878 resultados para Innovative student support


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BACKGROUND: Social support has been found to be protective from adverse health effects of psychological stress. We hypothesized that higher social support would predict a more favorable course of Crohn's disease (CD) directly (main effect hypothesis) and via moderating other prognostic factors (buffer hypothesis). METHODS: Within a multicenter cohort study we observed 597 adults with CD for 18 months. We assessed social support using the ENRICHD Social Support Inventory. Flares, nonresponse to therapy, complications, and extraintestinal manifestations were recorded as a combined endpoint indicating disease deterioration. We controlled for several demographic, psychosocial, and clinical variables of potential prognostic importance. We used multivariate binary logistic regression to estimate the overall effect of social support on the odds of disease deterioration and to explore main and moderator effects of social support by probing interactions with other predictors. RESULTS: The odds of disease deterioration decreased by 1.5 times (95% confidence interval [CI]: 1.2-1.9) for an increase of one standard deviation (SD) of social support. In case of low body mass index (BMI) (i.e., 1 SD below the mean or <19 kg/m(2)), the odds decreased by 1.8 times for an increase of 1 SD of social support. In case of low social support, the odds increased by 2.1 times for a decrease of 1 SD of BMI. Low BMI was not predictive under high social support. CONCLUSIONS: The findings suggest that elevated social support may favorably affect the clinical course of CD, particularly in patients with low BMI. (Inflamm Bowel Dis 2010;).

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Purpose of the study: Basic life support (BLS) and automated externaldefibrillation (AED) represent important skills to be acquired duringpregraduate medical training. Since 3 years, our medical school hasintroduced a BLS-AED course (with certification) for all second yearmedical students. Few reports about quality and persistence over timeof BLS-AED learning are available to date in the medical literature.Comprehensive evaluation of students' acquired skills was performedat the end of the 2008 academic year, 6 month after certification.Materials and methods: The students (N = 142) were evaluated duringa 9 minutes «objective structured clinical examination» (OSCE) station.Out of a standardized scenario, they had to recognize a cardiac arrestsituation and start a resuscitation process. Their performance wererecorded on a PC using an Ambuman(TM) mannequin and the AmbuCPR software kit(TM) during a minimum of 8 cycles (30 compressions:2 ventilations each). BLS parameters were systematically checked. Nostudent-rater interactions were allowed during the whole evaluation.Results: Response of the victim was checked by 99% of the students(N = 140), 96% (N = 136) called for an ambulance and/or an AED. Openthe airway and check breathing were done by 96% (N = 137), 92% (N =132) gave 2 rescue breaths. Pulse was checked by 95% (N=135), 100%(N = 142) begun chest compression, 96% (N = 136) within 1 minute.Chest compression rate was 101 ± 18 per minute (mean ± SD), depthcompression 43 ± 8 mm, 97% (N = 138) respected a compressionventilationratio of 30:2.Conclusions: Quality of BLS skills acquisition is maintained during a6-month period after a BLS-AED certification. Main targets of 2005 AHAguidelines were well respected. This analysis represents one of thelargest evaluations of specific BLS teaching efficiency reported. Furtherfollow-up is needed to control the persistence of these skills during alonger time period and noteworthy at the end of the pregraduatemedical curriculum.

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Early immunological data, obtained by immunodiffusion and immunoelectrophoresis, on the whole-cell antigenicity of kinetoplastid protozoa were retrieved and used to construct a dendrogram of antigenic distances. Remarkably, they supported the same taxonomic conclusions as analyses based on DNA and protein sequence data.

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Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

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In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

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BACKGROUND The number of copies of the HLA-DRB1 shared epitope, and the minor alleles of the STAT4 rs7574865 and the PTPN22 rs2476601 polymorphisms have all been linked with an increased risk of developing rheumatoid arthritis. In the present study, we investigated the effects of these genetic variants on disease activity and disability in patients with early arthritis. METHODOLOGY AND RESULTS We studied 640 patients with early arthritis (76% women; median age, 52 years), recording disease-related variables every 6 months during a 2-year follow-up. HLA-DRB1 alleles were determined by PCR-SSO, while rs7574865 and rs2476601 were genotyped with the Taqman 5' allelic discrimination assay. Multivariate analysis was performed using generalized estimating equations for repeated measures. After adjusting for confounding variables such as gender, age and ACPA, the TT genotype of rs7574865 in STAT4 was associated with increased disease activity (DAS28) as compared with the GG genotype (β coefficient [95% confidence interval] = 0.42 [0.01-0.83], p = 0.044). Conversely, the presence of the T allele of rs2476601 in PTPN22 was associated with diminished disease activity during follow-up in a dose-dependent manner (CT genotype = -0.27 [-0.56- -0.01], p = 0.042; TT genotype = -0.68 [-1.64- -0.27], p = 0.162). After adjustment for gender, age and disease activity, homozygosity for the T allele of rs7574865 in STAT4 was associated with greater disability as compared with the GG genotype. CONCLUSIONS Our data suggest that patients with early arthritis who are homozygous for the T allele of rs7574865 in STAT4 may develop a more severe form of the disease with increased disease activity and disability.

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The presentation will focus on the reasons for deploying an e-reader loan service at a virtual university library as a part of an e-learning support system to aid user mobility, concentration of documentary and electronic resources, and ICT skills acquisition, using the example of the UOC pilot project and its subsequent consolidation. E-reader devices at the UOC are an extension of the Virtual Campus. They are offered as a tool to aid user mobility, access to documentary and electronic resources, and development of information and IT skills. The e-reader loan service began as a pilot project in 2009 and was consolidated in 2010. The UOC Library piloted the e-reader loan service from October to December 2009. The pilot project was carried out with 15 devices and involved 37 loans. The project was extended into 2010 with the same number of devices and 218 loans (October 2010). In 2011 the e-reader loan service is to involve 190 devices, thus offering an improved service. The reasons for deploying an e-reader loan service at the UOC are the following: a) to offer library users access to the many kinds of learning materials available at the UOC through a single device that facilitates student study and learning; b) to enhance access to and use of the e-book collections subscribed to by the UOC Library; c) to align with UOC strategy on the development of learning materials in multiple formats, and promote e-devices as an extension of the UOC Virtual Campus, and d) to increase UOC Library visibility within and beyond the institution. The presentation will conclude with an analysis of the key issues to be taken into account at a university library: the e-reader market, the unclear business and license model for e-book contents, and the library's role in promoting new reading formats to increase use of e-collections.