980 resultados para Exascale, Supercomputer,OFET,energy effincency, data locality, HPC


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Background: Emerging evidence indicates that consumers of alcohol mixed with energy drink (AmED) self-report lower odds of risk-taking after consuming AmED versus alcohol alone. However, these studies have been criticized for failing to control for relative frequency of AmED versus alcohol-only consumption sessions. These studies also do not account for quantity of consumption and general alcohol-related risk-taking propensity. The aims of the present study were to (i) compare rates of risk-taking in AmED versus alcohol sessions among consumers with matched frequency of use and (ii) identify consumption and person characteristics associated with risk-taking behavior in AmED sessions. Methods: Data were extracted from 2 Australian community samples and 1 New Zealand community sample of AmED consumers (n = 1,291). One-fifth (21%; n = 273) reported matched frequency of AmED and alcohol use. Results: The majority (55%) of matched-frequency participants consumed AmED and alcohol monthly or less. The matched-frequency sample reported significantly lower odds of engaging in 18 of 25 assessed risk behaviors in AmED versus alcohol sessions. Similar rates of engagement were evident across session type for the remaining behaviors, the majority of which were low prevalence (reported by <15%). Regression modeling indicated that risk-taking in AmED sessions was primarily associated with risk-taking in alcohol sessions, with increased average energy drink (ED) intake associated with certain risk behaviors (e.g., being physically hurt, not using contraception, and driving while over the legal alcohol limit). Conclusions: Bivariate analyses from a matched-frequency sample align with past research showing lower odds of risk-taking behavior after AmED versus alcohol consumption for the same individuals. Multivariate analyses showed that risk-taking in alcohol sessions had the strongest association with risk-taking in AmED sessions. However, hypotheses of increased risk-taking post-AmED consumption were partly supported: Greater ED intake was associated with increased likelihood of specific behaviors, including drink-driving, sexual behavior, and aggressive behaviors in the matched-frequency sample after controlling for alcohol intake and risk-taking in alcohol sessions. These findings highlight the need to consider both personal characteristics and beverage effects in harm reduction strategies for AmED consumers.

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Recently, fields with substantial computing requirementshave turned to cloud computing for economical, scalable, and on-demandprovisioning of required execution environments. However, current cloudofferings focus on providing individual servers while tasks such as applicationdistribution and data preparation are left to cloud users. This article presents anew form of cloud called HPC Hybrid Deakin (H2D) cloud; an experimentalhybrid cloud capable of utilising both local and remote computational servicesfor large embarrassingly parallel applications. As well as supporting execution,H2D also provides a new service, called DataVault, that provides transparentdata management services so all cloud-hosted clusters have required datasetsbefore commencing execution.

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Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). Recent algorithms proposed for such WSNs are aimed at achieving better energy efficiency and minimizing latency. This creates a partitioned network area due to the overuse of certain nodes in areas which are on the shortest or closest or path to the base station or data aggregation points which results in hotspots nodes. In this paper, we propose a time-based multi-dimensional, multi-resolution storage approach for range queries that balances the energy consumption by balancing the traffic load as uniformly as possible. Thus ensuring a maximum network lifetime. We present simulation results to show that the proposed approach to information discovery offers significant improvements on information discovery latency compared with current approaches. In addition, the results prove that the Quality of Service (QoS) improvements reduces hotspots thus resulting in significant network-wide energy saving and an increased network lifetime.

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The constrained battery power of mobile devices poses a serious impact on user experience. As an increasingly prevalent type of applications in mobile cloud environments, location-based applications (LBAs) present some inherent limitations concerning energy. For example, the Global Positioning System based positioning mechanism is well-known for its extremely power-hungry attribute. Due to the severity of the issue, considerable researches have focused on energy-efficient locating sensing mechanism in the last a few years. In this paper, we provide a comprehensive survey of recent work on low-power design of LBAs. An overview of LBAs and different locating sensing technologies used today are introduced. Methods for energy saving with existing locating technologies are investigated. Reductions of location updating queries and simplifications of trajectory data are also mentioned. Moreover, we discuss cloud-based schemes in detail which try to develop new energy-efficient locating technologies by leveraging the cloud capabilities of storage, computation and sharing. Finally, we conclude the survey and discuss the future research directions. © 2013 Springer-Verlag Wien.

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There are currently no studies available reporting intervention effects on breaking up children's sedentary time. This study examined the UP4FUN intervention effect on objectively measured number of breaks in sedentary time, number of sedentary bouts (≥ 10 mins) and total and average amount of time spent in those sedentary bouts among 10- to 12-year-old Belgian children. The total sample included 354 children (mean age: 10.9 ± 0.7 years; 59% girls) with valid ActiGraph accelerometer data at pre- and posttest. Only few and small intervention effects were found, namely on total time spent in sedentary bouts immediately after school hours (4-6PM; β = -3.51mins) and on average time spent in sedentary bouts before school hours (6-8.30AM; β = -4.83mins) and immediately after school hours in favor of children from intervention schools (β = -2.71mins). Unexpectedly, girls from intervention schools decreased the number of breaks during school hours (8.30AM-4PM; β = -23.45breaks) and increased the number of sedentary bouts on a weekend day (β = +0.90bouts), whereas girls in control schools showed an increase in number of breaks and a decrease in number of bouts. In conclusion, UP4FUN did not have a consistent or substantial effect on breaking up children's sedentary time and these data suggest that more intensive and longer lasting interventions are needed.

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Background: Previous research on alcohol mixed with energy drinks (AmED) has shown that use is typically driven by hedonistic, social, functional, and intoxication-related motives, with differential associations with alcohol-related harm across these constructs. There has been no research looking at whether there are subgroups of consumers based on patterns of motivations. Consequently, the aims were to determine the typology of motivations for AmED use among a community sample and to identify correlates of subgroup membership. In addition, we aimed to determine whether this structure of motivations applied to a university student sample. Methods: Data were used from an Australian community sample (n = 731) and an Australian university student sample (n = 594) who were identified as AmED consumers when completing an online survey about their alcohol and ED use. Participants reported their level of agreement with 14 motivations for AmED use; latent classes of AmED consumers were identified based on patterns of motivation endorsement using latent class analysis. Results: A 4-class model was selected using data from the community sample: (i) taste consumers (31%): endorsed pleasurable taste; (ii) energy-seeking consumers (24%): endorsed functional and taste motives; (iii) hedonistic consumers (33%): endorse pleasure and sensation-seeking motives, as well as functional and taste motives; and (iv) intoxication-related consumers (12%): endorsed motives related to feeling in control of intoxication, as well as hedonistic, functional, and taste motives. The consumer subgroups typically did not differ on demographics, other drug use, alcohol and ED use, and AmED risk taking. The patterns of motivations for the 4-class model were similar for the university student sample. Conclusions: This study indicated the existence of 4 subgroups of AmED consumers based on their patterns of motivations for AmED use consistently structured across the community and university student sample. These findings lend support to the growing conceptualization of AmED consumers as a heterogeneous group in regard to motivations for use, with a hierarchical and cumulative class order in regard to the number of types of motivation for AmED use. Prospective research may endeavor to link session-specific motives and outcomes, as it is apparent that primary consumption motives may be fluid between sessions.

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In this work, the crystallization rates and spherulitic growth rate of miscible blends of poly(vinylidene fluoride) (PVDF) and acrylic rubber (ACM) were determined using differential scanning calorimetry (DSC), real-time FTIR, and optical microscopy. FTIR results suggest that blending does not induce the creation of polymorphic crystalline forms of PVDF. SAXS data demonstrate the formation of interlamellar structure after blending. The fold surface-free energy (σ e) was analyzed and compared using different thermal analysis techniques. The isothermal crystallization curves obtained using real-time FTIR and DSC explored in two different methods: t 1/2 or Avrami equation. While the Avrami equation is more widespread and precise, both analytical methods gave similar free energy of folding values. However, it was found that the direct optical method of measuring spherulitic growth rate yields σ e values 30-50 % lower than those obtained from the overall crystallization rate data. Conversely, the σ e values were found to increase with increasing amorphous ACM phase content regardless of the analytical methods.

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Cloud and service computing has started to change the way research in science, in particular biology and medicine, is being carried out. Researchers that have taken advantage of this technology (making use of public and private cloud compute resources) can process large amounts of data (big data) and speed up discovery. However, this requires researchers to acquire a solid knowledge and skills in the development of sequential and high performance computing (HPC), and cloud development and deployment background. In response a technology exposing HPC applications as services through the development and deployment of a SaaS cloud, and its proof of concept in the form of implementation of a cloud environment, Uncinus, has been developed and implemented to allow researchers easy access to cloud computing resources. The new technology offers and Uncinus supports the development of applications as services and the sharing of compute resources to speed up applications' execution. Users access these cloud resources and services through web interfaces. Using the Uncinus platform, a bio-informatics workflow was executed on a private (HPC) cloud, server and public cloud (Amazon EC2) resources, performance results showing a 3 fold improvement compared to local resources' performance. Biology and medicine specialists with no programming and application deployment on clouds background could run the case study applications with ease.

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While High Performance Computing clouds allow researchers to process large amounts of genomic data, complex resource and software configuration tasks must be carried out beforehand. The current trend exposes applications and data as services, simplifying access to clouds. This paper examines commonly used cloud-based genomic analysis services, introduces the approach of exposing data as services and proposes two new solutions (HPCaaS and Uncinus) which aim to automate service development, deployment process and data provision. By comparing and contrasting these solutions, we identify key mechanisms of service creation, execution and data access required to support non-computing specialists employing clouds.

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Radar observations on the altitude of bird migration and altitudinal profiles of meteorological conditions over the Sahara desert are presented for the autumn migratory period. Migratory birds fly at an average altitude of 1016 m (a.s.l.) during the day and 571 m during the night. Weather data served to calculate flight range using two models: an energy model (EM) and an energy-and-water model (EWM). The EM assumes that fuel supply limits flight range whereas the EWM assumes that both fuel and water may limit flight range. Flight ranges estimated with the EM were generally longer than those with the EWM. This indicates that trans-Sahara migrants might have more problems balancing their water than their energy budget. However, if we assume fuel stores to consist of 70% instead of 100% fat (the remainder consisting of 9% protein and 21% water), predicted flight ranges of the EM and EWM largely overlap. Increased oxygen extraction, reduced flight costs, reduced exhaled air temperature, reduced cutaneous water loss and increased tolerance to water loss are potential physiological adaptations that would improve the water budget in migrants. Both the EM and EWM predict optimal flight altitudes in agreement with radar observations in autumn. Optimal flight altitudes are differently predicted by the EM and EWM for nocturnal spring migration. During spring, the EWM predicts moderately higher and the EM substantially higher flight altitudes than during autumn. EWM predictions are therefore in better agreement with radar observations on flight altitude of migrants over the Negev desert in spring than EM predictions.

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The relationship between mass loss rate and chemical power in flying birds is analysed with regard to water and heat balance. Two models are presented: the first model is applicable to situations where heat loads are moderate. i.e. when heat balance can be achieved by regulating non-evaporative heat loss, and evaporative water loss is minimised. The second model is applicable when heat loads are high, non-evaporative heat loss is maximised. and heat balance has to be achieved by regulating evaporative heat loss. The rates of mass loss of two Thrush Nightingales Luscinia luscinia and one Teal Anas crecca were measured at various flight speeds in a wind tunnel. Estimates of metabolic water production indicate that the Thrush Nightingales did not dehydrate during experimental flights. Probably, the Thrush Nightingales maintained heat balance without actively increasing evaporative cooling. The Teal, however, most likely had to resort to evaporative cooling, although it may not have dehydrated. Chemical power was estimated from our mass loss rate data using the minimum evaporation model for the Thrush Nightingales and the evaporative heat regulation model for the Teal. For both Thrush Nightingales and the Teal, the chemical power calculated from our mass loss rate data showed a greater change with speed (more 'U-shaped' curve) than the theoretically predicted chemical power curves based on aerodynamic theory. The minimum power speeds calculated from our data differed little from theoretical predictions but maximum range speeds were drastically different. Mass loss rate could potentially be used to estimate chemical power in flying birds under laboratory conditions where temperature and humidity are controlled. However, the assumptions made in the models and the model predictions need further testing.

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Lindstrom and Alerstam presented a model that predicts optimal departure fuel loads as a function of the rate of fuel deposition in time-minimizing migrants. The basis of the model is that the coverable distance per unit of fuel deposited, diminishes with increasing fuel load. This is an effect of the increasing flight costs associated with increasing body mass. Lindstrom and Alerstam (1992) found that birds left at lower fuel loads than their model predicted for which they considered various ecological explanations. Alternatively, we hypothesize that the difference between prediction and empirical data might be a result of extra resting metabolic and transport costs associated with an increase in fuel load during stopover. We develop a new version of the Lindstrom and Alerstam (1992) model taking fuel load associated costs during stopover into account. We fit empirical data from rufous hummingbirds Selasphorus rufus and bluethroats Luscinia svecica to this new model. Estimated fuel-load costs are discussed in relation to knowledge presently available on variations in basal metabolic costs and transport costs with body mass. We show that fuel-load costs within a reasonable range can explain the observed departure fuel loads when migrating birds are time minimizers.

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Statistically significant association between energy consumption and economic growth is now well established in the literature. However, it still remains an unsettled issue whether economic growth is the cause or effect of energy consumption. The importance of identifying the direction of causality emanates from its relevance in national policy-making issues regarding energy conservation. Energy conservationissue is more important when energy acts as a contributing factor in economic growth than when it is used as a result of higher economic growth. In this backdrop, it is justified to search causal relationship between energy consumption and national output (GDP) of those countries that are expected to have higher energy consumption in future. Evidence shows that countries classified as non-OECD Asia will have the highest growth in energy consumption (3.7 percent) over the period 2003-2030. This forecasted energy consumption in these countries will have significant policy implication in the area of energy conservation. Hence, the present paper attempts to identify the direction of causality between energy consumption and output in the context of six major energy dependent non-OECD Asian countries.However, since the traditional bivariate approach suffers from omitted variable problems (Stern 1993, Masih and Masih, 1996 and Asafu-Adjaye, 2000), this paper employs a trivariate demand side approach consisting of energy consumption, income and prices. The countries selected for this purpose are Bangladesh, China, India, Malaysia, Pakistan and Thailand. Moreover, according to the Energy Information Administration (EIA) data of 2005, these six countries contribute 81.35% of the energyconsumption by all non-OECD Asian countries (aggregate energy consumption of 2005 by all non-OECD Asian countries is 113.60 quadrillion BTU while for these six countries alone the consumption is 92.42 quadrillion BTU).

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Understanding the dietary intakes of infants and toddlers is important because early life nutrition influences future health outcomes. The aim of this study was to determine the dietary sources of total energy and 16 nutrients in a nationally representative sample of U.S. infants and toddlers aged 0-24 months. Data from the 2005-2012 National Health and Nutrition Examination Survey were analyzed. Dietary intake was assessed in 2740 subjects using one 24-h dietary recall. The population proportion was used to determine the contribution of foods and beverages to nutrient intakes. Overall infant formulas and baby foods were the leading sources of total energy and nutrients in infants aged 0-11.9 months. In toddlers, the diversity of food groups contributing to nutrient intakes was much greater. Important sources of total energy included milk, 100% juice and grain based mixed dishes. A number of foods of low nutritional quality also contributed to energy intakes including sweet bakery products, sugar-sweetened beverages and savory snacks. Overall non-flavored milks and ready-to-eat cereals were the most important contributors to micronutrient intakes. In conclusion this information can be used to guide parents regarding appropriate food selection as well as inform targeted dietary strategies within public health initiatives to improve the diets of infants and toddlers.

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There is a burgeoning literature based on using panel cointegration techniques to study the relationship between energy consumption and GDP. Most panel cointegration tests employed take no cointegration as the null hypothesis. The current paper illustrates how a rejection by such a test cannot be taken as evidence of cointegration for the panel as a whole, a fact that seems to have gone largely unnoticed in the literature. Hence, even if the no cointegration null is rejected, this evidence is not enough to ensure that the relationship can be meaningfully estimated, as most (if not all) estimators in the literature require that the panel is cointegrated as a whole.