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Aqueous zinc-ion batteries are emerging as promising sustainable energy-storage devices. However, their cyclic stability is still a great challenge due to the inevitable parasitic reaction and dendrite growth induced by water. Herein, a cosolvent strategy based on competitive effect is proposed to address the aforementioned challenges. Ethanol with a higher Gutmann donor number demonstrates lower polarity and better wettability on the Zn surface compared with water, which endows ethanol with the ability of minimizing water activity by weakening H bonds and preferentially adsorbing on the Zn electrode. The above competitive advantages synergistically contribute to inhibiting the decomposition of free water and dendrite growth. Besides, an organic–inorganic hybrid solid–electrolyte interphase layer is in situ built based on ethanol additives, where organic matrix suppresses water corrosion while inorganic fillers promote fast Zn2+diffusion. Consequently, the electrolyte with ethanol additives boosts a high reversibility of Zn deposition, long-term durability, as well as superior Zn2+diffusibility in both Zn half-cells (Zn||Cu and Zn||Zn batteries) and Zn full cells (Zn||PTCDA and Zn||VO2batteries). This work sheds light on a universal strategy to design a high-reversible and dendrite-free Zn anode for stable aqueous batteries.

Androgen receptor (AR) antagonists play important roles in the treatment of castration-resistant prostate cancer (CRPC). The glucocorticoid receptor (GR) upregulation leads to drug resistance for clinically used antiandrogens. Therefore, blocking AR/GR signaling simultaneously has become an efficient strategy to overcome the drug resistance of CRPC. Our previous work indicated that Z19could inhibit the activity of both AR and GR. Herein, we optimized the structure of Z19and identified GA32as a potent AR/GR dual inhibitor. GA32efficiently reduced the mRNA and protein levels of AR/GR downstream genes. GA32efficiently inhibited the proliferation of enzalutamide resistance CRPC both in vitro and in vivo. GA32could directly bind to AR and GR, and the predicted binding modes for GA32with AR/GR suggested that GA32binds to the AR or GR hormone binding pocket. This work provides a potential lead compound with dual AR/GR inhibitory activity to conquer the drug resistance of CRPC.

The recent advances in 5G and mobile edge computing facilitate the rapid development of the Internet of Things (IoT), enabling collective intelligence with data support from a massive number of IoT devices. Meanwhile, federated learning (FL) has emerged as a promising solution for collaborative training while preserving user privacy, which, however, is prone to poor learning performance in large-scale IoT scenarios. On the one hand, due to the task heterogeneity in various IoT scenarios and data heterogeneity (non-IID) across different IoT clients, more than traditional FL models derived from a Uniform FL (UFL) learning architecture are required to satisfy the diversified demands of each client. On the other hand, with the proliferation of IoT devices, achieving low latency and low communication costs with traditional FL architectures becomes even more challenging. In this article, we argue that customizing a specific model for each client is an urgent requirement, calling for the development of UFL to Personalized FL (PFL). In addition, the confluence of PFL and edge computing further provides opportunities for practical implementation in the 5G IoT environment. Accordingly, we propose EdgeFHN, an edge computing-based personalized federated learning framework, which can strike a balance between collaborative FL training among different clients and efficient model personalization for each client. Experiments on image classification demonstrate the superiority of our framework in improving accuracy and reducing communication overhead compared with other state-of-the-art solutions.

Infection, autoimmunity, and cancer are principal human health challenges of the 21stcentury. Often regarded as distinct ends of the immunological spectrum, recent studies hint at potential overlap between these diseases. For example, inflammation can be pathogenic in infection and autoimmunity. T resident memory (TRM) cells can be beneficial in infection and cancer. However, these findings are limited by size and scope; exact immunological factors shared across diseases remain elusive. Here, we integrate large-scale deeply clinically and biologically phenotyped human cohorts of 526 patients with infection, 162 with lupus, and 11,180 with cancer. We identify an NKG2A+immune bias as associative with protection against disease severity, mortality, and autoimmune/post-acute chronic disease. We reveal that NKG2A+CD8+T cells correlate with reduced inflammation and increased humoral immunity and that they resemble TRMcells. Our results suggest NKG2A+biases as a cross-disease factor of protection, supporting suggestions of immunological overlap between infection, autoimmunity, and cancer.

We have synthesized a series of Li1+x(Ni0.5Mn0.5)1–xO2(LNMO) materials to study the influence of excess lithium ions on the structure and electrochemical behaviors of nickel–manganese-based layered compounds. The increasing content of Li+ions in the transition-metal (TM) layer leads to the departure of the follower-like clusters to Ni-rich and Mn-rich clusters. The Ni2+ions in the Li layer couple with adjacent transition-metal ions via strong 180° exchange interactions and moderate the local structure, which leads to magnetic clusters with finite size. Electrochemical performance shows that appropriate Ni2+ions could improve the cycle stability without decreasing the rate capability. Among them, Li1.1Ni0.45Mn0.45O2shows a rate capability of 76 mAh g–1at 1000 mA g–1and a lifespan of 300 cycles at 200 mA g–1. This work shows that structure moderation has an essential impact on its electrochemical performance. Besides this, the crystal and magnetic combined methods we use could offer a better way of studying cathode materials.

The development of a solid-state electrolyte (SSE) is crucial for overcoming the side reactions of metal potassium anodes and advancing the progress of K-ion batteries (KIBs). Exploring the diffusion mechanism of the K ion in SSE is important for deepening our understanding and promoting its development. In this study, we conducted static calculations and utilized deep potential molecular dynamics (DeepMD) to investigate the behavior of cubic K3SbS4. The original K3SbS4exhibited poor ionic conductivity, but we discovered that introducing heterovalent tungsten doping created vacancies, which significantly reduced the activation energy to 0.12 eV and enhanced the ionic conductivity to 1.80 × 10–2S/cm. The diffusion of K-ions in K3SbS4primarily occurs through the exchange of positions with K vacancies. This research provides insights into the design of SSE with high ionic conductivity. Furthermore, it highlights the effectiveness of DeepMD as a powerful tool for studying the SSE.

Zn2+ions doped quasi-one-dimensional spin-chain materials LiCu1-xZnxVO4(x=0, 0.1, 0.2) were prepared by solid-state reaction and the effect of nonmagnetic Zn2+ ions on the crystal structure, valence state and magnetic properties of them were studied by X-ray diffraction(XRD), X-ray photoelectron spectroscopy(XPS) and dc magnetization. The elongation of a and b axes and the shrinkage of caxis indicate a reduced effect of the Jahn-Teller distortion after Zn2+ions doping, while the valence state of transition metal ions in LiCu1–xZnxVO4remains unchanged since the equivalence doping of Zn2+ions on the Cu2+sites. The corrected Bonner-Fisher equation fitting to the susceptibility indicates that isolated dimers and spins are created along with the departure from infinite spin chains to finite ones.

RuO2nanocrystals are successfully impregnated into the surface carbon layer of the Li3V2(PO4)3/C cathode material by the precipitation method. Transmission electron microscopy shows that the RuO2particles uniformly embed in the surface carbon layer. Cyclic voltammetry and electrochemical impedance spectroscopy indicate that the coexistence of carbon and RuO2enables high conductivity for both Li ions and electrons and thus stabilizes the interfacial properties of the electrode, facilitates the charge transfer reactions, and improves the Li+diffusion in the electrode. As a result, the Li3V2(PO4)3cathode coated with the binary surface layer shows improved rate capability and cycle stability. Particularly, the material containing 2.4 wt % Ru exhibits the best electrochemical performance and delivers a discharge capacity of 106 mAh g–1at the 10 C rate with a capacity retention of 98.4% after 100 cycles.

A new principle is introduced to optimize the configuration of an interferometric array, based on the trade-off between the uniform and Gaussian u-vdistributions. The multi-objective optimization method, nondominated sorting genetic algorithm II (NSGA-II), is applied to achieve the optimal trade-off. The resulting array having a single configuration can meet the observation requirements of both compact and extended sources. This method has been successfully applied to design a 16-element array as the initial stage of the Daocheng Solar Radio Telescope to illustrate its feasibility. NSGA-II is improved by introducing artificial intervention into the genetic operator to solve the equality constraints. The improved NSGA-II is applied to obtain the Pareto optimal set, and a 16-element array configuration is retrieved with the best u-vtrade-off between the snapshot mode and Earth rotation synthesis mode.