFN!BCN!AFSAFGFCHFN;!"FCRF>!CLH!8F! NFGRAD8FN!HQAL@ TQ!HQF!@GF!LM!EBADB8>FG;!&CGHFBN!BTFCHG!WD>>!8F!@GFN!DC!LANFA!HL!=LNF>!

PAGE 29

Oi ! ! HQF!FCHDAF!G9GHF=!k P F!HL!RL=F!HL!B!RLCR>@GDLC!HQBH!BTFCHG! AFSAFGFCH!HQF!DCNDEDN@B>!RL=SLCFCHG!LM!B!G9GHF=;!/TFCHG!BAF! DCNDEDN@B>!BCN!@CD?@F!RL=SLCFCHG! kYUl!DC!HFA=G!LM ! HQFDA!>LRBHDLC>!CLH!DCHFABRH!WD HQ!B>>! LHQFA!BTFCHG!DC!HQF!G9GHF=m!DCGHFBN>!>D=DH!HQF!DCHFABRHDLCG!HL!HQF!BTFCHG!DC!HQF! CFDTQ8LAQLLN!kihl; ! '@F!HL!HQF!B8 LEF , =FCHDLCFN!AFBGLCGDFN!HL! 8LHQ!HQFDA!R@AAFCH!GHBHF!BCN!HQF!LEFAB>>!FCEDALC=F CH!kIUDCTF!HL!GL>EF!GL=F!LM!HQF!RL==LC!DGG@FG!BGGLRDBHFN!WDHQ!F=FATFCRF@NF! G9GHF=!N9CB=DRG!BCN!HQF!WB9!FBRQ ! BTFCH!AFGSLCNG!HL!HQF!FCEDALC=FCH!kiUDH9!LM!/$(!DC!= LNF>DCT!BCN!GD=@>BHDCT!RL=S>F^!G9GHF=G!WQDRQ! GSBC!BRALGG!EBADL@G!RLCHF^HG!kiU , hglF!BSS ALBRQ! BEBD>B8>F!WQFC!GH@N9DCT!B!G9GHF=!HQBH!AF?@DAFG!BNBSHDEF!8FQBEDLA!G9GHF=G!kg g l;! 7QFC!RLTCDHDEF ! /$(!DG! @GFN!HL!AFSAFGFCH!RLTCDHDLC!B8D>DH9!DC!Q@=BCGG!HQF! LATBCD]BHDLCB>!8FQBEDLA!8FQBEDLA!BCN!NFRDGDLC , =B_DCT!LM!DCNDE DN@B>G!kKDFN!HL!RLCGHA@RH!RL=S>F^!BCN!N9CB=DR!=LNF>G!LM!Q@=BC!NFRDGDLC , =B_DCT! DC!GD=@>BHDLCG ! LM!RALWN!BCN!FEBR@BHDLC!N9CB=DRG!kOY!HFCNG ! HL!8F!DCNFSFCNFCH!MAL=!LHQFA!DCNDEDN@B>G!DC!B! RLCCFRHFN!FCEDALC=FCH!kOJ!FCEDALC=FCHGFRH!B! TAL@S , 8BGFN!NFRDGDLCBHDLC! =FHQLN!LC!B!GLRDB>!GHA@RH@AF!kPil;! 2 LRDB>!GHA@RH@AF!BCN ! TAL@S!NFRDGDLC , =B_DCT!GRQF=FG!BAF! QDTQ>9!DCM>@FCHDB>!MBRHLAG!N@ADCT!Q@=BC!8FQBEDLA ;!+Q@G< ! HQF9!BAF!RADHDRB>!EBADB8>FG!HL!DCR>@NF! N@ADCT!HQF!RLCGHA@RHDLC!LM!GD=@>BHDLCG!LM!8FQBEDLA!G@RQ!BG!RALWN!FEBR@BHDLC!khU
PAGE 30

OK ! ! L8aFRHDEF!LM!BTFCH , 8BGFN!GD=@>B HDLC!DG!HL!NFHFA=DCF!QLW!HQF!BTFCHG!8FQBEF!DC!FCEDALC=FCHG!HQBH! DCR>@NF!LHQFA!BTFCHG9]DCT!HQF!WB9!BTFCHG!=B_F!NFRDGDLCGDH9!SAFGFCHG!DHGF>M!BG!B!WB9!HL!MDT@AF!L@H!HWL! ND=FCGDL CG!HQBH!NFMDCF!BTFCH! BARQDHFRH@AFGX!HQF ! GLRDB>!BCN!HQF!RLTCDHDEF!>FEF> G ! kiYl;!+QF!GLRDB>! >FEF>!LM!HQF!BTFCHG!DG!NFHFA=DCFN!89 ! HQFD A!B8D>DH9!HL!NDGHDCT@DGQ!GLRDB>!CFHWLA_!AF>BHDLCG;!&C! BNNDHDLCFEF>!LM!RL==@CDRBHDLC!HQBH!HQF!BTFCHG!BAF!RBSB8>F!LM!DG!B >GL!NFHFA=DCFN;!2L=F! BTFCHG!BAF!RBSB8>F!LM!=BCBTDCT!RL=S>F^!GLRDB>!SALaFRHG;!+QF!RLTCDHDEF!>FEF>!LM!HQF!BTFCHG! NFHFA=DCFG!WQFHQFA! LA!CLH!HQF9!BAF!FCHDAF>9!AFBRHDEF ! kK F!RLTCDHDEF! RL=SLCFCHG!BCN!MLA=G!LM!NF>D8FABHDLC!LM!HQF!BTFCHG!BA F!B>GL!NFHFA=DCFN!HQAL@TQ!HQDG!BSSALBRQ! kgl; ! 7QFC!>LL_DCT!BH!HQF!RL>>FRHDEF!8FQBEDLA!LM!BTFCHG!HQBH!F^DGH!WDHQDC!B!GLRDB>!CFHWLA_! FCEDALC=FCHF!HL!GFF!HQBH!RLCGF?@FCRFG!BAF!8BGFN!@SLC!HQF!BTTAFTBHDLC!LM!DCNDEDN@B>! 8FQBEDLAG!kU! BTFCHG!HFCN!HL!8F!DCNFSFCNFCH;!&C!LHQFA!WLANGF!LM!=LEDCT!MLAWBAN!WDHQ! HQFDA!WLA_!WDHQL@H!BC9!NFSFCNFCRDFG!LC!FBRQ!LHQFAHQL@TQ!HQF9!BAF!DCM>@FCRFN!89!HQF! 8FQBEDLAB>!HA FCNG; ! +QF!8FQBEDLAG!LM!DCNDEDN@B>!BTFCHG!BAF!HQFC!NFHFA=DCFN!DCNFSFCNFCH>9!LM!LHQFA!BTFCHG>! LM!WQDRQ!QBEF!HQFDA!LWC!DCQFAFCH!B HHAD8@HFG!BCN!SALSFAHDFG!k P , OPl;!6LA!F^B=S>FM , NDAFRHFN!BCN!B@HLCL=L@G;!+QF!8FQBEDLA!LM!BC!BTFCH!DG!B>GL!A F>BHFN!HL!HQF!DCMLA=BHDLC ! HQF9! WL@>N!GFCGF!MAL=!HQF!G@AAL@CNDCT!FCEDALC=FCH;!+QFGF!SDFRFG!LM!DCMLA=BHDLC!WD>>!DCM>@FCRF! BRHDLCG!BG!WF>>!BG!NFRDGDLCG!kPil;!(LN@>BADH9!RBC!8F!RLCGDNFAFN!BG!BCLHQFA!SAL=DCFCH!BHHAD8@HF! B=LCT!BTFCHG!kPIl;!/G!B!AFG@>HDH9!HL!DNFCHDM9!BC!BTFCH9!BCN!NDGRAFHF>9< ! WDHQ!B!GFH!LM!RQBABRHFADGHDRGDHDFG
PAGE 31

Og ! ! 2LRDB>DH9!k P l!DG!DNFCHDMDFN!BG!BC!BHHAD8@HF!LM!HQF!BTFCHG!BG!HQF9 ! BAF!8FDCT!GLRDB>D]FN!B>LCT! WDHQ! LHQFA!BTFCHG!BCN ! WD>>!F^RQBCTF!DCMLA=BHDLC!WDHQ!FBRQ!LHQFA!HQAL@TQ!GSFRDMDR!RL==@CDRBHDLC! =FHQLNG!HQBH ! @CD?@F>9!DNFCHDM9 ! HQF!LHQFA!BTFCHG!BCN!GFCN!HQF=!BSSALSADBHF!=FGGBTFG; ! /TFCH , HL , BTFCH!DCHFABRHDLCG!BAF!NFHFA=DCFN!89!RL==LC!HLSL>LTDFG!k P l>LWGX ! • ! 2 L@S! \ ! /CLC , GSBHDB>!=LNF>LRBHDLCB>! BHHAD8@HFG ; ! • ! 0 ADN! \ ! +QF!DCHFABRHDLCB>!S BHHFACG!LM!BTFCHG ; ! • ! -@R>DNFBC!GSBRF! \ ! +QF!B8D>DH9 ! HL!ALB=!BAL@CN!DC!HWL , ND=FCGDLCB>!BCN!HQAFF , ND=FCGDLCB>! GSBRFGm!HQF!LEFAB>>!GSBRF!DG!RB >>FN!HQF!-@R>DNFBC!GSBRF ; ! • ! 0FLTABSQDRB>!DCMLA=BHDLC!G9GHF=! \ ! /TFCHG!HFCN!HL!=LEF!BCN!DCHFABRH!WDHQ!TFL!GSBHDB>! >BCNGRBSFG ; ! • ! 1FHWLA_G! \ ! 1FHWLA_G!RBC!FDHQFA!8F!N9CB=DR!LA!GHBHDR;!+QF!>LRBHDLC!LM!BC!BTFCH!DG!AF>BHDEF!HL! HQF!>LRBHDLC!CLNF!LM!HQF!CFHWLA_; ! %FTBAN> FGG!LM!HQFGF!RL==LC!HLSL>LTDFGDH9!LM!HQF!BTFCHG!HL! DCHFABRH!BH!BC9!TDEFC!HD=F!B>LCT!WDHQ! LHQFA!BTFCHG!DC!HQF!SLS@>BHDLC!kgIl;!+QDG!DCHFABRHDLC!RBC!8F! NLCF!EDB!HQF!NFMDCDHDLC!LM!B!>LRB>!CFDTQ8LAQLLN!HQBH ! WD>>!8F!GHLAFN!WDHQDC! HQF!GB=F!CFHWLA_; ! +QF!MDCB>!BHHAD8@HF!LM!BTFCHG!DG!RLCNDHDLCB>DH9!k P l;!/>>!BTFCHG!BAF!F?@DSSFN!WDHQ!B!GSFRDMDR!GHBHF! HQB H ! RBC!EBA9!B>LCT!WDHQ!HD=F!BCN!RLCHBDCG!B!G@8GFH!LM!8FQBEDLAG!BCN!BHHAD8@HFG!LM!BC!BTFCH;!+QF! GHBHF!LM!HQF!FCEDALC=FCH!DG!RAFBHFN!MAL=!B >>!HQF!GHBHFG!LM!BTFCHG;!+QF!SALRFGG!LM!>FBACDCT!WD>>! NFGRAD8F!HQF!@>HD=BHF!8FQBEDLA!LM!BTFCHG; ! /TFCH , 8BGFN!=LNF>DCT!RBC ! 8F!NLCF!DC!HWL!GHFSG!k P l;!+QF!MDAGH!GHFS!DG!HL!NFHFA=DCF!HQF!R>BGGFG! LA!H9SFG!LM!BTFCHG!WQDRQ ! GQL@>N!8F!NLCF!B>LCT!WDHQ!NFHFA=DCDCT!HQF ! BHHAD8@HFG!LM!HQF!BTFCHG;!+QF!

PAGE 32

Oh ! ! GFRLCN!GHFS ! DG ! GSFRDM9DCT!BTFCH cG ! 8FQBEDLAG!kUN!8F! @GFN!BG!HQF!8BGDG!MLA!=LNF>DCT!BTFCH!8FQBEDLA;!&H!DG!B>GL!SLGGD8>F!HL!GHBAH ! WDHQ!B!TFCFADR! 8FQBEDLAB>!QF@ADGHDR!BCN!B!8L@CNFN!ABHDL CB>DH9!=LNF>!kOJl;!+QDG!WD>>!NFHFA=DCF!HQF!WB9!BTFCHG! DCHFABRH!D C!HQFDA!AF>BHDLCGQDSG!WDHQ!LHQFA!BTFCHG; ! 7QD>F!BCB>9]DCT!BTFCH , 8BGFN!=LNF>DCTF^!G9GHF=G!DC!HQF!AFB>!WLA> N!BCN!HABCGMLA=!HQF=!DCHL!G@DHB8>F!=LNF>G!kKDCT!>FEF>G!CFFN!HL!8F!GF>FRHFN;!/>LCT!WDHQ!HQF!BGGDGHBCRF! LM!BC!BSSALSADBHF!/$(!MAB=FWLA_DH9!HL!EB>DNBHF!B!>BATF , GRB>F!G9GHF=HDS>F!BTFCHG!kgOl;!+QDG!WD>>!CLH!8F!SLGGD8>F!WDHQL@H!HQF!@GF!LM!RLTCDHDEF! BTFCH , 8BGFN!RL=S@HDCT; ! /CLHQFA ! SAL=DCFCH!8FCFMDH!HQBH!RBC!8F!F^SFADFCRFN!HQAL@TQ!/$(!DG!HQBH!DH ! QBG!HQF!B8 D>DH9!HL! RLCHAD8@HF!HL!HQF!8@D>N@S!LM!=LNF>G!k P G!RBC!8F!NFEF>LSFN!WDHQL@H!BC9! @CNFAGHBCNDCT!LM!HQF!T>L8B>!DCHFA , NFSFCNFCRDFG>!RAFBHF!BC!D=SBRH!LC!FBRQ!LHQFA!WQD>F!NFEF>LSDCT!BC ! BTFCH , 8BGFN!=LNF>;!1LA!DG!DH ! D=SLAHBCH! HL!QBEF!BC!@CNFAGHBCNDCT ! LM!HQF!GF?@FCRF!LM!LSFABHDLC!kPi!SBAHDRDSBCHG!BCN!QLW!HQF!LEFAB>>!SALRFGG!WL@>N!8FQBEF!DG!RADHDRB> ! HL!NFEF>LS!HQF!>LRB>! 8FQBEDLAHD=BHF> 9!RLCHAD8@HFG!HL!T>L8B>!8FQBEDLA!kYIl; ! !F<;7 K A:=BATF!C@=8FA!LM!BSS>DRBHDLCG!DC!T>L8B>!G9GHF=G!kih , gil;!&C!LANFA!HL!=BCBTF!HQDG!_DCN!LM!G9GHF=!FMMFRHDEF>9!RL=SLCFCHG!BCN!HQF!WB9! HQF9!DC HFABRH!WDHQ!FBRQ!LHQFA!=@GH!8F! NFHFA=DCFN ;!+QFGF!DCHFABRHDLCG!QB EF!HQFDA!LWC!SBAB=FHFAG! BCN!A@>FGm!HQ@GDCT!B!G9GHF=!@GDCT!BTFCH , 8BGFN!=LNF>G
PAGE 33

OU ! ! F^BRH!AF>BHDLCGQDSG!HQBH!F^DGH!8FHWFFC!DCNDEDN@B>!BTFCHG!k PN!8F!>LRBHFN!WDHQDC!HQ F!FCEDALC=FCHm ! LHQFAWDGFDH9!HL! FGHB8>DGQ!HQF!AF>BHDLCGQDSG!8FHWFFC!HQF=;!/!EBADFH9!LM!=FHQLNG!BAF ! BEBD>B8>F!HL!FGHB8>DGQ! AF>BHDLCGQDSG!kYi , NDAFRHFN!AF> BHDLCGQDSG!BCN!GD=S>F!AFBRHDEF!AF>BHDLCGQDSG; ! &C! BNNDHDLCDHBHF!HQF!DCHFABRHDLCG!HQBH!HB_F!S>BRF!WDHQDC!HQF! G9GHF=!GQL@>N ! 8F!NFHFA=DCFN;!7QD>F!HQF!DCHFABRHDLCG!BAF!GD=@>BHFN!WDHQDC!BC!FCEDALC=FCH DH9!HL!AFSAFGFCH!HQF=!WDHQDC!B!RLCHDC@L@G!LA!N DGRAFHF!MDF>N!kYP>9!Q@=BC!8FQBEDLABHDLC!=FHQLN!LC!B!GLRDB>!GHA@RH@AF!DG!CFFNFN!kIYG!RB C! 8F!8@D>H!@GDCT!HWL!BSSALBRQFGX!NDGRAFHF!FEFC H!=LNF>DCT! LA ! F^DGHDCT!G9GHF=!N9CB=DRG!k P !RBC ! 8F!FCQBCRFN!WDHQ!HQF!L8aFRHDEF!LM!RBSH@ADCT!NFSFCNFCRDFG! BCN!=LAF!RL=S>F^!8FQBEDLA;! ! (DRAL!GD=@>BHDLC< ! WQDRQ!DG! BCLHQFA!D=S LAHBCH!BGSFRH!LM!HQF!BTFCH , 8BGFN!=LNF>< ! 8FRL=FG! RADHDRB>>9!D=SLAHBCH!WQFC!BTFCH , 8BGFN!=LNF>DCT!DG!BSS>DFN!HL!SABRHDRB>!GRFCBADLG!kYKl;!+QF! =LNF>FA!WQL!NFMDCFG!HQF!BTFCH , 8BGFN!=LNF>!GQL@>N!8F!DC!B!SLGDHDLC!HL!DNFCHDM9!B>>!EBADB8>FG@NDCT!BTFCHGFGBRFN!WDHQDC!B!GSFRDMDR! FCEDALC=FCH>!8F!FGHB8>DGQFN;!&CNDEDN@B>!8FQBEDLAG!LM!BTFCHG!RBC!RLCHAD8@H F!HL! HQF!T>L8B>!8FQBEDLA!LM!HQF!LEFAB>>! G9GHF=;!"FCRFBHDLC!RBC!8F!RLCGDNFAFN!BG ! HQF! 8@D>NDCT!8>LR_!LM!B!G9GHF=; ! !HHE8?:786;=,6C,:F<;7 K A:=DRBHDLCG!LM!/$(!GSBC!BRALGG!B!NDEFAGF!ABCTF!LM!NL=BDCG!kIY , IhH@AB>!HL!8DL>LTDRB>!G9GHF=G!BCN!DCR>@NF!

PAGE 34

IJ ! ! NFHFA=DCDCT!HQF!G@RRFGG!LM!SAL=LHDLCB>!RB=SBDTCGHQRBAF!G9GHF=G;!4CF!LM!HQF!D CDHDB>! BSS>DRBHDLCG!LM!BTFCH , 8BGFN!=LNF> DCT!WBG!@GFN!HL!SAFNDRH!HQF!GSAFBN!LM!/&'2!khPl;!&H!QBG!B>GL! 8FFC!@GFN!G@RRFGGM@>>9!DC ! BSS>DRBHDLCG!DCR>@NDCT!FRLCL=DRG!kPKlDR!SL>DR9DMFABHDLCLT9!BNBSHBHDLCDRBHDLCG!LM!BTFCH , 8BGFN!=LNF>DCT!QBEF!B>GL! 8FFC!@GFN!HL!GH@N9!Q@=BC!>FBACDCT!BCN!RLTCDHDLC!kKJ9G!QBEF ! 8FFC!@GFN!HL!=LNF>!HQF!NF=BCN!MLA ! BCN!BEBD>B8D>DH9!LM! WBHFA!kOYl!BG! SBAH!LM!ADG_!=BCBTF=FCH!N@ADCT!B!NDGBGHFA;!)GDCT!HQDG!=LNF>F!HL! RL=F!@S!WDHQ!FMMFRHDEF!M>LLN!=BCBTF=FCH!SALRFN@AFG!kOY l ! BCN< ! LC!B!TABCNFA!GRB>FDCT!DG!AFTBANFN! BG!HQF!=LGH!G@DHB8>F!BSSALBRQ!HL!GH @N9!RL=S>F^! BNBSHDEF!G9GHF=G!Z3/2[!kIUDH9!HL!BRRL==LNBHF!RL=S>F^! N9CB=DRG!BCN!GHA@RH@AFG!DC!BC!FMMFRHDEF!=BCCFA;!%FRFCH>9HD , BTFCH!G9GHF=G!WFAF!@GFN!HL! =BCBTF!HQF!RBA8LC!MLLHSADCH!WDHQ DC!B!RLASLABHF!FCEDALC=FCH;!+QDG!WB G!NLCF!WDHQ!HQF! SBAHDRDSBHDLC!LM!B!QFHFALTFCFL@G!G9GHF=!BCN!RLTCDHDEF!BTFCH , 8BGFN!RL=S@HDCT!kKJHD , BTFCH!G9GHF=G!BAF!AFBRHDEF!HFRQCD?@FG!HQBH!BAF!H9SDRB>>9!@GFN!HL!GH@N9!HQF!8FQBEDLA! BCN!HQF!F=FATFCH!SBHHFACG!LM! GWBA=!G9GHF=G!G@RQ!BG!BCH!RL>LCDFG! BCN!BCD=B>!M>LR_G;!+QF! RL=S>F^!8FQBEDLA!LM!M>LR_DCT!8DANGFL9!HQAFF!GD=S>F!AFBRHDEF!A@>FG!HL!RAFBHF!HQF! LEFAB>>!M>LR_DCT!8FQBEDLAX!BHHABRHDLCGDLC!kKYl;!/!C@=8FA!LM!GH@NDFG!kKY , gOl! @HD >D]F!BTFCH , 8BGFN!=LNF>G!HL!GH@N9!HQ F!FMMFRHG!LM!BCD=B>Gc!FCEDALC=FCHG!LC!HQF!GWBA=!G9GHF=Gc! MLABTDCT!GHABHFTDFG;!+QF!=@>HDS>F!BGSFRHG!LM!BCD=B>!8FQBEDLA!=B_F!DH!BC!DNFB>!G@8aFRH!LM ! GH@N9! @GDCT!/$(!BSSALBRQFG;!7QFAFBG!NFRFCHAB>D]FN!BCN!GF>M , LATBCD]FN!CBH@AB >!G9GHF=G!BAF!_CLWC!MLA!

PAGE 35

IO ! ! HQFDA!RL>>F RHDEF!8FQBEDLAG@NF!RL>>FRHDEF!NFRDGDLC , =B_DCT< ! B!TAL@S!LM!BCD=B>G!RBC! =B_F!LSHD=B>!RQLDRFG!WDHQL@H!SFAMFRH!FCEDALC=FCH!_CLW>FNTF!LA!>FBNFAGQDS!kKY!DCGFRH!RL>LCDFG!G@RQ!BG!BCHG!QBEF!B C!B8D>DH9!HL!RQLLGF!HQF!8FGH!B=LCT! GFEFAB>! AL@HFG!LM!BRHDLCm!B!RQLDRF ! WQDRQ!DG!8BGFN!LC!HQF!_CLW>FNTF!TBDCFN!B=LCT!B>>!DCNDEDN@B>G!kKK , gOl;! -BRQ!BCH!QBG!>D=DHFN!>LRB>!DCMLA=BHDLC!BCN!B!GFH!LM!A@>FG!HL!=B_F!NFRDGDLCG!BCN!@GFG!DCNDEDN@B>! =F=LA9!BCN!SQFAL=LCF ! RL==@CDRBHDLC!HL!BRQDFEF!RL>>FRHDE F!MLABTDCT!8FQBEDLA;!/CH!RL>LCDFG! LSFABHF!WDHQL@H!RFCHAB>!RLCHAL>LRB>!DCHFABRHDLCG!WDHQ!FBRQ!LHQFA! kKUl;!+QF!>LRB>!DCMLA=BHDLC!_CLWC!89!FBRQ!BCH!DG!8BGFN!LC!SLGDHDEF!MFFN8BR_LC9!BMHFA!DH!MDCNG!MLLN!kKY9!=LNF>FN!@GDCT!/$(!BCN!RBC!@>HD=BHF>9!>FBN!HL!B!SAFNDRHDLC!LM!HQF! 8FQBEDLA!LM!HQF!BCH!RL>LC9; ! 5AFEDL@G!AFGFBARQ!kKYl!QBG!D=S>F =FCHFN!BCHGc!MLABTDCT!GHABHFTDFG!BG ! NDGHAD8@HFN!GFBARQ!B>TLADHQ=G!DC!AL8LHDR!GWBA=G;!&C!L@A!WLA_!kOJIl!HL!GD=@>BHF!HQF!BCH!RL>LC9!RL=S>F^!G9GHF=!BCN!DCNDEDN@B>!BCHcG! NFRDGDLC , =B_DCT!BCN!MLABTDCT!8FQB EDLAG;!+QF!GD=@>BHDLC!=LNF>!SALEDNF G!HQF!B8D>DH9!HL!TFCFABHF! R@GHL=D]FN!RL=S>F^!BCH!FCEDALC=FCHG!BCN!HL!F^S>LAF!HQF!DCHFABRHDLC!8FHWFFC!HQF!BCHGc! FCEDALC=FCH!MFBH@AFG!BCN!HQFDA!8FQBEDLAG; ! +QF ! 8FCFMDHG!LM ! BTFCH , 8BGFN!=LNF>G!BAF!G@RQ!HQBH!HQF9!BAF!@GFN ! DC!EB ADL@G!BSS>DRBHDLCG;! /MHFA!HQF!RAFBH DLC!LM!BC!BTFCH , 8BGFN!=LNF>F!HL!F^S>LAF!CFW!ND=FCGDLCG!LM! SAL=DCFCH!BSS>DRBHDLCG!LM! /$(G ! DC!HQF ! M@H@AF;!&H!DG!B>GL!SLGGD8>F!HL!RL=8DCF!BTFCH , 8BGFN!=LNF>G! B>LCT!WDHQ!LHQFA!GD=D>BA!=LNF>G; ! &,!B76G:7: , 1 @=FAL@G!GH@NDFG!QBEF!8FFC!BD=FN!BH! LSHD=D]DCT!HQF!@GF!LM!RF>>@>BA!B@HL=BHB!Z3/[!kOi , I J !GHA@RH@AF!BG!DHG!MDAGH!D=SLAHBCH!SADCRDS>F!BCN!>LRB>!DCHFABRHDLC!BG!

PAGE 36

II ! ! HQF!GFRLCN!D=SLAHBCH!SADCRDS>F!kOiF!LM!B!RQFR_FA8 LBAN>!RBC!8F! RB>>FN!BC!D CNDEDN@B>!ZHQF!MDAGH!SADCRDS>F[!RQFR_FA< ! BCN!WF!_CLW!HQBH!FEFA9!RF>>!WD>>! QBEF!CFDTQ8LAGF[! kOKLRB>!DCHFABRHDLC!=FBCG ! HQBH!HQF!DCHFABRHDLC!DG!>D=DHFN! HL ! DHG!CFBA89!RF>>G;!+QDG!H9SF!LM!CFDTQ8LAQLLN!RBC!8F!RLCGDNFAFN!DM!RF>>!RL==@CDRBHDLC!DG!>D=DHFN! HL!LC>9!ML@A!LM!DHG!CFDTQ8LAG;!$@H!HQF!H9SF!BCN!ABCTF!LM!HQF!CFDTQ8LAQLLN!RBC!8F!RQBCTFN>!8ADCT! RQBCTFG!HL!HQF!AFG@>HG!LM!HQF!3/!GHA@RH@AFm!QFCRFH , LADFCHFN!GH@N9!RBC!8F! RBAADFN!L@H;!4CF!SBAB=FHFA!HQBH ! NFMDCFG!HQF!WLA_DCT!SBHHFACG!LM!HQ F!RF>>@>BA!B@HL=BHB!DG!HQF! N9CB=DR! LA! GHBHDR!GHBHF ! LM!HQF!RF>>!kOJi>G!RBC!RQBCTF!HQFDA!GHBHFG!BCN`LA!>LRBHDLC ; ! & M!LCF! LM!HQFGF!HQDCTG!RQBCTF!GHA@RH@AF!ZHQF!RQFR_FA8LBAN[!WD>>!RQBCTF!BCN! HQF!DCHFABRHDLC!WD>>!8F!BMMFR HFN!kOhH , LADFCHFN!CBH@AF!LM!3/!BG! B!AFGFBARQ!HLL>!DC!B!C@=8FA!LM!GRFCBADLG!DCEL>EDCT ! QFBED>9!RALWNFN!>LRBHDLCG>! =BHRQFG!BCN!BDASLAHGBCFG!kOi , I J >@>BA!B@HL=BHB!=LNF>G!BAF!WDNF>9!@GFN!WQFC!BCB>9]DCT!RL=S>F^!G9GHF=G!kOOODRBHDLC!HQBH!AFM>FRHG!RL=S>F^!RQBCTFG!DC!HQF!BGSFRHGBHFN>@>BA!B@HL=BHB!=LNF>DCT!DG! B!SAFMFAAFN!BSSALBRQ!kOi >LWG ! =BC9!=BHQF=BHDRB>!BCN!HQFLAFHDRB>!=LNF>G!HL ! G@RRFGGM@>>9!F>@RDNBHF!DCMLA=BHDLC!B8L@H ! B!C@=8FA! LM!RL=S>F^!G9GHF=G!kOJYl!_DCTNL=!HL!HQF!RQBCTFG!DC!HQF! Q@=BC!8LN9!LC!B!RF>>@>BA!> FEF>;!7DHQL@H!HQF!SAFGFC RF!LM!3/DCT!LM!RL=S>F^!RL>>FRHDEF! G9GHF=G!WL@>N!8F!NDMMDR@>H!kOUBATF!C@=8FA!LM!GH@NDFG!QBEF!R>FBA>9!DCNDRBHFN!QLW!HQF!

PAGE 37

IP ! ! SBABNDT=!RBC!8F!BSS>DFN!HL!MDCN!BCGWFAG!HL!B!>BATF!C@=8FA!LM!?@FGHDLCG!ABDGFN!WDHQDC!RL=S>F^! RL>> FRHDEF!G9GHF=G; ! 3F>>@>BA ! B@HL=BHB!QBEF!8FFC!BSS>DFN!HL!GH@N9!MLAFGH!MDAFG ! khODRBHDCT!HQF! DCRAFBGFN!MAF?@FCR9!LM!NAL@TQH!BCN!MDAFG ! SALEDNF G ! RA@RDB>!DCMLA=BHDLC!LC! SAFNDRHDCT!RBHBGHALSQDR!WD>NMDAF!FEFCHG;!&C!AFGFBARQ!RL CN@RHFN!89!0FLATL@NBG!FH ! B>;!kOIJlNMDAF!WBG!L8GFAEFN!HQAL@TQ!SBAB>>F>!3/!=FHQLN;!3F>>@>BA!B@HL=BHB!RBC!B>GL!8F!@GFN! HL!F^S>BDC!HQF!SADCRDS>FG!LM!R>L@N!RL=S@HDCT!kOil;!7QFC!DH!RL=FG!HL!>BATF , GRB>F!R>L@N!RL=S@HDCT! S>BHMLA=G!D G!FMMFRHDEF!DC ! BRQDFEDCT ! B!SFAMFRH!8B>BCRF!8FHWFFC!RL=S@HBHDLCB>! CLNFG; ! +QF!M>LLA!MDF>N!Z66[!=LNF>9!FMMFRHDEF!=FHQLN!MLA!GD=@>BHDLC!LM! BTFCHGc!N9CB=DRG!kUKEFG!BTFCHG!=LEDCT! GHLRQBGHDRB>>9 ! LC!>BHHDRFN!RF>>G!kOOIl ;!4CF!LM!HQF!BNEBCHBTFG! LM! HQF ! 66!=LNF>!DG!GD=S>DRDH9G!LM!3/!BCN!DG!RLCGHA@RHFN!DC!B!NDGRAFFH!BCN! =DRALGRLSDR!MLA=!kOIiDRBHDLCG!LM!HQDG!MLA=BH!DCR>@NF!HQF!=LEF=FCH!LM!B!GS FRDMDR!RF>>! 8FDCT!NDAFRH >9!SALSLAHDLCB>!HL!HQF!=LEF=FCH!LM!HQF!CFDTQ8LADCT!RF>>G;!/H!DHG!RLAFLLA!MDF>N!DG! RL=SLGFN!LM!B!TAL@S!LM!G@SFAD=SLGFN!RF>>G!kUK!BAF!HQF!GSAFBNG!L8GFAEFN!89!FBRQ!DCNDEDN@B>!RF >>!WDHQDC!HQF!TADNNG! kOOI>!L8GFAEBHDLC!LM!B>>!SBHQ!MDF>NG!DC!HQF!TADN!RBC!8F!@GFN!HL!F^S>BDC!G@RQ! SQFCL=FCB!BG ! HQF!CBEDTBHDLC!LM!SFNFGHADBCG!BG ! HQF!NFCGDH9!MDF>NG!QDTQ>DTQH!RALWNFN!BAFBG!DC!HQF! FCEDALC=FCH;!+WL!H9SFG ! LM!M>LLA!MDF>NG9!@GFN ! kOIgl;!+QF!GHBHDR! M>LLA!MDF>N!NLFG!CLH!RQBCTF!HQF!GHBH@G!N@ADCT!HQF!GHD=@>BHDLCLLA!MDF>N! RQBCTFG!HQAL@TQL@H!HQF!GD=@>BHDLC!SALRFGG;!+QF!GHBHDR!MDF>NG!NFGRAD8F!HQF!BHHABRHDEFCFG GX!F;T;>!DG! R>LGFA!HL!HQF!F^DH!SLDCHLLA!MDF>NG !

PAGE 38

IY ! ! DCNDRBHF!HQF!EDAH@B>!HABRF!HQBH!BTFCHG!>FBEF!kOIIl;!+QF!M>LLA!MDF>N!EB>@FG!RBC!8F!RLCGDNFAFN!BG!HQF! GSAFBN!HQBH!RBC!8F!ML@CN!DC!HQF!TADNBDC ! SQFCL=FCB!G@RQ!BG!CBEDTBHDLC!LM!SFNFGHADBCG!kOOOl;!7DHQ!HQF!SBHQ!MDF>NGB8>F! SBHQ!HL!B!TDEFC!NFGHDCBHDLC!DG!L8HBDCFNNG!QDTQ>DTQH!RALWNFN!BAFBG!DC!HQF! FCEDALC=FCH;!+QF!M >LLA!MDF>N!8BGFN!LC!3/!D G!RLCGHA@RHFN!DC!NDGRAFHF!BCN!=DRALGRLSDR!MLA=!kOIil;! &C!B!SFNFGHADBC!GD=@>BHDLCG ! BAF!SALEDNFN!WDHQ!HQF!B8D>DH9!HL!=LEF!BCN!DCHFABRH!B>LCT! WDHQ!HQF!CFDTQ8LADCT!RF>>G;!-EFA9 ! GHFS!LM!HQF!RF>>G!DG!NFHFA=DCFN!WDHQ!HQF!BGGDGH BCRF!LM!B!TDEFC!GFH! LM! A@>FG; ! &>6LD,16D9!GH@NDFN!khK!DC!BELDNDCT!GL=F!GRFCBADLG!HQBH! RL@>N!QBEF!8FFC!SAFEFCHFN!QBN!HQFA F!8FFC!BC!FBA>DFA!BCHDR DSBHDLC!kUO@NDCT!HQF!HFCNFCR9!HL!=LEF!MAL=!DCGHBCRFG!LM!NDGLATBCD]FN!MLA=G! HL!8FDCT!LATBCD]FN!WQFC!B!RL==LC!S@ASLGF!DG!8FDCT!S@AG@FN!kOOJl;!&C!G@RQ!B!RBGFFN! @GDCT!HQF!BSSALBRQFG!NFGRAD8FN!B8LEF; ! (LNF>DCT!RALWN!N9CB=DRG!DG!RL=S>DRBHFN!89!HQF!8FQBEDLA!LM!DCNDEDN@B>G!WQD>F!DC!B!GHBHF! LM!SBCDR!kOIUFG!WD>>!=LEF!HLWB ANG!HQFDA!LWC!TLB>!ABHQFA! HQBC!HQF!RL>>FRHDEF!TLB>!LM!HQF!RALWN;!+QDG!DG!HQL@TQH!HL!LRR@A!8FRB@GF!SFAGLCB>!=F=LA9!DG! =LGH>9!@GFN!HL!MDCN!HQF!GQLAHFGH!FGRBSF!AL@HFG!DC!F=FATFCR9!GDH@BHDLCG!kOYM!BCN!R L>>FRHDEF!8FQBEDLAG!BAF!8LHQ!RA@RDB>!MLA!RLCGDNFABHDLC! DC!GD=@>BHDLC!=LNF>DCT!MLA!FEBR@BHDLCG; !

PAGE 39

Ii ! ! +QFAF!BAF!NDMMFAFCH!MLA=G!LM!RALWNG!HQBH!BC9!=LNF>!GFF_G!HL!GD=@>BHF!TBHQFADCTG!kOKEFN!BHHABRHDLCF!B>HFACBHF!AL@HFG!HQBH!HQF9!=DTQH!FCHFAHBDC!B>LCT!HQF!WB9!kOJh>!LM ! HQFGF!MBRHLAG!=BA_!HQF ! 8FTDCCDCT!LM!B!GFF=DCT>9!DNFCHDMDB8>F!GD=@>BHDLC!HL! CLA=B>!SFNFGHADBC!=LEF=FCH!BCN!FEFCH@B>>9!SAFNDRHG!B!RALWN!=LEF=FCH!kOgG!BAF!@GFN!BG!MLA=B>!RL=S@HBHDLCB>!=LNF>G!HL!SAFNDRH!RALWN!N9CB=DRG;!+QFGF!N9CB=DRG! R BC!8F!HBR_>FN!MAL=!B!SF NFGHADBC!SLDCH!LM!EDFW!kUIlX ! O[ ! ! ! 5Q9GDRB>!BSSALBRQ ; ! &C!HQF!SQ9GDRB>!BSSALBRQFG!HQBH!BAF!G@8aFRH!HL!EBADL@G!MLARFG! HQBH!RBC!FDHQFA!8F!BHHABRHDLC!LA!AFS@>GDEF!kIUl;!7QDRQFEFA!HQF!MLARF@NF!bNDGHABRHDLCGe!DC!=LNF>DCT!GL>@HDLCG; ! I[ ! 3F>>@>BA!B@HL=BHB!BSSALBRQ ; ! +QDG!DG!B!8DL>LTDRB>!BCB>LT9!WQFAFDC!BC!BTFCH!DG!F?@BHFN!HL!LRR@S9!HQF!FCEDALC=FCH!a@GH!BG!RF>>G! NL!DC!>DEDCT!LATBCDG=G;!+QF!DC HFABRHDLCG!HQBH!SFNFGHA DBCG!FCTBTF!DC!BAF!R>BGGDMDFN!BRRLANDCT!HL!B! =FHQLN!AFMFAAFN!HL!BG!M>LLA!MDF>N!HABRFG!HQBH!DCM>@FCRF!HQF! HABCGDHDLCB>!BCN!=LEF=FCH!N9CB=DRG!LM!SFNFGHADBCG;!+QDG!=LNF>!DG!>D=DHFN9!LMMF A! GFSBABHF!SBHQG!LM!HQF ! SFNFGHADBCG;!"LWFEFALWG!BCN!NFCGDHDFG!BCN!HQF!8FQBEDLA!SBHHFACG!WQDRQ!HFCN!HL!8F!RL=S>F^!DC! GLRDB>>9 , DCN@RFN!MLARFG; ! P[ ! /TFCH , 8BGFN!BSSALBRQ ; !

PAGE 40

IK ! ! "FAF@FCRFN!89!A@>FG!LM! 8FQBEDLA!BCN!HQF!SBAB=FHFAG!BSS>DFN!HL!HQF!G9GHF=;!/G!G@RQDH9 , 8BGFN!BTFCH!WL@>N!AFSAFGFCH! B!GD=@>BHDLC!LM!SFNFGHADBCG!8BGFN!LC!B!RL=S@HBHDLCB> , NDGRAFHF!=LNF>; ! /TFCH , 8BGFN! GD= @>BHDLCG!QBEF!TBDCFN!SAL=DCFCRF!DC ! AFRFCH!9FBAG!N@F!HL!HQFDA!B@HLCL=9!BGSFRH! BCN!HQF!FMMDRDFCR9!LM!HQFDA!B8D>DH9!HL!=D=DR!Q@=BC!8FQBEDLA!89!@GDCT!GD=S>F!A@>FG!BCN!QF@ADGHDRG! kYhl;!&C!/$(FG!HQBH!QBEF!HL!8F!@HD>D]FN!HL!B>>LW!MLA!HQFGF!=LNF> G!H L!8F!@GFN!DC! =LNF>DCT!RALWN!FEBR@BHDLCG;!+QFAFMLAF!HL!MBRD>DHBHF!HFGHDCT!DC!BSSALSADBHF! FCEDALC=FCHG;!+QFGF!A@>FG!BAF!BG!ML>>LWGX ! D[ !! ! +QF!/$(!=@GH!SALSFA>9!AFSAFGFCH!RLTCDHDLC!B8D>DH9!DC!Q@=BCG!kK9!RL=S> F^! Q@=BC!=LEF=FCHG!BCN!DCHFABRHDLCG!DC!RDHDFG ; ! DDD[ !! +QF9!GQL@>N!8F!B8>F!HL!AFEFAH!8FQBEDLAG!BG!Q@=BC!SFARFSHDLC!WQD>F!SALEDNDCT!WBACDCTG!MLA! SLHFCHDB>!ADG_G!BCN!HQAFBHG; ! /SS>DRBHDLCG!LM!BTFCH , 8BGFN!G9GHF=G!DC!HFGHDCT!FEBR@BHDLCG!LM!WDNFGSAFBN!NDGBGHFAG!G@ RQ! BG!M>LLNG!QBEF!8FFC!@8D?@DHL@G>9!BSS>DFN!kOYHG!LM!HQFGF!GH@NDFG!QBEF!SALEFC! MFBGD8>F!BCN!QFCRF!HLL>!DC!S>BCCDCT!MLA!ADG_!=BCBTF=FCH ! kOJOl;!2SFRDMDRB>>9S!DC!NFHFA=DCDCT!FEBR@BHDLC!SBHHFACG!DCMABGHA@RH@AF!BCN! DNFCHDM9DCT!CFFN!MLA!D=SALEDCT!R@AAFCH!F=FATFCR9!AFGL@ARFG;!+QF!SLHFCHDB>!LM!/$(!DG!>D=DH>FGGFG! LM!3ALWN!(LNF>DCT ! O[ ! 1 :?>6=?6H8?,=?:E< ! , ! 2@RRFGGM@>>9!=BCBTDCT!@A8BC!RALWNG!DC!RL=S>DRBHFN!NDGBGHFAG!DG! RQB>>FCTDCT ! BG!SALRFGGFG!@G@B>>9!LRR@A!BH!NDMMFAFCH!HF=SLAB>!BCN!GSBHDB>!GRB>FG;!+QF!=BRA LGRLSDR! =LNF>!GFF_G!HL!LEFARL=F!HQFGF!F^HFCGDEF>9!GSAFBN , L@H!ADG_G!89!RLCGDNFADCT!G@8 aFRHG!MAL=!B! SFAGSFRHDEF!HQBH!DCR>@NFG!B>>!SALRFGGFG!kUIl;!+QF!=LNF>!LM!=BRALGRLSDR!GRB>FG!DG!NFADEFN!MAL=!B!

PAGE 41

Ig ! ! =BRALGRLSDR!SALRFGG!WQDRQ!=BSG!HL!HQF!MBRH!HQBH!=LNF>G!LC!HQDG ! GRB>F!MLR@G!LC!BRR@=@>BHDLC!LM! EB>@F!ABHQFA!HQBC!GDCT@>BA!FCHDHDFG!F?@DEB>FCH!HL!B!G DCT>F!SFNFGHADBC; ! I[ ! 18?>6=?6H8?,=?:E< ! , ! +QDG!GRB>F!DG!AFGSLCGD8>F!MLA!HQF!NFMDCDHDLC!LM!HQF!DCHADRBHF!MDCF!NFHBD>G!LM!B! SFNFGHADBCcG!=LEF=FCHG!kUPl;!+QFGF!N9CB=DRG!BAF!8B GFN!LC!RF>>@>BA!B@HL=BHB!WQFAFDC!B! SFNFGHADBC!DG!B!GDCT>F!NDGRAFHF!L8aFRH;!+QF!=LEF=F CHG!LM!SFNFGHADBCG!BAF!GD=@>BHFN!LC!B!I'! RF>>@>BA!TADN;!%@>FG!BAF!NFMDCFN!HL!DCM>@FCRF!HQF!=LEF=FCHG!LM!HQF!NDGRAFHF!L8aFRHG!HQBH!MLA=!HQF! RALWN; ! *FEF>G!LM! 3 ALWN! ( LNF>DCT ! O[ ! #7>:7BHDLC!LM!B!S>BC!BCN!HQF!MDCB>!L8aFRHDEFG!BAF!NABWC!DC! HQDG!>FEF>!kIil; ! I[ ! $:?78?:E,E<9DHBHF!HQF!S>BC!BAF!RL=S@HFN!BCN!GRQFN@>FN!kIgl; ! P[ ! *H<>:786;:E,E<9FEF>!B>>LWG!MLA!SQ9GDRB>!F^FR@HDLC!LM!HQF!BRHDEDHDFG!>BDN!L@HBA!FCEDALC=FC H!kIKl; ! $>:CC8?,16DLW!RAFBHFG!B!N9CB=DRB>>9!RL=S>F^!G9GHF=!GDCRF!DH!DCEL>EFG!B!CLC>DCFBA! DCHFABRHDLC!LM!=BC9!DCNFSFCNFCH!EFQDR>FG!WDHQ!>BATF>9!B@HLCL=L@G!8FQBEDLA!k hiFBN!HL!F=FATFCH!8FQBEDLAG!HQBH!S ALN@RF!NDMMFAFCH!_DCNG!LM!HABMMDR! SAL8>F=G;!6LA!F^B=S>FFG!RBC!8F!MLA=FN!WQFC!B!TAL@S!LM!EFQDR>FG! DG ! GH@R_!8FQDCN!LCF!NADEDCT!G>LW>9;!/!>BATF!C@=8FA!LM!=LNF>G!QBEF!8FFC!NFEF>LSFN!BCN!BSS>DFN!HL! GD= @>BHF!HQF!SALRFGG!LM!EFQDR@>BA!N9C B=DRG;!+QFGF!GH@NDFG!B>GL!FMMFRHDEF>9!GD=@>BHF!HQF!RL=S>F^! 8FQBEDLAG!LM!HABMMDR!BCN!SFLS>F!DC!L@HNLLA!LA!DCNLLA!GRFCBADLG;!+QF!AFG@>HG!LM!HQFGF!GH@NDFG!RBC! QF>S!AFGFBARQFAG!HL!NFEF>LS!CFW!WB9G!HL!DCHFTABHF!BCN!DCRLASLABHF! HQF!DCRAFBGDCT!BEBD>B8D>DH9!LM! B@H LCL=L@G!EFQDR>FG!BCN!HQF!EDAH@B>!NBHB!k hiBA>9!FMMFRHDEF!

PAGE 42

Ih ! ! RL=S@HBHDLCB>!GD=@>BHDLC!=FHQLN!DG!B!NFRFCHAB>D]FN!=@>HD , BTFCH!G9GHF=!Z(/2[9!RL==@CDRBHF!WDHQ!DHG!D==FNDBHF!CFDTQ8L ADCT!BTFCHG;!+QF!/$(!BSSALBRQ!DG!B ! MLA=!LM!LSHD=D]BHDLC!LM!DCNDEDN@B>!GL>@HDLCG!BCN!BSS>DFG!HL!G9GHF=G!LM!DCHFABRHDCT!BTFCHG;!+QF!BTFCHG!DC!HQF!NFRFCHAB>D]FN!G9GHF=!QBEF!CL!NDAFRH!DCMLA=BHDLC!B8L@H! HQFDA!T>L8B>!SLGDHDLC!8@H!NL!Q BEF!DCMLA=BHDLC!B8L@H!HQFDA!CFBA89 ! CFDTQ8LAG!BCN!HQFDA!FCEDALC=FCH! >LRB>>9!k P 9!@GF!HQDG!>LRB>!_CLW>FNTF!HL!RL>>FRHDEF>9!RLCGHA@RH!B! RLLANDCBHF!G9GHF=;!&C!/$(F! G9GHF=G!RL=SLCFCHGD]FN!CBH@AF < ! WQDRQ! DG!B8>F!HL!RBSH@AF!RL=S>F^!N9CB=DRG!BCN!GHA@RH@AFG ! kO YP DHFABH@AF!HQBH!8LHQ!/$(!BCN ! RL=S>F^!CFHWLA_G!BAF!8BGFN!LC!RL=S>F^DH9! HQFLA9;!+QF!/$(!BSSALBRQ!QBG!8FFC!G@RRFGGM@>>9!BSS>DFN!HL!B!WDNF!ABCTF!LM!GRFCBADLG!DCR>@NDCT! =D>DHBA9!HABDCDCTNDCT!FEBR@BHDLC 9GDG!LM!NDTDHB>!TB=FG!kO PJ F=FCHBHDLC!LM!BTFCH , 8BGFN!MAB=FWLA_!MLA!HQF!BCB>9GDG!LM!LHQFA!RL=S>F^!GLRDB>!G9GHF=G@NDCT!HABMMDR!N9CB=DRGLWG;!7DHQ!HQDG! _DCN!LM!B!MAB=FWLA_GL!SLGGD8>F!HL!=LNF>!BCN!GD=@>BHF!HQF!RL=S>F^!DCHFABRHDLCG!HQBH!HB_F! S>BRF!8FHWFFC!QL=LTFCFL@G!BTFCHG!BCN!EFQDR>FG!DC!ALBN!HABMMDR!kO PI !=BHQF=BHDRB>!=LNF> G!BAF!BEBD>B8>F!HL!GD=@>BHF!HAB MMDR!aB=G!BCN!TFH!B!R>FBA! @CNFAGHBCNDCT!B8L@H!HQFDA!LRR@AAFCRF!BCN!RLCGF?@FCRFG!kUPl;!+QF!LCFG!8BGFN!@SLC!HQF!SADCRDS>FG! LM!3/!QBEF!AFRFDEFN!B!>LH!LM!BHHFCHDLC!kUh!BSS>DRBHDLCG!LM! 3F>>@>B A!/@HL=BHB!DG!DC!HQF!GD=@>BHDLC ! LM!GHAFFH!HABMMDR!RLCHAL>;!+QF!3/!=LNF>!DG!BC!FMMFRHDEF! BSSALBRQ!HL!F^S>BDC!HQF!SADCRDS>FG!LM!HABMMDR!aB=GF!8@D>NDCT!HQF!HQFLA9!MAL=!M@CNB=FCHB>G;!

PAGE 43

IU ! ! 3F>>@>BA!/@HL=BHB!GD=@>BHDLCG!LM!RL=S>F^!CFHWLA_!N9CB=DRG!SALEDNF!F^RF> >FCH!BGGDGHBCRF!BCN! BNN!B!QDTQF A!>FEF>!LM!FMMDRDFCR9!DCHL!HQF!NFGDTC!LM!HABCGSLAHBHDLC!MBRD>DHDFG;!+QF!3/!=LNF>!DG! B! G@MMDRDFCH>9!BNEBCRFN!BCN!RL=S>F^! =LNF> ; ! & H!QBG!8FFC!WDNF>9!@GFN!BG!B!=BHQF=BHDRB>!HLL>!HL! GH@N9!B!G9GHF=!WQFAFDC!HQFAF!BAF!QDTQ!C@=8FAG!LM ! BTFCHG!HQBH!BAF!RLCGHBCH>9!RQB CTDCT!HQFDA!GHBHFG! kUPF!LM!G@RQ!B!GRFCBADL!DG!HABMMDR!LC!QDTQWB9G!LA!B! >LRBHDLC ! WQFAF!HQFAF!BAF!HLL! =BC9!EFQDR>FG!SAFGFCHD=DHG!HQFDA!=LEF=FCHDCT!BSSALBRQ!QBG!SALEFC!@GFM @>!WQFC!HQF!ABHF!LM!RQBCTF!DC!B!G9GHF=! 8FTDCG!G>LW>9!BCN!HQFC!DCRAFBGFG!LEFA!HD=F!kOIYl9!HQF!8AB_FG!BCN!RB@GF!B! RQBDC , AFBRHDLC!G>LWNLWC!LM!HABMMDR!8FQDCN!HQF=; ! /!>BATF!C@=8FA!LM!GH@NDFG!WFAF!RLCN@RHFN ! DC!LANFA!HL!TFH!B!R>FBA! @CNFAGHBCNDCT!LM!HQF!N9CB=DR! AL@HDCT , SAL8>F=DCF!LA!AFB> , HD=F!.FQDR>F!%L@HDCT!5AL8>F=!Z.%5[!k Ohi l;! +QF!SAL8>F=!QBG!8FFC!BCB>9]FN!MAL=!=BC9!NDMMFAFCH!BCT>FG!HL!NFHFA=DCF!DM!B!GL>@HDLC!RBC!8F! NFADEFN;!4CF! LM!HQF!=LGH! GDTCDMDRBCH!NFRDGDLCG!DC!HQF!N9CB=DR!AL@HDCT!GL>@HDLC!DG!HL!@CNFAGHBCN!QLW! RFAHBDC!NFRDGDLCG!WD>>!8F!=BNF!BCN!HQF!D=SBRH!LM!HQLGF!NFRDGDLCG!k h hDCT!LC!HQF!ALBNG!ZF;T;F!SQLCFG!BCN!T>L8B>!SLGDHDLCDCT! G9GHF=G[;!+ QFC >!8F!B8>F!HL!SAFEFCH!NF>B9G!HQBH!HQF9!WL@>N!LHQFAWDGF!F^SFADFCRF!N@F! HL!B!HABMMDR!RLCTFGHDLC;! ! '@ADCT! BC!BRRDNFCH< ! =LGH ! NADEFAG!HFCN!HL!>LL_!MLA!B>HFACBHDEF!AL@HFG;!/H!HQF!HD=F!HQF!NADEFA!GFF_G! HL!GF>FRH!BC!B>HFACBHDEF!AL@HFFBA!@CNFAGHBCNDCT!LM!HQF!F^DGHDCT!HABMMDR!RLCNDHDLCG!LC!HQF! ALBN!DG!F^HAF=F>9!@GFM@>!kUPB8>F! 052!CBEDTBHDLC!BSS>DRBHDLCG!BCN!G9GHF=G!SALEDNF!F^RF>>FCH!BGGDGHBCRF;!"LWFEFACFGG!DG!

PAGE 44

PJ ! ! =DHDTBHFN!8FRB@GF!FEFA9LCF! WD>>!8F!ML>> LWDCT!HQF!GB=F!NFHL@AHG!DC!HABCGMFAADCT!HQF! HABMMDR!RLCTFGHDLC!kPFAHFN!B8L@H!B>HFACBHDEF!AL@HFG!89! HQF!F^RQBCTF!LM!NBHB!B=LCT!HQF!LHQFA!NADEFAG!DCEL>EFN;!2LF! GQL@ >N!AFAL@HF!CFFNG!HL!8F!=BNF!WDHQ!NBHB!TBHQFAFN!MAL=!HQF!F^DGHDCT!CFHWLA_!HQAL@TQ!GFCGLAG; ! /GGDGHDCT!NADEFAG!DC!MDCNDCT!HQF!GQLAHFGH!SLGGD8>F!B>HFACBHDEF!AL@HFG!BMHFA!BC!BRRDNFCH!DG!a@GH!LCF! LM!=BC9!L8aFRHDEFG!LM!HABMMDR!DCMLA=BHDLC!G9GHF=G;!7QF C!HQF!AF?@DA FN!DCMLA=BHDLC!DG!=BNF! BEBD>B8>F>B8LABHDEF>9!>LL_!MLA!B>HFACBHDEF!AL@HFG;!7QFC!RL>>B8LABHDCT!WDHQ!FBRQ!LHQFA!HQAL@TQ!HQF!GB=F! G9GHF=>!CLH ! 8F!NDAFRHFN ! HL!a@GH!LCF!GSFRDMDR!AL@HF!BG!BC!LANDCBA9!052!G9GHF=!NLFG;! +QDG!AL@HDCT!=FHQLN>FN!N9CB=DR!LA!NDGHAD8@HFN!AL@HDCT!k Uh lLAFN!HQAL@TQ!B! C@=8FA!LM!SBSFAG!kUDCT! RL=S>F ^!HABCGSLAHBHDLC!CFHWLA_G!DC!B!=BCCFA!SFA=DHHDCT!EFQDR>FG!HL!RL==@CDRBHF!WDHQ!LHQFA! EFQDR>FG!HL!TBDC!B!8FHHFA!BGGFGG=FCH!LM!HQF!R@AAFCH!GHBHF!LM!CFBA89!ALBN!CFHWLA_G;!+QDG! RL==@CDRBHDLC!SALEDNFG!NADEFAG!WDHQ!AFB> , HD=F!ALBN!NBHB < ! BCN!BC!FCQBCRFN ! BWBAFCFGG!L M!HQF!ALBN! CFHWLA_!HL!QF>S!HQF=!GFF_!FMMDRDFCH!B>HFACBHDEF!AL@HFG
PAGE 45

PO ! ! &5!4$(%,))), , , 1*'(/,'(#&%)4$)*+ , &C!HQDG! NDGGFAHBHDLC HD , >FEF>!=@>HD , GHBTF!BTFCH , 8BGFN!=LNF>!Z(*(2 , /$([!DG! SAFGFCHFNLDHFN ! k IO , IP l ! HL!SALEDNF!B!=@>HD , >B9FAFN!NFRDGDLC!G@SSLAH!G9GHF=!DC!RBGFG!LM!RALWN`HABMMDR ! RLCTFGHDLCG!N@ADCT! NBCTFAL@G ! RBGFG;!+QF!SAFGFCHFN!WLA_!DCHALN@RFG!B!=@>HD , >FEF>FN!=LNF>!WQFAF!RALWN`HABMMDR! N9CB=DRG!B AF!NDEDNFN!DCHL!HQAFF!=BDC!>FEF>G!LM!NFRDGDLC!=B_DCTX! ZO[! GHABHFTDR;!+QF!S>BCCDCT!MLA!SAF , HADS!LM!HQF!AL@HF!BCN!HQF!MDCB>!NFGHDCBHD LC!DG!NFGDTCFN!BH!HQF! GHABHFTDR!>FEF>;!'@ADCT!GHABHFTDR!SALRFGG!RDAR@=GHBCRFG;! 'FRDGDLCG!MLA!HQF!GQLAH!HFA=D_F!BELDNDCT!L8GHBR>FG!LA!RQBCTDCT ! AL@HFG!NFSFCNDCT!LC!HQF!AFB>! GDH@BHDLC!>FEF>;!/NNDHDLCB>!DCMLA=BHDLC!B8L@H!HQF!CFHWLA_!G@RQ!BG!HQF! M>LW!LM!BTFCHG!DG!BEBD>B8>F! BH!HQDG!SLDCH;!+QF!LSFABHD LCB> ! >FEF>!AFSAFGFCHG!HQF!BTFCHGc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

PAGE 46

PI ! ! =BRALGRLSDR!SQFCL=FCB!LM!HQF!RL=S>F^!CFHWLA_!HQBH! WL@>N!8F!NDMMDR@>H!HL!=LNF>!DC!3/!MAB=FG;! +QDG!>B9FA!AFSAFGFCHG!HQF!RLCCFRHDLCG!8FHWFFC!DCHF>>DTFCH!T@DNF!BTFCHG! HQBH! FCQ BCRF!HQF!NFRDGDLCG! MLA!HQF!WQL>F!G9GHF=!BG!DH!WD>>!8F!NFGRAD8FN!8F>LW;!&CGHFBN!LM!RLCGDNFADCT!NDGRAFHF!BCN!GDCT@>BA! L8a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c!8FQBEDLAGFG!BCN!RLCNDHDLCG!LM!>LRB>!FCEDALC=FCH;!/G!B!AFG@>HB9FAFN!GH A@RH@AF!LM!HQF!SALSLGFN!G9GHF=; ! , 28FB>< ! M N ! (@>HD , >FEF>!=@>HD , GHBTF!BTFCH , 8BGFN!=LNF>!Z(*(2 , /$([!G9GHF=!LEFAEDFW; !

PAGE 47

PP ! ! ! 28FB>< , O N ! +QF!HWL!> B9FAG!LM!(*(2 , /$(!=LNF> ; ! +QF!HWL!=BDC!=BCBTFN!RL=SLCFCHG!LM!HQF!=LNF>!BAF!HQF! (!Q'9:!B(!= BHDLC!HB_FG!S>BRF>!D=SBRH!HQF!WQL>F! G9GHF=;!/$(G!BAF!RL=SLGFN!LM!BTFCHG>LWG!AFB> , HD=F!G9GHF=!8FQBEDLA! MFFN8BR_; ! (;98>6;G<;7, &6;C8FB>:786;,8;, 7 @<,16DBHDLC!DG!HQF!RLCMDT@ABHDLC!LM!HQF!GD=@>BHDLC! FCEDA LC=FCH;!+QF!FCEDALC=FCH!R L=SLCFCH!LM!HQDG!/$(!=LNF>!NFMDCFG!HQF!F>F=FCHG!LM!HQF! SQ9GDRB>!GSBRFNDCTGL! DCR>@NFG!DCHALN@RHDLC! LM!HQF!ML>>LWDCT!RL=SLCFCHGX!AFSAFGFCHBHDLC!LM! HQF! FCEDALC=FCH
PAGE 48

PY ! ! SLHFCHDB>!M>LLA!MDF>NG;!+QF!FCEDALC=FCH!BAFB!DG!AFSAFGFCHFN!@GDCT!B!3/!>B9FA!RF>>G;!+QF!GD=@>BHDLC!FCE DALC=FCH!DG!SAFGFCHFN!BG!B! TADN !BAAB9!LM! ! ! n! ! ! RF>>G;!&H!DG!BGG@=FN!HQBH!FBRQ!RF>>!DG!LM!G?@BAF!GQBSF!BCN!LM!B!GD]F!HQBH! RBC!8F!LRR@SDFN!89!LC>9!LCF!BTFCH!ZEFQDR>F!LA!SF NFGHADBC[; ! +QAFF!GSFRDMDR!H9SFG!LM!RF>>G!QBEF!8FFC!NFGDTCBH FN!DC!B!>BHHDRF ! kOOIl ! LM!B!CLC , QL=LTFCFL@G!RF>>@>BA!B@HL=BHLCX ! L8GHBR>F!RF>>GFm!HBATFH!RF>>GF!RF>>G9!RF>>G!8F>LCTDCT!HL! HQF!>BGH!HWL!H9SFG!RBC!8F!BRRFGGFN!89!HQF!BTFCHG;!+QF! >BHHDRF!DG!G@AAL@CNFN!89!L8GHBR>F!RF>>G!F^RFSH!MLA!B!C@=8FA!LM!HBATFH!RF>>G!WQFAF!BTFCHG!RBC!LC>9! FEBR@BHF!HQF!8@D>NDCT!HQAL@TQ!HQFGF!RF>>G; ! &C!HQF!SALSLGFN!=LNF>LLA!MDF>NG! BAF!RLCGDNFAFN!k OJU@NFG!8LHQ!HQF!HBATFH!MDF>NG!HQBH!BAF!AFGHADRHFN!HL!B!GSFRDMDR!BAFB!BCN!HQF!NDGHBCRF!MAL=! HQF!NFGHDCBHDLC!kO PO l;!+QF!GFRLCN ! DG!=BNF!L@H!LM!L8GHBR>F!MD F>NGGDEF! MLARF!k OOU l;!+QFGF!HWL ! M>LLA!MDF>NG!BAF!GHBHDR;!+QF!>BGH!H9SF!LM!M>LLA!MDF>N!DG!HQF!NFCGDH9!MDF>NF!RF>>! G@AAL@CNDCT!HQF!BTFCH!WD>>!RQ BCTF!B>LCT!WDHQ!HD=F!DC!LANFA!HL!BELDN!RL>>DGDLCG;!&C!BNNDHDL C!HL!HQF! BNEBCHBTF!LM!L8GFAEDCT!BTFCHGc!=LEF=FCH!HQAL@TQ!M>LLA!MDF>NGLW!LM!B! RL=S>F^!CFHWLA_ ,, ! RBC!R>FBA>9!8F!F^S>BDCFN!DC!HQF!RLCHF^H!LM!B!GSFRDMDR!FCEDALC=FCH;!+QF! SAF MFAAFN!=LEF=FCH!NDAFRHDLC!LM!HQF!SFLS>F!RBC!8F!F^B=DCFN!R>FBA >9!WDHQ!HQF!BGGDGHBCRF!LM!>LCT! ABCTFN!MLARFG ! k OI Il;!&C!MBRHLCT , ABCTF ! MLARF!HQBH!AFSAFGFCHG!BC!DCNDEDN@B>!RBC!TDEF!B!8FHHFA! @CNFAGHBCNDCT!LM!HQF!WB9!RALWN`HABMMDR!WL@>N!=LEF!HLWBANG!B!HBATFH;!+QDG!AFSAFGFCHG!HQF!>LRB>! MLARFN!DCRAFBGF!HQF!DC GHBCHBCFL@G!SAL8B8D>DH9!LM!=LEDCT!DC!B!TDEFC!NDAFRHDLC; !

PAGE 49

Pi ! ! &C!HQDG!=LNF>LLA!MDF>N!Z " ## [!DG!@GFN!HL!DCNDRBHF!HQF!NDGHBCRFG!HL!B!NFGHDCBHDLC!MLA! FEFA9!BTFCH!DC!HQF!FCEDALC=FCH;! "## ! EB>@F!DG!BGGDTCFN!HL!FEFA9!RF>>!HL!NFGRAD8F!HQF!NDGHBCRF!HL! HQF!FBA>D FGH!RQLGFC!HBATFH;!+QBH!=FBCG!LCF!M>LLA!MDF>N!DG!RL=S@HFN!MLA!FBRQ!BTFCH! HL!FBRQ!HBATFH! NFGHDCBHDLC;!+Q@GN!ML>>LW!HQF!GHBHDR!M>LLA!MDF>N!HLWBANG! HQBH!GSFRDMDR!HBATFH;!7F!@GF!HQF!WF>> , _CLWC!QF@ADGHDR!SBHQ , MDCNDCT! $ ! ! B>TLADHQ=!k OP K l!BCN! (BCQBHHBC!=FHADRG!HL!RL=S@HF!HQF!GHBHDR!WFDTQH!LM!R F>>G!DC!B!RF>>@>BA!FCEDALC=FCH;!(BCQBHHBC!BCN! 'Da_GHAB! kOP g l! =FHADRG!BAF!@GFN!MLA!HQF!BAFB!HQBH!RLCHBDC!L8GHBR>FG ; ! " LWFEFATLADHQ=!HL!RLCGHA@RH!B!GHBHDR!M>LLA!MDF>N! =B9!RLCG@=F!RLCGDNFAB8>F!HD=F!DC!>BATF!FCEDALC=FCHG;! &C! HQF ! =LNF>9! $ ! * =FHADR>!BG!'Da_GHAB!=FHADR!8@H!DG!FBGDFA!BCN!MBGHFA! HL!RL=S@HF!DC!LANFA!HL!NFHFA=DCF!HQF!GQLAHFGH!SBHQ!L@H!LM!=BC9!SLGGD8D>DHDFG!8FHWFFC!FBRQ!RF>>!HL! B!HBATF H!WDHQ!HQF!SAFGFCRF!LM!BA8DHABA9!L8GHBR>FG;!+L!RB>R@>BHF ! HQF ! $ ! * =FHADRDH9!TABSQ!DG! RLCGHA@RHFNm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
PAGE 50

PK ! ! DG!NFGRAD8FN!DC!MDEF!GHBHFG!BG!B!MDCDHF!GHBHF!=BRQDCF!Z62([!LA!GSBHDB>;!-BRQ!LM!HQFGF!GHBHFG!WD>>!8F! NFGRAD8FN!DC!NFHBD>! DC!HQF!ML>>LWDCT!GFRHDLCG; ! -BRQ!GHBHF!DC!HQF!MDCDHF!GHBHF! =BRQDCF!Z62([!AFSAFGFCHG!B!G@8 , =LNF>!ZGHBTF[!LM!HQF ! (*(2 , /$(!=LNF>!DCGDNF!HQF!=LNF>!AFSAFGFCHG!B! SBAHDR@>BA!8FQBEDLA!WQDRQ!DG!RLCGDNFAFN!BG!B!TFCFAB> , S@ASLGF!BR HDLC!LA!GFH!LM!BRHDLCG!HQBH!BC!BTFCH! SFAMLA=G;!+QF!G@8 , =LN F>!DG!NFGRAD8FN!@GDCT!B!SAFGRAD8FN!GFH!LM!GHBHFG!BCN!BRHDLCG;!/C!F^B=S>F!LM! B!TFCFAB>!H9SF!8FQBEDLA!WL@>N!8F!b6L>>LW!HQF!CFDTQ8LA!BTFCHe!LA!b6L>>LW! HQF! MBGHFGH!AL@HF ; e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

PAGE 51

Pg ! ! ! 28FB><,PN ! /!MDCDHF!GHBHF!=BRQD CF!Z62([!AFSAFGFCHBHDLC!RLAAFGSLCNDCT!HL!GHBHF!HABCGDHDLC!LM!HQF! BTFCHcG!8FQBEDLA ; ! &C!HQDG!=LNF>F!HL!>FBAC!MAL=!HQF!FCEDALC=FCH!ZHBG_!M L> >LW9! BNa@GH!HQF!CFHWLA_; ! &C! LANFA!HL!SFAMLA=!HQF!HBG_!FMMFRHDEF>99!>LRB>!BEBD>B8>F!DCMLA=BHDLC;!+QF!BTFCHG!BAF!SALEDNFN!WDHQ!HQF!B8D>DH9!HL!=LEF!BCN! DC HFABRH!B>LCT!WDHQ!HQF!CFDTQ8LADCT!RF>>G;!-EFA9!=LEF=FCH!DG ! NFHFA=DCFN!WDHQ!HQF!BGGDGHBCRF!LM!B! TDEFC!GFH!LM!A@>FG;!+L!SAL=LHF!HQF!SABRHDRB>DH9!LM!HQF!GD=@>BHDLC ! HB_F G ! DCHL!BRRL@CH ! HQF! QFHFALTFCFDH9!LM!HQF!BTFCHGc!=LEF=FCH!GSFFN!DG!CLH!RLCGHBCH;! &CGHFBN FN ! BG!B!RLCHDC@L@G>9!N9CB=DR!EBADB8>F!DCM>@FCRFN!89!HQF!G@AAL@CNDCT!NFCGDH9! RQBABRHFADGHDRG!LM!HQF!BTFCHG FN ! HL!8F!BNBSHFN!LC!HQF!BTFCHcG!R@AAF CH!RLCNDHDLC!BH!FBRQ!GD=@>BHDLC! GHFS;!&C!LHQFA!WLANG>!DCHFA=FNDBHF!RF>>G!8FHWFFC!HQF!R@AAFCH!>LRBHDLC! BCN!HQF!NFGHDCBHDLC!RF>>!BAF!CLH!LRR@SDFN!89!LHQFA!BTFCHG!LA!L8GHBR>FG;!&C!HQDG!=LNF>FEF>G!BAF!SALSLGFNF! O ;!/G!B!AFG@>H
PAGE 52

Ph ! ! CFDTQ8LAQLLN!kOIIl!DG!F^SBCNFN!MAL=!PnP!HL!gng;!+QDG!=FBCG!HQBH!BH!LCF!HD=F , GHB=SFEF>!LM!HQF!(LLAF ! CFDTQ8LAQLLN;! /H!HQF!GB=F!HD=F , GHB=SLWFGH!GSFFN!DM!HQF!R@AAFCH!NFCGDH9! BAL@CN!HQF!BTFCH!DG!BH!HQF!QDTQFGH!EB>@F;!+QF!=B^D=@=!GSFFN!LM!BTFCHG!DG!GFH!HL!8F!G!o!O=`GX ! B8L@H!P!RF>>G`HD=F , GHB=S;!+QF!GSFFN!WD>>!8F!_FSH!DC!HQF ! =B^D=@=!GSFFN!@CHD>!HQF!NFCGDH9 ! EB>@F! BAL@CN!HQF!BTFCH!8FRL=FG!F?@B>!HL!O;!/!RL>>DGDLC!DG!RLCGDNFAFN!BG!=B^D=@=!NFCGDH9>!HQF!BNaBRFCH!RF>>G!LM!BC!BTFCH!BAF!M@>>LRBHDLC!RBCCLH!8F!@SNBHFN;!&C! HQF!RBGF!WQFAF!GL=F!LA!B>>! LM!HQF!DCHFA=FNDBHF!RF>>G!BAF!LR R@SDFN!89!BCLHQFA!BTFCH!LA!L8GHBR>F>!8F!N9CB=DRB>>9!BNa@GHFN!HL!B!>LWFA!GSFFN!SALSLAHDLCB>!HL!HQF!NDGHBCRF!HL! HQBH!8BAADFA; ! $:AE<, M N ! /TFCHG!=LEF=FCH!GSFFN ; ! 2SFFN ! 2HFSG ! J;PP!=`G ! O!RF>>!SFA!HD=F , GHB=S ! J;Kg!=`G ! I!RF>> G ! SFA!HD=F , GHB=S ! O;JJ!=`G ! P!RF>> G ! SFA!HD=F , GHB=S ! ! +QF!BTFCHG!DC!HQF!SALSLGFN!=LNF>!BAF!ABCNL=>9!BGGDTCFN!WDHQ!L8aFRHDEF!BCN!G@8aFRHDEF! SBAB=FHFAG!BH!HQF!8FTDCCDCT!LM!HQF!GD=@>BHDLC;!+QF!DCNDEDN@B>Gc!RQBABRHFADGHDRG@NF! BWBAFCFGG!LM!HQF!FCEDALC=FCHDH9F^D8D>DH9!ADG_G>LW!LANFAGDH9!HL!BRRFGG!T>L8B>! DCMLA=BHDLC!B8L@H!HQF!FCEDALC=FCH;!4C!HQF!LHQFA!QBCN@N F! BTFHQ!GHBH@GDH9; ! /TFCHG!BAF!>LBNFN!DCHL!HQF!FCEDALC=FCH!BAFB!8BGFN!LC!B!SAFNFMDCFN!NF=BCN , >LBNDCT! SBHHFAC!GSFRDMDFN!89!HQF!@GFA;!)SLC!GHBAHDCT!HQF!GD=@>BHDLC!LM!FBRQ!BTFCH!DG!HL!BSSALBRQ! HQF!RLCTFGHDLC , M AFF!SLDC H!BCN!HL!8F!BG!R>LGF!BG!SLGGD8>F!HL!HQF!NFGHDCBHDLC!ZTLB>[;!+QF!GQLAHFGH!

PAGE 53

PU ! ! HABEF>!HD=F!SBHQ!8FHWFFC!HQF!LADTDC!BCN!HQF!GF>FRHFN!NFGHDCBHDLC!DG!NFHFA=DCFN!89!HQF!HABCGDHDLC! NFRDGDLC , =B_DCT!=LNF>!BG!NFGRAD8FN!8F>LW; ! $:>F<7 K '>89<;,'HD , GHBTFN!BTFCH , 8BGFN!RALWN!=LNF>>DCT!G9GHF=!DG!HQF!NFGDTC!LM! HQF!A@>FG!HQBH!TLEFAC!HQF!NFRDGDLC , =B_DCT!SALRFGG!MLA!BTFCHG!HL!RQLLGF!B!HBATFH!ZD;F;FG!F=SDADRB>>9!8BGFN!LC!NL=BDC!_CLWC!F^ SFADFCRF G!kO P h l;! +QF ! SALSLGFN ! G9GHF=!B@HL=BHFG!HQF!SALRFGG!LM!F^HABRHDCT!NFRDGDLC!A@>FG!89!BNBSHDCT!TFCF!F^SAFGGDLC! SALTAB==DCT!kO P U l!HL!MDCN!LSHD=B>!NFRDGDLC!A@>FG!MAL=!L8aFRHDEF!8FQBEDLAG; ! 6 DAGH < ! HQF!SAL8>F=!LM! MDCNDCT!LSHD=B>!NFRDGDLC!A@>FG!MAL=! HQF! SAF GRAD8FN!L8aFRHDEF!8FQBEDLAG ! WBG! MLA=@>BHFN ! BG!B! G9=8L>DR!AFTAFGGDLC!SAL8>F=;!+QFCDFN!HL!GL>EF!HQF! SAL8>F=;!2LFG!WD>>!8F!B8>F!HL!AFSALN@RF!GSFRDMDR! L8aFRHDEF!8FQBEDLAG; ! +QBH!=FBCG!DC!HQDG!GHBTF!LM!HQF!SALSLGFN!=LNF>FG; ! +QF!LSHD=B>!DCDHDB>!HBATFH!NFRDGDLC!DG!D=SBRH FN!89!NDMMFAFCH!MBRHLAG!HQBH!HQF!BTFCHG!SFARFDEF! MAL=!HQF! F CEDALC=FCH;!+QF ! =LNF>!DCEL>EFG ! ML@A!D=SLAHBCH!MBRHLAGX!HQF!NDGHBCRF!HL!B!HBATFH ! HBATFH!NFRDGDLC!Z 3#4 [!M@CRHDLC! DG!RB>R@>BHFN ! HL!BGGDTC!B!G SFRDMDR!HBATFH@FR@>BHFN! BG!ML>>LWGX ! 3#4 $ 2 ( , 1 678 $ 9 : ; < 0 1 =9 : > : ( 1 & ! ! ! ! ! ! ZI[ ! WQFAF : • ! " ? 1 DG!HQF!NDGHBCRF!HL!B!HBATFH! 5
PAGE 54

YJ ! ! • ! @ A 1 DG!HQF!GSFFN!LM!HQF!BTFCH< , • ! B" ? 1 DG!HQF!NFCGDH9!ZRLCTFGHDLC[!BH!HQBH!GSFRDMDR! HBATFH 1 5 LRBHFN!BH!SLDCH! $ % . & ' . ( R@>BHFN!8BGFN!LC!HQF!-@R>DNFBC! GRQF=F!kYYlX! ! ) $ * & + ( , D $ % . / % ( E 1 0 $ ' . / ' ( E 1 1 ; ! ! ! ! !! !!!! ZP[ ! $>:;=8786;, '!AL@HF!DG!8BGFN!LC!HQF!NFGDAFN!HABEF>!HD =F!HL!AFBRQ! HQF!NFGDAFN!NFGHDCBHDLC;!/H!FEFA9!HD=F , GHB=S!BCN!MLA!FBRQ!BTFCH>!DG!GF>FRHFN!MAL=! HQF!FDTQH!RBCNDNBHF!RF>>G!DC!HQF!(LLAF!CFDTQ8LAQLLN!HL!NFMDCF!HQ F!HABEF>>DCT!HABa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kOPKl ! HQBH!RB>R@>BHFG!HQF! NDGHBCRF!MAL=!HQF!LADTDC!SLDCH!HL!HQF!NFGHDCBHDLC;! /SS>9DCT! $P ! B>TLADHQ=!LC>9!BG!B!AL@HDCT! HFRQCD?@F!CFDHQFA ! GSFRDMDFG ! WQFAF!HQF!SALRFGGDCT!MLA!HQF!AL@HFG!F^DGHG!CLA ! RBSH@A FG!HQF!EBA9DCT! RLCNDHDLCG!LM!RLCTFGHDLCG!BH!BC9!SLDCH!DC!HD=F;!+QF!BTFCH! 2 ! WD>>!=LEF!HL!HQF!HBATFH!RF>>>!WDHQ!HQF!QDTQFGH! SAL8B8D>DH9!B=LCT!(LLAF!CFDTQ8LAQLLN!RF>>G!DC!HQF!CF^H!

PAGE 55

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cG!=LEF=FCHDH9!HQBH!AFM>FRHG!HQF!BTFCHcG!EDGD8>F!ABCTF; ! &C!HQF!=LNF>F!@G@B>>9!BELDN!WB>_DCT!R>LGF!HL!WB>>G!BCN! L8GHBR>FG;!(BC9!GH@NDFG!QBEF!L8GFAEFN!QDTQ!NFCGDH9!BAFBG!BAL@CN!L8GHBR >FG!BCN!RLACFAG!DC! GD=@>BHDLCG!HQBH!NL!CLH!DCR>@NF!WB>>!SLHFCHDB>G!kigLCT!HQF!=DCD=@=!SBHQ!>FCTHQ;!+QF!DCHALN@RHDLC!LM!B!AFS@ >GDEF!L8GHBR>F!SLHFCHDB>!DC! HQF!SALSLGFN!=LNF>!MDF>NG!BAL@CN!L8GHBR>FGLGF!HL!L8GHBR>FG;!+QF!AFS@>GDEF!L8GHBR>F!SLHFCHDB>!DG!DCEFAGF>9!SALSLAHDLCB>! HL!HQF!NDGHBCRF!MAL=!HQF!L8GHBR>FG;!+QF ! L8GHBR>FGc!FMMFRH!NDGBSSFBAG!MLA!NDGHBCRFG!TAFBHFA!HQBC!B! RFAHBDC!HQA FGQL>N;!+Q@G!MDF>N!DG!BMMFRHFN!89!HQF!L8GHBR>FGc! M>LLA!MDF>N!Z T## [;!+QF!EB>@FG!MLA!HQF!RF>>G!LRR@SDFN!89!L8GHBR>FG! BAF ! GFH!HL!8F!HQF!QDTQ FGH ! EB >@FG! LM!HQF!RF>>G!DC!HQF!FCEDALC=FCH;!+QF!L8GHBR>FGc!GHBHDR!SLHFCHDB>! MDF>N!DG!RB>R@>BHFN!BG!ML>>LWGX ! TUU $ % & ' ( , 1 678 $ 4 VAW 1 & " W & X ( 1 & !! ! ! ! ! ! Zi[ !

PAGE 56

YI ! ! WQFAF! " ! AFSAFGFCHG!HQF!=DCD=@=!NDGHBCRF!MAL=!HQF!L8GHBR>FGF!MFF>!HQF!L8GHBR>FG; ! 4CF!LM!HQF!_F9!F>F=FCHG!LM! HQF ! =LNF>!DG!HQF ! ,:&&'-':!*DQ :')D!,( ! G@8!=LNF>;!&H!SALEDNFG! HQF!B8D>DH9!HL!RB>R@>BHF!SLHFCHDB>!DCHFABRHDLCG ! 8FHWFFC!BTFCHG!BCN ! HQF!NFCGDH9!BAL@CN!FBRQ!RF>>;!&H! DG!=FBG@AFN!8BGFN!LC!HQF!C@=8FA!LM!BTFCHG!WDHQDC!HQF!GSFRDMDFN!GSBRF!LM!ABCTF! Y ;!&H!DCG@AFG! BELDNDCT! ,:&&'-':! ! N@ADCT!RB>R@>B HDLC!BCN!HQF!8FGH!HABaFRHLA9!HL!HB_F!MLA!FBRQ!BTFCH;!+QFAFMLAF!SALE DNFG!HQF!BWBAFCFGG!LM!WQFC!HQF!SLGGD8>F!DCHFABRHDLC!8FHWFFC!BTFCHG!RBC!LA!WD>>!LRR@A! N@ADCT!HABEF>FG!FBRQ!BTFCH!HL!8F!BWBAF!LM!SLHFCHDB>!DCHFABRHDLCG!WDHQ!LHQFA!BTF CHG; ! 6LA!FBRQ!BTFCH! 2 R@>BHF!HQF!HABCGDHDLC!SAL8B8D>DH9!HL!FBRQ!F=SH9! RF>>! $ % & ' ( ! DC!DHG! (LLAF!CFDTQ8LAQLLN!BG!ML>>LWGX ! F $ % & ' ( , Z [*\ $ / ] ^ #UU $ % & ' ( 0 ] _ 4UU $ % & ' ( 0 1 ] ` TUU $ % & ' ( 0 1 ] 9ab 4cd $ % & ' ( 0 1 ] e 3 1 ( & ! ! ! ! ! ! ! ! ! ! ! !!!!!! Z K[ ! WQFAFX ! • ! Z ! DG!HQF!CLA=B>D]BHDLC!RLFMMDRDFCH< , • ! #UU $ % & ' ( ! DG!HQF!HBATFH!GHBHDR!SLHFCHDB>!MDF>N!EB>@F< , • ! 4UU $ % & ' ( ! DG!HQF!EB>@F!LM!HQF!N9CB=DR!M>LLA!MDF>N< , • ! TUU $ % & ' ( ! DG!HQF!L8GHBR>FG!M>LLA!MDF>N!EB>@F< , • ! 4cd $ % & ' ( ! DG!HQF!EB>@F!LM!HQF!NFCGDH9!MDF>N< , • ! J ! DG! HQF!DCFAHDB!SBAB=FHFA< , • ! ] ^ FGLLA!MDF>NG9< , • ! ] e ! DG!WFDTQH!GFCGDHDEDH9!SBAB=FHFA!LM!HQF!DCFAHDB ; ,

PAGE 57

YP ! ! +L!GL>EF!B!RLCM>DRH>9!RQLGFC!WDHQ!F? @B>!SAL8B8D>DH9!BCN!G@RRFFNG!HL!SALRFFN>;!&M!CL!=LEF=FCH!DG!SLGGD8>F!DC!BC9!LM!HQF!BNaBRFCH!RF>>G>!GHBHF!WD>>!CLH!RQBCTFFGG; ! /SS>9DCT!HQDG!HABCGDHDLC!NFRDGDLC , =B_DCT!=LNF>!F CG@AFG!HQF!GQLAHFGH!SBHQ!HQBH!BELDNG! L8GHBR>FG!BCN!RLCTFGHFN!GSLHG!B>LCT!HQF!BTFCHcG!AL@HF;!+QDG!HABCGDHDLC!M@CRHDLC!FCB8>FG!HQF! BTFCHGc!SALa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aFRHDEF!BCN!L8aFRHDEF!RQBABRHFADGHDRG!LM!HQF!DCNDEDN@B>!BTFCHGF=FCHBHDLC9!NDEDNFN!DCHL! G?@BAF!AFTDLCG!HL!F GHD=BHF!HQF!NFCGDH9!BH!FBRQ!AFTDLC!ZDM!DH!DG!=LAF!HQBC!B!SAFNFMDCFN!HQAFGQL>N[;! +QF!AFTDLCB>!NFCGDH9!DG!=FBG@AFN!89!RL@CHDCT!B>>!BTFCHG!DC!HQF!AFTDLC!BCN!HQFC!NDEDNDCT!89!HQF! AFTDLC!BAFB;!/H!HQF!AFTDLCG! WDHQ!QDTQ!NFCGDH9
PAGE 58

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c G!NFRDGDLC!GSBRF>LWFAG!NFRDNF!@SLC!HQF!NFRDGDLC!EBADB8>FG!HQBH!LSHD=D]F!QDG!L8aFRHDEF!M@CRHDLC; ! />>!BTFCHG!BAF ! >LL_DCT!MLA!MBGHFA!AL@HFGF!RLCR@AAFCH>9!ML>>LWDC T!HQF!DCHF>>DTFCH!BTFCH! DC!B!TAL@S!LM!LHQFA!BTFCHG;!/H!HQF!GB=F!HD=FN!SLHFCHDB>>9!NFR AFBGF! HABEF> ! HD=F;! 5BAHDR@>BA>9DBA!BTFCHG!BSS> 9!LC>9!HQF!LSFABHDLCB>!>FEF>!89!ML>>LWDCT!LA!=D=DR_DCT! DCHF>>DTFCH!BTFCHGc!=LEF=FCHG>FRHDEF!SBHHFAC; ! &C!HQF!SALSLGFN!=LNF>>DTFCH!BTFCHG!DG!CLH!RLCGHBCHG L>DTFCH!BTFCHG!RL@>N!8F!DC!MALCH!LM! ML>>LWFA!BTFCHGDCTBHFAB>!Z>FMHDCT; ! &C!HQF!(*(2 , /$(!=LNF>BHDLC;!+QF!GHBH@G!B>HFABHDLC!NFSFCNG!LC!RQBCTFG!DC!HQF!G@AAL@CNDCTG! LA!RQBCTFG!DC!HQF!BTFCHcG!L8aFRHDEF!SBAB=FHFAG;!+QF!GHBH@G!LM!BC!BTFCH!RL@>N!RQBCTF>DTFCRF!>B9FA!LA!NLWC!HL!B!CLA=B>!>B9FABHDLC;!/C!@STABNDCT`NLWCTABNDCT! SALRFN@AF!FCB8>FG!HQF!SALSLGFN!=LNF>!HL!RLEFA!B>>!HQF!DCNDEDN@B>Gc!8FQBEDLAG!@CNFA!B>>!GDH@BHDLCG;!

PAGE 59

Yi ! ! 6LA!F^B=S>FBHDLC>DTFCH!BTFCHG!R L@>N!8F!RQBCTFN!8BR_!HL!CLA=B>! GHBH@G;!2L!DG!N9CB=DRB>>9!A@C!GFEFAB>!HD=FG!MLA!FBRQ!BTFCH!N@ADCT!HQF! GD=@>BHDLC;! ! /*04%&+"(!OX!'9CB=DRB>!2HBH@G!)STABNF! ! MLA * (D,>*D;(!=*D*'!*=>(* -'BA&D=':!*(!Q'9:!B(!= * NL ! ***** D R TVE(,='Q( W 8D9DB(=(9* o!%BCNL=!kJ(*(!Q'9:!B(!=*-%D,(*'!=:*(XAD&*9(;':!-Y * MLA * (Q(9N*Z*='B(-=DB%* NL * * !!!!!! MLA * (D,>*(!Q'9:!B(!=*9(;':!* NL * * !!!!!!!!!!!! DM * /S(!-'=N*[*S(!-'=N W ">9(->:&)2* HQFC ! !!!!!!!! !!!!!!!!! MLA * (D,>*D;(!=*D*'!*=>(*9(;':!* NL * * !!!!!!!!!!!!!!!!!!!!!!! DM * /DRTVE(,=' Q( W 8D9DB(=(9*[*TVE(,='Q( W ">9(->:&)2 D!)* * /DR +A VE(,='Q( W 8D9DB(=(9*[ * +A VE(,='Q( W ">9(->:&)2 * HQFC * * !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM * /DR+=D=A-*\*#:&&:](92 ! HQFC ! ************ DR+=D=A-*\*J!=(&&';(!= Y ! *********** DRG::9(^(';>V:9-R+=D=A-*\*#:&&:](9Y* ! !!!!! FCN! ! !!!!!!!!!! !! F>GF ! ! !!!!!! MLA * (D,>*D;(!=*D*'!*=>(*9(;':!* NL ! ************ DR+=D=A-*\*-:&'=D9N Y * !!!!!! FCN !

PAGE 60

YK ! ! !!!!!! FCN! ! FCN ! +QF!SALSLGFN!=LNF>!DG!TFCFAB>D]FN!89!DCRAFBGDC T!HQF!EBADFH9!DC!HQF!GHBH@GFG`ABC_DCTG!LM! DCHF>>DTFCRF!SLGGD8>F!MLA!HQF!BTFCHG!DCGHFBN!LM!QBEDCT!LC>9!HW L!>FEF>G!LM!BTFCHG;!+QF!R>BGGDMDRBHDLC! DG!8BGFN!LC!HQF!G@8aFRHDEF!SBAB=FHFA!LM!DCHF>>DTFCH!BTFCHG;!+QF!DCHFABRHDLCG!BCN!RL==@CDRBHDLC! 8FQBEDLAG!8FHWFFC! BTFCHG!DG!8BGFN!LC!DCHF>>DTFCRF!ABC_DCT;!6LA!DCGHBCRF>DTFCRF!ABC_DCT G!=FFH!BH!HQF!GB=F!SLDCH!BCN!QBEF!NDMMFAFCH!NFRDGDLCGLWFA , ABC_FN!BTFCH!ML>>LWG!HQF!QDTQFA , ABC_FN!LCF;!/>TLADHQ=! Z I [ ! D>>@GHABHFG!HQF!R>BGGDMD RBHDLC!LM! DCHF>>DTFCRF!ABC_G!8BGFN!LC!HQF!G@8a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

PAGE 61

Yg ! ! HQDG!RQBSHFA!FCB8>FG! HQF!DCHF>>DTFCH!BTFCHG!HL!BTTAFTBHF!QDGHLADRB>!DCMLA=BHDLC!BCN!BNa@GH!HQF! DCHFA=FNDBHF!HBATFHG!RLCHDC@L@G>9!HL!_FFS!@S!WDHQ!HQF!HB G_!AF?@DAF=FCHG; ! (9:EB:786;, 6C,$>B=7L6>7@8;<==,16D!RLCRFSH!kOY J , OiU l!DG!D=SLAHBCH!DC!@CNFAGHBCNDCT!HQF!HQL@TQH! SALRFGG!WDHQ!AFTBAN! HL! RQLDRFG >9!DC!GDH@ BHDLCG!WQFAF!HQFAF!DG!B!ADG_;!+QF!HFA=!HA@GH!k OYI l!DG!RL==LC>9!@GFN! DC!=@>HD , BTFCH!G9GHF=G!GDC RF!HQFGF!G9GHF=G!@G@B>>9!RLCHBDC!@CRFAHBDCFHFFNTF!MAL=!EBADL@G!DCMLA=BHDLC!GL@ARFG!k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cG!RLCMDNFCRF!DC!HQF!B8D>DH9!LM!B!AF>BHFN!DCHF>>DTFCH!BTFCH! ZDCML A=BHDLC!GL@ARF[!HL!NF>DEFA!BRR@ABHF!DCMLA=BHDLC;! / C!BTFCH! DG! RLCGDNFAFN! HL!8F!HA@GHWLAHQ9!DM! DH!QBG!B!QDTQ!SAL8B8D>DH9!LM!SFAMLA=DCT!B!SBAHDR@>BA!BRHDLC!WQDRQ!HBATFH;!+QF!B=L@CH!LM!H A@GHWLAHQDCFGG!LM!BC! DCHF>>DTFCH!BTFCH!DG!8@D>H!HQAL@TQ!LHQFA!CFDTQ8LADCT!BTFCHG; !

PAGE 62

Yh ! ! $FMLAF!BTFCH! 2 ! RBC!=B_F!B!NFRDGDLC!HL!ML>>LW!HQF!BRHDLCG!HB_FC!89!DCHF>>DTFCH!BTFCH! g @BHF!HQF!HA@GHWLAHQDCFGG!LM!BTFCH! g ;!5BAHDR@>BA>9DH9!HQBH!B! ML>>LWDCT!BTFCH!WL@>N!BSSALEF!LM!BC!DCHF>>DTFCH!BTFCHcG!LSDCDLC!LC!B!GSFRDMDR!HBATFH!DG!NFSFCNFCH! LC!HQF!BSSALEB>!LM!HQF!CFDTQ8LADCT!BTFCHG!B8L@H!HQF!NFRDGDLC!HB _FC!89!HQF!DCHF>>DTFCH!BTFCH; ! +L!D>>@GHABHF>DTFCH!BTFCH! g ! SALEDNFG!_CLW>FNTF@NDCT!HQF! DCHF>>DTFCH!BTFCH!WQL! DG!LCF!LM!HQF!CFDTQ8LAG;! 6DT@AF! Y ! GQLWG!HQF!AFG@>HDCT!NFRDGDLC!HAFF; ! ! 28FB><,RN, 'FRDGDLC!HAFF!WDHQ! ! ! CFDTQ8LA!BTFCHG ; ! /MHFA!HQF!NFRDGDLC!HAFF!QBG!8FFC!8@D>H@F!B TFCH! 2 ! QBG!LC!NFRDGDLC! Z_CLW>FNTF[! h ! RBC!8F!RB>R@>BHFN!MAL=!SALSBTBHDCT!SAL8 B8D>DHDFG!DC!HQF!HAFF;!+QF!HA@GHWLAHQDCFGG! SAL8B8D>DH9!B8L@H!HQF!NFRDGDLC! h ! DG!RB>R@>BHFN!BG!ML>>LWGX ! 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 F $ h ( , 1 i 1 j j F $ h 2 G ? ( F $ 2 G ? ( 1 k ? l J m G l J & 1 ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Zg[ ! WQFAFX ! • ! i * DG!HQF!CLA=B>D]DCT!MBRHLA< !

PAGE 63

YU ! ! • ! F $ h 2 G ( ! DG!HQF!RFAHBDCH9!MBRHLA!HQBH!BC!BTFCH! 2 G QBG!LC!NFRDGDLC! h ;!+QBH!=FBCG!BC!BTFCH! 2 G ! HQDC_G! h ! DG!RLAAFRH!WDHQ!SAL8B8D>DH9! F $ h 2 G ( & ! • ! F $ 2 G ? ( 1 ! DG!HQF!AF>DB8D>DH9!MBRHLA!LM!BC!BTFCH! 2 G ;! ! +QFAFMLAFDH9!LM!ML>>LWDCT!B!NFRDGDLC!SALRFGG!DG!8BGF N!LC!HQF!TAFBHFGH! RFAHBDCH9!EB>@F!LM! F $ h ( n ! &C!LHQFA!WLANG>DTF CH!BTFCH! g 1 LC>9!DM!HA@GHWLAHQDCFGG! SAL8B8D>DH9!EB>@F!DG!TAFBHFA!HQBC!LA!F?@B>!HL!B!SAFNFMDCFN!HQAFGQL>N; ! />>!SALSLGFN!GHBTFG!BCN!G@8 , =LNF>G!LM!HQF!HQAFF!>FEF>G!LM!HQF!(*(2 , /$(!=LNF>!BAF! SFAMLA=FN!DC!HQF!=DRALGRLSDR!>B9FA!BG!HQF9!BAF!D=S>F=FCHBHDLC ! RL=SLCFC HG!LM!HQF! >B9FA;! "LWFEFA!DG!SFAMLA=FN>DTFCH!BTFCHG!BAF! TFCFABHFNB9FA!DG!TFCFABHFN!BG!B!AFG@>H;!+QF!RL==@CDRBHDLC!BCN! HA@GHWLAHQDCFGG!FEB>@BHDLC!GHBTF!DG!SFAMLA=FN!DC!8LHQ!HQF!=DRA LGRLSDR!BC N!=BRALGRLSDR!>B9FAG; ! 6DT@AF! i ! GQLWG!HQF!LEFAB>>!=LNF>DCT!MAB=FWLA_!HQBH!RLCGDGHG!LM!HQAFF!=BDC!=LN@>FGX!DCS@HBHLA!BCN!L@HS@H;!+QF!DCS@H!=LN@>F!SALRFGGFG!HQF!DCS@H!NBHB!WQDRQ!DCR>@NFGX!ZB[!TFL=FHADRG! LM!HQF!FCEDALC=FCHBHDLC!SBAB=FHFAG;!+Q F!TFL=FHADRG! NFGRADSHDLC!DCR>@NFG!NFMDCDCT!HQF!FCEDALC=FCH!GQBSFG!WDHQ!HQFDA!ND=FCGDLCG!BCN ! GSBRFG!BCN! D>>@GHABHFG!QLW!HQF!FCEDALC=FCHB>!GSBRF!WD>>!8F!RQBCTFN!N@ADCT!HQF!GD=@>BHDLC;!&H!B>GL!SALEDNFG! HQF!>LRBHDLCG!LM! B>>!L8GHBR>FG!BCN!TBHFG!DCGDNF!MBRD>DHDF G;!+QDG!DCMLA=BHDLC!DG!H9SDRB>>9!F^HABRHFN! MAL=!3/'!MD>FG;!/TFCH!RLCMDT@ABHDLC!DCS@H!GSFRDMDFG!HQF!C@=8FA!LM!BTFCHG!FCHFADCT!HQF! GD=@>BHDLC!FCEDALC=FCH!MAL=!NDMMFAFCH!GHBAHDCT!SLDCHG!DC!HQF!NDMMFAFCH!HD=F!DCHFAEB>G;! &C!BNNDHDLCBHDLC>LW!HQFGF! 8FQBEDLAG!BAF!BGG@=FN!TDEFC;!/>GLDCFBHFN>LWFN!HL!=LEF!MAFF>9!DC! HQF!B AFB;!+QF!GSFFN!BHHAD8@HF!DG!BGGDTCFN!HL!HQF!BTFCHG!8BGFN!LC!G@AAL@CNDCT!RLCTFGHDLC!BCN!

PAGE 64

iJ ! ! NFCGDH9;!'@ADCT!HQF!GD=@>BHDLC@FG!RQBCTF!LEFA!HD=F;!2D=@>BHDLC!SBAB=FHFAG! NFHFA=DCF!HQF!TFCFAB>!ML>>LWDCT!8FQBEDLA G!LM!HQF!BTFCHGX!NFHFA=DCDGHDR>DTFCH;!6DAGH!DG!BSS>DFN!WQFAF!B>>! BTFCHG!GQL@>N!ML>>LW!HQF!DCHF>>DTFCH!BTFCH!DC!HQFDA!AFTDLC;!+Q@GF=FCHBHDLC!LM!HQF! HA@GHWLAHQDCFGG!G @8 , =LNF>!DG!CFFNFN;!2FRLCN>LW!LA!CLH!ML>>LW!HQF!DCHF>>DTFCH!BTFCH!DC!HQBH!AFTDLC< ! GL=F!LM!HQF! BTFCHG!BAF!DC!HQF!GL>DHBA9!RBGF!DGCcH!BSS>DFN! HL!HQF=;!6DCB>>9F=FCHFN!BG!B!8BGF>DCF!LM!HQF!F^SFAD=FCHG9!HQF! HABNDHDLCB>!BTFCH , 8BGFN!GD=@>BHDLC!DG!D=S>F=FCHFN!WDHQL@H!DCEL>EDCT!HQF!GHABHFTDR!BCN!HBRHDRB>! >FEF>G; ! ! ! ! 28FB><,SN, +QF!LEFAB>>!=LNF>DCT!MAB=FWLA_ ; !

PAGE 65

i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m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

PAGE 66

i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a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m!MLA!F^B=S>F!HQF!GD=@>BHDLC!FCEDALC=FCH!ZGSBRF[F!HQF!GSBHDB>!GF=BCHDRGTLADHQ=G!BCN!G@8 , =LNF>G!BAF!GRADSHFN ! @GDCT!59HQLC!SALTAB==DCT!>BCT@BTF;!+QF!

PAGE 67

iP ! ! A@CCDCT!HD=F!LM!HQF!GD=@>BHDLC!=LNF>!EBADFG!89!HQF!>LBNDCT!GRFCBADL!BCN!89!QLW!=BC9!BTFCHG!BAF! DC!HQF!G9GHF=!BH!HQF!GB=F!HD=F;!&H!A@CG!LC!B!=BR42!(LaBEF!RL=S@HFA!ZEFAGDLC ! OJ;OY;Y[!WDHQ!B! SALRFGGLA!&CHF>!3LAF!Di!35)!q ! I;K!0"]!BCN!(F=LA9!h!0$!OKJJ!("]!''%P;!+QF!RLNF!GD]F!DG! B8L@H!PJ!V$; ! $@<,*'',4>676?6E , +QF ! GHA@RH@AF!HQF!DCMLA=BHDLC!BCN!NFGRADSHDLC!LM!HQF!/$(!=LNF> ! DG ! 8BGFN!LC!HQF!GHBCNBAN! SALHLRL>!RLCGDGHG!LM!GFEFC!F>F=FCHG!HQBH!RBC!8F!TA L@SFN!DC!HQAFF! 8>LR_G!Z4EFAEDFWG[; ! +QF!4EFAEDFW!RLCGDGHG!LM!HQAFF!F>F=FCHG! ZS@ASLGFFG!BCN!GRB>FG!BCN!SALRFGG ! LEFAEDFWDCT[;!&C!HQF!4EFAEDFW>!S@ASLGF!BCN!GHA@RH@AF!LM!HQF!=LNF>!DG!SAFGFCHFN ! BG!DH! DG ! SAFGFCHFN!DC! HQDG! 3QBSHFA cG!MLR@G@HDLC!BCN!RL=S>F^DH9 ! DG! TDEF C ;!/>GL@NFG!HQF! NFR>BABHDLC!LM!B>>!L8aFRHG!ZR>BGGFG[!NFGRAD8DCT!HQF!=LNF>cG!FCHDHDFG!ZNDMMFAFCH!H9SFG!LM!DCNDEDN@B>G! ZBTFCHG[ ! BCN!HQ FDA!8FQBEDLAG ! BCN!FCEDALC=FCHG[!BCN!HQF!GRQFN@>DCT!LM!HQF!=LNF>c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

PAGE 68

iY ! ! &5!4$(%,)T , '(&)#)*+,#344*%$,#U#$(1,2*%,#)13/!$)+0,!+',1*'(/)+0,*2, &%*.','U+!1)&#,!+',(T!&3!$)*+ , );7>6DB?786; , /!RALWN ! FEBR@BHDLC!G9GHF=!DG!B!RL=S>F^!G9GHF=!WDHQ!=@>HDS>F!DCHFABRHDCT!BTFCHG!G@RQ!BG! SFLS>FFGDRBHDLCG!MLA!HQF!GBM FH9!LM!D CNDEDN@B>G! DCEL>EFN ! kUYl;! 2H@NDFG!RLCRFACFN!WDHQ!RQBABRHFAD]DCT>FRHDEF! 8FQBEDLAG!BCN!=LEF=FCH!N9CB=DRG!LM!SFNFGHADBCG!DC!S@8>DR!MBRD>DHDFG!QBEF!8FFC!RLCN@RHFN!MLA! NFRBNFG!DC!LANFA!HL!BGGFGG!SLHFCHDB> ! FEBR@BHDLC!A DG_G!BCN ! G@TTFGH!RL@CHFA=FBG@AFG!khJ@FCRDCT!8@D>NDCT!NFGDTC!BCN!RALWN!=BCBTF=FCH!GHABHFTDFG;! 2H@N9DCT!RALWN!8FQBEDLAG!DC! CLA=B>!BCN!F=FATFCR9!GDH @BHDLCG! QBG!8FFC!MBRD>DHBHFN!89!EBADL@G!BTFCH , 8BGFN!SFNFGHADBC!=LNF>G ! kOKI , OgJl ;!'DMMFAFCH!BGG@=SHDLCG!QBEF!8FFC!RLCGDNFAFN!WQFC!8@D>NDCT!HQF!=LNF>G!HQBH!AFSAFGFCH! LA!=D=DR!AFB>DH9> FCTFG!DC!SFNFGHADBC!=LNF>DCT;! ! 3ALWNG!HFCN!HL!=LEF!MAL=!NDGLATBCD]FN!HL!LATBCD]FN!MLA=G ! WQFC!B!RL==LC!TLB>!G@RQ!BG! FEBR@BHDCT!BC!FCR>LGFN!GSBRFFLR_! BG!HQF9!=LEF!DC!@CDGLC ! HLWBANG!F^DHG; ! &C! HQF ! =LNF>TLADHQ=!F=S>L9FN!89!DCNDEDN@B>G!WDHQDC ! HQF!RALWN!DG!NFADEFN!MAL=!L@A! SAFEDL@G!WLA_!HQBH!@GFN!BC! BTFCH , 8BGFN!=LNF>DCT!BSSALBRQ!Z /$([!HL!AFS>DRBHF!MLABTDCT! 8FQBEDLAG!LM!BCHG!kOJIl;!(LGH ! SBAB=FH FAG!MAL=!HQF!BCH!=LNF>!BAF!N@S>DRBHFN!DC!HQF!RALWN!BTFCHG ; !

PAGE 69

ii ! ! + QF!RALWN!BTFCHGc!=LEF=FCH!N@ADCT!@CNDAFRHFN!=LEF=FCH!AFS>DRBHFG!HQF!RLAAF>BHFN!ABCNL=! WB>_!LM!EDAH@B>!BCHG ! kOJIl;! +Q@GLDHFN ! HL!=LNF>!BCN!GD=@>BHF!HQF!RALWN! N9CB=DRG!GDCRF ! HQF!/$(!HFRQCD?@F!DG!H9SDRB>>9!F=S>L9FN!89!=LGH!BCD=B>!8FQBEDLA@NDCT! M>LR_DCT!8DANG; ! 7F ! NFEF>LSFN!B!=LNF>DCT!MAB=FWLA_ ! kOYIBATF!MBRD>DHDFG!@GDCT ! HQF!/$(!RL= 8DCFN!WDHQ!CLC , QL=LTFCFL@G!RF>>@>BA!B@HL=BHB! Z3 /[;!+QF!=LNF>DCT!MAB=FWLA_!kOYPl!DG!@GFN!HL!NFEF>LS!B!NFRDGDLC!G@SSLAH!G9GHF=!WQDRQ!BDNG!DC! HQF!@CNFAGHBCNDCT!LM!RALWN!N9CB=DRG>9!@CNFA!ADG_!RLCNDHDLCG!N@ADCT!FEBR@BHDLC G ;! ! +QF!SALSLGFN!=LNF> ! k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a@GHB8>F! BSSALBRQ ! DG! DCHALN@RF N ! MLA!GD=@>BHDCT!Q@=BC!SFARFSHDLC!BCN!NFRDGDLC , =B_DCT!DC!NBCTFAL@G! GRFCBADLG ! BG!HQF!TLB>!LM!HQDG!WLA_!D G!HL!RAFBHF!B!=LNF>!HQBH!DG!B8>F!HL!GD=@>BHF!EBA9DCT!DCNDEDN @B>! 8FQBEDLAG; ! +QF!RALWN!N9CB=DRG!NFRDGDLC , =B_DCT!=LNF>DCT!QBG!8FFC!8ABCRQFN!DCHL!HQAFF!>FEF>GX! GHABHFTDR;!+QF!MLA=@>BHDLC!LM!B!S>BC!BCN!HQF!MDCB>!L8aFRHDEFGFEF>;!/H!HQF!HBRHDRB>!>FEF>< ! B>>! BRHDEDHDFG ! BAF! RL=S@HF N ! BCN!SFAMLA= FN ! HL!MBRD>DHBHF!HQF!MLA=@>BHFN!S>BC;!+QF!LSFABHDLCB>!>FEF>! DCR>@NFG!HQF!SQ9GDRB>!F^FR@HDLCG!BCN!SALRFN@AFG!LM!HQF!BRHDEDHDFG ! NFEF>LSFN!DC!HQF!HBRHDRB>!>FEF>;! /C!F^B=S>F!LM! LSFABHDLCB>! >FEF>!8FQBEDLA! WL@>N!8F!HQF!=LEF=FCH!LM!B!SFAGLC!MAL=!LCF!SLDCH!HL!

PAGE 70

iK ! ! BCLHQFA;!+QF!TLB>!DG!HL!8F!B8>F!HL!=D=DR!DCHF>>DTFCH!BCN!GF>M , LATBCD]BHDLCB>!8FQBEDLAG!BCN!TBDC! AF>DB8>F!AFG@>HG;!+QF!HWL!=BDC!RL =SLCFCHG!LM!HQF!SALSLGFN!=LNF>!BAF!HQF!FCEDALC=FCH!DC!WQDRQ ! HQF!GD=@>BHDLC!HB_FG!S>BRF!BCN!HQF!BTFCHG>!D=SBRH!HQF!WQL>F! G9GHF=;! +QF!AF>BHDLCGQDS!B=LCT!B>>!HQF!F>F=FCHG!LM!B!RALWN!DG!FGGFCHDB>!8FRB@GF!HQF!N9CB=DR!LM! HQDG!DCHFA BRHDLC!DCM>@FCRFG!HQF!N9CB=DR G ! LM ! HQF!FCHDAF!G9GHF=; ! +QF!SAF EDL@G!RQBSHFA!=FCHDLCG!HQF!=BaLA!RLCHAD8@HDLCG!LM!HQDG! NDGGFAHBHDLC; ! &H!NFGRAD8FG! HQF!=@>HD , >FEF>!=@>HD , GHBTF!BTFCH , 8BGFN!NFRDGDLC!G@SSLAH!G9GHF=!MLA!RALWN!N9CB=DRG!N@ADCT!BC! FEBR@BHDLC! SALRFGG!kOJOl;!/$(LLA!MDF>N!BSSALBRQFGDFN!HL! =LNF>!SFNFGHADBC!8FQBEDLA!BCN!RALWN!SQFCL=FCB;!+QF!SALSLGFN!MAB=FWLA_!DCR>@N F G!=@>HDS>F! N9CB=DR!NFRDGDLC , =B_DCT!GHBTFG!HL!D=SALEF!HQF!RL=S>F^!SALRFGG!LM!FEBR@BHDLC!N@ADCT!BC! F= FATFCR9;!$LHQ!HQF!=BRALGRLSDR!BCN!=DRALGRLSDR!SLDCHG!LM!EDFW!LM!RALWN! M>LW!DCGDNF! RLCGHABDCFN!FCEDALC=FCHG!WFAF!F^B=DCFN;!+QF!MAB=FWLA_!B>GL!DCHALN@RFG!GFEFAB>! DCHFARLCCFRHDLC!A@>FG!8FHWFFC!DCNDEDN@B>G!DCGDNF!LM!HQF!G9GHF=!BG!WF>>!BG!8FHWFFC!HQFGF! DCNDEDN@ B>G!BCN!HQFDA!FCEDALC=FCH;!+QF!=BRALGRLSDR!>B9FA!AFSAFGFCHG!HQF!RLCCFR HDLCG!8FHWFFC! DCHF>>DTFCH!T@DNF!BTFCHG!BCN!HQFDA!RBSB8D>DH9!HL!FCQBCRF!HQF!NFRDGDLCG!MLA!HQF!WQL>F!G9GHF=;!+QF! =DRALGRLSDR!EDFW!DG!RL=SLGFN!LM!B!QDTQ!NFHFA=DCBHDLC!3/!MAB=FWLA_!MLA!FEFA9 ! LSFC!GSBRF;!&H! GQLWG!QLW!BC!BTFCHcG!CFDTQ8LAQLLN!=LEFG < ! BG!WF>>!BG!QL W!NFRDGDLC , =B_DCT!NFEF>LSG!BH!HQF! =DRALGRLSDR!>FEF>!LM!HQF!G9GHF=;!+QF!HWL!=BDC!>B9FAGFN!DC! HQAFF!>FEF>G!@GDCT!=@>HDS>F!G@8 , =LNF>G;!/H!HQF!GHABHFTDR!>F EF>! WBG! DCHALN@RFN! DC!WQDRQ! NFRDGDLC!A@>FG!WFAF!B@HL=BHDRB>>9 ! F^HABRHFN;!+QF!BD=!LM!HQDG!BSSALBRQ!DG!HL!BR?@DAF!FCEDALC=FCHB>! SFARFSHDLC!BCN!LSHD=D]FN!L8aFRHDEF!GF>FRHDLC;!/H!HQF!HBRHDRB>!>FEF>!GF>FRHDLCBH FN!

PAGE 71

ig ! ! DCHF>>DTFCH!BTFCHG!WFAF ! F^B=DCFN;!+QF!BTFCHGc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cG!GFRLCN!GHBTF!ZHABCGDHDLC!NF RDGDLC , =B_DCT[LSFN!BRRLANDCT!HL!GSFRDMDR! AFSAFGFCHBHDLC!LM!DCNDEDN@B>G>G!HQBH!BAF!F^SFRHFN!HL!8F!LRR@SDFN! 89!FBRQ!BTFCH!DC!HQF!ML>>LWDCT! HD=F , GHB=S;!+QLGF!RF>>G!BAF!=LGH>9!NFHFA=DCFN!89!@GDCT!HQF! +## ! GDCRF!S FNFGHADBCG!BAF!=LGH>9!F^SFRHFN!HL!=LEF!HLWBAN!HQF!NFGHDCBHDLC!LA!F^DH!DC!HQF!GQLAHFGH!WB9;! +Q@G_!B>LCT!HL!HQF!TABNDFCH!LM!HQF! +## ; ! , , ,

PAGE 72

ih ! ! (;98>6;G<;7,&6;C8FB>:786;,8;,7@<,16D>9!L8GFAEFN!DC!HQF!FEBR@BHDLC! >LRBHDLCG>!ND=FCGDLC!LM!YJ!RFCHD=FHFAG!DG!RLCGDNFAFN;!+QF!=LNF>!@GFG!3/!BG!B! NFHBD>FN!AFSAFGFCHBHDLC!LM!HQF!GD=@ >BHDLC!GSBRFG!BG!B!GHBHF!LM ! YJR=!^!YJR=!G?@BAF!RF>>;!+QF!RF>>!ND=FCGDLC!DG!RLCGDNFAFN!G@RQ!HQBH!B! =B^D=@=!NFCGDH9!LM!B8L@H!g \ h!SFNFGHADBCG`= I ! DG!@G@B>>9!L8GFAEFN!N@ADCT!EFA9!RALWNFN! GDH@BHDLCG;!&CDHDB>>9 >>;!/C!BTFCH!RBC!HABCGMFA!HL!BCLHQFA!RF>>!DC!HQF!(LLAF! CFDTQ8LAQLLN!LM!ABND@G!O!ZrYi>! DC!HQF!BAFB>G!DG!NFHFA=DCFN; ! ! 28F B><,VN , +QF!CF^H!HD=F , GHB=S!HBATFH!RF>>G ; ! PN ! (IH<>8G<;7:786;,:;D,!;:EJ=8= , +L!RLEFA!HQF!WQL>F!ABCTF!LM!NFCGDHDFGBHDLCG!WDHQ!EBADB8>F!SLS@>BHDLC!GD]FG! QBEF!8FFC!RL CN@RHFN;!+QF!F^SFAD=FCHG!DC!WQDRQ!HQF!GD]F!LM!HQF!RALWNG ! DG! GRB>F N ! @S FG!DC!HQF!FCEDALC=FCH!BTFCHG!CBEDTBHFG! WFAF!NLCF!WDHQ!RQBCTFG!QBSSFCDCT!DC!HQF!FCEDALC=FCH>DCT!WB>>!LA ! B!R>LGDCT!SBHQ;! !

PAGE 73

iU ! ! +L!DCEFGHDTBHF!HQF!SFAMLA=BCRF!LM!HQF!SALSLGFN!=LNF>F^DH9!WFAF!NFGDTCFN;!+QF!RALWN!8FQBEDLA!DG!=LAF! RL=S>DRBHFN!DC!HQF!HQDAN!GRFCBADL!HQBC!HQLGF!DC!HQF!MDAGH! BCN!GFRLCN!LCFG!HQAL@TQ!HQF!DCHALN@RHDLC! LM!=LAF!L8GHBR>FG!BCN!HQF!AF=LEB>!LM!B! C@=8FA!LM!HBATFHG!ZF^DHG[!BEBD>B8>F!DC!HQF!FCEDALC=FCH;! +QF!MDAGH!GRFCBADL!DG ! IJ=!n!OJ=!WDHQ!GD^!F^DHG>!BG!=LAF!RL=S>F^!DCHFADLA! WB>>G!BG!GQL WC!DC! 6DT@AF ! g;!/!GCBSGQLH!LM!HQF!GD=@>BHDLC!DG!TDEFC!DC! 6DT@AF ! h ! D>>@GHABHDCT ! RALWN! =LEF=FCHG!MD>>DCT!HQF!GSBRF;!+QF!8>BR_!NLHG!AFSAFGFCH!BTFCHG!DC!HQF!MBRD>DH9;!+QF!8>@ FD=F>DTFCH!BTFCHG!WDHQ!NDMMFAFCH!ABC_DCT;! ! ZB[!6D AGH!GRFCBADL; ! ! ! ! ! ! Z8[!2FRLCN!GRFCBADL; ! !" !# !$ !% !& !' !" !# !$ !%

PAGE 74

KJ ! ! ! ! Z8[!+QDAN!GRFCBADL ; ! 28FB><,WN, 3LCMDT@AFN!GD=@>BHDLC!FCEDALC=FCHG; ! ! 28FB><,XN, 2RAFFCGQLH!LM!HQF!GD=@>BHDLC! FCEDALC=FCH!Z+QDAN!GRFCBADL[ ; ! !" !# !$

PAGE 75

KO ! ! 6DT@AF ! U!GQLWG!HQF!EBADBHDLC!LM!NFCGDH9!HL!FBRQ!HBATFHc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m!HQ@G< ! HQFAF!DG!CL!D=S>F= FCHBHDLC!LM! HA@GHWLAHQDCFGG!=LNF>;!+QF!GFRLCN!RBGF!DG!CLC , NFHFA=DCDGHDR>LW!LA!CLH!ML>>LW!HQF!DCHF>>DTFCH!BTFCH!DC!HQBH!AFTDLC;!&C!HQF!HQDAN!RBGFBHDLC!WBG!D=S>F=FCHFN!WDHQL@H!DC EL>EDCT!HQF!HBRHDRB>!>FEF>!WQDRQ ! =FBCG! HQFAF!DG!CL!F^DGHFCRF!LM!DCHF>>DTFCH!BTFCHG!DC!HQF!GD=@>BHDLC!BCN!C L!BSS>DRBHDLC!LM!HA@GHWLAHQDCFGG; ! &C!HQDG!RBGF< ! SFNFGHADBCG!=LEF!CBH@AB>>9!WDHQL@H!BC9!DCGHA@RHDLCG;! 6LA!FBRQ!GD=@>BHDLC!GRFCBADLFN!@GDCT!NDMMFAFCH!>LBNDCT!EB>@FG!ZNDMMFAFCH!SLS@>BHDLC!GD]FG[! HL!RLEFA!HQF!WQL>F!ABCTF!L M!NFCGDHDFG;!&C!FBRQ!GD=@>BHDLCLBNG!LM!RALWNG!BAF! RLCGDNFAFN>!RALWNBATF!RALWN; ! &C!6DT@AF!U@F! ABNDBCRF!AFSAFGFCHG!HQF!QDTQFA!MLARF!LM!BHHABRHDLC!LM!HQF! "## ! EB>@F;!+QF!9F>>LW!ABNDBCRF! D>>@GHABH FG!BELDNDCT!BAFBG!HQBH!SAFEFCH!LA!NF>B9!BTFCHG!MAL=!AFBRQDCT!HQFDA!F^DH; !

PAGE 76

KI ! ! ! ! ZB[!6DAGH!GRFCBADL ; ! ! ! ! ! ! Z8[!2FRLCN!GRFCBADL ; ! Z8[!+QDAN!GRFCBADL ; ! 28FB><,YN , 2RFCBADLG!HBATFHGc!M>LLA!MDF>N!Z "## [;! ! ,

PAGE 77

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cG!FMMDRDFCR9!DC!SAL=LHDCT!HQF ! LEFAB>>! HABEF>!HD=F!LM!HQF!RALWN!N@ADCT!FEBR@BHDLC!MLA!NDMMFAFCH!SLS@>BHDLC!GD] FG!MLA!HQF!HQAFF!GRFCBADLG;! +QF!EB>@FG!LM!HQF!GFCGDHDEDH9!SBAB=FHFAG!DC! HQF ! A@CG!MLA!HQDG!F^SFADFCRF!WFAF!BG!ML>>LWGX! o p ! o!I;J>9>!BTFCHG!DC!HQF!FCEDALC=FCH!QBEF!8FFC!FEBR@BHFN!DC!B!GQLAH!BCN! AFBGLCB8>F!HD=F ; ! "LWFEFA< ! DH!HLL_!HQF!BTFCHG!B!>LCTFA!HABEF>!HD=F!HL!FEBR@ BHF!DC!HQF!>BGH!RBGFLCTFGH!HD=F! HL!FEBR@BHF!DC!HQF!1LC , (*(2 , /$(!RBGF>LWG;!+QDG!?@B>DHBHDEF!HFCNFCR9!DG!G DTCDMDRBCH!MLA!B>>!HQF!RALWN!>LBN G ! F^RFSH!MLA! HQF!G=B>>!RALWN!>LBN!LM ! iJJ!BTFCHG;!+QF!GB=F!HFCNFCR9!WBG!L8GFAEFN!DC!HQF!GFRLCN!GRFCBADL;!&C! HQF!HQDAN!GRFCBADLLCTFGH!HD=F!H L!FEBR@BHF!DC!HQF!1LC , (*(2 ,

PAGE 78

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

PAGE 79

Ki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

PAGE 80

KK ! ! ! Z B[!6DAGH!GRFCBADL ; ! Z 8[!2FRLCN!GRFCBADL ; ! ! " #! #" $! #!!! $!!! %!!! &'()*+(,)-.*+(/0.++1(/0.23()0435 6708.,+'9+4.:.3(,/); <=<>?@A<+1B.(.,0/;/3(/C5 <=<>?@A<+16';?B.(.,0/;/3(/C5 6';2<=<>?@A< ! "! #! $! %! &! '! (! "!!! #!!! $!!! )*+,-.+/,01-.+231..4+23156+,3768 9:3;1/.*<.71=16+/2,> ?@?ABCD?.4E1+1/32>26+2F8 ?@?ABCD?.49*>BE1+1/32>26+2F8 9*>5?@?ABCD?

PAGE 81

Kg ! ! ZR[!+QDAN!GRFCBADL ; ! 28FB><,MMN, +LHB>!HABEF> ! HD=F!HL!FEBR@BHF!HQF!GB=F!BTFCH! N@ADCT!HQF!HQAFF!RBGFG ; ! +QF!GFRLCN!MDCNDCT!D>>@GHABHFG!HQF!=LNF>cG!RBSB8D>DH9!LM!D=SALEDCT!HQF!RALWN!M>LW! SBHHFAC;!+QF!EB>@FG!LM!HQF!GFCGDHDEDH9!SBAB=FHFAG!LM!HQF!M>LLA!MDF>NG!DC!HQF!A@CG!HQBH!AFSAFGFCHG! DCNDEDN@B>pG!ABND@G ! MLA!HQDG!F^SFADFCRF!WFAF!GFH!BG! ML>>LWGX ! ] ^ oP;JLW!ABHF!DG ! HQF!QDTQFGH!DC!HQF!CLC , NFHFA=DCDGHDR!RBGF>LWFN!89!HQF!NFHFA=DCDGHDR!RBGF!DC!HQF!GFRLCN!GRFCBADL=LGH! HQF!GB=F! 8FHWFFC!HQFGF!HWL!RBGFG!DC!HQF!GFRLCN!GRFCBADL!BCN!HQF!M>LW!ABHF!DG!HQF!QDTQFGH!DC!HQF! NFHFA=DCDGHDR!RBGF!DC!HQF!HQDAN!GRFCBADL;!&C!RLCHABGHLWFGH!M>LW!ABHF!DG!DC!HQF!1LC , (*(2 , /$(!RBGF!DC!B>>!GRFCBADLG;!&C!TFCFAB>9!BH!H QF!8FTDCCDCT!LM!HQF! GD=@>BHDLC!BCN!TABN@B>>9!8FRL=FG!G>LWFA!BG!HQF!FEBR@BHDLC!SALRFFNG< ! DCNDRBHDCT!HQF!B8D>DH9!LM! SALSLGFN!=LNF>!HL!D=SALEF!HQF!LEFAB>>!RALWN!M>LW!N@ADCT!FEBR@BHDLC;! ! ! "! #! $! %! &! '! (! )! *! "!!! #!!! $!!! +,-./0-1.23/0-453006-45378-.598: ;<5=310,>093?38-14.@ ABACDEFA06G3-3154@48-4H: ABACDEFA06;,@DG3-3154@48-4H: ;,@7ABACDEFA

PAGE 82

Kh ! ! ZB[!6DAGH!GRFCBADL ; ! ! ! Z8[!2FRLCN!GRFCBADL ; ! ! ! ! ! ! ! !"# !"$ !"% !"& !"' !"( !") !"* !"+ # ' + #% #) $# $' $+ %% %) &# &' &+ '% ') (# (' (+ )% )) *# *' *+ +% +) #!# #!' #!+ ##% ##) #$# #$' #$+ #%% #%) #&# #&' #&+ ,-./0123405647483192:;<;8= >9@CDA05E4341<9:9839F= ABA>@CDA05G.:@E4341<9:9839F= G.:HABA>@CDA ! !"# !"$ !"% !"& !"' !"( !") !"* !"+ # % ' ) + ## #% #' #) #+ $# $% $' $) $+ %# %% %' %) %+ &# &% &' &) &+ '# '% '' ') '+ (# (% (' () (+ ,-./0123405647483192:;<;8= >9@CDA05E4341<9:9839F= ABA>@CDA05G.:@E4341<9:9839F= G.:HABA>@CDA

PAGE 83

KU ! ! ! ZR[!+QDAN! GRFCBADL ; ! 28FB><,MON, 3@=@>BHDEF!M>LW!LM!BTFCHG ; ! +QF!GSFFN!LM!HQF!BTFCHGc!=LEF=FCH!HL!FEBR@BHF!WBG!=FBG@AFN!89!HABR_DCT!HQF!GB=F!BTFCH! N@ADCT!HQF!GD=@>BHDLC!@CNFA!NDMMFAFCH!RLCNDHDLCG!BCN!NDMMFAFCH!RALWN!>LBNG;!&H!RBC!8F!CLHDRFN! MAL=! 6DT@AF ! OP! HQBH!HQF!CLC , NFHFA=DCDGHDR!(*(2 , /$(!=LNF>!QBG!L8EDL@G!BNEBCHBTFG!LEFA! LHQFA!HWL!=LNF>G!DC!HQF!MDAGH!BCN!GFRLCN!GRFCBADLGBGH!GRFCBADL!BG!HQF!RALWN!FEBR@BHFN!=LAF!?@DR_>9!HQBC!DC!HQF!1LC , ! (*(2 , / $(!=LNF>;!+QF ! GFCGDHDEDH9!SBAB=FHFAG!MLA!HQDG!F^SFAD=FCH!BAF ! BG!ML>>LWGX ! ] ^ o I ;J9@CDA05E4341<9:9839F= ABA>@CDA05G.:@E4341<9:9839F= G.:HABA>@CDA

PAGE 84

gJ ! ! ZB[!6DAGH!GRFCBADL ; ! ! Z8[!2FRLCN!GRFCBADL ; ! ZR[!+QDAN!GRFCBADL ; ! 28FB><,MPN, /TFCHGc!BEFABTF!GSFFN ; ! ! !"# $ $"# % %"# & &"# ' '"# $!!! %!!! &!!! ()*+,-./0*1/)*.23**4.56728 9:6;*1.<=.3*4*2,1>/+ ?@?AB(C?.5D*,*16>+>2,>E8 ?@?AB(C?.59<+BD*,*16>+>2,>E8 9<+F?@?AB(C? ! !"# $ $"# % %"# & &"# ' $!!! %!!! &!!! ()*+,-./0*1/)*.23**4.56728 9:6;*1.<=.3*4*2,1>/+ ?@?AB(C?.5D*,*16>+>2,>E8 ?@?AB(C?.59<+BD*,*16>+>2,>E8 9<+F?@?AB(C? ! !"# $ $"# % %"# & &"# $!!! %!!! &!!! '()*+,-./)0.()-12))3-45617 895:)0-;<-2)3)1+0=.* >?>@A'B>-4C)+)05=*=1+=D7 >?>@A'B>-48;*AC)+)05=*=1+=D7 8;*E>?>@A'B>

PAGE 85

g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

PAGE 86

gI ! ! ! Z8[!2FRLCN!GRFCBADL ; ! ZR[!+QDAN!GRFCBADL ; ! 28FB><,MRN, 3QBCTFG!DC!SLS@>BHDLC!GD]F!LEFA!HD=F!DC!NDMMFAFCH!FEBR@BHDLC!GRFCBADLG ; ! ! &C!BNNDHDLC>LWDCT!F^SFAD=FCH!GQLWG!HQF!=LNF>cG!FMMDRDFC R9! DC ! @STABNDCT!HQF! BTFCHcG!GHBH@G ! N9CB=DRB>>9 BHDLC;!+QF! GHBH@G!B>HFABHDLC!NFSFCNG!LC!RQBCTFG!DC!HQF!G@AAL@CNDCTG!LA!RQBCTFG!DC!HQF!BTFCHcG!L8aFRHDEF! SBAB=FHFAG;!+QF!F^SFAD=FCH!WBG!RLCN@RHFN!LC! HQF!HQDAN!GRFCBADL!BCN!HQF!C@=8FA!LM!BTFCHG! WBG ! ! " #! #" $! $" # % " & ' ## #% #" #& #' $# $% $" $& $' %# %% %" %& %' (# (% (" (& (' "# "% "" "& "' )# *+,-./0120.345+..60 78,+94:81;0:8,. < 6:4,=6 >?>7<@A>0BC.:./,8;86:85D >?>7<@A>0B*1;?>7<@A> ! " #! #" $! $" %! # % " & ' ## #% #" #& #' $# $% $" $& $' %# %% %" %& %' (# (% (" (& (' "# "% "" "& "' )# *+,-./0120.345+..60 78,+94:81;0:8,. < 6:4,=6 >?>7<@A>0BC.:./,8;86:85D >?>7<@A>0B*1;?>7<@A>

PAGE 87

gP ! ! OJJJ;! +QF!EB>@FG!LM!HQF!GFCGDH DEDH9!SBAB=FHFAG!DC! HQF ! A@CG!MLA!HQDG!F^SFADFCRF!WFAF!BG!ML>>LWGX! ] ^ ! o!O;h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

PAGE 88

gY ! ! ! 28FB><,MVN, +FGHDCT!N9CB=DRG!LM!@STABNDCT!=LNF>!HQAL@TQ!SFNFGHADBC c!BEFABTF!GSFFN ; ! 6DT@AF!Og!GQLWG!HQF!RALWNcG!LEFAB>>!HABEF>!HD=F! N@ADCT!FEBR@BHDLC!WQFC!HQF!FCEDALC=F CH! DG!N9CB=DR B>>9!RQBCT DCT ! RL=SBA FN ! HL! WQFC!HQF!FCEDALC=FCH!DG!GHBHDR ; ! />GL< ! 6DT@AF!Oh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
PAGE 89

gi ! ! 28FB><,MWN, 3L=SBADCT , FEBR@BHDLC!H LHB>!HD=F! WQFC ! HQF!FCEDALC=FCH!DG!N9CB=DR!EG;!GHBHDR ; ! 28FB><,MXN, 3L=SBADCT , G9GHF=!HQAL@TQS@H ! WQFC!HQF!FCEDALC=FCH!DG!N9CB=DR!EG;!GHBHDR ; , +QF!AFG@>HG HG!DG!DCGDTCDMDRBCH!WQFC!RLCGDNFADCT!HQF!BTFCHGc!HABEF>!HD=F!BCN! HQFDA!GSFFN;!&C! BNNDHDLC9DCT! $ ! ! B>TLADHQ=!WBG!B8>F! HL!GD=@ >BHF!HQF!RBGF!LM!=LEF=FCH!DC!B!8>LR_FN!ZLA!CLC , F^DH[!BAFB;!+QF!AFG@>HG!GQLW!HQBH!DC!HQF!>BGH! GRFCBADLF^! FCEDALC=FCH!WDHQ!=LAF!L8GHBR>FG!BCN!>FGG!F^DGHG !ZNFHFA=DCDGHDR!BCN!CLC , NFHFA=DCDGHDR[!B>WB9G!L EFARL=F!HQF!1LC , (*(2 , /$(!=LNF>!@CNFA!B>>!F^SFAD=FCHG!WDHQ!=LAF!8FCFMDHG!LM!HQF!NFHFA=DCDGHDR!LEFA!CLC , NFHFA=DCDGHDR!RBGF; ! ! " # $ % &! &" &# &$ &% "! & ' ( &) &* "& "' "( )) )* #& #' #( ') '* $& $' $( *) ** %& %' %( () (* &!& &!' &!( &&) &&* &"& &"' +,-./01231/456,//7 89-,:5;92<1=9-/ > 7;5-? @A<5-965:1/<4902<-/<; 8;5;961/<4902<-/<; ! "! #!! #"! $!! $"! %!! %"! &!! '()*+,-*./0)1,23)+0)4 54*4,-/0)1,23)+0)4 634*./42*10./4,+0/74,+0894*+:9;

PAGE 90

gK ! ! !HHE8 ?:786;,6C,1/1# K !"1,16D,6C,!E K , 5:>:G,!E K #@:>8C,8;,1:QQ:@ ! + L! NF=LCGHABHF!HQF!GRB>B8D>DH9!LM!HQF!SALSLGFN!BSSALBR Q!DG!F^B=DCFN!MLA! =LNF>DCT!RALWN!8FQBEDLA!BCN!N9CB=DRG!DC!B!GSFRDMDR ! >BATF , GRB>F!GRFCBADL ! kOgJl ; ! +QF ! CLEF>!=@>HD , RL=SLCFCH!BTFCH , 8BGFN!=LNF>DCT!MAB=FWLA_!DG!BSS>DFN!HL!GD=@>BHF!HQF!RL=SLCFCHG!LM! EBA9DCT! DCNDEDN@B>!8FQBEDLAG! BCN!SQFCL=FCB!LM ! RL=S>F^!G9GHF=G! WDHQDC ! HQF ! =BGGDEF!RALWN! HQBH! AFSAFGFCHG!HQF!SD>TAD=G!BHHFCNDCT ! SAB9FAG! DC!HQF!/> , ! "BAB=!/> , 2QBADM!(LG?@F!Z(BGaD N!/> , "BAB=[! kO gO l;!+QF!(BGa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kIlTAD=G!QBEF ! >DHH>F!BWBAFCFGG!LM!HQF!SQ9GDRB>!DCMABGHA@RH@AF!LM!HQF!(BGaDN!/> , "BAB=! MBRD>DH9!LA!HQF!FCHABCRFG!BCN!F^DHG!LM!HQDG!MBRD>DH9;!$FRB@GF!L M!HQF!@CMB=D>DBADH9!WDHQ!HQF! FCEDALC=FCH ! BCN!HQF!F^QB@GHDCT ! SFAMLA=BCRF!LM ! RFAHBDC!BRHDEDHDFG!SD>TAD=G!BAF!CLH!B>WB9G!M@> >9! BWBAF!LM!HQFDA!F^BRH!>LRBHDLC!WDHQDC!HQF!8@D>NDCT; ! VAB@G]!BCN!$B@R_QBTF! kOhPl ! NFGRAD8F!HQF! RALWN!NFCGDHDFG!HQBH!RAFBHF!B!SBHHFAC!LM! =LEF=FCH!BG!B!bGHLS , BCN , TL!WBEF;e!+QDG!SBHHFAC ! DCNDRBHFG ! NBCTFAL@G!LEFARALWNDCT!HQBH!RL@>N!8F!NDMMDR@>H!HL!=BCBTF;!7QFC!H QDG!SBHHFAC!BSSFBAGF!DC ! HQDG!WBEF!=LEF!DC!B>>!NDAFRHDLCG>;! ! +QF!Q@TF!RALWN!LM ! @S!HL!PJTAD=G!DC!HQF!(BGaDN!/> , "BAB=!BAFB!RBCCLH!FBGD>9!8F! GD=@>BHFN;!6AL=!HQF!G@AEF9FN!SBSFAG< ! GFEFAB>!RALWN!GD =@>BHDLC!=LNF>G!BAF!BEBD>B8>F!MLA!HQF!

PAGE 91

gg ! ! GD=@>BHDLC!LM!FEBR@BHDLC!BCN!=LEF=FCHG!LM!HQF!RALWNG!RBC!LC>9!QBCN>F! AF>BHDEF>9! G=B>>!RALWNG!BCN!BAF!CLH!B8>F!HL!GD=@>BHF!HQF!EFA9!>BATF!RALWN!ZG@RQ!BG!SD>TAD=G[!WDHQ! BRR@ABR9!BCN!NFHBD>G;!+QF!SALSLGFN ! =LNF>! RBC ! GD=@>BHFF!SFAGLCB>!RL=S@HFAFEF>!LM!HQF!(BGaDN!/> , "B AB=!WDHQ!RLCGDNFAB8>F! B=L@CH!LM!NFHBD>G ; ! %<=BE7=,:;D,'8=?B==86; , +QF ! RALWN!>LBNDCT!DC!HQDG!GD=@>BHDLC!F^SFAD=FCHG!WBG!BR?@DAFN!MAL=! +QF!3FCHFA!LM! %FGFBARQ!-^RF>>FCRF!DC!"Baa!BCN! )=ABQ ! BCN!HQF!3@GHLNDBC!LM!HQF!+WL!"L>9!(LG?@FG!&CGHDH@HF!LM! "Baa!%FGFBARQ!BH! )==!/> , :@AB!)CDEFAGDH9!DC!(B__BQBA >9! RL>>FRH!BCN!BCB>9]F!NBHB!B8L@H!HQF!+WL!"L>9!(LG?@FG!DC!(B__BQ!BCN!/> , (BNDCBQ!kOhJl;!+QF! SLS@>BHDLC!GD]F!LM!HQDG!F^SFAD=FCH!WBG!OJLLA!MDF>N!Z "## [; ! ! , , , , , , , , , 28FB><, MY N, +QF!EBADBHDLC!LM!NFCGDH9!HL!FBRQ!F^DHcG!HBATFH!M>LLA!MDF>N!Z "## [; !

PAGE 92

gh ! ! +QF!MDAGH!MDCNDCT!D>>@GHABHFG!HQF!=LNF>cG!RBSB8D>DH9!LM!D=SALEDCT!HQF!RALWN!M>LW!SBHHFAC; ! 6DT@AF ! I J ! GQLWG!HQBH!BTFCHGc!M>LW! ABHF!WBG!QDTQFA!DC! HQF ! SALSLGFN!=LNF>!HQBC!HQF!HABNDHDLCB>! /$(!BSS >DRBHDLC;!+QBH!DCNDRBHFG!HQF!B8D>DH9!LM! HQF ! =LNF>!HL!D=SALEF!HQF!LEFAB>>!RALWN!M>LW! N@ADCT!FEBR@BHDLC;!&H!WBG!B>GL!ML@CN!HQBH!HQF!BTFCHGc!BEFABTF!GSFFN!N@ADCT!HQF!GD=@>BHDLC!WBG! QDTQFA!DC!HQ F!SALSLGFN!=LNF>;! 6DT@AF ! I O ! GQLWG!HQF!FGHD=BHDLC!LM!HQF!BEFABTF!GS FFN!LM!OJBHDLC; ! ! 28FB>< , O Z N, 3@=@>BHDEF!M>LW!LM!BTFCHG ! HL!FEBR@BHF ; ! ! !"!!!# !"!!$ !"!!$# !"!!% !"!!%# !"!!& !"!!&# $ ' $# %% %( &) *& #! #+ )* +$ +' '# (% (( $!) $$& $%! $%+ $&* $*$ $*' $## $)% $)( $+) $'& $(! $(+ %!* %$$ %$' %%# %&% %&( %*) %#& %)! %)+ %+* %'$ %'' ,-./0123405 647483192: ;<;8= >9@CDA E.:@ABA>@CDA

PAGE 93

gU ! ! ! 28FB><, O M N, /EFABTF!GSFFN!LM!BTFCHG ; ! +QF!GFRLCN!AFG@>H!DG!AF>BHFN!HL!NF=LCGHABHDCT!HQF!= LNF>cG!FMMDRDFCR9!DC!SAL=LHDCT!HQF! RALWNcG ! LEFAB>>!HABEF>!HD=F!N@ADCT!FEBR@BHDLC;!2SFRDMDRB>>9>!BTFCHG!DC!HQF! FCEDALC=FCH!QBEF!8FFC!FEBR@BHFN!DC!B!GQLAHFA!HD=FF!DH!HLL_!HQF!BTFCHG!B!>LCTFA!HD=F!HL! FEBR@BHF!DC!HQF!HABNDHDLCB>!/ $(!=LNF>!HABEF>!HD=F! MLA!IJJ!BTFCHG!DC!8LHQ!RBGFG;!+QDG!AFG@>H!NF=LCGHABHFG!HQF!8FCFMDH!LM!AF>9DCT!LC!BC!DCHF>>DTFCH! BTFCH!HL!D=SALEF!HQF!FEBR@BHDLC!LEFAB>>!HABEF>!HD=F!BCN!HQF!FMMDRDFCR9!LM! HQF ! =LNF>G!DC!BRR@A BHF>9! GD=@>BHDCT!HQF!FEFCHG!N@ADCT!RALWN!F EBR@BHDLCG;! 2 DTCDMDRBCH!D=SALEF=FCH!LM!RALWN!M>LWG ! WBG! L8GFAEFN ! N@ADCT!GD=@>BHDLCG!RL=SBAFN!HL!RALWN!M>LWG!L8GFAEFN!N@ADCT!GD=@>BHDLCG!@GDCT! HABNDHDLCB>!BSS>DRBHDLCG!LM!/$(;!+QFGF!L8GFAEBHDLCG!RL@>N!DCM>@FCRF!=@>HD S>F!BGSFRHG!LM!QLW! FEBR@BHDLCG!BAF!S>BCCFN ! G@RQ!BG!HQF!S>BRF=FCH!LM ! F^DHG!DC!8@D>NDCTGHG!GQLW!HQBH!HQF!SALSLGFN!=@>HD , >FEF>FN! =@>HD , GHBTFN!BTFCH , 8BGFN!=LNF>!L@HSFAMLA=G!HQF! HABNDHDLCB>!/$(!BSSALBRQ!DC!D=SALEDCT!HQF! RALWN!N9CB=DRG!N@ADCT!FEBR@BHDLC!DC!B!QDTQ , NFCGDH9!GD=@>BHDLC!>LTDR;! ! , , "#"$ % &'" ! ()* % "#"$ % &'" !

PAGE 94

hJ ! ! 28FB><, O O N, +LHB>!HABEF>!HD=F!HL!FEBR@BHF ; ! +QF!BD=!LM!HQF!=LNF>!DC!G@RQ!RBGFG!DG!HL!QF>S!"Baa!BCN!)=ABQ!RALWN!=BCBTF=FCH! B@HQLADHDFG!8@D>N! G@R RFGGM@>!GRQF=BG!89!SAFNDRHDCT!RALWN!8FQBEDLA;!+QF!SALSLGFN!/$(!=LNF>!DG ! B8>F!HL!D=SALEF!RALWN!=BCBTF=FCH!GL>@HDLCG!89!RLCGDNFADCT!HQF!NDEFAGDH9!LM!SD>TAD=G ! BCN!HQFDA! DCNDEDN@B>!RQBABRHFADGHDRGHG!GQLW!HQF!B8D>DH9!LM!HQF!=LNF>!HL!G@SSLAH!HQ F! Q FHFALTFCFDH9!BCN!QDTQ!NFCGDH9!L8GFAEFN!B=LCT!HQF!=BGGDEF!C@=8FAG!LM!SD>TAD=G!89!@GDCT!G=B>>! HD=F!GHFSG!DC!LANFA!HL!RLCGDNFA!NDMMFAFCH!SFNFGHADBC!GSFFNG!BCN!AFN@RFN!=L8D>DH9!LM!GL=F!LM!HQF=NFA>DFG;!+QF!AFG@>HG!LM!HQDG!=LNF>TAD=G!RBAA9DCT!L@H!HQF!FEBR@BHDLC!=LEF=FCHG!DC!B!RBGF!LM!NBCTFAL@G! FEFCHG@NFG!CFW!A@>FG!BCN!QDTQFA!BRR@ABR9!BCN!M>F^D8D>DH9!RL=SBAFN!HL!HQF!F^DGHDCT!=LNF>G;! +QF!=LNF>!DCHFTABHFG!B!NDGRAFHF , FEFCH!BRHDL CG! =LNF>!DCHL!HQF!>BATF!RALWN!GD=@>BHDLCBHDLC!LM!BRHDLCG!BCN!=LEF=FCHG!LM!DCNDEDN@B>!SD>TAD=G!TDEFG!@G!DCGDTQH!DCHL!HQF!F=FATFCH! 8FQBEDLAG!LM!HQF!RALWN;!+QF!F^SFAD=FCHB>!AFG@>HG!SALEDNF!FEDNFCRF!HQBH!HQF!Q98ADNHD , >B9FAFN! BSSALBRQ!RBC!8F ! G@ RRFGGM@>>9!BSS>DFN!HL!FMMDRDFCH>9!GD=@>BHF!BTFCH!8FQBEDLAG!DC!DCHFCGDEF!RALWN! FCEDALC=FCHG;! ! (*(2 , /$( ! 1LC , (*(2 , /$( ! "#"$ % &'" ! ()* % "#"$ % &'" !

PAGE 95

hO ! ! &5!4$(%, T , '(&)#)*+,#344*%$,#U#$(1,2*%,#)13/!$)+0,!+',1*'(/)+0 , , *2,$%!22)&,'U+!1)&#, , );7>6DB?786; , /!GDTCDMDRBCH!B=L@CH!LM!AFGFBARQ!QBG!BNNAFGGFN!WB9G!LM!DCRLASLABH DCT!HFRQCL>LT9!HL!QF>S! BELDN!EFQDR>F!RL>>DGDLCG!BCN!AFN@RF!ALBN!BRRDNFCHG! kO gI , OgK l;!&H!QBG!8FRL=F!F^HAF=F>9!D=SLAHBCH! HL!NFEF>LS!FMMFRHDEF!HABCGSLAHBHDLC!GHABHFTDFG!HQBH!WD>>!CLH!LC>9 ! FCQBCR F!HQF!?@B>DH9!LM!>DMF!LM! DCNDEDN@B>G!WQL!@GF!S@8>DR! HABCGSLAHBHDL C!8@H ! RBC!B>GL!RLCHAD8@HF!HL ! HQF!GBMFH9!LM!HQF!TFCFAB>! S@8>DR!kO gI F!D=S>F=FCHDCT!G@RQ!GHABHFTDFG!RBC!>FBN!HL!HQF!SAFEFCHDLC!LM!BRRDNFCHG< ! HQLGF!GHABHFTDFG!RL=F!WDHQ!GL=F!CFTBHDEF! RLCGF?@FCRFG!kO gI !SL>>@HDLC!QBEF!8FFC!DNFCHDMDFN!BG!HWL!LM!HQF!=LGH! RL==LC!DGG@FG!HQBH!BAF!>DC_FN!WDHQ!FEFA9NB9! @A8BC!HABMMDR!k OgY l;! +ABMMDR!RLCTFGHDLC!HB_FG!S>BRF! WQFC!HQF!ALBN!G9GHF=! RBSBRDH9!DG!DCG@MMDRDFCH!HL!QBCN>F!HQF!HABMMDR!M>LW!BCN`LA!WQFC!NADEFAG!MBD>! HL!RL==@CDRBHF!WDHQ!FBRQ!LHQFA!RL>>FRHDEF>9!DC!AFB>!HD=F;!3@AAFCH!GL>@HDLCG!8AL@TQH!DC!HL!D=SALEF! HABMMDR! RLCNDHDLCG!LMHFC!=B_F!>DMF!FBGDFA!MLA!B!G=B>>!SFARFCHBTF!LM!HQF!SLS@>BHDL C!WQD>F!=B_DCT! >DMF!=LAF!NDMMDR@>H!MLA!LHQFAG!kOgPF!B=L@CHG!LM!EFQDR@>BA! F=DGGDLCG!RLCHAD8@HF!HL!BDA!SL>>@HDLC!DC!@A8BC!CFHWLA_G!kOgKl;!+QF!QDTQ!MAF?@F CR9!LM!GHBAHDCT!BCN! GHLSSDCT!BH!HABMMDR!GDTCB>G!BCN!DCHFAGFRHDLCG!RLCHAD8 @HFG!HL!B!QDTQFA!EL>@=F!LM!M@F>!RLCG@=SHDLC! N@ADCT!A@GQ!QL@AG!BG!WF>>!BG!@CRLCTFGHFN!HD=FG!WQFC!HQF!M>LW!LM!EFQDR>FG!DG!DCHFAA@SHFN!89! R9R>DGHG!BCN!SFNFGHADBCG;!+QFAFMLAF>!HABMMDR!GRFCBADLG!BCN!HQDG!S>B9G!B! RA@RDB>!AL>F!DC!BC 9!M>LW!BCB>9GDG;! !

PAGE 96

hI ! ! %LBN!B@HQLADHDFG!DC!@A8BC!BAFBG!DCHFAFGHFN!DC!AFN@RDCT!F=DGGDLCG!CFFN!HL! 8F!BWBAF!LM! FEB>@BHF ! HQF!LEFAB>>!HLHB>!HD=F!HQBH!SFLS>F!BAF!GSFCNDCT!LC!HQF!ALBN!BCN!HQF!LSH D=@=!GSFFN!BH! WQDRQ!HQF!HABMMDR!GQL@>N!M>LW!kOgY , OgKl;!/!AFN@RHDLC!DC!F=D GGDLCG!LRR@AG!WQFC!HQF!C@=8FA!LM! BRRF>FABHDLCG!BCN!NFRF>FABHDLCG!NFRAFBGFGBRF!DC!@A8BC!BAFBG!BAF! QFBED>9!D=SBRHFN!89!HQFGF!HWL!MBRHLAG!ZBRRF>FABHDLCG!B CN!NFRF>FABHDLCG[;!+QFAFMLAF@BHFN ! khYLW!RAFBHFG!B!N9CB=DRB>>9!RL=S>F^!G9GHF=!GDCRF!DH!DCEL>EFG!B!CLC>DCFBA! DCHFABRHDLC!LM!=BC9!DCNFSFCNFCH!EFQDR>FG!WDHQ!>BATF>9!B@HLCL=L@G!8FQBEDLA;!+QFGF!DCHFABRHDL CG! RBC!>FBN!HL!GDH@BHDLCG!HQBH!SALN@RF!NDMMFAFCH!_DCNG!LM!HABMMDR!SAL8>F= G;!6LA!F^B=S>FFG!BAF!GH@R_!8FQDCN!LCF!NADEDCT!SBAHDR@>BA>9!G>LW>9;!/!C@=8FA! LM!=LNF>G!QBEF!8FFC!NFEF>LSFN!BCN!BSS>DFN!HL!GD=@>BHF!HQF!SA LRFGG!LM!EFQDR@>BA!N9CB=DRG! RB@GDCT!HABMMDR!aB=G!RB@GFN!89!G>LW , =LEDCT!EF QDR>FG!khiHG!LM!HQFGF! GH@NDFG!QF>S!AFGFBARQFAG!NFEF>LS!CFW!WB9G!HL!DCHFTABHF!BCN!DCRLASLABHF!HQF!DCRAFBGDCT!BEBD>B8D>DH9! LM!EFQDR>FG!kg , OJl;!4CF!SBAHDR@>BA> 9!FMMFRHDEF!RL=S@HBHDLCB>!GD=@>BHDLC!=FHQLN!DG!B! NFRFCHAB>D]FNHD , BTF CH!G9GHF=!Z(/2[9!WDHQ!DHG! D==FNDBHF!CFDTQ8LADCT!BTFCHG; ! +QF!FGGFCHDB>!RLCHAD8@HDLC!LM!HQDG!RQBSHFA!DG!BSS>9DCT!HQF!NFEF>LSFN!NDGHAD8@HFN! BARQDHFR H@AFG!HL!HQF!NDGHAD8@HFN!EFQDR>F!AL@HDCT , SAL8>F=;!+QF!(*(2 , /$(!MAB=FWLA_! SALEDNFG!B! NFRFCHAB>D]FN!SALRFGGDCT!BSSALBRQ!WQFAF!HQF!_F9 G ! HL!NDGHAD8@HFN!EFQDR>F!AL@HDCT! BAF ! HQF! @CNFA>9DCT!DCHFABRHDLC!AF>BHDLCGQDSG!LM!HQF!EFQDR>FG!HQF=GF>EFG;!+QF!(/2!RLCHBDCG! RL==@CDRBHDLC!RLCGHABDCHG9!WDHQ!HQFDA!D== FNDBHF! CFDTQ8LADCT!BTFCHG;!+QF!EFQDR>FG!GQBAF!DCMLA=BHDLC!WDHQ!HQF!LHQFA!EFQDR>FG!WDHQDC!HQFDA ! CFDTQ8LAQLLN;!2@RQ!RL==@CDRBHDLC!8FHWFFC!EFQDR>FG!RL=8DCFG!HQF!FMMFRHDEFCFGG!LM!HQF!

PAGE 97

h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kOgILT9!8FQDCN! DCHF>>DTFCH!HABCGSLAHBHDLC!G9GHF=G!DG!FEFA!D=SALEDCT;!+QF!BNEBCRF=FCHG!DC! SALRFGGDCT! RBSB8D>DHDFGLT9FG!BCN!NADEFAG!WDHQ!HQF!

PAGE 98

hY ! ! LSSLAH@CDH9!HL!MDT@AF!L@H!HQF!RLCNDHDLCG!HQBH!F^DGH!LC!HQF!ALBN!kOg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kOgP! AF?@DAF=FCHG!8FQDCN!DCHF>>DTFCH!HABCGSLAHBHDLC!G9GHF=G;!'BHB 9< ! SALEDNFG! HQF!AFGL@ARF!HQBH!DG!CFFNFN!HL!=B_F!DCHF>>DTFCH!NFRDGDLCG;!&=BTDCF!HQBH!BC!DCHF>>DTFCH! HABCGSLAHBHDLC!G9GHF=!DG!BGGDGHDCT!NADEFAG!DC!HB_DCT!HQF!8FGH!AL@HF;!4CF!BGSFRH!HQBH!RL@>N!8F! RLCGDNFAFN!DG!HQF!bTAFFN9 , AL@HDCT!DGG@Fe!HQBH!RBC!8F!GL>EFN!WDH Q! HQF!BGGDGHBCRF!LM!RFCHAB>D]FN! BARQDHFRH@AF;!&C!RLCHABGH!HL!B!NFRFCHAB>D]FN!G9GHF=>!HQF!DCMLA=BHDLC!DG!8FDCT!TBHQFAFN! >LRB>>9LRBHFN!LC!HQF!ALBN!DC!HQF!RFCHAB>D]FN! BARQDHFRH@AF;!+QFC>9HDCT!DCMLA=BHDLC!DG!SALEDNFN!DC!B! =FBCDCTM@>!=BCCFA!kOgID]FN!+FRQCD?@FG ! /=LCT!HQF!=FHQLNG!HQBH!RBC!8F!@GFN!HL!HBR_>F!HQF!NDGHAD8@HFN!EFQDR>F!AL@HDCT , SAL8>F=@HDLCG!8BGFN!LC!NDGHAD8@HFN!B AR QDHFRH@AF!QBEF!AFRFDEFN!B!>LH!LM!BHHFCHDLC!kOgID]FN!CFHWLA_!DG!D=S>F=FCHFNF!HL!BRQDFEF!NDGHDCRH!BNEBCHBTFG!LEFA!B! RFCHAB>D]FN!LCF;!6LA!F^B=S>F>!HQF!EFQDR>FG!HQBH!BAF!>LRBHFN!DC!B!GSFRDMDR!CFDTQ8LAQLLN!WLA _! BG! GFCGLAG!LC!HQFDA!LWC>9!8FCFMDHG!B!G9GHF=!LM!GFCGLAG!BCN!NBHB , BTTAFTBHLAG!kOhJl;!

PAGE 99

hi ! ! &C!BNNDHDLC>!HQF!EFQDR>FG!BAF! SALEDNFN!WDHQ!HQF!HFRQCL>LT9!HL!BRRFGG!NBHB!NFRDGDLCG;!/G!B!AFG@>HD=DCBHFN!FMMFRHDEF>9;!"LWFEFA>FCTDCT!8FRB@GF!HQF!EFQDR>FG!BAF!SALEDNFN!WDHQ!HQF! AFGSLCGD8D>DH9!LM!SALRFGGDC T! NBHB!BG!GLLC!BG!DH!BAADEFG!DC!BC!BG9CRQALCL@G!=BCCFA!kOghD]FN!/ARQDHFRH@AFG!BCN!(@>HD , /TFCH!29GHF=G , &C!NFRFCHAB>D]FN!BARQDHFRH@AFG!BCN!=@>HD , BTFCH!G9GHF=GF!DG!RLCGDNFAFN!B! SALRFGGDCT!@CDH!LM!DHG!LWC!kOhJl;!+QF!HFA=!bBTFC He ! DG!@GFN!HL!NFHFA=DCF!HQF!DCHF>>DTFCH!BRHLA!WQL!DG! DCHFABRHDCT!WDHQ!HQF!FCEDALC=FCH!EDB!BC!BRH@BHLA!LA!B!GFCGLA;!+QFAFMLAFHD , BTFCH!G9GHF=!DG!B! SALN@RH!RL=SLGFN!LM!=@>HDS>F!BTFCHG!DCHFABRHDCT!EDB!HQDG!CFHWLA_!HL!RL==@CDRBHF!WDHQ!LCF! BCLHQFA;!)GDCT! B! =@>HD , BTFCH!BSSALBRQ!WDHQDC!B!NDGHAD8@HFN!BARQDHFRH@AF!DG!EDB8>Fm!QLWFEFAEF!B!SAL8>F=;!&C!LHQFA!WLANG@HDLCG!@GFN!MLA!SBAHDR@>BA!DGG@FG!CFFN!HL!8F!@CNFAGHLLN;!"LWFEFAF!HL!RL=S@HF!B! TFCFAB>!GL>@HDLC!HQBH!_FFSG!BTFCHG!WQL!BAF!DCHFABRHDCT!WDHQ!LHQFA!BTFCHG!BWB9!MAL=!SFAMLA=DCT!B! GSFRDMDR!HBG_!kOgPBCCFN!RLCNDH DL CG;!+QDG!@CD?@F!=FHQLN!LM!RL==@CDRBHDLC!DG!@G@B>>9! RLCGDNFAFN!B!EFQDR>F , HL , EFQDR>F!RL==@CDRBHDLC!=FHQLN!kOOKFG;! ! +ABMMDR!CFHWLA_G!@G@B>>9!MDH!DCHL!B!=@>HD , BTFCH!SB ABNDT=;!7DHQ!HQF!/$(!=FHQLNF!HL!@CNFAGHBCN!B!GFH!LM!A@>FG!WQDRQ!NFHFA=DCF!HQF!8FQBEDLA!LM!B!GSFRDMDR!BTFCH;!+QDG! SALRFGG!DG!RB>>FN!b=BSSDCTe!LM!B>>!HQF!GFCGLA9!DCS@HG!HQBH!RBC!BRQDFEF!B!HBG_! kOgIHD , BTFCH!G9GHF=G!@GF!GFE FAB> ! NDMMFAFCH!GHBHFG;!/>>!GHBHFG!BAF!NFGDTCFN!HL!WLA_!DC!HQF! GF?@FCRF!LM!GFCGDCTBCCDCT
PAGE 100

hK ! ! B8L@H!HQF!FCEDALC=FCH!WDHQ!HQF!BGGDGHBCRF!LM! GFCGLAG>FRHFN!89!HQF!GFCGLAG!DG! @GFN! HL!RAFBHF!B!=LNF>!FCEDALC=FCH;!4CRF!HQF!BTFCH!DG!MB=D>DBA!WDHQ!HQF!FCEDALC=FCHLSG!BC! BRHDLC!S>BC!HQBH!RBC!8F!@GFN!HL!BRQDFEF!B!GSFRDMDR!TLB>HDS>F>FA!=FHQLNGFHF!HQF!NFGDAFN ! HBG_!k P HD , BTFCH! BSSALBRQF!BRHG!BG!BC!BTFCH;!+QDG!WB9F!HL!AFRFDEF!RL=SAFQFCGDEF! DCMLA=BHDLC!WQDRQ!DG!@GFN!HL!=B_F!B!8FHHFA!NFRDGDLC;!+QFGF!BTFCHG! BAF!SLGDHDLCFN!HL!RAFBHF!B! EFQDR@>BA!BN , QLR!CFHWLA _!Z./1-+[!kOPJl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kOPJl;!)GDCT!HQDG!G9GHF=DCT;!/G!B!AFG@>HDGH!LM!NFSFCN FCHG!WQL!BAF!BRHDCT!BG!L8GFAEFAG;! +QF9!BAF!GFCH!L@ H!WDHQ!B@HL=BHDR!CLHDMDRBHDLCG!LM!HQF!RQBCTFG!DC!GHBH@G;!&H!ML>>LWG!HQBH!HQF! RL=S>F^DH9!LM!HQF!G9GHF=!DCRAFBGFG!WQFC!DH!DG!RLEFADCT!>BATFA!TFLTABSQDRB>!8L@CNBADFG!WDHQ! BNNDHDLCB>!BTFCHG;! ! &C!B!NFRFCHAB>D]FN ! CFHWLA_FG!HQBH ! GQBAF!DCMLA=BHDLC!DC!HQF! GB=F!>LRB>!ABCTF;!+QF!F^RQBCTFN!NBHB!B=LCT!BTFCHG!DCR>@NF!8@H!BAF!CLH!>D=DHFN!HLX!3@AAFCH! SLGDHDLCLRDH9LRB>>9!SALRFGGFN!89!HQF ! EFQDR>FG;!

PAGE 101

hg ! ! +QDG!SALRFGG!LM!RL==@CDRBHDCT!BCN!F^RQB CTDCT!NBHB!RBC!8F!RLCGDNFAFN!BC!F^B=S>F!LM!B!S@AF!=@>HD , BTFCH!G9GHF=!NFEF>LSFN!LC!HQF!&+2!MAB=FWLA_;!2FEFAB>!GH@NDFG!khYD]FN!BSSALBRQ!L@HSFAMLA=G!B!RFCHAB>D]FN! LCF!89!D=SALEDCT!EFQDR>FGc!HABEF>! HD=FG;! ! 3FCHAB>D ]FN!`!'FRFCHAB>D]FN!+FRQCD?@FG ! &C!HQDG!BSSALBRQ!LM!&+2FG!BG!WF>>!BG! MAL=!HQF!GFCGLA!G9GHF=!kO gI >!8F!GFCH!8BR_!HL!HQF!EFQDR>FG;!/G!B!A FG@>HFG!BAF!SALEDNFN!WDHQ!HQF!B8D>DH9!HL!SALRFGG! HQF!NBHB!HQBH!HQF9!AFRFDEF!k Og gl;!+QF!EFQDR>FG!BAF!=B_DCT!HQFDA!LWC!NFRDGDLCG!WDHQL@H!QBEDCT!B! R>FBA!@CNFAGHBCNDCT!LM!HQF!DCHFCH!L M!HQF!LHQFA!EFQDR>FG!LC!HQF!ALBN;!"LWFEFAFG!BAF! AFRFD EDCT!RLCHDC@L@G!NBHBSG!HQF=!HL!BNBSH!BRRLANDCT!HL!HQF!RQBCTFG!DC!HFRQCL>LTDFG! kO gI Q , + ABMMDR!NDGHAD8@HDLC!BCN!AL@HDCT!SAL8>F= G ! RBC!8FFC!D=SALEFN!NAB=BHDRB>>9!89!D CEL>EDCT! 8LHQ!B!NFRAFBGF!DC!ALBN!BRRDNFCHG!BCN!HD=F!GSFCH!DC!CFHW LA_>!BG!BC!DCRAFBGF!DC!>FEF>!LM! GFAEDRF!Z*42[!kOOil;!/!C@=8FA!LM!BSSALBRQFG!BCN!B>TLADHQ=G!QBEF!8FFC!DCHALN@RFN!HL!GL>EF! HABMMDR!AL@HDCT!SAL8>F=G;!6LA!F^B=S>F;!kOgY!HD=F!GSFCH!DC!B!CFH WLA_!89!DCM>@FCRDCT!HQF!HABMMDR!NDGHAD8@HDLC!LEFA!BEBD>B8>F! ALBNG!DC!B!CFHWLA_;!+QF!SAL8>F=!QBG!8FFC!=LNF>FN!89!HQF!=FBCG!LM!B!CLEF>!AFEFAGF!2HBR_F>8FAT! TB=F!BSSALBRQ;!#@BC!BCN!7BCT!kOgKl!RLC N@RHFN!B!SAF>D=DCBA9!GH@N9!LM!8>LR_RQBDC!HFRQCL>LT9! BCN!NFGDTCFN! BC!&+2 , LADFCHFN!=LNF>!MLA!8@D>NDCT!SBAB>>F>!HABCGSLAHBHDLC!=BCBTF=FCH!G9GHF=G;! 1QB!FH!B>;!kOIPl!GH@NDFN!BCN!RL=SBAFN!HQF!SFAMLA=BCRF!LM!NDMMFAFCH!AL@HF , S>BCCDCT!B>TLADHQ=G!DC!

PAGE 102

hh ! ! AFB>!ALBN!CFHWLA _G!BCN!R>BGGDMDFN!HQF=!BRRLANDCT!HL!HQF!=FRQBCDG=G!@GFN!MLA!GFBAR QDCT!HQF!8FGH! AL@HFG;!3L=SBAFN!HL!HQF!SALSLGFN!=LNF>9!BC!BTFCH , 8BGFN! =LNF>DCT!BSSALBRQ!HL!GL>EF!HQF!EFQDR>F!AL@HDCT!SAL8>F=;!$FRB@GF!LM!HQF!F=FATFCH!SQFCL=FCB!L M! HABMMDR!RL=S>F^!G9GHF=G!RL=SLCFCHG;! -=S>L9DCT!HQF!BNa@GHB8>F!/$(!BSSALBRQ!QF>SG!HL!GD=@>BHF!Q@=BC!SFARFSH DLC!BCN!NFRDGDLC , =B_DCT!DC!RL=S>F^!GRFCBADLG!G@RQ!BG!HABMMDR!BRRD NFCHG;!+QFAFMLAF!DG!B8>F!HL!BRR@ABHF>9!GD=@>BHF!HQF!EFQDR>FGc!8FQBEDLAG!BCN!SQFCL=FCB>LWDCT!MLA! D=SALEFN!NFRDGDLCG!HB_FC!HL!FCQBCRF!HQF!HABMMDR!G9GHF=G;! ! 4C!HQF!LHQFA!QBCND]FN!BCN!NFRFCHAB>D]FN!BARQDHFRH@AFG!LC!HABCGSLAHBHDLC!=L8D>DH9!WQFC!BRRDNFCHG! NL! LRR@A;! "LWFEFA9!B!RLCEFCHDLCB>!=@>HD , BTFCH!BSSALBRQ!HL!D =S>F=FCH!B!TFCFAB>! GL>@HDLC!MLA!EFQDR>FG!DC!B!NDGHAD8@HFN!BARQDHFR H@AF;!%DB]!FH!B>;!khil!@HD>D]FN!BC!/$(!HL!=LNF>! RL>>DGDLC!NFHFRHDLC!BCN!BELDNBCRF!@CNFA!RLCTFGHFN!@A8BC!ALBN!HABMMDR;!/NNDHDLCB>>9;! kOPJl!@GFN!(/2!HFRQCL>LT9!HL!8@D>N!B!EFQDR@>B A!DCMLA=BHDLC!BN , QLR!CFHWLA_;!*D_FWDGF!MLA!HQF!GD=@>BHDLC!LM!CLC , GDTCB>D]FN!ALBN!RALGGDCTG! WQFAF!HQFAF!DG!B!NDAFRH!DCHFABRHDLC!8FHWFFC!SFNFGHADBC!BCN!EFQDR@>BA!HABMMDR;!+QF!HABMMDR!WBG! =LNF>FN!89!BSS>9DCT!B!R LCHDC@L@G!RBA!ML>>LWDCT!=LNF>!89!@GDCT!HQF!0DSSG!F?@BHDLCG!WBG!@GFN!HL!GD=@>BHF!SFNFGHADBC!=LHDLC;!$DFNFA=BCC!FH!B>;!kUIl!SALSLGFN!B!=@>HDGRB>F! BSSALBRQ!HL!SAFNDRH!HABMMDR!BCN!RALWN!M>LW!N@ADCT!S@8>DR!FEFCHG;!"B>> s ! FH!B>;!kOhYl!SALSLGFN!B! QDFABARQDRB>!=LNF>!HL!BNNAFGG!HQF!RLLANDCBHDLC!DGG@F!MLA!B!S>BHLLC ! LM!EFQDR>FG!89!RLCGDNFADCT!DH!BG! B!(/2;!3L=SBAFN!HL!HQF!SALSLGFN!(*(2 , /$(!=LNF>9!HQF! RLCEFCHDLCB>!/$( ! BCN!QBEF!CLH!=LNF>FN ! BC!FCHDAF!RL=S>F^!G9GHF=!@GDCT!=@>HDS>F!>B9FAG!LM!

PAGE 103

h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c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

PAGE 104

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cG!SAFMFAFCRFG;!&C! (*(2 , /$(FG!QBEF!HQF!B8D>DH9!HL!AFSLAH!DCMLA =BHDLC!HL!HQFDA!CFDTQ8LAG!EDB!HF>F=BHDR! HFRQCL>LT9@FCRFG!HQF!BA8DH ABHDLC!8FHWFFC!8FQBEDLAG;!+QF!DCMLA=BHDLC!8FHWFFC! EFQDR>FG!DG!F^RQBCTFN!HQAL@TQ!RL==@CDRBHDLCG!HFRQCL>LT9!G@RQ!BG!EFQDR>F , HL , EFQDR>F! RL==@CDRBHDLC!ZSLDCH!HL!SLDCH!ABNDL[F!SQLCF!HLWFAG;!6LA!F^B=S>FFG!_CLW!HQFDA!R@AAFCH!SLG DHDLC!8BGFN!LC!B!NDTDHB>!=BS!LA!BC!LC8LBAN!HF>F=BHDR!NFEDRF; , ! &C!BNNDHDLCBHFN!FCEDALC=FCH!WFAF!B>GL! RLCGDNFAFN!HL!FCG@AF!HQF!B@HQFCHD RDH9!LM!HQF!GD=@>BHDLC;!&H!QBG!8FFC!RLCGDNFAFN!HQBH!HQF! QFHFALTFCFDH9!LM!HQF!B TFCHGc!=LEF=FCH!GSFFN!DG!CLH!RLCGHBCH;!&CGHFBNFN! BG!B!RLCHDC@L@G>9!N9CB=DR!EBADB8>F!DCM>@FCRFN!89!HQF!G@AAL@CNDCT!NFCGDH9! RQBABRHFADGHDRG!L M!HQF!BTFCHGFN ! HL!8F!BNBSHFN!LC!HQF!BTFCHcG!R@AAFCH!RLCNDHDLC!BH!FBRQ!GD=@>BHDLC!GHFS;!&C!LHQFA!WLANG>!DCHFA=FNDBHF!RF>>G!8FHWFFC!QDG!R@AAFCH! >LRBHDLC!

PAGE 105

UO ! ! BCN!HQF!NFGHDCBHDLC!RF>>!BAF!CLH!LRR@SDFN!89!LHQFA!BTFCHG!LA!L8GHBR>FG;! &C!HQF!(*(2 , /$(! GD=@>BHDLC!=LNF>FG!DG!GFH!HL!8F!G!o!Ki ! =SQm!HQBH! DG!B8L@H!P!RF>>G`HD=F , GHB=S!DC!HQF!3/!FCEDALC=FCH;! +QF!GSFFN!W D>>!8F!_F SH!DC!HQF!=B^D=@=! GSFFN!@CHD>!HQF!NFCGDH9!EB>@F!BAL@CN!HQF!BTFCH!8FRL=FG!F?@B>!HL!O;!/!RL>>DGDLC!DG!RLCGDNFAFN!BG! =B^D=@=!NFCGDH9>!HQF!BNaBRFCH!RF>>G!LM!BC!BTFCH!BAF!M@>>;!+Q@GLRBHDLC!RBCCLH!8F!@SNBHFN;!&C ! HQF!RBGF ! WQFAF!GL=F!LA!B>>!LM!HQF!DCHFA=FNDBHF!RF>>G!BAF! LRR@SDFN!89!BCLHQFA!BTFCH!LA!L8GHBR>F>!8F!N9CB=DRB>>9!BNa@GHFN!HL!B!>LWFA! GSFFN!SALSLAHDLCB>!HL!HQF!NDGHBCRF!HL!HQBH!8BAADFA; ! />GLF; ! .FQDR>F! >FCTHQG!RBC!EBA9!MAL=!HQF!SBGGFCTFA!RBA!HL!B!HWL , B^F>!HA@R_;!&C!HQF!SALSLGFN!=LNF>F!R>BGGFG!BAF!B>>LWFN!BG!HQF!EFQDR>F!H9SF!RL=SLGDHDLC!RBC!EBA9!TAFBH>9;! %FRLTCD]DCT!HQF!NDMMFAFCRFG!8FHWFFC!EFQDR >FG!QF>SG ! @G!HL!RQBABRHFAD]F!HQF!(/2!G9GHF=!BG!B! QFHFALTFCFL@G!=@>HD , BTFCH!G9GHF=;!+QDG!B>>LWG!MLA!=B_DCT!NFRDGDLCG!HQBH!BAF!8FHHFA!G@DHFN!HL!HQF! H9SF!LM!EFQDR>F!@GFN;!$9!HB_DCT!HQDG!DCHL!BRRL@CHF!HB_FG!HQF! DCNDEDN@B>!LS HD=B>!AL@ HF!DC!RBGF!LM!MAFFWB9!BRRDNFCHG;!6LA!F^B=S>FFG!DC!HQF!HABMMDR!M>LW!EFQDR>FG! EFQDR>FGGL!RB@GF!NF>B9G;! ! (;98>6;G<;7 , &6;C8FB>:786;,8;,7@<,16D>!DG!GF>FRHFN!MAL=!HQF!MDEF!SLGGD8>F! RBCNDNBHF!RF>>G!DC!HQF!(LLAF!CFDTQ8LAQLLN!HL!NFMDCF!HQF!HABEF>>DCT!HABaFRHLA9DH9!M @CRHDLC
PAGE 106

UI ! ! ! ! , , , , , 28FB><, O P N ! +QF!CF^H!HD=F , GHB=S!HBATFH!RF>>G ! MLA!B!EFQDR>F ; ! !F<;7, #7:7B=,3HF>:D8;F,16DLRDH9!LM!BTFCHG!DC!(/2!DG!BC!FGGFCHDB>!DGG@F!HQBH!CFFNG!HL!8F!BNNAFGGFN;!+QF! DCHF>>DTFCH!BTFCHG!QBEF!HL!AF SLAH!HQFDA!R@AAFCH!EF>LRDH9!HL!HQF!ML>>LWFA!BTFCHG;!+QF!DCHF>>DTFCH! BTFCHG!BAF!BQFBN!LM!ML>>LWFA!BTFCHG>DTFCH!BTFCH!RLCHDC@FG ! QDG`QFA!=LEF=FCH!WDHQ! B!G@MMDRDFCH!EF>LRDH9>LWFA!BTFCHG!_FFS!HQFDA!R@AAFCH!AL@HF;!4C!HQF!LHQFA!QBC N>DTFCH!BTFCHc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

PAGE 107

UP ! ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM * /DR+=D=A-*\*#:&&:]( 92 ! HQFC ! DM * /DR+%(()*`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

PAGE 108

UY ! ! =DRALGRLSDR!>B9FA!8FRB@GF!HQF9!BAF!D=S>F=FCHBHDLC!RL=SLCFCHG!LM!HQF!>B9FA;!"LWFEFA!DG!SFAMLA=FN>DTFCH!BTFCHG!BAF!TFCFABHFNB9FA!DG!HQ@G>9!TFCFABHFN;!+QF!RL==@CDRBHDLC!BCN!HA@GHWLAHQDCFGG!FEB>@BHDLC!GHBTF! DG!SFAMLA=FN!DC!8LHQ!HQF!=DRALGRLSDR!BCN!=BRALGRLSDR!>B9FAG;! 6DT@AF! I Y ! GQLWG!HQF!HWL , >B9FAFN! GHA@RH@AF!LM!HQF!SALSLGFN!G9GHF=;! ! ! 28F B>< , O R N ! +ABMMDR!N9CB=DR!=LNF>DCT!>B9FAG ; ! +QF!BTFCHcG!8FQBEDLAG!HQAL@TQL@H!HQF!GD=@>BHDLC!RBC!8F!G@==BAD]FN!BG!ML>>LWGX ! • ! #:&&:]*V(>DQ':9X!WQFAF!ML>>LWFA!BTFCHG!ML>>LW!HQF!DCHF>>DTFCH!BTFCH!DC! HQFDA!AFTDLC!BCN!HB_F! HQF!AL@HF!RQLGFC!89!HQF!DCHF>>DTFCH!BTFCH;! />GL>LWDCT!8FQBEDLA>LWFA! EFQDR>FG!=BDCHBDC!B!NDGHBCRF!MAL=!HQF!EFQDR>F!DC!MALCH!LM!DH!HL!BNa@GH!HQF!NDGHBCRF!MLA!HQF!TDEFC! GSFFN; ! • ! aA')D!,(*V(>DQ':9X!&CHF>>DTFCH!BTFC HG!T@DNF!LHQFA!BTFCHG!HL!HB_F!HQF!8FGH!B>HFACBHF!AL@HFZG[ ! HQBH!BE LDN!RLCTFGHDLC!WQFC!BRRDNFCHG!LRR@A; !

PAGE 109

Ui ! ! • ! K:&&'-':!*DQ:')D!,(*V(>DQ':9X!+QDG!8FQBEDLA!DCR>@NFG!BC9!BRHDLCG!HQBH!BELDN!SLHFCHDB>! RL>>DGDLCG>DGDLC!WDHQ!L HQFA!EFQDR>FG;!+QLGF! BELDNBCRF!HFRQCD?@FG!BAF!8BGFN!LC! N9CB=DR!M>LLA!MDF>N ; ! • ! "9D!-'=':!*V(>DQ':9X!+QDG!8FQBEDLA!SALEDNFG!8BGDR!=LHDLC!M@CRHDLCG!BCN!HABEF>DCT!HFRQCD?@FG! 8BGFN!LC!GHBHDR!M>LLA!MDF>N!BCN!D=S>F=FCHBHDLC!LM!HQF! $P ! AL@HDCT!B>TLADHQ=!HL!HABEF>!MA L=!DHG! LADTDC!HL!DHG!NFGHDCBHDLC;!+QLGF!8FQBEDLAG!B>GL! DCR>@NF!L8GHBR>FG!BELDNBCRF!8BGFN!LC!L8GHBR>FG! M>LLA!MDF>N;!+QLGF!F>F=FCHBA9!8FQBEDLAG!BAF!DCM>@FCRFN!89!HQAFF!NDMMFAFCH!GRLSFGLRB>! GRLSF!ZL8GHBR>F , BELDNDCT!8FQBEDLA[!GRLSF!ZAL@HDCT , MDCNDCT!8FQBEDLA[!BCN!T>L8B>! GRLSF!ZHBATFH , GFBARQDCT!8F QBEDLA[; ! (IH<>8G<;7:786;,:;D,!;:EJ=8= , +QF!B8LEF!NFGRAD8FN!=LNF>DCT!MAB=FWLA_!DG!F^FR@HFN!DCNFSFCNFCH>9!DC!HQAFF!NDMMFAFCH! EFAGDLCG!LM!HQF!SALSLGFN!=LNF>;!6DAGH!DG!BSS>DFN!WQFAF!B>>!BTFCHG!GQL@>N!ML >>LW!HQF!DCHF>>DTFCH!BTFCH!DC!HQFDA!AFTDLC;!+Q@GF=FCHBHDLC!LM!HQF!HA@GHWLAHQDCFGG!G@8 , =LNF>;!2FRLCN!DG!HQF!CLC , NFHFA=DCDGHDR!HFRQCD?@F>LW!LA!CLH!HL!ML>>LW!HQF! DCHF>>DTFCH!BTFCH! DC!HQBH!AFTDLC;!+QBH!=FBCG!GL=F!LM!HQF!BTFCHG!BAF!DC!HQF!GL>DHBA9!=LNF;!"FAF9!iJt!LM!HQF!EFQDR>FG! BAF!B8>F!HL!RL==@CDRBHF! WDHQ!FBRQ!LHQFA!BCN!DCHF>>DTFCH!BTFCHG!DC!HQFDA!AFTDLC< ! WQD>F!DC!HQF! GFRLCN!G@8 , RBGFDH9!HL!RL==@CDRBHF!DG!GSFRDMDFN! 8BGFN!LC!HQF!HA@GHWLAHQDCFGG!G@8 , =LNF>;! ! &C!LANFA!HL!SFAMLA=!HQF!BCB>9GDG!LM!HQF!NDMMFAFCH!MLA=G ! LM!HQF!BTFCH , 8BGFN!NDGHAD8@HFN! AL@HDCT!B>TLADHQ=GBHFN!WDHQL@H!BC9!MLA=!LM!&+2;!&C! LHQFA!WLANGF=FCHFN!BG!B!8BGF>DCF!LM!HQF!F^SFAD=FCHG
PAGE 110

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i ! GQ LWG!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_!F^B=S>F!HQBH! RLCGDGHG!LM!B!MAFFWB9!BCN!RDH9!BAHFADB>!ALBNG;!+QF!ALBN!CFHWLA_!DG!RLCGDNFAFN!DC!WQDRQ!GFEFAB>! ALBN!GFT=FCHG!BAF!GQBAFN ! 89!NDMMFAFCH!AL@HFG!BGGLRDBHFN!WDHQ!HQF!GB=F>!BG!HQF!NDMMFAFCHBHDLCBHDLC;! />GLLRBHDLC!LM!HQF!BRRDNFCH!DG!SAFNFMDCFN!DC!HQF!DCS@H!MD>F!LM!HQF! GD=@>BHDLC!FCEDALC=FCH;!&C! HQF!GD=@>BHDLCFHF>9!R>LGF!B>>!>BCFGm!LCF! >BCF!AF=BDCG!LSFC;!/>GL9!HABMMDR!Z/'+[!LC!HQF!=BDC!MAFFWB9!DG! BSSAL^D=BHF>9!uOJJ!BRALGG!B >>!>BCFGF G ! SFA!QL@A[!LC!HQF! =BDC!MAFFWB9; ! &C!HQDG!F^B=S>F!CFHWLA_
PAGE 111

Ug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kOhOl;!/!EFA9!H9SDRB>!ALBN!CFHWLA_!DG!HQF!& , Ii!&CHFAGHBHF!6AFFWB9!DC! 'FCEFA!3L@CH9!HQBH!LMHFC! F^QD8DHG!HABMMDR!BRRDNFCHG!kOhO!HQF!AL@HFG! DC!HQF!& , Ii!MAFFWB9; ! +QF!GFT=FCH!HQBH!WBG!DCEFGHDTBHFN!DCR>@NFG!BAHFADB>!ALBNG!HQBH!DCHFAGFRH!WDHQ! HQF!& , Ii! &CHFAG HBHF! 6AFFWB9!BCN!BAF!S>B9DCT!BC!D=SLAHBCH!AL>F!BG!NDMMFAFCH!B>HFACBHDEFG ; ! &C! BNNDHDLC!B>HFACBHDEF!ALBNG!HQF=GF>EFG!RBC!QBEF!>LRB>!HABMMDR!RLCTFGHDLCG;! +QDG! GFT=FCH!LM!HQF!MAFFWB9!DCR>@NFG!HQF!BAHFADB>!ALBNG!MAL=!$ALBNWB9!HL!KHQ!/EF C@F ;!+QLGF!BAHFADB>! 2><7<>8:E,>6:D , !>7<>8:E,>6:D ,

PAGE 112

Uh ! ! ALBNG!BAF!FBGH , WFGH!8L@CNB=FNB!/EFC@F!HQAL@TQ!2BCHB!6F!'ADEF ! QBEF!LC , AB=S!BCN!LMM , AB=S!MAFFWB9! BRRFGG;! 6DT@AF ! I K ! GQLWG!HQF! =BS!LM! H9SDRB>!ALBN! CFHWLA_G!MAL=!HQF!AFB>!WLA>N;!3'4+!NBHB8BGF! WBG!@GFN!MLA!ALBN!CFHWLA_!NFGRADSHDLC!BCN!HQF!EFQDR>F!EL>@=F!SFA!QL@A; ! )GD CT!HQF!NBHB!SALEDNFN! 89!3'4+BHDLC!WBG!SFAMLA=FN!BH!BSSAL^D=BHF>9!uYLBN!LC!HQF! MAFFWB9!BRALGG!B>>!MDEF!>BCFG;! +QF!HABMMDR!EL>@=F!NBHB!WBG!8BGFN!LC!NBHB!RBSH@AFN!N@ADCT!IJJU! k Oh O l; ! &C!HQDG!GRFCBADL!GRFCBADL;!$BGFN!LC!HQF!NBHB!MAL=!3'4+LRBHDLC!LM!HQF!BRRDNFCH!DG!SAFNFMDCFN! DC!HQF!DC S@H!MD>F;!+QF!HD=F!LM!TFCFABHDCT!HQF!BRRDNFCH!DG!B>GL!SAFNFHFA=DCFN!DC!HQF!RLNF;!+Q@GLBNDCT!SBHHFAC!LC!B >>!ALBNG!BCN!HQF!BRRDNFCH!BCN!FCEDALC=FCH!GFHHDCTG!DC!HQDG!AFB> , WLA>N! GRFCBADL!DG!BRRLANDCT!HL!AFB>!NBHBGFHG!kYKl;! ! 28FB><, O V N ! +QF!GFT=FCH!LM!HQF!AFB>!ALBN!CFHWLA_!DC!'FCEFA!3L@CH9 ; ! 6LA!FBRQ!GD=@>BHDLC!GRFCBADL!ALBNG!WBG!=LNF> FN!@GDCT!NDMMFAFCH! >LBN!EB>@FG!HL!L8GFAEF!HQF!D=SBRH!LM!HQF!B>HFACBHF!AL@HFZG[!LC!EBADL@G!M>LWG!89!=FBG@ADCT!HQF! >FEF>!LM!GFAED RF!Z*42[!BCN!HQF!HABEF>!HD=F!LC!HQF!MAFFWB9;!&C!HQF!GD=@>BHDLCLBNG! MLA!BAHFADB>!M>LW!ABHFG!WFAF!RLCGDNFAFNX!HQF ! =B^D=@=!BAHFADB>!>LBN!ZO!>LBN!ZhJJ!.5"[!>LBN!ZYJJ!.5"[!>L BN;!/>GL
PAGE 113

UU ! ! RLEFA!HQF!WQL>F!ABCTF!LM!NFCGDHDFGBHDLCG!WDHQ!EBADB8>F!SLS@>BHDLC!GD]FG! ZEFQDR>F!EL>@=FG`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k OOi lBGGDM9!HQF!RL=MLAH!LM!@A8BC!MBRD>DHDFG!MAL=!HQF!SFAGSFRHDEF ! LM!NADEFAG;!*FEF>!LM!GFAEDRF!RBC!8F! RLCGDNFAFN!BG!B!=FRQBCDG=!HL!NFHFA=DCF!HQF!FMMFRHDEFCFGG!LM!B!HABCGSLAH!MBRD>DH9!MAL=!HQF! SFAGSFRHDEF! LM!B!HABEF>FA;!&H!NFHFA=DCFG!QLW!B!GSFRDMDR!GFAEDRF!DG!8FDCT!LMMFAFN;!&C!TFCFAB>FEF>G!LM!GFAEDRF!BAF ! NFMDCFN;!+QF9!ABCTF!MAL=!/!HL!6@BHF!HQF!LEFAB>>!?@B>DH9!LM!GFAEDRF!k OOi l;! !

PAGE 114

OJJ ! ! &C!HQDG!RQBSHFA!LM!HQF!=LNF>!DG! HL!NDEFAH!HQF!HABMMDR!M>LW!DC!HQF!MAFFWB9!BRRDNFCH! LCHL!HQF!CFBA89!RDH9!ALBNF!FBRQ!EFQDR>F!HB_FG!DHG ! 8FGH! DCNDEDN@B>!AL@HF;!+QF!SAD=BA9!L8aFRHDEF!LM!HQDG!BSSALBRQ!DG!HL!=DCD=D]F!HABMMDR!RLCTFGHDLC!HD=FG; ! 6DT@AF! I g ! GQLWG!B!GRAFFCGQLH!LM!HQF!GD=@>BHDLC!D>>@GHABHDCT!HQF!BTFCHGc!=LEF=FCH!DC!HQF! Q9SLHQFHDRB>!ALBN!CFHWLA_;!&H!B>GL!GQLWG ! HQF!MAFFWB9!BCN!RDH9!BAHFADB>!ALBNG!BCN!WQFAF!BC! BRRDNFCH!LRR@AG!LC!HQF!MAFFWB9!ZHQF!AFN!RDAR>F[;! ! , 28FB><,OWN ! 2RAFFCGQLH!LM!HQF!GD=@>BHDLC!FCEDALC=FCH!LM!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_; ! &C!LANFA!HL!DCEFGHDTBHF!HQF!SFAMLA=BCRF!LM!HQF!=LNF>@FG!LM!HQF!WFDTQH!GFCGDHDEDH9!SBAB=FHFAG!DC!B>>!F^SFAD=FCHG!WFAF!GFH!HLX! ] ^ 1 , E n H FGLLA!MDF>NG!BCN!DCFAHDB9;!2D=@>BHDLCG!MLA!8LHQ!HQF!Q9SLHQFHDRB>!BCN!HQF!AFB>!& , Ii!ALBN!WFAF!SFAMLA=FN! HL! RBSH@A F ! HQF!H D=F!LM!HABEF>!MLA!HQF!EFQDR>FG!HL!AFAL@HF!BAL@CN!HQF! BRRDNFCH;!+ABEF>!HD=F!EBADB8D>DH9!DG!BC!D=SLAHBCH!=FBG@AF!LM!=LNF>!SFAMLA=BCRF;!-EFA9!BTFCHpG! NFRDGDLC!B8L@H!HQF!LSHD=B>!AL@HF!DG!8BGFN!LC!=DCD=D]DCT!HQF!NFGDAFN!HABEF>!HD=F!HL!AFBRQ!HQF! NFGDAFN!NF GHDCBH DLC; ! 2><7<>8:E,>6:D , !>7<>8:E,> 6:D ,

PAGE 115

OJO ! ! +QF!MDAGH!GD=@>BHDLC!DG!AF>BHFN!HL!NF=LCGHABHDCT!HQF!=LNF>cG!FMMDRDFCR9!DC!SAL=LHDCT!HQF! HABMMDR!LEFAB>>!HABEF>!HD=F!N@ADCT!HQF!BRRDNFCH!DC!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_;!+QDG!F^SFAD=FCH! WBG!A@C!WDHQ!i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

PAGE 116

OJI ! ! $:AE<,ON ! +LHB>!AFAL@HF!HD=F!EG;!=FHQLN!WDHQ!NDMMFAFCH!BAHFADB>!>LBN G ! MLA!HQF! Q9SLHQFHDRB>! ALBN! CFHWLA_; ! ! &C!BNNDHDLC!HD=F!QDGHLTAB=!GQLWC!DC! 6DT@AF! ! IU ! G@SSLAHG!HQF!AFG@>HG!DC! 6DT@AF! ! I h ! BG!DH!D>>@GHABHFG!HQF!HABEF>!HD=F!HB_FC!89!HQF!GB=F!EFQDR>F!MAL=!H QF!GB=F!SLDCH!DC!HQF!GD=@>BHDLC! FCEDALC=FCH!HL!AFBRQ!HQF!NFGHDCBHDLC;!&C!HQDG!F^SFAD=FCH!HD=F!WBG!RL=SBAFN!8FHWFFC! HQF!NFHFA=DCDGHDR!RBGF!LM!HQF!SALSLGFN!(*(2 , /$(!=LNF>!BCN!HQF!1LC , (*(2 , /$(!N@ADCT! EBADFH9!LM!BAHFADB>!>LBNG;!+QDG!AFG@>H!EB>DNBHF G ! HQF!(*(2 , /$(!AL@HDCT!=LNF>!SALEDNFG!?@DR_FA! AL@HF!HD=FG!HQBC!HQF!1LC , (*(2 , /$(!AFTBAN>FGG!LM!HQ F!HABMMDR!>LBNG!LC!HQF!BAHFADB>!ALBNG;!/>GL!SALEDNFG!HQF!MBGHFGH!HABEF>!HD=F!WQFC!HQFAF!DG!CL!BAHFADB>! HABMMDR!>LBN;!4C!HQ F!LHQFA!QBCNBA!aL@ACF9!HD=FG!WFAF!B>=LGH!HQF!GB=F!WDHQ!B>>!BAHFADB>! HABMMDR!>LBNG!W QFC!BSS>9DCT!HQF!(*(2 , /$(!AL@HDCT!=LNF; ! 28FB><, OY N ! +LHB>!HABEF>!HD=F!HL!AFAL@HF!BAL@CN! BRRDNFCH! MLA!HQF!GB=F!EFQDR>F!N@ADCT!EBADFH9!LM! BAHFADB>!>LBNG! ZQ9SLHQFHD RB>!ALBN!CFHWLA_[ ; ! $>:CC8? , /6:D= , ! 1/1# K !"1 , ['<7<>G8;8=78?\ ! 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=<,M\ ! 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=<,O\ ! +6;] , 1/1# K !"1 ! ! J!!.5" ! OPK ! OiJ ! OgU ! IYI ! YJJ!.5" * OIh ! OiU ! OKK ! IYg ! hJJ!.5" * OgO ! OgY ! OhY ! IYh ! OKJJ!.5" * OgK ! OUI ! OgU ! IiY ! ! "! #! $! %! &! '! (! )!)*+, %!!)*+, -!!)*+, "'!!)*+, ./012)031452)0675))806759:017;:< .31==6>)2/1?6@A:)/@)0B5)13053612)3/1?:)845B6>25:CB/D3<)) EFEGHIJE)8K505376@:606>< L/@9EFEGHIJE

PAGE 117

OJP ! ! +QF!GFRLCN!MDCNDCT!D>>@GHABHFG!HQF!=LNF>cG!B8D>DH9!HL!D=SALEF!HQF!EFQDR@>BA!HABMMDR!M>LW;! +QF!F^SFAD=FCH!WBG!A@C!LC!HQF!=DCD=@=!>LBN!HABMMDR!WDHQ!YJJ!.5"!DC!HQF!BAHFADB>!ALBNG!BCN! i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aL@ACF9!HD=F!WBG!HFGHFN;!+QF!F^SFAD=FC H!WBG! A@C!LC!HQF!(*(2 , /$(!=LNF>!WDHQ!EBA9DCT!HABMMDR!EL>@=FG!B>LCT!HQF!=BDC!QDTQWB9;!6L@A! HABMMDR!EL>@=FG!WFAF!HFGHFN!DC!HQDG!F^SF AD=FCHX!YJJJ!.5"?'/)@2 89836:;8%*<#56=)()&1-5-/(-.>?'/)A2 <#5>89836:;8

PAGE 118

OJY ! ! .5";!+QDG!F^SFAD=FCH!WBG!A@C!MLA!FBRQ!HABMMDR!EL>@=F!@CNFA!ML@A!NDMMFAFCH!BAHFA DB>!HABMMDR!>LBNG;! /G! FEDNFCRFN ! MAL=!HQF!QDGHLTAB=FG!LC!HQF!=BDC!ALBN!QBG!B!GDTCDMDRBCH! FMMFRH!LC!HQF!EFQDR> FGc!HABEF>!HD=F; ! /G!F^SFRHFNBHDLC!8FHWFFC!HQF!HABEF>! HD=F!BCN!HQF!HABMMDR!EL>@=F!LC!HQF!=BDC!QDTQWB 9m!WQFC!HABMMDR!EL>@=F!DCRAFBGFN!LC!HQF!=BDC! QDTQWB9!HABEF>!HD=F!DCRAFBGFN!ZGFF!6DT@AF ! PI [;! 4EFAB>> ! HD=F!WBG! CLHDRFN!WQFC!HABMMDR!EL>@=F!LC!HQF!=BDC!QDTQWB9!WBG!YJJJ!.5";!"LWFEFA! HD=F!N@ADCT!HABMMDR!EL>@=F!YJJJ!.5"!WBG!@CNFA!HQF!BAHFADB>!HABMMDR!>LBN!LM!YJJ!.5"; ! 28FB><, P M N ! +LHB>!HABEF>!HD=F!MLA!AFAL@HDCT!B AL@CN!BRRDNFCH!N@ADCT!NDMMF AFCH!HABMMDR!EL>@=FG!WDHQ! NDMMFAFCH!BAHFADB>!>LBNG; ! +QF!ML@AHQ!GD=@>BHDLC! WBG! SFAMLA=FN!HL!F^B=DCF!HQF!HABMMDR!HQAL@TQS@HFG!AFBRQDCT!HQFDA!NFGHDCBHDLCG!BG!B!M@CRHDLC!LM!HD=F;!6DT@AF! P I ! GQLWG!HQBH!HQF!C@=8FA!LM! BTFCHG!F^DHDCT!HQF ! GD=@>BHDLC!FCEDALC=FCHBHDLC!HQBC!DC!HQF!CLC , (*(2 , /$(!A@C;!+QDG!RLCMDA=G!HQF!B8D>DH9! LM!HQF!SALSLGFN!=LNF>!HL!D=SALEF!HQF!HQAL@TQS@H; ! ! "! #!! #"! $!! $"! %!!!&'() "!!!&'() *!!!&'() +!!!&'() ,-./0&.1/230&.453&&6.45378./598: ,1/;;4<&2-0=53&->&.?3&?4@?A/B&623?4<03C?-=1: &!&'() %!!&'() D!!&'() #*!!&'()

PAGE 119

OJi ! ! , 28FB><, P O N, +ABMMDR!HQAL@TQS@H!N@ADCT!GD=@ >BHDLC!WDHQ!NDMMFAFCH!BAHFADB>!>LBNG ; ! +QF!EFQDR@>BA!GSFFNG!MLA!HQF!GB=F!BTFCH!MAL=!HQF!GB=F!NDGHBCRF!DC!NDMMFAFCH!GRFCBADLG! ZHABMMDR!>LBNG[!QBEF!8FFC!RL=SBAFN9;!+QF!QDGHLTAB=!GQLWG!HQF! BTFCHcG!BEFABTF!GSFFN!WBG!QDTQFA!N@ADCT!HQF! BSS>DRBHDLC!LM!HQF!(*(2 , /$(!=LNF>!HQBC!N@ADCT!HQF!1LC , (*(2 , /$(!BSS>DRBHDLC!AFTBAN>FGG! LM!HQF!HABMMDR!>LBNG!LC!HQF!BAHFADB>!ALBNG;!/>GLFcG!BEFABTF! GSFFNG!WFAF!GDTCDMDRBCH>9!QDTQF A!MLA!B>>!RBGFG!LM!HQF!(*(2 , /$(!=LNF>!WDHQ!CL!LA!=DCD=@=! BAHFADB>!>LBNG!RL=SBAFN!HL!HQF!=FND@=!BCN!=B^D=@=!>LBNG!GRFCBADLG;!+QDG!AFG@>H!GQLWG!HQF! D=SBRH!LM!HQF!EL>@=F!LM!HABMMDR!LC!HQF!B AHFADB>!ALBNG!LC!HQF!GSFFN!LM!EFQDR>FG!N@ADCT!HABEF>DCT! LEFA!B>HFACBHD EF!AL@HFG!DC!RBGF!LM!BRRDNFCH; ! ! ! ! ! !

PAGE 120

OJK ! ! ! 28FB><, P P N, /EFABTF!EFQDR>F!GSFFNG!WDHQ!NDMMFAFCH!BAHFADB>!>LBNG!ZQ9SLHQFHDRB>!ALBN!CFHWLA_[; ! &C!HQF!LHQFA!GD=@>BHDLC!GRFCBADLGLCT!HQF!& , Ii!WFAF!=LNF>FN;!&C!HQF!MDAGH! F^SFAD=FCH!WQFAF!HQF!HABEF>!HD=F!WBG!=FBG @AFN!QBN!HQF!8FGH!SFAMLA=BCRF! B=LCT!LHQFA!=FHQLNG!DC!HQF!GD=@>BHDLC!LM!HQF!& , Ii!AL@HFG;!*LL_DCT!BH!HQF!NBHB ! MAL=!HQF! NFRFCHAB>D]FN!BSSALBRQFG>!HABEF> ! HD=F!HL!AFAL@HF!BAL@CN!BC!BRRDNFCH!DG!D=SALEFN!LEFA!HQF!CLC , &+2!=FHQLN;! />GL9!iJt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

PAGE 121

OJg ! ! ! 28FB><, P R N, +LHB>!HABEF>!HD=F!HQAL@ TQ!HQF!& , Ii!MAFFWB9!DC!NDMMFAFCH!=FHQLNG!WDHQ!NDMMFAFCH!HABMMDR! >LBNG ; ! $:AE<,PN ! +LHB>!AFAL@HF!HD=F!EG;!=FHQLN!WDHQ! NDMMFAFCH!BAHFADB>!>LBN!MLA!HQF!AFB> , WLA>N!ALBN! CFHWLA_; ! &C!BNNDHDLC!HD=F!QDGHLTAB=!GQLWC!DC! 6DT@AF ! P i ! G@SSLAHG!HQF!SAFEDL@G!AFG@>HG!BG! DH!D>>@GHABHFG!HQ F!a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ig ! OiK ! Ohi ! IiI ! YJJ!.5" * OiO ! OhJ ! OUi ! IYh ! hJJ!.5" * OgJ ! OKK ! Ohg ! IiO ! OKJJ!.5" * OhI ! OhK ! OUK ! IYh !

PAGE 122

OJh ! ! (*(2 , /$(;!/>GL!GQLWG!HQF!>LCTFGH!HABEF>! HD=F!DC!RBGFG!LM!CL!BAHFADB>!HABMMDR!BCN!=B^D=@=!>LBNG; ! ! , , , , , , , 28FB><, P S N, +LHB>!HABEF>!HD=F!HL!AFAL@HF! BAL@CN!DCRDNFCH!MLA!HQF!GB=F!EFQDR>F!N@ADCT!EBADFH9!LM! BAHFAD B>!>LBNG ! ZAFB> , WLA>N!CFHWLA_[ ; ! 6DT@AF! P K ! D>>@GHABHFG!HQF!=LNF>cG!RBSB8D>DH9!LM!D=SALEDCT!HQF!EFQDR@>BA!HABMMDR!M>LW;!+QF! F^SFAD=FCH!WBG!ABC!LC!HQF!=B^D=@=!>LBN!HABMMDR!RBGF!WDHQ!O!ALBNG!BCN!u! Y H!GQLWG!HQF!B8D>DH9!LM! HQF ! =LNF>!HL!D=SA LEF!HQF! LEFAB>>!HABMMDR!M>LW!N@ADCT!BRRDNFCHG;!6DT@AF! P g ! GQLWG ! HQBH! HQF!HABMMDR!M>LW!ABHF!BH!HQF!8FTDCCDCT! LM!HQF!GD=@>BHDLC!WBG!HQF!WLAGH!DC!1LC , (*(2 , /$(!RBG FG!W FAF ! DCGDTCDMDRBCH; ! ! "! #! $! %! &!! &"! &#! '!'()* #!!'()* %!!'()* &$!!'()* +,-./'-0.12/'-342''5-34267-.4879 +0.::3;'/,.<3=>7',='-?2'.0-203./'0,.<7'512?3;/27@?,A09'' BCBDEFGB H,=6BCBDEFGB

PAGE 123

OJU ! ! ! 28FB><, P V N ! +ABMMDR!M>LW!N@ADCT!GD=@>BHDLC!HD=F!ZAFB> , WLA>N!CFHWLA_[; ! +QF!EFQDR@>BA!GSFFNG!MLA!HQF!GB=F!EFQDR>F!MAL=!HQF!GB=F!NDGHBCRF!N@ADCT!NDMMFAFCH!HABMMDR! >LBNG!LC!BAHFADB>!ALBNG!QBEF!8FFC!R L=SBAFNF!WBG!ABCNL=>9! RQLGFC!MLA!HQDG!F^SFAD=FCH;!+QF!QDGHLTAB=!GQLWG ! HQF!BTFCHcG!BEFABTF!GSFFN!WBG!QDTQFA!N@ADCT! HQF!BSS>DRBHDLC!LM!HQF!(*(2 , /$(!=LNF>!RL=SBAFN!HL!HQF!1LC , (*(2 , /$(!BSS>DRBHDLC!MLA!B>>! BAHFADB>! HABMMDR!>LBNG;!"LWFEFA!HABMMDR!>LBNG;!/>GLFGc!BEFABTF!GSFFNG!WFAF!GDTCDMDRBCH>9!QDTQFA!N@ADCT!HQF! BSS>DRBHDLC!LM!B>>!RBGFG!LM!HQF!(*(2 , /$(!=LNF>!WDHQ!CL CF ! LA!=DCD=@=!BAHFADB>!>LB NG!HQBC! N@ADCT!HQF!=FND@=!BCN!=B^D=@=!>LBNG!GRFC BADLG;!/G!GQLWC!DC!6DT@AF! P g FcG! BEFABTF!GSFFN!WBG!AFRLANFN!DC!HQF!BSS>DRBHDLC!LM!HQF!NFHFA=DCDGHDR!RBGF!LM!(*(2 , /$(!=LNF>;! +QDG!AFG@>H!NFCLHFG!HQF!B8D>DH9!LM!HQF!SALSLGFN!=LNF>!HL!D=SALEF! HQF!GSFFN!LM!EFQDR>FG; ! ! !"# !"$ !"% !"& ' '"# '"$ '"% '"& # ' & '( ## #) *% $* (! (+ %$ +' +& &( )# )) '!% ''* '#! '#+ '*$ '$' '$& '(( '%# '%) '+% '&* ')! ')+ #!$ #'' #'& ##( #*# #*) #$% !"#$%&'()%*+),-.")/010/2 3-14"'(-#5%(-1) 6 /('17/ 89836:;8%*<)()&1-5-/(-.2 89836:;8%*=#56<)()&1-5-/(-.>?'/)@2 89836:;8%*=#56<)()&1-5-/(-.>?'/)%A2 =#5>89836:;8

PAGE 124

OOJ ! ! ! 28FB><, P W N ! .FQDR>FcG!BE FABTF!GSFFN!WDHQ!NDMMFAFCH!BAHFADB>!>LBNG!ZAFB> , WLA>N!CFHWLA_[; ! +B8>FG! Y DH9!LM!HQF!EFQDR@>BA!HABEF>!HD=FLW!ABHFG@FG9!ALBN!CFHWLA_!BCN!HQF!& , Ii!ALBN! CFHWLA_!WD HQ!NDMMFAFCH!>LBNG!LC!BAHFADB>!ALBNG;!$BGFN!LC!HQF!EB>@FG!MAL=!HQF!HB8>FG@FG!BAF!J;U!DC!HQF!MDAGH!BCN!GFRLCN!HB8>FGF!F^RFSH!MLA!HQF! GD=@>BHDLCG!WDHQ!=B^D=@=!BAHFADB>!>LBN;!&H!RBC!8F!RLCR>@NFN!MAL=! HQF!HQAFF!HB8>FG ! HQBH! HQFAF!DG! RLCGDGHFCR9!8FHWFFC!HQF!HWL!GD=@>BHDLCG; ! $:AE<,RN ! 3 L=SBADCT!HQF!HLHB>!HABEF>!HD=F!MLA!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_!BCN!HQF!& , Ii!ALBN! CFHWLA_; ! , , , ! !"# $ $"# % %"# & &"# '!'()* +!!'()* ,!!'()* $-!!'()* (./012.34'56.758.'39..:';<=3>' ?75@@01'2A5:0B83'AB'C/.'57C.7052'7A5:3';6./012.3=/AD7>'' EFEGHIJE';K.C.7<0B03C01> EFEGHIJE';LABHK.C.7<0B03C01MN53.$> EFEGHIJE';LABHK.C.7<0B03C01MN53.'%> LABMEFEGHIJE $>:CC8? , /6:D= , ! 1/1# K !"1 , ['<7<>G8;8=78?\ ! 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=<,M\ ! 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=<,O\ ! +6;] , 1/1# K !"1 ! ! J!!.5" ! J;U ! J;U ! J;U ! J;U ! YJJ! .5" * J;h ! J;U ! J;h ! J;U ! hJJ!.5" * O;J ! O;J ! J;U ! J;U ! OKJJ!.5" * J;U ! J;U ! J;h ! O;J !

PAGE 125

OOO ! ! $:AE<,SN ! 3L=SBADCT!M>LW!ABHFG!MLA!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_!BCN!HQF!& , Ii!ALBN!CFHWLA_ ; ! ! $:AE<,VN, 3L=SBADCT!HQF!EFQDR>FGc!BE FABTF!GSFFN!MLA!HQF!Q9SLHQFHDRB>!ALBN!CFHWLA_!BCN!HQF!& , Ii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c!BEFABTF!GSFFN!MLA!B>>!BAHFADB> ! HABMMDR!>LBNG;! ! ! $>:CC8? , /6:D = , , 1/1# K !"1 , ['<7<>G8;8=78?\ , 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=< , M\ , 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=<,O\ , +6;] , 1/1# K !"1 , ! J!!.5" ! J;U ! O;O ! O;J ! J;U ! YJJ!.5" ! J;U ! O;J ! O;J ! J;U ! hJJ!.5" ! O;J ! J;U ! J;U ! J;U ! OKJJ!.5" ! J;U ! J;U ! O;J ! J;U ! $>:CC8? , /6:D= , , 1/1# K !"1 , ['<7<>G8;8=78?\ , 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=< , M\ , 1/1# K !"1 , [+6; K ' ($(%1)+)#$)& \ , [&:=<,O\ , +6;] , 1/1# K !"1 , ! J!!.5" ! O;Y ! O;Y ! O;Y ! O;Y ! YJJ!.5" ! O;P ! O;h ! O;i ! O;J ! hJ J!.5" ! O;K ! O;g ! O;i ! O;U ! OKJJ!.5" ! P;Y ! P;J ! P;J ! P;J !

PAGE 126

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` EFQDR>FG! 8FQBEDLAG!BCN!SQFCL=FCB>LWDCT!MLA!D=SALEFN!NFRDGDLCG!HB_FC!HL!FCQBCRF!HQF! RALWN `H ABMMDR ! =BCBTF=FCH!SALRFGG;! +QF ! BD = ! WBG!HL!B>GL!FCG@AF!HQF!FMMFRHDEFCFGG!BCN!AL8@GHCFGG! LM!HQF!SALSLGFN!=LNF>!DC!G@SSLAHDCT!G@RQ!NFRDGDLCG; ! ! +QF!=LNF>DCT!MAB=FWLA_!8BGDRB>>9!DCR>@NFG!HWL!L8GFAEBHDLC!>FEF>GX!b=DRALe!HQBH! AFSAFGFCHG!DCNDEDN@B>!BTFCHG
PAGE 127

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c!8FQBEDLAG!RBC!8F!=LNF>FN!BH!NDMMFAFCH!GHBTFG!BCN!BH!GFEFAB>! >B9FAG;!2SFRDMDRB>>9 !DG!BSS>DFN!HL!NDMMFAFCH!RALWN`HABMMDR!GRFCBADLG9]FN!DC!RBGF!LM!B!QDTQ , NFCGDH9!RALWN`HABMMDR!a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

PAGE 128

OOY ! ! 8FQBEDLA! 8FHWFFC!HQF!RF>>G!DG!NFMDCFN!@GDCT!B!HABCGDHDLC!=LNF>;!$BGFN!LC!HQF!HABCGDHDLC!=LNF>>G!DG!SFADLNDRB>>9!@SNBHFN;!+WL!M>LLA!MDF>N!RF>>@>BA!B@HL =BHLC!=LNF>G! BCN ! =LNDMDFN! $ P ! B>TLADHQ=!BAF!SAFGFCHFN!MLA!HQF!GHBHDR!M>LLA!MDF>N;! +QF!SAFGFCHF N ! GH@N9!GQLWG!HQBH!HQF!=LNDMDFN! $ P ! B>TLADHQ=!WDHQ!(LLAF!NDGHBCRF!=FHADRG!RBC!SALEDNF!8FHHFA!MDHHDCT!MLA!HQF!CBEDTBHDLC! FCEDALC=FCHG!L8GHBR>FG; ! />GL< ! BC!DCHFTABHFN!S>BHMLA=!MLA!=LNF>DCT!B!RL=S>FHF!ABCTF!LM!AFB> , WLA>N!HABMMDR!SAL8>F=G! QBG!8FFC!SALSLGFN;!+QF! SAL8>F=!LM!BRQDFEDCT!B!G9GHF= , LSHD =B>!HABMMDR!M>LW!QBG!8FFC!BNNAFGGFN;! 4CF!LM!HQF!SLGGD8>F!RADHFADB!DC!FEB>@BHDCT! HQF ! =LNF> !HABEF>!HD=F!LM!EFQDR>FG!DC!B!CFHWLA_!89!DCM>@FCRDCT!HQF!HA BMMDR! NDGHAD8@HDLC!LEFA!LSFC!ALBNG ! DC!B!CFHWLA_;!&H!DG!B!NDMMDR@>H!HBG_!HL!NDAFRH!HD=FFG!HL!GSFRDMDR!SBHQG!HL!BELDN!RLCTFGHDLC!LA!HABMMDR!a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

PAGE 129

OOi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c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

PAGE 130

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bCLA=B>eH!LM! BC!@STABNDCT!SALRFGG>DTFCHe>!=BCBTFN!89!HQF!=LNF>!DC!HQF!GB=F ! WB9;!+QF! =LNF>!SALEDNFG!B>>!BTFCHG!WDHQ!BSSALSADBHF!BCN!RLCGDGHFCH!8FQBEDLAG;! ! +QF!=@>HD , >FEF>!=@>HD , GHBTF!=LNF>DCT!F^SFAD=FCHG!RL CMDA=!HQF!BSS>DRB8D>DH9!LM!HQF!=LNF>! HL!8F!F=S>L9FN!DC!GD=@>BHDLCG!LM!EFA9!RL=S>F^!G9GHF=G;!3L==@CDRBHDLCG!BAF!8DNDAFRHDLCB>!8FHWFFC!BTFCHG!MAL=!B!=DRAL , =BRAL!

PAGE 131

OOg ! ! RL@S>F>!BG!8FHWFFC!BTFCHG!MAL=!FBRQ ! LM!HQFGF!>FEF>G;!/>GLHBCFL@G>9!DCEL>EFG!BTFCHG!MAL=!8LHQ!=DRAL!BCN!=BRAL!>FEF>G;! ! + QF!GHA@RH@AB>!RQBABRHFADGHDRG!LM!HQF!(*(2 , /$(!=LNF>!BRQDFEFN!HQF!NFGDAFN!M@CRHDLCB>! TLB>G;!+QLGF!TLB>G!DCR>@NF!DCHALN@RDCT!HQF!B8GH ABRHDLC!>FEF>G!DC!HQF!=LNF>D]DCT!DCHFAFGHDCT! RL>>FRHDEF!BCN`LA!DCNDEDN@B>!8FQBEDLAGDCT!8FHWF FC!=DRAL , =BRAL!>FEF>G!FBGD>9;!&C!BNNDHDLC!=FFHG!HQF!BD=!LM!N9CB=DRB>>9!BNBSHDCT! HQF!>FEF>!LM!NF HBD>!LM!HQF!GD=@>BHDLC!DC!LANFA!HL!D=SALEF!RL=S@HBHDLCB>!FMMDRDFCR9;! ! +QF!=LNF>!=B9!S>B9!BC!BNEDGLA9!AL>F!DC! RALWN`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a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

PAGE 132

OOh ! ! FCQBCRF!HQF!NFRDGDL CG!LM!RALWN!=BCBTF=FCH; ! +QDG!WL@>N!DCEL>EF!SFAMLA=DCT!B!GD=D>BA!8LN9!LM! WLA_DRBHDLCG!LM!EFQDR>F!DCHFABRHDLC!G@RQ!BG!DCHFAGFRHDLC!=BCBTF=FCH;! /CLHQFA!= BaLA!SFAGSFRHDEF!LM!HQF!M@H@AF!D=SALEF=FCH!LM!HQDG!WLA_!DCEL>EFG!BNEBCRFN!RL>>DG DLC! BELDNBCRF!GHABHFTDFG!BCN!RBSH@ADCT!NDMMFAFCH!BSS>DRBHDLCG!LM!EFQDR>F!DCHFABRHDLCG;! ! &C!BNNDHDLC!HL!DCEFGHDTBHDCT ! HQF!SALSLGFN!=LNF>!DC!D=SALEDCT!HQF!HABMMDR!a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c! 8 FQBEDLA! WD>>!B>GL ! 8F ! L8GFAEF N ! WQD>F!HQF9!BSSALBRQ!RALGGWB>_G!BCN`LA!DCHFAMFAF!WDHQ!SFNFGHADBCG;! $FRB@GF! HQFAF!DG! DCHFABRHDCT ! 8FHWFFC ! HWL!NDGHDCRH!H9SFG!LM!BTFCHG!DC!HQDG!GRFCBA DL!BRHDLCG!8FHWFFC!SFNFGHADBCG!BCN!EFQDR>FGFG ! WD>> ! 8F ! BNN FN ! DC!8LHQ!LM!HQFDA!8FQBEDLAB>!GSFRDMDRBHDLCG;!+QDG!QBG!HL!8F!NLCF!WQD>F!DCRLASLABHDCT!NBHB9H DRG! _CLW>FNTFF!DCHFABRHDLCG; ! 4CF!LM!HQF!FGGFCHDB>!BSS>DRBHDLCG!LM!HQF!SALSLGFN!=LNF>!WD>>!8F!RALWN!=BCBTF=FCH! N@ADCT!HQF!FCLA=L@G!BCC@B>!AF>DTDL@G!TBHQFADCT!LM!HQF!"Baa!kO hh , O UJ B=DR!SD>TAD=BTF!HL!(B__BQ!BRHDEDH9!LRR@AADCT!BH!B!GFH!HD=F!BCN!S>BRF!kO Ug lEDCT!LEFA!HWL!=D>>DLC!SFLS>F!MAL=!BSSAL^D=BHF>9!OiJ!RL@CHADFGF^!=@>HD ,

PAGE 133

OOU ! ! BTFCH!G9GHF=!AFSAFGFCHFN!89!HQF!"Baa!DCR>@NFG!=BC9!BTFCHG!kO h h F!WDHQ!B! G@8GHBCHDB>!E BADFH9!LM!L8aFRHDEF!BCN!G@8aFRHDEF!RQBABRHFADGHDRGFGTAD=G!WDHQ!EBA9DCT!SQ 9GDRB>!RBSBRDHDFG ! BAF! RL==LC;!&C!BNNDHDLC!MFBH@AFG!G@RQ!BG!HQF ! BSSAL^D=BHF>9!PJFG!RLCHBDCFN! DC!B!>D=DHFN!GSBRF!LEFA!B!GQLAH!SFADLN!LM!HD=F!RLCHAD8@HF!HL!HQF!CFFN!MLA!M@AHQFA!GH@NDFG ! HL!D =SALEF! RALWN!=BCBTF=FCH!N@ADCT!"Baa!HL!BELDN ! G@RQ!NDGBGHFAG!kO UJ !WD>>!D=SALEF!RALWN!=BCBTF=FCH!GL>@HDLCG!MLA!=BGG! TBHQFADCT!G@RQ!BG!HQF!"Baa!89!RLCGDNFADCT!HQF!NDEFAGDH9!LM!BTFCHG!BCN!HQFDA!RQBABRHFADGHDRG! DCEL>E FN;!+QF!BD=!LM!HQF!SALSLGFN!=LNF>!DC!G@RQ!RB GFG!DG!HL!QF>S!RALWN!=BCBTF=FCH!B@HQLADHDFG! 8@D>N!G@RRFGGM@>!GRQF=BG!89!SAFNDRHDCT!HQF!RALWNcG!8FQBEDLAG; ! &C!LANFA!HL!TFCFABHF!RL>>DGDLC , MAFF! HABaFRHLADFG!@GFG!B!MDCDHF!GHBHF!=BRQDCF!DC!RLCa@C RHDLC!WDHQ!BC!BTFCH , 8BGFN! =LNF>!HL!NFHFA=DCF ! QLW!BTFCHG!DCHFABRH!WDHQ!FBRQ!LHQFA!>LRB>>9; ! +QF!SALSLGFN!=LNF>!WD>>!G@SSLAH! HQF!QFHFALTFCFDH9!BCN!QDTQ!NFCGDH9!L8GFAEFN!DC!HQF!SFAMLA=BCRF!LM!"Baa!ADH@B>G;!+QDG ! DCR>@NFG! @GDCT!G=B>>!HD=F!GHFSG!DC!LANFA!HL!RLCGD NFA!NDMMFAFCH!SFNFGHADBC!GSFFNG!BCN!AFN@RFN! =L8D>DH9!LM! GL=F!LM!HQF=;!+QF!=LNF>cG!D=S>F=FCHBHDLC!MLR@G!WD>>!DCR>@NF!GFEFAB>!AFB> , WLA>N@NF!FEBR@BHDLCG!@CNFA!ADG_9!RLCNDHDLCG!LM!HQF!RALWN!DC! RBGF!LM!SBCDR< ! AFTD=FCHBHDLC!LM ! HQF!=BGGDEF!C@=8FA!LM!SFNF GHADBCG!BCN!EFQDR>FG!?@DR_>9!BCN!DC!B! GBMF!=BCCFATAD=G; ! /CLHQFA!M@H@AF!SFAGSFRHDEF!LM!HQDG!WLA_!DG!BSS>9DCT!HQF!(*(2 , / $(!=LNF>!HL!NFMDCF! QLW!@CNFA>9DCT!RLCCFRHDED H9!8FHWFFC!SFLS>F!BMMFRHG!N9CB=DRB>!SALRFGGFG!G@RQ!BG ! QLW!=BC9! SFLS>F!BAF!DCMFRHFN!89!B!8DL>LTDRB>!RLCHBTDLC;!+QF!N9CB=DRG!DC!HQDG!H9SF!LM!G9GHF=!BAF!LRR@AADCT!

PAGE 134

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aLADH9!LSDCDLCG!BCN!QLW!LCF!RL==DHHFN!TAL@S!RL=SFHFG ! WDHQ!HQF! LSSLGDCT!@CRL==DHHFN!LCFG;!+QF!=LNF>!WD>>!GQLW!QLW ! HQF!NL=DCBCH!=Ba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

PAGE 135

OIO ! ! %(2(%(+&(# , kOl!2;!3@AHDGBA!MAB=FWLA_!MLA!GD=@>BHDCT!RALWN! = LEF=FCH;!O , VLN=BC9;!Oh< ! /42. * SS;!IhI , IUi!BCN!(;!1LAHQX!/TFC H , 8BGFN!=LNF>DCT!BCN!GD=@>BHDLC(*01?4*b'!=(9*+'BA&D=':!*K:!<(9(!,(. * IJOY; ! kYl!$;!wQL@>FRHDEF!RALWN!8FQBEDLAG!WDHQ!N9CB=DR! SFNFGHADBC , BTFCHG;!OOO< ! /?2 . * SS;!iJ , KhD]FN!=@>HD , BTFCH!G9GHF= , 8BGFN!RLLSFABHDEF!MAF?@FCR9!RLCHAL>!MLA! B@HLCL= L@G!=DRALTADNG!WDHQ!RL==@CDRBHDLC!RLCGHABDCHG;!i< ! /02. * SS;!YYK , YiK>DCT!RALWN!8FQBEDLA!WDHQ!GLRDB> , RLTCDHDEF! BTFCHG;!hU< ! /02. * SS;!YgUDCT!MLA!RAL WN!GD=@>BHDLC;!OU< ! /5d42. * SS;!IgO , IhO>F8LLTQ * (=*D& DCT! N9CB=DR!FCEDALC=FCHG!DC!=@>HD , BTFCH!GD=@>BHDLC;!OY< ! /?2. * SS;!hg , OOKDCTX!(FHQLNG!BCN!HFRQCD?@FG!MLA!GD=@>BHDCT!Q@=BC! G9GHF=G(*^D=':!D&*$,D)(BN*:<*+,'(!,( -. * EL>;!UU< ! /-A%%&*52. * SS;!gIhJ , gIhgFBACDCT!DC!BTFCH , 8BGFN!=LNF>GX!/!5ALGSFRH@GEDCT!TFCFAB>!GHB8D>D]BHDLC!SAL8>F=G!WDHQ! =@>HD , BTFCH!G9GHF=G8DCT!BCN!2;!$B>DFHHDBHDLCG!DC!HQF!M@H@AFX!6AL=!=LNF>DCT! GLRDB>!=F RQBCDG=G!HL!F=FATFCH!SQFCL=FCB!BCN!DCHFABRHDEF!G9GHF=G!NFGDTC.*KgF.* K&DA-'A--=9. * EL>;!iJ< ! /O1@02. * SS;!UU
PAGE 136

OII ! ! kOYl! 1;!(FNDCB!LM!BTFCH , 8BGFN!=LNF>G!MLA!HFGHDCT! RDH9!FEBR@BHDLC!GHABHFTDFG!@CNFA!B!M >LLN!FEFCH;!OiY>@>BA!B@HL=BHB , /!SAL=DGDCT!SFAGSFRHDEF!DC!RALWN! N9CB=DRG!=LNF>DCTN-',D*8:&:!',D*h*89:,(()'!;-*+A%%&(B(!=. * EL>;!U>@>BA!B@HL=BHB!=LNF>!MLA!SFNFGHADBC ! BCN!TAL@S!N9CB=DRG;v!DC ! bT$ !BCN!0;!.D]]BADHDGRB>F!SFNFGHADBC!=LNF>DCT!WDHQ!3/!BCN!BTFCH , 8BGFN!BSSALBRQFGX!)8D?@DH9!LA!RLCGDGHFCR9|v!DC ! J!=(9!D=':!D&*K:!<(9(!,(*:!*K(&&A&D9* $A=:BD=D. * IJOK; ! kOhl!*;!3ALRDBC D * (=*D& !LM!N9BNG!DC!SFNFGHADBC!RALWNGX!+QF! RBGF!LM!RL@CHFA! M>LW>@>BA!B@HL=BHLC!8BGFN!GD=@>BHDLC!LM!>BATF!SFNFGHADBC!MBRD>DHDFG , B!RBGF! GH@N9!LC!HQF! 2HB HFC ! DG>BCN!MFAA9!HFA=DCB>GDCT!RF>>@>BA!B@HL=BHB! =LN F>G?@ABGQDH=B C< ! b(@>HD , R>BGG!BTFCH , 8BGFN!=LNF>!LM!RALWN!N9CB=DRG(*01?6*J!=(9!D=':!D&*K:!<(9(!,(*:!*K:B%A=D=':!D&*+,'(!,(*D!)* K:B%A=D=':!D&* J!=(&&';(!,(. ! SS;!OhJO , OhJI?@ABGQDH=BC< ! b (@>HD , >FEF>!=@>HD , GHBTF!BTFCH , 8BGFN!N FRDGDLC!G@SSLAH!G9GHF=! MLA!GD=@>BHDLC!LM!RALWN!N9CB=DRG(*059)*J!=(9!D=':!D&*K:!<(9(!,(*:!* L!;'!((9'!;*:<*K:B%&(M*K:B%A=(9*+N-= (B-*/JKLKK+*01?O2 ?@ABGQDH=BC< ! b"DFABARQDRB>!/TFCH , $BGFN!(LNF>DCT!M LA!&=SALEFN!+ABMMDR! %L@HDCT;!U< ! /0123 4567 !NFRDGDLCG!DC! SFNFGHADBC!GD=@>BHDLCX!/!Q98ADN!BTFCH! BSSALBRQ(*J=D&'D!*$--:,'D=':!*<:9*$9='<','D&*J!=(&&';(!,(. * IJOi; ! kIi l!y;!7zG!BCN!%;!*@8B}DGHDR!BCN!FMMFRHDEF!BTFCH , 8BGFN!=LNF>G!LM!RALWN! N9CB=DRG;!U< ! /02. * SS;!OKP , OggLLA! MDF>N!SFNFGHADBC!=LNF>G!WDHQ!HBRHDRB>!>FEF>!NFRDGDLCG;v!DC ! bT$. * IJOi; !

PAGE 137

OIP ! ! kIhl!*;!3ALRDBCD!BSS>DFN!HL!B!AFB>!WLA>N!RBGF!GH@N9;!ODCT!RL=S>F^!G9GHF=G!WDHQ!BNBSHDEF!CFHWLA_G(BD=',-*]'= >*$%%&',D=':!-. * EL>;!Ki< ! /?12. * SS;!OKYi , OKKYLG!BCN!0;!';!&LBCCL@DCT!HQF!RL=S>F^!N9CB=DRG! LM!HQF!LC>DCF!GLRDB>!CFHWLA_GX!B!GRB>B8>F!RLCRFSH@B>!BSSALBRQ;!g< ! /52. * SS;! IJg , IPI , $BGFN!0@DNBCRF!MLA!"@=BC , &CHFCGDEF!5ALRFGGFGG!LM!GD=@>BHDLC!MLA!RL=S>F^!G9GHF=G;v ! +N-=(B* $!D&N-'-*D!)*G:)(&'!;*:<*J!=(;9D=()*b:9&)*+N-=(B-RHR?.* SS;!IPiF^!G9GHF=!GD=@>BHDLCX!SALSLGDHDLC!LM!B!($2-!MAB=FWLA_!MLA!NFGDTC , BCB>9GDG!DCHFTABHDLC;!OKFBACDCT!MLA! BTFCH , 8BGFN ! GD=@>BHDLCG!MLA! BCB>9]DCT!HQAFBHG!HL!MDCBCRDB>!GHB8D>DH9BHLEB * (=*D& !BTFCH , 8BGFN!=LNF>G!MLA!GLRDL , FRL >LTDRB>!G9GHF=GX!3QB>>FCTFG!BCN! SALGSFRHG;!Yi{ * (=*D& HD>B9FA! CFHWLA_G;!I< ! /52. * SS;!IJP , IgOF^!G9GHF=G!CFHWLA_G@HDLC!LM!GLRDB>! RL=S>F^DH9(*89(>'-=:9N*:<*JV(9'D FNTFFFGLC!G9GHF=G!LC!CFHWLA_G;!YDH9(*$!!D&-*:<*I(;':!D&*+,'(!,(. * EL>;! ig< ! /0k52. * SS;!PPi , PKUG
PAGE 138

OIY ! ! kYPl!6;!+DBC * (=*D& D]BHDLC!BCB>9GDG;v!DC ! $$$J. * IJOY; ! kYYl!%;!3LCAL9 * (=*D& @FCRF! NDBTAB=G;v! DC ! JcK$J >FRHDEF!8FQBEDLA!EDB!GLRDB>!ND=FCGDLC! F^HABRHDLC;!Ii< ! /42. * SS;!O U , Ii!BTFCH , 8BGFN!GD=@>BHDLC!MAB=FWLA_!MLA!GFCGDCT!DC! RL=S>F^!BNBSHDEF!FCEDALC=FCHG;!OO< ! /02. * SS;!YJY , YOIDCT!WD HQ! (LNF>DRB;!gi>< ! K:B%&(M'=N3*$*aA')()*":A9R * IJJU; ! kiJl!+;!0ALGG!BCN!$;!$>BGD@G@HDLCBA9!CFHWLA_GX!B!AFEDFW(*I:N D&* +:,'(=N*J!=(9;!i< ! /012. * SS;!IiU , IgO>F^!CFHWLA_GX!HFRQCD?@FG!BCN!F^S>LABHDLCGTLADHQ=G!MLA!3L==@CDH9!BCN!%L>F!'FHFRHDLC!DC!1FHWLA_G N-',-. * EL>;!OiO< ! /? W 02. * SS;!U , IJDSSLE!BTFCH! 8BGFN!=LNF>DCTX!%FBGLCGG(*00!)*J!=(9!D= ':!D&*K:!<(9(!,(* :<*=>(*+N-=(B*SN!DB',-*+:,'(=N. * IJJY; ! ! kiil!';!/;!*D=BDEFDAB>@>BA!B@HL=BHB!=LNF>!WDHQ!AFS@>GDEF! SQFAL=LCF!MLA!GWBA=!AL8LHDRG!DC!G@AEFD>>BCRF!MLARF!=LNF>!MLA!GD=@>BHDLC!LM!NLWCQD>>! G_DDCT;!OK
PAGE 139

OIi ! ! kihl! 2;!VQBWBH=DD]FN!R>@GHFADCT!BCN!>DC_DCT!89! CFHWLA_FN!BTFCHG;!Ki< ! /?52. * SS;!PiIK , PiPg!BCN!(;!/;!1DB]DDCT!HQF!DCHFACFH! LM!HQDCTGX!B!Q98ADN!=LNF>DCT!BSSALBRQ! @GDCT!RL=S>F^!CFHWLA_G!BCN!BTFCH , 8BGFN!=LNF>G;! i< ! /?2. * SS;!YDCT!HQF!DCHFACFH!LM!HQDCTGM , LATBCD]DCT!BCN!LHQFA! RL=S>F^!BNBSHDEF ! RL==@CDRBHDLC!CFHWLA_GX!B!RLTCDHDEF!BTFCH , 8BGFN!RL=S@HDCT!BSSALBRQ;!OO< ! /?2. * SS;!FJOYKgKJ9HDRB>!BCN!RL=S@HBHDLCB>!BSSALBRQFG(*G:)(&'!;*D!)*$!D&N-'-*:<*K:B%&(M*+N-=(B-R * IJOi; ! kKYl!y;!5;!"FR_FA * (=*D& !HL!EDAH@B>!BCN! 8BR_! BTBDC>D * (=*D& !RLGH!=DCD=D]BHDLC!DC!BCH!HABCGSLAH!CFHWLA_GX!MAL=!G=B>> , GRB>F!NBHB! HL!>BATF , GRB>F!HABNF , LMMG(*I:ND&*+:,'(=N*J!=(9;!OI< ! / ??02. * SS;!IJXOiJghJEDCT!HQF!/1+2!SAL8>F=!WDHQ!BG9CRQALCL@G!MDCDHF!GHBHF!=BRQDCFGDC8FATBCBTBC! (=*D & >FRHDEF!GFBARQ!89!BCHG!DC!=DRALTABEDH9;!IOU< ! /?@2. * SS;!IUgO , IUhPBGGDM9DCT!GWBA=!8FQBEDLA!EDB!RL=SAFGGDEF! G@8GSBRF!>FBACDCTG!LM!RL>>FRHDEF!NFRDGDLC!=B_DCT!DC! GWBA=DCT!G9GHF=GN-',D&*I(Q'(]*L. * EL>;!UY< ! /02. * SS;!JIIYOi>9!TAL@CNFN!BTFCH , 8BGFN!=LNF>G!LM!DCCLEBHDLC! NDMM@ GDLCX!B!RADHDRB>!AFEDFW
PAGE 140

OIK ! ! kgPl! (;!$B>B8BCF!WDHQ!NDGB8D>DHDFGX!/!=@>HD , =FHQLN!BSSALBRQ(* 01?4*b'!=(9*+'BA&D=':!*K:!<(9(!,(. * IJOY; ! kgYl!&;!0BARB , (BTBADL!BCN!&;!5 >B]BBHLA!LM!F=LHDLCG!DC! =DCNM@>CFGG!SALTAB=G*$%%&',D=':!-. * EL>;!hY;!i< ! /?2. * SS;!O , POFBACDCT!@GDCT!B!=@>HDBTFCH!8BGFN!@CDMDFN!>FBACDCT! =LNF>!GD=@>BHDLCF!/TFCH , $BGFN ! (LNF>DCTX!2D=@>BHDCT!+WDHHFA!)GFAGG!MLA!LSDCDLC!GSAFBNDCT!BCN!RL==@CDH9!NFHFRHDLC!DC! >BATF , GRB>F!GLRDB>!CFHWLA_G>D>B!RLCHDC@DH9!DC!R98FA , SQ9G DRB>!G9GHF=GX! /!RLCHAL> , RFCHFAFN!=FHQLNL>LT9!8BGFN!LC!BTFCHG;!PYi< ! /7? @O2. * SS;!gUi , gUULHHFA8FR_D]FN!FGHD=BHDLC!LM!MLAFGH!MDAF!GSAFBN! @GDCT!=L8D>F!GFCGLAG>FADCT!S B9=FCHG!MLA!FRLG9GHF=!GFAEDRFG!WDHQ! BTFCH , 8BGFN!=LNF>GDFM!C FHWLA_G!BCN!LSDCDLC!N9CB=DRG!=LNF>G;!YiDCT!LM!CLCRL==@CDRB8>F!NDGF BGFGX!B! G9GHF=BHDR!AFEDFW. * EL>;!OJi< ! /52. * SS;!FPO< ! IJOi; ! ! khYl!2;!(;!$LG_LEDRQTLADHQ=G!8BGFN!LC!EFQDR>F!HL! EFQDR>F!DCHFABRHDLC!B@HLCL=L@G!EFQDR>FGX!-MMDRDFCH!RL>>DGDLC!BELDNBCRF! GRQF=F!@GDCT!%DRQBANGLCcG ! BA=G!ABRF!=LNF>;!OI< ! /?12. * SS;!FJOhKOJP!LM!SFNFGHADBC!BCN!TAL@S!N9CB=DRGX! -^SFAD=FCHG!LC!TAL@S!RLQ FGDLC!NDGHBCRFG!=LNF>!MLA!=BGG!FEBR@BHDLC! GD=@>BHDLC;v ! c:A9!D&*:< ! K(&&A&D9*$A=:BD=D. * EL>;!h
PAGE 141

OIg ! ! khhl!5;!wBABHs!BCN!2;!*D@FNTF , 8BGFN!NFRDGDLC!G@SSLAH!G9GHF=G! NFGDTC;!h< ! /52. * SS;!PJiDL * (=*D& BHFCH!EBADB8>FG!MLA!=LNF>>DCT!NFRDGDLC , =B_DCT!DC!FEBR@BHDLC! GD=@>BHDLCGDL>DCT!NFRDGDLC , =B_DCT!DC!MD AF!FEBR@BHDLC!8BGFN!LC!ABCNL=!@HD>DH9!HQFLA9 !DC!QDTQ , EL>@=F!=FHAL!ABD>! GHBHDLCG;!OJhHDGRB>F! BSSALBRQ!HL!=LNF>!BCN!GD=@>BHF!=L8D>DH9! DC!HQF!RLCHF^H!LM!S@8>DR!FEFCHG*89:,()'D. * EL>;!OUD8ABHDLC!LM!B!=DRALGRLSDR!=LNF>!MLA!SFNFGHADBC!N9CB=DR! GD=@>BHDLC!BH!GDTCB>D]F N!DCHFAGFRHDLCGX!/!Q98ADN!BSSALBRQ*8D9=*K3* LB(9;'!;*"(,>!:&:;'(-. * EL>;!hJ8B!BCN!/;!(@CHFBCFNTF!DC!FEBR@BHDLC! GRFCBADLG!DCEL>EDCT!MDAF!BCN!G=L_F , B!=@>HD GRB>F!=LNF>>DCT!BCN!GD=@>BHDLC!BSSALBRQ!MAB=FWLA_!HL!GD=@>BHF!Q@=BC!GSBHDB>!8FQBEDLA!DC!8 @D>H! FCEDALC=FCHG(*+NB%:-'AB*:!*+'BA&D=':!*<:9*$9,>'=(,=A9(* j*F9VD!* S(-';!. * IJOK; ! kUKl!2;!$BCNDCD9GDG! BCN!RALWN!G9CHQFGDGX!/!RBGF!GH@N9!BCN!MDAGH!AFG@>HG;!YYLGQDCDG=! RL=SAL=DGF!DC!HQF!NFEF>LS=FCH!LM!HQF!SFNFGHADBC!CBEDTBHDLC!=LNF>;!iO>DGDLC!BELDNBCRF!N9CB=DRG!B=LCT!QFHFALTFCFL@G!BTFCH GX!+QF!RBGF!LM! SFNFGHADBC`EFQDR>F!DCHFABRHDLCG(*J=D&'D!*$--:,'D=':!*<:9*$9='<','D&* J!=(&&';(!,(. * IJOg; ! kUUl!(;!wQBCT * (=*D& DCT!GSBHDB>!RLCHBRHG!MLA!FSDNF=DR!SAFNDRHDLC!DC!B!>BATF , GRB>F!BAHDMDRDB>! RDH9!MLA! DCHFABRHDCT!RALWN!GD=@>BHDLC(*01?6*J!=(9!D=':!D&*K:!<(9(!,(*:!*K:B%A=D=':!D&* +,'(!,(*D!)*K:B%A=D =':!D&*J!=(&&';(!,(. ! SS;!IUg , PJI!AFG@>HG DCT!BCN! BSS>DRBHDLCGBHDLC!BCN!F^SFAD=F CHGDNBHDLC!BCN!EFADMDRBHDLC!LM!3/ , 8BGFN!SFNFGHADBC!N9CB=DRG! =LNF>G;v ! cRK(&&A&D9*$ A=:BD=D. * EL>;!OO< ! /42. * SS;!Ihi , IUhBHDLCG!LM!RALWN! N9CB=DR G;!PY< ! /72. * SS;!OYOh , OYPY>@>BA!B@HL=BHB , 8 BGFN!GD=@>BHDLC!HLL>!MLA!AFB>!MDAF!BRRDNFCH! SAFEFCHDLC(BD=',D&*89:V&(B-*'!*L!;'!((9'!;. * EL>;!IJOhDCT!BCN!F^SFAD=FCHGN-',D*$3*+=D='-=',D&*G( ,>D!',-*D!)*'=-*$%%&',D=':!-. * EL>;!PUO< ! /? W 02. * SS;!IYh , IKP>LW|!(LNF>>DCT!AL@HF!RQLD RF!8BGFN!LC!F^SFAD=FCHB>!F=SDADRB>! FEDNFCRFGD8>@>BA!B@HL=BHB!=LNF>!MLA!RDAR@>BA!=LEF=FCHG! LM!SFNFGHADBCG!N@ADCT!+BWBM*$9='<','D&*J!=(&&';(!,(.* E L>;!OL LA!MDF>N!RF>>@>BA!B@HL=BHLC!=LNF>*8D9=*K3*LB(9;'!;* "(,>!:&:;'(-. * EL>;!hOHDS>F!F^DHG!89!AFB> , RLNFN!RF>>@>BA!B@HL=BHB!Z%3/[BHDLC!LM!FEBR@BHDLC!SALRFGGFG!@GDCT!B!8 DLCDRG , DCGSDAFN!RF>>@>BA!B@HL=BHLC!=LNF>!MLA!SFNFGHADBC!N9CB=DRGN-',D*$3*+=D='-=',D&*G(,>D!',-*D!)* '=-*$%%&',D=':!-. * EL>; ! POI< ! /? W 02. * SS;!IKJ , IgK
PAGE 143

OIU ! ! kOOil! 3;!6F>DRDBCD * (=*D& BHDLC!=LNF>!MLA!CLC , GDTCB>D]FN!SFNFGHADBC!RALGGWB>_G!8BGFN!LC! FE DNFCRF!MAL=!LC!MDF>N!L8GFAEBHDLC;!OO< ! /02. * SS;!OOg , OPh< ! v(@>HD , NFGHDCBHDLC!SFNFGHADBC!M>LWG!DC!F?@D>D8AD@=X!/!3F>>@>BA! /@HL=BHLCx$BGFN!/SSALBRQ;! PO< ! /72. * SS;!YPI , YYhBHDLC!LM!SFNFGHADBC!=LEF=FC H!WDHQ!B@HL=BHDR! EB>DNBHDLC>@>BA! /@HL=BHB!BG!HQF!8BGDG!LM!FMMFRHDEF!BCN!AFB>DGHDR! BTFCH , 8BGFN!=LNF>G!LM!RALWN!8FQBEDLA(*c:A9!D&*:<*+A%(9,:B%A='!;. * EL>;!gI< ! /72. * SS;! IOgJ , IOUKFG!DC!NDGRAFHF!=LNF>G!MLA! SF NFGHADBC!GD=@>BHDLC>@>BA!B@HL=BHLC!=LNF>!MLA!RALWN!FEBR@BHDLC!BCN!DHG!B@HL , NFMDCFN!L 8GHBR>F!BELDNBCRF!BHHAD8@HFD]BNFQ >@>BA!B@HL=BHLC!=LNF>!MLA!FEBR@BHDLC!SALRFGG!WDHQ! L8GHBR>FG;!YU< ! /02. * SS;!POi , PIPR@>BHDLC! LM!HQF!NDGHBCRF!SLHFCHDB>!MDF>N!BCN!y;!(@ASQ9FGp!AL@HDCT!B>TLADH Q=G! MLA!AL@HF!S>BCCDCT!DC!G=BAH!RDHDFG',A&D9*"9D<<',*GD!D;(B(!=*<:9*+BD9=*K'='(-*/H"G2.*01?0* #'9-=*J!=(9!D=':! D&*b:9Z->:%*T!. * IJOI; ! kOIYl! 6;!1B_B=@AB!BCN!V;!#B=B]B_D!=FHQLNG!MLA!TAL@SDCT!EFQDR>FG!DC!HABMMDR! M>LW!8BGFN!LC!SAL8B8D> DGHDR!RF>>@>BA!B@HL=BHB*J!=(9!D=':!D&*+NB%:-'AB* : !*+:<=* K:B%A='!;*D!)*J!=(&&';(!=*+N-=(B-*/+KJ+2. * IJOY; ! kOIil ! -;!VDAD_!BCN!+;!.DHLEB!SAFGFCHBHDLC!LM!@SNBHF!A@>FGLLA!MDF>NG!DC!3/!66!SFNFGHADBC!N9CB=DRG!=L NF>!2&T(/;!3/LLA! MDF>N!=LNF>!8BGFN!LC!RF>>@>BA!B@HL=BHB!MLA!GD=@>BHDCT! DCNLLA!SFNFGHADBC!FEBR@BHDLC(BD=',D&*89:V&(B-*'!*L!;'!((9'!;. * EL>;!IJOiLLA!MDF>N!3/!=LNF>!MLA!FEBR@BHDLC!N9CB=DRG;! OU< ! /?2. * SS;!PI , Yi!MLA!SBGGFCTFA!GQDSG!HQBH!DCR>@NFG!HQF!DCM>@FCRF!LM!L8GHBR>FG! DC!RB8DCG(BD=',D&*89:V&(B-*'!*L!;'!(( 9'!;. * EL>;!IJOg>HD , /TFCH!29GHF=G!BG!B!5>BHMLA=! MLA!./1-+G„T>DCT!BCN!GD=@>BHDLC;! PP>FA!BCN!0;!$B]DLA>@>BA! B@HL=BHB , ! /!SAL=DGDCT!SFAGSFRHDEF!DC!RALWN!N9CB=DRG!=LNF>DCTN-',D*8:&:!',D*h* 89:, (()'!;-*+A%%&(B(!=. * EL>;!UG!MLA!BC!DCRAFBGDCT!C@=8FA!LM!=BGGDEF!BTFCHG(BD=',D&*8>N-',-. ! EL>;! IJOKBHDLC!MLA! B! =@>HD , GRFCBADL!BCB>9GDG!@GDCT!SBAB>>F>!RL=S@HDCTB-R * IJJU; ! kOPgl! 'Da_GHABF= G!DC!RLCCF^DLC!WDHQ!TABSQG;v ! ^AB(9'-,>(* BD=>(BD=',.* EL>; ! OF!DNFCHDMDRBHDLC!MLA!BTFCH , 8BGFN!RALWN!=LNF>G!HQAL@TQ!TFCF! F^SAFGGDLC!SALTAB==DCT(*01?4*J!=(9!D=':!D&*K:!<(9(!, (*:!*$A=:!:B:A-* $;(!=-*D!)*GA&=' W $;(!=*+N-=(B-. * IJOY; ! kOPUl! 1;!"@ * (=*D& !MAB=FWLA_!@GDCT!=@>HD , L8aFRHDEF!TFCFHDR!SALTAB==DCT;!KKRLCFMABCRQDFEBCRF!LM!RBHFTLADFG!MLA!HA@GHDCT! DCMLA=BHD LC!GL@ARFG;!Yh< ! /02. * SS;!IgXO , IgXYID!RLCRFSHRLCF!=LNF>!MLA! HA@GH!LC!DCMLA=BHDLC! GL@ARFG;v!DC ! bT$ FEBRLCF!BCN!/;!2BSDFC]B!AL>F!LM!HQF!B@H QLADH9(*J=D&'D!*$--:,'D=':!*<:9*$9='<','D&* J!=(&&';(!,(. * IJOg; ! ! kOYKl!V;!2;!$BA8FA!BCN!y;!VD=DFM!AFEDGDLC!SALRFGG!8BGFN!LC!HA@GHX!/TFCHG!FEB>@BHDCT! AFS@HBH DLC!LM!DCMLA=BHDLC!GL@ARFGF^!BTFCH!TAL@SGDFM!AFEDGDLC!BCN!HA@GH!HA@GHX!/!=BaLA! RQB>>FCTF!MLA!HQF!M@H@AF!LM! B@HLCL=L@G!G9GHF=GD&&(!;(-*<:9* $A=:!:B:A-*+N-=(B-. * IJOK; ! kOiJl!0;!*@ * (=*D& !HA@GH! =LNF>G!MLA!=@>HD , BTFCH!G9GHF=G(*T%(!* J!<:9BD=':!*+,'(!,(*c:A9!D& . * EL>;!I;!OI< ! /02. * SS;!OhP , OUh!=LNF>G!LM!HA@GH!BCN!AFS@HBH DLCX!/TFCHG@HDLCBA9!TB=FG!CFHWLA_GDGQDCTDFM!CFHWLA_G!BG!B!EFAGBHD>F!=FHQLN!MLA!BGGFGGDCT ! @CRFAHBDCH9!DC!>BCN , RQBCTF!=LNF>DCT',D&*J!<:9BD=':!* +,'(!,(. * EL>;!IU< ! /?2. * SS;!OOO , OPODFM!CFHWLA_!=LNF>G!HL!BCB>9]F!BCN!SAFNDRH!FRL>LTDRB>! WBHFA!?@B>DH9!DC!ADEFAG;!POID * (=*D& !HA@GH!DC!GLRDB>!CFHWLA_G
PAGE 146

OPI ! ! kOiKl!-;!(BaN!BCN!.;!$B>B_ADGQCBC! MLA!AFRL==FCNFA!BT FCH!G9GHF=G;!IO< ! /02. * SS;!YOg , YPP!BCN!3;!5BADG!CFHWLA_G;!gK< ! /42. * SS;!ihPP , ihYU>FAFG \ 4''Š!';v ! L!Q'9:! B(!=D&*G:)(&&'!;*j*+:<=]D9(. ! EL>;! Yh;!v/!GHBCNBAN! SALHLRL>!MLA!NFGRAD8DCT!DCNDEDN@B> , 8BGFN!BCN!BTFCH , 8BGFN!=LNF>G;v ! L,:&:;',D&*B:)(&&'!;. ! EL>;! OUh!MLA!GD=@>BHDCT!Q@=BC , >D_F!RALWN!DC!NFCGF!S>BRFGDCT!BCN!GD=@>BHDLC!LM!SFNFGHADBC!N9 CB=DRB>!8FQBEDL A!8BGFN!LC!B!M@]]9! >LTDR!BSSALBRQ;!PKJHD , SBAB=FHFAD]FN!RF>>@>BA!B@HL=BHLC!=LNF>!MLA!RALWN! FEBR@BHDLCX!+QF!RBGF!LM!B!@CDEFAGDH9!8@D>NDCTDLDNBHDLC!LM!FEBR@BHDLC!GD=@>BHDLC!=LNF>G! HQAL@TQ!HQF!BCB>9GDG!LM!8FQBEDL@AB>!@CRFAHBDCH9;! OPO FC_B!SFNFGHADBC!SBHQ!S>BCCDCT!DC!FEBR@BHDLC! GRFCBADL;!PP< ! /72. * SS;!OIKU , OIhgDWDFRBHDLC!LM!FEBR@BHDLCDC8FATDCT!FEBR@BHDLC!N9CB=DRG!LC!GHBDAG!89!BC!F^HFCNFN!LSHD=B>!GHFSG! =LNF>*89:,()'D. * EL>;!I
PAGE 147

OPP ! ! kOgJl! %;!/>?@ABGQDH=BC< ! b (@>HD , *FEF>!(@>HD , 2HBTF!/TFCH , $BGFN!2D=@>BHDLC!(LNF>!LM! 3AL WN! '9CB=DRG!DC!)SSFA!6>LLA!LM!/> , ! "BAB=!/> , 2QBADM ! ( ! ?@=> * +,'(!='<',* #:9AB*<:9*CDEE.*FB9D>*D!)*GD)'!D>*H'-'=*I(-(D9,> < ! SS;!OiU , OKg< ! IJOU; ! kOgOl! QHHSGX``WWW;TSQ;TLE;GB`BA , G B`5BTFG`NFMB@>H;BGS^ ! kOgIl!/;5FAB>>LGB!:&:;'(-*D!)*$%%&',D=':!;!yLQC! 7D>F9!‹!2LCG;!PJP!5@8>DGQDCT8FAT!TB=FGX!HQFLA9!BCN!BSS>DRBHDLCG!DC!HABMMDR!RLCH AL>>FCNLLAC;!v+LWBAN!G9GHF= , LSHD=B>!AL@HDCT!DC!HABMMDR! CFHWLA_GX!/!AFEFAGF!2HBR_F>8FAT!TB=F!BSSALBRQ;v ! JLLL*"9D!-D,=':!-*:!*J!=(&&';(!=* "9D!-%:9=D=':!*+N-=(B-. ! EL>;! OKLR_RQBDC , 8BGFN!DCHF>>DTFCH!HABCGSLAHBHDLC!G9GHF=G;v! &C ! 01?7*JLLL*?@=>*J!=(9!D=':!D&*K:!<(9(!,(*:!*J!=(&&';(!=*"9D!-%:9=D=':!*+N-=(B-*/J"+K2 9GDG!BCN!RL=SBADGLC!LM!EFQDR>FG!AL@HDCT!B>TLADHQ=G!DC!G=BAH!RDHDFGB=>DTFCH!HABCGSLAHBHDLC!G9GH F=G;v! &C ! J!=(&&';(!=* "9D!-%:9=D=':!*+N-=(B>DTFCH!HABCGSLAHBHDLC!G9GHF=GX!/!MFBGD8D>DH9! GH@N9;v ! JLLL*"9D!-D,=':!-*:!*J!=(&&';(!=*"9D!-%:9=D=':!*+N-=(B-. ! EL>; OKDL * (=*D& DH9!HQFLA9;!hI , AFSLAH , HABMMDR , RLCTFGHDLC , NFCEFA , AFTDLC ; ! kOhIl ! QHHSGX``WWW;aLANBC>BW;RL=`=LGH , NBCTFAL@G , ALBN , DC , NFCEFA` ! kOhPl! V ;! $BA8BAB9GDG!LM!B! RALWN!NDGBGHFA;v ! K:B%A=(9*H'-':!*D!)*JBD;(*F!)(9-=D!)'!; . ! EL>; OOK>sD]FN!BSSALBRQ!HL!RL>>B8LABHDEF! NA DEDCT!RLLANDCBHDLC(*6=>*J!=(9 !D=':!D&*JLLL*K:!<(9(!,(*:!*J!=(&&';(!=*"9D!-%:9=D=':!* +N-=(B-*/JLLL*KD=R*^:R*14"CO64@2
PAGE 148

OPY ! ! kOhil! V;! $ABF_FAG< ! V;! %B=BF_FAGF!AL@HDCT!SAL8>F=X!2HBHF!LM ! HQF!BAH ! R>BGGDMDRBHDLC!BCN!AFEDFW < ! v ! K:B%A=(9-*j*J!)A=9'D&*L!;'!((9'!; < ! EL>;! UU NDCT!HQF!FMMFRH!LM!>FBNFAGQDS!LC!RALWN!M>LW!N9CB=DRGDC8FATTQBC9TQBC9!BCN!";!(BQ=BGGBCDBHDLC , BGGDTC=FCH! =LNF>DCT!MAB=FWLA_!MLA!RALWN!N9CB=DRG!DC!>BATF , GRB>F!SFNFGHADBC!MBRD>DHDFG*8D9=*$3*8:&',N*D!)*89D,=',(. * EL>; ! hKDCT!BCN!?@F@FDCT!HQFLA9BHDLCG!MLA! NFGDTCFAcG!NFRDGDLC!G@SSLAHBG_B * (=*D& !=FBG@AFG!LC!HQF!LRR@AAFCRF!LM!GHB=SFNFG! N@ADCT!=BGG!TBHQFADCTGX!HQF!"Baa!F^S FADFCRF;!Oi * (=*D& 9]DCT!TAL@S!N9CB=DRG!DC!HQF!>BATFGH! BCC@B>!AF>DTDL@G!TBHQFADCT(*01?m*$KG*J!=(9!D=':!D&*c:'!=*K:! <(9(!,(*:!* 8(9QD-'Q(*D!)*FV'XA'=:A-*K:B%A='!;. * IJOi; ! kO U I l!*;!(BC]LCDDCT!WDHQ!RALWN!RA9GHB>G!DC!(/2 , 8BGFN!RALWN!GD=@>BHDLCX!/!SALSLGB>LSDCT!BC!B TFCH , 8BGFN!=LNF>!MLA!SD>TAD=!FEBR@BHDLC!@GDCT! EDG@B>!DCHF>>DTFCRFX!/!RBGF ! GH@N9!LM!%BHQB!#BHAB!BH!5@AD;!KYHFACBHF!HFA=DCB>!>LRBHDLC!S>BCCDCT!@GDCT!BRRFGGD 8D>DH9!BCB>9GDG!MLA! D=SALEFN!SD>TAD=!=LEF=FCH;!Ih< ! /52. * S S;!PiO , PKIF!B@T=FCHFN!AFB>DH9!BSS>DRBHDLCX!/! RBGF!LM!HQF!QBaa!FEFCHDCT!WDHQ!SFNFGHADBC!TAL@SG!DC!=BG , 8BGFN!RALWN! GD=@>BHDLC(*?0=>* b:9Z->:%*:!*TVE(,=-*D!)*$;(!=-. * IJOO; ! kO Ug l!/;!%BQ=BC * (=*D& FABHFN!BTFCH , 8BGFN!RALWN!GD=@>BHDLC!MLA!QBaa!BCN!@=ABQ
PAGE 149

OPi ! ! kOUhl ! /;!VDARQ CFA!BCN!/;! 2RQBNGRQCFDNFABHDLC!LM!FEBR@BHDLC!SALRFGGFG!@GDCT!B!8DLCDRG , DCGSDAFN!RF>>@>BA!B@HL=BHLC!=LNF>!MLA!SFNFGHADBC!N9CB=DRGN-',D*$3*+=D='-=',D&*G(,>D!',-*D!)* '=-*$%%&',D=':!-. * EL>;!POI< ! /? W 02. * SS;!IKJ , IgK
PAGE 150

OPK ! ! !44(+')^,! , #8GBE:78; F, : ;D,16D6LD,'J;:G8?= , 4J7@6;,&6D< , ! D=SLAH!C@=S9!BG!CS ! D=SLAH!=BHS>LH>D8;S9S>LH!BG!S>H ! D=SLAH!SBCNBG!BG!SN ! MAL=!NBHFHD=F!D=SLAH!NBHFHD=F ! D=SLAH!LG ! D=SLAH!HD=F ! D=SLAH!RF>>@>BA/@HL=BHFN ! D=SLAH!HLL>G ! ! >B9L@HŒC@=8FA!o!i ! =B^ŒGSFFN!o!P!!!HQF! =B^D=@=!G SFFN!BC9!BTFCH!RBC!TL> ! ! ! DGŒS>LH!o!+A@F!!! ! DGŒ>FBNFA!o!+A@F!!DM!+A@FFBNFAG!BAF!RAFBHFN!BH!HD=FGHB=S!P ! DGŒABC_FN!o!6B>GF!!DM!+A@FFBNFA!WD>>!QBEF!SADLADH9!8BGFN!LC!HQFDA!=DCŒL8aGF< ! FEFA9LCF ! GB=F!SADLADH9 ! NFHFA=DCDGHDR!o!+A@F!!+A@F!B>WB9G!ML>>LW!HQF!>FBNFAGF!HQF9!=B9!LA!=B9CLH!ML>>LW ! NFRDGDLCŒRBGF!o!I!!O!MLA!iJt>LWG!HQF!>FBNFAFBNFAŒ=LN!o!M>LBHZpDCMp[!!!LSHDLC!HL!AFNL!>FBNFA!GF>FRH DLC!ZDCM! oo!LCRFB9L@H!o!+A@F ! GFFN!o!OiJ ! ! ! GHBAHŒHD=F!o!HD=F;HD=FZ[ ! HABEF>ŒHD=FŒNDGHG!o! Ž ! !!!!!!!!!!!! RF>>@>BA/@HL=BHFN;A@CZ>B9L@HŒC@=8FALH!o!DGŒS>LHFBNFA!o!DGŒ>FBNFAFBNFAŒ=LN!o! >FBNFAŒ=LNB9L@H!o!N9CB=DRŒ>B9L@HBHDLCX!vBSGFN!HD=F!WBG!tT!GFRLCNGv!t!ZFCNŒHD=F! , ! GHBAHŒHD=F[[ ! ! ! DM!JX ! !!!! HHMŒ=BHAD^G;AFBNŒ>B9L@HZ>B9L@HŒC@=8FA[ !

PAGE 151

OPg ! ! !!! ! HLL>G;S>LHŒ>B9L@HZHHMŒ=BHAD^[ ! ! tt! ,,,,,,,, ! %FG@>HG!2FRHDLC ,,,,,,,,,,,,,,,,,,,,, ! BAFBŒSFAŒSD^F>!o!;Y;Y! !=I ! C@=8FAŒLMŒHD=FGHB=SGŒSFAŒGFR!o!P ! ! AFG@>HG!o!SN;'BHB6AB=FZ‘pC@=ŒBTFCHpX!HD=FŒC@=8FAŒBTFCHGHGkpNFCGDH 9pl!o!AFG@>HGkpC@=ŒBTFCHpl`ZBAFBŒSFAŒSD^F>SD^F>G[ ! ! AFG@>HGkpM>LWŒC@=8FAŒL@Hpl!o! , AFG@>HGkpC@=ŒBTFCHpl;ND MMZ[ ! AFG@>HGkpM>LWpl!o!AFG@>HGkpNFCGDH9plAFG@>HGkpBETŒGSFFNpl ! AFG@>HGkpM>LWOpl!o!AFG@>HGkpNFCGDH9pl`AFG@>HGkpBETŒGSFFNpl ! ! AFG@>HG;HLŒRGEZpCLCABC_Œ>B9L @HŒ‘J’ŒGFFNŒ‘O’ŒBTFCHGŒ‘I’;RGEp;MLA=BHZ>B9L@HŒC@=8FAŒHD=FpX!HABEF>ŒHD=FŒNDGHp!X!HABEF>ŒNDGH’[ ! BTFCHŒNBHBkpBEFABTFŒGSFFNpl!o!BTFCHŒNBHBkpHABEF>ŒNDGHpl`BTFCHŒNBHBkpHABEF>ŒHD=Fpl ! BTFCHŒNBHB;HLŒR GEZpCLCABC_ŒBTFCHGŒ>B9L@HŒ‘J’ŒGFFNŒ‘O’ŒBTFCHGŒ‘I’;RGEp;MLA=BHZ>B9L@HŒC@=8F ALLA!BG!GM ! D=SLAH!SDR_>F ! D=SLAH!=BHS>LH>D8;D=BTF!BG!=SD=T ! ! >B9L@HŒML>NFA!o!p*B9L@HGp ! ! WN!o!LG;TFHRWNZ[ ! ! MD>FG!o!LG;>DGH NDAZLG;SBHQ;aLD CZWNB9L@HŒML>NFA[[ ! ! ! MLA!MD>F!DC!MD>FGX ! !!!! MD>FSBHQ!o!LG;SBHQ;aLDCZWNB9L@HŒML>NFAF[ ! !!!! DM!MD>F;FCNGWDHQZp;RGEp[X ! !!!!!!!! DM!CLH!LG;SBHQ;DGMD>FZMD>FSBHQ;AFS>BRFZp;RGEpp[[X ! !!!!!!!!!!!! =B]F!o!GM;AFBNŒRGEZMD>FSBHQ[ ! !!!!!!!!!! !! HHMŒ=BHAD^LLAZ=B]F[ ! !!!!!!!!!!!! WDHQ!LSFCZMD>FSBHQ;AFS>BRFZp;RGEpp[F;N@=SZkHHMŒ=BHAD^<=B]FlDM!MD>F;FCNGWDHQZp;SCTp[X ! !!!!! !!!DM!CLH!LG;SBHQ;DGMD>FZMD>FSBHQ;AFS>BRFZp;RG Epp[[X !

PAGE 152

OPh ! ! !!!!!!!!!!!! ! ! D=SLAH!HLL>G ! D=SLAH!C@=S9!BG!CS ! D=SLAH!=BHS>LH>D8;S9S>LH!BG!S>H ! D=SLAH!HD=F ! ! ! NFM!A@CZ>B9L@HŒC@=8FAGFLHo6B>GFFBNFAo6B>GFGFFBNFAŒ=LNoM>LBHZpDCMp[B9L@Ho6B>GF[X ! ! !!!! CS;ABCNL=;GFFNZGFFN[ ! !!!! ! !!!! HHMŒ=BHAD^G;AFBNŒ>B9L@HZ>B9L@HŒC@=8FA[ ! !!!! ! !!!! SD^F>G!o!Z=B]F!oo!J[;G@=Z[ ! !!!! ! !!!! WDNHQ!o ! =B]F;GQBSFkJl ! !!!! QFDTQH!o!=B]F;GQBSFkOl!! ! !!!!!! ! ! !!! F^DHG!o!kZ^<9[!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!! F^DHGŒ>B8F>!o!k=B]Fk^<9l , P!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!! L8GHBR>FG!o!kZ^<9[!MLA! ^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9 l!oo!Ol ! !!!! ! !!!! ! !!!! BTFCHG!o!kZOJF!>FCZBTFCHG[!”!C@=ŒBTFCHGX ! !!!!!!!! CF^HŒBTFCH!o!ZDCHZWDNHQCS;ABCNL=;ABCNZ[[FGX ! !!!!!!!!!!!! BT FCHG;BNNZCF^HŒBTFCH[ ! !!!! BTFCHG!o!>DGHZBTFCHG[ ! !!!! ! !!!! BTFCHGŒ=B^ŒGSFFN!o!CS;ABCNL=;ABCNDCHZOFBNFA!o!k , Ol>FCZBTFCHG[ ! !!!! >FBNFAG!o!kl ! !!!! ! !!!! ! !!!! F^DHFN!o!CS;BAAB9Zk6B>GFl>FCZBTFCH G[[ ! !!!! R@AAFCHŒBTFCHG!o!BTFCHG;RLS9Z[ ! !!!! ! !!!! !DCDHDB>>9!B>>!BTFCHG!GF>FRH!HQFDA!F^DHG!ABCNL=>9 !

PAGE 153

OPU ! ! !!!! F^DHŒDCNF^!o!CS;A BCNL=;ABCNDCHZJ<>FCZF^DHG[ , OFCZBTFCHG[[ ! !!!! F^DHŒDCNF^!o!HLL>G;GF>FRHF^DHZBTFCHGFCZBTFCHG[[!!!! ! !!!!!!!! ! !!!! BTFCHŒ=BHAD^!o!kl!!N9C B=DR!M>LLA!MDF>N ! !!!! MLA!DCN^!DC!ABCTFZ>FCZBTFCHG[[X ! !!!!!!!! BTFCHŒ=BHAD^;BSSFCNZCS;]FALGZZWDNHQLHX ! !!!!!!!! S>H;MDT@AFZ[ ! !!!!!!!! ! !!!! ! !!!! HABEF>ŒHD=F!o!CS;BAAB9ZkJl>FCZBTFCHG[[ ! !!!! HABEF>ŒNDGH!o!CS;BAAB9ZkJl>FCZ BTFCHG[[ ! !!!! L8aŒSBAB=!o!CS;ABCNL=;ABCNZ>FCZBTFCHG[[!!HQDG!DG!MLA!>FBNFA!GF>FRHDLC ! !!!! SADLADHDFG!o!CS;BAAB9ZkPKl >FCZBTFCHG[[ ! !!!! ! !!!! ! !!!! =9=BHAD^!o!HLL>G;RAFBHF=BHAD^ZWDNHQFGBHDLC!2HBAHFN;;;p[ ! !!! ! WQD>F!>FCZR@AAFCHŒBTFCHG[!“!J!BCN!CDHFA!”!OJJJJX ! !!!!!!!! GHBAH!o!HD=F;HD=FZ[ ! !!!!!!!! SADCHZp&HFABHDLCX!pFCZR@AAFCHŒBTFCHG[[ ! !!!!!!!! CDHFA!Šo!O ! !!!!!!!! ! !!!!!!!! DM!CDHFAt>FBNFAŒ=LN!oo!Y!BCN!DGŒ>FBNFAX! ! BH!HQDG!DHFABHDLCFBNFAG!BAF!BGGDTCFN!MLA!FBRQ! AFTDLC ! !!!!!!!!!!!! L8aŒSBAB=!o!CS;ABCNL=;ABCNZ>FCZBTFCHG[[ ! !!!!!!!!!!!! BTFCHŒ>FBNFAFBNFAGG;RAFBHF>FBNFAZWDNHQB8F>FBNFAG!‘J’FBNFAp;MLA=BHZ>FCZ>FBNFAG[FBNFA!do! , O[;= FBCZ[[[ ! !!!!!!!! ! !!!!!!!! !HQDG!SBAH!DG!@GFN!HL!R QBCTF!HQF!>B9L@H!MAL=!>B9L@HŒC@=8FA!HL!>B9L@HŒC@=8FA !

PAGE 154

OYJ ! ! !!!!!!!! DM!CDHFA!oo!OJ!BCN!N9CB=DRŒ>B9L@HX ! !!!!!!!!!!!! HF=SŒHHMŒ=BHAD^G;AFBNŒ>B9L@HZGHAZ>B9L@HŒC@=8FA[Špp[ ! !!!!!!!!!!!! DM!HF=SŒHHMŒ=BHAD^X ! !!!!!!!!!!!!!!!! HHMŒ=BHAD^!o!HF=SŒHHMŒ=BHAD^ ! !!!! !!!!!!!!!!!! WDNHQ!o!=B]F;GQBSFkJl ! !!!!!!!!!!!!!!!! QFDTQH!o!=B]F;GQBSFkOl!! ! !!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! F^DHG!o!kZ^<9[!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!!!!!!!!!!!!!! F^ DHGŒ>B8F>!o!k=B]Fk^<9l , P!MLA!^!DC!ABCTFZWDNHQ[!ML A!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o! Pl ! !!!!!!!!!!!!!!!! L8GHBR>FG!o!kZ^<9[!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!oo!Ol ! !!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! !BTFCHG!CFFN!HL!AFGF>FRH!HQFDA!F^D HG ! !!!!!!!!!!!!!!!! F^DHŒDCNF^!o!HLL>G;GF>FRHF^DHZ BTFCHGG;RAFBHF=BHAD^ZWDNHQFGG;GF>FRHF^DHZBTFCHG< ! F^DHFN9!>FBNFAG!RBC!RQBCTF!HQFDA!F^DH!N@ADCT!GD=@>BHDLC ! !!!!!!!! MLA!>FBNFA!DC!>FBNFAGX ! !!!!!!!!!!!! ! !!!!!!!!!!!! SADCHZ>FBNFAFBNFAl[ ! !!!!!!!!!!!! F^DHŒDCNF^k>FBNFAl!o!DCGDNFŒF^DHŒDCNF^k>FBNFAl ! !!!!!!!!!!!! ! !!!!!!!! BTFCHGŒGSFFN!o!k l ! !!!!!!!! >HMŒ=BHAD^!o!HLL>G;@SNBHFŒ>HMZ>FBNFAGFCZBTFCHG[[ ! !!!!!!!! DM!DGŒABC_FNX ! !!!!!!!!!!!! DCNDRFG!o!DCNDRFGkCS;BATGLAHZSADLADHDFG[l!!WF!=LNDM9!HQF!DCNF^!LM!BTFCHG!8BGFN!LC!HQFDA! SADLADHD FG ! !!!!!!!! ! !!!!!!!! MLA!DCN^!DC!DCNDRFGX ! !!!!!!!!!!!! R@AAFCHŒBTFCHG!o!k^!MLA!DFCZBTFCHG[[ ! !!! !!!!!!!!!!!!! WQD>F!BTFCHŒDHFABHDLC!”!BTFCHGŒ=B^ŒGSFFNkDCN^l!BCN!CLH!F^DHFNkDCN^lX ! !!!!!!!!!!!!!!!!!!!! !SADCHZBTFCHŒDHFABHDLC[ ! !!!!!!!!!!!!!!!!!!!! R@A AFCHŒBTFCHG!o!k^!MLA!D>G!o!HLL> G;MDCNŒCFDTQ8LAGZBTFCHGkDCN^lFG!Š!F^DHG[ !

PAGE 155

OYO ! ! !!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! DM!CFDTQ8LAŒRF>>GX ! !!!!!!!! !!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! DM!DGŒ>FBNFAX!!DM!>FBNFA!DG!6>BGFFBNFAkDCN^l!oo! , OX!!BTFCH!QBG!CLH!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o!HLL>G;MDCNŒSAL8ZCFDTQ8L AŒRF>>GGFX!!DM!HQF!BTFCH!DG!CLH!B!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!! !!!!! DM!JX!!HQDG!DG!RLGH!DM!ML>>LWFAG!ML>>LW!HQF!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! F^DHŒDCNF^kDCN^l!o!F^DHŒDCNF^kBTFCHŒ>FBNFAkDCN^ll ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o!HLL>G; MDCNŒSAL8ZCFDTQ8LAŒRF>>GHMŒ=BHAD^kBTFCHŒ> FBNFAkDCN^ll>LWFAG!TL!HQF!F^DH!GF>FRHFN!89!HQF!>FBNFA ! !!!!!!!!!! !!!!!!!!!!!!!!!!!!!!!!!!!! F^DHŒDCNF^kDCN^l!o!F^DHŒDCNF^kBTFCHŒ>FBNFAkDCN^ll ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o!HLL>G;MDCNŒSAL8ZCFDTQ8LAŒRF>>GGFX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o!HLL>G;MDCNŒSAL8ZCFDTQ8LAŒRF>>GGF[! ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!! ! !!!! !!!!!!!!!!!!!!!!!!!!GF>FRHFNŒDCN^!o!CS;ABCNL=;RQLDRFZ>FCZCFDTQ8LAŒRF>>G[FRHFNŒDCN^!o!CS;BAT=B^ZSAL8G[ ! !!!!!!!!!!!!!!!!!! !!!!!! GF>FRHFNŒRF>>!o!CFDTQ8LAŒRF>>GkGF>FRHFNŒDCN^l ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! !>LRBHDLC!DG!EBRBCH!CLW ! !!!!!!!!!!!!!!!!!!!!!!!! =9=BHAD^kBTFCHGkDCN^lkJlFRHFNŒRF>>kXIl ! !!! !!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! @SNBHF!HQF!=BHAD^!WDHQ!CFW!>LRBHDLC ! !!!!!!!!!!!!!!!!!!!!!!!! =9=BHAD^kBTFCHGkDCN^lkJlFRHFNŒR F>>kJlFRHFNŒRF>>kOll!Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒNDAFRHDLCGkDCN^l!o!GF>FRHFNŒRF>>kIl ! !!!!!!!!!!!!!!!!!!!!!!!! HABEF>ŒNDGHkDCN^l!Šo!O ! !!!!!!!!!! !!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! SADCHZBTFCHŒNDAFRHDLCG[ ! !!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒDHFABHDLC ! Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! DM!HLL>G;NDGHZBTFCHGkDCN^l
PAGE 156

OYI ! ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! =9=BHAD^kBTF CHGkDCN^lkJlŒHD=FkDCN^l!o!CDHFA ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!!DM!NFCGDH9!“!J;PX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!8AFB_ ! !!!!!!!!!!!!!!!!! !!!!!!! ! !!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!!!!!!!!!!!!!!!!!! 8AFB_ ! !!!!!!!!!!!! ! !!!!!!!!!!!!!!!! BTFCHGŒGSF FN;BSSFCNZBTFCHŒDHFABHDLC[!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! ! !!!!!!!! HD=FŒBETŒGSFFN;BSSFCNZCS;=FBCZBTFCHGŒGSFFN[[!!!!!!!!!!! ! !!!!!!!! ! !!!!!!!! BTFCHŒ=BHAD^!o ! HLL>G;@SNBHFŒBTFCHŒ=BHAD^ZBTFCHŒ=BHAD^[ ! !!!!!!!! ! !!!!!!!! DM!DGŒS>LHX ! !!!!!!!!!!!! HLL>G;S>LHŒ=BHAD^ZWDN HQFGFBNFAGH;D=GQLWZ=9=BHAD^;+[ ! !!!!!!!!!!!! HLL>G;S>LHŒ=BHAD^Z=9=BHAD^[ ! !!!!!!!!!!!! S>H;HDH>FZp+D=FGHB=SX!‘JXPN’p;MLA=BHZCDHFA[[ ! !!!!!!!!!!!! S>H;SB@GFZJ;JO[ ! !!!!!!!!!!!! S>H;R>MZ[ ! !!!!! !!!!!!! ! !!!!!!!! F>BSGFN!o!HD=F;HD=FZ[! , ! GHBAH ! !!!!!!!! SADCHZp‘JX;IM’!GFRLCNG BSGFNFCZR@AAFCHŒBTFCHG[[[!!!! ! !!!! AFH@AC!HABEF>ŒHD=FŒNDGHG ! ! ! S>H;=BHGQLWZ=9=BHAD^;+[ ! S>H;G QLWZ[ ! !!!! ! S>H;=BHGQLWZRLGH;+[ ! ! D=SLAH!C@=S9!BG!CS ! D=SLAH!LG ! D=SLAH!SDR_>F ! D=SLAH!=BHS>LH>D8;S9S>LH!BG ! S>H ! D=SLAH!=BHS>LH>D8!BG!=S> ! ! >FEF>G!o!P!! ! B>SQB!o!J;I!!MLA!N9CB=DR!M>LLA ! NF>HB!o!J;I!!MLA!N9CB=DR!M>LLA ! ! DCBRHDLC!o!J;ii ! _N!o!J;i!!WFDTQH!LM!N9CB=D R!M>LLA! !

PAGE 157

OYP ! ! _G!o!I;J!!WFDTQH!LM!GHBHDR!M>LLA ! _D!o!J;i!!NDAFRHDLC ! _W!o!J;P!!WB>>!GFCGDHDEDH9 ! _H!o! J;JI!!NFCDGH9!GFCGDHDEDH9 ! '=B^!o!OJ ! ! >B9L@HŒML>NFA!o!p*B9L@HGp ! ! ! NFM!NDGHZSOFRHF^DHZBTFCHGFEF>GX ! !!!!!!!!!!!!!!!!!!!! R@AAFCHŒCFDTQ8LAG!Šo!O ! !!!!!!!! CFDTQ8LAG;BSSFCNZR@AAFCHŒCFDTQ8LAG[ ! !!!! ! !!!! MLA!BTFCH!DC!BTFCHGX ! !!!!!!!! NDGHBCRFG!o!kl ! !!!!!!!! MLA!F^!DC!ABCTFZ>FCZF^DHG[[X ! !!!!!!!!!!!! NDGHBCRFG;BSSFCNZHHMŒ=BHAD^kF^lkBTFCHl[ ! !!!!!!!! AFWBAN!o!k^`GSFFN!Š!9!MLA!^B9L@HZ>B9L@HŒC@=8FA[X ! !!!! WN!o!LG;TFHRWNZ[ ! !!!! ! !!!! SDR_>FŒMD>F!o!LG;SBHQ;aLDCZWNB9L@HŒML>NFAB9L@H‘J’;S_>p;MLA=BHZ>B9L@HŒC@=8FA[[ ! !!!! R GEŒMD>F!o!LG;SBHQ;aLDCZWNB9L@HŒML>NFAB9L@H‘J’;RGEp;MLA=BHZ>B9L@HŒC@=8FA[[ ! !!!! ! !!!! ! !!!! DM ! LG;SBHQ;DGMD>FZSDR_>FŒMD>F[X ! !!!!!!!! WDHQ!LSFCZSDR_>FŒMD>FF;>LBNZM[ ! !!!!!!!!!!!! HHMŒ=BHAD^F;>LBNZM[ ! !!!!!!!!!!!! !

PAGE 158

OYY ! ! !!!!!!!! =B]F!o!GM;AFBNŒRGEZRGEŒMD>F[ ! !!!!!!!! =B]Fk=B]F!oo!Il!o!O ! !!!! ! !!!!!!!! AFH @AC!HHMŒ=BHAD^GFX ! !!!!!!!! AFH@AC!1LCFLHŒ>B9L@HZHHMŒ=BHAD^[X ! !!!! B>>ŒF^DH!o!OJJJ ! !!!! MLA!F^Œ=BH!DC!HHMŒ=BHAD^X ! !!!!!!!! F^Œ=BH!o!F ^Œ=BH;RLS9Z[ ! !!!!!!!! F^Œ=BHkCS;DGCBCZF^Œ=BH[l!o!CS;DCM ! !!!!!!!! B>>ŒF^DH!o!CS;=DCD=@=ZB>>ŒF^DH>ŒF^DHkB>>ŒF^DH!oo!CS;CBC=B^ZB>>ŒF^DH[l!o!CS;DCM ! !!!! S>H;=BHGQLWZB>>ŒF^DH;+[ ! ! ! NFM!MDCNŒCFDTQ8LAGZBTFCHDGH!o!kZ^ , O<9 , ODNŒ>DGH!o!kl ! !!!! MLA!CFDTQ8LA!DC!CFDTQ8LAŒ>DGHX ! !!!!!!!! DM!J!”o!CFDTQ8LAkJl!”o!WDNHQ! , O!BCN!J!”o!CFDTQ8LAkOl!”o!QFDTQH! , OX ! !!!!!!!!!!!! DM!CFD TQ8LAkXIl!CLH!DC!BTFCHGX ! !!!!!!!!!!!!!!!! EB>DNŒ>DGH;BSSFCNZCFDTQ8LA[!!!!!!!!!!!! ! !!!! AFH@AC!EB>DNŒ>DGH ! !!!! ! ! NFM!MDCNŒNFCGDH9ZBTFCH>G!o!MDCNŒCFDTQ 8LAGZBTFCHB9FAG!o!kCFDTQ8LAŒRF>>Gl ! !!!!!!!! MLA!D!DC!ABCTFZNFSHQ[X ! !!!!!!!!!!!! >B9FAG;BSSFCNZkl[ ! !!!!!!!!!!!! MLA!RF>>!DC!>B9FAGk , IlX ! !!!!!!!!!!!!!!!! >B9FAGk , Ol;F^HFCNZMDCNŒCFDTQ8LAGZRF>>>G!o!>DGHZGFHZk^kXIl!MLA!>B9FA!DC!>B9FAG!MLA!^!DC!>B9FAl[[ ! !!!!!!!! CFDTQ8LAŒRF>>G!o!k^!ŠZD<[!MLA!D<^!DC!FC@=FABHFZCFDTQ8LAŒRF>>G[l ! !!!! ! !!!! =9C@=!o!J ! !!!! MLA!RF>>!DC ! CFDTQ8LAŒRF>>GX ! !!!!!!!! DM!=9=BHAD^kRF>>kJl>kOll!oo!OX ! !!!!!!!!!!!! =9C @=!Šo!O!!!!!!!!!!!! !

PAGE 159

OYi ! ! !!!! AFH@AC!=9C@=`>FCZCFDTQ8LAŒRF>>G[ ! !!!!!!!! ! ! ! NFM!S>LHŒ=BHAD^ZWDNHQFGFBNFAGFBNFAGX ! !!!!!!!!!!!!!!!! =9=BHAD^kSkJlGFX ! !!!!!!!!!!!!!!!! =9=BHAD^kSkJl FGX ! !!!!!!!! =9=BHAD^kSkJlLAŒ=BS!o!‘JX!pWQDHFpBC_ ! !!!!!!!!!!!!!!!!! OX!p8>BR_ppF ! !!!!!!!!!!!!!!!!! PX!pApFBNFA!O ! !!!!!!!!!!!!!!!!! iX!p(BTFC HBpFBNFA!I ! !!!!!!!!!!!!!!!!! KX!p8>@Fp’!!!!!!!!>FBNFA!P ! !!!! ! !!!! R=BS!o!=S>;RL>LAG;*DGHFN3L>LA=BS Zk^kOl!MLA!^!DC!GLAHFNZRL>LAŒ=BS;DHF=GZ[[l[ ! !!!! CLA=!o!=S>;RL>LAG;1LA=B>D]FZE=DCoJH;D=GQLWZ=9=BHAD^;+FGFGX ! !!!!!!!! =9=BHAD^kSkJlFBNFAZWDNHQB8F>
PAGE 160

OYK ! ! !!!! C%FTDLCG!o!OJ!!C@=8FA!LM!AFTDLCG!SFA!ND=FCGDLC ! !!!! HQAFGQL>N!o!J;JJO!!>LWFA!H QAFGQL>N!=FBCG!HQF!RQBCRF!LM!QBEDCT!>FBNFA!DCRAFBGFG ! !!!!L8aŒSBAB=!o!CS;ABCNL=;ABCNZ>FCZBTFCHG[[ ! !!!! ^8LANFADCGSBRFZJDCGSBRFZJFCZCS;@CD?@FZF^DHGŒ>B8F>[[ ! !!!! ! !!!! AFTDLCG!o!kl ! !!!! MLA!D!DC!ABCTFZC%FTDLCG[X ! !!!!!!!! MLA!a!DC!ABCTFZC%FTDLCG[X ! !!!!!!!!!!!! R@AAFCH!o!kl ! !!!!!!!!!!!! MLA!DCN^ FBNFA!o!CS;BAAB9Zk , Ol>FCZAFTDL CG[[ ! !!!! AFTDLCŒL8aFRH!o!CS;BAAB9ZkO;Jl>FCZAFTDLCG[[ ! !!!! AFTDLCŒABC_!o!CS;BAAB9ZkYl>FCZAFTDLCG[[! ! !!!! !O!DG!QDTQFGH!SADLADH9!BCN!Y!HQF!>FBGH!SADLADH9 ! !!!! MLA!AFTDLCŒDCN^FBNFA!o! , O ! ! !!!!!!! SADCHZ>FCZAFTDLC[`AFTDL CŒGD]F[ ! !!!!!!!! DM!>FCZAFTDLC[`AFTDLCŒGD]F!“!HQAFGQL>NX ! !!!!!!!!!!!! =DCŒL8a!o!OJJ ! !!!!!!!!!!!! MLA!D!DC!ABCTFZ>FCZL8aŒSBAB=kAFTDLCl[[X ! !!!!!!!!!!!!!!!! DM!L8aŒSBAB=kAFTDLClkDl!”!=DCŒL8aX ! !!!!!!!!!!!!!!!!!!!! =DCŒL8a!o!L8aŒSBAB=kAFTDLClkDl ! !!!!!!!!!!!!!!!!!!!! =DCŒ>FBNFA!o!AFTDLCkDl ! !!!!!!!!!!!!DM!=DCŒL8a!”o!J;iX ! !!!!!!!!!!!! DM!=DCŒL8a!”o!J;UX ! !!!!!!!!!!!!!!!! AFTDLCŒ>FBNFAkAFTDLCŒDCN^l!o!=DC Œ>FBNFA ! !!!!!!!!!!!!!!!! AFTDLCŒL8aFRHkAFTDLCŒDCN^l!o!=DCŒL8a ! !!!!!!!!!!!!!!!! DM!=DCŒL8a!”o!;OX ! !!!!!!!!!!!!!!!!!!!! AFTDLCŒ ABC_kAFTDLCŒDCN^l!o!O ! !!!!!!!!!!!!!!!! F>DM!J;O!”!=DCŒL8a!”o!J;PX ! !!!!!!!!!!!!!!!!!!!! AFTDLCŒABC_kAFTDLCŒDCN^l!o!I ! !!!!!!!!!!!!!!!! F>GF X ! !!!!!!!!!!!!!!!!!!!! AFTDLCŒABC_kAFTDLCŒDCN^l!o!P ! !!!! BTFCHŒ>FBNFA!o!CS;BAAB9Zk , Ol>FCZBTFCHG[[ ! !!!! SADLADHDFG!o!CS;BAAB9 ZkYl>FCZBTFCHG[[!!!!!!!!!! ! !!!! MLA!DFBNFA!o!AFTDLCŒ>FBNFAkDl ! !!!!!!!! DM!>FBNFA!do! , OX!!!!!!! !!!!! !

PAGE 161

OYg ! ! !!!!!!!!!!!! MLA!DCN^!DC!AFTDLCX ! !!!!!!!!!!!!!!!! DM!DCN^!oo!>FBNFAX!!MLA!>FBNFA!QD=GF>MFBNFAŒDCN^!DG! , O ! !!!!! !!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o! , O ! !!!!!!!!!!!!!!!!!!!! SADLADHDFGkDCN^l!o!AFTDLCŒABC_kDl ! !!!!!!!!!!!!!!!! F>GFX!!!! ! !!!!!!!!!!!!!!! !!!!! DM!CLH!NFHFA=DCDGHDRX ! !!!!!!!!!!!!!!!!!!!!!!!! DM!NFRDGDLCŒRBGF!oo!OX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!CS;ABCNL=;RQLDRFZ k+A@FGFl[X ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o! , O ! !!!!!!!!!!!!!!!!!!!!!!!! F>DM!NFRDGDLCŒRBGF!oo!IX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! S>!o!O`C@=ŒF^ DHG ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!F^DHGŒ>B8F>kF^DHŒDCNF^kDCN^ll!oo!F^DHGŒ>B8F>kF^DHŒDCNF^k>FBNFAllX ! !!!!!!!!! !!!!!!!!!!!!!!!!!!!!!!! SB!o!O`C@=ŒF^DHG ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SB!o!J ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!! !!!!!!!!!!!!!!!!!!!!!!!! CFDTQ8LAŒBTFCHGŒDCN^!o!kBTFCHG;DCNF^Z^[!MLA!^!DC!MDCNŒCFDTQ8LAGZBTFCHGkDCN^l[! DM!^!DC! BTFCHGl ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! SC!o!J!!C@=8FA!LM!CFDTQ8LADCT!BTFCHG!WQL!QBG!HQF!GB=F!F^DH!BG!HQF!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! MLA!CFDT Q8LAŒDCN^!DC!CFDTQ8LAŒBTFCHGŒDCN^X ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!F^DHGŒ>B8F>kF^DHŒDCNF^kCFDTQ8LAŒDCN^ll!o o!F^DHGŒ>B8F>kF^DHŒDCNF^k>FBNFAllX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SC!Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! SC!o!SC`C@=ŒF^DHG ! !!!!!!!!!!!!!!!!!!!!! !!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! SR!o!SCS>SB!Š!ZO , S>[ZO , SB[ZO , SC[ ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!! !!!!!!!!!!!!!!!!!!!! DM!SR!“!J;hX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!!!!!!!!!!!!! !!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o! , O ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! F>GFX!!! ! !!!!!!!!!!!!!!! !!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!! SADLADHDFGkDCN^l!o!AFTDLCŒABC_kDl ! !!!!!!!!!!!! ! !!!! >FBNFAG!o!CS;@CD?@FZBTFCHŒ>FBNFA[k OXl ! !!!! ! !!!! AFH@AC!BTFCHŒ>FBNFAFBNFAGHMZ>FBNFAGHMŒ=BHAD^!o!‘’ ! !!!! MLA!>FBNFA!DC!>FBNFAGX ! !!!!!!!! =9=BH!o!CS;]FALGZZWDNHQ
PAGE 162

OYh ! ! !!!!!!!! MLA!^!DC!ABCTFZWDNHQ[X ! !!!!!!!!!!!! MLA!9!DC!ABCTFZQFDTQH [X ! !!!!!!!!!!!!!!!! =9=BHk^lk9l!o!=B^ZkB8GZBTFCHGk>FBNFAlkJl! , ^[FBNFAlkOl! , ! 9[l[ ! ! !!!!!!! >HMŒ=BHAD^k>FBNFAl!o!=9=BH ! !!!! AFH@AC!>HMŒ=BHAD^ ! ! NFM!@SNBHFŒBTFCHŒ=BHAD^ZBTFCHŒ=BHAD^[X ! !!!! CFWŒ=BHAD^!o!kl ! !!!! MLA!L>N=BH!DC!BTFCHŒ=BHAD^X ! !!!!!!!! CFW=B H!o!ZO , B>SQB[ZO , NF>HB[L>N=BH! ! ! !!!!!!!! CFWŒ=BHAD^;BSSFCNZCFW=BH[ ! !!!!!!!! ! !!!! AFH@AC!CFWŒ=BHA D^!! ! !!!! ! NFM!MDCNŒSAL8ZRF>>GNŒNDA>!DC!RF>>GX ! !!!!!!!! DM!RF> >kIl!do!L>NŒNDAX ! !!!!!!!!!!!! =9_D!o!J ! !!!!!!!! F>GFX ! !!!!!!!!!!!! =9_D!o!_D ! !!!!!!!!!!! ! !!!!!!!! DM!DGŒNFCGDH9X ! !!!!!!!!!!!! NFCGDH9!o!MDCNŒNFCGDH9ZRF>>GFX ! !!!!!!!!!!!! NFCGDH9!o!J!! ! !!!!!!!!!!!!!!!! ! !!!!!!!! S!o!CS; F^SZ_NBTFCHŒ=BHAD^kRF>>kJl>kOll[CS;F^SZ , _GHHMŒ=BHAD^kRF>>kJl>kO ll[CS;F^SZ=9_D[CS;F^SZ_HNFCGDH9[ ! !!!!!!!! SAL8G;BSSFCNZS[ ! !!!! ! !!!! SAL8G!o!k^`G@=ZSAL8G[!MLA!^!DC!SAL8Gl ! !!!! AFH@AC!SAL8G ! ! MAL=!QFBS?!D=SLAH!QFBSSLSFSBHQ[X ! !!!! AL WG!o!kl ! !!!! WDHQ!LSFCZMD>FSBHQFDNX ! !!!!!!!! MLA!>DCF!DC!MD>FDN;AFBN>DCFGZ[X ! !!!!!!!!!!!! ALWG;BSSFCNZkDCHZ^[!DM!^!F>GF!J!MLA!^!DC!>DCF;AGHADSZp Ž Cp[;GS>DHZp
PAGE 163

OYU ! ! !!!! AFH@AC ! CS;BAAB9ZALWG[;+ ! ! ! NFM!AFBNŒSCTZMD>FSBHQ[X ! !!!! SD^F>G!o!DL;D=AFBNZMD>FSBHQG;GQBSF[ ! !!!! =B]FkSD^F>G!oo!Jl!o!O ! !!!! =B]FkSD^F>G!oo!J;IOIil!o!P ! !!!! ! NFM!=B]FITABSQZ=B]F[X ! !!!! QFDTQH!o!>FCZ=B]F[ ! !!!! WDNHQ!o!>FCZ=B] FkJl[!DM!QFDTQH!F>GF!J ! !!!! TABSQ!o!‘ZD!DC!TABSQ;_F9GZ[X ! !!!!!!!! DM!ALW!”!QFDTQH! , ! O!BCN!CLH!=B]FkALW!Š!OlkRL>lX ! !!!!!!!!!!!! TABSQkZALW[l;BSSFCNZZv2v[[[ ! !!!!!!!!!!!! TABSQkZALW!Š!O[l; BSSFCNZZv1v[[[ ! !!!!!!!! DM!RL>!”!WDNHQ! , ! O!BCN!CLH!=B]FkALWlkRL>!Š!OlX ! !!!!!!!!!!!! TABSQkZALW[l;BSSFCNZZv-v!Š!O[[[ ! !!!!!!!!!!!! TABSQkZALW!Š!O[l;BSSFCNZZv7v[[[ ! !!!! AFH@AC! TABSQ ! ! ! NFM!NDGHZSO>[X ! !!!! AFH@AC!B8GZRF>>kJl! , ! TLB>kJl[!Š!B8GZRF>>kOl! , ! TLB>kOl[ ! !!!! AFH@AC!NDGHZRF>>[ ! ! NFM!MDCNŒGQLAFGHŒSBHQZTABSQ[F!SAŒ?@F@FX ! !!!!!!!! ŒX ! !!!!!!!!!!!! AFH@AC!>FCZSBHQ[ ! !!!!!!!! DM!R@AAFCH!DC!QDGHL A9X ! !!!!!!!!!! !! AFH@AC!>FCZSBHQ[!Š!QDGHLA9kR@AAFCHl ! !!!!!!!! DM!R@AAFCH!DC!EDGDHFNX ! !!!!!!!!!!!! RLCHDC@F ! !!!!!!!! EDGDHFN;BNNZR@AAFCH[ ! !!!!!!!! MLA!NDAFRHDLC[
PAGE 164

OiJ ! ! !!!!!!!! !!!!!!!!!!!!!!!!!!!!!!!! SBHQ!Š!NDAFRHDLC9TLCZ^FCZSLDCHG[ ! !!!! DCGDNF!o!6B>GF ! !!!! SO^LLAZ=B]F9TLCZ^
PAGE 165

OiO ! ! !!!! ! !!!! =B]Fk=B]F!oo!Il!o!O ! !!!! TABSQ!o!=B]FITABSQZ=B]F[ ! !!!! F^ŒDCN^!o!J ! !!!! MLA! F^!DC!F^DHGX ! !!!!!!!! SADCHZp%@CCDCT!MLA!F^DH!‘J’p;MLA=BHZF^ŒDCN^[[ ! !!!!!!!! F^ŒDCN^!Šo!O ! !!!!!!!! QDGHLA9!o!‘’ ! !!!!! !!! =9=BH!o!CS;DCMCS;LCFGZZWDNHQLR_FN!o!6B>GF ! ! !!!!!!!!!!!!!!! DM!=B]Fk^<9l!do!OX ! !!!!!!!!!!!!!!!!!!!! =9=BHk^lk9l!o!QF@ADGHDRZk^<9lDCF!DC!ABCTFZ^=DC<^=B^[X ! !!!!!!!!!!!!!!!!!!!!!!!! 9>DCF!o!D CHZZ^>DCF , ^[`ZF^kJl , ^[ZF^kOl , 9[!Š!9[ ! !!!!!!!!!!!!!!!!!!!!!!!! DM!=B]Fk^>DCF<9>DCFl!oo!OX ! !!!!!!!!!!!!!!!!!!!!!!!!! !!! =9=BHk^lk9l!o! , CS;DCM ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! 8>LR_FN!o!+A@F ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! 8AFB_ ! !!!!!!!!!!!!!!!!!!!! DM!CLH!8>LR_FNX!! ! !! !!!!!!!!!!!!!!!!!!!!!! 9=DC!o!=DCZk9DCF!DC!ABCTFZ9=DC<9=B^[X ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ^>DCF!o!DCHZZ9>DCF , 9[`ZF^kOl , 9[ZF^kJl , ^[!Š!^[ ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!=B]Fk ^>DCF<9>DCFl!oo!OX ! !!!!!!!!!!!!!!!!!!!!!!!!! !!!!!!! =9=BHk^lk9l!o! , CS;DCM ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 8>LR_FN!o!+A@F ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 8AFB_! ! !!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! DM!CLH!8>LR_FNX ! !!!!!!!!!!!!!!!!!!!!!!!! QDGHLA9kZ^<9[l!o ! =9=BHk^lk9l ! !!!!!!!!!!!!!!!!!!!!!!!! !QDGHL A9!DG!@GFN!HL!_FFS!HABR_!LM!LC>9!*42!SD^F>G! ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!! MLA!^!DC!H?N=ZABCTFZWDNHQ[[X ! !!!!!!!!!!!! MLA!9!DC!ABCTFZQFDTQH[X! ! !!!!!!!!!!!!!!!! DM!=B]Fk^<9l!do!OX ! !!!!!!!!!!!!!!!!!!!! DM!CS;DGDCMZ= 9=BHk^lk9l[X!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!! !!!!!!!!! =9=BHk^lk9l!o!MDCNŒGQLAFGHŒSBHQZTABSQ
PAGE 166

OiI ! ! !44(+')^," , #8GBE:78;F, : ;D,16D:CC8?,'J;:G8?= , 4 J7@6;,&6D< , ! D=SLAH!C@=S9!BG!CS ! D=SLAH! =BHS>LH>D8;S9S>LH!BG!S>H ! D=SLAH!SBCNBG!BG!SN ! MAL=!NBHFHD=F!D=SLAH!NBHFHD=F ! D=SLAH!LG ! D=SLAH!HD=F ! D=SLAH!RF>>@>BA/@HL=BHFN ! D=SLAH!HLL>G ! ! >B9L@HŒC@=8FA!o!OP ! =B^ŒGSFFN!o!i!!!HQF!=B^D=@=!GSFFN!BC9!BTFCH!RBC!TL> ! ! ! DGŒS>LH!o!+A@F! ! DGŒ>FBNFA!o!+A@F!!DM!+A@FFBNFAG!BAF!RAFBHFN!BH!HD=FGHB=S!P ! DGŒABC_FN!o!6B>GF!!DM!+A@FFBNFA!WD>>!QBEF!SADLADH9!8BGFN!LC!HQFDA!=DCŒL8aGFWB9G!ML>>LW!HQF!>FBNFAG F!HQF9!=B9!LA!=B9CLH!ML>>LW ! NFRDGDLCŒRBGF!o!O!!O!MLA!iJt>LWG!HQF!>FBNFAFBNFAŒ=LN!o!M>LBHZpDCMp[!!!LSHDLC!HL!AFNL!>FBNFA!GF>FRHDLC!ZDCM!oo!LCRFB9L@H!o!+A@F ! GFFN!o!OiJ ! ! ! GHBAHŒHD=F!o!HD=F;HD=FZ[ ! HABEF>ŒHD=FŒNDGHG>@>BA/@HL=BHFN;A@CZ>B9L@HŒC@=8FALH!o!DGŒS>LHFBNFA!o!DGŒ>FBNFAFBNFAŒ=LN!o! >FBNFAŒ=LNB9L@H!o!N9CB=DRŒ >B9L@HBHDLCX!vBSGFN!HD=F!WBG!tT!GFRLCNGv!t!ZFCNŒHD=F! , ! GHBAHŒHD=F[[ ! ! ! DM!JX ! !!!! HHMŒ=BHAD^G;AFBNŒ>B9L@HZ>B9L@HŒC@=8FA[ !

PAGE 167

OiP ! ! !!!! HLL>G;S>LHŒ>B9L@HZHHM Œ=BHAD^[ ! ! tt! ,,,,,,,, ! %FG@>HG!2FRH DLC ,,,,,,,,,,,,,,,,,,,,, ! BAFBŒSFAŒSD^F>!o!;Y;Y!!=I ! C@=8FAŒLMŒHD=FGHB=SGŒSFAŒGFR!o!P ! ! AFG@>HG!o!SN;'BHB6AB=FZ‘pC@=ŒBTFCHpX!HD=FŒC@=8FAŒBTFCHGHGkpNFCGDH9pl!o!AFG@>HGkpC@=ŒBTF CHpl`ZBAFBŒSFAŒSD^F>SD^F>G[ ! ! AFG@ >HGkpBETŒGSFFNIplo!CS;BAAB9ZHABEF>ŒNDGH[`CS;BAAB9ZHABEF>ŒHD=F[ ! AFG@>HGkpM>LWŒC@=8FAŒL@Hpl!o! , AFG@>HGkpC@=ŒBTFCHpl;NDMMZ[ ! AFG@>HGkpM>LWpl!o!AFG@>HGkpNFCGDH9plAFG@>HGkpBETŒGSFFNpl ! AFG@>HGkpM>LWOpl!o!AFG@>HGkpNFCGDH9pl`AFG@ >HGkpBETŒGSFFNpl ! ! MD>FCB=F!o!LG;SBHQ;aLDCZLG;TFHRWNZ[HGpHG;HLŒRGEZpCLCŒNFHFA=DCDGHDRZO[ŒYJŒ>B9L@HŒ‘J’ŒGFFNŒ‘O’ŒBTFCHGŒ‘I’;RGEp;MLA=BHZ>B9L@HŒC @=8FAŒHD=FpX! HABEF>ŒHD=FŒNDGHp!X!HABEF>ŒNDGHŒNDGHpl`BTFCHŒNBHBkpHABEF>ŒHD=Fpl ! BTFCHŒNBHB;HLŒRGEZpCLCŒNFHFA=DCDGHDRZO[ ŒYJŒBTFCHGŒ>B9L@HŒ ‘J’ŒGFFNŒ‘O’ŒBTFCHGŒ‘I’;RGEp;MLA= BHZ>B9L@HŒC@=8FAG ! D=SLAH!C@=S9!BG!CS ! D=SLAH!=BHS>LH>D8;S9S>LH!BG!S>H ! D=SLAH!HD=F ! ! NFM!A@CZ>B9L@HŒC@=8FAGFLHo6B >GFFBNFAo6B>GFGFFBNFAŒ=LNoM>LBHZpDCMp[B9L@Ho6B>GF[X ! ! !!!! CS;ABCNL=;GFFNZGFFN[ ! !!!! ! !!!! HHMŒ=BHAD^G;AFBNŒ>B9L@HZ>B9L@HŒC@=8FA[ ! !!!! ! !!!! SD^F>G!o!Z=B]F!oo!J[;G@=Z[ ! !!!! ! !! !! WDNHQ!o!=B]F;GQB SFkJl ! !!!! QFDTQH!o!=B]F;GQBSFkOl!! ! !!!!!! ! !!!! F^DHG!o!kZ^<9[!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!! F^DHGŒ>B8F>!o!k=B]Fk^<9l , P!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!! L8GHBR>FG!o!kZ ^<9[!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!oo!Ol ! !!!! ! !!!! !

PAGE 168

OiY ! ! !!!! BTFCHG!o!kZOJF!>FCZBTFCHG[!”!C@=ŒBTFCHGX ! !!!!!!!! CF^HŒBTFCH!o!ZDCHZKJCS;ABCNL=;ABCNZ[[FG!BCN!CF^HŒBTFCHkOl!“!Oh!BCN!CF^HŒBTFCHkOl!”!IhX ! !!!!!!!!!!!! BTFCHG;BNNZCF^HŒBTFCH[ ! !!!! BTFCHG!o!>DGHZ BTFCHG[ ! !!!! ! !!!! ! !!!! !BTFCHG!DC!CFDT8LADCT!ALBNG ! !!!! C@=ŒGDNFG!o!J ! !!!! GDNFRBAG!o!GFHZ[ ! !!!! WQD>F!>FCZGDNFRBAG[ ! ”!C@=ŒGDNFGX ! !!!!!!!! CF^HŒBTFCH!o!ZDCHZWDNHQCS;ABCNL=;ABCNZ[[FG!BCN!ZCF^H ŒBTFCHkOl!“o!YJ!LA!CF^HŒBTFCHkOl!”o!g[X ! !!!!!!!!!!!! GDNFRBAG;BNNZCF^HŒBTFCH[ ! !!!! GDNFRBAG!o!>DGHZGDNFRBAG[ ! !!!! ! ! !!! ! !!!! GHBAHDCTŒSLDCH!o!BTFCHG;RLS9Z[ ! !!!! ! !!!! BTFCHGŒ=B^ŒGSFFN!o!CS;ABCNL=;ABCNDCHZOFBNFA!o!k , Ol>FCZBTFCHG[ ! !!!! >FBNFAG!o!kl ! !!!! ! !!!! ! !!!! F^DHFN!o!CS;BAAB9Zk6B>GFl>FCZBTFCHG[[ ! !!!! R@AAFCHŒBTFCHG!o!BTFCHG;RLS9Z[ ! !!!! ! !!!! !DC DHDB>>9!B>>!BTFCHG!GF>FRH!HQFDA!F^DHG!ABCNL=>9 ! !!!! !F^DHŒDCNF^!o!CS;ABCNL=;ABCNDCHZJ<>FCZF^DHG[ , OFCZBTFCHG[[ ! !!!! F^DHŒDCNF^!o!HLL>G;GF>FRHF^DHZBTFCHGFCZBTFCHG[[!!!! ! !!!!!!!! ! !!!! BTFCHŒ=BHAD^!o!kl!! N9CB=DR!M>LLA!MDF>N ! !!!! MLA!DCN^!DC!ABCTFZ>F CZBTFCHG[[X ! !!!!!!!! BTFCHŒ=BHAD^;BSSFCNZCS;]FALGZZWDNHQLHX !

PAGE 169

Oii ! ! !!!!!!!! S>H;MDT@AFZ[ ! !!!! HABEF>ŒHD=F!o!CS;BAAB9ZkJl>FCZBTFCHG[[ ! !!!! HABEF>ŒNDGH!o!CS;BAAB9ZkJl>FCZBTFCHG[[ ! !! !! L8aŒSBAB=!o!CS;ABCNL=;ABCNZ>FCZBTFCHG[[!!HQDG!DG!MLA!>FBNFA!GF>FRHDLC ! !!!! SADLADHDFG!o!CS;BAAB9ZkPKl>FCZBTFCHG[[ ! !!!! ! !!!! ! !!!! =9=BHAD^!o!HLL>G;RAFBHF=BHAD^ZWDNHQFGG;GF>FRHF^DH ZG DNFRBAGGFl>FCZGDNFRBAG[BHDLC!2HBAHFN;;;p[ ! !!!! WQD>F!>FCZR@AAFCHŒBTFCHG[!“!J!BCN!CDHFA!”!OJJJJX ! !!!!!!!! ! !!!!!!!! ! !!!!!!!! MLA!DCN^!DC!ABCTFZ>FCZGDNFRBAG[[X ! !!!!!!!!!!!! CFDTQ8LAŒRF>>G!o!HLL>G;MDCNŒCFD TQ 8LAGZGDNFRBAGkDCN^lFG!Š! F^DHG!Š!GDNFRBAG[ ! !!!!!!!!!!!! DM!CFDTQ8LAŒRF>>GX ! !!!!!!!!!!!!!!!! SAL8G!o!HLL>G;MDCNŒSAL8ZCFDTQ8LAŒRF>>GGF[! ! !!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! GF>FRHFNŒDCN^!o!CS;BAT=B^ZSAL8G[ ! !!!!!!!!!!!!!!!! GF>FRHFNŒRF>>!o!CFDTQ8LAŒRF>>GkGF>FRHFNŒDCN^l ! !!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! !>LRBHDLC!DG ! E BRBCH!CLW ! !!!!!!!!!!!!!!!! =9=BHAD^kGDNFRBAGkDCN^lkJlFRHFNŒRF>>kXIl ! !!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! @SNBHF!HQF!=BHAD^!WDHQ!CFW!>LRBHDLC ! !!!!!!!!!!!!!!!! =9=BHAD^kGDNFRBAGkDCN^lkJlG;NDGHZGDNFRBAGkDCN^lFCZR@AAFCHŒBTFCHG[[ ! !!!!!!!! CDHFA!Šo!O ! !!!!!!!! ! !!!!!!! ! DM!CDHFAt>FBNFAŒ=LN!oo!Y!BCN!DGŒ>FBNFAX!!BH!HQDG!DHFABHDLCFBNFAG!BAF!BGGDTCFN!MLA!FBRQ!AFTDLC ! !!!!!!!!!!!! L8aŒSBAB=!o!CS;ABCNL=;ABCNZ>FCZBTFCHG[[ ! !!!!!!!!!!!! BTFCHŒ>FBNFAFBNFAGG;RAFBHF>FBNFAZWDNHQB8F>FBNFAG!‘J’FBNFAp;MLA=BHZ>FCZ>FBNFAG[FBNFA!do! , O[;=FBCZ[[[ ! !!!!!!!! ! !!!!!!!! !HQDG!SBAH!DG!@GFN!HL!RQBCTF!HQF!>B9L@H!MAL=!>B9L@HŒC@=8FA!HL!>B9L@HŒC@=8FA ! !!!!!!!! DM!CDHFA!oo!OJ!BCN!N9CB=DRŒ>B9L@HX !

PAGE 170

OiK ! ! !!!!!!!!!!!! HF=SŒHHMŒ=BHAD^G;AFBNŒ>B9L@HZGHAZ >B9L@HŒC@=8FA[Špp[ ! !!!!!!!!!!!! DM!HF=SŒHHMŒ=BHAD^X ! !!!!!!! !!!!!!!!! HHMŒ=BHAD^!o!HF=SŒHHMŒ=BHAD^ ! !!!!!!!!!!!!!!!! WDNHQ!o!=B]F;GQBSFkJl ! !!!!!!!!!!!!!!!! QFDTQH!o!=B]F;GQBSFkOl!! ! !!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! F^DHG!o!kZ^<9[!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!!!!!!!!!!!!!! F^DHGŒ>B8 F>!o!k=B]Fk^<9l , P!MLA!^!DC!ABCTFZWDNHQ[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!“o!Pl ! !!!!!!!!!!!!!!!! L8GHBR>FG!o!kZ^<9[!MLA!^!DC!ABCTFZWDNH Q[!MLA!9!DC!ABCTFZQFDTQH[!DM!=B]Fk^<9l!oo!Ol ! !!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! !BTFCHG!CFFN!HL!AFGF>FRH!HQFDA!F^DHG ! !!!! !!!!!!!!!!!!! F^DHŒDCNF^!o!HLL>G;GF>FRHF^DHZBTFCHGG;RAF BHF=BHAD^ZWDNHQFG!Š!GDNFRBAGG;GF>FRHF^DHZBTFCHG9!>FBNFAG!RBC!R QBCTF!HQFDA!F^DH!N@ADCT!GD=@>BHDLC ! !!!!!!!!!!!! MLA!>FBNFA!DC!>FBNFAGX ! !!!!!!!!!!!!!!!! SADCHZ>FBNFA FBNFAl[ ! !!!!!!!!!!!!!!!! DM!CLH!F^DHFNk>FBNFAlX ! !!!!!!!!!!!!!!!!!!!! SADCHZp Ž CpFBNFAFBNFAl[ ! !!!!!!!!!!!!!!!!!!!! F ^DHŒDCNF^k>FBNFAl!o!DCGDNFŒF^DHŒDCNF^k>FBNFAl ! !!!!!!!!!!!! ! !!!!!!!! BTFCHGŒGSFFN!o!kl ! !!!!!!!! ! !!!!!!!! DCNDRFG!o!CS;BABCT FZJ<>FCZBTFCHG[[ ! !!!!!!!! DM!DGŒABC_FNX ! !!!!!!!!!!!! DCNDRFG!o!DCNDRFGkCS;BATGLAHZSADLADHDFG[l!!WF!=LNDM9!HQF!DCNF^!LM!BTFCHG!8BGFN!LC!HQ FDA!SADLADHDFG ! !!!!!!!! ! !!!!!!!! MLA!DCN^!DC!DCNDRFGX ! !!!!!!!!!!!! R@AAFCHŒBTFCHG!o!k^!MLA!DF!BTFCHŒDHFABHDLC!”!BTFCHGŒ=B^ŒGSFFNkDCN^l ! BCN!CLH!F^DHFNkDCN^lX ! !!!!!!!!!!!!!!!!!!!! R@AAFCHŒBTFCHG!o!k^!MLA!D< ! ^!DC!FC@=FABHFZBTFCHG[!DM!CLH!F^DHFNkDll ! !!!!!!!!!!!!!!!!!!!! CFDTQ8LAŒRF>>G!o!HLL>G;MDCNŒCFDTQ8LAGZBTFCHGkDCN^lFG! Š!F^DHG!Š!GDNFRBAG[ ! !!!!!!!!!!! !!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! DM!CFDTQ8LAŒRF>>GX ! !!!!!!!!!!!!!!!!!!!! !!!! ! !!!!!!!!!!!!!!!!!!!!!!!! DM!DGŒ>FBNFAX!!DM!>FBNFA!DG!6B>GFFBNFAkDCN^l!oo! , OX!!BTFCH!QBG!CLH!>FBNFA ! !!!!!! !!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o!HLL>G;MDCNŒSAL8ZCFDTQ8LAŒRF>>GGFX! ! !ML>>LWFAG!TL!HQF!F^DH!GF>FRHFN!89!HQF!>FBNFA !

PAGE 171

Oig ! ! !!!!!!!!!!!!!!!!!!!!! !!!!!!!!!!! DM!HLL>G;NDGHZBTFCHGkDCN^lG;NDGHZBTFCHGkBTFCHŒ>FBNFAkDCN^llFBNFAkDCN^ll ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o ! HLL>G;MDCNŒSAL8ZCFDTQ8LAŒRF>>GGFX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!! SAL8G!o!H LL>G;MDCNŒSAL8ZCFDTQ8LAŒRF>>GGF[! ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!! ! !!!!!!!!!!!!!!!!!!!!!!!! GF>FRH FNŒDCN^!o!CS;BAT=B^ZSAL8G[ ! !!!!!!!!!!!!!!!!!!!!!!!! GF>FRHFNŒRF>>!o!CFDTQ8LAŒRF>>GkGF>FRHFNŒDCN^l ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! !>LRBHDLC!DG!EBRBCH!CLW ! !!!!!!!!!!!!!!!! !!!!!!!! =9=BHAD^kBTFCHGkDCN^lkJlFRHFNŒRF>>kXIl ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! @SNBHF!HQF!=BHAD^!WDHQ!CFW!>LRBHDLC ! !!!!!!!!!!!!!!!!!!!!!!!! =9=BHAD^kBTFCHGkDCN ^lkJlFRHFNŒRF>>kJlFRHFNŒRF>>kOll!Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒNDAFRHDLCGkDCN^l!o!GF>FRHFNŒRF>>kIl ! !!!!!!!!!!!!!!!!!!!!!!!! HABEF> ŒNDGHkDCN^l!Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! SADCHZBTFCHŒNDAFRHDLCG[ ! !!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒDHFABHDLC!Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! DM!HLL>G;NDGHZBTFCHGkDCN^lŒHD=FkDCN^l!o!CDHFA ! !!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!!!!!!!! !!!!!!!!!! 8AFB_ ! !!!!!!!!!!!! ! !!!!!!!!!!!!!!!! BTFCHGŒGSFFN;BSSFCNZBTFCHŒDHFABHDLC[!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! ! !!!!!!!! HD=FŒBETŒGSFFN;BSSFCNZCS;=FBCZBTFCHGŒGSFFN[[!!!!!!!!!!! ! !!!!!!!! ! !!!!!!!! BTFCHŒ=BHAD^!o!HLL>G;@SNBHFŒBTFCHŒ=BHAD^ZBTFCHŒ=BHAD^[ ! !!!!!!!! ! !!!!!!!! DM!DGŒ S>LHX ! !!!!!!!!!!!! HLL>G;S>LHŒ=BHAD^ZWDNHQFGFBNFAGH;D=GQLWZ=9=BHAD^;+[ ! !!!!!!!!!!!! HLL>G;S>LHŒ=BHAD^Z=9=BHAD^[ ! !!!!!!!!!!!! S>H;HDH>FZp+D=FGHB=SX!‘JXPN’ p;MLA=BHZCDHFA[[ ! !!!!!! !!!!!! S>H;SB@GFZJ;JO[ ! !!!!!!!!!!!! S>H;R>MZ[ !

PAGE 172

Oih ! ! !!!!!!!!!!!! ! !!!!!!!! F>BSGFN!o!HD=F;HD=FZ[! , ! GHBAH ! !!!!!!!! SADCHZp‘JX;IM’!GFRLCNGBSGFNFCZR@AAFCHŒBTFCHG[[[!!!! ! !!!! AFH@AC!HABEF>ŒHD=FŒNDGHGF ! D=SLAH!=BHS>LH>D8;S9S>LH!BG!S>H ! D=SLAH!=BHS>LH>D8!BG!=S> ! ! >FEF>G!o!OJ!! ! B>SQB!o!J;I!!MLA!N9CB=DR!M>LLA ! NF>HB!o!J;I!!MLA!N9CB=DR!M>LLA ! ! DCBRHDLC!o!J;i ! _N!o! J;i!!WFDTQH!LM!N9CB=DR ! M>LLA! ! _G!o!I;J!!WFDTQH!LM!GHBHDR!M>LLA ! _D!o!J;i!!NDAFRHDLC ! _W!o!J;P!!WB>>!GFCGDHDEDH9 ! _H!o!J;JI!!NFCDGH9!GFCGDHDEDH9 ! '=B^!o!OJ ! ! >B9L@HŒML>NFA!o!p*B9L@HGp ! ! NFM!NDGHZSOFRHF^DHZBTFCHG>RBAG!o!GDNFRBAG!Š!k^!MLA!DCN^>RBAGX ! !!!!!!!!!!!! DM! NDGHZ^FEF>GX ! !!!!!!!!!!!!!!!! R@AAFCHŒCFDTQ8LAG!Šo!O ! !!!!!!!! CFDTQ8LAG;BSSFCNZR@AAFCHŒCFDTQ8LAG[ ! !!!! ! !!!! MLA!BTFCH!DC!BTFCHGX ! !!!!!!!! NDGHBCRFG!o!kl ! !!!!!!!! MLA!F^!DC!ABC TFZ>FCZF^DHG[[X ! !!!!!!!!!!!! NDGHBCRFG;BSSFCNZHHMŒ=BHAD^kF^lkBTFCHl[ ! !!!!!!!! AF WBAN!o!k^`GSFFN!Š!9!MLA!^
PAGE 173

OiU ! ! ! NFM! AFBNŒ>B9L@HZ>B9L@HŒC@=8FA[X ! !!!! WN!o!LG;TFHRWNZ[ ! !!!! ! !!!! SDR_>FŒMD>F!o!LG;SBHQ;aLDCZWNB9L@HŒML>NFAB9L@H‘J ’;S_>p;MLA=BHZ>B9L@HŒC@=8FA[[ ! !!!! RGEŒMD>F!o!LG;SBHQ;aLDCZWNB9L@HŒML>NFAB9L@H‘J’;RGEp;MLA=BHZ>B9L@HŒC@=8FA[[ ! !!!!!!! ! !!!! DM!LG;SBHQ;DGM D>FZSDR_>FŒMD>F[X ! !!!!!!!! WDHQ!LSFCZSDR_>FŒMD>FF;>LBNZM[ ! !!!!!!!!!!! ! HHMŒ=BHAD^F;>LBNZM[ ! !!!!!!!!!!!! ! !!!!!!!! =B]F!o!GM;AFBNŒRGEZRGEŒMD>F[ ! !!!!!!!! =B]Fk=B]F!oo!Il!o!O ! !!!! ! !!!!!!!! AFH@AC!HHMŒ=BHA D^GFX ! !!!!!!!! AFH@AC!1LCFLHŒ>B9L@HZHHMŒ=BHAD^[X ! !!!! B>>ŒF^DH!o!OJJJ ! !!!! MLA!F^Œ=BH!D C!HHMŒ=BHAD^X ! !!!!!!!! F^Œ=BH!o!F^Œ=BH;RLS9Z[ ! !!!!!!!! F^Œ=BHkCS;DGCBCZF^Œ=BH[l!o!CS;DCM ! !!!!!!!! B>>ŒF^DH!o!CS;=DCD=@=ZB>>ŒF^DH>ŒF^DHkB>>ŒF^DH!oo!CS;CBC=B^ZB>>ŒF^DH[l!o!CS;DCM ! !!!! S>H;=BHGQLWZB>>ŒF^DH;+[ ! ! ! NFM!MDCNŒCFDTQ8LAGZBTFCHDGH!o!kZ^ , O<9 , ODNŒ>DGH!o!kl ! !!!! MLA!CFDTQ8LA!DC!CFDTQ8LAŒ>DGHX ! !!!!!! !! DM!J!”o!CFDTQ8LAkJl!”o!WDNHQ! , O!BCN!J!”o!CFDTQ8LAkOl!”o!QFDTQH! , OX ! !!!!!!!!!!!! DM!CFD TQ8LAkXIl!CLH!DC!BTFCHGX ! !!!!!!!!!!!!!!!! EB>DNŒ>DGH;BSSFCNZCFDTQ8LA[!!!!!!!!!!!! ! !!!! AFH@AC!EB>DNŒ>DGH ! !!!! ! NFM!MDCNŒNFCGDH9ZBTFCH>G!o!MDCNŒCFDTQ8LAGZBTFCHB9FAG!o!kCFDTQ8LAŒRF>>Gl !

PAGE 174

OKJ ! ! !!!!!!!! MLA!D!DC!ABCTFZNFSHQ[X ! !!!!!!!!!!!! >B9FAG;BSSFCNZkl[ ! !!!!!!!!!!!! MLA!RF>>!DC!>B9FAGk , IlX ! !!!!!!!!!!!!!!!! >B9FAGk , Ol;F^HFCNZMDCNŒCFDTQ 8LAGZRF>>>G!o!>DGHZGFHZk^kXIl!MLA!>B9FA!DC!>B9FAG!MLA!^!DC!>B9FAl[[ ! !!!!!!!! CFDTQ8LAŒRF>>G!o!k^!ŠZD<[!MLA!D<^!DC!FC@=FABHFZCFDTQ8LAŒRF>>G[l ! !!!! ! !!!! =9C@=!o!J ! !!!! MLA!RF>>!DC ! CFDTQ8LAŒRF>>GX ! !!!!!!!! DM!=9=BHAD^kRF>>kJl >kOll!oo!OX ! !!!!!!!!!!!! =9C@=!Šo!O!!!!!!!!!!!! ! !!!! AFH@AC!=9C@=`>FCZCFDTQ8LAŒRF>>G[ ! ! NFM!S>LHŒ=BHAD^ZWDNHQFGFBNFAGFBNFAGX ! !!!!!!!!!!!!!!!! =9=BHAD^kSkJlGFX ! !!!!!!!!!!!!!!!! =9=BHAD^kSkJlFGX ! !!!!!!!! =9=BHAD^kSkJlLAŒ=BS!o!‘JX!pWQDHFpBC_ ! !!!!!!!!!!!!!!!!! OX!p8>BR_ppF ! !!!!!!! !!!!!!!!!! PX!pAFNpFBNFA!O ! !!!!!!!!!!!!!!!!! iX!p*D=FpFBNFA!I ! !!!!!!!!!!!!!!!!! KX!p$>@Fp FBNFA!P ! !!!!!!!!!!!!!!!!! gX!pTAB9p’!!!!!!! ! !!!! ! !!!! R=BS!o!=S>;RL>LAG;*DGHFN3L>LA=BSZk^kOl!ML A!^!DC!GLAHFNZRL>LAŒ=BS;DHF=GZ[[l[ ! !!!! CLA=!o!=S>;RL>LAG;1LA=B>D]FZE=DCoJH;D=GQLWZ=9=BHAD^;+FG
PAGE 175

OKO ! ! !!!! MLA!BTFC H!DC!BTFCHGX ! !!!!!!!! =9=BHAD^kBTFCHkJlFGX ! !!!!!!!! =9=BHAD^kSkJlFBNFAZWDNHQB8F>N!o!J;JO!!>LWFA!HQAFGQL>N!=FBCG!HQF!RQBCRF!LM!QBEDCT!>FBNFA!DCRAFBGFG ! !!!! L8aŒSBAB=!o!CS;ABCNL=;ABCNZ>FCZBTFCHG[[ ! !!!! ^8LANFADCGSBRFZJDCGSBRFZJFCZCS;@CD?@FZF^DHGŒ>B8F>[[ ! !!!! ! !!!! AFTDLCG!o!kl ! !!!! MLA!D!DC!ABCTFZC%FTDLCG[X ! !!!!!! !! MLA!a!DC!ABCTFZC%FTDLCG[X ! !!!!!!!!!!!! R@AAFCH!o!kl ! !!!!!!!!!!!! MLA!DCN^FB NFA!o!CS;BAAB9Zk , Ol>FCZAFTDLCG[[ ! !!!! AFTDLCŒABC_!o!CS;BAAB9ZkYl>FCZAFTDLCG[[! ! !!!! !O!DG!QDTQFGH!SADLADH9!BCN!Y!HQF!>FBGH!SAD LADH9 ! !!!! MLA!AFTDLCŒDCN^FBNFA!o! , O!!!!!!!! ! !!!!!!!! SADCHZ>FCZAFTDLC[`AFTDLCŒGD]F[ ! !!!! !!!! DM!>FCZAFTDLC[`AFTDLCŒGD]F!“!HQAFGQL>NX ! !!!!!!!!!!!! =DCŒL8a!o!OJJ ! !!!!!!!!!!!! MLA!D!DC!ABCTFZ>FCZAFTDLC[[X ! !!!!!!!!!!!!!!!! DM!Oh!”!BTFCHGkAFTDLCkDllkOl!”!IhX!!!HL!=B_F!G@AF!WF!QBEF!>FBNFA!LC>9!DC!HQF!=BDC!GHAFFH ! !!!!!!!!!!!!!!!!!!!! DM!L8aŒSBAB=kAFTDLClkDl!”!=DCŒL8aX ! !!!!!!!!!!!!!!!!!!!!!!!! =DCŒL8a!o!L8aŒSBAB=kAFTDLClkDl ! !!!!!!!!!!!!!!!!!!!!!!!! AFTDLCŒ>FBNFAkAF TDLCŒDCN^l!o!AFT DLCkDl ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!! !

PAGE 176

OKI ! ! !!!! BTFCHŒ>FBNFA!o!CS;BAAB9Zk , Ol>FCZBTFCHG[[ ! !!!! SADLADHDFG!o!CS;BAAB9ZkYl>FCZBTFCHG[[!!!!!!!!!! ! !!!! MLA!DFBNFA!o!AFTDLCŒ>FBNFAkDl ! !!!!! !!! DM!>FBNFA!do! , OX!!!!!!!!!!!! ! !!!!!!!!!!!! MLA!DCN^!DC!AFTDLCX ! !!!!!!!!!!!!!!!! DM!DCN^!oo!>FBNFAX!!MLA!>FBNFA!QD=GF>MFBNFAŒDCN^!DG! , O ! !!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o! , O ! !!!!!!!!!!!!!!!!!!!! SADLADHDFGkDCN^l!o!AFTDLCŒABC_kDl ! !!!!!!!!!!!!!!! ! F>GFX!!!! ! !!!!! !!!!!!!!!!!!!!! DM!CLH!NFHFA=DCDGHDRX ! !!!!!!!!!!!!!!!!!!!!!!!! DM!NFRDGDLCŒRBGF!oo!OX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!CS;ABCNL=;RQLDRFZk+A@FGFl[X ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! F>GF X ! !!!!!!!!!!!!!! !!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o! , O ! !!!!!!!!!!!!!!!!!!!!!!!! F>DM!NFRDGDLCŒRBGF!oo!IX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! S>!o!O`C@=ŒF^DHG ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!F^DHGŒ>B8F>kF^DHŒDCNF^kDCN^ll!oo!F^DHGŒ>B8F>kF^DHŒDCNF^k>FBNFAllX ! !!!!!!!!!!!!!!!!!!!!!!! !!!!!!!!! SB!o!O`C@=ŒF^DHG ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SB!o!J ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!! !!!!!!!!!!!!!!!!!!!! CFDTQ8LAŒBTFCHGŒDCN^!o!kBTFCHG;DCNF^Z^[!MLA!^!DC!MDCNŒCFDTQ8LAGZBTFCHGkDCN^lFBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!! !!! MLA!CFDTQ8LAŒDCN^!DC!CFDTQ8LAŒBTFCHGŒDCN^X ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!F^DHGŒ>B8F>kF^DHŒDCNF^kCFDTQ8LAŒDCN^ll! oo!F^DHGŒ>B8F>kF^DHŒDCNF^k>FBNFAllX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! SC!Šo!O ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! SC!o!SC`C@=ŒF^DHG ! !!!!!!!!!! !!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! SR!o!SCS>SB!Š!ZO , S>[ZO , SB[ZO , SC[ ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!! !!!!!!!!!!!!!!!!!!!!! DM!SR!“!J;hX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! F>GFX ! !!!!!!!! !!!!!!!!!!!!!!!!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o! , O ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! F>GFX!!! ! !!!!!!!!!!!!!! !!!!!!!!!! BTFCHŒ>FBNFAkDCN^l!o!>FBNFA ! !!!!!!!!!!!!!!!!!!!!!!!! SADLADHDFGkDCN^l!o!AFTDLCŒABC_kDl ! !!!!!!!!!!!! ! !!!! >FBNFAG!o!CS;@CD?@FZBTF CHŒ>FBNFA[kOXl ! !!!! ! !!!! AFH@AC!BTFCHŒ>FBNFAFBNFAG
PAGE 177

OKP ! ! ! NFM!@SNBHFŒ>HMZ>FBNFAG HMŒ=BHAD^!o!‘’ ! !!!! MLA!>FBNFA!DC!>FBNFAGX ! !!!!!!!! =9=BH!o!CS;]FALGZZWDNHQFBNFAlkJl! , ^[FBNFAlkOl! , ! 9[l[ ! !!!!!!!! >HMŒ=BH AD^k>FBNFAl!o!=9=BH ! !!!! AFH@AC!>HMŒ=BHAD^ ! ! ! NFM!@SNBHFŒBTFCHŒ=BHAD^ZBTFCHŒ=BHAD^[X ! !!!! CFWŒ=BHAD^!o!kl ! !!!! MLA!L>N=BH!DC!BTFCHŒ=BHAD^X ! !!!!!!!! CFW=BH!o!ZO , B>SQB[ZO , NF>HB[L>N=BH! ! ! !!!!!!!! CFWŒ=BHAD^;BSSFCNZCFW=BH[ ! !!!!!!!! ! !!!! AFH@AC!CFWŒ=BHAD^!! ! !!!! ! NFM ! MDCNŒSAL8ZRF>>GNŒNDA>!DC!RF>>GX ! !!!!!!!! DM!RF>>kIl!do!L>NŒNDAX ! !!!!!!!!!!!! =9_D!o!J ! !!!!!!!! F>GFX ! !!!!!!!!!!!! =9_D!o!_D ! !!!!!!!!!!! ! !!!!!!!! DM!DGŒNFCGDH9X ! !!!!!!!!!!!! NFCGDH9!o!MDCNŒNFCGDH9ZRF>>GFX ! !!!!!!!!!!!! NFCGDH9!o!J!! ! !!!!!!!!!!!!!!!! ! !!!!!!!! S!o!CS;F^SZ_NBTFCHŒ=BHAD^kRF>>kJl>kOll[CS;F^SZ , _GHHMŒ=BHAD^kRF>>kJl>kOll[CS;F^SZ=9_D[CS;F^SZ_HNFCGDH9 [ ! !!!!!!!! SAL8G;BSSFCNZS[ ! !!!! ! !!!! SAL8G!o!k^`G@=ZSAL8G[!MLA!^!DC!SAL8Gl ! !!!! AFH@AC!SAL8G ! MAL=!QFBS?!D=SLAH!QFBSSLS
PAGE 178

OKY ! ! ! NFM!AFBNŒRGEZMD>FSBHQ[X ! !!!! ALWG!o!kl ! !!!! WDHQ!LSFCZMD>FSBHQFDNX ! !!!!!!!! MLA!>DCF!DC!MD>FDN;AFBN>DCFGZ[X ! !!!!!!!!!!!! ALWG;BSSFCNZkDCHZ^[!DM!^!F>GF!J!MLA!^!DC!>DCF;AGHADSZp Ž Cp[;GS>DHZpFSBHQ[X ! !!!! SD^F>G!o!DL;D=AFBNZMD>FSBHQG;GQBSF[ ! !!!! =B]FkSD^F>G!oo!Jl!o!O ! !!!! =B]FkSD^F>G!oo!J;IOIil!o!P ! !!!! ! NFM!=B]FITABSQZ=B]F[X ! !!!! QFDTQH!o!>FCZ=B]F[ ! !!!! WDNHQ!o!>FCZ=B]FkJl[!DM!QFDTQH!F>GF!J ! !!!! TABSQ!o!‘ZD!DC!TABSQ;_F9GZ[X ! !!!!!!!! DM!ALW!”!QFDTQH! , ! O!BCN!CLH!=B]FkALW!Š!OlkRL>lX ! !!!!!!!!!!!! TABSQkZALW[l;BSSFCNZZv2v[[[ ! !!!!!!!!!!!! TABSQkZALW!Š!O[l; BSSFCNZZv1v[[[ ! !!!!!!!! DM!RL>!”!WDNHQ! , ! O!BCN!CLH!=B] FkALWlkRL>!Š!OlX ! !!!!!!!!!!!! TABSQkZALW[l;BSSFCNZZv-v!Š!O[[[ ! !!!!!!!!!!!! TABSQkZALW!Š!O[l;BSSFCNZZv7v[[[ ! !!!! AFH@AC!TABSQ ! ! ! NFM!NDGHZSO>[X ! !!!! AFH@AC!B8GZRF>>kJl! , ! TLB>kJl[!Š!B8GZRF>>kOl! , ! TLB>kOl[ ! !!!! AFH@AC!NDGHZRF>>[ ! ! NFM!MDCNŒGQLAFGHŒSBHQZTABSQ[F!SAŒ?@F@FX ! !!!!!!!! ŒX ! !!!!!!!!!!!! AFH@AC!>FCZSBHQ[ ! !!!!!!!! DM!R@AAFCH!DC!QDGHLA9X !

PAGE 179

OKi ! ! !!!!!!!!!! !! AFH@AC!>FCZSBHQ[!Š!QDGHLA9kR@AAFCHl ! !!!!!!!! DM!R@AAFCH!DC!EDGDHFNX ! !!!!!!!!!!!! RLCHDC@F ! !!!! !!!! EDGDHFN;BNNZR@AAFCH[ ! !!!!!!!! MLA!NDAFRHDLC[9TLCZ^9TLC!NFMDCFN!89 ! !!!! B!>DGH!LM!EFAHDRDFG!kZ^O;RL=;B@`B`S9HQLC , SLDCH , DCH , SL>9;QH=> ! !!!! vvv ! !!!! C!o!>FCZSLDCHG[ ! !!!! DCGDNF! o!6B>GF ! !!!! SO^LLAZ=B]F
PAGE 180

OKK ! ! !!!! DM!RQFR_ŒF^HFADLAX ! !!!!!!!! F^HFADLAG!o!CS;BAAB9ZkZ^<9[!MLA!^!DC!ABCTFZWDNHQ[! Ž ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!! MLA!9!DC!AB CTFZQFDTQH[!DM!=B]Fk^<9l!oo!Ol[ ! !!!!!!!! ! !!!!!!!! F^HFADLAG!o!GLAHŒSLDCHGZF^HFADLAG[ ! !!!!!!!!!!!! ! !!!!!!!! MLA!^!DC!ABCTFZWDNHQ[X ! !!!!!!!!!!!! MLA!9!DC!ABCTFZQFDTQH[X ! !!!!!!!!!!!!!!!! DM!=B]Fk^lk9l!oo!J!BCN!CLH!DCGDNFŒSL>9TLCZ^LR_FN!o!6B> GF ! !!!!!!!!!!!!!!!! DM!=B]Fk^<9l!do!OX ! !!!!!!!!!!!!!!!!!!!! =9=BHk^lk9l!o!QF@ADGHDRZk^<9lDCF!DC!ABCTFZ^=DC<^=B^[X ! !!!!!!!!!!!!!!!!!!!!!!!! 9>DCF ! o!DCHZZ^>DCF , ^[`ZF^kJl , ^[ZF^kOl , 9[!Š!9[ ! !!!!!!!!!!!!!!!!!!!!!!!! DM!=B]Fk^>DCF<9>DCFl!oo!OX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! =9=BHk^lk9l!o! , CS;DCM ! !!!!!!!!!!!!!!!! !!!!!!!!!!!! 8>LR_FN!o!+A@F ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! 8AFB_ ! !!!!!!!!!!!!!!!!!!!! DM!CLH!8>LR_FNX!! ! !!!!!!!!!!!!!!!!!!!!!!!! 9=DC!o!=DCZk9DCF!DC!ABCTFZ9=DC<9=B^[X ! !!!!!!!!!! !!!!!!!!!!!!!!!!!! ^>DCF!o!DCHZZ9>DCF , 9[`ZF^kOl , 9[ZF^kJl , ^[!Š ! ^[ ! !!!!!!!!!!!!!!!!!!!!!!!!!!!! DM!=B]Fk^>DCF<9>DCFl!oo!OX ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! =9=BHk^lk9l!o! , CS;DCM ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 8>LR_FN!o!+A@F ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 8AF B_! ! !!!!!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!! DM!CLH!8>LR_FNX ! !!!!!!!!!!!!!!!!!!!!!!!! QDGHLA9kZ^<9[l!o!=9=BHk^lk9l ! !!!!!!!!!!!!!!!!!!!!!!!! !QDGHLA9!DG!@GFN!HL!_FFS!HABR_!LM!LC>9!*42!SD^F>G! ! !!!!!!!!!!!!!!!!!!!!!!!! !

PAGE 181

OKg ! ! !!!!!!!! MLA!^!DC!H?N=ZABCTFZWDNHQ[[X ! !!!! !!!!!!!! MLA!9!DC!ABCTFZQFDTQH[X! ! !!!!!!!!!!!!!!!! DM!=B]Fk^<9l ! do!OX ! !!!!!!!!!!!!!!!!!!!! DM!CS;DGDCMZ=9=BHk^lk9l[X!!!!!!!!!!!!!!!! ! !!!!!!!!!!!!!!!!!!!!!!!! =9=BHk^lk9l!o!MDCNÂŒGQLAFGHÂŒSBHQZTABSQ