ORCID Profile
0000-0002-8071-9044
Current Organisation
University of Tasmania
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-10-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2017
Publisher: American Society for Clinical Investigation
Date: 22-12-2022
DOI: 10.1172/JCI.INSIGHT.156087
Abstract: Metastatic clear cell renal cell carcinomas (ccRCC) are resistant to DNA damaging chemotherapies, limiting therapeutic options for patients whose tumours are resistant to tyrosine kinase inhibitors and/or immune checkpoint therapies. Here we show that mouse and human ccRCC are frequently characterised by high levels of endogenous DNA damage and that cultured ccRCC cells exhibit intact cellular responses to chemotherapy-induced DNA damage. We identify that pharmacological inhibition of the DNA damage sensing kinase ATR with the orally administered, potent and selective drug M4344 (also called gartisertib) induces anti-proliferative effects in ccRCC cells due to replication stress and the accumulation of DNA damage in S phase. In some cells, DNA damage persists into subsequent G2/M and G1 phases, leading to the frequent accumulation of micronuclei. Daily single agent treatment with M4344 inhibited the growth of ccRCC xenograft tumours. M4344 synergises with chemotherapeutic drugs including cisplatin and carboplatin and the PARP inhibitor olaparib in mouse and human ccRCC cells. Weekly M4344 plus cisplatin treatment showed in vivo therapeutic synergy in ccRCC xenografts and was efficacious in an autochthonous mouse ccRCC model. These studies identify ATR inhibition as a potential novel therapeutic option for ccRCC.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2018
Publisher: SAGE Publications
Date: 06-2022
DOI: 10.1177/15501329221102371
Abstract: The advances and convergence in sensor technology, information and communication technology, and intelligent analytics have given rise to the Internet of Things or also known as the Internet of Everything or the Industrial Internet. The research and development works for the Internet of Things can be seen to have progressed in two main phases: (1) In the first phase, the earlier works for the Internet of Things focused on developing the building blocks and enabling technologies such as the sensors and RFID technologies, communications and wireless protocols, machine-to-machine interfaces, energy efficiency of nodes, and energy harvesting technologies, and (2) in the second phase, the latter and recent works focused on the addition of, and embedding value to application-specific Internet of Things using technologies for smart environments and applications such as intelligent analytics and machine learning, embedded vision and image processing, augmented reality, and autonomous systems. We associate the term of embedded intelligence and analytics with the data-driven future for application-specific Internet of Things. In this article, we give an introduction and review recent developments of embedded intelligence for the Internet of Things the various embedded intelligence computational frameworks such as edge, fog, and cloud for the application-specific Internet of Things and highlight the techniques, challenges, and opportunities for effective deployment of application-specific Internet of Things technology to address complex problems for various smart environments and applications.
Publisher: SAGE Publications
Date: 03-2022
DOI: 10.1177/15501477211062835
Abstract: The advances and convergence in sensor, information processing, and communication technologies have shaped the Internet of Things of today. The rapid increase of data and service requirements brings new challenges for Internet of Thing. Emerging technologies and intelligent techniques can play a compelling role in prompting the development of intelligent architectures and services in Internet of Things to form the artificial intelligence Internet of Things. In this article, we give an introduction and review recent developments of artificial intelligence Internet of Things, the various artificial intelligence Internet of Things computational frameworks and highlight the challenges and opportunities for effective deployment of artificial intelligence Internet of Things technology to address complex problems for various applications. This article surveys the recent developments and discusses the convergence of artificial intelligence and Internet of Things from four aspects: (1) architectures, techniques, and hardware platforms for artificial intelligence Internet of Things (2) sensors, devices, and energy approaches for artificial intelligence Internet of Things (3) communication and networking for artificial intelligence Internet of Things and (4) applications for artificial intelligence Internet of Things. The article also discusses the combination of smart sensors, edge computing, and software-defined networks as enabling technologies for the artificial intelligence Internet of Things.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: SAGE Publications
Date: 03-2022
DOI: 10.1177/15501477211067740
Abstract: Distributed sensor networks have emerged as part of the advancements in sensing and wireless technologies and currently support several applications, including continuous environmental monitoring, surveillance, tracking, and so on which are running in wireless sensor network environments, and large-scale wireless sensor network multimedia applications that require large amounts of data transmission to an access point. However, these applications are often h ered because sensor nodes are energy-constrained, low-powered, with limited operational lifetime and low processing and limited power-storage capabilities. Current research shows that sensors deployed for distributed sensor network applications are low-power and low-cost devices characterized with multifunctional abilities. This contributes to their quick battery drainage, if they are to operate for long time durations. Owing to the associated cost implications and mode of deployments of the sensor nodes, battery recharging/replacements have significant disadvantages. Energy harvesting and wireless power transfer have therefore become very critical for applications running for longer time durations. This survey focuses on presenting a comprehensive review of the current literature on several wireless power transfer and energy harvesting technologies and highlights their opportunities and challenges in distributed sensor networks. This review highlights updated studies which are specific to wireless power transfer and energy harvesting technologies, including their opportunities, potential applications, limitations and challenges, classifications and comparisons. The final section presents some practical considerations and real-time implementation of a radio frequency–based energy harvesting wireless power transfer technique using Powercast™ power harvesters, and performance analysis of the two radio frequency–based power harvesters is discussed. Experimental results show both short-range and long-range applications of the two radio frequency–based energy harvesters with high power transfer efficiency.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
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