Leading an Australian school towards an ecosystem for learning and flourishing

Purpose: The aim of this study was to present a systems model of successful school leadership from a rural school case study, demonstrating how it connects to the weaving circle for systemic impact model. Doing so builds an awareness of how both complement each other to prompt thinking about schools as complex and adaptive systems that achieve broader school and student outcomes alongside students’ academic results. Design/methodology/approach: This study was a multiple-perspective mixed-method case study. Data were collected through interviews with the principal on three separate occasions, school leaders (n = 3), teachers (n = 4), students (n = 12), parents (n = 9), the school council president and a system leader. Interview data were supported by school observations, document analysis and a whole-staff teacher survey. The case study was part of the International Successful School Principalship Project (ISSPP). Findings: The authors found a symbiosis between the research of the ISSPP and the ecosystems for learning and flourishing approach, specifically through the weaving circle for systemic impact model. This suggests that future ISSPP research protocols could be modified to consider the weaving circle model and also provides a way for thinking about how the weaving circle model could be extended to better capture the complex world of leading schools successfully. Originality/value: This research contributes to the existing literature on successful school leadership by engaging with understandings of leading schools as complex and adaptive systems. © 2024, Emerald Publishing Limited

Trustworthiness of IoT images leveraging with other modal sensor's data

Image sensors deployed in the Internet of Things (IoT) generate vast volumes of digital images. These images may be subject to deliberate alteration, compromising their trustworthiness. Estimating the trustworthiness of this image data is crucial for many applications; however, this aspect has not been adequately explored in the existing literature. In this article, we propose a robust and real-time trust estimation framework for IoT image data, leveraging numeric data generated from other types of sensors deployed in the same Area of Interest (AoI). The theoretical model was developed using statistical approaches, and Shannon's entropy was employed to measure the uncertainty associated with sensor readings during a specific event. Later, we applied Dempster-Shafer theory (DST) of combination to fuse information collected from image as well as numeric data-generating sensors where both types of sensors were observing the same event in the same AoI concomitantly. To evaluate the proposed framework, we implemented an IoT testbed using LoRa sensor nodes, edge devices, an LoRaWAN gateway, the things network (TTN), and a data analytics server. The testbed was used to collect observation data of a fire event using image and temperature sensors in an indoor residential setup in different conditions. Consequently, eight data sets (four authentic and four hacked) were built, each containing both image and temperature data readings under various scenarios. The proposed trust framework accurately estimated the trust score of images (91% overall accuracy) across all the data sets and outperformed existing trust models. © 2014 IEEE

Invasive Acacia mangium Leaf Litter Modifies Soil Chemical properties of a Bornean tropical heath forest : a soil incubation study

This study investigated the effects of Acacia mangium Willd. leaf litter on soil chemical properties of a tropical heath forest in Borneo using a controlled soil incubation experiment. The litter of exotic A. mangium and selected native heath forest species (Buchanania arborescens Blume., Calophyllum inophyllum L., Dillenia suffruticosa Griff. and Ploiarium alternifolium Vahl.) were incubated with heath forest soils collected under natural conditions and nine different treatments of heath forest soils (soils without leaf litter, soils treated with single species leaf litter, and soils treated with native leaf litter with and without A. mangium leaf litter). We quantified mass litter loss (%), and soil concentration

Acute care nurses' partnership with patients to recognise and respond to changes in patients' clinical states : a qualitative study

Aim: To explore and describe acute care nurses' partnership with patients to recognise and respond to changes in patients' clinical states. Acute care nurses' decisions to partner with patients to recognise deterioration in clinical states and to respond by activating a rapid response system improves patient outcomes. Acutely unwell patients can also experience clinical changes that include improvement and deterioration that does not trigger rapid response system activation over the course of hospitalisation from illness and treatment. How acute care nurses partner with patients in response to improvement and deterioration not triggering a rapid response system is not well-understood. Design: An exploratory, descriptive study underpinned by Tanner's Clinical Judgement Model. Methods: Using purposive and quota sampling, 20 nurses with direct patient care responsibilities on one medical and one surgical ward in a large Australian hospital were recruited. Nonparticipant observations followed by semistructured interviews were conducted between January and May of 2021. Nurse–patient interactions were observed for 4 h, and verbally described and recorded. Semistructured interviews were recorded and explored nurses' reasoning behind decisions observed. Reflexive thematic analysis was used to analyse the data. Results: Three themes were identified from the data: nurses checking in for changes; nurses forming judgements; and nurses partnering with patients to respond. Acute care nurses promoted subjective assessment based on patients' safety risks. Patients' participation in response to changes was prioritised based on acute care nurses' judgement of safety. Conclusion: Patients receive significant safety benefits when acute care nurses partner with patients in response to their experience of improvement and deterioration during acute illness. Further research should evaluate the sensitivity of subjective cues in patient assessment. Implications for the Profession and Patient Care: Partnership with patients in assessment and management of improvement and deterioration improves the quality and safety of patient care. Assessment frameworks should equally prioritise the use of objective and subjective cues. Nursing education should promote the safety benefits of patient partnerships in responding to patient changes. Reporting Method: Equator checklist COREQ. Patient or Public Contribution: Data collected included description of patients' interactions with study participants. © 2024 The Author(s). Journal of Advanced Nursing published by John Wiley & Sons Ltd

Transforming women's health, empowerment, and gender equality with digital health : evidence-based policy and practice

We evaluated the effects of digital health technologies (DHTs) on women's health, empowerment, and gender equality, using the scoping review method. Following a search across five databases and grey literature, we analysed 80 studies published up to Aug 18, 2023. The thematic appraisal and quantitative analysis found that DHTs positively affect women's access to health-care services, self-care, and tailored self-monitoring enabling the acquisition of health-related interventions. Use of these technologies is beneficial across various medical fields, including gynaecology, endocrinology, and psychiatry. DHTs also improve women's empowerment and gender equality by facilitating skills acquisition, health education, and social interaction, while allowing cost-effective health services. Overall, DHTs contribute to better health outcomes for women and support the UN Sustainable Development Goals by improving access to health care and financial literacy. © 2025 World Health Organizatio

Intelligent decision framework for booster fan optimization in underground coal mines : hybrid spherical fuzzy-cloud model approach enhancing ventilation safety and operational efficiency

Optimizing mine fan operations in underground coal mines is important for ensuring proper ventilation, enhancing safety, and improving operational efficiency. A single main ventilation fan is insufficient to meet the ventilation demands of the entire mine. Therefore, it is necessary to consider the addition of booster fans to ensure effective ventilation. However, the selection of booster fans involves multiple influencing factors, and the complex interrelationships among fans remain unclear, making solution selection and risk assessment more challenging. To address this issue, this study proposes an optimization and risk analysis method for booster fan selection based on an improved analytic hierarchy process. This method leverages spherical fuzzy sets to handle uncertainty in the ventilation parameters and cloud models to facilitate probabilistic decision making. Through this model, the important relationships of the influencing factors for fan selection can be systematically determined, allowing for a rational assessment of the performance scores of candidate solutions. It provides a ranking of the alternatives based on their superiority, along with the risk indicators and optimization potentials of the selected solution. Ultimately, the reliability of the chosen model was verified through comparison and validation. This method not only enhances the scientific and rational basis for booster fan selection, reducing the complexity of the selection process, but also provides theoretical support for the optimization of coal mine ventilation systems. This study demonstrates the model’s effectiveness at improving ventilation safety and cost efficiency, making it a valuable tool for modern underground mining operations. © 2025 by the authors

Obtaining performance of friction stir welding on aluminum 7075 from rework viewpoints

In the process of research and development and to manufacture products with zero waste, industries are acquiring 3 R's (recycle, rework, regenerate), which help in reducing the time to re-manufacture the parts and adhere to the cost. In die casting, industry follows the rework and recycling methods, as Aluminium has non-expiry property and can be recycled multiple times. In the following study, cracked Aluminium components produced during pressure die casting are welded through Friction Stir Welding (FSW), and a comparative analysis of flatness of reworked components with respect to non-reworked components is conducted. The process capability and process capability index mathematical modeling methods have been used. This paper explains the benefits of FSW in automotive industries, where rework and regeneration costs are higher than reworking. Reworking components is permissible by the customer as long as it does not cause any negative effect on primary or secondary functions. In the era of competency, reworking with FSW is a new way to proceed in the industrial field. The present work summarizes the ability of FSW to restructure the grain order, which in turn gives us the opportunity to produce fine-quality components. © 2024 Author(s)

Peduncle detection of ripe strawberry to localize picking point using DF-Mask R-CNN and monocular depth

Accurate localization of picking points and depth estimation is critical for implementing a robotic strawberry harvesting system. Due to the delicate nature of strawberries, harvesting must be performed without bruising or damage, typically by grasping and cutting the peduncle of the ripe strawberry. However, accurately detecting and localizing the thin peduncle in a cluttered environment is a significant challenge. This study proposed depth fused Mask R-CNN (DF-Mask R-CNN), which integrates depth information of the scene with the RGB image to enhance the detection, localization, and segmentation of strawberries and their peduncles in a greenhouse environment. To generate a dense depth map, a cutting-edge monocular depth estimator, ZoeDepth was used. The proposed DF-Mask R-CNN with ResNet101-FPN exhibited superior instance segmentation performance, with an overall mAP of 81.9%, with mAPsmall at 33.3%, mAPmedium at 78.79%, mAPlarge at 88.8 and APIOU=0.5 at 98.1%. In tests with 300 ripe strawberry samples, the method demonstrated a robust picking point detection, with a mean absolute error and root mean square error of 1.98 cm and 2.12 cm, respectively. These results highlight the effectiveness of the DF-Mask R-CNN model combined with the ZoeDepth estimator in enhancing the detection, localization, and segmentation of strawberries and their peduncles. This approach enables precise picking point localization and depth estimation for efficient vision systems for robotic strawberry harvesting. © 2013 IEEE

A review of threatened and poorly known samphires in Australia : their distribution, observed environmental threats and ecological responses

Australia is home to a rich assemblage of samphires (Tecticornia and Salicornia spp.) which are largely endemic, inhabiting saline and semi-saline areas across climatically diverse regions. While these plants are adapted to harsh conditions, they are vulnerable to the effects of climate change which is anticipated to exacerbate existing management and environmental pressures. Despite the threatened and priority status of many samphires, there is an overall lack of knowledge surrounding their distribution, ecology and responses to environmental threats, data which we believe is critical to support their conservation and management. We have compiled and critically assessed peer-reviewed and online grey literature and databases to provide an overview of threatened and poorly known samphires in Australia, with particular reference to their distribution, threats and ecological responses. Of the 58 species and 19 subspecies recorded in Australia, two are federally listed as threatened, eight have a formal conservation listing in at least one state or territory, and 25 are recognised as data deficient or priority taxa. Five samphire communities are also listed as threatened and seven are considered Priority Ecological Communities. We found gaps in data relevant to these threatened and priority species, with 40% having fewer than 20 distribution records available nationally. Species were distributed across 11 Conservation Management Zones (and 27 biogeographic regions). Despite their legislative protection, few species have management or recovery plans or peer reviewed ecological studies to guide conservation and management efforts. We propose further research to support effective management of these unique species and ecological communities. © The Author(s) 2025

The role of public events as a tool for economic recovery in an urban environment

This study investigates the effects of events in the New Zealand city of Christchurch’s Central Business District (CBD) on pedestrian movements over the period from 2018 to 2020. Christchurch represents an ideal example of how contemporary urban design and marketing techniques can be combined to attract people to places that have been negatively affected by a natural disaster. Events played an integral part of the regeneration efforts to attract pedestrians and support economic recovery. Through analysing hourly pedestrian movements in the rebuilt and revitalised parts of the city, results show that public events contribute positively to pedestrian volumes; however, the result is not statistically significant. Common cause, rather than entertainment events, draw larger pedestrian volumes, reflecting a stronger preference for events that contribute to social coherence after the disruptive event. Pedestrian visitations during the summer months, holidays, and from Thursday to Saturday have a positive effect on pedestrian volume and even non-event days draw pedestrians to the CBD, a likely result from the regeneration narrative and personal experience associated with the renewed CBD. This research shows how the importance of temporal effects challenges the role of events as a stand-alone tool designed to drive economic recovery within a revitalised urban environment. © 2025 by the authors