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Background Pulmonary hypertension is a rare, progressive disorder that can lead to right ventricular hypertrophy, right heart failure, and even sudden death. N6‐methyladenosine modification and the main methyltransferase that mediates it, methyltransferase‐like (METTL) 3, exert important effects on many biological and pathophysiological processes. However, the role of METTL3 in pyroptosis remains unclear. Methods and Results Here, we characterized the role of METTL3 and the underlying cellular and molecular mechanisms of pyroptosis, which is involved in pulmonary hypertension. METTL3 was downregulated in a pulmonary hypertension mouse model and in hypoxia‐exposed pulmonary artery smooth muscle cell. The small interfering RNA–induced silencing of METTL3 decreased the m6A methylation levels and promoted pulmonary artery smooth muscle cell pyroptosis, mimicking the effects of hypoxia. In contrast, overexpression of METTL3 suppressed hypoxia‐induced pulmonary artery smooth muscle cell pyroptosis. Mechanistically, we identified the phosphate and tension homology deleted on chromosome 10 (PTEN) gene as a target of METTL3‐mediated m6A modification, and methylated phosphate and tension homology deleted on chromosome 10 mRNA was subsequently recognized by the m6A “reader” protein insulin‐like growth factor 2 mRNA‐binding protein 2, which directly bound to the m6A site on phosphate and tension homology deleted on chromosome 10 mRNA and enhanced its stability. Conclusions These results identify a new signaling pathway, the METTL3/phosphate and tension homology deleted on chromosome 10/insulin‐like growth factor 2 mRNA‐binding protein 2 axis, that participates in the regulation of hypoxia‐induced pyroptosis.

Effective collision detection is crucial for creating a realistic and immersive virtual reality (VR) experience, especially in large and complex VR environments. Collision detection research currently focuses on improving two key aspects: accuracy and real-time performance. This paper proposes a novel collision detection algorithm that uses a mixed layer bounding box approach. The algorithm uses Sphere and EBB (Ellipsoidal Bounding Box) methods to quickly eliminate disjoint objects in the virtual environment and reduce the number of triangular primitives that need to be detected. Tree structures are used to traverse nodes from top to bottom, and then the Devillers & Guigue method is used to calculate accurate triangle-to-triangle primitives, further improving the effectiveness and accuracy of the collision detection. Experimental results show that the proposed algorithm (Sphere-EBB) performs better than traditional hybrid bounding box algorithms like Sphere Axial Aligned Bounding Box (Sphere-AABB) and EBB in terms of mean detection time, detection rate, and frame frequency. This makes the proposed algorithm suitable for large-scale, complex model collision detection tasks in terms of collision detection time and accuracy.

Due to the influence of signal-to-noise ratio in the early failure stage of rolling bearings in rotating machinery, it is difficult to effectively extract feature information. Variational Mode Decomposition (VMD) has been widely used to decompose vibration signals which can reflect more fault omens. In order to improve the efficiency and accuracy, a method to optimize VMD by using the Niche Genetic Algorithm (NGA) is proposed in this paper. In this method, the optimal Shannon entropy of modal components in a VMD algorithm is taken as the optimization objective, by using the NGA to constantly update and optimize the combination of influencing parameters composed of α and K so as to minimize the local minimum entropy. According to the obtained optimization results, the optimal input parameters of the VMD algorithm were set. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a rolling bearing. The decomposition process of the rolling-bearing fault signal was transferred to the variational frame by the NGA-VMD algorithm, and several eigenmode function components were obtained. The energy feature extracted from the modal component containing the main fault information was used as the input vector of a particle swarm optimized support vector machine (PSO-SVM) and used to identify the fault type of the rolling bearing. The analysis results of the simulation signal and measured signal show that: the NGA-VMD algorithm can decompose the vibration signal of a rolling bearing accurately and has a better robust performance and correct recognition rate than the VMD algorithm. It can highlight the local characteristics of the original sample data and reduce the interference of the parameters selected artificially in the VMD algorithm on the processing results, improving the fault-diagnosis efficiency of rolling bearings.

To explore the relationship between the cutting vibration and the cutting load of a single pick, this paper studied a new method for a single pick cutting rock load identification. This paper improved the low accuracy problem of the regularization method in the inverse process of frequency response function in the traditional load identification method by introducing a filter operator. By combining the inverse pseudoexcitation method and the improved regularization method, the identification of the load dependent on the vibration signal was realized. A single pick cutting rock test equipment was built, which could simulate the actual working conditions of pick cutting rock in the underground or tunnel. By changing cutting speed, cutting angle, cutting spacing, and cutting depth of the single pick, the change trends of real cutting load and identification load were obtained. The load identification method proposed in this paper was consistent with the change trend of the real load under the single pick cutting state. Therefore, the method had good recognition accuracy and the maximum load recognition error was 17.35%. Compared with other traditional load identification methods, the identification error was reduced by a maximum of 1.98%. This method can identify the cutting load of single pick and modify the morbidity problem of frequency response function matrix. The method has a better recognition effect on the cutting load of the pick than the traditional recognition methods. The research could benefit the design of the cutting system and the arrangement of the pick on the coal mine or tunneling machinery.

With the increasing market demand for artificial hip joints, total hip joint replacement has gradually become an effective means of treating a series of hip joint diseases. In order to improve the service life of artificial hip joints, some new artificial hip joint materials, including polyetheretherketone (PEEK) and carbon fiber reinforced polyetheretherketone (CFR-PEEK), have been developed. In this paper, pin-on-plate wear tests under different cross-shear ratios and contact pressures were carried out to study the wear mechanism and worn surface topography of PEEK and CFR-PEEK. The experimental results showed that the wear of PEEK was associated with cross-shear, while CFR-PEEK was not. When the cross-shear ratio was 0.039 and contact pressure was 3.18 MPa, PEEK had poor wear resistance and its wear factor was about eight times that of ultra-high molecular weight polyethylene (UHMWPE). The wear resistance of CFR-PEEK had a significant advantage, since its wear factor was about 30% of that of PEEK. The wear factors of PEEK and CFR-PEEK increased as the contact pressure increased. The arithmetic average of the height amplitude of the surface, Sa, also increased gradually according to the topography of the worn surface. The wear mechanisms of PEEK and CFR-PEEK were scratching, plough cutting, and abrasion Since CFR-PEEK had good wear resistance and insensitivity to cross-shear motion, it is suitable for making artificial hip joints under low contact pressure condition.

In order to explore the relationship between the surface topography parameters and friction properties of a rough contact interface under fluid dynamic pressure lubrication conditions, friction experiments were carried out. The three-dimensional surface topography of specimens was measured and characterized with a profile microscopy measuring system and scanning electron microscope. The friction coefficient showed a trend of decreasing first and then increasing with the increase in some surface topography parameters at lower pressure, such as the surface height arithmetic mean Sa, surface height distribution kurtosis Sku, surface volume average volume Vvv, and surface center area average void volume Vvc, which are the ISO 25178 international standard parameters. The effects of surface topographic parameters on friction were analyzed and the wear mechanism of the worn surface was presented. The wear characteristics of the samples were mainly characterized as strain fatigue, grinding, and scraping. The results provide a theoretical basis for the functional characterization of surface topography.