Intensive Variable And Its Application

There are still insufficient general theories on the law of diminishing returns, despite 100 years of development. Starting with intensive variables theory, and by utilizing tools of spatiotemporal correlation and intensive functions, moving on to the integrated curve of diminishing returns and intensive theory, and even more importantly, using a combination of static and dynamic GIS, and integrating numerical calculation and spatial optimization, this book not only creates a unique theoretical framework and methodology for the evaluation of land use effect, but also addresses the long-standing lack of universal theories and methods on the law of diminishing returns. It will have far-reaching impacts on the development of this area and its practical application. The book covers a wide range fields in geography, land science, geographic information science, management science and related areas. Novel theoretical perspectives illustrated with many detailed case studies offer an easier way for readers to expand their research, ensuring that both academic and business audiences will benefit. Prof. Xinqi Zheng works at the China University of Geosciences (Beijing), People’s Republic of China.

An understanding of the mechanical properties of unsaturated soilsis crucial for geotechnical engineers worldwide, as well as tothose concerned with the interaction of structures with the ground.This book deals principally with fine-grained clays and silts, orsoils containing coarser sand and gravel particles but with asignificant percentage of fines. The study of unsaturated soil is a practical subject, linkingfundamental science to nature. Soils in general are inherentlyvariable and their behaviour is not easy to analyse or predict, andunsaturated soils raise the complexity to a higher level. Evenamongst practicing engineers, there is often lack of awareness ofthe intricacies of the subject. This book offers a perspective ofunsaturated soils based on recent research and demonstrates howthis dovetails with the general discipline of soil mechanics. Following an introduction to the basic soil variables, thephases, the phase interactions and the relevance of soil structure,an up-to-date review of laboratory testing techniques is presented.This includes suction measurement and control techniques intriaxial cell testing. This is followed by an introduction tostress state variables, critical state and theoretical models inunsaturated soils. A detailed description of the thermodynamic principles asapplied to multi-phase materials under equilibrium conditionsfollows. These principles are then used to explore and develop afundamental theoretical basis for analysing unsaturated soils. Soilstructure is broken down into its component parts to developequations describing the dual stress regime. The critical statestrength and compression characteristics of unsaturated soils areexamined and it is shown how the behaviour may be viewed as athree-dimensional model in dimensionless stress-volume space. Theanalysis is then extended to the work input into unsaturated soilsand the development of conjugate stress, volumetric andstrain-increment variables. These are used to examine themicromechanical behaviour of kaolin specimens subjected to triaxialshear strength tests and lead to observations not detectable byother means. Unsaturated Soils: A fundamental interpretation of soilbehaviour covers a rapidly advancing area of study, researchand engineering practice and offers a deeper appreciation of thekey characteristics of unsaturated soil. It provides students andresearchers with a framework for understanding soil behaviour anddemonstrates how to interpret experimental strength and compressiondata. provides engineers with a deeper appreciation of keycharacteristics of unsaturated soils covers a rapidly advancing area of study, research andengineering practice provides students and researchers a framework for understandingsoil behaviour shows how to interpret experimental data on strength andcompression the limited number of books on the subject are all out ofdate

The five-volume set LNCS 3980-3984 constitutes the refereed proceedings of the International Conference on Computational Science and Its Applications, ICCSA 2006. The volumes present a total of 664 papers organized according to the five major conference themes: computational methods, algorithms and applications high performance technical computing and networks advanced and emerging applications geometric modelling, graphics and visualization information systems and information technologies. This is Part I.

With over 1000 references, tables, equations, and illustrations, this reference covers design-motivated modeling and analysis of systems with mechanical, fluid, electrical, thermodynamic, or hybrid components. Creating effective models based on Paynterian bond graphs and constitutive characteristics, it provides case studies, guided problems, numbered and highlighted examples, and numerous assignable problems in every chapter. Offering extensive developments of conventional linear methods, an introduction to automatic control, and the approach of classical vibrations, the author employs a step-by-step pedagogy that makes advanced techniques accessible to introductory courses.

This Research Topic is the fourth volume of the series Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine Volume I: Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume I Volume II:Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume II Volume III:Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume III Analytics based on artificial intelligence has greatly advanced scientific research fields like natural language processing and imaging classification. Clinical research has also greatly benefited from artificial intelligence. Emergency and critical care physicians face patients with rapidly changing conditions, which require accurate risk stratification and initiation of rescue therapy. Furthermore, critically ill patients, such as those with sepsis, acute respiratory distress syndrome, and trauma, are comprised of heterogeneous population. The “one-size-fit-all” paradigm may not fit for the management of such heterogeneous patient population. Thus, artificial intelligence can be employed to identify novel subphenotypes of these patients. These sub classifications can provide not only prognostic value for risk stratification but also predictive value for individualized treatment. With the development of transcriptome providing a large amount of information for an individual, artificial intelligence can greatly help to identify useful information from high dimensional data. Altogether, it is of great importance to further utilize artificial intelligence in the management of critically ill patients.