Multiple positive solutions to third-order three-point singular semipositone boundary value problem

By using a specially constructed cone and the fixed point index theory, this paper investigates the existence of multiple positive solutions for the third-order three-point singular semipositone BVP: \begin{cases} x'''(t)-\ld f(t,x) =0, &t\in(0,1); [.3pc] x(0)=x'(\eta)=x''(1)=0, & \end{cases} where ${1/2}<\eta<1$, the non-linear term f(t,x):(0,1)\times(0,+\i)\to (-\i,+\i) is continuous and may be singular at $t=0$, $t=1$, and $x=0$, also may be negative for some values of $t$ and $x$, \ld is a positive parameter.Comment: 14 page

PointOBB: Learning Oriented Object Detection via Single Point Supervision

Single point-supervised object detection is gaining attention due to its cost-effectiveness. However, existing approaches focus on generating horizontal bounding boxes (HBBs) while ignoring oriented bounding boxes (OBBs) commonly used for objects in aerial images. This paper proposes PointOBB, the first single Point-based OBB generation method, for oriented object detection. PointOBB operates through the collaborative utilization of three distinctive views: an original view, a resized view, and a rotated/flipped (rot/flp) view. Upon the original view, we leverage the resized and rot/flp views to build a scale augmentation module and an angle acquisition module, respectively. In the former module, a Scale-Sensitive Consistency (SSC) loss is designed to enhance the deep network's ability to perceive the object scale. For accurate object angle predictions, the latter module incorporates self-supervised learning to predict angles, which is associated with a scale-guided Dense-to-Sparse (DS) matching strategy for aggregating dense angles corresponding to sparse objects. The resized and rot/flp views are switched using a progressive multi-view switching strategy during training to achieve coupled optimization of scale and angle. Experimental results on the DIOR-R and DOTA-v1.0 datasets demonstrate that PointOBB achieves promising performance, and significantly outperforms potential point-supervised baselines.Comment: 11 pages,5 figures, 6 tables. Code: https://github.com/Luo-Z13/pointob

Long Non Coding RNA MALAT1 Promotes Tumor Growth and Metastasis by Inducing Epithelial-Mesenchymal Transition in Oral Squamous Cell Carcinoma

The prognosis of advanced oral squamous cell carcinoma (OSCC) patients remains dismal, and a better understanding of the underlying mechanisms is critical for identifying effective targets with therapeutic potential to improve the survival of patients with OSCC. This study aims to clarify the clinical and biological significance of metastasis-associated long non-coding RNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in OSCC. We found that MALAT1 is overexpressed in OSCC tissues compared to normal oral mucosa by real-time PCR. MALAT1 served as a new prognostic factor in OSCC patients. When knockdown by small interfering RNA (siRNA) in OSCC cell lines TSCCA and Tca8113, MALAT1 was shown to be required for maintaining epithelial-mesenchymal transition (EMT) mediated cell migration and invasion. Western blot and immunofluorescence staining showed that MALAT1 knockdown significantly suppressed N-cadherin and Vimentin expression but induced E-cadherin expression in vitro. Meanwhile, both nucleus and cytoplasm levels of β-catenin and NF-κB were attenuated, while elevated MALAT1 level triggered the expression of β-catenin and NF-κB. More importantly, targeting MALAT1 inhibited TSCCA cell-induced xenograft tumor growth in vivo. Therefore, these findings provide mechanistic insight into the role of MALAT1 in regulating OSCC metastasis, suggesting that MALAT1 is an important prognostic factor and therapeutic target for OSCC

Bifurcation of Positive Solutions for a Class of Boundary Value Problems of Fractional Differential Inclusions

Using Krein-Rutman theorem, topological degree theory, and bifurcation techniques, this paper investigates the existence of positive solutions for a class of boundary value problems of fractional differential inclusions

The R-Ras GTPase Mediates Cross Talk between Estrogen and Insulin Signaling in Breast Cancer Cells

The signaling cascades activated by insulin and IGF-1 contribute to the control of multiple cellular functions, including glucose metabolism and cell proliferation. In most cases these effects are mediated, at least in part, by insulin receptor substrates (IRS), one of which is insulin receptor substrate 1 (IRS-1). R-Ras is a member of the Ras family of GTPases and is involved in a variety of biological processes, including integrin activation, cell migration, and control of cell proliferation. Here we demonstrate that both R-Ras and BCAR3, a regulator of R-Ras activity that has been implicated in breast cancer, regulate the level of IRS-1 protein in estrogen-dependent MCF-7 and ZR75 breast cancer cells. In particular, expression of a constitutively activated R-Ras mutant, R-Ras38V, or of BCAR3 accelerates the degradation of IRS-1, leading to the impairment of signaling through insulin but not epidermal growth factor receptors. Moreover, knockdown of endogenous R-Ras levels in MCF-7 cells inhibits IRS-1 degradation induced by estrogen signaling blockade but not by long-term insulin treatment. Consistent with these results, both R-Ras38V expression and estrogen signaling blockade lead to the degradation of IRS-1, at least in part, through calpain activity. These findings show that R-Ras activity mediates inhibition of insulin signaling associated with suppression of estrogen action, implicating this GTPase in a growth-inhibitory mechanism associated with antiestrogen treatment of breast cancer

Investigation of bond strength of FRP-to-concrete interface

The study of bonding strength of FRP-to-concrete interface is a fundamental issue in analysis of fiber reinforce polymer (FRP) externally strengthened reinforced concrete structures. In this paper, a modified shear retention model for cracked concrete element is introduced and the meso-scale finite element method is used to analyze the bonding strength of the interface. A new semi-theoretical and semi-experiential constitutive model for FRP-to-concrete interface is developed to model the mechanical behavior of FRP-to-concrete interface based on meso-scale finite element outcomes and direct pullout test results. The proposed constitutive model is demonstrated to be accurate and effective and possess excellent computational stability by comparing with the experimental results and results from other literatures

A novel spectral coding in a large graph database

Retrieving related graphs containing a query graph from a large graph database is a key issue in many graph-based applications, such as drug discovery and structural pattern recognition. Because sub-graph isomorphism is a NP-complete problem [4], we have to employ a filter-and-verification framework to speed up the search efficiency, that is, using an effective and efficient pruning strategy to filter out the false positives (graphs that are not possible in the results) as many as possible first, then validating the remaining candidates by subgraph isomorphism checking. In this paper, we propose a novel filtering method, a spectral encoding method, i.e. GCoding. Specifically, we assign a signature to each vertex based on its local structures. Then, we generate a spectral graph code by combining all vertex signatures in a graph. Based on spectral graph codes, we derive a necessary condition for sub-graph isomorphism. Then we propose two pruning rules for sub-graph search problem, and prove that they satisfy the no-false-negative requirement (no dismissal in answers). Since graph codes are in numerical space, we take this advantage and conduct efficient filtering over graph codes. Extensive experiments show that GCoding outperforms existing counterpart methods. 1