A 0.821-ratio purely combinatorial algorithm for maximum k-vertex cover in bipartite graphs

We study the polynomial time approximation of the max k-vertex cover problem in bipartite graphs and propose a purely combinatorial algorithm that beats the only such known algorithm, namely the greedy approach. We present a computer-assisted analysis of our algorithm, establishing that the worst case approximation guarantee is bounded below by 0.821. © Springer-Verlag Berlin Heidelberg 2016

Reactive Security for Smart Grids Using [email protected] Simulation and Reasoning

Smart grids leverage modern information and communication technology to offer new perspectives to electricity consumers, producers, and distributors. However, these new possibilities also increase the complexity of the grid and make it more prone to failures. Moreover, new advanced features like remotely disconnecting meters create new vulnerabilities and make smart grids an attractive target for cyber attackers. We claim that, due to the nature of smart grids, unforeseen attacks and failures cannot be effectively countered relying solely on proactive security techniques. We believe that a reactive and corrective approach can offer a long-term solution and is able to both minimize the impact of attacks and to deal with unforeseen failures. In this paper we present a novel approach combining a [email protected] simulation and reasoning engine with reactive security techniques to intelligently monitor and continuously adapt the smart grid to varying conditions in near real-time

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Clinical significance of serum and urinary HER2/neu protein levels in primary non-muscle invasive bladder cancer

PubMed ID: 26742964Objective: We aimed to compare serum and urinary HER2/neu levels between healthy control group and patients with non-muscle invasive bladder cancer. Additionally, we evaluated relationship of HER2/neu levels with tumor stage, grade, recurrence and progression. Materials and Methods: Fourty-four patients with primary non-muscle invasive bladder tumors (Group 2) and 40 healthy control group (Group 1) were included the study. Blood and urinary samples were collected from all patients and HER2/neu levels were measured by ELISA method. Blood and urinary HER2/neu levels and additionally, ratio of urinary HER2/neu levels to urinary creatinine levels were recorded. Demographic data and tumor characteristics were recorded. Results: Mean serum HER2/neu levels were similar between two groups and statistically significant difference wasn't observed. Urinary HER2/neu levels were significantly higher in group 2 than group 1. Ratio of urinary HER2/neu to urinary creatinine was significantly higher in group 2 than group 1, (p=0,021). Serum and urinary HER2/ neu levels were not associated with tumor stage, grade, recurrence and progression while ratio of urinary HER2/neu to urinary creatinin levels were significantly higher in high-grade tumors. HER2/neu, the sensitivity of the test was found to be 20.5%, and the specificity was 97.5%, also for the urinary HER2/neu/urinary creatinine ratio, the sensitivity and specificity of the test were found to be 31.8% and 87.5%, respectively. Conclusions: Urinary HER2/neu and ratio of urinary creatinine urine were significantly higher in patients with bladder cancer compared to healthy subjects. Large series and controlled studies are needed for use as a tumor marker