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Predicting Room of Origin Fire Hazards (The Society of Fire Protection Engineers Series)

by The Society of Fire Protection Engineers

This engineering guide provides a methodology to define and quantify the fire development andensuing conditions within the room of fire origin from the fire’s incipient stage through its fulldevelopment. The approach presented in this guide was developed using the framework set forthin the SFPE Engineering Guide to Performance-Based Fire Protection. 2nd ed., Quincy, Mass.:National Fire Protection Association, 2007.)It consists of three distinct parts:1. Approach selection2. Input definition and data collection3. Results computationSpecifically, this guide was developed for use as a means to implement the requirements presented in Chapter 10 of the SFPE Engineering Guide to Performance-Based Fire Protection. However, material within this guide has broader applicability and is therefore not limited to performance-based design applications.

Predicting Solubility of New Drugs: Handbook of Critically Curated Data for Pharmaceutical Research

by Alex Avdeef

In pharmaceutical research, solubility plays a key part in the assessment of pharmacokinetic risks. Poor drug absorption, reduced efficacy, excessive metabolism, and adverse reactions are frequently related to issues of drug solubility. During early discovery research at pharmaceutical companies, many thousands of molecules are considered. Most are rejected due to perceived unfavorable properties. Here the author uses the Wiki-pS0TM database, which forms the backbone of this unique handbook. Also discussed is the emerging class of therapeutically promising research molecules called PROTACs (proteolysis-targeting chimeras), showing a propensity for ‘undruggable’ targets.FEATURES• A comprehensive and unique listing of measured aqueous intrinsic solubility focusing on drug-like and drug-relevant molecules.• The database can be used to predict the solubility of research pharmaceutical molecules.• Includes downloadable files of the database (.csv format).• The mining of the database can result in a better design of solubility assay protocols, leading to better quality of measurements.• Artificial intelligence and Bayesian statistics will likely be key to this subject area in the future.Alex Avdeef has been an American Association of Pharmaceutical Scientists (AAPS) Fellow since 2014, a former visiting senior research fellow at King’s College London, and is the author of Absorption and Drug Development (2nd ed., Wiley, 2012). In 2021, the book was translated into Chinese, by translators affiliated with the China Food and Drug Administration. For nearly 50 years, he has been teaching, researching, and developing methods, instruments, and analysis software for the measurement of ionization constants, solubility, dissolution, and permeability of drugs. His accomplishments in the development of instrumentation include several well-known instruments that are or recently have been manufactured by leading companies in the instrument market, including Thermo Fisher Scientific, Sirius Analytical, and Pion Inc. He has over 200 technical publications in primary scientific journals and book chapters. He has written several comprehensive technical guides and is a co-inventor on six patents. He cofounded Sirius Analytical (UK) in 1989, pION Inc. (USA) in 1996, and founded in–ADME Research (New York City) in 2011. His other positions were at Orion Research, Syracuse University, UC Berkeley, and Caltech.

Predicting Storm Surges: UNESCO-IHE PhD Thesis

by Michael Siek

Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled p

Predicting the Future

by Henry Abarbanel

Through the development of an exact path integral for use in transferring information from observations to a model of the observed system, the author provides a general framework for the discussion of model building and evaluation across disciplines. Through many illustrative examples drawn from models in neuroscience, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is explored.

Predicting the T2K Neutrino Flux and Measuring Oscillation Parameters (Springer Theses)

by Tomislav Vladisavljevic

This thesis reports the calculation of neutrino production for the T2K experiment; the most precise a priori estimate of neutrino production that has been achieved for any accelerator-based neutrino oscillation experiment to date. The production of intense neutrino beams at accelerator facilities requires exceptional understanding of chains of particle interactions initiated within extended targets. In this thesis, the calculation of neutrino production for T2K has been improved by using measurements of particle production from a T2K replica target, taken by the NA61/SHINE experiment. This enabled the reduction of the neutrino production uncertainty to the level of 5%, which will have a significant impact on neutrino oscillation and interaction measurements by T2K in the coming years. In addition to presenting the revised flux calculation methodology in an accessible format, this thesis also reports a joint T2K measurement of muon neutrino and antineutrino disappearance, and the accompanying electron neutrino and antineutrino appearance, with the updated beam constraint.

Prediction Technologies for Improving Engineering Product Efficiency

by Lev M. Klyatis

This book is aimed at readers who need to learn the latest solutions for interconnected simulation, testing, and prediction technologies that improve engineering product efficiency, including reliability, safety, quality, durability, maintainability, life-cycle costing and profit. It provides a detailed analysis of technologies now being used in industries such as electronics, automotive, aircraft, aerospace, off-highway, farm machinery, and others. It includes clear examples, charts, and illustrations. This book provides analyses of the simulation, testing, and prediction approaches and methodologies with descriptive, negative trends in their development. The author discusses why many current methods of simulation, testing, and prediction are not successful and describes novel techniques and tools developed for eliminating these problems. This book is a tool for engineers, managers, researches in industry, teachers, and students. Lev Klyatis, Hab. Dr.-Ing., ScD., PhD, Senior Advisor SoHaR, Inc., has been a professor at Moscow State Agricultural Engineering University, research leader and chairman of State Enterprise TESTMASH, and served on the US Technical Advisory Group for the International Electrotechnical Commission (IEC), the ISO/IEC Join Study Group in Safety Aspects of Risk Assessment, the United Nations European Economical Commission, and US-USSR Trade and Economic Council. He is presently a member of World Quality Council, the Elmer A. Sperry Board of Award, SAE International G-41 Reliability Committee, the Integrated Design and Manufacturing Committee and session chairman of SAE International World Congresses in Detroit since 2012. His vast experience and innovation enable him to create a new direction for the successful prediction of product efficiency during any given time, including accurate simulation of real-world conditions, accelerated reliability and durability testing technology, and reducing recalls. His approach has been verified in various industries, primarily automotive, farm machinery, aerospace, and aircraft industries. He has shared his new direction working as the seminar instructor and consultant to Ford, DaimlerChrysler, Nissan, Toyota, Jatko Ltd., Thermo King, Black an Dekker, NASA Research Centers, Karl Schenck, and many others. He holds over 30 patents worldwide and is the author of over 300 publications, including 15 books.

Prediction and Calculation of Crystal Structures

by Sule Atahan-Evrenk Alan Aspuru-Guzik

The series Topics in Current Chemistry presents critical reviews of the present and future trends in modern chemical research. The scope of coverage is all areas of chemical science including the interfaces with related disciplines such as biology, medicine and materials science. The goal of each thematic volume is to give the non-specialist reader, whether in academia or industry, a comprehensive insight into an area where new research is emerging which is of interest to a larger scientific audience. Each review within the volume critically surveys one aspect of that topic and places it within the context of the volume as a whole. The most significant developments of the last 5 to 10 years are presented using selected examples to illustrate the principles discussed. The coverage is not intended to be an exhaustive summary of the field or include large quantities of data, but should rather be conceptual, concentrating on the methodological thinking that will allow the non-specialist reader to understand the information presented. Contributions also offer an outlook on potential future developments in the field. Review articles for the individual volumes are invited by the volume editors. Readership: research chemists at universities or in industry, graduate students.

Prediction and Control of Noise and Vibration from Ventilation Systems

by Cheuk Ming Mak Kuen Wai Ma Hai Ming Wong

This book addresses the prediction and control of noise and vibration in ventilation systems and their psychoacoustic effects on people. The content is based on the authors’ research and lecture material on building acoustics and provides insights into the development of prediction methods and control of noise and vibration from ventilation systems, and an assessment of their psychological effects on people. The basic principles and methods for prediction and control of noise and vibration from ventilation systems are discussed, including the latest developments on flow-generated noise prediction, assessment methods for the performance of vibration isolation, noise control using periodic Helmholtz Resonators, and holistic psychoacoustic assessment of noise from ventilation systems. The insightful book on noise and vibration in ventilation systems Extends into prediction, control, and psychoacoustic assessment methods The book suits graduate students and engineers in acoustics and noise and vibration control, as well as in building services engineering and across the built environment.

Prediction and Validation Technologies of Aerodynamic Force and Heat for Hypersonic Vehicle Design (Springer Aerospace Technology)

by Min Zhao

This book provides an overview of advanced prediction and verification technologies for aerodynamics and aerothermodynamics and assesses a number of critical issues in advanced hypersonic vehicle design. Focusing on state-of-the-art theories and promising technologies for engineering applications, it also presents a range of representative practical test cases. Given its scope, the book offers a valuable asset for researchers who are interested in thermodynamics, aircraft design, wind tunnel testing, fluid dynamics and aerothermodynamics research methods, introducing them to inspiring new research topics.

Prediction in Forensic and Neuropsychology: Sound Statistical Practices

by Ronald D. Franklin

Psychologists are under increasing pressure to demonstrate the ecological validity of their assessment procedures--to show that the recommendations concluding their evaluations are relevant to urgent concerns in the legal and social policy arenas, such as predicting dangerousness, awarding compensation, and choosing a custodial parent. How much damage does a referred patient have? Who or what "caused" the damage? What impact will it have on his or her future life, work, and family? And what can be done to remediate the damage? The purpose of this book is to provide sound objective methods for answering these questions. It integrates the knowledge of experienced practitioners who offer state-of-the-art summaries of the best current approaches to evaluating difficult cases with that of basic theorists who describe emerging methods in both predictive and inferential statistics, such as Bayesian networks, that have proven their value in other scientific fields. Arguably, the enterprise of psychological assessment is so interdependent with that of data analysis that attempts to make inferences without consideration of statistical implications is malpractice. Prediction in Forensic and Neuropsychology: Sound Statistical Practices clarifies the process of hypothesis testing and helps to push the clinical interpretation of psychological data into the 21st century. It constitutes a vital resource for all the stakeholders in the assessment process--practitioners, researchers, attorneys, and policymakers.

Prediction of Long Term Corrosion Behaviour in Nuclear Waste Systems EFC 36 (European Federation of Corrosion Publications)

by Damien Feron

Papers presented on prediction of long term corrosion behaviour in nuclear waste systems EFC Issue 36.

Prediction of Polymer Properties (Plastics Engineering)

by Jozef Bicerano

Highlighting a broad range multiscale modeling and methods for anticipating the morphologies and the properties of interfaces and multiphase materials, this reference covers the methodology of predicting polymer properties and its potential application to a wider variety of polymer types than previously thought possible. A comprehensive source, the

Prediction of Polymeric Membrane Separation and Purification Performances

by Alexander Anim-Mensah Rakesh Govind

This brief describes the development of a new model for realistically characterizing solution-diffusion transport mechanisms in polymeric membranes that are used for separation and purification of organic solvents. Polymeric membranes used in these environments, if not selected appropriately, undergo excessive swelling and compaction resulting in lowered performance or membrane destruction in the long-term. This brief describes the relationship between key parameters from a chemical, mechanical and thermodynamic perspective. Moreover, the authors show how this new model points membrane manufacturers, scientists, and engineers towards an understanding of how these key parameters are considered in (1) designing and manufacturing membranes for the right application, (2) designing the right test experiments to determine the long-term membrane behavior in a short time, (3) minimizing the number of experiments to determine a reliable membrane for an application and (4) selecting the right membrane with higher level of certainty. The overall benefits of the model includes saving money and time. A simplified version of the model is included to assist the reader.

Prediction of Protein Secondary Structure

by Yaoqi Zhou Andrzej Kloczkowski Eshel Faraggi Yuedong Yang

This thorough volume explores predicting one-dimensional functional properties, functional sites in particular, from protein sequences, an area which is getting more and more attention. Beginning with secondary structure prediction based on sequence only, the book continues by exploring secondary structure prediction based on evolution information, prediction of solvent accessible surface areas and backbone torsion angles, model building, global structural properties, functional properties, as well as visualizing interior and protruding regions in proteins. Written for the highly successful Methods in Molecular Biology series, the chapters include the kind of detail and implementation advice to ensure success in the laboratory. Practical and authoritative, Prediction of Protein Secondary Structure serves as a vital guide to numerous state-of-the-art techniques that are useful for computational and experimental biologists.

Prediction of Protein Secondary Structure (Methods in Molecular Biology #2867)

by Andrzej Kloczkowski Eshel Faraggi Lukasz Kurgan

This second edition volume expands on the previous edition with updates on the latest methods, resources, and studies concerning analysis and prediction of various structural and functional aspects of proteins and ncRNAs. The chapters in this book cover topics such as secondary structure characterization and prediction; the use and impact of AI (including AlphaFold, large language models, and deep neural networks) in the protein structure prediction field; methods and resources for the prediction of posttranslational modifications, residue-residue contacts, subcellular localization, intrinsic disorder, protein-ligand interactions, and protein aggregation; analysis of cryo-EM data; and analysis of noncoding RNAs in the context of human diseases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions and surveys of the respective topics, list the necessary materials and methods, cover step-by-step instructions on how to use predictive tools and interpret their results, and provide tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Prediction of Protein Secondary Structure, Second Edition is a valuable resource for anyone interested in understanding the dynamic and growing field of the protein structure prediction.

Predictive ADMET

by Laszlo Urban Jianling Wang

This book helps readers integrate in silico, in vitro, and in vivo ADMET (absorption, distribution, metabolism, elimination and toxicity) and PK (pharmacokinetics) data with routine testing applications so that pharmaceutical scientists can diagnose ADMET problems and present appropriate recommendations to move drug discovery programs forward.The book introduces the current clinical practice for drug discovery and development along with the impact on early risk assessment; consolidates the tools and models to intelligently integrate existing in silico, in vitro and in vivo ADMET data; and demonstrates successful cases and lessons learned from real drug discovery and development. In short, it is a book aimed to provide a practical road map for drug discovery and development scientists to generate efficacious and safe drugs for unmet medical needs.

Predictive Analytics for Toxicology: Applications in Discovery Science

by Luis G. Valerio, Jr.

Predictive data science is already in use in many fields, but its application in toxicology is new and sought after by non-animal alternative testing initiatives. Predictive Analytics for Toxicology: Applications in Discovery Science provides a comprehensive overview of the application of predictive analytics in the field of toxicology, highlighting its role and applications in discovery science.This book addresses the challenges of accurately predicting high-level endpoints of toxicity and explores the use of computational and artificial intelligence research to automate predictive toxicology. It underscores the importance of predictive toxicology in proposing and explaining adverse outcomes resulting from human exposures to specific toxicants, especially when experimental and observational data on the toxicant are incomplete or unavailable.Key features: Includes a plain language description of predictive analytics in toxicology adding an overview of the wide range of applications Examines the science of prediction, computational models as an automated science and comprehensive discussions on concepts of machine learning Opens the hood on AI and its applications in toxicology Features coverage on how in silico toxicity predictions are translational science tools The book integrates strategies and practices of predictive toxicology and offers practical information that students and professionals of the toxicology, chemical, and pharmaceutical industries will find essential. It fulfills the expectations of student researchers seeking to learn predictive analytics in toxicology. This book will energize scientists to conduct predictive toxicology modeling using artificial intelligence and machine learning, and inspire students and seasoned scientists interested in automated science to pick up new research using predictive in silico models to evaluate chemical-induced toxicity.With its focus on practical applications and real-world examples, this book serves as a guide for navigating the complex issues and practices of discovery toxicology. It is an essential resource for those interested in computer-based methods in toxicology, providing valuable insights into the use of predictive analytics.

Predictive Control in Process Engineering: From the Basics to the Applications

by Ulrich Schmitz Ruth Bars Robert Haber

Describing the principles and applications of single input, single output and multivariable predictive control in a simple and lively manner, this practical book discusses topics such as the handling of on-off control, nonlinearities and numerical problems. It gives guidelines and methods for reducing the computational demand for real-time applications. With its many examples and several case studies (incl. injection molding machine and waste water treatment) and industrial applications (stripping column, distillation column, furnace) this is invaluable reading for students and engineers who would wish to understand and apply predictive control in a wide variety of process engineering application areas.

Predictive Cruise Control for Road Vehicles Using Road and Traffic Information (Advances in Industrial Control)

by Péter Gáspár Balázs Németh

This book focuses on the design of a multi-criteria automated vehicle longitudinal control system as an enhancement of the adaptive cruise control system. It analyses the effects of various parameters on the average traffic speed and the traction force of the vehicles in mixed traffic from a macroscopic point of view, and also demonstrates why research and development in speed control and predictive cruise control is important. The book also summarises the main steps of the system’s robust control design, from the modelling to its synthesis, and discusses both the theoretical background and the practical computation method of the control invariant sets.The book presents the analysis and verification of the system both in a simulation environment and under real-world conditions. By including the systematic design of the predictive cruise control using road and traffic information, it shows how optimization criteria can lead to multiobjective solutions, and the advanced optimization and control design methods required. The book focuses on a particular method by which the unfavourable effect of the traffic flow consideration can be reduced. It also includes simulation examples in which the speed design is performed, while the analysis is carried out in simulation and visualization environments.This book is a valuable reference for researchers and control engineers working on traffic control, vehicle control and control theory. It is also of interest to students and academics as it provides an overview of the strong interaction between the traffic flow and an individual vehicle cruising from both a microscopic and a macroscopic point of view.

Predictive Data Modelling for Biomedical Data and Imaging (River Publishers Series in Biotechnology and Medical Research)

by Poonam Tanwar K. Kalaiselvi Haider Raza Seema Rawat Tapas Kumar

In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding.Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Beginning of Predictive Data Modeling for Biomedical Data and Imaging/Healthcare, Section II – Data Design and Analysis for Biomedical Data and Imaging/Healthcare, and Section III – Case Studies of Predictive Analytics for Biomedical Data and Imaging/Healthcare. We hope this book will inspire further research and innovation in the field of predictive data modeling for biomedical data and imaging in healthcare. By exploring diverse case studies and methodologies, this book contributes to the advancement of healthcare practices, ultimately improving patient outcomes and well-being.

Predictive Health: How We Can Reinvent Medicine to Extend Our Best Years

by Kenneth Brigham Michael M. E. Johns

ItOCOs no stretch to claim that America is in the midst of a healthcare meltdown. Care is costly and unattainable for many, and often unsatisfactory even for those who can afford treatment. The medical system focuses on treating diseases and their symptoms, and spends so much effortOCoand moneyOCoin the last miserable month of patientsOCO lives that little is left to make sure that the preceding years are as healthful as possible. In "Predictive Health," distinguished doctors Kenneth Brigham and Michael M. E. Johns propose to radically change the current model by restructuring the way patients receive care. They introduce the concept of predictive health, which will turn the existing paradigm on its headOCofocusing on prediction instead of diagnosis, and health rather than disease. Rather than treating symptoms as they arise, doctors practicing predictive health would be involved in a patientOCOs life right from the start. A drop of blood from a tiny heel prick at birth would be run through nanolabs, the resulting information assembled into a picture of the newbornOCOs health. Any potential risk factorsOCorisk for type II diabetes, genetic propensity for obesityOCowould be caught long before they became problematic, and strategies forged for treatment. In essence, health care professionals would become committed consultants, sticking with a patient for the entire course of their lives. The potential savings from this kind of partnership is staggering: the cost of lifelong health care would amount to less than the cost of a month-long stay in an early twenty-first century ICU. Interweaving descriptions of phenomenal advances in science and technology with illustrative anecdotes and personal experiences of the authorsOCO combined century in academic medicine, "Predictive Health" translates the foundations of the new biomedicine into language accessible to a general audienceOCothose who must understand the potential of the unprecedented opportunity confronting us if major change is to happen. The product of a decade-long collaboration between two of the leading figures in predictive health, "Predictive Health" offers a deeply knowledgeable, deeply humane look at the state of medicine today, and the potential for medicine tomorrow.

Predictive Maintenance in Smart Factories: Architectures, Methodologies, and Use-cases (Information Fusion and Data Science)

by Tania Cerquitelli Nikolaos Nikolakis Niamh O’Mahony Enrico Macii Massimo Ippolito Sotirios Makris

This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.

Predictive Methods in Percutaneous Absorption

by Gary P. Moss Darren R. Gullick Simon C. Wilkinson

This book sheds new light on the development and use of quantitative models to describe the process of skin permeation. It critically reviews the development of quantitative predictive models of skin absorption and discusses key recommendations for model development. Topics presented include an introduction to skin physiology; the underlying theories of skin absorption; the physical laboratory-based processes used to generate skin absorption data, which is in turn used to construct mathematical models describing the skin permeation process; algorithms of skin permeability including quantitative structure-activity (or permeability) relationships (QSARs or QSPRs); relationships between permeability and molecular properties; the development of formulation-focused approaches to models of skin permeability prediction; the use of artificial membranes, e. g. polydimethylsiloxane as alternatives to mammalian skin; and lastly, the use of novel Machine Learning methods in developing the next generation of predictive skin permeability models. The book will be of interest to all researchers in academia and industry working in pharmaceutical discovery and development, as well as readers from the field of occupational exposure and risk assessment, especially those whose work involves agrochemicals, bulk chemicals and cosmetics.

Predictive Microbiology in Foods

by Antonio Valero Fernando Perez-Rodriguez

Predictive microbiology is a recent area within food microbiology, which studies the responses of microorganisms in foods to environmental factors (e.g., temperature, pH) through mathematical functions. These functions enable scientists to predict the behavior of pathogens and spoilage microorganisms under different combinations of factors. The main goal of predictive models in food science is to assure both food safety and food quality. Predictive models in foods have developed significantly in the last 20 years due to the emergence of powerful computational resources and sophisticated statistical packages. This book presents the concepts, models, most significant advances, and future trends in predictive microbiology. It will discuss the history and basic concepts of predictive microbiology. The most frequently used models will be explained, and the most significant software and databases (e.g., Combase, Sym'Previus) will be reviewed. Quantitative Risk Assessment, which uses predictive modeling to account for the transmission of foodborne pathogens across the food chain, will also be covered.

Predictive Species and Habitat Modeling in Landscape Ecology

by Falk Huettmann Yolanda F. Wiersma C. Ashton Drew

Most projects in Landscape Ecology, at some point, define a species-habitat association. These models are inherently spatial, dealing with landscapes and their configurations. Whether coding behavioral rules for dispersal of simulated organisms through simulated landscapes, or designing the sampling extent of field surveys and experiments in real landscapes, landscape ecologists must make assumptions about how organisms experience and utilize the landscape. These convenient working postulates allow modelers to project the model in time and space, yet rarely are they explicitly considered. The early years of landscape ecology necessarily focused on the evolution of effective data sources, metrics, and statistical approaches that could truly capture the spatial and temporal patterns and processes of interest. Now that these tools are well established, we reflect on the ecological theories that underpin the assumptions commonly made during species distribution modeling and mapping. This is crucial for applying models to questions of global sustainability. Due to the inherent use of GIS for much of this kind of research, and as several authors' research involves the production of multicolored map figures, there would be an 8-page color insert. Additional color figures could be made available through a digital archive, or by cost contributions of the chapter authors. Where applicable, would be relevant chapters' GIS data and model code available through a digital archive. The practice of data and code sharing is becoming standard in GIS studies, is an inherent method of this book, and will serve to add additional research value to the book for both academic and practitioner audiences.

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