High order hydrodynamical equations

Hydrodynamical equations act as a link between the local observed magnitudes of galactic motion and the general ones accounting for the behaviour of the Galaxy as a whole. Constraints are set usually in order to use them even in the lower order hierarchy. The authors present in this paper the complete expressions up to their fourth order. These equations will be used in the next future in their general form taking into account both the expected increase of kinematic data that the astrometric mission Hipparcos will provide, and some recent results indicating the possibility to obtain estimates for the momenta gradients.

Simulated Annealing, High-Order Statistics and Mutual Information for Separation of Sources

In this article, the fusion of a stochastic metaheuristic as Simulated Annealing (SA) with classical criteria for convergence of Blind Separation of Sources (BSS), is shown. Although the topic of BSS, by means of various techniques, including ICA, PCA, and neural networks, has been amply discussed in the literature, to date the possibility of using simulated annealing algorithms has not been seriously explored. From experimental results, this paper demonstrates the possible benefits offered by SA in combination with high order statistical and mutual information criteria for BSS, such as robustness against local minima and a high degree of flexibility in the energy function.

Quotient spaces of boundedly rational types

By identifying types whose low-order beliefs up to level li about the state of nature coincide, weobtain quotient type spaces that are typically smaller than the original ones, preserve basic topologicalproperties, and allow standard equilibrium analysis even under bounded reasoning. Our Bayesian Nash(li; l-i)-equilibria capture players inability to distinguish types belonging to the same equivalence class.The case with uncertainty about the vector of levels (li; l-i) is also analyzed. Two examples illustratethe constructions.

New approximation to the third-order density : application to the calculation of correlated multicenter indices

In this work we present the formulas for the calculation of exact three-center electron sharing indices (3c-ESI) and introduce two new approximate expressions for correlated wave functions. The 3c-ESI uses the third-order density, the diagonal of the third-order reduced density matrix, but the approximations suggested in this work only involve natural orbitals and occupancies. In addition, the first calculations of 3c-ESI using Valdemoro's, Nakatsuji's and Mazziotti's approximation for the third-order reduced density matrix are also presented for comparison. Our results on a test set of molecules, including 32 3c-ESI values, prove that the new approximation based on the cubic root of natural occupancies performs the best, yielding absolute errors below 0.07 and an average absolute error of 0.015. Furthemore, this approximation seems to be rather insensitive to the amount of electron correlation present in the system. This newly developed methodology provides a computational inexpensive method to calculate 3c-ESI from correlated wave functions and opens new avenues to approximate high-order reduced density matrices in other contexts, such as the contracted Schrödinger equation and the anti-Hermitian contracted Schrödinger equation

Multiresolution-based image fusion with additive wavelet decomposition

The standard data fusion methods may not be satisfactory to merge a high-resolution panchromatic image and a low-resolution multispectral image because they can distort the spectral characteristics of the multispectral data. The authors developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of such images. The method presented consists of adding the wavelet coefficients of the high-resolution image to the multispectral (low-resolution) data. They have studied several possibilities concluding that the method which produces the best results consists in adding the high order coefficients of the wavelet transform of the panchromatic image to the intensity component (defined as L=(R+G+B)/3) of the multispectral image. The method is, thus, an improvement on standard intensity-hue-saturation (IHS or LHS) mergers. They used the ¿a trous¿ algorithm which allows the use of a dyadic wavelet to merge nondyadic data in a simple and efficient scheme. They used the method to merge SPOT and LANDSATTM images. The technique presented is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

Random mixtures with orientational order, and the anisotropic resistivity tensor of high Tc superconductors

By generalizing effective-medium theory to the case of orientationally ordered but positionally disordered two component mixtures, it is shown that the anisotropic dielectric tensor of oxide superconductors can be extracted from microwave measurements on oriented crystallites of YBa2Cu3O7¿x embedded in epoxy. Surprisingly, this technique appears to be the only one which can access the resistivity perpendicular to the copper¿oxide planes in crystallites that are too small for depositing electrodes. This possibility arises in part because the real part of the dielectric constant of oxide superconductors has a large magnitude. The validity of the effective-medium approach for orientationally ordered mixtures is corroborated by simulations on two¿dimensional anisotropic random resistor networks. Analysis of the experimental data suggests that the zero-temperature limit of the finite frequency resistivity does not vanish along the c axis, a result which would simply the existence of states at the Fermi surface, even in the superconducting state

Model-based diagnosis system: application to constructed wetlands

Report for the scientific sojourn carried out at the Model-based Systems and Qualitative Reasoning Group (Technical University of Munich), from September until December 2005. Constructed wetlands (CWs), or modified natural wetlands, are used all over the world as wastewater treatment systems for small communities because they can provide high treatment efficiency with low energy consumption and low construction, operation and maintenance costs. Their treatment process is very complex because it includes physical, chemical and biological mechanisms like microorganism oxidation, microorganism reduction, filtration, sedimentation and chemical precipitation. Besides, these processes can be influenced by different factors. In order to guarantee the performance of CWs, an operation and maintenance program must be defined for each Wastewater Treatment Plant (WWTP). The main objective of this project is to provide a computer support to the definition of the most appropriate operation and maintenance protocols to guarantee the correct performance of CWs. To reach them, the definition of models which represent the knowledge about CW has been proposed: components involved in the sanitation process, relation among these units and processes to remove pollutants. Horizontal Subsurface Flow CWs are chosen as a case study and the filtration process is selected as first modelling-process application. However, the goal is to represent the process knowledge in such a way that it can be reused for other types of WWTP.

Predictive and distributed routing balancing (PR-DRB): high speed interconnection networks

Current parallel applications running on clusters require the use of an interconnection network to perform communications among all computing nodes available. Imbalance of communications can produce network congestion, reducing throughput and increasing latency, degrading the overall system performance. On the other hand, parallel applications running on these networks posses representative stages which allow their characterization, as well as repetitive behavior that can be identified on the basis of this characterization. This work presents the Predictive and Distributed Routing Balancing (PR-DRB), a new method developed to gradually control network congestion, based on paths expansion, traffic distribution and effective traffic load, in order to maintain low latency values. PR-DRB monitors messages latencies on intermediate routers, makes decisions about alternative paths and record communication pattern information encountered during congestion situation. Based on the concept of applications repetitiveness, best solution recorded are reapplied when saved communication pattern re-appears. Traffic congestion experiments were conducted in order to evaluate the performance of the method, and improvements were observed.

Conformations of poly{G}-poly{C} π stacks with high hole mobility

Charge transfer properties of DNA depend strongly on the π stack conformation. In the present paper, we identify conformations of homogeneous poly-{G}-poly-{C} stacks that should exhibit high charge mobility. Two different computational approaches were applied. First, we calculated the electronic coupling squared, V2, between adjacent base pairs for all 1 ps snapshots extracted from 15 ns molecular dynamics trajectory of the duplex G15. The average value of the coupling squared 〈 V2 〉 is found to be 0.0065 eV2. Then we analyze the base-pair and step parameters of the configurations in which V2 is at least an order of magnitude larger than 〈 V2 〉. To obtain more consistent data, ∼65 000 configurations of the (G:C)2 stack were built using systematic screening of the step parameters shift, slide, and twist. We show that undertwisted structures (twist<20°) are of special interest, because the π stack conformations with strong electronic couplings are found for a wide range of slide and shift. Although effective hole transfer can also occur in configurations with twist=30° and 35°, large mutual displacements of neighboring base pairs are required for that. Overtwisted conformation (twist38°) seems to be of limited interest in the context of effective hole transfer. The results may be helpful in the search for DNA based elements for nanoelectronics

Noninvasive functional and structural exploration of human subcortical structures with high resolution

Projecte de recerca elaborat a partir d’una estada al Max Planck Institute for Human Cognitive and Brain Sciences, Alemanya, entre 2010 i 2012. El principal objectiu d’aquest projecte era estudiar en detall les estructures subcorticals, en concret, el rol dels ganglis basals en control cognitiu durant processament lingüístic i no-lingüístic. Per tal d’assolir una diferenciació minuciosa en els diferents nuclis dels ganglis basals s’utilitzà ressonància magnètica d’ultra-alt camp i alta resolució (7T-MRI). El còrtex prefrontal lateral i els ganglis basals treballant conjuntament per a mitjançar memòria de treball i la regulació “top-down” de la cognició. Aquest circuit regula l’equilibri entre respostes automàtiques i d’alt-ordre cognitiu. Es crearen tres condicions experimentals principals: frases/seqüències noambigües, no-gramatical i ambigües. Les frases/seqüències no-ambigües haurien de provocar una resposta automàtica, mentre les frases/seqüències ambigües i no-gramaticals produïren un conflicte amb la resposta automàtica, i per tant, requeririen una resposta de d’alt-ordre cognitiu. Dins del domini de la resposta de control, la ambigüitat i no-gramaticalitat representen dues dimensions diferents de la resolució de conflicte, mentre per una frase/seqüència temporalment ambigua existeix una interpretació correcte, aquest no és el cas per a les frases/seqüències no-gramaticals. A més, el disseny experimental incloïa una manipulació lingüística i nolingüística, la qual posà a prova la hipòtesi que els efectes són de domini-general; així com una manipulació semàntica i sintàctica que avaluà les diferències entre el processament d’ambigüitat/error “intrínseca” vs. “estructural”. Els resultats del primer experiment (sintax-lingüístic) mostraren un gradient rostroventralcaudodorsal de control cognitiu dins del nucli caudat, això és, les regions més rostrals sostenint els nivells més alts de processament cognitiu

High-SNR power offset in multiantenna communication

The analysis of the multiantenna capacity in the high-SNR regime has hitherto focused on the high-SNR slope (or maximum multiplexing gain), which quantifies the multiplicative increase as function of the number of antennas. This traditional characterization is unable to assess the impact of prominent channel features since, for a majority of channels, the slope equals the minimum of the number of transmit and receive antennas. Furthermore, a characterization based solely on the slope captures only the scaling but it has no notion of the power required for a certain capacity. This paper advocates a more refined characterization whereby, as function of SNRjdB, the high-SNR capacity is expanded as an affine function where the impact of channel features such as antenna correlation, unfaded components, etc, resides in the zero-order term or power offset. The power offset, for which we find insightful closed-form expressions, is shown to play a chief role for SNR levels of practical interest.

High-growth cooperatives: Financial profile and key factors for competitiveness

Given the current economic environment, high-growth companies are particularly relevant for their contribution to employment generation and wealth.This paper discusses the results of a survey that was conducted in order to gain a deeper understanding of high-growth cooperatives through analyzing their financial profiles and then identifying key contributing factors to their growth. To do this, we compared this particular sample with other cooperatives and other high-growth mercantile companies.The results show the main drivers related to high-growth companies success. They are the competitive advantages based on the surveyed group, modern management techniques, quality and productivity, innovation and internationalization. Additionally, we have observed some financial strengths and weaknesses. In this sense, they are under capitalized companies with an unbalanced growth.

Development and Validation of Single Nucleotide Polymorphisms (SNPs) Markers from Two Transcriptome 454-Runs of Turbot (Scophthalmus maximus) Using High-Throughput Genotyping

The turbot (Scophthalmus maximus) is a commercially valuable flatfish and one of the most promising aquaculture species in Europe. Two transcriptome 454-pyrosequencing runs were used in order to detect Single Nucleotide Polymorphisms (SNPs) in genesrelated to immune response and gonad differentiation. A total of 866 true SNPs were detected in 140 different contigs representing 262,093 bp as a whole. Only one true SNP was analyzed in each contig. One hundred and thirteen SNPs out of the 140 analyzed were feasible (genotyped), while Ш were polymorphic in a wild population. Transition/transversion ratio (1.354) was similar to that observed in other fish studies. Unbiased gene diversity (He) estimates ranged from 0.060 to 0.510 (mean = 0.351), minimum allele frequency (MAF) from 0.030 to 0.500 (mean = 0.259) and all loci were in Hardy-Weinberg equilibrium after Bonferroni correction. A large number of SNPs (49) were located in the coding region, 33 representing synonymous and 16 non-synonymous changes. Most SNP-containing genes were related to immune response and gonad differentiation processes, and could be candidates for functional changes leading to phenotypic changes. These markers will be useful for population screening to look for adaptive variation in wild and domestic turbot