A Theory of Unstaggered Airfoil Cascades in Compressible Flow

By use of the methods of thin airfoil theory, which include effects of compressibility, rela.tio^as are developed which permit the rapid determination of the pressure distribution over an unstaggered cascade of airfoils of a given profile, and the determination of the profile shape necessary to yield a given pressure distribution for small chord gap ratios, For incompressible flow the results of the theory are compared with available examples obtained by the more exact method of conformal transformation. Although the theory is developed for small chord/gap ratios, these comparisons show that it may be extended to chord/gap ratios of order unity, at least for low speed flows. Choking of cascades, a phenomenon of particular importance in compressor design, is considered

X-Ray Microanalysis of Hollow Heart Potatoes

Electron microprobe and X-ray fluorescence techniques were used to study elemental gradients associated with the physiological disorder hollow heart i n potato tubers. Gradients were found along the length and across the width of mature tubers. These were not rela ted to the disorder, however . Tubers with advanced symptoms of the disorder had elemental levels and gradients similar to those in healthy, control tubers. The results suggest that if the disorder is initially caused by an elemental deficiency, as has sometimes been proposed , the deficiency is temporary and no longer exists in mature tubers with advanced hollow heart. Radial gradients were associated rnd inly with two contrasting tissues . the centra 1 pith and the surrounding perimedullary zone. Tissue differences are critical in microprobe studies involving small samples Microprobe studies of developing tubers containing incipient stages of hollow heart. employing strip samples restricted to the central pith where the disorder originates and taken so as to traverse the small lesions, showed a dramatic increase in Mg in lesion areas. It is suggested that a nutrient imbalance may trigger the onset of the cell necrosis that characterizes the initiation of hollow heart in potato . A localized Mg toxicity or Ca deficiency due to high Mg:Ca ratio is implicated

Synthesis of satellite (MODIS), aircraft (ICARTT), and surface (IMPROVE, EPA-AQS, AERONET) aerosol observations over eastern North America to improve MODIS aerosol retrievals and constrain surface aerosol concentrations and sources

We use an ensemble of satellite (MODIS), aircraft, and ground-based aerosol observations during the ICARTT field campaign over eastern North America in summer 2004 to (1) examine the consistency between different aerosol measurements, (2) evaluate a new retrieval of aerosol optical depths (AODs) and inferred surface aerosol concentrations (PM2.5) from the MODIS satellite instrument, and (3) apply this collective information to improve our understanding of aerosol sources. The GEOS-Chem global chemical transport model (CTM) provides a transfer platform between the different data sets, allowing us to evaluate the consistency between different aerosol parameters observed at different times and locations. We use an improved MODIS AOD retrieval based on locally derived visible surface reflectances and aerosol properties calculated from GEOS-Chem. Use of GEOS-Chem aerosol optical properties in the MODIS retrieval not only results in an improved AOD product but also allows quantitative evaluation of model aerosol mass from the comparison of simulated and observed AODs. The aircraft measurements show narrower aerosol size distributions than those usually assumed in models, and this has important implications for AOD retrievals. Our MODIS AOD retrieval compares well to the ground-based AERONET data (R = 0.84, slope = 1.02), significantly improving on the MODIS c005 operational product. Inference of surface PM2.5 from our MODIS AOD retrieval shows good correlation to the EPA-AQS data (R = 0.78) but a high regression slope (slope = 1.48). The high slope is seen in all AOD-inferred PM2.5 concentrations (AERONET: slope = 2.04; MODIS c005: slope = 1.51) and could reflect a clear-sky bias in the AOD observations. The ensemble of MODIS, aircraft, and surface data are consistent in pointing to a model overestimate of sulfate in the mid-Atlantic and an underestimate of organic and dust aerosol in the southeastern United States. The sulfate overestimate could reflect an excessive contribution from aqueous-phase production in clouds, while the organic carbon underestimate could possibly be resolved by a new secondary pathway involving dicarbonyls

New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO2 dataset: Algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new-generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of predefined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50% reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (∼1700 kt total SO2/ and Sierra Negra in 2005 (\u3e 1100DU maximum SO2/, OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments

Version 2 Ozone Monitoring Instrument SO2 product (OMSO2 V2): New anthropogenic SO2 vertical column density dataset

The Ozone Monitoring Instrument (OMI) has been providing global observations of SO2 pollution since 2004. Here we introduce the new anthropogenic SO2 vertical column density (VCD) dataset in the version 2 OMI SO2 product (OMSO2 V2). As with the previous version (OMSO2 V1.3), the new dataset is generated with an algorithm based on principal component analysis of OMI radiances but features several updates. The most important among those is the use of expanded lookup tables and model a priori profiles to estimate SO2 Jacobians for individual OMI pixels, in order to better characterize pixel-to-pixel variations in SO2 sensitivity including over snow and ice. Additionally, new data screening and spectral fitting schemes have been implemented to improve the quality of the spectral fit. As compared with the planetary boundary layer SO2 dataset in OMSO2 V1.3, the new dataset has substantially better data quality, especially over areas that are relatively clean or affected by the South Atlantic Anomaly. The updated retrievals over snow/ice yield more realistic seasonal changes in SO2 at high latitudes and offer enhanced sensitivity to sources during wintertime. An error analysis has been conducted to assess uncertainties in SO2 VCDs from both the spectral fit and Jacobian calculations. The uncertainties from spectral fitting are reflected in SO2 slant column densities (SCDs) and largely depend on the signal-to-noise ratio of the measured radiances, as implied by the generally smaller SCD uncertainties over clouds or for smaller solar zenith angles. The SCD uncertainties for individual pixels are estimated to be 0.15-0.3DU (Dobson units) between 40 S and 40 N and to be 0.2-0.5DU at higher latitudes. The uncertainties from the Jacobians are approximately 50 %-100% over polluted areas and are primarily attributed to errors in SO2 a priori profiles and cloud pressures, as well as the lack of explicit treatment for aerosols. Finally, the daily mean and median SCDs over the presumably SO2-free equatorial east Pacific have increased by only 0.0035DU and 0.003DU respectively over the entire 15-year OMI record, while the standard deviation of SCDs has grown by only 0.02DU or 10%. Such remarkable long-term stability makes the new dataset particularly suitable for detecting regional changes in SO2 pollution

GeTallele: A Method for Analysis of DNA and RNA Allele Frequency Distributions

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData Availability Statement: The data analyzed in this study is subject to the following licenses/restrictions: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Requests to access these datasets should be directed to [email protected] allele frequencies (VAF) are an important measure of genetic variation that can be estimated at single-nucleotide variant (SNV) sites. RNA and DNA VAFs are used as indicators of a wide-range of biological traits, including tumor purity and ploidy changes, allele-specific expression and gene-dosage transcriptional response. Here we present a novel methodology to assess gene and chromosomal allele asymmetries and to aid in identifying genomic alterations in RNA and DNA datasets. Our approach is based on analysis of the VAF distributions in chromosomal segments (continuous multi-SNV genomic regions). In each segment we estimate variant probability, a parameter of a random process that can generate synthetic VAF samples that closely resemble the observed data. We show that variant probability is a biologically interpretable quantitative descriptor of the VAF distribution in chromosomal segments which is consistent with other approaches. To this end, we apply the proposed methodology on data from 72 samples obtained from patients with breast invasive carcinoma (BRCA) from The Cancer Genome Atlas (TCGA). We compare DNA and RNA VAF distributions from matched RNA and whole exome sequencing (WES) datasets and find that both genomic signals give very similar segmentation and estimated variant probability profiles. We also find a correlation between variant probability with copy number alterations (CNA). Finally, to demonstrate a practical application of variant probabilities, we use them to estimate tumor purity. Tumor purity estimates based on variant probabilities demonstrate good concordance with other approaches (Pearson's correlation between 0.44 and 0.76). Our evaluation suggests that variant probabilities can serve as a dependable descriptor of VAF distribution, further enabling the statistical comparison of matched DNA and RNA datasets. Finally, they provide conceptual and mechanistic insights into relations between structure of VAF distributions and genetic events. The methodology is implemented in a Matlab toolbox that provides a suite of functions for analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies distributions. GeTallele is available at: https://github.com/SlowinskiPiotr/GeTalleleMcCormick Genomic and Proteomic Center (MGPC)George Washington UniversityWellcome TrustEngineering and Physical Sciences Research Council (EPSRC

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view