Identifying peer‐to‐peer communities in the network by connection graph analysis

In this paper we present a unified solution to identify peer‐to‐peer (P2P) communities operating in the network. We propose an algorithm that is able to progressively discover nodes cooperating in a P2P network and to identify that P2P network. Starting from a single known node, we can easily identify other nodes in the P2P network, through the analysis of widely available and standardized IPFIX (NetFlow) data. Instead of relying on the analysis of content characteristics or packet properties, we monitor connections of known nodes in the network and then progressively discover other nodes through the analysis of their mutual contacts. We show that our method is able to discover cooperating nodes in many P2P networks and present the real computational requirements of the algorithm on a large network. The use of standardized input data allows for easy deployment onto real networks. Copyright © 2014 John Wiley & Sons, Ltd.     

Renoprotective Angiographic Polymersomes

Computed tomography (CT) angiography is powerful for the diagnosis of vascular diseases. Unfortunately, this method usually requires a high dosage of iodinated contrast agents, which can lead to severe elevation of reactive oxygen species (ROS) levels within kidneys. This causes oxidative stress, apoptosis, and hence contrast-induced nephropathy (CIN), a leading cause of iatrogenic renal failure, especially for patients with renal insufficiency. Herein, a route is shown to circumvent such problems with the usage of rationally designed renoprotective angiographic polymersomes (RAPs) as blood pool CT contrast agents. RAPs are biodegradable nanoparticles prepared via self-assembly of poly(ethylene oxide)-block-poly(triiodobenzoic chloride-conjugated polylysine-stat-phenylboronic acid pinacol ester-conjugated polylysine) (PEO₄₅-b-P[(Lys-IBC)₄₅-stat-(Lys-PAPE)₁₅]). The key to the efficiency of such nanoparticles as renoprotective contrast agents arises from the rationally chosen repeat units: Lys-IBC exhibits a concentration-dependent X-ray attenuation capability and Lys-PAPE introduces an ROS-scavenging ability to the polymersome. The study shows that RAPs can reduce the risk of CIN in mice with kidney injury. Additionally, a 5-fold increase in angiographic live time is observed using RAPs, compared to commonly used iodinated small molecule contrast agents. In summary, a new strategy is proposed for the design of a renoprotective angiographic contrast agent that is capable of reducing the risk of CIN.     

Robust Single Molecule Magnet Monolayers on Graphene and Graphite with Magnetic Hysteresis up to 28 K

The chemical functionalization of fullerene single molecule magnet Tb₂@C₈₀(CH₂Ph) enables the facile preparation of robust monolayers on graphene and highly oriented pyrolytic graphite from solution without impairing their magnetic properties. Monolayers of endohedral fullerene functionalized with pyrene exhibit magnetic bistability up to a temperature of 28 K. The use of pyrene terminated linker molecules opens the way to devise integration of spin carrying units encapsulated by fullerene cages on graphitic substrates, be it single-molecule magnets or qubit candidates.     

Binary Cellulose Nanocrystal Blends for Bioinspired Damage Tolerant Photonic Films

Most attempts to emulate the mechanical properties of strong and tough natural composites using helicoidal films of wood‐derived cellulose nanocrystals (w‐CNCs) fall short in mechanical performance due to the limited shear transfer ability between the w‐CNCs. This shortcoming is ascribed to the small w‐CNC‐w‐CNC overlap lengths that lower the shear transfer efficiency. Herein, we present a simple strategy to fabricate superior helicoidal CNC films with mechanical properties that rival those of the best natural materials and are some of the best reported for photonic CNC materials thus far. Assembling the short w‐CNCs with a minority fraction of high aspect ratio CNCs derived from tunicates (t‐CNCs), we report remarkable simultaneous enhancement of all in‐plane mechanical properties and out‐of‐plane flexibility. The important role of t‐CNCs is revealed by coarse grained molecular dynamics simulations where the property enhancement are due to increased interaction lengths and the activation of additional toughening mechanisms. At t‐CNC contents greater than 5% by mass the mixed films also display UV reflecting behaviour. These damage tolerant optically active materials hold great promise for application as protective coatings. More broadly, we expect the strategy of using length‐bidispersity to be adaptable to mechanically enhancing other matrix‐free nanoparticle ensembles.     

Micrometer‐Scale Porous Buckling Shell Actuators Based on Liquid Crystal Networks

Micrometer‐scale liquid crystal network (LCN) actuators have potential for application areas like biomedical systems, soft robotics, and microfluidics. To fully harness their power, a diversification in production methods is called for, targeting unconventional shapes and complex actuation modes. Crucial for controlling LCN actuation is the combination of macroscopic shape and molecular‐scale alignment in the ground state, the latter becoming particularly challenging when the desired shape is more complex than a flat sheet. Here, one‐step processing of an LCN precursor material in a glass capillary microfluidic set‐up to mold it into thin shells is used, which are stretched by osmosis to reach a diameter of a few hundred micrometers and thickness on the order of a micrometer, before they are UV crosslinked into an LCN. The shells exhibit radial alignment of the director field and the surface is porous, with pore size that is tunable via the osmosis time. The LCN shells actuate reversibly upon heating and cooling. The decrease in order parameter upon heating induces a reduction in thickness and expansion of surface area of the shells that triggers continuous buckling in multiple locations. Such buckling porous shells are interesting as soft cargo carriers with capacity for autonomous cargo release.     

Iterative Joint Channel Estimation and Signal Detection for OFDM System in Double Selective Channels

Intercarrier interference caused by fast time-varying multipath fading channels degrades the system performance of high-mobility orthogonal frequency division multiplexing systems. This study considers the challenging problem of joint channel estimation and signal detection in high mobility environments. The estimation method is based on a pilot-aided linear approximation channel modeling and iterative process. After each iteration, the channel estimates are refined with the fed-back detection signal. The channel is re-estimated iteratively, detected increasingly reliable signals. The proposed method is independent of the Doppler-spectrum, delay-profile shape and the number of paths. Numerical simulation results indicate that the proposed method is highly robust to fast time-varying multipath fading channels.     

Performance bounds for VDE-SAT R-Mode

There has been growing interest within the satellite navigation community in the possibility of delivering positioning and timing services from existing or emerging constellations of Low-Earth Orbit communication satellites. At the same time, the international maritime community has been investigating the potential use of communication signals transmitted from shore-based stations for positioning—a concept commonly referred to as ‘ranging mode’, or R-Mode. The driving force for these developments is the desire to reduce the reliance on traditional Global Navigation Satellite Systems (GNSS). One of the technologies being considered for use in R-Mode is the evolution of the Automatic Identification System (AIS) known as the Very High Frequency Data Exchange System (VDES). VDES has a terrestrial and a satellite component. The feasibility of using terrestrial VDES transmissions for ranging was studied in a previous publication by the authors. This paper builds on the previous study and extends its results to the satellite component of VDES. Statistical bounds on the ranging error are derived for all downlink waveforms currently being considered for use in satellite VDES and for several custom-designed transmission formats. The analysis supports the feasibility of using both the existing and custom waveforms in ranging applications and points to related trade-offs that will need to be considered in the design of satellite VDES R-Mode systems.     

Energy-efficient Rate Adaptation MAC Protocol for Ad Hoc Wireless Networks

In this paper, two novel energy-efficient rate adaptation schemes are presented. The proposed protocols use the Distributed Power Control (DPC) algorithm to predict the channel state and determine the necessary transmission power which optimizes the energy consumption. The first proposed rate adaptation scheme heuristically alters the modulation rate to balance the energy-efficiency and the required throughput which is estimated with queue fill ratio. Moreover, the back-off scheme is incorporated to mitigate congestion and reduce packet losses due to buffer overflows thus minimizing energy consumption. Consequently, the nodes will conserve energy when the traffic is low, offer higher throughput when needed and save energy during congestion by limiting transmission rates. The second rate adaptation scheme employs dynamic programming (DP) principle to analytically select modulation rate and a burst size to be used during transmission. The proposed quadratic cost-function minimizes the energy consumption while alleviating network congestions and buffer overflows. The proposed DP solution renders a Riccati equation ultimately providing an optimal rate selection. The simulation results indicate that an increase in throughput by 96% and energy-efficiency by 131% is observed when compared to other available protocols, for example Receiver Based AutoRate (RBAR).

Using an eye tracker for accurate eye movement artifact correction

We present a new method to correct eye movement artifacts in electroencephalogram (EEG) data. By using an eye tracker, whose data cannot be corrupted by any electrophysiological signals, an accurate method for correction is developed. The eye-tracker data is used in a Kalman filter to estimate which part of the EEG is of ocular origin. The main assumptions for optimal correction are summed and their validity is proven. The eye-tracker-based correction method is objectively evaluated on simulated data of four different types of eye movements and visually evaluated on experimental data. Results are compared to three established correction methods: Regression, Principal Component Analysis, and Second-Order Blind Identification. A comparison of signal to noise ratio after correction by these methods is given in Table II and shows that our method is consistently superior to the other three methods, often by a large margin. The use of a reference signal without electrophysiological influences, as provided by an eye tracker, is essential to achieve optimal eye movement artifact removal.