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Engineering students and AI in education: aTAM-based study of perceptions, acceptance, and barriers to adoption.
Full text linkArtificial intelligence (AI) is gradually being accepted into education and has the potential of transforming learning and teaching. It is therefore important to understand the perceptions of various stakeholders on the impact of AI in engineering education. This study is framed with the Technology Acceptance Model (TAM) and employs a mixed-method approach to assess the perception of engineering students on the adoption of AI. The quantitative analysis of the survey findings using partial least square structural equation modelling (PLS-SEM), reveals that perceived usefulness and the ease of use has a statistically significant relationship with AI adoption amongst engineering students. Moreover, their attitude towards AI did not influence their intention to use AI in their education. Through the qualitative analysis, the perceived usefulness of AI in personalized learning, solving complex problems, increasing efficiency and solving global problems were highlighted. However, it was noted that wider adoption of AI would be achieved when there are strategies to address the institutional barriers, ethical issues and funding. Another interesting finding is that students raised concern about the potential impairment in their cognitive abilities if they over-rely on AI
Characteristics of supermarket-based interventions to improve the dietary quality and environmental sustainability of diets in people living with obesity, overweight and/or food insecurity in high-income countries: a scoping review.
Full text linkFood insecurity (FI), defined as unreliable access to healthy, nutritious food, is a major health concern in higher-income countries, primarily due to its association with an increased risk of obesity. Supermarket-based interventions may influence population-level food purchasing behaviour, an antecedent to consumption. It is unclear whether there are specific characteristics that these interventions should employ to resonate with vulnerable groups. This scoping review aimed to explore the characteristics of supermarket-based interventions that sought to support healthier and/or more environmentally sustainable food purchasing for people living with obesity, overweight (PLWO/Ow), and/or FI. A systematic literature search, conducted in Medline, Embase, CINAHL, Scopus, and Web of Science databases, identified 35 eligible studies, representing 43 interventions. Title and abstract screening and data extraction were conducted independently by two reviewers. Most interventions focused on supporting the purchase of healthy food items. No study applied a validated measure of FI. Area-level demographic data were used to identify FI related characteristics (i.e., area of low income, low socio-economic status) and in some cases, those living with obesity. Interventions utilised the behaviour change levers of price (n=8), promotion (n=2), placement (n=7), nudges (n=4) and education (n=2), or a combination of these (n=20). High heterogeneity in the way behavioural change levers were operationalised and combined, alongside the use of proxy measures to identify FI and PLWO/Ow, makes it difficult to determine the most supportive intervention characteristics. This presents challenges understanding how to best facilitate changes in purchasing patterns in favour of heathy, sustainable food items in this population
Top priorities for prehabilitation in orthopaedics: a critical research agenda.
No full textThe James Lind Alliance Priority Setting Partnership (PSP) on prehabilitation for hip and knee replacement surgery has identified the top ten research priorities for this field. Endorsed by the National Institute for Health and Care Research (NIHR), the James Lind Alliance brings together patients, carers, and clinicians to co-produce research priorities that reflect real-world needs and experiences of those directly affected. With National Health Service (NHS) waiting lists for hip and knee replacements now exceeding 1.2 million and many patients reporting health states "worse than death", waiting is no longer passive but perilous. In 2024, more than 180,000 primary hip and knee replacements were performed in England and Wales, yet median waiting times still exceed 180 days. For some patients, these delays mean prolonged pain, disability, and loss of independence. For the NHS, they mean escalating demand, growing inequity, and rising costs. Prehabilitation offers the opportunity to turn this lost time into preparation, improving outcomes for patients and efficiency for health systems
Comparison of through thickness residual strain in thermally sprayed coatings onto substrate with grooved surface and flat surface. [Dataset]
No full textThis proposal aims to compare through thickness residual strain in thermally sprayed coatings onto substrate with grooved surface and flat surface with a view to comprehend their tribological performance, as a reduced tensile residual stress at the interface could enhance coatings fatigue life. Shown by previous machining results, a corrugated or grooved surface alters the way tensile stress manifests which will be beneficial to the spraying field which forms the core of this scientific investigation. Reduced tensile residual stress are known to be beneficial to the fatigue life of coatings leading to enhanced tribological performance – which demonstrates wider impact of this investigation
Tailoring durability and tribological stability of PECVD-derived diamond-like carbon films through nitrogen doping .
Full text linkStructural integrity (SI), durability, and tribological stability (TS) of diamond-like carbon (DLC) films deposited on silicon substrates were tailored through nitrogen doping during deposition via radio-frequency plasma-enhanced chemical vapor deposition (RF-PECVD). This approach specifically addresses the challenges of poor adhesion, short lifetime, surface irregularities, and limited wear resistance encountered by DLC coatings in dry sliding environments. Nitrogen flow rates ranging from 0 to 10 sccm were introduced during deposition to modulate bonding structure and surface morphology. At 10 sccm, the nitrogen-doped DLC (N-DLC) films exhibited a uniform, droplet-free surface and suppressed voids achieving 42 % reduction in maximum surface height (Sz), reaching 27 nm and stable average roughness (Ra) of 1 nm. The deposition rate increased significantly from 0.5 to 13 nm/min, resulting in film thicknesses up to 2.3 μm due to enhanced adatom surface mobility. XPS analysis indicated a reduction in sp3 content from 43 % to 28 %, along with an increase in the ID/IG ratio, reflecting a shift toward graphitic sp2 bonding associated with improved self-lubricating behaviour. Although hardness decreased from 28 to 21 GPa, the adhesion strength improved by 73 % from 30 N to 52 N due to interfacial stress relaxation and formation of a silicon carbide interlayer. Under dry sliding conditions, the N-DLC coatings demonstrated negligible wear and ultra-low friction performance with ultra-low coefficient of friction of 0.05. These results demonstrate that N-doping effectively tailors bonding structures and interfacial properties, enhancing N-DLC coatings for MEMS and dry-contact applications
Evaluating for impact: the role of artists in residence in science-land management-community collaboration.
Full text linkThis paper uses a knowledge exchange-based approach to evaluation to explore the reported experiences of artists, scientists, and land managers participating in the 'NaturePLACE Program' (formerly UFS Arts), focusing on the period 2016-2024. The primary aim of the Program is to build understanding of and engagement with urban social-ecological systems through the arts. The approach to this evaluation draws on a range of literature on research in the arts, as well as research and knowledge exchange impact evaluation from the environmental research domain. The evaluation reported in this paper is distinctive in focusing on the interactions of participants rather than on perceptions of beneficiaries. The data analyzed comprises evaluations (n=49) submitted at the conclusion of the residency by six cohorts involved in the NaturePLACE program (2016, 2017, 2018, 2020- 21, 2022-23, 2024-25). This paper provides important insights into the impacts on artists, scientists, and land managers from transdisciplinary place-based work. Causes of impact not previously noted within the framework are identified as related specifically to the arts, including modes of sensuous aesthetic attunement, forms of focusing attention and eliciting public discourse, and shaping cultural imaginaries. Critical reflection also becomes evident as an aspect of capacity building
Roles of activated carbon in fuel cells: a critical review.
No full textFuel cells are widely recognized as a promising clean energy technology due to their high efficiency, low emissions, and potential integration within future sustainable energy systems. However, their widespread commercialization remains hindered by the high cost and limited scalability of main components, particularly platinum-based catalysts, advanced gas diffusion layers, and polymer electrolyte membranes. Despite extensive progress, conventional carbon materials offer limited multifunctionality across these components, highlighting a critical gap in cost-effective and durable material design. This review addresses this gap by focusing on activated carbon (AC) as a sustainable and multifunctional material platform for fuel cells. It critically analyzes the correlations between AC synthesis routes, structural characteristics, and electrochemical behavior that influences the performance in electrodes, gas diffusion layers, and polymer electrolyte membranes. Recent advances including heteroatom doping, hybrid carbon composites, and engineered biochar are systematically discussed to clarify the mechanisms that enhance conductivity, mass transport, and interfacial stability. The review uniquely integrates circular economy and sustainability perspectives, emphasizing biomass valorization and waste-to-carbon strategies. Overall, this work provides a concise and progressive assessment the potential of AC to advance next-generation, low-cost, and environmentally responsible fuel cell technologies aligned with global decarbonization goals, SDG 7 (Affordable and Clean Energy) and SDG 12 (Responsible Consumption and Production)
Mitigating class imbalance in multiclass educational data: a hybrid one-vs-one and density-based resampling approach.
No full textClass imbalance remains a critical challenge in educational data classification, particularly under multiclass settings where multiple majority and minority categories coexist. These issues are especially detrimental when predicting student performance, as standard machine learning models tend to exhibit bias toward dominant classes, resulting in poor detection of underrepresented, yet academically vulnerable, student groups. This paper presents a novel hybrid resampling framework tailored for multiclass educational datasets characterized by severe imbalance and blurred decision regions. The proposed method integrates one-vs-one decomposition to reduce multiclass complexity, a density-aware undersampling strategy to selectively reduce majority instances within high-density regions, and a targeted minority oversampling using Borderline-SMOTE to enhance decision boundary precision. Empirical evaluations conducted on a proprietary dataset of 3,094 undergraduate health sciences students and four benchmark educational datasets demonstrate the method’s superiority over state-of-the-art resampling techniques. The results validate the framework’s efficacy in improving the generalization and fairness of student performance prediction models in imbalanced multiclass educational settings
From plastic waste to pharmaceutical precursors: PET upcycling through ruthenium catalyzed semi‐hydrogenation.
No full textWe report here the upcycling of PET (polyethylene terephthalate) waste via semihydrogenation to make ethyl 4‐(hydroxymethyl)benzoate. The reaction is catalyzed by a ruthenium pincer catalyst at 80 °C in bioderived solvents – a combination of 2‐methyl THF and ethanol. A detailed mechanistic investigation through organometallic and kinetic studies, as well as chemical exchange saturation transfer (CEST) NMR spectroscopy, provides insights into the nature of active species and factors that promote and inhibit the catalytic hydrogenation of PET. Using this mechanistic knowledge, a record high turnover number of >30 000 was achieved for the hydrogenative depolymerization of end‐of‐life PET waste (e.g., bottles and textiles). The semihydrogenation product, ethyl 4‐(hydroxymethyl)benzoate, was utilized to make precursors of various known pharmaceutical drugs, an agrochemical, as well as a new and recyclable polyester. A cradle‐to‐gate life cycle assessment demonstrated that using PET waste as a feedstock for EHMB production significantly reduces the environmental footprint compared to the conventional route from p‐toluic acid
Development of a deep learning-based framework for operational optimisation of municipal solid waste incinerators.
No full textCombustion efficiency of Municipal Solid Waste (MSW) incinerators depends on numerous operational parameters like air flowrates, boiler feedwater temperature, conveyer speed etc. Optimising these operational parameters can lead to higher efficiency, reduce emissions and maximise waste-to-energy conversion however, the complex interdependence of these parameters makes it difficult to identify the optimal conditions on which to run the power plant. In this study, we develop a Deep Learning (DL) based framework to optimise the operation of MSW incinerators. Historical operational data from a 600 tonne/day MSW incinerator has been collected and ranked based on feature importance using Gradient Boosting Decision Trees (GBDT). The dimensionally reduced dataset is used to train a Backpropagation Neural Network (BPNN) model, characterizing highly non-linear relationship between operational parameters and steam production from the MSW incinerator, achieving a mean relative error of 7.79% and prediction accuracy of 92.21%. Finally, Particle Swarm Optimization (PSO) is then employed to optimise the operational parameters. The optimisation process converged within 650 iterations (∼3 min), yielding increase in steam production from 2.7 t/t to 3.11 t/t waste, which is equivalent to 15.2% increase in the thermal efficiency of the MSW incinerator. The proposed DL-PSO framework enables automated optimisation of the operational parameters, minimising dependency on operator experience, providing a novel, practical and computationally efficient tool for enhancing the combustion performance of MSW incinerators and reducing emissions
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