48651 research outputs found
Sort by
A multi-objective framework for predicting public opinion trends on infectious diseases using NSGA-II and interval predictions
Full text linkPredicting public opinion trends during major infectious disease outbreaks is critical for guiding effective public health responses. However, predicting public opinion remains challenging because it is influenced by socio-economic, psychological, and media factors. This paper presents a novel framework for predicting public opinion trends related to significant infectious diseases, with a focus on COVID-19 as a case study. The proposed framework identifies the key factors influencing public opinion development and enables both point and interval predictions. The framework uses information ecology theory and applies the NSGA-II algorithm to select the features that best drive public opinion trends. By incorporating this framework, accurate point forecasts are produced alongside prediction intervals, effectively quantifying the uncertainty inherent in public opinion dynamics. This approach minimizes the quality-driven loss function to generate precise prediction intervals, providing decision-makers with critical insights into public opinion fluctuations during epidemics. The results offer valuable, real-time public sentiment warnings, supporting timely and effective interventions in epidemic prevention and control efforts
An Introduction to Researching Student Lives: Methodological and Theoretical Perspectives
No full textThe last decade has witnessed a flourishing of research on student lives and student experiences around the world, transforming how we see higher education history within its social and cultural context. This introductory article provides a discussion of recent literature and historiographical trends in student histories outlining key methodological approaches. We explore how historians can grapple with the ephemerality of this material, with the shifting constellation of students involved with developing it, and with the variability of archival practices across institutions
Banded mongooses discriminate relatedness and MHC diversity in unfamiliar conspecifics
Full text linkLocal knowledge enhances the sustainability of interconnected fisheries
Full text linkLocal knowledge (LK) refers to the ancestral understanding that Indigenous Peoples and local communities have developed over centuries through trial‐and‐error and hands‐on management of natural resources. LK may provide valuable insights for biodiversity conservation and human well‐being. However, its effectiveness remains under‐explored at large scales, especially where multiple communities manage ecosystems. One example is fisheries, which form complex, interconnected networks where fish move across spatial boundaries between managed areas. Fisheries are critical for food security and income, yet face threats from overharvesting. Fisheries Co‐Management (FCM)—a partnership between local communities and governments—leverages LK. However, the value of LK in designing protection strategies remains unclear. Using a process‐based dynamical model parameterized with empirical data, we evaluated FCM strategies for pirarucu ( Arapaima gigas ) fisheries, which form a metapopulation network of protected and unprotected lakes in the Brazilian Amazon. We combined our metapopulation model with LK, fish biology and network theory to assess how lake protection, fishing quotas and illegal fishing impact pirarucu population abundance at the riverscape scale. By analysing 13 FCM‐protected lakes and 18 unprotected lakes, we contrasted six hypothesis‐driven management strategies against the current one, which is based on LK. In all strategies, protected lakes support higher pirarucu populations and buffer against increased fishing pressure, while unprotected lakes face population collapse due to the lack of fishing regulations. While a strategy that provides the best outcomes in terms of metapopulation persistence was based on pirarucu carrying capacity, the currently applied FCM strategy closely matched its efficacy. Synthesis and applications . Our modelling approach allows managers to compare alternative conservation strategies under different socio‐ecological scenarios, highlighting trade‐offs and guiding investment of effort and resources. While immediately valuable for pirarucu management in the Middle Juruá, the framework scales across tiers of applicability, each requiring progressively greater model adaptation: from supporting FCM in other Amazonian regions (with minimal adjustment), to adaptation for other riverine fisheries and ultimately to broader socio‐ecological systems. In this way, we provide both system‐specific insights and a flexible tool for advancing sustainable management of natural resources across contexts
Enabling Privacy-Preserving and Drop-Out Resilient Federated LLM Fine-Tuning for the Low-Altitude UAV Swarm Networks
Full text linkAdvancement of unmanned aerial vehicle (UAV) swarm networks presents transformative opportunities for low-altitude surveillance, disaster response, and distributed sensing, where federated large language models (LLMs) enable collaborative learning while preserving data privacy, enhance swarm-level situational awareness through decentralized knowledge fusion, and support adaptive decision-making across dynamic low-altitude operational environments. However, federated LLM fine-tuning for UAV swarm networks operating in low-altitude settings faces three unresolved security and practical issues: 1) lack of efficient methods to protect parameter security during uplink/downlink transmission under low-altitude communication constraints; 2) absence of effective mechanisms to handle frequent UAV dropouts caused by low-altitude dynamics that may compromise the robustness of federated LLM systems; and 3) constraints in UAVs’ computing, storage and communication resources under typical low-altitude mission profiles. To address these challenges, this paper proposes a Secure and privacy-preserving federated fine-tuning (SPFF) scheme for low-altitude UAV swarms that enables: efficient and privacy-preserving one-to-many distribution of global parameters for downlink federated fine-tuning; secure and efficient uplink local parameter uploading adapted to low-altitude network conditions; and encrypted-parameter-based global model fine-tuning. The scheme also incorporates an efficient supervised key update mechanism to address UAV dropout issues common in low-altitude operations. Moreover, we design a delegable extensional SPFF (DE-SPFF) scheme that employs proxy re-encryption to allow UAVs to delegate tasks to other drones before exiting the federated fine-tuning process in volatile low-altitude environments, while providing public verifiability for re-encryption operations performed by semi-trusted edge nodes. Formal security proofs demonstrate the security of the proposed schemes under low-altitude threat models. Theoretical analysis and experimental results confirm their superiority and practicality for low-altitude UAV swarm applications
Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
Full text link
Breaking barriers: feasibility of a cluster randomised trial evaluating an instrument for identifying and ameliorating adverse drug reactions
Full text linkObjectives We aimed to investigate the feasibility of a cluster randomised controlled trial (RCT) of the ADRe Profile in UK primary care. The ADRe Profile is a patient monitoring system to identify and address adverse drug reactions (ADR) and ADR-related issues to pre-empt clinical deterioration.Design A preliminary study to test the feasibility of an RCT.Setting General practices (GPs) in South-West Wales, UK.Participants 20 patients aged >64 and prescribed >4 long-term medicines.Interventions Participants reported their health-related problems using the ADRe-Profile. Participants completed the profile independently initially, then with researcher support, capturing vital signs, clinical observations and patient-reported symptoms.Main outcome measures Feasibility was assessed based on recruitment, retention, adherence to protocols, potential for clinical impact and staff costs.Results We recruited two GP practices (0.94% of 213 contacted), and 20 patients aged >64 (51.3% of those approached). Retention was 100%. ADRe Profiles had a 98.29% completion rate, identifying 289 clinical problems, including pain (16 of 20 patients), dyspnoea (10/20), dizziness (8/20), bleeding/bruising (7/20) and falls (4/20). Most problems (90%) and vital signs (78%) recorded on ADRe Profiles were absent from existing patient records. Researchers recommended further investigations (164 instances) and interventions (126 suggestions). Despite the potential for clinical benefits, engagement from clinicians was limited. Cost estimates for ADRe administration ranged from £40 to £73, within the funding available from Health and Care Research Wales.Conclusions An RCT of the ADRe Profile was feasible, despite gatekeeping by clinicians. Recruitment of GP practices was challenging, with <1% of eligible practices participating. In contrast, patient recruitment and retention were successful. ADRe aligns with WHO patient safety goals and could improve healthcare by addressing ADR-related problems proactively in this vulnerable population
The social learning and development of intra- and inter-ethnic sharing norms in the Congo Basin
Full text linkCompared to other species, the extent of human cooperation is unparalleled. Such cooperation is coordinated between community members via social norms. Developmental research has demonstrated that very young children are sensitive to social norms, and that social norms are internalized by middle childhood. Most research on social norm acquisition has focused on norms that modulate intra-group cooperation. Yet around the world, multi-ethnic communities also cooperate, and this cooperation is often shaped by distinct inter-group social norms. In the present study, we investigated whether intra-ethnic and inter-ethnic social norm acquisition follows the same, or distinct, developmental trajectories. Specifically, we worked with BaYaka foragers and Bandongo fisher-farmers who inhabit multi-ethnic villages in the Republic of the Congo. In these villages, inter-ethnic cooperation is regulated by sharing norms. Based on our ethnographic knowledge of the participating communities, we predicted that children’s intra-ethnic sharing choices would match those of adults at an earlier age than their inter-ethnic sharing choices. To test this prediction, children (5–17 years) and adults (17 + years) participated in a modified Dictator Game to investigate the developmental trajectories of children’s intra- and inter-ethnic sharing choices. Contrary to our prediction, both intra- and inter-ethnic sharing norms were acquired in middle childhood. Interviews with adult participants suggested that intra- and inter-ethnic sharing norms are acquired from multiple sources, including parents and peers. Further, Bandongo adults primarily reported learning sharing norms via Instruction, whereas BaYaka adults primarily reported learning via Observation/Imitation. These cross-cultural differences may reflect variation in norm complexity. Together, these findings suggest that when social contexts regularly expose children to out-group collaboration, inter-ethnic norms are acquired at similar timelines to intra-ethnic ones, as part of children’s broader cooperative repertoire
Entropy‐Driven Design of Stable High‐Performance Sodium‐Ion Battery Cathodes
Full text linkSodium‐ion batteries (SIBs) are emerging as a viable and cost‐effective alternative to lithium‐ion batteries, benefiting from sodium's high terrestrial abundance. However, their practical application is limited by rapid capacity fading stemming from structural instability during cycling and intrinsically sluggish Na + diffusion kinetics. High‐entropy materials (HEMs), through configurational entropy maximization and multi‐cation synergy, provide a promising strategy to stabilize structures and enhance the energy of SIB cathodes. This review focuses on the structural and chemical principles of key SIB cathodes—layered oxides and Prussian blue analogs—and critically evaluates high‐entropy engineering strategies to performance enhancement. Mechanistic insights into entropy‐driven performance enhancement are analyzed alongside current challenges and future research directions. The high‐entropy strategy offers significant flexibility in cathode design, potentially overcoming conventional material limitations and accelerating commercialization. Although in its nascent stages, requiring extensive fundamental investigation, this analysis aims to guide the development of next‐generation entropy‐stabilized cathodes and advance SIB technologies
Data sources:
Access Repository Dashboard
Do you manage Swansea University Cronfa? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!