954 resultados para Electric load forecasting
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Dietary acid load from Western diets may be a risk factor for osteoporosis. It can be estimated by net endogenous acid production (NEAP). No data currently exists for NEAP estimates and bone indices in the very elderly (i.e. > or = 75 y). The aim of this study was to determine the association between NEAP estimates by using the potential renal acid load (PRAL) equation and quantitative bone ultrasound (QUS) measurements at the heel [broadband ultrasound attenuation (BUA)] in Caucasian women. We assessed NEAP and QUS in 401 very elderly Swiss ambulatory women. We evaluated dietary intake and NEAP estimates with a validated FFQ. QUS was measured using Achilles (Lunar). We identified 2 subgroups: 256 women (80.6 y +/- 3; BUA, 96.8 dB/MHz) with a fracture history and the remaining 145 (79.9 y SD 2.9; BUA, 101.7 dB/MHz) without. Women who reported having suffered a fracture had lower BUA (P < 0.001) than nonfractured women but did not differ in nutrient intakes and NEAP. Lower NEAP (P = 0.023) and higher potassium intake (P = 0.033) were correlated with higher BUA, which remained significant even after adjustment for age, BMI, and osteoporosis treatment. BUA was positively correlated with calcium (P = 0.016) and BMI (P < 0.001). Women who reported no fractures had no significant correlations between nutrient intake, NEAP, and BUA. Low nutritional acid load was correlated with higher BUA in very elderly women with a fracture history. Although relatively weak compared with age and BMI, this association was significant and may be an important additional risk factor that might be particularly relevant in frail patients with an already high fracture risk.
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City Audit Report - Reaudit
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Amino acids stimulate the release of glucagon and insulin. To assess the role of aminogenic hyperglucagonemia, we have studied, in healthy young males, the effects of basal (less than 100 pg/ml) and high (200-400 pg/ml) plasma glucagon concentrations on amino acid metabolism during intravenous infusion (0.5 g.h-1.4 h) of a mixture of 15 amino acids. Basal plasma glucagon concentrations were obtained by infusion of somatostatin (0.5 mg/h) plus glucagon (0.25 ng.kg-1.min-1) and high plasma glucagon concentrations by infusion of somatostatin plus glucagon (3.0 ng.kg-1.min-1) or by infusion of amino acids alone. All studies were performed under conditions of euglycemic (83-91 mg/dl) hyperinsulinemia (50-80 microU/ml). Hyperglucagonemia significantly increased 1) net amino acid transport from the extracellular into the intracellular space (by approximately 4%), 2) net degradation of amino acids entering the intracellular space (by approximately 40%), and 3) conversion of degraded amino acids into glucose from 0-10% (basal glucagon) to 70-100% (high glucagon). Hyperglucagonemia did not affect the amount of amino acids excreted in the urine (approximately 4%). We conclude that glucagon plays an important role in the disposition of amino acids by increasing their inward transport, their degradation, and their conversion into glucose.
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OBJECTIVES: (1) To evaluate the changes in surface roughness and gloss after simulated toothbrushing of 9 composite materials and 2 ceramic materials in relation to brushing time and load in vitro; (2) to assess the relationship between surface gloss and surface roughness. METHODS: Eight flat specimens of composite materials (microfilled: Adoro, Filtek Supreme, Heliomolar; microhybrid: Four Seasons, Tetric EvoCeram; hybrid: Compoglass F, Targis, Tetric Ceram; macrohybrid: Grandio), two ceramic materials (IPS d.SIGN and IPS Empress polished) were fabricated according to the manufacturer's instructions and optimally polished with up to 4000 grit SiC. The specimens were subjected to a toothbrushing (TB) simulation device (Willytec) with rotating movements, toothpaste slurry and at three different loads (100g/250g/350g). At hourly intervals from 1h to 10h TB, mean surface roughness Ra was measured with an optical sensor and the surface gloss (Gl) with a glossmeter. Statistical analysis was performed for log-transformed Ra data applying two-way ANOVA to evaluate the interaction between load and material and load and brushing time. RESULTS: There was a significant interaction between material and load as well as between load and brushing time (p<0.0001). The microhybrid and hybrid materials demonstrated more surface deterioration with higher loads, whereas with the microfilled resins Heliomolar and Adoro it was vice versa. For ceramic materials, no or little deterioration was observed over time and independent of the load. The ceramic materials and 3 of the composite materials (roughness) showed no further deterioration after 5h of toothbrushing. Mean surface gloss was the parameter which discriminated best between the materials, followed by mean surface roughness Ra. There was a strong correlation between surface gloss and surface roughness for all the materials except the ceramics. The evaluation of the deterioration curves of individual specimens revealed a more or less synchronous course suspecting hinting specific external conditions and not showing the true variability in relation to the tested material. SIGNIFICANCE: The surface roughness and gloss of dental materials changes with brushing time and load and thus results in different material rankings. Apart from Grandio, the hybrid composite resins were more prone to surface changes than microfilled composites. The deterioration potential of a composite material can be quickly assessed by measuring surface gloss. For this purpose, a brushing time of 10h (=72,000 strokes) is needed. In further comparative studies, specimens of different materials should be tested in one series to estimate the true variability.
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To investigate the effect of age and change in body composition on the increase in energy expenditure consecutive to the ingestion of a 75-g glucose load, respiratory exchange measurements were performed on 24 subjects, 12 elderly (mean +/- SEM, 73 +/- 1 yr) and 12 young (25 +/- 1 yr). The body weight was comparable, 62 +/- 2 kg in the elderly group vs 61 +/- 3 in the young, but the body fat content of the elderly group was significantly greater than that of the young (29 +/- 2% vs 19 +/- 2%, p less than 0.001). The elderly group presented a slight glucose intolerance according to the World Health Organization (WHO) criteria, with a 120-min plasma glucose of 149 +/- 9 mg/dl (p less than 0.005 vs young). The postabsorptive resting energy expenditure (REE) was 0.83 +/- 0.03 kcal/min in the elderly group vs 0.98 +/- 0.04 in the young (p less than 0.02); this decrease of 15% was mainly related to the decrease in fat free mass (FFM) in the elderly group, which averaged 14%. The difference was not significant when REE was expressed per kg FFM. The glucose-induced thermogenesis (GIT) expressed as percent of energy content of the load was 6.2 +/- 0.6% in the elderly group and 8.9 +/- 0.9% in the young (p less than 0.05). It is concluded that the glucose-induced thermogenesis is decreased in elderly subjects. However, when expressed per kg FFM, the increment in energy expenditure (EE), in response to the glucose load, is not different in elderly subjects, suggesting that the decrease of thermogenesis may be attributed to the age-related decrease in FFM.
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Latin America participated in the electric revolution which profoundly transformed the most developed Western economies between 1880 and 1930. The electrification of Latin America began relatively soon after these economies, but it was incapable of keeping up with them. Public electric lighting was introduced early in the big Latin American cities, where electric trams started running at almost the same time as in Europe, and electricity spread rapidly in the mining sector. In the most advanced countries or areas in the region, the manufacturing industry substituted the steam engine with the electric motor, following the example of industry in the United States and Europe. Nevertheless, towards 1930 electricity consumption per inhabitant for Latin America was far below that of the more advanced economies, and only the Latin American countries which lead the process of electrification had reached levels of electric consumption that were similar to those of the late industrialised European countries. One of the most striking features of the electric revolution in Latin America is rooted precisely in the enormous national differences. These differences are indicative of the great economic inequalities existing in the heart of the region and these nations highly diverse capacity for economic modernisation.
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BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package
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BACKGROUND: To test the inflammatory origin of cardiovascular disease, as opposed to its origin in western lifestyle. Population-based assessment of the prevalences of cardiovascular risk factors and cardiovascular disease in an inflammation-prone African population, including electrocardiography and ankle-arm index measurement. Comparison with known prevalences in American and European societies. METHODOLOGY/PRINCIPAL FINDINGS: Traditional population in rural Ghana, characterised by adverse environmental conditions and a high infectious load. Population-based sample of 924 individuals aged 50 years and older. Median values for cardiovascular risk factors, including waist circumference, BMI, blood pressure, and markers of glucose and lipid metabolism and inflammation. Prevalence of myocardial infarction detected by electrocardiography and prevalence of peripheral arterial disease detected by ankle-arm index. When compared to western societies, we found the Ghanaians to have more proinflammatory profiles and less cardiovascular risk factors, including obesity, dysglycaemia, dyslipidaemia, and hypertension. Prevalences of cardiovascular disease were also lower. Definite myocardial infarction was present in 1.2% (95%CI: 0.6 to 2.4%). Peripheral arterial disease was present in 2.8% (95%CI: 1.9 to 4.1%). CONCLUSIONS/SIGNIFICANCE: Taken together, our data indicate that for the pathogenesis of cardiovascular disease inflammatory processes alone do not suffice and additional factors, probably lifestyle-related, are mandatory.
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We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.
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This paper presents a comparative analysis of linear and mixed modelsfor short term forecasting of a real data series with a high percentage of missing data. Data are the series of significant wave heights registered at regular periods of three hours by a buoy placed in the Bay of Biscay.The series is interpolated with a linear predictor which minimizes theforecast mean square error. The linear models are seasonal ARIMA models and themixed models have a linear component and a non linear seasonal component.The non linear component is estimated by a non parametric regression of dataversus time. Short term forecasts, no more than two days ahead, are of interestbecause they can be used by the port authorities to notice the fleet.Several models are fitted and compared by their forecasting behavior.
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Species' geographic ranges are usually considered as basic units in macroecology and biogeography, yet it is still difficult to measure them accurately for many reasons. About 20 years ago, researchers started using local data on species' occurrences to estimate broad scale ranges, thereby establishing the niche modeling approach. However, there are still many problems in model evaluation and application, and one of the solutions is to find a consensus solution among models derived from different mathematical and statistical models for niche modeling, climatic projections and variable combination, all of which are sources of uncertainty during niche modeling. In this paper, we discuss this approach of ensemble forecasting and propose that it can be divided into three phases with increasing levels of complexity. Phase I is the simple combination of maps to achieve a consensual and hopefully conservative solution. In Phase II, differences among the maps used are described by multivariate analyses, and Phase III consists of the quantitative evaluation of the relative magnitude of uncertainties from different sources and their mapping. To illustrate these developments, we analyzed the occurrence data of the tiger moth, Utetheisa ornatrix (Lepidoptera, Arctiidae), a Neotropical moth species, and modeled its geographic range in current and future climates.
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Report on a special investigation of the City of Ames Electric Department for the period July 1, 2003 through January 7, 2008
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The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. in this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean-atmosphere-biosphere models, and (4) specics-area curve models that consider all species or large aggregates of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in the solution to the different problems.