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multifunctional mXene/Carbon Nanotube Janus Film for Electromagnetic Shielding and Infrared Shielding/Detection in Harsh Environments

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Nano-micro Letters 2024年第10期16卷 543-560页

作者： Tufail Hassan aamir Iqbal Byungkwon Yoo Jun Young Jo Nilufer Cakmakci Shabbir madad Naqvi Hyerim Kim Sungmin Jung Noushad Hussain Ujala Zafar Soo Yeong Cho Seunghwan Jeong Jaewoo Kim Jung min Oh Sangwoon Park Youngjin Jeong Chong min Koo School of advanced materials Science and Engineering Sungkyunkwan UniversitySeobu-ro 2066Jangan-guSuwon-siGyeonggi-do 16419Republic of Korea Department of materials Science and Engineering Soongsil UniversitySeoul 06978Republic of Korea Institute of advanced Composite materials Korea Institute of Science and Technology92 Chudong-roBongdong-eupWanju-gunJeollabuk-do 55324Republic of Korea R&D Center INNOmXENE Co. Ltd.Daejeon 34365Republic of Korea School of Chemical Engineering Sungkyunkwan UniversitySeobu-ro 2066Jangan-guSuwon-siGyeonggi-do 16419Republic of Korea

multifunctional,flexible,and robust thin films capable of operating in demanding harsh temperature environments are crucial for various cutting-edge *** study presents a multifunctional Janus film integrating highly-crystalline Ti_(3)C_(2)T_(x) mXene and mechanically-robust carbon nanotube(CNT)film through strong hydrogen *** hybrid film not only exhibits high electrical conductivity(4250 S cm^(-1)),but also demonstrates robust mechanical strength and durability in both extremely low and high temperature environments,showing exceptional resistance to thermal *** hybrid Janus film of 15μm thickness reveals remarkable multifunctionality,including efficient electromagnetic shielding effectiveness of 72 dB in X band frequency range,excellent infrared(IR)shielding capability with an average emissivity of 0.09(a minimal value of 0.02),superior thermal camouflage performance over a wide temperature range(−1 to 300℃)achieving a notable reduction in the radiated temperature by 243℃ against a background temperature of 300℃,and outstanding IR detection capability characterized by a 44%increase in resistance when exposed to 250 W IR *** multifunctional mXene/CNT Janus film offers a feasible solution for electromagnetic shielding and IR shielding/detection under challenging conditions.

关键词： mXene/carbon nanotube Janus film Electromagnetic interference shielding Infrared shielding Thermal camouflage Infrared detection

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Left bundle branch pacing vs biventricular pacing in heart failure patients with left bundle branch block:A systematic review and meta-analysis

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World Journal of Cardiology 2024年第1期16卷 40-48页

作者： Farah Yasmin Abdul moeed Rohan Kumar Ochani hamna Raheel malik Ali Ehtsham Awan Ayesha Liaquat Arisha Saleem m.ham.ad aamir Nael Hawwa Salim Surani Department of Internal medicine Yale University School of MedicineNew HavenCT 06511United States Department of medicine Dow University of Health ScienceKarachi 74200SindhPakistan Department of medicine SUNNY Upstate Medical UniversitySyracuseNY 13210United States Department of Cardiovascular medicine Lehigh Valley Heart and Vascular InstituteAllentownPA 18105United States Department of medicine Cleveland ClinicClevelandOH 44195United States Department of medicine&Pharmacology Texas A&M UniversityCollege StationTX 77843United States

BACKGROUND Left bundle branch pacing(LBBP)is a novel pacing modality of cardiac resynchronization therapy(CRT)that achieves more physiologic native ventricular activation than biventricular pacing(BiVP).AIm To explore the validity of electromechanical resynchronization,clinical and echocardiographic response of *** Systematic review and meta-analysis were conducted in accordance with the standard guidelines as mentioned in detail in the methodology *** In our analysis,the success rate of LBBP-CRT was determined to be 91.1%.LBBP CRT significantly shortened QRS duration,with significant improvement in echocardiographic parameters,including left ventricular ejection fraction,left ventricular end-diastolic diameter and left ventricular end-systolic diameter in comparison with *** A significant reduction in New York Heart Association class and B-type natriuretic peptide levels was also observed in the LBBP-CRT group vs BiVP-CRT ***,the LBBP-CRT cohort had a reduced pacing threshold at follow-up as compared to BiVP-CRT.

关键词： Left bundle branch pacing Biventricular pacing QRS duration Left ventricular ejection fraction Heart failure

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Search for a lighter neutral custodial fiveplet scalar in the Georgi-machacek model

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Chinese Physics C 2022年第8期46卷 114-121页

作者：王储陶军全 m.aamir Shahzad 陈国明 S.Gascon-Shotkin Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China Institut de Physique des 2 Infinis de Lyon Universitéde LyonUniversitéClaude Bernard Lyon 1CNRS-IN2P3Villeurbanne 69622France

many researches from both theoretical and experimental perspectives have been performed to search for a new Higgs Boson that is lighter than the 125 GeV Higgs boson,which was discovered at the LHC in *** this study,we explore the possibility of constraining a lighter neutral custodial fiveplet scalar H_(5)^(0) in the Georgimachacek(Gm) model using the latest results of the search for a lighter Higgs boson decaying into two photons from LHC *** custodial-singlet mass eigenstate h or H is considered to be the LHC observed 125 GeV Higgs boson.A new set of constrained parameters that is favoured by low-mass H_(5)^(0) is proposed to generate events *** production of H_(5)^(0) from a scan based on the constrained parameters is compared to the latest results of the search for a lighter Higgs boson decaying into two photons by the CmS Collaboration after applying theoretical constraints from the Gm model and constraints from all existing relevant experimental measurements,including the recent results of the Higgs boson searches by the *** analyses of the surviving Gm parameter space are *** tendencies and correlations of the Gm input parameters from phenomenological studies are *** addition,the discovery potential of the other interesting decay channels of this low-mass neutral custodial fiveplet scalar are discussed.

关键词： Georgi-machacek model lighter neutral custodial fiveplet scalar phenomenological studies

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Data Reliability and Sensors Lifetime in Bridge Health monitoring using LoRaWAN-Zigbee

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Computers, materials & Continua 2022年第11期73卷 2663-2678页

作者： Awad Ali Reyazur Rashid Irshad Ahmed Abdu Alattaab aamir Fatahayab Department of Computer Science College of Science and Arts-SharourahNajran UniversityNajranKingdom of Saudi Arabia Department of Computer Science JJTUJhunjhunuRajasthanIndia

The Wireless Sensor Network(WSN)is regarded as the fastest expanding technological trend in recent years due its application in a variety of *** the monitoring region,several sensor nodes with various sensing capabilities are installed to gather appropriate data and communicate it to the *** proposed system of the heterogeneous WSN employing LoRaWAN-Zigbee based hybrid communication is explored in this research *** communicate in a network,two Long–Range Wide Area Network(LoRaWAN)sensor clusters and two Zigbee sensor clusters are employed,together with two Zigbee and LoRaWAN *** suggested Golden eagle shepherd optimization(GESO)method then forms Zigbee as well as LoRaWAN networking ***,depending on energy usage and data packet size,the fitness of each sensor node is assessed using the Dynamic Intelligent Reasoning Based Neural(DIRN)*** software is used to implement and execute this *** the Zigbee network’s transmission distance is 650 m and the LoRaWAN network’s transmission range is 3.5 km,the system can function with a packet loss rate of less than 0.04 *** study shows significant gains in the performance of the system when compared to traditional approaches based on digital findings obtained on software solutions.

关键词： Zigbee LoRaWAN wireless sensor network health monitoring routing protocol

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COVID-19 Classification from X-Ray Images:An Approach to Implement Federated Learning on Decentralized Dataset

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Computers, materials & Continua 2023年第5期75卷 3883-3901页

作者： Ali Akbar Siddique S.m.Umar Talha m.aamir Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Department of Telecommunication Engineering Sir Syed University of Engineering&TechnologyKarachi75300Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The COVID-19 pandemic has devastated our daily lives,leaving horrific repercussions in its *** to its rapid spread,it was quite difficult for medical personnel to diagnose it in such a big *** who test positive for Covid-19 are diagnosed via a nasal PCR *** comparison,polymerase chain reaction(PCR)findings take a few hours to a few *** PCR test is expensive,although the government may bear expenses in certain ***,subsets of the population resist invasive testing like ***,chest X-rays or Computerized Vomography(CT)scans are preferred in most cases,and more importantly,they are non-invasive,inexpensive,and provide a faster response *** advances in Artificial Intelligence(AI),in combination with state-of-the-art methods,have allowed for the diagnosis of COVID-19 using chest *** article proposes a method for classifying COVID-19 as positive or negative on a decentralized dataset that is based on the Federated learning *** order to build a progressive global COVID-19 classification model,two edge devices are employed to train the model on their respective localized dataset,and a 3-layered custom Convolutional Neural Network(CNN)model is used in the process of training the model,which can be deployed from the *** two edge devices then communicate their learned parameter and weight to the server,where it aggregates and updates the *** proposed model is trained using an image dataset that can be found on *** are more than 13,000 X-ray images in Kaggle Database collection,from that collection 9000 images of Normal and COVID-19 positive images are *** edge node possesses a different number of images;edge node 1 has 3200 images,while edge node 2 has *** is no association between the datasets of the various nodes that are included in the *** doing it in this manner,each of the nodes will have access to a separate image collection that has no correl

关键词： Artificial intelligence deep learning federated learning COVID-19 decentralized image dataset

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Thermophoresis and concentration effects in a fourth grade peristaltic flow with convective walls

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Journal of Central South University 2017年第7期24卷 1654-1662页

作者： Ali aamir Asghar S Awais m Department of mathematics COMSATS Institute of Information TechnologyAttock 43600Pakistan Department of mathematics COMSATS Institute of Information TechnologyIslamabad 44000Pakistan Department of mathematics King Abdulaziz UniversityJeddah 21432Saudi Arabia

In this investigation,we have studied the peristaltic fluid flow in an asymmetric channel with convective *** grade fluid model has been utilized in view of the fact that the results of all other differential type models can be deduced as the special *** effects of heat and mass transfer are *** thermophoresis effects occur in the energy *** heat and mass boundary conditions have been given special *** wave length and low Reynolds number approximations are utilized for the *** analytic solutions for the velocity,temperature and concentration profiles are calculated using perturbation technique and elaborated in the form of graphical observations for various physical quantities.

关键词： fourth grade fluid convective boundary conditions pumping and trapping peristalsis

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Recent advances on Porous materials for Synergetic adsorption and Photocatalysis

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Energy & Environmental materials 2022年第3期5卷 711-730页

作者： Tianqi Wang Bingbing Tian Bin Han Dingren ma mingzhe Sun aamir Hanif Dehua Xia Jin Shang International Collaborative Laboratory of 2D materials for Optoelectronics Science and Technology of ministry of Education Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060China School of Energy and Environment City University of Hong KongTat Chee AvenueKowloonHong Kong China Institute of microscale Optoelectronics Shenzhen UniversityShenzhen 518060China Key Laboratory for City Cluster Environmental Safety and Green Development of the ministry of Education Institute of Environmental and Ecological EngineeringGuangdong University of TechnologyGuangzhou 510006China School of Environmental Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275China City University of Hong Kong Shenzhen Research Institute Nanshan District8 Yuexing 1st RoadShenzhen Hi−Tech Industrial ParkShenzhen 518060China Department of Chemistry Islamic University of Science and TechnologyAwantipora 192122India

Porous photocatalysts are promising materials capable of simultaneously adsorbing and oxidizing/reducing target species,showing great potentials in environmental remediation and energy *** review offered a comprehensive overview of the recent progress in design,fabrication,and applications of porous photocatalysts,including carbon-based semiconductors,metal oxides/sulfides,metal–organic frameworks,and adsorbent–photocatalyst *** fundamental understanding of the structure–performance relationships of porous materials together with the in-depth insights into the synergetic effects between adsorption and photocatalysis was *** strategies to further improve the photocatalytic activity of porous photocatalysts were *** review would provide references and outlooks of constructing efficient porous materials for adsorptive and photocatalytic removal of pollutants and energy production.

关键词： adsorption photocatalysis porous materials synergetic effect

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A Novel Inherited modeling Structure of Automatic Brain Tumor Segmentation from mRI

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Computers, materials & Continua 2022年第11期73卷 3983-4002页

作者： Abdullah AAsiri Tariq Ali Ahmad Shaf m.ham.ad aamir m.ham.ad Shoaib m.ham.ad Irfan Hassan A.Alshamrani Fawaz F.Alqahtani Osama m.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Informatics and Systems University of Management and TechnologyLahore54000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Clinical Laboratory Sciences Collage of Applied Medical ScienceNajran UniversityNajranSaudi Arabia

Brain tumor is one of the most dreadful worldwide types of cancer and affects people leading to *** resonance imaging methods capture skull images that contain healthy and affected *** checked the affected tissue in the slice-by-slice manner,which was timeconsuming and hectic ***,auto segmentation of the affected part is needed to facilitate ***,we have considered a hybrid model that inherits the convolutional neural network(CNN)properties to the support vector machine(SVm)for the auto-segmented brain tumor *** CNN model is initially used to detect brain tumors,while SVm is integrated to segment the tumor region *** proposed method was evaluated on a publicly available BraTS2020 *** statistical parameters used in this work for the mathematical measures are precision,accuracy,specificity,sensitivity,and dice ***,our method achieved an accuracy value of 0.98,which is most prominent than existing ***,the proposed approach is more suitable for medical experts to diagnose the early stages of the brain tumor.

关键词： Brain tumor support vector machine convolutional neural network BraTS classification

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Optimal Site and Size of Distributed Generation Allocation in Radial Distribution Network Using multi-objective Optimization

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Journal of modern Power Systems and Clean Energy 2021年第2期9卷 404-415页

作者： aamir Ali m.U.Keerio J.A.Laghari the Department of Electrical Engineering Quaid-E-Awam University of Engineering Science and TechnologyNawabshahPakistan

Distributed generation(DG)allocation in the distribution network is generally a multi-objective optimization *** maximum benefits of DG injection in the distribution system highly depend on the selection of an appropriate number of DGs and their capacity along with the best *** this paper,the improved decomposition based evolutionary algorithm(I-DBEA)is used for the selection of optimal number,capacity and site of DG in order to minimize real power losses and voltage deviation,and to maximize the voltage stability *** proposed I-DBEA technique has the ability to incorporate non-linear,nonconvex and mixed-integer variable problems and it is independent of local extrema *** order to validate the effectiveness of the proposed technique,IEEE 33-bus,69-bus,and 119-bus standard radial distribution networks are ***,the choice of optimal number of DGs in the distribution system is also *** simulation results of the proposed method are compared with the existing *** comparison shows that the proposed method has the ability to get the multi-objective optimization of different conflicting objective functions with global optimal values along with the smallest size of DG.

关键词： Distribution system distributed generation multi-objective optimization active power loss improved decomposition based evolutionary algorithm(I-DBEA)

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multi-Level Deep Generative adversarial Networks for Brain Tumor Classification on magnetic Resonance Images

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Intelligent Automation & Soft Computing 2023年第4期36卷 127-143页

作者： Abdullah A.Asiri Ahmad Shaf Tariq Ali m.ham.ad aamir Ali Usman m.ham.ad Irfan Hassan A.Alshamrani Khlood m.mehdar Osama m.Alshehri Samar m.Alqhtani Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Department of Clinical Laboratory Sciences Collage of Applied Medical ScienceNajran UniversityNajranSaudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

The brain tumor is an abnormal and hysterical growth of brain tissues,and the leading cause of death affected patients *** in this technol-ogy-based arena,brain tumor images with proper labeling and acquisition still have a problem with the accurate and reliable generation of realistic images of brain tumors that are completely different from the original *** artiﬁcially created medical image data would help improve the learning ability of physicians and other computer-aided systems for the generation of augmented *** over-come the highlighted issue,a Generative adversarial Network(GAN)deep learn-ing technique in which two neural networks compete to become more accurate in creating artiﬁcially realistic data for mRI *** GAN network contains mainly two parts known as generator and ***,a generator is the convolutional neural network,and a discriminator is the deconvolutional neural *** this research,the publicly accessible Contrast-Enhanced mag-netic Resonance Imaging(CE-mRI)dataset collected from 2005-to 2020 from different hospitals in China consists of four classes has been *** proposed method is simple and achieved an accuracy of 96%.We compare our technique results with the existing results,indicating that our proposed technique outper-forms the best results associated with the existing methods.

关键词： GAN network CE-mRI images convolutional neural network brain tumor classiﬁcation

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