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Application, development and opportunities of Remote Underwater Video for freshwater fisheries management
No full textRemote Underwater Video (RUV) is a promising tool for progressing the future of freshwater fisheries monitoring and management. While uses have previously been focused on marine systems there has been a rise in application for freshwaters. Given the potential for coordinated geographical research using RUVs it is essential that standardised methodologies are described and promoted. We therefore conducted a systematic literature review which returned 185 publications that discussed using RUVs in freshwater environments. These publications used RUVs to measure: abundance, species richness, length-frequency, spawning/mating, behaviour, migration, foraging, size, habitat use, species presence and nesting. There were taxonomic and geographic biases in the results, with commercial salmonid fisheries the primary focus and 49% of published research was performed in North and Central America. While some research has investigated best practices, there are numerous gaps including: determining optimal deployment time in different systems/species compositions, determining suitable acclimation time for behavioural analysis and ascertaining the costs and benefits of using bait as an attractant and stereo-camera for photogrammetry. Until these gaps are addressed, we recommend a cautious set of standards for freshwater RUVs deployment which includes using a standard action camera, recording at ≥30 fps with a resolution of 1080p for 60 minutes. This will ensure that data are broadly comparable between studies. Current bottlenecks in methodology uptake relate to data storage, processing time and cost but this may be overcome with the optimisation of computer vision and machine learning. There are broad opportunities to develop RUV application into a powerful tool for freshwater fisheries management, invasive species detection, and ethological observations if standardised and findability, accessibility, interoperability, and reusability (FAIR) workflows are followed
A comprehensive framework for accurate estimation of performance loss rates in large photovoltaic systems using machine learning
No full textAccurate quantification of long-term Performance Loss Rate in photovoltaic systems is critical for ensuring system reliability, financial forecasting, and asset management across the global PV fleet. Conventional methods for estimating the performance loss rate, however, are often constrained by their sensitivity to environmental variability and reliance on rigid filtering heuristics that can introduce bias. This paper introduces a novel, data-driven framework that transcends these challenges by integrating unsupervised filtering, predictive modeling, and advanced trend analysis. The methodology employs Density-Based Spatial Clustering of Applications with Noise to adaptively isolate anomalous operational data while preserving approximately 80% of the core performance data. Subsequently, a Light Gradient Boosting Machine model, trained on early-life system data, establishes a weather-normalized performance baseline to generate a Performance Ratio Index—a high-fidelity time-series signal representing the system's intrinsic health. Finally, the degradation pathway is characterized via Seasonal-Trend decomposition combined with the Pruned Exact Linear Time algorithm, which robustly identifies change points and non-linear aging phases. The framework was validated across 8 distinct locations comprising 84 inverters, including commercial fleets and authoritative public benchmark datasets from Eurac Research and the FOSS Research Centre. While the broad fleet analysis captured a wide distribution of trend estimates (−4%/year to +3%/year) reflecting the method's sensitivity to data duration and sensor quality, the detailed primary case study demonstrated the framework's high precision, in identifying non-linear, multi-phase degradation. This analysis revealed complex aging dynamics that differed by device, including sharp initial deceleration and instances of mid-life performance acceleration. The resulting degradation rates, with both phase-specific and time-weighted averages ranging from −0.78%/year to −0.20%/year, were found to be physically plausible and consistent with reported industry benchmarks. These findings confirm the framework's utility as a scalable tool for automated performance loss rate assessment that separates non-linear degradation trends from environmental noise
A normalizing flow approach for the inference of star cluster properties from unresolved broadband photometry
No full textContext. Estimating properties of star clusters from unresolved broadband photometry is a challenging problem that is classically tackled using spectral energy distribution (SED) fitting methods that are based on simple stellar population models. However, grid-based methods suffer from computational limitations. Because of their exponential scaling, they can become intractable when the number of inference parameters grows. In addition, nuisance parameters in the model can make the computation of the likelihood function intractable. These limitations can be overcome by modern generative deep learning methods that offer flexible and powerful tools for modeling high-dimensional posterior distributions and fast inference from learned data.
Aims. We present a normalizing flow approach for the inference of cluster age, mass, and reddening parameters from Hubble Space Telescope broadband photometry. In particular, we explore our network’s behavior when dealing with an inference problem that has been analyzed in previous works.
Methods. We used the SED modeling code CIGAL
The mysterious globular cluster population of MATLAS-2019
No full textMATLAS-2019 (also known as NGC5846-UDG1) has attracted significant attention due to the ongoing debate surrounding its globular cluster (GC) population, with several studies addressing the issue, yet reaching little consensus. For this paper, we took advantage of HST’s multi-wavelength coverage (F475W, F606W, and F814W observations) with the addition of deep u-band imaging from the Gran Telescopio Canarias (GTC), to perform the most detailed study and estimation to date of the GC population of the ultra-diffuse galaxy MATLAS-2019. The improved constraints provided by the combination of high spatial resolution and better coverage of the GC spectral energy distribution has allowed us to obtain a clean sample of GCs in this galaxy. We report a number of 33 ± 3 GCs in MATLAS-2019, supporting the previous lower estimates for this galaxy. The GC population of this galaxy is highly concentrated with ∼80% of the GCs inside the effective radius (Re) of the galaxy, and the GC half-number radius Re,GC is 0.7 × Re. Using the GC-halo mass relation, we estimate a halo mass for MATLAS-2019 of (1.14 ± 0.1) × 1011 M⊙. The GC luminosity function and the distribution of effective radii of the GCs favour a distance to the galaxy of 20.0 ± 0.9 Mpc. In agreement with previous findings, we find that the distribution of GCs is highly asymmetric even though the distribution of stars in the galaxy is symmetric. This suggests that assumptions about the symmetry of the GC distribution may be incorrect when used to calculate the number of GCs with such low statistics
Mass-luminosity anomalies: Plausible evidence of recent stellar interaction in the extraordinary blue straggler S1082
No full textContext. We present an observational and theoretical study of the complex stellar system S1082 in the open cluster M67. This system consists of at least four stars: a blue straggler in a 1.07-day eclipsing binary with a main sequence star (binary A) and another blue straggler in a 1185-day orbit with an unknown companion (binary B).
Aims. We analyzed observational data to obtain the orbital and stellar parameters of the components of the eclipsing system. We then explored mass transfer and dynamical encounter scenarios that could explain the derived properties of all of the components of S1082.
Methods. We combined high-precision photometry from K2 and TESS with archival light curves, new radial-velocity measurements, and speckle imaging to refine the orbital and physical parameters of the system. To explore the formation pathways, we conducted binary evolution simulations with MESA and dynamical scattering experiments with FEWBODY, followed by a tidal evolution modeling procedure.
Results. Our revised radial-velocity solutions yield significantly changed dynamical masses for binary A, reducing the tension with the cluster turnoff mass compared to previous studies. Speckle imaging shows two resolved components separated by 390 AU in projection and, in combination with the two spectroscopic orbits, this is suggestive of a hierarchical quadruple configuration. Our results suggest that the two blue stragglers formed separately, with later dynamical encounters assembling the present configuration. This work underscores the importance of stellar dynamics in shaping the evolution of complex stellar systems within cluster environments such as M67
The lack of fast rotators in Cyg OB2
No full textContext. Cygnus OB2, located within the Cygnus X complex – one of the most active star-forming regions of the Galaxy – hosts hundreds of O- and B-type stars at different evolutionary stages. This rich association offers a unique opportunity to study the evolution and dynamic interactions of massive stars. However, despite extensive studies, a notable absence of a fast-rotating group (v sin i > 200 km s−1) among the O-type population of Cygnus OB2 challenges current models of massive star evolution.
Aims. Stellar rotation strongly impacts spectral line shapes of O-type stars, with high rotational velocities potentially leading to misclassifications. This study investigates whether some stars in Cygnus OB2, classified at low spectral resolution as B0, are actually rapidly rotating late-O types. Such cases could explain the observed lack of fast rotators in Cygnus OB2.
Methods. Considering the effects of rotation, we reclassified the known B0 population in Cygnus OB2, using the MG
SPT-GloCal: Enhancing [O/Fe] and [Mg/Fe] determinations in metal-poor stars with UV-extended low-resolution CSST spectra
No full textMetal-poor stars (MP, [Fe/H]<−1.0) retain the chemical signatures of the early Universe, making their α-element invaluable for tracing the Galactic chemical evolution. Traditional optical spectroscopic methods and machine learning approaches often struggle at low metallicities and neglect the diagnostic power of ultraviolet (UV) spectral features (e.g., OH bands, Mg II/Mg I lines) that are accessible to the forthcoming Chinese Space Station Telescope (CSST). Using over 1.8 × 105 simulated CSST spectra, we developed the spectral transformer (SPT)-GloCal model to quantify the impact of UV (2550−4000 Å) low-resolution (R ≈ 200) spectra on the precision of [O/Fe] and [Mg/Fe] estimates in MP stars. The model improves local attention through score-aware competitive filtering and integrates it with global attention via a learnable gating mechanism. We compared models trained on full spectra versus optical-only spectra. Incorporating UV spectra halved the mean absolute error (MAE) of [O/Fe] predictions from 0.0785 to 0.0367 dex and reduced the scatter (σ) from 0.135 to 0.063 dex. For [Mg/Fe], MAE decreased from 0.0010 to 0.0006 dex and σ from 0.054 to 0.0068 dex. Error analyses demonstrated that UV data lead to more stable and accurate estimates, especially at a high log g and low Teff. SPT-GloCal outperforms both its predecessor (SPT) and tree-based regressors, confirming the effectiveness of its global-local attention design. Furthermore, tests on spectra with simulated noise show that the model maintains consistent performance across a range of signal-to-noise ratios (S/N =30−50), with marginal gains over the SPT model at the lower S/N end. UV spectral features, even at low resolution (R ≈ 200), enhance α-element abundance determinations. The SPT-GloCal framework provides a scalable solution for upcoming space-based surveys. Future work will apply this model to real CSST data, thus extending it to other elements
Pre-perihelion evolution of the NiI/FeI abundance ratio in the coma of the interstellar comet 3I/ATLAS: From extreme to normal
No full textEmission lines of FeI and NiI are commonly found in the coma of Solar System comets, even at large heliocentric distances. These atoms are most likely released from the surface of the comet’s nucleus or from a short-lived parent. The presence of these lines in cometary spectra is unexpected because the surface blackbody equilibrium temperature is too low to allow the sublimation of refractory minerals containing these metals. These lines were also found in the interstellar comet 2I/Borisov, which has a NiI/FeI abundance ratio similar to that observed in Solar System comets. On average, this ratio is one order of magnitude higher than the solar Ni/Fe abundance ratio. Here, we report observations of the interstellar comet 3I/ATLAS, which were carried out with the ESO Very Large Telescope equipped with the UVES and X-shooter spectrographs. Spectra were obtained at heliocentric distances ranging from 3.14 to 1.85 au. Nil was detected at all epochs. FeI was only detected at heliocentric distances smaller than 2.64 au. We estimated the Nil and FeI production rates by comparing the observed line intensities with those produced by a dedicated fluorescence model. Comet 3I first exhibited extreme and unusual NiI/FeI abundance ratios during the initial stages of its activity. However, as its heliocentric distance decreased, this ratio became indistinguishable from those observed in Solar System comets and in comet 2I∕Borisov. Comet 3I was found to be C2-depleted, with a NiI/FeI abundance ratio finally consistent with other C2-depleted comets. Nevertheless, comet 3I remains exceptional due to its high, total production rate of NiI and FeI, which is at least one order of magnitude larger than that of other comets. We interpreted these observations assuming that the NiI and FeI atoms were released through the sublimation of Ni(CO)4 and Fe(CO)5 carbonyls. This scenario provides a straightforward explanation for the asymmetric release of NiI and FeI atoms in the cometary coma and how it depends on the heliocentric distance. It also supports the presence of carbonyls in the cometary material
Accelerating exoplanet climate modelling
No full textContext. With the development of ever-improving telescopes capable of observing exoplanet atmospheres in greater detail and number, there is a growing demand for enhanced three-dimensional climate models to support and help interpret observational data from space missions such as CHEOPS, TESS, JWST, PLATO, and Ariel. However, the computationally intensive and time-consuming nature of general circulation models (GCMs) poses significant challenges in simulating a wide range of exoplanetary atmospheres.
Aims. The aim of this study is to determine whether machine learning (ML) algorithms can be used to predict the three-dimensional temperature and wind structure of arbitrary tidally locked gaseous exoplanets in a range of planetary parameters.
Methods. We introduced a new three-dimensional GCM grid comprising 60 inflated hot Jupiters orbiting A, F, G, K, and M-type host stars, which we modelled using ExoRa
New methods to improve the decontamination of slitless spectra
No full textThis paper proposes four new methods to decontaminate spectra of stars and galaxies resulting from slitless spectroscopy used in many space missions such as Euclid. These methods are based on two distinct approaches that simultaneously take into account multiple dispersion directions of light. The first approach, called the local instantaneous approach, is based on an approximate linear instantaneous model. The second approach, called the local convolutive approach, is based on a more realistic convolutive model that allows for the simultaneous decontamination and deconvolution of spectra. For each approach, a mixing model was developed to link the observed data to the source spectra. This was done either in the spatial domain for the local instantaneous approach or in the Fourier domain for the local convolutive approach. Four methods were then developed to decontaminate these spectra from the mixtures, exploiting the direct images provided by photometers. Test results obtained using realistic, noisy, Euclid-like data confirmed the effectiveness of the proposed methods