Search Results (1,075)

With the advancement of low-carbon and sustainable development initiatives, electric scooters, recognized as essential transportation tools and leisure products, have gained significant popularity, particularly among young people. However, the current electric scooter market is plagued by severe product similarity. Once the initial novelty fades for users, the usage frequency declines, resulting in considerable resource wastage. This research collected user needs via surveys and employed the KJ method (affinity diagram) to synthesize fragmented insights into cohesive thematic clusters. Subsequently, a hierarchical needs model for electric scooters was constructed using analytical hierarchy process (AHP) principles, enabling systematic prioritization of user requirements through multi-criteria evaluation. By establishing a house of quality (HoQ), user needs were transformed into technical characteristics of electric scooter products, and the corresponding weights were calculated. After analyzing the positive and negative correlation degrees of the technical characteristic indicators, it was found that there are technical contradictions between functional zoning and compact size, lightweight design and material structure, and smart interaction and usability. Then, based on the theory of inventive problem solving (TRIZ), the contradictions were classified, and corresponding problem-solving principles were identified to achieve a multi-functional innovative design for electric scooters. This research, leveraging a systematic industrial design analysis framework, identified critical pain points among electric scooter users, established hierarchical user needs through priority ranking, and improved product lifecycle sustainability. It offers novel methodologies and perspectives for advancing theoretical research and design practices in the electric scooter domain. Full article

With the advance of digital transformation, the assessment of the environmental impact of digital tools and technologies grows more relevant. Considering the inflated expectations of environmental responsibility in higher education, this study analyses how websites of Polish universities conform to sustainable web design criteria. The sustainability audit employed a methodology encompassing carbon emissions measurement, technical website analysis, and SEO evaluation. The author analysed 63 websites of public universities in Poland using seven independent audit tools, including an original AI Custom GPT agent preconfigured in the ChatGPT ecosystem. The results revealed a substantial differentiation in CO₂ emissions and website optimisation, with an average EcoImpact Score of 66.41/100. Nearly every fourth website exhibited a significant carbon footprint and excessive component sizes, which indicates poor asset optimisation and energy-intensive design techniques. The measurements exposed considerable variability in emission intensities and resource intensity among the university websites, suggesting the need for standardised digital sustainability practices. Regulations on the carbon footprint of public institutions’ websites and mobile applications could become vital strategic components for digital climate neutrality. Promoting green hosting, “Green SEO” practices, and sustainability audits could help mitigate the environmental impact of digital technologies and advance sustainable design standards for the public sector. The proposed auditing methodology can effectively support the institutional transition towards sustainable management of digital infrastructure by integrating technical, sustainability, and organisational aspects. Full article

Introduction and Objectives: Risk-sharing agreements (RSAs) have emerged as a key strategy for financing high-cost medical technologies while ensuring financial sustainability. These payment mechanisms mitigate clinical and financial uncertainties, optimizing pricing and reimbursement decisions. Despite their widespread adoption globally, Latin America has reported limited implementation, particularly for high-cost medical devices. This study aims to share insights from designing RSAs in the form of Outcome Protection Programs (OPPs) for medical devices in Latin America from the perspective of a medical devices company. Methods: The report follows a structured approach, defining key OPP dimensions: payment base, access criteria, pricing schemes, risk assessment, and performance incentives. Risks were categorized as financial, clinical, and operational. The framework applied principles from prior models, emphasizing negotiation, program design, implementation, and evaluation. A multidisciplinary task force analyzed patient needs, provider motivations, and payer constraints to ensure alignment with health system priorities. Results: Over two semesters, a panel of seven experts from the manufacturer designed n = 105 innovative payment programs implemented in Argentina (n = 7), Brazil (n = 7), Colombia (n = 75), Mexico (n = 9), Panama (n = 4), and Puerto Rico (n = 3). The programs targeted eight high-burden conditions, including Coronary Artery Disease, atrial fibrillation, Heart Failure, and post-implantation arrhythmias, among others. Private providers accounted for 80% of experiences. Challenges include clinical inertia and operational complexities, necessitating structured training and monitoring mechanisms. Conclusions: Outcome Protection Programs offer a viable and practical risk-sharing approach to financing high-cost medical devices in Latin America. Their implementation requires careful stakeholder alignment, clear eligibility criteria and endpoints, and robust monitoring frameworks. These findings contribute to the ongoing dialogue on sustainable healthcare financing, emphasizing the need for tailored approaches in resource-constrained settings. Full article

Dynamic and Adaptive solar systems demonstrate a greater potential to enhance the satisfaction of occupants, in terms of indoor environment quality and the energy efficiency of the buildings, than conventional shading solutions. This study has evaluated Dynamic and Adaptive Photovoltaic Shading Systems (DAPVSSs) through a comprehensive analysis of six shading designs in which their energy production and the comfort of occupants were considered. Energy generation, thermal comfort, daylight, and glare control have been assessed in this study, considering multiple orientations throughout the seasons, and a variety of tools, such as Rhino 6.0, Grasshopper, ClimateStudio 2.1, and Ladybug, have been exploited for these purposes. The results showed that the prototypes that were geometrically more complex, designs 5 and 6 in particular, had approximately 485 kWh higher energy production and energy savings for cooling and 48% better glare control than the other simplified configurations while maintaining the minimum daylight as the threshold (min DF: 2%) due to adaptive and control methodologies. Design 6 demonstrated optimal balanced performance for all the aforementioned criteria, achieving 587 kWh/year energy production while maintaining the daylight factor within the 2.1–2.9% optimal range and ensuring visual comfort compliance during 94% of occupied hours. This research has established a framework that can be used to make well-informed design decisions that could balance energy production, occupants’ wellbeing, and architectural integration, while advancing sustainable building envelope technologies. Full article

This study aims to enhance the performance of an innovative steel slag–ceramsite foam concrete (SSCFC) to advance sustainable green building materials. An eco-friendly composite construction material was developed by integrating industrial by-product steel slag (SS) with lightweight ceramsite. Employing a three-factor, three-level orthogonal experimental design at a fixed density of 800 kg/m³, 12 mix proportions (including a control group) were investigated with the variables of water-to-cement (W/C) ratio, steel slag replacement ratio, and ceramsite replacement ratio. The governing mechanisms of the W/C ratio, steel slag replacement level, and ceramsite replacement proportion on the SSCFC’s fluidity and compressive strength (CS) were elucidated. The synergistic application of range analysis and analysis of variance (ANOVA) quantified the significance of factors on target properties, and partial least squares regression (PLSR)-based prediction models were established. The test results indicated the following significance hierarchy: steel slag replacement > W/C ratio > ceramsite replacement for fluidity. In contrast, W/C ratio > ceramsite replacement > steel slag replacement governed the compressive strength. Verification showed R² values exceeding 65% for both fluidity and CS predictions versus experimental data, confirming model reliability. Multi-criteria optimization yielded optimal compressive performance and suitable fluidity at a W/C ratio of 0.4, 10% steel slag replacement, and 25% ceramsite replacement. Full article

In engineering design, optimization is crucial for achieving sustainable goals. This involves creating environmentally responsible structures. Optimizing the design is the first step in reducing the environmental impact of construction. Topology optimization (TO) is one way to do this. TO is the process of designing the material layout in the design domain according to selected criteria. The criteria can be explicitly defined to promote sustainability. As a result, a new structure topology is proposed to make the structure both lightweight and durable, with the aim of improving its functionality and reducing its environmental impact. In optimal engineering design, it is particularly important to take into account the structure’s special operating conditions, e.g., loads subject to random changes. Predicting topologies under such conditions is important since random load changes can significantly affect the resulting topologies. In this paper, an easy to implement numerical method for this kind of problem is proposed. The basic idea is to transform a random loads case into the deterministic problem of multiple loads. A heuristic method of Cellular Automata is proposed as a numerical optimization tool. The examples of topology optimization have been performed to illustrate the concept, confirming the efficiency, versatility, and ease of its implementation. Full article

Natural fiber-based biocomposites are rapidly gaining traction in sustainable manufacturing. However, their supply chain (SC) designs at the feedstock pre-processing stage often lack robust multicriteria decision-making evaluations, which can impact downstream processes and final product quality. This case study proposes a sustainability-driven multicriteria decision-making framework for selecting pre-processing equipment configurations within a hemp-based biocomposite SC. Using a cradle-to-gate system boundary, four alternative configurations combining balers (square vs. round) and hammer mills (full-screen vs. half-screen) are evaluated. The analytical network process (ANP) model is used to evaluate alternative SC configurations while capturing the interdependencies among environmental, economic, social, and technical sustainability criteria. These criteria are further refined with the inclusion of sub-criteria, resulting in a list of 11 key performance indicators (KPIs). To evaluate ranking robustness, a non-linear programming (NLP)-based sensitivity model is developed, which minimizes the weight perturbations required to trigger rank reversals, using an IPOPT solver. The results indicated that the Half-Round setup provides the most balanced sustainability performance, while Full-Square performs best in economic and environmental terms but ranks lower socially and technically. Also, the ranking was most sensitive to the weight of the system reliability and product quality criteria, with up to a 100% shift being required to change the top choice under the ANP model, indicating strong robustness. Overall, the proposed framework enables decision-makers to incorporate uncertainty, interdependencies, and sustainability-related KPIs into the early-stage SC design of bio-based composite materials. Full article

Background: Mobile health applications have emerged as a novel tool to support secondary prevention after myocardial infarction (MI) or percutaneous coronary intervention (PCI). However, the impact of app-based interventions on clinically meaningful outcomes such as hospital readmissions remains uncertain. Objective: To systematically evaluate the effectiveness of smartphone app-based interventions in reducing unplanned hospital readmissions among post-MI/PCI patients. Methods: A systematic search of PubMed was conducted for randomized controlled trials published between January 2020 and April 2025. Eligible studies evaluated smartphone apps designed for secondary cardiovascular prevention and reported on unplanned hospital readmissions. Risk ratios (RRs) and 95% confidence intervals (CIs) were pooled using a random-effects model. Subgroup analyses were performed based on follow-up duration and user adherence. Results: Four trials encompassing 827 patients met inclusion criteria. App-based interventions were associated with a significant reduction in unplanned hospital readmissions compared to standard care (RR 0.45; 95% CI: 0.23–0.89; p = 0.0219). Greater benefits were observed in studies with longer follow-up durations and higher adherence rates. Improvements in patient-reported outcomes, including health-related quality of life, were also documented. Heterogeneity was moderate. Major adverse cardiovascular events (MACEs) were reported in only two studies and were not analyzed due to inconsistent definitions and low event rates. Conclusions: Smartphone applications for post-MI/PCI care are associated with reduced unplanned hospital readmissions and improved patient-reported outcomes. These tools may play a meaningful role in future cardiovascular care models, especially when sustained engagement and personalized features are prioritized. Full article

Lower respiratory tract infections remain a leading cause of morbidity and mortality among Intensive Care Unit patients, with severe cases often progressing to acute respiratory distress syndrome (ARDS). This life-threatening syndrome results from alveolar–capillary membrane injury, causing refractory hypoxemia and respiratory failure. Early detection and management are critical to treat the underlying cause, provide protective lung ventilation, and, eventually, improve patient outcomes. The 2012 Berlin definition standardized ARDS diagnosis but excluded patients on non-invasive ventilation (NIV) or high-flow nasal cannula (HFNC) modalities, which are increasingly used, especially after the COVID-19 pandemic. By excluding these patients, diagnostic delays can occur, risking the progression of lung injury despite ongoing support. Indeed, sustained, vigorous respiratory efforts under non-invasive modalities carry significant potential for patient self-inflicted lung injury (P-SILI), underscoring the need to broaden diagnostic criteria to encompass these increasingly common therapies. Recent proposals expand ARDS criteria to include NIV and HFNCs, lung ultrasound, and the SpO₂/FiO₂ ratio adaptations designed to improve diagnosis in resource-limited settings lacking arterial blood gases or advanced imaging. However, broader criteria risk overdiagnosis and create challenges in distinguishing ARDS from other causes of acute hypoxemic failure. Furthermore, inter-observer variability in imaging interpretation and inconsistencies in oxygenation assessment, particularly when relying on non-invasive measurements, may compromise diagnostic reliability. To overcome these limitations, a more nuanced diagnostic framework is needed—one that incorporates individualized therapeutic strategies, emphasizes lung-protective ventilation, and integrates advanced physiological or biomarker-based indicators like IL-6, IL-8, and IFN-γ, which are associated with worse outcomes. Such an approach has the potential to improve patient stratification, enable more targeted interventions, and ultimately support the design and conduct of more effective interventional studies. Full article

Agricultural development is vital for East Africa’s economic growth, yet the region faces significant disparities and systemic barriers. A critical problem exists due to the lack of an integrated quantitative framework to systematically comparing agricultural capacities and facilitate optimal resource allocation, as existing studies often overlook combined internal and external factors. This study proposes a comprehensive multi-criteria decision-making (MCDM) model to assess, categorize, and strategically profile the agricultural development capacity of 18 East African countries. The method employed is an integrated Entropy-MAIRCA model, which objectively weighs six criteria (the food production index, arable land, production fluctuation, food export/import ratios, and the political stability index) and ranks countries by their distance from an ideal development state. The experiment applied this framework to 18 East African nations using official data. The results revealed significant differences, forming four distinct strategic groups: frontier, emerging, trade-dependent, and high risk. The food export index (C4) and production volatility (C3) were identified as the most influential criteria. This model’s contribution is providing a science-based, transparent decision support tool for designing sustainable agricultural policies, aiding investment planning, and promoting regional cooperation, while emphasizing the crucial role of institutional factors. Full article

This study examines how a visitor-centered approach enhances engagement, participation, and intangible heritage transmission to support cultural sustainability in ethnographic museums. We conducted online and on-site behavioral observations, questionnaire surveys, and in-depth interviews at the She Ethnic Minority Museum to identify gaps in current visitor experience design. We combined the Analytic Hierarchy Process (AHP) with the Contextual Model of Learning (POE) and Emotional Experience Theory (EET) to develop a hierarchical evaluation model. The model comprises one goal layer, three criterion layers (Experience, Participation, Transmission), and twelve sub-criteria, each evaluated across People, Object, and Environment dimensions. Quantitative weighting revealed that participation exerts the greatest influence, followed by transmission and experience. Findings indicate that targeted interventions promoting active participation most effectively foster emotional resonance and heritage transmission, while strategies supporting intergenerational engagement and immersive experiences also play a significant role. We recommend prioritizing small-scale, low-cost participatory initiatives and integrating online and offline community engagement to establish a participatory chain where engagement leads to meaningful experiences and sustained cultural transmission. These insights offer practical guidance for museum practitioners and policymakers seeking to enhance visitor experiences and ensure the long-term preservation and vibrancy of ethnic minority cultural heritage. Full article

The complexity of assessment is a significant problem in designing renewable energy source (RES) products, especially when one wants to take into account their various aspects, e.g., technical, environmental, or social. Hence, the aim of the research is to develop a model supporting the decision-making process of RES product development based on meeting the criteria of quality, environmental impact, and social responsibility (QES). The model was developed in four main stages, implementing multi-criteria decision support methods such as DEMATEL (decision-making trial and evaluation laboratory) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), as well as criteria for social responsibility and environmental impact from the ISO 26000 standard. The model was tested and illustrated using the example of photovoltaic panels (PVs): (i) five prototypes were developed, (ii) 30 PV criteria were identified from the qualitative, environmental, and social groups, (iii) the criteria were reduced to 13 key (strongly intercorrelated) criteria according to DEMATEL, (iv) the PV prototypes were assessed taking into account the importance and fulfilment of their key criteria according to TOPSIS, and (v) a PV ranking was created, where the fifth prototype turned out to be the most advantageous (QES = 0.79). The main advantage of the model is its simple form and transparency of application through a systematic analysis and evaluation of many different criteria, after which a ranking of design solutions is obtained. QES ensures precise decision-making in terms of sustainability of new or already available products on the market, also those belonging to RES. Therefore, QES will find application in various companies, especially those looking for low-cost decision-making support techniques at early stages of product development (design and conceptualization). Full article

There is still a need to develop scenarios and models aimed at substituting fuelwood and reducing the use of fossil fuels such as liquefied petroleum gas (LPG), on which low-income rural households in the Global South often depend. The use of these fuels for cooking and heating in domestic and productive activities poses significant health and environmental risks. This study validated, in three different phases, the sustainability of a model for the production and use of biogas from the treatment of swine-rearing wastewater (WWs) on a community farm: (i) A Multi-Criteria Analysis (MCA), incorporating environmental, social/health, technical, and economic criteria, identified the main weighted criterion to C8 (use of small-scale technologies and low-cost access), with a score of 0.44 points, as well as the Tubular biodigester (Tb) as the most suitable option for the study area, scoring 8.1 points. (ii) Monitoring of the Tb over 90 days showed an average biogas production of 2.6 m³ d⁻¹, with average correlation 0.21 m³ Biogas kg Biomass⁻¹. Using the experimental biogas production rate (k = 0.0512 d⁻¹), the process was simulated with the BgMod model, achieving an average deviation of only 10.4% during the final production phase. (iii) The quantification of benefits demonstrated significant reductions in firewood use: in Scenario S1 (kitchen energy needs), biogas replaced 83.1% of firewood, while in Scenario S2 (citronella essential oil production), the substitution rate was 24.1%. In both cases, the avoided emissions amounted to 0.52 tons of CO_2eq per month. Finally, this study proposes a synthesised, community-based rural biogas framework designed for replication in regions with similar socio-environmental, technical, and economic conditions. Full article

Gobi solar greenhouses (GSGs) enhance energy, food, and financial security in Gobi Desert regions through passive solar utilization. Thermal mass walls are critical for plant thermal comfort in GSGs but can lead to resource waste if poorly designed. This study pioneers the integration of payback period constrains into thermal mass wall optimization, establishing a new performance–cost trade-off approach for GSG wall design, balancing thermal performance and economic feasibility. We quantified energy-conserving benefits against wall-construction costs to derive the optimal inner-layer thicknesses under <25% GSG lifespan payback criteria. Three GSG thermal mass walls in China’s Hexi Corridor were optimized. For the concrete-layered, stone-layered, and pebble-soil walls, the optimum inner-layer thicknesses were 0.47, 0.65, and 1.24 m, respectively, with extra costs of 620.75, 767.60, and 194.56 RMB yuan; annual energy-conserving benefits of 82.77, 102.35, and 51.88 RMB yuan·yr⁻¹; and payback periods of 7.5, 7.5, and 3.75 years. A dynamic thermal load analysis confirmed that GSGs with optimized walls required no heating during a sunny winter solstice night. Cooling loads of 33.15–35.27 kW further indicated the potential to maintain thermal comfort under colder weather conditions. This approach improves plant thermal comfort cost-effectively, advancing sustainable Gobi agriculture. Full article

This article demonstrates how positioning residents as active co-designers fundamentally transforms both the process and outcomes of carbon-positive building development. Through structured collaborative workshops, shared decision-making protocols, and continuous partnership throughout the building lifecycle, the REN+HOMES Positive Carbon Building methodology challenges the conventional expert-driven approach to sustainable construction. Developed and validated through the H2020 REN+HOMES project, this resident-centered approach achieved remarkable technical performance—65.9% reduction in final energy demand—while simultaneously enhancing community ownership and long-term sustainability practices. By integrating participatory design with Zero Emissions Building (ZEB) criteria, renewable energy systems, and national carbon offset programs, the methodology proves that resident collaboration is not merely beneficial but essential for creating buildings that truly serve both environmental and human needs. This research establishes a new paradigm where technical excellence emerges from authentic partnership between residents and sustainability experts, offering a replicable framework for community-driven environmental regeneration. Full article