Dissipative Processes in the Early Universe: Bulk Viscosity

In this talk, we discuss one of the dissipative processes which likely take place in the Early Universe. We assume that the matter filling the isotropic and homogeneous background is to be described by a relativistic viscous fluid characterized by an ultra-relativistic equation of state and finite bulk viscosity deduced from recent lattice QCD calculations and heavy-ion collisions experiments. We concentrate our treatment to bulk viscosity as one of the essential dissipative processes in the rapidly expanding Early Universe and deduce the dependence of the scale factor and Hubble parameter on the comoving time $t$. We find that both scale factor and Hubble parameter are finite at $t=0$, revering to absence of singularity. We also find that their evolution apparently differs from the one resulting in when assuming that the background matter is an ideal and non-viscous fluid.Comment: 8 pages, 2 eps figure, Invited talk given at the 7th international conference on "Modern Problems of Nuclear Physics", 22-25 September 2009, Tashkent-Uzbekista

Property and activity of molybdates dispersed on silica obtained from various synthetic procedures

The synthesis and characterization of several dispersed molybdena catalysts on silica support (MoO3-SiO2) prepared from a variety of precursors (Mo(VI)-acetylacetonate, oxo-peroxo Mo-species, hydrated ammonium heptamolybdate) and preparation methods (deposition of the Mo-phase on finite SiO2 support by aqueous and methanol impregnations, by adsorption, by oxo-peroxo route-like, and by one-step synthesis of MoO3-SiO2 system with molecular precursors) are presented. The molybdena concentration on silica was comprised in a large interval (1.5 - 14 wt%) depending on the preparation method which governed the Mo-loading on silica. Convenient comparisons among samples at similar Mo-concentration have been made discussing the morphologic-structural (XRD, XPS, UV-vis-DRS, and N2-adsorption) and physicochemical (TG-DTG, TPR, and n-butylamine-TPD) sample properties. Polymeric octahedral polymolybdate aggregates predominated in the samples prepared by aqueous and methanol impregnations, which were at high Mo-concentration. On the contrary, isolated Mo(VI) species in distorted Td symmetry predominated in the sample prepared by adsorption which was at very low Mo-concentration. The sample acidity was composed of a weak acidy site population, associated with the silica support, and a strong acid site population associated with the Mo-dispersed phase. Oxidation tests of formaldehyde, an oxygen-containing VOC (Volatile Organic Compound), were performed to determine the prevalent redox or acidic function of the Mo-species at the surface of the catalysts

Effect of Continuous Education on Readmission Rates for CHF Patients

Aim: To evaluate if continuing the education of Congest Heart Failure patients post-discharge will decrease the amount of readmissions within 6 months of discharge. Background: Causes for decreased readmission rates in Congestive Heart Failure patients have been evaluated in multiple studies. The evaluation of the current research showed having discharge education and post- discharge follow-ups decreased the rate of readmission within 6 months. There is a sufficient amount of evidence supporting the implementation of education upon discharge and follow-ups of Congestive Heart Failure patients. Data Source: Databases and search engines used included: PubMed, OneSearch, CINAHL, DogPile, and Google. Of 25 articles read, 10 articles were included in the review of literature. Results: Three specific forms of patient education were reviewed. These included a telephone follow up program, six months of continued patient education, and a plan tailored to the individual needs of the patient. All three interventions were effective in showing a decrease in readmission rates. Conclusion: Increased time of continued education is believed to be effective in decreasing the readmission of Congestive Heart Failure patients within 30 days of discharge

Detection of trend changes in time series using Bayesian inference

Change points in time series are perceived as isolated singularities where two regular trends of a given signal do not match. The detection of such transitions is of fundamental interest for the understanding of the system's internal dynamics. In practice observational noise makes it difficult to detect such change points in time series. In this work we elaborate a Bayesian method to estimate the location of the singularities and to produce some confidence intervals. We validate the ability and sensitivity of our inference method by estimating change points of synthetic data sets. As an application we use our algorithm to analyze the annual flow volume of the Nile River at Aswan from 1871 to 1970, where we confirm a well-established significant transition point within the time series.Comment: 9 pages, 12 figures, submitte

Statistical Mechanics of Learning: A Variational Approach for Real Data

Using a variational technique, we generalize the statistical physics approach of learning from random examples to make it applicable to real data. We demonstrate the validity and relevance of our method by computing approximate estimators for generalization errors that are based on training data alone.Comment: 4 pages, 2 figure

On the uniqueness of the surface sources of evoked potentials

The uniqueness of a surface density of sources localized inside a spatial region $R$ and producing a given electric potential distribution in its boundary $B_0$ is revisited. The situation in which $R$ is filled with various metallic subregions, each one having a definite constant value for the electric conductivity is considered. It is argued that the knowledge of the potential in all $B_0$ fully determines the surface density of sources over a wide class of surfaces supporting them. The class can be defined as a union of an arbitrary but finite number of open or closed surfaces. The only restriction upon them is that no one of the closed surfaces contains inside it another (nesting) of the closed or open surfaces.Comment: 16 pages, 5 figure

A Bayesian Approach to Inverse Quantum Statistics

A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over potentials implemented in form of stochastic processes. Its specific advantages are the possibilities to deal with heterogeneous data and to express a priori information explicitly, i.e., directly in terms of the potential of interest. A numerical solution in maximum a posteriori approximation was feasible for one--dimensional problems. Using correct a priori information turned out to be essential.Comment: 4 pages, 6 figures, revte