35 resultados para index model


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The objective of this work was to evaluate the Nelore beef cattle, growth curve parameters using the Von Bertalanffy function in a nested Bayesian procedure that allowed estimation of the joint posterior distribution of growth curve parameters, their (co)variance components, and the environmental and additive genetic components affecting them. A hierarchical model was applied; each individual had a growth trajectory described by the nonlinear function, and each parameter of this function was considered to be affected by genetic and environmental effects that were described by an animal model. Random samples of the posterior distributions were drawn using Gibbs sampling and Metropolis-Hastings algorithms. The data set consisted of a total of 145,961 BW recorded from 15,386 animals. Even though the curve parameters were estimated for animals with few records, given that the information from related animals and the structure of systematic effects were considered in the curve fitting, all mature BW predicted were suitable. A large additive genetic variance for mature BW was observed. The parameter a of growth curves, which represents asymptotic adult BW, could be used as a selection criterion to control increases in adult BW when selecting for growth rate. The effect of maternal environment on growth was carried through to maturity and should be considered when evaluating adult BW. Other growth curve parameters showed small additive genetic and maternal effects. Mature BW and parameter k, related to the slope of the curve, presented a large, positive genetic correlation. The results indicated that selection for growth rate would increase adult BW without substantially changing the shape of the growth curve. Selection to change the slope of the growth curve without modifying adult BW would be inefficient because their genetic correlation is large. However, adult BW could be considered in a selection index with its corresponding economic weight to improve the overall efficiency of beef cattle production.

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The modified Cam - Clay model was used to model experimental results of a saturated residual sandy soil from Sao Carlos - SP. Triaxial compression tests were performed using Bishop - Wesley cell with internal transducers to measure axial and radial strains. It was observed that the model fairly fitted experimental results, specially the principal stress difference at critical state. In general it was observed a good qualitative agreement between experimental and predicted strain values, considering compression or expansion of the samples. However, in all the stress path used, but 100 degrees and 140 degrees, the model yielded strains larger than that measured in the tests.

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Tsallis postulated a generalized form for entropy and give rise to a new statistics now known as Tsallis statistics. In the present work, we compare the Tsallis statistics with the gradually truncated Levy flight, and discuss the distribution of an economical index-the Standard and Poor's 500-using the values of standard deviation as calculated by our model. We find that both statistics give almost the same distribution. Thus we feel that gradual truncation of Levy distribution, after certain critical step size for describing complex systems, is a requirement of generalized thermodynamics or similar. The gradually truncated Levy flight is based on physical considerations and bring a better physical picture of the dynamics of the whole system. Tsallis statistics gives a theoretical support. Both statistics together can be utilized for the development of a more exact portfolio theory or to understand better the complexities in human and financial behaviors. A comparison of both statistics is made. (C) 2002 Published by Elsevier B.V. B.V.

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The paper presents a constructive heuristic algorithm (CHA) for solving directly the long-term transmission-network-expansion-planning (LTTNEP) problem using the DC model. The LTTNEP is a very complex mixed-integer nonlinear-programming problem and presents a combinatorial growth in the search space. The CHA is used to find a solution for the LTTNEP problem of good quality. A sensitivity index is used in each step of the CHA to add circuits to the system. This sensitivity index is obtained by solving the relaxed problem of LTTNEP, i.e. considering the number of circuits to be added as a continuous variable. The relaxed problem is a large and complex nonlinear-programming problem and was solved through the interior-point method (IPM). Tests were performed using Garver's system, the modified IEEE 24-Bus system and the Southern Brazilian reduced system. The results presented show the good performance of IPM inside the CHA.

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The generation expansion planning (GEP) problem consists in determining the type of technology, size, location and time at which new generation units must be integrated to the system, over a given planning horizon, to satisfy the forecasted energy demand. Over the past few years, due to an increasing awareness of environmental issues, different approaches to solve the GEP problem have included some sort of environmental policy, typically based on emission constraints. This paper presents a linear model in a dynamic version to solve the GEP problem. The main difference between the proposed model and most of the works presented in the specialized literature is the way the environmental policy is envisaged. Such policy includes: i) the taxation of CO(2) emissions, ii) an annual Emissions Reduction Rate (ERR) in the overall system, and iii) the gradual retirement of old inefficient generation plants. The proposed model is applied in an 11-region to design the most cost-effective and sustainable 10-technology US energy portfolio for the next 20 years.

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When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The trial and error approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. © 2011 Elsevier Inc.

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This paper presents a power system capacity expansion planning modelconsidering carbon emissions constraints. In addition to the traditionaltechnical and economical issues usually considered in the planning process, two environmental policies that consist on the taxation and the annual limitsof carbon dioxide (CO 2) emissions are considered. Furthermore, the gradualretirement of old inefficient generation plants has been included. The approachguarantees a cleaner electricity production in the expanded power system ata relatively low cost. The proposed model considers the transmission systemand is applied to a 4-region and 11-region power systems over a 20-yearplanning horizon. Results show practical investment decisions in terms of sustainability and costs.

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This study is aimed to analyze the thermal comfort in different areas in the city of São Paulo. Two different areas were selected, a densely built (Consolação district) and the other was Fontes do Ipiranga State Park (FISP), an area with only a few buildings and reduced impermeability. A micro-climatic ENVImet was used to simulate the interaction surface-atmosphere in the urban environment. The model resolution is between 0.5 and 10m. This model was developed by Bruse and Fleer (1998) and Bruse (2004). Through the thermal comfort index PMV (predicted mean vote) and MRT (mean radiant temperature) provided by the model, it revealed that the State Park displays PMV values close to comfortable compared to the other studied area. The analysis of thermal comfort index and the Wind flow showed the influence of high buildings in the local climatic environment.

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In this paper, a hybrid heuristic methodology that employs fuzzy logic for solving the AC transmission network expansion planning (AC-TEP) problem is presented. An enhanced constructive heuristic algorithm aimed at obtaining a significant quality solution for such complicated problems considering contingency is proposed. In order to indicate the severity of the contingency, 2 performance indices, namely the line flow performance index and voltage performance index, are calculated. An interior point method is applied as a nonlinear programming solver to handle such nonconvex optimization problems, while the objective function includes the costs of the new transmission lines as well as the real power losses. The performance of the proposed method is examined by applying it to the well-known Garver system for different cases. The simulation studies and result analysis demonstrate that the proposed method provides a promising way to find an optimal plan. Obtaining the best quality solution shows the capability and the viability of the proposed algorithm in AC-TEP. © Tübi̇tak..

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aim of this study was to assess the validity and reliability of the Fonseca Anamnestic Index (IAF), used to assess the severity of temporomandibular disorders, applied to Brazilian women. We used a probabilistic sampling design. The participants were 700 women over 18 years of age, living in the city of Araraquara (SP). The IAF questionnaire was applied by telephone interviews. We conducted Confirmatory Factor Analysis (CFA) using Chi-Square Over Degrees of Freedom (χ2/df), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA) as goodness of fit indices. We calculated the convergent validity, the average variance extracted (AVE) and the composite reliability (CR). Internal consistency was assessed by Cronbach's alpha coefficient (α).The factorial weights of questions 8 and 10 were below the adequate values. Thus, we refined the original model and these questions were excluded. The resulting factorial model showed appropriate goodness of fit to the sample (χ2/df = 3.319, CFI = 0.978, TLI = 0.967, RMSEA = 0.058). The convergent validity (AVE = 0.513, CR = 0.878) and internal consistency (α = 0.745) were adequate. The reduced IAF version showed adequate validity and reliability in a sample of Brazilian women.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Background: Cancer pain severely limits function and significantly reduces quality of life. Subtypes of sensory neurons involved in cancer pain and proliferation are not clear.Methods: We produced a cancer model by inoculating human oral squamous cell carcinoma (SCC) cells into the hind paw of athymic mice. We quantified mechanical and thermal nociception using the paw withdrawal assays. Neurotoxins isolectin B4-saporin (IB4-SAP), or capsaicin was injected intrathecally to selectively ablate IB4(+) neurons or TRPV1(+) neurons, respectively. JNJ-17203212, a TRPV1 antagonist, was also injected intrathecally. TRPV1 protein expression in the spinal cord was quantified with western blot. Paw volume was measured by a plethysmometer and was used as an index for tumor size. Ki-67 immunostaining in mouse paw sections was performed to evaluate cancer proliferation in situ.Results: We showed that mice with SCC exhibited both mechanical and thermal hypersensitivity. Selective ablation of IB4(+) neurons by IB4-SAP decreased mechanical allodynia in mice with SCC. Selective ablation of TRPV1(+) neurons by intrathecal capsaicin injection, or TRPV1 antagonism by JNJ-17203212 in the IB4-SAP treated mice completely reversed SCC-induced thermal hyperalgesia, without affecting mechanical allodynia. Furthermore, TRPV1 protein expression was increased in the spinal cord of SCC mice compared to normal mice. Neither removal of IB4(+) or TRPV1(+) neurons affected SCC proliferation.Conclusions: We show in a mouse model that IB4(+) neurons play an important role in cancer-induced mechanical allodynia, while TRPV1 mediates cancer-induced thermal hyperalgesia. Characterization of the sensory fiber subtypes responsible for cancer pain could lead to the development of targeted therapeutics.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)