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Large language models (LLMs) have offered new opportunities for emotional support, and recent work has shown that they can produce empathic responses to people in distress. However, long-term mental well-being requires emotional self-regulation, where a one-time empathic response falls short. This work takes a first step by engaging with cognitive reappraisals, a strategy from psychology practitioners that uses language to targetedly change negative appraisals that an individual makes of the situation; such appraisals is known to sit at the root of human emotional experience. We hypothesize that psychologically grounded principles could enable such advanced psychology capabilities in LLMs, and design RESORT which consists of a series of reappraisal constitutions across multiple dimensions that can be used as LLM instructions. We conduct a first-of-its-kind expert evaluation (by clinical psychologists with M.S. or Ph.D. degrees) of an LLM's zero-shot ability to generate cognitive reappraisal responses to medium-length social media messages asking for support. This fine-grained evaluation showed that even LLMs at the 7B scale guided by RESORT are capable of generating empathic responses that can help users reappraise their situations. 

Problem definition: Inventory management problems with periodic and controllable resets occur in the context of managing water storage in the developing world and dynamically optimizing endcap promotion duration in retail outlets. In this paper, we consider a set of sequential decision problems in which the decision maker must not only balance holding and shortage costs but discard all inventory before a fixed number of decision epochs with the option for an early inventory reset. Methodology/results: Finding optimal policies for these problems through dynamic programming presents unique challenges because of the nonconvex nature of the resulting value functions. Moreover, this structure cannot be readily analyzed even with extended convexity definitions, such as K-convexity. Managerial implications: Our key contribution is to present sufficient conditions that ensure the optimal policy has an easily interpretable structure, which generalizes the well-known [Formula: see text] policy from the operations management literature. Furthermore, we demonstrate that, under these rather mild conditions, the optimal policy exhibits a four-threshold structure. We then conclude with computational experiments, thereby illustrating the policy structures that can be extracted in various inventory management scenarios. Funding: This work was supported by the National Science Foundation [Grant CMMI-1847666] and the Division of Graduate Education [Grant DGE-2125913]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0318 . 

ABSTRACT Over the course of hundreds of millions of years, biomineralization has evolved independently many times across all kingdoms of life. Among animals, the phylum Mollusca displays a remarkable diversity in biomineral structures, particularly the molluscan shell, which varies greatly in shape, size, pigmentation, and patterning. Shell matrix proteins (SMPs) are key components of these shells, and are thought to drive the precipitation of calcium carbonate minerals and influence shell morphology. However, this structure‐function relationship has rarely been studied directly because tools for knocking out genes did not exist in molluscs until recently. In this study, we report the first successful use of CRISPR/Cas9 gene editing to target an SMP in gastropod molluscs. Using the emerging model gastropodCrepidula atrasolea, we generated knockouts of theSMP1gene. Successful gene editing was confirmed by Sanger and MiSeq sequencing, and loss ofSMP1expression was validated through high‐content imaging of crispant embryos. This study establishesC. atrasoleaas a valuable model for investigating the genetic basis of shell formation and provides a framework for applying CRISPR/Cas9 technology in other molluscan species. Our approach will enable future studies to thoroughly test the role of SMPs in shaping the diverse array of molluscan shell structures. 

Sea urchins are basal deuterostomes that share key molecular components of innate immunity with vertebrates. They are a powerful model for the study of innate immune system evolution and function, especially during early development. Here we characterize the morphology and associated molecular markers of larval immune cell types in a newly developed model sea urchin, Lytechinus pictus. We then challenge larvae through infection with an established pathogenic Vibrio and characterize phenotypic and molecular responses. We contrast these to the previously described immune responses of the purple sea urchin Strongylocentrotus purpuratus . The results revealed shared cellular morphologies and homologs of known pigment cell immunocyte markers ( PKS, srcr142 ) but a striking absence of subsets of perforin‐like macpf genes in blastocoelar cell immunocytes. We also identified novel patterning of cells expressing a scavenger receptor cysteine rich (SRCR) gene in the coelomic pouches of the larva (the embryonic stem cell niche). The SRCR signal becomes further enriched in both pouches in response to bacterial infection. Collectively, these results provide a foundation for the study of immune responses in L. pictus. The characterization of the larval immune system of this rapidly developing and genetically enabled sea urchin species will facilitate more sophisticated studies of innate immunity and the crosstalk between the immune system and development. 

Large Language Models (LLMs) have demonstrated surprising performance on many tasks, including writing supportive messages that display empathy. Here, we had these models generate empathic messages in response to posts describing common life experiences, such as workplace situations, parenting, relationships, and other anxiety- and anger-eliciting situations. Across two studies (N=192, 202), we showed human raters a variety of responses written by several models (GPT4 Turbo, Llama2, and Mistral), and had people rate these responses on how empathic they seemed to be. We found that LLM-generated responses were consistently rated as more empathic than human-written responses. Linguistic analyses also show that these models write in distinct, predictable “styles”, in terms of their use of punctuation, emojis, and certain words. These results highlight the potential of using LLMs to enhance human peer support in contexts where empathy is important. 

Abstract Metal halide perovskites show promise for next-generation light-emitting diodes, particularly in the near-infrared range, where they outperform organic and quantum-dot counterparts. However, they still fall short of costly III-V semiconductor devices, which achieve external quantum efficiencies above 30% with high brightness. Among several factors, controlling grain growth and nanoscale morphology is crucial for further enhancing device performance. This study presents a grain engineering methodology that combines solvent engineering and heterostructure construction to improve light outcoupling efficiency and defect passivation. Solvent engineering enables precise control over grain size and distribution, increasing light outcoupling to ~40%. Constructing 2D/3D heterostructures with a conjugated cation reduces defect densities and accelerates radiative recombination. The resulting near-infrared perovskite light-emitting diodes achieve a peak external quantum efficiency of 31.4% and demonstrate a maximum brightness of 929 W sr⁻¹m⁻². These findings indicate that perovskite light-emitting diodes have potential as cost-effective, high-performance near-infrared light sources for practical applications.