Search Results (65)

The variability of B-type stars offers valuable insights into the interiors of stars and the processes that drive pulsation and rotation in massive stars. In this study, we present the classification of the variability of 197 B-type stars observed in various Kepler/K2 campaigns, including 73 newly classified stars from Campaigns 13–18. For these stars, we derived atmospheric and evolutionary parameters using space-based photometry and ground-based spectroscopy. We obtained spectroscopic data for 34 targets with high-resolution instruments at OPD/LNA, which were supplemented by archival LAMOST spectra. After correcting for instrumental systematics, we analyzed the light curves using Fourier transforms and wavelet decomposition to identify both periodic and stochastic signals. The identified variability types included SPB stars, $\beta$ Cephei/SPB hybrids, fast-rotating pulsators, stochastic low-frequency variables, eclipsing binaries, and rotational variables. We also revised classifications of misidentified stars using Gaia astrometry, confirming the main-sequence nature of objects once considered subdwarfs. Our results indicate that hot-star variability exists along a continuum shaped by mass, rotation, and internal mixing rather than distinct instability domains. This study enhances our understanding of B-type star variability and supports future asteroseismic modeling with missions like PLATO. Full article

Resolved spectroscopic binaries (RSB) are the only way (besides trigonometric parallax) to determine the dynamical, hypothesis-free distances to the stars of the galaxy. Analyzing the most comprehensive up-to-date data on RSB, we found that trigonometric parallaxes of all distant ($d>\approx$ 0.5 kpc) binaries overestimate the distance by 10–50%. Such objects appear as single stars in Gaia and Hipparcos data, but their binarity can be detected/suspected by comparing trigonometric parallaxes in different data releases from these space missions. Full article

As urbanization processes are no longer characterized by simple linear expansion but exhibit leaping, edge-sparse, and discontinuous features, spatiotemporally continuous impervious surface coverage data are needed to better characterize urbanization processes. This study utilized GAIA impervious surface binary data and employed spatiotemporal aggregation methods to convert thirty years of 30 m resolution data into 1 km resolution spatiotemporal impervious surface coverage data, constructing a long-term time series annual impervious surface coverage dataset for the Beijing–Tianjin–Hebei region. Based on this dataset, we analyzed urban expansion processes and landscape pattern indices in the Beijing–Tianjin–Hebei region, exploring the spatiotemporal response relationships of ecological environment changes. Results revealed that the impervious surface area increased dramatically from 7579.3 km² in 1985 to 37,484.0 km² in 2020, representing a year-on-year growth of 88.5%. Urban expansion rates showed two distinct peaks: 800 km²/year around 1990 and approximately 1700 km²/year during 2010–2015. In high-density urbanized areas with impervious surfaces, the average forest area significantly increased from approximately 2500 km² to 7000 km² during 1985–2005 before rapidly declining, grassland patch fragmentation intensified, while in low-density areas, grassland area showed fluctuating decline with poor ecosystem stability. Furthermore, by incorporating natural and social factors such as Fractional Vegetation Coverage (FVC), Habitat Quality Index (HQI), Land Surface Temperature (LST), slope, and population density, we assessed the vulnerability of urbanization development in the Beijing–Tianjin–Hebei region. Results showed that high vulnerability areas (EVI > 0.5) in the Beijing–Tianjin core region continue to expand, while the proportion of low vulnerability areas (EVI < 0.25) in the northern mountainous regions decreased by 4.2% in 2020 compared to 2005. This study provides scientific support for the sustainable development of the Beijing–Tianjin–Hebei urban agglomeration, suggesting location-specific and differentiated regulation of urbanization processes to reduce ecological risks. Full article

Data spaces are increasingly recognized as a key enabler of secure, sovereign, and interoperable data exchange across manufacturing and supply chain networks. Despite growing institutional interest in Europe, academic research on this topic lacks a consolidated perspective. This study addresses this gap by combining a systematic literature review with an analysis of early insights from European initiatives to explore how data spaces are being conceptualized and implemented in industrial contexts. The review covers bibliometric trends and thematic content in the scientific literature, while also examining the structure and maturity of ongoing European projects. Results show a recent surge in scholarly interest, with early applications focusing primarily on resilience and sustainability. Practical initiatives are progressing toward implementation, supported by reference architectures like International Data Space and Gaia-X. The study concludes by outlining future research priorities, including the need for standardized design approaches and greater support for cross-sector collaboration. Full article

(1) Background: This study investigated seasonal variations in particulate matter (PM) ratios (PM₁/PM_2.5, PM_2.5/PM₁₀, and PM₁/PM₁₀) and their relationship with the meteorological conditions in Rio Grande, Brazil. (2) Methods: PM₁, PM_2.5, and PM₁₀ levels were collected using low-cost Gaia Air Quality Monitors, which measured PM concentrations at high temporal resolution. Meteorological variables, including atmospheric pressure, temperature, relative humidity, wind speed, and precipitation, were obtained from the National Institute of Meteorology (INMET). The data were analyzed through multiple linear regression to assess the influence of meteorological factors on PM ratios. (3) Results: The results show that the highest PM ratios occurred in winter, indicating a predominance of fine and ultrafine particles, while the lowest ratios were observed in spring and summer. Multiple linear regression analysis identified atmospheric pressure, wind speed, and maximum temperature as the key drivers of PM distribution. (4) Conclusions: This study highlights the importance of continuous monitoring of PM ratios, particularly PM₁, which remains underexplored in Brazil. The findings underscore the need for targeted air quality policies emphasizing seasonal mitigation strategies and improved pollution control to minimize the health risks associated with fine and ultrafine PM exposure. Full article

In this study, we utilized Gaia-DR3 astrometric data combined with the density-based spatial clustering of applications with noise (DBSCAN) algorithm to thoroughly investigate the dynamics and extra-tidal members of the open cluster NGC 6705. We determined more than 1900 cluster members within ∽12 pc of the cluster. We estimated the core and tidal radii to be 3.11 ± 0.21 arcmin (∽2 pc) and 20.02 ± 0.71 arcmin (∽13 pc), respectively, based on the cluster members. A Gaussian mixture model (GMM) was used to segregate the core and halo components of the cluster. The major and minor axes of the core and halo were determined through principal component analysis (PCA). The semi-major axis lengths of the core and halo were estimated to be $7^{\prime }$ (∽4.5 pc) and ${21}^{\prime }$ (∽13.6 pc), respectively. Additionally, the axis ratios of the core and halo were found to be e∽0.89 and e∽0.80, respectively, suggesting that the halo was significantly affected by the external tidal field. We detected a clear mass segregation effect within the cluster. Furthermore, we also detected some extra-tidal members around the cluster, implying that these stars are being lost from the cluster because of gravitational interactions with the Milky Way. This work provided a comprehensive characterization of NGC 6705, revealing its tighter structure, ongoing mass segregation, and potential star loss. Full article

Background: Assessing the real-world safety of preventive products against respiratory syncytial virus (RSV) in pregnant women holds significant public health implications, especially as vaccination programs become more widespread. This generic protocol describes a post-authorisation safety study (PASS) to evaluate the safety of RSV vaccination in pregnant women using a target trial emulation framework. Methods: This generic protocol, adapted from an ongoing PASS, is designed using the target trial emulation framework to evaluate the safety of an RSV vaccine in pregnant women. Emulating target trial conditions have the ability to minimise confounding and bias. In this pragmatic real-world observational study, RSV-vaccinated pregnant women are matched (1:N) with unexposed women based on gestational age, calendar time, maternal age, immunocompromised status, and high-risk pregnancy. Key adverse outcomes include preterm birth, stillbirth, hypertensive disorders of pregnancy, Guillain-Barré Syndrome (GBS), low birth weight (LBW), and small for gestational age (SGA). Future studies may add additional outcomes per vaccine risk profile and Global Alignment of Immunization safety Assessment (GAIA) recommendations. Distinguishing outcomes measured during pregnancy from those assessed at or after birth is crucial for analysis and interpretation. Conclusions: This protocol offers a structured approach to evaluating the safety of RSV vaccines in pregnant women. It aims to guide researchers in designing studies and should be adapted to specific settings and data availability. Full article

AS 314 (V452 Sct) is a poorly studied early-type emission-line star, which exhibits an infrared excess at wavelengths longer than 10 $\mathsf{\mu }$m. Its earlier studies have been limited to small amounts of observational data and led to controversial conclusions about its fundamental parameters and evolutionary status. Comparison of high-resolution spectra of AS 314 taken over 20 years ago with those of Luminous Blue Variables and other high-luminosity objects suggested its observed properties can be explained by a strong stellar wind from a distant (D∼10 kpc) massive star, possibly in a binary system. However, a recent assessment of its low-resolution spectrum along with a new distance from a Gaia parallax (∼1.6 kpc) resulted in an alternative hypothesis that AS 314 is a low-mass post-asymptotic giant branch (post-AGB) star. The latter hypothesis ignored the high-resolution data, which gave rise to the former explanation. We collected over 30 mostly high-resolution spectra taken in 1997–2023, supplemented them with results of long-term photometric surveys, compared the spectra and the spectral energy distribution with those of post-AGB objects and B/A supergiants, and concluded that the observed properties AS 314 are more consistent with those of the latter. Full article

The aim of the analysis of data from the Gaia Space Observatory is to obtain kinematic parameters of the collective motion of stars in a part of our galaxy. This research is based on a statistical analysis of the motion of $55,038,539$ stars selected in different directions from the Sun up to a distance of 3–6 kpc. We developed statistical methods for the analysis working with input data represented by the full astrometric solution (five parameters). Using the proposed statistical methods, we obtained the local velocity of the Sun $\left(U_{\odot },V_{\odot },W_{\odot }\right)=(9.58,16.25,7.33)\pm {(0.05,0.04,0.02)}_{stat}\pm {(0.7,0.9,0.1)}_{syst}$ km/s and the rotation velocity of the galaxy at different radii. For the Sun’s orbit radius, we obtained the velocity of the galaxy rotation$V_c\approx 234\pm 4$ km/s. Collective rotation slows down in the region under study linearly with distance from the disk plane: $\Delta V/\Delta Z\cong 33.5\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{kpc}}^{-1}$. We showed that the different kinematic characteristics and distributions, which depend on the position in the galaxy, can be well described in the studied 3D region by a simple Monte Carlo simulation model, representing an axisymmetric approximation of the galaxy kinematics. The optimal values of the six free parameters were tuned by comparison with the data. Full article

Over the past two decades, our understanding of star formation has undergone a major shift, driven by a wealth of data from infrared, submillimeter and radio surveys. The emerging view depicts star formation as a hierarchical process, which predominantly occurs along filamentary structures in the interstellar medium. These structures span a wide range of spatial scales, ultimately leading to the birth of young stars, which distribute in small groups, clusters and OB associations. Given the inherently complex and dynamic nature of star formation, a comprehensive understanding of these processes can only be achieved by examining their end products—namely, the distribution and properties of young stellar populations. In the Gaia era, the nearby OB associations are now characterised with unprecedented detail, allowing for a robust understanding of their formation histories. Nevertheless, to fully grasp the mechanisms of star formation and its typical scale, it is essential to study the much larger associations, which constitute the backbones of spiral arms. The large catalogues of young open clusters that have emerged from Gaia DR3 offer a valuable resource for investigating star formation on larger spatial scales. While the cluster parameters listed in these catalogues are still subject to many uncertainties and systematic errors, ongoing improvements in data analysis and upcoming Gaia releases promise to enhance the accuracy and reliability of these measurements. This review aims to provide a comprehensive summary of recent advancements and a critical assessment of the datasets available. Full article

Planetary nebulae (PNe) are the ejected gas and dust shells of evolved low- and intermediate-mass stars (LIMSs). We present an abundance comparison between PNe and their progenitors to reveal their similarities and differences since such a comparison has rarely, and not recently, been performed in the Milky Way. The dynamical expulsion of the outer envelope of an evolved LIMS produces the PN. We expected similarities in most $\alpha$-element distributions across the stellar and nebular populations, given that these elements are only marginally produced and destroyed during the LIMS evolution. Differences found in the Fe and S abundances allow us to determine their depletion due to grain condensation in the post-AGB phases. Differences in N and C between PNe and their progenitors set new limits to the low- and intermediate-mass star contributions to these elements. Finally, radial metallicity gradients from evolved LIMS and PNe and Gaia-calibrated distances constrain Galactic evolution in the framework of the current chemical evolutionary models. We found the following: (1) Gas-phase iron is significantly depleted in PNe compared to their progenitor stars, with an average depletion factor of <D[Fe/H]> = 1.74 ± 0.49. (2) Sulfur is also depleted in PNe, though to a much lesser extent than iron. (3) The median enrichment levels for carbon and nitrogen relative to the median stellar population of the same metallicity are approximately [C/H] ∼ +0.3 and [N/H] ∼ +0.4, respectively. PNe with progenitors that experienced hot-bottom burning (HBB) exhibit extreme nitrogen enrichment. (4) With the data available to date, the radial metallicity gradient derived from evolved LIMSs and PNe are compatible within the uncertainties. Full article

Gaia-X, a European initiative, aims to create a digital sovereignty framework for service ecosystems in the future Internet. Its applicability to the health domain was explored in the Gaia-X-Med project, which aimed to establish a common dataspace for various medical use cases based on Gaia-X principles. This paper presents a trust- and consent-based approach to the secure authentication and digital contract negotiation central to this endeavor and discusses the challenges that arose during the adoption of the Gaia-X framework, particularly relating to the strict requirements of the European healthcare domain with regards to privacy and consent regulations. By exploring the practical implications of Gaia-X in the healthcare context, this paper aims to contribute to the ongoing discussions surrounding the digital sovereignty of both citizens and corporations, as well as its realization via future Internet technologies. Full article

Estimating evapotranspiration is crucial for irrigation and agricultural applications. Although the FAO-56 Penman–Monteith method is highly accurate under conditions of abundant data, its extensive requirements limit its practical application. In the Mediterranean region, most empirical formulas used to estimate evapotranspiration are temperature-based and require calibration to be effective. The current study aims to introduce a novel formula to determine reference evapotranspiration using temperature, relative humidity, and extraterrestrial radiation daily in the Mediterranean region and evaluate its performance. Multi-linear regression was applied to agrometeorological data from the California Irrigation Management Information System (CIMIS) to develop the ETo formula. The formula was then validated using data from 252 stations in four countries (Greece, Spain, Portugal, and Cyprus) over the growing period of six years (2018–2023). The GAIA formula consistently outperformed formulas with the same or fewer variables, including Berti and Ahooghalaandari, across all metrics. The largest differences were observed in RMSE and the index of agreement. There is a strong correlation between GAIA and the FAO-56 Penman–Monteith formula (coefficient of determination = 0.88). While the GAIA formula shows a high coefficient of determination, its performance is somewhat lower than that of Copais and Valiatzas, particularly in terms of Pearson correlation and the coefficient of determination. A key difference is that Copais and Valiatzas rely on incoming solar radiation, whereas GAIA uses extraterrestrial radiation. Relative humidity was found to be the most influential variable, accounting for over 71% of the variance in ETo. Effective evapotranspiration (ETo) calculation methodologies, especially in areas with limited agrometeorological data, can significantly enhance irrigation system efficiency and promote sustainable water management. The GAIA formula offers a cost-effective method for estimating reference evapotranspiration (ETo) during the growing season with enhanced accuracy, eliminating the need for expensive equipment. However, its primary limitation is that it is validated in the Mediterranean region and within a specific geographical latitude range. Full article

This study addresses the need for enhanced sustainability in the nonwovens industry by developing a data ecosystem that improves data transparency, interoperability, and decision-making across the value chain. The research focuses on two conceptual models, including the Digital Product Passport (DPP) for tracking sustainability information and a holistic data management system for production environments. The research involved identifying key stakeholders, their tasks, and challenges related to sustainability and applying digital tools to meet these needs. The results demonstrate that integrating these data-space use cases can significantly enhance the availability and verifiability of sustainability data, aligning with European Union objectives such as those in the Gaia-X initiative. However, the proposed concepts have not yet been validated in real-world settings, highlighting the need for further research to assess their effectiveness and scalability. These findings suggest that digital ecosystems have the potential to drive sustainable transformation and foster collaboration in the nonwovens sector, offering a pathway towards more circular and resource-efficient practices. Full article

The recent astrometric data of hundreds of millions of stars from Gaia DR3 has allowed for a precise determination of the Milky Way rotation curve up to 28 kpc. The data suggest a rapid decline in the density of dark matter beyond 19 kpc. We fit the whole rotation curve with four components (gas, disk, bulge, and halo), and compute the microlensing optical depth to the Large Magellanic Cloud. With this model of the galaxy we reanalyse the microlensing events of the MACHO and EROS-2 Collaborations. Using the published MACHO efficiency function for the duration of their survey, together with the rate of expected events according to the new density profile, we find that the Dark Matter halo could be composed of up to 20% of massive compact halo objects for any mass between $0.001$ to $1M_{\odot }$. For the EROS-2 survey, using a modified efficiency curve for consistency with the MACHO analysis, we also find compatibility with a MACHO halo, but with a tighter constraint around $0.005M_{\odot }$ where the halo fraction cannot be larger than ∼10%. This result assumes that all the lenses have the same mass. If these were distributed in an extended mass function like that of the Thermal History Model, the constraints are weakened, allowing 100% of all DM in the form of Primordial Black Holes. Full article