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Impak Sihat: A telehealth system development and feasibility evaluation to empower rural population in Malaysia on the quality use of medicines
Full text linkThe escalating global burden of chronic diseases necessitates innovative approaches to enhance medication adherence and quality use of medicines (QUM), particularly in underserved rural populations. This study developed and evaluated Impak Sihat, a telehealth system tailored to address systemic healthcare barriers in rural Malaysia through a three-phase mixed-methods design. Phase 1 involved qualitative interviews with 15 villagers, revealing smartphone ownership, inconsistent internet connectivity, high social media engagement, and limited critical appraisal of online health information. Phase 2 utilised these insights to create a dual-component system: a public portal with Malay-language educational materials, appointment booking, and a practitioner platform featuring secured patient data management. Phase 3 assessed feasibility via community demonstrations with 77 participants (mean age 53.4 ± 11.8 years), showing high acceptance scores (73-87%) across six domains. Key findings included strong usability (87.0 ± 16.3) and interface design (74.8 ± 23.9), though older adults scored significantly lower on interface design for learnability (ρ=-0.29, p
Bitcoin and crypto-mining stocks: A quantile connectedness approach
Full text linkIn this paper, we studied the extreme connectedness between Bitcoin and crypto-mining stocks using the quantile connectedness approach of Ando et al. (2022). We estimated the connectedness (i.e., the direction and strength of spillover effects) at the median, extreme lower, and extreme upper quantiles. Our results revealed a highly interconnected system, with Bitcoin identified as a net transmitter of shocks. RIOT and MARA also emerged as major net transmitters in the system, while GREE and NILE were net receivers. The spillover effects were more pronounced during extreme market conditions compared to normal conditions. Moreover, the connectedness of the system progressively increased, peaking in 2021 when China banned crypto-mining. The extreme and dynamic connectedness identified in this study offers valuable insights for investors regarding hedging strategies and portfolio allocation, as well as for regulators focused on financial stability and systemic risk
What is Next for Universal Design for Learning?:UDL 3.0 and Implications for Diverse Settings
Full text linkThe Universal Design for Learning (UDL) framework guides educators and instructional designers in planning for learner diversity as a core facet of curricular design. Following an extensive four-year process, a revised UDL 3.0 framework was released in 2024 that expanded considerations for learner diversity and attended to exclusionary systemic biases. This refresh of UDL brought marked changes in guideline language that incorporated complex concepts such as learner identity, intersectionality, learner-centeredness, and interdependence. Through a conversation cafe during the International Conference on Education Quality, global educators dialogued about how they interpret these changes in terms of their understanding of UDL and its implications for inclusive education practice in their local contexts. Participant feedback on the revised framework revealed varied perceptions of the strengths of the UDL 3.0 language and applications for practice in differing settings, such as early years, formal school settings, tertiary education, and alternative education contexts, and potential challenges related to cultural and linguistic differences
A Pilot Feasibility Study Exploring the Preliminary Effectiveness of an AI-Driven Virtual Human Intervention for General Practitioner Obesity Education and Communication-Skills Training
Full text linkBackgroundRising global obesity rates demand effective weight management strategies from general practitioners (GPs). However, time constraints, training gaps, and low confidence often impede GPs' ability to conduct weight-based conversations. This pilot study assessed the feasibility and preliminary effectiveness of an AI-driven Virtual Human (VH) obesity education and communication-skills training tool, specifically designed to address these challenges and enhance obesity education and communication-skills among GPs.MethodsA pilot feasibility study with a pre-post survey design evaluated the impact of the VH tool on knowledge, self-efficacy, empathy toward patients with obesity, and confidence in clinical consultations. Participant perceptions, trust, and intention to use the VH tool were explored. Paired-sample t-tests were conducted to evaluate within-group mean differences. Descriptive statistics were used to evaluate feasibility and acceptability.ResultsA total of 22 GPs were recruited. Despite some attrition, significant improvements were observed in knowledge (p = 0.006), self-efficacy (p = 0.001), and combined empathy and confidence scores (p = 0.002). Alongside these improvements, participants demonstrated positive perceptions of the tool, high trust in the VH, and a strong intention to implement the learned strategies.#ConclusionsThis pilot study demonstrates the potential of an AI-driven VH tool to enhance GP obesity education and communication skills. The observed improvements in key outcomes support the potential of VH technology in medical education on obesity. To further establish the efficacy and explore the broader applicability, future research should focus on larger, controlled trials across various provider groups. Overall, these preliminary observations highlight a promising avenue for enhancing the skills of a wider range of providers in the obesity treatment space
Gender, sexuality, and coloniality: a visual analysis of the women, peace, and security agenda
No full textNutrition, genetics and the ageing brain: data analysis with application of artificial intelligence approaches to investigate brain health outcomes in older adults
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Still Somebody: a photography exhibition on female homelessness at 2 Royal Avenue, Belfast
Full text linkThis exhibition presented the photographic work produced by a group of women experiencing homelessness. Together with Dr Clare Gallagher and Cormac McArt, they explored narratives around home and housing and reflected on their own experiences. The work they produced extends the imagery around homelessness beyond the journalistic and illustrative, and gives creative voice to the underrepresented female experience. The exhibition also showcased new advocacy materials - posters, leaflets and postcards - produced with the women's images and texts written in collaboration with them and these extend the impact of this underrepresented issue
Using virtual reality to capture memories of border life in Northern Ireland
Full text linkBorder Sounds is a virtual reality film created during an outreach project by Northern Ireland’s national archive, PRONI, and creative media centre Nerve Centre in 2021. It features memories from 21 participants aged 20–60s who live near the invisible border line that divides the island of Ireland into two jurisdictions. This article uses Border Sounds as a case study to explore how sound, memory, and immersive technology can be combined to reimagine contested border spaces and to discuss the potential of participatory archives to reflect diverse voices in postconflict Northern Ireland. Through a content analysis of the film’s haiku poems and soundscapes created by the participants and a reflective analysis of the filmmaking process, we examine how borders shape identity and memory, and question whether memory-based projects such as Border Sounds can challenge dominant narratives, promote understanding across divides, and help archives become inclusive, collaborative spaces for diverse voices.</p
Alphaenhancer: A Resource-Aware Game Agent for Single Image Super Resolution for Next-Generation Edge Communication Networks
Full text linkEmbedded resources have been becoming part of the Internet of Things networks, where they are increasingly taking part in various kinds of decision-making using Tiny Machine Learning (TinyML) models. Although offloading the TinyML model for these devices includes removing many layers that have less impact on the overall performance, they often lead to a sacrifice on the overall performance of the model. In this paper, we propose a novel device-aware training strategy to customize the training based on the resources on which the model will be applied. We proposed AlphaEnhancer, a resource-aware game agent for medical image super-resolution. We baseline our approach on the Residual Feature Distillation Model (RFDN) and propose a device efficacy metrics, which is based on the learned actions of the agent. The model with the highest efficacy is deemed appropriate for that particular device. Our preliminary results show that our methods performed significantly well with respect to the baseline and other recent state-of-the-art