SN 1995ah-the first supernova observed in a Blue Compact Dwarf galaxy

We present the properties of the supernova SN 1995ah discovered in a Blue Compact Dwarf galaxy (BCD) around 10 days after the maximum. This is the first supernova event observed in a BCD. The photometric and spectroscopic data suggest that SN 1995ah is a Type II supernova and could belong to the rare Bright SNII Linear subclass, for which ~=-18.9+-0.6 at maximum light.Comment: 6 pages, late

Regional Differences in Antithrombotic Treatment for Atrial Fibrillation:Insights from the GLORIA-AF Phase II Registry

Introduction Although guideline-adherent antithrombotic therapy (ATT) for stroke prevention in atrial fibrillation (AF) is associated with lower mortality and thromboembolism, ATT uptake shows geographic variation worldwide. We aimed to assess thromboembolic risk and baseline ATT by geographic region and identify factors associated with prescription of ATT in a large, truly global registry of patients with recently diagnosed AF. Methods and Results Our analysis comprises 15,092 patients newly diagnosed with non-valvular AF at risk for stroke, enrolled in Phase II of Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF). Global oral anticoagulation (OAC) use was 79.9%, being highest in Europe (90.1%), followed by Africa/Middle East (87.4%) and Latin America (85.3%), North America (78.3%) and Asia (55.2%). Among OAC users, vitamin K antagonists (VKAs) have been replaced by non-VKA OACs (NOACs) as the more prevalent OAC option in all regions, with highest use in North America (66.5%) and lowest in Asia (50.2%). In Asia, OAC was 80.4% in community hospitals but only 49.8% in university hospitals and 42.6% in specialist offices, and varied from 21.0% in China to 89.7% in Japan (NOACs at 5.8% in China and 83.3% in Japan). Globally, 76.5% of low-risk patients were prescribed ATT (46.1% OAC), whereas 17.7% high-risk patients were not anticoagulated (Europe 8.8%; North America 18.9%; Asia 42.4%). Conclusion Substantial inter- and intra-regional differences in ATT for stroke prevention in AF are evident in this global registry. While guideline-adherent ATT can be further improved, NOACs are the main contributor to high OAC use worldwide.</jats:p

Removal of the pesticide tebuconazole in constructed wetlands: design comparison, influencing factors and modelling

Constructed wetlands (CWs) are a promising technology to treat pesticide contaminated water, but its implementation is impeded by lack of data to optimize designs and operating factors. Unsaturated and saturated CW designs were used to compare the removal of triazole pesticide, tebuconazole, in unplanted mesocosms and mesocosms planted with five different plant species: Typha latifolia, Phragmites australis, Iris pseudacorus, Juncus effusus and Berula erecta. Tebuconazole removal efficiencies were significantly higher in unsaturated CWs than saturated CWs, showing for the first time the potential of unsaturated CWs to treat tebuconazole contaminated water. An artificial neural network model was demonstrated to provide more accurate predictions of tebuconazole removal than the traditional linear regression model. Also, tebuconazole removal could be fitted an area-based first order kinetics model in both CW designs. The removal rate constants were consistently higher in unsaturated CWs (range of 2.6–10.9 cm d−1) than in saturated CWs (range of 1.7–7.9 cm d−1) and higher in planted CWs (range of 3.1–10.9 cm d−1) than in unplanted CWs (range of 1.7–2.6 cm d−1) for both designs. The low levels of sorption of tebuconazole to the substrate (0.7–2.1%) and plant phytoaccumulation (2.5–12.1%) indicate that the major removal pathways were biodegradation and metabolization inside the plants after plant uptake. The main factors influencing tebuconazole removal in the studied systems were system design, hydraulic loading rate and plant presence. Moreover, tebuconazole removal was positively correlated to dissolved oxygen and all nutrients removal

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase&nbsp;1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation&nbsp;disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age&nbsp; 6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score&nbsp; 652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc&nbsp;= 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N&nbsp;= 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in&nbsp;Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in&nbsp;Asia&nbsp;and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701