892 resultados para thickness estimation
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The physical disector is a method of choice for estimating unbiased neuron numbers; nevertheless, calibration is needed to evaluate each counting method. The validity of this method can be assessed by comparing the estimated cell number with the true number determined by a direct counting method in serial sections. We reconstructed a 1/5 of rat lumbar dorsal root ganglia taken from two experimental conditions. From each ganglion, images of 200 adjacent semi-thin sections were used to reconstruct a volumetric dataset (stack of voxels). On these stacks the number of sensory neurons was estimated and counted respectively by physical disector and direct counting methods. Also, using the coordinates of nuclei from the direct counting, we simulate, by a Matlab program, disector pairs separated by increasing distances in a ganglion model. The comparison between the results of these approaches clearly demonstrates that the physical disector method provides a valid and reliable estimate of the number of sensory neurons only when the distance between the consecutive disector pairs is 60 microm or smaller. In these conditions the size of error between the results of physical disector and direct counting does not exceed 6%. In contrast when the distance between two pairs is larger than 60 microm (70-200 microm) the size of error increases rapidly to 27%. We conclude that the physical dissector method provides a reliable estimate of the number of rat sensory neurons only when the separating distance between the consecutive dissector pairs is no larger than 60 microm.
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Les précipitations journalières extrêmes centennales ont été estimées à partir d'analyses de Gumbel et de sept formule empiriques effectuées sur des séries de mesures pluviométriques à 151 endroits de la Suisse pour deux périodes de 50 ans. Ces estimations ont été comparées avec les valeurs journalières maximales mesurées durant les 100 dernières années (1911-2010) afin de tester l'efficacité de ces sept formules. Cette comparaison révèle que la formule de Weibull serait la meilleure pour estimer les précipitations journalières centennales à partir de la série de mesures pluviométriques 1961-2010, mais la moins bonne pour la série de mesures 1911-1960. La formule de Hazen serait la plus efficace pour cette dernière période. Ces différences de performances entre les formules empiriques pour les deux périodes étudiées résultent de l'augmentation des précipitations journalières maximales mesurées de 1911 à 2010 pour 90% des stations en Suisse. Mais les différences entre les pluies extrêmes estimées à partir des sept formules empiriques ne dépassent pas 6% en moyenne.
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Captan and folpet are two fungicides largely used in agriculture, but biomonitoring data are mostly limited to measurements of captan metabolite concentrations in spot urine samples of workers, which complicate interpretation of results in terms of internal dose estimation, daily variations according to tasks performed, and most plausible routes of exposure. This study aimed at performing repeated biological measurements of exposure to captan and folpet in field workers (i) to better assess internal dose along with main routes-of-entry according to tasks and (ii) to establish most appropriate sampling and analysis strategies. The detailed urinary excretion time courses of specific and non-specific biomarkers of exposure to captan and folpet were established in tree farmers (n = 2) and grape growers (n = 3) over a typical workweek (seven consecutive days), including spraying and harvest activities. The impact of the expression of urinary measurements [excretion rate values adjusted or not for creatinine or cumulative amounts over given time periods (8, 12, and 24 h)] was evaluated. Absorbed doses and main routes-of-entry were then estimated from the 24-h cumulative urinary amounts through the use of a kinetic model. The time courses showed that exposure levels were higher during spraying than harvest activities. Model simulations also suggest a limited absorption in the studied workers and an exposure mostly through the dermal route. It further pointed out the advantage of expressing biomarker values in terms of body weight-adjusted amounts in repeated 24-h urine collections as compared to concentrations or excretion rates in spot samples, without the necessity for creatinine corrections.
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OBJECTIVES: The objective of this study was to evaluate associations between aortic pulse wave velocity (PWV) and aortic and carotid vessel wall thickness (VWT) using cardiovascular magnetic resonance imaging (MRI) in patients with hypertension as compared with healthy adult volunteers. MATERIALS AND METHODS: Local medical ethics approval was obtained and the participants gave informed consent. Fifteen patients with hypertension (5 men and 10 women; mean [SD] age, 49 [14] years) and 15 age- and sex-matched healthy volunteers were prospectively included and compared. All participants underwent MRI examination for measuring aortic and carotid VWT and aortic PWV with well-validated MRI techniques at 1.5- and 3-T MRI systems: PWV was assessed from velocity-encoded MRI and VWT was assessed by using dual-inversion black-blood gradient-echo imaging techniques. Paired t tests were used for testing differences between the volunteers and the patients and Pearson correlation (r) and univariable and multivariable stepwise linear regression analyses were used to test associations between aortic and carotid arterial wall thickness and stiffness. RESULTS: Mean values for aortic PWV and aortic and carotid VWT (indexed for body surface area [BSA]) were all significantly higher in patients with hypertension as compared with the healthy volunteers (ie, aortic PWV, 7.0 ± 1.4 m/s vs 5.7 ± 1.3 m/s; aortic VWT/BSA, 0.12 ± 0.03 mL/m vs 0.10 ± 0.03 mL/m; carotid VWT/BSA, 0.04 ± 0.01 mL/m vs 0.03 ± 0.01 mL/m; all P < 0.01). Aortic PWV was highly correlated with aortic VWT/BSA (r = 0.76 and P = 0.002 in the patients vs r = 0.63 and P = 0.02 in the volunteers), and in the patients, aortic PWV was moderately correlated with carotid VWT/BSA (r = 0.50; P = 0.04). In the volunteers, correlation between aortic PWV and carotid VWT/BSA was not significant (r = 0.40; P = 0.13). In addition, aortic VWT/BSA was significantly correlated with carotid VWT/BSA, in both the patients (r = 0.60; P = 0.005) and volunteers (r = 0.57; P = 0.007). CONCLUSIONS: In the patients with hypertension and the healthy volunteers, the aortic PWV is associated more strongly with aortic wall thickness than with carotid wall thickness, reflecting site-specific coupling between vascular wall thickness and function.
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Due to limited budgets and reduced inspection staff, state departments of transportation (DOTs) are in need of innovative approaches for providing more efficient quality assurance on concrete paving projects. The goal of this research was to investigate and test new methods that can determine pavement thickness in real time. Three methods were evaluated: laser scanning, ultrasonic sensors, and eddy current sensors. Laser scanning, which scans the surface of the base prior to paving and then scans the surface after paving, can determine the thickness at any point. Also, scanning lasers provide thorough data coverage that can be used to calculate thickness variance accurately and identify any areas where the thickness is below tolerance. Ultrasonic and eddy current sensors also have the potential to measure thickness nondestructively at discrete points and may result in an easier method of obtaining thickness. There appear to be two viable approaches for measuring concrete pavement thickness during the paving operation: laser scanning and eddy current sensors. Laser scanning has proved to be a reliable technique in terms of its ability to provide virtual core thickness with low variability. Research is still required to develop a prototype system that integrates point cloud data from two scanners. Eddy current sensors have also proved to be a suitable alternative, and are probably closer to field implementation than the laser scanning approach. As a next step for this research project, it is suggested that a pavement thickness measuring device using eddy current sensors be created, which would involve both a handheld and paver-mounted version of the device.
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The primary purpose of this project was to assess the potential of a nondestructive remote sensing system, specifically, ground penetrating subsurface interface radar, for identification and evaluation of D-cracking pavement failures. A secondary purpose was to evaluate the effectiveness of this technique for locating voids under pavements and determining the location of steel reinforcement. From the data collected and the analysis performed to date, the following conclusions can be made regarding the ground penetrating radar system used for this study: (1) steel reinforcement can be accurately located; (2) pavement thickness can be determined; (3) distressed areas in pavements can be located and broadly classified as to severity of deterioration; (4) voids under pavements can be located; and (5) higher resolution recording equipment is required to accurately determine both the thickness of sound pavement remaining over distressed areas and the depth of void areas under pavements.
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As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).
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The knowledge of the relationship that links radiation dose and image quality is a prerequisite to any optimization of medical diagnostic radiology. Image quality depends, on the one hand, on the physical parameters such as contrast, resolution, and noise, and on the other hand, on characteristics of the observer that assesses the image. While the role of contrast and resolution is precisely defined and recognized, the influence of image noise is not yet fully understood. Its measurement is often based on imaging uniform test objects, even though real images contain anatomical backgrounds whose statistical nature is much different from test objects used to assess system noise. The goal of this study was to demonstrate the importance of variations in background anatomy by quantifying its effect on a series of detection tasks. Several types of mammographic backgrounds and signals were examined by psychophysical experiments in a two-alternative forced-choice detection task. According to hypotheses concerning the strategy used by the human observers, their signal to noise ratio was determined. This variable was also computed for a mathematical model based on the statistical decision theory. By comparing theoretical model and experimental results, the way that anatomical structure is perceived has been analyzed. Experiments showed that the observer's behavior was highly dependent upon both system noise and the anatomical background. The anatomy partly acts as a signal recognizable as such and partly as a pure noise that disturbs the detection process. This dual nature of the anatomy is quantified. It is shown that its effect varies according to its amplitude and the profile of the object being detected. The importance of the noisy part of the anatomy is, in some situations, much greater than the system noise. Hence, reducing the system noise by increasing the dose will not improve task performance. This observation indicates that the tradeoff between dose and image quality might be optimized by accepting a higher system noise. This could lead to a better resolution, more contrast, or less dose.
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In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.
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BACKGROUND: Articular surfaces reconstruction is essential in total shoulder arthroplasty. Because of the limited glenoid bone support, thin glenoid component could improve anatomical reconstruction, but adverse mechanical effects might appear. METHODS: With a numerical musculoskeletal shoulder model, we analysed and compared three values of thickness of a typical all-polyethylene glenoid component: 2, 4 (reference) and 6mm. A loaded movement of abduction in the scapular plane was simulated. We evaluated the humeral head translation, the muscle moment arms, the joint force, the articular contact pattern, and the polyethylene and cement stress. Findings Decreasing polyethylene thickness from 6 to 2mm slightly increased humeral head translation and muscle moment arms. This induced a small decreased of the joint reaction force, but important increase of stress within the polyethylene and the cement mantel. Interpretation The reference thickness of 4mm seems a good compromise to avoid stress concentration and joint stuffing.
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This final report for Phase 1 of the research on epoxy-coated, prestressing strands in precast prestressed concrete (PC) panels has been published in two volumes. This volume, Volume 1--Technical Report, contains the problem description, literature review, and survey results; descriptions of the test specimens, experimental tests, and analytical models; discussions of the analytical and experimental results; summary, conclusions, and recommendations; list of references; and acknowledgment. Volume 2--Supplemental Report contains additional information in the form of summarized responses to the questionnaires; graphs showing the strand forces; figures showing the geometry of the specimens and concrete crack patterns that formed in the strand transfer length and strand development length specimens; and graphs of the concrete strains in the strand transfer length specimens, load-point deflections, and strand-slip measurements for the strand development length specimens.
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Preoperative imaging for resection of chest wall malignancies is generally performed by computed tomography (CT). We evaluated the role of (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in planning full-thickness chest wall resections for malignancies. We retrospectively included 18 consecutive patients operated from 2004 to 2006 at our institution. Tumor extent was measured by CT and PET, using the two largest perpendicular tumor extensions in the chest wall plane to compute the tumor surface assuming an elliptical shape. Imaging measurements were compared to histopathology assessment of tumor borders. CT assessment consistently overestimated the tumor size as compared to PET (+64% vs. +1%, P<0.001). Moreover, PET was significantly better than CT at defining the size of lesions >24 cm(2) corresponding to a mean diameter >5.5 cm or an ellipse of >4 cm x 7.6 cm (positive predictive value 80% vs. 44% and specificity 93% vs. 64%, respectively). Metabolic PET imaging was superior to CT for defining the extent of chest wall tumors, particularly for tumors with a diameter >5.5 cm. PET can complement CT in planning full-thickness chest wall resection for malignancies, but its true value remains to be determined in larger, prospective studies.
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