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Clinicobiochemical investigations of gangrenous mastitis in does:immunological responses and oxidative stress biomarkers

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2013年第1期14卷 33-39页

作者： wael m.EL-DEEB Department of Clinical Studies College of Veterinary Medicine and Animal ResourcesKing Faisal University Department of Veterinary medicine Infectious Diseases and Fish DiseasesFaculty of Veterinary MedicineMansoura University

A total of 50 does were used to determine selected hematological and biochemical parameters with special references to oxidative stress markers, acute phase protein profiles, and proinflammatory cytokines in healthy and gangrenous mastitis affected does. Animals were divided into two equal groups represented as clinically healthy （control） and diseased groups, respectively. The bacteriological examination of milk samples from diseased does revealed many types of bacterial infection. The isolated bacteria were Staphy/ococcus aureus （N=23/25）, Escherichia coil （N=11/25）, and Clostridium perfringens （N=4/25）. There was a significant increase in the levels of β-hydrexybutyrate, non-esterified free fatty acids, triglyceride, low density lipoprotein cholesterol （LDL-C）, aspartate aminotransferase, and alanine aminotransferase and a significant reduction in the levels of glucose, cholesterol, and high density lipoprotein cholesterol （HDL-C） in does with gangrenous mastitis compared to healthy does. moreover, there was a significant increase in the levels of malondialdehyde and uric acid with a significant decrease in the levels of reduced glutathione, super oxide dismutase, and catalase in does with gangrenous mastitis compared to healthy does. In addition, there was a significant increase in the haptoglobin, serum amyloid A, fibrinogen, interleukin 6 （IL-6）, IL-1β, and tumor necrosis factor-a （TNF-a） in does with gangrenous mastitis compared to healthy ones. Conclusively, oxidative stress biomarkers, acute phase proteins, and proinflammatory cytokines play an essential task as biomarkers for gangrenous mastitis in does. mastitis may be considered as one of the ketotic stressors in does after parturition.

关键词： Haptoglobin Serum amyloid A malondialdehyde Interleukin 1β Interleukin 6 Tumor necrosis factor-a

Thomson and rotation effects during photothermal excitation process in magnetic semiconductor medium using variable thermal conductivity

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Applied mathematics and mechanics(English Edition) 2020年第6期41卷 909-926页

作者： K.lotfy A.K.KHAmIS A.A.EL-BARY m.H.AHmED Department of mathematics Faculty of ScienceZagazig UniversityZagazig 44519Egypt Department of mathematics Faculty of ScienceTaibah UniversityAl-Madinah 30002Saudi Arabia Department of mathematics Faculty of ScienceNorthern Border UniversityArar 91431Saudi Arabia Arab Academy for Science Technology and Maritime TransportAlexandria 1029Egypt

This study investigates a strong magnetic field acting over an elastic rotator semiconductor *** Thomson effect due to the magnetic field during the photothermal transport process is studied,and the thermoelectricity theory is used to explain the behavior of waves in the homogenous and isotropic medium under the effect of variable thermal *** variable thermal conductivity is considered as a linear function of the *** two-dimensional deformation equations are used to describe the overlaps among plasma,electrical,thermal,and magneto-elastic *** charge density of inertia-particles is considered as a function of time for studying the induced electric *** normal mode analysis is used to obtain the exact solutions of the physical field distributions as part of this *** obtain the complete solutions of the physical field quantities,the certain mechanical loads,electromagnetic effects,thermal effects,and plasma recombination process are applied *** results of the physical distributions are graphically depicted and discussed in consideration of the internal heat source,rotation,and Peltier coefficient.

关键词： photothermal thermal conductivity Thomson effect rotation magnetic field Peltier coefficient

Efficient Data Augmentation Techniques for Improved Classification in Limited Data Set of Oral Squamous Cell Carcinoma

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Computer modeling in Engineering & Sciences 2022年第6期131卷 1387-1401页

作者： wael Alosaimi m.Irfan Uddin Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan

Deep Learning(DL)techniques as a subfield of data science are getting overwhelming attention mainly because of their ability to understand the underlying pattern of data in making *** techniques require a considerable amount of data to efficiently train the DL ***,when the data size is larger,the DL models perform ***,it is not possible to have a considerable amount of data in different domains such as *** healthcare,it is impossible to have a substantial amount of data to solve medical problems using Artificial Intelligence,mainly due to ethical issues and the privacy of *** solve this problem of small dataset,different techniques of data augmentation are used that can increase the size of the training ***,these techniques only change the shape of the image and hence the classification model does not increase *** Adversarial Networks(GANs)are very powerful techniques to augment training data as new samples are *** technique helps the classification models to increase their *** this paper,we have investigated augmentation techniques in healthcare image *** objective of this research paper is to develop a novel augmentation technique that can increase the size of the training set,to enable deep learning techniques to achieve higher *** have compared the performance of the image classifiers using the standard augmentation technique and *** results demonstrate that GANs increase the training data,and eventually,the classifier achieves an accuracy of 90%compared to standard data augmentation techniques,which achieve an accuracy of up to 70%.Other advanced CNN models are also tested and have demonstrated that more deep architectures can achieve more than 98%accuracy for making classification on Oral Squamous Cell Carcinoma.

关键词： Data science deep learning data augmentation classification data manipulation

Thermomagnetic effect with microtemperature in a semiconducting photothermal excitation medium

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Applied mathematics and mechanics(English Edition) 2018年第6期39卷 783-796页

作者： K.lotfy R.KUmAR W.HASSAN m.GABR Department of mathematics Faculty of ScienceZagazig University Department of mathematics Kurukshetra University mathematics and Physics Department Faculty of EngineeringPort Said University

The main goal of this paper is to focus on the investigation of interaction between a magnetic field and elastic materials with microstructure, whose microelements possess microtemperatures with photothermal excitation. The elastic-photothermal prob- lem in one-dimension is solved by introducing photothermal excitation at the free surface of a semi-infinite semiconducting medium （semiconductor rod）. The integral transform technique is used to solve the governing equations of the problem under the effect of the microtemperature field. The analytical expressions for some physical quantities in the physical domain are obtained with the heating boundary surface and free traction. The numerical inversion technique is used to obtain the resulting quantities in the physical domain. The obtained numerical results with some comparisons are discussed and shown graphically.

关键词： photothermal theory carrier density magnetic field microtemperature Laplace transform

Climate change and epidemiology of human parasitoses in Saudi Arabia:A review

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Journal of Coastal Life medicine 2016年第7期4卷 580-588页

作者： wael mohamed lotfy Souad mohamed Alsaqabi Parasitology Department Medical Research InstituteAlexandria UniversityAlexandriaEgypt Biology Department Faculty of ScienceQassim UniversityUnizahSaudi Arabia

Climate change is an emerging global *** has hazardous effects that vary across different geographic regions and *** is anticipated to have significant effects in Saudi *** present work reviews the future of human parasitoses in Saudi Arabia in response to the expected climate *** key projections are increased precipitations,flash floods,unstable temperatures,sea-level rise and shoreline *** environmental changes could strongly influence the epidemiology of fly-borne,mosquito-borne,snail-borne and water-borne human parasitoses in the country.

关键词： Global warming Kingdom of Saudi Arabia Parasites Fly-borne mosquito-borne Snail-borne Water-borne Infection

Leveraging User-Generated Comments and Fused BiLSTm models to Detect and Predict Issues with mobile Apps

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Computers, materials & Continua 2024年第4期79卷 735-759页

作者： wael m.S.Yafooz Abdullah Alsaeedi Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user ***, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-Termmemory (LSTm), and Convolutional Neural Network Long Short-Term memory (CNN-LSTm) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

关键词： mobile apps issues play store user comments deep learning LSTm bidirectional LSTm

Reduced differential transform and Sumudu transform methods for solving fractional financial models of awareness

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Applied mathematics(A Journal of Chinese Universities) 2023年第3期38卷 338-356页

作者： A.m.S.mahdy K.A.Gepreel Kh.lotfy A.El-Bary Department of mathematics and Statistics College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of mathematics Faculty of ScienceZagazig UniversityP.O.Box 44519ZagazigEgypt Arab Academy for Science Technology and Maritime Transport1029AlexandriaEgypt

In that paper,we new study has been carried out on previous studies of one of the most important mathematical models that describe the global economic movement,and that is described as a non-linear fractional financial model of awareness,where the studies are represented at the steps following:One:The schematic of the model is ***:The disease-free equilibrium point(DFE)and the stability of the equilibrium point are ***:The stability of the model is fulfilled by drawing the Lyapunov exponents and Poincare ***:The existence of uniformly stable solutions have ***:The Caputo is described as the fractional ***:Fractional optimal control for NFFmA is discussed by clarifying the fractional optimal control through drawing before and after ***:Reduced differential transform method(RDTm)and Sumudu Decomposition method(SDm)are used to take the resolution of an ***,we display that SDm and RDTm are highly identical.

关键词： financial of awareness stability Lyapunov exponents Poincare map fractional optimal control Hamiltonian

A Quality-aware Incremental LmS Algorithm for Distributed Adaptive Estimation

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International Journal of Automation and computing 2014年第6期11卷 676-682页

作者： wael m.Bazzi Amir Rastegarnia Azam Khalili Electrical and Computer Engineering Department American University in Dubai Dubai United Arab Emirates Department of Electrical Engineering Malayer University Malayer 65719-95863 Iran

In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive networks) are appealing solutions to the mentioned problem when the statistical information of the underlying process is not available or it varies over time. In this paper, our goal is to develop a new incremental least-mean square(LmS) adaptive network that considers the quality of measurements collected by the nodes. Thus, we use an adaptive combination strategy which assigns each node a step size according to its quality of measurement. The adaptive combination strategy improves the robustness of the proposed algorithm to the spatial variations of signal-to-noise ratio(SNR). The performance of our algorithm is more remarkable in inhomogeneous environments when there are some nodes with low SNRs in the network. The simulation results indicate the efficiency of the proposed algorithm.

关键词： Adaptive networks distributed estimation least mean-square (LmS) incremental cooperation quality aware

PeachNet: Peach Diseases Detection for Automatic Harvesting

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Computers, materials & Continua 2021年第5期67卷 1665-1677页

作者： wael Alosaimi Hashem Alyami m.Irfan Uddin Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan

To meet the food requirements of the seven billion people on Earth,multiple advancements in agriculture and industry have been *** main threat to food items is from diseases and pests which affect the quality and quantity of *** scientific mechanisms have been developed to protect plants and fruits from pests and diseases and to increase the quantity and quality of *** these mechanisms require manual efforts and human expertise to diagnose *** the current decade Artificial Intelligence is used to automate different processes,including agricultural processes,such as automatic *** Learning techniques are becoming popular to process images and identify different *** can use machine Learning algorithms for disease identification in plants for automatic harvesting that can help us to increase the quantity of the food produced and reduce crop *** this paper,we develop a novel Convolutional Neural Network(CNN)model that can detect diseases in peach plants and *** proposed method can also locate the region of disease and help farmers to find appropriate treatments to protect peach *** the detection of diseases in Peaches VGG-19 architecture is *** the localization of disease regions mask R-CNN is *** proposed technique is evaluated using different techniques and has demonstrated 94%*** hope that the system can help farmers to increase peach production to meet food demands.

关键词： Convolutional neural network computer vision image processing segmentation plant diseases