789 resultados para Assessment and Variability
The variability in adherence to dietary treatment and quality of weight loss: overweight and obesity
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Objective: Observation of weight loss and the maximum time that individualized dietary treatment qualitative and quantitative is shown to be effective. Method: 4625 consultations were conducted with 616 patients over 25 years old, in the nutrition consultation, using the qualitative and quantitative individualized dietary treatment. As a result we controlled the weight loss, the fat and the quality and variability of the loss, monthly according to sex, age and BMI in an urban area of southeastern Spain. Results and discussion: A low level of abandonment was proved in men, patients older than 45 years old compared to obese showed a higher degree. The quality of the loss was greater in men under 45 years old, overweight patients, however, more research is needed in this area. Measuring the waist and hips has led to an increasing interest in measuring indicators of body fat. Conclusion: The individualized dietary treatment has been proved to be effective for six months and then a multidisciplinary mode of this treatment is recommended. The use of new ways to assess weight loss is proposed taking into consideration the quality and variability of loss, regardless of the treatment used.
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"July 1979"
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"February 1, 2006; CERCLIS No. NYSFN0204190."
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A combination of physical and chemical measurements and biological indicators identified nutrient impacts throughout an Australian subtropical river estuary. This was a balance of sewage inputs in the lower river and agricultural inputs in the mid-upper river, the combined influence being greater in the wet season due to greater agricultural surface runoff. Field sampling in the region was conducted at 6 sites within the river, over 5 surveys to encapsulate both wet and dry seasonal effects. Parameters assessed were tissue nitrogen (N) contents and delta(15)N signatures of mangroves and macroalgae, phytoplankton nutrient addition bioassays, and standard physical and chemical variables. Strong spatial (within river) and temporal (seasonal) variability was observed in all parameters. Poorest water quality was detected in the middle (agricultural) region of the river in the wet season, attributable to large diffuse inputs in this region. Water quality towards the river mouth remained constant irrespective of season due to strong oceanic flushing. Mangrove and macroalgal tissue delta(15)N and %N proved a successful combination for discerning sewage and agricultural inputs. Elevated delta(15)N and %N represented sewage inputs, whereas low delta(15)N and elevated %N was indicative of agricultural inputs. Phytoplankton bioassays found the system to be primarily responsive to nutrient additions in the warmer wet season, with negligible responses observed in the cooler dry season. These results indicate that the Tweed River is sensitive to the different anthropogenic activities in its catchment and that each activity has a unique influence on receiving water quality.
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The behavior and stability of motor units (MUs) in response to electrical stimulation of different intensities can be assessed with the stimulus-response curve, which is a graphical representation of the size of the compound muscle action potential (CMAP) in relation to stimulus intensity. To examine MU characteristics across the whole stimulus range, the variability of CMAP responses to electrical stimulation, and the differences that occur between normal and disease states, the curve was studied in 11 normal subjects and 16 subjects with amyotrophic lateral sclerosis (ALS). In normal subjects, the curve showed a gradual increase in CMAP size with increasing stimulus intensity, although one or two discrete steps were sometimes observed in the upper half of the curve, indicating the activation of large MUs at higher intensities. In ALS subjects, large discrete steps, due to loss of MUs and collateral sprouting, were frequently present. Variability of the CMAP responses was greater than baseline variability, indicating variability of MU responses, and at certain levels this variability was up to 100 mu Vms. The stimulus-response curve shows differences between normal and ALS subjects and provides information on MU activation and variability throughout the curve.
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Large areas of tropical sub- and inter-tidal seagrass beds occur in highly turbid environments and cannot be mapped through the water column. The purpose of this project was to determine if and how airborne and satellite imaging systems could be used to map inter-tidal seagrass properties along the wet-tropics coast in north Queensland, Australia. The work aimed to: (1) identify the minimum level of seagrass foliage cover that could be detected from airborne and satellite imagery; and (2) define the minimum detectable differences in seagrass foliage cover in exposed intertidal seagrass beds. High resolution spectral-reflectance data (2040 bands, 350 – 2500nm) were collected over 40cm diameter plots from 240 sites on Magnetic Island, Pallarenda Beach and Green Island in North Queensland at spring low tides in April 2006. The seagrass species sampled were: Thalassia hemprechii, Halophila ovalis, Halodule uninerivs; Syringodium isoetifolium, Cymodocea serrulata, and Cymodoea rotundata. Digital photos were captured for each plot and used to derive estimates of seagrass species cover, epiphytic growth, micro- and macro-algal cover, and substrate colour. Sediment samples were also collected and analysed to measure the concentration of Chlorophyll-a associated with benthic micro-algae. The field reflectance spectra were analysed in combination with their corresponding seagrass species foliage cover levels to establish the minimum foliage projective cover required for each seagrass to be significantly different from bare substrate and substrate with algal cover. This analysis was repeated with reflectance spectra resampled to the bandpass functions of Quickbird, Ikonos, SPOT 5 and Landsat 7 ETM. Preliminary results indicate that conservative minimum detectable seagrass cover levels across most the species sampled were between 30%- 35% on dark substrates. Further analysis of these results will be conducted to determine their separability and satellite images and to assess the effects epiphytes and algal cover.
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Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.