Major depressive disorder (MDD) is often associated with deficits in executive function, but the long-term cognitive impact of specific depressive subtypes, in particular melancholic depression (MelD), is underexplored. This is the first prospective study aimed at exploring longitudinal associations between MelD and executive function in adult patients with MDD. This is a secondary analysis using data from a larger project with assessments at baseline, 6 and 12 months. MelD was identified using an algorithm derived from a subset of eight items from the Inventory of Depressive Symptomatology-Self Rated, which provides a standardized framework for the identification of this specific depressive subtype. Executive function was assessed using the Cambridge Neuropsychological Test Automated Battery. Longitudinal associations between MelD and executive function, including a global domain, four subdomains (working memory, planning, response inhibition and decision-making), and eight individual variables used to calculate the composite scores of the five (sub)domains, were analyzed using linear mixed-effects models adjusted for demographic and clinical variables and psychomotor speed. One hundred and five patients (20.95 % MelD) were analyzed at baseline, 73 (17.81 % MelD) at 6 months, and 61 (19.67 % MelD) at 12 months. MelD, older age and female sex were significantly associated with worse performance in the global executive function domain, in the working memory subdomain, and in four individual variables within the working memory, planning and decision-making subdomains, independent of other demographic and clinical variables and psychomotor speed. The findings highlight MelD as a distinct risk factor for worse long-term executive function in adult patients with MDD.

Advancements in AI for recognizing facial expressions of emotion rely heavily on the quality of underlying data. We present a comparative analysis of sequential databases for spontaneous (real) and posed (fake) facial expressions, introducing a modular, metric-based framework for evaluating data quality. This framework allows for flexible selection and weighting of metrics, making it adaptable to a wide range of research needs. Applied to 13 databases, it identifies key characteristics of an ideal data set, particularly for AI systems that distinguish between spontaneous and posed facial expressions. Our findings offer practical solutions to optimize data quality, laying a foundation for ensuring high-quality data in future emotion recognition research.

We have developed a virtual-reality pulsed laser laboratory for didactic training. Users can freely place and align optical elements and study their effect on ultrashort optical pulses in real time. We have created various tutorials that guide the user in a step-by-step fashion through the construction, alignment, and operation of optical setups. We illustrate the didactic concept and its implementation in our program through selected tutorials such as constructing a reflecting telescope or setting up an interferometer. We further demonstrate that we can teach pulse characterization methods such as spectral interferometry for direct electric-field reconstruction (SPIDER).

Platform organizations are pioneering the development and adoption of artificial intelligence (AI), yet AI poses substantial challenges by disrupting organizational capabilities and threatening competitive advantages. AI reshapes processes and products, influences ecosystem coordination, and foster inter-departmental collaboration. Recognizing its potential, businesses invest heavily in AI, but numerous applications fail to deliver significant value. Surprisingly, even though AI’s influence spans internal and external functions and capabilities, most studies focus on specific contexts and rarely examine the actual business outcomes of AI applications. This paper studies the empirical impact of AI on platform organizations’ value creation. Thus, we adopt a multi-study approach grounded in a Strategy-as-Practice perspective, investigating how AI integration transforms strategic practices. Study 1 draws on currently 45 interviews with platform organizations and develops a holistic framework that classifies AI applications according to their internal and external value creation and focus, enabling us to understand AI’s organizational impact on platform value-creation mechanisms. Study 2 will employ an event-study method and aims to assess the shareholder value impacts of these applications, empirically demonstrating AI’s business value. Preliminary insights from Study 1 indicate that platforms use AI to develop innovation platforms, introduce novel services, optimize ecosystem orchestration, and foster co-creation. By offering a holistic perspective on AI applications and empirically linking practices to shareholder value, this research contributes to both theory and practice. It clarifies how AI can function as a strategic capability within platform organizations, extending our understanding of micro-level strategic practices while guiding managers seeking to realize AI’s potential.

The discovery of the third interstellar object (ISO), 3I/ATLAS (`3I'), provides a rare chance to directly observe a small body from another Solar System. Studying its chemistry and dynamics will add to our understanding of how the processes of planetesimal formation and evolution happen across the Milky Way's disk, and how such objects respond to the Milky Way's potential. In this Letter, we present a first assessment of 3I in the context of the Ōtautahi-Oxford model, which uses data from Gaia in conjunction with models of protoplanetary disk chemistry and Galactic dynamics to predict the properties of the ISO population. The model shows that both the velocity and radiant of 3I are within the expected range. Its velocity suggests an origin within the Milky Way's thick disk, making it the first ISO from this population, and predicts a high water mass fraction, which may become observable shortly. We also conclude that it is very unlikely that 3I shares an origin with either of the previous two interstellar object detections.

The interstellar object 3I/ATLAS shows a weak cometary activity. Its brightness suggests a maximum radius of ~10km (A/0.05)^-1/2 for an asteroid with an albedo A. I show that interstellar objects with that radius would amount to an interstellar mass density that is well above the expected mass budget of interstellar comets or asteroids. Given this budget, the detection rate of objects like 3I/ATLAS implies that it is a comet with a small core radius <0.6km, or a member of a rare population with a number density <5x10^-8au^-3 for R>10km. The second possibility would suggest that the rare population of 3I/ATLAS objects favors plunging orbits towards the inner solar system to accommodate their inferred detection rate.

N6-methyladenosine (m(6)A) is the most abundant internal modification in mRNA and plays a crucial role in regulating mRNA turnover. This review explores the characteristics of m(6)A sites in the coding sequence (CDS) and their influence on mRNA decay, with a focus on the newly discovered CDS-m(6)A decay (CMD) pathway - a translation-dependent mechanism that promotes rapid and efficient degradation. Further, we examine how splicing-associated factors influence m(6)A deposition and discuss the enrichment of CMD targets in processing bodies (P-bodies). We emphasize the interplay between m(6)A modification and decay, and propose that targeting the CMD pathway could offer novel therapeutic strategies for diseases such as cancer and metabolic disorders.

Current advancements in the media landscape significantly impact adolescents’ development. Implementing media education in initial teacher education programs is essential for promoting pre-service teachers’ competence to foster their future students’ media literacy. In this study, we assess whether the objectives of a theory- and practice-based pedagogical concept to promote pre-service teachers’ media education competence have been reached. This represents the second iteration of a design-based research study, in which the first version of the pedagogical concept is further refined and implemented at a German university. In an empirical evaluation at pre- and post-intervention measurement points, a convenience sample of 38 pre-service teachers was presented with competence-based tasks. Responses were analyzed for differences in achieving media education competence based on the consideration of competence standards. Two consecutive levels of analysis were used, including a qualitative content analysis followed by a Wilcoxon signed-rank test. Findings indicate that participants showed significant improvements in referring to empirical findings related to adolescents’ media use, discussing theoretical approaches to media education, and evaluating these approaches and examples for media education activities from different perspectives. Based on these results, implications for further research on theory- and practice-based curriculum development in higher education are provided.

Digital technologies from the Internet and social media to artificial intelligence and robotics are reshaping the world. They offer joy, participation, and higher productivity, but they have also brought disruption, alienation, control, oppression, and exacerbated inequalities. This volume explores this ongoing transformation and its social implications between domination and participation. Outcomes at any given time are not taken as predetermined but as results of the decisions by a range of diverse social actors who compete, cooperate, or conflict with one another and can draw on differential access to resources within shifting political-legal frameworks and structural contexts. Scholars of communication, media studies, sociology, political ecology, employment and labor relations, science and technology come together to examine the social shaping of digital futures across different world regions and domains. Contributing to these fields, the volume highlights the merits of interdisciplinary research and transnational perspectives to illuminate the intricate complexity in which digital technologies are shaped by and are shaping social relations of power between domination and participation. The authors present critical case studies that make timely progress toward a deeper understanding of these new dynamics and toward broadening the horizon for imagining preferable democratic future alternatives.

A particularly well-studied evolutionary model is the vinegar fly Drosophila melanogaster, a cosmopolitan insect of ancestral southern-central African origin. Recent work suggests that it expanded out of Africa ∼9,000 years ago, and spread from the Middle East into Europe ∼1,800 years ago. During its global expansion, this human commensal adapted to novel climate zones and habitats. Despite much work on phenotypic differentiation and adaptation on several continents (especially North America and Australia), typically in the context of latitudinal clines, little is known about phenotypic divergence among European populations. Here, we sought to provide a continent-wide study of phenotypic differentiation among European populations of D. melanogaster. In a consortium-wide phenomics effort, we assayed 16 fitness-related traits on a panel of 173 isofemale lines from 9 European populations, with the majority of traits measured by several groups using semi-standardized protocols. For most fitness-related traits, we found significant differentiation among populations on a continental scale. Despite inevitable differences in assay conditions among labs, the reproducibility and hence robustness of our measurements were overall remarkably good. Several fitness components (e.g., viability, development time) exhibited significant latitudinal or longitudinal clines, and populations differed markedly in multivariate trait structure. Notably, populations experiencing higher humidity/rainfall and lower maximum temperature showed higher viability, fertility, starvation resistance, and lifespan at the expense of lower heat-shock survival, suggesting a pattern of local adaptation. Our results indicate that derived populations of this tropical fly have been shaped by pervasive spatially varying multivariate selection and adaptation to different climates on the European continent.

Transmission grid congestion management and outage planning are critical tasks in modern grid operation due to thenon-linear nature of power flows and the large-scale optimization challenges faced by operators. Traditionally, overloadsare addressed through generator redispatch, a costly and therefore suboptimal measure. In the project "Graph NeuralNetworks for Grid Control" (GNN4GC), we investigate alternative strategies, focusing on topological remedial actionsthat could minimize or even completely eliminate redispatch costs. Topology optimization, a core aspect of this project,presents significant challenges due to its combinatorial nature, requiring extensive computational resources for powerflow calculations. To address this, GNN4GC is split into three stages. In the first stage, we explore the use of GraphNeural Networks (GNNs) to accelerate these calculations and benchmark their performance against established tools likepandapower and a DC power flow solver developed by 50Hertz Transmission GmbH and TenneT TSO GmbH. In thesecond stage, we use Reinforcement Learning and other heuristics to select suitable topologies and solve the topologyoptimization problem. As a third stage, we test the respective agent on real-life grids to benchmark the methodology. Theaim of the final stage is to build a recommender system that can be used in a control room in the future.

Context. ESPRESSO guaranteed time observations (GTOs) at the 8.2m VLT telescope were performed to look for Earth-like exoplanets in the habitable zone of nearby stars. Barnard’s star is a primary target within the ESPRESSO GTO as it is the second closest neighbour to our Sun after the α Centauri stellar system. Aims. We present here a large set of 156 ESPRESSO observations of Barnard’s star carried out over four years with the goal of exploring periods of shorter than 50 days, thus including the habitable zone (HZ). Methods. Our analysis of ESPRESSO data using Gaussian process (GP) to model stellar activity suggests a long-term activity cycle at 3200 d and confirms stellar activity due to rotation at 140 d as the dominant source of radial velocity (RV) variations. These results are in agreement with findings based on publicly available HARPS, HARPS-N, and CARMENES data. ESPRESSO RVs do not support the existence of the previously reported candidate planet at 233 d. Results. After subtracting the GP model, ESPRESSO RVs reveal several short-period candidate planet signals at periods of 3.15 d, 4.12 d, 2.34 d, and 6.74 d. We confirm the 3.15 d signal as a sub-Earth mass planet, with a semi-amplitude of 55 ± 7 cm s −1 , leading to a planet minimum mass m p sin i of 0.37 ± 0.05 M ⊕ , which is about three times the mass of Mars. ESPRESSO RVs suggest the possible existence of a candidate system with four sub-Earth mass planets in circular orbits with semi-amplitudes from 20 to 47 cm s −1 , thus corresponding to minimum masses in the range of 0.17–0.32 M ⊕ . Conclusions. The sub-Earth mass planet at 3.1533 ± 0.0006 d is in a close-to circular orbit with a semi-major axis of 0.0229 ± 0.0003 AU, thus located inwards from the HZ of Barnard’s star, with an equilibrium temperature of 400 K. Additional ESPRESSO observations would be required to confirm that the other three candidate signals originate from a compact short-period planet system orbiting Barnard’s star inwards from its HZ.

The long-period comet C/1908 R1 (Morehouse) is distinguished by its early spectroscopic tail photography, which uncovered notably intense emission bands of N2+ and CO+ similar to the unusual characteristics of the atypical blue comet C/2016 R2 (Pan-STARRS). To probe potential parallels with C/2016 R2 further, we revisited the historical spectroscopic plates of C/1908 R1 while leveraging the New Astrometric Reduction of Old Observations (NAROO) project's advanced sub-micrometric scanner. We first reviewed the intensity ratio method, followed by a comprehensive spectroscopic analysis of the original historical plates to determine the comet's composition. Our analysis also encompassed an evaluation of C/1908 R1's dynamic trajectory using an N-body integrator and a detailed examination of tail morphology records. Our findings suggest that C/1908 R1 experienced no significant close encounters as it crossed the inner Solar System, anchoring its origins directly in the Oort Cloud and allowing us to ascertain that this was its inaugural voyage near the Sun. We determined a N2+ CO+ ratio of $ along with a dust-poor composition, particularities it shares with C/2016 R2. Moreover, by synthesizing observations of the tail's structure over the three-month period of visibility, we uncovered a link between tail dislocation events and aurora borealis sightings on Earth. This association underscores the comet tail’s heightened sensitivity to solar wind fluctuations due to its volatile makeup. The comet C/1908 R1 (Morehouse) emerges as one of the most unaltered relics of our Solar System's formation, offering another instance of a C/2016 R2-analogous comet. This underscores the importance of preserving and reexamining historical astronomical datasets, not only for historical significance but as a critical resource for contemporary scientific advancement.

The recently announced Oort-cloud comet C/2014 UN271 (Bernardinelli-Bernstein) is remarkable in at least three respects: (i) it was discovered inbound as far as textasciitilde29 au from the Sun (with prediscovery images up to \textasciitilde34 au); (ii) it showed cometary activity already at almost 24 au; and (iii) its nuclear magnitude (Hr \textasciitilde 8.0) indicates an exceptionally large object. Detection of gases is expected in the upcoming years as the comet is heading towards a textasciitilde11 au perihelion in 2031. We used ALMA in extended configuration (resolution \textasciitilde0.064") to measure the 1287 um (233 GHz) continuum flux of the comet. Observations were performed on August 8, 2021 at a 20.0 au distance from the Sun. The high spatial resolution was chosen in order to filter out any dust contribution. We detected the thermal emission of the object at textasciitilde10 sigma, with a flux of 0.128+/-0.012 mJy. Based on observational constraints and our theoretical estimates of the dust contribution, the entirety of the measured flux can be attributed to the nucleus. From NEATM modelling combined with the Hr magnitude, we determine a surface-equivalent diameter of 137+/-17 km and a red geometric albedo of 5.3+/-1.2 %. This confirms that 2014 UN271 is by far the largest Oort-cloud object ever found (almost twice as large as comet C/1995 O1 Hale-Bopp), and except for the Centaur 95P/Chiron which shows outburst-like activity, the largest known comet in the Solar System. On the other hand, the object albedo is typical of comets, adding credence for a "universal" comet nucleus albedo. With its distant perihelion and uniquely large size, 2014 UN271 is the prominent archetype of distant comets, whose activity is driven by hypervolatiles. Post-perihelion thermal measurements will permit to study possible albedo changes, such as a surface brightening compared to pre-perihelion, as was observed for Hale-Bopp.

We present a new method that views object detection as a direct set prediction problem. Our approach streamlines the detection pipeline, effectively removing the need for many hand-designed components like a non-maximum suppression procedure or anchor generation that explicitly encode our prior knowledge about the task. The main ingredients of the new framework, called DEtection TRansformer or DETR, are a set-based global loss that forces unique predictions via bipartite matching, and a transformer encoder-decoder architecture. Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. The new model is conceptually simple and does not require a specialized library, unlike many other modern detectors. DETR demonstrates accuracy and run-time performance on par with the well-established and highly-optimized Faster R-CNN baseline on the challenging COCO object detection dataset. Moreover, DETR can be easily generalized to produce panoptic segmentation in a unified manner. We show that it significantly outperforms competitive baselines. Training code and pretrained models are available at .

We provide a calculation of Pan-STARRS’ ability to detect objects similar to the interstellar object 1I/2017 U1 (hereafter ‘Oumuamua), including the most detectable approach vectors and the effect of object size on detection efficiency. Using our updated detection cross section, we infer an interstellar number density of such objects (). This translates to a mass density of that cannot be populated unless every star is contributing. We find that, given current models, such a number density cannot arise from the ejection of inner solar system material during planet formation. We note that a stellar system’s Oort cloud will be released after a star’s main-sequence life time and may provide enough material to obtain the observed density. The challenge is that Oort cloud bodies are icy and ‘Oumuamua was observed to be dry, which necessitates a crust-generation mechanism.

This paper introduces the motivation for and design of the Collaborative InterLingual Index (CILI). It is designed to make possible coordination between multiple loosely coupled wordnet projects. The structure of the CILI is based on the Interlingual index first proposed in the EuroWordNet project with several pragmatic extensions: an explicit open license, definitions in English and links to wordnets in the Global Wordnet Grid.