Indefinite linearized augmented Lagrangian method for convex programming with linear inequality constraints

The augmented Lagrangian method (ALM) is a benchmark for tackling the convex optimization problem with linear constraints; ALM and its variants for linearly equality-constrained convex minimization models have been well studied in the literatures. However, much less attention has been paid to ALM for efficiently solving the linearly inequality-constrained convex minimization model. In this paper, we exploit an enlightening reformulation of the most recent indefinite linearized (equality-constrained) ALM, and present a novel indefinite linearized ALM scheme for efficiently solving the convex optimization problem with linear inequality constraints. The proposed method enjoys great advantages, especially for large-scale optimization cases, in two folds mainly: first, it significantly simplifies the optimization of the challenging key subproblem of the classical ALM by employing its linearized reformulation, while keeping low complexity in computation; second, we prove that a smaller proximity regularization term is needed for convergence guarantee, which allows a bigger step-size and can largely reduce required iterations for convergence. Moreover, we establish an elegant global convergence theory of the proposed scheme upon its equivalent compact expression of prediction-correction, along with a worst-case $\mathcal{O}(1/N)$ convergence rate. Numerical results demonstrate that the proposed method can reach a faster converge rate for a higher numerical efficiency as the regularization term turns smaller, which confirms the theoretical results presented in this study

Simulation and Experimental Investigation on the AE Tomography to Improve AE Source Location in the Concrete Structure

Acoustic emission (AE) tomography, which is based on the time-travel tomography with AE events as its signal sources, is a new visualization tool for inspecting and locating the internal damages in the structures. In this paper, AE tomography is applied to examine a man-made damage in a typical heterogeneous concrete structure to validate its effectiveness. Firstly, the finite element (ABAQUS/Explicit) simulation model of the concrete structure with one damaged circle in its center is built, and the simulated AE signals are obtained to establish the AE tomography. The results show that the damaged circle in the created model can be visualized clearly with the AE tomography in its original location. Secondly, the concrete specimen based on the FE model is fabricated, and the pencil lead break (PLB) signal is taken as the exciting source for AE tomography. It is shown that the experimental results have good consistency with the FE simulation results, which also verifies the feasibility of the finite element model for AE tomography. Finally, the damage source location based on AE tomography is compared with the traditional time of arrival (TOA) location method, and the better location accuracy is obtained with the AE tomography. The research results indicate that AE tomography has great potential in the application of structure damage detection.Foundation of China (no. 51175079, no. 51305176) as well as the Fundamental Research Funds for the Central Universities (CXLX12 0079)

Highly concentrated KTFSI: Glyme electrolytes for K/bilayered-V2O5 batteries

Highly concentrated glyme-based electrolytes are friendly to a series of negative electrodes for potassium-based batteries, including potassium metal. However, their compatibility with positive electrodes has been rarely explored. In this work, the influence of the molar fraction of potassium bis(trifluoromethanesulfonyl)imide dissolved in glyme on the cycling ability of K/bilayered-V2O5 batteries has been investigated. At high salt concentration, the interaction between K+ ions with the glyme is strengthened, leading to a limited number of free glyme molecules. Therefore, the anodic decomposition of the electrolyte solvent, as well as the dissolution of the Al current collectors, is effectively suppressed, resulting in the improved cycling ability of the K/bilayered-V2O5 cells. In these cells, the positive electrode active material exhibits reversible capacities of 93 and 57 mAh g−1 at specific current densities of 50 and 1000 mA g−1, respectively. After 200 charge-discharge cycles at 500 mA g−1, the cell retains 94 % of the initial capacity. The promising rate performance and capacity retention demonstrate the importance of proper electrolyte engineering for the K/bilayered-V2O5 batteries, and the good compatibility of highly concentrated glyme-based electrolytes with positive electrode materials for potassium batteries. © 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA

Highly Concentrated KTFSI : Glyme Electrolytes for K/Bilayered‐V₂O₅ Batteries

Highly concentrated glyme‐based electrolytes are friendly to a series of negative electrodes for potassium‐based batteries, including potassium metal. However, their compatibility with positive electrodes has been rarely explored. In this work, the influence of the molar fraction of potassium bis(trifluoromethanesulfonyl)imide dissolved in glyme on the cycling ability of K/bilayered‐V2O5 batteries has been investigated. At high salt concentration, the interaction between K+ ions with the glyme is strengthened, leading to a limited number of free glyme molecules. Therefore, the anodic decomposition of the electrolyte solvent, as well as the dissolution of the Al current collectors, is effectively suppressed, resulting in the improved cycling ability of the K/bilayered‐V2O5 cells. In these cells, the positive electrode active material exhibits reversible capacities of 93 and 57 mAh g−1 at specific current densities of 50 and 1000 mA g−1, respectively. After 200 charge‐discharge cycles at 500 mA g−1, the cell retains 94 % of the initial capacity. The promising rate performance and capacity retention demonstrate the importance of proper electrolyte engineering for the K/bilayered‐V2O5 batteries, and the good compatibility of highly concentrated glyme‐based electrolytes with positive electrode materials for potassium batteries

Effective and Efficient Federated Tree Learning on Hybrid Data

Federated learning has emerged as a promising distributed learning paradigm that facilitates collaborative learning among multiple parties without transferring raw data. However, most existing federated learning studies focus on either horizontal or vertical data settings, where the data of different parties are assumed to be from the same feature or sample space. In practice, a common scenario is the hybrid data setting, where data from different parties may differ both in the features and samples. To address this, we propose HybridTree, a novel federated learning approach that enables federated tree learning on hybrid data. We observe the existence of consistent split rules in trees. With the help of these split rules, we theoretically show that the knowledge of parties can be incorporated into the lower layers of a tree. Based on our theoretical analysis, we propose a layer-level solution that does not need frequent communication traffic to train a tree. Our experiments demonstrate that HybridTree can achieve comparable accuracy to the centralized setting with low computational and communication overhead. HybridTree can achieve up to 8 times speedup compared with the other baselines

Bool Network: An Open, Distributed, Secure Cross-chain Notary Platform

With the advancement of blockchain technology, hundreds of cryptocurrencies have been deployed. The bloom of heterogeneous blockchain platforms brings a new emerging problem: typically, various blockchains are isolated systems, how to securely identify and/or transfer digital properties across blockchains? There are three main kinds of cross-chain approaches: sidechains/relays, notaries, and hashed time-lock contracts. Among them, notary-based cross-chain solutions have the best compatibility and user-friendliness, but they are typically centralized. To resolve this issue, we present Bool Network -- an open, distributed, secure cross-chain notary platform powered by MPC-based distributed key management over evolving hidden committees. More specifically, to protect the identities of the committee members, we propose a Ring verifiable random function (Ring VRF) protocol, where the real public key of a VRF instance can be hidden among a ring, which may be of independent interest to other cryptographic protocols. Furthermore, all the key management procedures are executed in the TEE, such as Intel SGX, to ensure the privacy and integrity of partial key components. A prototype of the proposed Bool Network is implemented in Rust language, using Polkadot Substrate

Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model

Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication methods, which suffer from limited availability, information loss, and process inefficiencies. One promising solution to facilitate patient-provider communication is to leverage large language models (LLMs) with their powerful natural conversation and summarization capability. However, there is a limited understanding of LLMs' role during the communication. We first conducted two interview studies with both older adults (N=10) and healthcare providers (N=9) to understand their needs and opportunities for LLMs in patient-provider asynchronous communication. Based on the insights, we built an LLM-powered communication system, Talk2Care, and designed interactive components for both groups: (1) For older adults, we leveraged the convenience and accessibility of voice assistants (VAs) and built an LLM-powered VA interface for effective information collection. (2) For health providers, we built an LLM-based dashboard to summarize and present important health information based on older adults' conversations with the VA. We further conducted two user studies with older adults and providers to evaluate the usability of the system. The results showed that Talk2Care could facilitate the communication process, enrich the health information collected from older adults, and considerably save providers' efforts and time. We envision our work as an initial exploration of LLMs' capability in the intersection of healthcare and interpersonal communication.Comment: Under submission to CHI202