From bit level systolic arrays to HDTV processor chips

The paper starts presents the work initially carried out by Queen's University and RSRE (now Qinetiq) in the development of advanced architectures and microchips based on systolic array architectures. The paper outlines how this has led to the development of highly complex designs for high definition TV and highlights work both on advanced signal processing architectures and tool flows for advanced systems. © 2006 IEEE.

Improved Linear Transmit Processing for Single-User and Multi-User MIMO Communications Systems

In this paper, we propose a novel linear transmit precoding strategy for multiple-input, multiple-output (MIMO) systems employing improper signal constellations. In particular, improved zero-forcing (ZF) and minimum mean square error (MMSE) precoders are derived based on modified cost functions, and are shown to achieve a superior performance without loss of spectrum efficiency compared to the conventional linear and nonlinear precoders. The superiority of the proposed precoders over the conventional solutions are verified by both simulation and analytical results. The novel approach to precoding design is also applied to the case of an imperfect channel estimate with a known error covariance as well as to the multi-user scenario where precoding based on the nullspace of channel transmission matrix is employed to decouple multi-user channels. In both cases, the improved precoding schemes yield significant performance gain compared to the conventional counterparts.

The exponentiated convex variable step-size (ECVSS) algorithm

For some time there is a large interest in variable step-size methods for adaptive filtering. Recently, a few stochastic gradient algorithms have been proposed, which are based on cost functions that have exponential dependence on the chosen error. However, we have experienced that the cost function based on exponential of the squared error does not always satisfactorily converge. In this paper we modify this cost function in order to improve the convergence of exponentiated cost function and the novel ECVSS (exponentiated convex variable step-size) stochastic gradient algorithm is obtained. The proposed technique has attractive properties in both stationary and abrupt-change situations. (C) 2010 Elsevier B.V. All rights reserved.

Parametric FIR Design of Propagation Loss Filters in Digital Waveguide String Models

One of the attractive features of sound synthesis by physical modeling is the potential to build acoustic-sounding digital instruments that offer more flexibility and different options in its design and control than their real-life counterparts. In order to develop such virtual-acoustic instruments, the models they are based on need to be fully parametric, i.e., all coefficients employed in the model are functions of physical parameters that are controlled either online or at the (offline) design stage. In this letter we show how propagation losses can be parametrically incorporated in digital waveguide string models with the use of zero-phase FIR filters. Starting from the simplest possible design in the form of a three-tap FIR filter, a higher-order FIR strategy is presented and discussed within the perspective of string sound synthesis with digital waveguide models.

Optical Nonlocalities and Additional Waves in Epsilon-Near-Zero Metamaterials

We analyze the optical properties of plasmonic nanorod metamaterials in the epsilon-near-zero regime and show, both theoretically and experimentally, that the performance of these composites is strongly affected by nonlocal response of the effective permittivity tensor. We provide the evidence of interference between main and additional waves propagating in the room-temperature nanorod metamaterials and develop an analytical description of this phenomenon. Additional waves are present in the majority of low-loss epsilon-near-zero structures and should be explicitly considered when designing applications of epsilon-near-zero composites, as they represent a separate communication channel.

Targeted 3' processing of antisense transcripts triggers Arabidopsis FLC chromatin silencing.

Noncoding RNA is emerging as an important regulator of gene expression in many organisms. We are characterizing RNA-mediated chromatin silencing of the Arabidopsis major floral repressor gene, FLC. Through suppressor mutagenesis, we identify a requirement for CstF64 and CstF77, two conserved RNA 3'-end-processing factors, in FLC silencing. However, FLC sense transcript 3' processing is not affected in the mutants. Instead, CstF64 and CstF77 are required for 3' processing of FLC antisense transcripts. A specific RNA-binding protein directs their activity to a proximal antisense polyadenylation site. This targeted processing triggers localized histone demethylase activity and results in reduced FLC sense transcription. Targeted 3' processing of antisense transcripts may be a common mechanism triggering transcriptional silencing of the corresponding sense gene.

Raman spectroscopy for the detection of AGEs/ALEs

Raman spectroscopy is a noninvasive, nondestructive tool for capturing multiplexed biochemical information across diverse molecular species including proteins, lipids, DNA, and mineralizations. Based on light scattering from molecules, cells, and tissues, it is possible to detect molecular fingerprints and discriminate between subtly different members of each biochemical class. Raman spectroscopy is ideal for detecting perturbations from the expected molecular structure such as those occurring during senescence and the modification of long-lived proteins by metabolic intermediates as we age. Here, we describe the sample preparation, data acquisition, signal processing, data analysis and interpretation involved in using Raman spectroscopy for detecting age-related protein modifications in complex biological tissues.

Quantum circuits for spin and flavor degrees of freedom of quarks forming nucleons

We discuss the quantum-circuit realization of the state of a nucleon in the scope of simple simmetry groups. Explicit algorithms are presented for the preparation of the state of a neutron or a proton as resulting from the composition of their quark constituents. We estimate the computational resources required for such a simulation and design a photonic network for its implementation. Moreover, we highlight that current work on three-body interactions in lattices of interacting qubits, combined with the measurement-based paradigm for quantum information processing, may also be suitable for the implementation of these nucleonic spin states.

Improved conjugate gradient implementation for least squares support vector machines

As a promising method for pattern recognition and function estimation, least squares support vector machines (LS-SVM) express the training in terms of solving a linear system instead of a quadratic programming problem as for conventional support vector machines (SVM). In this paper, by using the information provided by the equality constraint, we transform the minimization problem with a single equality constraint in LS-SVM into an unconstrained minimization problem, then propose reduced formulations for LS-SVM. By introducing this transformation, the times of using conjugate gradient (CG) method, which is a greatly time-consuming step in obtaining the numerical solution, are reduced to one instead of two as proposed by Suykens et al. (1999). The comparison on computational speed of our method with the CG method proposed by Suykens et al. and the first order and second order SMO methods on several benchmark data sets shows a reduction of training time by up to 44%. (C) 2011 Elsevier B.V. All rights reserved.

Rao-Blackwellised particle filter for colour-based tracking

Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved

A spatio-temporal 2D-models framework for human pose recovery in monocular sequences

This paper addresses the pose recovery problem of a particular articulated object: the human body. In this model-based approach, the 2D-shape is associated to the corresponding stick figure allowing the joint segmentation and pose recovery of the subject observed in the scene. The main disadvantage of 2D-models is their restriction to the viewpoint. To cope with this limitation, local spatio-temporal 2D-models corresponding to many views of the same sequences are trained, concatenated and sorted in a global framework. Temporal and spatial constraints are then considered to build the probabilistic transition matrix (PTM) that gives a frame to frame estimation of the most probable local models to use during the fitting procedure, thus limiting the feature space. This approach takes advantage of 3D information avoiding the use of a complex 3D human model. The experiments carried out on both indoor and outdoor sequences have demonstrated the ability of this approach to adequately segment pedestrians and estimate their poses independently of the direction of motion during the sequence. (c) 2008 Elsevier Ltd. All rights reserved.

An efficient particle filter for color-based tracking in complex scenes

In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

Optical Cooling of Atoms in Microtraps by Time-Delayed Reflection

We present a theoretical analysis of a novel scheme for optical cooling of particles that does not in principle require a closed optical transition. A tightly confined laser beam interacting with a trapped particle experiences a phase shift, which upon reflection from a mirror or resonant microstructure produces a time-delayed optical potential for the particle. This leads to a nonconservative force and friction. A quantum model of the system is presented and analyzed in the semiclassical limit.

How pathogen-derived cysteine proteases modulate host immune responses

In mammals, cysteine proteases are essential for the induction and development of both innate and adaptive immune responses. These proteases play a role in antigen-and pathogen-recognition and elimination, signal processing and cell homeostasis. Many pathogens also secrete cysteine proteases that often act on the same target proteins as the mammalian proteases and thereby can modulate host immunity from initial recognition to effector mechanisms. Pathogen-derived proteases range from nonspecific proteases that degrade multiple proteins involved in the immune response to enzymes that are very specific in their mode of action. Here, we overview current knowledge of pathogen-derived cysteine proteases that modulate immune responses by altering the normal function of key receptors or pathways in the mammalian immune system.