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探测激子极化激元在超薄范德华微晶中的光传播

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Chinese Journal of Chemical Physics 2024年第1期37卷 35-42,I0001-I0004,I0117页

作者： talha Ijaz 边琦曹琰丁皓璇陈晓瑞卢欢杨树邢雪婷方思敏刘孟源张鑫高健智潘明虎陕西师范大学物理学与信息技术学院西安710062 华中科技大学物理学院武汉430074 洛阳师范大学物理与电子信息学院洛阳英国伯明翰大学物理与天文学院伯明翰B152TT 西安文理学院机械与材料工程学院西安710065 陕西师范大学地理与旅游学院西安710119 复旦大学信息科学与工程学院上海200433 珠海复旦创新研究院珠海519000 西北大学物理学院西安710069

激子极化激元是一种准粒子,过渡金属二硫族化合物材料即使在室温下也能支持传播激子极化子,是非常好的纳米光子学研究平台.已有研究表明,通过散射型扫描近场光学显微镜可以对过渡金属二硫族化合物薄片中激子极化激元进行实空间探测,但... 详细信息

激子极化激元是一种准粒子,过渡金属二硫族化合物材料即使在室温下也能支持传播激子极化子,是非常好的纳米光子学研究平台.已有研究表明,通过散射型扫描近场光学显微镜可以对过渡金属二硫族化合物薄片中激子极化激元进行实空间探测,但波导厚度仅限于低至30 nm.本文采用三种不同波长的入射光(1550和1064 nm的近红外以及633 nm的可见光),通过基于原子力显微镜的散射型扫描近场光学显微镜测量,探测到moS2和WSe2薄片中激子极化子普通横电模式的纳米光学成像.在厚度分别低至~3 nm(相当于4原子层)和~8 nm(相当于12原子层)的超薄moS2和WSe2薄片上,可以清楚地观察到干涉条纹图案,大大打破了之前的测量厚度限制.当厚度接近几个原子层时,波矢量始终保持在1.6k0~1.7k0左右,而不是理论预言的1k0.这些模式的特性表明,体系是由近乎悬浮的过渡金属二硫族化合物薄片的三层对称波导构成,其对激子极性子的传播产生限域效应.研究结果为探索基于超薄过渡金属二硫族化合物材料的近红外区极化器件提供了深入的理解和开辟了新的途径.

关键词：二维过渡金属二硫族化合物材料散射型扫描近场光学显微镜激子极化子

Experimental Analysis and Damage modeling of High-Density Polyethylene under Fatigue Loading

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Acta mechanica Solida Sinica 2016年第2期29卷 133-144页

作者： A.Djebli m.Bendouba A.Aid A.talha N.Benseddiq m.Benguediab LPQ3m Faculte des sciences et des technologies Universite de Mustapha Stambouli Alegria LmL Departement de Genie mecanique Universite Lille-l France HEI Ecole des hautes etudes d'ingdnieurs France Faculte de Technologie Universite de Sidi Bel Abess Alegria

In this study,an experimental analysis for determining the fatigue strength of HDPE-100 under cyclic loading is *** curve of cumulative fatigue damage versus number of cycles（D-N） was deduced from stiffness *** on the three stage damage trend,the remaining fatigue life is numerically predicted by considering a double term power damage accumulation *** model is found to be accurate,both in modeling the rapid damage growth in the early life and near the end of the fatigue *** results illustrate that the proposed model is capable of accurately fitting several different sets of experimental data.

关键词： HDPE semi-crystalline damage accumulation stiffness degradation

Integration of 1D and 3D modeling schemes to establish the Farewell Formation as a self-sourced reservoir in Kupe Field,Taranaki Basin, New Zealand

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Frontiers of Earth Science 2021年第3期15卷 631-648页

作者： S.m.talha QADRI md Aminul ISLAm mohamad Ragab SHALABY Syed Haroon ALI Department of Earth Sciences University of Toronto Geosciences Program Faculty of Science Universiti Brunei Darussalam Geology Department Faculty of Science Tanta University Department of Earth Sciences University of Sargodha

Along with conventional methods, this paper proposed a method in which 1 D and 3 D models are integrated to identify the self-sourced reservoir potential of the Farewell Formation in the Kupe Gas Field within the Taranaki Basin, New Zealand. Source rock characteristics were evaluated at both field and basin scales by investigating source rock maturity, type of organic matter,and hydrocarbon generation potential by rock pyrolysis,using Rock-Eval 2 and 6. The 1 D thermal and burial history model established the rate of sedimentation and thermal history of the Kupe 4 well. Reservoir characterization at field-scale was determined by seismic interpretation, well log analysis, and 3 D structural and petrophysical models. The sediments of the Farewell Formation contain types II-III（oil/gas prone） and type III（gas prone） and have fair-to-excellent generation potential. The oxygen and hydrogen indices ranged from 3 to 476 mg CO2/g TOC and 26 to 356 mg HC/g TOC, respectively, whereas the thermal maturity determined by vitrinite reflectance values ranged between 0.3% and 0.72%, indicating that the Farewell Formation is in immature-to-mature hydrocarbon generation stage. Thus, Farewell Formation was verified to be a good source rock. Additionally, structural interpretations demonstrated the structural complexity of an extensional and contractional regime within the reservoir package. multiple faults indicated a good reservoir property there with a trapping mechanism as well as migration paths. A well-log-based petrophysical analysis established the presence of up to 70% hydrocarbon saturation within the pore spaces of Farewell *** 3 D models confirmed that the Farewell Formation has significant sand zones and hydrocarbon-saturated zones,thereby proving its very good reservoir characteristics. It has been proved that the 1 D and 3 D structural schemes,integrated with geological techniques, was vital in identifying the Kupe Field as a self-sourced reservoir.

关键词： self-sourced reservoir Kupe Field Farewell Formation Taranaki Basin

探测激子极化激元在超薄范德华微晶中的光传播（英文）

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Chinese Journal of Chemical Physics 2024年第1期 35-46页

作者： talha Ijaz 边琦曹琰丁皓璇陈晓瑞卢欢杨树邢雪婷方思敏刘孟源张鑫高健智潘明虎陕西师范大学物理学与信息技术学院华中科技大学物理学院洛阳师范大学物理与电子信息学院英国伯明翰大学物理与天文学院西安文理学院机械与材料工程学院陕西师范大学地理与旅游学院复旦大学信息科学与工程学院珠海复旦创新研究院西北大学物理学院

激子极化激元是一种准粒子,过渡金属二硫族化合物材料即使在室温下也能支持传播激子极化子,是非常好的纳米光子学研究平台.已有研究表明,通过散射型扫描近场光学显微镜可以对过渡金属二硫族化合物薄片中激子极化激元进行实空间探测,但波导厚度仅限于低至30 nm.本文采用三种不同波长的入射光(1550和1064 nm的近红外以及633 nm的可见光),通过基于原子力显微镜的散射型扫描近场光学显微镜测量,探测到moS2和WSe2薄片中激子极化子普通横电模式的纳米光学成像.在厚度分别低至～3 nm(相当于4原子层)和～8 nm(相当于12原子层)的超薄moS2和WSe2薄片上,可以清楚地观察到干涉条纹图案,大大打破了之前的测量厚度限制.当厚度接近几个原子层时,波矢量始终保持在1.6k0～1.7k0左右,而不是理论预言的1k0.这些模式的特性表明,体系是由近乎悬浮的过渡金属二硫族化合物薄片的三层对称波导构成,其对激子极性子的传播产生限域效应.研究结果为探索基于超薄过渡金属二硫族化合物材料的近红外区极化器件提供了深入的理解和开辟了新的途径.

关键词：二维过渡金属二硫族化合物材料散射型扫描近场光学显微镜激子极化子

Hemodynamic Response Detection Using Integrated EEG-fNIRS-VPA for BCI

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Computers, materials & Continua 2022年第1期70卷 535-555页

作者： Arshia Arif m.Jawad Khan Kashif Javed Hasan Sajid Saddaf Rubab Noman Naseer talha Irfan Khan National University of Sciences and Technology(NUST) IslamabadPakistan Intelligent Robotics Lab National Center of Artificial IntelligenceNational University of Sciences and Technology(NUST)IslamabadPakistan Department of mechatronics Engineering Air UniversityIslamabadPakistan Institute of Space Technology IslamabadPakistan

For BCI systems,it is important to have an accurate and less complex architecture to control a device with enhanced *** this paper,a novel methodology for more accurate detection of the hemodynamic response has been developed using a multimodal brain-computer interface(BCI).An integrated classifier has been developed for achieving better classification accuracy using two *** integrated EEG-fNIRS-based vector-phase analysis(VPA)has been *** open-source dataset collected at the TechnischeUniversit鋞Berlin,including simultaneous electroencephalography(EEG)and functional near-infrared spectroscopy(fNIRS)signals of 26 healthy participants during n-back tests,has been used for this *** and physiological noise removal has been done using preprocessing techniques followed by individually detecting activity in both *** resting state threshold circle,VPA has been used to detect a hemodynamic response in fNIRS signals,whereas phase plots for EEG signals have been constructed using Hilbert Transform to detect the activity in each *** threshold circles are drawn in the vector plane,where each circle is drawn after task completion in each trial of EEG ***,both processes are integrated into one vector-phase plot to get combined detection of hemodynamic response for *** of this study illustrate that the combined EEG-fNIRS VPA yields considerably higher average classification accuracy,that is 91.35%,as compared to other classifiers such as support vector machine(SVm),convolutional neural networks(CNN),deep neural networks(DNN)and VPA(with dual-threshold circles)with classification accuracies 82%,89%,87%and 86%*** of this research demonstrate that improved classification performance can be feasibly achieved using multimodal VPA for EEG-fNIRS hybrid data.

关键词： EEG-fNIRS hybrid BCI vector-phase analysis hemodynamic response detection

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

Ambient noise H/V spectral ratio in site effects estimation in Fateh jang area, Pakistan

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Earthquake Science 2015年第1期28卷 87-95页

作者： S.m.talha Qadri Bushra Nawaz S.H.Sajjad Riaz Ahmad Sheikh Department of Earth Sciences University of Sargodha College of Earth and Environmental Sciences University of the Punjab

Local geology or local site effect is a crucial component while conducting seismic risk assessment studies. Investigations made by utilization of ambient noise are an effective tool for local site estimation. The present study is conducted to perform site response analysis at 13 different sites within urban settlements of Fateh jang area （Pakistan）. The aim of this study was achieved by utilizing Nakamura method or H/V spectral ratio method. Some important local site parameters, e.g., the fundamental fre- quencies f0 of soft sediments, amplitudes A0 of corre- sponding H/V spectral ratios, and alluvium thicknesses over 13 sites within the study area, were measured and analyzed. The results show that the study area reflects low fundamental frequency fo. The fundamental frequencies of the sediments are highly variable and lie in a range of 0.6-13.0 Hz. Similarly, amplification factors at these sites are in the range of 2.0-4.0.

关键词： Local site effectspectral ratios Fundamentalfactor Alluvium thickness Ambient noise H/Vfrequency Amplification

multi-scale investigation of active failure for various modes of wall movement

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Frontiers of Structural and Civil Engineering 2021年第4期15卷 961-979页

作者： Ahmet talha GEZGIN Behzad SOLTANBEIGI Adlen ALTUNBAS Ozer CINICIOGLU Department of Civil Engineering Bogazici UniversityIstanbul34342Turkey Estimating&Engineering Department Van Oord Dredging and Marine ContractorsRotterdam3063 NHThe Netherlands Department of Civil Engineering Medipol UniversityIstanbul34810Turkey

Retained backfill response to wall movement depends on factors that range from boundary conditions to the geometrical characteristic of individual ***,mechanical understanding of the problem warrants multi-scale analyses that investigate reciprocal relationships between macro and micro ***,this study attempts a multi-scale examination of failure evolution in cohesionless ***,the transition of retained backfills from at-rest condition to the active state is modeled using the discrete element method(DEm).DEm allows conducting virtual experiments,with which the variation of particle and boundary properties is ***,various modes of wall movement(translation and rotation)toward the active state are modeled using two different backfills with distinct particle shapes(spherical and nonspherical)under varying *** each model,cumulative rotations of single particles are tracked,and the results are used to analyze the evolution of shear bands and their geometric ***,dependencies of lateral pressure coefficients and coordination numbers,as respective macro and micro behavior indicators,on particle shape,boundary conditions,and surcharge levels are ***,contact force networks are visually determined,and their influences on pressure distribution and deformation mechanisms are discussed with reference to the associated modes of wall movement and particle shapes.

关键词： discrete-element modelling granular materials retaining walls particle shape arching

A Quantum Spatial Graph Convolutional Network for Text Classification

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Computer Systems Science & Engineering 2021年第2期36卷 369-382页

作者： Syed mustajar Ahmad Shah Hongwei Ge Sami Ahmed Haider muhammad Irshad Sohail m.Noman Jehangir Arshad Asfandeyar Ahmad talha Younas College of Computer Science and Technology Dalian University of TechnologyDalian116024China Department of Computing University of WorcesterUK Department of Information Engineering Chang’an UniversityXi’an710054China Department of Cell Biology and Genetics Shantou University Medical CollegeShantou515041China Electrical and Computer Engineering Department COMSATS University IslamabadLahore CampusPakistan School of Information&Communication Engineering Dalian University of Technology Dalian116024China Electrical and Computer Engineering Department COMSATS University IslamabadSahiwal CampusPakistan

The data generated from non-Euclidean domains and its graphical representation(with complex-relationship object interdependence)applications has observed an exponential *** sophistication of graph data has posed consequential obstacles to the existing machine learning *** this study,we have considered a revamped version of a semi-supervised learning algorithm for graph-structured data to address the issue of expanding deep learning approaches to represent the graph ***,the quantum information theory has been applied through Graph Neural Networks(GNNs)to generate Riemannian metrics in closed-form of several graph *** further,to pre-process the adjacency matrix of graphs,a new formulation is established to incorporate high order *** proposed scheme has shown outstanding improvements to overcome the deficiencies in Graph Convolutional Network(GCN),particularly,the information loss and imprecise information representation with acceptable computational ***,the proposed Quantum Graph Convolutional Network(QGCN)has significantly strengthened the GCN on semi-supervised node classification *** parallel,it expands the generalization process with a significant difference by making small random perturbationsG of the graph during the training *** evaluation results are provided on three benchmark datasets,including Citeseer,Cora,and Pubmed,that distinctly delineate the superiority of the proposed model in terms of computational accuracy against state-of-the-art GCN and three other methods based on the same algorithms in the existing literature.

关键词： Text classiﬁcation deep learning graph convolutional networks semi-supervised learning GPUs performance improvements