859 resultados para Data-driven energy e ciency


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Given the shift toward energy efficient vehicles (EEVs) in recent years, it is important that the effects of this transition are properly examined. This paper investigates some of these effects by analyzing annual kilometers traveled (AKT) of private vehicle owners in Stockholm in 2008. The difference in emissions associated with EEV adoption is estimated, along with the effect of a congestion-pricing exemption for EEVs on vehicle usage. Propensity score matching is used to compare AKT rates of different vehicle owner groups based on the treatments of: EEV ownership and commuting across the cordon, controlling for confounding factors such as demographics. Through this procedure, rebound effects are identified, with some EEV owners found to have driven up to 12.2% further than non-EEV owners. Although some of these differences could be attributed to the congestion-pricing exemption, the results were not statistically significant. Overall, taking into account lifecycle emissions of each fuel type, average EEV emissions were 50.5% less than average non-EEV emissions, with this reduction in emissions offset by 2.0% due to rebound effects. Although it is important for policy-makers to consider the potential for unexpected negative effects in similar transitions, the overall benefit of greatly reduced emissions appears to outweigh any rebound effects present in this case study.

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The development and maintenance of large and complex ontologies are often time-consuming and error-prone. Thus, automated ontology learning and revision have attracted intensive research interest. In data-centric applications where ontologies are designed or automatically learnt from the data, when new data instances are added that contradict to the ontology, it is often desirable to incrementally revise the ontology according to the added data. This problem can be intuitively formulated as the problem of revising a TBox by an ABox. In this paper we introduce a model-theoretic approach to such an ontology revision problem by using a novel alternative semantic characterisation of DL-Lite ontologies. We show some desired properties for our ontology revision. We have also developed an algorithm for reasoning with the ontology revision without computing the revision result. The algorithm is efficient as its computational complexity is in coNP in the worst case and in PTIME when the size of the new data is bounded.

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Available industrial energy meters offer high accuracy and reliability, but are typically expensive and low-bandwidth, making them poorly suited to multi-sensor data acquisition schemes and power quality analysis. An alternative measurement system is proposed in this paper that is highly modular, extensible and compact. To minimise cost, the device makes use of planar coreless PCB transformers to provide galvanic isolation for both power and data. Samples from multiple acquisition devices may be concentrated by a central processor before integration with existing host control systems. This paper focusses on the practical design and implementation of planar coreless PCB transformers to facilitate the module's isolated power, clock and data signal transfer. Calculations necessary to design coreless PCB transformers, and circuits designed for the transformer's practical application in the measurement module are presented. The designed transformer and each application circuit have been experimentally verified, with test data and conclusions made applicable to coreless PCB transformers in general.

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One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.

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Although a number of studies have examined the role of gastric emptying (GE) in obesity, the influences of habitual physical activity level, body composition and energy expenditure (EE) on GE have received very little consideration. In this study, we have compared GE in active and inactive males, and we have characterised relationships with body composition (fat and fat free mass) and EE. Forty-four males (Active: n=22, Inactive: n=22; range BMI 21-36kg/m2; range percent fat mass 9-42%) were studied, with GE of a standardised (1676 kJ) pancake meal being assessed by 13C-octanoic acid breath test, body composition by air displacement plethysmography, resting metabolic rate (RMR) by indirect calorimetry and activity EE (AEE) by accelerometry. Results showed that GE was faster in active compared to inactive males (mean ±SD half time (t1/2): Active: 157±18 and Inactive: 179±21 min, p<0.001). When data from both groups were pooled, GE t1/2 was associated with percent fat mass (r=0.39, p<0.01) and AEE (r =-0.46, p<0.01). After controlling for habitual physical activity status, the association between AEE and GE remained, but not that for percent fat mass and GE. BMI and RMR were not associated with GE. In summary, faster GE is considered to be a marker of a habitually active lifestyle in males, and is associated with a higher AEE and lower percent fat mass. The possibility that GE contributes to a gross physiological regulation (or dysregulation) of food intake with physical activity level deserves further investigation.

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This study estimates the environmental efficiency of international listed firms in 10 worldwide sectors from 2007 to 2013 by applying an order-m method, a non-parametric approach based on free disposal hull with subsampling bootstrapping. Using a conventional output of gross profit and two conventional inputs of labor and capital, this study examines the order-m environmental efficiency accounting for the presence of each of 10 undesirable inputs/outputs and measures the shadow prices of each undesirable input and output. The results show that there is greater potential for the reduction of undesirable inputs rather than bad outputs. On average, total energy, electricity, or water usage has the potential to be reduced by 50%. The median shadow prices of undesirable inputs, however, are much higher than the surveyed representative market prices. Approximately 10% of the firms in the sample appear to be potential sellers or production reducers in terms of undesirable inputs/outputs, which implies that the price of each item at the current level has little impact on most of the firms. Moreover, this study shows that the environmental, social, and governance activities of a firm do not considerably affect environmental efficiency.

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In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.

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This paper investigates communication protocols for relaying sensor data from animal tracking applications back to base stations. While Delay Tolerant Networks (DTNs) are well suited to such challenging environments, most existing protocols do not consider the available energy that is particularly important when tracking devices can harvest energy. This limits both the network lifetime and delivery probability in energy-constrained applications to the point when routing performance becomes worse than using no routing at all. Our work shows that substantial improvement in data yields can be achieved through simple yet efficient energy-aware strategies. Conceptually, there is need for balancing the energy spent on sensing, data mulling, and delivery of direct packets to destination. We use empirical traces collected in a flying fox (fruit bat) tracking project and show that simple threshold-based energy-aware strategies yield up to 20% higher delivery rates. Furthermore, these results generalize well for a wide range of operating conditions.

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Background: IgE is the pivotal-specific effector molecule of allergic reactions yet it remains unclear whether the elevated production of IgE in atopic individuals is due to superantigen activation of B cell populations, increased antibody class switching to IgE or oligoclonal allergen-driven IgE responses. Objectives: To increase our understanding of the mechanisms driving IgE responses in allergic disease we examined immunoglobulin variable regions of IgE heavy chain transcripts from three patients with seasonal rhinitis due to grass pollen allergy. Methods: Variable domain of heavy chain-epsilon constant domain 1 cDNAs were amplified from peripheral blood using a two-step semi-nested PCR, cloned and sequenced. Results: The VH gene family usage in subject A was broadly based, but there were two clusters of sequences using genes VH 3-9 and 3-11 with unusually low levels of somatic mutations, 0-3%. Subject B repeatedly used VH 1-69 and subject C repeatedly used VH 1-02, 1-46 and 5a genes. Most clones were highly mutated being only 86-95% homologous to their germline VH gene counterparts and somatic mutations were more abundant at the complementarity determining rather than framework regions. Multiple sequence alignment revealed both repeated use of particular VH genes as well as clonal relatedness among clusters of IgE transcripts. Conclusion: In contrast to previous studies we observed no preferred VH gene common to IgE transcripts of the three subjects allergic to grass pollen. Moreover, most of the VH gene characteristics of the IgE transcripts were consistent with oligoclonal antigen-driven IgE responses.

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Since 2003, Mainland China has been promoting the public–private partnership (PPP) procurement model in the waste-to-energy incineration sector to reduce the waste burying rate and improve environmental quality. Five critical risk factors (CRFs) that affect the construction and operation of waste-to-energy incineration projects have been identified from real-life risk events of 14 PPP waste-to-energy incineration plants through content analysis. These risk factors are insufficient waste supply, disposal of non-licensed waste, environmental risk, payment risk, and lack of supporting infrastructure. A recently completed PPP waste-to-energy incineration plant, the Shanghai Tianma project, was investigated to learn from the effective management of CRFs. First-hand data about the Shanghai Tianma project was collected, with a focus on project negotiation and concession agreement. Lessons learned about risk management were acquired. This paper presents a detailed study of the contractual structure, risk sharing scheme, risk response measures to CRFs, and project transfer of a PPP project. The study results will provide governments with management implications to prepare equitable concession agreements and benefit private investors by effectively mitigating and managing risks in future PPP waste-to-energy incineration projects.

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Palladium (Pd)-catalyzed cross-coupling reactions are among the most important methods in organic synthesis. We report the discovery of highly efficient and green photocatalytic processes by which cross-coupling reactions, including Sonogashira, Stille, Hiyama, Ullmann, and Buchwald–Hartwig reactions, can be driven with visible light at temperatures slightly above room temperature using alloy nanoparticles of gold and Pd on zirconium oxide, thus achieving high yields. The alloy nanoparticles absorb visible light, and their conduction electrons gain energy, which is available at the surface Pd sites. Results of the density functional theory calculations indicate that transfer of the light excited electrons from the nanoparticle surface to the reactant molecules adsorbed on the nanoparticle surface activates the reactants. When the light intensity was increased, a higher reaction rate was observed, because of the increased population of photoexcited electrons. The irradiation wavelength also has an important impact on the reaction rates. Ultraviolet irradiation can drive some reactions with the chlorobenzene substrate, while visible light irradiation failed to, and substantially improve the yields of the reactions with the bromobenzene substrate. The discovery reveals the possibility of using low-energy and -density sources such as sunlight to drive chemical transformations.

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The concept of energy gap(s) is useful for understanding the consequence of a small daily, weekly, or monthly positive energy balance and the inconspicuous shift in weight gain ultimately leading to overweight and obesity. Energy gap is a dynamic concept: an initial positive energy gap incurred via an increase in energy intake (or a decrease in physical activity) is not constant, may fade out with time if the initial conditions are maintained, and depends on the 'efficiency' with which the readjustment of the energy imbalance gap occurs with time. The metabolic response to an energy imbalance gap and the magnitude of the energy gap(s) can be estimated by at least two methods, i.e. i) assessment by longitudinal overfeeding studies, imposing (by design) an initial positive energy imbalance gap; ii) retrospective assessment based on epidemiological surveys, whereby the accumulated endogenous energy storage per unit of time is calculated from the change in body weight and body composition. In order to illustrate the difficulty of accurately assessing an energy gap we have used, as an illustrative example, a recent epidemiological study which tracked changes in total energy intake (estimated by gross food availability) and body weight over 3 decades in the US, combined with total energy expenditure prediction from body weight using doubly labelled water data. At the population level, the study attempted to assess the cause of the energy gap purported to be entirely due to increased food intake. Based on an estimate of change in energy intake judged to be more reliable (i.e. in the same study population) and together with calculations of simple energetic indices, our analysis suggests that conclusions about the fundamental causes of obesity development in a population (excess intake vs. low physical activity or both) is clouded by a high level of uncertainty.

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Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.

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Introduction The epidemic of nutrition related non-communicable diseases such as type 2 diabetes mellitus and obesity has reached to epidemic portion in the Sri Lanka. However, to date, detailed data on food consumption in the Sri Lankan population is limited. The aim of this study is to identify energy and major nutrient intake among Sri Lankan adults. Methods A nationally-representative sample of adults was selected using a multi-stage random cluster sampling technique. Results Data from 463 participants (166 Males, 297 Females) were analyzed. Total energy intake was significantly higher in males (1913 ± 567 kcal/d) than females (1514 ± 458 kcal/d). However, there was no significant gender differences in the percentage of energy from carbohydrate (Male: 72.8 ± 6.4%, Female: 73.9 ± 6.7%), fat (Male: 19.9 ± 6.1%, Female: 18.5 ± 5.7%) and proteins (Male: 10.6 ± 2.1%, Female: 10.9 ± 5.6%). Conclusion The present study provides the first national estimates of energy and nutrient intake of the Sri Lankan adult population.

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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.