246 resultados para energy education


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The project was commissioned to investigate and analyse the issue of effective support for distance education students in the early years of school to maximise literacy and numeracy outcomes. The scope of this project was limited to students living in rural and remote areas who are undertaking education at home and who are in their early years of schooling. For the purpose of this project, the early years are conceptualised as the first three years of formal compulsory schooling in each of the States and Territories. There were a number of key tasks for the project which included: 1. Examining of the role of home tutors/supervisors This included interviewing personnel from the State and Territory distance education providers as well as the principals, teachers, home tutors and children. 2. Describing literacy and numeracy teaching and learning, and the use of information and communication technologies (ICT) in distance education This aspect of the project involved a critical review and analysis of relevant literature and reports in the last five years, and a consideration of the new initiatives that had been implemented in the States and Territories in the last two years. 3. The development of resources Through examination of the role of home tutors/supervisors, and an examination of literacy and numeracy and the use of technology in distance education, three resources were developed: ● A guide for home tutors/supervisors and schools of distance education about effective intervention and assessment strategies to support students’ learning and to assist the home tutors/supervisors in implementing ICT to support the development of literacy and numeracy in the early years. ● A calendar of activities for literacy and numeracy that would act as a stimulus for integrated and authentic activity for young children. ● An embryonic website of resources for the stakeholders in rural and distance education that might act as a catalyst for future resource building and sharing. In this way the final key task of the project, which was to create a context for a strategic dissemination plan, was realised when a strategy to address effective dissemination of the findings of the project so as to maximise their usefulness for the relevant groups was achieved.

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The linear relationship between work accomplished (W-lim) and time to exhaustion (t(lim)) can be described by the equation: W-lim = a + CP.t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five art-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W-lim-t(lim) regression and calculated three ways: 1) using the first, third and fifth W-lim-t(lim) coordinates (I-135), 2) using coordinates from the three highest power outputs (I-123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I-345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0 +/- 37.9W) > CPI135 (176.1 +/- 27.6W) > CPI345 (164.0 +/- 22.8W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W-lim-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain for a very long time without fatigue then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.

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The role of dissolved free amino acids (DFAA) in nitrogen and energy budgets was investigated for the giant clam, Tridacna maxima, growing under field conditions at One Tree Island, at the southern end of the Great Barrier Reef, Australia. Giant clams (121.5-143.7 mm in shell length) took up neutral, acidic and basic amino acids. The rates of net uptake of DFAA did not differ between light and dark, nor for clams growing under normal or slightly enriched ammonium concentrations. Calculations based on the net uptake concentrations typical of the maximum concentrations of DFAA found in coral reef waters (similar to 0.1 mu M)revealed that DFAA could only contribute 0.1% and 1% of the energy and nitrogen demands of giant clams, respectively. These results suggest that DFAA does not supply significant amounts of energy or nitrogen for giant clams or their symbionts.

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OBJECTIVE: To use magnetic resonance imaging (MRI) to validate estimates of muscle and adipose tissue (AT) in lower limb sections obtained by dual-energy X-ray absorptiometry (DXA) modelling. DESIGN: MRI measurements were used as reference for validating limb muscle and AT estimates obtained by DXA models that assume fat-free soft tissue (FFST) comprised mainly muscle: model A accounted for bone hydration only; model B also applied constants for FFST in bone and skin and fat in muscle and AT; model C was as model B but allowing for variable fat in muscle and AT. SUBJECTS: Healthy men (n = 8) and women (n = 8), ages 41 - 62 y; mean (s.d.) body mass indices (BMIs) of 28.6 (5.4) kg/m(2) and 25.1 (5.4) kg/m2, respectively. MEASUREMENTS: MRI scans of the legs and whole body DXA scans were analysed for muscle and AT content of thigh (20 cm) and lower leg (10 cm) sections; 24 h creatinine excretion was measured. RESULTS: Model A overestimated thigh muscle volume (MRI mean, 2.3 l) substantially (bias 0.36 l), whereas model B underestimated it by only 2% (bias 0.045 l). Lower leg muscle (MRI mean, 0.6 l) was better predicted using model A (bias 0.04 l, 7% overestimate) than model B (bias 0.1 l, 17% underestimate). The 95% limits of agreement were high for these models (thigh,+/- 20%; lower leg,+/- 47%). Model C predictions were more discrepant than those of model B. There was generally less agreement between MRI and all DXA models for AT. Measurement variability was generally less for DXA measurements of FFST (coefficient of variation 0.7 - 1.8%) and fat (0.8 - 3.3%) than model B estimates of muscle (0.5-2.6%) and AT (3.3 - 6.8%), respectively. Despite strong relationships between them, muscle mass was overestimated by creatinine excretion with highly variable predictability. CONCLUSION: This study has shown the value of DXA models for assessment of muscle and AT in leg sections, but suggests the need to re-evaluate some of the assumptions upon which they are based.