Search Results (2,179)

Municipal solid waste challenges (MSW) and concerns about fossil fuel dependence motivate efforts to recover energy from waste, including refuse-derived fuel (RDF). Techno-economic assessment (TEA) evaluates the feasibility of systems by quantifying investment performance. However, most RDF-TEA studies typically rely on isolated sensitivity analyses. That provides limited insight into interaction effects in emerging markets. This study maps the multivariable feasibility of RDF production from MSW in Ghana under realistic economic conditions. Using a pilot-calibrated case study, the assessment integrates discounted cash flow analysis with response surface methodology–design of experiment (RSM-DoE). A central composite design evaluates interaction effects among operational and economic variables for a system capacity of 2875 tonnes RDF/year. The results indicate economic viability with a net present value (NPV) of USD 892,556.44, a payback period (PBP) of 6.61 years and a levelised production cost (LPC) of USD 18.96/tonne. The RSM models show high explanatory power (R², R²adj, R²pred > 90%). Sensitivity results demonstrate that support mechanisms can significantly reduce LPC and PBP while preserving investment viability. The study quantifies the feasibility thresholds and the support instruments within the RDF design levers. It further provides a transferable framework for assessing deployment and upscaling in emerging markets. The findings highlight the need for structured pricing mechanisms and regulatory support for the long-term sustainability of RDF as an AF. Full article

This study addresses a key limitation in meso-scale discrete element modeling (DEM) of ultra-high performance concrete (UHPC). Most existing DEM frameworks rely on extensive macroscopic calibration and do not provide a clear, transferable pathway to derive contact law parameters from measurable micro-scale properties, limiting reproducibility and physical interpretability. To bridge this gap, we develop and validate a micro-indentation-informed, poromechanics-consistent calibration framework that links UHPC phase-level micromechanical measurements to a flat-joint DEM contact model for predicting uniaxial compression, direct tension, and flexural response. Elastic moduli and Poisson’s ratios of the constituent phases are obtained from micro-indentation and homogenization relations, while cohesion (c) and friction angle (α) are inferred through a statistical treatment of the indentation modulus and hardness distributions. The tensile strength limit (σₜ) is identified by matching the simulated flexural stress–strain peak and post-peak trends using a parametric set of (c, α, σₜ) combinations. The resulting DEM model reproduces the measured UHPC responses with strong agreement, capturing (i) compressive stress–strain response, (ii) flexural stress–strain response, and (iii) tensile stress–strain response, while also recovering the experimentally observed failure modes and damage localization patterns. These results demonstrate that physically grounded micro-scale measurements can be systematically upscaled to meso-scale DEM parameters, providing a more efficient and interpretable route for simulating UHPC and other porous cementitious composites from indentation-based inputs. Full article

The concept of neuroception of psychological safety, rooted in Polyvagal Theory, offers a framework for understanding how individuals perceive safety at a physiological and psychological level. Illness may disrupt this perception and affect bodily regulation, emotional resilience, social connection, and self-compassion. This study aims to explore how experiences of being unwell, across both acute and chronic contexts, affect individuals’ neuroception of psychological safety. Semi-structured interviews were conducted with eleven adult participants aged 20–79, including individuals with both acute and chronic illness experiences. Interview questions were informed by the Neuroception of Psychological Safety and Polyvagal Theory. Data were analysed using reflexive thematic analysis, following Braun and Clarke’s six-step process. Four key themes were identified: dysregulation and the narrowing window of tolerance (reduced emotional resilience and heightened bodily sensitivity); distrust and disappointment (a rupture in bodily and self-trust); responsibility and internalised guilt (moral and emotional burdens around illness and recovery); and illness demands attention and disrupts social connection (withdrawal, emotional depletion, and compromised compassion). Across these themes, participants described a diminished sense of psychological safety when unwell, shaped by both internal physiological changes and altered social dynamics. Illness can profoundly undermine psychological safety by disrupting neurobiological regulation, altering relational engagement, and eroding trust in one’s body and self. These findings highlight the importance of integrating psychological safety principles into models of care, particularly in how individuals experience and recover from illness. Full article

We analyze the time-dependent physical spectrum of a driven Jaynes–Cummings model in which both the two-level system and the quantized cavity mode are subject to coherent classical driving. The time-dependent Hamiltonian is mapped, via well-defined unitary transformations, onto an effective stationary Jaynes–Cummings form. Within this framework, we derive closed-form expressions for the two-time correlation functions of both the atomic and field operators. These correlation functions are subsequently used to evaluate the time-dependent physical spectrum according to the Eberly–Wódkiewicz definition, which properly accounts for finite spectral resolution and transient emission dynamics. We show that the external driving leads to substantial modifications of the atomic spectral response, including controllable frequency shifts and asymmetric line shapes. Importantly, we identify a regime in which the driving parameters are chosen such that the coherent displacement induced in the cavity field exactly cancels out the initial coherent amplitude. In this limit, the system dynamics reduce to that of an effectively vacuum-initialized Jaynes–Cummings model, and the standard vacuum Rabi splitting is recovered. This behavior provides a clear and physically transparent interpretation of the spectral features as arising from coherent field displacement rather than from modifications of the underlying atom–cavity coupling. Full article

Due to the non-convex characteristic of the power system, it may be difficult for power generators to recover costs by following the system operators. Therefore, independent system operators have introduced discriminatory supplementary payments as incentive measures. In this context, convex hull pricing serves as an integrated solution, capable of markedly reducing such additional payouts. For the convex hull pricing problem, we propose a distributed solution method. This algorithm is based on Dantzig–Wolfe decomposition and Benders decomposition. According to the characteristics of different units, the model is decomposed into a master problem and a group of independent subproblems, and the consensus ADMM method is used to solve the master problem. The convex hull pricing problem can still be solved using this method when the data is stored separately or when the independent agents responsible for each unit wish to protect their information privacy. While ensuring the confidentiality of each unit’s information, high-quality solutions can still be obtained with high efficiency. By comparing the numerical results with those of the other three convex hull pricing algorithms, it is evident that our algorithm can obtain high-quality solutions. Full article

Waste electrical and electronic equipment (WEEE) is one of the fastest-growing waste streams globally. Disposable e-cigarettes are among the products that have gained popularity in recent years. Their complex construction and embedded lithium-ion batteries (LIBs) present environmental, safety, and resource recovery challenges. Despite growing research interest, integrated analyses linking material composition with user disposal behavior remain limited. This study is the first to incorporate device-level mass balance, material contamination assessment, battery residual charge measurements, and user behavior to evaluate the waste management challenges of disposable e-cigarettes. A mass balance of twelve types of devices on the Polish market was performed. Plastics dominated in five devices, while non-ferrous metals prevailed in the others, depending on casing design. Materials contaminated with e-liquid residues accounted for 4.4–10.7% of device mass. Battery voltage measurements revealed that 25.6% of recovered LIBs retained a residual charge (greater than 2.5 V), posing a direct fire hazard during waste handling and treatment. Moreover, it was estimated that 7 to 12 tons of lithium are introduced annually into the Polish market via disposable e-cigarettes, highlighting substantial resource potential. Survey results showed that 46% of users disposed of devices in mixed municipal waste, revealing a knowledge–practice gap largely independent of gender or education. Integrating technical and social findings demonstrates that improper handling is a systemic issue. The findings support the relevance of eco-design requirements, such as modular casings for battery removal, alongside the enforcement of Extended Producer Responsibility (EPR) schemes. Current product fees (0.01–0.03 EUR/unit) remain insufficient to establish an effective collection infrastructure, highlighting a key systemic barrier. Full article

The erratic nature, increasing prevalence, and intensity of extreme meteorological phenomena are forcing researchers and farmers to urgently develop adaptation practices to enhance the resilience of agroecosystems to climate change. It is strategically crucial to identify farming systems that have successfully endured recent climatic disturbances and understand the agroecological attributes that enabled them to resist and/or recover from droughts and hurricanes. This paper describes a number of methodologies utilized by Latin American researchers to assess agroecosystem resilience by estimating the vulnerability and the response capacity of selected farming systems to cope with climatic threats. The methodologies utilize a set of socio-ecological indicators that can be easily evaluated in the field, allowing farmers to determine whether their farms can withstand a drought or a major storm and, based on this information, select agroecological practices able to enhance the resiliency of their farms in preparation for future events. The principles and practices of resilience identified on successful, climate-resistant farms can be shared with thousands of producers, facilitating the broader adoption and scaling up of agroecological adaptation strategies. Full article

Climate change has intensified summer drought and high solar radiation in Mediterranean ecosystems, generating abiotic stress that limits the establishment of riparian species. We conducted a nursery experiment to evaluate the effects of two levels of water availability and light intensity on the growth and physiological responses of two native riparian species from Mediterranean Chile: Drimys winteri and Persea lingue. A bi-factorial design combined two irrigation treatments (well-watered and water restriction) and two light intensity levels manipulated through a light protection treatment (20% shade mesh and full light exposure). Water restriction was applied gradually until 15–20% (v/v) substrate moisture, defined as maximum water restriction, followed by rehydration. Morphological variables (height, root collar diameter, and shoot-to-root ratio) and physiological traits (predawn water potential, chlorophyll fluorescence, and electron transport rate) were measured. Growth responses were affected by the light protection treatment, which promoted a significant height growth in both species. Water stress affected the global response of both species but they differed in their post-stress hydraulic recovery: P. lingue fully recovered its predawn water potential, whereas Drimys winteri did not. Our study provides measurable and quantifiable values that demonstrate the sensitivity of these species to water stress. Full article

Shape-memory polymers (SMPs) are a class of smart materials capable of recovering their original shape from a programmed temporary shape in response to external stimuli such as heat, light, or magnetic fields. SMPs have attracted significant interest for biomedical devices and soft robotics due to their large recoverable strains, programmable mechanical and thermal properties, tunable activation temperatures, responsiveness to various stimuli, low density, and ease of processing via additive manufacturing techniques, as well as demonstrated biocompatibility and potential bioresorbability. This review summarises recent progress in the fundamentals, classification, activation mechanisms, and fabrication strategies of SMPs, focusing particularly on design principles that influence performance relevant to specific applications. Both thermally and non-thermally activated SMP systems are discussed, alongside methods for controlling activation temperatures, including plasticisation, copolymerisation, and modulation of cross-linking density. The use of functional nanofillers to enhance thermal and electrical conductivity, mechanical strength, and actuation efficiency is also considered. Current manufacturing techniques are critically evaluated in terms of resolution, material compatibility, scalability, and integration potential. Biodegradable SMPs are highlighted, with discussion of degradation behaviour, biocompatibility, and demonstrations in devices such as haemostatic foams, embolic implants, and bone scaffolds. However, despite their promising potential, the widespread application of SMPs faces several challenges, including non-uniform activation, the need to balance mechanical strength with shape recovery, and limited standardisation. Addressing these issues is critical for advancing SMPs from laboratory research to clinical and industrial applications. Full article

This study presents a modular battery charging system based on a DC–DC buck converter with proportional–integral (PI) control, developed to support hands-on learning in power electronics education. In response to the need for flexible experimental platforms, the system is designed to bridge theoretical concepts of power conversion and control with practical implementation. The proposed setup employs cascaded current and voltage control loops to achieve constant current (CC) and constant voltage (CV) charging modes, while its modular hardware architecture allows modification of key parameters such as inductance, capacitance, and circuit topology. The control algorithms are implemented on a microcontroller, and real-time data acquisition is integrated using the ThingSpeak platform for monitoring system behaviour. Experimental results show that the current control loop recovers to its reference value within approximately 6 ms under abrupt load variations, whereas the voltage control loop settles within approximately 15 ms, demonstrating stable closed-loop performance. In addition, the system successfully charges a 12 V lead-acid battery following a standard CC–CV charging profile. Overall, the proposed experiment kit provides an effective educational platform and a practical basis for further exploration of battery charging strategies and power converter control. Full article

The development of cross-border hydrogen energy value chains involves complex interactions between technological, regulatory, and logistical subsystems. Static assessment models often fail to capture the dynamic response of these coupled systems to external perturbations. This study addresses this gap by proposing the Dual Carbon Cooperation Index (DCCI), a data-driven framework designed to quantify the synergy efficiency of the China–Korea hydrogen ecosystem. We construct a dynamic state estimation model integrating three coupled dimensions—Technology Synergy, Regulatory Alignment, and Supply Chain Resilience—utilizing an adaptive weighting algorithm (Triple Dynamic Response). Based on multi-source heterogeneous data (2020–2024), the model employs Natural Language Processing (NLP) for vectorizing unstructured regulatory texts and incorporates an exogenous signal detection mechanism (GPR). Empirical results reveal that the ecosystem’s composite synergy score recovered from 0.38 to 0.50, driven by robust supply chain resilience but constrained by high impedance in technological transfer protocols. Crucially, the novel dynamic weighting algorithm significantly reduces state estimation error during high-volatility periods compared to static linear models, as validated by bootstrapping analysis (1000 resamples). The study provides a quantitative engineering tool for monitoring ecosystem coupling stability and proposes a technical roadmap for reducing system constraints through secure IP data architectures and synchronized standard protocols. Full article

This study aims to evaluate the reliability and minimal detectable change (MDC) of the 2 min marching test (2MMT) for cardiovascular response, as well as to compare its outcomes with those of the 6 min walk test (6MWT), in youth recovering from post-COVID-19 condition. Forty-four youth with post-COVID-19 condition underwent two assessment sessions, separated by five days, utilizing both the 6MWT and 2MMT to measure cardiorespiratory response parameters. Test–retest reliability was found to be excellent for the 6MWT (ICC = 0.83; MDC₉₅ = 8.06%) and good for the 2MMT (ICC = 0.78; MDC₉₅ = 15.61%) between initial and follow-up measurements. The 2MMT demonstrates good reliability and validity for assessing cardiovascular response in youth with post-COVID-19 condition. The reported MDC values provide clinically meaningful thresholds that enable clinicians to distinguish true changes in performance from measurement error. These findings support the use of the 2MMT as a practical tool for clinical assessment, providing preliminary guidance for interpreting changes in performance. However, longitudinal monitoring of patient progress was not directly assessed in this study. Full article

Background/Objective: Existing abbreviated Geriatric Depression Scales (GDSs), derived via Classical Test Theory (CTT), often sacrifice accuracy for brevity and retain non-specific items. We aimed to develop a minimum-item GDS maintaining diagnostic performance equivalent to the full 30-item scale (GDS30) using Item Response Theory (IRT). Methods: This cross-sectional study employed rigorous 5:5 split-sample cross-validation. Participants included 6525 older adults (aged ≥60 years) from community-based (Korean Longitudinal Study on Cognitive Aging and Dementia) and clinical settings (geropsychiatry clinic). Depression was diagnosed through standardized clinical interviews based on DSM-IV criteria. Two-parameter logistic IRT models estimated item discrimination and difficulty parameters. Sequential item reduction with DeLong tests identified the minimum number of items required to maintain GDS30-equivalent area under the curve (AUC). Results: The 10-item IRT-optimized scale (GDS10-IRT) achieved an AUC of 0.856 (95% CI: 0.809–0.895) in the validation set, showing no significant difference from GDS30 (AUC = 0.883; p = 0.396). Conversely, the 15-item GDS (GDS15) demonstrated significantly lower AUC than GDS30 (p < 0.001) despite having more items. GDS10-IRT achieved a 234% improvement in efficiency ratio (AUC/items) over GDS30. Notably, Item 16 (“feeling downhearted and blue”), identified as the most discriminating symptom (a = 2.53), is absent from the GDS15 but included in GDS10-IRT. Conclusions: IRT-based item selection achieves GDS30-equivalent diagnostic accuracy with only 10 items, outperforming the widely used GDS15. By recovering high-discrimination items excluded by CTT, the GDS10-IRT offers a more efficient, specific screening tool for late-life depression. Full article

Objectives/Background: In this study, we aimed to examine the associations of participation in leisure dance activity with perceived health status, happiness level, and perceptions of leisure, and the relevance of demographic characteristics to these associations. Moreover, we sought to explore ways of revitalizing leisure dance activity. Methods: We used data from the 2022 Korea National Leisure Activity Survey organized by the Korean Ministry of Culture, Sports, and Tourism. The 2022 Korea National Leisure Activity Survey was conducted from September to November 2022. The survey was conducted among 10,046 Koreans aged ≥15 who lived in 17 cities and provinces across the country. The participants were informed about the survey schedule in advance, and interviews were conducted at the participants’ homes using tablet PCs. Random telephone verification was performed on the recovered questionnaires to ensure the accuracy of responses. Questionnaires that passed the first verification were subjected to secondary verification by a computerized program, and questionnaires that did not pass the verification were supplemented and re-examined. The collected data were entered electronically through an encoding process, and only the data that passed the final test were compiled in the multi-stage verification process. The data were analyzed using frequency analysis, chi-squared tests, and multivariate logistic regression analysis. Results: Of the 1004 participants, 655 (6.5%) participated in leisure dance activity. Women, individuals in their twenties and thirties, college graduates or those with lower-level educational qualifications, and unmarried individuals were more likely to participate in leisure dance activities. In addition, leisure dance activities were found to be likely to increase happiness levels and leisure life satisfaction, and leisure expenses were likely to be low. Conclusions: Schools should provide high-quality dance education and enhance the professionalism of physical education teachers in the management of dance classes. This is because dance-related experiences in childhood can increase the likelihood of engaging in dancing in adulthood. Efforts are also needed to increase men’s awareness of and participation in leisure dance activities and to lower barriers to entry. The convergence of dance, games, and technology can make this possible. Full article

The structural vibration of industrial droplet dispensers can be modeled by telegraph-like equations to a good approximation. We reinterpret the telegraph equation from the standpoint of an electric–circuit system consisting of an inductor and a resistor, which is in interaction with an environment, say, a substrate. This interaction takes place through a capacitor and a shunt resistor. Such interactions serve as leakage. We have performed an analytical investigation of the frequency dispersion of telegraph equations over an unbounded one-dimensional domain. By varying newly identified key parameters, we have not only recovered the well-known characteristics but also discovered crossover phenomena regarding phase and group velocities. We have examined frequency responses of the electric circuit underlying telegraph equations, thereby confirming the role as low-pass filters. By identifying a set of physically meaningful reduced cases, we have laid the foundations on which we could further explore wave propagations over a finite domain with appropriate side conditions. Full article