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The finite element simulation method of bolt torsion under the tightening torque process was carried out,a quantitative relation between the tightening torque and the bolt preload was established for an actual structure.Firstly,the geometric model of the bolt with three⁃dimensional oblique thread was built,and the finite element mesh with thread was divided by using Hypermesh software,and the corresponding mechanical contact pairs were redefined.Then,Ansys Workbench software was used to apply the different sizes of tightening torque to the lower surface of the nut to obtain the magnitude of the corresponding axial force,so that the functional relation between the tightening torque and the bolt tension could be obtained.Finally,a bolt preload test was designed and the experimental,emulational and theoretical results were compared to verify the method.The results show that the results of the finite element simulation model are closer to the experimental results compared to the theoretical calculation results.The high⁃fidelity finite element model of bolt preload in this paper provides an important method for further accurate analysis of the bolt mechanics mechanism.

Aiming at the fatigue fracture problem of aireraft hydraulic pipeline connector, the fatigue life of hydraulic conduit with axial assembly deviation was predicted based on random vibration theory. Starting with the establishment of the finite element model of the pipeline connector of the real aircraft hydraulic system, the influence law of the assembly stress caused by the axial assembly deviation on the structure was analyzed, and the damping ratio of the pipeline connector under different axial deviation is obtained through the test. The random vibration analysis was carried out by using the finite element analysis software, and the stress response power spectral density function of the dangerous part was obtained. Combined with Miner linear damage theory, the random vibration fatigue life of the pipeline connector with assembly stress was predicted. The resonance fatigue test of pipeline was designed and carried out. It is found that the crack initiation position and the decreasing trend of fatigue life of pipeline are consistent with the simulation results. The simulation and test results show that when the axial deviation reaches 0.8 mm, it seriously affects the flight safety. The research results provide theoretical reference and technical support for the design and assembly theory of aviation hydraulic pipeline.

The polyphenolic composition of the same variety of winter jujube was determined using ultra-performance liquid chromatography–mass spectrometry (UPLC–MS/MS). A metabolomic approach was employed to determine polyphenols at different developmental stages (S1, S2, and S3). The total phenolic content of Chinese jujube was quantified, and the metabolites were statistically analyzed using orthogonal partial least squares discriminant analysis (OPLS-DA) for differential metabolite screening and clustering analysis of key components. The findings revealed that 128 polyphenolic components of Chinese jujube had been identified. Different developmental periods could not be clearly distinguished in principal component analysis, and there was a crossover between S2 and S3 stages. In contrast, the OPLS-DA score plot could effectively distinguish between samples of different developmental periods, and its differential metabolites could be visualized by a volcano plot based on OPLS-DA. Ten phenolic differential metabolites in different developmental periods were clustered and analyzed, among which N′-p-coumaroylguanidinium, N-p-coumaroylbutylamine, caffeoyl guanidinium, N-feruloyl guanidinium, pianoside, isorhamnetin 5-O-hexoside, isorhamnetin O-acetyl-hexoside, quercetin, and lignan O-hexosyl-O-pentoside were higher in the S1 period and chrysoeriol 6-C-hexoside was higher in the S2 and S3 periods. In this study, the differences in jujube polyphenols were elucidated, which provided scientific guidance for the application of jujube polyphenols.

The Shenzhen Soil and Water Conservation Management Information System was developed within the framework of smart cities and smart water management,taking into consideration the characteristics of soil and water conservation business in Shenzhen.The system ensures unified storage and management of water-related data,consisting of five major subsystems,including scheme management,supervision and inspection,historical trend visualization,real-time warnings,and other key modules.By establishing a business supervision platform,it enables comprehensive supervision and management throughout the entire process.Additionally,the integration of intelligent models has greatly enhanced the decision-making and evaluation system for management personnel,thereby significantly improving the efficiency of both management and operational staff.The system integrates multiple functions, including data management,business support,model-based decision-making, data visualization,and real-time alerting.It effectively addresses various challenges encountered in the information construction of soil and water conservation in Shenzhen,such as insufficient information processing capacity,low levels of smart application,lack of unified business sources and data format standards,and difficulties in information sharing and access,ensuring that the information system effectively supports business requirements.

Aiming at the problem of fatigue fracture of pipeline connectors, a finite element model of pipeline connectors in aircraft hydraulic system is established. Based on the theory of continuous damage mechanics, the vibration fatigue life of pipeline connectors with assembly stress is predicted. The results show that under normal assembly state, the fatigue crack initiation point of pipeline connectors is located at the contact part between flared conduit and flat nozzle. With the increase of vibration load amplitude, the fatigue life of pipeline connections decreases gradually. When there is axial assembly deviation, due to the influence of stress concentration, the fatigue crack initiation point of pipeline connector is located at the connection between pipe flare and pipe body. The axial assembly deviation weakens the fatigue strength of pipeline connectors. The larger the axial deviation is, the smaller the fatigue life of pipeline structure is.

Aiming at the problems of high false detection rate, difficult to find unknown attack behavior and high cost of obtaining marked data in existing wireless network intrusion detection algorithms based on supervised learning, this paper proposes an unsupervised wireless network intrusion detection algorithm based on multiple perspectives hierarchical clustering. The algorithm is based on unsupervised learning, and does not need to manually mark a large number of wireless network data participating in classifier learning. It has the advantages of easy access to training datasets and detection of unknown types of attack behavior. At the same time, the algorithm introduces multiple perspectives cosine distance as the similarity measure between wireless network data objects in hierarchical clustering, which makes the clustering results more reasonable and the judgment of network data behavior more accurate, and reduces the false detection rate of intrusion detection to a certain extent. In this paper, Aegean WIFI intrusion dataset (AWID) is selected as the experimental dataset, and principal component analysis is used to reduce the dimension of the experimental dataset, which greatly reduces the time complexity of intrusion detection algorithm. Experimental results show that the proposed wireless network intrusion detection algorithm based on multiple perspectives hierarchical clustering has a significant improvement in detection rate, false detection rate and detection of unknown attack types compared with traditional wireless network intrusion detection algorithms.

Based on metabolomics, the metabolites of Jujube leaves LS1 (one bud and two leaves), LS2 (one bud and three leaves), and LS3 (one bud and four leaves) were taken and examined by ultra-high performance liquid chromatography-mass spectrometry technique. There were 22 substance categories that were identified. Principal component analysis was also utilized to distinguish the metabolomics at the three different foliar ages, and the results suggested that the samples at different foliar ages were clearly separated, demonstrating that the metabolites in the three foliar ages were significantly different. Through the screening of differential metabolites and hierarchical clustering analysis, our results suggested that the composition and the content distribution of the differential metabolites at three different foliar ages were significantly different. In the LS1, delphinidin, N-hydroxy tryptamine, serotonin, methylquercetin O-hexoside, tricin 7-O-hexoside, and eriodictyol C-hexoside were identified as the distinctive compounds. In the LS2, N-caffeoyl agmatine, lysoPC 18:3 (2n isomer), N-(4′-O-glycosyl)-p-coumaroyl-agmatine, dihydromyricetin, and hydroxy-methoxycinnamate were identified as the distinctive compounds. Similarly, the 3-O-p-coumaroyl-quinic acid, O-feruloyl 4-hydroxylcoumarin, isorhamnetin 3-O-neohesperidoside, cyanidin 3-O-galactoside, quercetin O-acetylhexoside, and DIMBOA glucoside were identified as the distinctive compounds in LS3. These characteristic compounds could provide a strong theoretical basis for rapid identification of jujube leaves at different foliar ages.

Chinese jujube is a delicious fruit with high antioxidant nutrients. The fruit peel, however, is always discarded due to its indigestibility. In the current study, the jujube peels were collected for red pigment extraction. Six extraction-related parameters (ethanol concentration, solid-liquid ratio, material granularity, enzyme concentration, enzymolysis time, and pH) were optimized for jujube peel pigment extraction using Plackett–Burman and Box–Behnken designs. When the fruit peels were treated with 1.18% cellulase and 73% ethanol at pH 3.15, optimization enhanced the pigment extraction efficiency by 29.7% compared with the control. Ultra-high performance liquid chromatography (UHPLC) assay revealed that delphinidin 3-O-galactoside and cyanidin 3-O-rutinoside chloride were the major components of the jujube pigment extracts. Additionally, the red pigment extracts exhibited high free radical scavenging capacity and strong Fe3+ reducing power. Finally, it also provides us a simple new method for efficient extraction of natural antioxidants from discarded jujube peels.

Real-time drilling depressurization technology is widely used in the prevention and control of dynamic disasters, such as deep-seated rock burst. However, current coal- and rock-loading tests under drilling conditions seldom account for real-time issues associated with drilling, thus failing to fully reflect the actual stress state of the surrounding rock during the implementation of drilling depressurization technology. Therefore, this study designed and implemented a uniaxial loading scheme for coal samples incorporating real-time-drilling characteristics. The results indicate a significant reduction in the uniaxial compressive strength ( R C ), elastic energy index ( W ET ), and impact energy index ( K E ) of the samples post-drilling. These parameters show a clear decreasing trend with increasing axial stress during real-time drilling. The weakening effect of impact tendency following real-time drilling depressurization is significant, and the depressurization effect is pronounced. The R C , W ET , and K E of each real-time-drilled sample exhibit a notable decrease with increasing drilling stress, with the reduction rate significantly diminishing after the drilling stress reaches 20% of the peak strength. [ABSTRACT FROM AUTHOR]

Taking gas disaster risk macro early warning of all coal mines within the jurisdiction of all levels of coal mine safety supervision departments and mining group companies, it is pointed out that the basic data of regional coal mine gas disaster risk prediction has the characteristics of multi-source, heterogeneous, massive, multi-dimensional, etc., and there are some problems in data collection, such as incomplete information collection and single data collection mode, solidified dimensions, etc.; the basic data of regional coal mine gas disater risk prediction is divided into four types： natural environment risk data of regional mine, production system risk data of regional mine, gas prevention risk data of regional mine, and macro-security environmental risk data; collection technologies of coal mine safety monitoring and gas disaster early warning data with structured characteristics, supervision and law enforcement inspection data with semi-structured characteristics, and coal mine audio and video monitoring data with unstructured characteristics are introduced, and the research of coal mine safety monitoring and gas disaster warning data collection technology based on .NET Core cross-platform Web API, and macro-security environmental risk data collection technology based on topic crawler are introduced in detail; data collection system of gas disaster risk early warning for regional coal mines suitable for Internet environment is designed, and field test show that the system can comprehensively, reliably and timely collect basic data of regional coal mine gas disaster risk early warning.

The working face footage acquired by traditional artificial static measurement technology has non-continuous and poor time-effectiveness, and ca't satisfy requirement of on-line real-time warning. For the above problem, an on-line monitoring system of working face footage based on radar ranging was designed. The system uses combination arrangement process of response radar ranging sensor and reflection radar ranging sensor to overcome shortcomings of short measuring range of the reflection radar and solve problem of difficult installatipn and maintainance of the response radar. Principle of the radar ranging was analyzed, and mine-used intrinsically safe radar ranging sensor composed of the reflection radar ranging sensor and response radar ranging sensor was developed. The test result shows that the system can stably and reliably realize on-line monitoring, real-time collection and analysis of working face footage. When measuring distance is less than 200 m, the maximum absolute error is 0.24 m, and the measuring distance and accuracy can meet the needs of gas disaster early warning.