Science

TSP conference: papers and posters

The TSP conference brings together the students’ research deliverables for their respective projects as they share their findings to the UNSW Science community in the form of presentations and posters.

TSP Conference members 2023

At the end of each year, TSP students, academics and other UNSW Science community members gather to celebrate the collaborative work students and researchers have achieved over the past few months.

Students choose a research project or research group in one of the schools of UNSW Science or UNSW Medicine to work on current challenges that our academics are trying to solve. This is an opportunity for our students to be immersed in the research realm where they may attend research group meetings, perform laboratory experiments and be at the forefront of science discovery.

  • Posters

     

    • Name: Caitlyn Tan
      Supervisor: Andrew Brown

    • Name: Ernest Deng
      Supervisors: Shawn Laffan

    • Name: Saxon Dean
      Supervisor: Caroline Foster and Ryan Bagge

    • Name: Julia Harrison
      Supervisor: Luke Hunter

    Presentations

    • Name: Nicole Chen
      Supervisor: School of Biomedical Science

      The ventral respiratory column (VRC) is a longitudinal group of neurons in the ventrolateral medulla that generates and coordinates the respiratory rhythm. It contains distinct subgroups, including the pre-Bötzinger complex, Bötzinger complex, and rostral ventral respiratory groups, which control inspiratory and expiratory patterns and integrate sensory inputs such as CO₂ levels. This study involved analysis of immunohistochemistry brain sections from mice exposed to long-term recurrent intermittent hypercapnia, an acute hypercapnic challenge, neither, or both. Using ΔFosB as a marker of repeated neuronal activation, ΔFosB⁺ neurons in the VRC were quantified to assess potential long-term neuronal adaptation.

    • Name: Caiyi Wang
      Supervisor: Blake Cochran and Nasir Shah

      Patients who prepare for dialysis often struggle to understand how arteriovenous fistulas function and why surgery is required. Currently, traditional methods of education involving 2D diagrams and verbal explanations can be difficult to visualise, leading to decreased confidence in patients during decision-making. With 3D-printing technology allowing users to customise unique models for clinical education, this project investigated whether using a 3D-printed fistula model or a 2D diagram was more effective in improving patient understanding during their education sessions. Qualitative feedback from patients was collected, highlighting their preference and suggestions to improve the model for future iterations. The 3D printed model appears to improve patient understanding by presenting a more tactile and life-size portrayal of human anatomy. These findings indicate that 3D-printed models may be a valuable education tool, warranting further investigation with a larger cohort.

    • Name: Jasmine Azizi, Harry Mangos, and Matilda Stewart
      Supervisor: Victor Flambaum

      The comprehension of quark nuggets - highly dense clusters of quarks including strange quarks - and their properties first requires considerations of the hierarchy problem and its potential solutions, *specifically the ADD model and Randall-Sundrum (RS) models. The ADD model suggests the existence of extra compactified dimensions through which gravity can propagate, resulting in greatly increased gravitational potential at small distances and explaining the comparative weakness of gravity to the other fundamental forces. The particular RS model that foregrounds quark nugget research proposes the existence of two ‘branes’ separated within ‘bulk’ through which gravity can propagate, and concentrating near the TeV brane where the rest of our observable universe and standard model are confined. For these models to apply effectively, the Einstein field equations for gravity must be modified for 3+n dimensions. In these models, gravity is significantly stronger at distances approximately equal to either the size of the extra dimensions in the ADD model, or the distance between the branes in the RS model. Quark nuggets are a potential candidate for dark matter. The increased gravity over small distances from the above theories provides a means for quark nuggets’ stabilisation and survival in hot primordial plasma.

    • Names: Akio Eastburn Todo
      Supervisors: Simona S. Capomolla and Jonathon E. Beves​

      Metal-ligand self assembly offers a powerful route to constructing complex, functional molecular architectures from far simpler components. In this work, we report the synthesis of a novel bidentate ligand designed to bias toward assembling into heteroleptic Pd(II) cages. The ligand, 1,4-bis(6-methylpyridin-3-yl)benzene, is obtained in good yields and high purity, with NMR data confirming its structure and coordination behaviour. Preliminary self assembly experiments using Pd(II) and a complementary ligand display early evidence that it is capable of participating in a range of heteroleptic assemblies. These results build upon the existing understanding of how ligand size and geometry influence heteroleptic cage formation.

    • Name: Lisa Chao
      Supervisors: Camille Mora and Lisa Alexander​

      Wheat is more than food—it is geopolitics. Russia, one of the world’s largest wheat exporters, has experienced major climate extremes that disrupted global supply, notably the 2003 and 2010 heatwaves. Yet 2012, a year when USDA and Rosstat reported wheat yields reduced by nearly 25%, remains strangely absent from the literature. This project investigates whether 2012 was an overlooked climate event. Using NOAA weather station data from Stavropol, daily climatologies were calculated with a 5‑day moving window and LOESS smoothing, validated with RMSE and train‑test methods (R² ≈ 0.95). Results revealed multiple days in May 2012 with anomalies exceeding +4 °C, and April–May contained significant deviations above one standard deviation from baseline. However, given Stavropol’s winter wheat cycle, anomalies in late 2011 may better explain yield declines. Comparative analysis with 2010 highlights the unusual nature of 2012. These findings underscore the importance of identifying “missing” climate extremes, as underestimation of events like 2012 risks misjudge global food security vulnerabilities and climate loss & damage estimates.

    • Name: Gabrielle Zhong
      Supervisor: Michael Janitz and Yulan Gao​

      Multiple sclerosis (MS) is an autoimmune disease characterised by demyelination and inflammation of the central nervous system. Recent advancements in RNA sequencing technology have revealed circular RNAs (circRNAs) have a key regulatory role in gene expression and have a promising capacity to act as biomarkers for the disease. In this study, we investigated circRNA expression in 13 MS samples obtained from white matter lesions and 23 control samples from healthy individuals. CircRNA prediction was performed using 2 circRNA detection tools, CIRI2 and CircExplorer2. Subsequent differential expression analysis revealed 192 differentially expressed circRNAs in MS samples compared to controls (p-value < 0.05). Several of these circRNAs may serve as potential biomarkers, providing insights into MS pathogenesis and molecular mechanisms.

  • Posters

     

    • Name: Jet Chong
      Supervisor: Kevin J Laws

    • Name: Isabella Bustos-McNeil
      Supervisors: Laura K McKemmish

    • Name: Caitlyn Tan
      Supervisors: Brenna Osborne, Calum Vancuylenburg, Stephanie Alexopoulos and Kyle Hoehn

    Presentations

    • Name: Sania Parekh
      Supervisors: Michael Janitz and Si-Mei Xu

      Also known as uterine cancer, endometrial cancer is the most common gynaecological cancer with 1900 women in Australia diagnosed every year. Current diagnostic principles rely on biomarkers such as microsatellite instability or mismatch repair deficiency genes. Fusion RNAs are RNA transcripts that contain exons and sometimes introns from different parental genes. With the emergence of fusion RNAs that have been associated with other cancers, an investigation into identifying fusion RNAs associated with endometrial cancer is paramount for earlier diagnosis and treatment. As such, the aim of this project was to identify fusion RNAs in an endometrial cancer cell line using a bioinformatic analytical pipeline involving fastQC, trimmomatic, STAR alignment and JAFFA. Results were validated using the Integrated Genome Viewer (IGV). A total of 70 high confidence fusion RNA transcripts were found. 

    • Name: Zara McNally and Alyssa Lim
      Supervisor: Newby Lab, School of Psychology

      Placebo controls are necessary to determine the true effect of a treatment by effectively controlling for the impact of expectations on treatment outcomes in clinical trials. Although typically used for pharmacological interventions, they are equally necessary when testing effective psychological interventions, but are often ignored in the experimental design of randomised controlled trials. This systematic review aims to determine the current state of randomised controlled trials for digital mental health interventions, including identifying the current control types (e.g., treatment-as-usual, waitlist controls, attention controls) and how each control type impacts treatment estimates. It is expected that the effect sizes of most digital interventions are inflated, because they lack adequate controls for expectation and blinding.

    • Name: Bronte Critchley
      Supervisors: Michael Janitz and Yulan Gao

      Circular RNAs are single-stranded, non-coding RNA molecules within the transcriptome which have been the focus of recent research due to the various locations they can be found in, including the brain. CircRNAs were discovered to play roles in gene expression, interacting with other coding and non-coding RNAs, as well as influencing downstream protein synthesis and functions. The Janitz lab, which I was a part of for my TSP project, investigates dysregulated circRNAs through bioinformatic programs. My aim specifically was to identify potential circRNA candidates to act as biomarkers for Parkinson’s disease. This is achieved by investigating the expression of circRNAs in patients with Parkinson's compared to healthy controls to identify circRNAs which are expressed differently. My project included running an analytical pipeline on Katana and Rstudio.

    • Names: Cindy Chen
      Supervisor: School of Psychology

      Safety learning is a form of fear inhibition that involves learning that a specific cue signals the absence of danger, which is disrupted in clinical anxiety disorders, leading sufferers to experience high levels of fear and anxiety in places they otherwise feel safe. Our understanding of the brain mechanisms is limited, partially due to the lack of a robust and reliable way to assess this learning. The current study explores safety learning in mice through a cue discrimination procedure, where an auditory cue was paired with two distinct visual cues. The mice learned to distinguish between a visual conditioned stimulus (CS) predicting a shock and one indicating safety (the safety signal). To ensure safety learning was achieved, the mice underwent a summation test which compared their response to a novel auditory signal when paired with a previously dangerous or safe cue and a retardation test, assessing if it took longer for the previously safe cue to be re-associated with danger when compared to the control group.

    • Name: Hannah Wah Day
      Supervisors: Martina Lessio and Fabio Colasuonno

      The widespread use of plastics today contributes significantly to the continuous accumulation of plastic waste in the environment which has various negative consequences including contamination of natural systems and harm to wildlife. The main recycling method currently is mechanical recycling which is limited by lifetime degradation and the presence of contaminants leading to low quality products. Chemical recycling by means of hydrogenolysis over a metal catalyst is currently being investigated as an alternate solution whereby polymer chains can be broken down into monomers and other desirable chemicals. Ruthenium has emerged as a promising catalyst for the upcyling of polyolefins, which are commonly found in plastics. This project computationally models the upcycling of polyethylene, a type of polyolefin used in plastic bags, films and containers, using short-chained alkanes, with the aim of gaining insight into how longer polymer chains may interact with the Ruthenium catalyst. Determining trends in the favourable configurations and binding energies of the alkanes interacting with different surfaces provides insight for further investigation into the mechanism of C-C bond cleavage in this system. 

    • Name: Rose Mitsui
      Supervisors: Michael Janitz and Grace Lindner

      Circular RNAs are emerging as important regulators in gene expression and disease. This project aimed to investigate the expression of circular RNAs in human brain samples treated with KCl at two time points: 0 and 6 hours. A bioinformatic pipeline was used to detect circular RNAs likely present in the samples. This project highlights the potential avenues to use circular RNAs for further research in brain activity and neurological disorders.

  • Posters

     

    • Name: Thomas Nguyen
      Supervisor: Sarah Brough

    • Name: Hannah Wah Day
      Supervisors: Martina Lessio and Fabio Colasuonno

    • Name: Kerri Belinda Wainstein
      Supervisor: Marc Wilkins

    Presentations

    • Name: Yashwanth Madan
      Supervisor: Sarah Martell

      Lithium is a rare element, constituting 1% of the universe, and is known for its susceptibility to destruction through nuclear fusion in stars. Subsequently, astronomers expect that the lithium content within a star will gradually diminish over time due to the fusion and convection that occur throughout its lifespan. An intriguing puzzle emerges as several thousand red giant stars have been observed to be rich in lithium content. This defies our expectations as the red giant phase is late in a star's life cycle, by which time most of the initial lithium abundance should have been destroyed. Studies of the other properties of lithium-rich red giants aim to pinpoint what is special about them, and what unusual processes they may have undergone. This project investigates the recent observation that ~55% of lithium rich stars also exhibit strong absorption in the helium absorption line at 10830 Å, using optical and near-infrared spectroscopy for a set of 49 red giants obtained with the Very Large Telescope in Chile. Within this data set we do not find any correlation between high lithium abundance and high helium absorption, with 2 stars having high helium absorption and none of those stars having high lithium abundance. Future work in this project will include simulating evolution of lithium abundance in a population of red giants to understand which processes are effective at creating lithium richness.

    • Name: Joseph Evans
      Supervisor: Michael Janitz

      Circular RNAs (circRNAs) are small noncoding molecules that are increasingly believed to play an important role in gene expression. They consist of a single strand of RNA, covalently looped to itself to form a circular molecule. As a relatively new focus in the literature, there are limited tools and softwares available for analysing circRNAs. In particular, the presence of microRNA recognition elements (MREs) and RNA-binding protein (RBP) sites, as well as the visualisation of the molecule, are the key features that could be considered using bioinformatics. Here, we investigated two bioinformatics softwares for circRNA analysis: CircView and CRAFT. We found that CircView was capable of basic visualisation of circRNAs, but was unable to provide any deeper MRE or RBP site analysis. CRAFT provided a much more promising bioinformatics platform for functional predictions involving MREs and RBP sites. 

    • Name: Auguste McNally
      Supervisor: Martina Stenzel

      Lithium metal anodes are ideal for lithium-ion battery use due to their high energy density. The use of zero excess lithium in batteries (i.e. anode-free batteries) offers the remarkable energy density of the lithium metal anode while minimising the risk and reducing cost by forming the anode in situ on the current collector. However, these anode free batteries suffer from poor cyclability due to formation of unreactive lithium from the plating and stripping process. This project investigated the use of lab made aluminium-lithium alloy as a cathode collector for anode free batteries to increase their cyclability and capacity. Current results show that the lithium, at low current rates, can be sufficiently stripped from the alloy and thus potentially act as an extra lithium source for anode free batteries. 

       

    • Names: Willow Heller and Alyssa Lim
      Supervisor: Gavan McNally

      Fibroplast growth factor (FGF21) is a liver-derived hormone with pharmaceutical applications in diabetes treatment. Further, recent research has nominated a potential circuit-specific function in suppressing alcohol consumption in both humans and rodents. Prior research has not examined the effect of this compound when animals are given a choice between alcohol and an alternative. Furthermore, the effect of this drug following escalated alcohol consumption has yet to be observed. The present study examined the effect of different dosages of an FGF21 analogue PF-05231023 on home-cage intermittent ethanol consumption in mice exhibiting pre-existing escalated alcohol consumption, freely choosing between water and ethanol. We observed that a 3% dosage of PF-05231023 but not a 1% or 10% dosage significantly reduced ethanol preference and consumption in the first day following injections. We conclude that PF-05231023 has some effect in reducing alcohol consumption in this model of alcohol use disorder, however its effects are less clear over extended periods.

    • Name: Xiangjun Tan
      Supervisor: Susan Coppersmith

      It is well known that quantum algorithms can simulate the many-body problem. Our work specifically focuses on simulating collective oscillations, which can contribute non-linearly to the evolution of flavours. We simulate the time evolution of a model with three neutrino flavours for one neutrino and collective neutrino oscillations using U ∈ SU(4) representation on a noisy quantum processor. We explore a generalization of the Trotter-Suzuki approximation for time-dependent Hamiltonian dynamics. Additionally, we suppress errors using strategies like the Trotter and Cartan decomposition to reduce the gate cost. A noise model for the corresponding quantum processor is also created to perform Zero-Noise Extrapolation (ZNE) and Probabilistic Error Cancellation (PEC) error mitigation on NISQ devices.

       

    • Name: Angela Lin
      Supervisor: Maitreyee Roy

      Epiretinal membrane (ERM), a prevalent eye condition primarily affecting the elderly, is characterised by fibrocellular tissue on the retina's inner surface. While Optical Coherence Tomography (OCT) has long served as the conventional method for ERM detection, the assessment process remains a formidable and time-consuming challenge for ophthalmologists. Recent advancements in the medical field have witnessed a transformative integration of deep learning-based artificial intelligence (AI) in the diagnosis of ERM. This innovative approach facilitates detecting and staging common ocular disorders, such as ERM, which possess distinctive features. This study delves into the research papers that have explored the capabilities of various AI models in ERM determination and conducted comparative analyses of their performance. The findings across these studies are remarkable, underscoring the AI models' superior performance metrics, including accuracy, specificity, and sensitivity in ERM diagnosis when compared to traditional ophthalmological assessments. In essence, the research unequivocally demonstrates that AI models exhibit a significantly enhanced capability to detect and diagnose ERM, thus presenting an advancement in the field of ophthalmology.

  • Posters

    • Name: Peta Gilbert
      Supervisor: Grace Lindner and       Dr Michael Janitz

    • Name: Karina Guo
      Supervisors: Jason Bragg and Will Cornwell

       

    • Name: Carmen Ossimitz
      Supervisors: Jai Tree, Thomas Zammit and Brandon Sy

  • Presentation Abstracts

    • Name: Vanessa Prajitno 
      Supervisor:       Dr. Blake Cochran & Dr. Kerry-Anne Rye

      Type 1 Diabetes (T1D) is a metabolic autoimmune disease caused by pancreatic β-cell dysfunction as a result of immune system disorders. Viral infections such as SARS-CoV-2 may induce activation of inflammatory chemokines which precipitates to chronic inflammation that may aggravate β-cell dysfunction as the patient’s immune system starts to produce auto-antibodies against virally infected β-cells. Reduced β-cell functions cause lower expression of insulin, resulting in persistent hyperglycaemia. However, studies have found that β-cell dysfunction can be mitigated by HDL apolipoprotein mimetic peptides such as D6PV. We demonstrated this by using NOD mice to analyse D6PV treatment efficacy, measuring blood glucose concentration and characterizing the severity of insulinitis in pancreatic islet cells. Our results found a significant reduction of blood glucose levels and less inflammatory infiltrates present in pancreatic islets of D6PV-treated mice, thus indicating that there is great potential in the usage of D6PV to treat patients with T1D.

    • Name: Hugo Sebesta 
      Supervisor:       Prof. Rajib Rahman and Dr Edyta Osika

      When a particle is constrained in a number of degrees of freedom, it becomes best described by quantum physics. Within this theory, a sufficiently small particle is best described by a wave function, the evolution of which is determined with Schrodinger’s equation. The quantum dot is a 1D approximation of an electron constrained in all three dimensions, such as at a phosphorus impurity in a silicon lattice. Such a quantum system can be described as “two-level”, making it relevant in the quantum computing scene. I have performed several typical calculations relating to this system, showcasing some important quantum effects and ideas including Hamiltonians, anticrossing and detuning, time evolution with a changing electric field (loosely simulating some interaction) and resonance-driven quantum state transitions between the computational base states.

    • Name: Yingze (Rita) Lyu 
      Supervisor:       Dr. Benjamin Montet 

      Star spots are areas of the reduced surface caused by magnetic fields inhibiting the process of convection or the transfer of heat due to the movement of plasma within a star. They appear as dark patches on the photosphere of stars, so it reduces the star’s overall brightness. Therefore, star spot activities may lead to erroneous planetary properties for transiting exoplanets. This may provoke false planet detections and reduce the precision of astrometry. In my research project, I have developed a python function that calculates the astrometric shift of the photometric centre of light caused by their star spots and used real-life sunspot data to test and validate the function.

    • Name: Felix Lempriere 
      Supervisor:       Scott Kable

      Prior experimental investigations of the roaming photodissociation of formaldehyde (H2CO -> CO + H2) through Velocity Map Imaging (VMI) of the dissociating CO fragment revealed anisotropic behaviour in the velocity distributions. This anisotropic behaviour is linked to the correlations between the v, J and μ vectors which in turn describe the mechanism behind the molecular reaction. An energy-dependent change in these correlations indicates potential energy-dependent switching between reaction mechanisms. In this project we aimed to determine the energy-dependent anisotropy of previous experimental CO data, to look for patterns in isotropy to guide further experimental investigation of these vector correlations, and better understand the dissociation mechanisms behind formaldehyde roaming.

    • Name: Claudia Tran  
      Supervisor: Dr Maitreyee Roy  

      Keratoconus is an eye disease of children & young adults, where vision is gradually distorted through changes to the front surface of the eye. There is limited success detecting keratoconus in less equipped clinics, so the aim of the project is to develop a necessary screening test. I have been involved in the conceptual development of SPARK, and I hope to present the work so far at the conference. SPARK involves the use of a smartphone and contact lens to detect keratoconus, using MATLAB to simulate the surface of the eye.  

      I was fortunate to work with Dr Maitreyee Roy and Jack Gordon, fostering an introductory understanding of keratoconus and machine learning through literature reviews. These involved concepts such as the emissions spectra of LEDs & Köhler illumination, the application of decision trees, the Cylite Hyperparallel OCT, as well the role of the Basement Membrane in keratoconus detection.

    • Name: Emily Huynh 
      Supervisor:

      Strokes are the cause of death for many people each year and by observing blood supply to the brain, therapies for stroke prevention and treatment can be developed. In particular, the brain’s response to losing oxygen and being reoxygenated is an interesting area for further research. In this presentation, I consider the significance of a paper published earlier this year that proposed a new model to monitor the brain. Instead of rodent models, which requires complex machinery and techniques, a group of Japanese scientists experimented with Zebrafish. This species has transparent larvae and has many advantages in terms of management, monitoring and data collection.

    • Name: Jessica Whetters
      Supervisor:       Richard Vickery & Ingvars Birznieks

      Electrical stimulation is a core tenant of research in sensory neurophysiology, as it allows the measurement of neural responses and the testing of specific variables on the sensation of touch. One form of electrical stimulation is Transcutaneous Electrical Stimulation (TENS) – a method which uses electrodes (often silver chloride) placed on the skin to deliver repetitive electrical pulses. Previous research demonstrates that nerve impulses tend to ‘fuse’ and plateau in response to TENS frequencies of 80-100Hz, demonstrating the inability of TENS to consistently recruit afferents at high frequency. To determine if this is the result of stimulus issues or physiology of nerve afferents, I will do a literature review of the current research – particularly focusing on how repetitive stimulation of frequencies 100Hz and upwards affects nerve recordings as SNAP recordings. I will also explain the relevance of this question to the research being conducted in Richard and Ingvars’ lab.

    • Name: Kaya Dahlke 
      Supervisor:       Dr Michael Janitz

      mRNA transmits information so cells can make proteins from the information contained in DNA. Mature mRNA has a chain of Adenine bases at its end for protection called a poly A tail. I used data collected using nanopore sequencing to compare the poly A tail length distribution between healthy uterus tissue and endometrial cancer. I did this for the full distribution, as well as for only the mitochondrial mRNA. I also compared the poly A tail length at different points along the chromosome between healthy and cancerous tissue. The aim of this was to cross check that the sequenced data was correct and follows known patterns.

    • Name: Konstantina Harellis 
      Supervisor:       Dr Dominic Glover

      As part of the iGEM 2021 UNSW PROTECC Coral team, we investigated two systems that could be used to improve the thermotolerance of the algal species Symbiodinium goreaui. Elevated ocean temperatures due to global warming result in the production of reactive oxygen species (ROS) in the algal species which get released and disrupt the coral-algae symbiotic relationship. The ROS result in the expulsion of the algae from the coral host, leading to the starvation of the host and subsequent coral bleaching. Our proposed glutathione system aims to neutralise ROS and hence prevent the expulsion of the algae. Additionally, the introduction of small heat shock proteins in the algae prevents protein aggregation and denaturation that might occur in higher temperatures. Therefore, introducing these two systems could hypothetically increase thermotolerance and prevent coral bleaching. This is what our research tested and what I will present in the TSP conference.

    • Name: Bethany Yee
      Supervisor:       Lawrence Lee

      Nature has been able to optimise biochemical reactions by bringing together, or colocalising, natural catalysts called enzymes. These structures are called multi-enzyme complexes (MECs). While there has been research into designing synthetic MECs that could be tailored for specific reactions there has been little work in using base-pairing complementarity between RNA as a scaffold and RNA-binding proteins. This would allow the structures to be modular, highly controlled and be able to self-assemble in vivo. Through Molecular Dynamic Simulation, Pymol and kinetic modelling we assessed the validity of RNA scaffolds and fine-tuned a MEC design based of the biochemical pathway of the cofactor f420. Further research will involve expressing the MEC in both in vitro and in vivo experiments in order to construct and characterise the function and synthesis of the multi-enzyme complex.

  • Posters

    • Student: Konstantina Harellis

      As part of the TSP Student Conference, I decided to create and present a poster about cellular reprogramming from literature review. It is a technique that can be potentially used in therapeutic medicine to treat patients who are incurable or suffer from severe side effects of current treatments. Cellular reprogramming can be divided into two categories: classic cellular reprogramming and transdifferentiation. Classic cellular reprogramming has already been demonstrated to generate functional red blood cells from human induced pluripotent stem cells. On the other hand, functional neural stem or progenitor cells can be produced from human fibroblasts bypassing the induced pluripotent stem cell state through the process of transdifferentiation. These two approaches have been the focus of my poster with the hope that a solution will be found in the immediate future for those currently incurable.

    • Student: Marko Beaocanin
      Supervisor:  Professor Rajib Rahman

      I had the opportunity to work with Professor Rajib Rahman on two primary aims: to develop an introductory understanding on the literature and theory of electron transfer in silicon spin-based quantum dots; and to perform numerical simulations on the Gadi supercomputer using the nemo3d simulator to verify this existing theory. My simulation process involved incrementally changing the vertically-applied magnetic and electric field parameters in the nemo3d simulator, and running 19 complete simulations in total. I produced results analogous to the Zeeman and Stark effects, which describe how the quantised energy levels of a quantum dot split apart in the presence of externally-applied magnetic and electric fields.  

    • Student: Catherine Cheng 
      Supervisor:  Dr Kim-Vy Tran 

      Cosmological simulations like the IllustrisTNG simulations have revolutionised the way we study galaxies, opening up many possibilities not previously available through observational data. This project focusses on exploring whether the IllustrisTNG simulations are able to corroborate findings from observational surveys - in particular whether or not we are able to detect galaxies with unusually extended gas regions such as Magpi179104. From our results it was determined that no objects within our stellar mass range had unusually large regions of gas between the stellar half mass radius and twice the stellar half mass radius for their given stellar size or the baryonic mass within their stellar disk. This indicates that we have not been able to yet detect the observed objects via simulation.

    Presentation Abstracts

    • Student: Jenny Wang,
      Research Group: UNSW NEWTS Lab 
      Supervisor: Dr. Ben Montet 

      TESS (Transiting Exoplanet Survey Satellite) has discovered over 2000 planetary candidates since its launch in 2018. However, since TESS only observes each sector of the sky for 27 days, most planetary candidates discovered so far have very short periods (less than 14 days). I have developed a pipeline that searches for single transit events among the existing TESS Objects of Interest (TOIs) in order to find longer-period companions to existing planetary candidates. I am currently running this pipeline on all known TOIs. 

    • Student: Michelle Ding 
      Supervisor: Associate Professor Dennis Stello 

      Astroseismology, the composite of studying oscillations and stars. Given the opportunity to use python to program a system that will differentiate between “good” and “bad” data, the task was an interesting challenge to take upon. Provided with data from the Kepler Telescope, the idea of the program is to eliminate “red” noise from the data and then determine whether peaks on the generated graph aligns with previous data. If the alignment is correct, then the data is “claimed” to be “reliable”. Researchers can therefore use the reliable data to determine stellar features such as structure and evolution.

    • Student: Pavitraa Hathi 
      Supervisor: Assistant Professor Sarah Martell  

      Globular clusters are collections of stars held together tightly by gravity. Studies have shown that all globular clusters (GCs) demonstrate anticorrelations in certain pairs of elemental abundances, however why these anticorrelations occur is still unknown. In my project I looked previous papers that have studied GCs in the Large Magellanic Cloud (LMC) that are approximately 2-8 Gyr (much younger than the heavily studied >10 Gyr GCs in the Milky Way). I compared the LMC data with data for GCs in the Milky Way to find the same anticorrelations in both sets of GCs. This means that the mechanism which causes anticorrelations in GCs operated more recently than previously thought, which could open up a new avenue for research into the formation of GCs.

    • Student: Nikki Huang 
      Research Group: Gatt Resilience Group, NeuRA 
      Supervisor: Dr. Justine Gatt  

      The absence of mental illness is not equivalent to mental health or wellbeing. It is therefore important to develop valid and reliable measures of wellbeing which can identify individuals at risk of poor coping and inform strategies to improve resilience. The COMPAS-W is a 26-item self-report measure of wellbeing developed by the Gatt Resilience Group with six constituent subcomponents: Composure, Own-worth, Mastery, Positivity, Achievement and Satisfaction. As the scale was developed using data from a cohort of 1669 healthy adult twins (18-61 years), researchers were also able to evaluate the relative contributions of genetic and environmental factors to wellbeing. It was found that genes play a moderate role in determining wellbeing (heritability h2 = 48%), although the Composure and Achievement subcomponents showed relatively higher sensitivity to unique environmental influences. COMPAS-W is a validated measure of wellbeing which can be used to quantify mental health and inform future strategies in health promotion and clinical treatment. 

    • Name: Felix Lempriere 
      Supervisor: Dr Laura McKemmish

      Computational Quantum Chemistry provides a bridge between experiment and theory in Chemistry allowing predictions and corroboration of properties for molecules and reactions of interest. The accuracy and usefulness of such models is limited by the method and choice of “basis set” used, which is in necessitated by the available computational time. In this project we benchmarked several commonly used moderate sized basis-sets against a large chemical database to determine which were the most cost-effective and accurate, to help guide computational chemists designing their calculations. 

    • Name: Rosanna Xu
      Supervisor:

      On the 14th of August 2019, researchers detected one of the most mysterious gravitational waves in history (called the ‘GW190814 event’). The gravitational wave corresponded to the collision between two astronomical bodies of 23 and 2.6 solar masses. The larger is easily classified as a black hole, but the smaller body falls into the ‘mass gap’ between neutron stars and black holes, meaning that it is either the heaviest neutron ever found, lightest black hole ever found, or an entirely new astronomical body altogether. In my research, I have used the knowledge that colliding black holes radiate more gravitational energy than neutron stars. I have calculated the constant of proportion between radiated energy and original kinetic energy for the collision between (a) black hole – black hole, (b) neutron star – neutron star collisions, and then used this information to calculate that constant for (c) black hole – neutron star collisions. Finally, I compared these constants with the GW190814 event and concluded that the GW190814 event is a collision between two black holes.