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Cardigan Commons: Co-Design Toolkit and Workshop Materials
No full textCollected here is the dataset to support the toolkit for RMIT PlaceLab’s ‘Cardigan Commons’ Research Project.Materials here include:> Codesign Toolkit Zine Instructions> Blobs template> More than Human name tags> Prompts and Notes for facilitation> CoLab Run Order> Post evaluation survey> Co-Lab Data Analysis – Excel> Co-Lab Data Analysis- IllustratorThe related toolkit has been developed as a playful way of bringing different – often confronting – voices together to have their say on what they’d like to do in public spaces. The methodology includes co-design dynamics, prompts for facilitators and useful ways to systematise and analyse the data that is captured. Our ‘blob’ modules, a visual and playful way of organising ideas in space, helps envision without the design constraint co-design methodologies often face.</p
Living Together: Research Project Report
No full textLiving Together forms part of a wider doctoral research investigation by Rebecca Roke that explores the role and impact of shared resources in Melbourne’s collective housing. For RMIT PlaceLab, the research scope drew on the broader themes and findings of this PhD with a focus on case study housing within the neighbourhoods of Brunswick and Brunswick East. These inner northern suburbs of Melbourne are active sites of collective housing: earlier developments, such as The Commons1 by Nightingale Housing (2013), began to set precedents in Melbourne, and Australia, for how housing at density may be designed and procured differently to typical speculative, market-led models. The research should be read in the context of a measurable increase of collective housing in Melbourne’s middle-ring suburbs since 2010 (Giannini 2011). Instead of focusing on dwellings as purely speculative financial tools, collective models aim to offer alternative housing strategies that encourage durable social networks and sustainable living practices based on an attitude towards sharing (Jarvis 2011). A principal intention behind collective housing, also known in Australia as deliberative development (Alves 2020; Riley 2018; Sharam et al. 2015), is a greater reliance on shared resources. Its expression borrows from international precedents, such as Danish co-housing (Bofællesskaber), German Baugruppe, and Swiss models of cooperative housing. The approach to sharing encompasses three principal areas: land, social capital, and amenities. This study identifies the integral notion of sharing in collective housing as an ‘economy of shared resources’ and aims to understand how this occurs in projects – and to what lived effect. The approach borrows from a growing area of design knowledge, social value, which considers the relation between human life and form, as investigated by pioneers including Jan Gehl (Wagner 2017) and Flora Samuel (RIBA and Hay 2016; Samuel 2022; Serin et al. 2018). Sharing typically occurs at a range of scales and in different ways. For example, collective housing usually produces private homes that are smaller than average homes on a comparable sized land plot; incorporate areas given over to shared open or planted spaces; and include common facilities, such as multi?purpose shared rooms, shared laundries, or shared productive gardens. Many collective models also encourage active property management by residents that invites decision-making by consensus (Jarvis 2011). The overall effect aims to inspire connection between residents, and by extension, the creation of a sense of community – or neighbourliness – within a housing complex. In Australia, the rising popularity and occurrence of collective housing types is mostly seen by residents as a means to buy a home, with an emphasis on quality at a more achievable purchase or rental cost than a speculative counterpart. Equally, collective housing buyers share a distinctive focus on buying a home with above-average environmental performance and construction standards, a heightened sense of community interaction, and (most often for smaller scale developments) collaborative decision-making. Overall, the driving interest for those adopting a different approach to housing is, arguably, to collocate cost and lifestyle choice; balancing quality of life in the context of Australia’s rising housing unaffordability (Apps et al. 2021; Ferguson et al. 2016; Infrastructure Victoria 2023; Parkinson et al. 2019). This research project seeks to integrate observations and findings of the built and social environments, adopting three case studies in Merri-bek as the means to examine this: Davison Collaborative (2020), Nightingale Evergreen (2022) and Balfe Park Lane (2021). Shared resources are explored through relationships between the built environment – the integral design decisions that shape the physical provision of housing – and the residents’ lived experience. Together, the research considers how, and if, shared resources of collective housing impact on the everyday experiences of residents.</p
A Systematic Review of Reimagining Fashion and Textiles Sustainability with AI: A Circular Economy Approach
No full textArtificial intelligence (AI) is revolutionizing the fashion, textile, and clothing industries by enabling automated assessment of garment quality, condition, and recyclability, addressing key challenges in sustainability. This systematic review explores the applications of AI in evaluating clothing quality and condition within the framework of a circular economy, with a focus on supporting second-hand clothing resale, charitable donations by NGOs, and sustainable recycling practices. A total of 135 research resources were identified through searching academic databases including Google Scholar, Springer, ScienceDirect, IEEE, Taylor and Francis, and Sage journals. These publications were subsequently refined down to 49 based on selected inclusion criteria. The selection of these sources from diverse databases was undertaken to mitigate any potential bias in the selection process. By analyzing the effectiveness and challenges of related peer-reviewed articles, conference papers, and technical reports, this study highlights state-of-the-art methodologies such as convolutional neural networks (CNNs), hybrid models, and other machine vision systems. A critical aspect of this review is the examination and analysis of datasets used for model development, categorized and detailed in a comprehensive table to guide future research. Whilst the findings emphasize the potential of AI to enhance quality assurance in second-hand clothing markets, streamline textile sorting for donations and recycling, and reduce waste in the fashion industry, they also highlight gaps in the available datasets, often due to limited size and scope. The types of textiles captured were most commonly swatches of fabric, with 20 studies examining these, whereas whole garments were less frequently studied, with only 7 instances. This review concludes with insights into future research directions and the promising use of AI within fashion and textiles to facilitate a transition to a circular economy. This project was supported through RMIT University’s School of Fashion and Textiles internal seed funding (2024).</p
A novel dictionary attack on ECG authentication system using adversarial optimization and clustering
No full textElectrocardiogram (ECG)-based biometric authentication has become a promising method to improve security in wearable devices due to its inherent uniqueness and difficulty to replicate. However, no studies currently demonstrate that ECG authentication can resist modern attack techniques employed against biometric authentication. In this paper, we present a novel dictionary attack against ECG authentication systems, which poses a significant threat. In contrast to conventional targeted attacks, this approach utilizes random pairing to breach a vast number of users, without requiring specific information about their biometric data. Our approach leverages adversarial optimization and clustering to generate synthetic ECG waveforms capable of bypassing authentication mechanisms of various systems, revealing critical vulnerabilities in the current implementation of ECG-based biometrics. We comprehensively evaluate the effectiveness of this attack across different ECG authentication models, demonstrating that despite the intrinsic uniqueness of ECG signals, a substantial number of users are vulnerable. Our attack method can bypass the authentication system of an average of 20% of users even at the most stringent false acceptance rate of 1%. With up to five attack attempts allowed, our method can bypass up to 62% of users’ ECG authentication models.</p
Cellular and genetic changes during and after fluconazole exposure in Cryptococcus neoformans
No full textThe validity of genome replication is fundamental to fungal survival, and errors in this process can result in ploidy changes. These changes can have negative effects, such as developmental defects or reduced fitness, or positive effects such as fungal adaptation and resilience. In the fungal pathogen Cryptococcus neoformans, ploidy changes have been consistently observed in clinical populations, and isolates exposed to the antifungal drug fluconazole commonly exhibit chromosome 1 aneuploidy. Chromosomal and putative metabolic function changes due to drug exposure are not well studied and are important for understanding resistance. Objectives: This study examined the fluconazole influence on C. neoformans transient aneuploidy and identified any potential genetic pathways that may be implicated. Methods: The study investigated 30 genes predicted to have a role in transient aneuploidy, which are related to chromosome organisation, DNA damage checkpoints and stress signalling. Other factors including ploidy status (haploid, diploid, polyploid) and species were also investigated to observe commonalities for a universal drug treatment strategy. Results: Fluconazole treatment increased DNA content, cell size and chromosomal changes in the wildtype and mutants. When fluconazole was removed, permanent changes were observed and were highly variable in the wildtypes and the 30 mutants. Additionally, some mutants lacked chromosomal changes such as tel1∆, mrc1∆ and hog1∆, highlighting the potential involvement in the aneuploidy process. Conclusions: These findings highlight that fluconazole influences the entire genome rather than specific chromosomes, which increases the heterogeneity in permanent changes after fluconazole removal. This heterogeneity may result in long–term consequences, including drug resistance.</p
Visual Veracity in an AI Age: One Simple Approach to Image Provenance
No full textNo description supplied</p
Green supply chain management and SMEs sustainable performance in developing country: role of green knowledge sharing, green innovation and big data-driven supply chain
No full textThe objective of this study was to examine the impact of green supply chain management (GSCM) on sustainable performance (SP) and the mediating role of green knowledge sharing (GKS), green innovation (GI), and big data-driven supply chain (BDDSC) in SMEs of Pakistan as a developing country. Primary data was gathered through adopted questionnaires from SME employees. Four hundred sixty-nine cases were considered for data analysis after data clearing in SPSS version 25. Furthermore, the proposed hypotheses were tested with the help of SmartPLS version 3 through structural equation modeling SEM. Findings revealed all seven direct hypotheses, including GSCM on SP, GKS, GI, and BDDSC and GKS, GI, and BDDSC on SP in SMEs of Pakistan. Moreover, the partial mediation effect of GKS, GI, and BDDSC was also confirmed between GSCM and SP. This study contributes to the context of SMEs in developing countries and recommends findings for future policies and implications at the firm and government levels for better results. Policymakers, SME owners, and managers must support innovation culture, engage their stakeholders, and invest in new products, processes, and business models relevant to addressing environmental and sustainability concerns. Moreover, Pakistan’s government policymakers recognize SMEs’ power to effectively integrate GSCM knowledge sharing, green innovation, GSCM practices, and big data technology into supply chain management.</p
Thyroid Hormone Analogues: Promising Therapeutic Avenues to Improve Neurodevelopmental Outcomes of Intrauterine Growth Restriction
No full textIntrauterine growth restriction (IUGR) is a pathological restriction of fetal weight commonly caused by placental insufficiency.1 Currently, there are no in utero interventions to prevent or correct placental dysfunction, which can severely compromise brain development.2-9 Thyroid hormone (TH) is crucial for brain maturation, and decreased expression of monocarboxylate transporter 8 (MCT8), a specific TH transporter, has been reported in the brains of IUGR human fetuses10 and rodents (Azhan, A., unpublished thesis, 2019).
The thyromimetic 3,5-diiodothyropropanoic acid (DITPA) does not require MCT8 for cellular uptake,11 making it a promising therapeutic candidate. Our laboratory has previously shown that short-term DITPA administration to IUGR rats from postnatal day (P) 1 to P6 improves myelination without detrimental effects on body composition when assessed immediately after treatment at P7 (Azhan, A., unpublished thesis, 2019). However, when DITPA was administered for a prolonged period, from P1 to P13, at P14 myelination was improved in the IUGR offspring only in some of the brain regions assessed (Kondos-Devcic, D., unpublished thesis, 2021). In fact, this prolonged treatment duration showed negative effects in IUGR rats, including reduced overall myelination in the cerebral cortex, as well as in the corpus callosum (CC) and external capsule (EC). These data suggest that a shorter treatment duration might be safer and sufficient to protect the developing IUGR brain, leading to question whether the beneficial effects of DITPA are sustained in the long-term.
The present thesis first conducted a systematic review (Chapter 3) to assess the long-term neurobehavioural effects of IUGR in humans and animal models caused by placental insufficiency. More specifically, the translatability of neurodevelopmental outcomes reported in preclinical models of IUGR to the human condition was systematically assessed. Findings in animal models were consistent with human outcomes, showing that individuals born with IUGR are at higher risk of motor and cognitive problems during adolescence and young adulthood. IUGR may also correlate with anxiety, although further clinical studies are needed to reach firm conclusions. This systematic review therefore served as a starting point for the present thesis, confirming the hypothesis that preclinical models of IUGR, including the rat model of IUGR, are valuable tools for investigating the underlying neurodevelopmental deficits and testing novel therapies.
Chapters 4 and 5 examined whether DITPA reduced long-term adverse neurostructural and functional outcomes following IUGR using a rat model induced by bilateral uterine vessel ligation (BUVL), a well-established technique to mimic the effects of placental insufficiency.12,13 In chapter 4, the optimal age for DITPA treatment was initially studied using immunohistochemical analysis (Chapter 4). The results confirmed decreased MCT8+ cell density in the CC, EC, and primary motor cortex (M1) in the P7 IUGR rat brain, which resolved only in the M1 by P10 and P14. Combined with the positive outcomes of DITPA treatment in the previous short-term administration study (P1-P6; Azhan, A., unpublished thesis, 2019) and the negative effects following a longer DITPA treatment duration (P1-P13; Kondos-Devcic, D., unpublished thesis, 2021), a 7-day administration regime was chosen for the present study. DITPA (0.5 mg/100 g) or saline (equivalent volume) were therefore injected daily to newborn IUGR and control rats from P1 to P7.
Behavioural tests were performed on all rats between P28 and P33, equivalent to early adolescence in humans. At P34, tissues were collected for wellbeing assessments (results reported in Chapter 6), and brains were processed for immunohistochemical analyses of oligodendrocyte (OL) density and myelination in major white and grey matter regions. Chapter 4 assessed motor function and anxiety-like behaviours, as well as OL density and myelination in the CC, EC, and M1. Chapter 5 examined memory function as well as OL density and myelination in the hippocampal cornu Ammonis (CA) 1 and CA3 regions and the fimbria.
In Chapter 4, IUGR rats exhibited no motor impairments compared to controls, but anxietylike behaviours in IUGR offspring increased and were alleviated by DITPA treatment. Immunohistochemical analysis in IUGR compared to control rats showed reduced density of the entire population of OLs (oligodendrocyte transcription factor 2; Olig2), and a reduced density of mature OLs (adenomatous polyposis coli; APC) in the CC, EC, and M1, with increased myelination (assessed using myelin basic protein, MBP) in all three regions. DITPA treatment in IUGR rats increased Olig2+ cell density in all three regions, however only improved mature APC+ cell density in the CC and EC. Furthermore, DITPA normalised myelination in IUGR rats compared to saline treated rats in all three regions. In control rats, DITPA decreased mature APC+ cell density in the EC, suggesting possible adverse effects in healthy animals. Chapter 4 highlights the region-specific impacts of IUGR and the restorative potential of DITPA, while cautioning against its use in healthy neonates.
In Chapter 5, male IUGR rats exhibited long-term non-spatial memory impairments, which were resolved with DITPA treatment. Spatial memory was not affected by IUGR or treatment. In the female offsprings, no differences in memory function were found between any of the groups. Both male and female IUGR rats showed reduced Olig2+ and APC+ OL densities in the hippocampal CA1 and CA3 regions, and in the fimbria, all of which were corrected by DITPA. Myelination was increased in the fimbria of IUGR + Saline rats compared to Control + Saline counterparts, but trended towards normalisation in IUGR + DITPA animals, while myelination in the CA1 and CA3 regions remained unaffected in IUGR rats. These results suggest that early postnatal TH-based therapy can restore neurodevelopmental processes in male and female IUGR rats and improve cognitive function in IUGR males.
Chapter 6 examined the effects of early-life DITPA administration on growth and wellbeing in IUGR and control rats during early adolescence. IUGR + Saline animals had reduced body and organ (liver and kidney) weights, total brain and cerebral hemisphere weights, as well as body morphometry (head and hip circumference, crown-rump length) and body composition (DEXA; bone area, bone mineral density, bone mineral content, lean mass, fat mass) parameters. Furthermore, male IUGR + Saline rats had reduced circulating free thyroxine (FT4) concentrations, along with elevated liver alkaline phosphatase (ALP) levels compared to Control + Saline males. In IUGR + Saline females, alkaline transaminase (ALT) and ALP concentrations were increased compared to Control + Saline females, however all values remained within normal ranges. Free triiodothyronine (FT3) and thyroid stimulating hormone (TSH) serum levels were also within normal ranges, although IUGR rats had higher FT3 values than controls. DITPA treatment normalised cerebral hemisphere weights and FT4 concentrations in IUGR rats but had no effect on the other parameters. In control rats, DITPA reduced fat mass and FT4 levels, and increased ALP enzyme levels in males, though all remained within safe limits. Overall, DITPA had no adverse effects on postnatal growth, supporting it as a suitable therapy in the context of IUGR.
In summary, this thesis provides evidence that early postnatal short-term administration of DITPA has sustained benefits on behavioural outcomes, OL density, and myelination in early adolescent-equivalent IUGR rats. DITPA did not negatively impact postnatal growth and metabolic parameters in IUGR animals, though it led to some undesirable effects in control animals. This work suggests that DITPA has the potential to improve in the long-term neurodevelopmental outcomes of IUGR in rats without harmful off-target effects. However further preclinical research using a large animal model is necessary before considering it as a therapeutic option.</p
Modelling Pedestrian Level of Service at Mid-Blocks in Urban Areas
No full textWalking is a sustainable mode of transport, an activity almost everyone performs for varying travel distances in everyday life. A pedestrian-friendly environment promoting physical activity is important for a healthy city infrastructure. In major cities, such as Melbourne, walking is becoming uncomfortable and challenging because of the increasing population, with a simultaneous increase in public transport modes and a reduction in car-sharing options. The 2018 survey results of Travel and Activity in Victoria show that 55% of the people travelling in the city for work mainly depend on public transport, walking, or cycling. By 2036, it has been estimated that around 1.4 million people will be walking in Melbourne city. This has drawn attention to creating new measures to assess the comfort of pedestrians who use those facilities. Pedestrian level of service is found to provide the measure of satisfaction experienced by pedestrians while using facilities such as walkways, crossings, and transit areas. The Pedestrian level of service has been evaluated for locations such as walkways, crosswalks, and intersections by collecting information such as walkway factors, pedestrian and road traffic, and demographic features. Additionally, some studies in the past also collected data about the purpose of trips for path users to find the walkway level of service. However, it has been found that existing models do not evaluate the impact of trip purpose on the walkway comfort of users. The variables considered for finding the pedestrian level of service based on comfort also vary based on the research methodology and the research location. To address these issues, the current study has considered all possible variables, such as pedestrian crowd, footpath continuity, opposite direction flow of pedestrians, street characteristics, etc., that impact pedestrian comfort while walking on a footpath in central cities. A machine learning approach has been adopted to develop a model that can evaluate the pedestrian level of service. City planners and local government can use this approach to make changes, provide excellent walking conditions in urban areas, and promote walking as the mode of transport where vehicle movement must be minimised.
This study aims to contribute to the field of active transportation by enhancing the factors and methodology used to find the pedestrian level of service. Firstly, the research analyses and determines the factors that affect pedestrian comfort in midblock walkways during a pandemic under walking restrictions such as social distancing. A similar methodology is used to identify the factors that impact the pedestrian level of service based on comfort for various trip purposes such as education, work, and recreation. Secondly, a machine-learning (ML) model called Extreme Gradient Boosting (XGBoost) is developed using the factors influencing walkway performance and comfort during a pandemic. Thirdly, two ML models- Random Forest (RF) and Light Gradient Boosting Machine (Light GBM) are developed, and their pedestrian level of service predictive capability for various trip purposes is compared to find the model that gives higher accuracy that could be used for modelling pedestrian comfort. Light GBM, in this case, gives 5% to 10% more accuracy for the model prediction than the RF model.
Data collection is conducted in two rounds. The initial phase of data collection focuses on pedestrian feedback obtained during the pandemic, while the subsequent phase captures data collected after the easing of pandemic-related restrictions. This dataset analyses pedestrian behaviour concerning the three most common trip purposes anticipated in Melbourne Central Business District (CBD). The pedestrian sensors in Melbourne CBD have been installed at various places to monitor pedestrian movements and flow density at different times of day over a year since 2009. The flow rate data combined with subjective pedestrian feedback data provide a reliable dataset to develop a model that optimises the walkway performance according to the needs of pedestrians.
Machine learning models often outperform conventional hybrid models in the transportation sector due to their ability to automatically learn complex, nonlinear relationships from data without the need for manually defined rules or membership functions. This adaptability allows ML models to handle large, high-dimensional datasets and improve predictive accuracy as more data becomes available.
This research study shows that during the pandemic, the personal space pedestrians try to maintain is one of the significant variables that decide the PLOS of the walkways. The other significant variables that contribute to assessing the PLOS in the model are pedestrian density, flow rate, and the continuity of footpaths, which are interrupted by factors such as outdoor dining and street vendors. The accuracy of prediction using the XG Boost model is 66%, and the Area under the curve value is 0.82. The post-pandemic models were created for education, work, and recreation trips. The accuracy of prediction using the RF model is from 65 to 70%, and for the Light GBM model, it is from 70 to 80% for various trip purposes. The value of AUROC values ranges from 0.73 to 0.87. This research shows that pedestrians going for educational purposes mainly concentrate on walking speed, safety from vehicles and safe distance from other travellers. Those using the walkways for work prefer to walk on safe and clean footpath surfaces, maintain their walking speed to get on time, and avoid being disturbed by the noise of high-speed vehicles and detours. Recreational trip users mainly feel comfortable about the smaller number of vehicles on the road close to them and the few pedestrians around them and construction sites if it doesn’t bother them. Shapley Additive Explanations (SHAP) have been used to derive the meaning of the working of ML models for different trip purposes. The SHAP summary plot provides insights into the top influencing variables and the direction of the relationship between those variables and their overall comfort or the PLOS. SHAP plots reveal that for a PLOS B or a good-condition walkway, educational trip users consider buffers for safety and landscaping for comfortable walking. On the other hand, recreational trip users prefer buffers for safety and vehicle volume to be less on the road next to them for perceiving better comfort on walkways. Walkway users who travel to work mainly prefer the noise of high-speed traffic to be reduced for safety and the lesser pedestrian crowd around them for comfort.
This research benefits the field of active transportation by providing a feature selection technique that can help to identify the significant variables that influence the pedestrian level of service during specific social climates or underlying conditions that impact pedestrian comfort in the region. The machine learning models that are suggested by this study give insight into the pedestrian level of service modelling using the significant variables, which are qualitative and quantitative, that influence pedestrian comfort while using those walkways. Thus, the predictive models can be used to identify the present condition of city walkways.</p
Exploring the potential impacts of anthropogenic heating on urban climate during heatwaves
No full textThis study modeled the impact of anthropogenic heat (AH) on urban climates, focusing on Sydney during 2017’s heightened temperatures. The motivation behind this study stems from the increasing significance of understanding urban heat dynamics as cities globally grapple with regional climate change, necessitating targeted strategies for effective climate resilience cities. By investigating how varying levels of AH influence local urban climate conditions, this study addresses a critical gap in current urban climate study, particularly in the context of Sydney, an area that has not yet been extensively explored. Utilizing the weather research and forecasting (WRF) model coupled with building effect parameterization (BEP) and building energy model (BEM), i.e., the WRF/BEP + BEM model, four AH release scenarios were analyzed. Higher AH levels, especially at 14:00 LT, exhibited significant peaks: 266.5 W m−2 for sensible heat and 35.3 W m−2 for latent heat compared to the control scenario. This increase corresponded to a notable rise in ambient temperatures by 2.1 °C, with surface temperatures surging by 8.1 °C. Wind speeds notably increased by 4.6 m s−1 during higher AH release periods, affecting city airflow patterns. Moreover, elevated AH levels amplified the convective planetary boundary layer (PBL) height by 2013.7 m at 14:00 LT, potentially impacting pollutant dispersion and atmospheric quality. Notably, heightened AH profiles intensified sea breeze circulations, particularly impacting densely populated urban areas. These findings demonstrate a direct link between AH, exacerbated local urban warming, altered boundary layer dynamics, and intensified sea breeze circulations. This study emphasizes the urgent need to comprehend and manage AH for sustainable urban development and effective climate resilience strategies in Sydney and similar urban environments. By shedding light on these relationships, this study aims to contribute to the formulation of policies that mitigate urban overheating and enhance the livability of urban areas.</p