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Flux excesses in the early-time light curves of Type Ia supernovae (SNe Ia) are predicted by multiple theoretical models and have been observed in a number of nearby SNe Ia over the last decade. However, the astrophysical processes that cause these excesses may affect their use as standardizable candles for cosmological parameter measurements. We perform a systematic search for early-time excesses in SNe Ia observed by the Zwicky Transient Facility (ZTF) to study whether SNe Ia with these excesses yield systematically different Hubble residuals. We analyze two compilations of SN Ia light curves from ZTF's first year of operations: 127 high-cadence light curves from Y. Yao et al. and 305 light curves from the ZTF cosmology data release of S. Dhawan et al. We detect significant early-time excesses for 17 SNe Ia in these samples and find that the excesses have a median g − r color of 0.10 ± 0.11 mag; we do not find a clear preference for blue excesses as predicted by several models. Using the SALT3 model, we measure Hubble residuals for these two samples, finding that excess-having SNe Ia may have lower Hubble residuals (HR) after correcting for shape, color, and host-galaxy mass, at ∼2–3 σ significance; our baseline result is ΔHR = −0.056 ± 0.026 mag (2.2 σ). We compare the host-galaxy masses of excess-having and no-excess SNe Ia and find they are consistent, though at marginal significance excess-having SNe Ia may prefer lower-mass hosts. Additional discoveries of early excess SNe Ia will be a powerful way to understand potential biases in SN Ia cosmology and probe the physics of SN Ia progenitors. [ABSTRACT FROM AUTHOR]

We introduce an improved method for decomposing the emission of active galactic nuclei (AGN) and their host galaxies using templates from principal component analysis (PCA). This approach integrates prior information from PCA with a penalized pixel fitting mechanism that improves the precision and effectiveness of the decomposition process. Specifically, we have reduced the degeneracy and overfitting in AGN host decomposition, particularly for those with low signal-to-noise ratios (SNRs), where traditional methods tend to fail. By applying our method to 76,565 Sloan Digital Sky Survey Data Release 16 quasars with z < 0.8, we achieve a success rate of ≈94%, thus establishing the largest host-decomposed spectral catalog of quasars to date. Our fitting results consider the impact of the host galaxy on the overestimation of the AGN luminosity and black hole mass (M BH). Furthermore, we obtained stellar velocity dispersion (σ ⋆) measurements for 4137 quasars. The slope of the M BH− σ ⋆ relation in this subsample is generally consistent with previous quasar studies beyond the local Universe. Our method provides a robust and efficient approach to disentangle the AGN and host galaxy components across a wide range of SNRs and redshifts. [ABSTRACT FROM AUTHOR]

In this paper, we re-estimate the astrometric and photometric parameters of the young open star cluster King 18 based on Gaia Data Release 3 (DR3), Two Micron All-sky Survey (2MASS) and VRI CCD observations using the f/4.9 Newtonian focus of 74-inch telescope at Kottamia Astronomical Observatory (KAO) in Egypt. King 18 is a poorly studied open star cluster, for which new results are found in the current study. In order to estimate the membership and determine all the astrophysical parameters of the cluster, we have used data from Gaia DR3 and KAO. The center, cluster radius, radial density distribution, color-magnitude diagrams, distance, age, and reddening of King 18 are calculated. Also, the luminosity and mass functions, the total mass and the relaxation time of the cluster are estimated. The slope value of the mass function (α ) of King 18 is found to be 2.27± 0.17, which is comparable with Salpeter value. Our estimates for the average cluster age and the relaxation time are 224 ± 6.3 and 28.92 Myrs, respectively. This indicates that King 18 is dynamically stable and a relaxed cluster. The cluster distance modulus from Gaia, 2Mass and VRI observations has been determined to be 12.380 ± 1.320, 12.320 ± 0.107 and 12.280 ± 0.290 mag respectively, which corresponds to distances of 2992.26, 2910.72 and 2857.59 pc, respectively. These results are in good agreement within the error. Moreover the color excesses E(V–I), E(J– K s ) and E( G BP – G RP ) are 0.850 ± 0.087, 0.380 ± 0.091 and 0.980 ± 0.130 respectively. Finally, the proper motions ( μ α cos δ , μ δ ), and parallaxes (ϖ ) are - 2.603 ± 0.018 , - 2.106 ± 0.013 and 0.324 ± 0.040, respectively. [ABSTRACT FROM AUTHOR]

Palomar Gattini-IR (PGIR) is a wide-field, synoptic infrared time domain survey covering ≈15,000 sq. deg. of the accessible sky at ≈1–3 night cadence to a depth of J ≈ 13.0 and ≈14.9 Vega mag in and outside the Galactic plane, respectively. Here, we present the first data release of J -band light curves of Two Micron All Sky Survey (2MASS) sources within the survey footprint covering approximately the first four years of operations. We describe the construction of the source catalog based on 2MASS point sources, followed by exposure filtering criteria and forced PSF photometry. The catalog contains light curves of ≈286 million unique sources with 2MASS magnitudes of J < 15.5 mag, with a total of ≈50 billion photometric measurements and ≈20 billion individual source detections at signal-to-noise-ratio > 3. We demonstrate the photometric fidelity of the catalog by (i) quantifying the magnitude-dependent accuracy and uncertainty of the photometry with respect to 2MASS and (ii) comparing against forced PGIR aperture photometry for known variable sources. We present simple filtering criteria for selecting reliable photometric measurements as well as example Python notebooks for users. This catalog is one of the largest compilation of nightly cadence, synoptic infrared light curves to date, comparable to those in the largest optical surveys, providing a stepping stone to upcoming infrared surveys in the coming decade. [ABSTRACT FROM AUTHOR]

The period of reentering society after prison is a critical time in the life-course and presents numerous challenges. With whom and where individuals live can determine aspects of social support, as well as bonds and informal social control that may predict whether a person "succeeds" by abstaining from crime and avoiding technical violations of parole. We use detailed administrative data from a release cohort in Missouri to construct monthly variation in household and community context at two levels (neighborhood disadvantage and county-level rural-urban designation). We follow the local-life circumstances approach, decomposing changing context into within and between person variation (Horney et al., 1995). We find important selection effects but also intervention effects – with households including family as particularly beneficial. This work further highlights the needs for multiple measures of recidivism and a broadening of the geographic locales researchers and policymakers consider. [ABSTRACT FROM AUTHOR]

Most of the stars in the Universe are M spectral class dwarfs, which are known to be the source of bright and frequent stellar flares. In this paper, we propose new approaches to discover M-dwarf flares in ground-based photometric surveys. We employ two approaches: a modification of a traditional method of parametric fit search and a machine learning algorithm based on active anomaly detection. The algorithms are applied to Zwicky Transient Facility (ZTF) data release 8, which includes the data from the ZTF high-cadence survey, allowing us to reveal flares lasting from minutes to hours. We analyse over 35 million ZTF light curves and visually scrutinize 1168 candidates suggested by the algorithms to filter out artefacts, occultations of a star by an asteroid, and other types of known variable objects. The result of this analysis is the largest catalogue of ZTF flaring stars to date, representing 134 flares with amplitudes ranging from −0.2 to −4.6 mag, including repeated flares. Using Pan-STARRS DR2 colours, we assign a spectral subclass to each object in the sample. For 13 flares with well-sampled light curves and available geometric distances from Gaia DR3, we estimate the bolometric energy. This research shows that the proposed methods combined with the ZTF's cadence strategy are suitable for identifying M-dwarf flares and other fast transients, allowing for the extraction of significant astrophysical information from their light curves. [ABSTRACT FROM AUTHOR]

We present the Ultracool Dwarf Companion Catalogue of 278 multiple systems, 32 of which are newly discovered, each with at least one spectroscopically confirmed Ultracool Dwarf, within a 100 pc volume-limited sample. This catalogue is compiled using the Gaia Catalogue of Nearby Stars for stellar primaries and the Gaia Ultracool Dwarf Sample for low-mass companions and includes 241 doubles, 33 triples, and 4 higher-order systems established from positional, proper motion, and parallax constraints. The catalogue seeks to identify probable benchmark systems within 100 pc to obtain model-independent astrophysical parameters of Ultracool Dwarfs. Chance alignment probabilities are calculated to evaluate the physical nature of each system. Astrometric and photometric data from Gaia Data Release 3 and the Two Micron All Sky Survey are included for all objects. We identify potential unseen companions using a combination of the renormalized unit weight error, image parameter determination statistics, non-single star solutions, and photometric blending as provided by Gaia , identifying hierarchical Ultracool triple systems. Our catalogue includes 17 White Dwarf – Ultracool Dwarf systems, whose ages are determined using cooling models. We also use the Gaia FLAME results and the BANYAN Σ procedures to age 40 and 34 systems, respectively, and derive mass estimates from evolutionary models. [ABSTRACT FROM AUTHOR]

We present the largest optical photometry compilation of gamma-ray bursts (GRBs) with redshifts (z). We include 64813 observations of 535 events (including upper limits) from 28 February 1997 to 18 August 2023. We also present a user-friendly web tool grbLC which allows users to visualize photometry, coordinates, redshift, host galaxy extinction, and spectral indices for each event in our database. Furthermore, we have added a Gamma-ray Coordinate Network (GCN) scraper that can be used to collect data by gathering magnitudes from the GCNs. The web tool also includes a package for uniformly investigating colour evolution. We compute the optical spectral indices for 138 GRBs, for which we have at least four filters at the same epoch in our sample, and craft a procedure to distinguish between GRBs with and without colour evolution. By providing a uniform format and repository for the optical catalogue, this web-based archive is the first step towards unifying several community efforts to gather the photometric information for all GRBs with known redshifts. This catalogue will enable population studies by providing light curves (LCs) with better coverage since we have gathered data from different ground-based locations. Consequently, these LCs can be used to train future LC reconstructions for an extended inference of the redshift. The data gathering also allows us to fill some of the orbital gaps from Swift in crucial points of the LCs, e.g. at the end of the plateau emission or where a jet break is identified. [ABSTRACT FROM AUTHOR]

Introduction: Closed-loop spinal cord stimulation (CL-SCS) is a recently introduced system that records evoked compound action potentials (ECAPs) from the spinal cord elicited by each stimulation pulse and uses this information to automatically adjust the stimulation strength in real time, known as ECAP-controlled SCS. This innovative system compensates for fluctuations in the distance between the epidural leads and the spinal cord by maintaining the neural response (ECAP) at a predetermined target level. This data collection study was designed to assess the performance of the first CL-SCS system in a real-world setting under normal conditions of use in multiple European centers. The study analyzes and presents clinical outcomes and electrophysiological and device data and compares these findings with those reported in earlier pre-market studies of the same system. Methods: This prospective, multicenter, observational study was conducted in 13 European centers and aimed to gather electrophysiological and device data. The study focused on the real-world application of this system in treating chronic pain affecting the trunk and/or limbs, adhering to standard conditions of use. In addition to collecting and analyzing basic demographic information, the study presents data from the inaugural patient cohort permanently implanted at multiple European centers. Results: A significant decrease in pain intensity was observed for overall back or leg pain scores (verbal numerical rating score [VNRS]) between baseline (mean ± standard error of the mean [SEM]; n = 135; 8.2 ± 0.1), 3 months (n = 93; 2.3 ± 0.2), 6 months (n = 82; 2.5 ± 0.3), and 12 months (n = 76; 2.5 ± 0.3). Comparison of overall pain relief (%) to the AVALON and EVOKE studies showed no significant differences at 3 and 12 months between the real-world data release (RWE; 71.3%; 69.6%) and the AVALON (71.2%; 73.6%) and EVOKE (78.1%; 76.7%) studies. Further investigation was undertaken to objectively characterize the physiological parameters of SCS therapy in this cohort using the metrics of percent time above ECAP threshold (%), dose ratio, and dose accuracy (µV), according to previously described methods. Results showed that a median of 90% (40.7–99.2) of stimuli were above the ECAP threshold, with a dose ratio of 1.3 (1.1–1.4) and dose accuracy of 4.4 µV (0.0–7.1), based on data from 236, 230, and 254 patients, respectively. Thus, across all three metrics, the majority of patients had objective therapy metrics corresponding to the highest levels of pain relief in previously reported studies (usage over threshold > 80%, dose ratio > 1.2, and error < 10 µV). Conclusions: In conclusion, this study provides valuable insights into the real-world application of the ECAP-controlled CL-SCS system, highlighting its potential for maintaining effective pain relief and objective neurophysiological therapy metrics at levels seen in randomized control trials, and potential for quantifying patient burden associated with SCS system use via patient–device interaction metrics. Clinical Trial Registration: In the Netherlands, the study is duly registered on the International Clinical Trials Registry Platform (Trial NL7889). In Germany, the study is duly registered as NCT05272137 and in the United Kingdom as ISCRTN27710516 and has been reviewed by the ethics committee in both countries. [ABSTRACT FROM AUTHOR]

Recent studies have identified star clusters with multiple components based on accurate spatial distributions and/or proper motions from Gaia  Data Release 3 (DR3), utilizing diverse diagnostics to gain an understanding of subgroup evolution. These findings motivated us to search for subgroups among the objects examined in our previous work, which employed fractal statistics. The present study considers seven open clusters that exhibit significant dispersion in age and/or proper motion distributions, suggesting that they are not single clusters. In order to characterize the stellar groups, we calculate the membership probability using Bayesian multidimensional analysis by fitting the observed proper motion distribution of the candidates. A probability distribution is also used to determine the distance of the cluster, which is obtained from the mean value of the distance modes. The photometry from Gaia  DR3 is compared with evolutionary models to estimate the cluster age and total mass. In our sample, double components are found only for Markarian 38 and NGC 2659. The other five clusters are confirmed as being single. The structural parameters, such as |$\mathcal {Q}$|⁠ , |$\Lambda _{\rm MSR}$|⁠ , and |$\Sigma _{\rm LDR}$|⁠ , are compared with results from N -body simulations to investigate how the morphology of the stellar clustering evolves. The new results, for a more complete sample of cluster members, provide a better definition of the distribution type (central concentration or substructured region) inferred from the |$\overline{m} - \overline{s}$| plot. [ABSTRACT FROM AUTHOR]

With the ever-increasing intertwining of social networks and daily existence, the accumulation of personal privacy information is steadily mounting. However, the exposure of such data could lead to disastrous consequences. Current graph data protection algorithms lack sufficient research on the characteristics of social users, while simultaneously incurring significant time and space overhead. Additionally, the strategies lack adaptability in incorporating noise, often resulting in a subsequent decrease in data availability. To address these issues, a novel approach called the Information Entropy-driven Adaptive Differential Privacy Protection Scheme (IEA-DP) is presented for the release of social data in this study. The proposed solution initially designs the InfomapMerge algorithm to divide the data into communities based on the characteristics of social networks, thereby enabling parallel processing, and mitigating the time and space overhead. Subsequently, the Adaptive Edge Modification Algorithm (AEMA) is proposed to optimize the noise addition process by adaptively adding noise based on the score of node importance. This effectively reduces the amount of added noise, increasing data availability. Finally, the experimental results conducted on six public datasets demonstrate that the IEA-DP scheme strikes a desirable balance between data availability and privacy. [ABSTRACT FROM AUTHOR]

The study of China's geo-relations has received wide attention from the academic world. Chinese diplomatic speeches objectively record the process of China's interaction with other countries and the evolution of its attention to current hotspots, and the study of geo-relations hotspots from China's perspective can be conducted based on this officially released unstructured data. This paper selects Chinese Foreign Ministry speech text data and analyzes the hot issues implied in the text data from the perspective of feature vocabulary and topic coding, and the study shows that: (1) The Asia-Pacific and neighboring countries occupy a primary position in the handling of China's geopolitical relations. (2) In recent years, the geopolitical conflict with the United States and other Western countries has shifted from geo-economic to geo-cultural aspects. (3) In terms of topics, trade and economy are the focus of geopolitical relations between countries in the world, and the role of science, technology and innovation elements in the penetration of great power competition is becoming increasingly prominent. (4) In terms of geostrategy, attention is drawn to the impact of NATO's "eastern concern" on the Asia-Pacific region, and the South Pacific island region is a potential major power geopolitical game area that deserves attention. This paper applies text analysis techniques to study the hot issues of China's geopolitical relations, providing a new perspective for the study of geopolitical relations and a certain reference for the development of China's geopolitical relations. [ABSTRACT FROM AUTHOR]

We present the stellar value-added catalogue based on the Dark Energy Spectroscopic Instrument (DESI) Early Data Release. The catalogue contains radial velocity and stellar parameter measurements for |$\simeq$| 400 000 unique stars observed during commissioning and survey validation by DESI. These observations were made under conditions similar to the Milky Way Survey (MWS) currently carried out by DESI but also include multiple specially targeted fields, such as those containing well-studied dwarf galaxies and stellar streams. The majority of observed stars have |$16\lt r\lt 20$| with a median signal-to-noise ratio in the spectra of |$\sim$| 20. In the paper, we describe the structure of the catalogue, give an overview of different target classes observed, as well as provide recipes for selecting clean stellar samples. We validate the catalogue using external high-resolution measurements and show that radial velocities, surface gravities, and iron abundances determined by DESI are accurate to 1 km s−1, 0.3 dex, and |$\sim$| 0.15 dex respectively. We also demonstrate possible uses of the catalogue for chemo-dynamical studies of the Milky Way stellar halo and Draco dwarf spheroidal. The value-added catalogue described in this paper is the very first DESI MWS catalogue. The next DESI data release, expected in less than a year, will add the data from the first year of DESI survey operations and will contain approximately 4 million stars, along with significant processing improvements. [ABSTRACT FROM AUTHOR]

Over the last couple of years, the appearance of the third data release from the Gaia satellite has triggered various wide binary low acceleration gravity tests. Wide binaries with typical total masses |$\approx 1.0 - 1.6\,\mathrm{ M}_{\odot }$| and separations above a few thousand au probe the low acceleration |$a \lesssim a_{0}$| regime, where at galactic and larger scales gravitational anomalies typically attributed to the presence of an as yet undetected dark matter component appear, where |$a_{0} \approx 1.2\times 10^{-10}$| m s |$^{-2}$| is the acceleration scale of Modified Newtonian Dynamics (MOND). Thus, studies of the relative velocities and separations on the plane of the sky, |$v_{2\mathrm{ D}}$| and |$s_{2\mathrm{ D}}$|⁠ , respectively, of wide binary stars extending to separations above a few kau, provide an independent approach on the empirical study of gravity in the interesting |$a \lesssim a_{0}$| acceleration range. Two independent groups, through complementary approaches, have obtained evidence for a departure from Newtonian predictions in the low acceleration regime, in consistency with MOND expectations for wide binary orbits in the Solar Neighbourhood. Two other groups however, have instead reported results showing a clear preference for Newtonian gravity over various MOND alternatives tested, over the same low acceleration regime. We here take a critical look at the various studies in question, from sample selection to statistical treatment of the wide binary relative velocities obtained. We discover a couple of critical problems in the formal design and statistical implementation shared by the two latter groups, and show explicitly how these yield biased conclusions. [ABSTRACT FROM AUTHOR]

This document is a correction to a previous article on gas-phase metallicities in MaNGA. The correction addresses an error in the calculation of O3N2-based calibrations, resulting in incorrect metallicity values. The correction decreases the raw metallicity values for these calibrations and slightly increases the number of overall spaxels with metallicities. The document also includes additional tables showing the number of metallicity values per calibration and the scatter of emission-line permutations between calibrations. The update on the polynomial fits used in the study shows a shift in the fits when converting between different calibrations, with a median magnitude of 0.032 dex. Some figures in the original study are affected, but most are not visibly different. The emission-line data used in the study is publicly available, and metallicity values can be obtained upon request. [Extracted from the article]

The Tully–Fisher Relation (TFR) is a well-known empirical relationship between the luminosity of a spiral galaxy and its circular velocity, allowing us to estimate redshift independent distances. Here we use high signal-to-noise H  i 21-cm integrated spectra from the second pilot data release (PDR2, 180 deg2) of the Widefield ASKAP L -band Legacy All-sky Blind surveY (WALLABY). In order to prepare for the full WALLABY survey, we have investigated the TFR in phase 2 of the pilot survey with a further three fields. The data were obtained with wide-field Phased Array Feeds on the Australian Square Kilometre Array Pathfinder (ASKAP) and have an angular resolution of 30 arcsec and a velocity resolution of |$\sim$| 4 km s−1. Galaxy luminosities have been measured from the Wide-field Infrared Survey Explorer , and optical galaxy inclinations from the Dark Energy Camera Legacy Survey. We present TFRs for wavelengths from 0.8 to 3.4  μ m. We examine sources of galaxy inclination data and investigate magnitudes from the DECam Local Volume Exploration Survey and DENIS catalogues and the 4HS target catalogue based on the VISTA Hemisphere Survey. We consider the baryonic TFR. These are all of interest for TFR using the full WALLABY survey of 200 000 galaxies. We demonstrate that WALLABY TFR distances can take their place among state-of-the-art studies of the local velocity field. [ABSTRACT FROM AUTHOR]

Combining detailed county-to-county migration data with Toxics Release Inventory data, and fine-scale PM 2.5 concentration levels, we investigate the relationship between internal migration, income of migrant and non-migrant households and county-level differences in environmental quality. We show that households moving to "cleaner" counties are relatively "richer"—a result consistent with a sorting by income in the spirit of Tiebout (1956). An implication of this finding is that internal migration could contribute to the persistence of disparities in pollution exposure at the county-level. [ABSTRACT FROM AUTHOR]

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Broad absorption line (BAL) quasars are characterized by gas clouds that absorb flux at the wavelength of common quasar spectral features, although blueshifted by velocities that can exceed |$0.1c$|⁠. BAL features are interesting as signatures of significant feedback, yet they can also compromise cosmological studies with quasars by distorting the shape of the most prominent quasar emission lines, impacting redshift accuracy and measurements of the matter density distribution traced by the Lyman |$\alpha$| forest. We present a catalogue of BAL quasars discovered in the Dark Energy Spectroscopic Instrument (DESI) survey Early Data Release, which were observed as part of DESI Survey Validation, as well as the first two months of the main survey. We describe our method to automatically identify BAL quasars in DESI data, the quantities we measure for each BAL, and investigate the completeness and purity of this method with mock DESI observations. We mask the wavelengths of the BAL features and re-evaluate each BAL quasar redshift, finding new redshifts which are |$243\, {\rm km}\, {\rm s}^{-1}$| smaller on average for the BAL quasar sample. These new, more accurate redshifts are important to obtain the best measurements of quasar clustering, especially at small scales. Finally, we present some spectra of rarer classes of BALs that illustrate the potential of DESI data to identify such populations for further study. [ABSTRACT FROM AUTHOR]

With the emergence and development of application requirements such as data analysis and publishing, it is particularly important to use differential privacy protection technology to provide more reliable, secure, and compliant datasets for research in the field of children's health. This paper focuses on the differential privacy protection of the ultrasound examination health dataset of adolescents in southern Texas from three aspects: differential privacy protection with output perturbation on basic statistics, publication of differential privacy marginal histogram and synthesized data, and a machine learning differential privacy learning algorithm. Firstly, differential privacy protection results with output perturbation show that Laplace and Gaussian mechanisms for numerical data, as well as the exponential mechanism for non-numerical data, can achieve the goal of protecting privacy. The exponential mechanism provides higher privacy protection. Secondly, a differential privacy marginal histogram with four attributes can be obtained with an appropriate privacy budget that approximates the marginal histogram of the original data. In order to publish synthetic data, we construct a synthetic query to obtain the corresponding differential privacy histogram for two attributes. Further, a synthetic dataset can be constructed by following the data distribution of the original dataset and the quality of the synthetic data publication can also be evaluated by the mean square error and error rate. Finally, consider a differential privacy logistic regression model under machine learning to predict whether children have fatty liver in binary classification tasks. The experimental results show that the model combined with quadratic perturbation has better accuracy and privacy protection. This paper can provide differential privacy protection models under different demands, which provides important data release and analysis options for data managers and research organizations, in addition to enriching the research on child health data releasing and mining. [ABSTRACT FROM AUTHOR]

To achieve precise prediction of the air pressure changes in the critical components of the air brake system, including brake pipes (BP), auxiliary reservoirs (AR), and brake cylinders (BC), this paper proposed a neural network-based air brake model developed from the brake application and release experimental data with different brake applications (50, 70, 100, and 150 kPa) conducted on a heavy haul train (HHT) test platform. The physical structures of the air brake system and the working mechanisms of a neural network are introduced, and the neural network-based air brake model scheme is presented by analysing the variation of air pressure within the air brake system under typical braking conditions (50 kPa). Besides, by comparing with other models, the superiority of the proposed model is verified, and the proposed model achieves higher computational efficiency, which increased by about 2900 times compared to the fluid dynamic model under the same conditions. Then, the model is applied to the calculation of the longitudinal dynamics of a 10,000-ton HHT, and the results demonstrate that the proposed model could serve as a promising tool for solving the braking excitation problem of longitudinal dynamics of trains and the study of intelligent braking control of trains. [ABSTRACT FROM AUTHOR]

Based on a sample of K giant from Large sky Area Multi-Object fibre Spectroscopic Telescope Data Release 8 and a sample of RR Lyrae (RRL) from Gaia Data Release 3, we investigate the compositions of the Hercules–Aquila Cloud (HAC) and Virgo Overdensity (VOD) and their collective contribution to the tilt and triaxiality of the stellar halo (⁠|$r\, \lt \, 40\, {\rm kpc}$|⁠) as well as two breaks at |$\approx 15\, {\rm kpc}$| and 30 kpc. We apply the Gaussian mixture model to divide the stellar halo into the isotropic component and the radially biased anisotropic component, namely Gaia–Sausage–Enceladus (GSE), and find that both HAC and VOD are dominated by the GSE debris stars with weights of |$0.67^{+0.09}_{-0.07}$| and |$0.57^{+0.07}_{-0.06}$|⁠ , respectively. In addition, using the K giants with orbital parameters, we identify the member stars of known substructures, including GSE, Sagittarius (Sgr), Helmi Streams, Sequoia, Thamnos, Pontus, Wukong, and Metal-weak Thick Disc, to probe the compositions of low-eccentricity stars in the HAC and VOD regions. In density fittings of the RRL sample, we note that the absence of HAC and VOD has a weak effect on the shape of halo. Finally, we find that the radially biased anisotropic halo contributes majorly to the stellar halo that can be modelled with a tilted triaxial ellipsoid and a doubly broken power law with breaking radii at |$18.08^{+2.04}_{-3.22}\, {\rm kpc}$| and |$33.03^{+1.30}_{-1.21}\, {\rm kpc}$|⁠. This has important significance for understanding the status of large diffuse overdensities in the Milky Way. [ABSTRACT FROM AUTHOR]

We present an extended suite of the Auriga cosmological gravo-magnetohydrodynamical 'zoom-in' simulations of 40 Milky Way-mass haloes and 26 dwarf galaxy–mass haloes run with the moving-mesh code arepo. Auriga adopts the Lambda cold dark matter cosmogony and includes a comprehensive galaxy formation physics model following the coupled cosmic evolution of dark matter, gas, stars, and supermassive black holes which has been shown to produce numerically well-converged galaxy properties for Milky Way-mass systems. We describe the first public data release of this augmented suite of Auriga simulations, which includes raw snapshots, group catalogues, merger trees, initial conditions, and supplementary data, as well as public analysis tools with worked examples of how to use the data. To demonstrate the value and robustness of the simulation predictions, we analyse a series of low-redshift global properties that compare well with many observed scaling relations, such as the Tully–Fisher relation, the star-forming (SF) main sequence, and H  i gas fraction/disc thickness. Finally, we show that SF gas discs appear to build rotation and velocity dispersion rapidly for |$z\gtrsim 3$| before they 'settle' into ever-increasing rotation-dispersion ratios (⁠|$V/\sigma$|⁠). This evolution appears to be in rough agreement with some kinematic measurements from H |$\alpha$| observations, and demonstrates an application of how to utilize the released data. [ABSTRACT FROM AUTHOR]

This study focuses on gender disparities in defiance prison -infractions—an understudied and highly discretionary type of rule violation—which have important implications for individuals' prison experiences and outcomes. Using administrative data on a release population in a large western state (N = 23,818), we employed multilevel modeling techniques to test whether (1) women were more likely than men to receive defiance infractions; (2) whether women received a greater number of defiance infractions than men, and (3) whether the gender differences observed for defiance were unique from other types of infractions (e.g. any infraction, nonviolent, violent) net of individual- and prison unit-level controls. Results confirmed that defiance infractions are uniquely gendered, which subjects incarcerated women to harsh consequences for far less serious behavior than their male counterparts. Our work fills key gaps in the literature and contributes to recent policy reform efforts aimed at prison disciplinary reform. [ABSTRACT FROM AUTHOR]

In vitro-In vivo correlation (IVIVC) is a main focus of the pharmaceutical industry, academia and the regulatory sectors, as this is an effective modelling tool to predict drug product in vivo performance based on in vitro release data and serve as a surrogate for bioequivalence studies, significantly reducing the need for clinical studies. Till now, IVIVCs have not been successfully developed for in situ forming implants due to the significantly different in vitro and in vivo drug release profiles that are typically achieved for these dosage forms. This is not unexpected considering the unique complexity of the drug release mechanisms of these products. Using risperidone in situ forming implants as a model, the current work focuses on: 1) identification of critical attributes of in vitro release testing methods that may contribute to differences in in vitro and in vivo drug release from in situ forming implants; and 2) optimization of the in vitro release method, with the aim of developing Level A IVIVCs for risperidone implants. Dissolution methods based on a novel Teflon shape controlling adapter along with a water non-dissolvable glass fiber membrane (GF/F) instead of a water dissolvable PVA film (named as GF/F-Teflon adapter and PVA-Teflon adapter, respectively), and an in-house fabricated Glass slide adapter were used to investigate the impact of: the surface-to-volume ratio, water uptake ratio, phase separation rate (measured by NMP release in 24 h post injection in vitro or in vivo), and mechanical pressure on the drug release patterns. The surface-to-volume ratio and water uptake were shown to be more critical in vitro release testing method attributes compared to the phase separation rate and mechanical pressure. The Glass slide adapter-based dissolution method, which allowed for the formation of depots with bio-mimicking surface-to-volume ratios and sufficient water uptake, has the ability to generate bio-relevant degradation profiles as well as in vitro release profiles for risperidone implants. For the first time, a Level A IVIVC (rabbit model) has been successfully developed for in situ forming implants. Release data for implant formulations with slightly different PLGA molecular weights (MWs) were used to develop the IVIVC. The predictability of the model passed external validation using the reference listed drug (RLD), Perseris®. IVIVC could not be developed when formulations with different PLGA molar ratios of lactic acid to glycolic acid (L/G) were included. The present work provides a comprehensive understanding of the impact of the testing method attributes on drug release from in situ forming implants, which is a valuable practice for level A IVIVC development. [Display omitted] [ABSTRACT FROM AUTHOR]

The objective of this study is to create a nanoemulgel formulation of Ribociclib (RIBO), a highly selective inhibitor of CDK4/6 through the utilization of spontaneous emulsification method. An experimental investigation was conducted to construct pseudo-ternary phase diagram for the most favourable formulation utilizing rice bran oil, which is known for its diverse anticancer properties. The formulation consisted of varying combination of the surfactant and as the co-surfactant (Tween 80 and Transcutol, respectively) referred to as Smix and the trials were optimized to get the desired outcome. The nanoemulsion (NE) formulations that were developed exhibited a droplet size of 179.39 nm, accompanied with a PDI of 0.211. According to the data released by Opt-RIBO-NE, it can be inferred that the Higuchi model had the most favourable fit among many kinetics models considered. The results indicate that the use of nanogel preparations for the topical delivery of RIBO in breast cancer therapy, specifically RIBO-NE-G, is viable. This is supported by the extended release of the RIBO, and the appropriate level of drug permeation observed in Opt-RIBO-NE-G. Due to RIBO and Rice Bran oil, RIBO-NE-G had greater antioxidant activity, indicating its effectiveness as antioxidants. The stability of the RIBO-NE-G was observed over a period of three months, indicating a favourable shelf life. Therefore, this study proposes the utilization of an optimized formulation of RIBO-NE-G may enhance the efficacy of anticancer treatment and mitigate the occurrence of systemic side effects in breast cancer patients, as compared to the use of suspension preparation of RIBO. [ABSTRACT FROM AUTHOR]

In recent years, the explosion of extensive geolocated datasets related to human mobility has presented an opportunity to unravel the mechanism behind daily mobility patterns on an individual and population level; this analysis is essential for solving social matters, such as traffic forecasting, disease spreading, urban planning, and pollution. However, the release of such data is limited owing to the privacy concerns of users from whom data were collected. To overcome this challenge, an innovative approach has been introduced for generating synthetic human mobility, termed as the "Pseudo‐PFLOW" dataset. Our approach leverages open statistical data and a limited travel survey to create a comprehensive synthetic representation of human mobility. The Pseudo‐PFLOW generator comprises three agent models that follow seven fundamental daily activities and captures the spatiotemporal pattern in daily travel behaviors of individuals. The Pseudo‐PFLOW dataset covers the entire population in Japan, approximately 130 million people across 47 prefectures, and has been compared with the existing ground truth dataset. Our generated dataset successfully reconstructs key statistical properties, including hourly population distribution, trip volume, and trip coverage, with coefficient of determination values ranging from 0.5 to 0.98. This innovative approach enables researchers and policymakers to access valuable mobility data while addressing privacy concerns, offering new opportunities for informed decision‐making and analysis. [ABSTRACT FROM AUTHOR]

We present griz photometric light curves for the full 5 yr of the Dark Energy Survey Supernova (DES-SN) program, obtained with both forced point-spread function photometry on difference images (DiffImg) performed during survey operations, and scene modelling photometry (SMP) on search images processed after the survey. This release contains 31,636 DiffImg and 19,706 high-quality SMP light curves, the latter of which contain 1635 photometrically classified SNe that pass cosmology quality cuts. This sample spans the largest redshift (z) range ever covered by a single SN survey (0.1 < z < 1.13) and is the largest single sample from a single instrument of SNe ever used for cosmological constraints. We describe in detail the improvements made to obtain the final DES-SN photometry and provide a comparison to what was used in the 3 yr DES-SN spectroscopically confirmed Type Ia SN sample. We also include a comparative analysis of the performance of the SMP photometry with respect to the real-time DiffImg forced photometry and find that SMP photometry is more precise, more accurate, and less sensitive to the host-galaxy surface brightness anomaly. The public release of the light curves and ancillary data can be found at github.com/des-science/DES-SN5YR and doi: 10.5281/zenodo.12720777. [ABSTRACT FROM AUTHOR]

Objective: To investigate the impact of gut microbiota on osteoporosis and identify the mediating role of blood metabolites in this process. Methods: This two-sample Mendelian randomization (MR) study utilized summary level data from genome-wide association studies (GWAS). Gut microbiota GWAS data were obtained from the MiBio-Gen consortium metaanalysis (n=13,266), while osteoporosis summary statistics were sourced from the FinnGen consortium R9 release data (7300 cases and 358,014 controls). Metabolite data, including 1400 metabolites or metabolite ratios, were derived from a study involving 8,299 unrelated individuals. The primary MR method employed was the inverse variance weighted (IVW) method. Reverse MR analysis was conducted on bacteria causally associated with osteoporosis in forward MR. The gut microbiota with the smallest p-value was selected as the top influencing factor for subsequent mediation analysis. A two-step MR approach quantified the proportion of the blood metabolite effect on gut microbiota influencing osteoporosis. IVW and Egger methods were used to assess heterogeneity and horizontal pleiotropy. Results: IVW estimates indicated a suggestive effect of family Christensenellaceae on osteoporosis (odds ratio(OR) = 1.292, 95% confidence interval(CI): 1.110-1.503, P =9.198 × 10-4). Reverse MR analysis revealed no significant causal effect of osteoporosis on family Christensenellaceae (OR = 0.947, 95% CI: 0.836-1.072, P =0.386). The proportion of the effect of family Christensenellaceae on osteoporosis mediated by circulating levels of 3,4-dihydroxybutyrate was 9.727%. No significant heterogeneity or horizontal pleiotropy was detected in the instrumental variables used for MR analysis. Conclusion: This study establishes a causal link between family Christensenellaceae and osteoporosis, with a minor proportion of the effect mediated by elevated circulating levels of 3,4-dihydroxybutyrate. Further randomized controlled trials (RCTs) are warranted to validate this conclusion. [ABSTRACT FROM AUTHOR]

Despite increasing expectations that researchers and funding agencies release their data for reuse, concerns about data misuse hinder the open sharing of data. The COVID‐19 crisis brought urgency to these concerns, yet we are currently missing a theoretical framework to understand, prevent, and respond to research data misuse. In the article, we emphasize the challenge of defining misuse broadly and identify various forms that misuse can take, including methodological mistakes, unauthorized reuse, and intentional misrepresentation. We pay particular attention to underscoring the complexity of defining misuse, considering different epistemological perspectives and the evolving nature of scientific methodologies. We propose a theoretical framework grounded in the critical analysis of interdisciplinary literature on the topic of misusing research data, identifying similarities and differences in how data misuse is defined across a variety of fields, and propose a working definition of what it means “to misuse” research data. Finally, we speculate about possible curatorial interventions that data intermediaries can adopt to prevent or respond to instances of misuse. [ABSTRACT FROM AUTHOR]

In this paper, a semisupervised machining learning technique had been utilized to analyse low-resolution stellar spectra from Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) Data Release 9 (DR9). We identified approximately 111 000 potential very metal-poor stars. Estimation of their stellar parameters (⁠|$T_{\rm eff}$|⁠ , |${\rm log}\, \rm {g}$|⁠ , [Fe/H]) indicate that over 99 per cent are metal-poor ([Fe/H] < −1.0), comprising 32 631 very metal-poor ([Fe/H] < −2.0), 702 extremely metal-poor ([Fe/H] < −3.0) and 30 ultra metal-poor ([Fe/H] < −4.0) stars. Based on kinematic characteristics, stars were categorized into thick disc-like, thin disc-like, and halo-like groups. We analysed their metallicity distributions (MDs) with respect to vertical height (⁠|$|Z|$|⁠) and orbital eccentricity (e). Thick disc-like stars in current sample show a clear trend of decreasing metallicty with increasing |$|Z|$| or e for the ranges −3.0 |$\lt $| [Fe/H] |$\lt $| −1.2 and |$|Z|$| |$\lt $| 3 kpc. Conversely, thin disc-like stars in current sample exhibit a slight increase in the fraction of more metal-poor stars with |$|Z|$| for the ranges −3.0 |$\lt $| [Fe/H] |$\lt $| −1.2 and |$|Z|$| |$\lt$| 1 kpc, but no obvious correlation with e. Additionally, we confirmed the presence of two prominent substructures among halo-like stars. One exhibits a high eccentricity (⁠|$e\ \gt\ 0.8$|⁠) orbit and higher metallicity, while the other follows a retrograde orbit with moderate eccentricity (⁠|$e\sim 0.6$|⁠) and lower metallicity. We believe they are related to the merger events known as Gaia Sausage and Sequoia, respectively. Furthermore, our observations indicate that the Sequoia has lower eccentricity and metallicity compared to the Gaia Sausage. [ABSTRACT FROM AUTHOR]

The Discrete Source Classifier (DSC) provides probabilistic classification of sources in Gaia Data Release 3 (GDR3) using a Bayesian framework and a global prior. The DSC Combmod classifier in GDR3 achieved for the extragalactic classes (quasars and galaxies) a high completeness of 92%, but a low purity of 22% (all sky, all magnitudes) due to contamination from the far larger star class. However, these single metrics mask significant variation in performance with magnitude and sky position. Furthermore, a better combination of the individual classifiers that comprise Combmod is possible. Here we compute two-dimensional (2D) representations of the completeness and the purity as a function of Galactic latitude and source brightness, and also exclude the Magellanic Clouds where stellar contamination significantly reduces the purity. Reevaluated on a cleaner validation set and without introducing changes to the published GDR3 DSC probabilities themselves, we here achieve for Combmod average 2D completenesses of 92% and 95% and average 2D purities of 55% and 89% for the quasar and galaxy classes, respectively. Since the relative proportions of extragalactic objects to stars in Gaia is expected to vary significantly with brightness and latitude, we then introduce a new prior that is a continuous function of brightness and latitude, and compute new class probabilities from the GDR3 DSC component classifiers, Specmod and Allosmod. Contrary to expectations, this variable prior only improves the performance by a few percentage points, mostly at the faint end. Significant improvement, however, is obtained by a new additive combination of Specmod and Allosmod. This classifier, Combmod-α, achieves average 2D completenesses of 82% and 93% and average 2D purities of 79% and 93% for the quasar and galaxy classes, respectively, when using the global prior. Thus, we achieve a significant improvement in purity for a small loss of completeness. The improvement is most significant for faint quasars (G≥20) where the purity rises from 20% to 62%. [ABSTRACT FROM AUTHOR]

Context. Weak gravitational lensing offers a powerful method to investigate the projected matter density distribution within galaxy clusters, granting crucial insights into the broader landscape of dark matter on cluster scales. Aims. In this study, we make use of the large photometric galaxy cluster data set derived from the publicly available Third Data Release of the Kilo-Degree Survey, along with the associated shear signal. Our primary objective is to model the peculiar sharp transition in the cluster profile slope, that is what is commonly referred to as the splashback radius. The data set under scrutiny includes 6962 galaxy clusters, selected by AMICO (an optimised detection algorithm of galaxy clusters) on the KiDS-DR3 data, in the redshift range of 0.1 ≤ z ≤ 0.6, all observed at a signal-to-noise ratio greater than 3.5. Methods. Employing a comprehensive Bayesian analysis, we model the stacked excess surface mass density distribution of the clusters. We adopt a model from recent results on numerical simulations that capture the dynamics of both orbiting and infalling materials, separated by the region where the density profile slope undergoes a pronounced deepening. Results. We find that the adopted profile successfully characterizes the cluster masses, consistent with previous works, and models the deepening of the slope of the density profiles measured with weak-lensing data up to the outskirts. Moreover, we measure the splashback radius of galaxy clusters and show that its value is close to the radius within which the enclosed overdensity is 200 times the mean matter density of the Universe, while theoretical models predict a larger value consistent with a low accretion rate. This points to a potential bias of optically selected clusters preferentially characterized by a high density at small scales compared to a pure mass-selected cluster sample. [ABSTRACT FROM AUTHOR]

Aims. We use near-infrared, ground-based data from the VISTA Variables in the Via Lactea (VVV) survey to indirectly extend the astrometry provided by the Gaia catalog to objects in heavily extinct regions toward the Galactic bulge and plane that are beyond Gaia's reach. Methods. We made use of state-of-the-art techniques developed for high-precision astrometry and photometry with the Hubble Space Telescope to process the VVV data. We employed empirical, spatially variable, effective point spread functions and local transformations to mitigate the effects of systematic errors, like residual geometric distortion and image motion, and to improve measurements in crowded fields and for faint stars. We also anchored our astrometry to the absolute reference frame of Gaia Data Release 3. Results. We measure between 20 and 60 times more sources than Gaia in the region surrounding the Galactic center, obtaining a single-exposure precision of about 12 mas and a proper-motion precision of better than 1 mas yr−1 for bright, unsaturated sources. Our astrometry provides an extension of Gaia into the Galactic center. We publicly release the astro-photometric catalogs of the two VVV fields considered in this work, which contain a total of ~3.5 million sources. Our catalogs cover ~3 sq. deg, about 0.5% of the entire VVV survey area. [ABSTRACT FROM AUTHOR]

Context. The third data release of Gaia, in June 2022, included the first large sample of sparse photometric data for more than 150 000 Solar System objects (SSOs), mainly asteroids. Aims. The SSO photometric data can be processed to derive information on the physical properties for a large number of objects, including spin properties, surface photometric behaviour in a variety of illumination conditions, and overall shape. Methods. After selecting a set of 22 815 objects for which an adequate number of accurate photometric measurements had been obtained by Gaia, we applied the 'genetic' algorithm of photometric inversion developed by the Gaia Data Processing and Analysis Consortium to process SSO photometric data. Given the need to minimise the required data processing time, the algorithm was set to adopt a simple triaxial ellipsoid shape model. Results. Our results show that in spite of the limited variety of observing circumstances and the limited numbers of measurements per object at present (in the majority of cases no greater than 40 and still far from the number expected at the end of the mission of about 60–70), the proportion of correct determinations for the spin period among the observed targets is about 85%. This percentage is based on a comparison with reliable literature data following a moderate filtering procedure developed to remove dubious solutions. Conclusions. The analysis performed in this paper is important in the context of developing further improvements to the adopted data reduction procedure. This includes the possible development of better solution filtering procedures that take into account, for each object, the possible presence of multiple, equivalent spin period solutions that have not been systematically investigated in this preliminary application. [ABSTRACT FROM AUTHOR]

Aims. The Archives of Photographic PLates for Astronomical USE (APPLAUSE) project is aimed at digitising astronomical photographic plates from three major German plate collections, making them accessible through integration into the International Virtual Observatory (IVO). Methods. Photographic plates and related materials (logbooks, envelopes, etc.) were scanned with commercial flatbed scanners. Astrometric and photometric calibrations were carried out with the developed PyPlate software, using Gaίa EDR3 data as a reference. The APPLAUSE data publication complies with IVO standards. Results. The latest data release contains images and metadata from 27 plate collections from the partner institutes in Hamburg, Bamberg, and Potsdam, along with digitised archives provided by Tautenburg, Tartu, and Vatican observatories. Altogether, over two billion calibrated measurements extracted from about 70 000 direct photographic plates can readily be used to create long-term light curves. For instance, we constructed the historic light curve of the enigmatic dipping star KIC 8462852. We found no evidence of previously assumed variations on timescales of decades in our light curve. Potential uses of APPLAUSE images for transient sources can be appreciated by following the development of the nova shell of GK Per (1901) over time and the change in brightness of two extragalactic supernovae. The database holds about 10 000 spectral plates. We made use of objective prism plates to follow the temporal changes of Nova DN Gem through 1912 and 1913, highlighting an outburst in early 1913. [ABSTRACT FROM AUTHOR]

Context. Over recent decades, astronomy has entered the era of massive data and real-time surveys. This is improving the study of transient objects – although they still contain some of the most poorly understood phenomena in astrophysics, as it is inherently more difficult to obtain data to constrain the proposed models. Aims. In order to help detect these objects in their brightest state and build synergies with multi-wavelength real-time surveys, we have built a quasi-real time automatic transient detection system for the XMM-Newton pipeline: the Search for Transient Objects in New detections using Known Sources (STONKS) pipeline. Methods. STONKS detects long-term X-ray transient events by automatically comparing new XMM-Newton detections to any available archival X-ray data at this position, sending out an alert if the variability between observations (defined as the ratio between the maximum flux and the minimum flux or upper limit) is over 5. This required an initial careful cross-correlation and flux calibration of various X-ray catalogs from different observatories (XMM-Newton, Chandra, Swift, ROSAT, and eROSITA). A Bayesian framework was put into place to solve any ambiguous associations. We also systematically computed the XMM-Newton upper limits at the position of any X-ray source covered by the XMM-Newton observational footprint, even without any XMM-Newton counterpart. The behavior of STONKS was then tested on all 483 observations performed with imaging mode in 2021. Results. Over the 2021 testing run, STONKS provided a daily alert rate of 0.7−0.5+0.7 alerts per day, about 80% of them corresponding to serendipitous sources. Among the detected variable serendipitous sources, there are: several highly variable active galactic nuclei (AGNs) and flaring stars, as well as new X-ray binary and ultra-luminous X-ray source candidates, some of which are present here. STONKS also detected targeted tidal disruption events, ensuring its ability to detect other serendipitous events. As a byproduct of our method, the archival multi-instrument catalog contains about one million X-ray sources, with 15% of them involving several catalogs and 60% of them having XMM-Newton (pointed or slew) upper limits. Conclusions. STONKS demonstrates a great potential for revealing future serendipitous transient X-ray sources, providing the community with the ability to follow-up on these objects a few days after their detection with the goal of obtaining a better understanding of their nature. The underlying multi-instrument archival X-ray catalog will be made available to the community and kept up to date with future X-ray data releases. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a U-Net model of deep learning algorithms for reconstructions of the 3D peculiar velocity field, which simplifies the reconstruction process with enhanced precision. We test the adaptability of the U-Net model with simulation data under more realistic conditions, including the redshift space distortion effect and halo mass threshold. Our results show that the U-Net model outperforms the analytical method that runs under ideal conditions, with a 16% improvement in precision, 13% in residuals, 18% in correlation coefficient, and 27% in average coherence. The deep learning algorithm exhibits exceptional capacities to capture velocity features in nonlinear regions and substantially improve reconstruction precision in boundary regions. We then apply the U-Net model trained under Sloan Digital Sky Survey (SDSS) observational conditions to the SDSS Data Release 7 data for observational 3D peculiar velocity reconstructions. [ABSTRACT FROM AUTHOR]

Summary Recent proprietary large language models (LLMs), such as GPT-4, have achieved a milestone in tackling diverse challenges in the biomedical domain, ranging from multiple-choice questions to long-form generations. To address challenges that still cannot be handled with the encoded knowledge of LLMs, various retrieval-augmented generation (RAG) methods have been developed by searching documents from the knowledge corpus and appending them unconditionally or selectively to the input of LLMs for generation. However, when applying existing methods to different domain-specific problems, poor generalization becomes apparent, leading to fetching incorrect documents or making inaccurate judgments. In this paper, we introduce Self-BioRAG , a framework reliable for biomedical text that specializes in generating explanations, retrieving domain-specific documents, and self-reflecting generated responses. We utilize 84k filtered biomedical instruction sets to train Self-BioRAG that can assess its generated explanations with customized reflective tokens. Our work proves that domain-specific components, such as a retriever, domain-related document corpus, and instruction sets are necessary for adhering to domain-related instructions. Using three major medical question-answering benchmark datasets, experimental results of Self-BioRAG demonstrate significant performance gains by achieving a 7.2% absolute improvement on average over the state-of-the-art open-foundation model with a parameter size of 7B or less. Similarly, Self-BioRAG outperforms RAG by 8% Rouge-1 score in generating more proficient answers on two long-form question-answering benchmarks on average. Overall, we analyze that Self-BioRAG finds the clues in the question, retrieves relevant documents if needed, and understands how to answer with information from retrieved documents and encoded knowledge as a medical expert does. We release our data and code for training our framework components and model weights (7B and 13B) to enhance capabilities in biomedical and clinical domains. Availability and implementation Self-BioRAG is available at https://github.com/dmis-lab/self-biorag. [ABSTRACT FROM AUTHOR]

Privacy and utility are two important objectives to consider when releasing census data. However, these two objectives are often conflicting, as protecting privacy usually necessitates introducing noise into the data, which compromises data utility. Determining the appropriate level of privacy protection presents a significant challenge in the data release. Therefore, it is necessary to investigate the tradeoff between privacy and utility before making a final decision on the level of privacy protection. In this article, we propose a multiobjective optimization framework to generate multiple optimal solutions that satisfy the two objectives of privacy and utility, as well as to analyze the tradeoff between privacy and utility for decision‐making. This framework relocates individuals susceptible to revealing their identities to protect their privacy. We maximize the number of individuals relocated while maximizing the utility of the data after relocations. The proposed framework is tested using synthetic population data in Franklin County, Ohio. Our experimental results show that the framework can efficiently generate a collection of optimal solutions and can be used to effectively balance privacy and utility. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Abant Social Sciences / Abant Sosyal Bilimler Dergisi is the property of Journal of Abant Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We present extended point spread function (PSF) models for the Hyper Suprime-Cam Subaru Strategic Program Public Data Release 3 (HSC-SSP PDR3) in all g, r, i, Z , and Y -bands. Due to its 8.2 m primary mirror and long exposure periods, HSC combines deep images with wide-field coverage. Both properties make HSC one of the most suitable observing facilities for low-surface brightness (LSB) studies, which are particularly sensitive to the PSF. By applying a median stacking technique of point-like sources with different brightness, we show how to construct the HSC-SSP PDR3 PSF models to an extent of R ∼ 5.6 arcmin. These models are appropriate for the HSC-PDR3 intermediate-state data which do not have applied the final aggressive background subtraction. The intermediate-state data is especially stored for users interested in large extended objects, where our new PSFs provide them with a crucial tool to characterise LSB properties at large angles. We demonstrate that our HSC PSFs behave reasonably in two scenarios. In the first one, we generate 2D models of a bright star, showing no evidence of residual structures across the five bands. In the second scenario, we recreate the PSF-scattered light on mock images with special consideration of the effect of this additional flux on LSB measurements. Despite the well-behaved nature of the HSC-PDR3 PSFs, there is a non-negligible impact on the faint light present in the mock images. This impact could lead to incorrect LSB measurements if a proper star subtraction is not applied. The PSF models are publicly available to the astronomical community at github.com/luciagarate/HSC_PSFs (DOI: 10.5281/zenodo.11273118). [ABSTRACT FROM AUTHOR]

Background: Recent researches have increasingly indicated a strong correlation between the gut microbiota and chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Nevertheless, the impact of gut microbiota on CP/CPPS still requires further elucidation. Methods: Employing the summary statistics provided by the MiBioGen consortium, we executed a two-sample Mendelian randomization (MR) analysis. The study involved 18,340 participants and considered gut microbiota as the instrumental variable. Chronic prostatitis summary statistics, representing 500 cases and 208,308 controls, were extracted from the GWAS Catalog release data as the disease outcome. Various methods, including weighted inverse variance, MR-Egger and weighted median, were employed to assess how gut microbiota interact and correlate with CP/CPPS. Sensitivity analysis was used to eliminate heterogeneity and horizontal pleiotropy. Results: Our findings, primarily derived from the IVW approach, provided evidence for a causal link between five categories of gut microbiota and CP/CPPS. Resultantly, the genus Christensenellaceae (OR = 0.39, 95% CI 0.17–0.87, P = 0.02), genus Eisenbergiella (OR = 0.62, 95% CI 0.40–0.97, P = 0.04), genus Hungatella (OR = 0.49, 95% CI 0.28–0.85, P = 0.01) and genus Terrisporobacter (OR = 0.39, 95% CI 0.20–0.75, P = 0.00) exhibited a protective impact on CP/CPPS, while family Prevotellaceae (OR = 1.78, 95% CI 1.01–3.15, P = 0.05) had the opposite effect. No notable heterogeneity of instrumental variables or horizontal pleiotropy was detected. Conclusions: The findings of this study, which used a two-sample Mendelian randomization approach, indicate a causal link between gut microbiota and CP/CPPS. This could be valuable in offering fresh perspectives for additional mechanistic and clinical investigations of microbiota-related CP/CPPS. Nevertheless, additional randomized controlled trials are necessary for validation. [ABSTRACT FROM AUTHOR]

Mounting evidence shows overall insect abundances are in decline globally. Habitat loss, climate change, and pesticides have all been implicated, but their relative effects have never been evaluated in a comprehensive large-scale study. We harmonized 17 years of land use, climate, multiple classes of pesticides, and butterfly survey data across 81 counties in five states in the US Midwest. We find community-wide declines in total butterfly abundance and species richness to be most strongly associated with insecticides in general, and for butterfly species richness the use of neonicotinoid-treated seeds in particular. This included the abundance of the migratory monarch (Danaus plexippus), whose decline is the focus of intensive debate and public concern. Insect declines cannot be understood without comprehensive data on all putative drivers, and the 2015 cessation of neonicotinoid data releases in the US will impede future research. [ABSTRACT FROM AUTHOR]

We use the emulation framework CosmoPower to construct and publicly release neural network emulators of cosmological observables, including the cosmic microwave background (CMB) temperature and polarization power spectra, matter power spectrum, distance-redshift relation, baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) observables, and derived parameters. We train our emulators on Einstein–Boltzmann calculations obtained with high-precision numerical convergence settings, for a wide range of cosmological models including ΛCDM, w CDM, ΛCDM +  N eff, and ΛCDM + Σ m ν. Our CMB emulators are accurate to better than 0.5 per cent out to ℓ = 104, which is sufficient for Stage-IV data analysis, and our P (k) emulators reach the same accuracy level out to |$k=50 \, \, \mathrm{Mpc}^{-1}$|⁠ , which is sufficient for Stage-III data analysis. We release the emulators via an online repository (CosmoPower Organisation), which will be continually updated with additional extended cosmological models. Our emulators accelerate cosmological data analysis by orders of magnitude, enabling cosmological parameter extraction analyses, using current survey data, to be performed on a laptop. We validate our emulators by comparing them to class and camb and by reproducing cosmological parameter constraints derived from Planck TT, TE, EE, and CMB lensing data, as well as from the Atacama Cosmology Telescope Data Release 4 CMB data, Dark Energy Survey Year-1 galaxy lensing and clustering data, and Baryon Oscillation Spectroscopic Survey Data Release 12 BAO and RSD data. [ABSTRACT FROM AUTHOR]

We present the SARAO MeerKAT Galactic Plane Survey (SMGPS), a 1.3 GHz continuum survey of almost half of the Galactic Plane (251° ≤ l ≤ 358° and 2° ≤ l ≤ 61° at | b | ≤ |$1{_{.}^{\circ}}5$|⁠). SMGPS is the largest, most sensitive, and highest angular resolution 1 GHz survey of the plane yet carried out, with an angular resolution of 8 arcsec and a broad-band root-mean-square sensitivity of ∼10–20 μJy beam−1. Here, we describe the first publicly available data release from SMGPS which comprises data cubes of frequency-resolved images over 908–1656 MHz, power-law fits to the images, and broad-band zeroth moment integrated intensity images. A thorough assessment of the data quality and guidance for future usage of the data products are given. Finally, we discuss the tremendous potential of SMGPS by showcasing highlights of the Galactic and extragalactic science that it permits. These highlights include the discovery of a new population of non-thermal radio filaments; identification of new candidate supernova remnants, pulsar wind nebulae and planetary nebulae; improved radio/mid-infrared classification of rare luminous blue variables and discovery of associated extended radio nebulae; new radio stars identified by Bayesian cross-matching techniques; the realization that many of the largest radio-quiet Wide-field Infrared Survey Explorer (WISE) H  ii region candidates are not true H  ii regions; and a large sample of previously undiscovered background H  i galaxies in the Zone of Avoidance. [ABSTRACT FROM AUTHOR]

The Galactic disc is one of the main components of the Milky Way, which contributes most of the luminosity. Its structure is essential for understanding the formation and evolution of the Milky Way. Using 174 443 K-type dwarf stars observed by both Large Sky Area Multi-Object Fiber Spectroscopic Telescope and Gaia Data Release 3, we study the disc density profile in the local volume within 1200 pc. In the azimuthal dimension, we find strong asymmetric signal of the thin disc. The surface density and the scale height of the southern disc significantly change versus the azimuthal angle at the same Galactocentric distance R. Meanwhile, in the vertical dimension, the scale height of the northern disc has quite different trend than that of the southern one. The scale height of the southern disc shows a decreasing trend with ϕ ∼ −2.5°, and change to an increasing one with ϕ ∼ 5.0°. Meanwhile, the scale height of the northern disc has a consistently smaller increase. Finally, we divide the entire sample into three subsamples based on metallicity and all three subsamples show significant non-axisymmetric and north–south asymmetric signals in the Galactic disc. Furthermore, we find that the scale height of the metal-poor ([Fe/H] < −0.4 dex) subsample in the northern disc is greater than that of the metal-rich ([Fe/H] > −0.1 dex) subsample. However, in the southern disc, the scale height exhibits varying relationships across different metallicity slices. [ABSTRACT FROM AUTHOR]

This study examines price data for coworking spaces in the City of New York, between September and October 2020. The data were released by an online source (Datarade 2022). The results and data can be used in future research to examine reasons behind frequent price changes at coworking spaces. [ABSTRACT FROM AUTHOR]

Fox Insight is an online, longitudinal study of over 54,000 people with and without Parkinson's disease, facilitating discovery, validation, and reproducibility in Parkinson's disease research. The study administers routine longitudinal assessments, one-time questionnaires on an array of topics such as environmental exposure or COVID-19, plus genetic and microbiome data collection. Researchers can explore and download patient-reported outcomes data and Parkinson's disease related genetic variants upon completing a Data Use Agreement. The full genetic data set, including approximately 650,000 single nucleotide polymorphisms for over 10,000 participants, and the microbiome data set for over 650 participants, can be requested with a heightened level of access. Since the first Fox Insight data descriptor was published in 2020, the data captured has been extended significantly, so this paper supersedes the previous one. Since then, the number of participants has increased by more than 20,000; an additional 1,747,729 surveys were completed; 130 gigabytes of genetic data were released; responses from 16 new one-time surveys were collected; and, data from one additional sub-study was made available. [ABSTRACT FROM AUTHOR]