The research extended to the suppliers (auto-component manufacturers) responsibility towards the environment. The statistical tools used for this section were Chi-square (Cross-tab) and Logistic Regression with the attributes of corporate governance, product design, green procurement, environmentally friendly manufacturing, green packaging, waste management, and green inspection was used to measure their environmental responsibility
Vertebrate Endocrinology, Sixth Edition, provides a comprehensive, up-to-date treatment of the endocrine system for college and university students as well as researchers. This book is logically arranged, easily comprehended, and well-illustrated. It covers traditional hormone-based systems and introduces all forms of chemical communication, their implications for the health of humans, domesticated, and wild vertebrates. Written by two experts who have completed extensive research in comparative vertebrate endocrinology with an emphasis on natural and anthropogenic environmental factors influencing endocrine systems. Collectively, the authors have taught courses in endocrinology at the undergraduate and graduate level for more than 60 years. After first publishing in 1985, Vertebrate Endocrinology, Sixth Edition, continues to serve as an important resource for graduate students and advanced undergraduates in the biological sciences, animal sciences, and veterinary sciences. Endocrine researchers will also benefit from the book's relevance in the areas of comparative, veterinary, and mammalian endocrinology. - Addresses the endocrinology of all vertebrate and non-vertebrate chordates - The only endocrinology textbook that deals with evolutionary aspects of endocrine systems - Includes biochemical, cellular, tissue, organismic, behavioral, and environmental aspects of chemical communication
As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.
The research extended to the suppliers (auto-component manufacturers) responsibility towards the environment. The statistical tools used for this section were Chi-square (Cross-tab) and Logistic Regression with the attributes of corporate governance, product design, green procurement, environmentally friendly manufacturing, green packaging, waste management, and green inspection was used to measure their environmental responsibility
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