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It is widely known among the Frontiers of physics, that “sweeping under the rug” practice has been quite the norm rather than exception. In other words, the leading paradigms have strong tendency to be hailed as the only game in town.
The National Science Foundation (NSF) has played a key role over the past several decades in advancing understanding of Earth's systems by funding research on atmospheric, ocean, hydrologic, geologic, polar, ecosystem, social, and engineering-related processes. Today, however, those systems are being driven like never before by human technologies and activities. Our understanding has struggled to keep pace with the rapidity and magnitude of human-driven changes, their impacts on human and ecosystem sustainability and resilience, and the effectiveness of different pathways to address those challenges. Given the urgency of understanding human-driven changes, NSF will need to sustain and expand its efforts to achieve greater impact. The time is ripe to create a next-generation Earth systems science initiative that emphasizes research on complex interconnections and feedbacks between natural and social processes. This will require NSF to place an increased emphasis on research inspired by real-world problems while maintaining their strong legacy of curiosity driven research across many disciplines ? as well as enhance the participation of social, engineering, and data scientists, and strengthen efforts to include diverse perspectives in research.
Why efforts to create a scientific basis of morality are neither scientific nor moral In this illuminating book, James Davison Hunter and Paul Nedelisky trace the origins and development of the centuries-long, passionate, but ultimately failed quest to discover a scientific foundation for morality. The "new moral science" led by such figures as E. O. Wilson, Patricia Churchland, Sam Harris, Jonathan Haidt, and Joshua Greene is only the newest manifestation of that quest. Though claims for its accomplishments are often wildly exaggerated, this new iteration has been no more successful than its predecessors. But rather than giving up in the face of this failure, the new moral science has taken a surprising turn. Whereas earlier efforts sought to demonstrate what is right and wrong, the new moral scientists have concluded, ironically, that right and wrong don't actually exist. Their (perhaps unwitting) moral nihilism turns the science of morality into a social engineering project. If there is nothing moral for science to discover, the science of morality becomes, at best, a feeble program to achieve arbitrary societal goals. Concise and rigorously argued, Science and the Good is a definitive critique of a would-be science that has gained extraordinary influence in public discourse today and an exposé of that project's darker turn.
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The purpose of the book is to advance in the understanding of brain function by defining a general framework for representation based on category theory. The idea is to bring this mathematical formalism into the domain of neural representation of physical spaces, setting the basis for a theory of mental representation, able to relate empirical findings, uniting them into a sound theoretical corpus. The innovative approach presented in the book provides a horizon of interdisciplinary collaboration that aims to set up a common agenda that synthesizes mathematical formalization and empirical procedures in a systemic way. Category theory has been successfully applied to qualitative analysis, mainly in theoretical computer science to deal with programming language semantics. Nevertheless, the potential of category theoretic tools for quantitative analysis of networks has not been tackled so far. Statistical methods to investigate graph structure typically rely on network parameters. Category theory can be seen as an abstraction of graph theory. Thus, new categorical properties can be added into network analysis and graph theoretic constructs can be accordingly extended in more fundamental basis. By generalizing networks using category theory we can address questions and elaborate answers in a more fundamental way without waiving graph theoretic tools. The vital issue is to establish a new framework for quantitative analysis of networks using the theory of categories, in which computational neuroscientists and network theorists may tackle in more efficient ways the dynamics of brain cognitive networks. The intended audience of the book is researchers who wish to explore the validity of mathematical principles in the understanding of cognitive systems. All the actors in cognitive science: philosophers, engineers, neurobiologists, cognitive psychologists, computer scientists etc. are akin to discover along its pages new unforeseen connections through the development of concepts and formal theories described in the book. Practitioners of both pure and applied mathematics e.g., network theorists, will be delighted with the mapping of abstract mathematical concepts in the terra incognita of cognition.
This work presents a series of dramatic discoveries never before made public. Starting from a collection of simple computer experiments---illustrated in the book by striking computer graphics---Wolfram shows how their unexpected results force a whole new way of looking at the operation of our universe. Wolfram uses his approach to tackle a remarkable array of fundamental problems in science: from the origin of the Second Law of thermodynamics, to the development of complexity in biology, the computational limitations of mathematics, the possibility of a truly fundamental theory of physics, and the interplay between free will and determinism.
The central question in the biological sciences for the past 100 years has concerned an understanding of how living systems differ from other general physical phenomena and what makes these systems unique. With new developments in the fields of nonequilibrium thermodynamics, systems theory, chaos, and information theory over the past few decades, there has been growing interest in finally answering the question first posed by Erwin Schrödinger in the 1940s concerning the true scientific nature of living systems. Similarly, there is also increasing interest within the biologic community for a more holistic and non-reductionist methodology. The approach followed in this book builds on a foundation of information theory and semiotics while integrating basic thermodynamic considerations and systems theory to form a singular unifying concept that is proposed to be the essential process of living systems. However, the premise presented is much more than simply the exposition of a new hypothesis. This book describes the logical progression of thought incorporating a diverse array of established scientific ideas that were used in the conceptualization of a dynamic mathematical framework that can be employed as a novel analytic means for the study of living systems and their fundamental processes.
How the NSF became an important yet controversial patron for the social sciences, influencing debates over their scientific status and social relevance. In the early Cold War years, the U.S. government established the National Science Foundation (NSF), a civilian agency that soon became widely known for its dedication to supporting first-rate science. The agency's 1950 enabling legislation made no mention of the social sciences, although it included a vague reference to "other sciences." Nevertheless, as Mark Solovey shows in this book, the NSF also soon became a major--albeit controversial--source of public funding for them.