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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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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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A concise review on surface and structural modification of porous zeolite scaffold for enhanced hydrogen storage

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Chinese Journal of Chemical Engineering 2024年第6期70卷 33-53页

作者： B.A.Abdulkadir R.S.R.Mohd Zaki A.T.Abd Wahab S.N.Miskan Anh-tam nguyen Dai-Viet N.Vo h.D.Setiabudi Centre for Research in Advanced Fluid&Processes Universiti Malaysia Pahang Al-Sultan AbdullahLebuh Persiaran Tun Khalil YaakobGambangPahang 26300Malaysia Faculty of Chemical&Process Engineering Technology Universiti Malaysia Pahang Al-Sultan AbdullahLebuh Persiaran Tun Khalil YaakobGambangPahang 26300Malaysia Center of Excellence for Green Energy and Environmental Nanomaterials(CE@GrEEN) Nguyen Tat Thanh University300A Nguyen Tat ThanhDistrict 4Ho Chi Minh City 755414Viet Nam

Investigating zeolites as hydrogen storage scaffolds is imperative due to their porous nature and favorable physicochemical ***,the storage capacity of the unmodified zeolites has been rather unsatisfactory(0.224%-1.082%(mass))compared to its modified ***,the contemporary focus on enhancing hydrogen storage capacities has led to significant attention towards the utilization of modified zeolites,with studies exploring surface modifications through physical and chemical treatments,as well as the integration of various active *** enhanced hydrogen storage properties of zeolites are attributed to the presence of aluminosilicates from alkaline and alkaline-earth metals,resulting in increased storage capacity through interactions with the charge density of these ***,there is a great demand to critically review their role such as well-defined topology,pore structure,good thermal stability,and tunable hydrophilicity in enhanced hydrogen *** article aimed to critically review the recent research findings based on modified zeolite performance for enhanced hydrogen *** of the factors affecting the hydrogen storage capacities of zeolites that can affect the rate of reaction and the stability of the adsorbent,like pressure,structure,and morphology were studied,and ***,future perspectives,recommendations,and directions for modified zeolites were discussed.

关键词： Zeolites hydrogen storage Surface modification Adsorption Active metal

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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

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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

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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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ALS-linked C9orf72 dipeptide repeats inhibit starvation-induced autophagy through modulating BCL2–BECN1 interaction

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Acta Pharmaceutica Sinica B 2024年第5期14卷 2026-2038页

作者： Shiqiang Xu Qilian Ma Junwen Shen Ningning Li Shan Sun Nana Wang Yang Chen Chunsheng Dong Kin Yip tam Jochen h.M.Prehn hongfeng Wang Zheng Ying Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences Soochow UniversitySuzhou 215123China MOE Key Laboratory of Geriatric Diseases and Immunology College of Pharmaceutical SciencesSuzhou Medical College of Soochow UniversitySuzhou 215123China Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development Soochow UniversitySuzhou 215123China Dept.of Physiology&Medical Physics and FUTURE-NEURO Research Centre Royal College of Surgeons in IrelandDublin D02 YN77Ireland Faculty of health Sciences University of MacaoTaipaMacao 999078China Insititutes of Biology and Medical Science Soochow UniversitySuzhou 215123China

Growing evidences indicate that dysfunction of autophagy contributes to the disease pathogenesis of amyotrophic lateral sclerosis(ALS)and frontotemporal dementia(FTD),two neurodegenerative *** GGGGCC·GGCCCC repeat RNA expansion in chromosome 9 open reading frame 72(C9orf72)is the most genetic cause of both ALS and *** to the previous studies,GGGGCC·GGCCCC repeat undergoes the unconventional repeat-associated non-ATG translation,which produces dipeptide repeat(DPR)*** there is a growing understanding that C9orf72 DPRs have a strong ability to harm neurons and induce C9orf72-linked ALS/FTD,whether these DPRs can affect autophagy remains *** the present study,we find that poly-GR and poly-PR,two arginine-containing DPRs which display the most cytotoxic properties according to the previous studies,strongly inhibit starvation-induced ***,our data indicate that arginine-rich DPRs enhance the interaction between BCL2 and BECN1/Beclin 1 by inhibiting BCL2 phosphorylation,therefore they can impair autophagic clearance of neurodegenerative disease-associated protein aggregates under starvation condition in ***,our study not only highlights the role of C9orf72 DPR in autophagy dysfunction,but also provides novel insight that pharmacological intervention of autophagy using SW063058,a small molecule compound that can disrupt the interaction between BECN1 and BCL2,may reduce C9orf72 DPR-induced neurotoxicity.

关键词： Amyotrophic lateral sclerosis Frontotemporal dementia C9orf72 Autophagy BCL2 BECN1/Beclin 1 Dipeptide repeat Neurodegeneration

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Photocatalytic degradation of antibiotic sulfamethizole by visible light activated perovskite LaZnO_(3)

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Journal of Environmental Sciences 2024年第10期144卷 212-224页

作者： Bui The huy XCuong nguyen Vu Khac hoang Bui nguyen Ngoc Tri Iqra Rabani Nhu hoa Thi Tran Quang Viet Ly hai Bang Truong Major of Biomedical Engineering Division of Smart HealthcareCollege of Information Technology and ConvergencePukyong National UniversityBusan 48513Korea Center for Advanced Chemistry Institute of Research and DevelopmentDuy Tan UniversityDa Nang 550000Viet Nam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDa Nang 550000Viet Nam Department of Environment and Energy Sejong UniversitySeoul 05006Korea Lab of Computational Chemistry and Modelling Department of ChemistryFaculty of Natural SciencesQuy Nhon UniversityQuy NhonViet Nam Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Korea Faculty of Materials Science and Technology University of ScienceHo Chi Minh City 700000Viet Nam Vietnam National University Ho Chi Minh City 700000Viet Nam Department of Environmental Engineering Seoul National University of Science and TechnologySeoul 01811Korea 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

In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light *** was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO3 at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·*** integration of RP-hPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 *** toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation *** visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.

关键词： Perovskite Antibiotics Photocatalysis Density functional theory Toxicity

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Comparison of Treatment Efficacy of Different Number of Botulinum Toxin Type A Injection Sites for Crow's Feet Lines: A Single-Center Retrospective Clinical Study in Vietnam

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International Journal of Dermatology and Venereology 2024年第3期7卷 131-136页

作者： nguyen Quang M. Le Thi M. Duong Phuc h. Vu Thai h. Le huu D. Department of Stem Cell Research and Application National Hospital of Dermatology and Venereology Hanoi 100000 Viet Nam Department of healthcare Activity Direction National Hospital of Dermatology and Venereology Hanoi 100000 Viet Nam Department of Dermatology Hanoi Medical University Hanoi 100000 Viet Nam

Objective: Botulinum toxin type A is frequently used to treat crow's feet lines. however, the optimal dose and injection sites are still controversial. The objective of this study was to compare the efficacy of different botulinum toxin type A injection patterns for the treatment of crow's feet. Methods: This single-center, retrospective, clinical study was conducted at the National hospital of Dermatology and Venereology from July 2020 to December 2020. Data on 60 patients with crow's feet were collected and divided into 2 groups (3- or 4-point intramuscular injection) according to the intramuscular injection technique the patients received. The treatment efficacy was assessed based on the changes in the Crow's Feet Grading Scale score at 1, 4, and 16 weeks after treatment. Repeated measures analysis of variance was used for the assessment of changes in scores over time between the two groups. Results: After treatment, the average Crow's Feet Grading Scale score was significantly decreased compared with the pretreatment score at all timepoints (1, 4, and 16 weeks) in both states (dynamic: For 3-point intramuscular injection technique, 1 week: 1.90 ± 0.71 vs. 2.97 ± 0.56; 4 weeks: 1.87 ± 0.68 vs. 2.97 ± 0.56; 16 weeks: 2.60 ± 0.67 vs. 2.97 ± 0.56. For 4-point intramuscular injection technique, 1 week: 1.73 ± 0.83 vs. 3.03 ± 0.49; 4 weeks: 1.73 ± 0.74 vs. 3.03 ± 0.49; 16 weeks: 2.57 ± 0.68 vs. 3.03 ± 0.49, all P hnique, 1 week: 1.20 ± 0.89 vs. 2.20 ± 0.85; 4 weeks: 1.20 ± 0.89 vs. 2.20 ± 0.85; 16 weeks: 1.87 ± 0.97 vs. 2.20 ± 0.85; For 4-point intramuscular injection technique, 1 week: 1.50 ± 0.86 vs. 2.30 ± 0.84; 4 weeks: 1.33 ± 0.84 vs. 2.30 ± 0.84; 16 weeks: 1.87 ± 0.97 vs. 2.30 ± 0.84. All P he average subjective patient-rated satisfaction scores after treatment were significantly higher in the 4-point injection group than in the 3-point injection group (P = 0.028). The adverse events were pos

关键词： botulinum toxin type A crow's feet lines dose injection site

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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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