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Journal of Renewable Materials 2021年第8期9卷 1393-1411页

作者： nguyen Thi thanh Thuy Le Hoang Huy Truong Thuy Vy nguyen Thi thanh tam Bien ThiLan thanh nguyen Thi My Lan Nong Lam University Ho Chi Minh City Ho Chi Minh City700000Vietnam Industrial University of Ho Chi Minh City Ho Chi Minh City700000Vietnam University of Science Viet Nam National University Ho Chi Minh CityHo Chi Minh City700000Vietnam

In the present study,the biogenic silver nanoparticles have been synthesized using aqueous leaf extract of Plectranthus amboinicus(PA),which acted as both reducing and stabilizing *** PA synthesized silver nanoparticles were blended with carboxymethyl cellulose/polyvinyl alcohol(CMC/PVA)*** prepared AgNPs as well as the biogenic AgNPs incorporated CMC/PVA films were investigated using UV-visible spectrophotometry,Fourier-transform infrared spectroscopy(FT-IR),dynamic light scattering(DLS),scanning electron microscope(SEM),and X–ray diffraction(XRD).The DLS results showed that biogenic AgNPs had the average particle size of 65.70 nm with polydispersity index of *** surface plasmon resonance of AgNPs,which was determined by UV-vis spectrophotometry,showed the value of 410.00 *** results therefore confirmed the reduction Ag+into Ag°and the formation of AgNPs in the *** SEM imaging showed that AgNPs was quasi-spherical and *** XRD peaks at 33.07°,44.19°,64.58°and 77.47°confirmed the crystalline nature and presence of *** CMC/PVA films that incorporated with AgNPs displayed best mechanical strength and morphological properties than the pure CMC/PVA *** film of CMC/PVA-AgNPs exhibited significant antibacterial activities against Bacillus spizizenii,Staphylococcus aureus,Salmonella typhi and Escherichia Coli.

关键词： Carboxymethyl cellulose antibacterial green synthesis silver nanoparticles plectranthus amboinicus polyvinyl alcohol

In vivo anticancer activity of maesopsin 4—O— β—glucoside isolated from leaves of Artocarpus tonkinensis *** Gagnep

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Asian Pacific Journal of Tropical Medicine 2016年第4期9卷 343-348页

作者： Trinh Thi Thuy Dao Duc Thien Tran Quang Hung nguyen thanh tam nguyen Thi Hoang Anh nguyen Thi Nga nguyen Thi Cuc Le Phuong Mai Tran Van Sung Domenico V.Delfino Do Thi Thao Institute of Chemistry.Vietnam Academy of Science and Technology Institute of Biotechnology Vietnam Academy of Science and Technology National Research Council Canada Measurement Science and Standards1200 Montreal RoadBuilding M-12.Ottatca.Ontario KIA OR6 Department of Medicine University of PerugiaPiazzale Gambuli.S.Andrea delle Fratte

Objective:To investigate the antitumor effect of maesopsin 4-O-β-glucoside(TAT2) isolated from the leaves of Artocarpus tonkinensis(***) *** ***:The antitumor activity of TAT2 was evaluated in Lewis lung carcinoma(LLC) tumor-bearing ***/c mice had tumors induced by implantation with 2× 10~6 LLC cells into the subcutaneous right posterior ***-bearing mice were treated orally with a range of doses of TAT2 and a standard drug,*** were observed for tumor growth and mortality *** was collected to determine hematological and biochemical *** TAT2 was isolated from an ethanolic extract of *** *** structure was determined by MS and NMR spectroscopy,and identified as *** compound did not show acute toxicity at the highest dose tested(2 OIK) mg/kg body weight).TAT2 exhibited antitumor activity by decreasing tumor growth,increasing the survival rale,and ameliorating some hematological and biochemical parameters at doses of 100 and 200 mg/kg body weight(P<0.05).Conclusions:These results indicate that TAT2 possesses clear antitumor *** to its bioavailability and low toxicity,and the fact that it could be isolated in a large scale from *** leaves,the compound shows promise as a potential anticancer drug.

关键词： Artocarpus tonkinensis BALB/c Hematological parameters Lewis lung carcinoma Maesopsin 4-0-β-glucoside

20-Hydroxyecdysone from Dacrycarpus imbricatus bark inhibits the proliferation of acute myeloid leukemia cells

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Asian Pacific Journal of Tropical Medicine 2017年第2期10卷 151-153页

作者： Trinh Thi Thuy nguyen thanh tam nguyen Thi Hoang Anh Dang Viet Hau Dinh Thi Phong Le Quoc Thang Sabrina Adorisio Tran Van Sung Domenico V Delfino Institute of Chemistry Vietnam Academy of Science and Technology Vietnam National Museum of Nature Vietnam Academy of Science and Technology Hue University’s College of Educations Section of Pharmacology Department of MedicineUniversity of Perugia

Objective:To investigate the anti-proliferative effects of 20-hydroxyecdysone isolated from the bark of Dacrycarpus imbricatus(Blume) de ***:Column chromatography was used for isolation of compounds from plant *** structure of the isolated compound was identified by mass spectrometry and nuclear magnetic resonance techniques,including HSQC,HMBC,NOE-difference *** isolated compound was tested for its anti-proliferative activity in acute myeloid leukemia(AML) and OCI-AML ***:Compound 1 was isolated from the ethyl acetate fraction of Dacrycarpus imbricatus barks by column *** chemical structure was identified as 20-hydroxyecdysone(20HE),a cholestane-type ecdysteroid,by a combination of mass spectrometry and nuclear magnetic resonance spectrometric *** goal was to test the anti-proliferative activity of 20 HE using the OCI-AML cell line.20 HE significantly decreased OCI cell number at a concentration of 1 mg/mL,whereas lower concentrations were ***,this decrease was due to partial blockage of the G_1/S phase of the cell cycle,with a reduction of cells in the G_2M phase,not due to increased ***:This indicates that 20 HE significantly decreases the number of cells in the G_1/S phase of the cell cycle in human AML *** is the first time that the anti-proliferative activity of 20 HE against a human tumor cell line has been reported.

关键词： Dacrycarpus imbricatus Ecdysteroid 20-hydroxyecdysone Proliferation Acute myeloid leukemia

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

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Computers, Materials & Continua 2024年第2期78卷 2181-2205页

作者： thanh-Lam nguyen HaoKao thanh-Tuan nguyen Mong-Fong Horng Chin-Shiuh Shieh Department of Electronic Engineering National Kaohsiung University of Science and TechnologyKaohsiung807618Taiwan Department of Electronic and Automation Engineering Nha Trang UniversityNha Trang650000Vietnam

Since its inception,the Internet has been rapidly *** the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the *** applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the ***,malicious threats on the internet are on the rise as *** Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet *** scale and complexity of DDoS attacks are constantly *** Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those *** addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant ***,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown *** attacks,which are not encountered during the system’s training,can lead to misclassification with significant *** this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional *** proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)***,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)*** success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering *** has yielded a novel method in the field of unknown attack *** further expands the trend of applying DL and M

关键词： Cybersecurity DDoS unknown attack detection machine learning deep learning incremental learning convolutional neural networks(CNN) open-set recognition(OSR) spatial location constraint prototype loss fuzzy c-means CICIDS2017 CICDDoS2019

GLOBAL BOUND ON THE GRADIENT OF SOLUTIONS TO p-LAPLACE TYPE EQUATIONS WITH MIXED DATA

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Acta Mathematica Scientia 2024年第4期44卷 1394-1414页

作者： Minh-Phuong TRAN The-Quang TRAN thanh-Nhan nguyen Applied Analysis Research Group Faculty of Mathematics and StatisticsTon Duc Thang UniversityHo Chi Minh CityVietnam nguyen Huu Huan High School Thu Duc CityVietnam Group of Analysis and Applied Mathematics Department of MathematicsHo Chi Minh City University of EducationVietnam

In this paper,the study of gradient regularity for solutions of a class of elliptic problems of p-Laplace type is *** particular,we prove a global result concerning Lorentz-Morrey regularity of the non-homogeneous boundary data problem:-div((s^(2)+|▽u|^(2)p-2/2)▽u)=-div(|f|^(p-2)f)+g inΩ,u=h in■Ω,with the(sub-elliptic)degeneracy condition s∈[0,1]and with mixed data f∈L^(p)(Q;R^(n)),g∈Lp/(p-1)(Ω;R^(n))for p∈(1,n).This problem naturally arises in various applications such as dynamics of non-Newtonian fluid theory,electro-rheology,radiation of heat,plastic moulding and many *** on the idea of level-set inequality on fractional maximal distribution functions,it enables us to carry out a global regularity result of the solution via fractional maximal *** to the significance of M_(α)and its relation with Riesz potential,estimates via fractional maximal functions allow us to bound oscillations not only for solution but also its fractional derivatives of orderα.Our approach therefore has its own interest.

关键词： gradient estimates p-Laplace quasilinear elliptic equation fractional maximal operators Lorentz-Morrey spaces

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

Prevalence and risk factors associated with long COVID symptoms in children and adolescents in a southern province of Vietnam

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Asian Pacific Journal of Tropical Medicine 2024年第3期17卷 119-128,I0001,I0002页

作者： Huynh Ngoc Linh nguyen The Tan Le Thi Minh Thu nguyen Tu Loan nguyen Thi To Uyen Le thanh Thao Trang Truong thanh Nam Doan Hoang Phu Faculty of Medicine Ca Mau Medical CollegeCa Mau 98000Vietnam Ca Mau Obstetrics and Pediatrics Hospital Ca Mau 98000Vietnam Faculty of Basic Science and Public Health Dong Thap Medical CollegeDong Thap 81000Vietnam Graduate University of Sciences and Technology Vietnam Academy of Science and TechnologyHa Noi 10000Vietnam Community Public Health Research Program School of Public HealthWalailak UniversityNakhon Si Thammarat 80160Thailand Faculty Public Health Can Tho University of Medicine and PharmacyCan Tho City 94000Vietnam Doctoral Program in Health Sciences College of Graduate StudiesWalailak UniversityNakhon Si Thammarat 80160Thailand

Objective:To investigate the prevalence and risk factors associated with long COVID symptoms among children and adolescents who have recovered from ***:This study applied a cross-sectional approach within community settings in a southern province of Vietnam.A structured questionnaire featuring socio-demographic information and common long COVID symptoms was *** correlation coefficients assessed associations among pairs of long COVID ***,multivariable logistic regression models were performed to investigate the risk factors of long COVID in recovered COVID-19 children and ***:Among 422 participants,39.3%reported long COVID symptoms,with a prevalence of 45.2%(SD=0.5)in children and 22.2%(SD=0.4)in *** symptoms reported were cough 34.6%(SD=0.5),fatigue 20.6%(SD=0.4),shortness of breath 10.9%(SD=0.3),and lack of appetite 6.6%(SD=0.3).Concerning risk factors of long COVID,a higher risk was observed among demographic groups,including girls(OR 1.25,95%CI 1.15-1.37;P<0.001,reference:boys),children compared to adolescents(OR 1.24,95%CI 1.12-1.37;P<0.001),overweight individuals(OR 1.14,95%CI 1.02-1.27;P=0.018,reference:healthy weight),and participants without any COVID-19 vaccination(OR 1.36,95%CI 1.20-1.54;P<0.001),or have received only one single dose(OR 1.35,95%CI 1.10-1.64;P=0.004)compared to those who have received two ***,patients with a COVID-19 treatment duration exceeding two weeks also had a higher risk of long COVID(OR 1.32,95%CI 1.09-1.60;P=0.003)than those who recovered less than seven ***:The insights from this study provide crucial guidance for predicting the factors associated with the occurrence of long COVID in pediatric patients,contributing to strategic interventions aimed at mitigating the long COVID risks among children and adolescents in Vietnam.

关键词： Long COVID Prevalence Risk factors Children Adolescent Vietnam

Tungsten-based nanocatalysts with different structures for visible light responsive photocatalytic degradation of bisphenol A

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Journal of Environmental Sciences 2024年第5期139卷 569-588页

作者： Hai Bang Truong Thi Thu Loan Doan nguyen Tien Hoang nguyen Van tam Minh Kim nguyen Le Gia Trung Jin Seog Gwag nguyen Tien Tran Optical Materials Research Group Science and Technology Advanced InstituteVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Applied Technology School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam The University of Da Nang University of Science and Technology54 Nguyen Luong BangDa NangViet Nam The University of Da Nang University of Science and Education459 Ton Duc Thang St.Lien ChieuDa Nang 550000Viet Nam Institute of Veterinary Science and Technology 31ha zoneTrau QuyGia LamHa Noi 12400Viet Nam Department of Physics Yeungnam UniversityGyeongsanGyeongbuk 38541Republic of Korea Center for Advanced Chemistry Institute of Research and DevelopmentDuy Tan University03 Quang TrungDa Nang 550000Viet Nam Faculty of Natural Sciences Duy Tan University03 Quang TrungDa Nang 550000Viet Nam

Environmental pollution,such as water contamination,is a critical issue that must be absolutely ***,three different morphologies of tungsten-based photocatalysts(WO_(3)nanorods,WO_(3)/WS_(2)nanobricks,WO_(3)/WS_(2)nanorods)are made using a simple hydrothermal method by changing the solvents(H_(2)O,DMF,aqueous HCl solution).The as-prepared nanocatalysts have excellent thermal stability,large porosity,and high *** results show all materials have good photocatalytic activity in aqueous media,with WO_(3)/WS_(2)nanorods(NRs)having the best activity in the photodegradation of bisphenol A(BPA)under visible-light *** may originate from increased migration of charge carriers and effective prevention of electron–hole recombination in WO_(3)/WS_(2)NRs,whereby this photocatalyst is able to generate more reactive·OH and·O_(2)^(–)species,leading to greater photocatalytic *** 99.6% of BPA is photodegraded within 60 min when using 1.5 g/L WO_(3)/WS_(2)NRs and 5.0 mg/L BPA at pH ***,the optimal conditions(pH,catalyst dosage,initial BPA concentration)for WO_(3)/WS_(2)NRs are also elaborately *** rod-like heterostructures are expressed as potential catalysts with excellent photostability,efficient reusability,and highly active effectivity in different types of *** particular,the removal efficiency of BPA by WO_(3)/WS_(2)NRs reduces by only 1.5% after five recycling runs and even reaches 89.1%in contaminated lake *** study provides promising insights for the nearly complete removal of BPA from wastewater or different water resources,which is advantageous to various applications in environmental remediation.

关键词： Photodegradation Bisphenol A Tungsten-based nanocatalyst Structure Nanorod

Some Mean Convergence Theorems for the Maximum of Normed Double Sums of Banach Space Valued Random Elements

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Acta Mathematica Sinica,English Series 2024年第7期40卷 1727-1740页

作者： Andrew ROSALSKY Le Van thanh nguyen Thi THUY Department of Statistics University of FloridaGainesvilleFL 32611-8545USA Department of Mathematics Vinh UniversityVinhNghe AnViet Nam High School for Gifted Students Vinh UniversityVinhNghe AnViet Nam

In this correspondence,we establish mean convergence theorems for the maximum of normed double sums of Banach space valued random *** of the results pertain to random elements which are *** expand and improve a number of particular cases in the literature on mean convergence of random elements in Banach *** of the main contributions of the paper is to simplify and improve a recent result of Li,Presnell,and Rosalsky[Journal of Mathematical Inequalities,16,117–126(2022)].A new maximal inequality for double sums of M-dependent random elements is proved which may be of independent *** sharpness of the results is illustrated by four examples.

关键词： Double sum mean convergence Rademacher type p Banach space Banach space valued random element M-dependent random elements

A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil Engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY tam T TRUONG Chanachai THONGCHOM T.nguyen-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data