35 resultados para coeficiente de Poisson
Resumo:
The ultrasonic measurement and imaging of tissue elasticity is currently under wide investigation and development as a clinical tool for the assessment of a broad range of diseases, but little account in this field has yet been taken of the fact that soft tissue is porous and contains mobile fluid. The ability to squeeze fluid out of tissue may have implications for conventional elasticity imaging, and may present opportunities for new investigative tools. When a homogeneous, isotropic, fluid-saturated poroelastic material with a linearly elastic solid phase and incompressible solid and fluid constituents is subjected to stress, the behaviour of the induced internal strain field is influenced by three material constants: the Young's modulus (E(s)) and Poisson's ratio (nu(s)) of the solid matrix and the permeability (k) of the solid matrix to the pore fluid. New analytical expressions were derived and used to model the time-dependent behaviour of the strain field inside simulated homogeneous cylindrical samples of such a poroelastic material undergoing sustained unconfined compression. A model-based reconstruction technique was developed to produce images of parameters related to the poroelastic material constants (E(s), nu(s), k) from a comparison of the measured and predicted time-dependent spatially varying radial strain. Tests of the method using simulated noisy strain data showed that it is capable of producing three unique parametric images: an image of the Poisson's ratio of the solid matrix, an image of the axial strain (which was not time-dependent subsequent to the application of the compression) and an image representing the product of the aggregate modulus E(s)(1-nu(s))/(1+nu(s))(1-2nu(s)) of the solid matrix and the permeability of the solid matrix to the pore fluid. The analytical expressions were further used to numerically validate a finite element model and to clarify previous work on poroelastography.
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Aims/hypothesis: We investigated the association between the incidence of type 1 diabetes mellitus and remoteness (a proxy measure for exposure to infections) using recently developed techniques for statistical analysis of small-area data.
Subjects, materials and methods: New cases in children aged 0 to 14 years in Northern Ireland were prospectively registered from 1989 to 2003. Ecological analysis was conducted using small geographical units (582 electoral wards) and area characteristics including remoteness, deprivation and child population density. Analysis was conducted using Poisson regression models and Bayesian
hierarchical models to allow for spatially correlated risks that were potentially caused by unmeasured explanatory variables.
Results: In Northern Ireland between 1989 and 2003, there were 1,433 new cases of type 1 diabetes, giving a directly standardised incidence rate of 24.7 per 100,000 personyears. Areas in the most remote fifth of all areas had a significantly (p=0.0006) higher incidence of type 1 diabetes mellitus (incidence rate ratio=1.27 [95% CI 1.07, 1.50]) than those in the most accessible fifth of all areas. There was also a higher incidence rate in areas that were less deprived (p<0.0001) and less densely populated (p=0.002). After adjustment for deprivation and additional adjustment for child population density the association between diabetes and remoteness remained significant (p=0.01 and p=0.03, respectively).
Conclusions/interpretation: In Northern Ireland, there is evidence that remote areas experience higher rates of type 1 diabetes mellitus. This could reflect a reduced or delayed exposure to infections, particularly early in life, in these areas.
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The chaotic profile of dust grain dynamics associated with dust-acoustic oscillations in a dusty plasma is considered. The collective behaviour of the dust plasma component is described via a multi-fluid model, comprising Boltzmann distributed electrons and ions, as well as an equation of continuity possessing a source term for the dust grains, the dust momentum and Poisson's equations. A Van der Pol–Mathieu-type nonlinear ordinary differential equation for the dust grain density dynamics is derived. The dynamical system is cast into an autonomous form by employing an averaging method. Critical stability boundaries for a particular trivial solution of the governing equation with varying parameters are specified. The equation is analysed to determine the resonance region, and finally numerically solved by using a fourth-order Runge–Kutta method. The presence of chaotic limit cycles is pointed out.
Resumo:
The nonlinear properties of two-dimensional cylindrical quantum dust-ion-acoustic (QDIA) and quantum dust-acoustic (QDA) waves are studied in a collisionless, unmagnetized and dense (quantum) dusty plasma. For this purpose, the reductive perturbation technique is employed to the quantum hydrodynamical equations and the Poisson equation, obtaining the cylindrical Kadomtsev–Petviashvili (CKP) equations. The effects of quantum diffraction, as well as quantum statistical and geometric effects on the profiles of QDIA and QDA solitary waves are examined. It is found that the amplitudes and widths of the nonplanar QDIA and QDA waves are significantly affected by the quantum electron tunneling effect. The addition of a dust component to a quantum plasma is seen to affect the propagation characteristics of localized QDIA excitations. In the case of low-frequency QDA waves, this effect is even stronger, since the actual form of the potential solitary waves, in fact, depends on the dust charge polarity (positive/negative) itself (allowing for positive/negative potential forms, respectively). The relevance of the present investigation to metallic nanostructures is highlighted.
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A method is proposed to accelerate the evaluation of the Green's function of an infinite double periodic array of thin wire antennas. The method is based on the expansion of the Green's function into series corresponding to the propagating and evanescent waves and the use of Poisson and Kummer transformations enhanced with the analytic summation of the slowly convergent asymptotic terms. Unlike existing techniques the procedure reported here provides uniform convergence regardless of the geometrical parameters of the problem or plane wave excitation wavelength. In addition, it is numerically stable and does not require numerical integration or internal tuning parameters, since all necessary series are directly calculated in terms of analytical functions. This means that for nonlinear problem scenarios that the algorithm can be deployed without run time intervention or recursive adjustment within a harmonic balance engine. Numerical examples are provided to illustrate the efficiency and accuracy of the developed approach as compared with the Ewald method for which these classes of problems requires run time splitting parameter adaptation.
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In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.
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Evidence is unclear as to whether there is a socio-economic gradient in cerebral palsy (CP) prevalence beyond what would be expected from the socio-economic gradient for low birthweight, a strong risk factor for CP. We conducted a population-based study in five regions of the UK with CP registers, to investigate the relationship between CP prevalence and socio-economic deprivation, and how it varies by region, by birthweight and by severity and type of CP. The total study population was 1 657 569 livebirths, born between 1984 and 1997. Wards of residence were classified into five quintiles according to a census-based deprivation index, from Q1 (least deprived) to Q5 (most deprived). Socio-economic gradients were modelled by Poisson regression, and region-specific estimates combined by meta-analysis.
The prevalence of postneonatally acquired CP was 0.14 per 1000 livebirths overall. The mean deprivation gradient, expressed as the relative risk in the most deprived vs. the least deprived quintile, was 1.86 (95% confidence interval [95% CI 1.19, 2.88]). The prevalence of non-acquired CP was 2.22 per 1000 livebirths. For non-acquired CP the gradient was 1.16 [95% CI 1.00, 1.35]. Evidence for a socio-economic gradient was strongest for spastic bilateral cases (1.32 [95% CI 1.09, 1.59]) and cases with severe intellectual impairment (1.59 [95% CI 1.06, 2.39]). There was evidence for differences in gradient between regions. The gradient of risk of CP among normal birthweight births was not statistically significant overall (1.21 [95% CI 0.95, 1.54]), but was significant in two regions. There was non-significant evidence of a reduction in gradients over time.
The reduction of the higher rates of postneonatally acquired CP in the more socioeconomically deprived areas is a clear goal for prevention. While we found evidence for a socio-economic gradient for non-acquired CP of antenatal or perinatal origin, the picture was not consistent across regions, and there was some evidence of a decline in inequalities over time. The steeper gradients in some regions for normal birthweight cases and cases with severe intellectual impairment require further investigation.
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The nonlinear dynamics of a rotating magnetoplasma consisting of electrons, positrons and stationary positive ions is considered. The basic set of hydrodynamic and Poisson equations are reduced to a Zakharov-Kuznetsov (ZK) equation for the electric potential. The ZK equation is solved by applying an improved modified extended tanh-function method (2008 Phys. Lett. A 372 5691) and its characteristics are investigated. A set of new solutions are derived, including localized solitary waves, periodic nonlinear waveforms and divergent (explosive) pulses. The characteristics of these nonlinear excitations are investigated in detail.
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In this paper, we discuss and evaluate two proposed metro wavelength division multiplexing (WDM) ring network architectures for variable-length packet traffic in storage area networks (SANs) settings. The paper begins with a brief review of the relevant architectures and protocols in the literature. Subsequently, the network architectures along with their medium access control (MAC) protocols are described. Performance of the two network architectures is studied by means of computer simulation in terms of their queuing delay, node throughput and proportion of packets dropped. The network performance is evaluated under symmetric and asymmetric traffic scenarios with Poisson and self-similar traffic. (C) 2011 Elsevier Inc. All rights reserved.
Resumo:
OBJECTIVE: To clarify whether the increase in childhood type 1 diabetes is mirrored by a decrease in older age-groups, resulting in younger age at diagnosis.
RESEARCH DESIGN AND METHODS: We used data from two prospective research registers, the Swedish Childhood Diabetes Register, which included case subjects aged 0-14.9 years at diagnosis, and the Diabetes in Sweden Study, which included case subjects aged 15-34.9 years at diagnosis, covering birth cohorts between 1948 and 2007. The total database included 20,249 individuals with diabetes diagnosed between 1983 and 2007. Incidence rates over time were analyzed using Poisson regression models.
RESULTS: The overall yearly incidence rose to a peak of 42.3 per 100,000 person-years in male subjects aged 10-14 years and to a peak of 37.1 per 100,000 person-years in female subjects aged 5-9 years and decreased thereafter. There was a significant increase by calendar year in both sexes in the three age-groups <15 years; however, there were significant decreases in the older age-groups (25- to 29-years and 30- to 34-years age-groups). Poisson regression analyses showed that a cohort effect seemed to dominate over a time-period effect.
CONCLUSIONS: Twenty-five years of prospective nationwide incidence registration demonstrates a clear shift to younger age at onset rather than a uniform increase in incidence rates across all age-groups. The dominance of cohort effects over period effects suggests that exposures affecting young children may be responsible for the increasing incidence in the younger age-groups.
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Laying hens generally choose to aggregate, but the extent to which the environments in which we house them impact on social group dynamics is not known. In this paper the effect of pen environment on spatial clustering is considered. Twelve groups of four laying hens were studied under three environmental conditions: wire floor (W), shavings (Sh) and perches, peat, nestbox and shavings (PPN). Groups experienced each environment twice, for five weeks each time, in a systematic order that varied from group to group. Video recordings were made one day per week for 30 weeks. To determine level of clustering, we recorded positional data from a randomly selected 20-min excerpt per video (a total of 20 min x 360 videos analysed). On screen, pens were divided into six equal areas. In addition, PPN pens were divided into an additional four (sub) areas, to account for the use of perches (one area per half perch). Every 5 s, we recorded the location of each bird and calculated location use over time, feeding synchrony and cluster scores for each environment. Feeding synchrony and cluster scores were compared against unweighted and weighted (according to observed proportional location use) Poisson distributions to distinguish between resource and social attraction.
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This ongoing prospective study examined characteristics of school neighborhood and neighborhood of residence as predictors of sick leave among school teachers. School neighborhood income data for 226 lower-level comprehensive schools in 10 towns in Finland were derived from Statistics Finland and were linked to register-based data on 3,063 teachers with no long-term sick leave at study entry. Outcome was medically certified (> 9 days) sick leave spells during a mean follow-up of 4.3 years from data collection in 2000-2001. A multilevel, cross-classified Poisson regression model, adjusted for age, type of teaching job, length and type of job contract, school size, baseline health status, and income level of the teacher's residential area, showed a rate ratio of 1.30 (95% confidence interval: 1.03, 1.63) for sick leave among female teachers working in schools located in low-income neighborhoods compared with those working in high-income neighborhoods. A low income level of the teacher's residential area was also independently associated with sick leave among female teachers (rate ratio = 1.50, 95% confidence interval: 1.18, 1.91). Exposure to both low-income school neighborhoods and low-income residential neighborhoods was associated with the greatest risk of sick leave (rate ratio = 1.71, 95% confidence interval: 1.27, 2.30). This study indicates that working and living in a socioeconomically disadvantaged neighborhood is associated with increased risk of sick leave among female teachers.