Competing electronic orders on Kagome lattices at van Hove filling

The electronic orders in Hubbard models on a Kagome lattice at van Hove filling are of intense current interest and debate. We study this issue using the singular-mode functional renormalization group theory. We discover a rich variety of electronic instabilities under short range interactions. With increasing on-site repulsion $U$, the system develops successively ferromagnetism, intra unit-cell antiferromagnetism, and charge bond order. With nearest-neighbor Coulomb interaction $V$ alone (U=0), the system develops intra-unit-cell charge density wave order for small $V$, s-wave superconductivity for moderate $V$, and the charge density wave order appears again for even larger $V$. With both $U$ and $V$, we also find spin bond order and chiral $d_{x^2 - y^2} + i d_{xy}$ superconductivity in some particular regimes of the phase diagram. We find that the s-wave superconductivity is a result of charge density wave fluctuations and the squared logarithmic divergence in the pairing susceptibility. On the other hand, the d-wave superconductivity follows from bond order fluctuations that avoid the matrix element effect. The phase diagram is vastly different from that in honeycomb lattices because of the geometrical frustration in the Kagome lattice.Comment: 8 pages with 9 color figure

Spectral Normalized Dual Contrastive Regularization for Image-to-Image Translation

Existing image-to-image (I2I) translation methods achieve state-of-the-art performance by incorporating the patch-wise contrastive learning into Generative Adversarial Networks. However, patch-wise contrastive learning only focuses on the local content similarity but neglects the global structure constraint, which affects the quality of the generated images. In this paper, we propose a new unpaired I2I translation framework based on dual contrastive regularization and spectral normalization, namely SN-DCR. To maintain consistency of the global structure and texture, we design the dual contrastive regularization using different deep feature spaces respectively. In order to improve the global structure information of the generated images, we formulate a semantically contrastive loss to make the global semantic structure of the generated images similar to the real images from the target domain in the semantic feature space. We use Gram Matrices to extract the style of texture from images. Similarly, we design style contrastive loss to improve the global texture information of the generated images. Moreover, to enhance the stability of model, we employ the spectral normalized convolutional network in the design of our generator. We conduct the comprehensive experiments to evaluate the effectiveness of SN-DCR, and the results prove that our method achieves SOTA in multiple tasks

RC-SSFL: Towards Robust and Communication-efficient Semi-supervised Federated Learning System

Federated Learning (FL) is an emerging decentralized artificial intelligence paradigm, which promises to train a shared global model in high-quality while protecting user data privacy. However, the current systems rely heavily on a strong assumption: all clients have a wealth of ground truth labeled data, which may not be always feasible in the real life. In this paper, we present a practical Robust, and Communication-efficient Semi-supervised FL (RC-SSFL) system design that can enable the clients to jointly learn a high-quality model that is comparable to typical FL's performance. In this setting, we assume that the client has only unlabeled data and the server has a limited amount of labeled data. Besides, we consider malicious clients can launch poisoning attacks to harm the performance of the global model. To solve this issue, RC-SSFL employs a minimax optimization-based client selection strategy to select the clients who hold high-quality updates and uses geometric median aggregation to robustly aggregate model updates. Furthermore, RC-SSFL implements a novel symmetric quantization method to greatly improve communication efficiency. Extensive case studies on two real-world datasets demonstrate that RC-SSFL can maintain the performance comparable to typical FL in the presence of poisoning attacks and reduce communication overhead by $2 \times \sim 4 \times$

A Common-Mode Voltage Suppression Strategy Based on Double Zero-Sequence Injection PWM for Two-Level Six-Phase VSIs

A common-mode voltage (CMV) suppression strategy, namely double zero-sequence injection common-mode voltage (DZICMV), is proposed in this paper for an asymmetrical six-phase induction motor fed by two-level dual three-phase voltage source inverters (VSIs). In this strategy, the sinusoidal waveforms injected by double zero-sequence signals are employed as modulation signals, and two opposite triangular waveforms are used as carriers. The fundamental period is divided into 24 sectors. In each sector, the carrier used by the medium amplitude phase is distinct from the carriers used by the other two phases in each set of three-phase windings. Using this method, the zero vectors (000) and (111) in each set of three-phase windings can be eliminated, and the peak values of sub-CMV and total CMV can be reduced from ±Udc/2 to ±Udc/6. The experiment results show that the root mean square (RMS) value of common-mode leakage current in DZICMV can be reduced by 51.83% compared with the double zero-sequence injection PWM (DZIPWM) strategy. It is also found in the other four existing benchmark CMV suppression strategies that the peak values of sub-CMV therein are nearly all ±Udc/2, and only in the low linear modulation region could one of these strategies suppress sub-CMV peak values to ±Udc/6. However, the proposed DZICMV can suppress the sub-CMV peak values to ±Udc/6 in the whole linear modulation range. Moreover, the maximum linear modulation index of the DZICMV is 1.15, which is larger than that of the four benchmark strategies, whose maximum modulation index is 1

Protective effect of Salvia miltiorrhiza in rheumatoid arthritis patients: A randomized, single-blind, placebocontrolled trial

Purpose: To study the protective effect of Salvia miltiorrhiza (SM) against rheumatoid arthritis (RA) in RA patients.Methods: Sixty RA patients were divided into two groups: SM (n = 30) and placebo (n =30) groups given SM at a dose of 250 mg/kg (3 capsules/day), and placebo (3 capsule/day), respectively, for 12 weeks. Patient responses based on American College of Rheumatology (ACR), health assessmentquestionnaire (HAQ) score, and global assessment of disease (GAD) were recorded. Moreover, Disease Activity Score (DAS) 28, pain score (visual analogue score, VAS), rheumatoid factor (Rh factor), and inflammatory cytokines (markers) were determined.Results: After 12 weeks of intervention with SM, ACR20 (30 %)/ACR50 patient response (13.3%, i.e., score for swelling and tenderness of joints), was significantly improved. There were considerable reductions in GAD, HAQ, DAS 28, pain score (VAS), and levels of erythrocyte sedimentation rate(ESR), acute phase reaction protein (CRP), Rh factor (IgM) and inflammatory cytokines (IL-1β, IL-6 and TNF-α), when compared to placebo (p < 0.01). Treatment with SM produced milder adverse effects than treatment with placebo (p < 0.01).Conclusion: Overall, SM produces better anti-RA effect than placebo by significantly altering ACR patient response, reducing GAD, HAQ, DAS 28 scores, Rh factor, ESR, CRP and inflammatory cytokines in RA patients. However, a large-scale clinical trial is needed before SM can be recommended for combating RA and its related symptoms. Keywords: Salvia miltiorrhiza, Rheumatoid arthritis, DAS 28, Adverse effec

From Jeff=1/2 insulator to p-wave superconductor in single-crystal Sr2Ir1-xRuxO4 (0 < x< 1)

Sr2IrO4 is a magnetic insulator assisted by strong spin-orbit coupling (SOC) whereas the Sr2RuO4 is a p-wave superconductor. The contrasting ground states have been shown to result from the critical role of the strong SOC in the iridate. Our investigation of structural, transport, and magnetic properties reveals that substituting 4d Ru4+ (4d4) ions for 5d Ir4+(5d5) ions in Sr2IrO4 directly adds holes to the t2g bands, reduces the SOC and thus rebalances the competing energies in single-crystal Sr2Ir1-xRuxO4. A profound effect of Ru doping driving a rich phase diagram is a structural phase transition from a distorted I41/acd to a more ideal I4/mmm tetragonal structure near x=0.50 that accompanies a phase transition from an antiferromagnetic-insulating state to a paramagnetic-metal state. We also make a comparison drawn with Rh doped Sr2IrO4, highlighting important similarities and differences.Comment: 18 pages,7 figure