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On the road again: Travelling with the artist’s book triennial vilnius
Get PDFSarah Bodman speaks with Lithuanian-based artist Kestutis Vasiliunas, curator of the Artist’s Book Triennial Vilnius as it celebrates its 30th year with a touring exhibition and events programme for its 10th edition, themed: “To Be”. The aim of the Triennial is to promote artists' books and their makers and to build connections with galleries, publishers, printmakers, the public and collectors
Recurrence resonance and 1/f noise in neurons under quantum conditions and their manifestations in proteinoid microspheres
Get PDFRecurrence resonance (RR), in which external noise is utilized to enhance the behaviour of hidden attractors in a system, is a phenomenon often observed in biological systems and is expected to adjust between chaos and order to increase computational power. It is known that connections of neurons that are relatively dense make it possible to achieve RR and can be measured by global mutual information. Here, we used a Boltzmann machine to investigate how the manifestation of RR changes when the connection pattern between neurons is changed. When the connection strength pattern between neurons forms a partially sparse cluster structure revealing Boolean algebra or Quantum logic, an increase in mutual information and the formation of a maximum value are observed not only in the entire network but also in the subsystems of the network, making recurrence resonance detectable. It is also found that in a clustered connection distribution, the state time series of a single neuron shows 1/f noise. In proteinoid microspheres, clusters of amino acid compounds, the time series of localized potential changes emit pulses like neurons and transmit and receive information. Indeed, it is found that these also exhibit 1/f noise, and the results here also suggest RR
A comprehensive review of retrofitted reinforced concrete members utilizing ultra-high-performance fiber-reinforced concrete
Get PDFStrengthening reinforced concrete (RC) buildings is a critical challenge in the construction industry, pushed by the necessity to address aging infrastructure, environmental degradation, and growing use requirements. Ultra-high-performance fiber-reinforced concrete (UHPFRC) is one of the advanced materials that present a viable solution owing to its exceptional durability and mechanical characteristics, which encompass higher compressive and tensile strengths, low permeability, and resilience against intense environmental as chloride ingress, cycles of freeze–thaw, and chemical assaults. This literature review comprehensively examines UHPFRC as a rehabilitation or strengthening mix material for the RC slabs and beams. Experimental key subjects include the influence of bonding techniques, strengthening configurations, steel fiber ratios, UHPFRC thickness, and reinforcing steel within the UHPFRC layer. In addition, the existing numerical and analytical approaches for forecasting the flexural or shear capability of reinforcing concrete structures retrofitted with UHPFRC were examined and critically assessed. Despite the improvements in the RC structures achieved through experiments utilizing UHPFRC as a reinforcement layer, this study highlights some deficiencies in the existing knowledge, such as the absence of effective ways to address debonding, insufficient research on cyclic loading, and the necessity for economical and sustainable strengthening techniques. This review establishes a basis for future research, intending to create an innovative UHPFRC-based strengthening system that mitigates current limits and improves the overall efficacy, performance, and durability of RC structures
What outcomes are important to people with foot and ankle disorders in rheumatic and musculoskeletal diseases? An OMERACT qualitative interview study across four continents
Get PDFThe foot and ankle are frequently affected in rheumatic and musculoskeletal diseases (RMDs), yet there is a lack of high-quality evidence to determine the effectiveness of treatments. Outcomes in research are often inconsistently measured, impeding evidence synthesis. Additionally, clinical decisions are based on research outcomes, but these are not always regarded as important by people with RMDs. This study aimed to determine domains of importance to people with RMDs who have experienced foot and ankle disorders, and aid in developing a standardised core outcome set (COS) to address these issues. Participants from four continents (Europe, Africa, Australia, North America) were recruited to semi-structured interviews through clinical departments and electronic mailing lists. Analysis was conducted using a mixed deductive/inductive approach to the framework method. Patient research partners co-produced the interview schedule and recruitment materials, and co-interpreted results. Fifty-six participants (age range 27 to 76 years; 66 % female), with foot and ankle disorders in a variety of RMDs (including inflammatory arthritis, osteoarthritis, crystal arthropathies, connective tissue diseases), were interviewed. Sixteen domains were described by participants: pain, physical function, fatigue, deformity, skin and nail health, swelling, temperature, numbness, poor circulation, cramping, activities/participation, footwear impact, psychological impact, sleep, healthcare utilisation and personal expenses. Most domains were considered important to participants regardless of RMD or geographic location. Foot and ankle disorders have far-reaching consequences for people with RMDs. This large qualitative study provides a foundation for achieving international consensus on a core outcome set for foot and ankle disorders in RMDs, to improve the quality of evidence demonstrating effectiveness of treatments. [Abstract copyright: Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.
Automatic pre-screening of outdoor airborne microplastics in micrographs using deep learning
Get PDFAirborne microplastics (AMPs) are prevalent in both indoor and outdoor environments, posing potential health risks to humans. Automating the process of spotting them in micrographs can significantly enhance research and monitoring. Although deep learning has shown substantial promise in microplastic analysis, existing studies have primarily focused on high-resolution images of samples collected from marine and freshwater environments. In contrast, this work introduces a novel approach by employing enhanced U-Net models (Attention U-Net and Dynamic RU-NEXT) along with the Mask Region Convolutional Neural Network (Mask R-CNN) to identify and classify AMPs in lower-resolution micrographs (256 × 256 pixels) obtained from outdoor environments. A key innovation involves integrating classification directly within the U-Net-based segmentation frameworks, thereby streamlining the workflow and improving computational efficiency which is an advancement over previous work where segmentation and classification were performed separately. The enhanced U-Net models attained average classification F1-scores exceeding 85% and segmentation scores above 77%. Additionally, the Mask R-CNN model achieved an average bounding box precision of 73.32% on the test set, a classification F1-score of 84.29%, and a mask precision of 71.31%, demonstrating robust performance. The proposed method provides a faster and more accurate means of identifying AMPs compared to thresholding techniques. It also functions effectively as a pre-screening tool, substantially reducing the number of particles requiring labour-intensive chemical analysis. By integrating advanced deep learning strategies into AMPs research, this study paves the way for more efficient monitoring and characterisation of microplastics
Local policies and interventions to reduce a city’s carbon footprint using plant-based diets: Bristol as a case study
Get PDFNet zero strategies are needed to mitigate the effects of the climate emergency. Food systems are responsible for one third of global GhG emissions. This study explores policies and interventions that can be applied at a local level to decarbonise the food system in the UK, using Bristol as a case study. Online elite interviews were conducted with 12 key stakeholders (policymakers, communities, and businesses). Through their lenses, potential interventions were identified that could promote behaviour change and enable a shift towards low-carbon plant-based diets in Bristol. Interventions are presented in an impact-effort matrix and include action on public procurement, community market gardens and food choice architecture. Although stakeholders think these interventions could be impactful, they also identified significant barriers, such as the need for specific subsidies/funding, resistance to change, and misinformation that will need to be overcome for the interventions to be implemented. The discussion provides examples of how each stakeholder group in the study could get involved to address the interventions proposed by the interviewees, concluding that further research is needed to explore the perspective of other key stakeholders (e.g. public) and different layers of governance (e.g. regional) to reach more holistic and comprehensive outcomes
Experiences and perceptions of academic motivation in adolescents with a refugee background: A reflexive thematic analysis
Get PDFLittle previous research exists on academic motivation in refugee adolescents, and none has been conducted in the UK that might help educators to promote motivation and mitigate demotivation in the young people they support. The aim of this study is to help address this gap by exploring experiences and perceptions of academic motivation in refugee adolescents settled in the UK. Semi‐structured interviews were conducted in person or online with three refugee adolescents and six key informants who support the education of refugee adolescents. Data was interpreted by reflexive thematic analysis, which generated three themes: refugee adolescents are striving for stability and security; academic motivation is affected by social and academic relationships; and refugee adolescents are unique individuals with varied educational needs. Of particular note, positive social and academic relationships were found to be motivating, whereas instability in refugee adolescents' lives and negative interactions with teachers were demotivating. The findings also highlight the importance of recognising refugee adolescents' individuality and their unique characteristics, which inform their educational needs and academic motivation
Evaluating the effectiveness of a Roblox video game (Super U Story) in improving body image among children and adolescents in the United States: Randomized controlled trial
Get PDFBody dissatisfaction is a global public health issue negatively impacting young people's mental and physical well-being, underscoring an urgent need to develop early interventions. Emerging evidence suggests that microinterventions are acceptable and effective in delivering mental health interventions. Given the popularity of video games among young people, gaming holds great promise for body image microinterventions. As such, we developed Super U Story, a stand-alone, self-paced, narrative-based adventure video game for the popular gaming platform Roblox grounded in the Tripartite Influence Model of body dissatisfaction and basic tenets of positive body image. This trial evaluated the effectiveness of playing a purpose-built Roblox video game once on US children and adolescents' state and trait body image and related outcomes. Gameplay was capped at 30 minutes. Overall, 1059 US-based girls and boys (n=460, 43.4% girls) aged 9 to 13 years (mean age 10.9, SD 1.36 years) from diverse ethnic, socioeconomic, and geographic backgrounds were recruited online via a research agency into a 3-arm, online, parallel randomized controlled trial. Participants were assigned to an intervention group, active control group (a Roblox game called Rainbow Friends 2 Story [Color Story]), or attention control group (web-based word search). Participants completed self-report assessments at baseline (1 week before the intervention and before randomization), immediately before and after intervention testing, and 1 week after the intervention. Outcomes included state measures of body satisfaction (primary outcome), mood, and body functionality and trait measures of body esteem, body appreciation, internalization of appearance ideals, and social media literacy. Data were evaluated using repeated-measure analysis of covariance controlling for baseline. Engagement and acceptability data were collected. Intervention participants showed improved state body satisfaction (F =5.20; P=.02; η =0.01) relative to the active control but not in comparison to the attention control. State mood, state body functionality, internalization of appearance ideals, and social media literacy showed no effects. Relative to the intervention group, the active control showed improved trait body esteem (F =5.40; P=.02; η =0.01) and body appreciation (F =6.08; P=.01; η =0.01). Exploratory analyses found that age and gender did not moderate the effects. We were unable to examine dose-response effects. Acceptability scores were good. Self-report engagement data suggested that participants experienced a highly variable and often low-dose exposure. This large-scale, fully powered trial is the first to assess the effectiveness of a Roblox-based body image intervention, demonstrating the potential for disseminating microinterventions to children and adolescents on large and popular commercial platforms. Overall, playing Super U Story did not cause harm; however, evidence is lacking to suggest that it improved body image. Learnings are discussed, including psychoeducation as an intervention technique, "chocolate-covered broccoli" phenomena (ie, losing players who recognize thinly disguised educational messages), and measuring intervention engagement. ClinicalTrials.gov NCT05669053; https://clinicaltrials.gov/study/NCT05669053. [Abstract copyright: ©Nicole Paraskeva, Sharon Haywood, Jason Anquandah, Paul White, Mahira Budhraja, Phillippa C Diedrichs, Heidi Williamson. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.07.2025.
Ecosystem-based reservoir computing. Hypothesis paper
Get PDFReservoir computing (RC) has emerged as a powerful computational paradigm, leveraging the intrinsic dynamics of complex systems to process temporal data efficiently. Here we propose to extend RC into ecological domains, where the ecosystems themselves can function as computational reservoirs, exploiting their complexity and extreme degree of interconnectedness. This position paper explores the concept of ecosystem-based reservoir computing (ERC), examining its theoretical foundations, empirical evidence, and potential applications. We argue that ERC not only offers a novel approach to computation, but also provides insights into the computational capabilities inherent in ecological systems and offers a new paradigm for remote sensing applications