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A Comprehensive Review of Predicting Vaccine Side Effects with AI
No full textVaccination is a key to public health and safety, but adverse vaccine side effects threaten its safety and monitoring. Traditional pharmacovigilance systems are characterised by flaws such as underreporting, delays, and data fragmentation. This paper presents a holistic review of the role of artificial intelligence (AI) in vaccine side effect detection and prediction. Methodologies like machine learning, deep learning, and natural language processing are examined, with a close look at their application to real-world data sources like electronic health records, social media, and vaccine registries. Evidence from the COVID-19, HPV, and influenza vaccines shows that AIs can detect vaccine side effects, with each of the AI models achieving a high accuracy of (AUC 0.91, F1-score 0.903) in vaccine side effect detection. However, despite the promising benefits, some challenges such as data quality, model generalisation, and ethical challenges still exist. This paper also suggests that future research directions should include vaccinology, federated learning, and explainable AI for real-time and personalised risk assessment. Conclusively, this paper brings to the fore the numerous benefits that AI offers in pharmacovigilance, showcasing its transformative potential for proactive vaccine safety surveillance
Global health governance and human rights
No full textDescription:Advancements in medical science and technology have the potential to transform global health, but they also bring ethical challenges related to fairness, accessibility, and equity. Intellectual property laws and governance structures, while encouraging innovation, can inadvertently limit access to essential treatments, particularly in underserved regions. Balancing the need for innovation with the imperative of equitable healthcare requires careful policy design and global cooperation. Addressing these issues is vital to ensuring that medical breakthroughs benefit all populations, not just those with economic or geographic advantages.Global Health Governance and Human Rights provides a comprehensive and interdisciplinary examination of the ethical dimensions of healthcare innovation and the mechanisms that either promote or restrict access to life-saving medical treatments. By engaging with diverse perspectives, including those from law, medicine, global health governance, and human rights advocacy, it offers practical insights into how to reconcile the competing demands for innovation and equity. Covering topics such as affordable pharmaceuticals, right to food, and transgender persons, this book is an excellent resource for academicians, legal professionals, policymakers, healthcare practitioners, and those working in global health governance
The PaCT Workshop: 10 Year Plan chapter: A workforce fit for the future
No full textAward category: Strengthening the foundation The Patient as Coach Team (PaCT) initiative at the University of Greater Manchester is a pioneering model in nurse education that places lived experience at the heart of learning. Coproduced and led by service users and carers, PaCT transforms students’ understanding of compassionate, personcentred care by embedding emotional intelligence, ethical awareness, and the 6Cs of Nursing throughout the curriculum. Delivered in small, safegroup settings across all three years of the adult nursing programme, PaCT combines immersive workshops with reflective learning. Students consistently report increased empathy, confidence, and accountability, with longevidenced in their professional development portfolios. The term impact initiative has also been successfully adapted for other disciplines, including Social Work and CBT. What makes PaCT stand out is its authentic coproduction, longitudinal structure, and tangible influence on practice. It elevates service users from contributors to educators, creating a culture of dignity, partnership, and emotional intelligence. PaCT is not just a teaching tool — it’s a blueprint for how we must train the future health and social care workforce
An investigation into differences in general intelligence and coaches' subjective assessment of players' decision-making skills across different playing positions in EPPP association football academies
No full textWith developments in tactical complexity in association football (soccer) general intelligence and decision-making are becoming increasingly important attributes for players at all levels. However, an absence of evidence regarding general intelligence and decision-making across different positions within English Academy soccer indicates that it is unknown how specific intelligence in soccer needs to be for successful performance. This study aimed to 1) examine differences in general intelligence scores between different playing positions, 2) investigate differences in coach assessed decision-making ability between different playing positions and 3) assess differences between general intelligence test score ranks and decision-making ranks awarded by coaches to each player per position. One hundred and one participants, aged 16–18 years were recruited from eight clubs in the English Football League. Participants completed an established psychometric test of general intelligence and the lead development phase coach at each club ranked players' decision-making ability. There were 99 outfield players who participated: 37 defenders, 34 midfielders and 28 attackers. No difference was found in general intelligence scores between playing positions. However, a significant difference was found in decision-making ranks, with coaches determining attacker's decision-making to be lower than midfielders and defenders. Likewise , no difference was found between general intelligence and decision-making ranks for either defenders or midfielders, but a difference was observed between attackers' general intelligence and decision-making ranks. In conclusion, attacker's game intelligence appears to be underestimated by coaches. Consequently, utilisation of a psychometric test of general intelligence could enhance identification of talented players in Academy soccer
Enhancing robot odometry : novel design, positioning accuracy, and performance evaluation
No full textMobile robots are increasingly used in rescue missions , household cleaning, and food service due to their stability and affordability. These robots require accurate positional data from sensors, environmental maps, and path-planning algorithms for effective navigation.This study presents a novel approach to indoor robot positioning that integrates Particle Filter (PF) with Adaptive Particle Filter (APF) methodologies. Our system combines data from multiple sensors including a Laser Range Finder (LRF), dual encoders, and a gyroscopic unit to enhance positional accuracy. By processing LRF measurements alongside reflected beacon signals, we developed an algorithm that dynamically adjusts particle distributions for improved localization. Experimental results show that this integrated approach achieves an accuracy improvement of 96.5% compared to traditional methods, demonstrating its potential for robust indoor navigation applications
Beyond Loan Volumes: A Multi-Dimensional Causal Evaluation Of Brazil's Minha Casa Minha Vida Program (2006-2023)
No full textWe provide the first multi-dimensional causal evaluation of Brazil's Minha Casa Minha Vida (MCMV) housing program using interrupted time series analysis, synthetic control methods, and state-level difference-indifferences. Using Central Bank administrative data (2006-2023) and Ministry of Cities program records, we test four pre-registered hypotheses regarding credit expansion, social targeting, institutional sustainability, and counter-cyclical stabilization. Our event-study analysis shows MCMV increased housing credit by 969.3 billion reais (95% CI: 793.2-1,145.4) with no pre-intervention trends, representing system-wide expansion rather than substitution effects. However, targeting analysis reveals regressive outcomes: Track 1 (poorest families) received 39.4% of units versus 60% target (Kakwani progressivity index = 0.12, below 0.25 benchmark). During the 2014-2016 recession, MCMV lending elasticity to unemployment was-0.34 versus-0.89 for private markets (difference = 0.55, p<0.01), demonstrating counter-cyclical buffering. Institutional sustainability metrics show manageable fiscal exposure (0.78% GDP) with default rates (3.8% Track 1, 2.1% Track 2/3) below international benchmarks. State-level heterogeneity analysis reveals stronger program effects in low pre-program mortgage penetration states (β=0.23, p<0.05), consistent with credit constraint mechanisms. Our findings demonstrate that preferential interest rates generate volume expansion but require complementary institutional design to achieve equity objectives
Job burnout and job satisfaction in Primary school teachers in Greece
No full textIn a sample of 154 primary school teachers (mainstream/regular teachers), working at the elementary school level in Greece, this research examines the degrees and relationships between job satisfaction and job burnout. Based on quantitative methodology, the current study is grounded on positivist principals. The hypothesis posits that (mainstream/regular) primary school teachers in Greece have moderate to low levels of job satisfaction across multiple dimensions, leading to the exacerbation of professional/job burnout.Two research instruments were used in the survey in order to test the hypothesis: (a) the Job Satisfaction Survey (JSS), by Spector (1994) was used to measure nine aspects of job satisfaction, and (b) the Maslach Burnout Inventory-Educator's Survey (MBI-ES) by Maslach and Jackson (1981) was used to assess the three burnout dimensions. The demographic questionnaire was also used, which developed to serve the purposes of the research, created ad hoc by the researcher.The main findings of the study were:1. Primary school teachers, who belong to the mainstream primary/elementary school teachers, reported moderated to high levels of Emotional Exhaustion, low levels of Depersonalization and as far as Personal Accomplishment is concerned, they reported a slight sense of success. They expressed a certain level of dissatisfaction with their financial rewards; promotion opportunities, standard operating procedures, as well as they expressed concern about potential rewards and benefits, in particular. As far as job satisfaction concerns, they felt satisfaction, to some extent, with communication and cooperation with supervisors and colleagues, while, they reported fairly satisfied with their profession itself.2. Compared to female primary school teachers, men were much more prone to be depersonalized and less satisfied with communication, in general, and with the nature of their work. Primary school teachers with a schedule with few hours reported noticeably more symptoms of Depersonalization than teachers who worked in a full time schedule. As far as supervision concerns, older teachers reported significantly higher levels of Emotional Exhaustion and less job satisfaction, than the younger ones. Also, teachers who belong to the more experienced group reported much higher levels of Emotional Exhaustion than their colleagues who belong to the less experienced group.3. Emotional Exhaustion has been found to be strongly correlated with satisfaction or dissatisfaction with standard operating procedures, potential rewards, and the overall nature of the work.Depersonalization has been found to be substantially associated with satisfaction or dissatisfaction with communication with supervisors and colleagues as well as benefits and the overall nature of work.Personal Accomplishment was significantly linked with satisfaction or dissatisfaction with potential rewards, communication with supervisors and colleagues as well as the overall nature of work.The results of our research indicated that there was, to some extent, a negative relationship between job satisfaction and job burnout, particularly as far the Emotional Exhaustion dimensions are concerned. That means that, whenever the levels of one phenomenon are higher, the levels in the other phenomenon are lower.Therefore, it should be taken into consideration the expectations and the desires of the primary school teachers, from their profession, in order to reduce the possibilities to job burnout το be appeared, and to give a push to the development of positive feelings towards the school teaching profession, which affects the future lives of so many students, the teachers have under their supervision and protection.It is suggest that, in primary education in Greece, some improvements should be taken place, towards the day to day practices and experiences, mainly towards the direction of improvement of the overall job environment and the system of rewards of all kinds e.g. ethical and financial. Appreciating teaching profession we avoid teachers' job burnout and thus we are proceeding towards the development of a climate of confidence, which will contribute to the realization of educational goals.This can be achieved by enhancing the school atmosphere and ambiance and by developing a system of rewards that recognizes teachers' contributions and helps the school achieve its objectives
Blooming with Brazilian queer studies Reflecting on experiences of co-authoring and publishing with LGBTQ+ academics
No full textIn this chapter, the author analyses his past experiences as a Brazilian early-career researcher publishing on queer studies. First, he draws on publications developed as part of a knowledge exchange (KE) project called Diversidade Sexual na Escola (Sexual Diversity at School) which trained teachers on gender and sexuality. Second, he discusses publications coming from engagement with other queer and feminist activists, academics, and students in Rio de Janeiro, Brazil. He focuses particularly on establishing partnerships through academic projects, activism, and affects for co-authoring, networking, and publishing within the LGBTQ+ community, as well as the challenges that moving to England brought and the need to build new local support networks. He also addresses the context of queer studies in Brazil, and particularly their presence in education policies and research. Finally, he suggests reinforcing partnerships by LGBTQ+ academics to support their capacity to thrive, paying special attention to those from marginalised backgrounds
Comparative analysis of machine learning models for uterine cancer prediction using clinical and genomic data
No full textUterine cancer prediction accuracy is important in clinical decision-making because it improves the overall chances of patient recovery. Several machine learning models, such as Decision Tree, Random Forest, XGBoost Regressor, and Support Vector Regressor, were explored to determine which is more effective in predicting uterine cancer. Attributes such as mutation counts, diagnosis age, and MSI score, were used for the analysis. The different models were tested using the standard performance metrics such as the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2 Score. Random Forest showed the highest predictive performance with an R2 score of 0.655, followed by XGBoost regressor, which was relatively close to the R2 score of Random Forest. Support Vector Regressor performed very poorly as the R2 score was negative, implying that the model is not suitable for such prediction. Ensemble-based models, which include Random Forest and XGBoost Regressor, have proven to be more effective in handling medical prediction tasks, and this is because of their robustness and their ability when it comes to handle overfitting. Though model generalizability was affected due to small data size and the absence of hyperparameter tuning. The future work will focus on expanding the dataset, implementing hyperparameter tuning, integrating deep learning, and leveraging explainable AI (XAI). The research has provided valuable insight for clinicians who wish to use machine learning for uterine cancer prognosis
The PaCT Workshop: Embedding Lived Experience in Nursing Education
No full textThe Patient as Coach Team (PaCT) initiative represents a transformative step forward in nurse education. Led by service users and carers, PaCT reimagines how student nurses learn about, connect with, and practise personcentred, compassionate care. By placing lived experience at the heart of its design, the initiative offers a powerful model of learning that supports the development of emotional intelligence, ethical awareness, and the values that underpin professional nursing practice. In an era where healthcare systems are under increasing pressure to maintain dignity, empathy, and humanity in care delivery, PaCT stands out as a pioneering and innovative educational response. It is firmly rooted in the 6Cs of Nursing— 1. Compassion and Empathy 2. Dignity and Confidentiality 3. Trust and Honesty 4. Collaboration and Communication 5. Courage and Commitment 6. Competence and Expressing Emotion It offers students an opportunity to engage in coproduced education shaped by people with direct experience of care. Rather than being passive recipients of care, service users and carers become educators in their own right, and are influencing the next generation of practitioners. The PaCT initiative offers a bold and sustainable way to bridge the gap between theory and real-world practice. It humanises the learning experience, embeds lived experience as a vital source of knowledge, and helps to shape a workforce that is not only clinically competent but also grounded in empathy, dignity, and ethical care. Recognising the value of PaCT is a recognition of what the future of nurse education must look like: one where compassion is not only taught, but genuinely understood, deeply felt, and consistently practised