19200 research outputs found
Sort by
IARC Workshop on the Key Characteristics of Carcinogens: Assessment of End Points for Evaluating Mechanistic Evidence of Carcinogenic Hazards
No full textBackgroundThe 10 key characteristics (KCs) of carcinogens form the basis of a framework to identify, organize, and evaluate mechanistic evidence relevant to carcinogenic hazard identification. The 10 KCs are related to mechanisms by which carcinogens cause cancer. The International Agency for Research on Cancer (IARC) Monographs programme has successfully applied the KCs framework for the mechanistic evaluation of different types of exposures, including chemicals, metals, and complex exposures, such as environmental, occupational, or dietary exposures. The use of this framework has significantly enhanced the identification and organization of relevant mechanistic data, minimized bias in evaluations, and enriched the knowledge base regarding the mechanisms of known and suspected carcinogens.ObjectivesWe sought to report the main outcomes of an IARC Scientific Workshop convened by the IARC to establish appropriate, transparent, and uniform application of the KCs in future IARC Monographs evaluations.MethodsA group of experts from different disciplines reviewed the IARC Monographs experience with the KCs of carcinogens, discussing three main themes: a) the interpretation of end points forming the evidence base for the KCs, b) the incorporation of data from novel assays on the KCs, and c) the integration of the mechanistic evidence as part of cancer hazard identification. The workshop participants assessed the relevance and the informativeness of multiple KCs-associated end points for the evaluation of mechanistic evidence in studies of exposed humans and experimental systems.DiscussionConsensus was reached on how to enhance the use of in silico, molecular, and cellular high-output and high-throughput data. In addition, approaches to integrate evidence across the KCs and opportunities to improve methodologies of mechanistic evaluation of cancer hazards were explored. The findings described herein and in a forthcoming IARC technical report will support future working groups of experts in reporting and interpreting results under the KCs framework within the IARC Monographs or in other contexts. https://doi.org/10.1289/EHP15389
Enhanced State of Charge Estimation Through Cluster-Based Learning Model: Impact Study on Degradation and Profitability of Second-Life Electric Vehicle Batteries
No full textThe growing adoption of electric vehicles (EVs) presents an opportunity for repurposing end-of-life batteries for second life (SL) applications, such as energy storage systems. However, accurate estimation of the state of charge (SOC) remains critical for optimising battery performance and extending operational life in these applications. This paper presents an in-depth investigation into the impact of advanced SOC estimation on the degradation and profitability of second-life EV batteries, utilising a Cluster-Based Learning Model (CBLM). An empirical degradation model is adapted to quantify how SOC estimation errors influence key battery health metrics, including capacity loss, State of Health (SOH), and energy retention. The study proposes the "energy advantage metric," which quantifies the usable energy retained in SL batteries based on SOC estimation accuracy. Capacity loss analysis across various SL applications demonstrates that the CBLM model significantly reduces battery degradation compared to the Standard Long Short-Term Memory (S. LSTM) model, particularly under deep discharge cycles. These improvements in capacity retention are then translated into economic impact, revealing cost savings ranging from £339 in residential PV systems to over €200,000 in grid-scale energy arbitrage.  T-test confirmed significant differences in degradation performance between CBLM and S. LSTM models, with Cohen’s d effect size showing a small but meaningful effect size for Loss of Lithium Inventory (LLI) (d = 0.24)
Exploring the Dynamics of Inquisitional and Acumenous GBL in Students' Experiences with Mathematics and Statistics
No full textGirls’ empowerment through politics in classrooms: UK National Report
Get PDFThis report presents the development and quasi-experimental and mixed methods evaluation of effectiveness of the Girls Empowerment through Politics in Classrooms (G-EPIC) 5 class programme of lessons designed to increase levels of political selfefficacy of disadvantaged girls. This programme was initially developed in England by Roehampton University and then upscaled and contextualised in Belgium, Czechia, Germany and Denmark.The G-EPIC intervention was designed to increase the political self-efficacy of Year 9 girls in schools with high levels of student deprivation. Political self-efficacy is defined as an individual’s confidence in their capacity to understand and engage in political processes. Addressing the enduring gender gap in political self-efficacy, which is evident in early adolescence and linked to future political participation, is crucial for enhancing gender equality in civic life and responding to current democratic challenges.<br/
Real-Time, Adaptive AI Driven Business Simulation::Design Science Research on a Dynamic Learning Platform
Get PDFThis working paper presents a design science research (DSR) investigation into the development and evaluation of an innovative real-time, adaptive AI-driven business simulation platform. Traditional business simulations typically operate with static scenarios and predefined parameters that fail to capture the dynamic complexity of contemporary business environments. Using a rigorous DSR methodology spanning four design cycles over twenty-four months, we developed and refined a prototype system that integrates machine learning algorithms, natural language processing, and knowledge graph technologies to create dynamically evolving simulation scenarios. The platform was evaluated across diverse contexts including MBA education programmes, corporate strategy training, and entrepreneurial incubators, involving 287 participants across multiple evaluation phases. Our findings demonstrate the system's efficacy in enhancing strategic decision-making capabilities, improving knowledge transfer, and fostering adaptive reasoning skills among users. The paper lays the groundwork for next-generation business education and strategy testing environments that more authentically reflect the complex, evolving nature of real-world business ecosystems
How do fathers make sense of their transition to fatherhood in the perinatal period in the UK
Get PDF
A closer look at the role of nutrition in children and adults with ADHD and neurodivergence
Get PDFThe role of nutrition in Attention-Deficit, Hyperactivity Disorder (ADHD) and other neurodivergent conditions is of growing public and research interest. There is little research reporting vitamin, mineral and omega-3 fatty acid levels in ADHD and brain health. This study presents nutritional and psychological data from a community UK sample of children ( = 47, : 10.1 years) and adults ( = 10, : 29.8 years) with ADHD, autism, dyslexia and other neurodivergent conditions (total = 57). The participants undertook a blood draw which measured a range of vitamins, minerals and omega-3 fatty acids as well as food allergies and food intolerances which were then correlated with psychological symptom scores measuring ADHD symptoms. The key findings, revealed that both children and adults presented with a range of insufficiencies in key nutrients which facilitate neurotransmitter function and, which are deemed as brain-essential, namely omega-3 fatty acids, zinc, B-vitamins and vitamin D. Furthermore, significant relationships were observed between nutrient levels and ADHD symptom severity in the children's group. For example, red blood cell magnesium was negatively correlated with the Conners CI-Parent Rating Scale (CPRS) Disruptive Behavior scores (rho = -0.597, = 0.024). The omega-3 index (sum of EPA + DHA as a percentage of total fatty acids) was negatively correlated with their Learning and Language Disorder scores, (rho = -0.601, = 0.018). Magnesium levels were also associated with overall ADHD symptom severity (rho = -0.612, = 0.02), implying that the greater the severity of ADHD symptoms, the lower the magnesium. This clinical cohort also presented with a range of food intolerances with over 80% of participants presenting with high reactivity scores to cow's milk, other dairy, and casein, and just over half the sample intolerant to wheat and wheat gluten. This is a novel study which presents preliminary data and insights in the role of nutrition in ADHD and neurodivergence. and relationships between nutritional insufficiencies and ADHD-symptoms. It specifically demonstrates a range of food intolerances and relationships between nutritional insufficiencies and ADHD-symptoms, which warrant further exploration in larger case-control groups. [Abstract copyright: Copyright © 2025 Hunter, Smith, Davies, Dyall and Gow.
