Longitudinal data consists of a series of repeated observations of the same subjects over an extended time frame, and is thus useful for measuring change. Such studies arise in a variety of fields, such as health sciences, genomic studies, experimental physics, sociology, sports and student enrollment in universities. Many challenges can arise in longitudinal studies. For example, in health studies, intra-subject correlation of responses must be accounted for, covariates can vary with time, and bias can arise due to patients dropping out of the study. This volume under development brings recent and classical works in the modeling and analysis of longitudinal data and their utility for improving society.

Integrated Population Biology and Modeling: Part A offers very complex and precise realities of quantifying modern and traditional methods of understanding populations and population dynamics. Chapters cover emerging topics of note, including Longevity dynamics, Modeling human-environment interactions, Survival Probabilities from 5-Year Cumulative Life Table Survival Ratios (Tx+5/Tx): Some Innovative Methodological Investigations, Cell migration Models, Evolutionary Dynamics of Cancer Cells, an Integrated approach for modeling of coastal lagoons: A case for Chilka Lake, India, Population and metapopulation dynamics, Mortality analysis: measures and models, Stationary Population Models, Are there biological and social limits to human longevity?, Probability models in biology, Stochastic Models in Population Biology, and more.

Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern Recognition, Facial Data Analysis, Deep Learning in Electronics, Pattern Recognition, Computer Vision and Image Processing, Mechanical Systems, Crop Technology and Weather, Manipulating Faces for Identity Theft via Morphing and Deepfake, Biomedical Engineering, and more.

Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information, Cramer-Rao and Bayesian Paradigm, Compound beta binomial distribution functions, MCMC for GLMMS, Signal Processing and Bayesian, Mathematical theory of Bayesian statistics where all models are wrong, Machine Learning and Bayesian, Non-parametric Bayes, Bayesian testing, and Data Analysis with humans, Variational inference or Functional horseshoe, Generalized Bayes.

Geometry and Statistics, Volume 46 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors.

Artificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics. Chapters in this new release include AI Teacher-Student based Adaptive Structural Deep Learning Model and Its Estimating Uncertainty of Image Data, Machine-derived Intelligence: Computations Beyond the Null Hypothesis, Object oriented basis of artificial intelligence methodologies I in Judicial Systems in India, Artificial Intelligence in Systems Biology, Machine-Learning in Geometry and Physics, Innovation and Machine Learning: Crowdsourcing Open-Source Natural Language Processing (NLP) Algorithms to Advance Public Health Surveillance, and more. Other chapters cover Learning and identity testing of Markov chains, Data privacy for machine learning and statistics, and The interface between AI and Mathematics.

Data Science: Theory and Applications, Volume 44 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of interesting topics, including Modeling extreme climatic events using the generalized extreme value distribution, Bayesian Methods in Data Science, Mathematical Modeling in Health Economic Evaluations, Data Science in Cancer Genomics, Blockchain Technology: Theory and Practice, Statistical outline of animal home ranges, an application of set estimation, Application of Data Handling Techniques to Predict Pavement Performance, Analysis of individual treatment effects for enhanced inferences in medicine, and more. Additional sections cover Nonparametric Data Science: Testing Hypotheses in Large Complex Data, From Urban Mobility Problems to Data Science Solutions, and Data Structures and Artificial Intelligence Methods.

Integrated Population Biology and Modeling: Part B, Volume 40, offers very delicately complex and precise realities of quantifying modern and traditional methods of understanding populations and population dynamics, with this updated release focusing on Prey-predator animal models, Back projections, Evolutionary Biology computations, Population biology of collective behavior and bio patchiness, Collective behavior, Population biology through data science, Mathematical modeling of multi-species mutualism: new insights, remaining challenges and applications to ecology, Population Dynamics of Manipur, Stochastic Processes and Population Dynamics Models: The Mechanisms for Extinction, Persistence and Resonance, Theories of Stationary Populations and association with life lived and life left, and more.

Handbook of Statistics: Disease Modelling and Public Health, Part B, Volume 37 addresses new challenges in existing and emerging diseases. As a two part volume, this title covers an extensive range of techniques in the field, with this book including chapters on Reaction diffusion equations and their application on bacterial communication, Spike and slab methods in disease modeling, Mathematical modeling of mass screening and parameter estimation, Individual-based and agent-based models for infectious disease transmission and evolution: an overview, and a section on Visual Clustering of Static and Dynamic High Dimensional Data. This volume covers the lack of availability of complete data relating to disease symptoms and disease epidemiology, one of the biggest challenges facing vaccine developers, public health planners, epidemiologists and health sector researchers.

This book offers a unique account on the life and works of Srinivasa Ramanujan-often hailed as the greatest "natural" mathematical genius. Sharing valuable insights into the many stages of Ramanujan's life, this book provides glimpses into his prolific research on highly composite numbers, partitions, continued fractions, mock theta functions, arithmetic, and hypergeometric functions which led the author to discover a new summation theorem. It also includes the list of Ramanujan's collected papers, letters and other material present at the Wren Library, Trinity College in Cambridge, UK. This book is a valuable resource for all readers interested in Ramanujan's life, work and indelible contributions to mathematics.

This book presents select proceedings of the International Conference on Future Learning Aspects of Mechanical Engineering (FLAME 2020). This book, in particular, focuses on characterizing materials using novel techniques. It covers a variety of advanced materials, viz. composites, coatings, nanomaterials, materials for fuel cells, biomaterials among others. The book also discusses advanced characterization techniques like X-ray photoelectron, UV spectroscopy, scanning electron, atomic power, transmission electron and laser confocal scanning fluorescence microscopy, and gel electrophoresis chromatography. This book gives the readers an insight into advanced material processes and characterizations with special emphasis on nanotechnology.

Agricultural Soil Sustainability and Carbon Management presents long-term research in the field of sustainable soil use and management to guide in the prioritizing the multifunctional value of soil health and addressing interdisciplinary links between major issues such as biodiversity and climate change. As soil is the largest terrestrial carbon pool, as well as a significant contributor of greenhouse gases, much progress can be made toward curtailing the climate crisis by sustainable soil management practices.The book provides valuable insight into the soil and carbon management, the research gaps and the methodological challenges for research into soil carbon management will be include over the decades.

This edited book discusses how effective soil carbon management plans and policies will ultimately make agriculture more secure against climate change and soil degradation. It is focused on initiatives to enhance soil organic carbon (SOC) and sequestration by launching different schemes and programs. An approach based on practical aspects of managing SOC in agriculture is provided with clear and concise descriptions. It has more attention to successfully implement plans and policies to meet the required level of SOC restoration. The book is covering the urgent needs of plans and policies for soil management and C restoration in agricultural ecosystems which can be beneficial to food, nutrition, environment, and economy security. There is also providing a roadmap on SOC policies to encourage the use of best management practices (BMPs) for soil health and C stock restoration, and achieve the Sustainable Development Goals of the United Nations. The book is suitable for teachers, researchers, government planners and policymakers, undergraduate and graduate students of soil science, soil microbiology, agronomy, ecology, and environmental sciences.

The subject of information geometry blends several areas of statistics, computer science, physics, and mathematics. The subject evolved from the groundbreaking article published by legendary statistician C.R. Rao in 1945. His works led to the creation of Cramer-Rao bounds, Rao distance, and Rao-Blackawellization. Fisher-Rao metrics and Rao distances play a very important role in geodesics, econometric analysis to modern-day business analytics. The chapters of the book are written by experts in the field who have been promoting the field of information geometry and its applications.

Advances in Organic Farming: Agronomic Soil Management Practices focuses on the integrated interactions between soil-plant-microbe-environment elements in a functioning ecosystem. It explains sustainable nutrient management under organic farming and agriculture, with chapters focusing on the role of nutrient management in sustaining global ecosystems, the remediation of polluted soils, conservation practices, degradation of pollutants, biofertilizers and biopesticides, critical biogeochemical cycles, potential responses for current and impending environmental change, and other critical factors. Organic farming is both challenging and exciting, as its practice of "feeding the soil, not the plant" provides opportunity to better understand why some growing methods are preferred over others. In the simplest terms, organic growing is based on maintaining a living soil with a diverse population of micro and macro soil organisms. Organic matter (OM) is maintained in the soil through the addition of compost, animal manure, green manures and the avoidance of excess mechanization.

A large number of physical phenomena are modeled by nonlinear partial

differential equations, subject to appropriate initial/ boundary conditions; these

equations, in general, do not admit exact solution. The present monograph gives

constructive mathematical techniques which bring out large time behavior of

solutions of these model equations. These approaches, in conjunction with modern

computational methods, help solve physical problems in a satisfactory manner. The

asymptotic methods dealt with here include self-similarity, balancing argument,

and matched asymptotic expansions. The physical models discussed in some detail

here relate to porous media equation, heat equation with absorption, generalized

Fisher's equation, Burgers equation and its generalizations. A chapter each is

devoted to nonlinear diffusion and fluid mechanics. The present book will be found

useful by applied mathematicians, physicists, engineers and biologists, and would

considerably help understand diverse natural phenomena.

This volume examines the processes and impacts of exclusion on the Adivasis (tribal or indigenous people) in India and what repercussions these have for their constitutional rights. The chapters explore a wide range of issues connected to the idea of exclusion - land and forest resources, habitats and livelihoods, health and disease management, gender relations, language and schooling, water resources, poverty, governance, markets and technology, and development challenges - through case studies from different parts of the country. The book argues that any laws intended to safeguard the fundamental rights of Adivasis must acknowledge the fact that their diverse and complex identities are not homogenous, and that uniform laws have failed to address their systemic marginalisation since the colonial era. This work appeals for a serious and meaningful political intervention towards tribal development. The volume will be useful to scholars and researchers of tribal and Third World studies, sociology and social anthropology, exclusion studies and development studies.

Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk factor of death, Alternative Sampling Designs for Time-To-Event Data with Applications to Biomarker Discovery in Alzheimer's Disease, Dynamic risk prediction for cardiovascular disease: An illustration using the ARIC Study, Theoretical advances in type 2 diabetes, Finite Mixture Models in Biostatistics, and Models of Individual and Collective Behavior for Public Health Epidemiology. As a two part volume, the series covers an extensive range of techniques in the field. It present a vital resource for statisticians who need to access a number of different methods for assessing epidemic spread in population, or in formulating public health policy.