983 resultados para best linear unbiased predictor


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The superior cervical ganglion (SCG) in mammals varies in structure according to developmental age, body size, gender, lateral asymmetry, the size and nuclear content of neurons and the complexity and synaptic coverage of their dendritic trees. In small and medium-sized mammals, neuron number and size increase from birth to adulthood and, in phylogenetic studies, vary with body size. However, recent studies on larger animals suggest that body weight does not, in general, accurately predict neuron number. We have applied design-based stereological tools at the light-microscopic level to assess the volumetric composition of ganglia and to estimate the numbers and sizes of neurons in SCGs from rats, capybaras and horses. Using transmission electron microscopy, we have obtained design-based estimates of the surface coverage of dendrites by postsynaptic apposition zones and model-based estimates of the numbers and sizes of synaptophysin-labelled axo-dendritic synaptic disks. Linear regression analysis of log-transformed data has been undertaken in order to establish the nature of the relationships between numbers and SCG volume (V(scg)). For SCGs (five per species), the allometric relationship for neuron number (N) is N=35,067xV (scg) (0.781) and that for synapses is N=20,095,000xV (scg) (1.328) , the former being a good predictor and the latter a poor predictor of synapse number. Our findings thus reveal the nature of SCG growth in terms of its main ingredients (neurons, neuropil, blood vessels) and show that larger mammals have SCG neurons exhibiting more complex arborizations and greater numbers of axo-dendritic synapses.

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The objective was to evaluate the influence of dental metallic artefacts on implant sites using multislice and cone-beam computed tomography techniques. Ten dried human mandibles were scanned twice by each technique, with and without dental metallic artefacts. Metallic restorations were placed at the top of the alveolar ridge adjacent to the mental foramen region for the second scanning. Linear measurements (thickness and height) for each cross-section were performed by a single examiner using computer software. All mandibles were analysed at both the right and the left mental foramen regions. For the multislice technique, dental metallic artefact produced an increase of 5% in bone thickness and a reduction of 6% in bone height; no significant differences (p > 0.05) were detected when comparing measurements performed with and without metallic artefacts. With respect to the cone-beam technique, dental metallic artefact produced an increase of 6% in bone thickness and a reduction of 0.68% in bone height. No significant differences (p > 0.05) were observed when comparing measurements performed with and without metallic artefacts. The presence of dental metallic artefacts did not alter the linear measurements obtained with both techniques, although its presence made the location of the alveolar bone crest more difficult.

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Objective. The purpose of this research was to provide further evidence to demonstrate the precision and accuracy of maxillofacial linear and angular measurements obtained by cone-beam computed tomography (CBCT) images. Study design. The study population consisted of 15 dry human skulls that were submitted to CBCT, and 3-dimensional (3D) images were generated. Linear and angular measurements based on conventional craniometric anatomical landmarks, and were identified in 3D-CBCT images by 2 radiologists twice each independently. Subsequently, physical measurements were made by a third examiner using a digital caliper and a digital goniometer. Results. The results demonstrated no statistically significant difference between inter-and intra-examiner analysis. Regarding accuracy test, no statistically significant differences were found of the comparison between the physical and CBCT-based linear and angular measurements for both examiners (P = .968 and .915, P = .844 and .700, respectively). Conclusions. 3D-CBCT images can be used to obtain dimensionally accurate linear and angular measurements from bony maxillofacial structures and landmarks. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2009; 108: 430-436)

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The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.

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Ussing [1] considered the steady flux of a single chemical component diffusing through a membrane under the influence of chemical potentials and derived from his linear model, an expression for the ratio of this flux and that of the complementary experiment in which the boundary conditions were interchanged. Here, an extension of Ussing's flux ratio theorem is obtained for n chemically interacting components governed by a linear system of diffusion-migration equations that may also incorporate linear temporary trapping reactions. The determinants of the output flux matrices for complementary experiments are shown to satisfy an Ussing flux ratio formula for steady state conditions of the same form as for the well-known one-component case. (C) 2000 Elsevier Science Ltd. All rights reserved.

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A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

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Any given n X n matrix A is shown to be a restriction, to the A-invariant subspace, of a nonnegative N x N matrix B of spectral radius p(B) arbitrarily close to p(A). A difference inclusion x(k+1) is an element of Ax(k), where A is a compact set of matrices, is asymptotically stable if and only if A can be extended to a set B of nonnegative matrices B with \ \B \ \ (1) < 1 or \ \B \ \ (infinity) < 1. Similar results are derived for differential inclusions.

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A question is examined as to estimates of the norms of perturbations of a linear stable dynamic system, under which the perturbed system remains stable in a situation R:here a perturbation has a fixed structure.

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We study the scattering of the quantized electromagnetic field from a linear, dispersive dielectric using the scattering formalism for quantum fields. The medium is modeled as a collection of harmonic oscillators with a number of distinct resonance frequencies. This model corresponds to the Sellmeir expansion, which is widely used to describe experimental data for real dispersive media. The integral equation for the interpolating field in terms of the in field is solved and the solution used to find the out field. The relation between the ill and out creation and annihilation operators is found that allows one to calculate the S matrix for this system. In this model, we find that there are absorption bands, but the input-output relations are completely unitary. No additional quantum-noise terms are required.

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Despite their limitations, linear filter models continue to be used to simulate the receptive field properties of cortical simple cells. For theoreticians interested in large scale models of visual cortex, a family of self-similar filters represents a convenient way in which to characterise simple cells in one basic model. This paper reviews research on the suitability of such models, and goes on to advance biologically motivated reasons for adopting a particular group of models in preference to all others. In particular, the paper describes why the Gabor model, so often used in network simulations, should be dropped in favour of a Cauchy model, both on the grounds of frequency response and mutual filter orthogonality.

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