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Effect of cold deformation and heat treatment on microstructure and mechanical properties of TC21 Ti alloy

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Transactions of Nonferrous metals Society of China 2020年第5期30卷 1290-1299页

作者： Ramadan N.ELSHAER khaled m.ibrahim mechanical Engineering Department Tabbin Institute for Metallurgical Studies(TIMS)11918CairoEgypt Casting Technology Department Central Metallurgical R&D Institute(CMRDI)11918CairoEgypt

In the present research work on TC21 titanium alloy(6.5 Al-3 mo-1.9 Nb-2.2 Sn-2.2 Zr-1.5 Cr), the effects of cold deformation, solution treatment with different cooling rates and then aging on microstructure, hardness and wear property were investigated. A cold deformation at room temperature with 15% reduction in height was applied on annealed samples. The samples were solution-treated at 920 ℃ for 15 min followed by different cooling rates of water quenching(WQ), air cooling(AC) and furnace cooling(FC) to room temperature. Finally, the samples were aged at 590 ℃ for 4 h. Secondary α-platelets precipitated in residual β-phase in the case of solution-treated samples with AC condition and aged ones. The maximum hardness of HV 470 was obtained for WQ + aging condition due to the presence of high amount of residual β-matrix(69%), while the minimum hardness of HV 328 was reported for FC condition. Aging process after solution treatment can considerably enhance the wear property and this enhancement can reach up to about 122% by applying aging after WQ compared with the annealed samples.

关键词： TC21 titanium alloy deformation heat treatment cooling rate microstructure mechanical properties wear

Effect of Si-addition as a grain refiner on microstructure and properties of Ti-6Al-4V Alloy

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Transactions of Nonferrous metals Society of China 2013年第7期23卷 1863-1874页

作者： khaled m.ibrahim Abdel Hamied HUSSEIN mohamed ABDELKAWY Central metallurgical R&D Institute CMRDICairoEgypt Cairo University GizaEgypt

Two different Ti alloys were cast in a graphite mould using vacuum induction skull melting furnace. The first alloy was Ti-6Al-4V and the second was Ti-6Al-4V 0.5Si. Silicon as a grain refiner was added into Ti-6Al-4V alloy, and the effects of Si-addition on the microstructure and properties of the as-cast and swaged alloys were investigated. Hot swaging at 900 °C was performed on the cast samples and then two different thermal treatments were applied. The first treatment was done by heating the swaged samples at 1050 °C to produce fine lamella structure, while the second treatment was carried out at 1050 °C and then decreased the temperature to 800 °C for getting coarse lamella structure. An addition of 0.5% Si to Ti-6Al-4V alloy decreased the grain size of the as-cast sample from 627 to 337 μm. There was an increase in ultimate tensile strength of about 25 mPa for the as-cast Ti-6Al-4V 0.5Si alloy compared to Ti-6Al-4V due to the refinement effect caused by Si addition. A maximum ultimate tensile strength of 1380 mPa and a minimum corrosion rate （1.35×10 6 mm/a in Hank’s solution and 5.78×10 4 mm/a in NaCl solution） were reported for the heat treated fine lamella structure of Ti-6Al-4V 0.5Si alloy. The wear rate was decreased to about 50% by adding 0.5% Si at low sliding speeds and to about 73% at high sliding speeds.

关键词： Ti-6Al-4V alloy silicon casting grain refinement heat treatment wear

microstructure and mechanical properties of cast and heat treated Ti-6.55Al-3.41mo-1.77Zr alloy

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Transactions of Nonferrous metals Society of China 2013年第12期23卷 3517-3524页

作者： khaled m.ibrahim Abdel moty m.EL-HAKEEm Ramadan N.ELSHAER Certral metallurgical R&D Institute Benha University

α＋βtitanium alloy with a composition of Ti-6.55Al-3.41mo-1.77Zr （mass fraction,%） was cast into bars in a graphite mould using vacuum induction skull melting furnace （ISm）. The cast bars were hot swaged at 700 °C and then heat treated by two different regimes which resulted in fine and coarse lamella structures, respectively. The grain size of the as-cast structure was estimated to be 660 μm and the swaged samples obtained a very fine grain size in the range of 50 μm. The overall best combination of hardness, tensile properties, and wear resistance of theα＋βtitanium alloy was achieved by heat treating the samples at 1050 °C for getting fine lamellar structure. The maximum compression strength was reported for the heat treated samples at 800 °C with coarse lamella structure. The minimum wear rate was reported for the heat treated samples with fine lamellar structure and the maximum wear rate was obtained for as-cast samples due to its coarse and heterogeneity microstructure.

关键词： α+βTi-alloy casting solution treatment microstructure mechanical properties

microstructure evolution and mechanical properties of heat treated LCB titanium alloy

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Transactions of Nonferrous metals Society of China 2012年第11期22卷 2609-2615页

作者： khaled m. ibrahim mansour mHAEDE Lothar WAGNER Central metallurgical R&D Institute-CmRDI P.O. Box 87 Helwan Cairo Egypt TU-Clausthal IWW Agricolastr. 6 Clausthal-Zellerfeld Germany

The influence of ageing time on microstructure and mechanical properties of low-cost beta （LCB） titanium alloy with a chemical composition of Ti-6.6mo-4.5Fe-1.5Al was investigated. The correlation between microstructure and fatigue crack initiation and growth was also studied. Increasing ageing time tended to increase the volume fraction of the secondary α-precipitates, β-grain size and partial spheroidization of primary α-phase. The maximum tensile strength （1565 mPa） and fatigue limit （750 mPa） were obtained for the samples aged at 500 °C for 0.5 h, while the minimum ones of 1515 mPa and 625 mPa, respectively, were reported for the samples aged at 500 °C for 4 h. The samples aged at 500 °C for 4 h showed a transgranular fracture mode. However, the samples aged at 500 °C for 0.5 h revealed a mixture fracture mode of transgranular and intergranular. The formed cracks on the outer surface of the fatigue samples were found to propagate through the β-grains connecting the primary α-particles existing at the β-grain boundaries.

关键词： beta Ti alloy Ti-6.6mo-4.5Fe-1.5Al alloy fatigue crack ageing secondary α primary α β-grain tensile strength fatigue limit

An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social media Forensics

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Computers, materials & Continua 2024年第4期79卷 243-262页

作者： Yasmine m.ibrahim Reem Essameldin Saad m.Darwish Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt Faculty of Computers and Information Technology Egyptian E-Learning University(EELU)Giza12611Egypt Faculty of Computers and Data Science Alexandria UniversityAlexandria21554Egypt

Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two multi-Layer Perceptron (mLPs)for neutrosophic sets classification. During the training process of the mLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the mLP as fine-tuning. Additionally, in this approach, two separate mLP models are employed. One mLPis dedicated to predicting degrees of truth membership, while the other mLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.

关键词： Hate speech detection whale optimization neutrosophic sets social media forensics

Analysis of cerium substitution in Co-Sr based spinel ferrites for high frequency application

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Journal of Rare Earths 2024年第9期42卷 1755-1763,I0005页

作者： Laura Khudaysh Inas A.Ahmed Syeda Rabia Ejaz Sajjad Ahmad Khan Yasir A.Haleem mohamed m.ibrahim mahmood Ali Hafiz muhammad Tahir Farid Zeinhom m.El-Bahy Department of Physics Faculty of ScienceJazan UniversityJazan45142Saudi Arabia Department of Chemistry Faculty of ScienceKing Khalid UniversityAbha62224Saudi Arabia Department of Physics The Government Sadiq College Women UniversityBahawalpur63100Pakistan Institute of Physics Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Centre of Excellence in Solid State Physics University of the PunjabLahorePakistan Department of Physics Government CollegeTaunsa Sharif32200Pakistan Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City11884CairoEgypt

Spinel ferrites exhibit exceptional magnetic properties,making them a distinctive class of magnetic *** sol-gel technique was utilized for the synthesis of spinel ferrites with the chemical formula Co_(0.6)Sr_(0.4)Ce_(x)Fe_(2-x)O_(4). Following that,a comprehensive X-ray diffraction analysis unveiled the crystalline cubic structure of the synthesized *** the utilization of the m-H loop approach,the ferromagnetic attributes of ferrites were assessed,and the assimilation of rare earth elements led to substantial enhancements in saturation magnetization,remanence,and *** ferrites with a high concentration of rare earth elements have improved direct current resistivity and activation *** logarithm of a material's resistance increased from 5.29 to 8.12 Ω·cm as cerium is *** a change in the amount of cerium,the activation energy goes up from 0.19 to *** changing the frequency from 5.5 to 9.5 GHz,the dielectric characteristics were *** the frequency goes up,the dielectric constant goes *** ferrites that have been made better in every way can be used in high-frequency applications.

关键词： Activation energy DC electrical resistance Remanence magnetization Cobalt strontium spinel ferrites High frequency application Rare earths

Enhancing mild Cognitive Impairment Detection through Efficient magnetic Resonance Image Analysis

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Computers, materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah Shahid Shahid Iqbal mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah mostafa m.ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).mild cognitive impairment(mCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify mCI,AD,and normal control(NC)*** paper focuses on using gray matter(Gm)scans obtained through magnetic resonance imaging(mRI)for the diagnosis of individuals with mCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and mCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose mCI,AD,and normal control individuals using Gm *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

Assessment the effect of Dapoxetine and/or Acetaminophen in rats;neurochemicals and oxidative stress biomarkers evaluation

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Brain Science Advances 2024年第1期10卷 57-71页

作者： Gehan S.Georgy ibrahim m.ibrahim Laila mohamed E.Amer Ebtehal mohammad F. Pharmacology Department Egyptian Drug Authority(EDA)Giza P.O.29Egypt molecular Drug Evaluation Department Egyptian Drug Authority(EDA)Giza P.O.29Egypt Histology Department Faculty of MedicineAl-Azhar UniversityDamietta P.O.11651Egypt

Dapoxetine is a newer anti-depressant that is used for severe forms of depression via selective serotonin reuptake inhibition *** aimed to evaluate the effect of different doses of dapoxetine lonely or with acetaminophen(AmP).Seven groups of albino rats were used where dapoxetine was administered orally at the doses of 3,5,and 8 mg/kg body weight for a period of 14 days in groups 2,4,and 6,***(67.5 mg/kg body weight)was co-administered with dapoxetine(3,5,and 8 mg/kg body weight)for 14 days in groups 3,5 and 7,*** in mid and high dose plus AmP increased body weight and hematological *** and rearing were declined with mid and high doses of dapoxetine+AmP,contrary to *** was decreased with high doses of dapoxetine+*** dose of dapoxetine+AmP induced lowering of serotonin and dopamine as well as increasing of *** derived neurotrophic factor was decreased in all *** stress biomarkers were augmented with high dose of dapoxetine+*** doses of dapoxetine and/or AmP induced loss of the Purkinje cell layer at *** high dose of dapoxetine+AmP denotes behavioral,histopathological and neurochemical alterations,even though no serotonin syndrome occurs.

关键词： acetaminophen dapoxetine neurotransmitters oxidative stress biomarkers

Robust malicious Executable Detection Using Host-Based machine Learning Classifier

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Computers, materials & Continua 2024年第4期79卷 1419-1439页

作者： khaled Soliman mohamed Sobh Ayman m.Bahaa-Eldin Department of Computer and Systems Engineering Ain Shams UniversityCairo11517Egypt Department of Computer Engineering Technology ElSewedy University of TechnologyCairo44629Egypt

The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are insufficientto prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust malicious ExecutableDetection (RmED) using Host-based machine Learning Classifier to discover malicious Portable Executable (PE)files in hosts using Windows operating systems through collecting PE headers and applying machine learningmechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031benign files and 179,071 malware samples from diverse sources to ensure the efficiency of RmED *** most effective PE headers that can highly differentiate between benign and malware files were selected totrain the model on 15 PE features to speed up the classification process and achieve real-time detection formalicious executables. The evaluation results showed that RmED succeeded in shrinking the classification timeto 91 milliseconds for each file while reaching an accuracy of 98.42% with a false positive rate equal to 1.58. Inconclusion, this paper contributes to the field of cybersecurity by presenting a comprehensive framework thatleverages Artificial Intelligence (AI) methods to proactively detect and prevent cyber-attacks.

关键词： Portable executable malware intrusion detection cybersecurity zero-day threats Host IntrusionDetection System(HIDS) machine learning Anomaly-based Intrusion Detection System(AIDS) deep learning