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Ph.toch.mical analysis,antioxidant,acetylch.linesterase,andα-amylase inh.bitors from h.ppeastrum h.bridum extract

Journal of Traditional Ch.nese Medicine 2024年第3期44卷 496-504页

作者： Naila Sh.r Mush.aq Ah.ed nadia Mush.aq Department of Biotech.ology University of Science and Technology Bannu-KPK 28100Pakistan Department of Botany University of Science and Technology Bannu-KPK 28100Pakistan

OBJECTIVE:To investigate th. effects of h.ppeastrum h.bridum(h.)as a free radical scavenger,and an inh.bitor of th. two enzymes i-e Alph.-amylase(α-amylase)and acetylch.linesterase(ACh.).METh.DS:In th.s study,h. plant was preliminary analyzed for ph.toch.mical screening and th.n tested for its antioxidant,anti-α-amylase,and anti-ACh. efficiency via standard ***:Ph.toch.mical analysis sh.ws th. existence of different compounds;wh.le Coumarins and quinones were *** total ph.nolic,flavonoid,and tannins content were found to be(78.52±0.69)mg GAE/g,(2.01±0.04)mg RUE/g,and(58.12±0.23)mg TAE/g of plant extract respectively.28.02%±0.02%alkaloid and 2.02%±0.05%saponins were present in th. h. *** h. extract sh.wed th. anti-oxidant property with.IC50(50%inh.bition)of(151.01±0.13)(h.),(79.01±0.04)(Ascorbic acid)for ferric reducing,(91.48±0.13)(h.),(48.02±0.11)(Ascorbic acid)against Ammonium molybdenum,(156.02±0.31)(h.),(52.38±0.21)(Ascorbic acid)against DPPh.136.01±0.21(h.),52.02±0.31(Ascorbic acid)against h.(2)O_(2),and 154.12±0.03(h.),(40.05±0.15)(Ascorbic acid)μg/mL against ABTS *** analysis indicated th.t h. caused a competitive type of inh.bition ofα-amylase(V_(max)remained constant and Km increases from 10.65 to84.37%)wh.le Glucoph.ge caused th. un-competitive type of inh.bition i-e both.Km and V_(max)decreased from40.49 to 69.15%and 38.86 to 69.61%*** K_(i),(inh.bition constant);K_(I),(dissociation constant),K_(m),(Mich.elis-Menten constant),and IC50 were found to be62,364,68.1,and 38.08±0.22 for h. and 12,101.05,195,34.01±0.21 for ***,h. causes an anon-competitive type of inh.bition of ACh. i-e Km remains constant wh.le V_(max)decreases from 60.5%to74.1%.Th. calculated K_(i),K_(I),K_(m),and IC50 were found to be 32,36.2,0.05,and 18.117±***:From th. current results,it is concluded th.t h. extract contains bioactive compounds,and could be a good alternative to controlling oxidant

关键词： h.ppeastrum h.bridum ph.toch.micals antioxidant alph.-amylase acetylch.linesterase

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Th.oretical investigations on electrocaloric properties of(111)-oriented PbMg_(1/3)Nb_(2)/3O_(3) single crystal

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Journal of Advanced Ceramics 2013年第4期2卷 308-312页

作者： mahmoud Aly h.MAD Ph.sics Department Faculty of ScienceTanta UniversityTantaEgypt

Th. electrocaloric(EC)effect accompanied with.th. ferroelectric to paraelectric ph.se transition in(111)-oriented PbMg_(1/3)Nb_(2)/3O_(3)(PMN)is *** is sh.wn th.t th. largest ch.nge TDis 0.37 K in 3 kV/cm electric field sh.ft near th. Curie temperature of 221 K;th.t is,th. cooling TDper unit field(MV/m)is 1.23×10^(-6) m·K/*** value is significantly larger,and comparable with.th. value of 0.254×10^(-6) m·K/V for PbZr_(0.95)Ti_(0.05)O_(3)th.n film under larger electric field sh.ft ED=30 kV/***,th. EC effect of(111)PMN single crystal provides cooling solutions at low temperatures,and opens more opportunities for practical application in cooling systems.

关键词： electrocaloric(EC)effect PbMg_(1/3)Nb_(2)/3O_(3)(PMN) model polarization entropy ch.nge h.at capacity ch.nge

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Th. Rank of th. 2-Class Group of Some Fields with.LargeDegree

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Algebra Colloquium 2022年第2期29卷 181-188页

作者： Moh.med mahmoud Ch.ms-Eddin Department of Math.matics Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah UniversityFezMorocco

Let n≥3 be an integer and d an odd square-free *** compute th. rank of th. 2-class group of some fields of th. form L_(n,d)=Q(ζ_(2^(n)),√d)wh.n all th. prime divisors of d are congruent to±3(mod 8)or 9(mod 16).

关键词： cyclotomic Z_(2)-extension 2-rank 2-class group

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A Novel Analytical Tech.ique of th. Fractional Bagley-Torvik Equations for Motion of a Rigid Plate in Newtonian Fluids

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Computer Modeling in Engineering & Sciences 2020年第9期124卷 969-983页

作者： mahmoud h.Tah. Moh.med A.Ramadan Dumitru Baleanu Galal M.Moatimid Department of Math.matics Faculty of EducationAin Shams UniversityCairoEgypt Department of Math.matics&Computer Science Faculty of ScienceMenoufia UniversityShebin El-KomEgypt Department of Math.matics Cankaya UniversityAnkara06530Turkey Institute of Atomic Ph.sics Magurele-Bucharest077125Romania Department of Medical Research China Medical University HospitalChina Medical UniversityTaichungTaiwan

Th. current paper is concerned with.a modified h.motopy perturbation *** modification allows ach.eving an exact solution of an initial value problem of th. fractional differential *** approach.is powerful,effective,and promising in analyzing some classes of fractional differential equations for h.at conduction problems and oth.r dynamical *** crystallize th. new approach.some illustrated examples are introduced.

关键词： Bagley-Torvik equation caputo sense Riemann-Liouville integral fractional differential equation

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Deer h.nting Optimization with.Deep Learning Model for Lung Cancer Classification

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Computers, Materials & Continua 2022年第10期73卷 533-546页

作者： mahmoud Ragab h.sh.m A.Abdush.our Alaa F.Nah.as Wajdi h.Aljedaibi Information Tech.ology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Center of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Math.matics Department Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Nautical Science Department Faculty of Maritime StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Bioch.mistry Department Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Lung cancer is th. main cause of cancer related death.owing to its destructive nature and postponed detection at advanced *** recognition of lung cancer is essential to increase th. survival rate of persons and it remains a crucial problem in th. h.alth.are *** aided diagnosis(CAD)models can be designed to effectually identify and classify th. existence of lung cancer using medical *** recently developed deep learning(DL)models find a way for accurate lung nodule classification ***,th.s article presents a deer h.nting optimization with.deep convolutional neural network for lung cancer detection and classification(Dh.DCNNLCC)*** proposed Dh.DCNN-LCC tech.ique initially undergoes pre-processing in two stages namely contrast enh.ncement and noise ***,th. features extraction process on th. pre-processed images takes place using th. Nadam optimizer with.RefineDet *** addition,denoising stacked autoencoder(DSAE)model is employed for lung nodule ***,th. deer h.nting optimization algorith.(Dh.A)is utilized for optimal h.per parameter tuning of th. DSAE model and th.reby results in improved classification *** experimental validation of th. Dh.DCNN-LCC tech.ique was implemented against bench.ark dataset and th. outcomes are assessed under various *** experimental outcomes reported th. superior outcomes of th. Dh.DCNN-LCC tech.ique over th. recent approach.s with.respect to distinct measures.

关键词： Lung cancer image classification computer aided diagnosis deep learning medical imaging parameter optimization

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A Blockch.in-Based Arch.tecture for Enabling Cybersecurity in th. Internet-of-Critical Infrastructures

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Computers, Materials & Continua 2022年第7期72卷 1579-1592页

作者： mahmoud Ragab Ali Altalbe Information Tech.ology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Center of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Math.matics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt

Due to th. drastic increase in th. number of critical infrastructures like nuclear plants,industrial control systems(ICS),transportation,it becomes h.gh.y vulnerable to several *** become th. major targets of cyberattacks due to th. increase in number of interconnections with.oth.r *** research.works h.ve focused on th. design of intrusion detection systems(IDS)using mach.ne learning(ML)and deep learning(DL)*** th. same time,Blockch.in(BC)tech.ology can be applied to improve th. security *** order to resolve th. security issues th.t exist in th. critical infrastructures and ICS,th.s study designs a novel BC with.deep learning empowered cyber-attack detection(BDLE-CAD)in critical infrastructures and *** proposed BDLE-CAD tech.ique aims to identify th. existence of intrusions in th. *** addition,th. presented enh.nced ch.mp optimization based feature selection(ECOA-FS)tech.ique is applied for th. selection of optimal subset of ***,th. optimal deep neural network(DNN)with.search.and rescue(SAR)optimizer is applied for th. detection and classification of ***,a BC enabled integrity ch.cking sch.me(BEICS)h.s been presented to defend against th. misrouting *** experimental result analysis of th. BDLE-CAD tech.ique takes place and th. results are inspected under varying *** simulation analysis pointed out th. supremacy of th. BDLE-CAD tech.ique over th. recent state of art tech.iques with.th. accuy of 92.63%.

关键词： BC internet of critical infrastructure ids deep learning security deep neural network mach.ne learning

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Fuzzy Logic with.Arch.medes Optimization Based Biomedical Data Classification Model

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Computers, Materials & Continua 2022年第8期72卷 4185-4200页

作者： mahmoud Ragab Diaa h.med Information Tech.ology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Math.matics Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Mineral Resources and Rocks Faculty of Earth SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Geology Department Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt

Medical data classification becomes a h.t research.topic in th. h.alth.are sector to aid ph.sicians in th. h.alth.are sector for decision ***,th. advances of mach.ne learning(ML)tech.iques assist to perform th. effective classification *** th.s motivation,th.s paper presents a Fuzzy Clustering Approach.Based on Breadth.first Search.Algorith.(FCA-BFS)with.optimal support vector mach.ne(OSVM)model,named FCABFS-OSVM for medical data *** proposed FCABFS-OSVM tech.ique intends to classify th. h.alth.are data by th. use of clustering and classification ***,th. proposed FCABFSOSVM tech.ique involves th. design of FCABFS tech.ique to cluster th. medical data wh.ch.h.lps to boost th. classification ***,th. OSVM model investigates th. clustered medical data to perform classification ***,Arch.medes optimization algorith.(AOA)is utilized to th. SVM parameters and boost th. medical data classification results.A wide range of simulations takes place to h.gh.igh. th. promising performance of th. FCABFS-OSVM *** comparison studies reported th. enh.nced outcomes of th. FCABFS-OSVM tech.ique over th. recent state of art approach.s.

关键词： Clustering medical data classification mach.ne learning parameter tuning support vector mach.nes

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A New Class of L-Moments Based Calibration Variance Estimators

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Computers, Materials & Continua 2021年第3期66卷 3013-3028页

作者： Usman Sh.h.ad Ish.aq Ah.ad Ibrah.m Mufrah.Almanjah.e nadia h.Al Noor Muh.mmad h.nif Department of Math.matics and Statistics International Islamic UniversityIslamabad46000Pakistan Department of Math.matics and Statistics PMAS-Arid Agriculture UniversityRawalpindi46300Pakistan Department of Math.matics King Khalid UniversityAbha62529Saudi Arabia Statistical Research.and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia Department of Math.matics College of ScienceMustansiriyah UniversityBaghdad10011Iraq

Variance is one of th.most important measures of descriptive statistics and commonly used for statistical *** traditional second-order central moment based variance estimation is a widely utilized ***,traditional variance estimator is h.gh.y affected in th. presence of extreme *** th.s paper initially,proposes two classes of calibration estimators based on an adaptation of th. estimators recently proposed by Koyuncu and th.n presents a new class of L-Moments based calibration variance estimators utilizing L-Moments ch.racteristics(L-location,Lscale,L-CV)and auxiliary *** is demonstrated th.t th. proposed L-Moments based calibration variance estimators are more efficient th.n adapted *** data is considered for assessing th. performance of th. proposed *** also demonstrated an application related to apple fruit for purposes of th. *** artificial and real data sets,percentage relative efficiency(PRE)of th. proposed class of estimators with.respect to adapted ones are *** PRE results indicate to th. superiority of th. proposed class over adapted ones in th. presence of extreme *** th.s manner,th. proposed class of estimators could be applied over an expansive range of survey sampling wh.never auxiliary information is available in th. presence of extreme values.

关键词： L-moments variance estimation calibration approach stratified random sampling

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Low Complexity Encoder with.Multilabel Classification and Image Captioning Model

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Computers, Materials & Continua 2022年第9期72卷 4323-4337页

作者： mahmoud Ragab Abdullah.Addas Information Tech.ology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Math.matics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Landscape Arch.tecture Department Faculty of Architecture&PlanningKing Abdulaziz UniversityJeddah21589Saudi Arabia

Due to th. advanced development in th. multimedia-on-demandtraffic in different forms of audio, video, and images, h.s extremely movedon th. vision of th. Internet of Th.ngs (IoT) from scalar to Internet ofMultimedia Th.ngs (IoMT). Since Unmanned Aerial Veh.cles (UAVs) generates a massive quantity of th. multimedia data, it becomes a part of IoMT,wh.ch.are commonly employed in diverse application areas, especially forcapturing remote sensing (RS) images. At th. same time, th. interpretationof th. captured RS image also plays a crucial issue, wh.ch.can be addressedby th. multi-label classification and Computational Linguistics based imagecaptioning tech.iques. To ach.eve th.s, th.s paper presents an efficient lowcomplexity encoding tech.ique with.multi-label classification and image captioning for UAV based RS images. Th. presented model primarily involves th.low complexity encoder using th. Neigh.orh.od Correlation Sequence (NCS)with.a burrows wh.eler transform (BWT) tech.ique called LCE-BWT forencoding th. RS images captured by th. UAV. Th. application of NCS greatlyreduces th. computation complexity and requires fewer resources for imagetransmission. Secondly, deep learning (DL) based sh.llow convolutional neural network for RS image classification (SCNN-RSIC) tech.ique is presentedto determine th. multiple class labels of th. RS image, sh.ws th. novelty ofth. work. Finally, th. Computational Linguistics based Bidirectional EncoderRepresentations from Transformers (BERT) tech.ique is applied for imagecaptioning, to provide a proficient textual description of th. RS image. Th.performance of th. presented tech.ique is tested using th. UCM dataset. Th.simulation outcome implied th.t th. presented model h.s obtained effectivecompression performance, reconstructed image quality, classification results,and image captioning outcome.

关键词： Image captioning unmanned aerial veh.cle low complexity encoder remote sensing images image classification

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Automated Artificial Intelligence Empowered Colorectal Cancer Detection and Classification Model

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Computers, Materials & Continua 2022年第9期72卷 5577-5591页

作者： mahmoud Ragab Ash.ag Albukh.ri Information Tech.ology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Math.matics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Bioch.mistry Department Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia

Colorectal cancer is one of th. most commonly diagnosed cancers and it develops in th. colon region of large *** h.stopath.logist generally investigates th. colon biopsy at th. time of colonoscopy or *** detection of colorectal cancer is h.lpful to maintain th. concept of accumulating cancer *** medical practices,h.stopath.logical investigation of tissue specimens generally takes place in a conventional way,wh.reas automated tools th.t use Artificial Intelligence(AI)tech.iques can produce effective results in disease detection *** th.s background,th. current study presents an Automated AI-empowered Colorectal Cancer Detection and Classification(AAI-CCDC)*** proposed AAICCDC tech.ique focuses on th. examination of h.stopath.logical images to diagnose colorectal ***,AAI-CCDC tech.ique performs preprocessing in th.ee levels such.as gray scale transformation,Median Filtering(MF)-based noise removal,and contrast *** addition,Nadam optimizer with.EfficientNet model is also utilized to produce meaningful feature ***,Glowworm Swarm Optimization(GSO)with.Stacked Gated Recurrent Unit(SGRU)model is used for th. detection and classification of colorectal *** proposed AAI-CCDC tech.ique was experimentally validated using bench.ark dataset and th. experimental results establish.d th. supremacy of th. proposed AAI-CCDC tech.ique over conventional approach.s.

关键词： Colorectal cancer medical data classification noise removal data classification artificial intelligence biomedical images deep learning optimizers

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