25 research outputs found

    Observations of the Askaryan Effect in Ice

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    We report on the first observations of the Askaryan effect in ice: coherent impulsive radio Cherenkov radiation from the charge asymmetry in an electromagnetic (EM) shower. Such radiation has been observed in silica sand and rock salt, but this is the first direct observation from an EM shower in ice. These measurements are important since the majority of experiments to date that rely on the effect for ultra-high energy neutrino detection are being performed using ice as the target medium. As part of the complete validation process for the Antarctic Impulsive Transient Antenna (ANITA) experiment, we performed an experiment at the Stanford Linear Accelerator Center (SLAC) in June 2006 using a 7.5 metric ton ice target, yielding results fully consistent with theoretical expectations

    New Limits on the Ultra-high Energy Cosmic Neutrino Flux from the ANITA Experiment

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    We report initial results of the first flight of the Antarctic Impulsive Transient Antenna (ANITA-1) 2006-2007 Long Duration Balloon flight, which searched for evidence of a diffuse flux of cosmic neutrinos above energies of 3 EeV. ANITA-1 flew for 35 days looking for radio impulses due to the Askaryan effect in neutrino-induced electromagnetic showers within the Antarctic ice sheets. We report here on our initial analysis, which was performed as a blind search of the data. No neutrino candidates are seen, with no detected physics background. We set model-independent limits based on this result. Upper limits derived from our analysis rule out the highest cosmogenic neutrino models. In a background horizontal-polarization channel, we also detect six events consistent with radio impulses from ultra-high energy extensive air showers.Comment: 4 pages, 2 table

    Searching for dark matter annihilation in recently discovered Milky Way satellites with Fermi-LAT

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    We search for excess γ-ray emission coincident with the positions of confirmed and candidate Milky Way satellite galaxies using six years of data from the Fermi Large Area Telescope (LAT). Our sample of 45 stellar systems includes 28 kinematically confirmed dark-matter-dominated dwarf spheroidal galaxies (dSphs) and 17 recently discovered systems that have photometric characteristics consistent with the population of known dSphs. For each of these targets, the relative predicted γ-ray flux due to dark matter annihilation is taken from kinematic analysis if available, and estimated from a distance-based scaling relation otherwise, assuming that the stellar systems are DM-dominated dSphs. LAT data coincident with four of the newly discovered targets show a slight preference (each ~2σ local) for γ-ray emission in excess of the background. However, the ensemble of derived γ-ray flux upper limits for individual targets is consistent with the expectation from analyzing random blank-sky regions, and a combined analysis of the population of stellar systems yields no globally significant excess (global significance 1 TeV and mDM,t+t-> 70 GeV) and weakening by a factor of ~1.5 at lower masses relative to previously observed limits

    Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

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    We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods—ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ—are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z’s. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z ¼ f0.45; 0.67; 1.00g. These bins each have systematic uncertainties δz ≲ 0.05 in the mean of the fiducial SKYNET photo-z nðzÞ. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of σ8 of approximately 3%. This shift is within the one sigma statistical errors on σ8 for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, Σcrit, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of nðzÞ of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis

    Peri-operative red blood cell transfusion in neonates and infants: NEonate and Children audiT of Anaesthesia pRactice IN Europe: A prospective European multicentre observational study

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    BACKGROUND: Little is known about current clinical practice concerning peri-operative red blood cell transfusion in neonates and small infants. Guidelines suggest transfusions based on haemoglobin thresholds ranging from 8.5 to 12 g dl-1, distinguishing between children from birth to day 7 (week 1), from day 8 to day 14 (week 2) or from day 15 (≥week 3) onwards. OBJECTIVE: To observe peri-operative red blood cell transfusion practice according to guidelines in relation to patient outcome. DESIGN: A multicentre observational study. SETTING: The NEonate-Children sTudy of Anaesthesia pRactice IN Europe (NECTARINE) trial recruited patients up to 60 weeks' postmenstrual age undergoing anaesthesia for surgical or diagnostic procedures from 165 centres in 31 European countries between March 2016 and January 2017. PATIENTS: The data included 5609 patients undergoing 6542 procedures. Inclusion criteria was a peri-operative red blood cell transfusion. MAIN OUTCOME MEASURES: The primary endpoint was the haemoglobin level triggering a transfusion for neonates in week 1, week 2 and week 3. Secondary endpoints were transfusion volumes, 'delta haemoglobin' (preprocedure - transfusion-triggering) and 30-day and 90-day morbidity and mortality. RESULTS: Peri-operative red blood cell transfusions were recorded during 447 procedures (6.9%). The median haemoglobin levels triggering a transfusion were 9.6 [IQR 8.7 to 10.9] g dl-1 for neonates in week 1, 9.6 [7.7 to 10.4] g dl-1 in week 2 and 8.0 [7.3 to 9.0] g dl-1 in week 3. The median transfusion volume was 17.1 [11.1 to 26.4] ml kg-1 with a median delta haemoglobin of 1.8 [0.0 to 3.6] g dl-1. Thirty-day morbidity was 47.8% with an overall mortality of 11.3%. CONCLUSIONS: Results indicate lower transfusion-triggering haemoglobin thresholds in clinical practice than suggested by current guidelines. The high morbidity and mortality of this NECTARINE sub-cohort calls for investigative action and evidence-based guidelines addressing peri-operative red blood cell transfusions strategies. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT02350348

    Mapping Invasive Phragmites australis in the Old Woman Creek Estuary Using UAV Remote Sensing and Machine Learning Classifiers

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    Unmanned aerial vehicles (UAV) are increasingly used for spatiotemporal monitoring of invasive plants in coastal wetlands. Early identification of invasive species is necessary in planning, restoring, and managing wetlands. This study assessed the effectiveness of UAV technology to identify invasive Phragmites australis in the Old Woman Creek (OWC) estuary using machine learning (ML) algorithms: Neural network (NN), support vector machine (SVM), and k-nearest neighbor (kNN). The ML algorithms were compared with the parametric maximum likelihood classifier (MLC) using pixel- and object-based methods. Pixel-based NN was identified as the best classifier with an overall accuracy of 94.80% and the lowest error of omission of 1.59%, the outcome desirable for effective eradication of Phragmites. The results were reached combining Sequoia multispectral imagery (green, red, red edge, and near-infrared bands) combined with the canopy height model (CHM) acquired in the mid-growing season and normalized difference vegetation index (NDVI) acquired later in the season. The sensitivity analysis, using various vegetation indices, image texture, CHM, and principal components (PC), demonstrated the impact of various feature layers on the classifiers. The study emphasizes the necessity of a suitable sampling and cross-validation methods, as well as the importance of optimum classification parameters

    Development and usability testing of an electronic patient-reported outcome (ePRO) solution for patients with inflammatory diseases in an Advanced Therapy Medicinal Product (ATMP) basket trial

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    Background: Electronic patient-reported outcome (ePRO) systems are increasingly used in clinical trials to provide evidence of efficacy and tolerability of treatment from the patient perspective. The aim of this study is twofold: (1) to describe how we developed an electronic platform for patients to report their symptoms, and (2) to develop and undertake usability testing of an ePRO solution for use in a study of cell therapy seeking to provide early evidence of efficacy and tolerability of treatment and test the feasibility of the system for use in later phase studies. Methods: An ePRO system was designed to be used in a single arm, multi-centre, phase II basket trial investigating the safety and activity of the use of ORBCEL-C™ in the treatment of patients with inflammatory conditions. ORBCEL-C™ is an enriched Mesenchymal Stromal Cells product isolated from human umbilical cord tissue using CD362+ cell selection. Usability testing sessions were conducted using cognitive interviews and the ‘Think Aloud’ method with patient advisory group members and Research Nurses to assess the usability of the system. Results: Nine patient partners and seven research nurses took part in one usability testing session. Measures of fatigue and health-related quality of life, the PRO-CTCAE™ and FACT-GP5 global tolerability question were included in the ePRO system. Alert notifications to the clinical team were triggered by PRO-CTCAE™ and FACT-GP5 scores. Patient participants liked the simplicity and responsiveness of the patient-facing app. Two patients were unable to complete the testing session, due to technical issues. Research Nurses suggested minor modifications to improve functionality and the layout of the clinician dashboard and the training materials. Conclusion: By testing the effectiveness, efficiency, and satisfaction of our novel ePRO system (PROmicsR), we learnt that most people with an inflammatory condition found it easy to report their symptoms using an app on their own device. Their experiences using the PROmicsR ePRO system within a trial environment will be further explored in our upcoming feasibility testing. Research nurses were also positive and found the clinical dashboard easy-to-use. Using ePROs in early phase trials is important in order to provide evidence of therapeutic responses and tolerability, increase the evidence based, and inform methodology development. Trial registration: ISRCTN, ISRCTN80103507. Registered 01 April 2022, https://www.isrctn.com/ISRCTN8010350

    Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS

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    We present the results of the first observations of the emission line galaxies (ELG) of the extended Baryon Oscillation Spectroscopic Survey. From the total 9000 targets, 4600 have been selected from the Dark Energy Survey (DES). In this subsample, the total success rate for redshifts between 0.6 and 1.2 is 71 and 68 per cent for a bright and a faint samples, respectively, including redshifts measured from a single strong emission line. The mean redshift is 0.80 for the bright and 0.87 for the faint sample, while the percentage of unknown redshifts is 15 and 13 per cent, respectively. In both cases, the star contamination is lower than 2 per cent. We evaluate how well the ELG redshifts are measured using the target selection photometry and validating with the spectroscopic redshifts measured by eBOSS. We explore different techniques to reduce the photometric redshift outliers fraction with a comparison between the template fitting, the neural networks and the random forest methods. Finally, we study the clustering properties of the DES SVA1 ELG samples. We select only the most secure spectroscopic redshift in the redshift range 0.6 < z < 1.2, leading to a mean redshift for the bright and faint sample of 0.85 and 0.90, respectively. We measure the projected angular correlation function and obtain a galaxy bias averaging on scales from 1 to 10 Mpc h−1 of 1.58 ± 0.10 for the bright sample and 1.65 ± 0.12 for the faint sample. These values are representative of a galaxy population with MB − log(h) < −20.5, in agreement with what we measure by fitting galaxy templates to the photometric data
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