Implicit Tracking-based Distributed Constraint-coupled Optimization

A class of distributed optimization problem with a globally coupled equality constraint and local constrained sets is studied in this paper. For its special case where local constrained sets are absent, an augmented primal-dual gradient dynamics is proposed and analyzed, but it cannot be implemented distributedly since the violation of the coupled constraint needs to be used. Benefiting from the brand-new comprehending of a classical distributed unconstrained optimization algorithm, the novel implicit tracking approach is proposed to track the violation distributedly, which leads to the birth of the \underline{i}mplicit tracking-based \underline{d}istribut\underline{e}d \underline{a}ugmented primal-dual gradient dynamics (IDEA). A projected variant of IDEA, i.e., Proj-IDEA, is further designed to deal with the general case where local constrained sets exist. With the aid of the Lyapunov stability theory, the convergences of IDEA and Pro-IDEA over undigraphs and digraphs are analyzed respectively. As far as we know, Proj-IDEA is the first constant step-size distributed algorithm which can solve the studied problem without the need of the strict convexity of local cost functions. Besides, if local cost functions are strongly convex and smooth, IDEA can achieve exponential convergence with a weaker condition about the coupled constraint. Finally, numerical experiments are taken to corroborate our theoretical results.Comment: in IEEE Transactions on Control of Network Systems, 202

Coordinated Control and Estimation of Multiagent Systems with Engineering Applications

Recently, coordinated control and estimation problems have attracted a great deal of attention in different fields especially in biology, physics, computer science, and control engineering. Coordinated control and estimation problems have prominent characteristics of distributed control, local interaction, and self-organization. Research on multiagent coordinated control and estimation problems not only helps better understand the mechanisms of natural collective phenomena but also benefits the applications of cyberphysical systems. This special issue focuses on theoretical and technological achievements in cooperative multiagent Systems. It contains twenty-six papers, the contents of which are summarized below

Adaptive Synchronization of Complex Dynamical Networks Governed by Local Lipschitz Nonlinearlity on Switching Topology

This paper investigates the adaptive synchronization of complex dynamical networks satisfying the local Lipschitz condition with switching topology. Based on differential inclusion and nonsmooth analysis, it is proved that all nodes can converge to the synchronous state, even though only one node is informed by the synchronous state via introducing decentralized adaptive strategies to the coupling strengths and feedback gains. Finally, some numerical simulations are worked out to illustrate the analytical results

MicroRNA-encoding long non-coding RNAs

© 2008 He et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Excessive transcription-replication conflicts are a vulnerability of BRCA1-mutant cancers

BRCA1 mutations are associated with increased breast and ovarian cancer risk. BRCA1-mutant tumors are high-grade, recurrent, and often become resistant to standard therapies. Herein, we performed a targeted CRISPR-Cas9 screen and identified MEPCE, a methylphosphate capping enzyme, as a synthetic lethal interactor of BRCA1. Mechanistically, we demonstrate that depletion of MEPCE in a BRCA1-deficient setting led to dysregulated RNA polymerase II (RNAPII) promoter-proximal pausing, R-loop accumulation, and replication stress, contributing to transcription-replication collisions. These collisions compromise genomic integrity resulting in loss of viability of BRCA1-deficient cells. We also extend these findings to another RNAPII-regulating factor, PAF1. This study identifies a new class of synthetic lethal partners of BRCA1 that exploit the RNAPII pausing regulation and highlight the untapped potential of transcription-replication collision-inducing factors as unique potential therapeutic targets for treating cancers associated with BRCA1 mutations

Nested Primal-dual Gradient Algorithms for Distributed Constraint-coupled Optimization

We study a class of distributed optimization problems with a globally coupled equality constraint. A novel nested primal-dual gradient algorithm (NPGA) is proposed from the dual perspective, which can achieve linear convergence under a quite weak condition. Furthermore, the upper bounds of the step-sizes and the converge rate are explicitly given. It is worth noting that NPGA is not only an algorithm but also an algorithmic framework. By choosing different parameter matrices, we can obtain many different versions of NPGA, which offers us a chance to design more efficient algorithms. Finally, the convergence rates of NPGA and existing algorithms are compared in numerical experiments

Pinning control of complex networked systems: synchronization, consensus and flocking of networked systems via pinning

Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Control Science and Engineering, Huazhong University of Science and Technology, China; Xiaofan Wang is a Professor at the Department of Automation, Shanghai Jiao Tong University, China