Serum ferritin is an independent risk factor for acute respiratory distress syndrome in COVID-19

Increased ferritin levels could be indicative of a strong inflammatory reaction in COVID-19 and recent studies suggest that increased levels of circulating ferritin levels play a critical role by contributing to the development of a cytokine storm. In this regard, ferritin evaluation could be an early, available and easy to use screening tool to assess the disease severity at the first admission in the emergency department. This test might be of crucial importance for the timely identification of patients at higher risk of an adverse outcome

New procedures for testing whether stock price processes are martingales

We propose procedures for testing whether stock price processes are martingales based on limit order type betting strategies. We first show that the null hypothesis of martingale property of a stock price process can be tested based on the capital process of a betting strategy. In particular with high frequency Markov type strategies we find that martingale null hypotheses are rejected for many stock price processes

Combined theoretical and experimental study of the transmission of tilted ion beams through macroscopic conical glass capillaries

The transmission as a function of the tilt angle of a 3 keV Ar+ ion beam through a conical macroscopic glass capillary is studied theoretically and experimentally. It was found that the charge patches which are responsible for the ion guiding also compress the beam spatially in the direction orthogonal to the patches, resulting into an enhancement of the transmission with increasing tilt angle

Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic-and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003-2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates

Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic-and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003-2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates

Development and demonstration of a Lagrangian dispersion modeling system for real‐time prediction of smoke haze pollution from biomass burning in Southeast Asia

Abstract Transboundary smoke haze caused by biomass burning frequently causes extreme air pollution episodes in maritime and continental Southeast Asia. With millions of people being affected by this type of pollution every year, the task to introduce smoke haze related air quality forecasts is urgent. We investigate three severe haze episodes: June 2013 in Maritime SE Asia, induced by fires in central Sumatra, and March/April 2013 and 2014 on mainland SE Asia. Based on comparisons with surface measurements of PM10 we demonstrate that the combination of the Lagrangian dispersion model NAME with emissions derived from satellite‐based active‐fire detection provides reliable forecasts for the region. Contrasting two fire emission inventories shows that using algorithms to account for fire pixel obscuration by cloud or haze better captures the temporal variations and observed persistence of local pollution levels. Including up‐to‐date representations of fuel types in the area and using better conversion and emission factors is found to more accurately represent local concentration magnitudes, particularly for peat fires. With both emission inventories the overall spatial and temporal evolution of the haze events is captured qualitatively, with some error attributed to the resolution of the meteorological data driving the dispersion process. In order to arrive at a quantitative agreement with local PM10 levels, the simulation results need to be scaled. Considering the requirements of operational forecasts, we introduce a real‐time bias correction technique to the modeling system to address systematic and random modeling errors, which successfully improves the results in terms of reduced normalized mean biases and fractional gross errors

Charge separation relative to the reaction plane in Pb-Pb collisions at sNN=2.76\sqrt{s_{\rm NN}}= 2.76 TeV

Measurements of charge dependent azimuthal correlations with the ALICE detector at the LHC are reported for Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV. Two- and three-particle charge-dependent azimuthal correlations in the pseudo-rapidity range $|\eta| < 0.8$ are presented as a function of the collision centrality, particle separation in pseudo-rapidity, and transverse momentum. A clear signal compatible with a charge-dependent separation relative to the reaction plane is observed, which shows little or no collision energy dependence when compared to measurements at RHIC energies. This provides a new insight for understanding the nature of the charge dependent azimuthal correlations observed at RHIC and LHC energies.Comment: 12 pages, 3 captioned figures, authors from page 2 to 6, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/286