Detecting ground level enhancements using soil moisture sensor networks

Ground level enhancements (GLEs) are space weather events that pose a potential hazard to the aviation environment through single event effects in avionics and increased dose to passengers and crew. The existing ground level neutron monitoring network provides continuous and well-characterized measurements of the radiation environment. However, there are only a few dozen active stations worldwide, and there has not been a UK-based station for several decades. Much smaller neutron detectors are increasingly deployed throughout the world with the purpose of using secondary neutrons from cosmic rays to monitor local soil moisture conditions (COSMOS). Space weather signals from GLEs and Forbush decreases have been identified in COSMOS data. Monte Carlo simulations of atmospheric radiation propagation show that a single COSMOS detector is sufficient to detect the signal of a medium-strength (10%–100% increase above background) GLE at high statistical significance, including at fine temporal resolution. Use of fine temporal resolution would also provide a capability to detect Terrestrial Gamma Ray Flashes (via secondary neutrons) which are produced by certain lightning discharges and which can provide a hazard to aircraft, particularly in tropical regions. We also show how the COsmic-ray Soil Moisture Observing System-UK detector network could be used to provide warnings at the International Civil Aviation Organization “Moderate” and “Severe” dose rate thresholds at aviation altitudes, and how multiple-detector hubs situated at strategic UK locations could detect a small GLE at high statistical significance and infer crucial information on the nature of the primary spectrum

Questioning ten common assumptions about peatlands

Peatlands have been widely studied in terms of their ecohydrology, carbon dynamics, ecosystem services and palaeoenvironmental archives. However, several assumptions are frequently made about peatlands in the academic literature, practitioner reports and the popular media which are either ambiguous or in some cases incorrect. Here we discuss the following ten common assumptions about peatlands: 1. the northern peatland carbon store will shrink under a warming climate; 2. peatlands are fragile ecosystems; 3. wet peatlands have greater rates of net carbon accumulation; 4. different rules apply to tropical peatlands; 5. peat is a single soil type; 6. peatlands behave like sponges; 7. Sphagnum is the main ‘ecosystem engineer’ in peatlands; 8. a single core provides a representative palaeo-archive from a peatland; 9. water-table reconstructions from peatlands provide direct records of past climate change; and 10. restoration of peatlands results in the re-establishment of their carbon sink function. In each case we consider the evidence supporting the assumption and, where appropriate, identify its shortcomings or ways in which it may be misleading

Erratum: "A Gravitational-wave Measurement of the Hubble Constant Following the Second Observing Run of Advanced LIGO and Virgo" (2021, ApJ, 909, 218)

[no abstract available

Search for Gravitational Waves Associated with Gamma-Ray Bursts Detected by Fermi and Swift during the LIGO-Virgo Run O3b

We search for gravitational-wave signals associated with gamma-ray bursts (GRBs) detected by the Fermi and Swift satellites during the second half of the third observing run of Advanced LIGO and Advanced Virgo (2019 November 1 15:00 UTC-2020 March 27 17:00 UTC). We conduct two independent searches: A generic gravitational-wave transients search to analyze 86 GRBs and an analysis to target binary mergers with at least one neutron star as short GRB progenitors for 17 events. We find no significant evidence for gravitational-wave signals associated with any of these GRBs. A weighted binomial test of the combined results finds no evidence for subthreshold gravitational-wave signals associated with this GRB ensemble either. We use several source types and signal morphologies during the searches, resulting in lower bounds on the estimated distance to each GRB. Finally, we constrain the population of low-luminosity short GRBs using results from the first to the third observing runs of Advanced LIGO and Advanced Virgo. The resulting population is in accordance with the local binary neutron star merger rate. © 2022. The Author(s). Published by the American Astronomical Society

Narrowband Searches for Continuous and Long-duration Transient Gravitational Waves from Known Pulsars in the LIGO-Virgo Third Observing Run

Isolated neutron stars that are asymmetric with respect to their spin axis are possible sources of detectable continuous gravitational waves. This paper presents a fully coherent search for such signals from eighteen pulsars in data from LIGO and Virgo's third observing run (O3). For known pulsars, efficient and sensitive matched-filter searches can be carried out if one assumes the gravitational radiation is phase-locked to the electromagnetic emission. In the search presented here, we relax this assumption and allow both the frequency and the time derivative of the frequency of the gravitational waves to vary in a small range around those inferred from electromagnetic observations. We find no evidence for continuous gravitational waves, and set upper limits on the strain amplitude for each target. These limits are more constraining for seven of the targets than the spin-down limit defined by ascribing all rotational energy loss to gravitational radiation. In an additional search, we look in O3 data for long-duration (hours-months) transient gravitational waves in the aftermath of pulsar glitches for six targets with a total of nine glitches. We report two marginal outliers from this search, but find no clear evidence for such emission either. The resulting duration-dependent strain upper limits do not surpass indirect energy constraints for any of these targets. © 2022. The Author(s). Published by the American Astronomical Society

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

GW190814: gravitational waves from the coalescence of a 23 solar mass black hole with a 2.6 solar mass compact object

We report the observation of a compact binary coalescence involving a 22.2–24.3 Me black hole and a compact object with a mass of 2.50–2.67 Me (all measurements quoted at the 90% credible level). The gravitational-wave signal, GW190814, was observed during LIGO’s and Virgo’s third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network. The source was localized to 18.5 deg2 at a distance of - + 241 45 41 Mpc; no electromagnetic counterpart has been confirmed to date. The source has the most unequal mass ratio yet measured with gravitational waves, - + 0.112 0.009 0.008, and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system. The dimensionless spin of the primary black hole is tightly constrained to �0.07. Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence. We estimate a merger rate density of 1–23 Gpc−3 yr−1 for the new class of binary coalescence sources that GW190814 represents. Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters. However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models of the formation and mass distribution of compact-object binaries