Integration of an Oxidation Catalyst with Pd/Zeolite-Based Passive NOx Adsorbers: Impacts on Degradation Resistance and Desorption Characteristics
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Engineering topics
Publications and source records attributed to Gu, Y.
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Purpose: To assess the reproducibility of quantitative structural features using images from the computed tomography thoracic FDA phantom database under different scanning conditions. Methods: Development of quantitative image features to describe lesion shape and size, beyond conventional RECIST measures, is an evolving area of research in need of benchmarking standards. Gavrielides et al. (2010) scanned a FDA-developed thoracic phantom with nodules of various Hounsfield units (HU) values, shapes and sizes close to vascular structures using several scanners and varying scanning conditions/parameters; these images are in the public domain. We tested six structural features, namely, Convexity, Perimeter, Major Axis, Minor Axis, Extent Mean and Eccentricity, to characterize lung nodules. Convexity measures lesion irregularity referenced to a convex surface. Previously, we showed it to have prognostic value in lung adenocarcinoma. The above metrics and RECIST measures were evaluated on three spiculated (8mm/-300HU, 12mm/+30HU and 15mm/+30HU) and two non-spiculated (8mm/+100HU and 10mm/+100HU) nodules (from layout 2) imaged at three different mAs values: 25, 100 and 200 mAs; on a Phillips scanner (16-slice Mx8000-IDT; 3mm slice thickness). The nodules were segmented semi-automatically using a commercial software tool; the same HU range was used for all nodules. Results: Analysis showed convexity having the lowest maximum coefficient of variation (MCV): 1.1% and 0.6% for spiculated and non-spiculated nodules, respectively, much lower compared to RECIST Major and Minor axes whose MCV were 10.1% and 13.4% for spiculated, and 1.9% and 2.3% for non-spiculated nodules, respectively, across the various mAs. MCVs were consistently larger for speculated nodules. In general, the dependence of structural features on mAs (noise) was low. Conclusion: The FDA phantom CT database may be used for benchmarking of structural features for various scanners and scanning conditions; we used only a small fraction of available data. Our feature convexity outperformed other structural features including RECIST measures.
Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. A total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.
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The climatic effects of dust aerosols in North Africa have been investigated using the atmospheric general circulation model (AGCM) developed at the University of California, Los Angeles (UCLA). The model includes an efficient and physically based radiation parameterization scheme developed specifically for application to clouds and aerosols. Parameterization of the effective ice particle size in association with the aerosol indirect effect based on cloud and aerosol data retrieved from A-Train satellite observations have been employed in the climate model simulations. Offline simulations reveal that the direct solar, IR, and net forcings by dust aerosols generally increase with increasing aerosol optical depth (AOD). When the dust semi-direct effect is included with the presence of ice clouds, positive IR radiative forcing is enhanced, since ice clouds trap substantial IR radiation, while the positive solar forcing with dust aerosols alone has been changed to negative values due to the strong reflection of solar radiation by clouds, indicating that cloud forcing could exceed aerosol forcing. With the aerosol indirect effect, the net cloud forcing is generally reduced for ice water path (IWP) larger than 20 g m-2. The magnitude of the reduction increases with IWP. AGCM simulations show that the reduced ice crystal mean effective size due to the aerosol first indirect effect result in less OLR and net solar flux at the top of the atmosphere over the cloudy area of the North Africa region because ice clouds with smaller size trap more IR radiation and reflect more solar radiation. The precipitation in the same area, however, increases due to the aerosol indirect effect on ice clouds, corresponding to the enhanced convection as indicated by reduced OLR. The increased precipitation seems to be associated with enhanced ice water contents in this region. The 200 mb radiative heating rate shows more cooling with the aerosol indirect effect since greater cooling is produced at the cloud top with smaller ice crystal size. The 500 mb omega indicates strong upward motion, which, together with the increased cooling effect, results in the increased ice water contents. Adding the aerosol direct effect into the model simulation reduces the precipitation in the normal rainfall band over North Africa, where precipitation is shifted to the south and the northeast produced by the absorption of sunlight and the subsequent heating of the air column by dust particles. As a result, rainfall is drawn further inland to the northeast. This study represents the first attempt to quantify the climate impact of aerosol indirect effect using a GCM in connection with A-train satellite data. The parameterization for the aerosol first indirect effect developed in this study can be readily incorporated for application to any other GCMs.
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