Results 211 to 220 of about 1,432,944 (317)
Research on a New Singularity-Free Controller for Uncertain Lorenz System [PDF]
Yuhuan Chen, Chenfu Yi
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A Microbiota‐ and IL‐15‐Dependent Innate‐Like B Cell Progenitor Expressing E4BP4
This work identifies CD3.NKp46.CD19.NK1.1. NK‐B cells enriched in PDK1‐deficient yet present in wild‐type bone marrow. IL‐15 (via CD122) and TLR9‐microbiota signaling maintain their E4BP4 expression. These cells demonstrate innate immunity, preferentially differentiate into B cells, and unveil a novel microbiota‐ and IL‐15‐dependent regulatory pathway ...
Junming He +11 more
wiley +1 more source
Robust detection framework for adversarial threats in Autonomous Vehicle Platooning. [PDF]
Ness S.
europepmc +1 more source
Adaptive Sliding Mode Control for A 2 DOF Magnetic Levitation System with Uncertain Parameters
Meng Duan, Yingmin Jia
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FPD‐GELNs co‐deliver Su and bioactive components. This active‐passive dual‐targeting strategy suppresses the progression of RCC through the following mechanisms: 1) inhibition of the PI3K‐Akt signaling pathway; 2) downregulation of ABCB1/P‐gp to enhance the chemosensitivity of RCC to Su; and 3) reprogramming of macrophages toward M1 polarization and ...
Haoyu Xu +8 more
wiley +1 more source
Multi-constraint model predictive control of flexible joint drive system based on unknown state estimator and constraint adaptive hierarchical planning. [PDF]
Song C, Du Q, Guo X.
europepmc +1 more source
Identifying disease‐causing genes in neurocognitive disorders remains challenging due to variants of uncertain significance. CLinNET employs dual‐branch neural networks integrating Reactome pathways and Gene Ontology terms to provide pathway‐level interpretability of genomic alterations.
Ivan Bakhshayeshi +5 more
wiley +1 more source
Prescribed-Time Leader-Follower Synchronization of Higher-Order Nonlinear Multi-Agent Systems via Fuzzy Neural Adaptive Sliding Control. [PDF]
Ullah S +5 more
europepmc +1 more source
Fully uncertain linear systems
Qing Yang, Yuanguo Zhu
openaire +1 more source
Extremum seeking control of uncertain systems
Extremum seeking is used in control problems where the reference trajectory or reference set point of the system is not known but it is searched in real time in order to maximize or minimize a performance function representing the optimal behaviour of the system.
openaire +2 more sources

