Bentham Science Publishers

Current and Emerging Concepts of Polycystic Ovary Syndrome – Manual from M.P. PCOS Society is a comprehensive and authoritative guide that explores the multifaceted nature of PCOS, redefining the understanding, diagnosis, and management of Polycystic Ovary Syndrome (PCOS).

Drawing upon cross-disciplinary insights and multi-institutional expertise, this two-part series unravels its epidemiology, diagnostic complexities, and phenotypic diversity. It dives deep into hormonal, metabolic, genetic, and environmental dimensions to present an integrated view of the syndrome. It presents PCOS not as a single disorder, but as an evolving clinical spectrum. It serves as both a foundation for clinicians and a catalyst for future research, setting the stage for Volume II, which expands into advanced management and innovative therapeutic paradigms.

Key Features

Examines the global epidemiology, pathophysiology, and heterogeneity of PCOS.

Clarifies diagnostic criteria and phenotypic variations through evidence-based insights.

Explores hormonal, metabolic, genetic, and environmental mechanisms driving PCOS.

Integrates emerging concepts from microbiome science, endocrinology, and mental health.

Highlights the evolving clinical understanding shaped by interdisciplinary collaboration.

This reference describes recent advances and applications of capillary electrophoresis in the field of food science. The first two chapters are devoted to the fundamentals of capillary electrophoresis, and to the main sample preparation techniques used for food analysis using this miniaturized separation technique, respectively. These two introductory chapters are followed by several chapters focused on the different strategies for analyzing specific food components, including lipids, carbohydrates, proteins, peptides, amino acids, vitamins, polyphenols, and food additives.

The information provided in these chapters helps readers to understand and develop appropriate methods to carry out a deep characterization of food samples. Relevant concepts such as food authentication, chemical food safety or the control of the quality and safety of dietary supplements, and food metabolomics are also covered, where appropriate. The big potential of capillary electrophoresis to achieve chiral separations and the determination of enantiomers in food samples or to develop targeted and non-targeted metabolomics strategies to ensure food safety and quality is also described. As an additional step towards analytical miniaturization, a chapter devoted to food analysis by microchip electrophoresis is also included in this book. All 14 chapters are contributed by highly experienced researchers in the field.

Capillary Electrophoresis in Food Analysis is a key source of information for food chemists and analytical chemists in industry (quality control laboratories) and academia (research labs and training courses).

Cancer is a broad group of diseases involving unregulated cell growth with elevated death rates as more people live in old age with mass lifestyle changes occurring in the world. The causes of cancer are diverse, complex, and still only partially understood. The chances of surviving the disease vary remarkably by the type and location of the malignancy and the extent of disease at the start of treatment. Early cancer detection is proving to be a valid approach. Cancer can be detected in a number of ways, including the presence of certain signs and symptoms, screening tests, or medical imaging. Cancer therapy is dynamically changing and revision and change in patient management is constant as our knowledge increases. Cancer is routinely treated with chemotherapy, radiation therapy and surgery. Tailored cancer targeted therapy is becoming an emerging objective of today. In this book, a constructive group of cancer research experts bring the reader their shared vision, to give an extensive and realistic view of individual tumors such as breast, oral, prostate, gastric, and neuroendocrine tumors. New and contemporary terms and concepts in genetics and epigenetics, diet, anticancer treatments, and anticancer drug delivery systems are introduced in this volume. This reference highlights present experimental strategies and key findings that enhance our understanding of cancer and of future therapies. This eBook is aimed at a broad audience of undergraduates, medical students, PhDs, cancer researchers, and also cancer patient families with the goal to conceive a curiosity about the subjects presented that will hopefully lead to further studies.

Cutting-Edge Solutions for Advancing Sustainable Development: Exploring Technological Horizons for Sustainability - Part 2 introduces innovative approaches to achieving sustainability through technological advancements. This comprehensive guide covers critical global challenges such as climate change and resource depletion, emphasizing the transformative role of emerging technologies.

Key Features:

- Detailed exploration of blockchain applications in supply chains and financial services.

- Innovations in HealthTech improving healthcare accessibility and quality.

- Utilization of AI for climate action and precision agriculture.

- Advancements in renewable energy technologies, focusing on solar and wind.

- Societal impacts of AI automation and financial literacy in technologically enhanced learning environments.

The book gives a comprehensive overview of the evolving landscape of cyber-physical systems (CPS) with a primary focus on security challenges and innovative solutions. CPS, encompassing a wide array of applications from e-Health to smart grid and industry automation, is explored in depth through eight edited reviews.

The book starts with an exploration of various threat detection and prevention techniques in IoT environments, followed by discussions on security in smart grid cyber-physical systems, and the integration of cyber-physical systems with game theory. It also covers important topics such as cyber-physical systems in healthcare, augmented reality challenges, network and computer forensic frameworks, and a review of industrial critical infrastructure perspectives.

The journey from traditional data warehouses to data lakes is thoroughly examined, shedding light on the evolution of data storage methods. The final chapter explains intrusion detection in industrial critical infrastructure, reviewing feature selection and classification models. By navigating through these topics, the book equips readers with a comprehensive understanding of cybersecurity challenges and solutions in an era of automation and IoT technologies.

This book is intended for a diverse readership, including professionals, researchers, and technology enthusiasts keen on exploring the intricacies of CPS, IoT security, data storage evolution, and industrial infrastructure protection.

Key Features:

-Analytical insights into cyber-physical systems security.

-Thorough exploration of threat detection and prevention techniques.

-Application-focused chapters covering smart grid, healthcare, and more.

-Integration of game theory and augmented reality in cyber-physical systems.

-Comprehensive overview on network and computer forensic frameworks.

DFT-Based Studies On Atomic Clusters explores the structures, properties, and applications of a variety of atomic clusters using density functional theory (DFT) methods to offer a simple and comprehensive explanation of the subject.

The book is organized into seven chapters. Chapter 1 introduces atomic clusters and provides a quick survey of density functional theory and its role in the study of atomic clusters. Chapter 2 discusses the optimization of atomic clusters using various algorithms. Chapters 3, 4, and 5 cover the applications of DFT methods on chemical interactions involving metal complexes and ions. Chapter 6 is devoted exclusively to molecular clusters for completeness. Chapter 7 concludes the book and provides a perspective on future directions on the subject.

Theoretical and practical concepts of DFT methods of the book are systematically and concisely presented with the help of clear language. Several illustrations in the form of graphics and tables are included for the benefit of readers.

This reference is intended as a guide for advanced graduate and doctorate level scholars, postdoctoral researchers, and faculty members who are required to understand the application of density functional theory for explaining the properties of atomic clusters as part of foundational coursework or supplementary reading.

Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0 unites data science, machine learning, IIOT, and AI to enable predictive and prescriptive maintenance across manufacturing, energy, transportation, agriculture, and healthcare. With contributions from leading academics and practitioners, the book bridges foundational principles with cutting-edge industrial case studies ranging from digital twins and anomaly detection to federated learning and secure healthcare analytics.

Key Features

Explains fundamental concepts of data analytics, AI, and machine learning for predictive maintenance.

Integrates IIoT, digital twins, federated learning, and blockchain into industrial maintenance strategies.

Demonstrates real-world applications across manufacturing, energy, healthcare, and agriculture sectors.

Analyzes optimization techniques, anomaly detection, condition monitoring, and RUL prediction models.

Addresses security and ethical issues, including hardware protection and homomorphic encryption for healthcare.

Maps future trends and emerging technologies driving predictive maintenance research.

Data Recovery Techniques for Computer Forensics is a practical and comprehensive reference designed for professionals, students, and researchers in digital forensics, data recovery, and information security. This handbook provides clear, structured guidance on essential principles and practical techniques for recovering lost or compromised digital data in forensic investigations.

The book begins with the fundamentals of data recovery and examines the major causes of data loss, including software errors and hardware failures. It then explores contemporary data protection technologies and delves into the structure and organization of hard disks, laying a solid foundation for understanding data storage systems.

Specialized chapters cover the recovery and management of various file systems, including FAT16, FAT32, and NTFS, along with methods for partition recovery and an introduction to dynamic disk management. The final section introduces essential data security software used to protect and recover digital information.

Key Features

Covers basic and applied data recovery concepts for forensic applications

Explains causes of data loss and modern data protection technologies

Detailed chapters on hard disk structure, data organization, and partition recovery

Practical guidance on managing and recovering FAT16, FAT32, and NTFS file systems

Introduces dynamic disk configurations and essential data security tools

Data Science for Agricultural Innovation and Productivity explores the transformation of agriculture through data-driven practices. This comprehensive book delves into the intersection of data science and farming, offering insights into the potential of big data analytics, machine learning, and IoT integration. Readers will find a wide range of topics covered in 10 chapters, including smart farming, AI applications, hydroponics, and robotics. Expert contributors, including researchers, practitioners, and academics in the fields of data science and agriculture, share their knowledge to provide readers with up-to-date insights and practical applications. The interdisciplinary emphasis of the book gives a well-rounded view of the subject. With real-world examples and case studies, this book demonstrates how data science is being successfully applied in agriculture, inspiring readers to explore new possibilities and contribute to the ongoing transformation of the agricultural sector. Sustainability and future outlook are the key themes, as the book explores how data science can promote environmentally conscious agricultural practices while addressing global food security concerns. Key Features: - Focus on data-driven agricultural practices - Comprehensive coverage of modern farming topics with an interdisciplinary perspective - Expert insights - Sustainability and future outlook -Highlights practical applications Data Science for Agricultural Innovation and Productivity is an essential resource for researchers, data scientists, farmers, agricultural technologists, students, educators, and anyone with an interest in the future of farming through data-driven agriculture.

Decolorization by Thanatephorus cucumeris Dec 1 explores the innovative use of the newly isolated fungal strain Dec1 in the biodegradation of recalcitrant colored substances produced by various industries. The book details the purification and characterization of key enzymes responsible for Dec1's activity, including peroxidases, aryl alcohol oxidase, and the newly discovered TcVP1. It highlights the successful cloning and high-yield production of recombinant DyP (rDyP) through a transformed Aspergillus oryzae, as well as the development of an optimized immobilization and H2O2 supply system to prevent rDyP inactivation.

The application of Thanatephorus cucumeris Dec 1 in treating kraft pulp bleaching effluent is discussed, demonstrating its effectiveness in removing colored substances and chlorinated organic compounds. This book is an essential resource for students tackling environmental challenges and engineers focused on innovative microbial solutions for the treatment of colored industrial effluents.