Abstract: The present disclosure provides methods and systems for identifying transcriptional regulatory modules (e.g., in non-coding portions of the genome), predicting gene regulation and expression, e.g., effects of non-coding mutations or chromosome rearrangements on the regulation and expression of the target genes, and designing and using modified regulatory sequences.

Abstract: Disclosed herein is a system for gait training and a method of gait training. The system includes a gait prediction module configured to: using a two-stage machine learning model, extract gait features from EEG signals acquired from a subject; and determine a predicted gait based on the gait features, wherein the two-stage machine learning model includes multiple first stage blocks and multiple second stage blocks, the first stage blocks and the second stage blocks being trained based on different gait data obtained solely from the subject at different time points, wherein at least one of the second stage blocks is a feature extractor block, each of the feature extractor block corresponding to respective ones of the first stage blocks.

Abstract: A method for quantitatively evaluating the anisotropy of joint roughness coefficient of rock joints is provided, comprising the following steps: selecting a joint sample of an engineering rock mass to be analyzed; uniformly arranging rock joint measurement segments in different orientations; recording each joint profile by a profilograph; measuring joint roughness coefficient of each measurement segment; calculating a statistical mean value of the joint roughness coefficients in each orientation under same dimensional conditions, and obtaining a roughness coefficient class ratio in each orientation; transforming each item in the roughness coefficient class ratio by R1(i)=r0(i)1/m; fitting the processed roughness coefficient of the rock joints by anisotropic ellipse function; determining a major axis a and a minor axis b of the anisotropic ellipse, ? representing a direction of rotation, where a ratio of the major axis to the minor axis indicates a difference between the maximum roughness coefficient and the m