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Tolerant sequential model predictive control based on lexicographic optimization method for t-type three-phase three-level inverters
No full textDue to the existence of the neutral point (NP) voltage, controlling the three-level inverters has essentially become a multiobjective optimization problem (MOOP) that needs to provide stable output voltages for the load and maintain the NP voltage simultaneously. Traditionally, this MOOP is converted into a single-objective optimization problem by weighting factors. However, since the physical dimensions of the two control objectives are usually different, it is challenging to choose proper weighting factors to obtain a satisfactory performance according to a specific theory. To address this issue, a tolerant sequential model predictive control (TSMPC) utilizing a lexicographic optimization method is proposed in this article. This method establishes two distinct layers for the output voltage and NP voltage, arranging them in sequence according to the importance of control objectives to evaluate all voltage vectors. By using an explainable tolerance value rather than conventional weighting factors, the proposed TSMPC algorithm presents superior performance over traditional MPC approaches. Finally, the feasibility and effectiveness of the proposed TSMPC algorithm have been verified through relevant experiments and the stability of this algorithm has also been analyzed. © 1986-2012 IEEE
Intelligent decision framework for booster fan optimization in underground coal mines : hybrid spherical fuzzy-cloud model approach enhancing ventilation safety and operational efficiency
No full textOptimizing 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
Navigating a nursing career four years after graduation : a qualitative descriptive study exploring drivers of staying amid wanting to leave
No full textAim: To explore the lived experience of Early Career Nurses four years post-graduation and identify factors influencing their decision to stay in or leave the profession. Background: The retention of Early Career Nurses is a critical issue globally, with many leaving the profession within the first few years. Various interventions have been implemented to support Early Career Nurses, but the complexities of retention require a more nuanced understanding, particularly for those in the latter stages of their transition. Design: A qualitative descriptive study. Methods: Early Career Nurses who participated in a longitudinal study as undergraduate nursing students were interviewed 48 months after graduation. The study used phenomenological approach to explore key experiences and phenomena. Data were analysed using Thematic Analysis, adhering to COREQ guidelines. Results: Among the 25 participants, key themes identified included being ‘Overworked and undervalued’ and being ‘Anchored by care.’ Early Career Nurses experienced significant pressures, including incivility, poor management and staffing shortages, leading to a desire to leave the profession. However, a strong commitment to patient care and support from peers and family helped some Early Career Nurses remain in the profession. Conclusion: The study highlights the need for systemic changes to support Early Career Nurses, including empathetic leadership, adequate training and supportive work environments. Addressing these issues is essential for the wellbeing of Early Career Nurses and maintaining high standards of patient care. Understanding the unique challenges faced by Early Career Nurses can inform strategies to improve retention and support their professional development. © 2025 The Author
Higher serum uric acid levels and risk of all-cause mortality in general population: a systematic review and meta-analysis
No full textAbstractBackgroundPopulation-based studies have reported a relationship between high serum uric acid (SUA) levels and all-cause mortality however, findings are inconsistent. To address this issue, we conducted a meta-analysis of general population-based studies. MethodsA systematic search was conducted in PubMed, Ovid Medline, EMBASE, and Web of science to identify relevant peer-reviewed articles using pre-specified search terms. Population-based cohort studies investigating the association between SUA levels and all-cause mortality were included. Risk ratios (RR) for all-cause mortality were calculated for higher and lower SUA levels based on data reporting on exposure and outcome. A meta-analysis based on a log-transformed random effect maximum likelihood model was used to obtain summary risk estimates. Heterogeneity was assessed through subgroup analysis and meta-regression of the study-level covariates. ResultsThirty-four studies with more than 2.5 million participants were identified and analysed. Higher SUA levels were associated with an increased risk of all-cause mortality (RR: 1.32 95 % confidence intervals (CIs):1.26–1.39, p < 0.001). The risk of mortality was higher in women (RR:1.91 95 %CI:1.40–2.61, p < 0.001) compared to men (RR:1.16 95 %CI:1.08 1.24, p < 0.001). Subgroup analyses suggested that middle-aged adults (RR: 1.52, 95 %CI: 1.35–1.68), individuals living in OECD countries (RR:1.39, 95 %CI:1.28–1.49) and those of Caucasian ethnicity (RR:1.43, 95 %CI:1.35–1.51) reported a greater impact of elevated SUA levels on all-cause mortality. ConclusionsHigher SUA levels were associated with a significant increase in the risk of all-cause mortality, with women appearing to be at greater risk than men. These findings highlight the need for research into mechanisms underlying the association between SUA and mortality and the reason for the sex difference identified
Sensor self-declaration of numeric data reliability in internet of things
No full textSince diverse noises and irregularities impact on sensor data, self-declaration of sensor data reliability is crucial for advancing Internet of Things applications and industrial automation. Relevant works on reliability include sensor self-attribution of data confidence, and self-diagnosis of sensor faults using temporal data redundancy or neighboring sensor data. Models are built on edge devices and then transferred to sensors. Overall, the existing methods are computationally expensive, require real-time data from other sensors and incur considerable transmission overhead. Therefore, they are not suitable for independent sensor data reliability assessment. Addressing these issues, we introduce an independent reliability self-declaration method for sensors. Two Kalman filter-inspired, block-based lightweight algorithms are designed that handle isolated and burst noises and estimate block data reliability. Moreover, a conceptual model to dynamically adjust block size is proposed leveraging noise level and maximum TCP/IP packet size to reduce data transmissions. The reliability levels are conveyed using TCP header reserved bits to avoid communication overhead. The approach was tested using water quality monitoring (WQM) and healthcare application datasets. Results show, for burst noise, our lightweight and scalable approach attains superior accuracy in WQM (89.06%) and healthcare (82.63%) for five-level reliability estimation. A real-world deployment using an Arduino-based sensor node demonstrates the feasibility of the approach for in-sensor operation. © 1963-2012 IEEE
The experiences and practices of nurse leaders in promoting and maintaining civility in Australian regional and rural health and aged care settings : a qualitative study
No full textBackground: It is well known that nurses strive to serve the needs of others through compassionate care. Less known, however, is that this same compassion is not always displayed between nurses. Nursing culture has been infiltrated with unprofessional behaviours, the most common of which is workplace incivility. Compared to bullying, workplace incivility typically lacks an intent to hurt others but equally offends and harms nurses, compromising their health and wellbeing and their ability to deliver quality patient care. Nurse leaders are ideally placed to influence the behaviours of nurses in their teams by promoting and maintaining civility within the clinical setting. However, these practices, and the influencing factors that are associated with them, have been poorly understood or explained in the literature. Aim: The overall aim of this research study was to gain a deeper understanding of the experiences and practices of nurse leaders in creating civility in regional and rural health and aged care settings in the state of Victoria, Australia. Methods: Using constructivist grounded theory methods, 11 nurse leaders were recruited and individually interviewed. Data were collected from the transcripts and the audio recordings generated from the interviews and memos. Results: Through applying reflexivity and constant comparison, open and focused codes were developed to inform category formation, which led to the creation of two key themes: A Disconnect in Practice and Leading With Courage. These themes informed the substantive theory titled Acknowledge, Communicate, Teach, Support (ACTS) Theory for Creating Civility in Nursing. Implications: Nurse leaders require ongoing precepting, mentoring and training aimed at enhancing their communication skills and role-modelling behaviours to create civility within nursing care teams. This study has contributed to the literature concerning civility in nursing by highlighting the practices of nurse leaders as well as serving the interests of other healthcare professions, administrators, researchers and policymakers interested in making a positive impact to this ongoing workforce issue across a range of sectors. The findings can be harnessed to influence workplace culture, and policy and educational development, as well as inform leadership development and foster meaningful change in health and aged care settings.Doctor of Philosoph
SD goal 15—life on land : progress to date, the role of business, and a case study in sustainable development in human-modified landscapes
No full textSustainable Development Goal 15 involves the development of terrestrial and freshwater ecosystems in a way that does not deleteriously affect resource use for future generations. Through a series of targets, it aims for no loss of biodiversity, sustainable forest management, increased coverage of protected areas, halting desertification, and reducing land degradation. Progress to achieving these targets by 2030 has been slow and patchy across the world. The business sector is becoming aware that its future prosperity and sustainability depend on healthy ecosystems and the services these provide. Many progressive and innovative corporations have committed to becoming nature-positive and ensuring their operations leave a better environmental footprint. However, there are others that have been accused of greenwashing, in which their claims of sustainable practices are without foundation. We present a case study in Australia in which damage to agricultural production has been averted using a humane and effective use of raptors to disperse large flocks of native birds that threatened to consume a large almond crop. The technique has been used to solve problems caused by birds not only in agricultural production but also in infrastructure damage and disruption to sporting and cultural activities. We have found the technique works best when the period of damage activity is discreet, the area small, and the financial risk of damage by the birds high. However, the method is labor-intensive and does not work in certain other circumstances. We also discuss the potential improvement in the effectiveness of the technique if lethal take of some of the pest birds is encouraged. © 2025 selection and editorial matter, Ranjula Bali Swain and Peter Dobers; individual chapters, the contributors
Immersion cooling innovations and critical hurdles in Li-ion battery cooling for future electric vehicles
Full text linkBattery electric vehicles are pivotal in advancing the circular economy by reducing carbon footprints through their sustainable design and low-emission operations. The growing demand for electric vehicles with fast-charging capabilities and high-energy-density Li-Ion batteries has significantly intensified the importance of effective battery thermal management systems, as elevated temperatures can lead to rapid battery degradation and thermal runaway. The study of typical battery cooling techniques seems insufficient to attain temperature homogeneity in the battery pack during fast-charging applications. Therefore, to address this significant challenge, a holistic analysis of immersion cooling technology for battery thermal management is provided, which has the heat transfer rate in the order of magnitudes compared to a typical battery cooling mechanism. In immersion cooling, the battery is submerged in a dielectric coolant, establishing direct contact between the coolant and the heat source. The current state-of-the-art immersion-cooled battery thermal management systems with single-phase and two-phase techniques are comprehensively reviewed. The performance of available immersion coolants is analyzed, and a suitable coolant selection strategy is formulated for battery immersion cooling applications. Besides, critical issues like suppression of thermal runaway, nucleate boiling, immersion coolant effects on battery, and fluid flow optimization with future directions have been discussed comprehensively. A detailed discussion on the economics of battery immersion cooling as a cost-effective solution is included. This study offers an up-to-date review of battery immersion cooling, fostering an improved understanding of advancement in thermal management systems in the context of promoting a circular economy and zero emissions. © 2024 The Author
Litter arthropods display greater differences among locations than grass species in a temperate grassland
Full text linkGrasslands comprise a significant portion of terrestrial ecosystems, contributing an estimated 20% of global carbon stores. Biomass is recycled in these systems by photodegradation, biotic decomposition, and through disturbances such as fire or grazing. Yet the role of the arthropod community in biotic decomposition remains unclear in many grasslands worldwide. To help close this knowledge gap we conducted a litter bag experiment to sample the arthropod community that readily associate with detached grass litter. We tested for the effects of four grass species (two native and two exotic) and two mesh sizes on arthropod assemblages surveyed at three grassland sites in southeastern Australia. We collected 7,933 arthropods across twelve orders and found that all sites had a diverse and abundant arthropod community associated with grass litter. There was greater difference in arthropod composition among sites than among grass species or grass origin, with significant differences in the abundance of Acari, Poduromorpha and Thysanoptera. There was no effect of litter bag mesh size on the sampled arthropod community. Conservation implications: We found that both geographic and floristic factors were important drivers of variation in grassland arthropod communities linked to decomposing litter, but the drivers of these differences, and their consequences for arthropod diversity and grassland ecosystem function, remain unresolved. Further research and monitoring are needed to determine the outcome of grassland management on arthropod communities and their ecological functions. © The Author(s) 2025
The digital future of farming : a bibliometric analysis of big data in smart farming research
Full text linkRecent advancement of technology in the analytics of big data has sparked a transformative revolution in smart agriculture, enabling farmers to make informed decisions, optimize resources, and enhance productivity and sustainability. Tracking developmental progress is crucial to understanding how big data applications in smart farming are rapidly evolving with ongoing technological advancements. We conducted a bibliometric analysis of academic publications and documents published in Scopus-indexed peer-reviewed journals. A total of 2,154 publications, including journal articles (45 %), conference proceedings (30 %), book series (16 %), and books (9 %), were retrieved, with 96 % of the documents in the English language and two-thirds of the documents published within the last four years of this research study. The reviewed publications were predominantly focused on the disciplines of computer science (64 %), engineering (36 %), and agriculture and biological science (22 %). The contributions of authors from India, China, and the United States were the highest, accounting for half of the publications when combined. As an outcome of the bibliometric analysis, five research domains of big data, i.e., data-driven decision-making, sustainability and supply chain management, technology and innovation, data management and governance, and digital transformation were identified, suggesting positive development in this field. As an implication of this work, we have identified a need for greater global collaboration to achieve big data advancement and technology adaptation. We also discussed the implications of this work for research, practice, and policy. Despite the opportunities that big data brings for smart farming, economics, data governance, and data sharing and reliability remain prevalent issues. These issues need to be addressed for fully effective utilisation of big data in smart farming. © 2024 The Author(s