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Properties of QCD Matter at High Baryon Density
by Xiaofeng Luo Qun Wang Nu Xu Pengfei ZhuangThis book highlights the discussions by renown researchers on questions emerged during transition from the relativistic heavy-ion collider (RHIC) to the future electron ion collider (EIC). Over the past two decades, the RHIC has provided a vast amount of data over a wide range of the center of mass energies. What are the scientific priorities, after RHIC is shut down and turned to the future EIC? What should be the future focuses of the high-energy nuclear collisions? What are thermodynamic properties of quantum chromodynamics (QCD) at large baryon density? Where is the phase boundary between quark-gluon-plasma and hadronic matter at high baryon density? How does one make connections from thermodynamics learned in high-energy nuclear collisions to astrophysical topics, to name few, the inner structure of compact stars, and perhaps more interestingly, the dynamical processes of the merging of neutron stars? While most particle physicists are interested in Dark Matter, we should focus on the issues of Visible Matter! Multiple heavy-ion accelerator complexes are under construction: NICA at JINR (4 ~ 11 GeV), FAIR at GSI (2 ~ 4.9 GeV SIS100), HIAF at IMP (2 ~ 4 GeV). In addition, the heavy-ion collision has been actively discussed at the J-PARC. The book is a collective work of top researchers from the field where some of the above-mentioned basic questions will be addressed. We believe that answering those questions will certainly advance our understanding of the phase transition in early universe as well as its evolution that leads to today's world of nature.
Responsible Data Science: Select Proceedings of ICDSE 2021 (Lecture Notes in Electrical Engineering #940)
by Jimson Mathew G. Santhosh Kumar Deepak P. Joemon M. JoseThis book comprises select proceedings of the 7th International Conference on Data Science and Engineering (ICDSE 2021). The contents of this book focus on responsible data science. This book tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy. The chapters in this book represent research from different perspectives that offer novel theoretical implications that span multiple disciplines. The book will serve as a reference resource for researchers and practitioners in academia and industry.
Embracing Machines and Humanity Through Cognitive Computing and IoT (Advanced Technologies and Societal Change)
by Mohammed Usman Xiao-Zhi GaoThis book sheds light on systems that learn extensively, with purpose and naturally interact with humans. Improving operations and increasing competitive differentiation among manufacturing organizations by harnessing the power of cognitive abilities, IoT can help build and influence the flow of information—making the shop floor more cognitive through effective processing, analysis, and operational optimization. Now we are seeing the first-hand potential of cognitive computing—its ability to transform businesses, governments, and society. The real potential of the cognitive age can be realized by combining data analysis and statistical reasoning of machines with uniquely human qualities, such as self-directed goals, common sense, and moral values, improving operations and increasing competitive differentiation among manufacturing organizations. By harnessing the power of cognitive abilities, IoT can help build and influence the flow of information—making the shop floor more cognitive through effective processing, analysis, and operational optimization. Cognitive initiatives come in all shapes and sizes, from change to strategy and everything in between. What most successful projects have in common, no matter how ambitious, is they start with a clear view of what technology can do. Therefore, the first job of a cognitive scientists is to gain a firm understanding of cognitive abilities, as presented in this book.
Performance Optimization of Fault Diagnosis Methods for Power Systems (Engineering Applications of Computational Methods #9)
by Dinghui Wu Juan Zhang Junyan Fan Dandan TangThis book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.
Data Analytics Applications in Emerging Markets
by Jose Antonio Nuñez Mora M. Beatriz Mota AragonThis book analyzes the impact of technology in emerging markets by considering conditions and the history of how it has changed the way of working and market development in such contexts. The book delves into key areas such as fintech enterprises, artificial intelligence, pension funds, stock markets, and energy markets though applied studies and research. This book is a useful read for practitioners and scholars interested in how technology has and continues to change the way in which development is defined and achieved, particularly in emerging markets.
Proceedings of the 9th Conference on Sound and Music Technology: Revised Selected Papers from CMST (Lecture Notes in Electrical Engineering #923)
by Xi Shao Kun Qian Xin Wang Kejun ZhangThe book presents selected papers at the 9th Conference on Sound and Music Technology (CSMT) held virtually in June 2022, organized by Zhejiang University, China. CSMT is a multidisciplinary conference focusing on audio processing and understanding with bias on music and acoustic signals. The primary aim of the conference is to promote the collaboration between art society and technical society in China. In this book, the paper included covers a wide range topic from speech, signal processing, music understanding, machine learning, and signal processing for advanced medical diagnosis and treatment applications, which demonstrates the target of CSMT merging arts and science research together. Its content caters to scholars, researchers, engineers, artists, and education practitioners not only from academia but also industry, who are interested in audio/acoustics analysis signal processing, music, sound, and artificial intelligence (AI).
Bayesian Statistical Modeling with Stan, R, and Python
by Kentaro MatsuuraBayesian Statistical Modeling with Stan, R, and Python
Traditional Chinese Medicine and Diseases: An Omics Big-data Mining Perspective (Translational Bioinformatics #18)
by Kang NingThis book focuses on the multi-omics big-data integration, the data-mining techniques and the cutting-edge omics researches in principles and applications for a deep understanding of Traditional Chinese Medicine (TCM) and diseases from the following aspects: (1) Basics about multi-omics data and analytical methods for TCM and diseases. (2) The needs of omics studies in TCM researches, and the basic background of omics research in TCM and disease. (3) Better understanding of the multi-omics big-data integration techniques. (4) Better understanding of the multi-omics big-data mining techniques, as well as with different applications, for most insights from these omics data for TCM and disease researches. (5) TCM preparation quality control for checking both prescribed and unexpected ingredients including biological and chemical ingredients. (6) TCM preparation source tracking. (7) TCM preparation network pharmacology analysis. (8) TCM analysis data resources, web services, and visualizations. (9) TCM geoherbalism examination and authentic TCM identification. Traditional Chinese Medicine has been in existence for several thousands of years, and only in recent tens of years have we realized that the researches on TCM could be profoundly boosted by the omics technologies. Devised as a book on TCM and disease researches in the omics age, this book has put the focus on data integration and data mining methods for multi-omics researches, which will be explained in detail and with supportive examples the “What”, “Why” and “How” of omics on TCM related researches. It is an attempt to bridge the gap between TCM related multi-omics big data, and the data-mining techniques, for best practice of contemporary bioinformatics and in-depth insights on the TCM related questions.
Resource Allocation in Network Function Virtualization: Problems, Models and Algorithms
by Song Yang Nan He Fan Li Xiaoming FuNetwork Function Virtualization (NFV) has recently attracted considerable attention from both research and industrial communities. Numerous papers have been published regarding solving the resource- allocation problems in NFV, from various perspectives, considering different constraints, and adopting a range of techniques. However, it is difficult to get a clear impression of how to understand and classify different kinds of resource allocation problems in NFV and how to design solutions to solve these problems efficiently.This book addresses these concerns by offering a comprehensive overview and explanation of different resource allocation problems in NFV and presenting efficient solutions to solve them. It covers resource allocation problems in NFV, including an introduction to NFV and QoS parameters modelling as well as related problem definition, formulation and the respective state-of-the-art algorithms.This book allows readers to gain a comprehensive understanding of and deep insights into the resource allocation problems in NFV. It does so by exploring (1) the working principle and architecture of NFV, (2) how to model the Quality of Service (QoS) parameters in NFV services, (3) definition, formulation and analysis of different kinds of resource allocation problems in various NFV scenarios, (4) solutions for solving the resource allocation problem in NFV, and (5) possible future work in the respective area.
Algorithms for Satellite Orbital Dynamics (Springer Series in Astrophysics and Cosmology)
by Lin LiuThis book highlights the fundamental physics of orbit theory, dynamical models, methods of orbit determination, design, measurement, adjustment, and complete calculations for the position, tracking, and prediction of satellites and deep spacecraft. It emphasizes specific methods, related mathematical calculations, and worked examples and exercises. Therefore, technicians and engineers in the aerospace industry can directly apply them to their practical work. Dedicated to undergraduate students and graduate students, researchers, and professionals in astronomy, physics, space science, and related aerospace industries, the book is an integrated work based on the accumulated knowledge in satellite orbit dynamics and the author’s more than five decades of personal research and teaching experience in astronomy and aerospace dynamics.
Fundamental and Applied Sciences in Asia: International Conference on Science Technology and Social Sciences (ICSTSS 2018)
by Nor Azizah Yacob Duratul Ain Tholibon Nor Yuziah Mohd Yunus Zadariana Jamil Syuhada Mohd TahirThis book gathers selected science and technology papers presented at the 2018 International Conference on Science Technology and Social Sciences (ICSTSS 2018), organised bi-annually by Universiti Teknologi MARA Pahang, Malaysia. Based on the theme “Redesigning Education for Industrial Revolution”, the papers in this book address a broad range of topics in the fundamental and applied sciences, including computer science, engineering, environmental and management, furniture, forestry, health and medicine, material science, mathematics, plantation and agrotechnology, sport science and statistics, covering theoretical, numerical and experimental studies. The book serves as a platform for disseminating research findings by academicians of local, regional and global prominence, as a catalyst to inspire positive innovations in the development of the region. It provides a significant point of reference for academicians and students: for academicians, it is a good source of information to conduct further research; for students, it is the latest point of reference on research conducted in their fields of study. The carefully reviewed papers intend to facilitate the creation of new knowledge through the exchange of ideas, strategies and innovations in various science and technology disciplines, and to contribute towards enhancing the learning environment.
Trust and Credit in Organizations and Institutions: As Viewed from the Evolution of Cooperation (Theoretical Biology)
by Mayuko NakamaruThis book shows that evolutionary game theory can unravel how mutual cooperation, trust, and credit in a group emerge in organizations and institutions. Some organizations and institutions, such as insurance unions, credit unions, and banks, originated from very simple mutual-aid groups. Members in these early-stage mutual-aid groups help each other, making rules to promote cooperation, and suppressing free riders. Then, they come to “trust” not only each other but also the group they belong to, itself. The division of labor occurs when the society comes to have diversity and complexity in a larger group, and the division of labor also requires mutual cooperation and trust among different social roles. In a larger group, people cannot directly interact with each other, and the reputation of unknown people helps other decide who is a trustworthy person. However, if gossip spreads untruths about a reputation, trust and cooperation are destroyed. Therefore, how to suppress untrue gossip is also important for trust and cooperation in a larger group. If trustworthiness and credibility can be established, these groups are successfully sustainable. Some develop and evolve and then mature into larger organizations and institutions. Finally, these organizations and institutions become what they are now. Therefore, not only cooperation but also trust and credit are keys to understanding these organizations and institutions.The evolution of cooperation, a topic of research in evolutionary ecology and evolutionary game theory, can be applied to understanding how to make institutions and organizations sustainable, trustworthy, and credible. It provides us with the idea that evolutionary game theory is a good mathematical tool to analyze trust and credit. This kind of research can be applied to current hot topics such as microfinance and the sustainable use of ecosystems.
Data Science in Societal Applications: Concepts and Implications (Studies in Big Data #114)
by Siddharth Swarup Rautaray Manjusha Pandey Nhu Gia NguyenThe book provides an insight into the practical applications and theoretical foundation of data science. The book discusses new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The book includes contributions from academia and industry experts detailing the shortfalls of current tools and techniques used and generating the blueprint of the new technologies. The topics covered in the book range from theoretical and foundational research, platforms, methods, applications, and tools in data science. The chapters in the book add a social, geographical, and temporal dimension to data science research. The papers included are application-oriented that prepare and use data in discovery research. This book will provide researchers and practitioners with a detailed snapshot of current progress in data science. Moreover, it will stimulate new study, research, and the development of new applications.
Music, Mathematics and Language: The New Horizon of Computational Musicology Opened by Information Science
by Keiji Hirata Satoshi Tojo Masatoshi HamanakaThis book presents a new approach to computational musicology in which music becomes a computational entity based on human cognition, allowing us to calculate music like numbers. Does music have semantics? Can the meaning of music be revealed using symbols and described using language? The authors seek to answer these questions in order to reveal the essence of music. Chapter 1 addresses a very fundamental point, the meaning of music, while referring to semiotics, gestalt, Schenkerian analysis and cognitive reality. Chapter 2 considers why the 12-tone equal temperament came to be prevalent. This chapter serves as an introduction to the mathematical definition of harmony, which concerns the ratios of frequency in tonic waves. Chapter 3, “Music and Language,” explains the fundamentals of grammar theory and the compositionality principle, which states that the semantics of a sentence can be composed in parallel to its syntactic structure. In turn, Chapter 4 explains the most prevalent score notation – the Berklee method, which originated at the Berklee School of Music in Boston – from a different point of view, namely, symbolic computation based on music theory. Chapters 5 and 6 introduce readers to two important theories, the implication-realization model and generative theory of tonal music (GTTM), and explain the essence of these theories, also from a computational standpoint. The authors seek to reinterpret these theories, aiming at their formalization and implementation on a computer. Chapter 7 presents the outcomes of this attempt, describing the framework that the authors have developed, in which music is formalized and becomes computable. Chapters 8 and 9 are devoted to GTTM analyzers and the applications of GTTM. Lastly, Chapter 10 discusses the future of music in connection with computation and artificial intelligence.This book is intended both for general readers who are interested in music, and scientists whose research focuses on music information processing. In order to make the content as accessible as possible, each chapter is self-contained.
Hyperparameter Tuning for Machine and Deep Learning with R: A Practical Guide
by Eva Bartz Thomas Bartz-Beielstein Martin Zaefferer Olaf MersmannThis open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II). Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike.
Data-Driven Approach for Bio-medical and Healthcare (Data-Intensive Research)
by Nilanjan DeyThe book presents current research advances, both academic and industrial, in machine learning, artificial intelligence, and data analytics for biomedical and healthcare applications. The book deals with key challenges associated with biomedical data analysis including higher dimensions, class imbalances, smaller database sizes, etc. It also highlights development of novel pattern recognition and machine learning methods specific to medical and genomic data, which is extremely necessary but highly challenging. The book will be useful for healthcare professionals who have access to interesting data sources but lack the expertise to use data mining effectively.
ICT Analysis and Applications: Proceedings of ICT4SD 2022 (Lecture Notes in Networks and Systems #517)
by Simon Fong Nilanjan Dey Amit JoshiThis book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 7th International Conference on ICT for Sustainable Development (ICT4SD 2022), held in Goa, India, on July 29–30, 2022. The book covers the topics such as big data and data mining, data fusion, IoT programming toolkits and frameworks, green communication systems and network, use of ICT in smart cities, sensor networks and embedded system, network and information security, wireless and optical networks, security, trust, and privacy, routing and control protocols, cognitive radio and networks, and natural language processing. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.
Reconstruction of Macroeconomics: Methods Of Statistical Physics, And Keynes Principle Of Effective Demand (Advances in Japanese Business and Economics #3)
by Hiroshi YoshikawaThis book explains how standard micro-founded macroeconomics is misguided and proposes an alternative method based on statistical physics. The Great Recession following the bankruptcy of Lehman Brothers in September 2015 amply demonstrated that mainstream micro-founded macroeconomics was in trouble. The new approach advanced in this book reasonably explains important macro-problems such as employment, business cycles, growth, and inflation/deflation. The key concept is demand failures, which modern micro-founded macroeconomics has ignored. “It (Chapter 3) captures analytically a good part of the intuition that underlies the Keynesian economics of people like Tobin and me.” Robert Solow, Emeritus Institute Professor of Economics, Massachusetts Institute of Technology, Nobel Laureate in Economics, 1987“Professor Hiroshi Yoshikawa provides a unique synthesis of statistical physics and macro-economic theory in order to confront the dismal failure in economics and in finance to understand how an economy or a financial market works, given the heterogeneous decision making of many different individual interacting actors. Economics has failed in this regard with the naive and often misleading concept of “representative agents.” The author presents many insights on the historical development, concepts, and errors made by the most illustrious economists in the past. This book should be essential readings for any economics students as well as academic researchers and policy makers, who should learn to bring back good-sense thinking in their impactful decisions.”Didier Sornette, Professor on the Chair of Entrepreneurial Risks at the Swiss Federal Institute of Technology Zurich (ETH Zurich)
Handbook of Biometric Anti-Spoofing: Presentation Attack Detection and Vulnerability Assessment (Advances in Computer Vision and Pattern Recognition)
by Sébastien Marcel Julian Fierrez Nicholas EvansThe third edition of this authoritative and comprehensive handbook is the definitive work on the current state of the art of Biometric Presentation Attack Detection (PAD) – also known as Biometric Anti-Spoofing. Building on the success of the previous editions, this thoroughly updated third edition has been considerably revised to provide even greater coverage of PAD methods, spanning biometrics systems based on face, fingerprint, iris, voice, vein, and signature recognition. New material is also included on major PAD competitions, important databases for research, and on the impact of recent international legislation. Valuable insights are supplied by a selection of leading experts in the field, complete with results from reproducible research, supported by source code and further information available at an associated website.Topics and features: reviews the latest developments in PAD for fingerprint biometrics, covering recent technologies like Vision Transformers, and review of competition series; examines methods for PAD in iris recognition systems, the use of pupil size measurement or multiple spectra for this purpose; discusses advancements in PAD methods for face recognition-based biometrics, such as recent progress on detection of 3D facial masks and the use of multiple spectra with Deep Neural Networks; presents an analysis of PAD for automatic speaker recognition (ASV), including a study of the generalization to unseen attacks; describes the results yielded by key competitions on fingerprint liveness detection, iris liveness detection, and face anti-spoofing; provides analyses of PAD in finger-vein recognition, in signature biometrics, and in mobile biometrics; includes coverage of international standards in PAD and legal aspects of image manipulations like morphing.This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics.This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics.
Sentiment Analysis and Deep Learning: Proceedings of ICSADL 2022 (Advances in Intelligent Systems and Computing #1432)
by Subarna Shakya Ke-Lin Du Klimis NtalianisThis book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 – 17 June, 2022. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes.
Complex-Valued Neural Networks Systems with Time Delay: Stability Analysis and (Anti-)Synchronization Control (Intelligent Control and Learning Systems #4)
by Ziye Zhang Zhen Wang Jian Chen Chong LinThis book provides up-to-date developments in the stability analysis and (anti-)synchronization control area for complex-valued neural networks systems with time delay. It brings out the characteristic systematism in them and points out further insight to solve relevant problems. It presents a comprehensive, up-to-date, and detailed treatment of dynamical behaviors including stability analysis and (anti-)synchronization control. The materials included in the book are mainly based on the recent research work carried on by the authors in this domain.The book is a useful reference for all those from senior undergraduates, graduate students, to senior researchers interested in or working with control theory, applied mathematics, system analysis and integration, automation, nonlinear science, computer and other related fields, especially those relevant scientific and technical workers in the research of complex-valued neural network systems, dynamic systems, and intelligent control theory.
Power-Based Study of Boundary Layer Ingestion for Aircraft Application (SpringerBriefs in Applied Sciences and Technology)
by Peijian LvThis book presents research on Boundary Layer Ingestion (BLI). BLI is an aircraft-engine integration technique that aims at integrating the aircraft and the propulsion system such that the overall aircraft fuel consumption can be reduced. In this research, theoretical analysis suggests that the minimization of total power consumption should be used as a design criterion for aircraft utilizing BLI rather than focusing on the minimization of drag. Numerical simulations are performed, and the simulation results are processed using the PBM to support the theoretical analysis. Furthermore, an experimental study is carried out with a focus on the power conversion processes involved for a propulsor operating in the wake. Stereoscopic PIV is employed in order to visualize the flow and understand the physics. The so-called Power-based Method is used to quantify the power conversion mechanisms. The results prove that the dominant mechanism responsible for the efficiency enhancement is due to the utilization of body wake energy by the wake ingesting propeller. In short, the importance of wake energy flow rate in understanding the BLI phenomenon is highlighted. This book will be useful for researchers in the field of aircraft propulsion, aircraft aerodynamics, and airframe propulsion integration.
Social and Economic Stimulating Development Strategies for China’s Ethnic Minority Areas
by Yanzhong Wang Sai DingThis book gathers the outcomes of various, extensive research efforts on building a moderately prosperous society in minority areas, which would allow China’s poor and poverty-stricken areas to comprehensively join the rest of society. Offering an essential reference guide, the book will help readers understand the process, achievements, problems, and future development with regard to building a moderately prosperous society in the new era.
Annual Report on the Big Data of New Energy Vehicle in China (2021)
by Zhenpo WangThis open access book, based on static indicators and dynamic big data from local electric vehicles, is the first New-Energy Vehicles (NEVs) research report on the Big Data in China.Using the real-time big data collected by China's National Monitoring and Management Platform for NEVs, this book delves into the main annual technological progress of NEVs, the vehicle operating characteristics, it also anticipates the trend of NEVs industry.Various graphs&charts, detailed data this book offers will familiarize readers with the operation characteristics and practical application of China's NEVs industry and popularize the concept of automobile electrification. Besides, this book also makes an objective evaluation of the current situation and technological improvement of China's NEVs industry, presenting sensible suggestions for the development of the industry.This book is written for government staff, researchers, college staff, and technical staff of automobile and spare parts enterprises, which serves as an important reference for the decision-making of government departments and strategic decisions of automotive companies.
Mathematical Theory of Uniformity and its Applications in Ecology and Chaos (SpringerBriefs in Applied Sciences and Technology)
by Chuanwen Luo Chuncheng WangThis book puts forward a new mathematical theory to study chaotic phenomenon. The uniform theory is established on the basis of two elementary concept of circle and externally tangent square in mathematics. The author studies the uniformity of a finite set of points distributed in space by uniform theory. This book also illustrates that uniform theory performs better than other indices such as entropy and Lyapunov exponent in chaos measurement by numerous examples. This book develops a new mathematical tool for studying chaos so it will be appealing to students and researchers interested in theory of chaos. It also has potential applications in various fields such as Engineering, Forestry and Ecology.