Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

Anthropometric characteristics and motor skills in talent selection and development in indoor soccer

Kick performance, anthropometric characteristics, slalom, and linear running were assessed in 49 (24 elite, 25 nonelite) postpubertal indoor soccer players in order to (a) verify whether anthropometric characteristics and physical and technical capacities can distinguish players of different competitive levels, (b) compare the kicking kinematics of these groups, with and without a defined target, and (c) compare results on the assessments and coaches` subjective rankings of the players. Thigh circumference and specific technical capacities differentiated the players by level of play; cluster analysis correctly classified 77.5% of the players. The correlation between players` standardized measures and the coaches` rankings was 0.29. Anthropometric characteristics and physical capacities do not necessarily differentiate players at post-pubertal stages and should not be overvalued during early development. Considering the coaches` rankings, performance measures outside the specific game conditions may not be useful in identification of talented players.

Raspberry (Rubus idaeus L.) wine: Yeast selection, sensory evaluation and instrumental analysis of volatile and other compounds

To evaluate the potential for fermentation of raspberry pulp, sixteen yeast strains (S. cerevisiae and S. bayanus) were studied. Volatile compounds were determined by GC-MS, GC-FID, and GC-PFPD. Ethanol. glycerol and organic acids were determined by HPLC. HPLC-DAD was used to analyse phenolic acids. Sensory analysis was performed by trained panellists. After a screening step, CAT-1, UFLA FW 15 and S. bayanus CBS 1505 were previously selected based on their fermentative characteristics and profile of the metabolites identified. The beverage produced with CAT-1 showed the highest volatile fatty acid concentration (1542.6 mu g/L), whereas the beverage produced with UFLA FIN 15 showed the highest concentration of acetates (2211.1 mu g/L) and total volatile compounds (5835 mu g/L). For volatile sulphur compounds. 566.5 mu g/L were found in the beverage produced with S. bayanus CBS 1505. The lowest concentration of volatile sulphur compounds (151.9 mu g/L) was found for the beverage produced with UFLA FW 15. In the sensory analysis, the beverage produced with UFLA FW 15 was characterised by the descriptors raspberry, cherry, sweet, strawberry, floral and violet. In conclusion, strain UFLA FW 15 was the yeast that produced a raspberry wine with a good chemical and sensory quality. (C) 2010 Elsevier Ltd. All rights reserved.

Selection of new glass-forming compositions in Al-La system using a combination of topological instability and thermodynamic criteria

A combination of an extension of the topological instability ""lambda criterion"" and a thermodynamic criterion were applied to the Al-La system, indicating the best range of compositions for glass formation. Alloy compositions in this range were prepared by melt-spinning and casting in an arc-melting furnace with a wedge-section copper mold. The GFA of these samples was evaluated by X-ray diffraction, differential scanning calorimetry and scanning electron microscopy. The results indicated that the gamma* parameter of compositions with high GFA is higher, corresponding to a range in which the lambda parameter is greater than 0.1, which are compositions far from Al solid solution. A new alloy was identified with the best GFA reported so far for this system, showing a maximum thickness of 286 mu m in a wedge-section copper mold. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Design and Characterization of a Biomimetic Piezoelectric Pump Inspired on Group Fish Swimming Effect

Flow pumps are important tools in several engineering areas, such as in the fields of bioengineering and thermal management solutions for electronic devices. Nowadays, many of the new flow pump principles are based on the use of piezoelectric actuators, which present some advantages such as miniaturization potential and lower noise generation. In previous work, authors presented a study of a novel pump configuration based on placing an oscillating bimorph piezoelectric actuator in water to generate flow. It was concluded that this oscillatory behavior (such as fish swimming) yields vortex interaction, generating flow rate due to the action and reaction principle. Thus, following this idea the objective of this work is to explore this oscillatory principle by studying the interaction among generated vortex from two bimorph piezoelectric actuators oscillating inside the same pump channel, which is similar to the interaction of vortex generated by frontal fish and posterior ones when they swim together in a group formation. It is shown that parallel-series configurations of bimorph piezoelectric actuators inside the same pump channel provide higher flow rates and pressure for liquid pumping than simple parallel-series arrangements of corresponding single piezoelectric pumps, respectively. The scope of this work includes structural simulations of bimorph piezoelectric actuators, fluid flow simulations, and prototype construction for result validation.

A biomimetic piezoelectric pump: Computational and experimental characterization

Flow pumps have been developed for classical applications in Engineering, and are important instruments in areas such as Biology and Medicine. Among applications for this kind of device we notice blood pump and chemical reagents dosage in Bioengineering. Furthermore, they have recently emerged as a viable thermal management solution for cooling applications in small-scale electronic devices. This work presents the performance study of a novel principle of a piezoelectric flow pump which is based oil the use of a bimorph piezoelectric actuator inserted in fluid (water). Piezoelectric actuators have some advantages over classical devices, such as lower noise generation and ease of miniaturization. The main objective is the characterization of this piezoelectric pump principle through computational simulations (using finite element software), and experimental tests through a manufactured prototype. Computational data, Such as flow rate and pressure curves, have also been compared with experimental results for validation purposes. (C) 2009 Elsevier B.V. All rights reserved.

Miniaturized structures for removal or selection of particles from liquid flow

The aim of this work was the development of miniaturized structures useful for retention and/or selection of particles and viscous substances from a liquid flow. The proposed low costs structures are similar to macroscopic wastewater treatment systems, named baffles, and allow disassemble. They were simulated using FEMLAB 3.2b package and manufactured in acrylic with conventional tools. Tests for retention or selection of particles in water or air and viscous fluids in water were carried out. Either in air or water particles with 50 mu m diameter will be retained but not with 13 mu m diameter. In aqueous flow, it is also possible the retention of viscous samples, such as silicone 350 cSt. The simulated results showed good agreement with experimental measurements. These miniaturized structures can be useful in sample pretreatment for chemical analysis and microorganism manipulation. (C) 2007 Elsevier B.V. All rights reserved.

Computational fluid dynamics investigation of a centrifugal blood pump

In the development of a ventricular assist device, computational fluid dynamics (CFD) analysis is an efficient tool to obtain the best design before making the final prototype. In this study, different designs of a centrifugal blood pump were developed to investigate flow characteristics and performance. This study assumed the blood flow as being an incompressible homogeneous Newtonian fluid. A constant velocity was applied at the inlet; no slip boundary conditions were applied at device wall; and pressure boundary conditions were applied at the outlet. The CFD code used in this work was based on the finite volume method. In the future, the results of CFD analysis can be compared with flow visualization and hemolysis tests.

A new technique to control brushless motor for blood pump application

This article presents a back-electromotive force (BEMF)-based technique of detection for sensorless brushless direct current motor (BLDCM) drivers. The BLDCM has been chosen as the energy converter in rotary or pulsatile blood pumps that use electrical motors for pumping. However, in order to operate properly, the BLDCM driver needs to know the shaft position. Usually, that information is obtained through a set of Hall sensors assembled close to the rotor and connected to the electronic controller by wires. Sometimes, a large distance between the motor and controller makes the system susceptible to interference on the sensor signal because of winding current switching. Thus, the goal of the sensorless technique presented in this study is to avoid this problem. First, the operation of BLDCM was evaluated on the electronic simulator PSpice. Then, a BEMF detector circuitry was assembled in our laboratories. For the tests, a sensor-dependent system was assembled where the direct comparison between the Hall sensors signals and the detected signals was performed. The obtained results showed that the output sensorless detector signals are very similar to the Hall signals at speeds of more than 2500 rpm. Therefore, the sensorless technique is recommended as a responsible or redundant system to be used in rotary blood pumps.

Obtaining and selection of hexokinases-less strains of Saccharomyces cerevisiae for production of ethanol and fructose from sucrose

Saccharomyces cerevisiae hexokinase-less strains were produced to study the production of ethanol and fructose from sucrose. These strains do not have the hexokinases A and B. Twenty-three double-mutant strains were produced, and then, three were selected for presenting a smaller growth in yeast extract-peptone-fructose. In fermentations with a medium containing sucrose (180.3 g L-1) and with cell recycles, simulating industrial conditions, the capacity of these mutant yeasts in inverting sucrose and fermenting only glucose was well characterized. Besides that, we could also see their great tolerance to the stresses of fermentative recycles, where fructose production (until 90 g L-1) and ethanol production (until 42.3 g L-1) occurred in cycles of 12 h, in which hexokinase-less yeasts performed high growth (51.2% of wet biomass) and viability rates (77% of viable cells) after nine consecutive cycles.

Genetic potential of a maize population from Southern Brazil for the modified convergent-divergent selection scheme

Maize (Zea mays L.) is a very important cereal to world-wide economy which is also true for Brazil, particularly in the South region. Grain yield and plant height have been chosen as important criteria by breeders and farmers from Santa Catarina State (SC), Brazil. The objective of this work was to estimate genetic-statistic parameters associated with genetic gain for grain yield and plant height, in the first cycle of convergent-divergent half-sib selection in a maize population (MPA1) cultivated by farmers within the municipality of Anchieta (SC). Three experiments were carried out in different small farms at Anchieta using low external agronomic inputs; each experiment represented independent samples of half-sib families, which were evaluated in randomized complete blocks with three replications per location. Significant differences among half-sib families were observed for both variables in all experiments. The expected responses to truncated selection of the 25% better families in each experiment were 5.1, 5.8 and 5.2% for reducing plant height and 3.9, 5.7 and 5.0% for increasing grain yield, respectively. The magnitudes of genetic-statistic parameters estimated evidenced that the composite population MPA1 exhibits enough genetic variability to be used in cyclical process of recurrent selection. There were evidences that the genetic structure of the base population MPA1, as indicated by its genetic variability, may lead to expressive changes in the traits under selection, even under low selection pressure.

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

Vegetative and fruit characteristics of papaya trees obtained by mass selection

The present work had as purpose to evaluate some characteristics of papaya trees (Carica papaya L.), Golden cultivar, obtained trough plant mass selection, regarding plant and fruit quality in the first months of production. The samples were evaluated in a commercial crop at: 0, 20, 40, 70, 130, 180, 230, 260, 280, 310 and 340 days after the planting (DAP) and the first fruits were harvested at 230 DAP. The results showed the low height (199cm in 340 DAP) and low first flowering`s heigth (71cm), which is important to facilitate the harvest process. The plants presented good yield with high number of leafs (allowing a great area of fruit cover) and about 60 fruits per plant. The fruits kept similar features to cv. Golden. The fruit`s fresh weight ranged from 302.4 to 467.5g, which is in the range of the Brazilian market. The pulp thickness was 2.35cm, which is a feature of great economic interest. The pulp thickness showed close relation with climatic factors, and great variations of temperature and precipitation accelerated the pulp loss of thickness.