Tracking control of a class of Hamiltonian mechanical systems with disturbances

This paper presents a trajectory-tracking control strategy for a class of mechanical systems in Hamiltonian form. The class is characterised by a simplectic interconnection arising from the use of generalised coordinates and full actuation. The tracking error dynamic is modelled as a port-Hamiltonian Systems (PHS). The control action is designed to take the error dynamics into a desired closed-loop PHS characterised by a constant mass matrix and a potential energy with a minimum at the origin. A transformation of the momentum and a feedback control is exploited to obtain a constant generalised mass matrix in closed loop. The stability of the close-loop system is shown using the close-loop Hamiltonian as a Lyapunov function. The paper also considers the addition of integral action to design a robust controller that ensures tracking in spite of disturbances. As a case study, the proposed control design methodology is applied to a fully actuated robotic manipulator.

A model for assessing information systems success and its application to e-logistics tracking systems

The DeLone and McLean (D&M) model (2003) has been broadly used and generally recognised as a useful model for gauging the success of IS implementations. However, it is not without limitations. In this study, we evaluate a model that extends the D&M model and attempts to address some of it slimitations by providing a more complete measurement model of systems success. To that end, we augment the D&M (2003) model and include three variables: business value, institutional trust, and future readiness. We propose that the addition of these variables allows systems success to be assessed at both the systems level and the business level. Consequently, we develop a measurement model rather than a structural or predictive model of systems success.

Tracking locomotive position to evaluate sugarcane railway schedules and predict arrival time

This research utilised software developed for managing the Australian sugar industry's cane rail transport operations and GPS data used to track locomotives to ensure safe operation of the railway system to improve transport operations. As a result, time usage in the sugarcane railway can now be summarised and locomotive arrival time to sidings and mills can be predicted. This information will help the development of more efficient run schedules and enable mill staff and harvesters to better plan their shifts ahead, enabling cost reductions through better use of available time.

Parallel attentive visual tracking

The research reported here addresses the problem of detecting and tracking independently moving objects from a moving observer in real-time, using corners as object tokens. Corners are detected using the Harris corner detector, and local image-plane constraints are employed to solve the correspondence problem. The approach relaxes the restrictive static-world assumption conventionally made, and is therefore capable of tracking independently moving and deformable objects. Tracking is performed without the use of any 3-dimensional motion model. The technique is novel in that, unlike traditional feature-tracking algorithms where feature detection and tracking is carried out over the entire image-plane, here it is restricted to those areas most likely to contain-meaningful image structure. Two distinct types of instantiation regions are identified, these being the “focus-of-expansion” region and “border” regions of the image-plane. The size and location of these regions are defined from a combination of odometry information and a limited knowledge of the operating scenario. The algorithms developed have been tested on real image sequences taken from typical driving scenarios. Implementation of the algorithm using T800 Transputers has shown that near-linear speedups are achievable, and that real-time operation is possible (half-video rate has been achieved using 30 processing elements).

Attentive visual tracking

The research reported here addresses the problem of detecting and tracking independently moving objects from a moving observer in real time, using corners as object tokens. Local image-plane constraints are employed to solve the correspondence problem removing the need for a 3D motion model. The approach relaxes the restrictive static-world assumption conventionally made, and is therefore capable of tracking independently moving and deformable objects. The technique is novel in that feature detection and tracking is restricted to areas likely to contain meaningful image structure. Feature instantiation regions are defined from a combination of odometry informatin and a limited knowledge of the operating scenario. The algorithms developed have been tested on real image sequences taken from typical driving scenarios. Preliminary experiments on a parallel (transputer) architecture indication that real-time operation is achievable.

Mechanisms underlying the effect of acupuncture on cognitive improvement: A systematic review of animal studies

Acupuncture has been reported to be beneficial in treating cognitive impairment in various pathological conditions. This review describes the effort to understand the signaling pathways that underlie the acupunctural therapeutic effect on cognitive function. We searched the literature in 12 electronic databases from their inception to November 2013, with full text available and language limited to English. Twenty-three studies were identified under the selection criteria. All recruited animal studies demonstrate a significant positive effect of acupuncture on cognitive impairment. Findings suggest acupuncture may improve cognitive function through modulation of signaling pathways involved in neuronal survival and function, specifically, through promoting cholinergic neural transmission, facilitating dopaminergic synaptic transmission, enhancing neurotrophin signaling, suppressing oxidative stress, attenuating apoptosis, regulating glycometabolic enzymes and reducing microglial activation. However, the quality of reviewed studies has room for improvement. Further high-quality animal studies with randomization, blinding and estimation of sample size are needed to strengthen the recognition of group differences.

Importance of animal models in schizophrenia research

Objective This review aims to summarize the importance of animal models for research on psychiatric illnesses, particularly schizophrenia. Method and Results Several aspects of animal models are addressed, including animal experimentation ethics and theoretical considerations of different aspects of validity of animal models. A more specific discussion is included on two of the most widely used behavioural models, psychotropic drug-induced locomotor hyperactivity and prepulse inhibition, followed by comments on the difficulty of modelling negative symptoms of schizophrenia. Furthermore, we emphasize the impact of new developments in molecular biology and the generation of genetically modified mice, which have generated the concept of behavioural phenotyping. Conclusions Complex psychiatric illnesses, such as schizophrenia, cannot be exactly reproduced in species such as rats and mice. Nevertheless, by providing new information on the role of neurotransmitter systems and genes in behavioural function, animal 'models' can be an important tool in unravelling mechanisms involved in the symptoms and development of such illnesses, alongside approaches such as post-mortem studies, cognitive and psychophysiological studies, imaging and epidemiology.

Neurodevelopmental animal models of schizophrenia: Effects on prepulse inhibition

Epidemiological studies have shown increased incidence of schizophrenia in patients subjected to different forms of pre- or perinatal stress. However, as the onset of schizophrenic illness does not usually occur until adolescence or early adulthood, it is not yet fully understood how disruption of early brain development may ultimately lead to malfunction years later. In order to elucidate a possible role for neurodevelopmental factors in the pathogenesis of schizophrenia and to highlight potential new treatments, animal models are needed. Prepulse inhibition (PPI) is a model of sensorimotor gating mechanisms in the brain. It is disrupted in schizophrenia patients and the disruption can be reversed with atypical antipsychotics. It has been widely used in animal studies to explore central mechanisms possibly involved in schizophrenia. There has been a recent surge of behavioural and neurochemical animal studies on neurodevelopmental models, particularly on the effects of postweaning isolation, maternal separation and neonatal lesions of the hippocampus. In these models, long lasting alterations in behaviour and/or molecular changes in specific brain regions are observed, comparable to those seen in schizophrenia. The aim of this article is to critically review the available literature on such neurodevelopmental animal models with special focus on the effects on PPI and brain regions that are putatively involved in regulation of PPI.

Comparison of human and animal Chlamydia pneumoniae responses to interferon gamma and penicillin treatment

This thesis has made a significant contribution to future chlamydial research by uncovering the chlamydial pathogenic mechanisms which will potentially help in the development of targeted vaccine against the pathogen. This thesis has made important new contributions to our understanding of Chlamydia pneumoniae specific adaptations to stress responses and has provided new perspectives on the survival of this successful pathogen. This thesis has used two well established microbial stressors and has identified major differences in stress responses between human and animal Chlamydia pneumoniae isolates.

Development of a new ultrasound-based system for tracking motion of the human lumbar spine: Reliability, stability and repeatability during forward bending movement trials

The aim of this study was to develop a new method for quantifying intersegmental motion of the spine in an instrumented motion segment L4–L5 model using ultrasound image post-processing combined with an electromagnetic device. A prospective test–retest design was employed, combined with an evaluation of stability and within- and between-day intra-tester reliability during forward bending by 15 healthy male patients. The accuracy of the measurement system using the model was calculated to be ± 0.9° (standard deviation = 0.43) over a 40° range and ± 0.4 cm (standard deviation = 0.28) over 1.5 cm. The mean composite range of forward bending was 15.5 ± 2.04° during a single trial (standard error of the mean = 0.54, coefficient of variation = 4.18). Reliability (intra-class correlation coefficient = 2.1) was found to be excellent for both within-day measures (0.995–0.999) and between-day measures (0.996–0.999). Further work is necessary to explore the use of this approach in the evaluation of biomechanics, clinical assessments and interventions.

Destination brand performance measurement over time: Tracking consumer perceptions of a competitive set of destinations over a 10 year period

There has been a paucity of research published in relation to the temporal aspect of destination image change over time. Given increasing investments in destination branding, research is needed to enhance understanding of how to monitor destination brand performance, of which destination image is the core construct, over time. This article reports the results of four studies tracking brand performance of a competitive set of five destinations, between 2003 and 2012. Results indicate minimal changes in perceptions held of the five destinations of interest over the 10 years, supporting the assertion of Gartner (1986) and Gartner and Hunt (1987) that destination image change will only occur slowly over time. While undertaken in Australia, the research approach provides DMOs in other parts of the world with a practical tool for evaluating brand performance over time; in terms of measures of effectiveness of past marketing communications, and indicators of future performance.

Tracking the arcuate fasciculus in patients with aphasia

The arcuate fasciculus (AF), a white matter tract linking temporal and inferior frontal language cortices, can be disrupted in stroke patients suffering from aphasia. Using diffusion tensor imaging (DTI) tractography it is possible to track AF connections to neural regions associated with either phonological or semantic linguistic processing. The aim of the current study is to investigate the relationship between integrity of white matter microstructure and specific linguistic deficits.

Tracking Alzheimer's disease

Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span.We describe three novel brain mapping techniques, cortical thickness mapping, tensor-based morphometry (TBM), and hippocampal surface modeling, which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI).We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer's disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling, plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

A robust optimization approach for index tracking problem

Index tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this paper, quadratic as well as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input data using a tractable robust framework that controls the level of conservatism while maintaining linearity. The linearity of the proposed robust optimization models allows a simple implementation of an ordinary optimization software package to find the optimal robust solution. The proposed model of this paper employs Morgan Stanley Capital International Index as the target index and the results are reported for six national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of the proposed models is evaluated using several financial criteria e.g. information ratio, market ratio, Sharpe ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of tracking error while raising values of portfolio performance measures.