997 resultados para Session variability
Individual variability in compensatory eating following acute exercise in overweight and obese women
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Background While compensatory eating following acute aerobic exercise is highly variable, little is known about the underling mechanisms that contribute to alterations in exercise-induced eating behaviour. Methods Overweight and obese women (BMI = 29.6 ± 4.0kg.m2) performed a bout of cycling individually tailored to expend 400kcal (EX), or a time-matched no exercise control condition in a randomised, counter-balanced order. Sixty minutes after the cessation of exercise, an ad libitum test meal was provided. Substrate oxidation and subjective appetite ratings were measured during exercise/time-matched rest, and during the period between the cessation of exercise and food consumption. Results While ad libitum EI did not differ between EX and the control condition (666.0 ± 203.9kcal vs. 664.6 ± 174.4kcal, respectively; ns), there was marked individual variability in compensatory energy intake (EI). The difference in EI between EX and the control condition ranged from -234.3 to +278.5kcal. Carbohydrate oxidation during exercise was positively associated with post-exercise EI, accounting for 37% of the variance in EI (r = 0.57; p = 0.02). Conclusions These data indicate that capacity of acute exercise to create a short-term energy deficit in overweight and obese women is highly variable. Furthermore, exercise-induced CHO oxidation can explain part of the variability in acute exercise-induced compensatory eating. Post-exercise compensatory eating could serve as an adaptive response to facilitate the restoration of carbohydrate balance.
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This thesis is a population-based epidemiological study to explore the spatial and temporal pattern of malaria, and to assess the relationship between socio-ecological factors and malaria in Yunnan, China. Geospatial and temporal approaches were applied; the high risk areas of the disease were identified; and socio-ecological drivers of malaria were assessed. These findings will provide important evidence for the control and prevention of malaria in China and other countries with a similar situation of endemic malaria.
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Recent developments in wearable ECG technology have seen renewed interest in the use of Heart Rate Variability (HRV) feedback for stress management. Yet, little is know about the efficacy of such interventions. Positive reappraisal is an emotion regulation strategy that involves changing the way a situation is construed to decrease emotional impact. We sought to test the effectiveness of an intervention that used feedback on HRV data to prompt positive reappraisal during a stressful work task. Participants (N=122) completed two 20-minute trials of an inbox activity. In-between the first and the second trial participants were assigned to the waitlist control condition, a positive reappraisal via psycho-education condition, or a positive reappraisal via HRV feedback condition. Results revealed that using HRV data to frame a positive reappraisal message is more effective than using psycho-education (or no intervention)–especially for increasing positive mood and reducing arousal.
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Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.
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This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.
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BACKGROUND Malaria remains a public health problem in the remote and poor area of Yunnan Province, China. Yunnan faces an increasing risk of imported malaria infections from Mekong river neighboring countries. This study aimed to identify the high risk area of malaria transmission in Yunnan Province, and to estimate the effects of climatic variability on the transmission of Plasmodium vivax and Plasmodium falciparum in the identified area. METHODS We identified spatial clusters of malaria cases using spatial cluster analysis at a county level in Yunnan Province, 2005-2010, and estimated the weekly effects of climatic factors on P. vivax and P. falciparum based on a dataset of daily malaria cases and climatic variables. A distributed lag nonlinear model was used to estimate the impact of temperature, relative humidity and rainfall up to 10-week lags on both types of malaria parasite after adjusting for seasonal and long-term effects. RESULTS The primary cluster area was identified along the China-Myanmar border in western Yunnan. A 1°C increase in minimum temperature was associated with a lag 4 to 9 weeks relative risk (RR), with the highest effect at lag 7 weeks for P. vivax (RR = 1.03; 95% CI, 1.01, 1.05) and 6 weeks for P. falciparum (RR = 1.07; 95% CI, 1.04, 1.11); a 10-mm increment in rainfall was associated with RRs of lags 2-4 weeks and 9-10 weeks, with the highest effect at 3 weeks for both P. vivax (RR = 1.03; 95% CI, 1.01, 1.04) and P. falciparum (RR = 1.04; 95% CI, 1.01, 1.06); and the RRs with a 10% rise in relative humidity were significant from lag 3 to 8 weeks with the highest RR of 1.24 (95% CI, 1.10, 1.41) for P. vivax at 5-week lag. CONCLUSIONS Our findings suggest that the China-Myanmar border is a high risk area for malaria transmission. Climatic factors appeared to be among major determinants of malaria transmission in this area. The estimated lag effects for the association between temperature and malaria are consistent with the life cycles of both mosquito vector and malaria parasite. These findings will be useful for malaria surveillance-response systems in the Mekong river region.
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The relationship between temperature and mortality is generally found to be bathtub shaped (rising at both extremes). However, there are limited data on the potential health effects of temperature variability and on temperature itself...
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Urban road dust comprises of a range of potentially toxic metal elements and plays a critical role in degrading urban receiving water quality. Hence, assessing the metal composition and concentration in urban road dust is a high priority. This study investigated the variability of metal composition and concentrations in road dust in 4 different urban land uses in Gold Coast, Australia. Samples from 16 road sites were collected and tested for selected 12 metal species. The data set was analyzed using both univariate and multivariate techniques. Outcomes of the data analysis revealed that the metal concentrations in road dust differ considerably within and between different land uses. Iron, aluminum, magnesium and zinc are the most abundant in urban land uses. It was also noted that metal species such as titanium, nickel, copper and zinc have the highest concentrations in industrial land use. The study outcomes revealed that soil and traffic related sources as key sources of metals deposited on road surfaces.
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Used frequently in food contact materials, bisphenol A (BPA) has been studied extensively in recent years, and ubiquitous exposure in the general population has been demonstrated worldwide. Characterising within- and between-individual variability of BPA concentrations is important for characterising exposure in biomonitoring studies, and this has been investigated previously in adults, but not in children. The aim of this study was to characterise the short-term variability of BPA in spot urine samples in young children. Children aged ≥2-<4 years (n = 25) were recruited from an existing cohort in Queensland Australia, and donated four spot urine samples each over a two day period. Samples were analysed for total BPA using isotope dilution online solid phase extraction-liquid chromatography-tandem mass spectrometry, and concentrations ranged from 0.53–74.5 ng/ml, with geometric mean and standard deviation of 2.70 ng/ml and 2.94 ng/ml, respectively. Sex and time of sample collection were not significant predictors of BPA concentration. The between-individual variability was approximately equal to the within-individual variability (ICC = 0.51), and this ICC is somewhat higher than previously reported literature values. This may be the result of physiological or behavioural differences between children and adults or of the relatively short exposure window assessed. Using a bootstrapping methodology, a single sample resulted in correct tertile classification approximately 70% of the time. This study suggests that single spot samples obtained from young children provide a reliable characterization of absolute and relative exposure over the short time window studied, but this may not hold true over longer timeframes.
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Software to create individualised finite element (FE) models of the osseoligamentous spine using pre-operative computed tomography (CT) data-sets for spinal surgery patients has recently been developed. This study presents a geometric sensitivity analysis of this software to assess the effect of intra-observer variability in user-selected anatomical landmarks. User-selected landmarks on the osseous anatomy were defined from CT data-sets for three scoliosis patients and these landmarks were used to reconstruct patient-specific anatomy of the spine and ribcage using parametric descriptions. The intra-observer errors in landmark co-ordinates for these anatomical landmarks were calculated. FE models of the spine and ribcage were created using the reconstructed anatomy for each patient and these models were analysed for a loadcase simulating clinical flexibility assessment. The intra-observer error in the anatomical measurements was low in comparison to the initial dimensions, with the exception of the angular measurements for disc wedge and zygapophyseal joint (z-joint) orientation and disc height. This variability suggested that CT resolution may influence such angular measurements, particularly for small anatomical features, such as the z-joints, and may also affect disc height. The results of the FE analysis showed low variation in the model predictions for spinal curvature with the mean intra-observer variability substantially less than the accepted error in clinical measurement. These findings demonstrate that intra-observer variability in landmark point selection has minimal effect on the subsequent FE predictions for a clinical loadcase.
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We report a novel technology for the rapid healing of large osseous and chondral defects, based upon the genetic modification of autologous skeletal muscle and fat grafts. These tissues were selected because they not only possess mesenchymal progenitor cells and scaffolding properties, but also can be biopsied, genetically modified and returned to the patient in a single operative session. First generation adenovirus vector carrying cDNA encoding human bone morphogenetic protein-2 (Ad.BMP-2) was used for gene transfer to biopsies of muscle and fat. To assess bone healing, the genetically modified (“gene activated”) tissues were implanted into 5mm-long critical size, mid-diaphyseal, stabilized defects in the femora of Fischer rats. Unlike control defects, those receiving gene-activated muscle underwent rapid healing, with evidence of radiologic bridging as early as 10 days after implantation and restoration of full mechanical strength by 8 weeks. Histologic analysis suggests that the grafts rapidly differentiated into cartilage, followed by efficient endochondral ossification. Fluorescence in situ hybridization detection of Y-chromosomes following the transfer of male donor muscle into female rats demonstrated that at least some of the osteoblasts of the healed bone were derived from donor muscle. Gene activated fat also healed critical sized defects, but less quickly than muscle and with more variability. Anti-adenovirus antibodies were not detected. Pilot studies in a rabbit osteochondral defect model demonstrated the promise of this technology for healing cartilage defects. Further development of these methods should provide ways to heal bone and cartilage more expeditiously, and at lower cost, than is presently possible.
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Lipoprotein(a) (Lp(a)) is bound to apolipoprotein B-100 by disulfide linkage and is associated in the upper density range of low density lipoprotein cholesterol. Persons with elevated concentrations of Lp(a) are regarded as having an increased risk for premature coronary artery disease. Although many studies exist evaluating the effects of a single session of exercise on lipids and lipoproteins, little information is available concerning the effects of exercise on Lp(a). Therefore, the purpose of this study was to determine the effects of a single exercise session on plasma Lp(a). Twelve physically active men completed two 30-min submaximal treadmill exercise sessions: low intensity (LI, 50% VO2max) and high intensity (HI, 80% VO2max). Blood samples were obtained immediately before and after exercise. Total cholesterol (LI: before 4.22 +/- 0.26, after 4.24 +/- 0.28; HI: before 4.24 +/- 0.31, after 4.11 +/- 0.28 mmol . l(-1), mean +/- SE) and triglyceride (LI: before 1.14 +/- 0.16, after 1.06 +/- 0.16; HI: before 1.12 +/- 0.19, after 1.21 +/- 0.19 mmol . l(-1)) concentrations did not differ immediately after either exercise session, nor did Lp(a) concentrations differ immediately after either exercise session (LI: before 4.1 +/- 2.2, after 4.0 +/- 2.1; HI: before 3.9 +/- 2.2, after 3.7 +/- 2.0 mg . dl(-1)). These results suggest that neither a low nor a high intensity exercise session lasting 30 min in duration has an immediate effect on plasma Lp(a).
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Public Transport Travel Time Variability (PTTV) is essential for understanding the deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes the key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyzes the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach, using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and analyzing the transit systems.
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Background Few data on the relationship between temperature variability and childhood pneumonia are available. This study attempted to fill this knowledge gap. Methods A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantify the impacts of diurnal temperature range (DTR) and temperature change between two neighbouring days (TCN) on emergency department visits (EDVs) for childhood pneumonia in Brisbane, from 2001 to 2010, after controlling for possible confounders. Results An adverse impact of TCN on EDVs for childhood pneumonia was observed, and the magnitude of this impact increased from the first five years (2001–2005) to the second five years (2006–2010). Children aged 5–14 years, female children and Indigenous children were particularly vulnerable to TCN impact. However, there was no significant association between DTR and EDVs for childhood pneumonia. Conclusions As climate change progresses, the days with unstable weather pattern are likely to increase. Parents and caregivers of children should be aware of the high risk of pneumonia posed by big TCN and take precautionary measures to protect children, especially those with a history of respiratory diseases, from climate impacts.
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Effective response by government and individuals to the risk of land degradation requires an understanding of regional climate variations and the impacts of climate and management on condition and productivity of land and vegetation resources. Analysis of past land degradation and climate variability provides some understanding of vulnerability to current and future climate changes and the information needs for more sustainable management. We describe experience in providing climate risk assessment information for managing for the risk of land degradation in north-eastern Australian arid and semi-arid regions used for extensive grazing. However, we note that information based on historical climate variability, which has been relied on in the past, will now also have to factor in the influence of human-induced climate change. Examples illustrate trends in climate for Australia over the past decade and the impacts on indicators of resource condition. The analysis highlights the benefits of insights into past trends and variability in rainfall and other climate variables based on extended historic databases. This understanding in turn supports more reliable regional climate projections and decision support information for governments and land managers to better manage the risk of land degradation now and in the future.