Functional MRI BOLD response to Tower of London performance of first-episode schizophrenia patients using cortical pattern matching

Due to its three-dimensional folding pattern, the human neocortex; poses a challenge for accurate co-registration of grouped functional; brain imaging data. The present study addressed this problem by; employing three-dimensional continuum-mechanical image-warping; techniques to derive average anatomical representations for coregistration; of functional magnetic resonance brain imaging data; obtained from 10 male first-episode schizophrenia patients and 10 age-matched; male healthy volunteers while they performed a version of the; Tower of London task. This novel technique produced an equivalent; representation of blood oxygenation level dependent (BOLD) response; across hemispheres, cortical regions, and groups, respectively, when; compared to intensity average co-registration, using a deformable; Brodmann area atlas as anatomical reference. Somewhat closer; association of Brodmann area boundaries with primary visual and; auditory areas was evident using the gyral pattern average model.; Statistically-thresholded BOLD cluster data confirmed predominantly; bilateral prefrontal and parietal, right frontal and dorsolateral; prefrontal, and left occipital activation in healthy subjects, while; patients’ hemispheric dominance pattern was diminished or reversed,; particularly decreasing cortical BOLD response with increasing task; difficulty in the right superior temporal gyrus. Reduced regional gray; matter thickness correlated with reduced left-hemispheric prefrontal/; frontal and bilateral parietal BOLD activation in patients. This is the; first study demonstrating that reduction of regional gray matter in; first-episode schizophrenia patients is associated with impaired brain; function when performing the Tower of London task, and supports; previous findings of impaired executive attention and working memory; in schizophrenia.

Reduction of diesel engine exhaust emissions using non-thermal plasma technology

Non-thermal plasma (NTP) is a promising candidate for controlling engine exhaust emissions. Plasma is known as the fourth state of matter, where both electrons and positive ions co-exist. Both gaseous and particle emissions of diesel exhaust undergo chemical changes when they are exposed to plasma. In this project diesel particulate matter (DPM) mitigation from the actual diesel exhaust by using NTP technology has been studied. The effect of plasma, not only on PM mass but also on PM size distribution, physico-chemical structure of PM and PM removal mechanisms, has been investigated. It was found that NTP technology can significantly reduce both PM mass and number. However, under some circumstances particles can be formed by nucleation. Energy required to create the plasma with the current technology is higher than the benchmark set by the commonly used by the automotive industry. Further research will enable the mechanism of particle creation and energy consumption to be optimised.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

Tensor reduction for user profiling in personalized recommender systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhoodbased collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.

Effects of microfinance on poverty reduction in Vietnam : a pseudo-panel data analysis

The development of microfinance in Vietnam since 1990s has coincided with a remarkable progress in poverty reduction. Numerous descriptive studies have illustrated that microfinance is an effective tool to eradicate poverty in Vietnam but evidence from quantitative studies is mixed. This study contributes to the literature by providing new evidence on the impact of microfinance to poverty reduction in Vietnam using the repeated cross - sectional data from the Vietnam Living Standard s Survey (VLSS) during period 1992 - 2010. Our results show that micro - loans contribute significantly to household consumption.

Comprehensive contribution of filament thickness and crosslinker failure to the rheological property of F-actin cytoskeleton

Rheological property of F-actin cytoskeleton is significant to the restructuring of cytoskeleton under a variety of cell activities. This study numerically validates the rheological property of F-actin cytoskeleton is not only a result of kinetic energy dissipation of F-actin, but also greatly depends on the configuration remodeling of networks structure. Both filament geometry and crosslinker properties can affect the remodeling of F-actin cytoskeleton. The crosslinker unbinding is found to dissipate energy and induce prominent stress relaxation in the F-actin adjacent to cross-linkages. Coupled with F-actin elasticity, the energy dissipation and stress relaxation are more significant in bundled F-actin networks than in single F-actin networks.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

Peripapillary choroidal thickness in childhood

Changes in the thickness of the invivo peripapillary choroid have been documented in a range of ocular conditions in adults; however, choroidal thickness in the peripapillary region of children has not been examined in detail. This study therefore aimed to investigate the thickness of the peripapillary choroid and the overlying retinal nerve fibre layer (RNFL) in a population of normal children with a range of refractive errors. Ninety-three children (37 myopes and 56 non-myopes) aged between 11 and 16 years, had measurements of peripapillary choroidal and RNFL thickness derived from enhanced depth imaging optical coherence tomography images (EDI-OCT, Heidelberg Spectralis). The average thickness was determined in a series of five 0.25 mm width concentric annuli (each divided into 8 equal sized 45° sectors) centred on the optic nerve head boundary, accounting for individual ocular magnification factors and the disc-fovea angle. Significant variations in peripapillary choroidal thickness were found to occur with both annulus location (p<0.001) and sector position (p<0.001) in this population of children. The innermost annulus (closest to the edge of the optic disc) exhibited the thinnest choroid (mean 77 ± 16 μm) and the outermost annulus, the thickest choroid (191 ± 52 μm). The choroid was thinnest inferior to the optic nerve head (139 ± 38 μm) and was thickest in the superior temporal sector (157 ± 40 μm). Significant differences in the distribution of choroidal thickness were also associated with myopia, with myopic children having significantly thinner choroids in the inner and outer annuli of the nasal and temporal sectors respectively (p<0.001). RNFL thickness also varied significantly with annulus location and sector (p<0.001), and showed differences in thickness distribution associated with refractive error. This study establishes the normal variations in the thickness of the peripapillary choroid with radial distance and azimuthal angle from the optic nerve head boundary. A significant thinning of the peripapillary choroid associated with myopia in childhood was also observed in both nasal and temporal regions. The changes in peripapillary RNFL and choroidal thickness associated with refractive error are consistent with a redistribution of these tissues occurring with myopic axial elongation in childhood.

Performance evaluation of non-thermal plasma on particulate matter, ozone and CO2 correlation for diesel exhaust emission reduction

This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.

The relationship between stress, HPA axis functioning and brain structure in first episode psychosis over the first 12 weeks of treatment

Stress and abnormal hypothalamic-pituitary-adrenal axis functioning have been implicated in the early phase of psychosis and may partly explain reported changes in brain structure. This study used magnetic resonance imaging to investigate whether biological measures of stress were related to brain structure at baseline and to structural changes over the first 12 weeks of treatment in first episode patients (n=22) compared with matched healthy controls (n=22). At baseline, no significant group differences in biological measures of stress, cortical thickness or hippocampal volume were observed, but a significantly stronger relationship between baseline levels of cortisol and smaller white matter volumes of the cuneus and anterior cingulate was found in patients compared with controls. Over the first 12 weeks of treatment, patients showed a significant reduction in thickness of the posterior cingulate compared with controls. Patients also showed a significant positive relationship between baseline cortisol and increases in hippocampal volume over time, suggestive of brain swelling in association with psychotic exacerbation, while no such relationship was observed in controls. The current findings provide some support for the involvement of stress mechanisms in the pathophysiology of early psychosis, but the changes are subtle and warrant further investigation.

A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

The contribution of genes to cortical thickness and volume

We analyzed brain MRI data from 372 young adult twins toidentify cortical regions in which gray matter thickness and volume are influenced by genetics. This was achieved using an A/C/E structural equation model that divides the variance of these traits, at each point on the cortex, into additive genetic (A), shared (C), and unique environmental (E) components. A strong genetic influencewas found in frontal and parietal regions. Inaddition, we correlated cortical thickness with full-scale intelligence quotient for comparison with the A/C/E maps, and several regions where cortical structure was correlated with intelligence quotient are under genetic control. These cortical measures may be useful phenotypes to narrow the searchfor quantitative trait lociinfluencing brain structure.

Electrochemical restructuring of copper surfaces using organic additives and its effect on the electrocatalytic reduction of nitrate ions

This work describes the fabrication of nanostructured copper electrodes using a simple potential cycling protocol that involves oxidation and reduction of the surface in an alkaline solution. It was found that the inclusion of additives, such as benzyl alcohol and phenylacetic acid, has a profound effect on the surface oxidation process and the subsequent reduction of these oxides. This results in not only a morphology change, but also affects the electrocatalytic performance of the electrode for the reduction of nitrate ions. In all cases, the electrocatalytic performance of the restructured electrodes was significantly enhanced compared with the unmodified electrode. The most promising material was formed when phenylacetic acid was used as the additive. In addition, the reduction of residual oxides on the surface after the modification procedure to expose freshly active reaction sites on the surface before nitrate reduction was found to be a significant factor in dictating the overall electrocatalytic activity. It is envisaged that this approach offers an interesting way to fabricate other nanostructured electrode surfaces.