New Foundation In The Sciences

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 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 book presents a new economic theory developed from physical and biological principles. It explains how technology, social systems and economic values are intimately related to resources. Many people have recognized that mainstream (neoclassical) economic theories are not consistent with physical laws and often not consistent with empirical patterns, but most feel that economic activities are too complex to be described by a simple and coherent mathematical theory. While social systems are indeed complex, all life systems, including social systems, satisfy two principles. First, all systems need to extract resources from the external environment to compensate for their consumption. Second, for a system to be viable, the amount of resource extraction has to be no less than the level of consumption. From these two principles, we derive a quantitative theory of major factors in economic activities, such as fixed cost, variable cost, discount rate, uncertainty and duration. The mathematical theory enables us to systematically measure the effectiveness of different policies and institutional structures at varying levels of resource abundance and cost.The theory presented in this book shows that there do not exist universally optimal policies or institutional structures. Instead, the impacts of different policies or social structures have to be measured within the context of existing levels of resource abundance. As the physical costs of extracting resources rise steadily, many policy assumptions adopted in mainstream economic theories, and workable in times of cheap and abundant energy supplies and other resources, need to be reconsidered. In this rapidly changing world, the theory presented here provides a solid foundation for examining the long-term impacts of today's policy decisions.

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.