Spinal cord injury necessitates effective rehabilitation strategies, with exercise therapies showing promise in promoting recovery. This study investigated the impact of rehabilitation exercise on functional recovery ...Spinal cord injury necessitates effective rehabilitation strategies, with exercise therapies showing promise in promoting recovery. This study investigated the impact of rehabilitation exercise on functional recovery and morphological changes following thoracic contusive spinal cord injury. After a 7-day recovery period after spinal cord injury, mice were assigned to either a trained group(10 weeks of voluntary running wheel or forced treadmill exercise) or an untrained group. Bi-weekly assessments revealed that the exercise-trained group, particularly the voluntary wheel exercise subgroup, displayed significantly improved locomotor recovery, more plasticity of dopaminergic and serotonin modulation compared with the untrained group. Additionally, exercise interventions led to gait pattern restoration and enhanced transcranial magnetic motor-evoked potentials. Despite consistent injury areas across groups, exercise training promoted terminal innervation of descending axons. In summary, voluntary wheel exercise shows promise for enhancing outcomes after thoracic contusive spinal cord injury, emphasizing the role of exercise modality in promoting recovery and morphological changes in spinal cord injuries. Our findings will influence future strategies for rehabilitation exercises, restoring functional movement after spinal cord injury.展开更多
Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and ...Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.展开更多
In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission...In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means.展开更多
The genus Scincella Mittleman,1950,within the family Scincidae,is a diverse group comprising 39 described species.The taxonomy of the genus is complex due to morphological similarities among species,which often obscur...The genus Scincella Mittleman,1950,within the family Scincidae,is a diverse group comprising 39 described species.The taxonomy of the genus is complex due to morphological similarities among species,which often obscures the true extent of biodiversity,resulting in several undescribed species requiring further exploration.In China,particularly within the unique ecosystems of the Hengduan Mountains,the diversity of Scincella is notably underestimated,with only 12 species currently recognized.In the present study,we describe a new species of the genus Scincella,Scincella liangshanensis sp.nov.,from Sichuan Province,Southwest China.Morphological characteristics and phylogenetic analyses revealed that the putative new species is distinct from all other known congeners.This discovery not only expands the known diversity of Scincella but also emphasizes the inadequacies in our current understanding of herpetological diversity in China.The addition of this species to the scientific record highlights the necessity for ongoing biodiversity assessments to uncover hidden species and enhance our understanding of the intricate web of life in one of the world’s biodiversity hotspots.展开更多
Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the...Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the research and applications of natural language processing across different modalities,our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos.Specifically,we propose a deep learning-basedMulti-ModalMutual Enhancement Video Semantic Communication system,called M3E-VSC.Built upon a VectorQuantized Generative AdversarialNetwork(VQGAN),our systemaims to leverage mutual enhancement among different modalities by using text as the main carrier of transmission.With it,the semantic information can be extracted fromkey-frame images and audio of the video and performdifferential value to ensure that the extracted text conveys accurate semantic information with fewer bits,thus improving the capacity of the system.Furthermore,a multi-frame semantic detection module is designed to facilitate semantic transitions during video generation.Simulation results demonstrate that our proposed model maintains high robustness in complex noise environments,particularly in low signal-to-noise ratio conditions,significantly improving the accuracy and speed of semantic transmission in video communication by approximately 50 percent.展开更多
针对传统铝合金在激光粉末床融合技术(Laser Powder Bed Fusion,LPBF)中的高裂纹敏感性,总结了近年来通过微合金化方法改善LPBF铝合金成型性及力学性能的研究进展。综述了微合金元素在成型过程中的作用机理,重点讨论了Er、Zr元素对微观...针对传统铝合金在激光粉末床融合技术(Laser Powder Bed Fusion,LPBF)中的高裂纹敏感性,总结了近年来通过微合金化方法改善LPBF铝合金成型性及力学性能的研究进展。综述了微合金元素在成型过程中的作用机理,重点讨论了Er、Zr元素对微观组织的调控即晶粒细化,总结了LPBF微合金化铝合金的成型工艺研究,分析了微合金改性后热处理工艺诱导第二相弥散析出及对应力学性能的研究。对未来LPBF铝合金微合金化研究提出展望,开发新的微合金改性铝合金并探索适合工业生产的热处理工艺,获得低成本、高强度的LPBF铝合金。展开更多
BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinica...BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinical data of 632 patients with AP were obtained from the Medical Information Mart for Intensive Care(MIMIC)-IV database.The nomogram for the prediction of 30-day,60-day and 90-day survival was developed by incorporating the risk factors identified by multivariate Cox analyses.RESULTS:Multivariate Cox proportional hazard model analysis showed that age(hazard ratio[HR]=1.06,95%confidence interval[95%CI]1.03-1.08,P<0.001),white blood cell count(HR=1.03,95%CI 1.00-1.06,P=0.046),systolic blood pressure(HR=0.99,95%CI 0.97-1.00,P=0.015),serum lactate level(HR=1.10,95%CI 1.01-1.20,P=0.023),and Simplified Acute Physiology Score II(HR=1.04,95%CI 1.02-1.06,P<0.001)were independent predictors of 90-day mortality in patients with AP.A prognostic nomogram model for 30-day,60-day,and 90-day survival based on these variables was built.Receiver operating characteristic(ROC)curve analysis demonstrated that the nomogram had good accuracy for predicting 30-day,60-day,and 90-day survival(area under the ROC curve:0.796,0.812,and 0.854,respectively;bootstrap-corrected C-index value:0.782,0.799,and 0.846,respectively).CONCLUSION:The nomogram-based prognostic model was able to accurately predict 30-day,60-day,and 90-day survival outcomes and thus may be of value for risk stratification and clinical decision-making for critically ill patients with AP.展开更多
A transient multi-physics model incorporated with an electromagneto-thermomechanical coupling is developed to capture the multi-field behavior of a single-pancake(SP)insert no-insulation(NI)coil in a hybrid magnet dur...A transient multi-physics model incorporated with an electromagneto-thermomechanical coupling is developed to capture the multi-field behavior of a single-pancake(SP)insert no-insulation(NI)coil in a hybrid magnet during the charging and discharging processes.The coupled problem is resolved by means of the finite element method(FEM)for the magneto-thermo-elastic behaviors and the Runge-Kutta method for the transient responses of the electrical circuits of the hybrid superconducting magnet system.The results reveal that the transient multi-physics responses of the insert NI coil primarily depend on the charging/discharging procedure of the hybrid magnet.Moreover,a reverse azimuthal current and a compressive hoop stress are induced in the insert NI coil during the charging process,while a forward azimuthal current and a tensile hoop stress are observed during the discharging process.The induced voltages in the insert NI coil can drive the currents flowing across the radial turns where the contact resistance exists.Therefore,it brings forth significant Joule heat,causing a temperature rise and a uniform distribution of this heat in the coil turns.Accordingly,a thermally/mechanically unstable or quenching event may be encountered when a high operating current is flowing in the insert NI coil.It is numerically predicted that a quick charging will induce a compressive hoop stress which may bring a risk of buckling instability in the coil,while a discharging will not.The simulations provide an insight of hybrid superconducting magnets under transient start-up or shutdown phases which are inevitably encountered in practical applications.展开更多
基金supported by the NIH (R01NS103481, R01NS111776, and R01NS131489)Indiana Department of Health (ISDH58180)(all to WW)。
文摘Spinal cord injury necessitates effective rehabilitation strategies, with exercise therapies showing promise in promoting recovery. This study investigated the impact of rehabilitation exercise on functional recovery and morphological changes following thoracic contusive spinal cord injury. After a 7-day recovery period after spinal cord injury, mice were assigned to either a trained group(10 weeks of voluntary running wheel or forced treadmill exercise) or an untrained group. Bi-weekly assessments revealed that the exercise-trained group, particularly the voluntary wheel exercise subgroup, displayed significantly improved locomotor recovery, more plasticity of dopaminergic and serotonin modulation compared with the untrained group. Additionally, exercise interventions led to gait pattern restoration and enhanced transcranial magnetic motor-evoked potentials. Despite consistent injury areas across groups, exercise training promoted terminal innervation of descending axons. In summary, voluntary wheel exercise shows promise for enhancing outcomes after thoracic contusive spinal cord injury, emphasizing the role of exercise modality in promoting recovery and morphological changes in spinal cord injuries. Our findings will influence future strategies for rehabilitation exercises, restoring functional movement after spinal cord injury.
基金funded by the National Natural Science Foundation of China(61991413)the China Postdoctoral Science Foundation(2019M651142)+1 种基金the Natural Science Foundation of Liaoning Province(2021-KF-12-07)the Natural Science Foundations of Liaoning Province(2023-MS-322).
文摘Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.
基金supported in part by the National Natural Science Foundation of China(61901231)in part by the National Natural Science Foundation of China(61971238)+3 种基金in part by the Natural Science Foundation of Jiangsu Province of China(BK20180757)in part by the open project of the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space,Ministry of Industry and Information Technology(KF20202102)in part by the China Postdoctoral Science Foundation under Grant(2020M671480)in part by the Jiangsu Planned Projects for Postdoctoral Research Funds(2020z295).
文摘In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means.
基金funded by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(2019QZKK0501)the National Natural Science Foundation of China(32300370,32200363)+2 种基金Sichuan Province Innovative Talent Funding Project for Postdoctoral Fellows(BX202323)Postdoctoral Fellowship Program of CPSF(GZC20232575)Biological Resources Programme,Chinese Academy of Sciences(KFJ-BRP-017-65).
文摘The genus Scincella Mittleman,1950,within the family Scincidae,is a diverse group comprising 39 described species.The taxonomy of the genus is complex due to morphological similarities among species,which often obscures the true extent of biodiversity,resulting in several undescribed species requiring further exploration.In China,particularly within the unique ecosystems of the Hengduan Mountains,the diversity of Scincella is notably underestimated,with only 12 species currently recognized.In the present study,we describe a new species of the genus Scincella,Scincella liangshanensis sp.nov.,from Sichuan Province,Southwest China.Morphological characteristics and phylogenetic analyses revealed that the putative new species is distinct from all other known congeners.This discovery not only expands the known diversity of Scincella but also emphasizes the inadequacies in our current understanding of herpetological diversity in China.The addition of this species to the scientific record highlights the necessity for ongoing biodiversity assessments to uncover hidden species and enhance our understanding of the intricate web of life in one of the world’s biodiversity hotspots.
基金supported by the National Key Research and Development Project under Grant 2020YFB1807602Key Program of Marine Economy Development Special Foundation of Department of Natural Resources of Guangdong Province(GDNRC[2023]24)the National Natural Science Foundation of China under Grant 62271267.
文摘Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the research and applications of natural language processing across different modalities,our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos.Specifically,we propose a deep learning-basedMulti-ModalMutual Enhancement Video Semantic Communication system,called M3E-VSC.Built upon a VectorQuantized Generative AdversarialNetwork(VQGAN),our systemaims to leverage mutual enhancement among different modalities by using text as the main carrier of transmission.With it,the semantic information can be extracted fromkey-frame images and audio of the video and performdifferential value to ensure that the extracted text conveys accurate semantic information with fewer bits,thus improving the capacity of the system.Furthermore,a multi-frame semantic detection module is designed to facilitate semantic transitions during video generation.Simulation results demonstrate that our proposed model maintains high robustness in complex noise environments,particularly in low signal-to-noise ratio conditions,significantly improving the accuracy and speed of semantic transmission in video communication by approximately 50 percent.
文摘针对传统铝合金在激光粉末床融合技术(Laser Powder Bed Fusion,LPBF)中的高裂纹敏感性,总结了近年来通过微合金化方法改善LPBF铝合金成型性及力学性能的研究进展。综述了微合金元素在成型过程中的作用机理,重点讨论了Er、Zr元素对微观组织的调控即晶粒细化,总结了LPBF微合金化铝合金的成型工艺研究,分析了微合金改性后热处理工艺诱导第二相弥散析出及对应力学性能的研究。对未来LPBF铝合金微合金化研究提出展望,开发新的微合金改性铝合金并探索适合工业生产的热处理工艺,获得低成本、高强度的LPBF铝合金。
基金supported by the Clinical Research Funds of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital(ynhg202125)。
文摘BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinical data of 632 patients with AP were obtained from the Medical Information Mart for Intensive Care(MIMIC)-IV database.The nomogram for the prediction of 30-day,60-day and 90-day survival was developed by incorporating the risk factors identified by multivariate Cox analyses.RESULTS:Multivariate Cox proportional hazard model analysis showed that age(hazard ratio[HR]=1.06,95%confidence interval[95%CI]1.03-1.08,P<0.001),white blood cell count(HR=1.03,95%CI 1.00-1.06,P=0.046),systolic blood pressure(HR=0.99,95%CI 0.97-1.00,P=0.015),serum lactate level(HR=1.10,95%CI 1.01-1.20,P=0.023),and Simplified Acute Physiology Score II(HR=1.04,95%CI 1.02-1.06,P<0.001)were independent predictors of 90-day mortality in patients with AP.A prognostic nomogram model for 30-day,60-day,and 90-day survival based on these variables was built.Receiver operating characteristic(ROC)curve analysis demonstrated that the nomogram had good accuracy for predicting 30-day,60-day,and 90-day survival(area under the ROC curve:0.796,0.812,and 0.854,respectively;bootstrap-corrected C-index value:0.782,0.799,and 0.846,respectively).CONCLUSION:The nomogram-based prognostic model was able to accurately predict 30-day,60-day,and 90-day survival outcomes and thus may be of value for risk stratification and clinical decision-making for critically ill patients with AP.
基金the National Natural Science Foundation of China(Nos.11932008 and 11672120)the Fundamental Research Funds for the Central Universities of China(No.lzujbky-2022-kb01)。
文摘A transient multi-physics model incorporated with an electromagneto-thermomechanical coupling is developed to capture the multi-field behavior of a single-pancake(SP)insert no-insulation(NI)coil in a hybrid magnet during the charging and discharging processes.The coupled problem is resolved by means of the finite element method(FEM)for the magneto-thermo-elastic behaviors and the Runge-Kutta method for the transient responses of the electrical circuits of the hybrid superconducting magnet system.The results reveal that the transient multi-physics responses of the insert NI coil primarily depend on the charging/discharging procedure of the hybrid magnet.Moreover,a reverse azimuthal current and a compressive hoop stress are induced in the insert NI coil during the charging process,while a forward azimuthal current and a tensile hoop stress are observed during the discharging process.The induced voltages in the insert NI coil can drive the currents flowing across the radial turns where the contact resistance exists.Therefore,it brings forth significant Joule heat,causing a temperature rise and a uniform distribution of this heat in the coil turns.Accordingly,a thermally/mechanically unstable or quenching event may be encountered when a high operating current is flowing in the insert NI coil.It is numerically predicted that a quick charging will induce a compressive hoop stress which may bring a risk of buckling instability in the coil,while a discharging will not.The simulations provide an insight of hybrid superconducting magnets under transient start-up or shutdown phases which are inevitably encountered in practical applications.
