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Revolutionizing Lung Cancer Detection: A High-Accuracy Machine Learning Framework for Early Diagnosis
No full textLung cancer is a deadly disease. According to a report of 2024, it is the primary reason for 1.82 million deaths. Given the high disease burden, early detection of lung cancer is crucial for improving survival rates and implementing effective strategies. This paper is aimed at conducting a systematic literature review and developing a highly accurate framework for predicting lung cancer effectively. Tollgate methodology has been used for systematic literature review, and quality assessment criteria were applied to select published articles relevant to the research questions. The paper investigates the effectiveness of machine learning in identifying patterns relevant to lung cancer prediction (Q1), examines the pros and cons of current predictive systems (Q2), compares the use of artificial intelligence in lung cancer prediction with traditional methods (Q3), and identifies key features that distinguish lung cancer from patient symptoms (Q4). Machine learning techniques were employed for the proposed framework. Two publicly available, distinct datasets containing clinical features were obtained. Then, the SelectKBest method was used for feature selection, and SMOTE was used to handle class imbalance. Our proposed framework includes a voting ensemble with random forest, support vector machine, and logistic regression with cross-validation. The results indicate an accuracy of 99% and 92.5% for the first and second datasets, respectively. This study's systematic literature review, based on four research questions and a machine learning model, exhibits high accuracy in predicting lung cancer
Antecedents and Consequences of Service Staff’s Advice-Giving Frequency on Diners’ Overordering Behavior
No full textThe Quantum Brain: The Untold Story of Docosahexaenoic Acid’s Role in Brain Evolution, Biophysics, and Cognition
No full textDocosahexaenoic acid (DHA), the dominant polyunsaturated fatty acid in photoreceptors, neurons, and synapses, is usually described as a passive structural membrane constituent. We propose a different view: DHA is a quantum-electronically active molecule whose conjugated double-bond system creates an electron-rich matrix that couples with proteins to form quantum “clouds” and high-speed signaling central to recognition, recall, and cognition. Integrating evidence from molecular evolution, biophysics, and neuroscience, we argue that, as the original chromophore, DHA’s unique properties enabled the emergence of the nervous system and continue to provide the electronic substrate for cognition. By suggesting that cognition depends not only on protein-based mechanisms but on DHA-mediated electron dynamics at the membrane–protein interface, this perspective reframes DHA as an active, conserved determinant of brain evolution and function
Using MDE to support sustainable re-engineering
Get PDFRe-engineering of legacy software systems is widely used to improve the maintainability of such systems, by migrating them to modernised platforms and environments. With increasing concern over the climate change impact of ICT, there is also a need to consider the energy use of legacy systems, and to identify and remove energy use flaws as part of a re-engineering process. In this paper we describe how energy use analysis and improvement can be carried out at the software model level within a model-driven re-engineering (MDRE) process. Our results show that significant improvements in the energy efficiency of re-engineered applications can be achieved. Additionally, we show that the energy efficiency of the MDRE process itself can be improved.<br/
Reading picture books with infants and toddlers TorrJane. Reading Picture Books with Infants and Toddlers. London, New York: Routledge, 2023, p. 138, ISBN 9780367768911
Get PDF©2025, [SAGE Publications]. This is an author produced version of a paper published in Journal of Early Childhood Literacy uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it
Lived experiences of students with specific learning disorders in university education in the Czech Republic: a case study
No full textLived experiences with inclusive education from the perspective of a pupil with visual impairment and his mother—a case study
No full textIn 2016, there was an important legislative change toward inclusive education (IE) in the Czech Republic, affecting students with different types of Special Educational Needs (SEN) such as visual impairment (VI). As no prior research has investigated the experiences of IE for Czech pupils with VI and their parents, we conducted this phenomenological case study to understand the experiences of a boy with VI and his mother in relation to IE at primary school. Methods: The case study was based on Van Manen's methodology, using semi-structured interviews and thematic analysis. The results (eight themes) show the importance of family support and parental engagement, which helped to overcome some of the education system's shortcomings (e.g., the teacher's unwillingness to cooperate with the family). However, the mother expressed fears about her son's education as he gets older. The boy experienced satisfaction with his education and was proud of his achievements thus far. The case study showed that pupils with VI and their parents may face specific barriers associated with the availability of assistive technologies for VI, and limited provision of support for self-care and orientation. Importantly, these barriers may extend to students with other types of SEN, such as limited awareness of appropriate teaching strategies for pupils with SEN or challenging attitudes of teachers. Involving parents in the educational process may serve as a strategy to overcome these barriers and facilitate inclusion in mainstream settings
How to Support Synergic Action for Transformation: Insights from Expert Practitioners and the Importance of Intentionality
No full textA global poly-crisis of climate change, biodiversity loss, dwindling natural resources, geopolitical instability, among other complex challenges, is on the rise. Societal transformations are therefore imminent, whether intended or unintended. The key question is how to steward and facilitate such changes where fragmentation and siloed ways of working persist. The concept of synergies and the notion of synergic action could help overcome fragmented efforts to steer transformative changes. However, there exists a critical research gap in understanding the conditions needed to enable synergic action. This paper thus explores how synergic action is currently undertaken and the key essentials needed to deliver synergic action. The study uses a case study of the Yorkshire food system transformation to learn from its exemplar practitioners. The study used semi-structured interviews and a thematic analysis process to reach our two key findings. First, we highlight the three types of synergic action: (1) Non-systemic synergic action, (2) Non-systemic synergic action with multiple outcomes, and (3) Systemic synergic action. Differentiating types of synergic action can help identify where synergic action is already underway and guide more explicit efforts towards transformative change. The second key finding is the five essentials for synergic action, which are (1) leadership for synergic action; (2) networking, partnerships, and collaborations; (3) care and understanding; (4) a systems approach; and (5) intentionality for synergic action. This study brings to the fore the importance of intentionality, without which the first four essentials are less likely to coalesce. This is important to inform the reflection and learning of practitioners of systemic change about how they are currently and could be working more synergistically in the future, driven by clear intentionality
Fostering healthy schools for students with SEND through co-production: creating an educational toolkit to support young people with 22q11.2 deletion syndrome
No full textChildren and young people with 22q11.2 deletion syndrome (22q) face unique educational and wellbeing challenges that are often poorly understood in mainstream schools. This participatory action research (PAR) aimed to produce a practical, school-based toolkit to support the needs of pupils with 22q with a focus on wellbeing and inclusive practice. Participants included educational professionals (N = 7), young people with 22q and their parents (N = 9), and staff in schools (N = 3). Data were collected through questionnaires, a co-production workshop, and a focus group, and analyzed thematically. Participants collaboratively designed three resources; an infographic poster, a pocket guide for staff, and a short, animated video aimed at peers. Survey findings identified key gaps in staff knowledge, inconsistent provision, especially for transition, and limited wellbeing support, in line with the authors’ previous research. These findings helped to inform the development of the resources, which were praised by staff in schools for clarity, adaptability and alignment with existing practices. This study demonstrated how co-produced, low-cost resources can enhance awareness, promote inclusion and support the holistic wellbeing of pupils with 22q. This approach offers a scalable model for addressing similar gaps across wider SEND