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| 1 | HepG2 cells support viral replication and gene expression of hepatitis C virus genotype 4 in vitro显示文摘瞄准:与丙肝的长期的复制建立一个房间文化系统病毒(HCV ) 染色体和病毒的抗原的表示在试管内。方法:HepG2 房间线被孵化与长期的丙肝从一个病人与浆液为它的危险性测试到 HCV。房间和上层清液在文化期间在各种各样的时间点被收获。文化上层清液为它感染天真的房间的能力被测试。存在减(反感觉) 在房间的核心和 E1 抗原的 RNA 海滨,和察觉被 RT-PCR 和免疫学的技术(流动血细胞计数和西方的污点) 分别地检验。结果:细胞内部的 HCV RNA 首先在 d 上被检测 3 在感染以后然后能一致地在至少三个月的一个时期上在房间和上层清液被检测。新鲜房间能从有教养的感染的房间感染上层清液。流动 cytometric 分析证明表面和在房子里使用的细胞内部的 HCV 抗原表示使 polyclonal 成为了抗体(反核心,和 anti-E1 ) 。西方的污点分析证明在分子量的产生免疫性的肽的簇的表示在一个月内在 31 和 45 kDa 之间延长了感染的房间的旧文化而这簇在 uninfected HepG2 房间是无法发现的。结论:HepG2 房间线产生 HCV 感染而且支持它的复制在试管内不仅。HCV 结构的蛋白质的表示能在感染的 HepG2 房间被检测。这些房间也能够流病毒的粒子进接着对 uninfected 房间变得传染的培养基。 | Mostafa K El-Awady Ashraf A Tabll Yasmine S El-Abd Mahmoud M Bahgat Hussein A Shoeb Samar S Youssef Noha G Bader El Din El-Rashdy M Redwan Maha El-Demellawy Moataza H Omran Wael T El-Garf Said A Goueli | 2006 | World Journal of Gastroenterology2006，12，30： | 2 |
| 2 | A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications显示文摘User’s data is considered as a vital asset of several organizations.Migrating data to the cloud computing is not an easy decision for any organization due to the privacy and security concerns.Service providers must ensure that both data and applications that will be stored on the cloud should be protected in a secure environment.The data stored on the public cloud will be vulnerable to outside and inside attacks.This paper provides interactive multi-layer authentication frameworks for securing user identities on the cloud.Different access control policies are applied for verifying users on the cloud.A security mechanism is applied to the cloud application that includes user registration,granting user privileges,and generating user authentication factor.An intrusion detection system is embedded to the security mechanism to detect malicious users.The multi factor authentication,intrusion detection,and access control techniques can be used for ensuring the identity of the user.Finally,encryption techniques are used for protecting the data from being disclosed.Experimental results are carried out to verify the accuracy and efficiency of the proposed frameworks and mechanism.The results recorded high detection rate with low false positive alarms. | Wael Said Elsayed Mostafa M.M.Hassan Ayman Mohamed Mostafa | 2022 | Computers, Materials & Continua2022，，5： | 0 |
| 3 | Space Division Multiple Access for Cellular V2X Communications显示文摘Vehicular communication is the backbone of future Intelligent Transportation Systems(ITS).It offers a network-based solution for vehicle safety,cooperative awareness,and traffic management applications.For safety applications,Basic Safety Messages(BSM)containing mobility information is shared by the vehicles in their neighborhood to continuously monitor other nearby vehicles and prepare a local traffic map.BSMs are shared using mode 4 of Cellular V2X(C-V2X)communications in which resources are allocated in an ad hoc manner.However,the strict packet transmission requirements of BSM and hidden node problem causes packet collisions in a vehicular network,thus reducing the reliability of safety applications.Moreover,as vehicles choose the transmission resources in a distributed manner in mode 4 of CV2X,the packet collision problem is further aggravated.This paper presents a novel solution in the form of a Space Division Multiple Access(SDMA)protocol that intelligently schedules BSM transmissions using vehicle position data to reduce concurrent transmissions from hidden node interferers.The proposed protocol works by dividing road segments into clusters and subclusters.Several sub-frames are allocated to a cluster and these sub-frames are reused after a certain distance.Within a cluster,sub-channels are allocated to sub-clusters.We implement the proposed SDMA protocol and evaluate its performance in a highway vehicular network.Simulation results show that the proposed SDMA protocol outperforms standard Sensing-Based Semi Persistent Scheduling(SB-SPS)in terms of safety range and packet delay. | Doaa Sami Khafaga Mohammad Zubair Khan Muhammad Awais Javed Amel Ali Alhussan Wael Said | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 4 | An Intelligent Secure Adversarial Examples Detection Scheme in Heterogeneous Complex Environments显示文摘Image-denoising techniques are widely used to defend against Adversarial Examples(AEs).However,denoising alone cannot completely eliminate adversarial perturbations.The remaining perturbations tend to amplify as they propagate through deeper layers of the network,leading to misclassifications.Moreover,image denoising compromises the classification accuracy of original examples.To address these challenges in AE defense through image denoising,this paper proposes a novel AE detection technique.The proposed technique combines multiple traditional image-denoising algorithms and Convolutional Neural Network(CNN)network structures.The used detector model integrates the classification results of different models as the input to the detector and calculates the final output of the detector based on a machine-learning voting algorithm.By analyzing the discrepancy between predictions made by the model on original examples and denoised examples,AEs are detected effectively.This technique reduces computational overhead without modifying the model structure or parameters,effectively avoiding the error amplification caused by denoising.The proposed approach demonstrates excellent detection performance against mainstream AE attacks.Experimental results show outstanding detection performance in well-known AE attacks,including Fast Gradient Sign Method(FGSM),Basic Iteration Method(BIM),DeepFool,and Carlini&Wagner(C&W),achieving a 94%success rate in FGSM detection,while only reducing the accuracy of clean examples by 4%. | Weizheng Wang Xiangqi Wang Xianmin Pan Xingxing Gong Jian Liang Pradip Kumar Sharma Osama Alfarraj Wael Said | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 5 | An E-Business Event Stream Mechanism for Improving User Tracing Processes显示文摘With the rapid development in business transactions,especially in recent years,it has become necessary to develop different mechanisms to trace business user records in web server log in an efficient way.Online business transactions have increased,especially when the user or customer cannot obtain the required service.For example,with the spread of the epidemic Coronavirus(COVID-19)throughout the world,there is a dire need to rely more on online business processes.In order to improve the efficiency and performance of E-business structure,a web server log must be well utilized to have the ability to trace and record infinite user transactions.This paper proposes an event stream mechanism based on formula patterns to enhance business processes and record all user activities in a structured log file.Each user activity is recorded with a set of tracing parameters that can predict the behavior of the user in business operations.The experimental results are conducted by applying clustering-based classification algorithms on two different datasets;namely,Online Shoppers Purchasing Intention and Instacart Market Basket Analysis.The clustering process is used to group related objects into the same cluster,then the classification process measures the predicted classes of clustered objects.The experimental results record provable accuracy in predicting user preferences on both datasets. | Ayman Mohamed Mostafa Saleh N.Almuayqil Wael Said | 2021 | Computers, Materials & Continua2021，，10： | 0 |
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