Automated Cloud Patch Segmentation of FY-2C Image Using Artificial Neural Network and Seeded Region Growing Method (ANN-SRG)

This paper presents a new algorithm Artificial Neural Network and Seeded Region Growing (ANN-SRG) to segment cloud patches of different types. This method used Seeded Region Growing (SRG) as segmentation algorithm, and Artificial Neural Network (ANN) Cloud classification as preprocessing algorithm. It can be trained to respond favorably to cloud types of interest, and SRG method is no longer sensitive to the seeds selection and growing rule. To illustrate the performance of this technique, this paper applied it on Chinese first operational geostationary meteorological satellite FengYun-2C (FY-2C) in three infrared channels (IR1, 10.3- 11.33BC;m; IR2, 11.5-12.53BC;m and WV 6.3-7.63BC;m) with 2864 samples collected by meteorologists in June, July, and August in 2007. The result shows that this method can distinguish and segment cloud patches of different types, and improves the traditional SRG algorithm by reducing the uncertainty of seeds extraction and regional growth

Effect of source tampering in the security of quantum cryptography

The security of source has become an increasingly important issue in quantum cryptography. Based on the framework of measurement-device-independent quantum-key-distribution (MDI-QKD), the source becomes the only region exploitable by a potential eavesdropper (Eve). Phase randomization is a cornerstone assumption in most discrete-variable (DV-) quantum communication protocols (e.g., QKD, quantum coin tossing, weak coherent state blind quantum computing, and so on), and the violation of such an assumption is thus fatal to the security of those protocols. In this paper, we show a simple quantum hacking strategy, with commercial and homemade pulsed lasers, by Eve that allows her to actively tamper with the source and violate such an assumption, without leaving a trace afterwards. Furthermore, our attack may also be valid for continuous-variable (CV-) QKD, which is another main class of QKD protocol, since, excepting the phase random assumption, other parameters (e.g., intensity) could also be changed, which directly determine the security of CV-QKD.Comment: 9 pages, 6 figure

Elevated circulating level of P2X7 receptor is related to severity of coronary artery stenosis and prognosis of acute myocardial infarction

Background: Acute myocardial infarction (AMI) is a severely life-threatening cardiovascular disease. Previous research has identified an association between the P2X7 receptor (P2X7R) and the development of atherosclerosis. However, the correlation of its expression with the clinical prognosis of patients with AMI remains unclear. The present study aimed to investigate the potential role of P2X7R in Chinese patients with AMI. Methods: Seventy-nine patients with AMI and 48 controls were consecutively enrolled in this prospective observational study. Circulating P2X7R mRNA expression levels and other clinical variables were determined upon admission to the hospital. Patients were followed up for 360 days, and the end-point was considered as the occurrence of major adverse cardiovascular events (MACE). Results: Circulating P2X7R mRNA expression level in peripheral blood mononuclear cells of patients with AMI were significantly higher than those in controls and had promising diagnostic ability of AMI with an area under the curve of 0.928. Furthermore, P2X7R was demonstrated to be correlated positively with the severity of coronary artery stenosis. Additionally, this is the first study to indicate that higher P2X7R mRNA expression is associated with a higher rate of MACE within 360 days after AMI. Conclusions: The present study showed that the circulating level of P2X7R was elevated in AMI patients and was closely associated with the severity of coronary artery stenosis and prognosis of AMI