Ning Li - Böcker

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues.Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website.This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Privileged Scaffolds in Drug Discovery is the most complete and up-to-date work in the area. Covering a wide range of privileged structures, it is a perfect reference for scientists involved in targeted drug development.

The editors recruited experts from several prestigious Chinese institutions to cover the areas of antiviral drugs, chalcone, pyrimidine, (benz)imidazoles, natural product-derived privileged scaffolds, N-Sulfonyl carboxamides, kinase inhibitors, antitumor molecules, antineurodegenerative drugs, triazoles, oxazolidinone, indole and indoline scaffolds, tigliane diterpenoids, peptide and peptide-based drugs, quassinoids, and others including pseudonatural products, macrocycles, stable peptides and peptidomimetics. The book also explores scaffolds in drug molecules approved in recent years.

Privileged Scaffolds in Drug Discovery is a complete reference for researchers in drug discovery and organic synthesis, in academic and corporate settings, who are investigating privileged structures upon which to base new drugs. Researchers in medicinal chemistry and chemical biology will also find the contents of this book valuable.

Provides wide coverage of privileged scaffolds in new drug discoveryIncludes complex and diverse natural product scaffoldsCovers applications to peptides and peptide-based drugs

Natural Product Drug Discovery: Highly Anticipated Natural Molecules, a new volume in the Drug Discovery Opinion series, provides a comprehensive examination of the role of natural products in innovative drug development. The book addresses the significant challenges that highly active natural molecules face in the drug development process, including issues related to bioavailability and potency. Sections present analyses of various classes of natural products, including polysaccharides, volatile oils, and diterpenoids, exploring their chemical properties, biological activities, and potential clinical applications. Each chapter, written by leading experts, offers insights into structural modification techniques, naturally sourced inhibitors, and the application of green biomanufacturing strategies.It will serve as an essential resource for researchers, pharmacologists, and industry professionals involved in natural product drug discovery. Readers will find the necessary information to navigate the complexities of the field, emphasizing the integration of traditional knowledge with modern scientific approaches. Through a thorough understanding of these natural compounds, this book aims to contribute to the advancement of therapeutic innovations in pharmacotherapy.Provides a comprehensive analysis of natural products' chemical properties and biological activities for informed drug developmentExplores challenges and solutions in the commercialization of highly active natural moleculesFeatures expert contributions that offer insights into structural modification and green biomanufacturing strategiesIncludes case studies that illustrate successful applications of natural products in therapeutic contextsServes as an essential resource for researchers and professionals in natural product drug discovery and pharmacotherapy

This book provides a multifaceted examination of solid waste management methods, the preparation, properties, and application of solid waste materials in the remediation of various environmental media, as well as the combination of solid waste materials and artificial intelligence.Based on the latest research results and cutting-edge technologies from around the world, the contributors combine the design principles of solid waste materials with application examples, including a complete system, clear routes, and illustrations. They integrate the idea of ecological civilization, the concept of sustainable development, and engineering innovation thinking, providing a reliable reference for resource recycling and contributing to global low-carbon emission.The book is suitable for teachers and students, as well as researchers, industrial technicians, and managers involved in solid waste resources and environmental remediation.

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues.Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website.This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2021, held in November 2021. The papers are organized in two topical tracks: mobile application and deep learning, and mobile application with data analysis.

A novel strain of influenza A (H1N1) virus emerged and an outbreak of influenza A (H1N1) occurred worldwide in 2009 and 2010, posing a severe threat to the health of human beings. The two Editors work together in Beijing You An Hospital, to combat this type of influenza. This book, Radiology of Influenza A (H1N1), is intended to provide first-hand clinical data and its scientific analysis, thus supporting sound clinical practice for influenza A (H1N1) prevention and treatment as well as related scientific research. The authors have collected over 100 critical influenza A (H1N1) virus-infected cases. For cases of influenza A (H1N1) that resulted in death, autopsies were performed for 8 cases after receiving their families’ informed consent. Over 200 reports on pathological and histological analysis as well as immunohistochemical and electroscopic analysis were brought together. This book was then compiled by comparing the published data with the present first-hand data. This book includes a wealth of content, including DR, CT and MRI images, pathological and histological figures, and immunohistochemical and electroscopic figures. Related research, clinical and educational needs can be readily satisfied by its detailed data, texts and figures, as well as typical case reports. Li Hongjun, is professor and director of the diagnostic radiology department in Beijing You An Hospital, affiliated with Capital Medical University, Beijing, China. Li Ning, is professor and president of Beijing You An Hospital, affiliated with Capital Medical University, Beijing, China.

A novel strain of influenza A (H1N1) virus emerged and an outbreak of influenza A (H1N1) occurred worldwide in 2009 and 2010, posing a severe threat to the health of human beings. The two Editors work together in Beijing You An Hospital, to combat this type of influenza. This book, Radiology of Influenza A (H1N1), is intended to provide first-hand clinical data and its scientific analysis, thus supporting sound clinical practice for influenza A (H1N1) prevention and treatment as well as related scientific research. The authors have collected over 100 critical influenza A (H1N1) virus-infected cases. For cases of influenza A (H1N1) that resulted in death, autopsies were performed for 8 cases after receiving their families’ informed consent. Over 200 reports on pathological and histological analysis as well as immunohistochemical and electroscopic analysis were brought together. This book was then compiled by comparing the published data with the present first-hand data. This book includes a wealth of content, including DR, CT and MRI images, pathological and histological figures, and immunohistochemical and electroscopic figures. Related research, clinical and educational needs can be readily satisfied by its detailed data, texts and figures, as well as typical case reports. Li Hongjun, is professor and director of the diagnostic radiology department in Beijing You An Hospital, affiliated with Capital Medical University, Beijing, China. Li Ning, is professor and president of Beijing You An Hospital, affiliated with Capital Medical University, Beijing, China.

Besides all monitoring data, the decision support module contains an irrigation calculator, a box model, and a distributed groundwater model to project the outcomes of different water allocation scenarios.