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Human dental pulp stem/stromal cells in clinical practice

World Journal of Stem Cells 2024年第2期16卷 54-57页

作者： mohammed e Grawish Department of oral Biology Faculty of DentistryMansoura UniversityMansoura 35561Egypt Department of oral Biology Faculty of Oral and Dental MedicineDelta University for Science and TechnologyMansoura 11152Egypt

Dental pulp stem/stromal cells(DPSCs)are fibroblast-like,neural crest-derived,and multipotent cells that can differentiate into several *** are relatively easy to isolate from healthy and inflamed pulps,with little ethical concerns and can be successfully cryopreserved and *** therapeutic effects of DPSCs derived from animal or human sources have been extensively studied through in-vitro and in-vivo animal experiments and the findings indicated that DPSCs are effective not only for dental diseases but also for systemic *** that translational research is a critical step through which the fundamental scientific discoveries could be translated into applicable diagnostics and therapeutics that directly benefit humans,several clinical studies were carried out to generate evidence for the efficacy and safety of autogenous or allogeneic human DPSCs(hDPSCs)as a treatment modality for use in cell-based therapy,regenerative medicine/dentistry and tissue *** clinical medicine,hDPSCs were effective for treating acute ischemic stroke and human exfoliated deciduous teeth-conditioned medium(SHeD-CM)repaired vascular damage of the corpus cavernous,which is the main cause of erectile *** in clinical dentistry,autologous SHeD was able to rege-nerate necrotic dental pulp after implantation into injured teeth,and micrografts enriched with autologous hDPSCs and collagen sponge were considered a treatment option for human intrabony *** contrast,hDPSCs did not add a significant regenerative effect when they were used for the treatment of post-extraction ***-scale clinical studies across diverse populations are still lacking to provide robust evidence on the safety and efficacy of hDPSCs as a new treatment option for various human diseases including dental-related problems.

关键词： Dental pulp stem/stromal cells Human clinical studies Regenerative medicine Regenerative dentistry Cell-based therapy

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Novel Framework for an Intrusion Detection System Using Multiple Feature Selection Methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.e.M.eljialy mohammed Yousuf Uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. Machine learning (ML) techniques are extensively applied to build robust IDSs. Many researchers have utilized different ML methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the ML model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. Multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

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Comparison between seismic analysis of twisting and regular 52-story towers considering soil-structure interaction

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earthquake engineering and engineering Vibration 2024年第3期23卷 663-675页

作者： Mohamed Naguib Abouelsaad mohammed Shaaban Salah el Bagalaty Mohamed e.el Madawy Structural engineering Department Faculty of EngineeringMansura UniversityMansoura 35511Egypt Faculty of engineering Delta University for Science and TechnologyGamasa 35712Egypt

A dynamic analysis of both twisting and regular towers is carried out to determine the results of considering soil-structure interaction(SSI)on high-rise *** addition,the difference between the seismic performance of using twisting towers over regular ones is *** twisting tower is a simulation of the evolution Tower(Moscow).The towers’skeletons consist of RC elements and rest on a reinforced concrete piled-raft *** soil model is considered as multi-layered with the same soil properties as the zone chosen for the analysis(New Mansoura City,egypt).The only difference between both towers is their shape in *** whole system is modelled and analyzed in a single step as one full 3D model,which is known as the direct approach in *** analyses are carried out using finite-element software(Midas GTS NX).Dynamic output responses due to three records of seismic loads are proposed and presented in some *** on the results,it is concluded that SSI has a considerable effect on the dynamic response of tall buildings mainly because of the foundation flexibility,as it leads to lengthening the vibration period,increasing the story drift and the base shear for both cases.

关键词： soil-structure interaction seismic analysis twisting towers base shear story drift finite element method Midas GTS NX

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Kaoline-based catalyst for a high stability desulfurization of sour heavy naphtha in a three-phase oscillatory baffled reactor

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Particuology 2024年第1期84卷 249-260页

作者： Hassan M.Hmood Saba A.Gheni Safaa M.R.Ahmed Mudheher M.Ali Hamid Yonis Saleh mohammed H.mohammed Awad e.mohammed Marwan A.Mahomood Hiba R.mohammed Ahmed A.Hassan Adam Harvey North Refineries Company Ministry of OilIraq Chemical engineering Department Tikrit UniversityIraq Ministry of oil Iraq AL-Hawija Technical Institute Northern Technical UniversityMoselIraq School of engineering Newcastle UniversityUK

To meet the rapidly increasing demand for energy and the dramatic depletion of conventional crude oil,it is imperative to utilize sour *** no coke being produced,oxidative desulfurization(oDS)of naphtha lowers its sulfur content and average molecular *** this article,we outline a method for heavy naphtha non-extractive oDS using a very stable *** technique involves the use of a solid catalyst with oxygen gas as the *** necessitated relatively high mixing intensities;hence a three-phase oscillatory Baffled Reactor(oBR)was *** catalyst was based on the zeolite ZSM-5,prepared from natural kaolin by a series of delamination and activation steps and impregnated with Fe.A Tio2 nanolayer was applied,using the sol-gel method,to prevent rapid *** reactor performance was evaluated to minimize the sulfur content in the naphtha *** to the protective coating,the sulfur conversion stabilized at 90%.The results of this work establish the use of natural clay-based catalysts in a continuous,three-phase oDS,particularly with regard to proving long-term *** also showed that modest oDS can be achieved using an environmentally friendly oxidant,at mild operating conditions,whilst maintaining stability.

关键词： Natural kaoline Desulfurization Three-phase oscillatory baffled reactor

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Communication-less Management Strategy for electric Vehicle Charging in Droop-controlled Islanded Microgrids

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Journal of Modern Power Systems and Clean energy 2024年第4期12卷 1227-1238页

作者： Abdullah Azhar Al-obaidi mohammed Zaki el-Sharafy Hany e.Z.Farag Saifullah Shafiq Ali Al-Awami Independent electricity System operator(IeSo) MississaugaCanada Department of electrical engineering and Computer Science York UniversityTorontoCanada University of Queensland StLucia QLD 4067Australia Department of electrical engineering King Fahd University of Petroleum&MineralsDhahranSaudi Arabia

Adopting high penetration levels of electric vehicles(eVs)necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on pow-er distribution ***,most of the proposed ev charging management techniques rely on the availability of high-bandwidth communication *** techniques are far from realization due to①the lack of utility-grade communica-tion systems in many cases such as secondary(low-voltage)pow-er distribution systems to which eVs are connected,rural ar-eas,remote communities,and islands,and②existing fears and concerns about the data privacy of eV users and cyber-physical *** these cases,appropriate local control schemes are needed to ensure the adequate management of eV charging without violating the grid operation ***,this paper introduces a new communication-less management strategy for eV charging in droop-controlled islanded *** proposed strategy is autonomous,as it is based on the measurement of system frequency and local bus *** proposed strategy implements a social charging fairness policy during periods when the microgrid distributed genera-tors(DGs)are in short supply by allocating more system capaci-ty to the eVs with less charging in the ***,a novel communication-less eV load shedding scheme is incorpo-rated into the management strategy to provide relief to the mi-crogrid during events of severe undervoltage or underfrequency occurrences due to factors such as high loading or DG *** simulations demonstrate the superiority of the pro-posed strategy over the state-of-the-art controllers in modulat-ing the eV charging demand to counteract microgrid instability.

关键词： Charging battery management communication-less control droop control electric vehicle islanded microgrid

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Fluorophosphates and fluorosulfates cathode materials: Progress towards high energy density sodium-ion battery

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Nano Research 2024年第3期17卷 1427-1440页

作者： mohammed Hadouchi Jingrong Hou Toshinari Koketsu Abdelilah Lahmar Jiwei Ma Laboratoire de Chimie Appliquée des Matériaux Centre des Sciences des MatériauxFaculty of ScienceMohammed V University in RabatAvenue Ibn BattoutaBP 1014RabatMorocco Shanghai Key Laboratory for R&D and Application of Metallic Functional Materials Institute of New Energy for VehiclesSchool of Materials Science and EngineeringTongji UniversityShanghai 201804China Battery Materials Development Section Business Creation Sector R&D CenterMitsui Mining&Smelting Co.Ltd.362-0021 SaitamaJapan Laboratoiry of Condensed Matter Physics University of Picardie Jules Verne33 Rue Saint-Leu 80039AmiensFrance

The rapid diffusion of renewable energy boosts the wide deployment of large-scale energy storage *** the low cost and high crustal abundance,sodium-ion battery(SIB)technology is expected to become a dominant technology in that area in the *** the practical application,novel cathode materials are urged to develop that show high energy density without sacrificing their cost and benignity to the *** the years of many studies,this still remains a huge challenge to battery *** this review,we discuss recent breakthroughs in SIB cathode materials with high energy density,namely fluorphosphates and *** design of materials,the crystal structure,the electrochemical performance,and the underlaying intercalation mechanism are systematically *** strategies and research directions are also provided to advance future high-energy,low-cost,and ecofriendly cathode materials for next generation SIB.

关键词： fluorophosphates fluorosulfates crystal structure intercalation mechanism high energy density sodium-ion battery

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experimental validation of double-fed induction generator in oscillating water column using circulatory system-based optimization

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CLeAN eNeRGY 2024年第2期8卷 127-143页

作者： elnaghi, Basem e. Ismaiel, Ahmed M. Abdel-Kader, Fathy el Sayed mohammed, Reham H. Abelwhab, M. N. Suez Canal Univ Elect Power & Machine Dept Ismailia Egypt Menoufia Univ Fac Engn Elect Machine & Power Dept Menoufia Egypt Suez Canal Univ Comp & Control Dept Ismailia Egypt

This paper validates the optimal operation for a grid-connected double-fed induction generator (DFIG) in an oscillating water column power plant (oWCPP). This study presents a novel optimization technique called the circulatory system-based optimization (CSBo) approach to develop six adaptive fuzzy logic controllers (AFLCs) with 30 parameters and compare them to chaotic-billiards optimization (C-Bo) and genetic algorithm (GA). The proposed controller is also compared with a proportional-integral differential (PID) controller based on a self-adaptive global-best harmony search (SGHS). CSBo-based AFLCs are fully investigated under different scenarios and experimented with using a real-time interface DSP1104. The results of using CSBo-AFLCs revealed a fast time response, fast convergence, less overshoot and minimal error compared with those achieved with C-Bo-AFLC, SGHS-PID and GA-AFLC during different case studies. The CSBo-based AFLCs ensure maximum power from the DFIG in an oWCPP and enhance dynamic response with very low errors. The results show that the CSBo shows better power tracking by 25% as compared with C-Bo, by 45% when compared with the GA and by 56% when compared with PID. Moreover, the integral absolute errors of six controllers are investigated to demonstrate the feasibility of CSBo-AFLC. The root mean square of the errors of six controllers using CSBo is improved by 68.27% when compared with GA, by 22.57% when compared with C-Bo and by 38.42% when compared with PID. These indicators demonstrate the feasibility of CSBo when compared with other algorithms with the same oWCPP. This paper validates the optimal operation of a grid-connected double-fed induction generator in an oscillating water column using a novel optimization technique called the circulatory system-based optimization approach. experiments using a real-time simulator demonstrate the feasibility of the approach when compared with other algorithms. Graphical Abstract

关键词： circulatory system-based optimization approach adaptive fuzzy logic controller grid-tied oscillating water column power plant maximum power point tracking WAVe eNeRGY-CoNVeRSIoN DeSIGN oPTIMIZATIoN ALGoRITHM CoNTRoLLeR TURBINe

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A Comprehensive Analysis of the Thermo-Chemical Properties of Sudanese Biomass for Sustainable Applications

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Journal of Renewable Materials 2024年第4期12卷 721-736页

作者： Wadah mohammed Zeinab osman Salah elarabi Bertrand Charrier Institute of Analytical Sciences and Physical-Chemistry for the environment and Materials-Xylomat University of Pau and the Adour RegionE2S UPPACNRSIPREM-UMR 5254Mont de Marsan40004France Institute of engineering Research and Materials Technology(IeRMT) National Center for Research(NCR)Ministry of Higher Education and Scientific ResearchKhartoum11111Sudan Faculty of Industries engineering and Technology University of GeziraGezira State21111Sudan

The chemical composition and thermal properties of natural fibers are the most critical variables that determine the overall properties of the fibers and influence their processing and use in different sustainable applications,such as their conversion into bioenergy and *** thermal and mechanical properties can be estimated by evaluating the content of cellulose,lignin,and other extractives in the *** this research work,the chemical composition and thermal properties of three fibers,namely bagasse,kenaf bast fibers,and cotton stalks,were evaluated to assess their potential utilization in producing biocomposites and bioenergy *** chemical composition analysis followed the Technical Association of the Pulp and Paper Industry Standards(TAPPI)*** total phenol content was quantified using the Folin-Ciocalteu method,while Fourier Transform Infrared Spectroscopy(FTIR)was employed to assess the light absorption by the *** evaluate thermal stability and higher heating values,Thermogravimetric Analysis(TGA),Differential Scanning Calorimetry(DSC),and bomb calorimetry were *** chemical analysis revealed that bagasse contained 50.6%cellulose and 21.6%lignin,kenaf bast fibers had 58.5%cellulose and 10%lignin,and cotton stalks exhibited 40.3%cellulose and 21.3%*** FTIR curves demonstrated a notable similarity among the *** TGA analysis showed degradation temperatures of 321°C for bagasse,354°C for kenaf bast fibers,and 289°C for cotton *** DSC analysis revealed glass transition temperatures of 81°C for bagasse,66.3°C for cotton stalks,and 64.5°C for kenaf bast *** higher heating values were measured as 17.3,16.6 and 17.1 MJ/kg for bagasse,kenaf bast fibers,and cotton stalks,*** three fibers have a high potential for biocomposites and bioenergy material manufacturing.

关键词： Bagasse kenaf bast fibers cotton stalks TGA DSC FTIR

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A Low Complexity ML-Based Methods for Malware Classification

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Computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud e.Farfoura Ahmad Alkhatib Deema mohammed Alsekait Mohammad Alshinwan Sahar A.el-Rahman Didi Rosiyadi Diaa Salama Abd elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-electrical engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MeU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BoDMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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The User Analysis of Amazon Using Artificial Intelligence at Customer Churn

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Journal of Data Analysis and Information Processing 2024年第1期12卷 40-48页

作者： mohammed Ali Alzahrani Information Technology Department Computing and ICT Faculty Taif University Taif Saudi Arabia

Customer churns remains a key focus in this research, using artificial intelligence-based technique of machine learning. Research is based on the feature-based analysis four main features were used that are selected on the basis of our customer churn to deduct the meaning full analysis of the data set. Data-set is taken from the Kaggle that is about the fine food review having more than half a million records in it. This research remains on feature based analysis that is further concluded using confusion matrix. In this research we are using confusion matrix to conclude the customer churn results. Such specific analysis helps e-commerce business for real time growth in their specific products focusing more sales and to analyze which product is getting outage. Moreover, after applying the techniques, Support Vector Machine and K-Nearest Neighbour perform better than the random forest in this particular scenario. Using confusion matrix for obtaining the results three things are obtained that are precision, recall and accuracy. The result explains feature-based analysis on fine food reviews, Amazon at customer churn Support Vector Machine performed better as in overall comparison.

关键词： Customer Churn Machine Learning Amazon Fine Food Reviews Data Science Artificial Intelligence

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