The test section’s Mach number in wind tunnel testing is a significant metric for evaluating system performance.The quality of the flow field in the wind tunnel is contingent upon the system's capacity to maintai...The test section’s Mach number in wind tunnel testing is a significant metric for evaluating system performance.The quality of the flow field in the wind tunnel is contingent upon the system's capacity to maintain stability across various working conditions.The process flow in wind tunnel testing is inherently complex,resulting in a system characterized by nonlinearity,time lag,and multiple working conditions.To implement the predictive control algorithm,a precise Mach number prediction model must be created.Therefore,this report studies the method for Mach number prediction modelling in wind tunnel flow fields with various working conditions.Firstly,this paper introduces a continuous transonic wind tunnel.The key physical quantities affecting the flow field of the wind tunnel are determined by analyzing its structure and blowing process.Secondly,considering the nonlinear and time-lag characteristics of the wind tunnel system,a CNN-LSTM model is employed to establish the Mach number prediction model by combining the 1D-CNN algorithm with the LSTM model,which has long and short-term memory functions.Then,the attention mechanism is incorporated into the CNN-LSTM prediction model to enable the model to focus more on data with greater information importance,thereby enhancing the model's training effectiveness.The application results ultimately demonstrate the efficacy of the proposed approach.展开更多
目的:探讨分析无创产前筛查(noninvasive prenatal screening,NIPS)技术在罕见常染色体三体(rare autosomal trisomies,RAT)及染色体拷贝数变异(copy number variation,CNV)筛查中的临床意义。方法:回顾性分析于2017年3月—2023年7月因N...目的:探讨分析无创产前筛查(noninvasive prenatal screening,NIPS)技术在罕见常染色体三体(rare autosomal trisomies,RAT)及染色体拷贝数变异(copy number variation,CNV)筛查中的临床意义。方法:回顾性分析于2017年3月—2023年7月因NIPS提示RAT和(或)CNV高风险在泉州市妇幼保健院·儿童医院产前诊断中心行羊水染色体核型分析及单核苷酸多态性微阵列(single nucleotide polymorphism array,SNParray)检测的108例患者情况。结果:83例NIPS提示RAT高风险者中产前诊断结果异常共15例,阳性预测值为18.07%,分别为1例致病性拷贝数变异(pathogenic copy number variants,pCNV)、9例临床意义不明确(variants of uncertain significance,VOUS)、4例杂合性丢失(loss of heterozygosity,LOH)及1例VOUS+LOH。25例NIPS提示CNV高风险者中产前诊断结果异常共16例,阳性预测值为64.00%,分别为11例pCNV、1例可能致病性拷贝数变异(likely pathogenic copy number variants,lpCNV)及4例VOUS。结论:NIPS技术对于RAT高风险阳性预测值不高,但提示不良妊娠结局风险增加;对于CNV高风险筛查有一定的应用价值。当NIPS提示RAT和染色体CNV高风险,应结合产前诊断结果及超声随访对胎儿预后进行评估,并加强妊娠期监测和管理。展开更多
基金funded by the National Natural Science Foundation of China(No.61503069)the Fundamental Research Funds for the Central Universities(N150404020).
文摘The test section’s Mach number in wind tunnel testing is a significant metric for evaluating system performance.The quality of the flow field in the wind tunnel is contingent upon the system's capacity to maintain stability across various working conditions.The process flow in wind tunnel testing is inherently complex,resulting in a system characterized by nonlinearity,time lag,and multiple working conditions.To implement the predictive control algorithm,a precise Mach number prediction model must be created.Therefore,this report studies the method for Mach number prediction modelling in wind tunnel flow fields with various working conditions.Firstly,this paper introduces a continuous transonic wind tunnel.The key physical quantities affecting the flow field of the wind tunnel are determined by analyzing its structure and blowing process.Secondly,considering the nonlinear and time-lag characteristics of the wind tunnel system,a CNN-LSTM model is employed to establish the Mach number prediction model by combining the 1D-CNN algorithm with the LSTM model,which has long and short-term memory functions.Then,the attention mechanism is incorporated into the CNN-LSTM prediction model to enable the model to focus more on data with greater information importance,thereby enhancing the model's training effectiveness.The application results ultimately demonstrate the efficacy of the proposed approach.
文摘目的:探讨分析无创产前筛查(noninvasive prenatal screening,NIPS)技术在罕见常染色体三体(rare autosomal trisomies,RAT)及染色体拷贝数变异(copy number variation,CNV)筛查中的临床意义。方法:回顾性分析于2017年3月—2023年7月因NIPS提示RAT和(或)CNV高风险在泉州市妇幼保健院·儿童医院产前诊断中心行羊水染色体核型分析及单核苷酸多态性微阵列(single nucleotide polymorphism array,SNParray)检测的108例患者情况。结果:83例NIPS提示RAT高风险者中产前诊断结果异常共15例,阳性预测值为18.07%,分别为1例致病性拷贝数变异(pathogenic copy number variants,pCNV)、9例临床意义不明确(variants of uncertain significance,VOUS)、4例杂合性丢失(loss of heterozygosity,LOH)及1例VOUS+LOH。25例NIPS提示CNV高风险者中产前诊断结果异常共16例,阳性预测值为64.00%,分别为11例pCNV、1例可能致病性拷贝数变异(likely pathogenic copy number variants,lpCNV)及4例VOUS。结论:NIPS技术对于RAT高风险阳性预测值不高,但提示不良妊娠结局风险增加;对于CNV高风险筛查有一定的应用价值。当NIPS提示RAT和染色体CNV高风险,应结合产前诊断结果及超声随访对胎儿预后进行评估,并加强妊娠期监测和管理。
