YTHDF3 phase separation regulates HSPA13-dependent clear cell renal cell carcinoma development and immune evasion.

Insufficient understanding about the immune evasion mechanism leads to the inability in predicting current immunotherapy effects in clear cell renal cell carcinoma (ccRCC) and sensitizing ccRCC to immunotherapy. RNA binding proteins (RBPs) can promote tumor progression and immune evasion. However, research on RBPs, particularly m6A reader YTHDF3, in ccRCC development and immune evasion is limited.

Cross-View Approximation on Grassmann Manifold for Multiview Clustering.

In existing multiview clustering research, the comprehensive learning from multiview graph and feature spaces simultaneously remains insufficient when achieving a consistent clustering structure. In addition, a postprocessing step is often required. In light of these considerations, a cross-view approximation on Grassman manifold (CAGM) model is proposed to address inconsistencies within multiview adjacency matrices, feature matrices, and cross-view combinations from the two sources.

Bidirectional Probabilistic Subspaces Approximation for Multiview Clustering.

The existing multiview clustering models learn a consistent low-dimensional embedding either from multiple feature matrices or multiple similarity matrices, which ignores the interaction between the two procedures and limits the improvement of clustering performance on multiview data. To address this issue, a bidirectional probabilistic subspaces approximation (BPSA) model is developed in this article to learn a consistently orthogonal embedding from multiple feature matrices and multiple similarity matrices simultaneously via the disturbed probabilistic subspace modeling and approximation. A skillful bidirectional fusion strategy is designed to guarantee the parameter-free property of the BPSA model.

Adaptive variable impedance control of dual-arm robots for slabstone installation.

The conventional dual-arm cooperative control method employed in the construction field cannot adequately meet the requirements of high precision and adaptability because of the use of large objects, heavy load, unstructured environment, and constraints related to the complex operation processes involved. Dual-arm robots are highly complex multi-degree-of-freedom system, and when using this robots for slabstone installation, it is necessary to consider not only the position constraint and force coupling relationship of the closed chain system, but also the force/position control while the slabstone contacts the wall. To solve this problem, this paper presents slabstone-installation model and motion element decomposition for dual-arm robots.

Practical Prescribed Time Control of Euler-Lagrange Systems With Partial/Full State Constraints: A Settling Time Regulator-Based Approach.

Many important engineering applications involve control design for Euler-Lagrange (EL) systems. In this article, the practical prescribed time tracking control problem of EL systems is investigated under partial or full state constraints. A settling time regulator is introduced to construct a novel performance function, with which a new neural adaptive control scheme is developed to achieve pregiven tracking precision within the prescribed time.

The optimized algorithm based on machine learning for inverse kinematics of two painting robots with non-spherical wrist.

This paper studies the inverse kinematics of two non-spherical wrist configurations of painting robot. The simplest analytical solution of orthogonal wrist configuration is deduced in this paper for the first time. For the oblique wrist configuration, there is no analytical solution for the configuration.

A novel method of combining generalized frequency response function and convolutional neural network for complex system fault diagnosis.

To solve the problem of low accuracy in traditional fault diagnosis methods, a novel method of combining generalized frequency response function(GFRF) and convolutional neural network(CNN) is proposed. In order to accurately characterize system state information, this paper proposed a variable step size least mean square (VSSLMS) adaptive algorithm to calculate the second-order GFRF spectrum values under normal and fault states; In order to improve the ability of fault feature extraction, a convolution neural network (CNN) with gradient descent learning rate and alternate convolution layer and pooling layer is designed to extract the fault features from GFRF spectrum. In the proposed method, the second-order GFRF spectrum of each state of Permanent Magnet Synchronous Motor (PMSM) is obtained by VSSLMS; Then, the two-dimension GFRF spectrum, which is regarded as the gray value of the image,will be further transformed into image.

An efficient estimation of distribution algorithm with rank-one modification and population reduction.

As a type of model-based metaheuristic, estimation of distribution algorithms (EDAs) show certain advantages over other metaheuristics by using statistical learning method to estimate the distribution of promising solutions. However, the commonly-used Gaussian EDAs (GEDAs) usually suffer from premature convergence that severely limits their efficiency. In this paper, we first attempt to enhance the performance of GEDA by improving its model estimation method.