Arc termination cracks in Inconel 718 and Incoloy 903

The welding of the nickel base, heat resistant alloys that are used extensively for welded Shuttle engine components revealed solidification cracking characteristics at weld termination points. If not detected and removed, these crater cracks may cause costly component failure. To better understand this characteristic, welding termination techniques were studied and methods developed to eliminate crater cracks. It was determined that weld termination solidification cracking can be eliminated by controlled decrease of welding current, welding voltage, wire feed, and travel speed

Weld peaking on heavy aluminum structures

Weld peaking is usually undesirable in any welded structure. In heavy structures, the forces involved in the welding process become very large and difficult to handle. With the shuttle's solid rocket booster, the weld peaking resulted in two major problems: (1) reduced mechanical properties across the weld joint, and (2) fit-up difficulties in subsequent assembly operation. Peaking from the weld shrinkage forces can be fairly well predicted in simple structures; however, in welding complicated assemblies, the amount of peaking is unpredictable because of unknown stresses from machining and forming, stresses induced by the fixturing, and stresses from welds in other parts of the assembly. When excessive peaking is encountered, it can be corrected using the shrinkage forces resulting from the welding process. Application of these forces is discussed in this report

The Ursinus Weekly, April 3, 1903

Like the ripples • Home rule for cities • Alumni notes • Among the colleges • Philadelphia letter • Racquet lovers meet • Locals • Zwinglian anniversary • Audubon science program • Athleticshttps://digitalcommons.ursinus.edu/weekly/3081/thumbnail.jp

On the complete testing of simple safety-related software

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1994.Includes bibliographical references (leaves 106-109).by Kenneth E. Poorman.M.S

Magnetic resonance fingerprinting review part 2: Technique and directions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154317/1/jmri26877.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154317/2/jmri26877_am.pd

Predicting cleavability of peptide sequences by HIV protease via correlation-angle approach

In designing HIV protease inhibitors as potential drugs for AIDS therapy, knowledge about what peptide sequences in polyproteins are cleavable by HIV proteases is very useful. In this article, based on the formulation that any octapeptide can be uniquely expressed as a 160-dimensional vector and the principle that the similarity of any two such vectors is associated with their correlation angle, a new method is proposed to predict the cleavability of a peptide sequence by HIV-1 and HIV-2 proteases. The average predicted accuracy the new method for the 105 peptide sequences whose cleavability by HIV-1 protease is known is 96/105=9.14%, which is about 8% higher than that by the existing method for the same set of data. A considerably high rate of correct prediction was also obtained when the new method was used to predict the HIV-2 protease-cleaved sites in some proteins.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45081/1/10930_2005_Article_BF01028191.pd

Design and development of a complex narrative intervention delivered by text messages to reduce binge drinking among socially disadvantaged men

Background: Socially disadvantaged men are at high risk of suffering from alcohol-related harm. Disadvantaged groups are less likely to engage with health promotion. There is a need for interventions that reach large numbers at low cost and which promote high levels of engagement with the behaviour change process. The aim of this study was to design a theoretically and empirically based text message intervention to reduce binge drinking by socially disadvantaged men. Results: Following MRC guidance, the intervention was developed in four stages. Stage 1 developed a detailed behaviour change strategy based on existing literature and theory from several areas. These included the psychological theory that would underpin the intervention, alcohol brief interventions, text message interventions, effective behaviour change techniques, narratives in behaviour change interventions and communication theory. In addition, formative research was carried out. A logic model was developed to depict the pathways between intervention inputs, processes and outcomes for behaviour change. Stage 2 created a narrative which illustrated and modelled key steps in the strategy. Stage 3 rendered the intervention into a series of text messages and ensured that appropriate behavioural change techniques were incorporated. Stage 4 revised the messages to ensure comprehensive coverage of the behaviour change strategy and coherence of the narrative. It also piloted the intervention and made final revisions to it. Conclusions: The structured, systematic approach to design created a narrative intervention which had a strong theoretical and empirical basis. The use of a narrative helped make the intervention realistic and allowed key behaviour change techniques to be modelled by characters. The narrative was intended to promote engagement with the intervention. The intervention was rendered into a series of short text messages, and subsequent piloting showed they were acceptable in the target group. Delivery of an intervention by text message offers a low-cost, low-demand method that can reach large numbers of people. This approach provides a framework for the design of behaviour change interventions which could be used for interventions to tackle other health behaviours

How to find simple and accurate rules for viral protease cleavage specificities

<p>Abstract</p> <p>Background</p> <p>Proteases of human pathogens are becoming increasingly important drug targets, hence it is necessary to understand their substrate specificity and to interpret this knowledge in practically useful ways. New methods are being developed that produce large amounts of cleavage information for individual proteases and some have been applied to extract cleavage rules from data. However, the hitherto proposed methods for extracting rules have been neither easy to understand nor very accurate. To be practically useful, cleavage rules should be accurate, compact, and expressed in an easily understandable way.</p> <p>Results</p> <p>A new method is presented for producing cleavage rules for viral proteases with seemingly complex cleavage profiles. The method is based on orthogonal search-based rule extraction (OSRE) combined with spectral clustering. It is demonstrated on substrate data sets for human immunodeficiency virus type 1 (HIV-1) protease and hepatitis C (HCV) NS3/4A protease, showing excellent prediction performance for both HIV-1 cleavage and HCV NS3/4A cleavage, agreeing with observed HCV genotype differences. New cleavage rules (consensus sequences) are suggested for HIV-1 and HCV NS3/4A cleavages. The practical usability of the method is also demonstrated by using it to predict the location of an internal cleavage site in the HCV NS3 protease and to correct the location of a previously reported internal cleavage site in the HCV NS3 protease. The method is fast to converge and yields accurate rules, on par with previous results for HIV-1 protease and better than previous state-of-the-art for HCV NS3/4A protease. Moreover, the rules are fewer and simpler than previously obtained with rule extraction methods.</p> <p>Conclusion</p> <p>A rule extraction methodology by searching for multivariate low-order predicates yields results that significantly outperform existing rule bases on out-of-sample data, but are more transparent to expert users. The approach yields rules that are easy to use and useful for interpreting experimental data.</p

Predicting sulfotyrosine sites using the random forest algorithm with significantly improved prediction accuracy

addresses: School of Biosciences, University of Exeter, Exeter EX4 5DE, UK. [email protected]: PMCID: PMC2777180types: Journal Article; Research Support, Non-U.S. Gov't© 2009 Yang; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Tyrosine sulfation is one of the most important posttranslational modifications. Due to its relevance to various disease developments, tyrosine sulfation has become the target for drug design. In order to facilitate efficient drug design, accurate prediction of sulfotyrosine sites is desirable. A predictor published seven years ago has been very successful with claimed prediction accuracy of 98%. However, it has a particularly low sensitivity when predicting sulfotyrosine sites in some newly sequenced proteins

Prediction of Protein Domain with mRMR Feature Selection and Analysis

The domains are the structural and functional units of proteins. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop effective methods for predicting the protein domains according to the sequences information alone, so as to facilitate the structure prediction of proteins and speed up their functional annotation. However, although many efforts have been made in this regard, prediction of protein domains from the sequence information still remains a challenging and elusive problem. Here, a new method was developed by combing the techniques of RF (random forest), mRMR (maximum relevance minimum redundancy), and IFS (incremental feature selection), as well as by incorporating the features of physicochemical and biochemical properties, sequence conservation, residual disorder, secondary structure, and solvent accessibility. The overall success rate achieved by the new method on an independent dataset was around 73%, which was about 28–40% higher than those by the existing method on the same benchmark dataset. Furthermore, it was revealed by an in-depth analysis that the features of evolution, codon diversity, electrostatic charge, and disorder played more important roles than the others in predicting protein domains, quite consistent with experimental observations. It is anticipated that the new method may become a high-throughput tool in annotating protein domains, or may, at the very least, play a complementary role to the existing domain prediction methods, and that the findings about the key features with high impacts to the domain prediction might provide useful insights or clues for further experimental investigations in this area. Finally, it has not escaped our notice that the current approach can also be utilized to study protein signal peptides, B-cell epitopes, HIV protease cleavage sites, among many other important topics in protein science and biomedicine