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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. 

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.

 

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. 

Human activities are accelerating rates of biological invasions and climate-driven range expansions globally, yet we understand little of how genomic processes facilitate the invasion process. Although most of the literature has focused on underlying phenotypic correlates of invasiveness, advances in genomic technologies are showing a strong link between genomic variation and invasion success. Here, we consider the ability of genomic tools and technologies to (i) inform mechanistic understanding of biological invasions and (ii) solve real-world issues in predicting and managing biological invasions. For both, we examine the current state of the field and discuss how genomics can be leveraged in the future. In addition, we make recommendations pertinent to broader research issues, such as data sovereignty, metadata standards, collaboration, and science communication best practices that will require concerted efforts from the global invasion genomics community. 

Abstract We consider the simultaneous propagation of two contagions over a social network. We assume a threshold model for the propagation of the two contagions and use the formal framework of discrete dynamical systems. In particular, we study an optimization problem where the goal is to minimize the total number of new infections subject to a budget constraint on the total number of available vaccinations for the contagions. While this problem has been considered in the literature for a single contagion, our work considers the simultaneous propagation of two contagions. This optimization problem is NP-hard. We present two main solution approaches for the problem, namely an integer linear programming (ILP) formulation to obtain optimal solutions and a heuristic based on a generalization of the set cover problem. We carry out a comprehensive experimental evaluation of our solution approaches using many real-world networks. The experimental results show that our heuristic algorithm produces solutions that are close to the optimal solution and runs several orders of magnitude faster than the ILP-based approach for obtaining optimal solutions. We also carry out sensitivity studies of our heuristic algorithm.