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| 1 | 籽瓜、黏籽和普通西瓜的果实代谢组比较显示文摘【目的】西瓜是一种广受欢迎的夏季水果,籽用西瓜(籽瓜)、黏籽西瓜和普通西瓜是3种重要的栽培类型,但对其果实中代谢物全面鉴定的研究很少,比较这3种西瓜果实的代谢组学差异,为明确驯化改良对不同类型西瓜代谢组的影响提供新见解。【方法】试验以5份籽用西瓜、5份黏籽西瓜和6份普通西瓜为材料,对成熟期果肉进行广泛靶向代谢组学检测,采用SIMCA-P、MetaboAnalyst 5.0、Origin等软件对代谢组数据进行分析。【结果】LC-MS分析共检测到323种代谢物,包括51种氨基酸及其衍生物、21种核苷酸及其衍生物、14种碳水化合物、32种有机酸、52种脂质、36种类黄酮、32种羟基肉桂酰衍生物等。PCA和聚类分析显示,籽用西瓜和黏籽西瓜的代谢组学轮廓差异较小,籽用西瓜的代谢组轮廓介于黏籽西瓜和普通西瓜之间。对分类贡献率较大的代谢物是蔗糖、柠檬酸、L-谷氨酸、L-苏氨酸、葫芦素类、香草酸糖苷异构体、脂质类等。聚类热图分析显示黏籽西瓜中特有的代谢物是葫芦素及其衍生物等,籽用西瓜中的绿原酸、LysoPE脂质类等化合物含量较高,普通西瓜中的糖类、精氨酸、阿魏酸及C18-2和C18-3不饱和脂肪酸等物质含量较高。比较分析共鉴定出156种差异代谢物,籽用西瓜与黏籽西瓜的主要差异代谢物有对香豆醛、阿魏酸、肉桂酸、蔗糖、葫芦素D O-葡萄糖苷、葫芦素E异构体、牡荆素、松柏醇等。籽用西瓜与普通西瓜的主要差异代谢物有脂质类、类黄酮类、有机酸类和糖类等。随着作物进化的程度增加,营养类代谢物质含量增加,抗性相关的代谢物质含量减少。【结论】籽用西瓜和黏籽西瓜的果实代谢组差异比籽用西瓜和普通西瓜的差异小,籽用西瓜的代谢轮廓介于黏籽西瓜和普通西瓜之间。除了表型和基因组差异外,代谢组差异也可以作为区分品种的重要依据。本研究首次在代谢组学水平比较了3种类型西瓜果实的差异,对深入理解西瓜种质资源,培育保健型西瓜新品种有重要的指导意义。 | 袁平丽 何楠 赵胜杰 路绪强 朱红菊 刁卫楠 龚成胜 MUHAMMAD Jawad Umer 刘文革 | 2021 | 中国农业科学2021，54，19： | 6 |
| 2 | Identification of key gene networks controlling organic acid and sugar metabolism during watermelon fruit development by integrating metabolic phenotypes and gene expression profiles显示文摘The organoleptic qualities of watermelon fruit are defined by the sugar and organic acid contents,which undergo considerable variations during development and maturation.The molecular mechanisms underlying these variations remain unclear.In this study,we used transcriptome profiles to investigate the coexpression patterns of gene networks associated with sugar and organic acid metabolism.We identified 3 gene networks/modules containing 2443 genes highly correlated with sugars and organic acids.Within these modules,based on intramodular significance and Reverse Transcription Quantitative polymerase chain reaction(RT-qPCR),we identified 7 genes involved in the metabolism of sugars and organic acids.Among these genes,Cla97C01G000640,Cla97C05G087120 and Cla97C01G018840(r^(2)=0.83 with glucose content)were identified as sugar transporters(SWEET,EDR6 and STP)and Cla97C03G064990(r^(2)=0.92 with sucrose content)was identified as a sucrose synthase from information available for other crops.Similarly,Cla97C07G128420,Cla97C03G068240 and Cla97C01G008870,having strong correlations with malic(r^(2)=0.75)and citric acid(r^(2)=0.85),were annotated as malate and citrate transporters(ALMT7,CS,and ICDH).The expression profiles of these 7 genes in diverse watermelon genotypes revealed consistent patterns of expression variation in various types of watermelon.These findings add significantly to our existing knowledge of sugar and organic acid metabolism in watermelon. | Muhammad Jawad Umer Luqman Bin Safdar Haileslassie Gebremeskel Shengjie Zhao Pingli Yuan Hongju Zhu M.O.Kaseb Muhammad Anees Xuqiang Lu Nan He Chengsheng Gong Wenge Liu | 2020 | Horticulture Research2020，7，1： | 4 |
| 3 | Nitrogen(N) metabolism related enzyme activities,cell uitrastructure and nutrient contents as affected by N level and barley genotype显示文摘Development of the new crop cultivars with high yield under low nitrogen(N) input is a fundamental approach to enhance agricultural sustainability,which is dependent on the exploitation of the elite germplasm.In the present study,four barley genotypes(two Tibetan wild and two cultivated),differing in N use efficiency(NUE),were characterized for their physiological and biochemical responses to different N levels.Higher N levels significantly increased the contents of other essential nutrients(P,K,Ca,Fe,Cu and Mn),and the increase was more obvious for the N-efficient genotypes(ZD9 and XZ149).The observation of ultrastructure showed that chloroplast structure was severely damaged under low nitrogen,and the two high N efficient genotypes were relatively less affected.The activities of the five N metabolism related enzymes,i.e.,nitrate reductase(NR),glutamine synthetase(GS),nitrite reductase(NiR),glutamate synthase(GOGAT) and glutamate dehydrogenase(GDH) all showed the substantial increase with the increased N level in the culture medium.However the increased extent differed among the four genotypes,with the two N efficient genotypes showing more increase in comparison with the other two genotypes with relative N inefficiency(HXRL and XZ56).The current findings showed that a huge difference exists in low N tolerance among barley genotypes,and improvement of some physiological traits(such as enzymes) could be helpful for increasing N utilization efficiency. | Jawad Munawar Shah Syed Asad Hussain Bukhari ZENG Jian-bin QUAN Xiao-yan Essa Ali Noor Muhammad ZHANG Guo-ping | 2017 | Journal of Integrative Agriculture2017，16，1： | 4 |
| 4 | 无线传感器网络中虫洞攻击实时被动式探测显示文摘在无线传感器网络所面临的安全问题中,虫洞攻击是最严重的威胁之一.由于无线传感器节点的资源非常有限,因此,适用于有线网络上的基于密码学的安全技术不能直接移植于无线传感网络.目前已知的传感网中,虫洞攻击的探测方案在应用上存在问题,这些方案或需要精确时间同步、或额外的定位算法或硬件、或有较大的通信开销,并且,现有方案均不能检测可自适应调整攻击策略的主动虫洞敌手.结合无线传感器网络的特点,提出了基于拓扑的被动式实时虫洞攻击探测方案,称为Pworm.通过利用虫洞攻击的主要特征——大量吸引网络流量和显著缩短平均网络路径,Pworm不需要任何额外的硬件,只需要收集网络中部分路由信息,就能实时地探测虫洞节点,即使是主动虫洞节点,也不能通过改变自身攻击策略而躲避探测.实验结果和分析表明:该方案具有轻量级、低漏报率、高可扩展性等优点,适用于大规模无线传感网络. | 鲁力 Muhammad Jawad HUSSAIN 朱金奇 | 2016 | 软件学报2016，27，12： | 3 |
| 5 | 黏籽西瓜、籽瓜和普通西瓜的植物学性状比较分析显示文摘西瓜属于葫芦科的重要水果作物,栽培类型丰富多样,其中黏籽西瓜、籽瓜和普通西瓜是被人类栽培和食用的主要类型,但是这3种类型西瓜的植物学性状差异并没有被系统调查过。针对18份黏籽西瓜、38份籽瓜、174份普通西瓜品种的14个植物学性状进行调查和统计分析,结果显示,供试西瓜品种的植物学性状变异范围大,不同性状在3种类型西瓜之间的差异显著,籽瓜和黏籽西瓜的表型更相似。系统聚类和PCA分析可以将3种类型的西瓜品种基本区分开来,籽瓜介于黏籽西瓜和普通西瓜之间。该研究结果有助于充分了解和利用西瓜种质资源,能够为培育理想株型和优质的西瓜新品种提供科学依据。 | 袁平丽 龚成胜 何楠 刁卫楠 Muhammad Jawad Umer 朱红菊 杨东东 Muhammad Anees 路绪强 Kaseb M O 赵胜杰 刘文革 | 2021 | 中国瓜菜2021，34，9： | 2 |
| 6 | Real-time-guided bone regeneration around standardized critical size calvarial defects using bone marrow-derived mesenchymal stem cells and collagen membrane with and without using tricalcium phosphate: an in vivo microcomputed tomographic and histologic e显示文摘The aim of the present real time in vivo micro-computed tomography(m CT)and histologic experiment was to assess the efficacy of guided bone regeneration(GBR)around standardized calvarial critical size defects(CSD)using bone marrow-derived mesenchymal stem cells(BMSCs),and collagen membrane(CM)with and without tricalcium phosphate(TCP)graft material.In the calvaria of nine female Sprague-Dawley rats,full-thickness CSD(diameter 4.6 mm)were created under general anesthesia.Treatment-wise,rats were divided into three groups.In group 1,CSD was covered with a resorbable CM;in group 2,BMSCs were filled in CSD and covered with CM;and in group 3,TCP soaked in BMSCs was placed in CSD and covered with CM.All defects were closed using resorbable sutures.Bone volume and bone mineral density of newly formed bone(NFB)and remaining TCP particles and rate of new bone formation was determined at baseline,2,4,6,and 10 weeks using in vivo m CT.At the 10th week,the rats were killed and calvarial segments were assessed histologically.The results showed that the hardness of NFB was similar to that of the native bone in groups 1 and 2 as compared to the NFB in group 3.Likewise,values for the modulus of elasticity were also significantly higher in group 3 compared to groups 1 and 2.This suggests that TCP when used in combination with BMSCs and without CM was unable to form bone of significant strength that could possibly provide mechanical'lock'between the natural bone and NFB.The use of BMSCs as adjuncts to conventional GBR initiated new bone formation as early as 2 weeks of treatment compared to when GBR is attempted without adjunct BMSC therapy. | Khalid Al-Hezaimi Sundar Ramalingam Mansour Al-Askar Aws S ArRejaie Nasser Nooh Fawad Jawad Abdullah Aldahmash Muhammad Atteya Cun-Yu Wang | 2016 | International Journal of Oral Science2016，8，1： | 2 |
| 7 | Classification of Citrus Plant Diseases Using Deep Transfer Learning显示文摘In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and fruits.This in turn has helped in improving the quality and production of vegetables and fruits.Citrus fruits arewell known for their taste and nutritional values.They are one of the natural and well known sources of vitamin C and planted worldwide.There are several diseases which severely affect the quality and yield of citrus fruits.In this paper,a new deep learning based technique is proposed for citrus disease classification.Two different pre-trained deep learning models have been used in this work.To increase the size of the citrus dataset used in this paper,image augmentation techniques are used.Moreover,to improve the visual quality of images,hybrid contrast stretching has been adopted.In addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature fusion.The 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 plants.The proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques. | Muhammad Zia Ur Rehman Fawad Ahmed Muhammad Attique Khan Usman Tariq Sajjad Shaukat Jamal Jawad Ahmad Iqtadar Hussain | 2022 | Computers, Materials & Continua2022，，1： | 1 |
| 8 | Evaluation of microstructure and mechanical properties of squeeze overcast Al7075-Cu composite joints显示文摘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. | Muhammad Waqas Hanif Ahmad Wasim Muhammad Sajid Salman Hussain Muhammad Jawad Mirza Jahanzaib | 2023 | China Foundry2023，20，1： | 1 |
| 9 | Integrated CWT-CNN for Epilepsy Detection Using Multiclass EEG Dataset显示文摘Electroencephalography is a common clinical procedure to record brain signals generated by human activity.EEGs 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 neuroscience.Various 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 beforehand.Deep learning models can learn features from data without having in depth knowledge of data and prior feature identification.One of the great implementations of deep learning is Convolutional Neural Network(CNN)which has outperformed traditional neural networks in pattern recognition and image classification.Continuous Wavelet Transform(CWT)is an efficient signal analysis technique that presents the magnitude of EEG signals as timerelated Frequency components.Existing deep learning architectures suffer from poor performance when classifying EEG signals in the Time-frequency domain.To improve classification accuracy,we propose an integrated CWT and CNN technique which classifies five types of EEG signals using.We compared the results of proposed integrated CWT and CNN method with existing deep learning models e.g.,GoogleNet,VGG16,AlexNet.Furthermore,the accuracy and loss of the proposed integrated CWT and CNN method have been cross validated using Kfold cross validation.The average accuracy and loss of Kfold cross-validation for proposed integrated CWT and CNN method are,76.12%and 56.02%respectively.This model produces results on a publicly available dataset:Epilepsy dataset by UCI(Machine Learning Repository). | Sidra Naseem Kashif Javed Muhammad Jawad Khan Saddaf Rubab Muhammad Attique Khan Yunyoung Nam | 2021 | Computers, Materials & Continua2021，，10： | 1 |
| 10 | Liquidity connectedness in cryptocurrency market显示文摘We examine the dynamics of liquidity connectedness in the cryptocurrency market.We use the connectedness models of Diebold and Yilmaz(Int J Forecast 28(1):57–66,2012)and Baruník and Křehlík(J Financ Econom 16(2):271–296,2018)on a sample of six major cryptocurrencies,namely,Bitcoin(BTC),Litecoin(LTC),Ethereum(ETH),Ripple(XRP),Monero(XMR),and Dash.Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies,whereas BTC and LTC play a significant role in connectedness magnitude.A distinct liquidity cluster is observed for BTC,LTC,and XRP,and ETH,XMR,and Dash also form another distinct liquidity cluster.The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium-and long-run time horizons.In the short run,BTC,LTC,and XRP are the leading contributor to liquidity shocks,whereas,in the long run,ETH assumes this role.Compared with the medium term,a tight liquidity clustering is found in the short and long terms.The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time,pointing to the possible effect of rising demand and higher acceptability for this unique asset.Furthermore,more pronounced liquidity connectedness patterns are observed over the short and long run,reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time–frequency connectedness. | Mudassar Hasan Muhammad Abubakr Naeem Muhammad Arif Syed Jawad Hussain Shahzad Xuan Vinh Vo | 2022 | Financial Innovation2022，8，1： | 1 |
| 11 | HD-Zip Transcription Factor is Responsible for No-Lobed Leaf in Watermelon(Citrullus lanatus L.)显示文摘Leaf is a vital organ of plants that plays an essential role in photosynthesis and respiration.As an important agronomic trait in leaf development,leaf shape is classified into lobed,entire(no-lobed),and serrated in most crops.In this study,two-lobed leaf watermelon inbred lines WT2 and WCZ,and a no-lobed leaf watermelon inbred line WT20 were used to create two F_(2)populations.Segregation analysis suggested that lobed leaves were dominant over the no-lobed leaves,and it was controlled by a signal gene.A locus on watermelon chromosome 4 controlling watermelon lobed/no-lobed leaves was identified through BSA-seq strategy combined with linkage analysis.The candidate gene was fine-mapped to a 61.5 kb region between 21,224,481 and 21,285,957 bp on watermelon chromosome 4 using two F_(2)populations.Four functional genes were annotated in the candidate region,while sequences blast showed that there was a single-base deletion(A/-)only in the exon of Cla018360,which resulted in premature termination of translation in the no-lobed leaf lines.Function prediction showed that Cla018360 encodes an HD-Zip protein that has been reported to regulate the development of leaf shape.The single-base deletion also occurred in the HD-Zip domain.We inferred that the Cla018360 gene is the candidate gene for regulating the development of lobed/no-lobed leaves in watermelon.Gene expression analysis showed that Cla018360 was highly expressed in young leaves.Phylogenetic analysis showed that Cla018360 had a close genetic relationship with AtHB51,which had been reported to regulate the formation of leaf shape in Arabidopsis.Furthermore,transcriptome analysis showed that a total of 333 differentially expressed genes were identified between WT2 and WT20,of which 115 and 218 genes were upregulated and downregulated in no-lobed leaved watermelon WT20.This study not only provides a good entry point for studying leaf development but also provides foundational insights into breeding for special plant architecture in watermelon. | Shixiang Duan Yaomiao Guo Yinping Wang Muhammad Jawad Umer Dongming Liu Sen Yang Huanhuan Niu Shouru Sun Luming Yang Junling Dou Huayu Zhu | 2023 | Phyton-International Journal of Experimental Botany2023，92，5： | 1 |
| 12 | Impact of prior antibiotic use in culture-negative endocarditis: review of 86 cases from southern Pakistan显示文摘 | Bilal Karim Siddiqui Muhammad Tariq Atif Jadoon Mahboob Alam Ghulam Murtaza Bilal Abid Muhammad Jawad Sethi Mehnaz Atiq Sohail Abrar Raymond A. Smego | 2008 | International Journal of Infectious Diseases2008，，5： | 1 |
| 13 | Enhanced Accuracy for Motor Imagery Detection Using Deep Learning for BCI显示文摘Brain-Computer Interface(BCI)is a system that provides a link between the brain of humans and the hardware directly.The recorded brain data is converted directly to the machine that can be used to control external devices.There are four major components of the BCI system:acquiring signals,preprocessing of acquired signals,features extraction,and classification.In traditional machine learning algorithms,the accuracy is insignificant and not up to the mark for the classification of multi-class motor imagery data.The major reason for this is,features are selected manually,and we are not able to get those features that give higher accuracy results.In this study,motor imagery(MI)signals have been classified using different deep learning algorithms.We 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 IIa.The outcome proved that deep learning algorithms provide greater accuracy results than traditional machine learning algorithms.Amongst the deep learning classifiers,LSTM outperforms the ANN and gives higher classification accuracy of 96.2%. | Ayesha Sarwar Kashif Javed Muhammad Jawad Khan Saddaf Rubab Oh-Young Song Usman Tariq | 2021 | Computers, Materials & Continua2021，，9： | 1 |
| 14 | Identification of hsa_circ_0092576 regulatory network in the pathogenesis of coronary heart disease显示文摘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. | Abdullahi Dandare Muhammad Rafiq Afrose Liaquat Afraz Ahmad Raj Muhammad Jawad Khan | 2023 | Genes & Diseases2023，10，1： | 1 |
| 15 | Dynamic Hand Gesture Recognition Using 3D-CNN and LSTM Networks显示文摘Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video stream.Many researchers have been working on visionbased gesture recognition due to its various applications.This paper proposes a deep learning architecture based on the combination of a 3D Convolutional Neural Network(3D-CNN)and a Long Short-Term Memory(LSTM)network.The proposed architecture extracts spatial-temporal information from video sequences input while avoiding extensive computation.The 3D-CNN is used for the extraction of spectral and spatial features which are then given to the LSTM network through which classification is carried out.The proposed model is a light-weight architecture with only 3.7 million training parameters.The model has been evaluated on 15 classes from the 20BN-jester dataset available publicly.The model was trained on 2000 video-clips per class which were separated into 80%training and 20%validation sets.An accuracy of 99%and 97%was achieved on training and testing data,respectively.We further show that the combination of 3D-CNN with LSTM gives superior results as compared to MobileNetv2+LSTM. | Muneeb Ur Rehman Fawad Ahmed Muhammad Attique Khan Usman Tariq Faisal Abdulaziz Alfouzan Nouf M.Alzahrani Jawad Ahmad | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 16 | Natural Convection and Irreversibility of Nanofluid Due to Inclined Magnetohydrodynamics(MHD)Filled in a Cavity with Y-Shape Heated Fin:FEM Computational显示文摘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. | Afraz Hussain Majeed Rashid Mahmood Sayed M.Eldin Imran Saddique S.Saleem Muhammad Jawad | 2024 | Computer Modeling in Engineering & Sciences2024，139，5： | 0 |
| 17 | Clinical relevance of circulating non-coding RNAs in metabolic diseases:Emphasis on obesity,diabetes,cardiovascular diseases and metabolic syndrome显示文摘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. | Abdullahi Dandare Muhammad Jawad Khan Aisha Naeem Afrose Liaquat | 2023 | Genes & Diseases2023，10，6： | 0 |
| 18 | IoTFLiP: IoT-based flipped learning platform for medical education显示文摘 | Maqbool Ali Hafiz Syed Muhammad Bilal Muhammad Asif Razzaq Jawad Khan Sungyoung Lee Muhammad Idris Mohammad Aazam Taebong Choi Soyeon Caren Han Byeong Ho Kang | 2017 | Digital Communications and Networks2017，3，3： | 0 |
| 19 | A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos显示文摘The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation(4G)and 5th generation(5G)etc.Researchers have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure way.Instead of the classical random walk,this paper proposes the quantum walk to achieve high image security.Classical random walk exhibits randomness due to the stochastic transitions between states,on the other hand,the quantum walk is more random and achieve randomness due to the superposition,and the interference of the wave functions.The proposed image encryption scheme is evaluated using extensive security metrics such as correlation coefficient,entropy,histogram,time complexity,number of pixels change rate and unified average intensity etc.All experimental results validate the proposed scheme,and it is concluded that the proposed scheme is highly secured,lightweight and computationally efficient.In the proposed scheme,the values of the correlation coefficient,entropy,mean square error(MSE),number of pixels change rate(NPCR),unified average change intensity(UACI)and contrast are 0.0069,7.9970,40.39,99.60%,33.47 and 10.4542 respectively. | Muhammad Islam Kamran Muazzam A.Khan Suliman A.Alsuhibany Yazeed Yasin Ghadi Arshad Jameel Arif Jawad Ahmad | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 20 | Ontology-Based News Linking for Semantic Temporal Queries显示文摘Daily newspapers publish a tremendous amount of information disseminated through the Internet.Freely available and easily accessible large online repositories are not indexed and are in an un-processable format.The major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and indexed.There is no method to reuse the online news images because of the unavailability of standardized benchmark corpora,especially for South Asian languages.The corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu language.Lack of indexing,primarily semantic indexing of the daily news items,makes news items impracticable for any querying.Moreover,the most straightforward search facility does not support these unindexed news resources.Our study addresses this gap by associating and marking the newspaper images with one of the widely spoken but under-resourced languages,i.e.,Urdu.The present work proposed a method to build a benchmark corpus of news in image form by introducing a web crawler.The corpus is then semantically linked and annotated with daily news items.Two techniques are proposed for image annotation,free annotation and fixed cross examination annotation.The second technique got higher accuracy.Build news ontology in protégéusing OntologyWeb Language(OWL)language and indexed the annotations under it.The application is also built and linked with protégéso that the readers and journalists have an interface to query the news items directly.Similarly,news items linked together will provide complete coverage and bring together different opinions at a single location for readers to do the analysis themselves. | Muhammad Islam Satti Jawad Ahmed Hafiz Syed Muhammad Muslim Akber Abid Gardezi Shafiq Ahmad Abdelaty Edrees Sayed Salman Naseer Muhammad Shafiq | 2023 | Computers, Materials & Continua2023，，2： | 0 |
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