China Coal Technology and Engineering Group Corp (China)

Nonalcoholic fatty liver disease (NAFLD), which affects approximately 25% of the global adult population, is a metabolic-associated hepatic disorder characterized by the interplay between inflammation and metabolism. Although evidence linking inflammatory factors and plasma metabolites to NAFLD progression, their causal relationships and mediating mechanisms remain unclear. This study employed a bidirectional Mendelian randomization (MR) approach combined with mediation analysis to investigate the causal relationships between inflammatory factors, plasma metabolites, and NAFLD. Summary data for 91 inflammatory factors and 1400 plasma metabolites were extracted from the genome-wide association studies databases and analyzed using MR. Mediation analysis was performed to examine whether the nine selected metabolites mediated the relationship between the eight inflammatory factors and NAFLD. All the analyses included tests for heterogeneity and pleiotropy. This study identified 11 inflammatory factors and 110 plasma metabolites that were significantly associated with NAFLD. Mediation analysis revealed that specific metabolites, including pregnenetriol disulfate, alanine: asparagine ratio, and X-21471, mediate the relationship between inflammatory factors and NAFLD. Notably, X-21471 was identified as a shared mediator of both tumor necrosis factor receptor superfamily member 9 (TNFRSF9) and CCL20. This integrative MR mediation analysis delineates an inflammation-metabolism-NAFLD axis, in which specific metabolites (X-21471, pregnenetriol disulfate) transmit pro-inflammatory signals (TNFRSF9/CCL20) involved in NAFLD pathogenesis. These findings suggest that combined targeting of TNFRSF9 and X-21471 may represent a precise preventive strategy for high-risk populations with metabolic comorbidities.

Underground bauxite comprehensive mechanized mining has attracted growing attention, yet regional differences in bauxite characteristics challenge its applicability and economic efficiency. The conical pick, a key cutting tool for this mining method, has cutting load characteristics that directly impact the cutting mechanism’s efficiency and reliability. Three typical bauxite samples from different mining areas were selected as research objects. After testing their composition and firmness coefficients, a linear cutting test bench was used to measure their tri-axial cutting forces at various cutting depths. Regression analysis and the linear fitting of cutting coefficients were conducted to study cutting force and normal force (two core cutting loads). The results show that power functions effectively describe the relationships between the cutting force, normal force, fluctuation coefficient and cutting depth. As the bauxite firmness coefficient and cutting depth rise, the cutting force peak value, fluctuation amplitude and frequency all increase. Excessively high or low cutting coefficients reduce the cutting efficiency; only when both the cutting coefficient and the depth are in an optimal range can the cutting efficiency reach its maximum.

This study examined how different photoperiods affect net energy partitioning and explored the mechanisms via blood biochemistry, gut microbiota, and fecal metabolites. Twelve healthy crossbred pigs (47.7 ± 7.5 kg) were randomly allocated to two groups and subjected to a self-controlled crossover design. Following an 8-day baseline under a normal photoperiod (12L:12D, 12 h light:12 h dark), pigs were assigned to two photoperiod treatment groups: prolonged photoperiod (18L:6D, 18 h light:6 h dark; P group) and shortened photoperiod (6L:18D, 6 h light:18 h dark; S group). Measurements during the baseline (12L:12D) and treatment phases are designated as N1/P (for the P group) and N2/S (for the S group), respectively. The treatment periods were interspersed with the baseline 12L:12D photoperiod and repeated six times. It was observed that, compared to N2, shortened photoperiod (S) had significantly higher net energy deposition, net energy for protein deposition, and net energy for fat deposition (p < 0.05). Compared with N2, plasma low-density lipoprotein in short photoperiod decreased (p < 0.05), and gastric inhibitory peptides increased (p < 0.05). Compared to the prolonged photoperiod, the levels of ghrelin and apolipoprotein A-IV were higher in the shortened photoperiod (p < 0.05). A shortened photoperiod decreased fecal acetic acid compared to N2 (p < 0.05) and decreased propionic acids compared to P (p < 0.05). The significance test of differences between microbial groups showed that there were different microorganisms among the different groups. The results indicated that shortening the photoperiod significantly altered the energy allocation in growing pigs.

Magnetically coupled resonant wireless power transfer (MC-WPT) systems with multi-relay coupling structures can significantly extend the transmission distance. However, system performance is highly sensitive to the spatial positions and coupling conditions of the relay coils. Any misalignment can alter the energy transfer path, causing shifts in the optimal operating frequency and reductions in efficiency. This makes conventional single-frequency or static-tuning strategies unsuitable for handling complex variations in coupling states. To address this issue, this paper investigates a three-relay MC-WPT system and proposes an adaptive frequency control and energy routing method that combines clustering and Q-learning for scenarios with severe coil misalignment. First, a physical model based on coupled-mode theory is established to describe the relationships among coupling coefficients, operating frequency, and transmission efficiency. High-dimensional coupling state data are then collected under different relay coil misalignment conditions. Next, principal component analysis (PCA) and clustering algorithms are used to extract representative coupling patterns and identify the system’s optimal efficiency points, forming an offline database that includes mappings of optimal frequencies. Furthermore, Q-learning is introduced to enable adaptive frequency control through online state recognition. Finally, under severe coil misalignment, frequency retuning of non-misaligned coils is applied to actively shield misaligned coils and reconstruct the energy transfer path. Simulation and experimental results show that the proposed method can achieve real-time frequency control and dynamic energy routing in multi-relay MC-WPT systems without additional hardware. The system transmission efficiency is significantly improved under all relay misalignment scenarios, effectively addressing the optimal frequency shift problem in multi-relay coupling structures and providing a new approach for intelligent and efficient MC-WPT systems under complex coupling conditions.

The simultaneous formation of stress transfer and structural optimization in deep underground engineering strongly influences the occurrence and severity of dynamic disasters, especially under complex stress–structure conditions. In western China, oil-rich coal is mainly distributed in complex geological structures, and the deformation, fracture, and failure of coal are essentially governed by fracture evolution under external loading. Therefore, the characteristics of the original fissure structure and the subsequent damage evolution process are critical for multi-source disaster prevention and control during oil-rich coal mining. In this study, the initiation, propagation, coalescence, and evolution of coal microfissures under multi-stage disturbances were investigated using CT scanning combined with mechanical testing. Differences in CT images among different regions were analyzed after initial oil and gas resource exploitation, and crack binary images were used to qualitatively describe fracture evolution. Meanwhile, coal CT number, crack number, trace width, gap length, and crack density were extracted to quantitatively characterize the spatio-temporal relationship between fracture structural features and multi-stage repeated disturbances, together with acoustic emission characteristics. The results provide a comprehensive description of fracture development and damage progression in disturbed coal samples, which is of great significance for understanding the fracture distribution and mechanical response mechanisms, thereby supporting safe and efficient coordinated mining of oil-rich coal in western China.

In the process of in situ stress fracturing drilling in coal mines, obtaining downhole vibration data not only improves drilling efficiency but also plays a key role in ensuring operational safety. Nevertheless, the energy supply techniques used in current vibration detectors reduce operational performance and escalate excavation expenses. This research proposes a self-powered vibration sensor based on the triboelectric nanogenerator, designed for the operational environment of coal mine in situ stress fracturing drilling. It can simultaneously detect axial and lateral vibration frequencies, and the inclusion of redundant sensing units provides the sensor with high reliability. Experimental outcomes demonstrate that the device functions across a frequency span of 0 to 11 Hz, maintaining error margins for frequency and amplitude under 4%. Furthermore, it functions reliably in environments where temperatures are under 150 °C and humidity is under 90%, proving its strong resilience to environmental factors. In addition, the device possesses self-generating potential, achieving a maximum voltage of 68 V alongside an output current of 51 nA. When connected to a 6 × 107 Ω load, the maximum output power can reach 3.8 × 10-7 W. Unlike traditional subsurface oscillation detectors, the proposed unit combines self-generation capabilities with highly reliable measurement characteristics, making it more suitable for practical drilling needs.