Browse Articles

Comparative mitogenomic study of the brown accentor (Prunella fulvescens) and a sympatric relative across an altitudinal gradient

Decoupling Electronic Effects in Oxygen Reduction Catalysts via a Model Nanowire Platform

ABSTRACT Understanding the intrinsic role of electronic structure in governing oxygen reduction reaction (ORR) activity on Pt‐based catalysts remains a long‐standing challenge due to the intrinsic coupling of electronic, strain, and ensemble effects in conventional alloy systems. Here, we establish a well‐defined Pt‐based nanowire (NW) model platform that enables the rigorous decoupling of electronic effects from structural contributions. By selectively incorporating electron‐donating Re (PtRe) or electron‐withdrawing Au (PtAu) into Pt NWs while maintaining identical morphology, surface structure, and coordination environment, the electronic contribution to ORR is isolated with minimal interference of strain and ensemble effects. A consistent activity trend (PtRe > Pt > PtAu) is observed from intrinsic ORR activity to device‐level membrane electrode assembly performance. Crucially, a correlation is established between the electronic structure, intermediate adsorption behavior, and intrinsic activity. Meanwhile, the high‐activity PtRe NW catalyst also delivers a robust durability with mass activity decline of 11.8% and voltage loss of 12 mV after 30,000‐cycle tests. In situ spectroscopy and theoretical calculations results collectively confirm that Re dopants donate electrons to Pt, generating an electron‐rich Pt surface that lowers the adsorption energy of oxygen intermediates and enhances ORR activity, while the Au dopant generates an opposite effect.

Destination image, satisfaction, and perceived value drive tourist loyalty in traditional village tourism

State-variable analysis of pulsed EM-fields in temporally layered media

Protonation‐Triggered Unlocking of Interlayer Carbon Nitride for Rapid Nanosheet Preparation

ABSTRACT The intrinsic topological and electronic merits of graphitic carbon nitride (g‑C 3 N 4 ) are fundamentally obscured by strong π‐π stacking interactions and hydrogen‐bonding interactions. Overcoming these noncovalent barriers without compromising the structural integrity remains a formidable chemical challenge. Herein, we report a targeted electrostatic decoupling strategy via protonation that rapidly unlocks the intralayer framework of g‑C 3 N 4 into discrete, highly crystalline two‐dimensional (2D) nanosheets under ambient conditions. By utilizing trifluoromethanesulfonic acid, selective protonation at the heterocyclic nitrogen sites induces pronounced interlayer electrostatic repulsion and simultaneous intralayer electronic reconstruction, achieving an unprecedented production efficiency of 200 mg·mL −1 ·h −1 . Crucially, the high aspect ratio and structural fidelity of the as‐exfoliated nanosheets enable unambiguous direct observation of the intrinsic lyotropic liquid‐crystalline phase transition in pure g‑C 3 N 4 , resolving long‐standing ambiguities regarding its mesoscopic assembly behavior. Furthermore, the 2D nanosheets display over 50‐fold enhancement in photocatalytic hydrogen peroxide production activity compared to their bulk counterpart, attributed to the reduced thickness and significantly increased exposure of active sites. This work not only provides an efficient route for the exfoliation of layered polymers but also opens new opportunities for their solution‐phase processing.

Intensive care physicians’ experiences of decision fatigue and characteristics of vulnerable clinical decisions

Abstract Decision fatigue (DF) has been proposed to describe changes in decision-making over the course of repeated decisions, but its mechanisms and relevance in clinical practice remain debated. While quantitative studies have reported time-related patterns in medical decisions, qualitative evidence on how DF is experienced and managed in everyday clinical settings is limited. Intensive care units (ICUs), characterised by high decision density, time pressure, and uncertainty, provide a particularly relevant context to explore these processes. This study explored intensive care physicians’ views and experiences on DF and its potential impact on medical decision making in the ICU. 19 semi-structured interviews were conducted in person with ICU physicians from October 2024 to March 2025. All interviews were audio-recorded, transcribed verbatim, and analysed using an inductive thematic analysis approach. Codes and categories were iteratively developed and grouped into higher-level themes and decision characteristics. 19 physicians from three different ICUs participated, including 13 residents and board-certified specialists in executing roles and 6 consultants with supervisory and treatment-planning responsibilities. Three major themes were identified and developed: (1) DF and mental exhaustion occur in the ICU; (2) Perceived effects of DF on decision-making processes and behaviours; and (3) physicians indicate various characteristics of decisions in which the effects of DF are more likely to occur. This study provides new insights into ICU physicians’ experiences of DF and presents a typology of clinical decisions according to their perceived susceptibility to DF as a hypothesis-generating framework. The findings suggest practical implications for workflow design, decision prioritisation, and team-based approaches to support clinical decision-making in the ICU.

Assessing disaster resilience in mountain villages using an improved DPSIR-A framework and multi-model machine learning

Abstract Amid the dual challenges of global climate change and frequent geological hazards, evaluating the disaster resilience of mountainous villages is crucial for sustainable regional development. This study proposes an integrated resilience assessment framework specifically designed for high-altitude, tourism-dependent ethnic villages. The framework extends the classical DPSIR model by incorporating an Adaptability (A) dimension, which quantifies traditional ecological knowledge and community learning capacity. To address the class imbalance typical of small-sample geological hazard datasets, the study integrates the SMOTE oversampling technique with a multi-model evaluation chain (IVM-SVM-RF). This method overcomes the generalization limitations of machine learning models in small-sample environments. The results show: (1) Model Performance Breakthrough: The SMOTE-enhanced Random Forest (S-RF) model outperforms both SVM and IVM models, with the highest performance (AUC = 0.753, Kappa = 0.754). It is particularly effective in identifying low-resilience areas under small-sample conditions, confirming that SMOTE augmentation corrects class imbalance and improves model accuracy in capturing marginal low-resilience zones. (2) Spatial Differentiation: Zhangzha Town exhibits distinct “topography-constrained economic clustering” patterns of resilience. The high-resilience core zone (13.05%) is concentrated in the Ganhaizi sector, driven by socio-economic adaptability, while the extremely low-resilience zone (9.42%) is scattered along the southern periphery, influenced by steep terrain and delayed responses. (3) Nonlinear Drivers: Feature importance analysis identifies Fractional Vegetation Cover, Rainfall, and Distance from Roads as key resilience determinants. Additionally, “soft resilience” factors, such as Building Disaster Resistance and Villagers’ Disaster Awareness, play significant roles in mitigating physical risks.

4‐Formyl‐N‐Methylpyridinium‐Mediated N‐Terminal Cysteine Modification/Removal Facilitates One‐Pot Multiplex Peptide Ligation

ABSTRACT The chemical synthesis of proteins with site‐specific modifications remains a fundamental challenge in chemical biology. One‐pot peptide ligation strategies have emerged as powerful tools to enhance synthetic efficiency, primarily relying on N‐terminal cysteine (Cys) protection. However, current Cys deprotection conditions require various reagents or pH adjustments during the reaction, rendering downstream processing cumbersome. Here, a visible‐light‐mediated deprotection strategy using 2‐(N‐methylpyridinium‐4‐yl)‐thiazolidine (4‐NMP‐Thz) as a novel N‐terminal Cys‐protecting group is reported. This reaction, catalyzed by [Ru(bpy) 3 ]Cl 2 at physiological pH (6.0–8.0), enables smooth one‐pot multi‐segment peptide assembly. The strategy demonstrates complete orthogonality to native chemical ligation (NCL) and desulfurization conditions, eliminating the requirement for intermediate purification or pH adjustment. This methodology was used to facilitate an efficient one‐pot synthesis of a 400‐amino acid (aa) glycosylated MUC1 glycoprotein bearing 40 O‐glycosyl modifications that is difficult to prepare using previously reported techniques. The 400‐aa MUC1 significantly enhanced antigenic immunogenicity compared with shorter MUC1 glycopeptides. This streamlined approach establishes a robust platform for the construction of complex post‐translationally modified proteins.

Effects of adaptive error-threshold practice on soccer instep kick learning

A multi-pollutant air quality health index for assessing mortality risk of ischemic heart disease in Jinan, China

Uncovering Aggregation‐Induced Emission in Carbon Dots for Color‐Changing Hydrogels and Information Encryption

ABSTRACT Since the discovery of carbon dots (CDs), the typical precursor combination of citric acid (CA)‐urea has been widely used in the scientific community to explore the formation mechanism and luminescence behavior of CDs. However, there have only been a few reports on the synthesis of CDs featuring aggregation‐induced emission (AIE) characteristics. In this study, CA and urea were used to synthesize hydrophilic red‐emissive carbon dots (R‐CDs) that exhibit blue fluorescence in water (dispersed state) and red fluorescence in DMF (aggregated state). The study reveals that the photoluminescence of R‐CDs is governed by π–π stacking interactions between solute molecules as well as solvent effects between solute and solvent molecules, leading to solvent‐responsive emission behavior. By tuning the solvent polarity, the intermolecular distance between R‐CDs can be adjusted, thereby influencing their photoluminescent properties. Taking advantage of the solvent‐responsive color change, anticounterfeiting printing and information encryption applications were designed. Moreover, by combining R‐CDs with poly(vinyl alcohol) (PVA), hydrogel‐based fluorescent information‐encoding materials were successfully fabricated.

Physical-chemical gradients, CO2 venting dynamics and microbial community composition in a shallow Mediterranean CO2-rich hydrothermal system

Abstract Shallow-water CO 2 -rich hydrothermal systems provide natural laboratories for studying localized ocean acidification under realistic environmental conditions. Here, we present a multidisciplinary characterization of the Calent mound CO 2 -rich system (Columbretes Islands, Western Mediterranean), based on oceanographic surveys conducted in 2020 and 2021. Localized pH anomalies were detected directly above active vents, reaching maximum reductions of 1.12 pH units, whereas water-column temperature anomalies were minimal and subsurface sediment temperatures exceeded ambient seawater by 5.67 °C. Gas analyses indicated high CO 2 concentrations (0.094 ± 0.008 mol L − 1 ), with heterogeneous degassing regimes, ranging from sporadic to continuous emissions and an average flux of 189.4 ± 15.4 kg CO 2 m − 2 yr − 1 at the active vent field. Vent fluids were significantly enriched in dissolved inorganic nutrients, particularly silicate, phosphate, nitrate+nitrite, and ammonium. Benthic microbial mats hosted metabolically diverse prokaryotic and eukaryotic communities, including hydrothermal-associated taxa such as Zetaproteobacteria, Campylobacterota, and Nitrosophaeria, consistent with iron, sulfur, and ammonia oxididation metabolisms. Several microbial core taxa persisted across years despite shifts in relative abundance. These findings demonstrate that Calent mound sustains an intense yet highly localized biogeochemical environment within the photic zone, where CO 2 venting and nutrient inputs jointly influence carbonate chemistry and microbial community structure.

CO ₂ ‐Derived Degradable Polythioester Adhesives From Proton‐Trap‐Assisted S/O Isomerization‐Driven Cationic Ring‐Opening Polymerization

ABSTRACT The development of degradable pressure‐sensitive adhesives (PSAs) holds great promise for enabling the recycling of adhesive‐containing materials. However, existing degradable PSAs are often constrained by insufficient or moderate adhesion strength, reliance on fossil‐based feedstocks, and/or incomplete degradation. Addressing these challenges requires the development of new polymerization strategies and material designs. Herein, we report a proton‐trap‐assisted S/O isomerization‐driven cationic ring‐opening polymerization of the CO 2 ‐derived thionolactone 3,6‐diethyltetrahydro‐2H‐pyran‐2‐thione, which enables the well‐controlled synthesis of high‐molecular‐weight CO 2 ‐based (co)polythioesters. The resulting materials exhibit a unique combination of high and tunable peel strength (up to 16.43 N/cm), excellent optical clarity (over 96% transmittance, low haze and low yellowness index), and the ability to undergo either complete degradation or quantitative depolymerization under mild conditions, delivering the first practical example of polythioester‐based PSAs. This study establishes a sustainable platform for PSA design that integrates robust performance with full life‐cycle management, thereby advancing the utilization of CO 2 ‐derived materials and circular polymer design.

Micronutrient intake and food insecurity among mothers of infants with orofacial clefts: a cross-sectional study in Iran

Unlocking an All‐Anisotropic‐Component Integrated Paradigm Toward Practical Solid‐State Zinc Metal Pouch Cells

ABSTRACT High‐safety and low‐cost Zn metal batteries hold great promise for energy storage, but their limited energy density remains a major bottleneck restricting their practical development. Here, an all‐anisotropic‐component integrated model with full high‐flux characteristic is presented for enabling high‐specific‐energy devices. By utilizing natural and recyclable wood‐based materials, we validate its feasibility in classic Zn–MnO 2 single‐electron reaction system. Among them, lightweight and carbonized wood material was used to serves as a universal current collector for both MnO 2 cathode and Zn anode. Simultaneously, a phosphate‐modified cellulose‐based hydrogel with vertically aligned channels was fabricated to achieve high electrochemical compatibility between electrode and electrolyte interfaces. As a result, this configuration enables the stable cycling of Zn||Ca‐MnO 2 pouch cells at high mass loading (even up to 50.13 mg cm −2 ), with a wide‐temperature operability (−30°C to 60°C). Impressively, a maximum energy density of 173.2 Wh kg −1 is achieved at the current density of 0.1 A g −1 , exceeding the vast majority of previous findings. Such battery structure model can be applied to both vanadium‐ and manganese‐based cathodes, but also expected to other multielectron reaction systems, promoting the fast development of economical nonlithium energy storage batteries.

Deep learning model for real time moisture content detection and prediction in white tea withering using near infrared spectroscopy

Synergistic Interaction Between N‐Heterocyclic Carbene (NHC)‐Anchored Cu(I) Atom and In Situ‐Generated Cu Nanoparticles in a Post‐Modified MOF‐808 Framework Promoting C─C Coupling in CO ₂ Reduction

ABSTRACT The electrochemical reduction of CO 2 to high‐value chemicals like C 2 H 4 represents a promising route for sustainable energy and CO 2 mitigation. However, its efficiency remains constrained by the high energy barrier for C─C bond formation and the competing hydrogen evolution reaction (HER). Herein, we report a synergistic catalyst for electrochemical CO 2 reduction reaction (eCO 2 RR), which comprises an N‐heterocyclic carbene (NHC)‐anchored Cu(I) atom and in situ electrogenerated Cu nanoparticles in a MOF‐808 framework. The catalyst exhibits outstanding performance in a neutral electrolyte, achieving a high Faradaic efficiency (FE) of 61.0% for C 2 H 4 and 79.5% for total C 2+ products. Experimental and theoretical studies reveal a dual role of the NHC ligand in eCO 2 RR: (i) promoting proton transfer and *CO hydrogenation via a robust hydrogen‐bonding network with interfacial water and (ii) stabilizing key intermediates such as *CHO and *COCHO through its strong electron‐donating ability. The synergy between a molecular NHC‐Cu(I) atom and adjacent Cu nanoparticles in a tailored microenvironment suppresses HER and lowers the energy barrier for asymmetric C─C coupling. This work offers a strategic design concept for constructing molecular‐nanostructured synergistic active sites in metal‐organic frameworks (MOFs) to advance electrocatalytic CO 2 conversion.

Development of surfactin-based nanocarrier for targeted doxorubicin delivery

Abstract Surfactin, one of the most powerful lipopeptide biosurfactants produced by Bacillus subtilis, has great potential for biomedical applications. Isolation, purification, and characterization of surfactin from Bacillus subtilis 6633 to be used as a doxorubicin (Dox) nanocarrier. Purified surfactin using different chromatographic columns was used to prepare a self-assembled nanocarrier for Dox, which was characterized for size, charge, and drug-loading efficiency. Biological activity against normal fibroblast (FB) and liver cancer (HepG2) cells was assessed. The hybrid nanoparticles showed a remarkable drug loading; 36%, a pH-responsive release profile with enhanced cytotoxicity toward HepG2 cells (IC₅₀ = 5.40 µg/mL), and a reduced toxicity to FB cells (IC₅₀ = 12.78 µg/mL). The nanoparticles were spherical in shape (100 ± 2 nm) with a polydisperse index of (0.019 ± 0.01) and a narrow size distribution pattern. The results support the potential of surfactin-based nanoparticles to act as a selective platform for anticancer drug delivery and underscore their relevance towards the Sustainable Development Goal 3 (Good Health and Well-being) through the development of safer and effective therapeutic strategies.

Charge‐Directed Photothermal Methane Dry Reforming Enabled by Interfacial TiO <i> _x </i> Nanodomains

ABSTRACT Photothermal dry reforming of methane (DRM) enables solar‐driven upgrading of CH 4 and CO 2 , yet its efficiency and durability are hindered by carbon deposition and poorly defined photochemical contributions. Here, we demonstrate a charge‐directed photothermal DRM catalyst composed of Rh nanoparticles supported on TiO x ‐functionalized TiC, where interfacial TiO x domains play a critical role by coupling directional photocarrier flow with adaptive oxygen chemistry. Upon illumination, metallic TiC generates charge carriers that transfer electrons to Rh sites while steering holes to TiO x surface oxygens. This charge‐directed interfacial chemistry selectively lowers the barrier for *OCH 3 formation, the potential‐determining step, thus suppressing *CH 3 over‐dehydrogenation and mitigating carbon formation. Concurrently, CO 2 activation at oxygen vacancies within TiO x regions restocks surface oxygens, closing a regenerative photothermal Mars–van Krevelen cycle. As a result, the catalyst delivers high syngas production rates (CO: 17.5 mol g Rh −1 h −1 , H 2 : 10.5 mol g Rh −1 h −1 ), attains a light‐to‐chemical energy efficiency of 29%, and operates stably for over 100 h without coking. This work highlights the mechanistic importance of amorphous TiO x interface in charge‐directed photothermal DRM and provides design insights for developing coking‐resistant reforming catalysts.

A cancelable ear recognition system via optimized deep feature fusion

Abstract The rapid expansion of biometric authentication technologies worldwide has heightened the need for highly reliable and secure identification methods. This research explores the human ear as a distinctive biometric trait, capitalizing on its stable and person-specific anatomical structure. Although ear biometrics offer notable advantages, their practical use is hindered by image variations arising from changes in pose, scale, rotation, illumination, and contrast. To overcome these challenges, this paper presents an innovative deep learning-based ear recognition framework. The proposed approach employs a dual-stream feature extraction strategy that integrates two advanced Convolutional Neural Network (CNN) models MobileNetV3 and DenseNet-121 to derive rich and complementary feature representations, which are subsequently fused. The resulting high-dimensional feature space is then optimized using a Multi-Learning Strategy Golden Eagle Optimization (MLSGEO) algorithm to retain only the most discriminative features. To strengthen security and privacy, the refined feature vector is transformed into a non-invertible, cancelable biometric template using a Comb-filter–based protection mechanism. Data augmentation techniques are further applied to compensate for dataset size limitations. The framework was evaluated on five benchmark ear datasets: AMI, AWE, IITD-I, IITD-II, and UERC, achieving recognition accuracies of 99.90%, 99.64%, 99.78%, 99.32%, and 93.31%, respectively. Experimental findings show that the proposed system outperforms existing state-of-the-art methods. Overall, the integration of robust feature learning with a resilient template protection scheme demonstrates strong potential for secure and high-accuracy biometric authentication applications.