Search Results (52)

Background: Influenza remains a persistent public health challenge due to antigenic drift and shift, necessitating vaccines capable of eliciting broad and durable immunity. Hemagglutinin (HA) antigen serves as the critical target for eliciting protective immune responses against influenza. DNA vaccines offer distinct advantages over conventional platforms, including accelerated development and induction of both humoral and cellular immune responses. Methods: To optimize HA antigen presentation, we designed and systematically compared the immunogenicity and protective efficacy of HA antigen display strategies—bacteriophage T4 fibritin (HA-Foldon) and ferritin-based virus-like particles (HA-Ferritin)—versus monomeric HA DNA vaccines against seasonal influenza viruses. Results: HA-Ferritin showed superior structural stability. All vaccines induced similar HA-specific antibody levels, but HA-Ferritin elicited higher neutralizing antibodies and stronger T cell responses. Upon challenge, HA-Ferritin and HA-Foldon protected mice from weight loss and reduced lung virus loads by 3.27 and 0.76 times, respectively. Monomeric HA provided limited protection, with only 40% survival and minimal viral or pathological reduction. Conclusions: The HA-Ferritin DNA vaccine demonstrated enhanced immunogenicity and protection, supporting structured antigen display as a promising strategy for influenza DNA vaccine development. Full article

Gelatin is a commonly used protein-based hydrogel. However, the thermo-reversible nature of gelatin makes it unstable at physiological and higher temperatures. Therefore, this study adopted phosphates and glutaminase transaminase (TG) to modify gelation and studied the effects of combining sodium hexametaphosphate (SHP) and TG on the structure and gel properties of TG-crosslinked gelatin. This study focused on the effects of different SHP concentrations (0, 0.4, 0.8, 1.2, 1.6, 2.0, 2.4, 2.8 mmol/L) on the water distribution, textural properties, rheological properties, and microstructure of the TG-crosslinked gelatin gels. Results showed that the free water content in the TG-crosslinked gelatin gel declined with the increasing SHP addition when the concentration of SHP was kept below 2.0 mmol/L. The gel of TG-crosslinked gelatin at the SHP concentration of 1.6 mmol/L exhibited the highest hardness (304.258 g), chewiness (366.916 g) and η₅₀. All the TG-crosslinked gelatin gels with SHP modification were non-Newtonian pseudoplastic fluids. The G′ and G″ of TG-crosslinked gelatin increased before the SHP concentration reached 1.6 mmol/L, and the TG-crosslinked gelatin with 1.6 mmol/L SHP exhibited the largest G″ and G′. The fluorescence intensity of TG-crosslinked gelatin with SHP concentration above 1.6 mmol/L decreased with the increasing SHP concentration. SHP modified the secondary structure of TG-crosslinked gelatin gels. The gel of TG-crosslinked gelatin with the SHP concentration of 1.6 mmol/L exhibited a porous, smooth, and dense network structure. This research provides references for modifying gelatin and the application of gels in the encapsulation of bioactive ingredients and probiotics. Full article

Accurate permafrost mapping in mountainous regions is hindered by sparse in situ observations and heterogeneous terrain. This study develops a GPR-augmented machine learning framework to map mountain permafrost in the northeastern Qinghai–Tibet Plateau. A total of 1037 presence–absence samples were compiled from boreholes, soil pits, 128 GPR transects collected in 2009, and 22 additional empirical points above 4700 m, covering diverse topographic and thermal conditions. Thirteen classification algorithms were evaluated using 5-fold cross-validation repeated 40 times, with LightGBM, CatBoost, XGBoost, and RF achieving top performance (F1 > 0.98). Elevation-based spatial comparisons revealed that LightGBM and CatBoost produced more terrain-adaptive predictions at high altitudes and slope transitions. Aspect-controlled permafrost boundaries were captured, with modeled lower elevation limits varying by >200 m across slope directions. SHAP analysis showed that climate and soil variables contributed nearly 80% to model outputs, with LST, FDD, BD, and TDD being dominant. Several predictors exhibited threshold or nonlinear responses, reinforcing their physical relevance. Additional experiments confirmed that integration of GPR and high-elevation constraint samples significantly improved model generalization, especially in underrepresented terrain zones. This study demonstrates that a GPR-augmented machine learning framework can support cost-effective, physically informed mapping of frozen ground in complex alpine environments. Full article

This study aims to address the issue of various defects on the surface of aluminum profile materials, which can significantly impact industrial production as well as the reliability and safety of products. An algorithmic model, BBW YOLO (YOLOv8-BiFPN-BiFormer-WIoU v3), based on an enhanced YOLOv8 model is proposed for aluminum profile material surface-defect detection. First, the model can effectively eliminate redundant feature information and enhance the feature-extraction process by incorporating a weighted Bidirectional Feature Pyramid Feature-fusion Network (BiFPN). Second, the model incorporates a dynamic sparse-attention mechanism (BiFormer) along with an efficient pyramidal network architecture, which enhances the precision and detection speed of the model. Meanwhile, the model optimizes the loss function using Wise-IoU v3 (WIoU v3), which effectively enhances the localization performance of surface-defect detection. The experimental results demonstrate that the precision and recall of the BBW YOLO model are improved by 5% and 2.65%, respectively, compared with the original YOLOv8 model. Notably, the BBW YOLO model achieved a real-time detection speed of 292.3 f/s. In addition, the model size of BBW YOLO is only 6.3 MB. At the same time, the floating-point operations of BBW YOLO are reduced to 8.3 G. As a result, the BBW YOLO model offers excellent defect detection performance and opens up new opportunities for its efficient development in the aluminum industry. Full article

Small bookstores constructed before the 1970s have a high fire risk in the context of the revitalization of historical buildings; while the setup of simple sprinklers is an effective and cheap method of extinguishing fires, the parameters of the sprinklers are uncertain. In this study, small bookstores in Beijing were selected, and physical combustion experiments with/without a sprinkler system were carried out following the provisions of the Code for the Design of Sprinkler Systems. After the experiments, an FDS model was set up using fire dynamics software. The results show that the total heat release rate (HRR) of books and desks is related to the square of time, with a coefficient of 2.528 × 10⁻⁶, and the maximum heat release rate is 40 KW. Unlike the standard test, the physical combustion experiment is significantly affected by the space. According to numerical simulations, when the sprinkler flow velocity is 60~100 L/min, the water consumption of the sprinkler is 195~218 L. This study lays the foundation for the analysis of the combustion characteristics of small bookstores and provides data support for the installation of simple sprinkler systems in small bookstores. Full article

This study utilized policy text quantification, the entropy weighting technique, and the standard setting of the vertical policy synergetic degree to measure the synergy status of the environmental protection and governance policies in the Bohai Rim Region horizontal space (2001–2021). The standard setting of the vertical policy synergetic degree encompasses three dimensions, namely the policy subjects, policy objectives, and policy instruments. A comprehensive text database was established to facilitate analysis with 122 pieces of Bohai Sea environmental governance policies. After policy text quantification, this research found that the weight coefficients of the three indicators of policy subjects, policy instruments, and policy objectives were slightly different. This study found that provinces should balance the roles of policy issuers, the selection of policy instruments, and the setting of objectives to enhance compatibility between local and central governance policies; the vertical synergy of policies is closely related to the scientific nature of policy formulation. The incompleteness of the vertical synergy of policies affects the effectiveness of Bohai Sea environmental governance. In the future, the Bohai Rim Region’s environmental governance should continue to deepen the synergy of policies, strengthen scientific governance, promote regional linkage, and improve the scientificity of the policy system. Full article

This paper investigates a class of distributed fractional-order stochastic differential equations driven by fractional Brownian motion with a Hurst parameter $1/2<H<1$. By employing the Picard iteration method, we rigorously prove the existence and uniqueness of solutions with Lipschitz conditions. Furthermore, leveraging the Girsanov transformation argument within the $L^2$ metric framework, we derive quadratic transportation inequalities for the law of the strong solution to the considered equations. These results provide a deeper understanding of the regularity and probabilistic properties of the solutions in this framework. Full article

Non-contact blade vibration measurement based on blade tip timing (BTT) is a signature method for health monitoring in large rotating machinery. Time of arrival (ToA), as the fundamental data in BTT, directly impacts the accuracy of subsequent vibration parameter identification, thereby affecting the effectiveness of real-time condition monitoring and fault detection. However, no direct calibration method currently exists for ToA, and BTT errors are typically assessed through indirect or relative measurements, resulting in imprecise accuracy evaluations. To address this gap, this paper proposes a method for evaluating BTT measurement accuracy through direct calibration of ToA. A ToA direct calibration model is developed, which equivalently transforms the ToA variation caused by blade vibration into the circumferential angle difference between the BTT sensor and the rotating blade disk. The associated errors are systematically analyzed, and the BTT measurement accuracy is assessed using the directly calibrated ToA. Additionally, a BTT accuracy evaluation device was developed to facilitate this assessment. The uncertainty of the device was evaluated using the Monte Carlo method, accounting for both systematic and random factors. At 0.5° and 1000 rpm, the device yielded an estimated ToA value of 83.3055 μs, with the standard uncertainty of 8.824 × 10⁻³ μs and the 95% confidence interval of [83.2881, 83.3233] μs. The accuracy evaluation tests performed with the developed device simulated various vibration displacement and rotational speed conditions to validate the optical fiber BTT measurement system. The results showed that the system achieved a relative accuracy better than 0.8% and a repeatability accuracy exceeding 0.5%. The proposed BTT accuracy evaluation method and device have been validated for assessing both the accuracy and stability of the BTT measurement system, providing a reliable and precise approach for its evaluation. Full article

This study investigated the effects of physical field protein modification methods on the mechanical properties, color, rehydration performance, thermal stability, and sensory quality of yuba. The results showed that all three modification methods shortened the drying time of yuba, and each method enhanced the tensile strength and thermal stability of yuba. Yuba treated with microwave–vacuum for 10 min demonstrated the best performance in terms of tensile strength, elongation, color, and overall sensory score, making it the optimal method for the physical field modification of yuba. In addition, microwave–vacuum treatment led to better rehydration performance, thermal stability, and a faster rehydration rate. Through the analysis of the microstructure of yuba as well as its protein secondary and tertiary structures, it was found that microwave–vacuum treatment can maintain the tissue network structure of yuba while promoting more heat-induced protein conformational changes, showing a greater increase in the content of β-sheets, which contribute to enhancing the tensile strength and water-holding capacity of yuba, thereby improving its product quality. Full article

The purpose of this research was to establish an effective method for extracting phenolic compounds from Eucommia ulmoides leaves. Seven different deep eutectic solvents (DESs) were prepared, and ultrasonic-assisted technology was employed to optimize the extraction parameters. Factors such as the DES molar ratio, water content, liquid-to-solid ratio, ultrasonic duration, temperature, and power were systematically investigated. The optimal extraction conditions were determined to include a choline-chloride-to-ethylene-glycol molar ratio of 1:4, 30% water content, a liquid-to-solid ratio of 40:1 mL/g, an ultrasonication time of 48 min, a temperature of 53 °C, and ultrasonication power of 60%. Under these optimized conditions, the yields of phenolic compounds and flavonoids reached 17.16 mg/g and 48.23 mg/g, respectively, which were significantly higher (p < 0.05) than those obtained by traditional extraction methods. These findings indicate that the use of ultrasonic-assisted DES extraction notably improved the content of active compounds and the antioxidant properties of the extracts. Fourier transform infrared spectroscopy and scanning electron microscopy analyses revealed that this method promotes the release of active compounds by disrupting the integrity of the cell walls. This research offers a theoretical foundation and practical guidance for the efficient utilization and advanced processing of E. ulmoides leaves. Full article

The surface roughness of sand rollers directly influences the precision of rice processing. Therefore, the effects of sand rollers with different grit sizes (46#, 36#, and 30#) on rice quality were investigated in this work. The results indicated that the embryo retention ratio of polished rice decreased, and the milling degree increased as the grit size of the sand rollers decreased. The milling degree of the polished rice milled with sand rollers 36# and 30# was higher than that of rice milled with sand roller 46#. The rice milled with sand roller 30# showed the lowest content of fat, ash, and total phenolics. The rice milled with sand roller 46# exhibited the highest scavenging of ABTS free radicals (41.55%) and DPPH free radical activity (36.79%). The polished rice milled with sand roller 30# exhibited a higher peak viscosity, trough, breakdown, and final viscosity and a lower setback. The retrogradation rate of rice decreased as the rice was milled by all grit sizes of sand rollers. In conclusion, milling brown rice with sand rollers with different abrasive particle sizes could affect the quality of polished rice. This study provides a reference for the processing techniques of polished rice with different degrees of processing. Full article

Competitive endogenous RNAs (ceRNAs) absorb microRNAs and subsequently promote corresponding mRNA and long noncoding RNA (lncRNA) expression, which may alter cancer cell malignancy. Thus, dissecting ceRNA networks may reveal novel targets in cancer therapies. In this study, we analyzed differentially expressed genes (DEGs) of mRNAs and lncRNAs, and differentially expressed microRNAs (DE-miRNAs) and circular RNAs (DE-circRNAs) extracted from high-throughput sequencing datasets of hepatocellular carcinoma patients. Based on these data, we identified 26 gene modules using weighted gene co-expression network analysis (WGCNA), of which 5 were associated with tumor differentiation. In these modules, 269 genes were identified by GO and KEGG enrichment and patient’s survival correlation analyses. Next, 40 DE-miRNAs, each of which potentially bound a pair of DE-circRNA and hub gene, were discovered. Together with 201 circRNAs and 24 hub genes potentially bound by these miRNAs, 1151 ceRNA networks were constructed. Among them, 75 ceRNA networks consisting of 24 circRNAs, 28 miRNAs and 17 hub genes showed a positive circRNA–hub gene correlation. For validation, we carried out experiments for 4 randomly selected circRNAs regulating 19 potential ceRNA networks and verified 5 of them. This study represents a powerful strategy to identify essential gene networks and provides insights into designing effective therapeutic strategies. Full article

The functional relationship between soil permittivity and soil water content serves as the theoretical foundation for electromagnetic wave-based techniques used to determine soil moisture levels. However, the response of permittivity to changes in soil water content varies significantly across different soil types. Current models that utilize soil permittivity to estimate soil water content are often based on empirical statistical relationships specific to particular soil types. Moreover, existing physical models are hindered by an excessive number of parameters, which can be difficult to measure or calculate. This study introduces a universal model, termed the Soil Refractive Index (SRI) model, to describe the relationship between soil permittivity and soil water content. The SRI model is derived from the propagation velocity of electromagnetic waves in various soil components and the functional relationship between electromagnetic wave velocity and relative permittivity. The SRI model expresses soil water content as a linear function of the square root of the relative permittivity for any soil type with the slope and intercept as the two undetermined parameters. The slope is primarily influenced by the relative permittivity of soil water, while the intercept is mainly affected by both the slope and the soil porosity. The applicability of the SRI model is validated through tested soil samples and comparison with previously published empirical statistical models. For dielectric lossless soil, the theoretical value of the slope is calculated to be 0.126. The intercept varies across different soil types and increases linearly with soil porosity. The SRI model provides a theoretical basis for calculating soil water content using permittivity across various soil types. Full article

In drug development, drug-target affinity (DTA) prediction is a key indicator for assessing the drug’s efficacy and safety. Despite significant progress in deep learning-based affinity prediction approaches in recent years, there are still limitations in capturing the complex interactions between drugs and target receptors. To address this issue, a dynamic heterogeneous graph prediction model, DynHeter-DTA, is proposed in this paper, which fully leverages the complex relationships between drug–drug, protein–protein, and drug–protein interactions, allowing the model to adaptively learn the optimal graph structures. Specifically, (1) in the data processing layer, to better utilize the similarities and interactions between drugs and proteins, the model dynamically adjusts the connection strengths between drug–drug, protein–protein, and drug–protein pairs, constructing a variable heterogeneous graph structure, which significantly improves the model’s expressive power and generalization performance; (2) in the model design layer, considering that the quantity of protein nodes significantly exceeds that of drug nodes, an approach leveraging Graph Isomorphism Networks (GIN) and Self-Attention Graph Pooling (SAGPooling) is proposed to enhance prediction efficiency and accuracy. Comprehensive experiments on the Davis, KIBA, and Human public datasets demonstrate that DynHeter-DTA exceeds the performance of previous models in drug-target interaction forecasting, providing an innovative solution for drug-target affinity prediction. Full article

Salt marsh vegetation in the Yellow River Delta, including Phragmites australis (P. australis), Suaeda salsa (S. salsa), and Tamarix chinensis (T. chinensis), is essential for the stability of wetland ecosystems. In recent years, salt marsh vegetation has experienced severe degradation, which is primarily due to invasive species and human activities. Therefore, the accurate monitoring of the spatial distribution of these vegetation types is critical for the ecological protection and restoration of the Yellow River Delta. This study proposes a multi-source remote sensing data fusion method based on Sentinel-1 and Sentinel-2 imagery, integrating the temporal characteristics of optical and SAR (synthetic aperture radar) data for the classification mapping of salt marsh vegetation in the Yellow River Delta. Phenological and polarization features were extracted to capture vegetation characteristics. A random forest algorithm was then applied to evaluate the impact of different feature combinations on classification accuracy. Combining optical and SAR time-series data significantly enhanced classification accuracy, particularly in differentiating P. australis, S. salsa, and T. chinensis. The integration of phenological features, polarization ratio, and polarization difference achieved a classification accuracy of 93.51% with a Kappa coefficient of 0.917, outperforming the use of individual data sources. Full article