The laminectomy robot is an auxiliary surgical robot developed for laminectomy in recent years. In order to explore the differences in reducing orthopedic surgeons' mental workload between laminectomy robot techniques and traditional laminectomy methods, a multimodal evaluation incorporating an electrocardiogram, eye tracking, and the NASA-TLX scale was utilized to assess the mental workload of orthopedic surgeons undergoing both surgical procedures. Through simulated surgical trials, 12 orthopedic surgeons performed laminectomies employing both the robot-assisted and the conventional techniques, collecting multimodal data for both variance and correlation analyses. The findings indicate significant differences in subjective mental workload between the laminectomy robot and traditional techniques (P<0.05). However, in terms of electrocardiogram indicators such as average heart rate, the low frequency/high frequency ratio (LF/HF), and the standard deviation of NN intervals (SDNN), no significant differences are noted. Significant differences are observed in eye movement indicators, including pupil diameter (P<0.05), fixation rate (P<0.05), and saccade rate (P<0.01). Further correlation analysis underscored a notably significant relationship between pupil diameter and levels of subjective mental workload in both surgery techniques. In conclusion, compared to traditional laminectomy methods, the use of laminectomy robots can alleviate the mental workload on orthopedic surgeons, with both pupil diameter and subjective mental workload levels providing effective reflections of the orthopedic surgeons’mental workload.

Machine learning technology is a hot research topic at present. It is widely used in various prediction, recognition and classification tasks with its strong learning ability and high versatility. The application of machine learning in computational structural mechanics was discussed, with emphasis on its role in material property prediction, structural damage analysis, improvement of traditional methods, constitutive equation establishment and differential equation solving. Through literature review, the advantages of machine learning algorithms such as neural networks, support vector machines and random forests in improving computational efficiency and design process optimization were summarized. It is pointed out that the combination of machine learning and classical computing methods provides a new way to solve engineering problems. Future research will focus on algorithm optimization, model improvement and interdisciplinary technology integration.

In order to investigate the vortex characteristics and wave propulsion generated by the undulating pectoral fins of the flatworm, a simplified model of the flatworm's pectoral fin was re-established using the linear interpolation method in MATLAB. The relationship between thrust and kinetic energy, during the flatworm's swimming was derived, and the undulating posture of the flatworm was simulated using Fluent software. The results show that compared to similar MPF propulsion fish species such as rays and cownose rays, the flatworm, due to its narrow and elongated body structure, exhibits better stability, adaptability, and flexibility in water. When the Reynolds number is set to 1.05×10⁵, the pectoral fins of the flatworm demonstrates more stable thrust, effectively reducing flow separation and turbulence effects. At a frequency of 0.6 Hz and a wavelength of 2.5 m, the pectoral fins displays optimal undulating parameters, enhancing fluid mixing and energy transfer efficiency, thereby improving the flatworm's propulsion performance. It is concluded that, during the mid-phase of an undulation cycle, the pressure distribution on the pectoral fins changes significantly, with the lift efficiency being highest at the peak of the undulation.

The non-lethal electric shock weapon is a research hotspot in the field of non-lethal weapons. In recent years, the research on wireless long-range electric shock bullets has become a key issue within this field. Therefore, aiming at the design of non-lethal long-range low-velocity electric shock bullet empennage, three airfoils of Clark Y, Eppler 387 and NACA-66 with good aerodynamic characteristics at low velocity were selected. The simulation results of NACA0012 airfoil at 30 m/s using CFD software were compared with the literature simulation results and wind tunnel test results to verify the algorithm's effectiveness. Subsequently, the aerodynamic characteristics of the three airfoils at low velocity were simulated, and the lift coefficient, drag coefficient and lift-drag ratio corresponding to different angles of attack at 30, 35 and 40 m/s were obtained respectively. The results show that at the same flight velocity, the lift coefficient and drag coefficient of the three airfoils gradually increase with the increase of the angle of attack, but the growth rate of the lift coefficient gradually decreases, and the growth rate of the drag coefficient gradually increases. The lift-to-drag ratio increases first and then decreases with the increase of the angle of attack. After comparison, it is found that the aerodynamic performance of the airfoil Eppler 387 is better than that of the other two airfoils. The velocity of 40 m/s and the angle of attack between 4° and 6° are the best working conditions, which can not only meet the structural design requirements of non-lethal long-range low-velocity electric shock bullets, but also produce less drag while providing as much rolling moment as possible.

In view of the deficiency of the research on the prevention and control of bolt anchoring in engineering rock mass, the method of cooperative prevention and control analysis based on bolt pre-tightening force was put forward, and the cooperative prevention and control test of bolt, anchor agent and surrounding rock based on bolt pre-tightening force was carried out, the variation law of pre-tightening force of bolt was obtained and the cooperative prevention and control state of bolt anchoring was identified. The results indicate that improving the synergy between anchoring agents and the surrounding rock of anchoring holes, as well as between anchor rods and anchoring agents, is beneficial for their synergistic evolution and can effectively enhance the prevention and control effect. A method for determining the collaborative state of anchor rod anchoring is provided, which can comprehensively determine the collaborative state of anchor rod anchoring through the relaxation process curve and relaxation degree of anchor rod pre-tightening force. Increasing the contact surface between the anchor rod pad and the surrounding rock on the free face is beneficial for their synergistic evolution. Based on the application and monitoring of pre-tightening force, a method for determining the overall coordination degree of anchor rod anchoring prevention and control has been developed, and strategies for improving the coordination degree of each part of anchor rod anchoring have been proposed. During design, special attention should be paid to the coordination of each part of anchor rod anchoring to ensure that they can perform at their best and be in their optimal state. The research results have good guidance and reference significance for the anchoring mechanism, monitoring, prediction and prevention of prestressed anchor rods in engineering rock masses.

The application of green NH₃-fuel on board has been widely regarded as a feasible way to realize the green and low-carbon transformation of the global shipping industry. However, the N₂O emission problem of marine NH₃-fuel engines has become one of the key technical bottlenecks hindering the development of ammonia-powered ships. To solve this problem, a series of TiO₂-supported transition metal oxide catalysts were prepared by impregnation method. The effect of transition metal element types on the N₂O removal performance of the catalysts was investigated, and the N₂O removal performance of Cu_x/TiO₂ catalysts was optimized. The results show that compared with Fe₅/TiO₂, Mn₅/TiO₂, Co₅/TiO₂ and Ni₅/TiO₂ catalysts, Cu₅/TiO₂ catalyst shows excellent catalytic activity, the N₂O conversion efficiency can reach 100% at 350 ℃. In addition, Cu₅/TiO₂ catalyst also has good water resistance. The experimental results show that 5% is the best Cu loading amount. X-ray diffraction, N₂ adsorption-desorption, H₂ temperature programmed reduction, O₂ temperature programmed desorption, and in-situ diffuse reflectance infrared Fourier transform spectroscopy were used to characterize the physicochemical properties and surface reaction intermediates of Cu₅/TiO₂ catalyst, and the relevant catalytic reaction mechanisms were discussed in depth from multiple perspectives. The characterization results show that compared with other Cu_x/TiO₂ catalysts, Cu₅/TiO₂ catalyst has higher dispersion of active species, specific surface area, oxygen vacancy content and stronger redox performance, which is conducive to its better catalytic activity. The main active species on the surface of Cu₅/TiO₂ catalyst are Cu²⁺ and Cu⁺ species, and the adsorption and deionization of N₂O is a key step in the catalytic reaction.

Molecular dynamics method is adopted to investigate the effect of different NaCl solutions concentrations on the bonding properties of the calcium silicate hydrate/γ-FeOOH(C-S-H/γ-FeOOH) interface. The effect mechanism of NaCl solution concentration is revealed from the interface ion evolution, radial distribution function, particle strength distribution, interaction energy and mechanical properties. The results show that as the concentration of NaCl solution increases, interlayer {\mathrm{Ca}}_{\mathrm{h}}^{2+} ions separate from the surface of C-S-H and diffuse to the interlayer solution, Na⁺ ions enter the C-S-H layer. {\mathrm{Ca}}_{\mathrm{h}}^{2+} ions adsorb Cl^- ions in the solution, resulting in the ion clusters of {\mathrm{Ca}}_{\mathrm{h}}^{2+} and Cl^- on the surface of C-S-H. In addition, the γ-FeOOH surface hydroxyl oscillation provides adsorption points for {{\mathrm{Na}}^{+}}^{}ions, resulting in the increase of Na⁺ ions on the γ-FeOOH surface. When the NaCl solution concentration increased, the RDF peak of Ca_h—O_s gradually decreased and the radial distribution function(RDF) peak of Ca_h—O_w, Ca_h—Cl, and Na—O_s gradually increases, consistent with the ionic strength distribution. Where, O_s is the oxygen on the silicon chain in C-S-H, and O_w is the oxygen in the interlayer solution water. {\mathrm{Ca}}_{\mathrm{h}}^{2+} ions form ionic bonds with O_w in water, leading to a reduction of Ca_h—O_s ionic bonds on the C-S-H surface. Since the strength and stability of Ca_h—O_s ionic bond are better than that of Ca_h—O_w,therefore, the C-S-H/γ-FeOOH interfacial interaction energy and peak stress both show a decreasing trend with the increase of NaCl solution concentration.

An algorithm has been proposed to detect small targets in unmanned aerial vehicle(UAV) aerial images. The algorithm is based on an improved real-time detection Transformer (RT-DETR) and aims to address the challenges posed by complex backgrounds and a large number of small target samples. To enhance the feature fusion network, a dedicated feature fusion structure for small targets has been incorporated, utilizing rich location information from the shallow feature map to improve the network's ability to detect small targets. Furthermore, the last residual block in the BackBone has been removed to prevent an increase in additional parameters. Additionally, the MCP Block, a reconstructed BasicBlock structure in the backbone network, has been designed, which includes a multi-channel feature partial convolution module (MCPConv) to reduce redundancy in channel features and enhance the acquisition of multi-scale detail features. Moreover, a location encoding mechanism with learning ability has been introduced to obtain more accurate and expressive location information. The normalized weighted deviation(NWD) and mean precision-driven IoU(MPDIoU) positioning loss functions have been incorporated to accelerate the convergence speed of the model and reduce sensitivity to position deviation. Experimental results on the VisDrone2019-DET dataset demonstrate that the improved model reduces parameters by 62% compared to the original model, increases mAP50 by 3.9%, and improves FPS by 17%. The improved model exhibits superior detection performance compared to other mainstream detection models.

An adaptive predefined-time prescribed performance backstepping fault-tolerant control strategy is presented based on radial basis function (RBF) neural networks, event-trigger mechanism and hysteresis quantizer for the attitude control problem of quadrotor unmanned aerial vehicle (UAV) with actuator faults. Firstly, the dynamic model of the quadrotor UAV system was constructed, and the attitude model was reconstructed by incorporating the actuator fault model. Secondly, by designing a class of time-varying functions, the error variables required for backstepping control were transformed. Thirdly, the nonlinear function approximation capability of RBF neural networks was utilized to estimate derivatives of virtual control laws and the actuator fault with unknown parameters. Finally, to reduce the update frequency of the actuator, a combination of event-trigger mechanism and hysteresis quantizer was used to design the control input. Stability of the closed-loop system was demonstrated through Lyapunov stability theory. The effectiveness of the proposed algorithm was verified through MATLAB. It is concluded that the designed event-triggered quantized controllers have a lower update frequency compared to controllers designed using only event-triggered techniques.

During tunnel construction, the deformation of surrounding rock and the mechanical response of the supporting structures are significantly influenced by the lateral pressure coefficient λ. Accurate determination of the on-site lateral pressure coefficient is essential for guiding tunnel design and construction. Firstly, the impact of the lateral pressure coefficient on settlement displacement of the tunnel vault and horizontal displacement of the side walls was analyzed theoretically. Secondly, the ratio between horizontal displacement of the side walls and settlement displacement of the vault was monitored, and a numerical simulation was employed to establish a mathematical relationship between the horizontal-vertical displacement coefficient K and the lateral pressure coefficient λ, enabling the inversion of the lateral pressure coefficient. Finally, the inverted lateral pressure coefficient was applied to optimize tunnel cross-section design. The results indicate that, under the same geological conditions, an approximately linear relationship exists between K and λ. Regardless of changes in tunnel depth or surrounding rock conditions, a proportional relationship between horizontal and settlement displacements is maintained, which can be used to invert the lateral pressure coefficient at the tunnel site. By adjusting the tunnel axis ratio m to gradually approach λ^-1, deformation is effectively controlled and the proportion of lining damage is reduced.