20 resultados para Energy requirements

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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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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Changing energy requirements and dramatic shifts in food availability are major factors driving behaviour and distribution of herbivores. We investigate this in wintering East Canadian High Arctic light-bellied brent geese Branta bernicla hrota in Northern Ireland. They followed a sequential pattern of habitat use, feeding on intertidal Zostera spp. in autumn and early winter before moving to predominantly saltmarsh and farmland in late winter and early spring. Night-time feeding occurred throughout and made a considerable contribution to the birds' daily energy budget, at times accounting for > 50% of energy intake. Nocturnal feeding, however, is limited to the intertidal, possibly because of predation risk on terrestrial habitat, and increases with moonlight. The amount of Zostera spp., declined dramatically after the arrival of birds, predominantly, but not entirely, due to consumption by the birds. Birds gained fat reserves in the first 2 months but then this was dramatically lost as their major food source collapsed and their daily energy intake declined. Single birds consistently fared worse than paired birds and pairs with juveniles fared better than those without suggesting a benefit of having a family to compete for food. Many birds leave the Lough at this time of reduced Zostera spp. for other sea inlets in Ireland but some remain. Body condition of the latter gradually improved in early spring and reflected a heavy reliance on terrestrial habitats, particularly farmland, to meet the birds' daily energy requirements. However, even in the period immediately before migration to the breeding ground, the birds did not regain the amount of abdominal fatness observed in November. The dramatic changes in available food and requirements of the birds drive the major changes seen in foraging behaviour as the birds evade starvation in the wintering period.

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Resting metabolic rate (RMR) is a measure of the minimum energy requirements of an animal at rest, and can give an indication of the costs of somatic maintenance. We measured RMR of free-ranging European badgers (Meles meles) to determine whether differences were related to sex, age and season. Badgers were captured in live-traps and placed individually within a metabolic chamber maintained at 20 ± 1°C. Resting metabolic rate was determined using an open-circuit respirometry system. Season was significantly correlated with RMR, but no effects of age or sex were detected. Summer RMR values were significantly higher than winter values (mass-adjusted mean ± standard error: 2366 ± 70 kJ⋅d-1; 1845 ± 109 kJ⋅d-1, respectively), with the percentage difference being 24.7%. While under the influence of anaesthesia, RMR was estimated to be 25.5% lower than the combined average value before administration, and after recovery from anaesthesia. Resting metabolic rate during the autumn and winter was not significantly different to allometric predictions of basal metabolic rate for mustelid species weighing 1 kg or greater, but badgers measured in the summer had values that were higher than predicted. Results suggest that a seasonal reduction in RMR coincides with apparent reductions in physical activity and body temperature as part of the overwintering strategy ('winter lethargy') in badgers. This study contributes to an expanding dataset on the ecophysiology of medium-sized carnivores, and emphasises the importance of considering season when making predictions of metabolic rate.

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A diverse range of concentrate allocation strategies are adopted on dairy farms. The objectives of this study were to examine the effects on cow performance [dry matter (DM) intake (DMI), milk yield and composition, body tissue changes, and fertility] of adopting 2 contrasting concentrate allocation strategies over the first 140 d of lactation. Seventy-seven Holstein-Friesian dairy cows were allocated to 1 of 2 concentrate allocation strategies at calving, namely group or individual cow. Cows on the group strategy were offered a mixed ration comprising grass silage and concentrates in a 50:50 ratio on a DM basis. Cows on the individual cow strategy were offered a basal mixed ration comprising grass silage and concentrates (the latter included in the mix to achieve a mean intake of 6 kg/cow per day), which was formulated to meet the cow’s energy requirements for maintenance plus 24 kg of milk/cow per day. Additional concentrates were offered via an out-of-parlor feeding system, with the amount offered adjusted weekly based on each individual cow’s milk yield during the previous week. In addition, all cows received a small quantity of straw in the mixed ration part of the diet (approximately 0.3 kg/cow per day), plus 0.5 kg of concentrate twice daily in the milking parlor. Mean concentrate intakes over the study period were similar with each of the 2 allocation strategies (11.5 and 11.7 kg of DM/cow per day for group and individual cow, respectively), although the pattern of intake with each treatment differed over time. Concentrate allocation strategy had no effect on either milk yield (39.3 and 38.0 kg/d for group and individual cow, respectively), milk composition, or milk constituent yield. The milk yield response curves with each treatment were largely aligned with the concentrate DMI curves. Cows on the individual cow treatment had a greater range of concentrate DMI and milk yields than those on the group treatment. With the exception of a tendency for cows on the individual cow treatment to lose more body weight to nadir than cows on the group treatment, concentrate allocation strategy had little effect on either body weight or body condition score over the experimental period. Cows on the individual cow treatment had a higher pregnancy rate to first and second service and tended to have a higher 100-d in calf rate than cows on the group treatment. This study demonstrates that concentrate allocation strategy had little effect on overall production performance.

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Different reproductive strategies of males and females may lead to the evolution of differences in their energetic costs of reproduction, overall energetic requirements and physiological performances. Sexual dimorphism is often associated with costly behaviours (e.g. large males might have a competitive advantage in fighting, which is energetically expensive). However, few studies of mammals have directly compared the energy costs of reproductive activities between sexes. We compared the daily energy expenditure (DEE) and resting metabolic rate (RMR) of males and females of two species of mole-rat, Bathyergus janetta and Georychus capensis (the former is sexually dimorphic in body size and the latter is not) during a period of intense digging when males seek females. We hypothesized that large body size might be indicative of greater digging or fighting capabilities, and hence greater mass-independent DEE values in males of the sexually dimorphic species. In contrast to this prediction, although absolute values of DEE were greater in B. janetta males, mass-independent values were not. No differences were apparent between sexes in G. capensis. By comparison, although RMR values were greater in B. janetta than G. capensis, no differences were apparent between the sexes for either species. The energy cost of dimorphism is most likely to be the cost of maintenance of a large body size, and not the cost of behaviours performed when an individual is large.

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Success rates of reintroduction programs are low, often owing to a lack of knowledge of site-specific ecological requirements. A reintroduction program of European roe deer (Capreolus capreolus (L., 1758)) in a dry Mediterranean region in Israel provides an opportunity to study the bottleneck effect of water requirements on a mesic-adapted species. Four does were hand-reared and released in a 10 ha site consisting of an early succession scrubland and a mature oak forest. We measured daily energy expenditure (DEE) and water turnover (WTO) using the doubly labeled water technique during summer and winter. DEE was similar in the summer and winter, but there was a significant difference in WTO and in the source of gained water. In winter, WTO was 3.3 L/day, of which 67% was obtained from vegetation. In summer, WTO dropped to 2.1 L/day, of which only 20% was obtained from the diet and 76% was gained from drinking. When the water source was moved to a nonpreferred habitat, drinking frequency dropped significantly, but water consumption remained constant. In a dry Mediterranean environment, availability of free water is both a physiological contraint and a behavioral constraint for roe deer. This study demonstrates the importance of physiological and behavioral feasibility studies for reintroduction programs.

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Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

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Research on fusion fast ignition (FI) initiated by laser-driven ion beams has made substantial progress in the last years. Compared with electrons, FI based on a beam of quasi-monoenergetic ions has the advantage of a more localized energy deposition, and stiffer particle transport, bringing the required total beam energy close to the theoretical minimum. Due to short pulse laser drive, the ion beam can easily deliver the 200 TW power required to ignite the compressed D-T fuel. In integrated calculations we recently simulated ion-based FI targets with high fusion gain targets and a proof of principle experiment [1]. These simulations identify three key requirements for the success of ion-driven fast ignition (IFI): (1) the generation of a sufficiently high-energetic ion beam (approximate to 400-500 MeV for C), with (2) less than 20% energy spread at (3) more than 10% conversion efficiency of laser to beam energy. Here we present for the first time new experimental results, demonstrating all three parameters in separate experiments. Using diamond nanotargets and ultrahigh contrast laser pulses we were able to demonstrate >500 MeV carbon ions, as well as carbon pulses with Delta E/E

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Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems. © 2010 IEEE.

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Most Wave Energy Converters (WECs) being developed are fundamentally different from known marine structures. Limited experience is a fundamental challenge for the design, especially issues concerning load assumptions and power estimates. Reynolds-Averaged Navier-Stokes (RANS) CFD methods are being used successfully in many areas of marine engineering. They have been shown to accurately simulate many hydrodynamic effects and are a helpful tool for investigating complex flows. The major drawback is the significant computational power required and the associated overhead with pre and post-processing. This paper presents the challenges and advantages in the application of RANS CFD methods in the design process of a wave energy converter and compares the time, labour and ultimately financial requirements for obtaining practical results.

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Today's multi-media electronic era is driven by the increasing demand for small multifunctional devices able to support diverse services. Unfortunately, the high levels of transistor integration and performance required by such devices lead to an unprecedented increase of on-chip power that significantly limits the battery lifetime and even poses reliability concerns. Several techniques have been developed to address the power increase, but voltage over-scaling (VOS) is considered to be one of the most effective ones due to the quadratic dependence of voltage on dynamic power consumption. However, VOS may not always be applicable since it increases the delay in all paths of a system and may limit high performance required by today's complex applications. In addition, application of VOS is further complicated since it increases the variations in transistor characteristics imposed by their tiny size which can lead to large delay and leakage variations, making it difficult to meet delay and power budgets. This paper presents a review of various cross-layer design options that can provide solutions for dynamic voltage over-scaling and can potentially assist in meeting the strict power budgets and yield/quality requirements of future systems. © 2011 IEEE.