Bentham Science Publishers

This laboratory manual is designed to introduce beginner level researchers to the essential experimental techniques of molecular cloning. With a strong focus on hands-on protocols and a clear, cloning-centric framework, the book simplifies complex methods while building a strong foundation in molecular biology.

Across eight structured chapters, the manual initially covers topics such as laboratory safety and fundamental skills, then progresses through microbiological techniques, DNA isolation and purification, DNA analysis, recombinant DNA construction to clone identification. The final chapter includes detailed appendices outlining standard reagent compositions and preparation methods. Special emphasis is placed on the rationale behind each procedure, making the learning process both practical and conceptually grounded.

Key features:

Explains experimental protocols with step-by-step clarity

Gives rationale and mode of action behind each procedure

Emphasizes critical steps through italicized notes and tips

Provides special information panels for deeper contextual knowledge

Include comprehensive appendices for reagent preparation and reference

A Primer on Earth Pollution: Pollution Types and Disposal, is an encyclopedia of important research articles and short essays on pollution. Chapters in the initial half provide information about a wide variety of pollutants (dyes and microplastics) and contributing factors (thermal pollution and the impact of GM plants, for instance). Each chapter explains the nature of polluting agents and presents notes and references on preventive measures. Notes on the associated clinical complications due to exposure are also proved where applicable, such as the case of MDR bacteria in marine environments. The latter chapters of the book cover the biotechnology of medical waste disposal using microbes as well as nanotechnology used for limiting the spread of COVID-19.

The volume is a handy reference for students and trainees in the field of environmental science as it brings a balance of basic and applied information on the subject of pollution.

Rapid Solidification Processing of molten metals and alloys has proved to be a reliable route for producing new and advanced materials. The Chill-Block Melt Spin (CBMS) technique is important because its simplicity, flexibility and perfection. High quality materials can be produced with lower costs, as compared to other routes, by refining the microstructure and trapping the nucleated (new) metastable phases. Melt-spun ribbons subsequently produced can then be consolidated to produce billets and sheets that can be used in many industries especially high-tech industries such as aerospace and racing automobiles. This book contains several perspectives about CBMS technology and should be a useful review for undergraduate and post-graduate metallurgy students.

AI Innovations in Drug Delivery and Pharmaceutical Sciences: Advancing Therapy through Technology offers a comprehensive exploration of how artificial intelligence (AI) is revolutionizing the pharmaceutical and healthcare sectors. This book addresses the AI’s role in drug discovery, development, and delivery, highlighting applications in personalized medicine, nanotechnology, and clinical trials. It also covers AI’s impact on community and hospital pharmacy, herbal medicine, and drug product design.

Each chapter examines the use of AI in optimizing drug processes, from designing innovative therapies to improving regulatory compliance and future trends in pharmaceutical technology. This insightful resource is invaluable for researchers, pharmaceutical professionals, and healthcare innovators aiming to advance therapeutic outcomes through AI.

Key Features:

- Comprehensive coverage of AI applications in drug discovery, delivery, and design.

- Insights into AI-driven personalized medicine and nanotechnology.

- Regulatory perspectives on AI in drug delivery and medical devices.

- Future trends and innovations in AI for pharmaceutical technology.

This two-part series examines how AI-powered image analysis and IoT-enabled devices enhance diagnostic precision, facilitate real-time monitoring and early detection through connected sensors. Together, these technologies bridge gaps in access, reduce diagnostic subjectivity, and support remote patient care. The books also address vital considerations such as data privacy, security, and ethical implications in digital healthcare. Highlighting both current applications and future directions, the series emphasizes interdisciplinary collaboration to advance AI and IoT-driven dermatology for improved clinical outcomes and equitable healthcare delivery.

Key Features:

Explores the convergence of AI and IoT in skin cancer detection and care.

Highlights advanced imaging, data analytics, and sensor-based monitoring.

Discusses challenges related to privacy, ethics, and healthcare accessibility.

Showcases current research and innovations targeting early and precise diagnosis.

Bridges medical, technological, and policy perspectives for holistic insight.

AI and ML in Early Warning Systems for Natural Disasters bridges the gap between advanced computational models and real-world disaster management practices by highlighting how data-driven intelligence can enhance resilience planning and reduce risks in the face of climate change and extreme environmental events.

Beginning with an overview of traditional early warning systems and the limitations they face in accuracy and timeliness The book sheds light on to AI- and ML-driven approaches, detailing predictive analytics, anomaly detection, sensor networks, geospatial data integration, and IoT-enabled monitoring systems. Case studies on earthquake prediction, flood forecasting, cyclone tracking, and wildfire detection illustrate the practical applicability of AI-powered models across diverse contexts. Later chapters examine legal frameworks, ethical considerations, and community-based strategies that ensure responsible, sustainable, and inclusive deployment of these technologies.

Key Features

Presents AI and ML techniques for predictive analytics, anomaly detection, and risk modeling in disaster scenarios.

Demonstrates real-world applications through case studies on earthquakes, floods, cyclones, and wildfires.

Explores integration of satellite imagery, remote sensing, and IoT-based sensor networks for real-time monitoring.

Assesses legal, regulatory, and ethical frameworks shaping AI use in disaster preparedness.

Provides multidisciplinary insights, blending computer science, engineering, and disaster management for resilient community planning.

Positioned at the intersection of intelligent transportation systems (ITS), computer vision, and machine learning, this book presents a comprehensive examination of how artificial intelligence and statistical techniques are reshaping traffic monitoring, management, and urban mobility in the era of smart cities.

The book begins with the core principles of AI and traffic systems, introducing statistical modeling, data acquisition, and image processing for traffic analysis. Midway, it transitions into deep learning-powered applications such as object detection, vehicle tracking, congestion forecasting, and real-time incident recognition. Later sections address legal, regulatory, and ethical frameworks, while concluding chapters highlight IoT-enabled models and future trajectories in AI-powered traffic management.

Key Features:

Introduces principles of AI, machine learning, and statistical modeling for traffic systems

Demonstrates applications of deep learning in congestion prediction, incident detection, and vehicle tracking

Examines AI-driven traffic optimization, urban mobility solutions, and self-driving technologies

Evaluates security, data privacy, and legal considerations in AI-based traffic surveillance

Integrates AI with IoT frameworks for real-time monitoring in smart city infrastructure

Highlights future directions and policy implications for sustainable and ethical traffic management.

AIoT (Artificial Intelligence of Things) and Big Data Analytics are catalyzing a healthcare revolution. This book is an accessible volume that summarizes the information available. In this book, researchers explore how AIoT and Big Data can seamlessly integrate into healthcare, enhancing medical services and devices while adhering to established protocols. The book demonstrates the crucial role of these technologies during healthcare crises like the COVID-19 pandemic. It presents novel solutions and computational techniques powered by AIoT, Machine Learning, and Deep Learning, providing a new frontier in healthcare problem-solving.

Key Features:

Real-Life Illustrations: Real-world examples showcase AIoT and Big Data in action, highlighting their impact in healthcare.

Comprehensive Exploration: The book offers a thorough examination of AIoT, Big Data, and their harmonious synergy within the healthcare landscape.

Visual Aids: Complex concepts become approachable through diagrams, flowcharts, and infographics, making technical processes and system designs more digestible.

Ethical Insights: Delving into the ethical dimensions of AIoT and Big Data, it addresses concerns like data bias, patient consent, and transparency in healthcare.

Forward-Looking Discourse: The book engages with emerging trends, potential innovations, and the future direction of AIoT and Big Data, making it a compass for healthcare transformation.

Researchers, whether from academia, industry, or research and development organizations, interested in AIoT, Big Data, artificial intelligence, and healthcare optimization, will find this book informative. It also serves as an update for tech enthusiasts who want to explore the future of healthcare powered by AI and data.

Abdominal pain is one of the frequent reasons for admission to emergency departments in hospitals. Diagnosis in patients presenting abdominal pain is a challenge for physicians owing to several indications, and a lack of contraindications. Delay in diagnosis and misdiagnosis is a common problem even for the most experienced emergency physician or general surgeon. Disruptions that may be related to ancillary services such as radiology and biochemistry also increase the difficulty. Abdominal Pain: Essential Diagnosis and Management in Acute Medicine is a definitive diagnosis guide that serves as a quick reference that supplements medical examinations.

It gives physicians involved in a range of medical specialties (emergency medicine, family medicine, gastroenterology, general surgery) an understanding of how to apply procedures to expediently relieve pain where possible, after evaluating and recording the initial vital signs and findings on systemic examination.

Key Features:

- Covers abdominal pain diagnosis and patient management patient in a systematic and structured manner in 12 chapters

- Chapters are dedicated to specific topics

- Presents an individualized approach tailored for the patient to address common problems

- Gives general working knowledge for specific diseases in the list of possible diagnoses

- Provides a guide to situations involving trauma and surgery

This Ebook brings together the latest developments and studies of Mobile Ad Hoc Networks (MANETs) and Wireless Sensor Networks (WSNs), which should provide a seedbed for new breakthroughs. It focuses on the most representative topics in MANETs and WSNs, such as energy-efficient routing, backbone construction, multicast/broadcast, resource allocation, data gathering/aggregation, sensor coverage, target tracking, and so on. This Ebook is suitable for scholars, researchers and developers to grasp the most updated work in MANETs and WSNs. Moreover, the Ebook is a valuable companion and comprehensive reference for graduate students who are taking a course in wireless networking. Compared with existing books in the field, this Ebook focuses on general architectures, algorithms and protocols for both MANETs and WSNs, and covers heterogeneous networks where sensors are co-existing with ad hoc nodes.