We developed an upper-limb power-assist exoskeleton actuated by pneumatic muscles. The exoskeleton included two metal links: a nylon joint, four size-adjustable carbon fiber bracers, a potentiometer and two pneumatic muscles. The proportional myoelectric control method was proposed to control the exoskeleton according to the user's motion intention in real time. With the feature extraction procedure and the classification (back-propagation neural network), an electromyogram (EMG)-angle model was constructed to be used for pattern recognition. Six healthy subjects performed elbow flexion-extension movements under four experimental conditions: (1) holding a 1-kg load, wearing the exoskeleton, but with no actuation and for different periods (2-s, 4-s and 8-s periods); (2) holding a 1-kg load, without wearing the exoskeleton, for a fixed period; (3) holding a 1-kg load, wearing the exoskeleton, but with no actuation, for a fixed period; (4) holding a 1-kg load, wearing the exoskeleton under proportional myoelectric control, for a fixed period. The EMG signals of the biceps brachii, the brachioradialis, the triceps brachii and the anconeus and the angle of the elbow were collected. The control scheme's reliability and power-assist effectiveness were evaluated in the experiments. The results indicated that the exoskeleton could be controlled by the user's motion intention in real time and that it was useful for augmenting arm performance with neurological signal control, which could be applied to assist in elbow rehabilitation after neurological injury.

External stimulation, mood swing, and physiological arousal are closely related and induced by each other. The exploration of internal relations between these three aspects is interesting and significant. Currently, video is the most popular multimedia stimuli that can express rich emotional semantics by its visual and auditory features. Apart from the video features, human electroencephalography (EEG) features can provide useful information for video emotion recognition, as they are the direct and instant authentic feedback on human perception with individuality. In this paper, we collected a total of 39 participants' EEG data induced by watching emotional video clips and built a fusion dataset of EEG and video features. Subsequently, the machine-learning algorithms, including Liblinear, REPTree, XGBoost, MultilayerPerceptron, RandomTree, and RBFNetwork were applied to obtain the optimal model for video emotion recognition based on a multi-modal dataset. We discovered that using the data fusion of all-band EEG power spectrum density features and video audio-visual features can achieve the best recognition results. The video emotion classification accuracy achieves 96.79% for valence (Positive/Negative) and 97.79% for arousal (High/Low).The study shows that this method can be a potential method of video emotion indexing for video information retrieval.

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Objectives Much of the information to date in terms of subtypes and function of bladder urothelial cells were derived from anatomical location or by the expression of a small number of marker genes. To have a comprehensive map of the cellular anatomy of bladder urothelial cells, we performed single‐cell RNA sequencing to thoroughly characterize mouse bladder urothelium. Materials and methods A total of 18,917 single cells from mouse bladder urothelium were analysed by unbiased single‐cell RNA sequencing. The expression of the novel cell marker was confirmed by immunofluorescence using urinary tract infection models. Results Unsupervised clustering analysis identified 8 transcriptionally distinct cell subpopulations from mouse bladder urothelial cells. We discovered a novel type of bladder urothelial cells marked by Plxna4 that may be involved with host response and wound healing. We also found a group of basal‐like cells labelled by ASPM that could be the progenitor cells of adult bladder urothelium. ASPM+ urothelial cells are significantly increased after injury by UPEC. In addition, specific transcription factors were found to be associated with urothelial cell differentiation. At the last, a number of interstitial cystitis/bladder pain syndrome–regulating genes were found differentially expressed among different urothelial cell subpopulations. Conclusions Our study provides a comprehensive characterization of bladder urothelial cells, which is fundamental to understanding the biology of bladder urothelium and associated bladder disease.

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