Work with Db2 to write SQL and access databases using optimized code for the fastest response. This book will give you complete documentation on DB2 via Python for the IBM_db module and provide a number of examples for the usage of each module API. Begin by getting your free version of Db2 for Linux and Windows. While the book concentrates more on the Linux version of Db2, it also covers enough of the Windows version so that you're comfortable with obtaining and installing Db2 on your version of Windows. Next, you'll see how to install the sample database that comes with Db2, and take some data from the web to design a database around it, including tables and indexes. For Db2 to be really useful you need to use strong SQL expressions. This book provides specific examples of how to avoid using poor ones that can cause extra processing time for the query. Lastly, you'll look at each API in the ibm_db and ibm_db_dbi module. This module is not sponsored by IBM and must be installed separately from the Db2 database. After reading Foundation Db2 and Python you'll be able to install Db2 on Windows or Linux, and perform backups and restore data. What You'll Learn Obtain and install Db2 properly on Linux and Windows Create databases and load them on Db2 Work with ibm_db and ibm_db_dbi API modules for Python Write SQL for Db2 Review the future of the ibm_db Python module Who This Book Is For Python programmers and DB2 administrators interested in building application with Python and DB2

Developing a large-scale software system in C++ requires more than just a sound understanding of the logical design issues covered in most books on C++ programming. To be successful, you will also need a grasp of physical design concepts that, while closely tied to the technical aspects of development, include a dimension with which even expert software developers may have little or no experience.

This is the definitive book for all C++ software professionals involved in large development efforts such as databases, operating systems, compilers, and frameworks. It is the first C++ book that actually demonstrates how to design large systems, and one of the few books on object-oriented design specifically geared to practical aspects of the C++ programming language.

In this book, Lakos explains the process of decomposing large systems into physical (not inheritance) hierarchies of smaller, more manageable components. Such systems with their acyclic physical dependencies are fundamentally easier and more economical to maintain, test, and reuse than tightly interdependent systems. In addition to explaining the motivation for following good physical as well as logical design practices, Lakos provides you with a catalog of specific techniques designed to eliminate cyclic, compile-time, and link-time (physical) dependencies. He then extends these concepts from large to very large systems. The book concludes with a comprehensive top-down approach to the logical design of individual components. Appendices include a valuable design pattern "Protocol Hierarchy" designed to avoid fat interfaces while minimizing physical dependencies; the details of implementing an ANSI C compatible C++procedural interface; and a complete specification for a suite of UNIX-like tools to extract and analyze physical dependencies. Practical design rules, guidelines, and principles are also collected in an appendix and indexed for quick reference.
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Do you have creative ideas that you wish you could transform into code? Do you want to boost your problem solving and logic skills? Do you want to enhance your career by adopting an algorithmic mindset? In our increasingly digital world, coding is an essential skill. Communicating an algorithm to a machine to perform a set of tasks is vital. Beginner's Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems written by Deepankar Maitra teaches you how to think like a programmer. The author unravels the secret behind writing code - building a good algorithm. Algorithmic thinking leads to asking the right question and enables a shift from issue resolution to value creation. Having this mindset will make you more marketable to employers. This book takes you on a problem-solving journey to expand your mind and increase your willingness to experiment with code. You will: Learn the art of building an algorithm through hands-on exercises Understand how to develop code for inspiring productivity concepts Build a mentality of developing algorithms to solve problems Develop, test, review, and improve code through guided experimentation This book is designed to develop a culture of logical thinking through intellectual stimulation. It will benefit students and teachers of programming, business professionals, as well as experienced users of Microsoft Excel who wish to become proficient with macros.

Understand how to apply auto machine learning to data streams and create transactional machine learning (TML) solutions that are frictionless (require minimal to no human intervention) and elastic (machine learning solutions that can scale up or down by controlling the number of data streams, algorithms, and users of the insights). This book will strengthen your knowledge of the inner workings of TML solutions using data streams with auto machine learning integrated with Apache Kafka. Transactional Machine Learning with Data Streams and AutoML introduces the industry challenges with applying machine learning to data streams. You will learn the framework that will help you in choosing business problems that are best suited for TML. You will also see how to measure the business value of TML solutions. You will then learn the technical components of TML solutions, including the reference and technical architecture of a TML solution. This book also presents a TML solution template that will make it easy for you to quickly start building your own TML solutions. Specifically, you are given access to a TML Python library and integration technologies for download. You will also learn how TML will evolve in the future, and the growing need by organizations for deeper insights from data streams. By the end of the book, you will have a solid understanding of TML. You will know how to build TML solutions with all the necessary details, and all the resources at your fingertips. What You Will Learn Discover transactional machine learning Measure the business value of TML Choose TML use cases Design technical architecture of TML solutions with Apache Kafka Work with the technologies used to build TML solutions Build transactional machine learning solutions with hands-on code together with Apache Kafka in the cloud Who This Book Is For Data scientists, machine learning engineers and architects, and AI and machine learning business leaders.

For use as a core text supplement in any course covering common LISP such as Artificial Intelligence or Concepts of Programming Languages.

Teaching students new and more powerful ways of thinking about programs, this text contains a tutorial—full of examples—that explains all the essential concepts of Lisp programming, plus an up- to-date summary of ANSI Common Lisp, listing every operator in the language. Informative and fun, it gives students everything they need to start writing programs in Lisp both efficiently and effectively, and highlights such innovative Lisp features as automatic memory management, manifest typing, closures, and more.

Make the most of R's extensive toolset R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R's graphics, interactive, and machine learning tools, you'll learn to apply R's extensive capabilities in an array of scenarios. The depth of the project experience is unmatched by any other content online or in print. And you just might increase your statistics knowledge along the way, too! R is a free tool, and it's the basis of a huge amount of work in data science. It's taking the place of costly statistical software that sometimes takes a long time to learn. One reason is that you can use just a few R commands to create sophisticated analyses. Another is that easy-to-learn R graphics enable you make the results of those analyses available to a wide audience. This book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more. Appropriate for R users at all levels Helps R programmers plan and complete their own projects Focuses on R functions and packages Shows how to carry out complex analyses by just entering a few commands If you're brand new to R or just want to brush up on your skills, R Projects For Dummies will help you complete your projects with ease.

The C programming language is a popular language in industries as well as academics. Since its invention and standardized as ANSI C, several other standards known as C99, C11, and C17 were published with new features in subsequent years. This book covers all the traits of ANSI C and includes new features present in other standards. The content of this book helps a beginner to learn the fundamental concept of the C language. The book contains a step-by-step explanation of every program that allows a learner to understand the syntax and builds a foundation to write similar programs. The explanation clarity, exercises, and illustrations present in this book make it a complete textbook in all aspects. Features: Other than ANSI C, the book explains the new C standards like C99, C11, and C17. Most basic and easy-to-follow programs are chosen to explain the concepts and their syntax. More emphasis is given to the topics like Functions, Pointers, and Structures. Recursion is emphasized with numerous programming examples and diagrams. A separate chapter on the command-line argument and preprocessors is included that concisely explains their usage. Several real-life figures are taken to explain the concepts of dynamic memory allocation, file handling, and the difference between structure and union. The book contains more than 260 illustrations, more than 200 programs, and exercises at the end of each chapter. This book serves as a textbook for UG/PG courses in science and engineering. The researcher, postgraduate engineers, and embedded software developers can also keep this book as reference material for their fundamental learning.

Start your video game development journey by learning how to build a 2D game engine from scratch. Using Java (with NetBeans as your IDE and using Java's graphics framework) or by following along in C# (with Visual Studio as your IDE and using the MonoGame framework), you'll cover the design and implementation of a 2D game engine in detail. Each class will be reviewed with demonstration code. You'll gain experience using the engine by building a game from the ground up. Introduction to Video Game Engine Development reviews the design and implementation of a 2D game engine in three parts. Part 1 covers the low-level API class by class. You'll see how to abstract lower-level functionality and design a set of classes that interact seamlessly with each other. You'll learn how to draw objects, play sounds, render text, and more. In Part 2, you'll review the mid-level API that is responsible for drawing the game, loading resources, and managing user input. Lastly, in Part 3, you'll build a game from the ground up following a step-by-step process using the 2D game engine you just reviewed. On completing this book, you'll have a solid foundation in video game engine design and implementation. You'll also get exposure to building games from scratch, creating the solid foundation you'll need to work with more advanced game engines, and industry tools, that require learning complex software, APIs, and IDEs. What You Will Learn Gain experience with lower-level game engine APIs and abstracting framework functionality Write application-level APIs: launching the game, loading resources, settings, processing input, and more Discover cross-platform APIs in the game engine projects written in both Java and C#/MonoGame Develop games with an SDK-based game engine and simplified tool chain focused on direct control of the game through code Master creating games by using the game engine to build a game from the ground up with only code and an IDE Who This Book Is For Those of you out there with some programming experience, moderate to advanced, who want to learn how to write video games using modern game engine designs.

Designed as a self-study guide, the book describes the real-world tradeoffs encountered in building a production-quality, platform-retargetable compiler. The authors examine the implementation of lcc, a production-quality, research-oriented retargetable compiler, designed at AT&T Bell Laboratories for the ANSI C programming language. The authors' innovative approach-a "literate program" that intermingles the text with the source code-uses a line-by-line explanation of the code to demonstrate how lcc is built.

This book systematically introduces readers to the finite element analysis software DIANA (DIsplacement ANAlyzer) and its applications in civil engineering. Developed by TNO Corporation in the 1970s, DIANA is frequently used in civil engineering and engineering mechanics. Unlike the software user's manual, which provides a comprehensive introduction and theoretical analysis, this book presents a simplified overview of the basic background theory to help beginners master the software quickly. It also discusses GUI operation and the command console in Python language, and includes examples involving classical modeling operations to help readers review each section. Both the book and DIANA itself are valuable resources for students and researchers in all the structural engineering fields, such as civil engineering, bridge engineering, geotechnical engineering, tunnel engineering, underground structural engineering, irrigation, municipal engineering and fire engineering.

For courses in Visual Basic Programming. A Current and Comprehensive Introduction to Visual Basic Programming Schneider's Introduction to Programming Using Visual Basic has been consistently praised in the industry since 1991 and is a favorite of instructors and students. The 11th Edition is updated for Visual Basic 2017, providing an ideal tool for students learning their first programming language. The text keeps pace with modern programming methodology while incorporating current content and good programming practices. Schneider emphasizes problem solving by discussing problem-solving techniques early and using them throughout the book. He also ensures each chapter is rich yet concise by developing chapters around crucial subjects rather than covering too many topics superficially. The new edition provides a broad range of real-world examples, section-ending exercises, case studies, and programming projects that provide students with the most current and hands-on experience of any Visual Basic book on the market. The number and range of projects give instructors the flexibility to adapt the course according to the interests and abilities of students. Some programming projects in later chapters can be assigned as end-of-the-semester projects. Also available with MyLab Programming MyLab (TM) is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student.With MyLab Programming, students work through hundreds of short, auto-graded coding exercises and receive immediate and helpful feedback based on their work. Note: You are purchasing a standalone product; MyLab Programming does not come packaged with this content. Students, if interested in purchasing this title with MyLab Programming, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab Programming, search for: 0135862167 / 9780135862162 Introduction to Programming Using Visual Basic Plus MyLab Programming - Access Card Package, 11e Package consists of: 0135416116 / 9780135416112 MyLab Programming Standalone Access Card 0135416035 / 9780135416037 Introduction to Programming Using Visual Basic

This book investigates two major systems: firstly, co-operating distributed grammar systems, where the grammars work on one common sequential form and the co-operation is realized by the control of the sequence of active grammars; secondly, parallel communicating grammar systems, where each grammar works on its own sequential form and co-operation is done by means of communicating between grammars. The investigation concerns hierarchies with respect to different variants of co-operation, relations with classical formal language theory, syntactic parameters such as the number of components and their size, power of synchronization, and general notions generated from artificial intelligence.

Survival analysis uses statistics to calculate time to failure. Survival Analysis with Python takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis. As the subject itself is very mathematical and full of expressions and formulations, the book provides detailed explanations and examines practical implications. The book begins with an overview of the concepts underpinning statistical survival analysis. It then delves into Parametric models with coverage of Concept of maximum likelihood estimate (MLE) of a probability distribution parameter MLE of the survival function Common probability distributions and their analysis Analysis of exponential distribution as a survival function Analysis of Weibull distribution as a survival function Derivation of Gumbel distribution as a survival function from Weibull Non-parametric models including Kaplan-Meier (KM) estimator, a derivation of expression using MLE Fitting KM estimator with an example dataset, Python code and plotting curves Greenwood's formula and its derivation Models with covariates explaining The concept of time shift and the accelerated failure time (AFT) model Weibull-AFT model and derivation of parameters by MLE Proportional Hazard (PH) model Cox-PH model and Breslow's method Significance of covariates Selection of covariates The Python lifelines library is used for coding examples. By mapping theory to practical examples featuring datasets, this book is a hands-on tutorial as well as a handy reference.

There are three fundamental components in Control-Flow Integrity (CFI) enforcement. The first component is accurately recovering the policy (CFG). Usually, the more precise the policy is, the more security CFI improves, but precise CFG generation was considered hard without the support of source code. The second component is embedding the CFI policy securely. Current CFI enforcement usually inserts checks before indirect branches to consult a read-only table which stores the valid CFG information. However, this kind of read-only table can be overwritten by some kinds of attacks (e.g., the Rowhammer attack and data-oriented programming). The third component is to efficiently enforce the CFI policy. In current approaches CFI checks are always executed whenever there is an indirect control flow transfer. Therefore, it is critical to minimize the performance impact of CFI checks. In this book, we propose novel solutions to handle these three fundamental components. To generate a precise CFI policy without the support of the source code, we systematically study two methods which recover CFI policy based on function signature matching at the binary level and propose our novel rule- and heuristic-based mechanism to more accurately recover function signature. To embed CFI policy securely, we design a novel platform which encodes the policy into the machine instructions directly without relying on consulting any read-only data structure, by making use of the idea of instruction-set randomization. Each basic block is encrypted with a key derived from the CFG. To efficiently enforce CFI policy, we make use of a mature dynamic code optimization platform called DynamoRIO to enforce the policy so that we are only required to do the CFI check when needed.

Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models. Each chapter includes a set of examples allowing you to understand the concepts, assumptions, and procedures behind each model. The book covers parametric methods or linear models that combat under- or over-fitting using techniques such as Lasso and Ridge. It includes complex regression analysis with time series smoothing, decomposition, and forecasting. It takes a fresh look at non-parametric models for binary classification (logistic regression analysis) and ensemble methods such as decision trees, support vector machines, and naive Bayes. It covers the most popular non-parametric method for time-event data (the Kaplan-Meier estimator). It also covers ways of solving classification problems using artificial neural networks such as restricted Boltzmann machines, multi-layer perceptrons, and deep belief networks. The book discusses unsupervised learning clustering techniques such as the K-means method, agglomerative and Dbscan approaches, and dimension reduction techniques such as Feature Importance, Principal Component Analysis, and Linear Discriminant Analysis. And it introduces driverless artificial intelligence using H2O. After reading this book, you will be able to develop, test, validate, and optimize statistical machine learning and deep learning models, and engineer, visualize, and interpret sets of data. What You Will Learn Design, develop, train, and validate machine learning and deep learning models Find optimal hyper parameters for superior model performance Improve model performance using techniques such as dimension reduction and regularization Extract meaningful insights for decision making using data visualization Who This Book Is For Beginning and intermediate level data scientists and machine learning engineers

Java is now well-established as one of the world's major programming languages, used in everything from desktop applications to web-hosted applications, enterprise systems and mobile devices. Java applications cover cloud-based services, the Internet of Things, self-driving cars, animation, game development, big data analysis and many more domains. The second edition of Foundational Java: Key Elements and Practical Programming presents a detailed guide to the core features of Java - and some more recent innovations - enabling the reader to build their skills and confidence though tried-and-trusted stages, supported by exercises that reinforce the key learning points. All the most useful and commonly applied Java syntax and libraries are introduced, along with many example programs that can provide the basis for more substantial applications. Use of the Eclipse Integrated Development Environment (IDE) and the JUnit testing framework is integral to the book, ensuring maximum productivity and code quality when learning Java, although to ensure that skills are not confined to one environment the fundamentals of the Java compiler and run time are also explained. Additionally, coverage of the Ant tool will equip the reader with the skills to automatically build, test and deploy applications independent of an IDE. Topics and features: * Presents the most up-to-date information on Java, including Java 14 * Examines the key theme of unit testing, introducing the JUnit 5 testing framework to emphasize the importance of unit testing in modern software development * Describes the Eclipse IDE, the most popular open source Java IDE and explains how Java can be run from the command line * Includes coverage of the Ant build tool * Contains numerous code examples and exercises throughout * Provides downloadable source code, self-test questions, PowerPoint slides and other supplementary material at the website http://www.foundjava.com This hands-on, classroom-tested textbook/reference is ideal for undergraduate students on introductory and intermediate courses on programming with Java. Professional software developers will also find this an excellent self-study guide/refresher on the topic. Dr. David Parsons is National Postgraduate Director at The Mind Lab, Auckland, New Zealand. He has been teaching programming in both academia and industry since the 1980s and writing about it since the 1990s.

Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Deploying computer vision, audio, and natural language processing in the browser Fine-tuning machine learning models with client-side data Constructing and training a neural network Interactive AI for browser games using deep reinforcement learning Generative neural networks to generate music and pictures TensorFlow.js is an open-source JavaScript library for defining, training, and deploying deep learning models to the web browser. It's quickly gaining popularity with developers for its amazing set of benefits including scalability, responsiveness, modularity, and portability. Shanging Cai and Eric Nielsen are senior software engineers on the Google Brain team. Stan Bileschi is the technical lead for Google's TensorFlow Usability team, which built the TensorFlow Layers API. All three have advanced degrees from MIT. Together, they're responsible for writing most of TensorFlow.js.

This book brings together a number of researchers and developers from industry and academia who report on their work. It is of interest to language designers and the creators of toolkits, UIMSs, and other user interface tools.

Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will Learn Get up to date with the latest MATLAB up to and including MATLAB 2020b Code in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectiveness Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.

Discover the new and updated features of PHP 8, such as the JIT compiler, union types, and attributes, with code examples of each. For each feature, the author includes real-life cases for its use and explains its benefits. What You Will Learn Utilize the new features of PHP 8 and modern development technologies Work with the JIT compiler in PHP 8 Discover PHP 8 using real-life cases Increase your available resources to become more valuable in your development team Who This Book Is For Experienced PHP programmers new to PHP 8.

Understand the newest trend in database programming for developers working in Java, Kotlin, Clojure, and other JVM-based languages. This book introduces Reactive Relational Database Connectivity (R2DBC), a modern way of connecting to and querying relational databases from Java and other JVM languages. The book begins by helping you understand not only what reactive programming is, but why it is necessary. Then building on those fundamentals, the book takes you into the world of databases and the newly released Reactive Relational Database Connectivity (R2DBC) specification. Examples in the book are worked using the freely available MariaDB database along with MariaDB's vendor-implementation of the R2DBC service-provider interface (SPI). Following along with the examples and the provided example code helps prepare you to work with any of the growing number of R2DBC implementations for popular enterprise databases such as Oracle Database and SQL Server. You'll be well prepared for what is becoming the future of database access from Java and other languages built on the JVM. What You Will Learn Understand why R2DBC was created and how it utilizes the Reactive Streams API Understand the components of the R2DBC service-provider interface Create and manage reactive database connections and connection pools using an R2DBC client Programmatically execute queries on a relational database using an R2DBC client Effectively utilize transactions using an R2DBC client Build relational database-driven applications that are event-driven and non-blocking Who This Book Is For Software developers building solutions using JVM languages and the JVM ecosystem, and developers who need an introduction to the R2DBC specification and reactive programming with relational databases and want to understand what Reactive Relational Database Connectivity is and why it came about. This book includes practical examples of using the R2DBC specification with Java and MariaDB that will provide developers with the knowledge they need to create their own solutions.

Use this handy field guide as a quick reference book and cheat sheet for all of the techniques you use or reference day to day. Covering up to Android 11, this Android Java programming reference guide focuses on non-UI elements with a security focus. You won't see Android UI development, nor will you see low-level C or kernel techniques. Instead, this book focuses on easily digestible, useful, and interesting techniques in Java and the Android system. This reference guide was created out of the need for myself to jot down all the useful techniques I commonly reached for, and so I'm now sharing these techniques with you, whether you are an Android internals software engineer or security researcher. What You Will Learn Discover the differences between and how to access application names, package names, IDs, and unique identifiers in Android Quickly reference common techniques such as storage, the activity lifecycle, and permissions Debug using the Android shell Work with Android's obfuscation and encryption capabilities Extract and decompile Android applications Carry out Android reflection and dex class loading Who This Book Is For Programmers, developers, and admins with at least prior Android and Java experience.

Term rewriting systems, which developed out of mathematical logic, consist of sequences of discrete steps where one term is replaced with another. Their many applications range from automatic theorem proving systems to computer algebra. This book begins with several examples, followed by a chapter on basic notions that provides a foundation for the rest of the work. First-order and higher-order theories are presented, with much of the latter material appearing for the first time in book form. Subjects treated include orthogonality, termination, lambda calculus and term graph rewriting. There is also a chapter detailing the required mathematical background.

Gain a better understanding of pointers, from the basics of how pointers function at the machine level, to using them for a variety of common and advanced scenarios. This short contemporary guide book on pointers in C programming provides a resource for professionals and advanced students needing in-depth hands-on coverage of pointer basics and advanced features. It includes the latest versions of the C language, C20, C17, and C14. You'll see how pointers are used to provide vital C features, such as strings, arrays, higher-order functions and polymorphic data structures. Along the way, you'll cover how pointers can optimize a program to run faster or use less memory than it would otherwise. There are plenty of code examples in the book to emulate and adapt to meet your specific needs. What You Will Learn Work effectively with pointers in your C programming Learn how to effectively manage dynamic memory Program with strings and arrays Create recursive data structures Implement function pointers Who This Book Is For Intermediate to advanced level professional programmers, software developers, and advanced students or researchers. Prior experience with C programming is expected.

Edited in collaboration with FoLLI, the Association of Logic, Language and Information this book constitutes the refereed proceedings of the Second Interdisciplinary Workshop on Logic, Language, and Meaning, TLLM 2020, held in Tsinghua, China, in December 2020. The 12 full papers together presented were fully reviewed and selected from 40 submissions. Due to COVID-19 the workshop will be held online. The workshop covers a wide range of topics where monotonicity is discussed in the context of logic, causality, belief revision, quantification, polarity, syntax, comparatives, and various semantic phenomena in particular languages.