Discrete Particle Swarm Optimization for the minimum labelling Steiner tree problem

Particle Swarm Optimization is an evolutionary method inspired by the social behaviour of individuals inside swarms in nature. Solutions of the problem are modelled as members of the swarm which fly in the solution space. The evolution is obtained from the continuous movement of the particles that constitute the swarm submitted to the effect of the inertia and the attraction of the members who lead the swarm. This work focuses on a recent Discrete Particle Swarm Optimization for combinatorial optimization, called Jumping Particle Swarm Optimization. Its effectiveness is illustrated on the minimum labelling Steiner tree problem: given an undirected labelled connected graph, the aim is to find a spanning tree covering a given subset of nodes, whose edges have the smallest number of distinct labels

Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

<p>Abstract</p> <p>Background</p> <p>Detailed experimental three dimensional structures of carbohydrates are often difficult to acquire. Molecular modelling and computational conformation prediction are therefore commonly used tools for three dimensional structure studies. Modelling procedures generally require significant training and computing resources, which is often impractical for most experimental chemists and biologists. <monospace>Shape</monospace> has been developed to improve the availability of modelling in this field.</p> <p>Results</p> <p>The <monospace>Shape</monospace> software package has been developed for simplicity of use and conformation prediction performance. A trivial user interface coupled to an efficient genetic algorithm conformation search makes it a powerful tool for automated modelling. Carbohydrates up to a few hundred atoms in size can be investigated on common computer hardware. It has been shown to perform well for the prediction of over four hundred bioactive oligosaccharides, as well as compare favourably with previously published studies on carbohydrate conformation prediction.</p> <p>Conclusion</p> <p>The <monospace>Shape</monospace> fully automated conformation prediction can be used by scientists who lack significant modelling training, and performs well on computing hardware such as laptops and desktops. It can also be deployed on computer clusters for increased capacity. The prediction accuracy under the default settings is good, as it agrees well with experimental data and previously published conformation prediction studies. This software is available both as open source and under commercial licenses.</p

Reverberation Mapping and the Physics of Active Galactic Nuclei

Reverberation-mapping campaigns have revolutionized our understanding of AGN. They have allowed the direct determination of the broad-line region size, enabled mapping of the gas distribution around the central black hole, and are starting to resolve the continuum source structure. This review describes the recent and successful campaigns of the International AGN Watch consortium, outlines the theoretical background of reverberation mapping and the calculation of transfer functions, and addresses the fundamental difficulties of such experiments. It shows that such large-scale experiments have resulted in a ``new BLR'' which is considerably different from the one we knew just ten years ago. We discuss in some detail the more important new results, including the luminosity-size-mass relationship for AGN, and suggest ways to proceed in the near future.Comment: Review article to appear in Astronomical Time Series, Proceedings of the Wise Observatory 25th Ann. Symposium. 24 pages including 7 figure

Preparation and surface functionalization of MWCNTs: study of the composite materials produced by the interaction with an iron phthalocyanine complex

Carbon nanotubes [CNTs] were synthesized by the catalytic vapor decomposition method. Thereafter, they were functionalized in order to incorporate the oxygen groups (OCNT) and subsequently the amine groups (ACNT). All three CNTs (the as-synthesized and functionalized) underwent reaction with an iron organometallic complex (FePcS), iron(III) phthalocyanine-4,4",4",4""-tetrasulfonic acid, in order to study the nature of the interaction between this complex and the CNTs and the potential formation of nanocomposite materials. Transmission electronic microscopy, N2 adsorption at 77 K, thermogravimetric analysis, temperature-programmed desorption, and X-ray photoelectron spectroscopy were the characterization techniques employed to confirm the successful functionalization of CNTs as well as the type of interaction existing with the FePcS. All results obtained led to the same conclusion: There were no specific chemical interactions between CNTs and the fixed FePcS

Estrogenicity of resin-based composites and sealants used in dentistry.

We tested some resin-based composites used in dentistry for their estrogenic activity. A sealant based on bisphenol-A diglycidylether methacrylate (bis-GMA) increased cell yields, progesterone receptor expression, and pS2 secretion in human estrogen-target, serum-sensitive MCF7 breast cancer cells. Estrogenicity was due to bisphenol-A and bisphenol-A dimethacrylate, monomers found in the base paste of the dental sealant and identified by mass spectrometry. Samples of saliva from 18 subjects treated with 50 mg of a bis-GMA-based sealant applied on their molars were collected 1 hr before and after treatment. Bisphenol-A (range 90-931 micrograms) was identified only in saliva collected during a 1-hr period after treatment. The use of bis-GMA-based resins in dentistry, and particularly the use of sealants in children, appears to contribute to human exposure to xenoestrogens

Attributable mortality to radon exposure in Galicia, Spain. Is it necessary to act in the face of this health problem?

<p>Abstract</p> <p>Background</p> <p>Radon is the second risk factor for lung cancer after tobacco consumption and therefore it is necessary to know the burden of disease due to its exposure. The objective of this study is to estimate radon-attributable lung cancer mortality in Galicia, a high emission area located at the Northwest Spain.</p> <p>Methods</p> <p>A prevalence-based attribution method was applied. Prevalence of tobacco use and radon exposure were obtained from a previously published study of the same area. Attributable mortality was calculated for each of six possible risk categories, based on radon exposure and smoking status. Two scenarios were used, with 37 Bq/m³and 148 Bq/m³as the respective radon exposure thresholds. As the observed mortality we used lung cancer mortality for 2001 from the Galician mortality registry.</p> <p>Results</p> <p>Mortality exclusively attributable to radon exposure ranged from 3% to 5% for both exposure thresholds, respectively. Attributable mortality to combined exposure to radon and smoking stood at around 22% for exposures above 148 Bq/m³. Applying the United States Environmental Protection Agency (EPA) action level, radon has a role in 25% of all lung cancers.</p> <p>Conclusions</p> <p>Although the estimates have been derived from a study with a relatively limited sample size, these results highlight the importance of radon exposure as a cause of lung cancer and its effect in terms of disease burden. Radon mitigation activities in the study area must therefore be enforced.</p

An entropy test for single-locus genetic association analysis

<p>Abstract</p> <p>Background</p> <p>The etiology of complex diseases is due to the combination of genetic and environmental factors, usually many of them, and each with a small effect. The identification of these small-effect contributing factors is still a demanding task. Clearly, there is a need for more powerful tests of genetic association, and especially for the identification of rare effects</p> <p>Results</p> <p>We introduce a new genetic association test based on symbolic dynamics and symbolic entropy. Using a freely available software, we have applied this entropy test, and a conventional test, to simulated and real datasets, to illustrate the method and estimate type I error and power. We have also compared this new entropy test to the Fisher exact test for assessment of association with low-frequency SNPs. The entropy test is generally more powerful than the conventional test, and can be significantly more powerful when the genotypic test is applied to low allele-frequency markers. We have also shown that both the Fisher and Entropy methods are optimal to test for association with low-frequency SNPs (MAF around 1-5%), and both are conservative for very rare SNPs (MAF<1%)</p> <p>Conclusions</p> <p>We have developed a new, simple, consistent and powerful test to detect genetic association of biallelic/SNP markers in case-control data, by using symbolic dynamics and symbolic entropy as a measure of gene dependence. We also provide a standard asymptotic distribution of this test statistic. Given that the test is based on entropy measures, it avoids smoothed nonparametric estimation. The entropy test is generally as good or even more powerful than the conventional and Fisher tests. Furthermore, the entropy test is more computationally efficient than the Fisher's Exact test, especially for large number of markers. Therefore, this entropy-based test has the advantage of being optimal for most SNPs, regardless of their allele frequency (Minor Allele Frequency (MAF) between 1-50%). This property is quite beneficial, since many researchers tend to discard low allele-frequency SNPs from their analysis. Now they can apply the same statistical test of association to all SNPs in a single analysis., which can be especially helpful to detect rare effects.</p

A Linear Algebra Approach for Detecting Binomiality of Steady State Ideals of Reversible Chemical Reaction Networks

Motivated by problems from Chemical Reaction Network Theory, we investigate whether steady state ideals of reversible reaction networks are generated by binomials. We take an algebraic approach considering, besides concentrations of species, also rate constants as indeterminates. This leads us to the concept of unconditional binomiality, meaning binomiality for all values of the rate constants. This concept is different from conditional binomiality that applies when rate constant values or relations among rate constants are given. We start by representing the generators of a steady state ideal as sums of binomials, which yields a corresponding coefficient matrix. On these grounds we propose an efficient algorithm for detecting unconditional binomiality. That algorithm uses exclusively elementary column and row operations on the coefficient matrix. We prove asymptotic worst case upper bounds on the time complexity of our algorithm. Furthermore, we experimentally compare its performance with other existing methods

Stress related epigenetic changes may explain opportunistic success in biological invasions in Antipode mussels

Different environmental factors could induce epigenetic changes, which are likely involved in the biological invasion process. Some of these factors are driven by humans as, for example, the pollution and deliberate or accidental introductions and others are due to natural conditions such as salinity. In this study, we have analysed the relationship between different stress factors: time in the new location, pollution and salinity with the methylation changes that could be involved in the invasive species tolerance to new environments. For this purpose, we have analysed two different mussels’ species, reciprocally introduced in antipode areas: the Mediterranean blue mussel Mytilus galloprovincialis and the New Zealand pygmy mussel Xenostrobus securis, widely recognized invaders outside their native distribution ranges. The demetylathion was higher in more stressed population, supporting the idea of epigenetic is involved in plasticity process. These results can open a new management protocols, using the epigenetic signals as potential pollution monitoring tool. We could use these epigenetic marks to recognise the invasive status in a population and determine potential biopollutants