948 resultados para 55-433C


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Nationally and internationally, context-based programs have been implemented in an attempt to engage students in chemistry through connecting the canonical science with the real-world. In Queensland, a context-based approach to chemistry was trialled in selected schools from 2002 but there is little research that investigates how students learn in a context-based setting. This paper presents one significant finding from an ethnographic study that explored the learning that occurred in an 11th grade context-based chemistry classroom in Queensland. The study found that by providing students with the opportunity to write, fluid transitions (or to-ing and fro-ing) between concepts and context were an outcome of context-based learning.

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26 tinnitus patients received either electromyogram (EMG) biofeedback with counterdemand instructions, EMG biofeedback with neutral demand instructions, or no treatment. Assessment was conducted on self-report measures of the distress associated with tinnitus, the loudness, annoyance and awareness of tinnitus, sleep-onset difficulties, depression, and anxiety. Audiological assessment of tinnitus was also conducted and EMG levels were measured (the latter only in the 2 treatment groups). No significant treatment effects were found on any of the measures. There was a significant decrease in the ratings of tinnitus awareness over the assessment occasions, but the degree of change was equivalent for treated and untreated groups. Results do not support the assertion that EMG biofeedback is an effective treatment for tinnitus.

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The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.