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Open educational resources (OER) are teaching, learning, or research resources that are offered freely to users in at least one form and that either reside in the public domain or have been released under an open copyright license that allows for its free use, reuse, modification, and sharing with attribution. Course marking (also called attributes, designations, tags, flags, labels) are specific, searchable attributes or designations that are applied to courses, allowing students to quickly identify important information to aid in their decision making and allow them to efficiently plan their academic careers. In 2022, the report, "Toward Convergence: Creating Clarity to Drive More Consistency in Understanding the Benefits and Costs of OER," introduced a set of principles and frameworks that provide guidance for states, systems, and institutions wanting to better understand the benefits of open educational resources (OER). MHEC led the national effort to produce the report, which details recommendations for consistently estimating the cost savings realized by students when a course uses OER compared to traditional course material. Realizing such analyses are not possible without accurate data on course materials, MHEC then led a national effort to create this report to highlight five steps critical for the development of an effective course marking process, providing committed stakeholders with a roadmap and set of recommendations to improve consistency and reliability for marking courses in college registration materials, so students know the costs and nature of such materials at the time they choose their classes. Consistency of course marking efforts across the United States contributes to the ability to aggregate data from many institutions and conduct studies of how OER saves students money and contributes to enhanced student outcomes.

Background: Deep learning (DL)-based organ segmentation is increasingly used in radiotherapy, yet voxel-wise DL uncertainty maps are rarely presented to clinicians. Purpose: This study assessed how DL-generated uncertainty maps impact radiation oncologists during manual correction of prostate radiotherapy DL segmentations. Methods: Two nnUNet models were trained by 10-fold cross-validation on 434 MRI-only prostate cancer cases to segment the prostate and rectum. Each model was evaluated on 35 independent cases. Voxel-wise uncertainty was calculated using the SoftMax standard deviation (n=10) and visualized as a color-coded map. Four oncologists performed segmentation in two steps: Step 1: Rated segmentation quality and confidence using Likert scales and edited DL segmentations without uncertainty maps. Step 2 ($\geq 4$ weeks later): Repeated step 1, but with uncertainty maps available. Segmentation time was recorded for both steps, and oncologists provided qualitative free-text feedback. Histogram analysis compared voxel edits across uncertainty levels. Results: DL segmentations showed high agreement with oncologist edits. Quality ratings varied: rectum segmentation ratings slightly decreased overall in step 2, while prostate ratings differed among oncologists. Confidence ratings also varied. Three oncologists reduced segmentation time with uncertainty maps, saving 1-2 minutes per case. Histogram analysis showed 50% fewer edits for step 2 in low-uncertainty areas. Conclusions: Presenting DL segmentation uncertainty information to radiation oncologists influences their decision-making, quality perception, and confidence in the DL segmentations. Low-uncertainty regions were edited less frequently, indicating increased trust in DL predictions. Uncertainty maps improve efficiency by reducing segmentation time and can be a valuable clinical tool, enhancing radiotherapy planning efficiency.

Social online games like Minecraft and Roblox have become increasingly integral to children's daily lives. Our study explores how children aged 8 to 13 create and customize avatars in these virtual environments. Through semi-structured interviews and gameplay observations with 48 participants, we investigate the motivations behind children's avatar-making. Our findings show that children's avatar creation is motivated by self-representation, experimenting with alter ego identities, fulfilling social needs, and improving in-game performance. In addition, designed monetization strategies play a role in shaping children's avatars. We identify the ''wardrobe effect,'' where children create multiple avatars but typically use only one favorite consistently. We discuss the impact of cultural consumerism and how social games can support children's identity exploration while balancing self-expression and social conformity. This work contributes to understanding how avatar shapes children's identity growth in social online games.

Recent years have seen a surge of interest in the community studying the effect of ultraviolet radiation environment, predominantly set by OB stars, on protoplanetary disc evolution and planet formation. This is important because a significant fraction of planetary systems, potentially including our own, formed in close proximity to OB stars. This is a rapidly developing field, with a broad range of observations across many regions recently obtained or recently scheduled. In this paper, stimulated by a series of workshops on the topic, we take stock of the current and upcoming observations. We discuss how the community can build on this recent success with future observations to make progress in answering the big questions of the field, with the broad goal of disentangling how external photoevaporation contributes to shaping the observed (exo)planet population. Both existing and future instruments offer numerous opportunities to make progress towards this goal., Comment: Submitted to the Open Journal of Astrophysics. Corresponding author Thomas Haworth

Human prosocial cooperation is essential for our collective health, education, and welfare. However, designing social systems to maintain or incentivize prosocial behavior is challenging because people can act selfishly to maximize personal gain. This complex and unpredictable aspect of human behavior makes it difficult for policymakers to foresee the implications of their designs. Recently, multi-agent LLM systems have shown remarkable capabilities in simulating human-like behavior, and replicating some human lab experiments. This paper studies how well multi-agent systems can simulate prosocial human behavior, such as that seen in the public goods game (PGG), and whether multi-agent systems can exhibit ``unbounded actions'' seen outside the lab in real world scenarios. We find that multi-agent LLM systems successfully replicate human behavior from lab experiments of the public goods game with three experimental treatments - priming, transparency, and varying endowments. Beyond replicating existing experiments, we find that multi-agent LLM systems can replicate the expected human behavior when combining experimental treatments, even if no previous study combined those specific treatments. Lastly, we find that multi-agent systems can exhibit a rich set of unbounded actions that people do in the real world outside of the lab -- such as collaborating and even cheating. In sum, these studies are steps towards a future where LLMs can be used to inform policy decisions that encourage people to act in a prosocial manner.

Despite its ubiquity in the workforce, spreadsheet programming remains challenging as programmers need both spreadsheet-specific knowledge (e.g., APIs to write formulas) and problem-solving skills to create complex spreadsheets. Large language models (LLMs) can help automate aspects of this process, and recent advances in planning and reasoning have enabled language agents, which dynamically plan, use tools, and take iterative actions to complete complex tasks. These agents observe, plan, and act, making them well-suited to scaffold spreadsheet programming by following expert processes. We present TableTalk, a language agent that helps programmers build spreadsheets conversationally. Its design reifies three design principles -- scaffolding, flexibility, and incrementality -- which we derived from two studies of seven programmers and 62 Excel templates. TableTalk structures spreadsheet development by generating step-by-step plans and suggesting three next steps users can choose from. It also integrates tools that enable incremental spreadsheet construction. A user study with 20 programmers shows that TableTalk produces spreadsheets 2.3 times more likely to be preferred over a baseline agent, while reducing cognitive load and time spent reasoning about spreadsheet actions by 12.6%. TableTalk's approach has implications for human-agent collaboration. This includes providing persistent direct manipulation interfaces for stopping or undoing agent actions, while ensuring that such interfaces for accepting actions can be deactivated.

JWST observations have uncovered a new population of red, compact objects at high redshifts dubbed 'Little Red Dots' (LRDs), which typically show broad emission lines and are thought to be dusty Active Galactic Nuclei (AGN). Some of their other features, however, challenge the AGN explanation, such as prominent Balmer breaks and extremely faint or even missing metal high-ionization lines, X-ray, or radio emission, including in deep stacks. Time variability is a unique test of AGN activity. Here, we exploit the $z=7.045$ multiply-imaged LRD A2744-QSO1, which offers a unique test of variability due to lensing-induced time delays between the three images spanning 22 yr (2.7 yr in the rest-frame), to investigate its photometric and spectroscopic variability. We find the equivalent widths (EWs) of the broad H$\alpha$ and H$\beta$ lines, which are independent of magnification and other systematics, to exhibit significant variations, up to $18\pm3$ % for H$\alpha$ and up to $22\pm8$ % in H$\beta$, on a timescale of 875 d (2.4 yr) in the rest-frame. This suggests that A2744-QSO1 is indeed an AGN. We find no significant photometric variability beyond the limiting systematic uncertainties, so it currently cannot be determined whether the EW variations are due to line-flux or continuum variability. These results are consistent with a typical damped random walk (DRW) variability model for an AGN like A2744-QSO1 ($M_{\mathrm{BH}}=4\times10^7 \mathrm{M}_{\odot}$) given the sparse sampling of the light-curve with the available data. Our results therefore support the AGN interpretation of this LRD, and highlight the need for further photometric and spectroscopic monitoring in order to build a detailed and reliable light-curve., Comment: Submitted to A&A. v2 updated to match the submitted version

Mainstream media, through their decisions on what to cover and how to frame the stories they cover, can mislead readers without using outright falsehoods. Therefore, it is crucial to have tools that expose these editorial choices underlying media bias. In this paper, we introduce the Media Bias Detector, a tool for researchers, journalists, and news consumers. By integrating large language models, we provide near real-time granular insights into the topics, tone, political lean, and facts of news articles aggregated to the publisher level. We assessed the tool's impact by interviewing 13 experts from journalism, communications, and political science, revealing key insights into usability and functionality, practical applications, and AI's role in powering media bias tools. We explored this in more depth with a follow-up survey of 150 news consumers. This work highlights opportunities for AI-driven tools that empower users to critically engage with media content, particularly in politically charged environments.

Accurate differentiation of pseudoprogression (PsP) from True Progression (TP) following radiotherapy (RT) in glioblastoma (GBM) patients is crucial for optimal treatment planning. However, this task remains challenging due to the overlapping imaging characteristics of PsP and TP. This study therefore proposes a multimodal deep-learning approach utilizing complementary information from routine anatomical MR images, clinical parameters, and RT treatment planning information for improved predictive accuracy. The approach utilizes a self-supervised Vision Transformer (ViT) to encode multi-sequence MR brain volumes to effectively capture both global and local context from the high dimensional input. The encoder is trained in a self-supervised upstream task on unlabeled glioma MRI datasets from the open BraTS2021, UPenn-GBM, and UCSF-PDGM datasets to generate compact, clinically relevant representations from FLAIR and T1 post-contrast sequences. These encoded MR inputs are then integrated with clinical data and RT treatment planning information through guided cross-modal attention, improving progression classification accuracy. This work was developed using two datasets from different centers: the Burdenko Glioblastoma Progression Dataset (n = 59) for training and validation, and the GlioCMV progression dataset from the University Hospital Erlangen (UKER) (n = 20) for testing. The proposed method achieved an AUC of 75.3%, outperforming the current state-of-the-art data-driven approaches. Importantly, the proposed approach relies on readily available anatomical MRI sequences, clinical data, and RT treatment planning information, enhancing its clinical feasibility. The proposed approach addresses the challenge of limited data availability for PsP and TP differentiation and could allow for improved clinical decision-making and optimized treatment plans for GBM patients.

Generative AI has gained a significant foothold in the creative and artistic sectors. In this context, the concept of creative work is influenced by discourses originating from technological stakeholders and mainstream media. The framing of narratives surrounding creativity and artistic production not only reflects a particular vision of culture but also actively contributes to shaping it. In this article, we review online media outlets and analyze the dominant narratives around AI's impact on creative work that they convey. We found that the discourse promotes creativity freed from its material realisation through human labor. The separation of the idea from its material conditions is achieved by automation, which is the driving force behind productive efficiency assessed as the reduction of time taken to produce. And the withdrawal of the skills typically required in the execution of the creative process is seen as a means for democratising creativity. This discourse tends to correspond to the dominant techno-positivist vision and to assert power over the creative economy and culture.

The distribution of chemical elements in the star-forming regions can store information on the chemical enrichment history of the galaxies. Negative metallicity gradients are expected in galaxies forming inside-out. However, observations show that the metallicity profiles can be broken. We aim to study the diversity of metallicity profiles that can arise in the current cosmological context and compare them with available observations. We also seek to identify the physical processes responsible for breaks in metallicity profiles by using two galaxies as case studies. We analyze central galaxies from the cosmological simulations of the CIELO project, within the stellar mass range [$10^{8.5}$, $10^{10.5}$] M$_\odot$ at $z=0$. A new algorithm, DB-A, was developed to fit multiple power laws to the metallicity profiles, enabling a flexible assessment of metallicity gradients in various galactic regions. The simulations include detailed modeling of gas, metal-dependent cooling, star formation, and supernova feedback. At $z=0$, we find diverse profile shapes, including inner and outer drops and rises, with some galaxies exhibiting double breaks. Gradient values align with observations. A temporal analysis of Local Group analogs shows inner and outer breaks occurring at all cosmic times, with outer breaks being more frequent. Metallicity gradients show high variability at high redshift, transitioning to mild evolution at lower redshift. Most inner breaks show central oxygen enhancement, linked to gas accretion and star formation. Inner drops result from disrupted gas due to feedback-driven outflows. Outer breaks with high metallicities arise from re-accreted material, extended star formation, and CGM-driven gas mixing. Outer drops are common at high redshift, linked to metal-poor gas accretion from cold flows. We highlight the complex interplay of these processes which often act together., Comment: 21 pages, 14 figures. Comments are welcome

Simulating human clients in mental health counseling is crucial for training and evaluating counselors (both human or simulated) in a scalable manner. Nevertheless, past research on client simulation did not focus on complex conversation tasks such as mental health counseling. In these tasks, the challenge is to ensure that the client's actions (i.e., interactions with the counselor) are consistent with with its stipulated profiles and negative behavior settings. In this paper, we propose a novel framework that supports consistent client simulation for mental health counseling. Our framework tracks the mental state of a simulated client, controls its state transitions, and generates for each state behaviors consistent with the client's motivation, beliefs, preferred plan to change, and receptivity. By varying the client profile and receptivity, we demonstrate that consistent simulated clients for different counseling scenarios can be effectively created. Both our automatic and expert evaluations on the generated counseling sessions also show that our client simulation method achieves higher consistency than previous methods.

We analyze Hubble Space Telescope (HST) optical imaging of eight low-mass galaxies hosting active galactic nuclei (AGN) identified via their photometric variability in \cite{baldassare_search_2020}. We use GALFIT to model the 2D galaxy light profiles, and find a diversity of morphologies. The galaxies with regular morphologies are best fit with pseudo-bulges and disks, rather than classical bulges. We estimate black hole masses using scaling relations and find black hole masses of 10$^{3.7-6.6}$ M$_\odot$. We compare this sample to dwarf galaxies with AGN selected via optical spectroscopy. On average, the variable host galaxies have lower mass black holes. We analyze the brightest point source in each galaxy and find their properties are not entirely consistent with star clusters, indicating that they are likely AGN. These point sources are found to have lower luminosities than spectroscopically selected dwarf AGN, but brighter than the point sources in dwarf galaxies not identified as AGN. Our detailed imaging analysis shows that variability selection has the potential to find lower mass black holes and lower luminosity AGN than optical spectroscopy. These active dwarfs may have been missed by spectroscopic searches due to star formation dilution or low gas content., Comment: 18 pages

ALMA observations have shown that candidate "post-starburst" galaxies (PSBs) at z$\sim$0.6 can retain significant molecular gas reservoirs. These results would imply that -- unlike many model predictions -- galaxies can shut down their star formation before their cold gas reservoirs are depleted. However, these studies inferred star formation rates (SFRs) either from [O II] line fluxes or from spectral energy distribution modeling, and could have missed large dust-obscured contributions to the SFRs. In this study, we present Keck/NIRES observations of 13 massive ($\mathrm{M_*}\gtrsim \times 10^{11} \,\, \mathrm{M_\odot}$) PSBs, which allow us to estimate $\mathrm{H\alpha}$ SFRs in these gas-rich post-starburst galaxies. We confirm the previously inferred low SFRs for the majority of the sample: 11/13 targets show clear $\mathrm{H\alpha}$ absorption, with minimal infilling indicating dust-corrected SFRs of $<4.1 \,\mathrm{M_\odot\, yr^{-1}}$. These SFRs are notably low given the large $\mathrm{H_2}$ reservoirs ($\sim 1-5 \times 10^{10} \,\, \mathrm{M_\odot}$) present in 5/13 of these galaxies, placing them significantly offset from star-forming galaxies on the Kennicutt-Schmidt relation for star-forming galaxies. The [N II]/H$\alpha$ ratios of all 13 PSBs imply contributions from non-star-forming ionization mechanisms (e.g., AGN, shocks, or hot evolved stars) to their $\mathrm{H\alpha}$ emission, suggesting that even these low ongoing SFRs may be overestimated. These low $\mathrm{H\alpha}$ SFRs, dust-corrected using A$_v$ estimates from SED fitting, confirm that these galaxies are very likely quiescent and, thus, that galaxies can quench before their cold gas reservoirs are fully depleted., Comment: 12 pages, 4 figures, 1 table. Accepted by the Astrophysical Journal (ApJ)

Systematic literature review is essential for evidence-based medicine, requiring comprehensive analysis of clinical trial publications. However, the application of artificial intelligence (AI) models for medical literature mining has been limited by insufficient training and evaluation across broad therapeutic areas and diverse tasks. Here, we present LEADS, an AI foundation model for study search, screening, and data extraction from medical literature. The model is trained on 633,759 instruction data points in LEADSInstruct, curated from 21,335 systematic reviews, 453,625 clinical trial publications, and 27,015 clinical trial registries. We showed that LEADS demonstrates consistent improvements over four cutting-edge generic large language models (LLMs) on six tasks. Furthermore, LEADS enhances expert workflows by providing supportive references following expert requests, streamlining processes while maintaining high-quality results. A study with 16 clinicians and medical researchers from 14 different institutions revealed that experts collaborating with LEADS achieved a recall of 0.81 compared to 0.77 experts working alone in study selection, with a time savings of 22.6%. In data extraction tasks, experts using LEADS achieved an accuracy of 0.85 versus 0.80 without using LEADS, alongside a 26.9% time savings. These findings highlight the potential of specialized medical literature foundation models to outperform generic models, delivering significant quality and efficiency benefits when integrated into expert workflows for medical literature mining.

For most galaxies in the cosmos, our knowledge of their motion is limited to line-of-sight velocities from redshift observations. Peculiar motions on the sky are only measured for a few cases. With increasingly detailed observations, the assumption that line-of-sight velocities suffice for an accurate and precise reconstruction of galaxy kinematics needs to be re-investigated and the impact of perpendicular velocities to be quantified. We analyse the motion of two galaxies with arbitrary velocities, determine their mutual velocity on an arbitrary background, and compare this general relative velocity to the one from line-of-sight components only. The latter are known as ``minor and major infall models'' established by Karachentsev and Kashibadze (2006). Our derivations reveal that the infall models approximate the radial velocity between two galaxies by two different projections employing different information about the system. For galaxies with small angular separations, all infall models agree that the radial velocity is the difference of their line-of-sight velocities. For larger angles, the minor infall model is mostly suitable when perpendicular velocity components are negligible and there is no information about the tangential velocity of the binary. The major infall model is best suitable when the motion is mainly radial and symmetry assumptions cancel the tangential and one perpendicular component. The latter often requires to transition from galaxy binaries to groups or clusters, as we show quantitatively. We give an encompassing overview how the infall models over- and under-estimate general binary or $N$-body motions. We quantify the impact of perpendicular velocity components, sparse sampling, and deviations of the tracer-galaxies from the motion in an embedding gravitational potential which are related to the angular momentum of the structure. (abridged), Comment: 6 pages, 4 figures; comments welcome!

Self-supervised deep learning has accelerated 2D natural image analysis but remains difficult to translate into 3D MRI, where data are scarce and pre-trained 2D backbones cannot capture volumetric context. We present a sequence-invariant self-supervised framework leveraging quantitative MRI (qMRI). By simulating multiple MRI contrasts from a single 3D qMRI scan and enforcing consistent representations across these contrasts, we learn anatomy-centric rather than sequence-specific features. This yields a robust 3D encoder that performs strongly across varied tasks and protocols. Experiments on healthy brain segmentation (IXI), stroke lesion segmentation (ARC), and MRI denoising show significant gains over baseline SSL approaches, especially in low-data settings (up to +8.3% Dice, +4.2 dB PSNR). Our model also generalises effectively to unseen sites, demonstrating potential for more scalable and clinically reliable volumetric analysis. All code and trained models are publicly available.

Effective debugging is a crucial aspect of software development, demanding problem-solving skills, expertise, and appropriate tools. Although previous research has studied expert developers' debugging strategies, the specific factors influencing strategy choice in complex scenarios remain underexplored. To investigate these contextual factors, we conducted two studies. First, we surveyed 35 developers to identify experiences with challenging debugging problems and contextual complexities. Second, we held semi-structured interviews with 16 experienced developers to gain deeper insight into strategic reasoning for complex debugging tasks. Insights from both groups enriched our understanding of debugging strategies at different expertise levels. We found that contextual factors interact in complex ways, and combinations of factors influence strategy choice, evolving throughout the debugging process. Hypothesis making is the baseline for debugging, with experience and code familiarity crucial for strategy selection. Our results show a gap between learning and effectively practicing strategies in challenging contexts, highlighting the need for carefully designed debugging tools and educational frameworks that align with problem contexts.

We present 450$\mu$m and 850$\mu$m James Clerk Maxwell Telescope (JCMT) observations of the Corona Australis (CrA) molecular cloud taken as part of the JCMT Gould Belt Legacy Survey (GBLS). We present a catalogue of 39 starless and protostellar sources, for which we determine source temperatures and masses using SCUBA-2 450$\mu$m/850$\mu$m flux density ratios for sources with reliable 450$\mu$m detections, and compare these to values determined using temperatures measured by the Herschel Gould Belt Survey (HGBS). In keeping with previous studies, we find that SCUBA-2 preferentially detects high-volume-density starless cores, which are most likely to be prestellar (gravitationally bound). We do not observe any anti-correlation between temperature and volume density in the starless cores in our sample. Finally, we combine our SCUBA-2 and Herschel data to perform SED fitting from 160-850$\mu$m across the central Coronet region, thereby measuring dust temperature $T$, dust emissivity index $\beta$ and column density $N({\rm H}_2)$ across the Coronet. We find that $\beta$ varies across the Coronet, particularly measuring $\beta = 1.55 \pm 0.35$ in the colder starless SMM-6 clump to the north of the B star R CrA. This relatively low value of $\beta$ is suggestive of the presence of large dust grains in SMM-6, even when considering the effects of $T-\beta$ fitting degeneracy and $^{12}$CO contamination of SCUBA-2 850$\mu$m data on the measured $\beta$ values., Comment: 27 pages, 18 figures, 4 tables. Accepted for publication in MNRAS

Gaze-based interaction techniques have created significant interest in the field of spatial interaction. Many of these methods require additional input modalities, such as hand gestures (e.g., gaze coupled with pinch). Those can be uncomfortable and difficult to perform in public or limited spaces, and pose challenges for users who are unable to execute pinch gestures. To address these aspects, we propose a novel, hands-free Gaze+Blink interaction technique that leverages the user's gaze and intentional eye blinks. This technique enables users to perform selections by executing intentional blinks. It facilitates continuous interactions, such as scrolling or drag-and-drop, through eye blinks coupled with head movements. So far, this concept has not been explored for hands-free spatial interaction techniques. We evaluated the performance and user experience (UX) of our Gaze+Blink method with two user studies and compared it with Gaze+Pinch in a realistic user interface setup featuring common menu interaction tasks. Study 1 demonstrated that while Gaze+Blink achieved comparable selection speeds, it was prone to accidental selections resulting from unintentional blinks. In Study 2 we explored an enhanced technique employing a deep learning algorithms for filtering out unintentional blinks.

The HALHF collaboration has discussed a new baseline for the project, taking into account comments from the accelerator community on various aspects of the original design. In particular, these concerned the practicality of the dual-purpose linac to accelerate both colliding positron bunches and the drive beams required for the plasma linac. In addition, many other aspects of the project were also considered; the discussion and conclusions are documented in this paper. Finally, a new baseline is outlined that has been optimised and addresses several weaknesses in the original design, has higher luminosity, reduced centre-of-mass energy boost and additional features such as positron polarization as well as electron polarization. Although HALHF has become longer and more expensive, it remains significantly smaller and cheaper than other mature Higgs factory designs currently under discussion., Comment: 32 pages, 13 figures, 2 tables

Galaxy clusters are currently the endpoint of the hierarchical structure formation; they form via the accretion of dark matter and cosmic gas from their local environment. In particular, filaments contribute grandly by accreting gas from cosmic matter sheets and underdense regions and feeding it to the galaxy clusters. Along the way, the gas in filaments is shocked and heated, which, together with the velocity structure within the filament, induces swirling and, thus, turbulence. In this work, we study a constrained hydrodynamical simulation replica of the Virgo cluster to characterise the velocity field in the two cosmic filaments connected to the cluster with unprecedented high resolution. First, we conduct a qualitative examination of slices extracted from the simulation. We study the temperature, the velocity field, and derived quantities in longitudinal cuts to study the general structure of the filaments and in transverse cuts to study their inner organisation and connection to cosmic matter sheets and underdense regions. Then, we conduct a quantitative study of velocities in Virgo's filaments by computing the 2D energy spectrum from 1 and 5~Mpc square maps extracted from the slices and centred on the core of the filaments. We show that the velocity field goes from mostly compressive far in the filaments to mostly solenoidal in Virgo's core. Moreover, we observe that the total energy spectrum in the filaments gains in amplitude and steepens towards Virgo., Comment: Submitted to A&A, 17 pages, 10 figures and 2 tables

Globular clusters (GCs) are some of the oldest bound structures in the Universe, holding clues to the earliest epochs of star formation and galaxy assembly. However, accurate age measurements of ancient clusters are challenging due to the age-metallicity degeneracy. Here, we report the discovery of 42 compact stellar systems within the 'Relic', a massive, quiescent galaxy at $z=2.53$. The Relic resides in an over-density behind the Abell 2744 cluster, with a prominent tidal tail extending towards two low-mass companions. Using deep data from the UNCOVER/MegaScience JWST Surveys, we find that clusters formed in age intervals ranging from 8 Myr up to $\sim2$ Gyr, suggesting a rich formation history starting at $z\sim10$. While the cluster-based star formation history is broadly consistent with the high past star formation rates derived from the diffuse host galaxy light, one potential discrepancy is a tentative $\sim2-3\times$ higher rate in the cluster population for the past Gyr. Taken together with the spatial distribution and low inferred metallicities of these young-to-intermediate age clusters, we may be seeing direct evidence for the accretion of star clusters in addition to their early in-situ formation. The cluster masses are high, $\sim10^6-10^7~M_{\odot}$, which may explain why we are able to detect them around this likely post-merger galaxy. Overall, the Relic clusters are consistent with being precursors of the most massive present-day GCs. This unique laboratory enables the first connection between long-lived, high-redshift clusters and local stellar populations, offering insights into the early stages of GC evolution and the broader processes of galaxy assembly., Comment: 19 pages, 7 figures, submitted to Astrophysical Journal on January 9, 2025 (comments welcome!)

Disk continuum reverberation mapping is one of the primary ways we learn about active galactic nuclei (AGN) accretion disks. Reverberation mapping assumes that time-varying X-rays incident on the accretion disk drive variability in UV-optical light curves emitted by AGN disks, and uses lags between X-ray and UV-optical variability on the light-crossing timescale to measure the radial temperature profile and extent of AGN disks. However, recent reverberation mapping campaigns have revealed oddities in some sources such as weakly correlated X-ray and UV light curves, longer than anticipated lags, and evidence of intrinsic variability from disk fluctuations. To understand how X-ray reverberation works with realistic accretion disk structures, we perform 3D multi-frequency radiation magnetohydrodynamic simulations of X-ray reprocessing by the UV-emitting region of an AGN disk using sophisticated opacity models that include line opacities for both the X-ray and UV radiation. We find there are two important factors that determine whether X-ray irradiation and UV emission will be well-correlated, the ratio of X-ray to UV luminosity and significant absorption. When these factors are met, the reprocessing of X-rays into UV is nearly instantaneous, as is often assumed, although linear reprocessing models are insufficient to fully capture X-ray reprocessing in our simulations. Nevertheless, we can still easily recover mock lags in our light curves using software that assumes linear reprocessing. Finally, the X-rays in our simulation heat the disk, increasing temperatures by a factor of 2--5 in the optically thin region, which could help explain the discrepancy between measured and anticipated lags., Comment: 14 pages, 6 figures, submitted to ApJ

This paper investigates the optimal use of the multilingual encoder model mDeBERTa for tasks in three Germanic languages -- German, Swedish, and Icelandic -- representing varying levels of presence and likely data quality in mDeBERTas pre-training data. We compare full fine-tuning with the parameter-efficient fine-tuning (PEFT) methods LoRA and Pfeiffer bottleneck adapters, finding that PEFT is more effective for the higher-resource language, German. However, results for Swedish and Icelandic are less consistent. We also observe differences between tasks: While PEFT tends to work better for question answering, full fine-tuning is preferable for named entity recognition. Inspired by previous research on modular approaches that combine task and language adapters, we evaluate the impact of adding PEFT modules trained on unstructured text, finding that this approach is not beneficial., Comment: Accepted at NoDaLiDa Baltic-HLT 2025 Conference

The CIELO project introduces a novel set of chemo-dynamical zoom-in simulations designed to simultaneously resolve galaxies and their nearby environments. The initial conditions include a diverse range of cosmic structures, such as local groups, filaments, voids, and walls, allowing for a detailed exploration of galaxies within the broader context of the cosmic web. This study presents the initial conditions and characterizes the global properties of CIELO galaxies and their environments. It focuses on galaxies with stellar masses ranging from log [8,11] solar masses and examines key scaling relations, including the mass-size relation, the Tully-Fisher relation, and the mass-metallicity relation for both stars and star-forming gas. The DisPerSe algorithm was used to determine the positions of CIELO galaxies within the cosmic web, with a specific focus on the Pehuen haloes. The selection of local group volumes was guided by criteria based on the relative positions and velocities of the two primary galaxies. The Pehuen regions were chosen to map walls, filaments, and voids. Synthetic images in the SDSS i, r, and g bands were generated using the SKIRT radiative transfer code. Additionally, a dynamical decomposition was performed to classify galaxy morphologies into bulge, disc, and stellar halo components (abridged)., Comment: 13 pages, 12 figures, submitted. Comments are welcomed

Student records, and specifically academic transcripts, are the traditional record of a student's completed coursework and their earned credential at an educational institution. Transcripts can serve as proof and a signal to potential employers and other educational institutions that a student has engaged in certain learning activities and obtained knowledge in given areas. Early in 2021, staff members from the Higher Learning Commission (HLC), the U.S. Department of Education and the regional compacts -- the Midwestern Higher Education Compact (MHEC), the New England Board of Higher Education (NEBHE), and the Western Interstate Commission for Higher Education (WICHE) -- met to discuss students' access to their records as a matter of student success. Three concerns were identified: student access to transcripts when there are financial or administrative holds placed on student accounts at institutions; access to student records when an institution closes; and the future of student records access. HLC and the regional compacts have continued to discuss and study the topic of transcript holds and closed school records. The issues surrounding transcript holds and closed school records have received ever greater attention in light of supporting student success since the pandemic. Because of the many ways the pandemic caused a re-thinking of business as usual, changes to transcript holds became a policy and process initiative at the federal, state, and institutional levels. The definition of student success for this paper includes enrolling in and completing a postsecondary education, transferring between institutions, earning licensure, securing employment, qualifying for military service, and other scenarios that vary by student. This paper provides an overview of student records issues, from an accreditor and regional compacts perspective. It includes recent legislative and policy actions at the federal and state levels as well as practitioner solutions and tools for institutions created by regional compacts, institutions, and other organizations. Resources are provided for those working at the institutional level as well as at the state or federal policy level to help students succeed.

The EdResearch for Action "Overview Series" summarizes the research on key topics to provide K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students. This overview brief discusses the central question: What is the evidence on strategies to build a sense of school connectedness and engagement among all students? Key insights are arranged in the following sections: (1) breaking down the issue; (2) evidence-based practices; and (3) practices to avoid. [The BARR Center and Network for College Success are additional collaborators for this report.]

We prove PSPACE-completeness of the well-studied pushing-block puzzle Push-1F, a theoretical abstraction of many video games (introduced in 1999). The proof also extends to Push-$k$ for any $k \ge 2$. We also prove PSPACE-completeness of two versions of the recently studied block-moving puzzle game with gravity, Block Dude - a video game dating back to 1994 - featuring either liftable blocks or pushable blocks. Two of our reductions are built on a new framework for "checkable" gadgets, extending the motion-planning-through-gadgets framework to support gadgets that can be misused, provided those misuses can be detected later., Comment: 35 pages, 40 figures. Presented at FUN 2022

The stellar haloes of dwarf galaxies are becoming an object of interest in the extragalactic community due to their detection in some recent observations. Additionally, new cosmological simulations of very high resolution were performed, allowing their study. These stellar haloes could help shed light on our understanding of the assembly of dwarf galaxies and their evolution, and allow us to test the hierarchical model for the formation of structures at small scales. We aim to characterise the stellar haloes of simulated dwarf galaxies and analyse their evolution and accretion history. We use a sample of 17 simulated galaxies from the Auriga Project with a stellar mass range from 3.28x10^8 Msun to 2.08x10^10 Msun. We define the stellar halo as the stellar material located outside an ellipsoid with semi-major axes equal to 4 times the half light radius (Rh) of each galaxy. We find that the inner regions of the stellar halo (4 to 6 times the Rh) are dominated by in-situ material. For the less massive simulated dwarfs (M*<=4.54x10^8 Msun), this dominance extends to all radii. We find that this in-situ stellar halo is mostly formed in the inner regions of the galaxies and then ejected into the outskirts during interactions and merger events. In ~50% of the galaxies, the stripped gas from satellites contributed to the formation of this in-situ halo. The stellar haloes of the galaxies more massive than M*>=1x10^9 Msun are dominated by the accreted component beyond 6 Rh. We find that the more massive dwarf galaxies accrete stellar material until later times (t90~4.44 Gyr ago, being t90 the formation time) than the less massive ones (t90~8.17 Gyr ago), impacting on the formation time of the accreted stellar haloes. The galaxies have a range of 1 to 7 significant progenitors contributing to their accreted component but there is no correlation between this quantity and the galaxies' accreted mass., Comment: Submitted to A&A. 21 pages, 1 table, 15 figures and 2 appendices

Smaller LLMs still face significant challenges even in medium-resourced languages, particularly when it comes to language-specific knowledge -- a problem not easily resolved with machine-translated data. In this case study on Icelandic, we aim to enhance the generation performance of an LLM by specialising it using unstructured text corpora. A key focus is on preventing interference with the models' capabilities of handling longer context during this adaptation. Through ablation studies using various parameter-efficient fine-tuning (PEFT) methods and setups, we find that increasing the number of trainable parameters leads to better and more robust language adaptation. LoRAs placed in the feed-forward layers and bottleneck adapters show promising results with sufficient parameters, while prefix tuning and (IA)3 are not suitable. Although improvements are consistent in 0-shot summarisation, some adapted models struggle with longer context lengths, an issue that can be mitigated by adapting only the final layers., Comment: To appear at NoDaLiDa 2025

Stellar halos around galaxies contain key information about their formation and assembly history. Using simulations, we can trace the origins of different stellar populations in these halos, contributing to our understanding of galaxy evolution. We aim to investigate the assembly of stellar halos and their chemical abundances in 28 galaxies from CIELO project with logMgal[9 and 11]Msun. Stellar halos were identified using the AM E method, focusing on the outer regions between the 1.5 optical radius and the virial radius. We divided the stellar populations based on their formation channel: exsitu, endodebris, and insitu, and analyzed their chemical abundances, ages, and spatial distributions. Additionally, we explored correlations between halo mass, metallicity, and alpha element enrichment. CIELO simulations reveal that stellar halos are predominantly composed of accreted material (exsitu and endodebris stars), in agreement with previous works. The mass fraction of these populations is independent of stellar halo mass, though their metallicities scale linearly with it. Exsitu stars tend to dominate the outskirts and be more alpha rich and older, while endodebris stars are more prevalent at lower radii and tend to be less alpha rich and slightly younger. Massive stellar halos require a median of five additional satellites to build 90 percent of their mass, compared to lower mass halos, which typically need fewer (median of 2.5) and lower-mass satellites and are assembled earlier. The diversity of accreted satellite histories results in well defined stellar halo mass metallicity and [alpha/Fe] [Fe/H] relations, offering a detailed view of the chemical evolution and assembly history of stellar halos. We find that the [alpha/Fe] [Fe/H] is more sensitive to the characteristics and star formation history of the contributing satellites than the stellar halo mass metallicity relationship, Comment: 16 pages, 14 figures, accepted for publication in A&A

Background: This protocol introduces an ultrasound (US) configuration for whole-body 3D dynamic contrast-enhanced ultrasound (DCE-US) imaging in preclinical applications. The set-up relies on a clinical abdominal matrix US probe to enable mice imaging beyond current preclinical systems that are generally unable to capture whole-body volumetric and dynamic imaging. We demonstrate via this protocol the feasibility of volumetric contrast-enhanced and molecular 3D imaging in the entire lower body of mouse, as well as the capability of imaging multiple lesions in the same animal simultaneously with a single contrast bolus injection. Methods: We modified a silicone cup with a 101.6 mm inner diameter and 6.4 mm wall thickness, to a height of 76.2 mm and cut out a rectangular side window (12.7 mm x 15.9 mm) at the lower part of the cup. Mice were positioned with their head and the two front legs outside of the cup while the rest of the body remained inside the cup and submerged under water; the edges around the mouse's body in contact with the cup's wall were sealed with Vaseline to prevent water leakage, and the cup was filled with warm water to maintain the mouse's body heat. Imaging was conducted using a portable clinical ultrasound system (EPIQ 7 Philips) with an abdominal matrix-array transducer (PM mode, X6-1) inserted into the top of the cup, and positioned to visualize the entire of the mouse's abdomen. The mice were imaged before and after the injection of P-selectin-targeted microbubbles. Results: Here, in nude mice with two adjacent tumors, we demonstrate that a commercially available clinical matrix transducer can be utilized to achieve whole-body 3D DCE-US and molecular US imaging, as well as capture independent qualitative and quantitative information from several lesions or organs at different locations in the animal, through a single bolus injection., Comment: 16 pages, 4 figures

We study the rest-frame optical and ultraviolet morphology of galaxies in the first billion years of the Universe. Using JWST data from the UNCOVER and MegaScience surveys targeting the lensing cluster Abell 2744 we present multi-band morphological measurements for a sample of 995 galaxies selected using 20-band NIRCam photometry and 35 using NIRSpec Prism spectroscopy over the redshift range of $4

We present a detailed exploration of the most optically-luminous Little Red Dot ($L_{H\alpha}=10^{44}$erg/s, $L_V=10^{45}$erg/s, F444W=22AB) found to date. Located in the Abell 2744 field, source A744-45924 was observed by NIRSpec/PRISM with ultradeep spectroscopy reaching SNR$\sim$100pix$^{-1}$, high-resolution 3-4 micron NIRCam/Grism spectroscopy, and NIRCam Medium Band imaging. The NIRCam spectra reveal high rest-frame EW $W_{H\alpha,0,broad}>800$\r{A}, broad H$\alpha$ emission (FWHM$\sim$4500 km/s), on top of narrow, complex absorption. NIRSpec data show exceptionally strong rest-frame UV to NIR Fe II emission ($W_{FeII-UV,0}\sim$340\r{A}), N IV]$\lambda\lambda$1483,1486 and N III]$\lambda$1750, and broad NIR O I $\lambda$8446 emission. The spectra unambiguously demonstrate a broad-line region associated with an inferred $M_{BH}\sim10^9M_\odot$ supermassive black hole embedded in dense gas, which might explain a non-detection in ultradeep Chandra X-ray data (>$10\times$ underluminous relative to broad $L_{H\alpha}$). Strong UV Nitrogen lines suggest supersolar N/O ratios due to rapid star formation or intense radiation near the AGN. The continuum shows a clear Balmer break at rest-frame 3650\r{A}, which cannot be accounted for by an AGN power-law alone. A stellar population model produces an excellent fit with a reddened Balmer break and implying a massive ($M_*\sim8\times10^{10}M_\odot$), old $\sim$500 Myr, compact stellar core, among the densest stellar systems known ($\rho\sim3\times10^6M_\odot$/pc$^2$ for $R_{e,opt}=70\pm10$ pc), and AGN emission with extreme intrinsic EW $W_{H\alpha,0}\gg$1000\r{A}. However, although high $M_*$ and $M_{BH}$ are supported by evidence of an overdensity containing 40 galaxies at $z=4.41-4.51$, deep high-resolution spectroscopy is required to confirm stellar absorption and rule out that dense gas around the AGN causes the Balmer break instead., Comment: 28 pages,10 figures, submitted to ApJ