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In vitro and in silico studies of salicylic acid on systemic induced resistance against bacterial leaf blight disease and enhancement of crop yield

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Journal of Integrative Agriculture 2023年第1期22卷 170-184页

作者： Wannaporn THEPBANDIT Narendra Kumar PAPATHOTI Jayasimha Rayulu DADDAM Nguyen Huy HOANG toan le thanh Chanon SAENGCHAN Kumrai BUENSANTEAI School of Crop Production Technology Suranaree University of TechnologyNakhon Ratchasima 30000Thailand Department of Animal Science Agriculture Research OrganizationRishon Lezion 7505101Israel Department of Plant Protection Can Tho UniversityCan Tho 900000Vietnam

Salicylic acid(SA)is an effective elicitor to promote plant defenses and *** study aimed to investigate rice(Oryza sativa L.)*** Dawk Mali 105 treated with salicylic acid(SA)-Ricemate as an enhanced plant protection mechanism against bacterial leaf blight(BLB)disease caused by Xanthomonas oryzae ***(Xoo).Results indicated that the use of SA-Ricemate as a foliar spray at concentrations of more than 100 mg L^(-1)can reduce the severity of BLB disease by 71%.SA-Ricemate treatment also increased the hydrogen peroxide(H_(2)O_(2))content of rice leaf tissues over untreated samples by 39–61%.Malondialdehyde(MDA)in rice leaves treated with SA-Ricemate also showed an increase of 50–65%when comparing to non-treated *** differential development of these defense compounds was faster and distinct when the SA-Ricemate-treated rice was infected with Xoo,indicating plant-induced ***,SA-Ricemate elicitor at a concentration of 50–250 mg L^(-1)was correlated with a substantial increase in the accumulation of total chlorophyll content at 2.53–2.73 mg g^(-1)of fresh weight which suggests that plant growth is activated by *** catalase-and aldehyde dehydrogenase-binding sites were searched for using the CASTp server,and the findings were compared to the *** was used to design and optimize SA,which was then docked to the catalase and aldehyde dehydrogenase-binding domains of the enzymes using the GOLD 3.0.1 *** is shown in several docked conformations with the enzymes catalase and aldehyde *** three catalase amino acids(GLN7,VAL27,and GLU38)were discovered to be involved in the creation of a strong hydrogen bond with SA when SA was *** this mechanism,the aldehyde dehydrogenase amino acids LYS5,HIS6,and ASP2 were all implicated,and these amino acids created strong hydrogen bonds with *** field conditions,SA-Ricemate significantly reduced disease severity by 78%and the total grain yield was si

关键词： bacterial leaf blight crop yield in vitro in silico rice defense salicylic acid

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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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Dynamic response of honeycomb-FGS shells subjected to the dynamic loading using non-polynomial higher-order IGA

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Defence Technology（防务技术） 2024年第7期37卷 149-161页

作者： Pham Binh le Trung-thanh Tran Faculty of Mechanical Engineering Le Quy Don Technical UniversityHanoiViet Nam

The main goal of this study is to use higher-order isogeometric analysis(IGA)to study the dynamic response of sandwich shells with an auxetic honeycomb core and two different functionally graded materials(FGM)skin layers(namely honeycomb-FGS shells)subjected to dynamic ***'s non-polynomial higher-order shear deformation theory(HSDT)is used due to its simplicity and *** governing equation is derived from Hamilton's *** verifying the present approach,the effect of input parameters on the dynamic response of honeycomb-FGS shells is carried out in detail.

关键词： IGA Elastic foundation Dynamic response FGM Auxetic honeycomb Shell

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An efficient improved Gradient Boosting for strain prediction in Near-Surface Mounted fiber-reinforced polymer strengthened reinforced concrete beam

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1148-1168页

作者： Abdelwahhab KHATIR Roberto CAPOZUCCA Samir KHATIR Erica MAGAGNINI Brahim BENAISSA thanh CUONG-le Structural Section DICEA Polytechnic University of MarcheAncona 60131Italy Centre for Engineering Application&Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh City 70000Vietnam Design Engineering Laboratory Toyota Technological InstituteNagoya 468-8511Japan

The Near-Surface Mounted(NSM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent *** the past two decades,researchers have extensively studied its potential,advantages,and applications,as well as related parameters,aiming at optimization of construction ***,there is still a need to explore further,both from a static perspective,which involves accounting for the nonconservation of the contact section resulting from the bond-slip effect between fiber-reinforced polymer(FRP)rods and resin and is typically neglected by existing analytical models,as well as from a dynamic standpoint,which involves studying the trends of vibration frequencies to understand the effects of various forms of damage and the efficiency of *** address this gap in knowledge,this research involves static and dynamic tests on simply supported reinforced concrete(RC)beams using rods of NSM carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP).The main objective is to examine the effects of various strengthening *** research conducts bending tests with loading cycles until failure,and it helps to define the behavior of beam specimens under various damage degrees,including concrete *** analysis by free vibration testing enables tracking of the effectiveness of the reinforcement at various damage levels at each stage of the loading *** addition,application of Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)is proposed to optimize Gradient Boosting(GB)training performance for concrete strain prediction in NSM-FRP *** GB using Particle Swarm Optimization(GBPSO)and GB using Genetic Algorithm(GBGA)systems were trained using an experimental data set,where the input data was a static applied load and the output data was the consequent *** models of GBPSO and GBGA have been shown to provide highly accurate results for predicting *** model

关键词： NSM technique fiber-reinforced polymer rods static and dynamic analysis GB PSO GA finite element analysis

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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;Plescents(OR 1.24,95%CI 1.12-1.37;Ple 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

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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

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Predicting 3D Radiotherapy Dose-Volume Based on Deep learning

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Intelligent Automation & Soft Computing 2024年第2期39卷 319-335页

作者： Do Nang toan Lam thanh Hien Ha Manh toan Nguyen Trong Vinh Pham Trung Hieu Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi10072Vietnam Faculty of Information Technology Lac Hong UniversityBien HoaDong Nai76120Vietnam

Cancer is one of the most dangerous diseaseswith *** of the principal treatments is radiotherapy by using radiation beams to destroy cancer cells and this workflow requires a lot of experience and skill from doctors and *** our study,we focused on the 3D dose prediction problem in radiotherapy by applying the deeplearning approach to computed tomography(CT)images of cancer *** image data has more complex characteristics than normal image data,and this research aims to explore the effectiveness of data preprocessing and augmentation in the context of the 3D dose prediction *** proposed four strategies to clarify our hypothesis in different aspects of applying data preprocessing and *** strategies,we trained our custom convolutional neural network model which has a structure inspired by the U-net,and residual blocks were also applied to the *** output of the network is added with a rectified linear unit(Re-Lu)function for each pixel to ensure there are no negative values,which are absurd with radiation *** experiments were conducted on the dataset of the Open Knowledge-Based Planning Challenge which was collected from head and neck cancer patients treatedwith radiation *** results of four strategies showthat our hypothesis is rational by evaluating metrics in terms of the Dose-score and the Dose-volume histogram score(DVH-score).In the best training cases,the Dose-score is 3.08 and the DVH-score is *** addition,we also conducted a comparison with the results of another study in the same context of using the loss function.

关键词： CT image 3D dose prediction data preprocessing augmentation

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Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset

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Intelligent Automation & Soft Computing 2024年第2期39卷 281-299页

作者： Nguyen Trong Vinh Lam thanh Hien Ha Manh toan Ngo Duc Vinh Do Nang toan Faculty of Information Technology Lac Hong UniversityBien HoaDong Nai76120Vietnam Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi10072Vietnam Faculty of Information Technology Hanoi University of IndustryHanoi11915Vietnam

Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse ***,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very *** late detection of tuberculosis could lead to danger to patient health,even *** one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long *** demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis *** our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese *** chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning *** paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image *** detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a *** prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this *** support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network *** experiment results were evaluated regarding sensitivity,specificity,and *** achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over *** on the X-ray image classification result,we visualize pr

关键词： Tuberculosis classification Vietnamese chest X-ray deep learning

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Dry eye rate and its relationship with disease stage in patients with primary hypertension:a cross-sectional study in Vietnam

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International Journal of Ophthalmology(English edition) 2024年第4期17卷 653-658页

作者： Tran Tat Thang Pham Hong Phuong Nguyen Sa Huynh Nguyen Trung Kien NguyenDuy toan Nguyen Thi Thu Ha le Ha Khoa Nguyen Huu Dung Thai Doan Thang le Viet Thang Nghe An Eye Hospital Nghe An 43000Vietnam Nghe An Friendship General Hospital Nghe An 43000Vietnam Military Hospital 103 Ha Noi 100000Vietnam Vietnam Military Medical University Ha Noi 100000Vietnam Hanoi Medical University Ha Noi 100000Vietnam Bạch Mai Hospital Ha Noi 100000Vietnam TTH Vinh General Hospital Nghe An 100000Vietnam

AIM:To determine the dry eye(DE)rate and its relationship with disease stage in patients with primary ***:A cross-sectional study included 432 patients with primary hypertension(with an equal number of patients in each group:144 in stage Ⅰ,Ⅱ,and Ⅲ hypertension)and 144 healthy subjects as a control *** Ocular Surface Disease Index(OSDI)and Schirmer Ⅰ test without anesthetics were conducted on all 576 *** with OSDI scoreslevels in hypertension patients with DE were higher than those without DE,Plevated plasma creatinine,and CRP-hs levels were independent factors associated with DE in primary hypertension patients,Plevated plasma CRP-hs,and creatinine levels in patients with primary hypertension.

关键词： primary hypertension dry eye stage of hypertension plasma creatinine

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Random vibration analysis of FGM plates subjected to moving load using a refined stochastic finite element method

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Defence Technology（防务技术） 2024年第4期34卷 42-56页

作者： Ngoc-Tu Do Trung thanh Tran Faculty of Mechanical Engineering Hanoi University of IndustryHanoiViet Nam Faculty of Mechanical Engineering Le Quy Don Technical UniversityHanoiViet Nam

The article introduces a finite element procedure using the bilinear quadrilateral element or four-node rectangular element(namely Q4 element) based on a refined first-order shear deformation theory(rFSDT) and Monte Carlo simulation(MCS), so-called refined stochastic finite element method to investigate the random vibration of functionally graded material(FGM) plates subjected to the moving *** advantage of the proposed method is to use r-FSDT to improve the accuracy of classical FSDT, satisfy the stress-free condition at the plate boundaries, and combine with MCS to analyze the vibration of the FGM plate when the parameter inputs are random quantities following a normal distribution. The obtained results show that the distribution characteristics of the vibration response of the FGM plate depend on the standard deviation of the input parameters and the velocity of the moving ***, the numerical results in this study are expected to contribute to improving the understanding of FGM plates subjected to moving loads with uncertain input parameters.

关键词： FGM Moving load R-FSDT Q4 element Monte Carlo simulation Random vibration

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