134125 research outputs found
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Recontextualising code of conduct policies: negotiating ethical dilemmas in VET pedagogic practices
No full textThis study examines how code of conduct (CoC) policiesFootnote1 function within Australia’s marketised vocational education and training sector, revealing fundamental contradictions in their implementation as instruments of neoliberal governance rather than for ethical guidance. While ostensibly designed to regulate professional behaviour across all employment categories (from teaching staff to administrative personnel, including casual and contract workers), these regulatory frameworks function primarily as mechanisms of institutional control and risk management. Drawing on Bernstein’s concepts of policy recontextualisation and pedagogic discourse, we investigate how CoC policies for teachers are implemented to create ‘ethical impossibility’: structural conditions where adherence to official ethical policies becomes antithetical to ethical practice. Through interpretative phenomenological analysis of semi-structured interviews with 19 teachers from public and private vocational education and training institutions across three Australian states, we examine how teachers navigate ethical dilemmas. Our analysis reveals how recontextualisation establishes strong symbolic boundaries between collective professional ethical discourse and situated educational practice, thus constraining teachers’ contextual ethical reasoning. Rather than guiding professional ethical decision-making, these policy instruments individualise collective ethical responsibilities, forcing teachers to develop ‘ethical resilience’: maintaining professional integrity under structural constraints. Findings reveal how competitive funding and performance-driven accountability create conditions where teachers must choose between institutional survival and ethical practices. We conclude that effective ethical practice requires reconceptualising CoC policies as collective social practices rather than as individualised regulatory mechanisms of regulation and control.Full Tex
Unravelling the molecular fingerprint of plastic accumulation on blue carbon sediment
No full textA disproportionately large accumulation of plastic waste has turned blue carbon ecosystems (mangrove forests, tidal marshes, and seagrass meadows) into hotspots of plastic pollution. Although our understanding of the effects of plastics on coastal ecosystems has advanced considerably, the underlying effects on blue carbon sediment biogeochemistry are yet to be assessed. Here, we examined the potential organic matter turnover and degradability of conventional plastics, i.e. polyethylene terephthalate (PET) and polypropylene (PP) and biodegradable plastic, i.e. polylactic acid (PLA) in a controlled microcosm experiment containing mangrove sediments. We measured dissolved organic carbon (DOC) leaching, changes in sediment dissolved organic matter (DOM), and the simultaneous greenhouse gas emissions caused by plastics. After 90 days of incubation, low molecular weight PP was visibly degraded on the surface, but high molecular weight PET and PLA were not. The degradation of PP and granular structure of PET led to higher DOC content and number of DOM molecules in sediment compared to that of PLA. Initially, PET contributed higher bio-labile compounds to the sediment, but after 90 days of incubation biologically recalcitrant compounds were more prominent. Despite contributing less DOC and DOM, sediment with PLA emitted higher CO2, suggesting that PLA may accelerate the degradation of native organic matter, whereas PP reduced the cumulative emission. In short, both conventional and biodegradable plastics affect sediment biogeochemistry by altering DOC content, DOM composition and turnover. This study provides new insights into the signature of different plastics in blue carbon sediment dynamics.Full Tex
Workplace demands, resources, and well-being among police staff working in forensic services
No full textForensic staff play a crucial role in law enforcement through providing specialist services to police agencies in criminal investigations. Given the unique work, including frequent exposure to potentially distressing material, administrative workloads, and other work-related pressures, forensic staff are at risk of increased occupational stress. The current study examined the demands and resources associated with stress-related outcomes among forensic staff. It further provides descriptions of the coping strategies used, perceptions of organizational support resources, and attitudes toward help-seeking and using sick leave. Participants were 114 sworn and non-sworn forensic staff working in an Australian law enforcement organization. The study used a mixed methods design with participants completing survey questions online. Quantitative data were analyzed using bivariate correlations and partial least squares regression analyses. Qualitative data were analyzed using thematic analysis. Results identified the key role of occupational and organizational stressors, and forensic-specific job-related demands, in predicting various stress-related outcomes. Supervisor support, peer support, and psychosocial safety climate also had a key role in predicting stress-related outcomes among forensic staff. Law enforcement organizations employing staff in forensic job roles should take a holistic approach to optimizing demands which not only focuses on trauma, but also on mitigating occupational and organizational stressors. Demands specific to the role of forensics also need to be considered. In an effort to offset job demands, police agencies should seek to uplift the capacity of key resources such as supervisors and peers and should focus on ensuring a positive psychosocial safety climate.No Full Tex
Economic evaluation of microvascular reconstruction of the jaw: A micro-costing analysis and identification of key cost-drivers
No full textPurpose: Efficient resource allocation in surgery requires thorough economic evaluation that reflects the true costs of a procedure, with micro-costing being a primary method. Existing economic studies on microvascular jaw reconstruction of the jaw often exclude or estimate key cost-drivers. The aim of this study was to estimate the direct financial costs and cost-drivers associated with surgical reconstruction of the jaw from the perspective of the healthcare provider. Methods: A retrospective micro-costing study from the perspective of the healthcare provider was performed on 100 patients who underwent mandibular or maxillary free flap reconstruction. Direct financial costs of activities (in USD) from admission to discharge were examined, and classified into operative and perioperative admission periods. Results: The mean cost for the entire admission was 9142.02, p = 0.044), ASA IV (10,445.81, p = 0.012), return to the operating room (+25,316.26, p = 0.014). Conclusion: Jaw reconstruction is associated with considerable direct financial costs to the healthcare provider with complications requiring return to the operating room and/or return to the intensive care unit the critical key cost-drivers. These insights will support future health technology assessments focused on jaw reconstruction to assist decision-makers in implementing or reimbursing these procedures.No Full Tex
Innovative carbon-based materials for efficient hydrogen storage: A review of solid, gaseous, and liquid systems
No full textHydrogen (H2) stands as a cornerstone of sustainable energy and an indispensable pathway toward achieving carbon neutrality. Yet, the advancement of the hydrogen economy is significantly impeded by challenges related to storage and transportation. Conventional storage strategies—primarily high-pressure gaseous storage—rely on expensive fiber-reinforced composite tanks that not only escalate costs but also suffer from low efficiency and notable safety concerns. This scenario underscores the critical need for hydrogen storage solutions that are safe, efficient, and economically viable. Carbon-based materials have emerged as a compelling alternative, offering robust hydrogen storage capabilities via both physical adsorption and chemical bonding. These materials promise enhanced safety and improved efficiency for hydrogen transport. This review comprehensively examines the state-of-the-art developments in hydrogen storage across three distinct categories of carbon-based materials: solid carbon materials, gaseous carbon dioxide (CO2) hydrogen carrier, and liquid organic hydrogen carriers. Moreover, it critically evaluates the reversibility of these storage mechanisms and explores their potential for commercial application, providing insight into their role in the future of the hydrogen economy. This refined exploration aims to guide future research at the intersection of material science and energy technology, fostering innovations that may eventually overcome the current barriers in hydrogen storage and utilization.No Full Tex
Comparison of modified Khorana scores for prediction of venous thromboembolism in cancer patients: A systematic review and network meta-analysis
No full textBackground: The Khorana score is a guideline-recommended tool for identifying cancer patients at high risk of venous thromboembolism (VTE), while recent evidence indicates that it fails to distinguish low- and high-risk patients accurately. Increasingly, modified Khorana scores are being proposed to improve VTE risk prediction, yet their predictive performance remains uncertain. Objectives: This study aimed to systematically evaluate and compare the predictive performance of the modified Khorana scores with the original Khorana score, thereby assisting clinicians in selecting the most appropriate tool for clinical practice. Design: Systematic review and network meta-analysis. Methods: Eight databases were last searched on February 1, 2025, to identify studies that developed or validated the modified Khorana scores. The Prediction Model Risk of Bias Assessment Tool was used to evaluate the risk of bias and applicability concerns of the included studies. Both pairwise and Bayesian network meta-analysis were employed using random effects model to synthesize available data on predictive performances and thoroughly compare the modified and original Khorana scores. Results: Twenty-eight studies were included, identifying 12 modified versions of the Khorana score. Among these, PROTECHT, CONKO, ONKOTEV, and Vienna CATS were the most extensively validated, with pooled C-indices of 0.59 (95 % confidence interval [CI] 0.56, 0.62), 0.57 (95 % CI 0.54, 0.60), 0.70 (95 % CI 0.56, 0.81), and 0.63 (95 % CI 0.13, 0.95), respectively. In pairwise meta-analysis, no modified Khorana scores were significantly superior to the original Khorana score, while leave-one-out sensitivity analyses showed significantly better performance for CONKO (mean difference [MD] = 0.02, 95 % CI 0.00, 0.04) compared with the original Khorana score. Bayesian network meta-analysis demonstrated that none of the comparisons (PROTECHT, CONKO, ONKOTEV, Vienna CATS, and the original Khorana score) was significantly different (P > 0.05). Calibration performance was rarely reported across the modified scores. The majority of included studies (96.4 %) were identified to have a high risk of bias. Conclusion: Many modified Khorana scores have been developed and validated in different settings and cancer populations. Modified Khorana scores showed limited discriminative ability and were not superior to the original Khorana score. Given the pervasive high risk of bias of included studies and the poor pooled discriminative ability of the modified Khorana scores, the Khorana score and its modifications did not currently meet clinically desirable standards of evidence quality and predictive accuracy. Further large-scale, high-quality validation studies are warranted to validate them comprehensively. Registration: The protocol for this study is registered with PROSPERO (registration number: CRD42024601258).No Full Tex
Greening the boardroom: How executives’ environmental backgrounds shape green R&D manipulation in Chinese private firms
No full textThis paper examines the influence of the presence and proportion of executives with environmental backgrounds on corporate green R&D manipulation using data from Chinese private firms between 2010 and 2022. The results show that a higher representation of environmentally experienced executives on the board significantly reduces green R&D manipulation by attracting green investors and mitigating managerial short-sightedness. The governance effect is particularly strong in private firms with higher executive pay stickiness, stronger internal controls, and lower levels of green R&D subsidies. However, the effect diminishes in state-owned enterprises, where policy mandates and institutional constraints restrict managerial discretion, and in regions with stricter environmental regulation or entrenched industrial structures. Overall, the findings highlight that executives’ environmental backgrounds play a vital role in promoting sustainable innovation and reducing opportunistic behavior, though their effectiveness depends on ownership structure, institutional environment, and regional context.Full Tex
Machine learning downscaling of GRACE satellite data for local-scale water storage assessment in South-East Queensland, Australia
Get PDFMonitoring changes in terrestrial water storage (TWS) at local scales remains challenging due to the coarse spatial resolution of Gravity Recovery and Climate Experiment (GRACE) data. Although machine learning (ML)-based downscaling techniques offer a pathway to improve resolution, their reliability in capturing localised hydrological variability requires further evaluation. The main aim of this study is to evaluate five ML models - Support Vector Machine (SVM), Random Forest (RF), Gaussian Process Regression (GPR), Generalised Additive Model (GAM), and Artificial Neural Network (ANN) - to downscale GRACE-derived TWS anomalies from 1.0°× 1.0° to 0.05°× 0.05° across South-East Queensland, Australia, for the 2002–2022 period. High-resolution predictors of precipitation, evapotranspiration, and runoff from the Australian Water Outlook platform were used as inputs into the ML models. The downscaled outputs were validated using in-situ observations from 43 precipitation gauges, 98 groundwater monitoring wells, and 42 surface water level stations distributed across the study region. Among all the models, GPR consistently achieved the best performance (MAE = 1.4 mm, RMSE = 2.5 mm), followed in performance by RF (MAE = 4.6 mm, RMSE = 7.2 mm), GAM (MAE = 5.1 mm, RMSE = 8.1 mm), ANN, and SVM, respectively. Correlation coefficients between in-situ groundwater levels (GWL) and downscaled outputs ranged from 0.77 to 0.79, while for surface water levels (SWL) they varied from 0.47 to 0.48, with RF, GPR and GAM providing the best fit for GWL estimates. This study provides an opportunity to enhance the use of GRACE in regional hydrological assessments where dense monitoring networks are absent or limited.Full Tex
Entrepreneurship Education for Nurses and Healthcare Professionals: A scoping review and future research agenda
Get PDFAim
To map and synthesise global evidence on entrepreneurship education for nurses and healthcare professionals.
Background
As healthcare systems face increasing complexity, entrepreneurial skills—including innovation, value creation and resourcefulness in addressing service gaps—are recognised as vital for transforming healthcare delivery. While entrepreneurship training has expanded in medical education, its integration into nursing and allied health education remains limited and under-researched.
Design
Scoping review guided by the Joanna Briggs Institute methodology and reported in accordance with PRISMA-ScR guidelines.
Methods
A systematic search of five databases (Embase, Scopus, Web of Science, CINAHL and Medline) identified 18 eligible studies. Data were thematically analysed and mapped using the Quintuple Aim framework alongside a consolidated set of ten entrepreneurial competencies derived from established entrepreneurship literature, enabling integrated analysis of program content and outcomes.
Results
Programs were predominantly concentrated in urban academic centres and primarily targeted physicians. Nursing-focused initiatives were fewer and demonstrated narrower competency coverage, with key gaps in risk management and financial literacy. Most programs employed experiential, team-based pedagogies. Evidence of impact was strongest for improving the work life of healthcare providers, while empirical evidence for patient outcomes, cost reduction and health equity remained limited.
Conclusions
Entrepreneurship education shows promise for strengthening the leadership, innovation and system-change capacity of nurses and healthcare professionals. However, current offerings are fragmented and physician centric. This review highlights the need for more robust, nursing-specific entrepreneurship education grounded in comprehensive competency frameworks and evaluated through rigorous, longitudinal approaches, providing a foundation for curriculum development, faculty capacity-building and future research.Full Tex
Dual-label noise filtering for weakly supervised person search
No full textWeakly supervised person search aims to train an effective network for joint person detection and re-identification (re-id) without identity labels. Existing works perform self-training which alternates between unsupervised clustering for generating pseudo labels and supervised representation learning with the labels, neglecting the underlying misguidance induced by the label noise. In this work, we propose to suppress training samples with noisy labels and reduce unreliable pseudo labels to tackle this problem. Specifically, we present Dual-label Noise Filtering Network (DNFNet), the first noise-resistant weakly supervised person search network. Hybrid feature similarity and global feature similarity are calculated to perform parallel clustering and produce dual pseudo labels for each person. By estimating the confidence of training samples through dual-label consistency, we filter out persons with low confidence to resist noisy labels. A Context-aided Hierarchical Clustering (CHC) algorithm is proposed for generating reliable pseudo identities. CHC fully exploits the contextual prior knowledge and hierarchical relationship between data clusters to refine the generated labels during clustering. Experimental results demonstrate that DNFNet significantly outperforms previous works on PRW and CUHK-SYSU person search datasets. The code will be available on the project website: https://github.com/JackFlying/DNFNet_release/No Full Tex