Quantum state storage and processing for polarization qubits in an inhomogeneously broadened Λ-type three-level medium

We address the propagation of a single photon pulse with two polarization components, i.e., a polarization qubit, in an inhomogeneously broadened "phaseonium" \Lambda-type three-level medium. We combine some of the non-trivial propagation effects characteristic for this kind of coherently prepared systems and the controlled reversible inhomogeneous broadening technique to propose several quantum information processing applications, such as a protocol for polarization qubit filtering and sieving as well as a tunable polarization beam splitter. Moreover, we show that, by imposing a spatial variation of the atomic coherence phase, an effcient quantum memory for the incident polarization qubit can be also implemented in \Lambda-type three-level systems.

Processing of short auditory stimuli:The rapid audio sequential presentation paradigm (RASP)

Human listeners seem to be remarkably able to recognise acoustic sound sources based on timbre cues. Here we describe a psychophysical paradigm to estimate the time it takes to recognise a set of complex sounds differing only in timbre cues: both in terms of the minimum duration of the sounds and the inferred neural processing time. Listeners had to respond to the human voice while ignoring a set of distractors. All sounds were recorded from natural sources over the same pitch range and equalised to the same duration and power. In a first experiment, stimuli were gated in time with a raised-cosine window of variable duration and random onset time. A voice/non-voice (yes/no) task was used. Performance, as measured by d', remained above chance for the shortest sounds tested (2 ms); d's above 1 were observed for durations longer than or equal to 8 ms. Then, we constructed sequences of short sounds presented in rapid succession. Listeners were asked to report the presence of a single voice token that could occur at a random position within the sequence. This method is analogous to the "rapid sequential visual presentation" paradigm (RSVP), which has been used to evaluate neural processing time for images. For 500-ms sequences made of 32-ms and 16-ms sounds, d' remained above chance for presentation rates of up to 30 sounds per second. There was no effect of the pitch relation between successive sounds: identical for all sounds in the sequence or random for each sound. This implies that the task was not determined by streaming or forward masking, as both phenomena would predict better performance for the random pitch condition. Overall, the recognition of familiar sound categories such as the voice seems to be surprisingly fast, both in terms of the acoustic duration required and of the underlying neural time constants.

The Pan-STARRS Moving Object Processing System

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves >99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a nonphysical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss, and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains highly efficient at detecting objects but drops to 80% efficiency at producing orbits. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.

A review of ADP processing software

Data processing is an essential part of Acoustic Doppler Profiler (ADP) surveys, which have become the standard tool in assessing flow characteristics at tidal power development sites. In most cases, further processing beyond the capabilities of the manufacturer provided software tools is required. These additional tasks are often implemented by every user in mathematical toolboxes like MATLAB, Octave or Python. This requires the transfer of the data from one system to another and thus increases the possibility of errors. The application of dedicated tools for visualisation of flow or geographic data is also often beneficial and a wide range of tools are freely available, though again problems arise from the necessity of transferring the data. Furthermore, almost exclusively PCs are supported directly by the ADP manufacturers, whereas small computing solutions like tablet computers, often running Android or Linux operating systems, seem better suited for online monitoring or data acquisition in field conditions. While many manufacturers offer support for developers, any solution is limited to a single device of a single manufacturer. A common data format for all ADP data would allow development of applications and quicker distribution of new post processing methodologies across the industry.

IPPro: FPGA based Image Processing Processor

The paper presents IPPro which is a high performance, scalable soft-core processor targeted for image processing applications. It has been based on the Xilinx DSP48E1 architecture using the ZYNQ Field Programmable Gate Array and is a scalar 16-bit RISC processor that operates at 526MHz, giving 526MIPS of performance. Each IPPro core uses 1 DSP48, 1 Block RAM and 330 Kintex-7 slice-registers, thus making the processor as compact as possible whilst maintaining flexibility and programmability. A key aspect of the approach is in reducing the application design time and implementation effort by using multiple IPPro processors in a SIMD mode. For different applications, this allows us to exploit different levels of parallelism and mapping for the specified processing architecture with the supported instruction set. In this context, a Traffic Sign Recognition (TSR) algorithm has been prototyped on a Zedboard with the colour and morphology operations accelerated using multiple IPPros. Simulation and experimental results demonstrate that the processing platform is able to achieve a speedup of 15 to 33 times for colour filtering and morphology operations respectively, with a reduced design effort and time.

Processing, microstructure and mechanical properties of air plasma-sprayed ceria-yttria co-stabilized zirconia coatings

Thermal barrier coatings (TBCs) are widely adopted to protect mechanical components in gas turbine engines operating at high temperature. Basically, the surface temperature of these components must be low enough to retain material properties within acceptable bounds and to extend component life. From this standpoint, air plasma-sprayed (APS) ceria and yttria co-stabilized zirconia (CYSZ) is particularly promising because it provides enhanced thermal insulation capabilities and resistance to hot corrosion. However, essential mechanical properties, such as hardness and Young's modulus, have been less thoroughly investigated. Knowledge of Young's modulus is of concern because it has a significant effect on strain tolerance and stress level and, hence, on durability. The focus of the present study was to determine the mechanical properties of APS CYSZ coatings. In particular, X-ray diffraction (XRD) is adopted for phase analysis of powders and as-sprayed coatings. In addition, scanning electron microscopy (SEM) and image analysis (IA) are employed to explore coating microstructure and porosity. Finally, the Young's modulus of the coating is determined using nanoindentation and a resonant method. The results obtained are then discussed and a cross-check on their consistency is carried out by resorting to a micromechanical model. © 2010 Blackwell Publishing Ltd.

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.

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

No abstract available