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Investigation on cost-effective composites for CO_(2) adsorption from post-gasification residue and metal organic framework

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Journal of Environmental Sciences 2025年第2期148卷 174-187页

作者： Hong Nam nguyen Thu Phuong nguyen Phuong Thu le Quang Minh Tran thi Hai Do Trung Dung nguyen Phuong Lan Tran-nguyen Toshiki Tsubota thi Mai thanh Dinh University of Science and Technology of Hanoi Vietnam Academy of Science and Technology18 Hoang Quoc VietCau GiayHanoi 100000Vietnam Institute for Tropical Technology Vietnam Academy of Science and Technology18 Hoang Quoc VietCau GiayHanoi 100000Vietnam Faculty of Basic Science Hanoi University of Mining and Geology18 Pho VienDuc ThangNam Tu LiemHanoi 100000Vietnam Faculty of Physical and Chemical Engineering Le Quy Don Technical University236 Hoang Quoc VietBac Tu LiemHanoi 100000Vietnam Department of Mechanical Engineering Can Tho University3/2 streetCan Tho City 94000Vietnam Department of Engineering Graduate School of EngineeringKyushu Institute of Technology1-1 SensuichoTobata-kuKitakyushuFukuoka 804-8550Japan

Cost-effective CO_(2) adsorbents are gaining increasing attention as viable solutions for mitigating climate *** this study,composites were synthesized by electrochemically combining the post-gasification residue of Macadamia nut shell with copper benzene-1,3,5-tricarboxylate(CuBTC).Among the different composites synthesized,the ratio of 1:1 between biochar and CuBTC(B 1:1)demonstrated the highest CO_(2) adsorption *** controlled laboratory conditions(0°C,1 bar,without the influence of ambient moisture or CO_(2) diffusion limitations),B 1:1 achieved a CO_(2) adsorption capacity of 9.8 mmol/g,while under industrial-like conditions(25℃,1 bar,taking into account the impact of ambient moisture and CO_(2) diffusion limitations within a bed of adsorbent),it reached 6.2 mmol/*** values surpassed those reported for various advanced CO_(2) adsorbents investigated in previous *** superior performance of the B 1:1 composite can be attributed to the optimization of the number of active sites,porosity,and the preservation of the full physical and chemical surface properties of both ***,the composite exhibited a notable CO_(2)/N_(2) selectivity and improved stability under moisture *** favorable characteristics make B 1:1 a promising candidate for industrial applications.

关键词： Biochar-based composites CO_(2)adsorption CuBTC Metal organic framework Post-gasification residue

Privacy-preserving explainable AI: a survey

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Science China(Information Sciences) 2025年第1期68卷 23-56页

作者： thanh Tam nguyen thanh Trung HUYNH Zhao REN thanh Toan nguyen Phi le nguyen Hongzhi YIN Quoc Viet Hung nguyen School of Information and Communication Technology Griffith University School of Computer and Communication Sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer Science University of Bremen Faculty of Information Technology HUTECH University Department of Computer Science Hanoi University of Science and Technology School of Electrical Engineering and Computer Science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. this article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. this work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. this survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

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： 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)

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

Optimization of the in Vitro Fertilization System in Cỏ Goat Oocytes

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Open Journal of Animal Sciences 2025年第1期15卷 39-50页

作者： Van Khanh nguyen Huong thi Thu Vu Au thi Hoang Yen thi Kim Pham Dat Van le Quan Xuan Huu Lan Anh thi nguyen Huong le thi nguyen Lan Doan Pham Key Laboratory of Animal Cell Biotechnology National Institute of Animal Sciences Hanoi Vietnam

this study aimed to optimization of the in vitro fertilization system in Cỏ goat oocytes to achieve the maximum possible blastocyst development rate. In Experiment 1, we assessed the effects of IVF media on the in vitro fertilization of Cỏ goat oocytes. There was no significant difference in the cleavage, blastocyst, or hatching rates between TALP-Fert and BO-IVF media. Experiment 2 was performed to assess the concentration of sperm in the in vitro fertilization of Cỏ goat oocytes. The matured Cỏ goat oocytes were fertilized in BO-IVF for four sperm concentrations: 5 × 105, 1 × 106, 2 × 106 and 3 × 106 sperm/ml. The blastocyst rate of 2 × 106 sperm/ml and 3 × 106 sperm/ml groups was higher than that of 5 × 105 sperm/ml and 1 × 106 sperm/ml groups (P Experiment 3 was performed to assess the IVF duration on the in vitro fertilization of Cỏ goat oocytes. The matured Cỏ goat oocytes were fertilized in BO-IVF with sperm concentration of 3 × 106 sperm/ml for 18, 20, 22 and 24 h. The cleavage, blastocyst, and hatching blastocyst rates of 18 h group were lower than those of 20, 22 and 24 h groups (P 0.05). In conclusion, the matured Cỏ goat oocytes were fertilized in BO-IVF with sperm concentration of 3 × 106 sperm/ml for 20 hours, which is suitable for the in vitro Cỏ goat embryo production.

关键词： Cỏ Goat Oocytes In Vitro Fertilizaition Media In Vitro Fertilizaition Duration Sperm Concentration In Vitro Embryos

ON A NONLINEAR VOLTERRA-HAMMERSTEIN INTEGRAL EQUATION IN TWO VARIABleS

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Acta Mathematica Scientia 2013年第2期33卷 484-494页

作者： le thi Phuong Ngoc nguyen thanh Long Nhatrang Educational College 01 Nguyen Chanh Str.Nhatrang CityVietnam Department of Mathematics and Computer Science University of Natural ScienceVietnam National University Ho Chi Minh City227 Nguyen Van Cu Str.Dist. 5Ho Chi Minh CityVietnam

Using a fixed point theorem of Krasnosel＇skii type, this article proves the exis- tence of asymptotically stable solutions for a Volterra-Hammerstein integral equation in two variables.

关键词： Volterra-Hamnmrstein integral equation in two variables the fixed point theo-rem of Krasnosel'skii type contraction mapping completely continuous asymp-totically stable solution

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Green Synthesis of Silver Nanoparticles Using Plectranthus Amboinicus leaf Extract for Preparation of CMC/PVA Nanocomposite Film

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Journal of Renewable Materials 2021年第8期9卷 1393-1411页

作者： nguyen thi thanh Thuy le Hoang Huy Truong Thuy Vy nguyen thi thanh Tam Bien thiLan thanh nguyen thi My Lan Nong Lam University Ho Chi Minh City Ho Chi Minh City700000Vietnam Industrial University of Ho Chi Minh City Ho Chi Minh City700000Vietnam University of Science Viet Nam National University Ho Chi Minh CityHo Chi Minh City700000Vietnam

In the present study,the biogenic silver nanoparticles have been synthesized using aqueous leaf extract of Plectranthus amboinicus(PA),which acted as both reducing and stabilizing *** PA synthesized silver nanoparticles were blended with carboxymethyl cellulose/polyvinyl alcohol(CMC/PVA)*** prepared AgNPs as well as the biogenic AgNPs incorporated CMC/PVA films were investigated using UV-visible spectrophotometry,Fourier-transform infrared spectroscopy(FT-IR),dynamic light scattering(DLS),scanning electron microscope(SEM),and X–ray diffraction(XRD).The DLS results showed that biogenic AgNPs had the average particle size of 65.70 nm with polydispersity index of *** surface plasmon resonance of AgNPs,which was determined by UV-vis spectrophotometry,showed the value of 410.00 *** results therefore confirmed the reduction Ag+into Ag°and the formation of AgNPs in the *** SEM imaging showed that AgNPs was quasi-spherical and *** XRD peaks at 33.07°,44.19°,64.58°and 77.47°confirmed the crystalline nature and presence of *** CMC/PVA films that incorporated with AgNPs displayed best mechanical strength and morphological properties than the pure CMC/PVA *** film of CMC/PVA-AgNPs exhibited significant antibacterial activities against Bacillus spizizenii,Staphylococcus aureus,Salmonella typhi and Escherichia Coli.

关键词： Carboxymethyl cellulose antibacterial green synthesis silver nanoparticles plectranthus amboinicus polyvinyl alcohol

On the Laws of Large Numbers for Double Arrays of Independent Random Elements in Banach Spaces

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Acta Mathematica Sinica,English Series 2014年第8期30卷 1353-1364页

作者： Andrew ROSALSKY le Van thanh nguyen thi THUY Department of Statistics University of FloridaGainesville Department of Mathematics Vinh University

For a double array of independent random elements {Vmn,m ≥ 1,n ≥ 1} in a real separable Banach space,conditions are provided under which the weak and strong laws of large numbers for the double sums mi=1 nj=1Vij,m ≥ 1,n ≥ 1 are *** the identically distributed and the nonidentically distributed cases are *** the main theorems,no assumptions are made concerning the geometry of the underlying Banach *** theorems are applied to obtain Kolmogorov,Brunk–Chung,and Marcinkiewicz–Zygmund type strong laws of large numbers for double sums in Rademacher type p（1 ≤ p ≤ 2） Banach spaces.

关键词： Real separable Banach space double array of independent random elements strong and weak laws of large numbers almost sure convergence convergence in probability Rademacher type p Banach space

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A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area

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Big Earth Data 2023年第4期7卷 1005-1034页

作者： thanh Trinh Binh thanh Luu Trang Ha thi le Duong Huy nguyen Trong Van Tran thi Hai Van nguyen Khanh Quoc nguyen Lien thi nguyen Faculty of Computer Science Phenikaa UniversityYen NghiaHa DongHanoi 12116Vietnam Phenikaa Research and Technology Institute(PRATI) A&A Green Phoenix Group JSCNo.167 Hoang NganTrung HoaCau GiayHanoi 11313Vietnam Northwestern Geological Division General Department of Geology and Minerals of VietnamHanoiVietnam Youth union office Thuyloi University175 Tay SonDong DaHanoiVietnam Center of Remote Sensing and Geohazards Vietnam Institute of Geosciences and Mineral ResourcesHanoiVietnam

Landslide susceptibility maps (LSMs) are very crucial for planningpolicies in hazardous areas. However, the accuracy and reliability ofLSMs depend on available data and the selection of suitable *** study is conducted to produce LSMs by combinations of machinelearning methods and weighting techniques for Ha Giang province,Vietnam, where has limited data. In study area, we gather 11 landslideconditioning factors and establish a landslide inventory *** the weights of classes (or factors) is very important toprepare data for machine learning methods to generate LSMs. Wefrst use frequency ratio (FR) and analytic hierarchy process (AHP)techniques to generate the weights. Then, random forest (RF), supportvector machine (SVM), logistic regression (LR), and AHP methods arecombined with FR and AHP weights to yield accurate and reliableLSMs. Finally, the performance of these methods is evaluated by fivestatistical metrics, ROC and R-index. The empirical results have shownthat RF is the best method in terms of R-index and the five metrics, *** rate (0.9661), FP rate (0.0), ACC (0.9835), MAE (0.0046), and RMSE(0.0350) for this study area. this study opens the perspective of weightbasedmachine learning methods for landslide susceptibility mapping.

关键词： Landslide logistic regression random forest SvM Vietnam