994 resultados para Serial method
Resumo:
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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The role of busulfan (Bu) metabolites in the adverse events seen during hematopoietic stem cell transplantation and in drug interactions is not explored. Lack of availability of established analytical methods limits our understanding in this area. The present work describes a novel gas chromatography-tandem mass spectrometric assay for the analysis of sulfolane (Su) in plasma of patients receiving high-dose Bu. Su and Bu were extracted from a single 100 μL plasma sample by liquid-liquid extraction. Bu was separately derivatized with 2,3,5,6-tetrafluorothiophenolfluorinated agent. Mass spectrometric detection of the analytes was performed in the selected reaction monitoring mode on a triple quadrupole instrument after electronic impact ionization. Bu and Su were analyzed with separate chromatographic programs, lasting 5 min each. The assay for Su was found to be linear in the concentration range of 20-400 ng/mL. The method has satisfactory sensitivity (lower limit of quantification, 20 ng/mL) and precision (relative standard deviation less than 15 %) for all the concentrations tested with a good trueness (100 ± 5 %). This method was applied to measure Su from pediatric patients with samples collected 4 h after dose 1 (n = 46), before dose 7 (n = 56), and after dose 9 (n = 54) infusions of Bu. Su (mean ± SD) was detectable in plasma of patients 4 h after dose 1, and higher levels were observed after dose 9 (249.9 ± 123.4 ng/mL). This method may be used in clinical studies investigating the role of Su on adverse events and drug interactions associated with Bu therapy.
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Background: b-value is the parameter characterizing the intensity of the diffusion weighting during image acquisition. Data acquisition is usually performed with low b value (b~1000 s/mm2). Evidence shows that high b-values (b>2000 s/mm2) are more sensitive to the slow diffusion compartment (SDC) and maybe more sensitive in detecting white matter (WM) anomalies in schizophrenia.Methods: 12 male patients with schizophrenia (mean age 35 +/-3 years) and 16 healthy male controls matched for age were scanned with a low b-value (1000 s/mm2) and a high b-value (4000 s/mm2) protocol. Apparent diffusion coefficient (ADC) is a measure of the average diffusion distance of water molecules per time unit (mm2/s). ADC maps were generated for all individuals. 8 region of interests (frontal and parietal region bilaterally, centrum semi-ovale bilaterally and anterior and posterior corpus callosum) were manually traced blind to diagnosis.Results: ADC measures acquired with high b-value imaging were more sensitive in detecting differences between schizophrenia patients and healthy controls than low b-value imaging with a gain in significance by a factor of 20- 100 times despite the lower image Signal-to-noise ratio (SNR). Increased ADC was identified in patient's WM (p=0.00015) with major contributions from left and right centrum semi-ovale and to a lesser extent right parietal region.Conclusions: Our results may be related to the sensitivity of high b-value imaging to the SDC believed to reflect mainly the intra-axonal and myelin bound water pool. High b-value imaging might be more sensitive and specific to WM anomalies in schizophrenia than low b-value imaging
A fully validated method for the determination of arsenic species in rice and infant cereal products
Resumo:
A full validation of inorganic arsenic (iAs), methylarsonic acid (MA), and dimethyl arsinic acid (DMA) in several types of rice and rice-based infant cereals is reported. The analytical method was developed and validated in two laboratories. The extraction of the As species was performed using nitric acid 0.2 % and hydrogen peroxide 1 %, and the coupled system liquid chromatography-inductively coupled plasma-mass spectrometry (LCICP-MS) was used for speciation measurements. Detection limit (DL), quantification limit, linearity, precision, trueness, accuracy, selectivity, as well as expanded uncertainty for iAs, MA, and DMA were established. The certified reference materials (CRMs) (NMIJ 7503a, NCS ZC73008, NIST SRM 1568a) were used to check the accuracy. The method was shown to be satisfactory in two proficiency tests (PTs). The broad applicability of the method is shown from the results of analysis of 29 samples including several types of rice, rice products, and infant cereal products. Total As ranged from 40.1 to 323.7 μg As kg1. From the speciation results, iAs was predominant, and DMA was detected in some samples while MA was not detected in any sample.
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Visual inspection remains the most frequently applied method for detecting treatment effects in single-case designs. The advantages and limitations of visual inference are here discussed in relation to other procedures for assessing intervention effectiveness. The first part of the paper reviews previous research on visual analysis, paying special attention to the validation of visual analysts" decisions, inter-judge agreement, and false alarm and omission rates. The most relevant factors affecting visual inspection (i.e., effect size, autocorrelation, data variability, and analysts" expertise) are highlighted and incorporated into an empirical simulation study with the aim of providing further evidence about the reliability of visual analysis. Our results concur with previous studies that have reported the relationship between serial dependence and increased Type I rates. Participants with greater experience appeared to be more conservative and used more consistent criteria when assessing graphed data. Nonetheless, the decisions made by both professionals and students did not match sufficiently the simulated data features, and we also found low intra-judge agreement, thus suggesting that visual inspection should be complemented by other methods when assessing treatment effectiveness.
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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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If single case experimental designs are to be used to establish guidelines for evidence-based interventions in clinical and educational settings, numerical values that reflect treatment effect sizes are required. The present study compares four recently developed procedures for quantifying the magnitude of intervention effect using data with known characteristics. Monte Carlo methods were used to generate AB designs data with potential confounding variables (serial dependence, linear and curvilinear trend, and heteroscedasticity between phases) and two types of treatment effect (level and slope change). The results suggest that data features are important for choosing the appropriate procedure and, thus, inspecting the graphed data visually is a necessary initial stage. In the presence of serial dependence or a change in data variability, the Nonoverlap of All Pairs (NAP) and the Slope and Level Change (SLC) were the only techniques of the four examined that performed adequately. Introducing a data correction step in NAP renders it unaffected by linear trend, as is also the case for the Percentage of Nonoverlapping Corrected Data and SLC. The performance of these techniques indicates that professionals" judgments concerning treatment effectiveness can be readily complemented by both visual and statistical analyses. A flowchart to guide selection of techniques according to the data characteristics identified by visual inspection is provided.
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Diffusion-weighting in magnetic resonance imaging (MRI) increases the sensitivity to molecular Brownian motion, providing insight in the micro-environment of the underlying tissue types and structures. At the same time, the diffusion weighting renders the scans sensitive to other motion, including bulk patient motion. Typically, several image volumes are needed to extract diffusion information, inducing also inter-volume motion susceptibility. Bulk motion is more likely during long acquisitions, as they appear in diffusion tensor, diffusion spectrum and q-ball imaging. Image registration methods are successfully used to correct for bulk motion in other MRI time series, but their performance in diffusion-weighted MRI is limited since diffusion weighting introduces strong signal and contrast changes between serial image volumes. In this work, we combine the capability of free induction decay (FID) navigators, providing information on object motion, with image registration methodology to prospectively--or optionally retrospectively--correct for motion in diffusion imaging of the human brain. Eight healthy subjects were instructed to perform small-scale voluntary head motion during clinical diffusion tensor imaging acquisitions. The implemented motion detection based on FID navigator signals is processed in real-time and provided an excellent detection performance of voluntary motion patterns even at a sub-millimetre scale (sensitivity≥92%, specificity>98%). Motion detection triggered an additional image volume acquisition with b=0 s/mm2 which was subsequently co-registered to a reference volume. In the prospective correction scenario, the calculated motion-parameters were applied to perform a real-time update of the gradient coordinate system to correct for the head movement. Quantitative analysis revealed that the motion correction implementation is capable to correct head motion in diffusion-weighted MRI to a level comparable to scans without voluntary head motion. The results indicate the potential of this method to improve image quality in diffusion-weighted MRI, a concept that can also be applied when highest diffusion weightings are performed.
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A new method was developed for breaking high strength prestressed cable. The old method used an aluminum oxide grit packed into a special gripping jaw. The new method uses aluminum shims wrapped around the cable and then is gripped with a V-grip. The new method gives nearly 100% "good breaks" on the cable compared to approximately 10% good breaks with the old method. In addition, the new cable breaking method gives higher ultimate tensile strengths, is more reproducible, is quicker, cleaner and easier on equipment.
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Purpose: Although several approaches have been already used to reduce radiation dose, CT doses are still among the high doses in radio-diagnostic. Recently, General Electric introduced a new imaging reconstruction technique, adaptive statistical iterative reconstruction (ASIR), allows to taking into account the statistical fluctuation of noise. The benefits of ASIR method were assessed through classic metrics and the evaluations of cardiac structures by radiologists. Methods and materials: A 64-row CT (MDCT) was employed. Catphan600 phantom acquisitions and 10 routine-dose CT examinations performed at 80 kVp were reconstructed with FBP and with 50% of ASIR. Six radiologists then assessed the visibility of main cardiac structures using the visual grading analysis (VGA) method. Results: On phantoms, for a constant value of SD (25 HU), CTDIvol is divided by 2 (8 mGy to 4 mGy) when 50% of ASIR is used. At constant CTDIvol, MTF medium frequencies were also significantly improved. First results indicated that clinical images reconstructed with ASIR had a better overall image quality compared with conventional reconstruction. This means that at constant image quality the radiation dose can be strongly reduced. Conclusion: The first results of this study shown that the ASIR method improves the image quality on phantoms by decreasing noise and improving resolution with respect to the classical one. Moreover, the benefit obtained is higher at lower doses. In clinical environment, a dose reduction can still be expected on 80 kVp low dose pediatric protocols using 50% of iterative reconstruction. Best ASIR percentage as a function of cardiac structures and detailed protocols will be presented for cardiac examinations.
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A new aggregation method for decision making is presented by using induced aggregation operators and the index of maximum and minimum level. Its main advantage is that it can assess complex reordering processes in the aggregation that represent complex attitudinal characters of the decision maker such as psychological or personal factors. A wide range of properties and particular cases of this new approach are studied. A further generalization by using hybrid averages and immediate weights is also presented. The key issue in this approach against the previous model is that we can use the weighted average and the ordered weighted average in the same formulation. Thus, we are able to consider the subjective attitude and the degree of optimism of the decision maker in the decision process. The paper ends with an application in a decision making problem based on the use of the assignment theory.
Resumo:
The main objective of this work was to compare two methods to estimate the deposition of pesticide applied by aerial spraying. Hundred and fifty pieces of water sensitive paper were distributed over an area of 50 m length by 75 m width for sampling droplets sprayed by an aircraft calibrated to apply a spray volume of 32 L/ha. The samples were analysed by visual microscopic method using NG 2 Porton graticule and by an image analyser computer program. The results reached by visual microscopic method were the following: volume median diameter, 398±62 mum; number median diameter, 159±22 mum; droplet density, 22.5±7.0 droplets/cm² and estimated deposited volume, 22.2±9.4 L/ha. The respective ones reached with the computer program were: 402±58 mum, 161±32 mum, 21.9±7.5 droplets/cm² and 21.9±9.2 L/ha. Graphs of the spatial distribution of droplet density and deposited spray volume on the area were produced by the computer program.