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Low sulfur utilization and poor cycling stability are two major factors that currently impede the wide-spread commercialization of lithium-sulfur (Li-S) batteries. Herein, sulfur-rich side chains are anchored onto Schiff-base copolymer of thiourea aldehyde resin (cp (S-TAR)) nanosheets via inverse vulcanization to form a large number of intermolecular crosslinkers as well as mesopores. Application of the resultant copolymer as a cathode material in Li-S batteries can not only provide abundant porous channels for Li + diffusion but also significantly alleviate the dissolution of polysulfides by chemical confinement through the covalent bonds between sulfur-rich side chains and TAR. With this novel polymer cathode, a Li-S battery prototype is constructed which can operate at 1 C for over 500 charge-discharge cycles at nearly 99% coulombic efficiency, showing an ultralow cyclic fading rate of 0.045% per cycle, and an outstanding high-rate response of up to 5 C. The present strategy demonstrates the great potential of using highly crosslinked organosulfur copolymers as high-performance polymer cathode materials for low-cost, high-energy density Li-S batteries. [ABSTRACT FROM AUTHOR]

3D mesh denoising is a crucial pre-processing step in many graphics applications. However, existing data-driven mesh denoising models, primarily trained on synthetic white noise, are less effective when applied to real-world meshes with the noise of complex intensities and distributions. Moreover, how to comprehensively capture information from input meshes and apply suitable denoising models for feature-preserving mesh denoising remains a critical and unresolved challenge. This paper presents a rotation-Equivariant model-based Mesh Denoising (EMD) model and a Realistic Mesh Noise Generation (RMNG) model to address these issues. Our EMD model leverages rotation-equivariant features and self-attention weights of geodesic patches for more effective feature extraction, thereby achieving SOTA denoising results. The RMNG model, based on the Generative Adversarial Networks (GANs) architecture, generates massive amounts of realistic noisy and noiseless mesh pairs data for data-driven mesh denoising model training, significantly benefiting real-world denoising tasks. To address the smooth degradation and loss of sharp edges commonly observed in captured meshes, we further introduce varying levels of Laplacian smoothing to input meshes during the paired training data generation, endowing the trained denoising model with feature recovery capabilities. Experimental results demonstrate the superior performance of our proposed method in preserving fine-grained features while removing noise on real-world captured meshes. • Introduced an EMD method using rotation-equivariant features for SOTA mesh denoising. • Developed an RMNG model to create realistic noisy-clean pairs, enhancing real-world denoising. • Proposed a method to add smoothing degradation in data generation, improving feature recovery. [ABSTRACT FROM AUTHOR]

• Network pharmacology method was performed to analyze the mechanisms of BuYangHuanWu decoction on atherosclerosis. • Cytokines including IL1β, TGFB1, TNF-α, IL-6 are proved to be key pharmacological targets. • AS animal model was bulit and BuYangHuanWu decoction was determined to be effective in treating atherosclerosis. • NF-κB signaling pathway was blocked by BYHWD. Atherosclerosis (AS) is one of the leading causes of cardiovascular disease and has a high rate of morbidity and mortality. Traditional Chinese Medicine (TCM) supplied many therapies for AS treatment for centuries. Among these treatments, BuYangHuanWu decoction (BYHWD) is a classic prescription. In this study, we analyzed the mechanisms of BYHWD in the treatment of AS by using a network pharmacology method. Our results revealed the mechanisms of BYHWD in treating AS, which is highly related to inflammation and apoptosis pathways, moreover, the genes including IL1β, TGFB1, TNF, IL6, NFκB1 are proved to be the key pharmacological targets for the treatment of AS. Furthermore, an AS rat model was established and the rats in the treatment group received different amounts of BYHWD. Serum lipid levels (TC/TG/HDL-C/LDL-C) and tissue oxidative stress levels (SOD, GSH-Px, CAT and MDA) were ameliorated in a dose-dependent manner. The morphology of the aortic intima in the BYHWD -treated groups was improved. Real-time PCR and Western blot analysis results indicated that inflammatory cytokines were suppressed and that the NF-κB signaling pathway was blocked by BYHWD. All of this evidence suggested that BYHWD is an ideal prescription for treating AS. [ABSTRACT FROM AUTHOR]

One of the primary challenges to apply the access control policy language XACML is the performance problem of the policy decision point (PDP), particularly when the PDP experience a great number of policies. The research on improving the PDP evaluation performance is of great significance. By combining with automaton theory an efficient policy decision engine is constructed in this paper, and attribute bitmaps are established statically for each subject, resource and action attribute of policies loaded by the policy decision engine. In evaluating access requests, the policy decision engine dynamically analyzes the requests and extracts the required attribute bitmaps to enforce the AND operation. According to the result of the AND operation, the policy decision engine matches the policies rapidly and gives out an authorization decision. The time that the policy decision engine takes to complete the evaluation of one access request is within 0.5 microsecond. This method not only greatly saves the storage space of policies, but also significantly reduces the time that the PDP takes to match the policies and evaluate access requests. Comparisons of the evaluation time taken by the policy decision engine with that taken by the Sun PDP, as well as XEngine and SBA-XACML, are made under different numbers of access requests. Experimental results show that the evaluation performance of the policy decision engine has a great improvement over that of the Sun PDP, XEngine and SBA-XACML. [ABSTRACT FROM AUTHOR]