Search Results (2,020)

Ionic liquids (ILs) are salts that are liquid at or below 100 °C. They are composed entirely of ions and have unique properties like negligible vapor pressure, high thermal stability, and tunable structures. These characteristics make them a promising alternative to traditional, often volatile and toxic organic solvents in the petrochemical industry. They have broad applications in chemical and petrochemical industry processes. Ionic liquids may be applied in the following processes: desulfurization, benzene toluene xylene (BTX) separation, alkylation, and carbon capture units. Two different ionic liquid-based process configurations have been evaluated for BTX separation. It has been found that the process configuration working with 1-ethyl-3methylimidazolium tricyanomethanide ([emim][TCM]) reduces the energy costs and capital expenditures associated with the Morphylane process by 67 and 63%, respectively. It also reduces solvent costs, confirming it as a cleaner alternative. The hydrodesulfurization (HDS) process is operated under harsh conditions, such as high temperature and high pressure and the requirement of a noble catalyst and hydrogen. High-Temperature Hydrogen Attack (HTHA) failure occurs at high temperatures between the gaseous molecular hydrogen contained inside the steel pressure vessel and the carbon atoms located in the steel matrix or in carbides. Methane molecules are produced during this reaction. This phenomenon can consequently lead to a loss of mechanical properties due to surface decarburization and to the formation of defects caused by methane bubbles mainly located at grain boundaries. The application of ionic liquids (ILs) in oil refineries offers significant advantages, such as safety, environmental sustainability, and process efficiency, primarily by serving as versatile alternatives to hazardous traditional solvents and catalysts. Across BTX extraction, carbon capture, and desulfurization/HDS-adjacent service, the recurring barriers are high viscosity, difficult regeneration, solvent cost/inventory and uncertain long-term stability. Full article

Background: The management of diabetic foot disease and knee osteoarthritis (OA) with smart orthotics holds significant importance during the early stages of these conditions, given their potential consequences, including functional impairment, chronic pain, and economic burden. Real-time monitoring of plantar foot pressure enables early detection of abnormal force distribution and gait biomechanics, allowing for the redirection of forces away from affected ulcers or arthritic joints. This is the first systematic review to synthesise clinical evidence for smart orthotics technology with real-time plantar pressure sensor biofeedback across both diabetic foot ulcer prevention and knee osteoarthritis management simultaneously. A search of the PROSPERO register confirmed no existing registration covers this specific combination. Objectives: To examine the clinical evidence for the use of standard and smart orthotics in the prevention and management of diabetic foot ulcers (DFUs) and knee OA, and to evaluate their impact on plantar pressure redistribution, ulcer recurrence, pain, biomechanics, and economic burden. Eligibility criteria: Studies published in English involving human adult participants (≥18 years) with a clinical diagnosis of diabetes mellitus (at risk of DFU or with peripheral neuropathy) or knee OA, where the intervention involved any orthotic device or smart/intelligent insole with clinical outcomes reported, were included. Studies on healthy individuals only, those not reporting participant age, and non-weight-bearing protocols not differentiated from weight-bearing were excluded. Information sources: Five databases were searched: CINAHL (EBSCO Information Services, Ipswich, MA, USA), PubMed Advanced (National Library of Medicine, Bethesda, MD, USA), Wiley Online Library (John Wiley & Sons, Hoboken, NJ, USA), Cochrane Library (Cochrane Collaboration, London, UK), and Google Scholar (Google LLC, Mountain View, CA, USA). Searches were completed in May 2026. Methods: We conducted a comprehensive literature review. This review was structured and reported with reference to the PRISMA 2020 statement (Preferred Reporting Items for Systematic Reviews and Meta-Analysis; University of Ottawa, Ottawa, ON, Canada) to guide transparency of reporting. It does not constitute a full Cochrane-style systematic review; risk of bias assessment was applied to key included studies and GRADE (Grading of Recommendations Assessment, Development and Evaluation; McMaster University, Hamilton, ON, Canada) certainty ratings were applied informally and narratively rather than as formal per-outcome evidence profiles. Five databases were searched yielding 92,637 records. After removal of 398 duplicates by Rayyan, 92,239 records remained. A subsequent automated keyword-based relevance filter applied within Rayyan (Rayyan AI, Doha, Qatar), prior to human screening, excluded 84,572 records that did not contain any terms related to orthotics, diabetic foot, or knee osteoarthritis, yielding 7667 records for human title/abstract screening. A narrative synthesis approach was adopted owing to the heterogeneity of study designs and outcome measures across included studies, which precluded meta-analysis. This review was not prospectively registered. A complete list of all 78 included studies, including those not individually discussed in the results and discussion. Results: The available clinical studies report promising findings for orthotics and smart orthotics in pain reduction, ulcer prevention, and potential reduction in economic burden, though conclusions are limited by small sample sizes, heterogeneity, and predominantly open-label designs. Recent research found that orthotics can be used to alter the gait pattern that influences knee OA by reducing excessive force on the affected joint. A randomised controlled trial demonstrated an 80% relative risk reduction in DFU recurrence (RR = 0.20; 95% CI: 0.06–0.79; p = 0.022), with absolute event rates of 6.3% in the intervention group versus 30.8% in controls (ARR = 24.5%); a second trial reported a 71% reduction in ulcer incidence over 18 months; and a third randomised controlled trial demonstrated statistically significant plantar pressure reduction (p < 0.01) in patients with diabetic neuropathy. Conclusions: The available evidence suggests that orthotics may be associated with improved pressure redistribution, reduced ulcer incidence, and benefit in the management of knee OA. Although the number of studies directly comparing smart orthotics with standard orthotics remains limited, the limited comparative studies suggested that smart orthotics showed promising results in reducing ulcer incidence, providing the patient with real-time feedback to offload via their electronic devices. These findings, while preliminary, highlight the potential of smart orthotic technology as an adjunct to standard orthotic care in reducing the overall burden of diabetic foot disease and knee osteoarthritis. Limitations: The primary methodological limitation of this review is the open-label design of all included smart orthotic trials, which precludes participant blinding and introduces performance bias. However, this limitation is structural and inherent to the wearable technology field—analogous to surgical trials—and is substantially mitigated by the use of objective primary outcome measures (plantar pressure and ulcer recurrence) across the three included RCTs, the consistency of effect direction across independent RCTs conducted in different countries, and a narrative sensitivity analysis confirming robustness of findings (Risk of Bias Across Studies Section). Formal per-outcome GRADE evidence profiles were not produced; overall certainty of evidence was assessed narratively with reference to GRADE domains and is judged to be low to moderate for smart orthotics in DFU prevention and low for knee OA management, consistent with the Level 2–3 evidence base and open-label study designs. Future adequately powered, multi-site RCTs with standardised outcome reporting, minimum 24-month follow-up, and integrated health economic modelling are the highest priority to extend these preliminary findings. Registration: This review was not prospectively registered. Full article

Most airline passengers and crew assume that the air in the cabin is free from harmful or hazardous substances, as is mandated by airworthiness regulations. While fresh air entering the cabin is sterile (and if recirculated is usually efficiently filtered to remove microorganisms), if the fresh air is bled off the turbine compressors (as is the case in about 95% of airliners currently in service), it may be contaminated with traces of engine oil and ultrafine particles abraded from the turbine blades, and possibly traces of hydraulic fluid leaking from servo systems. Engine oil contains tricresyl phosphate (TCP) as an essential antiwear agent, but it is also a well-known neurotoxin, and it has been suggested that there may be no safe lower limit of exposure, not least because of considerable variation among individuals in sensitivity to tri-ortho-cresyl phosphate (ToCP) and other isomers with at least one ortho constituent. This paper reviews current knowledge about these hazards and discusses the medical and economic motivations for diminishing them. A calculation based on maintaining the life quality index shows that eliminating xenobiotic hazards in aircraft cabin air is likely to be affordable. Full article

Plastic waste presents a significant environmental and public health concern in Malawi, where rapid urban growth, limited waste collection services, and informal disposal practices contribute to persistent plastic waste hotspots. In Lilongwe City, the waste collection rate has been reported ranges from 10% to 30%. This means that out of the 500 to 600 tons of municipal solid waste produced each day, only about 50 to 150 tons are collected daily. These hotspots occur in settings such as drains, markets, settlement edges, riverbanks, and lakeshore environments. They intensify health-relevant exposure pathways by encouraging stagnant water, increasing flood risk, facilitating open burning, and supporting the formation of plastisphere biofilms that can contain pathogenic and antimicrobial resistant organisms. This research synthesises evidence on the main sources of plastic waste in Malawi, the mechanisms of leakage across different environments, and the associated health implications. It uses a scoping approach aligned with PRISMA-ScR guidance and is informed by the UK Research and Innovation (UKRI) funded Sustainable Plastic Attitudes to benefit Communities and their Environments (SPACES project), which highlights the influence of behavioural, governance, and environmental factors on plastic pollution. A two phase, risk-based decision framework to support targeted management of plastic waste hotspots is described. Phase 1 focuses on rapid harm reduction through the identification and ranking of hotspots according to risk severity, spatial extent, and feasibility, guiding timely interventions such as drain clearance, waste capture, and temporary stabilisation. Phase 2 addresses longer term prevention by tackling upstream drivers through policy measures, improved services, reuse and reduction schemes, and community engagement. The framework has been developed using evidence from Malawi; however, its methodology could be applied to other low- and middle-income countries that experience similar constraints and exposure pathways. The framework offers a transparent and practical tool for decision makers seeking to allocate limited resources effectively while reducing environmental and health risks associated with plastic waste. Full article

Western saline soil areas contain a large amount of chloride and sulfate ions, leading to a reduction in the service life of Portland concrete in this environment. Magnesium oxychloride cement recycled concrete (MOCRC) is mainly prepared with light-burnt magnesia and magnesium chloride, which is more suitable for application in a western saline soil environment than Portland concrete. In this paper, ultrasonic non-destructive testing technology was used to investigate the effects of multiple factors on the deterioration process and service life of MOCRC in a western saline soil environment. The results showed a clear functional relationship between the relative dynamic elastic modulus and the compressive strength or size of MOCRC. On this basis, a multiparameter time-varying degradation model for MOCRC considering the compressive strength, size effect, and environmental error is established. Moreover, a service life prediction model for MOCRC based on the relative dynamic elastic modulus is proposed, using reliability theory and the first-order second-moment method. This study provides a foundational method for the durability examination and service life prediction of MOCRC. Full article

Silicone rubber is an important external insulating material for composite bushings, composite insulators, and other power equipment. During long-term service, it is inevitably exposed to coupled environmental and electrical stresses, such as elevated temperature, moisture ingress, strong electric fields, and partial discharge, which may lead to hydrophobicity loss, surface chalking, crack propagation, and particle shedding. To reveal the microscopic degradation mechanism of silicone rubber under complex operating conditions, a molecular model of methyl vinyl silicone rubber was constructed using Materials Studio. A stable silicone rubber molecular structure was obtained through crosslinking, geometry optimization, and ensemble relaxation. Subsequently, a reactive molecular dynamics simulation system under coupled temperature–humidity–electric field conditions was established using LAMMPS and the ReaxFF reactive force field. Different temperature gradients, electric field intensities, and aging–recovery stages were designed to investigate the degradation behavior of silicone rubber. The evolution of the maximum carbon content, maximum silicon content, carbon-containing decomposition products, and typical small-molecule products, including H₂, H₂O, CH₄, C₂H₂, C₂H₄, and C₂H₆, was statistically analyzed. In addition, atomic trajectory tracking was performed to clarify the processes of methyl group detachment, Si-O bond cleavage, water molecule participation, and molecular chain reconstruction. The results show that high temperature mainly promotes methyl group detachment from side chains and fracture of the siloxane main chain, while a strong electric field accelerates the decomposition process and induces the transformation of long siloxane chains into shorter chains. Water molecules can react with broken siloxane chains to form hydroxyl-containing structures, making the structural degradation partially irreversible. The degradation process of silicone rubber under coupled temperature–humidity–electric field stress can be summarized as side-chain detachment, main-chain scission, water-assisted reactions, free-radical recombination, and local molecular aggregation. This study provides a molecular-level theoretical basis for aging mechanism analysis, condition assessment, and lifetime prediction of composite external insulating materials. Full article

Human activities and economic development require large amounts of water and energy. The analysis of the nexus between water and energy flows can improve the understanding of the quantitative relationship between the two resources and guide actions and policies to obtain better results with lower risks. This article aimed to analyse and evaluate the use of rainwater in urban environments and its relationship with the water–energy nexus through a literature review. The PRISMA guidelines were used to structure the research, and the RStudio programme was used for the bibliometric analysis. A total of 118 articles published between 2013 and 2023 were identified in the Scopus and Web of Science databases, of which 30 met the eligibility criteria and were included in the review. The risk of bias in the studies included was assessed by two independent reviewers, and disagreements were resolved by consensus. The results were synthesized in a narrative and descriptive way, and organized in a table containing the authors, year, country, and main findings. The studies were grouped according to the theme addressed and the results related to the use of rainwater and the water–energy nexus were compared. The results indicate that the main use of rainwater is for non-drinkable purposes, to reduce the demand for potable water, lessen the pressure on water resources and contribute to environmental sustainability. Climate change can affect rainfall regimes and, consequently, the feasibility of systems. By decentralizing water supply services, the use of rainwater can save drinking water. When assessing energy savings, the use of rainwater is not always the best option, as system configurations and pump specifications are determining factors. Regarding the environmental impacts, all stages of the urban water cycle consume energy for their operation, and the environmental impact is directly related to the energy source used. Policies and regulations focused on rational use, water conservation, demand reduction, and tax incentives for the installation of rainwater harvesting systems, together with awareness campaigns, are necessary for the widespread adoption of rainwater harvesting systems. Finally, there is consensus regarding saving drinking water, but there is still a lack of studies and specifications regarding energy savings. The findings highlight the need for future longitudinal and simulation-based studies to strengthen knowledge of water–energy nexus dynamics in buildings. Full article

The use of alternative water sources in construction, especially in regions with limited freshwater availability, makes the influence of mixing water composition on the durability of cement mortars a critical issue, particularly under aggressive conditions such as ammonium exposure (XA3). A clear difference in material behavior was observed before and after exposure to an aggressive aqueous environment, highlighting the importance of durability assessment under realistic service conditions. Cement mortar specimens prepared with tap water, distilled water, and modified waters containing Cl⁻, Ca²⁺, SO₄²⁻, and PO₄³⁻ ions were tested. The experimental program included flexural and compressive strength, water absorption, and residual properties after exposure to an NH₄Cl solution. Statistical analysis was performed using one-way ANOVA, correlation analysis, a heatmap, and PCA. Compressive strength varied within a narrow range (33.85–47.24 MPa), while flexural strength showed larger differences (5.21–10.40 MPa). After exposure, residual flexural strength decreased to 1.16–5.87 MPa and compressive strength to 23.92–37.68 MPa. The most severe degradation was observed for sulfate- and chloride-modified waters. Correlation analysis revealed weak dependence between flexural and compressive strength. ANOVA confirmed a significant influence of water composition (p < 0.05), with the strongest effect observed for residual compressive strength (η² = 0.81). The results demonstrate that mixing water composition is a key factor controlling durability in an XA3 environment. Compressive strength alone is not a reliable durability indicator. Durability is governed primarily by transport properties and microstructure. A multi-parameter approach is required for an accurate durability assessment. Full article

Thermally conductive epoxy potting compounds require high filler loadings for effective heat dissipation. However, high filler loadings can increase viscosity and brittleness, thereby impairing processability and service reliability. In this study, a mesogen-containing reactive liquid–crystalline epoxy monomer (LCE) was designed, synthesized, and incorporated into a commercial thermally conductive epoxy potting compound to investigate its effects on thermal behavior, rheological and mechanical properties, thermal conductivity, and fracture-surface morphology. The chemical structure and thermotropic liquid–crystalline behavior of LCE were characterized via Fourier-transform infrared spectroscopy, proton nuclear magnetic resonance spectroscopy, differential scanning calorimetry, and polarized optical microscopy. Increasing LCE loading elevated the DSC-derived glass transition temperature (T_g) from 59 °C to 96 °C and markedly increased the room-temperature complex viscosity. Single-point measurements at 25 °C showed a monotonic decrease in thermal conductivity from 0.95 to 0.52 W/(m·K) with increasing LCE content. Mechanical testing revealed that the nominal 10% LCE formulation provided the best balance between load-bearing capacity and ductility among the tested formulations, whereas higher LCE loadings were associated with greater local microstructural variation and reduced mechanical properties. This study clarifies the modulation effect of LCE on the performance balance of highly filled epoxy potting compounds, providing valuable insights for future formulation optimization. Full article

Although asbestos has been banned in the European Union since 2005, asbestos-containing materials, such as brake pads and clutch linings, may still occur in waste streams due to the long service life of vehicles, legacy equipment, and international trade in spare parts. The persistence of these materials raises environmental and occupational health concerns, particularly in waste management systems. This study aims to assess the presence, temporal trends, and sectoral distribution of asbestos-containing friction materials in the Hungarian waste management system two decades after the EU ban, and to evaluate the associated regulatory and occupational risk implications. The analysis is based on national hazardous waste datasets classified under EWC code 16 01 11* (asbestos-containing brake pads), with a specific focus on this waste category rather than on the full range of asbestos-related waste streams recorded in the national database. The results indicate that asbestos-containing friction materials are still present in the waste stream, with measurable quantities recorded annually. Despite regulatory control, identification challenges and potential misclassification may contribute to underreporting. The continued occurrence of asbestos-containing materials highlights the persistence of legacy hazardous materials within circular economy systems. Strengthened monitoring, improved identification protocols, and enhanced occupational safety measures are necessary to mitigate residual exposure risks. The findings underline that asbestos is not merely a historical issue but remains a contemporary environmental and public health challenge. Full article

Protected areas (PAs) are increasingly challenged by the need to reconcile biodiversity conservation with sustainable human use, particularly in landscapes containing underutilized or resting area (RA). This study evaluated the potential of resting forest and agricultural lands to enhance biodiversity and support sustainable land use within protected areas of Cesme, Türkiye. A Geographic Information System (GIS)-based multi-criteria evaluation approach was employed, integrating land cover data, soil group maps, topographic parameters, and protected area classifications to generate Plant Suitability Maps (PSMs). Eight thematic layers were developed, incorporating soil depth, slope, erosion risk, and land capability classes to identify suitable plant species and land-use options. The results indicate that the strategic use of resting agricultural lands could contribute up to 35.5% to ecological enhancement, while resting forest lands could contribute an additional 18%. The proposed plant assemblages include medicinal and aromatic species, erosion-control plants, and economically valuable perennial species that support ecosystem services such as pollination, beekeeping, and agro-tourism. Overall, the findings demonstrate that integrating RA management into conservation planning can simultaneously strengthen biodiversity, improve ecosystem services, and generate socio-economic benefits for local communities. The proposed GIS-based framework offered a transferable and scalable methodology for sustainable land management in Mediterranean landscapes and other protected regions worldwide. Also, in this research, the aim was to determine plant species using GIS-based suitability analyses of multi-spatial datato guide vegetation decisions in multi-criteria PA. Full article

This study proposes a novel simulation-driven intelligent framework for the performance and reliability assessment of renewable energy-integrated pavement systems by unifying coupled multiphysics finite element modeling, structured dataset generation, and graph-based artificial intelligence within a single computational paradigm. The proposed pavement is formulated as a seven-layer multifunctional infrastructure system comprising the asphalt surface, intermediate binder, base layer, thermoelectric energy layer, piezoelectric insert zone, subbase, and subgrade soil, thereby enabling simultaneous consideration of structural load transfer, thermal gradient-driven energy harvesting, moisture-sensitive support behavior, and reliability-oriented performance interpretation. A three-dimensional thermo-hydro-mechanical Abaqus model was developed to simulate the concurrent effects of moving wheel load, solar heat flux, rainfall infiltration, and internal moisture diffusion, and it was subsequently used to construct an AI-ready dataset containing 6000 simulation cases and 68 variables spanning geometric, material, environmental, traffic, uncertainty, structural, thermal, hydraulic, renewable-energy, and probabilistic reliability descriptors. To preserve the physical hierarchy of the layered pavement within the learning process, a Layer-Coupled Reliability Graph Operator Network (LaRGO-Net) was proposed, in which pavement layers are represented as interacting graph nodes linked through adaptive interlayer coupling and optimized through multi-task, physics-aware, and coupling-consistent learning. Experimental evaluation across nine progressive configurations demonstrated a monotonic improvement from baseline dense and graph-convolution models to the full LaRGO-Net formulation. The final model achieved the best overall performance with mean RMSE = 0.040, mean MAE = 0.028, mean $R^2=0.994$, and reliability prediction accuracy characterized by F1 = 99.21 and AUC = 99.53. These results confirm that the proposed framework provides a highly accurate, physically interpretable, and reliability-aware surrogate for next-generation pavement systems capable of simultaneously supporting structural serviceability, renewable-energy functionality, and intelligent decision-making. Full article

Small and medium enterprises (SMEs) in the entertainment sector face significant challenges managing seat assignments through manual processes that are error-prone and time-consuming. This paper presents an intelligent agent-based system that automates seat assignment, while providing natural language support for operational staff. The system integrates a large language model (Gemini 2.5 Flash) for conversational interaction with a constraint-based optimization algorithm that considers capacity, accessibility, revenue, and business priorities. A fuzzy matching engine combining spaCywith the fuzzy string matching library FuzzyWuzzy consolidates duplicate reservations from multiple channels. The cloud-based architecture leverages AWS managed serverless services (ECS Fargate for container orchestration and Lambda for event-driven pipelines) with PostgreSQL for data management. Technology Readiness Level 4 (TRL4) validation demonstrated 94% precision in duplicate detection, successful assignment of 87% of reservations with 82% average capacity utilization, and effective natural language query handling. The system reduces manual processing time by 65%, while improving assignment quality through systematic enforcement of constraints. This work demonstrates the feasibility of AI-powered operations management for resource-constrained SMEs, offering a practical reference architecture combining conversational AI with algorithmic optimization. Full article

The integrated usage of metro and bus services plays a key role in long-distance trips in big cities. Revealing the nonlinear relationship between the intermodal transfer demand and the built environment is significant for building a sustainable public transport system. This paper proposes a stacking ensemble explainable machine learning framework, which uses meta-learner to learn the prediction results of diverse base learners to improve performance, to detect how the impact factors impact the intermodal demand, including metro-to-bus and bus-to-metro directions. In this framework, the ensemble model is the stacking model; the ridge regression model is the second model. The base learners contain tree-based models (e.g., Random Forest, XGBoost and CatBoost) and non-tree-based models (e.g., SVR and KNN). The framework is applied to the case study of Beijing, China, based on one weekday (13 May 2019) and one weekend day (18 May 2019) of smart card data covering the main urban districts within the Sixth Ring Road. The results indicate that the stacking ensemble learning model outperforms the base learning models. For the metro-to-bus direction, transfer time, bus station count, and degree centrality are the top three influential factors; for the bus-to-metro direction, transfer time, bus station count, and shopping POI count are the top three, with lower predictive performance due to greater variability in this direction. However, the interaction effect of transfer time and bus station count is negative. This study could provide new insights into public transport planning and management. Full article

Crack opening and reinforcement stress are two complementary indicators of the service state of reinforced concrete hydraulic structures, yet they are often predicted separately. This study develops a data-driven multi-task temporal fusion framework for joint 48 h ahead prediction of dam crack responses and rebar stress using multi-source monitoring data. The measured data comprise five crack-monitoring series, five rebar stress series, local temperature channels, reservoir water level, antecedent rainfall, and an auxiliary environmental signal over approximately four years. Target responses are aligned only at common measured timestamps; no synthetic target observations are introduced. A simplified engineering layout and plan-based crack–rebar distances are further used to examine whether an explicit spatial prior can strengthen the shared temporal representation without introducing synthetic target values. A residual multi-task temporal fusion network (MTTF-Net) is proposed with a shared Transformer encoder, attention pooling, task-specific decoders, and a response-continuity regularization term. The model is compared with persistence, Ridge regression, random forest, Extra Trees, XGBoost, and GRU baselines under a chronological train/validation/test split. For the independent test period, Ridge regression obtains the lowest overall RMSE (2.2968), whereas MTTF-Net provides the lowest crack RMSE (0.0141), the lowest overall MAE (1.0035), and the second-best overall RMSE (2.3813). Distance-informed ablation, denoted as MTTF-Net-S, remains close to MTTF-Net in macro-averaged $R^2$ but is not superior in the overall test metrics, indicating that the available horizontal distances are valuable engineering metadata but cannot replace richer three-dimensional structural connectivity. These results indicate that the monitoring data contain a strong linear autoregressive component, while multi-task temporal fusion improves nonlinear crack response prediction and remains competitive for stress forecasting. The source code is prepared as a public implementation package, whereas the measured monitoring dataset is subject to data owner restrictions. Full article