<p dir="ltr">The existing landscape of collaboration and partnership-based research involving university writing centers primarily explores joint initiatives with campus libraries, academic programs, and high schools designed to support a variety of student learning objectives. This project is motivated by the increasing demand for partnerships between institutions of higher education across national borders and responds to a critical gap in writing center collaboration research involving international partners and identity-affirming campus partners to support the literacy and language learning needs of culturally and linguistically diverse students. Through the lens of a multi-institutional partnership between Colombia and the United States, the study draws on the insights and experiences of staff, tutors, and administrators from two writing centers at partner institutions in Colombia and a Latino cultural center at a university in the United States offering multilingual support programming. Qualitative findings support ideas for the development of collaborative visions between partners and suggest implications for individual and collective agency in partnership settings. Based on participant input about student experiences with language politics, sense of belonging, and access to support on campus, this study also proposes recommendations for building accompliceships with partners through a critical collaborative approach aimed at developing intercultural competence and a mindfulness of difference in writing mentorship.</p>

No / Despite an explosion of interest in improving safety and reducing error in health care, one important aspect of patient safety that has received little attention is a systematic approach to education and training for the whole health care workforce. This article describes an evaluation of an innovative multiprofessional, team-based training program that embeds patient safety within quality improvement methods. METHODS: Kirkpatrick's "levels of evaluation" model was adopted to evaluate the program in health organizations across one city in the north of England. Questionnaires were used to assess reaction of participants to the program (Level 1). Improvements in patient safety knowledge and patient safety culture (Level 2) were assessed using a 12-item multiple-choice questionnaire and a culture questionnaire. Interviews and project-specific quantitative measurements were used to assess changes in professional practice and patient outcomes (Levels 3 and 4). RESULTS: All aspects of the program were positively received by participants. Few participants completed the MCQ at both time points, but those who did showed improvement in knowledge. There were some small but significant improvements in patient safety culture. Interviews revealed a number of additional benefits beyond the specific problems addressed. Most importantly, 8 of the 11 teams showed improvements in patient safety practices and/or outcomes. DISCUSSION: This program is an example of interprofessional education in practice and demonstrates that team-based learning using quality improvement methods is feasible and can be effective in improving patient safety, but requires time and space for participants. Alignment with continuing education arrangements could support mainstream adoption of this approach within organizations. / Despite an explosion of interest in improving safety and reducing error in health care, one important aspect of patient safety that has received little attention is a systematic approach to education and training for the whole health care workforce. This article describes an evaluation of an innovative multiprofessional, team-based training program that embeds patient safety within quality improvement methods. Methods: Kirkpatrick's “levels of evaluation” model was adopted to evaluate the program in health organizations across one city in the north of England. Questionnaires were used to assess reaction of participants to the program (Level 1). Improvements in patient safety knowledge and patient safety culture (Level 2) were assessed using a 12-item multiple-choice questionnaire and a culture questionnaire. Interviews and project-specific quantitative measurements were used to assess changes in professional practice and patient outcomes (Levels 3 and 4). Results: All aspects of the program were positively received by participants. Few participants completed the MCQ at both time points, but those who did showed improvement in knowledge. There were some small but significant improvements in patient safety culture. Interviews revealed a number of additional benefits beyond the specific problems addressed. Most importantly, 8 of the 11 teams showed improvements in patient safety practices and/or outcomes. Discussion: This program is an example of interprofessional education in practice and demonstrates that teambased learning using quality improvement methods is feasible and can be effective in improving patient safety, but requires time and space for participants. Alignment with continuing education arrangements could support mainstream adoption of this approach within organizations.

This thesis details the development, verification and validation of an unsteady unstructured high order (≥ 3) h/p Discontinuous Galerkin - Fourier solver for the incompressible Navier-Stokes equations on static and rotating meshes in two and three dimensions. This general purpose solver is used to provide insight into cross-flow (wind or tidal) turbine physical phenomena. Simulation of this type of turbine for renewable energy generation needs to account for the rotational motion of the blades with respect to the fixed environment. This rotational motion implies azimuthal changes in blade aero/hydro-dynamics that result in complex flow phenomena such as stalled flows, vortex shedding and blade-vortex interactions. Simulation of these flow features necessitates the use of a high order code exhibiting low numerical errors. This thesis presents the development of such a high order solver, which has been conceived and implemented from scratch by the author during his doctoral work. To account for the relative mesh motion, the incompressible Navier-Stokes equations are written in arbitrary Lagrangian-Eulerian form and a non-conformal Discontinuous Galerkin (DG) formulation (i.e. Symmetric Interior Penalty Galerkin) is used for spatial discretisation. The DG method, together with a novel sliding mesh technique, allows direct linking of rotating and static meshes through the numerical fluxes. This technique shows spectral accuracy and no degradation of temporal convergence rates if rotational motion is applied to a region of the mesh. In addition, analytical mappings are introduced to account for curved external boundaries representing circular shapes and NACA foils. To simulate 3D flows, the 2D DG solver is parallelised and extended using Fourier series. This extension allows for laminar and turbulent regimes to be simulated through Direct Numerical Simulation and Large Eddy Simulation (LES) type approaches. Two LES methodologies are proposed. Various 2D and 3D cases are presented for laminar and turbulent regimes. Among others, solutions for: Stokes flows, the Taylor vortex problem, flows around square and circular cylinders, flows around static and rotating NACA foils and flows through rotating cross-flow turbines, are presented.

Genome-wide association studies have greatly improved our understanding of the contribution of common variants to the genetic architecture of complex traits. However, two major limitations have been highlighted. First, common variant associations typically do not identify the causal variant and/or the gene that it is exerting its effect on to influence a trait. Second, common variant associations usually consist of variants with small effects. As a consequence, it is more challenging to harness their translational impact. Association studies of rare variants and complex traits may be able to help address these limitations. Empirical population genetic data shows that deleterious variants are rare. More specifically, there is a very strong depletion of common protein truncating variants (PTVs, commonly referred to as loss-of-function variants) in the genome, a group of variants that have been shown to have large effect on gene function, are enriched for severe disease-causing mutations, but in other instances may actually be protective against disease. This thesis is divided into three parts dedicated to the study of protein truncating variants, their medical relevance, and their functional consequences. First, I present statistical, bioinformatic, and computational methods developed for the study of protein truncating variants and their association to complex traits, and their functional consequences. Second, I present application of the methods to a number of case-control and quantitative trait studies discovering new variants and genes associated to breast and ovarian cancer, type 1 diabetes, lipids, and metabolic traits measured with NMR spectroscopy. Third, I present work on improving annotation of protein truncating variants by studying their functional consequences. Taken together, these results highlight the utility of interrogating protein truncating variants in medical and functional genomic studies.

The Protein Data Bank (PDB) is the definitive electronic repository for experimentally-derived protein structures, composed mainly of those determined by X-ray crystallography. Approximately 200 new structures are added weekly to the PDB, and at the time of writing, it contains approximately 97,000 structures. This represents an expanding wealth of high-quality information but there seem to be few bioinformatics tools that consider and analyse these data as an ensemble. This thesis explores the development of three efficient, fast algorithms and software implementations to study protein structure using the entire PDB. The first project is a crystal-form matching tool that takes a unit cell and quickly (< 1 second) retrieves the most related matches from the PDB. The unit cell matches are combined with sequence alignments using a novel Family Clustering Algorithm to display the results in a user-friendly way. The software tool, Nearest-cell, has been incorporated into the X-ray data collection pipeline at the Diamond Light Source, and is also available as a public web service. The bulk of the thesis is devoted to the study and prediction of protein disorder. Initially, trying to update and extend an existing predictor, RONN, the limitations of the method were exposed and a novel predictor (called MoreRONN) was developed that incorporates a novel sequence-based clustering approach to disorder data inferred from the PDB and DisProt. MoreRONN is now clearly the best-in-class disorder predictor and will soon be offered as a public web service. The third project explores the development of a clustering algorithm for protein structural fragments that can work on the scale of the whole PDB. While protein structures have long been clustered into loose families, there has to date been no comprehensive analytical clustering of short (~6 residue) fragments. A novel fragment clustering tool was built that is now leading to a public database of fragment families and representative structural fragments that should prove extremely helpful for both basic understanding and experimentation. Together, these three projects exemplify how cutting-edge computational approaches applied to extensive protein structure libraries can provide user-friendly tools that address critical everyday issues for structural biologists.