Griffith Sciences Collaborative Research Summer Scholarship

Monitoring, analysis, and orientation visualisation of human activities using a wireless wearable inertial sensor

Dr Huaizhong Li (EBE); Dr Can Wang* (ICT)

Monitoring of human activities is required in applications such as healthcare, safety, and sports. This project will explore the application of a low-cost wireless wearable inertial sensor in human activity monitoring. The sensor records data for three orthogonal directions using 3-axis accelerometer, gyroscope, and magnetometer. Student will conduct tests to record signals for some basic human activities with the inertial sensor attached to different body segments. The data will be analysed using quaternion orientation solutions to identify the 3D orientation and rotation of the corresponding body segment. Computer algorithms will be developed to visualise the movement, rotation, and orientation.

When Glycobiology meets Nanotechnology

Prof. Joe Tiralongo (ESC); Dr Oren Cooper* (GLY)

Micro-technologies in the form of Micro-Electro-Mechanical Systems (MEMS) and micro-plasmonics platforms offer the potential for high-resolution, high-throughput label-free sensing of biological and chemical analytes. Silicon carbide (SiC) is an ideal material for augmenting both MEMS and plasmonics routes, however such inorganic surfaces need to appropriately and efficiently functionalised to allow subsequent immobilisation of functional biomolecules. To this end we trialled various organosilane-based self-assembled monolayers for the covalent functionalisation of 2-dimensional SiC films, and have now developed an affordable, facile one-step method. Using high-throughput glycan arrays as our model system a novel platform that has the potential to combine established array technology with the label-free capabilities of MEMS or plasmonic systems is one step closer.

Geo-spatial Bird Hotspots in Airspace by Utilizing Weather Radar Data

Xiaoyu Wu (EBE) & Xiaohan Yu (IIIS)

This study focuses on the innovative application of weather radar data to locate geo-spatial hotspots of bird populations in the airspace. By examining high-resolution radar imagery, researchers will analyse bird density, movement patterns, and the influence of environmental factors on bird behaviour. The study aims to provide critical insights into the spatial distribution of avian hotspots, facilitating the development of more targeted and effective aviation wildlife management strategies. Furthermore, these findings can contribute to the understanding of bird migration patterns, promoting the conservation of avian species and improving airspace safety.

Variation in remote sensing of chlorophyll in reservoirs in South East Queensland

David Hamilton, Hassan Ranbar

This project will take remote sensing images from Google Earth Engine to examine the variation of chlorophyll (indicating algal concentrations) in several reservoirs in South East Queensland. The focus will be on variation among reservoirs, locations within reservoirs and through time.

Superparamagnetic Drug Nanoparticles via Microfluidics Electrostatic Atomization for Medical Applications

Van Dau (CCEE, EBE) and Khoa-Tuan Nguyen* (QMNC, EBE)

The project’s goal is to develop a methodology and prototype device to functionalize superparamagnetic iron oxide nanoparticles (SPIONs) generated by microfluidics electrostatic atomization process for medical applications. The research will develop a solvent containing SPIONs, and the electrostatic atomization process to produce the SPIONs droplets as well as for better biological performance. In this project timeframe, we aim to develop a 3D prototype and collect fundamental results of delivering micro/nano drug particle which has superparamagnetic characteristic. Future steps and applications, including lung imaging and targeted pulmonary drug delivery, will be followed as several IAP projects in Term 1, 2023.

Measuring soil carbon content using hyperspectral-imaging and NIR technology

Prof. Jun Zhou and Dr. Xiangyu Liu   ECR: Xiangyu Liu from ESC

Measuring soil carbon with hyperspectral-imaging and NIR technology is essential for precision agriculture, soil health assessment, climate change mitigation, and environmental monitoring. It enables data-driven decisions, aids in resource-efficient land management, and promotes sustainable practices.  During this project, soil carbon content in 500 (Approx.) samples will be measured via hyperspectral imaging and NIR. Estimation model of soil carbon content will be generated via two spectral based technology. Machine learning will be adopted in the process of model establishment and lab measured result will be used as validation. Reliable carbon estimation model will be developed at the end of the project.

Setup and characterisation of atmospheric plasma jet experiment

Nathan Garland* ESC, Maksym Rybachuk EBE

This project will be a pilot study to help researchers understand and set up an atmospheric air plasma jet experiment. This will involve assembling the required equipment and laboratory environment, and establishing basic operations of the experimental apparatus for future research projects.

Developing a failure criterion for FFF-manufactured polymer parts

Dr Zia Javanbakht (EBE), Dr Jayishni Maharaj (SHS)

With the introduction of Fused Filament Fabrication (FFF) in the early 2000’s, a new, renewable and waste free manufacturing technique became the standard for sustainable manufacturing. New materials are consistently developed, namely, plastic polymers to support this manufacturing process, and thus must withstand the natural and unnatural forces acting upon them. The mechanical properties of 3D printed materials are widely studied due to the unique style of manufacturing testing specimens. Typical failure modes reported include inter-layer and in-layer failures. Most notably in tensile samples but occasionally in compression. The investigation of FFF parts includes the preposition of failure theory to predict these behaviours accurately.

Numerical modelling of customised foot insole for diabetic patients

Dr Zia Javanbakht (EBE), Dr Jayishni Maharaj (SHS) [both are ECRs]

The development of manufacturing methods has enabled the production of structures with desired geometries. In biomedical applications, scaffolds, bone implants, and foot insoles can take advantage of this advancement. However, the challenge is providing a customised design for the specific need of patients and streamline the design approach using automated numerical/analytical methods. More specifically, diabetic patients require specific foot insoles to reduce/prevent the damage to their feet. This project aims to develop a numerical solution to optimize the stress distribution in foot insole for diabetic patients.

Harmonizing Housing and Sustainability: A Transdisciplinary Framework for Energy Efficiency and Livability Enhancement

Dr Peyman Akhgar* (CRI), Dr Mohammad Sanjari (IIIS)

The goal of this project is to create a framework that can improve the energy efficiency and overall livability of the current housing stock. The primary objective is to initiate transdisciplinary research through close collaboration between architects and engineers to develop a cost-effective and practical framework alongside comprehensive transitional strategies toward sustainable housing. The employed student on this project will work with an energy expert and architect to conduct spatial and energy analyses of current housing in SEQ, review relevant studies, and assist in publishing interdisciplinary research.

Skies in Harmony: Navigating Sustainability, Biodiversity, and Safety in Aviation

Xiaoyu Wu Ph.D. (ECR), Ali Chauvenet

To provide a holistic understanding of the multifaceted challenges faced by the aviation industry, encompassing sustainability, biodiversity conservation, climate change mitigation, and safety, and to develop potential strategies for balancing these considerations.

Analysing Simulations of B-Raf Protein and its Oncogenic Mutant V600E

Dr Alpesh Malde (ESC, Glycomics) and Dr Shern Tee* (ESC, QMNC)

B-Raf is an important regulatory protein with a significant cancer-causing mutation V600E. The supervisory team is conducting extensive molecular dynamics simulations of the protein and its mutant to understand its structural fluctuations, informing future cancer detection and treatment methods. The student will assist in literature review of previous simulations and structural studies and in visualising our results. They should have a strong biochemistry background and be comfortable organising computer data and learning new software.

AI-Enhanced Real-time Quality Assurance in Additive Manufacturing

Stefanie Feih (EBE); Xuefei Yin* (ICT)

This project aims to improve the quality assurance of powder-based polymer additive manufacturing using real-time AI-powered image analysis. The goal is to enhance precision and efficiency in the printing process, addressing challenges in maintaining high-quality output. The focus involves developing advanced algorithms for real-time image analysis, enabling immediate feedback to optimize quality assurance during manufacturing. The research explores existing AI frameworks tailored to additive manufacturing and novel methodologies for adaptable and robust AI models. Successful implementation could streamline production, reduce waste, and enhance the reliability of printed components. Participants in this internship gain hands-on experience in AI applications for advanced manufacturing, contributing to groundbreaking research in real-time quality assurance.

Epigenetic factors associated with pathogenicity in the nectotrophic fungus Ascochyta rabiei infecting chickpea

Dr. Jonathan W. Lawley* (CPHFS), Dr. Mark de Bruyn (ARCHE)

Ascochyta Blight caused by the fungus Ascochyta rabiei is a major biotic threat to chickpea worldwide and incurs substantial costs to the Australian multimillion-dollar chickpea industry in disease control and yield losses. As part of a grant funded by the Grains Research and Development Corporation (GRDC) on investigating the biology and epidemiology of Ascochyta rabiei, this project will analyse the epigenetic factors potentially associated with aggressiveness of the fungal pathogen. This project will involve conducting high molecular weight DNA extractions for high-throughput sequencing and bioinformatic analyses, a great opportunity to gain experience in cutting-edge molecular biology techniques and bioinformatics.