Neuroscience is a fascinating discipline – its dynamic progress has led to the emergence of new interdisciplinary research programmes with great potential. One of these research areas is neuroeconomics. As will be shown in this article, this discipline, which is diffi cult to clearly characterize and defi ne, is faced with many problems. Th is paper argues that social scientists should be interested in the problems and tendencies in social neuroscience for several reasons. Neuroeconomics, and other disciplines inspired by neuroscience, will compete with their parent disciplines in many fi elds of interest. On one hand it will be necessary for scientists to defi ne and defend the irreplaceable roles of their disciplines, but also critically evaluate the potential of new approaches on the other. In the context of this discussion, which reopens questions about the scientifi c status of economics and its roles, this paper introduces the main problems related to neuroeconomics. Th is paper concludes that these problems represent a wide domain for social scientists and methodologists of science. and Neurověda je fascinující disciplínou – její dynamický rozvoj podněcuje vznik nových interdisciplinárních výzkumných programů s velkým potenciálem. Jednou takovou oblastí je i neuroekonomie. Jak se ukáže v článku, tato disciplína, kterou je obtížné jednoznačně vymezit a určit její defi nici, se potýká se spoustou problémů. Článek y jj fi argumentuje, že by se společenští vědci měli těmito problémy a tendencemi v sociální neurovědě zabývat, a to hned z několika důvodů. Neuroekonomie, a také další neurovědou inspirované disciplíny, budou svým mateřským oborům konkurovat v mnoha oblastech, přičemž bude nezbytné, aby vědci byli schopni na jedné straně defi novat a obhájit nezastupitelné role svých disciplín, na straně druhé kriticky vyhodnocovat potenciál nových přístupů. V kontextu této diskuze, která znovu otevírá otázky ohledně vědeckého statusu ekonomie a jejích rolí, článek vymezuje základní problémy, s nimiž se neuroekonomie potýká. Práce dospívá k závěru, že tyto problémy představují široké pole působnosti pro společenské vědce a metodology vědy.
We review recent developments in the field of B stars circumstellar environment modelling and discuss future improvements which are necessary to obtain more realistic models of the circumstellar environment of B stars.
When the dimensions of standard commercial chambers for measuring gas exchange cannot accommodate the object being measured, scientists construct their own chambers. The time needed to reach chamber steady state (chamber response time) depends on net system volume (e.g. chamber and tubing volume) and airflow. Unfortunately, some authors take chamber response time into consideration while others ignore it. We present the formula for calculating chamber response time. and I. Weiss, Y. Mizrahi, E. Raveh.
Significant part of our work was developing a new type of CO2 and H2O gas exchange chambers fit for measuring stand patches. Ground areas of six chambers (ranged between 0.044-4.531 m2) constituted a logarithmic series with doubling diameters from 7.5 to 240.0 cm. We demonstrate one of the first results for stand net ecosystem CO2 exchange (NEE) rates and temporal variability for two characteristic Central European grassland types: loess and sand. The measured mean NEE rates and their ranges in these grasslands were similar to values reported in other studies on temperate grasslands. We also dealt with the spatial scale dependence from ecophysiological point of view. Our chamber-series measurement was performed in a perennial ruderal weed association. The variability of CO2-assimilation of this weed vegetation showed clear spatial scale-dependence. We found the lowest variability of the vegetation photosynthesis at the small-middle scales. The results of spatial variability suggest the 0.2832 m2 patch size is the characteristic unit of the investigated weed association and there is a kind of synphysiological minimi-area with characteristic size for each vegetation type. and Sz. Czóbel ... [et al.].
The aim of the AIRFLY (air fluorescence yield) project is to simulate and to measure the process of the fluorescence and Cherenkov emission produced by impact of cosmic rays on molecules of nitrogen in high level atmosphere. Several setups were designed to measure fluorescent and Cherenkov light. In this paper we report the chamber with controlled atmosphere to simulate conditions in various levels of the Earth atmosphere. The chamber was designed in the Institute of Physics of Academy of Sciences of the Czech Republic in cooperation with the Faculty of Mechanical Engineering, Czech Technical University and the Joint Laboratory of Optics of Palacky University and Institute of Physics of Academy of Sciences in Olomouc. and Cílem projektu AIRFLY je napodobit a proměřit proces fluorescenční a Čerenkovské emise vznikající dopadem kosmického záření na molekuly dusíku ve vyšších vrstvách atmosféry. Bylo navrženo několik uspořádání pro měření fluorescenčního a Čerenkovského světla. V tomto článku je popsána komora s řízenou atmosférou pro modelování podmínek v různých výškách zemské atmosféry. Komora byla zkonstruována ve Fyzikálním ústavu AV ČR ve spolupráci se Strojní fakultou ČVUT a Společnou laboratoří optiky Univerzity Palackého a FZÚ AV ČR v Olomouci.
This paper considers a variant of the bottleneck transportation problem. For each supply-demand point pair, the transportation time is an independent random variable. Preference of each route is attached. Our model has two criteria, namely: minimize the transportation time target subject to a chance constraint and maximize the minimal preference among the used routes. Since usually a transportation pattern optimizing two objectives simultaneously does not exist, we define non-domination in this setting and propose an efficient algorithm to find some non-dominated transportation patterns. We then show the time complexity of the proposed algorithm. Finally, a numerical example is presented to illustrate how our algorithm works.
In this paper, we are concerned with a civil engineering application of optimization, namely the optimal design of a loaded beam. The developed optimization model includes ODE-type constraints and chance constraints. We use the finite element method (FEM) for the approximation of the ODE constraints. We derive a convex reformulation that transforms the problem into a linear one and find its analytic solution. Afterwards, we impose chance constraints on the stress and the deflection of the beam. These chance constraints are handled by a sampling method (Probabilistic Robust Design).
We explore reformulation of nonlinear stochastic programs with several joint chance constraints by stochastic programs with suitably chosen penalty-type objectives. We show that the two problems are asymptotically equivalent. Simpler cases with one chance constraint and particular penalty functions were studied in [6,11]. The obtained problems with penalties and with a fixed set of feasible solutions are simpler to solve and analyze then the chance constrained programs. We discuss solving both problems using Monte-Carlo simulation techniques for the cases when the set of feasible solution is finite or infinite bounded. The approach is applied to a financial optimization problem with Value at Risk constraint, transaction costs and integer allocations. We compare the ability to generate a feasible solution of the original chance constrained problem using the sample approximations of the chance constraints directly or via sample approximation of the penalty function objective.
Jednou, krátce před půlnocí, tížen příslibem redakci Československého časopisu pro fyziku, nechávám běžné práce, otevřu Word a po nadpisu mě napadne podívat se do kalendáře: opravdu, za chvíli začíná 19. říjen 2010. Právě před 100 lety, 19-10-1910 (tak sám rád psal), se narodil Subrahmanyan Chandrasekhar, velká postava vědy 20. století, jeden z nejuniverzálnějších astrofyziků, nositel Nobelovy ceny za fyzku v roce 1983, ve vědeckých kruzích známý jako Chandra. O fyzikálním a astronomickém významu jeho Nobelovy ceny, kterou získal společně s W. A. Fowlerem, jsem již v tomto časopisu psal [1]. V následujícím se chci více zaměřit na události a postavy v okolí jeho světočáry; přitom čerpám především z podrobné biografie [2]. Na závěr připojím několik osobních vzpomínek na interakci s ním, nebudu však již opakovat ty, které jsou uvedeny v článku psaném před 27 lety., Jiří Bičák., and Obsahuje bibliografii
The problem of change detection in nonstatioriary time series using
linear regression models is addressed. It is assumed that the data can by accurately described by a linear regression model with piece-wise constant parameters. Due to the limitations of some classical approaches, based upon the innovation of one autoregressive (AR) model, most algorithms for the change detection presented make use of two AR models: one is a reference model, and the other one is a current model updated via a sliding block. Changes are detected when a suitable “distance” between these two models is high. Three “distance” measures are considered in the paper: cepstral distance, log-likelihood ratio (justified by GLR) and a distance involving the cross-entropy of the two conditional probabilities laws (divergence test). Other methods based on the quadratic forms of Gaussian random variables are also discussed in the paper. Finally, a change detection algorithm using three models and the evolution of Akaike Information Criterion is presented. All the presented algorithms constituted the object of evaluation by multiple simulation and háve been used to change detection in some nonstationary financial and economic time series.