EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book Dynamic Biosystem Modeling   Simulation Methodology   Integrated   Accessible

Download or read book Dynamic Biosystem Modeling Simulation Methodology Integrated Accessible written by Joseph Distefano, 3rd and published by Biomodeling. This book was released on 2019-09-16 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is uniquely crafted for use in teaching undergraduate students in the life, math, computer and other sciences and engineering. It is INTRODUCTORY LEVEL, for students who have taken or are currently completing their undergraduate math requirements, and are acquiring analytical-thinking and doing skills, along with introductory biology, chemistry and physics subject matter. It's about learning HOW to model and simulate dynamic biological systems, which also makes it useful for graduate students and professional researchers who want a more rigorous treatment of introductory life science math modeling, integrated with the biology. It brings together the multidisciplinary pedagogy of these subjects into a SINGLE INTRODUCTORY MODELING METHODOLOGY COURSE, crystalizing the experience of an author who has been teaching dynamic biosystems modeling and simulation methodology for the life sciences for more than 50 years. DiStefano maximizes accessibility and "systems-math-biology" integration - without diminishing conceptual rigor. Minimally essential applied math and SYSTEMS ENGINEERING METHODS are included, along with a synopsis of the biology and physiology underlying dynamic biosystem modeling, all in a modeling pedagogy context. This textbook fills a major need in the training of contemporary biology students.Dynamic biosystems modeling methodology is presented over 12 distinctive chapters, primarily with systems diagrams and simple differential equations and algebra for expressing them quantitatively, integrated with the biology. Solving and analyzing (quantifying) the biomodels are then accomplished by simulation, using a facile control system simulation language Simulink, a GUI/Matlab toolbox that emulates control systems diagramming, rather than by "coding" the model in a standard computer programming language. Students see and work with the system model - not the code - a big plus. Higher math and complex analytical solutions are avoided.Each chapter begins with a list of LEARNING GOALS, to help with both perspective for the chapter material, and retrospective, to measure learning. EXERCISES for the student at the end of each chapter are designed to test and reinforce learning. A SOLUTIONS MANUAL for chapter exercises is available to qualified instructors from the author, as are LECTURE SLIDES and LAB ASSIGNMENTS AND SOLUTIONS, for courses that adopt the textbook for student use.

Book Dynamic Biosystem Modeling   Simulation Methodology   Integrated   Accessible

Download or read book Dynamic Biosystem Modeling Simulation Methodology Integrated Accessible written by Joseph Distefano, 3rd and published by . This book was released on 2019-09-16 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is uniquely crafted for use in teaching undergraduate students in the life, math, computer and other sciences and engineering. It is INTRODUCTORY LEVEL, for students who have taken or are currently completing their undergraduate math requirements, and are acquiring analytical-thinking and doing skills, along with introductory biology, chemistry and physics subject matter. It's about learning HOW to model and simulate dynamic biological systems, which also makes it useful for graduate students and professional researchers who want a more rigorous treatment of introductory life science math modeling, integrated with the biology. It brings together the multidisciplinary pedagogy of these subjects into a SINGLE INTRODUCTORY MODELING METHODOLOGY COURSE, crystalizing the experience of an author who has been teaching dynamic biosystems modeling and simulation methodology for the life sciences for more than 50 years. DiStefano maximizes accessibility and "systems-math-biology" integration - without diminishing conceptual rigor. Minimally essential applied math and SYSTEMS ENGINEERING METHODS are included, along with a synopsis of the biology and physiology underlying dynamic biosystem modeling, all in a modeling pedagogy context. This textbook fills a major need in the training of contemporary biology students.Dynamic biosystems modeling methodology is presented over 12 distinctive chapters, primarily with systems diagrams and simple differential equations and algebra for expressing them quantitatively, integrated with the biology. Solving and analyzing (quantifying) the biomodels are then accomplished by simulation, using a facile control system simulation language Simulink, a GUI/Matlab toolbox that emulates control systems diagramming, rather than by "coding" the model in a standard computer programming language. Students see and work with the system model - not the code - a big plus. Higher math and complex analytical solutions are avoided.Each chapter begins with a list of LEARNING GOALS, to help with both perspective for the chapter material, and retrospective, to measure learning. EXERCISES for the student at the end of each chapter are designed to test and reinforce learning. A SOLUTIONS MANUAL for chapter exercises is available to qualified instructors from the author, as are LECTURE SLIDES and LAB ASSIGNMENTS AND SOLUTIONS, for courses that adopt the textbook for student use.

Book Dynamic Systems Biology Modeling and Simulation

Download or read book Dynamic Systems Biology Modeling and Simulation written by Joseph DiStefano III and published by Academic Press. This book was released on 2015-01-10 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic Systems Biology Modeling and Simuation consolidates and unifies classical and contemporary multiscale methodologies for mathematical modeling and computer simulation of dynamic biological systems – from molecular/cellular, organ-system, on up to population levels. The book pedagogy is developed as a well-annotated, systematic tutorial – with clearly spelled-out and unified nomenclature – derived from the author’s own modeling efforts, publications and teaching over half a century. Ambiguities in some concepts and tools are clarified and others are rendered more accessible and practical. The latter include novel qualitative theory and methodologies for recognizing dynamical signatures in data using structural (multicompartmental and network) models and graph theory; and analyzing structural and measurement (data) models for quantification feasibility. The level is basic-to-intermediate, with much emphasis on biomodeling from real biodata, for use in real applications. Introductory coverage of core mathematical concepts such as linear and nonlinear differential and difference equations, Laplace transforms, linear algebra, probability, statistics and stochastics topics The pertinent biology, biochemistry, biophysics or pharmacology for modeling are provided, to support understanding the amalgam of “math modeling” with life sciences Strong emphasis on quantifying as well as building and analyzing biomodels: includes methodology and computational tools for parameter identifiability and sensitivity analysis; parameter estimation from real data; model distinguishability and simplification; and practical bioexperiment design and optimization Companion website provides solutions and program code for examples and exercises using Matlab, Simulink, VisSim, SimBiology, SAAMII, AMIGO, Copasi and SBML-coded models A full set of PowerPoint slides are available from the author for teaching from his textbook. He uses them to teach a 10 week quarter upper division course at UCLA, which meets twice a week, so there are 20 lectures. They can easily be augmented or stretched for a 15 week semester course Importantly, the slides are editable, so they can be readily adapted to a lecturer’s personal style and course content needs. The lectures are based on excerpts from 12 of the first 13 chapters of DSBMS. They are designed to highlight the key course material, as a study guide and structure for students following the full text content The complete PowerPoint slide package (~25 MB) can be obtained by instructors (or prospective instructors) by emailing the author directly, at: [email protected]

Book Biological Modeling and Simulation

Download or read book Biological Modeling and Simulation written by Russell Schwartz and published by MIT Press. This book was released on 2008-07-25 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems. There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

Book Systems Biology  Simulation of Dynamic Network States

Download or read book Systems Biology Simulation of Dynamic Network States written by Bernhard Ø. Palsson and published by Cambridge University Press. This book was released on 2011-05-26 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biophysical models have been used in biology for decades, but they have been limited in scope and size. In this book, Bernhard Ø. Palsson shows how network reconstructions that are based on genomic and bibliomic data, and take the form of established stoichiometric matrices, can be converted into dynamic models using metabolomic and fluxomic data. The Mass Action Stoichiometric Simulation (MASS) procedure can be used for any cellular process for which data is available and allows a scalable step-by-step approach to the practical construction of network models. Specifically, it can treat integrated processes that need explicit accounting of small molecules and protein, which allows simulation at the molecular level. The material has been class-tested by the author at both the undergraduate and graduate level. All computations in the text are available online in MATLAB and MATHEMATICA® workbooks, allowing hands-on practice with the material.

Book Systems Biology  Simulation of Dynamic Network States

Download or read book Systems Biology Simulation of Dynamic Network States written by Bernhard Ø. Palsson and published by Cambridge University Press. This book was released on 2011-05-26 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biophysical models have been used in biology for decades, but they have been limited in scope and size. In this book, Bernhard Ø. Palsson shows how network reconstructions that are based on genomic and bibliomic data, and take the form of established stoichiometric matrices, can be converted into dynamic models using metabolomic and fluxomic data. The Mass Action Stoichiometric Simulation (MASS) procedure can be used for any cellular process for which data is available and allows a scalable step-by-step approach to the practical construction of network models. Specifically, it can treat integrated processes that need explicit accounting of small molecules and protein, which allows simulation at the molecular level. The material has been class-tested by the author at both the undergraduate and graduate level. All computations in the text are available online in MATLAB® and Mathematica® workbooks, allowing hands-on practice with the material.

Book Modeling Dynamic Biological Systems

Download or read book Modeling Dynamic Biological Systems written by Bruce Hannon and published by Springer. This book was released on 2014-07-05 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many biologists and ecologists have developed models that find widespread use in theoretical investigations and in applications to organism behavior, disease control, population and metapopulation theory, ecosystem dynamics, and environmental management. This book captures and extends the process of model development by concentrating on the dynamic aspects of these processes and by providing the tools such that virtually anyone with basic knowledge in the Life Sciences can develop meaningful dynamic models. Examples of the systems modeled in the book range from models of cell development, the beating heart, the growth and spread of insects, spatial competition and extinction, to the spread and control of epidemics, including the conditions for the development of chaos. Key features: - easy-to-learn and easy-to-use software - examples from many subdisciplines of biology, covering models of cells, organisms, populations, and metapopulations - no prior computer or programming experience required Key benefits: - learn how to develop modeling skills and system thinking on your own rather than use models developed by others - be able to easily run models under alternative assumptions and investigate the implications of these assumptions for the dynamics of the biological system being modeled - develop skills to assess the dynamics of biological systems

Book System Modeling in Cellular Biology

Download or read book System Modeling in Cellular Biology written by Zoltan Szallasi and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction and overview of system modeling in biology that is accessible to researchers from different fields, including biology, computer science, mathematics, statistics, physics, and biochemistry. Research in systems biology requires the collaboration of researchers from diverse backgrounds, including biology, computer science, mathematics, statistics, physics, and biochemistry. These collaborations, necessary because of the enormous breadth of background needed for research in this field, can be hindered by differing understandings of the limitations and applicability of techniques and concerns from different disciplines. This comprehensive introduction and overview of system modeling in biology makes the relevant background material from all pertinent fields accessible to researchers with different backgrounds. The emerging area of systems level modeling in cellular biology has lacked a critical and thorough overview. This book fills that gap. It is the first to provide the necessary critical comparison of concepts and approaches, with an emphasis on their possible applications. It presents key concepts and their theoretical background, including the concepts of robustness and modularity and their exploitation to study biological systems; the best-known modeling approaches, and their advantages and disadvantages; lessons from the application of mathematical models to the study of cellular biology; and available modeling tools and datasets, along with their computational limitations.

Book Guide to Simulation and Modeling for Biosciences

Download or read book Guide to Simulation and Modeling for Biosciences written by David J. Barnes and published by Springer. This book was released on 2015-09-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible text presents a detailed introduction to the use of a wide range of software tools and modeling environments for use in the biosciences, as well as the fundamental mathematical background. The practical constraints presented by each modeling technique are described in detail, enabling the researcher to determine which software package would be most useful for a particular problem. Features: introduces a basic array of techniques to formulate models of biological systems, and to solve them; discusses agent-based models, stochastic modeling techniques, differential equations, spatial simulations, and Gillespie’s stochastic simulation algorithm; provides exercises; describes such useful tools as the Maxima algebra system, the PRISM model checker, and the modeling environments Repast Simphony and Smoldyn; contains appendices on rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; offers supplementary material at an associated website.

Book Process Integration in Biochemical Engineering

Download or read book Process Integration in Biochemical Engineering written by Urs von Stockar and published by Springer. This book was released on 2003-04-10 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Process integration has been one of the most active research fields in Biochemical Engineering over the last decade and it will continue to be so if bioprocessing is to become more rational, efficient and productive. This volume outlines what has been achieved in recent years. Written by experts who have made important contributions to the European Science, Foundation Program on Process Integration in Biochemical Engineering, the volume focuses on the progress made and the major opportunities, and in addition on the limitations and the challenges in bioprocess integration that lie ahead. The concept of bioprocess integration is treated at various levels, including integration at the molecular, biological, bioreactor and plant levels, but also accounting for the integration of separation and mass transfer operations and biology, fluid dynamics and physiology, as well as basic science and process technology.

Book Bioreactor Modeling

Download or read book Bioreactor Modeling written by Jerome Morchain and published by Elsevier. This book was released on 2017-10-06 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic simulation of bioreactors is a challenge for both the industrial and academic worlds. Beyond the large number of physical and biological phenomena to be considered and the wide range of scales involved, the central difficulty lies in the need to account for the dynamic behavior of suspended microorganisms. In the case of chemical reactors, knowledge of the thermodynamic equilibrium laws at the interfaces makes it possible to produce macroscopic models by integrating local laws. Microorganisms, on the other hand, have the ability to modulate the rate of substrate assimilation. Moreover, the nature of the biochemical transformations results from a compromise between the needs of the cell and the available resources. This book revisits the modeling of bioreactors using a multi-scale approach. It addresses issues related to mixing, phase-to-phase transfers and the adaptation of microorganisms to variations in concentration, and explores the use of population balances for the simulation of bioreactors. By adopting a multidisciplinary perspective that draws on process engineering, fluid mechanics and microbiology, this book sheds new light on the particularity of bioprocesses in relation to physical and chemical phenomena. Presents a multiphase description of bioreactor modeling Includes a combination of concepts issued from different scientific fields to address a practical issue Provides a detailed description of the population balance concept as applied to biological systems Covers a set of illustrative examples of the interaction between hydrodynamics and biological response

Book Selected Water Resources Abstracts

Download or read book Selected Water Resources Abstracts written by and published by . This book was released on 1977 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Computational Modeling and Simulation Examples in Bioengineering

Download or read book Computational Modeling and Simulation Examples in Bioengineering written by Nenad Filipovic and published by John Wiley & Sons. This book was released on 2021-12-14 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic overview of the quickly developing field of bioengineering—with state-of-the-art modeling software! Computational Modeling and Simulation Examples in Bioengineering provides a comprehensive introduction to the emerging field of bioengineering. It provides the theoretical background necessary to simulating pathological conditions in the bones, muscles, cardiovascular tissue, and cancers, as well as lung and vertigo disease. The methodological approaches used for simulations include the finite element, dissipative particle dynamics, and lattice Boltzman. The text includes access to a state-of-the-art software package for simulating the theoretical problems. In this way, the book enhances the reader's learning capabilities in the field of biomedical engineering. The aim of this book is to provide concrete examples of applied modeling in biomedical engineering. Examples in a wide range of areas equip the reader with a foundation of knowledge regarding which problems can be modeled with which numerical methods. With more practical examples and more online software support than any competing text, this book organizes the field of computational bioengineering into an accessible and thorough introduction. Computational Modeling and Simulation Examples in Bioengineering: Includes a state-of-the-art software package enabling readers to engage in hands-on modeling of the examples in the book Provides a background on continuum and discrete modeling, along with equations and derivations for three key numerical methods Considers examples in the modeling of bones, skeletal muscles, cartilage, tissue engineering, blood flow, plaque, and more Explores stent deployment modeling as well as stent design and optimization techniques Generates different examples of fracture fixation with respect to the advantages in medical practice applications Computational Modeling and Simulation Examples in Bioengineering is an excellent textbook for students of bioengineering, as well as a support for basic and clinical research. Medical doctors and other clinical professionals will also benefit from this resource and guide to the latest modeling techniques.

Book Computer Simulation Validation

Download or read book Computer Simulation Validation written by Claus Beisbart and published by Springer. This book was released on 2019-04-09 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.

Book Modeling Biological Systems

    Book Details:
  • Author : James W. Haefner
  • Publisher : Springer Science & Business Media
  • Release : 2005-05-06
  • ISBN : 9780387250113
  • Pages : 500 pages

Download or read book Modeling Biological Systems written by James W. Haefner and published by Springer Science & Business Media. This book was released on 2005-05-06 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: I Principles 1 1 Models of Systems 3 1. 1 Systems. Models. and Modeling . . . . . . . . . . . . . . . . . . . . 3 1. 2 Uses of Scientific Models . . . . . . . . . . . . . . . . . . . . . . . . 4 1. 3 Example: Island Biogeography . . . . . . . . . . . . . . . . . . . . . 6 1. 4 Classifications of Models . . . . . . . . . . . . . . . . . . . . . . . . 10 1. 5 Constraints on Model Structure . . . . . . . . . . . . . . . . . . . . . 12 1. 6 Some Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1. 7 Misuses of Models: The Dark Side . . . . . . . . . . . . . . . . . . . 13 1. 8 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2 The Modeling Process 17 2. 1 Models Are Problems . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2. 2 Two Alternative Approaches . . . . . . . . . . . . . . . . . . . . . . 18 2. 3 An Example: Population Doubling Time . . . . . . . . . . . . . . . . 24 2. 4 Model Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2. 5 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3 Qualitative Model Formulation 32 3. 1 How to Eat an Elephant . . . . . . . . . . . . . . . . . . . . . . . . . 32 3. 2 Forrester Diagrams . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3. 3 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3. 4 Errors in Forrester Diagrams . . . . . . . . . . . . . . . . . . . . . . 44 3. 5 Advantages and Disadvantages of Forrester Diagrams . . . . . . . . . 44 3. 6 Principles of Qualitative Formulation . . . . . . . . . . . . . . . . . . 45 3. 7 Model Simplification . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3. 8 Other Modeling Problems . . . . . . . . . . . . . . . . . . . . . . . . 49 viii Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. 9 Exercises 53 4 Quantitative Model Formulation: I 4. 1 From Qualitative to Quantitative . . . . . . . . . . . . . . . . . Finite Difference Equations and Differential Equations 4. 2 . . . . . . . . . . . . . . . . 4. 3 Biological Feedback in Quantitative Models . . . . . . . . . . . . . . . . . . . . . . . . . . 4. 4 Example Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. 5 Exercises 5 Quantitative Model Formulation: I1 81 . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 1 Physical Processes 81 . . . . . . . . . . . . . . . 5. 2 Using the Toolbox of Biological Processes 89 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 3 Useful Functions 96 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 4 Examples 102 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. 5 Exercises 104 6 Numerical Techniques 107 . . . . . . . . . . . . . . . . . . . . . . . 6. 1 Mistakes Computers Make 107 . . . . . . . . . . . . . . . . . . . . . . . . . . 6. 2 Numerical Integration 110 . . . . . . . . . . . . . . . . 6. 3 Numerical Instability and Stiff Equations 115 . . . . . . . . . . . . . .

Book Building a Web Based Education System

Download or read book Building a Web Based Education System written by Colin McCormack and published by . This book was released on 1998 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is the "how to" book for setting up a distance learning program on the Web. First touching on the principles of online education, this book discusses five different systems, supplying code, screen shots, and ideas for customization. The CD-ROM contains templates for online university classrooms with HTML, C, Perl scripts, and Java files that can be customized.

Book Process Modelling and Simulation

Download or read book Process Modelling and Simulation written by César de Prada and published by MDPI. This book was released on 2019-09-23 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.