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ABSTRACT Here we introduce an electrochemical strategy for the selective and quantitative removal of thiocarbonylthio end groups from polymers prepared by reversible addition–fragmentation chain transfer (RAFT) or photoiniferter polymerization. Our results indicate that applying a cathodic potential in an undivided cell promotes reductive cleavage of the thiocarbonylthio moiety, generating terminal polymer radicals that are efficiently capped with hydrogen atoms in the presence of benign donors. This transformation proceeds cleanly across diverse polymer backbones and end‐group chemistries, including trithiocarbonates and dithiobenzoates, without chain coupling or degradation. Moreover, the applied potential can be tuned to enable chemoselective end‐group removal in mixed‐polymer systems, a level of control inaccessible by thermal, photochemical, or nucleophilic strategies. Beyond delivering colorless and optically transparent materials, electrochemical end‐group removal significantly enhances polymer stability. Poly(methyl methacrylate) subjected to electrochemical end‐group removal exhibited aT₉₅of 342 °C, exceeding the stabilities of analogous polymers with end groups removed by aminolysis (T₉₅= 260 °C) or radical‐based methods (T₉₅= 299 °C). These findings demonstrate redox‐directed post‐polymerization modification as a tool for designing robust, transparent, and thermally stable macromolecules and establish electrochemistry as a platform strategy in polymer synthesis and processing. 

The challenges of monitoring wildlife often limit the scales and intensity of the data that can be collected. New technologies—such as remote sensing using unoccupied aircraft systems (UASs)—can collect information more quickly, over larger areas, and more frequently than is feasible using ground‐based methods. While airborne imaging is increasingly used to produce data on the location and counts of individuals, its ability to produce individual‐based demographic information is less explored. Repeat airborne imagery to generate an imagery time series provides the potential to track individuals over time to collect information beyond one‐off counts, but doing so necessitates automated approaches to handle the resulting high‐frequency large‐spatial scale imagery. We developed an automated time‐series remote sensing approach to identifying wading bird nests in the Everglades ecosystem of Florida, USA to explore the feasibility and challenges of conducting time‐series based remote sensing on mobile animals at large spatial scales. We combine a computer vision model for detecting birds in weekly UAS imagery of colonies with biology‐informed algorithmic rules to generate an automated approach that identifies likely nests. Comparing the performance of these automated approaches to human review of the same imagery shows that our primary approach identifies nests with comparable performance to human review, and that a secondary approach designed to find quick‐fail nests resulted in high false‐positive rates. We also assessed the ability of both human review and our primary algorithm to find ground‐verified nests in UAS imagery and again found comparable performance, with the exception of nests that fail quickly. Our results showed that automating nest detection, a key first step toward estimating nest success, is possible in complex environments like the Everglades and we discuss a number of challenges and possible uses for these types of approaches. 

ABSTRACT Freezing rain is a common winter weather hazard across eastern North America, resulting in damage and disruption to energy utilities, transportation, and the economy. Due to its short lasting and self‐limiting nature, observational gaps, and the need for high temporal and spatial resolution model output, this phase type is less studied in the context of climate change. Through the application of freezing rain regimes identified from prior analysis combined with additional data spanning from 2000 to 2013, a comparative analysis of historical and perturbed global warming simulations of freezing rain events is conducted. Regime‐based evolutions of precipitation type, rates, event duration, and thermal features are explored. Additionally, a novel storm‐relative compositing technique that identifies the degree of geospatial shifts in phase types and other metrics is used. Notable changes to the median values were identified, including a 258 km shift north for the primary freezing rain axis. A general increase in total precipitation (17.9%) was noted, driven by increases in rain (39%) and decreases in snow (−19.8%) and freezing rain precipitation (−14.5%). However, in two of the four full‐area regimes, freezing rain minimally declined (regime 1) or slightly increased (regime 4). These regimes were generally associated with cooler onset conditions, which in a warmer climate permitted more mixed‐phase precipitation due to increasing warm‐layer depth and magnitude, and warming the sub‐freezing surface layer to favour supercooling. This regime‐based framework thus permits us to better identify how the evolution of a winter weather event will influence how it responds to a late 21st century atmosphere. 

ABSTRACT Energy conservation by the electron transport chain (ETC) is a fundamental cellular process. Utilising membrane‐bound protein complexes, the ETC allows cells to conserve chemical energy into proton motive force (PMF), which further drives the production of adenosine triphosphate (ATP) used for cell chemistry. In bacteria, diverse respiratory chain compositions exist, enabling them to adapt and thrive in a variety of habitats. In this mini‐review, we discuss the energetic efficiency of bacterial respiratory chains to reveal underlying design principles and further explore its implications in supporting survival of bacteria utilising different energy sources. Particularly, our cross‐database analyses suggest that the incorporation of cytochromebc₁complexes in ETCs, which enables efficient PMF generation, is associated with the dominant bacterial taxa in global oceans and soil, thus highlighting the ecological significance of ETC energetic efficiency. 

Abstract Freezing rain is highly disruptive to society, ecology, and transportation; however, the driving physical processes governing variability and trends in freezing rain have not been extensively studied. This work investigated the temporal and spatial variability of freezing rain occurrence across eastern North America, using ERA5 reanalysis data from 1941 to 2020. After validation of freezing rain frequencies over time using 132 station sites, relationships between freezing rain and several modes of natural variability that influence North American temperature and hydroclimate are investigated across subdomains. Additionally, random forest regression analysis was used to examine nonlinear relationships between freezing rain and natural variability. Results indicate that within the eastern continental United States, freezing rain is more common with a weaker Aleutian low/anomalous ridge, or a negative Pacific–North American pattern—linked to Alaskan/North Pacific ridging—and cold air intrusion into continental North America. The long-duration modes (e.g., decadal oscillations) generally exert weaker influence at the studied time scales but can modulate the effect of some of the other modes. When evaluating these patterns using random forest, nonlinearities become apparent, particularly with the Arctic Oscillation and El Niño–Southern Oscillation, where highly positive and negative values are linked to more freezing rain in some domains. The analysis also revealed a generally limited signal for significant trends in freezing rain over time, though northernmost domains show increases. The fact that notable trends in freezing rain frequency (particularly decreasing trends in the south) have not yet occurred considering global climate change indicates that the role of natural climate variability is the dominant driver of historical variations. Significance StatementThe purpose of this study was to examine long-term trends in freezing rain across central and eastern North America. The study first evaluated frequencies over time, noting that there are limited overall trends (increasing and decreasing). One of the main reasons for this is due to the important role that natural climate variability plays in modulating the occurrence of freezing rain events. Natural climate variability that promotes higher atmospheric pressure over the Pacific sub-Arctic regions appears to be strongly indicative of favorable conditions for freezing rain, particularly in the United States. This work extends our knowledge of the important factors that drive seasonal to multiyear freezing rain variability. 

Abstract Vitrimers, a class of covalent adaptable networks (CANs), promise sustainability through recyclability and reprocessability, yet suffer from creep under prolonged stress due to dynamic bond exchange. Here, a materials design strategy is reported that integrates polymerization‐induced self‐assembly (PISA) to embed core‐crosslinked nanoparticles within vitrimer networks, yielding hierarchical dual‐crosslinked systems with a reduction of creep susceptibility by up to 90% at 150 °C yet good reprocessability at elevated temperatures (E_a= 246 kJ mol⁻¹). These spherical nanostructures restrict chain mobility and act as rheological modifiers that can be synthetically tuned through core block length. This approach offers precise architectural control, leveraging nanoparticle phase morphology to direct bulk vitrimer properties. This study establishes a new paradigm for creep‐resistant CANs and showcases how PISA can advance vitrimer performance by structurally encoding mechanical robustness and reprocessability.