A prior regularized multi-layer graph ranking model for image saliency computation

Bottom-up saliency detection has been widely studied in many applications, such as image retrieval, object recognition, image compression and so on. Saliency detection via manifold ranking (MR) can identify the most salient and important area from an image efficiently. One limitation of the MR model is that it fails to consider the prior information in its ranking process. To overcome this limitation, we propose a prior regularized multi-layer graph ranking model (RegMR), which uses the prior calculating by boundary connectivity. We employ the foreground possibility in the first stage and background possibility in the second stage based on a multi-layer graph. We compare our model with fifteen state-of-the-art methods. Experiments show that our model performs well than all other methods on four public databases on PR-curves, F-measure and so on

TNF-α-Induced VEGF and MMP-9 Expression Promotes Hemorrhagic Transformation in Pituitary Adenomas

Pituitary apoplexy is a clinical syndrome with unknown pathogenesis. Therefore, identifying the underlying mechanisms is of high clinical relevance. Tumor necrosis factor alpha (TNF-α) is a critical cytokine mediating various hemorrhagic events, but little is known about its involvement in pituitary apoplexy. Here we show that TNF-α may be an important regulator of hemorrhagic transformation in pituitary adenomas. In this study, sixty surgical specimens of hemorrhagic and non-hemorrhagic human pituitary adenomas were examined. Hemorrhagic pituitary adenomas displayed higher protein and mRNA levels of TNF-α, vascular endothelial growth factor (VEGF) and matrix metalloproteinase-9 (MMP-9) compared with those of non-hemorrhagic tumors. Exposure of MMQ pituitary adenoma cells to TNF-α induced VEGF and MMP-9 expression in vitro. Additionally, TNF-α administration caused hemorrhagic transformation and enhanced VEGF and MMP-9 expression in MMQ pituitary adenoma cell xenografts in mice. Blockers of VEGF or MMP-9, either alone or in combination, attenuated but not abrogated TNF-α mediated hemorrhagic transformation in xenografts. This study suggests that TNF-α may play a role in the development of intratumoral hemorrhage in pituitary adenomas via up-regulation of VEGF and MMP-9

TNF-α-Induced VEGF and MMP-9 Expression Promotes Hemorrhagic Transformation in Pituitary Adenomas

Pituitary apoplexy is a clinical syndrome with unknown pathogenesis. Therefore, identifying the underlying mechanisms is of high clinical relevance. Tumor necrosis factor alpha (TNF-α) is a critical cytokine mediating various hemorrhagic events, but little is known about its involvement in pituitary apoplexy. Here we show that TNF-α may be an important regulator of hemorrhagic transformation in pituitary adenomas. In this study, sixty surgical specimens of hemorrhagic and non-hemorrhagic human pituitary adenomas were examined. Hemorrhagic pituitary adenomas displayed higher protein and mRNA levels of TNF-α, vascular endothelial growth factor (VEGF) and matrix metalloproteinase-9 (MMP-9) compared with those of non-hemorrhagic tumors. Exposure of MMQ pituitary adenoma cells to TNF-α induced VEGF and MMP-9 expression in vitro. Additionally, TNF-α administration caused hemorrhagic transformation and enhanced VEGF and MMP-9 expression in MMQ pituitary adenoma cell xenografts in mice. Blockers of VEGF or MMP-9, either alone or in combination, attenuated but not abrogated TNF-α mediated hemorrhagic transformation in xenografts. This study suggests that TNF-α may play a role in the development of intratumoral hemorrhage in pituitary adenomas via up-regulation of VEGF and MMP-9

Simulating 3D Flows Passing Wind Turbine Rotors with a Domain Decomposition Method on a Moving Domain

AbstractAccurate numerical simulations of flows around wind turbines play an important role in rotor blades design and operation control. The computation is very challenging because of the large size of the blades, the large fluids domain, the complex moving geometry, and the high Reynolds number. A popular method is the blade element momentum method which is relatively easy to implement, but has low fidelity. More recently, some high fidelity methods have been developed for the wind turbine simulations, such as Reynolds averaged Navier-Stokes methods, large-eddy simulations and direct numerical simulations (DNS). In this paper, we study DNS for flows passing 3D wind turbine rotors. The flow in the moving domain is modeled by the 3D unsteady incompressible Navier-Stokes equations in the arbitrary Lagrangian-Eulerian form. A stabilized bi-linear moving mesh finite element method, based on the unstructured tetrahedron mesh, is introduced to discretize the problem in space, and an implicit scheme is used to discretize the temporal variable. A parallel Newton-Krylov method with a domain decomposition type preconditioner is applied to solve the fully coupled nonlinear algebraic system at each timestep. We mainly focus on the performance of the domain decomposition preconditioner. To understand the efficiency of the algorithm, we test the software on a supercomputer for the simulation of a NREL 5MW wind turbine rotor. The numerical results show that the newly developed algorithm is scalable with thousands of processors for problems with tens of millions of unknowns

Minimum Barrier Distance-Based Object Descriptor for Visual Tracking

In most visual tracking tasks, the target is tracked by a bounding box given in the first frame. The complexity and redundancy of background information in the bounding box inevitably exist and affect tracking performance. To alleviate the influence of background, we propose a robust object descriptor for visual tracking in this paper. First, we decompose the bounding box into non-overlapping patches and extract the color and gradient histograms features for each patch. Second, we adopt the minimum barrier distance (MBD) to calculate patch weights. Specifically, we consider the boundary patches as the background seeds and calculate the MBD from each patch to the seed set as the weight of each patch since the weight calculated by MBD can represent the difference between each patch and the background more effectively. Finally, we impose the weight on the extracted feature to get the descriptor of each patch and then incorporate our MBD-based descriptor into the structured support vector machine algorithm for tracking. Experiments on two benchmark datasets demonstrate the effectiveness of the proposed approach

Correlation Hiding by Independence Masking

Extracting useful correlation from a dataset has been extensively studied. In this paper, we deal with the opposite, namely, a problem we call correlation hiding (CH), which is fundamental in numerous applications that need to disseminate data containing sensitive information. In this problem, we are given a relational table T whose attributes can be classified into three disjoint sets A, B, and C. The objective is to distort some values in T so that A becomes independent from B, and yet, their correlation with C is preserved as much as possible. CH is different from all the problems studied previously in the area of data privacy, in that CH demands complete elimination of the correlation between two sets of attributes, whereas the previous research focuses on partial elimination up to a certain level. A new operator called independence masking is proposed to solve the CH problem. Implementations of the operator with good worst case guarantees are described in the full version of this short note

Correlation between circulating myeloid-derived suppressor cells and serum miRNA21 in non-small cell lung cancer and its clinical significance

Objective: To investigate the effect and clinical significance of myeloid-derived suppressor cells (MDSCs) levels and serum miRNA-21 expression in advanced non-small cell lung cancer (NSCLC) patients. Methods: Advanced NSCLC patients treated at the First People’s Hospital of Tongxiang City, Zhejiang Province, between July 2021 and June 2022 were included in this study. MDSCs in the peripheral circulation were assessed by flow cytometry, and serum miRNA-21 expression was assessed by q-PCR. The effects of miRNA-21 on MDSC proliferation and ARG-1 and inducible nitric oxide synthase (iNOS) secretion from MDSCs were examined using in vitro cell experiments. In addition, the correlation between MDSC and CEA, CRP and Ki67 was analyzed. Results: Compared with those in the peripheral circulation of individuals in the control group, the expression levels of polymorphonuclear-MDSCs (PMN-MDSCs) and miRNA-21 in the peripheral circulation of NSCLC patients were significantly higher, and the two groups were significantly positively correlated. In in vitro cell experiments, miRNA-21 mimics promoted MDSC proliferation and increased ARG-1 and iNOS secretion and miRNA-21 inhibtor has an opposite result. In addition, PMN-MDSCs in the peripheral circulation of NSCLC patients were significantly positively correlated with carcinoembryonic antigen (CEA), C-reactive protein (CRP), and Ki67. Conclusion: The blood of advanced NSCLC patients contains high levels of MDSCs and miRNA-21, and the two may interact to impact on NSCLC