含氟聚酰亚胺的热光性能

用5,5′-(六氟异丙基)-二-(2-氨基苯酚)(6FHP),4,4-′(六氟异丙基)-苯二酸酐(6FDA)和分散红19(DR19)合成了可制作光波导器件的含氟聚酰亚胺(PI-19)有机聚合物;采用示差扫描量热(DSC)、热失重分析(TGA)和近红外吸收光谱等方法对PI-19的热稳定性和光学性质进行了表征。示差扫描量热和热失重分析结果显示,PI-19的玻璃化转变温度(Tg)为256℃,在5%的热失重温度为380℃,表明具有非常好的热稳定性。近红外吸收光谱表明,材料在光通信波段(1.3μm和1.55μm)有2个较低吸收的“窗口”,可以用来制作低损耗的光通信器件、光开关等。制得的聚合物材料具有较大的热光系数,其值为-4.13×10-4~-3.72×10-4℃-1(650~1310 nm),对于研制具有低驱动功率的新型数字热光开关具有一定意义。     

Morphological and antigenic variations of human T cell leukemia virus type I particles in human lymphocytes

HTLV-I particles grown in 4 human lymphocyte cultures were observed by electron microscopy. Particles in all cell lines showed marked size and structural variations that were characteristic of each cell line. Profiles of size-distributions were found to be similar among virus particles of the same origin in different cell lines. Immunogold electron microscopy using monoclonal antibody to HTLV-I-p15, -p19, or -p24 revealed varying reactivities of individual particles. By double-labeling technique using antibody to HTLV-I-p19 or -p24, particles were found to be classifiable into 4 groups: p19+p24+, p19+p24-, p19-p24%, and p19-p24-. Each cell line showed the characteristic profile of distributions of virus particles of each group as observed at different in vitro passage levels. These antibodies reacted with certain structures in the extracellular space and in the cytoplasm. Results of this study demonstrate variations in morphology and antigenicity, as well as the morphogenesis of HTLV-I particles in different host cells.     

钕掺杂钡铁氧体聚苯胺复合材料的制备

采用溶胶凝胶法制备了BaNdxFe12-xO19,并用化学氧化法制备了聚苯胺-BaNdxFe12-xO19复合物。对制备的聚苯胺-BaNdxFe12-xO19复合物通过XRD、红外光谱和透射电镜等进行了表征,通过测定产物在磁性条件下的沉淀时间对其磁性进行了初步研究。结果显示:BaNdxFe12-xO19为磁铅石型铁氧体,钕掺杂钡铁氧体的磁性良好,聚苯胺/BaNdxFe12-xO19包裹良好,整个粒子呈核-壳结构,直径在55 nm左右。经复合后,产物沉淀时间增长,磁力降低,在微量掺杂范围内聚苯胺复合物的最佳掺杂比为0.2。     

注意力引导梯形金字塔融合网络识别新冠肺炎X射线影像

新型冠状病毒肺炎(corona virus disease 2019,COVID-19)严重影响人类社会和经济的发展,威胁人类的健康。如何更准确、快速地排查感染病毒的患者,使用卷积神经网络(convolutional neural network, CNN)的方法识别COVID-19胸部X射线影像,完成计算机自动辅助诊断。但是,由于识别精度不高,难以准确判断是否感染了COVID-19。为了提高网络模型对COVID-19胸部X射线影像的识别性能,首先提出注意力引导梯形金字塔融合网络(attention steered trapezoid pyramid fusion network, ASTPNet),该网络可以附加在不同的CNN上,有效地利用模型中深层与浅层网络的特点;其次提出注意力引导块(attention steered block, AS Block),通过通道和空间注意力,强调通道和空间中的有效语义信息,弱化无效的干扰信息,高效地聚合加权信息。最终实验结果表明：将ASTPNet附加在VGG16/19、ResNet34/50和ResNeXt上,识别精度有了显著提升;应用于自建的C...     

Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China

The development and uptake of the COVID-19 (coronavirus disease 2019) vaccine is a top priority in stifling the COVID-19 pandemic. How the public perceives the COVID-19 vaccine is directly associated with vaccine compliance and vaccination coverage. This study takes a cultural sensitivity perspective and adopts two well-known social media platforms in the United States (Twitter) and China (Weibo) to conduct a public perception comparison around the COVID-19 vaccine. By implementing semantic network analysis, results demonstrate that the two countries' social media users overlapped in themes concerning domestic vaccination policies, priority groups, challenges from COVID-19 variants, and the global pandemic situation. However, Twitter users were prone to disclose individual vaccination experiences, express anti-vaccine attitudes. In comparison, Weibo users manifested evident deference to authorities and exhibited more positive feelings toward the COVID-19 vaccine. Those disparities were explained by the cultural characteristics' differences between the two countries. The findings provide insights into comprehending public health issues in cross-cultural contexts and illustrate the potential of utilizing social media to conduct health informatics studies and investigate public perceptions during public health crisis time.     

钡铁氧体厚膜的制备工艺研究

采用丝网印刷方法来制备钡铁氧体(BaFe12O19)厚膜,研究了轧制时间和取向磁场强度对BaFe12O19厚膜样品的微观结构和磁性能的影响规律。结果表明,随着轧制时间的增加,所制BaFe12O19厚膜样品表面的气孔数量和大小都逐渐减小,且剩磁比和矫顽力均逐渐增加;随着取向磁场强度的增加,厚膜样品中晶粒的分布具有各向异性,且剩磁比和矫顽力均随取向磁场强度的增加而逐渐增加。     

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

The COVID-19 pandemic has caused major global changes both in the areas of healthcare and economics. This pandemic has led, mainly due to conditions related to confinement, to major changes in consumer habits and behaviors. Although there have been several studies on the analysis of customers’ satisfaction through survey-based and online customers’ reviews, the impact of COVID-19 on customers' satisfaction has not been investigated so far. It is important to investigate dimensions of satisfaction from the online customers’ reviews to reveal their preferences on the hotels' services during the COVID-19 outbreak. This study aims to reveal the travelers’ satisfaction in Malaysian hotels during the COVID-19 outbreak through online customers’ reviews. In addition, this study investigates whether service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. Accordingly, we develop a new method through machine learning approaches. The method is developed using text mining, clustering, and prediction learning techniques. We use Latent Dirichlet Allocation (LDA) for big data analysis to identify the voice-of-the-customer, Expectation-Maximization (EM) for clustering, and ANFIS for satisfaction level prediction. In addition, we use Higher-Order Singular Value Decomposition (HOSVD) for missing value imputation. The data was collected from TripAdvisor regarding the travelers’ concerns in the form of online reviews on the COVID-19 outbreak and numerical ratings on hotel services from different perspectives. The results from the analysis of online customers’ reviews revealed that service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. In addition, the results showed that although the customers are always seeking hotels with better performance, they are also concerned with the quality of related services in the COVID-19 outbreak.     

新冠肺炎疫情对我国数字经济投资的影响及对策

2020年春节期间,新型冠状病毒感染肺炎疫情迅速向全国蔓延,对经济发展、社会生产带来较大冲击。数字经济投资因其在短期内拉动经济增长效果明显,对国民经济发展发挥着关键作用。短期来看,疫情对数字经济整体投资规模、产业数字化转型投资、民间投资、外商直接投资等会造成一定冲击。长期来看,疫情对数字经济投资的冲击不具有可持续性,一旦疫情得到控制,数字经济投资规模将持续扩张,数字经济新模式新业态、产业数字化转型、数字化治理将成为投资的热点领域。为此,政府应充分发挥财政作用,帮助受疫情影响较大企业渡过难关,长远来看,要加强数字经济投资引导,激活数字经济民间投资,优化数字经济投资环境。     

基于泽尼克模式系数的自适应光学遗传算法

为了提高遗传算法(GA)控制的自适应光学(AO)系统的收敛性能,建立了一套新型的基于泽尼克(Zernike)模式系数的19单元自适应光学系统模型。在优化过程中,遗传算法不直接优化变形镜(DM)19个驱动器上的电压值,而是优化前10阶泽尼克模式系数。推导出19个电压值与前10阶泽尼克模式系数之间的关系矩阵,并进行了对比数值仿真。结果表明,该系统能够更好地校正固体激光器系统输出光束的波前像差。相对于直接优化变形镜电压值的无波前自适应光学系统,该自适应光学系统能够将遗传算法的收敛速度提高5倍以上。     

Blockchain Assisted Disease Identification of COVID-19 Patients with the Help of IDA-DNN Classifier

Wireless Personal Communications - Globally, millions of people were affected by the Corona-virus disease-2019 (COVID-19) causing loads of deaths. Most COVID-19 affected people recover in a few...     

采用音质特征和VLAD编码的新冠肺炎检测算法

2020年,世界卫生组织宣布COVID-19疫情为大流行病。为了实现COVID-19快速地、可靠地检测,本研究通过语音信号分析技术来寻找感染COVID-19的语音信号特征,利用咳嗽声片段和语音片段对是否感染COVID-19做出自动判断。在INTERSPEECH 2021 ComParE竞赛提供的相关数据集和baseline的基础上,本文首先利用语音端点检测技术对数据集进行增广,其次在特征集中加入语音质量特征,使相关baseline结果得到了提升,证明了语音质量特征在对COVID-19自动语音检测任务上的有效性。同时,引入局部聚合描述子向量对低级别特征进行编码,当字典大小较小时,有效地提升了系统的分类性能。最后,对多种算法得到的分类结果进行融合,进一步提升分类效果,最终在两个子任务中的验证集上UAR分别取得了73.9%和77.2%。      

对Zernike模式法重构19单元哈特曼测量波前的研究

通过对19单元哈特曼测量和模式法重构波前的过程进行数值模拟,研究了Zern ike模式法重构波前时耦合和混淆出现的原因、条件、程度和数学算法的表现。确定了在综合考虑最高可识别模式和计算稳定性同计算工具关系的情况下,选择最佳重构阶数的基本原则。同时对19单元哈特曼复原精度进行了评价,得出模式耦合是影响精度的主要因素,得到了模式法波前测量的适用条件,为利用哈特曼进行光束质量诊断提供了依据。     

铁电场效应晶体管

介绍了铁电场效应晶体管 (FFET)的基本结构、存储机制、制作方法 ,综述其结构设计的改进、铁电薄膜在 FFET中应用的进展情况 ,探讨围绕铁电薄膜材料、过渡层、结构设计、不同成膜方法及工艺对 FFET存储特性的影响 ,对 FFET的研究现状和存在的一些问题进行评述     

Digital capacity and employment outcomes: Microdata evidence from pre- and post-COVID-19 Europe

This paper examines the relationship between employment outcomes and broadband Internet access, education and digital skills using the pre- and post-COVID-19 survey waves of the Eurostat Community Statistics on Information Society from 2017, 2019, and 2021 in 27 European countries. Joint estimates of individuals’ employment status and skills employ external controls based on Eurostat and COVID-19 European Regional Tracker NUTS1-level regional statistics and Oxford COVID-19 Government Response Tracker information on governments’ containment and economic support measures. Broadband access, digital skills and educational attainment combine to raise employment outcomes, but COVID-19 has changed these relationships in distinct ways. It has increased employment benefits from formal education and roughly tripled the labor market advantages from having household members with tertiary education. The pandemic has increased the employment value of having at least some digital skills, while the relative benefits of more advanced digital skills shrank.     

Impact of Coronavirus Pandemic Crisis on Technologies and Cloud Computing Applications

In light of the coronavirus disease 2019 (COVID-19) outbreak caused by the novel coronavirus, companies and institutions have instructed their employees to work from home as a precautionary measure to reduce the risk of contagion. Employees, however, have been exposed to different security risks because of working from home. Moreover, the rapid global spread of COVID-19 has increased the volume of data generated from various sources. Working from home depends mainly on cloud computing (CC) applications that help employees to efficiently accomplish their tasks. The cloud computing environment (CCE) is an unsung hero in the COVID-19 pandemic crisis. It consists of the fast-paced practices for services that reflect the trend of rapidly deployable applications for maintaining data. Despite the increase in the use of CC applications, there is an ongoing research challenge in the domains of CCE concerning data, guaranteeing security, and the availability of CC applications. This paper, to the best of our knowledge, is the first paper that thoroughly explains the impact of the COVID-19 pandemic on CCE. Additionally, this paper also highlights the security risks of working from home during the COVID-19 pandemic.     

Graphene-Based Technologies for Tackling COVID-19 and Future Pandemics

The COVID-19 pandemic highlighted the need for rapid tools and technologies to combat highly infectious viruses. The excellent electrical, mechanical and other functional properties of graphene and graphene-like 2D materials (2DM) can be utilized to develop novel and innovative devices to tackle COVID-19 and future pandemics. Here, the authors outline how graphene and other 2DM-based technologies can be used for the detection, protection, and continuous monitoring of infectious diseases including COVID-19. The authors highlight the potential of 2DM-based biosensors in rapid testing and tracing of viruses to enable isolation of infected patients, and stop the spread of viruses. The possibilities of graphene-based wearable devices are discussed for continuous monitoring of COVID-19 symptoms. The authors also provide an overview of the personal protective equipment, and potential filtration mechanisms to separate, destroy or degrade highly infectious viruses, and the potential of graphene and other 2DM to increase their efficiency, and enhance functional and mechanical properties. Graphene and other 2DM could not only play a vital role for tackling the ongoing COVID-19 pandemic but also provide technology platforms and tools for the protection, detection and monitoring of future viral diseases.     

后疫情时代日本数字化转型政策的思考

回顾了2000年后日本政府在数字化转型方面的政策和制度,包括历时20年的数字政府实施计划,指出新冠肺炎疫情中身份卡和生活补助金发放面临的问题,暴露了日本过去数字化政策的短板和不足,这构成了新冠肺炎疫情后日本新政府推进数字化转型政策的起点;阐明了日本新冠肺炎疫情后数字化转型政策的三大方向:下调移动通信资费、实施5G推进计划和设置数字办公厅;最后,在总结新冠肺炎疫情后期日本政府出台的一系列移动通信产业改革举措的基础上,进一步思考了日本数字化转型政策的必要性和意义,并对隐藏在体制背后的日本移动通信产业存在的结构问题进行了探讨。     

Rain Attenuation Statistics from a 19 and 28 GHz COMSTAR Beacon Propagation Experiment: One Year Cumulative Distributions and Relationships Between the Two Frequencies

Cumulative attenuation distributions for one year and relationships between attenuations at 19 GHz and 28 GHz are presented for an earth-space propagation path terminating at Crawford Hill, New Jersey. An example from the distributions indicates that 20 dB attenuation was exceeded for 0.012% of the year at 19.04 GHz and for 0.06% at 28.56 GHz. For both frequencies the polarization was linear and oriented 21° from vertical at the receiver. When the attenuation at 19 GHz was less than 20 dB, the attenuation in dB at 28 GHz averaged 2.1 times that at 19 GHz. This ratio was lower at higher attenuations.     

结合SoftPool的VGG19与CapsNet相级联的表情识别模型研究

表情识别作为计算机视觉领域的研究热点,在情感识别、人机交互、智能安防等领域有着重要的应用.文章针对VGG19在训练人脸表情数据集时由于全连接层参数量过大而易过拟合的问题,利用胶囊网络CapsNet对VGG19的全连接层进行替换,以实现VGG19与CapsNet相级联,从而改善训练时过拟合的问题,同时使得级联后的模型在RAF-DB数据集上的精度提高了5.28％.针对VGG19特征提取网络的MaxPool易丢失人脸特征图信息的问题,利用SoftPool对MaxPool进行替换,从而在最大程度上保留了人脸的细粒度特征.实验结果表明,改进后的模型在RAF-DB数据集上取得了 84.21％的精度,在FER2013数据集上取得了 73.16％的精度,表情识别效果更优.     

Modeling predictors of COVID-19 health behaviour adoption,sustenance and discontinuation among social media users in Nigeria

The aim of this study was to suggest a model that explains the predictors of COVID-19 health behaviour adoption, sustenance and discontinuation among social media users in Nigeria. Survey research design was used for the study. The sample size was made of 600 social media users with questionnaire as the instrument for data collection. The structural equation modeling (SEM) was utilized to analyse the result for the study. It was found that six variables-risk vulnerability, risk severity, barriers to action, benefits of action, self-efficacy, and cue to behaviour-predict COVID-19 health behaviour adoption. Also, two variables-risk vulnerability and risk severity-predict COVID-19 health behaviour sustenance. Finally, two variables-behaviour fatigue and behaviour discomfort-predict COVID-19 health behaviour discontinuation. The result of the current study has provided information that could guide health experts in dealing with the issue of behaviour fatigue and behaviour discomfort, which have been identified as responsible for health behaviour discontinuation. In addition, a model for predicting health behaviour adoption, sustenance and discontinuation has been suggested.