13361 research outputs found
Sort by
Teaching within war in Ukraine: applying an ethic of care lens to extend our understanding of service-learning theory and praxis
Get PDFService-learning is an educational approach that has become part of the higher education landscape. Although research and scholarship in this area has flourished over the past thirty years, little is known about higher education teachers’ experiences when using service-learning within war. Utilizing interpretative phenomenological analysis (IPA), we explore this gap by interviewing university teachers living and working in Ukraine who incorporated service-learning into their courses within the first 1.5 years following the full-scale Russian invasion in February 2022. Using a double hermeneutic approach, we draw a set of practice themes from their lived experience reflections. To better understand the underlying relationships among the practice themes and their fit within a context of war, we examine them through an ethic of care lens. The results offer novel insights and extend our understanding of the intersections between service-learning and care in two ways: (1) identifying a set of practices drawn from the reflections of higher education teachers who used service-learning in their courses within an environment of war and (2) contextualizing the resultant service-learning practices within an ethic of care framework to extend our understanding of service-learning theory and praxis
Development of ROBUST-RCT: Risk Of Bias instrument for Use in SysTematic reviews-for Randomised Controlled Trials
No full textRecent innovations in evidence based medicine methods, in particular instruments assessing risk of bias in randomised trials, have focused on methodological rigour at the expense of simplicity and practicability. Such a focus could lead to challenges in application and loss of reliability of instruments. To deal with these shortcomings, the Risk Of Bias instrument for Use in SysTematic reviews-for Randomised Controlled Trials (ROBUST-RCT) was created—a rigorously developed, simply structured, and user friendly instrument for assessing risk of bias of randomised controlled trials included in systematic reviews. This paper describes the development of ROBUST-RCT and provides associated documents and a manual of instructions
Surf Tourism
No full textSurf tourism is a commercially significant and growing niche within the wider adventure tourism sector. One of the main factors contributing to the increasing interest in surf tourism is the democratization of the sport as more people and diverse communities take to the waves globally. This chapter explores surf tourism from a consumer’s perspective and then switches to an industry lens, considering some of the issues that inevitably come with growth. First, the changing business models and scalability issues in commercial surf tourism are explored; then second, we unpack the rise and prevalence of “soft” surf tourism. Third, the different ways in which public sector actors are now interested in surf tourism is discussed; examples that demonstrate benefits accruing from reputation building, destination branding, soft power, and international diplomacy benefits are explored. We then segue into the fourth and final topic which discusses the continued tensions between growth and sustainability and, equally, recent criticisms raised in how we should go about researching and understanding these tensions. A pragmatic way forward that recognizes the socioeconomic benefits that surfing contributes to a community and the need for robust policy frameworks that protect the environment within which surfing takes place is proposed.</p
Treatment Decision-Making for Anterior Cruciate Ligament Rupture from the Perspective of Physical Therapists in Australia: A Mixed Methods Study
Get PDFIMPORTANCE: In Australia, few people with acute anterior cruciate ligament (ACL) rupture are managed with rehabilitation alone despite clinical trials demonstrating similar outcomes to ACL reconstruction (ACLR). The reasons for the low uptake of rehabilitation alone for the treatment of acute ACL rupture in Australia are unclear.OBJECTIVES:The objectives of this study were to evaluate physical therapists' beliefs and the information they provide to patients about treatment options for ACL rupture, and to explore ACL rupture treatment decision-making from the perspective of physical therapists.DESIGN: The design was a mixed-methods convergent parallel design comprising an Australia-wide survey (n = 246) and semi-structured interviews (n = 10).PARTICIPANTS: Participants included physical therapists who manage people with ACL rupture in Australia.MAIN OUTCOMES: The survey contained 41 items that assessed demographics, treatment of ACL rupture, referral pathways, treatment beliefs, and the information provided to patients with ACL rupture.RESULTS:Physical therapists' beliefs about treatment options varied and did not always reflect the information they provided to patients. Although 60% agreed that ACLR and rehabilitation-alone result in similar outcomes on average, only 37% reported regularly informing patients about this. To return to pivoting/contact sport, 23% believed that ACLR was required and 79% informed patients that ACLR was the best treatment to do so.Physical therapists felt that rehabilitation-alone is underutilized as a treatment for ACL rupture. Physical therapists encountered barriers to offering and providing rehabilitation-alone for ACL rupture, reflected in 7 qualitative themes: preference for surgery reflecting societal beliefs; more weight given to surgeon's opinion; unbalanced information from surgeon; referral pathways; uncertain recovery timeline; beliefs about treatment suitability; and knowledge and experience.CONCLUSIONS: Physical therapists had mixed beliefs about treatment options and the information provided to patients was not always evidence based. Physical therapists felt that nonsurgical management was underutilized, and experienced barriers to offering and providing non-surgical management of ACL rupture in clinical practice.RELEVANCE: Informed decision-making can only occur if accurate, evidence-based information about ACL rupture treatment options is provided to patients. These findings may be used to guide professional development for physical therapists and inform strategies to improve evidence uptake by physical therapists
ESG reporting horizon: A way forward for managers and directors
No full textEnvironmental, Social, and Governance (ESG) reporting is a critical aspect of corporate strategy influencing investor confidence and stakeholder trust worldwide. As global markets move towards standardized ESG disclosure and assurance frameworks, Australia must navigate the evolving regulatory landscape while maintaining competitiveness. Our research benchmarks ASX 100 firms against three key international comparators: the Asia-Pacific region, major global economies, and leading mining jurisdictions. By evaluating ESG performance and disclosure practices across these regions, this study provides insights into Australia’s relative strengths and areas for improvement
Deep learning applications in investment portfolio management: a systematic literature review
No full textPurpose:Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.Design/methodology/approach:This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.Findings:The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.Originality/value:Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used
Non-Homogeneous Distribution of Inhibitory Inputs Among Motor Units in Response to Nociceptive Stimulation
No full textPain significantly influences movement, yet the neural mechanisms underlying the range of observed motor adaptations remain unclear. This study combined experimental data and in silico models to investigate the contribution of inhibitory and neuromodulatory inputs to motor unit behaviour in response to nociceptive stimulation during contractions at 30% of maximal torque. Specifically, we aimed to unravel the distribution pattern of inhibitory inputs to the motor unit pool. Seventeen participants performed isometric knee extension tasks under three conditions: Control, Pain (induced by injecting hypertonic saline into the infra-patellar fat pad), and Washout. We identified large samples of motor units in the vastus lateralis (up to 53/participant) from high-density electromyographic signals, leading to three key observations. First, while motor unit discharge rates significantly decreased during Pain, a substantial proportion of motor units (14.8-24.8%) did not show this decrease and, in some cases, even exhibited an increase. Second, using complementary approaches, we found that pain did not significantly affect neuromodulation, making it unlikely to be a major contributor to the observed changes in motor unit behaviour. Third, we observed a significant reduction in the proportion of common inputs to motor units during Pain. To explore potential neurophysiological mechanisms underlying these results, we simulated the behaviour of motor unit pools with varying distribution patterns of inhibitory inputs. Our simulations support the hypothesis that a non-homogeneous distribution of inhibitory inputs, not strictly organised according to motor unit size, is a key mechanism underlying the motor response to nociceptive stimulation during moderate contraction intensity
GBCHV an advanced deep learning anatomy aware model for accurate classification of gallbladder cancer utilizing ultrasound images
Get PDFThis study introduces a novel deep learning approach aimed at accurately classifying Gallbladder Cancer (GBC) into benign, malignant, and normal categories using ultrasound images from the challenging GBC USG (GBCU) dataset. The proposed methodology enhances image quality and specifies gallbladder wall boundaries by employing sophisticated image processing techniques like median filtering and contrast-limited adaptive histogram equalization. Unlike traditional convolutional neural networks, which struggle with complex spatial patterns, the proposed transformer-based model, GBC Horizontal-Vertical Transformer (GBCHV), incorporates a GBCHV-Trans block with self-attention mechanisms. In order to make the model anatomy-aware, the square-shaped input patches of the transformer are transformed into horizontal and vertical strips to obtain distinctive spatial relationships within gallbladder tissues. The novelty of this model lies in its anatomy-aware mechanism, which employs horizontal-vertical strip transformations to depict spatial relationships and complex anatomical features of the gallbladder more accurately. The proposed model achieved an overall diagnostic accuracy of 96.21% by performing an ablation study. A performance comparison between the proposed model and seven transfer learning models is further conducted, where the proposed model consistently outperformed the transfer learning models, showcasing its superior accuracy and robustness. Moreover, the decision-making process of the proposed model is further explained visually through the utilization of Gradient-weighted Class Activation Mapping (Grad-CAM). With the integration of advanced deep learning and image processing techniques, the GBCHV-Trans model offers a promising solution for precise and early-stage classification of GBC, surpassing conventional methods with superior accuracy and diagnostic efficacy.</p
Editorial March 2025
Get PDFWe are delighted to present the first edition of the Australian and New Zealand Continence Journal since transferring to CSIRO Publishing. It has been exciting to see such informative articles populating the journal’s new website, and we look forward to continued growth throughout 2025. While this change presents a new look and direction, we remain dedicated to providing a consistent service that meets the needs of our researchers and readers. Articles are now more visible and rapidly available online after acceptance, with our model remaining entirely Diamond Open Access, with no cost to authors or readers. Each article is linked to an individual DOI number to assist with referencing and tracking, and accepted submissions will be listed across an increasing number of online databases. The end result is that our journal now stands out even more amongst the crowd, and we are confident that it has become a very attractive outlet for the submission and publication of high-quality works from across the global continence research community
Critically appraised paper: In rural youth, the iAmHealthy paediatric weight management intervention stabilises body mass index z-scores and impacts health behaviours compared with newsletters with similar content [synopsis]
No full textSummary of: Davis A, Lancaster B, Fleming K, Swinburne Romine R, ForsethB, Nelson E-L, et al. Effectiveness of a paediatric weight management intervention for rural youth (iAmHealthy): Primary outcomes of a cluster randomised control trial. Pediatric Obesity. 2024;19:e13094