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Automated detection of parasitized Cadra cautella eggs by Trichogramma bourarachae using machine vision

International Journal of Agricultural and Biological Engineering 2018年第3期11卷 94-101页

作者： mohammed s.el-faki Yuqi song Naiqian Zhang Hamadttu A.el-shafie Pan Xin Date Palm Research Center of Excellence King Faisal UniversityAl-AhsaKingdom of Saudi Arabia Department of Biological and Agricultural Engineering College of EngineeringKansas State UniversityManhattanKS 66506USA College of Computer and Information Engineering Inner Mongolia Agricultural UniversityHohhot 010018Inner MongoliaChina

Cadra(Ephestia)cautella(Walker)is a moth that attacks dates from ripening stages while on tree,throughout storage,and until consumption,causing enormous qualitative and quantitative damages,resulting in economic ***-processing algorithms were developed for detecting and differentiating between three Cadra egg categories based on the success of Trichogramma bourarachae(Pintureau and Babaul)*** categories were parasitized(black and dark red),unparasitized fertile unhatched(yellow),and unparasitized hatched(white)***,light intensity,and shape information was used to develop detection *** image processing methods were developed based on three randomly selected images and were tested on a larger validation image set of 40 images:(i)segmentation and extractions of color and morphological features followed by Watershed delineation,and is referred to as Algorithm 1(ALGO1),(ii)finding circular objects by Hough Transformation followed by convolution filtering,and is referred to as Algorithm 2(ALGO2).ALGO1 and ALGO2 achieved correct classification rates(CCRs)for parasitized eggs of 92%and 96%,*** CCRs for unhatched eggs were 48%and 94%,and for hatched eggs were 42%and 73%,*** parasitized eggs,both methods performed satisfactorily,but,in general,ALGO2 outperformed *** results ensure automatic evaluation of the efficiency of biological control of Cadra cautella by the egg parasitoid Trichogramma bourarachae by quantifying the rate of *** developed detection methods can be used by producers of biocontrol agents for online monitoring of Trichogramma and similar insect natural enemies during mass production and before release against crop ***,with few adjustments these methods can be used in similar applications such as detecting plant diseases.

关键词： Trichogramma parasitization Cadra eggs detection machine vision date fruit image processing objects recognition algorithms biological control

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some Factorization Properties in A+B[Г^(*)]Domains

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Algebra Colloquium 2020年第3期27卷 643-650页

作者： E.Boulayat s.el Baghdadi Department of Mathematics Beni Mellal University FSTP.O.Box 523Beni MellalMorocco

Let A■B be an extension of integral domains andГa commutative,additive,cancellative,torsion-free monoid with T∩-Г=el.Let B[Г]be the semigroup ring ofГover B and setГ^(*)=Г\el.Then R=A+B[Г^(*)]is a subring of B[Г].We investigate various factorization properties which are weaker than unique factorization in the domainsof the form A+B[Г^(*)].

关键词： monoid factorization atomic ACCP BFD

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Advanced Functional electromagnetic shielding Materials:A Review Based on Micro‑Nano structure Interface Control of Biomass Cell Walls

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Nano-Micro Letters 2025年第1期17卷 98-134页

作者： Yang shi Mingjun Wu shengbo Ge Jianzhang Li Anoud saud Alshammari Jing Luo mohammed A.Amin Hua Qiu Jinxuan Jiang Yazeed M.Asiri Runzhou Huang Hua Hou Zeinhom M.el‑Bahy Zhanhu Guo Chong Jia Kaimeng Xu Xiangmeng Chen Co‑Innovation Center of Efficient Processing and Utilization of Forest Resources College of Materials Science and EngineeringNanjing Forestry UniversityNanjing 210037People’s Republic of China state Key Laboratory of Efficient Production of Forest Resourced Beijing Forestry UniversityQinghua East Road 35Haidian DistrictBeijing 100083People’s Republic of China Department of Physics Faculty of Sciences‑ArarNorthern Border UniversityArar 91431Saudi Arabia Department of Chemistry College of ScienceTaif UniversityP.O.Box 1109921944 TaifSaudi Arabia shaanxi Key Laboratory of Macromolecular science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’anShaanxi 710072People’s Republic of China Integrated Composites Lab Department of Mechanical and Construction EngineeringNorthumbria UniversityNewcastle Upon Tyne NE18STUK College of Materials science and Engineering Taiyuan University of Science and TechnologyTaiyuan 030024People’s Republic of China Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr CityCairo 11884Egypt Yunnan Provincial Key Laboratory of Wood Adhesives and Glued Products International Joint Research Center for Biomass MaterialsSouthwest Forestry UniversityKunming 650224People’s Republic of China school of science Henan Agricultural UniversityZhengzhou 450002People’s Republic of China

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass *** materials offer numerous advantages such as being lightweight,porous,and *** to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding *** concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding *** particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be *** preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and *** composite methods and fillers of various biomass materials were *** paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

关键词： Biomass materials electromagnetic interference shielding Micro-nano structure interface control Conductivity

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Efficient Classification of Remote sensing Images Using Two Convolution Channels and sVM

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Computers, Materials & Continua 2022年第7期72卷 739-753页

作者： Khalid A.AlAfandy Hicham Omara Hala s.el-sayed mohammed Baz Mohamed Lazaar Osama s.Faragallah mohammed Al Achhab ENsA Abdelmalek Essaadi UniversityTetouan 93002Morocco Fs Abdelmalek Essaadi UniversityTetouan 93002Morocco Department of electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom 32511Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia ENsIAs Mohammed V University in Rabat 10000Morocco Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

Remote sensing image processing engaged researchers’attentiveness in recent years,especially *** main problem in classification is the ratio of the correct predictions after *** extraction is the foremost important step to build high-performance image *** convolution neural networks can extract images’features that significantly improve the image classifiers’*** paper proposes two efficient approaches for remote sensing images classification that utilizes the concatenation of two convolution channels’outputs as a features extraction using two classic convolution models;these convolution models are the ResNet 50 and the DenseNet *** elicited features have been used by the fully connected neural network classifier and support vector machine classifier as input *** results of the proposed methods are compared with other antecedent approaches in the same experimental *** is based on learning curves plotted during the training of the proposed classifier that is based on a fully connected neural network and measuring the overall accuracy for the both proposed *** proposed classifiers are used with their trained weights to predict a big remote sensing scene’s classes for a developed *** results ensure that,compared with the other traditional classifiers,the proposed classifiers are further accurate.

关键词： Remote sensing images deep learning ResNet DenseNet sVM

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Conventional Breeding and Molecular Markers for Blast Disease Resistance in Rice (Oryza sativa L.)

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Phyton-International Journal of Experimental Botany 2023年第3期92卷 725-746页

作者： Adel A.Rezk Mohamed M.el-Malky Hossam s.el-Beltagi mohammed Al-daej Kotb AAttia Agricultural Biotechnology Department College of Agricultural and Food ScienceKing Faisal UniversityAl-Ahsa31982Saudi Arabia Plant Pathology Research Institute Agriculture Research CenterGiza12619Egypt Rice Research and Training Center SakhaField Crops Research InstituteAgricultural Research CenterKafr El-Sheikh33717Egypt Biochemistry Department Faculty of AgricultureCairo UniversityGiza12613Egypt Center of Excellence in Biotechnology Research King Saud UniversityRiyadh11451Saudi Arabia Rice Biotechnology Laboratory Rice Research DepartmentField Crops Research InstituteARCKafr EL-Sheikh33717Egypt

Monogenic lines,which carried 23 genes for blast resistance were tested and used donors to transfer resistance genes by crossing *** results under blast nursery revealed that 9 genes from 23 genes were susceptible to highly susceptible under the three locations(sakha,Gemmeza,and Zarzoura in Egypt);Pia,Pik,Pik-p,Piz-t,Pita,Pi b,Pi,Pi 19 and Pi ***,the genes Pii,Pik-s,Pik-h,Pi z,Piz-5,Pi sh,Pi 3,Pi 1,Pi 5,Pi 7,Pi 9,Pi 12,Pikm and Pita-2 were highly resistant at the same *** analysis confirmed the results,which divided into two groups;the first one included all the susceptible genes,while the second one included the resistance *** the greenhouse test,the reaction pattern of five races produced 100%resistance under artificial inoculation with eight genes showing complete resistance to all *** completely resistant genes:Pii,Pik-s,Piz,Piz-5(=bi2)(t),Pita(=Pi4)(t),Pita,Pi b and Pi1 as well as clustering analysis confirmed the *** the F1 crosses,the results showed all the 25 crosses were resistant for leaf blast disease under field ***,the results in F2 population showed seven crosses with segregation ratio of 15(R):1(s),two cross gave segregated ratio of 3 R:1 s and one gave 13:*** the identification of blast resistance genes in the parental lines,the marker K3959,linked to Pik-s gene and the variety IRBLKs-F5 carry this gene,which was from the monogenic *** results showed that four genotypes;sakha 105,sakha 103,sakha 106 and IRBLKs-F5 were carrying Pik-s gene,while was absent in the sakha 101,sakha 104,IRBL5-M,IRBL9-W,IRBLTACP1 and IRBL9-W(R)*** for Pi 5 gene,the results showed that it was present in sakha 103 and sakha 104 varieties and absent in the rest of the *** addition,Pita-Pita-2 gene was found in the three Egyptian genotypes(sakha 105,sakha 101 and sakha 104)plus IRBLTACP1 *** F2 generation,six populations were used to study the inheritance of blast resistance and s

关键词： Biotechnology tools clustering analysis monogenic lines resistance genes breeding Oryza sativa L.

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Large magnetocaloric effect and magnetic properties of EuRhO_(3)

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Journal of Rare Earths 2024年第9期42卷 1724-1729,I0004页

作者： M.Lassri M.sajieddine A.elouafi A.el Hachmi s.el Ouahbi R.Moubah Laboratory of Energy and Materials Engineering(LGEM) University of Sultan Moulay SlimaneFaculty of Science and Technology(FST)BP 52323000Béni-MellalMorocco Institute of Applied Physics(IAP)-school of Industrial Management(EMINEs) Mohammed Ⅵ Polytechnic UniversityHay Moulay RachidLot 6603150Ben GuerirMorocco National school of Applied sciences(ENsA) University of Sultan Moulay SlimaneBP 7725000KhouribgaMorocco Laboratory of Mechanics Production and Industrial Engineering(LMPGI)Higher School of Technology of Casablanca(ESTC)University of Hassan Ⅱ CasablancaCasablancaMorocco Laboratory of Radiation on Matter and Instrumentation(LRMI) Faculty of Science and Technology(FST)SettatHassan Ⅰ UniversitySettatMorocco Laboatory of Physics of Advanced Materials and Thermic(LPMAT) Faculty of Science Ain Chock(FSAC)University of Hassan Ⅱ CasablancaCasablancaMorocco

We report on the structural,magnetic,and magnetocaloric properties of EuRhO_(3) *** oxidation states of Eu and Rh ions were studied using X-ray photoelectron spectroscopy(XPs).It is found that the Eu ions are mainly in the divalent oxidation state while the Rh ions have+4 ***_(3) powders are found to be antiferromagnetic with a second order magnetic transition at Neel temperature(T_(N)=2.9 K).Analysis of the magnetic susceptibility versus temperature data in terms of the Curie=Weiss law:(χ=C/(T-θ_(W))) for T>T_(N),yields θ_(W)=-3.1 K and effective magne tic moment μ_(ff)^(exp),which is close to the theoretical value μ_(eff)^(theo).The magnetic entropy change(-Δ_(sM)),was determined by em ploying the thermodynam ic Maxwell's *** μ_0H=5 T and near T_(N),Δs_(M)^(Max) and relative cooling power(RCP) exhibit large values of 33.7 J/(kg·K) and 238 J/kg,*** large magnitude of-Δ_(sM) and RCP show that the EuRhO_(3) compound could be a potential candidate to be used in cryogenic magnetic refrigeration.

关键词： X-ray photoelectron spectroscopy Cryogenic magnetic refrigeration Magnetic properties Magnetocaloric effect Rare earths

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Efficient Deep CNN Model for COVID-19 Classification

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Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： Walid el-shafai Amira A.Mahmoud el-sayed M.el-Rabaie Taha E.Taha Osama F.Zahran Adel s.el-Fishawy mohammed Abd-elnaby Fathi E.Abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection was initially acknowledged as a global pandemic in Wuhan in *** Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death *** X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis *** are numerous ways to identify positive COVID-19 *** of the fundamental ways is radiology imaging through CXR,or CT *** comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high ***,automated classification techniques are required to facilitate the diagnosis *** Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical *** deep Convolutional Neural Networks(CNNs)can learn and extract essential features from different medical image *** this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is *** activation functions as well as three optimizers are tested and compared for this *** proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train *** performance is tested and investigated on the CT and CXR *** activation functions:Tanh,sigmoid,and RelU are compared using a constant learning rate and different batch *** optimizers are studied with different batch sizes and a constant learning ***,a comparison between different combinations of activation functions and optimizers is presented,and the optimal configuration is ***,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early *** proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset with training times of 58 min and 46 min on CXR an

关键词： COVID-19 image classification CNN DL activation functions optimizers

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Exploitation of the antibacterial,antibiofilm and antioxidant activities of salvadora Persica(Miswak)extract

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Journal of Bioresources and Bioproducts 2023年第1期8卷 59-65页

作者： Gamal M.el-sherbiny Ahmed Mohamed Gazelly mohammed H.sharaf saad A.Moghannemm shehata M.E Mahmoud K.A.Ismail Ahmad s.el-Hawary Botany and Microbiology Department Faculty of Science(Boys)Al-Azhar UniversityCairo 11884Egypt

The salvadora persica(***)*** stick,usually known as miswak,is still being em-ployed as an oral hygiene agent for plaque and gingivitis *** study aims to assess the antibacterial,antibiofilm,antioxidant,and phytochemical profile of *** *** ***-sica was purchased from a local market,grinded and extracted with petroleum *** disk dif-fusion,microdilution,and micro-plate assays were performed to evaluate the antibacterial and an-tibiofilm activities of the prepared extract at different concentrations against𝛽-lactam resistance streptococcus *** radical scavenging 2,2-diphenyl-1-picrylhydrazyl(DPPH)and stable radical cationic chromophore,2,2-azinobis-(3-ethylbenzothiazoline-6-sulfonate)(ABTs)methods were used to determine their antioxidant *** and spectrometric analyses were performed using gas chromatography-mass(GC-Ms)*** minimum inhibitory concentration(MIC)of *** extract against𝛽-lactam resistance streptococcus species ranged from 6.25 to 12.5 mg/*** maximum suppression of biofilm formation by *** extract was observed at MIC with a percentage of 68.66%,against streptococcus *** *** ex-tract exhibited antioxidant activity with IC 50 of 20μg/mL and 35μg/mL from DPPH and ABTs,*** phytochemical characterization showed the presence of 22 compounds with ma-jor compounds;benzyl isothiocyanate(36.21%)and n-hexadecanoic acid(27.62%).The *** extract exhibited antibacterial activity against𝛽-lactam resistant streptococcus species,showing a promising natural alternative that could be a treatment option.

关键词： β-lactam resistance streptococcus species s.persica extract Antibacterial Antibiofilm Antioxidant GC-Ms analysis

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Correction:A Lightweight Approach for skin Lesion Detection through Optimal Features Fusion

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Computers, Materials & Continua 2025年第1期82卷 1459-1459页

作者： Khadija Manzoor Fiaz Majeed Ansar siddique Talha Meraj Hafiz Tayyab Rauf mohammed A.el-Meligy Mohamed sharaf Abd elatty E.Abd elgawad Department of Information Technology University of GujratGujrat50700Pakistan Department of software Engineering University of GujratGujrat50700Pakistan Department of Computer science COMSATS University Islamabad-Wah CampusWah Cantt47040Pakistan Independent Researcher BradfordBD80HSUK Advanced Manufacturing Institute King Saud UniversityRiyadh11421Saudi Arabia Department of Industrial Engineering College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

In the article“A Lightweight Approach for skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar siddique,Talha Meraj,Hafiz Tayyab Rauf,mohammed ***-Meligy,Mohamed sharaf,Abd elatty *** elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–***:10.32604/cmc.2022.018621,URL:https://***/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab *** of“Centre for smart systems,AI and Cybersecurity,staffordshire University,stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80Hs,UK”.

关键词： Fusion skin Feature

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Decoding molecular mechanisms:brain aging and Alzheimer's disease

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Neural Regeneration Research 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay Ali syed Hammad Qaiser Mohammad Uzair Khalid Al-Regaiey Roaa Khallaf Lubna Abdullah mohammed Albassam Imdad Kaleem Xueyi Wang Ran Wang Mehwish sBhatti shahid Bashir Atta-ur-Rahman school of Applied Biosciences(AsAB) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological sciences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Physiology College of MedicineKing Saud UniversityRiyadhSaudi Arabia Department of Neurology Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Mental Health Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Biosciences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Psychiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Institute of Hebei Medical University ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuroscience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for *** aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as Alzheimer's *** these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging *** these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect *** review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of Alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly Alzheimer's disease.

关键词： Alzheimer’s disease brain aging cognitive health dementia molecular mechanisms neuronal activity neuroplasticity neurotransmission

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