935 resultados para diluizione,olio,CFD,MCI
Resumo:
River bifurcations are key nodes within braided river systems controlling the flow and sediment partitioning and therefore the dynamics of the river braiding process. Recent research has shown that certain geometrical configurations induce instabilities that lead to downstream mid-channel bar formation and the formation of bifurcations. However, we currently have a poor understanding of the flow division process within bifurcations and the flow dynamics in the downstream bifurcates, both of which are needed to understand bifurcation stability. This paper presents results of a numerical sensitivity experiment undertaken using computational fluid dynamics (CFD) with the purpose of understanding the flow dynamics of a series of idealized bifurcations. A geometric sensitivity analysis is undertaken for a range of channel slopes (0.005 to 0.03), bifurcation angles (22 degrees to 42 degrees) and a restricted set of inflow conditions based upon simulating flow through meander bends with different curvature on the flow field dynamics through the bifurcation. The results demonstrate that the overall slope of the bifurcation affects the velocity of flow through the bifurcation and when slope asymmetry is introduced, the flow structures in the bifurcation are modified. In terms of bifurcation evolution the most important observation appears to be that once slope asymmetry is greater than 0.2 the flow within the steep bifurcate shows potential instability and the potential for alternate channel bar formation. Bifurcation angle also defines the flow structures within the bifurcation with an increase in bifurcation angle increasing the flow velocity down both bifurcates. However, redistributive effects of secondary circulation caused by upstream curvature can very easily counter the effects of local bifurcation characteristics. Copyright (C) 2011 John Wiley & Sons, Ltd.
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Purpose: To report the findings of the clinical and molecular evaluation in a Greek family with fleck corneal dystrophy (CFD).Methods: A 58-year-old woman was seen on routine ophthalmic examination and diagnosed as having CFD. All available family members were examined to evaluate the clinical findings and inheritance of the disease. Twenty members of the family in five generations underwent slit-lamp examination. Eleven were females and nine males, aged from two years to 85 years old. Blood samples were available from four patients with CFD and seven unaffected relatives, and the DNAs were subjected to molecular screening of the phosphoinositide kinase, five finger-containing (PIKFYVE) gene by direct sequencing or denaturing high performance liquid chromatography (DHPLC).Results: The clinical evaluation revealed six family members (five females and one male) with CFD. In two CFD patients early cataract formation was noticed. All patients affected with the corneal dystrophy were asymptomatic. The molecular analyses demonstrated the existence of a novel c. 3060-3063delCCTT (p.P968Vfs23) mutation in PIKFYVE in all CFD patients tested but in none of the six unaffected family members. No molecular screening was performed in the seventh unaffected member as the causative mutation was clearly transmitted from his affected wife to his affected son.Conclusions: We report on the clinical and molecular findings of a five generation Greek family with CFD and we conclude that the novel c. 3060-3063delCCTT (p. P968Vfs23) mutation in PIKFYVE, which segregated with the disease, was the causative mutation in this family.
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Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.
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Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.
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Dois métodos, utilizando permeâmetros a disco, foram usados para medir a sorvidade e a condutividade hidráulica em três horizontes de um solo de Santa Maria da Boa Vista, Pernambuco, utilizando-se potenciais de fornecimento de água de 0, -2,5, -5 e -10 cm de água. No primeiro método, a condutividade hidráulica foi obtida através de estimativas da sorvidade e do fluxo estacionário, utilizando-se apenas um permeâmetro. No segundo, as medidas da sorvidade e da condutividade hidráulica foram feitas utilizando-se valores dos fluxos estacionários, obtidos a partir de dois permeâmetros de diferentes raios. Esse segundo método apresentou resultados mais consistentes dos tempos -- gravitacional e geométrico --, e do raio característico de poros que o primeiro método. A sorvidade foi tão importante quanto a condutividade hidráulica para caracterizar o processo de infiltração. A redução brusca dos valores dos raios característicos de poros do horizonte A2/B, com mudanças no potencial de fornecimento de água, revelou a heterogeneidade da estrutura deste horizonte, permitindo identificar a influência dos volumes argilosos compactados sobre o processo de infiltração.
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A determinação da condutividade hidráulica de um Podzólico Amarelo foi obtida a partir de experimento montado em uma parcela de 3,5 m x 3,5 m, localizada na Estação Experimental da Empresa Pernambucana de Pesquisa Agropecuária (IPA), de Itapirema, Goiana, PE. Foi utilizado o método de drenagem interna para calcular a condutividade hidráulica (K(q)) como função da umidade do solo, nos três horizontes característicos do solo. Os perfis de umidade e de potencial matricial, em função do tempo, obtidos no experimento de drenagem interna mostram claramente a existência de um joelho que marca a transição entre as fases de drenagem rápida e lenta. Várias funções do tipo potência, soma de duas e três exponenciais, foram usadas para modelar essa transição entre a fase rápida e a fase lenta de drenagem. O horizonte A, arenoso, com poros maiores, é um horizonte de elevada condutividade hidráulica, enquanto o horizonte BA, de estrutura maciça com poros pouco visíveis, é um horizonte de impedimento para a infiltração. A dinâmica hídrica do horizonte Bt é mais complexa em virtude de sua heterogeneidade. A caracterização dos horizontes A e BA pode trazer subsídios significativos para a elaboração de modelos de simulação numérica dos processos de transferência de água nos horizontes superficiais, que são os mais condicionantes para a exploração agrícola e a conservação dos solos.
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The early diagnostic value of glucose hypometabolism and atrophy as potential neuroimaging biomarkers of mild cognitive impairment (MCI) and Alzheimer's disease (AD) have been extensively explored using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (MRI). The vast majority of previous imaging studies neglected the effects of single factors, such as age, symptom severity or time to conversion in MCI thus limiting generalisability of results across studies. Here, we investigated the impact of these factors on metabolic and structural differences. FDG-PET and MRI data from AD patients (n = 80), MCI converters (n = 65) and MCI non-converters (n = 64) were compared to data of healthy subjects (n = 79). All patient groups were split into subgroups by age, time to conversion (for MCI), or symptom severity and compared to the control group. AD patients showed a strongly age-dependent pattern, with younger patients showing significantly more extensive reductions in gray matter volume and glucose utilisation. In the MCI converter group, the amount of glucose utilisation reduction was linked to the time to conversion but not to atrophy. Our findings indicate that FDG-PET might be more closely linked to future cognitive decline whilst MRI being more closely related to the current cognitive state reflects potentially irreversible damage.
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In order to study the various health influencing parameters related to engineered nanoparticles as well as to soot emitted b diesel engines, there is an urgent need for appropriate sampling devices and methods for cell exposure studies that simulate the respiratory system and facilitate associated biological and toxicological tests. The objective of the present work was the further advancement of a Multiculture Exposure Chamber (MEC) into a dose-controlled system for efficient delivery of nanoparticles to cells. It was validated with various types of nanoparticles (diesel engine soot aggregates, engineered nanoparticles for various applications) and with state-of-the-art nanoparticle measurement instrumentation to assess the local deposition of nanoparticles on the cell cultures. The dose of nanoparticles to which cell cultures are being exposed was evaluated in the normal operation of the in vitro cell culture exposure chamber based on measurements of the size specific nanoparticle collection efficiency of a cell free device. The average efficiency in delivering nanoparticles in the MEC was approximately 82%. The nanoparticle deposition was demonstrated by Transmission Electron Microscopy (TEM). Analysis and design of the MEC employs Computational Fluid Dynamics (CFD) and true to geometry representations of nanoparticles with the aim to assess the uniformity of nanoparticle deposition among the culture wells. Final testing of the dose-controlled cell exposure system was performed by exposing A549 lung cell cultures to fluorescently labeled nanoparticles. Delivery of aerosolized nanoparticles was demonstrated by visualization of the nanoparticle fluorescence in the cell cultures following exposure. Also monitored was the potential of the aerosolized nanoparticles to generate reactive oxygen species (ROS) (e.g. free radicals and peroxides generation), thus expressing the oxidative stress of the cells which can cause extensive cellular damage or damage on DNA.
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Computational anatomy with magnetic resonance imaging (MRI) is well established as a noninvasive biomarker of Alzheimer's disease (AD); however, there is less certainty about its dependency on the staging of AD. We use classical group analyses and automated machine learning classification of standard structural MRI scans to investigate AD diagnostic accuracy from the preclinical phase to clinical dementia. Longitudinal data from the Alzheimer's Disease Neuroimaging Initiative were stratified into 4 groups according to the clinical status-(1) AD patients; (2) mild cognitive impairment (MCI) converters; (3) MCI nonconverters; and (4) healthy controls-and submitted to a support vector machine. The obtained classifier was significantly above the chance level (62%) for detecting AD already 4 years before conversion from MCI. Voxel-based univariate tests confirmed the plausibility of our findings detecting a distributed network of hippocampal-temporoparietal atrophy in AD patients. We also identified a subgroup of control subjects with brain structure and cognitive changes highly similar to those observed in AD. Our results indicate that computational anatomy can detect AD substantially earlier than suggested by current models. The demonstrated differential spatial pattern of atrophy between correctly and incorrectly classified AD patients challenges the assumption of a uniform pathophysiological process underlying clinically identified AD.
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In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.
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The report compares and contrasts the automated PASCO method of pavement evaluation to the manual procedures used by the Iowa Department of Transportation (DOT) to evaluate pavement condition. Iowa DOT's use of IJK and BPR roadmeters and manual crack and patch surveys are compared to PASCO's use of 35-mm photography, artificial lighting and hairline projection, tracking wheels and lasers to measure ride, cracking and patching, rut depths, and roughness. The Iowa DOT method provides a Present Serviceability Index (PSI) value and PASCO provides a Maintenance Control Index (MCI). Seven sections of Interstate Highway, county roads and city streets, and one shoulder section were tested with different speeds of data collection, surface types and textures, and stop and start conditions. High correlation of results between the two methods in the measurement of roughness (0.93 for the tracking wheel and 0.84 for the laser method) were recorded. Rut depth correlations of 0.61 and cracking of 0.32 are attributed to PASCO's more comprehensive measurement techniques. A cost analysis of the data provided by both systems indicates that PASCO is capable of providing a comparable result with improved accuracy at a cost of $125-$150 or less per two-lane mile depending on survey mileage. Improved data collection speed, accuracy, and reliability, and a visible record of pavement condition for comparable costs are available. The PASCO system's ability to provide the data required in the Highway Pavement Distress Identification Manual, the Pavement Condition Rating Guide, and the Strategic Highway Research Program Long Term Pavement Performance (LTPP) Studies, is also outlined in the report.
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Cet article retrace une recherche qualitative pluridisciplinaire. Les cinq auteurs - anthropologues, médecin psychiatre, psychologue et sociologue - ont développé une collaboration autour d'une problématique récurrente chez les personnes âgées: les troubles cognitifs associés à l'âge, les difficultés à les diagnostiquer et à communiquer le diagnostic aux patients et à leurs proches. Huit patients et leurs proches se sont rencontrés séparément lors de deux séries d'entretiens sur l'annonce du diagnostic Mild Cognitive Impairment (MCI). Les résultats montrent que la communication du diagnostic MCI n'insuffle pas un tournant dans la trajectoire des patients. Les propos des experts semblent n'avoir qu'un faible impact sur la compréhension qu'ont les patients et leurs accompagnants de la santé mentale des sujets diagnostiqués.
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The main objective of the proposed study is to use Computational Fluid Dynamics (CFD) tools to determine the wind loads by accurate numerical simulations of air flow characteristics around large highway sign structures under severe wind speeds conditions. Fully three-dimensional Reynolds- Averaged Navier-Stokes (RANS) simulations are used to estimate the total force on different panels, as well as the actual pressure distribution on the front and back faces of the panels. In particular, the present study investigates the effects of aspect ratio and sign spacing for regular panels, the effect of sign depth for the dynamic message signs that are now being used on Iowa highways, the effect induced by the presence of back-to-back signs, the effect of the presence of add-on exit signs, and the effect of the presence of trucks underneath the signs potentially creating “wind tunnel” effect.
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In this report, we confirm our previous findings of increased concentrations of soluble amyloid-β protein precursor (sAβPP) in cerebrospinal fluid (CSF) of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) in a large cohort of patients (n = 314), not overlapping with those of our previous study, and we extend our observations by including a control group of participants with normal cognition. In addition, we investigate the effects of age, the APOEε4 genotype, and the blood-CSF barrier function on the concentrations of sAβPPα and sAβPPβ. The study participants were categorized according to clinical-neuropsychological criteria, supported by CSF neurochemical dementia diagnostics (NDD) analyses. sAβPPα concentrations in the AD group (132.0 ± 44.8) were significantly higher than in the control group (105.3 ± 37.3, p < 0.0005) but did not differ from the MCI-AD group (138.5 ± 39.5, p = 0.91). The MCI-AD group differed significantly from the MCI-O (97.3 ± 34.3, p < 0.05) group. There was no difference between the control and the MCI-O groups (p = 0.94). Similarly, sAβPPβ concentrations in the AD group (160.2 ± 54.3) were significantly higher than in the control group (129.9 ± 44.6, p < 0.005) but did not differ from the MCI-AD group (184.0 ± 56.4, p = 0.20). The MCI-AD group differed significantly from the MCI-O (127.8 ± 46.2, p < 0.05) group. There was no difference between the control and the MCI-O groups (p > 0.99). We observed highly significant correlation of the two sAβPP forms. Age and the CSF-serum albumin ratio were significant albeit weak predictors of the sAβPPα and sAβPPβ concentrations, while carrying the APOEε4 allele did not influenced the levels of the sAβPP forms. Taken together, the results strongly suggest that CSF sAβPP concentrations may be considered as an extension of already available NDD tools.
Resumo:
Large Dynamic Message Signs (DMSs) have been increasingly used on freeways, expressways and major arterials to better manage the traffic flow by providing accurate and timely information to drivers. Overhead truss structures are typically employed to support those DMSs allowing them to provide wider display to more lanes. In recent years, there is increasing evidence that the truss structures supporting these large and heavy signs are subjected to much more complex loadings than are typically accounted for in the codified design procedures. Consequently, some of these structures have required frequent inspections, retrofitting, and even premature replacement. Two manufacturing processes are primarily utilized on truss structures - welding and bolting. Recently, cracks at welding toes were reported for the structures employed in some states. Extremely large loads (e.g., due to high winds) could cause brittle fractures, and cyclic vibration (e.g., due to diurnal variation in temperature or due to oscillations in the wind force induced by vortex shedding behind the DMS) may lead to fatigue damage, as these are two major failures for the metallic material. Wind and strain resulting from temperature changes are the main loads that affect the structures during their lifetime. The American Association of State Highway and Transportation Officials (AASHTO) Specification defines the limit loads in dead load, wind load, ice load, and fatigue design for natural wind gust and truck-induced gust. The objectives of this study are to investigate wind and thermal effects in the bridge type overhead DMS truss structures and improve the current design specifications (e.g., for thermal design). In order to accomplish the objective, it is necessary to study structural behavior and detailed strain-stress of the truss structures caused by wind load on the DMS cabinet and thermal load on the truss supporting the DMS cabinet. The study is divided into two parts. The Computational Fluid Dynamics (CFD) component and part of the structural analysis component of the study were conducted at the University of Iowa while the field study and related structural analysis computations were conducted at the Iowa State University. The CFD simulations were used to determine the air-induced forces (wind loads) on the DMS cabinets and the finite element analysis was used to determine the response of the supporting trusses to these pressure forces. The field observation portion consisted of short-term monitoring of several DMS Cabinet/Trusses and long-term monitoring of one DMS Cabinet/Truss. The short-term monitoring was a single (or two) day event in which several message sign panel/trusses were tested. The long-term monitoring field study extended over several months. Analysis of the data focused on trying to identify important behaviors under both ambient and truck induced winds and the effect of daily temperature changes. Results of the CFD investigation, field experiments and structural analysis of the wind induced forces on the DMS cabinets and their effect on the supporting trusses showed that the passage of trucks cannot be responsible for the problems observed to develop at trusses supporting DMS cabinets. Rather the data pointed toward the important effect of the thermal load induced by cyclic (diurnal) variations of the temperature. Thermal influence is not discussed in the specification, either in limit load or fatigue design. Although the frequency of the thermal load is low, results showed that when temperature range is large the restress range would be significant to the structure, especially near welding areas where stress concentrations may occur. Moreover stress amplitude and range are the primary parameters for brittle fracture and fatigue life estimation. Long-term field monitoring of one of the overhead truss structures in Iowa was used as the research baseline to estimate the effects of diurnal temperature changes to fatigue damage. The evaluation of the collected data is an important approach for understanding the structural behavior and for the advancement of future code provisions. Finite element modeling was developed to estimate the strain and stress magnitudes, which were compared with the field monitoring data. Fatigue life of the truss structures was also estimated based on AASHTO specifications and the numerical modeling. The main conclusion of the study is that thermal induced fatigue damage of the truss structures supporting DMS cabinets is likely a significant contributing cause for the cracks observed to develop at such structures. Other probable causes for fatigue damage not investigated in this study are the cyclic oscillations of the total wind load associated with the vortex shedding behind the DMS cabinet at high wind conditions and fabrication tolerances and induced stresses due to fitting of tube to tube connections.