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Data-driven approach is promising for predicting impedance profile of grid-connected voltage source converters (VSCs) under a wide range of operating points (OPs). However, the conventional approaches rely on a one-to-one mapping between operating points and impedance profiles, which, as pointed out in this article, can be invalid for multiconverter systems. To tackle this challenge, this article proposes a stacked-autoencoder-based machine learning framework for the impedance profile predication of grid-connected VSCs, together with its detailed design guidelines. The proposed method uses features, instead of OPs, to characterize impedance profiles, and hence, it is scalable for multiconverter systems. Another benefit of the proposed method is the capability of predicting VSC impedance profiles at unstable OPs of the grid-VSC system. Such prediction can be realized solely based on data collected during stable operation, showcasing its potential for rapid online state estimation. Experiments on both single-VSC and multi-VSC systems validate the effectiveness of the proposed method. 

In solid materials, non-trivial topological states, electron correlations and magnetism are central ingredients for realizing quantum properties, including unconventional superconductivity, charge and spin density waves and quantum spin liquids. The kagome lattice, made up of cornersharing triangles, can host these three ingredients simultaneously and has proved to be a fertile platform for studying diverse quantum phenomena including those stemming from the interplay of these ingredients. This Review introduces the fundamental properties of the kagome lattice and discusses the complex phenomena observed in several materials systems, including the intertwining of charge order and superconductivity in some kagome metals, the modulation of magnetism and topology in some kagome magnets, and the combination of symmetry breaking and Mott physics in ‘breathing’ kagome insulators. The Review also highlights open questions in the field and future research directions in kagome systems. 

Cellular form and function are controlled by the assembly and stability of actin cytoskeletal structures—but disassembling/pruning these structures is equally essential for the plasticity and remodeling that underlie behavioral adaptations. Importantly, the mechanisms of actin assembly have been well-defined—including that it is driven by actin’s polymerization into filaments (F-actin) and then often bundling by crosslinking proteins into stable higher-order structures. In contrast, it remains less clear how these stable bundled F-actin structures are rapidly disassembled. We now uncover mechanisms that rapidly and extensively disassemble bundled F-actin. Using biochemical, structural, and imaging assays with purified proteins, we show that F-actin bundled with one of the most prominent crosslinkers, fascin, is extensively disassembled by Mical, the F-actin disassembly enzyme. Furthermore, the product of this Mical effect, Mical-oxidized actin, is poorly bundled by fascin, thereby further amplifying Mical’s disassembly effects on bundled F-actin. Moreover, another critical F-actin regulator, cofilin, also affects fascin-bundled filaments, but we find herein that it synergizes with Mical to dramatically amplify its disassembly of bundled F-actin compared to the sum of their individual effects. Genetic and high-resolution cellular assays reveal that Mical also counteracts crosslinking proteins/bundled F-actin in vivo to control cellular extension, axon guidance, and Semaphorin/Plexin cell-cell repulsion. Yet, our results also support the idea that fascin-bundling serves to dampen Mical’s F-actin disassembly in vitro and in vivo—and that physiologically relevant cellular remodeling requires a fine-tuned interplay between the factors that build bundled F-actin networks and those that disassemble them. 

Previously, we found that Ureaplasma parvum internalised into HeLa cells and cyto- solic accumulation of galectin-3. U. parvum induced the host cellular membrane dam- age and survived there. Here, we conducted vesicular trafficking inhibitory screening in yeast to identify U. parvum vacuolating factor (UpVF). U. parvum triggered endo- plasmic reticulum (ER) stress and upregulated the unfolded protein response-related factors, including BiP, P-eIF2 and IRE1 in the host cells, but it blocked the induction of the downstream apoptotic factors. MicroRNA library screening of U. parvum- infected cells and UpVF-transfected cells identified miR-211 and miR-214 as the negative regulators of the apoptotic cascade under ER stress. Transient expression of UpVF induced HeLa cell death with intracellular vacuolization; however, some stable UpVF transformant survived. U. parvum-infected cervical cell lines showed resistance to actinomycin D, and UpVF stable transformant cell lines exhibited resistance to X- ray irradiation, as well as cisplatin and paclitaxel. UpVF expressing cervical cancer xenografts in nude mice also acquired resistance to cisplatin and paclitaxel. A myco- plasma expression vector based on Mycoplasma mycoides, Syn-MBA (multiple banded antigen)-UpVF, reduced HeLa cell survival compared with that of Syn-MBA after 72 hr of infection. These findings together suggest novel mechanisms for Ureaplasma infection and the possible implications for cervical cancer malignancy.