937 resultados para energy auto-correlation function


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Ethanol, the main automotive biofuel, has its production based on the fermentation of sugars found in biological materials and on the distillation of the alcoholic media formed during the fermentative process. Stillage is the main residue from ethanol production, containing a high organic loading in addition to acidic and corrosive characteristics. Considering the available technologies to treat stillage, we highlight anaerobic digestion, which allows the reduction of the impacts associated to pollutants loading of this effluent and the generation of energy from the methane gas produced in the process. Based on the high treatment efficiency usually associated to the anaerobic process, this work aimed to assess whether anaerobic systems applied to the treatment of stillage are energetically self-sufficient. First we evaluated the energy recovery capacity in an anaerobic reactor applied to the treatment of stillage resulting from corn-to-ethanol processing. The results indicated the great influence that a correct selection of electrical equipment and their respective operating periods have on the net energy balance of the anaerobic treatment. The high energy consumption of the heater would not allow the system to achieve a positive net energy balance – the maximum energy recovery would reach only 0.68% of the consumption. However, the replacement of the mixture equipment would result in energy gains ranging from 8.5 to 967.9% of the consumption. In this work we also assessed the efficiency of methane yields for a few studies and the correlation between some parameters of the anaerobic process. With respect to the methane yield, we noted that mesophilic systems tend to be more advantageous than the thermophilic ones (efficiency of 76.45 ± 22.51% vs. 69.40 ± 30.36%). Considering the study... (Complete abstract click electronic access below)

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Biofuels and their blends with fossil fuel are important energy resources, which production and application have been largely increased internationally. This study focus on the development of a correlation between apparent activation energy (Ea) and NOx emission of the thermal decomposition of three pure fuels: farnasane (renewable diesel from sugar cane), biodiesel and fossil diesel and their blends. Apparent Activation energy was determined by using thermogravimetry and Model-Free Kinetics. NOx emission was obtained from the European Stationary Cycle (ESC) with OM 926LA CONAMA P7/Euro 5 engine. Results showed that there is a linear correlation between apparent activation energy and NOx emission with R2 of 0,9667 considering pure fuels and their blends which is given as: NOx = 2,2514Ea - 96,309. The average absolute error of this correlation is 2.96% with respect to the measured NOx value. The main advantage of this correlation is its capability to predict NOx emission when either a new pure fuel or a blend of fuels is proposed to use in enginees.

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Multidimensional and one-dimensional quantum-statistical (Bose-Einstein) correlations are measured in proton proton collisions at 0.9, 2.76 and 7 TeV, in proton lead collisions at 5.02 TeV/nucleon pair and peripheral lead lead collisions at 2.76 TeV/nucleon pair center-of-mass energy with the CMS detector at the LHC. The correlation functions are extracted in terms of different components of the relative momentum of the pair, in order to investigate the extension of the emission source in different directions. The results are presented for different intervals of transverse pair momentum, k(T), and charged particle multiplicity of the collision, N-tracks, as well as for their integrated values. Besides inclusive charged particles, charged pions and kaons, identified via their energy loss in the silicon tracker detector, can also be correlated. The extracted source radii increase with increasing multiplicity, and decrease with increasing k(T). The results open the possibility to study scaling and factorization properties of these radii as a function of multiplicity, k(T), colliding system size and center-of-mass energy.

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Two-particle azimuthal (Delta phi) and pseudorapidity (Delta eta) correlations using a trigger particle with large transverse momentum (p(T)) in d+Au, Cu+Cu, and Au+Au collisions at root s(NN) = 62.4 GeV and 200 GeV from the STAR experiment at the Relativistic Heavy Ion Collider are presented. The near-side correlation is separated into a jet-like component, narrow in both Delta phi and Delta eta, and the ridge, narrow in Delta phi but broad in Delta eta. Both components are studied as a function of collision centrality, and the jet-like correlation is studied as a function of the trigger and associated p(T). The behavior of the jet-like component is remarkably consistent for different collision systems, suggesting it is produced by fragmentation. The width of the jet-like correlation is found to increase with the system size. The ridge, previously observed in Au+Au collisions at root s(NN) = 200 GeV, is also found in Cu+Cu collisions and in collisions at root s(NN) = 62.4 GeV, but is found to be substantially smaller at root s(NN) = 62.4 GeV than at root s(NN) = 200 GeV for the same average number of participants (< N-part >). Measurements of the ridge are compared to models.

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We propose an alternative, nonsingular, cosmic scenario based on gravitationally induced particle production. The model is an attempt to evade the coincidence and cosmological constant problems of the standard model (Lambda CDM) and also to connect the early and late time accelerating stages of the Universe. Our space-time emerges from a pure initial de Sitter stage thereby providing a natural solution to the horizon problem. Subsequently, due to an instability provoked by the production of massless particles, the Universe evolves smoothly to the standard radiation dominated era thereby ending the production of radiation as required by the conformal invariance. Next, the radiation becomes subdominant with the Universe entering in the cold dark matter dominated era. Finally, the negative pressure associated with the creation of cold dark matter (CCDM model) particles accelerates the expansion and drives the Universe to a final de Sitter stage. The late time cosmic expansion history of the CCDM model is exactly like in the standard Lambda CDM model; however, there is no dark energy. The model evolves between two limiting (early and late time) de Sitter regimes. All the stages are also discussed in terms of a scalar field description. This complete scenario is fully determined by two extreme energy densities, or equivalently, the associated de Sitter Hubble scales connected by rho(I)/rho(f) = (H-I/H-f)(2) similar to 10(122), a result that has no correlation with the cosmological constant problem. We also study the linear growth of matter perturbations at the final accelerating stage. It is found that the CCDM growth index can be written as a function of the Lambda growth index, gamma(Lambda) similar or equal to 6/11. In this framework, we also compare the observed growth rate of clustering with that predicted by the current CCDM model. Performing a chi(2) statistical test we show that the CCDM model provides growth rates that match sufficiently well with the observed growth rate of structure.

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Background Atopic dermatitis (AD) is a chronic dermatosis, predominant in childhood, characterized by pruritus and eczematous-type lesions with xerosis as the prominent clinical sign. Objectives To analyze the correlation between biophysical measurements of skin barrier function and other assessment criteria of clinical severity according to Rajka and Langelands criteria. Methods Biophysical measurements [transepidermal water loss (TEWL) and corneometry] were obtained from 120 patients with the diagnosis of AD. Serum levels of IgE were also evaluated. Results A significant correlation between corneometry, TEWL, and clinical severity of AD was found. Data showed an inverse correlation between corneometry, TEWL, and AD severity, and a significant difference (P < 0.001) between mean of corneometry and TEWL and AD severity (mild, moderate, and severe). As for IgE levels, corneometry had significant negative correlation, in contrast with TEWL, which showed a significant positive correlation (P < 0.001). Conclusion Biophysical measurements of skin barrier in non-lesional skin of AD may work as an evaluation factor for AD severity.

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In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).

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Pneumococcal meningitis causes neurological sequelae, including learning and memory deficits in up to half of the survivors. In both humans and in animal models of the disease, there is apoptotic cell death in the hippocampus, a brain region involved in learning and memory function. We previously demonstrated that in an infant rat model of pneumococcal meningitis, there is activation of the kynurenine (KYN) pathway in the hippocampus, and that there was a positive correlation between the concentration of 3-hydroxykynurenine and the extent of hippocampal apoptosis. To clarify the role of the KYN pathway in the pathogenesis of hippocampal apoptosis in pneumococcal meningitis, we specifically inhibited 2 key enzymes of the KYN pathway and assessed hippocampal apoptosis, KYN pathway metabolites, and nicotinamide adenine dinucleotide (NAD) concentrations by high-performance liquid chromatography. Pharmacological inhibition of kynurenine 3-hydroxylase and kynureninase led to decreased cellular NAD levels and increased apoptosis in the hippocampus. The cerebrospinal fluid levels of tumor necrosis factor and interleukin-1? and -? were not affected. Our data suggest that activation of the KYN pathway in pneumococcal meningitis is neuroprotective by compensating for an increased NAD demand caused by infection and inflammation;this mechanism may prevent energy failure and apoptosis in the hippocampus.

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Fatal falls from great height are a frequently encountered setting in forensic pathology. They present--by virtue of a calculable energy transmission to the body--an ideal model for the assessment of the effects of blunt trauma to a human body. As multislice computed tomography (MSCT) has proven not only to be invaluable in clinical examinations, but also to be a viable tool in post-mortem imaging, especially in the field of osseous injuries, we performed a MSCT scan on 20 victims of falls from great height. We hereby detected fractures and their distributions were compared with the impact energy. Our study suggests a marked increase of extensive damage to different body regions at about 20 kJ and more. The thorax was most often affected, regardless of the amount of impacting energy and the primary impact site. Cranial fracture frequency displayed a biphasic distribution with regard to the impacting energy; they were more frequent in energies of less than 10, and more than 20 kJ, but rarer in the intermediate energy group, namely that of 10-20 kJ.

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A Maple scheme for quickly parameterizing vibrational potential energy functions is presented. As an example, the potential energy function's parameters for the vibrational motions in H_2O_2 are obtained assuming the simplest potential energy function. This paper was originally written as a research paper, but rejected by the referees. It is therefore being edited into an ``educational'' paper for student usage.

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Metabolic reprogramming has been shown to be a major cancer hallmark providing tumor cells with significant advantages for survival, proliferation, growth, metastasis and resistance against anti-cancer therapies. Glycolysis, glutaminolysis and mitochondrial biogenesis are among the most essential cancer metabolic alterations because these pathways provide cancer cells with not only energy but also crucial metabolites to support large-scale biosynthesis, rapid proliferation and tumorigenesis. In this study, we find that 14-3-3σ suppresses all these three metabolic processes by promoting the degradation of their main driver, c-Myc. In fact, 14-3-3s significantly enhances c-Myc poly-ubiquitination and subsequent degradation, reduces c-Myc transcriptional activity, and down-regulates c-Myc-induced metabolic target genes expression. Therefore, 14-3-3σ remarkably blocks glycolysis, decreases glutaminolysis and diminishes mitochondrial mass of cancer cells both in vitro and in vivo, thereby severely suppressing cancer bioenergetics and metabolism. As a result, a high level of 14-3-3σ in tumors is strongly associated with increased breast cancer patients’ overall and metastasis-free survival as well as better clinical outcomes. Thus, this study reveals a new role for 14-3-3s as a significant regulator of cancer bioenergetics and a promising target for the development of anti-cancer metabolism therapies.