Nidhi Gupta – författare

Advances in Nanomedicine for the Delivery of Therapeutic Nucleic Acids addresses several issues related to safe and effective delivery of nucleic acids (NAs) using nanoparticles. A further emphasis would be laid on the mechanism of delivery of NAs, the barriers encountered and the strategies adapted to combat them. An exhaustive account of the advantages as well shortcomings of all the delivery vectors being employed in delivery of various NAs will be provided. On final note the regulatory aspects of nanoparticles mediated NA would be discussed, with focus on their clinical relevance.

The design and development of nucleic acid-based therapeutics for the treatment of diseases arising from genetic abnormalities has made significant progress over the past few years. NAs have been widely explored for the treatment of cancer and infectious diseases or to block cell proliferation and thereby caused diseases. Advances in synthetic oligonucleotide chemistry resulted in synthesis of NAs that are relatively stable in in vivo environments. However, cellular targeting and intracellular delivery of NAs still remains a challenge. Further development of NA-based therapeutics depends on the progress of safe and effective carriers for systemic administration. Nanomedicine has facilitated availability of vectors with diminished cytotoxicity and enhanced efficacy which are rapidly emerging as systems of choice. These vectors protect NAs from enzymatic degradation by forming condensed complexes along with targeted tissue and cellular delivery. During the past few years, a myriad reports have appeared reporting delivery of NAs mediated by nanoparticles. This book will provide an overview of nanoparticles being employed in the in vitro and in vivo delivery of therapeutically relevant NAs like DNA, siRNA, LNA, PNA, etc.

This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT.

Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning, IoT and image processing.

KEY FEATURES:

• Includes fundamental concepts towards advanced applications in machine learning and IoT.

• Discusses potential and challenges of machine learning for IoT and optimization

• Reviews recent advancements in diverse researches on computer vision, networking and optimization field.

• Presents latest technologies such as machine learning in image processing and IoT

This book has been written for readers in academia, engineering, IT specialists, researchers, industrial professionals and students, and is a great reference for those just starting out in the field as well as those at an advanced level.

This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT.

Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning, IoT and image processing.

KEY FEATURES:

• Includes fundamental concepts towards advanced applications in machine learning and IoT.

• Discusses potential and challenges of machine learning for IoT and optimization

• Reviews recent advancements in diverse researches on computer vision, networking and optimization field.

• Presents latest technologies such as machine learning in image processing and IoT

This book has been written for readers in academia, engineering, IT specialists, researchers, industrial professionals and students, and is a great reference for those just starting out in the field as well as those at an advanced level.

Generative artifical intelligence (AI) technologies are reshaping the way we create, communicate, and compute, presenting both unprecedented opportunities and profound challenges. As these systems increasingly influence decisions that shape our lives, it becomes clear that performance metrics alone cannot define their success. A deeper understanding of the intersection between technical innovation and human values is essential to navigate this transformative era.

The Art and Ethics of Generative AI: Fairness, Transparency, and Human Values provides a balanced exploration of generative AI, combining technical insights with ethical considerations. It explains generative model architectures and learning paradigms in an accessible way while addressing critical issues such as algorithmic bias, explainability challenges, and emerging regulatory approaches. Practical frameworks for responsible AI development are offered, alongside multidisciplinary perspectives that bridge technical and humanistic viewpoints. Abstract concepts are brought to life through practical illustrations, demonstrating how ethical considerations play out in real-world AI applications.

Designed for a wide audience, the book serves AI practitioners seeking actionable guidance for building responsible systems, researchers exploring nuanced ethical dimensions, educators and students looking for comprehensive learning materials, and policymakers needing governance insights. It is an essential resource for anyone engaged in the rapidly evolving AI ecosystem.

Generative artifical intelligence (AI) technologies are reshaping the way we create, communicate, and compute, presenting both unprecedented opportunities and profound challenges. As these systems increasingly influence decisions that shape our lives, it becomes clear that performance metrics alone cannot define their success. A deeper understanding of the intersection between technical innovation and human values is essential to navigate this transformative era.

The Art and Ethics of Generative AI: Fairness, Transparency, and Human Values provides a balanced exploration of generative AI, combining technical insights with ethical considerations. It explains generative model architectures and learning paradigms in an accessible way while addressing critical issues such as algorithmic bias, explainability challenges, and emerging regulatory approaches. Practical frameworks for responsible AI development are offered, alongside multidisciplinary perspectives that bridge technical and humanistic viewpoints. Abstract concepts are brought to life through practical illustrations, demonstrating how ethical considerations play out in real-world AI applications.

Designed for a wide audience, the book serves AI practitioners seeking actionable guidance for building responsible systems, researchers exploring nuanced ethical dimensions, educators and students looking for comprehensive learning materials, and policymakers needing governance insights. It is an essential resource for anyone engaged in the rapidly evolving AI ecosystem.