The role of ATP6V0D2 in breast cancer: associations with prognosis, immune characteristics, and TNBC progression.

Objective: Researches have identified ATPase H+ transporting V0 subunit d2 (ATP6V0D2) as a significant factor in various cancers. However, its prognostic value in breast cancer (BRCA) and its biological role in BRCA cells remain unclear.

Methods: In this research, we examined the varying expression levels of ATP6V0D2 in both BRCA and normal breast tissue by utilizing information derived from databases including the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), along with clinical samples.

Adjustable Ultra-Light Mechanical Negative Poisson's Ratio Metamaterials with Multi-Level Dynamic Crushing Effects.

Mechanical metamaterials with multi-level dynamic crushing effects (MM-MLs) are designed in this study through coordinate transformation and mirror arrays. The mechanical effects of the diameter and length ratio of the struts and connecting rods, the Euler angles, and the cell numbers on the mechanical properties are investigated separately. MM-ML can exhibit significant two-level platform stress, and the local cells in the first platform stress stage undergo rotational motion, while the second platform stress stage mainly involves collapse compression and bending.

Optimal Output Consensus of Heterogeneous Linear Multiagent Systems Over Weight-Unbalanced Directed Networks.

This article investigates the distributed optimal output consensus problem of heterogeneous linear multiagent systems over weight-unbalanced directed networks. A novel distributed continuous-time state feedback controller is proposed to steer the outputs of all the agents to converge to the optimal solution of the global cost function. Under the standard condition that the unbalanced digraph is strongly connected and the local cost functions are strongly convex with global Lipschitz gradients, the exponential convergence of the closed-loop multiagent system is established.

Cooperative line-of-sight guidance with optimal evasion strategy for three-body confrontation.

This paper focuses on the three-body confrontation problem of a Target-Defender team against an Attacker possessing greater maneuverability. Based on the input-to-state stability approach, a cooperative robust line-of-sight guidance law is proposed for the Target-Defender team to ensure that the Attacker has a certain tolerance range on the unavailable guidance information. In addition, the optimal evasion strategy is developed for the Target to maximize the terminal distance between the Target and Attacker.

Distributed Nash Equilibrium Seeking for Aggregative Games With Nonlinear Dynamics Under External Disturbances.

In this paper, we study the distributed Nash equilibrium (NE) seeking problem for a class of aggregative games with players described by uncertain perturbed nonlinear dynamics. To seek the NE, each player needs to construct a distributed algorithm based on information of its cost function and the exchanging information obtained from its neighbors. By combining the internal model principle and the average consensus technique, we propose a distributed gradient-based algorithm for the players.

LncRNA BE503655 inhibits osteosarcoma cell proliferation, invasion/migration via Wnt/β-catenin pathway.

In previous studies, numerous dysregulated long non-coding RNAs (lncRNAs) were identified by RNA-sequencing (RNA-seq). However, the relationship between lncRNA and osteosarcoma remains unclear. In the present study, the function and mechanism of lncRNA BE503655 were investigated.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m.

Guidance laws with input saturation and nonlinear robust H∞ observers.

A novel three-dimensional law based on input-to-state stability (ISS) and nonlinear robust H∞ filtering is proposed for interception of maneuvering targets in the presence of input saturation. A dead zone operator model is introduced to design an ISS-based guidance law to guarantee robust tracking of a maneuvering target. Input saturation and system stability are considered simultaneously, and the globally input-to-state stability have been ensured in theory.

Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection.

The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree.