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Recent climate change has caused an increase in warming-driven erosion and sediment transport processes on the Tibetan Plateau (TP). Yet a lack of measurements hinders our understanding of basin-scale sediment dynamics and associated spatiotemporal changes. Here, using satellite-based estimates of suspended sediment, we reconstruct the quantitative history and patterns of erosion and sediment transport in major headwater basins from 1986 to 2021. Out of 13 warming-affected headwater regions, 63% of the rivers have experienced significant increases in sediment flux. Despite such intensified erosion, we find that 30% of the total suspended sediment flux has been temporarily deposited within rivers. Our findings reveal a pronounced spatiotemporal heterogeneity within and across basins. The recurrent fluctuations in erosion-deposition patterns within river channels not only result in the underestimation of erosion magnitude but also drive continuous transformations in valley morphology, thereby endangering local ecosystems, landscape stability, and infrastructure project safety. Climate change intensifies erosion and sediment transport in rivers of the Tibetan Plateau. Satellite data unveil unprecedented patterns of sediment deposition in rivers. Pronounced spatiotemporal heterogeneities within and across basins are found.

With the in-depth development of globalization, individuals are increasingly embedded in a culturally diverse environment. Effective communication and management ability (Cultural Intelligence) of employees in this type of diverse and heterogeneous environment impacts behavior and performance, affecting the sustainable innovation ability of organizations. Researchers have not yet fully assessed the impact of individuals’ cross-cultural management ability on sustainable innovation. Using Cultural Intelligence Theory and Trait Activation Theory, this paper discusses the influence of individual cultural intelligence on sustainable innovation behavior. The results showed that employees’ cultural intelligence positively affected their sustainable innovation behavior. Employee knowledge sharing plays an mediating role between intelligence and behavior. Differences in organizational culture have a negative moderating effect on the impact of employees’ cultural intelligence on knowledge sharing and sustainable innovation behaviors. The research results provide theoretical guidance for managing organizational cultural diversity and advancing cultural intelligence and sustainable innovation behaviors among employees.

As a critical molecule in the onset and sustainment of inflammatory response, the receptor for advanced glycation end products (RAGE) has a variety of ligands, such as advanced glycation end products (AGEs), S100/calcium granule protein, and high-mobility group protein 1 (HMGB1). Recently, an increasing number studies have shown that RAGE ligand binding can initiate the intracellular signal cascade, affect intracellular signal transduction, stimulate the release of cytokines, and play a vital role in the occurrence and development of immune-related diseases, such as systemic lupus erythematosus, rheumatoid arthritis, and Alzheimer’s disease. In addition, other RAGE signaling pathways can play crucial roles in life activities, such as inflammation, apoptosis, autophagy, and endoplasmic reticulum stress. Therefore, the strategy of targeted intervention in the RAGE signaling pathway may have significant therapeutic potential, attracting increasing attention. In this paper, through the systematic induction and analysis of RAGE-related signaling pathways and their regulatory mechanisms in immune-related diseases, we provide theoretical clues for the follow-up targeted intervention of RAGE-mediated diseases.

Background Phototherapy is a promising strategy for cancer therapy by reactive oxygen species (ROS) of photodynamic therapy (PDT) and hyperthermia of photothermal therapy (PTT). However, the therapeutic efficacy was restricted by tumor hypoxia and thermal resistance of increased expression of heat shock protein (Hsp). In this study, we developed albumin nanoparticles to combine hypoxia relief and heat shock protein inhibition to overcome these limitations for phototherapy enhancement. Results Near-infrared photosensitizer (IR780) and gambogic acid (GA, Hsp90 inhibitor) were encapsulated into albumin nanoparticles via hydrophobic interaction, which was further deposited MnO 2 on the surface to form IGM nanoparticles. Both in vitro and in vivo studies demonstrated that IGM could catalyze overexpress of hydrogen peroxide to relive hypoxic tumor microenvironment. With near infrared irradiation, the ROS generation was significantly increase for PDT enhancement. In addition, the release of GA was promoted by irradiation to bind with Hsp90, which could reduce cell tolerance to heat for PTT enhancement. As a result, IGM could achieve better antitumor efficacy with enhanced PDT and PTT. Conclusion This study develops a facile approach to co-deliver IR780 and GA with self-assembled albumin nanoparticles, which could relive hypoxia and suppress Hsp for clinical application of cancer phototherapy.

Cubosomes, a product of nanobioengineering, are self-structured lipid nanoparticles that act like drug-loaded theranostic probes. Here, we describe a simple method for the preparation of combinatorial drug-loaded cubosomes with, proof-of-principle, therapeutic effect against cancer cells, along with diagnostic capabilities. Anticancer drugs cisplatin and paclitaxel were loaded in the cubosomes in combination. The cubosomes were coated with a layer of poly-Ɛ-lysine, which helped avoid the initial burst release of drug and allowed for a slow and sustained release for better efficacy. Cubosomes were imaged by transmission electron microscope, and their dispersion analyzed in vitro by differential scanning calorimetric and X-ray diffractogram studies. The microscopic images depicted spherical polyangular structures, which are easily distinguishable. The analyses revealed that the drug is uniformly dispersed all through the cubosomes. Further characterization was carried out by zeta-potential measurement, in vitro release, and entrapment efficiency studies. The in vitro studies established that the coating of cubosomes successfully reduced the burst release of drugs initially and confirmed a slow, sustained release over increased time. Comparative cytotoxicity of coated, uncoated, and blank cubosomes was evaluated, using human hepatoma HepG2 cell line, and the formulations were found to be entirely nontoxic, similar to the blank ones. The therapeutic efficiency of the cubosomes against HeLa cells was confirmed by the impedance measurement and fluorescent imaging. Furthermore, the reduction in impedance in cells treated with coated combinatorial cubosomes proved the impairment of HeLa cells, as confirmed by fluorescence microscopy.

Within the framework of differential augmentation, this paper introduces the basic technical framework and performance of the BeiDou Global Navigation Satellite System (BDS-3) Satellite-Based Augmentation System (BDSBAS), including orbit products, satellite clock offset products, ionosphere and its integrity performance. The basic principle of BDS-3 Precise Point Positioning (PPP-B2b) is expounded, the similarities and differences between the PPP service provided by BDS-3 and International Global Navigation Satellite System (GNSS) Service (IGS) are discussed, and the limitations of PPP-B2b are analyzed. Since both the BDSBAS and PPP-B2b utilize a ground monitoring station network to determine the satellite orbits and clock offset corrections, and broadcast differential corrections through the three Geostationary Orbit (GEO) satellites of BDS-3, the feasibility of the co-construction of BDSBAS and PPP-B2b is analyzed, strategies for the infrastructure sharing and correction broadcasting are presented, and the influences of BDSBAS correction broadcasting strategy adjustment are evaluated. In addition, it assesses the possibility of broadcasting differential corrections through the Inclined Geosynchronous Orbit (IGSO) satellites of BDS-3, and the feasibility of augmenting satellite navigation with Low Earth Orbit (LEO) satellites.

The development of bone repair scaffolds has long been a research hotspot in tissue engineering. Owing to its unique capability for personalized customization of scaffold geometry and microstructure, 3D printing technology has been extensively adopted for fabricating bone repair scaffolds. Poly-L-lactic acid (PLLA), endowed with favorable biodegradability, excellent biocompatibility, and reliable in vivo safety, is widely used as a matrix material for 3D printed bone repair scaffolds. PLLA is a bioinert polymer characterized by inferior cell adhesion and osteogenic differentiation capabilities. To mitigate this bioinertness limitation, the present study employed N-methylpyrrolidone (NMP) etching to modify the surface of 3D-printed PLLA bone repair scaffolds. Following NMP etching for 1–24 h, the originally smooth scaffold surface evolved into a hierarchical, petal-like gradient microstructure, accompanied by a marked increase in surface roughness. Correspondingly, the hydrophilicity of the treated scaffolds was also enhanced. Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) analyses further confirmed that the crystallinity of PLLA in the scaffolds was significantly enhanced. Concomitantly, the modified scaffolds exhibited a marked improvement in adsorption capacity for green fluorescent protein (GFP), while the adhesion and proliferation of MC3T3-E1 on their surface were also significantly promoted. In vivo animal experiments demonstrated that the NMP-etched scaffolds could accelerate the process of bone defect repair. Collectively, surface modification of 3D-printed PLLA bone scaffolds via NMP etching enables precise modulation of their physicochemical properties, thereby effectively mitigating the inherent bioinertness limitation of PLLA scaffolds. Graphical Abstract

In recent years, a multitude of self-supervised anomaly detection algorithms have been proposed. Among them, PatchCore has emerged as one of the state-of-the-art methods on the widely used MVTec AD benchmark due to its efficient detection capabilities and cost-saving advantages in terms of labeled data. However, we have identified that the PatchCore similarity principal approach faces significant limitations in accurately locating anomalies when there are positional relationships between similar samples, such as rotation, flipping, or misaligned pixels. In real-world industrial scenarios, it is common for samples of the same class to be found in different positions. To address this challenge comprehensively, we introduce Feature-Level Registration PatchCore (FR-PatchCore), which serves as an extension of the PatchCore method. FR-PatchCore constructs a feature matrix that is extracted into the memory bank and continually updated using the optimal negative cosine similarity loss. Extensive evaluations conducted on the MVTec AD benchmark demonstrate that FR-PatchCore achieves an impressive image-level anomaly detection AUROC score of up to 98.81%. Additionally, we propose a novel method for computing the mask threshold that enables the model to scientifically determine the optimal threshold and accurately partition anomalous masks. Our results highlight not only the high generalizability but also substantial potential for industrial anomaly detection offered by FR-PatchCore.

Point cloud registration plays a great role in many application scenarios; however, the registration of large-scale point clouds for actual different moments suffers from the problems of low efficiency, low accuracy, and a lack of stability. In this paper, we propose a registration framework for large-scale point clouds at different moments, which firstly downsamples large-scale point clouds using a random sampling method, then performs a random expansion strategy to make up for the loss of information caused by the random sampling, then completes the first registration by a deep learning network based on the extraction of keypoints and feature descriptors in combination with RANSAC, and finally completes the registration using the point-to-point ICP method. We conducted validation experiments and application experiments on large-scale point clouds of key train components, and the experimental results are much higher in accuracy or efficiency than other methods, which proves the effectiveness of our framework, which can be applied to actual large-scale point clouds.

Train wheels are crucial components for ensuring the safety of trains. The accurate and fast identification of wheel tread defects is necessary for the timely maintenance of wheels, which is essential for achieving the premise of conditional repair. Image-based detection methods are commonly used for detecting tread defects, but they still have issues with the misdetection of water stains and the leaking of small defects. In this paper, we address the challenges posed by the detection of wheel tread defects by proposing improvements to the YOLOv8 model. Firstly, the impact of water stains on tread defect detection is avoided by optimising the structure of the detection layer. Secondly, an improved SPPCSPC module is introduced to enhance the detection of small targets. Finally, the SIoU loss function is used to accelerate the convergence speed of the network, which ensures defect recognition accuracy with high operational efficiency. Validation was performed on the constructed tread defect dataset. The results demonstrate that the enhanced YOLOv8 model in this paper outperforms the original network and significantly improves the tread defect detection indexes. The average precision, accuracy, and recall reached 96.95%, 96.30%, and 95.31%.