924 resultados para Limited dependent variable regression


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Pós-graduação em Enfermagem (mestrado profissional) - FMB

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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To assess the influence of anatomic location on the relationship between computed tomography (CT) number and X-ray attenuation in limited and medium field-of-view (FOV) scans. Materials and Methods Tubes containing solutions with different concentrations of K2HPO4 were placed in the tooth sockets of a human head phantom. Cone-beam computed tomography (CBCT) scans were acquired, and CT numbers of the K2HPO4 solutions were measured. The relationship between CT number and K2HPO4 concentration was examined by linear regression analyses. Then, the variation in CT number according to anatomic location was examined. Results The relationship between K2HPO4 concentration and CT number was strongly linear. The slopes of the linear regressions for the limited FOVs were almost 2-fold lower than those for the medium FOVs. The absolute CT number differed between imaging protocols and anatomic locations. Conclusion There is a strong linear relationship between X-ray attenuation and CT number. The specific imaging protocol and anatomic location of the object strongly influence this relationship.

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

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The number of electronic devices connected to agricultural machinery is increasing to support new agricultural practices tasks related to the Precision Agriculture such as spatial variability mapping and Variable Rate Technology (VRT). The Distributed Control System (DCS) is a suitable solution for decentralization of the data acquisition system and the Controller Area Network (CAN) is the major trend among the embedded communications protocols for agricultural machinery and vehicles. The application of soil correctives is a typical problem in Brazil. The efficiency of this correction process is highly dependent of the inputs way at soil and the occurrence of errors affects directly the agricultural yield. To handle this problem, this paper presents the development of a CAN-based distributed control system for a VRT system of soil corrective in agricultural machinery. The VRT system is composed by a tractor-implement that applies a desired rate of inputs according to the georeferenced prescription map of the farm field to support PA (Precision Agriculture). The performance evaluation of the CAN-based VRT system was done by experimental tests and analyzing the CAN messages transmitted in the operation of the entire system. The results of the control error according to the necessity of agricultural application allow conclude that the developed VRT system is suitable for the agricultural productions reaching an acceptable response time and application error. The CAN-Based DCS solution applied in the VRT system reduced the complexity of the control system, easing the installation and maintenance. The use of VRT system allowed applying only the required inputs, increasing the efficiency operation and minimizing the environmental impact.

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Habitat use by Sharp-tailed Tyrant (Culicivora caudacuta), and Cock-tailed Tyrant (Alectrurus tricolor) in the Cerrado of Southeastern Brazil. Obligatory grassland birds are dependent on a limited set of native habitats that are disappearing almost everywhere. We examined the use of macrohabitat and microhabitat by two threatened species of flycatchers, the Sharp-tailed Tyrant, Culicivora caudacuta and the Cock-tailed Tyrant, Alectrurus tricolor in a preserved area of cerrado. We generated logistic regression models to explain the presence of these species through variables of microhabitat. Both flycatchers occurred mainly in grassland areas and favored areas with a low density of palms (Attalea geraensis) and trees. The Sharp-tailed Tyrant also favored areas with a high density of low shrubs (< 1 m) and less exposed soil. The positive relationship found between the presence of Sharp-tailed Tyrant and soil cover may indicate the importance of litter and understory vegetation for shelter and food. The conservation of both flycatcher species in the study area should benefit from controlling palm density and the maintenance of grasslands with low shrubs.

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Fundamental principles of mechanics were primarily conceived for constant mass systems. Since the pioneering works of Meshcherskii (see historical review in Mikhailov (Mech. Solids 10(5):32-40, 1975), efforts have been made in order to elaborate an adequate mathematical formalism for variable mass systems. This is a current research field in theoretical mechanics. In this paper, attention is focused on the derivation of the so-called 'generalized canonical equations of Hamilton' for a variable mass particle. The applied technique consists in the consideration of the mass variation process as a dissipative phenomenon. Kozlov's (Stek. Inst. Math 223:178-184, 1998) method, originally devoted to the derivation of the generalized canonical equations of Hamilton for dissipative systems, is accordingly extended to the scenario of variable mass systems. This is done by conveniently writing the flux of kinetic energy from or into the variable mass particle as a 'Rayleigh-like dissipation function'. Cayley (Proc. R Soc. Lond. 8:506-511, 1857) was the first scholar to propose such an analogy. A deeper discussion on this particular subject will be left for a future paper.

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Osteoporotic hip fractures (OHF) are not limited to elderly; however, studies in non-elderly are scarce. Thus, the aim of this study was to evaluate co-morbidities in non-elderly patients with OHF in a Community Teaching Hospital. All hospitalizations due to OHF during a 3-year period in a Community Teaching Hospital were retrospectively evaluated for co-morbidities, and patients 18-64 years old were compared with those a parts per thousand yen65 years old. Of all hospitalizations, 232 (0.73%) were due to hip fractures, and 120/232 (51.7%) patients had OHF. The comparison of the 13 (10.8%) OHF patients < 65 years old (47.3 +/- A 9.7 years) with 107 (89.2%) a parts per thousand yen65 years old (80.4 +/- A 7.7 years) revealed a male predominance (61.5 vs. 27.1%, P = 0.022) and a distinct ethnic distribution with a lower proportion of Caucasians in the former (61.5 vs. 86.9%, P = 0.033). Moreover, non-elderly OHF patients had higher frequencies of insulin-dependent DM (38.5 vs. 3.7%, P = 0.001) and alcoholism (38.5 vs. 4.7%, P = 0.001) than aged patients. In contrast, rates of age-related co-morbidities such as stroke (7.7 vs. 18.7%, P = 0.461), heart failure (23.1 vs. 14.0%, P = 0.411), and dementia (7.7 vs. 15.9%, P = 0.689) were comparable in both groups. Logistic regression analysis demonstrated that insulin-dependent DM (OR = 25.4, 95% CI = 4.7-136.8, P < 0.001) and alcoholism (OR = 20.3, 95% CI = 3.9-103.3, P < 0.001) remained as independent risk factors for OHF in non-elderly patients. Osteoporosis is an important cause of HF in Community Hospital. Non-elderly patients with OHF have a peculiar demographic profile and associated co-morbidities. These findings reinforce the need of early osteoporosis diagnosis and rigorous fracture prevention in patients with DM and alcoholism.

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Yield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor.

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Within the nutritional context, the supplementation of microminerals in bird food is often made in quantities exceeding those required in the attempt to ensure the proper performance of the animals. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.

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Further advances in magnetic hyperthermia might be limited by biological constraints, such as using sufficiently low frequencies and low field amplitudes to inhibit harmful eddy currents inside the patient's body. These incite the need to optimize the heating efficiency of the nanoparticles, referred to as the specific absorption rate (SAR). Among the several properties currently under research, one of particular importance is the transition from the linear to the non-linear regime that takes place as the field amplitude is increased, an aspect where the magnetic anisotropy is expected to play a fundamental role. In this paper we investigate the heating properties of cobalt ferrite and maghemite nanoparticles under the influence of a 500 kHz sinusoidal magnetic field with varying amplitude, up to 134 Oe. The particles were characterized by TEM, XRD, FMR and VSM, from which most relevant morphological, structural and magnetic properties were inferred. Both materials have similar size distributions and saturation magnetization, but strikingly different magnetic anisotropies. From magnetic hyperthermia experiments we found that, while at low fields maghemite is the best nanomaterial for hyperthermia applications, above a critical field, close to the transition from the linear to the non-linear regime, cobalt ferrite becomes more efficient. The results were also analyzed with respect to the energy conversion efficiency and compared with dynamic hysteresis simulations. Additional analysis with nickel, zinc and copper-ferrite nanoparticles of similar sizes confirmed the importance of the magnetic anisotropy and the damping factor. Further, the analysis of the characterization parameters suggested core-shell nanostructures, probably due to a surface passivation process during the nanoparticle synthesis. Finally, we discussed the effect of particle-particle interactions and its consequences, in particular regarding discrepancies between estimated parameters and expected theoretical predictions. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi. org/10.1063/1.4739533]

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Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

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This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.