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Fusarium pseudograminearum and *** affect the root system architecture of bread wheat

作物学报：英文版 2023年第1期11卷 316-321页

作者： Ahmed saad Jack Christopher Anke Martin Stephen McDonald Cassandra Percy Centre for Crop Health University of Southern QueenslandToowoombaQLD 4350Australia University of Queensland Queensland Alliance for Agriculture and Food Innovation(QAAFI)Leslie Research FacilityToowoombaQLD 4350Australia

Yield losses of bread wheat due to crown rot can be more severe when drought conditions occur during the grain-filling *** architecture characteristics are important for soil exploration and belowground resource acquisition and are essential for adaptation to water-limited *** such as root angle,length and density have been strongly associated with acquisition efficiency and contribute to yield stability of the *** impact of crown rot pathogens on wheat root architecture is poorly *** examined differences in root angle,length and number,as well as dry root weight of the crown rot-susceptible bread wheat cultivar,Livingston inoculated with one of two crown rot pathogens Fusarium culmorum or Fusarium pseudograminearum in a transparent-sided root observation *** adverse impacts on plant health and growth were revealed by visual discolouration of the leaf sheaths;fresh and dry shoot weight;leaf area of the oldest and the youngest fully expanded leaf and leaf *** of most recorded root system measurements were reduced when inoculated with either *** or *** contrast,root angle was increased in the presence of *** but was not significantly changed by *** development of whiteheads and grain losses in bread wheat caused by crown rot have previously been associated with blockages of the vascular *** method employed here was able to identify differences in the pathogen impacts on roots,which were not detected using previous *** research indicates that in the presence of *** and *** infection,not only reductions in the size and biomass of the shoot system but also changes in the length,biomass and architecture of the root system could play an important role in yield loss.

关键词： Crown rot Root characteristics Livingston Wheat

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Improvement in potassium ion batteries electrodes: Recent developments and efficient approaches

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Journal of Energy Chemistry 2021年第11期30卷 307-337,I0007页

作者： Syed Musab Ahmed Guoquan Suo Wei Alex Wang Kai Xi saad bin Iqbal School of Materials Science and Engineering Shaanxi University of Science and TechnologyXi’an 710021ShaanxiChina Beijing Key Laboratory of Bio-inspired Energy Materials and Devices School of Space and EnvironmentBeihang UniversityBeijing 100191China Cambridge Graphene Centre Department of EngineeringUniversity of CambridgeCambridge CB30FAUK Department of Chemical and Energy Engineering Faculty of Process and System EngineeringOtto-von-Guericke UniversitätMagdeburg 39106Germany

Demand for efficient and continuous application for high-grid energy storage systems involves the study towards novel battery technologies. Hence, considering the vast naturally available resources of potassium all over the world and its encouraging intercalation chemistries, it has recently enticed attention in electrochemical energy storage industry in the form of potassium ion batteries (PIBs). The major factor in this K+ based battery, is to develop efficient approaches to manufacture electrode substance to intercalate its big size potassium ions with considerable voltage, kinetics, charge/discharge capacity, capacity retention, cost, etc. This study contributes in the recent developments of anode and cathode materials for PIBs, including several electrode materials in regards to synthesis, structure, electrochemical performance, and K-storage mechanisms. Finally, the review contributes to provide helpful sources for the increasing number of scientists working in this industry regarding its critical issues and challenges and also to indicate the future direction of electrode materials in PIBs.

关键词： Potassium ion batteries Efficient approaches Recent developments

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End-to-End 2D Convolutional Neural Network Architecture for Lung Nodule Identification and Abnormal Detection in Cloud

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Computers, Materials & Continua 2023年第4期75卷 461-475页

作者： Safdar Ali saad Asad Zeeshan Asghar Atif Ali Dohyeun Kim Department of Software Engineering the University of LahoreDefence Road CampusLahore55150Pakistan Department of Computer Engineering Jeju National UniversityAra CampusJeju City63243Korea

The extent of the peril associated with cancer can be perceivedfrom the lack of treatment, ineffective early diagnosis techniques, and mostimportantly its fatality rate. Globally, cancer is the second leading cause ofdeath and among over a hundred types of cancer;lung cancer is the secondmost common type of cancer as well as the leading cause of cancer-relateddeaths. Anyhow, an accurate lung cancer diagnosis in a timely manner canelevate the likelihood of survival by a noticeable margin and medical imagingis a prevalent manner of cancer diagnosis since it is easily accessible to peoplearound the globe. Nonetheless, this is not eminently efficacious consideringhuman inspection of medical images can yield a high false positive rate. Ineffectiveand inefficient diagnosis is a crucial reason for such a high mortalityrate for this malady. However, the conspicuous advancements in deep learningand artificial intelligence have stimulated the development of exceedinglyprecise diagnosis systems. The development and performance of these systemsrely prominently on the data that is used to train these systems. A standardproblem witnessed in publicly available medical image datasets is the severeimbalance of data between different classes. This grave imbalance of data canmake a deep learning model biased towards the dominant class and unableto generalize. This study aims to present an end-to-end convolutional neuralnetwork that can accurately differentiate lung nodules from non-nodules andreduce the false positive rate to a bare minimum. To tackle the problem ofdata imbalance, we oversampled the data by transforming available images inthe minority class. The average false positive rate in the proposed method isa mere 1.5 percent. However, the average false negative rate is 31.76 *** proposed neural network has 68.66 percent sensitivity and 98.42 percentspecificity.

关键词： Convolutional neural networks medical image processing lung nodule identification data imbalance deep learning

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Torsional postbuckling characteristics of functionally graded graphene enhanced laminated truncated conical shell with temperature dependent material properties

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Theoretical & Applied Mechanics Letters 2023年第4期13卷 272-279页

作者： Hamad M.Hasan saad S.Alkhfaji Sattar A.Mutlag Department of Mechanical Engineering University of AnbarRamadi 31001Iraq Department of Medical Instrumentation Engineering Ashur University CollegeBaghdad 10044Iraq

Buckling and postbuckling characteristics of laminated graphene-enhanced composite(GEC)truncated conical shells exposed to torsion under temperature conditions using finite element method(FEM)simulation are presented in this *** the thickness direction,the GEC layers of the conical shell are ordered in a piece-wise arrangement of functionally graded(FG)distribution,with each layer containing a variable volume fraction for graphene *** calculate the properties of temperaturedependent material of GEC layers,the extended Halpin-Tsai micromechanical framework is *** FEM model is verified via comparing the current results obtained with the theoretical estimates for homogeneous,laminated cylindrical,and conical shells,the FEM model is *** computational results show that a piece-wise FG graphene volume fraction distribution can improve the torque of critical buckling and torsional postbuckling ***,the geometric parameters have a critical impact on the stability of the conical ***,a temperature rise can reduce the crucial torsional buckling torque as well as the GEC laminated truncated conical shell’s postbuckling strength.

关键词： Torsional postbuckling Graphene enhanced composite Functionally graded graphene Finite element method Conical shell

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Real and Altered Fingerprint Classification Based on Various Features and Classifiers

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Computers, Materials & Continua 2023年第1期74卷 327-340页

作者： Saif saad Hameed Ismail Taha Ahmed Omar Munthir Al Okashi College of Computer Sciences and Information Technology University of AnbarAnbarIraq

Biometric recognition refers to the identification of individuals through their unique behavioral features(e.g.,fingerprint,face,and iris).We need distinguishing characteristics to identify people,such as fingerprints,which are world-renowned as the most reliablemethod to identify *** recognition of fingerprints has become a standard procedure in forensics,and different techniques are available for this *** current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification ***,we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and hackers routinely change their fingerprints to generate fake *** order to improve fingerprint classification accuracy,our proposed method used the most effective texture features and *** Analysis(DCA)and Gaussian Discriminant Analysis(GDA)are employed as classifiers,along with Histogram of Oriented Gradient(HOG)and Segmentation-based Feature Texture Analysis(SFTA)feature vectors as *** performance of the classifiers is determined by assessing a range of feature sets,and the most accurate results are *** proposed method is tested using a Sokoto Coventry Fingerprint Dataset(SOCOFing).The SOCOFing project includes 6,000 fingerprint images collected from 600 African people whose fingerprints were taken ten *** distinct degrees of obliteration,central rotation,and z-cut have been performed to obtain synthetically altered replicas of the genuine *** proposal achieved massive success with a classification accuracy reaching 99%.The experimental results indicate that the proposed method for fingerprint classification is feasible and *** experiments also showed that the proposed SFTA-based GDA method outperformed state-of-art approaches in feature dimension and classification accuracy.

关键词： Fingerprint classification HOG SFTA discriminant analysis(DCA)classifier gaussian discriminant analysis(GDA)classifier SOCOFing

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Link between COVID-19 vaccines and myocardial infarction

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World Journal of Clinical Cases 2022年第28期10卷 10109-10119页

作者： Umema Zafar Hamna Zafar Mian saad Ahmed Madiha Khattak Department of Physiology Khyber Medical CollegePeshawar 25000Pakistan Department of Medicine Khyber Teaching HospitalPeshawar 25000Pakistan Department of Forensic Medicine Khyber Medical CollegePeshawar 25000Pakistan

BACKGROUND Vaccines for coronavirus disease 2019(COVID-19) include Ch Ad Ox1-SARS-COV-2(Astra Zeneca),***2.S(Janssen),m RNA-1273(Moderna),BNT162b2(Pfizer),BBIBP-Cor V(Sinopharm),Corona Vac(Sinovac),and Bharat Biotech BBV152(Covaxin).AIM To find the association between COVID-19 vaccines and myocardial infarction(MI).METHODS This is a systematic review that involved searching databases such as MEDLINE,EMBASE,and Pak Medi Net after making a search strategy using Me SH and Emtree *** criteria were set,and studies having no mention of MI as a complication of COVID-19 vaccination,protocols,genetic studies,and animal studies were *** was extracted using a predesigned extraction table,and 29 studies were selected after screening and applying the eligibility *** The majority of studies mentioned Astra Zeneca(18 studies) followed by Pfizer(14 studies) and Moderna(9 studies) in subjects reporting MI after *** of all the studies,69% reported MI cases after the first COVID-19 vaccination dose and 14% after the second,44% reported ST-segment elevation MI,and 26% reported non-ST-segment elevation *** mortality rate was 29% after *** In conclusion,many studies linked MI to COVID-19 vaccinations,but no definitive association could be found.

关键词： SARS-Co V-2 infection Vaccination Myocardial infarction Association Pfizer Astra Zeneca Moderna Sinovac Janssen Covaxin

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Numerical Simulation of a Granular Flow on a Smooth Inclined Plane

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Fluid Dynamics & Materials Processing 2022年第6期18卷 1631-1638页

作者： Rida Tazi Adil Echchelh Mohammed El Ganaoui Aouatif saad Laboratory of Materials and Energy Faculty of SciencesIbn Tofail UniversityKenitraMorocco LERMAB/IUT Longwy Institut CarnotNancyFrance ASELab Advanced Systems Engineering Laboratory National School of Applied SciencesIbn Tofail UniversityKenitraMorocco

Unlike most fluids,granular materials include coexisting solid,liquid or gaseous regions,which produce a rich variety of complex *** flows of grains driven by gravity down inclines occur in nature and in *** describe the granular flow on an inclined surface,several studies were carried *** can cite in particular the description of Saint-Venant which considers a dry granular flow,without cohesion and it only takes into account the substance-substrate friction,this model proposes a simplified form of the granular flow,which depends on the one side on the angle of inclination of the substrate with respect to the horizontal plane and on the other side on the thickness of the substance *** numerical simulation we have developed is first based on the Saint-Venant model,it allowed us to visualize the variation of the speed according to the thickness of the substance(from 0 to H)and to deduce the average speed of the substance on an inclined ***,this restrictive model does not take into account the effect of particle friction on the flow and considers that the thickness H is *** make our simulation more realistic,we opted for the Savage-Hatter *** took into account the variation of the thickness on the particles speed,in addition we have studied the effect of the variation of many parameters on the granular flow,namely the temperature and the roughness of the substrate,the density and the compactness of the substance,we found that the speed of the particles increases and the treatment time decreases with an increase in temperature.

关键词： Granular flow friction cohesion angle ofinclination temperature

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A System of Sylvester-type Quaternion Matrix Equations with Ten Variables

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Acta Mathematica Sinica,English Series 2022年第8期38卷 1399-1420页

作者： Meng Yan XIE Qing Wen WANG Zhuo Heng HE Mehany Mahmoud saad Department of Mathematics Shanghai UniversityShanghai 200444P.R.China

This paper studies a system of three Sylvester-type quaternion matrix equations with ten variables A_(i)X_(i)+Y_iB_(i)+C_(i)Z_(i)D_(i)+F_(i)Z_(i+1)G_(i)=E_(i),i=1,3^-.We derive some necessary and sufficient conditions for the existence of a solution to this system in terms of ranks and Moore–Penrose inverses of the matrices *** present the general solution to the system when the solvability conditions are *** applications of this system,we provide some solvability conditions and general solutions to some systems of quaternion matrix equations involvingφ-***,we give some numerical examples to illustrate our *** findings of this paper extend some known results in the literature.

关键词： Quaternion matrix equation φ-Hermitian solution general solution solvability

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Deep Learning Control for Autonomous Robot

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Computers, Materials & Continua 2022年第8期72卷 2811-2824页

作者： Rihem Farkh saad Alhuwaimel Sultan Alzahrani Khaled Al Jaloud Mohammad Tabrez Quasim College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Laboratory for Analysis Conception and Control of SystemsLR-11-ES20Department of Electrical Engineering National Engineering School of TunisTunis El Manar University1002Tunisia King Abdulaziz City for Science and Technology Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

Several applications of machine learning and artificial intelligence,have acquired importance and come to the fore as a result of recent advances and improvements in these *** cars are one such *** is expected to have a significant and revolutionary influence on *** with smart cities,new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving *** autonomous automobile,often known as selfdriving systems or driverless vehicles,is a vehicle that can perceive its surroundings and navigate predetermined routes without human *** are on the verge of evolving into autonomous robots,thanks to significant breakthroughs in artificial intelligence and related technologies,and this will have a wide range of socio-economic ***,in order for these automobiles to become a reality,they must be endowed with the perception and cognition necessary to deal with high-pressure real-life events and make proper judgments and take appropriate *** majority of self-driving car technologies are based on computer systems that automate vehicle control *** forward-collision warning and antilock brakes to lane-keeping and adaptive drive control,to fully automated driving,these technological components have a wide range of capabilities.A self-driving car combines a wide range of sensors,actuators,and *** researches on computer vision and deep learning are used to control autonomous driving *** self-driving automobiles,lane-keeping is *** study presents a deep learning approach to obtain the proper steering angle to maintain the robot in the *** propose an advanced control for a selfdriving robot by using two controllers *** neural networks(CNNs)are employed,to predict the car’and a proportionalintegral-derivative(PID)controller is designed for speed and steering *** stu

关键词： Autonomous car cascade PID control deep learning convolutional neural network differential drive system raspberry PI road lane detector

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BN-GEPSO:Learning Bayesian Network Structure Using Generalized Particle Swarm Optimization

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Computers, Materials & Continua 2023年第5期75卷 4217-4229页

作者： Muhammad saad Salman Ibrahim M.Almanjahie AmanUllah Yasin Ammara Nawaz Cheema Air University Islamabad44000Pakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia

At present Bayesian Networks(BN)are being used widely for demonstrating uncertain knowledge in many disciplines,including biology,computer science,risk analysis,service quality analysis,and *** they suffer from the problem that when the nodes and edges increase,the structure learning difficulty increases and algorithms become *** solve this problem,heuristic optimization algorithms are used,which tend to find a near-optimal answer rather than an exact one,with particle swarm optimization(PSO)being one of *** is a swarm intelligence-based algorithm having basic inspiration from flocks of birds(how they search for food).PSO is employed widely because it is easier to code,converges quickly,and can be parallelized *** use a recently proposed version of PSO called generalized particle swarm optimization(GEPSO)to learn bayesian network *** construct an initial directed acyclic graph(DAG)by using the max-min parent’s children(MMPC)algorithm and cross relative average *** used to create a population for theGEPSO optimization ***,we propose a velocity update procedure to increase the efficiency of the algorithmic search *** of the experiments show that as the complexity of the dataset increases,our algorithm Bayesian network generalized particle swarm optimization(BN-GEPSO)outperforms the PSO algorithm in terms of the Bayesian information criterion(BIC)score.

关键词： Bayesian network structure learning particle swarm optimization

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