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Experimental investigation of enhancement of carbon dioxide foam stability, pore plugging, and oil recovery in the presence of silica nanoparticles

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Petroleum Science 2019年第2期16卷 344-356页

作者： Abdul Rahim Risal muhammad a.manan Nurudeen Yekeen Nur Bashirah Azli Ali Mohamed Samin Xin Kun Tan Department of Petroleum Engineering Faculty of Petroleum and Renewable Energy Engineering Universiti Teknologi Malaysia Institute of Hydrocarbon Recovery Universiti Teknologi PETRONAS

The influence of surface-modified silica(SiO_2) nanoparticles on the stability and pore plugging properties of foams in porous media was investigated in this study. The pore plugging ability of foams was estimated from the pressure drop induced during foam propagation in porous media. The results clearly showed that the modified Si02 nanoparticlestabilized foam exhibited high stability, and the differential pressure increased in porous media by as much as three times.The addition of SiO_2 nanoparticles to the foaming dispersions further mitigated the adverse effect of oil toward the foam pore plugging ability. Consequently, the oil recovery increased in the presence of nanoparticles by approximately 15%during the enhanced oil recovery experiment. The study suggested that the addition of surface-modified silica nanoparticles to the surfactant solution could considerably improve the conventional foam stability and pore plugging performance in porous media.

关键词： Foam Pore plugging Surface-modified nanoparticle Enhanced oil recovery

The effect of nanosilica sizes in the presence of nonionic TX100 surfactant on CO_(2)foam flooding

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Petroleum Research 2022年第1期7卷 62-76页

作者： Suriatie Mat Yusuf Radzuan Junin Mohd Akhmal Muhamad Sidek muhammad Amanan Mohd Fazril Irfan Ahmad Fuad Mohd Zaidi Jaafar Effah Yahya Nor Roslina Rosli Department of Petroleum Engineering School of Chemical and Energy EngineeringFaculty of EngineeringUniversiti Teknologi Malaysia81310Johor BahruMalaysia Institute for Oil and Gas Universiti Teknologi Malaysia81310Johor BahruMalaysia School of Chemical Engineering College of EngineeringUniversiti Teknologi MARA40450 Shah AlamSelangorMalaysia

The aim of this research is to study the effect of hydrophilic silica nanoparticles,sizes as CO_(2) foam stabilizer in the presence of nonionic TX100 surfactant.Two nanosilica sizes,15 and 70 nm,have been examined thoroughly.Physisorption of TX100 on silica nanoparticles(nanosilica)was characterized by adsorption isotherm and surface tension measurement,while CO_(2) foams stability was quantified based on their foamability,foam stability,particle partitioning in the foams,and bubble sizes.Results show that direct contact of TX100 with nanosilica does altered the wettability of hydrophilic nanosilica surface,enable them to lengthen CO_(2) foams life at certain surfactant and nanoparticles concentrations.For 15 nm nanosilica,CO_(2) foam stability shows excellent performance at 0.1 and 0.5 wt%TX100 concentrations.As for 70 nm nanosilica,CO_(2) foam demonstrates longer lifetime at much lower TX100 concentration,0.01 wt%.Without the presence of TX100,CO_(2) foams exhibit undesirable lifetime performances for both nanosilica sizes.Nanosilica partitioning in CO_(2) foams structures demonstrate consistent relation with contact angle measurement.Estimated bubble sizes shows insignificant effect on CO_(2) foams life.With the assists of nanosilica and TX100,enhanced oil recovery via CO_(2) foam injection succeeds in increasing oil production by 13e22%of original oil-in-place(OOIP).

关键词： Nanoparticle sizes Adsorption Nonionic surfactant TX100 surfactant Foamability CO_(2)foam stability CO_(2)foam flooding EOR

Enhancing PDF Malware Detection through Logistic Model Trees

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Computers, Materials & Continua 2024年第3期78卷 3645-3663页

作者： muhammad Binsawad Department of Information Systems King Abdulaziz UniversityP.O.Box 80217Jeddah21589Saudi Arabia

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection approaches.The study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial methodologies.The article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model Tree.Using a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and Stochastic Gradient Descent.Beyond traditional structural and JavaScript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware detection.The use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus detection.The paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the sector.The results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

关键词： Malware detection PDF files logistic model tree feature selection cybersecurity

Progress in electrocatalytic nitrate reduction for green energy: Catalyst engineering, mechanisms, and techno-economic feasibility

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Journal of Energy Chemistry 2024年第8期95卷 380-406页

作者： Hafiz muhammad Adeel Sharif Hafiz muhammad Farooq Khan Sadeeq Ullah Yuwei Wang muhammad Ahmad Bo Yang Changping Li muhammad Bilal Asif Research Center for Eco-Environmental Engineering Dongguan University of Technology College of Chemistry and Engineering Shenzhen University FMH College of Medicine and Dentistry School of Environment and Civil Engineering Research Center for Eco-Environment Engineering Dongguan University of Technology Advanced Membranes and Porous Materials Center (AMPMC) Physical Sciences and Engineering (PSE) King Abdullah University of Science and Technology (KAUST)

Ammonia（NH3） is an irreplaceable chemical that has been widely demanded to keep the sustainable development of modern society.However,its industrial production consumes a huge amount of energy and releases extraordinary greenhouse gases（GHGs）,leading to various environmental issues.Achieving the green production of ammonia is a great challenge,which has been extensively pursued in the last decade.In this review,the most promising strategy,electrochemical nitrate reduction reaction（e-NO3RR）,is comprehensively investigated to give a complete understanding of its development and mechanism and provide guidance for future directions.However,owing to the complex reactions and limited selectivity,a comprehensive understanding of the mechanisms is crucial to further development and commercialization.Moreover,NO3-RR is a promising strategy for simultaneous water treatment and NH3production.A detailed overview of the recent progress in NO3-RR for NH3production with nontransition and transition metal based electrocatalysts is summarized.In addition,critical advanced techniques,future challenges,and prospects are discussed to guide future research on transition metal-based catalysts for commercial NH3synthesis by NO3-reduction.

关键词： Ammonia synthesis Electrolysis Green energy Nitrate reduction Pollution to solution Transition metal catalysts

An indicator model for assessing community resilience to the COVID-19 pandemic and its validation: A case study in Hong Kong

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Journal of Safety Science and Resilience 2024年第2期5卷 222-234页

作者： Nan Liao muhammad Nawaz Departnent of Geography Faculty Art and Social SciencesSingapore 65166666Singapore

The COVID-19 outbreak had a significant negative impact on the world,and the fifth wave of COVID-19 in Hong Kong brought a considerable shock to Chinese society.There is a growing call for more resilient cities.However,empirical evidence and validation of modeling studies of resilience indicators for urban community responses to the COVID-19 pandemic still need to be provided.In this study,a resilience assessment indicator model comprising 4 subsystems,7 indicators,and 12 variables was developed to assess the resilience of Hong Kong communities in response to COVID-19(i.e.,Resilience Index).Furthermore,this study utilized regression models such as geographically weighted regression(GWR)and multiscale GWR(MGWR)to validate the resilience model proposed in this study at the model and variable levels.In the regression model,the Resilience Index and the individual variables in the resilience model are explanatory variables,and the outcomes of the COVID-19 pandemic(confirmed cases,confirmation rate,discharged cases,discharge rate)are dependent variables.The results showed that:(i)the resilience of Hong Kong communities to the COvID-19 pandemic was not strong in general and showed some clustered spatial distribution characteristics;(i)the validation results at the model level showed that the Resilience Index did not explain the consequences of the COvID-19 pandemic to a high degree;(ii)the validation results at the variable level showed that the MGWR model was the best at identifying the relationships between explanatory variables and the dependent variable;and(iv)compared with the model-level assessment results,the variable-level assessment explained the consequences of the COvID-19 pandemic better than the model level assessment results.The above analysis and the spatial distribution maps of the resilience variables can provide empirically based and targeted insights for policymakers.

关键词： Resilience Community resilience CoVID-19pandemic Resilience assessment indicator model Resilience model validation MGWR

Consequences of Rényi entropy on the thermal geometries and Hawking evaporation of topological dyonic dilaton black hole

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Communications in Theoretical Physics 2024年第2期76卷 102-110页

作者： muhammad Yasir Xia Tiecheng muhammad Usman Shahid Chaudhary Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai200444China Department of Natural Sciences and Humanities University of Engineering and Technology LahoreNew CampusPakistan

The thermodynamics of black holes(BHs)has had a profound impact on theoretical physics,providing insight into the nature of gravity,the quantum structure of spacetime and the fundamental laws governing the Universe.In this study,we investigate thermal geometries and Hawking evaporation of the recently proposed topological dyonic dilaton BH in anti-de Sitter(Ad S)space.We consider Rényi entropy and obtain the relations for pressure,heat capacity and Gibbs free energy and observe that the Rényi parameter and dilaton field play a vital role in the phase transition and stability of the BH.Moreover,we use Weinhold,Ruppeiner and Hendi Panahiyah Eslam Momennia models to evaluate the scalar curvature of the BH and find out that the divergence points of the scalar curvature coincides with the zero of specific heat.Finally,using Stefan–Boltzmann law,we determine that the BH without a dilaton field evaporates far more quickly compared to the dilaton BH in Ad S space.

关键词： topological dyonic dilaton black hole phase transition thermal geometry Hawking evaporation

Depositional and Bio-Sequence Stratigraphic Framework of Late Cretaceous Kawagarh Formation,Kala-Chitta Range,Pakistan:Equivalent of Gurpi Formation(Iran)

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Journal of Earth Science 2024年第2期35卷 332-348页

作者： muhammad Awais Bilal Wadood muhammad Ishaq muhammad Bilal Zeeshan Zafar Nasar Khan Aminullah Khan Department of Geology University of SwabiAnbar-SwabiKhyber PakhtunkhwaSwabi23561Pakistan Department of Earth Environmental and Resources SciencesUniversity of Naples FedericoⅡNaples80126Italy State Key Laboratory of Continental Dynamics Department of GeologyNorthwest UniversityXi’an710069China National Centre of Excellence in Geology University of PeshawarPeshawarKhyber Pakhtunkhwa25130Pakistan Department of Geological Engineering School of Earth Sciences and EngineeringXi’an Shiyou UniversityXi’an610500China Department of Petroleum Geology and Engineering School of Earth ResourcesChina University of GeosciencesWuhan430074China Department of Geology University of MalakandDir Lower18800ChakdaraPakistan Department of Earth and Environmental Sciences KU LeuvenLeuven3001Belgium

The present study is focused on evaluation of deep marine pelagic sediments of Late Cretaceous Kawagarh Formation of Kala-Chitta Range in the context of microfacies analysis,paleoenvironmental interpretation,planktonic foraminiferal biostratigraphy,sequence stratigraphy and diversification of species.A total of thirty three rock samples were collected from the measured section.Three microfacies are interpreted,namely planktonic foraminifera wackestone,planktonic foraminifera mudstone and sandy mudstone indicating low energy depositional environment i.e.,outer ramp.The biostratigraphic studies show plentiful planktonic foraminifera species of Globotruncana,Heterohelix and Globotruncanita.However,no association of benthic or siliceous organisms was observed.On the basis of available species assemblage,a single local planktonic foraminifera biozone i.e.,Globotruncana-Heterohelix-Globotruncanita Assemblage Biozone is established.The biozone information is combined with published literature and Lower Santonian to Middle Maastrichtian age has been assigned to the Kawagarh Formation.The trend of species occurrences evinces that species number decreases over time with pulsated rise in the Kawagarh Formation.The Kawagarh Formation carbonates show an overall Transgressive Systems Tract(TST).The Kawagarh Formation of Pakistan evinces analogous characteristics to that of the Late Cretaceous Gurpi Formation of Iran based on the geologic age,outcrop lithology,microfacies,planktonic foraminiferal assemblages,depositional setting and sequence stratigraphy.

关键词： depositional fabric biostratigraphy sequence stratigraphy Late Cretaceous Kawagarh Formation Pakistan Gurpi Formation Iran

Cold plasma-induced effects on electromagnetic wave scattering in waveguides:a mode-matching analysis

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Communications in Theoretical Physics 2024年第3期76卷 144-156页

作者： Shahana Rizvi muhammad Afzal Department of Mathematics Capital University of Science and TechnologyIslamabadPakistan

This article presents advancements in an analytical mode-matching technique for studying electromagnetic wave propagation in a parallel-plate metallic rectangular waveguide.This technique involves projecting the solution onto basis functions and solving linear algebraic systems to determine scattering amplitudes.The accuracy of this method is validated via numerical assessments,which involve the reconstruction of matching conditions and conservation laws.The study highlights the impact of geometric and material variations on reflection and transmission phenomena in the waveguide.

关键词： electromagnetic waves scattering cold plasma metallic conducting mode-matching technique

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy muhammad Adnan Khan muhammad Hasnain Azam Khan muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or pathologic.Various cardiotocography measures infer wrongly and give wrong predictions because of human error.The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well.Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being.In the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional results.ML techniques play a pivotal role in detecting fetal disease in its early stages.This research article uses Federated machine learning(FML)and ML techniques to classify the condition of the fetus.This study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the data.So,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,respectively.So,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal