Tabla de Contenidos: “…Intro -- Preface -- Organization -- Invited Talks -- How to Solve Math Problems Without Talent -- Bridging Formal Mathematics and Software Verification -- The Art of SMT Solving -- Contents - Part II -- Concurrency -- The VerCors Verifier: A Progress Report -- 1 Introduction -- 2 New and Improved Language Support -- 2.1 Improved Existing Language Support -- 2.2 Newly Supported Frameworks -- 2.3 Programming Languages Encoded into VerCors -- 3 VerCors Implementation Changes -- 4 Deriving Verified, Optimised Programs -- 5 Case Studies -- 5.1 Tunnel Control Software Components -- 5.2 Verification of Red-Black Trees and their Parallel Merge -- 5.3 GPU Case Studies -- 5.4 Student Projects -- 6 Conclusions, Related Work and Future Work -- References -- Parsimonious Optimal Dynamic Partial Order Reduction -- 1 Introduction -- 2 Main Concepts -- 3 Programs, Executions, and Equivalence -- 4 Design of the POP Algorithm -- 4.1 Parsimonious Race Reversals -- 4.2 The Parsimonious-OPtimal DPOR (POP) Algorithm -- 4.3 Parsimonious Sleep Set Characterization -- 5 Correctness and Space Complexity -- 6 Implementation and Evaluation -- 7 Related Work -- 8 Conclusion -- References -- Collective Contracts for Message-Passing Parallel Programs -- 1 Introduction -- 2 A Theory of Collective Contracts -- 2.1 Language -- 2.2 Semantics -- 2.3 Collective Correctness -- 2.4 Simulation -- 3 Collective Contracts for C/MPI -- 3.1 Background from MPI -- 3.2 Contract Structure -- 4 Evaluation -- 4.1 Collective Contract Examples -- 4.2 Bounded Verification of Collective Contracts -- 5 Related Work -- 6 Discussion -- References -- Distributed Systems -- mypyvy: A Research Platform for Verification of Transition Systems in First-Order Logic -- 1 Introduction -- 2 Modeling Language -- 2.1 Benchmarks -- 3 Satisfiability-Based Queries -- 3.1 Queries -- 3.2 Counterexamples…”

Tabla de Contenidos: “…Intro -- Preface -- Organization -- Invited Talks -- How to Solve Math Problems Without Talent -- Bridging Formal Mathematics and Software Verification -- The Art of SMT Solving -- Contents - Part III -- Synthesis and Repair -- Syntax-Guided Automated Program Repair for Hyperproperties -- 1 Introduction -- 2 Preliminaries -- 3 Program Repair by Symbolic Execution -- 3.1 Symbolic Execution -- 3.2 Symbolic Paths and Safety Automata -- 3.3 Encoding for HyperLTL -- 3.4 Program Repair Using SyGuS -- 4 Transparent Repair -- 4.1 Transparency -- 4.2 Encoding for Transparent Repair -- 5 Iterative Repair -- 5.1 Encoding for Iterative Repair -- 5.2 Iterative Repair Loop -- 6 Implementation and Evaluation -- 6.1 Iterative Repair for Hyperproperties -- 6.2 Scalability in Solution Size -- 6.3 Evaluation on k-Safety Instances -- 6.4 Evaluation on Functional Properties -- 7 Related Work -- 8 Conclusion -- References -- The SemGuS Toolkit -- 1 Introduction -- 2 The SemGuS Format 1.0 -- 3 A Baseline SemGuS Solver -- 3.1 Verifying Candidate Solutions -- 3.2 Baseline Enumerative Solvers -- 3.3 Extensibility -- 4 Benchmarks and Performance of Baseline Solvers -- 5 Related Work -- References -- Relational Synthesis of Recursive Programs via Constraint Annotated Tree Automata -- 1 Introduction -- 2 Motivating Example -- 3 Preliminaries -- 4 Constraint Annotated Tree Automata -- 4.1 CATA Operations for Synthesis -- 5 Synthesis Algorithm -- 5.1 Problem Statement -- 5.2 Basic Synthesis Algorithm -- 5.3 Lazy Synthesis Algorithm -- 6 Implementation -- 7 Evaluation -- 8 Related Work -- 9 Conclusion -- References -- Information Flow Guided Synthesis with Unbounded Communication -- 1 Introduction -- 2 Running Example: Sequence Transmission -- 3 Preliminaries -- 4 Prefix Information Flow -- 5 Unbounded Communication in Distributed Systems -- 5.1 Receiving Information…”

Tabla de Contenidos: “…-- Healthcare analytics improves medical care -- Better outcomes -- Lower costs -- Ensure quality -- Foundations of healthcare analytics -- Healthcare -- Mathematics -- Computer science -- History of healthcare analytics -- Examples of healthcare analytics -- Using visualizations to elucidate patient care -- Predicting future diagnostic and treatment events -- Measuring provider quality and performance -- Patient-facing treatments for disease -- Exploring the software -- Anaconda -- Anaconda navigator -- Jupyter notebook -- Spyder IDE -- SQLite -- Command-line tools -- Installing a text editor -- Summary -- References -- Chapter 2: Healthcare Foundations -- Healthcare delivery in the US -- Healthcare industry basics -- Healthcare financing -- Fee-for-service reimbursement -- Value-based care -- Healthcare policy -- Protecting patient privacy and patient rights -- Advancing the adoption of electronic medical records -- Promoting value-based care -- Advancing analytics in healthcare -- Patient data - the journey from patient to computer -- The history and physical (H&amp -- P) -- Metadata and chief complaint -- History of the present illness (HPI) -- Past medical history -- Medications -- Family history -- Social history -- Allergies -- Review of systems -- Physical examination -- Additional objective data (lab tests, imaging, and other diagnostic tests) -- Assessment and plan -- The progress (SOAP) clinical note -- Standardized clinical codesets -- International Classification of Disease (ICD)…”

“…This book dispels that idea by building up your shader knowledge in stages, starting with fundamental shader mathematics and how shader development mindset differs from other types of art and programming, and slowly delves into topics such as vertex and fragment shaders, lighting, depth-based effects, texture mapping, and Shader Graph. …”

Tabla de Contenidos: “…Preparing the Stable Diffusion components -- Loading the training data -- Defining the training components -- Training a Stable Diffusion V1.5 LoRA -- Kicking off the training -- Verifying the result -- Summary -- References -- Chapter 22: Exploring Beyond Stable Diffusion -- What sets this AI wave apart -- The enduring value of mathematics and programming -- Staying current with AI innovations -- Cultivating responsible, ethical, private, and secure AI -- Our evolving relationship with AI -- Summary -- References -- Index -- Other Books You May Enjoy…”

Tabla de Contenidos: “…DE MATEMÁTICA APLICADA DE LA UNIVERSIDAD DE GRANADA -- CAPÍTULO 38 ABP EN EL AULA UNIVERSITARIA: UN CONGRESO CIENTÍFICO DE ECUACIONES DIFERENCIALES EN 2o CURSO DE INGENIERÍA AEROESPACIAL -- CAPÍTULO 39 HASKELL EN LA DOCENCIA DE LA MATEMÁTICA DISCRETA -- CAPÍTULO 40 FREE SOFTWARE AS A TOOL IN MATHEMATICAL LABORATORIES: GEOGEBRA, R, MAXIMA, SAGEMATH AND PYTHON REVISITED -- CAPÍTULO 41 EXPERIENCIAS BASADAS EN MICROAPRENDIZAJES EN HIDRÁULICA A TRAVÉS DE ACTIVIDADES Y EJERCICIOS REALES EN EL LABORATORIO -- CAPÍTULO 42 APRENDIZAJE COLABORATIVO EN EL DISEÑO DE INSTALACIONES ELÉCTRICAS Y DE ILUMINACIÓN -- CAPÍTULO 43 PROPUESTA DE APRENDIZAJE BASADO EN INVESTIGACIÓN: EXPERIENCIA TRANSVERSAL EN EL ÁREA DE GEOMÁTICA -- CAPÍTULO 44 JUPYTER NOTEBOOK PARA EL ACCESO DE DATOS DE COPERNICUS -- CAPÍTULO 45 EVALUACIÓN DE LA APLICACIÓN DE LA CLASE AL REVÉS A LA PRÁCTICA "HEXÁPODOS, INSECTOS" DE LA ASIGNATURA ZOOLOGÍA EN EL GRADO EN BIOLOGÍA -- Back Matter…”

Tabla de Contenidos: “…Summarizing -- Adding AJAX calls -- An even bigger solution -- Summary -- Chapter 3: Asynchronous Programming -- The callback pattern -- The callback pattern on the web -- The callback pattern in Node.js -- Problems with structuring async code - callback hell -- Promises -- Thenables -- Handling rejected promises -- Chaining - dealing with several promises -- Asynchronous libraries -- Async library -- async.map() -- async.parallel() -- async.series() -- Async/await -- Summary -- Chapter 4: Functional Reactive Programming -- Functional programming versus imperative programming -- Imperative programming versus declarative programming -- First-class higher-order functions -- Pure functions -- Recursion -- No more loops -- Reoccurring pattern -- Summarise -- Count -- Width -- Asynchronous data streams -- Comparing lists to async streams - preparing for RxJS -- Combining the functional programming paradigm with streams -- Projection -- Filtering -- Combining mindsets -- Summary -- Chapter 5: RxJS Basics -- Observer pattern -- RxJS core concepts -- Observable and Observer -- Producer -- Observable error and completion -- Operator -- Creating Observables -- Creation operators -- of() -- interval() -- from() -- fromEvent() -- bindCallback() -- Cleanup -- Subscriptions -- Creating a core implementation of RxJS -- Implementing create() -- Handling subscriptions -- Adding operators -- Revisiting the basics, adding errors, and complete -- Summary -- Chapter 6: Manipulating Streams and Their Values -- Starting out -- Understanding operators -- Stream in a stream -- AJAX -- fetch() -- ajax() operator -- Cascading calls -- A deeper look -- Creation operators -- of() operator -- from() operator -- range() operator -- fromEvent() operator -- Combination -- merge() operator -- combineLatest() -- zip() -- concat() -- Mathematical -- max -- min -- sum -- Time…”

Tabla de Contenidos: “…6.2.4.1 - Cyclic Voltammetry -- 6.2.4.2 - Differential Pulse Voltammetry -- 6.2.4.3 - Square Wave Voltammetry -- 6.2.5 - Electrochemical Impedance Spectroscopy -- 6.2.6 - Electronic Tongue: Concepts, Principles, and Applications -- List of Symbols -- References -- 7 - Molecular Modeling Applied to Nanobiosystems -- 7.1 - Introduction -- 7.1.1 - Molecular Modeling -- 7.1.2 - Computer-Assisted Molecular Modeling -- 7.2 - Basic Representation Types -- 7.3 - Biomolecules and Protein Modeling -- 7.3.1 - Biomolecules -- 7.3.2 - Proteins -- 7.3.3 - Protein Structure -- 7.3.4 - Types of Protein and Biomolecule Representations -- 7.3.5 - Biological Structure Databases -- 7.3.6 - Protein Structure Visualization, Manipulation, and Analysis Tools -- 7.4 - Molecular Computer Modeling Methods Applied To Biomolecules -- 7.4.1 - Classical Methods -- 7.4.1.1 - Molecular Dynamics -- 7.4.1.1.1 - Molecular dynamics and related potentials -- 7.4.1.1.2 - Molecular dynamics simulation methods -- 7.4.1.2 - Molecular Docking -- 7.4.1.2.1 - Receptor-ligand molecular docking -- 7.4.1.2.2 - Genetic algorithms -- 7.4.2 - Hybrid Methods (Quantum Mechanics/Molecular Mechanics) -- 7.4.2.1 - Introduction to Hybrid Methods -- 7.4.2.2 - Simulation of Biomolecular Systems -- 7.4.2.3 - Programs for Using the QM/MM Methodology -- 7.4.2.4 - Theoretical Foundations and Mathematical Description -- 7.4.2.5 - Electrostatic Interactions -- 7.4.2.6 - Applications of QM/MM in Molecular Systems -- 7.4.3 - Structural Characterization -- 7.4.3.1 - X-Ray Diffraction -- 7.4.3.2 - Nuclear Magnetic Resonance -- 7.4.3.3 - Protein Modeling by Homology -- 7.5 - Some Recent Applications -- 7.5.1 - Applications in the Pharmaceutical Industry -- 7.5.1.1 - Pharmaceutical Development -- 7.5.1.2 - Rational Pharmaceutical Design -- 7.5.2 - Technological Applications…”

Tabla de Contenidos: “…. =) -- 2.3 Specifying the data type -- 2.4 Telling R to ignore something -- 2.5 Try it yourself -- Terminology -- Summary -- Chapter 3: Making new data values -- 3.1 Basic mathematics -- 3.2 Operator precedence -- 3.3 String concatenation (joining) -- 3.4 Comparisons -- 3.5 Automatic conversion (coercion) -- 3.6 Try it yourself -- Terminology -- Summary -- Chapter 4: Understanding the tools you'll use: Functions -- 4.1 Functions -- 4.1.1 Under the hood -- 4.1.2 Function template -- 4.1.3 Arguments -- 4.1.4 Multiple arguments -- 4.1.5 Default arguments -- 4.1.6 Argument name matching -- 4.1.7 Partial matching -- 4.1.8 Scope…”

Tabla de Contenidos: “…Front Cover -- Bio-Inspired Strategies for Modeling and Detection in Diabetes Mellitus Treatment -- Copyright -- Dedication -- Contents -- List of figures -- List of tables -- Biographies -- Preface -- 1 Introduction -- 1.1 Diabetes Mellitus from a medical point of view -- 1.2 Current diagnosis of Diabetes Mellitus and glucose intolerance -- 1.2.1 Oral glucose tolerance test -- 1.3 Current treatment of Diabetes Mellitus -- 1.4 Prediction of Diabetes Mellitus and its complications -- 1.5 Intelligent strategies inspired in biology and their applications in engineering and medicine -- 1.5.1 Main branches of Computational Intelligence -- 1.5.1.1 Evolutionary computation -- 1.5.1.2 Swarm intelligence -- 1.5.1.3 Neural network -- 1.5.1.4 Fuzzy logic -- 1.5.1.5 Artificial immune system -- 1.5.1.6 Medical applications using bio-inspired strategies -- References -- 2 Problem statement -- 2.1 State-of-the-art in modeling, identification, and detection of diabetes mellitus using bio-inspired strategies -- 2.1.1 Parametric estimation -- 2.1.2 Neural identification -- 2.1.3 Prediction -- 2.1.4 Detection -- 2.2 Compartmental models Sorensen and Dalla Man -- 2.2.1 Sorensen model -- 2.2.2 Glucose subsystem -- 2.2.3 Insulin subsystem -- 2.2.4 Metabolic rates and dynamics of glucagon -- 2.2.5 Dalla Man model -- 2.3 Serial data -- 2.3.1 Continuous glucose monitoring system data -- 2.3.2 Tolerance tests to oral intake data -- References -- 3 Mathematical preliminaries -- 3.1 Evolutionary algorithms -- 3.1.1 Evonorm -- 3.1.2 Differential evolution -- 3.2 Particle swarm-based algorithms -- 3.2.1 Particle swarm optimization -- 3.2.2 Ant colony optimization -- 3.3 Neural networks -- 3.3.1 Multilayer perceptron neural network -- 3.3.2 Discrete-time high order neural networks -- 3.3.2.1 RHONN training algorithm -- 3.4 Deep neural networks…”

Tabla de Contenidos: “…2.3.5 Creating 3D models/sketches using VR -- 2.3.6 Continuous development and optimisation -- 2.4 Conclusions -- Acknowledgements -- Bibliography -- Chapter 3: Innovations in healthcare product development: Exploring AR/VR/MR technologies -- 3.1 Introduction -- 3.2 Medical and healthcare education -- 3.2.1 Human anatomy using AR -- 3.2.2 Human anatomy using MR -- 3.2.3 Human anatomy using VR -- 3.3 Diagnostics -- 3.4 Surgery -- 3.4.1 Examining complex dynamics using AR -- 3.4.2 VR in surgery -- 3.4.3 Broadcasting and recording VR surgery -- 3.5 Dentistry -- 3.6 AR-based technologies to improve physical rehabilitation -- 3.7 Discussion (Challenges and future of AR in healthcare) -- References -- Part 2: Enhancing manufacturing with virtual, augmented, and mixed reality -- Chapter 4: Transforming manufacturing with digital twins and metrology in VR -- 4.1 Introduction -- 4.1.1 Background and driving forces -- 4.2 Ontological modeling of geometry -- 4.2.1 Geometrical features and parameters -- 4.2.2 EO and CAD geometry -- 4.3 Measuring path modeling -- 4.3.1 Mathematical modeling of initial measuring path -- 4.3.2 Collision avoidance principle -- 4.3.3 PW setup and probe configuration -- 4.3.4 Initial measuring path -- 4.3.5 Optimal measuring path -- 4.4 Simulation models -- 4.4.1 PTC Creo -- 4.4.2 PC-DMIS -- 4.5 Digital measuring twin -- 4.6 Conclusions -- Acknowledgements -- References -- Chapter 5: Enhancing human-robot collaboration: Augmented reality interfaces for smarter path planning -- 5.1 Introduction -- 5.2 Research method -- 5.2.1 Human-robot interaction -- 5.2.2 Path planning -- 5.2.3 Augmented reality for human-robot collaboration -- 5.3 Implementations and results -- 5.3.1 Augmented reality interfaces for path planning -- 5.3.2 System architecture -- 5.3.3 Interfaces for handheld devices -- 5.3.4 Interfaces for head-mounted devices…”

Tabla de Contenidos: “…Fraud detection model with differential privacy using the Opacus framework -- Differential privacy machine learning frameworks -- Limitations of differential privacy and strategies to overcome them -- Summary -- Part 3: Hands-On Federated Learning -- Chapter 6: Federated Learning and Implementing FL Using Open Source Frameworks -- Federated learning -- Preserving privacy -- FL definition -- Characteristics of FL -- FL algorithms -- FedSGD -- FedAvg -- Fed Adaptative Optimization -- The steps involved in implementing FL -- Open source frameworks to implement FL -- TensorFlow Federated -- Flower -- An end-to-end use case of implementing fraud detection using FL -- Developing an FL model for fraud detection using the Flower framework -- FL with differential privacy -- Approach one -- Approach two -- A sample application using FL-DP -- Summary -- Chapter 7: Federated Learning Benchmarks, Start-Ups, and the Next Opportunity -- FL benchmarks -- The importance of FL benchmarks -- FL datasets -- Frameworks for FL benchmarks -- Selecting an FL framework for a project -- A comparison of FedScale, FATE, Flower, and TensorFlow Federated -- State-of-the-art research in FL -- Communication-efficient FL -- Privacy-preserving FL -- Federated Meta-Learning -- Adaptive FL -- Federated reinforcement learning -- Key company products related to FL -- Summary -- Part 4: Homomorphic Encryption, SMC, Confidential Computing, and LLMs -- Chapter 8: Homomorphic Encryption and Secure Multiparty Computation -- Encryption, anonymization, and de-identification -- Data anonymization -- De-identification -- Exploring Homomorphic encryption -- Ring-based -- Lattice-based -- Elliptic curve-based -- Exploring the mathematics behind HE -- Encryption -- Homomorphism -- Types of HE -- Fully Homomorphic Encryption (FHE) -- Somewhat Homomorphic Encryption (SHE)…”

“…The Second Edition continues the tradition of the first in avoiding complicated algebra and complex numbers, with the mathematics reduced to the bare minimum; there is nothing more complicated to grapple with than a square root. …”

Tabla de Contenidos: “…Exercise 3.4 - Practice exception handling -- Exercise 3.5 - Explore topics -- Summary -- Chapter 4: Writing, Debugging, and Testing Functions -- Writing functions -- Writing a times table function -- Writing a function that returns a value -- Writing mathematical functions -- Formatting numbers for output -- Calculating factorials with recursion -- Debugging an application during development -- Creating an application with a deliberate bug -- Setting a breakpoint -- The debugging toolbar -- Debugging windows -- Stepping through code -- Customizing breakpoints -- Logging during development and runtime -- Instrumenting with Debug and Trace -- Writing to the default trace listener -- Configuring trace listeners -- Switching trace levels -- Unit testing functions -- Creating a class library that needs testing with Visual Studio 2017 -- Creating a unit test project with Visual Studio 2017 -- Creating a class library that needs testing with Visual Studio Code -- Writing unit tests -- Running unit tests with Visual Studio 2017 -- Running unit tests with Visual Studio Code -- Practicing and exploring -- Exercise 4.1 - Test your knowledge -- Exercise 4.2 - Practice writing functions with debugging and unit testing -- Exercise 4.3 - Explore topics -- Summary -- Chapter 5: Building Your Own Types with Object-Oriented Programming -- Talking about OOP -- Building class libraries -- Creating a class library with Visual Studio 2017 -- Creating a class library with Visual Studio Code -- Defining a class -- Instantiating a class -- Referencing an assembly using Visual Studio 2017 -- Referencing an assembly using Visual Studio Code -- Importing a namespace -- Managing multiple projects with Visual Studio Code -- Inheriting from System.Object -- Storing data with fields -- Defining fields -- Understanding access modifiers -- Storing a value using the enum keyword…”

“…No matter how you elect todivide the material, Fundamentals of Futures and OptionsMarkets offers a wide audience a sound and easy-to-graspintroduction into financial mathematics…”

Tabla de Contenidos: “…GENERALIZED EXTREME VALUE DISTRIBUTION -- GENERALIZED PARETO DISTRIBUTION -- NORMAL INVERSE GAUSSIAN DISTRIBUTION -- Normal Distribution versus Normal Inverse Gaussian Distribution -- α-STABLE DISTRIBUTION -- KEY POINTS -- REFERENCES -- Stable and Tempered Stable Distributions -- α-STABLE DISTRIBUTION -- Definition of an α-Stable Random Variable -- Useful Properties of an α-Stable Random Variable -- Smoothly Truncated Stable Distribution -- TEMPERED STABLE DISTRIBUTIONS -- Classical Tempered Stable Distribution -- Generalized Classical Tempered Stable Distribution -- Modified Tempered Stable Distribution -- Normal Tempered Stable Distribution -- Kim-Rachev Tempered Stable Distribution -- Rapidly Decreasing Tempered Stable Distribution -- INFINITELY DIVISIBLE DISTRIBUTIONS -- Exponential Moments -- HYPERGEOMETRIC FUNCTION AND CONFLUENT HYPERGEOMETRIC FUNCTION -- The Hypergeometric Function -- The Confluent Hypergeometric Function -- KEY POINTS -- NOTES -- REFERENCES -- Fat Tails, Scaling, and Stable Laws -- SCALING, STABLE LAWS, AND FAT TAILS -- Fat Tails -- The Class L of Fat-Tailed Distributions -- The Law of Large Numbers and the Central Limit Theorem -- Stable Distributions -- EXTREME VALUE THEORY FOR IID PROCESSES -- Maxima -- Max-Stable Distributions -- Generalized Extreme Value Distributions -- Order Statistics -- Point Process of Exceedances or Peaks over Threshold -- Estimation -- ELIMINATING THE ASSUMPTION OF IID SEQUENCES -- Heavy-Tailed ARMA Processes -- ARCH/GARCH Processes -- Subordinated Processes -- Markov Switching Models -- Estimation -- Scaling and Self-Similarity -- KEY POINTS -- NOTES -- REFERENCES -- Copulas -- DRAWBACKS OF CORRELATION -- OVERCOMING THE DRAWBACKS OF CORRELATION: COPULAS -- MATHEMATICAL DEFINITION OF COPULAS -- KEY POINTS -- NOTES -- REFERENCES -- Applications of Order Statistics to Risk Management Problems…”

Tabla de Contenidos: “…-- Hot versus Cold Observables -- Hot Observables -- Hot Observables and the replay mechanism -- Observers and their variants (Subscribers) -- Subjects -- Schedulers -- ObserveOn versus SubscribeOn -- The RunLoop Scheduler -- Operators -- Creational Operators -- Transformation Operators -- Filtering Operators -- Combining Operators -- Error-handling Operators -- Observable utility Operators -- Conditional and Boolean Operators -- Mathematical and Aggregate operators -- Connectable Observable Operators -- Summary -- Chapter 9: Reactive GUI Programming Using Qt/C++ -- A quick introduction to Qt GUI programming -- Qt object model -- Signals and slots -- Event system -- Event handlers -- Sending events -- Meta-object system -- Hello World - Qt program -- Qt event model with signals/slots/MOC - an example -- Creating a custom widget -- Creating the application dialog -- Executing the application -- Integrating the RxCpp library with the Qt event model -- Qt event filter - a reactive approach -- Creating the window - setting layouts and alignments…”

Tabla de Contenidos: “…Handling Common Data Formats -- Text -- Special Syntax for Strings -- String Immutability -- Regular Expressions -- Numbers and Math -- How Java Represents Integer Types -- Java and Floating-Point Numbers -- Java's Standard Library of Mathematical Functions -- Java 8 Date and Time -- Introducing the Java 8 Date and Time API -- Queries -- Adjusters -- Legacy Date and Time -- Summary -- Chapter 10. …”

Tabla de Contenidos: “…Missing It -- Wag the Dog -- The Ethnographic Examples -- Muddying the Waters: The Case of Cassandra -- Missing It: The Case of SSgt Michaels -- Wag the Dog: The Case of Fedor the Troll -- Conclusion -- References -- Chapter 10 Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context -- Introduction -- The Brain‐as‐Predictor Approach -- Predicting Individual Behaviors -- Interpreting Associations Between Brain Activation and Behavior -- Predicting Aggregate Out‐of‐Sample Group Outcomes -- Predicting Social Interactions and Peer Influence -- Sociocultural Context -- Future Directions -- Conclusion -- References -- Chapter 11 Social Models from Non-Human Systems -- Emergent Patterns in Groups of Behaviorally Flexible Individuals -- From Bird Motivations to Human Applications -- Game‐Theoretic Model of Frequency‐Dependent Tactic Choice -- Mathematical Model as Behavioral Microscope on Carefully Prepared Birds -- Transferable Insights from Behavioral Games to Human Groups -- Model Systems for Understanding Group Competition -- Social Spiders as Model Systems for Understanding Personality in Groups -- Ants as Model Systems for Understanding the Costs and Benefits of Specialization -- Personality and Specialization: From Nonhuman to Human Groups -- Information Dynamics in Tightly Integrated Groups -- Linear and Nonlinear Recruitment Dynamics -- Herd Behavior and Information Cascades in Ants -- From Ants to Human Decision Support Systems -- Additional Examples: Rationality and Memory -- Conclusions -- Acknowledgments -- References -- Chapter 12 Moving Social‐Behavioral Modeling Forward: Insights from Social Scientists -- Why Do People Do What They Do? …”