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Abstract One of the most conspicuous signals of climate change in high‐latitude tundra is the expansion of ice wedge thermokarst pools. These small but abundant water features form rapidly in depressions caused by the melting of ice wedges (i.e., meter‐scale bodies of ice embedded within the top of the permafrost). Pool expansion impacts subsequent thaw rates through a series of complex positive and negative feedbacks which play out over timescales of decades and may accelerate carbon release from the underlying sediments. Although many local observations of ice wedge thermokarst pool expansion have been documented, analyses at continental to pan‐Arctic scales have been rare, hindering efforts to project how strongly this process may impact the global carbon cycle. Here we present one of the most geographically extensive and temporally dense records yet compiled of recent pool expansion, in which changes to pool area from 2008 to 2020 were quantified through satellite‐image analysis at 27 survey areas (measuring 10–35 km²each, or 400 km²in total) dispersed throughout the circumpolar tundra. The results revealed instances of rapid expansion at 44% (15%) of survey areas. Considered alone, the extent of departures from historical mean air temperatures did not account for between site variation in rates of change to pool area. Pool growth was most clearly associated with upland (i.e., hilly) terrain and elevated silt content at soil depths greater than one meter. These findings suggest that, at short time scales, pedologic and geomorphologic conditions may exert greater control on pool dynamics in the warming Arctic than spatial variability in the rate of air temperature increases. 

This study applied Transmodal Analysis (TMA), a newly developed quantitative ethnographic approach, to examine whether and how virtual patient simulations can aid in educating undergraduate nursing students with competencies that exemplify practice-ready nurses. Multimodal transcripts capturing patient interactions, exam actions, and documentation were obtained from two students who used Elsevier’s Shadow Health® Digital Clinical Experiences (DCE) in Fall 2022 and Spring 2023. Patient scenarios were situated in three content areas (Gerontology, Mental Health, and Community Health) and two assignment types (focused exam and contact tracing). In each scenario, similar patterns of engagement were observed for both students as they completed learning activities such as collecting patient data and establishing a caring relationship. These activities—guided by the instructional design of DCE—indicated how students practiced recognizing and analyzing cues, subjective assessment, diagnosing and prioritizing hypotheses, generating solutions, evaluating outcomes, therapeutic communication, and care coordination and management in relation to each patient’s needs and conditions. A statistical difference was observed between competencies practiced while completing focused exam and contact tracing assignments. This study provides evidence for using simulations to facilitate competency-based education in nursing. Additionally, it provides motivation for using Transmodal Analysis combined with Ordered Network Analysis (T/ONA) to advance quantitative ethnography research in health care and health professions education. 

The field of geology is poised to make a fundamental transition in the quality, character, and types of science that are possible for practitioners. Geologists are developing data systems—consistent with their workflow—to digitally collect, store, and share data. Separately, geologists and cognitive scientists have been working together to develop tools that can characterize the level of uncertainty of both data and models. The transformational change comes from the simultaneous combination of these two approaches: digital data systems designed to capture and convey scientific uncertainty. This approach promotes better data collection practice, improves reproducibility, and increases trust in community-based digital data. We applied these methods—attending to uncertainty and its incorporation into digital repositories—to the Sage Hen Flat pluton in eastern California, USA, where two published maps provide different interpretations. Incorporating uncertainty into our workflow, from field data collection to publication, allows us to move beyond binary choices (e.g., is this data/model right or wrong?) to a more nuanced view (e.g., what is my level of uncertainty about the data/model?) that is shareable with the larger community. 

In acquiring morphology, the language learner faces the challenge of identifying both the form of morphemes and their location within words. For example, individuals acquiring Chamorro (Austronesian) must learn an agreement morpheme with the form -um- that is infixed before the first vowel of the stem (1a). This challenge is more difficult when a morpheme has multiple forms and/or locations: in some varieties of Chamorro, the same agreement morpheme appears as mu- prefixed on verbs beginning with a nasal/liquid consonant (1b). The learner could potentially overcome the acquisition challenge by employing strong inductive biases. This hypothesis is consistent with the typological finding that, across languages, morphemes occupy a restricted set of prosodically-defined locations (Yu, 2007) and there are strong correlations between morpheme form and position (Anderson, 1972). We conducted a series of artificial morphology experiments, modeled after the Chamorro pattern, that provide converging evidence for such inductive biases (Pierrehumbert & Nair, 1995; Staroverov & Finley, 2021). 

Targeted delivery of nucleic acid therapeutics to the lungs could transform treatment options for pulmonary disease. We have previously developed oligomeric charge-altering releasable transporters (CARTs) for in vivo mRNA transfection and demonstrated their efficacy for use in mRNA-based cancer vaccination and local immunomodulatory therapies against murine tumors. While our previously reported glycine-based CART-mRNA complexes (G-CARTs/mRNA) show selective protein expression in the spleen (mouse, >99%), here, we report a new lysine-derived CART-mRNA complex (K-CART/mRNA) that, without additives or targeting ligands, shows selective protein expression in the lungs (mouse, >90%) following systemic IV administration. We further show that by delivering siRNA using the K-CART, we can significantly decrease expression of a lung-localized reporter protein. Blood chemistry and organ pathology studies demonstrate that K-CARTs are safe and well-tolerated. We report on the new step economical, organocatalytic synthesis (two steps) of functionalized polyesters and oligo-carbonate-co-α- aminoester K-CARTs from simple amino acid and lipid-based monomers. The ability to direct protein expression selectively in the spleen or lungs by simple, modular changes to the CART structure opens fundamentally new opportunities in research and gene therapy. 

Decisions made by mammals and birds are often temporally extended. They require planning and sampling of decision-relevant information. Our understanding of such decision-making remains in its infancy compared with simpler, forced-choice paradigms. However, recent advances in algorithms supporting planning and information search provide a lens through which we can explain neural and behavioral data in these tasks. We review these advances to obtain a clearer understanding for why planning and curiosity originated in certain species but not others; how activity in the medial temporal lobe, prefrontal and cingulate cortices may support these behaviors; and how planning and information search may complement each other as means to improve future action selection.