Multipair Full-Duplex Relaying with Massive Arrays and Linear Processing

We consider a multipair decode-and-forward relay channel, where multiple sources transmit simultaneously their signals to multiple destinations with the help of a full-duplex relay station. We assume that the relay station is equipped with massive arrays, while all sources and destinations have a single antenna. The relay station uses channel estimates obtained from received pilots and zero-forcing (ZF) or maximum-ratio combining/maximum-ratio transmission (MRC/MRT) to process the signals. To reduce significantly the loop interference effect, we propose two techniques: i) using a massive receive antenna array; or ii) using a massive transmit antenna array together with very low transmit power at the relay station. We derive an exact achievable rate in closed-form for MRC/MRT processing and an analytical approximation of the achievable rate for ZF processing. This approximation is very tight, especially for large number of relay station antennas. These closed-form expressions enable us to determine the regions where the full-duplex mode outperforms the half-duplex mode, as well as, to design an optimal power allocation scheme. This optimal power allocation scheme aims to maximize the energy efficiency for a given sum spectral efficiency and under peak power constraints at the relay station and sources. Numerical results verify the effectiveness of the optimal power allocation scheme. Furthermore, we show that, by doubling the number of transmit/receive antennas at the relay station, the transmit power of each source and of the relay station can be reduced by 1.5dB if the pilot power is equal to the signal power, and by 3dB if the pilot power is kept fixed, while maintaining a given quality-of-service.

Validation study to compare effects of processing protocols on measured N (ε)-(carboxymethyl)lysine and N (ε)-(carboxyethyl)lysine in blood

Epidemiological studies show that elevated plasma levels of advanced glycation end products (AGEs) are associated with diabetes, kidney disease, and heart disease. Thus AGEs have been used as disease progression markers. However, the effects of variations in biological sample processing procedures on the level of AGEs in plasma/serum samples have not been investigated. The objective of this investigation was to assess the effect of variations in blood sample collection on measured N (ε)-(carboxymethyl)lysine (CML), the best characterised AGE, and its homolog, N (ε)-(carboxyethyl)lysine (CEL). The investigation examined the effect on CML and CEL of different blood collection tubes, inclusion of a stabilising cocktail, effect of freeze thaw cycles, different storage times and temperatures, and effects of delaying centrifugation on a pooled sample from healthy volunteers. CML and CEL were measured in extracted samples by ultra-performance liquid chromatography-tandem mass spectrometry. Median CML and CEL ranged from 0.132 to 0.140 mM/M lys and from 0.053 to 0.060 mM/M lys, respectively. No significant difference was shown CML or CEL in plasma/serum samples. Therefore samples collected as part of epidemiological studies that do not undergo specific sample treatment at collection are suitable for measuring CML and CEL.

Production and Processing of Spider Silk Proteins

Natural spider silk fibers have impressive mechanical properties (outperforming many man-made fibers) and are, moreover, biocompatible, biodegradable, and produced under benign conditions (using water as a solvent at ambient temperature). The problems associated with harvesting natural spider silks inspired us to devise a method to produce spider silk-like proteins biotechnologically (the first subject tackled in this highlight); we subsequently discuss their processing into various materials morphologies, and some potential technical and biomedical applications.

Automatic extruder for processing recycled polymers with ultrasound and temperature control system

Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

An Extended Event Reasoning Framework for Decision Support under Uncertainty

To provide in-time reactions to a large volume of surveil- lance data, uncertainty-enabled event reasoning frameworks for CCTV and sensor based intelligent surveillance system have been integrated to model and infer events of interest. However, most of the existing works do not consider decision making under uncertainty which is important for surveillance operators. In this paper, we extend an event reasoning framework for decision support, which enables our framework to predict, rank and alarm threats from multiple heterogeneous sources.

Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

“Signal, image and video processing” special issue: Semantic representations for social behavior analysis in video surveillance systems

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