⦁Why does robot help organizations to shorten time to reach growth life cycle stage or maturity life cycle stage rapidly ?The robotic market is growing rapidly, but adoption of robots and truck products through the manufacturing life-cycle and uses robots to participate any organizational tasks efficiently and effectively. According to a new study from Oxford Economics, economists predict that robots could take over 20 million manufacturing jobs around the world by 2030, and within the next 11 years. These could be 14 million robots put to work in China alone. So, such as developing country, China, many China employers will accept robots to help their organizations to do different kinds of simple or complex tasks, also clerical or non-clerical workers, they can concentrate on dealing to do their urgent tasks, it means that efficiency will be possible raised in performance will be improved, productive number may be influenced to increase. Robots may help the experiencing birth life cycke stage organizations to shorten time to reach growth life cycle syahe or the experiencing the growth life cycle stage organizations to shorten time to reach mature life cycle stage in possible, because their clerical or non-clerical staffs need to learn how to dominate or control robots to work in order to achieve raising efficiency aim. When these organizations' every department has robots to participate to do simple or complex tasks. In long time., robots may help workers to shorten time to finish any tasks in any task processing or step. When working time is shorten to every task's step, then productivies and efficiencies willl be also raised. SO, such as this China developing country's future experiencing birth or growth life cycle stage organizations case, if there are many these birth or growth life cycle stage China's business organizations decided to apply robots to assist non-clerical and clerical workers to do simple or comples tasks. Then, their working steps or procesess time will be shorten . So, that efficiency or performance can be improved. Even if in developing country China's hospital organizations can apply surgical robots to assist surgeons or doctors to do any complex or simple surgeon health care will still likely become more automated . Because China has high population, so patients' medical need must be high, just as robots can transport and deliver goods in manufacturing and retail, they can also move medicine and equipment through hospitals when doctos and burses focus on other tasks. So, robots can help future any hospital organizations to improve service level to satisfy patients' needs in China's hospitals. Moreover, robots can improve developing countries, e.g. China, India patients' life. One of the most popular ways robots help doctors is by performing surgery or making operations easier. These machines make it in easier to see into a patient's body and repair problemshave been receptive to robots in the operating room and appreciate their precision countries, such as India, China their experiencing birth or growth life cycle stage organizations can continue to enhance technology like 3D embedded vision, multispectral, and hypesspectral imaging. This combined with artificial intelligence and deep learning wil empower industrial robots to improve themselves and keep pace with the human workers around them. A BCG analysis found the using advanced robots can reduce conversion costs by up to 15% and robot adoption will likely be a critical determinant of appreciable enable shorten. Robot adoption will likely be a critical determinant of appear to enable shorten production runs, smaller factories and the need for faster productivity growth. As robot production has increased, costs have gone down .

Social isolation and loneliness are serious yet underappreciated public health risks that affect a significant portion of the older adult population. Approximately one-quarter of community-dwelling Americans aged 65 and older are considered to be socially isolated, and a significant proportion of adults in the United States report feeling lonely. People who are 50 years of age or older are more likely to experience many of the risk factors that can cause or exacerbate social isolation or loneliness, such as living alone, the loss of family or friends, chronic illness, and sensory impairments. Over a life course, social isolation and loneliness may be episodic or chronic, depending upon an individual's circumstances and perceptions. A substantial body of evidence demonstrates that social isolation presents a major risk for premature mortality, comparable to other risk factors such as high blood pressure, smoking, or obesity. As older adults are particularly high-volume and high-frequency users of the health care system, there is an opportunity for health care professionals to identify, prevent, and mitigate the adverse health impacts of social isolation and loneliness in older adults. Social Isolation and Loneliness in Older Adults summarizes the evidence base and explores how social isolation and loneliness affect health and quality of life in adults aged 50 and older, particularly among low income, underserved, and vulnerable populations. This report makes recommendations specifically for clinical settings of health care to identify those who suffer the resultant negative health impacts of social isolation and loneliness and target interventions to improve their social conditions. Social Isolation and Loneliness in Older Adults considers clinical tools and methodologies, better education and training for the health care workforce, and dissemination and implementation that will be important for translating research into practice, especially as the evidence base for effective interventions continues to flourish.

"The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come." -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading.

HEALTH BEHAVIOR AS BASIC RESEARCH Health behavior is not a traditional discipline, but a newly emerging interdisciplinary field. It is still in the process of establishing its identity. Few institutional or organizational structures, i. e. , departments and programs, reflect it, and few books and journals are directed at it. The primary objective of this book is thus to identify and establish health behavior as an important area of basic research, worthy of being studied in its own right. As a basic research area, health behavior transcends commitment to a particular behavior, a specific illness or health problem, or a single set of determinants. One way of achieving this objective is to look at health behavior as an outcome of a range of personal and social determinants, rather than as a set of risk factors or as targets for intervention strategies directed at behavioral change. The book is thus organized pri marily in terms of the size of the determinants of concern, rather than in terms of specific health behaviors, or specific health problems or conditions. With the first part of the book establishing working defmitions of health behavior and health behavior research as basic frameworks, the second part moves from smaller to larger systems, informing the reader about basic research that demonstrates how health behavior is determined by personal, family, social, institutional, and cultural factors. These distinctions reflect some arbitrar iness: the family, organizations, and institutions, for example, are social units.

This departmental paper analyzes the impact of the COVID-19 pandemic on tourism in the Asia Pacific region, Latin America, and Caribbean countries. Many tourism dependent economies in these regions, including small states in the Pacific and the Caribbean, entered the pandemic with limited fiscal space, inadequate external buffers, and foreign exchange revenues extremely concentrated in tourism. The empirical analysis leverages on an augmented gravity model to draw lessons from past epidemics and finds that the impact of infectious diseases on tourism flows is much greater in developing countries than in advanced economies.

This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data