Bentham Science Publishers

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.

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.

The management of COVID-19 is challenging due to the lack of clear information about the Sars-Cov2 and recommendations for specific treatment regimens. The scale of the pandemic has also exacerbated the situation, with health care systems under stress from the high volume of COVID-19 patients.

In Demystifying COVID-19: Understanding the Disease, Its Diagnosis, and Treatment, medical experts explain many aspects about the COVID-19 pandemic, including guidelines to minimize risk of infection, diagnostic methods, treatment, real scenarios in the course of the disease and issues that need attention in specific patient groups. The book equips both general readers and healthcare professionals with key information required to understand COVID-19 and navigate a situation typical to a pandemic. Public health officials who wish to mobilize awareness campaigns for the benefit of the general public can also find value in the comprehensive information presented in this reference.

Demystifying Emerging Trends in Machine Learning (Volume 2) offers a deep dive into emerging and trending topics in the field of machine learning (ML). This edited volume showcases several machine learning methods for a variety of tasks. A key focus of this volume is the application of text classification for cybersecurity, E-commerce, sentiment analysis, public health and web content analysis.

The 49 chapters highlight a wide variety of machine learning methods including SVNs, K-Means Clustering, CNNs, DCNNs, among others. Each chapter includes accessible information through summaries, discussions and reference lists. This comprehensive volume is essential for students, researchers, and professionals eager to understand the emerging trends reshaping machine learning today.

Depression is considered as a complex problem with potentially serious economic consequences for affected individuals as well as public healthcare systems. There is much debate among laypersons, patients, academics and clinicians about the causes of depression, its clinical significance and the effect of conventional medical interventions such as antidepressants. This monograph showcases some aspects of depression through specific reviews on some of the intricacies behind its mechanism. The book includes five reviews on the subject, covering the significance of depression in patient well-being, an update on P300 wave findings and the link with clinical depression, the genomics behind depression, the effects of ageing on the onset of depression in stroke patients, and tensor imaging techniques used in studies on patients exhibiting suicidal behaviors as a result of major depressive disorder.

This reference provides useful updates for healthcare workers, neuroscientists and behavioral scientists interested in basic research on depression and in planning to develop methods to study depression in either a clinical or laboratory setting

This book is an essential guide to analysis and design of tall buildings and foundations. The book covers the basic consideration of tall buildings, selection of a suitable structural form, structural materials, and analytical methods for several types of construction loadings. The last chapter of this book presents an illustrated case study for learners. An appendix of different structural analysis calculations rounds up the book. The detailed analysis and learning material presented in the book is intended to enable readers to master the basics and understand how to execute practical civil engineering projects.

Key features:

- Covers the essentials of skyscraper design and construction in detail with a focus on learning.

- Covers building modelling parameters and criteria with design reports and computer inputs.

- Includes analysis and notes for foundation layout, loadings and the excavation and lateral support system (ELS).

- Includes more than 250 detailed illustrations of concepts, construction plans and photos from real projects.

- Includes references and appendices for advanced readers.

- Includes more details than most of the similar texts, with practical guidelines based on references from many buildings and foundation projects.

The authors have extensive research and practical experience of buildings and foundation analysis and design in Hong Kong, and have actively served as regional engineering committee members overseeing structural and foundation disciplines.