225 resultados para Linear function

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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In the late seventies, Megiddo proposed a way to use an algorithm for the problem of minimizing a linear function a(0) + a(1)x(1) + ... + a(n)x(n) subject to certain constraints to solve the problem of minimizing a rational function of the form (a(0) + a(1)x(1) + ... + a(n)x(n))/(b(0) + b(1)x(1) + ... + b(n)x(n)) subject to the same set of constraints, assuming that the denominator is always positive. Using a rather strong assumption, Hashizume et al. extended Megiddo`s result to include approximation algorithms. Their assumption essentially asks for the existence of good approximation algorithms for optimization problems with possibly negative coefficients in the (linear) objective function, which is rather unusual for most combinatorial problems. In this paper, we present an alternative extension of Megiddo`s result for approximations that avoids this issue and applies to a large class of optimization problems. Specifically, we show that, if there is an alpha-approximation for the problem of minimizing a nonnegative linear function subject to constraints satisfying a certain increasing property then there is an alpha-approximation (1 1/alpha-approximation) for the problem of minimizing (maximizing) a nonnegative rational function subject to the same constraints. Our framework applies to covering problems and network design problems, among others.

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Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the past decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of an active dendritic tree is a highly non-linear function of its afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease in dynamic range.

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Bose-Einstein correlations of charged kaons are used to probe Au+Au collisions at s(NN)=200 GeV and are compared to charged pion probes, which have a larger hadronic scattering cross section. Three-dimensional Gaussian source radii are extracted, along with a one-dimensional kaon emission source function. The centrality dependences of the three Gaussian radii are well described by a single linear function of N(part)(1/3) with a zero intercept. Imaging analysis shows a deviation from a Gaussian tail at r greater than or similar to 10 fm, although the bulk emission at lower radius is well described by a Gaussian. The presence of a non-Gaussian tail in the kaon source reaffirms that the particle emission region in a heavy-ion collision is extended, and that similar measurements with pions are not solely due to the decay of long-lived resonances.

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Two ureolytic strains, B. sphaericus LMG 22257 and Bacillus sp (I-001), were tested for their ability to consolidate sand by submitting them to two days` treatment using 10(7) viable cell concentrations of inocula and medium precipitation with calcium ions. The results showed that B. sphaericus LMG 22257 induced greater calcium carbonate formation. Both strains produced calcite and were able to consolidate sand. Tensile strength of consolidated sand was not a function of the amount of precipitated CaCO(3) but a linear function of the ratio bioconsolidation index (BC) defined as the ratio of CaCO(3) volume to initial sand porosity. A simple model to estimate the engineering benefits of consolidation is proposed. (C) 2011 Elsevier B.V. All rights reserved.

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The functional relation between the decline in the rate of a physiological process and the magnitude of a stress related to soil physical conditions is an important tool for uses as diverse as assessment of the stress-related sensitivity of different plant cultivars and characterization of soil structure. Two of the most pervasive sources of stress are soil resistance to root penetration (SR) and matric potential (psi). However, the assessment of these sources of stress on physiological processes in different soils can be complicated by other sources of stress and by the strong relation between SR and psi in a soil. A multivariate boundary line approach was assessed as a means of reducing these cornplications. The effects of SR and psi stress conditions on plant responses were examined under growth chamber conditions. Maize plants (Zea mays L.) were grown in soils at different water contents and having different structures arising from variation in texture, organic carbon content and soil compaction. Measurements of carbon exchange (CE), leaf transpiration (ILT), plant transpiration (PT), leaf area (LA), leaf + shoot dry weight (LSDW), root total length (RTL), root surface area (RSA) and root dry weight (RDW) were determined after plants reached the 12-leaf stage. The LT, PT and LA were described as a function of SR and psi with a double S-shaped function using the multivariate boundary line approach. The CE and LSDW were described by the combination of an S-shaped function for SR and a linear function for psi. The root parameters were described by a single S-shaped function for SR. The sensitivity to SR and psi depended on the plant parameter. Values of PT, LA and LSDW were most sensitive to SR. Among those parameters exhibiting a significant response to psi, PT was most sensitive. The boundary line approach was found to be a useful tool to describe the functional relation between the decline in the rate of a physiological process and the magnitude of a stress related to soil physical conditions. (C) 2009 Elsevier B.V. All rights reserved.

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We present measurements of J/psi yields in d + Au collisions at root S(NN) = 200 GeV recorded by the PHENIX experiment and compare them with yields in p + p collisions at the same energy per nucleon-nucleon collision. The measurements cover a large kinematic range in J/psi rapidity (-2.2 < y < 2.4) with high statistical precision and are compared with two theoretical models: one with nuclear shadowing combined with final state breakup and one with coherent gluon saturation effects. In order to remove model dependent systematic uncertainties we also compare the data to a simple geometric model. The forward rapidity data are inconsistent with nuclear modifications that are linear or exponential in the density weighted longitudinal thickness, such as those from the final state breakup of the bound state.

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The objective of this paper is two-fold: firstly, we develop a local and global (in time) well-posedness theory for a system describing the motion of two fluids with different densities under capillary-gravity waves in a deep water flow (namely, a Schrodinger-Benjamin-Ono system) for low-regularity initial data in both periodic and continuous cases; secondly, a family of new periodic traveling waves for the Schrodinger-Benjamin-Ono system is given: by fixing a minimal period we obtain, via the implicit function theorem, a smooth branch of periodic solutions bifurcating a Jacobian elliptic function called dnoidal, and, moreover, we prove that all these periodic traveling waves are nonlinearly stable by perturbations with the same wavelength.

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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

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We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

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Nutrition in bean plants and anthracnose intensity in function of silicon and copper application. The objective of this work was to evaluate the effect of calcium silicate and copper sulfate on anthracnose intensity and nutrition of bean plants. The experiment was conducted using an experimental design in randomized blocks following a 4 x 4 factorial arrangement , (four levels of calcium silicate and four levels of copper sulfate) and two additional treatments (plants without inoculation and plants sprinkled with Benomyl). Four evaluations of the incidence and severity of anthracnose were done, in addition to measuring, total leaf area. At the end of the evaluations, incidence: and data were integrated over time, obtaining the area under disease progress curve (AUDPC). Contents of N, P, K, Ca, Mg, B, Cu, Fe, Mn, Zn, Si and lignin were determined in the aerial Part. A linear decrease of the intensity AUDPC was observed with the increase of the doses of calcium silicate. The severity AUDPC was influenced by the doses of copper, obtaining a reduction of 35% on the higher dosage. The supply of silicon and copper altered the content of the K, mg, S, Zn, Ca and Si in the aerial part of the bean plants.

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Background and Aim: It is unclear to what extent diabetes modulates the ageing-related adaptations of cardiac geometry and function. Methods and Results: We examined 1005 adults, aged 25-74 years, from a population-based survey at baseline in 1994/5 and at follow-up in 2004/5. We compared persistently non-diabetic individuals (ND; no diabetes at baseline and at follow-up, n = 833) with incident (ID; non-diabetic at baseline and diabetic at follow-up, n = 36) and with prevalent diabetics (PD; diabetes at baseline and follow-up examination, n = 21). Left ventricular (LV) geometry and function were evaluated by echocardiography. Statistical analyses were performed with multivariate linear regression models. Over ten years the PD group displayed a significantly stronger relative increase of LV mass (+9.34% vs. +23.7%) that was mediated by a more pronounced increase of LV end-diastolic diameter (+0% vs. +6.95%) compared to the ND group. In parallel, LA diameter increased (+4.50% vs. +12.7%), whereas ejection fraction decreased (+3.02% vs. -4.92%) more significantly in the PD group. Moreover, at the follow-up examination the PD and ID groups showed a significantly worse diastolic function, indicated by a higher E/EM ratio compared with the ND group (11.6 and 11.8 vs. 9.79, respectively). Conclusions: Long-standing diabetes was associated with an acceleration of age-related changes of left ventricular geometry accumulating in an eccentric remodelling of the left ventricle. Likewise, echocardiographic measures of systolic and diastolic ventricular function deteriorated more rapidly in individuals with diabetes. (C) 2009 Elsevier B.V. All rights reserved.

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Context: Cannabis sativa use can impair verbal learning, provoke acute psychosis, and increase the risk of schizophrenia. It is unclear where C sativa acts in the human brain to modulate verbal learning and to induce psychotic symptoms. Objectives: To investigate the effects of 2 main psychoactive constituents of C sativa, Delta 9-tetrahydrocannabinol (Delta 9-THC) and cannabidiol, on regional brain function during verbal paired associate learning. Design: Subjects were studied on 3 separate occasions using a block design functional magnetic resonance imaging paradigm while performing a verbal paired associate learning task. Each imaging session was preceded by the ingestion of Delta 9-THC (10 mg), cannabidiol (600 mg), or placebo in a double-blind, randomized, placebo-controlled, repeated-measures, within-subject design. Setting: University research center. Participants: Fifteen healthy, native English-speaking, right-handed men of white race/ethnicity who had used C sativa 15 times or less and had minimal exposure to other illicit drugs in their lifetime. Main Outcome Measures: Regional brain activation ( blood oxygen level-dependent response), performance in a verbal learning task, and objective and subjective ratings of psychotic symptoms, anxiety, intoxication, and sedation. Results: Delta 9-Tetrahydrocannabinol increased psychotic symptoms and levels of anxiety, intoxication, and sedation, whereas no significant effect was noted on these parameters following administration of cannabidiol. Performance in the verbal learning task was not significantly modulated by either drug. Administration of Delta 9-THC augmented activation in the parahippocampal gyrus during blocks 2 and 3 such that the normal linear decrement in activation across repeated encoding blocks was no longer evident. Delta 9-Tetrahydrocannabinol also attenuated the normal time-dependent change in ventrostriatal activation during retrieval of word pairs, which was directly correlated with concurrently induced psychotic symptoms. In contrast, administration of cannabidiol had no such effect. Conclusion: The modulation of mediotemporal and ventrostriatal function by Delta 9-THC may underlie the effects of C sativa on verbal learning and psychotic symptoms, respectively.

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Electromagnetic induction (EMI) method results are shown for vertical magnetic dipole (VMD) configuration by using the EM38 equipment. Performance in the location of metallic pipes and electrical cables is compared as a function of instrumental drift correction by linear and quadratic adjusting under controlled conditions. Metallic pipes and electrical cables are buried at the IAG/USP shallow geophysical test site in Sao Paulo City. Brazil. Results show that apparent electrical conductivity and magnetic susceptibility data were affected by ambient temperature variation. In order to obtain better contrast between background and metallic targets it was necessary to correct the drift. This correction was accomplished by using linear and quadratic relation between conductivity/susceptibility and temperature intending comparative studies. The correction of temperature drift by using a quadratic relation was effective, showing that all metallic targets were located as well deeper targets were also improved. (C) 2010 Elsevier B.V. All rights reserved.

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A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

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The concept of Fock space representation is developed to deal with stochastic spin lattices written in terms of fermion operators. A density operator is introduced in order to follow in parallel the developments of the case of bosons in the literature. Some general conceptual quantities for spin lattices are then derived, including the notion of generating function and path integral via Grassmann variables. The formalism is used to derive the Liouvillian of the d-dimensional Linear Glauber dynamics in the Fock-space representation. Then the time evolution equations for the magnetization and the two-point correlation function are derived in terms of the number operator. (C) 2008 Elsevier B.V. All rights reserved.