69 resultados para medicinal component

em Deakin Research Online - Australia


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The awareness support for activities in collaborative environments is important for effective collaboration and coordination. It helps people know who else is doing what in a shared workspace. The amount of awareness needed varies due to specific roles users undertake during collaboration. While emphasizing the importance of roles, we introduced related research on awareness and a component-based collaboration metamodel. Based on that metamodel, several awareness elements were discussed and implemented in a collaborative environment LiveNet4. Model view controller pattern used to construct the Web-based interface of LiveNet4 was also introduced at the end of this paper.

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Examines the relationship between the magnitude of the relative slow component (SC) of pulmonary oxygen uptake VO[sub 2], citrate synthase activity, UCP2 and UCP3 mRNA levels and muscle fiber composition in both endurance-trained and recreationally active subjects. Magnitude of the relative SC of the Tr group; Indicators of aerobic fitness; High negative correlations between the magnitude of the relative SC and citrate synthase activity and VO[sub 2] peak.

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This article presents information about agricultural news and studies. Pharmacologists know the medicinal properties of the tropical species of Malaysia. Areca catechu is known as a common masticatory drug. An overview of the various medicinal plants, including Andrographis paniculata, Aquilaria malaccenis, and Cassia alata is offered. Malaysian medicinal plants act as strong therapeutic agents for several human diseases.

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This article reveals some common medicinal plants from Thailand.

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Clinical education is an essential part of every undergraduate nursing curriculum. The main benefits are that it allows students to put theory into practice and experience the realities of the practice- based nursing profession. Limitations include the unstable nature of the clinical area as a learning environment and the challenges this produces with students' assessments. This article reviews the literature and concludes there is room for significant improvement in the area of clinical education and numerous strategies can be implemented to do so.

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Summary We examined the independent and combined effects of a multi-component exercise program and calcium–vitamin-D3-fortified milk on bone mineral density (BMD) in older men. Exercise resulted in a 1.8% net gain in femoral neck BMD, but additional calcium–vitamin D3 did not enhance the response in this group of older well-nourished men.

Introduction This 12-month randomised controlled trial assessed whether calcium–vitamin-D3-fortified milk could enhance the effects of a multi-component exercise program on BMD in older men.

Methods Men (n  = 180) aged 50–79 years were randomised into: (1) exercise + fortified milk; (2) exercise; (3) fortified milk; or (4) controls. Exercise consisted of high intensity progressive resistance training with weight-bearing impact exercise. Men assigned to fortified milk consumed 400 mL/day of low fat milk providing an additional 1,000 mg/day calcium and 800 IU/day vitamin D3. Femoral neck (FN), total hip, lumbar spine and trochanter BMD and body composition (DXA), muscle strength 25-hydroxyvitamin D and parathyroid hormone (PTH) were assessed.

Results There were no exercise-by-fortified milk interactions at any skeletal site. Exercise resulted in a 1.8% net gain in FN BMD relative to no-exercise (p < 0.001); lean mass (0.6 kg, p < 0.05) and muscle strength (20–52%, p < 0.001) also increased in response to exercise. For lumbar spine BMD, there was a net 1.4–1.5% increase in all treatment groups relative to controls (all p < 0.01). There were no main effects of fortified milk at any skeletal site.

Conclusion A multi-component community-based exercise program was effective for increasing FN BMD in older men, but additional calcium–vitamin D3 did not enhance the osteogenic response.

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The eigenvector associated with the smallest eigenvalue of the autocorrelation matrix of input signals is called minor component. Minor component analysis (MCA) is a statistical approach for extracting minor component from input signals and has been applied in many fields of signal processing and data analysis. In this letter, we propose a neural networks learning algorithm for estimating adaptively minor component from input signals. Dynamics of the proposed algorithm are analyzed via a deterministic discrete time (DDT) method. Some sufficient conditions are obtained to guarantee convergence of the proposed algorithm.