Search Results (273)

This study investigated the physiological regulatory mechanisms by which exogenous trehalose intake enhances the adaptation of the global stored-grain pest T. castaneum to high-concentration carbon dioxide (CO₂) stress. By supplementing exogenous trehalose under high-CO₂ controlled atmosphere stress, we measured the activities of key detoxification enzymes (e.g., carboxylesterase and cytochrome P450) and the levels of carbohydrate substances (e.g., glycogen, glucose, and trehalose). The results demonstrated that trehalose feeding significantly alleviated CO₂ induced mortality in T. castaneum and prolonged their survival time. In terms of detoxification metabolism, a trehalose-rich diet significantly reduced the activities of cytochrome P450 and carboxylesterase, while the glucose content in the beetles decreased markedly. These findings indicate that trehalose accumulation mitigates physiological damage caused by high-CO₂ stress in T. castaneum. Furthermore, exogenous trehalose intake did not disrupt carbohydrate metabolic homeostasis in the beetles, as trehalase activity and the levels of various carbohydrates remained relatively stable. This study elucidates the role of trehalose metabolism in T. castaneum’s adaptation to high-CO₂ environments, providing a theoretical foundation for optimizing controlled atmosphere grain storage technology and developing novel pest control strategies. Full article

To address the decline in measurement accuracy of magnetometers due to process errors and environmental interference, as well as the insufficient robustness of traditional calibration algorithms under strong interference conditions, this paper proposes an ellipsoid fitting algorithm based on Dynamic Adaptive Elite Particle Swarm Optimization (DAEPSO). The proposed algorithm integrates three enhancement mechanisms: dynamic stratified elite guidance, adaptive inertia weight adjustment, and inferior particle relearning via Lévy flight, aiming to improve convergence speed, solution accuracy, and noise resistance. First, a magnetometer calibration model is established. Second, the DAEPSO algorithm is employed to fit the ellipsoid parameters. Finally, error calibration is performed based on the optimized ellipsoid parameters. Our simulation experiments demonstrate that compared with the traditional Least Squares Method (LSM) the proposed method reduces the standard deviation of the total magnetic field intensity by 54.73%, effectively improving calibration precision in the presence of outliers. Furthermore, when compared to PSO, TSLPSO, MPSO, and AWPSO, the sum of the absolute distances from the simulation data to the fitted ellipsoidal surface decreases by 53.60%, 41.96%, 53.01%, and 27.40%, respectively. The results from 60 independent experiments show that DAEPSO achieves lower median errors and smaller interquartile ranges than comparative algorithms. In summary, the DAEPSO-based ellipsoid fitting algorithm exhibits high fitting accuracy and strong robustness in environments with intense interference noise, providing reliable theoretical support for practical engineering applications. Full article

In this paper, a viscoelastic (VE) tuned inerter damper (TID) that replaces conventional stiffness and damping elements with a cost-effective VE element is proposed to achieve a target-based improvement of seismically protected buildings. The semi-analytical solution of the optimal tuning frequency ratio of the VE TID is presented based on a two-degree-of-freedom (2-DOF) system, accounting for inherent structural damping disturbances, and then is extended to a MDOF system via an effective mass ratio. The accuracy of the semi-analytical solution is validated by comparing the numerical solution. Finally, numerical analyses on a viscoelastically damped building and a base-isolated building with optimally designed VE TIDs under historical earthquakes are performed. The numerical results validate the target-based improvement capability of the VE TID with a modest mass ratio in avoiding large strokes or deformation of existing dampers and isolators, and further reducing the specific mode vibration. Full article

Under the background of global climate change, shallow landslide clusters induced by extreme rainfall are occurring with increasing frequency, causing severe casualties and economic losses. To address this challenge, this study proposes an integrated approach to support both emergency response and long-term mitigation for rainfall-induced shallow landslides. The workflow includes (1) rapid landslide detection based on time-series image fusion and threshold segmentation on the Google Earth Engine (GEE) platform; (2) numerical simulation of landslide runout using the R.avaflow model; (3) landslide susceptibility assessment based on event-driven inventories and machine learning; and (4) delineation of high-risk slopes by integrating simulation outputs, susceptibility results, and exposed elements. Applied to Qugaona Township in Zhouqu County, Bailong River Basin, the framework identified 747 landslides. The R.avaflow simulations captured the spatial extent and depositional features of landslides, assisting post-disaster operations. The Gradient Boosting-based susceptibility model achieved an accuracy of 0.870, with 8.0% of the area classified as highly susceptible. In Cangan Village, high-risk slopes were delineated, with 31.08%, 17.85%, and 22.42% of slopes potentially affecting buildings, farmland, and roads, respectively. The study recommends engineering interventions for these areas. Compared with traditional methods, this approach demonstrates greater applicability and provides a more comprehensive basis for managing rainfall-induced landslide hazards. Full article

Oxidative stress poses a challenge to in vitro embryo culture. As a flavonoid, galangin (GAL) has been shown to have antioxidant effects, but the effect and antioxidant capacity of GAL in the in vitro development of porcine parthenogenetic embryos are still unknown. In this study, we demonstrated that 1 µM GAL significantly increased the blastocyst rate, decreased the accumulation of intracellular reactive oxygen species (ROS), increased the glutathione (GSH) level, and enhanced mitochondrial function in early porcine embryos. Nuclear factor erythroid-2-related factor 2 (Nrf2) was identified as the target gene of GAL via network pharmacology, and the transcript levels of related antioxidant enzymes (HO-1, NQO1, SOD2, and CAT) were found to be increased. Since Nrf2 has seven domains, we constructed Nrf2 mutants lacking different domains in vitro. We found that GAL specifically binds to the Neh1 domain of Nrf2. Subsequent embryonic experiments demonstrated that the antioxidant effect of GAL was abolished after Nrf2 deletion. These results suggest that GAL can directly bind to Nrf2 to regulate the level of oxidative stress and improve mitochondrial function in embryos. Full article

This study elucidates the mechanisms underlying the positive effect of glyceryl monolaurate (GML) on fetal intrauterine development via maternal gut-microbiota modulating effects using a sow model. Addition of GML (1000 mg/kg) improved neonatal intestinal conditions (jejunal villus height, VH/CD ratio and tight junctions) and dorsal longissimus muscle (MyoD, MyoG and MSTN) development in the GML-treated group. Furthermore, GML improved maternal gut microbiota composition by enriching short-chain fatty acid (SCFA)-producing bacteria Lactobacillus and Akkermansia. Meanwhile, SCFA concentrations in sow feces and newborn plasma, as well as their receptors (GPR41/43) in intestine and muscle were upregulated with GML, corresponding with enhanced antioxidative and anti-inflammatory capacity. Further correlation analysis revealed Akkermansia and Lactobacillus positively correlated with SCFAs, antioxidative indicators, and anti-inflammatory capacity markers. Moreover, GML inhibited the activation of the MAPK/NF-κB inflammatory signaling pathway. In summary, GML enhanced fetal intrauterine development by modulating sow intestinal SCFA-producing bacteria. Full article

Achieving the synergistic effect of pollution reduction and carbon mitigation (PRCM) is a core pathway for promoting green and low-carbon transition and realizing the “dual carbon” goals, as well as a crucial mechanism for coordinating ecological environment governance with climate action. Based on panel data from three major urban agglomerations (Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta) between 2008 and 2019, this study employs network centrality and structural holes to characterize urban network positions (UNP), and systematically investigates the impact mechanisms and spatial heterogeneity of urban network positions on PRCM synergy using a dual fixed-effects model. The findings reveal that (1) urban network positions exert significant inhibitory effects on the overall synergy of PRCM, meaning higher centrality and structural hole advantages hinder synergistic progress. This conclusion remains valid after robustness checks and endogeneity tests using instrumental variables. (2) Heterogeneity analysis shows the inhibitory effects are particularly pronounced in Type I large cities and southern urban agglomerations, attributable to environmental governance path dependence caused by complex industrial structures in metropolises and compounded pressures from export-oriented economies undertaking industrial transfers in southern regions. Northern cities demonstrate stronger environmental resilience due to first-mover advantages in heavy industry transformation. (3) Mechanism testing reveals that cities occupying advantageous network positions tend to reduce environmental regulation stringency and research and development investment levels. Conversely, cities at the network periphery demonstrate late-mover advantages by embedding environmental regulations and building stable technological cooperation partnerships. This study provides a theoretical foundation for optimizing urban network spatial configurations and implementing differentiated environmental governance policies. It emphasizes the necessity of holistically integrating network effects with ecological effects during new-type urbanization, advocating for the establishment of a multi-scale coordinated environmental governance system. Full article

Objective: Growth retardation in adolescents caused by nutritional deficiency requires effective intervention. A novel dietary supplement containing bamboo shoot extract, amino acids, and calcium citrate (Kidtal + Ca, KDTCa) was evaluated for its growth-promoting effects. Methods: After acclimatization, sixty-three 3-week-old male Sprague-Dawley (SD) rats were randomly divided into a normal control group and model groups. Growth retardation was induced in the modeling groups through calcium-deficient feeding, followed by administration of KDTCa, bamboo shoot extract and amino acids (Kidtal), or calcium citrate (CC). After 6 weeks of intragastric administration, the mechanical properties, microstructure, and growth plate development of bone were evaluated using three-point bending, micro-CT, and H&E staining, respectively. Bone calcium/phosphorus distribution and fecal calcium apparent absorption rate were measured by ICP-MS. Results: All inter-group differences were analyzed using one-way analysis of variance and checked using the Tuckey test. KDTCa treatment dose-dependently enhanced bone development in calcium-deficient rats. Compared to the model group, H-KDTCa significantly restored naso-anal length (p < 0.05) and body weight (p < 0.01). KDTCa supplementation significantly restored calcium and phosphorus levels in blood and bone. Three-point bending experiments showed that the stiffness and bending energy were increased by 142.58% and 384.7%. In bone microarchitecture, both bone mineral density (BMD) and microstructural parameters were significantly improved. These findings were consistent with the increased long bone length (p < 0.05) and decreased serum BALP/TRACP levels (p < 0.001). Dose-dependent IGF-1 elevation (p < 0.01) potentially mediated growth plate elongation by 35.34%. Notably, KDTCa increased calcium apparent absorption by 6.1% versus calcium-only supplementation at equal intake. Conclusions: KDTCa improves bone microstructure and strength, restores bone metabolism, and enhances growth plate height via promoting IGF-1 secretion to facilitate bone development. Further studies are needed to determine whether the components and calcium in Kidtal have a synergistic effect. Full article

5-aminotetrazole (5AT)-based gas generators, particularly the 5AT/NaIO₄ system, have garnered interest for their high gas production and energy potential. This study investigates the impact of various metal oxides (MnO₂, Al₂O₃, TiO₂, CuO, Fe₂O₃, MgO, ZnO, and MoO₃) on the thermal decomposition and combustion performance of 5AT/NaIO₄. The REAL calculation program was used to infer reaction products, which indicated that the gas products are almost all harmless, with negligibly low percentages of NO and CO. Thermogravimetric analysis revealed that metal oxides, especially MoO₃, significantly advance the decomposition process above 400 °C, reducing the activation energy by 130 kJ/mol and lowering critical ignition and thermal explosion temperatures. Combustion performance tests and closed bomb tests confirmed MoO₃’s positive effect, accelerating reaction rates and enhancing decomposition efficiency. The system’s high Gibbs free energy indicates non-spontaneous reactions. These findings provide valuable insights for designing environmentally friendly gas generators, highlighting MoO₃’s potential as an effective catalyst. Full article

Network traffic generation technology plays a critical role in network testing and security protection. It simulates various network traffic patterns, offering intrusion detection systems with diverse samples. These samples enhance the system’s adaptability to emerging traffic types and improve detection capabilities. Additionally, it provides high-quality data for traffic analysis algorithms. These data help optimize model performance by increasing robustness and applicability. However, traditional generative models, like GAN networks, have limited capacity for capturing temporal flow features. As a result, they produce suboptimal generation outcomes. To address this issue, we propose the diffusion–attention traffic generation (DATG) framework. This framework combines a diffusion model with a self-attention mechanism. This integration ensures more accurate simulation of temporal characteristics. The diffusion model’s progressive denoising process guarantees generation stability. Meanwhile, the self-attention mechanism captures global temporal dependencies in traffic sequences. Experimental results validate the superior performance of our DATG by reducing the JSD to 0.18 through the synergistic optimization of the diffusion model and the self-attention mechanism, which is 41.9% better than that of GAN. Additionally, it establishes cross-step-length dependencies through the time dimension self-attention mechanism, which reduces the CRPS value to 0.13, which is 31.6% lower than that of GAN. Full article

A spherical CuO-Bi₂O₃-MgO/SiO₂ catalyst was prepared using the coprecipitation-gel method. The study investigated the influence of the MgO/SiO₂ ratio on the catalyst structure and the activity of the catalyst in the preparation of 1,4-butanediol from formaldehyde acetylenation. The activity and filtration performance of the catalyst were compared with commercial samples. The study found that different MgO/SiO₂ ratios not only changed the size of CuO particles, the orientation of crystal faces, the specific surface area, and the pore distribution in the catalyst, but also adjusted the interaction between CuO and SiO₂. In addition, different MgO/SiO₂ ratios could significantly alter the structure of the catalyst and enhance its activity, with the highest activity achieved when the MgO/SiO₂ ratio was 1:3. Experimental results showed that the spherical CuO-Bi₂O₃-MgO/SiO₂ catalyst in this study achieved a selectivity of 96.3% and a conversion rate of 94.0% when reacting with formaldehyde at a concentration of 38 wt% for 12 h. The catalyst outperformed commercial samples in terms of activity and had the same strength level and better filtration separation performance as commercial samples. Full article

Wood–plastic composites (WPCs) are important materials used in interior architectural decorations and landscape construction products. Enhancing the cutting performance of WPCs is of great significance for improving both production efficiency and product quality in factories. This study aims to elucidate the impact of fluorine nano-coating technology on the cutting performance of cemented carbide tools during the milling of WPCs. The main results are given as follows. The cutting force and surface roughness showed similar trends with the varied parameters; both increased with increasing cutting depth and decreased with increasing cutting speed. The fluorine nano-coating technology exerts a positive influence on the cutting performance in terms of lower cutting forces and surface roughness. Meanwhile, based on the analysis of variance results, the experimental factors of cutting speed, depth, and surface treatment had a significant contribution to both cutting force and surface roughness, and cutting depth had the greatest impact on cutting force and surface roughness, followed by cutting speed and tool surface treatment. In general, the cutting performance of WPCs can be improved by higher cutting speed and lower depth, with the tool surface treated with fluorine nano-coating. Full article

Magnetosomes are magnetic nanocrystals synthesized by bacteria that have important application value in biomedicine. Therefore, it is very important to evaluate their biocompatibility. It has been reported that the extremophilic acidophilic bacterium Acidithiobacillus ferrooxidans, which is aerobic, can synthesize intracellular Fe₃O₄ magnetosomes. In this paper, we performed a comprehensive and systematic evaluation of the biocompatibility of magnetosomes with an average particle size of 53.66 nm from Acidithiobacillus ferrooxidans, including pharmacokinetics, degradation pathways, acute systemic toxicity, cytotoxicity, genotoxicity, blood index and immunotoxicity. The phase composition of the magnetosomes was identified as Fe3O4 through XRD and HRTEM analyses. Biocompatibility evaluation results showed that magnetosomes metabolized rapidly in rats and degraded thoroughly in major organs, with almost no residue. When the injection concentration was low (40 mg/kg, 60 mg/kg), magnetosomes would not cause pathological changes in the major organs of mice, basically. At the same time, magnetosomes had low cytotoxicity, genotoxicity, immunotoxicity and hemolysis rate, which proved that the magnetosomes synthesized by Acidithiobacillus ferrooxidans are magnetic nanomaterials with good biocompatibility. This research provides an important theoretical basis for the large-scale application of bacterial magnetosomes as functional magnetic nanomaterials. Full article

CO₂, an abundant and renewable C1 source, presents significant potential for applications in organic synthesis. Hydrazones, recognized for their distinctive properties, exhibit high versatility in synthetic chemistry, facilitating numerous chemical transformations. Given their crucial roles in organic synthesis, the combination of CO₂ with hydrazones has garnered increasing research interest. This review provides a comprehensive summary of recent progress in reactions involving CO₂ and hydrazones or their derivatives. These include the coupling of amines and N-tosylhydrazones with CO₂, the umpolung-mediated carboxylation of hydrazones/N-tosylhydrazones with CO₂, the cyclization of hydrazones with CO₂, and lactamization reactions incorporating N-tosylhydrazones and CO₂. These transformations utilize the diverse reactivity of hydrazones and their derivatives to capture and convert CO₂, generating valuable organic compounds with both academic and practical relevance. Additionally, the review examines the mechanisms underlying these reactions, offering critical insights for advancing research in this area. Full article

To address the measurement accuracy degradation of triaxial magnetometers caused by manufacturing errors and environmental interference, and the limited robustness of traditional calibration methods, this study proposes a Dynamic Hierarchical Elite-guided Particle Swarm Optimization (DHEPSO)-based ellipsoid fitting algorithm. First, an error model for the triaxial magnetometers is established. Next, the DHEPSO algorithm is utilized to fit the ellipsoid parameters by integrating a dynamic hierarchical mechanism, elite guidance strategy, and adaptive inertia weight adjustment, thereby balancing global exploration and local exploitation to efficiently optimize the parameters. Finally, error compensation and precise calibration are achieved using the optimized parameters. The simulation results show that, compared to the Least Squares Method (LSM), it reduces the absolute distance between the simulated data and the ellipsoid by 63.10% and the post-calibration total magnetic field intensity standard deviation by 60% under outlier interference. Against the traditional PSO, TSLPSO, MPSO, and AWPSO, DHEPSO achieves total distance reductions of 48.52%, 47.74%, 56.71%, and 33.09%, respectively, with faster convergence. The statistical analysis of 60 trials confirms DHEPSO’s stability, exhibiting lower median error and interquartile range. The results validate DHEPSO’s high precision and robustness in high-noise environments, offering theoretical support for engineering applications. Full article