18624 research outputs found
Sort by
Nurturing resilience and healing from within : the impact of an 8-week yoga program on nursing students
No full textBackground/Objectives: Nursing students encounter significant stress due to the demanding nature of their academic and clinical training, negatively impacting their mental health and overall wellbeing. Self-care strategies, such as yoga, have been suggested to effectively manage stress and promote resilience. Despite the growing recognition of the importance of self-care in nursing education, there is limited research on the specific benefits of yoga. This study aimed to explore the experiences and perceived benefits associated with undergraduate nursing students’ participation in an 8-week yoga study. Methods: A qualitative study using a hermeneutic phenomenological approach was conducted. Participants were Baccalaureate nursing students from an Australian university. Data were collected through semi-structured interviews and analysed using reflexive thematic analysis. Reporting methods followed the consolidated criteria for reporting qualitative research guidelines. Results: Among the 14 students who participated, three main themes emerged: “Me Time”, highlighting the importance of prioritising self-care; “Slowing Down,” emphasising the psychological benefits of yoga; and “Self-Acceptance,” reflecting personal growth and improved self-awareness. Participants reported reduced stress, improved mood, and enhanced physical and mental wellbeing. Conclusion: Students who participated in yoga were positively impacted through greater stress management and wellbeing. As nursing students transition into the workplace, the ability to manage stress and maintain mental wellbeing becomes even more critical. The high-pressure environment of healthcare settings can exacerbate stress, leading to burnout and decreased job satisfaction. By incorporating self-care practices such as yoga into their routine, nursing students can develop resilience and coping mechanisms that will benefit them as students and throughout their careers. © 2025 by the authors
Enhancing IoT security : assessing instantaneous communication trust to detect man-in-the-middle attacks
No full textCommunication trust is regarded as an effective tool to detect various dangerous cyber attacks, including Man-in-the-Middle (MITM) attacks and acts as a complement to zero trust. There exist some approaches in the literature to calculate inter-node communication trust in Wireless Sensor Networks (WSNs) and IoT networks and leverage it to detect attacks. In WSNs, since promiscuous communication mode is used in calculating inter-node communication trust, it is not suitable for IoT networks. For IoT, the packet forwarding behavior of edge nodes is used in calculating inter-node communication trust, which is limited to detect the MITM attacks effectively unless an edge node is compromised and acts as an MITM attacker. Additionally, these trust calculation mechanisms neither leverage communication channel characteristics nor the communication trust between sensor and edge nodes. Protecting IoT networks from various cyber attacks like MITM attacks requires the instantaneous trust calculation using communication channel characteristics. Since active MITM attacks incur delays, consideration of delay in trust calculation appears to be an effective means in identifying attacks. Neither end-to-end (E2E) delay nor delay due to attacks has been used in communication trust calculation in the existing literature. To bridge this research gap and detect active MITM attacks accurately and spontaneously, in this paper, a new conceptual model, named IPCTCM is introduced for instantaneous trust calculation of an IoT communication channel leveraging delay due to active MITM attacks. Two popular time-series data estimation tools, named Kalman filter and LSTM are used to estimate the expected E2E delay to identify delay due to attacks. Our proposed communication trust calculation model is validated using the data, generated by a testbed implementation in our IoT lab at Federation University Australia. Performance evaluation shows our proposed model achieves an attack detection accuracy of 98.9%, which outperforms an existing intrusion detection method with the improvement of 48.1% accuracy. Furthermore, our trust calculation method has broader applicability in other communication domains as well. © 2025 The Author
DeepCSS : severity classification for code smell based on deep learning
No full textCode smell severity refers to the different levels of impact extent that smelly instances may have upon a specific project when more than one kind of code smell exists. Severity classification helps developers better understand a code smell and prioritize multiple refactoring operations more efficiently, thus improving the efficiency of software maintenance. However, existing studies on code smell severity assessment and classification suffer from insufficient quantitative evaluation and low accuracy. To this end, this paper proposes DeepCSS, a novel approach to classify code smell severity based on deep learning. To evaluate the severity of code smells reasonably and accurately, a quantitative evaluation framework is proposed to evaluate the importance of assessing each related metric. With this evaluation framework, datasets are constructed for four types of code smell (including data class, god class, long method, and feature envy) extracted from 100 real-world projects. DeepCSS acquires structural and semantic information from which features are extracted by leveraging BiLSTM-Attention and the improved CNN model. Then the final classification is done by a fully connected network containing the Attention mechanism and softmax functions. The experimental results show that DeepCSS can achieve an accuracy ranging from 95.11% to 98.97%. Compared to other studies, DeepCSS obtained an average improvement of 6.97% and 1.39% in MCC, demonstrating its effectiveness. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025
The Behaviour of Elbow Elements at Pure Bending Applications Compared to Beam and Shell Element models
No full textThis paper studies the response of ELBOW31 and ELBOW31B element types under pure bending conditions, using shell and beam element models for benchmarking. Various model lengthsareevaluated,showingthatamodellengthofsixpipediametersexhibitsahardening effect when total strain exceeds 3.5%, though a strain up to 1% is deemed sufficient for pipeline design. The study examines the effects of ovality modes and boundary conditions suchasNOWARPandNOOVALonthebendingresponse.ELBOW31withoneortwoovality modesyields accurate results, while additional ovality modes or zero ovality mode can lead to overprediction of the elastic bending moment capacity. The introduction of the NOWARP condition enhances the accuracy of the ELBOW31 model, while the NOOVAL condition aloneproducesunrealisticresults.ThesimplifiedELBOW31Bmodelshowsgoodagreement with the ELBOW31-NOWARP model but similarly overpredicts the bending moment when zero ovality mode isused.Thestudy alsofindsthatPoisson’sratioandmodellengthhaveno significant impact on the bending response when no restrictions are applied. Additional analyses, as presented in Appendices A and B, highlight the importance of D/t ratios in pipeline performance. A D/t ratio of 20 offers a stiffer response with reduced ovalization, while a D/t ratio of 50 results in greater flexibility and increased ovalization. These findings provide valuable insights for the selection of element types, boundary conditions, and D/t ratios in robust pipeline design
Analyzing the impacts on stability of ibr-dominated power systems under evolving composite loads
No full textAddressing climate change through the integration of renewable energy resources necessitates the development of advanced control strategies and precise load modeling to ensure the secure and stable operation of electric grids. This paper investigates the voltage and frequency stability of a transmission network with a high penetration of inverter-based resources (IBRs) under evolving composite load models. At first, the stability of the network is analyzed for different penetration levels of renewable generation. Later, a mix of Grid-following and Grid-forming inverter controls is employed to enhance the system stability. Finally, composite load models are integrated into the network to investigate the impacts on the stability of the system. All simulations are conducted using DIgSILENT PowerFactory software under different load scenarios, employing eigenvalue analysis and RMS simulations as stability indices on a 9-bus transmission network. The results demonstrate that increased dynamic loads lead to significant voltage dips and oscillations in the network and advanced control strategies and precise load modeling are essential for maintaining stability in the IBR-dominated grids. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025
Psychiatrists’ attitude towards smoking cessation support (PATSS) : exploring psychometric properties of the measurement tool
Full text linkThe attitude of psychiatrists plays a crucial role in screening and supporting smoking cessation, especially with people with serious mental illness (SMI). The development of an attitude scale can improve the success of quitting among people with SMI. This study aimed to develop and test the psychometric properties of psychiatrists’ attitudes toward smoking cessation support (PATSS). Based on the literature review, the attitude scale, which comprised 15 items, was developed and tested with 289 psychiatrists. The tool’s psychometric properties were tested by examining item performance, content and construct validity (by exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability. The content validity was demonstrated by content validity ratio (CVR) (0.80) and item content validity index (ICVI) (0.88). Both EFA and CFA identified four factors: Priority and Time Commitment, Recovery Impact and Training, Social Support and Patient Factors, and Coping Mechanisms and Rights. A Cronbach alpha of (0.81) demonstrated high internal consistency. PATSS was found to be a valid and reliable tool to assess the attitude of psychiatrists towards smoking cessation support provided to people with SMI. © The Author(s) 2025
ADHD : the experiences of children and parents in the educational context
Full text linkDoctor of Philsoph
ESG performance and supply chain contracts : evidence from ASX-listed companies
No full textThis paper utilizes agency and stakeholder theories to explore the relationship between ESG (environmental, social, and governance) performance and supply chain contracts. Drawing from data using a sample of ASX 300 firms over the period of 2012 to 2021, our analysis reveals a negative relationship between ESG performance and supply chain contracts, aligning with agency theory principles. Furthermore, this negative association is observed to be more pronounced among firms characterized by lower levels of information asymmetry. These findings hold significant practical implications for management, business suppliers, and customers alike. Specifically, managers can leverage these insights to reinforce the commitment of supply chain partners towards ESG initiatives, thereby enhancing sustainability practices within the supply chain ecosystem. © 2025, IGI Global Scientific Publishing. All rights reserved
Transformational learning and agency for professional identity development : first-year social work student retention and wellbeing
No full textChallenges relating to first-year student retention and learning outcomes are recognized as a multi-faceted issue in the tertiary education sector across many professional programs, including social work. Graduating students can find it difficult to establish themselves in the workplace. The researchers wanted to understand if fostering a sense of professional identity for social work students as part of the research experience might in and of itself enable retention because of improved opportunities for transformational learning, agency, and wellbeing as a student. The participatory action research project was designed around a community of practice of social work students facilitated by two recent graduates to undertake the collaborative design and creation of supportive educational resources. Student empowerment, connectedness, and wellbeing were improved by involvement in the collaborative professional task of doing research, with students reporting increased connection with the university and engagement in their learning. Implications for fostering professional identity development during social work education are explored. © 2024 Informa UK Limited, trading as Taylor & Francis Group
pH-responsive bacterial nanocellulose smart labels derived from acid whey for estimating beef mince quality alterations during storage
Full text linkThis study develops a pH-responsive label by incorporating anthocyanin from Clitoria ternatea into a bacterial nanocellulose (BNC) film derived from acid whey fermen tation. The labels were designed to display two distinct colors—pink and purple—by adjusting the pH of anthocyanin and were integrated into beef mince packaging to monitor quality changes over a 15-day storage period at