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Unanticipated Emergence of the Photo‐Switchable Cs ⁺ ‐Selective Ion Channels From One‐Dimensional 18‐Crown‐6 Arrays

ABSTRACT A photo‐regulated cesium ion channel—the first artificial ion channel of its kind—has been successfully constructed using a small‐molecule self‐assembly strategy. This breakthrough emerged from an initial effort to design a light‐responsive potassium ion channel, incorporating azobenzene‐modified 18‐crown‐6 units, amino acid residues, and side chains. Unexpectedly, the azobenzene‐functionalized 18‐crown‐6 units displays a surprising and previously unrecognized capability for transporting Cs + ions. Among the six channels studied, trans ‐isomers t ‐F and t ‐L exhibit the highest Cs + transport rates. They also demonstrate pronounced ion selectivity, with Cs + /K + selectivity ratios of 2.66 and 2.03, and markedly higher Cs + /Na + selectivity ratios of 32.1 and 31.5, respectively. Moreover, by alternating exposure to ultraviolet and visible light, the opening and closing of these channels can be effectively and reversibly controlled, resulting in a 4‐fold difference in ion transport activity between the trans ‐ and cis ‐configured channels. This work establishes, for the first time, that the 18‐crown‐6 motif can be rationally engineered for selective Cs + transport, thereby broadening its potential applications in ion‐transport systems and separation technologies.

Unlocking the financing potential of forest-based carbon assets: a valuation framework for pledge lending under uncertainty in China

Abstract Forest-based carbon assets are increasingly proposed as collateral for green credit, yet a central problem remains unresolved: a higher collateral valuation does not necessarily translate into greater lendable value. Here we develop a contract-consistent framework for pricing forest-based carbon collateral under uncertainty and apply it to the Ning’er afforestation case in Yunnan, China, covering 51,365 mu and 719,680 t $${CO}_{2}$$ e of expected carbon assets. The framework combines weekly carbon-price forecasting from thin and irregular China Certified Emission Reduction (CCER) trading data with threshold-based option valuation and a lender-oriented pledge-rate equation anchored to the observed three-year loan structure. Using weekly pre-loan transactions from 31 August 2018 to 30 September 2022, we show that incorporating uncertainty and timing flexibility raises the option-adjusted collateral value to CNY 71.87 million. However, once effective deliverability, downside protection and prudential threshold calibration are imposed, the model-implied lower-bound pledgeable amount is only CNY 5.92 million, below the realised loan of CNY 12 million. Sensitivity analysis further shows that financing capacity is jointly shaped by carbon price, effective deliverability, volatility identification and threshold calibration. Our results show that valuing forest-based carbon assets for lending is not a single-stage asset-pricing problem, but a constrained translation problem between economic collateral value and lender-recognised lendable value.

A Semi-Markov framework for modeling football possessions and temporal expected threat

Isomerized Dithienopyrazine‐Based Solid Additive Enables Organic Solar Cells With 20.5% Efficiency

ABSTRACT Solid additives have emerged as a widely adopted strategy in organic solar cells (OSCs) due to their efficacy in modulating the film morphology and regulating the aggregation behavior of the photoactive layer, which is crucial for achieving high power conversion efficiencies (PCEs). However, the chemical structure of these solid additives fundamentally dictates their performance. Herein, we designed two isomeric solid additives, syn ‐dithieno[2,3‐ b :3',2'‐ e ]pyrazine ( syn ‐DTPy) and anti ‐dithieno[2,3‐ b :2',3' ‐e ]pyrazine ( anti ‐DTPy), to enhance OSCs’ performance. When incorporated into the D18:L8‐BO system, anti ‐DTPy establishes directional intermolecular interactions that optimize phase separation and charge transport pathways. This approach enabled OSCs to achieve a remarkable PCE of 20.5%, with a high fill factor (FF) of 81.9%, ranking among the highest reported values. This study reveals a distinct isomer‐dependent conformational effect for morphology control, providing profound insights into structure‐property relationships and guiding the design of advanced solid additives.

Comparison of immediate therapeutic effects of 3% diquafosol and 2% rebamipide in dry eye disease: a prospective, randomized, paired-eye trial

Highly Dispersed Molybdenum Carbide Clusters Enable Efficient CO ₂ Hydrogenation

ABSTRACT The reverse water–gas shift (RWGS) offers a promising route to convert CO 2 into CO, a vital feedstock for chemical synthesis. However, the reaction is strongly endothermic and only driven by marginal entropy increasing, requiring high temperature to achieve appreciable CO yields. At such conditions, non‐noble metal catalysts suffer from low activity, and noble metals, though being more active, are prone to deactivation. Here, we report that sub‐nanometer molybdenum carbide (MoC) clusters supported on carbon enable highly efficient and stable RWGS catalysis without noble metals. The catalyst achieves CO formation rate of 1.26 mol CO mol Mo −1 s −1 and mass‐specific activity of 1028 µmol CO g cat −1 s −1 , with near 100% CO selectivity and exceptional stability. Characterizations reveal that MoC spontaneously disperses as sub‐nanometer clusters on support, maximizing the density of coordinatively unsaturated surface sites. These sites facilitate efficient CO 2 adsorption/activation, enabling rapid removal of surface oxygen species. Density functional theory calculations show that highly dispersed MoC sites exhibit distinct local environment, which accounts for weak Mo–O binding and enhances overall catalytic power. This work demonstrates a noble‐metal‐free catalyst that couples high activity, selectivity, and stability with exceptional atom efficiency, offering robust and sustainable strategy for CO 2 valorization.

Environmental pressure and sensory uncertainty modulate free-throw performance: psychological, neurophysiological, and kinematic evidence

Hydrophobic porous polysulfone membrane contactors with gravity-driven Ca(OH)2 absorption for low-energy CO2 removal from biogas

High‐Efficiency All‐Polymer Solar Cells: Toward Sustainable Smart Windows With Flexibility, Semitransparency, and Thermal Insulation

ABSTRACT Layer‐by‐layer (LBL) all‐polymer solar cells (all‐PSCs) feature flexible modulation of donor/acceptor morphology and crystallinity, a unique merit for unlocking maximum material potential toward high efficiency, while rational selection of donor/acceptor regulators is crucial for advanced device fabrication. In this study, 1‐methoxynaphthalene (1‐MeON) is identified as an additive capable of inducing ordered stacking of classic polymer donors (D18, PM6 and PBQx‐TF). Building on this, we employed distinct additives to independently optimize the ordered stacking/aggregation of polymer donor and acceptor in LBL all‐PSCs, as well as the vertical phase distribution, which well match the excellent charge management and deliver an outstanding efficiency of 20.03% (certified 19.60%) for rigid and 18.76% for flexible binary devices. Importantly, this combined strategy further enables thickness‐tunable donor layers to balance efficiency and transmittance, facilitating high‐performance semitransparent devices. The rigid semitransparent all‐PSC achieves an efficiency of 16.07% with transmittance of 20.1%, while the flexible counterpart reaches an efficiency of 15.17% and retains over 96% of its initial efficiency after 1000 bending cycles. Moreover, these semitransparent devices also demonstrate excellent thermal insulation (reducing temperature over 10 degrees celsius). This achievement establishes a pivotal paradigm for high‐efficiency all‐PSCs and verifies their immense practical application in sustainable smart windows.

The role of serum oxytocin levels in the third trimester of pregnancy in the incidence of postpartum depressive symptoms

Suppressing Metallic Co ⁰ Formation in Co‐Based Catalyst by In‐Situ Selective H ₂ Oxidation for Efficient Ethane Dehydrogenation

ABSTRACT Cobalt‐based catalysts are attractive for ethane dehydrogenation owning to their high ethane activation activity. However, in the H 2 ‐rich environment generated during the reaction, cobalt species are readily reduced to metallic Co 0 , leading to coke deposition and catalyst deactivation. Here, we present a tandem strategy that integrates a CoO x /HZSM‐5 (Co/HZ) dehydrogenation catalyst with CeO 2 ‐promoted Bi 2 O 3 (CeBiO x ) as a selective H 2 oxidation oxygen carrier. Under chemical looping oxidative dehydrogenation (CL‐ODH) conditions, CeBiO x selectively oxidizes over 75% of the in‐situ generated H 2 , thereby effectively suppressing the formation of metallic Co 0 in Co/HZ. As a result, an ethane conversion of 40% and an ethylene selectivity exceeding 80% are achieved at 600°C, with stable performance maintained over 100 redox cycles. Pulse reaction experiments, semi in‐situ characterizations, and density functional theory (DFT) calculations collectively reveal that the selective oxidation of H 2 by CeBiO x inhibits the reduction of cobalt species to Co 0 , thereby mitigating coke formation and enhancing ethylene yield. By coupling an ethane dehydrogenation catalyst with a selective H 2 oxidation oxygen carrier, this work establishes a new paradigm for stabilizing active Co species in Co‐based ethane dehydrogenation systems and intensifying ethylene production.

Correction: Acute beetroot juice supplementation enhances short duration high-intensity exercise performance and influences muscle oxygenation in football players

An explainable AI framework integrating machine and deep learning models for multi-species DNA functional group classification

Abstract DNA functional group classification across species plays a crucial role in understanding genetic diversity, evolutionary relationships and biological function. The increasing availability of genomic data has led to the use of machine learning and deep learning methods for identifying functional patterns within DNA sequences. However, the interpretability of these models remains a challenge in validating biological relevance. This study presents an explainable AI framework that integrates machine learning and deep learning models for multi-species DNA functional group classification. The functional groups represent gene families, including transcription factors and kinases, and the classification task is carried out on Human, Chimpanzee, Dog, and a custom Combined dataset merging sequences from all three species. The DNA sequences were transformed into k-mers to capture local compositional patterns before training. Following a controlled hyperparameter tuning strategy, the Logistic Regression model consistently achieved the highest MCC and F1-scores across all evaluated datasets. While deep learning architectures captured longer motif dependencies, classical models showed stronger generalization across species. A multi-level XAI analysis was conducted using techniques such as Feature Importance, Saliency Maps, Integrated Gradients, GradientSHAP, and Attention Heatmaps. The analysis identified consensus motifs, cross-dataset and cross-model motif patterns, and evaluated model stability based on motif overlap and Jaccard similarity, as well as model fidelity based on performance drops after masking model-identified motifs.

A Decoupled‐Motif Strategy Directs Supramolecular Charge‐Transfer Architectures Toward Efficient Photocatalytic H ₂ Evolution

ABSTRACT Supramolecular topology dictates the fate of charge‐transfer (CT) excitons in donor–acceptor assemblies. By tailoring the geometric connectivity of NDI–pyrene conjugates (NPCs), we control whether CT channels remain confined or segregate into parallel pathways. Confined topologies localize electron–hole pairs to form emissive CT states, while segregated double‐cable architectures facilitate long‐range charge migration for visible‐light‐driven H 2 evolution. Comprehensive structural and photophysical analyses collectively reveal how topology transforms excited‐state dynamics into distinct photochemical outcomes. This study highlights the design principle of using geometric confinement to link supramolecular assembly with photocatalytic function.

Characterization and machine learning based optimization of banana and paddy straw fiber reinforced epoxy hybrid composites

Challenging the paradigm that neonatal uterine bleeding represents the first menstrual episode

Effect of Antagonistic Binder–Catalyst Interactions on Catalytic Activity in Lithium–Sulfur Batteries

ABSTRACT Lithium‐sulfur (Li‐S) batteries are a promising next‐generation energy storage solution, as they can reduce reliance on critical transition metals while offering high energy densities. However, their deployment is hindered by low sulfur utilization and the formation/diffusion of lithium polysulfides (LiPSs). While transition‐metal catalysts and polymeric binders have been independently developed to enhance redox kinetics and LiPS adsorption, their mutual compatibility has remained largely unexplored. We show here that binder‐catalyst interactions can significantly impact catalytic performance. Employing TiO 2 as a generic catalyst, the electrochemical performance is shown to depend strongly on the binder environment. TiO 2 paired with lithiated polyacrylic acid (LiPAA) shows benign interactions, resulting in enhanced cycle life. In contrast, pairing TiO 2 with protonated PAA produces antagonistic interactions that hinder Li 2 S growth. A mechanistic analysis unveils that the carboxylic H atom in PAA promotes COO − coordination to Ti sites, occupying catalytic centers and suppressing LiPS adsorption, increasing charge transfer and diffusion resistances. This phenomenon is observed across multiple catalysts, indicating that COOH‐functionalized binders may broadly hinder catalytic activity. Overall, this study underscores the need for holistic cathode design and identifies binder‐catalyst compatibility as an important parameter for high‐performance Li‐S batteries.

Evaluation of a behavioral intervention to support adolescents undergoing bariatric surgery using the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework

Isolation and Reactivity of a Square‐Planar Trisamido Silane

ABSTRACT Square‐planar coordination at tetravalent silicon is highly disfavored, rendering structurally authenticated Si(+IV) complexes of this type exceedingly rare. Herein, we report the synthesis and isolation of a square‐planar silicon(+IV) hydride supported by an unsymmetric, trianionic N , N , N ‐pincer ligand with a dearomatised backbone. Single‐crystal X‐ray diffraction confirms a strictly planar, four‐coordinate silicon centre, with spectroscopic data and quantum‐chemical calculations providing complementary support for this bonding motif. Reactivity studies demonstrate element–ligand cooperative substrate activation driven by ligand rearomatisation, thereby paralleling constant‐oxidation‐state transformations in late transition metal systems and challenging the prevailing reliance on low‐valent p‐block species for bond activation.