Search Results (3,041)

Severe accidental hypothermia represents a unique and potentially reversible cause of cardiac arrest in which prolonged resuscitation may still result in favorable neurological recovery. Unlike normothermic cardiac arrest, hypothermic cardiac arrest (HCA) is characterized by profound metabolic suppression and temperature-mediated myocardial instability, requiring a fundamentally different therapeutic paradigm. Veno-arterial extracorporeal membrane oxygenation (V-A ECMO) provides not only circulatory support but also controlled reperfusion and rewarming, positioning it as the cornerstone of modern management. Recent international guidelines have clarified indications for extracorporeal life support (ECLS) in HCA and have contributed to improved standardization of care. Building upon these recommendations, this narrative review focuses on physiological principles underlying extracorporeal rewarming and their implications for bedside management. We examine mechanisms of ischemia–reperfusion injury, rewarming-associated hemodynamic instability and myocardial stunning, discuss dynamic risk assessment beyond statistical thresholds such as the HOPE score and summarize practical considerations regarding cannulation strategies, differential hypoxia, left ventricular unloading and neurologic evaluation. By integrating current evidence with pathophysiological insight and organizational considerations, this review proposes a clinically oriented framework to support decision-making in hypothermic cardiac arrest and to optimize meaningful neurological recovery. 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

The construction sector’s transition to carbon neutrality requires innovative strategies to address the performance and cost challenges of advanced building designs, such as passive-oriented nearly zero-energy buildings. This study proposes an artificial intelligence-based multi-objective optimization framework to reduce both energy consumption and construction costs for residential building envelopes in Chengdu’s hot summer and cold winter climate. The framework uses the NSGA-II genetic algorithm within DesignBuilder to explore trade-offs between energy efficiency and economic cost. Key design parameters (wall insulation thickness, roof insulation thickness, and window glazing type) are optimized to obtain a Pareto-optimal front. A subsequent global incremental cost analysis of the non-dominated solutions identifies the optimal balance where significant energy savings are achieved before diminishing returns set in. The research results show that by combining the NSGA-II algorithm with the global incremental cost method in the Chengdu area, the parameters of the enclosure structure can be systematically optimized, and the optimal balance point between energy conservation and cost can be effectively identified. Based on this, an “energy-saving optimal—trade-off optimal—cost optimal” template set design path based on dual objectives of energy consumption and cost can be obtained, which is applicable to different demand-oriented engineering scenarios. This research provides a quantifiable decision-making basis for the design of buildings with passive design strategies that achieve near-zero energy consumption in hot summer and cold winter regions, helping to achieve the coordinated optimization of energy efficiency goals and economic feasibility, and promoting the reliable promotion and application of near-zero energy buildings. Full article

Last-mile delivery companies can face demand surges where large-volume order requests exceed daily courier capacity. In such cases fast and robust feasibility-first planning becomes more practical and valuable than building optimal routes. This paper proposes a hierarchical, computationally feasible decomposition pipeline that produces shift-feasible clusters under a strict shift-duration limit using travel-time-based duration estimates. While decomposition methods for large-scale VRPs are well established, they typically remain oriented toward route-construction quality within a single operational day or toward balancing customer counts, demand, or Euclidean territory partitions. In contrast, the proposed method targets a different decision problem: rapid feasibility-first strategic capacity planning for one-time extreme demand surges, where the primary requirement is to estimate, within seconds, a conservative upper bound on the number of courier shifts under a strict shift-duration limit. When end-to-end latency is evaluated from raw geographic points, including distance-matrix preparation for monolithic baselines, the proposed pipeline becomes 187 to 1315 times faster than matrix-based monolithic optimization on the common benchmark sizes. Methodologically, the contribution lies in combining (i) topology-preserving spatial linearization with a Hilbert Space-Filling Curve, (ii) adaptive greedy microclustering driven by empirical travel-time quantiles, and (iii) lexicographic dynamic-programming merge that minimizes the number of shifts first and total travel time second. This yields a planning-oriented decomposition mechanism that is distinct from classical route-quality-centered hierarchical VRP approaches. Full article

Building Information Modeling (BIM) supports information integration and coordination across the construction lifecycle, but benefits depend on collaboration that is shaped by the selected project delivery method (PDM). BIM-PDM evidence is difficult to consolidate due to heterogeneous terminology and fragmented, context-specific studies. This scoping review maps which PDMs are addressed in the BIM-related literature and how adequacy is framed. Following PRISMA-ScR, Web of Science and Scopus were searched and 71 studies met the eligibility criteria. Publications increased markedly after 2018 and were geographically concentrated, with the largest shares associated with author affiliations in China, the United Kingdom, Australia, Canada, Malaysia, and the United States. Integrated Project Delivery (IPD) was the most frequently examined (46 studies), followed by Design–Bid–Build (DBB) (29), Design–Build (DB) (29), Public–Private Partnership (PPP) (17), and Engineering, Procurement, and Construction (EPC) (14), while Alliancing, Lean-oriented delivery approaches, and Construction Management were comparatively underrepresented. A temporal analysis indicates a recent shift toward collaborative delivery methods in BIM research. Case-based studies are predominantly situated in public sector projects, with DBB, DB, EPC, and IPD examined across both infrastructure and building contexts, while PPP is limited to infrastructure. The literature is largely focused on design and construction phases, with limited attention to early project stages and operation and maintenance. Results indicate both traditional and relationship-based PDMs are studied in the existing literature, with research framing PDMs that allow for early contractor involvement as most compatible with BIM. Moreover, IPD, DB, and EPC show the best alignment compared to most used traditional DBB methods primarily due to the early involvement of the contractor in the project. EPC and DB achieve this through the allocation of responsibility to the contractor, whereas IPD relies on the early engagement of key participants and the systematic alignment of their objectives. Collaborative and relationship-based approaches are consistently presented as the most suitable for BIM, while DBB tends to constrain BIM benefits because of its fragmented nature. This study contributes by providing a systematic synthesis of BIM-PDM relationships in the scientific literature, identifying the key mechanisms underlying the suitability of different delivery methods for BIM implementation, and offering recommendations for future research based on the identified gaps. Full article

Equitable prioritization of public investments is increasingly critical as municipalities face constrained budgets, heterogeneous neighborhood needs, and demands for transparent decisions. This paper proposes a fairness-aware group multi-criteria decision-making (MCDM) framework for ranking municipal infrastructure investments when budgets are constrained, and neighborhood needs differ. Six alternatives are assessed in the Istanbul case study: flood risk mitigation, inclusive public realm and cooling, smart and energy-efficient municipal assets, walking and cycling infrastructure, healthcare access improvements, and seismic retrofitting of public buildings. The criteria system combines efficiency, implementability, socio-environmental performance, and equity-oriented priorities through five main dimensions and 23 sub-criteria. In addition to cost, feasibility, and service effectiveness, the framework incorporates fairness-related criteria such as baseline need and deficit severity, vulnerability-targeting effectiveness, minimum service guarantee for the worst-off, and priority for low-accessibility centers. Public acceptance and environmental performance are also included. Stakeholder panels provide expert judgments using intuitionistic fuzzy sets, capturing membership, non-membership, and hesitation to reflect uncertainty. Criteria weights are derived with Intuitionistic Fuzzy Step-wise Weight Assessment Ratio Analysis (IF-SWARA), enabling importance elicitation and group aggregation without forcing crisp consensus. Alternatives are then ranked using Intuitionistic Fuzzy Combined Compromise Solution (IF-CoCoSo), which blends additive and multiplicative compromise solutions to balance overall performance with equity objectives. Robustness is assessed through sensitivity analysis by varying the γ parameter within the IF-CoCoSo procedure. A municipal case study demonstrates that healthcare access improvements achieve the highest compromise performance, followed by flood risk mitigation and seismic retrofitting of public buildings, while smart and energy-efficient municipal assets rank last. The findings confirm that explicitly embedding fairness criteria can shift municipal priorities toward alternatives that more directly reduce deprivation, risk, and spatial inequality. The main contribution of this study is not merely empirical application, but the development of a fairness-aware group MCDM framework that operationalizes distributive justice in municipal investment prioritization through a structured set of criteria. Full article

Corporate sustainability has emerged as a critical strategic imperative for organizations seeking to mitigate their environmental impacts amid escalating climate pressures and growing stakeholder demands. This study examines corporate strategies aimed at reducing environmental footprints—including circular economy models, energy efficiency measures, and digitalization—and investigates how young adults perceive and evaluate corporate sustainability commitments, with particular emphasis on greenwashing skepticism. A cross-sectional quantitative survey was administered to 150 university students and young professionals aged 18–25 years in Spain. Data were analyzed using descriptive statistics, analysis of variance (ANOVA), and linear regression to examine the influence of prior sustainability knowledge, academic background, age, and sectoral context on perceived corporate sustainability commitment, greenwashing perception, and willingness to consume sustainable products. The findings reveal that prior sustainability knowledge significantly and positively predicts higher evaluations of corporate environmental commitment, while age and academic background—particularly among students in Economics and Business—are associated with heightened greenwashing skepticism. Perceived corporate sustainability commitment is found to exert a significant positive influence on sustainable consumption intention, and production-intensive sectors are consistently perceived as more environmentally harmful than service-oriented industries. These findings underscore the importance of transparent, credible, and verifiable sustainability strategies in building legitimacy and trust among younger generations, and contribute to the growing literature on stakeholder perceptions of corporate environmental responsibility. Full article

The increasing penetration of wind generation requires performance evaluation methods that extend beyond average annual energy production. Temporal delivery characteristics, such as monthly dispersion and exposure to low-production periods, can influence both technical robustness and economic sensitivity. Building upon a previously developed probabilistic and entropy-based assessment framework, this study evaluates the robustness of delivery-oriented performance metrics for onshore and offshore wind units under parametric and economic uncertainty. Using high-resolution operational data from four wind units (three onshore and one offshore), the analysis incorporates percentile sensitivity, threshold variation in low-production exposure, bootstrap-based uncertainty intervals, and Monte Carlo simulation of economic inputs including CAPEX, operation and maintenance costs, and discount rate. The results indicate that variations in percentile definitions and stochastic economic assumptions modify absolute performance values but do not substantially alter the relative positioning between offshore and onshore units. Averaged over 2022–2024, the analyzed offshore unit exhibited a lower monthly energy dispersion coefficient ($C{V}_E=0.255$) [Reviewer2]than the analyzed onshore units ($C{V}_E=0.368$), [Reviewer2]corresponding to an approximate 30% reduction in relative variability. The offshore unit also showed lower mean low-production exposure ($LPE=0.526$ versus $0.581$ for onshore units) [Reviewer2]and consistently lower amplification of robustness-adjusted LCOE under conservative delivery assumptions. These results indicate that the analyzed offshore unit retains stronger delivery robustness and lower economic sensitivity across the tested parameter ranges. The proposed robustness-validation framework complements conventional yield-based assessments and provides additional insight for risk-aware evaluation of wind generation assets in renewable-dominated power systems. Full article

The electric vehicle (EV) battery industry has become a strategic pillar of the low-carbon transition, with far-reaching implications for industrial competitiveness and sustainability. This paper compares the policy mixes governing EV batteries in the EU and China and examines how different approaches shape technological innovation, industrial development, and export performance. A qualitative comparative case study is conducted, combining content analysis of core policy and regulatory documents with descriptive indicators on EV deployment, patenting activity, manufacturing capacity, and international trade. The analysis identifies two distinct but partly complementary policy models. The EU relies on innovation-driven and regulation-based instruments, coupling large research and development programs with stringent sustainability and circular-economy requirements; this model is associated with stronger performance in regulatory upgrading, collaborative innovation, and sustainability-oriented governance. China emphasizes demand expansion, large-scale fiscal support, and long-term industrial planning, which has accelerated capacity build-up, cost reductions, supply-chain integration, and manufacturing-based export competitiveness. The findings show that these contrasting policy mixes generate different technological trajectories and value-chain configurations, while both contribute to strengthening strategic competitiveness in the EV battery sector. More broadly, the study demonstrates that policy effectiveness depends less on any single instrument than on the coherence of the overall policy mix. It concludes that effective EV battery strategies should combine strong innovation incentives with mechanisms that support industrial scaling, supply-chain resilience, and high environmental standards. Full article

Urbanization and climate change intensify urban heat islands and air pollution; therefore, street canyon building planning that accounts for road orientation, shading, thermal environment, and ventilation is crucial. This study uses numerical simulations to investigate how non-uniform wall and road heating affects airflow and pollutant dispersion in street canyons under varying Richardson numbers (Ri) and heating scenarios (windward wall, leeward wall, road surface). The results indicate that large wall–atmosphere temperature differences combined with low incoming wind speed (high Ri) make thermal buoyancy a dominant control on canyon flow and pollutant transport. Heating of the leeward wall and road surface enhances ventilation and pollutant removal (prominently when the Ri ≥ 0.49), whereas heating of the windward wall suppresses dispersion and increases concentrations (prominently when the Ri ≥ 0.12). For a north–south street, diurnal solar heating produces strong micro-environmental contrasts. With easterly winds, morning heating of the windward wall elevates pollutant levels, while afternoon heating of the leeward wall promotes dispersion and lowers concentrations. Specifically, compared with the isothermal condition, the turbulent exchange rate at the top of the street canyon is enhanced to 1.71~6.86 times, while the convective exchange rate is suppressed to 58%~83% in the morning and enhanced to 1.21~1.92 times. These findings suggest that urban planning should limit windward wall temperature rises via shading and greening; thus, single-sided sidewalk and greening layouts on the windward side are recommended. Full article

As natural and anthropogenic hazards intensify, improving the performance of reinforced-concrete (RC) infrastructure within a resilience-oriented assessment framework while limiting environmental burdens has become an important challenge for sustainable construction. In this context, this study proposes an OpenBIM-based digital-twin methodology to compare two equivalent RC structural scenarios: a conventional solution and an alternative incorporating unprocessed waste sheep wool fibres into cementitious materials. Using an IFC-based model of a high-rise building, the workflow enables automated extraction of structural quantities and a consistent building-scale assessment of material use, environmental impacts, and circularity indicators. Laboratory evidence from the literature is translated into element-level performance criteria through a dual-factor selection strategy based on key structural properties and secondary indicators related to cracking and post-cracking behaviour. The results show that the wool-fibre alternative enables the incorporation of a relevant amount of waste wool into the structure while causing only negligible increases in embodied energy and carbon emissions relative to the conventional RC scenario. The selected formulations also maintain or improve the governing mechanical and serviceability-related factors, indicating potential benefits in crack control, toughness, and repairability. Overall, this methodology provides a reproducible pathway for linking laboratory-scale material innovation with building-scale digital assessment, supporting more sustainable and performance-aware decision-making in RC construction. Full article

Global climate change has brought issues of pollution and environmental protection to the forefront of public attention. The energy consumption and carbon emissions of buildings have become critical issues in energy conservation and emission reduction, and are important for environmental protection. This article focuses on typical residential buildings in Wuhan, a representative of regions with hot summers and cold winters, to study the impacts of different layout design parameters on energy consumption and carbon emission intensity of building complexes. VirVil-HTB2 was used for modeling and simulating building complex layouts, while SPSS was used for data analysis. This study shows that solar radiation is an important indicator for predicting building energy efficiency, directly affecting energy consumption and carbon emissions. We also examined the impact of building orientation, building spacing, staggered spacing, and the layout of open spaces between buildings on heating energy consumption, cooling energy consumption, and carbon emissions. Building spacing was positively correlated with cooling energy consumption and negatively correlated with heating energy consumption and carbon emissions. The effect of staggered spacing on energy consumption is greater in the south–north direction than in the west–east direction. Additionally, setting the building orientation to 135° results in the lowest carbon emissions. Under the idealized simulation conditions of this study, the west–east dispersed open-space layout is a preferable configuration for reducing carbon emissions from residential neighborhood buildings. This study explores the impact of layout design parameters on energy consumption and carbon emissions of building complexes in hot summer and cold winter regions, providing references for energy optimization and environmental sustainability research. Full article

Wicked problems spanning systemic educational inequities, economic disparities, and environmental sustainability resist most traditional change efforts. This theory-building article advances a systems explanation that introduces complex conceptual systems theory which models collective conceptualizations as complex adaptive systems composed of densely interconnected ideas. These systems stabilize around attractor states that generate emergent potentials for what becomes sayable, seeable, doable, and valuable, thereby constraining the very practices needed for transformation. The article defines core constructs and articulates operational principles for diagnosis and intervention in complex social and socio-technical systems. It then specifies a first-generation analytical workflow, complex conceptual systems analysis (CCSA), that integrates qualitative coding with network-based modeling to map conceptual architectures, identify attractor states, and locate leverage points where sustained pressure can catalyze system reorganization. Empirical grounding is provided through a synthesis of a decade-long research program reported in prior publications across multiple domains, rather than through a single new empirical dataset. Accordingly, the manuscript is organized as a theory-development and methodology contribution, moving from conceptual architecture to operational principles, analytic workflow, and cross-domain exemplars. The theory offers systems science a pragmatic, justice-attentive approach for anticipatory, intervention-oriented change in entrenched wicked problems. Full article

Urban heat dynamics are strongly influenced by the interaction between built structures, surface materials, and vegetation cover. This study investigates the relationship between land surface temperature (LST) and key urban morphological and structural parameters in a municipality of Thessaloniki, Greece. LST was retrieved from Landsat imagery using the NDVI-based emissivity method within Google Earth Engine (GEE). To characterize the urban form of the study area, a WorldView-2 summer image was classified to extract indices of surface roughness, built-up density, greenness density, building orientation and roof material type. Statistical analyses, including regression models and one-way ANOVA, were applied to assess the influence of these parameters on LST variability. Results reveal significant correlations between LST and both structural and vegetative factors, highlighting the cooling role of urban greenness and the amplifying effect of dense built-up areas and specific roof materials. The findings provide valuable insights into the spatial drivers of urban heat at a high-resolution scale, and offer practical guidance for planning strategies designed to lessen heat intensity in compact urban environments. Full article

This study develops a Life-Cycle Sustainability Framework for circular business models in the context of post-war economic reconstruction and sustainable value chain transformation. Ukraine is used as the main case study due to its post-war reconstruction context and the need for resource-efficient economic recovery strategies. Under conditions of disrupted supply systems, resource constraints, and structural economic change, circular economy principles are conceptualized as strategic mechanisms for enhancing resilience, resource efficiency, and long-term competitiveness rather than solely as environmental policy instruments. Building on a structured hierarchy of circular business models aligned with product life-cycle stages, the framework emphasizes value retention through functional and usage extension beyond material recovery. The framework includes a hierarchical classification of 12 circular business models and a sustainability evaluation approach based on four criteria (K1–K4), which allow for the comparative assessment of circular business models and their combinations across life-cycle stages. Using secondary statistical data and policy review as analytical inputs, the study identifies sectors with high potential for circular transformation and sustainable investment, including agriculture, energy, industry, construction, and logistics. The results indicate that circular business models applied at early life-cycle stages, such as reuse, repair, and remanufacturing, provide the highest potential for reducing resource intensity and improving long-term economic sustainability, while recycling and energy recovery play a supporting role. These findings highlight how life-cycle-oriented circular strategies can support sustainable reconstruction pathways, strengthen international cooperation, and inform policy and managerial decision-making in transitional economic contexts. Full article