Aldosterone is a steroid hormone which is secreted from the zona glomerulosa of the adrenal gland. It has a mineralocorticoid activity and is the most important regulator of plasma potassium. When plasma potassium increases, increased stimulation of aldosterone occurs directly and also as a result of the Renin-Angiotensin-Aldosterone System (RAAS). Aldosterone is also the most important regulator of sodium excretion.

This course discusses how to use algebra for a variety of everyday tasks, such as calculate change without specifying how much money is to be spent on a purchase, analyzing relationships by graphing, and describing real-world situations in business, accounting, and science.

This course is oriented toward US high school students. Its structure and materials are aligned to the US Common Core Standards. Foci include: graphing, equations and inequalities.

This undergraduate level course follows Algebra I. Topics include group representations, rings, ideals, fields, polynomial rings, modules, factorization, integers in quadratic number fields, field extensions, and Galois theory.

Algebra and Trigonometry provides a comprehensive exploration of algebraic principles and meets scope and sequence requirements for a typical introductory algebra and trigonometry course. The modular approach and the richness of content ensures that the book meets the needs of a variety of courses. Algebra and Trigonometry offers a wealth of examples with detailed, conceptual explanations, building a strong foundation in the material before asking students to apply what they’ve learned.

Table of Contents
1 Prerequisites
2 Equations and Inequalities
3 Functions
4 Linear Functions
5 Polynomial and Rational Functions
6 Exponential and Logarithmic Functions
7 The Unit Circle: Sine and Cosine Functions
8 Periodic Functions
9 Trigonometric Identities and Equations
10 Further Applications of Trigonometry
11 Systems of Equations and Inequalities
12 Analytic Geometry
13 Sequences, Probability, and Counting Theory

Access also available here: https://openstax.org/details/books/algebra-and-trigonometry

Algebra and Trigonometry provides a comprehensive exploration of algebraic principles and meets scope and sequence requirements for a typical introductory algebra and trigonometry course. The modular approach and the richness of content ensures that the book meets the needs of a variety of courses. Algebra and Trigonometry offers a wealth of examples with detailed, conceptual explanations, building a strong foundation in the material before asking students to apply what they’ve learned.

" This is an introductory course in algebraic combinatorics. No prior knowledge of combinatorics is expected, but assumes a familiarity with linear algebra and finite groups. Topics were chosen to show the beauty and power of techniques in algebraic combinatorics. Rigorous mathematical proofs are expected."

" This course provides an introduction to the language of schemes, properties of morphisms, and sheaf cohomology. Together with 18.725 Algebraic Geometry, students gain an understanding of the basic notions and techniques of modern algebraic geometry."

In this second term of Algebraic Topology, the topics covered include fibrations, homotopy groups, the Hurewicz theorem, vector bundles, characteristic classes, cobordism, and possible further topics at the discretion of the instructor.

There are both practical and theoretical reasons to study algorithms. From a practical standpoint, you have to know a standard set of important algorithms from different areas of computing; in addition, you should be able to design new algorithms and analyze their efficiency. From the theoretical standpoint, the study of algorithms, sometimes called algorithmics, has come to be as the cornerstone of computer science.

This course aim to provide an in-depth understanding of the fundamental algorithmic techniques for design and analysis, in turn impart knowledge and practical competence in use of advanced data structures and the design and Welcome to Advanced computer Security Module. This module provides a study of high-level computer security issues in computer networks and advanced methods of data encryption. It focuses on advanced aspects of computer security, such as encryption, security practices, system security, security for authentication on the Web and password management techniques. Finally this module, students should be able to create secure network architectures adapted to the investment level and required security. Take responsibility for installation, configuration and network security maintenance.

The module aims to give IT infrastructure management skills, where the role of computer security is critical to ensure the integrity of data and the normal operation of the various systems: computer networks, servers and personal computers in the organization. The course will also explore various Information Security controls, how to handle various risk assessment in an organization and finally creating a security policy in organization.

Today, we note that the information is considered the key business of an organization / company due to its usefulness and importance, however, the issue of the company’s Information Security is a priority task for managers, because they recognize the value it has and therefore organizations must make sure that it is managed effectively. For this reason, this module is important because you will learn the methods and tools for computer security that can ensure the confidentiality of information in organizations and also learn how to protect their information and systems in a network environment.

There are both practical and theoretical reasons to study algorithms. From a practical standpoint, you have to know a standard set of important algorithms from different areas of computing; in addition, you should be able to design new algorithms and analyze their efficiency. From the theoretical standpoint, the study of algorithms, sometimes called algorithmics, has come to be as the cornerstone of computer science.

This course aim to provide an in-depth understanding of the fundamental algorithmic techniques for design and analysis, in turn impart knowledge and practical competence in use of advanced data structures and the design and analysis of algorithms.

This book aims to be an accessible introduction into the design and analysis of efficient algorithms. Throughout the book we will introduce only the most basic techniques and describe the rigorous mathematical methods needed to analyze them.

The topics covered include:

The divide and conquer technique.
The use of randomization in algorithms.
The general, but typically inefficient, backtracking technique.
Dynamic programming as an efficient optimization for some backtracking algorithms.
Greedy algorithms as an optimization of other kinds of backtracking algorithms.
Hill-climbing techniques, including network flow.

The goal of the book is to show you how you can methodically apply different techniques to your own algorithms to make them more efficient. While this book mostly highlights general techniques, some well-known algorithms are also looked at in depth. This book is written so it can be read from "cover to cover" in the length of a semester, where sections marked with a * may be skipped.

This course focuses on the fundamentals of computer algorithms, emphasizing methods useful in practice. Upon successful completion of this course, the student will be able to: explain and identify the importance of algorithms in modern computing systems and their place as a technology in the computing industry; indentify algorithms as a pseudo-code to solve some common problems; describe asymptotic notations for bounding algorithm running times from above and below; explain methods for solving recurrences useful in describing running times of recursive algorithms; explain the use of Master Theorem in describing running times of recursive algorithms; describe the divide-and-conquer recursive technique for solving a class of problems; describe sorting algorithms and their runtime complexity analysis; describe the dynamic programming technique for solving a class of problems; describe greedy algorithms and their applications; describe concepts in graph theory, graph-based algorithms, and their analysis; describe tree-based algorithms and their analysis; explain the classification of difficult computer science problems as belonging to P, NP, and NP-hard classes. (Computer Science 303)

This is a textbook for first year Computer Science. Algorithms and Data Structures With Applications to Graphics and Geometry.

This textbook is an introductory coverage of algorithms and data structures with application to graphics and geometry.

This textbook is an introductory coverage of algorithms and data structures with application to graphics and geometry.

Table of Contents
Part I: Programming environments for motion, graphics, and geometry

1. Reducing a task to given primitives: programming motion
2. Graphics primitives and environments
3. Algorithm animation
Part II: Programming concepts: beyond notation

4. Algorithms and programs as literature: substance and form
5. Divide-and-conquer and recursion.
6. Syntax
7. Syntax analysis
Part III: Objects, algorithms, programs.

8. Truth values, the data type 'set', and bit acrobatics
9. Ordered sets
10. Strings
11. Matrices and graphs: transitive closure
12. Integers
13. Reals
14. Straight lines and circles
Part IV: Complexity of problems and algorithms

15. Computability and complexity
16. The mathematics of algorithm analysis
17. Sorting and its complexity
Part V: Data structures

18. What is a data structure?
19. Abstract data types
20. Implicit data structures
21. List structures
22. Address computation
23. Metric data structures
Part VI: Interaction between algorithms and data structures: case studies in geometric computation

24. Sample problems and algorithms
25. Plane-sweep: a general-purpose algorithm for two-dimensional problems illustrated using line segment intersection
26. The closest pair

In-depth study of an active research topic in computer graphics. Topics change each term. Readings from the literature, student presentations, short assignments, and a programming project. Animation is a compelling and effective form of expression; it engages viewers and makes difficult concepts easier to grasp. Today's animation industry creates films, special effects, and games with stunning visual detail and quality. This graduate class will investigate the algorithms that make these animations possible: keyframing, inverse kinematics, physical simulation, optimization, optimal control, motion capture, and data-driven methods. Our study will also reveal the shortcomings of these sophisticated tools. The students will propose improvements and explore new methods for computer animation in semester-long research projects. The course should appeal to both students with general interest in computer graphics and students interested in new applications of machine learning, robotics, biomechanics, physics, applied mathematics and scientific computing.

This course treats various methods to design and analyze datastructures and algorithms for a wide range of problems. The most important new datastructure treated is the graph, and the general methods introduced are: greedy algorithms, divide and conquer, dynamic programming and network flow algorithms. These general methods are explained by a number of concrete examples, such as simple scheduling algorithms, Dijkstra, Ford-Fulkerson, minimum spanning tree, closest-pair-of-points, knapsack, and Bellman-Ford. Throughout this course there is significant attention to proving the correctness of the discussed algorithms. All material for this course is in English. The recorded lectures, however, are in Dutch.

This text is the beta version of a participatory critical edition of Lewis Carroll’s Alice’s Adventures in Wonderland and Through The Looking Glass. By “beta version,” we mean “text in progress.”

Each chapter also includes an annotation layer that you can use to take private notes or reflect on the text in public with other readers.

We live in an exciting time for the digital humanities, and for those of you who enjoy viewing your text using digital analysis tools to see which words pop up the most frequently, we’ve included a Voyant Visualizer word cloud and link in an annotation attached to each chapter heading. (Here’s an example of a Voyant annotation link. Note that the annotation may take a few moments to load on your screen.)

This book also includes supplemental essays and interactive elements by students and scholars that reflect on print culture of the nineteenth century and the present day. Some of these essays are already published, while some will be published during the course of the year.

The horse is a monogastric hindgut fermenter. The horse evolved for grazing and it does so for up to 17 hours a day. A high proportion of the horse's dietary carbohydrate is in the form of starch. A mature horse eats 2-2.5% of it's body weight in dry matter every day, 1.5-1.75% of this should be fibre (hay/haylage). This is to prevent a rapid drop in pH in the large intestine and also to stimulate peristalsis in the gut and prevent build up of gas.