Products related to Selectivity:
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Drug Selectivity : An Evolving Concept in Medicinal Chemistry
The book "Drug Selectivity - An Evolving Concept in Medicinal Chemistry" provides a current overview and comprehensive compilation for medicinal chemists that discusses the effects of aiming for multiple targets on the entire drug development process. The result is a broad survey of current and future strategies for drug selectivity in medicinal chemistry with theoretical but also practical aspects.Different strategies are presented and evaluated, such as various design approaches, merged multiple ligands, discovery technologies and a broad range of successful examples of unselective drugs taken from all major disease areas.With its wide-ranging view of an emerging new paradigm in drug development, this handbook is of prime importance for every medicinal and pharmaceutical chemist.
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Bioinformatics Data Skills : Reproducible and Robust Research with Open Source Tools
Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings.With this practical guide, you'll learn how to use freely available open source tools to extract meaning from large complex biological data sets.At no other point in human history has our ability to understand life's complexities been so dependent on our skills to work with and analyze data.This intermediate-level book teaches the general computational and data skills you need to analyze biological data.If you have experience with a scripting language like Python, you're ready to get started.Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles
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Big Data for the Public Good : Regulating Access to Public Sector Big Data for Research and Innovation
Can researchers and innovators use UK public sector data to produce knowledge that improves policy making, scrutinises government work and promotes the public interest?This book looks at interactions between UK public sector officials and researchers/innovators to shed light on barriers to data access and use.It asks: what are the frameworks that govern access to public sector big datasets for researchers and innovators?How are these frameworks applied in practice? What are the governance solutions for policy makers interested in harnessing the untapped potential of public sector big data to improve their policies and create public benefit?Public sector data is a valuable resource that can help researchers and innovators create knowledge and solutions that benefit society.As public bodies collect increasingly more data about us, UK policy makers try to maximise the use of public sector big data for the benefit of the public.But accessing this data is not easy. There are many legal, technical, and ethical barriers that prevent the use of public sector data for research and innovation.This book is for researchers and innovators who want to understand and overcome the barriers to accessing UK public sector data.It is also for policy makers who are interested in how public sector data can be used to improve decision-making, scrutinise government work, and promote the public interest.
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Managing Cloud Native Data on Kubernetes : Architecting Cloud Native Data Services Using Open Source Technology
Kubernetes has become the primary platform for deploying and managing cloud native applications.But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging.If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll discover open source technologies that are designed and built for the cloud.Delve into case studies to avoid the pitfalls others have faced and explore new use cases.Get an insider's view of what's coming from the innovators who are creating next-generation architectures and infrastructure. And you'll learn how to: Manage different data use cases on Kubernetes Reduce costs and simplify application development Leverage data and infrastructure to create new use cases and business models Make data infrastructure choices that are cost-efficient, secure, scalable, and elastic And more
Price: 63.99 £ | Shipping*: 0.00 £
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What is selectivity in electrical engineering?
Selectivity in electrical engineering refers to the ability of a system or device to respond to specific signals while ignoring others. It is a measure of how well a system can discriminate between different frequencies or channels. Selectivity is important in applications such as filtering out unwanted noise or interference in communication systems, allowing for the desired signal to be received or transmitted effectively. In electrical engineering, selectivity is often achieved through the use of filters or other signal processing techniques.
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What is the selectivity of reinsurance?
The selectivity of reinsurance refers to the process of choosing which risks to transfer to a reinsurer based on specific criteria. Reinsurers typically select risks that align with their underwriting guidelines, risk appetite, and financial capacity. By being selective in the risks they assume, reinsurers can manage their exposure to catastrophic events and ensure a balanced portfolio. This selectivity helps reinsurers maintain profitability and stability in the face of unpredictable events.
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What does selectivity mean in LS switches?
Selectivity in LS switches refers to the ability of the switch to accurately and efficiently route signals to their intended destination while minimizing interference or crosstalk with other signals. A highly selective LS switch will have low insertion loss and high isolation between channels, ensuring that signals remain clean and intact throughout the switching process. This is crucial in applications where multiple signals need to be switched simultaneously without compromising signal integrity.
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What is the selectivity of pre-insurance?
The selectivity of pre-insurance refers to the process of evaluating and selecting individuals or groups who are eligible for insurance coverage based on certain criteria. This helps insurance companies manage risk by only insuring individuals who are less likely to make claims or pose a higher risk. By carefully selecting who can obtain insurance coverage, insurance companies can maintain a balanced risk pool and offer competitive premiums to their policyholders.
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Open Source Software for Statistical Analysis of Big Data : Emerging Research and Opportunities
With the development of computing technologies in today's modernized world, software packages have become easily accessible.Open source software, specifically, is a popular method for solving certain issues in the field of computer science.One key challenge is analyzing big data due to the high amounts that organizations are processing.Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python.Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
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Open Source Software for Statistical Analysis of Big Data : Emerging Research and Opportunities
With the development of computing technologies in today's modernized world, software packages have become easily accessible.Open source software, specifically, is a popular method for solving certain issues in the field of computer science.One key challenge is analyzing big data due to the high amounts that organizations are processing.Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python.Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
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Open Access and the Future of Scholarly Communication : Policy and Infrastructure
It is impossible to imagine the future of academic libraries without an extensive consideration of open access—the removal of price and permission barriers from scholarly research online. As textbook and journal subscription prices continue to rise, improvements in technology make online dissemination of scholarship less expensive, and faculty recognize the practical and philosophical appeal of making their work available to wider audiences.As a consequences, libraries have begun to consider a wide variety of open access “flavors” and business models. These new possibilities have significant impact on both library services and collection policies, and the call for new skills within library staffing.Volume 9 of the series Creating the 21st-Century Academic Library is the first of two addressing the topic of open access in academic libraries and focuses on policy and infrastructure for libraries that wish to provide leadership on their campus in the transition to more open forms of scholarship. Chapters in the book discuss how to make the case for open access on campus, as well as the political and policy implications of libraries that themselves want to become publishing entities.Infrastructure issues are also addressed including metadata standards and research management services.Also considered here is how interlibrary loan, preservation and the library’s role in providing textbooks, support the concept of open access. It is hoped that this volume, and the series in general, will be a valuable and exciting addition to the discussions and planning surrounding the future directions, services, and careers in the 21st-century academic library.
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Scholarly Editing : A Guide to Research
This collection of twenty-six essays, written by acknowledged experts in literary studies, surveys the history of scholarly editing, describes the major research in a variety of disciplines, summarizes the resources available to scholars, and analyzes the issues currently facing textual editors. The book begins with an overview of scholarly editing, followed by four essays on the long tradition of editing the Bible and the Greek and Latin classics.The next cluster of essays proceeds through the major periods of British and American literature, from medieval to modern, further subdividing the Renaissance and the nineteenth century by genre and including a chapter devoted to Shakespeare.Additional essays cover other European literatures: French (Old French and early modern), Italian, medieval Spanish, German, and Russian.The concluding essays discuss representative non-European literatures and the “nonliterary” editing of folk literature in various languages.Each chapter includes a history of scholarly editing in the field, a citation of exemplary editions, and an introduction to a recommended list of further readings.
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What does selectivity mean in circuit breakers?
Selectivity in circuit breakers refers to the ability of the breakers to isolate and disconnect only the faulty section of the electrical system while leaving the rest of the system operational. This is important in preventing unnecessary power outages and disruptions to the entire system. Selectivity allows for a more targeted and efficient response to electrical faults, minimizing downtime and maximizing the reliability of the electrical system. It also helps in identifying and addressing the specific issue without affecting the rest of the system.
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What is selectivity among electrical engineering components?
Selectivity among electrical engineering components refers to the ability of a component to respond to specific signals or frequencies while ignoring others. This is important in applications where different signals need to be processed or filtered selectively. Components like filters, amplifiers, and sensors can exhibit selectivity based on their design and characteristics, allowing them to perform specific functions within a circuit or system. By controlling the selectivity of components, engineers can tailor the performance of a system to meet desired specifications and requirements.
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What is the selectivity in FI switches?
Selectivity in FI switches refers to the ability of the switch to accurately and reliably detect the presence of a fault in the protected circuit while ignoring normal transient disturbances. This means that the switch can distinguish between a genuine fault and harmless fluctuations in the system, ensuring that it only operates when necessary to isolate the fault and maintain the continuity of the power supply. High selectivity is essential for the reliable and efficient operation of FI switches in protecting electrical circuits and preventing electrical hazards.
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What is the selectivity of a circuit breaker?
The selectivity of a circuit breaker refers to its ability to isolate and disconnect only the faulty section of a circuit while allowing the rest of the system to continue functioning. This is important in preventing unnecessary power outages and disruptions. Selectivity is achieved by setting different time-current characteristics for each circuit breaker in a system, ensuring that the breaker closest to the fault operates first without affecting other parts of the system.
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