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Establishing the Basic Indicator for the Calculation of the Flood vulnerability Index for River Basins in Vietnam

Journal of Environmental Science and Engineering(B) 2016年第8期5卷 390-394页

作者： Can Thu Van Nguyen Thanh Son phan vu hoang phuong Hydrology Department Faculty of Hydro-Meteorology Hochiminh City University of Natural Resources and Environment Hochiminh City 70000 Vietnam Faculty of Hydro-meteorology & Oceanography Hanoi University of Science Hanoi 100000 Vietnam Climate Change Department Faculty of Hydro-Meteorology Hochiminh City University of Natural Resources and EnvironmentHochiminh City 70000 Vietnam

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Stem cell-based therapy for human diseases

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Signal Transduction and Targeted Therapy 2022年第9期7卷 3242-3282页

作者： Duc M.hoang phuong T.Pham Trung Q.Bach Anh T.L.Ngo Quyen T.Nguyen Trang T.K.phan Giang H.Nguyen phuong T.T.Le Van T.hoang Nicholas R.Forsyth Michael Heke Liem Thanh Nguyen Department of Research and Development Vinmec Research Institute of Stem Cell and Gene TechnologyVinmec Healthcare SystemHanoiVietnam Department of Cellular Therapy Vinmec High.Tech CenterVinmec Healthcare SsystemHanoiVietnam Institute for Science&Technology in Medicine Keele UniversityKeeleUK a Department of Biology Stanford UniversityStanfordCAUSA

Recent advancements in stem cell technology open a new door for patients suffering from diseases and disorders that have yet to be treated.Stem cell-based therapy,including human pluripotent stem cells(hPsCs)and multipotent mesenchymal stem cells(MSCs),has recently emerged as a key player in regenerative medicine.hPSCs are defined as self-renewable cell types conferring the ability to differentiate into various cellular phenotypes of the human body,including three germ layers.MsCs are multipotent progenitor cells possessing self-renewal ability(limited in vitro)and differentiation potential into mesenchymal lineages,according to the International Society for Cell and Gene Therapy(ISCT).This review provides an update on recent clinical applications using either hPSCs or MSCs derived from bone marrow(BM),adipose tissue(AT),or the umbilical cord(UC)for the treatment of human diseases,including neurological disorders,pulmonary dysfunctions,metabolic/endocrine-related diseases,reproductive disorders,skin burns,and cardiovascular conditions.Moreover,we discuss our own clinical trial experiences on targeted therapies using MsCs in a clinical setting,and we propose and discuss the MSC tissue origin concept and how MSC origin may contribute to the role of MSCs in downstream applications,with the ultimate objective of facilitating translational research in regenerative medicine into clinical applications.The mechanisms discussed here support the proposed hypothesis that BM-MSCs are potentially good candidates for brain and spinal cord injury treatment,AT-MSCs are potentially good candidates for reproductive disorder treatment and skin regeneration,and UC-MsCs are potentially good candidates for pulmonary disease and acute respiratory distress svndrometreatment.

关键词： diseases distress treatment

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Mechanism of Japanese encephalitis virus genotypes replacement based on human,porcine and mosquito-originated cell lines model

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Asian Pacific Journal of Tropical Medicine 2016年第4期9卷 325-328页

作者： Loan phuong Do Trang Minh Bui Nga Thi phan National Institute of Hygiene and Epidemiology

Objective:To examine the multiplication efficiency Japanese encephalitis virus(JEV)genotype Ⅰ(G Ⅰ) and genotype Ⅲ(GⅢ) of different cell lines which originated from human,porcine,mosquitoes in order to prove mechanism of JEV G Ⅰ replacement JEV GⅢ since it emerging in nature recent decades.Methods:The mixture of Gi and GⅢ JEV isolates was inoculated on human rhabdomyosarcoma(RD).pig kidney epithelial(PS) and Aedes albopictus C6/36 clone(C6/36) which originated from human,porcine and mosquitoes,respectively.Plaque assays were performed to calculate virus titer and real-time RT-PCR with GⅠand GⅢspecific primer sets to quantify the number of GⅠ and GUI RNA copies.Results:The highest virus titer reached at the 3rd day of post infection when G Ⅰand GⅢ mixture was inoculated on RD and PS and that of C636 was at the 4^(th)day.JEVs were amplified and maintained by C6/36 cells after 10 passages whereas that by RD and PS only limited within 8 and 6 passages,respectively.GⅠ strain amplified and maintained more efficiently on C6/36 and PS but not RD.whereas GⅢ strain amplified and maintained more efficiently on RD.Conclusions:There is a correlation between the multiplication efficiency of GⅠ and GⅢ JEV strains when these two genotype strains co-infected on different cell lines with the predominance of GⅠstrains in C6/36 and PS and the limited detection of G 1 strains in RD cells proving a possible mechanism of shift JEV genotypes in nature recent decades since GⅠ emerging.

关键词： Japanese encephalitis virus Genotype I Genotype Ⅲ Multiplication Shift genotype

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Dynamic Power Transmission Using Common RF Feeder with Dual Supply

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ZTE Communications 2022年第2期20卷 28-36页

作者： DUONG Quang-Thang VO Quoc-Trinh phan Thuy-phuong OKADA Minoru Nara Institute of Science and Technology Nara 630-0192Japan FPT University Da Nang Da Nang 50500Vietnam

This paper proposes the design concept of a dynamic charging system for electric vehicles using multiple transmitter coils connected to a common radio frequency(RF)feeder driven by a pair of two power supplies.Using a common RF feeder for multiple transmitter coils reduces the power electronic redundancy compared to a conventional system,where each transmitter coil is individually driven by one switched-mode power supply.Currently,wireless charging of electric vehicles is recommended to operate in the frequency range of 85 kHz and beyond.In this frequency range,the signal wavelength is shorter than about 3.5 km.Therefore,a charging pad longer than several hundred meters is subject to the standing wave effect.In such a case,the voltage significantly varies along the RF feeder,resulting in a variation in the received power level when the receiver moves.Specifically,the received power significantly deteriorates when the receiver is nearby a node of the voltage standing wave.In this paper,we employ a pair of two power sources which are electrically separated by an odd-integer number of the quarter wavelength to drive the RF feeder.As a result,the voltage standing wave generated by one power source is complemented by that of the other,leading to stable received power and transmission efficiency at all the receiver’s positions along with the charging pad.Simulation results at the 85 kHz frequency band verify the output power stabilization effect of the proposed design.It is worth noting that the proposed concept can also be applied to simultaneous wireless information and power transfer(SWIPT)for passive radio frequency identification(RFID)tags by raising the operation frequency to higher industrial,scientific and medical(ISM)bands,e.g.,13.56 MHz and employing similar modulation methods as in the current RFID technology.

关键词： dynamic charging common RF feeder standing wave dual power supply

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An Effective Integrated Machine Learning Framework for Identifying Severity of Tomato Yellow Leaf Curl Virus and Their Experimental Validation

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Research 2023年第3期2023卷 91-104页

作者： Nattanong Bupi Vinoth Kumar Sangaraju Le Thi phan Aamir Lal Thuy Thi Bich Vo phuong Thi Ho Muhammad Amir Qureshi Marjia Tabassum Sukchan Lee Balachandran Manavalan Department of Integrative Biotechnology College of Biotechnology and BioengineeringSungkyunkwan UniversitySuwon 16419.Gyeonggi-doRepublic of Korea Computational Biology and Bioinformatics Laboratory Department of Integrative BiotechnologyCollege of Biotechnology and Bioengineering.Sungkyunkwan UniversitySuwon 16419Gyeonggi-doRepublic of Korea

Tomato yellow leaf curl virus(TYLCV)dispersed across different countries,specifically to subtropical regions,associated with more severe symptoms.Since TYLCV was first isolated in 1931,it has been a menace to tomato industrial production worldwide over the past century.Three groups were newly isolated from TYLCV-resistant tomatoes in 2022;however,their functions are unknown.The development of machine learning(ML)-based models using characterized sequences and evaluating blind predictions is one of the major challenges in interdisciplinary research.The purpose of this study was to develop an integrated computational framework for the accurate identification of symptoms(mild or severe)based on TYLCV sequences(isolated in Korea).For the development of the framework,we first extracted 11 different feature encodings and hybrid features from the training data and then explored 8 different classifiers and developed their respective prediction models by using randomized 10-fold cross-validation.Subsequently,we carried out a systematic evaluation of these 96 developed models and selected the top 90 models,whose predicted class labels were combined and considered as reduced features.On the basis of these features,a multilayer perceptron was applied and developed the final prediction model(IML-TYLCVs).We conducted blind prediction on 3 groups using IML-TYLCVs,and the results indicated that 2 groups were severe and 1 group was mild.Furthermore,we confirmed the prediction with virus-challenging experiments of tomato plant phenotypes using infectious clones from 3 groups.Plant virologists and plant breeding professionals can access the user-friendly online IML-TYLCVs web server at https://***/IML-TYLCVs,which can guide them in developing new protection strategies for newly emerging viruses.

关键词： breeding fir prediction

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An Optimal Deep Learning Based Computer-Aided Diagnosis System for Diabetic Retinopathy

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Computers, Materials & Continua 2021年第3期66卷 2815-2830页

作者： Phong Thanh Nguyen Vy Dang Bich Huynh Khoa Dang Vo phuong Thanh phan Eunmok Yang Gyanendra Prasad Joshi Department of Project Management Ho Chi Minh City Open UniversityHo Chi Minh City7000000Vietnam Department of Learning Material Ho Chi Minh City Open UniversityHo Chi Minh City7000000Vietnam Department of Convergence Science Kongju National UniversityGongju32588South Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006South Korea

Diabetic Retinopathy(DR)is a significant blinding disease that poses serious threat to human vision rapidly.Classification and severity grading of DR are difficult processes to accomplish.Traditionally,it depends on ophthalmoscopically-visible symptoms of growing severity,which is then ranked in a stepwise scale from no retinopathy to various levels of DR severity.This paper presents an ensemble of Orthogonal Learning Particle Swarm Optimization(OPSO)algorithm-based Convolutional Neural Network(CNN)Model EOPSO-CNN in order to perform DR detection and grading.The proposed EOPSO-CNN model involves three main processes such as preprocessing,feature extraction,and classification.The proposed model initially involves preprocessing stage which removes the presence of noise in the input image.Then,the watershed algorithm is applied to segment the preprocessed images.Followed by,feature extraction takes place by leveraging EOPSO-CNN model.Finally,the extracted feature vectors are provided to a Decision Tree(DT)classifier to classify the DR images.The study experiments were carried out using Messidor DR Dataset and the results showed an extraordinary performance by the proposed method over compared methods in a considerable way.The simulation outcome offered the maximum classification with accuracy,sensitivity,and specificity values being 98.47%,96.43%,and 99.02%respectively.

关键词： Diabetic retinopathy convolutional neural network classification image processing computer-aided diagnosis

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Deep Learning Based Optimal Multimodal Fusion Framework for Intrusion Detection Systems for Healthcare Data

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Computers, Materials & Continua 2021年第3期66卷 2555-2571页

作者： Phong Thanh Nguyen Vy Dang Bich Huynh Khoa Dang Vo phuong Thanh phan Mohamed Elhoseny Dac-Nhuong Le Department of Project Management Ho Chi Minh City Open UniversityHo Chi Minh City700000Vietnam Department of Learning Material Ho Chi Minh City Open UniversityHo Chi Minh City700000Vietnam Faculty of Computers and Information Mansoura UniversityDakahlia Governorate35516Egypt Institute of Research and Development Duy Tan UniversityDanang550000Vietnam Faculty of Information Technology Duy Tan UniversityDanang550000Vietnam

Data fusion is a multidisciplinary research area that involves different domains.It is used to attain minimum detection error probability and maximum reliability with the help of data retrieved from multiple healthcare sources.The generation of huge quantity of data from medical devices resulted in the formation of big data during which data fusion techniques become essential.Securing medical data is a crucial issue of exponentially-pacing computing world and can be achieved by Intrusion Detection Systems(IDS).In this regard,since singularmodality is not adequate to attain high detection rate,there is a need exists to merge diverse techniques using decision-based multimodal fusion process.In this view,this research article presents a new multimodal fusion-based IDS to secure the healthcare data using Spark.The proposed model involves decision-based fusion model which has different processes such as initialization,pre-processing,Feature Selection(FS)and multimodal classification for effective detection of intrusions.In FS process,a chaotic Butterfly Optimization(BO)algorithmcalled CBOA is introduced.Though the classic BO algorithm offers effective exploration,it fails in achieving faster convergence.In order to overcome this,i.e.,to improve the convergence rate,this research work modifies the required parameters of BO algorithm using chaos theory.Finally,to detect intrusions,multimodal classifier is applied by incorporating three Deep Learning(DL)-based classification models.Besides,the concepts like Hadoop MapReduce and Spark were also utilized in this study to achieve faster computation of big data in parallel computation platform.To validate the outcome of the presented model,a series of experimentations was performed using the benchmark NSLKDDCup99 Dataset repository.The proposed model demonstrated its effective results on the applied dataset by offering the maximum accuracy of 99.21%,precision of 98.93%and detection rate of 99.59%.The results assured the betterment of the proposed model.

关键词： Big data data fusion deep learning intrusion detection bio-inspired algorithm spark

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Evaluation of Agronomic Characteristics,Drought Tolerance and Yield of Some Rice Varieties in Central Vietnam

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Journal of Agricultural Science and Technology(A) 2017年第B10期7卷 1-9页

作者： phan Thi phuong Nhi Tran Thi Huong Sen Trinh Thi Sen Tran Thi hoang Dong Faculty of Agronomy University of Agriculture and ForestryHue University102 Phung Hung StreetHue 530000Vietnam

The aim of the study was to evaluate the drought tolerance,agro-morphological characteristics and yield of 10 rice varieties collected from different locations.In experiment one,drought tolerance of rice varieties under artificial drought condition in the greenhouse was assessed through root and leaf characteristics.In experiment two,the growth and yield of rice varieties in the rainfed rice field was estimated.The results showed that drought has affected the root characteristics,leaf rolling and leaf drying of these varieties.In rainfed rice field of Thua Thien Hue and Quang Nam province,summer-autumn 2016 and winter-spring 2016-2017 crop season,these rice varieties grew and developed well.The growth time was 90-119 d in summer-autumn crop season,while in winter-spring crop season was 107-131 d.The yield of these rice varieties ranged from 37.02 quintals/ha to 56.33 quintals/ha and from 42.33 quintals/ha to 66.60 quintals/ha,respectively.Some rice varieties with high yields in both two crop seasons were OM4900,GSR38,IR93340 and OM7347.It is sugessted to conduct production experiment on a large area in rainfed field for these four varieties to evaluate them objectively and early put them into structure of rice varieties in Central Vietnam.

关键词： Central Vietnam drought tolerance growth rice variety yield

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Ecoregional variations of aboveground biomass and stand structure in evergreen broadleaved forests

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Journal of Forestry Research 2020年第5期31卷 1713-1722页

作者： Tran Van Do Mamoru Yamamoto Osamu Kozan Vo Dai Hai Phung Dinh Trung Nguyen Toan Thang Lai Thanh Hai vu Thanh Nam Trieu Thai Hung hoang Van Thang Tran Duc Manh Cao Chi Khiem vu Tien Lam Nguyen Quang Hung Tran hoang Quy Pham Quang Tuyen Trinh Ngoc Bon Nguyen Thi Thu phuong Ninh Viet Khuong Nguyen Van Tuan Dang Thi Hai Ha Tran Hai Long Dang Van Thuyet Dang Thinh Trieu Nguyen Van Thinh Tran Anh Hai Duong Quang Trung Nguyen Van Bich Dinh Hai Dang Pham Tien Dung Nguyen Huy hoang Le Thi Hanh phan Minh Quang Nguyen Thi Thuy Huong hoang Thanh Son Nguyen Thanh Son Nguyen Thi Van Anh Nguyen Thi Hoai Anh Pham Dinh Sam hoang Thi Nhung hoang Van Thanh Nguyen Huu Thinh Tran Hong Van Ho Trung Luong Bui Kieu Hung Research Institute for Sustainable Humanosphere Kyoto UniversityUjiKyotoJapan Silviculture Research Institute Vietnamese Academy of Forest SciencesNorth Tu LiemHanoiVietnam Center for Southeast Asian Studies Kyoto UniversityKyotoJapan Vietnamese Academy of Forest Sciences North Tu LiemHanoiVietnam Vietnam Administration of Forestry No.2 Ngoc HaBa DinhHanoiVietnam

Biotic and abiotic factors control aboveground biomass(AGB)and the structure of forest ecosystems.This study analyses the variation of AGB and stand structure of evergreen broadleaved forests among six ecoregions of Vietnam.A data set of 1731-ha plots from 52 locations in undisturbed old-growth forests was developed.The results indicate that basal area and AGB are closely correlated with annual precipitation,but not with annual temperature,evaporation or hours of sunshine.Basal area and AGB are positively correlated with trees>30 cm DBH.Most areas surveyed(52.6%)in these old-growth forests had AGB of 100–200 Mg ha^-1;5.2%had AGB of 400–500 Mg ha^-1,and 0.6%had AGB of>800 Mg ha^-1.Seventy percent of the areas surveyed had stand densities of 300–600 ind.ha^-1,and 64%had basal areas of 20–40 m^2 ha^-1.Precipitation is an important factor influencing the AGB of old-growth,evergreen broadleaved forests in Vietnam.Disturbances causing the loss of large-diameter trees(e.g.,>100 cm DBH)affects AGB but may not seriously affect stand density.

关键词： Aboveground biomass Carbon storage Climatic variables Ecoregion Edaphic variables Oldgrowth forest

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Salinity Effect at Seedling and Flowering Stages of Some Rice Lines and Varieties(Oryza sativa L.)

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Journal of Agricultural Science and Technology(A) 2017年第B10期7卷 32-39页

作者： Tran Thi Huong Sen phan Thi phuong Nhi Trinh Thi Sen Faculty of Agronomy University of Agriculture and ForestryHue University102 Phung Hung StreetHue 530000Vietnam

This study used 10 rice lines and varieties,including the salt tolerant variety(Pokkali)and salt susceptible variety(IR29)as control.Experiment for screening rice salinity tolerance at seedling stage was conducted in hydroponic system using five different salinity concentrations(0,4,6,8 and 10 dS/m).Flowering stage was evaluated at the salinity level of 8 dS/m.The experiment was designed in randomized completely block(RCBD)with three replications for each line/variety under non-saline and saline condition.The results showed that the growth of rice lines/varieties was retarded severely with increasing salinity levels,and almost all of leaves were drying and dead completely(score 7 and 9).Plants of IR29 and OM7347 were dead at the electrical conductivity(EC)=10 dS/m,whereas Pokkali(the tolerant variety)and IR93350 were evaluated at score 5.Salinity stress caused the reduction of overall vigor of rice lines/varieties especially in the pollen germination,fertilization and grain yield.Rice lines/varieties were classified to salinity tolerance levels as following:IR5040,IR93350,IR86385-8D-1-2-B and Pokkali(tolerant);OM8104,IR93340 and IR93343(moderate susceptible);OM7347,IR87832-303-1-B and IR29(susceptible).

关键词： Tolerant salinity pollen seedling stage flowering stage screening for salinity tolerance

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