Forecast, observation and modelling of a deep stratospheric intrusion event over Europe

A wide range of measurements was carried out in central and southeastern Europe within the framework of the EU-project STACCATO (Influence of Stratosphere-Troposphere Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity) with the principle goal to create a comprehensive data set on stratospheric air intrusions into the troposphere along a rather frequently observed pathway over central Europe from the North Sea to the Mediterranean Sea. The measurements were based on predictions by suitable quasi-operational trajectory calculations using ECMWF forecast data. A predicted deep Stratosphere to Troposphere Transport (STT) event, encountered during the STACCATO period on 20-21 June 2001, could be followed by the measurements network almost from its inception. Observations provide evidence that the intrusion affected large parts of central and southeastern Europe. Especially, the ozone lidar observations on 20-21 June 2001 at Garmisch-Partenkirchen, Germany captured the evolution of two marked tongues of high ozone with the first one reaching almost a height of 2 km, thus providing an excellent data set for model intercomparisons and validation. In addition, for the first time to our knowledge concurrent measurements of the cosmogenic radionuclides <sup>10</sup>Be and <sup>7</sup>Be and their ratio <sup>10</sup>Be/<sup>7</sup>Be are presented together as stratospheric tracers in a case study of a stratospheric intrusion. The ozone tracer columns calculated with the FLEXPART model were found to be in good agreement with water vapour satellite images, capturing the evolution of the observed dry streamers of stratospheric origin. Furthermore, the time-height cross section of ozone tracer simulated with FLEXPART over Garmisch-Partenkirchen captures with many details the evolution of the two observed high-ozone filaments measured with the IFU lidar, thus demonstrating the considerable progress in model simulations. Finally, the modelled ozone (operationally available since October 1999) from the ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric model is shown to be in very good agreement with the observations during this case study, which provides the first successful validation of a chemical tracer that is used operationally in a weather forecast model. This suggests that coupling chemistry and weather forecast models may significantly improve both weather and chemical forecasts in the future

A Large Catalog of Homogeneous Ultra-Violet/Optical GRB Afterglows: Temporal and Spectral Evolution

We present the second Swift Ultra-Violet/Optical Telescope (UVOT) gamma-ray burst (GRB) afterglow catalog, greatly expanding on the first Swift UVOT GRB afterglow catalog. The second catalog is constructed from a database containing over 120,000 independent UVOT observations of 538 GRBs first detected by Swift, the High Energy Transient Explorer 2 (HETE2), the INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL), the Interplanetary Network (IPN), Fermi, and Astro-rivelatore Gamma a Immagini Leggero (AGILE). The catalog covers GRBs discovered from 2005 Jan 17 to 2010 Dec 25. Using photometric information in three UV bands, three optical bands, and a `white' or open filter, the data are optimally co-added to maximize the number of detections and normalized to one band to provide a detailed light curve. The catalog provides positional, temporal, and photometric information for each burst, as well as Swift Burst Alert Telescope (BAT) and X-Ray Telescope (XRT) GRB parameters. Temporal slopes are provided for each UVOT filter. The temporal slope per filter of almost half the GRBs are fit with a single power-law, but one to three breaks are required in the remaining bursts. Morphological comparisons with the X-ray reveal that approximately 75% of the UVOT light curves are similar to one of the four morphologies identified by Evans et al. (2009). The remaining approximately 25% have a newly identified morphology. For many bursts, redshift and extinction corrected UV/optical spectral slopes are also provided at 2000, 20,000, and 200,000 seconds.Comment: 44 pages, 14 figures, to be published in Astrophysical Journal Supplementa

Mitogenomes reveal two major influxes of Papuan ancestry across Wallacea following the last glacial maximum and Austronesian contact

The tropical archipelago of Wallacea contains thousands of individual islands interspersed between mainland Asia and Near Oceania, and marks the location of a series of ancient oceanic voyages leading to the peopling of Sahul—i.e., the former continent that joined Australia and New Guinea at a time of lowered sea level—by 50,000 years ago. Despite the apparent deep antiquity of human presence in Wallacea, prior population history research in this region has been hampered by patchy archaeological and genetic records and is largely concentrated upon more recent history that follows the arrival of Austronesian seafarers ~3000–4000 years ago (3–4 ka). To shed light on the deeper history of Wallacea and its connections with New Guinea and Australia, we performed phylogeographic analyses on 656 whole mitogenomes from these three regions, including 186 new samples from eight Wallacean islands and three West Papuan populations. Our results point to a surprisingly dynamic population history in Wallacea, marked by two periods of extensive demographic change concentrated around the Last Glacial Maximum ~15 ka and post-Austronesian contact ~3 ka. These changes appear to have greatly diminished genetic signals informative about the original peopling of Sahul, and have important implications for our current understanding of the population history of the region.1. Introduction 2. Materials and Methods 2.1. Sample Collection and Ethics 2.2. Mitochondrial Sequence Generation 2.3. Combined Wallacea–Sahul Dataset 2.4. Phylogenetic Parameter Estimation 2.5. Using Ancestral Node Dates from Geographically Exclusive Clades to Infer Demographic History 2.6. Migration Model Inference and Testing 2.7. Simulating and Estimating the Timing of Migration Events 3. Results 3.1. Summary of New Mitochondrial Haplogroups from Wallacea and West Papua 3.2. Phylogeographic Analyses 4. Discussion 4.1. Post-LGM Population Expansions and Movements 4.2. Redistribution of Papuan mtDNA Lineages Following Austronesian Contact 4.3. Comparison with Wallacean Archaeological and Linguistic Records 5. Conclusion

The Affective Impact of Financial Skewness on Neural Activity and Choice

Few finance theories consider the influence of “skewness” (or large and asymmetric but unlikely outcomes) on financial choice. We investigated the impact of skewed gambles on subjects' neural activity, self-reported affective responses, and subsequent preferences using functional magnetic resonance imaging (FMRI). Neurally, skewed gambles elicited more anterior insula activation than symmetric gambles equated for expected value and variance, and positively skewed gambles also specifically elicited more nucleus accumbens (NAcc) activation than negatively skewed gambles. Affectively, positively skewed gambles elicited more positive arousal and negatively skewed gambles elicited more negative arousal than symmetric gambles equated for expected value and variance. Subjects also preferred positively skewed gambles more, but negatively skewed gambles less than symmetric gambles of equal expected value. Individual differences in both NAcc activity and positive arousal predicted preferences for positively skewed gambles. These findings support an anticipatory affect account in which statistical properties of gambles—including skewness—can influence neural activity, affective responses, and ultimately, choice

FACT -- The G-APD revolution in Cherenkov astronomy

Since two years, the FACT telescope is operating on the Canary Island of La Palma. Apart from its purpose to serve as a monitoring facility for the brightest TeV blazars, it was built as a major step to establish solid state photon counters as detectors in Cherenkov astronomy. The camera of the First G-APD Cherenkov Telesope comprises 1440 Geiger-mode avalanche photo diodes (G-APD), equipped with solid light guides to increase the effective light collection area of each sensor. Since no sense-line is available, a special challenge is to keep the applied voltage stable although the current drawn by the G-APD depends on the flux of night-sky background photons significantly varying with ambient light conditions. Methods have been developed to keep the temperature and voltage dependent response of the G-APDs stable during operation. As a cross-check, dark count spectra with high statistics have been taken under different environmental conditions. In this presentation, the project, the developed methods and the experience from two years of operation of the first G-APD based camera in Cherenkov astronomy under changing environmental conditions will be presented.Comment: Proceedings of the Nuclear Science Symposium and Medical Imaging Conference (IEEE-NSS/MIC), 201

West Nile Virus Infections Projected from Blood Donor Screening Data, United States, 2003

Routine donor nucleic acid amplification testing is a valuable surveillance screening tool

FACT - The First G-APD Cherenkov Telescope: Status and Results

The First G-APD Cherenkov telescope (FACT) is the first telescope using silicon photon detectors (G-APD aka. SiPM). It is built on the mount of the HEGRA CT3 telescope, still located at the Observatorio del Roque de los Muchachos, and it is successfully in operation since Oct. 2011. The use of Silicon devices promises a higher photon detection efficiency, more robustness and higher precision than photo-multiplier tubes. The FACT collaboration is investigating with which precision these devices can be operated on the long-term. Currently, the telescope is successfully operated from remote and robotic operation is under development. During the past months of operation, the foreseen monitoring program of the brightest known TeV blazars has been carried out, and first physics results have been obtained including a strong flare of Mrk501. An instantaneous flare alert system is already in a testing phase. This presentation will give an overview of the project and summarize its goals, status and first results

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Characterization of non-refractory (NR) PM1 and source apportionment of organic aerosol in Krakow, Poland

Kraków is routinely affected by very high air pollution levels, especially during the winter months. Although a lot of effort has been made to characterize ambient aerosol, there is a lack of online and long-term measurements of non-refractory aerosol. Our measurements at the AGH University of Science and Technology provide the online long-term chemical composition of ambient submicron particulate matter (PM1) between January 2018 and April 2019. Here we report the chemical characterization of non-refractory submicron aerosol and source apportionment of the organic fraction by positive matrix factorization (PMF). In contrast to other long-term source apportionment studies, we let a small PMF window roll over the dataset instead of performing PMF over the full dataset or on separate seasons. In this way, the seasonal variation in the source profiles can be captured. The uncertainties in the PMF solutions are addressed by the bootstrap resampling strategy and the random a-value approach for constrained factors. We observe clear seasonal patterns in the concentration and composition of PM1, with high concentrations during the winter months and lower concentrations during the summer months. Organics are the dominant species throughout the campaign. Five organic aerosol (OA) factors are resolved, of which three are of a primary nature (hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and coal combustion OA (CCOA)) and two are of a secondary nature (more oxidized oxygenated OA (MO-OOA) and less oxidized oxygenated OA (LO-OOA)). While HOA contributes on average 8.6 % ± 2.3 % throughout the campaign, the solid-fuel-combustion-related BBOA and CCOA show a clear seasonal trend with average contributions of 10.4 % ± 2.7 % and 14.1 %, ±2.1 %, respectively. Not only BBOA but also CCOA is associated with residential heating because of the pronounced yearly cycle where the highest contributions are observed during wintertime. Throughout the campaign, the OOA can be separated into MO-OOA and LO-OOA with average contributions of 38.4 % ± 8.4 % and 28.5 % ± 11.2 %, respectively