ANTARES: Progress towards building a `Broker' of time-domain alerts

The Arizona-NOAO Temporal Analysis and Response to Events System (ANTARES) is a joint effort of NOAO and the Department of Computer Science at the University of Arizona to build prototype software to process alerts from time-domain surveys, especially LSST, to identify those alerts that must be followed up immediately. Value is added by annotating incoming alerts with existing information from previous surveys and compilations across the electromagnetic spectrum and from the history of past alerts. Comparison against a knowledge repository of properties and features of known or predicted kinds of variable phenomena is used for categorization. The architecture and algorithms being employed are described

Machine Learning-based Brokers for Real-time Classification of the LSST Alert Stream

The unprecedented volume and rate of transient events that will be discovered by the Large Synoptic Survey Telescope (LSST) demands that the astronomical community update its followup paradigm. Alert-brokers -- automated software system to sift through, characterize, annotate and prioritize events for followup -- will be critical tools for managing alert streams in the LSST era. The Arizona-NOAO Temporal Analysis and Response to Events System (ANTARES) is one such broker. In this work, we develop a machine learning pipeline to characterize and classify variable and transient sources only using the available multiband optical photometry. We describe three illustrative stages of the pipeline, serving the three goals of early, intermediate and retrospective classification of alerts. The first takes the form of variable vs transient categorization, the second, a multi-class typing of the combined variable and transient dataset, and the third, a purity-driven subtyping of a transient class. While several similar algorithms have proven themselves in simulations, we validate their performance on real observations for the first time. We quantitatively evaluate our pipeline on sparse, unevenly sampled, heteroskedastic data from various existing observational campaigns, and demonstrate very competitive classification performance. We describe our progress towards adapting the pipeline developed in this work into a real-time broker working on live alert streams from time-domain surveys.Comment: 33 pages, 14 figures, submitted to ApJ

Wavelet Methods for Photometric Classification of Supernovae

Several fundamental experiments in physics and astronomy, such as the discovery of dark energy and the accelerated expansion of the Universe, have relied on the study of transient events -- short-lived astrophysical sources which allow only a narrow time window for study before fading into obscurity. Transient studies have largely relied on humans with significant domain expertise to identify these rare events within the thousands of detections, and tens of thousands of false detection artifacts from wide-field astronomical surveys. However, with volumes of data from astronomical surveys increasing rapidly, moving past human inspection of these transient phenomena has now become of paramount importance. In this senior honors thesis, I outline an automated method to analyze, characterize and classify transient events discovered by large-scale synoptic surveys. This project combines algorithms from signal processing and machine-learning, and applies them to a complex astrophysical problem. I explore the properties of a specific class of transient phenomenon: supernovae. I attempt to restructure the sparse, unevenly sampled, heteroskedastic data from various existing observational campaigns. I use Gaussian Processes to generate a non-parametric representation of the time-domain supernovae data, or light curves\u27 , apply wavelet methods for feature extraction that allow for approximate translation invariance, and employ a Random Forest classifier algorithm to distinguish between supernovae types. Initial results from our classification scheme indicate good performance for all wavelet classes. The classification code will be used in a stage of the ANTARES pipeline, created for use on the upcoming Large Synoptic Survey Telescope and other precursor wide-field surveys

Characterization of metal-resistant plant-growth promoting Bacillus weihenstephanensis isolated from serpentine soil in Portugal

A metal-resistant bacterial strain SM3 isolated from a serpentine soil in the north-east of Portugal was characterized as Bacillus weihenstephanensis based on the morphological and biochemical characteristics and on the comparative analysis of the partial 16S ribosomal DNA sequence. Bacillus weihenstephanensis SM3 showed a high degree of resistance to nickel (1500 mg l-1), copper (500 mg l-1) and zinc (700 mg l-1) and also to antibiotics (ampicillin, penicillin, kanamycin and streptomycin). Strain SM3 has also exhibited the capability of solubilizing phosphate and producing indole-3-acetic acid (IAA) both in the absence and in the presence of metals (Ni, Cu and Zn). A pot experiment was conducted to elucidate the effects of strain SM3 on plant growth and uptake of Ni, Cu or Zn by Helianthus annuus. Inoculation with strain SM3 increased the shoot and root biomass of H. annuus grown in both non-contaminated and contaminated soil. Furthermore, strain SM3 increased the accumulation of Cu and Zn in the root and shoot systems. A batch experiment was also conducted to assess the metal mobilization potential of strain SM3 in soil. Inoculation with this strain increased the concentrations of water soluble Ni, Cu and Zn in soil. Metal solubilization by this bacterial strain may be an important process to promote the uptake of heavy metals by plants. This study elucidates the multifarious role of strain SM3 in plant growth promotion and its metal mobilizing potential. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Cost-effectiveness of gallbladder histopathology after cholecystectomy for benign disease

Background The prevalence of incidental gallbladder cancer is low when performing cholecystectomy for benign disease. The performance of routine or selective histological examination of the gallbladder is still a subject for discussion. The aim of this study was to assess the cost-effectiveness of these different approaches. Methods Four management strategies were evaluated using decision-analytical modelling: no histology, current selective histology as practised in Sweden, macroscopic selective histology, and routine histology. Healthcare costs and life-years were estimated for a lifetime perspective and combined into incremental cost-effectiveness ratios (ICERs) to assess the additional cost of achieving an additional life-year for each management strategy. Results In the analysis of the four strategies, current selective histology was ruled out due to a higher ICER compared with macroscopic selective histology, which showed better health outcomes (extended dominance). Comparison of routine histology with macroscopic selective histology resulted in a gain of 12 life-years and an incremental healthcare cost of approximately euro1 000 000 in a cohort of 10 000 patients, yielding an estimated ICER of euro76 508. When comparing a macroscopic selective strategy with no histological assessment, 50 life-years would be saved and the ICER was estimated to be euro20 708 in a cohort of 10 000 patients undergoing cholecystectomy. Conclusion A macroscopic selective strategy appears to be the most cost-effective approach

Multiple novel astrovirus species in human stool

Diarrhoea remains a significant cause of morbidity and mortality in developing countries where numerous cases remain without identified aetiology. Astroviruses are a recently identified cause of animal gastroenteritis which currently includes two species suspected of causing human diarrhoea. Using pan-astrovirus RT-PCR, we analysed human stool samples from different continents for astrovirus-related RNA sequences. We identified variants of the two known human astrovirus species plus, based on genetic distance criteria, three novel astrovirus species all distantly related to mink and ovine astroviruses, which we provisionally named HMOAstV species A–C. The complete genome of species A displayed all the conserved characteristics of mammalian astroviruses. Each of the now three groups of astroviruses found in human stool (HAstV, AstV-MLB and HMOAstV) were more closely related to animal astroviruses than to each other, indicating that human astroviruses may periodically emerge from zoonotic transmissions. Based on the pathogenic impact of their closest phylogenetic relatives in animals, further investigations of the role of HMOAstV, so far detected in Nigeria, Nepal and Pakistan, in human gastroenteritis are warranted