Search Results (1,710)

This study investigates the adoption and utilisation of hidden roof construction as an innovative alternative to traditional roofing systems in Ghana’s urban housing. Although hidden roofs offer advantages in climate adaptability, aesthetics, and cost efficiency, their adoption remains limited. Using a survey-based partial least squares structural equation modelling approach, this study identifies the factors influencing their acceptance and use. Quantitative data were collected through field surveys from residents and construction professionals within the Kumasi Metropolitan Area. A structured questionnaire was administered using purposive and convenience sampling, yielding 175 valid responses from a total of 220 distributed questionnaires (79.5% response rate). Findings indicate that hidden roof systems are valued for their climatic suitability, particularly their resistance to water leakage and reduced heat absorption, alongside their efficient drainage design. Aesthetic appeal, cultural relevance, and ease of maintenance also emerged as key determinants of positive perception and adoption. Structural analysis confirmed significant positive relationships between design concept, aesthetic and social values, sustainability, functionality, and overall acceptance. The study provides practical guidance for architects, engineers, developers, and policymakers seeking to promote sustainable, user-centred roof design in tropical urban contexts. Findings are, however, limited to Kumasi and may not fully generalise to other Ghanaian cities. Full article

This study examined residents’ perceptions, preferences, and experiences of urban green spaces in four regional units of the Region of Attica—West Athens, Central Athens, South Athens, and Piraeus—demonstrating how demographic diversity, urban morphology, and external stressors—such as extreme heat and the COVID-19 pandemic—shape green space use. The results show that, while green spaces are essential for health, well-being, and social cohesion, their distribution is uneven, which limits their availability (27.3%) and access (21.8%) to residents. Main concerns expressed by residents when visiting green spaces and open green spaces are poor maintenance (50.7%), lack of security (36.7%), and socially irresponsible behaviour (e.g., littering, vandalism) (32.8%). Extreme heat emerged as a major constraint on outdoor activities, particularly affecting women and the elderly. Household-associated outdoor areas (balconies, courtyards, and verandas) were highly valued (59.8%), highlighting the role of private green spaces in dense urban environments. Major metropolitan parks were the most visited and valued by residents for providing contact with nature (23.0%) and benefiting from stress relief (54.0%) while practicing their favourite activity, though their use was limited during heatwaves (30.3% of the residents do not visit). Most activities during and after the COVID-19 pandemic were reported unchanged, though reported increases in walking (34.3%) and park visits (28.3%) demonstrate the importance of green spaces in fostering urban resilience. However, the reported lack of engagement in gardening (48.0%), indoor plant care (41.2%) and bird/wildlife watching (58.3%) suggest missed opportunities for ecological and cultural enrichment. Overall, the study underscores the urgent need for integrated planning strategies to improve accessibility, maintenance, and equity in green space provision. By aligning with the sustainable development goals, the four regional units of the Region of Attica can transform its green infrastructure into an inclusive, resilient system that supports public health, social inclusion, and climate adaptation. Full article

The growing complexity of modern building systems requires advanced monitoring frameworks to improve fault detection, energy efficiency, and operational resilience. Digital Twin (DT) technology, which integrates real-time data with virtual models of physical systems, has emerged as a promising enabler for predictive diagnostics. Despite growing interest, key challenges remain, including the neglect of short- and long-term forecasting across different scenarios, insufficiently robust data preparation, and the rare validation of models on multi-zone buildings over extended test periods. To address these gaps, this study presents a comprehensive DT-enabled framework for predictive monitoring and anomaly detection, validated in a multi-zone educational building in Rhode Island, USA, using a full year of operational data for validation. The proposed framework integrates a robust data processing pipeline and a comparative analysis of machine learning models, including LSTM, RNN, GRU, ANN, XGBoost, and RF, to forecast short-term (1 h) and long-term (24 h) indoor temperature variations. The LSTM model consistently outperformed other methods, achieving R² > 0.98 and RMSE < 0.55 °C for all tested rooms. For real-time anomaly detection, we applied the hybrid LSTM–Interquartile Range (IQR) method on one-step-ahead residuals, which successfully identified anomalous deviations from expected patterns. The model’s predictions remained within a ±1 °C error margin for over 90% of the test data, providing reliable forecasting up to 16 h ahead. This study contributes a validated, generalizable DT methodology that addresses key research gaps, offering practical tools for predictive maintenance and operational optimization in complex building environments. Full article

Predicting the remaining useful life (RUL) of aircraft engines is crucial for ensuring flight safety, optimizing maintenance, and reducing operational costs. This paper introduces a novel hybrid deep learning model, Transformer–KAN–BiLSTM, for aero-engine RUL prediction. The model is designed to leverage the complementary strengths of its components: the Transformer architecture effectively captures long-range temporal dependencies in sensor data, the emerging Kolmogorov–Arnold Network (KAN) provides superior approximation flexibility and a unique degree of interpretability through its spline-based activation functions, and the Bidirectional LSTM (BiLSTM) extracts nuanced local temporal patterns. Evaluated on the benchmark NASA C-MAPSS dataset, the proposed fusion framework demonstrates exceptional performance, achieving remarkably low Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) values that significantly surpass existing benchmarks. These results validate the model’s robustness and its high potential for practical deployment in prognostics and health management systems. Full article

Background: Hemodynamic management in veno-arterial extracorporeal membrane oxygenation (V-A ECMO) is inherently complex, as extracorporeal circulation profoundly alters preload, afterload, ventriculo-arterial coupling and tissue perfusion. This review summarizes current and emerging monitoring strategies to guide initiation, maintenance and weaning. Methods: A structured literature search was performed in PubMed and Scopus (1990–2025), including clinical studies, consensus statement and expert reviews addressing hemodynamic monitoring in V-A ECMO. Results: A multiparametric framework is required. Echocardiography remains central for assessing biventricular performance, aortic valve dynamics and ventricular unloading. Pulmonary artery catheterization provides complementary data on filling pressures, cardiac output and global oxygen balance. Metabolic indices such as lactate clearance and veno-arterial CO₂ gap, together with regional oximetry (NIRS), inform the adequacy of systemic and tissue perfusion. Microcirculatory monitoring, though technically demanding, has shown prognostic value, particularly during weaning. Additional adjuncts include arterial pulse pressure, end-tidal CO₂ and waveform analysis. Phenotype oriented priorities, such as detection of differential hypoxemia, prevention of left ventricular distension or surveillance for limb ischemia, require tailored monitoring strategies. Artificial intelligence and machine learning represent future avenues for integrating multiparametric data into predictive models. Conclusions: No single modality can capture the hemodynamic complexity of V-A ECMO. Precision monitoring demands a dynamic, phenotype-specific and time-dependent approach that integrates systemic, cardiac, metabolic and microcirculatory variables. Such individualized strategies hold promise to optimize outcomes, reduce complications and align V-A ECMO management with the principles of precision medicine. Full article

Drones are increasingly being used in maritime engineering for ship maintenance, emergency rescue, and safety monitoring tasks. In these tasks, action recognition is important for human–drone interaction and for detecting abnormal situations such as falls or distress signals. However, the maritime environment is highly challenging, with illumination variations, water spray, and dynamic backgrounds often leading to ambiguity between similar actions. To address this issue, we propose MSG-GCN, a multi-semantic guided graph convolutional network for human action recognition. Specifically, MSG-GCN integrates structured prior semantic information and further introduces a textual–semantic alignment mechanism to improve the consistency and expressiveness of multimodal features. Benefiting from its lightweight hierarchical design, our model offers excellent deployment flexibility, making it well suited for resource-constrained UAV applications. Experimental results on large-scale benchmark datasets, including NTU60, NTU120 and UAV-human, demonstrate that MSG-GCN surpasses state-of-the-art methods in both classification accuracy and computational efficiency. Full article

Punta Carola beach, located on San Cristóbal Island in the Galápagos Archipelago, exemplifies how island environments of recent human settlement can rapidly acquire cultural significance. Drawing on a survey of 201 residents, this study examines perceptions of the ecosystem services provided by Punta Carola, their relationship to subjective wellbeing, and attitudes toward alternative tourism and governance strategies. The findings reveal that the inhabitants of San Cristóbal recognize a wide range of tangible and intangible benefits that the natural environment of Punta Carola contributes to their quality of life, sense of belonging, and cultural identity, as well as recreational and aesthetic values. Life satisfaction was positively associated with perceptions of nature’s contribution, the maintenance of local ecological knowledge, and household income, while formal education correlated negatively. Residents identified freshwater and artisanal fishing as the most critical ecosystem services, reflecting their centrality to local livelihoods and wellbeing. The results also underscore widespread criticism of large-scale tourism projects perceived as exclusionary or unsustainable and highlight the importance of participatory governance schemes that legitimize local values. Punta Carola thus emerges as a “cultural landscape of resistance”, where external pressures catalyze identity construction and territorial rootedness. This case contributes to academic debates on socio-ecological resilience in fragile island contexts and offers actionable insights for inclusive planning in the Galápagos. Full article

Background: The Wnt/β-catenin signaling pathway plays a pivotal role in embryonic development, maintenance of the central nervous system, and the formation of neuronal circuits. Disruption of this pathway is closely associated with oncogenesis and neurodegenerative diseases, notably Alzheimer’s disease. Flavonoids such as quercetin derivatives have emerged as promising neuroprotective agents. This study investigates the impact of 3-O-methylquercetin (3OMQ), a methylated quercetin metabolite, on Wnt/β-catenin signaling and its potential relevance in neurodegenerative disease models. Methods: The ability of 3OMQ to modulate Wnt/β-catenin activity was analyzed using a luciferase-based reporter assay in both neural and non-neural cell lines. Cell viability assays evaluated cytotoxicity at various concentrations. We mapped 3OMQ activity within the pathway using targeted cell signaling experiments. Docking and molecular dynamics simulations suggested glycogen synthase kinase 3β (GSK3β) as a putative target of 3OMQ. Finally, we employed a mouse model of acute amyloid-β oligomer (AβO) toxicity to assess the in vivo effects of 3OMQ on spatial memory and Wnt-related gene expression. Results: We compared the flavonoids quercitrin, quercetin, and 3-O-methylquercitrin (3OMQ) with pharmacologically active compounds in a gene reporter assay (TOPFLASH) using Wnt-sensitive RKO cells treated with Wnt3a-conditioned medium. XAV-939 and PNU-74654 showed inhibitory activity, while BIO, CHIR99021, quercitrin, and 3OMQ enhanced the Wnt/β-catenin pathway. Notably, 3OMQ potentiated this pathway at concentrations 5–10 times lower than quercitrin and outperformed 1 μM BIO at 10 μM without cytotoxicity, highlighting its remarkable potency. Mechanistically, 3OMQ acts downstream of initial membrane activation and upstream of the β-catenin destruction complex. Consistently, molecular docking indicates a strong interaction with GSK3, a central regulator of the pathway. In adult mice, 3OMQ administration prevented AβO-induced recognition memory deficits and favored normalization of Wnt-related gene expression. Conclusions: These findings identify 3OMQ as a potent positive modulator of the Wnt/β-catenin pathway, with both in vitro and in vivo neuroprotective effects. Targeting Wnt signaling with compounds such as 3OMQ holds promise for maintaining neuronal health and developing therapeutic strategies for neurodegenerative conditions. Full article

Hybrid geothermal–solar systems leverage complementary resources to enhance efficiency, dispatchability, and low-carbon supply. This review compares mainstream configurations (solar-preheating configurations, solar-superheating configuration, and other emerging concepts) and reports typical performance gains—thermal efficiency of 5–80% and exergy efficiency up to ~60%—observed across resource contexts. Findings indicate that preheating routes are generally preferable under medium direct normal irradiance (DNI) and operation-and-maintenance (O&M)-constrained conditions, while superheating routes become attractive at high DNI with thermal storage; integrated multigeneration systems can deliver system-level benefits for multi-energy parks and district applications. In addition, this paper identifies technical bottlenecks—source matching, storage dependence, and the absence of a unified evaluation—and summarizes control/optimization strategies, including emerging advanced artificial-intelligence algorithms. In addition, the review highlights a standardized comprehensive performance evaluation framework, which covers thermal and exergy efficiency, net power output, complexity, the levelized cost of electricity (LCOE), reliability, and storage. Finally, according to the research status and findings, future research directions are proposed, which pave the way for more effective exploitation of geothermal and solar energy. Full article

Catheter ablation (CA) has become a validated technique for treating patients with symptomatic or paroxysmal atrial fibrillation (AF), as recommended by the latest 2024 European society of cardiology (ESC) guidelines, class II level A. The procedure is also recommended for patients with persistent AF without major risk factors for AF recurrence, as an alternative to antiarrhythmic medications class I or III. However, CA carries the risk of AF recurrence in 30–35% of patients, sometimes after the procedure. Multiple factors impact the onset, maintenance, and recurrence of AF after CA, including clinical, biohumoral, echocardiographic, genetic, and lifestyle factors. Beyond traditional predictors, emerging factors such as obstructive sleep apnea syndrome, chronic renal failure, chronic lung disease, physical activity patterns, gut microbiota composition, and epicardial fat thickness significantly influence outcomes. Therefore, optimizing patient’s selection for CA is an important strategy to minimize the risk of AF recurrence. Many echocardiographic parameters emerged as predictors of AF recurrence post-CA, but none stood out as a potential single factor. These factors include traditional markers such as left atrial size by 2D echocardiography, LV ejection fraction, LV diastolic function parameters as well as myocardial deformation addressed by the recently developed speckle tracking analysis. Additionally, the duration and type of AF represent fundamental risk factors, with longstanding persistent AF showing significantly higher recurrence rates compared to paroxysmal forms. Novel biomarkers including MR-proANP, caspase-8, hsa-miR-206, and neurotrophin-3 show promise in enhancing risk prediction capabilities. The aim of this review is to explore the most relevant echocardiographic parameters, including myocardial deformation, that could accurately predict recurrence of AF after CA, while also examining the role of emerging clinical and biochemical predictors in comprehensive patient selection strategies. Full article

Hybrid Renewable Energy Systems (HRESs) are a practical solution for providing reliable, low-carbon electricity to off-grid and remote communities. This review examines the role of energy storage within HRESs by systematically comparing electrochemical, mechanical, thermal, and hydrogen-based technologies in terms of technical performance, lifecycle cost, operational constraints, and environmental impact. We synthesize findings from implemented off-grid projects across multiple countries to evaluate real-world performance metrics, including renewable fraction, expected energy not supplied (EENS), lifecycle cost, and operation & maintenance burdens. Special attention is given to the emerging role of hydrogen as a long-term and cross-sector energy carrier, addressing its technical, regulatory, and financial barriers to widespread deployment. In addition, the paper reviews real-world implementations of off-grid HRES in various countries, summarizing practical outcomes and lessons for system design and policy. The discussion also includes recent advances in metaheuristic optimization algorithms, which have improved planning efficiency, system reliability, and cost-effectiveness. By combining technological, operational, and policy perspectives, this review identifies current challenges and future directions for developing sustainable, resilient, and economically viable HRES that can accelerate equitable electrification in remote areas. Finally, the review outlines key limitations and future directions, calling for more systematic quantitative studies, long-term field validation of emerging technologies, and the development of intelligent, Artificial Intelligence (AI)-driven energy management systems within broader socio-techno-economic frameworks. Overall, this work offers concise insights to guide researchers and policymakers in advancing the practical deployment of sustainable and resilient HRES. Full article

Aim: Post-COVID condition (PCC) is largely considered the biggest public health emergency in recent times. The role of exercise therapy in PCC is currently unknown, and evaluative studies are currently lacking in this area. This study therefore aimed to evaluate the effects of a football club community trust exercise rehabilitation programme on physical function and quality of life in individuals with PCC. Method: A mixed-methods retrospective design was employed, utilising a framework to assess the programme’s reach, effectiveness, adoption, implementation, and maintenance (RE-AIM). Quantitative data (questionnaires and physiological assessments) were collected at baseline, 6 weeks, and 12 weeks during the programme, and at 6 months post-intervention (n = 7). Qualitative data were gathered through semi-structured focus groups at week 12 (n = 7) and 12 months (n = 5) post-intervention. Quantitative data and qualitative data were analysed using repeated measures ANOVAs and thematic analysis, respectively. Results: The programme led to significant improvements in physical function, including increased six-minute walking distance (6MWT, p < 0.001), one-minute sit-to-stand repetitions (1MSST, p < 0.035), and lung function (spirometry; MIP: p = 0.048, MEP: p = 0.024). Participants also reported enhanced QoL (HRQoL-14, p = 0.004), reduced anxiety (GAD-7, p = 0.008) and depression (PHQ-9, p = 0.008), and increased confidence and self-efficacy. The programme was well-received, with participants valuing the supportive environment and personalised approach. Conclusions: Football community trust exercise rehabilitation programmes can effectively improve physical function and quality of life in individuals with PCC, offering a promising model for community-based rehabilitation. Further studies are needed with larger sample sizes to assess the scalability of similar programmes. Full article

Hepatic zonation reflects the concept that hepatocytes and nonparenchymal cells (NPCs) perform distinct metabolic functions, depending on their spatial localization along the porto-central axis. The maintenance of this fine-tuned organization is essential for liver homeostasis, and its disruption may contribute to liver diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD). Fat overload perturbs zonal gene signatures, lipid handling and oxygen/metabolite gradients progressively leading to steatohepatitis (MASH), fibrosis and HCC, conditions in which the hepatic architecture is lost. Traditional approaches have provided valuable insights into zonation, although they lack the spatial resolution and mask the heterogeneity of NPCs. Thus, the premise of this review is to discuss how spatial omics can redefine our understanding of hepatic zonation by integrating tissue mapping with metabolic organization, specifically focusing on MASLD. The advent of spatial omics accelerates knowledge regarding MASLD pathophysiology, providing more informative insights into transcriptional/translational/lipidomic/metabolomics zone-specific perturbations. Emerging spatial genomics and epigenomics applications further expand this scenario, allowing for the capture of chromatin remodeling in situ. The integration of these state-of-the-art approaches, coupled with artificial intelligence (AI)-based analyses, is promising in the clinic, as it may provide novel zonal prognostic biomarkers and pave the way for precision-medicine strategies targeting zonal switching. Full article

This study investigates the vulnerability of Internet of Things (IoT) devices to climate change in Kazakhstan, where extreme seasonal variability and rising climate risks threaten device reliability. Using high-resolution climate projection data from ERA5 and CMIP6 models (RCP4.5 and RCP8.5 scenarios), combined with qualitative interviews with stakeholders in agriculture, energy, transport, and urban infrastructure, we develop risk assessment models for IoT systems. The analysis quantifies device failure probabilities through temperature and humidity thresholds and extends risk curves to include additional climatic stressors such as solar radiation, wind, and snowfall. Results reveal that IoT devices face heightened risks in northern regions during extreme cold events (below −40 °C) and in southern regions during prolonged heatwaves (above +40 °C). Interviews confirm that maintenance, power supply reliability, and device calibration remain major concerns under harsh climate conditions. The findings provide evidence-based recommendations for adaptation strategies, including resilient hardware design, predictive maintenance protocols, and climate-informed deployment planning. This research contributes to the emerging field of climate-resilient IoT, offering both methodological advances and practical insights for policymakers and infrastructure planners in Central Asia. Full article

Neuropathic pain is a clinically challenging syndrome that is largely refractory to conventional therapies. It arises from lesions or diseases affecting somatosensory pathways, which trigger extensive neuroplastic and neuroimmune remodeling. Unlike nociceptive pain, which establishes a protective response to tissue injury, neuropathic pain arises from maladaptive signaling within the nervous system. In this context, the spinal endocannabinoid system (ECS) has emerged as a pivotal modulator of nociceptive processing. However, its precise role in neuropathic pain remains debated due to its dual effects. Numerous studies report antinociceptive and neuroprotective effects; however, emerging data indicate that under specific pathological conditions, ECS activation may paradoxically facilitate pain transmission. This review examines spinal ECS context dependence, uncovering its bidirectional antinociceptive and pronociceptive effects in neuropathic pain. By integrating current evidence on cellular, molecular, and pathophysiological mechanisms, we delineate the factors that determine whether ECS modulation inhibits or promotes pain. A comprehensive understanding of these mechanisms is essential for optimizing cannabinoid-based strategies to maximize therapeutic benefits while minimizing adverse outcomes. Finally, we highlight the spinal cord’s centrality as the principal site for the initiation and maintenance of neuropathic pain and advocate for rigorous translational research to clarify the therapeutic potential of spinal ECS-targeted interventions. Full article