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Communicable diseases have been an important part of human history.
Epidemics afflicted populations, causing many deaths before
gradually fading away and emerging again years after. Epidemics of
infectious diseases are occurring more often, and spreading faster
and further than ever, in many different regions of the world. The
scientific community, in addition to its accelerated efforts to
develop an effective treatment and vaccination, is also playing an
important role in advising policymakers on possible
non-pharmacological approaches to limit the catastrophic impact of
epidemics using mathematical and machine learning models.
Controlling Epidemics With Mathematical and Machine Learning Models
provides mathematical and machine learning models for epidemical
diseases, with special attention given to the COVID-19 pandemic. It
gives mathematical proof of the stability and size of diseases.
Covering topics such as compartmental models, reproduction number,
and SIR model simulation, this premier reference source is an
essential resource for statisticians, government officials, health
professionals, epidemiologists, sociologists, students and
educators of higher education, librarians, researchers, and
academicians.
The Missing Link blazes a unique trail through the conundrums and
controversies generated by evolutionary theory and religious
thought. To date, these debates have centered on the origin of
species. This book, however, turns the spotlight on the origins of
consciousness, thought, and the self while also considering the
relationship between God and science. Remarkably, Darwin himself
highlighted the relevance of the origin of consciousness to the
question of a creator. Therefore, The Missing Link works within a
framework that was laid out at the dawn of the creation-evolution
debate. Since that time, however, this framework has rarely been
considered or explored. The unifying theme of this volume is the
conclusion that the existence of God is grounded in rational
thought. Contributors to The Missing Link include three Nobel Prize
winners, renowned scientists from Oxford, Cambridge, and Harvard,
and noted contemporary philosophers of consciousness, language, and
the self.
The most penetrating scientific intellects have found that
something beyond science is required to make sense of the cosmos,
while many of those working for inter-faith dialogue have concluded
that "the story of the universe is the only thing that can bring
the religions of the world together."
"Putting three basic questions to a well-chosen group of people
has provided a lush collection of thoughtful reflection and
informed speculation. A wonderfully provocative and enlightening
book." -- James Mosher Publisher of Mindfield
This innovative and challenging book presents cogent answers from
some of the greatest thinkers of the twentieth century to fifteen
of the most enduring questions posed by humanity. For questioning
minds who seek alternative philosophical viewpoints, this is a
unique and accessible assessment of humankind's common experience
that offers a new vision for the next millenium.
Communicable diseases have been an important part of human history.
Epidemics afflicted populations, causing many deaths before
gradually fading away and emerging again years after. Epidemics of
infectious diseases are occurring more often, and spreading faster
and further than ever, in many different regions of the world. The
scientific community, in addition to its accelerated efforts to
develop an effective treatment and vaccination, is also playing an
important role in advising policymakers on possible
non-pharmacological approaches to limit the catastrophic impact of
epidemics using mathematical and machine learning models.
Controlling Epidemics With Mathematical and Machine Learning Models
provides mathematical and machine learning models for epidemical
diseases, with special attention given to the COVID-19 pandemic. It
gives mathematical proof of the stability and size of diseases.
Covering topics such as compartmental models, reproduction number,
and SIR model simulation, this premier reference source is an
essential resource for statisticians, government officials, health
professionals, epidemiologists, sociologists, students and
educators of higher education, librarians, researchers, and
academicians.
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