Abstract
Context. Direct observations of exoplanet and brown dwarf companions with near-infrared interferometry, first enabled by the dualfield mode of VLTI/GRAVITY, provide unique measurements of the objects' orbital motions and atmospheric compositions. Aims. Here we compile a homogeneous library of all exoplanet and brown dwarf K-band spectra observed by GRAVITY thus far. This ExoGRAVITY Spectral Library is made publicly available online. Methods. We re-reduced all the available GRAVITY dual-field high-contrast data in a uniform and highly automated way and, where companions were detected, extracted their similar to 2.0-2.4 mu m K-band contrast spectra. We then derived stellar model atmospheres for all the employed flux references (either the host star or the swap calibrator), which we used to convert the companion contrast into companion flux spectra. Solely from the resulting GRAVITY K-band flux spectra, we extracted spectral types, spectral indices, and bulk physical properties for all the companions. Finally, and with the help of age constraints from the literature, we also derived isochronal masses for most of the companions using evolutionary models. Results. The resulting library contains R similar to 500 GRAVITY K-band spectra of 39 substellar companions from late M to late T spectral types, including the entire L-T transition. Throughout this transition, a shift from CO-dominated late M- and L-type dwarfs to CH4-dominated T-type dwarfs can be observed in the K-band. The GRAVITY spectra alone constrain the objects' bolometric luminosity to typically within +/- 0.15 dex. The derived isochronal masses agree with dynamical masses from the literature where available, except for HD 4113 c for which we confirm its previously reported potential underluminosity. Conclusions. Medium-resolution spectroscopy of substellar companions with GRAVITY provides insight into the carbon chemistry and the cloudiness of these objects' atmospheres. It also constrains these objects' bolometric luminosities, which can yield measurements of their formation entropy if combined with dynamical masses, for instance from Gaia and GRAVITY astrometry.

Abstract
Healthcare systems are complex adaptive environments in which clinical work, digital technologies, and organizational routines interact continuously, often challenging the integration of artificial intelligence (AI) into everyday practice. Although explainable AI (xAI) has been proposed to address concerns related to algorithmic opacity and professional trust, explainability is still frequently approached. Grounded in General Systems Theory, sociotechnical systems theory, and complexity science, this study conceptualizes explainability as an emergent system-level property of healthcare systems. Using Design Science Research as a systems-oriented inquiry methodology, a human-centered conceptual framework for AI-supported clinical decision-making was developed through iterative cycles of problem framing, design, demonstration, and evaluation. The framework was explored in rehabilitation nursing, a domain characterized by multidimensional patient data, longitudinal decision processes, and close professional-patient interaction. Iterative engagement with Rehabilitation Nursing Specialists informed design principles related to user participation, contextualized explanations, and workflow alignment. An exploratory evaluation with 144 Specialists assessed perceived usefulness, comprehensibility of explanations, and acceptance of AI-supported recommendations in realistic scenarios. The findings indicate that explainability is experienced not as a property of the algorithm alone, but as an outcome emerging from interactions between AI behavior, human interpretation, and organizational context. The framework shows potential to meaningfully support clinical decision-making in Rehabilitation Nursing by providing contextually aligned, human-centered explanatory outputs.

Abstract
This paper introduces JACABench, the JACA Benchmark Suite for embedded computing systems. JACABench is a C-based benchmark suite designed to complement existing evaluation frameworks. JACABench incorporates a set of features that support the systematic assessment of compilers, code transformations and optimizations, high-level synthesis (HLS) tools, hardware accelerators, and embedded computer architectures, as well as the impact of code variants on performance and energy consumption. For each benchmark, the suite provides multiple code variants that capture relevant dimensions, including alternative code transformations, data types, scenario-specific specializations, and configurable parameters. JACABench is conceived as a continuously evolving benchmark suite, with a particular emphasis on FPGA-based embedded computing. We present the initial set of benchmarks currently included in the suite and show the impact of selected code variants on FPGA implementations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.

Abstract
The Industry 5.0 concept guides the industry to the premise of sustainability, resilience and human-centric solutions. The last related pillar tries to create solutions to empower the people in production line processes since solutions should be designed to be easy to use and easy to learn without discarding the working people. In this regard, it's natural that robots become closer to humans in industrial applications where it is possible to absorb human-machine qualities. Robotic grasping has widespread application with a wide range of applicability. However, engineers and shop-floor operators spend time finding a fast response solution when the production demand changes. Aiming to create a tool to help this procedure in a human-centred fashion, the current paper proposes a programming-by-demonstration solution that is easy to use, reuse, adapt, and increment with its modular design.

Abstract
Context. The center of our Galaxy hosts Sagittarius A*, which is a supermassive compact object of similar to 4.3 & times; 10(6) solar masses and is usually associated with a black hole. Nevertheless, black holes possess a central singularity that is considered unphysical, and an event horizon that leads to loss of unitarity in a quantum description of the system. To address these theoretical inconsistencies, alternative models, collectively known as exotic compact objects, have been proposed. Aims. We investigate the potential detectability of signatures associated with nonrotating exotic compact objects (ECOs) within the dataset of Sgr A* polarized flares as observed through GRAVITY and the upcoming GRAVITY+. Methods. We examined a total of eight distinct metrics that originate from four different categories of static and spherically symmetric compact objects: black holes, boson stars, fluid spheres, and gravastars. Our approach involved using a toy model that orbits the compact object in the equatorial plane at the Schwarzschild-Keplerian velocity. Using simulated astrometric and polarimetric data with current GRAVITY uncertainties as well as improved flux uncertainties expected for the GRAVITY+ upgrade, we fit the datasets across all metrics we examined. We evaluated the detectability of the metric for each dataset based on the resulting chi(2)(red) and Bayesian information criteria-based Bayes factors. Results. Plunge-through images of ECOs affect polarization and astrometry in a distinguishable way from the spin of a Kerr black hole. With GRAVITY's current uncertainties, none of the metrics models are discernible. However, when the data are modeled within a compact boson star background, the corresponding best fit is sufficiently superior to the Kerr fit to rule out the latter. We examined the best expected enhanced flux uncertainties and discovered that a fourfold increase in flux sensitivity enables the detection of some of the exotic compact object models we investigated. The signals of the others are too close to each other to be distinguishable. However, with the GRAVITY+ flux uncertainties, when the data are produced using an ECO model, the best-fit ECO model is significantly preferred (with a BIC-based Bayes factor exceeding two) over the best fit in the Kerr metric, such that the latter can be ruled out. Nevertheless, enhancing the astrophysical complexity of the hot-spot model might diminishes these outcomes. Conclusions. With the improved sensitivity of GRAVITY+, we expect to be able to determine whether Sgr A* is a Kerr black hole or some form of exotic compact object, although we will not be able to identify the specific ECO models that describe Sgr A* best.

Abstract