"This book contains ideas to develop interdisciplinary and transdisciplinary views on economy and society. It aims to disseminate heterodox ideas on various subjects related to economics and global society. The book is organised in six parts. Part 1 contains the key lectures of Backhaus on the concept of state sciences and of Klamer on the importance of culture for economics. Parts 2- 6 contain successively contributions in the areas of economic paradigms and theories, population and society, corporate issues, environment, and (...) international relations. Examples of the content are: - the changes of family life cycles due to the rise of non-traditional households; - subjective and objective inflation rates after the introduction of the Euro; - the economics of genetic engineering; - the contribution of foreign direct investment to the economic development of host countries; - the inaccuracy of economic models applied in places characterized by extreme income disparities; - the improvement of political and corporate governance; - evolutionary thinking and emission trading; - freedom and order in the European Union; - the reform of social policy in Europe. The book provides interesting creative multi-disciplinary ideas with respect to various topical issues concerning the contemporary global society. It is highly recommended for economists and social scientists in search of broad views on social science and society.". (shrink)

The static properties of leaves with parallel venation from terrestrial orchids of the genus Epipactis were modelled as coupled elastic rods using the geometrically exact Cosserat theory and the resulting boundary-value problem was solved numerically using a method from Shampine, Muir and Xu. The response of the leaf structure to the applied force was obtained from preliminary measurements. These measurements allowed the Young’s modulus of the Epipactis leaves to be determined. The appearance of wrinkles and undulation characteristics for some leaves (...) has been attributed to the small torsional stiffness of the leaf edges. (shrink)

This is the collection of essays presented to Bochenski on his 60th birthday, and it contains, as a mirror of Bochenski's own work, a broad spectrum of studies ranging from formal logic and history of logic, to the philosophy of logic and language, and to the methodology of explanation in Greek philosophy. Of the seventeen articles, these are some of the more important to the reviewer: "Betrachtungen zum Sequenzen Kalkül" by Paul Bernays, which is an extensive study of Gentzen-type formulations (...) of logic; "Remarks on Formal Deduction," H. B. Curry, a further discussion of sequenzen-logics; "Marginalia on Gentzen's Sequenzen Kalkül" by Hughes Leblanc; "Method and Logic in Presocratic Explanation," Jerry Stannard; "On the Logic of Preference and Choice," H. S. Houthakker, a suggestive presentation of decision and utility theory in logical form; "Leibniz's Law in Belief Contexts," Chisholm; "On Ontology and the Province of Logic," R. M. Martin; and "N. A. Vasilev and the Development of Many-valued Logics," G. L. Kline, an important addition to the history of logic. Other contributors are: Storrs McCall, Albert Menne, E. W. Beth, Benson Mates, Ivo Thomas, J. F. Staal, F. R. Barbò, A.-T. Tymieniecka, and N. M. Luyten. There is a bibliography of Bochenski's writings through 1962.—P. J. M. (shrink)

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates. BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ’learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the (...) relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system. (shrink)