Exact Bounded Risk Estimation When the Terminal Sample Size and Estimator Are Dependent: The Exponential Case

Suboptimal play the winner and one step ahead sequential sampling rules for the Bernoulli two armed bandit are compared with respect to several criteria.     

X-ray detection by Nb STJs above 1.4 K

We have designed and tested a 5×5 mm² chip which includes 24 island Josephson tunnel junctions (STJs) with square, circular and diamond geometries, two arrays of 100 island junctions and other detection devices. The junctions were based on Nb-AlOx-Nb trilayers, obtained on Si substrate by a process consisting of underlayer Nb deposition, self-aligned insulation and anodization steps. The junction quality was extensively tested by measurements of the I–V characteristics down to T=1.2 K. I_cR_n values up to 2.16 mV have been obtained. Preliminary results concerning the response of these samples to 6 keV X-ray radiation are discussed. Effects of the substrate on the detector response have also been observed and reported. A rough estimation of the energy resolution gives about 700 eV. The quality of the junctions is such that the electronic noise is the predominant limitation to the ultimate resolution.     

Assessment of UV-permeability in nano-ZnO filled coatings via high throughput experimentation

The degree of UV protection afforded by nano-ZnO in a polyurethane/acrylic clear topcoat was investigated. The influence of nano-ZnO concentration and dry film thickness on the optical properties (e.g., UV permeability and visible transmittance) of the coating was probed using a library of 28 samples that were prepared by high throughput techniques. A model for predicting the UV permeability of nano-ZnO filled coatings was developed and the nano-ZnO loading condition required to block >99% UV radiation was determined to be 2.0 g/m². This model can be used to assist in the development of coatings and other polymeric systems embedded with nano-ZnO to protect the coating and underlying materials (i.e., substrate) from UV degradation.

Differential Expression of Sphingolipid Metabolizing Enzymes in Spontaneously Hypertensive Rats: A Possible Substrate for Susceptibility to Brain and Kidney Damage

Alterations in the metabolism of sphingolipids, a class of biologically active molecules in cell membranes with direct effect on vascular homeostasis, are increasingly recognized as important determinant in different vascular disorders. However, it is not clear whether sphingolipids are implicated in the pathogenesis of hypertension-related cerebrovascular and renal damage. In this study, we evaluated the existence of possible abnormalities related to the sphingolipid metabolism in the brain and kidneys of two well validated spontaneously hypertensive rat strains, the stroke-prone (SHRSP) and the stroke-resistant (SHRSR) models, as compared to the normotensive Wistar Kyoto (WKY) rat strain. Our results showed a global alteration in the metabolism of sphingolipids in both cerebral and renal tissues of both hypertensive strains as compared to the normotensive rat. However, few defects, such as reduced expression of enzymes involved in the metabolism/catabolism of sphingosine-1-phosphate and in the de novo biosynthetic pathways, were exclusively detected in the SHRSP. Although further studies are necessary to fully understand the significance of these findings, they suggest that defects in specific lipid molecules and/or their related metabolic pathways may likely contribute to the pathogenesis of hypertensive target organ damage and may eventually serve as future therapeutic targets to reduce the vascular consequences of hypertension.     

Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns

Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration (N = 291) constructed from the bibliographic record of a research centerin the development and application of wireless and sensor network technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortative mixing of selected node characteristics, unveiling the researchers’ propensity to collaborate preferentially with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.     

A new approach to state observation of nonlinear systems withdelayed output

The article presents a new approach for the construction of a state observer for nonlinear systems when the output measurements are available for computations after a nonnegligible time delay. The proposed observer consists of a chain of observation algorithms reconstructing the system state at different delayed time instants (chain observer). Conditions are given for ensuring global exponential convergence to zero of the observation error for any given delay in the measurements. The implementation of the observer is simple and computer simulations demonstrate its effectiveness     

Combining sketches and wavelet analysis for multi time-scale network anomaly detection

With the rapid development and the increasing complexity of computer and communication systems and networks, traditional security technologies and measures can not meet the demand for integrated and dynamic security solutions. In this scenario, the use of Intrusion Detection Systems has emerged as a key element in network security.In this paper we address the problem proposing a wavelet-based technique able to detect network anomalies almost in real-time. In more detail, our approach is based on the combined use of sketches and wavelet analysis to reveal the anomalies in data collected at the router level. Moreover, to improve the detection rate we propose a multi time-scale analysis. The performance analysis, presented in this paper, demonstrates the effectiveness of the proposed method.