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The Javalambre Photometric Local Universe Survey (J-PLUS) is a 12-band photometric survey using the 83-cm JAST telescope. Data Release 3 includes 47.4 million sources. J-PLUS DR3 only provides star-galaxy classification so that quasars are not identified from the other sources. Given the size of the data set, machine learning methods could provide a valid alternative classification and a solution to the classification of quasars. Our objective is to classify J-PLUS DR3 sources into galaxies, stars, and quasars, outperforming the available classifiers in each class. We use an automated machine learning tool called TPOT to find an optimized pipeline to perform the classification. The supervised machine learning algorithms are trained on the crossmatch with SDSS DR18, LAMOST DR8, and Gaia. We checked that the training set of about 660 thousand galaxies, 1.2 million stars, and 270 thousand quasars is both representative and contain a minimal presence of contaminants (less than 1 per cent). We considered 37 features: the 12 photometric bands with respective errors, 6 colours, 4 morphological parameters, galactic extinction with its error, and the PSF relative to the corresponding pointing. With TPOT genetic algorithm, we found that XGBoost provides the best performance: the AUC for galaxies, stars, and quasars is above 0.99 and the average precision is above 0.99 for galaxies and stars and 0.96 for quasars. XGBoost outperforms the classifiers already provided in J-PLUS DR3 and also classifies quasars. [ABSTRACT FROM AUTHOR] more...

Context. The Copernican principle, the notion that we are not at a special location in the Universe, is one of the cornerstones of modern cosmology. Its violation would invalidate the Friedmann-Lemaître-Robertson-Walker metric, causing a major change in our understanding of the Universe. Thus, it is of fundamental importance to perform observational tests of this principle. Aims. We determine the precision with which future surveys will be able to test the Copernican principle and their ability to detect any possible violations. Methods. We forecast constraints on the inhomogeneous Lemaître-Tolman-Bondi (LTB) model with a cosmological constant Λ, basically a cosmological constant Λ and cold dark matter (CDM) model but endowed with a spherical inhomogeneity. We consider combinations of currently available data and simulated Euclid data, together with external data products, based on both ΛCDM and ΛLTB fiducial models. These constraints are compared to the expectations from the Copernican principle. Results. When considering the ΛCDM fiducial model, we find that Euclid data, in combination with other current and forthcoming surveys, will improve the constraints on the Copernican principle by about 30%, with ±10% variations depending on the observables and scales considered. On the other hand, when considering a ΛLTB fiducial model, we find that future Euclid data, combined with other current and forthcoming datasets, will be able to detect gigaparsec-scale inhomogeneities of contrast −0.1. Conclusions. Next-generation surveys, such as Euclid, will thoroughly test homogeneity at large scales, tightening the constraints on possible violations of the Copernican principle. [ABSTRACT FROM AUTHOR] more...

Context. With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3192 deg2 and contains 47.4 million objects. However, the classification algorithms currently implemented in the J-PLUS pipeline are deterministic and based solely on the morphology of the sources. Aims. Our goal is to classify the sources identified in the J-PLUS DR3 images as stars, quasi-stellar objects (QSOs), or galaxies. For this task, we present BANNJOS, a machine learning pipeline that utilizes Bayesian neural networks to provide the full probability distribution function (PDF) of the classification. Methods. BANNJOS has been trained on photometric, astrometric, and morphological data from J-PLUS DR3, Gaia DR3, and CatWISE2020, using over 1.2 million objects with spectroscopic classification from SDSS DR18, LAMOST DR9, the DESI Early Data Release, and Gaia DR3. Results were validated on a test set of about 1.4 × 105 objects and cross-checked against theoretical model predictions. Results. BANNJOS outperforms all previous classifiers in terms of accuracy, precision, and completeness across the entire magnitude range. It delivers over 95% accuracy for objects brighter than r = 21.5 mag and ~ 90% accuracy for those up to r = 22 mag, where J-PLUS completeness is ≲ 25%. BANNJOS is also the first object classifier to provide the full PDF of the classification, enabling precise object selection for high purity or completeness, and for identifying objects with complex features, such as active galactic nuclei with resolved host galaxies. Conclusions. BANNJOS effectively classified J-PLUS sources into around 20 million galaxies, one million QSOs, and 26 million stars, with full PDFs for each, which allow for later refinement of the sample. The upcoming J-PAS survey, with its 56 color bands, will further enhance BANNJOS's ability to detail the nature of each source. [ABSTRACT FROM AUTHOR] more...

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will scan thousands of square degrees of the northern sky with a unique set of 56 filters using the dedicated 2.55 m Javalambre Survey Telescope (JST) at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera (4.2 deg2 field-of-view with 1.2 Gpixels), the JST was equipped with the JPAS-Pathfinder, a one CCD camera with a 0.3 deg2 field-of-view and plate scale of 0.23 arcsec pixel−1. To demonstrate the scientific potential of J-PAS, the JPAS-Pathfinder camera was used to perform miniJPAS, a ∼1 deg2 survey of the AEGIS field (along the Extended Groth Strip). The field was observed with the 56 J-PAS filters, which include 54 narrow band (FWHM ∼ 145 Å) and two broader filters extending to the UV and the near-infrared, complemented by the u, g, r, i SDSS broad band filters. In this miniJPAS survey overview paper, we present the miniJPAS data set (images and catalogs), as we highlight key aspects and applications of these unique spectro-photometric data and describe how to access the public data products. The data parameters reach depths of magAB ≃ 22−23.5 in the 54 narrow band filters and up to 24 in the broader filters (5σ in a 3″ aperture). The miniJPAS primary catalog contains more than 64 000 sources detected in the r band and with matched photometry in all other bands. This catalog is 99% complete at r = 23.6 (r = 22.7) mag for point-like (extended) sources. We show that our photometric redshifts have an accuracy better than 1% for all sources up to r = 22.5, and a precision of ≤0.3% for a subset consisting of about half of the sample. On this basis, we outline several scientific applications of our data, including the study of spatially-resolved stellar populations of nearby galaxies, the analysis of the large scale structure up to z ∼ 0.9, and the detection of large numbers of clusters and groups. Sub-percent redshift precision can also be reached for quasars, allowing for the study of the large-scale structure to be pushed to z > 2. The miniJPAS survey demonstrates the capability of the J-PAS filter system to accurately characterize a broad variety of sources and paves the way for the upcoming arrival of J-PAS, which will multiply this data by three orders of magnitude. [ABSTRACT FROM AUTHOR] more...

The concentration values of polychlorodibenzodioxins (PCDDs), polychlorodibenzofurans (PCDFs), and dioxin-like polychlorobiphenyls (DL-PCBs) in blood serum samples (pools) of metallurgical workers in the area of the city of Brescia (northern Italy) were statistically processed. As to workers' exposure characteristics, pools were divided into 34 professionally exposed (PE) and 11 non-professionally exposed (NPE). A further subdivision of PE pools was according to workplaces in which ferrous (N = 24) and non-ferrous (N = 10) materials were handled. To evaluate the aforesaid differences we applied the age-adjusted Generalized Linear Models. We identified significant (P ≤ 0.05) exposure models of the classification groups. The first subdivision was confirmed by the concentrations of 1,2,3,4,6,7,8-H 7 CDF, DL-PCB 105, and DL-PCB 189; the second was confirmed by the concentrations of PCDF TEQ 97 , PCDD + PCDF + DL-PCB (TEQ TOT ) TEQ 97 , 2,3,4,7,8-P 5 CDF, 1,2,3,6,7,8-H 6 CDD, 1,2,3,4,6,7,8-H 7 CDD, and PCB 189. Based on the literature, all mentioned congeners have been found in stack gas and fly ash samples of metallurgical plants: therefore, these indicators indicate the exposure to such work environments. Specifically, the concentrations measured in the workers’ blood serum appear to depend on the type of material processed during work. [ABSTRACT FROM AUTHOR] more...

In September 2013 a waste-to-energy (WTE) incinerator located in the Turin area (Piedmont, Northern Italy) started to produce energy by the incineration of municipal solid wastes. The plant, one of the largest WTE incinerator in Europe, burns up to 490,000 tons of waste per year. A health surveillance program was implemented in order to evaluate the potential health effects on the population living near the plant. This program included a biomonitoring study aimed at assessing levels of several environmental contaminants including, among others, PCDDs, PCDFs, and PCBs. Before the WTE incinerator start-up (T 0), a group of 85 subjects (41 "exposed" and 44 "not exposed" subjects) was randomly selected for enrollment by the local health units among individuals aged 36–50 years who had been living in the same area for at least five years prior to the study. Subjects were balanced by exposure area, sex and five-year age classes. As from the study design, the same cohort was re-evaluated after three years of incinerator activity (T 2). A parallel study was conducted on a group of 12 farmers living and/or working in farms located in an area in the range of 5 km around the incinerator. Results of this study did not evidence any impact of the WTE plant on human exposure to PCDDs, PCDFs, and PCBs. In fact, no significant differences were found in the concentrations of PCDDs + PCDFs, DL-PCBs, and NDL-PCBs measured in the population group residing near the plant after three years of activity (T 2) with respect to the control group. A significant decrease of serum concentrations of all the analytes was observed at T 2 in both groups compared to T 0. Serum concentrations of PCDDs, PCDFs, and PCBs in the group of farmers were higher than those observed in the adult population under study. [Display omitted] • Human exposure to waste incinerator emissions is of great concern. • No impact of the WTE plant was observed on human exposure to PCDDs, PCDFs, and PCBs. • PCDD, PCDF and PCB decrease was observed at T 2 in exposed and not exposed groups. • Observed concentrations of PCDDs, PCDFs, and PCBs were higher in females. [ABSTRACT FROM AUTHOR] more...