Filling the Missing: Exploring Generative AI for Enhanced Federated Learning over Heterogeneous Mobile Edge Devices

Distributed Artificial Intelligence (AI) model training over mobile edge networks encounters significant challenges due to the data and resource heterogeneity of edge devices. The former hampers the convergence rate of the global model, while the latter diminishes the devices' resource utilization efficiency. In this paper, we propose a generative AI-empowered federated learning to address these challenges by leveraging the idea of FIlling the MIssing (FIMI) portion of local data. Specifically, FIMI can be considered as a resource-aware data augmentation method that effectively mitigates the data heterogeneity while ensuring efficient FL training. We first quantify the relationship between the training data amount and the learning performance. We then study the FIMI optimization problem with the objective of minimizing the device-side overall energy consumption subject to required learning performance constraints. The decomposition-based analysis and the cross-entropy searching method are leveraged to derive the solution, where each device is assigned suitable AI-synthesized data and resource utilization policy. Experiment results demonstrate that FIMI can save up to 50% of the device-side energy to achieve the target global test accuracy in comparison with the existing methods. Meanwhile, FIMI can significantly enhance the converged global accuracy under the non-independently-and-identically distribution (non-IID) data.Comment: 13 pages, 5 figures. Submitted to IEEE for possible publicatio

Field Emission Properties and Fabrication of CdS Nanotube Arrays

A large area arrays (ca. 40 cm2) of CdS nanotube on silicon wafer are successfully fabricated by the method of layer-by-layer deposition cycle. The wall thicknesses of CdS nanotubes are tuned by controlling the times of layer-by-layer deposition cycle. The field emission (FE) properties of CdS nanotube arrays are investigated for the first time. The arrays of CdS nanotube with thin wall exhibit better FE properties, a lower turn-on field, and a higher field enhancement factor than that of the arrays of CdS nanotube with thick wall, for which the ratio of length to the wall thickness of the CdS nanotubes have played an important role. With increasing the wall thickness of CdS nanotube, the enhancement factorβdecreases and the values of turn-on field and threshold field increase

Effect of Aspect Ratio on Field Emission Properties of ZnO Nanorod Arrays

ZnO nanorod arrays are prepared on a silicon wafer through a multi-step hydrothermal process. The aspect ratios and densities of the ZnO nanorod arrays are controlled by adjusting the reaction times and concentrations of solution. The investigation of field emission properties of ZnO nanorod arrays revealed a strong dependency on the aspect ratio and their density. The aspect ratio and spacing of ZnO nanorod arrays are 39 and 167 nm (sample C), respectively, to exhibit the best field emission properties. The turn-on field and threshold field of the nanorod arrays are 3.83 V/μm and 5.65 V/μm, respectively. Importantly, the sample C shows a highest enhancement of factorβ, which is 2612. The result shows that an optimum density and aspect ratio of ZnO nanorod arrays have high efficiency of field emission

Ultra-Sensitivity Glucose Sensor Based on Field Emitters

A new glucose sensor based on field emitter of ZnO nanorod arrays (ZNA) was fabricated. This new type of ZNA field emitter-based sensor shows high sensitivity with experimental limit of detection of 1 nM glucose solution and a detection range from 1 nM to 50 μM in air at room temperature, which is lower than that of glucose sensors based on surface plasmon resonance spectroscopy, fluorescence signal transmission, and electrochemical signal transduction. The new glucose sensor provides a key technique for promising consuming application in biological system for detecting low levels of glucose on single cells or bacterial cultures

Arctic introgression and chromatin regulation facilitated rapid Qinghai-Tibet Plateau colonization by an avian predator

The Qinghai-Tibet Plateau (QTP), possesses a climate as cold as that of the Arctic, and also presents uniquely low oxygen concentrations and intense ultraviolet (UV) radiation. QTP animals have adapted to these extreme conditions, but whether they obtained genetic variations from the Arctic during cold adaptation, and how genomic mutations in non-coding regions regulate gene expression under hypoxia and intense UV environment, remain largely unknown. Here, we assemble a high-quality saker falcon genome and resequence populations across Eurasia. We identify female-biased hybridization with Arctic gyrfalcons in the last glacial maximum, that endowed eastern sakers with alleles conveying larger body size and changes in fat metabolism, predisposing their QTP cold adaptation. We discover that QTP hypoxia and UV adaptations mainly involve independent changes in non-coding genomic variants. Our study highlights key roles of gene flow from Arctic relatives during QTP hypothermia adaptation, and cis-regulatory elements during hypoxic response and UV protection