Several Treatments on Nonconforming Element Failed in the Strict Patch Test

For nonconforming finite elements, it has been proved that the models whose convergence is controlled only by the weak form of patch tests will exhibit much better performance in complicated stress states than those which can pass the strict patch tests. However, just because the former cannot provide the exact solutions for the patch tests of constant stress states with a very coarse mesh (strict patch test), their usability is doubted by many researchers. In this paper, the non-conforming plane 4-node membrane element AGQ6-I, which was formulated by the quadrilateral area coordinate method and cannot pass the strict patch tests, was modified by three different techniques, including the special numerical integration scheme, the constant stress multiplier method, and the orthogonal condition of energy. Three resulting new elements, denoted by AGQ6M-I, AGQ6M-II, and AGQ6M, can pass the strict patch test. And among them, element AGQ6M is the best one. The original model AGQ6-I and the new model AGQ6M can be treated as the replacements of the well-known models Q6 and QM6, respectively

A tunable plasmonic refractive index sensor with nanoring-strip graphene arrays

In this paper, a tunable plasmonic refractive index sensor with nanoring-strip graphene arrays is numerically investigated by the finite difference time domain (FDTD) method. The simulation results exhibit that by changing the sensing medium refractive index nmed of the structure, the sensing range of the system is large. By changing the doping level ng, we noticed that the transmission characteristics can be adjusted flexibly. The resonance wavelength remains entirely the same and the transmission dip enhancement over a big range of incidence angles [0,45] for both TM and TE polarizations, which indicates that the resonance of the graphene nanoring-strip arrays is insensitive to angle polarization. The above results are undoubtedly a new way to realize various tunable plasmon devices, and may have a great application prospect in biosensing, detection and imaging

An Improved Trace Driven Instruction Cache Timing Attack on RSA

The previous I-cache timing attacks on RSA which exploit the instruction path of a cipher were mostly proof-of-concept, and it is harder to put them into practice than D-cache timing attacks. We propose a new trace driven timing attack model based on spying on the whole I-cache. An improved analysis algorithm of the exponent using the characteristic of the size of the window is advanced, which could further reduce the search space of the bits of the key than the former and provide an error detection mechanism to detect some erroneous decisions of the operation sequence. We implemented an attack on RSA of OpenSSL under a practical environment, proving that the feasibility and effectiveness of I-Cache timing attack could be improved

CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation

We study the task of weakly-supervised point cloud semantic segmentation with sparse annotations (e.g., less than 0.1% points are labeled), aiming to reduce the expensive cost of dense annotations. Unfortunately, with extremely sparse annotated points, it is very difficult to extract both contextual and object information for scene understanding such as semantic segmentation. Motivated by masked modeling (e.g., MAE) in image and video representation learning, we seek to endow the power of masked modeling to learn contextual information from sparsely-annotated points. However, directly applying MAE to 3D point clouds with sparse annotations may fail to work. First, it is nontrivial to effectively mask out the informative visual context from 3D point clouds. Second, how to fully exploit the sparse annotations for context modeling remains an open question. In this paper, we propose a simple yet effective Contextual Point Cloud Modeling (CPCM) method that consists of two parts: a region-wise masking (RegionMask) strategy and a contextual masked training (CMT) method. Specifically, RegionMask masks the point cloud continuously in geometric space to construct a meaningful masked prediction task for subsequent context learning. CMT disentangles the learning of supervised segmentation and unsupervised masked context prediction for effectively learning the very limited labeled points and mass unlabeled points, respectively. Extensive experiments on the widely-tested ScanNet V2 and S3DIS benchmarks demonstrate the superiority of CPCM over the state-of-the-art.Comment: Accepted by ICCV 202

Using Left and Right Brains Together: Towards Vision and Language Planning

Large Language Models (LLMs) and Large Multi-modality Models (LMMs) have demonstrated remarkable decision masking capabilities on a variety of tasks. However, they inherently operate planning within the language space, lacking the vision and spatial imagination ability. In contrast, humans utilize both left and right hemispheres of the brain for language and visual planning during the thinking process. Therefore, we introduce a novel vision-language planning framework in this work to perform concurrent visual and language planning for tasks with inputs of any form. Our framework incorporates visual planning to capture intricate environmental details, while language planning enhances the logical coherence of the overall system. We evaluate the effectiveness of our framework across vision-language tasks, vision-only tasks, and language-only tasks. The results demonstrate the superior performance of our approach, indicating that the integration of visual and language planning yields better contextually aware task execution.Comment: 19 pages, 13 figure

A tunable plasmonic refractive index sensor with nanoring-strip graphene arrays

In this paper, a tunable plasmonic refractive index sensor with nanoring-strip graphene arrays is numerically investigated by the finite difference time domain (FDTD) method. The simulation results exhibit that by changing the sensing medium refractive index nmed of the structure, the sensing range of the system is large. By changing the doping level ng, we noticed that the transmission characteristics can be adjusted flexibly. The resonance wavelength remains entirely the same and the transmission dip enhancement over a big range of incidence angles [0,45] for both TM and TE polarizations, which indicates that the resonance of the graphene nanoring-strip arrays is insensitive to angle polarization. The above results are undoubtedly a new way to realize various tunable plasmon devices, and may have a great application prospect in biosensing, detection and imaging

Ube2L6 promotes M1 macrophage polarization in HFD-fed obese mice via ISGylation of STAT1 to trigger STAT1 activation

Introduction: In obesity-related type 2 diabetes mellitus (T2DM), M1 macrophages aggravate chronic inflammation and insulin resistance. ISG15-conjugation enzyme E2L6 (Ube2L6) has been demonstrated as a promoter of obesity and insulin resistance. This study investigated the function and mechanism of Ube2L6 in M1 macrophage polarization in obesity. Methods: Obesity was induced in Ube2L6AKO mice and age-matched Ube2L6flox/flox control mice by high-fat diet (HFD). Stromal vascular cells (SVCs) were isolated from epididymal white adipose tissue of mice. Polarization induction was performed in mouse bone marrow-derived macrophages (BMDMs) by exposure to IFN-γ, lipopolysaccharide (LPS), or IL-4. F4/80 expression was assessed by immunohistochemistry staining. Expression of M1/M2 macrophage markers and target molecules was determined by flow cytometry, RT-qPCR, and Western blotting, respectively. Protein interaction was validated by co-immunoprecipitation (Co-IP) assay. The release of TNF-α and IL-10 was detected by ELISA. Results: The polarization of pro-inflammatory M1 macrophages together with an increase in macrophage infiltration were observed in HFD-fed mice, which could be restrained by Ube2L6 knockdown. Additionally, Ube2L6 deficiency triggered the repolarization of BMDMs from M1 to M2 phenotypes. Mechanistically, Ube2L6 promoted the expression and activation of signal transducer and activator of transcription 1 (STAT1) through interferon-stimulated gene 15 (ISG15)-mediated ISGlylation, resulting in M1 macrophage polarization. Conclusion: Ube2L6 exerts as an activator of STAT1 via post-translational modification of STAT1 by ISG15, thereby triggering M1 macrophage polarization in HFD-fed obese mice. Overall, targeting Ube2L6 may represent an effective therapeutic strategy for ameliorating obesity-related T2DM