Search Results (3,987)

Against the backdrop of expanding digital dissemination and experiential transformation in cultural heritage, visitors’ visual attention and symbolic choices increasingly shape heritage cognition and value transmission. Taking the Yellow Crane Tower as a case study, this research constructs a cultural symbol recognition dataset based on visitor-shared social media images and develops an enhanced ResNet-50 model for multi-label analysis. By integrating attention mechanisms and regularisation strategies, the model improves its capacity to capture complex cultural imagery, achieving a macro F1 score of 72.70% and a micro F1 score of 81.05% on the test set, indicating strong generalisation performance. The results reveal a significant imbalance in visual preferences: landmark symbols centred on the main architectural structure dominate at 32.95%, whereas culturally informative elements such as signage, cultural products, and interpretive facilities each account for less than 5%. Tag co-occurrence analysis further identifies three image production patterns: commemorative presentation, contextual documentation, and detail-oriented cultural photography reflecting different levels of heritage perception. Rather than directly proposing prescriptive strategies, the findings provide an empirical basis for informing future interventions aimed at shifting from landmark-focused viewing to deeper cultural perception. In this way, the study contributes to heritage display optimisation and research on visitor visual behaviour. Full article

Methane (CH₄) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH₄ emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH₄ emissions at the facility-level. Near-field quantification of methane (CH₄) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH₄ emissions to controlled single-point emissions between 0.4 and 5.2 kg CH₄ h⁻¹. Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain. Full article

The inefficient utilization of industrial by-product phosphogypsum, coupled with the increasing global demand for cooling, has spurred the development of sustainable radiative cooling materials. Compared with conventional cooling coatings that primarily rely on expensive synthetic materials or complex fabrication processes, this study provides a promising cost-effective and sustainable route for integrating industrial solid waste valorization with zero-energy cooling technologies. In this study, we fabricated a composite coating (β-HPG@CA/SiO₂@OTS) consisting of β-hemihydrate phosphogypsum (β-HPG), a derivative product of phosphogypsum, cellulose acetate (CA), SiO₂ particles and octadecyltrichlorosilane (OTS) by a facile combination of blade coating and spraying, which exhibited strong solar reflectivity (90.9%), high mid-infrared emissivity (98.7%) and satisfactory superhydrophobicity (157°). The as-prepared composite achieved an ambient temperature drop of 18.7 °C under direct sunlight during sunny weather, achieving a net cooling power of 92.23 W/m². Meanwhile, the composite coating exhibits excellent durability after prolonged immersion in strongly acidic and alkaline solutions, ultraviolet radiation and outdoor testing. Owing to its simple fabrication process and robust cooling performance, this coating shows promise for scalable production and practical outdoor applications, such as building envelopes and equipment enclosures. Full article

Ukraine’s reconstruction, estimated at $524 billion over the next decade, presents an unprecedented opportunity to embed circular economy principles into industrial rebuilding, but the financial architecture currently deployed for reconstruction is structurally blind to circular outcomes. This paper examines how digital tools and innovative financing mechanisms can channel investment toward circular industrial reconstruction in Ukraine, drawing on Germany’s National Circular Economy Strategy (NCES, adopted December 2024) as a reference model. A comparative institutional analysis combines a documentary review of Ukrainian reconstruction policy frameworks (Ukraine Plan 2024–2027, RDNA4, Ukraine Facility) and German NCES instruments with the construction of a financing−technology pathway typology. Five pathways are proposed: circular bond issuance with Digital Product Passport integration; blended finance with blockchain impact verification; EU Facility conditionality with AI-driven resource management; war risk insurance with circular construction standards; and SME digitalisation credit with circular economy competency building. Each pathway is assessed against five criteria: investment scale, risk mitigation, circular measurement, digital readiness, and institutional feasibility, and applied to four industrial corridors (Dnipro region, Zaporizhzhia region, Kharkiv region, and Donetsk region). The analysis reveals that no single pathway is sufficient; a layered strategy differentiating by region is required. Digital tools, particularly the Digital Product Passport and blockchain traceability, serve as partial substitutes for institutional trust in post-conflict settings, reducing information asymmetry between investors and project operators. The paper contributes a practically oriented framework at the under-theorised intersection of post-conflict reconstruction finance and circular economy scholarship. Full article

Addressing the persistent challenges of low resource utilization efficiency and the difficulty in quantifying hidden costs within the beef cattle sector, this study proposes an integrated diagnostic methodology that couples Material Flow Cost Accounting (MFCA) with Value Stream Mapping (VSM). Using a cohort of 1623 beef cattle finished in 2024 at the case study farm in Heilongjiang Province, China, the full life-cycle accounting reveals that hidden costs constitute 6.43% of total inputs. Attribution analysis further pinpoints two critical nodes: feed loss and bedding consumption, which account for 33.14% and 35.77% of negative product costs, respectively. Based on these diagnostics, two optimization strategies were devised: refined feed supply chain management and a recycled bedding system centered on the aerobic fermentation of cattle manure. Empirical estimates indicate that upgrading hardware facilities could reduce the feed loss rate to under 2%, yielding annual savings of ¥485,200. Furthermore, the bedding recycling system not only achieves zero waste discharge but also generates an average annual displacement income of ¥3.504 million, with an investment payback period of just 0.54 years. These findings demonstrate the efficacy of the coupled MFCA-VSM model in identifying environmental costs and unlocking economic potential, thereby providing an actionable pathway for the livestock industry’s transition toward more intensive and circular practices. Full article

Phosphorus is an essential and finite resource critical for global food production, yet its inefficient use and discharge from wastewater systems contribute to eutrophication and resource depletion. The transition from conventional wastewater treatment plants to water resource recovery facilities has intensified interest in technologies that enable phosphorus recovery within a circular economy framework. This review provides a critical and up-to-date synthesis of phosphorus recovery strategies from wastewater, with primary emphasis on struvite (MgNH₄PO₄·6H₂O) crystallization as one of the most mature and practically implemented recovery routes. The occurrence and chemical forms of phosphorus in wastewater streams are discussed alongside conventional approaches, such as enhanced biological phosphorus removal and chemical precipitation, in order to position struvite recovery within the broader phosphorus management landscape. In addition to struvite crystallization, selected competing and complementary recovery pathways, including electrochemical systems, biochar-assisted processes, and sludge ash recovery, are discussed to compare technological maturity, recovery potential, and practical applicability. Particular attention is given to reactor configurations, full-scale applications, and commercial technologies to assess operational reliability, recovery performance, and fertilizer product quality. Life-cycle assessment results and regulatory developments are also discussed to contextualize sustainability claims, technology selection, and market integration. The review identifies key technical and economic challenges, particularly regarding magnesium supply, competing ions, wastewater matrix effects, and the feasibility of mainstream application. Overall, controlled sidestream struvite crystallization appears to offer the most favorable balance between recovery efficiency, operational reliability, and fertilizer product quality under suitable plant conditions. Full article

This study introduces a novel Quantum-Inspired Hybrid Bald Eagle-Ukari Algorithm with Reinforcement Learning (QI-HBEUA-RL) for comprehensive optimization of conical solar distillers equipped with sand-filled copper conical fins. The proposed algorithm synergistically combines quantum computing principles (superposition and entanglement), bio-inspired metaheuristics (Bald Eagle Search and Ukari Algorithm), and reinforcement learning mechanisms to achieve unprecedented optimization performance in complex thermal-hydraulic systems. The QI-HBEUA-RL framework employs quantum-encoded population representation, enabling simultaneous exploration of multiple solution states, while reinforcement learning dynamically adjusts algorithmic parameters based on search landscape characteristics and historical performance data. Experimental validation tested seven distiller configurations in El-Oued, Algeria, under controlled conditions (7.85 kWh/m²/day solar radiation, 42.2 °C ambient temperature). The optimal configuration of copper conical fins with 14 g sand at 0 cm spacing achieved: daily productivity of 7.75 L/m²/day (+61.46% improvement over conventional design), thermal efficiency of 61.9%, exergy efficiency of 4.02%, and economic payback period of 5.8 days. Comprehensive algorithm comparison against six state-of-the-art multi-objective optimizers (NSGA-II, MOEA/D, MOPSO, MOGWO, MOHHO) across 30 independent runs demonstrated statistically significant superiority (p < 0.001, Wilcoxon test). QI-HBEUA-RL achieved 7.42% improvement in hypervolume indicator, 29.35% reduction in inverted generational distance, and 19.49% better solution spacing. Generalization validation on seven benchmark problems (ZDT1-6, DTLZ2, DTLZ7) and three renewable energy applications confirmed algorithm robustness across diverse problem types. Three real-world case studies, remote village water supply (238:1 benefit–cost), industrial facility (100% energy reduction), and emergency relief (740× cost savings) validate practical implementation viability. This research advances solar thermal desalination technology and multi-objective optimization methodologies, providing validated solutions for sustainable freshwater production in water-scarce regions. Full article

Powder bed fusion (PBF) and directed energy deposition (DED) additive manufacturing use feedstock powders that contain metals associated with skin diseases. We performed a survey of surface contamination and limited task-based dermal exposure assessment (four employees) at a PBF and DED facility. Skin wipes of wrists for two employees in the PBF room had higher post-task levels of chromium, cobalt, molybdenum, and nickel. Personal clothing worn by PBF employees showed evidence of contamination with metals as did personal protective equipment (PPE). Microscopy analysis documented contamination of metals throughout most areas of the facility. Levels of metals on surfaces throughout the facility were (ng/cm²) <5.0–7247 (aluminum), <0.2–4899 (chromium), <background-6.0 (chromium VI), 0.03–468.1 (cobalt), 1.6–100.0 (copper), 32.9–19,000 (iron), 0.01–789.0 (molybdenum), 0.1–12,058 (nickel), 0.1–482.8 (titanium), and 0.07–9.3 (vanadium). Levels were significantly lower in administrative areas compared with the production area but generally did not differ among powder handling and non-powder handling rooms in production. The small number of participants in the dermal exposure assessment and uniqueness of the facility might limit generalizability of the results. At least for this facility, steps to lower skin contact with metals can include washing, consistent use of PPE, and increasing awareness of dermal hazards among workers. Approaches to reduce migration of metals throughout a facility can include using adhesive (“tacky”) mats and boot covers and frequent wet cleaning of floors, tools, handles, and high touch surfaces. Full article

5-Hydroxymethylfurfural (5-HMF) and the mycotoxin patulin (PAT) serve as crucial chemical markers for evaluating the quality and safety of fruit-derived beverages, particularly pomegranate juice. This study aimed to quantify the occurrence of 5-HMF and PAT in commercial reconstituted pomegranate juices and assess the associated dietary exposure risks. A total of 154 commercial samples, collected from a Turkish processing facility during the 2024–2025 production seasons, were analysed using high-performance liquid chromatography with diode-array detection. 5-HMF was detected in 152 samples (98.7%) at concentrations ranging from 1.03 to 10.79 mg/kg, with only two samples (1.3%) exceeding the critical threshold of 10 mg/kg. PAT was found in 57 samples (37.0%), with concentrations between 3.61 and 50.69 µg/kg, and only one sample (0.6%) exceeded the European Union maximum level established for fruit juices. Estimated mean daily intakes for adults and children ranged from 0.374 to 2.362 and 1.139 to 8.546 µg/kg bw/day for 5-HMF, and from 0.001 to 0.006 and 0.002 to 0.021 µg/kg bw/day for PAT, respectively. Risk characterisation based on hazard quotient values indicated that PAT exposure did not pose a significant health risk for either population group, highlighting the overall safety of the analysed products. Full article

We investigate whether short-range nucleon–nucleon correlations (NN-SRC) and cluster configurations in nuclei can be explored by studying spectator neutrons produced in high-energy nucleus–nucleus collisions. In particular, we propose to measure the multiplicity distributions of forward spectator neutrons in symmetric ¹²C–¹²C and ⁴⁰Ca–⁴⁰Ca collisions at $\sqrt{s_{\mathrm{NN}}}=11$ GeV with the Spin Physics Detector (SPD) at the NICA facility. To assess this method, we simulate the production of spectator nucleons in these reactions using the Abrasion–Ablation Monte Carlo for Colliders model with MST clustering (AAMCC-MST). Short-range nucleon–nucleon correlations inside ¹²C and ⁴⁰Ca are implemented via a Monte Carlo rejection sampling procedure. Our results indicate that spectator production exhibits only a weak dependence on the specific features of NN-SRC. We also observe that including $\alpha$-cluster configurations in ¹²C leads to a reduction of the average multiplicity of spectator neutrons as a function of collision centrality. Full article

Beef production is widely recognized as a significant contributor to global greenhouse gas emissions, making robust and transparent environmental assessments essential for advancing sustainability within supply chains. This study applies a comprehensive cradle-to-grave Life Cycle Assessment (LCA) to evaluate the environmental performance of beef destined for export, following ISO 14040, ISO 14044 and ISO 14067 standards and the Product Category Rules for meat of mammals. Sixteen impact categories were quantified for 1 kg of vacuum-packed beef using detailed primary data from a pasture-based production system and a representative processing facility. The total climate change impact was 3.27 × 10¹ kg CO₂eq, with enteric methane and feed production jointly responsible for over 70% of overall impacts. Slaughtering and distribution were associated mainly with fossil energy use and ozone depletion, while soil carbon sequestration partially compensated biogenic emissions. The results were consistent with international benchmarks, highlighting the environmental advantages of pasture-based systems, low fertilizer use, and stable land management. Key hotspots were identified in animal growth, feed efficiency, and manure management, with logistics also contributing notably. Overall, the study provides a high-resolution environmental baseline that can support Environmental Product Declarations and guide targeted mitigation strategies across beef supply chains. While the results are derived from a specific pasture-based production system, the study is positioned as a case-study-based application of a high-resolution LCA framework, illustrating how detailed inventories can support environmental benchmarking and hotspot identification without implying statistical representativeness of all beef production systems. Full article

The location of the decommissioned factory of plastics and chemical products Jugovinil, City of Kaštela, Croatia, has gained significant attention for urban development and the establishment of tourist facilities over the past three decades. Since the site is on the coast of the Adriatic Sea, on the shore of Kaštela Bay, where nautical tourism is already developed, plans for a five-star tourism complex were initiated. Given that the former industrial plant, its coal-powered power plant, and other later industrial activities (small shipyards) caused a certain degree of contamination with NORM (naturally occurring radioactive material) residues and heavy metals, an on-site detailed investigation was conducted into the spatial distribution and concentration evaluation of contaminants within dozens of soil samples, and the distributions of contaminants in the area of interest were shown in the form of maps. This study applies an integrated GIS and geostatistical framework to analyze the spatial distribution of multiple contaminants. Maps highlighting polluted zones are included, along with maps indicating areas with higher cumulative concentrations of contaminants. This paper provides an overview of potential issues related to the detected contaminants, as well as proposals for remediation methods before repurposing the site using retrospective data about sources of residues and contaminants. Full article

Supply chain management (SCM) involves complex coordination among multiple actors under demand uncertainty. However, most existing studies focus on simplified network structures that fail to capture all relevant dimensions of real-world supply chains or assume deterministic demand. This study proposes a comprehensive stochastic bi-level optimization framework for a multi-factory, multi-retailer, multi-customer, and multi-product supply chain network. The model captures the hierarchical interaction between decision-makers, where the production facility owner acts as the leader and the retailer as the follower, and jointly optimizes profit across both levels. To efficiently solve the resulting bi-level problem, two tailored metaheuristic solution approaches—a two-tier genetic algorithm (TT-GA) and a two-tier particle swarm optimization (TT-PSO)—are developed. Computational experiments across multiple scenarios demonstrate that TT-PSO outperforms TT-GA in Scenarios 1 and 2, achieving overall profit improvements of 6.46% and 0.76%, respectively, while TT-GA yields superior performance in Scenario 3 with a 2.80% profit improvement. The proposed framework provides decision-makers with a robust and practical tool for improving profitability and operational efficiency in complex, uncertain supply chain environments. Full article

Over the past decade, Building Information Modelling (BIM) has become increasingly adopted across the Architecture, Engineering, Construction, and Operation (AECO) industry. As its use in practice has expanded, BIM has also received growing scholarly attention. Existing research has largely concentrated on specific applications of BIM, such as construction management, sustainable building design, infrastructure development, and facility management. However, comparatively limited attention has been given to examining BIM implementation from a global perspective. This study addresses this gap by applying a scientometric approach to analyse global BIM implementation research published between 2004 and 2023. The analysis is conducted using co-authorship, co-word, and co-citation analysis to map the structure and development of the research field. A total of 1349 published articles were obtained from the Scopus database for the analysis. The study identifies the most productive and influential contributors to BIM implementation research, including leading researchers, research institutions, countries, subject areas, and academic journals. In addition, the analysis highlights several key thematic domains within global BIM research. These include topics related to Industry Foundation Classes (IFC), Internet of Things (IoT), Geographic Information Systems (GIS), Historic Building Information Modelling (HBIM), and Digital Twin technologies, which appear as prominent keywords within the BIM implementation literature. Beyond mapping these trends, this paper integrates dispersed scientometric evidence into a coherent global perspective, revealing how BIM implementation research has evolved, matured, and diversified across regions and disciplines. It also establishes a structured knowledge base that can serve as a benchmark for future comparative studies, performance assessments, and policy development initiatives in the digital construction domain. These findings provide valuable insights for researchers, practitioners, and policymakers by illustrating landscape of BIM-related research and highlighting potential directions for future investigation. Full article

Morocco’s recent legalization of industrial and medicinal cannabis has created a rapidly expanding seed-oil sector whose sustainability has yet to be fully assessed. This study applies an environmental life cycle assessment (LCA) in accordance with ISO 14040:2006 and ISO 14044:2006, complemented by a qualitative social responsibility assessment based on ISO 26000:2010, aiming to evaluate the life cycle sustainability of Moroccan cannabis seed oil. Three representative processing chains, traditional artisanal presses, producer cooperatives and regulated industrial plants are compared using a functional unit of 1 kg of cold-pressed oil packaged for local distribution. Inventory data were drawn from field measurements and interviews and were modeled in OpenLCA with background datasets from Ecoinvent 3.8 and Agribalyse v3.1. Impact assessment used the ReCiPe 2016 (H) method at the midpoint level across nine categories (climate change, fossil resource scarcity, water use, freshwater eutrophication, terrestrial acidification, land occupation, carcinogenic, non-carcinogenic human toxicity, and fine particulate matter formation). Sensitivity analyses varied seed yield, electricity mix and transport distances by ±20% to gauge uncertainty. Results show that the cooperative scenario achieves the lowest impacts across nearly all categories because of higher extraction yields (3 kg seed per kg oil), lower energy use (0.54 kWh kg⁻¹ oil) and more effective co-product recovery. In contrast, artisanal extraction requires approximately 1 kg of additional seed input per functional unit compared to optimized scenarios, significantly increasing upstream environmental burdens and causing upstream agricultural burdens to multiply. Industrial facilities perform comparably to cooperatives if powered by renewable electricity. Integrating a semi-quantitative social responsibility assessment reveals that legalization has markedly improved organizational governance, labor conditions, consumer protection and community involvement. Cooperatives display the most balanced social performance, whereas industrial plants excel in governance and quality control. A set of recommendations, including drip irrigation, cultivar improvement, co-product valorisation, renewable energy adoption, eco-designed packaging and cooperative governance, is proposed to enhance the environmental and socio-economic sustainability of Morocco’s emerging cannabis seed-oil industry. Full article