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With over 6 million tons produced annually, thermoplastic elastomers (TPEs) have become ubiquitous in modern society, due to their unique combination of elasticity, toughness, and reprocessability. Nevertheless, industrial TPEs display a tradeoff between softness and strength, along with low upper service temperatures, typically ≤100 °C. This limits their utility, such as in bio‐interfacial applications where supersoft deformation is required in tandem with strength, in addition to applications that require thermal stability (e.g., encapsulation of electronics, seals/joints for aeronautics, protective clothing for firefighting, and biomedical devices that can be subjected to steam sterilization). Thus, combining softness, strength, and high thermal resistance into a single versatile TPE has remained an unmet opportunity. Through de novo design and synthesis of novel norbornene‐basedABAtriblock copolymers, this gap is filled. Ring‐opening metathesis polymerization is employed to prepare TPEs with an unprecedented combination of properties, including skin‐like moduli (<100 kPa), strength competitive with commercial TPEs (>5 MPa), and upper service temperatures akin to high‐performance plastics (≈260 °C). Furthermore, the materials are elastic, tough, reprocessable, and shelf stable (≥2 months) without incorporation of plasticizer. Structure–property relationships identified herein inform development of next‐generation TPEs that are both biologically soft yet thermomechanically durable. 

Let P(k) denote the largest size of a non-collinear point set in the plane admitting at most k distinct angles. We prove P(2) = P(3) = 5, and we characterize the optimal sets. We also leverage results from Fleischmann et al. [Disc. Comput. Geom. (2023)] to provide the general bounds k+2 ≤ P(k) ≤ 6k, although the upper bound may be improved pending progress toward the Strong Dirac Conjecture. We conjecture that the lower bound is tight, providing infinite families of configurations meeting the bound and ruling out several classes of potential counterexamples. 

Abstract Image‐based machine learning tools are an ascendant ‘big data’ research avenue. Citizen science platforms, like iNaturalist, and museum‐led initiatives provide researchers with an abundance of data and knowledge to extract. These include extraction of metadata, species identification, and phenomic data. Ecological and evolutionary biologists are increasingly using complex, multi‐step processes on data. These processes often include machine learning techniques, often built by others, that are difficult to reuse by other members in a collaboration.We present a conceptual workflow model for machine learning applications using image data to extract biological knowledge in the emerging field of imageomics. We derive an implementation of this conceptual workflow for a specific imageomics application that adheres to FAIR principles as a formal workflow definition that allows fully automated and reproducible execution, and consists of reusable workflow components.We outline technologies and best practices for creating an automated, reusable and modular workflow, and we show how they promote the reuse of machine learning models and their adaptation for new research questions. This conceptual workflow can be adapted: it can be semi‐automated, contain different components than those presented here, or have parallel components for comparative studies.We encourage researchers—both computer scientists and biologists—to build upon this conceptual workflow that combines machine learning tools on image data to answer novel scientific questions in their respective fields. 

Abstract The conference “Transposable Elements at the Crossroads of Evolution, Health and Disease” was hosted by Keystone Symposia in Whistler, British Columbia, Canada, on September 3–6, 2023, and was organized by Kathleen Burns, Harmit Malik and Irina Arkhipova. The central theme of the meeting was the incredible diversity of ways in which transposable elements (TEs) interact with the host, from disrupting the existing genes and pathways to creating novel gene products and expression patterns, enhancing the repertoire of host functions, and ultimately driving host evolution. The meeting was organized into six plenary sessions and two afternoon workshops with a total of 50 invited and contributed talks, two poster sessions, and a career roundtable. The topics ranged from TE roles in normal and pathological processes to restricting and harnessing TE activity based on mechanistic insights gained from genetic, structural, and biochemical studies.