Proximity As Method

This book examines proximity as a benchmarked concept that can be deployed across a range of humanities disciplines to rethink the ways in which existences in the world are always already coexistences - and to parse the heuristic, ethical, epistemological, praxeological consequences of this recognition.

This book provides detailed protocols and untold tips and tricks regarding the most well-known examples of proximity labeling methods, in which the protein of interest is genetically fused to or labeled with an enzyme that can generate short-lived reactive species to non-specifically label molecules within a certain radius of up to twenty nanometers. Beginning with peroxidase-based proximity labeling methods, the volume continues with BioID, proximity labeling methods that describe the proximity ligation assay to detect RNA-DNA interactions, UV cross-linking to demonstrate RNA-protein interactions, and how chemical and enzymatic reactivities can be improved upon DNA-DNA and protein-protein interactions, as well as “proximity-induced self-labeling,” where the radius of labeling is zero. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Proximity Labeling: Methods and Protocols serves as an ideal guide for researchers exploring the crucial roles that proximity-driven reactions play in biological systems.

Designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond, this title includes chapters that address traditional and emerging quantitative methods of data analysis.

Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that's just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code! Use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software. This combination gives you insights you can't get from the code alone. Use these insights to prioritize refactoring needs, measure their effect, find implicit dependencies between different modules, and automatically create knowledge maps of your system based on actual code contributions. In a radical, much-needed change from common practice, guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover a comprehensive set of practical analysis techniques based on version-control data, where each point is illustrated with a case study from a real-world codebase. Because the techniques are language neutral, you can apply them to your own code no matter what programming language you use. Guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Apply research findings from social psychology to software development, ensuring you get the tools you need to coach your organization towards better code. If you're an experienced programmer, software architect, or technical manager, you'll get a new perspective that will change how you work with code. What You Need: You don't have to install anything to follow along in the book. TThe case studies in the book use well-known open source projects hosted on GitHub. You'll use CodeScene, a free software analysis tool for open source projects, for the case studies. We also discuss alternative tooling options where they exist.

This unique volume returns in its second edition, revised and updated with the latest advances in problem solving research. It is designed to provide readers with skills that will make them better problem solvers and to give up-to-date information about the psychology of problem solving. Professor Hayes provides students and professionals with practical, tested methods of defining, representing, and solving problems. Each discussion of the important aspects of human problem solving is supported by the most current research on the psychology problem solving. The Complete Problem Solver, Second Edition features: *Valuable learning strategies; *Decision making methods; *Discussions of the nature of creativity and invention, and *A new chapter on writing. The Complete Problem Solver utilizes numerous examples, diagrams, illustrations, and charts to help any reader become better at problem solving. See the order form for the answer to the problem below.

Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

This book constitutes the refereed proceedings of the 14th International Conference on Pattern Recognition and Information Processing, PRIP 2019, held in Minsk, Belarus, in May 2019. The 25 revised full papers were carefully reviewed and selected from 120 submissions. The papers of this volume are organized in topical sections on pattern recognition and image analysis; information processing and applications.

This book presents the achievements in bionanoelectronics in a coherent manner. It deals with nanodevices applied to biostructures, molecular motors, molecular pumps, molecular nanoactuators and electronic biodevices, including nanodevices for sensing and imaging biomolcules. The book describes bionanoelectronics, detection of biomolecules and targets various biological applications such as detection and sequencing of DNA and early detection of various deseases and nanomedicine. Further important topics of the book are biomimetics and bioinspired electronics.The book also deals with biomolecules as building blocks of nanodevices for nanoelectronics or future computing architecture The application of scanning probe techniques to biological samples is described.