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We present a search for magnetically broadened gamma-ray emission around active galactic nuclei (AGNs), using VERITAS observations of seven hard-spectrum blazars. A cascade process occurs when multi-TeV gamma-rays from an AGN interact with extragalactic background light (EBL) photons to produce electron-positron pairs, which then interact with cosmic microwave background photons via inverse-Compton scattering to produce gamma-rays. Due to the deflection of the electron- positron pairs, a non-zero intergalactic magnetic field (IGMF) would potentially produce detectable effects on the angular distribution of the cascade emission. In particular, an angular broadening compared to the unscattered emission could occur. Through non-detection of angularly broadened emission from 1ES 1218 vertical bar 304, the source with the largest predicted cascade fraction, we exclude a range of IGMF strengths around 10(-14) G at the 95% confidence level. The extent of the exclusion range varies with the assumptions made about the intrinsic spectrum of 1ES. 1218+304 and the EBL model used in the simulation of the cascade process. All of the sources are used to set limits on the flux due to extended emission.
We present a new measurement of the energy spectrum of iron nuclei in cosmic rays from 20 TeV to 500 TeV; The measurement makes use of a template-based analysis method, which, for the first time, is applied to the energy reconstruction of iron-induced air showers recorded by the VERITAS array of imaging atmospheric Cherenkov telescopes. The event selection makes use of the direct Cherenkov light which is emitted by charged particles before the first interaction, as well as other parameters related to the shape of the recorded air shower images. The measured spectrum is well described by a power law dF/dE = f(0) center dot (E/E-0)(-gamma) over the full energy range, with gamma = 2.82 +/- 0.30(stat)(-0.27)(+0.24)(syst) and f(0) = (4.82 +/- 0.98(stat)(-2.70)(+2.12)(syst)) x 10(-7) m(-2) s(-1) TeV-1 sr(-1) at E-0 = 50 TeV, with no indication of a cutoff or spectral break. The measured differential flux is compatible with previous results, with improved statistical uncertainty at the highest energies.
HESS J1943+213
(2018)
HESS J1943+213 is a very high energy (VHE; > 100 GeV) gamma-ray source in the direction of the Galactic plane. Studies exploring the classification of the source are converging toward its identification as an extreme synchrotron BL Lac object. Here we present 38 hr of VERITAS observations of HESS J1943+213 taken over 2 yr. The source is detected with a significance of similar to 20 standard deviations, showing a remarkably stable flux and spectrum in VHE gamma-rays. Multifrequency Very Long Baseline Array (VLBA) observations of the source confirm the extended, jet-like structure previously found in the 1.6 GHz band with the European VLBI Network and detect this component in the 4.6 and 7.3 GHz bands. The radio spectral indices of the core and the jet and the level of polarization derived from the VLBA observations are in a range typical for blazars. Data from VERITAS, Fermi-LAT, Swift-XRT, the FLWO 48 ' telescope, and archival infrared and hard X-ray observations are used to construct and model the spectral energy distribution (SED) of the source with a synchrotron self-Compton model. The well-measured gamma-ray peak of the SED with VERITAS and Fermi-LAT provides constraining upper limits on the source redshift. Possible contribution of secondary gamma-rays from ultra-high-energy cosmic-ray-initiated electromagnetic cascades to the gamma-ray emission is explored, finding that only a segment of the VHE spectrum can be accommodated with this process. A variability search is performed across X-ray and gamma-ray bands. No statistically significant flux or spectral variability is detected.
We present results from deep observations toward the Cygnus region using 300 hr of very high energy (VHE)gamma-ray data taken with the VERITAS Cerenkov telescope array and over 7 yr of high-energy.-ray data taken with the Fermi satellite at an energy above 1 GeV. As the brightest region of diffuse gamma-ray emission in the northern sky, the Cygnus region provides a promising area to probe the origins of cosmic rays. We report the identification of a potential Fermi-LAT counterpart to VER J2031+415 (TeV J2032+4130) and resolve the extended VHE source VER J2019+368 into two source candidates (VER J2018+367* and VER J2020+368*) and characterize their energy spectra. The Fermi-LAT morphology of 3FGL J2021.0+4031e (the Gamma Cygni supernova remnant) was examined, and a region of enhanced emission coincident with VER J2019+407 was identified and jointly fit with the VERITAS data. By modeling 3FGL J2015.6+3709 as two sources, one located at the location of the pulsar wind nebula CTB 87 and one at the quasar QSO J2015+371, a continuous spectrum from 1 GeV to 10 TeV was extracted for VER J2016+371 (CTB 87). An additional 71 locations coincident with Fermi-LAT sources and other potential objects of interest were tested for VHE gamma-ray emission, with no emission detected and upper limits on the differential flux placed at an average of 2.3% of the Crab Nebula flux. We interpret these observations in a multiwavelength context and present the most detailed gamma-ray view of the region to date.
On 2015 March 23, the Very Energetic Radiation Imaging Telescope Array System (VERITAS) responded to a Swift-Burst Alert Telescope (BAT) detection of a gamma-ray burst, with observations beginning 270 s after the onset of BAT emission, and only 135 s after the main BAT emission peak. No statistically significant signal is detected above 140 GeV. The VERITAS upper limit on the fluence in a 40-minute integration corresponds to about 1% of the prompt fluence. Our limit is particularly significant because the very-high-energy (VHE) observation started only similar to 2 minutes after the prompt emission peaked, and Fermi-Large Area Telescope observations of numerous other bursts have revealed that the high-energy emission is typically delayed relative to the prompt radiation and lasts significantly longer. Also, the proximity of GRB 150323A (z = 0.593) limits the attenuation by the extragalactic background light to similar to 50% at 100-200 GeV. We conclude that GRB 150323A had an intrinsically very weak high-energy afterglow, or that the GeV spectrum had a turnover below similar to 100 GeV. If the GRB exploded into the stellar wind of a massive progenitor, the VHE non-detection constrains the wind density parameter to be A greater than or similar to 3 x 10(11) g . cm(-1), consistent with a standard Wolf-Rayet progenitor. Alternatively, the VHE emission from the blast wave would be weak in a very tenuous medium such as the interstellar medium, which therefore cannot be ruled out as the environment of GRB 150323A.
Cosmic-ray electrons and positrons (CREs) at GeV-TeV energies are a unique probe of our local Galactic neighborhood. CREs lose energy rapidly via synchrotron radiation and inverse-Compton scattering processes while propagating within the Galaxy, and these losses limit their propagation distance. For electrons with TeV energies, the limit is on the order of a kiloparsec. Within that distance, there are only a few known astrophysical objects capable of accelerating electrons to such high energies. It is also possible that the CREs are the products of the annihilation or decay of heavy dark matter (DM) particles. VERITAS, an array of imaging air Cherenkov telescopes in southern Arizona, is primarily utilized for gamma-ray astronomy but also simultaneously collects CREs during all observations. We describe our methods of identifying CREs in VERITAS data and present an energy spectrum, extending from 300 GeV to 5 TeV, obtained from approximately 300 hours of observations. A single power-law fit is ruled out in VERITAS data. We find that the spectrum of CREs is consistent with a broken power law, with a break energy at 710 +/- 40(stat) +/- 140(syst) GeV.
Background:
Epidemiological evidence indicates that diets rich in plant foods are associated with a lower risk of ischaemic heart disease (IHD), but there is sparse information on fruit and vegetable subtypes and sources of dietary fibre. This study examined the associations of major plant foods, their subtypes and dietary fibre with risk of IHD in the European Prospective Investigation into Cancer and Nutrition (EPIC).
Methods:
We conducted a prospective analysis of 490 311 men and women without a history of myocardial infarction or stroke at recruitment (12.6 years of follow-up, n cases = 8504), in 10 European countries. Dietary intake was assessed using validated questionnaires, calibrated with 24-h recalls. Multivariable Cox regressions were used to estimate hazard ratios (HR) of IHD.
Results:
There was a lower risk of IHD with a higher intake of fruit and vegetables combined [HR per 200 g/day higher intake 0.94, 95% confidence interval (CI): 0.90-0.99, P-trend = 0.009], and with total fruits (per 100 g/day 0.97, 0.95-1.00, P-trend = 0.021). There was no evidence for a reduced risk for fruit subtypes, except for bananas. Risk was lower with higher intakes of nuts and seeds (per 10 g/day 0.90, 0.82-0.98, Ptrend = 0.020), total fibre (per 10 g/day 0.91, 0.85-0.98, P-trend = 0.015), fruit and vegetable fibre (per 4 g/day 0.95, 0.91-0.99, P-trend = 0.022) and fruit fibre (per 2 g/day 0.97, 0.95-1.00, P-trend = 0.045). No associations were observed between vegetables, vegetables subtypes, legumes, cereals and IHD risk.
Conclusions:
In this large prospective study, we found some small inverse associations between plant foods and IHD risk, with fruit and vegetables combined being the most strongly inversely associated with risk. Whether these small associations are causal remains unclear.
Background:
Epidemiological evidence indicates that diets rich in plant foods are associated with a lower risk of ischaemic heart disease (IHD), but there is sparse information on fruit and vegetable subtypes and sources of dietary fibre. This study examined the associations of major plant foods, their subtypes and dietary fibre with risk of IHD in the European Prospective Investigation into Cancer and Nutrition (EPIC).
Methods:
We conducted a prospective analysis of 490 311 men and women without a history of myocardial infarction or stroke at recruitment (12.6 years of follow-up, n cases = 8504), in 10 European countries. Dietary intake was assessed using validated questionnaires, calibrated with 24-h recalls. Multivariable Cox regressions were used to estimate hazard ratios (HR) of IHD.
Results:
There was a lower risk of IHD with a higher intake of fruit and vegetables combined [HR per 200 g/day higher intake 0.94, 95% confidence interval (CI): 0.90-0.99, P-trend = 0.009], and with total fruits (per 100 g/day 0.97, 0.95-1.00, P-trend = 0.021). There was no evidence for a reduced risk for fruit subtypes, except for bananas. Risk was lower with higher intakes of nuts and seeds (per 10 g/day 0.90, 0.82-0.98, Ptrend = 0.020), total fibre (per 10 g/day 0.91, 0.85-0.98, P-trend = 0.015), fruit and vegetable fibre (per 4 g/day 0.95, 0.91-0.99, P-trend = 0.022) and fruit fibre (per 2 g/day 0.97, 0.95-1.00, P-trend = 0.045). No associations were observed between vegetables, vegetables subtypes, legumes, cereals and IHD risk.
Conclusions:
In this large prospective study, we found some small inverse associations between plant foods and IHD risk, with fruit and vegetables combined being the most strongly inversely associated with risk. Whether these small associations are causal remains unclear.
Background:
COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.
Objective:
The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points.
Methods:
We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.
Results:
Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction.
Conclusions:
We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.
By traversing the plume erupting from high southern latitudes on Saturn's moon Enceladus, Cassini orbiter instruments can directly sample the material therein. Cassini Plasma Spectrometer, CAPS, data show that a major plume component comprises previously-undetected particles of nanometer scales and larger that bridge the mass gap between previously observed gaseous species and solid icy grains. This population is electrically charged both negative and positive, indicating that subsurface triboelectric charging, i.e., contact electrification of condensed plume material may occur through mutual collisions within vents. The electric field of Saturn's magnetosphere controls the jets' morphologies, separating particles according to mass and charge. Fine-scale structuring of these particles' spatial distribution correlates with discrete plume jets' sources, and reveals locations of other possible active regions. The observed plume population likely forms a major component of high velocity nanometer particle streams detected outside Saturn's magnetosphere.
The extragalactic background light (EBL), a diffuse photon field in the optical and infrared range, is a record of radiative processes over the universe?s history. Spectral measurements of blazars at very high energies (>100 GeV) enable the reconstruction of the spectral energy distribution (SED) of the EBL, as the blazar spectra are modified by redshift- and energy-dependent interactions of the gamma-ray photons with the EBL. The spectra of 14 VERITAS-detected blazars are included in a new measurement of the EBL SED that is independent of EBL SED models. The resulting SED covers an EBL wavelength range of 0.56?56 ?m, and is in good agreement with lower limits obtained by assuming that the EBL is entirely due to radiation from cataloged galaxies.