918 resultados para model-based testing
Resumo:
Periacetabular Osteotomy (PAO) is a joint preserving surgical intervention intended to increase femoral head coverage and thereby to improve stability in young patients with hip dysplasia. Previously, we developed a CT-based, computer-assisted program for PAO diagnosis and planning, which allows for quantifying the 3D acetabular morphology with parameters such as acetabular version, inclination, lateral center edge (LCE) angle and femoral head coverage ratio (CO). In order to verify the hypothesis that our morphology-based planning strategy can improve biomechanical characteristics of dysplastic hips, we developed a 3D finite element model based on patient-specific geometry to predict cartilage contact stress change before and after morphology-based planning. Our experimental results demonstrated that the morphology-based planning strategy could reduce cartilage contact pressures and at the same time increase contact areas. In conclusion, our computer-assisted system is an efficient tool for PAO planning.
Resumo:
The events of the 1990's and early 2000's demonstrated the need for effective planning and response to natural and man-made disasters. One of those potential natural disasters is pandemic flu. Once defined, the CDC stated that program, or plan, effectiveness is improved through the process of program evaluation. (Centers for Disease Control and Prevention, 1999) Program evaluation should be accomplished not only periodically, but in the course of routine administration of the program. (Centers for Disease Control and Prevention, 1999) Accomplishing this task for a "rare, but significant event" is challenging. (Herbold, John R., PhD., 2008) To address this challenge, the RAND Corporation (under contract to the CDC) developed the "Facilitated Look-Backs" approach that was tested and validated at the state level. (Aledort et al., 2006).^ Nevertheless, no comprehensive and generally applicable pandemic influenza program evaluation tool or model is readily found for use at the local public health department level. This project developed such a model based on the "Facilitated Look-Backs" approach developed by RAND Corporation. (Aledort et al., 2006) Modifications to the RAND model included stakeholder additions, inclusion of all six CDC program evaluation steps, and suggestions for incorporating pandemic flu response plans in seasonal flu management implementation. Feedback on the model was then obtained from three LPHD's—one rural, one suburban, and one urban. These recommendations were incorporated into the final model. Feedback from the sites also supported the assumption that this model promotes the effective and efficient evaluation of both pandemic flu and seasonal flu response by reducing redundant evaluations of pandemic flu plans, seasonal flu plans, and funding requirement accountability. Site feedback also demonstrated that the model is comprehensive and flexible, so it can be adapted and applied to different LPHD needs and settings. It also stimulates evaluation of the major issues associated with pandemic flu planning. ^ The next phase in evaluating this model should be to apply it in a program evaluation of one or more LPHD's seasonal flu response that incorporates pandemic flu response plans.^
Resumo:
As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^
Resumo:
The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^
Resumo:
The central paradigm linking disadvantaged social status and mental health has been the social stress model (Horwitz, 1999), the assumption being that individuals residing in lower social status groups are subjected to greater levels of stress not experienced by individuals from higher status groups. A further assumption is that such individuals have fewer resources to cope with stress, in turn leading to higher levels of psychological disorder, including depression (Pearlin, 1989). Despite these key assumptions, there is a dearth of literature comparing the social patterning of stress exposure (Hatch & Dohrenwend, 2007; Meyer, Schwartz, & Frost, 2008; Kessler, Mickelson, & Williams, 1999; Turner & Avison, 2003; Turner & Lloyd, 1999; Turner, Wheaton, & Lloyd, 1995), and the distribution and contribution of protective factors, posited to play a role in the low rates of depression found among African- and Latino-Americans (Alegria et al., 2007; Breslau, Aguilar-Gaxiola, Kendler, Su, Williams, & Kessler, 2006; Breslau, Borges, Hagar, Tancredi, Gilman, 2009; Gavin, Walton, Chae, Alegria, Jackson, & Takeuchi, 2010; Williams, & Neighbors, 2006). Thus, this study sought to describe both the distribution and contribution of risk and protective factors in relation to depression among a sample of African-, European-, and Latina-American mothers of adolescents, including testing a hypothesized mechanism through which social support, an important protective factor specific to women and depression, operates. ^ Despite the finding that the levels of depression were not statistically different across all three groups of women, surprising results were found in describing the distribution of both risk and protective factors, in that results reported among all women who were mothers when analyzed masked differences within each ethnic group when SES was assessed, a point made explicit by Williams (2002) regarding racial and ethnic variations in women's health. In the final analysis, while perceived social support was found to partially mediate the effect of social isolation on depression, among African-Americans, the direct effect of social isolation and depression was lower among this group of women, as was the indirect effect of social isolation and perceived social support when compared to European- and Latina-American mothers. Or, put differently, higher levels of social isolation were not found to be as associated with more depression or lower social support among African-American mothers when compared to their European- and Latina-American counterparts. ^ Women in American society occupy a number of roles, i.e., that of being female, married or single, mother, homemaker or employee. In addition, to these roles, ethnicity and SES also come into play, such that the intersection of all these roles and the social contexts that they occupy are equally important and must be taken into consideration when making predictions drawn from the social stress model. Based on these findings, it appears that the assumptions of the social stress model need to be revisited to include the variety of roles that intersect among individuals from differing social groups. More specifically, among women who are mothers and occupy a myriad of other roles, i.e., that of being female, married or single, African- or Latina-American, mother, homemaker or employee, the intersection of all the roles and the social contexts that women occupy are equally important and must be taken into consideration when looking at both the types and distribution of stressors across women. Predictions based on simple, mutually exclusive categories of social groups may lead to erroneous assumptions and misleading results.^
Resumo:
Contaminated soil reuse was investigated, with higher profusion, throughout the early 90’s, coinciding with the 1991 Gulf War, when efforts to amend large crude oil releases began in geotechnical assessment of contaminated soils. Isolated works referring to geotechnical testing with hydrocarbon ground contaminants are described in the state-of-the-art, which have been extended to other type of contaminated soil references. Contaminated soils by light non-aquous phase liquids (LNAPL) bearing capacity reduction has been previously investigated from a forensic point of view. To date, all the research works have been published based on the assumption of constant contaminant saturation for the entire soil mass. In contrast, the actual LNAPLs distribution plumes exhibit complex flow patterns which are subject to physical and chemical changes with time and distance travelled from the release source. This aspect has been considered along the present text. A typical Madrid arkosic soil formation is commonly known as Miga sand. Geotechnical tests have been carried out, with Miga sand specimens, in incremental series of LNAPL concentrations in order to observe the soil engineering properties variation due to a contamination increase. Results are discussed in relation with previous studies and as a matter of fact, soil mechanics parameters change in the presence of LNAPL, showing different tendencies according to each test and depending on the LNAPL content, as well as to the specimen’s initially planned relative density, dense or loose. Geotechnical practical implications are also commented on and analyzed. Variation on geotechnical properties may occur only within the external contour of contamination distribution plume. This scope has motivated the author to develop a physical model based on transparent soil technology. The model aims to reproduce the distribution of LNAPL into the ground due to an accidental release from a storage facility. Preliminary results indicate that the model is a potentially complementary tool for hydrogeological applications, site-characterization and remediation treatment testing within the framework of soil pollution events. A description of the test setup of an innovative three dimensional physical model for the flow of two or more phases, in porous media, is presented herein, along with a summary of the advantages, limitations and future applications for modeling with transparent material. En los primeros años de la década de los años 90, del siglo pasado, coincidiendo con la Guerra del Golfo en 1991, se investigó intensamente sobre la reutilización de suelos afectados por grandes volúmenes de vertidos de crudo, fomentándose la evaluación geotécnica de los suelos contaminados. Se describen, en el estado del arte de esta tésis, una serie de trabajos aislados en relación con la caracterización geotécnica de suelos contaminados con hidrocarburos, descripción ampliada mediante referencias relacionadas con otros tipos de contaminación de suelos. Existen estudios previos de patología de cimentaciones que analizan la reducción de la capacidad portante de suelos contaminados por hidrocarburos líquidos ligeros en fase no acuosa (acrónimo en inglés: LNAPL de “Liquid Non-Aquous Phase Liquid”). A fecha de redacción de la tesis, todas las publicaciones anteriores estaban basadas en la consideración de una saturación del contaminante constante en toda la extensión del terreno de cimentación. La distribución real de las plumas de contaminante muestra, por el contrario, complejas trayectorias de flujo que están sujetas a cambios físico-químicos en función del tiempo y la distancia recorrida desde su origen de vertido. Éste aspecto ha sido considerado y tratado en el presente texto. La arena de Miga es una formación geológica típica de Madrid. En el ámbito de esta tesis se han desarrollado ensayos geotécnicos con series de muestras de arena de Miga contaminadas con distintas concentraciones de LNAPL con el objeto de estimar la variación de sus propiedades geotécnicas debido a un incremento de contaminación. Se ha realizado una evaluación de resultados de los ensayos en comparación con otros estudios previamente analizados, resultando que las propiedades mecánicas del suelo, efectivamente, varían en función del contenido de LNAPL y de la densidad relativa con la que se prepare la muestra, densa o floja. Se analizan y comentan las implicaciones de carácter práctico que supone la mencionada variación de propiedades geotécnicas. El autor ha desarrollado un modelo físico basado en la tecnología de suelos transparentes, considerando que las variaciones de propiedades geotécnicas únicamente deben producirse en el ámbito interior del contorno de la pluma contaminante. El objeto del modelo es el de reproducir la distribución de un LNAPL en un terreno dado, causada por el vertido accidental de una instalación de almecenamiento de combustible. Los resultados preliminares indican que el modelo podría emplearse como una herramienta complementaria para el estudio de eventos contaminantes, permitiendo el desarrollo de aplicaciones de carácter hidrogeológico, caracterización de suelos contaminados y experimentación de tratamientos de remediación. Como aportación de carácter innovadora, se presenta y describe un modelo físico tridimensional de flujo de dos o más fases a través de un medio poroso transparente, analizándose sus ventajas e inconvenientes así como sus limitaciones y futuras aplicaciones.
Resumo:
The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.
Resumo:
An extended 3D distributed model based on distributed circuit units for the simulation of triple‐junction solar cells under realistic conditions for the light distribution has been developed. A special emphasis has been put in the capability of the model to accurately account for current mismatch and chromatic aberration effects. This model has been validated, as shown by the good agreement between experimental and simulation results, for different light spot characteristics including spectral mismatch and irradiance non‐uniformities. This model is then used for the prediction of the performance of a triple‐junction solar cell for a light spot corresponding to a real optical architecture in order to illustrate its suitability in assisting concentrator system analysis and design process.
Resumo:
Recently, we have presented some studies concerning the analysis, design and optimization of one experimental device developed in the UK - GPTAD - which has been designed to remove blood clots without the need to make contact with the clot itself, thereby potentially reducing the risk of problems such as downstream embolisation. Based on the idea of a modification of the previous device, in this work, we present a model based in the use of stents like the SolitaireTM FR, which is in contact with the clot itself. In the case of such devices, the stent is self-expandable and the extraction of the blood clot is faciliatated by the stent, which must be inside the clot. Such stents are generally inserted in position by using the guidewire inserted into the catheter. This type of modeling could potentially be useful in showing how the blood clot is moved by the various different forces involved. The modelling has been undertaken by analyzing the resistances, compliances and inertances effects. We model an artery and blood clot for range of forces for the guidewire. In each case we determine the interaction between blood clot, stent and artery.
Resumo:
Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.
Resumo:
We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.