Pub Date : 2022-09-01DOI: 10.3724/sp.j.1249.2022.05559
X. Zhu, Bin Yuan, Yuanhui Tong, Ming Zhao, He Zheng, Xiulei Liu
{"title":"Deep-learning-based proxy model for forecasting gas flooding performance of fractured well pattern in tight oil reservoirs","authors":"X. Zhu, Bin Yuan, Yuanhui Tong, Ming Zhao, He Zheng, Xiulei Liu","doi":"10.3724/sp.j.1249.2022.05559","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05559","url":null,"abstract":"","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48140585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.3724/sp.j.1249.2022.05504
Xin Hao, Lin Gan, Shipeng Hu, Q. Luo, Zhengxin Wu, Jian Zhong, Haige Zhao, Huibin Sun
Abstract: High purity germanium detector plays an important role in the field of radiation detection. High purity germanium with 13N purity and dislocation density between 100 ~ 10 000 cm-2 was successfully prepared through zone melting purification and single crystal growth. In the zone melting experiment, the self-made horizontal zone furnace is used to achieve the purification requirements through 20 ~ 50 times of zone melting in the environment of high-purity hydrogen. The single crystal is grown by Czochralski method along the [100] direction in high-purity hydrogen environment with effective length > 50 mm and effective diameter > 30 mm. The dislocation density measurement adopts the etching method. The acid etching solution is used to etch the crystal (100) surface and the number of the etch pits is counted. The results show that the dislocation densities at 25, 50 and 72 mm from the head of the single crystal are 2 537, 3 425 and 4 075 cm-2 respectively. These results indicate that the dislocation density before 72 mm meets the requirements for the preparation of high-purity germanium detectors. The research can provide reference for the preparation of high purity germanium single crystal.
{"title":"Preparation of high purity germanium single crystal and analysis of dislocation density","authors":"Xin Hao, Lin Gan, Shipeng Hu, Q. Luo, Zhengxin Wu, Jian Zhong, Haige Zhao, Huibin Sun","doi":"10.3724/sp.j.1249.2022.05504","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05504","url":null,"abstract":"Abstract: High purity germanium detector plays an important role in the field of radiation detection. High purity germanium with 13N purity and dislocation density between 100 ~ 10 000 cm-2 was successfully prepared through zone melting purification and single crystal growth. In the zone melting experiment, the self-made horizontal zone furnace is used to achieve the purification requirements through 20 ~ 50 times of zone melting in the environment of high-purity hydrogen. The single crystal is grown by Czochralski method along the [100] direction in high-purity hydrogen environment with effective length > 50 mm and effective diameter > 30 mm. The dislocation density measurement adopts the etching method. The acid etching solution is used to etch the crystal (100) surface and the number of the etch pits is counted. The results show that the dislocation densities at 25, 50 and 72 mm from the head of the single crystal are 2 537, 3 425 and 4 075 cm-2 respectively. These results indicate that the dislocation density before 72 mm meets the requirements for the preparation of high-purity germanium detectors. The research can provide reference for the preparation of high purity germanium single crystal.","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44587587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.3724/sp.j.1249.2022.05550
Zhikai Guo, Rong Wang, Weicheng Wu, Ming Li, Wanggui He, Shi-Yin Zhou
Actinomycetes residing in marine habitat are an excellent treasure house of structurally novel and Received: 2022-01-10; Accepted: 2022-06-06; Online (CNKI): 2022-08-09 Foundation: Hainan Provincial Basic and Applied Basic Research Fund for High-Level Talents in Natural Science (2019RC306, 2019RC352); Central Public-Interest Scientific Institution Basal Research Fund for CATAS-ITBB (1630052022028, 1630052022016, 1630052019011); Financial Fund of the Ministry of Agriculture and Rural Affairs of China (NFZX2021) Corresponding author: Associate professor GUO Zhikai. E-mail: guozhikai@itbb.org.cn Associate professor LI Ming. E-mail: liming0898@163.com Citation: GUO Zhikai, WANG Rong, WU Weicheng, et al. Bioactive secondary metabolites from two sponge-derived actinomycetes [J]. Journal of Shenzhen University Science and Engineering, 2022, 39(5): 550-558. (in Chinese) 第 5期 郭志凯,等:两株海绵放线菌产生的抗菌活性产物研究 http://journal.szu.edu.cn bioactive natural products with potent medicinal values. To exploit chemically diverse and bioactive natural products from actinomycetes living in underexplored ecological niche, we isolate a large number of marine actinomycetes from marine sponges, corals, algae, mollusks, sea grasses, and sediments collected from the South China Sea. In order to assess the values of these special marine actinomycetes in the green development of tropical agriculture, we screen the activity of marine actinomycetes against phytopathogenic fungi and bacteria. As a result, we identify two strains of sponge-derived actinobacteria Streptomyces sp. HMH1 and HML1 possessing antagonism effect against tested phytopathogenic microbes. The secondary metabolites produced by these two actinomycete strains and their antiphytopathogenic fungi activity are investigated. The secondary metabolites from the fermentation extract of Streptomyces sp. HMH1 and HML1 are isolated and purified using various chromatography methods including silica gel column, reverse gel column and Sephadex LH-20 column chromatography. The structures of the isolated compounds are characterized by NMR, HR-ESI-MS spectroscopic data analyses and comparison with previously reported data. Three major compounds belonging to the family of actinomycin are purified from the solid fermentation extract of the sponge-derived actinobacterium Streptomyces sp. HMH1. They actinomycin D, actinomycin X2, and actinomycin Xoβ. A compound identified as K-252d belonging to the family of indolocarbazole alkaloid is isolated from the solid fermentation extract of another sponge-derived actinobacterium Streptomyces sp. HML1. The antiphytopathogenic fungi and bacteria activities of these compounds are evaluated against ten species of plant pathogenic fungi including Fusarium oxysporum FOC4, Lasiodiplodia theobromae, Phomopsis caricae-papayae Fetrak&Cif., Corynespora cassiicola, Phytophthora capsica, Pythium aphanidermatum (Edson) Fitzp, Corynespora sp., Fusarium graminearum, Verticillium dahlia, Pestalotiopsis microspo
{"title":"Bioactive secondary metabolites from two sponge-derived actinomycetes","authors":"Zhikai Guo, Rong Wang, Weicheng Wu, Ming Li, Wanggui He, Shi-Yin Zhou","doi":"10.3724/sp.j.1249.2022.05550","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05550","url":null,"abstract":"Actinomycetes residing in marine habitat are an excellent treasure house of structurally novel and Received: 2022-01-10; Accepted: 2022-06-06; Online (CNKI): 2022-08-09 Foundation: Hainan Provincial Basic and Applied Basic Research Fund for High-Level Talents in Natural Science (2019RC306, 2019RC352); Central Public-Interest Scientific Institution Basal Research Fund for CATAS-ITBB (1630052022028, 1630052022016, 1630052019011); Financial Fund of the Ministry of Agriculture and Rural Affairs of China (NFZX2021) Corresponding author: Associate professor GUO Zhikai. E-mail: guozhikai@itbb.org.cn Associate professor LI Ming. E-mail: liming0898@163.com Citation: GUO Zhikai, WANG Rong, WU Weicheng, et al. Bioactive secondary metabolites from two sponge-derived actinomycetes [J]. Journal of Shenzhen University Science and Engineering, 2022, 39(5): 550-558. (in Chinese) 第 5期 郭志凯,等:两株海绵放线菌产生的抗菌活性产物研究 http://journal.szu.edu.cn bioactive natural products with potent medicinal values. To exploit chemically diverse and bioactive natural products from actinomycetes living in underexplored ecological niche, we isolate a large number of marine actinomycetes from marine sponges, corals, algae, mollusks, sea grasses, and sediments collected from the South China Sea. In order to assess the values of these special marine actinomycetes in the green development of tropical agriculture, we screen the activity of marine actinomycetes against phytopathogenic fungi and bacteria. As a result, we identify two strains of sponge-derived actinobacteria Streptomyces sp. HMH1 and HML1 possessing antagonism effect against tested phytopathogenic microbes. The secondary metabolites produced by these two actinomycete strains and their antiphytopathogenic fungi activity are investigated. The secondary metabolites from the fermentation extract of Streptomyces sp. HMH1 and HML1 are isolated and purified using various chromatography methods including silica gel column, reverse gel column and Sephadex LH-20 column chromatography. The structures of the isolated compounds are characterized by NMR, HR-ESI-MS spectroscopic data analyses and comparison with previously reported data. Three major compounds belonging to the family of actinomycin are purified from the solid fermentation extract of the sponge-derived actinobacterium Streptomyces sp. HMH1. They actinomycin D, actinomycin X2, and actinomycin Xoβ. A compound identified as K-252d belonging to the family of indolocarbazole alkaloid is isolated from the solid fermentation extract of another sponge-derived actinobacterium Streptomyces sp. HML1. The antiphytopathogenic fungi and bacteria activities of these compounds are evaluated against ten species of plant pathogenic fungi including Fusarium oxysporum FOC4, Lasiodiplodia theobromae, Phomopsis caricae-papayae Fetrak&Cif., Corynespora cassiicola, Phytophthora capsica, Pythium aphanidermatum (Edson) Fitzp, Corynespora sp., Fusarium graminearum, Verticillium dahlia, Pestalotiopsis microspo","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41597964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.3724/sp.j.1249.2022.05567
Chengcheng Luo, N. Wu, Hua Wang, Yonghui Liu, Teng Zhang, Benqiang Wang, Pengbo Wu, J. Liu
{"title":"Pressure gradient prediction of gas-liquid two-phase pipe flow in horizontal gas wells","authors":"Chengcheng Luo, N. Wu, Hua Wang, Yonghui Liu, Teng Zhang, Benqiang Wang, Pengbo Wu, J. Liu","doi":"10.3724/sp.j.1249.2022.05567","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05567","url":null,"abstract":"","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41884287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.3724/sp.j.1249.2022.05515
Liang Hong, Xin Jin, Xiaohan Liu, X. Wei
Abstract: In order to predict the fuel rod temperature performance effectively, we establish a series of machine learning models based on k-nearest neighbor, decision tree and AdaBoost algorithms. The input parameters and calculation results of fuel rod performance analysis software JASMINE and data feature engineering are used as the training and test data for the machine learning models. The models are trained by the training data set which includes the characteristic parameters such as pellet and cladding type, axial height, local power, cladding corrosion thickness and core inlet temperature. After training, the models use the test data to predict the cladding outside surface temperature and pellet center temperature. The prediction results show that the model based on AdaBoost algorithm has the best prediction performances, and the mean square errors of cladding outside surface temperature and pellet center temperature are 0. 605 °C and 8. 347 °C, respectively, and the average absolute errors are 0. 273 °C and 3. 814 °C , respectively. Comparing the predicted values with the target values, the maximum deviation of Adaboost algorithm for the cladding outside surface temperature is 3 °C, and the most of the prediction deviation of the pellet center temperature is less than 10 °C, indicating that the model based on AdaBoost algorithm has the high prediction accuracy for the temperature performance of fuel rods.
{"title":"Application of machine learning algorithm in the prediction of fuel rod temperature performance","authors":"Liang Hong, Xin Jin, Xiaohan Liu, X. Wei","doi":"10.3724/sp.j.1249.2022.05515","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05515","url":null,"abstract":"Abstract: In order to predict the fuel rod temperature performance effectively, we establish a series of machine learning models based on k-nearest neighbor, decision tree and AdaBoost algorithms. The input parameters and calculation results of fuel rod performance analysis software JASMINE and data feature engineering are used as the training and test data for the machine learning models. The models are trained by the training data set which includes the characteristic parameters such as pellet and cladding type, axial height, local power, cladding corrosion thickness and core inlet temperature. After training, the models use the test data to predict the cladding outside surface temperature and pellet center temperature. The prediction results show that the model based on AdaBoost algorithm has the best prediction performances, and the mean square errors of cladding outside surface temperature and pellet center temperature are 0. 605 °C and 8. 347 °C, respectively, and the average absolute errors are 0. 273 °C and 3. 814 °C , respectively. Comparing the predicted values with the target values, the maximum deviation of Adaboost algorithm for the cladding outside surface temperature is 3 °C, and the most of the prediction deviation of the pellet center temperature is less than 10 °C, indicating that the model based on AdaBoost algorithm has the high prediction accuracy for the temperature performance of fuel rods.","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46119211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An algorithm for matching original experimental records based on improved CDC","authors":"Yi'na Cai, Xin Chen, Zhi-qiang Qin, Xin Wang, Xianyu Bao, Jinxue Peng, Yongqi Lin, Junlin Li","doi":"10.3724/sp.j.1249.2022.05509","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05509","url":null,"abstract":"","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43126102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: To evaluate the effect of policy on province-wide toll discount for electronic toll collection (ETC) trucks, and to clarify the influence of trucks registered in other provinces on the toll discount flowed back to the local enterprises, we use structured query language server (SQL Server) database technology to process the toll collection data on expressway network, and propose an algorithm of recovery rate for the explanatory variables of toll preference, and verify the feasibility of the algorithm is by a case study. The results show that the recovery rate of the study case is 43. 38% when there is an 85% discount on ETC truck toll in 2019, and 52. 77% of the 56. 62% toll discount outflowed from the case studied is generated by the trucks registered in other provinces according to a conservative estimate. Among them, the proportion of the toll discount of trucks registered in other provinces with 6 axles accounts for 77. 29%, which is the root of toll discount loss. Although the traffic number across the province is not
{"title":"Impact of trucks registered in other provinces on ETC differentiated charging in provincial expressway network","authors":"Sheng-yu Yan, Zhenyu Zhan, Yanhong Li, Junyi Zhang","doi":"10.3724/sp.j.1249.2022.05608","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05608","url":null,"abstract":"Abstract: To evaluate the effect of policy on province-wide toll discount for electronic toll collection (ETC) trucks, and to clarify the influence of trucks registered in other provinces on the toll discount flowed back to the local enterprises, we use structured query language server (SQL Server) database technology to process the toll collection data on expressway network, and propose an algorithm of recovery rate for the explanatory variables of toll preference, and verify the feasibility of the algorithm is by a case study. The results show that the recovery rate of the study case is 43. 38% when there is an 85% discount on ETC truck toll in 2019, and 52. 77% of the 56. 62% toll discount outflowed from the case studied is generated by the trucks registered in other provinces according to a conservative estimate. Among them, the proportion of the toll discount of trucks registered in other provinces with 6 axles accounts for 77. 29%, which is the root of toll discount loss. Although the traffic number across the province is not","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45581331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
One of the effective ways to improve the operational efficiency of the rail system and achieve intelligent operation of rail transit, based on machine learning algorithm theory, combined with the passenger flow characteristics of rail transit stations such as time, space, and external influencing factors, a lightweight gradient boosting machine (LightGBM), long short term memory (LSTM), and LightGBM-LSTM fusion model for station short-term passenger flow prediction are established, Simultaneously constructing differential autoregressive integrated moving average (ARIMA) and extreme gradient boosting (XGBoost) models as control models for predictive experiments. Taking the swiping data of the Hangzhou subway ticketing system in China as an example, Five subway stations (residential type, work type, mixed residential and work type, shopping type, and transportation hub type) and three accuracy evaluation indicators (average absolute error, root mean square error, and average absolute percentage error) were selected to quantitatively evaluate the predictive accuracy of different models
{"title":"Machine learning based method for forecasting short-term passenger flow in urban rail stations","authors":"Mingwei Hu, Xiaolong Shi, Wen Wu, Guoqing He","doi":"10.3724/sp.j.1249.2022.05593","DOIUrl":"https://doi.org/10.3724/sp.j.1249.2022.05593","url":null,"abstract":"交通压力的有效途径之一.为提高轨道系统的运行效率,实现轨道交通智慧化运营,基于机器学习算法理 论,结合轨道交通车站的时间、空间及外部影响因素等客流特征,建立轻量的梯度提升机(light gradient boosting machine,LightGBM)、长短期记忆(long short-term memory,LSTM)及 LightGBM-LSTM融合模型的车 站短时客流预测模型,同时构建差分自回归移动平均(autoregressive integrated moving average,ARIMA)和极 限梯度提升(extreme gradient boosting,XGBoost)模型作为预测实验的对照模型.以中国杭州地铁自动售票系 统刷卡数据为例,选取了5种地铁车站(居住类型、工作类型、居住工作混合类型、购物类型及交通枢纽类 型)和3个准确性评价指标(平均绝对误差、均方根误差及平均绝对百分误差),量化评价不同模型的预测准","PeriodicalId":35396,"journal":{"name":"Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41770587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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