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Aldosterone synthase inhibitor“Baxdrostat”for resistant hypertension:A clinical approach or futuristic idea?

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Chronic Diseases and Translational Medicine 2024年第2期10卷 146-148页

作者： muhammad Osama Siddiqui Ayaan Ahmed qureshi Arooba Siddiqui Noor ul ain Liaquat National Hospital and Medical College KarachiSindhPakistan Karachi Medical and Dental College KarachiSindhPakistan

The American College of Cardiology/American Heart Association defines resistant hypertension(RH)as a clinical blood pressure(BP)reading of>130/80 mmHg in patients taking three antihypertensive drugs,including a renin–angiotensin system inhibitor,a calcium channel blocker(CCB),and a diuretic at well-tolerated doses.1,2 It is reported from multiple population-based surveys that in the United States,there is an approximately 12%–15%prevalence of RH among adults diagnosed with hypertension.2 A prospective study demonstrates that 20%of people diagnosed with RH had primary hyperaldosteronism.3,4 In addition to the classic three antihypertensive drugs,spironolactone and mineralocorticoid are also administered for ***,with respect to the safety profile of spironolactone,it has been reported to have several side effects such as low testosterone production,menstrual irregularities,and excessively raised serum potassium levels,leaving the drug unfit for the longitudinal therapeutic purpose of treating RH.

关键词： hypertension drugs hypertensive

Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman muhammad Farrukh qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

Limits of Depth: Over-Smoothing and Over-Squashing in GNNs

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Big Data Mining and Analytics 2024年第1期7卷 205-216页

作者： Aafaq Mohi ud din Shaima qureshi Department of Computer Science and Engineering National Institute of Technology SrinagarSrinagar 190006India

Graph Neural Networks(GNNs)have become a widely used tool for learning and analyzing data on graph structures,largely due to their ability to preserve graph structure and properties via graph representation ***,the effect of depth on the performance of GNNs,particularly isotropic and anisotropic models,remains an active area of *** study presents a comprehensive exploration of the impact of depth on GNNs,with a focus on the phenomena of over-smoothing and the bottleneck effect in deep graph neural *** research investigates the tradeoff between depth and performance,revealing that increasing depth can lead to over-smoothing and a decrease in performance due to the bottleneck *** also examine the impact of node degrees on classification accuracy,finding that nodes with low degrees can pose challenges for accurate *** experiments use several benchmark datasets and a range of evaluation metrics to compare isotropic and anisotropic GNNs of varying depths,also explore the scalability of these *** findings provide valuable insights into the design of deep GNNs and offer potential avenues for future research to improve their performance.

关键词： Graph Neural Networks(GNNs) learning on graphs over-smoothing over-squashing isotropic-GNNs anisotropic-GNNs

Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 485-512页

作者： Fatma Nese Efil Sania qureshi Nezihal Gokbulut Kamyar Hosseini Evren Hincal Amanullah Soomro Near East University Department of MathematicsNicosia99010North Cyprus Mehran University of Engineering and Technology Department of Basic Sciences and Related StudiesJamshoro76090Pakistan Department of Computer Science and Mathematics Lebanese American UniversityP.O.Box 13-5053BeirutLebanon Near East University Mathematics Research CenterNicosia99010North Cyprus

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 *** primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and ***,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart *** that,we highlight the stability assessments that can be applied to these *** analysis is used to examine how changes in certain factors impact different aspects of *** sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to *** correlation between diabetes and cardiovascular illness is also illustrated *** effects of smoking and obesity are also found to be significant in disease *** fitting is also provided for interpreting the relationship between real data and the results of *** people,in particular,need tomonitor their health conditions closely and practice heart health *** with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable *** main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and *** provision of the recommendations requires an increase in public consciousness.

关键词： COVID-19 mathematical modeling cancer diabetes heart diseases sensitivity analysis

Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan 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 Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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 143-150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 Sciences King Abdulaziz University Lithography in Devices Fabrication and Development Research Group Deanship of Scientific ResearchKing Abdulaziz University Joint Laboratory of Plasma Application Technology Institute of Advanced Technology University of Science and Technology of China CAS Key Laboratory of Geospace Environment University of Science and Technology of China Department of Physics Zhejiang Normal University Department of Physics Graduate School of Science Tokyo Metropolitan University Department of Physics GC University

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 function. Recent studies have reported the argon-helium plasma and conducted a brief theoretical and experimental survey. To deepen our understanding further, this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the(r, q)-distribution function. For 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 q. It 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 ratio. By incorporating the multi-ion(argon-helium) species, the significance of low-temperature nonMaxwellian dusty(complex) plasma is briefly examined.

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

Feeding behavior and hormoligosis associated with imidacloprid resistance in Asian citrus psyllid,Diaphorina citri

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Insect Science 2024年第4期31卷 1211-1221页

作者： Xue Dong Chen Justin George Lauren M.Diepenbrock Hunter Gossett Guoping Liu Jawwad A.qureshi Lukasz L.Stelinski Entomology and Nematology Department University of FloridaCitrus Research and Education CenterLake AlfredFloridaUSA Southern Insect Management Research Unit USDA-ARSStonevilleMississippiUSA Entomology and Nematology Department University of FloridaSouthwest Florida Research and Education CenterImmokaleeFloridaUSA

Imidacloprid is a neonicotinoid insecticide used for managing the Asian citrus psyllid,Diaphorina citri Kuwayama,which serves as vector of phytopathogens causing citrus ***,development of resistance to neonicotinoids among populations of *** has coincided with occasional control failures in the *** objectives of this research were to(1)survey current levels of imidacloprid resistance in Florida citrus;(2)compare feeding behavior between imidacloprid-resistant and susceptible *** using electrical penetration graph recordings,and(3)investigate the possible amplification of insecticide hormoligosis associated with *** surveys confirmed that the susceptibility of *** populations to imidacloprid has decreased in commercial Florida citrus groves compared with a laboratory-susceptible *** 12 generations of selection,resistance to imidacloprid increased by 438 fold compared with the susceptible ***-susceptible *** feeding on citrus exhibited significantly more bouts associated with intercellular pathway(C),phloem penetration(D),phloem salivation(E1),and nonprobing(Np)activities than imidacloprid-resistant ***,there were no differences observed in the frequency or duration of phloem ingestion or xylem feeding between susceptible and resistant *** was no statistical difference in fecundity between resistant and susceptible ***,the fecundity of imidacloprid-susceptible female *** treated with a sublethal concentration of imidacloprid(LC_(25))increased significantly compared with controls,while such hormoligosis was less pronounced among imidacloprid-resistant *** results suggest that imidacloprid-resistant psyllids may cease feeding sooner than susceptible counterparts following sublethal exposure to this insecticide,indicative of a behavioral resistance mechanism.

关键词： artificial selection electrical penetration graph feeding behavior hormoligosis insecticide resistance sublethal exposure

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

Leveraging UAV-assisted communications to improve secrecy for URLLC in 6G systems

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Digital Communications and Networks 2023年第6期9卷 1458-1464页

作者： Hemant Kumar Narsani ali Ranjha Kapal Dev Fida Hussain Memon Nawab muhammad Faseeh qureshi Faculty of Engineering and Technology University of SindhPakistan Department of Electrical Engineering Ecole de Technologie Superieure Montreal QCCanada Department of Institute of Intelligent Systems University of JohannesburgSouth Africa Department of Electrical Engineering Sukkur IBA UniversityPakistan Department of Computer Education Sungkyunkwan UniversitySeoulRepublic of Korea

Unmanned Aerial Vehicles(UAVs)will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication(URLLC)in futuristic Sixth-Generation(6G)***,several security vulnerabilities and attacks have plagued previous generations of communication systems;thus,physical layer security,especially against eavesdroppers,is vital,especially for upcoming 6G *** this regard,UAVs have appeared as a winning candidate to mitigate security *** this paper,we leverage UAVs to propose two *** first method utilizes a UAV as Decode-and-Forward(DF)relay,whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver ***,we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception,*** secrecy rate,and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF ***,simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height,blocklength,decoding error probability and transmitter-receiver separation ***,we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

关键词： URLLC UAV-Assisted communications 6G systems Secrecy rate