Evaluated plasma interleukin-18/interleukin-10 ratio is a risk factor for acute coronary syndromes in patients with stable angina pectoris

Background: Studies suggested that interleukin-18 (IL-18)/interleukin-10 (IL-10) ratio is an independent predictor of adverse cardiovascular events in patients with acute coronary syndromes (ACS). In this study we aimed to evaluate the predictive significance of IL-18/IL-10 for the occurrence of ACS in patients with stable angina pectoris (SAP) over a 40-month follow-up.Methods: The IL-18, IL-10 levels of 257 patients with SAP were determined by Enzyme-Linked Immunosorbent Assay (ELISA). Two hundred and fifty-two patients, 42 of whom had ACS and 210 were event-free, were divided into two groups according to the presence or absence of the occurrence of ACS during the 40-month follow-up.Results: Plasma IL-18 and IL-18/IL-10 ratios were both significantly higher (p = 0.001 and p = 0.044, respectively) among patients with ACS, however, IL-10 level was lower (p = 0.046) compared to the patients without ACS. The elevation of plasma IL-18/IL-10 ratio and the number of coronary artery lesions made the advantage ratio of ACS in patients with SAP increase 4.242 times and 1.942 times (p = 0.000 and p = 0.011, respectively).Conclusions: Plasma IL-18 and IL-10 levels in patients with SAP are closely related to the occurrence of ACS, elevated IL-18/IL-10 ratio has a positive predictive value for the occurrence of ACS in patients with SAP

Real-Time Chromakey Matting Using Image Statistics

Given a video signal, we generate an alpha matte based on the chromakey information. The computation is done in interactive-time using pixel shaders. To accomplish this, we use Principle Components Analysis to generate a linear transformation matrix where the resulting color triplets Euclidean distance is directly related to the probability that the color exists in the chromakey spectrum. The result of this process is a trimap of the video signals opacity. To solve the alpha matte from the trimap, we minimize an energy function constrained by the trimap with gradient descent. This energy function is based on the least-squared error of overlapping neighborhoods around each pixel and is independent of the background or foreground color

Evaluation of Ecosystem Services in Strategic Environmental Assessment for River Basin Planning

Water Resources Planning and Managemen

Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs

Bipartite graphs model relationships between two different sets of entities, like actor-movie, user-item, and author-paper. The butterfly, a 4-vertices 4-edges $2\times 2$ bi-clique, is the simplest cohesive motif in a bipartite graph and is the fundamental component of higher-order substructures. Counting and enumerating the butterflies offer significant benefits across various applications, including fraud detection, graph embedding, and community search. While the corresponding motif, the triangle, in the unipartite graphs has been widely studied in both static and temporal settings, the extension of butterfly to temporal bipartite graphs remains unexplored. In this paper, we investigate the temporal butterfly counting and enumeration problem: count and enumerate the butterflies whose edges establish following a certain order within a given duration. Towards efficient computation, we devise a non-trivial baseline rooted in the state-of-the-art butterfly counting algorithm on static graphs, further, explore the intrinsic property of the temporal butterfly, and develop a new optimization framework with a compact data structure and effective priority strategy. The time complexity is proved to be significantly reduced without compromising on space efficiency. In addition, we generalize our algorithms to practical streaming settings and multi-core computing architectures. Our extensive experiments on 11 large-scale real-world datasets demonstrate the efficiency and scalability of our solutions