Further development of discrete computational techniques for calculation of restricted diffusion propagators in porous media

Magnetic resonance is a well-established tool for structural characterisation of porous media. Features of pore-space morphology can be inferred from NMR diffusion-diffraction plots or the time-dependence of the apparent diffusion coefficient. Diffusion NMR signal attenuation can be computed from the restricted diffusion propagator, which describes the distribution of diffusing particles for a given starting position and diffusion time. We present two techniques for efficient evaluation of restricted diffusion propagators for use in NMR porous-media characterisation. The first is the Lattice Path Count (LPC). Its physical essence is that the restricted diffusion propagator connecting points A and B in time t is proportional to the number of distinct length-t paths from A to B. By using a discrete lattice, the number of such paths can be counted exactly. The second technique is the Markov transition matrix (MTM). The matrix represents the probabilities of jumps between every pair of lattice nodes within a single timestep. The propagator for an arbitrary diffusion time can be calculated as the appropriate matrix power. For periodic geometries, the transition matrix needs to be defined only for a single unit cell. This makes MTM ideally suited for periodic systems. Both LPC and MTM are closely related to existing computational techniques: LPC, to combinatorial techniques; and MTM, to the Fokker-Planck master equation. The relationship between LPC, MTM and other computational techniques is briefly discussed in the paper. Both LPC and MTM perform favourably compared to Monte Carlo sampling, yielding highly accurate and almost noiseless restricted diffusion propagators. Initial tests indicate that their computational performance is comparable to that of finite element methods. Both LPC and MTM can be applied to complicated pore-space geometries with no analytic solution. We discuss the new methods in the context of diffusion propagator calculation in porous materials and model biological tissues.

How does the use of a reflective journal enhance students’ critical thinking about complexity?

Introduction to Youth Services is a second year Social Work and Human Services unit. In this unit a reflective writing task was introduced to assess students’ reflections on an ongoing tutorial discussion to which they contributed. The discussion was based on a fictional young person each tutorial group ‘worked with’ across eight weeks of a semester. In developing the process and the criteria for the reflective journal, the ideas raised by the Teaching and Assessing Reflective Learning (TARL) in Higher Education project (see Chap. 2) were utilised, scaffolding the work with resources and submission of a draft. The students were also invited to choose the form of reflective process they used, it could be a written journal but did not need to be. The evidence exemplified that a reflective journal is an effective tool for students to record their developing understanding regarding the concept that issues people experience are complex and compounding. Importantly, it was also a useful vehicle for students to begin to consider the impacts of their own and others’ values and beliefs on their response to the issues raised within the case discussion. The reflective journal also helped participants to consider how this learning contributes to the ongoing development of their professional practice framework.

Design thinking frameworks as transformative cross-disciplinary pedagogy

Final report for the Australian Government Office for Learning and Teaching. "This seed project ‘Design thinking frameworks as transformative cross-disciplinary pedagogy’ aimed to examine the way design thinking strategies are used across disciplines to scaffold the development of student attributes in the domain of problem solving and creativity in order to enhance the nation’s capacity for innovation. Generic graduate attributes associated with innovation, creativity and problem solving are considered to be amongst the most important of all targeted attributes (Bradley Review of Higher Education, 2009). The project also aimed to gather data on how academics across disciplines conceptualised design thinking methodologies and strategies. Insights into how design thinking strategies could be embedded at the subject level to improve student outcomes were of particular interest in this regard. A related aim was the investigation of how design thinking strategies could be used by academics when designing new and innovative subjects and courses." Case Study 3: QUT Community Engaged Learning Lab Design Thinking/Design Led Innovation Workshop by Natalie Wright Context "The author, from the discipline area of Interior Design in the QUT School of Design, Faculty of Creative Industries, is a contributing academic and tutor for The Community Engaged Learning Lab, which was initiated at Queensland University of Technology in 2012. The Lab facilitates university-wide service-learning experiences and engages students, academics, and key community organisations in interdisciplinary action research projects to support student learning and to explore complex and ongoing problems nominated by the community partners. In Week 3, Semester One 2013, with the assistance of co-lead Dr Cara Wrigley, Senior Lecturer in Design led Innovation, a Masters of Architecture research student and nine participating industry-embedded Masters of Research (Design led Innovation) facilitators, a Design Thinking/Design led Innovation workshop was conducted for the Community Engaged Learning Lab students, and action research outcomes published at 2013 Tsinghua International Design Management Symposium, December 2013 in Shenzhen, China (Morehen, Wright, & Wrigley, 2013)."

Exploring variation in measurement as a foundation for statistical thinking in the elementary school

This study was based on the premise that variation is the foundation of statistics and statistical investigations. The study followed the development of fourth-grade students' understanding of variation through participation in a sequence of two lessons based on measurement. In the first lesson all students measured the arm span of one student, revealing pathways students follow in developing understanding of variation and linear measurement (related to research question 1). In the second lesson each student's arm span was measured once, introducing a different aspect of variation for students to observe and contrast. From this second lesson, students' development of the ability to compare their representations for the two scenarios and explain differences in terms of variation was explored (research question 2). Students' documentation, in both workbook and software formats, enabled us to monitor their engagement and identify their increasing appreciation of the need to observe, represent, and contrast the variation in the data. Following the lessons, a written student assessment was used for judging retention of understanding of variation developed through the lessons and the degree of transfer of understanding to a different scenario (research question 3).

Computational micromodel for epigenetic mechanisms

Characterization of the epigenetic profile of humans since the initial breakthrough on the human genome project has strongly established the key role of histone modifications and DNA methylation. These dynamic elements interact to determine the normal level of expression or methylation status of the constituent genes in the genome. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters epigenetic patterns causing imbalance that can lead to cancer initiation. This chain of consequences has motivated attempts to computationally model the influence of histone modification and DNA methylation in gene expression and investigate their intrinsic interdependency. In this paper, we explore the relation between DNA methylation and transcription and characterize in detail the histone modifications for specific DNA methylation levels using a stochastic approach.

Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis

Systems-level identification and analysis of cellular circuits in the brain will require the development of whole-brain imaging with single-cell resolution. To this end, we performed comprehensive chemical screening to develop a whole-brain clearing and imaging method, termed CUBIC (clear, unobstructed brain imaging cocktails and computational analysis). CUBIC is a simple and efficient method involving the immersion of brain samples in chemical mixtures containing aminoalcohols, which enables rapid whole-brain imaging with single-photon excitation microscopy. CUBIC is applicable to multicolor imaging of fluorescent proteins or immunostained samples in adult brains and is scalable from a primate brain to subcellular structures. We also developed a whole-brain cell-nuclear counterstaining protocol and a computational image analysis pipeline that, together with CUBIC reagents, enable the visualization and quantification of neural activities induced by environmental stimulation. CUBIC enables time-course expression profiling of whole adult brains with single-cell resolution.

An improved computational method in structural dynamics

Purpose – In structural, earthquake and aeronautical engineering and mechanical vibration, the solution of dynamic equations for a structure subjected to dynamic loading leads to a high order system of differential equations. The numerical methods are usually used for integration when either there is dealing with discrete data or there is no analytical solution for the equations. Since the numerical methods with more accuracy and stability give more accurate results in structural responses, there is a need to improve the existing methods or develop new ones. The paper aims to discuss these issues. Design/methodology/approach – In this paper, a new time integration method is proposed mathematically and numerically, which is accordingly applied to single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. Finally, the results are compared to the existing methods such as Newmark’s method and closed form solution. Findings – It is concluded that, in the proposed method, the data variance of each set of structural responses such as displacement, velocity, or acceleration in different time steps is less than those in Newmark’s method, and the proposed method is more accurate and stable than Newmark’s method and is capable of analyzing the structure at fewer numbers of iteration or computation cycles, hence less time-consuming. Originality/value – A new mathematical and numerical time integration method is proposed for the computation of structural responses with higher accuracy and stability, lower data variance, and fewer numbers of iterations for computational cycles.

Biophysical correlates of intrinsic and stress-induced morphological variability in lateral amygdaloid neurons: A computational study

Morphological and physiological characteristics of neurons located in the dorsolateral and two ventral subdivisions of the lateral amygdala (LA) have been compared in order to differentiate their roles in the formation and storage of fear memories (Alphs et al, SfN abs 623.1, 2003). Briefly, in these populations, significant differences are observed in input resistance, membrane time constant, firing frequency, dendritic tortuosity, numbers of primary dendrites, dendritic segments and dendritic nodes...

Rediscovering law students as citizens: Critical thinking and the public value of legal education

In a series of publications over the last decade, Australian National University Professor Margaret Thornton has documented a disturbing change in the nature of legal education. This body of work culminates in a recently published book based on interviews with 145 legal academics in Australia, the United Kingdom, New Zealand and Canada. In it, Thornton describes a feeling of widespread unease among legal academics that society, government, university administrators and students themselves are moving away from viewing legal education as a public good which benefits both students and society. Instead, legal education is increasingly being viewed as a purely private good, for consumption by the student in the quest for individual career enhancement.

Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.