Search Results (616)

Underground gas storage (UGS) in heterogeneous carbonate reservoirs is crucial for energy security but frequently faces wellbore instability challenges, which traditional static methods struggle to address due to dynamic full life cycle changes. This study systematically analyzes the dynamic evolution of wellbore stress in the Bs8 well (Qianmiqiao carbonate UGS) during drilling, acidizing, and injection-production operations, establishing a quantitative risk assessment model based on the Mohr–Coulomb criterion. Results indicate a significantly higher wellbore instability risk during drilling and initial gas injection stages, primarily manifested as shear failure, with greater severity observed in deeper well sections (e.g., 4277 m) due to higher in situ stresses. During acidizing, while the wellbore acid column pressure can reduce principal stress differences, the process also significantly weakens rock strength (e.g., by approximately 30%), inherently increasing the risk of wellbore instability, though the primary collapse mode remains shallow shear breakout. In the injection-production phase, increasing formation pressure is identified as the dominant factor, shifting the collapse mode from initial shallow shear failure to predominant wide shear collapse, notably at 90°/270° from the maximum horizontal stress direction, thereby significantly expanding the unstable zone. This dynamic assessment method provides crucial theoretical support for full life cycle integrity management and optimizing safe operation strategies for carbonate gas storage wells. Full article

Fiber-reinforced resin matrix composites are generally composed of fibers and matrix with significantly different properties, which are non-uniform and anisotropic in nature. Macro-failure criteria generally view composite plies as a uniform whole and do not accurately reflect fiber- and matrix-scale failures. In this study, the interface phase effect between fiber and matrix has been introduced into the frame of trans-scale analysis to better model the failure process, and the equivalent mechanical property characterization model of the interface phase has also been established. Combined with the macro–micro-strain transfer method, the trans-scale correlation of the mechanical response of the composite laminates between the macro scale and the fiber, matrix and interface micro scale has been achieved. Based on the micro-scale failure criterion and the stiffness reduction strategy, the trans-scale failure analysis method of composite materials incorporating the interface phase effect has been developed, which can simultaneously predict the failure modes of the matrix, fiber and interface phase. A numerical implementation of the developed trans-scale failure analysis method considering interface phase was carried out using the Python and Abaqus 2020 joint simulation technique. Case studies were carried out for three material systems, and the prediction data of the developed trans-scale failure analysis methodology incorporating interface phase effects for composite materials, the prediction data of the Linde failure criterion and the experimental data were compared. The comparison with experimental data confirms that this method has good prediction accuracy, and compared with the Linde and Hashin failure methods, only it can predict the failure mode of the fiber–matrix interface. The case analysis shows that its prediction accuracy has been improved by about 2–3%. Full article

Grapholita molesta is a globally significant fruit pest. Females achieve maximal reproductive output through efficient sperm utilization following a single copulation. Post-mating maturation of eupyrene sperm is a critical step in reproductive success. Here, we report that a male accessory gland-derived serine protease (named GmAGSP1) is essential for this process. GmAGSP1 was only distantly related to other identified sperm-activating SPs, and its transcript was highly expressed in the AG at 48 h after emergence. RNAi-mediated knockdown of GmAGSP1 in males did not affect courtship rate, copulation duration, or mating frequency, whereas male fertility decreased significantly. Mating with GmAGSP1-knockdown males markedly impaired eupyrene sperm maturation in the spermatophores, with phenotypes including failure of eupyrene sperm bundles to dissociate normally and marked reduction in viability of the dissociated eupyrene sperm. Finally, untargeted metabolomic analysis preliminarily demonstrated marked alterations in multiple metabolic pathways within the spermatophore following mating with GmAGSP1-knockdown males. This study advances our understanding of the regulatory mechanism of “sperm activation in the spermatophore’s metabolic microenvironment mediated by male AG-derived SP” while providing critical insights for the development of novel genetic control strategies targeting G. molesta. Full article

Acute hepatopancreatic necrosis disease (AHPND), caused by the bacterium Vibrio parahaemolyticus, is a major threat to global shrimp aquaculture. In this study, we evaluated the therapeutic effects of phage therapy in Litopenaeus vannamei challenged with AHPND-causing Vibrio parahaemolyticus. Phage application at various concentrations significantly improved shrimp survival, with the 1 ppm group demonstrating the highest survival rate. Enzymatic assays revealed that phage-treated shrimp exhibited enhanced immune enzyme activities, including acid phosphatase (ACP), alkaline phosphatase (AKP), and lysozyme (LZM). In addition, antioxidant defenses such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-PX), and total antioxidant capacity (T-AOC) significantly improved, accompanied by reduced malondialdehyde (MDA) levels. Serum biochemical analyses demonstrated marked improvements in lipid metabolism, particularly reductions in triglyceride (TG), total cholesterol (TC), and low-density lipoprotein (LDL), alongside higher levels of beneficial high-density lipoprotein (HDL). Transcriptomic analysis identified 2274 differentially expressed genes (DEGs), notably enriched in pathways involving fatty acid metabolism, peroxisome functions, lysosomes, and Toll-like receptor (TLR) signaling. Specifically, phage treatment upregulated immune and metabolic regulatory genes, including Toll-like receptor 4 (TLR4), myeloid differentiation primary response protein 88 (MYD88), interleukin-1β (IL-1β), nuclear factor erythroid 2-related factor 2 (Nrf2), and peroxisome proliferator-activated receptor (PPAR), indicating activation of innate immunity and antioxidant defense pathways. These findings suggest that phage therapy induces protective immunometabolic adaptations beyond its direct antibacterial effects, thereby providing an ecologically sustainable alternative to antibiotics for managing bacterial diseases in shrimp aquaculture. Full article

Background: Skipping breakfast, a prevalent issue among children and adolescents, has been reported to be associated with academic performance and long-term health. However, less attention has been given to the types of breakfast foods consumed. Therefore, our study aims to investigate the association between breakfast variety and dietary knowledge, attitude, and practice (KAP) among preadolescents. Methods: The study included 1449 students in grades 4–6 from Zhongshan city, Guangdong province. Data were collected through face-to-face field investigation using a validated questionnaire. The questionnaire encompassed sociodemographic characteristics, as well as dietary KAP. Results: Among all participants, 1315 reported consuming breakfast daily. Dietary diversity varied significantly: 8.8% consumed only 1 type of food, 52.9% consumed 2–4 types, and 38.3% consumed ≥5 types. Students who consumed a greater variety of breakfast foods exhibited more favorable dietary and lifestyle patterns. Specifically, those who consumed ≥5 types of food showed statistically significant associations with healthier practices, including reduced intake of sugary beverages and night snacks, stronger adherence to dietary guidelines, more positive attitudes toward improving eating habits, longer sleep durations, increased participation in meal preparation, greater dish variety in meals, and higher engagement in daily physical activity. Conclusions: Breakfast variety was associated with KAP, particularly when breakfast types ≥ 5, providing more sufficient and favorable evidence for breakfast consumption. Full article

In response to the high-performance requirements of concrete materials under complex triaxial stress states and water-containing environments in marine engineering, this study focuses on water-containing basalt fiber-reinforced concrete (BFRC). Uniaxial compression and splitting tensile tests were conducted on specimens with different fiber contents (0.0%, 0.05%, 0.10%, 0.15%, and 0.20%) to determine the optimal fiber content of 0.1%. The compressive strength of the concrete with this fiber content increased by 13.5% compared to the control group without fiber, reaching 36.90 MPa, while the tensile strength increased by 15.9%, reaching 2.33 MPa. Subsequently, NMR and SEM techniques were employed to analyze the internal pore structure and micro-morphology of BFRC. It was found that an appropriate amount of basalt fiber (content of 0.1%) can optimize the pore structure and form a reticular three-dimensional structure. The pore grading was also improved, with the total porosity decreasing from 7.48% to 7.43%, the proportion of harmless pores increasing from 4.03% to 4.87%, and the proportion of harmful pores decreasing from 1.67% to 1.42%, thereby significantly enhancing the strength of the concrete. Further triaxial compression tests were conducted to investigate the mechanical properties of BFRC under different confining pressures (0, 3, and 6 MPa) and water contents (0%, 1%, 2%, and 4.16%). The results showed that the stress–strain curves primarily underwent four stages: initial crack compaction, elastic deformation, yielding, and failure. In terms of mechanical properties, when the confining pressure increased from 0 MPa to 6 MPa, taking dry sandstone as an example, the peak stress increased by 54.0%, the elastic modulus increased by 15.7%, the peak strain increased by 37.0%, and the peak volumetric strain increased by 80.0%. In contrast, when the water content increased from 0% to 4.16%, taking a confining pressure of 0 MPa as an example, the peak stress decreased by 27.4%, the elastic modulus decreased by 43.2%, the peak strain decreased by 59.3%, and the peak volumetric strain decreased by 106.7%. Regarding failure characteristics, the failure mode shifted from longitudinal splitting under no confining pressure to diagonal shear under confining pressure. Moreover, as the confining pressure increased, the degree of failure became more severe, with more extensive cracks. However, when the water content increased, the failure degree was relatively mild, but it gradually worsened with further increases in water content. Based on the CDP model, a numerical model for simulating the triaxial compression behavior of BFRC was developed. The simulation results exhibited strong consistency with the experimental data, thereby validating the accuracy and applicability of the model. Full article

This paper addresses the issues of insufficient expansion force, low early strength (1-day compressive strength < 1.5 MPa), and poor toughness (flexural strength < 0.8 MPa) in traditional chemical foamed cement used for road grouting repair. By combining single-factor gradient experiments with microscopic mechanism analysis, the study systematically investigates the performance modulation mechanisms of controlled-release foamed cement using additives such as heavy calcium powder (0–20%), calcium chloride (0.2–1.2%), latex powder (0.2–1.2%), and polypropylene fiber (0.2–0.8%). The study innovatively employs a titanium silicate coupling agent coating technique (with the coating agent amounting to 25% of the catalyst’s mass) to delay foaming by 40 s. Scanning electron microscopy (SEM) and pore structure analysis reveal the microscopic essence of material performance optimization. Full article

Our previous study has shown that supplementation of 0.50% benzoic acid (BA) increased growth performance, promoted rumen fermentation, and improved the composition and function of rumen microbiota. This research was designed to conduct a deeper exploration of the impacts of dietary supplementation with BA on the apparent digestibility of nutrients and the composition of rectal microbiota in weaned Holstein dairy calves. Sixteen Holstein heifer calves with similar body weights (91.2 ± 0.7 kg) were selected and randomly allocated into two groups, each comprising eight calves. Calves in the control group (CON group) were fed with a basal diet, while those in the benzoic acid group (BA group) were fed with the basal diet supplemented with 0.50% benzoic acid (on a dry matter basis). The experimental period started at 60 days of age and ended at 102 days of age, lasting for a total of 42 days. The calves were weaned at 60 days of age, with a transition period of 7 days. Feed samples were collected every two weeks, fecal samples were collected from 99 to 101 days of age, and blood samples were collected at 102 days of age. The results showed that supplementation with BA did not influence the digestibility of dry matter, crude protein, ether extract, neutral detergent fiber, acid detergent fiber, calcium, and phosphorus between the two groups. Compared with the CON group, BA supplementation tended to decrease the total cholesterol (TC) in the serum of the calves (p = 0.067). Supplementation with BA increased the relative abundances of the two beneficial bacteria, Bifidobacterium and Bifidobacterium pseudolongum (p < 0.05, LDA > 2), but decreased that of the harmful bacterium, Clostridium sensu stricto 1, in the rectum of dairy calves. The microbial functional prediction revealed that the fecal microbial metabolism involved in primary bile acid biosynthesis was higher in the calves from the BA group. In conclusion, the present study demonstrated that adding 0.50% BA to the diet did not influence the apparent nutrient digestibility, but improved rectal microbiota health, which finally promoted the growth performance in weaned Holstein dairy calves. Full article

Aflatoxin B₁ (AFB₁) contamination in corn silage poses significant risks to livestock and human health. This study developed a non-destructive detection method for AFB₁ using color-sensitive arrays (CSAs). Twenty self-developed CSAs were employed to react with samples, with reflectance spectra collected using a portable spectrometer. Spectral data were optimized through seven preprocessing methods, including Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), first-order derivative (1st D), second-order derivative (2nd D), wavelet denoising, and their combinations. Key variables were selected using five feature selection algorithms: Competitive Adaptive Reweighted Sampling (CARS), Principal Component Analysis (PCA), Random Forest (RF), Uninformative Variable Elimination (UVE), and eXtreme Gradient Boosting (XGBoost). Five machine learning models were constructed: Light Gradient Boosting Machine (LightGBM), XGBoost, Support Vector Regression (SVR), RF, and K-Nearest Neighbor (KNN). The results demonstrated significant AFB₁-responsive characteristics in three dyes: (2,3,7,8,12,13,17,18-octaethylporphynato)chloromanganese(III) (Mn(OEP)Cl), Bromocresol Green, and Cresol Red. The combined 1st D-PCA-KNN model showed optimal prediction performance, with determination coefficient ($R_p^2$ = 0.87), root mean square error (RMSEP = 0.057), and relative prediction deviation (RPD = 2.773). This method provides an efficient solution for silage AFB₁ monitoring. Full article

Background: Chinese school-age students are at a high risk of developing obesity. However, few studies have reported individualized ways to prevent obesity by age, gender, and living regions. Methods: A total of 11,285 students aged 6–18 years were recruited and participated in this cross-sectional study. Questionnaires were used to assess scores of dietary diversity (DDS), physical activity (PA) duration, and nutritional literacy awareness. According to age and gender-specific BMI thresholds, the participants were categorized into normal and participants with obesity groups. Pearson correlation and logistic regression analysis were used to explore the association between nutritional literacy, DDS, PA, and the risk of BMI or obesity. Results: Scores of nutritional literacy were positively associated with Total DDS, Plant DDS, Animal DDS, and PA, and were negatively associated with BMI. High Total DDS (OR = 0.878, p = 0.030), Plant DDS (OR = 0.885, p = 0.027), and PA (OR = 0.869, p = 0.022) were strongly associated with a low risk of obesity. Furthermore, high Total DDS and Plant DDS decreased the risk of obesity only in the high PA group but not in the low PA group. High PA only decreased the risk of obesity in the high Total DDS and high Plant DDS group. Gender-, age-, and living-region-specific associations were also observed. Conclusions: Diverse dietary intakes and physical activity are essential for reducing the risk of obesity in Chinese school-age students. Notably, gender-, age-, and living-region-specific health and nutritional literacy education are required in school-age children to prevent obesity. Full article

The aim of this study is to develop a rapid method for monitoring leaf nitrogen content (LNC) in winter wheat, which is essential for precise field management and accurate crop growth assessment. This study used a natural winter wheat population at Shanxi Agricultural University’s experimental base as the subject. UAV-mounted multispectral sensors collected images at jointing, heading, pre-grouting, and late grouting stages. Canopy spectral reflectance was extracted using image segmentation, and vegetation indices were calculated. Correlation analysis identified highly relevant indices with LNC. Support Vector Regression (SVR), Random Forest (RF), Ridge Regression (RR), K-Nearest Neighbors (K-NN), and ensemble learning algorithms (Voting and Stacking) were employed to model the relationship between selected vegetation indices and LNC. Model performance was evaluated using the coefficient of determination (R²) and root mean square error (RMSE). Results showed that the Voting-based ensemble learning model outperformed other models. At the pre-grouting stage, this model achieved an R² of 0.85 and an RMSE of 1.57 for the training set, and an R² of 0.82 and an RMSE of 1.64 for the testing set. This study provides a theoretical basis and technical reference for monitoring LNC in winter wheat at key growth stages using low-altitude multispectral sensors, supporting precision agriculture and variety evaluation. Full article

Rationally designing and synthesizing chemosensors capable of simultaneously detecting both anions and cations via water content modulation is challenging. In this study, we synthesized and characterized a novel triazine calixarene derivative-based iodide and copper ion-selective fluorescent “turn-off” sensor. This dual-channeled fluorescent probe is able to recognize Cu²⁺ and I⁻ ions simultaneously in aqueous systems. The fluorescent sensor s4 was synthesized by displacement reaction of acridine with 1, 3-bis (dichloro-mono-triazinoxy) benzene in acetonitrile. Mass spectrometry (MS), UV-vis, and fluorescence spectra were acquired to characterize the fluorescence response of s4 to different cations and anions, while infrared (IR) spectroscopy and isothermal titration calorimetry (ITC) were employed to study the underlying selectivity mechanism of s4 to Cu²⁺ and I⁻. In detail, s4 displayed extremely high sensitivity to Cu²⁺ with over 80% fluorescence decrement caused by the paramagnetic nature of Cu²⁺ in the aqueous media. The reversible fluorescence response to Cu²⁺ and the responses to Cu²⁺ in the solution of other potential interferent cations, such as Li⁺, Na⁺, K⁺, Ca²⁺, Cd²⁺, Zn²⁺, Sr²⁺, Ni²⁺, Co²⁺ were also investigated. Probe s4 also exhibited very good fluorescence selectivity to iodide ions under various anion (F⁻, Cl⁻, Br⁻, NO₃⁻, HSO₄⁻, ClO₄⁻, PF₆⁻, AcO⁻, H₂PO₄⁻) interferences. In addition to the fluorescent response to I⁻, s4 showed a highly selective naked-eye-detectable color change from colorless to yellow with the other tested anions. Full article

In this study, a C-C bond-linked triazole-fused oxadiazole energetic compound, 4-amino-5-(4-amino-1,2,5-oxadiazol-3-yl)-2,4-dihydro-3H-1,2,4-triazol-3-one (1), was successfully designed and efficiently synthesized. Following nitration, a functional group-modified nitramine energetic compound (2) was obtained, and its energetic ionic salt (3) was further prepared. A comprehensive characterization of the structures of these three compounds was conducted, resulting in the successful elucidation of the single-crystal structures of compound 2·Ca²⁺·6H₂O and compound 3·MeOH. Compound 2 exhibited a positive formation enthalpy (56.2 kJ·mol⁻¹) and moderate mechanical sensitivity (FS = 120 N, IS = 12 J). Due to the presence of the nitramine group, compound 2 exhibited a relatively low thermal decomposition temperature (T_dec = 94 °C). However, the thermal stability of compound 3 was significantly improved (T_dec = 233 °C), which is attributed to salt formation. Compound 3 exhibits a positive formation enthalpy (121.0 kJ·mol⁻¹), along with excellent detonation performance (D = 8120 m·s⁻¹, P = 32.1 GPa) and reduced mechanical sensitivity (FS = 224 N, IS = 24 J). Therefore, the multi-heterocyclic compound, joined via C-C bond linkage, demonstrates outstanding performance, offering a new avenue for the design and synthesis of energetic materials. Full article

During the past decades, agricultural soil heavy metal pollution has been becoming increasingly severe due to urbanization and industrialization. However, the impact of externally input heavy metals on deep soils remains unclear because most previous relevant research only focused on surface soils. In the present study, Concentrations of eight heavy metals (Cu, Zn, Ni, Pb, Cr, Cd, As, and Hg) were determined for 72 pairs of surface and deep soil samples collected from an agricultural region close to the Pearl River estuary. Subsequently, heavy metal pollution and potential health risks were assessed using the Geo-accumulation Index and Potential Ecological Risk Index, a dose response model and Monte Carlo simulation, respectively. Principal component analysis (PCA) and the positive matrix factorization (PMF) receptor model were combined to analyze heavy metal sources. The results indicated that average concentrations of all heavy metals exceeded their corresponding background values. Cd was identified as the main pollutant due to its extremely high values of I_geo and Er. Unacceptable potential heavy metal non-carcinogenic and carcinogenic risks indicated by respectively calculated HI and TCR, higher than thresholds 1.0 and 1.0 × 10⁻⁴, mainly arose from heavy metals As, Cd, Cr, and Ni through food ingestion and dermal absorption. Anthropogenic sources respectively contributed 19.7% and 38.9% for soil As and accounted for the main contributions to Cd, Cu, and Hg (Surface: 90.2%, 65.4%, 67.3%; Deep: 53.8%, 54.6%, 56.2%) within surface and deep layers. These results indicate that soil heavy metal contents with deep layers were also significantly influenced by anthropogenic input. Therefore, we suggest that both surface and deep soils should be investigated simultaneously to gain relatively accurate results for soil heavy metal pollution and source apportionments. Full article

The development of materials science, artificial intelligence and wearable technology has created both opportunities and challenges for the next generation of bionic sensor technology. Bionic sensors are extensively utilized in the collection and monitoring of human biological signals. Human biological signals refer to the parameters generated inside or outside the human body to transmit information. In a broad sense, they include bioelectrical signals, biomechanical information, biomolecules, and chemical molecules. This paper systematically reviews recent advances in bionic sensors in the field of biometric acquisition and monitoring, focusing on four major technical directions: bioelectric signal sensors (electrocardiograph (ECG), electroencephalograph (EEG), electromyography (EMG)), biomarker sensors (small molecules, large molecules, and complex-state biomarkers), biomechanical sensors, and multimodal integrated sensors. These breakthroughs have driven innovations in medical diagnosis, human–computer interaction, wearable devices, and other fields. This article provides an overview of the above biomimetic sensors and outlines the future development trends in this field. Full article