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Carboxymethyl starch cross-linked by electron beam radiation in presence of acrylic acid sensitizer

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Nuclear Science and Techniques 2013年第B12期24卷 19-22页

作者： Doan Binh nguyen thanh Duoc Pham thi Thu Hong R & D Center for Radiation Technology Vietnam Atomic Energy Institute 202A St. 11 Linh Xuan Ward Thu Duc District Ho Chi Minh City Vietnam

Carboxymethyl starch (CMS) can be cross-linked by electron beam radiation to form a biocompatible and environment-friendly hydrogel at a high absorbed dose and a condensed CMS concentration. Acrylic acid (AAc) can be used as a sensitizer in order to reduce the absorbed doses to an acceptable certain level. At an absorbed dose of 3-4 kGy, the gel content of crosslinked CMS can be obtained about 50% with 5% (w/w) AAc concentration used. The compressive strength of CMS samples increased with increasing their cross-linked densities due to raising absorbed doses. The swelling ratio of cross-linked CMS was also attainable at a maximum of 50 times in the distilled water. The enzymatic degradation of cross-linked CMS was carried out in acetate buffer pH 4.6 with 0.1% α-amylase enzymatic solution incubated at 40°C for 6 h. The crosslinked CMS samples were degraded slower than uncrosslinked CMS ones. The results indicated that the highly cross-linked CMS was almost fully degradable when the enzymatic hydrolysis was performed during 6 h. The FT IR spectra of cross-linked CMS in the presence of AAc were examined to observe the carboxyl group of AAc in the structure of cross-linked CMS. The hydrophilic of cross-linked CMS surface was determined by a contact-angle analysis. © 2013, Science Press. All rights reserved.

关键词：交联密度羧甲基淀粉电子束辐射丙烯酸敏化剂 FT-IR光谱吸收剂量 CMS

Electrochemical Immunosensor for Detection of Atrazine Based on Polyaniline/Graphene

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Journal of Materials Science & Technology 2016年第6期32卷 539-544页

作者： nguyen Van Chu nguyen Hai Binh Cao thi thanh nguyen Van Tu nguyen Le Huy nguyen Tuan Dzung Phan Ngoc Minh Vu thi Thu Tran Dai Lam Institute of Materials Science Vietnam Academy of Science and Technology18 Hoang Quoc VietCau Giay.HanoiViet Nam School of Chemical Engineering.Hanoi University of Science and Technology 1 Dai Co VietHanoiViet Ham Institute for Tropical Technology.Vietnam Academy of Science and Technology 18 Hoang Quoc VietHanoiViet Nam Center for High Technology Development Vietnam Academy of Science and Technology18 Hoang Quoc VietHanoiViet Nam University of Science and Technology of Hanoi.18 Hoang Quoc Viet HanoiViet Ham Graduate University of Science and Technology.Vietnam Academy of Science and Technology 18 Hoang Quoc Viet.HanoiViet Nam

In this study, a novel layer-by-layer polyaniline/graphene （PANi/Gr） structure for electrochemical detec- tion of atrazine was developed. Gr film was synthesized by thermal chemical vapor deposition （CVD） method and transferred onto the PANi-predeposited microelectrode. The properties of PANi/Gr film were thoroughly investigated by high-resolution transmission electron microscopy and Raman techniques. The most attractive feature of this system is a suitable microenvironment, which could provide an amplifi- cation of the conductive signal, thus may contribute to enhancing electron transfer and subsequently improve the sensitivity in electrochemical measurements. With low detection limit （- 43 × 10 -12 g/L）, ac-ceptable stability and good reproducibility, the proposed electrochemical immunosensor could be advantageously extended for multiplexed detection of other agents of environmental pollution.

关键词： Electrochemical immunosensor Polyaniline Graphene Atrazine

Understanding bike trip patterns leveraging bike sharing system open data

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Frontiers of Computer Science 2017年第1期11卷 38-48页

作者： Longbiao CHEN Xiaojuan MA thi-mai-Trang nguyen Gang PAN Jeremie JAKUBOWICZ Institut Mines-Telecom Telecom SudParis UMR CNRS Samovar Evry 91000 France Laboratoire d'Informatique de Paris 6 (LIP6) University of Paris 6 Paris 75005 France College of Computer Science Zhejiang University Hangzhou 310027 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China

Bike sharing systems are booming globally as a green and flexible transportation mode, but the flexibility also brings difficulties in keeping the bike stations balanced with enough bikes and docks. Understanding the spatio-temporal bike trip patterns in a bike sharing system, such as the popular trip origins and destinations during rush hours, is important for researchers to design models for bike scheduling and sta- tion management. However, due to privacy and operational concerns, bike trip data are usually not publicly available in many cities. Instead, the station feeds about real-time bike and dock number in stations are usually public, which we refer to as bike sharing system open data. In this paper, we propose an approach to infer the spatio-temporal bike trip patterns from the public station feeds. Since the number of possible trips （i.e., origin-destination station pairs） is much larger than the number of stations, we define the trip infer- ence as an ill-posed inverse problem. To solve this problem, we identify the sparsity and locality properties of bike trip patterns, and propose a sparse and weighted regularization model to impose both properties in the solution. We evaluate our method using real-world data from Washington, D.C. and New York City. Results show that our method can effectively infer the spatio-temporal bike trip patterns and outperform the baselines in both cities.

关键词： bike sharing system open data ill-posed inverse problems urban computing

Optimization Agricultural Supply Chain:A Case Study of Fertilizer Supplier Selection

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Computers, Materials & Continua 2022年第8期72卷 4057-4068页

作者： nguyen Van thanh nguyen thi Kim Lan Syed Tam Husain nguyen Hoang Hai nguyen Viet Tinh Faculty of Commerce Van Lang UniversityHo Chi Minh CityVietnam International Education Institute Van Lang UniversityHo Chi Minh CityVietnam

The 21st century is associated with the IndustrialRevolution 4.0 and the organic agriculture trend,making the utilization of high-quality fertilizers,abundant nutritional content,economical,and no affect to environment *** to the new concept,clean agricultural production and organic agricultural products are not allowed to excessively use synthetic chemicals such as chemical fertilizers,and plant protection drugs,but priority is to use manure,organic fertilizers,and natural mineral *** must meet the balanced nutritional requirements of crops,maintain,and improve the fertility of the ground,protect the surrounding ecosystem,and leave harmful effects in agricultural products,products with high quality,safe for users and high economic efficiency for *** achieve the above goal,the selection of a fertilizer supplier is an important decision,supporting the supply chain’s sustainable development,fertilizer supplier selection is a multicriteria decision making model,the decision maker must assess all qualitative and quantitative *** this paper,the author proposed an integer decision making model including Fuzzy Analytic Hierarchy Process(FAHP)and Complex Proportional Assessment of Alternatives(COPRAS)for fertilizer supplier *** weightings of the criteria are calculated by using FAHP,COPRAS is then applied for ranking some potential fertilizer *** efficiency of the proposed models is proved by a case study conducted in a farm located in the south of *** research is the first fertilizer supplier evaluation and se-lection model in Vietnam by interviewing experts and reviewing the ***-search result is to provide a case study on evaluating supplier in agricultural supply chain utilizing the model proposed by the combination of FAHP and COPRAS models.

关键词： Fertilizer industry optimization model fuzzy theory agricultural supply chain

Luminescent and magnetic properties of multifunctional europium(Ⅲ) complex based nanocomposite

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Journal of Rare Earths 2019年第11期37卷 1237-1241页

作者： Hoang thi Khuyen nguyen thanh Huong Tran Thu Huong Pham thi Lien Do thi Anh Thu nguyen thi Anh Huong Wieslaw Strek Le Quoc Minh Institute of Materials Science Vietnam Academy of Science and Technology18 Hoang Quoc VietCau CiayHanoiViet Nam Graduate University of Science and Technology Vietnam Academy of Science and Technology18 Hoang Quoc VietCau GiayHanoiViet Nam Department of Chemistry University of Natural SciencesHanoi National University19 Le Thanh TongHoan KiemHanoiViet Nam Institute of Low Temperature and Structure Research PASOkolna 2Wroclaw 50-422Poland Duy Tan University K7/25 Quang TrungDa DangViet Nam

The luminescent rare earth(RE)complex based multifunctional nanocomposites offer new potential applications of multimodal imaging(magnetic resonance imaging(MRI),fluorescent bioimaging,etc.)that can be associated with therapeutic *** this study,we report some results obtained with novel multifunctional Fe3O4/Si-amine/Eu(NTA)3 nanocomposites that are composed of europium(Ⅲ)complex with 1-(2-naphthoyl)-3,3,3-trifluoroacetone ligands(NTA)(Eu(NTA)3)and superparamagnetic Fe3O4 *** nanocomposites were functionalized with an amine group for biomedicine *** multifunctional Fe3O4/Si-amine/Eu(NTA)3 nanocomposites exhibit both good magnetic behavior of Fe3O4 nanoparticles as a core and strong fluorescent property of europium(Ⅲ)*** characterizations were analyzed by XRD,SEM,EDX and FTIR *** optical properties were studied in detail by UV-VIS spectra and luminescent emission *** magnetic property was estimated by *** effect of concentrations of luminescent Eu(NTA)3 complex on luminescent and magnetic properties is discussed.

关键词： Multifunctional nanocomposite Luminescence Magnetic Europium(Ⅲ)complex Fe3O4 Rare earths

Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

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结构与土木工程前沿:英文版 2023年第2期17卷 284-305页

作者： Hai-Van thi mai May Huu nguyen Son Hoang TRINH Hai-Bang LY Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

Fiber-reinforced self-compacting concrete(FRSCC)is a typical construction material,and its compressive strength(CS)is a critical mechanical property that must be adequately *** the machine learning(ML)approach to estimating the CS of FRSCC,the current research gaps include the limitations of samples in databases,the applicability constraints of models owing to limited mixture components,and the possibility of applying recently proposed *** study developed different ML models for predicting the CS of FRSCC to address these *** neural network,random forest,and categorical gradient boosting(CatBoost)models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique.A database of 381 samples was created,representing the most significant FRSCC dataset compared with previous studies,and it was used for model *** findings indicated that CatBoost outperformed the other two models with excellent predictive abilities(root mean square error of 2.639 MPa,mean absolute error of 1.669 MPa,and coefficient of determination of 0.986 for the test dataset).Finally,a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of *** results showed that the cement content,testing age,and superplasticizer content are the most critical factors affecting the CS.

关键词： compressive strength self-compacting concrete artificial neural network decision tree CatBoost

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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Frontiers of Structural and Civil Engineering 2022年第7期16卷 928-945页

作者： Van Quan TRAN Hai-Van thi mai Thuy-Anh nguyen Hai-Bang LY Faculty of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

The compressive strength of self-compacting concrete(SCC)needs to be determined during the construction design *** paper shows that the compressive strength of SCC(CS of SCC)can be successfully predicted from mix design and curing age by a machine learning(ML)technique named the Extreme Gradient Boosting(XGB)algorithm,including non-hybrid and hybrid *** ML techniques,such as Linear regression(LR),K-Nearest Neighbors(KNN),Support Vector Machine(SVM),Decision Trees(DTR),Random Forest(RF),Gradient Boosting(GB),and Artificial Neural Network using two training algorithms LBFGS and SGD(denoted as ANN_LBFGS and ANN_SGD),are also compared with the XGB ***,the hybrid models of eight ML techniques and Particle Swarm Optimization(PSO)are constructed to highlight the reliability and accuracy of SCC compressive strength prediction by the XGB_PSO hybrid *** highest number of SCC samples available in the literature is collected for building the ML *** with previously published works’performance,the proposed XGB method,both hybrid and non-hybrid models,is the most reliable and robust of the examined techniques,and is more accurate than existing ML methods(R2=0.9644,RMSE=4.7801,and MAE=3.4832).Therefore,the XGB model can be used as a practical tool for engineers in predicting the CS of SCC.

关键词： compressive strength self-compacting concrete machine learning techniques particle swarm optimization extreme gradient boosting

Ardisia gigantifolia ethanolic extract inhibits cell proliferation and targets cancer stem cells in gastric cancer

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Asian Pacific Journal of Tropical Biomedicine 2023年第6期13卷 258-267页

作者： thi thanh Huong Le Phu Hung nguyen Van Phuong nguyen Thy Ngoc nguyen Faculty of Biotechnology TNU-University of SciencesThai NguyenVietnam Department of Life Science University of Science and Technology of HanoiVietnam Academy of Science and TechnologyHanoiVietnam

Objective:To evaluate the effects of ethanol extract from Ardisia gigantifolia leaves on cell proliferation and cancer stem cell(CSC)number in gastric ***:The inhibitory effect of Ardisia gigantifolia extract on the proliferation of MKN45 and MKN74 gastric cancer cells was assessed using 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazolium bromide ***-adherent culture(3D)model was used to evaluate the effect of the extract on tumorsphere size and ***,the expression of CD44,ALDH,and p21 was determined by immunofluorescence *** cytometric analysis was performed to evaluate cell cycle arrest and the expression of gastric CSC markers CD44 and ***-time PCR analysis was also carried out to assess the effect of the extract on the expression of cell cycle-regulated ***:Ardisia gigantifolia extract effectively inhibited cell proliferation with an IC_(50)of 55.7μg/m L in MKN45 cells and 123.6μg/m L in MKN74 *** extract also arrested cell cycle in the G_(0)/G_(1)phase as well as significantly reduced the size and number of *** markedly increased expression of p21 was observed at both m RNA and protein levels in the extract-treated adherent cells and *** addition,Ardisia gigantifolia extract significantly reduced the number of CD44-and/or ALDH-expressing gastric ***:The development of gastric CSC can be inhibited by the ethanol extract of Ardisia gigantifolia.

关键词： Ardisia gigantifolia Gastric cancer Cancer stem cell markers CD44 ALDH

Polygonatum kingianum rhizome extract alleviates collagen antibody-induced arthritis by modulating proinflammatory cytokine production in mice

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Asian Pacific Journal of Tropical Biomedicine 2020年第11期10卷 490-495页

作者： Huyen Do thi thanh Phuong Ngo thi Hien nguyen thi Thu Nga nguyen thi Hung Le Ngoc Thao Dothi Ha Le Minh Graduate University of Science and Technology Vietnam Academy of Science and Technology18 Hoang Quoc VietNghia DoCau GiayHanoiVietnam Institute of Natural Products Chemistry Vietnam Academy of Science and Technology18 Hoang Quoc VietNghia DoCau GiayHanoiVietnam Hanoi Open University101 nguyen Hien str Hai Ba Trung Dist.HanoiVietnam Laboratory of Bioassay Institute of BiotechnologyVietnam Academy of Science and Technology18 Hoang Quoc VietNghia DoCau GiayHanoiVietnam Chemistry Lab Project Center for Research and Technology transferVietnam Academy of Science and Technology18 Hoang Quoc VietNghia DoCau GiayHanoiVietnam

Objective: To evaluate the anti-arthritic effects of Polygonatum kingianum rhizome extract using both in vitro and in vivo ***: Lipopolysaccharide-induced RAW 264.7 macrophages were treated with an ethanol extract of Polygonatum kingianum rhizomes at different concentrations to determine nitric oxide and prostaglandin E2(PGE2) production. For in vivo study, Polygonatum kingianum ethanol extract was further investigated for its antiinflammatory effect in a mouse model with collagen antibodyinduced arthritis. Phytochemical study of Polygonatum kingianum ethanol extract was also ***: Saponins(142 mg/g total yield) was the main component in the Polygonatum kingianum ethanol extract. 5α,8α-ergosterol peroxide,(E,E)-9-oxooctadeca-10,12-dienoic acid and 3-(2?-hydroxy-4?-methoxy-benzyl)-5,7-dihydroxy-8-methyl-chroman-4-one were isolated from the extract. Polygonatum kingianum ethanol extract exhibited potential anti-inflammatory effects by inhibiting nitric oxide and PGE2 production in RAW 264.7 cells in a dosedependent manner. The level of arthritis in mice with collagen antibody-induced arthritis was significantly reduced(Pmain component, and sterols(daucosterol and 5α,8α-ergosterol peroxide) from Polygonatum kingianum ethanol extract may contribute to its promising in vitro and in vivo anti-inflammatory activities.

关键词： inflammatory cytokine PGE2