Holographic Operator Product Expansion of Loop Operators in N=4\mathcal{N}=4 SO(N)SO(N) Super Yang-Mills Theory

In this paper, we compute the correlation functions of Wilson(-'t~Hooft) loops with chiral primary operators in $\mathcal{N}=4$ supersymmetric Yang-Mills theory with $SO(N)$ gauge symmetry, which has a holographic dual description of Type IIB superstring theory on the $AdS_{5}\times\mathbf{RP}^{5}$ background. Specifically, we compute the coefficients of the chiral primary operators in the operator product expansion of Wilson loops in the fundamental representation, Wilson-'t Hooft loops in the symmetric representation, Wilson loops in the anti-fundamental representation and the spinor representation. We also compare these results to the $\mathcal{N}=4$ $SU(N)$ super Yang-Mills theory.Comment: 20 pages, no figures

Disruption of gradient expression of Zic3 resulted in abnormal intra-retinal axon projection

The targeting of retinal ganglion axons toward the optic disc is the first step in axon pathfinding in the visual system. The molecular mechanisms involved in guiding the retinal axons to project towards the optic disc are not well understood. We report that a gene encoding a zinc-finger transcription factor, Zic3, is expressed in a periphery-high and center-low gradient in the retina at the stages of active axon extension inside the retina. The gradient expression of Zic3 recedes towards the periphery over the course of development, correlating with the progression of retinal cell differentiation and axonogenesis. Disruption of gradient expression of Zic3 by retroviral overexpression resulted in mis-targeting of retinal axons and some axons misrouted to the sub-retinal space at the photoreceptor side of the retina. Misexpression of Zic3 did not affect neurogenesis or differentiation inside the retina, or grossly alter retinal lamination. By stripe assay, we show that misexpression of Zic3 may induce the expression of an inhibitory factor to the retinal axons. Zic3 appears to play a role in intra-retinal axon targeting, possibly through regulation of the expression of specific downstream genes involved in axon guidance

Concept Vector for Similarity Measurement Based on Hierarchical Domain Structure

The concept vector model generalizes standard representations of similarity concept in terms of tree-like structure. In the model, each concept node in the hierarchical tree has ancestor and descendent concept nodes composing its relevancy nodes, thus a concept node is represented as a concept vector according to its relevancy nodes' density and the similarity of the two concepts is obtained by computing cosine similarity between their vectors. In addition, the model is adjusted in terms of local density and multiple descendents problem. The model contains structure information inherent and hidden in the tree. We show that this measure compares favorably to other measures, and it is flexible in that it can make comparisons between any two concepts in a hierarchical tree without relying on additional dictionary or corpus information

Serum zinc levels in 368 patients with oral mucosal diseases: a preliminary study

Background: The aim of this study was to assess the serum zinc levels in patients with common oral mucosal diseases by comparing these to healthy controls. Material and Methods: A total of 368 patients, which consisted of 156 recurrent aphthous stomatitis (RAS) patients, 57 oral lichen planus (OLP) patients, 55 burning mouth syndrome (BMS) patients, 54 atrophic glossitis (AG) patients, 46 xerostomia patients, and 115 sex-and age-matched healthy control subjects were enrolled in this study. Serum zinc levels were measured in all participants. Statistical analysis was performed using a one-way ANOVA, t-test, and Chi-square test. Results: The mean serum zinc level in the healthy control group was significantly higher than the levels of all other groups ( p < 0.001). No individual in the healthy control group had a serum zinc level less than the minimum normal value. However, up to 24.7% (13/54) of patients with AG presented with zinc deficiency, while 21.2% (33/156) of patients with RAS, 16.4% (9/55) of patients with BMS, 15.2% (7/46) of patients with xerostomia, and 14.0% (8/57) of patients with OLP were zinc deficient. Altogether, the zinc deficiency rate was 19.02% (70/368) in the oral mucosal diseases (OMD) group (all patients with OMD). The difference between the OMD and healthy control group was significant ( p < 0.001). Gender differences in serum zinc levels were also present, although not statistically significant. Conclusions: Zinc deficiency may be involved in the pathogenesis of common oral mucosal diseases. Zinc supplementation may be a useful treatment for oral mucosal diseases, but this requires further investigation; the optimal serum level of zinc, for the prevention and treatment of oral mucosal diseases, remains to be determined

Content-sensitive superpixel generation with boundary adjustment.

Superpixel segmentation has become a crucial tool in many image processing and computer vision applications. In this paper, a novel content-sensitive superpixel generation algorithm with boundary adjustment is proposed. First, the image local entropy was used to measure the amount of information in the image, and the amount of information was evenly distributed to each seed. It placed more seeds to achieve the lower under-segmentation in content-dense regions, and placed the fewer seeds to increase computational efficiency in content-sparse regions. Second, the Prim algorithm was adopted to generate uniform superpixels efficiently. Third, a boundary adjustment strategy with the adaptive distance further optimized the superpixels to improve the performance of the superpixel. Experimental results on the Berkeley Segmentation Database show that our method outperforms competing methods under evaluation metrics

Addressless: A New Internet Server Model to Prevent Network Scanning

Eliminating unnecessary exposure is a principle of server security. The huge IPv6 address space enhances security by making scanning infeasible, however, with recent advances of IPv6 scanning technologies, network scanning is again threatening server security. In this paper, we propose a new model named addressless server, which separates the server into an entrance module and a main service module, and assigns an IPv6 prefix instead of an IPv6 address to the main service module. The entrance module generates a legitimate IPv6 address under this prefix by encrypting the client address, so that the client can access the main server on a destination address that is different in each connection. In this way, the model provides isolation to the main server, prevents network scanning, and minimizes exposure. Moreover it provides a novel framework that supports flexible load balancing, high-availability, and other desirable features. The model is simple and does not require any modification to the client or the network. We implement a prototype and experiments show that our model can prevent the main server from being scanned at a slight performance cost

CM-CASL: Comparison-based Performance Modeling of Software Systems via Collaborative Active and Semisupervised Learning

Configuration tuning for large software systems is generally challenging due to the complex configuration space and expensive performance evaluation. Most existing approaches follow a two-phase process, first learning a regression-based performance prediction model on available samples and then searching for the configurations with satisfactory performance using the learned model. Such regression-based models often suffer from the scarcity of samples due to the enormous time and resources required to run a large software system with a specific configuration. Moreover, previous studies have shown that even a highly accurate regression-based model may fail to discern the relative merit between two configurations, whereas performance comparison is actually one fundamental strategy for configuration tuning. To address these issues, this paper proposes CM-CASL, a Comparison-based performance Modeling approach for software systems via Collaborative Active and Semisupervised Learning. CM-CASL learns a classification model that compares the performance of two given configurations, and enhances the samples through a collaborative labeling process by both human experts and classifiers using an integration of active and semisupervised learning. Experimental results demonstrate that CM-CASL outperforms two state-of-the-art performance modeling approaches in terms of both classification accuracy and rank accuracy, and thus provides a better performance model for the subsequent work of configuration tuning