Self-Organized Monitoring in Ad-Hoc Networks

We propose in this paper a self-organized monitoring architecture for mobile ad-hoc networks based on a selective scheme where subsets of nodes are managed. These nodes are determined based on their network behavior in order to favor subsets of well-connected nodes. The key idea is to relax the requirements of the management plane, and to use these manageable subsets to monitor the performance of the overall network. We therefore propose a new performance metric to be monitored, in order to estimate the capability of ad-hoc nodes to communicate end-to-end in the network. Extensive simulations show how different parameters affect this metric.     

Synthesis and applications of fluoroalkyl end-capped cooligomers having fullerene and mixed fullerenes in the main chain

Fluoroalkanoyl peroxides reacted with FULLERENES [fullerene (C₆₀) and commercially available fullerenes (Nanom Mix^TR and Nanom Black^TR)] and radical polymerizable comonomers such as acrylic acid, N,N-dimethylacrylamide, N-(1,1-dimethyl-3-oxobutyl)acrylamide, and acryloylmorpholine to afford fluoroalkyl end-capped cooligomers having FULLERENES in the main chain under very mild conditions. Fluoroalkyl end-capped Nanom Mix and Nanom Black cooligomers thus obtained were found to exhibit a similar solubility to that of the corresponding fluoroalkyl end-capped cooligomers having fullerene in the main chain. These fluorinated FULLERENES cooligomers were found to form the nanometer size-controlled self-assembled cooligomeric aggregates in aqueous solutions. These fluoroalkyl end-capped FULLERENES cooligomers were more effective for solubilizing fullerene, Nanom Mix and Nanom Black into water, compared to those of the corresponding fluoroalkyl end-capped homooligomers having no FULLERENES in the main chain. Fluoroalkyl end-capped fullerene- and Nanom Mix-acrylic acid cooligomers were found to exhibit fluorescence spectra related to fullerene and Nanom Mix in cooligomers, respectively, in aqueous solutions. Additionally, these fluorinated fullerene- and Nanom Mix-acrylic acid cooligomers were able to increase chemiluminescence intensity related to luminol, effectively, compared to the corresponding fluorinated acrylic acid homooligomers.     

FracSym: Automated symbolic computation of Lie symmetries of fractional differential equations

In this paper, we present an algorithm for the systematic calculation of Lie point symmetries for fractional order differential equations (FDEs) using the method as described by Buckwar & Luchko (1998) and Gazizov, Kasatkin & Lukashchuk (2007, 2009, 2011). The method has been generalised here to allow for the determination of symmetries for FDEs with n$n$ independent variables and for systems of partial FDEs. The algorithm has been implemented in the new MAPLE package FracSym (Jefferson and Carminati 2013) which uses routines from the MAPLE symmetry packages DESOLVII (Vu, Jefferson and Carminati, 2012) and ASP (Jefferson and Carminati, 2013). We introduce FracSym by investigating the symmetries of a number of FDEs; specific forms of any arbitrary functions, which may extend the symmetry algebras, are also determined. For each of the FDEs discussed, selected invariant solutions are then presented.     

Digestion and absorption of free and esterified fish oil fatty acids in rats

This study was designed to test the hypotheses that digestibility and post-absorption metabolism of fish oil are influenced by impaired lipolysis and by the stereospecific composition of its triacylglycerols. Male Wistar rats were fed nonpurified diets containing one of the following fat sources: 9% native fish oil (NFO), 9% autorandomized fish oil (RFO), 8.1% fish oil-derived free fatty acids (FO-FFA) plus 0.9% glycerol, or 9% soybean oil (SO) as a reference fat. In a 24-day balance study, apparent digestibility of total dietary fat averaged 93.1% in the SO, NFO and RFO groups, and 90.9% in the FO-FFA group. Randomization of fish oil had no effect on apparent digestibility of individual fatty acids. In rats fed FO-FFA, apparent absorption of saturated and monounsaturated fatty acids was lower when compared to the NFO and RFO groups. Feeding the FO-FFA diet tended to increase plasma triglyceride content. The hypocholesterolemic effect of polyunsaturated n−3 fatty acids was not influenced by the dietary source. Similar effects on fatty acid profiles of plasma and liver phospholipids were caused by the NFO, RFO and the FO-FFA diets. We conclude that once polyunsaturated n−3 fatty acids are absorbed, their effect on lipid metabolism is not determined by the dietary source.     

Projected sequential Gaussian processes: A C++ tool for interpolation of large datasets with heterogeneous noise

Heterogeneous datasets arise naturally in most applications due to the use of a variety of sensors and measuring platforms. Such datasets can be heterogeneous in terms of the error characteristics and sensor models. Treating such data is most naturally accomplished using a Bayesian or model-based geostatistical approach; however, such methods generally scale rather badly with the size of dataset, and require computationally expensive Monte Carlo based inference. Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential Bayesian framework for inference in such projected processes is presented. The observations are considered one at a time which avoids the need for high dimensional integrals typically required in a Bayesian approach. A C++ library, gptk, which is part of the INTAMAP web service, is introduced which implements projected, sequential estimation and adds several novel features. In particular the library includes the ability to use a generic observation operator, or sensor model, to permit data fusion. It is also possible to cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the covariance parameters is explored, including the impact of the projected process approximation on likelihood profiles. We illustrate the projected sequential method in application to synthetic and real datasets. Limitations and extensions are discussed.     

Modeling and control of an airbrake electro‐hydraulic smart actuator

In this paper, an accurate model of an airbrake electro‐hydraulic smart actuator is obtained by physical considerations, and then different control strategies (variable‐gain proportional control, PT₁ control with switching integrator, and second order sub‐optimal sliding mode control) are proposed and analyzed. This application is innovative in the avionic field, and is one of the first attempts to realize a fly‐by‐wire system for airbrakes, oriented to its immediate employment and installation on current aircraft. The project was carried on with the participation of the Italian Ministry of Defense, and was commissioned to MAG, a leading provider of integrated systems and aviation services for aerospace. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Self-Adaptive Fault Tolerance in Multi-/Many-Core Systems

This paper presents a novel approach to the design of multi-/many-core systems with an adaptive level of reliability. The approach defines a layer at the operating system level that achieves fault detection/tolerance/diagnosis properties by means of thread replication and re-execution mechanisms. The layer applies the most convenient hardening mechanism to achieve the desired trade-off between reliability and performance by adapting at run-time to the changes of the working scenario. The proposed strategy has been applied in a set of experimental sessions considering a real-world parallel application, to evaluate its benefits on the final system with respect to various strategies selected at design time.     

Design and characterization of a current sensing platform for silicon-based nanopores with integrated tunneling nanoelectrodes

Solid-state nanopores have been gaining popularity in nano-biotechnology for single molecule detection, in particular for label-free high-throughput DNA sequencing. In order to address the improvement of the resolution/speed trade-off critical in this application, here we present a new two-channel current amplifier tailored for solid-state nanopore devices with integrated tunneling electrodes. The simultaneous detection of ion and tunneling currents provides enhanced molecule tracking capability. We describe the system design starting from a detailed noise analysis and device modeling, highlighting the detrimental role of the conductive silicon substrate and of all the stray capacitive couplings between the electrodes. Given the high input capacitance (0.1–1 nF), the input voltage noise has been carefully minimized choosing a discrete couple of matched low-noise JFETs as input stage, thus achieving an equivalent input noise of 1.5 nV/√Hz (corresponding to a current noise floor of 15 fA/√Hz at 10 kHz). Low-noise performance (11 pA rms noise integrated over a 75 kHz bandwidth) is preserved at a wide bandwidth (300 kHz) and high gain (100 MΩ) thanks to the adoption of an improved integrator/differentiator cascade topology. Furthermore, along with biasing networks and selectable low-pass filters, an AC-coupled channel providing additional gain has been introduced in order to “zoom” in the current signature during pore blockade events. Together with an experimental characterization of the system (and comparison with the noise performance of other instruments), the platform is validated by demonstrating the detection of λ-DNA with 20 nm pores.