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Colleges face growing pressures to maintain or enhance the quality of what they offer while being challenged to meet the needs of an increasingly diverse range of students. Staff in higher education face the challenge of supporting students to feel they belong and are valued. The co-creation of teaching and learning is one model in which we may be able to meet these challenges. The purpose of this study was to describe the process, benefits, and challenges of co-creating teaching and learning experiences in one college classroom from the perspectives of both teachers and students. A qualitative research methodology was used to explore and describe the implementation of a co-created curriculum model in a college classroom. Ethnographic field notes of the researcher's reflections on implementing a co-created curriculum were collected in narrative form, and data from students' perspectives were collected using open-ended survey questions. This study found that co-creating teaching and learning experiences in a college classroom included the process and preparation of implementing the model. Similar to previous research, this study's results show the benefits of autonomy, gaining experience and skills, motivation and engagement, and challenges that fall under the categories of resistance and institutional norms and practices. Implications for practice from this study include implications for both students and faculty. Implementing a co-created teaching and learning model allows for greater collaboration and engagement for students and faculty and develops a stronger sense of community in the classroom.

One of the outstanding goals of the planetary science community is to measure the present-day atmospheric composition of planets and link this back to formation. As giant planets are formed by accreting gas, ices, and rocks, constraining the relative amounts of these components is critical to understand their formation and evolution. For most known planets, including the Solar System giants, this is difficult as they reside in a temperature regime where only volatile elements (e.g., C, O) can be measured, while refractories (e.g., Fe, Ni) are condensed to deep layers of the atmosphere where they cannot be remotely probed. With temperatures allowing for even rock-forming elements to be in the gas phase, ultra-hot Jupiter atmospheres provide a unique opportunity to simultaneously probe the volatile and refractory content of giant planets. Here we directly measure and obtain bounded constraints on the abundances of volatile C and O as well as refractory Fe and Ni on the ultra-hot giant exoplanet WASP-121b. We find that ice-forming elements are comparatively enriched relative to rock-forming elements, potentially indicating that WASP-121b formed in a volatile-rich environment much farther away from the star than where it is currently located. The simultaneous constraint of ice and rock elements in the atmosphere of WASP-121b provides insights into the composition of giant planets otherwise unattainable from Solar System observations., Comment: 24 pages, 9 figures, 2 tables, Accepted for publication in The Astronomical Journal

A primary goal of exoplanet science is to measure the atmospheric composition of gas giants in order to infer their formation and migration histories. Common diagnostics for planet formation are the atmospheric metallicity ([M/H]) and the carbon-to-oxygen (C/O) ratio as measured through transit or emission spectroscopy. The C/O ratio in particular can be used to approximately place a planet's initial formation radius from the stellar host, but a given C/O ratio may not be unique to formation location. This degeneracy can be broken by combining measurements of both the C/O ratio and the atmospheric refractory-to-volatile ratio. We report the measurement of both quantities for the atmosphere of the canonical ultra hot Jupiter WASP-121 b using the high resolution (R=45,000) IGRINS instrument on Gemini South. Probing the planet's direct thermal emission in both pre- and post-secondary eclipse orbital phases, we infer that WASP-121 b has a significantly super-stellar C/O ratio of 0.70$^{+0.07}_{-0.10}$ and a moderately super-stellar refractory-to-volatile ratio at 3.83$^{+3.62}_{-1.67} \times$ stellar. This combination is most consistent with formation between the soot line and H$_2$O snow line, but we cannot rule out formation between the H$_2$O and CO snow lines or beyond the CO snow line. We also measure velocity offsets between H$_2$O, CO, and OH, potentially an effect of chemical inhomogeneity on the planet day side. This study highlights the ability to measure both C/O and refractory-to-volatile ratios via high resolution spectroscopy in the near-infrared H and K bands., Comment: 21 pages, 15 figures, accepted to AJ

Creativity is a fundamental pillar of human expression and a driving force behind innovation, yet it now stands at a crossroads. As artificial intelligence advances at an astonishing pace, the question arises: can machines match and potentially surpass human creativity? This study investigates the creative performance of artificial intelligence (AI) compared to humans by analyzing the effects of two distinct prompting strategies (a Naive and an Expert AI) on AI and across three different tasks (Text, Draw and Alternative Uses tasks). Human external evaluators have scored creative outputs generated by humans and AI, and these subjective creative scores were complemented with objective measures based on quantitative measurements and NLP tools. The results reveal that AI generally outperforms humans in creative tasks, though this advantage is nuanced by the specific nature of each task and the chosen creativity criteria. Ultimately, while AI demonstrates superior performance in certain creative domains, our results suggest that integrating human feedback is crucial for maximizing AI's creative potential.

Ultra hot Jupiters (gas giants, Teq>2000 K) are intriguing exoplanets due to their extreme atmospheres. Their torrid daysides can be characterised using ground-based high-resolution emission spectroscopy. We search for signatures of neutral and singly ionised iron (Fe I and Fe II) in the dayside of the ultra hot Jupiter WASP-76 b, as these species were detected via transmission spectroscopy in this exoplanet. Furthermore, we aim to confirm the existence of a thermal inversion layer, which has been reported in previous studies, and attempt to constrain its properties. We observed WASP-76 b on four epochs with ESPRESSO at the VLT, at orbital phases shortly before and after the secondary transit, when the dayside is in view. We present the first analysis of high-resolution optical emission spectra for this exoplanet. We compare the data to synthetic templates from petitRADTRANS, using cross-correlation function techniques. We detect a blueshifted (-4.7+-0.3 km/s) Fe I emission signature on the dayside of WASP-76 b at 6.0-sigma. The signal is detected independently both before and after the eclipse, and blueshifted in both cases. The presence of iron emission features confirms the existence of a thermal inversion layer. Fe II was not detected, possibly because this species is located in the upper layers of the atmosphere, which are more optically thin. Thus the Fe II signature on the dayside of WASP-76 b is too weak to be detected with emission spectroscopy. We propose that the blueshifted Fe I signature is created by material rising from the hot spot to the upper layers of the atmosphere, and discuss possible scenarios related to the position of the hotspot. This work unveils some of the dynamic processes ongoing on the dayside of WASP-76 b through the analysis of the Fe I signature from its atmosphere, and complements previous knowledge obtained from transmission studies., Comment: 15 pages, 8 figures + 2 figures in appendix. Abstract slightly abridged. Published in Astronomy & Astrophysics

In this paper the notion of Dirac structure in finite dimension is extended to the convenient setting. In particular, we introduce the notion of partial Dirac structure on convenient Lie algebroids and manifolds. We then look for those structures whose classical geometrical results in finite dimension can be extended to this infinite dimensional context. Finally, we are interested in the projective and direct limits of such structures., Comment: 2 figures

The vast amount of biomedical information available today presents a significant challenge for investigators seeking to digest, process, and understand these findings effectively. Large Language Models (LLMs) have emerged as powerful tools to navigate this complex and challenging data landscape. However, LLMs may lead to hallucinatory responses, making Retrieval Augmented Generation (RAG) crucial for achieving accurate information. In this protocol, we present RUGGED (Retrieval Under Graph-Guided Explainable disease Distinction), a comprehensive workflow designed to support investigators with knowledge integration and hypothesis generation, identifying validated paths forward. Relevant biomedical information from publications and knowledge bases are reviewed, integrated, and extracted via text-mining association analysis and explainable graph prediction models on disease nodes, forecasting potential links among drugs and diseases. These analyses, along with biomedical texts, are integrated into a framework that facilitates user-directed mechanism elucidation as well as hypothesis exploration through RAG-enabled LLMs. A clinical use-case demonstrates RUGGED's ability to evaluate and recommend therapeutics for Arrhythmogenic Cardiomyopathy (ACM) and Dilated Cardiomyopathy (DCM), analyzing prescribed drugs for molecular interactions and unexplored uses. The platform minimizes LLM hallucinations, offers actionable insights, and improves the investigation of novel therapeutics.

To overcome the innovation gap of the Guidance, Navigation and Control (GNC) design process between research and industrial practice a benchmark of industrial relevance has been developed and is presented. This initiative is driven as well by the necessity to train future GNC engineers and the GNC space community on a set of identified complex problems. It allows to demonstrate the relevance of state-of-the-art modeling, control and analysis algorithms for future industrial adoption. The modeling philosophy for robust control synthesis, analysis including the control architecture that enables the simulation of the mission, i.e. the acquisition of a high pointing space mission, are provided.

For several years, the metastable helium triplet line has been successfully used as a tracer to probe atmospheric escape in transiting exoplanets. This absorption in the near-infrared (1083.3 nm) can be observed from the ground using high-resolution spectroscopy, providing new constraints on the mass-loss rate and the temperature characterizing the upper atmosphere of close-in exoplanets. The aim of this work is to search for the He triplet signature in 15 transiting exoplanets -- ranging from super-Earths to ultrahot Jupiters -- observed with SPIRou, a high-resolution (R~70 000) near-infrared spectropolarimeter at the CFHT, in order to bring new constraints or to improve existing ones regarding atmospheric escape through a homogeneous study. We developed a full data processing and analysis pipeline to correct for the residual telluric and stellar contributions. We then used two different 1D models based on the Parker-wind equations and nonlocal thermodynamic equilibrium (NLTE) radiative transfer to interpret the observational results. We confirm published He triplet detections for HAT-P-11 b, HD 189733 b, and WASP-69 b. We tentatively detect the signature of escaping He in HD 209458 b, GJ 3470 b, and WASP-76 b. We report new constraints on the mass-loss rate and temperature for our three detections and set upper limits for the tentative and nondetections. We notably report improved constraints on the mass-loss rate and temperature of the escaping gas for TOI-1807 b, and report a nondetection for the debated atmospheric escape in GJ 1214 b. We also conducted the first search for the He signature in GJ 486 b since its discovery and report a nondetection of the He triplet. Finally, we studied the impact of important model assumptions on our retrieved parameters, notably the limitations of 1D models and the influence of the H/He ratio on the derived constraints., Comment: 33 pages, 14 figures

The Near-InfraRed Planet Searcher or NIRPS is a precision radial velocity spectrograph developed through collaborative efforts among laboratories in Switzerland, Canada, Brazil, France, Portugal and Spain. NIRPS extends to the 0.98-1.8 $\mu$m domain of the pioneering HARPS instrument at the La Silla 3.6-m telescope in Chile and it has achieved unparalleled precision, measuring stellar radial velocities in the infrared with accuracy better than 1 m/s. NIRPS can be used either stand-alone or simultaneously with HARPS. Commissioned in late 2022 and early 2023, NIRPS embarked on a 5-year Guaranteed Time Observation (GTO) program in April 2023, spanning 720 observing nights. This program focuses on planetary systems around M dwarfs, encompassing both the immediate solar vicinity and transit follow-ups, alongside transit and emission spectroscopy observations. We highlight NIRPS's current performances and the insights gained during its deployment at the telescope. The lessons learned and successes achieved contribute to the ongoing advancement of precision radial velocity measurements and high spectral fidelity, further solidifying NIRPS' role in the forefront of the field of exoplanets., Comment: Proceeding at the SPIE Astronomical Telescopes + Instrumentation conference [Yokohama,Japan; June 2024]

Satellite imaging generally presents a trade-off between the frequency of acquisitions and the spatial resolution of the images. Super-resolution is often advanced as a way to get the best of both worlds. In this work, we investigate multi-image super-resolution of satellite image time series, i.e. how multiple images of the same area acquired at different dates can help reconstruct a higher resolution observation. In particular, we extend state-of-the-art deep single and multi-image super-resolution algorithms, such as SRDiff and HighRes-net, to deal with irregularly sampled Sentinel-2 time series. We introduce BreizhSR, a new dataset for 4x super-resolution of Sentinel-2 time series using very high-resolution SPOT-6 imagery of Brittany, a French region. We show that using multiple images significantly improves super-resolution performance, and that a well-designed temporal positional encoding allows us to perform super-resolution for different times of the series. In addition, we observe a trade-off between spectral fidelity and perceptual quality of the reconstructed HR images, questioning future directions for super-resolution of Earth Observation data.

We introduce the notion of \textbf{Q}-principal bundle, which is the appropriate version of principal fibre bundles in the setting of R. Barre's \textbf{Q}-manifolds. As an application, we prove that every transitive Lie algebroid arises from the Atiyah sequence of a certain \textbf{Q}-principal bundle, and we give the interpretation of this result in terms of groupoids., Comment: 43 pages

This paper offers an adaptation to the convenient setting of finite dimensional Nambu-Poisson structures. In particular, for partial Nambu structures, we look for those whose classical geometrical results in finite dimension can be extended to this infinite dimensional context. Finally, we are interested in the projective and direct limits of such structures., Comment: 2 figures. arXiv admin note: substantial text overlap with arXiv:2112.14592

Earth observation (EO) satellite missions have been providing detailed images about the state of the Earth and its land cover for over 50 years. Long term missions, such as NASA's Landsat, Terra, and Aqua satellites, and more recently, the ESA's Sentinel missions, record images of the entire world every few days. Although single images provide point-in-time data, repeated images of the same area, or satellite image time series (SITS) provide information about the changing state of vegetation and land use. These SITS are useful for modeling dynamic processes and seasonal changes such as plant phenology. They have potential benefits for many aspects of land and natural resource management, including applications in agricultural, forest, water, and disaster management, urban planning, and mining. However, the resulting satellite image time series (SITS) are complex, incorporating information from the temporal, spatial, and spectral dimensions. Therefore, deep learning methods are often deployed as they can analyze these complex relationships. This review presents a summary of the state-of-the-art methods of modelling environmental, agricultural, and other Earth observation variables from SITS data using deep learning methods. We aim to provide a resource for remote sensing experts interested in using deep learning techniques to enhance Earth observation models with temporal information., Comment: This work has been submitted to the IEEE for possible publication

Exoplanets in the ultra-hot Jupiter regime provide an excellent laboratory for testing the impact of stellar irradiation on the dynamics and chemical composition of gas giant atmospheres. In this study, we observed two transits of the ultra-hot Jupiter WASP-189 b with MAROON-X/Gemini-North to probe its high-altitude atmospheric layers, using strong absorption lines. We derived posterior probability distributions for the planetary and stellar parameters by calculating the stellar spectrum behind the planet at every orbital phase during the transit. This was used to correct the Rossiter-McLaughlin imprint on the transmission spectra. Using differential transmission spectroscopy, we detect strong absorption lines of Ca+, Ba+, Na, H$\alpha$, Mg, Fe, and Fe+, providing an unprecedented and detailed view of the atmospheric chemical composition. Ca+ absorption is particularly well suited for analysis through time-resolved narrow-band spectroscopy, owing to its transition lines formed in high-altitude layers. The spectral absorption lines show no significant blueshifts that would indicate high-altitude day-to-night winds, and further analysis is needed to investigate the implications for atmospheric dynamics. These high signal-to-noise observations provide a benchmark data set for testing high-resolution retrievals and the assumptions of atmospheric models. We also simulate observations of WASP-189 b with ANDES/ELT, and show that ANDES will be highly sensitive to the individual absorption lines of a myriad of elements and molecules, including TiO and CO., Comment: 34 pages, 31 figures, accepted for publication in A&A on 16 February 2024

Studying and understanding the physical and chemical processes that govern hot Jupiters gives us insights on the formation of these giant planets. Having a constraint on the molecular composition of their atmosphere can help us pinpoint their evolution timeline. Namely, the metal enrichment and carbon-to-oxygen ratio can give us information about where in the protoplanetary disk a giant planet may have accreted its envelope, and subsequently, indicate if it went through migration. Here we present the first analysis of the atmosphere of the hot Jupiter HIP 65Ab. Using near-infrared high-resolution observations from the IGRINS spectrograph, we detect H$_2$O and CO absorption in the dayside atmosphere of HIP 65Ab. Using a high-resolution retrieval framework, we find a CO abundance of log(CO) = $-3.85^{+0.33}_{-0.36}$, which is slightly under abundant with expectation from solar composition models. We also recover a low water abundance of log(H$_2$O) = $-4.42\pm{0.18}$, depleted by 1 order of magnitude relative to a solar-like composition. Upper limits on the abundance of all other relevant major carbon- and oxygen-bearing molecules are also obtained. Overall, our results are consistent with a sub-stellar metallicity but slightly elevated C/O. Such a composition may indicate that HIP 65Ab accreted its envelope from beyond the water snowline and underwent a disk-free migration to its current location. Alternatively, some of the oxygen on HIP 65Ab could be condensed out of the atmosphere, in which case the observed gas-phase abundances would not reflect the true bulk envelope composition., Comment: Accepted for publication in AJ

Even though sub-Neptunes likely represent the most common outcome of planet formation, their natures remain poorly understood. In particular, planets near 1.5-2.5$\,R_\oplus$ often have bulk densities that can be explained equally well with widely different compositions and interior structures, resulting in grossly divergent implications for their formation. Here, we present the full 0.6-5.2$\,\mu \mathrm{m}$ JWST NIRISS/SOSS+NIRSpec/G395H transmission spectrum of the 2.2$\,R_\oplus$ TOI-270d ($4.78\,M_\oplus$, $T_\mathrm{eq}$=350-380 K), delivering unprecedented sensitivity for atmospheric characterization in the sub-Neptune regime. We detect five vibrational bands of CH$_4$ at 1.15, 1.4, 1.7, 2.3, and 3.3$\,\mu$m (9.4$\sigma$), the signature of CO$_2$ at 4.3$\,\mu$m (4.8$\sigma$), water vapor (2.5$\sigma$), and potential signatures of SO$_2$ at 4.0$\,\mu \mathrm{m}$ and CS$_2$ at 4.6$\,\mu\mathrm{m}$. Intriguingly, we find an overall highly metal-rich atmosphere, with a mean molecular weight of $5.47_{-1.14}^{+1.25}$. We infer an atmospheric metal mass fraction of $58_{-12}^{+8}\%$ and a C/O of $0.47_{-0.19}^{+0.16}$, indicating that approximately half the mass of the outer envelope is in high-molecular-weight volatiles (H$_2$O, CH$_4$, CO, CO$_2$) rather than H$_2$/He. We introduce a sub-Neptune classification scheme and identify TOI-270d as a "miscible-envelope sub-Neptune" in which H$_2$/He is well-mixed with the high-molecular-weight volatiles in a miscible supercritical metal-rich envelope. For a fully miscible envelope, we conclude that TOI-270d's interior is $90_{-4}^{+3}\,$wt$\,\%$ rock/iron, indicating that it formed as a rocky planet that accreted a few wt % of H$_2$/He, with the overall envelope metal content explained by magma-ocean/envelope reactions without the need for significant ice accretion. TOI-270d may well be an archetype of the overall population of sub-Neptunes., Comment: 25 pages, 12 figures

The hot-Neptune desert is one of the most sparsely populated regions of the exoplanet parameter space, and atmosphere observations of its few residents can provide insights into how such planets have managed to survive in such an inhospitable environment. Here, we present transmission observations of LTT 9779 b, the only known hot-Neptune to have retained a significant H/He-dominated atmosphere, taken with JWST NIRISS/SOSS. The 0.6-2.85$\mu$m transmission spectrum shows evidence for muted spectral features, rejecting a perfectly flat line at >5$\sigma$. We explore water and methane-dominated atmosphere scenarios for LTT 9779 b's terminator, and retrieval analyses reveal a continuum of potential combinations of metallicity and cloudiness. Through comparisons to previous population synthesis works and our own interior structure modelling, we are able to constrain LTT 9779 b's atmosphere metallicity to 20-850x solar. Within this range of metallicity, our retrieval analyses prefer solutions with clouds at mbar pressures, regardless of whether the atmosphere is water- or methane-dominated -- though cloud-free atmospheres with metallicities >500x solar cannot be entirely ruled out. By comparing self-consistent atmosphere temperature profiles with cloud condensation curves, we find that silicate clouds can readily condense in the terminator region of LTT 9779 b. Advection of these clouds onto the day-side could explain the high day-side albedo previously inferred for this planet and be part of a feedback loop aiding the survival of LTT 9779 b's atmosphere in the hot-Neptune desert., Comment: Accepted for publication in ApJL

Purpose: The aim of this study was to explore the feasibility of natural capital accounting for the purpose of strengthening sustainability claims by reporting entities. The study linked riparian land improvement to ecosystem services and tested options for incorporating natural capital into financial accounting practices, specifically on the balance sheet. Methodology: To test the approach, the study used a public asset manager (a water utility) with accountabilities to protect the environment including maintaining and enhancing riparian land assets. Research activities included stakeholder engagement, physical asset measurement, monetary valuation and financial recognition of natural capital income and assets. Natural capital income was estimated by modelling and valuing ecosystem services relating to stormwater filtration and carbon storage. Findings: This research described how a water utility could disclose changes in the natural capital assets they manage either through voluntary disclosures, in notes to the financial statements or as balance sheet items. We found that current accounting standards allowed the recognition of some types of environmental income and assets where ecosystem services were associated with cost savings. The proof-of-concept employed to estimate environmental income through ecosystem service modelling proved useful to strengthen sustainability claims or report financial returns on natural capital investment. Originality/value: This study applied financial accounting processes and principles to a realistic public asset management scenario with direct participation by the asset manager working together with academic researchers and a sub-national government environment management agency. Importantly it established that natural assets could be included in financial statements, proposing a new approach to measuring and reporting on natural capital., Comment: 26 pages, 4 figures, 8 tables

Let $p_E : E \to M$ be a fibre bundle over the $m$-dimensional manifold $M$ whose typical fibre is the vector space $\R^e$ and let $p_F : F \to N$ be a fibre bundle over the $n$-dimensional manifold $N$ whose typical fibre is the vector space $\R^f$. We are interested in the structure of the set $\Morph(E,F)$ of smooth linear bundle morphisms $\Phi : E \to F$ above smooth maps $\varphi : M \to N$., Comment: 1 figure

This paper investigates the relationship between scientists' cognitive profile and their ability to generate innovative ideas and gain scientific recognition. We propose a novel author-level metric based on the semantic representation of researchers' past publications to measure cognitive diversity both at individual and team levels. Using PubMed Knowledge Graph (PKG), we analyze the impact of cognitive diversity on novelty, as measured by combinatorial novelty indicators and peer labels on Faculty Opinion. We assessed scientific impact through citations and disruption indicators. We show that the presence of exploratory individuals (i.e., cognitively diverse) is beneficial in generating distant knowledge combinations, but only when balanced by a significant proportion of exploitative individuals (i.e., cognitively specialized). Furthermore, teams with a high proportion of exploitative profiles tend to consolidate science, whereas those with a significant share of both profiles tend to disrupt it. Cognitive diversity between team members appears to be always beneficial to combining more distant knowledge. However, to maximize the relevance of these distant combinations of knowledge, maintaining a limited number of exploratory individuals is essential, as exploitative individuals must question and debate their novel perspectives. These specialized individuals are the most qualified to extract the full potential of novel ideas and integrate them within the existing scientific paradigm.

New technologies have the power to revolutionize science. It has happened in the past and is happening again with the emergence of new computational tools, such as artificial intelligence and machine learning. Despite the documented impact of these technologies, there remains a significant gap in understanding the process of their adoption within the scientific community. In this paper, we draw on theories of scientific and technical human capital to study the integration of AI in scientific research, focusing on the human capital of scientists and the external resources available within their network of collaborators and institutions. We validate our hypotheses on a large sample of publications from OpenAlex, covering all sciences from 1980 to 2020, and identify a set key drivers and inhibitors of AI adoption and use in science. Our results suggest that AI is pioneered by domain scientists with a `taste for exploration' and who are embedded in a network rich of computer scientists, experienced AI scientists and early-career researchers; they come from institutions with high citation impact and a relatively strong publication history on AI. The access to computing resources only matters for a few scientific disciplines, such as chemistry and medical sciences. Once AI is integrated into research, most adoption factors continue to influence its subsequent reuse. Implications for the organization and management of science in the evolving era of AI-driven discovery are discussed.

Using novel approaches to dataset development, the Biasly dataset captures the nuance and subtlety of misogyny in ways that are unique within the literature. Built in collaboration with multi-disciplinary experts and annotators themselves, the dataset contains annotations of movie subtitles, capturing colloquial expressions of misogyny in North American film. The dataset can be used for a range of NLP tasks, including classification, severity score regression, and text generation for rewrites. In this paper, we discuss the methodology used, analyze the annotations obtained, and provide baselines using common NLP algorithms in the context of misogyny detection and mitigation. We hope this work will promote AI for social good in NLP for bias detection, explanation, and removal., Comment: 8 pages, 2 figures

Inverse Reinforcement Learning (IRL) learns an optimal policy, given some expert demonstrations, thus avoiding the need for the tedious process of specifying a suitable reward function. However, current methods are constrained by at least one of the following requirements. The first one is the need to fully solve a forward Reinforcement Learning (RL) problem in the inner loop of the algorithm, which might be prohibitively expensive in many complex environments. The second one is the need for full trajectories from the experts, which might not be easily available. The third one is the assumption that the expert data is homogeneous rather than a collection from various experts or possibly alternative solutions to the same task. Such constraints make IRL approaches either not scalable or not usable on certain existing systems. In this work we propose an approach which removes these requirements through a dynamic, adaptive method called Adversarial Imitation Learning on Aggregated Data (AILAD). It learns conjointly both a non linear reward function and the associated optimal policy using an adversarial framework. The reward learner only uses aggregated data. Moreover, it generates diverse behaviors producing a distribution over the aggregated data matching that of the experts.

The JWST Early Release Observations (ERO) included a NIRISS/SOSS (0.6-2.8$\,\mu$m) transit of the $\sim\,$850$\,$K Saturn-mass exoplanet HAT-P-18$\,$b. Initial analysis of these data reported detections of water, escaping helium, and haze. However, active K dwarfs like HAT-P-18 possess surface heterogeneities $-$ starspots and faculae $-$ that can complicate the interpretation of transmission spectra, and indeed, a spot-crossing event is present in HAT-P-18$\,$b's NIRISS/SOSS light curves. Here, we present an extensive reanalysis and interpretation of the JWST ERO transmission spectrum of HAT-P-18$\,$b, as well as HST/WFC3 and $\textit{Spitzer}$/IRAC transit observations. We detect H$_2$O (12.5$\,\sigma$), CO$_2$ (7.3$\,\sigma$), a cloud deck (7.4$\,\sigma$), and unocculted starspots (5.8$\,\sigma$), alongside hints of Na (2.7$\,\sigma$). We do not detect the previously reported CH$_4$ ($\log$ CH$_4$ $<$ -6 to 2$\,\sigma$). We obtain excellent agreement between three independent retrieval codes, which find a sub-solar H$_2$O abundance ($\log$ H$_2$O $\approx -4.4 \pm 0.3$). However, the inferred CO$_2$ abundance ($\log$ CO$_2$ $\approx -4.8 \pm 0.4$) is significantly super-solar and requires further investigation into its origin. We also introduce new stellar heterogeneity considerations by fitting for the active regions' surface gravities $-$ a proxy for the effects of magnetic pressure. Finally, we compare our JWST inferences to those from HST/WFC3 and $\textit{Spitzer}$/IRAC. Our results highlight the exceptional promise of simultaneous planetary atmosphere and stellar heterogeneity constraints in the era of JWST and demonstrate that JWST transmission spectra may warrant more complex treatments of the transit light source effect.

Determination of fundamental parameters of stars impacts all fields of astrophysics, from galaxy evolution to constraining the internal structure of exoplanets. This paper presents a detailed spectroscopic analysis of Barnard's star that compares an exceptionally high-quality (an average signal-to-noise ratio of $\sim$1000 in the entire domain), high-resolution NIR spectrum taken with CFHT/SPIRou to PHOENIX-ACES stellar atmosphere models. The observed spectrum shows thousands of lines not identified in the models with a similar large number of lines present in the model but not in the observed data. We also identify several other caveats such as continuum mismatch, unresolved contamination and spectral lines significantly shifted from their expected wavelengths, all of these can be a source of bias for abundance determination. Out of $>10^4$ observed lines in the NIR that could be used for chemical spectroscopy, we identify a short list of a few hundred lines that are reliable. We present a novel method for determining the effective temperature and overall metallicity of slowly-rotating M dwarfs that uses several groups of lines as opposed to bulk spectral fitting methods. With this method, we infer $T_{eff}$ = 3231 $\pm$ 21 K for Barnard's star, consistent with the value of 3238 $\pm$ 11 K inferred from the interferometric method. We also provide abundance measurements of 15 different elements for Barnard's star, including the abundances of four elements (K, O, Y, Th) never reported before for this star. This work emphasizes the need to improve current atmosphere models to fully exploit the NIR domain for chemical spectroscopy analysis., Comment: 29 pages, 23 figures, accepted for publication in ApJ

Knowledge graphs (KGs) have emerged as a powerful framework for representing and integrating complex biomedical information. However, assembling KGs from diverse sources remains a significant challenge in several aspects, including entity alignment, scalability, and the need for continuous updates to keep pace with scientific advancements. Moreover, the representative power of KGs is often limited by the scarcity of multi-modal data integration. To overcome these challenges, we propose Know2BIO, a general-purpose heterogeneous KG benchmark for the biomedical domain. Know2BIO integrates data from 30 diverse sources, capturing intricate relationships across 11 biomedical categories. It currently consists of ~219,000 nodes and ~6,200,000 edges. Know2BIO is capable of user-directed automated updating to reflect the latest knowledge in biomedical science. Furthermore, Know2BIO is accompanied by multi-modal data: node features including text descriptions, protein and compound sequences and structures, enabling the utilization of emerging natural language processing methods and multi-modal data integration strategies. We evaluate KG representation models on Know2BIO, demonstrating its effectiveness as a benchmark for KG representation learning in the biomedical field. Data and source code of Know2BIO are available at https://github.com/Yijia-Xiao/Know2BIO/., Comment: 26 pages, 2 figures, 14 figures

The location of the mobility edge is a long standing problem in Anderson localization. In this paper, we show that the effective confining potential introduced in the localization landscape (LL) theory predicts the onset of delocalization in 3D tight-binding models, in a large part of the energy-disorder diagram. Near the edge of the spectrum, the eigenstates are confined inside the basins of the LL-based potential. The delocalization transition corresponds to the progressive merging of these basins resulting in the percolation of this classically-allowed region throughout the system. This approach, shown to be valid both in the cases of uniform and binary disorders despite their very different phase diagrams, allows us to reinterpret the Anderson transition in the tight-binding model: the mobility edge appears to be composed of two parts, one being understood as a percolation transition., Comment: 6 pages, 6 figures

The magnetic and structural properties of the recently discovered pnictogen/chalcogen-free superconductor LaFeSiH ($T_c\simeq10$~K) have been investigated by $^{57}$Fe synchrotron M{\"o}ssbauer source (SMS) spectroscopy, x-ray and neutron powder diffraction and $^{29}$Si nuclear magnetic resonance spectroscopy (NMR). No sign of long range magnetic order or local moments has been detected in any of the measurements and LaFeSiH remains tetragonal down to 2 K. The activated temperature dependence of both the NMR Knight shift and the relaxation rate $1/T_1$ is analogous to that observed in strongly overdoped Fe-based superconductors. These results, together with the temperature-independent NMR linewidth, show that LaFeSiH is an homogeneous metal, far from any magnetic or nematic instability, and with similar Fermi surface properties as strongly overdoped iron pnictides. This raises the prospect of enhancing the $T_c$ of LaFeSiH by reducing its carrier concentration through appropriate chemical substitutions. Additional SMS spectroscopy measurements under hydrostatic pressure up to 18.8~GPa found no measurable hyperfine field.