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Cold sintering enabled the upcycling of polypropylene with gypsum (CaSO₄) into a fully recyclable composite, paving the way for the integration of waste into high-performance, recyclable composites. 

Beneficial relationships between animals and microbial organisms (symbionts) are ubiquitous in nature. In the ocean, microbial symbionts are typically acquired from the environment and their composition across geographic locations is often shaped by adaptation to local habitat conditions. However, it is currently unknown how generalizable these patterns are across symbiotic systems that have contrasting ecological characteristics. To address this question, we compared symbiont population structure between deep-sea hydrothermal vent mussels and co-occurring but ecologically distinct snail species. Our analyses show that mussel symbiont populations are less partitioned by geography and do not demonstrate evidence for environmental adaptation. We posit that the mussel's mixotrophic feeding mode may lower its need to affiliate with locally adapted symbiont strains, while microhabitat stability and symbiont genomic mixing likely favors persistence of symbiont strains across geographic locations. Altogether, these findings further our understanding of the mechanisms shaping symbiont population structure in marine environmentally transmitted symbioses. 

Abstract All‐solid‐state batteries have the potential for enhanced safety and capacity over conventional lithium ion batteries, and are anticipated to dominate the energy storage industry. As such, strategies to enable recycling of the individual components are crucial to minimize waste and prevent health and environmental harm. Here, we use cold sintering to reprocess solid‐state composite electrolytes, specifically Mg and Sr doped Li₇La₃Zr₂O₁₂with polypropylene carbonate (PPC) and lithium perchlorate (LLZO−PPC−LiClO₄). The low sintering temperature allows co‐sintering of ceramics, polymers and lithium salts, leading to re‐densification of the composite structures with reprocessing. Reprocessed LLZO−PPC−LiClO₄exhibits densified microstructures with ionic conductivities exceeding 10⁻⁴ S/cm at room temperature after 5 recycling cycles. All‐solid‐state lithium batteries fabricated with reprocessed electrolytes exhibit a high discharge capacity of 168 mA h g⁻¹at 0.1 C, and retention of performance at 0.2 C for over 100 cycles. Life cycle assessment (LCA) suggests that recycled electrolytes outperforms the pristine electrolyte process in all environmental impact categories, highlighting cold sintering as a promising technology for recycling electrolytes. 

While the popularity of online social network (OSN) apps continues to grow, little attention has been drawn to the increasing cases of Social Network Addictions (SNAs). In this paper, we argue that by mining OSN data in support of online intervention treatment, data scientists may assist mental healthcare professionals to alleviate the symptoms of users with SNA in early stages. Our idea, based on behavioral therapy, is to incrementally substitute highly addictive newsfeeds with safer, less addictive, and more supportive newsfeeds. To realize this idea, we propose a novel framework, called Newsfeed Substituting and Supporting System (N3S), for newsfeed filtering and dissemination in support of SNA interventions. New research challenges arise in 1) measuring the addictive degree of a newsfeed to an SNA patient, and 2) properly substituting addictive newsfeeds with safe ones based on psychological theories. To address these issues, we first propose the Additive Degree Model (ADM) to measure the addictive degrees of newsfeeds to different users. We then formulate a new optimization problem aiming to maximize the efficacy of behavioral therapy without sacrificing user preferences. Accordingly, we design a randomized algorithm with a theoretical bound. A user study with 716 Facebook users and 11 mental healthcare professionals around the world manifests that the addictive scores can be reduced by more than 30%. Moreover, experiments show that the correlation between the SNA scores and the addictive degrees quantified by the proposed model is much greater than that of state-of-the-art preference based models.