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At least 451 records · Page 25Linked to original sources

PubMed2001

Finite element model of the Jefferson fracture: comparison with a cadaver model.

This study tries to explain the reason why the Jefferson fracture is a burst fracture, using two different biomechanical models: a finite element model (FEM) and a cadaver model used to determine strain distribution in C1 during axial static compressive loading. For the FEM model, a three-dimensional model of C1 was obtained from a 29-year-old healthy human, using axial CT scans with intervals of 1.0 mm. The mesh model was composed of 8200 four-noded isoparametric tetrahedrons and 37,400 solid elements. The material properties of the cortical bone of the vertebra were assessed according to the previous literature and were assumed to be linear isotropic and homogeneous for all elements. Axial static compressive loads were applied at between 200 and 1200 N. The strain and stress (maximum shear and von Mises) analyses were determined on the clinically relevant fracture lines of anterior and posterior arches. The results of the FEM were compared with a cadaver model. The latter comprised the C1 bone of a cadaver placed in a methylmethacrylate foam. Axial static compressive loads between 200 and 1200 N were applied by an electrohydraulic testing machine. Strain values were measured using strain gauges, which were cemented to the bone where the clinically relevant fracture lines of the anterior and posterior arches were located. As a result, compressive strain was observed on the outer surface of the anterior arch and inferior surface of the posterior arch. In addition, there was tensile strain on the inner surface of the anterior arch and superior surface of the posterior arch. The strain values obtained from the two experimental models showed similar trends. The FEM analysis revealed that maximum strain changes occurred where the maximum shear and von Mises stresses were concentrated. The changes in the C1 strain and stress values during static axial loading biomechanically prove that the Jefferson fracture is a burst fracture.

Adult↗

PubMed2006

Putting Wilson and Cleary to the test: analysis of a HRQOL conceptual model using structural equation modeling.

Wilson and Cleary (1995) proposed a conceptual model of health-related quality of life (HRQOL) that integrates both biological and psychological aspects of health outcomes. There are five different levels in their model, namely, physiological factors, symptom status, functional health, general health perceptions, and overall quality of life. Their model has been widely applied to different populations, including patients living with cancer, Parkinson's disease, arthritis, and HIV+/AIDS. However, their conceptual model has only been partially examined. That is, the five major concepts have not been examined simultaneously. Using structural equation modeling (SEM), the Wilson and Cleary HRQOL model was validated in patients living with HIV from the AIDS Time-Oriented Health Outcomes Study. The results showed that the HRQOL model fit the data adequately, and the relationships between the constructs were all significant (at p<0.05 level). Based on the modification indexes, an alternative model linking symptom status directly with general health perceptions and overall quality of life was specified. Implication and limitation of the findings are discussed.

Adult↗

PubMed2005

Evaluating user interactions with clinical information systems: a model based on human-computer interaction models.

OBJECTIVES: This article proposes a model for dimensions involved in user evaluation of clinical information systems (CIS). The model links the dimensions in traditional CIS evaluation and the dimensions from the human-computer interaction (HCI) perspective. PROPOSED METHOD: In this article, variables are defined as the properties measured in an evaluation, and dimensions are defined as the factors contributing to the values of the measured variables. The proposed model is based on a two-step methodology with: (1) a general review of information systems (IS) evaluations to highlight studied variables, existing models and frameworks, and (2) a review of HCI literature to provide the theoretical basis to key dimensions of user evaluation. RESULTS: The review of literature led to the identification of eight key variables, among which satisfaction, acceptance, and success were found to be the most referenced. DISCUSSION: Among those variables, IS acceptance is a relevant candidate to reflect user evaluation of CIS. While their goals are similar, the fields of traditional CIS evaluation, and HCI are not closely connected. Combining those two fields allows for the development of an integrated model which provides a model for summative and comprehensive user evaluation of CIS. All dimensions identified in existing studies can be linked to this model and such an integrated model could provide a new perspective to compare investigations of different CIS systems.

Attitude to Computers↗

PubMed2005

Estimation of time since death by heat-flow Finite-Element model. Part I: method, model, calibration and validation.

The determination of the time since death which often represents the presumed time of an offence plays an important role in medico-legal practice. In the early postmortem phase analyses of postmortem cooling provide the most accurate estimates. Empirical models of postmortem cooling are methodically restricted to standard conditions while heat flow models can in principle be applied to any complex cooling situations. The main problem having so far prevented heat flow models from being used in practice was the difficulty of solving the heat transfer equation for complex geometrical, initial and boundary conditions. This problem is now overcome by using the Finite-Element-Method as a numerical procedure. The study presents a three-dimensional Finite-Element-Model of the human body containing various tissue compartments with different thermal tissue properties. The initial temperature field is modelled inhomogeneously with a temperature gradient between body core and shell. Heat loss by conduction, convection and radiation as well as heat gain by supravital activity or irradiation from external sources can be simulated. One model parameter, the decrease rate of the supravital energy production, was calibrated and the model successfully validated using the experimentally verified empirical model by Marshall and Hoare.

Algorithms↗

PubMed2006

An ultrasonic measurement model using a multi-Gaussian beam model for a rectangular transducer.

To date, ultrasonic measurement models have primarily treated systems where circular transducers are used. Recently, however, a highly efficient ultrasonic beam model for a rectangular transducer has also become available where the transducer is represented as a superposition of a relatively few Gaussian beams. Thus, using the multi-Gaussian beams, we developed ultrasonic measurement models for systems where a rectangular transducer is employed. In this paper, we describe the developed models including the beam model, the efficiency factor for a rectangular transducer and far-field scattering models for some standard scatterers. Furthermore, the accuracy of the proposed model is verified by the comparison of the model-based predictions to the experimental measurements.

Journal Article↗

PubMed1998

A model of the combination of optic flow and extraretinal eye movement signals in primate extrastriate visual cortex. Neural model of self-motion from optic flow and extraretinal cues.

The determination of the direction of heading from optic flow is a complicated task. To solve it the visual system complements the optic flow by non-visual information about the occurrence of eye movements. Psychophysical studies have shown that the need for this combination depends on the structure the visual scene. In a depth-rich visual environment motion parallax can be exploited to differentiate self-translation from eye rotation. In the absence of motion parallax, i.e. in the case of movement towards a frontoparallel plane, extraretinal signals are necessary for correct heading perception ([Warren and Hannon, 1990]). [Lappe and Rauschecker (1993b)] have proposed a model of visual heading detection that reproduces many of the psychophysical findings in the absence of extraretinal input and links them to properties of single neurons in the primate visual cortex. The present work proposes a neural network model that integrates extraretinal signals into this network. The model is compared with psychophysical and neurophysiological data from experiments in human and non-human primates. The combined visual/extraretinal model reproduces human behavior in the case of movement towards a frontoparallel plane. Single model neurons exhibit several similarities to neurons from the medial superior temporal (MST) area of the macaque monkey. Similar to MST cells ([Erickson and Thier, 1991]) they differentiate between self-induced visual motion that results from eye movements in a stationary environment, and real motion in the environment. The model predicts that this differentiation can also be achieved visually, i.e. without extraretinal input. Other simulations followed experiments by [Bradley et al. (1996)], in which flow fields were presented that simulated observer translation towards a frontoparallel plane plus an eye rotation. Similar to MST cells, model neurons shift their preference for the focus of expansion along the direction of the eye movement when extraretinal input is not available. They respond to the retinal location of the focus of expansion which is shifted by the eye movement. In the presence of extraretinal input the preference for the focus of expansion is largely invariant to eye movements and tied to the location of the focus of expansion with regard to the visual scene. The model proposes that extraretinal compensation for eye movements need not be perfect in single neurons to achieve accurate heading detection. It thereby shows that the incomplete compensation found in most MST neurons is sufficient to explain the psychophysical data.

Journal Article↗

PubMed2005

Empirical and conceptual problems with longitudinal trait-state models: introducing a trait-state-occasion model.

The latent trait-state-error model (TSE) and the latent state-trait model with autoregression (LST-AR) represent creative structural equation methods for examining the longitudinal structure of psychological constructs. Application of these models has been somewhat limited by empirical or conceptual problems. In the present study, Monte Carlo analysis revealed that TSE models tend to generate improper solutions when N is too small, when waves are too few, and when occasion factor stability is either too large or too small. Mathematical analysis of the LST-AR model revealed its limitation to constructs that become more highly auto-correlated over time. The trait-state-occasion model has fewer empirical problems than does the TSE model and is more broadly applicable than is the LST-AR model.

Empirical Research↗

PubMed2001

Best harmony, unified RPCL and automated model selection for unsupervised and supervised learning on Gaussian mixtures, three-layer nets and ME-RBF-SVM models.

After introducing the fundamentals of BYY system and harmony learning, which has been developed in past several years as a unified statistical framework for parameter learning, regularization and model selection, we systematically discuss this BYY harmony learning on systems with discrete inner-representations. First, we shown that one special case leads to unsupervised learning on Gaussian mixture. We show how harmony learning not only leads us to the EM algorithm for maximum likelihood (ML) learning and the corresponding extended KMEAN algorithms for Mahalanobis clustering with criteria for selecting the number of Gaussians or clusters, but also provides us two new regularization techniques and a unified scheme that includes the previous rival penalized competitive learning (RPCL) as well as its various variants and extensions that performs model selection automatically during parameter learning. Moreover, as a by-product, we also get a new approach for determining a set of 'supporting vectors' for Parzen window density estimation. Second, we shown that other special cases lead to three typical supervised learning models with several new results. On three layer net, we get (i) a new regularized ML learning, (ii) a new criterion for selecting the number of hidden units, and (iii) a family of EM-like algorithms that combines harmony learning with new techniques of regularization. On the original and alternative models of mixture-of-expert (ME) as well as radial basis function (RBF) nets, we get not only a new type of criteria for selecting the number of experts or basis functions but also a new type of the EM-like algorithms that combines regularization techniques and RPCL learning for parameter learning with either least complexity nature on the original ME model or automated model selection on the alternative ME model and RBF nets. Moreover, all the results for the alternative ME model are also applied to other two popular nonparametric statistical approaches, namely kernel regression and supporting vector machine. Particularly, not only we get an easily implemented approach for determining the smoothing parameter in kernel regression, but also we get an alternative approach for deciding the set of supporting vectors in supporting vector machine.

Algorithms↗

PubMedDate not supplied

Simulation of micropopulations in epidemiology: tutorial. 3. Simulation model evaluation methods. A series of tutorials illustrated by coronary heart disease models.

This is the third in a series of tutorials concerning the simulation of micropopulation models to support epidemiological research. The series emphasizes techniques used in studies at the National Micropopulation Simulation Resource at the University of Minnesota. For pedagogic purposes, applications to coronary heart disease (CHD) models are used to illustrate the principles and methodologies employed. All of the models presented are implemented using available software. A variety of tests and techniques are used to evaluate these models. This tutorial presents some of those methods stressing the advantages and limitations of the tests rather than the formal definitions. To make the evaluation methods more understandable, some of the risk factors for CHD models are introduced. The interpretation of the evaluation depends critically on the goals of the modeling effort. The subset of evaluation methods presented includes investigations of the epidemiological, mathematical and statistical aspects of the models.

Computer Simulation↗

PubMed2004

Modelling functional integration: a comparison of structural equation and dynamic causal models.

The brain appears to adhere to two fundamental principles of functional organisation, functional integration and functional specialisation, where the integration within and among specialised areas is mediated by effective connectivity. In this paper, we review two different approaches to modelling effective connectivity from fMRI data, structural equation models (SEMs) and dynamic causal models (DCMs). In common to both approaches are model comparison frameworks in which inferences can be made about effective connectivity per se and about how that connectivity can be changed by perceptual or cognitive set. Underlying the two approaches, however, are two very different generative models. In DCM, a distinction is made between the 'neuronal level' and the 'hemodynamic level'. Experimental inputs cause changes in effective connectivity expressed at the level of neurodynamics, which in turn cause changes in the observed hemodynamics. In SEM, changes in effective connectivity lead directly to changes in the covariance structure of the observed hemodynamics. Because changes in effective connectivity in the brain occur at a neuronal level DCM is the preferred model for fMRI data. This review focuses on the underlying assumptions and limitations of each model and demonstrates their application to data from a study of attention to visual motion.

Algorithms↗

PubMed2003

The variance of icosahedral virus models is a key indicator in the structure determination: a model-free reconstruction of viruses, suitable for refractory particles.

A model-free method to determine the three-dimensional structure of icosahedral viruses is described. The novel strategy is based upon the approximate principle that correct virus structures have high variance as do all other well-detailed structures, even wrong ones. The original projections of individual particles are reduced to a radius of 25 pixels and are used to compute single particle reconstruction models by assigning them 1800 different Euler triads. The variance of the models obtained from all projections is stored in maps and a decimation process is carried out. In a first stage, thresholds are adopted for the variance values, and in a second stage, carried out by correspondence analysis and classification, 30 clusters of models are sorted out. The clusters are refined to yield models contained in boxes of 64(3) voxels. The refined models with highest variance and closest similarity represent the correct solution. Once enlarged, these models can be used to align all available projections in their original scale in a customary projection-matching process. The method has proved successful in determining the structures of poliovirus, of the empty and filled capsids of L-A virus, and of a modified capsid of hepatitis B virus.

Capsid↗

PubMed2006

Three-component competitive adsorption model for fixed-bed and moving-bed granular activated carbon adsorbers. Part II. Model parameterization and verification.

COMPSORB-GAC is a 3-component competitive adsorption kinetic model for granular activated carbon (GAC) adsorbers that was developed in Part I of this study, including a proposed procedure for determining model parameters in natural water applications with background natural organic matter (NOM). Part II of this study demonstrates the proposed parameterization procedure and validates the modeling approach by comparing predictions with experimental breakthrough curves at multiple empty-bed contact times for both fixed-bed and moving-bed reactors. The parameterization procedure consists of a set of independent, short-term experimental tests with fresh and batch preloaded adsorbents and then data fitting using both classic and recently developed theoretical expressions. The model and parameterization procedure simplifies NOM into two fictive fractions (pore-blocking and strongly competing) and incorporates three competitive effects that vary both temporally and axially in a GAC column (direct competition for sites, intraparticle pore blockage, and external surface pore blockage). With all three competitive mechanisms accounted for, the model could accurately predict breakthrough profiles for column lengths and durations that were much longer than those used for model parameterization. Model predictions that ignored one or more of the competitive mechanisms showed that each mechanism was important for different regions of the breakthrough curve. The external surface pore-blockage effect was predominant for the prediction of early breakthrough data, whereas direct competition for sites and intraparticle pore blockage were prevalent when predicting higher breakthrough levels and data later in the column run.

Adsorption↗

PubMed2002

Experimental modelling of human spinal cord injury: a model that crosses the species barrier and mimics the spectrum of human cytopathology.

STUDY DESIGN: Literature review and presentation of an experimental model of human spinal cord injury, (SCI). OBJECTIVES: Experimental designs seek to mimic and model the physical processes by which human SCI occurs and replicate the variety of chronic pathologies that characterize its long term effects. The variations in biological processes that are present between species have contributed to recent difficulties in generalizing experimental findings to the human condition. In this review, one finds: (1) a discourse on the pathological nature of the chronic human lesion, (2) a consideration of how the physical properties of soft tissue injury result in acute and chronic changes in the spinal substance, (3) a description of a device (ESCID) that is able to replicate and dynamically monitor physical indices of SCI as they take place in experimental models, and (4) a summary of how use of this device in different species has allowed the biomechanical descriptors of such injuries to be easily compared even in murine models. SETTING: Ohio State University, Ohio, USA. RESULTS: Careful attention to the details of injury device design has finally allowed a direct comparison of contusion-type injury models in the rat and mouse. Biomechanical outcomes with predictive capabilities have evolved that allow the investigator to create the range of pathologies seen in the human lesion even in these small vertebrates. The predictive cytopathology and our ability to manipulate the mouse genome will allow the testing of specific hypotheses related to cause and effect in experimental spinal cord injuries. Since the biomechanics, pathology, and chronic outcomes appear to be similar to those seen in the human, these animal models should facilitate rapid progress in the design of human therapeutics. CONCLUSIONS: Biomechanics of certain elements of experimental spinal injury are surprisingly accurate descriptors of acute and chronic pathologies in the spinal cord. This tenet applies across species and has often allowed more accurate design of clinical trials in the past few decades. As molecular approaches to this problem evolve, the use of species with known genomes appear warranted. Models that take advantage of these approaches are likely to produce innovations that quicken the pace of human trial strategies.

Animals↗

PubMed2004

Development of realistic high-resolution whole-body voxel models of Japanese adult males and females of average height and weight, and application of models to radio-frequency electromagnetic-field dosimetry.

With advances in computer performance, the use of high-resolution voxel models of the entire human body has become more frequent in numerical dosimetries of electromagnetic waves. Using magnetic resonance imaging, we have developed realistic high-resolution whole-body voxel models for Japanese adult males and females of average height and weight. The developed models consist of cubic voxels of 2 mm on each side; the models are segmented into 51 anatomic regions. The adult female model is the first of its kind in the world and both are the first Asian voxel models (representing average Japanese) that enable numerical evaluation of electromagnetic dosimetry at high frequencies of up to 3 GHz. In this paper, we will also describe the basic SAR characteristics of the developed models for the VHF/UHF bands, calculated using the finite-difference time-domain method.

Body Height↗

PubMed1994

An anatomical and physiological model of the renal parenchyma--model development and parametric identification.

Renal function is often characterized by the activity/time curves obtained by imaging the aorta and kidney. Non-parametric deconvolution of the activity/time curves is clinically useful as a diagnostic tool in determining renal transit times. Typically non-parametric deconvolution is performed using a technique that does not require a priori information, e.g. matrix-based and Fourier-transform methods. Using data filtering and conservation of mass constraints, non-parametric deconvolution continues to exhibit noise in the deconvolved curves. This noise hampers the identification of renal transit times. Given the shortcomings of non-parametric deconvolution, a parametric model of the renal response has been developed. Our model is shown to be anatomically and physiologically plausible. In this paper, the parametric model structure is used, in conjunction with experimental data, to estimate renal physiological parameters. These parameters include the filtration fraction, renal blood transit time and urine transit times. The model parameters are then related to the minimum transit time (MinTT), mean transit time (MTT), glomerular filtration rate (GFR) and parenchymal transit time index (PTTI). As deconvolution techniques often produce negative artifacts, Fine et al developed a technique to determine an aorta background to minimize this effect. In this paper this work is extended to determine a reasonable renal background from aorta activity/time curves. Non-parametric deconvolution is used to provide initial estimates of model parameters. The model is then fitted to twelve healthy background-corrected kidneys by an iterative parameter-estimation technique. The normal values correspond to those reported in the literature. These normal values are then used to identify renal arterial stenosis in two renal hypertensive patients. The results suggest that parametric identification, based on a renal-retention-function model, may provide additional anatomical and physiological information that is not provided by conventional non-parametric methods.

Aging↗

PubMed2000

The Beta Poisson dose-response model is not a single-hit model.

The choice of a dose-response model is decisive for the outcome of quantitative risk assessment. Single-hit models have played a prominent role in dose-response assessment for pathogenic microorganisms, since their introduction. Hit theory models are based on a few simple concepts that are attractive for their clarity and plausibility. These models, in particular the Beta Poisson model, are used for extrapolation of experimental dose-response data to low doses, as are often present in drinking water or food products. Unfortunately, the Beta Poisson model, as it is used throughout the microbial risk literature, is an approximation whose validity is not widely known. The exact functional relation is numerically complex, especially for use in optimization or uncertainty analysis. Here it is shown that although the discrepancy between the Beta Poisson formula and the exact function is not very large for many data sets, the differences are greatest at low doses--the region of interest for many risk applications. Errors may become very large, however, in the results of uncertainty analysis, or when the data contain little low-dose information. One striking property of the exact single-hit model is that it has a maximum risk curve, limiting the upper confidence level of the dose-response relation. This is due to the fact that the risk cannot exceed the probability of exposure, a property that is not retained in the Beta Poisson approximation. This maximum possible response curve is important for uncertainty analysis, and for risk assessment of pathogens with unknown properties.

Algorithms↗

PubMed1994

Sensitivity of physiologically based pharmacokinetic models to variation in model parameters: methylene chloride.

The parameters in a physiologically based pharmacokinetic (PBPK) model of methylene chloride were varied systematically, and the resulting variation in a number of model outputs was determined as a function of time for mice and humans at several exposure concentrations. The importance of the various parameters in the model was highly dependent on the conditions (concentration, species) for which the simulation was performed and the model output (dose surrogate) being considered. Model structure also had a significant impact on the results. For sensitivity analysis, particular attention must be paid to conservation equations to ensure that the variational calculations do not alter mass balance, introducing extraneous effects into the model. All of the normalized sensitivity coefficients calculated in this study ranged between -1.12 and 1, and most were much less than 1 in absolute value, indicating that individual input errors are not greatly amplified in the outputs. In addition to ranking parameters in terms of their impact on model predictions, time-dependent sensitivity analysis can also be used as an aid in the design of experiments to estimate parameters by predicting the experimental conditions and sampling points which will maximize parameter identifiability.

Animals↗

PubMed1995

Physiological modeling of speech production: methods for modeling soft-tissue articulators.

As the initial components of a comprehensive physiological model of speech production, methods have been developed for modeling soft tissue structures, such as the tongue and lips, as continua. This approach provides a foundation for applying finite element methods to simulate these structures in a biomechanical model of speech production. Movements and deformations of the structures can then be computed as the solutions of a nonlinear second-order constraint system of ordinary differential equations, which is obtained from a finite element approximation of an energy rate equation. The muscle fibers in the soft tissue structures are represented as fields that specify the directions in which active and passive tensile stress is produced. The elastic behavior of the passive components is modeled using an isotropic exponential constitutive strain energy function, and the viscous stress components, by using linear viscosity. Incompressibility is maintained elementwise in the simulation using a simultaneously solved system for the computation of Lagrange multipliers. As first step towards modeling a vocal tract, a preliminary model of a tongue with eight muscles has been completed. Simulation results demonstrate the validity of the method and they support the feasibility of a physiologically based model of speech production.

Biomechanical Phenomena↗