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What factors influence the knowledge and attitudes of UK university students towards breastfeeding?
Full text linkBackground Breastfeeding provides substantial benefits for individuals, families, and society, yet rates in the UK remain lower than in comparable countries. Early knowledge and attitudes, formed before pregnancy and breastfeeding experiences, strongly influence future feeding practices. As future parents and societal influencers, university students are a key population for fostering informed attitudes and understanding of breastfeeding. Aim This study assessed breastfeeding knowledge and attitudes among university students, comparing health and non-health disciplines, and exploring associated factors. Methods A cross-sectional survey of 114 students at a UK university was conducted using an online self-administered questionnaire. Convenience sampling recruited participants across health and non-health disciplines. Data were analysed descriptively and inferentially, with regression analyses identifying predictors of knowledge and attitudes. Results Intention to breastfeed was high in both groups. However, students overall had neutral attitudes, and knowledge was at the threshold between low and high. Health students showed significantly greater knowledge and more positive attitudes than non-health students (p < 0.001). Regression analyses indicated that prior breastfeeding education and field of study were the strongest predictors of knowledge and attitudes, while male gender and urban residence were linked to slightly lower knowledge. Discussion Despite high intentions, overall knowledge and attitudes were limited. Findings suggest targeted interventions emphasising breastfeeding education and exposure could improve knowledge and attitudes, supporting informed and confident breastfeeding practices. Conclusion Universities are strategic settings for interventions to enhance breastfeeding knowledge and attitudes in advance of personal experience. Public health strategies should also address social, cultural, and community factors to foster supportive breastfeeding environments
Belief network assessment of fire management in East African savannas under socioeconomic and climate change
Full text linkFire regimes across East Africa's savanna conservation landscapes increasingly reflect interconnected ecological and biocultural breakdown, reinforcing systemic vulnerabilities. Yet colonially inherited fire suppression and exclusionary tenure arrangements continue to overlook the ecological value of pyrodiversity and the stewardship roles of Indigenous and local actors. This study presents a novel probabilistic systems model for evaluating seven predictive, exploratory, and normative fire management approaches across best-, intermediate-, and worst-case socioeconomic–climate futures. The SAV Belief Network (SAV BN) advances BN modelling by explicitly incorporating system complexity and future uncertainty through systemic feedbacks, bidirectional interactions, and high node complexity, supporting rigorous scenario analysis in data-limited contexts. Grounded in empirical data from the Tsavo Conservation Area, the model reflects relational epistemologies that emphasise human–nature interdependencies and place-based knowledge. No approach proved capable of simultaneously achieving wildfire mitigation, ecological integrity, and livelihood resilience. Most reduced wildfire risk and, under best-case trajectories, improved livelihoods; however, even highly normative approaches only slowed, rather than halted or reversed, ecological degradation. Fire suppression and carbon-oriented strategies focused on above-ground biomass accounting intensified ecological decline, particularly under inequitable futures, while locally conceptualised bottom-up strategies failed to confront entrenched colonial legacies and reproduced exclusionary power structures and degradation narratives. These findings highlight the need to reimagine fire regimes as products of multi-scalar, path-dependent dynamics shaped by institutional erosion, political–economic preferences, and contested land claims. Addressing this complexity requires moving beyond ‘integrated’ or ‘community-based’ framings towards historical institutional and environmental justice approaches that centre representation and equity
Designing for Effective Human-XAI Interaction: User Experience Research Plays and Cards
No full textExplainable Artificial Intelligence (XAI) has emerged as a critical field for fostering trust, transparency, and comprehension in human-AI interactions. However, existing XAI systems often fall short of addressing real-world usability challenges, resulting in suboptimal adoption and engagement. This paper applies the User Experience Research Point of View (UXR PoV) playbook to Human-XAI interactions as a case study, i.e., a structured framework designed to guide multidisciplinary teams in creating effective human centered XAI systems. The playbook consists of actionable play cards, organised into three dimensions: Usability Enhancement, Human-Like Enhancement, and Learning Enhancement. Our proposed Human-XAI plays and cards aim to improve the usability and long-term impact of XAI systems by leveraging iterative design principles, interdisciplinary collaboration, and evidence-based practices
Solutions to inequalities in dementia diagnosis and care: A systematic review
Full text linkBackground: People with dementia and their carers often face barriers during diagnosis and accessing post-diagnostic care, causing avoidable inequalities in health outcomes. Without any previous synthesis to date to help improve people with dementia’s health outcomes, the aim of this systematic review was to identify and synthesise existing solutions to increase equity in dementia diagnosis and care.
Methods: A search was conducted across five databases in March 2025. All abstracts and full texts were independently screened by two researchers, with a third researcher sorting through any conflicts. Data were extracted by two public advisor researchers and reviewed by a senior research team member, who synthesised the data into solutions on individual, community, and system and infrastructure levels.
Findings: Forty-three studies (42 from High Income Countries) comprising solutions from 13 countries, were included in this systematic review. The majority of studies focused on access to care, with most solutions centering on system-level change. Only one study was conducted in two middle-income countries. Evidence is diverse and minimal for most types of solutions, with a lack of cost-effectiveness data. There are clear indications for key solutions including dementia link workers, communities of practice and wider networks, as well as one-stop memory clinics providing same day diagnostic assessments in rural countries or regions.
Conclusions: Whilst this review highlights a diversity in solutions, more research needs to be conducted that uses clear measurements of health and social care usage and health economics. Importantly, research needs to be undertaken across different countries, particularly lower- and middle-income countries
Microstructural refinement and intermetallic formation in an Al–5Cu alloy consolidated by high-pressure torsion
No full textBulk Al–5Cu (wt.%) was successfully fabricated from commercial Al and Cu powders at room temperature using high-pressure torsion up to 50 turns. The microstructure near the edge of the disc was heterogeneous with an Al-rich solid solution matrix having an average grain size of ~110±20 nm and regions with lamellae bands in a supersaturated solid solution containing nanosized grains of ~25±5 nm. A partial dissolution of Cu into the Al matrix occurred concurrently with the formation of Al2Cu and Al4Cu9 intermetallic phases. A high microhardness of 200-230 Hv was reached at the edge of the disc. This study demonstrates the ability to engineer a novel Al-Cu system by processing via severe plastic deformation
The evaluation of machine learning models using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF–MS) spectra for the prediction of antibiotic resistance in Klebsiella pneumoniae
Full text linkAntimicrobial resistance in Klebsiella pneumoniae poses a major clinical challenge, driving development in rapid, diagnostic strategies that extend beyond conventional susceptibility testing. Twenty-three studies demonstrate that using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF–MS) spectra to create machine learning (ML) models yields rapid and accurate predictions of antibiotic resistance in K. pneumoniae. Across these studies, most models focused on carbapenem resistance and achieved Area Under the Receiver Operating Characteristic Curve (AUROC) values consistently above 0.90, with ensemble algorithms, particularly Random Forest, XGBoost, and Light Gradient Boosting Machine, and deep learning models such as Convolutional Neural Networks attaining accuracies as high as 97% and even AUROCs reaching 0.99 or higher. Sample sizes ranged from 35 to over 15,000 isolates, reinforcing the robustness of these findings across diverse clinical settings. In addition to high discrimination performance, this evaluation reports that ML models developed using MALDI–TOF–MS spectra shorten diagnostic turnaround from days (48–96 h with conventional methods) to minutes or hours, using existing MALDI–TOF–MS equipment for economical implementation. However, ML diagnostic tools remain constrained by limited external validation, spectra preprocessing protocols, and variability between different MALDI–TOF–MS platforms. These limitations may restrict model generalizability and clinical translation, highlighting the need for standardized workflows and larger multicenter evaluations
Who cares? For whom? How the ethics of care might inform boardroom governance, and beyond
No full textA persistent problem in corporate governance is the defining scope of the fiduciary and other duties of directors of public corporations, private companies, and other organisations that adopt a corporate form. Moreover, over the past three decades, public policy initiatives have sought to foster greater director accountability not just as a solution to the agency problem but also in aid of broader social goals. This push-and-pull of policy can confuse decision-making and for directors pose a version of the famous “trolley problem” in ethics, with the added complication that boards must decide on how to act collectively and not as individuals. This conceptual paper poses the question: Might the ethics of care – sometimes labelled “feminist ethics” – come to the rescue
From margins to mainstream: Understanding the Amazonian Polychrome Tradition Expansion through spatial and chronological modelling
Full text linkThe Polychrome Expansion marks the widespread dispersal of an emblematic ceramic style across much of Amazonia during a period of broad social transformation. Yet the timing and constituent routes for this dispersal are poorly understood, in part due to a lack of dating at many sites. Here, the authors apply computational methods to model the expansion via existing radiocarbon dates, critically examining issues of timing, travel and trade/conflict. The results, they argue, call for a reinterpretation of the Polychrome Expansion as a long-lasting and gradual process that advanced from secondary rivers and spread along main channels, eventually impacting colonial history
Focus Stacking with photogrammetry: An effective workflow for capturing sub-millimeter detail in the photogrammetric digitization of Roman coins
Full text linkConventional photogrammetric methods often struggle with the fine details and delicate features of ancient coins, which are critical for numismatic analysis. This paper presents an effective workflow integrating focus stacking with photogrammetry to enhance the digitization of Roman coins, achieving high-quality sub-millimeter detail. Focus stacking, which combines multiple images taken at different focus points into a single image with extended depth of field, addresses this limitation. By systematically capturing and processing stacked images, our workflow significantly improves the depth and clarity of surface details. We evaluate the workflow’s efficacy through a comparative analysis against established photogrammetric techniques, highlighting substantial improvements in the quality of 3D models and textures. The research includes a step-by-step guide, from image acquisition using varied focal planes to the integration and processing within photogrammetric software. Results demonstrate that our workflow not only preserves the minute features of Roman coins but also facilitates better visual and qualitative analysis for researchers and curators. This advancement paves the way for more detailed and accurate digital representations of numismatic artifacts, contributing to enhanced documentation, study, and preservation of cultural heritage