48651 research outputs found
Sort by
Efficient Removal of Phosphate, Nitrate, and Ammonia from Wastewater Using Unmodified Woodchip Biochar
Get PDFExcess nutrients in wastewater pose significant environmental risks, highlighting the need for low-cost treatment strategies that enable their removal. This study evaluated the adsorption capacity of woodchip biochar, a widely available waste material, for phosphate (PO43−), nitrate (NO3−), and ammonium (NH4+) in raw and secondary-treated wastewater, and compared the results against those obtained using synthetic solutions. Approach to equilibrium was reached quicker for NH4+ (≈20 min) than for NO3− and PO43− (≈40 min), with NH4+ removal reaching up to 80% at a dosage of 20 g/L. Nutrient adsorption kinetics were best described by the pseudo-second-order model for the anionic species (NO3− and PO43−), while the pseudo-first-order model provided a better fit for the cationic species NH4+. The Freundlich isotherm provided a good fit to the equilibrium data for all species, indicating the presence of heterogeneous adsorption sites. SEM–EDX and FTIR analyses confirmed nutrient adsorption onto the biochar surface and highlighted the involvement of carboxyl and hydroxyl functional groups, with FTIR showing the greatest spectral changes for NH4+. Adsorption tests using secondary-treated wastewater showed high removal efficiencies (100% PO43−, 25.4% NO3−, 89.5% NH4+), whereas performance in raw wastewater was poor (maximum 32% NH4+). Overall, woodchip biochar demonstrates strong potential as a tertiary treatment material, and its nutrient-saturated form may be reused as fertiliser, supporting nutrient recovery within a circular-economy framework
A quantitative methodology for systemic impact assessment of cyber threats in connected vehicles
No full textThe increasing integration of digital technologies in connected vehicles introduces cybersecurity risks that extend beyond individual vehicles, with the potential to disrupt entire transportation systems. Current practice (e.g., ISO/SAE 21434 TARA) focuses on threat identification and qualitative impact ratings at the vehicle boundary, with limited systemic quantification. This study presents a systematic, simulation-based methodology for quantifying the systemic operational and safety impacts of cyber threats on connected vehicles, evaluating cascading effects across the transport network. Three representative scenarios are examined: (I) telematics-induced sudden braking causing a cascading collision, (II) remote disabling on a motorway (M25) segment, and (III) a compromised Roadside Unit (RSU) spoofing Variable Speed Limit (VSL) and phantom lane closure messages to connected and automated vehicles (CAVs). The results highlight the potential for cascading safety incidents and systemic operational degradation, as evidenced by the defined systemic operational and safety vectors, factors that are insufficiently addressed in the current scope of the ISO/SAE 21434 standard, which primarily focuses on individual vehicle-level threats. The findings underscore the need to incorporate systemic evaluation into existing frameworks to enhance cyber resilience across connected vehicle ecosystems. The framework complements ISO/SAE 21434 by supplying quantitative, reproducible evidence for the impact rating step at a systemic scale, reducing assessor subjectivity and supporting policy and operations, enabling more data-driven evaluations of systemic cyber risks
Diagnosing Breastfeeding Difficulties: Where Do We Stand?
No full textDespite lactation being a natural occurrence in mammals, many structural barriers and individual factors can impact the ability of a woman to breastfeed her newborn. At the individual level, evidence has widely documented several risk factors and societal barriers for impaired lactation, many of which have been steeply increasing in human societies in the past few decades (e.g., psychosocial stress, metabolic disorders, births interventions, etc.). Yet the healthcare system worldwide does not seem to be prepared to support women facing such breastfeeding difficulties. Pregnant women are often provided with unrealistic expectations of how the breastfeeding experience should unfold, which can then translate into negative feelings when they encounter difficulties. In this context, the development of objective diagnostic tools able to help healthcare professionals and women identify breastfeeding difficulties that could then be treated accordingly would seem an ideal solution. Previous studies have tried to provide evidence for the use of milk compositional variations during early lactation as a tool to identify delayed secretory activation of the mammary gland, which often results in impaired lactation. However, despite portable technology for this purpose being successfully developed and/or validated, a consistent research gap remains around the true diagnostic power of such biomarkers in relation to clinically significant outcomes. This obstructs the development of effective diagnostic tools that could be employed in clinical practice to improve breastfeeding outcomes and breastfeeding rates
The Architecture of Trust: A Three-Layered Mathematical Model for Human-Robot Collaboration
Get PDFUnderstanding and modelling how humans develop and maintain trust in robots is crucial for ensuring appropriate trust calibration during Human-Robot Interaction (HRI). This paper presents a mathematical model that simulates a three-layered framework of trust, encompassing dispositional, situational and learned trust. This framework aims to estimate human trust in robots during real-time interactions. Our trust model was tested and validated in an experimental setting where participants engaged in a collaborative trust game with a robot over four interactive sessions. Results from mixed-model analysis revealed that both the Trust Perception Score (TPS) and interaction session significantly predicted the Trust Modeled Score (TMS), explaining a substantial portion of the variance in TMS. Statistical analysis demonstrated significant differences in trust across sessions, with mean trust scores showing a clear increase from the first to the final session. Additionally, we observed strong correlations between situational and learned trust layers, demonstrating the model’s ability to capture dynamic trust evolution. These findings underscore the potential of this model in developing adaptive robotic behaviours that can respond to changes in human trust levels, ultimately advancing the design of robotic systems capable of real-time trust calibration
AI and trusteeship: operational assistance or something more?
No full textIn light of the ‘AI as a fiduciary’ hypothesis, this article refutes the possibility of AI assuming the role of trustee by highlighting the doctrinal limits that constrain its operation in the trust context, particularly those arising from trustee-specific and fiduciary duties. At the same time, it advances a normative argument that AI should be confined to a role of operational responsibility only, given the central importance of trustee discretion and judgment. At its core, this piece is concerned with trustee decision-making and offers practical guidance for the safe and responsible use of AI in trust administration
‘Becoming “hool a-ȝen”: Grains of Integrity and Nourishment in The Book of Margery Kempe’
No full textSustainable eating for all: consumer acceptability of sustainable food consumption
Get PDFFood systems are a key contributor to global greenhouse gas emissions and climate change. Failure to reduce greenhouse gas emissions will have severe consequences for food production, which in turn will directly impact food security, meaning that the most vulnerable members of society will be at an increased risk of malnutrition and undernutrition. Changing the dietary patterns of consumers will be vital in the transition towards food systems that do not degrade the environment but support the nutritional needs and preferences of current and future generations. However, most consumers have resisted recommendations for a more sustainable diet, particularly around meat consumption. Therefore, the overarching aim of this thesis was to examine the factors that influence consumers’ acceptance of more sustainable foods, with a particular focus on meat eaters. Following a comprehensive cross-cultural systematic scoping review, two approaches were taken. Firstly, we showed that food choices were not influenced by the provision of information on the environmental impact of foods and personalised feedback on grocery choices. The second approach examined consumer acceptance of offal; eating more offal can improve the sustainability of meat production by reducing food waste and lowering the number of animals required for food production. We showed that acceptance of offal was significantly higher when included as an ingredient within minced meat, compared to its natural form. Acceptance and expected product characteristics were also found to differ between meals that contained offal. Overall, this thesis highlights that innovative strategies are required to engage meat eaters with sustainability; meat eaters are resistant to dietary change when informed of the environmental impact of their individual food choices, despite having positive attitudes and intentions. Instead, interventions must satisfy other food related values, including superior taste, health benefits, affordability, familiarity and curiosity
Critical success factors, knowledge management, organizational learning, and financial performance in tourism SMEs
No full textThis study investigates which critical success factors enable knowledge management activities in tourism SMEs and how organizational learning mediates the knowledge management-financial performance relationship. Using an online survey of tourism SME managers (n=100, predominantly Finnish), we found that organizational learning fully mediates the relationship between knowledge management activities and financial performance, with no direct effect observed. Human resource management emerged as the most influential critical success factor, followed by strategy, resources, and information technology, while management leadership, culture, and measurement showed no significant effects. These findings extend the knowledge-based view of the firm by establishing organizational learning as the essential mechanism through which knowledge management generates financial returns in tourism SMEs, revealing contextual specificity in critical success factors within the tourism SME context and demonstrating that simplified linear models assuming direct knowledge-performance linkages may not apply universally
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!