Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients

The authors would like to thank David Kirkby and Connor Sheere for insightful discussions. This work is part of the Recommendation System for Spectroscopic Followup (RESSPECT) project, governed by an inter-collaboration agreement signed between the Cosmostatistics Initiative (COIN) and the LSST Dark Energy Science Collaboration (DESC). This research is supported in part by the HPI Research Center in Machine Learning and Data Science at UC Irvine. EEOI and SS acknowledge financial support from CNRS 2017 MOMENTUM grant under the project Active Learning for Large Scale Sky Surveys. SGG and AKM acknowledge support by FCT under Project CRISP PTDC/FIS-AST-31546/2017. This work was partly supported by the Hewlett Packard Enterprise Data Science Institute (HPE DSI) at the University of Houston. DOJ is supported by a Gordon and Betty Moore Foundation postdoctoral fellowship at the University of California, Santa Cruz. Support for this work was provided by NASA through the NASA Hubble Fellowship grant HF2-51462.001 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. BQ is supported by the International Gemini Observatory, a program of NSF's NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation, on behalf of the Gemini partnership of Argentina, Brazil, Canada, Chile, the Republic of Korea, and the United States of America. AIM acknowledges support from the Max Planck Society and the Alexander von Humboldt Foundation in the framework of the Max Planck-Humboldt Research Award endowed by the Federal Ministry of Education and Research. L.G. was funded by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 839090. This work has been partially supported by the Spanish grant PGC2018-095317-B-C21 within the European Funds for Regional Development (FEDER).The recent increase in volume and complexity of available astronomical data has led to a wide use of supervised machine learning techniques. Active learning strategies have been proposed as an alternative to optimize the distribution of scarce labeling resources. However, due to the specific conditions in which labels can be acquired, fundamental assumptions, such as sample representativeness and labeling cost stability cannot be fulfilled. The Recommendation System for Spectroscopic followup (RESSPECT) project aims to enable the construction of optimized training samples for the Rubin Observatory Legacy Survey of Space and Time (LSST), taking into account a realistic description of the astronomical data environment. In this work, we test the robustness of active learning techniques in a realistic simulated astronomical data scenario. Our experiment takes into account the evolution of training and pool samples, different costs per object, and two different sources of budget. Results show that traditional active learning strategies significantly outperform random sampling. Nevertheless, more complex batch strategies are not able to significantly overcome simple uncertainty sampling techniques. Our findings illustrate three important points: 1) active learning strategies are a powerful tool to optimize the label-acquisition task in astronomy, 2) for upcoming large surveys like LSST, such techniques allow us to tailor the construction of the training sample for the first day of the survey, and 3) the peculiar data environment related to the detection of astronomical transients is a fertile ground that calls for the development of tailored machine learning algorithms.HPI Research Center in Machine Learning and Data Science at UC IrvineCNRS 2017 MOMENTUM grant under the project Active Learning for Large Scale Sky SurveysFCT under Project CRISP PTDC/FIS-AST-31546/2017Hewlett Packard Enterprise Data Science Institute (HPE DSI) at the University of HoustonGordon and Betty Moore Foundation postdoctoral fellowship at the University of California, Santa CruzSpace Telescope Science InstituteNational Aeronautics & Space Administration (NASA) HF2-51462.001 NAS5-26555International Gemini Observatory, a program of NSF's NOIRLabNational Science Foundation (NSF)Max Planck SocietyFoundation CELLEXAlexander von Humboldt FoundationEuropean Commission 839090Spanish grant within the European Funds for Regional Development (FEDER) PGC2018-095317-B-C2

A characterization of ASAS-SN core-collapse supernova environments with VLT+MUSE: I. Sample selection, analysis of local environments, and correlations with light curve properties

The analysis of core-collapse supernova (CCSN) environments can provide important information on the life cycle of massive stars and constrain the progenitor properties of these powerful explosions. The MUSE instrument at the VLT enables detailed local environment constraints of the progenitors of large samples of CCSNe. Using a homogeneous SN sample from the ASAS-SN survey has enabled us to perform a minimally biased statistical analysis of CCSN environments. We analyze 111 galaxies observed by MUSE that hosted 112 CCSNe detected or discovered by the ASAS-SN survey between 2014 and 2018. The majority of the galaxies were observed by the the AMUSING survey. Here we analyze the immediate environment around the SN locations and compare the properties between the different CCSN types and their light curves. We used stellar population synthesis and spectral fitting techniques to derive physical parameters for all HII regions detected within each galaxy, including the star formation rate (SFR), H$\alpha$ equivalent width (EW), oxygen abundance, and extinction. We found that stripped-envelope (SE) SNe occur in environments with a higher median SFR, H$\alpha$ EW, and oxygen abundances than SNe II and SNe IIn/Ibn. The distributions of SNe II and IIn are very similar, indicating that these events explode in similar environments. For the SESNe, SNe Ic have higher median SFRs, H$\alpha$ EWs, and oxygen abundances than SNe Ib. SNe IIb have environments with similar SFRs and H$\alpha$ EWs to SNe Ib, and similar oxygen abundances to SNe Ic. We also show that the postmaximum decline rate, $s$, of SNe II correlates with the H$\alpha$ EW, and that the luminosity and the $\Delta m_{15}$ parameter of SESNe correlate with the oxygen abundance, H$\alpha$ EW, and SFR at their environments. This suggests a connection between the explosion mechanisms of these events to their environment properties

The carbon-rich type Ic supernova 2016adj in the iconic dust lane of Centaurus A: signatures of interaction with circumstellar hydrogen?

We present a comprehensive data set of supernova (SN) 2016adj located within the central dust lane of Centaurus A. SN 2016adj is significantly reddened and after correcting the peak apparent $B$-band magnitude ($m_B = 17.48\pm0.05$) for Milky Way reddening and our inferred host-galaxy reddening parameters (i.e., $R_{V}^{host} = 5.7\pm0.7$ and $A_{V}^{host} = 6.3\pm0.2$), we estimate it reached a peak absolute magnitude of $M_B \sim -18$. Detailed inspection of the optical/NIR spectroscopic time-series reveals a carbon-rich SN Ic and not a SN Ib/IIb as previously suggested in the literature. The NIR spectra shows prevalent carbon-monoxide formation occurring already by +41 days past $B$-band maximum, which is $\approx 11$ days earlier than previously reported in the literature for this object. Interestingly around two months past maximum, the NIR spectrum of SN~2016adj begins to exhibit H features, with a +97~d medium resolution spectrum revealing both Paschen and Bracket lines with absorption minima of $\sim 2000$ km/s, full-width-half-maximum emission velocities of $\sim 1000$ km/s, and emission line ratios consistent with a dense emission region. We speculate these attributes are due to circumstellar interaction (CSI) between the rapidly expanding SN ejecta and a H-rich shell of material formed during the pre-SN phase. A bolometric light curve is constructed and a semi-analytical model fit suggests the supernova synthesized 0.5 solar masses of $^{56}$Ni and ejected 4.2 solar masses of material, though these values should be approached with caution given the large uncertainties associated with the adopted reddening parameters, possible CSI contamination, and known light echo emission. Finally, inspection of Hubble Space Telescope archival data yielded no progenitor detection.Comment: Submitted to A&A, comments are welcom

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Supernova Rates, Rise-Ttmes and their Relations to Progenitors

Supernovae are fundamental in astronomy: they inject high mass elements into the interstellar medium enriching the chemistry of galaxies, they feed processes of star formation and active galactic nuclei, and they have been a key for the developments in cosmology of the past decades. This dissertation presents a set of subluminous type Ia supernovae (SNe Ia) at z>0.1 from the Supernova Legacy Survey (SNLS). These faint and short-lived transients are found in massive and passive host galaxies. We measure a volumetric rate as a function of redshift that is different from the normal SNIa population. The observations point towards a long delay time since the birth of the progenitors systems and argue for progenitor stars of initial low mass. We calculate a stretch-corrected rise-time since explosion to maximum brightness for different sets of SNe~Ia. We find that a fiducial 17 day quadratic rise is sufficient to explain all SNe Ia, including subluminous ones, arguing for their homogeneity throughout the entire light-curve. Subluminous SNe Ia are powered by as little as 0.05 solar masses of radioactive nickel synthesized in the explosion. Theoretical models need to explain these challenging weak explosions within the framework of SNe Ia. Finally, we develop one of the first robust automated techniques to identify plateau supernovae (SNe IIP) in large photometric transient surveys. This simple method was tested with a variety of real and simulated SN samples and proved to be effective across different redshifts. Such a photometric typing will be of great power for coming surveys and will allow numerous scientific studies of SNe IIP.Ph