How Robust is Federated Learning to Communication Error? A Comparison Study Between Uplink and Downlink Channels

Because of its privacy-preserving capability, federated learning (FL) has attracted significant attention from both academia and industry. However, when being implemented over wireless networks, it is not clear how much communication error can be tolerated by FL. This paper investigates the robustness of FL to the uplink and downlink communication error. Our theoretical analysis reveals that the robustness depends on two critical parameters, namely the number of clients and the numerical range of model parameters. It is also shown that the uplink communication in FL can tolerate a higher bit error rate (BER) than downlink communication, and this difference is quantified by a proposed formula. The findings and theoretical analyses are further validated by extensive experiments.Comment: Submitted to IEEE for possible publicatio

Rescue of mesangial cells from high glucoseinduced over-proliferation and extracellular matrix secretion by hydrogen sulfide

Abstract Background. Hydrogen sulfide (H 2 S) is considered as the third gasotransmitter after nitric oxide and carbon monoxide. This gas molecule participates in the regulation of renal function. Diabetic nephropathy (DN) is one of the major chronic complications of diabetes. The present study aimed to explore the changes in H 2 S metabolism in the early stage of DN and the effects of H 2 S on cultured rat renal glomerular mesangial cells (MCs). Methods. Cultured rat MCs and streptozotocin (STZ)-induced diabetic rats were used in this study. Expression levels of cystathionine γ-lyase (CSE), transforming growth factor-β1 (TGF-β1) and collagen IV in rat renal cortex and in cultured MCs were determined by quantitative real-time PCR and western blot. Reactive oxygen species (ROS) released from rat MCs was assessed by fluorescent probe assays. MCs proliferation was analyzed by 5′-bromo-2′-deoxyuridine incorporation assay. Results. H 2 S levels in the plasma and renal cortex and the levels of CSE messenger RNA (mRNA) and protein in renal cortex were significantly reduced, while the levels of TGF-β1 and collagen IV increased 3 weeks after STZ injection. Administration of NaHS, a H 2 S donor, reversed the increases in TGF-β1 and collagen IV in diabetic rats. By contrast, NaHS did not alter the TGF-β1 and collagen IV levels in non-diabetic rats. But NaHS lowered the CSE mRNA level in renal cortex. Exposure to high glucose promoted ROS generation and cell proliferation, up-regulated the expression of TGF-β1 and collagen IV but decreased the CSE expression in cultured MCs. Treatment of cultured MCs with NaHS reversed the effect of high glucose. NaHS did not change ROS generation, cell proliferation, TGF-β1 and collagen IV expression in the cells cultured with normal glucose. Reduction of endogenous H 2 S generation by DLpropargylglycine, a CSE inhibitor, produced similar cellular effects as high glucose, including increases in cell proliferation, TGF-β1 and collagen IV expressions and ROS generation. Conclusion. Suppressed CSE-catalyzed endogenous H 2 S production in the kidney by hyperglycemia may play an important role in the pathogenesis of DN

Tax-Scheduler: An interactive visualization system for staff shifting and scheduling at tax authorities

Given a large number of applications and complex processing procedures, how to efficiently shift and schedule tax officers to provide good services to taxpayers is now receiving more attention from tax authorities. The availability of historical application data makes it possible for tax managers to shift and schedule staff with data support, but it is unclear how to properly leverage the historical data. To investigate the problem, this study adopts a user-centered design approach. We first collect user requirements by conducting interviews with tax managers and characterize their requirements of shifting and scheduling into time series prediction and resource scheduling problems. Then, we propose Tax-Scheduler, an interactive visualization system with a time-series prediction algorithm and genetic algorithm to support staff shifting and scheduling in the tax scenarios. To evaluate the effectiveness of the system and understand how non-technical tax managers react to the system with advanced algorithms and visualizations, we conduct user interviews with tax managers and distill several implications for future system design