Testing the hypothesis that the lateral cerebellum forms a sensory representation of arm movements, we investigated cortical neuronal activity in two monkeys performing visually guided step-tracking movements with a manipulandum. A virtual target and cursor image were viewed co-planar with the manipulandum. In the normal task, manipulandum and cursor moved in the same direction; in the mirror task, the cursor was left-right reversed. In one monkey, 70- and 200-ms time delays were introduced on cursor movement. Significant task-related activity was recorded in 31 cells in one animal and 142 cells in the second: 10.2% increased activity before arm movements onset, 77.1% during arm movement, and 12.7% after the new position was reached. To test for neural representation of the visual outcome of movement, firing rate modulation was compared in normal and mirror step-tracking. Most task-related neurons (68%) showed no significant directional modulation. Of 70 directionally sensitive cells, almost one-half (n = 34, 48%) modulated firing with a consistent cursor movement direction, many fewer responding to the manipulandum direction (n = 9, 13%). For those "cursor-related" cells tested with delayed cursor movement, increased activity onset was time-locked to arm movement and not cursor movement, but activation duration was extended by an amount similar to the applied delay. Hence, activity returned to baseline about when the delayed cursor reached the target. We conclude that many cells in the lateral cerebellar cortex signaled the direction of cursor movement during active step-tracking. Such a predictive representation of the arm movement could be used in the guidance of visuo-motor actions.

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Aiming at the anomaly detection problem in sensor data, traditional algorithms usually only focus on the continuity of single-source data and ignore the spatiotemporal correlation between multisource data, which reduces detection accuracy to a certain extent. Besides, due to the rapid growth of sensor data, centralized cloud computing platforms cannot meet the real-time detection needs of large-scale abnormal data. In order to solve this problem, a real-time detection method for abnormal data of IoT sensors based on edge computing is proposed. Firstly, sensor data is represented as time series; K-nearest neighbor (KNN) algorithm is further used to detect outliers and isolated groups of the data stream in time series. Secondly, an improved DBSCAN (Density Based Spatial Clustering of Applications with Noise) algorithm is proposed by considering spatiotemporal correlation between multisource data. It can be set according to sample characteristics in the window and overcomes the slow convergence problem using global parameters and large samples, then makes full use of data correlation to complete anomaly detection. Moreover, this paper proposes a distributed anomaly detection model for sensor data based on edge computing. It performs data processing on computing resources close to the data source as much as possible, which improves the overall efficiency of data processing. Finally, simulation results show that the proposed method has higher computational efficiency and detection accuracy than traditional methods and has certain feasibility.

As the spiritual implication of socialist rule of law with Chinese characteristics, legal belief is an important value support for the construction of the rule of law in China. However, the cultivation of legal beliefs carried out nowadays is hindered by many factors, which in turn affects the belief of the whole society in law. Wherein, the deviation of citizens' cognition on law, the problems existing in the operation process of current laws, the citizens' obligation-based consciousness under the influence of the "rule of man" in traditional Chinese society, and the national psychological habits against the background of human relationship society all bring challenges to the cultivation of contemporary Chinese legal beliefs. Therefore, having a deep understanding of several factors that hinder the cultivation of contemporary Chinese legal beliefs has important theoretical value in cultivating and guiding citizens to have a sincere belief in law. Keywords-socialist rule of law; legal belief; rule of man; obligation-based consciousness *Fund: This paper is a phased research result of the Shanghai Higher Education Society Planning Fund Project hosted by Xuguang Liu: "Research on Boosting Xi Jinping's 'Three Accesses (Incorporating into textbook, bringing into classroom and entering into students' mind)" Thoughts of Socialism with Chinese Characteristics in the New Era by Means of New Media Micro-course: Taking the Course of 'Ideological and Moral Cultivation and the Basis of Law' as an Example (Project No.: GJEL1870)".