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Relationship between peripheral arterial disease, carotid intima-media thickness and C-reactive protein in elderly diabetic patients

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Advances in Aging Research 2013年第4期2卷 115-120页

作者： Moatassem Salah Amer Samia Ahmed Abdul-Rahman Wafaa Mostafa Abd-El Gawad Ibrahim Ahmad abdel Aal Ahmad abdel khalek abdel Razek mohamed Wessam El-Huseiny Moustafa abdel Wahab Clinical Pathology Department Faculty of Medicine Mansoura University Mansoura Egypt Geriatrics and Gerontology Department Faculty of Medicine Ain Shams University Cairo Egypt Geriatrics and Gerontology Department Faculty of Medicine Mansoura University Mansoura Egypt Radiodiagnosis Department Faculty of Medicine Mansoura University Mansoura Egypt

Purpose: To study the association between carotid intima media thickness (CIMT) and high sensitivity CRP (hs-CRP) level as markers for PAD in elderly patients with DM. Subjects: A case-control study on 90 participants aged 60 years and older divided into 60 cases (30 patients with DM alone and 30 patients with DM and comorbidities) and 30 healthy controls. All were assessed by measuring CIMT, ankle brachial index (AB), and markers for cardiovascular disease such as high-sensitivity CRP (hs-CRP), total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and low density lipoprotein (LDL). Results: hs-CRP levels showed statistically significant difference being highest among patients with DM and comorbidities and lowest among controls (P < 0.001). Also, symptoms of PAD were significantly higher among cases than controls. ABI was able to detect PAD in many asymptomatic patients. Color changes were present in only 43.30% (n = 26) of positive PAD cases while delayed wound healing, claudication pain, rest pain, cold extremities, and trophic changes were present in 23.30% (n = 14), 16.71% (n = 10), 16.71% (n = 10), 45.00% (n = 27), and 21.7% (n = 13). Using logistic regression analysis revealed that DM, CIMT, and hs-CRP were independent predictors for PAD (OR = 4.194, 7.236, 1.003;P value = 0.044, 0.25, 0.031) after adjustment of other coronary risk factors such as sex, smoking, hypertension, TC, and TG. Conclusion: Diabetic elderly have higher prevalence of asymptomatic PAD thannon-diabetics using solely ABI. DM, CIMT, and hs-CRP are independent predictors for the occurrence of PAD. Hs-CRP levels are highest among diabetics with comorbidities.

关键词： Peripheral Arterial Disease Carotid Intima-Media Thickness Ankle Brachial Index C-Reactive Protein Elderly

A geometric phase for superconducting qubits under the decoherence effect

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Chinese Physics B 2013年第10期22卷 88-93页

作者： S.abdel-khalek K.Berrada mohamed A.El-Sayed M.Abel-Aty Mathematics Department Faculty of ScienceSohag University82524 SohagEgypt Mathematics Department Faculty of ScienceTaif UniversityTaifSaudi Arabia Al Imam Mohammad Ibn Saud Islamic University (IMSIU) College of ScienceDepartment of PhysicsRiyadhSaudi Arabia The Abdus Salam International Centre for Theoretical Physics Strada Costiera 11Miramare-TriesteItaly Laboratoire de Physique The'orique Faculte' des SciencesUniversite' Mohammed V-AgdalAvenue Ibn BattoutaBote Postale 1014Agdal RabatMorocco Informatics Department Faculty of ScienceTaif UniversityTaifSaudi Arabia

We propose a relaxation rate or dissipative cavity-based parameters that can be used as indicators of the stationary limit of a mixed state geometric phase. We perform our considerations for the system of a superconducting qubit in an open transmission line or interacting with a dissipative cavity. This system is very useful for performing an effective quantum computation by exhibiting the long collapse time of the geometric phase. It is shown that the geometric phase in the stationary limit does not depend on interaction time if the decay time exceeds an upper bound.

关键词： superconducting-qubit meometric phase mixed state decoherence

Effects of P301L-TAU on post-translational modifications of microtubules in human iPSC-derived cortical neurons and TAU transgenic mice

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Neural Regeneration Research 2025年第8期20卷 2348-2360页

作者： mohamed Aghyad Al Kabbani Christoph Köhler Hans Zempel Institute of Human Genetics Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany Center for Molecular Medicine Cologne(CMMC) University of CologneCologneGermany Center Anatomy Department ⅡMedical FacultyUniversity of CologneCologneGermany

TAU is a microtubule-associated protein that promotes microtubule assembly and stability in the *** is missorted and aggregated in an array of diseases known as *** are essential for neuronal function and regulated via a complex set of post-translational modifications,changes of which affect microtubule stability and dynamics,microtubule interaction with other proteins and cellular structures,and mediate recruitment of microtubule-severing *** impairment of microtubule dynamics causes neuronal dysfunction,we hypothesize cognitive impairment in human disease to be impacted by impairment of microtubule *** therefore aimed to study the effects of a disease-causing mutation of TAU(P301L)on the levels and localization of microtubule post-translational modifications indicative of microtubule stability and dynamics,to assess whether P301L-TAU causes stability-changing modifications to *** investigate TAU localization,phosphorylation,and effects on tubulin post-translational modifications,we expressed wild-type or P301L-TAU in human MAPT-KO induced pluripotent stem cell-derived neurons(i Neurons)and studied TAU in neurons in the hippocampus of mice transgenic for human P301L-TAU(p R5 mice).Human neurons expressing the longest TAU isoform(2N4R)with the P301L mutation showed increased TAU phosphorylation at the AT8,but not the p-Ser-262 epitope,and increased polyglutamylation and acetylation of microtubules compared with endogenous TAU-expressing neurons.P301L-TAU showed pronounced somatodendritic presence,but also successful axonal enrichment and a similar axodendritic distribution comparable to exogenously expressed 2N4R-wildtype-TAU.P301L-TAU-expressing hippocampal neurons in transgenic mice showed prominent missorting and tauopathy-typical AT8-phosphorylation of TAU and increased polyglutamylation,but reduced acetylation,of microtubules compared with non-transgenic *** sum,P301L-TAU results in changes in micr

关键词： human induced pluripotent stem cell microtubules P301L pR5 mice TAU tauopathy tubulin code

Intelligent Deep Learning Based Disease Diagnosis Using Biomedical Tongue Images

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Computers, Materials & Continua 2022年第3期70卷 5667-5681页

作者： V.Thanikachalam S.Shanthi K.Kalirajan Sayed abdel-khalek mohamed Omri Lotfi M.Ladhar Sri Sivasubramaniya Nadar College of Engineering Chennai603110India Department of Information Technology Department of Electronics and Communication EngineeringCARE College of EngineeringTiruchirappalli620009India Department of Electronics and Communication Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Department of Mathematics and Statistics College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Mathematics Department Faculty of ScienceSohag UniversitySohagEgypt Deanship of Scientific Research King Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia

The rapid development of biomedical imaging modalities led to its wide application in disease ***-based diagnostic procedures are proficient and non-invasive in nature to carry out secondary diagnostic processes ***,physicians examine the characteristics of tongue prior to *** this scenario,to get rid of qualitative aspects,tongue images can be quantitatively inspected for which a new disease diagnosis model is *** model can reduce the physical harm made to the *** tongue image analytical methodologies have been proposed ***,there is a need exists to design an intelligent Deep Learning(DL)based disease diagnosis *** this motivation,the current research article designs an Intelligent DL-basedDisease Diagnosis method using Biomedical Tongue Images called IDLDD-BTI *** proposed IDLDD-BTI model incorporates Fuzzy-based Adaptive Median Filtering(FADM)technique for noise removal ***,SqueezeNet model is employed as a feature extractor in which the hyperparameters of SqueezeNet are tuned using Oppositional Glowworm Swarm Optimization(OGSO)*** last,Weighted Extreme Learning Machine(WELM)classifier is applied to allocate proper class labels for input tongue color *** design of OGSO algorithm for SqueezeNet model shows the novelty of the *** assess the enhanced diagnostic performance of the presented IDLDD-BTI technique,a series of simulations was conducted on benchmark dataset and the results were examined in terms of several *** resultant experimental values highlighted the supremacy of IDLDD-BTI model over other state-of-the-art methods.

关键词： Biomedical images image processing tongue color image deep learning squeezenet disease diagnosis

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia mohamed Elhassan Saad mohamed Darwish Saleh Mesbah Elkaffas Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and Information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

The effect of atomic spontaneous decay on the dynamics of the negativity of the Wigner function of radiation

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Chinese Physics B 2011年第9期20卷 44-48页

作者： abdel-Baset A.mohamed Faculty of Science Assiut UniversityAssiutEgypt

The exact solution of the master equation for the case of a high-Q cavity with atomic decay is found. We use the negativity of the Wigner function （WF） as an indicator of nonclassicality. It is found that the negative values of the field WF are very sensitive to any change in the damping parameter. The atomic spontaneous decay leads to the simultaneous disappearance of both entanglement and nonclassicality of quantum states. Moreover, the purity of the field states is completely lost.

关键词： non-classicality entanglement atomic decay

Combining Committee-Based Semi-Supervised Learning and Active Learning

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Journal of Computer Science & Technology 2010年第4期25卷 681-698页

作者： mohamed Farouk abdel Hady Friedhelm Schwenker Institute of Neural Information Processing University of Ulm

Many data mining applications have a large amount of data but labeling data is usually difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supervised learning addresses this problem by using unlabeled data together with labeled data in the training process. Co-Training is a popular semi-supervised learning algorithm that has the assumptions that each example is represented by multiple sets of features （views） and these views are sufficient for learning and independent given the class. However, these assumptions axe strong and are not satisfied in many real-world domains. In this paper, a single-view variant of Co-Training, called Co-Training by Committee （CoBC） is proposed, in which an ensemble of diverse classifiers is used instead of redundant and independent views. We introduce a new labeling confidence measure for unlabeled examples based on estimating the local accuracy of the committee members on its neighborhood. Then we introduce two new learning algorithms, QBC-then-CoBC and QBC-with-CoBC, which combine the merits of committee-based semi-supervised learning and active learning. The random subspace method is applied on both C4.5 decision trees and 1-nearest neighbor classifiers to construct the diverse ensembles used for semi-supervised learning and active learning. Experiments show that these two combinations can outperform other non committee-based ones.

关键词： data mining classification active learning co-training semi-supervised learning ensemble learning randomsubspace method decision tree nearest neighbor classifier

Optimized Tuned Deep Learning Model for Chronic Kidney Disease Classification

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Computers, Materials & Continua 2022年第2期70卷 2097-2111页

作者： R.H.Aswathy P.Suresh mohamed Yacin Sikkandar S.abdel-khalek Hesham Alhumyani Rashid A.Saeed Romany F.Mansour Department of Computer Science and Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAlMajmaah11952Saudi Arabia Department of Mathematics College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

In recent times,Internet of Things(IoT)and Cloud Computing(CC)paradigms are commonly employed in different healthcare *** gadgets generate huge volumes of patient data in healthcare domain,which can be examined on cloud over the available storage and computation resources in mobile *** Kidney Disease(CKD)is one of the deadliest diseases that has high mortality rate across the *** current research work presents a novel IoT and cloud-based CKD diagnosis model called Flower Pollination Algorithm(FPA)-based Deep Neural Network(DNN)model abbreviated as *** steps involved in the presented FPA-DNN model are data collection,preprocessing,Feature Selection(FS),and ***,the IoT gadgets are utilized in the collection of a patient’s health *** proposed FPA-DNN model deploys Oppositional Crow Search(OCS)algorithm for FS,which selects the optimal subset of features from the preprocessed *** application of FPA helps in tuning the DNN parameters for better classification *** simulation analysis of the proposed FPA-DNN model was performed against the benchmark CKD *** results were examined under different *** simulation outcomes established the superior performance of FPA-DNN technique by achieving the highest sensitivity of 98.80%,specificity of 98.66%,accuracy of 98.75%,F-score of 99%,and kappa of 97.33%.

关键词： Deep learning chronic kidney disease IoT cloud computing feature selection classification

A New Decision-Making Model Based on Plithogenic Set for Supplier Selection

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Computers, Materials & Continua 2021年第3期66卷 2751-2769页

作者： mohamed abdel-Basset Rehab mohamed Florentin Smarandache mohamed Elhoseny Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Math&Science Department University of New MexicoGallupNew Mexico87301USA College of Computer Information Technology American University in the EmiratesDubaiThe United Arab Emirates

Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its *** choice of supplier is a multicriteria decision making(MCDM)to obtain the optimal decision based on a group of *** health care sector faces several types of problems,and one of the most important is selecting an appropriate supplier that fits the desired performance *** development of service/product quality in health care facilities in a country will improve the quality of the life of its *** paper proposes an integrated multi-attribute border approximation area comparison(MABAC)based on the best-worst method(BWM),plithogenic set,and rough *** is applied to regulate the weight vector of the measures in group decision-making problems with a high level of *** the treatment of uncertainty,a plithogenic set and rough number(RN)are used to improve the accuracy of *** set operations are used to deal with information in the desired manner that handles uncertainty and ***,based on the plithogenic aggregation and the results of BWM evaluation,we use MABAC to find the optimal alternative according to defined *** examine the proposed integrated algorithm,an empirical example is produced to select an optimal supplier within five options in the healthcare industry.

关键词： Supplier selection rough set theory MABAC MCDM BWM plithogenic set