984 resultados para Energy Functions


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The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

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This paper is on the self-scheduling for a power producer taking part in day-ahead joint energy and spinning reserve markets and aiming at a short-term coordination of wind power plants with concentrated solar power plants having thermal energy storage. The short-term coordination is formulated as a mixed-integer linear programming problem given as the maximization of profit subjected to technical operation constraints, including the ones related to a transmission line. Probability density functions are used to model the variability of the hourly wind speed and the solar irradiation in regard to a negative correlation. Case studies based on an Iberian Peninsula wind and concentrated solar power plants are presented, providing the optimal energy and spinning reserve for the short-term self-scheduling in order to unveil the coordination benefits and synergies between wind and solar resources. Results and sensitivity analysis are in favour of the coordination, showing an increase on profit, allowing for spinning reserve, reducing the need for curtailment, increasing the transmission line capacity factor. (C) 2014 Elsevier Ltd. All rights reserved.

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This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

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Double-differential three-jet production cross-sections are measured in proton--proton collisions at a centre-of-mass energy of s√=7TeV using the ATLAS detector at the Large Hadron Collider. The measurements are presented as a function of the three-jet mass (mjjj), in bins of the sum of the absolute rapidity separations between the three leading jets (|Y∗|). Invariant masses extending up to 5 TeV are reached for 8<|Y∗|<10. These measurements use a sample of data recorded using the ATLAS detector in 2011, which corresponds to an integrated luminosity of 4.51fb−1. Jets are identified using the anti-kt algorithm with two different jet radius parameters, R=0.4 and R=0.6. The dominant uncertainty in these measurements comes from the jet energy scale. Next-to-leading-order QCD calculations corrected to account for non-perturbative effects are compared to the measurements. Good agreement is found between the data and the theoretical predictions based on most of the available sets of parton distribution functions, over the full kinematic range, covering almost seven orders of magnitude in the measured cross-section values.

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We provide a comparative analysis of how short-run variations in carbon and energy prices relate to each other in the emerging greenhouse gas market in California (Western Climate Initiative [WCI], and the European Union Emission Trading Scheme [EU ETS]). We characterize the relationship between carbon, gas, coal, electricity and gasoline prices and an indicator for economic activity, and present a first analysis of carbon prices in the WCI. We also provide a comparative analysis of the structures of the two markets. We estimate a vector autoregressive model and the impulse--response functions. Our main findings show a positive impact from a carbon shock toward electricity, in both markets, but larger in the WCI electricity price, indicating more efficiency. We propose that the widening of carbon market sectors, namely fuels transport and electricity imports, may contribute to this result. To conclude, the research shows significant and coherent relations between variables in WCI, which demonstrate some degree of success for a first year in operation. Reversely, the EU ETS should complete its intended market reform, to allow for more impact of the carbon price. Finally, in both markets, there is no evidence of carbon pricing depleting economic activity.

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Peroxisome proliferator-activated receptors, PPARs, (NR1C) are nuclear hormone receptors implicated in energy homeostasis. Upon activation, these ligand-inducible transcription factors stimulate gene expression by binding to the promoter of target genes. The different structural domains of PPARs are presented in terms of activation mechanisms, namely ligand binding, phosphorylation, and cofactor interaction. The specificity of ligands, such as fatty acids, eicosanoids, fibrates and thiazolidinediones (TZD), is described for each of the three PPAR isotypes, alpha (NR1C1), beta (NR1C2) and gamma (NR1C3), so as the differential tissue distribution of these isotypes. Finally, general and specific functions of the PPAR isotypes are discussed, namely their implication in the control of inflammatory responses, cell proliferation and differentiation, the roles of PPARalpha in fatty acid catabolism and of PPARgamma in adipogenesis.

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PURPOSE OF REVIEW: The control of glucose and energy homeostasis, including feeding behaviour, is tightly regulated by gut-derived peptidic and nonpeptidic endocrine mediators, autonomic nervous signals, as well as nutrients such as glucose. We will review recent findings on the role of the gastrointestinal tract innervation and of portal vein glucose sensors; we will review selected data on the action of gastrointestinally released hormones. RECENT FINDINGS: The involvement of mechanosensory vagal afferents in postprandial meal termination has been clarified using mouse models with selective impairments of genes required for development of mechanosensory fibres. These activate central glucogen-like peptide-1/glucogen-like peptide-2 containing ascending pathways linking the visceroceptive brainstem neurons to hypothalamic nuclei. Mucosal terminals comprise the chemosensory vagal afferents responsive to postprandially released gastrointestinal hormones. The mechanism by which the hepatoportal glucose sensor stimulates glucose utilization by muscles was demonstrated, using genetically modified mice, to be insulin-independent but to require GLUT4 and AMP-kinase. This sensor is a key site of glucogen-like peptide-1 action and plays a critical role in triggering first phase insulin secretion. PeptideYY and ghrelin target intracerebral receptors as they are bidirectionally transported across the blood brain barrier. The anorectic functions of peripherally released peptideYY may however be mediated both via vagal afferents and intracerebral Y2 receptors in the brainstem and arcuate nucleus. SUMMARY: These recent findings demonstrate that the use of improved anatomical and physiological techniques and animal models with targeted gene modifications lead to an improved understanding of the complex role of gastrointestinal signals in the control of energy homeostasis.

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The costs of coping with stressful situations are traded-off against other functions such as immune responses. This trade-off may explain why corticosterone secretion reduces immune reactions. Corticosterone differentially affects various immunity components. However, which component is suppressed varies between studies. It remains unclear whether the trade-off in energy, nutrition, autoimmunity or oxidative stress accounts for differential immunosuppression. In this study, we investigated whether corticosterone differentially affects the constitutive innate and humoral acquired immunity. We used barn owl nestlings, implanting 50% with a corticosterone-releasing pellet and the other 50% with a placebo pellet. To measure the effect on humoral immunity we vaccinated 50% of the corticosterone-nestlings and 50% of the placebo-nestlings with the antigens 'Tetravac' and the other 50% were injected with PBS. To assess the costs of elevated corticosterone, we measured body mass and resistance to oxidative stress. Administration of corticosterone increased corticosterone levels whereas vaccination induced the production of antibodies. Corticosterone reduced the production of antibodies, but it did not significantly affect the constitutive innate immunity. Corticosterone reduced body growth and resistance to oxidative stress. Under stressful conditions barn owl nestlings seem to keep the constitutive innate immunity, whereas elevated corticosterone levels negatively affected inducible immune responses. We found evidence that mounting a humoral immune reaction is not costly in terms of growth, but reduces the resistance to oxidative stress independently of corticosterone administration. We suggest that humoral immunity is suppressed because the risk of immunopathologies may be disproportionately high when mounting an antibody response under stressful situations.

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The endocannabinoid system (ECS) has been implicated in many physiological functions, including the regulation of appetite, food intake and energy balance, a crucial involvement in brain reward systems and a role in psychophysiological homeostasis (anxiety and stress responses). We first introduce this important regulatory system and chronicle what is known concerning the signal transduction pathways activated upon the binding of endogenous cannabinoid ligands to the Gi/0-coupled CB1 cannabinoid receptor, as well as its interactions with other hormones and neuromodulators which can modify endocannabinoid signaling in the brain. Anorexia nervosa (AN) and bulimia nervosa (BN) are severe and disabling psychiatric disorders, characterized by profound eating and weight alterations and body image disturbances. Since endocannabinoids modulate eating behavior, it is plausible that endocannabinoid genes may contribute to the biological vulnerability to these diseases. We present and discuss data suggesting an impaired endocannabinoid signaling in these eating disorders, including association of endocannabinoid components gene polymorphisms and altered CB1-receptor expression in AN and BN. Then we discuss recent findings that may provide new avenues for the identification of therapeutic strategies based on the endocannabinod system. In relation with its implications as a reward-related system, the endocannabinoid system is not only a target for cannabis but it also shows interactions with other drugs of abuse. On the other hand, there may be also a possibility to point to the ECS as a potential target for treatment of drug-abuse and addiction. Within this framework we will focus on enzymatic machinery involved in endocannabinoid inactivation (notably fatty acid amide hydrolase or FAAH) as a particularly interesting potential target. Since a deregulated endocannabinoid system may be also related to depression, anxiety and pain symptomatology accompanying drug-withdrawal states, this is an area of relevance to also explore adjuvant treatments for improving these adverse emotional reactions.

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Selected configuration interaction (SCI) for atomic and molecular electronic structure calculations is reformulated in a general framework encompassing all CI methods. The linked cluster expansion is used as an intermediate device to approximate CI coefficients BK of disconnected configurations (those that can be expressed as products of combinations of singly and doubly excited ones) in terms of CI coefficients of lower-excited configurations where each K is a linear combination of configuration-state-functions (CSFs) over all degenerate elements of K. Disconnected configurations up to sextuply excited ones are selected by Brown's energy formula, ΔEK=(E-HKK)BK2/(1-BK2), with BK determined from coefficients of singly and doubly excited configurations. The truncation energy error from disconnected configurations, Δdis, is approximated by the sum of ΔEKS of all discarded Ks. The remaining (connected) configurations are selected by thresholds based on natural orbital concepts. Given a model CI space M, a usual upper bound ES is computed by CI in a selected space S, and EM=E S+ΔEdis+δE, where δE is a residual error which can be calculated by well-defined sensitivity analyses. An SCI calculation on Ne ground state featuring 1077 orbitals is presented. Convergence to within near spectroscopic accuracy (0.5 cm-1) is achieved in a model space M of 1.4× 109 CSFs (1.1 × 1012 determinants) containing up to quadruply excited CSFs. Accurate energy contributions of quintuples and sextuples in a model space of 6.5 × 1012 CSFs are obtained. The impact of SCI on various orbital methods is discussed. Since ΔEdis can readily be calculated for very large basis sets without the need of a CI calculation, it can be used to estimate the orbital basis incompleteness error. A method for precise and efficient evaluation of ES is taken up in a companion paper

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A comparision of the local effects of the basis set superposition error (BSSE) on the electron densities and energy components of three representative H-bonded complexes was carried out. The electron densities were obtained with Hartee-Fock and density functional theory versions of the chemical Hamiltonian approach (CHA) methodology. It was shown that the effects of the BSSE were common for all complexes studied. The electron density difference maps and the chemical energy component analysis (CECA) analysis confirmed that the local effects of the BSSE were different when diffuse functions were present in the calculations

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Geometries, vibrational frequencies, and interaction energies of the CNH⋯O3 and HCCH⋯O3 complexes are calculated in a counterpoise-corrected (CP-corrected) potential-energy surface (PES) that corrects for the basis set superposition error (BSSE). Ab initio calculations are performed at the Hartree-Fock (HF) and second-order Møller-Plesset (MP2) levels, using the 6-31G(d,p) and D95++(d,p) basis sets. Interaction energies are presented including corrections for zero-point vibrational energy (ZPVE) and thermal correction to enthalpy at 298 K. The CP-corrected and conventional PES are compared; the unconnected PES obtained using the larger basis set including diffuse functions exhibits a double well shape, whereas use of the 6-31G(d,p) basis set leads to a flat single-well profile. The CP-corrected PES has always a multiple-well shape. In particular, it is shown that the CP-corrected PES using the smaller basis set is qualitatively analogous to that obtained with the larger basis sets, so the CP method becomes useful to correctly describe large systems, where the use of small basis sets may be necessary

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The present work provides a generalization of Mayer's energy decomposition for the density-functional theory (DFT) case. It is shown that one- and two-atom Hartree-Fock energy components in Mayer's approach can be represented as an action of a one-atom potential VA on a one-atom density ρ A or ρ B. To treat the exchange-correlation term in the DFT energy expression in a similar way, the exchange-correlation energy density per electron is expanded into a linear combination of basis functions. Calculations carried out for a number of density functionals demonstrate that the DFT and Hartree-Fock two-atom energies agree to a reasonable extent with each other. The two-atom energies for strong covalent bonds are within the range of typical bond dissociation energies and are therefore a convenient computational tool for assessment of individual bond strength in polyatomic molecules. For nonspecific nonbonding interactions, the two-atom energies are low. They can be either repulsive or slightly attractive, but the DFT results more frequently yield small attractive values compared to the Hartree-Fock case. The hydrogen bond in the water dimer is calculated to be between the strong covalent and nonbonding interactions on the energy scale

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Peroxisome proliferator-activated receptor gamma (PPARgamma) is an essential regulator of adipocyte differentiation, maintenance, and survival. Deregulations of its functions are associated with metabolic diseases. We show here that deletion of one PPARgamma allele not only affected lipid storage but, more surprisingly, also the expression of genes involved in glucose uptake and utilization, the pentose phosphate pathway, fatty acid synthesis, lipolysis, and glycerol export as well as in IR/IGF-1 signaling. These deregulations led to reduced circulating adiponectin levels and an energy crisis in the WAT, reflected in a decrease to nearly half of its intracellular ATP content. In addition, there was a decrease in the metabolic rate and physical activity of the PPARgamma(+/-) mice, which was abolished by thiazolidinedione treatment, thereby linking regulation of the metabolic rate and physical activity to PPARgamma. It is likely that the PPARgamma(+/-) phenotype was due to the observed WAT dysfunction, since the gene expression profiles associated with metabolic pathways were not affected either in the liver or the skeletal muscle. These findings highlight novel roles of PPARgamma in the adipose tissue and underscore the multifaceted action of this receptor in the functional fine tuning of a tissue that is crucial for maintaining the organism in good health.

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Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.