7 resultados para competitions

em CentAUR: Central Archive University of Reading - UK


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Travellers’ diarrhoea (TD) is the most common gastrointestinal illness to affect athletes competing abroad. Consequences of this debilitating condition include difficulties with training and/or participating in competitions which the athlete may have spent several years preparing for. Currently, there are no targeted strategies to reduce TD incidence in athletes. General methods used to reduce TD risk, such as avoidance of contaminated foods, chemoprophylactics and immunoprophylactics, have disadvantages. Since most causative agents of TD are microbial, strategies to minimise TD risks may be better focused on the gut microbiota. Prebiotics and probiotics can fortify the gut microbial balance, thus potentially aiding the fight against TD-associated microorganisms. Specific probiotics have shown promising actions against TD-associated microorganisms through antimicrobial activities. Use of prebiotics has led to an improved intestinal microbial balance which may be better equipped to combat TD-associated microorganisms. Both approaches have shown promising results in general travelling populations; therefore, a targeted approach for athletes has the potential to provide a competitive advantage.

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Cybernetics is a broad subject, encompassing many aspects of electrical, electronic, and computer engineering, which suffers from a lack of understanding on the part of potential applicants and teachers when recruiting students. However, once the engineering values, fascinating science, and pathways to rewarding, diverse careers are communicated, appropriate students can be very interested in enrolling. At the University of Reading, Reading, U.K., a key route for outreach to prospective students has been achieved through the use of robots in interactive talks at schools, competitions (often funded by Public Understanding of Science projects), a collectable fortnightly magazine, exhibitions in museums, open days at the University, and appearances in the media. This paper identifies the interactive engagement, anthropomorphic acceptability, and inspirational nature of robots as being key to their successful use in outreach activities. The statistical results presented show that the continued popularity of degrees at Reading in cybernetics, electronic engineering, and robotics over the last 20 years is in part due to the outreach activities to schools and the general public.

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Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

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Growing interest in bilingual education in sub-Saharan Africa has highlighted an urgent need for reading material in African languages. In this paper, we focus on authors, one of several groups of stakeholders with responsibility for meeting this demand. We address three main issues: the nature and extent of African language publishing for children; the challenges for authors; and the available support. Our analysis is based on interviews and focus group discussions with publishers, authors, translators, educationalists, and representatives of book promotion organisations from nine African countries and documentary data on children's books in African languages in South Africa. Although there is evidence of a growing interest in producing books in local languages, the number of titles is constrained by funding. The challenges for authors include the need to understand the ingredients for successful children's books and for the sensitivity necessary to negotiate the linguistic challenges associated with a newly emergent genre in African languages. Support, in the form of competitions and workshops, relies on external funding and expertise and offers only temporary solutions. We finish with suggestions for more sustainable ways forward.

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This paper describes some recent advances and contributions to our understanding of economic forecasting. The framework we develop helps explain the findings of forecasting competitions and the prevalence of forecast failure. It constitutes a general theoretical background against which recent results can be judged. We compare this framework to a previous formulation, which was silent on the very issues of most concern to the forecaster. We describe a number of aspects which it illuminates, and draw out the implications for model selection. Finally, we discuss the areas where research remains needed to clarify empirical findings which lack theoretical explanations.

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Model quality assessment programs (MQAPs) aim to assess the quality of modelled 3D protein structures. The provision of quality scores, describing both global and local (per-residue) accuracy are extremely important, as without quality scores we are unable to determine the usefulness of a 3D model for further computational and experimental wet lab studies.Here, we briefly discuss protein tertiary structure prediction, along with the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) competition and their key role in driving the field of protein model quality assessment methods (MQAPs). We also briefly discuss the top MQAPs from the previous CASP competitions. Additionally, we describe our downloadable and webserver-based model quality assessment methods: ModFOLD3, ModFOLDclust, ModFOLDclustQ, ModFOLDclust2, and IntFOLD-QA. We provide a practical step-by-step guide on using our downloadable and webserver-based tools and include examples of their application for improving tertiary structure prediction, ligand binding site residue prediction, and oligomer predictions.

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Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.