Yan Du – författare

Contributions by Yoshiko Akamatsu, Carol L. Beran, Rita Bode, Lesley D. Clement, Allison McBain Hudson, Kate Lawson, Jessica Wen Hui Lim, Lindsey McMaster, E. Holly Pike, Katharine Slater, Margaret Steffler, and Anastasia UlanowiczLucy Maud Montgomery (1874–1942) was a Canadian author best known for writing the wildly popular Anne of Green Gables. At the time of its publication in 1908, it was an immediate bestseller and launched Montgomery to fame. Less known than the dreamy and accidentally mischievous Anne Shirley is Emily Byrd Starr, the title character in the trilogy that followed much later in Montgomery’s professional career, Emily of New Moon. Published in 1923, Emily of New Moon is the first in a series of novels about an orphan girl growing up on Prince Edward Island, a story that mirrors Anne’s but intentionally resists many of the defining qualities of Montgomery's most famous creation. Despite being overshadowed by the immense popularity of Anne of Green Gables, the Emily of New Moon trilogy has become a subject of endless fascination to fans and scholars around the world. The trilogy was conceived during an important phase in Montgomery’s career during which she turned from Anne and plunged into more intricate aspects of gender, adolescence, nature, and authorship. While the novels have attracted rich critical attention since their publication, book-length studies proved surprisingly scarce. L. M. Montgomery’s "Emily of New Moon": A Children’s Classic at 100 is the first scholarly volume exclusively dedicated to the trilogy, coalescing different research perspectives. It offers a fresh point of entrance into a well-loved classic at its one-hundredth anniversary.

Contributions by Yoshiko Akamatsu, Carol L. Beran, Rita Bode, Lesley D. Clement, Allison McBain Hudson, Kate Lawson, Jessica Wen Hui Lim, Lindsey McMaster, E. Holly Pike, Katharine Slater, Margaret Steffler, and Anastasia UlanowiczLucy Maud Montgomery (1874–1942) was a Canadian author best known for writing the wildly popular Anne of Green Gables. At the time of its publication in 1908, it was an immediate bestseller and launched Montgomery to fame. Less known than the dreamy and accidentally mischievous Anne Shirley is Emily Byrd Starr, the title character in the trilogy that followed much later in Montgomery’s professional career, Emily of New Moon. Published in 1923, Emily of New Moon is the first in a series of novels about an orphan girl growing up on Prince Edward Island, a story that mirrors Anne’s but intentionally resists many of the defining qualities of Montgomery's most famous creation. Despite being overshadowed by the immense popularity of Anne of Green Gables, the Emily of New Moon trilogy has become a subject of endless fascination to fans and scholars around the world. The trilogy was conceived during an important phase in Montgomery’s career during which she turned from Anne and plunged into more intricate aspects of gender, adolescence, nature, and authorship. While the novels have attracted rich critical attention since their publication, book-length studies proved surprisingly scarce. L. M. Montgomery’s "Emily of New Moon": A Children’s Classic at 100 is the first scholarly volume exclusively dedicated to the trilogy, coalescing different research perspectives. It offers a fresh point of entrance into a well-loved classic at its one-hundredth anniversary.

A sweet story about the importance of self-care and having a place of one’s own.Po is a small girl living in a BIG, loud city who has always had to share her favorite relaxing retreat—her bathroom—with her busy family. But when a mysterious visitor arrives one night, everything changes. Po’s bathroom is a place where she can be herself, enjoy quiet time, and do anything she dreams of: put on shows, dance and sing, and create whatever she imagines. But her mom, dad, and brother always barge in and interrupt her alone time. She wishes for a sanctuary all her own. Then one night, Lady Violet, a beautiful toilet guardian, appears with a magical gift. Things for Po will never be the same. But maybe she isn’t the only one who needs her very own private bathroom.Author Yan Du and illustrator Erin Vanessa bring to life a sweet story about the importance of self-care and having a place of one’s own.

This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control.Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers.Provides a history of AI in power grid operation and planning;Introduces deep learning algorithms and applications in power systems;Includes several representative case studies.

This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control.Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers.Provides a history of AI in power grid operation and planning;Introduces deep learning algorithms and applications in power systems;Includes several representative case studies.

This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control.Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers.Provides a history of AI in power grid operation and planning;Introduces deep learning algorithms and applications in power systems;Includes several representative case studies.

Comprehensive overview of the various diagnosis techniques employed in disease detection and public health crisis management Diagnostic Techniques in Public Health: Analytical and Chemometric Approaches in Disease Detection and Management explores the roles of advanced chemometric approaches and modern diagnostic tools in addressing complex analytical challenges in global health. The book provides a systematic examination of major international public health emergencies, including COVID-19 and Monkeypox, as defined by the World Health Organization. This volume brings together carefully curated chapters that integrate perspectives from molecular biology, analytical chemistry, nanotechnology, biomedical engineering, and informatics, addressing how diagnostic science can evolve to meet the demands of a rapidly changing and interconnected world. Diagnostic Techniques in Public Health provides in-depth coverage of representative topics, including: Molecular diagnostic technologies, ranging from classical polymerase chain reaction to next-generation isothermal amplification methodsELISA-based immunoassays and genomic sequencing as key tools for pathogen surveillanceEmerging technologies such as CRISPR-based diagnostics and microfluidic systems enabling high automation, multiplexing, and reagent efficiencyPlasmonic biosensors and flexible bioelectronics, highlighting advances toward non-invasive, continuous, and personalized health monitoringBridging advanced analytical methodologies with public health applications, Diagnostic Techniques in Public Health serves as a valuable reference for analytical, medicinal, and pharmaceutical chemists, molecular biologists, and public health professionals.

Comprehensive overview of the various diagnosis techniques employed in disease detection and public health crisis management Diagnostic Techniques in Public Health: Analytical and Chemometric Approaches in Disease Detection and Management explores the roles of advanced chemometric approaches and modern diagnostic tools in addressing complex analytical challenges in global health. The book provides a systematic examination of major international public health emergencies, including COVID-19 and Monkeypox, as defined by the World Health Organization. This volume brings together carefully curated chapters that integrate perspectives from molecular biology, analytical chemistry, nanotechnology, biomedical engineering, and informatics, addressing how diagnostic science can evolve to meet the demands of a rapidly changing and interconnected world. Diagnostic Techniques in Public Health provides in-depth coverage of representative topics, including: Molecular diagnostic technologies, ranging from classical polymerase chain reaction to next-generation isothermal amplification methodsELISA-based immunoassays and genomic sequencing as key tools for pathogen surveillanceEmerging technologies such as CRISPR-based diagnostics and microfluidic systems enabling high automation, multiplexing, and reagent efficiencyPlasmonic biosensors and flexible bioelectronics, highlighting advances toward non-invasive, continuous, and personalized health monitoring Bridging advanced analytical methodologies with public health applications, Diagnostic Techniques in Public Health serves as a valuable reference for analytical, medicinal, and pharmaceutical chemists, molecular biologists, and public health professionals.

Comprehensive overview of the various diagnosis techniques employed in disease detection and public health crisis management Diagnostic Techniques in Public Health: Analytical and Chemometric Approaches in Disease Detection and Management explores the roles of advanced chemometric approaches and modern diagnostic tools in addressing complex analytical challenges in global health. The book provides a systematic examination of major international public health emergencies, including COVID-19 and Monkeypox, as defined by the World Health Organization. This volume brings together carefully curated chapters that integrate perspectives from molecular biology, analytical chemistry, nanotechnology, biomedical engineering, and informatics, addressing how diagnostic science can evolve to meet the demands of a rapidly changing and interconnected world. Diagnostic Techniques in Public Health provides in-depth coverage of representative topics, including: Molecular diagnostic technologies, ranging from classical polymerase chain reaction to next-generation isothermal amplification methodsELISA-based immunoassays and genomic sequencing as key tools for pathogen surveillanceEmerging technologies such as CRISPR-based diagnostics and microfluidic systems enabling high automation, multiplexing, and reagent efficiencyPlasmonic biosensors and flexible bioelectronics, highlighting advances toward non-invasive, continuous, and personalized health monitoring Bridging advanced analytical methodologies with public health applications, Diagnostic Techniques in Public Health serves as a valuable reference for analytical, medicinal, and pharmaceutical chemists, molecular biologists, and public health professionals.

This book highlights cutting-edge research into emergency early warning management and decision-making for severe accidents. Using toxic gas leakages as examples, it puts forward new design methods for emergency early warning systems, as well as a systematic description of emergency early warning information communication mechanisms and characteristics of regional evacuation, based on a wide range of theories, including safety engineering, information engineering, communication, behaviorology and others. The book applies a range of methods, such as case analysis, questionnaire interviews, and multi-objective optimization modeling. Drawing on this basis, it subsequently proposes a multi-objective optimization modeling and algorithm for emergency path selection, together with an evacuation risk assessment method. Divided into six chapters prepared by an international team of researchers, the book addresses the design of early warning systems, communication and dissemination mechanismsof early warning information, characteristics of regional evacuation, multi-objective optimization of emergency paths, and evacuation risk assessment. ­­­­­The book offers an essential reference guide for engineering technicians and researchers in a wide range of fields, including emergency management, safety science and engineering, disaster relief engineering, and transportation optimization, as well as graduate students in related majors at colleges and universities.