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Inter-layer interference for multi-layered tight gas reservoir in the absence and presence of movable water

Petroleum Science 2024年第3期21卷 1751-1764页

作者： Tao Zhang Bin-Rui Wang Yu-Long Zhao Lie-Hui Zhang Xiang-Yang Qiao Lei Zhang Jing-Jing Guo hung vo thanh National Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Southwest Petroleum UniversityChengdu60500SichuanChina Shaanxi Yanchang Petroleum(Group)Corp.Ltd. Xian710075ShaanxiChina Waseda Research Institute for Science and Engineering Waseda UniversityTokyoJapan

Due to the dissimilarity among different producing layers,the influences of inter-layer interference on the production performance of a multi-layer gas reservoir are ***,systematic studies of inter-layer interference for tight gas reservoirs are really limited,especially for those reservoirs in the presence of *** this work,five types of possible inter-layer interferences,including both absence and presence of water,are identified for commingled production of tight gas ***,a series of reservoir-scale and pore-scale numerical simulations are conducted to quantify the degree of influence of each type of *** field evidence from the Yan'an tight gas reservoir(Ordos Basin,China)is found to support the simulation ***,suggestions are proposed to mitigate the potential inter-layer *** results indicate that,in the absence of water,commingled production is favorable in two situations:when there is a difference in physical properties and when there is a difference in the pressure system of each *** reservoirs with a multi-pressure system,the backflow phenomenon,which significantly influences the production performance,only occurs under extreme conditions(such as very low production rates or well shut-in periods).When water is introduced into the multi-layer system,inter-layer interference becomes nearly *** both the gas-rich layer and water-rich layer for commingled production is not desirable,as it can trigger water invasion from the water-rich layer into the gas-rich *** gas-rich layer might also be interfered with by water from the neighboring unperforated water-rich layer,where the water might break the barrier(eg weak joint surface,cement in fractures)between the two layers and migrate into the gas-rich ***,the gas-rich layer could possibly be interfered with by water that accumulates at the bottom of the wellbore due to gravitational diff

关键词： Tight gas Comingled production Interference Two-phase flow Water blocking

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Machine learning based models for predicting compressive strength of geopolymer concrete

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： Quang-Huy LE Duy-hung NGUYEN thanh SANG-TO Samir KHATIR Hoang LE-MINH Amir H.GANDOMI thanh CUONG-LE Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

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Comparative Chemical Research in Essential Oils from Six Apiaceae Species Growing in the Northern Region of Vietnam

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Phyton-International Journal of Experimental Botany 2024年第7期93卷 1677-1687页

作者： Nguyen Quang hung Nguyen thanh Tung Nguyen Phuong Hanh Chu Thi Thu Ha Nguyen Thi Nhung Nguyen Thai An Vu Xuan Giang Luong Van Hao Oleh Koshovyi Ain Raal Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology(VAST)Cau GiayHa Noi100000Viet Nam Graduate University of Science and Technology Vietnam Academy of Science and Technology(VAST)Cau GiayHa Noi100000Viet Nam Department of Pharmacognosy Faculty of Pharmacognosy and Traditional MedicineHanoi University of PharmacyHoan KiemHa Noi100000Viet Nam Sa Pa Research Center of Medicinal Materials National Institute of Medicinal MaterialsDien Bien PhuSa PaLao Cai330000Viet Nam Institute of Pharmacy Faculty of MedicineUniversity of TartuTartu50411Estonia

Our study aimed to compare the essential oil(EO)concentration and composition of several Apiaceae species growing in the Northern region of *** yields of EOs from materials ranged from 0.03%(root EO of Angelica acutiloba and aerial parts EO of Heracleum bivittatum)-0.27%(leaf EO of Xyloselinum vietnamense).Gas chromatography-mass spectrometry(GC-MS)allowed the identiﬁcation of 74 components in the EOs of six Apiaceae species,making up 94.4%–100.0%of the *** EO from Angelica acutiloba,(Z)-ligustilide accounted for an extremely large proportion(94.9%).EO of Angelica pubescens was dominated by six character-istic components includingα-pinene(21.5%),β-phellandrene(18.1%),p-cymene(12.2%),3-methylnonane(8.7%),o-cymene(8.1%),and D-sylvestrene(6.2%).The EO from Cryptotaenia japonica was characterized by high amounts ofα-selinene(48.7%),β-selinene(23.7%),and trans-β-farnesene(5.4%).The EOs from leaves and stems of Xyloselinum vietnamense were characterized by high concentrations of sabinene(69.8%and 33.8%),4-terpineol(8.7%and 7.4%)andβ-pinene(4.0%and 6.5%)while EOs from aerial parts and root of Xylo-selinum leonidii comprise four characteristic monoterpenes includingα-pinene(28.2%and 52.8%),β-pinene(7.9%and 10.3%),β-phellandrene(7.6%and 15.3%),and sabinene(3.0%and 4.1%).Additionally,cryptone is also one of the major components in the EO of Xyloselinum leonidii(13.2%in the aerial parts oil and 2.8%in the root oil).In the EOs isolated from the aerial parts and root of Heracleum bivittatum,α-pinene(22.5%and 70.2%)andβ-pinene(43.2%and 20.0%)were the predominant *** appeared in the EO from aerial parts of Heracleum bivittatum with a relatively high concentration(13.5%)while bornyl acetate(5.1%)was also one of the main components in the EO from its aerial parts but was not detected in other Apiaceae species in the present *** databases help identify and control the quality of plant material studied from the family Apiaceae growing in Vietnam.

关键词： Apiaceae essential oil terpenoids gaschromatography-mass spectrometry

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Effect of Freeze-Thaw and Urea in Solubility of GPC3-Csub Protein Expressed in Escherichia coli

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Journal of Biosciences and Medicines 2024年第4期12卷 288-297页

作者： Xuan-Truc Chu-Dao Kim-Tuyen Huynh-Dam Dang-Thuc Ngo-Luong Quang-Luan Le thanh-Thao vo-Nguyen Department of Medical Biotechnology Biotechnology Center of Ho Chi Minh City Ho Chi Minh City Vietnam

Glypican-3 is a protein encoded by the Glypican-3 gene located on human X chromosome (Xq26), composed of two subunits, a 40 kDa N-terminal subunit, and a 30 kDa C-terminal subunit. Glypican-3 is a currently potential target molecule for liver cancer treatments because of its over-expression and growth effects on hepatocellular carcinoma (HCC). This study examined the expression and purification of a C-terminal subunit of Glypican-3 protein (GPC3-Csub) due to its application in both diagnosis and therapy for hepatocellular carcinoma. The gene encoding for GPC3-Csub was successfully cloned into plasmid pET28a fused with an affinity tag composed of six consecutive histidine residues (His-tag). Recombinant protein GPC3-Csub was expressed in Escherichia coli BL21 (DE3) in the condition of adding 3% ethanol with IPTG induction. GPC3-Csub was extracted using repeated freeze-thaw cycles with lysozyme, and inclusion bodies were solubilized by 8M Urea, SDS 10% in pH 12. His-tag fused GPC3-Csub proteins allowed it to be purified by affinity chromatography method using the Nickel-nitrilotriacetic acid (Ni-NTA) column. High expression of GPC3-Csub was confirmed by Coomassie staining and western-blot. GPC3-Csub could be isolated with a Ni-NTA column and have a purity of about 90%.

关键词： Glypican-3 Affinity Chromatography Inclusion Body Liver Cancer

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A Study on Optimizing the Double-Spine Type Flow Path Design for the Overhead Transportation System Using Tabu Search Algorithm

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Intelligent Automation & Soft Computing 2024年第2期39卷 255-279页

作者： Nguyen Huu Loc Khuu Thuy Duy Truong Quoc Dien Le Tran thanh Cong Vu Hoa Binh Tran Tuong Quan vo Department of Mechatronics Faculty of Mechanical EngineeringHo Chi Minh City University of Technology(HCMUT)Ho Chi Minh CityVietnam Bach Khoa Research Center for Manufacturing Engineering Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh CityVietnam VietnamNational University Ho ChiMinh City Ho ChiMinh CityVietnam

Optimizing Flow Path Design(FPD)is a popular research area in transportation system design,but its application to Overhead Transportation Systems(OTSs)has been *** study focuses on optimizing a double-spine flow path design for OTSs with 10 stations by minimizing the total travel distance for both loaded and empty *** employ transportation methods,specifically the North-West Corner and Stepping-Stone methods,to determine empty vehicle travel ***,the Tabu Search(TS)algorithm is applied to branch the 10 stations into two main layout *** results obtained from our proposed method demonstrate a reduction in the objective function value compared to the initial feasible ***,we explore howchanges in the parameters of the TS algorithm affect the optimal *** validate the feasibility of our approach by comparing it with relevant literature and conducting additional tests on layouts with 20 and 30 stations.

关键词： Overhead transportation systems tabu search double-spine layout transportationmethod empty travel flow path design

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Exponentially Bounded C-semigroup and the Cauchy Initial Value Problems in Complete Random Normed Modules

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Acta Mathematica Sinica,English Series 2024年第9期40卷 2195-2212页

作者： Son TA CONG Thang Dang hung Oanh Le THI Department of Mathematics University of ScienceVietnam National University 334 Nguyen TraiThanh XuanHanoiVietnam Faculty of Natural Sciences Hong Duc University565 Quang TrungDong VeThanh HoaVietnam

In this paper,the notion of C-semigroup of continuous module homomorphisms on a complete random normal(RN)module is introduced and *** existence and uniqueness of solution to the Cauchy problem with respect to exponen... 详细信息

关键词： C-semigroup Cauchy problem random normed modules L^(0)-Lipschitz

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Effects of Serum Concentration, Synchronization Time and Confluence on the Cell-Cycle Synchronization Efficiency of Goat Fibroblasts

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Open Journal of Animal Sciences 2024年第3期14卷 194-203页

作者： Van Khanh Nguyen Huong Thu Thi Vu Au Thi Hoang Yen Kim Thi Pham Giang Thi thanh Nhan hung Phu Lai Lan Doan Pham Key Laboratory of Animal Cell Biotechnology National Institute of Animal Science Hanoi Vietnam

This study aims to evaluate the effect of serum concentration, synchronization time, and confluence degree on the synchronisation efficiency of goat fibroblast cycle. The results indicated that there was no difference in the percentage of nucleated fibroblasts in the G0/G1 stage between serum concentrations of 0.3% and 0.4% (83.89% and 82.69%, respectively, P > 0.05) as well as between serum concentrations of 0.2% and 0.5% (76.95% and 75.46%, respectively, P > 0.05). The percentage of nucleated fibroblasts in the G0/G1 stage was highest at the concentration of 0.3% and lowest in the control group (83.89% vs. 62.67%, P 0.05). The beneficial effect of high confluence was confirmed by the large percentage of nucleated fibroblasts at the G0/G1 stage. The 60% confluency was significantly lower than the 80% and 100% confluency (73.44%, 86.63%, and 87.17%, respectively, P < 0.05). The results indicate that the goat fibroblast cycle synchronization is the most effective at the serum concentration of 0.3%, 72 hours of synchronization and 100% confluency.

关键词： Goat Fibroblast Cycle Synchronisation Serum Concentration Synchronization Time Confluence

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A concise review on surface and structural modification of porous zeolite scaffold for enhanced hydrogen storage

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Chinese Journal of Chemical Engineering 2024年第6期70卷 33-53页

作者： B.A.Abdulkadir R.S.R.Mohd Zaki A.T.Abd Wahab S.N.Miskan Anh-Tam Nguyen Dai-Viet N.vo H.D.Setiabudi Centre for Research in Advanced Fluid&Processes Universiti Malaysia Pahang Al-Sultan AbdullahLebuh Persiaran Tun Khalil YaakobGambangPahang 26300Malaysia Faculty of Chemical&Process Engineering Technology Universiti Malaysia Pahang Al-Sultan AbdullahLebuh Persiaran Tun Khalil YaakobGambangPahang 26300Malaysia Center of Excellence for Green Energy and Environmental Nanomaterials(CE@GrEEN) Nguyen Tat Thanh University300A Nguyen Tat ThanhDistrict 4Ho Chi Minh City 755414Viet Nam

Investigating zeolites as hydrogen storage scaffolds is imperative due to their porous nature and favorable physicochemical ***,the storage capacity of the unmodified zeolites has been rather unsatisfactory(0.224%-1.082%(mass))compared to its modified ***,the contemporary focus on enhancing hydrogen storage capacities has led to significant attention towards the utilization of modified zeolites,with studies exploring surface modifications through physical and chemical treatments,as well as the integration of various active *** enhanced hydrogen storage properties of zeolites are attributed to the presence of aluminosilicates from alkaline and alkaline-earth metals,resulting in increased storage capacity through interactions with the charge density of these ***,there is a great demand to critically review their role such as well-defined topology,pore structure,good thermal stability,and tunable hydrophilicity in enhanced hydrogen *** article aimed to critically review the recent research findings based on modified zeolite performance for enhanced hydrogen *** of the factors affecting the hydrogen storage capacities of zeolites that can affect the rate of reaction and the stability of the adsorbent,like pressure,structure,and morphology were studied,and ***,future perspectives,recommendations,and directions for modified zeolites were discussed.

关键词： Zeolites Hydrogen storage Surface modification Adsorption Active metal

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OPT-BAG Model for Predicting Student Employability

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Computers, Materials & Continua 2023年第8期76卷 1555-1568页

作者： Minh-thanh vo Trang Nguyen Tuong Le Faculty of Information Technology HUTECH UniversityHo Chi Minh CityVietnam Faculty of Information Technology Ho Chi Minh City Open UniversityHo Chi Minh CityVietnam Laboratory for Artificial Intelligence Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityVietnam Faculty of Information Technology School of TechnologyVan Lang UniversityHo Chi Minh CityVietnam

The use of machine learning to predict student employability is important in order to analyse a student’s capability to get a *** on the results of this type of analysis,university managers can improve the employability of their students,which can help in attracting students in the *** addition,learners can focus on the essential skills identified through this analysis during their studies,to increase their *** effectivemethod calledOPT-BAG(OPTimisation of BAGging classifiers)was therefore developed to model the problem of predicting the employability of *** model can help predict the employability of students based on their competencies and can reveal weaknesses that need to be ***,we analyse the relationships between several variables and the outcome variable using a correlation heatmap for a student employability ***,a standard scaler function is applied in the preprocessing module to normalise the variables in the student employability *** training set is then input to our model to identify the optimal parameters for the bagging classifier using a grid search cross-validation ***,the OPT-BAG model,based on a bagging classifier with optimal parameters found in the previous step,is trained on the training dataset to predict student *** empirical outcomes in terms of accuracy,precision,recall,and F1 indicate that the OPT-BAG approach outperforms other cutting-edge machine learning models in terms of predicting student *** this study,we also analyse the factors affecting the recruitment process of employers,and find that general appearance,mental alertness,and communication skills are the most *** indicates that educational institutions should focus on these factors during the learning process to improve student employability.

关键词： Ensemble classifier grid search cross-validation OPT-BAG student employability

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A Hybrid Deep Learning Approach for PM2.5 Concentration Prediction in Smart Environmental Monitoring

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Intelligent Automation & Soft Computing 2023年第6期36卷 3029-3041页

作者： Minh thanh vo Anh Hvo Huong Bui Tuong Le Faculty of Information Technology HUTECH UniversityHo Chi Minh CityVietnam Natural Language Processing and Knowledge Discovery Laboratory Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Computing Fundamentals FPT UniversityHo Chi Minh CityVietnam Laboratory for Artificial Intelligence Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityVietnam Faculty of Information Technology Van Lang UniversityHo Chi Minh CityVietnam

Nowadays,air pollution is a big environmental problem in develop-ing *** this problem,particulate matter 2.5(PM2.5)in the air is an air *** its concentration in the air is high in developing countries like Vietnam,it will harm everyone’s *** prediction of PM2.5 concentrations can help to make the correct decision in protecting the health of the *** study develops a hybrid deep learning approach named PM25-CBL model for PM2.5 concentration prediction in Ho Chi Minh City,***,this study analyzes the effects of variables on PM2.5 concentrations in Air Quality HCMC *** variables that affect the results will be selected for PM2.5 concentration ***,an efficient PM25-CBL model that integrates a convolutional neural network(CNN)andBidirectionalLongShort-TermMemory(Bi-LSTM)*** model consists of three following modules:CNN,Bi-LSTM,and Fully connected ***,this study conducts the experiment to compare the performance of our approach and several state-of-the-art deep learning models for time series prediction such as LSTM,Bi-LSTM,the combination of CNN and LSTM(CNN-LSTM),and *** empirical results confirm that PM25-CBL model outperforms other methods for Air Quality HCMC dataset in terms of several metrics including Mean Squared Error(MSE),Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).

关键词： Time series prediction PM2.5 concentration prediction CNN Bi-LSTM network

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