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High-density genetic mapping identified a major locus for environmental sex expression in pumpkin(Cucurbita moschata Duch.)

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Horticultural Plant Journal 2022年第5期8卷 593-601页

作者： Hafiz Muhammad Khalid Abbas Hexun Huang Tingquan Wu Rui Wang Hu Du Sen Lu Shudan Xue Chunpeng Yao Qingmin Jin Yujuan Zhong Guangdong Key Laboratory for New Technology Research of Vegetables Vegetable Research InstituteGuangdong Academy of Agricultural SciencesGuangzhou 510640China

Long-day length and high temperature inhibit sex expression in pumpkin(Cucurbita moschata Duch.),and therefore directly impact the production potential.In this study,female flowering patterns in photoperiod-insensitive(PPIS)and photoperiod-sensitive(PPS)germplasms differed significantly in a moderately long day and high temperature environment.However,both germplasms exhibited a similar response in short day with either low temperature or high temperature environment.Photoperiod sensitivity led to this difference in sex expression between the germplasms.For the traits of 1st female flowering node(FFFN)and number of female flowers(NFF),high-density linkage map construction and quantitative trait locus(QTL)mapping were performed using SLAF-seq technology and 162 F_(2) individuals generated from PPIS and PPS.In total,4655 SLAFs were selected and mapped on 20 linkage groups(LGs).The total map length was 2502.01 cM with an average interval distance of 0.75 cM.Major QTLs for both FFFN and NFF were detected on LG6 with intervals of 7.89 and 17.67 cM and PVE values of 30.5%and 22.9%,respectively.Further analyses of the major locus for FFFN revealed 73 protein-coding genes.Among them,4 were related to sex expression,photoperiod flowering,and hormone response.An InDel(insertion and deletion)marker partially correlated with FFFN of the F_(2) population was also developed.Our study identified the QTL for the sex expression response to environmental factors using the high-density linkage map.The identified candidate genes and markers will provide useful information about the molecular interaction between the environment and sex expression and for marker-assisted selection of pumpkin environment-insensitive resources.

关键词： Pumpkin Photoperiod sensitivity Sex expression High-density genetic map SLAF-seq QTL mapping

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Modelling and Verification of Context-Aware Intelligent Assistive Formalism

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Computers, Materials & Continua 2022年第5期71卷 3355-3373页

作者： Shahid Yousaf hafiz Mahfooz Ul Haque abbas khalid muhammad Adnan Hashmi Eraj Khan Department of Computer Science&IT The University of LahoreLahore54000Pakistan Department of Software Engineering The University of LahoreLahore54000Pakistan Higher Colleges of Technology Abu Dhabi25026UAE

Recent years have witnessed the expeditious evolution of intelligentsmart devices and autonomous software technologies with the expandeddomains of computing from workplaces to smart computing in everydayroutine life activities. This trend has been rapidly advancing towards the newgeneration of systems where smart devices play vital roles in acting intelligently on behalf of the users. Context-awareness has emerged from the pervasive computing paradigm. Context-aware systems have the ability to acquirecontextual information from the surrounding environment autonomously,perform reasoning on it, and then adapt their behaviors accordingly. With theproliferation of context-aware systems and smart sensors, real-time monitoring of environmental situations (context) has become quite trivial. However,it is often challenging because the imperfect nature of context can cause theinconsistent behavior of the system. In this paper, we propose a contextaware intelligent decision support formalism to assist cognitively impairedpeople in managing their routine life activities. For this, we present a semanticknowledge-based framework to contextualize the information from the environment using the protégé ontology editor and Semantic Web Rule Language(SWRL) rules. The set of contextualized information and the set of rulesacquired from the ontology can be used to model Context-aware Multi-AgentSystems (CMAS) in order to autonomously plan all activities of the users andnotify users to act accordingly. To illustrate the use of the proposed formalism,we model a case study of Mild Cognitive Impaired (MCI) patients usingColored Petri Nets (CPN) to show the reasoning process on how the contextaware agents collaboratively plan activities on the user’s behalf and validatethe correctness properties of the system.

关键词： Context-awareness multi-agents colored petri net ontology

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Disease resistance conferred by components of essential chrysanthemum oil and the epigenetic regulation of OsTPS1

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Science China(Life Sciences) 2023年第5期66卷 1108-1118页

作者： Chuansong Zhan Long Lei Hao Guo Shen Zhou Congping Xu Zixin Liu Zichen Wu Yuan Deng Yuanyuan Miao Yu Han Meng Zhang Hua Li Sishu Huang Chenkun Yang Feng Zhang Yufei Li Ling Liu Xianqing Liu Hafiz Muhammad Khalid Abbas Alisdair R.Fernie Meng Yuan Jie Luo College of Tropical Crops Hainan UniversityHaikou 570228China Sanya Nanfan Research Institute of Hainan University Hainan Yazhou Bay Seed LaboratorySanya 572025China National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research(Wuhan) Huazhong Agricultural UniversityWuhan 430070China Max Planck Institute of Molecular Plant Physiology Am Mühlenberg 114476 Potsdam-GolmGermany

The sesquiterpene alpha-bisabolol is the predominant active ingredient in essential oils that are highly valued in the cosmetics industry due to its wound healing,anti-inflammatory,and skin-soothing properties.Alpha-bisabolol was thought to be restricted to Compositae plants.Here we reveal that alpha-bisabolol is also synthesized in rice,a non-Compositae plant,where it acts as a novel sesquiterpene phytoalexin.Overexpressing the gene responsible for the biosynthesis of alpha-bisabolol,Os TPS1,conferred bacterial blight resistance in rice.Phylogenomic analyses revealed that alpha-bisabolol-synthesizing enzymes in rice and Compositae evolved independently.Further experiments demonstrated that the natural variation in the disease resistance level was associated with differential transcription of Os TPS1 due to polymorphisms in its promoter.We demonstrated that Os TPS1 was regulated at the epigenetic level by JMJ705 through the methyl jasmonate pathway.These data reveal the cross-family accumulation and regulatory mechanisms of alpha-bisabolol production.

关键词： alpha-bisabolol epigenetic regulation natural variation

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Intelligent Forecasting Model of COVID-19 Novel Coronavirus Outbreak Empowered with Deep Extreme Learning Machine

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Computers, Materials & Continua 2020年第9期64卷 1329-1342页

作者： muhammad Adnan Khan Sagheer abbas khalid Masood Khan Mohammed AAl Ghamdi Abdur Rehman Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science Umm Al-Qura UniversityMakkah23500Saudi Arabia

An epidemic is a quick and widespread disease that threatens many lives and damages the economy.The epidemic lifetime should be accurate so that timely and remedial steps are determined.These include the closing of borders schools,suspension of community and commuting services.The forecast of an outbreak effectively is a very necessary but difficult task.A predictive model that provides the best possible forecast is a great challenge for machine learning with only a few samples of training available.This work proposes and examines a prediction model based on a deep extreme learning machine(DELM).This methodology is used to carry out an experiment based on the recent Wuhan coronavirus outbreak.An optimized prediction model that has been developed,namely DELM,is demonstrated to be able to make a prediction that is fairly best.The results show that the new methodology is useful in developing an appropriate forecast when the samples are far from abundant during the critical period of the disease.During the investigation,it is shown that the proposed approach has the highest accuracy rate of 97.59%with 70%of training,30%of test and validation.Simulation results validate the prediction effectiveness of the proposed scheme.

关键词： Coronavirus nCoV DELM Mis rate SERS-CoV WHO COVID-19

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Effect of Measurement Error on the Multivariate CUSUM Control Chart for Compositional Data

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1207-1257页

作者： muhammad Imran Jinsheng Sun Fatima Sehar Zaidi Zameer abbas hafiz Zafar Nazir School of Automation Nanjing University of Science and TechnologyNanjing210094China School of Economics and Statistics Guangzhou UniversityGuangzhou510006China Department of Mathematics and Statistics East China Normal UniversityShanghai200062China Department of Statistics Government Ambala Muslim Graduate CollegeSargodha40100Pakistan Department of Statistics University of SargodhaSargodha40100Pakistan

Control charts(CCs)are one of the main tools in Statistical Process Control that have been widely adopted in manufacturing sectors as an effective strategy for malfunction detection throughout the previous decades.Measurement errors(M.E’s)are involved in the quality characteristic of interest,which can effect the CC’s performance.The authors explored the impact of a linearmodel with additive covariate M.E on the multivariate cumulative sum(CUSUM)CC for a specific kind of data known as compositional data(CoDa).The average run length(ARL)is used to assess the performance of the proposed chart.The results indicate that M.E’s significantly affects themultivariate CUSUM-CoDaCCs.The authors haveused theMarkov chainmethod to study the impact of different involved parameters using six different cases for the variance-covariance matrix(VCM)(i.e.,uncorrelated with equal variances,uncorrelated with unequal variances,positively correlated with equal variances,positively correlated with unequal variances,negatively correlatedwith equal variances and negatively correlated with unequal variances).The authors concluded that the error VCM has a negative impact on the performance of themultivariate CUSUM-CoDa CC,as the ARL increases with an increase in the value of the error VCM.The subgroup size m and powering operator b positively impact the proposed CC,as the ARL decreases with an increase in m or b.The number of variables p also has a negative impact on the performance of the proposed CC,as the values of ARL increase with an increase in p.For the implementation of the proposal,two illustrated examples have been reported formultivariate CUSUM-CoDaCCs inthe presence ofM.E’s.Onedealswith themanufacturingprocessof uncoated aspirin tablets,and the other is based on monitoring the machines involved in the muesli manufacturing process.

关键词： MCUSUM chart CoDa measurement error manufacturing process performance

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Convergence Track Based Adaptive Differential Evolution Algorithm(CTbADE)

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Computers, Materials & Continua 2022年第7期72卷 1229-1250页

作者： Qamar abbas khalid Mahmood Malik Abdul Khader Jilani Saudagar muhammad Badruddin Khan Mozaherul Hoque Abul Hasanat Abdullah AlTameem Mohammed AlKhathami Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Computer Science and Engineering Oakland UniversityRochesterMIUSA Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia

One of the challenging problems with evolutionary computing algorithms is to maintain the balance between exploration and exploitation capability in order to search global optima.A novel convergence track based adaptive differential evolution(CTbADE)algorithm is presented in this research paper.The crossover rate and mutation probability parameters in a differential evolution algorithm have a significant role in searching global optima.A more diverse population improves the global searching capability and helps to escape from the local optima problem.Tracking the convergence path over time helps enhance the searching speed of a differential evolution algorithm for varying problems.An adaptive powerful parameter-controlled sequences utilized learning period-based memory and following convergence track over time are introduced in this paper.The proposed algorithm will be helpful in maintaining the equilibrium between an algorithm’s exploration and exploitation capability.A comprehensive test suite of standard benchmark problems with different natures,i.e.,unimodal/multimodal and separable/non-separable,was used to test the convergence power of the proposed CTbADE algorithm.Experimental results show the significant performance of the CTbADE algorithm in terms of average fitness,solution quality,and convergence speed when compared with standard differential evolution algorithms and a few other commonly used state-of-the-art algorithms,such as jDE,CoDE,and EPSDE algorithms.This algorithm will prove to be a significant addition to the literature in order to solve real time problems and to optimize computationalmodels with a high number of parameters to adjust during the problem-solving process.

关键词： Differential evolution function optimization convergence track parameter sequence adaptive control parameters

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Defocus blur detection using novel local directional mean patterns(LDMP)and segmentation via KNN matting

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Frontiers of Computer Science 2022年第2期16卷 110-122页

作者： Awais KHAN Aun IRTAZA Ali JAVED Tahira NAZIR hafiz MALIK khalid Mahmood MALIK muhammad Ammar KHAN Department of Computer Science University of Engineering and TechnologyTaxila 47050Pakistan Department of Electrical and Computer Engineering University of MichiganDearbornMI 48128USA Department of Software Engineering University of Engineering and TechnologyTaxila 47050Pakistan Department of Computer Science and Engineering Oakland UniversityMI 48309USA

Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp regions that wrap significant information and require effective methods for information extraction.Existing defocus blur detection and segmentation methods have several limitations i.e.,discriminating sharp smooth and blurred smooth regions,low recognition rate in noisy images,and high computational cost without having any prior knowledge of images i.e.,blur degree and camera configuration.Hence,there exists a dire need to develop an effective method for defocus blur detection,and segmentation robust to the above-mentioned limitations.This paper presents a novel features descriptor local directional mean patterns(LDMP)for defocus blur detection and employ KNN matting over the detected LDMP-Trimap for the robust segmentation of sharp and blur regions.We argue/hypothesize that most of the image fields located in blurry regions have significantly less specific local patterns than those in the sharp regions,therefore,proposed LDMP features descriptor should reliably detect the defocus blurred regions.The fusion of LDMP features with KNN matting provides superior performance in terms of obtaining high-quality segmented regions in the image.Additionally,the proposed LDMP features descriptor is robust to noise and successfully detects defocus blur in high-dense noisy images.Experimental results on Shi and Zhao datasets demonstrate the effectiveness of the proposed method in terms of defocus blur detection.Evaluation and comparative analysis signify that our method achieves superior segmentation performance and low computational cost of 15 seconds.

关键词： defocus blur detection local directional mean patterns image matting sharpness metrics blur segmentation

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Application of GIS for the identification and demarcation of selective heavy metal concentrations in the urban groundwater

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Journal of Geographical Sciences 2015年第2期25卷 225-235页

作者： Sobia ASHRAF Farhat abbas muhammad IBRAHIM Umer RASHID Shoaib khalid Hammad Raza AHMAD khalid Rehman HAKEEM Tahir MAJEED Department of Environmental Sciences and Engineering Government College University Faisalabad (38000) Pakistan Institute of Advanced Technology Universiti Putra Malaysia UPM Serdang 43400 Selangor Malaysia Department of Geography Government College University Faisalabad 38000 Pakistan institute of Soil & Environmental Sciences University of Agriculture Faisalabad 38040 Pakistan Faculty of Forestry University of Putra Malaysia Serdang 43400 Selangor Malaysia Institute of Soil Chemistry and Environmental Sciences Ayub Agricultural Research Institute (AARI) Jhang Road Faisalabad

Groundwater is the most appropriate and widely used source of drinking water, which is increasingly threatened by pollution from industrial and agricultural activities. To check the severity of the problem, 156 groundwater samples were collected from various depths （60-110 ft） of 52 different localities in Faisalabad city, the third largest metropolis in Pakistan, and analyzed for the metals （Zn, Cu, Cd, Ni, Pb, Mn and Fe） concentration in 2009. Quantification was done by using Flame Atomic Absorption Spectrophotometer technique and the results were compared with WHO standards for drinking water quality. Results showed that the levels of Cu, Mn and Fe were below the WHO standards while the concentrations of Zn, Cd, Ni and Pb were above the recommended levels of safe drinking water. Correlation analysis among the occurrence of these heavy metals revealed a highly significant and positive correlation of Mn with Zn and Fe. A significant and positive correlation of Cd was also found with Cu and groundwater depth showing that there is strong association between Cu-Cd pair and that the Cd concentration varies with depth of groundwater in the study area. Regional patterns of heavy metals occurrence were mapped using Geographical Information System （GIS） for the identification and demarcation of risk areas. The concentration maps may be used by policymakers of the city to mitigate groundwater pollution.

关键词： heavy metals groundwater contamination Faisalabad pollution mitigation

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烧结铜丝和沟槽热管热性能特性的实验研究

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Journal of Central South University 2021年第11期28卷 3507-3520页

作者： Saif Ullah khalid hafiz muhammad ALI muhammad Ali NASIR Riffat Asim PASHA ZAFAR SAID L.Syam SUNDAR Ahmed Kadhim HUSSEIN Mechanical Engineering Department University of Engineering and TechnologyTaxila 47050Pakistan Mechanical Engineering Department King Fahd University of Petroleum&Minerals(KFUPM)Dhahran 31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Sustainable and Renewable Energy Engineering Department College of EngineeringUniversity of SharjahSharjah 27272United Arab Emirates Centre for Mechanical Technology and Automation(TEMA-UA) Department of Mechanical EngineeringUniversity of AveiroAveiro 3810-131Portugal Mechanical Engineering Department College of EngineeringUniversity of BabylonBabylon CityHillaIraq

热管是最常用的热管理解决方案。为达到最佳效果,在特定的情况下选择合适的热管类型是非常必要的。本研究的目的是比较烧结铜丝热管和沟槽热管两种常用热管的热性能特点。采用重力辅助定位实验对充蒸馏水热管进行了测试,得到毛细管压力... 详细信息

热管是最常用的热管理解决方案。为达到最佳效果,在特定的情况下选择合适的热管类型是非常必要的。本研究的目的是比较烧结铜丝热管和沟槽热管两种常用热管的热性能特点。采用重力辅助定位实验对充蒸馏水热管进行了测试,得到毛细管压力、操作温度、热阻和传热系数等参数结果。烧结热管的毛细管压力比所有尺寸沟槽热管的都高。在相同的热负荷下,与烧结热管相比,沟槽热管的工作温度更低。在8 W热负荷下,与烧结热管相比,沟槽热管冷凝器表面温度降低8.24%,蒸发器表面温度降低4.41%,饱和温度降低7.79%。烧结热管的热阻比沟槽热管低得多,在8 W热负荷下,最大相对差值为63.8%。在8 W热负荷下,烧结热管的传热系数是开槽热管的2倍。烧结热管的热阻和传热系数随热负荷的变化几乎呈线性变化,而沟槽热管的热阻和传热系数却出现意外的拐点。与烧结热管相比,沟槽热管更早达到平衡。当热负荷从4增加至20 W时,沟槽热管达到平衡的时间从7 min缩短至4 min,烧结热管的平衡时间从10 min缩短至7 min。

关键词：热管热阻传热系数热性能毛细管压力

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Intelligent Software-Defined Network for Cognitive Routing Optimization Using Deep Extreme Learning Machine Approach

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Computers, Materials & Continua 2021年第4期67卷 1269-1285页

作者： Fahd Alhaidari Sultan H.Almotiri Mohammed A.Al Ghamdi muhammad Adnan Khan Abdur Rehman Sagheer abbas khalid Masood Khan Atta-ur-Rahman Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Science Umm Al-Qura UniversityMakkah City715Saudi Arabia Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science NCBA&ELahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

In recent years,the infrastructure,instruments,and resources of network systems are becoming more complex and heterogeneous,with the rapid development of current internet and mobile communication technologies.In order to efficaciously prepare,control,hold and optimize networking systems,greater intelligence needs to be deployed.However,due to the inherently dispensed characteristic of conventional networks,Machine Learning(ML)techniques are hard to implement and deployed to govern and operate networks.Software-Defined Networking(SDN)brings us new possibilities to offer intelligence in the networks.SDN’s characteristics(e.g.,logically centralized control,global network view,software-based site visitor analysis,and dynamic updating of forwarding rules)make it simpler to apply machine learning strategies.Various perspectives of fiber-optic communications including fiber nonlinearity coverage,optical performance checking,cognitive shortcoming detection/anticipation,and arranging and improvement of softwaredefined networks are examined in Machine Learning(ML)applications.This research paper has presented an imaginative framework concept called Intelligent Software Defined Network(ISDN)for Cognitive Routing Optimization(CRO)using Deep Extreme Learning Machine(DELM)approach(ISDN-CRO-DELM)in light of the new challenges in the development and operation of communication systems,and capturing motivation from how living creatures deal with difficulty and usability.The proposed methodology develops around the planned applications of progressive DELM methods and,specifically,probabilistic generative models for framework wide learning,demonstrating,improvement,and information description.Furthermore,ISDN-CRO-DELM,suggest to integrate this learning framework with the ISDN for CRO and reconfiguration approaches at the system level.MATLAB 2019a is used for DELM simulation and superior results show the effectiveness of the proposed framework.

关键词： SDN DELM machine learning cognition

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