928 resultados para Data-driven energy e ciency
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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It is still controversial whether intestinal parasitic infections can influence the nutritional status of children. The relationship between protein-energy malnutrition, vitamin A and parasitic infections was evaluated in 124 children. The food intake estimated by recall method was generally low and poor. Seventy five percent of the children were infected with intestinal parasites. The mean±SD weight-for-age and height-for-age Z-score were skewed one standard deviation to the left, when compared to normal standards. An association was found between protein-energy malnutrition and Giardia lamblia, but not with Ascaris lumbricoides or Hymenolepis nana infection. Only Giardia-infected children had a decreased weight-for-age and weight-for-height Z-score. Hypovitaminosis A was a major nutritional problem, but no relationship between this deficiency and parasitic infection was found. Our data indicate that low and poor food intake were the major cause of protein-energy malnutrition among the children, and except for Giardia, this was not influenced by parasitic infections.
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Dissertation presented to obtain the Ph.D degree in Chemistry
Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel
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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores
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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.
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The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.
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Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.
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Pressure sores are common among bedridden, elderly, or malnourished patients, and may occur in terminal ill patients because of impaired mobility, fecal or urinary incontinence, and decreased healing capacity. The aim of this study was to compare frequency of pressure sores between malnourished and non-malnourished necropsied adults. METHOD: All (n = 201) adults (age ³ 18 years) autopsied between 1986 and 1996 at the Teaching Hospital of Triangulo Mineiro Medical School (Uberaba) were eligible for the study. Gender, race, weight, height and main diagnoses were recorded. Ninety-six cases were excluded because of probable body water retention (congestive heart failure, hepatic insufficiency, nephrotic syndrome) or pressure sores secondary to peripheral vascular ischemia. Body mass index (BMI) was used to define malnourished (BMI < 18.5 kg/m²) and non-malnourished (BMI > 18.5kg/m²) groups. RESULTS: Except for weight (42.5kg; range: 28-57 vs. 60; 36-134.5kg) and BMI (16.9; range: 12.4-18.5 vs. 22.7; range: 18.5-54.6kg/m²), respectively, there were no statistical differences among 43 malnourished and 62 non-malnourished cases in relation to age (54.9 ± 20.4 vs. 52.9 ± 17.9 years), percentage of white persons (74.4 vs. 64.5%), male gender (76.7 vs. 69.3%) and main diagnoses. Five malnourished (11.6%) and 7 (11.5%) non-malnourished cases had pressure sores (p=0.89). CONCLUSION: Pressure sores were equally common findings in necropsied persons with protein-energy malnutrition, as assessed by body mass index.
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Dissertação de Mestrado em Engenharia Informática
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The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.
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The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton–proton collision data with a centre-of-mass energy of s√=7 TeV corresponding to an integrated luminosity of 4.7 fb −1 . Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti- kt algorithm with distance parameters R=0.4 or R=0.6 , and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a Z boson, for 20≤pjetT<1000 GeV and pseudorapidities |η|<4.5 . The effect of multiple proton–proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region ( |η|<1.2 ) for jets with 55≤pjetT<500 GeV . For central jets at lower pT , the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton–proton collisions and test-beam data, which also provide the estimate for pjetT>1 TeV. The calibration of forward jets is derived from dijet pT balance measurements. The resulting uncertainty reaches its largest value of 6 % for low- pT jets at |η|=4.5 . Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5–3 %.
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A search is performed for Higgs bosons produced in association with top quarks using the diphoton decay mode of the Higgs boson. Selection requirements are optimized separately for leptonic and fully hadronic final states from the top quark decays. The dataset used corresponds to an integrated luminosity of 4.5 fb−1 of proton--proton collisions at a center-of-mass energy of 7 TeV and 20.3 fb−1 at 8 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No significant excess over the background prediction is observed and upper limits are set on the tt¯H production cross section. The observed exclusion upper limit at 95% confidence level is 6.7 times the predicted Standard Model cross section value. In addition, limits are set on the strength of the Yukawa coupling between the top quark and the Higgs boson, taking into account the dependence of the tt¯H and tH cross sections as well as the H→γγ branching fraction on the Yukawa coupling. Lower and upper limits at 95% confidence level are set at −1.3 and +8.0 times the Yukawa coupling strength in the Standard Model.
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Searches are performed for resonant and non-resonant Higgs boson pair production in the hh→γγbb¯ final state using 20 fb−1 of proton--proton collisions at a center-of-mass energy of 8TeV recorded with the ATLAS detector at the CERN Large Hadron Collider. A 95% confidence level upper limit on the cross section times branching ratio of non--resonant production is set at 2.2 pb, while the expected limit is 1.0 pb. The corresponding limit observed for a narrow resonance ranges between 0.8 and 3.5 pb as a function of its mass.
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Companies and researchers involved in developing miniaturized electronic devices face the basic problem of the needed batteries size, finite life of time and environmental pollution caused by their final deposition. The current trends to overcome this situation point towards Energy Harvesting technology. These harvesters (or scavengers) store the energy from sources present in the ambient (as wind, solar, electromagnetic, etc) and are costless for us. Piezoelectric devices are the ones that show a higher power density, and materials as ceramic PZT or polymeric PVDF have already demonstrated their ability to act as such energy harvester elements. Combinations between piezoelectric and electromagnetic mechanism have been also extensively investigated. Nevertheless, the power generated by these combinations is limited under the application of small magnetic fields, reducing the performance of the energy harvester [1]. In the last years the appearance of magnetoelectric (ME) devices, in which the piezoelectric deformation is driven by the magnetostrictive element, enables to extract the energy of very small electromagnetic signals through the generated magnetoelectric voltage at the piezoelectric element. However, very little work has been done testing PVDF polymer as piezoelectric constituent of the ME energy harvester device, and only to be proposed as a possibility of application [2]. Among the advantages of using piezopolymers for vibrational energy harvesting we can remember that they are ductile, resilient to shock, deformable and lightweight. In this work we demonstrate the feasibility of using magnetostrictive Fe-rich magnetic amorphous alloys/piezoelectric PVDF sandwich-type laminated ME devices as energy harvesters. A very simple experimental set-up will show how these laminates can extract energy, in amounts of μW, from an external AC field.
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Dijet events produced in LHC proton--proton collisions at a center-of-mass energy s√=8 TeV are studied with the ATLAS detector using the full 2012 data set, with an integrated luminosity of 20.3 fb−1. Dijet masses up to about 4.5 TeV are probed. No resonance-like features are observed in the dijet mass spectrum. Limits on the cross section times acceptance are set at the 95% credibility level for various hypotheses of new phenomena in terms of mass or energy scale, as appropriate. This analysis excludes excited quarks with a mass below 4.09 TeV, color-octet scalars with a mass below 2.72 TeV, heavy W′ bosons with a mass below 2.45 TeV, chiral W∗ bosons with a mass below 1.75 TeV, and quantum black holes with six extra space-time dimensions with threshold mass below 5.82 TeV.