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Frontiers of Structural and Civil Engineering 2024年第6期18卷 899-917页

作者： Huong-Giang Thi hoang Hai-Van Thi MAI hoang long nguyen Hai-Bang LY University of Transport Technology Hanoi 100000Vietnam

Complex modulus(G^(*))is one of the important criteria for asphalt classification according to AASHTO M320-10,and is often used to predict the linear viscoelastic behavior of asphalt *** addition,phase angle(φ)characterizes the deformation resilience of asphalt and is used to assess the ratio between the viscous and elastic *** is thus important to quickly and accurately estimate these two *** purpose of this investigation is to construct an extreme gradient boosting(XGB)model to predict G^(*)andφof graphene oxide(GO)modified asphaltat medium and high *** data sets are gathered from previously published experiments,consisting of 357 samples for G^(*)and 339 samples forφ,and the se are used to develop the XGB model using nine inputs representing theasphalt binder *** findings show that XGB is an excellent predictor of G^(*)andφof GO-modified asphalt,evaluated by the coefficient of determination R^(2)(R^(2)=0.990 and 0.9903 for G^(*)andφ,respectively)and root mean square error(RMSE=31.499 and 1.08 for G^(*)andφ,respectively).In addition,the model’s performance is compared with experimental results and five other machine learning(ML)models to highlight its *** the final step,the Shapley additive explanations(SHAP)value analysis is conducted to assess the impact of each input and the correlation between pairs of important features on asphalt’s two physical properties.

关键词： complex modulus phase angle graphene oxide asphalt extreme gradient boosting machine learning

Prediction of falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptive neuro-fuzzy inference system

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Frontiers of Structural and Civil Engineering 2023年第5期17卷 812-826页

作者： long hoang nguyen Dung Quang VU Duc Dam nguyen Fazal E.JALAL Mudassir IQBAL Vinh The DANG Hiep Van LE Indra PRAKASH Binh Thai PHAM Faculty of Civil Engineering University of Transport TechnologyHanoi 10000Vietnam Department of Civil Engineering State Key Laboratory of Ocean EngineeringShanghai Jiao Tong UniversityShanghai 200025China Department of Civil Engineering University of Engineering and TechnologyPeshawar 25120Pakistan DDG(R)Geological Survey of India Gandhinagar 382010India

A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements,such as the modulus of the subgrade reaction(Y1)and the elastic modulus of the slab(Y2),which are crucial for assessing the structural strength of *** this study,we developed a novel hybrid artificial intelligence model,i.e.,a genetic algorithm(GA)-optimized adaptive neuro-fuzzy inference system(ANFIS-GA),to predict Y1 and Y2 based on easily determined 13 parameters of rigid *** performance of the novel ANFIS-GA model was compared to that of other benchmark models,namely logistic regression(LR)and radial basis function regression(RBFR)*** models were validated using standard statistical measures,namely,the coefficient of correlation(R),mean absolute error(MAE),and root mean square error(RMSE).The results indicated that the ANFIS-GA model was the best at predicting Y1(R=0.945)and Y2(R=0.887)compared to the LR and RBFR ***,the ANFIS-GA model can be used to accurately predict Y1 and Y2 based on easily measured parameters for the appropriate and rapid assessment of the quality and strength of pavements.

关键词： falling weight deflectometer modulus of subgrade reaction elastic modulus metaheuristic algorithms

Thornthwaite moisture index and depth of suction change under current and future climate‒An Australian study

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第5期16卷 1761-1775页

作者： Md Rajibul Karim Bikash Devkota Md Mizanur Rahman hoang Bao Khoi nguyen UniSA STEM University of South AustraliaMawson Lakes CampusMawson LakesSouth Australia5095Australia

Climate change is one of the major global challenges and it can have a significant influence on the behaviour and resilience of geotechnical *** changes in moisture content in soil lead to effective stress changes and can be accompanied by significant volume changes in reactive/expansive *** volume change leads to ground movement and can exert additional stresses on structures founded on or within a shallow depth of such *** change is likely to amplify the ground movement potential and the associated problems are likely to *** effect of atmospheric boundary interaction on soil behaviour has often been correlated to Thornthwaite moisture index(TMI).In this study,the long-term weather data and anticipated future projections for various emission scenarios were used to generate a series of TMI maps for *** changes in TMI were then correlated to the depth of suction change(H s),an important input in ground movement *** all climate scenarios considered,reductions in TMI and increases in H s values were observed.A hypothetical design scenario of a footing on expansive soil under current and future climate is *** is observed that a design that might be considered adequate under the current climate scenario,may fail under future scenarios and accommodations should be made in the design for such events.

关键词： Climate change Future prediction Thornthwaite moisture index(TMI) Characteristic surface movement Infrastructure resilience

A Complex Fuzzy LSTM Network for Temporal-Related Forecasting Problems

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Computers, Materials & Continua 2024年第9期80卷 4173-4196页

作者： nguyen Tho Thong nguyen Van Quyet Cu nguyen Giap nguyen long Giang Luong Thi Hong Lan Institute of Information Technology Vietnam Academy of Science and TechnologyHoang Quoc VietCau GiayHanoi100000Vietnam Academic Affairs Department Thai Nguyen University of EducationThai Nguyen250000Vietnam Center of Science and Technology Research and Development Thuongmai UniversityHo Tung MauCau GiayHanoi100000Vietnam Faculty of Information Technology Hanoi University of IndustryBac Tu LiemHanoi100000Vietnam

Time-stamped data is fast and constantly growing and it contains significant information thanks to the quick development ofmanagement platforms and systems based on the Internet and cutting-edge information communication *** the time series data including time series prediction has many practical *** new techniques were developed for use with various types of time series data in the prediction *** those,this work suggests a unique strategy to enhance predicting quality on time-series datasets that the timecycle matters by fusing deep learning methods with fuzzy *** order to increase forecasting accuracy on such type of time-series data,this study proposes integrating deep learning approaches with fuzzy ***,it combines the long short-termmemory network with the complex fuzzy set theory to create an innovative complex fuzzy long short-term memory model(CFLSTM).The proposed model adds a meaningful representation of the time cycle element thanks to a complex fuzzy set to advance the deep learning long short-term memory(LSTM)technique to have greater power for processing time series *** on standard common data sets and real-world data sets published in the UCI Machine Learning Repository demonstrated the proposedmodel’s utility compared to other well-known forecasting *** results of the comparisons supported the applicability of our proposed strategy for forecasting time series data.

关键词： Complex fuzzy set long short-term memory(LSTM) CFLSTM T-CFLSTM

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

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;Plong 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

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

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Carbon Energy 2024年第1期6卷 72-93页

作者： Roshan M.Bhattarai Kisan Chhetri Nghia Le Debendra Acharya Shirjana Saud Mai Cao hoang Phuong Lan nguyen Sang Jae Kim Young Sun Mok Department of Chemical Engineering Jeju National UniversityJejuRepublic of Korea Department of Nano Convergence Engineering Jeonbuk National UniversityJeonjuRepublic of Korea Regional Leading Research Center(RLRC)for Nanocarbon-based Energy Materials and Application Technology Jeonbuk National UniversityJeonjuRepublic of Korea Department of Chemistry Mississippi State UniversityStarkvilleMississippiUSA Nanomaterials and System Laboratory Department of Mechatronics EngineeringJeju National UniversityJejuRepublic of Korea

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion *** NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside *** obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode ***,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed ***,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and ***,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

关键词： carbon cloth energy conversion energy storage flexible metal embedding ultra-stable

First Trimester Preeclampsia Screening and Prevention:Perspective in Chinese Mainland

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Maternal-Fetal Medicine 2024年第2期6卷 84-91页

作者： Jiao Liu Yunyu Chen Sin Ting Tai long nguyen-hoang Kunping Li Jing Lin Xiaohong Lu Liona C.Poon Department of Obstetrics and Gynecology The Chinese University of Hong KongShatinHong Kong 999077China

Preeclampsia(PE),a multisystem disorder in pregnancy,is one of the leading causes of perinatal morbidity and mortality that poses financial and physical burdens *** PE with delivery at<37 weeks of gestation is associated with a higher risk of adverse maternal and perinatal outcomes than term PE with delivery at≥37 weeks of gestation.A myriad of first trimester screening models have been developed to identifying women at risk of preterm *** fact,the Fetal Medicine Foundation(FMF)first trimester prediction model has undergone successful internal and external *** FMF triple test enables the estimation of patient-specific risks,using Bayes theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure,uterine artery pulsatility index,and serum placental growth *** a quality control process for regular monitoring and to ensure data standardization,reliability,and accuracy is key to maintaining optimal screening *** rate of preterm PE can be reduced by 62%by using the FMF prediction model,followed by the administration of low-dose *** evidence has also demonstrated that metformin has the potential for preventing PE in patients at high-risk of the *** this article,we will summarize the existing literature on the different screening methods,different components of risk assessment,therapeutic interventions,and clinical implementation of the first trimester screening and prevention program for PE with specific considerations for Chinese mainland.

关键词： Preeclampsia Chinese population First trimester Screening Prevention

Influence of different land-use types on selected soil properties related to soil fertility in A Luoi District,Thua Thien Hue,Vietnam

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Soil Ecology Letters 2024年第1期6卷 131-140页

作者： Khoa Phuc nguyen Tan Trong Tran Huy Dinh Le Phuong Thuy nguyen Hien Thao Thi Pham Dien Thanh nguyen Ngu Huu nguyen University of Agriculture and Forestry Hue UniversityHue CityThua Thien Hue 52000Vietnam School of Biotechnology Tan Tao UniversityTan Duc ECityDuc HoaLong An850000Vietnam

Land use type affects the physicochemical properties of *** value of OM and TN is high in acacia *** acidity of soil is considered a serious constraint for *** cash crops are acacia,cassava,banana,rice and *** fertility is affected by land-use types and land management,which exacerbates soil erosion and various other forms of soil degradation in the mountainous regions of *** study was conducted in A Luoi District,Thua Thien Hue,Vietnam to identify the effects of land-use types on specific soil physicochemical characteristics related to soil *** physicochemical properties,such as organic matter(OM),total nitrogen(TN),total phosphorous(TP),and K+were significantly affected by land-use *** results showed that the soils were sandy in rice but clay loam for acacia and *** mean bulk density value of acacia soil was significantly greater than that of other *** were higher in the acacia soils than those in the rice,maize,and banana *** OM content was significantly higher in the acacia,cassava,and banana soils than those in the rice and maize *** mean of exchangeable K+in the rice soil was higher compared to those in other soils and was affected by land-use *** high exchangeable acidity content in the soils was probably due to intensive ***,both land use type and management did not affect the CEC ***,the inappropriate land use caused the disturbance of soil physicochemical properties,indicating that the conditions of rice and maize soils are becoming worse than acacia ***,lowering the intensity of cultivation,adopting incorporated soil fertility management,and applying organic fertilizer should preserve the existing conditions and enhance soil properties.

关键词： Land-use types soil characteristics soil frility suitable crop Vietnam

Investigation of crack segmentation and fast evaluation of crack propagation, based on deep learning

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Frontiers of Structural and Civil Engineering 2024年第4期18卷 516-535页

作者： Than V.TRAN H.nguyen-XUAN Xiaoying ZHUANG Institute of Photonics Leibniz University HannoverHannover 30167Germany CIRTech Institute HUTECH UniversityHo Chi Minh City 700000Vietnam College of Civil Engineering Tongji UniversityShanghai 200092China

Identifying crack and predicting crack propagation are critical processes for the risk assessment of engineering *** traditional approaches to crack modeling are faced with issues of high computational costs and excessive computing *** address this issue,we explore the potential of deep learning(DL)to increase the efficiency of crack detection and forecasting crack ***,there is no single algorithm that can fit all data sets well or can apply in all cases since specific tasks *** the paper,we present DL models for identifying cracks,especially on concrete surface images,and for predicting crack ***,SegNet and U-Net networks are used to identify concrete *** gradient descent(SGD)and adaptive moment estimation(Adam)algorithms are applied to minimize loss function during ***,time series algorithms including gated recurrent unit(GRU)and long short-term memory(LSTM)are used to predict crack *** experimental findings indicate that the U-Net is more robust and efficient than the SegNet for identifying crack segmentation and achieves the most outstanding *** evaluation of crack propagation,GRU and LSTM are used as DL models and results show good agreement with the experimental data.

关键词： deep learning crack segmentation crack propagation encoder−decoder recurrent neural network