Visible practices of Christian community in online video small groups

https://place.asburyseminary.edu/ecommonsatsdissertations/2262/thumbnail.jp

Bimodal or quadrimodal? Statistical tests for the shape of fault patterns

DH gratefully acknowledges receipt of NERC grant NE/N003063/1, and thanks the School of Geosciences at the University of Aberdeen for accommodating a period of research study leave, during which time this paper was written. We thank two anonymous reviewers, plus Atilla Aydin (Stanford) and Nigel Woodcock (Cambridge) for comments which helped us improve the paper.Peer reviewedPublisher PD

The influence of secondary flow structures in a turbocharger turbine housing in steady state and pulsating flow conditions

This paper presents a computational investigation into the effect of volute secondary flow structures on turbine inlet flow conditions. The steady state results show Dean type vortices exist early in the volute. As a result a substantial variation in absolute flow angle at the volute exit was observed. Pulsed flow simulations showed that the size and position of the secondary flow structures are time dependent. The resulting volute exit flow conditions were also found to be time dependent with the absolute flow angle at the volute exit varying with pulse pressure. This paper shows that that the secondary flow structures that exist in the volute as a result of cross sectional shape can have significant downstream effects on rotor performance

The introduction of a tilted volute design for operation with a mixed flow turbine for turbocharger applications

This paper introduces a tilted volute design for operation with a mixed flow turbine rotor. CFD results show an efficiency gain of up to 1.2% over the standard radial design at the highest tested turbine rotational speed. The efficiency gain was found to be the result of a reduction in separation from the blade suction surface. A reduction in the flow cone angle was also observed for the tilted housing, as a result an increase in negative incidence angles at the blade LE was observed. This work shows that optimization of the turbine housing specifically for mixed flow applications can yield significant performance benefits

Fundamental modelling of friction during the hot rolling of steel.

Friction is one of the most significant physical phenomena influencing metal forming, yet in comparison with metallurgy, heat transfer and mechanics it remains the least understood. The goal of this project was to develop, on as fundamental a level as possible, a friction model based upon the physics of the process to be applied to the hot rolling of steel. A fundamental friction model was developed based upon the simplified approach to the adhesion theory by Straffelini (Wear, 249, 79-85, 2001), which is an extension of Bowden and Tabor's original adhesion theory. In this work, the simplified approach's dependence on the thermodynamic work of adhesion was exploited to apply it over a wide range of temperatures. The thermodynamic work of adhesion describes the work required to form a new surface and is a function of the surface energy of the contacting materials was estimated using two approaches: Rabinowicz's and the geometric mean rule. Since high temperature surface energy data is not generally available the relative change in Young's modulus with temperature was used to estimate a material's surface energy at a desired temperature. Reciprocating friction experiments, which provided a controlled environment in which to investigate friction, were conducted to verify the application of this theory to high temperature conditions and metal-oxide contacting materials. The fundamental model describing friction was applied to the hot rolling of steel via a friction algorithm using the commercial finite element (FE) code MARC. Simply described the friction algorithm calculated a friction coefficient using material properties, defined by the user, and contact temperatures, taken from the rolling model. This resulted in the friction coefficient predicted throughout the roll bite, compared to an average friction coefficient typically employed in rolling models. The combined friction algorithm-rolling model was validated against laboratory rolling experiments. One of the assumptions of the finite element rolling model is the presence of a thin, continuous and adherent scale layer. To achieve this in the laboratory a two pass rolling schedule was employed; the first pass to remove the furnace scale and the second pass to input the desired deformation. The success of the friction algorithm was determined by comparing the experimental torques and loads to the predictions of the finite element model. The FE model with the friction algorithm predicted the friction coefficient to vary in the roll gap between approximately 0.25 and 0.35 and was able to predict the measured rolling torque with an average error of 15%, which was considered acceptable and the accuracy was increased after the bearing torque was considered. The error in the load predictions compared to the measured loads was 13.5% on average, which was also acceptable

Withdrawal from escalated cocaine self-administration impairs reversal learning by disrupting the effects of negative feedback on reward exploitation: a behavioral and computational analysis.

Addiction is regarded as a disorder of inflexible choice with behavior dominated by immediate positive rewards over longer-term negative outcomes. However, the psychological mechanisms underlying the effects of self-administered drugs on behavioral flexibility are not well understood. To investigate whether drug exposure causes asymmetric effects on positive and negative outcomes we used a reversal learning procedure to assess how reward contingencies are utilized to guide behavior in rats previously exposed to intravenous cocaine self-administration (SA). Twenty-four rats were screened for anxiety in an open field prior to acquisition of cocaine SA over six daily sessions with subsequent long-access cocaine SA for 7 days. Control rats (n = 24) were trained to lever-press for food under a yoked schedule of reinforcement. Higher rates of cocaine SA were predicted by increased anxiety and preceded impaired reversal learning, expressed by a decrease in lose-shift as opposed to win-stay probability. A model-free reinforcement learning algorithm revealed that rats with high, but not low cocaine escalation failed to exploit previous reward learning and were more likely to repeat the same response as the previous trial. Eight-day withdrawal from high cocaine escalation was associated, respectively, with increased and decreased dopamine receptor D2 (DRD2) and serotonin receptor 2C (HTR2C) expression in the ventral striatum compared with controls. Dopamine receptor D1 (DRD1) expression was also significantly reduced in the orbitofrontal cortex of high cocaine-escalating rats. These findings indicate that withdrawal from escalated cocaine SA disrupts how negative feedback is used to guide goal-directed behavior for natural reinforcers and that trait anxiety may be a latent variable underlying this interaction.Pinsent Darwin Studentship, Cambridge University Swedish Research Council AXA Research Fund National Health and MRC of Australia Cambridge Isaac Newton Trust Boehringer Ingelheim Pharma GmbH, German

Supplemental Information 2: Example dataset description

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets

Correction: Withdrawal from escalated cocaine self-administration impairs reversal learning by disrupting the effects of negative feedback on reward exploitation: a behavioral and computational analysis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper