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Despite extensive research on AI’s theoretical benefits in entrepreneurship, few studies compare machine learning models’ effectiveness using real-world data or address challenges like model interpretability and overfitting. This study investigates how AI-driven big data analytics enhances entrepreneurial decision-making in the digital economy by evaluating four machine learning models—Decision Trees, Random Forest, Gradient Boosting, and Histogram-Based Gradient Boosting—to predict AI service focus. The results reveal that Gradient Boosting outperformed others with a testing R² of 0.9914, identifying company reputation and location as the most influential predictors of AI adoption. These findings challenge assumptions about organizational size’s role in digitalization, emphasizing the strategic value of brand and geography. Key limitations include overfitting in Decision Trees and Random Forest, and reliance on static datasets that constrain real-time adaptability. The results demonstrate AI’s potential to reduce uncertainty in entrepreneurial strategy, offering actionable insights for market entry and investment decisions. Future research should incorporate real-time data streams and hybrid AI-human frameworks to improve generalizability.

The dissolution kinetics occurring on clay minerals are influenced by various factors, including pH, temperature and mineral lattice structure. However, the influence of the surfactant is rarely studied. In the present work, cationic surfactants were investigated in terms of the dissolution of clay minerals in acidic environments. Kaolinite was selected as the representative clay mineral. The cationic surfactant inhibited the dissolution of clay minerals because it limited the attack of H+ on the kaolinite surface and then inhibited the dissolution of kaolinite by modifying the hydrophilicity of the kaolinite surface towards hydrophobicity. The inhibition ability of the surfactant might be related to its molecular structure and the type of acid used in dissolution experiments.

Heavy metal pollution refers to the presence of excessive levels of heavy metal elements in soil beyond their natural background concentrations, posing serious threats to human health and ecological systems. Several factors are involved in the contamination disparity in agriculture soils from various terrains, demanding extra care. An examination of the topographical HM dispersions in farmland soils from the Licheng District was conducted to reveal spatial changes in pollution levels and sources and to establish an empirical framework to develop targeted remediation strategies and promote sustainable land management practices. Cd and As had over-standard rates of more than 50% in the low-lying area, whereas the HMs in the high-lying area had over-standard rates of more than 50%. Also, the rates of HMs in high terrain were higher than in low terrain. Using the single-factor pollution index, only low-lying Cu, Ni, Pb, and Hg contamination levels were clean in low-lying and high-lying areas. The overall decline in HM pollution occurred from high to low terrain, triggered by soil physicochemical properties and human interventions. Meanwhile, strong anthropogenic influence fell in high terrain for pollution. Nevertheless, low levels of HM-integrated contamination prevailed in both topographies. Natural and anthropogenic processes gave rise to environmental pollution, such as soil formation, fertilization, metal smelting, and traffic emissions. Overall, the district held a low risk for HMs. The results highlight that strong anthropogenic interventions resulted in increased HM contamination, in addition to natural processes. It is possible to further reduce HM pollution and risk by promoting scientific agricultural techniques, new energy vehicles, and cleaner production.

In order to study the fatigue performance of wheel and enhance its lightweight design level, this article proposes the structure, design and optimization method of magnesium-aluminum alloy assembled wheel. Taking a 16 × 61 / 2 J type wheel as the research object, the optimal topology of wheel spoke is solved by constructing a topology optimization model for wheel bending and radial fatigue test conditions. A finite element model for bending and radial fatigue testing of assembled wheels was established, which simulates and analyzes the fatigue performance and its influencing factors of the wheel under two working conditions. Combined with contribution analysis method, the modified NSGA-II and entropy weight grey relation analysis (EGRA), the multi-objective optimization of assembled wheel was performed. The result demonstrated that the weight reduction of the assembled wheel after optimized design is 4.49%, while the bending fatigue life and radial fatigue safety factor are decreased by 9.95% and 25%, respectively. In order to better balance the performance of assembled wheel and achieve lightweight design, this article combines the joint topology optimization of assembled wheels with multi-objective optimization method for multiple working conditions and screens the optimal compromise solution by EGRA, which provides an approach for wheel lightweight design and multi-objective optimization.

The long-term circulation of cold water within the deep heat reservoir in enhanced geothermal system (EGS) involves dynamic evolution of thermal-hydraulic-mechanical (THM) fields. The characteristics of discrete fracture network (DFN) in the reservoir also affect the thermal performance of EGS. In this paper, the influence of the DFN on the performance of EGS considering THM multi-physical field couple was numerically investigated. The effect of water property change and cold tension stress with temperature was considered. The influence of DFN characteristics (fracture density, fracture aperture, angle between fracture and well connection line and fracture pattern) was discussed. Results indicate that the effect of considering water property change on the Darcy velocity is larger than considering the stress field. Considering water property change and stress field both lead to a larger Darcy velocity of the fracture water and make the temperature field drop faster. With the increase of fracture density, the production Darcy’s velocity increases gradually and the difference in thermal recovery efficiency is significant. Fracture aperture has a greater influence on the temperature field of the whole DFN reservoir than fracture density. The larger the fracture aperture, it will take away the heat energy from the heat reservoir faster. The smaller the angle between fracture and well connection line, the smaller the flow resistance of the working fluid, and the larger the equivalent permeability of the reservoir DFN system. The differences in the seepage field are small for the same range of statistical characteristics and parameter values for the DFN patterns. The DFN system with uniform fracture distribution should be selected for a better EGS reservoir, and the angle between the direction of the main fracture group and the direction of the well connection line should be at a certain acute angle.

Freshwater mussels are both among the most diverse and endangered faunas worldwide. The gut microbiota of species plays a key role in nutrition and immunity, such as preventing it from pathogen invasion, synthesizing beneficial secondary metabolites, and contributing to the digestion of complex nutrients. Information on the gut microbiota could have significant implications for conservation biology, especially for threatened or endangered species. However, there is relatively little study into the gut microbiota of freshwater mussels. Here, the gut microbiota diversity was analyzed in endangered (Solenaia carinata), economical (Sinohyriopsis cumingii), and common (Sinanodonta woodiana) freshwater mussels using 16S rRNA gene sequencing. This study represents the first to compare the gut microbiota diversity of endangered, economical, and common Chinese freshwater mussels. The results showed that 13,535 OTUs were found in S. carinata, 12,985 OTUs in S. cumingii, and 9,365 OTUs in S. woodiana. The dominant phylum in S. carinata and S. cumingii was Fusobacteria, and was Firmicutes in S. woodiana. Alpha diversity indices indicated that S. carinata and S. cumingii had a higher abundance and diversity of gut microbiota than S. woodiana. The composition of gut microbiota was different among three freshwater mussels, but their composition variation was not significant. This study provides insight for the conservation of freshwater mussel biodiversity, which will not only help conserve these vulnerable groups but also, will offer wider benefits to freshwater ecosystems. This study represents the first to compare with the gut microbiota diversity in endangered, economical, and common Chinese freshwater mussels. The composition of gut microbiota among three freshwater mussels was different, but their composition variation was not significant. The composition of gut microbiota for three freshwater mussels was correlated with dissolved oxygen, turbidity, and chlorophyll‐a. This study provides valuable insight for the conservation of freshwater mussel biodiversity, which will not only help conserve these vulnerable groups but also, will offer wider benefits to freshwater ecosystems.

The Yangtze River drainage in China is among the most species rich rivers for freshwater mussels (order Unionida) on Earth with at least 68 species known. The freshwater mussels of the Yangtze River face a variety of threats with indications that species are declining in abundance and area of occupancy. This study represents the first analyses of the genetic structure and diversity for the common and widespread freshwater mussel Nodularia douglasiae based on microsatellite DNA genotypes and mitochondrial DNA sequences. Phylogenetic analysis a fragment of the COI mitochondrial gene indicated that N. douglasiae collected from across the middle and lower Yangtze River drainage are monophyletic with N. douglasiae from Japan, Russia, and South Korea. The results of the analysis of both the mtDNA and microsatellite datasets indicated that the seven collection locations of N. douglasiae in the middle and lower Yangtze River drainage showed high genetic diversity, significant genetic differentiation and genetic structure, and stable population dynamics over time. Moreover, we found that the connections among tributaries rivers and lakes in the Yangtze River drainage were important in maintaining gene flow among locations that N. douglasiae inhabits. An understanding of the genetic structure and diversity of a widespread species like N. douglasiae could be used as a surrogate to better understand the populations of other freshwater mussel species that are more rare in the Yangtze River drainage. At the same time, these results could provide a basis for the protection of genetic diversity and management of unionid mussels diversity and other aquatic organisms in the system.

The coal production process is faced with intricate groundwater intrusion mechanisms and variable groundwater intrusion primary governing factors, and the uncertainties associated with the factors make the prediction of base groundwater intrusion more difficult. This research focuses on the Tangjiahui Coal Mine, which is a representative coalfield in Northwest China. The prediction index system including coal seam base aquifer capacity, aquiclude capacity, and geological structure is selected, with seven prediction factors being considered. Secondly, the analytic hierarchy process (AHP) and entropy weight (EW) method are applied to calculate the subjective and objective weights. On this basis, two models of comprehensive weight based on AHP-EW improved by game theory and improved variable weight of base groundwater intrusion risk based on the foundation of comprehensive weight are constructed. The predicted results are displayed by using the powerful spatial management and information processing functions of GIS, and the performance of the two models is discussed and compared. By comparing the prediction results with the in-situ groundwater intrusion points, it is found that the prediction model has high accuracy. Finally, the prevention strategies of base groundwater intrusion are put forward based on the risk zoning outcomes. The research findings can generate a scientific theoretical foundation for mine groundwater disaster prediction.

This study was to analyze the dynamics of tissue damage and inflammatory response markers perioperatively and whether these differ between robotic laparoscopy and conventional laparoscopy in early endometrial cancer. In a randomized controlled trial conducted at SHANGHAI FIRST MATERNITY and INFANT HOSPITAL, eighty women with early-stage, low-risk endometrial cancer were randomly assigned to receive either robotic or conventional laparoscopy. Blood samples were collected at admission, immediately before surgery, 2 h after surgery, 24 h after surgery, 48 h after surgery, and 1 week after surgery. The samples were analyzed for various biomarkers associated with inflammatory processes and tissue damage. These included high-sensitivity C-reactive protein (hs-CRP), white blood cell count (WBC), platelet count, interleukin-6 (IL-6), cortisol, creatine kinase (CK), and tumor necrosis factor-alpha (TNF- ). These markers provide insights into the underlying physiological responses and potential tissue-level changes within the study participants. There was no significant difference in clinical and preoperative data between two groups. The results showed that the patients who underwent robotic laparoscopy had a longer pre-surgical time compared to the conventional laparoscopy group. However, the robotic group had shorter operating times, quicker vaginal cuff closures, and lower estimated blood loss compared to the conventional laparoscopy group. The hospital stays, Visual Analog Scale (VAS) score and drainage volume on the first day after operation were lower in robotic group compared to conventional laparoscopy group. hs-CRP, WBC, IL-6 and cortisol were significantly lower in the robotic group, though the differences were transient. This study demonstrated that robotic laparoscopy, used in early endometrial cancer treatment, leads to a reduced inflammatory response, less tissue damage, and lower stress levels, as evidenced by decreased levels of hs-CRP, IL-6, and cortisol, compared to conventional laparoscopy. These findings suggest that robot- laparoscopy may facilitate a quicker recovery and improve patient-reported outcomes.

Background This study aimed to evaluate the management of asymptomatic intrauterine lesions detected by ultrasonography. Methods Patients who underwent diagnostic hysteroscopy for asymptomatic lesions, including pre- and post-menopausal endometrial polyps, post-menopausal endometrial thickening (ET ≥5 mm) and reduplicative endometrial heterogeneity detected by transvaginal ultrasonography (TVUS), were recruited for this study. Results In the 792 recruited patients, the symptom-free focal masses within the uterine cavity detected by TVUS included 558 patients with pre- or post-menopausal endometrial polyps and 234 patients with postmenopausal endometrial thickening. No pre-menopausal patient presented with carcinoma. The polyp diameter (PD) was not identified as an independent risk factor for malignancy in this study. A significant difference ( P  = 0.036, < 0.05) in both benign and malignant endometrial lesions was observed between two groups of post-menopausal women stratified using an endometrial thickness cut-off of ≥11 mm. The TVUS was highly sensitive (94%) for pre-menopausal polyps. This technique had a specificity and positive predictive value of 84.4 and 92.7%, respectively, for postmenopausal polyps. The TVUS was clearly valuable for ruling out polyps, as indicated by a negative likelihood ratio (LR-) of 0.087. Among postmenopausal women with endometrial thickening, the area under the receiver operating characteristic curve was 0.828 ( P  < 0.001). An ET cut-off value of 12.5 mm yielded a sensitivity of 72.7% and specificity of 86%. Conclusion We recommend follow-up alone for women with asymptomatic uterine polyps, particularly those who are pre-menopausal. Additionally, gynaecologists should consider risk factors such as age, obesity, polycystic ovarian syndrome, and diabetes. Prospective long-term follow-up studies should be conducted after hysteroscopic polypectomy to evaluate the recurrence rate of endometrial lesions.