目的 探讨妊娠期糖尿病高危孕妇孕前体质指数(body mass index, BMI)与孕早期糖脂代谢之间的关联。方法 收集2021年8月—2022年4月在北京市海淀区妇幼保健院营养科就诊的具有妊娠期糖尿病高危因素的孕早期孕妇298例,平均年龄(32.24±...目的 探讨妊娠期糖尿病高危孕妇孕前体质指数(body mass index, BMI)与孕早期糖脂代谢之间的关联。方法 收集2021年8月—2022年4月在北京市海淀区妇幼保健院营养科就诊的具有妊娠期糖尿病高危因素的孕早期孕妇298例,平均年龄(32.24±4.04)岁,66.11%为初产妇,采血时间平均为孕12.5周。按照孕前BMI将孕妇分为低体重组(15例)、正常体重组(181例)、超重/肥胖组(102例)。比较各组孕妇空腹血糖、空腹胰岛素、血脂四项、C反应蛋白、瘦素与脂联素水平。结果 (1)孕前超重/肥胖组孕妇孕早期甘油三酯浓度明显高于低体重组(1.51 mmol/L vs. 1.15 mmol/L)(P<0.01),高密度脂蛋白胆固醇水平低于低体重组(1.64 mmol/L vs. 1.95 mmol/L)(P<0.01)。(2)孕前低体重组妇女孕早期胰岛β细胞功能降低,HOMA-β指数为60.41%,超重/肥胖组妇女孕早期空腹胰岛素水平(7.86 vs. 3.42μU/mL)、胰岛素抵抗程度(1.75 vs. 0.74)高于低体重组(P<0.01)。(3)孕妇孕前BMI与孕早期甘油三酯、C反应蛋白、空腹胰岛素、胰岛素抵抗程度呈正相关(r=0.30、0.28、0.45、0.45,P<0.01),与孕早期高密度脂蛋白胆固醇水平呈负相关(r=-0.29,P<0.01)。结论 在具有妊娠期糖尿病高危因素的孕妇中,孕前超重肥胖与妊娠早期糖脂代谢水平存在关联。展开更多
In this paper, we give an up-to-date survey on physically-based fluid animation research. As one of the most popular approaches to simulate realistic fluid effects, physically-based fluid animation has spurred a large...In this paper, we give an up-to-date survey on physically-based fluid animation research. As one of the most popular approaches to simulate realistic fluid effects, physically-based fluid animation has spurred a large number of new results in recent years. We classify and discuss the existing methods within three categories： Lagrangian method, Eulerian method and Lattice-Boltzmann method. We then introduce techniques for seven different kinds of special fluid effects. Finally we review the latest hot research areas and point out some future research trends, including surface tracking, fluid control, hybrid method, model reduction, etc.展开更多
Analyzing a vehicle’s abnormal behavior in surveillance videos is a challenging field,mainly due to the wide variety of anomaly cases and the complexity of surveillance videos.In this study,a novel intelligent vehicl...Analyzing a vehicle’s abnormal behavior in surveillance videos is a challenging field,mainly due to the wide variety of anomaly cases and the complexity of surveillance videos.In this study,a novel intelligent vehicle behavior analysis framework based on a digital twin is proposed.First,detecting vehicles based on deep learning is implemented,and Kalman filtering and feature matching are used to track vehicles.Subsequently,the tracked vehicle is mapped to a digital-twin virtual scene developed in the Unity game engine,and each vehicle’s behavior is tested according to the customized detection conditions set up in the scene.The stored behavior data can be used to reconstruct the scene again in Unity for a secondary analysis.The experimental results using real videos from traffic cameras illustrate that the detection rate of the proposed framework is close to that of the state-of-the-art abnormal event detection systems.In addition,the implementation and analysis process show the usability,generalization,and effectiveness of the proposed framework.展开更多
Multi-object tracking is a vital problem as many applications require better tracking approaches.Although learning-based detectors are becoming extremely powerful,there are few tracking methods designed to work with t...Multi-object tracking is a vital problem as many applications require better tracking approaches.Although learning-based detectors are becoming extremely powerful,there are few tracking methods designed to work with them in real time.We explored an efficient flexible online vehicle tracking-by-detection framework suitable for real-virtual mapping systems,which combines a non-recursive temporal window search with delayed output and produces stable trajectories despite noisy detection responses.Its computation speed meets the real-time requirements,whereas its performance is comparable with that of state-of-the-art online trackers on the DETRAC dataset.The trajectories from our approach also contain the target class and color information important for virtual vehicle motion reconstruction.展开更多
文摘目的 探讨妊娠期糖尿病高危孕妇孕前体质指数(body mass index, BMI)与孕早期糖脂代谢之间的关联。方法 收集2021年8月—2022年4月在北京市海淀区妇幼保健院营养科就诊的具有妊娠期糖尿病高危因素的孕早期孕妇298例,平均年龄(32.24±4.04)岁,66.11%为初产妇,采血时间平均为孕12.5周。按照孕前BMI将孕妇分为低体重组(15例)、正常体重组(181例)、超重/肥胖组(102例)。比较各组孕妇空腹血糖、空腹胰岛素、血脂四项、C反应蛋白、瘦素与脂联素水平。结果 (1)孕前超重/肥胖组孕妇孕早期甘油三酯浓度明显高于低体重组(1.51 mmol/L vs. 1.15 mmol/L)(P<0.01),高密度脂蛋白胆固醇水平低于低体重组(1.64 mmol/L vs. 1.95 mmol/L)(P<0.01)。(2)孕前低体重组妇女孕早期胰岛β细胞功能降低,HOMA-β指数为60.41%,超重/肥胖组妇女孕早期空腹胰岛素水平(7.86 vs. 3.42μU/mL)、胰岛素抵抗程度(1.75 vs. 0.74)高于低体重组(P<0.01)。(3)孕妇孕前BMI与孕早期甘油三酯、C反应蛋白、空腹胰岛素、胰岛素抵抗程度呈正相关(r=0.30、0.28、0.45、0.45,P<0.01),与孕早期高密度脂蛋白胆固醇水平呈负相关(r=-0.29,P<0.01)。结论 在具有妊娠期糖尿病高危因素的孕妇中,孕前超重肥胖与妊娠早期糖脂代谢水平存在关联。
基金Supported partially by the National Basic Research Program of China (Grant No. 2009CB320804)the National High-Tech Research & Development Program of China (Grant No. 2006AA01Z307)
文摘In this paper, we give an up-to-date survey on physically-based fluid animation research. As one of the most popular approaches to simulate realistic fluid effects, physically-based fluid animation has spurred a large number of new results in recent years. We classify and discuss the existing methods within three categories： Lagrangian method, Eulerian method and Lattice-Boltzmann method. We then introduce techniques for seven different kinds of special fluid effects. Finally we review the latest hot research areas and point out some future research trends, including surface tracking, fluid control, hybrid method, model reduction, etc.
文摘Analyzing a vehicle’s abnormal behavior in surveillance videos is a challenging field,mainly due to the wide variety of anomaly cases and the complexity of surveillance videos.In this study,a novel intelligent vehicle behavior analysis framework based on a digital twin is proposed.First,detecting vehicles based on deep learning is implemented,and Kalman filtering and feature matching are used to track vehicles.Subsequently,the tracked vehicle is mapped to a digital-twin virtual scene developed in the Unity game engine,and each vehicle’s behavior is tested according to the customized detection conditions set up in the scene.The stored behavior data can be used to reconstruct the scene again in Unity for a secondary analysis.The experimental results using real videos from traffic cameras illustrate that the detection rate of the proposed framework is close to that of the state-of-the-art abnormal event detection systems.In addition,the implementation and analysis process show the usability,generalization,and effectiveness of the proposed framework.
文摘Multi-object tracking is a vital problem as many applications require better tracking approaches.Although learning-based detectors are becoming extremely powerful,there are few tracking methods designed to work with them in real time.We explored an efficient flexible online vehicle tracking-by-detection framework suitable for real-virtual mapping systems,which combines a non-recursive temporal window search with delayed output and produces stable trajectories despite noisy detection responses.Its computation speed meets the real-time requirements,whereas its performance is comparable with that of state-of-the-art online trackers on the DETRAC dataset.The trajectories from our approach also contain the target class and color information important for virtual vehicle motion reconstruction.
