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At least 577 records · Page 32

The overlooked interaction of emerging contaminants and microbial communities: a threat to ecosystems and public health

Abstract Context and aims Emerging contaminants (ECs) and microbial communities should not be viewed in isolation, but through the One Health perspective. Both ECs and microorganisms lie at the core of this interconnected framework, as they directly influence the health of humans, animals, and the environment. The interactions between ECs and microbial communities can have profound implications for public health, affecting all three domains. However, these ECs-microorganism interactions remain underexplored, potentially leaving significant public health and ecological risks unrecognized. Therefore, this article seeks to alert the scientific community to the overlooked interactions between ECs and microbial communities, emphasizing the pivotal role these interactions may play in the management of ‘One Health.’ Results The most extensively studied interaction between ECs and microbial communities is biodegradation. However, other more complex and concerning interactions demand attention, such as the impact of ECs on microbial ecology (disruptions in ecosystem balance affecting nutrient and energy cycles) and the rise and spread of antimicrobial resistance (a growing global health crisis). Although these ECs-microbial interactions had not been extensively studied, there are scientific evidence that ECs impact on microbial communities may be concerning for public health and ecosystem balance. Conclusions So, this perspective summarizes the impact of ECs through a One Health lens and underscores the urgent need to understand their influence on microbial communities, while highlighting the key challenges researchers must overcome. Tackling these challenges is vital to mitigate potential long-term consequences for both ecosystems and public health.

Gomes, Inês B. (ORCID:0000000207313662)↗

Real-time discovery of AT2020xnd: a fast, luminous ultraviolet transient with minimal radioactive ejecta

ABSTRACT The many unusual properties of the enigmatic AT2018cow suggested that at least some subset of the empirical class of fast blue optical transients (FBOTs) represents a genuinely new astrophysical phenomenon. Unfortunately, the intrinsic rarity and fleeting nature of these events have made it difficult to identify additional examples early enough to acquire the observations necessary to constrain theoretical models. We present here the Zwicky Transient Facility discovery of AT2020xnd (ZTF20acigmel, the ‘Camel’) at z = 0.243, the first unambiguous AT2018cow analogue to be found and confirmed in real time. AT2018cow and AT2020xnd share all key observational properties: a fast optical rise, sustained high photospheric temperature, absence of a second peak attributable to ejection of a radioactively heated stellar envelope, extremely luminous radio, millimetre, and X-ray emission, and a dwarf-galaxy host. This supports the argument that AT2018cow-like events represent a distinct phenomenon from slower-evolving radio-quiet supernovae, likely requiring a different progenitor or a different central engine. The sample properties of the four known members of this class to date disfavour tidal disruption models but are consistent with the alternative model of an accretion powered jet following the direct collapse of a massive star to a black hole. Contextual filtering of alert streams combined with rapid photometric verification using multiband imaging provides an efficient way to identify future members of this class, even at high redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

The ‘Giraffe’: discovery of a stripped red giant in an interacting binary with an ∼2 M ⊙ lower giant

We report the discovery of a stripped giant + lower giant Algol-type binary, 2M04123153+6738486 (2M0412), identified during a search for non-interacting compact object – star binaries. 2M0412 is an evolved ( T eff, giant ≃ 4000 K), luminous ( L giant ≃ 150 L ⊙ ) red giant in a circular P = 81.2 d binary. 2M0412 is a known variable star previously classified as a semiregular variable. The cross-correlation functions of follow-up Keck/HIRES and LBT/Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) spectra show an radial velocity variable second component with implied mass ratio q = M giant / M comp ≃ 0.20 ± 0.01. The All-Sky Automated Survey for SuperNovae (ASAS-SN), Asteroid Terrestrial-impact Last Alert System (ATLAS), Transiting Exoplanet Survey Telescope ( TESS ), and Zwicky Transient Facility (ZTF) light curves show that the giant is a Roche lobe filling ellipsoidal variable with an inclination of 49.4 ± 0.3°, and a giant mass of M giant = 0.38 ± 0.01 M ⊙ for a distance of ≃ 3.7 kpc. The mass of the giant indicates that its envelope has been partially stripped. The giant companion on the lower red giant branch has a mass of M comp = 1.91 ± 0.03 M ⊙ with T eff, comp ≃ 5000 K, L comp ≃ 60 L ⊙ , and R comp ≃ 11 R ⊙ . The lower giant contributes ${\sim }35{{\ \rm per\ cent}}$ of the flux in the V band. We also identify an orbital phase dependent, broad $\rm H\,\alpha$ emission line which could indicate ongoing accretion from the stripped red giant on to the companion.

(stars:) binaries: spectroscopic↗

Deep drilling in the time domain with DECam: survey characterization

ABSTRACT This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4-m Blanco telescope at the Cerro Tololo Inter-American Observatory (CTIO). During the first year of observations in 2021, >4000 images covering 21 deg2 (seven DECam pointings), with ∼40 epochs (nights) per field and 5 to 6 images per night per filter in g, r, i, and/or z have become publicly available (the proprietary period for this program is waived). We describe the real-time difference-image pipeline and how alerts are distributed to brokers via the same distribution system as the Zwicky Transient Facility (ZTF). In this paper, we focus on the two extragalactic deep fields (COSMOS and ELAIS-S1) characterizing the detected sources, and demonstrating that the survey design is effective for probing the discovery space of faint and fast variable and transient sources. We describe and make publicly available 4413 calibrated light curves based on difference-image detection photometry of transients and variables in the extragalactic fields. We also present preliminary scientific analysis regarding the Solar system small bodies, stellar flares and variables, Galactic anomaly detection, fast-rising transients and variables, supernovae, and active Galactic nuclei.

79 ASTRONOMY AND ASTROPHYSICS↗

SCAT uncovers ATLAS’s first tidal disruption event ATLAS18mlw: a faint and fast TDE in a quiescent Balmer strong Galaxy

ABSTRACT We present the discovery that ATLAS18mlw was a tidal disruption event (TDE) in the galaxy WISEA J073544.83+663717.3, at a luminosity distance of 334 Mpc. Initially discovered by the Asteroid Terrestrial Impact Last Alert System (ATLAS) on 2018 March 17.3, the TDE nature of the transient was uncovered only recently with the re-reduction of a SuperNova Integral Field Spectrograph (SNIFS) spectrum. This spectrum, taken by the Spectral Classification of Astronomical Transients (SCAT) survey, shows a strong blue continuum and a broad H α emission line. Here, we present roughly 6 yr of optical survey photometry beginning before the TDE to constrain active galactic nucleus activity, optical spectroscopy of the transient, and a detailed study of the host galaxy properties through analysis of archival photometry and a host spectrum. ATLAS18mlw was detected in ground-based light curves for roughly 2 months. From a blackbody fit to the transient spectrum and bolometric correction of the optical light curve, we conclude that ATLAS18mlw is best explained by a low-luminosity TDE with a peak luminosity of log(L [erg s−1]) = 43.5 ± 0.2. The TDE classification is further supported by the quiescent Balmer strong nature of the host galaxy. We also calculated the TDE decline rate from the bolometric light curve and find ΔL40 = −0.7 ± 0.2 dex, making ATLAS18mlw a member of the growing class of ‘faint and fast’ TDEs with low peak luminosities and fast decline rates.

79 ASTRONOMY AND ASTROPHYSICS↗

Probing quasar viewing angle with the variability structure function

Given the anisotropic emission from quasar accretion discs, their viewing angle affects estimates of the quasar luminosity, black hole mass, and Eddington ratio. Discs appear overluminous when viewed pole-on and underluminous when viewed at high inclination. In radio-quiet quasars, the viewing angle is usually unknown, although spectroscopic indicators have been proposed. Here, we use a recently discovered universality in the variability structure function (SF) of quasar light curves (LCs), where all quasars show the same SF when clocks run in units of orbital time-scale. As an offset from the mean relation can be caused by incorrect orbital time-scales and thus incorrect luminosities, we correlate these offsets with suggested inclination indicators. We derive SFs from NASA/Asteroid Terrestrial-impact Last Alert System (ATLAS) LCs spanning ~6 yr of observation, using a sample of 183 luminous quasars with measured H β lines as well as 753 quasars with C $\tiny{IV}$ and Mg $\tiny{II}$ lines. Starting from the proposed orientation indicators, we expect quasars with narrower H β lines and with more blueshifted C $\tiny{IV}$ lines to be viewed more pole-on and thus appear overluminous. In contrast, our SF analysis finds that presumed pole-on discs appear underluminous, consistently for both line indicators. We discuss possible explanations for the behaviour of quasars with highly blueshifted C $\tiny{IV}$ lines irrespective of inclination angle, including dusty outflows that might render the accretion disc underluminous and flatter disc temperature profiles with longer orbital time-scales than in thin-disc models but reach no satisfying conclusion.

79 ASTRONOMY AND ASTROPHYSICS↗

The variability structure function of the highest luminosity quasars on short time-scales

ABSTRACT The stochastic photometric variability of quasars is known to follow a random-walk phenomenology on emission time-scales of months to years. Some high-cadence rest-frame optical monitoring in the past has hinted at a suppression of variability amplitudes on shorter time-scales of a few days or weeks, opening the question of what drives the suppression and how it might scale with quasar properties. Here, we study a few thousand of the highest luminosity quasars in the sky, mostly in the luminosity range of $L_{\rm bol}$$=[46.4, 47.3]$ and redshift range of $z=[0.7, 2.4]$. We use a data set from the NASA/Asteroid Terrestrial-impact Last Alert System facility with nightly cadence, weather permitting, which has been used before to quantify strong regularity in longer term rest-frame-UV variability. As we focus on a careful treatment of short time-scales across the sample, we find that a linear function is sufficient to describe the UV variability structure function. Although the result can not rule out the existence of breaks in some groups completely, a simpler model is usually favoured under this circumstance. In conclusion, the data are consistent with a single-slope random walk across rest-frame time-scales of $\Delta t=[10, 250]$ d.

Tang, Ji-Jia (ORCID:0000000218600886)↗

The Atacama cosmology telescope: flux upper limits from a targeted search for extragalactic transients

ABSTRACT We have performed targeted searches of known extragalactic transient events at millimetre wavelengths using nine seasons (2013–2021) of 98, 150, and 229 GHz Atacama Cosmology Telescope (ACT) observations that mapped ∼40 per cent of the sky for most of the data volume. Our data cover 88 gamma-ray bursts (GRBs), 12 tidal disruption events (TDEs), and 203 other transients, including supernovae (SNe). We stack our ACT observations to increase the signal-to-noise ratio of the maps. In all cases but one, we do not detect these transients in the ACT data. The single candidate detection (event AT2019ppm), seen at ∼5σ significance in our data, appears to be due to active galactic nuclei activity in the host galaxy coincident with a transient alert. For each source in our search we provide flux upper limits. For example, the medians for the 95 per cent confidence upper limits at 98 GHz are 15, 18, and 16 mJy for GRBs, SNe, and TDEs, respectively, in the first month after discovery. The projected sensitivity of future wide-area cosmic microwave background surveys should be sufficient to detect many of these events using the methods described in this paper.

Hervías-Caimapo, Carlos↗

Swift /UVOT discovery of Swift J221951−484240: a UV luminous ambiguous nuclear transient

We report the discovery of Swift J221951−484240 (hereafter: J221951), a luminous slow-evolving blue transient that was detected by the Neil Gehrels Swift Observatory Ultraviolet/Optical Telescope (Swift/UVOT) during the follow-up of gravitational wave alert S190930t, to which it is unrelated. Swift/UVOT photometry shows the UV spectral energy distribution of the transient to be well modelled by a slowly shrinking blackbody with an approximately constant temperature of T ∼ 2.5 × 10 4 K. At a redshift z = 0.5205, J221951 had a peak absolute magnitude of M u,AB = −23 mag, peak bolometric luminosity Lmax = 1.1 x 10 45 ergs -1 and a total radiated energy of E > 2.6 × 10 52 erg. The archival Wide-field Infrared Survey Explorer IR photometry shows a slow rise prior to a peak near the discovery date. Spectroscopic UV observations display broad absorption lines in N V and O VI, pointing towards an outflow at coronal temperatures. The lack of emission in the higher H α lines, N I and other neutral lines is consistent with a viewing angle close to the plane of the accretion or debris disc. The origin of J221951 cannot be determined with certainty but has properties consistent with a tidal disruption event and the turn-on of an active galactic nucleus.

79 ASTRONOMY AND ASTROPHYSICS↗

Search for multimessenger signals in NOvA coincident with LIGO/Virgo detections

Using the NOvA neutrino detectors, a broad search has been performed for any signal coincident with 28 gravitational wave events detected by the LIGO/Virgo Collaboration between September 2015 and July 2019. For all of these events, NOvA is sensitive to possible arrival of neutrinos and cosmic rays of GeV and higher energies. For five (seven) events in the NOvA Far (Near) Detector, timely public alerts from the LIGO/Virgo Collaboration allowed recording of MeV-scale events. No signal candidates were found.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗

Kensor: Coordinated Intelligence from Co-Located Sensors

Internet of Things (IoT) is becoming more pervasive in many installations, including homes, manufacturing plants, and industrial facilities of all kinds. The data that IoT produces is a reflection of usual behavior such as daily routines and scheduled tasks, but also from unexpected behavior due to unintentional or undesirable abnormalities. Here, we focus on achieving coordinated intelligence about normal and abnormal phenomena from multiple sensors that are geographically colocated in close proximity, monitoring and controlling a set of co-located devices. Given a set of co-located sensors, we seek an intelligent approach that would automatically determine the “normal” patterns of behaviors among the correlated sensors. After normal behavior is extracted, later monitoring should detect any deviant variations over time. An example application is an entry monitoring and alert system for facilities such as nuclear reactors, where badge readers, door locks, lights, weight trackers and other co-located sensors at the entry point are collectively tracked. To address this problem, we identify the possible solution approach that can be used to solve its different variants. The implemented model is developed as a combination of rules and Markov Chain methods.

Kotevska, Olivera↗

Power Electronics Based Self-Monitoring and Diagnosing for Photovoltaics Systems

Self-monitoring and diagnosing technology for photovoltaic (PV) systems is a method to reduce energy production losses. The proposed technology will enable existing panel-level power optimizers and inverters in a PV system to actively perturb the system, measure its response to these small-signal perturbations, and detect any changes in the small-signal impedances. Impedance measurement will be used to identify specific faults and power degradation trends in a PV panel. This information can be used to instantly alert Operations and Maintenance (O&M) personnel of the need for corrective action, thereby reducing energy production losses earlier relative to standard PV systems.

Panchal, Jeet↗

SNNPG: Using Spiking Neural Networks to Detect Attacks in the Power Grid

We explore the potential of Spiking Neural Networks (SNN) to enhance the security of power grid operations by detecting False Data Injection (FDI) attacks. These attacks manipulate PMU readings, leading to erroneous control decisions and grid disruptions. We develop a method to convert Phase Measurement Unit (PMU) data into spike trains, capturing both temporal and spatial dimensions. Using an SNN model, we conduct evaluations with simulated power grid data, showcasing accuracy in detecting FDI attacks. SNN models rapidly identify anomalies in real-time PMU data, safeguarding grid operations by alerting operators to irregular readings and preventing incorrect decisions.

artificial intelligence↗

Method for Assessment of Security-Relevant Settings in Anomaly-Based Intrusion Detection for Industrial Control Systems

Ensuring the integrity of Ethernet-based networks is a challenging and constantly evolving domain. This problem is exacerbated for those operational technology (OT) networks supporting industrial control systems (ICS) since much of that equipment was originally designed to be on a network that was isolated and generally considered free of malefactors. Increasing pressure to bridge these systems with traditional information technology (IT) networks has introduced a bevy of new threats. In response, both academia and industry have responded with security solutions tailored to ICS environments. Deploying these protection systems often involves several configuration choices. While some of these choices are clear (e.g., block/enable protocol X) others are far more subjective (e.g. alert threshold == 3.43). Further complicating the situation, while often similar to IT networks, OT networks have unique challenges and characteristics that make the task of protecting them simultaneously more difficult and straight forward.Extant solutions for quantifying the relative security of intrusion detection systems fail to effectively support the operators of said systems with understanding the impact of various configuration changes. Further, they assume that the attacks are static and not subject to manipulation or alteration in the face of defenses. In this paper, we present a threat-based method for quantifying the relative impact of various security settings for intrusion detection systems (IDSs) within ICS environments. This method provides operational staff with a clear understanding of the relative impact of their settings and assumes that the attacks levied against them are dynamic. The model is described in detail, we apply the model to a synthetic data set, and discuss the inferences that can be made and what types of decisions they could be used to support.

Gillen, Rob↗

The Recent Improvements of the SNS Extraction Kicker Power Supplies

A total of 14 extraction kickers., with one as the hot spare., are in service to extract protons out of the storage ring at the SNS. The jitter issue and the short lifetime of the switches were resolved after the thyratrons were replaced with solid state switches in 2018. This paper discusses the recent improvements. Two thyristor switches suffered overheating damage in separate incidents. One was due to the oil pump failure and the other was the result of a disconnected oil hose. An ultrasonic flow meter and a fiber optic temperature monitoring system have been installed for each extraction kicker power supply. The flow meter continuously monitors the entire tank oil flow. The temperature monitor detects the thyristor switch real-time temperatures in three locations. Fault thresholds are selected so that the thyristor switches are protected from overheating damage. Alarms are configured to alert staff to take actions before faults occur. In addition., the cause of an intermittent misfire issue was identified, and the solution was implemented. Lastly., a future oscilloscope upgrade and an oil level sensor are discussed.

Tan, Yugang↗

Predicting Power Outage During Extreme Weather with EAGLE-I and NWS Datasets

Extreme weather events, such as hurricanes, severe thunderstorms, and floods can significantly disrupt power grid systems, leading to electrical outages that result in inconvenience, economic losses, and life-threatening situations. There is a growing need for a robust and precise predictive model to forecast power outages, which will help prioritize emergency response before, during, and after extreme weather events. In this paper, we introduce machine-learning models that predict power outage risk at the state level during and after extreme weather events. We jointly utilized two publicly available datasets: the U.S. historical power outage data collected by the Environment for Analysis of Geo-Located Energy Information (EAGLE-I™) system, and the National Weather Service historical weather alert data sets. We highlight our initial result and discuss future work aimed at enhancing the model's robustness and accuracy for real-world applications.

Lee, Sangkeun (Matt)↗

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs) at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring, Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases, distribution system state estimation (DSSE) and fault identification are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1 feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system↗