This volume takes a multidisciplinary approach to study and evaluate the global human vulnerability to the exposure of contaminants of emerging concern (CECs) in the natural environment. It provides a comprehensive resource on structurally diverse groups of chemical compounds that have adverse effects on the aquatic environment. It explores the global strength, environmental status, chemical risk assessment and management strategies of CECs with relevant modern techniques. The principle focus is on concurrent emerging water quality issues. It defines the impacts of the environmental exposure of trace concentrations of CECs and/or their metabolites and discusses possible technological advances to combat the emerging pollutants. It will be useful to researchers, multi-stakeholder expert groups, policymakers, and graduate students.

This volume takes a multidisciplinary approach to study and evaluate the global human vulnerability to the exposure of contaminants of emerging concern (CECs) in the natural environment. It provides a comprehensive resource on structurally diverse groups of chemical compounds that have adverse effects on the aquatic environment. It explores the global strength, environmental status, chemical risk assessment and management strategies of CECs with relevant modern techniques. The principle focus is on concurrent emerging water quality issues. It defines the impacts of the environmental exposure of trace concentrations of CECs and/or their metabolites and discusses possible technological advances to combat the emerging pollutants. It will be useful to researchers, multi-stakeholder expert groups, policymakers, and graduate students.

River Basin Ecohydrology in the Indian Sub-Continent: Sustainable Strategies and Sustenance provides a multidisciplinary approach that focuses on conservation strategies, water quality management in the eco-regions, catchment management practices, estuaries, preservation of in-stream habitat populations, and natural /bioengineering techniques for the sustainable management of ecological resources in the Indian sub-continent. The book provides a unique platform for readers from branches of science and technology, including engineering sciences, agricultural sciences, biogeochemical sciences, hydrogeochemistry, toxicological sciences, social sciences, environmental policy, and governance, etc. to exchange ideas and information at multiple levels on sustainable water management, degradation of marine quality and indicators of ecological degradation. The book's contributors provide impressive and comprehensive information on different management strategies for sustainable restoration of aquatic ecological systems covering vital aspects of hydrogeochemical and geoenvironmental parameters. This book aims to provide a "platform" for scientists and environmental researchers/planners to discuss the environmental degradation, spatial heterogeneity on water quality and aquatic species, methodological approaches on sustainable management of biodiversity, etc.

The book describes the development and performance of proximal classifiers, a class of kernel-based regularized mean square error type classifier that learns within the penalized modeling paradigm. The name proximal classifier indicates the fact of classification of a test pattern by its proximity either to a hyperplane or to a class centroid. The basic idea of the nonparallel plane classifier is to model each class of data by fitting separate hyperplane through it. A computationally efficient binary Nonparallel Plane Proximal Classifier (NPPC) is described in detail along with its nonlinear extension. NPPC is also extended to classify multiclass data. A new approach of multiclass data classification through vector-valued regression technique by the proximity to a class centroid is described in detail. These classifiers are applied to discriminate cancerous tissue samples from gene microarray data. The book provides a complete literature survey in the field of Support Vector Machine (SVM). It includes mathematical models, detailed solution procedures and algorithms of the different proximal classifiers with hands-on examples and well-documented MATLAB programs.