Human motion recognition is a research hotspot in the field of computer vision,which has a wide range of applications,including biometrics,intelligent surveillance and human-computer interaction.In visionbased human m...Human motion recognition is a research hotspot in the field of computer vision,which has a wide range of applications,including biometrics,intelligent surveillance and human-computer interaction.In visionbased human motion recognition,the main input modes are RGB,depth image and bone data.Each mode can capture some kind of information,which is likely to be complementary to other modes,for example,some modes capture global information while others capture local details of an action.Intuitively speaking,the fusion of multiple modal data can improve the recognition accuracy.In addition,how to correctly model and utilize spatiotemporal information is one of the challenges facing human motion recognition.Aiming at the feature extraction methods involved in human action recognition tasks in video,this paper summarizes the traditional manual feature extraction methods from the aspects of global feature extraction and local feature extraction,and introduces the commonly used feature learning models of feature extraction methods based on deep learning in detail.This paper summarizes the opportunities and challenges in the field of motion recognition and looks forward to the possible research directions in the future.展开更多
The nuclear Chirality-Parity(ChP) violation, a simultaneous breaking of chiral and reflection symmetries in the intrinsic frame, is investigated with a reflection-asymmetric triaxial particle rotor model. A new symmet...The nuclear Chirality-Parity(ChP) violation, a simultaneous breaking of chiral and reflection symmetries in the intrinsic frame, is investigated with a reflection-asymmetric triaxial particle rotor model. A new symmetry for an ideal ChP violation system is found and the corresponding selection rules of the electromagnetic transitions are derived. The fingerprints for the ChP violation including the nearly degenerate quartet bands and the selection rules of the electromagnetic transitions are provided. These fingerprints are examined for ChP quartet bands by taking a two-j shell h11/2 and d5/2 with typical energy spacing for A = 130 nuclei.展开更多
Summer green tea(SGT)is not favored by consumers due to its strong bitterness and astringency.This study aims to improve the taste of SGT using tea-derived fungi isolated from Liupao tea by solid-state fermentation.Ba...Summer green tea(SGT)is not favored by consumers due to its strong bitterness and astringency.This study aims to improve the taste of SGT using tea-derived fungi isolated from Liupao tea by solid-state fermentation.Based on 19 detected main compounds,principal component analysis(PCA)and hierarchical cluster analysis(HCA)showed Aspergillus sydowii,Penicillium manginii,Aspergillus intermedius,Aspergillus amstelodami,and Aspergillus niger groups were clustered together with significant differences from the control.Additionally,metabolomics analysis showed P.manginii,A.intermedius,and A.amstelodami strains could reduce the chemical components associated with bitter and astringent flavors,such as epicatechin gallate,epicatechin,(+)-gallocatechin,quercetin,kaempferol,myricetin,procyanidin B2,L-phenylalanine and its glycoside derivatives(VIP>1,P<0.05),and increase the contents of theabrownins associated with umami taste(P<0.05).In summary,the taste of SGT can be improved by the above fungi fermentation.展开更多
基金2021 Scientific research funding project of Liaoning Provincial Education Department(Research and implementation of university scientific research information platform serving the transformation of achievements).
文摘Human motion recognition is a research hotspot in the field of computer vision,which has a wide range of applications,including biometrics,intelligent surveillance and human-computer interaction.In visionbased human motion recognition,the main input modes are RGB,depth image and bone data.Each mode can capture some kind of information,which is likely to be complementary to other modes,for example,some modes capture global information while others capture local details of an action.Intuitively speaking,the fusion of multiple modal data can improve the recognition accuracy.In addition,how to correctly model and utilize spatiotemporal information is one of the challenges facing human motion recognition.Aiming at the feature extraction methods involved in human action recognition tasks in video,this paper summarizes the traditional manual feature extraction methods from the aspects of global feature extraction and local feature extraction,and introduces the commonly used feature learning models of feature extraction methods based on deep learning in detail.This paper summarizes the opportunities and challenges in the field of motion recognition and looks forward to the possible research directions in the future.
基金supported by the National Natural Science Foundation of China (11875075, 11935003, 11975031, and 11621131001)the National Key R&D Program of China (2018YFA0404400 and 2017YFE0116700)+1 种基金the State Key Laboratory of Nuclear Physics and Technology, Peking University (NPT2020ZZ01)the China Postdoctoral Science Foundation (2020M670014)。
文摘The nuclear Chirality-Parity(ChP) violation, a simultaneous breaking of chiral and reflection symmetries in the intrinsic frame, is investigated with a reflection-asymmetric triaxial particle rotor model. A new symmetry for an ideal ChP violation system is found and the corresponding selection rules of the electromagnetic transitions are derived. The fingerprints for the ChP violation including the nearly degenerate quartet bands and the selection rules of the electromagnetic transitions are provided. These fingerprints are examined for ChP quartet bands by taking a two-j shell h11/2 and d5/2 with typical energy spacing for A = 130 nuclei.
基金supported by the following project funds:1.Liupao tea processing technology optimization supported by Wuzhou Academy of Agricultural Sciences(No.H20496)supported by Wuzhou Tea Industry Development Service Center(No.H220644),Wuzhou 543003,China。
文摘Summer green tea(SGT)is not favored by consumers due to its strong bitterness and astringency.This study aims to improve the taste of SGT using tea-derived fungi isolated from Liupao tea by solid-state fermentation.Based on 19 detected main compounds,principal component analysis(PCA)and hierarchical cluster analysis(HCA)showed Aspergillus sydowii,Penicillium manginii,Aspergillus intermedius,Aspergillus amstelodami,and Aspergillus niger groups were clustered together with significant differences from the control.Additionally,metabolomics analysis showed P.manginii,A.intermedius,and A.amstelodami strains could reduce the chemical components associated with bitter and astringent flavors,such as epicatechin gallate,epicatechin,(+)-gallocatechin,quercetin,kaempferol,myricetin,procyanidin B2,L-phenylalanine and its glycoside derivatives(VIP>1,P<0.05),and increase the contents of theabrownins associated with umami taste(P<0.05).In summary,the taste of SGT can be improved by the above fungi fermentation.
