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Laparoscopic, Endoscopic and Robotic surgery 2018年第2期1卷 33-36页

作者： M.johnson O.A.Khan E.R.McGlone A.A.Roman j.s.qureshi A.Kayal Anaesthetic Registrar St Helier HospitalWrythe LaneSM51AAUK st Georges NHs Trust LondonSW17 OQTUK

Complete and reliable neuromuscular reversal is important to successful anaesthetic recovery in the morbidly obese patient undergoing laparoscopic *** goal was to determine whether sugammadex,a selective reversal agent is associated with better respiratory recovery than neostigmine following the reversal of anaesthesia-associated neuromuscular blockade by rocuronium in the morbidly *** Expiratory Flow Rate a surrogate marker for respiratory function,was the primary outcome measured and secondary outcome measures included post-operative nausea and vomiting,pain and head *** found that patients reversed with sugammadex had a significantly higher post-operative PEFR as compared to those reversed with neostigmine and glycopyrrolate group.

关键词： sugammadex Laparoscopic surgery Neuromuscular blockade Morbidly obese

Dust particle surface potential in an argonhelium plasma using the(r,q)-distribution function

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Communications in Theoretical Physics 2024年第9期76卷 141-148页

作者： Bahaaudin M Raffah A A Abid Abdullah Khan Amin Esmaeili Yas Al-Hadeethi M N s qureshi Department of Physics Faculty of SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Lithography in Devices Fabrication and Development Research Group Deanship of Scientific ResearchKing Abdulaziz UniversityJeddah 21589Saudi Arabia joint Laboratory of Plasma Application Technology Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei230026China CAs Key Laboratory of Geospace Environment University of Science and Technology of ChinaHefei230026China Department of Physics Zhejiang Normal UniversityJinhua321005China Department of Physics Graduate School of ScienceTokyo Metropolitan UniversityMinami-Osawa 1-1Hachioji City192-0397Japan Department of Physics GC UniversityLahore 54000Pakistan

In this paper,the dust particle surface potential for argon-helium plasma is evaluated analytically and numerically in the context of negatively charged dust particles by employing a power-law(r,q)-distribution *** studies have reported the argon-helium plasma and conducted a brief theoretical and experimental *** deepen our understanding further,this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the(r,q)-distribution *** this purpose,the current balance equations are derived for electron,helium and argon ions,when these charge species attain the quasineutrality *** numerically examined the currents of plasma species for a broad range of effective distribution function parameters r and *** is revealed that the surface potential of dust particles is significantly affected by the parameters r and q,helium ion-to-electron temperature ratio,argon ion-to-electron temperature ratio,and helium ion to argon ion number density *** incorporating the multi-ion(argon-helium)species,the significance of low-temperature nonMaxwellian dusty(complex)plasma is briefly examined.

关键词： dusty plasma dust charge potential plasma physics helium argon plasma r q distribution function non-Maxwellian distribution

Evaluating the spike in the symptomatic proportion of sARs-CoV-2 in China in 2022 with variolation effects:a modeling analysis

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Infectious Disease Modelling 2024年第2期9卷 601-617页

作者： salihu s.Musa shi Zhao Ismail Abdulrashid sania qureshi Andrés Colubri Daihai He Department of Genomics and Computational Biology University of Massachusetts Chan Medical SchoolWorcesterMA01605USA Department of Applied Mathematics Hong Kong Polytechnic UniversityHong Kong SARChina Department of Mathematics Aliko Dangote University of Science and TechnologyKanoNigeria school of Public Health Tianjin Medical UniversityTianjin300070China school of Finance and Operations Management The University of Tulsa800 South Tucker Dr.TulsaOK74104USA Department of Basic sciences and Related studies Mehran University of Engineering and Tech.JamshoroPakistan Department of Computer science and Mathematics Lebanese American UniversityBeirutLebanon

Despite most COVID-19 infections being asymptomatic,China's Mainland had a high increase in symptomatic cases at the end of *** this study,we examine China's sudden COVID-19 symptomatic surge using a conceptual sIR-based *** model considers the epidemiological characteristics of sARs-CoV-2,particularly variolation,from non-pharmaceutical intervention(facial masking and social distance),demography,and disease mortality in China's *** increase in symptomatic proportions in China may be attributable to(1)higher sensitivity and vulnerability during winter and(2)enhanced viral inhalation due to spikes in sARs-CoV-2 infections(high transmissibility).These two reasons could explain China's high symptomatic proportion of COVID-19 in December *** study,therefore,can serve as a decision-support tool to enhance sARs-CoV-2 prevention and control ***,we highlight that facemask-induced variolation could potentially reduces transmissibility rather than severity in infected ***,further investigation is required to understand the variolation effect on disease severity.

关键词： sARs-CoV-2 Epidemic Epidemiological modeling Reproduction number Variolation

Computational Approach for Automated segmentation and Classification of Region of Interest in Lateral Breast Thermograms

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Computers, Materials & Continua 2024年第9期80卷 4749-4765页

作者： Dennies Tsietso Abid Yahya Ravi samikannu Basit qureshi Muhammad Babar Department of Electrical Computer and Telecommunications EngineeringBotswana International University of Science and TechnologyPalapyePrivate Bag 16Botswana College of Computer and Information sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Robotics and Internet of Things Lab Prince Sultan UniversityRiyadh11586Saudi Arabia

Breast cancer is one of the major health issues with high mortality rates and a substantial impact on patients and healthcare systems *** Computer-Aided Diagnosis(CAD)tools,based on breast thermograms,have been developed for early detection of this ***,accurately segmenting the Region of Interest(ROI)fromthermograms remains *** paper presents an approach that leverages image acquisition protocol parameters to identify the lateral breast region and estimate its bottomboundary using a second-degree *** proposed method demonstrated high efficacy,achieving an impressive jaccard coefficient of 86%and a Dice index of 92%when evaluated against manually created ground *** features were extracted from each view’s ROI,with significant features selected via Mutual Information for training Multi-Layer Perceptron(MLP)and K-Nearest Neighbors(KNN)*** findings revealed that the MLP classifier outperformed the KNN,achieving an accuracy of 86%,a specificity of 100%,and an Area Under the Curve(AUC)of *** consistency of the method across both sides of the breast suggests its viability as an auto-segmentation ***,the classification results suggests that lateral views of breast thermograms harbor valuable features that can significantly aid in the early detection of breast cancer.

关键词： Breast cancer CAD machine learning ROI segmentation thermography

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision support system

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原子能科学技术 2024年第10期58卷 2068-2076页

作者： BILAL Ahmed Khan HAsEEB ur Rehman QAIsAR Nadeem MUHAMMAD Ahmad Naveed qureshi jAWARIA Ahad MUHAMMAD Naveed Akhtar AMjAD Farooq MAsROOR Ahmad Pakistan Institute of Engineering and Applied sciences Islamabad 44000Pakistan

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) *** meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support *** of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and ***,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological *** evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-south *** performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological *** show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single ***,accuracy is slightly compromised when predicting wind speed *** mean square error (RMsE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of *** conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

关键词： prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system

semantic segmentation and YOLO Detector over Aerial Vehicle Images

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Computers, Materials & Continua 2024年第8期80卷 3315-3332页

作者： Asifa Mehmood qureshi Abdul Haleem Butt Abdulwahab Alazeb Naif Al Mudawi Mohammad Alonazi Nouf Abdullah Almujally Ahmad jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Computer science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Cognitive systems Lab University of BremenBremen28359Germany

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway ***,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall *** learning is considered to be an efficient method for object detection in vision-based *** this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation *** model consists of six *** the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the *** pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in *** detection was exposed to speeded Up Robust Feature(sURF)feature extraction to track multiple *** on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching ***,we implemented a Kalman filter to track multiple *** the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking *** experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art *** proposed implemented system provided 94.1%detection precision for Roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

关键词： semantic segmentation YOLOv5 vehicle detection and tracking Kalman filter sURF

Generalized polynomial chaos expansion by reanalysis using static condensation based on substructuring

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 819-836页

作者： D.LEE s.CHANG j.LEE Department of Automotive Engineering Hanyang UniversitySeoul 04763Republic of Korea school of Mechanical Engineering Chungnam National UniversityDaejeon 34134Republic of Korea Department of Mechanical Robotics and Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea

This paper presents a new computational method for forward uncertainty quantification(UQ)analyses on large-scale structural systems in the presence of arbitrary and dependent random *** method consists of a generalized polynomial chaos expansion(GPCE)for statistical moment and reliability analyses associated with the stochastic output and a static reanalysis method to generate the input-output data *** the reanalysis,we employ substructuring for a structure to isolate its local regions that vary due to random *** allows for avoiding repeated computations of invariant substructures while generating the input-output data *** substructuring with static condensation further improves the computational efficiency of the reanalysis without losing ***,the GPCE with the static reanalysis method can achieve significant computational saving,thus mitigating the curse of dimensionality to some degree for UQ under high-dimensional *** numerical results obtained from a simple structure indicate that the proposed method for UQ produces accurate solutions more efficiently than the GPCE using full finite element analyses(FEAs).We also demonstrate the efficiency and scalability of the proposed method by executing UQ for a large-scale wing-box structure under ten-dimensional(all-dependent)random inputs.

关键词： forward uncertainty quantification(UQ) generalized polynomial chaos expansion(GPCE) static reanalysis method static condensation substructuring

Background removal from global auroral images:Data-driven dayglow modeling

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Earth and Planetary Physics 2024年第1期8卷 247-257页

作者： A.Ohma M.Madelaire K.M.Laundal j.P.Reistad s.M.Hatch s.Gasparini s.j.Walker Birkeland Centre for space science Department of Physics and TechnologyUniversity of BergenBergenNorway

Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth ***,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by *** emissions and scattered sunlight can contribute to the background *** fully utilize such images in space science,background contamination must be removed to isolate the auroral *** we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical *** approach is robust,flexible,and iteratively deselects outliers,such as auroral *** final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the *** demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)*** method can be applied to historical missions and is relevant for upcoming missions,such as the solar wind Magnetosphere Ionosphere Link Explorer(sMILE)mission.

关键词： aurora dayglow modeling global auroral images far ultraviolet images dayglow removal

Mathematical modeling and simulations of stress mitigation by coating polycrystalline particles in lithium-ion batteries

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 947-962页

作者： N.IQBAL j.CHOI s.F.sHAH C.LEE s.LEE Department of Mechanical Roboticsand Energy EngineeringDongguk University-SeoulSeoul 04620Republic of Korea

A chemo-mechanical model is developed to investigate the effects on the stress development of the coating of polycrystalline Ni-rich LiNixMnyCo_(z)O_(2)(x≥0.8)(NMC)particles with poly(3,4-ethylenedioxythiophene)(PEDOT).The simulation results show that the coating of primary NMC particles significantly reduces the stress generation by efficiently accommodating the volume change associated with the lithium diffusion,and the coating layer plays roles both as a cushion against the volume change and a channel for the lithium transport,promoting the lithium distribution across the secondary particles more ***,the lower stiffness,higher ionic conductivity,and larger thickness of the coating layer improve the stress *** paper provides a mathematical framework for calculating the chemo-mechanical responses of anisotropic electrode materials and fundamental insights into how the coating of NMC active particles mitigates stress levels.

关键词： lithium-ion battery(LIB) polycrystalline particle coating finite element simulation Ni-rich LiNixMnyCo_(z)O_(2)(x>0.8)(NMC)

Mathematical modelling of ball and plate system with experimental and correlation function-based model validation

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Control Theory and Technology 2024年第2期22卷 326-341页

作者： T.R.Dil Kumar s.j.Mija Department of Electrical Engineering National Institute of Technology CalicutKozhikode673601KeralaIndia

The ball and plate system is an inherently nonlinear under actuated benchmark system used for validating the performance of various control schemes. A mathematical model depicting the dynamics close to that of the system is very much required for such a test bed. In this correspondence, the complete nonlinear model, a simplified nonlinear model, and a linearized model of the ball and plate system are developed. The system comprises a ball and plate mechanism and a rotary servo unit. The ball and plate mechanism is modelled using the Euler–Lagrange method, whereas the rotary servo subsystem is modelled from the first principles. The nonlinear model of the combined system is developed by including the dynamics of the servo motor with gear and rolling resistance between the ball and the plate. The simplified nonlinear model of the system is obtained with suitable assumptions. The model is linearized around the operating point using the jacobian. The validity of the developed models is investigated through correlation function analysis. The open-loop response of the three models, viz., nonlinear, simplified nonlinear, and linearized models, is analyzed in the MATLAB/simulink platform. since the open-loop system is unstable, the experimental validation of the model is performed with a double-loop PsO (particle swarm optimization) PID control scheme.

关键词： Ball and plate system Correlation function Model validation Particle swarm optimization(PsO) PsO PID controller