Physical Sciences and Mathematics Commons^™

Analysis Of The Outer Retinal Bands In Abca4 And Prph2-Associated Retinopathy Using Oct, Rachael C. Heath Jeffery, Johnny Lo, Jennifer A. Thompson, Tina M. Lamey, Terri L. Mclaren, John N. De Roach, Lauren N. Ayton, Andrea L. Vincent, Abhishek Sharma, Fred K. Chen

Research outputs 2022 to 2026

Purpose: To evaluate the outer retinal bands using OCT in ABCA4- and PRPH2-associated retinopathy and develop a novel imaging biomarker to differentiate between these 2 genotypes. Design: Multicenter case-control study. Participants: Patients with a clinical and genetic diagnosis of ABCA4- or PRPH2-associated retinopathy and an age-matched control group. Methods: Macular OCT was used to measure the thickness of the outer retinal bands 2 and 4 by 2 independent examiners at 4 retinal loci. Main Outcome Measures: Outcome measures included the thicknesses of band 2, band 4, and the band 2/band 4 ratio. Linear mixed modeling was used to make comparisons …

Examination Of Traditional Botnet Detection On Iot-Based Bots, Ashley Woodiss-Field, Michael N. Johnstone, Paul Haskell-Dowland

Research outputs 2022 to 2026

A botnet is a collection of Internet-connected computers that have been suborned and are controlled externally for malicious purposes. Concomitant with the growth of the Internet of Things (IoT), botnets have been expanding to use IoT devices as their attack vectors. IoT devices utilise specific protocols and network topologies distinct from conventional computers that may render detection techniques ineffective on compromised IoT devices. This paper describes experiments involving the acquisition of several traditional botnet detection techniques, BotMiner, BotProbe, and BotHunter, to evaluate their capabilities when applied to IoT-based botnets. Multiple simulation environments, using internally developed network traffic generation software, were …

Scene Graph Generation: A Comprehensive Survey, Hongsheng Li, Guangming Zhu, Liang Zhang, Youliang Jiang, Yixuan Dang, Haoran Hou, Peiyi Shen, Xia Zhao, Syed A. A. Shah, Mohammed Bennamoun

Research outputs 2022 to 2026

Deep learning techniques have led to remarkable breakthroughs in the field of object detection and have spawned a lot of scene-understanding tasks in recent years. Scene graph has been the focus of research because of its powerful semantic representation and applications to scene understanding. Scene Graph Generation (SGG) refers to the task of automatically mapping an image or a video into a semantic structural scene graph, which requires the correct labeling of detected objects and their relationships. In this paper, a comprehensive survey of recent achievements is provided. This survey attempts to connect and systematize the existing visual relationship detection …

Understanding The Impact Of Environmental Impact Assessment Research On Policy And Practice, Angus Morrison-Saunders, Annette Nykiel, Nicole Atkins

Research outputs 2022 to 2026

There is an enormous and ever-growing body of environmental impact assessment (EIA) research, much of which is grounded in practice or seeks to advance it. In this paper we show how the impact of EIA research on policy and practice might be conceptualised and how to set about evidencing it. A framework is developed through literature review to account for impact in four areas pertaining to instrumental impact, conceptual impact, capacity building and knowledge brokerage and co-production. Methods for implementing the framework include citations within policy documents along with content analysis to determine influence and interviews or surveys with policy …

A Technical Perspective On Integrating Artificial Intelligence To Solid-State Welding, Sambath Yaknesh, Natarajan Rajamurugu, Prakash K. Babu, Saravanakumar Subramaniyan, Sher A. Khan, C. Ahamed Saleel, Mohammad Nur-E-Alam, Manzoore E. M. Soudagar

Research outputs 2022 to 2026

The implementation of artificial intelligence (AI) techniques in industrial applications, especially solid-state welding (SSW), has transformed modeling, optimization, forecasting, and controlling sophisticated systems. SSW is a better method for joining due to the least melting of material thus maintaining Nugget region integrity. This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes …

Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Multimodal Human Action Recognition (MHAR) is an important research topic in computer vision and event recognition fields. In this work, we address the problem of MHAR by developing a novel audio-image and video fusion-based deep learning framework that we call Multimodal Audio-Image and Video Action Recognizer (MAiVAR). We extract temporal information using image representations of audio signals and spatial information from video modality with the help of Convolutional Neutral Networks (CNN)-based feature extractors and fuse these features to recognize respective action classes. We apply a high-level weights assignment algorithm for improving audio-visual interaction and convergence. This proposed fusion-based framework utilizes …

Mhair: A Dataset Of Audio-Image Representations For Multimodal Human Actions, Muhammad Bilal Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Audio-image representations for a multimodal human action (MHAiR) dataset contains six different image representations of the audio signals that capture the temporal dynamics of the actions in a very compact and informative way. The dataset was extracted from the audio recordings which were captured from an existing video dataset, i.e., UCF101. Each data sample captured a duration of approximately 10 s long, and the overall dataset was split into 4893 training samples and 1944 testing samples. The resulting feature sequences were then converted into images, which can be used for human action recognition and other related tasks. These images can …

Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer

Research outputs 2022 to 2026

Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …

The Impact Of Environmental Policy On Renewable Energy Innovation: A Systematic Literature Review And Research Directions, Hiva Rastegar, Gabriel Eweje, Aymen Sajjad

Research outputs 2022 to 2026

Renewable energy innovations are imperative to tackle the climate change crisis. However, there is a gap in the literature regarding the effectiveness of environmental policies in promoting renewable energy innovations. To bridge this gap, we have adopted a systematic literature review process covering the period from 2005 to 2023. We identified and analysed 29 articles in our final sample. Further, we employ two levels of analysis (individual-policy and policy-mix levels) for analysing the extant research. Our findings show that fiscal incentives and emissions trading policies such as the European Union (EU) Emissions Trading System (ETS) consistently promote renewable energy innovations. …

Unleashing The Power Of Internet Of Things And Blockchain: A Comprehensive Analysis And Future Directions, Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Sandeep Jagtap, Mohammad Iranmanesh, Salem Alghamdi, Yaser Alhasawi, Yasanur Kayikci

Research outputs 2022 to 2026

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics …

Analysis Of Element Yield, Bacterial Community Structure And The Impact Of Carbon Sources For Bioleaching Rare Earth Elements From High Grade Monazite, Melissa K. Corbett, April Gifford, Nick Fimognari, Elizabeth L. J. Watkin

Research outputs 2022 to 2026

Rare earth element (REE) recovery from waste streams, mine tailings or recyclable components using bioleaching is gaining traction due to the shortage and security of REE supply as well as the environmental problems that occur from processing and refining. Four heterotrophic microbial species with known phosphate solubilizing capabilities were evaluated for their ability to leach REE from a high-grade monazite when provided with either galactose, fructose or maltose. Supplying fructose resulted in the greatest amount of REE leached from the ore due to the largest amount of organic acid produced. Gluconic acid was the dominant organic acid identified produced by …

Development Of A Regional Climate Change Model For Aedes Vigilax And Aedes Camptorhynchus (Diptera: Culicidae) In Perth, Western Australia, Kerry Staples, Peter J. Neville, Steven Richardson, Jacques Oosthuizen

Research outputs 2022 to 2026

Mosquito-borne disease is a significant public health issue and within Australia Ross River virus (RRV) is the most reported. This study combines a mechanistic model of mosquito development for two mosquito vectors; Aedes vigilax and Aedes camptorhynchus, with climate projections from three climate models for two Representative Concentration Pathways (RCPs), to examine the possible effects of climate change and sea-level rise on a temperate tidal saltmarsh habitat in Perth, Western Australia. The projections were run under no accretion and accretion scenarios using a known mosquito habitat as a case study. This improves our understanding of the possible implications of sea-level …

Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia

Research outputs 2022 to 2026

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …

Performance Evaluation Of A Dual-Chamber Plant Microbial Fuel Cell Developed For Electricity Generation And Wastewater Treatment, Mahmood Golzarian, M. Ghiasvand, S. Shokri, M. Bahreini, Fatemeh Kazemi

Research outputs 2022 to 2026

Plant microbial fuel cells (PMFC) have attracted great scholarly attention as a renewable energy source. These cells have three main components: anode, cathode chambers, and a proton exchange membrane. In this study, a dual-chamber plant microbial fuel cell system was designed using Cyperus papyrus and Shewanella oneidensis. The effects of various factors, including the size of the electrodes, the distance between the electrodes, and the inoculation volume of Shewanella oneidensis, on the ability of electricity generation, were scrutinized. The results indicated that increasing the size area of the electrodes from 2 × 2 to 4 × 4 and 6 × …

Malware Detection With Artificial Intelligence: A Systematic Literature Review, Matthew G. Gaber, Mohiuddin Ahmed, Helge Janicke

Research outputs 2022 to 2026

In this survey, we review the key developments in the field of malware detection using AI and analyze core challenges. We systematically survey state-of-the-art methods across five critical aspects of building an accurate and robust AI-powered malware-detection model: malware sophistication, analysis techniques, malware repositories, feature selection, and machine learning vs. deep learning. The effectiveness of an AI model is dependent on the quality of the features it is trained with. In turn, the quality and authenticity of these features is dependent on the quality of the dataset and the suitability of the analysis tool. Static analysis is fast but is …

Pdf Malware Detection: Toward Machine Learning Modeling With Explainability Analysis, G. M.Sakhawat Hossain, Kaushik Deb, Helge Janicke, Iqbal H. Sarker

Research outputs 2022 to 2026

The Portable Document Format (PDF) is one of the most widely used file types, thus fraudsters insert harmful code into victims' PDF documents to compromise their equipment. Conventional solutions and identification techniques are often insufficient and may only partially prevent PDF malware because of their versatile character and excessive dependence on a certain typical feature set. The primary goal of this work is to detect PDF malware efficiently in order to alleviate the current difficulties. To accomplish the goal, we first develop a comprehensive dataset of 15958 PDF samples taking into account the non-malevolent, malicious, and evasive behaviors of the …

Unifying Context With Labeled Property Graph: A Pipeline-Based System For Comprehensive Text Representation In Nlp, Ali Hur, Naeem Janjua, Mohiuddin Ahmed

Research outputs 2022 to 2026

Extracting valuable insights from vast amounts of unstructured digital text presents significant challenges across diverse domains. This research addresses this challenge by proposing a novel pipeline-based system that generates domain-agnostic and task-agnostic text representations. The proposed approach leverages labeled property graphs (LPG) to encode contextual information, facilitating the integration of diverse linguistic elements into a unified representation. The proposed system enables efficient graph-based querying and manipulation by addressing the crucial aspect of comprehensive context modeling and fine-grained semantics. The effectiveness of the proposed system is demonstrated through the implementation of NLP components that operate on LPG-based representations. Additionally, the proposed …

Trends In Monitoring Of Australia’S Threatened Birds (1990–2020): Much Improved But Still Inadequate, Simon J. Verdon, Robert A. Davis, Ayesha Tulloch, Sarah M. Legge, David M. Watson, John C. Z. Woinarski, G. Barry Baker, Joris Driessen, Hayley M. Geyle, Hugh Possingham, Stephen T. Garnett

Research outputs 2022 to 2026

Monitoring is vital to conservation, enabling conservation scientists to detect population declines, identify threats and measure the effectiveness of interventions. However, not all threatened taxa are monitored, monitoring quality is variable, and the various components of monitoring are likely to differ in their rates of improvement over time. We assessed the presence of monitoring and monitoring quality, using a range of metrics, for all Australia’s threatened bird taxa from 1990 to 2020 (four assessments spanning 30 years). We used our assessments to understand decadal trends in the number of taxa monitored; monitoring quality; and the groups that conduct monitoring. The …

Opportunities And Challenges Posed By Disruptive And Converging Information Technologies For Australia's Future Defence Capabilities: A Horizon Scan, Pi-Shen Seet, Anton Klarin, Janice Jones, Mike Johnstone, Helen Cripps, Jalleh Sharafizad, Violetta Wilk, David Suter, Tony Marceddo

Research outputs 2022 to 2026

Introduction: The research project's objective was to conduct a comprehensive horizon scan of Network Centric Warfare (NCW) technologies—specifically, Cyber, IoT/IoBT, AI, and Autonomous Systems. Recognised as pivotal force multipliers, these technologies are critical to reshaping the mission, design, structure, and operations of the Australian Defence Force (ADF), aligning with the Department of Defence (Defence)’s offset strategies and ensuring technological advantage, especially in the Indo-Pacific's competitive landscape.

Research process: Employing a two-pronged research approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding …

Consequences Of Group-Based Misperceptions Of Climate Concern For Efficacy And Action, Zoe Leviston, Tanvi Nangrani, Samantha K. Stanley, Iain Walker

Research outputs 2022 to 2026

People tend to underestimate others’ environmental values, including when judging the values of minority-status groups. Using a large national sample (N = 5110), we test whether these misperceptions extend to concern about climate change in Australia, and differ depending on immigrant status, ethnicity, and where one is located (i.e., in or outside capital cities). We also examine the consequences of misperceptions for self-efficacy and pro-environmental behaviour. We find personal climate concern is high, but perceptions of others’ concern is lower. Immigrants and Australian-born participants have similarly high concern, but both groups underestimate how concerned immigrants are. Southern-Central-Asian identifiers are the …

Microbes Of Biotechnological Importance In Acidic Saline Lakes In The Yilgarn Craton, Western Australia, Katelyn Boase, Talitha Santini, Elizabeth Watkin

Research outputs 2022 to 2026

Acidic salt lakes are environments that harbor an array of biologically challenging conditions. Through 16S rRNA, 18S rRNA, and ITS amplicon sequencing of eight such lakes across the Yilgarn Craton of Western Australia, we aim to understand the microbial ecology of these lakes with a focus on iron- and sulfur-oxidizing and reducing microorganisms that have theoretical application in biomining industries. In spite of the biological challenges to life in these lakes, the microbial communities were highly diverse. Redundancy analysis of soil samples revealed sulfur, ammonium, organic carbon, and potassium were significant diversities of the microbial community composition. The most abundant …

A Systematic Review Of K-12 Cybersecurity Education Around The World, Ahmed Ibrahim, Marnie Mckee, Leslie F. Sikos, Nicola F. Johnson

Research outputs 2022 to 2026

This paper presents a systematic review of K-12 cybersecurity education literature from around the world. 24 academic papers dated from 2013-2023 were eligible for inclusion in the literature established within the research protocol. An additional 19 gray literature sources comprised the total. A range of recurring common topics deemed as aspects of cybersecurity behavior or practice were identified. A variety of cybersecurity competencies and skills are needed for K-12 students to apply their knowledge. As may be expected to be the case with interdisciplinary fields, studies are inherently unclear in the use of their terminology, and this is compounded in …

Attitudes And Perceptions Towards Privacy And Surveillance In Australia, Aleatha J. Shanley

Theses: Doctorates and Masters

Understanding attitudes towards privacy and surveillance technologies used to enhance security objectives is a complex, but crucial aspect for policy makers to consider. Historically, terrorism-related incidents justified the uptake of surveillance practices. More recently however, biosecurity concerns have motivated nation-states to adopt more intrusive surveillance measures. There is a growing body of literature that supports the public’s desire to maintain privacy despite fears of biological or physical threats.

This research set out to explore attitudes towards privacy and surveillance in an Australian context. Throughout the course of this endeavour, the COVID-19 pandemic emerged bringing with it a variety of track …

Region-Specific Drivers Cause Low Organic Carbon Stocks And Sequestration Rates In The Saltmarsh Soils Of Southern Scandinavia, Carmen Leiva-Dueñas, Anna E. L. Graversen, Gary T. Banta, Jeppe N. Hansen, Marie L. K. Schrøter, Pere Masqué, Marianne Holmer, Dorte Krause-Jensen

Research outputs 2022 to 2026

Saltmarshes are known for their ability to act as effective sinks of organic carbon (OC) and their protection and restoration could potentially slow down the pace of global warming. However, regional estimates of saltmarsh OC storage are often missing, including for the Nordic region. To address this knowledge gap, we assessed OC storage and accumulation rates in 17 saltmarshes distributed along the Danish coasts and investigated the main drivers of soil OC storage. Danish saltmarshes store a median of 10 kg OC m−2 (interquartile range, IQR: 13.5–7.6) in the top meter and sequester 31.5 g OC m−2 yr−1 (IQR: 41.6–15.7). …

Simulating Compatible Solute Biosynthesis Using A Metabolic Flux Model Of The Biomining Acidophile, Acidithiobacillus Ferrooxidans Atcc 23270, Himel N. Khaleque, Hadi Nazem-Bokaee, Yosephine Gumulya, Ross P. Carlson, Anna H. Kaksonen

Research outputs 2022 to 2026

Halotolerant, acidophilic, bioleaching microorganisms are crucial to biomining operations that utilize saline water. Compatible solutes play an important role in the adaptation of these microorganisms to saline environments. Acidithiobacillus ferrooxidans ATCC 23270, an iron- and sulfur-oxidizing acidophilic bacterium, synthesizes trehalose as its native compatible solute but is still sensitive to salinity. Recently, halotolerant bioleaching bacteria were found to use ectoine as their key compatible solute. Previously, bioleaching bacteria were recalcitrant to genetic manipulation; however, recent advancements in genetic tools and techniques allow successful genetic modification of A. ferrooxidans ATCC 23270. Therefore, this study aimed to test, in silico, the effect …

Developing A Novel Ontology For Cybersecurity In Internet Of Medical Things-Enabled Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Syed A. A. Shah

Research outputs 2022 to 2026

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. …

From Grain To Malt: Tracking Changes Of Ultra-Low-Gluten Barley Storage Proteins After Malting, Mahya Bahmani, Angéla Juhász, Utpal Bos, Mitchell G. Nye-Wood, Malcolm Blundell, Crispin A. Howitt, Michelle L. Colgrave

Research outputs 2022 to 2026

Barley (Hordeum vulgare L.) is a major cereal crop produced globally. Hordeins, the major storage proteins in barley, can trigger immune responses leading to celiac disease or symptoms associated with food allergy. Here, proteomics approaches were employed to investigate the proteome level changes of grain and malt from the malting barley cultivar, Sloop, and single-, double- and triple hordein-reduced lines. The triple hordein-reduced line is an ultra-low gluten barley cultivar, Kebari®. Using discovery proteomics, 2,688 and 3,034 proteins in the barley and malt samples were detected respectively. Through the application of targeted proteomics, a significant reduction in the quantity …

Confined Feni Alloy Nanoparticles In Carbon Nanotubes For Photothermal Oxidative Dehydrogenation Of Ethane By Carbon Dioxide, Jinqiang Zhang, Meng Li, Xiaojie Tan, Lei Shi, Kun Xie, Xiaoli Zhao, Shuaijun Wang, Shiyong Zhao, Huayang Zhang, Xiaoguang Duan, Haijun Chen, Yuezhao Zhu, Mingbo Wu, Hongqi Sun, Shaobin Wang

Research outputs 2022 to 2026

Oxidative dehydrogenation of ethane with CO2 (ODEC) is an attractive reaction for reduction of carbon footprints and ethene production. In this work, we present photothermal catalysis on confined bimetal catalysts for ODEC. Carbon nanotubes confined non-noble bimetal alloy (i.e., CoNi@CNTs and FeNi@CNTs) catalysts were prepared and FeNi@CNTs showed effective performance in photothermal catalytic ODEC to ethene. Experiments and simulations reveal that UV and visible lights (420 – 490 nm) are responsible for ODEC and non-oxidative dehydrogenation of ethane, respectively, to ethene. Additionally, ODEC to ethene is preferred to C-C cracking to methane on FeNi@CNTs in light ( > 490 nm)-induced thermocatalysis. …

Improved Image Recognition Via Synthetic Plants Using 3d Modelling With Stochastic Variations, Chris C. Napier, David M. Cook, Leisa Armstrong, Dean Diepeveen

Research outputs 2022 to 2026

This research extends previous plant modelling using L-systems by means of a novel arrangement comprising synthetic plants and a refined global wheat dataset in combination with a synthetic inference application. The study demonstrates an application with direct recognition of real plant stereotypes, and augmentation via a plant-wide stochastic growth variation structure. The study showed that the automatic annotation and counting of wheat heads using the Global Wheat dataset images provides a time and cost saving over traditional manual approaches and neural networks. This study introduces a novel synthetic inference application using a plant-wide stochastic variation system, resulting in improved structural …

Substantial Blue Carbon Sequestration In The World’S Largest Seagrass Meadow, Chuancheng Fu, Sofia Frappi, Michelle N. Havlik, Wells Howe, S. David Harris, Elisa Laiolo, Austin J. Gallagher, Pere Masqué, Carlos M. Duarte

Research outputs 2022 to 2026

Seagrass meadows are important sinks for organic carbon and provide co-benefits. However, data on the organic carbon stock in seagrass sediments are scarce for many regions, particularly The Bahamas, which accounts for up to 40.7% of the documented global seagrass area, limiting formulation of blue carbon strategies. Here, we sampled 10 seagrass meadows across an extensive island chain in The Bahamas. We estimate that Bahamas seagrass meadows store 0.42–0.59 Pg organic carbon in the top-meter sediments with an accumulation rate of 2.1–2.9 Tg annually, representing a substantial global blue carbon hotspot. Autochthonous organic carbon in sediments decreased from ~1980 onwards, …