Stochastic interdependence of a probability distribution on a product space is measured by its Kullback-Leibler distance from the exponential family of product distributions (called multi-information). Here we investigate low-dimensional exponential families that contain the maximizers of stochastic interdependence in their closure. Based on a detailed description of the structure of probability distributions with globally maximal multi-information we obtain our main result: The exponential family of pure pair-interactions contains all global maximizers of the multi-information in its closure.
The problem to maximize the information divergence from an exponential family is generalized to the setting of Bregman divergences and suitably defined Bregman families., Johannes Rauh., and Obsahuje bibliografické odkazy
We generalize some criteria of boundedness of L-index in joint variables for in a bidisc analytic functions. Our propositions give an estimate the maximum modulus on a skeleton in a bidisc and an estimate of (p + 1)th partial derivative by lower order partial derivatives (analogue of Hayman’s theorem).
This paper deals with the personality and the work of the noble, writer and intellectual Maximilian count Lamberg (1729–1792) which was already examined by several Czech historians (Polišenský, Kroupa, Cerman). Firstly, the paper evaluates the current state of research to show that despite of the attention of researchers focused on this personality, there are still lot of contexts and details which remain unknown. Secondly, the paper analyses the question of the relevance and the historical value of Lamberg’s conserved works which are situated between memories, essays and autobiographical fiction. In the main part of the paper, the thesis of Jiří Kroupa, which assumes the appurtenance of Maxmilian Lamberg both to the Moravian milieu and to the European Republic of letters, is examined. Lamberg’s accessible works, not only the most famous Mémorial d’un mondain but also the other books, are used as a base of the research.
Intrahepatic cholestasis of pregnancy (ICP) is a frequent liver disorder, mostly occurring in the third trimester. ICP is not harmful to the mothers but threatens the fetus. The authors evaluated steroid alterations in maternal and mixed umbilical blood to elucidate their role in the ICP development. Ten women with ICP were included in the study. Steroids in the maternal blood were measured by Gas Chromatography-Mass Spectrometry (GC-MS) (n=58) and RIA (n=5) at the diagnosis of ICP, labor, day 5 postpartum, week 3 postpartum and week 6 postpartum. The results were evaluated by ANOVA consisting of the subject factor, between subject factors ICP, gestational age at the diagnosis of ICP and gestational age at labor, withinsubject factor Stage and ICP × Stage interaction. The 17 controls were firstly examined in the week 36 of gestation. ICP patients showed reduced CYP17A1 activity in the C17,20 lyase step thus shifting the balance between the toxic conjugated pregnanediols and harmless sulfated 5α/β-reduced-17-oxo C19 steroids. Hence, more toxic metabolites originating in maternal liver from the placental pregnanes may penetrate backward to the fetal circulation. As these alterations persist in puerperium, the circulating steroids could be potentially used for predicting the predisposition to ICP even before next pregnancy., P. Šimják, M. Hill, A. Pařízek, L. Vítek, M. Velíková, M. Dušková, R. Kancheva, J. Bulant, M. Koucký, Z. Kokrdová, K. Adamcová, A. Černý, Z. Hájek, L. Stárka., and Obsahuje bibliografii
V sobotu 27. dubna 2019 se na observatoři v Ondřejově uskutečnilo slavnostní odhalení pamětní desky na dalekohledu D65, který byl pojmenován po jeho konstruktérovi RNDr. Pavlu Mayerovi, DrSc. (1932-2018). Památeční desku odhalil ředitel Astronomického ústavu AV ČR prof. Vladimír Karas spolu s doc. Markem Wolfem (Astronomický ústav UK) a Dr. Jiřím Grygarem (Fyzikální ústav AV ČR). and Jana Žďárská.
This paper describes an application of a neural network approach to
the SM (standard model) and the MSSM (minimal supersymetry standard model) Higgs search in the associated production ttH with H —> bb. This decay channel is considered as a discovery channel for Higgs scenarios for Higgs boson masses in the range 80 - 130 GeV. A neural network model with a special type of data flow is used to separate ttjj background from H —> bb events. The neural network used combines together a classical neural network approach and a linear decision tree separation process. The parameters of these neural networks are randomly generated and the population of the predefined size of those networks is learned to get initial generation for the following genetic algorithm optimization process. A genetic algorithm principles are used to tnne parameters of further neural network individuals derived from previous neural networks by GA operations of crossover and mutation. The goal of this GA process is optimization of the final neural network performance.
Our results show that the NN approach is applicable to the problem of Higgs bosou detection. Neural network filters can be used to emphasize the difference of the Mbb distribntion for events accepted by filter from the distribntion for original events under condition that there is no loss of significance. This improvement of the shape of the Mbb, distribntion can be used as a criterion of existence of Higgs bosou decay in the discovery channel considered.