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Magnetic Fusion Energy: From Experiments to Power Plants is a timely exploration of the field, giving readers an understanding of the experiments that brought us to the threshold of the ITER era, as well as the physics and technology research needed to take us beyond ITER to commercial fusion power plants. With the start of ITER construction, the world's magnetic fusion energy (MFE) enterprise has begun a new era. The ITER scientific and technical (S&T) basis is the result of research on many fusion plasma physics experiments over a period of decades. Besides ITER, the scope of fusion research must be broadened to create the S&T basis for practical fusion power plants, systems that will continuously convert the energy released from a burning plasma to usable electricity, operating for years with only occasional interruptions for scheduled maintenance. - Provides researchers in academia and industry with an authoritative overview of the significant fusion energy experiments - Considers the pathway towards future development of magnetic fusion energy power plants - Contains experts contributions from editors and others who are well known in the field
This book offers an overall review, applying systems engineering and architecture approaches, of the design, optimization, operation and results of leading fusion experiments. These approaches provide a unified means of evaluating reactor design. Methodologies are developed for more coherent construction or evaluation of fusion devices, associated experiments and operating procedures. The main focus is on tokamaks, with almost all machines and their important results being integrated into a systems design space. Case studies focus on DIII-D, TCV, JET, WEST, the fusion reactor prototype ITER and the EU DEMO concept. Stellarator, Mirror and Laser inertial confinement experiments are similarly analysed, including reactor implications of breakeven at NIF. The book examines the engineering and physics design and optimization process for each machine, analysing their performance and major results achieved, thus establishing a basis for the improvement of future machines. The reader will gain a broad historical and up-to-date perspective of the status of nuclear fusion research from both an engineering and physics point of view. Explanations are given of the computational tools needed to design and operate successful experiments and reactor-relevant machines. This book is aimed at both graduate students and practitioners of nuclear fusion science and engineering, as well as those specializing in other fields demanding large and integrated experimental equipment. Systems engineers will obtain valuable insights into fusion applications. References are given to associated complex mathematical derivations, which are beyond the scope of this book. The general reader interested in nuclear fusion will find here an accessible summary of the current state of nuclear fusion.
Banana is one of the most important fruits worldwide and a staple food for millions of people in developing countries. However, vegetative propagation of commercial cultivars results in a limited genetic background, making banana plants susceptible to disease infection. Conventional chemical control is typically inefficient, owing to the plant's inability to absorb significant quantities of chemicals in a short period of time. The overuse leads to chemical reagent resistance and a rise in environmental contamination. Furthermore, the inappropriate chemical application might result in a relatively high quantity of residues on banana fruits, posing human health risks through consumption. As a result, new technology and discoveries for integrated banana plant protection are urgently required.
This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application. Key features: Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions. Comprehensive summary tables of the properties of the distributions. Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness. Includes mixed distributions which are continuous distributions with additional specific values with point probabilities. Includes many real data examples, with R code integrated in the text for ease of understanding and replication. Supplemented by the gamlss website. This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.