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Kalonji Grower Guide Factsheet
Get PDFThis kalonji grower guide factsheet comes from the research project, Great Northern Spices and includes information to support producers.
Research was conducted across Northern Australian sites of Central Queensland, North Queensland, Katherine/Douglas Daly region of the NT, and Kununurra/ Ord region of WA.
Grower guides have been produced for sesame, fennel and kalonji as part of this research project.
Grower guide factsheets include:
- Quick grower facts
- Production potential and markets
- Crop establishment
- Sowing and water management
- Crop rotation and nutrition
- Harvest management
- Pests and management
- Weeds and managemen
Highly Thermal Conductive and Electromagnetic Shielding Polymer Nanocomposites from Waste Masks
Get PDFOver 950 billion (about 3.8 million tons) masks have been consumed in the last four years around the world to protect human beings from COVID-19 and air pollution. However, very few of these used masks are being recycled, with the majority of them being landfilled or incinerated. To address this issue, we propose a repurposing upcycling strategy by converting these polypropylene (PP)-based waste masks to high-performance thermally conductive nanocomposites (PP@G, where G refers to graphene) with exceptional electromagnetic interference shielding property. The PP@G is fabricated by loading tannic acid onto PP fibers via electrostatic self-assembling, followed by mixing with graphene nanoplatelets (GNPs). Because this strategy enables the GNPs to form efficient thermal and electrical conduction pathways along the PP fiber surface, the PP@G shows a high thermal conductivity of 87 W m⁻1 K⁻1 and exhibits an electromagnetic interference shielding effectiveness of 88 dB (1100 dB cm−1), making it potentially applicable for heat dissipation and electromagnetic shielding in advanced electronic devices. Life cycle assessment and techno-economic assessment results show that our repurposing strategy has significant advantages over existing methods in reducing environmental impacts and economic benefits. This strategy offers a facile and promising approach to upcycling/repurposing of fibrous waste plastics
Rapid Reconnaissance: Seeking Immediate Results
Get PDFThis article aims to reorient evaluators to a methodology that has perhaps been overlooked in recent years but whose methods are likely to be used, at least in part. Rapid reconnaissance emerged in sociological and rural research in the 1960s as a fast data-gathering and process evaluation tool that relies on multidisciplinary teams and information sharing between evaluators and professionals. Situated within developmental evaluation, rapid reconnaissance is often seen as a primer or first data-gathering exercise to inform future research direction or focus. Three main tools used for conducting rapid reconnaissance are explored in this article: proxies, sondeo, and rapid assessment procedures. Proxies require multidisciplinary evaluators to have some experience in the area under investigation to know when data saturation has been reached. Sondeos help orient evaluators and researchers to the culture under investigation. Three major techniques make up rapid assessment procedures, but all rely on a holistic view in which communication is key. Recognizing that evaluators work in many settings, and not necessarily only in the settings where rapid reconnaissance first emerged, this article also explores rapid reconnaissance in the organizational and higher education sectors. Finally, the authors describe how they have used rapid reconnaissance as evaluators at the University of Southern Queensland in the context of course enhancement conversations
Can international human rights perspectives help Queenslanders to resolve harm from noxious odours caused by waste disposal?
No full textThis perspective addresses the question of whether noxious odours or pollution in the community that harm an individual’s health or cause environmental harm may also engage international human rights law. In other words, can bad smells amount to a violation of a person’s human rights in certain circumstances?
This submission also discusses international human rights protections and provisions of the Human Rights Act 2019 (Qld) to identify whether international human rights law is available to guide interpretations of human rights law in Queensland
Impact of CO2 and methane adsorption and emission on coalss mechanical properties and pillar stability: Implications for ECBM and CO2 sequestration
No full textThis study investigates the effects of carbon dioxide (CO2) and methane (CH4) adsorption and emission on the
mechanical Properties of coal and the stability of underground mines. Given the significance of the coal industry and its associated environmental and safety challenges, optimizing extraction methods and effective gas management is essential. In this research, the impact of CO2 and CH4 on the peak strength (PS), elastic modulus, and
axial strain of coal samples under various laboratory conditions was examined. The results indicated that CO2 gas
adsorption had more significant negative impacts on the engineering properties of coal, notably reducing its
strength. Key findings reveal that CO2 adsorption significantly degrades coal’s engineering properties more than CH4. Specifically, CO2 at 15 and 30 bar injection pressures reduced compressive strength by 57.80 % and 57.15
%, and Young’s modulus by 77.67 % and 22.03 %, respectively. In contrast, CH4 reduced compressive strength
by 27.9 % and 41.7 %, and Young’s modulus by 18.06 % and 19.91 % at the same pressures. This reduction is
influenced by factors such as gas pressure, coal type, cleat structure and orientation, moisture content, and other
relevant parameters. Overall, the stability of coal pillars exposed to CO2 decreases, which should be carefully
considered when designing enhanced coalbed methane recovery (ECBM) methods and CO2 storage projects in
coal seams. Furthermore, the study highlights that gas emission from both depleted and non-depleted coal layers
reduces coal strength, increasing the risk of gas explosions, spontaneous combustion, and pillar instability. These
findings emphasize the need for thorough assessments of gas effects on mine stability and underscore the
importance of further research in this area
'The customer is always right': why some uni teachers give higher grades than students deserve
Get PDFThe differential response in fascicle behaviors of the individual plantarflexors to the post-activation potentiation
No full textWe aimed to clarify whether post-activation potentiation (PAP) is associated with the amount of fascicle shortening of individual muscles during twitch and whether this relationship depends on muscle fiber composition in humans. Eighteen healthy young adults (four female) participated in this study. Single supramaximal electrical stimulations were applied to the tibial nerve to elicit plantarflexion twitch, involving the medial gastrocnemius (MG) with approximately 50 % Type I fibers and the synergist soleus (SOL) with more than 80 % Type I fibers. The stimuli were delivered before (Pre), immediately after (Post-0 min), 5 min after (Post-5 min), and 10 min after a 6-s maximal voluntary isometric plantarflexion contraction (MVC) and peak torque (PT) during twitch contraction were calculated. The instantaneous fascicle length of each muscle was measured using ultrasound B-mode images acquired at 125 fps during twitch contraction and the amount of fascicle shortening (?FL) was calculated. PT was greater after MVC than that at Pre (P < 0.05). The ?FL of both MG and SOL were greater at Post-0 min and Post-5 min than at Pre (P < 0.05). PT and ?FL at Post-0 min relative to values at Pre were positively correlated in the MG (r = 0.624, P = 0.006), but not in the SOL. These results suggest that the contribution to PAP of isometric plantarflexion is greater from the MG than that from the SOL, implying a dependence of PAP on muscle fiber composition. © 2025 Elsevier Lt
StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images
Get PDFBackground and Objective
Stroke ranks among the leading causes of disability and death worldwide. Timely detection can reduce its impact. Machine learning delivers powerful tools for image‑based diagnosis. This study introduces StrokeNeXt, a lightweight convolutional neural network (CNN) for computed tomography (CT) and magnetic resonance (MR) scans, and couples it with deep feature engineering (DFE) to improve accuracy and facilitate clinical deployment.
Materials and Methods
We assembled a multimodal dataset of CT and MR images, each labeled as stroke or control. StrokeNeXt employs a ConvNeXt‑inspired block and a squeeze‑and‑excitation (SE) unit across four stages: stem, StrokeNeXt block, downsampling, and output. In the DFE pipeline, StrokeNeXt extracts features from fixed‑size patches, iterative neighborhood component analysis (INCA) selects the top features, and a t algorithm-based k-nearest neighbors (tkNN) classifier has been utilized for classification.
Results
StrokeNeXt achieved 93.67% test accuracy on the assembled dataset. Integrating DFE raised accuracy to 97.06%. This combined approach outperformed StrokeNeXt alone and reduced classification time.
Conclusion
StrokeNeXt paired with DFE offers an effective solution for stroke detection on CT and MR images. Its high accuracy and fewer learnable parameters make it lightweight and it is suitable for integration into clinical workflows. This research lays a foundation for real‑time decision support in emergency and radiology settings
Health Care and Health Information Access by Parents With Young Children in Regional Queensland
Get PDFObjective
The effects of childhood health, education and experiences can have long-term impacts on adult health and wellbeing. Access to health services and information can be complex especially in regional and rural areas of Australia. This research aimed to: (1) investigate how and where parents living in regional and rural Australia with young children search for health information and (2) explore how parents decide what is appropriate health information to enable them to meet the health needs of their families.
Setting
Regional and rural areas of Southern Queensland.
Participants
Parents with a child under the age of 5 years.
Design
A convergent mixed methods design was utilised. Parents participated in an online survey and were invited to in-depth semi-structured telephone interviews about their health information search methods. Inductive content analysis was applied to the transcripts.
Results
The 11 interviewees searched for health information when their child was unwell, using the internet, family and friends and GPs and medical services. Websites were used for health information, whereas social media sites provided support and connection. The internet helped determine when to seek medical advice, and a preference was shown for Australian, hospital and government websites and websites recommended by GPs.
Conclusion
The results may inform the development of targeted hospital and government websites to ensure all parents have easy access to evidence-based children's health information. GPs may also play a role in discussing internet-sourced health information with parents
A systematic review of machine learning-based remote sensing data analysis for geological and mined materials characterisation
Get PDFThe mining industry is undergoing a significant transformation, driven by advancements in remote sensing technology that enable the collection of large-scale data on the geological and geotechnical properties of mined materials. As the volume and complexity of data generated by advanced imaging methods continue to increase, traditional analytical techniques struggle to effectively process and interpret this information. To explore current practices and the application of machine learning in interpreting complex imaging data for mine material characterisation, a review of 92 studies from 2004 to 2024 was conducted. This review focuses on key aspects of mining operations, including exploration, extraction, and waste management. It highlights the unique challenges inherent in the mining environment—particularly the heterogeneous nature of geological and mined material samples, which can result in spurious absorption features that complicate data analysis. In addition, it discusses the challenges posed by high-dimensional data resulting from sensor capabilities, as well as the cost and time constraints associated with existing algorithms. Ultimately, the review underscores both the opportunities and limitations of current machine learning approaches in analysing geological and mined materials, emphasising the need for ongoing research to overcome these challenges and fully utilise machine learning-based remote sensing in the mining sector