An ultra-narrow spectroscopy of clock transition with high signal-to-noise ratio is crucial for a high-performance atomic optical clock. We present a detailed study about how to obtain a Hertz-level clock transition s...An ultra-narrow spectroscopy of clock transition with high signal-to-noise ratio is crucial for a high-performance atomic optical clock. We present a detailed study about how to obtain a Hertz-level clock transition spectrum of 171 Yb atoms. About 4 × 10^4 atoms are loaded into a one-dimensional optical lattice with a magic wavelength of 759 nm, and a long lifetime of 3 s is realized with the lattice power of I W. Through normalized shelving detection and spin polarization, 171 Yb clock spectroscopy with a fourier-limited linewidth of 5.9 Hz is obtained. Our work represents a key step toward an ytterbium optical clock with high frequency stability.展开更多
目的探讨子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素,并构建预测模型。方法选取2020年10月至2022年5月某医院收治的180例子宫肌瘤患者作为研究对象,根据患者术后是否出现下肢深静脉血栓分为发生组(38例)和未发生组(142例)。采...目的探讨子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素,并构建预测模型。方法选取2020年10月至2022年5月某医院收治的180例子宫肌瘤患者作为研究对象,根据患者术后是否出现下肢深静脉血栓分为发生组(38例)和未发生组(142例)。采用Logistic回归分析影响子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素;采用内部数据验证Nomogram模型临床效能。结果180例子宫肌瘤患者中有38例发生下肢深静脉血栓,发生率为21.11%;年龄>50岁(OR=1.847)、手术时间>60 min(OR=1.623)、术中气腹压>15 mm Hg(OR=1.518)、术后卧床时间>5 d(OR=2.208)、术后常规护理(OR=1.791)是子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素(P<0.05);模型预测患者术后出现下肢深静脉血栓的风险阈值>0.07。结论年龄、手术时间、术中气腹压、术后卧床时间、术后护理方式是影响子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素,且基于此构建的模型有较好的预测价值。展开更多
Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This pa...Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This paper proposes a novel fault line detection method using waveform fusion and one-dimensional convolutional neural networks(1-D CNN).After an SLG fault occurs,the first-half waves of zero-sequence currents are collected and superimposed with each other to achieve waveform fusion.The compelling feature of fused waveforms is extracted by 1-D CNN to determine whether the fused waveform source contains the fault line.Then,the 1-D CNN output is used to update the value of the counter in order to identify the fault line.Given the lack of fault data in existing distribution systems,the proposed method only needs a small quantity of data for model training and fault line detection.In addition,the proposed method owns fault-tolerant performance.Even if a few samples are misjudged,the fault line can still be detected correctly based on the full output results of 1-D CNN.Experimental results verified that the proposed method can work effectively under various fault conditions.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 61227805,91536104 and 11574352
文摘An ultra-narrow spectroscopy of clock transition with high signal-to-noise ratio is crucial for a high-performance atomic optical clock. We present a detailed study about how to obtain a Hertz-level clock transition spectrum of 171 Yb atoms. About 4 × 10^4 atoms are loaded into a one-dimensional optical lattice with a magic wavelength of 759 nm, and a long lifetime of 3 s is realized with the lattice power of I W. Through normalized shelving detection and spin polarization, 171 Yb clock spectroscopy with a fourier-limited linewidth of 5.9 Hz is obtained. Our work represents a key step toward an ytterbium optical clock with high frequency stability.
文摘目的探讨子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素,并构建预测模型。方法选取2020年10月至2022年5月某医院收治的180例子宫肌瘤患者作为研究对象,根据患者术后是否出现下肢深静脉血栓分为发生组(38例)和未发生组(142例)。采用Logistic回归分析影响子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素;采用内部数据验证Nomogram模型临床效能。结果180例子宫肌瘤患者中有38例发生下肢深静脉血栓,发生率为21.11%;年龄>50岁(OR=1.847)、手术时间>60 min(OR=1.623)、术中气腹压>15 mm Hg(OR=1.518)、术后卧床时间>5 d(OR=2.208)、术后常规护理(OR=1.791)是子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素(P<0.05);模型预测患者术后出现下肢深静脉血栓的风险阈值>0.07。结论年龄、手术时间、术中气腹压、术后卧床时间、术后护理方式是影响子宫肌瘤患者腹腔镜术后形成下肢深静脉血栓的危险因素,且基于此构建的模型有较好的预测价值。
基金supported by the National Natural Science Foundation of China through the Project of Research of Flexible and Adaptive Arc-Suppression Method for Single-Phase Grounding Fault in Distribution Networks(No.51677030).
文摘Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This paper proposes a novel fault line detection method using waveform fusion and one-dimensional convolutional neural networks(1-D CNN).After an SLG fault occurs,the first-half waves of zero-sequence currents are collected and superimposed with each other to achieve waveform fusion.The compelling feature of fused waveforms is extracted by 1-D CNN to determine whether the fused waveform source contains the fault line.Then,the 1-D CNN output is used to update the value of the counter in order to identify the fault line.Given the lack of fault data in existing distribution systems,the proposed method only needs a small quantity of data for model training and fault line detection.In addition,the proposed method owns fault-tolerant performance.Even if a few samples are misjudged,the fault line can still be detected correctly based on the full output results of 1-D CNN.Experimental results verified that the proposed method can work effectively under various fault conditions.
