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    Properties of the Exfresh fiber and its fabrics
    FENG Longlong, XIE Bingbing, ZHANG Ruiyun, LU Jian, YU Hao, WANG Yunhai
    Shandong Science    2023, 36 (3): 60-68.   DOI: 10.3976/j.issn.1002-4026.2023.03.008
    Abstract756)   HTML11)    PDF(pc) (1164KB)(1342)       Save

    The Exfresh fiber is a new type of modified acrylic fiber with fine denier and antibacterial properties; it is fabricated by adding an antibacterial agent to the spinning stock solution. The surface morphologies, mechanical properties, moisture absorption properties, specific resistance, friction properties, and curling properties of the Exfresh and ordinary acrylic fibers were tested and compared in this study. The elemental composition and chemical bonds of the two fibers were analyzed via X-ray photoelectron spectroscopy (XPS). Furthermore, the moisture-absorbing quick-drying and moisture-absorbing heat-generating properties of the Exfresh blended fabrics were tested. Results showed that the Exfresh fiber featured a circular cross-section, rough longitudinal surface and dense grooves as well as a low linear density, excellent mechanical properties, and high spinnability. Additionally, it has a lower specific resistance and higher friction coefficient than the ordinary acrylic fiber, thereby making it difficult to produce static electricity. Results of the XPS analysis showed that the added antibacterial agent was a quaternary ammonium salt. Additionally, the evaporation rate of an Exfresh fiber-blended fabric is bigger than 0.18 g/h, and its maximum moisture-absorbing heat-generating temperature rise is bigger than 4 ℃. Moreover, it exhibits excellent moisture-absorbing quick-drying and moisture-absorbing heat-generating properties, and can be used to develop multifunctional fabrics.

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    Molecular dynamics simulation and gas adsorption properties of CO2/CH4 adsorbed using Mg-MOF-74
    XIE Yi, ZHANG Jing, SUN Jinqiang, LIU Xiaochan, YI Xibin, SUN Yongxing
    Shandong Science    2023, 36 (3): 123-134.   DOI: 10.3976/j.issn.1002-4026.2023.03.015
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    Natural gas is an environmentally friendly energy source that can be used in various chemical raw materials. However, the presence of CO2 in natural gas has a significant impact on the heat value and transportation performance of natural gas. Therefore, effective CO2 removal from natural gas is critical. In this study, Mg-MOF-74 was selected as an adsorbent and its effect on CO2/CH4 adsorption and separation performance was investigated using a molecular dynamics simulation method. Based on the simulation results, at certain pressure and temperature settings, CO2 is more likely to bind to the metal sites of Mg-MOF-74 than CH4. Moreover, Mg-MOF-74 exhibits a stronger interaction force with CO2 gas, indicating a higher capacity for CO2 adsorption. To verify the accuracy of the simulation results, Mg-MOF-74 was prepared and its CO2/CH4 adsorption performance was tested.The experiment results is consistent with the simulation,that proved Mg-MOF-74 is more attractive to CO2.

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    Survey of underwater biological object detection methods based on deep learning
    YU Yu, GUO Baoqi, CHU Shibo, LI Heng, YANG Pengru
    Shandong Science    2023, 36 (6): 1-7.   DOI: 10.3976/j.issn.1002-4026.2023.06.001
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    Underwater biological object detection is crucial for aquaculture, endangered species protection,and ecological environment monitoring. This study comprehensively analyzes the applications of various deep learning methods in underwater biological object detection. The commonly used underwater biological object detection datasets are introduced. The state-of-the-art underwater biological object detection methods are classified, analyzed, and summarized by two stages and one stage. The actual applications of various detection methods are thoroughly described, and the advantages and disadvantages of their optimization strategies are analyzed and summarized. Future works in the field of underwater biological object detection based on deep learning are presented. This study provides a reference basis for researchers in the field of underwater biological object detection.

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    The mechanism of Xiaoqinglong Decoction in treatment of COVID-19 based on network pharmacology
    ZHU Jie, WANG Zheng, LIANG Yanni
    Shandong Science    2023, 36 (3): 10-17.   DOI: 10.3976/j.issn.1002-4026.2023.03.002
    Abstract434)   HTML11)    PDF(pc) (1093KB)(693)       Save

    This research aims to study the mechanism of Xiaoqinglong Decoction in the treatment of coronavirus disease 2019 (COVID-19) based on network pharmacology. The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) online tool was used to screen the active ingredients of Xiaoqinglong Decoction. PubChem, SwissTargetPrediction, and TCMSP databases were used to obtain the potential targets of eight traditional Chinese medicines. OMIM, DisGeNET, and GeneCards databases were used to obtain COVID-19 and delta variant of COVID-19 related targets. The intersecting targets of eight traditional Chinese medicines and Xiaoqinglong decoction and COVID-19 were screened using online tool Venny 2.1, and a Venn diagram was prepared. The Cytoscape 3.7.2 software was used to construct Xiaoqinglong Decoction-components-(COVID-19)-target network. After using STRING database to collect data, protein-protein interaction network was built online. Metascape database was used for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the GO and KEGG enrichment analysis maps were plotted using Weishengxin online plotting tool. Molecular docking was performed using the AutoDockTools 1.5.6 software. A total of 169 active ingredients, 1 363 targets of Xiaoqinglong Decoction, and 292 intersecting targets of drugs and diseases were screened. A total of 2 393 biological process, 168 cell components, 264 molecular functions were obtained via GO enrichment analysis. A total of 225 pathways were obtained via KEGG. Molecular docking showed that the core components of Xiaoqinglong Decoction screened in this study combined well with the COVID-19 related targets. Xiaoqinglong Decoction could treat COVID-19 through TNF, AKT1, GAPDH, IL-6, ALB, TP53, IL-1β, VEGFA, STAT3, EGFR, and other targets and participate in MAPK signaling pathway, PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetes complications, and other pathways.

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    Comparison of structure and properties of EKS and acrylic fibers
    XIE Bingbing, FENG Longlong, ZHANG Ruiyun, FANG Bin, WU Zhiping
    Shandong Science    2023, 36 (3): 69-77.   DOI: 10.3976/j.issn.1002-4026.2023.03.009
    Abstract434)   HTML4)    PDF(pc) (1121KB)(479)       Save

    EKS fiber is a subacrylate fiber with significant hygroscopic-heating properties. In this study, the surface morphologies of EKS and acrylic fibers were compared, and their mechanical properties, friction properties, specific resistance, curling properties, moisture absorption and liberation properties, and hygroscopic-heating properties were tested and analyzed. The results showed that compared with the acrylic fiber, the EKS fiber featured a circular cross section and rough longitudinal structure as well as low breaking strength, friction coefficient, specific resistance and curl rate; moreover, it featured a high linear density, elongation at break, and moisture recovery rate. With the initial absorption rate and liberation rate being 0.39% min-1 and 8.94% min-1, respectively, the moisture absorption and liberation rates of the EKS fiber decreased exponentially with time, and the time required to achieve the absorption and liberation balance was longer than that for the acrylic fiber. The EKS fiber exhibited good hygroscopic-heating properties with a maximum hygroscopic-heating value of 8.2 ℃, which was 4.7 ℃ higher than that for the acrylic fiber.

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    Environment-friendly high-efficiency CH3NH3PbI3 perovskite solar cells fabrication based on green antisolvent method
    MENG Jing, GAO Bowen
    Shandong Science    2023, 36 (3): 46-52.   DOI: 10.3976/j.issn.1002-4026.2023.03.006
    Abstract380)   HTML6)    PDF(pc) (1116KB)(208)       Save

    The energy conversion efficiency of CH3NH3PbI3 (MAPPbI3) perovskite solar cells is closely related to the quality of the perovskite film. To obtain high quality perovskite films, the film preparation method and process were optimized. It was found that the green solvents, propylene glycol methyl ether acetate and glycerol, can promote nucleation of PbI2 particles, provide heterogeneous nucleation sites for CH3NH3PbI3 perovskite crystals, and thus facilitate the rapid growth of perovskite crystals. Compared to perovskite films treated with the common toxic solvent chlorobenzene, films treated with propylene glycol methyl ether acetate and glycerol have larger grain size, lower root-mean-square value, and greater surface roughness optimization. This can result in a uniform, full-coverage perovskite film that is close to the perovskite carrier diffusion length. The performance of devices under different treatment conditions was tested and it was found that compared to CH3NH3PbI3 perovskite solar cells treated with chlorobenzene (energy conversion efficiency of 17.86%), the device treated with green solvent glycerol had the highest efficiency of 21.60%, which is an increase of nearly 21%. These experimental results have some reference value and guiding significance for researchers in this field to obtain environmentally friendly high-quality perovskite type solar cells in the future.

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    Exploration of the dosing pattern and anti-respiratory syncytial virus mechanism of traditional Chinese medicine based on data mining and network pharmacology
    SUN Tiefeng, DONG Limin, JIAO Ziqi, WANG Ping
    Shandong Science    2023, 36 (3): 1-9.   DOI: 10.3976/j.issn.1002-4026.2023.03.001
    Abstract374)   HTML19)    PDF(pc) (1175KB)(295)       Save

    The study aims to analyze the anti-respiratory syncytial virus (RSV) dosing pattern of traditional Chinese medicine (TCM) using data mining and network pharmacology, and to explore the possible mechanisms of core TCM. The CNKI database was searched to retrieve TCM prescriptions for treating RSV studies. SPSS Statistics 26.0 was used to classify and explore the qualified TCMs on their frequency, nature, taste, four qi and five flavors and their efficacy. Systematic cluster analysis was performed on the TCMs with a frequency greater than five. The compounds and targets were screened using the traditional Chinese medicine systematic pharmacology analysis platform. The above targets were then matched with the RSV disease targets obtained from GeneCards/OMIM database to obtain the key targets of high frequency anti-RSV TCM. Protein-protein interaction network analysis of the key targets was performed using the STRING platform, DAVID database, and the Kyoto encyclopedia of genes and genomes enrichment analysis. Finally, the Chinese herbal medicine-active ingredient-key target-pathway network was constructed using Cytoscape 3.7.1 software and topology analysis was performed. Ninety-one TCM compound prescriptions were identified which involves 121 TCMs that met the criteria. Among them, heat-clearing drugs, phlegm-relieving, cough-suppressing, and asthma-suppressing drugs were mostly found, with the majority attributed to the lung and liver meridians, mainly cold, warm, flat, bitter, pungent, and sweet. Ephedrae Herba, Scutellariae Radix, licorice, and Amygdalus Communis Vas had the highest cumulative frequency and were clustered into one category. A total of 126 active ingredients of Ephedra Herba, Scutellariae Radix, Glycyrrhizae Radix Et Rhizoma, and Armeniacae Semen Amarum were obtained. A total of 110 anti-RSV key targets were obtained, the core targets include GSR, TP53, SOD1, etc., cancer pathway, fluid shear and atherosclerosis pathway, AGE-RAGE signaling pathway, blood lipids and atherosclerotic lipids, etc.

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    Exploringtrait genes and predicting the targeted Chinese medicine for ulcerative colitis based on bioinformatics and machine learning
    LIANG Jiahao, ZHANG Xinhui, WANG Hai
    Shandong Science    2023, 36 (6): 56-67.   DOI: 10.3976/j.issn.1002-4026.2023.06.008
    Abstract371)   HTML10)    PDF(pc) (2803KB)(178)       Save

    For the identification of potential biomarkers for ulcerative colitis (UC) and prediction of their targeted traditional Chinese medicines, datasets containing human UC and healthy control tissues (GSE179285, GSE206285, and GSE87466) were downloaded from the GEO database. The GSE179285 and GSE206285 datasets were merged, and the differentially expressed genes (DEGs) between UC and healthy control tissues were screened using the limma R package. The LASSO regression model and SVM-RFE (support vector machine recursive feature elimination) algorithm were used to identify core biomarkers. The GSE87466 dataset was used as a validation cohort, and the ROC (receiver operating characteristic) curve was used to evaluate the diagnostic performance. CIBERSORT was used to investigate the immune infiltration characteristics in UC, and the correlation between potential biomarkers and different immune cells was further analyzed. Subsequently, the targeted traditional Chinese medicinal herbs were predicted using the HERB database. In total, 157 DEGs were screened out, with 102 genes upregulated and 55 genes downregulated. Functional enrichment analysis showed that these DEGs were mainly involved in IL-17 and TNF signaling pathway, rheumatoid arthritis, chemokine signaling pathway, humoral immune response, neutrophil chemotaxis, neutrophil migration, etc. LOC389023, OLFM4, AQP8, and CWH43 were identified as potential biomarkers for UC, and their diagnostic values were significant in the GSE87466 validation dataset. CIBERSORT immune infiltrate analysis showed significant differences in immune infiltration characteristics between UC and healthy control tissues. High levels of CD4+ memory activated T cells, M1 macrophages, and neutrophils were found in the UC group, while high levels of memory B cells, CD4+ memory resting T cells, M2 macrophages, and resting dendritic cells were found in the healthy control group. Seven traditional Chinese medicinal herbs targeting core biomarkers, including Sojae Semen Praeparatum, Fructus Viticis Cannabifoliae, Herba Equiseti Palustris, Liquor, Sophora alopecuroides L., Cervi Cornu Pantotrichum, and Placenta Hominis, were predicted in the HERB database. The study suggested that LOC389023, OLFM4, AQP8, and CWH43 were identified as diagnostic biomarkers for UC, and the aforementioned seven targeted traditional Chinese medicinal herbs may play a therapeutic role in UC by regulating gut microbiota, affecting inflammation pathways, and modulating the immune system.

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    The mechanism of Guishaozhenxian Tablet in the treatment of temporal lobe epilepsy based on network pharmacology and molecular docking
    ZHAO Xin, HUANG Biyun, WU Dan, ZHANG Mei
    Shandong Science    2023, 36 (3): 27-37.   DOI: 10.3976/j.issn.1002-4026.2023.03.004
    Abstract355)   HTML10)    PDF(pc) (1289KB)(164)       Save

    To study the mechanism of Guishaozhenxian Tablet in the treatment of temporal lobe epilepsy (TLE) based on network pharmacology. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to retrieve the active ingredients and action targets of Guishaozhenxian Tablet, and the standard gene was transformed using the UniProt database. The OMIM, GeneCards, and DrugBank databases were searched for disease targets related to TLE, and the intersection targets of Guishaozhenxian Tablet in the treatment of TLE were obtained using a Venn diagram. The medicinal herb-component-target network diagram was constructed using the Cytoscape 3.8.2 software, and the core components and key molecular targets were analyzed.Gene Ontology enrichment and the Kyoto encyclopedia of genes and genomes were used to analyze the biological processes and related pathways. The first three key targets and their corresponding top two core compounds were validated using molecular docking. In total, 127 active ingredients and 46 related targets were identified, with 14 ingredients, including β-sitosterol, quercetin, and kaempferol, playing a central role in 11 key targets such as CALM1, SCN5A, and GSK3B. The anti-TLE effect was primarily due to biological processes (regulation of membrane potential, response to drug, etc.), cell components (postsynaptic membrane, dendrites, etc.), molecular functions (channel activity, calmodulin binding, etc.), neuroactive ligand-receptor interaction, nicotine addiction, and other related pathways. Molecular docking results showed that CALM1, SCN5A, and GSK3B had good binding abilities with core compounds. Guishaozhenxian Tablet can reduce oxidative damage; protect neurons; affect ion channels and receptors, intracellular signal transduction, apoptosis, and synaptic structure; and exert anti-TLE effects via multi-components, multi-targets, and multi-pathway coordination.

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    Exploring the mechanism of Xiangsha Liujunzi Decoction in treating Helicobacter pylori-associated gastritis based on network pharmacology and molecular docking technology
    YIN Zhipeng, GAO Yunyun, LIU Wenwen, GUO Pengbo, ZHAO Yinghui
    Shandong Science    2023, 36 (4): 52-60.   DOI: 10.3976/j.issn.1002-4026.2023.04.007
    Abstract323)   HTML8)    PDF(pc) (1150KB)(956)       Save

    This study aimed to analyze the active ingredients of Xiangsha Liujunzi Decoction and its molecular mechanism in treating Helicobacter pylori-associated gastritis using network pharmacology and molecular docking. The drug active compounds, drug target genes, and disease-related targets of H. pylori-associated gastritis in Xiangsha Liujunzi Decoction were screened using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, GeneCards database, and OMIM database, and the drug targets and disease-related targets were analyzed using Venn analysis. Cytoscape software and STRING database were used to construct drug-compound potential target interaction network and protein-protein interaction network, respectively. Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed for intersection targets using the DAVID database. The key components and targets were docked using AutoDock PyMOL and other software. The apoptosis rate was determined with Jimsa staining and CCK-8 assay, and the expressions of the related target proteins were detected with western blot. Finally, 122 active compounds, such as quercetin, luteolin, and kaempferol, in Xiangsha Liujunzi Decoction were screened out. These genes may be involved in the treatment of H. pylori-associated gastritis by acting on 101 potential targets, such as STAT3, TP53, and AKT1, as well as 109 pathways, such as toll-like receptor, TNF, and T-cell receptor signaling pathways. Molecular docking showed that quercetin, β-sitosterol, and luteolin had good affinity for the target proteins STAT3, TP53, and AKT1. Compared with the model group, after treatment with Xiangsha Liujunzi Decoction, the nuclear hyperchromism of GES-1 cells was enhanced, the apoptosis rate was significantly decreased, and the expression of p-STAT3 was also significantly decreased. Based on these findings, it can be concluded that Xiangsha Liujunzi Decoction exerts antibacterial and anti-inflammatory effects in the treatment of H. pylori-associated gastritis in multiple ways via multiple components and targets.

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    Identification of rutin metabolites and analysis of rutin metabolic pathway in rats
    WANG Changlin, GAO Mingzhou, GUO Yinghui, SUN Ya, YU Xiaojun, YAN Zhi, WANG Jieqiong, QIAO Mingqi
    Shandong Science    2023, 36 (5): 9-18.   DOI: 10.3976/j.issn.1002-4026.2023.05.002
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    Herein, metabolites in plasma, urine and feces of rats were analyzed after oral administration of rutin and the metabolic pathway of rutin was evaluated. After intragastric administration of 250 mg/kg rutin, plasma, urine, and feces were collected and treated via solid phase extraction. Ultra-high performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrapmass spectrometry (UPLC-Q-Orbitrap MS) was used with 0.05% formic acid water (A)-0.05% formic acid acetonitrile (B) as mobile phase gradient elution. The sample data were collected in positive- and negative-ion modes. The metabolites and metabolic pathway of rutin in rats were determined via high resolution extraction ion chromatography in the parallel reaction monitoring mode, combined with chromatographic retention time, accurate mass measurement and diagnostic ions.Twenty-nine rutin metabolites were detected and identified in positive and negative ion modes,and their main metabolic pathways were methylation, glucuronidation, sulfation and their compound reaction. The study provided the overall metabolic profile of rutin, which will provide a reference for further pharmacodynamic evaluation, development, and utilization in the future and offer a comprehensive research method for drug metabolism identification.

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    Short-term prediction of urban railtransit passenger flow based on the Sparrow Search Algorithm-Long Short Term Memory combination model
    JIANG Jiawei, ZHAO Jinbao, LIU Wenjing, XU Yuejuan, LI Mingxing
    Shandong Science    2023, 36 (5): 75-84.   DOI: 10.3976/j.issn.1002-4026.2023.05.010
    Abstract316)   HTML13)    PDF(pc) (1252KB)(174)       Save

    With the rapid growth of China's economy and the continuous urbanization, rail transit plays an increasingly important role in residents' travel. As a key factor affecting the operation efficiency and service level of urban rail transit,accurate passenger flow prediction has attracted increasing attention from operation managers and researchers. To improve the prediction accuracy of the urban rail transit passenger flow, this paper combines sparrow search algorithm (SSA) and long short-term memory network (LSTM) and proposed a SSA-LSTM combined model. Based on the passenger flow data obtained from four stations of Hangzhou Metro Line 1 and the selected factors affecting the rail transit passenger flow, we used the proposed SSA-LSTM model to predict the short-term passenger flow of relevant stations. Then, we compared the predicted results with those estimated by the LSTM, GA-LSTM, and PSO-LSTM models. Results show that the prediction accuracy of the proposed model is 16.0%, 8.8%, and 2.3%, higher than the aforementioned models, respectively; furthermore, the proposed method exhibited better performance in terms of the root mean square error. Thus, the proposed model has potential applicationin predicting the urban rail transit passenger flow. Moreover, it can assistoperation managers in improving the operation efficiency and service level of urban rail transit.

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    Long-term performance maintenance decisions for asphalt pavements based on reinforcement learning
    HOU Mingye, WANG Xiaoyang, XU Qingjie, YANG Bo, WANG Xiaofeng
    Shandong Science    2023, 36 (3): 108-114.   DOI: 10.3976/j.issn.1002-4026.2023.03.013
    Abstract314)   HTML8)    PDF(pc) (1083KB)(311)       Save

    To address the huge data analysis problem in the decision-making for long-term road performance maintenance, this paper introduces the deep deterministic policy gradient (DDPG) reinforcement learning model in the maintenance decision analysis. A set of scientific and effective decision-making methods for long-term performance maintenance of asphalt pavements has been established through machine learning. These methods can improve road performance and make effective use of maintenance funds. Compared with the deep Q-learning network and Q-Learning algorithms, the DDPG algorithm requires less sampling data, converges faster, performs better, and can effectively improve the evaluation efficiency of the road service performance. Therefore, the proposed model plays an important role in the development of multi-objective maintenance decision-making for asphalt pavements.

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    Research progress on cascading failures in complex networks
    ZHANG Duyu, WU Jianjun, YANG Xin, MA Zhi’ao, ZHU Tianlei
    Shandong Science    2024, 37 (2): 85-96.   DOI: 10.3976/j.issn.1002-4026.20230179
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    With the development of network science and the emergence of complex systems theory, scholars have embarked on in-depth research on the structural and dynamic properties of complex networks. Among the dynamic properties of complex networks, cascading failures, as one of the most important research areas, describe a situation where a fault or error in a system or process leads to the failures of other related components or links. Various models and recovery strategies have been proposed for cascading failures in complex networks. This study analyzes the mechanisms of cascading failures, provides a comprehensive summary on the development of domestic and international cascading failure in complex networks, outlines the recovery strategies for addressing cascading failures, and highlights the existing issues and shortcomings in current research, providing valuable insights for future studies.

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    Exploring the traffic state identification of highway based on gantry data
    LIU Chunsheng, CAO Rong, WANG Xiaohan, ZHAO Heran, JIA Jianmin
    Shandong Science    2023, 36 (3): 100-107.   DOI: 10.3976/j.issn.1002-4026.2023.03.012
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    To thoroughly investigate the traffic state of highways, Jiqing Highway was selected as the study case. By mining the gantry data, a two-stage clustering algorithm combining k-means and density-based special clustering of applications with noise (DBSCAN) algorithms were proposed. The method was used to identify vehicles entering the service area and driving abnormally. Subsequently, the filtered vehicle records were extracted to realize a traffic state index weighted by the vehicle type to analyze the traffic state of the highway in terms of spatiotemporal dimensions. Results indicate that the two-stage clustering algorithm performs very well in the identification. The traffic state index indicated three periods when the highway is defined as congested during 7:00—20:00. Furthermore, it accurately identifies the congested sections of the highway. Moreover, it shows out that the mixed rate of large vehicles and the degree of traffic congestion in a section have a close positive correlation. Finally, according to the evaluation index, the traffic state of the Jiqing Highway is divided into four levels, which provides technical support for the traffic authorities to evaluate and manage the highway sections.

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    Mechanism of Sanhuang Xiexin decoction in treatment of Alzheimer's disease based on network pharmacology and molecular docking method
    WANG Yifan, ZHANG Zhe, TIAN Caijun
    Shandong Science    2023, 36 (5): 19-26.   DOI: 10.3976/j.issn.1002-4026.2023.05.003
    Abstract295)   HTML8)    PDF(pc) (1099KB)(517)       Save

    The aim of this study was to investigate the mechanism of action of Sanhuang Xiexin Decoction in the treatment of Alzheimer's disease (AD) using a network pharmacology approach. The active ingredients and targets of the Sanhuang Xiexin decoction were examined and screened using the systematic pharmacology database and the analysis platform of traditional Chinese medicine. AD-related targets were retrieved and screened through Gene Cards database, and drug and disease intersection targets were obtained through through Venn diagram.The STRING database was used to obtain the network information of protein-protein interaction (PPI). The Cytoscape was used to construct drugs-active ingredients-target-disease network and PPI,and DAVID database was used to analyze common targets in gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG). Furthermore, the Sybyl-x 2.1.1 software was used for molecular docking validation. The screening yielded 47 active ingredients and 71 related targets. Herein,the main active ingredients were quercetin, β-sitosterol, wogonin, baicalein, rivularin, and moslosooflavone; and the core targets were IL-6,TNF,IL-1β,VEGFA,TP53.The GO function enrichment analysis predominantly involved biological processes including drug response, hypoxia response, positive regulation of cell migration,and positive regulation of nitric oxide biosynthesis.KEGG analysis mainly involved pathways such as cancer pathways, HIF-1 signaling pathways, and TNF signaling pathways.Molecular docking results showed the presence of a relatively strong binding ability between the core target and the core compounds, such as β-sitosterol and rivularin.This study preliminarily explained that the Sanhuang Xiexin Decoction can interfere with AD by modulating HIF-1, TNF, and other signaling pathways, thereby inhibiting Aβ aggregation and tau phosphorylation, blocking acetylcholinesterase activation, and suppressing inflammation.

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    Action mechanism of the herb pair Aurantii Fructus Immaturus-Magnoliae Officinalis Cortex in the treatment of slow transit constipation based on network pharmacology and metabolomics
    DONG Pengjun, CAI Bin
    Shandong Science    2023, 36 (3): 18-26.   DOI: 10.3976/j.issn.1002-4026.2023.03.003
    Abstract294)   HTML8)    PDF(pc) (1877KB)(673)       Save

    The potential action mechanism of aurantii fructus immaturus and magnoliae officinalis cortex in the treatment of slow transit constipation (STC) was investigated via network pharmacology and metabolomics.The chemical ingredients and targets of aurantii fructus immaturus and magnoliae officinalis cortex were obtained using the traditional Chinese medicine systems pharmacology database and analysis platform. The disease prediction targets of STC were collected through the GeneCards, OMIM, and DisGeNET databases. The intersection targets of ingredients and diseases were obtained using Venn diagrams. The STRING database was used to construct the protein-protein interaction network. The Cytoscape 3.8.0 software was used to calculate and screen the key targets, and then the network diagram of TCM-ingredient targets was plotted. The gene ontology(GO) functional enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of the intersection targets were performed using the Metascape database. A loperamide-induced STC mouse model was used in the study. After intragastric administration of aurantii fructus immaturus and magnoliae officinalis cortex, GC/TOF-MS-based untargeted metabolomics of cecal contents was performed to analyze differential metabolites. A total of 24 active ingredients and 106 intersection targets were obtained. The key targets with higher degree values included AKT1, TNF, TP53, IL6, CASP3, and JUN. GO analysis revealed that the possible processes were cellular response to nitrogen compound, cellular response to lipid, positive regulation of protein phosphorylation, regulation of inflammatory response, regulation of ion transport, etc. KEGG analysis revealed the pathways involved in cancer, the PI3K-Akt signaling pathway, the calcium signaling pathway, serotonergic synapse, etc. In addition, 21 differential metabolites were found via untargeted metabolomics, including the Akt-associated metabolites nicotinic acid, fructose, and protocatechuic acid. The results suggested that aurantii fructus immaturus and magnoliae officinalis cortex exerted therapeutic effects on STC via multi-ingredient, multi-target and multi-pathway mechanisms, thereby providing ideas and a theoretical basis for future basic research. The active ingredients naringenin and lignan, as well as the key target Akt and its related metabolites, deserves special attention.

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    Research on differentiated toll pricing for highways based on bi-level programming
    CHENG Sijie, SHAO Xiaoming, LI Zhen, WANG Jiangfeng
    Shandong Science    2023, 36 (5): 93-101.   DOI: 10.3976/j.issn.1002-4026.2023.05.012
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    To improve the utilization of highway resources and the traffic situation in parallel national and provincial roads, in this study, the interests of highway operators and users was comprehensively accounted; a differentiated toll pricing model with the upper-level objective of increasing highway operating revenues and the lower-level objective of achieving multiclass stochastic traffic network equilibrium was established; and a model incorporating the genetic algorithm, simulated annealing algorithm, and iterative weighting method was developed. Based on the analysis of the traffic characteristics of the Longqing highway and its parallel national and provincial roads in the Shandong Province, the proposed model was used to develop differential toll schemes for entrance and exit sections, time periods, and vehicle types on the highway. The results show that the optimal differentiated tolling schemes can increase the operating revenue of the Longqing highway in the north-south direction by 7861900 yuan/year and reduce the travel cost of the road network by 7 165 100 yuan/year, which confirms the practicality of the proposed model and the effectiveness of the multimode differentiated tolling schemes for highways.

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    Wave sensor fault diagnosis method based on t-SNE reduction and KNN algorithm
    TAI Peng, SONG Miaomiao, WANG Bo, CHEN Shizhe, FU Xiao, HU Wei, GAO Saiyu, CHENG Kaiyu, ZHENG Shanshan, JIAO Zixuan, WANG Longfei
    Shandong Science    2023, 36 (4): 1-9.   DOI: 10.3976/j.issn.1002-4026.2023.04.001
    Abstract286)   HTML26)    PDF(pc) (1283KB)(378)       Save

    This study proposes an efficient wave sensor fault diagnosis method based on wavelet packet decomposition, dimension reduction, and k-nearest neighbor algorithm(KNN) classification network to address the difficulty of wave sensor fault diagnosis, unidentifiable fault types, and time-consuming diagnosis. First, the standard deviation of the original signal is normalized. The normalized data is then subjected to a three-layer wavelet packet decomposition. The extracted feature vectors represent normalized data from the eight bands on layer 3. The second step involves using the t-distributed stochastic neighbor embedding (t-SNE) algorithm to reduce the dimension of the feature data. Finally, the dimension-reduced feature data is input into the KNN classification network for fault classification and detection. Experimental results show that the proposed method can improve the accuracy and diagnosis speed of the wave sensor fault diagnosis, with a diagnosis accuracy of up to 93.55% for normal and six faulty conditions.

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    Train control method for high-speed railways combining“hit-hard-wall” and “hit-soft-wall” control modes
    LI Wei, ZHANG Shoushuai
    Shandong Science    2023, 36 (5): 85-92.   DOI: 10.3976/j.issn.1002-4026.2023.05.011
    Abstract285)   HTML7)    PDF(pc) (1075KB)(191)       Save

    The passing capacity of several busy high-speed railway lines in China is declining, and reducing train headway can considerably improve train density.However, optimizing the control method for train control systems is important to reduce the headway. On one hand, the commonly employed “hit-hard-wall” control mode has redundancies, rendering it inefficient. On the other hand,the “hit-soft-wall” control mode cannot ensure the absolute safety of train operation. Therefore, this paper proposes a combined“hit-hard-wall” and “hit-soft-wall” control mode, which reduces train tracking interval while ensuring the absolute safety of the train. Further, basic principles for optimizing this control mode are presented herein.In addition, solutions for problems such as the inability to determine the speed of the preceding train and to fulfill control curve constraints under this mode are explored.The solutions include track circuit information-based train speed estimation and control curve generation techniques that satisfy relevant constraints. Considering the CRH380BL train as an example, a solution was developed to obtain recommended values for train control deceleration.Consequently, the train tracking interval on straight tracks was reduced by 3035 meters, and the interval tracking time was reduced by 31 seconds through the proposed control mode. This is of great significance for improving the operational efficiency and passing capacity of high-speed railway lines.

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    Network pharmacology to explore the mechanism of Wangbi formula in the treatment of rheumatoid arthritis
    WANG Yifan, ZHANG Yanyan, TIAN Caijun
    Shandong Science    2023, 36 (3): 38-45.   DOI: 10.3976/j.issn.1002-4026.2023.03.005
    Abstract284)   HTML3)    PDF(pc) (1140KB)(251)       Save

    Based on the research methods of network pharmacology, we discuss the potential mechanism of Wangbi formula in the treatment of rheumatoid arthritis (RA) in this article. The chemical components and action targets of the Wangbi formula were extracted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The RA-related targets were retrieved from the GeneCards database, the intersection targets of drugs and diseases were obtained using a Venn diagram, and the protein-protein interaction (PPI) network information was obtained using the STRING database. Moreover, the Cytoscape software was used to create the network diagram of drug-active ingredient-target-diseases and PPI, and the common targets were analyzed using Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) from the DAVID database. Furthermore, the Sybyl-x 2.1.1 software was used for molecular docking validation. Screening yielded 32 active ingredients and 99 related targets, and the core targets were found to be IL-6, TNF, ATK1, PTGS2, VEGFA, etc. The GO function enrichment analysis mainly involved biological processes, such as positive regulation of RNA polymerase II promoter transcription, whereas KEGG pathway enrichment analysis mainly involved TNF, T-cell receptor, toll-like receptor, osteoclast differentiation, and other signaling pathways. The molecular docking results revealed that the core components, such as kaempferol, triptolide, naringenin, kaempferoside, and prickly shank anthocyanin, demonstrated good binding activity with the core targets, such as IL-6, TNF, ATK1, PTGS2, and VEGFA. This study provided a preliminary explanation of the multicomponent and multitarget mechanisms that may underlie the Wangbi formula's potential mechanism of action in the treatment of RA.

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    Progress and development trends in the use of zebrafish as a model organism for evaluating cosmetic efficacy
    XIA Qing, ZANG Xiaohan, WANG Yongcheng, ZHANG Yun, LI Peihai, ZHANG Xuanming, LIU Kechun
    Shandong Science    2024, 37 (2): 36-46.   DOI: 10.3976/j.issn.1002-4026.20240016
    Abstract284)   HTML19)    PDF(pc) (3892KB)(517)       Save

    Zebrafish models have been widely used in various fields such as drug screening, pharmacology, and toxicology research. In recent years, with the implementation of regulations such as the standard for the Evaluation of Cosmetic Efficacy Claims, cosmetic efficacy claims have entered into an era of strict supervision, which has led to higher standards for the scientific nature of the efficacy evaluation models and methods. The skin structure of zebrafish is highly similar to that of humans, with zebrafish also having transparent embryos that are easy to observe. Moreover, efficacy evaluation experiments using zebrafish offer advantages such as minimal sample dosage, shortened experimental cycles, and high-throughput capacity. Consequently, zebrafish have become a popular research topic in the field of cosmetic efficacy evaluation. Based on bibliometric methods, this study analyzes the relevant literature on the use of zebrafish to evaluate cosmetic efficacy over the past decade. The study provides an overview of the progress of the application of zebrafish in cosmetic efficacy evaluation, and examines the development dynamics and trends through comprehensive analysis. This is so as to provide a reference for the application of zebrafish models in the cosmetics industry.

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    Three-dimensional characterization of inclusions in alloy steel using X-ray micro-CT computer tomo-graphy
    SUN Fei, MENG Genglong, TIAN Linan, LI Qiumeng, LI Nan, LIU Long
    Shandong Science    2023, 36 (3): 53-59.   DOI: 10.3976/j.issn.1002-4026.2023.03.007
    Abstract282)   HTML6)    PDF(pc) (1154KB)(199)       Save

    Inclusions have an impact on the fatigue strength and fatigue life of steel, but inclusions in large samples cannot be accurately imaged using X-ray micro computer tomo-graphy(X-ray micro-CT). This study provides a novel approach to obtain the three-dimensional morphology of inclusions in large steel samples. To realize the three-dimensional features of inclusions in large alloy samples, this study used a nonaqueous electrolysis method to obtain inclusions; then scanning electron microscopy was performed to observe and analyze the electrolyzed inclusions.Furthermore, the electrolyzed inclusions were aggregated into cylindrical samples and finally scanned with X-ray micro-CT to obtain their three-dimensional information, and the obtained dimensional data of the inclusions were statistically analyzed.

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    Progress in the research on the mechanism of action of Scutellaria baicalensis and its active ingredients in treating ulcerative colitis
    LUO Yaqin, HUANG Wei
    Shandong Science    2024, 37 (2): 20-28.   DOI: 10.3976/j.issn.1002-4026.20240017
    Abstract281)   HTML12)    PDF(pc) (1112KB)(949)       Save

    Ulcerative colitis (UC) is an inflammatory bowel disease characterized by persistent mucosal inflammation.Scutellaria baicalensis (also known as Huangqin), as a common traditional Chinese medicines used in clinical practice, is known for its efficacy at clearing internal heat,eliminating dampness, purging fire,eliminating toxins, stopping bleeding, and calming fetal activity. Its formulations, including Huangqin Decoction, Peony Decoction, and Pueraria, Scutellaria, and Coptis Decoction, are often used to treat damp-heat UC. Studies have shown that S. baicalensis and its active ingredients play an important role in protecting the intestinal mucosa, and have anti-inflammatory and immunomodulatory effects. This study reviews the mechanism of action of S. baicalensisand its active ingredients (baicalin,baicalein,oroxindin, wogonin, Scutellaria baicalensis polysaccharide, etc.) in the treatment of UC in recent years, including the protection and repair of the intestinal mucosal barrier, the active ingredients anti-inflammatory and immunomodulatory properties, effects against antioxidative stress, and regulation of intestinal flora, to provide a reference for targeted clinical treatment of UC and drug development.

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    Review of marine environment monitoring methods based on GNSS technology
    QI Suiping, XU Xiaofei, LI Yunzhou, WANG Juncheng, DU Jun
    Shandong Science    2024, 37 (2): 1-11.   DOI: 10.3976/j.issn.1002-4026.20240023
    Abstract277)   HTML35)    PDF(pc) (2142KB)(177)       Save

    Real-time, accurate and reliable monitoring of marine environmental information plays a crucial role in marine disaster warning and prediction, disaster prevention and reduction, marine resource development, and ensuring marine safety. In recent years, with the continuous development and upgrading of global navigation satellite systems (GNSS), the detection of atmospheric and marine environmental information based on GNSS navigation signals has become a new method and a hot research topic in the marine environmental monitoring technology. This method has been widely applied to domains such as marine meteorological monitoring and numerical forecasting. This article systematically reviews the current research status of the GNSS technology in marine environmental monitoring, including effective wave height, wind speed, rainfall intensity, water vapor and tide level monitoring. Furthermore, this paper systematically summarizes new technologies and methods and looks forward to provide reference for the future research in related fields.

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    Analysis of the contents of active ingredients in Lonicerae japonicae flos based on UPLC-MS/MS combined with chemometrics
    QIAN Guiying, QIAN Yunying, WU Xiaoming, JIN Fengzhu
    Shandong Science    2023, 36 (5): 1-8.   DOI: 10.3976/j.issn.1002-4026.2023.05.001
    Abstract276)   HTML18)    PDF(pc) (1148KB)(116)       Save

    This study aimed to devise a methodology for the simultaneous determination of the contents of nine primary components in Lonicerae japonicae flos through ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The chemometric analysis of the nine primary components was performed via negative ion scanning. Further, chromatographic separation was performed on a Thermo Hypersil GOLD column at a temperature of 35 ℃. The mobile phase comprised methanol and water containing 0.2% formic acid, as determined through the cluster thermogram and principal component analyses of Lonicerae japonicae flos. The peak areas with concentrations of nine components exhibited a good linear relationship (R2>0.999 1), and the intraday (0.96%~2.26%) and interday (0.52%~3.04%) precisions and stability values (0.85%~2.15%) agreed well with relative standard deviation (RSD). The recovery rate was between 96.77% and 101.94%, and the RSD was between 2.48% and 4.01%. The results of the chemometric, hierarchical cluster, and principal component analyses revealed that there were considerable differences in the contents of the active ingredients of Lonicerae Japonicae Flos from various regions, and 3-O-caffeoylquinic acid and 3,5-dicaffeoylquinic acid were considered as the dominant compounds. UPLC-MS/MS quantitative and chemometric analyses of Lonicerae Japonicae Flos performed herein may provide a reference for the modernization of and innovative research on the effective ingredients of Lonicerae Japonicae Flos and related quantity effect relations as well as the quality control of related products.

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    Spatial and temporal distribution characteristics of air pollution and potential source areas in winter of Jinan
    WANG Zhifei, WANG Zaifeng, LÜ Chen, FU Huaxuan, BIAN Meng, SUN Fengjuan, ZHANG Wenjuan
    Shandong Science    2023, 36 (4): 114-121.   DOI: 10.3976/j.issn.1002-4026.2023.04.014
    Abstract271)   HTML13)    PDF(pc) (1128KB)(299)       Save

    Using the datasets of major air pollutants and meteorological observations during the winter from 2016 to 2018 in Jinan, the characteristics of air pollution were analyzed to identify the major transport pathway of airmass. The results showed that during the winter from 2016 to 2018 in Jinan, about 63.8% and 34.7% of the major pollutants were PM2.5 and PM10, respectively. Of the total number of days, 58.6% had a pollution level worse than good polluted. The annual average concentration of PM2.5 increased by 7.5 μg/m3 due to its high concentration in the winter. In terms of spatial distribution, the concentrations of PM10 and PM2.5 were high inTianqiao District, Huaiyin District, and Pingyin County; the concentration of SO2 was high in Shanghe County and Jiyang District; and the concentrations of NO2 and CO were high in Jiyang District, Tianqiao District and Huaiyin District. The results also showed that ρ(NO2), ρ(CO), ρ(PM10), and ρ(PM2.5) had a positive correlation, with all r >0.7. It was inferred that traffic source, industrial combustion source, and burning coal were the major sources of particulate matter. The airmass in the winter of Jinan came from south, northwest, north, and east, and the airmass from south and east were the major transport pathway of air pollution. Further analyses of the potential source contribution and concentration weight showed that the air pollution in Jinan City was affected by the local and surrounding cities, and the current air pollution presents the characteristics of cross-contamination across regions. Therefore, a supervision and coordination mechanism for the joint prevention and control of air pollution in the region should be established to coordinate research and solve growing problems of air pollution.

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    Streamline optimization analysis of side-scan sonar on small autonomous underwater vehicle
    LIU Jin, TAN Hua, SU Liang, QIU Guoji, LIU Rui, LUO Chongxin, WANG Yu, LIU Hao
    Shandong Science    2023, 36 (6): 8-14.   DOI: 10.3976/j.issn.1002-4026.2023.06.002
    Abstract262)   HTML13)    PDF(pc) (3216KB)(262)       Save

    Water dynamics analysis was conducted on a compact and portable autonomous underwater vehicle(AUV) with side-scan sonar and amodified AUV with streamlined side-scan sonar. The analysis focused on examining the drag forces experienced by both AUVs at different speeds. The results demonstrated that the streamlined side-scan sonar effectively reduced pressure and viscous drag forces, resulting in an overall drag reduction of 15.4% at a normal speed of 3 knots, with a 9% reduction in viscous drag and an 18% reduction in pressure drag.At a high speed of 6 knots, the overall drag was reduced by 10.1%, with a 4.2% reduction in viscous drag and a 12% reduction in pressure drag. These findings demonstrate that optimizing the streamlined design of the AUV with side-scan sonar can effectively enhance the dynamic performance of the AUV, reduce its drag force, and improve its efficiency and performance.

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    Optical fiber microseismic monitoring system and its application research in Wuyang Coal Mine
    ZHANG Hua, HU Binxin, ZHU Feng, WANG Jiqiang, SONG Guangdong
    Shandong Science    2023, 36 (5): 60-66.   DOI: 10.3976/j.issn.1002-4026.2023.05.008
    Abstract261)   HTML6)    PDF(pc) (1137KB)(249)       Save

    Optical fiber microseismic monitoring technology is used to monitor and alert the microvibration events generated during production activities through observation and analysis with passivity and high reliability. Herein, the sensors are vertically installed on the side bolts along the roadway, and the monitoring substation is installed in the chamber. The sensors and the monitoring substation constitute a monitoring network through the laid optical cables. Besides, the simplex method is used to locate the seismic source. This method is free from divergence problems in the location calculation and is highly stable. Moreover, in this method, the solution of the partial derivative and inverse matrix is not required, which reduces the calculation amount and improves the calculation efficiency. Additionally, each sensor can use different wave velocities during the calculation based on the actual situation. The optical fiber microseismic monitoring system was installed in Shanxi Wuyang Coal Mine for preliminary monitoring and application, and the monitoring results were analyzed. The results show that the system can monitor mine activities and warn early, thereby playing a positive role in safe production.

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    Review on the analytical technique for antimony speciation in environmental media
    XU Lei, ZHAO Rusong, JING Chuanyong, WANG Xia
    Shandong Science    2023, 36 (4): 122-133.   DOI: 10.3976/j.issn.1002-4026.2023.04.015
    Abstract261)   HTML7)    PDF(pc) (1052KB)(214)       Save

    This study reviews the speciation analysis methods of antimony indifferent environmental media in recent years. Inductively-coupled plasma mass spectrometry is widely used in the antimony speciation analysis because of its advantages such as low detection limit, high sensitivity, and good stability. Before the speciation analysis, extracting different forms of antimony from a complex matrix and maintaining its valence stability are essential. This can be achieved by combining the sensitive detection technology, efficient sample pretreatment techniques, and separation methods. In recent years, the combined techniques have been widely used for the determination of antimony in various environmental samples. Moreover, the challenges in this field and the development prospect of antimony speciation analysis method are discussed.

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    Fault detection of an on-load tap changer based on generative adversarial network
    JIANG Xiaodong, WANG Leilei, SUN Peng, YANG Guang, GENG Junqi, WANG Jiawen, HUANG Sheng, QU Shuai, WANG Chen, SHANG Ying
    Shandong Science    2023, 36 (6): 68-73.   DOI: 10.3976/j.issn.1002-4026.2023.06.009
    Abstract258)   HTML6)    PDF(pc) (2336KB)(100)       Save

    The probability of power transformer failure is extremely low, which leads to a great impact on further in-depth analysis results due to unbalanced data when processing transformer fault data. To solve these problems, this study processes and judges the unbalanced data using an confrontation neural network combined with an artificial neural network, uses the distributed acoustic wave sensing technology based on ultraweak fiber Bragg gratings to collect and analyze the data of the simulation site of the transformer built in a laboratory, and achieves good results on the collected transformer fault simulation data. This method has an important referential significance for developing the small sample fault identification system of the on-load transformer using confrontation generation network.

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    Path planning for material transportation by combining mountain road and freight ropeway
    QIN Jian, ZHANG Feikai, LIU Chen, XIA Yongjun
    Shandong Science    2023, 36 (3): 90-99.   DOI: 10.3976/j.issn.1002-4026.2023.03.011
    Abstract255)   HTML6)    PDF(pc) (1295KB)(277)       Save

    Path planning for material transportation is the fundamental work for constructing power transmission line in complex terrain areas. Such paths generally comprise road and ropeway transportation paths. Based on the digital elevation model and Dijkstra algorithm, this study proposed a combined material transportation path planning algorithm for road and ropeway. Using the fast search method of no-load ropeway transportation path based on parabola, a load ropeway transportation path optimization based on catenary was implemented. Then, the road transportation path was optimally searched using Dijkstra algorithm, and the coordinated planning of road and ropeway transportation paths was conducted. The proposed algorithm was applied to the material transportation path planning of an ultra-high voltage transmission line's towers. Results showed that the combined ropeway and road transportation paths can effectively shorten the design period of material transportation path and improve the efficiency of construction material transportation.

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    A multitask learning model for the prediction of short-term subway passenger flow
    ZHANG Hanxiao, LIU Yuran, LIU Yuan, NIU Zichen
    Shandong Science    2024, 37 (1): 95-106.   DOI: 10.3976/j.issn.1002-4026.20230038
    Abstract253)   HTML16)    PDF(pc) (1274KB)(192)       Save

    An accurate prediction of short-term subway passenger flowscan effectively alleviate traffic congestion and improve the quality of travel services for urban residents. Herein, we propose a multitask learning-based model for the prediction of short-term subway passenger flows, which uses a residual convolutional neural network (NN) and a nested long short-term memory NN to extract the spatio-temporal correlation of traffic patterns, and introduces an attention mechanism to enhance the feature extraction performance of the NNs. Considering the characteristics of subway operations, the model selects train operation features, bus stops around subway stations, and point of interest data as external features to improve the accuracy of the prediction. Based on the historical data of the Beijing Subway, experiments were conducted in multiple time granularity scenarios, such as 10, 30, and 60 min. The results showed that the methodsuccessfully modeled and analyzed the inflow-outflow interaction through multitask learning, improved the prediction performance and generalization ability of the model, and providednovel approaches for the prediction of short-term subway passenger flows.

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    Research progress in high-salinity wastewater treatment by the freeze concentration method
    WANG Xiaokai, ZHAO Changsheng, LI Luzhen, ZHANG Bowei, LIU Xuzhen, TAN Yu
    Shandong Science    2023, 36 (6): 121-130.   DOI: 10.3976/j.issn.1002-4026.2023.06.015
    Abstract252)   HTML9)    PDF(pc) (1815KB)(1164)       Save

    The industrial production process produces large quantities of high-salinity wastewater comprising complex water-quality components, including a large amount of Na+, Cl-, SO42-, and other salts as well as toxic substances. Traditional high-salinity wastewater treatment technology has low efficiency and high operating cost. The freeze concentration method for high-salinity wastewater treatment has received widespread attention as a highly efficient and clean treatment technology without secondary pollution. However, the problem of impurities in the ice crystals prepared via freeze concentration should be solved urgently. This article summarizes the research progress of freeze concentration technology in high-salinity wastewater treatment in recent years. The key parameters such as freezing time, freezing temperature, and initial solution concentration were discussed, and various methods for removing impurities from ice crystals, including immersion, gravity, and water addition purification methods, were investigated. To accelerate the desalination process and improve the desalination effect, nucleating agent and ultrasonic-assisted freeze concentration methods were investigated. Furthermore, the energy consumption of the freeze concentration technology was economically analyzed. Moreover, the development of the technology is summarized and a prospect is proposed to provide specific references for the development and application of freeze concentration method in high-salinity wastewater treatment.

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    Research progress of green scale inhibitors for circulating cooling water
    HE Zhenbo, ZHANG Li, GAO Mingxin, LUAN Lingyu
    Shandong Science    2023, 36 (5): 102-120.   DOI: 10.3976/j.issn.1002-4026.2023.05.013
    Abstract250)   HTML8)    PDF(pc) (1208KB)(219)       Save

    Recently, circulating cooling water systems have been widely used to alleviate water shortage.However, cooling water usually contains various mineral ions,such as calcium and magnesium, which can easily form insoluble salts and scale on the surface of the equipment. The use of scale inhibitors in cooling water systems is one of the most effective methods to solve the scaling problem. In this paper, the recent research progress on green scale inhibitors at home and abroad was reviewed. The development and applications of green scale inhibitors were introduced here. The characteristics and scale inhibition performance of different types of scale inhibitors are also analyzed.Moreover,the scale inhibition mechanism was explained from different aspects,such as chelation and solubilization, coagulation and dispersion, and lattice distortion.Therefore,this review would provide an excellent reference for future research and development of green scale inhibitors.

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    Electric vehicle pickup and delivery based on link recharging and time windows
    CHEN Qing, XU Xiaoming
    Shandong Science    2023, 36 (3): 78-89.   DOI: 10.3976/j.issn.1002-4026.2023.03.010
    Abstract250)   HTML4)    PDF(pc) (1140KB)(325)       Save

    In this paper, the electric vehicles pickup and delivery problem considering link recharging and time windows was studied. Aims to minimize the total travel distance of vehicles, considering the constraints of vehicle capacity, time windows and battery capacity, etc., to determine a group of optimal vehicle routes. The problem is formulated as a mixed integer linear programming model; a variable neighborhood search algorithm is proposed to solve it. Numerical instances are used to verify the model properties and algorithm performance. The results show that the proposed algorithm is only 0.08% worse than the commercial solver CPLEX in small scale instances; however, in large scale instances, the algorithm can obtain high quality feasible solutions in the specified time, in contrast to the CPLEX.

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    Characteristics of spatiotemporal variation of monthly-scale extreme precipitation in Shandong Province under climate warming
    ZOU Jin, LI Jun, GAO Li
    Shandong Science    2023, 36 (4): 104-113.   DOI: 10.3976/j.issn.1002-4026.2023.04.013
    Abstract249)   HTML7)    PDF(pc) (1172KB)(206)       Save

    To reveal the multiscale variation law of extreme precipitation events under climate warming, based on the daily precipitation data of the National Meteorological Station from 1961 to 2020, the spatiotemporal variation characteristics of extreme precipitation events on the monthly scale in Shandong Province were analyzed using the percentile relative threshold method. The results show that the monthly-scale extreme precipitation events in Shandong Province mainly occurred in July and August with the annual frequency bigger than 40%. The annual frequency showed a decreasing trend as one moves from southeast to northwest regions. The annual frequency and precipitation of extreme precipitation events increased in most areas for all seasons except autumn and considerably increased in winter. After the mid-1980s, extreme precipitation events have generally increased and intensified, and their interannual changes have increased significantly. The intensity of extreme precipitation in summer and winter increased significantly by 10 mm to 20 mm during 10 years in summer in the central, southwestern, and peninsular areas of Shandong and 20% to 50% in winter months in Shandong province. The precipitation instability generally increases under climate warming in Shandong, and it is necessary to strengthen early warning and defense services for disaster risks such as rainstorm, flood, and blizzard.

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    The mechanism of Gandouling tablet in alleviating hepatolenticular degeneration neuroinflammation via the regulation of the TLR4/NF-κB/NLRP3 signaling pathway
    WEN Yuya, DONG Ting, JIANG Zhangsheng, CHEN Jie, TIAN Liwei, ZHAO Chenling, TANG Lulu
    Shandong Science    2023, 36 (4): 42-51.   DOI: 10.3976/j.issn.1002-4026.2023.04.006
    Abstract248)   HTML11)    PDF(pc) (1330KB)(242)       Save

    This study aimed to investigate the effect of Gandouling tablet on neuroinflammation in hepatolenticular degeneration in TX mice and mechanism of generating CuCl2-induced microglia inflammatory response based on TLR4/NF-κB/NLRP3 signaling pathway. TX mice were divided into control, model, Gandouling tablet low-dose, Gandouling tablet medium-dose, Gandouling tablet high-dose, and penicilamine groups. BV2 cells were divided into control, model, Gandouling tablet, TAK-242, and Gandouling tablet + TAK-242 groups. Hematoxylin and eosin staining was performed to detect histopathological changes in the hippocampus of mice in each group. Western blot was used to detect the expressions of TLR4, p65, NLRP3, and IL-1β in hippocampal tissue and BV2 cells of mice in each group. Enzyme-linked immunosorbent assay was performed to quantify TNF-α, IL-1β, and IL-6 levels in hippocampal tissue and BV2 cells of mice in each group. Real-time polymerase chain reaction was used to determine the expression of TLR4, p65, NLRP3, TNF-α, and IL-1β mRNA in all groups of BV2 cells. Compared with the control group, hippocampal tissue in the model group showed considerable inflammatory damage; increased protein expressions of TLR4, p65, NLRP3, and IL-1β; and significantly increased levels of TNF-α, IL-1β, and IL-6 (P<0.05). Compared with the model group, the pathological damage of hippocampal tissue improved in both Gandouling tablet and penicillamine groups, and the effect of Gandouling tablet in the Gandouling tablet high-dose group was more prominent than that in the other groups. The Gandouling tablet and TAK-242 groups inhibited the activation of BV2 cells. Additionally, the expression of TLR4, p65, NLRP3, and IL-1β protein and mRNA were significantly reduced in these two groups as compared with the model group, and TNF-α, IL-1β and IL-6 levels were significantly decreased (P < 0.05). Gandouling tablet can alleviate hippocampal inflammation and inhibit CuCl2-induced hyperactivation of BV2 cells in TX mice probably by downregulating TLR4/NF-κB/NLRP3 signaling pathway.

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    Research progress on the mechanisms by which natural phenolic compounds alleviate hyperuricemia
    LIU Shuang, DONG Hongjing, CHEN Panpan, WANG Xiao
    Shandong Science    2024, 37 (2): 12-19.   DOI: 10.3976/j.issn.1002-4026.20240028
    Abstract248)   HTML18)    PDF(pc) (1595KB)(2424)       Save

    Hyperuricemia (HUA) is a metabolic disorder caused by the physiologic disorders in purine metabolism, resulting in increased serum uric acid levels, which can lead to gout in severe cases. HUA pathogenesis primarily involves enzyme dysfunction, urate transporter expression dysregulation, glucose and lipid metabolism disorders, and intestinal homeostasis disruption. Numerous studies have reported the effectiveness of natural polyphenols in alleviating hyperuricemia and gout. This article summarizes HUA pathogenesis and the mechanisms of action of polyphenolic compounds in reducing uric acid, to provide a theoretical basis for the research and development of uric acid-lowering drugs.

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    Optimization study on customized bus stop location and fare considering carbon tax
    CAO Hong, REN Hualing
    Shandong Science    2023, 36 (4): 69-79.   DOI: 10.3976/j.issn.1002-4026.2023.04.009
    Abstract245)   HTML8)    PDF(pc) (1125KB)(95)       Save

    To study the influence of carbon tax on the relation between residents' commuting travel choices and social welfare in the process of optimizing customized bus fares for commuter corridors, a two-tier planning model that considers the flexible passenger flow demand and overall social welfare of corridors is established. The upper layer of the model decides the departure location and customized bus fare, and the lower layer is the flexible demand passenger flow allocation model, considering both customized bus and private carbon the commuter corridor. From the perspective of residents' travel satisfaction, the relationship between random passenger flow demand and ticket price was analyzed in the context of carbon tax. According to different passenger departure points, the passenger flow demand is refined as the input of the passenger flow allocation model of the lower elastic demand. Considering the relationship among the passenger flow demand, road congestion, passenger satisfaction, and social welfare, the welfare of corridor passenger transportation system is set as the optimization goal of the upper model. The measurement statistical analysis and particle swarm algorithm are used to solve the two-layer programming model. The calculation results show that the optimized social welfare is considerably improved, the road traffic conditions are significantly improved, and the progressive carbon tax shows positive effect on increasing the sharing rate of customized buses. Under the carbon tax setting, the optimized customized bus fares and departure locations can serve social welfare and reduce the operating costs of urban passenger transportation systems.

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