Decomposing elements of a right self-injective ring

It was proved independently by both Wolfson [An ideal theoretic characterization of the ring of all linear transformations, Amer. J. Math. 75 (1953), 358-386] and Zelinsky [Every Linear Transformation is Sum of Nonsingular Ones, Proc. Amer. Math. Soc. 5 (1954), 627-630] that every linear transformation of a vector space $V$ over a division ring $D$ is the sum of two invertible linear transformations except when $V$ is one-dimensional over $\mathbb Z_2$. This was extended by Khurana and Srivastava [Right self-injective rings in which each element is sum of two units, J. Algebra and its Appl., Vol. 6, No. 2 (2007), 281-286] who proved that every element of a right self-injective ring $R$ is the sum of two units if and only if $R$ has no factor ring isomorphic to $\mathbb Z_2$. In this paper we prove that if $R$ is a right self-injective ring, then for each element $a\in R$ there exists a unit $u\in R$ such that both $a+u$ and $a-u$ are units if and only if $R$ has no factor ring isomorphic to $\mathbb Z_2$ or $\mathbb Z_3$.Comment: To appear in J. Algebra and App

Docking and QSAR Studies of Camptothecin Derivatives as Inhibitor of DNA Topoisomerase-I

Camptothecin (CPT) is a cytotoxic quinoline alkaloid which inhibits the DNA enzyme Topoisomerase-I (Topo-I) and has shown remarkable anticancer activity in preliminary clinical trials. The major limitation is its low solubility and high adverse reaction. In the studied work, we performed molecular docking of CPT derivatives against Topo-I and developed the quantitative structure activity relationship (QSAR) model for anticancer activity screening. For QSAR, we used CPT and other anticancer drugs with its IC50 values. We used a total of forty seven anticancer drugs as training set and eight compounds as test set and thirty derivatives of CPT as query set. Total of fifty two chemical descriptors were used for the quantitative data calculation. Only four showed good correlation with the experimental activity. Forward feed regression method was used for development of multiple linear regression (MLR) QSAR model. Model showed acceptable regression coefficient (r2) 0.89 (i.e., 89% of correlation) and cross validation coefficient (rCV2) 0.86 (i.e., 86 % of prediction accuracy). After drug likeness test, ten compounds namely, MSB3a, MSB3b, MSB19, MSB22L, MSB22M, MSB22O, MSB22R, MSB25D, MSB37G and MSB39D, showed promising predicted anticancer activity and drug likeness properties. Out of ten, only six compounds namely, MSB19, MSB22L, MSBM, MSB22O, MSB22R and MSB37D indicate two times more activity than the parent CPT compound. In molecular docking studies, all the identified active CPT derivatives showed high binding affinity with Topo-I. QSAR study indicates that connectivity index, electron affinity, mol.wt. & ether group count highly contribute to inhibitory activity of CPT derivatives. These results can offer useful references for directing the molecular design of Topo-I inhibitor with improved anticancer activity.
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Floating Offshore Wind Turbines Oscillations Damping.

This article deals with the modelling and control of oscillations that appear on floating offshore wind turbines (FOWT). First, these offshore wind energy systems, located in deep waters, are described and the modeling approach is presented. Secondly, the traditional structural control strategies based on tuned mass-damper (TMD) systems for oscillations reduction are complemented with a passive mechanism called inerter in order to improve the performance of the structural controller. This work is based on a previous work by the authors in which the inerter was located in parallel to an existing TMD in the nacelle of the FOWT. In this work, the inerter is located between the tower and the barge and results are compared to those obtained previously showing better performance. The results here presented are promising in terms of oscillations damping, both in amplitude and frequency, and constitute preliminary results of the ongoing current research of the authors

Use of the MultiNest algorithm for gravitational wave data analysis

We describe an application of the MultiNest algorithm to gravitational wave data analysis. MultiNest is a multimodal nested sampling algorithm designed to efficiently evaluate the Bayesian evidence and return posterior probability densities for likelihood surfaces containing multiple secondary modes. The algorithm employs a set of live points which are updated by partitioning the set into multiple overlapping ellipsoids and sampling uniformly from within them. This set of live points climbs up the likelihood surface through nested iso-likelihood contours and the evidence and posterior distributions can be recovered from the point set evolution. The algorithm is model-independent in the sense that the specific problem being tackled enters only through the likelihood computation, and does not change how the live point set is updated. In this paper, we consider the use of the algorithm for gravitational wave data analysis by searching a simulated LISA data set containing two non-spinning supermassive black hole binary signals. The algorithm is able to rapidly identify all the modes of the solution and recover the true parameters of the sources to high precision.Comment: 18 pages, 4 figures, submitted to Class. Quantum Grav; v2 includes various changes in light of referee's comment

A Coverage Study of the CMSSM Based on ATLAS Sensitivity Using Fast Neural Networks Techniques

We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of ~ 10^4 with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.Comment: Further checks about accuracy of neural network approximation, fixed typos, added refs. Main results unchanged. Matches version accepted by JHE

Detection of substrate binding motifs for morphine biosynthetic pathway intermediates in novel wound inducible (R,S)-reticuline 7-O-methyltransferase of Papaver somniferum

The benzylisoquinoline alkaloids (BIA) comprise a large and diverse group of nitrogen-containing secondary metabolites with about 2500 compounds identified in plants. BIA biosynthesis begins with the condensation of the tyrosine derived precursors dopamine and p-hydroxyphenylacetaldehyde to (S)-norcoclaurine. Subsequent regiospecific O- and N-methylations and aromatic ring hydroxylation lead to (S)-reticuline, which is the central intermediate for almost all BIAs. For morphinan alkaloid biosynthesis, (S)-reticuline undergoes an inversion of stereochemistry to (R)-reticuline, followed by C-C phenol coupling catalyzed by a unique cytochrome P450-dependent monooxygenase to yield salutaridine. The cDNA sequence of enzymes leading to (S)-reticuline, as well as those involved in the conversion of (R)-reticuline to salutaridine-7-O-acetate are already characterized. The inversion of (S)-reticuline to (R)-reticuline represent the important steps in morphine biosynthesis. Wound induced transcript accumulation in Papaver reveals a novel wound inducible EST (NCBI DbEST: GO238757) showing homology with (R,S)-reticuline 7-O-methyltransferase (ID: Q6WUC2) isolated from Papaver somniferum. We compare the substrate binding homology of this novel wound inducible (R,S)-reticuline 7-O-methyltransferase (7-OMT) using template of P. somniferum (Q6WUC2; gb|AAQ01668) as experimental control. Homology modeling with 70% identity & 85% similarity with catalytic site of template protein i.e., (Q6WUC2) short chain dehydrogenase/reductase (SDR), showed docking energy -69.9 and -75.8 kcal/mol with (S)-Reticuline (CID:439653) and (R)-Reticuline (CID:440586) respectively, which are comparable with experimental control binding site interaction energies. Docking of S- & R-reticuline into the active site revealed eight (F(5), E(18), W(24), C(47), F(44), P(45), C(46) and I(47) amino acids presumably responsible for the high substrate specificity of (R,S)-reticuline 7-O-methyltransferase

Classifying LISA gravitational wave burst signals using Bayesian evidence

We consider the problem of characterisation of burst sources detected with the Laser Interferometer Space Antenna (LISA) using the multi-modal nested sampling algorithm, MultiNest. We use MultiNest as a tool to search for modelled bursts from cosmic string cusps, and compute the Bayesian evidence associated with the cosmic string model. As an alternative burst model, we consider sine-Gaussian burst signals, and show how the evidence ratio can be used to choose between these two alternatives. We present results from an application of MultiNest to the last round of the Mock LISA Data Challenge, in which we were able to successfully detect and characterise all three of the cosmic string burst sources present in the release data set. We also present results of independent trials and show that MultiNest can detect cosmic string signals with signal-to-noise ratio (SNR) as low as ~7 and sine-Gaussian signals with SNR as low as ~8. In both cases, we show that the threshold at which the sources become detectable coincides with the SNR at which the evidence ratio begins to favour the correct model over the alternative.Comment: 21 pages, 11 figures, accepted by CQG; v2 has minor changes for consistency with accepted versio

Kinetic Model of CCA Fixation on Wood. Part I. The Initial Reaction Zone

The fixation process for chromated copper arsenate (CCA-C) preservative treated wood has at least two distinctly different zones. One of these is a fast "Initial Reaction," characterized by a rapid increase in pH and a decrease in available hexavalent chromium (Crvi). In the present study we develop a mathematical model that describes the initial reaction kinetics for red pine (Pinus resinosa Ait.) treated with 1% CCA-C. The results show that the initial fixation reactions follow pseudo 10th order kinetics. The activation energy and pre-exponential factors were found to be 37.8 kj.mol-1 and 8.7 X 10-19 h-1 mol-9 I9, respectively. At all treatment temperatures tested, the initial reaction resulted in approximately 47% chromium reduction. At 4° the time required to complete the initial reaction is approximately 4.5 h; at room temperature the initial reaction is complete in about 1.7 h. At 50° the initial reaction is complete in about 25 min. The complete model incorporates the rate equation, Arrhenius temperature dependence, and the fixation definition into a single equation that expresses % chromium fixation as a function of initial chromium concentration in the treating solution and time and temperature history of the wood following treatment.This model can also be used as an integral part of an overall fixation model that can be used to predict the percent fixation at a given treatment condition based on knowledge of the temperature history of the wood during fixation

Bayes-X: a Bayesian inference tool for the analysis of X-ray observations of galaxy clusters

We present the first public release of our Bayesian inference tool, Bayes-X, for the analysis of X-ray observations of galaxy clusters. We illustrate the use of Bayes-X by analysing a set of four simulated clusters at z=0.2-0.9 as they would be observed by a Chandra-like X-ray observatory. In both the simulations and the analysis pipeline we assume that the dark matter density follows a spherically-symmetric Navarro, Frenk and White (NFW) profile and that the gas pressure is described by a generalised NFW (GNFW) profile. We then perform four sets of analyses. By numerically exploring the joint probability distribution of the cluster parameters given simulated Chandra-like data, we show that the model and analysis technique can robustly return the simulated cluster input quantities, constrain the cluster physical parameters and reveal the degeneracies among the model parameters and cluster physical parameters. We then analyse Chandra data on the nearby cluster, A262, and derive the cluster physical profiles. To illustrate the performance of the Bayesian model selection, we also carried out analyses assuming an Einasto profile for the matter density and calculated the Bayes factor. The results of the model selection analyses for the simulated data favour the NFW model as expected. However, we find that the Einasto profile is preferred in the analysis of A262. The Bayes-X software, which is implemented in Fortran 90, is available at http://www.mrao.cam.ac.uk/facilities/software/bayesx/.Comment: 22 pages, 11 figure

A CROSS-SECTIONAL INVESTIGATION OF SLEEP HABITS AND SELECTED BODY COMPOSITION PARAMETERS AMONG UNIVERSITY STUDENTS

The study's objective was to compare sleep quality and body composition between male and female participants. A cross-sectional study was conducted with five hundred participants (male and female) from different community places. Body composition was measured with the help of a bioelectric impedance device. The sleep habits were determined with the Pittsburgh Sleeps Quality Index that used to evaluate sleep quality during the past seven days, and the Epworth Sleepiness Scale (Johns, 1991) was used to measure the level of the daytime sleepiness. The identified variables were statistically analyzed with an independent t-test, and Eta Squared was applied to find effect size. From the whole study population, only 12.2 % of participants are underweight, 51.4 % are healthy, 16.6 % are overweight, and 19.8 % are obese. Pittsburgh Sleep Quality Index is the lowest (7.90 ± 2.18) into the normal, whereas the highest (8.38 ± 2.93) into the underweight participants. Daytime sleepiness is lowest (10.23 ± 4.18) in underweight, whereas the highest (11.28 ± 3.28) in obese participants. This study demonstrates females had a higher percentage of body fat than males throughout all categories that leads them towards poor sleep habits, which are mediating factors for good health and quality of life.  Article visualizations