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CASIA-Iris-Africa:A Large-scale African Iris Image Database

Machine Intelligence Research 2024年第2期21卷 383-399页

作者： jawad muhammad Yunlong Wang Junxing Hu Kunbo Zhang Zhenan Sun School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Iris biometrics is a phenotypic biometric trait that has proven to be agnostic to human natural physiological changes.Research on iris biometrics has progressed tremendously,partly due to publicly available iris databases.Various databases have been available to researchers that address pressing iris biometric challenges such as constraint,mobile,multispectral,synthetics,long-distance,contact lenses,liveness detection,etc.However,these databases mostly contain subjects of Caucasian and Asian docents with very few Africans.Despite many investigative studies on racial bias in face biometrics,very few studies on iris biometrics have been published,mainly due to the lack of racially diverse large-scale databases containing sufficient iris samples of Africans in the public domain.Furthermore,most of these databases contain a relatively small number of subjects and labelled images.This paper proposes a large-scale African database named Chinese Academy of Sciences Institute of Automation(CASIA)-Iris-Africa that can be used as a complementary database for the iris recognition community to mediate the effect of racial biases on Africans.The database contains 28717 images of 1023 African subjects(2046 iris classes)with age,gender,and ethnicity attributes that can be useful in demographically sensitive studies of Africans.Sets of specific application protocols are incorporated with the database to ensure the database’s variability and scalability.Performance results of some open-source state-of-the-art(SOTA)algorithms on the database are presented,which will serve as baseline performances.The relatively poor performances of the baseline algorithms on the proposed database despite better performance on other databases prove that racial biases exist in these iris recognition algorithms.

关键词： African iris recognition racial bias iris image database biometrics iris recognition

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Natural Convection and Irreversibility of Nanofluid Due to Inclined Magnetohydrodynamics(MHD)Filled in a Cavity with Y-Shape Heated Fin:FEM Computational

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1505-1519页

作者： Afraz Hussain Majeed Rashid Mahmood Sayed M.Eldin Imran Saddique S.Saleem muhammad jawad School of Energy and Power Engineering Jiangsu UniversityZhenjiang212013China Department of Mathematics Air UniversityIslamabad44000Pakistan Center of Research Faculty of EngineeringFuture University in EgyptNew Cairo11835Egypt Department of Mathematics University of Management and TechnologyLahore54770Pakistan Department of Mathematics University of SargodhaSargodha40100Pakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha61413Saudi Arabia Faculty of Sciences The Superior UniversityLahore54000Pakistan

This study explains the entropy process of natural convective heating in the nanofluid-saturated cavity in a heated fin andmagnetic field.The temperature is constant on the Y-shaped fin,insulating the topwall while the remaining walls remain cold.All walls are subject to impermeability and non-slip conditions.The mathematical modeling of the problem is demonstrated by the continuity,momentum,and energy equations incorporating the inclined magnetic field.For elucidating the flow characteristics Finite ElementMethod(FEM)is implemented using stable FE pair.A hybrid fine mesh is used for discretizing the domain.Velocity and thermal plots concerning parameters are drawn.In addition,a detailed discussion regarding generation energy by monitoring changes in magnetic,viscous,total,and thermal irreversibility is provided.In addition,line graphs are created for the u and v components of the velocity profile to predict the flow behavior.Current simulations assume the dimensionless representative of magnetic field Hartmann number Ha between 0 and 100 and a magnetic field inclination between 0 and 90 degrees.A constant 4% volume proportion of nanoparticles is employed throughout all scenarios.

关键词： Finite element method nanomaterials entropy MHD square cavity Y-fin

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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 rearrangement.The aberrant expression of ncRNAs is associated with several pathological conditions.In 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 highlighted.miRNAs regulate the expression of genes at transcriptional and translational levels.circRNAs modulate the regulation of gene expression via miRNA sponging activity,interacting with RNA binding protein and polymerase II transcription regulation.lncRNAs 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 modifiers.We examined the role of ncRNAs in the disease pathogenesis and their potential role as molecular markers for diagnosis,prognosis and therapeutic targets.We showed the involvement of ncRNAs in the onset of obesity and its progression to MetS and CVD.miRNA-192,miRNA-122,and miRNA-221 were dysregulated in all these metabolic diseases.Other ncRNAs,implicated in at least three diseases include miRNA-15a,miRNA-26,miRNA-27a,miRNA-320,and miRNA-375.Dysregulation of ncRNAs increased the risk of development of DM and MetS and its progression to CVD in obese individuals.Hence,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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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 globally.Coronary 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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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 process.The effects of melt temperature,die temperature,and squeeze pressure on hardness and ultimate tensile strength(UTS)of squeeze overcast Al7075-Cu composite joints were studied.The experimental results depict that squeeze pressure is the most significant process parameter affecting the hardness and UTS.The 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 MPa.Scanning electron microscopy(SEM)shows that fractured surfaces show flatfaced morphology at the optimal experimental condition.Energy-dispersive spectroscopy(EDS)analysis depicts that the atomic weight percentage of Zn decreases with an increase in melt temperature and squeeze pressure.The 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 bonds.Gray relational analysis integrated with the Taguchi method was used to develop an optimal set of control variables for multi-response parametric optimization.Confirmatory tests were performed to validate the effectiveness of the employed technique.The 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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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 diseases.The 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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Transmission dynamics of Hand-Foot-Mouth Disease with partial immunity through non-integer derivative

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生物数学学报:英文版 2023年第6期16卷 149-173页

作者： Rashid Jan Salah Boulaaras Sultan Alyobit muhammad jawad Department of Mathematics University of Swabi Swabi 23561Khyber PakhtunkhwaPakistan Department of Mathematics College of Sciences and Arts Qassim UniversityAr RassSaudi Arabia Department of Mathematics College of Science 8 Arts King Abdulaziz UniversityRabighSaudi Arabia

In this paper,we formulate the transmission phenomena of Hand-Foot-Mouth Disease(HFMD)through non-integer derivative.We interrogate the biological meaningful results of the recommended system of HFMD.The basic reproduction number is determined through next generation method and the impact of different parameters on the reproduction number is examined with the help of partial rank correlation coeficient(PRCC)technique.In addition,we concentrated on qualitative analysis and dynamical behavior of HFMD dynamics.Banach's and Schaefer's fixed-point theorems are used to analyze the uniqueness and existence of the solution of the proposed HFMD model.The HFMD system's Ulam-Hyers stability has been confirmed to be sufficient.To highlight the impact of the parameters on the dynamics of HFMD,we performed several simulations through numerical scheme to conceptualize the transmission route of the infection.To be more specific,numerical simulations are used to visualize the effect of input parameters on the systems dynamics.We have shown the key input parameters of the system for the control of infection in the society.

关键词： Hand-Foot-Mouth Disease fractional derivatives mathematical model threshold parameter numerical scheme dynamical behavior

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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 dialect.Researchers 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 score.The 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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Short-Term Wind Energy Forecasting Using Deep Learning-Based Predictive Analytics

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Computers, Materials & Continua 2022年第7期72卷 1017-1033页

作者： Noman Shabbir Lauri Kütt muhammad jawad Oleksandr Husev Ateeq Ur Rehman Akber Abid Gardezi muhammad Shafiq Jin-Ghoo Choi Department of Electrical Power Engineering&Mechatronics Tallinn University of TechnologyTallinn19086Estonia Department of Electrical and Computer Engineering COMSATS University Islamabad(Lahore Campus)54000Pakistan Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Wind energy is featured by instability due to a number of factors,such as weather,season,time of the day,climatic area and so on.Furthermore,instability in the generation of wind energy brings new challenges to electric power grids,such as reliability,flexibility,and power quality.This transition requires a plethora of advanced techniques for accurate forecasting of wind energy.In this context,wind energy forecasting is closely tied to machine learning(ML)and deep learning(DL)as emerging technologies to create an intelligent energy management paradigm.This article attempts to address the short-term wind energy forecasting problem in Estonia using a historical wind energy generation data set.Moreover,we taxonomically delve into the state-of-the-art ML and DL algorithms for wind energy forecasting and implement different trending ML and DL algorithms for the day-ahead forecast.For the selection of model parameters,a detailed exploratory data analysis is conducted.All models are trained on a real-time Estonian wind energy generation dataset for the first time with a frequency of 1 h.The main objective of the study is to foster an efficient forecasting technique for Estonia.The comparative analysis of the results indicates that Support Vector Machine(SVM),Non-linear Autoregressive Neural Networks(NAR),and Recurrent Neural Network-Long-Term Short-Term Memory(RNNLSTM)are respectively 10%,25%,and 32%more efficient compared to TSO’s forecasting algorithm.Therefore,RNN-LSTM is the best-suited and computationally effective DL method for wind energy forecasting in Estonia and will serve as a futuristic solution.

关键词： Wind energy production energy forecast machine learning

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Neural stem cell-based in vitro bioassay for the assessment of neurotoxic potential of water samples

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Journal of Environmental Sciences 2021年第3期33卷 72-86页

作者： muhammad Irfan Masood Natalie Tamara Hauke muhammad jawad Nasim muhammad Sarfraz Mahrukh Naseem Karl Herbert Schäfer Division of Bioorganic Chemistry School of PharmacySaarland UniversityD-66123 SaarbrückenGermany Applied Life Sciences University of Applied Sciences Kaiserslautern66482 ZweibrückenGermany ENS Group University of Applied Sciences Kaiserslautern66482 ZweibrückenGermany Abwasserverband Bergstrasse Altau 1069469 WeinheimGermany Institute of Pharmaceutical Sciences University of Veterinary and Animal Sciences54000 LahorePakistan Department of Zoology University of BalochistanQuetta 87550Pakistan

Intensive agriculture activities,industrialization and growing numbers of wastewater treatment plants along river banks collectively contribute to the elevated levels of neurotoxic pollutants in natural water reservoirs across Europe.We established an in vitro bioassay based upon neural stem cells isolated from the subventricular zone of the postnatal mouse to evaluate the neurotoxic potential of raw wastewater,treated sewage effluent,groundwater and drinking water.The toxic potential of water samples was evaluated employing viability,proliferation,differentiation and migration assays.We found that raw wastewater could reduce the viability and proliferation of neural stem cells,and decreased the neuronal and astrocyte differentiation,neuronal neurite growth,astrocyte growth and cell migration.Treated sewage water also showed inhibitory effects on cell proliferation and migration.Our results indicated that relatively high concentrations of nitrogenous substances,pesticides,mercuric compounds,bisphenol-A,and phthalates,along with some other pollutants in raw wastewater and treated sewage water,might be the reason for the neuroinhibitory effects of these water samples.Our model successfully predicted the neurotoxicity of water samples collected from different sources and also revealed that the incomplete removal of contaminants from wastewater can be problematic for the developing nervous system.The presented data also provides strong evidence that more effective treatments should be used to minimize the contamination of water before release into major water bodies which may be considered as water reservoirs for human usage in the future.

关键词： Neural stem cells Subventricular zone Neurotoxicity Bioassay Treated sewage effluents Pesticides

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