Use of Electron Backscatter Diffraction in Understanding Texture and the Mechanisms of Backscattered Noise Generation in Titanium Alloys

Developing a quantitative understanding of ultrasonic beam propagation in engineering materials such as Ti-6A1-4V is important because flaw signals can be altered greatly by the macrostructure that the ultrasonic beam propagates through between the transducer and the flaw. Two consequences of the macrostructure are particularly important: 1) back scattered noise which competes with flaw signals and 2) forward scattered signals and the associated beam profile fluctuations which can modulate the strength of flaw signals [1,2,3], These effects are particularly important when ultrasonic beams are used to detect subtle defects such as unvoided, uncracked hard-alpha inclusions (regions with a high content of interstitial nitrogen or oxygen), because the flaw signal is inherently weak due to a small mismatch of acoustic impedance. Each of these effects is controlled by the inherently complex macrostructure which develops during routine processing. Current theories suggest that the most important physical feature which controls noise is the two-point correlation of elastic constants, which is in turn controlled by local variations in crystallographic orientation [4]. Therefore, in order to quantify the effects of the macrostructure on ultrasonic beam propagation, one must determine the elastic constants on a microscopic level with length scales less than the ultrasonic wavelength, approximately 600 μm at 10 MHz.</p

Rapid induction of autoantibodies during ARDS and septic shock

<p>Abstract</p> <p>Background</p> <p>Little is known about the induction of humoral responses directed against human autoantigens during acute inflammation. We utilized a highly sensitive antibody profiling technology to study autoantibodies in patients with acute respiratory distress syndrome (ARDS) and severe sepsis, conditions characterized by intensive immune activation leading to multiple organ dysfunction.</p> <p>Methods</p> <p>Using Luciferase Immunoprecipitation Systems (LIPS), a cohort of control, ARDS and sepsis patients were tested for antibodies to a panel of autoantigens. Autoantibody titers greater than the mean plus 3 SD of the 24 control samples were used to identify seropositive samples. Available longitudinal samples from different seropositive ARDS and sepsis patient samples, starting from within the first two days after admission to the intensive care, were then analyzed for changes in autoantibody over time.</p> <p>Results</p> <p>From screening patient plasma, 57% of ARDS and 46% of septic patients without ARDS demonstrated at least one statistically significant elevated autoantibody compared to the controls. Frequent high titer antibodies were detected against a spectrum of autoantigens including potassium channel regulator, gastric ATPase, glutamic decarboxylase-65 and several cytokines. Analysis of serial samples revealed that several seropositive patients had low autoantibodies at early time points that often rose precipitously and peaked between days 7-14. Further, the use of therapeutic doses of corticosteroids did not diminish the rise in autoantibody titers. In some cases, the patient autoantibody titers remained elevated through the last serum sample collected.</p> <p>Conclusion</p> <p>The rapid induction of autoantibodies in ARDS and severe sepsis suggests that ongoing systemic inflammation and associated tissue destruction mediate the break in tolerance against these self proteins.</p

On Coupling FCA and MDL in Pattern Mining

International audiencePattern Mining is a well-studied field in Data Mining and Machine Learning. The modern methods are based on dynamically updating models, among which MDL-based ones ensure high-quality pattern sets. Formal concepts also characterize patterns in a condensed form. In this paper we study MDL-based algorithm called Krimp in FCA settings and propose a modified version that benefits from FCA and relies on probabilistic assumptions that underlie MDL. We provide an experimental proof that the proposed approach improves quality of pattern sets generated by Krimp

The Effect of Transposable Element Insertions on Gene Expression Evolution in Rodents

Background:Many genomes contain a substantial number of transposable elements (TEs), a few of which are known to be involved in regulating gene expression. However, recent observations suggest that TEs may have played a very important role in the evolution of gene expression because many conserved non-genic sequences, some of which are know to be involved in gene regulation, resemble TEs. Results:Here we investigate whether new TE insertions affect gene expression profiles by testing whether gene expression divergence between mouse and rat is correlated to the numbers of new transposable elements inserted near genes. We show that expression divergence is significantly correlated to the number of new LTR and SINE elements, but not to the numbers of LINEs. We also show that expression divergence is not significantly correlated to the numbers of ancestral TEs in most cases, which suggests that the correlations between expression divergence and the numbers of new TEs are causal in nature. We quantify the effect and estimate that TE insertion has accounted for ~20% (95% confidence interval: 12% to 26%) of all expression profile divergence in rodents. Conclusions:We conclude that TE insertions may have had a major impact on the evolution of gene expression levels in rodents

How the other half lives: CRISPR-Cas's influence on bacteriophages

CRISPR-Cas is a genetic adaptive immune system unique to prokaryotic cells used to combat phage and plasmid threats. The host cell adapts by incorporating DNA sequences from invading phages or plasmids into its CRISPR locus as spacers. These spacers are expressed as mobile surveillance RNAs that direct CRISPR-associated (Cas) proteins to protect against subsequent attack by the same phages or plasmids. The threat from mobile genetic elements inevitably shapes the CRISPR loci of archaea and bacteria, and simultaneously the CRISPR-Cas immune system drives evolution of these invaders. Here we highlight our recent work, as well as that of others, that seeks to understand phage mechanisms of CRISPR-Cas evasion and conditions for population coexistence of phages with CRISPR-protected prokaryotes.Comment: 24 pages, 8 figure

Dietary Pattern Trajectories from 6 to 12 Months of Age in a Multi-Ethnic Asian Cohort

10.3390/nu8060365Nutrients86365GUSTO (Growing up towards Healthy Outcomes

Gas-cushioned droplet impacts with a thin layer of porous media

The authors are grateful to Dr. Manish Tiwari for introducing them to experiments involving droplet impacts with textured substrates. PDH is grateful for the use of the Maxwell High-Performance Computing Cluster of the University of Aberdeen IT Service. RP is grateful for the use of the High-Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia.Peer reviewedPostprin

Stress effects on stability and diffusion behavior of sulfur impurity in nickel: A first-principles study

A systematic investigation regarding the effect of stress on the stability and diffusion behavior of S impurity in Ni was carried out via first-principles methods. A comparison of the formation energy of S in Ni indicated that S more easily forms as a solution atom with increasing S concentration in Ni supercells, but the binding energy showed that as the concentration of S that dissolved into Ni increased, the structure became less stable. The diffusion barrier via the octahedral-tetrahedral-octahedral site path was always lower than that via the octahedral-octahedral site path. The diffusion barrier of single S decreased with increase in tensile stress. S diffusion accelerated under applied tensile stress, which was disadvantageous in suppressing S retention in Ni. These results implied that even at a low concentration, dissolved S still had a tendency of precipitating from the Ni matrix, to further increase the stability of the system. (C) 2014 Elsevier B. V. All rights reserved

Entity linking of tweets based on dominant entity candidates

© 2018, Springer-Verlag GmbH Austria, part of Springer Nature. Entity linking, also known as semantic annotation, of textual content has received increasing attention. Recent works in this area have focused on entity linking on text with special characteristics such as search queries and tweets. The semantic annotation of tweets is specially proven to be challenging given the informal nature of the writing and the short length of the text. In this paper, we propose a method to perform entity linking on tweets built based on one primary hypothesis. We hypothesize that while there are formally many possible entity candidates for an ambiguous mention in a tweet, as listed on the disambiguation page of the corresponding entity on Wikipedia, there are only few entity candidates that are likely to be employed in the context of Twitter. Based on this hypothesis, we propose a method to identify such dominant entity candidates for each ambiguous mention and use them in the annotation process. Particularly, our proposed work integrates two phases (i) dominant entity candidate detection, which applies community detection methods for finding the dominant candidates of ambiguous mentions; and (ii) named entity disambiguation that links a tweet to entities in Wikipedia by only considering the identified dominant entity candidates. Our investigations show that: (1) there are only very few entity candidates for each ambiguous mention in a tweet that need to be considered when performing disambiguation. This helps us limit the candidate search space and hence noticeably reduce the entity linking time; (2) limiting the search space to only a subset of disambiguation options will not only improve entity linking execution time but will also lead to improved accuracy of the entity linking process when the main entity candidates of each mention are mined from a temporally aligned corpus. We show that our proposed method offers competitive results with the state-of-the-art methods in terms of precision and recall on widely used gold standard datasets while significantly reducing the time for processing each tweet

Cross section balance in the 14N + 159Tb reaction and the origin of fast alpha particles

Exclusive cross sections have been obtained from particle-K X-ray coincidence data measured at 236 MeV for ejectiles ranging from 4 He to 15 N. Production cross sections for primary fragments and alpha particle multiplicities associated with different channels have been deduced. The major fraction of the alpha particles appears to originate from inelastic (damped) processes in which only light particles with Z < 2 are emitted