Browse Articles

Default-threshold operating-point validation of a commercial chest radiograph AI system for selected CT-anchored thoracic findings: a bi-national multicenter retrospective study

Abstract This retrospective bi-national multicenter diagnostic accuracy study evaluated the locked default-threshold performance of a commercial chest radiograph AI system for selected thoracic findings using a CT-anchored, radiographic-detectability reference framework. Consecutive eligible adult patients who underwent frontal chest radiography and chest CT at four tertiary-care centers in Turkey and Bulgaria between June and December 2024 were included. Reference labels were assigned using temporally paired CT, with adjudication of whether CT-confirmed abnormalities had a corresponding radiographic manifestation on the paired chest radiograph. For potentially dynamic findings, the allowable CT–CXR interval was restricted to ≤ 2 days. The AI system was evaluated at the manufacturer’s default threshold of 0.50. Diagnostic performance was summarized using prevalence, sensitivity, specificity, positive predictive value, negative predictive value, and false-positive burden with 95% confidence intervals. The study included 940 patients with paired CXR-CT examinations. Reference-positive prevalence ranged from 2.2% for pneumothorax to 21.0% for pleural effusion. Sensitivity was highest for fracture (91%) and pneumothorax (90%) and lowest for atelectasis (64%); specificity ranged from 82% for consolidation/opacity to 98% for fracture and pneumothorax. PPV ranged from 43% to 63%, indicating a non-trivial false-positive burden at the evaluated operating point. Because continuous probability scores, human-reader comparison, and workflow outcomes were unavailable, these findings should be interpreted as default-threshold technical validation and support further evaluation of the system as radiologist-supervised decision support with local performance monitoring, rather than standalone diagnosis.

Gut acidification impairment links altered acidogenic microbiota to infantile eczema: a cross-sectional study

Agent-based modeling of low-emission fertilizer adoption for dairy farm decarbonisation using empirical farm data

A lightweight underwater biological object detector with enhanced cross-scale feature interaction

Abstract Underwater biological object detection is important for intelligent marine monitoring, yet its performance is often limited by severe image degradation, background clutter, and large variations in target scale. These factors can weaken feature representation during multi-scale fusion and reduce localization reliability in lightweight detectors. In this study, we propose UD-YOLO, a lightweight underwater object detector designed to improve cross-scale feature interaction and localization stability under degraded underwater conditions. The framework enhances contextual representation in the backbone, stabilizes bidirectional information propagation in the neck, and improves multi-scale localization with a lightweight shared detection head and scale-aware regression supervision. On the RUOD dataset, UD-YOLO improves mAP@0.5:0.95 by 2.1% points over YOLOv11n, while reducing parameter count by 0.1 M and computational cost by 0.2 GFLOPs. Additional evaluations on the URPC and DUO show consistent gains over YOLOv11n under different underwater benchmark settings. These results suggest that UD-YOLO provides an effective accuracy-efficiency trade-off for lightweight underwater biological object detection.

Community-based health insurance enrollment and service experiences in Ethiopia’s Somali Region: a sequential explanatory mixed-methods study

Abstract Community-based health insurance (CBHI) is a key strategy for improving financial protection and access to healthcare in Ethiopia; however, evidence from pastoralist settings remains limited. This sequential explanatory mixed-methods study assessed CBHI enrollment, determinants, and healthcare service experiences among 600 adult patients attending three public hospitals in Ethiopia’s Somali Region between July and August 2025. Quantitative data were analyzed using descriptive statistics and multivariable logistic regression, while qualitative interviews with 12 patients and four healthcare providers were analyzed thematically to contextualize the quantitative findings. Although awareness of CBHI was nearly universal (98.3%), only 65.0% of participants were enrolled, and functional knowledge of benefit packages and referral procedures remained limited. Higher educational attainment, greater trust in CBHI management, and stronger perceived benefits were positively associated with CBHI participation, whereas perceived barriers were negatively associated. Medication shortages were the most frequently reported barrier (72.7%). Interviews further revealed that administrative complexity, medicine shortages, long waiting times, and transportation difficulties continued to undermine healthcare experiences despite insurance coverage. Although CBHI enrollment was associated with perceived improvements in healthcare access and financial protection, service experiences remained constrained by persistent health-system limitations. Policymakers should prioritize community education, simplify enrollment procedures, ensure reliable medicine availability, and strengthen CBHI governance and transparency to improve implementation and sustainability in pastoralist settings.

Evaluating LEM, FEM, and DFN approaches for rock slope stability across GSI ranges for open pit mine

Preliminary results on using machine learning methods to predict exercise induced hypoxemia of endurance athletes a posteriori

Quality, reliability, and clinical accuracy of bronchiectasis-related videos on Douyin and Bilibili: a cross-sectional study

Digital entrepreneurship intention among Chinese and Vietnamese students: an EEM-imprinting-informed SEM-ANN model

Investigating self-efficacy as a mediating mechanism between AI-dialogic scaffolding and Saudi learners’ speaking anxiety and confidence

Foreground guided identity and view disentanglement for few-shot ship re-identification

Exploring the potential of Proboscidea louisianica (Martyniaceae) as a live trap for insects, with emphasis on aphids and parasitoids

Metaheuristic optimization of photovoltaic water pumping system using the scalar control of an induction motor drive

A Chemical Framework for Engineering Extracellular Vesicles’ Biointerface to Advance Precision Therapeutics

ABSTRACT Extracellular vesicles (EVs) are membrane‐bound nanoparticles ubiquitously secreted by all cell types and serve diverse physiological and pathological functions. Due to their pivotal roles in pathophysiological processes and their inherent biomimetic properties, EVs have attracted significant attention as biomarkers, as well as for tissue engineering and drug delivery. The surface chemistry of EVs dictates their interactions with their environment. Great strides have been made to tailor this biochemical interface with the aim of enhancing cargo delivery, target specificity, immune evasion, and tracking capabilities, while preserving EVs’ stability and functional integrity. Approaches to surface modification primarily encompass genetic and metabolic manipulation of parent cells, application of physical forces, and chemical reactions. In this manuscript, we introduce a comprehensive chemistry‐centric framework for EV surface engineering that integrates demonstrated EV modification strategies with protein‐ and cell‐surface chemistries not yet applied to EVs, delineating their functional scope and translational potential for advancing EV‐based therapeutics.

Fundamentals to Prospects: Synthetic Tuning of Covalent Organic Frameworks for Solid‐State Hydrogen Storage

ABSTRACT Achieving optimal hydrogen storage performance in covalent organic frameworks (COFs) requires precise synthetic tuning to balance pore architecture, functionalization, and structural stability while ensuring scalability. However, significant challenges remain in translating laboratory‐scale advancements into practical applications. This review critically examines the key challenges in COF synthesis, including the trade‐off between porosity and functionalization, the need for precise control over hierarchical pore structures, and limitations in reproducibility and large‐scale fabrication. We highlight the bottlenecks in current synthetic strategies, such as the difficulty in maintaining crystallinity while achieving high hydrogen binding affinity, and the challenges of integrating scalable synthesis techniques without compromising material performance. We explore emerging scalable synthesis approaches, including microwave‐assisted, mechanochemical, and interfacial synthesis, which offer pathways toward industrial feasibility. Additionally, we discuss the future prospects of COF design, emphasizing the role of machine learning, high‐throughput screening, and predictive modeling in accelerating material discovery and optimization. By integrating computational and experimental insights, we propose a data‐driven roadmap for guiding the rational design of COFs, aiming to bridge the gap between fundamental research and practical hydrogen storage applications.

From Solution to Stretched Film: Probing and Controlling Microstructure in Conjugated Polymer Systems for Emerging Stretchable Organic Photovoltaics

ABSTRACT The advancement of stretchable organic photovoltaics is hindered by a fundamental trade‐off between high optoelectronic performance and mechanical durability, in particular, a challenge rooted in the complex microstructure of conjugated polymers and their blends. This review addresses a critical literature gap on the microstructure of various conjugated polymer systems by systematically examining how multiscale microstructural evolution, from solution‐state aggregation to solid‐state morphology and dynamic response under strain, can be characterized, understood, and rationally controlled. Analysis begins with how advanced X‐ray and neutron scattering techniques elucidate the formative solution‐aggregation structures that dictate the final solid‐state morphology. Subsequently, multiscale characterization methods for thin films are reviewed, alongside material design strategies, such as elastomeric modifiers, engineered to optimize phase‐separated morphologies for simultaneous conductivity and mechanical flexibility. A key focus is the transition beyond static X‐ray scattering analysis to explore the dynamic evolution of microstructure under mechanical stretching, thereby underscoring the pivotal role of in situ and operando characterization in revealing deformation and failure mechanisms. By integrating insights across these scales, this review aims to distill rational design principles, offer a coherent processing‐structure‐performance framework, and provide a complete picture for the predictive design of next‐generation intrinsically robust stretchable photovoltaics and related electronics.

Mechanical‐Electrochemical Coupling Enables Pressure‐Informed Diagnosis and Interfacial Self‐Leveling in Sodium‐Ion Batteries

ABSTRACT Sodium (Na)‐ion batteries (NIBs) are attractive for sustainable energy storage because of the abundance and low cost of Na resources. However, their practical fast‐charging operation is severely challenged by metallic Na plating, continuous interfacial degradation, and the associated safety risks. Here we establish a quantitative mechanical‐electrochemical coupling framework that links macroscopic pressure signals with microscopic electrode reactions, enabling real‐time and nondestructive diagnosis of Na plating in NIBs. On this basis, we develop an integrated diagnose‐repair‐utilize management strategy (DRUMS) that shifts battery management from passive warning to active intervention. Beyond early identification of hazardous metallic Na plating, DRUMS further induces dual‐interfacial self‐leveling by redirecting plated Na at the anode into an in situ Na source for reconstruction of the cathode interphase, while simultaneously eliminating unsafe metallic Na accumulation on the anode. This coupling‐enabled strategy mitigates interfacial deterioration and markedly enhances the cycling stability of fast‐charging NIBs. More broadly, this work provides a mechanistically guided strategy for dynamic interface management and offers a practical route toward safer and more durable fast‐charging batteries.

High‐Entropy Ceramic‐Enhanced Deformable Triboelectric Nanogenerator for Noncontact Biomechanical and Raindrop Energy Harvesting

ABSTRACT To address interfacial friction losses associated with physical contact separation in triboelectric nanogenerators (TENGs), noncontact or liquid‐solid‐contact TENGs have recently been developed. However, the limited performance of noncontact TENGs has hindered their further advancement. This study proposed a large‐area deformable high‐entropy ceramic (HEC)‐enhanced noncontact TENG (HEC‐TENG) by integrating an HEC‐doped silicone triboelectric layer with a charge‐storage graphitic textile and a stretchable carbon black electrode. This strategy establishes a comprehensive tribo‐charge regulation mechanism, including charge generation, capture, transport, and retention, resulting in a noncontact output of 90 V and 450 µA m −2 at a separation distance of 1 mm, while maintaining a stretchability exceeding 230%. Notably, by leveraging the synergistic effects of HEC doping and the trilayer composite configuration, the HEC‐TENG achieved a maximum voltage of 466 V for droplet‐based energy harvesting. Furthermore, wearable power sources and large‐area rainwater‐harvesting systems enabled by HEC‐TENGs were demonstrated. Overall, this work validates the universal enhancement effect of HECs when employed as triboelectric layers in both noncontact and liquid‐solid contact TENGs, establishing a representative paradigm for the development of wearable HEC‐based TENGs. These findings provide new insights into future wearable self‐powered electronics and distributed energy‐harvesting systems.

Integration of High‐κ and Ultrawide Bandgap Single‐Crystalline Beryllium Borate Dielectric for 2D Electronics

ABSTRACT The development of van der Waals (vdW) dielectric materials with high dielectric constants and wide bandgaps is crucial for advancing the practical application of two‐dimensional (2D) transistors. However, current dielectrics often exhibit advantages in only one of these two aspects, which limits the further improvement of transistor performance. This study demonstrates an ideal dielectric NH 4 Be 2 BO 3 F 2 (ABBF) for 2D electronic devices, which exhibit a high dielectric constant up to 39 and a wide bandgap of 8.1 eV. Dielectric performance tests show that it has an ultralow leakage current density (≈ 10 −8 A cm −2 ) and a robust breakdown field (12.6 MV cm −1 ). The MoS 2 field‐effect transistors (FETs) gated by ABBF achieve a high on/off ratio of 2 × 10 9 , near‐Boltzmann‐limit subthreshold swing (60 mV dec −1 ), and negligible hysteresis of 2.7 mV. Benefiting from its inert vdW surface, ABBF forms a high‐quality MoS 2 /ABBF interface with an extremely low density of trap states ( D it ≈ 4.6 × 10 10 cm −2 eV −1 ). In addition, high‐κ ABBF dielectrics were also applied for fabricating short‐channel MoS 2 FETs and high‐gain logic inverters. This research enlarges the pool of dielectric candidates and unlocks new possibilities for advancing low‐power electronics and integrated circuits.

Pollen‐Based Artificial Enzyme With Efficient Biocatalysis and Immune‐Priming to Prevent Primary and Secondary Wound Infection

ABSTRACT Bacterial infection poses a significant threat to clinical treatment due to the emergence of drug resistance and the high risk of recurrence. Here, we report the de novo design of a spiky pollen‐based vanadium artificial enzyme particle (VAE‐Pollen) that integrates potent reactive oxygen species (ROS)‐catalytic activity with immune priming to prevent both primary and secondary bacterial infections. Experimental and theoretical analyses confirm that bacteria are efficiently captured by the micro‐structured surface of VAE‐Pollen, and the introduction of oxygen vacancies modulates the electronic configuration of vanadium catalytic sites, significantly enhancing their versatile ROS‐catalytic performance. Meanwhile, VAE‐Pollen enhances bacterial capture and ROS‐triggered release of bacterial antigens, which mimics the sustained allergen exposure characteristic of natural pollen, thereby potently activating systemic defensive responses and providing sustained anti‐infective surveillance to prevent secondary wound infection. Notably, the VAE‐Pollen demonstrates significant efficacy in treating methicillin‐resistant Staphylococcus aureus ( MRSA ) and preventing its recurrence, offering a potent and intelligent antibacterial alternative that may circumvent the limitations of conventional antibiotics.