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Climate change and groundwater resources in Mekong delta, Vietnam

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Journal of Groundwater Science and Engineering 2017年第1期5卷 76-90页

作者： duong d bui Nghia C Nguyen Nuong T bui Anh T T Le dao T Le National Center for Water Resources Planning and Investigation MONRE Vietnam Tokyo Metropolitan University Japan Center for Environmental Fluid dynamics Hanoi University of Science Vietnam

Groundwater resources have considerable influences on the human population and socioeconomic development of Vietnam and the Mekong River delta(MRd). This paper presents an overview of the relationship between climate change and groundwater in the MRd, including the challenges, strategies and technical measures. Our results showed that groundwater levels are related to other climate and hydrological variables(i.e., rainfall, river levels, etc.); therefore, the impacts of climate change on the groundwater resources of the Mekong delta are significant, especially on groundwater recharge. Based on the results of this study, it is recommended that groundwater development in the future should focus on reducing groundwater harvesting, enhancing groundwater quantity by establishing artificial works and exploiting surface water. This study suggests that the Artificial Neural Network(ANN) model is an effective tool for forecasting groundwater levels in periods of 1 month and 3 months for aquifers in the natural and tidal regime areas of the delta.

关键词： Groundwater management Climate change ANN model Mekong River delta

Advancing Wound Filling Extraction on 3d Faces:An Auto-Segmentation and Wound Face Regeneration Approach

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2197-2214页

作者： duong Q.Nguyen Thinh d.Le Phuong d.Nguyen Nga T.K.Le H.Nguyen-Xuan department of Mathematics and Statistics Quy Nhon UniversityQuy Nhon City55100Viet Nam Applied Research Institute for Science and Technology Quy Nhon UniversityQuy Nhon City55100Viet Nam CIRTECH Institute HUTECH UniversityHo Chi Minh City72308Viet Nam

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical *** this paper,we propose an efficient approach for automating 3d facial wound segmentation using a two-stream graph convolutional *** method leverages the Cir3d-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss *** achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the *** selectedmodel demonstrates exceptional segmentation performance for complex 3d facial ***,based on the segmentation model,we propose an improved approach for extracting 3d facial wound fillers and compare it to the results of the previous *** method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous *** this result,we use 3d printing technology to illustrate the shape of the wound *** outcomes of this study have significant implications for physicians involved in preoperative planning and intervention *** automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient ***,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3d bioprinting for printing skin tissue *** source code is available at https://***/SIMOGroup/WoundFilling3d.

关键词： 3d printing technology face reconstruction 3d segmentation 3d printed model

deep learning long short-term memory combined with discrete element method for porosity prediction in gravel-bed rivers

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International Journal of Sediment Research 2023年第1期38卷 128-140页

作者： duong Tran Anh Ahad Hasan Tanim daniel Prakash Kushwaha Quoc Bao Pham Van Hieu bui HUTECH University Center for River Harbor and Landslide Research Chittagong University of Engineering & Technology Govind Ballabh Pant University of Agriculture and Technology Institute of Applied Technology Thu Dau Mot University Faculty of Mechanical Engineering Thuyloi University

The porosity of gravel riverbed material often is an essential parameter to estimate the sediment transport rate, groundwater-river flow interaction, river ecosystem, and fluvial geomorphology. Current methods of porosity estimation are time-consuming in simulation. To evaluate the relation between porosity and grain size distribution(GSd), this study proposed a hybrid model of deep learning Long Short-Term Memory(LSTM) combined with the discrete Element Method(dEM). The dEM is applied to model the packing pattern of gravel-bed structure and fine sediment infiltration processes in threedimensional(3d) space. The combined approaches for porosity calculation enable the porosity to be determined through real time images, fast labeling to be applied, and validation to be done. dEM outputs based on the porosity dataset were utilized to develop the deep learning LSTM model for predicting bed porosity based on the GSd. The simulation results validated with the experimental data then segregated into 800 cross sections along the vertical direction of gravel pack. Two dEM packing cases, i.e., clogging and penetration are tested to predict the porosity. The LSTM model performance measures for porosity estimation along the z-direction are the coefficient of determination(R~2), root mean squared error(RMSE), and mean absolute error(MAE) with values of 0.99, 0.01, and 0.01 respectively, which is better than the values obtained for the Clogging case which are 0.71, 0.14, and 0.03, respectively. The use of the LSTM in combination with the dEM model yields satisfactory results in a less complex gravel pack dEM setup, suggesting that it could be a viable alternative to minimize the simulation time and provide a robust tool for gravel riverbed porosity prediction. The simulated results showed that the hybrid model of the LSTM combined with the dEM is reliable and accurate in porosity prediction in gravel-bed river test samples.

关键词： Numerical modeling discrete element method LSTM Bed porosity Gravel-bed river

Targeted therapy for capillary-venous malformations

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Signal Transduction and Targeted Therapy 2024年第7期9卷 3024-3039页

作者： Lola Zerbib Sophia Ladraa Antoine Fraissenon Charles Bayard Marina Firpion Quitterie Venot Sanela Protic Clément Hoguin Amandine Thomas Sylvie Fraitag Jean-Paul duong Sophie Kaltenbach Estelle Balducci Coline Lefevre Patrick Villarese Vahid Asnafi Christine Broissand Nicolas Goudin Ivan Nemazanyy Gwennhael Autret Bertrand Tavitian Christophe Legendre Nadia Arzouk Veronique Minard-Colin Caroline Chopinet Michael dussiot denise MAdams Tristan Mirault Laurent Guibaud Paul Isenring Guillaume Canaud UniversitéParis Cité ParisFrance INSERM U1151 Institut Necker-Enfants MaladesParisFrance Service d’Imagerie Pédiatrique Hôpital Femme-Mère-EnfantHCLBronFrance CREATIS UMR 5220 Villeurbanne 69100France Service de Radiologie Mère-Enfant Hôpital NordSaint EtienneFrance Service d’Anatomie pathologique Hôpital Necker-Enfants MaladesAP-HPParisFrance Laboratoire d’Oncohématologie Hôpital Necker-Enfants MaladesAP-HPParisFrance Pharmacie Hôpital Necker-Enfants MaladesAP-HPParisFrance Necker Bio-Image Analysis INSERM US24/CNRS UMS 3633ParisFrance Platform for Metabolic Analyses Structure Fédérative de Recherche NeckerINSERM US24/CNRS UMS 3633ParisFrance Plateforme Imageries du Vivant Universitéde ParisPARCCINSERMParisFrance Service de Néphrologie Transplantation AdultesHôpital Necker-Enfants MaladesAP-HPParisFrance Service de Transplantation Hôpital La PitiéSalpétrièreAP-HPParisFrance department of Pediatric and Adolescent Oncology INSERM 1015Gustave RoussyUniversitéParis-SaclayVillejuifFrance Service de Physiologie&Explorations Fonctionnelles Cardiovasculaires CHU de LilleLille 59000France INSERM U1163 Laboratory of Cellular and Molecular Mechanisms of Hematological Disorders and Therapeutic ImplicationsLaboratoire d’Excellence GR-ExParisFrance division of Oncology Comprehensive Vascular Anomalies ProgramChildren’s Hospital of PhiladelphiaPhiladelphiaPAUSA Service de Médecine Vasculaire hôpital Européen Georges-PompidouParisFrance Nephrology Research Group L’Hôtel-Dieu de Québec Research CenterDepartment of MedicineFaculty of MedicineLaval UniversityQuebecQC G1R2J6Canada Unitéde médecine translationnelle et thérapies ciblées Hôpital Necker-Enfants MaladesAP-HPParisFrance CNRS UMR8253 Institut Necker-Enfants MaladesParisFrance

Sporadic venous malformations are genetic conditions primarily caused by somatic gain-of-function mutation of PIK3CA or TEK,an endothelial transmembrane receptor signaling through *** malformations are associated with pain,bleedings,thrombosis,pulmonary embolism,esthetic deformities and,in severe cases,life-threatening *** authorized medical treatment exists for patients with venous ***,we created a genetic mouse model of PIK3CA-related capillary venous malformations that replicates patient *** showed that these malformations only partially signal through AKT *** compared the efficacy of different drugs,including rapamycin,a mTORC1 inhibitor,miransertib,an AKT inhibitor and alpelisib,a PI3Kαinhibitor at improving the lesions seen in the mouse *** demonstrated the effectiveness of alpelisib in preventing vascular malformations’occurrence,improving the already established ones,and prolonging *** these findings,we were authorized to treat 25 patients with alpelisib,including 7 children displaying PIK3CA(n=16)or TEK(n=9)-related capillary venous malformations resistant to usual therapies including sirolimus,debulking surgical procedures or percutaneous *** assessed the volume of vascular malformations using magnetic resonance imaging(MRI)for each *** demonstrated improvement in all 25 *** malformations previously considered intractable were reduced and clinical symptoms were *** showed a decrease of 33.4%and 27.8%in the median volume of PIK3CA and TEK malformations respectively,over 6 months on *** conclusion,this study supports PI3Kαinhibition as a promising therapeutic strategy in patients with PIK3CA or TEK-related capillary venous malformations.

关键词： PIK3CA malformations venous

Comparison of Layer-stacking and dempster-Shafer Theory-based Methods Using Sentinel-1 and Sentinel-2 data Fusion in Urban Land Cover Mapping

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Geo-Spatial Information Science 2022年第3期25卷 425-438页

作者： dang Hung bui LászlóMucsi department of Geoinformatics Physical and Environmental GeographyUniversity of SzegedSzegedHungary Institute for Environmental Science Engineering and ManagementIndustrial University of Ho Chi Minh CityHo Chi Minh CityVietnam

data fusion has shown potential to improve the accuracy of land cover mapping,and selection of the optimal fusion technique remains a *** study investigated the performance of fusing Sentinel-1(S-1)and Sentinel-2(S-2)data,using layer-stacking method at the pixel level and dempster-Shafer(d-S)theory-based approach at the decision level,for mapping six land cover classes in Thu dau Mot City,*** the pixel level,S-1 and S-2 bands and their extracted textures and indices were stacked into the different single-sensor and multi-sensor datasets(*** datasets).The datasets were categorized into two *** group included the datasets containing only spectral and backscattering bands,and the other group included the datasets consisting of these bands and their extracted *** random forest(RF)classifier was then applied to the datasets within each *** the decision level,the RF classification outputs of the single-sensor datasets within each group were fused together based on d-S ***,the accuracy of the mapping results at both levels within each group was *** results showed that fusion at the decision level provided the best mapping accuracy compared to the results from other products within each *** highest overall accuracy(OA)and Kappa coefficient of the map using d-S theory were 92.67%and 0.91,*** decision-level fusion helped increase the OA of the map by 0.75%to 2.07%compared to that of corresponding S-2 products in the ***,the data fusion at the pixel level delivered the mapping results,which yielded an OA of 4.88%to 6.58%lower than that of corresponding S-2 products in the groups.

关键词： Land cover mapping data fusion random forest dempster-Shafer theory optical data radar data pixel level decision level

Social media study of public opinions on potential COVId-19 vaccines: informing dissent, disparities, and dissemination

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Intelligent Medicine 2022年第1期2卷 1-12页

作者： Hanjia Lyu Junda Wang Wei Wu Viet duong Xiyang Zhang Timothy ddye Jiebo Luo Goergen Institute for data Science University of RochesterRochesterNew York 14627United States department of Computer Science University of RochesterRochesterNew York 14627United States department of Psychology University of AkronAkronOhio 44325United States department of Obstetrics and Gynecology University of Rochester School of Medicine and DentistryRochesterNew York 14642United States

Background The current development of vaccines for severe acute respiratory syndrome coronavirus 2(SARSCoV-2)is *** is known,however,about the nuanced public opinions on the vaccines on social *** We adopted a human-guided machine learning framework using more than six million tweets from almost two million unique Twitter users to capture public opinions on the vaccines for SARS-CoV-2,classifying them into three groups:pro-vaccine,vaccine-hesitant,and *** feature inference and opinion mining,10,945 unique Twitter users were included in the study *** logistic regression and counterfactual analysis were *** Socioeconomically disadvantaged groups were more likely to hold polarized opinions on coronavirus disease 2019(COVId-19)vaccines,either pro-vaccine(B=0.40,SE=0.08,Pdemic experience were more likely to hold the anti-vaccine opinion(B=−0.18,SE=0.04,Pd States public is most concerned about the safety,effectiveness,and political issues regarding vaccines for COVId-19,and improving personal pandemic experience increases the vaccine acceptance level.

关键词： Vaccine hesitancy COVId-19 Public opinion Social Media Twitter

Monte Carlo simulation of a cone-beam CT system for lightweight casts

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Radiation detection Technology and Methods 2021年第4期5卷 504-512页

作者： Thuy duong Tran Ngoc Ha bui Kim Tuan Tran Ngoc Toan Tran department of Nuclear Engineering and Environmental Physics School of Engineering PhysicsHanoi University of Science and Technology01 Dai Co VietHai Ba TrungHanoiVietnam Vietnam Atomic Energy Institute 59 Ly Thuong KietHoan KiemHanoiVietnam

Cone-beam computed tomography(CBCT),a modern technique with many applications,is becoming increasingly important and essential in many areas of economics and *** equipment has been commercialized in both hardware and ***,having a device system suitable for a specific group of objects will be the *** work used Monte Carlo simulation to optimize the design of a Cone-beam Computed Tomography(CBCT)for lightweight and small-size *** affecting image quality such as radiation-source,flat-panel detector,and geometrical distance were *** results indicate that an X-ray generator with a focal spot size of 4×4µm^(2),high voltage of 240 kV,and a radiation intensity of 10^(13) photon/s with a flat panel CsI(Tl)detector of 0.3 mm thickness and a pixel size of 0.1–0.2 mm,is suitable for a CBCT to inspect small objects in *** Monte Carlo model was validated against experiments and to evaluate some characteristics of the existing system.

关键词： Cone-beam computed technology Monte Carlo simulation Lightweight casts in industry Applied radiation

Utilization and Satisfaction with HIV Services at 7 Provinces in Vietnam: A Cross-Sectional Study

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World Journal of AIdS 2022年第2期12卷 65-82页

作者： Le Bao Chau Pham Thi Huyen Chang duong Minh duc Hoang Van Minh Luu Quoc Toan bui Thi Tu Quyen Le Thi Vui bui Thi Thu Ha Hanoi University of Public Health Hanoi Vietnam

The study was carried out to determine utilization and satisfaction with essential HIV services from HIV individuals and high-risk populations in 7 socioeconomic provinces nationwide. A cross-sectional approach was applied in the study. data were collected through face-to-face interviews using self-report questionnaires. Findings from 2380 respondents indicated a high percentage of utilization as well as a high level of satisfaction, in particular among men who have sex with men (MSM) and female sex worker (FSW) sub-group. Needle, syringe, and condom programs had lower usage and satisfaction mean scores in comparison with other services. The proportion of people who used drugs (PWId) and participated in the needle and syringe program was 53.6%. HIV counseling and testing uptake proportion of overall respondents in the last 12 months was 82.2% while the rate of antiretroviral treatment among infected PWId was 74.9%. The level of satisfaction with treatment services was found to be higher than preventive interventions (p d an association between some socioeconomic factors such as income, employment, educational attainment, and marital status with subjects’ satisfaction with several HIV services. Preventive services, especially needle, syringe and condom programs should be prioritized to scale up the coverage and effectiveness. Innovative approaches targeting at PWId should be promoted to increase their access to prevention programs as well as HIV care when needed.

关键词： HIV Service Utilization Satisfaction

Profiling of Urban Noise Using Artificial Intelligence

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Computer Systems Science & Engineering 2023年第5期45卷 1309-1321页

作者： Le Quang Thao duong duc Cuong Tran Thi Tuong Anh Tran duc Luong Ph.d.Faculty of Physics VNU University of ScienceHanoi100000Vietnam University of Science Vietnam National UniversityHanoi100000Vietnam The International School of Penang(Uplands) PenangMalaysia Alpha School Hanoi100000Vietnam

Noise pollution tends to receive less awareness compared to other types of pollution,however,it greatly impacts the quality of life for humans such as causing sleep disruption,stress or hearing *** urban sound through the identification of noise sources in cities could help to benefit livability by reducing exposure to noise pollution through methods such as noise control,planning of the soundscape environment,or selection of safe living *** this paper,we proposed a self-attention long short-term memory(LSTM)method that can improve sound classification compared to previous *** attention mechanism will be designed solely to capture the key section of an audio data *** is practical as we only need to process important parts of the data and can ignore the rest,making it applicable when gathering information with long-term *** dataset used is the Urbansound8k dataset which specifically pertains to urban environments and data augmentation was applied to overcome imbalanced data and dataset *** audio sources in the dataset were normalized to mono *** the dataset above,an experiment was conducted to confirm the suitability of the proposed model when applied to the mel-spectrogram and MFCC(Mel-Frequency Cepstral Coefficients)datasets transformed from the original *** the classification accuracy depends on the machine learning models as well as the input data,therefore we have evaluated different class models and extraction methods to find the best *** combining data augmentation techniques and various extraction methods,our classification model has achieved state-of-the-art performance,each class accuracy is up to 98%.

关键词： Urban noise noise classification mel-spectrogram MFCC LSTM self-attention