Search Results (493)

Buying local food can support local economies, but the factors that drive these purchases in specific retail settings, such as local shops, are still not well understood. Research that considers sustainability alongside factors such as trust and perceived retail access remains limited. This study examines how dimensions of sustainability, trust, and perceived retail access influence purchase intention, using the Theory of Planned Behaviour (TPB). Data were collected via an online survey in Međimurje County, Croatia (n = 303), and analysed using partial least squares structural equation modelling (PLS-SEM), which explained 55% of the variance in purchase intention. The results show that, in addition to attitude, subjective norm, and perceived behavioural control, only the environmental dimension of sustainability significantly influences purchase intention. These findings suggest that consumer decision-making in local shops is more strongly shaped by internal evaluations and perceived environmental benefits than by trust or access. The study provides channel-specific evidence from an intermediated short food supply chain (SFSC) format and shows that the relevance of extended TPB predictors varies across retail contexts. Full article

South Africa’s food system reflects a growing imbalance between nutritionally rich indigenous foods and the increasing dominance of commercially processed alternatives. Despite well documented health, cultural, and environmental benefits, indigenous leafy vegetables and edible insects remain marginal within formal markets and everyday diets. This systematic review synthesised 141 empirical and theoretical studies to examine how household attitudes, consumption behaviours, and market structures interact to shape the role of indigenous foods in South Africa. The review identifies a consistent pattern in which positive perceptions of indigenous foods do not translate into regular consumption. Rural households continue to utilise these foods as part of seasonal and livelihood strategies, while uptake in urban areas remains uneven and context specific. Emerging interest among certain consumer segments highlights potential for product diversification and market development, particularly where indigenous foods are adapted to align with modern preferences. However, this potential is constrained by weak value chain integration, limited standardisation, and the absence of reliable consumption data. These structural limitations restrict both market participation and consumer access, reinforcing the peripheral position of indigenous foods within the broader food system. The findings suggest improving availability, strengthening markets, and enhancing positioning critical for inclusion of indigenous foods in diets. Full article

Effective supply chain planning increasingly requires balancing cost-efficiency with environmental responsibility, particularly as organisations face growing pressure to reduce the carbon footprint of logistics operations. This study develops a mixed-integer linear programming model to optimise inventory and transportation decisions in a multi-echelon distribution network comprising a central warehouse, regional warehouses, and retailers. The model integrates a continuous-review (r,Q) replenishment policy, stochastic demand, safety stock requirements, transportation lead times, and stockout behaviour, enabling a detailed representation of operational dynamics under uncertainty and environmental concerns. Unlike most sustainable inventory models—which typically treat environmental impacts and replenishment control separately or rely on simplified service assumptions—this study provides an integrated framework that jointly embeds (r,Q) policies, stochastic demand, stockouts and distance-based CO₂ metrics within a unified optimisation structure. The model advances prior work by explicitly integrating continuous-review (r,Q) replenishment policies with distance-based CO₂ metrics under stochastic demand, a combination rarely addressed in sustainable multi-echelon inventory models. A multi-objective formulation captures the trade-off between economic performance and CO₂ emissions, allowing the identification of Pareto-efficient strategies that reconcile financial and environmental goals. Reducing emissions by over 90% requires an additional cost of only about 4%, demonstrating that substantial emission reductions can be achieved at relatively low additional cost. The findings offer practical insights for managers seeking to design more sustainable and cost-effective distribution policies, highlighting the value of integrated optimisation approaches in contemporary logistics systems. Full article

A novel graphene-based nanomaterial, trade registered Hastalex^®, has been synthesised and investigated for its application as a 3D scaffold in surgical implantation. Hastalex is developed through the covalent bonding of amine-group-functionalised graphene oxide to the base chemical, poly(carbonate-urea)urethane. The material is under development for medical application including tendon, heart valve, and pelvic implant for prolapse surgery. For successful clinical translation, long-term rheological and chemical stability must be demonstrated and until now no systematic multi-year evaluation has been reported for graphene-poly(carbonate-urea)urethane nanocomposites. The material was synthesised in accordance with the patented formulation and evaluated at 0, 6, 12, and 24 months post-synthesis. Physicochemical properties were assessed using attenuated total reflectance Fourier-transform infrared spectroscopy, scanning electron microscope, contact angle measurements, thermogravimetric analysis, and mechanical analysis with tensile tests. Flow behaviour of Hastalex was evaluated using a rheometer to determine viscosity, shear stress response and impact of temperature changes and ageing on these factors. Hastalex exhibited non-Newtonian, shear-thinning behaviour consistent across all timepoints. Viscosity was found to increase progressively with ageing, attributed not to chemical degradation, but likely due to gradual solvent evaporation and densification of the polymer matrix during storage under ambient conditions. Rheological measurements across increasing temperature regimes revealed a heat-sensitive decrease in viscosity, followed by a reversal of changes beyond ~80 °C—likely due to enhanced solvent evaporation and chain reorganisation. This comprehensive material characterisation supports Hastalex as a promising candidate for bioengineering applications. Full article

The mechanical recycling of styrenic polymers from waste electrical and electronic equipment (WEEE) is often limited by thermomechanical degradation occurring during repeated processing. In this work, the degradation behaviour of acrylonitrile–butadiene–styrene (ABS) recovered from sorted WEEE streams was systematically investigated through multiple extrusion cycles, and the effectiveness of antioxidant stabilization was evaluated. Progressive degradation was assessed by chemical structure, rheological, thermal and mechanical testing, and colorimetric analysis. Repeated processing resulted in increased melt flow, altered viscoelastic behaviour, molecular weight reduction, deterioration of mechanical properties, and discoloration. To mitigate these effects, antioxidant-stabilized compounds were prepared and subjected to identical reprocessing pathways. The addition of antioxidants effectively reduced chain scission, stabilized rheological properties, and limited colour changes during reprocessing. Furthermore, the processability of the optimized recycled ABS is demonstrated through filament extrusion for fused filament fabrication, highlighting its potential for high-value additive manufacturing applications. These results demonstrate that appropriate stabilization strategies can significantly enhance the process stability and recyclability of styrenic polymers from WEEE streams, supporting their use in higher-value applications within a circular economy framework. Full article

The growing environmental impact of textile consumption has intensified the need for efficient post-consumer waste collection systems capable of supporting circular economy transitions. Designing effective logistics systems for textile waste is therefore crucial, and their proper dimensioning requires accurate forecasts of collected volumes. However, textile waste flows are highly heterogeneous and strongly influenced by behavioural factors, making reliable forecasting particularly challenging. This study investigates whether urban textile waste collection can be effectively predicted by combining stable bin-level heterogeneity with time-varying socio-spatial and behavioural indicators. Using panel data generated by a hybrid simulation model for the municipality of Parma, we implemented a fixed-effects econometric framework and compared its performance with traditional benchmarks, including seasonal means and Holt–Winters exponential smoothing. The results demonstrate that incorporating structural heterogeneity across collection points, together with behaviour-related dynamics, enhances prediction accuracy and significantly outperforms traditional univariate time-series approaches, both at the aggregate level (R² ≈ 0.81) and at the bin level (MAE ≈ 25). These findings also support the robustness and generalizability of the proposed panel-data econometric framework, which shows strong potential for application in other urban settings characterized by similar structural and behavioural features. Full article

This work provides a comprehensive exploration of α-olefin polymerization characteristics catalyzed by the classic α-diimine Ni catalyst. The polymerization process exhibited quasi-living behaviour, and a reaction kinetic model for the monomer coordination–insertion process was established. It was observed that the reaction exhibits living polymerization features during the first 10 min, and the coordination–insertion rate constant was determined to be 1.08 L·mol⁻¹·s⁻¹ at 30 °C. The regulation rules for factors including co-catalyst amount, monomer concentration, polymerization temperature, monomer type on the molecular weight, molecular weight distribution and chain structure of poly(α-olefin)s were clarified. The co-catalyst (methylaluminoxane) primarily served to activate the catalyst without inducing a chain transfer effect, suggesting that chain stagnation is likely the primary cause of the deviation from typical living polymerization behaviour. Based on temperature-controlled experiments, the activation energy for the coordination–insertion reaction was calculated to be 28.40 kJ·mol⁻¹ through GPC curve analysis. The kinetic model established in this study, along with the revealed chain branching rules, provides a theoretical foundation for the design of poly(α-olefin)s with novel structures and functions. Full article

Digital Product Passports came with the promise to bring about supply chain transparency. However, since their emergence, several adoption barriers have been identified primarily due to stakeholder disengagement and misaligned incentives. To this end, while regulatory mandates drive compliance, passive information repositories often fail to generate meaningful participation from suppliers and/or consumers. In consideration of this shortcoming, the present work proposes a Digital Product Passport framework enriched by gamification elements as a means of transforming transparency from burden to opportunity and individual motivations to collective transparency goals. In greater detail, the framework addresses supplier reluctance through competitive transparency scoring and value sharing mechanisms and further engages consumers through interactive product journey narratives and impact visualisation. The work contributes to the behavioural design research field by proposing an alternative framework that leverages intrinsic and extrinsic motivation in order to overcome traditional barriers to supply chain transparency. To contextualise these ideas, we provide illustrative scenarios demonstrating how gamification mechanisms could create self-reinforcing feedback loops between suppliers and consumers. Full article

A continuous-time Markov chain framework is developed for service life prediction of building assets, and three formulations are compared: a homogeneous generator, a time-varying generator, and a fractional model. The framework delivers survival, density of absorption time, hazard, and mean time to absorption. For the homogeneous case, state trajectories are computed using matrix exponentials. The time-varying case is solved both by local exponential propagation on a time grid and by direct integration of the Kolmogorov equation. The fractional case is implemented in two independent ways, via a truncated series expansion and via an in-house routine for the Mittag-Leffler function, which also allows the direct evaluation of survival and hazard from the standard fractional relations while avoiding singular behaviour at the origin. This study shows that non-homogeneous rates accelerate deterioration relative to the homogeneous benchmark, whereas fractional dynamics reproduce early-time acceleration followed by a slow decline of the hazard, which is consistent with heavy-tailed survival and longer effective service life. The two fractional solvers provide mutually consistent outputs, which supports the numerical robustness of the approach. The framework is readily applicable to sparse inspection data and short observation windows and provides a transparent basis for comparing modelling assumptions that affect life cycle forecasts used in asset management and maintenance planning. Full article

Canine Cognitive Dysfunction Syndrome (CCDS) is a progressive neurodegenerative disease affecting older dogs that shares many pathological mechanisms with human Alzheimer’s disease (AD). Although it is common in geriatric dogs, CCDS is often underdiagnosed in veterinary medicine. Both CCDS and AD involve a gradual decline in cognitive functions such as memory, learning and executive abilities. From a pathological perspective, dogs with CCDS show brain changes similar to those seen in AD, including cerebral atrophy, loss of neurons and accumulation of amyloid-beta plaques. CCDS is diagnosed by exclusion, meaning that other medical or neurological conditions that could cause similar behavioural signs must first be ruled out. Clinical evaluation mainly relies on structured questionnaires completed by owners. Magnetic resonance imaging is used to confirm cerebral atrophy and, at the same time, to exclude other brain disorders, such as cerebrovascular accidents and neoplasia. Current research focuses on identifying fluid biomarkers, such as amyloid-beta, neurofilament light chain and glial fibrillary acidic protein, to support an early and objective diagnosis. The most effective management combines pharmacological therapy, targeted nutrition and non-pharmacological strategies, including environmental enrichment and behavioural support. Early intervention, ideally during mild cognitive impairment, is crucial to slow disease progression and maintain quality of life. Full article

Singleplex and multiplex real-time PCR-HRM (polymerase chain reaction with high resolution melting), both with specific and non-specific amplicon detection, are used for a wide range of applications, from clinical diagnostics to food authentication. However, their results can be influenced by the quality of the template DNA and composition of the reaction mixture. The methods used for the analysis of these results then influence the conclusions drawn. In this work we present an example from our laboratory practice, where the results of singleplex and multiplex real-time PCR differed, despite using the same reaction conditions, primers and analyzed plant material. We show the influence of a singleplex and multiplex PCR setup on the results, as well as the influence of template contamination on the melting behaviour of amplicons. We also discuss the usefulness of cluster analysis for the clarification of real-time PCR-HRM results which appear unclear when only melting and difference curves or similarity scores are used for the analysis of these results. We provide a discussion of problems which we encountered during an analysis of commercial teas and which should be considered by researchers new to PCR-based analysis of plant material, especially if the studied material is rich in various contaminants. Full article

Medical drone delivery (MDD), defined as the use of uncrewed aerial vehicles to transport medical products, is an emerging technological innovation responding to persistent health supply chain challenges in rural and low-resource settings. Within sub-Saharan Africa, MDD systems have demonstrated large-scale success in improving key health outcomes, health supply chain efficiency, and reductions in medical product stockouts and wastage. However, the existing evidence base on the effectiveness of this technology is dominated by quantitative, performance-based evaluations, with limited emphasis on the community-driven mechanisms that shape such outcomes. Drawing on original qualitative research, this article presents a qualitative secondary analysis (QSA) of interview data collected as part of a larger case study on MDD in Madagascar. The QSA, guided by socio-technical systems theory, analyzes a subset of 18 interviews with 23 community-level stakeholders to understand how MDD affects healthcare services in remote regions of the country. Participants reported that MDD led to downstream healthcare improvements in vaccination coverage and malaria-related health outcomes. These improvements were enabled through four interconnected socio-technical mechanisms: (1) improved medical product availability through the mitigation of geographic and transportation barriers, (2) stabilization of vaccine and cold chain transportation, (3) building trust and healthcare-seeking behaviours through predictable service delivery, and (4) reduced physical, mental, and financial burdens experienced by healthcare workers. A final, cross-cutting theme emphasized was the criticality of MDD program continuity, with participants noting that operation disruptions or withdrawals risked reversing benefits and breaking communities’ trust in the health system. By centering lived realities, perceptions, and social processes, this article bridges the gap between predominantly quantitative evidence on MDD systems and the experiences of the communities they are intended to serve. Full article

Qualification is the evidence-based process through which confidence is established that a component will perform its intended function, in its intended environment, for its intended lifetime, with the required reliability. It is an owner-led activity that defines the type, quantity and quality of data required for codification and for the industrial deployment of components and their structural materials. This paper presents a structured qualification framework and applies it to a fusion machine breeder blanket structure as a representative component. It demonstrates that qualification, rather than material properties alone, dictates the use of fusion structural materials and the deployment of such materials under ASME BPV and AFCEN RCC codes. Current limitations in addressing irradiation synergy, liquid metal corrosion, and joint integrity expose gaps that these codes cannot yet prescribe. Two contrasting structural blanket material case studies: metallic-based ferritic-martensitic steel Eurofer97 and non-metallic-based silicon carbide fibre-reinforced composites (SiC_f/SiC) are used to illustrate the differing evidence requirements for each system type. Industrial scale-up considerations, including alloy specifications, manufacturing readiness, inspection reliability, and supply-chain maturity, are evaluated alongside the need for internationally harmonised datasets and design methodologies. Fusion programmes can use a phased qualification strategy in which early, time-limited operation under controlled conditions builds the evidence needed for codification and scale-up, with the required pre-operation qualification level depending on risk, component criticality and failure consequences, and with the pace of qualification ultimately setting how quickly industry can supply components for commercial fusion. Codification remains essential for commercial deployment because construction codes express codified material behaviour through allowable stresses and permitted fabrication routes, enabling designers to use advanced materials without disclosing proprietary data. In jurisdictions where ASME BPV compliance is mandatory, codification determines whether a material may enter pressure boundary service and must therefore form part of the fusion machine owner’s long-term strategy for deployment. Full article

Yam (Dioscorea rotundata) is a major staple crop in West Africa and plays a central role in regional food security, rural livelihoods, and cultural identity. Its wide ecological adaptation, diverse maturity periods, and in-ground storage capacity make yams critical to seasonal food availability and resilience of smallholder farming systems. Despite its importance, existing yam research has largely emphasized biophysical and agronomic dimensions, with limited integration of the socio-cultural and ecological factors that shape yam-based food systems. This review addresses this gap by synthesizing interdisciplinary knowledge on yam food ecology, focusing on how socio-cultural values, beliefs, behaviours, and interactions influence production, utilization, and sustainability of yam systems. We examine the roles of culture, politics, power relations, gender dynamics, and community organization in structuring yam production and consumption across the West African yam belt. The review further explores the long-standing human–yam relationship and the implications of eroding traditional knowledge for future food system resilience. By adopting a systems and ecological perspective that integrates life and social sciences, this review provides a framework to inform sustainable yam crop improvement, value chain development, and inclusive policy interventions, thereby supporting long-term food security and rural development in West Africa. Full article

To elucidate the mechanisms by which the hydrophobic hydrocarbon chain length of emulsifiers and the surface properties of aggregates influence the adhesive performance at the emulsified asphalt–aggregate interface, this study employed molecular dynamics simulations to construct interface models. Key parameters, including relative concentration, diffusion coefficients, and interfacial adhesion work, were systematically analysed to reveal the intrinsic effects of imidazoline-type emulsifier chain length and aggregate type on interfacial behaviour. The results indicate that increasing the hydrophobic chain length of the emulsifier suppresses the adsorption of emulsified asphalt at the aggregate interface. The diffusion coefficients of both emulsifier and asphalt molecules initially increase and subsequently decrease with chain length, with the non-polar asphalt components (aromatics and saturates) exhibiting greater sensitivity to chain length variations. Moderate extension of the hydrophobic chain enhances interfacial adhesion work, whereas exceeding the optimal chain length reverses this trend, weakening adhesion. Aggregate surface properties exert a significant influence on interfacial behaviour. Compared with the acidic SiO₂ (0 0 1) surface, the basic CaCO₃ (1 0 4) surface exhibits lower peak relative concentrations of emulsified asphalt, reduced sensitivity to variations in emulsifier chain length, lower molecular diffusion coefficients, and stronger interactions with asphalt molecules, resulting in superior interfacial adhesion. This study provides a molecular-level theoretical basis for the targeted design of emulsifier structures and the efficient adaptation of emulsified asphalt to different aggregate systems. Full article