Search Results (2,280)

Thangka is a unique form of painting in Tibet, which holds rich cultural significance and artistic value. In Thangkas, in addition to the standard human form, there are also figures with multiple limbs. Existing human pose estimation methods are not well suited for keypoint detection of figures in Thangka paintings. This paper builds upon YOLOv11-Pose and introduces the Mamba structure to enhance the model’s ability to capture global features. A feature fusion module is employed to integrate both shallow and deep features, and a KAL loss function is proposed to alleviate the interference between keypoints of different body parts. In this study, a dataset of 6208 Thangka images is collected and annotated for Thangka keypoint detection, and data augmentation techniques are used to enhance the generalization of the dataset. Experimental results show that MythPose achieves 89.13% mAP@0.5, 92.51% PCK, and 87.22% OKS in human pose estimation tasks on Thangka images, outperforming the baseline model. This research not only provides a reference for the digital preservation of Thangka art but also offers insights for pose estimation tasks in other similar artworks. Full article

Multidrug resistance (MDR) remains a formidable barrier to successful cancer treatment, driven by mechanisms such as efflux pump overexpression, enhanced DNA repair, evasion of apoptosis and the protective characteristics of the tumour microenvironment. Nanoparticle-based delivery systems have emerged as promising platforms capable of addressing these challenges by enhancing intracellular drug accumulation, enabling targeted delivery and facilitating stimuli-responsive and controlled release. This review provides a comprehensive overview of the molecular and cellular mechanisms underlying MDR and critically examines recent advances in nanoparticle strategies developed to overcome it. Various nanoparticle designs are analysed in terms of their structural and functional features, including surface modifications, active targeting ligands and responsiveness to tumour-specific cues. Particular emphasis is placed on the co-delivery of chemotherapeutic agents with gene regulators, such as siRNA, and the use of nanoparticles to deliver CRISPR/Cas9 gene editing tools as a means of re-sensitising resistant cancer cells. While significant progress has been made in preclinical settings, challenges such as tumour heterogeneity, limited clinical translation and immune clearance remain. Future directions include the integration of precision nanomedicine, scalable manufacturing and non-viral genome editing platforms. Collectively, nanoparticle-based drug delivery systems offer a multifaceted approach to combat MDR and hold great promise for improving therapeutic outcomes in resistant cancers. Full article

Satellite sea surface salinity (SSS) products suffer from coarse spatiotemporal resolution, limiting their utility for mesoscale ocean monitoring. To address this, we proposed the Transformer-based satellite SSS super-resolution (SR) model (TSR) coupled with a progressive transfer learning (PTL) strategy. TSR improved the resolution of the salinity satellite SMOS from 1/4° and 10 days to 1/12° and daily. Leveraging Transformer, TSR captured long-range dependencies critical for reconstructing fine-scale structures. PTL effectively balanced structural detail acquisition and local accuracy correction by combining the gridded reanalysis products with scattered in situ observations as training labels. Validated against independent in situ measurements, TSR outperformed existing L3 salinity satellite products, as well as convolutional neural network and generative adversarial network-based SR models, particularly reducing the root mean square error (RMSE) by 33% and the mean bias (MB) by 81% compared to the SMOS input. More importantly, TSR demonstrated an enhanced capability in resolving mesoscale eddies, which were previously obscured by noise in salinity satellite products. Compared to training with a single label type or switching label types non-progressively, PTL achieved a 3%–66% lower RMSE and a 73–92% lower MB. TSR enables higher-resolution satellite monitoring of SSS, contributing to the study of ocean dynamics and climate change. Full article

Premature ovarian insufficiency (POI) is an important factor in female infertility and is often associated with oxidative stress. Alginate oligosaccharides (AOSs), derived from the degradation of alginate, have been demonstrated to have protective effects against various oxidative stress-related diseases. However, the impact of AOSs on POI has not been previously explored. The current study explored the effects of AOSs on ovarian dysfunction in a mouse model of POI induced by D-galactose (D-gal). Female C57BL/6 mice were randomly divided into five groups: the control (CON), POI model (D-gal), and low-, medium-, and high-dose AOS groups (AOS-L, 100 mg/kg/day; AOS-M, 150 mg/kg/day; AOS-H, 200 mg/kg/day). For 42 consecutive days, mice in the D-gal, AOS-L, AOS-M, and AOS-H groups received daily intraperitoneal injections of D-gal (200 mg/kg/day), whereas those in the CON group received equivalent volumes of sterile saline. Following D-gal injection, AOSs were administered via gavage at the specified doses; mice in the CON and D-gal groups received sterile saline instead. AOS treatment markedly improved estrous cycle irregularities, normalized serum hormone levels, reduced granulosa cell apoptosis, and increased follicle counts in POI mice. Moreover, AOSs significantly reduced ovarian oxidative stress and senescence in POI mice, as indicated by lower levels of malondialdehyde (MDA), higher activities of catalase (CAT) and superoxide dismutase (SOD), and decreased protein expression of 4-hydroxynonenal (4-HNE), nitrotyrosine (NTY), 8-hydroxydeoxyguanosine (8-OHdG), and p16 in ovarian tissue. Analysis of the gut microbiota through 16S rRNA gene sequencing and short-chain fatty acid (SCFA) analysis revealed significant differences in gut microbiota composition and SCFA levels (acetic acid and total SCFAs) between control and D-gal-induced POI mice. These differences were largely alleviated by AOS treatment. AOSs changed the gut microbiota by increasing the abundance of Ligilactobacillus and decreasing the abundance of Clostridiales, Clostridiaceae, Marinifilaceae, and Clostridium_T. Additionally, AOSs mitigated the decline in acetic acid and total SCFA levels observed in POI mice. Notably, the total SCFA level was significantly correlated with the abundance of Ligilactobacillus, Marinifilaceae, and Clostridium_T. In conclusion, AOS intervention effectively mitigates ovarian oxidative stress, restores gut microbiota homeostasis, and regulates the microbiota–SCFA axis, collectively improving D-gal-induced POI. Therefore, AOSs represent a promising therapeutic strategy for POI management. Full article

Daphnis nerii cypovirus-23 (DnCPV-23) is a new type of cypovirus that has a lethal effect on many species of Sphingidae pests. DnCPV-23 can replicate in Spodoptera frugiperda Sf9 cells, but the replication characteristics of the virus in this cell line are still unclear. To determine the replication characteristics of DnCPV-23 in Sf9 cells, uninfected Sf9 cells and Sf9 cells at 24 and 72 h after DnCPV-23 infection were collected for transcriptome analysis. Compared to uninfected Sf9 cells, a total of 188 and 595 differentially expressed genes (DEGs) were identified in Sf9 cells collected at 24 hpi and 72 h, respectively. KEGG analyses revealed that 139 common DEGs in two treatment groups were related to nutrition and energy metabolism-related processes, cell membrane integrity and function-related pathways, detoxification-related pathways, growth and development-related pathways, and so on. We speculated that these cellular processes might be manipulated by viruses to promote replication. This study provides an important basis for further in-depth research on the mechanism of interaction between viruses and hosts. It provides additional basic information for the future exploitation of DnCPV-23 as a biological insecticide. Full article

Multimodal sentiment analysis (MSA) faces key challenges such as incomplete modality inputs, long-range temporal dependencies, and suboptimal fusion strategies. To address these, we propose MGMR-Net, a Mamba-guided multimodal reconstruction and fusion network that integrates modality-aware reconstruction with text-centric fusion within an efficient state-space modeling framework. MGMR-Net consists of two core components: the Mamba-collaborative fusion module, which utilizes a two-stage selective state-space mechanism for fine-grained cross-modal alignment and hierarchical temporal integration, and the Mamba-enhanced reconstruction module, which employs continuous-time recurrence and dynamic gating to accurately recover corrupted or missing modality features. The entire network is jointly optimized via a unified multi-task loss, enabling simultaneous learning of discriminative features for sentiment prediction and reconstructive features for modality recovery. Extensive experiments on CMU-MOSI, CMU-MOSEI, and CH-SIMS datasets demonstrate that MGMR-Net consistently outperforms several baseline methods under both complete and missing modality settings, achieving superior accuracy, robustness, and generalization. Full article

To enhance the anti-overturning performance of poles and prevent tilting or collapse, a prefabricated foundation for distribution lines is developed. Field tests are conducted on five groups of foundations. Based on the test results, finite element analysis (FEA) is employed to investigate the influence of different factors—such as pole embedment depth, foundation locations, soil type, and soil parameters—on the anti-overturning performance of pole prefabricated foundations. The results indicate that under ultimate load conditions, the reaction force distribution at the base of the foundation approximates a triangular pattern, and the lateral earth pressure on the pole follows an approximately quadratic parabolic distribution along the depth. When the foundation size increases from 0.8 m to 0.9 m, the bearing capacity of the prefabricated foundation improves by 8%. Furthermore, when the load direction changes from 0° to 45°, the foundation’s bearing capacity increases by 14%. When the foundation is buried at a depth of 1.0 m, compared with the ground position, the ultimate overturning moment of the prefabricated foundation increases by 10%. Based on field test results, finite element simulation results, and limit equilibrium theory, a calculation method for the anti-overturning bearing capacity of prefabricated pole foundations is developed, which can provide a practical reference for the engineering design of distribution line poles and their prefabricated foundations. Full article

Based on molecular dynamics simulation, we conducted a comprehensive study on the tensile behaviors and properties of the $\gamma$(Ni)/${\gamma }^{\prime }$(Ni₃Al) superalloy with varying ${\gamma }^{\prime }$(Ni₃Al) phase volume fractions ($V\left({\gamma }^{\prime }\right))$ under high-temperature, high-strain-rate service environments. Our investigation revealed that the tensile behavior of the superalloy depends critically on the $V\left({\gamma }^{\prime }\right)$. When the $V\left({\gamma }^{\prime }\right)$ increased from 13.5 to 67%, the system’s tensile strength exhibited a non-monotonic response, peaking at $\mathrm{V}\left({\gamma }^{\prime }\right)$ = 40.3% before progressively decreasing. Conversely, the maximum uniform plastic strain decreased linearly and significantly when $V\left({\gamma }^{\prime }\right)$ increased. These results establish an atomistically informed framework that elucidates the composition–microstructure–property relationships in $\gamma$(Ni)/${\gamma }^{\prime }$(Ni₃Al) superalloys, specifically addressing how $V\left({\gamma }^{\prime }\right)$ governs variations in deformation mechanisms and mechanical performance. Furthermore, this work provides quantitative design paradigm for optimizing ${\gamma }^{\prime }$(Ni₃Al) precipitate architecture and compositional tuning in the Ni-based $\gamma$(Ni)/${\gamma }^{\prime }$(Ni₃Al) superalloy. Full article

Firstly, this paper reviews the fundamental theories of solid surface wettability and contact angle hysteresis. Subsequently, it further introduces four typical wettability-engineered surfaces with low hysteresis (superhydrophobic, superamphiphobic, super-slippery, and liquid-like smooth surfaces). Finally, it focuses on the latest research progress in the field of droplet manipulation on open planar surfaces with engineered wettability. To achieve droplet manipulation, the core driving forces primarily stem from natural forces guided by bioinspired gradient surfaces or the regulatory effects of external fields. In terms of bioinspired self-propelled droplet movement, this paper summarizes research inspired by natural organisms such as desert beetles, cacti, self-aligning floating seeds of emergent plants, or water-walking insects, which construct bioinspired special gradient surfaces to induce Laplace pressure differences or wettability gradients on both sides of droplets for droplet manipulation. Moreover, this paper further analyzes the mechanisms, advantages, and limitations of these self-propelled approaches, while summarizing the corresponding driving force sources and their theoretical formulas. For droplet manipulation under external fields, this paper elaborates on various external stimuli including electric fields, thermal fields, optical fields, acoustic fields, and magnetic fields. Among them, electric fields involve actuation mechanisms such as directly applied electrostatic forces and indirectly applied electrocapillary forces; thermal fields influence droplet motion through thermoresponsive wettability gradients and thermocapillary effects; optical fields cover multiple wavelengths including near-infrared, ultraviolet, and visible light; acoustic fields utilize horizontal and vertical acoustic radiation pressure or acoustic wave-induced acoustic streaming for droplet manipulation; the magnetic force acting on droplets may originate from their interior, surface, or external substrates. Based on these different transport principles, this paper comparatively analyzes the unique characteristics of droplet manipulation under the five external fields. Finally, this paper summarizes the current challenges and issues in the research of droplet manipulation on the open planar surfaces and provides an outlook on future development directions in this field. Full article

Sepsis is a fetal disease that requires a clear diagnostic biomarker for timely antibiotic treatment. Recent research has identified a pyroptosis-inducing epitope known as P5-5 in tetranectin (TN), a plasma protein produced by monocytes. Previously, we produced a 12F1 monoclonal antibody against the P5-5 and discovered that it could not only diagnose the presence but also monitor the progress of sepsis in the clinic. In the current study, we further investigated the structure site of the P5-5 and the recognition mechanism between the 12F1 mAb and the P5-5 epitope. To this end, 10 amino acids (NDALYEYLRQ) in the P5-5 were individually mutated to alanine, and their binding to the mAb was tested to confirm the most significant antigenic recognition sites. In the meanwhile, the spatial conformation of 12F1 mAb variable regions was modeled, and the molecular recognition mechanisms in detail of the mAb to the P5-5 epitope were further studied by molecular docking. Following epitope prediction and experimental verification, we demonstrated that the motif “DALYEYL” in the epitope sequence position 2−8 of TN-P5-5 is the major binding region for mAb recognition, in which two residues (4L and 8L) were essential for the interaction between the P5-5 epitope and the 12F1 mAb. Therefore, our study greatly narrowed down the previously reported motif from ten to seven amino acids and identified two Leu as critical contact residues. Finally, a single-chain variable fragment (scFv) from the 12F1 hybridoma was constructed, and it was confirmed that the identified motif and residues are prerequisites for the strong binding between P5-5 and 12F1. Altogether, the data of the present work could serve as a theoretic guide for the clinical design of biosynthetic drugs by artificial intelligence to treat sepsis. Full article

The C-terminus of the BoNT/A heavy chain (BoNT/AHC) mediates binding to its receptor, SV2, a critical step for toxicity. Antibody inhibition of this interaction enhances neuronal survival. We previously identified a functional anti-BoNT/AHC nanobody, HM. To extend its in vivo half-life, we designed and prepared two Fc-optimized nanoparticles, HM-Fc5 and HM-Fc6. Structural modeling (homology/docking) of the HM Fv-AHC complex predicted that HM engages key AHC residues (Tyr¹¹⁵⁵, Phe¹¹⁶⁰, Ile¹¹⁶¹, Val¹¹⁸⁴, Asn¹¹⁸⁸, Lys¹¹⁸⁹, Glu¹¹⁹⁰), which overlap with the SV2 binding site. This suggests HM’s protective mechanism involves blocking toxin-receptor binding and cellular entry. HM-Fc5 and HM-Fc6 retained the stability and function of the parental HM antibody while exhibiting prolonged in vivo half-life. These optimized nanobodies offer economical candidates potentially enabling longer dosing intervals, beneficial for prophylaxis or chronic disease treatment. Significance Statement: The purpose of the study is to design and prepare two Fc optimized nanoparticles, HM-Fc5 and HM-Fc6, and predict the key residues involved in the interaction between HMs and AHC. The experimental results showed that HM-Fc5 and HM-Fc6 have the same stability as the parent HM antibody but have a longer half-life in vivo. The key residues Tyr¹¹⁵⁵, Phe¹¹⁶⁰, Ile¹¹⁶¹, Val¹¹⁸⁴, Asn¹¹⁸⁸, Lys¹¹⁸⁹, and Glu¹¹⁹⁰ overlap with the SV2 binding site. Our experimental results indicate that these nanobody candidates are not only more economical and convenient, but may also have longer dosing intervals, providing strong evidence and reference for prolonging the in vivo half-life of nanomaterials. Full article

Winter wheat (Triticum aestivum L.) silage has high feeding value and has become an important roughage resource in China. To recognize the optimal fermentation time of the silage product, this study systematically evaluated the temporal dynamics of microbial communities and metabolic profiles in whole winter wheat silage at days 7, 14, 30, 50, and 70. The dry matter (DM) content slightly fluctuated with the extension of fermentation time, with 28.14% at 70 days of ensiling. The organic matter and neutral detergent fiber content gradually decreased with the extension of fermentation time. A significant decrease in pH was observed at days 30, 50, and 70 compared to days 7 and 14 (p < 0.05), with the lowest pH value of 4.4 recorded at day 70. The contents of lactic acid, acetic acid, butyric acid, and total volatile fatty acids gradually increased with the extension of fermentation time, reaching a maximum at 70 days of ensiling. The dominant bacteria were Proteobacteria and Firmicutes at the phylum level, and the predominant bacteria were Hafnia-Obesumbacterium, Enterobacter, and Lactobacillus at the genus level. The relative abundance of Hafnia-Obesumbacterium and Lactobacillus fluctuated slightly with the duration of fermentation, reaching a minimum for the former and a maximum for Lactobacillus at 50 days of ensiling. By day 70, Sporolactobacillus emerged as a distinct silage biomarker. The dominant fungi was Ascomycota at the phylum level, and the predominant fungi were Fusarium and an unidentified fungus at the genus level. The correlation analysis revealed significant pH–organic acid–microbe interactions, with pH negatively correlating with organic acids but positively with specific bacteria, while organic acids showed complex microbial associations. Collectively, under natural fermentation conditions, the optimal fermentation period for wheat silage exceeds 70 days, and Sporolactobacillus shows potential as a microbial inoculant for whole winter wheat silage. These findings provide a theoretical foundation for optimizing whole winter wheat silage utilization and enhancing fermentation quality. Full article

A novel prefabricated pile foundation is presented to improve the disaster resistance of the pole line. Bearing performance analysis of prefabricated inclined pile foundations for electric poles under downward pressure-horizontal loading is carried out, and the effects of prefabricated foundation dimensions and pile inclination on the horizontal load–displacement curves at the top of the poles, the horizontal displacement and settlement at the top of the piles, the horizontal displacement and tilt rate of the poles’ bodies and piles bending moments are investigated. The findings indicate the following: as the prefabricated foundation size grows, the bearing capacity of the foundation improves, and the anti-overturning ability of the electric pole improves; the foundation size increases from 0.9 m to 1.35 m, the anti-overturning bearing capacity of the foundation increases by 15.77%, the maximum bending moment of the foundation pile body increases by 19.7%, and the maximum bending moment occurs at about 0.2 m of the pile body; the bearing capacity of inclined piles is larger than that of straight piles—with an increase in the pile inclination angle, the foundation bearing performance increases, and the overturning bearing capacity of the poles increases; the pile inclination angle grows from 0° to 20°, the overturning bearing performance of the foundation increases by 19.2%, the maximum bending moment of the foundation piles reduces by 21.2%, and the maximum of the bending moment occurs at the pile body at a position of about 0.2 m. Full article

A State of Health (SOH) estimation of lithium-ion batteries is a core function of battery management systems, directly affecting the safe operation, lifetime prediction, and economic efficiency of batteries. However, existing methods still face challenges in balancing feature robustness and model generalization ability; for instance, some studies rely on features whose physical correlation with SOH lacks strict verification, or the models struggle to simultaneously capture the temporal dynamics of health factors and nonlinear mapping relationships. To address this, this paper proposes an SOH estimation method based on incremental capacity (IC) curves and a Temporal Convolutional Network—Relevance Vector Machine (TCN-RVM) model, with core innovations reflected in two aspects. Firstly, five health factors are extracted from IC curves, and the strong correlation between these features and SOH is verified using both Pearson and Spearman coefficients, ensuring the physical rationality and statistical significance of feature selection. Secondly, the TCN-RVM model is constructed to achieve complementary advantages. The dilated causal convolution of TCN is used to extract temporal local features of health factors, addressing the insufficient capture of long-range dependencies in traditional models; meanwhile, the Bayesian inference framework of RVM is integrated to enhance the nonlinear mapping capability and small-sample generalization, avoiding the overfitting tendency of complex models. Experimental validation is conducted using the lithium-ion battery dataset from the University of Maryland. The results show that the mean absolute error of the SOH estimation using the proposed method does not exceed 0.72%, which is significantly superior to comparative models such as CNN-GRU, KELM, and SVM, demonstrating higher accuracy and reliability compared with other models. Full article

Fenton oxidation can contribute to meeting effluent standards for COD in actual wastewater treatment plant effluents. However, Fenton oxidation is prone to produce iron sludge waste. The application of heterogeneous Fenton-like systems based on Fenton iron mud carbon in wastewater treatment plants is essential for Fenton iron mud reduction and recycling. In this study, a Fenton iron mud carbon catalyst/Ferrate salts/H₂O₂ (FSC/Fe(VI)/H₂O₂) system was developed to remove chemical oxygen demand (COD) from secondary effluents at the pilot scale. The results showed that the FSC/Fe(VI)/H₂O₂ system exhibited excellent COD removal performance with a removal rate of 57% under slightly neutral conditions in laboratory experiments. In addition, the effluent COD was stabilized below 40 mg·L⁻¹ for 65 days at the pilot scale. Fe(IV) and ¹O₂ were confirmed to be the main active species in the degradation process through electron paramagnetic resonance (EPR) and quenching experiments. C=O, O-C=O, N sites and Fe⁰ were responsible for the generation of Fe(IV) and ¹O₂ in the FSC/Fe(VI)/H₂O₂ system. Furthermore, the cost per ton of water treated by the pilot-scale FSC/Fe(VI)/H₂O₂ system was calculated to be only 0.6209 USD/t, further confirming the application potential of the FSC/Fe(VI)/H₂O₂ system. This study promotes the engineering application of heterogeneous Fenton-like systems for water treatment. Full article