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Sliding bearings are one of the core components of modern mechanical equipment.They have been widely used in engineering because of their stable and reliable performance, low working noise, convenient manufacture and variety of types.However, during operation,due to the influence of unstable working conditions, the bearing surface is prone to serious friction and wear, which can even lead to failure.Surface texture modification is one of the effective ways to solve this problem, as it has excellent performance in reducing friction and wear.In this paper, the research progress on the antifriction performance of sliding bearings with surface texture was summarized.The influence of the shape, arrangement, depth and area occupancy of surface texture on the tribological performance of sliding bearings was analyzed, and the antifriction performance when surface texture and other surface modification technologies were combined was summarized.The tribological properties after the application of surface texturing, reflected by the friction coefficient between mechanical parts, provided a reference for subsequent researchers in this field.Finally, existing research and future needs were considered to discuss the prospects for applying surface texturing in antifriction studies of sliding bearings.

In high-altitude environments, low temperature and low-pressure conditions can lead to decreased power and incomplete combustion in diesel engines, which may also cause increased wear of valve components. Although valve manufacturing technology has been widely explored for decades, valve components often face severe working conditions of high temperature, high pressure, frequent impacts and friction, resulting in an exceptionally complex friction wear mechanism. Previous optimization measures for valve manufacturing have not fully addressed the problem of valve component wear. Therefore, a novel solution was proposed, namely the use of aluminized titanium alloy as valve material. This material, characterized by its high thermal strength and lightweight properties, is particularly suitable for use as valve material in diesel engines. However, due to the limited wear resistance of aluminized titanium alloys, it was necessary to improve their tribological performance and fatigue characteristics through surface treatment processes before practical application. In this paper, research on various surface treatment methods for aluminized titanium alloys was summarized, including ultrasonic surface rolling, laser surface cladding, chemical heat treatment and laser surface micro-texture. These surface treatment techniques effectively enhanced the tribological performance and fatigue characteristics of the aluminized titanium alloy materials and mitigated negative impacts on the material surfaces. Researchers have also achieved better results by employing composite treatments using different surface treatment technologies. The future research focus and direction were pointed out to be in-depth research on the precise machining parameters of aluminized titanium alloys, as well as the feasibility and effectiveness of using multiple machining methods. This will contribute to better addressing the issue of wear in valve components, thereby enhancing the performance and reliability of diesel engines. Furthermore, the applications of aluminized titanium alloys in other fields require to be widely researched and explored.

Surface texture technology as a kind of effective anti-friction and anti-wear method has been widely applied to improve the pistoncylinder liner system in the study of tribology performance of friction pair， but the piston -cylinder liner system surface texture friction mechanism research and texture design system is still imperfect.So， in order to better broaden the surface texture technology application in this field， the research purpose and development status of surface texture were systematically summarized in this paper， and the friction mechanism of surface texture and the causes of friction mechanism were discussed.After that， a classification review was conducted from the aspects of surface texture morphology and direction (pit texture， groove texture)， texture geometric parameters (depth， diameter， aspect ratio， surface density， and angle)， distribution position (piston ring， cylinder liner)， distribution form (full texture distribution， partial texture distribution)， etc.The research progress on composite texture and composite modification， which was currently less studied， was elaborated.Finally，combined with the existing research and future requirements， the problems to be solved and the future development trend of surface texture applied to piston-cylinder liner system friction pair were summarized and prospected.

Introduction: In response to the issues of complexity and low efficiency in line loss calculations for actual distribution networks, this paper proposes a fast power flow calculation method for distribution networks based on Neo4j graph models and a hierarchical forward-backward sweep parallel algorithm. Methods: Firstly, Neo4j is used to describe the distribution network structure as a simple graph model composed of nodes and edges. Secondly, a hierarchical forward-backward sweep method is adopted to perform power flow calculations on the graph model network. Finally, during the computation of distribution network subgraphs, the method is combined with the Bulk Synchronous Parallel (BSP) computing model to quickly complete the line loss analysis. Results and Discussion: Results from the IEEE 33-node test system demonstrate that the proposed method can calculate network losses quickly and accurately, with a computation time of only 0.175s, which is lower than the MySQL and Neo4j graph methods that do not consider hierarchical parallel computing. [ABSTRACT FROM AUTHOR]

Brown cotton is a major cultivar of naturally colored cotton, and brown cotton fibers (BCFs) are widely utilized as raw materials for textile industry production due to their advantages of being green and dyeing-pollution-free. However, the mechanisms underlying the pigmentation in fibers are still poorly understood, which significantly limits their extensive applications in related fields. In this study, we conducted a multidimensional comparative analysis of the transcriptomes and metabolomes between brown and white fibers at different developmental periods to identify the key genes and pathways regulating the pigment deposition. The transcriptomic results indicated that the pathways of flavonoid biosynthesis and phenylpropanoid biosynthesis were significantly enriched regulatory pathways, especially in the late development periods of fiber pigmentation; furthermore, the genes distributed in the pathways of PAL, CHS, F3H, DFR, ANR, and UFGT were identified as significantly up-regulated genes. The metabolic results showed that six metabolites, namely (−)-Epigallocatechin, Apiin, Cyanidin-3-O-glucoside, Gallocatechin, Myricetin, and Poncirin, were significantly accumulated in brown fibers but not in white fibers. Integrative analysis of the transcriptomic and metabolomic data demonstrated a possible regulatory network potentially regulating the pigment deposition, in which three MYB transcription factors promote the expression levels of flavonoid biosynthesis genes, thereby inducing the content increase in (−)-Epigallocatechin, Cyanidin-3-O-glucoside, Gallocatechin, and Myricetin in BCFs. Our findings provide new insights into the pigment deposition mechanism in BCFs and offer references for genetic engineering and breeding of colored cotton materials. [ABSTRACT FROM AUTHOR]

Traditional load prediction methods are unable to effectively predict the loads according to the spatial topology of each electricity consumer in neighboring areas and the load dependency correlations. In order to further improve the load prediction accuracy of each consumer in the region, this paper proposes a shortterm prediction method of electric load based on multi-graph convolutional network. First, the input data are selected with maximum information coefficient method by integrating multi-dimensional information such as load, weather, electricity price and date in the areas. Then, a gated convolutional network is used as a temporal convolutional layer to capture the temporal features of the loads. Moreover, a physical-virtual multi-graph convolutional network is constructed based on the spatial location of each consumer as well as load dependencies to capture the different evolutionary correlations of each spatial load. Comparative studies have validated the effectiveness of the proposed model in improving the prediction accuracy of power loads for each consumer. [ABSTRACT FROM AUTHOR]

Based on the background of frequent cracking failures of the cab floor of a light commercial truck,the cause analysis and optimization designs of the strength of the cab floor of this brand commercial vehicle were carried out. First,the CAE modeling and simulation of the light truck floor cab were carried out,and the time domain data onto the strain of each measuring point of the road driving of the light commercial truck was measured using the electrical measurement method. The calculation results show that the stress extreme value of the CAE calculation simulation results reaches 160. 7 MPa,and the stress extreme value of the same part measured by the electrical measurement method reaches 250. 3 MPa,which is far beyond the yield strength limit of the cab material. Then,on this basis,the nature of the problem is judged,and the force analysis and calculation are carried out on the turning mechanism. The calculation results show that the theoretical difference between the torque limits of both sides is only 3 424. 2 N·m,and the reason for the crack is that the strength of the cab body is too low. Finally,on the basis of experiments and theoretical analysis,this paper proposes two structural strength optimization measures,including strengthening plates and welding seams,and adding structural adhesive,and conducts comparative analysis in various aspects to provide a reference for the subsequent engineering structure optimization and strength analysis.

In recent years, both surface texturing technology and surface coating technology have made significant progress in improving the tribological performance. More and more researches have combined surface texturing technology with coating technology, and it has been found that under suitable external conditions and appropriate texturing parameters, the combination of surface texturing and DLC coating can exhibit excellent tribological characteristics, achieving a synergistic effect greater than the sum of the individual parts. Surface texture technology has been widely used to improve the fictional performance of materials, but t cannot provide good lubrication under dry sliding conditions. However, DLC coating is widely recognized as an effective solid lubricant, with good anti-friction and anti-wear properties, but the disadvantage of poor adhesion. Surface texturing can increase the effective bonding strength between the coating and the substrate, thereby improving the coating's tribological performance, corrosion resistance, and biocompatibility. This article mainly introduces the friction and wear characteristics of surface texturing and DLC coating composite treatment, discussing geometric parameters of the texture, external conditions, contact modes, ingestion of different elements, coating thickness, etc. to provide references for future research directions. Finally, the development trends of composite modulation of texturing and coating are discussed. Surface texture and DLC coating are two widely used techniques in the field of surface engineering. Surface texture is typically formed using methods such as laser processing, electrical discharge machining, and chemical etching to enhance surface friction, lubrication, wear resistance, and corrosion resistance. DLC coating is a diamond-like carbon film with high hardness, wear resistance, and low friction coefficient, which can be used to improve surface performance and extend service life. In recent years, some researchers have begun to study the combined treatment of surface texture and DLC coating on surface performance. The research results have shown that this combination treatment can greatly improve the surface wear resistance, corrosion resistance, and lubrication performance. For example, using laser micro-texturing treatment on the surface of stainless steel and coating it with DLC coating can significantly improve its wear and corrosion resistance. Other researchers have studied the texturization of DLC coatings. By creating microtextures on the surface of DLC coatings, their friction and lubrication performance can be improved. For example, using electron beam physical vapor deposition technology to create microtextures on the surface of DLC coatings can significantly improve their lubrication performance. Still, others have studied the effect of coating DLC on surface texture. This combined treatment can further improve surface performance. For example, after creating microtextures on the surface of stainless steel, coating it with DLC coating can significantly improve its friction and wear resistance. Overall, surface texture and DLC coating are two very useful surface engineering techniques that can be used alone or in combination to improve surface performance and extend service life. With the continuous development and improvement of these technologies, we can expect to see more innovative applications in the future. [ABSTRACT FROM AUTHOR]