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Tree species diversity and utilities in a contracting lowland hillside rainforest fragment in Central Vietnam

Forest Ecosystems 2017年第3期4卷 182-200页

作者： yen thi van Roland Cochard Hue University of Agriculture and Forestry Hue University Institute of Integrative Biology Swiss Federal Institute of Technology

Background： Within the highly bio-diverse ‘Northern Vietnam Lowland Rain Forests Ecoregion＇ only small, and mostly highly modified forestlands persist within vast exotic-species plantations. The aim of this study was to elucidate vegetation patterns of a secondary hillside rainforest remnant（elevation 120–330 m, 76 ha） as an outcome of natural processes, and anthropogenic processes linked to changing forest ***： In the rainforest remnant tree species and various bio-physical parameters（relating to soils and terrain）were surveyed on forty 20 m × 20 m sized plots. The forest＇s vegetation patterns and tree diversity were analysed using dendrograms, canonical correspondence analysis, and other statistical ***： Forest tree species richness was high（172 in the survey, 94 per hectare）, including many endemic species（〉16%; some recently described）. Vegetation patterns and diversity were largely explained by topography, with colline/sub-montane species present mainly along hillside ridges, and lowland/humid-tropical species predominant on lower slopes. Scarcity of high-value timber species reflected past logging, whereas abundance of light-demanding species, and species valued for fruits, provided evidence of human-aided forest restoration and ‘enrichment＇ in terms of useful trees. Exhaustion of sought-after forest products, and decreasing appreciation of non-wood products concurred with further encroachment of exotic plantations in between 2010 and 2015. Regeneration of rare tree species was reduced probably due to forest ***： Despite long-term anthropogenic influences, remnant forests in the lowlands of Vietnam can harbor high plant biodiversity, including many endangered species. Various successive future changes（vanishing species, generalist dominance, and associated forest structural-qualitative changes） are, however, expected to occur in smal forest *** forest biodiversity can only be maintained if forest fragments m

关键词： Secondary evergreen monsoon forest Floristic patterns Tree species richness Timber NTFP Biodiversity conservation

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Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh thi Bui Dam Duc Nguyen Hiep van Le Indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

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Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh thi Bui Hiep van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

this study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).this combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

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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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Investigation of Polymorphisms in Coding Region of OsHKT1in Relation to Salinity in Rice

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Rice science 2016年第6期23卷 334-338页

作者： pham quynh-hoa tran xuan-an nguyen thi-nha-trang tran thi-thuy-anh hoang hai-yen nguyen thi-hong-van tang thi-hanh do thi-phuc Faculty of Biology VNU University of ScienceHanoi334 Nguyen TraiThanh XuanHanoiVietnam Faculty of Agronomy Vietnam National University of AgricultureNgo Xuan Quang StreetTrau QuyGia LamHanoiVietnam

Rice （Oryza sativa） is sensitive to salinity, but the salt tolerance level differs among cultivars,which might result from natural variations in the genes that are responsible for salt tolerance. High-affinitypotassium transporter （HKTs） has been proven to be involved in salt tolerance in plants. Therefore, wescreened for natural nucleotide polymorphism in the coding sequence of OsHKT1, which encodes the HKTprotein in eight Vietnamese rice cultivars differing in salt tolerance level. In total, seven nucleotidesubstitutions in coding sequence of OsHKT1 were found, including two non-synonymous and five synonymoussubstitutions. Further analysis revealed that these two non-synonymous nucleotide substitutions （G50Tand T1209A） caused changes in amino acids （Gly17Val and Asp403Glu） at signal peptide and the loop ofthe sixth transmembrane domain, respectively. To assess the potential effect of these substitutions on theprotein function, the 3D structure of HKT protein variants was modelled by using PHYRE2 webserver. Theresults showed that no difference was observed when compared those predicted 3D structure of HKTprotein variants with each other. In addition, the codon bias of synonymous substitutions cannot clearlyshow correlation with salt tolerance level. It might be interesting to further investigate the functional roles ofdetected non-synonymous substitutions as it might correlate to salt tolerance in rice.

关键词： polymorphism salt stress OsHKT1 gene rice

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Impacts of optimization strategies on performance,power/energy consumption of a GPU based parallel reduction

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Journal of Central South University 2017年第11期24卷 2624-2637页

作者： Phuong thi yen Lee Deok-Young Lee Jeong-Gun Smart Computing Lab. Department of Computer EngineeringHallym UniversityChuncheon 24252Korea College of General Education Hallym UniversityChuncheon 24252Korea

In the era of modern high performance computing, GPUs have been considered an excellent accelerator for general purpose data-intensive parallel applications. To achieve application speedup from GPUs, many of performance-oriented optimization techniques have been proposed. However, in order to satisfy the recent trend of power and energy consumptions, power/energy-aware optimization of GPUs needs to be investigated with detailed analysis in addition to the performance-oriented optimization. In this work, in order to explore the impact of various optimization strategies on GPU performance, power and energy consumptions, we evaluate performance and power/energy consumption of a well-known application running on different commercial GPU devices with the different optimization strategies. In particular, in order to see the more generalized performance and power consumption patterns of GPU based accelerations, our evaluations are performed with three different Nvdia GPU generations(Fermi, Kepler and Maxwell architectures), various core clock frequencies and memory clock frequencies. We analyze how a GPU kernel execution is affected by optimization and what GPU architectural factors have much impact on its performance and power/energy consumption. this paper also categorizes which optimization technique primarily improves which metric(i.e., performance, power or energy efficiency). Furthermore, voltage frequency scaling(VFS) is also applied to examine the effect of changing a clock frequency on these metrics. In general, our work shows that effective GPU optimization strategies can improve the application performance significantly without increasing power and energy consumption.

关键词： parallel reduction GPU code optimization power energy voltage frequency scaling

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Successful containment of a COVID-19 outbreak in Bach Mai Hospital by prompt and decisive responses

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Asian Pacific Journal of Tropical Medicine 2021年第5期14卷 234-235页

作者： van Minh Hoang thi Phuong Thao Tran thi Ngoc Phuong Nguyen thi Hai yen Nguyen Quang Tuan Nguyen Hanoi University of Public Health HanoiVietnam Bach Mai Hospital HanoiVietnam

In low-and middle-income countries,tertiary care hospitals frequently face an extremely heavy workload and shoulder an even heavier burden during the COVID-19 *** Mai Hospital(BMH),one of the leading tertiary hospitals in Vietnam,is on the frontline in the fierce battle against *** letter aims to describe how BMH tackles the COVID-19 outbreak in the hospitallevel battle,which could support policymakers in time-management and well-preparation for this unpredictable pandemic.

关键词： prompt income policy

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Application of extreme gradient boosting in predicting the viscoelastic characteristics of graphene oxide modified asphalt at medium and high temperatures

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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

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Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques

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Geoscience Frontiers 2021年第3期12卷 333-342页

作者： Binh Thai Pham Abolfazl Jaafari Tran van Phong Hoang Phan Hai yen Tran thi Tuyen Vu van Luong Huu Duy Nguyen Hiep van Le Loke Kok Foong University of Transport Technology Ha Noi 100000Viet Nam Research Institute of Forests and Rangelands Agricultural ResearchEducation and Extension Organization(AREEO)TehranIran Institute of Geological Sciences Vietnam Academy of Sciences and Technology84 Chua Lang StreetDong daHa NoiViet Nam Department of Geography School of Social EducationVinh UniversityViet Nam Department of Resource and Environment Management School of Agriculture and ResourcesVinh UniversityViet Nam Faculty of Geography VNU University of Science334 Nguyen TraiHa NoiViet Nam Institute of Research and Development Duy Tan UniversityDa Nang 550000Viet Nam Department for Management of Science and Technology Development Ton Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam

Improving the accuracy of flood prediction and mapping is crucial for reducing damage resulting from flood *** this study,we proposed and validated three ensemble models based on the Best First Decision Tree(BFT)and the Bagging(Bagging-BFT),Decorate(Bagging-BFT),and Random Subspace(RSS-BFT)ensemble learning techniques for an improved prediction of flood susceptibility in a spatially-explicit manner.A total number of 126 historical flood events from the Nghe An Province(Vietnam)were connected to a set of 10 flood influencing factors(slope,elevation,aspect,curvature,river density,distance from rivers,flow direction,geology,soil,and land use)for generating the training and validation *** models were validated via several performance metrics that demonstrated the capability of all three ensemble models in elucidating the underlying pattern of flood occurrences within the research area and predicting the probability of future flood *** on the Area Under the receiver operating characteristic Curve(AUC),the ensemble Decorate-BFT model that achieved an AUC value of 0.989 was identified as the superior model over the RSS-BFT(AUC=0.982)and Bagging-BFT(AUC=0.967)models.A comparison between the performance of the models and the models previously reported in the literature confirmed that our ensemble models provided a reliable estimate of flood susceptibilities and their resulting susceptibility maps are trustful for flood early warning systems as well as development of mitigation plans.

关键词： Machine learning Ensemble learners Hybrid modeling

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Does green growth in E-7 countries depend on economic policy uncertainty,institutional quality,and renewable energy?Evidence from quantile-based regression

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Geoscience Frontiers 2023年第6期14卷 224-233页

作者： Yongzhong Jiang Arshian Sharif Ahsan Anwar Phan The Cong Bawani Lelchumanan Vu thi yen Nguyen thi Thuy Vinh College of Management Science Chengdu University of TechnologyChengdu 610059China Department of Economics and Finance Sunway Business SchoolSunway UniversitySubang JayaMalaysia University of Economics and Human Sciences in Warsaw WarsawPoland Faculty of Management Sciences Department of Business AdministrationILMA UniversityKarachiPakistan Faculty of Economics Thuongmai UniversityHanoiViet Nam Foreign Trade University HanoiViet Nam

Environmental degradation is one of the most debatable topics at international forums and it is considered a prime concern for the entire ***,researchers and policymakers have turned their attention from conventional economic growth to green *** the existing literature has discussed several determinants of green growth,the impact of economic policy uncertainty(EPU),renewable energy consumption(RENE),and institutional quality(IQ)on green growth(GGDP)is relatively ***,this study is the earliest attempt to investigate the impact of EPU,IQ,and RENE on GGDP for emerging seven(E-7)countries from 1996 to *** doing so,we apply panel quantile regression(PQR).The empirical findings delineate that EPU has a negative impact on GGDP,whereas IQ and RENE enhance the GGDP in E-7 *** on the outcomes,this study suggests policy implications for achieving targets of the SDG 07,SDG 08,SDG 13,and SDG *** governments of these countries can achieve higher GGDP by ensuring political stability and reliable macroeconomic policies and through making such flexible policies that can easily control or address unpredictable future economic issues.

关键词： Green growth Economic policy uncertainty Institutional quality Renewable energy Sustainable development goals

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