This book provides a complete practical guide of processing data in public health with R language. On the basis of the author’s research and teaching experiences, this book serves either as a textbook for undergraduates and graduates in public health or as a tutorial for self-learning. Many first-hand examples are presented with source data, R scripts, and graphs, as well as detailed explanations, which could be easily reproduced by readers so as to better understand the data processing principles and procedures. Popular and novel R packages in public health are introduced as well.

There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.

The genus Juglans consists of about 21 species, many of which are of biological and economically important becasue of their high quality timber and nutirtious nuts. The fields of genetics and genomics are growing by leaps and bounds. In particular, new technologies now allow investigators to use high-throughput tools to generate large molecular datasets on non-model organisms. Theoretical concepts and DNA markers, including random amplified polymorphic DNA (RAPDs), Microsatellites(Simple sequence repeats, SSR), Cleaved Amplified Polymorphic Sequences(CAPS), Internal transcribed spacer (ITS), and Chloroplast DNAs could be used to address applied problems in the ecological and genetic sciences, including those pertaining to the conservation, management, and genetic improvement of Walnut trees. This book might be used to better manage our natural resources and to better understand natural ecological and evolutionary processes that influence the distribution and abundance of especially for walnuts, other animal and plant speci

There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.