972 resultados para Energy Requirements


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Poor nutritional status in patients with cystic fibrosis (CF) is associated with severe lung disease, and possible causative factors include inadequate intake, malabsorption, and increased energy requirements. Body cell mass (which can be quantified by measurement of total body potassium) provides an ideal standard for measurements of energy expenditure. The aim of this study was to compare resting energy expenditure (REE) in patients with CF with both predicted values and age-matched healthy children and to determine whether REE was related to either nutritional status or pulmonary function. REE was measured by indirect calorimetry and body cell mass by scanning with total body potassium in 30 patients with CF (12 male, mean age = 13.07 ± 0.55 y) and 18 healthy children (six male, mean age = 12.56 ± 1.25 y). Nutritional status was expressed as a percentage of predicted total body potassium. Lung function was measured in the CF group by spirometry and expressed as the percentage of predicted forced expiratory volume in 1 s. Mean REE was significantly increased in the patients with CF compared with healthy children (119.3 ± 3.1% predicted versus 103.6 ± 5% predicted, P < 0.001) and, using multiple regression techniques, REE for total body potassium was significantly increased in patients with CF (P = 0.0001). There was no relation between REE and nutritional status or pulmonary disease status in the CF group. In conclusion, REE is increased in children and adolescents with CF but is not directly related to nutritional status or pulmonary disease.

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The food sources of the leptocephali of the teleostean superorder Elopomorpha have been controversial, yet observations on the leptocephali of the worm eels, Myrophis spp. (family Ophichthidae) collected in the northern Gulf of Mexico indicate active, not passive, feeding. Leptocephali had protists in their alimentary canals. Estimates of the physiological energetics of worm eels indicate that large aloricate protozoa including ciliates could provide substantial energy to these leptocephali toward the end of the premetamorphic and metamorphic stages, given the low energy requirements of metamorphosing leptocephali. Global ocean warming will likely force a shift in oceanic food webs; a shift away from large protozoa toward smaller protists is possible. Such a disruption of the oceanic food webs could further compromise the survival of leptocephali.

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In this paper, we review the energy requirements to make materials on a global scale by focusing on the five construction materials that dominate energy used in material production: steel, cement, paper, plastics and aluminium. We then estimate the possibility of reducing absolute material production energy by half, while doubling production from the present to 2050. The goal therefore is a 75 per cent reduction in energy intensity. Four technology-based strategies are investigated, regardless of cost: (i) widespread application of best available technology (BAT), (ii) BAT to cutting-edge technologies, (iii) aggressive recycling and finally, and (iv) significant improvements in recycling technologies. Taken together, these aggressive strategies could produce impressive gains, of the order of a 50-56 per cent reduction in energy intensity, but this is still short of our goal of a 75 per cent reduction. Ultimately, we face fundamental thermodynamic as well as practical constraints on our ability to improve the energy intensity of material production. A strategy to reduce demand by providing material services with less material (called 'material efficiency') is outlined as an approach to solving this dilemma.

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Winter is energetically challenging for small herbivores because of greater energy requirements for thermogenesis at a time when little energy is available. We formulated a model predicting optimal wintering body size, accounting for the scaling of both energy expenditure and assimilation to body size, and the trade-off between survival benefits of a large size and avoiding survival costs of foraging. The model predicts that if the energy cost of maintaining a given body mass differs between environments, animals should be smaller in the more demanding environments, and there should be a negative correlation between body mass and daily energy expenditure (DEE) across environments. In contrast, if animals adjust their energy intake according to variation in survival costs of foraging, there should be a positive correlation between body mass and DEE. Decreasing temperature always increases equilibrium DEE, but optimal body mass may either increase or decrease in colder climates depending on the exact effects of temperature on mass-specific survival and energy demands. Measuring DEE with doubly labeled water on wintering Microtus agrestis at four field sites, we found that DEE was highest at the sites where voles were smallest despite a positive correlation between DEE and body mass within sites. This suggests that variation in wintering body mass between sites was due to variation in food quality/availability and not adjustments in foraging activity to varying risks of predation.

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Background & aims: Little is known about energy requirements in brain injured (TBI) patients, despite evidence suggesting adequate nutritional support can improve clinical outcomes. The study aim was to compare predicted energy requirements with measured resting energy expenditure (REE) values, in patients recovering from TBI.

Methods: Indirect calorimetry (IC) was used to measure REE in 45 patients with TBI. Predicted energy requirements were determined using FAO/WHO/UNU and Harris–Benedict (HB) equations. Bland– Altman and regression analysis were used for analysis.

Results: One-hundred and sixty-seven successful measurements were recorded in patients with TBI. At an individual level, both equations predicted REE poorly. The mean of the differences of standardised areas of measured REE and FAO/WHO/UNU was near zero (9 kcal) but the variation in both directions was substantial (range 591 to þ573 kcal). Similarly, the differences of areas of measured REE and HB demonstrated a mean of 1.9 kcal and range 568 to þ571 kcal. Glasgow coma score, patient status, weight and body temperature were signi?cant predictors of measured REE (p < 0.001; R2= 0.47).

Conclusions: Clinical equations are poor predictors of measured REE in patients with TBI. The variability in REE is substantial. Clinicians should be aware of the limitations of prediction equations when estimating energy requirements in TBI patients.

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Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

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Energy balance is the difference between metabolizable energy intake and total energy expenditure. Energy intake is difficult to measure accurately; changes in body weight, for example, are not a good measure of the adequacy of energy intake, because fluctuations in body weight are common even if the overall trend is toward weight loss. It is now customary to assess energy requirements indirectly from total energy expenditure. Total energy expenditure consists of basal metabolism, postprandial thermogenesis, and physical activity. Energy expenditure is related to both body weight and body composition. A reduction in total energy expenditure accompanies weight loss, because basal metabolic rate decreases with the loss of lean tissue mass. Similarly, with weight gain, there is an increase in basal metabolic rate, because lean tissue mass grows to support the increase in fat tissue mass. Excess energy intake over energy expenditure causes weight gain and an accompanying increase in total energy expenditure. Following a period of adaptation, total energy expenditure will match energy intake and body weight will stabilize at a higher level. This same relationship holds for weight loss. Respiratory quotient (measured in steady state) is an indication of the proportion of energy expenditure derived from fat and carbohydrate oxidation. Over long periods of time, fat balance is equivalent to energy balance, as an excess of fat intake over fat oxidation causes fat storage.

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Clustering combined with multihop communication is a promising solution to cope with the energy requirements of large scale Wireless Sensor Networks. In this work, a new cluster based routing protocol referred to as Energy Aware Cluster-based Multihop (EACM) Routing Protocol is introduced, with multihop communication between cluster heads for transmitting messages to the base station and direct communication within clusters. We propose EACM with both static and dynamic clustering. The network is partitioned into near optimal load balanced clusters by using a voting technique, which ensures that the suitability of a node to become a cluster head is determined by all its neighbors. Results show that the new protocol performs better than LEACH on network lifetime and energy dissipation

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The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

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Wild bird feeding is popular in domestic gardens across the world. Nevertheless, there is surprisingly little empirical information on certain aspects of the activity and no year-round quantitative records of the amounts and nature of the different foods provided in individual gardens. We sought to characterise garden bird feeding in a large UK urban area in two ways. First, we conducted face-to-face questionnaires with a representative cross-section of residents. Just over half fed birds, the majority doing so year round and at least weekly. Second, a two-year study recorded all foodstuffs put out by households on every provisioning occasion. A median of 628 kcal/garden/day was given. Provisioning level was not significantly influenced by weather or season. Comparisons between the data sets revealed significantly less frequent feeding amongst these ‘keen’ feeders than the face-to-face questionnaire respondents, suggesting that one-off questionnaires may overestimate provisioning frequency. Assuming 100% uptake, the median provisioning level equates to sufficient supplementary resources across the UK to support 196 million individuals of a hypothetical average garden-feeding bird species (based on 10 common UK garden-feeding birds’ energy requirements). Taking the lowest provisioning level recorded (101 kcal/day) as a conservative measure, 31 million of these average individuals could theoretically be supported.

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The process of host cell invasion by Trypanosoma cruzi depends on parasite energy. What source of energy is used for that event is not known. To address this and other questions related to T. cruzi energy requirements and cell invasion, we analyzed metacyclic trypomastigote forms of the phylogenetically distant CL and G strains. For both strains, the nutritional stress experienced by cells starved for 24, 36, or 48 h in phosphate-buffered saline reduced the ATP content and the ability of the parasite to invade HeLa cells proportionally to the starvation time. Inhibition of ATP production by treating parasites with rotenone plus antimycin A also diminished the infectivity. Nutrient depletion did not alter the expression of gp82, the surface molecule that mediates CL strain internalization, but increased the expression of gp90, the negative regulator of cell invasion, in the G strain. When L-proline was given to metacyclic forms starved for 36 h, the ATP levels were restored to those of nonstarved controls for both strains. Glucose had no such effect, although this carbohydrate and L-proline were transported in similar fashions. Recovery of infectivity promoted by L-proline treatment of starved parasites was restricted to the CL strain. The profile of restoration of ATP content and gp82-mediated invasion capacity by L-proline treatment of starved Y-strain parasites was similar to that of the CL strain, whereas the Dm28 and Dm30 strains, whose infectivity is downregulated by gp90, behaved like the G strain. L-Proline was also found to increase the ability of the CL strain to traverse a gastric mucin layer, a property important for the establishment of T. cruzi infection by the oral route. Efficient translocation of parasites through gastric mucin toward the target epithelial cells in the stomach mucosa is an essential requirement for subsequent cell invasion. By relying on these closely associated ATP-driven processes, the metacyclic trypomastigotes effectively accomplish their internalization.

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Embodied energy (EE) analysis has become an important area of energy research, in attempting to trace the direct and indirect energy requirements of products and services throughout their supply chain. Typically, input-output (I-O) models have been used to calculate EE because they are considered to be comprehensive in their analysis. However, a major deficiency of using I-O models is that they have inherent errors and therefore cannot be reliably applied to individual cases. Thus, there is a need for the ability to disaggregate an I-O model into its most important 'energy paths', for the purpose of integrating case-specific data. This paper presents a new hybrid method for conducting EE analyses for individual buildings, which retains the completeness of the I-O model. This new method is demonstrated by application to an Australian residential building. Only 52% of the energy paths derived from the I-O model were substituted using case-specific data. This indicates that previous system boundaries for EE studies of individual residential buildings are less than optimal. It is envisaged that the proposed method will provide construction professionals with more accurate and reliable data for conducting life cycle energy analysis of buildings. Furthermore, by analysing the unmodified energy paths, further data collection can be prioritized effectively.

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There are 3 distinct yet closely integrated processes that operate together to satisfy the energy requirements of muscle. The anaerobic energy system is divided into alactic and lactic components, referring to the processes  involved in the splitting of the stored phosphagens, ATP and  phosphocreatine (PCr), and the nonaerobic breakdown of carbohydrate to lactic acid through glycolysis. The aerobic energy system refers to the combustion of carbohydrates and fats in the presence of oxygen. The anaerobic pathways are capable of regenerating ATP at high rates yet are limited by the amount of energy that can be released in a single bout of intense exercise. In contrast, the aerobic system has an enormous capacity yet is somewhat hampered in its ability to delivery energy quickly. The focus of this review is on the interaction and relative contribution of the energy systems during single bouts of maximal exercise. A particular emphasis has been placed on the role of the aerobic energy system during high intensity exercise.

Attempts to depict the interaction and relative contribution of the energy systems during maximal exercise first appeared in the 1960s and 1970s. While insightful at the time, these representations were based on calculations of anaerobic energy release that now appear questionable. Given repeated reproduction over the years, these early attempts have lead to 2 common misconceptions in the exercise science and coaching professions. First, that the energy systems respond to the demands of intense exercise in an almost sequential manner, and secondly, that the aerobic system responds slowly to these energy demands, thereby playing little role in determining performance over short durations. More recent research suggests that energy is derived from each of the energy-producing pathways during almost all exercise activities. The duration of maximal exercise at which equal contributions are derived from the anaerobic and aerobic energy systems appears to occur between 1 to 2 minutes and most probably around 75 seconds, a time that is considerably earlier than has traditionally been suggested.

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Energy efficient design principles and the minimisation of operational energy requirements have been demonstrated in the refurbishment of a small existing residential building. Significant thought has been given to these areas, together with an emphasis on the minimisation of resource consumption and material wastage. However, less consideration has been given to the embodied energy of the additional materials, components and systems required to meet these aims. The additional embodied energy may reduce the advantages of minimising the operational energy consumption by extending the energy payback period beyond the life of the building. In general, the embodied energy of buildings and their products has been found to be significant, when national average input-output data is used to fill gaps in traditional life-cycle assessment inventories. Through the use of an input-outputbased hybrid embodied energy analysis, the embodied energy of this refurbished building has increased by 63% compared to the existing building, showing the impact that filling the gaps in traditional inventories can have on energy payback periods.

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It is commonly assumed that solar hot water systems save energy and reduce greenhouse gas emissions. Very rarely has the life-cycle energy requirements of solar hot water systems been analysed, including their embodied energy. The extent to which solar hot water systems save energy compared to conventional systems in Melbourne, Australia, is shown through a comparative net energy analysis. The solar systems provided a net energy saving compared to the conventional systems after 0.5 to 2 years, for electricity and gas systems respectively.