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Launching of the Sultan Qaboos Comprehensive Cancer Care and Research Center(SQCCCRC)in the Sultanate of Oman to manage HBP type of cancers

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Hepatobiliary Surgery and Nutrition 2022年第2期11卷 338-339页

作者： Abdallah al Farai mansour al Moundhri Fabrizio Panaro Department of Surgi.al Oncology Sultan Qaboos Comprehensive Cancer Care and Research CentreMuscatSultanate of Oman Sultan Qaboos Comprehensive Cancer Care and Research Centre MuscatSultanate of Oman Department of Surgery/Division of HBP Surgery and Transplantation St.Eloi HospitalMontpellier University Hospital-School of MedicineMontpellierFrance

in July 2021 a new governmental cancer center,the Sultan Qaboos Comprehensive Cancer Care and Research Centre(SQCCCRC)(Figure 1)open its doors to provide excellent,evidenced-based patient-centered care for cancer patients in the Sultanate of *** is dedicated to treat cancer patients while building an environment to continuously advance clini.al and scientific innovation in the treatment of Cancer.

关键词： Cancer Care cancer

Deep Learning Approach for COViD-19 Detection in Computed Tomography images

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Computers, Materials & Continua 2021年第5期67卷 2093-2110页

作者： Mohamad Mahmoud al Rahhal Yakoub Bazi Rami M.Jomaa mansour Zuair Naif al Ajlan Department of Applied Computer Science College of Applied Computer EngineeringKing Saud UniversityRiyadh11362Saudi Arabia Department of Computer Engineering College of Computer and Information ScienceKing Saud UniversityRiyadh11362Saudi Arabia Department of Computer Science College of Computer and Information ScienceKing Saud UniversityRiyadh11362Saudi Arabia

With the rapid spread of the coronavirus disease 2019(COViD-19)worldwide,the establishment of an accurate and fast process to diagnose the disease is *** routine real-time reverse transcription-polymerase chain reaction(rRT-PCR)test that is currently used does not provide such high accuracy or speed in the screening *** the good choices for an accurate and fast test to screen COViD-19 are deep learning *** this study,a new convolutional neural network(CNN)framework for COViD-19 detection using computed tomography(CT)images is *** EfficientNet architecture is applied as the backbone structure of the proposed network,in which feature maps with different scales are extracted from the input CT scan *** addition,atrous convolution at different rates is applied to these multi-scale feature maps to generate denser features,which facilitates in obtaining COViD-19 findings in CT scan *** proposed framework is also evaluated in this study using a public CT dataset containing 2482 CT scan images from patients of both classes(i.e.,COViD-19 and non-COViD-19).To augment the dataset using additional training examples,adversarial examples generation is *** proposed system validates its superiority over the state-of-the-art methods with values exceeding 99.10%in terms of several metrics,such as accuracy,precision,recall,and *** proposed system also exhibits good robustness,when it is trained using a small portion of data(20%),with an accuracy of 96.16%.

关键词： COViD-19 deep learning computed tomography multi-scale features atrous convolution adversarial examples

intelligent Deep Data Analytics Based Remote Sensing Scene Classification Model

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Computers, Materials & Continua 2022年第7期72卷 1921-1938页

作者： Ahmed althobaiti abdullah alhumaidi.alotaibi Sayed Abdel-Khalek Suliman A.alsuhibany Romany F.mansour Department of Electri.al Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Science and Technology College of RanyahTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics College of ScienceP.O.Box 11099Taif UniversityTaif21944Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Latest advancements in the integration of camera sensors paves a way for newUnmannedAerialVehicles(UAVs)applications such as analyzing geographi.al(spatial)variations of earth science in mitigating harmful environmental impacts and climate *** have achieved significant attention as a remote sensing environment,which captures high-resolution images from different scenes such as land,forest fire,flooding threats,road collision,landslides,and so on to enhance data analysis and decision *** scene classification has attracted much attention in the examination of earth data captured by *** paper proposes a new multi-modal fusion based earth data classification(MMF-EDC)*** MMF-EDC technique aims to identify the patterns that exist in the earth data and classifies them into appropriate class *** MMF-EDC technique involves a fusion of histogram of gradients(HOG),local binary patterns(LBP),and residual network(ResNet)*** fusion process integrates many feature vectors and an entropy based fusion process is carried out to enhance the classification *** addition,the quantum artificial flora optimization(QAFO)algorithm is applied as a hyperparameter optimization *** AFO algorithm is inspired by the reproduction and the migration of flora helps to decide the opti.al parameters of the ResNet model namely learning rate,number of hidden layers,and their number of ***,Variational Autoencoder(VAE)based classification model is applied to assign appropriate class labels for a useful set of feature *** proposedMMF-EDCmodel has been tested using UCM and WHU-RS *** proposed MMFEDC model attains exhibits promising classification results on the applied remote sensing images with the accuracy of 0.989 and 0.994 on the test UCM and WHU-RS dataset respectively.

关键词： Remote sensing unmanned aerial vehicles deep learning artificial intelligence scene classification

Facies development and sedimentology of the Middle Miocene carbonates of the Raghama Formation, northeastern Saudi Arabia

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Acta Geochimica 2024年第1期43卷 87-96页

作者： mansour H.al-Hashim Abdelbaset S.El-Sorogy Meshal Wadani Department of Geology and Geophysics College of ScienceKing Saud University2455Riyadh 11451Saudi Arabia

Ragahama Formation comprises a siliciclastic continental deposits followed by marine carbonates, representing prograding alluvial fans from adjacent high hinterlands seaward into lagoons and fringing reef environments. The present work aimed to document the facies development and sedimentology of the Raghama carbonates exposed along the eastern coastal plain of the Red Sea, northwestern Saudi Arabia. Four stratigraphic sections were measured and sampled(D1–D4) and thin sections and major and trace element analyses were prepared and applied for petrographic and geochemi.al approaches. The carbonates were subdivided into three successive fore-reef, reef-core, and back-reef depositional facies. Sandy stromatolitic boundstone, microbial laminites, dolomitic ooi.al grainstone, bioclastic coralline algal wackestone, sandy bioclastic wackestone, and coral boundstones were the reported microfacies types. Petrographic analysis reveals that the studied carbonates were affected by dissolution, dolomitization, and aggrading recrystallization, which affects both the origi.al micrite matrix and grains or acts as fracture and veinlet filling leading to widespread vuggy and moldic porosity. No evidence of physi.al compaction, suggesting rapid lithification and recrystallization during early diagenesis and prior to substantial burial and intensive flushing by meteoric waters. Most of the origi.al microstructure of corals were leached and destructed. This is indicated by the higher depletion in Sr and Ca levels and increase in Mg,Na, Fe, and Mn levels, especially in section D1, in comparison with the worldwide carbonates.

关键词： Raghama Formation Miocene Diagenesis Geochemistry Saudi Arabia

Hepatocellular carcinoma with complete response to the immunotherapy:the oncologist’s dilemma

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Hepatobiliary Surgery and Nutrition 2022年第1期11卷 119-122页

作者： mansour al-Moundhri Antonio Cubisino Fabrizio Panaro Medi.al Oncology Department Sultan Qaboos Comprehensive Cancer CenterSultan Qaboos UniversityMuscatOman Department of Surgery University of Illinois at ChicagoChicagoILUSA Department of Surgery Montpellier University HospitalMontpellierFrance Surgi.al Oncology Department Sultan Qaboos Comprehensive Cancer CenterSultan Qaboos UniversityMuscatOman

Hepatocellular carcinoma(HCC)is the seventh most common cancer and the fourth leading cause of cancer-related death worldwide(1).During the last decade,many efforts have been made to improve patient survi.al by conducting clini.al trials investigating local and systemic treatment options for patients with unresectable ***,despite significant research efforts,only few treatment approaches have been validated for HCC.

关键词： cancer immunotherapy clini.al

Y^(3+) substituting-adjusted mechani.al,dielectric,and impedance properties of cobalt copper zinc nanoferrites for high frequency applications

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Journal of Rare Earths 2023年第10期41卷 1597-1605,I0005页

作者： S.F.mansour N.S.al-Bassami M.Afifi M.A.Abdo Physics Department Faculty of ScienceZagazig UniversityZagazigEgypt General Studies Department Jubail Industrial CollegeJubail Industrial CitySaudi Arabia Faculty of Nanotechnology for Postgraduate Studies Cairo UniversityEl-Sheikh Zayed12588Egypt

Upgrading mechani.al-dielectric features of ferrites through rare-earth yttrium(Y^(3+))doping provides feasibility to evolving high-frequency electronic *** paper reports the mechani.al and dielectric properties of Co_(0.5)Cu_(0.25)Zn_(0.25)Y_(x)Fe_(2-x)O_(4)ferrite nanoparticles labeled as CCZYF#0,CCZYF#1,CCZYF#2,CCZYF#3,CCZYF#4 and CCZYF#5 for x=0.***.0.02,0.04,0.06,0.08,and 0.1,*** frequency and temperature dependence of dielectric parameters and co nductivity of all CCZYF nanoferrites are well *** nanoferrite CCZYF#5 has the highest dielectric constant(enhancing ratio 170%)and the highest conductivity(enhancing ratio 7125.81%)compared with the undoped *** plots of all CCZYF nano ferrites manifest two arcs;the main reasons for the dielectric process are the grain boundaries and bulk *** impedance parameters were determined,which showed the effective role of Y^(3+)ions on their *** nanoferrite CCZYF#5 has the highest grain boundaries capacitance(with enhancing ratio of 59.40%)and the highest grains capacitance(with enhancing ratio of 22.53%)with a relaxation time decrement efficiency of 62.51%.An ultrasonic flaw detector was utilized to determine the elastic moduli of all CCZYF *** nanoferrite CCZYF#5 has the highest longitudi.al modulus(with enhancing ratio of 20.95%),the highest shear modulus(with enhancing ratio of48.72%),highest Young's modulus(with enhancing ratio of 88.47%),the highest bulk modulus(with enhancing ratio 13.27%)and the highest micro hardness(with enhancing ratio 77.77%).Hence,Y3+tuned Co-Cu-Zn nanoferrites possess new opportunities for high-frequency and storage applications.

关键词： Nanoferrites Rare arth ions Mechani.al properties Dielectric parameters impedance spectroscopy

Application of Plant Growth-Promoting Bacteria as an Eco-Friendly Strategy for Mitigating the Harmful Effects of Abiotic Stress on Plants

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Phyton-international Journal of Experimental Botany 2023年第12期92卷 3305-3321页

作者： Ahmed Hassan Abdou Omar abdullah alkhateeb Hossam Eldin Hamed mansour Hesham S.Ghazzawy Muayad Saud albadrani Nadi Awad al-harbi Wasimah B.al-Shammari Khaled Abdelaal Social Studies Department College of ArtsKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Agribusiness and Consumer Sciences College of Agriculture&Food SciencesKing Faisal UniversityAl-Ahsa31982Saudi Arabia Agribusiness and Consumer Sciences Department College of Agricultural and Food SciencesKing Faisal UniversityAl-Ahsa31982Saudi Arabia Date Palm Research Center of Excellence King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Family and Community Medicine College of MedicineTaibah UniversityAl-Madinah Al-Munawara42353Saudi Arabia Biology Department University College of TaymaUniversity of TabukTabukSaudi Arabia Department of Biology College of ScienceUniversity of HailP.O.Box 2440Hail55476Saudi Arabia EPCRS Excellence Center Plant Pathology and Biotechnology LaboratoryAgricultural Botany DepartmentFaculty of AgricultureKafrelsheikh University33516Egypt

Plant growth-promoting bacteria(PGPB)play an important role in improving agricultural production under several abiotic stress *** can be used to increase crop growth and development through hormonal balance and increase nutrient *** positive effect of PGPB may be due to its pivotal role in morphophysiologi.al and biochemi.al characteristics like leaf number,leaf area,and stem ***,relative water content,chlorophyll content,carotenoids,antioxidant enzymes,and plant hormones were improved with PGPB *** yield and yield components were also increased with PGPB treatment in numerous *** anatomi.al structure of plant organs was increased such as lamina thickness,stem diameter,xylem vessel diameter,and number of xylem vessels as well as phloem thickness under treatment with ***,PGPB can alleviate the negative effects of several abiotic stresses by regulating the antioxidant defense system to scavenge the reactive oxygen species resulting in an improvement of yield production in the stressed ***,gene expressions were controlled by calcium ion modulation during secondary messengers that act upon calcium-dependent protein kinase and protein *** includes many transcription factors such as MYB,AP2/ERF,bZiP,and NAC which regulate genes related to salinity stress *** can demonstrate induction genes of signaling under abiotic stress *** review gives an outline of the PGPB role in alleviating the harmful effects of abiotic factors such as salinity,drought,and heat associated with the improvement of the morpho-physiologi.al and biochemi.al features especially,leaves and branches number,leaf area,antioxidant compounds,plant hormones,and relative water content.

关键词： PGPB salinity drought heat reactive oxygen species antioxidants gene expressions

An Opti.al Big Data Analytics with Concept Drift Detection on High-Dimensional Streaming Data

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Computers, Materials & Continua 2021年第9期68卷 2843-2858页

作者： Romany F.mansour Shaha al-Otaibi Amal al-Rasheed Hanan aljuaid irina V.Pustokhina Denis A.Pustokhin Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia

Big data streams started becoming ubiquitous in recent years,thanks to rapid generation of massive volumes of data by different *** is challenging to apply existing data mining tools and techniques directly in these big data *** the same time,streaming data from several applications results in two major problems such as class imbalance and concept *** current research paper presents a new Multi-Objective Metaheuristic Optimization-based Big Data Analytics with Concept Drift Detection(MOMBD-CDD)method on High-Dimensional Streaming *** presented MOMBD-CDD model has different operational stages such as pre-processing,CDD,and ***-CDD model overcomes class imbalance problem by Synthetic Minority Over-sampling Technique(SMOTE).in order to determine the oversampling rates and neighboring point values of SMOTE,Glowworm Swarm Optimization(GSO)algorithm is ***,Statisti.al Test of Equal Proportions(STEPD),a CDD technique is also ***,Bidirectional Long Short-Term Memory(Bi-LSTM)model is applied for *** order to improve classification performance and to compute the optimum parameters for Bi-LSTM model,GSO-based hyperparameter tuning process is carried *** performance of the presented model was evaluated using high dimensional benchmark streaming datasets namely intrusion detection(NSL KDDCup)dataset and ECUE spam *** extensive experimental validation process confirmed the effective outcome of MOMBD-CDD *** proposed model attained high accuracy of 97.45%and 94.23%on the applied KDDCup99 Dataset and ECUE Spam datasets respectively.

关键词： Streaming data concept drift classification model deep learning class imbalance data

Numeri.al prediction of hydrodynamic cavitating flow structures and their corresponding erosion

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Journal of Hydrodynamics 2021年第3期33卷 546-571页

作者： Amirhossein Mohammadkhani mansour alizadeh Department of Mechani.al Engineering Iran University of Science and TechnologyTehranIran

Hydrodynamic cavitating flows usually consist of 3-D intense vorti.al flows that are detached from solid *** vorti.al flows normally generate heaps of cavitating flow structures,which,in turn,govern the location of cavitation erosion before ***,this study introduces a new numeri.al approach based on the improved delayed detached eddy simulation(iDDES)turbulence modeling for predicting cavitating ***,the solution of compressible Eulerian-Eulerian two-phase flow and the iDDES turbulence model was linked to the microjet hypothesis and unsteady behavior of pressure and vapor volume to predict the corresponding erosion of cavitating *** method for cavitation erosion prediction,a modified version taken from previous studies,was applied as a post-processing *** validation of cavitating flow predictions was performed for the first time on the Grenoble axisymmetric nozzle by comparing them with 21 photos of cavitation from the previous experimental *** results showed that the present numeri.al approach estimated various features of hydrodynamic cavitation well,including shedding processes and the length,shape,and collapse of cavitating *** the numeri.al analysis,three main stages were detected for the present cavitating flow,and the vorticity-cavitation interactions were investigated by the vorticity transport *** streak-like and tube-like cavitating(STLiC and TULiC)structures were introduced in the second stage,initiated by flow instability,and entirely governed by corresponding turbulent flow *** collapse of these cavitating structures is one of the primary sources of cavitation erosion on lower and upper *** results of the numeri.al erosion predictions were compared with those of the previous erosion tests on the Grenoble axisymmetric *** numeri.al performance was achieved in predicting the location and intensity of cavitation erosion.

关键词： Turbulent and cavitating structures cavitation erosion detached vorti.al flow Hybrid RANS-LES turbulence modeling flow instability flow visualization