Vikram Rao – författare

Shale oil and gas have altered the energy landscape, possibly permanently. They burst upon the fossil energy scene with a suddenness that initially defied prediction. Even the political balance of the world has changed. But, with the methods employed, the vast majority of the oil and gas remains in the ground. At the same time, serious environmental impact issues have been raised. A new volume in the Emerging Issues in Analytical Chemistry series, Sustainable Shale Oil and Gas: Analytical Chemistry, Geochemistry, and Biochemistry Methods was written on the premise that analytical methods to inform these areas were wanting. While not attempting to be comprehensive, it describes important analytical methods, some still in development. These methods are underpinned primarily by chemistry, but geochemistry and even biochemistry play significant roles. The book has a solutions flavor; problems are posed together with approaches to ameliorate them.

Provides a clear understanding of the potential environmental issues as well as a path to solutions Includes background information for understanding potential impacts of shale operations from both an environmental and public health perspective Authored by leaders from diverse disciplines with expertise in a variety of areas: groundwater quality, petroleum-related operations, microbial ecology, and electronic technologies Reviews new sensing and evaluation methods that could be key enablers to sustainable fracking: portable mass spectrometry, microbiome analysis, DNA as tracers, and a microparticulate matter detector

Shale oil and gas have altered the energy landscape, possibly permanently. They burst upon the fossil energy scene with a suddenness that initially defied prediction. Even the political balance of the world has changed. But, with the methods employed, the vast majority of the oil and gas remains in the ground. At the same time, serious environmental impact issues have been raised. A new volume in the Emerging Issues in Analytical Chemistry series, Sustainable Shale Oil and Gas: Analytical Chemistry, Geochemistry, and Biochemistry Methods was written on the premise that analytical methods to inform these areas were wanting. While not attempting to be comprehensive, it describes important analytical methods, some still in development. These methods are underpinned primarily by chemistry, but geochemistry and even biochemistry play significant roles. The book has a solutions flavor; problems are posed together with approaches to ameliorate them.- Provides a clear understanding of the potential environmental issues as well as a path to solutions- Includes background information for understanding potential impacts of shale operations from both an environmental and public health perspective- Authored by leaders from diverse disciplines with expertise in a variety of areas: groundwater quality, petroleum-related operations, microbial ecology, and electronic technologies- Reviews new sensing and evaluation methods that could be key enablers to sustainable fracking: portable mass spectrometry, microbiome analysis, DNA as tracers, and a microparticulate matter detector

A title in the Emerging Issues in Analytical Chemistry series, Particulates Matter: Impact, Measurement, and Remediation of Airborne Pollutants provides the latest technical findings in the study of particulate matter (PM). It links these findings to awareness-raising and actionable schemes for legislated remediation and engineered solutions. Written in an engaging and informative manner, the book begins with a multi-disciplinary overview of the major sources and unique classes of PM, detection techniques, and their impact, including molecular changes resulting in health effects. It then goes one step further by proposing and examining the means to curtail and contain PM generation and ameliorate their impacts.

Particulates Matter: Impact, Measurement, and Remediation of Airborne Pollutants offers a high-quality reference guide to PM that will greatly benefit technology leaders in environmental compliance groups, epidemiologists and other public health professionals focused on pollution and health, and researchers and scholars working in pollution, climate change, and urbanization. It may also be useful to advanced undergraduate and�early graduate students in environmental sciences.

Includes a summary of the current knowledge on nanoparticles as pollutants and their negative health effects Provides a framework for the evolution and maturation of air pollution characterization and mitigation Describes an integrated set of engineered solutions that account for the concatenated relationships between technology, policy, and society necessary for long-term success

A title in the Emerging Issues in Analytical Chemistry series, Particulates Matter: Impact, Measurement, and Remediation of Airborne Pollutants provides the latest technical findings in the study of particulate matter (PM). It links these findings to awareness-raising and actionable schemes for legislated remediation and engineered solutions. Written in an engaging and informative manner, the book begins with a multi-disciplinary overview of the major sources and unique classes of PM, detection techniques, and their impact, including molecular changes resulting in health effects. It then goes one step further by proposing and examining the means to curtail and contain PM generation and ameliorate their impacts.Particulates Matter: Impact, Measurement, and Remediation of Airborne Pollutants offers a high-quality reference guide to PM that will greatly benefit technology leaders in environmental compliance groups, epidemiologists and other public health professionals focused on pollution and health, and researchers and scholars working in pollution, climate change, and urbanization. It may also be useful to advanced undergraduate and early graduate students in environmental sciences.- Includes a summary of the current knowledge on nanoparticles as pollutants and their negative health effects- Provides a framework for the evolution and maturation of air pollution characterization and mitigation- Describes an integrated set of engineered solutions that account for the concatenated relationships between technology, policy, and society necessary for long-term success

Epilepsy research promises new treatments and insights into brain function, but statistics and machine learning are paramount for extracting meaning from data and enabling discovery. Statistical Methods in Epilepsy provides a comprehensive introduction to statistical methods used in epilepsy research. Written in a clear, accessible style by leading authorities, this textbook demystifies introductory and advanced statistical methods, providing a practical roadmap that will be invaluable for learners and experts alike.

Topics include a primer on version control and coding, pre-processing of imaging and electrophysiological data, hypothesis testing, generalized linear models, survival analysis, network analysis, time-series analysis, spectral analysis, spatial statistics, unsupervised and supervised learning, natural language processing, prospective trial design, pharmacokinetic and pharmacodynamic modeling, and randomized clinical trials.

Features:

Provides a comprehensive introduction to statistical methods employed in epilepsy research Divided into four parts: Basic Processing Methods for Data Analysis; Statistical Models for Epilepsy Data Types; Machine Learning Methods; and Clinical Studies Covers methodological and practical aspects, as well as worked-out examples with R and Python code provided in the online supplement Includes contributions by experts in the field https://github.com/sharon-chiang/Statistics-Epilepsy-Book/

The handbook targets clinicians, graduate students, medical students, and researchers who seek to conduct quantitative epilepsy research. The topics covered extend broadly to quantitative research in other neurological specialties and provide a valuable reference for the field of neurology.

Epilepsy research promises new treatments and insights into brain function, but statistics and machine learning are paramount for extracting meaning from data and enabling discovery. Statistical Methods in Epilepsy provides a comprehensive introduction to statistical methods used in epilepsy research. Written in a clear, accessible style by leading authorities, this textbook demystifies introductory and advanced statistical methods, providing a practical roadmap that will be invaluable for learners and experts alike.

Topics include a primer on version control and coding, pre-processing of imaging and electrophysiological data, hypothesis testing, generalized linear models, survival analysis, network analysis, time-series analysis, spectral analysis, spatial statistics, unsupervised and supervised learning, natural language processing, prospective trial design, pharmacokinetic and pharmacodynamic modeling, and randomized clinical trials.

Features:

Provides a comprehensive introduction to statistical methods employed in epilepsy research Divided into four parts: Basic Processing Methods for Data Analysis; Statistical Models for Epilepsy Data Types; Machine Learning Methods; and Clinical Studies Covers methodological and practical aspects, as well as worked-out examples with R and Python code provided in the online supplement Includes contributions by experts in the field https://github.com/sharon-chiang/Statistics-Epilepsy-Book/

The handbook targets clinicians, graduate students, medical students, and researchers who seek to conduct quantitative epilepsy research. The topics covered extend broadly to quantitative research in other neurological specialties and provide a valuable reference for the field of neurology.

Epilepsy research promises new treatments and insights into brain function, but statistics and machine learning are paramount for extracting meaning from data and enabling discovery. Statistical Methods in Epilepsy provides a comprehensive introduction to statistical methods used in epilepsy research. Written in a clear, accessible style by leading authorities, this textbook demystifies introductory and advanced statistical methods, providing a practical roadmap that will be invaluable for learners and experts alike.Topics include a primer on version control and coding, pre-processing of imaging and electrophysiological data, hypothesis testing, generalized linear models, survival analysis, network analysis, time-series analysis, spectral analysis, spatial statistics, unsupervised and supervised learning, natural language processing, prospective trial design, pharmacokinetic and pharmacodynamic modeling, and randomized clinical trials.Features:Provides a comprehensive introduction to statistical methods employed in epilepsy researchDivided into four parts: Basic Processing Methods for Data Analysis; Statistical Models for Epilepsy Data Types; Machine Learning Methods; and Clinical StudiesCovers methodological and practical aspects, as well as worked-out examples with R and Python code provided in the online supplementIncludes contributions by experts in the fieldhttps://github.com/sharon-chiang/Statistics-Epilepsy-Book/The handbook targets clinicians, graduate students, medical students, and researchers who seek to conduct quantitative epilepsy research. The topics covered extend broadly to quantitative research in other neurological specialties and provide a valuable reference for the field of neurology.