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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.

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.

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.

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.

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.

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.

Definition of early warning of coal and gas outburst was given, and difference between the early warning and forecasting was clearly pointed out. The early warning of coal and gas outburst was classified from angle of space, time and index system, and features of the early warning were put forward according to specific characteristics of coal and gas outburst disaster. System structure and implementation of the early warning were analyzed guided by system theory and accident theory. Steps of the early warning were described from five aspects of detection of risk source, warning sign identification, analysis of warning situation, alert release and early warning response. Method of effect evaluation of the early warning was put forward by using three indicators of initial warning accuracy, false negative rate and false alarm rate. The field application results show that the average accuracy rate of state warning is 89.1%, the average accuracy rate of trend warning is 92.5%, and the false negative rate is 0.

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is employed as the hole transport material in inverted perovskite solar cells (PSCs) due to its good conductivity, uniform film formation, and low energy consumption. However, the presence of sulfonic acid groups in the PSS chains of PEDOT:PSS makes the solution acidic. Moreover, PEDOT:PSS as a hole transport layer (HTL) exhibits hygroscopicity and anisotropy, which can reduce the power conversion efficiency (PCE) and long-term stability of PSCs. Here, we employed arginine as an additive in the PEDOT:PSS solution to adjust the pH value of the PEDOT:PSS solution from 3.7 to 6.8. By incorporating arginine, the open-circuit voltage (Voc) of the PSCs increased from 0.92 V to 1.08 V, and the PCE improved from 15.06% to 17.35%. The enhancement of performance is attributed to the interaction between the amino groups in arginine and the sulfonic acid groups in the PSS chains, which reduces the acidity and surface roughness of PEDOT:PSS. This modification decreases the contact barrier between the perovskite layer and the HTL, enhances charge collection and transport capabilities, and thereby improves the PCE and long-term stability of the inverted PSCs. This study provides a new approach for the industrialization of perovskite solar cells. [ABSTRACT FROM AUTHOR]

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) suffers from lower conductivity and surface defects, which hinders the extraction and transport of effective charges, thereby reducing the Power conversion efficiency (PCE) and long-term stability of PSCs. Therefore, this study introduces potassium stearate (KSt) doping in PEDOT:PSS to regulate its conductivity and interface charge transfer. As a result, KSt-doped PEDOT:PSS increase the PCE of the device from 16.35% to 18.35%. Moreover, the PCE of PSCs with KSt-doped PEDOT:PSS can maintain 87% of its initial value after being stored in a glove box for over 700 hours. This work provides a simple and effective method for designing high-performance and stable PSCs. [ABSTRACT FROM AUTHOR]