White matter integrity measured by fractional anisotropy correlates poorly with actual individual fiber anisotropy

Fractional anisotropy (FA), a very widely used measure of fiber integrity based on diffusion tensor imaging (DTI), is a problematic concept as it is influenced by several quantities including the number of dominant fiber directions within each voxel, each fiber's anisotropy, and partial volume effects from neighboring gray matter. High-angular resolution diffusion imaging (HARDI) can resolve more complex diffusion geometries than standard DTI, including fibers crossing or mixing. The tensor distribution function (TDF) can be used to reconstruct multiple underlying fibers per voxel, representing the diffusion profile as a probabilistic mixture of tensors. Here we found that DTIderived mean diffusivity (MD) correlates well with actual individual fiber MD, but DTI-derived FA correlates poorly with actual individual fiber anisotropy, and may be suboptimal when used to detect disease processes that affect myelination. Analysis of the TDFs revealed that almost 40% of voxels in the white matter had more than one dominant fiber present. To more accurately assess fiber integrity in these cases, we here propose the differential diffusivity (DD), which measures the average anisotropy based on all dominant directions in each voxel.

Best individual template selection from deformation tensor minimization

We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

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.

Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Financially optimized scheduling of electric energy storage in presence of renewable energy resources

The increasing integration of Renewable Energy Resources (RER) and the role of Electric Energy Storage (EES) in distribution systems has created interest in using energy management strategies. EES has become a suitable resource to manage energy consumption and generation in smart grid. Optimize scheduling of EES can also maximize retailer’s profit by introducing energy time-shift opportunities. This paper proposes a new strategy for scheduling EES in order to reduce the impact of electricity market price and load uncertainty on retailers’ profit. The proposed strategy optimizes the cost of purchasing energy with the objective of minimizing surplus energy cost in hedging contract. A case study is provided to demonstrate the impact of the proposed strategy on retailers’ financial benefit.

Sustainable construction trends in journal papers

Sustainable construction is gaining worldwide attention and has inspired research to identify and solve the problems involved in its implementation over a project lifecycle. While an impressive number of papers have been published on the topic to date, little has been done to review these papers to identify current research status or provide guidance for future research. This paper reviews existing sustainability papers in 12 internationally renowned construction journals. Based on a three-stage literature review, sustainability papers published in these journals from 2000 to 2012 are analyzed in terms of the annual number of papers published and the research interests involved. The number of sustainability-related papers in construction increases from 30 papers in 2000 to 127 papers in 2012, which shows an increasing trend in sustainability topics. A content analysis identifies seven major research interest in sustainability, including: (1) sustainable project management; (2) sustainability assessment/evaluation; (3) sustainable technology/innovation implementation; (4) sustainable building/infrastructure performance; (5) government policy on sustainability; (6) enterprise sustainability, and; (7) sustainability education. The results of this study provide a reference for scholars and academics to understand the current status of sustainability research in major construction journals.

Measuring sustainability performance within the Australian energy industry

Sustainability has become crucial for the energy industry as projects in this industry are extensively large and complex and have significant impacts on the environment, community and economy. It demands the energy industry to proactively incorporate sustainability ideas and commit to sustainable project development. This study aims to investigate how the Australian energy industry responds to sustainability requirements and in particular what indicators used to measure sustainability performance. To achieve this, content analysis of sustainability reports, vision statements and policy statements of Australian energy companies listed in the 2013 PLATTS Top 250 Global Energy Company Rankings and government reports relating to sustainability has been conducted. The findings show that the energy companies extensively discuss sustainability aspects within three dimensions, i.e. community, environment, and economy. Their primary goals in sustainability are supplying cleaner energy for future, and doing business in a way that improves outcomes for shareholders, employees, business partners and the communities. In particular, energy companies have valued the employees of the business as a one of the key area that needs to be considered. Furthermore, the energy industry has become increasingly aware of the importance of measuring sustainability performance to achieve sustainability goals. A number of sustainability indicators have been developed on the basis of the key themes beyond economic measures. It is envisaged that findings from this research will help stakeholders in the energy industry to adopt different indicators to evaluate and ultimately achieve sustainability performance.

Defining green road infrastructure projects—A critical review

Green infrastructure is considered as a strategic approach to address the ecological and social impacts of urban sprawl. The main elements of green infrastructure have been well established and include a series of multifunctional ecological systems, such as green urban space, green road infrastructure and the links between these systems. However, it should be noted that the elements of green road infrastructure have only been briefly mentioned in isolated life cycle stages, e.g. design, procurement, construction, maintenance and operation. The definition of green road infrastructure and the elements in green road infrastructure projects remain largely unknown. To explore the elements in green road infrastructure, a critical review was adopted. As the development of green road infrastructure projects is guided by rating systems, a comparison of three major green roads rating systems, including GreenroadsTM, EnvisionTM and Infrastructure Sustainability Rating Tool—IS, was conducted. The comparison reveals that green roads can be defined as road projects that have superior performance in economic, social and environmental sustainability. The sustainability features in green roads mainly include environmental sustainability, social sustainability, economic sustainability, quality, pavement technology and innovation. The results will contribute to an increased understanding of green roads and will be useful to improve the performance of road projects on these sustainability features.

Are green project management practices applicable to traditional projects?

As the social environment begins to create more awareness in the area of conserving the natural environment, a new generation of building has emerged. A trend of constructing buildings that minimise impacts on the environment has been established in the construction industry. Therefore, suitable project management practices have been adopted to efficiently manage the construction of these green buildings. This study aims at investigating practices of project management in traditional and accredited green construction projects, with the purpose of discovering if Green Project Management (GPM) practices can be applied to traditional projects to achieve more successful outcomes. The process of GPM contains what applied to traditional projects, could possibly result in benefits in terms of budget control and constructability. Currently the construction industry has been known to suffer difficulties within these areas; therefore GPM practices could possibly hold a solution to these common problems.

Engineering education and sustainable development: Rapid curriculum renewal

The issue of engineering education and how it can systemically embed sustainable development knowledge and skills is now a major consideration for engineering educators globally. In this plenary presentation Ms Desha will begin by highlighting the rapidly changing market and regulatory environment and the time lag dilemma facing higher education with regard to delivering professionals who can address societal needs. She will then briefly present a series of elements of curriculum renewal to support engineering educators who are grappling with how programs of study can be rapidly renewed to address such emerging 21st Century challenges. The presentation will conclude with a discussion of the need for astrategic approach by higher education institutions, to ensure that the latest research and opportunities are communicated, while being sufficiently pragmatic and realistic with regard to the scale of the challenges, and existing inertia within the higher education system.

The influence of small amounts of N2 in SF6 on prebreakdown discharges

Pre-breakdown discharge activity in SF6 and SF6 +2% N2 at 1 bar absolute has been investigated to assess the feasibility of adding small amounts of N2 to SF6 to improve the luminosity of the pre-breakdown discharges. It has been shown that small amounts of N2 does not significantly alter the breakdown strength of the mixture but will have a profound influence on the pre-breakdown discharge activity under 50 Hz voltages and lightning impulse voltages. This influence is attributed to the following three mechanisms: 1. The increased availability of free electrons due to the lower ionisation potential of the N2 compared to SF6 2. The removal of high energy electrons from the discharge by electron scattering due to negative ion resonance in N2, thus effectively increasing the attachment of SF6. 3. The creation of longer lived SF6- ions by the attachment of the scattered low energy electrons from N2 thus effectively enhancing the negative ion space charge.

VFT performance of a 180/110 mm co-axial gap in SF6 up to 4 bar absolute

Disconnector switch operation in GIS generates VFT voltages in the system. It is important, for insulation co-ordination purposes, to obtain accurate VFT V-t data for typical gap geometries found in GIS. This paper presents experimentally obtained VFT V-t data for a 180/1 lOmm co-axial gap. The VFT has a time to first peak of 35 ns and a oscillation frequency of 13,6 MHz. Due to the location of the voltage divider in a compartment adjacent to the gap, a correction factor of 1.1 is used to relate the measured breakdown voltage to that in the gap. Positive polarity VFT V-t data is presented for 1, 2, 3 and 4 bar absolute and negative polarity VFT data for 3 and 4 bar absolute. Two methods of generating the VFT's are used. The first is to power up the test transformer at power frequency. The second is to generate a switching impulse by discharging a capacitor into the primary of the test transformer.

Novel window coupler for the detection of partial discharge activity in GIS

This work investigates the feasibly in using a low noise “C” Band block down-converter as a Ultra High Frequency window coupler for the detection of partial discharge activity from free conducting practices and a protrusion on the high voltage conductor in Gas Insulated Switchgear. The investigated window coupler has a better sensitivity than the internal Ultra High Frequency couplers fitted to the system. The investigated window couplers however are sensitive to changes in the frequency content of the discharge signals and appear to be less sensitive to negative discharges signals produced by a protrusion than the positive discharge signals.