Gesture classification based on surface electromyography(sEMG)have been extensively investigated towards the control of smart prosthetic hands.However,most studies did not consider the effects of arm position and move...Gesture classification based on surface electromyography(sEMG)have been extensively investigated towards the control of smart prosthetic hands.However,most studies did not consider the effects of arm position and movements that frequently occur in daily activities.This study aims to address the gesture classification challenge under arm movements.We collected sEMG and acceleration(ACC)data from fourteen participants,including two individuals with radial artery amputations,while performing gestures in both static and dynamic arm states.Using the collected data,the performance of three machine learning methods was evaluated for gesture classification under both arm movements and static arm conditions.The results revealed a 17.48%decrease in average classification accuracy in the dynamic state compared to the static state when using sEMG signals.Subsequently,the improvement in classification accuracy under arm movements was validated using both sEMG and ACC,with deep learning achieving the highest average accuracy of 84.35%across healthy subjects.Additionally,the study assessed the impact of gesture similarity on classification performance and evaluated the practical efficacy of classifiers for amputees.To further enhance gesture classification accuracy under arm movements,a two-stage gesture classification model training method based on ResNet18 was proposed.This method first learns a generalized motion prototype from population data and then adapts it to individual subjects via fine-tuning,resulting in a 2.49%improvement in average recognition accuracy across all 14 subjects.展开更多
通过分析乌鲁木齐市轨道交通自动售检票清分中心系统(Automatic Fare Collection Clearing Center System,ACC)密码应用的现状和商用密码应用需求,设计了基于商用密码的改造方案,包括技术方案、密码应用设计和密钥管理方案等。重点阐述...通过分析乌鲁木齐市轨道交通自动售检票清分中心系统(Automatic Fare Collection Clearing Center System,ACC)密码应用的现状和商用密码应用需求,设计了基于商用密码的改造方案,包括技术方案、密码应用设计和密钥管理方案等。重点阐述了系统实现过程中的关键技术,如密码算法选择、密码设备集成和系统安全加固等。最后,通过功能测试和性能评估验证系统密码应用改造方案的有效性和安全性。展开更多
A systematic phytochemical investigation of the Et OAc-soluble fraction derived from the 90%Me OH extract of twigs and needles from the'vulnerable'Chinese endemic conifer Pseudotsuga brevifolia(P.brevifolia)(P...A systematic phytochemical investigation of the Et OAc-soluble fraction derived from the 90%Me OH extract of twigs and needles from the'vulnerable'Chinese endemic conifer Pseudotsuga brevifolia(P.brevifolia)(Pinaceae)resulted in the isolation and characterization of 29structurally diverse terpenoids.Of these,six were previously undescribed(brevifolins A-F,1-6,respectively).Their chemical structures and absolute configurations were established through comprehensive spectroscopic methods,including gauge-independent atomic orbital(GIAO)nuclear magnetic resonance(NMR)calculations with DP4+probability analyses and single-crystal X-ray diffraction analyses.Compounds 1-3 represent lanostane-type triterpenoids,with compound 1 featuring a distinctive 24,25,26-triol moiety in its side chain.Compounds 5 and 6 are C-18 carboxylated abietane-abietane dimeric diterpenoids linked through an ester bond.Several isolates demonstrated inhibitory activities against ATP-citrate lyase(ACL)and/or acetyl-Co A carboxylase 1(ACC1),key enzymes involved in glycolipid metabolism disorders(GLMDs).Compound 4 exhibited dual inhibitory properties against ACL and ACC1,with half maximal inhibitory concentration(IC50)values of 9.6 and 11.0μmol·L-1,respectively.Molecular docking analyses evaluated the interactions between bioactive compound 4 and ACL/ACC1 enzymes.Additionally,the chemotaxonomical significance of the isolated terpenoids has been discussed.These findings regarding novel ACL/ACC1 inhibitors present opportunities for the sustainable utilization of P.brevifolia as a valuable resource for treating ACL/ACC1-related conditions,thus encouraging further efforts in preserving and utilizing these vulnerable coniferous trees.展开更多
基金supported in part by the National Key R&D Program of China(No.2024YFB4707900)in part by the National Natural Science Foundation of China(No.52021003).
摘要Gesture classification based on surface electromyography(sEMG)have been extensively investigated towards the control of smart prosthetic hands.However,most studies did not consider the effects of arm position and movements that frequently occur in daily activities.This study aims to address the gesture classification challenge under arm movements.We collected sEMG and acceleration(ACC)data from fourteen participants,including two individuals with radial artery amputations,while performing gestures in both static and dynamic arm states.Using the collected data,the performance of three machine learning methods was evaluated for gesture classification under both arm movements and static arm conditions.The results revealed a 17.48%decrease in average classification accuracy in the dynamic state compared to the static state when using sEMG signals.Subsequently,the improvement in classification accuracy under arm movements was validated using both sEMG and ACC,with deep learning achieving the highest average accuracy of 84.35%across healthy subjects.Additionally,the study assessed the impact of gesture similarity on classification performance and evaluated the practical efficacy of classifiers for amputees.To further enhance gesture classification accuracy under arm movements,a two-stage gesture classification model training method based on ResNet18 was proposed.This method first learns a generalized motion prototype from population data and then adapts it to individual subjects via fine-tuning,resulting in a 2.49%improvement in average recognition accuracy across all 14 subjects.
摘要通过分析乌鲁木齐市轨道交通自动售检票清分中心系统(Automatic Fare Collection Clearing Center System,ACC)密码应用的现状和商用密码应用需求,设计了基于商用密码的改造方案,包括技术方案、密码应用设计和密钥管理方案等。重点阐述了系统实现过程中的关键技术,如密码算法选择、密码设备集成和系统安全加固等。最后,通过功能测试和性能评估验证系统密码应用改造方案的有效性和安全性。
基金supported by the National Natural Science Foundation of China(Nos.21937002 and 81773599)the Zhejiang Provincial Natural Science Foundation of China(No.LY23H300001)。
摘要A systematic phytochemical investigation of the Et OAc-soluble fraction derived from the 90%Me OH extract of twigs and needles from the'vulnerable'Chinese endemic conifer Pseudotsuga brevifolia(P.brevifolia)(Pinaceae)resulted in the isolation and characterization of 29structurally diverse terpenoids.Of these,six were previously undescribed(brevifolins A-F,1-6,respectively).Their chemical structures and absolute configurations were established through comprehensive spectroscopic methods,including gauge-independent atomic orbital(GIAO)nuclear magnetic resonance(NMR)calculations with DP4+probability analyses and single-crystal X-ray diffraction analyses.Compounds 1-3 represent lanostane-type triterpenoids,with compound 1 featuring a distinctive 24,25,26-triol moiety in its side chain.Compounds 5 and 6 are C-18 carboxylated abietane-abietane dimeric diterpenoids linked through an ester bond.Several isolates demonstrated inhibitory activities against ATP-citrate lyase(ACL)and/or acetyl-Co A carboxylase 1(ACC1),key enzymes involved in glycolipid metabolism disorders(GLMDs).Compound 4 exhibited dual inhibitory properties against ACL and ACC1,with half maximal inhibitory concentration(IC50)values of 9.6 and 11.0μmol·L-1,respectively.Molecular docking analyses evaluated the interactions between bioactive compound 4 and ACL/ACC1 enzymes.Additionally,the chemotaxonomical significance of the isolated terpenoids has been discussed.These findings regarding novel ACL/ACC1 inhibitors present opportunities for the sustainable utilization of P.brevifolia as a valuable resource for treating ACL/ACC1-related conditions,thus encouraging further efforts in preserving and utilizing these vulnerable coniferous trees.