Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

How does angular resolution affect diffusion imaging measures?

A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4T. From gradient image subsets of varying size (6 ≤ N ≤ 94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66, and 62 gradients for MD, FA, and RA, respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.

Innovation in energy efficiency education for engineers

Energy efficiency as a concept has gained significant attention over the last few decades, as governments and industries around the world have grappled with issues such as rapid population growth and expanding needs for energy, the cost of supplying infrastructure for growing spikes in peak demand, the finite nature of fossil based energy reserves, and managing transition timeframes for expanding renewable energy supplies. Over the last decade in particular, there has been significant growth in understanding the complexity and interconnectedness of these issues, and the centrality of energy efficiency to the engineering profession. Furthermore, there has been a realisation amongst various government departments and education providers that associated knowledge and skill sets to achieve energy efficiency goals are not being sufficiently developed in vocational or higher education. Within this context, this poster discusses the emergence of a national energy efficiency education agenda in Australia, to support embedding such knowledge throughout the engineering curriculum, and throughout career pathways. In particular, the posterprovides insights into the national priorities for capacity building in Australia, and how this is influencing the engineering education community, from undergraduate education through to postgraduate studies and professional development. The poster is intended to assist in raising awareness about the central role of energy efficiency within engineering, significant initiatives by major government, professional, and training organisations, and the increasing availability of high quality energy efficiency engineering education resources. The authors acknowledge the support for and contributions to this poster by the federal Department of Resources, Energy and Tourism, through members of the national Energy Efficiency Advisory Group for engineering education.

Consultation: Energy efficiency and engineering education

This report provides the Commonwealth Department of Resources, Energy and Tourism (RET) with a summary of consultation undertaken with representatives from industry and academia around Australia regarding mainstreaming energy efficiency within engineering education. Specifically, the report documents the purpose of the consultation process, key messages and emerging themes, industry-perceived gaps in energy efficiency related knowledge and skills, and academic considerations regarding graduate attributes and learning pathways to close these gaps. This information complements previous reports by presenting the current thoughts and ideas of more than 100 engineering academic and practising professionals who are actively involved in building capacity through the education system or implementing energy efficiency improvements in companies/the workplace. Furthermore, the report describes the emergence of a potential ‘community of practice’ in energy efficiency capacity building that arose during the project.

State of Education for Energy Efficiency in Australian Engineering Education - Summary of Questionnaire Results

In 2007 the National Framework for Energy Efficiency provided funding for the first survey of energy efficiency education across all Australian universities teaching engineering education. The survey asked the question, ‘What is the state of education for energy efficiency in Australian engineering education?’. There was an excellent response to the survey, with 48 course responses from lecturers across 27 universities from every state and territory in Australia, and 260 student responses from 18 courses across 8 universities from all 6 states. It is concluded from the survey findings that the state of education for energy efficiency in Australian engineering education is currently highly variable and ad hoc across universities and engineering disciplines.

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.

Impact of electric energy storage scheduling on reliability of distribution system

The development of Electric Energy Storage (EES) integrated with Renewable Energy Resources (RER) has increased use of optimum scheduling strategy in distribution systems. Optimum scheduling of EES can reduce cost of purchased energy by retailers while improve the reliability of customers in distribution system. This paper proposes an optimum scheduling strategy for EES and the evaluation of its impact on reliability of distribution system. Case study shows the impact of the proposed strategy on reliability indices of a distribution system.

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.

Energy productivity and decarbonization of the global economy: Factor five resource productivity

In the 21st Century much of the world will experience untold wealth and prosperity that could not even be conceived only some three centuries before. However as with most, if not all, of the human civilisations, increases in prosperity have accumulated significant environmental impacts that threaten to result in environmentally induced economic decline. A key part of the world’s response to this challenge is to rapidly decarbonise economies around the world, with options to achieve 60-80 per cent improvements (i.e. in the order of Factor 5) in energy and water productivity now available and proven in every sector. Drawing upon the 2009 publication “Factor 5”, in this paper we discuss how to realise such large-scale improvements, involving complexity beyond technical and process innovation. We begin by considering the concept of greenhouse gas stabilisation trajectories that include reducing current greenhouse gas emissions to achieve a ‘peaking’ of global emissions, and subsequent ‘tailing’ of emissions to the desired endpoint in ‘decarbonising’ the economy. Temporal priorities given to peaking and tailing have significant implications for the mix of decarbonising solutions and the need for government and market assistance in causing them to be implemented, requiring careful consideration upfront. Within this context we refer to a number of examples of Factor 5 style opportunities for energy productivity and decarbonisation, and then discuss the need for critical economic contributions to take such success from examples to central mechanisms in decarbonizing the global economy.

Environmental efficiency of energy, materials, and emissions

This study estimates the environmental efficiency of international listed firms in 10 worldwide sectors from 2007 to 2013 by applying an order-m method, a non-parametric approach based on free disposal hull with subsampling bootstrapping. Using a conventional output of gross profit and two conventional inputs of labor and capital, this study examines the order-m environmental efficiency accounting for the presence of each of 10 undesirable inputs/outputs and measures the shadow prices of each undesirable input and output. The results show that there is greater potential for the reduction of undesirable inputs rather than bad outputs. On average, total energy, electricity, or water usage has the potential to be reduced by 50%. The median shadow prices of undesirable inputs, however, are much higher than the surveyed representative market prices. Approximately 10% of the firms in the sample appear to be potential sellers or production reducers in terms of undesirable inputs/outputs, which implies that the price of each item at the current level has little impact on most of the firms. Moreover, this study shows that the environmental, social, and governance activities of a firm do not considerably affect environmental efficiency.

Birdcall retrieval from environmental acoustic recordings using image processing

Acoustic recordings of the environment provide an effective means to monitor bird species diversity. To facilitate exploration of acoustic recordings, we describe a content-based birdcall retrieval algorithm. A query birdcall is a region of spectrogram bounded by frequency and time. Retrieval depends on a similarity measure derived from the orientation and distribution of spectral ridges. The spectral ridge detection method caters for a broad range of birdcall structures. In this paper, we extend previous work by incorporating a spectrogram scaling step in order to improve the detection of spectral ridges. Compared to an existing approach based on MFCC features, our feature representation achieves better retrieval performance for multiple bird species in noisy recordings.

Patenting free energy: The BlackLight litigation and the hydrogen economy

Legal Context In the wake of the Copenhagen Accord 2009 and the Cancun Agreements 2010, a number of patent offices have introduced fast-track mechanisms to encourage patent applications in relation to clean technologies - such as those pertaining to hydrogen. However, patent offices will be under increasing pressure to ensure that the granted patents satisfy the requisite patent thresholds, as well as to identify and reject cases of fraud, hoaxes, scams, and swindles. Key Points This article examines the BlackLight litigation in the United States, the United Kingdom, and the European Patent Office, and considers how patent offices and courts deal with patent applications in respect of clean energy and perpetual motion machines. Practical Significance The capacity of patent offices to grant sound and reliable patents is critical to the credibility of the patent system, particularly in the context of the current focus upon promoting clean technologies.

Energy based time equivalent approach to determine the fire resistance ratings of light gauge steel frame walls exposed to realistic design fire curves

Structural fire safety has become one of the key considerations in the design and maintenance of the built infrastructure. Conventionally the fire resistance rating of load bearing Light gauge Steel Frame (LSF) walls is determined based on the standard time-temperature curve given in ISO 834. Recent research has shown that the true fire resistance of building elements exposed to building fires can be less than their fire resistance ratings determined based on standard fire tests. It is questionable whether the standard time-temperature curve truly represents the fuel loads in modern buildings. Therefore an equivalent fire severity approach has been used in the past to obtain fire resistance rating. This is based on the performance of a structural member exposed to a realistic design fire curve in comparison to that of standard fire time-temperature curve. This paper presents the details of research undertaken to develop an energy based time equivalent approach to obtain the fire resistance ratings of LSF walls exposed to realistic design fire curves with respect to standard fire exposure. This approach relates to the amount of energy transferred to the member. The proposed method was used to predict the fire resistance ratings of single and double layer plasterboard lined and externally insulated LSF walls. The predicted fire ratings were compared with the results from finite element analyses and fire design rules for three different wall configurations exposed to both rapid and prolonged fires. The comparison shows that the proposed energy method can be used to obtain the fire resistance ratings of LSF walls in the case of prolonged fires.

Scalable Bayesian Computation for intractable likelihoods in image analysis

The inverse temperature hyperparameter of the hidden Potts model governs the strength of spatial cohesion and therefore has a substantial influence over the resulting model fit. The difficulty arises from the dependence of an intractable normalising constant on the value of the inverse temperature, thus there is no closed form solution for sampling from the distribution directly. We review three computational approaches for addressing this issue, namely pseudolikelihood, path sampling, and the approximate exchange algorithm. We compare the accuracy and scalability of these methods using a simulation study.