On the effect of power amplifier nonlinearity on MIMO transmit diversity systems

Nonlinearity of high-power amplifier (HPA) plays a crucial role in the performance of multiple-input multiple-output (MIMO) systems. In this paper, we investigate the performance of MIMO orthogonal space-time block coding (STBC) systems in the presence of nonlinear HPA. Specifically, we assess the impact of HPA nonlinearity on the average symbol error probability (SEP), total degradation (TD), and system capacity of orthogonal STBC in uncorrelated Nakagami-m fading channels. Numerical results are provided and show the effects of several system parameters, such as the output back-off (OBO) of nonlinear HPA, numbers of transmit and receive antennas, and modulation order of quadrature amplitude modulation (QAM), on performance.

Oblique h.f. radiowave propagation in the main trough region of the ionosphere

The propagation of 7.335 MHz, c.w. signals over a 5212 km sub-auroral, west-east path is studied. Measurements and semi-empirical predictions are made of the amplitude distributions and Doppler shifts of the received signals. The observed amplitude distribution is fitted with one produced by a numerical fading model, yielding the power losses suffered by the signals during propagation via the predominating modes. The signals are found to suffer exceptionally low losses at certain local times under geomagnetically quiet conditions. The mid-latitude trough in the F2 peak ionization density is predicted by a statistical model to be at the latitudes of this path at these times and at low Kp values. A sharp cut-off in low-power losses at a mean Kp of 2.75 strongly implicates the trough in the propagation of these signals. The Doppler shifts observed at these times cannot be explained by a simple ray-tracing model. It is shown however, that a simple extension of this model to allow for the trough can reproduce the form of the observed diurnal variation.

Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

Decomposition of surface electromyographic signal using Hidden Markov Model

The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

Scene understanding for auto-calibration of surveillance cameras

In the last decade, several research results have presented formulations for the auto-calibration problem. Most of these have relied on the evaluation of vanishing points to extract the camera parameters. Normally vanishing points are evaluated using pedestrians or the Manhattan World assumption i.e. it is assumed that the scene is necessarily composed of orthogonal planar surfaces. In this work, we present a robust framework for auto-calibration, with improved results and generalisability for real-life situations. This framework is capable of handling problems such as occlusions and the presence of unexpected objects in the scene. In our tests, we compare our formulation with the state-of-the-art in auto-calibration using pedestrians and Manhattan World-based assumptions. This paper reports on the experiments conducted using publicly available datasets; the results have shown that our formulation represents an improvement over the state-of-the-art.

Sensory enhancement, a pilot perceptual study of subdermal magnetic implants

Subdermal magnetic implants originated as an art form in the world of body modification. To date an in depth scientific analysis of the benefits of this implant has yet to be established. This research explores the concept of sensory extension of the tactile sense utilising this form of implantation. This relatively simple procedure enables the tactile sense to respond to static and alternating magnetic fields. This is not to say that the underlying biology of the system has changed; i.e. the concept does not increase our tactile frequency response range or sensitivity to pressure, but now does invoke a perceptual response to a stimulus that is not innately available to humans. Within this research two social surveys have been conducted in order to ascertain one, the social acceptance of the general notion of human enhancement, and two the perceptual experiences of individuals with the magnetic implants themselves. In terms of acceptance to the notion of sensory improvement (via implantation) ~39% of the general population questioned responded positively with a further ~25% of the respondents answering with the indecisive response. Thus with careful dissemination a large proportion of individuals may adopt this technology much like this if it were to become available for consumers. Interestingly of the responses collected from the magnetic implants survey ~60% of the respondents actually underwent the implant for magnetic vision purposes. The main contribution of this research however comes from a series of psychophysical testing. In which 7 subjects with subdermal magnetic implants, were cross compared with 7 subjects that had similar magnets superficially attached to their dermis. The experimentation examined multiple psychometric thresholds of the candidates including intensity, frequency and temporal. Whilst relatively simple, the experimental setup for the perceptual experimentation conducted was novel in that custom hardware and protocols were created in order to determine the subjective thresholds of the individuals. Abstract iv The overall purpose of this research is to utilise this concept in high stress scenarios, such as driving or piloting; whereby alerts and warnings could be relayed to an operator without intruding upon their other (typically overloaded) exterior senses (i.e. the auditory and visual senses). Hence each of the thresholding experiments were designed with the intention of utilising the results in the design of signals for information transfer. The findings from the study show that the implanted group of subjects significantly outperformed the superficial group in the absolute intensity threshold experiment, i.e. the implanted group required significantly less force than the superficial group in order to perceive the stimulus. The results for the frequency difference threshold showed no significant difference in the two groups tested. Interestingly however at low frequencies, i.e. 20 and 50 Hz, the ability of the subjects tested to discriminate frequencies significantly increased with more complex waveforms i.e. square and sawtooth, when compared against the typically used sinewave. Furthermore a novel protocol for establishing the temporal gap detection threshold during a temporal numerosity study has been established in this thesis. This experiment measured the subjects’ capability to correctly determine the number of concatenated signals presented to them whilst the time between the signals, referred to as pulses, tended to zero. A significant finding was that when altering the length of, the frequency of, and the number of cycles of the pulses, the time between pulses for correct recognition altered. This finding will ultimately aid in the design of the tactile alerts for this method of information transfer. Preliminary development work for the use of this method of input to the body, in an automotive scenario, is also presented within this thesis in the form of a driving simulation. The overall goal of which is to present warning alerts to a driver, such as rear-to-end collision, or excessive speeds on roads, in order to prevent incidents and penalties from occurring. Discussion on the broader utility of this implant has been presented, reflecting on its potential use as a basis for vibrotactile, and sensory substitution, devices. This discussion furthers with postulations on its use as a human machine interface, as well as how a similar implant could be used within the ear as a hearing aid device.

Decadal predictability of the Atlantic meridional overturning circulation and climate in the IPSL-CM5A-LR model

This study explores the decadal potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) as represented in the IPSL-CM5A-LR model, along with the predictability of associated oceanic and atmospheric fields. Using a 1000-year control run, we analyze the prognostic potential predictability (PPP) of the AMOC through ensembles of simulations with perturbed initial conditions. Based on a measure of the ensemble spread, the modelled AMOC has an average predictive skill of 8 years, with some degree of dependence on the AMOC initial state. Diagnostic potential predictability of surface temperature and precipitation is also identified in the control run and compared to the PPP. Both approaches clearly bring out the same regions exhibiting the highest predictive skill. Generally, surface temperature has the highest skill up to 2 decades in the far North Atlantic ocean. There are also weak signals over a few oceanic areas in the tropics and subtropics. Predictability over land is restricted to the coastal areas bordering oceanic predictable regions. Potential predictability at interannual and longer timescales is largely absent for precipitation in spite of weak signals identified mainly in the Nordic Seas. Regions of weak signals show some dependence on AMOC initial state. All the identified regions are closely linked to decadal AMOC fluctuations suggesting that the potential predictability of climate arises from the mechanisms controlling these fluctuations. Evidence for dependence on AMOC initial state also suggests that studying skills from case studies may prove more useful to understand predictability mechanisms than computing average skill from numerous start dates.

Convergent evolution: floral guides, stingless bee nest entrances, and insectivorous pitchers

Several recent hypotheses, including sensory drive and sensory exploitation, suggest that receiver biases may drive selection of biological signals in the context of sexual selection. Here we suggest that a similar mechanism may have led to convergence of patterns in flowers, stingless bee nest entrances, and pitchers of insectivorous plants. A survey of these non-related visual stimuli shows that they share features such as stripes, dark centre, and peripheral dots. Next, we experimentally show that in stingless bees the close-up approach to a flower is guided by dark centre preference. Moreover, in the approach towards their nest entrance, they have a spontaneous preference for entrance patterns containing a dark centre and disrupted ornamentation. Together with existing empirical evidence on the honeybee's and other insects' orientation to flowers, this suggests that the signal receivers of the natural patterns we examined, mainly Hymenoptera, have spontaneous preferences for radiating stripes, dark centres, and peripheral dots. These receiver biases may have evolved in other behavioural contexts in the ancestors of Hymenoptera, but our findings suggest that they have triggered the convergent evolution of visual stimuli in floral guides, stingless bee nest entrances, and insectivorous pitchers.

Leafy, terminal flower1 and agamous are functionally conserved but do not regulate terminal flowering and floral determinacy in Impatiens balsamina

In Impatiens balsamina a lack of commitment of the meristem during floral development leads to the continuous requirement for a leaf-derived floral signal. In the absence of this signal the meristem reverts to leaf production. Current models for Arabidopsis state that LEAFY (LFY) is central to the integration of floral signals and regulates flowering partly via interactions with TERMINAL FLOWER1 (TFL1) and AGAMOUS (AG). Here we describe Impatiens homologues of LFY, TFL1 and AG (IbLFY, IbTFL1 and IbAG) that are highly conserved at a sequence level and demonstrate homologous functions when expressed ectopically in transgenic Arabidopsis. We relate the expression patterns of IbTFL1 and IbAG to the control of terminal flowering and floral determinacy in Impatiens. IbTFL1 is involved in controlling the phase of the axillary meristems and is expressed in axillary shoots and axillary meristems which produce inflorescences, but not in axillary flowers. It is not involved in maintaining the terminal meristem in either an inflorescence or indeterminate state. Terminal flowering in Impatiens appears therefore to be controlled by a pathway that uses a different integration system than that regulating the development of axillary flowers and branches. The pattern of ovule production in Impatiens requires the meristem to be maintained after the production of carpels. Consistent with this morphological feature IbAG appears to specify stamen and carpel identity, but is not sufficient to specify meristem determinacy in Impatiens.

Parallel Monte Carlo sampling scheme for sphere and hemisphere

The sampling of certain solid angle is a fundamental operation in realistic image synthesis, where the rendering equation describing the light propagation in closed domains is solved. Monte Carlo methods for solving the rendering equation use sampling of the solid angle subtended by unit hemisphere or unit sphere in order to perform the numerical integration of the rendering equation. In this work we consider the problem for generation of uniformly distributed random samples over hemisphere and sphere. Our aim is to construct and study the parallel sampling scheme for hemisphere and sphere. First we apply the symmetry property for partitioning of hemisphere and sphere. The domain of solid angle subtended by a hemisphere is divided into a number of equal sub-domains. Each sub-domain represents solid angle subtended by orthogonal spherical triangle with fixed vertices and computable parameters. Then we introduce two new algorithms for sampling of orthogonal spherical triangles. Both algorithms are based on a transformation of the unit square. Similarly to the Arvo's algorithm for sampling of arbitrary spherical triangle the suggested algorithms accommodate the stratified sampling. We derive the necessary transformations for the algorithms. The first sampling algorithm generates a sample by mapping of the unit square onto orthogonal spherical triangle. The second algorithm directly compute the unit radius vector of a sampling point inside to the orthogonal spherical triangle. The sampling of total hemisphere and sphere is performed in parallel for all sub-domains simultaneously by using the symmetry property of partitioning. The applicability of the corresponding parallel sampling scheme for Monte Carlo and Quasi-D/lonte Carlo solving of rendering equation is discussed.

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is computationally more efficient.

Planning rigid body motions using elastic curves

This paper tackles the problem of computing smooth, optimal trajectories on the Euclidean group of motions SE(3). The problem is formulated as an optimal control problem where the cost function to be minimized is equal to the integral of the classical curvature squared. This problem is analogous to the elastic problem from differential geometry and thus the resulting rigid body motions will trace elastic curves. An application of the Maximum Principle to this optimal control problem shifts the emphasis to the language of symplectic geometry and to the associated Hamiltonian formalism. This results in a system of first order differential equations that yield coordinate free necessary conditions for optimality for these curves. From these necessary conditions we identify an integrable case and these particular set of curves are solved analytically. These analytic solutions provide interpolating curves between an initial given position and orientation and a desired position and orientation that would be useful in motion planning for systems such as robotic manipulators and autonomous-oriented vehicles.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Bi-directional human machine interface via direct neural connection

This paper presents an application study into the use of a bi-directional link with the human nervous system by means of an implant, positioned through neurosurgery. Various applications are described including the interaction of neural signals with an articulated hand, a group of cooperative autonomous robots and to control the movement of a mobile platform. The microelectrode array implant itself is described in detail. Consideration is given to a wider range of possible robot mechanisms, which could interact with the human nervous system through the same technique.

The early transcriptomic response to interleukin 1β and interleukin 33 in rat neonatal cardiomyocytes

In the heart, inflammatory cytokines including interleukin (IL) 1β are implicated in regulating adaptive and maladaptive changes, whereas IL33 negatively regulates cardiomyocyte hypertrophy and promotes cardioprotection. These agonists signal through a common co-receptor but, in cardiomyocytes, IL1β more potently activates mitogen-activated protein kinases and NFκB, pathways that regulate gene expression. We compared the effects of external application of IL1β and IL33 on the cardiomyocyte transcriptome. Neonatal rat cardiomyocytes were exposed to IL1β or IL33 (0.5, 1 or 2h). Transcriptomic profiles were determined using Affymetrix rat genome 230 2.0 microarrays and data were validated by quantitative PCR. IL1β induced significant changes in more RNAs than IL33 and, generally, to a greater degree. It also had a significantly greater effect in downregulating mRNAs and in regulating mRNAs associated with selected pathways. IL33 had a greater effect on a small, select group of specific transcripts. Thus, differences in intensity of intracellular signals can deliver qualitatively different responses. Quantitatively different responses in production of receptor agonists and transcription factors may contribute to qualitative differences at later times resulting in different phenotypic cellular responses.