Magnetic field gradient tensor measurement is an important technique to obtain position information of magnetic objects. When using magnetic field sensors to measure magnetic field gradient as the coefficients of tens...Magnetic field gradient tensor measurement is an important technique to obtain position information of magnetic objects. When using magnetic field sensors to measure magnetic field gradient as the coefficients of tensor, field differentiation is generally approximated by field difference. As a result, magnetic objects positioning by magnetic field gradient tensor measurement always involves an inherent error caused by sensor sizes, leading to a reduction in detectable distance and detectable angle. In this paper, the inherent positioning error caused by magnetic field gradient tensor measurement is calculated and corrected by iterations based on the systematic position error distribution patterns. The results show that, the detectable distance range and the angle range of an ac magnetic object（2.44 Am^2@1 kHz） can be increased from（0.45 m, 0.75 m）,（0？, 25？） to（0.30 m, 0.80 m）,（0？,80？）, respectively.展开更多
The quality of oranges is grounded on their appearance and diameter.Appearance refers to the skin’s smoothness and surface cleanliness;diameter refers to the transverse diameter size.They are visual attributes that v...The quality of oranges is grounded on their appearance and diameter.Appearance refers to the skin’s smoothness and surface cleanliness;diameter refers to the transverse diameter size.They are visual attributes that visual perception technologies can automatically identify.Nonetheless,the current orange quality assessment needs to address two issues:1)There are no image datasets for orange quality grading;2)It is challenging to effectively learn the fine-grained and distinct visual semantics of oranges from diverse angles.This study collected 12522 images from 2087 oranges for multi-grained grading tasks.In addition,it presented a visual learning graph convolution approach for multi-grained orange quality grading,including a backbone network and a graph convolutional network(GCN).The backbone network’s object detection,data augmentation,and feature extraction can remove extraneous visual information.GCN was utilized to learn the topological semantics of orange feature maps.Finally,evaluation results proved that the recognition accuracy of diameter size,appearance,and fine-grained orange quality were 99.50,97.27,and 97.99%,respectively,indicating that the proposed approach is superior to others.展开更多
In view of the problems of architectural eco-civilization in Ningbo City against the background of "sponge city", this paper proposed that development of roof greening in the city met the development concept...In view of the problems of architectural eco-civilization in Ningbo City against the background of "sponge city", this paper proposed that development of roof greening in the city met the development concepts of sponge city, summarized six basic countermeasures and four cooperation mechanisms for the developmental application of roof greening in Ningbo City by analyzing practical experience of roof greening construction in foreign countries.展开更多
目的 探索脑血管病患者主观性失眠与慢性期功能预后的关系。方法 本研究是对多中心、大型前瞻性研究--中国卒中后抑郁发生及其结局的前瞻性队列研究(prospective cohort study on the incidence and outcome of patients with post-stro...目的 探索脑血管病患者主观性失眠与慢性期功能预后的关系。方法 本研究是对多中心、大型前瞻性研究--中国卒中后抑郁发生及其结局的前瞻性队列研究(prospective cohort study on the incidence and outcome of patients with post-stroke depression in China,PRIOD)的事后分析。选取PRIOD中入组患者人数较多的15个中心,对入组的脑血管病患者进行发病5年后的电话随访。收集患者的一般资料、临床特点。根据《精神障碍诊断与统计手册》(第五版)中失眠的诊断标准编制调查问卷,收集失眠及相关睡眠问题,评估患者是否存在主观性失眠以及睡眠时间。采用mRS评估患者的功能预后。采用多因素logistic回归分析脑血管病患者主观性失眠与功能预后的关系。结果 本研究共纳入698例患者,其中319例(45.70%)为主观性失眠患者,仅17.55%(56/319)服用助眠药物。logistic回归分析显示,主观性失眠与脑血管病患者功能预后存在显著关联:校正协变量后,与无失眠患者相比,主观性失眠患者功能残疾风险较高(OR 1.64,95%CI 1.11~2.42,P=0.013);亚组分析显示,在基线为首次脑血管病发作患者中,与无失眠患者相比,主观性失眠患者功能残疾的风险较高(OR 1.74,95%CI 1.13~2.68,P=0.013)。结论 主观性失眠是导致脑血管病慢性期功能残疾的危险因素。展开更多
基金supported by the National Natural Science Foundation of China(61473023)
文摘Magnetic field gradient tensor measurement is an important technique to obtain position information of magnetic objects. When using magnetic field sensors to measure magnetic field gradient as the coefficients of tensor, field differentiation is generally approximated by field difference. As a result, magnetic objects positioning by magnetic field gradient tensor measurement always involves an inherent error caused by sensor sizes, leading to a reduction in detectable distance and detectable angle. In this paper, the inherent positioning error caused by magnetic field gradient tensor measurement is calculated and corrected by iterations based on the systematic position error distribution patterns. The results show that, the detectable distance range and the angle range of an ac magnetic object（2.44 Am^2@1 kHz） can be increased from（0.45 m, 0.75 m）,（0？, 25？） to（0.30 m, 0.80 m）,（0？,80？）, respectively.
基金supported by the National Natural Science Foundation of China(31901240,31971792)the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2016-AⅡ)the Central Public-interest Scientific Institution Basal Research Funds,China(Y2022QC17,CAAS-ZDRW202107).
文摘The quality of oranges is grounded on their appearance and diameter.Appearance refers to the skin’s smoothness and surface cleanliness;diameter refers to the transverse diameter size.They are visual attributes that visual perception technologies can automatically identify.Nonetheless,the current orange quality assessment needs to address two issues:1)There are no image datasets for orange quality grading;2)It is challenging to effectively learn the fine-grained and distinct visual semantics of oranges from diverse angles.This study collected 12522 images from 2087 oranges for multi-grained grading tasks.In addition,it presented a visual learning graph convolution approach for multi-grained orange quality grading,including a backbone network and a graph convolutional network(GCN).The backbone network’s object detection,data augmentation,and feature extraction can remove extraneous visual information.GCN was utilized to learn the topological semantics of orange feature maps.Finally,evaluation results proved that the recognition accuracy of diameter size,appearance,and fine-grained orange quality were 99.50,97.27,and 97.99%,respectively,indicating that the proposed approach is superior to others.
文摘In view of the problems of architectural eco-civilization in Ningbo City against the background of "sponge city", this paper proposed that development of roof greening in the city met the development concepts of sponge city, summarized six basic countermeasures and four cooperation mechanisms for the developmental application of roof greening in Ningbo City by analyzing practical experience of roof greening construction in foreign countries.
文摘目的 探索脑血管病患者主观性失眠与慢性期功能预后的关系。方法 本研究是对多中心、大型前瞻性研究--中国卒中后抑郁发生及其结局的前瞻性队列研究(prospective cohort study on the incidence and outcome of patients with post-stroke depression in China,PRIOD)的事后分析。选取PRIOD中入组患者人数较多的15个中心,对入组的脑血管病患者进行发病5年后的电话随访。收集患者的一般资料、临床特点。根据《精神障碍诊断与统计手册》(第五版)中失眠的诊断标准编制调查问卷,收集失眠及相关睡眠问题,评估患者是否存在主观性失眠以及睡眠时间。采用mRS评估患者的功能预后。采用多因素logistic回归分析脑血管病患者主观性失眠与功能预后的关系。结果 本研究共纳入698例患者,其中319例(45.70%)为主观性失眠患者,仅17.55%(56/319)服用助眠药物。logistic回归分析显示,主观性失眠与脑血管病患者功能预后存在显著关联:校正协变量后,与无失眠患者相比,主观性失眠患者功能残疾风险较高(OR 1.64,95%CI 1.11~2.42,P=0.013);亚组分析显示,在基线为首次脑血管病发作患者中,与无失眠患者相比,主观性失眠患者功能残疾的风险较高(OR 1.74,95%CI 1.13~2.68,P=0.013)。结论 主观性失眠是导致脑血管病慢性期功能残疾的危险因素。
