Jun Sun – författare

The Microbiome in Health and Disease, Volume 171 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Microbiome in health and disease, CNS development and microbiome in infants, A gut feeling in ALS, Microbiome (Virome) and virus infection, Bugs and Drugs: microbiome in medicine metabolism, Immunity, T cells, and microbiome, Salmonella (Bacterial) infection and cancer: of mice and men, and many other highly researched topics.

Provides a novel theme and multiple disciplinary topics of microbiome research in basic and translational studies Presents an updated collection on bacteria, virus, fungi and their interactions in microbiome Includes a timely discussion on the tools and methods used for modeling and analysis of microbiome data

Microbiome and the Eye: What's the connection? highlights how alterations in the gut and eye microbiomes can lead to systemic immune alterations with subsequent effects on the eye. The book is divided into two sections, one highlighting how alterations in the gut microbiome impact various components of health outside the gut, with a focus on the immune system and inflammatory mediators, and the second focusing on studies on a variety of ocular diseases, including ocular surface diseases/dry eye, keratitis, uveitis, glaucoma, and retinopathy to gut dysbiosis. With its translational approach, the book is suitable for both researchers and clinicians.

The book will help readers understand the mechanisms in which gut and eye microbiome composition may influence health in multiple compartments, with a focus on eye diseases.

Helps researchers understand the clinical eye diseases that have been linked to gut microbiome abnormalities Helps clinicians understand the mechanisms in which gut microbiome composition may influence health in multiple compartments Provides a foundation for future studies that consider gut microbiome manipulations as a treatment for specific eye diseases

Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives, the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle swarm optimisation (QPSO) algorithm. This globally convergent algorithm has fewer parameters, a faster convergence rate, and stronger searchability for complex problems.The book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles of the PSO algorithm. Examples illustrate how the PSO algorithm solves optimisation problems. The authors also analyse the reasons behind the shortcomings of the PSO algorithm.Moving on to the QPSO algorithm, the authors give a thorough overview of the literature on QPSO, describe the fundamental model for the QPSO algorithm, and explore applications of the algorithm to solve typical optimisation problems. They also discuss some advanced theoretical topics, including the behaviour of individual particles, global convergence, computational complexity, convergence rate, and parameter selection. The text closes with coverage of several real-world applications, including inverse problems, optimal design of digital filters, economic dispatch problems, biological multiple sequence alignment, and image processing. MATLAB®, Fortran, and C++ source codes for the main algorithms are provided on an accompanying downloadable resources.Helping you numerically solve optimisation problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. It not only explains how to use the algorithms, but also covers advanced topics that establish the groundwork for understanding.

This unique book officially defines microbiome statistics as a specific new field of statistics and addresses the statistical analysis of correlation, association, interaction, and composition in microbiome research. It also defines the study of the microbiome as a hypothesis-driven experimental science and describes two microbiome research themes and six unique characteristics of microbiome data, as well as investigating challenges for statistical analysis of microbiome data using the standard statistical methods. This book is useful for researchers of biostatistics, ecology, and data analysts.Presents a thorough overview of statistical methods in microbiome statistics of parametric and nonparametric correlation, association, interaction, and composition adopted from classical statistics and ecology and specifically designed for microbiome research.Performs step-by-step statistical analysis of correlation, association, interaction, and composition in microbiome data.Discusses the issues of statistical analysis of microbiome data: high dimensionality, compositionality, sparsity, overdispersion, zero-inflation, and heterogeneity.Investigates statistical methods on multiple comparisons and multiple hypothesis testing and applications to microbiome data.Introduces a series of exploratory tools to visualize composition and correlation of microbial taxa by barplot, heatmap, and correlation plot.Employs the Kruskal–Wallis rank-sum test to perform model selection for further multi-omics data integration.Offers R code and the datasets from the authors’ real microbiome research and publicly available data for the analysis used.Remarks on the advantages and disadvantages of each of the methods used.

Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives, the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle swarm optimisation (QPSO) algorithm. This globally convergent algorithm has fewer parameters, a faster convergence rate, and stronger searchability for complex problems.The book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles of the PSO algorithm. Examples illustrate how the PSO algorithm solves optimisation problems. The authors also analyse the reasons behind the shortcomings of the PSO algorithm.Moving on to the QPSO algorithm, the authors give a thorough overview of the literature on QPSO, describe the fundamental model for the QPSO algorithm, and explore applications of the algorithm to solve typical optimisation problems. They also discuss some advanced theoretical topics, including the behaviour of individual particles, global convergence, computational complexity, convergence rate, and parameter selection. The text closes with coverage of several real-world applications, including inverse problems, optimal design of digital filters, economic dispatch problems, biological multiple sequence alignment, and image processing. MATLAB®, Fortran, and C++ source codes for the main algorithms are provided on an accompanying downloadable resources.Helping you numerically solve optimisation problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. It not only explains how to use the algorithms, but also covers advanced topics that establish the groundwork for understanding.

Only recently have we begun to appreciate the role of microbiome in health and disease.

Only recently have we begun to appreciate the role of microbiome in health and disease.

This book constitutes the proceedings of the 5th International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, SETTA 2019, held in Shanghai, China, in November 2019.

Further, the chapters highlight the progress of immune therapy, stem cells and the role of the microbiome in the pathophysiology of cancers.Readers will gain insights into complex microbial communities, that inhabit most external human surfaces and play a key role in health and disease.

Further, the chapters highlight the progress of immune therapy, stem cells and the role of the microbiome in the pathophysiology of cancers.Readers will gain insights into complex microbial communities, that inhabit most external human surfaces and play a key role in health and disease.

This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for  microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing.  It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter so that these new methods can be readily applied in their own research. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.

This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for  microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing.  It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter so that these new methods can be readily applied in their own research. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.

This book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023.

This book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023.

This book constitutes the refereed proceedings of the 19th International Symposium on Formal Methods, FM 2014, held in Singapore, May 2014. The 45 papers presented together with 3 invited talks were carefully reviewed and selected from 150 submissions. The focus of the papers is on the following topics: Interdisciplinary Formal Methods, Practical Applications of Formal Methods in Industrial and Research Settings, Experimental Validation of Tools and Methods as well as Construction and Evolution of Formal Methods Tools.

This book constitutes the thoroughly refereed proceedings of the 6th Joint International Semantic Technology Conference, JIST 2016, held in Singapore, Singapore, in November 2016.

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.

This book highlights principles and applications of electromagnetic compatibility (EMC). After introducing the basic concepts, research progress, standardizations and limitations of EMC, the book puts emphasis on presenting the generation mechanisms and suppression principles of conducted electromagnetic interference (EMI) noise, radiated EMI noise, and electromagnetic susceptibility (EMS) problems such as electrostatic discharge (ESD), electric fast transient (EFT) and surge. By showing EMC case studies and solved examples, the book provides effective solutions to practical engineering problems. Students and researchers will be able to use the book as practical reference for EMC-related measurements and problem- solution.

This book highlights principles and applications of electromagnetic compatibility (EMC). After introducing the basic concepts, research progress, standardizations and limitations of EMC, the book puts emphasis on presenting the generation mechanisms and suppression principles of conducted electromagnetic interference (EMI) noise, radiated EMI noise, and electromagnetic susceptibility (EMS) problems such as electrostatic discharge (ESD), electric fast transient (EFT) and surge. By showing EMC case studies and solved examples, the book provides effective solutions to practical engineering problems. Students and researchers will be able to use the book as practical reference for EMC-related measurements and problem- solution.