Realtime实时质控结合Westgard多规则理论

本文利用Realtime QC结合Westgard多规则分析血糖的模拟质控数据,并将其与Levey-Jennings质控图及Z-分数图进行比较分析,探讨Roche Realtime QC结合Westgard多规则在生化室内质控中的应用。Realtime QC正确显示了违反质控规则的质控点,可直观、实时分析临床生化定量项目的双水平质控数据。

豇豆花叶病毒和黑眼豇豆花叶病毒RT-Realtime PCR及IC-RT-Realtime PCR检测方法研究

建立了豇豆两种种传病毒豇豆花叶病毒(CPMV)和黑眼豇豆花叶病毒(BlCMV)RT-Realtime PCR检测方法以及双重RT-Realtime PCR检测方法。在此基础上,根据免疫学抗原抗体特异性吸附的特点,建立了CPMV和BlCMV免疫捕获反转录荧光定量(IC-RT-Realtime)PCR检测方法以及双重IC-RT-Realtime PCR检测方法。该单重及双重IC-RT-Real-time PCR检测方法具有灵敏度高、特异性强和稳定性好等优点,适用于豆类种苗中对CPMV和BlCMV的检测。

双引物探针RT-Realtime PCR检测马铃薯A病毒

马铃薯A病毒(Potato virus A,PVA)是我国重要的检疫性有害生物。本研究根据PVA中CP基因(coat protein gene)的保守序列,设计了两套PCR引物和TaqMan探针,建立了双引物探针RT-RealtimePCR检测PVA的方法。该方法采用实时荧光PCR技术,有效地提高了检测的灵敏度;同时两套引物探针相互验证,有效提高了结果的准确性。实验结果表明,本方法准确、灵敏、简便、快速,检出低限可达0.5fg/μL植物总RNA。

使用IBM Rational Test RealTime进行嵌入式软件测试

介绍IBM Rational Test RealTime测试工具,并以单元测试为重点说明其在嵌入式软件测试中的应用。

基于simulink-realtime的数控系统仿真与实验平台研究

提出一种采用simulink-realtime构建数控系统仿真实验平台的方法。首先,介绍了simulink-realtime的硬件部分结构及其软件部分原理与设置。然后,详述了基于simulink-realtime应用程序的开发流程,并以一个单轴PID控制器的程序开发为例。最后,以对轮廓误差控制中典型的交叉耦合控制器研究证明了所搭建的仿真实验平台对于研究数控技术的实用性。

半巢式RT-Realtime PCR检测南芥菜花叶病毒

根据南芥菜花叶病毒(Ar MV)外壳蛋白(CP)基因的保守序列,设计合成了3条巢式PCR引物和1条Taq MAN荧光探针,建立了半巢式RT-Realtime PCR检测Ar MV的新方法。该方法有机地结合了巢式PCR和Taq MAN探针检测技术。第二步半巢式-RT-Realtime PCR既是对第一步信号的进一步放大,也是对第一步PCR产物的确认,因此,检测的准确性、灵敏度比巢式PCR、Realtime PCR等方法高。结果表明:该方法检测灵敏度可达0.06 fg/μL植物总RNA。

半巢式RT-Realtime PCR检测番茄丛矮病毒

番茄丛矮病毒(ToBSV)是我国进境植物检疫对象,也是进境种子苗木等必检项目。该病毒能侵染番茄、曼陀罗、葡萄、豇豆等20余科120余种植物。该研究根据ToBSV全基因组中p33蛋白基因,设计引物和Taq Man探针,建立了半巢式实时PCR检测ToBSV的新方法。该研究巧妙地融合了巢式PCR和Taq Man探针技术,第二步半巢式-RT-Realtime PCR既进一步放大了第一步检测信号,也是对第一步PCR产物的确认,与单一的巢式PCR或Realtime PCR等方法相比其检测的准确性、灵敏度更高。该方法检测灵敏度可达50 fg/μL植物总RNA。

Comparison of Two Molecular Diagnostic Tests for COVID-19: Abbott RealTime SARS-CoV-2 and Allplex™2019-nCoV, in the Epidemic Context in Senegal

Background: The persistence of the rapid spread of the COVID-19 pandemic is linked to the appearance of several variants of SARS-CoV2 with an impact on biological diagnosis, treatment and vaccination. The United States Food and Drug Administration (FDA) has granted several SARS-CoV-2 detection tests Emergency Use Authorization (EUA) for diagnosis and better epidemiological surveillance. Thus, multiple RT-PCR tests have been developed and brought to market in order to meet the urgent need for the diagnosis of COVID-19. However, comparative data between these tests in clinical laboratories are scarcely available to assess their performance. Objective: To compare two molecular methods for detecting SARS-CoV-2: the RT-PCR, Allplex™2019-nCoV tests on CFX96 Bio-Rad and the Abbott m2000sp/rt RealTime SARS-CoV-2. Materials and Methods: Nasopharyngeal and oropharyngeal swabs were taken from patients to diagnose SARS-CoV-2 infection. For each sample, we searched for the virus with two different RT-PCR tests: 1) first on Abbott m2000 SARS-CoV-2 targeting the N and RdRp genes, 2) then on Allplex™2019-nCoV Assay looking for the E, N and RdRp genes. Results: Percentages of the agreement were calculated. A total of 100 samples that tested negative and 90 positives on Abbott m2000 SARS-CoV-2 were retested on Allplex™2019-nCoV. Overall agreement was 74.74% on all samples. The specific agreement was 84% and 64.4% respectively for negative and positive samples with the RealTime SARS-CoV-2 test. A positive correlation (r2 = 0.63;p Conclusion: Our results showed good overall agreement between RT-PCR, Allplex™2019-nCoV and Abbott RealTime SARS-CoV-2 tests in the diagnosis of COVID-19. As the concordance is low for small viremias, the RT-PCR Allplex™2019-nCoV Assay would be better indicated during the acute and symptomatic phase of the disease.

Realtime Worlds——镇压

Realtime Worlds是一家总部设在苏格兰的独立游戏开发商。在轰轰烈烈的游戏开发过程中，公司在Dave-Jones的领导下，从一个DMA设计小组发展成为拥有170名员工和三万平方英尺办公面积并荣获过游戏大奖的工作室。除了位于在苏格兰中心邓迪市的主工作室，公司还有两个分别设在韩国首尔和美国科罗拉多州的工作室。

巢式-多重RT-Realtime PCR检测马铃薯黑环斑病毒的研究

马铃薯黑环斑病毒(Potato black ringspot virus,PBRSV)是马铃薯重要病毒病害之一。本研究根据PBRSV基因组中RNA依赖的RNA聚合酶(RDRP)保守序列,设计合成了两对巢式PCR引物和1条Taq-MAN荧光探针,建立了巢式-多重RT-Realtime PCR检测PBRSV的新方法。该方法采用E.Z.N.ATM试剂盒快速提取植物总RNA,并有机地结合了巢式PCR、多重PCR和探针检测技术。实验结果表明,该方法检测灵敏度可达450fg/μL植物总RNA。利用4对引物和1条TaqMAN探针对PCR阳性产物进行确认,本方法检测的准确性、灵敏度比巢式PCR、单重Realtime PCR等方法高。

RealTime:真正的协作

RealTime Notes Release 2是Lotus的产品。它是Intel的ProShare软件和Lotus Notes相结合的产物,能让你与其它用户同时创建并编辑基于Microsoft Windows的任何文档。如果你想与更多的人同时工作,那最新版本的RealTimeNoes还支持PorShare的多用户会议和视频会议(可选)。不过如果实现了RealTime Notes的方方面面——这意味着要投资购买Intel的ProShare Conferencing System 200——将会带来很大的变化。

巢式-多重RT-Realtime PCR检测马铃薯Y病毒脉坏死株系的方法

马铃薯Y病毒脉坏死株系(Potato virus Yvein necrosis strain,PVYn)是马铃薯中一个非常重要的病毒病害。本研究根据PVYn基因组中RNA依赖的RNA聚合酶(RNA dependentRNA polymerase,RDRP)基因序列保守区域,设计合成了两对巢式PCR引物和一条TaqMAN荧光探针,建立了巢式-多重RT-Real-time PCR检测PVYn的新方法。该方法采用E.Z.N.ATM快速提取植物总RNA,并有机地结合了巢式PCR、多重PCR和探针检测技术。实验结果表明,本方法检测的准确性、灵敏度比巢式PCR、单重Real time PCR等方法高。该方法检测灵敏度可达3 fg/μL植物总RNA。利用四对引物和一条TaqMAN探针对PCR阳性产物进行确认,检测的准确性比其它方法高。

达索系统收购Realtime Technology AG(RTT)公司

近日，达索系统正式与3D可视化软件Realtime Technology AG（RTT）公司签署收购协议。达索系统将持有RTT公司高达84％的股份，收购涉及RTT的软件业务，包括业界知名的DeltaGen、PictureBook、POS Configurator解决方案、营销咨询服务及其控股子公司Bunkspeed功能强大的直觉式渲染软件等。在如今的体验经济时代，

Partial Iterative Decode of Turbo Codes for On-Board Processing Satellite Platform

There is a contradiction between high processing complexity and limited processing resources when turbo codes are used on the on-board processing(OBP)satellite platform.To solve this problem,this paper proposes a partial iterative decode method for on-board application,in which satellite only carries out limited number of iteration according to the on-board processing resource limitation and the throughput capacity requirements.In this method,the soft information of parity bits,which is not obtained individually in conventional turbo decoder,is encoded and forwarded along with those of information bits.To save downlink transmit power,the soft information is limited and normalized before forwarding.The iteration number and limiter parameters are optimized with the help of EXIT chart and numerical analysis,respectively.Simulation results show that the proposed method can effectively decrease the complexity of onboard processing while achieve most of the decoding gain..

Role of on-board discharge in shock wave drag reduction and plasma cloaking

In the present paper, a physical model is proposed for reducing the problem of the drag reduction of an attached bow shock around the nose of a high-speed vehicle with on-board discharge, to the problem of a balance between the magnetic pressure and gas pressure of plane shock of a partially ionized gas consisting of the environmental gas around the nose of the vehicle and the on-board discharge-produced plasma. The relation between the shock strength and the discharge-induced magnetic pressure is studied by means of a set of one-fluid, hydromagnetic equations reformed for the present purpose, where the discharge-induced magnetic field consists of the electron current （produced by the discharge）-induced magnetic field and the partially ionized gas flow-induced one. A formula for the relation between the above parameters is derived. It shows that the discharge-induced magnetic pressure can minimize the shock strength, successfully explaining the two recent experimental observations on attached bow shock mitigation and elimination in a supersonic flow during on-board discharge [Phys. Plasmas 9 （2002） 721 and Phys. Plasmas 7 （2000） 1345]. In addition, the formula implies that the shock elimination leaves room for a layer of higher-density plasma rampart moving around the nose of the vehicle, being favourable to the plasma radar cloaking of the vehicle. The reason for it is expounded.

Optimal energy saving in DC railway system withon-board energy storage system by using peak demand cutting strategy

A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system(OBESS) by using peak demand cutting strategy under different trip time controls.The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced.Bangkok Mass Transit System(BTS)-Silom Line in Thailand is used to test and verify the proposed strategy.The results show that substation peak power is reduced by63.49% and net energy consumption is reduced by 15.56%using coasting and deceleration trip time control.

Radiation Tolerant Viterbi Decoders for On-Board Processing(OBP) in Satellite Communications

Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,among which single event upsets(SEUs)are important as they can lead to data corruption and system failure.This paper studies the fault tolerance capability of a SRAM-FPGA implemented Viterbi decoder to SEUs on the user memory.Analysis and fault injection experiments are conducted to verify that over 97%of the SEUs on user memory would not lead to output errors.To achieve a better reliability,selective protection schemes are then proposed to further improve the reliability of the decoder to SEUs on user memory with very small overhead.Although the results are obtained for a specific FPGA implementation,the developed reliability estimation model and the general conclusions still hold for other implementations.

An Interconnected Multi-Plane Multi-Stage Fault-Tolerant On-Board Switching Fabric

The harsh space radiation environment compromises the reliability of an on-board switching fabric by leading to cross-point and switching element(SE)faults.Different from traditional faulttolerant switching fabrics only taking crosspoint faults into account,a novel Input and Output Parallel Clos network,referred to as the(p_1,p_2)-IOPClos,is proposed to tolerate both cross-point and SE faults.In the(p_1,p_2)-IOPClos,there are p_1 and p_2 expanded parallel switching planes in the input and output stages,respectively.The multiple input/output switching planes are interconnected through the middle stage to provide multiple paths in each stage by which the network throughput can be increased remarkably.Furthermore,the network reliability of the(p_1,p_2)-IOPClos under the above both kinds of faults is analyzed.The corresponding implementation cost is also presented along with the network size.Both theoretical analysis and numerical results indicate that the(p_1,p_2)-IOPClos outperforms traditional Clos-type networks at reliability,while has less implementation cost than the multi-plane Clos network.

Stream-computing of High Accuracy On-board Real-time Cloud Detection for High Resolution Optical Satellite Imagery

This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition ability is growing continuously and the volume of raw data is increasing explosively. Meanwhile, because of the higher requirement of data accuracy, the computation load is also becoming heavier. This situation makes time efficiency extremely important. Moreover, the cloud cover rate of optical satellite imagery is up to approximately 50%, which is seriously restricting the applications of on-board intelligent photogrammetry services. To meet the on-board cloud detection requirements and offer valid input data to subsequent processing, this paper presents a stream-computing of high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board. Without external memory, the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in, processing, stream-out” real-time stream computing. In experiments, images of GF-2 satellite are used to validate the accuracy and performance of this approach, and the experimental results show that this solution could not only bring up cloud detection accuracy, but also match the on-board real-time processing requirements.

Fault diagnosis for on-board equipment of train control system based on CNN and PSO-SVM hybrid model

Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.