Perceived risk of substance use and associations with early experimentation: A latent profile analysis using ABCD study data.

Patch-level colorimetric quantification of coral bleaching for marine pollution monitoring using standardized CoralWatch references.

New H(z) Measurement at Redshift = 0.12 with DESI Data Release 1

Abstract This study provides a detailed examination of the structural, astrophysical, kinematic, and dynamical properties of the open clusters COIN-Gaia~24, Czernik~24, FSR~0893, and UBC~74, which are located in the opposite direction to the Galactic center. Astrometric, photometric, and spectroscopic data from the {\it Gaia} Data Release 3 catalog were used to ensure a precise characterization of cluster members and their physical properties. Membership determination was performed using the \texttt{UPMASK} algorithm applied to a five-dimensional parameter space, yielding 116, 179, 238, and 387 likely members for each cluster, respectively. Structural parameters were derived by fitting King profiles to the radial density distributions of high-probability members. Astrophysical parameters were estimated through Bayesian Markov chain Monte Carlo isochrone fitting based on \texttt{PARSEC} evolution models, complemented by spectral energy distribution analysis using \texttt{ARIADNE}. The resulting extinctions, distances, metallicities, and ages indicate that these are moderately reddened, intermediate-age clusters located between 1 and 3.5 kpc from the Sun. Mean radial velocities combined with Galactic orbital integrations computed with \texttt{galpy}, show that all four clusters follow nearly circular, low-eccentricity orbits typical of thin-disc populations. All four OCs have dynamical relaxation times of 22-98~Myr. Yet, their ages surpass these times by several factors, particularly in Czernik~24, revealing that they are dynamically evolved systems even though the calculated $T_{\rm E}$ values represent lower limits. The results confirm that these OCs serve as reliable tracers of the Galactic thin disc’s chemical and dynamical evolution.

The extent to which the environment affects galaxy evolution has been under scrutiny by researchers for decades. With the first data from Euclid, we can begin to systematically study a wide range of environments and their effects as a function of redshift, using 63, ^2 of space-based data. In this paper, we present results from the Euclid Quick Data Release, where we measured the passive-density and morphology-density relations in the redshift range z=0.25--1. We determined if a galaxy is passive using the specific star formation rate, and we classified the morphologies of galaxies using the Sérsic index n and the u-r colours. We measured the local environmental density of each galaxy using the N . This result is indicative of the separability of the effects from the stellar mass and the environment. Similarly, at all redshifts in this work, the early-type galaxy fraction increases with increasing density at fixed stellar mass, meaning the environment also transforms the morphology of the galaxy independently of stellar mass, up to M_* łesssim 10^ deg neighbour method. We find that at a fixed stellar mass, the quenched fraction (the fraction of galaxies that have ceased star formation) increases with increasing local environmental density up to z=1 10.8 M_⊙. For M_* 10.8 M_⊙, almost all galaxies are early-types, with minimal impact from the environment. At z>0.75, the morphology depends mostly on stellar mass, with only low-mass galaxies being affected by the environment. Given that the morphology classifications use u-r colours, these are correlated to the star formation rate, and as such our morphology results should be taken with caution, yet future morphology classifications should help verify these results. To summarise, we successfully identify the passive-density and morphology-density relations at 0.25<z<1. Future Euclid data releases are key to confirm these trends at higher redshifts.

Abstract Precise measurements of Type Ia supernovae (SNe Ia) at low redshifts ( z ) serve as one of the most viable keys to unlocking our understanding of cosmic expansion, isotropy, and growth of structure. The Dark Energy Bedrock All-Sky Supernovae (DEBASS) program will deliver a uniformly calibrated low- z dataset of more than 400 spectroscopically confirmed SNe Ia in the Southern Hemisphere. DEBASS utilizes the Dark Energy Camera to image supernovae in conjunction with the Wide-Field Spectrograph to gather comprehensive host-galaxy information. By using the same photometric instrument as both the Dark Energy Survey (DES) and the DECam Local Volume Exploration Survey, DEBASS not only benefits from a robust photometric pipeline and well-calibrated images across the Southern sky, but can replace the historic and external low- z samples that were used in the final DES supernova analysis. In this paper, along with a companion paper, we present an early data release of 77 DEBASS SNe within the DES footprint. We introduce the DEBASS program, discuss its scientific goals and the advantages it offers for supernova cosmology, and present our initial results demonstrating data quality. With this early data release, we find a robust median absolute standard deviation of Hubble diagram residuals of ∼0.10 mag and an initial measurement of the host-galaxy mass step of 0.06 ± 0.04 mag, both before performing bias corrections. This low scatter shows the promise of a low- z SN Ia program with a well-calibrated telescope and high signal-to-noise ratio across multiple bands.

ABSTRACT Smart card data are increasingly used to optimize public transit services and analyze urban mobility patterns, but the release of such data may expose metro users to the risk of de-anonymization. This study proposes a quantitative framework for assessing privacy risks based on limited historical trip records. The framework characterizes individual travel behavior using station visitation distributions and station-to-station transition patterns, which are measured using Kullback–Leibler divergence and a Markov model. These complementary similarity measures are integrated through a weighted voting mechanism and further optimized through a bipartite matching algorithm to resolve identity conflicts in large-scale datasets. Experiments using Chengdu metro smart card records show that the voting method alone correctly de-anonymizes about 48% of users. After incorporating bipartite matching, the framework achieves 88% precision and 90% recall. These findings provide quantitative evidence of substantial de-anonymization risks in transit data and highlight the need to develop and implement robust privacy-preserving mechanisms prior to data publication.

Abstract We present the first public data release of the DDO51 band from the Stellar Abundances and Galactic Evolution Survey (SAGES), based on Nanshan One-meter Wide-field Telescope observations obtained between 2023 September and 2024 January. This release initiates the DDO51-band component of the survey, covering ∼2500 deg 2 of the northern sky and including more than 10 million sources. The DDO51 filter is centered near the Mg i b triplet and the adjacent MgH feature, offering sensitivity to stellar surface gravity. The data reduction pipeline incorporates an improved astrometric solution anchored to Gaia DR3 and a photometric calibration strategy tied to synthetic photometry from Gaia XP spectra. These procedures yield a point-source depth of ∼18.9 mag at a signal-to-noise ratio ∼10 and an internal photometric precision ≈6–7 mmag at the bright end. A preliminary color–color analysis using Gaia broadband photometry confirms the expected sensitivity of the DDO51 band to stellar surface gravity, demonstrating a clear photometric separation between dwarf and giant sequences for late-type stars. This dataset, when combined with existing SAGES photometry in other bands, provides a crucial tool for disentangling the substructures of the Milky Way. All data products from this release are available upon publication.

Identification of New Be Stars from LAMOST Data Release 11 Based on Deep Learning

Dual active galactic nuclei (AGNs) are expected in hierarchical galaxy evolution models, in which low-mass galaxies merge to build more massive ones. While observational evidence for dual AGNs is growing in massive galaxies, no clear detection has yet been found in the low-mass regime. We used photometry and spectroscopy from the first Euclid Quick Data Release, combined with a collection of multi-wavelength data from the Dark Energy Spectroscopic Instrument (DESI), the LOw-Frequency ARray (LOFAR) high band antenna, and counterparts in X-ray and mid-infrared catalogues to identify dual AGNs at redshift z łesssim 1. Focusing on low-mass galaxies with stellar masses below 10 10 $,M_⊙, we find nine dual AGN candidates with projected separations ranging from $∼20 to 51,kpc. We also find 49 dual AGN candidates in more massive galaxies. We derive a dual AGN fraction of 0.1% for the low-mass galaxies and estimate that these systems likely trace a population of progenitor black hole pairs that may evolve into bound binaries and eventually coalesce, emitting gravitational waves in the LISA band. These results constitute the first sample of spectroscopically confirmed dual AGN candidates in low-mass galaxies and have important implications for models in which supermassive black holes grow from lower-mass black holes located in low-mass galaxies, as well as for predictions of gravitational waves from low-mass binary black holes.

Abstract Quasar samples remain severely incomplete at low Galactic latitudes because of strong extinction and source confusion. We conduct a systematic search for quasars behind the Galactic plane using X-ray sources from the Chandra Source Catalog (CSC), combined with optical data from Gaia Data Release 3 and mid-infrared data from CatWISE2020. Using spectroscopically confirmed quasars and stellar-type objects from datasets including DESI, the Sloan Digital Sky Survey, and LAMOST, we apply a random forest classifier to identify quasar candidates, with stellar contaminants suppressed using Gaia proper-motion constraints. Photometric redshifts are estimated for the candidates using a random forest regression model. Applying this framework to previously unclassified CSC sources, we identify 7570 quasar candidates, including 1060 Galactic plane quasar (GPQ) candidates at ∣ b ∣ < 20°, of which 551 are high-confidence candidates. Relative to the previously known GPQ sample, our selected GPQs reach lower optical and X-ray fluxes, improving sensitivity to low-flux GPQs. In addition, both the GPQ candidates and known GPQs display harder X-ray spectra than the all-sky quasar sample, consistent with increased absorption through the Galactic plane. Pilot spectroscopy confirms two high-confidence GPQ candidates as quasars at spectroscopic redshifts of z = 1.2582 and z = 1.1313, and further spectroscopic follow-up of the GPQ sample is underway. This work substantially improves the census of GPQs and provides a valuable target sample for future spectroscopic follow-up, enabling the use of GPQs to refine the reference frames for astrometry and probe the Milky Way interstellar and circumgalactic media with the absorption features of GPQs.

Abstract Wolf–Rayet (W-R) stars, which represent a key evolutionary stage of massive stars, exhibit strong stellar winds and broad emission lines. These features serve as direct tracers of stellar feedback and chemical enrichment in star-forming regions. Utilizing the recently released Dark Energy Spectroscopic Instrument (DESI) Data Release 1, we conduct a systematic search for W-R stars. To enhance physical interpretability while achieving high performance in the survey data, we introduce an improved model, LPA-MLK-CNN, which combines two key innovations: (i) a line-prior attention (LPA) mechanism that emphasizes diagnostic W-R emission lines by embedding astrophysical priors within a data-driven framework; (ii) a multiscale large-kernel convolutional neural network (MLK-CNN) structure that captures diverse emission-line features across stellar types. Trained on spectra from a six-class dataset, the model achieves significantly improved performance compared to conventional machine learning and deep learning baselines. When applied to the DESI spectral data, LPA-MLK-CNN recovers two newly discovered W-R candidates, contributing to the expansion of the W-R star catalog.

Abstract We present the characterisation, including a photometric redshift (photo- z ) analysis, of the optical counterparts (CTPs) to over 45 000 bright ( S 856 MHz ≥ 30 mJy) compact radio sources, identified across all ASKAP First Large Absorption Survey in H i (FLASH) fields observed up to April 2025. These sources constitute a large, homogeneous population of background continuum sightlines specifically selected to enable statistical studies of cold gas at intermediate redshifts of 0.42 ≤ z ≤ 1. As spectroscopic redshift measurements are not available for the majority of these candidate absorbers, we estimate photo- z s for the CTPs of all FLASH continuum sources cross-matched to the tenth data release of the DESI Legacy Imaging Surveys (LS10). Using these estimates, we establish the redshift distribution and find that approximately 13% of continuum sources lie at z < 0.42 (foreground), 35% within the detectability range of FLASH (‘in-band’), and 52% at z > 1 (background). We examine the subset of FLASH continuum sources with CTPs in the eROSITA X-ray survey, providing additional insight into their AGN content, multiwavelength properties, and environments. Finally, we discuss how this information can be used as a statistical prior to aid in distinguishing between associated and intervening H i absorption systems and estimating the total comoving absorption path length of the survey, establishing a framework for incorporating redshift-based priors in future large radio absorption surveys. We release a catalogue of LS10 counterparts to FLASH continuum sources, providing photo- z estimates, associated uncertainties, and measures of redshift degeneracies.

Abstract The spectra of type 1 active galactic nuclei (AGNs) often exhibit a broad component in [O iii ] λ 5007, which is typically blueshifted and associated with strong outflows. We systematically analyze the [O iii ] emission-line properties of type 1 AGNs with broad components to investigate how these kinematic features relate to the physical properties of the central engine. From a parent sample of 11,557 QSOs at z < 0.3 in Data Release 16 of the Sloan Digital Sky Survey, we select 2290 type 1 AGNs exhibiting broad components in [O iii ]. Previous studies have reported a strong correlation between the blue emission, defined as the full extent of the broad component on the blue side, and black hole mass when the latter is estimated from the M BH – σ * relation using the line width σ of the [O iii ] core component as a surrogate for σ * . In the same way, the black hole mass also shows a strong correlation with the blue emission parameter in our sample. However, this correlation becomes negligible when virial black hole masses are adopted. Besides, the velocity shifts between the broad and core components of [O iii ] show a weak correlation with the Eddington ratio. This is consistent with the expectation that higher accretion rates enhance radiative pressure, thereby driving faster or more prominent outflows. In future work, we will compare the properties of the [O iii ] road component between typical type 1 AGNs and those with double-peaked [O iii ] to probe differences in narrow-line region kinematics and the impact of outflows or dual AGNs.

The first influenza A(H5N1) human case associated with the A(H5N1) dairy cattle outbreak in the United States was identified in April 2024. The U.S. CDC response to this outbreak was activated days later and remained active until July 2025. During this time, 70 human cases of influenza A(H5N1) were detected with a range of epidemiological links to sources of exposure. Next-generation sequencing (NGS) of human samples was an effectual mechanism for tracking and analyzing the outbreak evolution throughout the response. Due to the specimens' importance and their variable physical quality, an assortment of laboratory methods was utilized including influenza segment-specific amplification, enrichment capture, short-read, and long-read sequencing. Combining these methods allowed for high-quality genomic data production with rapid turnaround times-typically 2 days from sample receipt to public database submission. By leveraging replicate sequencing, enrichment capture, and sequencing of diagnostic amplicons, valuable genomic data could be produced directly from human clinical specimens that would have normally been considered too weak for routine virologic surveillance sequencing. The resulting assemblies were characterized and analyzed by CDC and shared with local and state public health authorities to facilitate case investigations and risk assessment. These data were further used for phylogenetic analyses of viruses from human cases to investigate likely animal-to-human transmission events and identify clusters within the outbreak that might indicate trends in the types of exposures. Through the adaptable laboratory workflow and the rapid release of viral genomic data, the public health risk mitigation strategies could be evaluated and adjusted in real time.

Abstract I revisit the contradictory claims regarding the detection of low-frequency extra modes in the RR Lyrae star HH Puppis. A Research Note by T. Love noted that the star shows no extra signals in the Transiting Exoplanets Survey Satellite (TESS) observations. In a response, M. Chadid attributed this to the limitations of the TESS mission over their longer dataset collected with the PAIX instrument they used. Here I show that some of the capabilities of TESS have been underestimated, and the claims made could be verified with a more detailed analysis (and public release) of the PAIX data.

Satellite-derived bathymetry (SDB) offers a practical alternative for mapping shallow reefs in remote oceanic settings where acoustic surveys are costly and logistically constrained. Here we benchmark PlanetScope 8-band (3 m) surface reflectance—an underused commercial constellation for reef SDB—using ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) ATL03 photon data (Release 006) as independent vertical control. Seventeen ATL03 ground tracks (2019–2025) were processed using geometric filtering, photon classification, and explicit air–water refraction correction. This yielded 5171 candidate seafloor observations, of which 5021 were co-located with valid PlanetScope water pixels after Usable Data Mask screening (UDM2/UDM2.1), sun-glint correction, and reflectance quality screening. Four SDB formulations (Lyzenga, Bierwirth, and Stumpf) were calibrated and independently validated using depth-stratified train/validation partitions (70/30, 80/20, and 90/10). Across partitions, the multiband polynomial model of Lyzenga 2006 generalized best (R2 = 0.843–0.859; RMSE = 1.734–1.813 m; bias = −0.070 to −0.081 m), followed by Bierwirth (R2 = 0.826–0.845; RMSE = 1.818–1.904 m). Lyzenga 1985 reported lower skill (RMSE ≈ 3.1 m), while the Stumpf log-ratio failed in independent validation. ICESat-2 photon bathymetry provides repeatable point-based control in clear waters but remains less precise than echo sounding due to photon classification and spatial-support effects; therefore, uncertainties and applicability limits must be reported. Overall, PlanetScope 3 m, 8-band surface reflectance supports reproducible reef-scale SDB in Seaflower under the evaluated conditions, with Lyzenga 2006 as a robust baseline.

The NIH Common Fund Data Ecosystem (CFDE) integrates data resources from 18 NIH Common Fund programs for discovery and integrative analysis. These programs generate valuable but heterogeneous datasets that can be difficult to discover, access, and reuse. CFDE aims to provide a collaborative, community-built infrastructure that links and enriches Common Fund programs. We describe the evolution, structure, and core technologies of CFDE, including practical approaches that support submission, integration, visualization, and public release of multimodal data. Training programs and workforce initiatives lower barriers to adoption. CFDE has devised solutions to critical issues facing cross-program initiatives, including data scale and heterogeneity, dataset integration, and long-term sustainability. We demonstrate the utility of linking Common Fund resources through integrative tools and cross-dataset queries to yield insights that would otherwise be infeasible. Collectively, CFDE shows that a standards-driven, federated approach enhances and unifies cross-disciplinary resources, fostering collaboration and data-driven discovery.

ABSTRACT We examine how citizens update their economic assessments using a real-world event: the Japanese government’s release of official GDP data. While prior research shows that subjective evaluations correlate with macroeconomic indicators, the mechanisms through which new information changes public opinion remain unclear. To address this gap, we fielded an original survey that compared Japanese respondents’ economic views immediately before and after the February 2020 release of quarterly GDP figures, which reported a larger-than-expected decline in growth. Respondents surveyed after the release expressed significantly greater pessimism, particularly on the retrospective-sociotropic and prospective-egotropic dimensions. However, not all groups updated to the same degree. Individuals who regularly engaged in marketplace activities – through employment, financial investments, or supermarket shopping – showed smaller changes, consistent with having more accurate priors. The moderating effect of shopping is especially notable, suggesting that everyday market interactions can provide valuable insights into the broader economy. Taken together, these findings indicate that official statistics can shape public opinion, but their influence is conditional on the informational resources individuals bring to bear.

Signatures of a Tidally Induced Spiral Arm at the Anticenter of the Milky Way and a Kinematically Extended Anticenter Stream Using DESI Data Release 2