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Clinical relevance of circulating non-coding RNAs in metabolic diseases:Emphasis on obesity,diabetes,cardiovascular diseases and metabolic syndrome

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Genes & Diseases 2023年第6期10卷 2393-2413页

作者： Abdullahi Dandare muhammad jawad khan Aisha Naeem Afrose Liaquat Department of Biosciences COMSATS University IslamabadIslamabad 45550Pakistan Department of Biochemistry Usmanu Danfodiyo UniversitySokoto 840104Nigeria Ministry of Public Health POB42DohaQatar Department of Oncology Lombardi Comprehensive Cancer CenterGeorgetown University Medical CenterWashingtonDC 20057USA Shifa College of Medicine Shifa Tameer-E-Millat UniversityIslamabad 45550Pakistan

Non-coding RNAs(ncRNAs)participate in the regulation of several cellular processes including transcription,RNA processing and genome *** aberrant expression of ncRNAs is associated with several pathological *** this review,we focused on recent information to elucidate the role of various regulatory ncRNAs i.e.,micro RNAs(miRNAs),circular RNAs(circRNAs)and long-chain non-coding RNAs(lncRNAs),in metabolic diseases,e.g.,obesity,diabetes mellitus(DM),cardiovascular diseases(CVD)and metabolic syndrome(MetS).The mechanisms by which ncRNAs participated in disease pathophysiology were also *** regulate the expression of genes at transcriptional and translational *** modulate the regulation of gene expression via miRNA sponging activity,interacting with RNA binding protein and polymerase II transcription *** regulate the expression of genes by acting as a protein decoy,miRNA sponging,miRNA host gene,binding to miRNA response elements(MRE)and the recruitment of transcriptional element or chromatin *** examined the role of ncRNAs in the disease pathogenesis and their potential role as molecular markers for diagnosis,prognosis and therapeutic *** showed the involvement of ncRNAs in the onset of obesity and its progression to MetS and ***-192,miRNA-122,and miRNA-221 were dysregulated in all these metabolic *** ncRNAs,implicated in at least three diseases include miRNA-15a,miRNA-26,miRNA-27a,miRNA-320,and *** of ncRNAs increased the risk of development of DM and MetS and its progression to CVD in obese ***,these molecules are potential targets to arrest or delay the progression of metabolic diseases.

关键词： Biomarkers CircRNAs LncRNAs Metabolic diseases miRNAs Non-coding RNAs Therapeutic targets

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Integrated CWT-CNN for Epilepsy Detection Using Multiclass EEG Dataset

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Computers, Materials & Continua 2021年第10期69卷 471-486页

作者： Sidra Naseem Kashif Javed muhammad jawad khan Saddaf Rubab muhammad Attique khan Yunyoung Nam Robotics and Machine Intelligence Engineering School of Mechanical and Manufacturing EngineeringNational University of Sciences and Technology(NUST)Islamabad44000Pakistan National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Computer Science HITEC University TaxilaTaxilaPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Electroencephalography is a common clinical procedure to record brain signals generated by human *** are useful in Brain controlled interfaces and other intelligent Neuroscience applications,but manual analysis of these brainwaves is complicated and time-consuming even for the experts of *** EEG analysis and classification techniques have been proposed to address this problem however,the conventional classification methods require identification and learning of specific EEG characteristics *** learning models can learn features from data without having in depth knowledge of data and prior feature *** of the great implementations of deep learning is Convolutional Neural Network(CNN)which has outperformed traditional neural networks in pattern recognition and image *** Wavelet Transform(CWT)is an efficient signal analysis technique that presents the magnitude of EEG signals as timerelated Frequency *** deep learning architectures suffer from poor performance when classifying EEG signals in the Time-frequency *** improve classification accuracy,we propose an integrated CWT and CNN technique which classifies five types of EEG signals *** compared the results of proposed integrated CWT and CNN method with existing deep learning models e.g.,GoogleNet,VGG16,***,the accuracy and loss of the proposed integrated CWT and CNN method have been cross validated using Kfold cross *** average accuracy and loss of Kfold cross-validation for proposed integrated CWT and CNN method are,76.12%and 56.02%*** model produces results on a publicly available dataset:Epilepsy dataset by UCI(Machine Learning Repository).

关键词： Deep learning electroencephalography epilepsy continuous wavelet transform

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Identification of hsa_circ_0092576 regulatory network in the pathogenesis of coronary heart disease

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Genes & Diseases 2023年第1期10卷 26-28页

作者： Abdullahi Dandare muhammad Rafiq Afrose Liaquat Afraz Ahmad Raj muhammad jawad khan Department of Biosciences COMSATS University IslamabadIslamabad 45550Pakistan Department of Biochemistry Usmanu Danfodiyo University SokotoSokoto P.M.B.2346Nigeria Department of Biochemistry Shifa College of MedicineShifa Tameer-E-Millat UniversityIslamabad 45550Pakistan Department of Psychosomatic Medicine and Psychotherapy University Medical CenterGottingen 37075Germany

Cardiovascular diseases(CVDs)are responsible for 30%of all deaths *** heart disease(CHD),is the most common form of CVD,accounting for 46%of male and 38%female cardiovascular deaths.1 CHD is characterized by chronic inflammation and endothelial injuries in coronary arteries,and subsequent development of atherosclerotic plaques which eventually leads to myocardial ischemia.

关键词： coronary injuries inflammation

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Circulating miR-548c-3p possesses good diagnostic potential for metabolic syndrome

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Genes & Diseases 2023年第3期10卷 683-686页

作者： Abdullahi Dandare Afrose Liaquat muhammad Rafiq Mbah Ntepe Leonel Javeres Sidra Younis muhammad jawad khan Department of Biosciences COMSATS University IslamabadIslamabad 45550Pakistan Department of Biochemistry Usmanu Danfodiyo University SokotoSokoto PMB 2346Nigeria Department of Biochemistry Shifa College of MedicineShifa Tameer-E-Millat UniversityIslamabad 45550Pakistan Institute of Medical Research and Medical Plant Studies Ministry of Scientific ResearchYaoindeCameroon Department of Biological Sciences National University of Medical SciencesRawalpindiPunjab 46000Pakistan

Studies have shown that dysregulated expression of miRNAs is a major underlying event in the onset and progression of many metabolic *** pathological role of miR-548c-3p in various cancer types,including breast cancer,glioma,prostate cancer,and gastric cancer,has been documented.1 However,experimental evidences validating the role of miR-548c-3p in the development of metabolic diseases are still lacking,and no data is available on its diagnostic potential for metabolic syndrome(MS).Recently,we predicted the involvement of miR-548c-3p in the pathogenesis of MS and its progression to cardiovascular diseases(CVD)via the regulation of target genes necessary for the proper function of insulin resistance,mTOR,and JAK/STAT signaling pathways.2 Therefore,we deemed it necessary to engage in wet laboratory analysis and validate these claims in patients with metabolic syndrome compared to healthy individuals.

关键词： JAK/STAT involvement diseases

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Enhanced Accuracy for Motor Imagery Detection Using Deep Learning for BCI

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Computers, Materials & Continua 2021年第9期68卷 3825-3840页

作者： Ayesha Sarwar Kashif Javed muhammad jawad khan Saddaf Rubab Oh-Young Song Usman Tariq National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Software Sejong UniversitySeoulGwangjin-guKorea College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Brain-Computer Interface(BCI)is a system that provides a link between the brain of humans and the hardware *** recorded brain data is converted directly to the machine that can be used to control external *** are four major components of the BCI system:acquiring signals,preprocessing of acquired signals,features extraction,and *** traditional machine learning algorithms,the accuracy is insignificant and not up to the mark for the classification of multi-class motor imagery *** major reason for this is,features are selected manually,and we are not able to get those features that give higher accuracy *** this study,motor imagery(MI)signals have been classified using different deep learning *** have explored two different methods:Artificial Neural Network(ANN)and Long Short-Term Memory(LSTM).We test the classification accuracy on two datasets:BCI competition III-dataset IIIa and BCI competition IV-dataset *** outcome proved that deep learning algorithms provide greater accuracy results than traditional machine learning *** the deep learning classifiers,LSTM outperforms the ANN and gives higher classification accuracy of 96.2%.

关键词： Brain-computer interface motor imagery artificial neural network long-short term memory classification

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Smart-City-based Data Fusion Algorithm for Internet of Things

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Computers, Materials & Continua 2022年第11期73卷 2407-2421页

作者： jawad khan muhammad Amir khan N.Z.Jhanjhi Mamoona Humayun Abdullah Alourani Department of Computer Science IIC University of TechnologyPhnom PenhCambodia Department of Computer Science COMSATS University IslamabadAbbottabad Campus22060Pakistan School of Computer Science and Engineering SCETaylor’s UniversitySubang JayaSelangorMalaysia Department of Information Systems College of Computer and Information SciencesJouf Universityal-JoufKSA Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Increasingly,Wireless Sensor Networks(WSNs)are contributing enormous amounts of *** the recent deployments of wireless sensor networks in Smart City infrastructures,significant volumes of data have been produced every day in several domains ranging from the environment to the healthcare system to *** wireless sensor nodes,a Smart City environment may now be shown for the benefit of *** Smart City delivers intelligent infrastructure and a stimulating environment to citizens of the Smart Society,including the elderly and ***,Quality of Service(QoS)and poor data performance are common problems in WSNs,caused by the data fusion method,where a small amount of bad data can significantly impact the total fusion *** our proposed research,a WSN multisensor data fusion technique employing fuzzy logic for event *** the new proposed Algorithm,sensor nodes will collect less repeated data,and redundant data will be used to increase the data’s overall *** network’s fusion delay problem is investigated,and a minimum fusion delay approach is provided based on the nodes’fusion waiting *** proposed algorithm performs well in fusion,according to the results of the *** a result of these discoveries,It is concluded that the algorithm describe here is effective and dependable instrument with a wide range of applications.

关键词： Internet of things data fusion wireless sensor network fuzzy inference system

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Classification of Citrus Plant Diseases Using Deep Transfer Learning

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Computers, Materials & Continua 2022年第1期70卷 1401-1417页

作者： muhammad Zia Ur Rehman Fawad Ahmed muhammad Attique khan Usman Tariq Sajjad Shaukat Jamal jawad Ahmad Iqtadar Hussain Department of Electrical Engineering HITEC UniversityTaxilaPakistan Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia School of Computing Edinburgh Napier UniversityUK Department of Mathematics Statisticsand PhysicsQatar UniversityDoha2713Qatar

In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and *** in turn has helped in improving the quality and production of vegetables and *** fruits arewell known for their taste and nutritional *** are one of the natural and well known sources of vitamin C and planted *** are several diseases which severely affect the quality and yield of citrus *** this paper,a new deep learning based technique is proposed for citrus disease *** different pre-trained deep learning models have been used in this *** increase the size of the citrus dataset used in this paper,image augmentation techniques are ***,to improve the visual quality of images,hybrid contrast stretching has been *** addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature *** fused feature set is optimized using a meta-heuristic algorithm,the Whale Optimization Algorithm(WOA).The selected features are used for the classification of six different diseases of citrus *** proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques.

关键词： Citrus plant disease classification deep learning feature fusion deep transfer learning

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Evaluation of microstructure and mechanical properties of squeeze overcast Al7075-Cu composite joints

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China Foundry 2023年第1期20卷 29-39页

作者： muhammad Waqas Hanif Ahmad Wasim muhammad Sajid Salman Hussain muhammad jawad Mirza Jahanzaib Department of Industrial Engineering University of Engineering and Technology TaxilaPunjabPakistan

Al7075-Cu composite joints were prepared by the squeeze overcast *** effects of melt temperature,die temperature,and squeeze pressure on hardness and ultimate tensile strength(UTS)of squeeze overcast Al7075-Cu composite joints were *** experimental results depict that squeeze pressure is the most significant process parameter affecting the hardness and *** optimal values of UTS(48 MPa)and hardness(76 HRB)are achieved at a melt temperature of 800℃,a die temperature of 250℃,and a squeeze pressure of 90 *** electron microscopy(SEM)shows that fractured surfaces show flatfaced morphology at the optimal experimental ***-dispersive spectroscopy(EDS)analysis depicts that the atomic weight percentage of Zn decreases with an increase in melt temperature and squeeze *** optimal mechanical properties of the Al7075-Cu overcast joint were achieved at the Al2Cu eutectic phase due to the large number of copper atoms that dispersed into the aluminum melt during the solidification process and the formation of strong intermetallic *** relational analysis integrated with the Taguchi method was used to develop an optimal set of control variables for multi-response parametric *** tests were performed to validate the effectiveness of the employed *** manufacturing of squeeze overcast Al7075-Cu composite joints at optimal process parameters delivers a great indication to acknowledge a new method for foundry practitioners to manufacture materials with superior mechanical properties.

关键词： squeeze overcast joints Al7075-Cu composite joints mechanical properties gray relational analysis Taguchi method

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Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’Response Against COVID Variants

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Computers, Materials & Continua 2023年第5期75卷 3517-3535页

作者： Hassam Tahir muhammad Shahbaz khan Fawad Ahmed Abdullah M.Albarrak Sultan Noman Qasem jawad Ahmad Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Cyber Security Pakistan Navy Engineering CollegeNUSTKarachi75350Pakistan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Computing Edinburgh Napier UniversityEdinburghEH105DTU.K

TheCOVID-19 outbreak began in December 2019 andwas declared a global health emergency by the World Health *** four most dominating variants are Beta,Gamma,Delta,and *** the administration of vaccine doses,an eminent decline in new cases has been *** COVID-19 vaccine induces neutralizing antibodies and T-cells in our ***,strong variants likeDelta and Omicron tend to escape these neutralizing antibodies elicited by COVID-19 ***,it is indispensable to study,analyze and most importantly,predict the response of SARS-CoV-2-derived t-cell epitopes against Covid variants in vaccinated and unvaccinated *** this regard,machine learning can be effectively utilized for predicting the response of COVID-derived t-cell *** this study,prediction of T-cells Epitopes’response was conducted for vaccinated and unvaccinated people for Beta,Gamma,Delta,and Omicron *** dataset was divided into two classes,i.e.,vaccinated and unvaccinated,and the predicted response of T-cell Epitopes was divided into three categories,i.e.,Strong,Impaired,and *** the aforementioned prediction purposes,a self-proposed Bayesian neural network has been designed by combining variational inference and flow normalization ***,the Hidden Markov Model has also been trained on the same dataset to compare the results of the self-proposed Bayesian neural network with this state-of-the-art statistical *** experimentation and results demonstrate the efficacy of the proposed network in terms of accurate prediction and reduced error.

关键词： Omicron COVID-19 hidden Markov model Bayesian neural network

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RUSAS: Roman Urdu Sentiment Analysis System

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Computers, Materials & Continua 2024年第4期79卷 1463-1480页

作者： Kazim jawad muhammad Ahmad Majdah Alvi muhammad Bux Alvi Faculty of Computer Science and Engineering Frankfurt University of Applied SciencesFrankfurt am Main60318Germany Technical Writer and Researcher Proteus Technologies LLCIslamabad04405Pakistan Faculty of Engineering The Islamia University of BahawalpurBahawalpur63100Pakistan

Sentiment analysis, the meta field of Natural Language Processing (NLP), attempts to analyze and identify thesentiments in the opinionated text data. People share their judgments, reactions, and feedback on the internetusing various languages. Urdu is one of them, and it is frequently used worldwide. Urdu-speaking people prefer tocommunicate on social media in Roman Urdu (RU), an English scripting style with the Urdu language *** have developed versatile lexical resources for features-rich comprehensive languages, but limitedlinguistic resources are available to facilitate the sentiment classification of Roman Urdu. This effort encompassesextracting subjective expressions in Roman Urdu and determining the implied opinionated text polarity. Theprimary sources of the dataset are Daraz (an e-commerce platform), Google Maps, and the manual effort. Thecontributions of this study include a Bilingual Roman Urdu Language Detector (BRULD) and a Roman UrduSpelling Checker (RUSC). These integrated modules accept the user input, detect the text language, correct thespellings, categorize the sentiments, and return the input sentence’s orientation with a sentiment intensity *** developed system gains strength with each input experience gradually. The results show that the languagedetector gives an accuracy of 97.1% on a close domain dataset, with an overall sentiment classification accuracy of94.3%.

关键词： Roman Urdu sentiment analysis Roman Urdu language detector Roman Urdu spelling checker flask

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