Urumqi Vocational University

This study systematically investigates the synergistic effects of Al/Ti microalloying and subsequent aging treatment on the microstructure and properties of the Cr₉Fe₄₆Ni₁₅Mn₃₀ high-entropy alloy. The results demonstrate that Al and Ti additions induce pronounced grain refinement, reducing the average grain size from 5.2 μm to 1.52 μm, promote the formation of nanoscale Al/Ti-rich precipitates together with ~0.7 % body-centered cubic (BCC) phase, and decrease the recrystallization fraction to 92.1 %. Subsequent aging at 600 °C further improves microstructural homogeneity, increases the recrystallization fraction to 99.2 %, and reduces the kernel average misorientation (KAM) to 0.07°. Mechanical testing reveals that microalloying enhances the tensile strength to 708 MPa and significantly lowers the hydrogen embrittlement sensitivity index (δH) to 2.6 %. After aging, a pronounced hydrogen-induced plasticity effect is observed, with δH decreasing to −16.8 % and the elongation after hydrogen charging increasing to 29.2 %. In addition, the aged Al/Ti-microalloyed alloy exhibits superior corrosion resistance, characterized by the most positive corrosion potential (−0.279 V), the lowest corrosion current density (6.39 × 10⁻⁷ A·cm⁻²), and the largest capacitive arc radius in electrochemical impedance spectroscopy. These improvements are attributed to the formation of a stable Cr₂O₃ passive film and a reduced defect density.

With the booming development of the tourism industry, scenic spots often face the risk of tourist overload during peak hours. In response to the weak dynamic adaptability of traditional safety management methods and the difficulty in accurately predicting passenger flow in high-density scenarios, a safety capacity management method based on Elman Recurrent Neural Network Genetic Algorithm (Elman-GA) is proposed. This method uses Elman neural network for passenger flow prediction, and decomposes the raw data for denoising through Complete Ensemble Empirical Mode Decomposition (CEEMD). Using an improved GA as the optimization engine and designing a simulated annealing mechanism, the network is deeply coupled with the algorithm to achieve intelligent and secure capacity management decisions. The experimental findings reveal that the prediction accuracy of the research method is tested, and the lowest Root Mean Square Error (RMSE) reaches 12.3% when the window length is 6 h. When testing the safety control effect of the research approach, the highest F1 score is 0.91 when the warning threshold reaches 85%. The robustness of the research approach is assessed, and when the noise amplitude increases to 30%, the RMSE reaches 35.4%. The prediction results of the research method are more accurate and stable, which can offer technical foundation to the establishment of smart tourism scenic spots.

Lacticaseibacillus rhamnosus WH.FH-19 exhibits robust probiotic and technological traits for fermented dairy applications. L. rhamnosus WH.FH-19 shows superior functional potential compared to the benchmark strain Lacticaseibacillus rhamnosus GG. Kinetic studies confirm L. rhamnosus WH.FH-19’s vigorous growth and rapid acidification kinetics in bovine milk. In vitro characterization reveals enhanced probiotic properties, including significantly greater epithelial adhesion, tolerance to gastrointestinal stresses, cholesterol assimilation capacity, and antioxidant activity. Comprehensive safety assessment demonstrated the absence of hemolysis, sensitivity to clinically relevant antibiotics, and negligible tyramine production. Optimal synergistic fermentation with L. bulgaricus CICC 6047 and S. thermophilus CICC 6038 was achieved using a defined inoculum ratio. Under these conditions, L. rhamnosus WH.FH-19 specifically potentiated the activity of the S. thermophilus strain, accelerating fermentation kinetics without subsequent post-acidification while improving product sensory attributes. These findings establish L. rhamnosus WH.FH-19 as a safe, functionally robust probiotic with significant technological benefit for commercial fermented dairy production.

IntroductionInflammatory bowel disease (IBD) is a chronic, relapsing inflammatory disorder of the gastrointestinal tract. Its pathogenesis is complex and not fully understood, so it remains incurable. Traditional Chinese medicine (TCM) attracts attention as a potential option. It offers multi-target actions. This study investigated the protective effects of an aqueous extract of Miniature Rose (MR), a medicinal plant from Xinjiang, in a dextran sulfate sodium (DSS)-induced murine model of IBD. We focused on gut microbiota, intestinal barrier integrity, and metabolic homeostasis.MethodsIBD was induced in mice by DSS, followed by intervention with different doses of aqueous MR extract. A multi-faceted approach incorporating 16S rRNA sequencing, non-targeted metabolomics, immunohistochemistry, and ELISA was used to evaluate the effects of MR on gut microbiota composition, fecal metabolic profiles, intestinal barrier protein expression, and the expression of the inflammatory proteins TLR4 and TLR9.ResultsTreatment with aqueous MR extract markedly alleviated DSS-induced colitis. MR improved intestinal barrier integrity by upregulating the tight junction proteins Occludin (OCC) and Zonula Occludens-1 (ZO-1), while concurrently downregulating TLR4 and TLR9. MR administration also markedly modulated the gut microbiota, increasing the relative abundance of beneficial genera (Bacteroides and Alloprevotella) and decreasing the abundance of the pathobiont Erysipelatoclostridium. In addition, MR mitigated the metabolic dysregulation observed in DSS-induced colitis.ConclusionMR ameliorates DSS-induced colitis through a multifaceted mechanism that involves coordinated regulation of the gut microbiota, restoration of the intestinal barrier, inhibition of inflammatory protein expression, and correction of metabolic dysregulation. These findings highlight the potential of MR as a multi-target therapeutic candidate and provide an experimental basis for its further preclinical and clinical evaluation in IBD.

With the rapid development of the intelligent manufacturing industry, the demand for technical talents in industrial robot technology has become increasingly urgent. Focusing on the application value of virtual simulation technology in the practical teaching of industrial robot major and combining with the national vocational education reform policies, this paper explores the innovative role of virtual simulation technology in the practical teaching model from four dimensions: teaching cost optimization, safety improvement, scenario expansion, and evaluation innovation. The research shows that virtual simulation technology can effectively solve the “three highs and three difficulties” problems in traditional practical teaching, promote the in-depth development of the integration of industry and education, and provide strong support for cultivating high-quality technical and skilled talent in the field of industrial robots.

This study presents a comprehensive numerical investigation into the aerodynamic behavior of pedestrian walkway slabs and cable troughs mounted on high-speed railway bridges under crosswind conditions. Using a full-scale T-beam bridge model with auxiliary components, unsteady flow simulations were performed employing the Improved Delayed Detached-Eddy Simulation (IDDES) approach coupled with the Shear Stress Transport (SST) k-ω turbulence model. Both steady and unsteady flow fields were examined to characterize velocity and pressure distributions, vortex shedding mechanisms, and aerodynamic force responses over a range of attack angles (α = –20° to +20°), yaw angles (β = 0° to 60°), and wind speeds (20–40 m/s). Results reveal that vortex-induced oscillations dominate at negative attack angles, while high positive angles suppress shedding and widen spectral energy. Spanwise flow effects persist across large yaw angles, maintaining consistent wake patterns but with reduced magnitudes. Aerodynamic coefficients of lift on slabs and troughs peak near α = 0°, with failure wind speeds computed at approximately 35 m/s for slabs and 22 m/s for troughs. Based on these findings, design recommendations are proposed to mitigate uplift and vibration risks in auxiliary bridge fixtures under extreme wind conditions. This work advances the assessment of crosswind safety for railways by incorporating the indirect effects of line-side structures on train operations, providing a basis for defining critical wind speed thresholds for railway bridge safety.

Liu Liangcheng’s first prose collection, A Village of One’s Own, was published in 1998 and quickly attracted widespread attention in the literary circle. In this work, assuming the identity of a “rural philosopher”, he employs a multitude of animal imageries to convey his unique insights into life. Particularly, the imagery of dogs occupies a prominent position in the text. It not only showcases his distinctive artistic style but also profoundly embodies the depth of his thoughts. Through diverse narrative techniques and the interweaving of memories and reality, Liu Liangcheng depicts the rich and three-dimensional life of dogs. Meanwhile, via this imagery, he presents the close yet complex relationship between animals and human life. Additionally, influenced by the geographical and cultural features of the borderland, Liu Liangcheng also reveals in-depth reflections on bioethics and the human living condition. These reflections encompass the relationship between humans and all things in nature, with “dogs” serving as a vivid carrier.

Abstract This paper focuses on the fixed-time (FDT) phase agreement and frequency synchronization problem of Kuramoto-oscillator networks. Traditional controllers for FDT synchronization of Kuramoto-oscillator networks often suffer from complex structures and high costs. To address these issues, a novel FDT controller consisting of only two terms or even a single term is proposed. The simplicity of this controller allows it to adapt better to various types of Kuramoto-oscillator networks and more complex scenarios, thereby significantly expanding the application scope of FDT synchronization control. By efficiently allocating control resources and reducing unnecessary adjustments of control signals, the controller achieves cost-effective and efficient synchronization. Furthermore, the upper bound of the synchronization time and the sufficient conditions for synchronization are rigorously derived, simulation results show that the newly designed controller is effective.

Businesses can utilize machine learning (ML) to analyze large and complex datasets more efficiently. This article reviews how the use of ML enhances data analysis and discusses issues related to data quality, managing large datasets, and integrating models with business intelligence. The study highlights the application of ML, encompassing supervised, unsupervised, and reinforcement learning, in customer segmentation, data-driven insights, and the identification of unusual occurrences. Case studies demonstrate that the use of ML analytics leads to improved accuracy, more efficient resource utilization, and enhanced sustainability support in technology and transportation sectors. The results highlight that effective data preparation, flexible training, and seamless BI integration are essential for addressing implementation challenges. Therefore, the article highlights that utilizing ML for business data analysis is a successful and repeatable approach to drive innovation and enhance a company’s competitive position.