984 resultados para Diffusion measurements


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Purpose: To evaluate inter- and intraobserver variability of indices crucial for detection of keratoconus progression derived from the Pentacam HR® (high-resolution) tomographer (OCULUS Optikgeräte GmbH, Wetzlar, Germany) in patients with mild to moderate keratoconus. Methods: Three repeated corneal topography measurements in the 25-picture mode by two independent observers were performed. The extent of variability across a large range of measurement parameters was analyzed including anterior and posterior corneal surface measurements, pachymetry values, corneal volume, anterior chamber volume and depth, and iridocorneal angle. The intraclass correlation coefficient (ICC) between and within each investigator was calculated to assess reproducibility and repeatability, respectively. Results: 31 eyes of 20 patients (mean age 31.6, SD ± 8.6) were included. Overall, the repeatability and reproducibility were excellent. The range of variability was reported by calculating the standard deviation of measurements. The detailed results are shown in Table 1. Conclusions: This study shows that the Pentacam HR® tomographer provides reliable measurements in patients with mild to moderate keratoconus. However, all parameters showed a certain range of variability. This should be taken into account when assessing keratoconus progression in order to distinguish true progression from variability in measurements. In addition, the excellent reproducibility suggests that the measurements can be reliably performed by different individuals from one visit to another.

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We study hydrogen stability and its evolution during thermal annealing in nanostructured amorphous silicon thin films. From the simultaneous measurement of heat and hydrogen desorption, we obtain the experimental evidence of molecular diffusion in these materials. In addition, we introduce a simple diffusion model which shows good agreement with the experimental data

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The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration, a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of certain constraints involving the sigmoid master curve coefficients. The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing (related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine implementation, future research recommendations have been provided making a strong case for an expanded research study.

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An effect of drift is investigated on the segregation pattern in diffusion-limited aggregation (DLA) with two components (A and B species). The sticking probability PAB (=PBA) between the different species is introduced into the DLA model with drift, where the sticking probability PAA (=PBB) between the same species equals 1. By using computer simulation it is found that the drift has an important effect on not only the morphology but also the segregation pattern. Under the drift and the small sticking probability, a characteristic pattern appears where elongated clusters of A species and of B species are periodically dispersed. The period decreases with increasing drift. The periodic structure of the deposits is characterized by an autocorrelation function. The shape of the cluster consisting of only A species (or B species) shows a vertically elongated filamentlike structure. Each cluster becomes vertically longer with decreasing sticking probability PAB. The segregation pattern is distinctly different from that with no drift and a small sticking probability PAA. The effect of the concentration on the segregation pattern is also shown.

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Recently a fingering morphology, resembling the hydrodynamic Saffman-Taylor instability, was identified in the quasi-two-dimensional electrodeposition of copper. We present here measurements of the dispersion relation of the growing front. The instability is accompanied by gravity-driven convection rolls at the electrodes, which are examined using particle image velocimetry. While at the anode the theory presented by Chazalviel et al. [J. Electroanal. Chem. 407, 61 (1996)] describes the convection roll, the flow field at the cathode is more complicated because of the growing deposit. In particular, the analysis of the orientation of the velocity vectors reveals some lag of the development of the convection roll compared to the finger envelope.

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Schizophrenia is a complex psychiatric disorder characterized by disabling symptoms and cognitive deficit. Recent neuroimaging findings suggest that large parts of the brain are affected by the disease, and that the capacity of functional integration between brain areas is decreased. In this study we questioned (i) which brain areas underlie the loss of network integration properties observed in the pathology, (ii) what is the topological role of the affected regions within the overall brain network and how this topological status might be altered in patients, and (iii) how white matter properties of tracts connecting affected regions may be disrupted. We acquired diffusion spectrum imaging (a technique sensitive to fiber crossing and slow diffusion compartment) data from 16 schizophrenia patients and 15 healthy controls, and investigated their weighted brain networks. The global connectivity analysis confirmed that patients present disrupted integration and segregation properties. The nodal analysis allowed identifying a distributed set of brain nodes affected in the pathology, including hubs and peripheral areas. To characterize the topological role of this affected core, we investigated the brain network shortest paths layout, and quantified the network damage after targeted attack toward the affected core. The centrality of the affected core was compromised in patients. Moreover the connectivity strength within the affected core, quantified with generalized fractional anisotropy and apparent diffusion coefficient, was altered in patients. Taken together, these findings suggest that the structural alterations and topological decentralization of the affected core might be major mechanisms underlying the schizophrenia dysconnectivity disorder. Hum Brain Mapp, 36:354-366, 2015. © 2014 Wiley Periodicals, Inc.

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Lutetium zoning in garnet within eclogites from the Zermatt-Saas Fee zone, Western Alps, reveal sharp, exponentially decreasing central peaks. They can be used to constrain maximum Lu volume diffusion in garnets. A prograde garnet growth temperature interval of 450-600 A degrees C has been estimated based on pseudosection calculations and garnet-clinopyroxene thermometry. The maximum pre-exponential diffusion coefficient which fits the measured central peak is in the order of D-0= 5.7*10(-6) m(2)/s, taking an estimated activation energy of 270 kJ/mol based on diffusion experiments for other rare earth elements in garnet. This corresponds to a maximum diffusion rate of D (600 A degrees C) = 4.0*10(-22) m(2)/s. The diffusion estimate of Lu can be used to estimate the minimum closure temperature, T-c, for Sm-Nd and Lu-Hf age data that have been obtained in eclogites of the Western Alps, postulating, based on a literature review, that D (Hf) < D (Nd) < D (Sm) a parts per thousand currency sign D (Lu). T-c calculations, using the Dodson equation, yielded minimum closure temperatures of about 630 A degrees C, assuming a rapid initial exhumation rate of 50A degrees/m.y., and an average crystal size of garnets (r = 1 mm). This suggests that Sm/Nd and Lu/Hf isochron age differences in eclogites from the Western Alps, where peak temperatures did rarely exceed 600 A degrees C must be interpreted in terms of prograde metamorphism.

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The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.

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A model has been developed for evaluating grain size distributions in primary crystallizations where the grain growth is diffusion controlled. The body of the model is grounded in a recently presented mean-field integration of the nucleation and growth kinetic equations, modified conveniently in order to take into account a radius-dependent growth rate, as occurs in diffusion-controlled growth. The classical diffusion theory is considered, and a modification of this is proposed to take into account interference of the diffusion profiles between neighbor grains. The potentiality of the mean-field model to give detailed information on the grain size distribution and transformed volume fraction for transformations driven by nucleation and either interface- or diffusion-controlled growth processes is demonstrated. The model is evaluated for the primary crystallization of an amorphous alloy, giving an excellent agreement with experimental data. Grain size distributions are computed, and their properties are discussed.

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To study telomere length dynamics in hematopoietic cells with age, we analyzed the average length of telomere repeat sequences in diverse populations of nucleated blood cells. More than 500 individuals ranging in age from 0 to 90 yr, including 36 pairs of monozygous and dizygotic twins, were analyzed using quantitative fluorescence in situ hybridization and flow cytometry. Granulocytes and naive T cells showed a parallel biphasic decline in telomere length with age that most likely reflected accumulated cell divisions in the common precursors of both cell types: hematopoietic stem cells. Telomere loss was very rapid in the first year, and continued for more than eight decades at a 30-fold lower rate. Memory T cells also showed an initial rapid decline in telomere length with age. However, in contrast to naive T cells, this decline continued for several years, and in older individuals lymphocytes typically had shorter telomeres than did granulocytes. Our findings point to a dramatic decline in stem cell turnover in early childhood and support the notion that cell divisions in hematopoietic stem cells and T cells result in loss of telomeric DNA.

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Concrete paving is often at a disadvantage in terms of pavement type selection due to the time of curing required prior to opening the pavement to traffic. The State of Iowa has been able to reduce traffic delay constraints through material selection and construction methods to date. Methods for monitoring concrete strength gain and quality have not changed since the first concrete pavements were constructed in Iowa. In 1995, Lee County and the Iowa DOT cooperated in a research project, HR-380, to construct a 7.1 mile (11. 43 km) project to evaluate the use of maturity and pulse velocity nondestructive testing (NDT) methods in the estimation of concrete strength gain. The research identified the pros and cons of each method and suggested an instructional memorandum to utilize maturity measurements to meet traffic delay demands. Maturity was used to reduce the traffic delay opening time from 5-7 days to less than 2 days through the implementation of maturity measurements and special traffic control measures. Recommendations on the development of the maturity curve for each project and the location and monitoring of the maturity thermocouples are included. Examples of equipment that could easily be used by project personnel to estimate the concrete strength using the maturity methods is described.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.