21 results (0,16796 seconds)

Show all filters

Brand

Merchant

Price (EUR)

Reset filter

Products
From
Shops

C++ for Financial Mathematics

C++ for Financial Mathematics

If you know a little bit about financial mathematics but don’t yet know a lot about programming then C++ for Financial Mathematics is for you. C++ is an essential skill for many jobs in quantitative finance but learning it can be a daunting prospect. This book gathers together everything you need to know to price derivatives in C++ without unnecessary complexities or technicalities. It leads the reader step-by-step from programming novice to writing a sophisticated and flexible financial mathematics library. At every step each new idea is motivated and illustrated with concrete financial examples. As employers understand there is more to programming than knowing a computer language. As well as covering the core language features of C++ this book teaches the skills needed to write truly high quality software. These include topics such as unit tests debugging design patterns and data structures. The book teaches everything you need to know to solve realistic financial problems in C++. It can be used for self-study or as a textbook for an advanced undergraduate or master’s level course.

GBP 44.99
1

C Programming Learn to Code

C Programming Learn to Code

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. | C Programming Learn to Code

GBP 105.00
1

Data Structures using C A Practical Approach for Beginners

Data Structures using C A Practical Approach for Beginners

The data structure is a set of specially organized data elements and functions which are defined to store retrieve remove and search for individual data elements. Data Structures using C: A Practical Approach for Beginners covers all issues related to the amount of storage needed the amount of time required to process the data data representation of the primary memory and operations carried out with such data. Data Structures using C: A Practical Approach for Beginners book will help students learn data structure and algorithms in a focused way. Resolves linear and nonlinear data structures in C language using the algorithm diagrammatically and its time and space complexity analysis Covers interview questions and MCQs on all topics of campus readiness Identifies possible solutions to each problem Includes real-life and computational applications of linear and nonlinear data structures This book is primarily aimed at undergraduates and graduates of computer science and information technology. Students of all engineering disciplines will also find this book useful. | Data Structures using C A Practical Approach for Beginners

GBP 105.00
1

Anyone Can Code The Art and Science of Logical Creativity

Anyone Can Code The Art and Science of Logical Creativity

Anyone Can Code: The Art and Science of Logical Creativity introduces computer programming as a way of problem-solving through logical thinking. It uses the notion of modularization as a central lens through which we can make sense of many software concepts. This book takes the reader through fundamental concepts in programming by illustrating them in three different and distinct languages: C/C++ Python and Javascript. Key features: Focuses on problem-solving and algorithmic thinking instead of programming functions syntax and libraries; Includes engaging examples including video games and visual effects; Provides exercises and reflective questions. This book gives beginner and intermediate learners a strong understanding of what they are doing so that they can do it better and with any other tool or language that they may end up using later. | Anyone Can Code The Art and Science of Logical Creativity

GBP 56.99
1

Data Science with Julia

Data Science with Julia

This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist. Professor Charles Bouveyron INRIA Chair in Data Science Université Côte d’Azur Nice France Julia an open-source programming language was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible intuitive and highly efficient base language with speed that exceeds R and Python makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use there are already over 1 900 packages available and Julia can interface (either directly or through packages) with libraries written in R Python Matlab C C++ or Fortran. The book is for senior undergraduates beginning graduate students or practicing data scientists who want to learn how to use Julia for data science. This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist. Professor Charles BouveyronINRIA Chair in Data ScienceUniversité Côte d’Azur Nice France

GBP 51.99
1

The New S Language

The New S Language

This book provides documentation for a new version of the S system released in 1988. The new S enhances the features that have made S popular: interactive computing flexible graphics data management and a large collection of functions. The new S features make possible new applications and higher-level programming including a single unified language user defined functions as first-class objects symbolic computations more accurate numerical calculations and a new approach to graphics. S now provides direct interfaces to the poowerful tool of the UNIX operating system and to algorithms implemented in Fortran and C. | The New S Language

GBP 325.00
1

High Performance Computing Programming and Applications

High Performance Computing Programming and Applications

High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high performance computing (HPC) applications. Omitting tedious details the book discusses hardware architecture concepts and programming techniques that are the most pertinent to application developers for achieving high performance. Even though the text concentrates on C and Fortran the techniques described can be applied to other languages such as C++ and Java. Drawing on their experience with chips from AMD and systems interconnects and software from Cray Inc. the authors explore the problems that create bottlenecks in attaining good performance. They cover techniques that pertain to each of the three levels of parallelism: Message passing between the nodes Shared memory parallelism on the nodes or the multiple instruction multiple data (MIMD) units on the accelerator Vectorization on the inner level After discussing architectural and software challenges the book outlines a strategy for porting and optimizing an existing application to a large massively parallel processor (MPP) system. With a look toward the future it also introduces the use of general purpose graphics processing units (GPGPUs) for carrying out HPC computations. A companion website at www. hybridmulticoreoptimization. com contains all the examples from the book along with updated timing results on the latest released processors. | High Performance Computing Programming and Applications

GBP 59.99
1

bookdown Authoring Books and Technical Documents with R Markdown

bookdown Authoring Books and Technical Documents with R Markdown

bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown and extends R Markdown for technical writing so that you can make better use of document elements such as figures tables equations theorems citations and references. Similar to LaTeX you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats including LaTeX/PDF HTML EPUB and Word thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers reports dissertations course handouts study notes and even novels. You do not have to use R either. Other choices of computing languages include Python C C plus plus SQL Bash Stan JavaScript and so on although R is best supported. You can also leave out computing for example to write a fiction. This book itself is an example of publishing with bookdown and R Markdown and its source is fully available on GitHub. | bookdown Authoring Books and Technical Documents with R Markdown

GBP 89.99
1

A Concise Introduction to Robot Programming with ROS2

A Concise Introduction to Robot Programming with ROS2

A Concise Introduction to Robot Programming with ROS2 provides the reader with the concepts and tools necessary to bring a robot to life through programming. It will equip the reader with the skills necessary to undertake projects with ROS2 the new version of ROS. It is not necessary to have previous experience with ROS2 as it will describe its concepts tools and methodologies from the beginning. Key Features Uses the two programming languages officially supported in ROS2 (C++ mainly and Python) Approaches ROS2 from three different but complementary dimensions: the Community Computation Graph and the Workspace Includes a complete simulated robot development and testing strategies Behavior Trees and Nav2 description setup and use A GitHub repository with code to assist readers It will appeal to motivated engineering students engineers and professionals working with robot programming.

GBP 44.99
1

Summability Theory and Its Applications

Summability Theory and Its Applications

Summability Theory and Its Applications explains various aspects of summability and demonstrates its applications in a rigorous and coherent manner. The content can readily serve as a reference or as a useful series of lecture notes on the subject. This substantially revised new edition includes brand new material across several chapters as well as several corrections including: the addition of the domain of Cesaro matrix C(m) of order m in the classical sequence spaces to Chapter 4; and introducing the domain of four-dimensional binomial matrix in the spaces of bounded convergent in the Pringsheim's sense both convergent in the Pringsheim's sense and bounded and regularly convergent double sequences in Chapter 7. Features Investigates different types of summable spaces and computes their dual Suitable for graduate students and researchers with a (special) interest in spaces of single and double sequences matrix transformations and domains of triangle matrices Can serve as a reference or as supplementary reading in a computational physics course or as a key text for special Analysis seminars.

GBP 130.00
1

Combinatorics of Compositions and Words

Combinatorics of Compositions and Words

A One-Stop Source of Known Results a Bibliography of Papers on the Subject and Novel Research Directions Focusing on a very active area of research in the last decade Combinatorics of Compositions and Words provides an introduction to the methods used in the combinatorics of pattern avoidance and pattern enumeration in compositions and words. It also presents various tools and approaches that are applicable to other areas of enumerative combinatorics. After a historical perspective on research in the area the text introduces techniques to solve recurrence relations including iteration and generating functions. It then focuses on enumeration of basic statistics for compositions. The text goes on to present results on pattern avoidance for subword subsequence and generalized patterns in compositions and then applies these results to words. The authors also cover automata the ECO method generating trees and asymptotic results via random compositions and complex analysis. Highlighting both established and new results this book explores numerous tools for enumerating patterns in compositions and words. It includes a comprehensive bibliography and incorporates the use of the computer algebra systems Maple™ and Mathematica® as well as C++ to perform computations.

GBP 74.99
1

The Art of Algorithm Design

The Art of Algorithm Design

The Art of Algorithm Design is a complementary perception of all books on algorithm design and is a roadmap for all levels of learners as well as professionals dealing with algorithmic problems. Further the book provides a comprehensive introduction to algorithms and covers them in considerable depth yet makes their design and analysis accessible to all levels of readers. All algorithms are described and designed with a pseudo-code to be readable by anyone with little knowledge of programming. This book comprises of a comprehensive set of problems and their solutions against each algorithm to demonstrate its executional assessment and complexity with an objective to: Understand the introductory concepts and design principles of algorithms and their complexities Demonstrate the programming implementations of all the algorithms using C-Language Be an excellent handbook on algorithms with self-explanatory chapters enriched with problems and solutions While other books may also cover some of the same topics this book is designed to be both versatile and complete as it traverses through step-by-step concepts and methods for analyzing each algorithmic complexity with pseudo-code examples. Moreover the book provides an enjoyable primer to the field of algorithms. This book is designed for undergraduates and postgraduates studying algorithm design.

GBP 150.00
1

A Systematic Approach to Learning Robot Programming with ROS

A Systematic Approach to Learning Robot Programming with ROS

A Systematic Approach to Learning Robot Programming with ROS provides a comprehensive introduction to the essential components of ROS through detailed explanations of simple code examples along with the corresponding theory of operation. The book explores the organization of ROS how to understand ROS packages how to use ROS tools how to incorporate existing ROS packages into new applications and how to develop new packages for robotics and automation. It also facilitates continuing education by preparing the reader to better understand the existing on-line documentation. The book is organized into six parts. It begins with an introduction to ROS foundations including writing ROS nodes and ROS tools. Messages Classes and Servers are also covered. The second part of the book features simulation and visualization with ROS including coordinate transforms. The next part of the book discusses perceptual processing in ROS. It includes coverage of using cameras in ROS depth imaging and point clouds and point cloud processing. Mobile robot control and navigation in ROS is featured in the fourth part of the book The fifth section of the book contains coverage of robot arms in ROS. This section explores robot arm kinematics arm motion planning arm control with the Baxter Simulator and an object-grabber package. The last part of the book focuses on system integration and higher-level control including perception-based and mobile manipulation. This accessible text includes examples throughout and C++ code examples are also provided at https://github. com/wsnewman/learning_ros

GBP 62.99
1

Linux with Operating System Concepts

Linux with Operating System Concepts

A True Textbook for an Introductory Course System Administration Course or a Combination Course Linux with Operating System Concepts Second Edition merges conceptual operating system (OS) and Unix/Linux topics into one cohesive textbook for undergraduate students. The book can be used for a one- or two-semester course on Linux or Unix. It is complete with review sections problems definitions concepts and relevant introductory material such as binary and Boolean logic OS kernels and the role of the CPU and memory hierarchy. Details for Introductory and Advanced Users The book covers Linux from both the user and system administrator positions. From a user perspective it emphasizes command-line interaction. From a system administrator perspective the text reinforces shell scripting with examples of administration scripts that support the automation of administrator tasks. Thorough Coverage of Concepts and Linux Commands The author incorporates OS concepts not found in most Linux/Unix textbooks including kernels file systems storage devices virtual memory and process management. He also introduces computer science topics such as computer networks and TCP/IP interpreters versus compilers file compression file system integrity through backups RAID and encryption technologies booting and the GNUs C compiler. New in this Edition The book has been updated to systemd Linux and the newer services like Cockpit NetworkManager firewalld and journald. This edition explores Linux beyond CentOS/Red Hat by adding detail on Debian distributions. Content across most topics has been updated and improved.

GBP 82.99
1

Fortran 2018 with Parallel Programming

Fortran 2018 with Parallel Programming

The programming language Fortran dates back to 1957 when a team of IBM engineers released the first Fortran Compiler. During the past 60 years the language had been revised and updated several times to incorporate more features to enable writing clean and structured computer programs. The present version is Fortran 2018. Since the dawn of the computer era there had been a constant demand for a “larger” and “faster” machine. To increase the speed there are three hurdles. The density of the active components on a VLSI chip cannot be increased indefinitely and with the increase of the density heat dissipation becomes a major problem. Finally the speed of any signal cannot exceed the velocity of the light. However by using several inexpensive processors in parallel coupled with specialized software and hardware programmers can achieve computing speed similar to a supercomputer. This book can be used to learn the modern Fortran from the beginning and the technique of developing parallel programs using Fortran. It is for anyone who wants to learn Fortran. Knowledge beyond high school mathematics is not required. There is not another book on the market yet which deals with Fortran 2018 as well as parallel programming. FEATURES Descriptions of majority of Fortran 2018 instructions Numerical Model String with Variable Length IEEE Arithmetic and Exceptions Dynamic Memory Management Pointers Bit handling C-Fortran Interoperability Object Oriented Programming Parallel Programming using Coarray Parallel Programming using OpenMP Parallel Programming using Message Passing Interface (MPI) THE AUTHOR Dr Subrata Ray is a retired Professor Indian Association for the Cultivation of Science Kolkata. | Fortran 2018 with Parallel Programming

GBP 140.00
1

Random Circulant Matrices

Random Circulant Matrices

Circulant matrices have been around for a long time and have been extensively used in many scientific areas. This book studies the properties of the eigenvalues for various types of circulant matrices such as the usual circulant the reverse circulant and the k-circulant when the dimension of the matrices grow and the entries are random. In particular the behavior of the spectral distribution of the spectral radius and of the appropriate point processes are developed systematically using the method of moments and the various powerful normal approximation results. This behavior varies according as the entries are independent are from a linear process and are light- or heavy-tailed. Arup Bose obtained his B. Stat. M. Stat. and Ph. D. degrees from the Indian Statistical Institute. He has been on its faculty at the Theoretical Statistics and Mathematics Unit Kolkata India since 1991. He is a Fellow of the Institute of Mathematical Statistics and of all three national science academies of India. He is a recipient of the S. S. Bhatnagar Prize and the C. R. Rao Award. He is the author of three books: Patterned Random Matrices Large Covariance and Autocovariance Matrices (with Monika Bhattacharjee) and U-Statistics M_m-Estimators and Resampling (with Snigdhansu Chatterjee). Koushik Saha obtained a B. Sc. in Mathematics from Ramakrishna Mission Vidyamandiara Belur and an M. Sc. in Mathematics from Indian Institute of Technology Bombay. He obtained his Ph. D. degree from the Indian Statistical Institute under the supervision of Arup Bose. His thesis on circulant matrices received high praise from the reviewers. He has been on the faculty of the Department of Mathematics Indian Institute of Technology Bombay since 2014. | Random Circulant Matrices

GBP 44.99
1

Introduction to Real Analysis

Introduction to Real Analysis

This classic textbook has been used successfully by instructors and students for nearly three decades. This timely new edition offers minimal yet notable changes while retaining all the elements presentation and accessible exposition of previous editions. A list of updates is found in the Preface to this edition. This text is based on the author’s experience in teaching graduate courses and the minimal requirements for successful graduate study. The text is understandable to the typical student enrolled in the course taking into consideration the variations in abilities background and motivation. Chapters one through six have been written to be accessible to the average student w hile at the same time challenging the more talented student through the exercises. Chapters seven through ten assume the students have achieved some level of expertise in the subject. In these chapters the theorems examples and exercises require greater sophistication and mathematical maturity for full understanding. In addition to the standard topics the text includes topics that are not always included in comparable texts. Chapter 6 contains a section on the Riemann-Stieltjes integral and a proof of Lebesgue’s t heorem providing necessary and sufficient conditions for Riemann integrability. Chapter 7 also includes a section on square summable sequences and a brief introduction to normed linear spaces. C hapter 8 contains a proof of the Weierstrass approximation theorem using the method of aapproximate identities. The inclusion of Fourier series in the text allows the student to gain some exposure to this important subject. The final chapter includes a detailed treatment of Lebesgue measure and the Lebesgue integral using inner and outer measure. The exercises at the end of each section reinforce the concepts. Notes provide historical comments or discuss additional topics. | Introduction to Real Analysis

GBP 46.99
1

Introduction to Stochastic Level Crossing Techniques

Introduction to Stochastic Level Crossing Techniques

Introduction to Stochastic Level Crossing Techniques describes stochastic models and their analysis using the System Point Level Crossing method (abbreviated SPLC or LC). This involves deriving probability density functions (pdfs) or cumulative probability distribution functions (cdfs) of key random variables applying simple level-crossing limit theorems developed by the author. The pdfs and/or cdfs are used to specify operational characteristics about the stochastic model of interest. The chapters describe distinct stochastic models and associated key random variables in the models. For each model a figure of a typical sample path (realization i. e. tracing over time) of the key random variable is displayed. For each model an analytic (Volterra) integral equation for the stationary pdf of the key random variable is created−by inspection of the sample path using the simple LC limit theorems. This LC method bypasses a great deal of algebra usually required by other methods of analysis. The integral equations will be solved directly or computationally. This book is meant for students of mathematics management science engineering natural sciences and researchers who use applied probability. It will also be useful to technical workers in a range of professions. Key Features: A description of one representative stochastic model (e. g. a single-server M/G/1 queue; a multiple server M/M/c queue; an inventory system; etc. ) Construction of a typical sample path of the key random variable of interest (e. g. the virtual waiting time or workload in queues; the net on-hand inventory in inventory systems; etc. ) Statements of the simple LC theorems which connect the sample-path upcrossing and downcrossing rates across state-space levels to simple mathematical functions of the stationary pdf of the key random variable at those state-space levels Creation of (usually Volterra) integral equations for the stationary pdf of the key random variable by inspection of the sample path Direct analytic solution of the integral equations where feasible; or computational solutions of the integral equations Use of the derived stationary pdfs for obtaining operational characteristics of the model

GBP 120.00
1

Probability and Statistics for Computer Scientists

Probability and Statistics for Computer Scientists

Praise for the Second Edition: The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures and concludes with appendices and an index. The book is erudite and … could work well as a required text for an advanced undergraduate or graduate course. Computing Reviews Probability and Statistics for Computer Scientists Third Edition helps students understand fundamental concepts of Probability and Statistics general methods of stochastic modeling simulation queuing and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB this classroom-tested book can be used for one- or two-semester courses. Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis including estimation and testing Bayesian approach multivariate regression chi-square tests for independence and goodness of fit nonparametric statistics and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science software engineering telecommunications and related areas In-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting with the fundamentals of probability the text takes students through topics heavily featured in modern computer science computer engineering software engineering and associated fields such as computer simulations Monte Carlo methods stochastic processes Markov chains queuing theory statistical inference and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). About the Author Michael Baron is David Carroll Professor of Mathematics and Statistics at American University in Washington D. C. He conducts research in sequential analysis and optimal stopping change-point detection Bayesian inference and applications of statistics in epidemiology clinical trials semiconductor manufacturing and other fields. M. Baron is a Fellow of the American Statistical Association and a recipient of the Abraham Wald Prize for the best paper in Sequential Analysis and the Regents Outstanding Teaching Award. M. Baron holds a Ph. D. in statistics from the University of Maryland. In his turn he supervised twelve doctoral students mostly employed on academic and research positions.

GBP 99.99
1

Financial Mathematics Two Volume Set

Financial Mathematics Two Volume Set

This textbook provides complete coverage of discrete-time financial models that form the cornerstones of financial derivative pricing theory. Unlike similar texts in the field this one presents multiple problem-solving approaches linking related comprehensive techniques for pricing different types of financial derivatives. Key features: In-depth coverage of discrete-time theory and methodology. Numerous fully worked out examples and exercises in every chapter. Mathematically rigorous and consistent yet bridging various basic and more advanced concepts. Judicious balance of financial theory mathematical and computational methods. Guide to Material. This revision contains: Almost 200 pages worth of new material in all chapters. A new chapter on elementary probability theory. An expanded the set of solved problems and additional exercises. Answers to all exercises. This book is a comprehensive self-contained and unified treatment of the main theory and application of mathematical methods behind modern-day financial mathematics. Table of Contents List of Figures and Tables Preface I Introduction to Pricing and Management of Financial Securities 1 Mathematics of Compounding 2 Primer on Pricing Risky Securities 3 Portfolio Management 4 Primer on Derivative Securities II Discrete-Time Modelling 5 Single-Period Arrow–Debreu Models 6 Introduction to Discrete-Time Stochastic Calculus 7 Replication and Pricing in the Binomial Tree Model 8 General Multi-Asset Multi-Period Model Appendices A Elementary Probability Theory B Glossary of Symbols and Abbreviations C Answers and Hints to Exercises References Index Biographies Giuseppe Campolieti is Professor of Mathematics at Wilfrid Laurier University in Waterloo Canada. He has been Natural Sciences and Engineering Research Council postdoctoral research fellow and university research fellow at the University of Toronto. In 1998 he joined the Masters in Mathematical Finance as an instructor and later as an adjunct professor in financial mathematics until 2002. Dr. Campolieti also founded a financial software and consulting company in 1998. He joined Laurier in 2002 as Associate Professor of Mathematics and as SHARCNET Chair in Financial Mathematics. Roman N. Makarov is Associate Professor and Chair of Mathematics at Wilfrid Laurier University. Prior to joining Laurier in 2003 he was an Assistant Professor of Mathematics at Siberian State University of Telecommunications and Informatics and a senior research fellow at the Laboratory of Monte Carlo Methods at the Institute of Computational Mathematics and Mathematical Geophysics in Novosibirsk Russia. | Financial Mathematics Two Volume Set

GBP 130.00
1