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Virtual screening of flavonoids from Jatropha gossypiifolia *** potential drugs for diabetic complications

Traditional Medicine Research 2022年第2期7卷 34-42页

作者： Yudith Cañizares-Carmenate Roberto Díaz-Amador Mirtha Mayra Gonzalez-Bedia tan tran quang nhat Francisco Torrens Juan Alberto Castillo-Garit Unit of Computer-Aided Molecular“Biosilico”Discovery and Bioinformatic Research Departamento de FarmaciaFacultad de Química-FarmaciaUniversidad Central“Marta Abreu”de Las VillasSanta Clara 54830Villa ClaraCuba Departamento de Ciencias de la Computación Facultad de MatemáticaFísica y ComputaciónUniversidad CelaraCuntral“Marta Abreu”de Las VillasSanta Clara 54830Villa ClaraCuba Institut Universitari de Ciència Molecular Universitat de ValènciaEdifici d’Instituts de PaternaP.O.Box 22085ValènciaSpain. Unidad de Toxicología Experimental Universidad de Ciencias Médicas de Villa ClaraSanta Clara 50200Villa ClaraCuba.

Background:Diabetes mellitus is a chronic metabolic disease that is a risk factor for epidemic *** hyperglycemic conditions,the enzyme aldose reductase catalyzes the formation of sorbitol in the metabolism of glucose via polyols,leading to the development of diabetic ***,inhibitors of this enzyme are therapeutic targets for the prophylaxis and treatment of these ***:In this study,a generalized linear regression model was developed to analyze flavonoids-obtained from a database-that have been tested as inhibitors of aldose *** this sense,the molecular descriptors implemented in DRAGON and MATLAB software were used to determine the correlation between the chemical structure of the inhibitors and their pharmacological *** model was validated according to the Organisation for Economic Co-operation and Development Standards and subsequently used for the virtual screening of the flavonoids identified in Jatropha gossypiifolia ***:The proposed model showed a good fit for its statistical parameters(R2=0.95).In addition,it showed good predictive power(R2 ext=0.94)and robustness(Q2 LOO=0.92).The experimental chemical space wherein the predictions were reliable(domain of application)was also ***,the model was used to identify 10 flavonoids from Jatropha gossypiifolia *** candidates for natural *** with a low probability of oral absorption were identified,among which the elagic acid biflavonoid showed the greatest promise(pIC50 predicted=9.75).Conclusion:The Jatropha gossypiifolia *** harbors flavonoids with high potential as inhibitors of the aldose reductase enzyme,in which the biflavonoid ellagic acid was shown to be the most promising inhibitor of the aldose reductase enzyme,suggesting its possible use in the treatment of the late complications of diabetes mellitus.

关键词： Jatropha gossypiifolia L. aldose reductase generalized linear regression model diabetic complications

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GLOBAL BOUND ON THE GRADIENT OF SOLUTIONS TO p-LAPLACE TYPE EQUATIONS WITH MIXED DATA

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Acta Mathematica Scientia 2024年第4期44卷 1394-1414页

作者： Minh-Phuong tran The-quang tran Thanh-Nhan NGUYEN Applied Analysis Research Group Faculty of Mathematics and StatisticsTon Duc Thang UniversityHo Chi Minh CityVietnam Nguyen Huu Huan High School Thu Duc CityVietnam Group of Analysis and Applied Mathematics Department of MathematicsHo Chi Minh City University of EducationVietnam

In this paper,the study of gradient regularity for solutions of a class of elliptic problems of p-Laplace type is *** particular,we prove a global result concerning Lorentz-Morrey regularity of the non-homogeneous boundary data problem:-div((s^(2)+|▽u|^(2)p-2/2)▽u)=-div(|f|^(p-2)f)+g inΩ,u=h in■Ω,with the(sub-elliptic)degeneracy condition s∈[0,1]and with mixed data f∈L^(p)(Q;R^(n)),g∈Lp/(p-1)(Ω;R^(n))for p∈(1,n).This problem naturally arises in various applications such as dynamics of non-Newtonian fluid theory,electro-rheology,radiation of heat,plastic moulding and many *** on the idea of level-set inequality on fractional maximal distribution functions,it enables us to carry out a global regularity result of the solution via fractional maximal *** to the significance of M_(α)and its relation with Riesz potential,estimates via fractional maximal functions allow us to bound oscillations not only for solution but also its fractional derivatives of orderα.Our approach therefore has its own interest.

关键词： gradient estimates p-Laplace quasilinear elliptic equation fractional maximal operators Lorentz-Morrey spaces

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A comparative study on kinetics and dynamics of two dump truck lifting mechanisms using MATLAB simscape

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Theoretical & Applied Mechanics Letters 2024年第2期14卷 146-156页

作者： Thong Duc Hong Minh quang Pham Son Cong tran Lam quang tran Truong Thanh Nguyen Faculty of transportation Engineering Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam Vietnam National University Ho Chi Minh City(VNU-HCM) Ho Chi Minh City 700000Vietnam Industrial Maintenance Training Center Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam

In this paper,two lifting mechanism models with opposing placements,which use the same hydraulic hoist model and have the same angle of 50°,have been *** mechanical and hydraulic simulation models are established using MATLAB Simscape to analyze their kinetics and dynamics in the lifting and holding *** simulation findings are compared to the analytical calculation results in the steady state,and both methods show good *** the early lifting stage,Model 1 produces greater force and discharges goods in the container faster than Model ***,Model 2 reaches a higher force and ejects goods from the container cleaner than its counterpart at the end lifting *** established simulation models can consider the effects of dynamic loads due to inertial moments and forces generated during the system *** is crucial in studying,designing,and optimizing the structure of hydraulic-mechanical systems.

关键词： Dump truck Lifting mechanism Hydraulic MATLAB Simscape Kinetic dynamic analysis

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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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An In-Depth Analysis of Road Fatal Crash Patterns and Discussions in Ho Chi Minh City

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Journal of Traffic and transportation Engineering 2024年第3期12卷 141-150页

作者： Vuong tran quang Faculty of Civil Engineering Campus in Ho Chi Minh CityUniversity of Transport and CommunicationsHo Chi MinhVietnam

Although there has been a slight decrease in road traffic crashes, fatalities, and injuries in recent years, HCMC (Ho Chi Minh City) will continue to encounter challenges in mitigating and preventing road crashes. This study analyzes road crash data from the past five years, obtained from the Road-Railway Police Bureau (PC08) and TSB (Traffic Safety Board) in HCMC. This analysis gives us valuable insights into road crash patterns, characteristics, and underlying causes. This comprehensive understanding serves as a scientific foundation for developing cohesive strategies and implementing targeted solutions to address road traffic safety issues more effectively in the future.

关键词： Traffic safety safety policies fatal crash patterns

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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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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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Tungsten-based nanocatalysts with different structures for visible light responsive photocatalytic degradation of bisphenol A

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Journal of Environmental Sciences 2024年第5期139卷 569-588页

作者： Hai Bang Truong Thi Thu Loan Doan Nguyen Tien Hoang Nguyen Van Tam Minh Kim Nguyen Le Gia Trung Jin Seog Gwag Nguyen Tien tran Optical Materials Research Group Science and Technology Advanced InstituteVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Applied Technology School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam The University of Da Nang University of Science and Technology54 Nguyen Luong BangDa NangViet Nam The University of Da Nang University of Science and Education459 Ton Duc Thang St.Lien ChieuDa Nang 550000Viet Nam Institute of Veterinary Science and Technology 31ha zoneTrau QuyGia LamHa Noi 12400Viet Nam Department of Physics Yeungnam UniversityGyeongsanGyeongbuk 38541Republic of Korea Center for Advanced Chemistry Institute of Research and DevelopmentDuy Tan University03 Quang TrungDa Nang 550000Viet Nam Faculty of Natural Sciences Duy Tan University03 Quang TrungDa Nang 550000Viet Nam

Environmental pollution,such as water contamination,is a critical issue that must be absolutely ***,three different morphologies of tungsten-based photocatalysts(WO_(3)nanorods,WO_(3)/WS_(2)nanobricks,WO_(3)/WS_(2)nanorods)are made using a simple hydrothermal method by changing the solvents(H_(2)O,DMF,aqueous HCl solution).The as-prepared nanocatalysts have excellent thermal stability,large porosity,and high *** results show all materials have good photocatalytic activity in aqueous media,with WO_(3)/WS_(2)nanorods(NRs)having the best activity in the photodegradation of bisphenol A(BPA)under visible-light *** may originate from increased migration of charge carriers and effective prevention of electron–hole recombination in WO_(3)/WS_(2)NRs,whereby this photocatalyst is able to generate more reactive·OH and·O_(2)^(–)species,leading to greater photocatalytic *** 99.6% of BPA is photodegraded within 60 min when using 1.5 g/L WO_(3)/WS_(2)NRs and 5.0 mg/L BPA at pH ***,the optimal conditions(pH,catalyst dosage,initial BPA concentration)for WO_(3)/WS_(2)NRs are also elaborately *** rod-like heterostructures are expressed as potential catalysts with excellent photostability,efficient reusability,and highly active effectivity in different types of *** particular,the removal efficiency of BPA by WO_(3)/WS_(2)NRs reduces by only 1.5% after five recycling runs and even reaches 89.1%in contaminated lake *** study provides promising insights for the nearly complete removal of BPA from wastewater or different water resources,which is advantageous to various applications in environmental remediation.

关键词： Photodegradation Bisphenol A Tungsten-based nanocatalyst Structure Nanorod

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Novel Soft ComputingModel for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on the Bagging and Sibling of Extra Trees Models

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Computer Modeling in Engineering & Sciences 2023年第3期134卷 2227-2246页

作者： quang-Hieu tran Hoang Nguyen Xuan-Nam Bui Department of Surface Mining Mining FacultyHanoi University of Mining and GeologyHanoi100000Vietnam Innovations for Sustainable and Responsible Mining(ISRM)Research Group Hanoi University of Mining and GeologyHanoi100000Vietnam

This study considered and predicted blast-induced ground vibration(PPV)in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning ***,four machine learning algorithms,including support vector regression(SVR),extra trees(ExTree),K-nearest neighbors(KNN),and decision tree regression(DTR),were used as the base models for the purposes of combination and PPV initial *** bagging regressor(BA)was then applied to combine these base models with the efforts of variance reduction,overfitting elimination,and generating more robust predictive models,abbreviated as BA-ExTree,BAKNN,BA-SVR,and *** is emphasized that the ExTree model has not been considered for predicting blastinduced ground vibration before,and the bagging of ExTree is an innovation aiming to improve the accuracy of the inherently ExTree model,as *** addition,two empirical models(i.e.,USBM and Ambraseys)were also treated and compared with the bagging models to gain a comprehensive *** this aim,we collected 300 blasting events with different parameters at the Sin Quyen copper mine(Vietnam),and the produced PPV values were also *** were then compiled as the dataset to develop the PPV predictive *** results revealed that the bagging models provided better performance than the empirical models,except for the BA-DTR *** those,the BA-ExTree is the best model with the highest accuracy(i.e.,88.8%).Whereas,the empirical models only provided the accuracy from 73.6%–76%.The details of comparisons and assessments were also presented in this study.

关键词： Mine blasting blast-induced ground vibration environmentally friendly blasting peak particle velocity bagging extra trees

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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

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