To expose the statistical properties of the degenerated spectrum, with the aid of the random matrix theory, a possible form of the NNS distribution function of the degenerate spectrum was proposed by providing a solut...To expose the statistical properties of the degenerated spectrum, with the aid of the random matrix theory, a possible form of the NNS distribution function of the degenerate spectrum was proposed by providing a solution in terms of the same-degeneracy case. The results indicate that the target spectrum is transformed into two sub-spectra： a random one and a regular one, and that the repulsion level of the regular spectrum is also decreased.展开更多
Based on the concept of the energy level repulsion, a potential function followed by the energy level particles is suggested. By regarding the energy level fluctuation spectrum as a dynamic system which consists of th...Based on the concept of the energy level repulsion, a potential function followed by the energy level particles is suggested. By regarding the energy level fluctuation spectrum as a dynamic system which consists of the pairs of energy level particles behaving as the generalized harmonic oscillator, a generalized Schrdinger equation valid for the nearest neighbor space (NNS) distribution of the levels is established. It turns out that the different kinds of NNS distributions found so far are the solutions of this equation: Both the Poisson type and Wigner type are its eigen solutions whereas the Gaussian unitary ensemble (GUE) type and the Brody type of NNS distribution are its composite solutions. Furthermore, the influences of the small perturbation on the NNS distribution are analyzed.展开更多
Ironmaking process(IP)is indispensable to modern iron and steel industry,where real-time monitoring is crucial for achieving high molten iron quality(MIQ)with low energy consumption.While neural network-based models s...Ironmaking process(IP)is indispensable to modern iron and steel industry,where real-time monitoring is crucial for achieving high molten iron quality(MIQ)with low energy consumption.While neural network-based models show some promising results,they are generally limited by non-negligible drawbacks such as interpretability issues of feature learning.To address these issues,we propose a novel concept based on the shallow-to-deep correlation network representation regression(Sh-to-De CNRR).Our approach,shallow correlation network representation regression(ShCNRR),combines neural network and canonical correlation analysis thoughts to generate explainable features via shallow correlation network representation(CNR).A twin inverse network is then derived to obtain the explicit model output,leveraging the shallow CNR.To capture deeper nonlinear information,we extend ShCNRR into a hierarchical deep correlation network representation regression(DeCNRR)model that features stacked neural networks,enabling us to learn deeper CNR from process data.The feasibility and advantages of our proposals are validated by theoretical derivations and practical IP cases,which contain one MIQ regression and three MIQ-related fault detection tasks.The results reveal that highly fused statistical and neural network models yield superior monitoring performance compared to current state-of-the-art models,while statistical tests verify the convincing feature mining.展开更多
目的探讨两种干预方法缓解早产儿眼底筛查所致疼痛的效果。方法纳入2017年7月~2019年6月某三级甲等专科医院早产儿病房进行眼底筛查的168例早产儿进行研究,依据随机对照原则分为三组,各56例,对照组早产儿采取常规眼底筛查,非营养性吸吮(...目的探讨两种干预方法缓解早产儿眼底筛查所致疼痛的效果。方法纳入2017年7月~2019年6月某三级甲等专科医院早产儿病房进行眼底筛查的168例早产儿进行研究,依据随机对照原则分为三组,各56例,对照组早产儿采取常规眼底筛查,非营养性吸吮(NNS)组早产儿接受NNS护理,25%葡萄糖(GS)+NNS组早产儿接受25%GS安慰奶嘴护理。比较三组早产儿不同时间点疼痛、心率(HR)、血氧饱和度(SpO2)变化情况。结果 NNS组与25%GS+NNS组早产儿筛查过程中、筛查后1 min PIPP评分、HR均低于对照组,SpO2均高于对照组,差异显著(P<0.05);GS+NNS组早产儿筛查过程中、筛查后1 min PIPP评分、HR均低于NNS组,SpO2高于NNS组,差异显著(P<0.05)。结论采取25%GS+NNS的干预方式能够有效减轻早产儿眼底筛查所致疼痛,值得临床推荐。展开更多
基金V. ACKN0WLEDGMENT This work was supported by the National Natural Sci- ence Foundation of China （No.10375024） and the Science Foundation of Hunan Educational Committee.
文摘To expose the statistical properties of the degenerated spectrum, with the aid of the random matrix theory, a possible form of the NNS distribution function of the degenerate spectrum was proposed by providing a solution in terms of the same-degeneracy case. The results indicate that the target spectrum is transformed into two sub-spectra： a random one and a regular one, and that the repulsion level of the regular spectrum is also decreased.
文摘Based on the concept of the energy level repulsion, a potential function followed by the energy level particles is suggested. By regarding the energy level fluctuation spectrum as a dynamic system which consists of the pairs of energy level particles behaving as the generalized harmonic oscillator, a generalized Schrdinger equation valid for the nearest neighbor space (NNS) distribution of the levels is established. It turns out that the different kinds of NNS distributions found so far are the solutions of this equation: Both the Poisson type and Wigner type are its eigen solutions whereas the Gaussian unitary ensemble (GUE) type and the Brody type of NNS distribution are its composite solutions. Furthermore, the influences of the small perturbation on the NNS distribution are analyzed.
基金supported in part by the Pioneer Research and Development Program of Zhejiang(2025C01021)Zhejiang Province Postdoctoral Research Project Selection Fund(ZJ2025061)+3 种基金the National Science and Technology Major Project-Intelligent Manufacturing Systems and Robotics of China(2025ZD1602000,2025ZD1601800)the National Natural Science Foundation of China(61933015,62273030,62573387)the Natural Science Foundation of Zhejiang province,China(LY24F030004)the Fundamental Research Funds of Zhejiang Sci-Tech University(25222139-Y)。
文摘Ironmaking process(IP)is indispensable to modern iron and steel industry,where real-time monitoring is crucial for achieving high molten iron quality(MIQ)with low energy consumption.While neural network-based models show some promising results,they are generally limited by non-negligible drawbacks such as interpretability issues of feature learning.To address these issues,we propose a novel concept based on the shallow-to-deep correlation network representation regression(Sh-to-De CNRR).Our approach,shallow correlation network representation regression(ShCNRR),combines neural network and canonical correlation analysis thoughts to generate explainable features via shallow correlation network representation(CNR).A twin inverse network is then derived to obtain the explicit model output,leveraging the shallow CNR.To capture deeper nonlinear information,we extend ShCNRR into a hierarchical deep correlation network representation regression(DeCNRR)model that features stacked neural networks,enabling us to learn deeper CNR from process data.The feasibility and advantages of our proposals are validated by theoretical derivations and practical IP cases,which contain one MIQ regression and three MIQ-related fault detection tasks.The results reveal that highly fused statistical and neural network models yield superior monitoring performance compared to current state-of-the-art models,while statistical tests verify the convincing feature mining.
文摘目的探讨两种干预方法缓解早产儿眼底筛查所致疼痛的效果。方法纳入2017年7月~2019年6月某三级甲等专科医院早产儿病房进行眼底筛查的168例早产儿进行研究,依据随机对照原则分为三组,各56例,对照组早产儿采取常规眼底筛查,非营养性吸吮(NNS)组早产儿接受NNS护理,25%葡萄糖(GS)+NNS组早产儿接受25%GS安慰奶嘴护理。比较三组早产儿不同时间点疼痛、心率(HR)、血氧饱和度(SpO2)变化情况。结果 NNS组与25%GS+NNS组早产儿筛查过程中、筛查后1 min PIPP评分、HR均低于对照组,SpO2均高于对照组,差异显著(P<0.05);GS+NNS组早产儿筛查过程中、筛查后1 min PIPP评分、HR均低于NNS组,SpO2高于NNS组,差异显著(P<0.05)。结论采取25%GS+NNS的干预方式能够有效减轻早产儿眼底筛查所致疼痛,值得临床推荐。
