Newtonian perturbations on models with matter creation

Creation of cold dark matter (CCDM) can macroscopically be described by a negative pressure, and, therefore, the mechanism is capable to accelerate the Universe, without the need of an additional dark energy component. In this framework, we discuss the evolution of perturbations by considering a Neo-Newtonian approach where, unlike in the standard Newtonian cosmology, the fluid pressure is taken into account even in the homogeneous and isotropic background equations (Lima, Zanchin, and Brandenberger, MNRAS 291, L1, 1997). The evolution of the density contrast is calculated in the linear approximation and compared to the one predicted by the Lambda CDM model. The difference between the CCDM and Lambda CDM predictions at the perturbative level is quantified by using three different statistical methods, namely: a simple chi(2)-analysis in the relevant space parameter, a Bayesian statistical inference, and, finally, a Kolmogorov-Smirnov test. We find that under certain circumstances, the CCDM scenario analyzed here predicts an overall dynamics (including Hubble flow and matter fluctuation field) which fully recovers that of the traditional cosmic concordance model. Our basic conclusion is that such a reduction of the dark sector provides a viable alternative description to the accelerating Lambda CDM cosmology.

Systematic Management of Variability in UML-based Software Product Lines

This paper presents SMarty, a variability management approach for UML-based software product lines (PL). SMarty is supported by a UML profile, the SMartyProfile, and a process for managing variabilities, the SMartyProcess. SMartyProfile aims at representing variabilities, variation points, and variants in UML models by applying a set of stereotypes. SMartyProcess consists of a set of activities that is systematically executed to trace, identify, and control variabilities in a PL based on SMarty. It also identifies variability implementation mechanisms and analyzes specific product configurations. In addition, a more comprehensive application of SMarty is presented using SEI's Arcade Game Maker PL. An evaluation of SMarty and related work are discussed.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Estimation of the thickness and the optical parameters of several stacked thin films using optimization

The reverse engineering problem addressed in the present research consists of estimating the thicknesses and the optical constants of two thin films deposited on a transparent substrate using only transmittance data through the whole stack. No functional dispersion relation assumptions are made on the complex refractive index. Instead, minimal physical constraints are employed, as in previous works of some of the authors where only one film was considered in the retrieval algorithm. To our knowledge this is the first report on the retrieval of the optical constants and the thickness of multiple film structures using only transmittance data that does not make use of dispersion relations. The same methodology may be used if the available data correspond to normal reflectance. The software used in this work is freely available through the PUMA Project web page (http://www.ime.usp.br/similar to egbirgin/puma/). (C) 2008 Optical Society of America

Atratividade de projetos de software livre: importância teórica e estratégias para administração

Thousands of Free and Open Source Software Projects (FSP) were, and continually are, created on the Internet. This scenario increases the number of opportunities to collaborate to the same extent that it promotes competition for users and contributors, who can guide projects to superior levels, unachievable by founders alone. Thus, given that the main goal of FSP founders is to improve their projects by means of collaboration, the importance to understand and manage the capacity of attracting users and contributors to the project is established. To support researchers and founders in this challenge, the concept of attractiveness is introduced in this paper, which develops a theoretical-managerial toolkit about the causes, indicators and consequences of attractiveness, enabling its strategic management.

Response surface methodology as an approach to determine optimal activities of lipase entrapped in sol-gel matrix using different vegetable oils

The conditions for maximization of the enzymatic activity of lipase entrapped in sol-gel matrix were determined for different vegetable oils using an experimental design. The effects of pH, temperature, and biocatalyst loading on lipase activity were verified using a central composite experimental design leading to a set of 13 assays and the surface response analysis. For canola oil and entrapped lipase, statistical analyses showed significant effects for pH and temperature and also the interactions between pH and temperature and temperature and biocatalyst loading. For the olive oil and entrapped lipase, it was verified that the pH was the only variable statistically significant. This study demonstrated that response surface analysis is a methodology appropriate for the maximization of the percentage of hydrolysis, as a function of pH, temperature, and lipase loading.

A contribution for thermoeconomic modelling: A methodology proposal

This work presents a thermoeconomic optimization methodology for the analysis and design of energy systems. This methodology involves economic aspects related to the exergy conception, in order to develop a tool to assist the equipment selection, operation mode choice as well as to optimize the thermal plants design. It also presents the concepts related to exergy in a general scope and in thermoeconomics which combines the thermal sciences principles (thermodynamics, heat transfer, and fluid mechanics) and the economic engineering in order to rationalize energy systems investment decisions, development and operation. Even in this paper, it develops a thermoeconomic methodology through the use of a simple mathematical model, involving thermodynamics parameters and costs evaluation, also defining the objective function as the exergetic production cost. The optimization problem evaluation is developed for two energy systems. First is applied to a steam compression refrigeration system and then to a cogeneration system using backpressure steam turbine. (C) 2010 Elsevier Ltd. All rights reserved.

Improved xylitol production in media containing phenolic aldehydes: application of response surface methodology for optimization and modeling of bioprocess

BACKGROUND: The combined effects of vanillin and syringaldehyde on xylitol production by Candida guilliermondii using response surface methodology (RSM) have been studied. A 2(2) full-factorial central composite design was employed for experimental design and analysis of the results. RESULTS: Maximum xylitol productivities (Q(p) = 0.74 g L(-1) h(-1)) and yields (Y(P/S) = 0.81 g g(-1)) can be attained by adding only vanillin at 2.0 g L(-1) to the fermentation medium. These data were closely correlated with the experimental results obtained (0.69 +/- 0.04 g L(-1) h(-1) and 0.77 +/- 0.01 g g(-1)) indicating a good agreement with the predicted value. C. guilliermondii was able to convert vanillin completely after 24 h of fermentation with 94% yield of vanillyl alcohol. CONCLUSIONS: The bioconversion of xylose into xylitol by C. guilliermondii is strongly dependent on the combination of aldehydes and phenolics in the fermentation medium. Vanillin is a source of phenolic compound able to improve xylitol production by yeast. The conversion of vanillin to alcohol vanilyl reveals the potential of this yeast for medium detoxification. (C) 2009 Society of Chemical Industry

Simultaneous saccharification and ethanol fermentation of oxalic acid pretreated corncob assessed with response surface methodology

Response surface methodology was used to evaluate optimal time, temperature and oxalic acid concentration for simultaneous saccharification and fermentation (SSF) of corncob particles by Pichia stipitis CBS 6054. Fifteen different conditions for pretreatment were examined in a 2(3) full factorial design with six axial points. Temperatures ranged from 132 to 180 degrees C, time from 10 to 90 min and oxalic acid loadings from 0.01 to 0.038 g/g solids. Separate maxima were found for enzymatic saccharification and hemicellulose fermentation, respectively, with the condition for maximum saccharification being significantly more severe. Ethanol production was affected by reaction temperature more than by oxalic acid and reaction time over the ranges examined. The effect of reaction temperature was significant at a 95% confidence level in its effect on ethanol production. Oxalic acid and reaction time were statistically significant at the 90% level. The highest ethanol concentration (20 g/l) was obtained after 48 h with an ethanol volumetric production rate of 0.42 g ethanol l(-1) h(-1). The ethanol yield after SSF with P. stipitis was significantly higher than predicted by sequential saccharification and fermentation of substrate pretreated under the same condition. This was attributed to the secretion of beta-glucosidase by P. stipitis. During SSF, free extracellular beta-glucosidase activity was 1.30 pNPG U/g with P. stipitis, while saccharification without the yeast was 0.66 pNPG U/g. Published by Elsevier Ltd.

Evaluation of three brands of drug interaction software for use in intensive care units

Objective To evaluate drug interaction software programs and determine their accuracy in identifying drug-drug interactions that may occur in intensive care units. Setting The study was developed in Brazil. Method Drug interaction software programs were identified through a bibliographic search in PUBMED and in LILACS (database related to the health sciences published in Latin American and Caribbean countries). The programs` sensitivity, specificity, and positive and negative predictive values were determined to assess their accuracy in detecting drug-drug interactions. The accuracy of the software programs identified was determined using 100 clinically important interactions and 100 clinically unimportant ones. Stockley`s Drug Interactions 8th edition was employed as the gold standard in the identification of drug-drug interaction. Main outcome Sensitivity, specificity, positive and negative predictive values. Results The programs studied were: Drug Interaction Checker (DIC), Drug-Reax (DR), and Lexi-Interact (LI). DR displayed the highest sensitivity (0.88) and DIC showed the lowest (0.69). A close similarity was observed among the programs regarding specificity (0.88-0.92) and positive predictive values (0.88-0.89). The DIC had the lowest negative predictive value (0.75) and DR the highest (0.91). Conclusion The DR and LI programs displayed appropriate sensitivity and specificity for identifying drug-drug interactions of interest in intensive care units. Drug interaction software programs help pharmacists and health care teams in the prevention and recognition of drug-drug interactions and optimize safety and quality of care delivered in intensive care units.

Developing and implementing an open and non-proprietary device description for FOUNDATION fieldbus based on software standards

Support for interoperability and interchangeability of software components which are part of a fieldbus automation system relies on the definition of open architectures, most of them involving proprietary technologies. Concurrently, standard, open and non-proprietary technologies, such as XML, SOAP, Web Services and the like, have greatly evolved and been diffused in the computing area. This article presents a FOUNDATION fieldbus (TM) device description technology named Open-EDD, based on XML and other related technologies (XLST, DOM using Xerces implementation, OO, XMIL Schema), proposing an open and nonproprietary alternative to the EDD (Electronic Device Description). This initial proposal includes defining Open-EDDML as the programming language of the technology in the FOUNDATION fieldbus (TM) protocol, implementing a compiler and a parser, and finally, integrating and testing the new technology using field devices and a commercial fieldbus configurator. This study attests that this new technology is feasible and can be applied to other configurators or HMI applications used in fieldbus automation systems. (c) 2008 Elsevier B.V. All rights reserved.

Human gait recognition using extraction and fusion of global motion features

This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.

Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

Combined solution for fault location in three-terminal lines based on wavelet transforms

This work presents the study and development of a combined fault location scheme for three-terminal transmission lines using wavelet transforms (WTs). The methodology is based on the low- and high-frequency components of the transient signals originated from fault situations registered in the terminals of a system. By processing these signals and using the WT, it is possible to determine the time of travelling waves of voltages and/or currents from the fault point to the terminals, as well as estimate the fundamental frequency components. A new approach presents a reliable and accurate fault location scheme combining some different solutions. The main idea is to have a decision routine in order to select which method should be used in each situation presented to the algorithm. The combined algorithm was tested for different fault conditions by simulations using the ATP (Alternative Transients Program) software. The results obtained are promising and demonstrate a highly satisfactory degree of accuracy and reliability of the proposed method.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.