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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 scores<13 and Schirmer Ⅰ values equal to or under 10 mm were diagnosed with ***:The ratio of DE in hypertension patients was higher than in the control group(41.7%versus 18.8%;P<0.001).The proportion of patients with DE increased gradually according to the hypertension stage:27.1% in stage Ⅰ,40.3% in stage Ⅱ,and 57.6% in stage Ⅲ,P<***,duration of hypertension,plasma urea,creatinine,and high-sensitivity C-reactive protein(CRP-hs)levels in hypertension patients with DE were higher than those without DE,P<*** age,a long duration of hypertension,diabetes mellitus,elevated plasma creatinine,and CRP-hs levels were independent factors associated with DE in primary hypertension patients,P<***:DE is a common disorder associated with advanced age,a long duration of hypertension,diabetes mellitus,elevated 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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An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

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Computers, Materials & Continua 2024年第3期78卷 3585-3602页

作者： duy Quang Tran Huy Q.Tran Minh Van nguyen Faculty of Civil Engineering Nha Trang UniversityNha Trang650000Vietnam Robotics and Mechatronics Research Group Faculty of Engineering and TechnologyNguyen Tat Thanh UniversityHo Chi Minh City700000Vietnam Department of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh City700000Vietnam

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

关键词： Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning

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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

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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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Building the ARIMA Model for Forecasting the Production of Vietnam’s Coffee Export

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Journal of Applied Mathematics and Physics 2024年第4期12卷 1237-1246页

作者： duy Quang Phung Quoc thang Trinh Quang Truong Do Ngan Giang nguyen Van Ha nguyen Gia Khiem Ngo Thi Minh Ngoc Tran Faculty of Technology and Data Science Foreign Trade University Hanoi Vietnam School of Economics and International Business Foreign Trade University Hanoi Vietnam

Coffee is a significant industry, accounting for 3% of Vietnam’s GDP, with annual export turnover consistently exceeding USD 3 billion. Despite global economic challenges affecting purchasing power at various times, Vietnam’s coffee exports in December 2023 continued to surge, reaching the highest level in the past 9 months at 190,000 tons, a 59.3% increase compared to November 2023, but still a slight 3.5% decrease from the same period last year. The export turnover reached USD 538 million, a 51% increase from November 2023 and a 26.4% increase from the same period last year. Therefore, forecasting the coffee export volume holds significant importance for coffee producers nationwide. This research employs the Box-Jenkins method to construct an ARIMA model for forecasting Vietnam’s coffee export volume based on annual data published by the General Statistics Office. Results indicate that among the models considered, the ARIMA(1, 1, 2) model is the most suitable. The study also provides short-term forecasts for Vietnam’s coffee export volume. However, the current model is limited to forecasting and is not yet optimized, as the assumed linearity in the model is a simplification.

关键词： ARIMA Forecasting Coffee Export Volume Data Science

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循环三轴试验加载频率和压实度对重塑砂土液化行为的影响

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岩土力学 2024年第6期45卷 1813-1823页

作者： THUY Do Van TIEP Pham Duc HIEU nguyen Van thang Pham Cao 勒奎东技术大学特殊工程技术研究所越南河内越南航空科技协会越南河内

通过对各向同性固结不排水试样进行循环三轴试验,研究了饱和重塑砂土的液化行为。试验采用恒幅正弦载荷,通过测量剪切模量、阻尼比、轴向应变和超孔隙水压力比的变化,评估了加载频率(分别为0.1、0.5、1.0 Hz)和压实度(分别为0.95、0.90... 详细信息

通过对各向同性固结不排水试样进行循环三轴试验,研究了饱和重塑砂土的液化行为。试验采用恒幅正弦载荷,通过测量剪切模量、阻尼比、轴向应变和超孔隙水压力比的变化,评估了加载频率(分别为0.1、0.5、1.0 Hz)和压实度(分别为0.95、0.90和0.80)对砂土液化行为的影响。试验结果表明,对于压实度为0.95的砂样,在5000次加载循环中,0.1 Hz的加载频率对液化过程影响甚微;而对于压实度为0.90和0.80的砂样,此频率的影响显著。对于压实度为0.80的砂样,当频率增加到0.5 Hz时几乎一加载就直接发生液化。这表明增加加载频率会加快液化速度,而增加压实度则会减慢液化速度。因此,通过一系列的试验可以模拟现场砂土在不同频率下的动荷载条件。试验结果表明,饱和砂土的液化行为由以下因素决定:(1)试样的压实度越低,液化越容易发生;(2)加载频率越高,液化越容易发生;(3)循环轴向应变越大,发生液化所需的循环次数越少;(4)超孔隙水压力随加载循环次数增加,直至试样完全液化。

关键词：液化行为加载频率循环三轴试验饱和固结不排水条件重塑砂土压实度

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Optimal Scheduling of Multiple Rail Cranes in Rail Stations with Interference Crane Areas

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Intelligent Automation & Soft Computing 2024年第1期39卷 15-31页

作者： nguyen Vu Anh duy nguyen Le Thai nguyen Huu Tho Faculty of Engineering and Technology Nguyen Tat Thanh UniversityHo Chi Minh City700000Vietnam

In this paper,we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail *** particular,the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes.A dual cycle of cranes is used to minimize the number of working cycles of *** rail crane scheduling problems in this study are based on the movement of *** consider not only the gantry moves,but also the trolley moves as well as the rehandle cases are also included.A mathematical model of multi-crane scheduling is *** traditional and parallel simulated annealing(SA)are adapted to determine the optimal scheduling *** examples are conducted to evaluate the applicability of the proposed *** of the proposed parallel SA is done by comparing it to existing previous *** of numerical computation highlighted that the parallel SA algorithm outperformed the SA and gave better solutions than other considered algorithms.

关键词： Multi-crane scheduling logistics containers makespan rail stations

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Exponentially Bounded C-semigroup and the Cauchy Initial Value Problems in Complete Random Normed Modules

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Acta Mathematica Sinica,English Series 2024年第9期40卷 2195-2212页

作者： Son TA CONG thang Dang HUNG Oanh Le THI Department of Mathematics University of ScienceVietnam National University 334 Nguyen TraiThanh XuanHanoiVietnam Faculty of Natural Sciences Hong Duc University565 Quang TrungDong VeThanh HoaVietnam

In this paper,the notion of C-semigroup of continuous module homomorphisms on a complete random normal(RN)module is introduced and *** existence and uniqueness of solution to the Cauchy problem with respect to exponen... 详细信息

关键词： C-semigroup Cauchy problem random normed modules L^(0)-Lipschitz

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Transient responses of double-curved sandwich two-layer shells resting on Kerr's foundations with laminated three-phase polymer/GNP/fiber surface and auxetic honeycomb core subjected to the blast load

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Defence Technology（防务技术） 2024年第5期35卷 222-247页

作者： nguyen Thi Hai Van Thi Hong nguyen Researcher&Lecturer Faculty of Industrial EducationThe University of Danang-University of Technology and Education48 Cao ThangDanang550000Viet Nam Researcher&Lecturer Faculty of Mechanical EngineeringThuyloi University175 Tay SonDong DaHanoi100000Viet Nam

This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fiber surface subjected to the blast *** of the two layers that make up the double-curved shell structure is made up of an auxetic honeycomb core and two laminated sheets of three-phase polymer/GNP/*** exterior is supported by a Kerr elastic foundation with three *** key innovation of the proposed theory is that the transverse shear stresses are zero at two free surfaces of each *** contrast to previous first-order shear deformation theories,no shear correction factor is ***'s exact solution was used to treat the double-curved shell problem with a single title boundary,while the finite element technique and an eight-node quadrilateral were used to address the other boundary *** ensure the accuracy of these results,a thorough comparison technique is employed in conjunction with credible *** problem model's edge cases allow for this kind of *** study's findings may be used in the post-construction evaluation of military and civil works structures for their ability to sustain explosive *** addition,this is also an important basis for the calculation and design of shell structures made of smart materials when subjected to shock waves or explosive loads.

关键词： Blast load Two-layer shell Polymer/GNP/Fiber surface Auxetic honeycomb Shear connectors

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Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

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Journal of Pharmaceutical Analysis 2024年第1期14卷 16-38页

作者： nguyen Quang Thu nguyen Tran Nam Tien nguyen Thi Hai Yen Thuc-Huy Duong nguyen Phuoc Long Huy Truong nguyen Department of Pharmacology and PharmacoGenomics Research Center Inje University College of MedicineBusan47392Republic of Korea Department of Chemistry University of EducationHo Chi Minh City700000Viet Nam Faculty of Pharmacy Ton Duc Thang UniversityHo Chi Minh City700000Viet Nam

The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB *** strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and *** chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous *** technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics *** improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target *** on TDM,the dose would be optimized individually to achieve favorable *** is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome *** article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two ***,we discussed the advantages and disadvantages of this technique in practical *** pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was ***,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

关键词： Tuberculosis Therapeutic drug monitoring LC-MS MIPD Pharmacometabolomics Precision medicine

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