Wind wizard : Alan G. Davenport and the art of wind engineering / / Siobhan Roberts

• Record Nr.: UNINA9910966353103321
• Autore: Roberts Siobhan
• Pubbl/distr/stampa: Princeton, NJ, : Princeton University Press, 2013
• ISBN: 9781400844708; 1400844703
• Edizione: [Course Book]
• Descrizione fisica: 1 online resource (289 p.)
• Disciplina: 624.1/75
• Soggetti: Wind-pressure; Buildings - Aerodynamics; Bridges - Aerodynamics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Front matter -- Contents -- I. Sowing Wind Science -- II. Tall and Taller Towers -- III. Long and Longer Bridges -- IV. Project Storm Shelter -- Acknowledgments -- Notes -- Interview Sources -- Glossary -- Bibliography -- Index
• Sommario/riassunto: With Wind Wizard, Siobhan Roberts brings us the story of Alan Davenport (1932-2009), the father of modern wind engineering, who investigated how wind navigates the obstacle course of the earth's natural and built environments--and how, when not properly heeded, wind causes buildings and bridges to teeter unduly, sway with abandon, and even collapse. In 1964, Davenport received a confidential telephone call from two engineers requesting tests on a pair of towers that promised to be the tallest in the world. His resulting wind studies on New York's World Trade Center advanced the art and science of wind engineering with one pioneering innovation after another. Establishing the first dedicated "boundary layer" wind tunnel laboratory for civil engineering structures, Davenport enabled the study of the atmospheric region from the earth's surface to three thousand feet, where the air churns with turbulent eddies, the average wind speed increasing with height. The boundary layer wind tunnel mimics these windy marbled striations in order to test models of buildings and ; bridges that inevitably face the wind when built. Over the years, Davenport's revolutionary lab investigated and improved the wind-worthiness of the world's greatest structures, including the Sears Tower, the John Hancock Tower, Shanghai's World Financial Center, the CN Tower, the iconic Golden Gate Bridge, the Bronx-Whitestone Bridge, the Sunshine Skyway, and the proposed crossing for the Strait of Messina, linking Sicily with mainland Italy. Chronicling Davenport's innovations by analyzing select projects, this popular-science book gives an illuminating behind-the-scenes view into the practice of wind engineering, and insight into Davenport's steadfast belief that there is neither a structure too tall nor too long, as long as it is supported by sound wind science. Some images inside the book are unavailable due to digital copyright restrictions.

Computational immunology : applications / / Shyamasree Ghosh

• Record Nr.: UNINA9910969754203321
• Autore: Ghosh Shyamasree
• Pubbl/distr/stampa: Boca Raton, FL : , : CRC Press, Taylor & Francis Group, , [2020]
• ISBN: 1-351-02348-9; 1-351-02349-7; 1-351-02350-0
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (201 pages)
• Disciplina: 616.0790285
• Soggetti: Immunoinformatics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- Author -- List of Abbreviations -- Introduction -- Chapter 1: Understanding Cell Fate and Computational Immunology -- 1.1 Introduction -- 1.2 Cell Fate -- 1.3 Computation and Stem Cell Biology and Cell Fate -- 1.4 Cell Cycle and Microenvironment in Cell Fate Determination -- 1.5 T and B Cell Fate Determination -- 1.5.1 T Cell Fate -- 1.5.2 B Cell Fate -- 1.6 Computational Prediction of Stem Cell Fates -- 1.7 Statistical Analysis ; and Application in Understanding of Stem Cell Fate -- 1.8 Deterministic and Stochastic Models of Cell Fate Choice -- 1.9 Decision Making and Disease -- 1.10 Statistical Analyses and Gene Regulatory Networks (GRNs) -- 1.10.1 Principal Components Analysis (PCA) -- 1.10.2 Partial Least Squares (PLS) Regression and GRNs -- 1.11 Discussions -- References -- Chapter 2: Next Generation Sequencing (NGS) and Computational Immunology -- 2.1 Introduction -- 2.2 NGS: A Glimpse through Available Technologies -- 2.3 NGS: Applications of Different Tools and Techniques -- 2.4 NGS and Tools of Data Analysis -- 2.5 NGS Applications -- 2.5.1 Applications in the Immune System -- 2.5.1.1 NGS in TCR Studies -- 2.5.1.2 NGS in BCR Studies -- 2.5.2 Cancer -- 2.5.3 NGS and Microbial Application -- 2.5.4 Infectious Diseases -- 2.5.5 NGS and Transplantation -- 2.5.6 Systemic Autoimmune Diseases -- 2.6 Single Cell Transcriptomics -- 2.7 ImmuneDB -- 2.8 ASAP-A Webserver for Immunoglobulin-Sequencing Analysis Pipeline -- 2.9 Discussions -- References -- Chapter 3: Computational Modeling and Biology of Disease -- 3.1 Introduction -- 3.2 Computation and Biology of Disease -- 3.2.1 Neurological Disorders -- 3.2.2 Respiratory Disorders -- 3.2.3 Cardiovascular Disorders -- 3.2.4 Diseases of the Bone -- 3.2.5 Kidney Diseases -- 3.2.6 Cancer.; 3.2.7 Immunological Disorders -- 3.2.8 Infectious Diseases -- 3.2.9 Metabolic Disorder -- 3.2.9.1 Databases -- 3.2.9.2 Human Microbiome and Computational Methods -- 3.3 Discussion -- References -- Chapter 4: Drug Designing and Computational Immunology -- 4.1 Introduction -- 4.2 Computer-Aided Drug Designing (CADD) -- 4.3 Structure-Based Computer-Aided Drug Design (SB-CADD) -- 4.4 Polypharmocology -- 4.5 Adverse Drug Reactions -- 4.6 Retrobiosynthesis -- 4.7 Applications in Diseases -- 4.7.1 Neurological Diseases -- 4.7.2 Targeting Biomolecules and Channelopathies -- 4.7.3 Targeting P450 -- 4.7.4 Nanoparticle Drug Delivery Devices -- 4.7.5 Cancer -- 4.7.6 Cardiovascular -- 4.7.7 Antimicrobials -- 4.7.8 Drug Design and Immune System -- 4.7.9 Diabetes -- 4.7.10 Infectious Diseases -- 4.7.10.1 Influenza -- 4.7.10.2 Human Trypanosomiasis -- 4.7.10.3 HIV -- 4.7.10.4 Malaria -- 4.8 Small Molecules -- 4.9 Pocket-Based Drug Design -- 4.10 Drug Repositioning -- 4.11 Natural Compounds -- 4.12 Vaccination -- 4.13 Ligand-Based CADD (LB-CADD) -- 4.14 Discussion -- References -- Chapter 5: Computation and Identification of Biomarkers -- 5.1 Introduction -- 5.2 Biomarkers -- 5.3 Different Approaches to Biomarker Discovery -- 5.4 Computation and Identification of Biomarkers in Health -- 5.5 Computation and Identification of Biomarkers in Disease -- 5.5.1 Cancer -- 5.5.2 Inflammation Disorders -- 5.5.3 Inflammatory Bowel Disease (IBD) -- 5.5.4 HIV -- 5.5.5 Cardiovascular -- 5.5.6 Neurological -- 5.6 Discussion: Biomarkers in Detection of Clinical Outcomes -- References -- Chapter 6: Applications in Organ Transplantation -- 6.1 Introduction -- 6.2 Global Knowledge Base on Transplantation -- 6.3 Computer Simulations and Applications in Transplantation -- 6.4 Cardiac Transplants -- 6.5 Liver Transplantation -- 6.6 Kidney Transplantation -- 6.7 Lung Transplantation.; 6.8 Others -- 6.9 Immunosuppression -- 6.10 Discussion -- References -- Chapter 7: Application in Disease Detection and Therapy -- 7.1 Introduction -- 7.2 Computation and Disease Detection and Monitoring -- 7.3 Cancer -- 7.4 Surgery -- 7.5 Brain Disorders -- 7.6 Cardiac Disorders -- 7.7 Studies in Animal Models -- 7.7.1 Neural Disorders -- 7.7.2 Therapy Outcome in HIV -- 7.7.3 Asthma -- 7.7.4 Antibiotic Research -- 7.7.5 Immunization -- 7.8 Discussion -- ; References -- Chapter 8: Computational Methods and Applications in Understanding of the Invertebrate Immune System -- 8.1 Introduction -- 8.1.1 Immune Cells and Systems and Pathways in Different Organisms in the Invertebrate Phyla -- 8.1.1.1 Immune System in Sponges -- 8.1.1.2 Cnidaria -- 8.1.1.3 Platyhelminthes -- 8.1.1.4 Nematodes -- 8.1.1.5 Annelida -- 8.1.1.6 Arthropoda -- 8.1.1.7 Mollusca -- 8.1.2 Regeneration in Planaria -- 8.1.3 Invertebrate Immunity and Database -- 8.2 Discussion -- References -- Chapter 9: Computational Immunology and Studies from the Human Immune System -- 9.1 Introduction -- 9.2 Infectious Disease -- 9.3 Modeling of H. pylori Infection Responses -- 9.4 Computational Immunology and Immune Responses -- 9.5 Computational Immunology and Insights into Macrophage Function -- 9.6 Discussion -- References -- Further Reading -- Glossary -- Index.
• Sommario/riassunto: Computational Immunology: Applications focuses on different mathematical models, statistical tools, techniques, and computational modelling that helps in understanding complex phenomena of the immune system and its biological functions. The book also focuses on the latest developments in computational biology in designing of drugs, targets, biomarkers for early detection and prognosis of a disease. It highlights the applications of computational methods in deciphering the complex processes of the immune system and its role in health and disease. This book discusses the most essential topics, including Next generation sequencing (NGS) and computational immunology Computational modelling and biology of diseases Drug designing Computation and identification of biomarkers Application in organ transplantation Application in disease detection and therapy Computational methods and applications in understanding of the invertebrate immune system Shyamasree Ghosh (MSc, PhD, PGDHE, PGDBI) Scientific Officer (F), is currently working in the School of Biological Sciences, National Institute of Science Education and Research (NISER), Bhubaneswar, DAE, Govt of India, graduated from the prestigious Presidency College Kolkata in 1998. She was awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.