Abstract
Local pulse-wave velocity (PWV) is recognized as the simplest and most reproducible process of non-invasively assessing the vascular marker of arterial stiffness that allowing the risk of cardiovascular diseases to be determinate. Devices currently available for local PWV measurement have not yet been generalized to clinical practice since they require high technical expertise and most of them are limited in precision, due to the lack of reliable signal processing methods. This work describes a new type of probes, based on a piezoelectric sensor in different configurations, single probe and double probe. The principle of PWV measurement involves determination of the pulse transit time between the signals acquired simultaneously by both piezoelectric placed 23 mm apart in the same probe. The double probe characterization is accomplished in different studies, carried out in a dedicated test bench system, capable of reproducing a range of clinically relevant properties of the cardiovascular system.

Abstract
This paper envisages showing the potential of innovative non-invasive techniques based on affordable and easily operated instrumentation as well as user-friendly computer aided algorithms in the screening of cardiovascular (CV) diseases. These techniques are based on the assumption that arterial stiffness is currently an important predicator of the CV diseases development and can be assessed by analyzing the arterial pressure waveform (APW). A previously developed PZ based device for non-invasive APW capture is currently under test in clinical environment, using a heterogeneous population constituted by healthy and unhealthy subjects. A dedicated Matlab analysis tool was designed and developed to extract relevant information and further APW analysis. Several recordings of the APW in the same day and in consecutive months are being performed by trained observers, to evaluate its reproducibility. Data mining analysis is subsequently the last task where the Weka 3-6-5 package software is used. The usefulness of developing data mining algorithms for cardiovascular applications can benefit the CV screenings contributing for the early identification of arterial stiffness related patterns.

Abstract

Abstract
Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumption. Having a high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

Abstract
Optical characterization and internal structure of biological tissues is highly important for biomedical optics. In particular for optical clearing processes, such information is of vital importance to understand the mechanisms involved through the variation of the refractive indices of tissue components. The skeletal muscle presents a fibrous structure with an internal arrangement of muscle fiber cords surrounded by interstitial fluid that is responsible for strong light scattering. To determine the refractive index of muscle components we have used a simple method of measuring tissue mass and refractive index during dehydration. After performing measurements for natural and ten dehydration states of the muscle samples, we have determined the dependence between the refractive index of the muscle and its water content. Also, we have joined our measurements with some values reported in literature to perform some calculations that have permitted to determine the refractive index of the dried muscle fibers and their corresponding volume percentage inside the natural muscle.

Abstract
Ubiquitous Internet access is becoming a major requirement for end-users due to the increasing number of services and applications supported over the Internet. Extending the coverage of current Wi-Fi infrastructures installed in companies, universities and cities, has been considered a solution to help in fulfilling this requirement, namely when it comes to wireless and nomadic Internet access. This paper describes and analyses a new and simple solution, called Wi-Fi network Infrastructure eXtension (WiFIX), aimed at extending current Wi-Fi infrastructures. WiFIX is based on standard IEEE 802.1D bridges and a single-message protocol that is able to self-organize the network, and it only requires software changes in IEEE 802.11 access points (APs); no changes to IEEE 802.11 stations are needed. Overhead analysis and experimental results show both the higher efficiency of the solution compared to the IEEE 802.11s draft standard and its good performance as far as data throughput, delay and packet loss are concerned. Copyright (C) 2010 John Wiley & Sons, Ltd.