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As an intelligent polymer material, pH-sensitive hydrogels exhibit the capability to dynamically sense alterations in ambient pH levels and subsequently initiate corresponding physical or chemical responses, including swelling, contraction, degradation, or ion exchange. Given the significant pH variations inherent in human pathophysiological microenvironments, particularly in tumor tissues, inflammatory lesions, and the gastrointestinal system, these smart materials demonstrate remarkable application potential across diverse domains such as targeted drug delivery systems, regenerative medicine engineering, biosensing, and disease diagnostics. Recent breakthroughs in nanotechnology and precision medicine have substantially propelled advancements in the design and application of pH-responsive hydrogels. This review systematically elaborates on the current research progress and future challenges regarding pH-responsive hydrogels in biomedical applications, with particular emphasis on their stimulus–response mechanisms, fabrication methodologies, multifunctional integration strategies, and application scenarios.

The application of artificial intelligence (AI) in venture capital has gained significant attention as a means to improve risk assessment and decision-making. This study examines AI’s role in venture capital by analyzing its real-world implementations in related industries, focusing on case studies from Ping An Bank in financial services and Midea Group in manufacturing. The research employs a qualitative analysis of documented AI applications, including Ping An Bank’s credit scoring and fraud detection systems, as well as Midea Group’s predictive maintenance and smart manufacturing solutions. Findings indicate that AI enhances risk management capabilities through advanced data processing and pattern recognition. Ping An Bank’s systems demonstrate improved accuracy in financial risk evaluation, while Midea’s implementations show increased operational efficiency in production environments. The study suggests that similar AI approaches could be adapted for venture capital applications, particularly in startup evaluation and investment risk analysis. However, the research also identifies challenges in implementation, including data quality requirements and system transparency needs. These insights contribute to understanding how proven AI applications in established industries may inform venture capital practices, while highlighting important considerations for practical adoption.

The active layer morphology transition of organic photovoltaics under non-equilibrium conditions are of vital importance in determining the device power conversion efficiency and stability; however, a general and unified picture on this issue has not been well addressed. Using combined in situ and ex situ morphology characterizations, morphological parameters relating to kinetics and thermodynamics of morphology evolution are extracted and studied in model systems under thermal annealing. The coupling and competition of crystallization and demixing are found to be critical in morphology evolution, phase purification and interfacial orientation. A unified model summarizing different phase diagrams and all possible kinetic routes is proposed. The current observations address the fundamental issues underlying the formation of the complex multi-length scale morphology in bulk heterojunction blends and provide useful morphology optimization guidelines for processing devices with higher efficiency and stability. Designing efficient blue perovskite LEDs by using mixed halides perovskite is still a challenge, limited mainly by the phase segregation issue. Here, the authors demonstrate in situ fabrication of quasi-2D CsPbClBr2 nanocrystal films with mixed ligands to overcome the constraint.

A new salamandroid salamander, Qinglongtriton gangouensis (gen. et sp. nov.), is named and described based on 46 fossil specimens of juveniles and adults collected from the Upper Jurassic (Oxfordian) Tiaojishan Formation cropping out in Hebei Province, China. The new salamander displays several ontogenetically and taxonomically significant features, most prominently the presence of a toothed palatine, toothed coronoid, and a unique pattern of the hyobranchium in adults. Comparative study of the new salamander with previously known fossil and extant salamandroids sheds new light on the early evolution of the Salamandroidea, the most species-diverse clade in the Urodela. Cladistic analysis places the new salamander as the sister taxon to Beiyanerpeton, and the two taxa together form the basalmost clade within the Salamandroidea. Along with recently reported Beiyanerpeton from the same geological formation in the neighboring Liaoning Province, the discovery of Qinglongtriton indicates that morphological disparity had been underway for the salamandroid clade by early Late Jurassic (Oxfordian) time.

In engineering measurements, metal foil strain gauges suffer from a limited range and low sensitivity, necessitating the development of flexible sensors to fill the gap. This paper presents a flexible, high-performance piezoresistive sensor using a composite consisting of graphene nanoplatelets (GNPs) and polydimethylsiloxane (PDMS). The proposed sensor demonstrated a significantly wider range (97%) and higher gauge factor (GF) (6.3), effectively addressing the shortcomings of traditional strain gauges. The microstructure of the GNPs/PDMS composite was observed using a scanning electron microscope, and the distribution of the conductive network was analyzed. The mechanical behavior of the sensor encapsulation was analyzed, leading to the determination of the mechanisms influencing encapsulation. Experiments based on a standard equal-strength beam were conducted to investigate the influence of the base and coating dimensions of the sensor. The results indicated that reducing the base thickness and increasing the coating length both contributed to the enhancement of the sensor’s performance. These findings provide valuable guidance for future development and design of flexible sensors.

Four previously undescribed drimane-type sesquiterpenoids, ramaribotrytols A–D (1–4), were isolated from the fruiting bodies of the clavarioid fungus Ramaria botrytoides. Their structures and absolute configurations were elucidated by comprehensive 1D and 2D NMR spectroscopic analyses, high-resolution electrospray ionization mass spectrometry (HRESIMS), and electronic circular dichroism (ECD) calculations. Compounds 1–4 are characterized by oxygenation at C-2, a structural feature that is rare within the drimane sesquiterpene family. These findings expand the chemical diversity of secondary metabolites from the medicinal and edible fungus Ramaria and enrich the structural repertoire of drimane-type sesquiterpenoids derived from higher fungi.

This study focuses on the importance of the real-time monitoring of bolt loads in roadways affected by high-intensity mining and the limitations of conventional monitoring methods. Fiber Bragg grating (FBG) sensors were embedded and encapsulated in rock bolts, and tensile tests were conducted indoors to verify their feasibility. The research was conducted using the consolidated face of the Bultai Coal Mine in the Shendong Mining Area as the engineering background. Real-time monitoring wavelength data from the FBG bolt sensor were obtained through field tests. The analysis of the data aimed to assess the condition of the FBG sensor and variations in axial force within the service bolts of the mining roadway. Using these monitoring results, the real-time stability and safety of the roadway bolts were evaluated. The study indicates that as the working face advances, the axial force in the bolt progressively rises under the effect of mine pressure. The left gang bolt rod’s shaft force changes significantly, while the right gang’s change is relatively small. When the working face moves 60 m past the bolt rod, the axial force in the bolt rises sharply. Moreover, the axial force at different positions of the left and right gang bolts exhibits a distinct variation pattern. The real-time monitoring of bolt support in the return roadway provides essential data for assessing bolt safety.

Ecological preferences and life history strategies have enormous impacts on the evolution and phenotypic diversity of salamanders, but the yet established reliable ecological indicators from bony skeletons hinder investigations into the paleobiology of early salamanders. Here, we statistically demonstrate by using time-calibrated cladograms and geometric morphometric analysis on 71 specimens in 36 species, that both the shape of the palate and many non-shape covariates particularly associated with vomerine teeth are ecologically informative in early stem- and basal crown-group salamanders. Disparity patterns within the morphospace of the palate in ecological preferences, life history strategies, and taxonomic affiliations were analyzed in detail, and evolutionary rates and ancestral states of the palate were reconstructed. Our results show that the palate is heavily impacted by convergence constrained by feeding mechanisms and also exhibits clear stepwise evolutionary patterns with alternative phenotypic configurations to cope with similar functional demand. Salamanders are diversified ecologically before the Middle Jurassic and achieved all their present ecological preferences in the Early Cretaceous. Our results reveal that the last common ancestor of all salamanders share with other modern amphibians a unified biphasic ecological preference, and metamorphosis is significant in the expansion of ecomorphospace of the palate in early salamanders.

We employed synthetic aperture radar interferometry (InSAR) to assess the slope stability of a high-altitude landfill in Sangri County, Shannan, Tibet. To address the unique climatic conditions of high-altitude regions, the InSAR deformation monitoring model was enhanced to mitigate the effects of temperature and rainfall. The accuracy of InSAR monitoring in high-elevation slopes was validated by comparison with GNSS RTK measurements. Both Differential Interferometric Synthetic Aperture Radar (D-InSAR) and Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) techniques were applied to monitor and evaluate slope deformation at the landfill site. The findings indicate that the average error between the improved InSAR model and GNSS measurements is 0.28 mm, with no statistically significant difference. The maximum slope displacement exceeds 20 mm when rainfall exceeds 300 mm, reaching the blue warning threshold. From 2018 to 2022, the deformation rate of the high-altitude landfill ranged from 0 to − 9.00 mm/a, classified as slip category VII. Significant deformation was observed during the rainy season, while the slope remained stable during dry periods, suggesting that rainfall is a primary trigger for slope deformation. A certain hysteresis effect in the deformation response to rainfall was also identified. The results demonstrate that InSAR technology offers comprehensive and dynamic monitoring capabilities for high-altitude slopes and serves as an effective tool for slope stability management in challenging environments.

With the increasing depth of coal mining operations, traditional ventilation systems are becoming insufficient to address the growing safety and operational challenges, particularly in dynamic underground environments. To enhance the sustainability and environmental performance of the coal mining industry, this study proposes an innovative framework that integrates deep learning with the DL-Koopman operator theory for accurate gas concentration prediction and a fuzzy adaptive PID (Fuzzy-PID) control strategy for optimized airflow regulation. The DL-Koopman-based model significantly improves prediction accuracy under fluctuating ventilation conditions, effectively addressing the challenges posed by variable wind speeds and other dynamic factors. By analyzing historical data on gas concentrations and wind speeds, the model identifies underlying patterns to develop a robust predictive framework. Furthermore, the Fuzzy-PID control strategy dynamically adjusts PID parameters in real-time, incorporating a dead zone mechanism to mitigate disturbances and enhance system stability. This dual approach not only ensures rapid adaptation to changing underground conditions but also significantly improves energy efficiency and safety. The proposed method demonstrates a practical pathway toward intelligent ventilation systems, contributing to cleaner and more sustainable mining practices. This research aligns with the global energy transition goals by reducing the environmental footprint of coal mining operations while maintaining high safety standards.