Comparative statistical aging studies on an oil-pressboard insulation model

Accelerated aging experiments have been conducted on a representative oil-pressboard insulation model to investigate the effect of constant and sequential stresses on the PD behavior using a built-in phase resolved partial discharge analyzer. A cycle of the applied voltage starting from the zero of the positive half cycle was divided into 16 equal phase windows (Φ1 to Φ16) and partial discharge (PD) magnitude distribution in each phase was determined. Based on the experimental results, three stages of aging mechanism were identified. Gumbel's extreme value distribution of the largest element was used to model the first stage of aging process. Second and subsequent stages were modeled using two-parameter Weibull distribution. Spearman's non-parametric rank correlation test statistic and Kolmogrov-Smirnov two sample test were used to relate the aging process of each phase with the corresponding process of the full cycle. To bring out clearly the effect of stress level, its duration and test procedure on the distribution parameters and hence of the aging process, non-parametric ANOVA techniques like Kruskal-Wallis and Fisher's LSD multiple comparison tests were used. Results of the analysis show that two phases (Φ13 and Φ14) near the vicinity of the negative voltage peak were found to contribute significantly to the aging process and their aging mechanism also correlated well with that of the corresponding full cycle mechanism. Attempts have been made to relate these results with the published work of other workers

Withania somnifera reverses Alzheimer's disease pathology by enhancing low-density lipoprotein receptor-related protein in liver

A 30-d course of oral administration of a semipurified extract of the root of Withania somnifera consisting predominantly of withanolides and withanosides reversed behavioral deficits, plaque pathology, accumulation of beta-amyloid peptides (A beta) and oligomers in the brains of middle-aged and old APP/PS1 Alzheimer's disease transgenic mice. It was similarly effective in reversing behavioral deficits and plaque load in APPSwInd mice (line J20). The temporal sequence involved an increase in plasma A beta and a decrease in brain A beta monomer after 7 d, indicating increased transport of A beta from the brain to the periphery. Enhanced expression of low-density lipoprotein receptor-related protein (LRP) in brain microvessels and the A beta-degrading protease neprilysin (NEP) occurred 14-21 d after a substantial decrease in brain A beta levels. However, significant increase in liver LRP and NEP occurred much earlier, at 7 d, and were accompanied by a rise in plasma sLRP, a peripheral sink for brain A beta. In WT mice, the extract induced liver, but not brain, LRP and NEP and decreased plasma and brain A beta, indicating that increase in liver LRP and sLRP occurring independent of A beta concentration could result in clearance of A beta. Selective down-regulation of liver LRP, but not NEP, abrogated the therapeutic effects of the extract. The remarkable therapeutic effect of W. somnifera mediated through up-regulation of liver LRP indicates that targeting the periphery offers a unique mechanism for A beta clearance and reverses the behavioral deficits and pathology seen in Alzheimer's disease models.

Root cause diagnostics using temporal data mining

A method, system, and computer program product for fault data correlation in a diagnostic system are provided. The method includes receiving the fault data including a plurality of faults collected over a period of time, and identifying a plurality of episodes within the fault data, where each episode includes a sequence of the faults. The method further includes calculating a frequency of the episodes within the fault data, calculating a correlation confidence of the faults relative to the episodes as a function of the frequency of the episodes, and outputting a report of the faults with the correlation confidence.

Efficient sequential assignments in proteins with reduced dimensionality 3D HN(CA)NH

We present reduced dimensionality (RD) 3D HN(CA)NH for efficient sequential assignment in proteins. The experiment correlates the N-15 and H-1 chemical shift of a residue ('i') with those of its immediate N-terminal (i - 1) and C-terminal (i + 1) neighbors and provides four-dimensional chemical shift correlations rapidly with high resolution. An assignment strategy is presented which combines the correlations observed in this experiment with amino acid type information obtained from 3D CBCA(CO)NH. By classifying the 20 amino acid types into seven distinct categories based on C-13(beta) chemical shifts, it is observed that a stretch of five sequentially connected residues is sufficient to map uniquely on to the polypeptide for sequence specific resonance assignments. This method is exemplified by application to three different systems: maltose binding protein (42 kDa), intrinsically disordered domain of insulin-like growth factor binding protein-2 and Ubiquitin. Fast data acquisition is demonstrated using longitudinal H-1 relaxation optimization. Overall, 3D HN(CA)NH is a powerful tool for high throughput resonance assignment, in particular for unfolded or intrinsically disordered polypeptides.

Helix and hairpin nucleation in short peptides using centrally positioned conformationally constrained dipeptide segments

The effect of incorporation of a centrally positioned Ac(6)c-Xxx segment where Xxx = (L)Val/(D)Val into a host oligopeptide composed of L-amino acid residues has been investigated. Studies of four designed octapeptides Boc-Leu-Phe-Val-Ac(6)c-Xxx-Leu-Phe-Val-OMe (Xxx = (D)Val 1, (L)Val 2) Boc-Leu-Val-Val-Ac(6)c-Xxx-Leu-Val-Val-OMe (Xxx = (D)Val 3, (L)Val 4) are reported. Diagnostic nuclear Overhouse effects characteristic of hairpin conformations are observed for Xxx = (D)Val peptides (1 and 3) while continuous helical conformation characterized by sequential NiH <-> Ni+1H NOEs are favored for Xxx = (L)Val peptides (2 and 4) in methanol solutions. Temperature co-efficient of NH chemical shifts are in agreement with distinctly different conformational preferences upon changing the configuration of the residue at position 5. Crystal structures of peptides 2 and 4 (Xxx = (L)Val) establish helical conformations in the solid state, in agreement with the structures deduced from NMR data. The results support the design principle that centrally positioned type I beta-turns may be used to nucleate helices in short peptides, while type I' beta-turns can facilitate folding into beta-hairpins.

H-1, C-13, N-15 assignment and secondary structure determination of glutamine amido transferase subunit of gaunosine monophosphate synthetase from Methanocaldococcus jannaschii

Sequence specific resonance assignments have been obtained for H-1, C-13 and N-15 nuclei of the 21 kDa (188 residues long) glutamine amido transferase subunit of guanosine monophosphate synthetase from Methanocaldococcus jannaschii. From an analysis of H-1 and C-13(alpha), C-13(beta) secondary chemical shifts, (3) JH(N)H(alpha) scalar coupling constants and sequential, short and medium range H-1-H-1 NOEs, it was deduced that the glutamine amido transferase subunit has eleven strands and five helices as the major secondary structural elements in its tertiary structure.

A new method for fracture toughness determination of graded (Pt,Ni)Al bond coats by microbeam bend tests

A novel method is proposed for fracture toughness determination of graded microstructurally complex (Pt,Ni)Al bond coats using edge-notched doubly clamped beams subjected to bending. Micron-scale beams are machined using the focused ion beam and loaded in bending under a nanoindenter. Failure loads gathered from the pop-ins in the load-displacement curves combined with XFEM analysis are used to calculate K-c at individual zones, free from substrate effects. The testing technique and sources of errors in measurement are described and possible micromechanisms of fracture in such heterogeneous coatings discussed.

Consistency tests of Ampcalculator and chiral amplitudes in SU(3) Chiral Perturbation Theory: A tutorial-based approach

Ampcalculator (AMPC) is a Mathematica (c) based program that was made publicly available some time ago by Unterdorfer and Ecker. It enables the user to compute several processes at one loop (upto O(p(4))) in SU(3) chiral perturbation theory. They include computing matrix elements and form factors for strong and non-leptonic weak processes with at most six external states. It was used to compute some novel processes and was tested against well-known results by the original authors. Here we present the results of several thorough checks of the package. Exhaustive checks performed by the original authors are not publicly available, and hence the present effort. Some new results are obtained from the software especially in the kaon odd-intrinsic parity non-leptonic decay sector involving the coupling G(27). Another illustrative set of amplitudes at tree level we provide is in the context of tau-decays with several mesons including quark mass effects, of use to the BELLE experiment. All eight meson-meson scattering amplitudes have been checked. The Kaon-Compton amplitude has been checked and a minor error in the published results has been pointed out. This exercise is a tutorial-based one, wherein several input and output notebooks are also being made available as ancillary files on the arXiv. Some of the additional notebooks we provide contain explicit expressions that we have used for comparison with established results. The purpose is to encourage users to apply the software to suit their specific needs. An automatic amplitude generator of this type can provide error-free outputs that could be used as inputs for further simplification, and in varied scenarios such as applications of chiral perturbation theory at finite temperature, density and volume. This can also be used by students as a learning aid in low-energy hadron dynamics.

Active Sequential Hypothesis Testing with Application to a Visual Search Problem

We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

The Coil-to-Helix Transition in IlvN Regulates the Allosteric Control of Escherichia coli Acetohydroxyacid Synthase I

The solution structure of IlvN, the regulatory subunit of Escherichia coil acetohydroxyacid synthase I, in the valine-bound form has been determined using high-resolution multidimensional, multinuclear nuclear magnetic resonance (NMR) methods. IlvN in the presence or absence of the effector molecule is present as a 22.5 kDa dimeric molecule. The ensemble of 20 low-energy structures shows a backbone root-mean-square deviation of 0.73 +/- 0.13 angstrom and a root-mean-square deviation of 1.16 +/- 0.13 angstrom for all heavy atoms. Furthermore, more than 98% of the backbone phi and psi dihedral angles occupy the allowed and additionally allowed regions of the Ramachandran map, which is indicative of the fact that the structures are of high stereochemical quality. Each protomer exhibits a beta alpha beta beta alpha beta alpha topology that is a characteristic feature of the ACT domain seen in metabolic enzymes. In the valine-bound form, IlvN exists apparently as a single conformer. In the free form, IlvN exists as a mixture of conformational states that are in intermediate exchange on the NMR time scale. Thus, a large shift in the conformational equilibrium is observed upon going from the free form to the bound form. The structure of the valine-bound form of IlvN was found to be similar to that of the ACT domain of the unliganded form of IlvH. Comparisons of the structures of the unliganded forms of these proteins suggest significant differences. The structural and conformational properties of IlvN determined here have allowed a better understanding of the mechanism of regulation of branched chain amino acid biosynthesis.

A sequential dual method for structural SVMs

In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to compu- tational biology or computer vision and have been tackled using algorithms, referred to as structured output learning algorithms. We consider the problem of structured classifi- cation. In the last few years, large margin classifiers like sup-port vector machines (SVMs) have shown much promise for structured output learning. The related optimization prob -lem is a convex quadratic program (QP) with a large num-ber of constraints, which makes the problem intractable for large data sets. This paper proposes a fast sequential dual method (SDM) for structural SVMs. The method makes re-peated passes over the training set and optimizes the dual variables associated with one example at a time. The use of additional heuristics makes the proposed method more efficient. We present an extensive empirical evaluation of the proposed method on several sequence learning problems.Our experiments on large data sets demonstrate that the proposed method is an order of magnitude faster than state of the art methods like cutting-plane method and stochastic gradient descent method (SGD). Further, SDM reaches steady state generalization performance faster than the SGD method. The proposed SDM is thus a useful alternative for large scale structured output learning.