High-Temperature, Lightweight, Self-Healing Ceramic Composites for Aircraft Engine Applications

The use of reliable, high-temperature, lightweight materials in the manufacture of aircraft engines is expected to result in lower fossil and biofuel consumption, thereby leading to cost savings and lower carbon emissions due to air travel. Although nickel-based superalloy blades and vanes have been successfully used in aircraft engines for several decades, there has been an increased effort to develop high-temperature, lightweight, creep-resistant substitute materials under various NASA programs over the last two decades. As a result, there has been a great deal of interest in developing SiC/SiC ceramic matrix composites (CMCs) due to their higher damage tolerance compared to monolithic ceramics. Current-generation SiC/SiC ceramic matrix composites rely almost entirely on the SiC fibers to carry the load, owing to the premature cracking of the matrix during loading. Thus, the high-temperature usefulness of these CMCs falls well below their theoretical capabilities. The objective of this work is to develop a new class of high-temperature, lightweight, self-healing, SiC fiber-reinforced, engineered matrix ceramic composites

Forensic Identification of Suspected Poached Wild Boar (Sus scrofa affinis)

A case of suspected wild boar death due to dynamite blast by poachers was received by us for confirmation. The skin sample was collected and examined histologically for identification based on hair follicle arrangement in the horizontal section of skin. The horizontal sections of skin from both domestic and wild boar was stained in order to study the distribution of hair follicles. Linear arrangement of hair follicles comprising three primary follicles in a row was observed in both domestic and suspected wild boar. Based on circumstantial evidence it was concluded that it may be belonging to wild boar

Stover Quality Traits for Improvement of Dual-Purpose Sorghum

Twenty four sorghum stovers were investigated with sheep for organic matter digestibility (OMD) and intake (OMI), and for digestible organic matter intake (DOMI) and for relations between laboratory fodder quality traits and these in vivo measurements. Statistically highly significant and nutritionally important differences were found between the stover with OMD differing by 15 percentage units and OMI and DOMI varying 1.6 and 2 times, respectively. For each of the in vivo measurements, chemical (NDF, ADF, ADL) and in vitro (in vitro digestibility, metabolisable energy content) traits were identified which accounted for at least 50% of the variation in the respective traits. Using multiple regression procedures and stringent cross-validation (“blind-predictions”) procedures OMD, OMI and DOMI could be predicted with R2 for comparing observed and predicted values of 0.36, 0.65 and 0.75, respectively. The reported research showed selection for dual purpose sorghum cultivars is promising, and identified and validated simple laboratory traits that can be used for such phenotypin

Rational mutagenesis to support structure-based drug design: MAPKAP kinase 2 as a case study

<p>Abstract</p> <p>Background</p> <p>Structure-based drug design (SBDD) can provide valuable guidance to drug discovery programs. Robust construct design and expression, protein purification and characterization, protein crystallization, and high-resolution diffraction are all needed for rapid, iterative inhibitor design. We describe here robust methods to support SBDD on an oral anti-cytokine drug target, human MAPKAP kinase 2 (MK2). Our goal was to obtain useful diffraction data with a large number of chemically diverse lead compounds. Although MK2 structures and structural methods have been reported previously, reproducibility was low and improved methods were needed.</p> <p>Results</p> <p>Our construct design strategy had four tactics: <it>N</it>- and <it>C</it>-terminal variations; entropy-reducing surface mutations; activation loop deletions; and pseudoactivation mutations. Generic, high-throughput methods for cloning and expression were coupled with automated liquid dispensing for the rapid testing of crystallization conditions with minimal sample requirements. Initial results led to development of a novel, customized robotic crystallization screen that yielded MK2/inhibitor complex crystals under many conditions in seven crystal forms. In all, 44 MK2 constructs were generated, ~500 crystals were tested for diffraction, and ~30 structures were determined, delivering high-impact structural data to support our MK2 drug design effort.</p> <p>Conclusion</p> <p>Key lessons included setting reasonable criteria for construct performance and prioritization, a willingness to design and use customized crystallization screens, and, crucially, initiation of high-throughput construct exploration very early in the drug discovery process.</p

Bistability versus Bimodal Distributions in Gene Regulatory Processes from Population Balance

In recent times, stochastic treatments of gene regulatory processes have appeared in the literature in which a cell exposed to a signaling molecule in its environment triggers the synthesis of a specific protein through a network of intracellular reactions. The stochastic nature of this process leads to a distribution of protein levels in a population of cells as determined by a Fokker-Planck equation. Often instability occurs as a consequence of two (stable) steady state protein levels, one at the low end representing the “off” state, and the other at the high end representing the “on” state for a given concentration of the signaling molecule within a suitable range. A consequence of such bistability has been the appearance of bimodal distributions indicating two different populations, one in the “off” state and the other in the “on” state. The bimodal distribution can come about from stochastic analysis of a single cell. However, the concerted action of the population altering the extracellular concentration in the environment of individual cells and hence their behavior can only be accomplished by an appropriate population balance model which accounts for the reciprocal effects of interaction between the population and its environment. In this study, we show how to formulate a population balance model in which stochastic gene expression in individual cells is incorporated. Interestingly, the simulation of the model shows that bistability is neither sufficient nor necessary for bimodal distributions in a population. The original notion of linking bistability with bimodal distribution from single cell stochastic model is therefore only a special consequence of a population balance model

Quality control and beam test of GEM detectors for future upgrades of the CMS muon high rate region at the LHC

Gas Electron Multipliers (GEM) are a proven position sensitive gas detector technology which nowadays is becoming more widely used in High Energy Physics. GEMs offer an excellent spatial resolution and a high particle rate capability, with a close to 100% detection efficiency. In view of the high luminosity phase of the CERN Large Hadron Collider, these aforementioned features make GEMs suitable candidates for the future upgrades of the Compact Muon Solenoid (CMS) detector. In particular, the CMS GEM Collaboration proposes to cover the high-eta region of the muon system with large-area triple-GEM detectors, which have the ability to provide robust and redundant tracking and triggering functions. In this contribution, after a general introduction and overview of the project, the construction of full-size trapezoidal triple-GEM prototypes will be described in more detail. The procedures for the quality control of the GEM foils, including gain uniformity measurements with an x-ray source will be presented. In the past few years, several CMS triple-GEM prototype detectors were operated with test beams at the CERN SPS. The results of these test beam campaigns will be summarised

MultiMiTar: A Novel Multi Objective Optimization based miRNA-Target Prediction Method

BACKGROUND: Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. METHODOLOGY/PRINCIPAL FINDING: In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. CONCLUSIONS/SIGNIFICANCE: MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm

Performance of a Large-Area GEM Detector Prototype for the Upgrade of the CMS Muon Endcap System

Gas Electron Multiplier (GEM) technology is being considered for the forward muon upgrade of the CMS experiment in Phase 2 of the CERN LHC. Its first implementation is planned for the GE1/1 system in the $1.5 < \mid\eta\mid < 2.2$ region of the muon endcap mainly to control muon level-1 trigger rates after the second long LHC shutdown. A GE1/1 triple-GEM detector is read out by 3,072 radial strips with 455 $\mu$rad pitch arranged in eight $\eta$-sectors. We assembled a full-size GE1/1 prototype of 1m length at Florida Tech and tested it in 20-120 GeV hadron beams at Fermilab using Ar/CO$_{2}$ 70:30 and the RD51 scalable readout system. Four small GEM detectors with 2-D readout and an average measured azimuthal resolution of 36 $\mu$rad provided precise reference tracks. Construction of this largest GEM detector built to-date is described. Strip cluster parameters, detection efficiency, and spatial resolution are studied with position and high voltage scans. The plateau detection efficiency is [97.1 $\pm$ 0.2 (stat)]\%. The azimuthal resolution is found to be [123.5 $\pm$ 1.6 (stat)] $\mu$rad when operating in the center of the efficiency plateau and using full pulse height information. The resolution can be slightly improved by $\sim$ 10 $\mu$rad when correcting for the bias due to discrete readout strips. The CMS upgrade design calls for readout electronics with binary hit output. When strip clusters are formed correspondingly without charge-weighting and with fixed hit thresholds, a position resolution of [136.8 $\pm$ 2.5 stat] $\mu$rad is measured, consistent with the expected resolution of strip-pitch/$\sqrt{12}$ = 131.3 $\mu$rad. Other $\eta$-sectors of the detector show similar response and performance.Comment: 8 pages, 32 figures, submitted to Proc. 2014 IEEE Nucl. Sci. Symposium, Seattle, WA, reference adde