目的:评估飞秒激光辅助超声乳化联合Ahmed青光眼引流阀植入术治疗合并难治性青光眼的白内障的有效性和安全性。方法:回顾性病例对照研究。2019-10/2021-10入院合并难治性青光眼的白内障患者53例53眼,依据自愿选择分为飞秒激光辅助白内...目的:评估飞秒激光辅助超声乳化联合Ahmed青光眼引流阀植入术治疗合并难治性青光眼的白内障的有效性和安全性。方法:回顾性病例对照研究。2019-10/2021-10入院合并难治性青光眼的白内障患者53例53眼,依据自愿选择分为飞秒激光辅助白内障超声乳化(FLACS)组26例26眼和常规白内障超声乳化(CPCS)组27例27眼。两组分别行FLACS和CPCS联合Ahmed青光眼引流阀植入术。比较两组患者术中超声乳化能量释放量(CDE)、有效超声时间(EPT)的差异和术前与术后抗青光眼药物数量的变化,以及术后观察不同时期(1d,1wk,1、3mo)在提高最佳矫正视力(BCVA),降低眼压、角膜内皮细胞损伤程度和手术并发症及成功率状况。结果:FLACS组术中CDE和EPT明显低于CPCS组(t=8.50、5.16;P<0.01、=0.001)。两组术后抗青光眼药物较术前均明显减少(t=9.12、7.76;P=0.011、0.016),但两组间无差异(t=1.79,P=0.082)。两组术后BCVA均较术前改善,眼压均较术前降低(P<0.05)。FLACS组在术后早期(1d,1wk)BCVA的改善较CPCS组更显著(t=9.74、8.49;P=0.008、0.012),但在术后1、3mo的BCVA改善程度并无不同(t=0.62、0.44;P=1.415、2.021)。CPCS组在术后随访不同时期的角膜内皮细胞损伤较FLACS组更明显(P<0.05)。术后随访的不同时期FLACS组和CPCS组在控制眼压方面无差异(F_(组间)=0.64,P_(组间)=0.421)。FLACS组的手术并发症发生率27%(7/26)较CPCS组89%(24/27)低(χ^(2)=20.95,P<0.01),其中角膜水肿(8%vs 41%)、前囊撕裂(0 vs 11%)在FLACS组中明显低于CPCS组,后囊破裂(0 vs 7%)、玻璃体脱出(0 vs 4%)及人工晶状体偏位(0 vs 7%)也均发生在CPCS组。但两组的治疗总成功率相近(P=28.718)。结论:飞秒激光辅助超声乳化联合Ahmed青光眼引流阀植入术可充分发挥联合手术的精准微创可控优势,帮助合并难治性青光眼的白内障患者有效降低眼压及更早获得视力恢复。展开更多
Under the background of judicial responsibility system, making similar judgments according to similar cases is vital for front-line judges to solve complicated problems such as non-standard use of law and inconsistenc...Under the background of judicial responsibility system, making similar judgments according to similar cases is vital for front-line judges to solve complicated problems such as non-standard use of law and inconsistency of judicial ruling standards. In this paper, a method is proposed for judicial cases based on the LDA topic model. The case, penalty and legal provisions were set. Gibbs Sampling algorithm was employed to estimate the probability distribution of topics on the implicit topic set in a text and calculate the similarity between texts by cosine similarity. The quality of screening was used as a final evaluation indicator. The verification of massive experiments shows that the case screening method based on LDA and cosine similarity has a satisfactory effect.展开更多
针对自然结冰试飞空域确定时使用的结冰指数只能给出结冰概率和结冰等级的问题,提出一种新的方法。通过对美国联邦航空条例(FAR)25部附录C连续最大结冰条件采样,对采样点进行空气流场和水滴撞击特性求解,获得不同工况的水滴收集量;基于P...针对自然结冰试飞空域确定时使用的结冰指数只能给出结冰概率和结冰等级的问题,提出一种新的方法。通过对美国联邦航空条例(FAR)25部附录C连续最大结冰条件采样,对采样点进行空气流场和水滴撞击特性求解,获得不同工况的水滴收集量;基于POD(Proper Orthogonal Decomposition)和Kriging构建水滴收集量代理模型;使用WRF(Weather Research and Forecasting)对目标区域进行气象模拟,获得温度以及液态水含量分布;使用代理模型对目标区域内水滴收集量进行预测,以中度结冰强度对目标区域进行划分;最后,针对2种飞行速度对试飞空域的影响进行研究。结果表明:代理模型能够很好地预测温度、液态水含量、水滴中值体积直径、高度以及速度对水滴收集量的影响;WRF获得的目标区域的温度、液态水含量与观测值符合良好;基于代理模型可快速获得目标区域水滴收集量分布及随时间的变化,还可获得适合自然结冰试飞的目标区域及结冰速度;飞行速度的增加使得水滴收集量增加,进而引起试飞空域的变化。本文对结冰试飞空域确定具有一定参考意义。展开更多
Deciding the penalty of a law case has always been a complex process, which may involve with much coordination. Despite the judicial study based on the rules and conditions, artificial intelligence and machine learnin...Deciding the penalty of a law case has always been a complex process, which may involve with much coordination. Despite the judicial study based on the rules and conditions, artificial intelligence and machine learning has rarely been used to study the problem of penalty inferring, leaving the large amount of law cases as well as various factors among them untouched. This paper aims to incorporate the state-of-the-art artificial intelligence methods to exploit to what extent this problem can be alleviated. We first analyze 145 000 law cases and observe that there are two sorts of labels, temporal labels and spatial labels, which have unique characteristics. Temporal labels and spatial labels tend to converge towards the final penalty, on condition that the cases are of the same category. In light of this, we propose a latent-class probabilistic generative model, namely Penalty Topic Model （PTM）, to infer the topic of law cases, and the temporal and spatial patterns of topics embedded in the case judgment. Then, the learnt knowledge is utilized to automatically cluster all cases accordingly in a unified way. We conduct extensive experiments to evaluate the performance of the proposed PTM on a real large-scale dataset of law cases. The experimental results show the superiority of our proposed PTM.展开更多
文摘目的:评估飞秒激光辅助超声乳化联合Ahmed青光眼引流阀植入术治疗合并难治性青光眼的白内障的有效性和安全性。方法:回顾性病例对照研究。2019-10/2021-10入院合并难治性青光眼的白内障患者53例53眼,依据自愿选择分为飞秒激光辅助白内障超声乳化(FLACS)组26例26眼和常规白内障超声乳化(CPCS)组27例27眼。两组分别行FLACS和CPCS联合Ahmed青光眼引流阀植入术。比较两组患者术中超声乳化能量释放量(CDE)、有效超声时间(EPT)的差异和术前与术后抗青光眼药物数量的变化,以及术后观察不同时期(1d,1wk,1、3mo)在提高最佳矫正视力(BCVA),降低眼压、角膜内皮细胞损伤程度和手术并发症及成功率状况。结果:FLACS组术中CDE和EPT明显低于CPCS组(t=8.50、5.16;P<0.01、=0.001)。两组术后抗青光眼药物较术前均明显减少(t=9.12、7.76;P=0.011、0.016),但两组间无差异(t=1.79,P=0.082)。两组术后BCVA均较术前改善,眼压均较术前降低(P<0.05)。FLACS组在术后早期(1d,1wk)BCVA的改善较CPCS组更显著(t=9.74、8.49;P=0.008、0.012),但在术后1、3mo的BCVA改善程度并无不同(t=0.62、0.44;P=1.415、2.021)。CPCS组在术后随访不同时期的角膜内皮细胞损伤较FLACS组更明显(P<0.05)。术后随访的不同时期FLACS组和CPCS组在控制眼压方面无差异(F_(组间)=0.64,P_(组间)=0.421)。FLACS组的手术并发症发生率27%(7/26)较CPCS组89%(24/27)低(χ^(2)=20.95,P<0.01),其中角膜水肿(8%vs 41%)、前囊撕裂(0 vs 11%)在FLACS组中明显低于CPCS组,后囊破裂(0 vs 7%)、玻璃体脱出(0 vs 4%)及人工晶状体偏位(0 vs 7%)也均发生在CPCS组。但两组的治疗总成功率相近(P=28.718)。结论:飞秒激光辅助超声乳化联合Ahmed青光眼引流阀植入术可充分发挥联合手术的精准微创可控优势,帮助合并难治性青光眼的白内障患者有效降低眼压及更早获得视力恢复。
基金the National Key Research and Development Program of China (2016YFC0800805)the National Natural Science Foundation of China (61772014).
文摘Under the background of judicial responsibility system, making similar judgments according to similar cases is vital for front-line judges to solve complicated problems such as non-standard use of law and inconsistency of judicial ruling standards. In this paper, a method is proposed for judicial cases based on the LDA topic model. The case, penalty and legal provisions were set. Gibbs Sampling algorithm was employed to estimate the probability distribution of topics on the implicit topic set in a text and calculate the similarity between texts by cosine similarity. The quality of screening was used as a final evaluation indicator. The verification of massive experiments shows that the case screening method based on LDA and cosine similarity has a satisfactory effect.
文摘针对自然结冰试飞空域确定时使用的结冰指数只能给出结冰概率和结冰等级的问题,提出一种新的方法。通过对美国联邦航空条例(FAR)25部附录C连续最大结冰条件采样,对采样点进行空气流场和水滴撞击特性求解,获得不同工况的水滴收集量;基于POD(Proper Orthogonal Decomposition)和Kriging构建水滴收集量代理模型;使用WRF(Weather Research and Forecasting)对目标区域进行气象模拟,获得温度以及液态水含量分布;使用代理模型对目标区域内水滴收集量进行预测,以中度结冰强度对目标区域进行划分;最后,针对2种飞行速度对试飞空域的影响进行研究。结果表明:代理模型能够很好地预测温度、液态水含量、水滴中值体积直径、高度以及速度对水滴收集量的影响;WRF获得的目标区域的温度、液态水含量与观测值符合良好;基于代理模型可快速获得目标区域水滴收集量分布及随时间的变化,还可获得适合自然结冰试飞的目标区域及结冰速度;飞行速度的增加使得水滴收集量增加,进而引起试飞空域的变化。本文对结冰试飞空域确定具有一定参考意义。
基金This work is supported in part by the National Key Research and Development Program of China under Grant No. 2016YFC0800805 and the National Natural Science Foundation of China under Grant No. 61690201.
文摘Deciding the penalty of a law case has always been a complex process, which may involve with much coordination. Despite the judicial study based on the rules and conditions, artificial intelligence and machine learning has rarely been used to study the problem of penalty inferring, leaving the large amount of law cases as well as various factors among them untouched. This paper aims to incorporate the state-of-the-art artificial intelligence methods to exploit to what extent this problem can be alleviated. We first analyze 145 000 law cases and observe that there are two sorts of labels, temporal labels and spatial labels, which have unique characteristics. Temporal labels and spatial labels tend to converge towards the final penalty, on condition that the cases are of the same category. In light of this, we propose a latent-class probabilistic generative model, namely Penalty Topic Model （PTM）, to infer the topic of law cases, and the temporal and spatial patterns of topics embedded in the case judgment. Then, the learnt knowledge is utilized to automatically cluster all cases accordingly in a unified way. We conduct extensive experiments to evaluate the performance of the proposed PTM on a real large-scale dataset of law cases. The experimental results show the superiority of our proposed PTM.
