19683 research outputs found
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RACER: A Lightweight Distributed Consensus Algorithm for the IoT with Peer-Assisted Latency-Aware Traffic Optimisation
No full textInternet-of-Things (IoT) devices are interconnected objects embedded with sensors and software, enabling data collection and exchange. These devices encompass a wide range of applications, from household appliances to industrial systems, designed to enhance connectivity and automation. In distributed IoT networks, achieving reliable decision-making necessitates robust consensus mechanisms that allow devices to agree on a shared state of truth without reliance on central authorities. Such mechanisms are critical for ensuring system resilience under diverse operational conditions. Recent research has identified three common limitations in existing consensus mechanisms for IoT environments: dependence on synchronised networks and clocks, reliance on centralised coordinators, and suboptimal performance. To address these challenges, this paper introduces a novel consensus mechanism called Randomised Asynchronous Consensus with Efficient Real-time Sampling (RACER). The RACER framework eliminates the need for synchronised networks and clocks by implementing the Sequenced Probabilistic Double Echo (SPDE) algorithm, which operates asynchronously without timing assumptions. Furthermore, to mitigate the reliance on centralised coordinators, RACER leverages the SPDE gossip protocol, which inherently requires no leaders, combined with a lightweight transaction ordering mechanism optimised for IoT sensor networks. Rather than using a blockchain for transaction ordering, we opted for an eventually consistent transaction ordering mechanism to specifically deal with high churn, asynchronous networks and to allow devices to independently and deterministically order transactions. To enhance the throughput of IoT networks, this paper also proposes a complementary algorithm, Peer-assisted Latency-Aware Traffic Optimisation (PLATO), designed to maximise efficiency within RACER-based systems. The combination of RACER and PLATO is able to maintain a throughput of above 600 mb/s on a 100-node network, significantly outperforming the compared consensus mechanisms in terms of network node size and performance.</p
Developing New Methodologies for Studying Ovarian Physiology in Mice
No full textA thesis submitted in total fulfilment of the requirements for the degree of Master of Science to the School of Agriculture, Biomedicine and Environment, La Trobe University, Victoria, Australia.</p
The Role of PLAG1 in Brain Development
No full textSubmitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Agriculture, Biomedicine and Environment, La Trobe University, Victoria, Australia.</p
Key concepts and reporting recommendations for mapping reviews: A scoping review of 68 guidance and methodological studies
No full textAbstract: Mapping reviews (MRs) are crucial for identifying research gaps and enhancing evidence utilization. Despite their increasing use in health and social sciences, inconsistencies persist in both their conceptualization and reporting. This study aims to clarify the conceptual framework and gather reporting items from existing guidance and methodological studies. A comprehensive search was conducted across nine databases and 11 institutional websites, including documents up to January 2024. A total of 68 documents were included, addressing 24 MR terms and 55 definitions, with 39 documents discussing distinctions and overlaps among these terms. From the documents included, 28 reporting items were identified, covering all the steps of the process. Seven documents mentioned reporting on the title, four on the abstract, and 14 on the background. Ten methods-related items appeared in 56 documents, with the median number of documents supporting each item being 34 (interquartile range [IQR]: 27, 39). Four results-related items were mentioned in 18 documents (median: 14.5, IQR: 11.5, 16), and four discussion-related items appeared in 25 documents (median: 5.5, IQR: 3, 13). There was very little guidance about reporting conclusions, acknowledgments, author contributions, declarations of interest, and funding sources. This study proposes a draft 28-item reporting checklist for MRs and has identified terminologies and concepts used to describe MRs. These findings will first be used to inform a Delphi consensus process to develop reporting guidelines for MRs. Additionally, the checklist and definitions could be used to guide researchers in reporting high-quality MRs.</p
Collaborative autoethnography: The potential for health professional education research
No full textCollaborative autoethnography (CAE) is a qualitative methodology that enables new knowledge through a process of collective meaning making. Common in higher education, the paucity of CAE in health professional education scholarship indicates that its value remains underexplored in the field. This paper describes the experiences and processes underpinning one example of CAE applied in higher education and how this approach informed the use of CAE as part of a clinical education research project. We offer one means of conducting CAE, highlighting our own experiences as well as the potential for health professional education scholarship. In the context of a centrally sponsored curriculum redesign project that promoted online modes of teaching, we detail how CAE data can be generated through a mix of written reflections and structured collaborative conversations over a defined period of data collection. Data was analysed individually, collectively and iteratively and, ultimately, drew on theory. We experienced shifts in our relationships and selves as the university increased its online and blended modes for teaching and learning, impacting both professional and personal identities. We then describe how the CAE processes have been translated into the health professional education context. In conclusion, the rich collaborative conversations inherent in CAE offer more than just the exploration of research questions: they foster collegiality and professional relationships that resonate well beyond the study period. In this paper, we illustrate how CAE can be a robust method in educational research when it is undertaken systematically and over time, allowing for non-hierarchical conversations and collective analysis to form new knowledge.</p
Exploring the identification, outcomes and experiences of women with a disability accessing public maternity services in Australia
No full textA thesis submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the Judith Lumley Centre, School of Nursing and Midwifery, La Trobe University, Victoria, Australia.</p
Harmonising Theory: Integrating Singing With Grounded Theory Methods
No full textThe integration of singing and song with established grounded theory methods offers readers unique methodological insights. Readers will be guided through the process of including singing and song within grounded theory methods using a worked example that explores the facilitator factors in group singing. We detail innovative approaches to research design including data generation, analysis and dissemination of findings. Specific examples will illustrate how singing and song can be incorporated into interviews, participatory workshops, coding, memo writing, and for the enhancement of theoretical sensitivity. Additionally, we introduce novel concepts such as practice-informed research, song reaching, and song fragments, and explore their implications for developing a grounded theory of group singing. Finally, we offer recommendations for using singing and song in the teaching and application of grounded theory methods.</p
Innila Sunitha Mohan – Chemoaitotrophs
No full textStudent created video as part of Threshold Concepts in Biochemistry published by La Trobe eBureau. https://doi.org/10.26826/1017</p
Open-source convolutional neural network to classify distal radial fractures according to the AO/OTA classification on plain radiographs
No full textPurpose: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the performance of an open-source CNN algorithm to classify DRFs according to the AO/OTA classification system.Methods: Patients with postero-anterior, lateral and oblique radiographs were included. Radiographs were classified according to the AO/OTA-classification and were used to train a CNN algorithm. The algorithm was tested on an internal and external validation set (two other level 1 trauma centers), with the DRFs classified by three independent surgeons. Results: 659 radiographs were used to train the algorithm. Internal- and external validation sets contained 190 and 188 patients, respectively. Upon internal validation, the CNN had an accuracy of 62% and an area under receiving operating characteristic curve (AUC) of 0.63–0.93 (type 2R3A 0.84, type 2R3B 0.63, type 2R3C 0.75, and no DRF 0.93). On the external validation, the algorithm has an accuracy of 61% and an AUC of 0.56–0.88 (type 2R3A 0.82, type 2R3B 0.56, type 2R3C 0.75, and no DRF 0.88). Conclusion: The presented algorithm has demonstrated excellent accuracy in classifying type 2R3A DRFs and excluding DRFs. However, poor to moderate accuracy is observed in classifying 2R3B and 2R3C DRFs according to the AO/OTA system, similar to limited surgeons’ inter-observer agreement. These results show that despite previous excellence in fracture detection, CNN-algorithms struggle with classifying; potentially showing the inherent problems with these classification systems.</p
Metabolic traits are shaped by phylogenetic conservatism and environment, not just body size
No full textMetabolic rate dictates life’s tempo, yet how ecological and environmental factors integrate to shape metabolic traits remains contentious. Considering metabolic traits of 114 species of ants from seven subfamily clades along a 1,500 km climatic and soil phosphorus availability gradient in Australia, we tested four hypotheses relating to variation in metabolic rate due to niche conservatism, temperature, aridity, and ecological stoichiometry. We also tested the contested hygric hypothesis, which predicts that insect ventilation patterns can be modified to reduce water loss in arid environments. Mass-independent metabolic rate was phylogenetically conserved. The ant clade Myrmecia had metabolic rates 3 to 10× higher than other species, likely related to their large eye size, a correlate of cognitive complexity. Metabolic rate was higher in ants from warm, arid sites relative to those from wet, cool sites. A weak positive interaction between soil phosphorus and body mass indicated that, at sites with low soil phosphorus, smaller ants respired at higher rates than expected based on their mass—consistent with ecological stoichiometry theory. Larger ants, regardless of clade, were more likely to exhibit discontinuous gas exchange (DGC) with increasing aridity, likely reflecting a water conservation strategy. Phylogenetic conservatism of metabolic rate and a moderate influence of environment suggest that, in addition to biophysical geometric constraints, metabolic rate has evolved to match the energetic demands required of ecological strategies to address environmental stressors. For larger insect species confronting their metabolic limits, DGC may promote resilience in a world that is becoming hotter and more arid.</p