To investigate neural mechanisms of human psychology with electroencephalography(EEG),we typically instruct participants to perform certain tasks with simultaneous recording of their brain activities.The identificatio...To investigate neural mechanisms of human psychology with electroencephalography(EEG),we typically instruct participants to perform certain tasks with simultaneous recording of their brain activities.The identification of task-related EEG responses requires data analysis techniques that are normally different from methods for analyzing resting-state EEG.This review aims to demystify commonly used signal processing methods for identifying task-related EEG activities for psychologists.To achieve this goal,we first highlight the different preprocessing pipelines between task-related EEG and resting-state EEG.We then discuss the methods to extract and visualize event-related potentials in the time domain and event-related oscillatory responses in the time-frequency domain.Potential applications of advanced techniques such as source analysis and single-trial analysis are briefly discussed.We conclude this review with a short summary of task-related EEG data analysis,recommendations for further study,and caveats we should take heed of.展开更多
Nucleus PLUS SMP是一种支持对称多核处理器架构的嵌入式实时操作系统内核。深入研究了其任务管理机制,分析了其对称多核任务管理的主要技术,研究并提出了多核操作系统任务管理功能的测试思路,搭建了系统测试环境,设计了包括任务状态机...Nucleus PLUS SMP是一种支持对称多核处理器架构的嵌入式实时操作系统内核。深入研究了其任务管理机制,分析了其对称多核任务管理的主要技术,研究并提出了多核操作系统任务管理功能的测试思路,搭建了系统测试环境,设计了包括任务状态机、调度算法、负载均衡、亲和性、BCD调度域及核间通信等在内的一套完整的测试用例,实现了对操作系统任务管理功能的有效测试。展开更多
Transient stability batch assessment(TSBA)is es-sential for dynamic security check in both power system planning and day-ahead dispatch.It is also a necessary technique to generate sufficient training data for data-dr...Transient stability batch assessment(TSBA)is es-sential for dynamic security check in both power system planning and day-ahead dispatch.It is also a necessary technique to generate sufficient training data for data-driven online transient stability assessment(TSA).However,most existing work suffers from various problems including high computational burden,low model adaptability,and low performance robustness.Therefore,it is still a significant challenge in modern power systems,with numerous scenarios(e.g.,operating conditions and"N-k"contin-gencies)to be assessed at the same time.The purpose of this work is to construct a data-driven method to early terminate time-domain simulation(TDS)and dynamically schedule TSBA task queue a prior,in order to reduce computational burden without compromising accuracy.To achieve this goal,a time-adaptive cas-caded convolutional neural networks(CNNs)model is developed to predict stability and early terminate TDS.Additionally,an information entropy based prioritization strategy is designed to distinguish informative samples,dynamically schedule TSBA task queue and timely update model,thus further reducing simulation time.Case study in IEEE 39-bus system validates the effectiveness of the proposed method.展开更多
Many studies have shown that fibronectin type III domain-containing protein 5(FDNC5) and brain-derived neurotrophic factor(BDNF) play vital roles in plasticity after brain injury. An enriched environment refers to an ...Many studies have shown that fibronectin type III domain-containing protein 5(FDNC5) and brain-derived neurotrophic factor(BDNF) play vital roles in plasticity after brain injury. An enriched environment refers to an environment that provides animals with multi-sensory stimulation and movement opportunities. An enriched environment has been shown to promote the regeneration of nerve cells, synapses, and blood vessels in the animal brain after cerebral ischemia;however, the exact mechanisms have not been clarified. This study aimed to determine whether an enriched environment could improve neurobehavioral functions after the experimental inducement of cerebral ischemia and whether neurobehavioral outcomes were associated with the expression of FDNC5 and BDNF. This study established ischemic mouse models using permanent middle cerebral artery occlusion(pMCAO) on the left side. On postoperative day 1, the mice were randomly assigned to either enriched environment or standard housing condition groups. Mice in the standard housing condition group were housed and fed under standard conditions. Mice in the enriched environment group were housed in a large cage, containing various toys, and fed with a standard diet. Sham-operated mice received the same procedure, but without artery occlusion, and were housed and fed under standard conditions. On postoperative days 7 and 14, a beam-walking test was used to assess coordination, balance, and spatial learning. On postoperative days 16–20, a Morris water maze test was used to assess spatial learning and memory. On postoperative day 15, the expression levels of FDNC5 and BDNF proteins in the ipsilateral cerebral cortex were analyzed by western blot assay. The results showed that compared with the standard housing condition group, the motor balance and coordination functions(based on beam-walking test scores 7 and 14 days after operation), spatial learning abilities(based on the spatial learning scores from the Morris water maze test 16–19 days after operation), and memory 展开更多
城市污水处理运行过程的优化控制方法是提高其运行效率和改善其运行效果的关键.然而,由于城市污水处理过程进水负荷多变,运行过程存在多种工况且变化频繁,导致城市污水处理过程难以实现优化运行.因此,如何设计优化控制策略应对多种工况...城市污水处理运行过程的优化控制方法是提高其运行效率和改善其运行效果的关键.然而,由于城市污水处理过程进水负荷多变,运行过程存在多种工况且变化频繁,导致城市污水处理过程难以实现优化运行.因此,如何设计优化控制策略应对多种工况变化,保证出水总氮和出水总磷等水质指标达标,是城市污水处理过程亟需解决的挑战性问题.本文设计了基于领域自适应的城市污水处理运行过程多工况优化控制方法(multi-operating optimization control with domain adaptive,MOOC-DA).首先,建立城市污水处理运行过程多工况优化目标模型,捕获运行能耗以及出水水质的时间序列特性,实现运行指标的精确预测.其次,设计基于多任务领域自适应粒子群的多工况优化设定方法,保证多工况运行出水水质达标.最后,设计基于多任务模糊神经网络的优化设定跟踪控制方法,实现城市污水处理过程多工况优化运行.为了验证所提出方法的有效性,基于活性污泥模型仿真平台将提出的MOOC-DA与其他优化控制方法进行对比实验.结果表明,该方法能够实现污水处理过程多工况的优化运行,保证出水总氮和出水总磷等水质指标达标.展开更多
基金supported by the National Natural Science Foundation of China(No.31822025,No.31671141)
文摘To investigate neural mechanisms of human psychology with electroencephalography(EEG),we typically instruct participants to perform certain tasks with simultaneous recording of their brain activities.The identification of task-related EEG responses requires data analysis techniques that are normally different from methods for analyzing resting-state EEG.This review aims to demystify commonly used signal processing methods for identifying task-related EEG activities for psychologists.To achieve this goal,we first highlight the different preprocessing pipelines between task-related EEG and resting-state EEG.We then discuss the methods to extract and visualize event-related potentials in the time domain and event-related oscillatory responses in the time-frequency domain.Potential applications of advanced techniques such as source analysis and single-trial analysis are briefly discussed.We conclude this review with a short summary of task-related EEG data analysis,recommendations for further study,and caveats we should take heed of.
文摘Nucleus PLUS SMP是一种支持对称多核处理器架构的嵌入式实时操作系统内核。深入研究了其任务管理机制,分析了其对称多核任务管理的主要技术,研究并提出了多核操作系统任务管理功能的测试思路,搭建了系统测试环境,设计了包括任务状态机、调度算法、负载均衡、亲和性、BCD调度域及核间通信等在内的一套完整的测试用例,实现了对操作系统任务管理功能的有效测试。
基金This work was supported by China scholarship council under Grant 201906320221.
文摘Transient stability batch assessment(TSBA)is es-sential for dynamic security check in both power system planning and day-ahead dispatch.It is also a necessary technique to generate sufficient training data for data-driven online transient stability assessment(TSA).However,most existing work suffers from various problems including high computational burden,low model adaptability,and low performance robustness.Therefore,it is still a significant challenge in modern power systems,with numerous scenarios(e.g.,operating conditions and"N-k"contin-gencies)to be assessed at the same time.The purpose of this work is to construct a data-driven method to early terminate time-domain simulation(TDS)and dynamically schedule TSBA task queue a prior,in order to reduce computational burden without compromising accuracy.To achieve this goal,a time-adaptive cas-caded convolutional neural networks(CNNs)model is developed to predict stability and early terminate TDS.Additionally,an information entropy based prioritization strategy is designed to distinguish informative samples,dynamically schedule TSBA task queue and timely update model,thus further reducing simulation time.Case study in IEEE 39-bus system validates the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China,Nos.81601961(to KWY),81672242(to YW)the Key Construction Projects of Shanghai Health and Family Planning on Weak Discipline,China,No.2015ZB0401(to YW)
文摘Many studies have shown that fibronectin type III domain-containing protein 5(FDNC5) and brain-derived neurotrophic factor(BDNF) play vital roles in plasticity after brain injury. An enriched environment refers to an environment that provides animals with multi-sensory stimulation and movement opportunities. An enriched environment has been shown to promote the regeneration of nerve cells, synapses, and blood vessels in the animal brain after cerebral ischemia;however, the exact mechanisms have not been clarified. This study aimed to determine whether an enriched environment could improve neurobehavioral functions after the experimental inducement of cerebral ischemia and whether neurobehavioral outcomes were associated with the expression of FDNC5 and BDNF. This study established ischemic mouse models using permanent middle cerebral artery occlusion(pMCAO) on the left side. On postoperative day 1, the mice were randomly assigned to either enriched environment or standard housing condition groups. Mice in the standard housing condition group were housed and fed under standard conditions. Mice in the enriched environment group were housed in a large cage, containing various toys, and fed with a standard diet. Sham-operated mice received the same procedure, but without artery occlusion, and were housed and fed under standard conditions. On postoperative days 7 and 14, a beam-walking test was used to assess coordination, balance, and spatial learning. On postoperative days 16–20, a Morris water maze test was used to assess spatial learning and memory. On postoperative day 15, the expression levels of FDNC5 and BDNF proteins in the ipsilateral cerebral cortex were analyzed by western blot assay. The results showed that compared with the standard housing condition group, the motor balance and coordination functions(based on beam-walking test scores 7 and 14 days after operation), spatial learning abilities(based on the spatial learning scores from the Morris water maze test 16–19 days after operation), and memory
文摘城市污水处理运行过程的优化控制方法是提高其运行效率和改善其运行效果的关键.然而,由于城市污水处理过程进水负荷多变,运行过程存在多种工况且变化频繁,导致城市污水处理过程难以实现优化运行.因此,如何设计优化控制策略应对多种工况变化,保证出水总氮和出水总磷等水质指标达标,是城市污水处理过程亟需解决的挑战性问题.本文设计了基于领域自适应的城市污水处理运行过程多工况优化控制方法(multi-operating optimization control with domain adaptive,MOOC-DA).首先,建立城市污水处理运行过程多工况优化目标模型,捕获运行能耗以及出水水质的时间序列特性,实现运行指标的精确预测.其次,设计基于多任务领域自适应粒子群的多工况优化设定方法,保证多工况运行出水水质达标.最后,设计基于多任务模糊神经网络的优化设定跟踪控制方法,实现城市污水处理过程多工况优化运行.为了验证所提出方法的有效性,基于活性污泥模型仿真平台将提出的MOOC-DA与其他优化控制方法进行对比实验.结果表明,该方法能够实现污水处理过程多工况的优化运行,保证出水总氮和出水总磷等水质指标达标.
