目的对胶乳增强免疫比浊神经元特异性烯醇化酶(neuron-specific enolase,NSE)试剂盒进行性能验证。方法按照CNAS-GL037:2019《临床化学定量检验程序性能验证指南》、WS/T492-2016《临床检测定量测定项目精密度与正确度性能验证》并结合...目的对胶乳增强免疫比浊神经元特异性烯醇化酶(neuron-specific enolase,NSE)试剂盒进行性能验证。方法按照CNAS-GL037:2019《临床化学定量检验程序性能验证指南》、WS/T492-2016《临床检测定量测定项目精密度与正确度性能验证》并结合试验工作,重新设计了检验方法,在贝克曼库尔特AU5800全自动生化分析对北京九强金斯尔NSE胶乳增强免疫比浊法试剂盒的正确度、精密度、线性范围、可报告范围和生物参考区间等性能进行验证和评估,并与对应罗氏电化学发光法试剂盒进行方法学比对。测试结果与厂家所给出的产品分析性能以及美国国家卫生委员会临床检测中心(National Center for Clinical Laboratories,NCCL)的相关指标进行了对比。结果5个水平的正确度偏倚分别为1.74%、-1.42%、-0.88%、-3.09%和-0.90%;2个水平的批内及批间精密度的变异系数(coefficient of variation,CV)分别为1.85%和0.88%(判断标准CV<7.5%),4.99%和3.34%(判断标准CV<10%);线性范围(3.5~148.1ng/mL)验证回归系数a值为0.9894,R2=0.9978;最大稀释倍数为8倍,临床可报告上限为1165.2ng/mL;厂家提供的生物参考区间为0~16.3ng/L,符合率R为100%,各性能均通过验证。此外,与罗氏电化学发光试剂盒进行方法学比对,其相关性分析结果为:两种方法的相关性(R2=0.989)、一致性(CCC=0.984)均较好,在临床判定效果上同Roche的电化学发光试剂盒相比,免疫增强比浊方法阳性符合率为95.74%,阴性符合率为96.23%,两者测定值接近,相关系数达0.9894。结论基于全自动生化分析平台测定的NSE胶乳增强免疫比浊试剂盒,各性能均可以较好地满足临床使用要求,且与电化学发光法检测结果一致性较好,有望进一步推进NSE国产体外诊断试剂盒的临床应用。展开更多
Scientific computing libraries,whether in-house or open-source,have witnessed enormous progress in both engineering and scientific research.Therefore,it is important to ensure that modifications to the source code,pro...Scientific computing libraries,whether in-house or open-source,have witnessed enormous progress in both engineering and scientific research.Therefore,it is important to ensure that modifications to the source code,prompted by bug fixing or new feature development,do not compromise the accuracy and functionality that have been already validated and verified.This paper introduces a method for establishing and implementing an automatic regression test environment,using the open-source multi-physics library SPHinXsys as an illustrative example.Initially,a reference database for each benchmark test is generated from observed data across multiple executions.This comprehensive database encapsulates the maximum variation range of metrics for different strategies,including the time-averaged,ensemble-averaged,and dynamic time warping methods.It accounts for uncertainties arising from parallel computing,particle relaxation,physical instabilities,and more.Subsequently,new results obtained after source code modifications undergo testing based on a curve-similarity comparison against the reference database.Whenever the source code is updated,the regression test is automatically executed for all test cases,providing a comprehensive assessment of the validity of the current results.This regression test environment has been successfully implemented in all dynamic test cases within SPHinXsys,including fluid dynamics,solid mechanics,fluid-structure interaction,thermal and mass diffusion,reaction-diffusion,and their multi-physics couplings,and demonstrates robust capabilities in testing different problems.It is noted that while the current test environment is built and implemented for a particular scientific computing library,its underlying principles are generic and can be easily adapted for use with other libraries,achieving equal effectiveness.展开更多
GaN MOSFET作为宽禁带的第三代半导体不仅开关速度快而且导通电阻小,把其用于变换器具有一定的高效性,而LLC谐振变换器作为高效的DC-DC变换器一直被广泛关注。现将GaN MOSFET用作全桥LLC谐振变换器的原边开关管进一步提升变换器的效率,...GaN MOSFET作为宽禁带的第三代半导体不仅开关速度快而且导通电阻小,把其用于变换器具有一定的高效性,而LLC谐振变换器作为高效的DC-DC变换器一直被广泛关注。现将GaN MOSFET用作全桥LLC谐振变换器的原边开关管进一步提升变换器的效率,并且通过PFM(变频)控制将变换器的工作频率划分为3个区域,进而找到效率最高的频率点,使变换器以此频率高效运行,文中对全桥LLC谐振变换器进行了参数设计,并基于Plecs和Matlab软件联合仿真验证参数和方案的可行性,搭建硬件平台得到谐振电流、输出电压的实验波形与仿真波形进行对比。实验结果表明,将GaN器件引入全桥LLC谐振变换器后能提高系统的频率及功率密度且最高效率可达96%。展开更多
文摘目的对胶乳增强免疫比浊神经元特异性烯醇化酶(neuron-specific enolase,NSE)试剂盒进行性能验证。方法按照CNAS-GL037:2019《临床化学定量检验程序性能验证指南》、WS/T492-2016《临床检测定量测定项目精密度与正确度性能验证》并结合试验工作,重新设计了检验方法,在贝克曼库尔特AU5800全自动生化分析对北京九强金斯尔NSE胶乳增强免疫比浊法试剂盒的正确度、精密度、线性范围、可报告范围和生物参考区间等性能进行验证和评估,并与对应罗氏电化学发光法试剂盒进行方法学比对。测试结果与厂家所给出的产品分析性能以及美国国家卫生委员会临床检测中心(National Center for Clinical Laboratories,NCCL)的相关指标进行了对比。结果5个水平的正确度偏倚分别为1.74%、-1.42%、-0.88%、-3.09%和-0.90%;2个水平的批内及批间精密度的变异系数(coefficient of variation,CV)分别为1.85%和0.88%(判断标准CV<7.5%),4.99%和3.34%(判断标准CV<10%);线性范围(3.5~148.1ng/mL)验证回归系数a值为0.9894,R2=0.9978;最大稀释倍数为8倍,临床可报告上限为1165.2ng/mL;厂家提供的生物参考区间为0~16.3ng/L,符合率R为100%,各性能均通过验证。此外,与罗氏电化学发光试剂盒进行方法学比对,其相关性分析结果为:两种方法的相关性(R2=0.989)、一致性(CCC=0.984)均较好,在临床判定效果上同Roche的电化学发光试剂盒相比,免疫增强比浊方法阳性符合率为95.74%,阴性符合率为96.23%,两者测定值接近,相关系数达0.9894。结论基于全自动生化分析平台测定的NSE胶乳增强免疫比浊试剂盒,各性能均可以较好地满足临床使用要求,且与电化学发光法检测结果一致性较好,有望进一步推进NSE国产体外诊断试剂盒的临床应用。
基金supported by the China Scholarship Council(Grant No.202006230071)the Deutsche Forschungsgemeinschaft(DFG)(Grant No.DFG HU1527/12-4).
文摘Scientific computing libraries,whether in-house or open-source,have witnessed enormous progress in both engineering and scientific research.Therefore,it is important to ensure that modifications to the source code,prompted by bug fixing or new feature development,do not compromise the accuracy and functionality that have been already validated and verified.This paper introduces a method for establishing and implementing an automatic regression test environment,using the open-source multi-physics library SPHinXsys as an illustrative example.Initially,a reference database for each benchmark test is generated from observed data across multiple executions.This comprehensive database encapsulates the maximum variation range of metrics for different strategies,including the time-averaged,ensemble-averaged,and dynamic time warping methods.It accounts for uncertainties arising from parallel computing,particle relaxation,physical instabilities,and more.Subsequently,new results obtained after source code modifications undergo testing based on a curve-similarity comparison against the reference database.Whenever the source code is updated,the regression test is automatically executed for all test cases,providing a comprehensive assessment of the validity of the current results.This regression test environment has been successfully implemented in all dynamic test cases within SPHinXsys,including fluid dynamics,solid mechanics,fluid-structure interaction,thermal and mass diffusion,reaction-diffusion,and their multi-physics couplings,and demonstrates robust capabilities in testing different problems.It is noted that while the current test environment is built and implemented for a particular scientific computing library,its underlying principles are generic and can be easily adapted for use with other libraries,achieving equal effectiveness.
