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Data Mining: Concepts and Techniques Jiawei Han and Micheline Kamber Simon Fraser University Note: This manuscript is based on a forthcoming book by Jiawei Han and Micheline Kamber, c 2000 c Morgan Kaufmann Publishers All rights reserved Preface Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades Contributing factors include the widespread use of bar codes for most commercial products, the computerization of many business, scienti c and government transactions and managements, and advances in data collection tools ranging from scanned texture and image platforms, to on-line instrumentation in manufacturing and shopping, and to satellite remote sensing systems In addition, popular use of the World Wide Web as a global information system has ooded us with a tremendous amount of data and information This explosive growth in stored data has generated an urgent need for new techniques and automated tools that can intelligently assist us in transforming the vast amounts of data into useful information and knowledge This book explores the concepts and techniques of data mining, a promising and ourishing frontier in database systems and new database applications Data mining, also popularly referred to as knowledge discovery in databases KDD, is the automated or convenient extraction of patterns representing knowledge implicitly stored in large databases, data warehouses, and other massive information repositories Data mining is a multidisciplinary eld, drawing work from areas including database technology, arti cial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing, and data visualization We present the material in this book from a database perspective That is, we focus on issues relating to the feasibility, usefulness, e ciency, and scalability of techniques for the discovery of patterns hidden in large databases As a result, this book is not intended as an introduction to database systems, machine learning, or statistics, etc., although we provide the background necessary in these areas in order to facilitate the reader's comprehension of their respective roles in data mining Rather, the book is a comprehensive introduction to data mining, presented with database issues in focus It should be useful for computing science students, application developers, and business professionals, as well as researchers involved in any of the disciplines listed above Data mining emerged during the late 1980's, has made great strides during the 1990's, and is expected to continue to ourish into the new millennium This book presents an overall picture of the eld from a database researcher's point of view, introducing interesting data mining techniques and systems, and discussing applications and research directions An important motivation for writing this book was the need to build an organized framework for the study of data mining | a challenging task owing to the extensive multidisciplinary nature of this fast developing eld We hope that this book will encourage people with di erent backgrounds and experiences to exchange their views regarding data mining so as to contribute towards the further promotion and shaping of this exciting and dynamic eld To the teacher This book is designed to give a broad, yet in depth overview of the eld of data mining You will nd it useful for teaching a course on data mining at an advanced undergraduate level, or the rst-year graduate level In addition, individual chapters may be included as material for courses on selected topics in database systems or in arti cial intelligence We have tried to make the chapters as self-contained as possible For a course taught at the undergraduate level, you might use chapters to as the core course material Remaining class material may be selected from among the more advanced topics described in chapters and 10 For a graduate level course, you may choose to cover the entire book in one semester Each chapter ends with a set of exercises, suitable as assigned homework The exercises are either short questions i ii that test basic mastery of the material covered, or longer questions which require analytical thinking To the student We hope that this textbook will spark your interest in the fresh, yet evolving eld of data mining We have attempted to present the material in a clear manner, with careful explanation of the topics covered Each chapter ends with a summary describing the main points We have included many gures and illustrations throughout the text in order to make the book more enjoyable and reader-friendly" Although this book was designed as a textbook, we have tried to organize it so that it will also be useful to you as a reference book or handbook, should you later decide to pursue a career in data mining What you need to know in order to read this book? You should have some knowledge of the concepts and terminology associated with database systems However, we try to provide enough background of the basics in database technology, so that if your memory is a bit rusty, you will not have trouble following the discussions in the book You should have some knowledge of database querying, although knowledge of any speci c query language is not required You should have some programming experience In particular, you should be able to read pseudo-code, and understand simple data structures such as multidimensional arrays It will be helpful to have some preliminary background in statistics, machine learning, or pattern recognition However, we will familiarize you with the basic concepts of these areas that are relevant to data mining from a database perspective To the professional This book was designed to cover a broad range of topics in the eld of data mining As a result, it is a good handbook on the subject Because each chapter is designed to be as stand-alone as possible, you can focus on the topics that most interest you Much of the book is suited to applications programmers or information service managers like yourself who wish to learn about the key ideas of data mining on their own The techniques and algorithms presented are of practical utility Rather than selecting algorithms that perform well on small toy" databases, the algorithms described in the book are geared for the discovery of data patterns hidden in large, real databases In Chapter 10, we brie y discuss data mining systems in commercial use, as well as promising research prototypes Each algorithm presented in the book is illustrated in pseudo-code The pseudocode is similar to the C programming language, yet is designed so that it should be easy to follow by programmers unfamiliar with C or C++ If you wish to implement any of the algorithms, you should nd the translation of our pseudo-code into the programming language of your choice to be a fairly straightforward task Organization of the book The book is organized as follows Chapter provides an introduction to the multidisciplinary eld of data mining It discusses the evolutionary path of database technology which led up to the need for data mining, and the importance of its application potential The basic architecture of data mining systems is described, and a brief introduction to the concepts of database systems and data warehouses is given A detailed classi cation of data mining tasks is presented, based on the di erent kinds of knowledge to be mined A classi cation of data mining systems is presented, and major challenges in the eld are discussed Chapter is an introduction to data warehouses and OLAP On-Line Analytical Processing Topics include the concept of data warehouses and multidimensional databases, the construction of data cubes, the implementation of on-line analytical processing, and the relationship between data warehousing and data mining Chapter describes techniques for preprocessing the data prior to mining Methods of data cleaning, data integration and transformation, and data reduction are discussed, including the use of concept hierarchies for dynamic and static discretization The automatic generation of concept hierarchies is also described iii Chapter introduces the primitives of data mining which de ne the speci cation of a data mining task It describes a data mining query language DMQL, and provides examples of data mining queries Other topics include the construction of graphical user interfaces, and the speci cation and manipulation of concept hierarchies Chapter describes techniques for concept description, including characterization and discrimination An attribute-oriented generalization technique is introduced, as well as its di erent implementations including a generalized relation technique and a multidimensional data cube technique Several forms of knowledge presentation and visualization are illustrated Relevance analysis is discussed Methods for class comparison at multiple abstraction levels, and methods for the extraction of characteristic rules and discriminant rules with interestingness measurements are presented In addition, statistical measures for descriptive mining are discussed Chapter presents methods for mining association rules in transaction databases as well as relational databases and data warehouses It includes a classi cation of association rules, a presentation of the basic Apriori algorithm and its variations, and techniques for mining multiple-level association rules, multidimensional association rules, quantitative association rules, and correlation rules Strategies for nding interesting rules by constraint-based mining and the use of interestingness measures to focus the rule search are also described Chapter describes methods for data classi cation and predictive modeling Major methods of classi cation and prediction are explained, including decision tree induction, Bayesian classi cation, the neural network technique of backpropagation, k-nearest neighbor classi ers, case-based reasoning, genetic algorithms, rough set theory, and fuzzy set approaches Association-based classi cation, which applies association rule mining to the problem of classi cation, is presented Methods of regression are introduced, and issues regarding classi er accuracy are discussed Chapter describes methods of clustering analysis It rst introduces the concept of data clustering and then presents several major data clustering approaches, including partition-based clustering, hierarchical clustering, and model-based clustering Methods for clustering continuous data, discrete data, and data in multidimensional data cubes are presented The scalability of clustering algorithms is discussed in detail Chapter discusses methods for data mining in advanced database systems It includes data mining in objectoriented databases, spatial databases, text databases, multimedia databases, active databases, temporal databases, heterogeneous and legacy databases, and resource and knowledge discovery in the Internet information base Finally, in Chapter 10, we summarize the concepts presented in this book and discuss applications of data mining and some challenging research issues Errors It is likely that this book may contain typos, errors, or omissions If you notice any errors, have suggestions regarding additional exercises or have other constructive criticism, we would be very happy to hear from you We welcome and appreciate your suggestions You can send your comments to: Data Mining: Concept and Techniques Intelligent Database Systems Research Laboratory Simon Fraser University, Burnaby, British Columbia Canada V5A 1S6 Fax: 604 291-3045 Alternatively, you can use electronic mails to submit bug reports, request a list of known errors, or make constructive suggestions To receive instructions, send email to with Subject: help" in the message header We regret that we cannot personally respond to all e-mails The errata of the book and other updated information related to the book can be found by referencing the Web address: http: db.cs.sfu.ca Book dk@cs.sfu.ca Acknowledgements We would like to express our sincere thanks to all the members of the data mining research group who have been working with us at Simon Fraser University on data mining related research, and to all the members of the system development team, who have been working on an exciting data mining project, , and have made it a real success The data mining research team currently consists of the following active members: Julia Gitline, DBMiner DBMiner iv Kan Hu, Jean Hou, Pei Jian, Micheline Kamber, Eddie Kim, Jin Li, Xuebin Lu, Behzad Mortazav-Asl, Helen Pinto, Yiwen Yin, Zhaoxia Wang, and Hua Zhu The development team currently consists of the following active members: Kan Hu, Behzad Mortazav-Asl, and Hua Zhu, and some partime workers from the data mining research team We are also grateful to Helen Pinto, Hua Zhu, and Lara Winstone for their help with some of the gures in this book More acknowledgements will be given at the nal stage of the writing DBMiner Contents Introduction 1.1 What motivated data mining? Why is it important? 1.2 So, what is data mining? 1.3 Data mining | on what kind of data? 1.3.1 Relational databases 1.3.2 Data warehouses 1.3.3 Transactional databases 1.3.4 Advanced database systems and advanced database applications 1.4 Data mining functionalities | what kinds of patterns can be mined? 1.4.1 Concept class description: characterization and discrimination 1.4.2 Association analysis 1.4.3 Classi cation and prediction 1.4.4 Clustering analysis 1.4.5 Evolution and deviation analysis 1.5 Are all of the patterns interesting? 1.6 A classi cation of data mining systems 1.7 Major issues in data mining 1.8 Summary 3 11 12 13 13 13 14 15 16 16 17 18 19 21 CONTENTS c J Han and M Kamber, 1998, DRAFT!! DO NOT COPY!! DO NOT DISTRIBUTE!! September 7, 1999 Chapter Introduction This book is an introduction to what has come to be known as data mining and knowledge discovery in databases The material in this book is presented from a database perspective, where emphasis is placed on basic data mining concepts and techniques for uncovering interesting data patterns hidden in large data sets The implementation methods discussed are particularly oriented towards the development of scalable and e cient data mining tools In this chapter, you will learn how data mining is part of the natural evolution of database technology, why data mining is important, and how it is de ned You will learn about the general architecture of data mining systems, as well as gain insight into the kinds of data on which mining can be performed, the types of patterns that can be found, and how to tell which patterns represent useful knowledge In addition to studying a classi cation of data mining systems, you will read about challenging research issues for building data mining tools of the future 1.1 What motivated data mining? Why is it important? Necessity is the mother of invention | English proverb The major reason that data mining has attracted a great deal of attention in information industry in recent years is due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge The information and knowledge gained can be used for applications ranging from business management, production control, and market analysis, to engineering design and science exploration Data mining can be viewed as a result of the natural evolution of information technology An evolutionary path has been witnessed in the database industry in the development of the following functionalities Figure 1.1: data collection and database creation, data management including data storage and retrieval, and database transaction processing, and data analysis and understanding involving data warehousing and data mining For instance, the early development of data collection and database creation mechanisms served as a prerequisite for later development of e ective mechanisms for data storage and retrieval, and query and transaction processing With numerous database systems o ering query and transaction processing as common practice, data analysis and understanding has naturally become the next target Since the 1960's, database and information technology has been evolving systematically from primitive le processing systems to sophisticated and powerful databases systems The research and development in database systems since the 1970's has led to the development of relational database systems where data are stored in relational table structures; see Section 1.3.1, data modeling tools, and indexing and data organization techniques In addition, users gained convenient and exible data access through query languages, query processing, and user interfaces E cient methods for on-line transaction processing OLTP, where a query is viewed as a read-only transaction, have contributed substantially to the evolution and wide acceptance of relational technology as a major tool for e cient storage, retrieval, and management of large amounts of data Database technology since the mid-1980s has been characterized by the popular adoption of relational technology and an upsurge of research and development activities on new and powerful database systems These employ ad3 CHAPTER INTRODUCTION Data collection and database creation (1960’s and earlier) - primitive file processing Database management systems (1970’s) - network and relational database systems - data modeling tools - indexing and data organization techniques - query languages and query processing - user interfaces - optimization methods - on-line transactional processing (OLTP) Advanced databases systems (mid-1980’s - present) Data warehousing and data mining (late-1980’s - present) - advanced data models: extended-relational, objectoriented, object-relational - application-oriented: spatial, temporal, multimedia, active, scientific, knowledge-bases, World Wide Web - data warehouse and OLAP technology - data mining and knowledge discovery New generation of information systems (2000 - ) Figure 1.1: The evolution of database technology 1.1 WHAT MOTIVATED DATA MINING? WHY IS IT IMPORTANT? How can I analyze ??? this data? ??? Figure 1.2: We are data rich, but information poor vanced data models such as extended-relational, object-oriented, object-relational, and deductive models Applicationoriented database systems, including spatial, temporal, multimedia, active, and scienti c databases, knowledge bases, and o ce information bases, have ourished Issues related to the distribution, diversi cation, and sharing of data have been studied extensively Heterogeneous database systems and Internet-based global information systems such as the World-Wide Web WWW also emerged and play a vital role in the information industry The steady and amazing progress of computer hardware technology in the past three decades has led to powerful, a ordable, and large supplies of computers, data collection equipment, and storage media This technology provides a great boost to the database and information industry, and makes a huge number of databases and information repositories available for transaction management, information retrieval, and data analysis Data can now be stored in many di erent types of databases One database architecture that has recently emerged is the data warehouse Section 1.3.2, a repository of multiple heterogeneous data sources, organized under a uni ed schema at a single site in order to facilitate management decision making Data warehouse technology includes data cleansing, data integration, and On-Line Analytical Processing OLAP, that is, analysis techniques with functionalities such as summarization, consolidation and aggregation, as well as the ability to view information at di erent angles Although OLAP tools support multidimensional analysis and decision making, additional data analysis tools are required for in-depth analysis, such as data classi cation, clustering, and the characterization of data changes over time The abundance of data, coupled with the need for powerful data analysis tools, has been described as a data rich but information poor" situation The fast-growing, tremendous amount of data, collected and stored in large and numerous databases, has far exceeded our human ability for comprehension without powerful tools Figure 1.2 As a result, data collected in large databases become data tombs" | data archives that are seldom revisited Consequently, important decisions are often made based not on the information-rich data stored in databases but rather on a decision maker's intuition, simply because the decision maker does not have the tools to extract the valuable knowledge embedded in the vast amounts of data In addition, consider current expert system technologies, which typically rely on users or domain experts to manually input knowledge into knowledge bases Unfortunately, this procedure is prone to biases and errors, and is extremely time-consuming and costly Data mining tools which perform data analysis may uncover important data patterns, contributing greatly to business strategies, knowledge bases, and scienti c and medical research The widening gap between data and information calls for a systematic development of data mining tools which will turn data tombs into golden nuggets" of knowledge BIBLIOGRAPHY 45 85 R S Michalski, J G Carbonell, and T M Mitchell Machine Learning, An Arti cial Intelligence Approach, Vol Morgan Kaufmann, 1983 86 R S Michalski, J G Carbonell, and T M Mitchell Machine Learning, An Arti cial Intelligence Approach, Vol Morgan Kaufmann, 1986 87 R S Michalski and G Tecuci Machine Learning, A Multistrategy Approach, Vol Morgan Kaufmann, 1994 88 D Michie, D J Spiegelhalter, and C C Taylor Machine Learning, Neural and Statistical Classi cation Ellis Horwood, 1994 89 J Mingers An empirical comparison of pruning methods for decision-tree induction Machine Learning, 4:227 243, 1989 90 M Mitchell An Introduction to Genetic Algorithms MIT Press, 1996 91 T M Mitchell Machine Learning McGraw Hill, 1997 92 D Mitchie, D J Spiegelhalter, and C C Taylor Machine Learning, Neural and Statistical Classi cation New York: Ellis Horwood, 1994 93 R Mooney, J Shavlik, G Towell, and A Grove An experimental comparison of symbolic and connectionist learning algorithms In Proc 11th Int Joint Conf on Arti cial Intelligence IJCAI'89, pages 775 787, Detroit, MI, Aug 1989 94 S K Murthy Automatic construction of decision trees from data: A multi-disciplinary survey Data Mining and Knowledge Discovery, 2:345 389, 1998 95 J Neter, M H Kutner, C J Nachtsheim, and L Wasserman Applied Linear Statistical Models, 4th ed Irwin: Chicago, 1996 96 T Niblett and I Bratko Learning decision rules in noisy domains In M A Bramer, editor, Expert Systems '86: Research and Development in Expert Systems III, pages 25 34 British Computer Society Specialist Group on Expert Systems, Dec 1986 97 Z Pawlak Rough sets Intl J Computer and Information Sciences, 11:341 356, 1982 98 Z Pawlak On learning - rough set approach In Lecture Notes 208, pages 197 227, New York: Springer-Verlag, 1986 99 Z Pawlak Rough Sets, Theoretical Aspects of Reasonign about Data Boston: Kluwer, 1991 100 J Pearl Probabilistic Reasoning in Intelligent Systems Palo Alto, CA: Morgan Kau man, 1988 101 W H Press, S A Teukolsky, V T Vetterling, and B P Flannery Numerical Recipes in C, The Art of Scienti c Computing Cambridge, MA: Cambridge University Press, 1996 102 D Pyle Data Preparation for Data Mining Morgan Kaufmann, 1999 103 J R Quinlan The e ect of noise on concept learning In Michalski et al., editor, Machine Learning: An Arti cial Intelligence Approach, Vol 2, pages 149 166 Morgan Kaufmann, 1986 104 J R Quinlan Induction of decision trees Machine Learning, 1:81 106, 1986 105 J R Quinlan Simplifying decision trees Internation Journal of Man-Machine Studies, 27:221 234, 1987 106 J R Quinlan An empirical comparison of genetic and decision-tree classi ers In Proc 5th Intl Conf Machine Learning, pages 135 141, San Mateo, CA: Morgan Kaufmann, 1988 107 J R Quinlan Learning logic de nitions from relations Machine Learning, 5:139 166, 1990 108 J R Quinlan C4.5: Programs for Machine Learning Morgan Kaufmann, 1993 46 BIBLIOGRAPHY 109 J R Quinlan Bagging, boosting, and C4.5 In Proc 13th Natl Conf on Arti cial Intelligence AAAI'96, volume 1, pages 725 730, Portland, OR, Aug 1996 110 J R Quinlan and R L Rivest Inferring decision trees using the minimum description length principle Information and Computation, 80:227 248, March 1989 111 R Rastogi and K Shim Public: A decision tree classifer that integrates building and pruning In Proc 1998 Int Conf Very Large Data Bases, pages 404 415, New York, NY, August 1998 112 C Riesbeck and R Schank Inside Case-Based Reasoning Hillsdale, NJ: Lawrence Erlbaum, 1989 113 B D Ripley Pattern Recognition and Neural Networks Cambridge: Cambridge University Press, 1996 114 S Romanski Operations on families of sets for exhaustive search, given a monotonic function In Proc 3rd Intl Conf on Data and Knowledge Bases, C Beeri et al eds.,, pages 310 322, Jerusalem, Israel, 1988 115 D E Rumelhart, G E Hinton, and R J Williams Learning internal representations by error propagation In D E Rumelhart J L McClelland, editor, Parallel Distributed Processing Cambridge, MA: MIT Press, 1986 116 D E Rumelhart and J L McClelland Parallel Distributed Processing Cambridge, MA: MIT Press, 1986 117 S Russell, J Binder, D Koller, and K Kanazawa Local learning in probabilistic networks with hidden variables In Proc 14th Joint Int Conf on Arti cial Intelligence IJCAI'95, volume 2, pages 1146 1152, Montreal, Canada, Aug 1995 118 S Russell and P Norvig Arti cial Intelligence: A Modern Approach Prentice-Hall, 1995 119 K Saito and R Nakano Medical diagnostic expert system based on PDP model In Proc IEEE International Conf on Neural Networks, volume 1, pages 225 262, San Mateo, CA, 1988 120 J C Schlimmer and D Fisher A case study of incremental concept induction In Proc 5th Natl Conf Arti cial Intelligence, pages 496 501, Phildelphia, PA: Morgan Kaufmann, 1986 121 J Shafer, R Agrawal, and M Mehta SPRINT: A scalable parallel classi er for data mining In Proc 1996 Int Conf Very Large Data Bases, pages 544 555, Bombay, India, Sept 1996 122 J W Shavlik, R J Mooney, and G G Towell Symbolic and neural learning algorithms: An experimental comparison Machine Learning, 6:111 144, 1991 123 J.W Shavlik and T.G Dietterich Readings in Machine Learning Morgan Kaufmann, 1990 124 A Skowron, L Polowski, and J Komorowski Learning tolerance relations by boolean descriptors: Automatic feature extraction from data tables In Proc 4th Intl Workshop on Rough Sets, Fuzzy Sets, and Machine Discovery, S Tsumoto et al eds., pages 11 17, University of Tokyo, 1996 125 A Skowron and C Rauszer The discernibility matrices and functions in information systems In R Slowinski, editor, Intelligent Decision Support, Handbook of Applications and Advances of the Rough Set Theory, pages 331 362 Boston: Kluwer, 1992 126 P Smyth and R.M Goodman Rule induction using information theory In G Piatetsky-Shapiro and W J Frawley, editors, Knowledge Discovery in Databases, pages 159 176 AAAI MIT Press, 1991 127 M Stone Cross-validatory choice and assessment of statistical predictions Journal of the Royal Statistical Society, 36:111 147, 1974 128 R Swiniarski Rough sets and principal component analysis and their applications in feature extraction and seletion, data model building and classi cation In S Pal A Skowron, editor, Fuzzy Sets, Rough Sets and Decision Making Processes New York: Springer-Verlag, 1998 129 K Sycara, R Guttal, J Koning, S Narasimhan, and D Navinchandra CADET: A case-based synthesis tool for engineering design Int Journal of Expert Systems, 4:157 188, 1992 BIBLIOGRAPHY 47 130 S B Thrun et al The monk's problems: A performance comparison of di erent learning algorithms In Technical Report CMU-CS-91-197, Department of Computer Science, Carnegie Mellon Univ., Pittsburgh, PA, 1991 131 G G Towell and J W Shavlik Extracting re ned rules from knowledge-based neural networks Machine Learning, 13:71 101, Oct 1993 132 P E Utgo An incremental ID3 In Proc Fifth Int Conf Machine Learning, pages 107 120, San Mateo, California, 1988 133 R Uthurusamy, U M Fayyad, and S Spangler Learning useful rules from inconclusive data In G PiatetskyShapiro and W J Frawley, editors, Knowledge Discovery in Databases, pages 141 157 AAAI MIT Press, 1991 134 S M Weiss and N Indurkhya Predictive Data Mining Morgan Kaufmann, 1998 135 S M Weiss and I Kapouleas An empirical comparison of pattern recognition, neural nets, and machine learning classi cation methods In Proc 11th Int Joint Conf Arti cial Intelligence, pages 781 787, Detroit, MI, Aug 1989 136 S M Weiss and C A Kulikowski Computer Systems that Learn: Classi cation and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems Morgan Kaufman, 1991 137 B Widrow, D E Rumelhart, and M A Lehr Neural networks: Applications in industry, business and science Comm ACM, 37:93 105, 1994 138 K D Wilson Chemreg: Using case-based reasoning to support health and safety compliance in the chemical industry AI Magazine, 19:47 57, 1998 139 J York and D Madigan Markov chaine monte carlo methods for hierarchical bayesian expert systems In Cheesman and Oldford, pages 445 452, 1994 140 L A Zadeh Fuzzy sets Information and Control, 8:338 353, 1965 141 W Ziarko The discovery, analysis, and representation of data dependencies in databases In G PiatetskyShapiro W J Frawley, editor, Knowledge Discovery in Databases, pages 195 209 AAAI Press, 1991   ✁✄✂✆☎✞✝✟✂✆☎✡✠ ☛ ✫✭✍☞ ✯✬ ✌✏✮✆✎✒✑✔✓✖✰✲✕✘✗✚✱✴✳✶✙✚✵✸✛✢✷✯✹✻✜✣✺✽✌✥✤✦✼✯✾✭✑★✹✿✧✩✵✿✑ ❀✔❁❂✳✶❃✴✳✶✼❅❄✘✹✿✷❅✹❇❆❈✬❂✬❈✬❂✬✍✬❉✬✍✬✍✬✍✬❉✬✍✬✍✬❉✬✍✬❂✬✍✬❉✬✍✬✍✬❉✬✍✬✍✬✍✬❉✬✍✬❂✬❈✬❂✬✍✬✍✬❉✬✍✬✍✬❉✬✍✬✍✬❂✬❈✬❂✬✍✬❉✬✍✬✍✬✍✬ ✪ ❊ ✫✭✬ ❋❍●✸✭✫ ✬ ❄✘❋✭■❏✬❅✮ ❀★✹▲❑✶❱▲▼✒✷❅◆✣✹✿✹◗✳✶✷❅✵❖❲❙✳❉✷❅✷❅✼❳❃€✳✶❁✿✺❖✷❅✵◗✼❅✾✣✷❨❀★✹✿✹❩✵◗❀★✳❚❁✿❃❏✷❅❃✣◆❬❘❙✹✿✷❅✳❚❲❙❃❏✳✶✷❅✼❳✼❅✳✶❄✘❁◗✹✿✷❅✷❅✵✿✹❉✷❨❀✔✬✍✹✖❭✦✬✍❪❫✬❉❀❴✬✍✳✶✹✿✬✍✾✭✬❉❁✿✷❅❃✣✬✍❘✚✬❂✵✿✬✍✱✭❀❛✬❉❵❜✬✍✾❏✬✍✳✶✬❉✼❅✷❅✵✩✬✍❄❛✬✍❑❚▼❩✬✍✺❖✬❉✼❅✾✣✬✍✹✿✵◗✬❂❀★❁✿✬❈✷❅❃✣✬❂❘❝✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✬ ❯❞ ✭✫✭✫ ✬✬ ❋✭❋✭✬❡✬❡❋❊ ❢✩♥♦❃✘✷❅✵◗❃❏❀★✳✶❁✿❁◗❣❤❄❙✳❚✼❨❣❤✐✩✹❇✳❚✺✔❁✿✳✶✷❳✳✶✼❅❀✖❦✣◆❬✼❅❀★❣❤✹♣✳✶❁◗✷❥✬❂✳❚❦✣✬❈✼❅✬❂❀★✹❧✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✬ ♠q ✭✫✭✫ ✬✬ ❋✭❋✭✬✬❡❯❞ ②✸rs✳✶❑❤❁✿❲❬✷❳✳❚✷✯❦✣❃✴✼❅✳✶❀★✼✩✹❩t✶❑❤❑❚❁❖▼③◆✘❲❬✷❅❃❏✷❨④✣✳✶✼✩❀✖t✘◆✈✳✶✵✩❃❏❄✘◆❬■❏❁❖❀★✳✶✹✚✵✿✷❅✬❉❑❚✐✉✬✍✹❖✺★✬✍✳✶✬✍✼❅❀✖✬❉◆✈✬✍❣❤✳✶✬✍❁✿✷❳✬❉✳❚❦✣✬✍✼❅✬❂❀★✹✇✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✡✬ ✮✖⑤① ✫✭✫✭✬✬ ❯❊❍⑥❧⑩✢✳✶★✺◗❁ ✳❚✵✿✷❅✵✿✵✿❀★✷❅❘❜❑❜❑❤❃✣❁◗✷❅✷✯❃✣⑦❴❘❉✳✶✵✿❲❙✷❅❑❜❀✔❃⑧✵✿✱✣❑❚❑✣▼③◆✘❲❫✹✚✳★✬✍⑨❖❑❤✬✍❁✸✬❂✺❖✼❅✬❈✾✣✬❂✹✿✵◗✬✍❀★❁✿✬❉✷❅❃✣✬✍❘❬✬✍❲❙✬✍❀★✵◗✬❉✱✣✬✍❑✣◆✘✬✍✹❝✬❉✬✍✬✍✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✡✬✡✮✖✮❤❋✮ ✫✭✫✭✬✬ ❯✴❯✴❅✬❡✬ ❋✮ ❶✸⑩✢✳❚✼❳✳❚❁✿✹✿✵✿✹✿✷❅✵◗✷❳✺★✷✯❑❜✳❚❃✣✼❷✷❅■❏❃✣✳✶❘❉❁◗✵✿❲❬✷❅✵✿❀★✷❅✵✿❑❜✱✣❃✣❑✣✷❅❃✣◆✘❘❉✹❻❲❙✷❅❃❬❀✔✼❥✵✿✳❚✱✣❁✿❑✣❘❜◆✘❀❼✹❴◆✭❭✒✳✶❸❜✵❇✐✉✳❚❲❬❦❏✳✶❀✖✹◗✳✶❀★❃✭✹✖✹❹❭❽✳❚▼✥❁✿❃❏❑❤◆❫❲❾❸❜✐✉❸❜❲❬✐✩❲❙❀✖◆✘❀✖❑❜◆❺✷❥❑❤◆❺✷❳✹❝◆✘✹✒✬❉✵◗❑❙✬✍❶❻✬❂❿❷✬❈⑥❂✬❂➀s✬✍⑥❂✬✍r▲✬❉➁➂✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✡✬✡✮✖✮✖❋❞ ✫✭✬ ❞➄✫✭➃s✬ ✷✯❞✭❀✔✬❅❇❁ ✮ ✳✶❁❖✺◗✱✣⑥▲✷❳❘❤✺★❘❜✳✶✼❽✼✯❑❜❲❙❲❙❀★❀★✵◗❁❖✱✣✳✶❑✣✵◗✷✯◆✘❣❜✹❙❀✻✬✍✳✶❃❏✬✍◆❬✬❂◆✘✬❈✷❅❣✘✬❂✷✯✹◗✬✍✷❅❣❤✬❉❀✻✬✍✱✭✷✯✬✍❀✔❁❇✬✍✳✶✬❉❁❖✺◗✬✍✱✣✷❳✬✍✺★✳✶✬❉✼✢✬✍✺❖✼❅✬❂✾✣✹✿✬✍✵◗❀★✬❉❁✿✷❅✬✍❃✣❘✚✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✡✬✡✮✖✮✖♠♠ ✫✭✫✭✬✬ ❞✭❞✭✬❡✬❡❋❊ ♦♥❻❶ ❢✿➆▲➀❻➀✻❶❻➇❻➃❉❭✣❭✣❶✸♥✸✼❅✾✣✳✶✹◗✼❳✳❚✵✿❀★❃❏❁◗✺❖✷❅❀✖❃✣◆❬❘❙❢✩➆❻✵✿❀✔✹◗❁❇✷✯✳✶❃✭✵◗❘❙✷❅❣❤➀✻❀❛➇✢➀s■✣❀✖❁◗◆✘❀★✹✿✾❏❀✔✺❖❃➈✷❅❃✣✵❖✳✶❘❙✵◗✷✯✳❚❣❜❃❏❀★◆❙✹➉❶✸✬✍✼❅✾✣✬❉✹◗✵✿✬✍❀★✬✍❁◗✷❅❃✣✬❉❘✚✬✍✾✣✬✍✹✿✷❅✬✍❃✣❘❙✬❉✬✍➃s✬❂✷❅❀★❁❇✬❈✳❚✬❂❁❇✺◗✬✍✱✣✷❅✬✍❀★✹➅✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✡✬✡✮✖✮✖✫q ✫✭✬ ♠➄✫✭✫✭❱▲✬✬ ❀★❞✭♠✭❃✣✬✬❅❯✮ ✹◗✷❅✵✩❄❤❻❶❱✍✩✐ ❦❏➃s✸♥ ✳❚⑥❂➁✣✹✿❀✖❶✸❪€◆❫⑥❂➇♦✺❖r❈✼❅❿✦✾✣❭✶➇✒✹◗⑥✲✵✿➊✍❀★❁◗◆✘r❉✷✯❀★❃✭❭✭❃✣❘❙⑥➋✹◗✷❅❲❙✵✩✱✣❄❤❀✔✷❅✐✩✵✿❀★❦❏✱✣❁❇✳❚✳❚❑✣✹✿❁❇◆✘❀✖✺◗✹❙◆✚✱✣✷❳✺❖✬✍✺★✼❅✳❚✾✣✬✍✼③✹◗✬✍✵✿✺❖❀★✼❅✬❉✾✣❁◗✷❅✹◗✬✍❃✣✵✿❘✍❀★✬✍❁◗❲❙✷✯✬❉❃✭❀★❘⑧✬✍✵◗✱✣✬❂✳✶❑✣✼❅✬✍❘❜◆❉❑❤✬❉❦❏❁✿✷❅✬✍✳❚✵◗✹✿✱✣✬✍❀✖❲✡◆❈✬❉❑❤✾✣✬✍❃✚✹✿✬✍✷❅❃✣✺❖✬✍❑❜❘✚❃✣✬❉◆✘❃✣✬✍❄✘❀✖❃❏✺❖✬❂✵◗✳✶❀✖✬❈❲❬◆✚✬❂✷❳❁◗✺❻❀★✬✍❘❤❲❙✬✍✷❅❑❜❑✣✬❉❃✣◆✘✹✢✬✍❀✔✼✯➌❻✷❅✬✍❃✣✷✯✬❉✵◗❘ ✱❛✬✍✹◗✬✍✬✍✾✘➍⑧✬❂✬❂✺❖✬❈✬❈✷❅❀★✬❂✬❂❃✘✬✍✬✍✵✿✼❅❄❉✬❉✬❉✱✭✬✍✬✍✷✯✬✍❘❜✬✍✱ ✬✍✬✍✬➋✬➋❋✣❋❤⑤✮ ✫✭✫✭✬✬ ♠✭♠✭✬❡✬❡❋❊ ◆❺➊✍❱✍❀★⑩✢➇✒✣❃ ❻●▲r✹✿✷❅❢✿❶❻✵✩❶❻❄ ❿✦➁➎➆▲❭❏✬✍➇❻➊▲✬✍❭❏❁❇❶✸◆✘✬❉❀✔✼❅✬✍❁✿✾✣✷❅✹◗❃✣✬✍✵✿❘❙❀★✬❂❁◗⑩❽✷✯✬❈❃✭❑❤❘✚✬❂✷❅❃✘✬✍❦❏✵✿✳✶✹❻✬❉✹◗●✢❀✖✬✍◆❬❑➏✬✍❑❤❢✿✬✍◆✘❃€❀★✬❉❃✘◆✘✵✿✬✍❀★✷➐❃✣▼✏✬✍❄❬✹◗✷❅✬❉✵✩✵✿❄⑧✱✣✬✍❀❉◆✘✬❂✷❅❶✸✹✿✬✍✵◗✼❅✾✣❁✿✬❉✷❅✹✿❦✣✬✍✵◗✾✣❀★✬✍❁✿✵◗✷❅✷❅✬❉❃✣❑❤❃✚❘❙✬✍▼✥➁❺✬✍✾✣✵✿❃❏✬✍❁✿✾✴✺❖✬❉✵◗✺❖✷✯✵✿✬✍❑❜✾✣❃✣❁◗✬❂✹➑❀❾✬❈✬❂✬❂✬❂✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❂✬❂✬❂✬❈✬❈✬❈✬❂✬❂✬❂✬✍✬✍✬✍✬❉✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬✍✬✍✬✍✬➋✬➋✬➋❋✣❋❤❋❤❊❋✮ ✫✭✬ q➄✫✭➒✍✬ ❁◗q✭✷❳✬❅◆❜✮ ✐✉❦✴✳✶➁❺✹✿●❻❀❴◆⑧❢✿r✻✽✺ ✼✯✚➒ ✾✭✹✿❭✘✵✿⑥❧❀✔❁✿✷❅➁✘❃✣✵❖❘✚✳✶✵◗❲❙✷✯✹◗❀✔✵✿✷❳✵✿✺★✱✣✳❚❑✣✼❷◆✘❢✩✹➓❃✘▼✏❑❤✬❉❁◗❲⑧✬✍✳❚✬✍✵✿✷❅✬✍❑❤❃❙✬❉✬✍➒✍✬✍❁◗✷❳◆✚✬❉✬✍⑥✻■✭✬❂■✣✬✍❁✿❑✘✬❉✳❤✬✍✺◗✱➅✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬➋✬➋❋✶❋❤❯❞ ✫✭✫✭✬✬ q✭q✭✬❡✬❡❋❊ ✰➅❶❻❿➎✳❴❢✿❣❜→✍❀✖✸❶ ✻➆ ✼❅➇❻✾✣✹✿❭✴✵◗❶✸❀★❁✖✼✯✾✭❭✒✹✿❶✸✵✿❀✔✼❅✾✣❁✿✷❅✹◗❃✣✵✿❘✚❀★❁◗✱✣✷❅❃✣✷❅❘❤❘✚✱❺✾✣✐➣◆✘✹✿✷❅✷❅❃✣❲❬❘➏❀★➌❻❃✣✹✿✳❴✷❅❣❤❑❜❀★❃❏✼❅✳✶❀★✵❻✼✣✹◗✵◗■❏❁❇✳✶✳❤❃✭✺✽❀❂✹✩▼✏✬❉❑❜❁✿✬✍❲⑧✬✍✳❚✵✿✬❉✷❅❑❤✬✍❃➔✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬➋✬➋❋❤❋❤✫♠ ✫✭✫✭✬✬ ✫➄ ❫ ❪ ✣ ❑ ✘ ◆ ✔ ❀ ❨ ✼ ✩ ✐ ❏ ❦ ❚ ✳ ✿ ✹ ✖ ❀ ❫ ◆ ✺ ❖ ❅ ✼ ✣ ✾ ◗ ✹ ✿ ✵ ★ ❀ ◗ ❁ ✯ ✷ ✭ ❃ ❙ ❘ ❙ ❲ ✔ ❀ ✿ ✵ ✣ ✱ ✣ ❑ ✘ ◆ ↔ ✹ ✍ ✬ ✍ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ❂ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ✍ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ❂ ✬ ❈ ✬ ❂ ✬ ✍ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ✍ ✬ ❂ ✬ ❈ ✬ ❂ ✬ ✍ ✬ ❉ ✬ ✍ ✬ ✍ ✬ ✍ ✬ ➋ ✬ ❤ ❋ ① ①➄✫✭➊▲✬ ✾✣①✭✵◗✬❅✮✼✯✷❅❀★❁✻➁❺✳❚✵❇❃❏✳✶✳✶✵◗✼❅✷❅❄✘✹✿✵✿✹✿✷❳❅✷ ★✺ ✹€✳❚✼✦✬✍✳✶✬✍■✣✬❉■✭❁✿✬✍❑➈✳❜✬✍✺◗✬❂✱❙✬❈▼✥❑❤✬❂❁✸✬✍❑❤✾✣✬❉✵◗✬✍✼✯✷❅❀★✬✍❁✻✬✍◆❺❀★✬❉✵✿✬✍❀✖✺✽✬✍✵✿✷❅✬❉❑❤❃↕✬✍✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬➋✬➋❋❤❊❤①⑤ ✫✭✫✭✬✬ ①✭①✭✬❡✬❡❋❊ ❱▲❱▲✷❅❀★✹✿❣✘✵❖✷❳✳✶✳✶❃❏✵◗✺✽✷❅❑❤❖❀ ✘❃✐✉❦✴✐✩❦❏✳✶✹✿✳✶❀❴✹◗◆❫❀✖◆✚❑❤❑❜✾✣✾✣✵◗✼❅✵✿✷✯✼❅❀✔✷❅❁❹❀★❁✻◆✘◆✘❀✔✵✿❀✔❀✖✵✿✺❖❀✖✵◗✺❖✷❅✵◗❑❤✷❅❑❤❃ ❃❝✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬❂✬❂✬❈✬❈✬❂✬❂✬✍✬✍✬❉✬❉✬✍✬✍✬✍✬✍✬✍✬✍✬➋✬➋❊✣❊❤❋✮ ✫✭✬✯✮❴⑤➅➁✘✾✭❲❙❲⑧✳❚❁✿❄➙✬✍✬✍✬❉✍✬ ✬✍✬❉✬✍✬✍✬❂✬❈✬❂✬✍✬❉✬✍✬✍✬✍✬❉✬✍✬✍✬❉✬✍✬❂✬✍✬❉✬✍✬✍✬❉✬✍✬✍✬✍✬❉✬✍✬❂✬❈✬❂✬✍✬✍✬❉✬✍✬✍✬❉✬✍✬✍✬❂✬❈✬❂✬✍✬❉✬✍✬✍✬✍✬➋❊❤❊ ✮ ❋ ẽéééẹềểễếệìệẹỉỉếỉĩệìệẹỉỉếẹíịếềíòếỏsệệ ểõóõọồổỗổốốố ộ ờở ỡợớùũủúụừửúữứựùỳùừỷúủúỹ ýỵỵ ýỵỵ ỵýýỵỵ t tũ t tt t t ✵◗❜✷❅❑❤❀★❃❙✵✒❁✿■✴❀✔✳✶✹✿❀✖✵✿✵◗✳❚❀★❁❇❁✿✺◗❃✭✱✦✹✻t✴✳✶❀★✵❇❃❏✺❚◆✈✬❩✷✯♥♦❃✘✵◗❄❙❀★❁✿✺❖❀★✼❅✾✣✹◗✵✿✹✿✷❅✵◗❃✣❀★❘❙❁✿✷❅❃✣✺❖❑❜❘✴❁✿t✣❁◗❑❤❀★❃✭✼❳✳✶❀❂✵✿✷❅✺★❑❜✳❚❃✣❃❙✹❹✷❳✳❚◆✘❲❙❀★❃✘❑❜✵✿❃✣✷➐▼✏❘❉❄❙◆✣✺✽✳✶❁✿✵❖❑✶✳❛➌✻✳❚◆✘✵✿❀✖✵✿◆❬❁◗✷❅✳✶❦✣❃❏✾✣◆✈✵✿❀✔✹✿✹✖■❏✬✒✳❚❢✩❁✿❃❬✹◗❀❉❦✣✾✣❁✿❀★✹◗❘❜✷✯❃✭✷❅❑❤❀★❃✣✹✿✹❴✹❴t❏t✣✺❖✳✶✼❅❃❏✾✣◆✈✹◗✵✿✵✿❀★✱✣❁◗✷✯❀★❃✭❁◗❘✚❀❖▼✏❑❜❲⑧❁✿❀❤✳❴❄❉t✴◆✘✱✣✷❅❀✔✹❇✼✯✺❖■❬❑✶❣❜❲⑧❀★❁❩✳❚❁❑✶❤❣❜❀✔❀★✵✿❁❇❀★✳❚❁◗✼❅✹ ✼ ❦✣✷❅◆✘❃✣✷❅✷❅✹❇❑❤✹✿✷❅✺✽✼❅❘❜❑❜❑✶✱➈❣❤❘❤✵♦❀★❄✘❁✍t❤✷✯❃✘✷❅◆✘✵✻✵◗✷❅❑❛✹✿✺★✵✿✳❚✹◗✷❅❃€✵✿❃❏❁✿✺✽✾✴❦❏✵❻✺❖❀❈✵✿❘❤✾✣✾✣❁✿❁◗❑❜✹✿❀★✾✣❀✖✹✻◆■✣✷❅✹❻❃✣✵✿❑❙✷❅✱✭❃❙❀★◆✘❁✿✵◗❀★❀★✱✣❁◗❃✘❀★✷❅✵❻❣❤✷❅❁❂❀❉✷❅❃✚✺✽■✣✾✣■✴✼❳✹✿✳❚❑❤✵◗❃➈❑❤■✣✵✻❲❙✾✣✳❚✼❳❀✔✳❚❃❏❁❩✵✿◆❫✷❅❦❏❑❤✳✶✳❚❃✣❃✣✹✿✹❴❀★✷❅✬③❲❫✹✍❶✸✳✶✳✶✼❅❃❏✼✣✾✣◆❫✵❖✹◗✳❴✵✿❀★✺◗④✣✱❏❁◗❑❤✷❅✳❚❃✣❃✣❁❇❑❜❘❛✳❤❲❙✺✽❲❫✵✿✷❅❀★❀★✳❴❁◗✹❴❄❛✷✯t➈⑦✔✳✶✺★❀ ✼❅✳❚✹◗✺❖✵✿❑❉✾✭❀★❘❜✹✿✱✣✵✿❑❤❀★❑❜❁◗✼❅❲❙✷✯■❙⑦✔❀❛❀★✷❅❃❬❁❻❘❜❘❜✵✿❀★✱✣❁✿❃✣❑❜❀▲❀★✾✣✹▲✷❥■✣◆❺➌❻✹❻❀★✷✯❃✘❦❏✵◗✵✿✱❫✳❚✷ ✹✿✹✿❀✖✺★✷❅◆❬❲❙✳❚✵✿❑❤✷❅✷❅✼❳❑❤❃❫✳✶❃✚❁✢■✣❑❚▼✥✾✭✾✣▼ ❁❇❃❏✳✶✺◗✺❖✱❏❁◗✵◗❀✖✳✶✷✯✳✶✹◗❑❜✹✸✷❅❃❏❃✣❑✶✳✶❘✚▼✦✼❅✷❅■❏✵✩✹◗❄✘✷❅✳✶❲❙t➈✵◗✵✿✳❚✷❅❀★✼❳❃❏✳✶❁◗◆❬❃✣❁✢✹✖✼❳❘➈✬♦✳✶✳✶❃❏❢✩✷❅❃❃◆ ✾✣✱✣✹◗✷❅❘❤❀✚✱❙✷✯❃➷✳❴❣❜✳✶❀★❃➫❁❇✳❚❀✖❘❤✳❚❀✍❁✿✺❖✵✿✱➷✼❳✳✶✷❅❑❜❲➧❦✣✹✿✺❖❀✔❑❜❁✿✹✿❣❤✵❴✳✶t❏✵◗✳✶✷❅❑❤✹♦❃ ➌❩◆✣❀★✼❅✳❚✼❷✵❇✳✶✳❚✹✸❦❏✳✶✵✿✹◗✱✣❀❤❀▲t③✷❳✳❚◆✘❃❏❀★❃✘◆ ✵✿✷✷✯❃ ✺★✵✿✳❚✱✣✵✿❀✚✷❅❑❤❃✚✷❳◆✘❑❚❀★❃✘▼✦✵◗❘❤✷ ❁◗❷❑❤✺★✾✣✳✶■✣✵◗✷✯✹✸❑❜❑✶❃ ▼✦❑❚✱✭▼❩❑❤✾✣❘❤❁◗✹◗❑❤❀★✹❻✾✣■✭✷❅❃❙✹❉✳❛❑✶▼❩✺❖✷❅❲❬✵✩❄✚❑❤✵◗✳❤❑❤✺★❁✻✺✽❑❤✷❅❃✣❁❇◆❺✹◗✾✣✷✯❃✭❁❇❘❛✳❚❃❏✵◗✺❖❑❉❀✚✱✣■✴❑❤❑❤✾✭✼❅✹✿✷❳❀✍✺❖❄❫✵✩❄✘✱✣■❏❑❤❀❤✼❳◆✘t✘❀✔❣❤❁✿✳❚✹❉✼❅✾✣➌❻❀❤✷❅t❤✵✿✳❚✱➷❃❏◆✳ ▼✏❘❤✵✿✾✣✱✭❀✔❃✴❑❤❀ ❘❤✺❖✺◗✵✿❁❖✱❏✷❅✳✶❑❤✳❚■✣❃❽❁❇✱✭✳❤t ✷❥✺✽✺✔✺✽✵✿✼✯✳✶❀★✾✭✼✣❁◗✹✿✼❅✷✯✵✿❑✣✹◗❀✔✵✿✺★❁❼✷❳✳✶✺❖✵◗✳❚✹❉✷❅❃❏❑❤❑❚✳✶❃✦▼✒✼❅✬❷❄✘❀✖✹✿❢✩✳❤✵✢✷❅✺◗✹✻✱➷❲❫✺★✳❚✳❴✺❖✼❅❃€❄❼✾✣✳❚✹✿❦✴✵◗✼❅❀❛✹✿❀★❑✻❁✖✾✣t✦✱✭✹◗✳❚❀✖❀★❃❏◆➫✼❅■❙◆❫✳✶✺❖✵◗✹❂✼❳❑✚✳✶✳➏✹✿▼✏✹◗❑✣✹◗✷➐✵❇▼✏✺❖❄❉✳❚✾✣❃❏✹▲◆✘◆❜❑✣❑❤✐✿✺❖❃✳✶✾✣✼❅❑❤❲❙✳✈❃✣❀✔■❏❀❈❃➈✳✶✵✿✵◗❁◗❑✘✹✒✵✿❑❤✷❳❑❤✺❖✼❽❃➏✾✣✵✿✼❳✵✿❑❙✳❚✱✭❁❻❘✘❀❻✹✿✳✶✰✲❀★✷❅✵✍❃❫✰✲❑✶✷❅❃✣▼❻✰➑✹✿✺❖✷❅✼❅❘❤✾✣▼✏✱✘❑❜✹✿✵❻✵◗❁✢❀★✷❅✷✯❁✿❃✘❃❺✹▲✵✿▼✏❑❬❑❤▼✏❑❜❁◗✵✿❲⑧❁❻✱✣▼✏❀❛✳✶✾✣✵◗❁◗◆❺✷❅✵✿❑❤✷✯✱✣✹◗❃❂✵✿❀✔❁◗◆❺❁❼✷✯✷✯❦✭✹❖✳❚✾✣✺❖❃❏❑✶✵✿✳✶✷❅❣❤❑❤✼❅❀✔❄✘❃ ❁✿✹✿❄✘✷❅❑✶✹❴✬✦▼❩✬❻⑥▲◆✣⑥✻✹❩✳✶✼❅✵❖✳✍✵✿✳✣❀✔◆✣❁✿t✭❃❏✳✶✵✿✵❖✳❚❑❙✳✻✵✿✷❅❑❜❲❬❣❤❦✣❀★✹✿✷❅✼❅❃✣❀✔❄✘❁✿✷❅t✣❃✣❣❤✷❅❀❘✵ ❲⑧◆✘❀★✳❴✵◗❄➏❀✖✺❖✹✿✵◗❀✔❀✖❁✿◆ ❣❤❀✚✺✽✼✯✳✶✾✭✹✻✹✿✵✿✳❈❀✔❁✿■✣✹✖❁◗✬ ❀★■✣❁✿❑✣✺❖❀✔✹✿✹✿✷❅❃✣❘❫✹◗✵✿❀★■❫▼✥❑❤❁❻❑❤✵◗✱✣❀★❁✻✳❚✼✯❘❜❑❤❁◗✷✯✵◗✱✣❲❙✹❴t❤✹◗✾❏✺◗✱€✳✶✹✻✺❖✼❳✳✶✹◗✹✿✷ ✺★✳❚✵✿✷❅❑❤❃€✳❚❃❏◆❫✺✿✱✴✳✶❁❇✳❜✺❖✵✿❀✔❁✿✷❅⑦✖✳✶✵◗✷❅❑❤❃✦t✭❑❤■✴❀★❁❇✳❚✵✿✷❅❃✣❘✚❑❤❃❫✵◗✱✣❀ ■❏❲⑧✳❚✳❜■❏✺◗❱✍❀★✱✣❁◗✳✶✷❅✹❙❃✣✵❖❀✻✳❉✹❖✺★✼❅✺❖✳✶❀✖✼❅✵◗✳❚✾✣✵✿❁✿✹◗❀★❃✣✵✿❁◗❀★✷❅❀✖❃✣❁◗◆✲✷✯❘✴❃✭t❤❘❛✷❅❃ù✹◗■❏✷❅✹❻✳✶❲⑧✵◗✳✍✷❥✳✶✳❚❄❤❃✘✼✦❑❜❄➷◆✣✾✣✳✶❃✣✺❖❑❤✵❖❘❉✳✶❃❺✹❖❦❏▼✏✺❖❀★✳❚✷❅❁✿✹✿❀★❀✔❀❤❃✘❃❏t✭✵✿✺❖✷❦✣❀➫✷❅✺✍❑❤■✣✼❅◆✘❑❤❁✿❑✣✷❅❘❜✹❇✺❖❄➈✺❖❀★t❚✷❅❀❴■✣❲⑧◆✘✼❅✷❅✷❅✳✶❃✣❃✣❁ ❀❻❘❤❤✹❫✾✣❀★✵◗❃✴✳✶✷❅❃✣◆✘❃❏❀★❘❏◆ù❁❻t✘✳✶❣✘■✴❃❏✷❅❀★❘❤◆✈❁✿❑❤✷❅❑✣❁◗✹✿❑❤❑✚◆✘✾✣✷❳❑❜✺★✹✸✳✶❃✦◆✘✼❅t✘✹❴❀★➌❻t✒❣❤❲❙❀✔✷❅✵✿✼✯✱€❑❜❑❜■✣✹✿◆✘✵◗❲❙✼✯✷ ❄➫❀✔❀✔❃➈✷❅❁✿✵❴❃ ❀★✬✦❃✘✵✿●❻✵❻✱✣✱✭❀★❀ ❲❬❀★❁✿❏❀❉■✣❀★✱❏✼❳✳✶◆✘✳✶❁◗✹✚✹◗❀❂❀★❑❚✳❈✹✻▼❼✳✶✼❳✳✶◆✣❃✴❁✿✳❚◆⑧❘❜✵❇❀❻✳➫◆❺❃✘✷ ❷❲❬✾✣❀★❲✚✷✯❁◗❃✭❀★❦❏✷✯❃✘❃✭❀✔✵❻❁✒❘❏✵✿t❽❑✶❀✖▼✦✹✿✺◗✵❇✱✣❁◗✳❚❀★❃✣✵✿✹✿✷❳✷❅❀✖❵❜✹✿✳❚✵◗✾✣✷❳❁❇❀★✺❖✺◗✹❴✹✖✱ ✬t ✷❅➊▲❃€➌❻◆✣✷❅⑥▲✳✶❃✣✵❖✹⑧❘❛✳❉✵◗✳➫❲❬❑❉❦✣✷✯✵✿❃✭❁❖✱✭✳✶✷✯❀✻❃✭❃❏❘❉✱✘✺◗✱↕✾✣❁✿❘❤❀★❑✶❀✍✹◗❀✖▼❉✳✶✳✶✹✿❲❬❁❖✵❖✺◗✳✶❑❤✱✦✵✿✾✣✬ ✷❅❃✘✹◗✵✿✵✿✷❳✹✢✺❖✹✖❑❚t✍▼ ◆✣✺❖✼❅✳❚✾✣✵❇✹◗✳❉✵✿❀★✺❖❁€❑❜✼❅✳✶✼✯❀❴❃✴✺❖✳✶✵✿✼❅❀✖❄✘◆✈✹✿✷❅✷❅✹✚❃⑧✱❏◆✣✳✶✳❚✹❬✵❇✳✶❦❏❦✴❀✔✳✶❀★✹✿❃✇❀✔✹✖✹◗t✣✵✿✺❖✾❏✼❅✾✣◆❺✹◗✷✯❀❴✵✿❀★◆ ❁✻❀❖✳❚④✣❃❏✵✿✳✶❀★✼❅❃✭❄✘✹✿✹✿✷❅✷❅❣❤✹✒❀★✱❏✼❅❄ù✳❚✹✒▼✏❑❜❁✿❀❴❁❙✺❖❀★❲⑧❃✘✳❚✵✿✼❅❃✘❄❙❄➷❦✴❄❤❀✖❀✖✺❖✳❚❑❜❁✿❲❙✹✖t❹❀✍▼✏✳✍❑✣✺❖✱✣✾✣✷❅❘❤✹✿✹◗✱✣✷❅✼❅❃✣❄✚❘➅✳❤❲❫✺❖✵◗✷❅✳✶❣❤✷❅❀❻❃✣✼❅✵✿❄ ❑❜■✣❑❜✷❳❃ ✺ ◆✘✳✶✼❅✷❅✹◗✹✿❑✚✵❖✳✶❦❏❃❏❀★✺✽❀✔❀❖❃€✐✉❦✴❦✣✳✶✹✿✾✣❀❴✷❅◆⑧✼❅✵❩✺✽✷❅❃❬✼✯✾✭✹✿❲⑧✵✿❀✔✳✶❁✻❃✘❄➏✳✶❃❏✹✿✳❚✵❖✼✯✳✶❄✘✵✿✹◗✷❅✹◗✷✯✹❴✵✿✬✦✷❳✺★❶✸✳✶✼✢✼❅✾✣✳✶✹✿❃❏✵◗✳❚❀★❁✻✼❅❄➈✳✶✹◗❃✴✷❅✹❩✳✶✹◗✼❅❄✘❑✶✹✿▼✏✵✩✷❅✹✢➌❻✵✿✳✶❑✘❁◗❑❤❀❂✼❅✹✒■✴✳❤❦❏✺ ✳❚❤✹✿✳✶❀✖❘❜◆✈❀★❑❤✹❻❃❙❑❤❁❻❸❜✐✩✹◗❲❙❄➈✹◗❀❴✵✿✳✶❀★❃✣❲❬✹❴✹✖t➈t✘❸❜✹◗✐✩✾❏❲❙✺◗✱❀❴◆✘✳✶❑❤✹✻✷❳◆✘➁❜✹❴✐✿t ⑩✢✳❚✼❅❃❏✾✣◆✚✹❴t✣✹◗➁✣❀★❣❤⑩✒❀✔➁✣❁❇➁❷✳✶✼✴t✴❑❤✳✶✵◗❃❏✱✣◆❫❀★❁✸➁✘⑥✍❲❙➁❷❀★✵◗✬ ✱✣❑✣◆✘✹✒✱❏✳❴❣❜❀ ◆✘❑✘✤ ❀★❢✩✹➏❃➷❃✣❲❫❑❤✑✔✕✘✵❈✳❤✗ ❁✿✺◗✘❀★✱✣✜✣✼❅✷❅❄➫✓✖❃✣✧ t t ỵ ý ✷✯✹❈t✣✬✚❁✿✳❬❀✖➆s✳❚❘❤❃✣✹✿❁◗❑❤❑❤✼❅✷❃❽✾✣❜t✢■➷❀❙✷✯✵✍✺❖❑❚✼❳▼❹✷❅✳✶✹❛❑❜✹◗✹✿❦❤✳❬✷ ⑨❖❀✖▼✥✺★❑❤✺❖✳❚✵◗❁✿✵✿✹✍❲ ✷❅❑❤▼✏❃✦❑❤❑✶❁◗t✢▼ ❲❙✺❖✌✏✼❅✕✘✹❉✾✣✜✣✹◗✳❫✗✶✵✿❀★✛✢✺❖❁◗✼❳✧✥✷✯✳✶✛ ❃✭✹◗❘ ✹ ❑❤❘❤❃✭❀✔❑❤✼✯❄❫❲❙✷➐❀✔▼✒✵✿❁✿✷❅✵✻✷❳✺✍✷❅✹❂◆✘✷❅◆✘✹✿✵❖❀✔✳✶✹❇✺❖❃❏❁◗✺✽✷✯❀❤❦✴✬✻✳✶❦✣❶✸✼❅❑❤❀➏❃✴❦➈✺❖❄€❀★■✣✳❬✵◗✾❏✺❖✳✶❑❤✼✒❃❏✺❖✺✽✼❅❀★✾✣■✣✹◗✵✖✵✿✬✍❀★❁◗●❻✷✯❃✭✱✭❘⑧✷✯✹✍✺❖◆✘❑❜❃✣✷ ✹✿❀✔✷❅✹✿❁✿✵◗✹▲✹✍▼✏❑✶❁✿❑❜▼✒❲ ✵✩➌❩✺❖❑❙❑❤❃✘✺✽❑❤❣❜❲❙❀★❃✘■✴✵✿❑❤✷❅❑❤❃✭❃❏❀★✳❚❃✘✼③✵✿✹✖✺❖❭✼❅✾✣❇✹◗✮ ✵✿✸❀★❁◗✷✯✷❅✵✍❃✣❘❫◆✘✷❅✹❇➌❻✺❖✱✣❑✶❣❜✷❳✺✿❀★✱ ❁✿✹▲❲❙✵✿✱✣❀✖✳❚❀➏✹✿✾✣✳✶■✣❁◗❀★■✣✹✻❁◗❑❤✹◗■✣✷✯❲❬❁◗✷❳✷❅✳✶✼❥✵✿✳❚❀➏❁✿✷❅✵✩✺❖❄✚✼❳✳✶❦❏✹✿✹◗✳❚❀★✹✿✹✖❀✖t❷◆❫✳❚❃❏❑❜❃◆ ✼❅✉❑✶❋ ➌✲✒❢✩✷❅✷❅❃€✵✢❃✘▼✥✵✿◆✣❑❤❀★✳❚❁✿❁❖❲❬✵❇✺❖✳❈✼❳✳✶✹✒❲❙✹✿◆✘✹▲❀★✷❅✹✿❃✣✹❇✷❅✺✽✷❅❲❙❃✣❁✿✷❅❘❏✷❅■✣✼❳t❜✵✿✳✶■✴✷❅❁◗❑❜✷❅❀★✵✩❃✣❑❤❄❉✹✒■✣✹✿▼✥✼❅✵◗❀✍❑❤✷✯❁✒✼❅✱❏✼✦❀✖✳❴✳❚✳❜❣❜■✣✺◗❀❂✱⑧■✣❦✴✼❅✺❖✷❅❀★❀★✼❳❀★✳✶✹✖❃ ✹◗✬ ✹✖✹✿t✘✵✿✳✶✾✴✹✸◆✘✷❅❄✘❃❙✷✯❃✭✺❖❘✚✼❳✳✶❲❙✹✿✹◗✷❀★✵◗✺★✱✣✳✶❑✣✵◗◆✘✷❅❑❤✹✸❃✦▼✏❑❤✬❽❁✸●❻❀❖✱✣➍⑧❀✻✺❖❘❜✷❅✾✣❀★❃✘✷❳◆✘✵✍❀★✳✶✼❅✷❅❃❏❃✣◆❬❀✸❑✶❀ ❷▼✦❀✖✹✿✵◗✺❖❁✿✵◗✷❅✷✯❣✘❣❜✷❅❀❛❃✣✺❖❘✍✼❅✾✣▼✏❑❜✹◗❁✒✵✿❀★✱✣❁❉✷❅❘❤✳✶✱✚❃✴✳✶✷❅❃✘✼❅❄✘✵✿✹✿❁❖✷❅✳❤✹❩✺❖✷❅✼❳❃✳✶✹◗✹✒✹✿✷❅❲❬✷✯✼❳✳❚❁✿✷❅✵✩❄❂❴✳❚ý ❃❏❖ý★◆ ✬ ❊ ✁ ✄✂✆☎ ✝ ✞✝ ✡ ✄✂☛☎ ✠✟ ✞☞ ✁ ✄✂✆☎ ✍✌ ✏✎ ✏✎ ✍✌ ✑✌ ✍✌ ✍✌ ✍✌ ✒✌ ✓✎ ✍✔ ✑✔ ✓✎ ✖✕ ☛✗ ✙✘ ✢ ✚✌ ✤✣ ✢ ☛✗ ✥✣ ✖✟ ✜✛ ✦ ✄✧✚✂☛☎✩★ ✁★✫✪✭✬✯✮✰✧✚✱✲✂ ✴✳✵ ✶✧ ✷✝ ✣ ✝ ✸✕ ✝ ✄✎ ✍✌ ✖✟ ✠✟ ✍✔ ✺✹ ✼✻ ✹ ✽✻ ✍✌ ✚✔ ✾ ✄✂✆☎✿✪✲✧❀☞✲✂❂❁❃✂✽✬✚✂ ❄✧ ❯ ➛ ❻➞✒➟ ➪➛ ③➠➎➞✒➟ ❂➝ ♦➠ ✿➠ ⑥❂✶✺✽ÿ ý ý ý t ỵ ỵý ýỵ ỵ ỵ tt ỵ ỵ ỵ ❶ ❅ ✼ ✣ ✾ ◗ ✹ ✿ ✵ ★ ❀ ◗ ❁ ●❻✱✣❀✍▼✥❑❤✼❅✼❅❑✶➌❻✷✯❃✭❘❼✳❚❁✿❀✍✵✩❄✘■✣✷❳✺★✳✶✼❷❁◗❀✖❵❜✾✣✷❅❁✿❀★❲❬❀★❃✘✵✿✹❻❑❚▼♦✺✽✼✯✾✭✹✿✵✿❀✔❁✿✷❅❃✣❘✚✷❅❃€◆✣✳✶✵❖✳❉❲❬✷✯❃✭✷✯❃✭❘❏✬ ✮❜✬ ✱✣❑✶➌❩✜✣✌✥❀✔✜ ❣❤❀★❁❴✧✏t➈✌✥✧✏✳✍✓❖✤ ✼❳✳❚❭✸❁✿❪€❘❤❀❻✳✶◆✣❃✘✳❚❄ ✵❇✳✶✺❖❦✴✼❅✾✣✳✶✹◗✹✿✵✿❀❻❀★❁◗❲❫✷❅❃✣✳❴❘ ❄❉✺❖✳✶❑❤✼❅❘❜❃✘❑❤✵❇❁✿✳❚✷❅✷❅✵◗❃❛✱✣❲❙❲❬✹✸✷✯✼❅✼❅➌❩✷❅❑❤❑❜❃✣❁ ✹❷€❑❚➌✸▼ ❀★❑❜✼❅❦❤✼✒⑨❖✷❅❀✖❃€✺❖✵◗✹◗✹✖❲⑧✬✸❶✸✳✶✼❅✼✯✼✢✾✭◆✣✹✿✵✿✳✶❀✔✵❖❁✿✳❙✷❅❃✣✹◗❘❉❀★✵✿❑❜✹➏❃ ✺❖✳➏❑❤❃✘ý ✵❇❚✳❚ÿ ✷❅❃✣✷❅❃✣✢❘❙❑❚▼➎✼❅❀★✳▲✹◗✹❉❘❜✷✯✵✿❣❜✱❏❀★✳❚❃✚❃ ✼❳✳✶❋❜❁◗⑤❤❘❤⑤❬❀❻◆✣◆✣✳✶✳✶✵❖✵❖✳❙✳✻✹◗❑❜❀★❦❤✵✸⑨❖❀✖❲⑧✺❖✵◗✳❴✹ ❄ ✼✯❀❴✳❤◆❬✵✿❑➏❦✣✷❳✳✶✹◗❀✖◆❬❁✿❀★✹◗✾✣✼❅✵✿✹✖✬❻➃s❑✶➌✇✺★✳✶❃❫➌✸❀❉◆✘❀★❣❤❀✔✼✯❑❜■€✺❖✼❅✾✣✹✿✵◗❀★❁✿✷❅❃✣❘❫✳✶✼❅❘❤❑❜❁✿✷❅✵✿✱✣❲❬✹✢✵✿✱❏✳❚✵✻✳✶❁✿❀❈✱✣✷❅❘❤✱✣✼❅❄➏✹❇✺★✳❚✼❥✳❚❦✣✼❅❀✍✷✯❃❬✼❳✳✶❁✿❘❜❀❉◆✣✳✶✵❖✳✶❦❏✳❚✹✿❀★✹❖❆ ❋✭✬ ❦❏✙ ✳✶✹◗❀✖✧✏✌✥◆ ✧✥✓★✤✥❃✘✾✣✓ ❲❙❀★❽❁◗✷❳✕➈✺★✜✭✳✶✌ ✼ ✚➏◆✣✧✏✳❚✓ ✵❇✳✣✬✞❽✧ ➃❻❩❑✶✕✘➌✸✗✶✕✘❀★❣❤✛✦❀★✓❫❁❴t✻✓★✤ ❲❫✒✳✶✕✣❃✘✑ ❄➅✳✶❙■✭■✣✜✣✼❅✓❴✷❥✓✖✺✔✗✶✳✶✧✵✿✷❅❑❜✎③❃✣✓❴✹✚✕✣❲⑧✑ ❭❉✳❴❪❄➷✳✶❁◗❀✖❃✘❵❜❄➅✾✣✷❅✳✶❁✿✼❅❀➷❘❤❑❜✺❖❁✿✼❅✷❅✾✣✵✿✱✭✹✿✵◗❲❙❀★❁✿✹❂✷❅❃✣✳❚❘ ❁✿❀€❑❤✵◗◆✘✱✣❀★❀★✹◗✷❅❁❫❘❤❃✣✵✩❄✘❀✖◆■❏❀✔✵✿✹⑧❑➷❑❚✺❖▼❛✼❅✾✣◆✣✹✿✳✶✵◗✵❖❀★✳✣❁✚t❻✷❅❃✘✹◗✾❏✵✿❀★✺◗❁◗✱ ❣❤✳✶✳❚✼➐✹✐ ❦✣✷❅❃❏✳✶❁◗❄➈t✣✺★✳❚✵✿❀★❘❜❑❤❁◗✷❥✺✔✳✶✼ ✏❃✭❑❤❲❙✷❅❃❏✳❚✼ ★t❤✳❚❃❏◆❬❑❤❁❇◆❺✷✯❃✴✳✶✼✦◆✣✳❚✵❇✳✣t✘❑❜❁❻❲❙✷➐④✣✵✿✾✣❁◗❀★✹✸❑✶▼③✵◗✱✣❀★✹◗❀❛◆✣✳✶✵❖✳➏✵✩❄✘■❏❀★✹❴✬ ❊✭✬ ➇✢✾❏✧✩✑✺❖✼❅✷❳◆✘✴❀✖✳❚✕✘❃✚✗✶✤ ❑❤❁❩❪€✳❚❃✣✌✥✎✱❏✳❚✑✔✵✿✓❴✵❇✕➈✳❚✗❤❃ ✑ ◆❺➏✷✯✹◗✧✏✵❇✓ ✳❚❝❃❏✺❖✜✣❀✻✗ ❲❬❀✖✧✥✓✖✳✶✗✶✹◗✾✣✜✣❁✿✗✶❀✔✤➋✹✖✬❽✑ ⑥✻③✼❅✜ ❘❤✒❑❜✕❁✿✷❅❭€✵✿✱✣❪€❲❬✳✶✹✦❃✘❦❏❄ò✳❚✹✿✺✽❀✖✼✯◆➏✾✭✹✿❑❜✵✿❃✚❀✔❁✿✹✿✷❅❃✣✾❏❘➅✺◗✱❙✳✶◆✘✼❅❘❜✷❅✹◗❑❤✵❇❁✿✳✶✷❅❃✴✵◗✱✣✺❖❀✻❲❙❲❬✹❛❀✖◆❺✳✶❀★✹◗✵✿✾✣❀★❁◗❁✿❲❙❀★✹♦✷❅✵✿❃✣❀★❀€❃❏◆➏✺❖✼❅✾✣✵◗❑ ✹◗✵✿❏❀★❃❏❁◗✹⑧◆➏❦✴✹◗■✣✳✶✱✣✹✿❀❴❀★◆➅❁◗✷❳✺★❑❜✳✶❃ ✼ ✺❖✳✶✼❅✼❅✾✣❘❤✹✿❑❜✵◗❁✿❀★✷❅❁✿✵✿✹➏✱✣❲❬➌❻✹✒✷❅✵✿➌❻✱➫✱✣✹✿✷❳✷❅✺◗❲❙✱⑧✷❅✺★✼❳✳✶✳❚❁❻❃ ✹◗◆✘✷✯⑦✔❀★❀❙✵◗❀✖✳✶✺❖❃❏✵✍◆➷✺❖✼❅◆✘✾✣❀✔✹✿✵◗❃✣❀★✹✿❁✿✷❅✹✍✵✩❄✘❑✶✬ ▼✒➃s✳✶❁◗❑✶❦✣➌❩✷❅✵✿❀✔❁❇❣❤✳❚❀★❁✿❁❴❄❬t③✳❫✹✿✱❏✺❖✳❚✼❅■❏✾✣❀❤✹◗✬✵✿❀★❁✚✺❖❑❤✾✭✼❥◆ ❦✴❀✚❑✶▼✻✳✶❃✘❄€✹✿✱✴✳✶■✴❀❤✬✚❢✩✵❉✷❅✹✍✷❅❲❙■✴❑❤❁✿✵❖✳✶❃✘✵✻✵◗❑€◆✘❀★❣❤❀✔✼✯❑❜■ ❯✴✬ ✳✶✼❅❘❤✧✏❑❜✛✢❁✿✧ ✷❅➷✵✿✱✣✜✣❲❬✌✚✹❷✗✶❁✿✕❀✖❵❜✴✾✣✎③✷❅✧✥❁◗✗✶❀❻✕ ✾✣➷✹✿❀★✕✘❁◗✛✦✹❩✓✖✵◗✑❑✍✷✯❃✭❏■✣✗ ✾✣✵✒✺❖❀★➷❁◗✵❇✜✣✳✶✷❅✧✏❃✚✛ ■❏❷✳❚✛❁❇✳❚❲❙❛❀★✌✥✵◗✕ ❀★❁✿✹✢✴✷❅✕↕❃ ✓✺✽✼✯✾✭✹✿✦✵✿❀✔✕✘❁❩✓❴✕✘✳✶❃❏✗ ➷✳❚✼❅❄➈✧✏✛✢✹◗✷❅✕ ✹ ✏✧✏✹◗✛ ✾❏✢✺◗✱❙✎✢✓✳✶✹✒✢✵◗✱✣✜✣❀❻✗✶✜ ❃✘➷✾✣❲✚✕➈✓❴❦✴✕✘❀★✗❤❁✦✑ ❑❚❭➫▼➎◆✘❪€❀✔✹✿✳✶✷❅❃✘❁✿❀✖❄✲◆✚✺❖✺✽✼❅✼✯✾✣✾✭✹◗✹✿✵✿✵✿❀★❀✔❁◗❁✿✷✯✹❃✭✔❘ ✬ ●❻❀★✹✿✱✣■✴❀❛❀✖✺❖✺❖✷❳✼❅✳✶✾✣✼❅✼❅✹◗❄❬✵✿❀★▼✏❁◗❑❤✷✯❃✭❁✻❘❙◆✭✳✶❁✿❀✔✵❇✹✿✳✈✾✣✹✿✼❅✵✿❀★✹❉✵◗✹❉✳❚❁✿✺❖❀❉❑❤❃✘❑❚✵❇▼✏✳❚✵✿✷❅❀★❃✣❃€✷❅❃✣❵❜❘❛✾✣✷❅✱✭✵✿✷✯❀❈❘❜✱✘✹✿❀★✐✿❃✣◆✘✹◗✷❅❲❙✷❅✵✿✷❅❀★❣❤❃✣❀❉✹◗✷❅✵◗❑❤❑❙❃❏✷❅✳❚❃✣✼❏■✣❑❜✾✭❦❤✵❻⑨❖❀✖■❏✺❖✳✶✵◗❁❖✹✖✳✶✬▲❲❙●❻❀✔✱✣✵✿✷❅❀★✹❻❁◗✹✖❃✣✬❻❑❤✵▲❪€❑❤✳✶❃✣❃✘✼❅❄❬❄❙■❏❦✭✳✶✾✣❁❖❁❇✳✶◆✘❲❙❀✔❃✣❀✔✹✍✵✿❀★✾✣❁◗✹❂✹✿❀★✳✶❁◗❁◗✹✖❀❉t❷❦✭✱❏✾✣✳❚✵❂❁❇◆❬✳❚✼✯✵✿✹◗❑❫❑✚◆✘❲⑧❀★✵✿✳ ❀✔❤❁✿❀★❲❙✹❻✷❅✵◗❃✣✱✣❀❜❀ t ❵❤✾✴✳✶✼❅✷❅✵✩❄✚❑✶▼ ✺✽✼✯✾✭✹✿✵✿❀✔❁✿✷❅❃✣❘❙◆✘✷➐➍⑧✺❖✾✣✼❅✵❻✵◗❑ ✺❖❑❜❃✘✵✿❁✿❑❜✼✩✬ ❞✭✬ ❀★✙ ❁✿❁◗❑❤✧✏❃✣✌✥✧✥❀★✓★❑❜✤➋✾✣✹✻✓ ◆✣✳❚✵❇❽✳✣✕✘✬✢✜✣➁✘✌ ❑❜❲❙➏✧✥❀✻✓ ✺❖❝✼❅✾✣✛✹◗✵✿✴❀★✧✉❁◗✑✔✷✯❃✭✤ ❘ ❽✳❚✜✣✼✯❘❜✓✖❑❤✜ ❁◗❭✷✯✵◗✱✣❪ ❲❙❑❤✹✒✹✿✵❫✳❚❁✿❁◗❀✻❀✖✹◗✳✶❀★✼➐✐✩❃✣➌❩✹◗✷✯❑❜✵◗❁✿✷❅❣❤✼❳◆ ❀✻✵◗◆✣❑❉✳✶✵❖✹✿✳✶✾✴❦❏✺✿✱€✳❚✹✿◆✣❀★✹€✳❚✵❇✺❖✳❉❑❜✳❚❃➈❃❏✵❖✳✶◆✚✷❅❃✲❲❫✳❴❑❜❄✍✾✣✵✿✼✯✼❅❀❴✷❅✳❤❀★❁✿◆✚✹❬✵◗❑❛❑❤❁❬✺❖✼❅❲❙✾✣✹◗✷❅✵✿✹✿❀★✹◗❁◗✷✯❃✭✹✻❘❏❑✶t✒▼✦✾✭■✴❃ ❑✘✘❑❤❃✣❁❻❑✶❵❜➌❻✾❏❃✦✳✶✼❅t❻✷❅✵✩❑❜❄➈❁ ✬ ♠✭✬ ◆✣✛✒✳✶✵❖✑★✳✣✕✘t✴✛✒❀❤✑★✬✧✥❘❏✓❴✬❅✧ t✴❷✵✿✧❳✱✣✓✔✤❙❀➏✓✹❇✳❚⑧❲❙✓ ❀❉✢✕ ✹◗❀★✴✵✍✗ ❑✶❽▼❹✕➈◆✭✗ ✳✶✵❇✳✭❹t❷✧✥✛➌❻✢✱✣❀★✎③❃➫✓▲■✣✗✶✕❁◗❀★✹✿✴❀★✗❃✘③✵◗❀✖✑ ◆➫❭❷➁✘➌❻❑❤✷❅❲❬✵✿✱➷❀✻◆✘✺❖✷✼❅✾✣❀★✹✿✵◗❁◗❀★❀★❁✿❃✘✷❅✵✍❃✣❘✚❑❤❁❇✳✶◆❺✼❅❀★❘❜❁✿❑❤✷❅❁✿❃✣✷❅❘❜✵◗✱✣✹❂❲❙✵◗❑❫✹✢✹✿✳✶✾❏❁✿❀❻✺◗✱➷✹◗❀★✳✶❃✣❃ ✹◗✷✯✵◗✳❚✷❅✼✯❣❤❘❜❀✻❑❤❁◗✵◗✷✯❑❛✵◗✱✣✵◗❲✱✣❀✻t✘❑❜❲❫❁❇◆✘✳❴❀✔❄❙❁❩❘❜❑❚❀★▼ ❃✣✷❅❀★❃✣❁❖■✣✳✶✾✭✵✿❀✵ ◆✘❁❇✳❚❲⑧✳✶✵◗✷❳✺★✳✶✼❅✼❅❄❂◆✘✷ ❷❀★❁✿❀✔❃➈✵✸✺❖✼❅✾✣✹✿✵◗❀★❁✿✹❴✬✒❢✩✵✢✷❅✹③✷❅❲❬■❏❑❜❁✿✵❇✳❚❃✘✵✦✵✿❑❉◆✘❀✔❣❤❀★✼❅❑❤■✚✳✶✼❅❘❜❑❤❁✿✷❅✵◗✱✣❲❙✹❷➌❻✱✣✷❳✺◗✱✚✳✶❁✿❀❻✷❅❃✣✹◗❀★❃✣✹◗✷✯✵◗✷❅❣❤❀✸✵✿❑✍✵✿✱✣❀❻❑❜❁❇◆✘❀✔❁✒❑✶▼❷✷❅❃✣■✣✾✣✵❴✬ q✭✬ ✺❖✼❅✾✣✧ ✹✿✵◗❀★❁✿❽✷❅❃✣✧ ❘ ➷✳✶✕✘✼❅✛ ❘❤✑✔❑❜✧ ❁✿❏✷❅✵✿✛✢✱✣✜✣❲❬✌❳✧×✹ ✓★✤ ✳❚❭✴❁✿❀€⑥❧❘❜◆✣❑✘✳✶❑❺✵❖◆➪✳✶❦❏✳✶✳❚✵✚✹✿❀✍✱❏❑❤✳❚❁✻❃❏◆✘✳✚✼❅✷❅◆✣❃✣✳❚❘➷✵❇✳➏✼❅❑✶➌❻➌ ✳✶❁◗◆✘❀★✷❅✱✣❲❬❑❤❀★✾✭❃✣✹✿❀❉✹✿✷❅❑❜❲❫❃❏✳❴✳✶❄ ✼✻✺❖◆✣❑❜✳❚❃✘✵❇✳✭✵❇✳✶t❩✷❅❃❬✷❅❃✘✹✿❣❤❀★❑❜❣❜✼❅❣➈❀★❁❇✷❅❃✣✳❚✼❘➫◆❺❑❤✷✯❃✭❲❬✼✯❄ù❀★❃✣✵✩✹◗➌❩✷✯❑❜❑➷❃✣✹✒✵◗❑➅❑❜❁✻✵◗✳✶✱✣✵✿❁✿✵◗❀★❁✿❀➷✷❅❦✣◆✘✾✣✷❅✵◗❲❙❀★✹✖❀✔✬❻❃✣❪€✹✿✷❅❑❤✳❚❃✭❃✘✹✖❄ ✬ ➃❻◆✣✳✶✾✣✵❖❲❫✳❉✳✶❑❜❃❉❦❤⑨❖❀★❀✖❄❜✺❖❀★✵◗✹❻✹❻✳✶✷✯❃❬❁✿❀❻✱✣❘❜✷❅❘❤❑✘✱❫❑❺◆✚◆✘✳❚✷❅❲❙✵✣⑨❖❀★✾❏❃✣◆✘✹◗✷❅❘❜❑❤✷✯❃❏❃✭✳❚❘❂✼➈✵◗✹◗✱✣■❏❀✻✳❤❵❜✺✽❀❤✾❏t✣✳✶❀★✼❅✷❅✹◗✵✩■❏❄❉❀❴❑❚✺❖✷❳▼➎✳✶✺❖✼❅✼❅✼❅✾✣❄⑧✹◗✺❖✵✿❀★❑❜❁◗❃✣✷❅✹✿❃✣✷❳❘✍◆✘❀★▼✏❁◗❑❜✷❅❁✒❃✣✾✣❘❛■✚✵◗✱❏✵✿❑✍✳✶✵❻✵◗✱✣◆✣❁✿✳❚❀★✵❇❀✍✳❈◆✘✷✯❃❬✷❅❲❙✱✣❀★✷❅❃✭❘❤✱❫✹✿✷❅❑❤◆✘❃✣✷❅❲❙✹❴✬❷❀★❢✩❃✣✵✒✹◗✷❅✷❅✹❩❑❤❃❏✺◗✱❏✳❚✳❚✼➈✼✯✹◗❅■❏❀★❃✭✳❤✺✽❘❤❀❛✷❅❃✣✺★❘✻✳✶❃❬✵◗❑❛❦❏✺❖❀✍✼❅✾✣❣❜✹◗❀★✵✿❁✿❀★❄ ❁ ✹✿■❏✳❚❁✿✹✿❀➏✳✶❃❏◆❬✱✣✷❅❘❤✱✭✼✯❄✚✹ ❤❀★➌✸❀✖◆❷✬ ✫✭✬ ❑✶☞ ▼❂✴✺❖✛✒❑❜✑★❃✣✓❴✹✿✗✶✵◗✜✣❁❇✳✶✧✥✛✦✷❅❃✘✓ ✵✿✹❴✬ ✜❏➁✘✑✔✕✾✭■✣■❏❑❜✌✏✹✿✎✒❀❬✑✔✓✖✵✿✱❏✕✘✗✶✳❚✧✥✵❉✛ ❄❤❑❜❭✢✾✣➀❻❁❩❀✖⑨❖✳❚❑❜✼➐❦➷✐✉➌✸✷✯✹❈❑❤❁◗✵✿✼❥❑➷◆❬✳✶✺✿✱✭■✣❑➈■✭❑❜✼✯✷❳✹✿✺★❀❬✳❚✵✿✵✿✷❅✱✣❑❤❀❬❃✭✹❻✼✯❑✣❲⑧✺★✳❚✳❴✵✿❄✚✷❅❑❤❃✣❃✭❀★✹✻❀❴◆❫▼✥❑❤✵✿❁❛❑❬✳❫■❏❘❜❀★❁➣✷❅❣❤▼✏❑❤❀★❁◗❃➷❲ ❃✘✾✣✺❖✼❅❲✚✾✣✹✿❦✴✵◗❀★❀★❁❉❁✿✷❅❃✣❑❚▼❹❘❫❃✣✾✣❀✔❃✴➌➉◆✘❀★✳✶❁✻✾✣❣❤✵◗✳❚❑❤❁✿❲❫✷❅❑❤✳✶✾✭✵✿✹✷❳✺➏➈✺★✷❅❃❏✳✶✹◗◆❺✱ ✹ ✹✿✳✶✵❇❃❏✳❚◆ ✵✿✷❅❑❤✱✣❃✭✷❅❘❤✹ ✱✘✏➌❹⑥✒✳❴●✻❄➫❪❫❃✣✹ ❀★❻✵✩➌✸✷❅❃⑧❑❤❁ ✳✚✘✹✖✺✽t❩✷✯✵✩❄✘✳❚❃❏✬✢◆➅●✢❑ ✺✽✾✣◆❺✹✿❀✖✵◗✺❖❑❤✷❳❲❙◆✘❀❉❀✔❁✚✾✣■✴❁✿❑❤❀✖❵❜❃❫✾✣✵◗✷❅✱✣❁✿❀✔✷❅✹✖❲❙t✣❀★❄❜❃✘❑❤✵✿✾❬✹➏❲⑧■✴❀★✳❴❁✚❄❙❁✿✺❖❀★✼❅❘❜✾✣✷❅✹◗❑❤✵✿❃ò❀★❁▲✳❚✱✣✹❙❑❤✾✣✺❖❑❤✹◗❃✭❀★✱✣✹✿✵✿❑❜❁❖✼❥✳✶◆❺✷❅✹❻❃✘✵✿➌❻✹❴✱✣✬➷✷❅✼✯⑥ ❀❉✺❖✺◗❑❜✱❏❃✣✳✶✹✿✼❅✷❳✼❅◆✘❀★❀✔❃✣❁✿❘❜✷❅❃✣✷✯❃✭❘✚❘€✵✿✱✭✵❇✳❚❀❛✹ ➷✺❖✷❅✵✩✷❅❄ ✹❛✹❻✵◗❑ ❁◗✷❅❣❤✴❀★❃❏❁◗◆ ✹ ❘❤❁✿❑❜✾✣■✣✹❻❑❚▼ ◆✣✳❚✵❇✳➏➌❻✷❅✵✿✱❫❘❤❑✘❑✣◆❙✺✽✼✯✾✭✹✿✵✿❀✔❁✿✷❅❃✣❘✚❦✴❀★✱❏✳❴❣✘✷❅❑❤❁✻✳✶❃✴◆❙✹❖✳✶✵◗✷✯✹➣▼✏❄✘✷❅❃✣❘❛❣❤✳❚❁✿✷❅❑❤✾✭✹❹✺❖❑❜❃✣✹✿✵◗❁❇✳❚✷✯❃✘✵◗✹✖✬ ①✭✬ ✾✣✛✦✹❇✳❚✓❴❦✣✕✘✼❅✗ ❀❤③✬❻✗✶●❻✕✘✓❴✱❏✜ ✳❚✵✻✧❳✷❅✌❳✹✖✧✥t✴✓❖✤✚✺❖✼❅✜✣✾✣✛✹✿✵◗€❀★❁✿✎✒✷❅❃✣✑✔❘❫✜ ❲⑧✧✏✳❴✌✥✧✏❄✚✓❖✤ ❃✭❭✴❀★❀✖➆❻◆❫✹✿❀✔✵◗❁✿❑❙✹✸❦✴❲⑧❀❉✳❴✵✿❄✻✷❅❀✖❀✽◆❫④❺■✴✾✭❀✖■€✺❖✵❻➌❻✺❖✷❅✼❅✵✿✾✣✱€✹◗✵✿✹◗❀★■❏❁◗❀✖✷✯❃✭✺✽❘❉✷ ❷❁✿✺❉❀★✹◗✹◗✾✣❀★❲⑧✼❅✵✿✹✒✳❚❃➈✵◗❑✍✵◗✷❳❦❏✺✻❀❻✷❅❃✘✷❅❃✘✵✿❀✔✵✿❁✿❀★■✣❁◗■✣❁◗❀★❁✿✵❇❀✔✳❚✵❇✵✿✳✶✷❅❦✭❑❤✼✯❃✣❀❜✹❉t➈✺❖✳❚❑❜❃❏❲❙◆❫■✣✳✶❁◗■✣❀★■✣✱✣✼❅❀★✷❳❃✭✺★✳❚✹✿✷❅✵✿❦✣✷❅❑❤✼❅❀❤❃✣t❤✹❴✳❚✬✸❃❏❢✩◆ ✵ ✷✯✹❻✷❅❲❬■❏❑❜❁✿✵❇✳❚❃✘✵✒✵✿❑✚✹◗✵✿✾❏◆✘❄❬✱✣❑✶➌➋✳✶❃⑧✳❚■✣■✣✼❅✷❳✺★✳✶✵◗✷❅❑❤❃❙❘❜❑➈✳❚✼❏❲❫✳❴❄❛✷❅❃ ❏✾✭❀★❃❏✺❖❀❉✵◗✱✣❀❉✹◗❀★✼❅❀✖✺❖✵✿✷❅❑❜❃⑧❑❚▼❩✺❖✼❅✾✣✹✿✵◗❀★❁✿✷❅❃✣❘✚❲❬❀★✵✿✱✣❑✣◆✘✹❴✬ ❑✶❲❙▼✻❀✔◆✣✵✿✰✲✱✣✳❚❑✣✵❇✷❅✳€◆✘✵◗✱❛✹❴✳❚✬❫✵◗❃❏✱✣◆€✰➷❀★✹✿✱✭❀✚❀▲❑✶✵✿❁✿➌❧✱✣❀✖❵❜❀★✵✿❃ù✾✣✱✭✷❅❀★❁◗✹✿❄❀★✵◗❲❙✾❏✺✔◆✘❀★✳✶❄➫❃✘❃➷✵◗❀✖✹✒✷❅✳❤❃ ✷❅✺◗❏❃❛✱ò✾✣❲❬❀✔✺✽❃❏✷✯✼✯❃✴✾✭✺❖✹✿❀⑧◆❷✵✿t★❀✔✺✽❑❜❁✿✼✯✾✣✷❅✾✭❃✣❁✒✹✿❘➫✵✿✹✿❀✔✵◗❁✿❲❙✾❏✷❅❃✣◆✘❀★❘€❄➏✵◗✱✣❑✶❲❬❑✣▼✦◆€❀★✺❖✵✿✼❅✷❅✱✣✾✣❃➅❑✣✹✿✵◗◆✘◆✘❀★✹❴❀★❁❻✬❙✵❖✳✶✳✶➁✘✷❅❃❏✼✩❀✖✳❚t✦✺✽✼✯✷❅❑❤❄✘❃❏❃❏✹◗✺✽✷✯◆❷✼✯✹✢✾✴t❽■✣◆✘➌✸❁◗✷❅❑✣❃✣❀✚✺❖❘❫❀★■✣❀✖■❏❁✿◆✘❀★✳✶✹❻✹◗❁◗❀★✵✿✳✶❃✘✷❅✹✵✿✵ ✷❅▼✏❑❤✳❑❤❃✭✼❅✷✯✼❅❘❤❃✭❑✶❀★➌❻❘⑧❃✣✹✖❀✔❲❬✬❁❇✳✶❽❀★✼✸✵✿✷❅✱✭❁✿✺★✹◗❑❺✳✶✵✖◆❺✵◗t❜❀★✹✖➌❩❘❤t❽❑❜❀❻✱✣❁✿✹◗✷❅✷❅❀★✵✿⑦✖❁❇✾❏✳✶✳❚✵◗◆❺❁❇✷❅❄ ❑❤✺◗✱✣❃➷◆✘✷❳✷✺★❑✶❷✳✶▼✻❀★✼✸❁✿✺❖❲❙❀✔✼❅❃➈✾✣❀✔✵♦✹◗✵✿✵✿✵✩✱✣❀★❄➈❁◗❑✣■✴✷✯◆✘❃✭❀★✹❴❘ ✹ t ✹✿◆✘✷❅❀★❑❜❃✭❃❏✹✿✳✶✷❅✵✩✼❷❄❜✹◗✐✉■❏❦❏✳❤✳❚✺❖✹✿❀➏❀✖◆ ✳✶❃❏❲❙◆❫❀★◆✘✵◗✱✣✷❅✹❇❑✣✺✽◆✘✾✣✹✖✹✿t✭✹▲❘❤❣❤❁✿✳✶✷❳◆❜❁✿✷❳✐✩✳❚❦❏✵✿✳❚✷❅❑❤✹✿❀✖❃✣◆❬✹♦❑✶❲❙▼❩❀✔◆✘✵✿✱✣✷ ❑✣❀✔◆✘❁✿✹❴❀★t❏❃✘✵✻✳✶❃✴❲❬◆❙❀★❲❬✵✿✱✭❑✣❑❺◆✘◆❺❀★✹✖✼➐✬✐✉❦✴✳✶✹✿❀❴◆❙❲❬❀★✵✿✱✭❑❺◆❺✹✖✬✒✰➷❀✍✳✶✼❅✹✿❑✚❀✽④✭✳❚❲❙✷❅❃✣❀✍✺❖✼❅✾✣✹✿✵◗❀★❁✿✷❅❃✣❘❬✷✯❃❫✱✣✷❅❘❜✱ ◆❺✷✯❲❬❀★❃✘✐ é❻ê ❬û ❉÷❽ó ▲ï✦ð✣ï✞đ✿ú➔ơ❷õ✿ư✻ó❜ð✣÷✦ø✭đ✿ú ✞ï✢ú✻ï✢õ✩û✻ó✘đ✿ó ❢✩✹✿❃€✾✴✺✿✵◗✱➷✱✣✷❅✳✶✹✻❃➫✹✿❀❴✳✶✺❖❃❏✵✿✳❚✷❅❑❤✼✯❄✘❃❽✹◗t❏✷✯✹❴➌✸✬✻❀❉➁✘✹◗✾✣✵✿■✭✾❏■❏◆✘❑❜❄ ✹✿❀➏✵✿✱✣✵✿❀❉✱❏✳❚✵✩❄✘✵❂■✴✳❙❀★✹✍◆✭✳✶❑✶✵❇▼❩✳✈◆✣✹✿✳❚❀★✵❇✵✍✳✚✵◗➌❻❑❙✱✭❦✴✷❥✺◗❀ ✱❫✺❖❑✶✼❅✾✣▼✥✵✿✹◗❀★✵✿❀★❁▲❁◗❑❺❀✖◆➫✺✔✺❖✾✣✺❖❑❤❁✍❃✘✷❅✵❇❃ ✳❚✷❅✺❖❃✣✼❅✹✾✣✹✿➫✵◗❀★❑❜❁✿✷❅❦❤❃✣⑨❖❘❫❀✖✺❖✳✶✵◗❃❏✹❉✳❚➌❻✼❅❄➈✱✣✹◗✷❳✷❅✺◗✹✻✱€✳✶❲⑧❃❏◆❫✳❴❄✚✱✭❑✶❁◗➌✇❀★■✣❁✿✵◗❀✔❑❙✹✿❀★■✣❃✘❁◗✵❉❀★■✣■✴❁✿❀★❑✣❁✿✺❖✹◗❀✔❑❤✹✿❃✣✹➏✹❴✵✿t✦✱✣✱✭❀★❑❤❲➔✾✣✹◗▼✥❀★❑❤✹✖❁ t ❆❅❈❇❊❉ ❄€✚✂☛ ✶✂✲✬ ✁  ✶❁✿✮ €✚◗ ✴✳✵ ✶✧✚✱ ❙❘✙✂✚✳✙✧ ▲✂✆★✵☞✴❁✿✮✚✳❚✧ ❯◗✿❱❯☞✲✂❂❁❃✂ ✫❘ ❲✪❄❘✽❳❙☞ ❨✧✩★ ❆❋❍●✸■ ❆❏❈❑ ❆❋✤❇ ✺❇▲❏◆▼ ✫❖ ✚✔ ✥◗☛★✵✂✆  ❲✱✆✧✚☞❊★✙❩ ❨✧✩☎ ❬€✚✂☛  ✂☛★❭☞❪€✚✂❂❁❃✧❃✪✲◗☛☎ ❬€✚✂✆ ◆☞✲✂✼❁✏✂ ❊✌ ✢ ✴❫❴✝ ✏✎ ❄❵ ❄✂ ❯✳❭ ✄✧ ✢ ❄✣❛✘ ❝❜ ❛✹ ✼❞❡✘ ✡❢ ❣✕ ✖✹ ❈❥ ✢ ✞✣✐❤ ✁✻ ✝ ✣✙✗ ✁✻ ✝ ❛✣✙❤ ❦❜ ✢ ✼❞ ✯❞ ✐✕ ❊✌ ❈❧ ✥♠ ✙♥ ✫♠ ✭❤✏✣ ✦✘♦✣❭♠ q♣ ✠✣✐❜ ✙✘◆✟ ❄✣r✘ ☛♠ ✖✕ s✕ ✐♠ ❆✹ ❙✻ ✆✎ ✢ ❄✣t✘ ✈✉ ❬✗ ✜❜ ✼✣ ❄❞ ✼❞ ✖✣ ✙✎ ✜✣ ✲✘ t✘ ❊✣✐❤ ✖✕ ✝ ✣ ✲✘ ✍✔ ✍✔ ❈✇ ✥✟❭❞①✘ ✥♠ ✥✣ ✓✎ ✼② ✢ ▲✣ ❊✹ ❚✘ ✝ ❈✎ ✖✟ ✚✻ ❣③ ✓✎ ✈✉ ☛✕ ✢ ✏✎ ✢ ❆✘ ✑✌ ✫④ ◆✛ ✫④ ✍✔ ❃⑤ ⑥ ❯⑦ ✾⑧✖⑨❪⑩ ❯❶ ▲❷ ✍✔ ✰✌ ✲➞ ✒➟♦➠➷➜ ▲➞ ✿➝✡➛ ✢➠❷➞✒➟ ✿➝ ✍➝ ✒➠ ✿➠ ❞ ◆✘◆✣❑✣✳❚✵❇✺❖✳➏✾✣❲❬✹✿✵◗❀★❁✿❃✘✾❏✵✿✺✽✹❴✵✿t➈✾✣✺❖❁◗❑❜❀★✾✣✹✖✬ ts ý ý ỵ ỵ ýý t ttttttt t ✔t✣✳✶✹❻✹✿✱✭❑✶➌❻❃⑧✷❅❃ ✉✫✣✬❅✮ ★✬ ●✸■❹❸✐■ ❯▼❆❉ ❈❺❼❻❈❇ ❈❥ ✾♠ ✹ ✥❾ ✹ ✵❇✤❖ ❆❏❈❑ ❆❋✺❖ ❀❽✦❇ ✜◗✲✬✡❿❄✧✚€✚❁✥❳❙✬✯✮✼❳✏➀❂✂✆☎ ❬✂✲✬✯ ✄✧ ❨✧❙✂ ✩❩✸☎✚✧ ❨✧✯★✫❁ ❈❇❊❏◆▼ ✫❖ ✚❁✿☎✩❩✙€✚❁✿❩✫☎❙✧✓✻ ❨❷ ✞➁ ✢ ✗ ❝✂❂❁❬❁✿☎ ❬✬✯❩✽❁❃✧ ✏✻ ❯❷ ✁➁ ➄➅ ❪✹✿❷ ✜➂➃➁ ➅ ➇❴➈❙➈ ➅ ➉✼➉❄➉➎➉✼➉❄➉➎➉✼➉✼➉➏➉✼➉❄➉➐➉❄➉✼➉ ➅ ➉✼➉❄➉➊➇❣➈✿➋ ❙✻ ➇✐➑✥➈ ✉✫✭✬❅✮ ↔ ↔ ↔ ✹ ❄✻ ➉✼➉❄➉➒➇✙➑❹➍ ➉✼➉❄➉➎➉✼➉❄➉➎➉✼➉✼➉➏➉✼➉❄➉➐➉❄➉✼➉ ➆ ✼✻ ➣✑↔ ➉✼➉❄➉➌➇❣➈✁➍ ➉✼➉❄➉➒➇✙➑✶➋ ❦✹ ➇✐➓✙➈➏➉✼➉❄➉➔➇✙➓✽➋ ↕ ➉✼➉❄➉→➇✐➓❄➍ ❋✭✬ ▼✏❑❤❁✻✧✩✑❴✳❚✑★✼✯✧ ✴➷■❏✧✏✳❚✌×✷✯✜✣❁◗✗✶✹❻✧❳❑✶✓★▼✤ €➷❑❜✜✣❦❤✓❴⑨❖✗✶❀✖✧ ✺❖✵◗✹✖✏✬✒❑❜❢✩❁ ✵❻✷❅✹❻❑❚▼✏✵✿❀★❃❫❁◗❀★■✣❁✿❀✔✹✿✒❀★❃✘ý ✵✿❀❴◆➫❦➈❄❙✳❚✔❃ ❭✦●❻✭✐✉✱✣❦✘✷❅❄❜✹✸✐ ✹✿✵◗❑❤✵❇❁✿✳✶❀✔❦✭✹✻✼✯❀❉✳❉✳❚✺❖✹❻❑❤✼❅✹✿✼❅❀✖✱✣✺❖❑✶✵◗➌❻✷❅❑❤❃❫❃❙❦✴❑❚❀★▼✦✼❅❑✶■✣➌❉❁✿❑❴t ④✣✷❅❲❙✷❅✵◗✷✯❀✔✹③✵◗✱❏✳✶✵❻✳✶❁◗❀❂✳❴❣❤✳❚✷✯✼❳✳❚❦✣✼❅❀ ✉✉❋❊ ⑤ ✖✖✮✮ ✉❊ ⑤ ❖❋ ⑤ ✉✫✭✬❡❋ ✬✬ ✬✬ ✬✬ ✖✮ ❖❋ ⑤ ➌❻✱✣❀★❁✿❀ ✲⑤✣t✘➌✸✸❀❉✷✯✹✸✱❏✵✿✳❴✱✭❣❜❀❂❀✻❲❬✵◗✱✣❀✖❀❉✳✶✹◗❲⑧✾✣❁✿✳❚❀❴✵✿◆❁◗✷❨④✚❽✧✷❅❩❃ ✕✘✩✗✶✫✣✕✘✬❡❋ ✛ ✔✬✒✕ ❪❫❑❤❀✖❁ ✳✶❽✹◗✾✣✧✩✑✖❁✿❀✔✑✔✹✻✧ ➷❑✶▼✒✧❳✌✏◆✘✜✭✷❅✗✖✹✿✧✥✹◗✓❖✷✯✤❲❬❦✴✷❅✼❥❀★✳❚✵✩❁✿➌❩✷❅✵✩❀✔❄❛❀★❃€✳❚❁✿❀❛❑❤❦❤◆✘⑨✽✷❅❀✖✹❖✺❖✺❖✵✿✾✣✹ ✹✿✹◗✒❀✖✳✶◆❫❃✴✵◗◆ ✱✣✣❁✿❑❜✬❩✾✣➁✘❘❤✷❅✱✣❃❏❑❜✺❖❀✾✣✵❻✵✿✱✭✷✯✹❻✹◗❀✖✺❖✵◗✷✯❑❜❃✦✬ ★t✣✳❚❃❏◆ ●❻✹✿✷❅❃❏✱✣✺✽❀✍❀⑧◆✣✵◗✳✶✱✣✵❖✳❉❀❙❲❫❁◗❑✶✳✶➌❻✵✿✹ ❁◗✷➐④❛✳❚❃❏✷❅✹✒◆➷❑✶✺❖▼✏❑❜✵◗❀★✼✯✾✭❃⑧❲❙✺✔❃✣✳✶✼❅✹✍✼❅❀✖❑✶◆❙▼✻✳ ✵◗✱✣✓ ❀✚▼✥❑❤❁✿❲❬❀★❁❉❽✕ ❁◗❀★❲⑧■✣❁✿✳❚❀✔✵✿✹✿❁✿❀★✷➐❃✘④✦✵⑧t✶➌❻◆❺✱✣✷ ❷❀✔❀★❁✿❁◗❀✖❀★✳❚❃✘✹❻✵❛✵✿✱✣❀★❃✘❀✍✵◗◆✘✷✯✵◗✷❅✷❅✹✿❀★✹✿✹✖✷❅❲❬t♦➌❻✷✯✼❳✳❚✱✣❁✿✷❅✼✯✷❅❀✚✵✩❄✍✵◗❲⑧✱❏✳✶✳✶✵❈✵◗❁✿❑✶✷➐④❛▼✻✵✿✷❅✹❩✱✭❀❙✺★✳❚✼❳✼❅✳✶✼✯❀❴✵◗✵✿◆❙❀★❁➏✳ ❁✿✴❀★✛✢■✭✕ ❁✿❀★✹◗❀★❃✘✵❙❽✕✵✿✱✭❲❫❀❙✳✶✹❇✵✿✳❚❁◗❲❙✷➐④➎❀ t ❀★❲⑧❃✘✳❚✵✿✷❅✵✿✵✩❁◗❄✘✷❨④✦✬③t❜❪ ✷❅✵❹✳✶✺★❃✘✳❚❄❙❃ ✺❖❏✼❅✾✣❁✿✹✿✹◗✵◗✵✻❀★❁✿❦✴✷❅❀❉❃✣❘❙✵✿❁❖✳❚✳✶✼❅❃✣❘❤✹➣❑❤▼✏❁◗❑❤✷❅❁◗✵✿❲❙✱✣❲❬❀✖◆✈✹✦✷✯❑❤❃✘■✴✵◗❀★❑ ❁❖✳✶✳✚✵✿❀❈◆✘✷❅❑❤✹◗✹✿❃❙✷❅❲❙✳➏✷❅◆✘✼❳✳✶✷❅✹✿❁◗✹✿✷✯✷❅✵✩❲❬❄✍❲❫✷✯✼❳✳❚✳✶❁✿✵✿✷❅❁◗✵✩❄✍✷➐④ ❲⑧❦✴✳✶❀❖▼✏✵◗❑❜❁✿✷➐❁✿④✦❀❛✬❷✳❚❢✥■✣▼③■✣✵◗✼❅✱✣❄✘❀❂✷✯❃✭◆✭❘❛✳✶✵❇✹◗✳➏✾❏✺◗✳✶✱ ❁◗❀✍✺✽✼✯■✣✾✭❁✿✹✿❀★✵✿✹◗❀✔❀★❁✿❃✘✷❅❃✣✵✿❀✖❘⑧◆ ỵ ỵýýỵỵ ỵỵ ýự ỵỵ ýt t ỵýý ỵìỵ ỵ ý t ỵ st ỵ ỵ t ỵ ý t ộờ ❩ê✿ë ✲đ✿ó✘ó✘đ đ✿õ✿ï✢ø✣đ✥ð✣đ◗÷❷ó€ï✢ú ❾ó✘đ ❝đ◗õ✿ï✢ø✣đ➣ð❺đ◗÷❷ó ➂÷✦ï✢ó✘ư✻ø✭đ✿ú ð✣í✻÷ ❻ư✻ï✢õ◗đ✩ð✶û ⑧ơ❷õ◗ư✻ó❜ð✣÷✦ø✣đ◗ú ❪❫❽✧✉❀✖✑❴✳❚✑✔✹✿✧ ỵýýỵìỵ ỵ ỵýýỵỵ ỵỵ ý t t ➌❻✱✣❀★❱▲❃ ✷❅✹✿✵✿✹◗✱✣✷✯❀★❲❬❄❫✷❅✼❥✳✶✳❴❁◗❁◗❀❂✷❅✵✿❲❬✷❅❀★✹❩❑❤❁◗✺★❀❂✳❚❃€◆✘✷ ❷❦✴❀★❀❉❁✿❑❤❀★❃✘❦✣✵❴✵❖✬✳✶✷❅❃✣❀✖◆❬❦✘❄❙✹◗✷❅❲❙■✣✼❅❀✻✹◗✾✣❦❤⑨❖❀✖✺✽✵✿✷❅❣❤❀➏❁❇✳❚✵✿✷❅❃✣❘❤✹❻❲❫✳❤◆✘❀✍❦✘❄⑧✳➏✹◗❀★✵✻❑❚▼✒❑❤❦✣✹◗❀★❁✿❣❜❀★❁✿✹✍❑❤❁▲❀❖④✣■❏❀✔❁✿✵✿✹✍❑❜❃⑧✱✭❑✶➌✇❲✚✾❏✺◗✱ ✺❖✳✶❀★✹❈❁◗✵❇❲⑧✳❚✷✯✳✶❃ ✵◗✱✣❑❜❀★❦❤❲❫⑨❖❀✖✳✶✺❖✵✿✵◗✷❳✺❖✹❙✹❴◆✘t✴✷✷✯✹❈❀★✵✿❁❈❑ ▼✏❁◗✳❚❑❤❃✣❲➂❑❤✵◗✱✣❀✖❀★✳❜❁✖✺◗t❽✱➅✹✿✾✴❑❤✺✿✵◗✱✱✣❀★❁❴✳✶✬✹❉❦✭✣✷✯❑❜❑❜❁❛✼❅❑❤❀✽❘❤④✭❄✘✳❚t❷❲❙✺❖❑❤■✣❲❬✼❅❀❤■✣t❽✾✣✷❅❃➅✵◗❀★❁✍✹◗❑❺✹❇✺✽✺❖✷❥✷❅✳❚❀★✼❩❃❏✺✽✹❖❀❤✺❖✷❅t✒❀★❑❜❃❏❁❉✺❖❀❜■✣t❩✱✘❑❜❄✘❃✣✹✿❀❫✷❳✺❖✹✖❲⑧✬❫✳❴⑥▲❄€✼❅✵✿❁❖❀★✳✶❁◗✵◗❃❏❀❙✳✶✱✣✵◗✷✯❑✶❣❜➌➉❀★✼❅❄➈✺✽t❽✼✯❑❜◆✘✹✿✷❅❀❬✹✿✹✿❑❤✷❅❲❬❃✣❀❬✷✯✼❳✳❚✹✿❁✿✾✣✷❅❦❤✵✿✷❅⑨❖❀★❀❴✹✍✺❖✵✖✺★t✸✳✶❃➷✹✿✾✴❦✴✺✿✱ ❀ ✺❖❑❜✴❲❙✗✶✗✶■✣✕✘✾✣✌✏✜✭✵◗❀✖✓✖◆✈✧ ❏▼✏✛ ❁✿❑❜❦✴❲➉❀★✵✩✺❖➌✸❑❜❀★❁✿❁✿❀★❀✔❃➫✼❥✳❚✵✩✵✿➌❩✷❅❑❤❑❬❃❫❣❤✺❖✳✶❑✘❁◗❀❖✷❥✳❚➍⑧❦✣✺❖✼❅❀★✷❅❀★✹ ❃✘➷✵✿✹❴✬❻✳❚❃❏➒✍◆ ✷❅❣❤❫❀★❃ ✷❅✹❂❫◆✘❀❑❤❏❦❤❃✣⑨❖❀❴❀✖✺❖◆ ✵✿✹s✷❅❃ ▼✏❑❤✉❁✻✫✭✺❖✬ ❊ ✼❅✾✣★t✴✹◗✵✿➌❻❀★❁◗✱✣✷❅❀★❃✣❁◗❘❏❀ t✭➷✵✿✱✣✳❚❀✍❃❏■❏◆ ✳❚❁❇⑧✳✶❲❬✳✶❁◗❀★❀❛✵✿❁◗❣❤✷❳✳❚✺ ❁✿✷❳✳✶✕✘❦✭✜✣✼✯❀✔✗❤✹❂✑ ✴◆✘✛❀★✹❖✺❖✢❁✿✗✷❅❦✣✷❅❽❃✣✎❘❫✵◗✓ ✱✣❀❛❑❜❦❤➷⑨❖❀✖✕✘✺❖✵◗✛✦✹✖✓ t ❣❤✳✶✼❅✾✣✳✶❀✍❃❏❑❚◆ ▼ ➏▼✏❑❜✳❚❁❩❁✿✵◗❀❉✱✣❀✵◗✱✣×❀❉✵✿✱❫❲❙❑❤❀❴❦❤✳✶⑨❖❃❙❀❴✺❖❣❤✵✖✳❚✬ ✼❅✾✣❀★✹❻❑✶▼ ✳❚❃❏◆ ❏t✭❁✿❀★✹◗■❏❀✖✺✽✵✿✷❅❣❤❀★✼❅❄✘t❷✳✶❃❏◆ ✷❅✹❻✵✿✱✣❀✍❣❤✳✶✼❅✾✣❀✍❑❚▼ ìt tỵt tt ✼❅◆✾✣➏✹❴✷✯✬ ❃✷❅✹▲✹✿✾✣❑❤✹✿❲❬❀✖◆ ❀❉▼✏✳✶❑❜■✣❁✻■✣✳❙✼❅✷❳✺★✺❖✳❚❑❜✵✿❁✿✷❅❁✿❑❤❀✔❃✣✼❥✳❚✹❴✵✿✬❻✷❅❑❤r❻❃❽❑❤✬✻✵◗✷❳♥✒✺❖❀❉❑❜✵✿✵✿✱➷✱✴✳✶✺❖✵ ❑✘❀❖✞➍⑧✷❅✺❖✹❻✷❅❀★✾✣❃✘✹◗✵✿❀✖✹❉◆€✳❚✷❅❁✿❃❫❀❉✹✿■✣✵❖❁◗✳✶❑✶✵◗❣✘✷✯✹◗✷❥◆❺✵✿✷❳❀✖✺❖◆ ✹ ❈❥ ✥♠ ✞♠ ❬❾ ✹ ➙◗✽✬✁❿❄✧✚€➛❁❬❳❙✬✯✮✼❳❙◗✲✬✡❿❄✧✚€➛❁ ✚❁➜☎✩❩✙€➛❁➜❩✫☎✚✧✏✻ ❆❷ ✰❷ ❃❷ ➄➅ ➣✑↔ ➅ ➝ ✹ ✐➞ ✼✻ ➅ ➝ ✹ ✐➞ ✼✻ ➝ ✹ ✙➞ ✲✻ ➝ ✹✿❷✖➞ ✼✻ ➝ ✹➜❷✖➞ ✲✻ ➅ ➆ ➝ ✹✿➟✏➞❃➠✲✻ ✘ ✝ ✡❢ ➝ ✹✿➟✏➞✚➟✥✻❆➢ ↔ ➅ ✰✹ ↔ ✘ ↔ ↔ ✹ ✲✻ ↕ ➉✼➉❄➉➌➉✼➉❄➉ ❊➟ ✥♠ ➝ ✹➜➟✓➞❃➠✆✻❆➢ ➡➠ ➝ ✹✡➠✲➞❙➟✥✻ ✲✻ ✯❜❀✣✵②✓♠✾✣◆✘ ✣ ✸②✓♠✾✣◆✘ ✑✔ ✒✌ ➡✌ ✦€✚◗☛☎✩☎✚✧✩ ✶✂✼❁ ❬◗☛★✾€✚◗❄✧✡➤✦€ ❬✧✯★✫❁  ✄✂✆☎ ✶❁✿✮✰€❙◗✼✧✡➤①€ ❬✧✯★✫❁ ✁★✫❁✏✧✩☎✯➀❂✂✆ ❹❳ ❄€✚✂☛ ✄✧✚☞ ❃⑤ ➧ ✏➨ s✬ ✡★✵✂☛☎✩✮ ❯⑩ ➙☞ ✘ ✁ ✶✂☛☎ ❲❁➜✮ ➯☞ ✏➨ ✰★✵◗ ❭➩✜➫ ❯❶ ✁★✵✂✆ ❹➥➦◗✆☎❙☞ ✡★✵✂☛  ❛➭ ✶❳ ➃☎❙✂✼❁ ❬◗❂❳ ✯€✚✂✆ ✄✧✚☞ t⑧✖⑨ ❯❶ ✡ ✄✂☛☎ ✶❁➜✮✜€✚◗✼✧✁➤✦€ ❬✧✯★✫❁ ➝ ✹✿➟✏➞❃➠✲✻ ❬♠ ❼☞ ✁ ✶✂☛☎ ✶❁✿✮❪€✚◗✼✧✁➤✦€ ❬✧✯★✫❁ ❪➟ ➙➠ ✍✔ ✍✔ ❼✛ ✞❷ ✝ ✣ ➺❨➋ ▲➳ ✥✣ ❆➳ ➺➯➻ ✠➵ ❯➲ ✞➵ ➛✌ ✾✹ ✽✻ ✒➵ ➸➳ ✩✣ ❼✕ ☛✣◆✘ ✝ ✼②✏♠✾✣❭♠ ❦➵ ➼➳ ➇✐➑✄➋ ❝➟ ➇✙➑✶➻ ❝➟ ➓ ➽➾✹➜➳❭➞✏➵✫✻➚➢ ➘ ➑✁➶♦➈ ➑✁➶♦➈ ✹ ➇✙➑✶➋ ➓ ➪ ➪ ✹ ➇ ➑✶➋❀➹ ➹ ➾➬✲✳✙✧✚✂☛☎ ❨✂☛★✾€✚◗☛☎✩☎✚✧✩ ✶✂✼❁ ❬◗☛★ ✻ ➴ ➘ ➺ ➋ ✓ ❨ ➋ ✻✚✹ ➇ ➑✶➻❯➹ ➪ ➓ ➑❲➶♦➈ ➺ ✹ ➇✐➑✶➻ ➻ ✻ ➹ ✹ ➺❨➻ ✻✏➴♦➷ ▲➽ ➙➮ ✓✎ ➺ ✲✻ ♠ ➛ ❻➞✒➟ ➪➛ ③➠➎➞✒➟ ❂➝ ♦➠ ✿➠ ❃✣❑❜❃✣❶✸■❏✳✶❑❜❁❖❃➈✳✶❣❜❲❬❀★❁✿❀★✹◗✵✿✷❅❁◗❑❤✷❥❃➷✺▲✺❖▼✥❑❤❑❤❁✿❁◗❲✚❁✿❀★✾✭✼❳✳❚✼❥✵✿✳ ✷❅❑❤✉❃€✫✭✬ ❯✺❖❑✘❛❀❖✺✔➍⑧✳✶✺❖❃ ✷❅❀★❦❏❃✘❀❬✵◗✹✖✾✣t ✹✿❀❴◆ ✵✿❑➷★❭✺❖❑❤❲❬■✣✾✣✵◗❀⑧◆✘✷❅✹✿✹◗✷❅❲❙✷❅✼❳✳✶❁✿✷❅✵✩❄€✺❖❑✘❀❖➍⑧✺❖✷❅❀★❃✘✵◗✹✖t ★t ▼✏❁✿❑❜❲➂❀★✷❅✵✿✱✣❀✔❁✚■❏✳✶❁❖✳✶❲❙❀✔✵✿❁✿✷❳✺➏❑❜❁ ❇✮ ❤❋ ✉✫✭✬ ❯ ➌❻➒✍✳✶❁◗✷❅✷❅❀❉✵✿❣❤✱✚❀✔❣❤❃✚❀✔✳✍❁✿❣❤✹✿❄⑧✳✶✵◗❁✿❁✿◆❺❑❜✷❳✷✯✳❚❃✣✹◗❦✣✹✿❘✍✷❅✼❅❲❙❀★❃✣✹✒❀★✷❅✼❳❘➈➌❻✳✶✳❚✷❅❁ ✵✿✵✿★✱❙✷❅✬ ❣❤❀✻✳✍✺✽✱✭❑❤✷✯❁✿❘❜❁◗✱✚❀★✼❳■❏✳✶❑❜✵◗✷✯✹✿❑❜✷❅✵✿❃ ✷❅❣❜✳❚❀✻❁✿❀✻✺❖❑❤✳❚❁◗✹✿❁✿✹✿❀★✷❅✼❳❘❜✳✶❃✣✵◗❀✖✷❅❑❤◆✚❃✦✳✍t❜✵✿◆✘✱✣✷❅✹✿✷❅✹◗✹❻✷✯❲❬✳✶✹◗✷❅✹✿✼❥✷❅✳❚❘❤❁✿❃✣✷❅✵✩✹✸❄✻✳❛✺❖❑✘◆✘❀❖✷❅✹◗➍⑧✹✿✷❅✺❖❲❙✷❅❀★✷❅❃✘✼❳✳✶✵✒❁◗✵◗✷✯✵✩✱❏❄✍✳✶✵♦✺❖❑✘✷✯✹✒❀❖➍⑧✺❖✼❅✺❖❑❜✷❅✹✿❀★❀❻❃✘✵✿✵✸❑✚✵✿✱❏✮ ✳❚✥✵❩❲❙✷❅✹❩❀✖✳❚✺❖❃✣✼❅❑❜✷❅❃✣✹✿❀✻❘❻✵◗✵✿❑❉✱✴✳✶⑦★✵✒❀★❁◗✵◗❑❏✱✣✬♦❀❻②❩❣❤✳✶✳✶❁◗❁◗✷❥✷❥✳❚✳❚❦✣❦✣✼❅✼❅❀★❀★✹✹ ❃✣❀★❘✘❢✩✳✶❃€✵◗✷✯❣❜✹◗❑❤❀❉❲❬✺❖❑❤❀❛❁◗❁✿✳✶❀★■✣✼❳■✭✳✶✵◗✼✯✷❳✷❅✺★❑❤✳❚❃€✵✿✷❅✳✶❑❤❁◗❃✭❀❼✹✖✳❚t✴✹✿✾✣✹◗✹✿✷✯❀✔❘❜❁✿❃✣✹➏❀✖◆❬❲⑧✵✿✳❴✱✭❄✚❀❉■✣✹❇❁◗✳❚❀❖❲❙▼✏❀★❀✻❁❉✱✭✵◗❑❫✷✯❘❜✱❙✾✣✹✿✹◗❀❙✷✯❲❬✺❖❑❜✷❅✼❥❃✘✳❚❣❤❁✿❀★✷❅✵✩❁◗❄❉✹✿✷❅❑❤❣❤❃✳❚✼✯✾✭▼✏❑❤❀❤❁◗✬ ❲✚✾✣✼❳✳ ✩✫✣✬❡❞ ✔t✴➌❻✱✣❀★❁✿❀✚❣❤✳❚❁✿✷❳✳✶❦✭✼✯❀✔✹✻➌❻✷❅✵✿✱➷✳❬✱✣✷❅❘❤✱€■✴❑❤✹◗✷✯✵◗✷❅❣❤❀❉❑❜❁ ✮ t ýỵỵ ỵ ỵ ✉✫✭✬❡♠ ✮ ✉✫✭✬❡♠ ✳✵✿▲✱✭❘❤❀❉✷❅rs❣❤✵✿❀✔❀★❑❤❃❛✼❅✵✿❀★✷❳■✭✺❖✺❖✼❅✱✣❀❻✾✣❑❤✹✿✵◗❃✣✵◗✱❏❀★❀❈✳✶❁✿✵♦✷❅❃➈❃✣❃✣✾✭❘✍❑❤❲✚✵✒✷❅✹✦❦❏✳✶➌✸❀★✼❅❁❻✼✣❑❤❑❚❑❚❁◗▼✹✿▼❩❀✸✵◗✳➏✱✣✵✿✱❏❀❻■❏✳❚❀★❣❤❃❛❁◗✳✶✹✿❁◗✾✭❑❜✷❳❃€✹✿✳✶❀★❦✣✼❅✷❅✼❅❀★✹❻❀★✹◗✹✢❑✶✹✖t❜▼✏✹✿✵◗✱✭✹✿❀★✷❅❑❤❃€❃❏✾✣✺❖✼❳✾✣❀❻◆➏✹◗✷❅❀★❦✴✵✦✼❅❀❻❀★✱✭✹✿✷❥✷✯✹▲◆❺❃✴❀★✷✯✺❖❃❫✹✢✼❅✾❏✵✿✵◗◆✘✱✣✱✣❀✖❀✸❀❛◆➏✾✣✺❖✷❅✹✿✼❅❃✚❀✽✾✣▼✏✹◗✵✿✾✣✵✿✱✭✼✣❀★❀✻❁◗✷❅❃✘✷✯✺❖❃✭▼✏✼❅❑❜✾✣❘❙❁✿✹✿❲❫❑✶✵◗❀★▼✒✳✶❁✿■✴✷❅✵✿❃✣✷❅❀★❑❜❘❛❑❤❃✻■✭✳❚✼✯■✣❃❏❀➏❁◗✳✶❑✶✳❤✼❅❣➈❄✘✺★✷❳✺❖✹✿◆✘✷❅❑❜✹❴❀❴❁❇✬✦◆✍◆✘⑥✲✷❅❦✘❃✣❄❂❘✚❣❤❑❜✳❚✵◗❁✿✵✿❑✚✷❳✱✣✳✶❀✔✵✿❦✭✱✣❁✒✼✯❀✔❀♦❣❤✷✯✳✶❁✍✵✿❁◗✱❏✺◗✷❥✳❚✳❚✱❏✵✒❦✣✳✶✼❅✷❅❁❖❀★✹✒✳❤✹✖✺❖❲❙✬ ✵◗❀★✣❀✖❁✿✳❚❑❜✷❅❃✣❁✦✹✿✵◗✷❅❀❖❃✣✷❳④❏✺❖❘❤✹✖✳✶✼❅t✴❲❬❀★✹✿✹◗✾✴✹✦■✣✺✿✼❅✵◗❀❤✱❑ t ✳✶✺❖✼❅✹✍✾✣✳✶✹◗✵✿❘❜❀★❀❤❁◗t✴✷✯❃✭✱✣❘❙❀★✷❅■✣❘❤✱✘❁◗❑❺✵✖✺✽t✭❀★➌❩✹✿✹❴❀✔✬✷✯❘❜✱✘✵✖t❷✳✶❃❏◆❬✹◗❑❙❑❤❃❽✬✻➁✘✾❏✺◗✱ ✘✷❅❃❏◆❫❑❚▼ ◗✵✿❁❖✳✶✹✿✱ ❙❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀✍✹✿✱✣❑❜✾✣✼❳◆❬❦❏❀➏❘❤✷❅❣❤❀✔❃⑧⑦✔❀★❁✿❑❫➌✸❀★✷❅❘❤✱✘✵✖t✭❀❖④❏✺❖✼❅✾❏◆✘✷❅❃✣❘❙✷❅✵✸▼✏❁◗❑❤❲❾✵◗✱✣❀ ộờ ỳữứ ùừ úụùừữ ùứủù ừữú ỵ ý ỵ ý ự ỵ t ỵ ý ỵ ỵýý ➌✸❀★✷❅❘❤●❻✱✘✱✣✵✻❀❈✳✶❲❙❃❏◆✈❀✖✳❚✱✣✹✿❀★✾✣✷❅❁◗❘❤❀★✱✘❲❙✵❴t✣❀★✼❳❃✘✳✶✵▲✵◗✷✯✾✣✵◗❃✣✾❏✷❅◆✘✵✻❀✍✾✣✳✶✹◗❃❏❀✖◆❬◆➫✼❅✺★❑❤✳✶❃✣❃➷❘❜✷❅✳ ✵✿❷✾❏❀✖◆✘✺❖❀✍✵✍✺❖✵✿❑✘✱✭❑❤❀ ❁❖◆✘✺❖✷❅✼❅❃❏✾✣✳✶✹◗✵✿✵◗❀★❀★❁◗✹ ✷❅❃✣✥❀❤❘€✬ ❘❏✳✶✬❅❃❏t❤✳❚➌❻✼✯✱✭❄✘✹◗❀★✷✯❃ ✹❴✬ ✺❖✼❅✭✾✣❑❤✹◗❁▲✵✿❀★❀❖❁◗④❏✷✯❃✭✳✶❘✚❲❬✱✣■✣❑❤✼❅❀❤✾✣t❏✹◗❀★✺◗✹✱❏✔✳❚t❷❃✣✳✶❘❤❃❏✷❅❃✣◆❬❘❬➌✸❲❙❀✖✳✶❀✖✵◗✳❚✱✣✹✿❀★✾✣❁❻❁◗❀★✵✿❲❙❀✔❲❙❀★❃✘■✴✵❻❀★❁❇✾✣✳❚❃✭✵✿✷✯✾✣✵◗❁◗✹✖❀❤t✴✬ ✹✿✾✴✺✿✱ ✳✶✺❖✼❅✹✍✾✣✺◗✹◗✱❏✵✿❀★✳✶❁◗❃✣✷✯❃✭❘❜❘⑧✷❅❃✣✹◗❘✚✵✿❁◗▼✏✾❏❁◗❑❤✺❖❲➔✵✿✾✭❁✿❲❙❀❤✬✚❀★✵◗❢✩❀★❃ ❁✿✹▲❘❤✵✿❀★❑❬❃✣❀✔✷✯❁❇❃✴✳✶✺✿✼✩✱✭t❷❀★❀✽✹▲④❺▼✏■✭❑❤❁✿❁▲❀★✹◗✱✣✹✿❀★✷❅❃✣✷❅❘❤❘ ✱✘✵✖✳✈t✴❣❤❑❜✳✶❁❻❁✿▼✏✷❳❁◗✳❚❑❤❦✣❲ ✼❅❀❉➈✷❅❃€✷❅✼❅❑❤✹✿❘❜❲❫❁❇✳❚✳✶❲❙✼❅✼❅❀★✹✒❁❻✵◗✾✣❑❙❃✣■✴✷❅✵✿❑❤✹▲✾✣➌❻❃❏◆❺✷❅✼✯✹✻✢✼❅▼✥❀✖❑❤✳❜❁✻◆❫➌✸✵✿❀★❑❫✷❅❘❤✳❙✱✘✵❴✼❳t✣✳❚❁✿❲⑧❘❤❀✔✳❴❁✻❄✚❁❇✼❅✳❚❀✖✳❜❃✣◆❫❘❤❀❈✵✿❑❫▼✏❑❜✳✚❁✻✵✿❣❜✱✴❀★✳✶❁✿❄€✵✍❣❤◆✘✳✶✷ ❷❁◗✷❥❀★✳❚❁✿❦✣❀★✼❅❃✘❀❤✵ t ✾✣●❻✳✶❃✴❃✣✱✣◆➏✷❅✷❅✵◗✹✍✹✖✵✿t✣✱✘✷❅✹✻✵◗✾✣✱✣✹❩■❏❀❉✳❚✳▲❁✿◆✣✼❳✵✿✳✶✳✶✷❳✺❖✵❖❁◗✾✭✳❉❘❤✼❥❀★✹◗✳❚❁✒✱✣❁✿❀✼❅❑❤❄❫✾✭❀✖✼❥✾✣✺✽◆❬✹✿✵❩❀✽❦✴❑❜▼✏❀✍✾✣❃❛✼✒✹✿✵◗✵❇➌❻✱✣✳❚❀❻✱✣❃❏❀✔◆✣❁✿❃ ❀★✳❚✹◗❁❇✾✣❘❜◆✘✷✯✼❅✷❅❣❜✵✿⑦★✷❅❀★❀✖❃✣❃€◆➎❘❛✬❩❃✣✺✽➁✘❑❬✼✯✾✭✵❖■✣✹✿✳✶✵✿❁✿❃❏❀✔✷❅◆✣❑❜❁✿✷❅✳❚❁ ❃✣❁❇❘❉✘◆✘❃✣✷❅✹◗⑦★❑✶✵✿✷❅❁✿➌❻❃✣✾✴❘➏✼❅✺❖❀✖✵✿❲❙◆❺✾✣❘❤❀❴❁◗❀❉❀❤✳✶✬✸✹✿❑❚✾✭▼❩●✢❁✿✵✿❑✻❀★✱✣❲❬✱✣❀✚❀★❀★◆✣✼❅❃✘■❙✳❚✵✿✹❻✵❇✳❴✳✣❣❜✳✶✬❉❑❤✵✿✵◗✷❳➃s❀★◆❉❲❙❑✶◆✘➌❩■✭❀★❀✔■✴✵✿❣❤✹✸❀★❀★❃❏✵✿❁❴❑✚◆❺t❷❀★❘❤✷❅❃❏❃€✷❅✺❖❣❜❀❉✹✿❀❂❑❜❑❜✳✶❲❙❃❛✼❅✼✴❀❛✵◗❣❤✱✣✳❚✳✶❀✻■✣❁◗✷❥■✣✺◗✳❚✱✣✼❅❦✣✷❳❑❤✺★✼❅✷❳❀★✳✶✺❖✹❻✵◗❀❻✷✯✳✶❑❜❑❚❃❫❃✣▼ ✹✖❲❬❀✖t✭❵❜■❏❀✖✾❏✳✶❀✔✳✶❑❤✹◗✼❷✾✣■✣➌✸❁✿✼❅❀➏❀✔❀★❲❙✷❅❲⑧❘❤❀★✱✘✳❴❃✘✵❴❄ ✵ ✬ ✷❅❦❏❃✘✳❚✵✿✹ ❀★❤❃✘❀✔✵✿✵✿✷❅❦❏❑❜✳❚❃❏✼✯✳✶❽✼❅✼❅■✣❄➷✼❳✳❴➌❹❄❤❀★✳❚❁❻❃✘✵✚✺★✳❚✵✿❃❏❑➷◆✘✷❳❘❤◆✣✷❅✳✶❣❜✵◗❀⑧❀★✹✖❲❬t✭❑❤❑❤❁◗❃✣❀⑧❀✍➌✸❲❫❀★✳❴✷❅❄❛❘❤✱✘✼❅✵✚✷ ❤❀▲✵◗❑➅✵✿❑✚✳➷❘❤✺❖✷❅❀★❣❜❁✿❀✻✵❖✳✶❲❙✷❅❃✲❑❜❁✿❀▲✹◗❀★➌❩✵❫❀★❑✶✷❅❘❜▼❉✱➈❣❤✵❻✳✶✵◗❁◗❑❛✷❥✳❚✵◗❦✣✱✣✼❅❀★❀❉✹➏❣❤✵✿✳❚✱❏❁✿✳❚✷❳✳✶❃✲❦✣✼❅❑❤❀▲✵◗✱✣✱✣❀★❀★✷❅❁✿❘❤✹❴✱✘✬ ✵✖✬ ✭❑❤❁✚❀❖④❏✳✶❲❬■✣✼❅❀❤t✒➌❻✱✭❀★❃✇✺❖✼❅✾✣✹◗✵✿❀★❁◗✷✯❃✭❘ ❲❙❀❴✳✶●✢✹✿❑❫✾✭❁✿✹✿❀★✵❖❲❬✳✶❃❏❀★❃✘◆✣✵✿✳❚✹✸❁❇◆✘▼✏❑❜✷❅⑦★❁❹❀✚✳➏❲❬❣❤❀✖✳❚✳✶❁✿✷❳✹◗✳✶✾✣❦✣❁✿✼❅❀✔❀ ❲❙❽❀★t✴❃✘✵✿✵✿✱✣✹❴t✦✷❅✹✻❑❜✺★❃✣✳❚❀❙❃⑧✺◗❦✴✱✣❑❤❀✍✷❳■❏✺❖❀❬❀✔❁✩✷❅▼✏✹❂❑❜❁✿✵◗❲❙❑ ❀❴✺❖◆⑧❑❜❃➈✳❚❣❜✹✸❀★▼✏❁✿❑❤✵➏✼❅✼❅✵✿❑✶✱✭➌❻❀✚✹✖✬❑❤❁✿✷❅❘❜✷✯❃✴✳✶✼✢❲❙❀✖✳❚✹✿✾✣❁◗❀★❲❙❀✔❃➈✵◗✹✍✵✿❑€✾✣❃✭✷✯✵◗✼❅❀★✹✿✹➏❣❤✳✶❁◗✷❥✳❚❦✣✼❅❀★✹✖✬❬➒✍✷❅❣❤❀★❃ ✮❜✬❻❶❻✳✶✼❳✺❖✾✣✼❳✳✶✵◗❀✍✵✿✱✣❀ ➷✕✘✜✣✛ ✜ ✑ ✴✌✥✎③✓❴✕ ❽✕ ❷✧✥✜✣✓✖✧ ✴✛ t t ✮ ✉✫✭✬❡q ➌❻✱✣❀★❁✿❀ ✳✶❁◗❀ ❲❙❀✖✳❚✹✿✾✣❁◗❀★✹❻❑✶▼ ✦t✴✳✶❃❏◆ ✷❅✹❩✵◗✱✣❀❙ÿ ➏❣❤✳✶✼❅✾✣❀✻❑❚▼ ✦t✭✷✉✬ ❀❤✬❅t ★✬ ❋✭✬❻❶❻✳✶✼❳✺❖✾✣✼❳✳✶✵◗❀✍✵✿✱✣❀ ✑✔✓✖✜✣✛ ❽✜✣✗ ❽✧ ❤✕ ➷✕✘✜❏✑★✎✢✗✶✕ ➷✕✘✛✦✓ t✶✺★✳✶✼❅✼❅❀✖◆ ❖✑ ❏✗✶✕ t✣✳✶✹✸▼✥❑❤✼❅✼❅❑✶➌❻✹✖t tt t t t t ỵ ỵ tt ỵ ý t ✫❖ ➝ ✹➜➳❭➞✏➵✫✻ ✫✻ ❣➽➾✹➜➳❭➞✏➵✫✻ ➝ ✹➜➳❭➞✓➵✸✻➚➢ ✹ ➽➾✹➜➳❭➞✏➵✫✻✏✻✓➱ ➹ ✹ ✸✻ ✹ ✲✻ ➷ ❊✹ ✚✻ ❨✹ ➝ ✹✿➳❭➞✏➵✫✻➚➢ ✶✎ ✲✻ ➹✦✃ ➽❀✹✿➳❭➞✏➵✫✻ ✃ ✁ ✄✂✆☎ ✶❁✿✮❝€✚◗❄✧✡➤✦€ ❬✧✯★✫❁◆❐✆✹➜➟✓➞✿➠✲✻ ❐☛✹✿➟✏➞❃➠✲✻➚➢ ✈✛ ➾✹ ➝ ✹➜➟✓➞❃➠✆✻ ✲✻ ➹ ✹ ✲✻ ♦✛ ✰✎ ❃⑤ ✿⑤ ❰ ✫Ï ✿Ð ◆⑩❍Ï ➙❒ ✐❮ ✖Ñ ✁★✫❁✏✧✯☎✩➀❂✂✆ ❹❳ ❄€✚✂☛ ✶✧❙☞✴➀☛✂☛☎ ✥✂✲✬✯ ✄✧ ỊĨ❩✙€✯  ❬☞✽✧❙✂✆★✫➥❆Ơs✂☛★❚❘❚✂✼❁✥❁✏✂☛★ ✉ ☛✗ ✥② ✝ ✰Ơ ✁★❚Õ✆◗✆Ư ✚Õ Ó☞ ✚❁❃✂✆★✵€✚✧ ✢ ✙✘✦✗ ❀✹ ❙✻ ✼✔ ▲✛ ➔✎ ✍✔ ➛✔ ▲✎ ×✛ ✏✎ ✶✎ ❯➳ ✢ ♠ ✩✣ ❪✘ ❐ ➋ ➇❣➈✿➋ ➞ ➷✶➷ ➞ ➇✐➓✲➋ ✥✣ ➢ ❝❷ ❆✘ ✫✗ ❷ ✹ ✃ ➇ ➈✿➋❊➹ ❆➳ ✲✘ ✥Ù ✙✘➃♠ ✽❐ ➋ ➺ ➋◆✃✩Ø✤✃ ➇ ➴ ➋❊➹ ➺ ➉❄➉✼➉ Ø❛✃ ➇ ➓✲➋✴➹ ➋❴✃✯Ø ❨✧❙✂✆★ ➺❨➋ ✫♠ Ù✲② Ú✯➑✄➋ ➢ Ó➳ ➺❨➋ ➋◆✃ ✻ ➺ ➢ ➓ ➈ ✹ ➇❣➈✿➋ ✹ Ø ➇ ➴ ➋ Ø ➉❄➉✼➉ Ø ✲✻ ➇✐➓✲➋ ✻ ✝ ✣ ➇✙➑✶➋ ➹ ❐ ➋ ➺❨➋ ✹ ✲✻ ➷ ✫❐ ➋ ✽Û ➋ ❦✹ ✃ ➇ ➑✶➋❊➹ ➺ ➋ ✃✻ Ü ✚✔ ❨✧❙☞ ❬✂☛★❼✂✽✬ ❄◗✆ ✑❩✽❁❃✧ ☞✲✧✯➀ ❬✂❂❁ ✥◗☛★ ✲➞ ✒➟♦➠➷➜ ▲➞ ✿➝✡➛ ✢➠❷➞✒➟ ✿➝ ✍➝ ✒➠ ✿➠ q ■✴❀★❁✩▼✏⑥s➁✘❑❜✵❖❁✿▼✏✳✶✵✿❲➔❃❏❀★❁❻◆✭✹✿✳✶✹◗✵❖✵❇✳✶❁❇✳❚◆❺❃❏❃❏✷✯◆✣⑦❴◆✣✳❚✳✶✳✶❁❇✵✿❁❖◆✘✷❅❑❜◆✘✷❅⑦✖❃€✷❅⑦✖✳❚✳✶❲⑧✵✿✵◗✷❅❑❤✷❅✳❴❑❤❃❫❄❬❃✦✹◗t✘❑❤✱✣❑❜❁✻❑❤❁❻❲❫✾✣➌❻✼❳✳❴◆❬✷✯❄❙✵◗❦✴✱✣❃✣❀❂❑❤❑❜✾✭✼❅✵✍❀❖✵❻▼✥❦❏✵❻✹✿✵❇❀✚✵✿✳❚❑➏❃❏✾✣✹◗◆✣✾✣❀❖✳❚✹✿▼✏❀★❁❇✾✣❁◗◆✘✼♦✹✖✷❅⑦✖✬✷✯❃➫✳❚✵✿✳❙✷❅❑❤❃❬■✴✳✶✷✯❁✿❃€✵◗✷❳✺❖✺❖❀✔✾✣❁✿✼❳✵❇✳✶✳❚❁✍✷❅❃ ✳✶■✣✳❚■✣■✣✼❅■✣✷❳✺★✼❅✷❳✳❚✺★✵✿✳✶✷❅✵◗❑❤✷❅❃✦❑❤✬✍❃✣✹❴●❻t✘✱✘➌❩✾✣❀❉✹✍✺❖✵◗❑❜✱✣❲❙❀ ■✣✺◗✾✣✱✣✵◗❑❜❀✻✷❳✺❖✵◗❀✚✱✣❀❛❑✶▼❩◆✘➌❻✷❅✹✿✹◗✱✭✷❅❀★❲❙✵✿✱✣✷❅✼❳❀✔✳✶❁❛❁✿✷❅✳✶✵✩❄❃❏◆ ✏❑❜✱✣❁❻❑✶✹✿➌➋✷❅❲❙✵◗✷➐❑ ✐ ✼❳❑✶✳✶▼✦❁◗❑❜✷✯✵✩❦❤❄ ⑨❖✢❀✖✺❖❦✴✵◗❀★✹✖✵✩✬✢➌✸●❻❀★❀★✱✣❃❫❀✔❁✿✵✿❀❉✱✭✳✶❀❂❁◗❑❜❀✻❦❤✳▲⑨❖❀✖▼✏✺❖❀★✵◗➌✲✹✖✬✒✳✶➒✍■✭■✣✷❅❣❜❁✿❑✘❀★❃❙✳❤✺◗✷❅✱✣❃✘❀★✵✿✹✸❀★❁◗✵✿❣❤❑❛✳✶◆❺✼➐✐✩❀ ✹❇❏✺★✳❚❃✣✼✯✷❅❀❴❃✣◆➏❘❉❣❤✵◗✳✶✱✣❁✿❀❂✷❳✳❚◆❺❦✣✷✯✹◗✼❅❀★✵❇✹✖✳❚t❜❃❏✵✿✺❖✱✣❀✻✷❅✹✒❦✴❀★✷❅✹✸✵✩➌✸✵✩❄✘❀★■✣❀★❃❫✷❳✺★✳✶❑❤✼❅❦❤✼❅⑨✽❄❉❀✖❦❏✺❖✵✿✳❚✹❴✹✿✬✢❀✖◆❬●❻✱✣❑❤❀✻❃✚❲❬✵◗✱✣❑❤❀❉✹◗✵③◆✘✷❅■✴✹✿❑❤✵❖✳✶■✭❃❏✾✣✺❖✼❳✳✶❀▲❁✒❦❏◆✘❀✔✷❅✵✩✹✿➌❩✵❖✳✶❀★❃❏❀✔❃⑧✺❖❀▲❀❴❲❙✳❤✺◗❀✖✱❫✳❚✹✿■❏✾✣✳✶❁◗✷❅❀❁ ✷❅✹ ✎ ✌✥✧ ✦✕✘✜✣✛ ❽✧✉✑✔✓✖✜✭✛ ✕ t✶➌❻✱✣✷❳✺◗✱⑧✷❅✹✻◆✘❀ ❏❃✣❀✖◆€✳❚✹ ✉✫✭✬❡① ➌❻✱✣❀★⑥▲❁◗❀ ❃✣❑❤✵◗✱✣❀★❁❻➌✸❀★✼❅✼❨✐ ✘❃✣❑✶➌❻❃❙❲❬❀★★✵✿t✣❁◗✳❚✷❳✺❻❃❏◆ ✷❅✹ ★t✴✳✶❁✿❀✍✵✩➌✸❑ ✘✐✿◆✘✷❅❲❙❀★❃✭✹✿✷❅❑❤t❤❃❏◆✘✳❚❀ ✼❏✴◆✣❃✣✳❚❀✖✵❇◆❫✳❈❦✘❑❤❄ ❦❤⑨❖❀✖✺✽✵✿✹✖✬ ✜✣✛ ✢✜✣✓✖✓❴✜✣✛ ✴✗ ✧✥✓★✤ ✌ ❽✧✉✑✔✓❴✜✣✛ ✕ ✉✫✣✬❅✮❴⑤ ▼✏✾✣❃✴✺❖♥♦✵✿❑❤✷❅❑❤✵◗❃❽✱✚❭ ✵✿✱✣❀✻➇✢✾✴✺❖✼❅✷❥◆❺❀✖✳✶❃❙◆✘✷❅✹◗✵❇✳✶❃✴✺❖❀✻✳✶❃❏◆✚❪ ✳✶❃✣✱❏✳❚✵✿✵❖✳✶❃✚◆✘✷❅✹✿✵❇✳❚❃❏✺❖❀▲✹❇✳✶✵◗✷❅✹✩▼✏❄❉✵◗✱✣❀❻▼✥❑❤✼❅✼❅❑✶➌❻✷✯❃✭❘❻❲⑧✳✶✵◗✱✣❀★❲❫✳✶✵✿✷❳✺❽❁✿❀❴❵❤✾✭✷✯❁◗❀★❲❙❀✔❃➈✵◗✹✒❑✶▼✦✳✍◆✘✷❅✹✿✵❖✳✶❃❏✺❖❀ ✮❜✬ ⑤✭❭✦●❻✱✭✷✯✹❻✹◗✵❇✳❚✵✿❀★✹▲✵✿✱❏✳❚✵✻◆✘✷❅✹✿✵❇✳❚❃❏✺❖❀❉✷❅✹❻✳➏❃✣❑❤❃✭❃✣❀★❘➈✳❚✵✿✷❅❣❤❀✍❃✘✾✣❲✚❦✴❀★❁ ❋✭✬ ✲⑤✣❭✢●❻✱✭✷✯✹❻✹◗✵❇✳❚✵✿❀★✹▲✵✿✱❏✳❚✵❻✵✿✱✣❀❉◆✘✷❅✹✿✵❖✳✶❃❏✺✽❀❉❑✶▼✒✳✶❃❫❑❤❦❤⑨❖❀❴✺❖✵✻✵◗❑❛✷❅✵✿✹◗❀★✼➐▼✒✷✯✹✻⑤ ỵ ỵ ỵ ✷❳✺✿✱❫✹◗✵❇✳✶✵◗❀★✹✻✵◗✱❏✳✶✵❻❘❜❑❤✷❅❃✣❘✚◆✘✷❅❁✿❀✖✺✽✵✿✼❅❄❬▼✏❁✿❑❜❲❝■❏❑❜✷❅❃➈✵ ♦✵✿❑✚■✴❑❤✷❅❃✘✵ ✧✥✛ ✚✑ ❷✧ ❽✧✉✑✔✓✖✜✭✛ ✕ ✷❅✹❻✳➏❘❤❀★❃✭❀★❁❇✳❚✼✯✷❅⑦✖✳❚✵✿✷❅❑❤❃❬❑✶▼✒❦✴❑❤✵✿✱€➇✢✾✴✺❖✼❅✷❥◆❺❀✖✳✶❃€◆✘✷❅✹✿✵❖✳✶❃❏✺✽❀❼✳❚❃❏◆❫❪€✳✶❃✭✱❏✳✶✵◗✵❇✳✶❃€◆✘✷❅✹◗✵❇✳✶❃✴✺❖❀❤✬✢❢✩✵❻✷❅✹✻◆✘❀ ❏❃✭❀✖◆€✳✶✹ ✉✫✣✬❅✮❜✮ tt ỵ ❦✴❀❛✺❖❑❤❲❬■✣✾✣✵◗❀✖◆❙✳❚✹✸▼✏❑❤✼❅✼❅❑✶➌❻✹✖✬ ✉✫✣✬❅✮❴❋ ✰➷❀★✷❅❘❤✱✘✵◗✷✯❃✭❘❛✺★✳✶❃➫✳✶✼❅✹✿❑➏❦❏❀❉✳❚■✣■✣✼❅✷❅❀✖◆❬✵✿❑➏✵✿✱✣❀❛❪ ✳✶❃✣✱❏✳❚✵✿✵❖✳✶❃⑧✳❚❃❏◆❫❪❫✷❅❃ ❤❑✶➌❻✹ ✘✷✦◆✘✷❅✹✿✵❇✳❚❃❏✺❖❀★✹❴✬ é❻ê ❩ê ➷ñ✿ú▲ï③ø❺û ✒ï✢ø✣ñ◗ï ừữú ỵ ỵý ý ỵ ý ỵ ✷❅⑤➏✹✻✷❅■✣❃❏⑥❁◗◆✘❀★✷❳✹✿✺★❀✔✳❚❃➈✧✥✵✿✛③✵❴❀★✬✚✜✭✹▲✗✶✵✿➒✍✤ ✱❏✷❅✳❚❣❤➈✵❻❀★✜✭❃❫✵✿✗✶✱✣✧✏✵✿✜❀❉✱✭❀❛■✴✌✥✳✶✕❣❤✵✿✳❚✷❅✱❏❀★❁✿✷❳✳✶❃✘✳✶✹❻✵✻❦✣❑❜◆✘✼❅❀➏❃✣❑✘✼❅❀★ý★❄❙✹▲ÿ ✵✩❃✣➌✸❑❤❑✚✵❴✬✢✍✹✿●✢✵❖◆✘✳✶❁✿❀★✵✿❀✖✹❇❀✔✳❚✺✽✹✖❁✿✵✿❭❻✷❅✷❅❦✣❃✣⑤✚✷❅❘✚❃✣❑❜❘⑧❦✣❁❉✷❅❃❏✳❬✮❤✳❚t✣■❏❁✿➌❻❄✚✳❚✱✭✵✿❣❤✷❅❀★❀★✳✶❁✿❃✘❁◗❀❛✵✖✷❳✳✶t✭⑤✈❦✣▼✏❑❜❲❙✼❅❀★❁✻✹✻❀✖✷❅✳❚✳❚❃✣❃✣✹❻✹◗✹✸✵❇✷❨✳✶▼✢✵✿❃✴✱❏✵✿✺❖✱✣✳❚❀❤✵✻❀✔t✒❄ ✵✿✮❈✱✭✳❚❀❉✷✯❁✿❃✴❀❉❣❤◆✘✳✶✷❅✷❳❃✘❁◗✺★✷❥✵✿✳✶✳❚❀✔✵◗❦✣❁✿❀★❣❤✼❅✹✍❀✻✳✶✵✿✼➐✷❅✐✩✱❏✹✻✹❇✳❚✺★✳✶✵✻✳❚❦✭✼❅✵✿✹✿❀✖✱✭❀★◆❙❃✘❀❛✺★✵✖■❏✳❚t❷✳❚❃€✳❚✵✿❃❏✷❅✼❅❀★❀✖◆➫❃✘✳❤✵✻◆❬✮✍✹◗❲❙✵◗❲❙❑✚❀✖❑ ✳❚❲❙❤❃✣✷❅❀★✹❻✹✿✹❴✼❅✵✿t❏❀✖✱❏✳❜➌❻✳❚◆✘✱✭✵✻✷❅❃✣✷✯✼❅✷❅❘❀✵ ✺❖✼❅✾✣✹◗➊▲✵✿❀★❃✣❁◗❀✍✷✯❃✭✳✶❘❙■✣❁✿■✣❀✔❁◗✹✿❑➈✾✣✳❜✼❅✵✿✺✿✹❴✱✚✬✒✷❅●❻✹✒✵◗✱✣❑❛❀✔❁✿✺❖❀❖❑❜▼✏❲❙❑❜❁✿■✣❀❤✾✣t✴✵◗❲❬❀✻❀★✳❉✵✿✱✣◆✘❑✣✷❅✹✿◆✘✹◗✹✸✷❅❲❙✹✿■✴✷❅✼❳❀✖✳✶✺❖❁✿✷ ✷❅✵✩✺❼❄▲✵✿❲⑧❑✚✳✶❦✣✵◗❁✿✷❅❃❏✷➐④❉✳❚❁✿▼✏❄⑧❁◗❑❤◆✭❲✞✳✶✵❇✵✿✳➏✱✣❀▲✳✶❁◗❘❤❀✍✷❅❣❤❃✣❀★❀✖❃✚✺❖❀★❦✭✹◗✷✯✹❇❃✴✳❚✳✶❁✿❁✿❄❫❄✚▼✏◆✣❑❜✳❚❁✻✵❇✺❖✳✣❑❤✬❽❲❬❢✥▼③■✣✳✶✾✣✼❅✵◗✼✣✷✯❃✭❦✭❘❛✷✯❃✴◆✘✳✶✷❅❁✿✹✿❄➏✹◗✷✯❣❤❲❬✳✶❁◗✷❅✼❥✷❳✳❚✳✶❁✿❦✣✷❅✼❅✵✿❀★✷❅❀★✹❩✹❴✳❚✬ ❁✿❀❻✵◗✱✣❑❤✾✣❘❜✱✘✵ ❑✶❀✖❵❜▼✒✾❏✳✶✳❚✹✒✼❩✱✴✮▲✳❴❣➈▼✏❑❜✷❅❃✣❁❻❘❈❦❏✵✿❑❜✱✣✵✿❀✍✱❫✹❇❑❤✳❚❦❤❲❙⑨❖❀❴❀❻✺❖✵✿➌✸✹ ❀★✷❅✒❘❤✳❚✱✘❃❏✵✖◆t❜➌✸❺❀✻t ✱❏▲✳❴✷❅❣❜✹❻❀❂✵✿✱✣✳❉❀❉❋ ❃✘✐✉❦✘✾✣❄❜❲✚✐➣❋❈❦✴❀★✺❖❁✸❑❤❃✘❑✶✵✿▼✒✷❅❃✣❣❤✳✶❘❜❁◗❀★✷❳❃❏✳✶✺❖❦✣❄✚✼❅❀★✵❖✹✸✳✶✵✿❦✣✱❏✼❅❀❤✳❚t✘✵✻●✒❀✖✳❚❵❜❦✣✾❏✼❅✳❚❀✻✼✒✫✣✮▲✬❅✮❤▼✏❑❤t❜❁❻➌❻❑❜✱✣❦❤❀★⑨❖❁◗❀❀✖✺❖❈✵ ✷❅✒✹❩❦✭✵◗✾✣✱✣✵❻❀✍✵✿❃✘✱❏✾✣✳❚❲✚✵❂❦❏✳❚❀✔❁✿❁✒❀❉❑✶⑤❈▼✦▼✏❣❤❑❤✳❚❁❻❁✿✷❳❑❜✳✶❦❤❦✣⑨❖✼❅❀✖❀★✺❖✹♦✵ ✵✿❺✱❏t ✳❚✵ ✷❅❀✖✹✻❵❜✾❏✵◗✱✣✳❚❀❛✼③⑤❼❃✘✾✣▼✏❑❤❲✚❁❻❦✴❦✴❀★❑❤❁▲✵◗❑✶✱⑧▼❩❑❜❣❤❦❤✳❚⑨❖❁✿❀✖✷❳✺❖✳✶✵◗❦✣✹ ✼❅❀★✒✹❻✳❚✵◗❃❏✱❏◆ ✳✶✵✍❺✬✢❀✖❵❜●❻✾❏✱✭✳❚❀❉✼✒✵✿⑤➏❑❜▼✏✵❇❑❜✳✶❁❻✼❷❃✘❑❤✾✣❦❤⑨❖❲✚❀✖❦✴✺✽✵ ❀★❁✸✒❑✶❦✭▼✢✾✣❣❤✵✍✳✶❀✖❁✿✷❳❵❜✳❚✾❏❦✣✳✶✼❅✼❻❀★✹❩✮✍✷❅✹▼✥❑❤❽❁✻t✘❑❜➌❻❦❤✱✣⑨❖❀✖❀★✺❖❁✿✵❀ ✣t❷✳✶❃❏◆ ✷❅✹✻✵◗✱✣❀➏❃➈✾✭✬ ❲✚❦❏❀★❁▲❑✶▼❩❣❤✳❚❁✿✷❳✳✶❦✭✼✯❀✔✹❻✵✿✱❏✳❚✵ ✵✿✱✭❀★❁✿⑥❝❀❉✔✷❅❦✭✹❻✬❛✷✯❃✴❃✣➁✘✳✶❑✚✷❅❁✿❲❙❄■✭✷❅❁✿✼❳❣❤❀❖✳✶▼✏✳✶❁◗❀✔❁✿✷❅❁✿✵✩✷❳❀★✳❚❄❛❃❏❦✣❦❏✺✽✼❅❀❛❀❛✳❚✹✿✷❅❑❜❀✖✹ ❃⑧◆ ✑✔➌❻❑❤✤ ❃➫✱✭✷❥✹✿✺◗➷❄✘✱❬❲❬✕✘❑❤✓✖❲❙✾✣✗✶✵❖✧❀★✺❖❬✵◗❑❤❁✿❲❬✷❨✷❳▼❻✺▲❀✻❦✴❦✣✹✿❑❤✷❅✱✭❃❏✵✿❑❤✱➷✳✶✾✣❁◗❄⑧❑❚✼❳◆❬▼✻❣❤✷❅❦❏✳❚✵✿❀❉❁✿✹❉✷❳✳✶✺❖✹◗❑✣❦✭✵❇✳✶◆✘✼✯❀✔✵◗❀❴✹✻❀★◆€✹✚✷❅✹❂✳✶✳✶✹✻✺★❁✿❀❬✳❚⑤❈✼❅✼✯❀✖❑❤❀❴❵❜❁❉◆ ✾❏✮❜✳✶✧✥✬✒✛ ✼❅✼❅✘❄€➊✻✜✣❃✭❣❤✗✶❀❉✳❚✧✥✜✣✼✯✹✿✾✴✛✦✾❏✳✶✓✚✺◗❦✣✱❫✼❅✑✔❀✚✧❀❖➷④❏✳✶✳✶❃❏✧✥❲❬✌✏◆➷✜✭■✣✗✶✺★✼❅✧❳✳❚❀❂✓★❁✿✤ ❁◗✺❖❄➷❑❜✷❅✾✣❃ ✵✿✼❳✱✣◆✚✵◗❀✚✱❏❦✴✳✶✹❖❀❙✵▲✳✶❲❙ÿ✵✿✱✣❀✚❀✚✍➌✸❁◗❀★❀★✳❚✹✿✷❅❃❏✾✣❘❤◆ ✱✘✼❅✵❉✵❴t✦◆✘✔ÿ✵◗❑✘✱❏❀★✹✍✳✶✵❉✍❃✣✷❅❑❜✷❅✹❴❃ ✵ t ●✸■❹❸✐■ ❯▼❆❉ ❈❺❼❻❈❇ ✵❇✤❖ ❆❏❈❑ ❆❋✺❖ ❀❽✦❇ ❈❇❊❏◆▼ ✫❖ ➡✹ ✙✻ ✚✌ ❯Ý ✝ ✿✘ ✝ Þ✘ ìò õ ➴ ✿✎ ➷❄➷✼➷ ➞ ➇ ➑❹➍ ✻ ✹ ✃ ➇✙➑✥➈ ➇✲à✆➈ ✃ ➴ ➹ ➯➠➙➢â✹ ➇ à☛➈ ➞ ➇ ➞ ➴ ❯❧ ➷ ➷✼➷ ✼ ✤ã✏✣ ✖❞ ➝ ✹➜➟✓➞❃➠✆✻❆➢ ✃ ➇✐➑✥➈ Øá✃ ➇✙➑ ➴ ➞ ➇ à✏➍ ✻ ➉✼➉❄➉ Ø✤✃ ➇✐➑❹➍ Ø ✢ ❬✣ ✝ ♣✖ä❀✘ ➇✲à ➴ ✃✩Ø ➹ ✝ ✲✻ ➇✽à✏➍ ✃ ➹ ✹ ✲✻ ✹ ❄✻ ➷ ❄❵ ➝ ✹✿➟✏➞✚➟✥✻❆➢ ✐❵ ➝ ✹✿➟✏➞❃➠✲✻❆➢ ➝ ✹✡➠✆➞✚➟✥✻ ➝ ỗ ố ỉ ố ✡★✵✧✚é✩❩✙✂☛  ✶❁✿✮ ☛✎ ✖♣✵✣✙❜ ✹ ➷ ✚✌ ➉❄➉✼➉ Øá✃ ➇✐➑❹➍ ➝ ✹✿➟✏➞❃➠✲✻✈æ ❧ ➇✽à✏➍ ✃ ➴ ➹ ❀➁ ✝ ➇✽à☛➈ ✃✯Øå✃ ➇✐➑ ➴ ➹ ➇✲à ➴ ✃ ➴ ➹ ❯➟ ❈è ✝ ✯♣ Ó✘ ✚✌ ➝ ✹➜➟✓➞✿➠✲✻✖➢❛✹ ✃ ➇ ➑✥➈✖➹ ➇ à✆➈❂✃ ê✠Ø✤✃ ➇ ➑ ➴ ➇ ➴ ✃ ê✖Ø ➹ ➉❄➉✼➉ Øá✃ ➇ ➑❹➍❯➹ ❝ì ➈✏ë ➞ ➇ à✏➍✵✃ ê ✻ ê ✰ì❊➢ ✰ì✴➢ ✜ƯĨ✧ ✶✪✼❘✲❁✏✧✚☞ ➝ ✹✿➟✏➞❃➠✆✻➼➢ ß í ➈✆✃ ➇ ➑❬➈✖➹ ➇ à✆➈❂✃ ➴ í Ø ➴ ✃➇ ➑ ➴ ➹ ✙✎ ❃⑤ ❬ỵ ï ❡Ï ➇ ➴ ✃➴ Ø ➉✼➉✼➉ Ø í ➇ à✏➍❭✃ ➴ ➍❣✃ ➇ ➑❹➍❊➹ ✹ ✲✻ ➷ ✓✎ ✠Ñ ✩✮ ➸✧➛❁✿☎ ❬€ ❯✂ ✩✮ ➸✧➛❁➜☎ ❬€ ✬ ✁★✵✂☛☎✯✮❨➀❂✂✆☎ ❬✂✲✬✯ ✄✧ ✢ ✾✗ ✢ ➸◗❂Õ✆✧✯☎ ✽✎ ✍✌ ➙ð ❀➟ ➯➠ ❣ñ ❊➟ ❝➟ ▲➟ ➯➠ ❣♠✾♠ ❆➁ ✺➠ ❭ị ➝ ✴➠ ✴➁✰➢×ð Ø đ Ø ị Ø ➝ ✝ ❨✂☛ ✄✧ ✪✲✧✩★✵☞✽✧✩☎ ◆✗ ❬♠ ➡❱❄✧ ➸✂✆ ✄✧ ✫ ➛ ❻➞✒➟ ➪➛ ③➠➎➞✒➟ ❂➝ ♦➠ ✿➠ ❆❅❈❇❊❉ ❑❜✮ ❦❤⑨❖❀✖✺❖✵ ⑤ ✹✿✾✣❲ ❆❋❍●✸■ ❆❏❈❑ ❆❋✤❇ ✺❇▲❏◆▼ ✫❖ ✈➠ ❤❑ ❦❤⑨❖❀✖✺✽✵ ✹✿✾✣⑤✮ ❲ ●✒✳❚❦✣✼❅❀❂✫✣✬❅✮❜❭✦⑥❧✺❖❑❜❃✘✵✿✷❅❃✣❘❤❀✔❃❏✺❖❄❫✵❇✳❚❦✣✼❅❀❻▼✏❑❜❁❻❦✣✷❅❃❏✳✶❁◗❄✚❣❤✳✶❁✿✷❳✳❚❦✣✼❅❀★✹✖✬ ✺◗✺❖✱❏❑✘❀❖✳✶➍⑧❃✭❘❤✺❖❀✻✷❅❀★➌❻❃✘✵▲✱✭❀★✷✯✹❻❃❙✵◗✹◗✱✣❑❤❀ ❲❙✑★❀❻✧ ❑❜❁❩✢✳✶✌✏✼❅✕ ✼✣❑❚➷▼✦✵✿✜✣✱✣✓ ❀▲③❦✣✧✥✷❅✛❃❏✳✶❁◗❄❛❷❣❤✕ ✳❚❁✿✷❳✳✶❦✭✧✥✕✘✼✯❀✔✛✦✹❩✓ ✳✶t➈❁◗◆✘❀❂❀ ✺❖❏❑✣❃✣◆✘❀✖❀✖◆❫◆❬✷❅❃◆✘✷ ✉✫✣❀✔✬❅❁✿✮❴❀★❊❃✘★✵✿✬✼❅❄✘✬ ✣❑❜❁✒✷❅❃✘❣❤✳✶❁✿✷❳✳❚❃➈✵❽✹✿✷❅❲❙✷❅✼❳✳✶❁◗✷❅✵✿✷❅❀★✹✖t❴✵◗✱✣❀✻❲❬❑❤✹✿✵✢➌✸❀★✼❅✼➐✐ ✘❃✣❑✶➌❻❃ ✉✫✣✬❅✮❴❊ ✳✵✿✶✱✭❃✴❀❻◆ ỵ t t ýỵỵ ý tt tỵ t t ýỵ ỵ ũ ựự ❀✚✿✹◗✾✣✷❅❘❤❃❏❃✣✳❚✷ ❁✿❄➫✺★✳❚❣❤❃✘✳✶✵❛❁◗✷❥✵◗✳❚✱❏❦✣✳✶✼❅❀❃ù❏✬❬✵✿✱❏●❻✳❚✵❛✱✣❀✚❑❚▼❂✹◗✷✯✵✩❲❬➌✸✷❅❑€✼❥✳❚⑦★❁✿❀★✷❅✵✩❁◗❄❙❑❤✹ ❦✴✳✶✩✳€✹✿❀❴◆➷❃✭❀★❑❤❘➈❃➷✳❚✵✿✷❅✹◗❣❤✾❏❀✚✺◗✱➅❲❫❣❤✳✶✳❚✵❇❁✿✺◗✷❳✱ ✳✶✔❦✣✬➷✼❅❀★➁✘✹✍✾❏✷❅✹❛✺◗✱ò✺★✳❚✳ ✼❅✼✯❀❴✿◆❦✣✷❅❃❏✛ ✳❚✴❁✿✛✢❄ ✧✏€✛ ✘❣❤✳❚✜✣❁✿✗✶✷❳✧✏✳✶✜✭❦✣✛✦✼❅❀✓ ✑✔✉✫✭✧ ➷✬❅✮★❯✧✥✌✏✔✜✭t❤✗✶➌❻✧✏✓❖✱✭✤ ❀★❁✿✬ ❀✍✣✵✿❑❜✱✭❁❉❀❂❃✣❃✘❑❜✾✣❃✣❲✚✷❅❃➈❦✴❣❤❀★✳❚❁✒❁✿❑❚✷❳✳✶▼③❃✘❃✣✵✍❀✔❘➈✹✿✷❅✳✶❲❬✵◗✷❅✷✯❣❤✼❳✳❚❀✻❁✿❲❫✷❅✵✿✷❅✳✶❀★✵❖✹❴✺✿t❏✱✭✵◗❀★✱✣✹✖❀❙t ❲❬t✘❑❤✷✯✹❻✹◗✵❂✺❖❑❜➌✸❃✣❀★✹✿✼❅✷❳✼➐◆✘✐ ✘❀★❁◗❃✣❀✖❑✶◆❬➌❻✾✣❃➷❃✣✺❖✷❅❲❙❑✘❀❖■✴➍⑧❑❤✺❖❁◗✷❅✵❇❀★✳❚❃✘❃➈✵➏✵✸✷❅✳✶✹❉❃❏✵✿◆✈✱✣✵✿❀ ✱✘✾✣✹✸✜ ✷✯✹✸✜✣✷❅❘❤✗ ❃✣❑❜❁✿❀✖❷◆✈✕ ✷❅❃❙✵✿✱✭✧✥✕✘❀❂✛✦✺❖✓ ❑❜t❷❲❙◆✘■✣❀ ✾✣❏✵❖❃✣✳✶❀❴✵◗◆➅✷✯❑❜✷❅❃✦❃ ✬ ✉✫✣✬❅✮✔❯ ◆✘❀★✹❖✺❖✰✲❁✿✷❅❦✴✱✭❀✖❀★◆❃✚❦❏✷✯❃❫❑❜✵✿➁✘✱✚❀✖✺❖✹◗✵◗❄➈✷❅❲❬❑❤❃ ❲❙✫✭❀★✬ ✵◗❋✭❁✿✬❡✷❳❞❉✺✒✺★✳❚✳✶❃❏❃❫◆✚❦✴✳✶❀❉✹◗❄➈✳✶❲❬■✣❲❙■✣✼❅❀★✷❅❀✖✵◗◆❷❁✿✷❳✬ ✺✢❦✣✷❅❃❏✳❚❁✿❄➏❣❤✳✶❁◗✷❥✳❚❦✣✼❅❀★✹✢❑✣✺★✺❖✾✣❁✸✷❅❃✚✵✿✱✣❀▲✹❇✳✶❲❬❀❹◆✭✳✶✵❇✳❼✹✿❀★✵❴t✘✵✿✱✣❀❻❲❬✷❨④✣❀✖◆❈❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀★✹✒✳✶■✭■✣❁✿❑✘✳❤✺◗✱ ✵✿✹✿✱✭❄✘❷❲❬❀ ✜ ✳❚❲❙✵✿❀★✵✿③❁◗✵◗✷❅❁✿✌✥❦✣✷❳✕€✺❻✾✣☛✵✿✳✶❀✔✵◗✹ ✵✿❁✿✷❅❦✣❚✾✭ÿ ✧✩✵✿✑❴❀❤✑★t✴✧ ➷✳✶❃❏✧✏◆❬✌×✜✣✵✿✗✶✱✭✧❳✓★❀❉✤ ❁✿❀★❲❫✕✘✓ ✳✶❈✷❅❃✣✕➈✷❅❃✣✕✘✛❘❉✳✶✵◗✧✏✵✿✛✢❁◗✽✷✯✜✣❦✭ý ✗✶✾✣✤ ✵✿❀★✘✹✍✜✣✳✶❖✗✶ý❁◗✧✥❀❼✜ ✳❚✹✿✌✏✕✣❄✘❲❙✑✽ý ❲❬➁✘❤✾✭❀★t✴✵✿■✣❁◗✳✶■❏✷❳❃❏✺✶❑❜✬◆ ✹✿❀▲✵✿✽✱❏ý ✳❚✵❩✭t✣✳▲➌❻■❏✱✣✳✶✵◗❀★✷✯❁◗❀✔❀ ❃➈✵♦❚❁✿❀✖ÿ ✺❖❑❜➏❁❇✷❅◆✈✹✻✵❇✳❚✳✶❃€❦✭✼✯❑❤❀❜❦❤t❤⑨❖●✒❀❴✺❖✳✶✵✩❦✭✐✩✼✯✷❳❀❻◆❷t✫✣✬❡❋✭t ✺✽❑❤❃✘➏✵❇✳❚✷❅✷✯✹❂❃✭✳✹ ð ▲➟ đ ð ð ➝ ị ò Ø ñ ➝ Ø ✍✔ ✥♠✾✕ ✝ ❞ ✒♠ ✝ ✣ ✽ó ✖✟ ✝ ➛✌ ð ➙✹ ✫õ❈ư✙÷❨✳✙◗ ✶❁ ✁➀☛✧✏✻ ị đ Ø ị ✹ ✲✻ ➝ Ø ➾✹ ❚õ➦ư✙÷➃★✵✧❃✪✲✂✼❁ ✁➀❂✧✓✻ ✍✌ ✶❁ ✁➀☛✧ ✲③ ✈✹ ✰✹ ✵✻ ø❒ ✫❮ ✩❮ ✠✣ ❨✛ ➜✎ ✒ù ✝✲✝ ✲✘ ✝ ✣ ✽ó ✝ ♦✗ ✚✌ ➝ ✸✻ đ ➝ ✹➜➟✓➞✿➠✲✻➚➢ ❾ ✐♠✾✕ Ø Ø ñ ❨✳✙◗ ①❒ Ý ➜✎ ✲✻ ➡❁❃✧ ✚❁ ✵✻ ✹ ➁ ✝ ❣♠✾♠ ✰★✵✧❃✪✲✂✼❁ ✁➀❂✧ ❬♠ Ø ➝ ❆✛ ❦✹ ➝ ✹✿➟✏➞❃➠✲✻ơ➢ đ Ø ị ❣ú✡û ❥ ✢ ✥♠ ✢ ✩❜ ð ✢ ✞✗ ị Ø đ Ø Ø ✹ ị ✸✻ ✆ú ❝★✵✂ ➸✧➛➥Ĩ✪✲✧✯★✵☞✲✧✯☎✚➥❣❱❄✧✩➀☛✧✯☎✚➥➦€✚◗☛❩✽✪✼❘✲➥✈❁❃✧ ✚❁❬❳✏ü✆➥Ĩ❁✏✧ ✚❁✥❳✏ý☛➥❆❁✏✧ ỵ ✵✿❀★✹◗✵✩✐★✮ ✵◗❀★✹✿✵➣✐➣❋ ✵✿❀✔✹✿✵✩✐✿❊ ✵◗❀★✹✿✵➣✐✉❯ ❪€ ✘ ❤✳❤✷❅✳❚❲ ✺ ❁✿❄ ❪❪ ✁✁✁ rr⑩ r⑩⑩ rrr rr⑩ rrr ✬✬ ✬✬ ✬✬ ✬✬ ✬✬ ✬✬ ✬✬ ✬✬ ●✒✳✶❦✣✼❅❀❂✫✭✬❡❋✣❭❽⑥➋❁✿❀★✼❳✳✶✵◗✷❅❑❤❃❏✳❚✼❏✵❖✳✶❦✣✼❅❀❉✺❖❑❤❃✘✵❖✳✶✷❅❃✣✷❅❃✣❘➏❲❙❑❤✹◗✵✿✼❅❄➏❦✣✷❅❃❏✳✶❁◗❄❙✳✶✵✿✵◗❁✿✷❅❦✣✾✣✵◗❀★✹✖✬ ◆✘✺❖❑✘✷❅✹✿❀❖✵❖➍⑧✭✳✶❑❤❃❏✺❖❁✢✷❅✺✽❀★❀❉✳✶❃✘✹✿❦❏✵s❄✘❀✔❲❬▼✏✵✩❑❤➌❩❁◗❲❙❲✚❀★❀★❀✔✾✣✵◗❃ ❁✿✼❳✷❳✳ ❑❜✺✒❦❤✩✳✶✫✣⑨❖✵◗❀✖✬❅✵✿✮★✺❖❁◗❯✵◗✷✯✹❦✭★t✘✾✣✏✵◗■✴✵✿✱✣❀✸✳✶❀❉✵✿❣❤✷❅✳✶◆✘❀★✼❅❃✘✷❅✾✣✹✿✵◗✵❇❀★✹ ✳❚✹❴❻❃❏t✶✷❅✼❅✺❖✹✍❀★❀❉✵✢✺❖❦✴❑❤✵✿✱✣❀★❲❬✵✩❀❻➌✸■✣❣❤✾✣❀★✳❚❀★✵✿✼❅❃€❀❴✾✣◆✚❀★❀❴✄✹ ❦❏✳❤✂❧✺◗✳❚✱€✹✿❀✖✳✶■❏◆❫❃❏✳❚✆◆ ❑❜✷✯❁✸❃✣☎ ✼❅❑✶❄❙▼✢❦✴❀❻✵✿❑❜✱✣❃⑧✹✿❀❈❀★✵◗✵♦✵✿✱✣✱✣✵✿❀❛❑✚❁◗❀★✳❚✮❤❀❉✹✿t❤❄✘■❏✳❚❲❙✳❚❃❏✵✿❲❬◆❈✷❅❀★✵✿❀★❃✘✱✣✵✿✵✿❁◗❀❻✹❴✷❥✺✸✠t ❣❤ ➈✳❚❣❤✳❜✼✯✳❚✾✭✺ ❁✿✞❀ ✷❳✳✶t✣✝❝❦✭❪ ✼✯❀✔❦✴✳✶✹✖❀❻❁✿✬✢❄❫✹✿⑥❂❀✔✳✶✵✒✺✔❃❏✺❖✵✿✡◆❑❤❑❉❁❖ ❜◆✘⑤✣✷✯✷❅✬✢❲➫❃✣➁✘❘❙t❤✾✣✹◗✵◗■✭✱✣❑✚■❏❑❤❑❜✵✿✾✭✱✣✹✿✼❥❀❻❀✟◆✈✵✿ ✘❦❏✱✴✳❤❀❜✳✶✺★t✵✒✺✔✳✶✵◗✱✣❁❇◆ ❀ ⑤❋ ⑤ ✮ ✮ ↕⑤ ❊❜❊ ✔❸ ☞☛ ✉✫✣✬❅✮❴❞ ✮✮ ✮ ✮ ✮ ↕⑤ ♠❜q ★❸ ✉✫✣✬❅✮❴♠ ☞☛ ✉✫✣✬❅✮❴q ✮ ✮ ✮ ❋ ❋ ↕⑤ q❜❞ ●❻✳✶❃✴✱✣◆⑧❀★✹◗❪ ❀❛✳✶❲❬❁✿❄❫❀✖✳✶✳✶✹◗✾✣❁◗❀❂❁✿❀✔✵◗❲❙✱✣❀❉❀★❃✘❲❬✵✿✹❻❑❤✹✿✹◗✵♦✾✣❘❤✼✯✷ ❘❜❜❀★❀★✹✿✼❅✵✍❄✚✵◗✵✿✱❏❑✚✳✶✱❏✌✵ ✳❴ ❤❣❜✷❅❀❂❲ ✳➏✳❚✹✿❃❏✷❅❲❬◆❫✷✯❪€✼❳✳❚✳✶❁ ❁◗◆❺❄€✷✯✹◗✳✶❀✖❁✿✳✶❀❈✹◗❀❤✾✣✬ ❃✣✼❅✷ ❤❀★✼❅❄❙✵◗❑✚✱❏✳❴❣❤❀➏✳➏✹✿✷❅❲❙✷❅✼❳✳✶❁❻◆✘✷❅✹✿❀✖✳❚✹✿❀❤✬▲➊❻▼✸✵✿✱✣❀❉✵◗✱✣❁✿❀✔❀❛■❏✳❚✵✿✷❅❀★❃✘✵✿✹❴✍t  ➈✳❤✺ ✎ ✓✎ ✛ ✛ ❀✹ ❀✹ ❙✻ ✫✻ ✓✎ ➝ ✹✁➠✲ð✸ò ❣➞ ➺ ➝ ✹✡➠✆ð✫ò ❣➞❃➠✲➟ ➺ ➝ ✹✡➠✆➟ ➺ ➞ ➺ ñ ð✫➮ ✲✻➚➢ ð ñ Ø ñ ✻ ð✫➮ ✽✻ ị Ø ➢ ➢ ð đ đ Ø Ø Ø ò Ø Ø ✹ ✲✻ ✹ ✲✻ ➷ Ø ➢ ✲✻ ➢ Ø ị đ ✶✎ ✶✎ Ø ✹ ➷ Ø ➢ ò Ø ➢ Ø ò Ø Ø ð Ø ➢ ò Ø ➢ Ø ➷ ✓✎ ✲➞ ✒➟♦➠➷➜ ▲➞ ✿➝✡➛ ✢➠❷➞✒➟ ✿➝ ✍➝ ✒➠ ✿➠ ① é❻ê ❩✑ê ✏ ✒ ❝đ✿ú▲ï③õ✔✓ ✒ø ✻đ◗ú✻ï✢õ✕✓✍ï✢ú ❾ø✣ï❽ð✣đ ó✘ơ❷ï✢õ✿÷ ✒ï③ø✭đ✿ï ✻õ◗÷✦ó ●❻✹❇✺✔✱✣✳✶✷❅✼❅✹✍❀✖◆❫✹✿❀✖❣❤✺✽✳❚✵✿❁✿✷❅❑❤✷❳✳✶❃➅❦✣✼❅◆✘❀★✷❅✹❴✹❖✬ ✺❖✾✣✹✿✹◗❀★✹➏✱✣❑✶➌❧✵◗❑⑧✺❖❑❜❲❙■✣✾✣✵◗❀❛✵◗✱✣❀❙◆✘✷❅✹✿✹◗✷❅❲❙✷❅✼❳✳✶❁✿✷❅✵✩❄✚❦✴❀★✵✩➌✸❀★❀★❃➷❑❤❦❤⑨✽❀✖✺❖✵✿✹➏◆✘❀★✹❇✺✽❁✿✷❅❦❏❀❴◆➷❦✘❄€❃✣❑❜❲❙✷❅❃❏✳✶✼✩t✘❑❜❁❇◆✘✷❅❃❏✳❚✼✉t❷✳❚❃❏◆€❁❖✳✶✵◗✷✯❑❚✐ ✖ ➷✧✥✛✢✜✣✌ ✘✜✣✗✶✧✥✜ ✌✏✕✣✑ ⑥❀❖④❏✳✶✛ ❲❬■✣➷✼❅❀❤✧✏✛✢t✴ÿ✜✣✌ ➈✜✭✗✶✧✏✜ tt ỵ t t ✾✭✷✯❃✭❲✚✳❚❘❏✹ ❦❏✬ ❀★✮❜❁✸t❷❑✶❋✣▼✒t✒✹◗✬★✵❇✬❴✳✶✬★✵◗✙t ❀★✹✻✗✡❑❚✬❉▼ ✳➏rs❑❤❃✣✵◗❑❜✷❥❲❙✺✽❀❛✷❅❃❏✵◗✳❚✱❏✼✣✳✶❣❤✵✍✳✶✹✿❁◗✾✴✷❥✳❚✺✿✱➷❦✣✼❅❀✻✷❅❃✘❦✴✵✿❀✔❀✘❘❤✗✡❀★❁◗✹❼✬✢✳❚●❻❁✿✱✣❀➏❀❉✾✣✹◗✹✿✵❇❀❴✳❚◆✚✵✿❀★⑨❖✹✍✾✣✹✿✺★✵▲✳✶❃❫▼✏❑❜❦✴❁❂❀❛◆✣✳❚◆✘✵❇❀★✳❬❃✣❑❜✱❏✵✿✳❚❀✖❃❏◆ ◆✘❦➈✼❅✷❅❄❬❃✣❘❙✼❅❀★✵✿✳✶✵◗❃❏❀★◆➫❁✿✹❴◆✘t❏❑❬✹◗❄✘❃✣❲✚❑❤❦❏✵✍❑❜❁✿✼✯❀✔✹❴■✣t❤❁✿❑❜❀★❁✻✹◗❀★✳➏❃✘✵✹✿❀★✵▲✳❚❃✘❑✶❄ ▼ ✉✫✭✬❅✮✖●❻✫ ✔✱✣❭ ❀❫◆✘✷❅✹✿✹◗✷✯❲❬✷❅✼❥✳❚❁✿✷❅✵✩❄❫❦❏❀✔✵✩➌❩❀★❀✔❃ò✵✩➌✸❑➫❑❤❦❤⑨❖❀✖✺✽✵✿✹ ✍✳✶❃❏◆ ✺★✳✶❃ù❦❏❀€✺❖❑❜❲❙■✣✾✣✵◗❀✖◆➫✾✣✹◗✷✯❃✭❘ ✵◗✱✣❀ ✑✔✧ ✢✌✥✕ ➷✜✣✓ ✢✧✏✛ ✳❚■✣■✣❁✿❑✘✳❤✺◗✱ò✳❚✹❛✷❅❃ ✉✫✣✬❅✮❴✫ ➌❻✵✿✱✭✱✣❀❂❀★❁◗✵◗❀❑❤✵❖✳✶✼✴❃➈✷❅✹✻✾✭❲✚✵◗✱✣❦❏❀➏❀★❃➈❁✸✾✭❑✶❲✚▼✦❣❤❦❏✳❚❀★❁✿❁❻✷❳✳✶❑❚❦✭▼❂✼✯❀✔ÿ ✹✖✬❽✰➷❀★❖✷❅ý ❘❤✱✘✥✷✩✵✿✬✹❻❀❜✬✯✺★t✭✳✶✵✿❃❬✱✣❀❈❦❏❀❉❃➈✾✭✳❚❲✚✹✿✹✿✷❅❦❏❘❜❀★❃✣❁▲❀✖◆✚❑✶▼❩✵◗❣❤❑❛✳❚✷❅❁✿❃❏✷❳✳✶✺✽❁✿❦✭❀✖✼✯✳❚❀✔✹✿✹✸❀❉▼✏❑❤✵◗❁▲✱✣❀✻➌❻❀ ✱✣❷✷❳❀✖✺✿✱✺❖✵▲❩❑✶✳❚▼ ❃❏◆ t✘⑧❑❤❁✸✳✶❁◗✵✿❀❛❑✚✷❅✳✶❃❫✹◗✹✿✵✿✷❅✱✭❘❤❀❛❃❬✹❖❘❤✳✶❁◗❲❙❀✖✳✶❀✍✵◗❀★✹◗❁❻✵❇✳✶➌❩✵◗❀✔❀ ✷✯★❘❜t❽✱✘✳✶✵❩❃❏✵◗◆ ❑❛✵◗✱✣✷❅❀✹ ❲⑧✳❚✵❇rs✺◗✱✣❑❤❀★❲❙✹❻✷❅✷❅❃❏❃❬✳❚✼❷❣❤✳✶❣❤❁✿✳✶✷❳❁◗✳❚✷❥❦✣✳❚✼❅❦✣❀★✼❅✹❩❀★✹❂✱✴✳❴✺✔❣➈✳✶❃➫✷❅❃✣❘✚❦❏❀✚✳➏❀★✼❳❃✴✳✶❁◗✺❖❘❤❑✣❀★◆✘❁❻❀✖◆➫❃✘✾✣❦✘❲✚❄ ❦✴✳✚❀★❁✸✼❳✳❚❑✶❁✿▼③❘❤✹◗❀➏✵❇✳❚❃✘✵✿✾✣❀★❲✚✹❴✬ ❦✴❀★❁✻❑❚▼❹✳✶✹◗❄➈❲❬❲❙❀★✵◗❁✿✷❳✺▲❦✣✷❅❃❏✳✶❁◗❄€❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀★✹▲❦➈❄€✺❖❁◗❀✖✳✶✵◗✷❅❃✣❘ ✳✚❃✭❀★➌✡❦✣✷❅❃❏✳✶❁◗❄ ❣❤✵✿✱✴✳✶✳✶❁◗✷❳✵✸✳✶✹✿❦✣✵❇✼❅✳❚❀▲✵✿▼✏❀✍❑❤✷❅❁▲✹❩❀✖✹◗✳❤❀★✺◗✵❻✱€✵✿❑❫❑❚▼✒✮❤✵✿t✘✱✣➌❻✚❀ ✱✭✗✆✷✯✼❅❀❻❃✣✵◗✱✣❑❤❀✍❲❬❁✿✷❅❀★❃❏❲❫✳✶✼✴✳✶✹✿✷❅❃✣✵❖✳✶✷❅❃✣✵✿❀✔❘✍✹✖❦✣✬ ✷❅✣❃❏❑❜✳✶❁❂❁◗❄✚✳✶❃❫❣❤✳✶❑❜❁◗✷❥❦❤✳❚⑨❖❦✣❀✖✼❅✺❖❀★✵✍✹❩➌❻✳❚❁✿✷❅✵✿❀✻✱ ✹◗❀★✳➏✵❻❘❜✵✿✷❅❑✚❣❤❀★⑤✣❃€✬ ✹◗✭✵❇❑❤✳❚❁✸✵✿❀➏❀❖④❏❣❤✳✶✳✶❲❬✼❅✾✣■✣❀❤✼❅t✭❀❤✵✿t✶✱✣✵◗❀❉❑❛❦✭❀★❃✴✷✯❃✴✺❖✳✶❑✣❁✿◆✘❄❫❀✍❣❤✵✿✳❚✱✣❁✿❀✍✷❳✳✶❃✣❦✣❑❜✼❅❲❙❀✍✷❅❁✿❃❏❀✔■✣✳✶✼✘❁✿❀★❣❤✹◗✳❚❀★❁✿❃✘✷❳✵✿✳✶✷❅❦✣❃✣✼❅❘ ❀ ÿ ✒t❤✵◗✱✣★❀ t❷✳✚❦✣✷❅❃❏❫✳❚❁✿❣❤❄❬✳✶❁◗❣❤✷❳✳✶✳✶❁✿❦✣✷❳✼❅✳❚❀✸❦✣✷✯✼❅✹✸❀❛✹✿✺★❀✔✳✶✵❩❃ ✵◗❑⑧❦❏❀✚✮❜t❤✺❖➌❻❁✿❀❴✱✣✳✶✷❅✵✿✼❅❀❴❀❻◆ ✵✿✱✭▼✏❑❤❀✻❁▲❁✿❀✔❀✖❲⑧✳❤✺◗✳✶✱➫✷❅❃✣❑✶✷❅▼✒❃✣❘▲✵✿✱✣▼✏❀ ❑❜✾✣❏❁✒❣❜❣❤❀ ✳❚✺❖❁✿❑❜✷❳✳✶✼❅❑❤❦✣❁✿✼❅✹▲❀★✹✸✼❅✷✯✳✶✹◗❁✿✵✿❀▲❀✖◆ ✹✿❀★✳✶✵✸❦✴✵✿❑✶❑➏❣❤❀❤⑤✣✬✬✢●❻✣❑❜✱✣❁❂❀✍✳❚◆✘❃€✷❅✹✿✹✿❑❤✷❅❦❤❲❬⑨❖❀❴✷✯✼❳✺❖✳❚✵✍❁✿✷❅✱❏✵✩❄❂✳❴❣✘✺❖✷✯❑✘❃✭❀❖❘❙➍⑧✵✿✺✽✱✭✷✯❀❀✔❃➈✺❖✵✸❑❜▼✥✼❅❑❤❑❤❁❁ ✵✿✱✭✷✯✹✸▼✥❑❤❁✿❲ ❑✶▼✒❀★❃❏✺❖❑✣◆✘✷❅❃✣❘❙✺✔✳✶❃❫❦❏❀❉✺★✳❚✼❳✺❖✾✣✼❳✳✶✵◗❀✖◆❬✾✣✹✿✷❅❃✣❘✚✵◗✱✣❀✍❲❙❀★✵◗✱✣❑✣◆✘✹✻◆✘✷❅✹❇✺❖✾✭✹✿✹✿❀❴◆❫✷❅❃ ➁❺❀✖✺❖✵✿✷❅❑❜❃ ✫✭✬❡❋✣✬❡❊✣✬ ✛ ✗ ❽✧✥✛✢✜✣✌ ➈✜✭✗✶✧✏✜ ✌✥✕✣✑ ⑥✷❅❃ ❽✳✈✧✉✑❲❙❀✖✗✶✳❚✕✘❃✣✓❴✕✷❅❃✣❏❘✶▼✥✗ ✾✣❽✼✦✧✥✛✢✹◗❀✖✜✣❵❜✌ ✾✣✘❀★✜✣❃❏✗✶✺❖✧✥❀❜✜ ✬❙➊▲✌✥✕ ❁❇◆✘❁◗❀★✷❅❃❏✹✿❀✔✳❚❲✚✼✒❣❤❦✣✳✶✼❅❀★❁◗✹✒✷❥✳❚✳✻❦✣✼❅❃✭❀★❑❤✹❂❲❙✳❚✷❅❁✿❃❏❀➏✳❚❣❤✼✶❀★❣❤❁◗✳✶❄€❁◗✷❥✾✣✳❚❦✣✹◗❀❖✼❅▼✏❀❤✾✣t❴✼✢❀❖④❏▼✥❑❤✺❖❀★❁✍■✣❁✿✵✸❀★❘❜✵✿✱✴✷❅✹✿✳✶✵✿✵✢❀✔❁✿✵✿✷❅✱✣❃✣✜❀ ❘❫✗ ✹✿✾✣❦❤✹✿⑨✽✵❖❀✖✳✶✺❖✵✿✵✿❀✔✷❅✹✒❣❜❑✶❀⑧▼❏✳✶✵◗✹◗✱✣✹✿❀❻❀★✹◗❑❤✹✿❁❖❲❬◆✘✷❅❀★❃❏❃✘✳✶✵✿✼✘✹❉❣❤❑❚✳❚▼❹✼✯✾✭❵❜❀❩✾❏✳✶✳✶❁◗✼❅❀❻✷❅✵✿✷❅❑❤❀★❁❇✹▲◆❺✵✿❀★✱❏❁✿❀✖✳❚◆ ✵ ✺★✳✶✳❚✹◗✹✿❃✣✷❅❃✣✹✿✵❖❑❤✳✶✵✸❃✘❦✴✵✖t❽❀❂✳✶❲❬✹✿✹◗❀✖❑✣✳✶✺❖✹◗✷❳✾✣✳✶❁✿✵✿❀❴❀❜◆✚t③✳❚❑❤❃❏❦❤⑨✽◆❫❀✖✺❖▼✥✾✣✵✿✷❅✼❅❣❜✼✉✬▲❀★✼❅❄➈⑥ ✬ ✣✴❑❜❁❩✛✦✓❴❀✽✧✏④✭✛❽✳❚✎ ❲❙❏■✣✎✒✼❅❀❤✑ t❚❏■✣✗ ❁✿❑❚❽▼✏✧✥❀★✛③✹✿✹◗✜✭✷❅✌ ❑❤❃❏✘✳❚✜✣✼❷✗✶✧✥❁❇✜ ✳✶❃ ➈✌✏✕ ✹❻✳✶✼❅❑➈❁◗❑❀✍✘❑✶✹❂▼✏✵◗✼❅❀★✷ ❤❃❙❀➏❀★✳✚❃✘✾✣✹✿❲❬❀✔✵❉❀★❁❇❑✶✳❚▼❹✵✿✺✽❀✖❑❤◆✈❃✘✷❅✵✿❃❙✷❅❃✘✳❉✾✣❑❤✹◗❀✖✾✭❵❜✹❼✾✣◆✭❀★❃✘✳✶✵❇✵✿✳❬✷❳✳✶✼❷❑❚▼❹❑❜❁❇✳✶◆✘❃➫❀✔❁✖✾✣t✘❃ ✹✿✘✾✴❃✣✺✿✱€❑✶➌❻✳❚❃ ✹ ✹❇❁❇✺✔✳❚✳✶❃ ✼❅✘❀❤✷❅t✘❃✣✵✿❘✍✱✴✷✯✳✶❃✚✵✒✳▲✷❅✹✖■❏t❚✵✿✳✶✱✣❁◗✵✿❀▲✷❳✺❖❁✿✾✣❀★✼❳✼❳✳✶✳❚✵◗❁③✷❅❣❤✹◗■❏❀✸❑❜❑❤❁✿❁❇✵✒◆❺✷❅❀★✹✢❁✿✷❅❑✶❃✣▼✥❘❉✵✿❀★❑❚❃➏▼✦❲❙✵✿✱✣❑❜❀❻❁✿❀✒❣❤✳❚❀★✹◗✼❅✾✣✹✿❀★❀★❃✘✹✒✵◗✷❅✷❥✹✢✳❚✼❏❀★✹✿✵◗✹◗✱❏❀★✳✶❃✘❃➏✵✿✷❳✵✿✳✶✱✭✼❷❀✻❦✭✾✣✳❤✺❖✵✒✵◗❃✣✾❏❑❜✳✶✵③✼✣❣❤✵◗✱✣✳❚❀★✼❅✾✣✷❅❁❻❀★✹✢✳❤✺❖❑✶✵◗▼✦✾❏✳▲✳✶✼✣■❏❲❫✳✶❁◗✳✶✵✿✷❳❘❜✺❖❃✣✾✣✷❅✼❳✵✿✳✶✾❏❁✢◆✘❲❬❀❜✬ ❀✖✳✶✣✹◗❑❜✾✣❁✢❁✿❀❖❀❤④❏✬↕✳✶❲❙➊▲■✭❁❇◆✘✼✯❀❜✷❅❃❏t✶✵✿✳❚✱✣✼✣❀❻❣❤✳✶❁◗❀★❁◗✷❥✼❳✳❚✳✶❦✣✵◗✷✯✼❅❣❜❀★❀✹ ❲⑧❃✘✾✣✳❴❲✚❄❫❦✴✳✶❀★✼❅❁❩✹✿❑❫❑❚▼ ❦✴✺❖❀✚✼❳✳❚❑❤✹✿❦✣✹✿❀✔✵❖✳✶✹✖✷❅✬✸❃✣●❻❀✖◆ ✱✣❀✍▼✏❁◗❣❤❑❤✳✶❲❾✼❅✾✣❀★✵✿✹✸✱✭❀❙❑✶▼✒◆✘✳✶✷❅✹❇❃❫✺❖❁◗❑❤❀★❁❖✵✿◆✘✷❅⑦✖✷❅❃❏✳❚✵✿✳✶✷❅✼✴❑❤❣❤❃➫✳✶❁◗❑✶✷❳▼❻✳✶❦✣✷❅❃➈✼❅❀❂✵◗❀★✺✔❁✿✳✶❣❤❃❫✳❚✼➐✐✉❦❏✹❖❀✍✺★✳✶❲❫✼❅❀✖✳✶◆€■✣❵❜■✴✾❏❀✖◆✚✳❚❃✘✵◗✵✿❑ ✷❅✵✿✷❅❀★✹✍❴❦✘ý★❄€✬ ✹✿✣■✭❑❜✼✯❁❩✷❅✵◗❀✽✵✿④✭✷❅❃✣✳❚❘❙❲❙✵◗■✣✱✣✼❅❀✚❀❤t❜❣❤✹✿✳✶✾✭✼❅■✣✾✣■❏❀❈❑❜❁❇✹✿✳✶❀❉❃✭✵◗❘❤✱❏❀✚✳✶✷❅✵✻❃✘✳❚✵✿❑⑧❃❙✳❑❜❁❇❏◆✘❃✭✷❅❃❏✷✯✵◗✳❚❀ ✼ ❣❤✳✶❁◗✷❳●❻✳✶❦✣✱✣✼❅❀➏❀ ✵✿❁◗❀✖✱❏✳✶✳❚✵◗❲❙✹✜✗❀★❃✘✵✍✹✿❑✶✵❇▼✸✳❚❑❤✵✿❀★❁❇✹❴◆❺✬✸✷✯❃✴●❻✳✶✱✣✼✢❀★❣❤✹✿✳✶❀❈❁◗✷❥❑❤✳❚❁❇❦✣◆❺✼❅❀★❀★❁✿✹✻❀✖✷❅◆ ✹❉✹✿❵❜✵❇✾✣✳❚✷❅✵✿✵✿❀★❀➏✹✍✹✿◆✘✷❅❀❲❙❏✷❅❃✭✼❳✳✶❀❉❁❻✵✿✵◗✱✣❑❫❀✍✵✿❁❖✱❏✳✶✳❚❃ ✵❂✘✷❅❑❚❃✣▼❩❘€✷❅❃✘✮ ✵✿❀★❁◗✢❣❤✗ ✳✶✼➐✐✉✹❖✬ ✺★✳✶✼❅❀✖◆ ❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀★✹▲➌❻✱✣❀★❃➷✺❖❑❤❲❬■✣✾✣✵✿✷❅❃✣❘❬✵✿✱✣❀✚◆✘✷❅✹✩✐ ✹✿✺❖✷❅❑❜❲❬❲❙✷✯■✣✼❳✳❚✾✣❁✿✵❖✷❅✵✩✳✶❄✍✵◗✷✯❦❏❑❜❃✚❀★✵✩➌✸➌❻❀★✷❅✵✿❀★✱❫❃❫❁✿❑❜❀★❦❤✹◗⑨❖■❏❀✖❀❴✺❖✺❖✵◗✵✍✹✖✬❩✵✿❑ ➁❺✾✣■✣✷✯■✴❃✘❑❤❣❜✹✿❑❤❀▲✼❅❣❤✵✿✱❏❀★✹♦✳❚✵✵✿✱✣❀✍✷✯▼✥✹♦❑❤❑❤✼❅✼❅❃✣❑✶❀▲➌❻❑✶✷✯❃✭▼③❘❂✳✍✹◗✹◗✵✿❀★❀★✵❻■✭✹✖❑✶✬ ▼✦❑❜❁❇◆✘✷❅❃❏✳❚✼❏❣❤✳❚❁✿✷❳✳✶❦✣✼❅❀★✹✸◆✘❀★✹❇✺✽❁✿✷❅❦✣✷❅❃✣❘ ❙❑❜❦❤⑨❖❀✖✺❖✵◗✹✖✬♦●❻✱✣❀❂◆✘✷❅✹◗✹✿✷❅❲❙✷❅✼❳✳✶❁◗✷✯✵✩❄ ✮❜✬✸●❻❀✖✳❤✱✣✺◗❀❻✱ ❣❤✳✶✼❅✾✣❀✒❦✘❄❙❑❚▼ ✷❅➏✵◗✹✻▼✥❑❤✺❖❑❤❁✢❁◗✵✿❁✿✱✣❀★❀✹◗■❏×❑❜✵✿✱✚❃❏◆✘❑❤✷❅❦❤❃✣⑨✽❘❙❀✖✺❖❁❖✵✒✳✶✷❅❃ ✹ ❷t t❤✳✶❃❏◆ ✮➏✱❏✳❚✣✹ ✤✗ ✗ ❑❤✬ ❁❇◆❺❀★❁✿❀✖◆✈✹✿✵❖✳✶✵✿❀✔✹✖t❜❁✿❀★■✣❁◗❀★✹✿❀✔❃➈✵◗✷❅❃✣❘❛✵◗✱✣❀✸❁❇✳✶❃ ➈✷❅❃✣❘➏✮ ✤✗ ✬✢➀❻❀★■✣✼❳✳❜✺❖❀ ✚✥✧✦ ✠★ ❋✭✬❻❣❤➁✘✳✶✷❅❃❏❁✿✷❳✺❖✳❚❀✻❦✣❀❴✼❅❀❉✳❤✺◗❑❤✱❙❃✘❑❜✵✿❑✪❁❇◆✘✩❡✷❅⑤❴❃❏✐★✳❚✮✤✼❏✫③❣❤✹◗✳❚❑❫❁✿✷❳✵✿✳✶✱❏❦✣✳❚✼❅✵✻❀❻❀✖✺★✳❜✳✶✺✿❃❬✱➫✱❏❣❤✳❴✳✶❣❤❁◗❀✻✷❳✳✶✳❈❦✣◆✘✼❅❀❉✷ ✱❏❀★✳❚❁◗❀★✹✍❃✘❀✖✵❻❵❜❃✘✾❏✾✣✳✶❲✚✼✢➌✸❦❏❀★❀✔✷❅❁✒❘❤❑✶✱✘▼❷✵✖✬✍✹✿✵❖●❻✳✶✵✿✱✣❀✔✷❅✹✖✹✍t✣✺★✷❅✵✒✳✶❃➫✷❅✹✸❦❏❑✶❀❙▼✏✵◗❀★✳❜❃✚✺◗✱✣❃✣✷❅❀✖❀★✺✽❣❤❀★❀✖✹✿◆ ✹❖✳✶❦✘❁✿❄❫❄❫❁✿✵◗❀★❑❉■✣❲⑧✼❳✳❜✳❚✺❖✷❅■❛❃✣❘❙✵◗✱✣✵◗❀✻✱✣❁❖❀✚✳✶❃✣❁❇✳❚❘❜❃ ❀✻❑✶▼✦❀❴✳❤✺◗❑✶✱ ▼ ✵✿✱✣❀ ❥✐✩✵✿✱❫❑❤❦❤⑨❖❀❴✺❖✵❻✷❅❃⑧✵◗✱✣❀ ✘✐✩✵✿✱ ❣❤✳✶❁✿✷❳✳❚❦✣✼❅❀✻❦✘❄ ✮ ✉✫✣✬❅✮❴① ✗ ✮ ❊✭✬❻✹❇❱✻✺★✷❅✳❚✹◗✼✯✹✿❀❴✷❅◆❫❲❙❣❤✷❅✼❳✳✶✳✶❁◗❁◗✷❥✷✯✳❚✵✩❄❉❦✣✼❅✺★❀★✳❚✹✖❃❫t❜✾✣✵✿✹◗✱✣✷✯❃✭❀★❃❘ ❦❏❀❉✺❖✵✿❑❜❑✚❲❙❁◗■✣❀★■✣✾✣❁◗✵◗❀★❀✖✹✿◆✚❀★❃✘✾✭✵✍✹✿✷❅✵✿❃✣✱✭❘❙❀ ✳✶❫❃✘❄✚❣❤✳✶❑❚✼❅▼③✾✣✵✿❀▲✱✭▼✏❀❼❑❜❁❩◆❺✷✯✵◗✹◗✱✣✵❇❀ ✳❚❃❏×✵✿✺❖✱❫❀❉❲❬❑❤❦❤❀✖⑨✽✳✶❀✖✹◗✺❖✾✣✵✖❁✿✬ ❀★✹✻◆❺❀★✹❇✺❖❁◗✷❅❦❏❀✖◆ ✷✯❃€➁✘❀❴✺❖✵✿✷❅❑❤❃€✫✭✬ ❋✭✬❡❋▲▼✏❑❤❁✸✷❅❃✘✵✿❀★❁◗❣❤✳✶✼➐✐ ●✸■❹❸✐■ ❯▼❆❉ ❃⑤ ❈❺❼❻❈❇ á⑧➼➨ ✣✵♠ ❈⑧ ❆❏❈❑ ✙⑩ ❆❋✺❖ ❀❽✦❇ ❯⑩ ✏⑧ ❈❇❊❏◆▼ ✫❖ Ð ♦⑩rÏ ✖Ñ ✢ ❆✗ ✖✣❭♠ ✵❇✤❖ ✴✗ ✢ ➸✂➛✳ €✚◗✆ ✄◗☛☎ ☛✎ ✽✌ ❯☎✚✧✚☞✼➥❆✮✲✧✩ ✡ ✄◗☛Ö s✛ ➥✠✪☛☎❙✧✚✧✯★✫➥❣✳ ✁★❚Õ ✾✬✯ ✑❩✙✧ ✍✌ ✜➟ ✹ ✷➠ ❬♠✾✕ ✝ ❞ ❼♠ ✖✟ ✲✻ ➝ ✹➜➟✓➞✿➠✲✻ ➁ ➢ ➺ ➹ ➞ ➁ ✹ ❨✂✼❁✏€✚❘✙✧ ❀✹ ➺ ➃➟ ✒➠ ✚✔ ❄✻ ✲✻ ❨➁ ➺ ❊✛ ❆✛ ❨✂✚✳ €✚◗☛ ✄◗✆☎ ✮✲✧✯ ✁ ✄◗✆Ö ❊✛ ❝✮✲✧✯ ✁ ✶◗☛Ö ✲✘ ✘ ➾✌ ✢ ✖✗ ✝ ❀✣ ✲✘ ✵✗ ✢ ✖✛ t✝ ✣ ✐✎ ✖✣ ➾✣ ✲✘ ✢ Ó✗ ✽✎ ✶✎ ✙✎ ◆✛ ✙✎ ➯✌ ❪☎✚✂☛★✫Õ ▲➳ ✚✌ ➋ ✙✎ ✲➞ ➞ ➷✶➷ ➦➳ ❆✛ ➋ ❨❷ ✜➳ Ü➳ ❈➟ ➡➳ ➇ ➑✶➋ ✙✎ ✙➮ ✶➑ ➋ ➇ ➑✶➋ ✐✎ ➋ ✲➞ ➞ ➷❄➷✼➷ ✲➞ ➞ ➷✶➷ ➋ ➋ ✍✔ ✙✎✰➮ ➑✶➋ ❝➟ ❀➳ Ú✯➑✶➋ Ú ➑✶➋ ❝➳ ➢ ➮ ➑✶➋ ➹ ➋❀➹ ❝➟ ✹ ➷ ✲✻ ✮✖⑤ ➛ ❻➞✒➟ ➪➛ ③➠➎➞✒➟ ❂➝ ♦➠ ✿➠ ❆❅❈❇❊❉ ❆❋❍●✸■ ❆❏❈❑ ❆❋✤❇ ✺❇▲❏◆▼ ✫❖ ✭✜ ✓✖✧ ❖✑ ✜✣✌✥✕ ✘✜✣✗✶✧✏✜ ✌✥✕✣✑ ⑥✷❅❲⑧✗✶✳❚✜✣✵✿❀★✓❴✼❅✧ ❄❈❇▼✏✑❑❤✼❅✼❅✜✭❑✶✌✏➌❻✕ ✷❅❃✣❘✍✘✜✣✵✿✱✣✗✶❀✍✧✥✜ ▼✥❑❤✌✏❁✿✕❲✚❲⑧✾✭✼❥✳✳ ❤❀★✹❻✳❉■✴❑❤✹◗✷❅✵✿✷❅❣❤❀✍❲❙❀❴✳✶✹✿✾✭❁✿❀★❲❬❀★❃✘✵✒❑❤❃€✳❈❃✣❑❤❃✣✼❅✷❅❃✣❀✖✳❚❁❩✹❖✺★✳✶✼❅❀❤t✭✹✿✾❏✺◗✱€✳✶✹✻✳❚❃❫❀❖④✣■❏❑❜❃✣❀★❃✘✵✿✷❳✳✶✼❷✹❖✺★✳✶✼❅❀❤t✴✳✶■✣■✭❁✿❑❴④✘✐ ✭✯✮✕✰✲✱✴✳ ✭✯✮☞✵✍✰✙✱ ✉✫✣✬❡❋❜⑤ ➌❻❑✶▼❩✱✣✳❈❀★❁◗❁❇❀ ✳❜✭◆✘✷❅❑✶✳✶✐✿❃✴✳❤✷◆✺❖✵◗✷✯✶✡❣❜❀✻✳❚❀★❁✿✼❅❀✍❀★❲❬■❏❑❜❀★✹✿❃✘✷❅✵✖✵✿✷❅✬ ❣❜❀❂✺❖❑❜❃✣✹✿✵❖✳✶❃✘✵✿✹❴✬✡●❩❄✘■✣✷❳✺★✳❚✼❏❀❖④❏✳❚❲❙■✣✼❅❀★✹✸✷❅❃❏✺❖✼❅✾❏◆✘❀✍✵✿✱✭❀❂❘❜❁✿❑✶➌❻✵◗✱⑧❑❚▼ ✳➏❦❏✳❜✺❖✵✿❀✔❁✿✷❳✳➏■❏❑❜■✣✾✣✼❳✳✶✵◗✷❅❑❤❃✦t❜❑❤❁✸✵✿✱✣❀➏◆✘❀✖✺★✳❴❄ ●❻✱✣❀✔❁✿❀❛✳❚❁✿❀✍✵✿✱✣❁◗❀★❀❉❲❬❀★✵✿✱✣❑✣◆✘✹❻✵◗❑❛✱✴✳✶❃❏◆✘✼❅❀✍❁❇✳❚✵✿✷❅❑✶✐✩✹❇✺✔✳✶✼❅❀✖◆❬❣❤✳✶❁◗✷❥✳❚❦✣✼❅❀★✹♦▼✏❑❤❁❻✺❖❑❤❲❬■✣✾✣✵◗✷✯❃✭❘❛✵◗✱✣❀❉◆✘✷❅✹✿✹✿✷❅❲❬✷✯✼❳✳❚❁✿✷❅✵✩❄❉❦✴❀★✵✩➌❩❀✔❀★❃€❑❤❦❤⑨✽❀✖✺❖✵✿✹❴✬ ✮❜✬✸●③✼✯✷ ❜❁◗❀✖❀★✳✶✼❅❄✚✵✸✵✿❁❇✱❏✳❚✵✿✳❚✷❅✵❻❑✶✐✩✵✿✹❇✱✣✺✔❀✍✳✶✼❅✹❇❀✖✺✔◆✚✳✶✼❅❣❤❀✍✳❚❲⑧❁✿✷❳✳✶✳❴❦✭❄➏✼✯❀✔❦❏✹❩❀❛✼❅✷◆❺❤✷✯❀❻✹◗✵✿✷❅❑❜❃✘❁✿✵✿✵✿❀★❀❴❁◗◆❷❣❤✬✳✶✼➐✐✩✹❇✺★✳❚✼✯❀❴◆✚❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀★✹❴✬✦●❻✱✣✷❅✹❴t❤✱✣❑✶➌✸❀★❣❜❀★❁✖t✘✷❅✹✸❃✣❑❤✵✸✾✣✹✿✾✴✳✶✼❅✼❅❄❙✳✍❘❤❑✘❑✣◆❙✺◗✱✣❑❜✷❥✺✽❀❂✹◗✷❅❃❏✺❖❀✍✷❅✵✒✷❅✹ ❋✭✬✸▼✏⑥✻❑❤■✣❁◗❲✚■✣✼❅✾✣❄ ✼❳✟✳ ✌ ☛ ❏✜✣✗✶↕✧✥✓ ✼❅❑❤➷❘ ✧ ✓❴✔✗✶✬✒✜✣●❻✛✒✱✣✑ ✘❀ ❏☛ ✗ ➷✜✣❣❤✳✶✓❴✧✼❅✾✣❏❀★✛ ✹✻✵◗✺★❑ ✳❚❃❫✳❬❦❏❁❖❀❉✳✶✵✿✵◗✷❅❁✿❑❚❀✖✐✉✳❚✹❖✺★✵✿❀✖✳✶◆✼❅❀✖◆➫✳✶✹✻❣❤✷❅✳❚❃✘❁✿✵✿✷❳❀✔✳✶❁✿❦✣❣❤✼❅✳✶❀ ✼➐✐✩❣❤✳✶✱❏✼❅✾✣✳❴❣✘❀✖◆➎✷❅❃✣t➈❘❙✳❚✹✻❣❤✳❚◆✘✼✯❀★✾✭✹❇❀ ✺✽❁✿✷❅❦❏❀❴◆€▼✥❑❤✷❅❁✍❃€❑❤➁✘❦❤❀✖⑨❖✺❖❀❴✵◗✺❖✷❅✵❑❤❃ ✸✫✭❦✘✬❄€❋✭✬❡✾✭❋✣✹✿✬✢✷❅❃✣r❻❘€❑❤✵◗✵◗✷❳✱✣✺❖❀❀ ✵✿◆✘✱❏❀★✳❚■✴✵✚❀★❃❏▼✏◆✘❑❜✷❅❁❙❃✣❘❬✹✿❑❜❑❤❲❙❃❙❀❫✵◗✱✣❁❇✳❚❀❛✵✿✷❅◆✘❑✶❀ ✐✩❏✹❇✺✔❃✣✳✶✷❅✵✿✼❅❀✖✷❅❑❤◆➪❃❫❣❤✳✶✳✶❃❏❁✿◆❫✷❳✳❚✳❚❦✣■✣✼❅❀★■✣✹✖✼❅t✸✷❳✺★❑❤✳✶❃✭✵◗✷✯❀ ❑❜❃✦❲❫✬ ✳❴❄➅✳✶✼❅✹✿❑➅✳❚■✣■✣✼❅❄ ✼✯❑❜❘✶✐✩✼❅❑❤❘➫✵✿❁❇✳❚❃✣✹✩▼✥❑❤❁✿❲❫✳✶✵◗✷✯❑❜❃✦t✒❑❜❁❙❑❜✵✿✱✣❀★❁❫✵◗❁❇✳✶❃✭✹✩▼✏❑❜❁✿❲⑧✳❚✵✿✷❅❑❤❃✭✹✖t ❊✭✬✸●③❁◗❀✖✳✶✵ ✳✶✹✻✺❖❑❜❃✘✵✿✷❅❃✘✾✣❑❤✾✣✹❻❑❜❁❇◆✘✷❅❃❏✳❚✼ ◆✭✳✶✵❇✳✚✳❚❃❏◆❬✵✿❁◗❀✖✳✶✵❻✵◗✱✣❀★✷❅❁✻❁❖✳✶❃ ✘✹✻✳✶✹❻✷❅❃✘✵✿❀✔❁✿❣❤✳✶✼➐✐✩❣❤✳✶✼❅✾✣❀✖◆➎✬ ●❻✳✶■✭✱✣■✣❀❉✼❅✷❥✼❳✺✔✳❚✳✶✵✿✵✿✵✿✷❅❀✔❑❜❁✻❃✦✵✩✬ ➌✸❑✚❲❙❀★✵◗✱✣❑✣◆✘✹✻✳✶❁◗❀❂✵◗✱✣❀❉❲❬❑❤✹✿✵❻❀ ❀✖✺✽✵✿✷❅❣❤❀❤t❷✳❚✼✯✵◗✱✣❑❤✾✭❘❤✱❙✵◗✱✣❀❛✺◗✱✣❑❜✷❥✺✽❀❉❑✶▼✒❲❙❀✔✵✿✱✣❑✣◆❬✾✣✹✿❀❴◆❫❲⑧✳❴❄➏❦❏❀➏◆✘❀★■✴❀★❃❏◆✘❀★❃✘✵❉❑❜❃❫✵✿✱✣❀❉❘❜✷❅❣❤❀★❃ é❻ê ❩✹ê ✸ ✺€ï③ø✭đ✿ï ✻õ◗÷✦ó ❝✹đ ✻✻÷ ỷ ữú ỵ tý st ỵ týtý ỵ ỵ ựýỵ ỵỵt ỵựỵ t t ❦✴✳❫❀★◆✣✵✩➌❩✳✶➊▲✵❖❀✔❃✣✳✶❀★❦❏❀✍❃ ✳❚✳✶❑❜✹✿■✣❀❙❦❤■✣⑨❖✺★❁◗❀✖✳❚❑➈✺❖❃➅✳❜✵◗✹✻✺✿✱❬✺❖❑❚❑❤▼③✷❅❃✘✹✒❲❙✵❖✵✿✳✶❑➏✷➐✷❅④✣❃ ❘❤❀✖❁◗◆➏✳❚❑❤✼❅❣❤✼③✾✣✳❚■✚❑❚❁✿▼❹✷❳❀✖✳✶✵◗✳❜❦✣✱✣✺◗✼❅✱❀✚❀▲✘✹✿✵✩✷➐❄➈✷❅④ ❃❏■✴◆➏❀★❣❤✹❴✳❚❑✶✬ ❁✿▼✦✷❳✳✶❣❤❦✭✳❚❁✿✼✯❀❈✷❳✳✶✵✩❦✣❄➈✼❅■✴❀★✹♦❀★✹❉✵✿❑❤✼❅❘❜✷❅✹✿❀★✵◗✵✿❀✖✱✭◆➷❀★❁✖✳✶t✭❦✴■❏❑✶❀★❣❤❁➣❀❜▼✏❑❤✬❛❁◗✰➷❲❙✷❅❀➏❃✣❘❉❃✣❀★✳✍❀❴◆➅✹◗❀★■❏✳❬✳✶❲❙❁❖✳✶❀★✵◗✵◗❀❼✱✣✺✽❑✣✼✯◆❫✾✭✹✿✵✿✵✿❑€❀✔❁✻✺❖✳✶❑❜❃❏❲❙✳❚■✣✼✯❄✘✾✭✹◗✵✿✷✯❀➏✹ ▼✏✵✿❑❤✱✣❁✒❀❙❀❴◆✘✳❤✷❅✺◗✹◗✱❙✹✿✷❅❲❙❣❤✳❚✷❅❁✿✼❳✷❳✳✶✳✶❁◗❦✣✷✯✵✩✼❅❄❀ ✵✩✹✿❄✘❀✔■❏■❏✳✶❀❜❁❖✬❛✳✶✵✿●❻❀➏✱✭✺❖✷✯✹✍✼❅✾✣✷❅✹✿✹▲✵◗❀★▼✏❁❂❀✖✳❚✳❚✹✿❃❏✷❅❦✣✳✶✼❅✼❅❀❛❄✘✹✿✷➐✷❅▼❩✹❻✵◗■✴✱✣❀★❀★❁❻✹◗❀❙❣❤✳✶✳✶❁◗❃❏✷❥✳❚✳❚❦✣✼✯❄✘✼❅❀✻✹◗❀★✵✩✹❉❄✘◆✘■✴❀★❀❉❁✿✷❅➌❻❣❜✷❅❀❙✼✯✴✳✶❘❤❘❤❀✔❁◗❃✣❀★❀★❀✖❁❇✳❚✳❚❦✣✵✿✼❅❀❛❀❛✳❚❁◗❘❤❀★✹✿❁◗✾✣❀★❀✖✼❅✵◗✳✶✹✖❦✭✬✚✼✯❀✍➃❻❁◗❑✶❀★➌✸✹✿✾✣❀★✼❅❣❤✵◗❀✔✹✖❁✖✬ t❽✷✯❃ ❁✿❀✖✳❚✼❩✳✶■✣■✭✼✯✷❳✺★✳❚✵✿✷❅❑❤❃✭✹✖t✴✷❅✵❂✷❅✹✍✾✣❃✣✼❅✷ ❤❀✔✼✯❄❬✵✿✱❏✳❚✵❛✳ ✹✿◆✘✾✴✷ ❷✺✿✱➷❀★⑥✡❁✿❀★✵◗❲❙❃✘❀✖✺◗✵✍❑❜✱✣❣❤❁✿❃✣❀❉✳✶✷❳❵❜❁◗■✭✷❳✾✣✳✶❁✿❀❤❀❖❦✣t❽▼✏✼❅❀✔❀★■✣❁❇✹❻❁✿✳✶❑❜✷❅❦✭❃✘■❏✼✯✵✿❀❙❑❜❑❙✹✿✳❚❀✖✳➏■✣◆➫■✣✹◗✷✯❦✘❁◗❃✭❑➈❄ ❘❤✳❤✼❅✺◗✉❀❉❱▲✱➫◆✘✾❏✷❅✷❅✹✻✺✹✿❜✹✿✵✿✷❅❀★❑❫❲❬❁❉■✣✷✯❀★✼❳❁◗✵❉✳❚❑✣❁✿✳✶✺❖✷❅✵✩✼✩❀★❄❛✬✢✹✿✹✚✮✖❲❫①❜✳✶♠❤✳✶✼❅✼✢✵◗❞ ❁✿✻❣❤✷➐④✈✳✶✳✶❁◗❃✴✳❚✷❳✳✶◆€❃❏❦✣◆❫❀❖✼❅❀❉④✣❦✣✵◗❁◗✵✩❀★✷❅❄✘❃❏❃✣■✴◆✘❘❤❀★✹✻❀✖✹❉◆➫✳❚✵✿✼✯❑❜❦✘❽❘❤❄ ✵✿❀★✱✣✵◗✹❀❈✱✣✼✍❀★❲❙✳✶❁❴✾✘t✦❀✖▼✏✳❚■✴❲❫❃✣❀★✷❅✳✶❁✩❃✣▼✥❃€❑❤❘✶❁✿▼✏✳✶✾✭❲❬❃✴✼❏◆✷❅❣❤❃✣✳❚❘❙➀s❁✿❑❤✷❳✳❬✳✶✾✣❦✣✹✿✹◗✷❅✼❅✹✿❃✣❀★❀★✹❻❘❤❀★✾✘✼❅❑❜❀✚➌❾❃✘✺❖✵✿❑❙✼❅✮✖✾✣①❜✹✿✳✚①❤✵◗❀★⑤✺❖❁❛❑❜★t❷❲❙✳❚✺❖❃❏❲❙❑❤✳✶❲✚❑❜✼❅❄✘❃✚❦✭✹✿✷✯✷❅✹❇❃✭✹✖✺★✬❉❀★✳❚✹✻✼❅➊▲❀❉✵◗❃✣✱✣❑✶❀❀ ▼ ✵✿✱✭❀❉➁✘✷❅❃➈✾✭✵◗■✣❀★■❏❁✿❑❜❣❤✳❚✹✿❀✍✼✽✵✿✩❡⑤✣✱✴t❅✳✶✮✤✵✸✫✿✬ ✵✿✱✣❀❉◆✣✳❚✵❇✳❈✹✿❀★✵✍✺❖❑❤❃✘✵❇✳❚✷❅❃✣✹ ❬❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀★✹✸❑✶▼✢❲❙✷➐④✣❀✖◆❉✵✩❄✘■✴❀❤✬✒●❻✱✭❀❼◆❺✷✯✹◗✹✿✷❅❲❙✷❅✼❳✳✶❁◗✷❅✵✩❄ ♦❦✴❀★✵✩➌❩❀✔❀★❃€❑❤❦❤⑨✽❀✖✺❖✵✿✹ ✢✳✶❃❏◆ ❉✷❅✹ ◆✘❀ ✴❃✣❀✖◆€✳❚✹ ✤✾☞✿ ❁❀ ✿ ☞❀ ✉✫✣✬❡❋✭✮ ✾ ✿ ❁❀ ➌❻✱✣❀★❁◗❀❉✵✿✱✭❀❉✷❅❃❏◆✘✷❳✺★✳✶✵◗❑❤❂❁ ✾☞✿ ☞❀ ↕⑤❈✷❨▼✢❀★✷❅✵✿✱✣❀✔❁ ❇✮ ❑❤❁ ✷❅✹❻❲❙✷❅✹✿✹◗✷✯❃✭❘ ✥✷✩✬ ❀❜✬✯t✘✵◗✱✣❀★❁◗❀❉✷❅✹❻❃✣❑❛❲❬❀✖✳✶✹◗✾✣❁✿❀✔❲❙☞❀ ❀★❃✘✵✸❑✶▼③❣❤✳❚❁✿✷❳✳✶❦✭✼✯❀ ❬▼✏❑❜❁❩❑❜❦❤⑨❖❀✖✺❖✵ ✸❑❤❁▲❑❤❦❤⑨❖❀❴✺❖✵ ★t❷❑❜❁ ✉❋ ✞⑤❙✳❚❃❏◆€❣❤✳❚❁✿✷❳✳✶❦✭✼✯❀ ❁➫❀ ✷❅✹❂✳❚✹✿❄✘❲❙❲❬❀★✵✿❁◗✷❳✺✻❦✭✷✯❃✴✳✶❁✿❄ ✴❑❤✵◗✱✣❀★❁◗➌❻✷✯✹◗❀❤✙t ✾☞✿ ❝✮❜✬✍●❻✱✣❀✚✺❖❑❤❃✘✵✿❁◗✷❅❦✣✾✣✵✿✷❅❑❜❃€❑✶▼ ❣❤✳✶❁◗✷❳✳✶❦✣✼❅❀ ✵✿❑➏✵✿✱✭❀❛◆✘✷❅✹✿✹◗✷✯❲❬✷❅✼❥✳❚❁✿✷❅✵✩❄❉❦✴❀★✵✩➌✸❀★❀★❃ ✒✳❚❃❏◆ ❺t ✿ t✘✷❅✹✻✺❖❑❜❲❙■✣✾✭✵✿❀✖◆❬◆✘❀★■✴❀★❃❏◆✘❀★❃✘✵✍❑❤❃❫✷❅✵✿✹✸✵✩❄✘■❏❀❜❭ ✮❜✬✸❢✥▼ ✷✯✹❻❦✭✷✯❃✴✳✶❁✿❄✚❑❜❁❻❃✣❑❤❲❬✷❅❃❏✳✶✼✩❭ ✿ ❁❀ ↕⑤❉✷➐▼ t✘❑❜✵✿✱✣❀★❁◗➌❻✷❅✹✿❀ ✿ ☞❀ ✞✮❤✬ ❋✭✬✸❢✥▼ ✷✯✹❻✷❅❃✘✵✿❀✔❁✿❣❤✳✶✼➐✐✩❦❏✳✶✹◗❀✖◆❷❭ ✿ ☞❀ ●■❍ ❄❁❏❉❃ ❄☞❄❆❏❅ ❇ ❇ ✵✵ ❄❉● ❈❊❇❋❃ ❏✔❄❁❏ ❇ t✘➌❻✱✣❀★❁✿❀ ❫❁✿✾✣❃✭✹✻❑✶❣❤❀✔❁✻✳✶✼❅✼❏❃✭❑❤❃✣❲❬✷✯✹◗✹✿✷❅❃✣❘❉❑❜❦❤⑨❖❀✖✺❖✵◗✹❻▼✏❑❜❁❻❣❤✳✶❁◗✷❥✳❚❦✣✼❅❀ ❽✬ ❊✭✬✸❢✥▼ ✷✯✹❻❑❜❁❇◆✘✷❅❃❏✳❚✼❷❑❤❁❻❁❖✳✶✵✿✷❅❑❚✐✉✹❖✺★✳✶✼❅❀✖◆❷❭✢✺❖❑❜❲❙■✣✾✣✵◗❀✍✵✿✱✣❀✍❁❇✳❚❃ ✘✹ ✳❚❃❏◆ ▲▼❑✤❅ ❇❇ ✵✵ t✣✳✶❃✴◆❙✵◗❁✿❀✖✳❚✵ ✳✶✹❻✷❅❃✘✵✿❀★❁◗❣❤✳✶✼➐✐✉✹❖✺★✳✶✼❅❀✖◆➎✬ ◆✘✷ ❷❀★●❻❁✿❀★✱✘❃✘✾✣✵▲✹❴t❏✵✩❄➈✵◗✱✣■✴❀❙❀★✹❴◆✘✬ ✷❅✹✿✹◗✷❅❲❙✷❅✼❳✳✶❁✿✷❅✵✩❄➏❦❏❀✔✵✩➌❩❀★❀✔❃➷❑❤❦❤⑨❖❀✖✺✽✵✿✹❛✺★✳❚❃ ❦✴❀✚✺❖❑❤❲❬■✣✾✣✵✿❀❴◆❫❀★❣❤❀✔❃ ➌❻✱✣❀✔❃➷✵✿✱✣❀➏❣❤✳✶❁◗✷❥✳❚❦✣✼❅❀★✹❂◆❺❀★✹❇✺❖❁◗✷❅❦✣✷❅❃✣❘❫✵✿✱✣❀➏❑❤❦❤⑨❖❀❴✺❖✵✿✹❛✳❚❁✿❀➏❑✶▼ ✬ ✝ ✥✣✵② ❬✣❭② ❚✘ ✝ ✢ ✗ ✢ ✙✘➃✗ ✆✎ ➮ ➞ ✹ ✲✻ ✶✎ ✶✎ ✥✣❭✟ ✝ ✼❞✠♠ ➢ ➑✶➋ ➛❤✏✣ ☛♠ ✫✹ ➇✐➑✶➋ ✻ ❝➳ ✥✣ ➸➟ ➇✐➑✶➋ ➑✶➋ ➛✌ ✙✎ ➇✐➑✶➋ ➛✔ ❃⑤ ✖Ñ ✾⑧✖⑨✞➨ ♦⑩ ❯⑦ ✁★✫❁✏✧✩☎✯➀❂✂✆ ❹❳ ❄€✚✂☛ ✄✧✚☞ ✩✮ ❨✧✚❁✿☎ ❬€✒✬ ✡★✵✂☛☎✩✮✼➥❀✂ ✩✮ ☎❙✂❂❁ ✥◗✼❳ ❄€✚✂☛ ✄✧✚☞ ➸✧➛❁➜☎ ❬€✜✬ ✁★✵✂✆☎✩✮ Ó★❭◗ ✁★✵✂☛  ➥➙◗✆☎❙☞ ✡★✵✂☛  ✶✱✼❁✿❩✸☎✚✧ ✜✎ ✶✎ ➃✹ ✓✎ ✽✻ ✾✹ ✽✻ ✍✔ ➝ ✹✿➟✏➞❃➠✆✻ ✠➁ ❊➟ ➯➠ ✚✌ ➍ ➝ ✹➜➟✓➞✿➠✲✻➚➢ ➪ ➋❂➶♦➈ ➍ ➪ ➑❹à ➟ ❊➠✲✻ ❀✹ ✽✻ ➋ ➇✐➑✶➋ ➢ ❀✹ ✼✻ ➢ s➟ ➼➳ ✍✔ ➋ ➝ ➝ ➑❹à ➋ ➑❹à ➢ ➑à ➢ ➝ ➯➠ ➢ ➇✐➑✄➋ ➑à ✹ ➋ ❊➳ ❀➳ ▲➳ ➼➳ ➑❹à ➋☛➶♦➈ ➋ ➝ ➑❹à ❝✹ ➇✽à✩➋ ➢ ➇✽à✩➋ ➼➳ ➇✐➑✶➋ ➋ ➞ ❣❵ ➑❹à ➋ ➝ ➇✲à✯➋ ➋ ➋ ➢ ➑❹à ➡è ➑✶➓ ✙✎ ▲➮ ➑✶➋ ➢ ▲➳ Ú ➑✶➋ ➢ ➈ ➈ Ú ➑✶➋ ❄✻ ❝➛ ✻➞✒➟ ❉➜ ◗€ ✻➞ ★➜❻➝✡➜ ❙❘ ❯❚✭➜ ✡➛ ③➠➎➞✒➟ ✿➝ ❱❘ ➟❻➞ ❉➜ ✍➠ ✮❤✮ é❻ê ❲❍ơ❷ï✦ð✣÷ ✒ø✣đ❨❳❷ï✦ð✣đ ✒ú ❝ï❬❩ ✒ø➅ơ❷õ◗ư✻ó❜ð✣÷✦ø✣đ◗ú ❝÷➎ð❺í ✻ó ●❻❦✴❑❤✱✣✵✿❀★✱➷❁◗❀❙❑❜❃❀❖④✣✵◗✷❅✹✿✱✣✵➏❀✚✳❫✵✩❄✘✼❳■❏✳✶❁✿❀✚❘❜❑❚❀❛▼s❃✘◆✭✾✣✳✶❲✚✵❇✳ ❦✴❀★✳❴❁✍❣❤✳✶❑✶✷❅▼❂✼❳✳✶✺✽❦✣✼✯✾✭✼❅❀❉✹✿✵✿✳✶❀✔❃❏❁✿✷❅◆ ❃✣❘ ❑❤❃➫✳❚✼✯✵✿❘❜✱✭❑❤❀❙❁◗✷✯✵◗■❏✱✣✳❚❲❙❁✿✵✿✹❻✷❳✺❖✷❅✾✭❃➷✼❥✳❚✵◗❁✍✱✣❀✚■✣✾✣✼❅✷✯❁✿✵◗■✴❀★❑❤❁❇✹◗✳❚❀⑧✵✿✾✣✳❚❁◗❃❏❀❤✬❬◆ ●❻✳❚■✣✱✣■✣❀⑧✼❅✷❳✺◗✺★✱✣✳✶❑❜✵◗✷❅✷❥❑❤✺✽❀✚❃✦✬❈❑✶▼✻❢✥▼❂✺❖✼❅✺❖✾✣✼❅✾✣✹✿✵◗✹✿❀★✵◗❁✿❀★✷❅❁❛❃✣❘✳✶❃✴✳❚✳✶✼❅✼❅❘❤❄✘❑❤✹✿❁◗✷❅✷❅✹✍✵✿✱✣✷✯✹✍❲➑✾✣✹◗◆✘❀✖❀★◆➅■✴❀★✳❚❃❏✹❛◆✘✳✹ ◆✘◆✘❀★✷❅✹❇✹❖✺✽✺❖✼✯❁✿❑❜✷❅✹✿■✣❀❤✵◗✬✷❅❣❤❀✚❑❤❁▲❀❖④✣■✣✼❅❑❤❁❖✳✶✵✿❑❜❁✿❄❫✵✿❑✘❑❜✼✉t✴✷❅✵✻✷❅✹✍■✴❑❤✹✿✹◗✷❅❦✣✼❅❀❉✵✿❑❫✵✿❁◗❄❫✹✿❀★❣❜❀★❁❇✳❚✼❩✳✶✼❅❘❤❑❜❁✿✷❅✵✿✱✭❲❙✹❻❑❤❃ ✵✿✱✣❀➏✹❇✳❚❲❙❀❉◆✣✳✶✵❖✳❬✵✿❑❙✹◗❀★❀✚➌❻✱❏✳❚✵✻✵✿✱✭❀ ◆✣✳❚✵❇✳✈❲⑧✳❴❄ ❢✩❃❬❘❤❀★❃✣❀✔❁❇✳✶✼✩t✭❲⑧✳★⑨❖❑❜❁❩✺❖✼❅✾✣✹◗✵✿❀★❁◗✷✯❃✭❘❙❲❙❀✔✵✿✱✣❑✣◆✘✹❻✺★✳✶❃❫❦✴❀❛✺❖✼❳✳✶✹◗✹✿✷ ❏❀✖◆❬✷❅❃✘✵✿❑➏✵✿✱✣❀❼▼✏❑❤✼❅✼❅❑✶➌❻✷❅❃✣❘❉✺★✳✶✵◗❀★❘❤❑❜❁✿✷❅❀★✹✖✬ ✮❜✬ ✜✭✗✶✓✖✧✥✓✖✧ ✴✛✦✧✥✛ ➷✕✘✓ ✢✑ ✬ ❀✖✵✿➒✍✱✣✳❤✷❅❀✸✺◗❣❤✱➏❀★▼✏❑❜❃❫■❏✼❅✳✶✼✯✳❛❑✶❁◗➌❻✵✿◆✣✷❅✷❅✳❚✵✿❃✣✷❅✵❇❑❤❘❻✳❚❃❈❦❏❁◗❀✖✳✶❁✿❀★❵❜✹◗■✣❀✻✾✣❁◗✷❅❑✶❁✿❀★▼❀★✹✿❲❬❀✔❫❃➈❀★✵◗❑❤❃✘✹❹❦❤✵✿⑨✽✳▲✹❴❀✖❭ ✺❖✺❖✼❅✵✿❖✾✣✹▲✮ ✹✿✢✵◗❑❤❀★❀✖❁❻❁✖✳❜◆✣t✘✺◗✱✚✳✶✳✶✵❖❃✴❘❤✳❉◆❛❁✿✵◗❑❜❸ ✾✣✾✣■✣■➏✼❅❀★❲✚✢✹❴t❏✬❽✾✣✳❈✹✿●❻✵✢■❏✱❏✺❖✳✶✳❚❑❤❁◗✵✦❃✘✵✿✵❇✷❅✷❅✹✖✳❚✵✿t✶✷❅✷❅❑❤❃❙✷❅✵✢❃✭✳✶✷✯✺❖❃✭✵✢✼❳✳✶❘❉✼❅✹✿❀✖✹◗❲❙✳✶✷ ✹◗❏❀★✵✒❀★✵◗✹✢❑❤✱✣❃✣❑✣✵✿✱✣❀✸◆✚❀❻❑❤✺❖❦❤◆✣❑❤⑨✽✳❚❃✭❀✖✵❇✹✿✺❖✳❻✵✿✵✖❁◗✷❅t✣✾❏❃✘✳❚✺❖✵✿❃❏✵◗❑✍✹❼◆ ❸❉❸✈✉❘❜❋ ■❏❁✿❽❑❜✳✶❀✖✾✣❁◗✳❜✵✿■✣✺◗✷❅✵✿✹✖✱✚✷❅t❚❑❜❑❤➌❻❃✣❦❤✱✣✹❩⑨❖✷❳❀✖❑❚✺✿✺✽✱❈▼✦✵❩✵✿✵✿❲✚✱✣❑❤❀❉❘❜✾✣❀★◆✣✹◗✵✿✵✦✳❚✱✭✵❇❦✴❀★✳✭❀★❁✒t✘✼❅✹❇❑❤➌❻✳❚❃✣✵✿✱✣❘✍✷❅❀★✹✩✵◗❁✿▼✥❑❄❀ ❀❖➌❻④❏✷✯✳❤✼❅✼✴✺❖❦❏✵◗✼✯❀❈❄❬❦✣❑❤❁✿❃✣✷❅❀❀❈❏❘❤❄❫❁✿❑❜◆✘✾✣✷❅✹❇■✦✺❖✬✒✾✭rs✹✿✹✿❑❤❀❴✵✿◆€✷❳✺❖✼❳❀✍✳✶✵◗✵◗❀★✱❏❁❻✳✶✷❅✵▲❃❙✵✿✵◗✱✣✱✣❀✍✷❅✹✻✹✿❀❴✺✿✺❖✱✴❑❤✳✶❃❏■✣◆ ✵◗❀★❁✿❁✖❀❴✬ ❵❤✾✭✷✯❁◗❀★❲❙❀✔❃➈✵❻✷❅✹✸❁✿❀★✼❳✳ ④❺❀❴◆❫✷❅❃⑧✹◗❑❤❲❬❀❻▼✏✾✣⑦✔⑦★❄❙■❏✳❚❁✿✵◗✷✯✵◗✷❅❑❤❃✣✷❅❃✣❘➏✵✿❀✖✺◗✱✣❃✭✷❥❵❜✾✣❀✔✹✻➌❻✱✣✷❳✺◗✱ tỵ ỵỵ ỵ st ❁✿➈❀★✷❅✼❳❃❏✳✶◆❺✵◗✹❻❀✖◆❫❑✶▼③✵◗❑✚❑❜✵✿❀✖✱✣✳❤❀✔✺◗❁❂✱€✺❖❑❜❁◗✷✯✵✿✵◗✱✣❀★❀★❁✿❁❴✷❳✳❈t✣➌❻▼✏❑❜✱✣❁ ❀✔⑨✽❁✿✾❏❀✖◆✘✳❚✹❂❘❤✷❅❑❜❃✣❦❤❘➏⑨❖❀✖✵✿✱✭✺❖✵◗❀❛✹✻❵❜❑❚✾❏▼♦✳✶◆❺✼❅✷❅✷ ✵✩❷❄❛❀★❁◗❑❚❀★▼③❃✘■❏✵❂✳❚✺❖❁✿✼❅✵◗✾✣✷✯✵◗✹◗✷❅✵✿❑❤❀★❃✣❁◗✹❼✹❴✬ ✳❚❁✿❀ ➣▼✉✳✶❁✻✳❚■❏✳✶❁◗✵ ✚❑❜❁❻❣❤❀★❁◗❄ ◆❺✷ ❷❀★❁◗❀★❃✘✵✖✬✸●❻✱✣❀★❁◗❀❛✳✶❁◗❀❉❣❤✳✶❁◗✷✯❑❜✾✣✹ ●③❑✶▼✻❑❫✵✿✳❤✱✭✺◗❀⑧✱✣✷❅■✴❀★❑❤❣❜✹◗❀❉✹✿✷❅❘❤❦✣✼❅✼❅❑❤❀❙❦✴✳✶■✴✼✦✳✶❁✿❑❜✵◗■✣✷❅✵✿✵✿✷❅✷❅❑❤❲❫❃✣✳✶✹❴✼❅✬➫✷❅✵✩❄❛❢✩❃✣✷❅✹✿❃€✵◗❀✖■❏✳❤✳❚◆❷❁✿t✸✵◗✷✯❲❬✵◗✷❅❑❤❑❤❃✣✹✿✵❉✷❅❃✣✳❚❘❚■✣✐✉❦❏■✣✳❚✼❅✷❳✹✿✺★❀✖✳✶◆ ✵◗✷✯✺❖❑❜✼❅❃✣✾✣✹❛✹✿✵◗✳❜❀★◆✘❁✿✷❅❑❤❃✣■✣❘❫✵➏➌✸❑❤❑❤❃✭✾✣❀❙✼❳◆❬❑✶▼✍❁✿❀✖✵✩❵❜➌❩✾✣❑ ý ỵ ýt ❀❴✳❤t✭✺◗➌❻✱ò✱✣✺❖❀★✼❅❁✿✾✣❀✚✹◗✵✿❀❴❀★✳❤❁✚✺◗✱➅✷❅✹❉✺❖❁◗✼❅❀★✾✣■✣✹✿✵◗❁◗❀★❀★❁❉✹✿❀★✷❅❃✘✹✍✵◗❀✖❁✿◆❀★■✭❁✿❦✘❀★❄➷✹◗❀★✵✿❃✘✱✣✵✿❀❬❀✖◆ù❲❙❦✘❀✖❄€✳❚❃✣❑❤✹✍❃✭❣❤❀❛✳✶❑❚✼❅✾✣▼❹❀✚✵◗✱✣❑❚❀✚▼✻❑❤✵✿✱✣❦❤❀❬⑨❖❀❴❑❤✺❖✵✿❦❤✹❉⑨❖❀✖✼❅✺✽❑✣✵✿✺★✹✚✳❚✵✿✷❅❀✖❃➷◆ ✵✿❃✣✱✣❀✖❀❫✳❚✺❖❁❉✼❅✾✣✵✿✱✣✹✿✵◗❀❙❀★❁ ✺✽❻❀★❃✘✳❚✵✿❃❏❀★◆ ❁ ❑✶❲❙▼❩❀✖✵◗◆✘✱✣✷❅❀❙✾✣❲➑✺❖✼❅✾✣✹◗✹✿✷✯✵◗⑦✔❀★❀✖❁✖◆ ✬✈◆✣●❻✳✶✱✣✵❖✳✶❀★✹✿❦❏❀✚✳❚✹✿✱✭❀★❀★✹❴✾✣✬ ❁✿✷❅✭✹◗✵✿❑❤✷❳❁ ✺✚❏✺❖❃❏✼❅✾✣◆✘✹✿✷❅✵◗❃✣❀★❘➷❁✿✷❅❃✣✺❖❘❫✼❅✾✣✹◗❲❬✵✿❀★❀★❁◗✵✿✹❙✱✣❑✣➌❻◆✘✷❅✹✍✵✿✱ ➌✸❑❤✺❖❑❤❁ €❲❬➌❩■✣✼❅❀✔❀❖✼✯④ ❽▼✏✹◗❑❜✱❏❁ ✳✶❏■✴❃❏❀★✹❙◆✘✷❅✳❚❃✣❃❏❘❬◆ ✹✿■✣▼✏❑❤✱✣❁✚❀✔❁✿✺❖✷❳✺★✼❅✾✣✳✶✹✿✼➐✐✩✵◗✹✿❀★✱❏❁✿✷❅✳❚❃✣■❏❘➷❀❴◆➷❣❜❀★✺❖❁✿✼❅❄➷✾✣✹✿✼❳✵◗✳❚❀★❁✿❁✿❘❤✹➏❀❫✷❅❃ ◆✣✳✶✹◗✵❖❲⑧✳€✳✶✹◗✼❅❀★✼❷✵✿✵◗✹❴❑ t ■❏✷✯❃❫✳✶❁◗➁✘✵✿❀✖✷❅✵✿✺❖✷❅✵◗❑❤✷❅❑❤❃✭❃ ✷✯❃✭✫✭❘✶✐✩✬ ❯✴❦❏✬✳✶✹◗❀✖◆❬❲❙❀★✵◗✱✣❑✣◆✘✹✻❃✣❀✔❀✖◆€✵◗❑❙❦✴❀❉❀❖④✣✵✿❀✔❃❏◆✘❀✖◆❷✬❉⑩✢✳❚❁✿✵✿✷❅✵◗✷✯❑❜❃✣✷❅❃✣❘✶✐✩❦❏✳❚✹✿❀✖◆€✺✽✼✯✾✭✹✿✵✿❀✔❁✿✷❅❃✣❘❙❲❬❀★✵✿✱✭❑❺◆❺✹❂✳✶❁◗❀❉✹✿✵◗✾❏◆✘✷❅❀✖◆ ✷❅❃ ◆✘❀★■✣✵◗✱ ❋✭✬ ✧✥✕✘✗✶✜✣✗ ✢✧ ✜✣✌ ➷✕✘✓ ✢✑ ✬ ⑥➉❲❙❀★✱✣✵◗✱✣✷❅❀★❑✣❁❖◆❛✳✶❁❖✺★✺✿✳❚✱✭❃❙✷❥✺✔❦✴✳✶✼✸❀✻❲❙✺❖✼❳✳✶❀★✵◗✹◗✱✣✹✿✷ ❑✣❏◆➷❀✖◆❬✺❖❁✿✳✶❀✖✹✒✳❚❦✴✵✿❀★❀★✹❙✷❅❃✣✳❘❉❀★✱✣✷❅✷❅✵◗❀★✱✣❁❇❀★✳❚❁ ❁❇✺◗✱✣✷❳✺★✳✶✶✼✻ÿ ỵ ỵ ỵýỵ t ỵ ựt tt t t t ỵ ỵýỵ t tựt tt ❀❤❃ ✬ ❦❏❀✖✺✔✳✶✾✣✹◗❀❛✷❅✵❻✺★✳✶❃✣❃✭❑❤✵✻✺❖❑❜❁✿❁✿❀❴✺❖✵✍❀★❁✿❁◗❑❤❃✣❀★❑❜✾✣✹❂◆❺❀✖✺❖✷❅✹✿✷❅❑❤❃✭✹✖✬ ❢✩✳✶✵ ❘❤❘❜✺✔✳✶✼❅❑❤❃➏❲❙❦❏❀✔❀✻❁❇✳✶✳❜✵◗◆✘✷❅❣❤❣❤✳✶❀✻❃✘✳✶✵❇✼❅✳❚❘❜❘❤❑❤❀★❁✿❑❜✷❅✵◗✾✣✱✣✹✦❲❝✵◗❑❉✳✶✺❖❃❏❑❤◆❬❲✚✵✿❦✣✱✭✷❅❀★❃✣❃€❀✢✷❅❁✿✵✿❀ ❀✔❏❁❇❃✣✳✶✷❅✵◗❃✣✷❅❣❤❘❙❀✸✵◗❁✿✱✣❀★❀❉✼❅❑✣❁◗✺★❀★✳✶✹✿✵◗✾✣✷❅❑❤✼❅✵▲❃✚✾✣✳✶✹✿❃❏✷❅❃✣◆❈❘✚✱✣✷❅✷❅✵✿❀★❀✔❁❇❁❇✳❚✳✶❁❇✵◗✺◗✷❅✱✣❣❤✷❳❀✍✺★✳❚❁✿✼❺❀★✼❅✳❚❑✣❘❤✺★❘❜✳❚✼✯✵✿❑❜✷❅❲❙❑❤❃✦❀★✬✸❁❖✳✶➁✘✵◗❑❤✷✯❑❜❲❬❃✻❀✻❦✘✹❖❄ ✺★❏✳✶✼❳❁◗✳✶✹✿❦✭✵✒✼✯✾✭❀❉✹✿✺❖✷❅❃✣✼❅✾✣❘✻✹◗✱✭✵✿❀★✷✯❁◗❀✔✷❅❁❇❃✣✳✶❘⑧❁❖✺◗✳❚✱✣✼✯✷❳❘❜✺★❑✶✳✶✐✼ ❁✿✺❖✷❅✼❅✵✿✾✣✱✣✹✿❲❬✵◗❀★✹✖❁✿✷❅t✘❃✣✹◗❘❬✾❏✺◗❲❙✱ ❀★✳❚✵◗✹❂✱✣❑✣♥♦◆✘❢✿✹❹➀❻✳❚❶❻❁✿❀✍➃➋✹✿✳✶✵◗✾❏❃❏◆✘◆€✷❅❀✖❶❻◆❫➆▲✷❅➀✻❃❫➇❻➁✘❀✖t✭✺❖✱❏✵◗✳❴✷✯❑❜❣❤❃€❀✍❦✴✫✣❀★✬❡❞✣❀★✬❃➷◆✘❀★❣❜❀★✼❅❑❤■✴❀✖◆❫❦❏✳❚✹✿❀✖◆ ❑❤❃❫✹✿✾✴✺✿✱➫✳✶❃€✷❅❃✘✵✿❀★❘❜❁❇✳❚✵✿❀✖◆€✳❚■✣■✣❁◗❑➈✳❤✺◗✱✦✬❻➃s✷✯❀✔❁❇✳✶❁❖✺◗✱✣✷❳✺★✳✶✼ ự ý ỵ ◆✘◆✘✶✷❅✷❅✬✢✹❇✹✿✺✽✵❖●❻❑✶✳✶✱✣❣❤❃❏❀❻❀★✺❖❁◗❀❫❘❤✷✯❃✭❀★❦✴❃✭❘⑧❀★❀★✵✩✺❖❁❇➌✸✼❅✳❚✾✣❀★✼❏✹◗❀★✷❳✵✿❃↕◆✘❀★❀✖❁◗✳❼✹❉❑❤❦❤✷✯❑✶⑨❖✹♦▼❹❀✖✵✿✺✽✳❚❑❛✵✿❁✿✹✖❦✣✺❖✬↕❑❜✷❅✵◗❃✘❁❇➁✘✵✿✳✶✾❏✷❅❁◗❃✘✺◗❄❫✾✣✱ ❀❻✹✿✱❏❲❙❘❤✳❚❁◗❀★■❏❑✶✵◗➌❻❀★✱✣✹❴✷✯❑✣✬❛❃✭◆✘❘❂❶✸✹❙✵◗✼❅✺★✱✣✾✣✳❚❀✻✹◗❃ ✵✿❘❜❀★✷❅❁◗✴❣❤✷✯❃❏❃✭❀★◆❃❘ ✷✉❲❙✺❖✬✼❅❀❤✾✣✷❅✬❅❃✣✹✿t✴✵◗✷❅▼✥❲❛❀★❑❤❁❩❁✍✾✭✹◗❲❧❑✍❀✖✳❤✼✯❃✘✺◗❑❜✱➅✾✣❃✣❲✚❘❉◆✣❦✴✳❚✳✶✵❇✹✢❀★✳❬❁❻✵✿✱✭❑✶■✴❀✻▼✒❑❤■✴◆✘✷❅❃✘❀★❑❤✵❂❃✣✷❅❃✘✹◗➌❻✵✿✷✯✵✩✹✖✷❅❄✵◗✬▲✱✣✏➁✘✷❅❃✘❃ ✾❏✾✣✺◗✳❬❲✚✱ ❘❤❦✴✳➏✷❅❀★❣❜❁❽❲❙❀★❑✶❃ ❀✔▼❷✵✿✺✽❑❤✱✣✼✯❦❤❑✣✾✭⑨❖◆❫✹✿❀✖✵✿✺✽❀✔✺★✵✿❁✖✳✶✹✸t✢❃ ❑❤✵✿❦❏❁✒✱✭❀❉❀✚◆✣✳✶✾✭❃✣✵❖✹✿❀★✳▲❀✖✷❅❘❤◆❫■❏✱✘❑❜✵◗❦✴✷✯❑ ❃✘❑❤✵◗❁✿❏✹✱✭✼❅✢✵◗❑➈❀★✷❅❑✣❃❉❁✻◆ ❑❜✵◗✱✣❑✶✾✣▼✻❀ ✵✻✳❬✿❃✣❃✣❑❜❘❤❀✔✷❅✷❅✹✿✷✯❣❤❘❜❀ ❀★✱✘❃➫✏❦❏❑❜❑❜✾✣❁❇❁✿✳❜✵✿✱✣✼❅◆✘✷❅❑✘✷❅❀★✾✣❑✣❁✿✹❉✹◆ ★✍✱❏t❷✳❚❀❖✳✶④❏✹✍❃✴✺❖◆€✵✿❀★❑€❀✖◆✘◆❺✺❖✷❅✹❻✹❇❑❤✺❖❃✘✹✿❑✶❑❤✵❖❣❜✳✶❲❬❀★✷❅❁❂❃➅❀✒✺✽✵✿✳✶✼✯✱✭✾✭✵✍❁✿✹✿❀★✼❅✵✿❀✖✹◗❀✔✱✣✳✶❁✿✹◗❑❤✹✍✵❛✼❳◆❷❑✶✳ ▼ t ✳✶❁✿❦✭✷✯✵◗❁❇✳❚❁✿❄❙✹◗✱❏✳✶■✴❀❤✬ ❖◆ ●✸■ ✫■✾❇ ✖❇ ❈❽ ✥ỵ ❈❋✺❖ ❭❇ ♦❶❆⑧ ✖❖ ➦❺ ✓⑧ ✞❇ t⑧✖⑨✞➨ ❈❋ ❆❏❈❑ ❆❋❈❖ ➾❽ ✫⑧ ❆❅ ❯❶❛➨ ❈❻ ✴⑧❈⑩ ✍✌ ỗ ✲✻ ✚④ ❲❁❃✧✯☎❙✂❂❁ ✁➀☛✧➾☎❙✧✯ ✄◗✼€❙✂❂❁ ✥◗☛★✞❁✏✧✚€✚❘✫★ ❬é✯❩❚✧ ✒❒ ✑✔ ✰❒ ✏❮ ✩❮ ✑✔ ✎ ✞✹ ✼✻ ❭❳ ➸✧✚✂✆★ ❄❵ ✹ ✲✻ ❭❳ ❨✧❙☞✽◗ ❬☞ ✓✎ ✛ ❈✇ ✝ ❞ ✝ ✖♠ ❄❞✖✣◆✘ ✍✌ ❀✂✼✪✼✪❂ ✶◗ ❨✧✩☎✚✂✼❁ ✁➀❂✧ ✜✂✼✪✼✪❂ ✶◗ ❨✧✩☎✚✂✼❁ ✁➀☛✧❝✂➛✳✲✳✵☎✚◗❄✂✽€✚❘ ▲☞ ✁➀ ✡➀❂✧ ✰❒☛✬✚◗✼❁✥❁❃◗ ❀❳✏❩✼✳✲❮ ❨✹ ✂✚✳✲✳❭☎❙◗✼✂✲€➛❘ ✴✌ ➾✌ ✙✻ ❪☞ ✁➀ ➡❒✩❁✏◗✚✳✙❳❙☞✽◗☛Ư❆★✆❮ ✫✔ Þ✹ ✚✻ ❀✎ ✍✔ ❈✎ ❊✌ ➛✌ ❈❥ ❣② ✢ ✙✘❦♠ ❄❞✖✣◆✘ ❼✌ Ó☞✲✧✯★ ✶❁✿✮ ✒✹ ❙✻ ❨✌ ❨❒ ✫❮ ➡✹ ✚✻ ✁➀☛✧ ✮✖❋ ➛ ❻➞✒➟ ➪➛ ③➠➎➞✒➟ ❂➝ ♦➠ ✿➠ ✷✯❱❂✺❖✹✚✼❅✾✣♥✸✳➫✹✿➁✣✵◗❶✸❀★◆✘❁❂❀★⑥✍❃✣✳❚r❧✹◗❃❏✷✯✵✩✳✶✷❅❄❜✼❅✹✍❄✘✐✩❦❏✹✿✳✚✷❅✳✶✹✖✵✩✹◗✬✢❄✘❀✖◆ù❱▲■✣✷❳❀★✺★❲❙❃✣✳✶✹◗✼✒❀★✷✯✵◗✵✩◆✘✱✣❄❜❀✔❑✣✐✩❃✣❦❏◆➫✹✿✳✶✷❅✵✩✹◗➌❻❄❜❀✖✱✣◆€✐✉❦✴✷❳✺◗✺❖✳✶✱ò✼❅✹✿✾✣❀❴✺❖✹◗◆€✵✿❑❜❀★❲❙❲❬❁◗✷❅■✣❀★❃✣✵✿✾✣❘✚✱✣✵◗❑✣❀★❲❙✹✚◆❫❀★✳✶✵◗➌❻✱✣❃➅✱✭❑✣✷❥✳✶◆✘✺◗✾✭✹✻✱€❘❤✳✶❲❙❘❜❁◗❁✿❀✍❀✔❑✶❃➈➌❻✹✿✵✿✵◗✹❉✾✴❀✖◆➷◆✘✺❖✷❅✼❅❀✖✾✣✺❖✼❅◆❫✹◗✾✣✵✿✹◗❀★✷❅❃⑧✵✿❁◗❀★✹❛❁◗➁✘✷✯✳❤❀❴❃✭✺★✺❖❘➷✺✽✵✿✷❅❑❤❑❤❑❤❁❇❃€❁❇◆❺◆❺✷✯✫✭❃✭❀★❁✿✬❘❙♠✭✷❅❃✣✬ ✵✿❘❑❫▼✏✳❫❑❤❁✚◆✘❀★✳✶❃✣✾✭✹◗✵✿✷✯❑❤✵✩❄❫❲❫✵◗✳✶✱✣✵◗❁✿✷❥✺➏❀★✹◗✳✶✱✣❃✴❑❤◆➷✼❳◆❷✬➏✷❅❃✘➊✍✵✿❀★⑩✢❁❖✳❤●❻✺❖❢✿✵◗❶❻✷✯❣❜➁ ❀ ❯✴✬✌❭ ✗✶✧ ✜✴✑★✕ ➷✕✘✓ ✢✑ ✬ ⑥➧✵✿✱✣❀★❘❜❃➫❁✿✷❳■✴◆❜✐✩❀★❦❏❁✩▼✏✳✶❑❜✹◗❁✿❀✖❲❬◆❫✹❼❲❬✳❚❀★✼❅✵✿✼✦✱✣❑✶❑✣▼❻◆€✵✿✱✭❵❜❀ ✾❏✳❚✺❖❃✘✼❅✾✣✵✿✷❅✹◗⑦★✵✿❀★❀★✹✍❁◗✷❅❃✣✵✿✱✭❘❫❀❛❑❤❑❜■✴❦❤❀★⑨❖❁❇❀✖✳❚✺❖✵✿✵❉✷❅❑❤✹◗❃✣■❏✹✍✳❤✺✽❑❜❀❛❃ ✷❅✵◗❃✘✱✣✵✿❀❛❑❫❘❜✳ ❁✿✷❳❏◆ ❃✣✷❅✹✿✵◗✵✿❀❛❁◗✾❏❃✘✺❖✾✣✵◗❲✚✾✣❁✿❦✴❀ ❀★❁✻✥✷✉✬❑❚❀❤▼❹✬❅t✴✺❖❑❤❀★✼❅❃➫✼❅✹✻✵✿➌❻✱✭❀ ✱✭✷❥❵❜✺◗✾❏✱ ✳❚▼✏❃➈❑❤✵◗❁◗✷❅❲⑦★❀✖◆ ✳✚✹✿❘❜■❏❁✿✳❜✷❳◆❫✺❖❀ ✹✿★✵◗✬➏❁✿✾❏●❻✺✽✱✣✵✿✾✣❀➏❁◗❲⑧❀❤✬➏✳❚✷❅❢✩❃ ✵ ❑❤✳❤❦❤◆✘⑨❖❣❤❀✖✳❚✺✽❃➈✵✿✵❖✹✖✳✶t❷❘❜✳❚❀❛❃❏❑❚◆❙▼✻◆✘✵✿❀✔✱✣■❏✷❅❀★✹❛❃✴✳❚◆✘■✣❀★■✣❃✘❁✿✵✍❑✘❑❤✳❤❃✣✺◗✱➷✼❅❄✚✷❅❑❤✹❉❃❫✷❅✵✿✵◗✹❈✱✣▼✉❀✍✳✶❃➈✹◗✵❉✾✭❲✚■✣❁◗❦❏❑❺❀★✺✽❁✸❀★✹✿❑✶✹◗▼❩✷✯❃✭✺❖❘❀✔✼✯❅✵◗✹❻✷✯❲❬✷❅❃❙❀❛❀❴➌❻✳❤✺◗✱✭✱ ✷❥✺◗◆✘✱➷✷❅❲❙✷❅✹❉❀✔✵✩❃✣❄✘✹✿■✣✷❅❑❤✷❳❃✚✺★✳❚✷❅✼✯❃❬❅❄€✵✿✱✣✷❅❃❏❀❛◆❺❵❜❀★■❏✾❏❀✔✳❚❃❏❃✘◆✘✵✿✷❅❀★⑦★❃✘❀✖✵➏◆❬❑✶✹✿▼✻■✴✳❤✵✿✱✭✺❖❀❤❀❙✬ ❃✘✾✣❲✚❦✴❀★❁✍❑✶▼❂◆✣✳❚✵❇✳ ➌❻➁✘●❻✱✣❢✿✷❳✺✿r✻✱€➒↕✳❚❁✿✷❅❀✍✹❻✳✍❦❏❑❜✵✩✵✿❄✘✱❫■✣✷❳❘❤✺★❁◗✳✶✷❳✼✴◆❜❀❖✐✉④❏❦✴✳✶✳✶❲❬✹✿❀❴■✣◆⑧✼❅❀❩✳❚❃❏❑❚◆❫▼③✳❉◆✘❀★❘❜❃✣❁✿✷❳✹◗◆❜✷❅✵✩✐✩❄❤❦❏✐✩✳✶❦❏✹◗✳❚❀✖✹✿◆➏❀✖◆❷❲❙✬✸❀★➒✍✵◗✱✣❁✿❑✣✷❳◆❜◆❷✐✩✬✢❦❏❶❻✳❚✹✿❿❷❀✖❢✿◆❫→✍✺❖➆✻✼❅✾✣➇ù✹◗✵✿✳✶❀★❃❏❁◗✷✯◆✈❃✭❘✚✰➅❲❙✳❴❣❤❀★❀❖✵◗✐✿✱✣❶✸❑✣✼❅◆✘✾✣✹❹✹✿✵◗✳❚❀★❁✿❁❩❀❉✳✶✹◗❁◗✵✿❀✻✾❏◆❺✵✩➌✸✷✯❀❴❑❛◆❙✺❖✷❅✼❅❃€✾✣✹◗➁✘✵✿❀✖❀★✺✽❁◗✷✯✵✿❃✭✷❅❑❤❘❙❃€✳✶✫✣✼❅❘❤✬❡q✭❑❜✬❁✿✷❅✵✿✱✣❲❬✹ ❞✭✬ ✦✕✘✌ ✜❏✑✔✕ ➷✕✘✓ ✢✑ ✬ ⑥➉✵✿✱❏✳❚❲❬✵❻❑❺❲❙◆❺❑✣❀★✼➐◆✘✐✉❀★❦❏✼✩✳❚✬✢✹✿⑥❧❀✖◆➫❲❬❲❬❑✣❀★◆✘✵✿❀★✱✭✼➐❑❺✐✉❦✴◆ ✳✶✹✿✱✘❀❴❄➈◆❙■✴❑❤✳✶✵◗✼❅❘❜✱✣❑❤❀★❁✿✹◗✷❅✷✯✵◗⑦✔✱✣❀★❲❝✹❙✳€❲⑧❲❬✳❴❄➏❑✣◆✘✼❅❑✣❀★✺★✼✢✳✶▼✏✵◗❑❜❀❛❁❛✺❖❀❴✼❅✳❤✾✣✺◗✹✿✱ ✵◗❀★❁✿❑✶✹✍▼✻❦✘✵✿❄⑧✱✭❀ ✺✽❑❤✺✽❃✣✼✯✾✭✹◗✹✿✵✿✵✿❁✿❀✔✾✴❁✿✺❖✹✖✵✿t❻✷❅❃✣✳❚❘❫❃❏◆✳✚◆✘❏❀★❃✴❃✣◆✘✹◗✹❛✷✯✵✩✵◗❄❬✱✣▼✏❀❫✾✭❃❏❦❏✺❖❀✔✵✿✹✿✷❅✵ ❑❜❃⑧❏✵✚✵◗✱❏❑❚✳✶▼✻✵❻✵✿❁◗✱✣❀ ❀€❏❀✖◆✣✺✽✳❚✵✿✵❇✹❉✳❫✵◗✱✣✵◗❑❀ ✹✿✺❖■❏✼❅✾✣✳❚✹✿✵✿✵◗✷❳❀★✳✶❁✿✼✒✹❻◆✘❦❏✷❅✹✿✳❚✵◗✹✿❁✿❀✖✷❅◆➏❦✣✾✣❑❜✵◗❃✚✷❅❑❤✹✿❃€✵❖✳✶❑❚❃❏▼❩◆✣✵✿✳❚✱✣❁❇❀❙◆➏◆✭✹◗✵❇✳✶✳✶✵❇✵◗✳✈✷❅✹✿■❏✵✿✷❳❑❜✺❖✷❅✹❴❃➈t✘✵◗✵❇✹✖✳ ✬ ➈✷❅❃✣❘ ❢✩✵❉◗❃✣✳✶❑❤✼❅✹✿✷❅❑❬✹✿❀ ✼✯❉❀❴✳❤❑❤◆✘❁✒✹✍❑❜✾✣✵✿❑❫✵✿✼❅✷❅✳❬❀★❁◗➌❹✹✒✳❴✷❅❃➈❄❫✵◗❑❉❑✶▼❻✳❤✳✶✺★✺❖✾✣❑❜✵◗✾✣❑❤❃✘❲⑧✵❩✳❚✳✶✵✿❃✴✷❳✺★◆➏✳❚✼✯✵✿❅✱✘❄❙✾✣◆✘✹✒❀✔❄✘✵✿✷❅❀★❀★❁◗✼❳❲❙◆✘✷❅✷❅❃✣❃✣❘✍✷❅❃✣❁✿❘✚❑❜❦✣✵✿✱✭✾✣❀✚✹✿✵❻❃➈✺❖✾✭✼❅✾✣❲✚✹◗✵✿❦❏❀★❀★❁◗❁▲✷✯❃✭❑✶❘ ▼ ❲❙❀★✵◗✱✣❑✣◆✘✹✖✬✒❪❫❑✣◆✘❀✔✼❨✐✩❦❏✳❚✹✿❀✖◆❫✺❖✼❅✾✣✹◗✵✿❀★❁◗✷✯❃✭❘✚❲❙❀★✵◗✱✣❑✣◆✘✹✻✳✶❁◗❀❂✹◗✵✿✾❏◆❺✷✯❀❴◆❫✷❅❃⑧➁✘❀✖✺✽✵✿✷❅❑❤❃€✫✣✬❡✫✭✬ ✵✿✳✶❑➅■✭■✣✺✽➁✘✼❅✼❥✷❥❑❜✳❚✺✔❲❙✹✿✳✶✹◗✵✿✷❨❀❙✷❅▼✥❑❜❄➅✺❖❃✣✼❅✹❩✳➫✾✣✹◗❲❫❘❤✵✿❀★✷❅✳❴❣❤❁◗❄❛✷❅❀★❃✣❃ ✱✴❘ ✳❴✳✶❣❤✳❚✼❅❀❉❘❤✼❅❘❤❑❜✺❖❑❤❁✿✼❅❁◗✾✣✷❅✵✿✷❅✹✿✵✿✱✭✵◗✱✣❲❀★❲❬❁✿✷❅❃✣✹❂✳❚❘❙✹✚✷❅❃✘✺✽✾✣✵✿❁✿❃✣❀✔✷❅❘❤✵✿✷❳❵❜❀★❁❇❁◗✳❚✾✣✷❳✵✿❀★✳➏❀❫✼❅❄➅➌❻✵✿✱✭✱✣❦✴❀⑧✷❳❀★✺✿✼❅✱❫❑❤✷❳◆✘❃✭❁◗❀❴❘❤❀✖✳✶✷❅❵❜✹➏❃✣✾✣❘➫❑✶✷❅❁✿▼❂✵✿❀❉❑➫✹◗✵◗❀★✱✣❑❤❣❤❀✍❃✣❀✔❁❇✼❅✷✯❄➷✳✶❃✘✼✍✵◗❑❤❀★✺❖❃✭❘❤✼❅✾✣❁❖❀ ✳✶✹✿✵✿✵◗✺✽✷❅❀★✼✯❑❜✾✭❁✿❃⑧✷❅✹✿❃✣✵✿❀✔❑❚❘➫❁✿▼③✷❅❲❙❃✣✹◗❀★❘➅❀✔❣❤✵✿❀★✱✣❲❬❁❖❑✣✳✶❀★◆✘✼✢✵✿✹❴✱✭✺❖t✒✼❅❑❺✾✣✹✿◆ù✹✿❑➫✵◗✺★❀★✵✿✳✶❁✿✱✴✷❅✵◗❃✣✳✶❀★❘❬❘❤✵➏❑❜✵✿✷✯❁✿✵➏❀✖❄✘✺◗✬✷❅✱✣✹❛❃✣✣✹◗✷❳❑❤❵❜✾✭❲❬✾✣❁✿✵✿❀★❀★✱✭✹❴✵✿❀★✬ ✷❅❁✿❲❙❲❬❀✔❑❤✹❛❁✿❀❜◆✘t✒✷➐➍⑧✹✿❑❜✺❖❲❙✾✣✼❅❀✵ ✳✶✼❅❘❜❑❤❢✩❁✿❃ù✷❅✵◗✵✿✱✣✱✣❲❙❀✈✹✒▼✏➌❻❑❤✼❅✱✭✼❅❑✶✷❥✺◗➌❻✱❫✷❅❃✣✷❅❘❫❃✘✵✿✹✿❀★❀✖❘❜✺❖❁❇✵◗✳✶✷❅✵◗❑❤❀✍❃✣✹❴✵✿✱✣t❩❀✍➌✸✷❳❀❙◆✘❀✖❀✽✳❚④✭✹❻✳❚❲❙❑✶▼✒✷❅❃✣✹✿❀★❀✚❣❜❀★❀✖❁❇✳❜✳❚✺◗✼③✱➅✺❖❑✶✼❅✾✣▼✍✹◗✵✿✵✿✱✣❀★❁◗❀❫✷❅❃✣✳✶❘❙❦✴❑✶❲❬❣❤❀★❀ ✵✿✱✣❏❑✣❣❤◆✘❀❫✹❴✺❖✬ ✼❅✾✣✹✿✵◗❀★❁✿✷❅❃✣❘➷❲❬❀★✵✿✱✣❑✣◆✘✹➏✷❅❃➅◆✘❀★✵❖✳✶✷❅✼✩✬ ✰➷❀❫✳✶✼❅✹✿❑➫✷❅❃✘✵✿❁✿❑✣◆✘✾✴✺❖❀ é❻❪ê ✏ ❫❬ï③ø❺ð❺đ➣ð✣đ ✒ú▲đ✿ú ❝÷❷ð✣í ú ttt týỵỵ ỵỵ ttts t ✍✷❅❃❫✵✿❀★❁◗❲❙✹✸❑✶▼✒✵✿✱✣❀❉◆✣✳❚✵❇✳❚❦❏✳✶✹◗❀❼✳❚✵✿✵◗❁✿✷❅❦✣✾✣✵◗❀★✹✖✬ é❻❪ê ✏❻ê✿ë ❴ õ✿ï✢ó✘ó✘đ✿ơ❷ï✢õ ▲ï✢ø✘ð✣đ✩ð✣đ ✒ú▲đ✿ú ❝÷➎ð❺í ✻ó ❛❵ ❝÷✦ï✢ú✻ó➫ï✢ú ▲❵ ❝÷ ✒đ ▲ó ●❻❸ ✱✣➷❀➏✕ ❲❙❑❜✴✹✿✧ ✵✻✢➌✸✑ ❀★■✣✼❅❁✿✼➐✐❑❜✘■❏❃✣❑❜❑✶✹✿➌❻❀✖◆❬❃€❦✘✳❚❄ ❃❏◆ ✹✼❂✺✽✳❚❑❤✾✘❲❙▼✏❲❫❲❬✳✶❑❤❃❙❃✣✼❅✳✶❄➏❃✴✾✣◆⑧✹✿❀❴➀s◆➫❑❤✾✣■❏✹◗✳✶✹✿❁◗❀★✵✿❀✔✷❅✵✿✾➈✷❅➌❝❑❤❃✭✮❴✷✯❃✭①❤❘✚✫❜q ❲❙★t✘❀★✳✶✵◗✱✣❃✴❑✣◆❙◆✘✵◗✹❂✱✣✳❚❀★✷❅❁✿❁❻❀✚❣❤❸ ✳✶❁◗➷✷❳✳✶✕✘✵✿✷❅✜✣❑❜✛✒❃✣✑✹✖✬ ■✣❁✿❑❜■❏❑❜✹✿❀✖◆➫❦✘❄ ✉❪€✳❜✺★→▲✾✣❀★❀★❃↕✮✖①❜♠❤q ✔t❏✳❚❃❏◆ ☞✍✕➈✛❽✓✖✗ ✴✧ ✜❏✑★✕ ✓✖✕ ✢✛✢✧ ✴✎✢✍✕ ❜✜❝ ✢✕ ❸ ➷✕➈✜✭✛ ✑ ➷✕✘✓ ●❻❁✿❀✔✱✣✹✿✾✣❀❙✼❅✵✿❸❜✷❅✐✩❃✣❲❙❘❬❀❴✷❅✳✶❃➈❃✣✵◗❁❇✹✍✳ tt tt ỵ ❀✖✳✶❃ ❑❤❦❏❁➏✳❚✹✿✺❖❀✖❀★◆➫❃✘✵✿❑❜❀★❃ ❁❴✬ ✵◗✱✣✭❀ ❑❤❁✍◆❺✷✯❀✖✹◗✳❜✵❇✳❚✺✿✱ù❃❏✺❖❑✶❀✚▼❻❦✴✵✿❀★✱✣✵✩❀✚➌❩❁◗❀✔❀★❀★❲⑧❃➷✳❚✵✿✷❅✱✣❃✣❀✚✷❅❃✣❑❜❘❙❦❤⑨❖❑❜❀✖❦❤✺❖⑨❖✵❉❀✖✺❖✳❚✵◗❃❏✹✖◆€t❩✳❚✵◗❃✱✣❀❙❑❜✺❖❦❤✼❅⑨❖✾✣❀✖✹◗✺❖✵✿✵➏❀★❁❉✷❅✹❛❲❬✳✶❀✖✹◗✳✶✹✿✷❅❃❽❘❤✬✍❃✭❀✖❢✩◆➫✵❂✵◗✵✿✱✣❑€❀★❃➷✵◗✱✣✺❖❀❙❑❤✺❖❲❬✼❅✾✣■✣✹◗✾✣✵✿✵◗❀★❀★❁➏✹✍✵✿✵✿❑€✱✣❀➏➌❻✱✭❃✣✷❥❀★✺◗➌✡✱➷❲❙✷❅✵✍❀❴✷❅✳✶✹❉❃❬✵✿✱✣▼✏❑❤❀✚❁✍❲❬❀✖✳❜❑❤✺◗✹◗✱ ✵❂✹◗✺❖✷❅✼❅❲❙✾✣✹◗✷❅✵✿✼❳❀★✳✶❁❴❁✖✬ t ●❻✱✣✷❅✹❻■✣❁◗❑❺✺✽❀★✹✿✹✍✷❅✵✿❀★❁❖✳✶✵◗❀★✹✻✾✣❃✘✵◗✷✯✼✴✵✿✱✭❀❛✺❖❁✿✷❅✵◗❀★❁✿✷❅❑❤❃❬▼✏✾✭❃❏✺❖✵✿✷❅❑❜❃ ✺✽❑❤❃✘❣❤❀★❁◗❘❤❀★✹❴✬✒●✸❄✘■✣✷❳✺★✳✶✼❅✼❅❄➈t❚✵✿✱✣❀❉✹❖❵❜✾❏✳✶❁◗❀✖◆❜✐✩❀★❁✿❁◗❑❤❁❂✺✽❁✿✷❅✵✿❀★❁◗✷❅❑❤❃❫✷❅✹❻✾✣✹✿❀✖◆➎t❏◆✘❀ ✴❃✣❀✖◆€✳❚✹ ❞ ✉✫✣✬❡❋❜❋ ❄❆❢❋❣❬❅ ❂❡ ➌❻❲✚✱✣✾✣❀★✼❅✵✿❁◗✷❳❀ ◆✘✷❅❲✚✷❅❀★✹❂❃✭✵◗✹✿✱✣✷❅❑❤❀✚❃❏■✴✳❚✼❑❤★✷❅✬✴❃✘●❻✵✻✱✣✷❅❃ ✷❅✹❹✹◗✺✽■❏❁✿✳❤✷❅✵✿✺✽❀★❀✚❁◗✷❅❁✿❑❤❀★❃❫■✣❁◗✵✿❀★❁◗✹✿✷✯❀✔❀✔❃➈✹❻✵◗✵✿✷❅❑➏❃✣❘ ❲⑧✵◗✳ ✱✣❜❀➏❀❻❘❤✵✿✱✣✷❅❣❤❀✍❀★❃➫❁◗❀★✹✿❑❤✾✣❦❤✼❅⑨✽✵◗❀✖✷✯❃✭✺❖✵✖❘❙t✢❸❙✳✶❃✴✺❖◆✼❅✾✣✹◗✵✿❀★❁◗✷✯✹❂✹✍✳✶✵◗✹✻✱✣✺✽❀✚❑❤❲❙❲❙❀✖■✴✳❚✳❤❃❫✺❖✵❻❑✶✳✶▼✻❃❏✺❖◆❬✼❅✾✣✳✶✹✿✵◗✹✸❀★✹✿✘❁ ❀★■✴❤ ✳✶❁❇✳❚✏❦✴✵✿❀❛❑❤✵◗✳❚✱ ✹❻■❏❑❜✳❚✹✿❃❏✹◗✷✯◆ ❦✭✼✯❀❜✬✢●❻✳✶✱✣❁◗❀❀ ●❻❸❜✺❖✼❅✐✩✱✣✾✣❲❙❀❉✹◗✵✿❀✖❀★✳✶✳❚❁◗✼❅❃✣❘❜✹❼✹✸❑❤✳❚❁✿■✣❁✿✷❅❁✿✵◗❀❛❑✣✱✣✺✽✺❖❲❝❑❤❀✖❲❙◆❺✳✶✾✣✵✿■✴❁✿✵◗✳❤❀➏❀★✺❖❲❙✷❅✵❻✹❻■✭✺❖✹✿✵✿✼❅✾✣❑❤✹✸✾❏❲❬✵✿◆❺❑✚❲⑧✹✻◆✘✳✶✵✿❀★✱✴❁◗✵✿✷❅✳✶❀✔⑦★❁✿✵✻❀✖❲❙◆➏✳✶❁◗✷❅✷❅❃✣❃❀❉❀❉❁❇❽✳❚❸✈✷❅✵✿❘❤✱✣■❏✾✣❀✔✳✶❁◗❁✻❁◗❀❉✵✿➌✸✷❅✫✣✵✿❀★✬❅✷❅✮❤❑❤✼❅✼✦✬❃✭✹✿✹❩❀✔✵◗■❏✱❏✳✶✳✶❁❖✵✸✳✶✵✿❲❙❀❴◆❬✷❅❃✣▼✏✷❅❁✿❲❙❑❜❲➉✷➐⑦★❀✸❑❜✵✿❃✣✱✣❀❉❀✍✳✶✹❇❃✣❵❜❑❜✾❏✵✿✳❚✱✣❁✿❀✔❀✖❁✖◆➈✬✸✐✉❀★●❻❁◗❁✿✱✣❑❜❀❉❁❻❲❬▼✏✾✣❀★❃✴✵✿✺❖✱✣✵✿❑✣✷❅❑❤◆✈❃❽✷✯✬✢✹▲❢✩❁✿✵❻❀★✼❳➌❩✳❚❑❜✵✿✷❅❁ ❣❤✘❀★✹❩✼❅❄✚➌✸✹❖❀★✺★✼❅✼❷✳✶✼❳➌❻✳✶✱✣❦✭❀★✼✯❀❉❃❫✳❚✵◗❃❏✱✣◆ ❀ ❆❅❈❇❊❉ ➜✘♦② ✢ ✙✘➃♠ ❆❋❍●✸■ ❆❏❈❑ ❆❋✤❇ ✺❇▲❏◆▼ ✫❖ ❄❞✖✣◆✘ ➡✌ ✞✹ ❈❧ ✣◆✘ ✥② ✢ ✙✘✾♠ ❄✻ ❄❞✖✣◆✘ ➃✌ ➡✌ ✚④ ✆✎ ✞❒ ỗ ✶❁✿✮❯❱✩❩✫★✵€➛❁ ❬◗☛★ ❒ ✏❮ ✍✔ ❝⑦ ✏⑧ ❪❒ ✴❶×➨ ✴⑧❈⑩ ❭➩ ✏❮ ❣Ð☛➨ ❯⑩ ❣Ð☛➨ ➜✎ ②✓♠ ✝ ❞ ✙✘ ✏⑩ ➃✹ ②✏♠ ✰✹ ❚✘♦✣ ➜✘ ☛✣ ✿✘◆② ✢ ◆⑩✴⑧ ✲✻ ✲✻ ➜♥ ❊❞ ②✓♠ ➾♠ ❄❞✖✣◆✘ ☛✎ ➦❷ ➸✧✚✂✆★ ✼③ ✜❒❂€✚✧✯★✫❁✏✧✩☎❀◗✿❱➙✪❂☎✚✂☛➀ ✶❁➜✮✚❮ Ü✛ s✛ ✚✌ ➢ ➇ ➪ ➑✁➶♦➈ ➪ ✃➇ ➹ ➺ ➺➯➑ ✁✻ ➑❄✃ ➴ ➞ ➑ ✹ ✹ ➇ ☛✎ ❪✛ ✏✎ ➺❨➑ ✲✻ ... phone sec 818 K 894K 940K 978K 746K 769K 795K 864K 43K 52K 58K 59K 591K 682K 728K 784K location = New York" item home ent comp phone sec 10 87K 11 30K 10 34K 11 42K 968K 10 24K 10 48K 10 91K 38K 41K 45K... York 968 10 87 38 Montreal 818 746 43 Vancouver Q1 605K Q2 680 825K 14 K 952 31 89 623 872 5 91 698 925 400K 682 time (quarters) Q3 812 10 23 512 30 789 10 02 870 728 984 5 01 784 Q4 927 10 38 38 580... 3 11 12 13 13 13 14 15 16 16 17 18 19 21 CONTENTS c J Han and M Kamber, 19 98, DRAFT!! DO NOT COPY!! DO NOT DISTRIBUTE!! September 7, 19 99 Chapter Introduction This