Bentham Science Publishers

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 Management and Security in Blockchain Systems offers a comprehensive exploration of how blockchain technology is reshaping the landscape of data management and security. This book addresses key aspects of blockchain-based systems, including data integrity, transparency, and tamper resistance, making it an essential resource for students, researchers, and professionals.

Covering topics from blockchain-enabled IoT traffic management to the integration of AI for enhanced security, this book presents solutions to current challenges such as cyberattacks, smart grid security, and scalable network designs. Each chapter is thoughtfully structured to provide readers with a solid understanding of blockchain applications in diverse domains. Perfect for those seeking to understand blockchain's potential to secure and manage data in an increasingly interconnected world.

Key Features:

- Comprehensive overview of data management and security in blockchain networks.

- Practical insights into IoT, smart grids, and AI integration.

- In-depth analysis of cybersecurity challenges and solutions.

Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields.

Key Themes:

Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting.

Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis.

Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity.

Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture.

Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities.

Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments.

Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face.

Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis.

Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data.

Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics.

This volume bridges the gap between data science and interdisciplinary research, making it a valuable resource for researchers, academics, and professionals seeking to leverage cutting-edge technologies for transformative applications.

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.

This book is a detailed reference guide on deep learning and its applications. It aims to provide a basic understanding of deep learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters contributed by computer science academics and researchers. By the end of the book, the reader will become familiar with different deep learning approaches and models, and understand how to implement various deep learning algorithms using multiple frameworks and libraries. The second part is dedicated to sentiment analysis using deep learning and machine learning techniques. This book section covers the experimentation and application of deep learning techniques and architectures in real-world applications. It details the salient approaches, issues, and challenges in building ethically aligned machines. An approach inspired by traditional Eastern thought and wisdom is also presented. The final part covers artificial intelligence approaches used to explain the machine learning models that enhance transparency for the benefit of users. A review and detailed description of the use of knowledge graphs in generating explanations for black-box recommender systems and a review of ethical system design and a model for sustainable education is included in this section. An additional chapter demonstrates how a semi-supervised machine-learning technique can be used for cryptocurrency portfolio management. The book is a timely reference for academicians, professionals, researchers and students at engineering and medical institutions working on artificial intelligence applications.

Demystifying Emerging Trends in Green Technology explores the transformative intersection of computational intelligence, disruptive technologies, and green innovations. This volume offers insights into diverse fields such as blockchain, IoT, artificial intelligence, machine learning, and sustainable development. Each chapter presents cutting-edge research and practical solutions addressing environmental sustainability, energy efficiency, and eco-friendly technologies.

With contributions from leading researchers, this book discusses advancements like blockchain-based security, green marketing, smart waste management, sustainable agriculture, and innovative healthcare solutions. It emphasizes the role of interdisciplinary approaches in driving a greener and smarter future.

Key Features:

- Integration of AI, IoT, and blockchain in sustainable systems

- Applications in healthcare, agriculture, energy, and environmental science

- Practical and innovative solutions for real-world challenges

- Insights into future trends in green technology and disruptive innovation