882 resultados para energy requirement model
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This work presents a mathematical model for helping mills choose sugarcane varieties for planting. It maximizes crop residual biomass energy balance by considering the difference between generated and consumed energy in the process of transferring this biomass from the field to the processing center; it takes into account enterprise demand restrictions and cane planting area. For this full zero-one linear programming techniques were proposed. The model is viable for choosing sugarcane varieties that would benefit sugarcane production and industrial systems, by reducing crop residue and increasing final energy production. (c) 2006 Published by Elsevier Ltd.
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Protein-energy malnutrition is a syndrome in which anaemia together with multivitamin and mineral deficiency may be present. The pathophysiological mechanisms involved have not, however, yet been completely elucidated. The aim of the present study was to evaluate the pathophysiological processes that occur in this anaemia in animals that were submitted to protein-energy malnutrition, in particular with respect to Fe concentration and the proliferative activity of haemopoietic cells. For this, histological, histochemical, cell culture and immunophenotyping techniques were used. Two-month-old male Swiss mice were submitted to protein-energy malnutrition with a low-protein diet (20g/kg) compared with control diet (400 g/kg). When the experimental group had attained a 20% loss of their original body weight, the animals from both groups received, intravenously, 20IU erythropoietin every other day for 14 d. Malnourished animals showed a decrease in red blood cells, Hb concentration and reticulocytopenia, as well as severe bone marrow and splenic atrophy. The results for serum Fe, total Fe-binding capacity, transferrin and erythropoietin in malnourished animals were no different from those of the control animals. Fe reserves in the spleen, liver and bone marrow were found to be greater in the malnourished animals. The mixed colony-forming unit assays revealed a smaller production of granulocyte-macrophage colony-forming units, erythroid burst-forming units, erythroid colony-forming units and CD45, CD117, CD119 and CD71 expression in the bone marrow and spleen cells of malnourished animals. These findings suggest that, in this protein-energy malnutrition model, anaemia is not caused by Fe deficiency or erythropoietin deficiency, but is a result of ineffective erythropoiesis.
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In order to determine the net energy, protein and macrominerals requirements of 70 to 120 day old, 52 female White New Zealand rabbits, weighing 1900g +/- 40g were used. At the beginning of the experimental period, 14 of the 52 young does were slaughtered and the 38 remaining animals were kept under two dietary management: ad libitum and restricted feeding. Slaughters were performed to determine each nutrient body content. The weight gain nutrient requirements depicted by the quantities of each nutrient stored into the body were obtained by applying the regression equation, which estimate the empty body nutrient content logarithm as a function of the empty body weight logarithm, as described by ARC (1980). By determining the heat production logarithm at the zero level of metabolizable energy intake, the maintenance net energy requirement was estimated to be 45.31 Kcal/day/Kg(0.75) the mean net energy. protein, calcium, phosphorous, sodium, magnesium and potassium requirements for each gram of weight gain per day were estimated to be, 2.51 Kcal, 0.21g, 0.02g, 0.005g, 0.001g, 0.0004g and 0.002g, respectively.
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A search motivated by supersymmetric models with light top squarks is presented using proton-proton collision data recorded with the CMS detector at a center-of-mass energy of √s=7 TeV during 2011, corresponding to an integrated luminosity of 4.98 fb-1. The analysis is based on final states with a single lepton, b-quark jets, and missing transverse energy. Standard model yields are predicted from data using two different approaches. The observed event numbers are found to be compatible with these predictions. Results are interpreted in the context of the constrained minimal supersymmetric standard model and of a simplified model with four top quarks in the final state. © 2013 CERN.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Models of daily energy requirement can help to establish better and more profitable feeding programs for poultry. Studies have been conducted at UNESP-Jaboticabal-Brazil with the aim of studying energy utilization in broiler breeders, laying hens, and broilers, and to establish metabolisable energy requirement models. The factorial approach was used to partition the energy requirements into maintenance, growth, and production components. The resulting models consider body weight, weight gain, egg production, and environmental temperature for the determination of the energy requirements of poultry. These models were evaluated in performance trials and provided good estimates. Therefore, they can be used to establish nutritional programs. The aim of this chapter is to describe the development of these models and to outline the results of our studies at UNESP.
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This study evaluated a nonlinear programming excel workbook PPFR (http://www.fmva.unesp.br/ppfr) for determining the optimum nutrient density and maximize margins. Two experiments were conducted with 240 one-day-old female chicks and 240 one-day-old male chicks distributed in 48 pens (10 chicks per pen, 4 replicates) in a completely randomized design. The treatments include the average price history (2009s and 2010s) for broiler increased and decreased by 25% or 50% (5 treatments to nonlinear feed formulation) and 1 linear feed formulation. Body gain, feed intake, feed conversion were measured at 21, 42 and 56 d of age. Chicks had ad libitum access to feed and water in floor pens with wood shavings as litter. The bio-economic Energy Conversion [BEC= (Total energy intake*Feed weighted cost per kg)/ (Weight gain*kg live chicken cost)] was more sensitive for measuring the bio-economic performance for broilers, and especially with better magnitude. This allowed a better assessment of profitability, the rate of growth and not just energy consumption, the production of broilers, by incorporating energy consumption, allowing for more sensitivity to the new index (BEC). The BEC was demonstrated that the principle of nonlinear formulation minimizes losses significantly (P<0.05), especially under unfavorable conditions the price of chicken in the market. Thus, when considering that a diet of energy supply shows up as the most expensive item of a formulation, it should compose necessarily the formula proposed for a bio-economic index. Thus, there is need to evaluate more accurately, not only the ingredients of a ration, but the impact of nutrients on the stability of a solution, mainly due to the energy requirement. This strategy promotes better accuracy for decision making under conditions of uncertainty, to find alternative post-formulation. From the above, both weight gain and feed conversion, as traditional performance indicators, cannot finalize or predict a performance evaluation of an economic system creating increasingly intense and competitive. Thus, the energy concentration of the diet becomes more important definition to feed formulator, by directly impact profit activity by interactions with the density of nutrients. This allowed a better evaluation of profitability, the rate of energy performance for broilers, by incorporating the energy consumption formula, allowing more sensitivity to the new index (BEC). These data show that nonlinear feed formulation is a toll to offer new opportunities for poultry production to improved profitability.
Glucocorticoid and Estrogen Receptors Are Reduced in Mitochondria of Lung Epithelial Cells in Asthma
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Mitochondrial glucocorticoid (mtGR) and estrogen (mtER) receptors participate in the coordination of the cell's energy requirement and in the mitochondrial oxidative phosphorylation enzyme (OXPHOS) biosynthesis, affecting reactive oxygen species (ROS) generation and induction of apoptosis. Although activation of mtGR and mtER is known to trigger anti-inflammatory signals, little information exists on the presence of these receptors in lung tissue and their role in respiratory physiology and disease. Using a mouse model of allergic airway inflammation disease and applying confocal microscopy, subcellular fractionation, and Western blot analysis we showed mitochondrial localization of GR alpha and ER beta in lung tissue. Allergic airway inflammation caused reduction in mtGR alpha, mtER beta, and OXPHOS enzyme biosynthesis in lung cells mitochondria and particularly in bronchial epithelial cells mitochondria, which was accompanied by decrease in lung mitochondrial mass and induction of apoptosis. Confirmation and validation of the reduction of the mitochondrial receptors in lung epithelial cells in human asthma was achieved by analyzing autopsies from fatal asthma cases. The presence of the mitochondrial GR alpha and ER beta in lung tissue cells and especially their reduction in bronchial epithelial cells during allergic airway inflammation suggests a crucial role of these receptors in the regulation of mitochondrial function in asthma, implicating their involvement in the pathophysiology of the disease.
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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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In this work the numerical coupling of thermal and electric network models with model equations for optoelectronic semiconductor devices is presented. Modified nodal analysis (MNA) is applied to model electric networks. Thermal effects are modeled by an accompanying thermal network. Semiconductor devices are modeled by the energy-transport model, that allows for thermal effects. The energy-transport model is expandend to a model for optoelectronic semiconductor devices. The temperature of the crystal lattice of the semiconductor devices is modeled by the heat flow eqaution. The corresponding heat source term is derived under thermodynamical and phenomenological considerations of energy fluxes. The energy-transport model is coupled directly into the network equations and the heat flow equation for the lattice temperature is coupled directly into the accompanying thermal network. The coupled thermal-electric network-device model results in a system of partial differential-algebraic equations (PDAE). Numerical examples are presented for the coupling of network- and one-dimensional semiconductor equations. Hybridized mixed finite elements are applied for the space discretization of the semiconductor equations. Backward difference formluas are applied for time discretization. Thus, positivity of charge carrier densities and continuity of the current density is guaranteed even for the coupled model.
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This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today’s most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today’s widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.
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The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.
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Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^
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A review of existing studies about LCA of PV systems has been carried out. The data from this review have been completed with our own figures in order to calculate the Energy Payback Time of double and horizontal axis tracking and fixed systems. The results of this metric span from 2 to 5 years for the latitude and global irradiation ranges of the geographical area comprised between −10◦ to 10◦ of longitude, and 30◦ to 45◦ of latitude. With the caution due to the uncertainty of the sources of information, these results mean that a GCPVS is able to produce back the energy required for its existence from 6 to 15 times during a life cycle of 30 years. When comparing tracking and fixed systems, the great importance of the PV generator makes advisable to dedicate more energy to some components of the system in order to increase the productivity and to obtain a higher performance of the component with the highest energy requirement. Both double axis and horizontal axis trackers follow this way, requiring more energy in metallic structure, foundations and wiring, but this higher contribution is widely compensated by the improved productivity of the system.