Over-the-air Federated Policy Gradient

In recent years, over-the-air aggregation has been widely considered in large-scale distributed learning, optimization, and sensing. In this paper, we propose the over-the-air federated policy gradient algorithm, where all agents simultaneously broadcast an analog signal carrying local information to a common wireless channel, and a central controller uses the received aggregated waveform to update the policy parameters. We investigate the effect of noise and channel distortion on the convergence of the proposed algorithm, and establish the complexities of communication and sampling for finding an $\epsilon$-approximate stationary point. Finally, we present some simulation results to show the effectiveness of the algorithm

A Differential Private Method for Distributed Optimization in Directed Networks via State Decomposition

In this paper, we study the problem of consensus-based distributed optimization where a network of agents, abstracted as a directed graph, aims to minimize the sum of all agents' cost functions collaboratively. In existing distributed optimization approaches (Push-Pull/AB) for directed graphs, all agents exchange their states with neighbors to achieve the optimal solution with a constant stepsize, which may lead to the disclosure of sensitive and private information. For privacy preservation, we propose a novel state-decomposition based gradient tracking approach (SD-Push-Pull) for distributed optimzation over directed networks that preserves differential privacy, which is a strong notion that protects agents' privacy against an adversary with arbitrary auxiliary information. The main idea of the proposed approach is to decompose the gradient state of each agent into two sub-states. Only one substate is exchanged by the agent with its neighbours over time, and the other one is kept private. That is to say, only one substate is visible to an adversary, protecting the privacy from being leaked. It is proved that under certain decomposition principles, a bound for the sub-optimality of the proposed algorithm can be derived and the differential privacy is achieved simultaneously. Moreover, the trade-off between differential privacy and the optimization accuracy is also characterized. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed approach

LQG Control Over SWIPT-enabled Wireless Communication Network

In this paper, we consider using simultaneous wireless information and power transfer (SWIPT) to recharge the sensor in the LQG control, which provides a new approach to prolonging the network lifetime. We analyze the stability of the proposed system model and show that there exist two critical values for the power splitting ratio {\alpha}. Then, we propose an optimization problem to derive the optimal value of {\alpha}. This problem is non-convex but its numerical solution can be derived by our proposed algorithm efficiently. Moreover, we provide the feasible condition of the proposed optimization problem. Finally, simulation results are presented to verify and illustrate the main theoretical results

Distributed Average Consensus via Noisy and Non-Coherent Over-the-Air Aggregation

Over-the-air aggregation has attracted widespread attention for its potential advantages in task-oriented applications, such as distributed sensing, learning, and consensus. In this paper, we develop a communication-efficient distributed average consensus protocol by utilizing over-the-air aggregation, which exploits the superposition property of wireless channels rather than combat it. Noisy channels and non-coherent transmission are taken into account, and only half-duplex transceivers are required. We prove that the system can achieve average consensus in mean square and even almost surely under the proposed protocol. Furthermore, we extend the analysis to the scenarios with time-varying topology. Numerical simulation shows the effectiveness of the proposed protocol

Differentially Private Dual Gradient Tracking for Distributed Resource Allocation

This paper investigates privacy issues in distributed resource allocation over directed networks, where each agent holds a private cost function and optimizes its decision subject to a global coupling constraint through local interaction with other agents. Conventional methods for resource allocation over directed networks require all agents to transmit their original data to neighbors, which poses the risk of disclosing sensitive and private information. To address this issue, we propose an algorithm called differentially private dual gradient tracking (DP-DGT) for distributed resource allocation, which obfuscates the exchanged messages using independent Laplacian noise. Our algorithm ensures that the agents' decisions converge to a neighborhood of the optimal solution almost surely. Furthermore, without the assumption of bounded gradients, we prove that the cumulative differential privacy loss under the proposed algorithm is finite even when the number of iterations goes to infinity. To the best of our knowledge, we are the first to simultaneously achieve these two goals in distributed resource allocation problems over directed networks. Finally, numerical simulations on economic dispatch problems within the IEEE 14-bus system illustrate the effectiveness of our proposed algorithm

Self-assembly of a silicon-containing side-chain liquid crystalline block copolymer in bulk and in thin films: kinetic pathway of a cylinder to sphere transition

The self-assembly of a high-χ silicon-containing side-chain liquid crystalline block copolymer (LC BCP) in bulk and in thin films is reported, and the structural transition process from the hexagonally packed cylinder (HEX) to the body-centered cubic structure (BCC) in thin films was examined by both reciprocal and real space experimental methods. The block copolymer, poly(dimethylsiloxane-b-11-(4′-cyanobiphenyl-4-yloxy)undecylmethacrylate) (PDMS-b-P(4CNB11C)MA) with a molecular weight of 19.5 kg mol−1 and a volume fraction of PDMS 27% self-assembled in bulk into a hierarchical nanostructure of sub-20 nm HEX cylinders of PDMS with the P(4CNB11C)MA block exhibiting a smectic LC phase with a 1.61 nm period. The structure remained HEX as the P(4CNB11C)MA block transformed to an isotropic phase at ∼120 °C. In the thin films, the PDMS cylindrical microdomains were oriented in layers parallel to the substrate surface. The LC block formed a smectic LC phase which transformed to an isotropic phase at ∼120 °C, and the microphase-separated nanostructure transformed from HEX to BCC spheres at ∼160 °C. The hierarchical structure as well as the dynamic structural transition of the thin films were characterized using in situ grazing-incidence small-angle X-ray scattering and grazing-incidence wide-angle X-ray scattering. The transient morphologies from the HEX to BCC structure in thin films were captured by scanning electron microscopy and atomic force microscopy, and the transition pathway was described.National Science Foundation (U.S.) (DMR-1606911)National Natural Science Foundation (China) (Grant 51403132)National Natural Science Foundation (China) (Grant 51773124

Psoralen Induces Developmental Toxicity in Zebrafish Embryos/Larvae Through Oxidative Stress, Apoptosis, and Energy Metabolism Disorder

Psoralen toxicity is an issue of wide concern. However, an assay for psoralen-induced developmental toxicity has not been reported to date. Moreover, the underlying mechanism of psoralen-induced developmental toxicity is unclear. Therefore, this study attempted to develop a psoralen-induced developmental toxicity assay in zebrafish embryos/larvae. Psoralen treatment caused a decrease in the hatching rate and body length and a significant increase in the malformation rate of zebrafish. Yolk retention, pericardial edema, swim-bladder deficiency, and curved body shape were also observed after psoralen treatment. Yolk retention might have been caused by an abnormality in lipid metabolism. Further experiments indicated that psoralen exerted toxic effects on the developing heart, liver, phagocytes, and nervous system. Increased generation of reactive oxygen species, inhibition of total superoxide dismutase activity, and increased malondialdehyde concentrations indicated inhibition of antioxidant capacity and the presence of oxidative stress. A greater number of apoptotic cells were observed after psoralen exposure, relative to the control. Furthermore, the results of gene-expression analysis showed that psoralen induced developmental toxicity by means of oxidative stress, apoptosis, and energy metabolism abnormalities. These findings will be helpful in understanding psoralen-induced toxicity