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.

An algorithmic Friedman-Pippenger theorem on tree embeddings and applications

An (n, d)-expander is a graph G = (V, E) such that for every X subset of V with vertical bar X vertical bar <= 2n - 2 we have vertical bar Gamma(G)(X) vertical bar >= (d + 1) vertical bar X vertical bar. A tree T is small if it has at most n vertices and has maximum degree at most d. Friedman and Pippenger (1987) proved that any ( n; d)- expander contains every small tree. However, their elegant proof does not seem to yield an efficient algorithm for obtaining the tree. In this paper, we give an alternative result that does admit a polynomial time algorithm for finding the immersion of any small tree in subgraphs G of (N, D, lambda)-graphs Lambda, as long as G contains a positive fraction of the edges of Lambda and lambda/D is small enough. In several applications of the Friedman-Pippenger theorem, including the ones in the original paper of those authors, the (n, d)-expander G is a subgraph of an (N, D, lambda)-graph as above. Therefore, our result suffices to provide efficient algorithms for such previously non-constructive applications. As an example, we discuss a recent result of Alon, Krivelevich, and Sudakov (2007) concerning embedding nearly spanning bounded degree trees, the proof of which makes use of the Friedman-Pippenger theorem. We shall also show a construction inspired on Wigderson-Zuckerman expander graphs for which any sufficiently dense subgraph contains all trees of sizes and maximum degrees achieving essentially optimal parameters. Our algorithmic approach is based on a reduction of the tree embedding problem to a certain on-line matching problem for bipartite graphs, solved by Aggarwal et al. (1996).

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Hybrid layer-by-layer assembly based on animal and vegetable structural materials: multilayered films of collagen and cellulose nanowhiskers

Layer-by-layer (LBL) assembly was used to combine crystalline rod-like nanoparticles obtained from a vegetable source, cellulose nanowhiskers (CNWs), with collagen, the main component of skin and connective tissue found exclusively in animals. The film growth of the multilayered collagen/CNW was monitored by UV-Vis spectroscopy and ellipsometry measurements, whereas the film morphology and surface roughness were characterized by SEM and AFM. UV-Vis spectra showed the deposition of the same amount of collagen, 5 mg m(-2), in each dipping cycle. Ellipsometry data showed an increment in thickness with the number of layers, and the average thickness of each bilayer was found to be 8.6 nm. The multilayered bio-based nanocomposites were formed by single layers of densely packed CNWs adsorbed on top of each thin collagen layer where the hydrogen bonding between collagen amide groups and OH groups of the CNWs plays a mandatory role in the build-up of the thin films. The approach used in this work represents a potential strategy to mimic the characteristics of natural extracellular matrix (ECM) which can be used for applications in the biomedical field.

Economic viability of doses and split-applications of nitrogen fertilization in corn crop in a eutrophic Red Latosol

Nitrogen is the nutrient that is most absorbed by the corn crop, with the most complex management, and has the highest share on the cost of corn production. The objective of this work was to evaluate the economic viability of different rates and split-applications of nitrogen fertilization, as such as urea, in the corn crop in a eutrophic Red Latosol (Oxisol). The study was carried out in the Experimental Station of the Regional Pole of the Sao Paulo Northwest Agribusiness Development (APTA), in Votuporanga, State of Sao Paulo, Brazil. The experimental design was randomized complete blocks with nine treatments and four replications, consisting of five N rates: 0, 55, 95, 135 and 175 kg ha(-1), 15 kg ha-l applied in the seeding and the remainder in top dressing: 40 and 80 kg ha(-1) N at forty days after seeding (DAS), or 1/2 + 1/2 at 20 and 40 DAS; 120 kg ha-1 N split in 1/2 + 1/2 or 1/3 + 1/3 + 1/3 at 20, 40 or 60 DAS; 160 kg ha(-1) N split in 1/4 + 3/8 + 3/8 or 114 + 1/4 + 1/4 + 1/4 at 20, 40, 60 and 80 DAS. The application of 135 kg ha-l of N split in three times provided the best benefit/cost ratio. The non-application of N provided the lowest economic return, proving to be unviable.

Fractionation of Zn, Cd and Pb in a Tropical Soil After Nine-Year Sewage Sludge Applications

A long-term field experiment was carried out in the experiment farm of the Sao Paulo State University, Brazil, to evaluate the phytoavailability of Zn, Cd and Pb in a Typic Eutrorthox soil treated with sewage sludge for nine consecutive years, using the sequential extraction and organic matter fractionation methods. During 2005-2006, maize (Zea mays L.) was used as test plants and the experimental design was in randomized complete blocks with four treatments and five replicates. The treatments consisted of four sewage sludge rates (in a dry basis): 0.0 (control, with mineral fertilization), 45.0, 90.0 and 127.5 t ha(-1), annually for nine years. Before maize sowing, the sewage sludge was manually applied to the soil and incorporated at 10 cm depth. Soil samples (0-20 cm layer) for Zn, Cd and Pb analysis were collected 60 days after sowing. The successive applications of sewage sludge to the soil did not affect heavy metal (Cd and Pb) fractions in the soil, with exception of Zn fractions. The Zn, Cd and Pb distributions in the soil were strongly associated with humin and residual fractions, which are characterized by stable chemical bonds. Zinc, Cd and Pb in the soil showed low phytoavailability after nine-year successive applications of sewage sludge to the soil.

Stimuli-responsive magnetic particles for biomedical applications

In recent years, magnetic nanoparticles have been studied due to their potential applications as magnetic carriers in biomedical area. These materials have been increasingly exploited as efficient delivery vectors, leading to opportunities of use as magnetic resonance imaging (MRI) agents, mediators of hyperthermia cancer treatment and in targeted therapies. Much attention has been also focused on ""smart"" polymers, which are able to respond to environmental changes, such as changes in the temperature and pH. In this context, this article reviews the state-of-the art in stimuli-responsive magnetic systems for biomedical applications. The paper describes different types of stimuli-sensitive systems, mainly temperature- and pH sensitive polymers, the combination of this characteristic with magnetic properties and, finally, it gives an account of their preparation methods. The article also discusses the main in vivo biomedical applications of such materials. A survey of the recent literature on various stimuli-responsive magnetic gels in biomedical applications is also included. (C) 2010 Elsevier B.V. All rights reserved.

A novel electrocatalyst support with proton conductive properties for polymer electrolyte membrane fuel cell applications

The objective of this study is to graft the Surface of carbon black, by chemically introducing polymeric chains (Nafion (R) like) with proton-conducting properties. This procedure aims for a better interaction of the proton-conducting phase with the metallic catalyst particles, as well as hinders posterior support particle agglomeration. Also loss of active surface call be prevented. The proton conduction between the active electrocatalyst site and the Nafion (R) ionomer membrane should be enhanced, thus diminishing the ohmic drop ill the polymer electrolyte membrane fuel cell (PEMFC). PtRu nanoparticles were supported on different carbon materials by the impregnation method and direct reduction with ethylene glycol and characterized using amongst others FTIR, XRD and TEM. The screen printing technique was used to produce membrane electrode assemblies (MEA) for single cell tests in H(2)/air(PEMFC) and methanol operation (DMFC). In the PEMFC experiments, PtRu supported on grafted carbon shows 550 mW cm(-2) gmetal(-1) power density, which represents at least 78% improvement in performance, compared to the power density of commercial PtRu/C ETEK. The DMFC results of the grafted electrocatalyst achieve around 100% improvement. The polarization Curves results clearly show that the main Cause of the observed effect is the reduction in ohmic drop, caused by the grafted polymer. (C) 2009 Elsevier B.V. All rights reserved.

Comparative analysis of triple band S-C-L erbium-doped fibre and semiconductor optical amplifier for CWDM applications

The authors present a comparative analysis between a triple-band S-C-L erbium-doped fibre amplifier and a commercial semiconductor optical amplifier in a CWDM application scenario. Both technologies were characterised for gain and noise figures from 1480 to 1610 nm (S, C and L bands) and their systemic performances were evaluated in terms of bit error rate measurements for a wide range of optical power levels.

A novel multiobjective optimization algorithm based on bacterial chemotaxis

In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

Evaluation of austenitic-ferritic stainless steel wires for orthodontic applications

Several studies have shown that austenitic stainless steels are suitable for use in the final phases of orthodontic treatments, such as finishing and retention. These steels demonstrate appropriate mechanical properties, such as high ultimate tensile strength and good corrosion resistance. A new class of materials, the austenic-ferritic stainless steels, is substituting for austenitic stainless steels in several industrial applications where these properties are necessary. This work supports the hypothesis that orthodontic wires of austenic-ferritic stainless steels can replace austenitic stainless steels. The advantages are cost reduction and decrease of the nickel hypersensitivity effect in patients undergoing orthodontic treatments. The object of this study was to evaluate wires of austenitic-ferritic stainless steel SEW 410 Nr. 14517 (Cr26Ni6Mo3Cu3) produced by cold working through rolling and drawing processes. Tests were performed to evaluate the ultimate tensile strength, hardness, ductility, and formability. In accordance with technical standards the wires exhibited ultimate tensile strength and ductility suitable for orthodontic clinical applications. These austenitie-ferritic wires can be an alternative to substitute the common commercial wires of austenic stainless steels with the advantage of decreasing the nickel content.

Porous alumina-spinel ceramics for high temperature applications

In order to reduce energy costs, high-temperature insulation porous refractory ceramics have been subjected to increasing demands. Among the techniques used to produce these materials (such as the addition of foaming agents and organic compounds), the pore generation via phase transformation presents key aspects, such as easy processing and the absence of toxic volatiles. In this study, this technique was applied to produce porous ceramics by decomposing an aluminum magnesium hydro-carbonate known as hydrotalcite (Mg(6)Al(2)(CO(3))(OH)(16)center dot 4H(2)O). It was found out that by using this complex compound, a large fraction of pores can be generated and kept at high temperatures (above 1300 degrees C) due to the in situ formation of spinel-like phases (MgAl(2)O(4)). (C) 2011 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Monitoring Services for Industrial Applications

Sao Paulo Research Foundation (FAPESP) in Brazil

Recycling Krylov subspaces for efficient large-scale electrical impedance tomography

Electrical impedance tomography (EIT) captures images of internal features of a body. Electrodes are attached to the boundary of the body, low intensity alternating currents are applied, and the resulting electric potentials are measured. Then, based on the measurements, an estimation algorithm obtains the three-dimensional internal admittivity distribution that corresponds to the image. One of the main goals of medical EIT is to achieve high resolution and an accurate result at low computational cost. However, when the finite element method (FEM) is employed and the corresponding mesh is refined to increase resolution and accuracy, the computational cost increases substantially, especially in the estimation of absolute admittivity distributions. Therefore, we consider in this work a fast iterative solver for the forward problem, which was previously reported in the context of structural optimization. We propose several improvements to this solver to increase its performance in the EIT context. The solver is based on the recycling of approximate invariant subspaces, and it is applied to reduce the EIT computation time for a constant and high resolution finite element mesh. In addition, we consider a powerful preconditioner and provide a detailed pseudocode for the improved iterative solver. The numerical results show the effectiveness of our approach: the proposed algorithm is faster than the preconditioned conjugate gradient (CG) algorithm. The results also show that even on a standard PC without parallelization, a high mesh resolution (more than 150,000 degrees of freedom) can be used for image estimation at a relatively low computational cost. (C) 2010 Elsevier B.V. All rights reserved.

Comparison between DC(+) and Square Wave AC SAW Current Outputs to Weld AISI 304 for Low-Temperature Applications

Welded equipment for cryogenic applications is utilized in chemical, petrochemical, and metallurgical industries. One material suitable for cryogenic application is austenitic stainless steel, which usually doesn`t present ductile/brittle transition temperature, except in the weld metal, where the presence of ferrite and micro inclusions can promote a brittle failure, either by ferrite cleavage or dimple nucleation and growth, respectively. A 25-mm- (1-in.-) thick AISI 304 stainless steel base metal was welded with the SAW process using a 308L solid wire and two kinds of fluxes and constant voltage power sources with two types of electrical outputs: direct current electrode positive and balanced square wave alternating current. The welded joints were analyzed by chemical composition, microstructure characterization, room temperature mechanical properties, and CVN impact test at -100 degrees C (-73 degrees F). Results showed that an increase of chromium and nickel content was observed in all weld beads compared to base metal. The chromium and nickel equivalents ratio for the weld beads were always higher for welding with square wave AC for the two types of fluxes than for direct current. The modification in the Cr(eq)/Ni(eq) ratio changes the delta ferrite morphology and, consequently, modifies the weld bead toughness at lower temperatures. The oxygen content can also affect the toughness in the weld bead. The highest absorbed energy in a CVN impact test was obtained for the welding condition with square wave AC electrical output and neutral flux, followed by DC(+) electrical output and neutral flux, and square wave AC electrical output and alloyed flux.