171 resultados para ENERGY ANALYSIS
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Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n 5 14 260), velocity of sound (VOS; n 5 15 514) and BMD (n 5 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n 5 11 452) and new genotyping in 15 cohorts (de novo n 5 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 3 108) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 3 1014). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 3 106 also had the expected direction of association with any fracture (P < 0.05), including threeSNPswithP < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, thisGWAstudy reveals the effect of several genescommon to central DXA-derivedBMDand heel ultrasound/DXAmeasures and points to anewgenetic locus with potential implications for better understanding of osteoporosis pathophysiology.
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This paper evaluates and compares the system performance of a solar desiccant-evaporative cooling (SDEC) system with a referenced conventional variable air volume (VAV) system for a typical office building in all 8 Australian capital cities. A simulation model of the building is developed using the whole building simulation software EnergyPlus. The performance indicators for the comparison are system coefficient of performance (COP), annual primary energy consumption, annual energy savings, and annual CO2 emissions reduction. The simulation results show that Darwin has the most apparent advantages for SDEC system applications with an annual energy savings of 557 GJ and CO2 emission reduction of 121 tonnes. The maximum system COP is 7. For other climate zones such as Canberra, Hobart and Melbourne, the SDEC system is not as energy efficient as the conventional VAV system.
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Background Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown. Aim To identify genetic variants associated with forearm BMD and forearm fractures. Methods BMD at distal radius, measured by dualenergy x-ray absorptiometry, was tested for association with common genetic variants. We conducted a metaanalysis of genome-wide association studies for BMD in 5866 subjects of European descent and then selected the variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-nucleotide polymorphism (SNP) association test. We then tested the BMD-associated SNPs for association with forearm fracture in 2023 cases and 3740 controls. Results We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (p<5×10-8) in meta-analysis (lead SNP, rs11951031[T] -0.20 SDs per allele, p=9.01×10-9). The gene-based association test suggested an association between MEF2C and forearm BMD ( p=0.003). The association between MEF2C variants and risk of fracture did not achieve statistical significance (SNP rs12521522[A]: OR=1.14 (95% CI 0.92 to 1.35), p=0.14). Meta-analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2. Conclusions These findings demonstrate that variants at MEF2C were associated with forearm BMD, implicating this gene in the determination of BMD at forearm.
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OBJECTIVES: There is controversy in the literature regarding the effect of inflammatory bowel disease (IBD) on resting energy expenditure (REE). In many cases this may have resulted from inappropriate adjustment of REE measurements to account for differences in body composition. This article considers how to appropriately adjust measurements of REE for differences in body composition between individuals with IBD. PATIENTS AND METHODS: Body composition, assessed via total body potassium to yield a measure of body cell mass (BCM), and REE measurements were performed in 41 children with Crohn disease and ulcerative colitis in the Royal Children's Hospital, Brisbane, Australia. Log-log regression was used to determine the power function to which BCM should be raised to appropriately adjust REE to account for differences in body composition between children. RESULTS: The appropriate value to "adjust" BCM was found to be 0.49, with a standard error of 0.10. CONCLUSIONS: Clearly, there is a need to adjust for differences in body composition, or at the very least body weight, in metabolic studies in children with IBD. We suggest that raising BCM to the power of 0.5 is both a numerically convenient and a statistically valid way of achieving this aim. Under circumstances in which the measurement of BCM is not available, raising body weight to the power of 0.5 remains appropriate. The important issue of whether REE is changed in cases of IBD can then be appropriately addressed. © 2007 Lippincott Williams & Wilkins, Inc.
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Background: A knowledge of energy expenditure in infancy is required for the estimation of recommended daily amounts of food energy, for designing artificial infant feeds, and as a reference standard for studies of energy metabolism in disease states. Objectives: The objectives of this study were to construct centile reference charts for total energy expenditure (TEE) in infants across the first year of life. Methods: Repeated measures of TEE using the doubly labeled water technique were made in 162 infants at 1.5, 3, 6, 9 and 12 months. In total, 322 TEE measurements were obtained. The LMS method with maximum penalized likelihood was used to construct the centile reference charts. Centiles were constructed for TEE expressed as MJ/day and also expressed relative to body weight (BW) and fat-free mass (FFM). Results: TEE increased with age and was 1.40,1.86, 2.64, 3.07 and 3.65 MJ/day at 1.5, 3, 6, 9 and 12 months, respectively. The standard deviations were 0.43, 0.47, 0.52,0.66 and 0.88, respectively. TEE in MJ/kg increased from 0.29 to 0.36 and in MJ/day/kg FFM from 0.36 to 0.48. Conclusions: We have presented centile reference charts for TEE expressed as MJ/day and expressed relative to BW and FFM in infants across the first year of life. There was a wide variation or biological scatter in TEE values seen at all ages. We suggest that these centile charts may be used to assess and possibly quantify abnormal energy metabolism in disease states in infants.
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Background: Better understanding of body composition and energy metabolism in pediatric liver disease may provide a scientific basis for improved medical therapy aimed at achieving optimal nutrition, slowing progression to end-stage liver disease (ESLD), and improving the outcome of liver transplantation. Methods: Twenty-one children less than 2 years of age with ESLD awaiting liver transplantation and 15 healthy, aged-matched controls had body compartment analysis using a four compartment model (body cell mass, fat mass, extracellular water, and extracellular solids). Subjects also had measurements of resting energy expenditure (REE) and respiratory quotient (RQ) by indirect calorimetry. Nine patients and 15 control subjects also had measurements of total energy expenditure (TEE) using doubly labelled water. Results: Mean weights and heights were similar in the two groups. Compared with control subjects, children with ESLD had higher relative mean body cell mass (33 ± 2% vs 29 ± 1% of body weight, P < 0.05), but had similar fat mass, extracellular water, and extracellular solid compartments (18% vs 20%, 41% vs 38%, and 7% vs 13% of body weight respectively). Compared with control subjects, children with ESLD had 27% higher mean REE/body weight (0.285 ± 0.013 vs 0.218. ± 0.013 mJ/kg/24h, P < 0.001), 16% higher REE/unit cell mass (P < 0.05); and lower mean RQ (P < 0.05). Mean TEE of patients was 4.70 ± 0.49 mJ/24h vs 3.19 ± 0.76 in controls, (P < 0.01). Conclusions: In children, ESLD is a hypermetabolic state adversely affecting the relationship between metabolic and non-metabolic body compartments. There is increased metabolic activity within the body cell mass with excess lipid oxidation during fasting and at rest. These findings have implications for the design of appropriate nutritional therapy.
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Background and Aims: The objective of the study was to compare data obtained from the Cosmed K4 b2 and the Deltatrac II™ metabolic cart for the purpose of determining the validity of the Cosmed K4 b2 in measuring resting energy expenditure. Methods: Nine adult subjects (four male, five female) were measured. Resting energy expenditure was measured in consecutive sessions using the Cosmed K4 b2, the Deltatrac II™ metabolic cart separately and the Cosmed K4 b2 and Deltatrac II™ metabolic cart simultaneously, performed in random order. Resting energy expenditure (REE) data from both devices were then compared with values obtained from predictive equations. Results: Bland and Altman analysis revealed a mean bias for the four variables, REE, respiratory quotient (RQ), VCO2, VO2 between data obtained from Cosmed K4 b2 and Deltatrac II™ metabolic cart of 268 ± 702 kcal/day, -0.0±0.2, 26.4±118.2 and 51.6±126.5 ml/min, respectively. Corresponding limits of agreement for the same four variables were all large. Also, Bland and Altman analysis revealed a larger mean bias between predicted REE and measured REE using Cosmed K4 b2 data (-194±603 kcal/day) than using Deltatrac™ metabolic cart data (73±197 kcal/day). Conclusions: Variability between the two devices was very high and a degree of measurement error was detected. Data from the Cosmed K4 b2 provided variable results on comparison with predicted values, thus, would seem an invalid device for measuring adults. © 2002 Elsevier Science Ltd. All rights reserved.
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The purpose of this study is to examine the changes of energy cost during a high-heeled continuous jogging.Thirteen healthy female volunteers jointed in this study with heel height of the shoes varied from 1, 4.5 and 7 cm, respectively. Each subjects jogged on the treadmill with K4b2 portable gas analysis system. The results of this study showed that ventilnation, relative oxygen consumption and energy expenditure increased with the increase of heel height and these values shows significantly larger when the heel height reached to 7 cm. Present study suggest that wearing high heel shoes jogging could directly increase energy consumption, causing neuromuscular fatigue.
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Background Several approaches have been used to express energy expenditure in youth, but no consensus exists as to which best normalizes data for the wide range of ages and body sizes across a range of physical activities. This study examined several common metrics for expressing energy expenditure to determine whether one metric can be used for all healthy children. Such a metric could improve our ability to further advance the Compendium of Physical Activities for Youth. Methods A secondary analysis of oxygen uptake (VO2) data obtained from five sites was completed, that included 947 children ages 5 to 18 years, who engaged in 14 different activities. Resting metabolic rate (RMR) was computed based on Schofield Equations [Hum Nutr Clin Nut. 39(Suppl 1), 1985]. Absolute oxygen uptake (ml.min-1), oxygen uptake per kilogram body mass (VO2 in ml.kg-1.min-1), net oxygen uptake (VO2 – resting metabolic rate), allometric scaled oxygen uptake (VO2 in ml.kg-0.75.min-1) and YOUTH-MET (VO2.[resting VO2] -1) were calculated. These metrics were regressed with age, sex, height, and body mass. Results Net and allometric-scaled VO2, and YOUTH-MET were least associated with age, sex and physical characteristics. For moderate-to-vigorous intensity activities, allometric scaling was least related to age and sex. For sedentary and low-intensity activities, YOUTH-MET was least related to age and sex. Conclusions No energy expenditure metric completely eliminated the influence of age, physical characteristics, and sex. The Adult MET consistently overestimated EE. YOUTH-MET was better for expressing energy expenditure for sedentary and light activities, whereas allometric scaling was better for moderate and vigorous intensity activities. From a practical perspective, The YOUTH-MET may be the more feasible metric for improving of the Compendium of Physical Activities for Youth.
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Aims We combine measurements of weak gravitational lensing from the CFHTLS-Wide survey, supernovae Ia from CFHT SNLS and CMB anisotropies from WMAP5 to obtain joint constraints on cosmological parameters, in particular, the dark-energy equation-of-state parameter w. We assess the influence of systematics in the data on the results and look for possible correlations with cosmological parameters. Methods We implemented an MCMC algorithm to sample the parameter space of a flat CDM model with a dark-energy component of constant w. Systematics in the data are parametrised and included in the analysis. We determine the influence of photometric calibration of SNIa data on cosmological results by calculating the response of the distance modulus to photometric zero-point variations. The weak lensing data set is tested for anomalous field-to-field variations and a systematic shape measurement bias for high-redshift galaxies. Results Ignoring photometric uncertainties for SNLS biases cosmological parameters by at most 20% of the statistical errors, using supernovae alone; the parameter uncertainties are underestimated by 10%. The weak-lensing field-to-field variance between 1 deg2-MegaCam pointings is 5-15% higher than predicted from N-body simulations. We find no bias in the lensing signal at high redshift, within the framework of a simple model, and marginalising over cosmological parameters. Assuming a systematic underestimation of the lensing signal, the normalisation increases by up to 8%. Combining all three probes we obtain -0.10 < 1 + w < 0.06 at 68% confidence ( -0.18 < 1 + w < 0.12 at 95%), including systematic errors. Our results are therefore consistent with the cosmological constant . Systematics in the data increase the error bars by up to 35%; the best-fit values change by less than 0.15.
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Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.
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Purpose Energy is a resource of strategic importance for high density cities. International trade reshapes the urban economy and industrial structure of a city, which will indirectly affect energy use. As an international trade hub, Hong Kong relies on the import and export of services. Energy performance in the international trading of these services needs to be properly understood and assessed for Hong Kong’s urban renewal efforts. Design/methodology/approach This study evaluates Hong Kong’s embodied energy in service trades based on an input-output analysis. The three criteria used for assessment include trading areas, industry sector, and trade balance. Findings Analyzed by region, results show that Mainland China and the USA are the two largest sources of embodied energy in imports of services, while Mainland China and Japan are the two largest destinations of exports. In terms of net embodied energy transfer, Hong Kong mainly receives net energy import from Mainland China and the USA and supplies net energy export to Japan, the UK and Taiwan. Among industry sectors, Manufacturing services, Transport and Travel contribute most significantly to the embodied energy in Hong Kong’s imported services, while Transport and Travel contribute most to the energy embodied in exported services. Originality/value This study identifies the characteristics of energy consumption of service trading and establishes a feasible approach to analyze energy performance of service trade in energy-deficient Hong Kong for the first time. It provides necessary understanding and foundation for developing energy strategies in a service-based, high density urban economy.
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In this paper, we describe our investigation of the cointegration and causal relationships between energy consumption and economic output in Australia over a period of five decades. The framework used in this paper is the single-sector aggregate production function, which is the first comprehensive approach used in an Australian study of this type to include energy, capital and labour as separate inputs of production. The empirical evidence points to a cointegration relationship between energy and output and implies that energy is an important variable in the cointegration space, as are conventional inputs capital and labour. We also find some evidence of bidirectional causality between GDP and energy use. Although the evidence of causality from energy use to GDP was relatively weak when using the thermal aggregate of energy use, once energy consumption was adjusted for energy quality, we found strong evidence of Granger causality from energy use to GDP in Australia over the investigated period. The results are robust, irrespective of the assumptions of linear trends in the cointegration models, and are applicable for different econometric approaches.
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This paper provides an empirical estimation of energy efficiency and other proximate factors that explain energy intensity in Australia for the period 1978-2009. The analysis is performed by decomposing the changes in energy intensity by means of energy efficiency, fuel mix and structural changes using sectoral and sub-sectoral levels of data. The results show that the driving forces behind the decrease in energy intensity in Australia are efficiency effect and sectoral composition effect, where the former is found to be more prominent than the latter. Moreover, the favourable impact of the composition effect has slowed consistently in recent years. A perfect positive association characterizes the relationship between energy intensity and carbon intensity in Australia. The decomposition results indicate that Australia needs to improve energy efficiency further to reduce energy intensity and carbon emissions. © 2012 Elsevier Ltd.
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Changes in energy-related CO2 emissions aggregate intensity, total CO2 emissions and per-capita CO2 emissions in Australia are decomposed by using a Logarithmic Mean Divisia Index (LMDI) method for the period 1978-2010. Results indicate improvements in energy efficiency played a dominant role in the measured 17% reduction in CO2 emissions aggregate intensity in Australia over the period. Structural changes in the economy, such as changes in the relative importance of the services sector vis-à-vis manufacturing, have also played a major role in achieving this outcome. Results also suggest that, without these mitigating factors, income per capita and population effects could well have produced an increase in total emissions of more than 50% higher than actually occurred over the period. Perhaps most starkly, the results indicate that, without these mitigating factors, the growth in CO2 emissions per capita could have been over 150% higher than actually observed. Notwithstanding this, the study suggests that, for Australia to meet its Copenhagen commitment, the relative average per annum effectiveness of these mitigating factors during 2010-2020 probably needs to be almost three times what it was in the 2005-2010 period-a very daunting challenge indeed for Australia's policymakers.