Mathematical modelling of fumigant transport in stored grain

Computational fluid dynamics, analytical solutions, and mathematical modelling approaches are used to gain insights into the distribution of fumigant gas within farm-scale, grain storage silos. Both fan-forced and tablet fumigation are considered in this work, which develops new models for use by researchers, primary producers and silo manufacturers to assist in the eradication grain storage pests.

Stabilization of experimental bioretention basins during intermittent wetting and drying

Stormwater bioretention basins are subjected to spontaneous intermittent wetting and drying, unlike water treatment filter systems that are subjected to continuous feed. Drinking water filters when constructed new or after back-wash, are subjected to a phase of stabilization. Experiments show that bioretention basins are similarly impacted by intermittent wetting and drying. The common parameter monitored in the stabilisation of filters is the concentration of total solids in the outflow. Filter media in bioretention basins however, consists of a mix of particulate organic matter and fine sand. Organic carbon and solids are therefore needed to be monitored. Four Perspex bioretention filter columns of 94 mm (ID) were packed with a filter layer (800 mm), transition layer and a gravel layer and operated with synthetic stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. Synthetic stormwater was prepared by adding NH4NO3 (ammonium nitrate) and C2H5NO2 (glycine) and a mixture of kaolinite and montmorillonite clay, to tapwater. The columns were fed with synthetic stormwater with different Antecedent Dry Days (ADD) (0 – 25 day) and constant inflow concentration (2 ppm: nitrate-nitrogen, 1.5 ppm: ammonium-nitrogen, 2.5 ppm: organic-nitrogen 100 ppm: total suspended solids and 7 ppm: organic carbon) at a feed rate of 100mL.min (85.7cm/h). Samples were collected from the outflow at different time intervals between 2 – 150 min from the start of outflow and were tested for Total Suspended Solids (TSS) and Total Organic Carbon (TOC). Both TSS and TOC concentrations in the outflow were observed to be much higher than the concentration of both the parameters in the inflow during the stabilisation period indicating a phase of wash-off (first flush) which lasted for approximately 30 min for both parameters at the beginning of each storm event. The wash-off of TSS and TOC were found to be highly variable depending on the age of the filter and the number of antecedent dry days. The duration of stabilisation phase in the experiments is significant compared with many of the stormwater events. A computational analysis on total mass of each pollutant further affirmed the significance of the first flush of an event on removal of these pollutants. Therefore, the kinetics of the first flush in the stabilisation phase needs to be considered in the performance analysis of the systems.

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

How can partnerships between the universities and schools exploit new opportunities for pedagogies at the intersection of the arts/design and the sciences?

Driven by information accessibility-on-demand provided by the internet, education modes are changing from a teacher-led approach focused on content delivery and assessible outcomes, to a learner-based approach encouraging self-directed, peer-tutored, and cooperative learning. New pedagogies are required to extend learning beyond the classroom and traditional subject areas such as contemporary arts, in alignment with the cross disciplinary priorities of the Australian Curriculum and values of the International Baccalaureate Organisation. This research explores how partnerships with universities and cultural organisations are implicated in the generation of these new forms of pedagogy and contribute to the field of educational research within the context of Education Queensland’s Framework For Gifted Education. In particular, this paper explores a new pedagogical framework for highly capable year five to nine Queensland state school students at the intersection of arts, design and the sciences, which has arisen from an explicit secondary/ tertiary partnership between the Queensland University of Technology Creative Industries Faculty and Precincts and the Queensland Academies Young Scholars Program. The Young Scholars Program offers experiences in the International Baccalaureate and Australian Curriculum contexts to enhance outcomes via global understanding, unique industry partnerships and 21st century pedagogical innovation based not on 'content' but tacit/experiential learning concepts including immersive, creative, intellectual and social strategies. These strategies for highly capable students are centred around authentic opportunities, primary resources, transdisciplinary learning and relationships with likeminded peers including tertiary arts, design and STEM educators and students, professionals and researchers. The presentation details case studies which are hands-on real time workshops involving inquiry based challenges in the arts, design and sciences, mathematics, history, creative writing and other disciplines, with content drawn from collections from public institutions, academic research and tertiary pedagogy. Both programs implicate student collaboration and creative production as methodology/data capture for ongoing action research, in alignment with the Framework For Gifted Education’s emphasis on evidence-based practices. They also challenge gifted students “to continue their development through curricular activities that require depth of study, complexity of thinking, fast pace of learning, high-level skills development and/or creative and critical thinking (e.g. through independent investigations, tiered tasks, diverse real-world applications, mentors)”(Education Queensland, 2011:3). This presentation highlights the strengths of the ongoing collaboration between QUT Creative industries Faculty and Queensland Academies, which not only provides successful extra curricular activities for gifted students towards a place in the International Baccalaureate Program, but also provides mentoring opportunities for tertiary students in their field of endeavor to assist with their own learning, and unique research opportunities for the Faculty as it focuses on excellence in arts, design and creative education and research. Education Queensland.(2011). Framework For Gifted Education Revised Edition 2011 (accessed Nov 19 2011)

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision.