Signal reconstruction in sensor networks with flat and clustered topologies

We apply signal processing techniques to the study of wireless sensor networks, whose nodes are deployed over a planar region for environmental monitoring. We address the problem of reconstructing the phenomenon of interest at a sink node, from the samples gathered by the sensors, and we evaluate the system performance in presence of both a flat and a clustered network topology. When the sensors are grouped into (possibly overlapping) clusters, the data collected within each cluster are compressed by the cluster head and sent to the sink node. By representing the compressed data through the Fourier coefficients of the field spectrum, we analyze both the case where the sensor positions are known to the sink, and the case where they are available at the cluster head only. We show that clustering significantly reduces the energy expenditure due to data transmission with respect to the case of a flat network topology, and, most importantly, we derive the possible degradation of the quality of the reconstructed field due to compression.     

Information Density Estimation for Content Retrieval in MANETs

The paper focuses on a cooperative environment in wireless ad hoc networks, where mobile nodes share information in a peer-to-peer fashion. Nodes follow a pure peer-to-peer approach (i.e., without the intervention of servers), thus requiring an efficient query/response propagation algorithm to prevent network congestion. The main contribution of the paper is the proposal of a novel solution, called Eureka, that identifies the regions of the network where the required information is more likely to be stored and steers the queries toward those regions. To discriminate among regions, the concept of information density is introduced, along with a procedure that allows nodes its estimation. Eureka does not require the use of satellite positioning systems, and proves to be very effective in both vehicular and pedestrian environments.     

An Analytical Model for Wireless Sensor Networks with Sleeping Nodes

We consider a wireless sensor network whose nodes may enter the so-called sleep mode, corresponding to low power consumption and reduced operational capabilities. We develop a Markov model of the network representing: 1) the behavior of a single sensor as well as the dynamics of the entire network, 2) the channel contention among sensors, and 3) the data routing through the network. We use this model to evaluate the system performance in terms of energy consumption; network capacity, and data delivery delay. Analytical results present a very good matching with simulation results for a large variety of system scenarios, showing the accuracy of our approach     

Physico-Chemical Characterization of Sesame Oil Derivatives

Ozone treatment of commercially available vegetable oils gives rise to the formation of chemical species that are responsible for the therapeutic properties of ozonated oil derivatives in dermatological diseases. In the last years, these products have been successfully used as a topical disinfectant in a number of serious skin affections. The medical application of empirically prepared ozonated oil has yielded striking improvements with unexpected and rapid healing, compelling us to begin a long-range study aiming first to define the main characteristics of the most common ozonated vegetable oils, about which there is usually no medical consensus because of the lack of standardization of their technological parameters. Sesame oil was selected because of its great amount of polyunsaturated acyl groups, as well as natural antioxidants. Moreover, we have determined the kinetics and optimal conditions of ozonation (e.g., ozone concentrations, time of exposure, temperature) for obtaining an ozonated oil characterized by well-established technological and physico-chemical properties, namely an accurate peroxide value determination. On the basis of the results, we have gained an understanding of the modifications of the vegetable oils during the ozonation process.     

MAC-layer channel utilisation enhancements for wireless mesh networks

The authors focus on a wireless mesh network, that is, an ad hoc IEEE 802.11-based network whose nodes are either user devices or Access Points providing access to the mesh network or to the Internet. By relying on some work done within the IEEE 802.11s TG, the network nodes can use one control channel and one or more data channels, each on separate frequencies. Then, some problems related to channel access are identified and a MAC scheme is proposed that specifically addresses the problem of hidden terminals and the problem of coexisting control and data traffic on different frequency channels. An analytical model of the MAC scheme is presented and validated by using the Omnet++ simulator. Through the developed model, we show that our solution achieves very good performance both in regular and in very fragmented mesh topologies, and it significantly outperforms the standard 802.11 solution.     

Energy efficient battery management

A challenging aspect of mobile communications consists in exploring ways in which the available run time of terminals can be maximized. We present a detailed electrochemical battery model and a simple stochastic model that captures the fundamental behavior of the battery. The stochastic model is then matched to the electrochemical model and used to investigate battery management techniques that may improve the energy efficiency of radio communication devices. We consider an array of electrochemical cells. Through simple scheduling algorithms, the discharge from each cell is properly shaped to optimize the charge recovery mechanism, without introducing any additional delay in supplying the required power. Then, a battery management scheme, which exploits knowledge of the cells' state of charge, is implemented to achieve a further improvement in the battery performance. In this case, the discharge demand may be delayed. Results indicate that the proposed battery management techniques improve system performance no matter which parameters values are chosen to characterize the cells' behavior     

Identification of differentially expressed proteins in papillary thyroid carcinomas with V600E mutation of BRAF

BRAF, a serine/threonine kinase of the RAF family, is a downstream transducer of the RAS-regulated MAPK pathway. V600E mutation of BRAF protein is the most common genetic alteration occurring in papillary thyroid carcinomas and is prognostic of poor clinicopathological outcomes. Protein expression in the subclass of PTC bearing the BRAF(V600E) mutation was investigated by using 2-DE and MS/MS techniques and compared to that of matched normal thyroid tissues from seven patients. 2-D gel image analysis revealed that the expression of eight polypeptide spots, corresponding to five proteins, were significantly underexpressed in PTC bearing BRAF(V600E) mutation whereas 25 polypeptides, representing 19 distinct proteins, were significantly upregulated in tumour tissue, as compared to normal thyroid. Among the differentially expressed polypeptides, mitochondrial proteins, ROS-scavenger enzymes, apoptosis-related proteins as well as proteins involved in tumour cell proliferation were identified. Although dissimilarities between the present results and those previously reported can be ascribed to the use of different 2-DE techniques, the possibility that BRAF(V600E) mutation is responsible for changes in protein expression distinct from those induced by other oncogenes cannot be ruled out.     

Improving battery performance by using traffic shaping techniques

We present a new approach to minimizing energy consumption by addressing battery management techniques that exploit the charge recovery effect inherent to many secondary storage batteries. We review results that pertain to the capacity of a battery and its dependence on the intensity of the discharge current. The phenomenon of charge recovery that takes place under bursty or pulsed discharge conditions is identified as a mechanism that can be exploited to enhance the capacity of a battery. The bursty nature of many data traffic sources suggests that data transmissions may provide natural opportunities for charge recovery. We explore stochastic models to track charge recovery in conjunction with bursty discharge processes. Using the postulated model, we identify the improvement to battery capacity that results from a pulsed discharge driven by bursty stochastic discharge demand. The insight from this analysis leads us to propose discharge shaping techniques that trade-off energy efficiency with delay     

Route Stability in MANETs under the Random Direction Mobility Model

A fundamental issue arising in mobile ad hoc networks (MANETs) is the selection of the optimal path between any two nodes. A method that has been advocated to improve routing efficiency is to select the most stable path so as to reduce the latency and the overhead due to route reconstruction. In this work, we study both the availability and the duration probability of a routing path that is subject to link failures caused by node mobility. In particular, we focus on the case where the network nodes move according to the Random Direction model, and we derive both exact and approximate (but simple) expressions of these probabilities. Through our results, we study the problem of selecting an optimal route in terms of path availability. Finally, we propose an approach to improve the efficiency of reactive routing protocols.