36 research outputs found

    Numerical modeling to determine test conditions of shear blanking test for a hybrid material

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    A dedicated blanking test (DBT) was designed to measure the bonding shear strength of a metallic hybrid sample. To identify the required design parameters of the rig, a macro numerical model was developed using Abaqus Finite element (FE) package. Copper clad aluminum hybrid samples fabricated by an axi symmetric forward spiral composite extrusion (AFSCE) process were analyzed using the developed numerical model. The effect of the design parameters including sample thickness, blanking clearance and the die and punch fillet radii were determined to ensure a pure shear blanking along the interface. The numerical results showed that the sample thickness, clearance and fillet radii have a significant effect on the measured bond shear strength and the location of the failure. The required rig was designed and composite copper clad aluminum bonding shear strength was experimentally determined based on the numerical findings.</jats:p

    Depression and anxiety symptoms moderate the relation between negative reinforcement smoking outcome expectancies and nicotine dependence.

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    ObjectiveSmoking reinforcement expectancies-expectations that smoking modulates mood-can be powerful motivators to smoke, resulting in increased nicotine dependence. The impact of smoking reinforcement expectancies on nicotine dependence may be particularly strong in individuals with increased mood or anxiety symptoms because they may be more likely to act on expectancies with smoking behavior in order to offset their affective symptoms. This study examined levels of emotional symptom dimensions as moderators of the relation between positive and negative smoking reinforcement expectancies and nicotine dependence severity in a community sample.MethodIn a cross-sectional design, 317 daily cigarette smokers (215 men) completed self-report measures of smoking reinforcement expectancies, mood and anxiety symptoms, and nicotine dependence.ResultsIncreasing levels of negative affect and anxiety symptoms strengthened associations between negative reinforcement smoking expectancies and nicotine dependence severity (moderation effects; (βs &gt; .13; ps &lt; .03) but did not moderate relations between positive reinforcement expectancies and dependence. Anhedonia did not moderate relations involving either positive or negative reinforcement smoking expectancies.ConclusionsDistinct components of anxiety and depressive symptoms interact differently with smoking reinforcement expectancies. Emotional symptoms characterized by excesses in aversive (but not deficits in appetitive) functioning may amplify tendencies to compulsively act on negative reinforcement expectancies by smoking. Cessation treatments that target negative reinforcement expectancies may be particularly salient for emotionally distressed smokers

    Erratum to: Environment-Assisted Cracking of Twinning Induced Plasticity (TWIP) Steel: Role of pH and Twinning (Metallurgical and Materials Transactions A, (2014), 45, 4, (1979-1995), 10.1007/s11661-013-2142-8)

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    Due to an error by the authors, Ref. 3, R.K. Singh Raman, M. Khalissi, and S. Khoddam: Scripta Mater., 2012, vol. 67, p. 943 should have been cited as a source of some of the data for Figures. 3, 4, 8, and 9

    Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework

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    We introduce a new approach to unsupervised estimation of feature-rich semantic role labeling models. Our model consists of two components: (1) an encoding component: a semantic role labeling model which predicts roles given a rich set of syntactic and lexical features; (2) a reconstruction component: a tensor factorization model which relies on roles to predict argument fillers. When the components are estimated jointly to minimize errors in argument reconstruction, the induced roles largely correspond to roles defined in annotated resources. Our method performs on par with most accurate role induction methods on English and German, even though, unlike these previous approaches, we do not incorporate any prior linguistic knowledge about the languages
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