Serum cholesterol and variant in cholesterol-related gene CETP predict white matter microstructure

Several common genetic variants influence cholesterol levels, which play a key role in overall health. Myelin synthesis and maintenance are highly sensitive to cholesterol concentrations, and abnormal cholesterol levels increase the risk for various brain diseases, including Alzheimer's disease. We report significant associations between higher serum cholesterol (CHOL) and high-density lipoprotein levels and higher fractional anisotropy in 403 young adults (23.8 ± 2.4years) scanned with diffusion imaging and anatomic magnetic resonance imaging at 4Tesla. By fitting a multi-locus genetic model within white matter areas associated with CHOL, we found that a set of 18 cholesterol-related, single-nucleotide polymorphisms implicated in Alzheimer's disease risk predicted fractional anisotropy. We focused on the single-nucleotide polymorphism with the largest individual effects, CETP (rs5882), and found that increased G-allele dosage was associated with higher fractional anisotropy and lower radial and mean diffusivities in voxel-wise analyses of the whole brain. A follow-up analysis detected white matter associations with rs5882 in the opposite direction in 78 older individuals (74.3 ± 7.3years). Cholesterol levels may influence white matter integrity, and cholesterol-related genes may exert age-dependent effects on the brain.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Towards developing an integrated model of information behaviour

This paper presents the results from a study of information behaviors in the context of people's everyday lives undertaken in order to develop an integrated model of information behavior (IB). 34 participants from across 6 countries maintained a daily information journal or diary – mainly through a secure web log – for two weeks, to an aggregate of 468 participant days over five months. The text-rich diary data was analyzed using a multi-method qualitative-quantitative analysis in the following order: Grounded Theory analysis with manual coding, automated concept analysis using thesaurus-based visualization, and finally a statistical analysis of the coding data. The findings indicate that people engage in several information behaviors simultaneously throughout their everyday lives (including home and work life) and that sense-making is entangled in all aspects of them. Participants engaged in many of the information behaviors in a parallel, distributed, and concurrent fashion: many information behaviors for one information problem, one information behavior across many information problems, and many information behaviors concurrently across many information problems. Findings indicate also that information avoidance – both active and passive avoidance – is a common phenomenon and that information organizing behaviors or the lack thereof caused the most problems for participants. An integrated model of information behaviors is presented based on the findings.

Model interoperability in building information modelling

The exchange of design models in the design and construction industry is evolving away from 2-dimensional computer-aided design (CAD) and paper towards semantically-rich 3-dimensional digital models. This approach, known as Building Information Modelling (BIM), is anticipated to become the primary means of information exchange between the various parties involved in construction projects. From a technical perspective, the domain represents an interesting study in model-based interoperability, since the models are large and complex, and the industry is one in which collaboration is a vital part of business. In this paper, we present our experiences with issues of model-based interoperability in exchanging building information models between various tools, and in implementing tools which consume BIM models, particularly using the industry standard IFC data modelling format. We report on the successes and challenges in these endeavours, as the industry endeavours to move further towards fully digitised information exchange.

A 3D visualisation model applied to a thick, multi-layered alluvial groundwater system under stress : Condamine Valley, QLD

The upper Condamine River in southern Queensland has formed extensive alluvial deposits which have been used for irrigation of cotton crops for over 40 years. Due to excessive use and long term drought conditions these groundwater resources are under substantial threat. This condition is now recognised by all stakeholders, and Qld Department of Environment and Resource Management (DERM) are currently undertaking a water planning process for the Central Condamine Alluvium with water users and other stakeholders. DERM aims to effectively demonstrate the character of the groundwater system and its current status, and notably the continued long-term drawdown of the watertable. It was agreed that 3D visualisation was an ideal tool to achieve this. The Groundwater Visualisation System (GVS) developed at QUT was utilised and the visualisation model developed in conjunction with DERM to achieve a planning-management tool for this particular application

A measurement instrument for process modeling research : development, test and procedural model

Process modeling is an emergent area of Information Systems research that is characterized through an abundance of conceptual work with little empirical research. To fill this gap, this paper reports on the development and validation of an instrument to measure user acceptance of process modeling grammars. We advance an extended model for a multi-stage measurement instrument development procedure, which incorporates feedback from both expert and user panels. We identify two main contributions: First, we provide a validated measurement instrument for the study of user acceptance of process modeling grammars, which can be used to assist in further empirical studies that investigate phenomena associated with the business process modeling domain. Second, in doing so, we describe in detail a procedural model for developing measurement instruments that ensures high levels of reliability and validity, which may assist fellow scholars in executing their empirical research.

Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions

In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

An information literacy integration model and its application in higher education

Purpose - The purpose of this paper is to present a model for curricular integration of information literacy for undergraduate programs in higher education. Design/methodology/approach - Data are drawn from individual interviews at three universities in Australia and curricular integration working experience at a New Zealand university. Sociocultural theories are adopted in the research process and in the development of the model, Findings - Key characteristics of the curriculum integration of information literacy were identified and an information literacy integration model was developed. The S2J2 key behaviours for campus-wide multi-partner collaboration in information literacy integration were also identified. Research limitations/implications - The model was developed without including the employer needs. Through the process of further research, the point of view of the employer on how to provide information literacy education needs to be explored in order to strengthen the model in curricular design. Practical implications - The information literacy integration model was developed based on practical experience in higher education and has been applied in different undergraduate curricular programs. The model could be used or adapted by both librarians and academics when they integrate information literacy into an undergraduate curriculum from a lower level to a higher level. Originality/value - The information literacy integration model was developed based on recent PhD research. The model integrates curriculum, pedagogy and learning theories, information literacy theories, information literacy guidelines, people and collaborative together. The model provides a framework of how information literacy can be integrated into multiple courses across an undergraduate academic degree in higher education.

Analytical solutions for the multi-term time-fractional diffusion-wave/diffusion equations in a finite domain

Multi-term time-fractional differential equations have been used for describing important physical phenomena. However, studies of the multi-term time-fractional partial differential equations with three kinds of nonhomogeneous boundary conditions are still limited. In this paper, a method of separating variables is used to solve the multi-term time-fractional diffusion-wave equation and the multi-term time-fractional diffusion equation in a finite domain. In the two equations, the time-fractional derivative is defined in the Caputo sense. We discuss and derive the analytical solutions of the two equations with three kinds of nonhomogeneous boundary conditions, namely, Dirichlet, Neumann and Robin conditions, respectively.

Attitudes, Ideologies and Self-Organisation : Information Load Minimisation in Multi-Agent Decision Making

Sophisticated models of human social behaviour are fast becoming highly desirable in an increasingly complex and interrelated world. Here, we propose that rather than taking established theories from the physical sciences and naively mapping them into the social world, the advanced concepts and theories of social psychology should be taken as a starting point, and used to develop a new modelling methodology. In order to illustrate how such an approach might be carried out, we attempt to model the low elaboration attitude changes of a society of agents in an evolving social context. We propose a geometric model of an agent in context, where individual agent attitudes are seen to self-organise to form ideologies, which then serve to guide further agent-based attitude changes. A computational implementation of the model is shown to exhibit a number of interesting phenomena, including a tendency for a measure of the entropy in the system to decrease, and a potential for externally guiding a population of agents towards a new desired ideology.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: A time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O₂Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O₂Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O₂Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.