The glyoxal budget and its contribution to organic aerosol for Los Angeles, California, during CalNex 2010

Recent laboratory and field studies have indicated that glyoxal is a potentially large contributor to secondary organic aerosol mass. We present in situ glyoxal measurements acquired with a recently developed, high sensitivity spectroscopic instrument during the CalNex 2010 field campaign in Pasadena, California. We use three methods to quantify the production and loss of glyoxal in Los Angeles and its contribution to organic aerosol. First, we calculate the difference between steady state sources and sinks of glyoxal at the Pasadena site, assuming that the remainder is available for aerosol uptake. Second, we use the Master Chemical Mechanism to construct a two-dimensional model for gas-phase glyoxal chemistry in Los Angeles, assuming that the difference between the modeled and measured glyoxal concentration is available for aerosol uptake. Third, we examine the nighttime loss of glyoxal in the absence of its photochemical sources and sinks. Using these methods we constrain the glyoxal loss to aerosol to be 0-5 × 10-5 s-1 during clear days and (1 ± 0.3) × 10-5 s-1 at night. Between 07:00-15:00 local time, the diurnally averaged secondary organic aerosol mass increases from 3.2 μg m-3 to a maximum of 8.8 μg m -3. The constraints on the glyoxal budget from this analysis indicate that it contributes 0-0.2 μg m-3 or 0-4% of the secondary organic aerosol mass. Copyright 2011 by the American Geophysical Union

Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)

Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolic categories were “medium-risk” (D-dimer >1000 ng/mL or CRP >200 mg/L); “high-risk” (D-dimer >3000 ng/mL or CRP >250 mg/L) or “suspected” (D-dimer >5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 69 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolic flag criteria were reached by 568/939 (60.4%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p < 0.0001. Cytokine storm flag criteria were reached by 212 (22.5%) of admissions, including 80/275 (29.0%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p < 0.0001. The maximum thromboembolic flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p < 0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1–28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30–0.37) before traffic light implementation, 0.22 (0.17–0.27) after implementation, p < 0.001. In subgroup analyses, older patients, males, and patients with hypertension (p ≤ 0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy

Arctic marine secondary organic aerosol contributes significantly to summertime particle size distributions in the Canadian Arctic Archipelago

Summertime Arctic aerosol size distributions are strongly controlled by natural regional emissions. Within this context, we use a chemical transport model with sizeresolved aerosol microphysics (GEOS-Chem-TOMAS) to interpret measurements of aerosol size distributions from the Canadian Arctic Archipelago during the summer of 2016, as part of the "NETwork on Climate and Aerosols: Addressing key uncertainties in Remote Canadian Environments" (NETCARE) project. Our simulations suggest that condensation of secondary organic aerosol (SOA) from precursor vapors emitted in the Arctic and near Arctic marine (ice-free seawater) regions plays a key role in particle growth events that shape the aerosol size distributions observed at Alert (82.5° N, 62.3° W), Eureka (80.1° N, 86.4° W), and along a NETCARE ship track within the Archipelago. We refer to this SOA as Arctic marine SOA (AMSOA) to reflect the Arctic marine-based and likely biogenic sources for the precursors of the condensing organic vapors. AMSOA from a simulated flux (500 μgm-2 day-1, north of 50° N) of precursor vapors (with an assumed yield of unity) reduces the summertime particle size distribution model-observation mean fractional error 2- to 4-fold, relative to a simulation without this AMSOA. Particle growth due to the condensable organic vapor flux contributes strongly (30 %-50 %) to the simulated summertime-mean number of particles with diameters larger than 20 nm in the study region. This growth couples with ternary particle nucleation (sulfuric acid, ammonia, and water vapor) and biogenic sulfate condensation to account for more than 90% of this simulated particle number, which represents a strong biogenic influence. The simulated fit to summertime size-distribution observations is further improved at Eureka and for the ship track by scaling up the nucleation rate by a factor of 100 to account for other particle precursors such as gas-phase iodine and/or amines and/or fragmenting primary particles that could be missing from our simulations. Additionally, the fits to the observed size distributions and total aerosol number concentrations for particles larger than 4 nm improve with the assumption that the AMSOA contains semivolatile species: the model-observation mean fractional error is reduced 2- to 3-fold for the Alert and ship track size distributions. AMSOA accounts for about half of the simulated particle surface area and volume distributions in the summertime Canadian Arctic Archipelago, with climaterelevant simulated summertime pan-Arctic-mean top-of-theatmosphere aerosol direct (-0:04Wm-2) and cloud-albedo indirect (-0:4Wm-2) radiative effects, which due to uncertainties are viewed as an order of magnitude estimate. Future work should focus on further understanding summertime Arctic sources of AMSOA

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction

Religion's Role in Promoting Health and Reducing Risk Among American Youth

Although past research has long documented religion's salutary impact on adult health-related behaviors and outcomes, relatively little research has examined the relationship between religion and adolescent health. This study uses large, nationally representative samples of high school seniors to examine the relationship between religion and behavioral predictors of adolescent morbidity and mortality. Relative to their peers, religious youth are less likely to engage in behaviors that compromise their health (e.g., carrying weapons, getting into fights, drinking and driving) and are more likely to behave in ways that enhance their health (e.g., proper nutrition, exercise, and rest). Multivariate analyses suggest that these relationships persist even after controlling for demographic factors, and trend analyses reveal that they have existed over time. Particularly important is the finding that religious seniors have been relatively unaffected by past and recent increases in marijuana use.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66995/2/10.1177_109019819802500604.pd

Feedback as intervention for team learning in virtual teams: the role of team cohesion and personality

Scholars and practitioners agree that virtual teams (VTs) have become commonplace in today's digital workplace. Relevant literature argues that learning constitutes a significant contributor to team member satisfaction and performance, and that, at least in face-to-face teams, team cohesion fosters team learning. Given the additional challenges VTs face, e.g. geographical dispersion, which are likely have a negative influence on cohesion, in this paper we shed light on the relationship between team cohesion and team learning. We adopted a quantitative approach and studied 54 VTs in our quest to understand the role of feedback in mediating this relationship and, more specifically, the role of personality traits in moderating the indirect effect of team feedback and guided reflection intervention on TL through team cohesion within the VT context. Our findings highlight the importance of considering aspects related to the team composition when devising intervention strategies for VTs, and provide empirical support for an interactionist model between personality and emergent states such as cohesion. Implications for theory and practice are also discussed

Identification of Mendelian inconsistencies between SNP and pedigree information of sibs

Background Using SNP genotypes to apply genomic selection in breeding programs is becoming common practice. Tools to edit and check the quality of genotype data are required. Checking for Mendelian inconsistencies makes it possible to identify animals for which pedigree information and genotype information are not in agreement. Methods Straightforward tests to detect Mendelian inconsistencies exist that count the number of opposing homozygous marker (e.g. SNP) genotypes between parent and offspring (PAR-OFF). Here, we develop two tests to identify Mendelian inconsistencies between sibs. The first test counts SNP with opposing homozygous genotypes between sib pairs (SIBCOUNT). The second test compares pedigree and SNP-based relationships (SIBREL). All tests iteratively remove animals based on decreasing numbers of inconsistent parents and offspring or sibs. The PAR-OFF test, followed by either SIB test, was applied to a dataset comprising 2,078 genotyped cows and 211 genotyped sires. Theoretical expectations for distributions of test statistics of all three tests were calculated and compared to empirically derived values. Type I and II error rates were calculated after applying the tests to the edited data, while Mendelian inconsistencies were introduced by permuting pedigree against genotype data for various proportions of animals. Results Both SIB tests identified animal pairs for which pedigree and genomic relationships could be considered as inconsistent by visual inspection of a scatter plot of pairwise pedigree and SNP-based relationships. After removal of 235 animals with the PAR-OFF test, SIBCOUNT (SIBREL) identified 18 (22) additional inconsistent animals. Seventeen animals were identified by both methods. The numbers of incorrectly deleted animals (Type I error), were equally low for both methods, while the numbers of incorrectly non-deleted animals (Type II error), were considerably higher for SIBREL compared to SIBCOUNT. Conclusions Tests to remove Mendelian inconsistencies between sibs should be preceded by a test for parent-offspring inconsistencies. This parent-offspring test should not only consider parent-offspring pairs based on pedigree data, but also those based on SNP information. Both SIB tests could identify pairs of sibs with Mendelian inconsistencies. Based on type I and II error rates, counting opposing homozygotes between sibs (SIBCOUNT) appears slightly more precise than comparing genomic and pedigree relationships (SIBREL) to detect Mendelian inconsistencies between sib

Influence of helium-ion bombardment on the optical properties of ZnO nanorods/p-GaN light-emitting diodes

Light-emitting diodes (LEDs) based on zinc oxide (ZnO) nanorods grown by vapor-liquid-solid catalytic growth method were irradiated with 2-MeV helium (He+) ions. The fabricated LEDs were irradiated with fluencies of approximately 2 × 1013 ions/cm2 and approximately 4 × 1013 ions/cm2. Scanning electron microscopy images showed that the morphology of the irradiated samples is not changed. The as-grown and He+-irradiated LEDs showed rectifying behavior with the same I-V characteristics. Photoluminescence (PL) measurements showed that there is a blue shift of approximately 0.0347 and 0.082 eV in the near-band emission (free exciton) and green emission of the irradiated ZnO nanorods, respectively. It was also observed that the PL intensity of the near-band emission was decreased after irradiation of the samples. The electroluminescence (EL) measurements of the fabricated LEDs showed that there is a blue shift of 0.125 eV in the broad green emission after irradiation and the EL intensity of violet emission approximately centered at 398 nm nearly disappeared after irradiations. The color-rendering properties show a small decrease in the color-rendering indices of 3% after 2 MeV He+ ions irradiation