目的:分析儿童事件影响量表(Children’s revised impact of event scale,CRIES)、躁动及镇静评估量表(neonatal pain,agitation and sedation scale,N-PASS)用于先天性食道闭锁术后镇静镇痛效果评估中的价值。方法:选取2019年1月-2020...目的:分析儿童事件影响量表(Children’s revised impact of event scale,CRIES)、躁动及镇静评估量表(neonatal pain,agitation and sedation scale,N-PASS)用于先天性食道闭锁术后镇静镇痛效果评估中的价值。方法:选取2019年1月-2020年3月本院收治的18例先天性食道闭锁患儿为观察组,另选取2017年1月-2018年12月本院收治的37例先天性食道闭锁的患儿为对照组。术后,观察组根据CRIES、N-PASS评估量表评估结果进行镇静镇痛校准,对照组给予经验性镇痛镇静。比较两组不同时间点的吸氧浓度、平均气道压、治疗相关指标及并发症发生情况。结果:术后第96小时,观察组吸氧浓度低于对照组(P<0.05)。术后第24、48、96小时,观察组平均气道压低于对照组(P<0.05)。观察组上机时间、吸氧时间、住院时间、恢复出生体重时间及肠内喂养量达120 mL/(kg·d)的时间均短于对照组(P<0.05)。观察组并发症发生率低于对照组(P<0.05)。结论:CRIES、N-PASS评估量表对先天性食道闭锁术后镇静镇痛效果评估具有应用价值,根据其评估结果进行镇静镇痛校准可有效促进患儿恢复,缩短住院时间,减少并发症,值得推广。展开更多
Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning al...Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.展开更多
基金the National Natural Science Foundation of China under Grants 62176083,62176084,61877016,and 61976078the Key Research and Development Program of Anhui Province under Grant 202004d07020004the Natural Science Foundation of Anhui Province under Grant 2108085MF203.
文摘Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.
文摘大气温湿廓线是数值预报中最基本的气象参数，高光谱红外卫星可以观测到较高垂直分辨率的大气信息，为了准确获取廓线信息，利用搭载于美国对地观测卫星Suomi NPP（national polar-orbiting partner-ship）平台上的CrIS（cross-track infrared sounder）红外高光谱观测资料，讨论了通道选取方法，采用特征向量统计法反演法得到初始大气廓线，利用非线性牛顿迭代法进一步提高反演精度。将反演结果和全球数据同化系统GDAS（global data assimilation system ）模式分析数据以及配对的无线探空值进行比较，发现反演结果与真值趋势一致，较之初始廓线有显著提高，在100～700 hPa之间，温度廓线反演精度最高，均方差小于1 K ，在300～900 hPa之间，湿度廓线反演精度最高，均方差小于20％，与所选取通道的雅各比峰值区间一致。
