Bentham Science Publishers

Anthropogenic changes in the environment, caused by 250 years of economic growth and utilization of fuel and mineral resources, have considerably impacted the natural environment. The resulting physical and chemical alterations to the Earth's sphere and our adaptive responses in the biosphere are detailed in this reference book. Readers will learn about concepts relevant to Earth’s history, the evolution of life, economy, ecology, environmental history, biology, and medicine and how these concepts can be linked to environmental change. The scope of this interdisciplinary work entails to convey the true degree of responsibility for the universal consequences of ecosystem degradation resulting from industrial processing, human consumption and the transformation of natural sites due to industrialization and urbanization.

Topics covered in the book include:

-Ecosystem transformations by natural and anthropogenic forces

-The Anthropocene epoch

-A short history of industrialization

-Environmental sites and the impact of socio-economic influences

-The current environmental crisis,

This textbook is intended for graduate students in economics, civil engineering, architecture, agronomics, forestry, technical and mining sciences, political sciences, business studies and humanities. General readers who wish to understand the basic philosophy behind environmental studies and their relation to human activity can also benefit from this book.

2D Materials: Chemistry and Applications, Part 2 addresses the cutting-edge advancements in the synthesis, functionalization, and applications of two-dimensional materials, focusing on graphene and other emerging materials like boron nitride, germanene, silicene, and stanene. This volume explores the potential of these materials in energy storage, nanoelectronics, waste management, and more, while addressing challenges like toxicity and cost-effective production.

The book highlights innovative approaches to graphene-based supercapacitors, nanoparticle-functionalized graphene, and the application of 2D materials in diverse fields. It also provides insights into the toxicity and remediation strategies of graphene family materials and outlines the roadmap for sustainable graphene production.

This book is ideal for researchers, academics, and professionals in materials science, nanotechnology, chemistry, and environmental engineering.

Key Features:

Advanced applications of graphene-based supercapacitors.

Functionalization and applications of boron nitride, germanene, silicene, and stanene.

Insights into graphene toxicity and remediation approaches.

Roadmap for cost-effective graphene production and waste management.

Congenital heart defects (CHD) are the most frequent malformation in the human fetus and are the leading cause of mortality due to malformations in the first year of life. Despite its clinical importance screening performed by ultrasonographic examination during the second trimester of pregnancy has shown disappointingly low detection rates mainly due to the difficulties in obtaining an adequate examination of the fetal heart. Four-dimensional (4D) ultrasound of the fetal heart has been recently suggested as a tool to improve the detection rate of CHD by decreasing the dependency on operator skills required in two-dimensional ultrasound scans but up to now no practical manuals are available in describing its application in clinical practice for the study of fetal heart. The objective of this Ebook is to explain the role of 4D during second trimester examination and in fetuses with CHD. T

A Blueprint for the Hard Problem of Consciousness addresses the fundamental mechanism that allows physical events to transcend into subjective experiences, termed the Hard Problem of Consciousness. Consciousness is made available as the abstract product of self-referent realization of information by strange loops through the levels of processing of the brain.

Readers are introduced to the concept of the Hard Problem of Consciousness and related concepts followed by a critical discourse of different theories of consciousness. Next, the author identifies the fundamental flaw of the Integrated Information Theory (IIT) and proposes an alternative that avoids the cryptic intelligent design and panpsychism of the IIT. This author also demonstrates how something can be created out of nothing without resorting to quantum theory, while pointing out neurobiological alternatives to the bottom-up approach of quantum theories of consciousness.

The book then delves into the philosophy of qualia in different physiological knowledge networks (spatial, temporal and olfactory, cortical signals, for example) to explain an action-based model consistent with the generational principles of Predictive Coding, which maps prediction and predictive-error signals for perceptual representations supporting integrated goal-directed behaviors. Conscious experiences are considered the outcome of abstractions realized out of map overlays and provided by sustained oscillatory activity.

The key feature of this blueprint is that it offers a perspective of the Hard Problem of Consciousness from the point of view of the subject; the experience of ‘being the subject’ is predicted to be the realization of inference inversely mapped out of hidden causes of global integrated actions. The author explains the consistencies of his blueprint with ideas of the Global Neuronal Workspace and the Adaptive Resonance Theory of consciousness as well as with the empirical evidence supporting the Integrated Information Theory.

A Blueprint for the Hard Problem of Consciousness offers a unique perspective to readers interested in the scientific philosophy and cognitive neuroscience theory in relation to models of the theory of consciousness.

This handbook explains the application of nanoparticles in medical diagnosis and treatment. It is a ready reference on the subject, starting with the introduction to nanoparticles and progressing to synthetic procedures for nanotherapeutics, human disease diagnosis and nanocarrier-based drug delivery. The book also covers information about specific nanoparticle conjugates, in which nanoparticles are combined with drugs or nucleic acid strands (DNA, siRNAs, shRNAs, miRNAs) as well as topics of relevant to this field such as immunotherapy and vaccination development strategies. Each chapter also provides references for further reading.

A Comprehensive Guide to Nanoparticles in Medicine is an ideal resource for scholars in medicine, pharmacology and technology who require an understanding to some basic facets of nanoparticles.

This reference demonstrates the development of a context aware decision-making health informatics system with the objective to automate the analysis of human centric wellness and assist medical decision-making in healthcare.

The book introduces readers to the basics of a clinical decision support system. This is followed by chapters that explain how to analyze healthcare data for anomaly detection and clinical correlations. The next two sections cover machine learning techniques for object detection and a case study for hemorrhage detection. These sections aim to expand the understanding of simple and advanced neural networks in health informatics. The authors also explore how machine learning model choices based on context can assist medical professionals in different scenarios.

Key Features :

-Reader-friendly format with clear headings, introductions and summaries in each chapter

-Detailed references for readers who want to conduct further research

-Expert contributors providing authoritative knowledge on machine learning techniques and human-centric wellness

-Practical applications of data science in healthcare designed to solve problems and enhance patient wellbeing

-Deep learning use cases for different medical conditions including hemorrhages, gallbladder stones and diabetic retinopathy

Demonstrations of fast and efficient CNN models with varying parameters such as Single shot detector, R-CNN, Mask R-CNN, modified contrast enhancement and improved LSTM models.

This reference is intended as a primary resource for professionals, researchers, software developers and technicians working in healthcare informatics systems and medical diagnostics. It also serves as a supplementary resource for learners in bioinformatics, biomedical engineering and medical informatics programs and anyone who requires technical knowledge about algorithms in medical decision support systems.

A Crisis Like No Other: Understanding and Defeating Global Warming couples engaging and creative storytelling with accurate details to explain global warming.

It covers both the technical and human issues of global warming by addressing what's causing global warming, and why people don't believe it exists. The book tells readers how to convince others that global warming is not only real, but life-threatening, and offers a clearly laid out path to solve it. The book is accurate and carefully researched, drawing on the author's thirty years of studying the science of global warming, and the human psyche that surrounds it. The author breaks down the subject into four parts, which can be thought of as four mini-books in one. The first part covers the psychology of global warming denial, how to defend ourselves against its lies and fake news, and how to convince others of global warming's grave harm. The second part describes exactly what global warming is. The third answers the question what makes us so sure? Finally, the last part provides a road map showing us how to defeat global warming.

This book is comprehensive, fast-paced, and easily accessible to readers from all walks of life. It provides an overview of everything one needs to know about global warming and, as such, is an excellent survey of global warming topics. In addition to being an easy and enjoyable read for the general public, A Crisis Like No Other: Understanding and Defeating Global Warming serves as a handy primer on climate change for environmental science classes.

The importance of Artificial Intelligence cannot be over-emphasised in current times, where automation is already an integral part of industrial and business processes.

A First Course in Artificial Intelligence is a comprehensive textbook for beginners which covers all the fundamentals of Artificial Intelligence. Seven chapters (divided into thirty-three units) introduce the student to key concepts of the discipline in simple language, including expert system, natural language processing, machine learning, machine learning applications, sensory perceptions (computer vision, tactile perception) and robotics. Each chapter provides information in separate units about relevant history, applications, algorithm and programming with relevant case studies and examples. The simplified approach to the subject enables beginners in computer science who have a basic knowledge of Java programming to easily understand the contents. The text also introduces Python programming language basics, with demonstrations of natural language processing. It also introduces readers to the Waikato Environment for Knowledge Analysis (WEKA), as a tool for machine learning.

The book is suitable for students and teachers involved in introductory courses in undergraduate and diploma level courses which have appropriate modules on artificial intelligence.

This handbook provides a comprehensive understanding of computational linguistics, focusing on the integration of deep learning in natural language processing (NLP). 18 edited chapters cover the state-of-the-art theoretical and experimental research on NLP, offering insights into advanced models and recent applications.

Highlights:

- Foundations of NLP: Provides an in-depth study of natural language processing, including basics, challenges, and applications.

- Advanced NLP Techniques: Explores recent advancements in text summarization, machine translation, and deep learning applications in NLP.

- Practical Applications: Demonstrates use cases on text identification from hazy images, speech-to-sign language translation, and word sense disambiguation using deep learning.

- Future Directions: Includes discussions on the future of NLP, including transfer learning, beyond syntax and semantics, and emerging challenges.

Key Features:

- Comprehensive coverage of NLP and deep learning integration.

- Practical insights into real-world applications

- Detailed exploration of recent research and advancements through 16 easy to read chapters

- References and notes on experimental methods used for advanced readers

Ideal for researchers, students, and professionals, this book offers a thorough understanding of computational linguistics by equipping readers with the knowledge to understand how computational techniques are applied to understand text, language and speech.

A Journey Through Water: A Scientific Exploration of The Most Anomalous Liquid on Earth, is a monograph about water at molecular level. The monograph explores how its peculiar properties are related to its molecular structure. Readers are introduced to water through information about water in a wider perspective, properties of its liquid state, experimental techniques for molecular level investigations of liquid water, and computer simulation techniques. This is followed by chapters explaining the structural properties and principal applications of various phases of water (water as a normal liquid, supercooled water, ice and supercritical water). Key features of this reference include:

- easy to understand, sequential and structured text making this reference ideal for readers with limited scientific knowledge of water physics

- a list of institutions where water research is promoted in larger scales

- 130 figures which supplement the text

- an explanation of ten principal anomalies of water and associated theories

The book is an excellent resource for novice researchers (physicists, chemists and chemical engineers) working on water and laymen who are interested in furthering their understanding of this precious liquid.

This book demonstrates several use cases of how artificial intelligence (AI) and machine learning (ML) are revolutionizing problem-solving across various industries. The book presents 18 edited chapters beginning with the latest advancements in human-AI interactions and neuromorphic computing, setting the stage for practical applications.

Chapters focus on AI and ML applications such as fingerprint recognition, glaucoma detection, and lung cancer identification using image processing. The book also explores the role of AI in professional operations such as UX design, event detection, and content analysis. Additionally, the book includes content that examines AI's impact on technical operations wireless communication, VLSI systems, and advanced manufacturing processes. Each chapter contains summaries and references for addressing the needs of beginner and advanced readers.

This comprehensive guide is an essential resource for anyone seeking to understand AI's transformative role in modern problem-solving in professional industries.

A Primer on Wireless Technology and IoT Basics covers the journey of wireless networks from the early 1G systems to the anticipated capabilities of 6G, while also explaining essential wireless technologies such as GSM, WLAN, WPANs, MANETs, and Wireless Sensor Networks (WSNs). It further delves into how these technologies underpin IoT ecosystems, emphasizing their role in data collection, transmission, and smart system integration.

Chapters explore key developments in wireless communication, types of networks, sensor architectures, IoT system layers, and real-world implementation challenges. Special attention is given to IoT applications across diverse sectors and how wireless protocols support their functionality.

This book is particularly useful for readers seeking a strong foundational understanding of wireless systems and IoT, making it ideal for both technical and non-technical audiences.

Key Features:

Explain key generations of wireless technology from 1G to 6G.

Clarify concepts related to GSM, WLAN, WPANs, MANETs, and WSNs

Illustrate IoT architecture, protocols, and system layers

Highlight real-world IoT use cases and applications

Address implementation challenges and data handling in IoT systems

A Treatise on Ecological Science provides a fresh perspective on modern ecological thought by exploring topics often overlooked in traditional ecological texts. The book opens with a discussion of Network Ecology, unraveling the interconnectedness of ecosystems, and transitions to the intricate relationship between biodiversity and climate change. It further addresses Human Ecology, highlighting its central role in shaping ecological discourse, and explores the principles of Industrial Ecology, emphasizing sustainable practices in industrial systems. The final chapter critically examines the Sustainable Development Goals, offering a balanced view of their benefits and limitations.

Designed to bridge gaps between ecology, industry, and global sustainability, this book serves as an insightful resource for students, researchers, and policymakers interested in contemporary ecological science and its practical applications.

Key Features:

- Examines underexplored topics in ecological science.

- Connects biodiversity, climate change, and human ecology.

- Highlights the role of industrial ecology in sustainability.

- Provides a critical analysis of Sustainable Development Goals.

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.

The book aims to provide a deeper understanding of the synergistic impact of Artificial intelligence (AI) and the Internet of Things (IoT) for disease detection. It presents a collection of topics designed to explain methods to detect different diseases in humans and plants. Chapters are edited by experts in IT and machine learning, and are structured to make the volume accessible to a wide range of readers.

Key Features:

- 17 Chapters present information about the applications of AI and IoT in clinical medicine and plant biology

- Provides examples of algorithms for heart diseases, Alzheimer's disease, cancer, pneumonia and more

- Includes techniques to detect plant disease

- Includes information about the application of machine learning in specific imaging modalities

- Highlights the use of a variety of advanced Deep learning techniques like Mask R-CNN

- Each chapter provides an introduction and literature review and the relevant protocols to follow

The book is an informative guide for data and computer scientists working to improve disease detection techniques in medical and life sciences research. It also serves as a reference for engineers working in the healthcare delivery sector.

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.

AI-Driven Innovations in Electrochemical Technologies for Sustainable Energy Solutions blends principles of data science, materials engineering, and energy technology to offer a forward-looking exploration of how Artificial Intelligence is reshaping the design, optimisation, and performance of electrochemical technologies.

Across nine well-structured chapters, the book progresses from foundational principles of AI-integrated electrochemical systems to advanced applications in batteries, fuel cells, supercapacitors, and electrolysers. Topics include AI-assisted materials discovery, performance optimisation, real-time monitoring, predictive maintenance, and system-level energy management. Ethical, environmental, and policy considerations surrounding AI adoption are also examined, along with case studies that demonstrate real-world impact.

With its interdisciplinary perspective and emphasis on practical innovations, this book equips readers with a deep understanding of how AI reduces experimentation time, streamlines design processes, and drives next-generation sustainable energy solutions.

Key Features

Comprehensive coverage of AI-enhanced electrochemical systems

Real-world case studies and application-driven insights

Focus on AI-assisted material discovery, optimisation, and predictive maintenance

Discussions on the ethical, environmental, and policy dimensions

Forward-looking perspectives on integrating AI with sustainable energy and healthcare technologies

AI-Powered Innovations in Ophthalmic Diagnosis and Treatment is a forward-looking assessment of how artificial intelligence is redefining modern eye care. The book connects computational advancements with clinical practice, presenting a structured, multidisciplinary roadmap for integrating AI across diagnostic workflows, therapeutic decisions, patient monitoring, and future-ready developments in ophthalmology.

Across seven insightful chapters, the book establishes AI-driven frameworks that enhance ophthalmic workflows through federated, reinforcement, and prompt-based learning. Subsequent chapters detail AI-enabled diagnostics for retinal, glaucoma, and ocular surface diseases, alongside governance challenges in real-world deployment. The book also explores personalized therapeutics by integrating AI with Traditional Chinese Medicine, stem cell strategies, and precision care models.

It further examines next-generation technologies including LLMs, AIGC, and multi-agent systems and their transformative roles in clinical research, drug discovery, and medical education. Broader applications are highlighted through AI's connection to systemic disease surveillance and wearable healthcare. The final chapters address regulatory, ethical, and legal considerations, concluding with a visionary outlook on quantum computing and global collaboration shaping the future of ophthalmic AI.

Uniting clinical evidence, computational methodologies, and patient-centred perspectives, this book provides actionable insights for implementing responsible, explainable, and scalable AI within ophthalmic practice. Key Features

Introduces AI-driven frameworks enhancing diagnostic and clinical workflows in ophthalmology.

Presents practical AI applications for retinal, glaucoma, and ocular surface disease detection.

Explores AI-guided personalized therapeutics, including TCM integration and stem cell innovations.

Examines emerging technologies such as LLMs, AIGC, and multi-agent systems in research and education.

Addresses ethical, regulatory, and governance challenges in deploying medical AI.

Highlights AI's role in systemic disease prediction, wearable monitoring, and next-generation healthcare models.

Envisions future innovations shaped by quantum computing and global AI collaboration.

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.

Adulteration refers to the practice of altering food or pharmaceutical content to reduce production costs. Factors affecting this practice include market forces such as easy availability of food adulterants, bargaining power of consumers and large demand and supply gaps which incentivize such practices. Technological advancements in chemical analysis now help us to identify adulterated food and drugs more easily.

Adulteration Analysis of Some Foods and Drugs is a sourcebook describing analytical methodologies for the determination of adulterants in different food items (milk, honey, juice) and drugs (dietary supplements, sildenafil and specific plant extracts). Additional chapters give guidelines for analyzing a food or drug sample. This book is suitable for researchers working in the field of analytical chemistry for the determination of adulterants. The concise and organized presentation of the contents also serves to enhance the level of knowledge of students undertaking food and drug safety / quality control training courses.

Vector calculus is an essential mathematical tool for performing mathematical analysis of physical and natural phenomena. It is employed in advanced applications in the field of engineering and computer simulations.

This textbook covers the fundamental requirements of vector calculus in curricula for college students in mathematics and engineering programs. Chapters start from the basics of vector algebra, real valued functions, different forms of integrals, geometric algebra and the various theorems relevant to vector calculus and differential forms.

Readers will find a concise and clear study of vector calculus, along with several examples, exercises, and a case study in each chapter. The solutions to the exercises are also included at the end of the book.

This is an ideal book for students with a basic background in mathematics who wish to learn about advanced calculus as part of their college curriculum and equip themselves with the knowledge to apply theoretical concepts in practical situations.