Search Results (1,716)

Used engine oil (UEO) is a hazardous waste stream that poses significant environmental risks when improperly managed. However, its high heating value makes it a promising candidate for energy recovery. In Kuwait, rising vehicle ownership has led to increasing quantities of UEO, while the power sector remains heavily dependent on conventional fossil fuels. Although extensive research has examined UEO treatment methods and combustion characteristics, limited attention has been given to its integration into utility-scale power-generation systems. This study presents a national-scale techno-economic and environmental assessment of using UEO as a supplementary fuel for electricity generation in Kuwait. East Doha Power Station was selected as a representative case study to evaluate fuel-substitution potential and the practicality of integrating UEO into existing power-generation infrastructure. Historical vehicle-registration data were used to estimate UEO generation, and future availability was projected through 2035 based on vehicle-growth trends. The corresponding thermal energy potential, equivalent electricity generation, fuel-displacement capacity, economic benefits, and environmental impacts were subsequently evaluated. The results indicate that annual UEO generation is projected to increase from approximately 181,800 tonnes/year in 2024 to 303,300 tonnes/year in 2035. This quantity corresponds to about 12,126 TJ/year of recoverable thermal energy and an equivalent electricity-generation potential of approximately 1.1 TWh/year (4000 TJ/year), assuming a power-plant efficiency of 33%. The recovered UEO could displace approximately 311,000 tonnes/year of heavy oil or 287,000 tonnes/year of crude oil, with estimated net annual fuel-cost savings of approximately 28–30 million KD. Based on literature-reported emission factors, UEO utilization could reduce combustion-related CO₂ emissions by up to 19.0% and NO_x emissions by up to 45.5% compared with heavy oil. Sensitivity analysis further confirmed the robustness of the findings under a range of recovery and operating conditions. To the best of the authors’ knowledge, this study represents the first comprehensive national-scale assessment of the potential use of UEO for utility-scale power generation in Kuwait. The findings indicate that UEO has the potential to serve as a strategic secondary energy resource that supports waste reduction, fuel conservation, economic savings, and circular-economy objectives. However, practical implementation will require appropriate collection and treatment infrastructure together with further technical validation, pilot-scale demonstration, and regulatory evaluation. Full article

This paper presents “Quantifying Airline Reputation from Multilingual Online Content: Artificial Intelligence and a Practical Application in a Lightweight Reputation-Intelligence Framework.” Airline reputation is increasingly shaped by multilingual digital narratives that evolve faster than conventional survey cycles, creating a need for timely and interpretable monitoring tools. This study develops and evaluates a lightweight reputation-intelligence framework that integrates brand-safe retrieval, multilingual transformer-based sentiment inference, zero-shot natural-language-inference aspect categorization, TF–IDF/KMeans topic induction, and short-horizon forecasting. The framework formalizes document-level outputs into managerial indicators, including a Net Sentiment Index, polarity shares, aspect scores, topic summaries, and projected sentiment trajectories. On a 3990-document annotated sentiment subset, the multilingual transformer achieved 0.9015 accuracy, 0.9048 macro-F1, 0.9050 weighted-F1, a Cohen’s kappa of 0.8492, and a Net Sentiment Index of 48.5%, while errors were concentrated between adjacent polarity classes. Aspect evaluation showed that supervised in-domain learning substantially outperformed zero-shot inference, clarifying the trade-off between cold-start portability and benchmark accuracy. The results support the framework as a pilot decision-support architecture for airline reputation sensing rather than as a definitive large-scale benchmark. The approach offers scalable and CPU-friendly monitoring capability for airlines, airports, consultants, and public-sector users, while future work should expand multilingual annotation and domain adaptation. Full article

Expansive soils represent a critical challenge in geotechnical engineering due to their significant volumetric changes in response to moisture variations, which cause recurrent structural damage to foundations, pavements and infrastructure. The intensification of wet–dry cycles associated with climate change increases the likelihood of failures, reinforcing the need for more efficient and sustainable stabilization methods. Conventional techniques based on lime or salts present environmental and performance limitations when used independently. This study evaluates a combined approach using sodium chloride (NaCl) and lime sludge (LS), an abundant industrial by-product, to improve the behavior of expansive soils while simultaneously valorizing a difficult-to-manage waste material. Mixtures containing 3%, 6% and 9% NaCl and 5%, 10% and 15% LS were prepared. Atterberg limits, free swell, swelling pressure and infiltration tests were carried out to analyze the response of the treated soil. The results show significant reductions in plasticity and swelling potential: the liquid limit decreased by up to 35%, the plasticity index by up to 36% and the free swell by up to 65% for the optimal combination (9% NaCl + 15% LS). In addition, infiltration increased from 25 to 40 mm, indicating improved hydraulic behavior of the treated soil. The direct reuse of lime sludge prevented its disposal in landfills and reduced the environmental impact associated with its management. Overall, the findings demonstrate that the combination of NaCl and LS is an effective and economical alternative under short-term laboratory conditions, with potential for sustainable application subject to long-term validation for mitigating the swelling of expansive soils. Pilot-scale validation under extreme climatic conditions is recommended to advance toward its integration into resilient infrastructure projects. This approach offers a more efficient, cost-effective, and sustainable technical solution, distinguished by its dual action (chemical and recycling) and its contribution to waste valorization. Future research will focus on validating the method at the pilot scale and assessing its performance under extreme climatic conditions, consolidating its applicability in resilient infrastructure projects. Full article

Post-COVID condition is frequently associated with persistent fatigue, reduced functional capacity, and loss of independence in activities of daily living. Exercise intolerance and post-exertional symptom exacerbation limit participation in conventional rehabilitation programs, highlighting the need for safe and scalable home-based interventions. The REACT-COVID project aims to evaluate the feasibility, safety, and potential effects of a home-based intervention combining whole-body electromyostimulation (WB-EMS) with functional activities of daily living in individuals with post-COVID condition. This study will be a randomized, placebo-controlled, participant-blinded pilot trial including 30 participants allocated to either an experimental group receiving active WB-EMS or a control group receiving sham stimulation over a 12-week period. The primary aim is to assess feasibility, safety, and acceptability. As exploratory clinical outcomes, fatigue severity (Chalder Fatigue Questionnaire, CFQ-11) and functional capacity (Six-Minute Walk Test, 6 MWT) will also be evaluated. Secondary outcomes include handgrip strength and independence in activities of daily living (ADLQ). Assessments will be conducted at baseline (week 0), post-intervention (week 12), and three-month follow-up (week 24). This intervention is designed to provide a low-mechanical-load, accessible alternative for individuals unable to tolerate conventional exercise programs. This study’s findings will inform larger multicenter trials and contribute to scalable rehabilitation models for post-COVID care. Trial registration number: ClinicalTrials.gov (NCT07312357). Full article

Offshore geothermal energy and the reuse of decommissioned oil and gas platforms are emerging as linked pathways for reducing the carbon intensity of marine energy supply while extending the value of mature offshore assets. This review examines offshore geothermal development from a full-chain perspective that connects resource assessment, platform and wellbore reuse, heat extraction, medium- and low-temperature conversion, multi-energy coupling, techno-economic evaluation and environmental risk management. The paper first clarifies the resource logic of offshore geothermal systems, especially sedimentary-basin resources that spatially overlap with mature petroleum provinces. It then analyzes two principal engineering routes: the reuse of existing offshore platforms as energy hubs and the reutilization of abandoned wells as open-loop or closed-loop heat-extraction systems. The review finds that platform and wellbore reuse can reduce drilling demand, shorten offshore construction cycles and lower life-cycle environmental burdens, but engineering feasibility remains constrained by wellbore integrity, thermal losses, corrosion and scaling, platform life extension, regulatory liability and the limited availability of field-scale demonstration data. Coupling geothermal energy with offshore wind power, hydrogen production, OTEC and desalination can improve system stability and equipment utilization; however, standardized assessment boundaries and comparable cost models are still insufficient. Future research should focus on resource-engineering-economic integrated assessment, standardized reuse packages, long-term offshore reliability databases, corrosion-resistant material systems, auditable TEA/LCA models and risk-based regulatory frameworks. This review provides a technical basis for offshore geothermal pilot projects and for the low-carbon transformation of offshore oil and gas infrastructure. Full article

Background/Objectives: Health systems across Europe are increasingly challenged by population ageing, multimorbidity, and persistent inequities in access to care. Community Nursing has emerged as a promising approach to strengthening preventive, community-based services, yet evidence on stakeholder-perceived needs during early implementation remains limited. This study aimed to explore how different types of needs are perceived and articulated during the early implementation of Community Nursing in Austria. Methods: An interpretive descriptive qualitative study was conducted as part of an Austrian Community Nursing pilot project. Semi-structured interviews were carried out with eleven stakeholders, including informal caregivers, network partners (e.g., local healthcare providers), and local political decision-makers. Data were analyzed using qualitative content analysis, guided deductively by Bradshaw’s Taxonomy of Needs and complemented by inductive sub-category development. Interviews were conducted via telephone or video call (Zoom) and ranged from approximately 30 min to an hour. Results: Normative needs reflected expectations for preventive services, continuity of care, advocacy, and sustainable organizational structures. Felt needs centered on trust, emotional security, and relational continuity. Expressed needs became visible through active use of Community Nursing services, including preventive programs, transitional care support, and administrative navigation. Comparative needs highlighted geographic inequities and differences between municipalities with and without access to Community Nursing. Across stakeholder groups, concerns regarding long-term financing and sustainability were prominent. Conclusions: The findings suggest that Community Nursing addresses multiple stakeholder-perceived needs simultaneously, particularly by providing relational, accessible, and preventive support. However, sustained impact depends on stable funding and systemic integration beyond pilot phases. These results offer transferable insights for the development and scaling of community-based nursing models in ageing societies. Full article

Smart-port decarbonisation requires operations-research decision support under day-ahead uncertainty. We present a rolling-horizon Model Predictive Control Energy Management System, formulated as a Mixed-Integer Linear Program with five forecast streams, and benchmark it against a deterministic rule-based controller on an identical configuration. A full-year proof-of-concept at the Port of Ancona (8760 hourly steps over the 2024 Italian Day-Ahead Market, 6.5 MWp PV, 1.0 MWh BESS) combines realised 2024 market, photovoltaic and auxiliary-demand series with a post-AFIR projected cold-ironing demand—the dominant load—and is therefore an operational proof-of-concept rather than a fully metered baseline. The principal MPC outcome is structural: anticipatory dispatch raises the mean BESS state of charge from 13.6% to 46.0% and cuts residence at the minimum SoC from 81% to 6% of hours. The forecasting layer attains sub-7% sMAPE on cold-ironing-loaded demand and 9–18% on the remaining streams (seasonal MASE₂₄ ≤ 0.74 on demand and price streams). At the relay-constrained 0.08 C pilot, the realised savings is 0.44% (€14,463 yr⁻¹; 95% moving-block bootstrap CI [€12,842, €15,742]); benchmarked against an enhanced rule-based controller that is itself permitted price-threshold grid charging, the residual value of predictive optimisation is €5652 yr⁻¹ (0.17%), with the remainder of the gap being the value of enabling grid charging. A C-rate sweep shows the savings doubling to 0.93% at 0.5 C, and a direct 20 MWh/±10 MW simulation yields a €0.57 M yr⁻¹ gross arbitrage savings whose net value, after a realistic battery-degradation penalty, is substantially smaller. Controller-level operational CO₂ rises marginally (+6.2 t, +0.13%), an effect distinct from—and dwarfed by—the system-level cold-ironing decarbonisation. The framework is reproducible in open-source Python (PuLP/HiGHS) from the actual data and is portable to other single-node smart city energy hubs. Full article

Mongolian rangelands face interacting ecological and livelihood pressures, including livestock pressure, vegetation change, soil-carbon dynamics, household income variability, and inefficiencies in livestock by-product recovery. This paper examines whether observed administrative and household data, field-observed pilot-area audit evidence, satellite-derived/backcast vegetation indicators, model-reconstructed ecological trajectories, econometric associations, machine-learning diagnostics, Monte Carlo uncertainty outputs, and scenario-based carbon-finance calculations are consistent with a study-specific ecological–economic feedback framework in Mongolian pastoral rangelands. The analysis combines observed livestock and household data, satellite-derived vegetation indicators, field-anchored soil organic carbon (SOC) information, climate controls, and pilot-area by-product audit evidence in a dual-scale framework comprising nine pasture-user groups in Öndörshireet Soum, Töv Aimag, and a national soum-level panel for 2002–2024. SOC, above-ground biomass (AGB), and below-ground biomass (BGB) trajectories are treated as model-reconstructed series rather than independently observed annual field measurements. Fixed-effects panel models are used to estimate conditional associations, while machine-learning models assess predictive consistency within reconstructed data structures. Under the fitted full specification, the best-performing national-panel model reports an out-of-sample R² of 0.942 for model-reconstructed SOC; this value is interpreted as high internal predictive consistency within the reconstructed SOC panel, not as independent validation of observed annual SOC change. Because the SU/SOC ratio mechanically contains SOC, the full-specification predictive results are subject to leakage risk, and leakage-free validation is needed for a more conservative assessment of predictive performance. Panel estimates suggest that vegetation condition is positively associated with ln(household income), while the by-product waste ratio is negatively associated with ln(income), conditional on fixed effects and model specification. Scenario-based carbon-finance outputs, framed with reference to Verra’s VM0042 Improved Agricultural Land Management methodology, vary materially with compliance, carbon price, weighted average cost of capital, and revenue-sharing assumptions; these outputs are illustrative sensitivity calculations and do not demonstrate VM0042 compliance, project eligibility, project-registration readiness, verified emission reductions, or credit-issuance readiness. The findings are associational, reconstruction-dependent, and scenario-based. They support an analytical framework rather than establish a closed causal loop. Full article

Enhancing urban resilience has become a central objective of sustainable urban development, yet there is limited information on whether urban renewal can effectively contribute to this goal. In this study, we investigated whether urban renewal enhanced urban resilience by exploiting China’s 2017 pilot policy for the renovation projects of old residential communities as a quasi-natural experiment. Drawing on panel data for 286 prefecture-level- and-above cities from 2010 to 2021, we adopted a difference-in-differences method to estimate the causal impact of urban renewal. The results show that urban renewal significantly improves urban resilience, although the overall magnitude of the effect is modest. Mechanism analyses indicate that this effect operates through three interrelated channels: upgraded physical infrastructure, stronger local government attention, and enhanced technological innovation. Heterogeneity analyses further reveal that the resilience effects are stronger in eastern China, larger cities, fiscally stronger cities, and cities located within urban agglomerations. These findings suggest that urban renewal can serve as a meaningful pathway for resilience enhancement, but its effectiveness depends on local institutional and resource conditions. Overall, the study provides city-level empirical evidence of how spatial governance interventions can support the achievement of Sustainable Development Goal 11 and promote more resilient urban development. Full article

Promoting the transition toward green and low-carbon lifestyles is essential for advancing sustainable consumption and environmental sustainability. Based on 6903 valid survey responses from 19 digital household pilot regions in China, this study examines the relationship between household digitalization and green and low-carbon lifestyles. A household digitalization level (HDL) index is constructed using the entropy method across five dimensions: digital network services, digital infrastructure, digital literacy, digital skills, and digital applications. The empirical results show that higher HDL is positively associated with the adoption of green and low-carbon lifestyles, and this association remains robust across a series of sensitivity analyses. Exploratory mechanism analysis indicates that HDL is linked to green and low-carbon lifestyles through improved satisfaction with digital smart technologies and enhanced environmental awareness. Heterogeneity analysis shows that this association is stronger among larger households, urban and suburban households, and households with development-oriented consumption, but weaker among smaller, rural, and subsistence-oriented households. These findings provide micro-level evidence supporting the exploration of the linkage between household digitalization and sustainable household consumption and the coordinated development of digitalization and environmental sustainability. Full article

Background: Sexuality education is essential for adolescent health and well-being, yet in Italy it is not included in a mandatory national curriculum, resulting in heterogeneous implementation across regions. Within the ESPRIT project, a multidisciplinary training-of-trainers (ToT) model was developed to prepare professionals to support school-based peer-education pathways. This study aimed to describe the training model and perform a pilot evaluation of short-term knowledge outcomes among trained participants. Methods: A pilot non-randomized controlled comparative study was conducted within the ESPRIT project framework. A multidisciplinary Training Team developed a structured ToT pathway based on WHO guidance, national recommendations, and peer-education models. Ten advanced public health residents in Hygiene and Preventive Medicine attended a three-day residential training course. One month later, a 10-item knowledge questionnaire was administered to trained participants (n = 10) and untrained advanced public health residents (n = 10). Results: Trained participants achieved higher questionnaire scores than the comparator group (median score 8 [IQR 2] vs. 3.5 [IQR 2]; p < 0.0005). Conclusions: Structured ToT programmes may represent a promising approach for strengthening professional preparation in sexuality education. Larger studies with longer follow-up are needed to evaluate sustainability and real-world implementation. Full article

This study critically addresses the challenge of selecting optimal insulation materials for contemporary, energy-efficient building envelopes, a decision with profound environmental, structural, and occupational health consequences. The paper responds to the growing demand for sustainable, resilient solutions by comparing wool, a bio-based, regenerative material, and expanded polystyrene (EPS), a synthetic polymer widely implemented in the construction industry, and advanced laboratory testing (thermal conductivity, moisture buffering, freeze–thaw resistance) is discussed in a comprehensive synthesis of the recent literature. Also, field evaluations from European retrofits and pilot projects (UK, Denmark, Finland, Iceland, Norway, Sweden, Germany and France) further contextualize performance outcomes, and life cycle impacts are considered. Recent results reveal that wool insulation achieves a moisture buffering value (MBV) between 1.8 and 2.7 (g/m²) % RH, minimal vapor resistance (mvr = 1–2), and preserves functional and structural integrity through more than 100 freeze–thaw cycles, leading to significant stabilization of the interior microclimate and enhanced durability. In contrast, EPS delivers lower thermal conductivity (0.032–0.037 (W/mK), critical for reducing heating/cooling demand, but exhibits limited vapor permeability (lvp = 60–150 MN·s/(g·m)), increased risk of condensation and mold, and reduced compressive strength (<22% after 30 cycles), especially when ventilation details are inadequate. Hybrid envelope systems leveraging both EPS and wool are demonstrated to optimize energy efficiency (up to 23% seasonal savings) and reduce interior humidity fluctuations, while lifecycle and recycling assessments show wool panels to be markedly superior in carbon footprint reduction and circularity. The stratification of insulation layers incorporating wool for vapor and moisture control, and EPS for pure thermal resistance is emerging as best practice in sustainable retrofit and new-build projects. Recommendations highlight the necessity for rigorous laboratory validation, international standards alignment, and integrated material design for robust hygrothermal comfort and environmental performance. The review also covers wool- and EPS-based hybrid composites, showing how natural fibers can improve key mechanical properties without compromising thermal insulation performance or environmental benefits. Full article

This study presents and pilot-tests the Biomimetic Design Education Framework, a structured pedagogical model developed to systematize the translation of biological knowledge into furniture design within studio-based educational contexts. Positioned as a pilot implementation, the study introduces the Biomimetic Transfer Matrix as an accompanying analytical tool for assessing the depth of biological knowledge integration in student design work. It is based on 18 student projects developed during a furniture design course, assessed through qualitative content analysis. The projects were evaluated according to four types of biomimetic transfer: formal, structural, mechanical, and functional/behavioral. Results reveal that structural transfer was the most prevalent category (38.9%), followed by functional/behavioral transfer (33.3%), formal transfer (16.7%), and mechanical transfer (11.1%). This distribution indicates that structured pedagogical guidance can successfully direct students beyond surface-level morphological imitation toward deeper principle-based biological abstraction, while also identifying mechanical and system-based transfer as areas requiring targeted curricular development. On this basis, the study presents the Biomimetic Design Education Framework and introduces the Biomimetic Transfer Matrix as an analytical tool for examining different levels of biomimetic knowledge transfer in design. Results underline the importance of structured approaches to support deeper levels of biological abstraction in design education. The findings contribute to SDG 4 (Quality Education) by advancing evidence-based approaches to biomimetic design instruction. Full article

Background: Electroencephalographic (EEG) functional connectivity analysis requires multiple signal-processing, source-modelling, and statistical steps that can limit its adoption in clinician-led randomised controlled trials (RCTs). NeuroStat was developed as a prototype research tool to integrate this workflow; formal usability validation with clinician end-users has not yet been conducted. Methods: NeuroStat is an open-source Python/PyQt6 desktop application that integrates automated artefact removal (a Generalised Eigenvalue Decomposition for Artefact Identification [GEDAI] pathway and a traditional Artefact Subspace Reconstruction (ASR)/Independent Component Analysis (ICA)/ICLabel pathway), boundary element model (BEM) source localisation using the Desikan–Killiany atlas (68 cortical regions), Phase Lag Index (PLI) connectivity estimation across five canonical frequency bands, and RCT-oriented statistical analysis. Evaluation separated sensor-space and source-space claims: a sensor-level simulation (repeated across five independent random seeds) tested preprocessing robustness, a repeated source-space simulation tested recovery of a known cortical parcel-pair contrast after forward projection and inverse reconstruction, a PhysioNet benchmark tested posterior Desikan–Killiany alpha PLI in 20 healthy adults, and an illustrative application to 20 sessions from a published chiropractic RCT demonstrated real-world workflow applicability. Results: In the sensor-level simulation benchmark, the Traditional pathway achieved a mean absolute error of 0.168 ± 0.017 PLI units and root mean squared error of 0.219 ± 0.045 (mean ± SD across five independent random seeds) across all artefact conditions. In the source-space simulation, reconstructed alpha PLI for the known bilateral lateral-occipital parcel pair exceeded anterior control edges across 60 repeated condition runs (mean known-control difference = 0.105 PLI units, 95% CI 0.096–0.114; t(59) = 22.61, p < 0.001). In the PhysioNet source-space benchmark, posterior Desikan–Killiany alpha PLI was higher during eyes-closed than eyes-open rest (Cohen’s d = 0.85, p = 0.001; 16/20 subjects showing the expected direction) after ICLabel-enabled preprocessing. In the pilot RCT application, all 20 sessions completed processing without manual intervention, with default-mode network alpha PLI showing a pre-to-post change of +0.071 in the intervention group versus +0.015 in the active control group. Conclusions: NeuroStat integrates preprocessing, source-space construction, connectivity estimation, and statistical reporting within a parameter-logged desktop workflow for EEG functional connectivity studies. Current evidence supports initial technical feasibility, sensor-level preprocessing robustness for one pathway in controlled simulations, source-space recovery of a known parcel-level contrast, source-space sensitivity to an expected posterior alpha resting-state contrast, and error-free processing across 20 real RCT sessions in a pilot workflow demonstration. Formal usability testing, test–retest reliability analysis, participant-specific source-model validation, and clinical-population validation remain necessary before clinician-facing or trial-deployment claims can be made. Full article

Industrial water reuse and resource recovery are essential for advancing circular economy principles in water-intensive industries. Despite technological maturity, large-scale implementation continues to lag due to high costs, effluent variability, integration challenges, and weak economic returns. Going beyond technology, this paper critically examines what truly works at scale, why most systems fail, and how to build resilient multi-stream recovery solutions. Drawing on major European demonstration projects (INCOVER, RESURGENCE, MEloDIZER) and recent literature, the paper demonstrates that multi-stream systems significantly outperform single-resource approaches. Success depends less on individual technologies and more on modular design, digital integration, sector-specific adaptation, and supportive governance. The study introduces the Industrial Circular Performance Framework (ICPF) and provides clear, actionable pathways to move from promising pilots to bankable, resilient circular industrial water systems. Full article