Search Results (7,869)

Traditional benefit–cost analysis (BCA) summarizes the average net social benefit of a policy but often obscures how benefits and costs are distributed across groups. This is a major limitation in health policy settings, where decision-makers must assess both efficiency and equity. This article develops an integrated equity-weighted causal benefit–cost analysis (IEW-BCA) framework for equity-conscious policy evaluation. The framework links subgroup-specific causal effect estimates, explicit valuation functions, and equity weights within a single evaluation pipeline suitable for applied policy appraisal. It makes three contributions: first, it provides an implementable structure for combining causal heterogeneity with welfare-consistent valuation; second, it introduces a compound equity vector and associated weighting functions that extend income-based schemes and can be interpreted, under standard conditions, as a first-order approximation to a broad class of social welfare functions; and third, it develops equity-oriented summary tools, including a causal equity gradient and related dominance criteria, to improve transparency about distributional impacts. A stylized example illustrates implementation, and the discussion outlines implications for uncertainty, sensitivity analysis, and potential application in health economics, public health policy, and regulatory evaluation. Full article

Japan’s universal health coverage is often discussed in terms of broad access and regulated prices, but its national fee schedule also shapes how services are organized, governed, and delivered. Pediatric procedural sedation illustrates this governance function in short-horizon, safety-critical care, where quality depends not only on technical expertise but also on staffing, monitoring, recovery capacity, rescue readiness, and coordination across departments. In this setting, reimbursement policy, specialist capacity, patient safety, and short-term economic consequences intersect in routine practice. Japanese studies of pediatric magnetic resonance imaging suggest that comparative economic results are sensitive to sedation failure pathways and payment design, while the FY2026 medical fee revision signals a shift toward recognizing deep sedation as a managed clinical service rather than a simple act of drug administration. These issues extend beyond Japan, because many health systems face growing demand for procedural sedation under constrained specialist capacity. Value in this setting should therefore be considered more broadly than price or adverse events alone. It should also include implementation, family and system consequences, and the design of reliable service models. Reappraising value in this way may help move discussion beyond fee revision toward better alignment of payment, governance, measurable outcomes, and feasible service design. Full article

In this study, the double-neutral (3P + 2N) configuration, considered a traditional solution for busbar systems subjected to overcurrent and thermal stresses under harmonic loads, and alternative cross-sectional expansion (from 6 mm × 55 mm to 6 mm × 65 mm) scenarios are investigated using a multidisciplinary approach. In this context, the electrical, electromagnetic, current density distributions, and magnetic flux densities (B_max) of the systems are modeled in the COMSOL Multiphysics® (AC/DC Module 6.2 version) environment; the obtained q″ (W/m³) loss maps were transferred to FLOEFD convective airflow (CFD) simulations as volumetric heat sources, and steady-state electro-thermal analyses were performed. Convergence tests were conducted with the BiCGStab solver to ensure numerical stability, solver convergence, and spatial grid independence, and high accuracy was obtained at a margin of error of 3.5222 × 10⁻⁴. The findings showed that the proximity effect, due to the close placement of the pair of neutral conductors at the 150 Hz harmonic frequency, increased the current density to 4.68 A/mm² and turned the neutral line into an additional heat source. In contrast, in the 4-conductor scheme where all conductor cross-sections were increased by 18.18%, the magnetic flux density at 150 Hz was suppressed from 27.21 mT to 23.50 mT, and the current density was distributed more homogeneously, optimizing the temperature rise limits (ΔT). Furthermore, the techno-economic cost analysis conducted revealed that, under premium scenarios for LME raw copper and processed bar copper, the application of increased cross-sectional area offered an optimization that was approximately 5.77% more economical per meter (approximately $36 USD for a standard 3 m length) compared to the double-neutral configuration. Consequently, it has been proven that in BTS designs, not only total harmonic distortion (THD) but also the triplen harmonic ratio, frequency-dependent AC resistance (R_ac) variations, and material mass–cost balance should be considered together. Full article

There is ongoing debate about the value of infrastructure systems—energy, water, transport, waste, and communications—and how infrastructure investments should be prioritized to account for social, economic, and environmental wellbeing. The concept of an infrastructure system is inherently linked to interdependencies. Although infrastructure systems differ across countries and cities, they are all closely connected to transport, as movement involves both cost and utility. These systems ultimately exist to serve individuals, who assign value to them. To explore the full spectrum of value creation, which underpins business models, the relationship between individuals and transport infrastructure must be understood. This research tests the hypothesis that integrating economic, environmental, and social value dimensions within a unified business model provides a more comprehensive representation of infrastructure interdependencies than conventional economically focused approaches. Economic value was analyzed using principal component analysis of input–output tables, social value through structured interviews and statistical analysis, and environmental value using secondary data linked to economic demand in the infrastructure context of England, Scotland, Wales, and Northern Ireland. The proposed business model integrates social, economic, and environmental values, giving policymakers a clearer understanding of infrastructure system interactions and supporting more informed investment decisions that maximize societal value. Full article

The widespread adoption of EVs is expected to intensify peak demand, stress distribution networks, and increase carbon emissions if traditional grid-based charging models continue. Therefore, this study proposes a smart-grid-connected microgrid (MG) architecture for EV charging stations (EVCSs) that integrates renewables and energy storage, while incorporating incentive-based response (iDR) and net energy metering schemes into a single optimization framework. To maintain the quality of EV charging services, optimize grid interactions and MG reliability, and explore the socioeconomic impact of establishing such infrastructures, a comprehensive 4E optimization framework incorporating energy, environmental, employment, and economic metrics is developed. The suggested framework is applied to an urban case study in Riyadh, including realistic load profiles, tariff structures, EV charging behavior, network outage scenarios, NEM conditions, and an assumed iDR incentive scenario. A grid-dependent BES/Conv/Grid configuration optimized without iDR is adopted as the common reference for consistently evaluating all system configurations. Compared with this common reference, the results show that while renewable hybridization improves performance, the assumed iDR scenario provides further economic and operational benefits. The optimal iDR-enabled configuration achieves an 87.5% reduction in TNPC and a standard HOMER Grid LCOE of $0.0287/kWh, corresponding to a 67% reduction relative to the common grid-dependent reference. When electricity exports are excluded from the LCOE normalization, the corresponding load-serving LCOE is approximately $0.0372/kWh, which remains approximately 57.3% lower than the reference value of $0.0872/kWh. In addition, the optimal MG generates $63,128 in revenue/year through participation in iDR events without degrading EV charging service performance relative to the non-iDR scenario. Employment analysis indicates that the optimal system supports approximately 49 job-years of direct project-associated employment over the 25-year project lifetime through infrastructure deployment, operation, and maintenance, while ecologically, it limits annual grid-related CO₂ emissions to approximately 280.18 tons, representing about an 84.7% reduction relative to the reference scenario. These findings confirm that coordinated demand-side flexibility and intelligent storage dispatch can partially substitute for infrastructure oversizing, enabling cost-effective, low-carbon, and investor-attractive EVCS-based MGs aligned with sustainability targets. Full article

This review provides a comprehensive analysis of waste-to-hydrogen (WtH) pathways for the conversion of various types of WtH, focusing on hydrogen generation, energy efficiency, environmental implications, and economic viability. The result shows that feedstock characteristics influence each pathway’s feasibility and performance. Thermochemical treatment, particularly gasification, demonstrates high hydrogen yield and the processing versatility of heterogeneous wastes. Hydrogen concentrations of 10–45 vol% can be obtained by dry gasification, while 35–55 vol% H₂ and 70–90% carbon conversion can be obtained by plasma-assisted gasification. Hydrothermal gasification converts 45–70% of the energy in the feedstock, suitable for wet feedstocks. Pyrolysis produces H₂-rich gas along with bio-oil and char, while plasma-assisted pyrolysis could enhance H₂ production by up to threefold compared with conventional catalytic systems. Biological pathways are more suitable for wet and biodegradable wastes. Dark fermentation provides lower H₂ recovery than thermochemical routes, whereas sequential dark and photo-fermentation improves substrate utilization, achieving hydrogen yields of 4.44–4.96 mol H₂/mol glucose and hydrogen production efficiencies of 45.31–82.67%. Among the evaluated feedstocks, plastic waste achieved a hydrogen production rate of 189.6 kg H₂/h, but also generated up to 4.3 kg CO₂-eq/kg H₂. Mixed plastic waste achieved 0.29 kg H₂/kg waste at a levelized cost of hydrogen (LCOH) of 3.41 USD/kg H₂. Integrated systems demonstrated performance improvements, including 71.3% energy efficiency for anaerobic digestion and gasification with heat recovery, 61.6% for gasification coupled with electrochemical CO₂ reduction, and more than 99% CO₂ capture in the latter configuration. The LCOH from investigated pathways vary from 0.3 to 13.37 USD/kg H₂ for different feedstock, conversion technology, system configuration, and carbon management requirements. Overall, gasification appears promising for heterogeneous and energy-dense wastes, as well as biological routes for wet biodegradable fractions, while integrated configurations offer a promising strategy for balancing hydrogen recovery, energy efficiency, economic performance, and environmental impacts. Full article

Weather variability and CO₂ supply costs remain key barriers to the commercial viability of algal biofuel production. Recent experimental work has demonstrated that the algae Chlorella sp. strain SLA-04 achieves high productivity in extreme alkaline growth media (pH > 10), where the solution chemistry enables direct capture of atmospheric CO₂, eliminating the need for costly CO₂ sparging. Despite these promising results, the commercial-scale economic and environmental implications of this cultivation approach have not yet been assessed. Here, we present the first integrated Techno-Economic Analysis (TEA)/Life-Cycle Analysis (LCA) of high-pH–high-alkalinity production. We compare four SLA-04 cultivation scenarios with a baseline strain cultivation scenario with Nannochloropsis oceanica. These scenarios also include the first incorporation of Trona, a naturally occurring carbonate mineral and the primary domestic source of bicarbonate in the United States, into our TEA/LCA framework as a low-cost alternative to commercial NaHCO₃ for establishing the high-alkalinity growth medium. Our results indicate that the SLA-04-Trona scenario reduces carbon intensity and present value of lifetime expenses by 40% and 55% on a per-gallon basis, while simultaneously exhibiting lower production variability across all seasons. Quarterly revenues reflected an improvement of $6 million over the baseline strain revenue over 40,000 simulations. Modeled productivity was lower than what was observed experimentally and resulted in a MBSP of $705/ton. These findings provide the first quantitative evidence that high-pH–high-alkalinity cultivation can substantially improve both the economics and environmental footprint of commercial-scale algal biofuel production. Full article

Economically motivated adulteration of powdered ginger with low-cost cereal flours represents an increasing concern for food authenticity and quality control. The aim of this study was to develop and validate a rapid, reliable, and non-destructive method for the quantitative determination of powdered ginger adulteration using visible and near-infrared (Vis–NIR) spectroscopy coupled with chemometric modelling. Ginger powder samples were adulterated with wheat, corn, and rice flours at concentrations ranging from 5 to 50% (w/w), with particular emphasis on the low-to-medium adulteration interval (10–25%), where reliable quantification is especially relevant for food fraud detection. Spectral data acquired in the visible (400–700 nm), near-infrared (700–2500 nm), and combined Vis–NIR (400–2500 nm) regions were preprocessed using Savitzky–Golay filtering and evaluated using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest Regression (RFR). In addition, Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Random Forest (RF) were compared for sample classification. Among the evaluated approaches, LDA achieved the highest classification accuracy (>95%) using the NIR spectroscopic region, while PLSR models developed from the NIR spectral region provided the best quantitative performance, with validation coefficients of determination above 0.99, prediction errors below 1%, and RPD values greater than 13. The results demonstrate that Vis–NIR spectroscopy combined with chemometric modelling enables accurate discrimination between authentic and adulterated samples, as well as reliable quantification of flour adulteration in powdered ginger without sample preparation or chemical reagents. The proposed methodology constitutes a rapid, environmentally friendly, and cost-effective analytical strategy with strong potential for routine quality control and food fraud prevention. Full article

Photovoltaic (PV) deployment is expanding rapidly, but the climate and economic value of identical generation varies with electricity-system and market conditions. This study examines whether avoided-emission rankings align with project-level financial valuation when physical project characteristics are held constant. A documented 1.101 MWp PV project, with expected annual generation of 1592.6 MWh/year, was assessed counterfactually across seven regional electricity groupings, with Brazil as the reference case. The framework integrates generation-weighted emission factors, avoided-emission accounting, discounted cash flow, carbon-abatement costs, deterministic sensitivity analysis, Monte Carlo simulation, and exploratory Pearson and Spearman correlations with exact permutation inference. To address the physical variability of the reference asset, an auxiliary hourly PV simulation covering ten complete years (2016–2025) was additionally performed using solar irradiance, ambient temperature, and wind-speed data. The modeled annual generation averaged 1472.4 MWh/year, with a coefficient of variation of 1.44%, indicating limited interannual variability over the evaluated decade. Financial indicators were evaluated over a 20-year horizon, whereas lifetime avoided emissions and carbon-abatement costs were assessed over a 25-year technical lifetime. The Arab League presented the highest avoided emissions (1005 tCO₂/year; 6.1 times Brazil) but the weakest base-case financial result: a net abatement cost of approximately USD 7/tCO₂ and a 70.1% probability of positive NPV. The European Union achieved the highest NPV, a net abatement cost of approximately −USD 255/tCO₂, and a 100% probability of positive NPV despite lower mitigation. An inverse association between emission factor and electricity tariff further characterized this mismatch (Spearman’s $\rho =-0.786$; exact permutation $p=0.048$). The results show that physical PV production, mitigation potential, and project-level financial valuation represent distinct but complementary dimensions that should be assessed jointly when comparing PV deployment contexts. Full article

Battery energy storage systems (BESSs) are increasingly coupled with photovoltaic (PV) generation, yet their deployment is governed by economics rather than by technical feasibility. This review synthesises 122 indexed Q1/Q2 studies (2016–2026) on the financial payback and return on investment of PV-coupled storage, extending the analysis to vehicle-to-grid (V2G) integration. Records retrieved from Scopus, Web of Science, IEEE Xplore, and the MDPI portal were screened to peer-reviewed journals, assigned to ten thematic clusters, appraised against a ten-criterion reporting-transparency rubric, and combined by narrative synthesis. Reported payback periods range from a few years to beyond the asset’s service life, and the levelized cost of storage spans roughly 170–350 USD/MWh. In the reviewed corpus, the retail-to-export price spread, the stacking of self-consumption, arbitrage, grid-service revenues, and degradation-aware operation each move returns in a consistent direction, whereas which of them binds hardest is a property of the case rather than a ranking the evidence supports. V2G is almost always analysed in isolation from stationary storage; an illustrative harmonised comparison indicates that it substitutes for stationary capacity rather than adding to it. The review maps the combined PV+BESS+V2G revenue stack and identifies an integrated, degradation-corrected, policy-sensitive economic model as the principal research gap. Full article

Background and Objectives: Artificial intelligence (AI) tools promise efficiency gains in oncology, yet adoption depends on economic factors that remain under-characterized in Eastern European health systems. We quantified AI economic literacy, cost-effectiveness perceptions, reimbursement readiness, and return-on-investment (ROI) confidence among Romanian oncology professionals; we described candidate economic adoption profiles and examined whether sector was associated with the strength of the indirect association between literacy and willingness to invest via ROI confidence. Materials and Methods: A multicenter cross-sectional survey (N = 108) was conducted between September 2025 and April 2026 at “Victor Babes” University of Medicine and Pharmacy Timisoara and affiliated oncology services. Participants completed a 25-item AI Economic Literacy Index (AIELI; 0–25) plus 1–5 scales for ROI confidence, willingness to invest, perceived financial barriers, cost-effectiveness perception, and adoption intention. Analyses used Spearman correlations, multivariable logistic regression, k-means clustering, and covariate-adjusted moderated mediation with 5000 bootstrap resamples. Results: Mean age was 41.3 ± 10.7 years; 58.3% were female. AIELI was moderate (13.7 ± 4.6/25). Familiarity favored cost-effectiveness analysis (59.3%) over AI-specific reimbursement codes (16.7%). High willingness to invest occurred in 48.1% and was independently associated with higher AIELI (aOR 1.78 per +1 SD; 95% CI 1.17–2.71), higher ROI confidence (aOR 1.93; 1.24–3.02), lower perceived financial barriers (aOR 0.58; 0.37–0.91), and prior AI training (aOR 2.34; 1.13–4.86). Three exploratory profiles were identified: Cost-Conscious Adopters (n = 43), Reimbursement-Cautious (n = 37), and Budget-Constrained Skeptics (n = 28). Moderated-mediation models were consistent with a sector-conditional indirect association, largest in private clinics (β = 0.193; 95% CI 0.087–0.318) and weakest in public hospitals (β = 0.072; 0.014–0.158). Conclusions: In this exploratory cross-sectional sample, AI economic literacy and ROI confidence were associated with willingness to invest in oncology AI, interpreted as stated support for investment rather than an enacted procurement decision, since many respondents lacked formal budgetary authority. Because the design cannot establish temporal ordering, whether sector-tailored capability-building and reimbursement clarity would increase adoption remains a hypothesis for prospective evaluation. Full article

Lithium-ion batteries are widely used in electric mobility, renewable energy integration, portable electronics, and renewable–hydrogen hybrid energy systems. Despite significant advances in battery materials and design, long-term degradation remains a major challenge that affects system reliability, efficiency, and economic viability. In renewable–hydrogen hybrid architectures, battery degradation influences not only energy storage performance but also hydrogen production stability, electrolyzer operation, fuel cell utilization, and overall system efficiency. Major degradation mechanisms include solid electrolyte interphase (SEI) growth, electrolyte decomposition, lithium inventory loss, transition-metal dissolution, particle cracking, and structural phase transformations. This review provides a comprehensive assessment of degradation mechanisms affecting lithium-ion battery components and their implications for renewable–hydrogen hybrid systems. Advanced characterization techniques, including in situ and operando X-ray diffraction, electron microscopy, spectroscopy, electrochemical impedance spectroscopy, cyclic voltammetry, and differential capacity analysis, are examined for their ability to reveal chemical, structural, and morphological changes during battery operation. Particular emphasis is placed on the effects of dynamic load variations, partial state-of-charge cycling, temperature fluctuations, and intermittent renewable energy inputs that accelerate degradation in hybrid systems. The review further discusses mitigation strategies such as surface engineering, electrolyte optimization, material doping, thermal management, intelligent energy management systems, predictive maintenance, and machine learning-based prognostics. Key challenges associated with battery–hydrogen integration, including efficiency trade-offs, component ageing, hydrogen production stability, and lifecycle costs, are critically analysed. The adaptability of hybrid systems under varying operating conditions is also explored, highlighting the importance of degradation-aware control strategies, digital twins, and real-time diagnostics. Finally, future research directions are identified, including multiscale characterization, physics-informed machine learning, techno-economic optimization, and life-synergy modelling. These approaches are essential for developing reliable, adaptive, and cost-effective renewable–hydrogen hybrid energy systems capable of supporting long-term decarbonization objectives. Full article

The construction industry is increasingly pressured to reduce its environmental footprint through the adoption of sustainable materials and digital innovation. This literature review examines the convergence of Building Information Modeling (BIM) and related digital technologies with bio-based and sustainable construction materials, aiming to enhance environmental, economic, and social sustainability performance. A descriptive search of Scopus, Web of Science, and IEEE Xplore databases yielded 94 peer-reviewed articles published between 2015 and April 2026. The analysis identifies three principal integration pathways: (i) material quantification and environmental accounting through BIM−LCA integration, (ii) parametric design exploration and multi-objective optimization, and (iii) life cycle coordination via digital twins and automated fabrication. BIM was identified in 62 of 94 publications (66%), making it the dominant technology, followed by LCA (35 publications, 37%) and digital twins (25 publications, 27%). Findings indicate that BIM functions as a central enabling platform, improving material traceability, design accuracy, and decision-making quality particularly by managing the inherent variability of bio-based materials through moisture-dependent parameters, sourcing data, and performance monitoring. While environmental sustainability—particularly embodied carbon reduction—dominates the literature, economic and social dimensions remain underexplored, appearing in less than 1.1% of reviewed studies. The review also highlights persistent barriers, including data interoperability issues, high upfront costs, limited material databases, and skill gaps. Drawing on socio-technical systems theory, a conceptual framework is proposed to illustrate the interdependencies between digital capabilities, bio-based material strategies, and sustainability outcomes. A three-stage implementation roadmap is outlined to support practitioners in adopting BIM-enabled bio-based workflows. The review concludes that the synergy between digital technologies and renewable materials offers a promising trajectory toward circular, low-carbon construction, but calls for more longitudinal empirical research, standardized sustainability metrics, and integrated assessment frameworks that encompass social and economic considerations alongside environmental performance. Full article

Road crashes undermine the sustainability of transportation systems by generating substantial human, social, and economic costs. Identifying the factors associated with severe crash outcomes is therefore essential for supporting safer and more sustainable mobility, in accordance with Vision Zero and Sustainable Development Goals 3.6 and 11.2. This study investigates the influence of behavioral, environmental, and infrastructural factors on road crash severity through a comparative evaluation of three modeling approaches: Ordinal Logistic Regression (OLR), eXtreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost). The analysis was based on 5194 police-reported crash records from Cyprus covering the period 2015–2024. The dataset included crash severity outcomes together with traffic violations and roadway and environmental conditions. The results identified speeding, substance use, and improper turning maneuvers as influential predictors of crash severity. Among the evaluated models, CatBoost achieved the strongest overall predictive performance, obtaining the highest accuracy (0.52), weighted area under the curve (AUC) (0.72), weighted precision (0.50), and weighted recall (0.52), while CatBoost and XGBoost tied for the highest weighted F1-score (0.48). CatBoost’s overall performance reflects its ability to efficiently process categorical variables and capture nonlinear relationships without extensive preprocessing. The findings highlight the dominant role of driver behavior in determining crash severity and demonstrate how the comparative modeling framework can serve as an analytical decision-support tool for identifying and monitoring crash-severity risk factors, prioritizing targeted interventions, and supporting progress towards safer and more sustainable transportation systems. Full article

Appropriate-scale operation is important for integrating ordinary farm households into modern agriculture, yet the appropriate scale may differ substantially across producer types. Using micro-level data from the nationally representative 2021 China Household Finance Survey, this study develops an analytical framework integrating efficiency and resilience perspectives to compare ordinary farm households and family farms. Efficiency is the core empirical dimension and is assessed using cost–benefit analysis, the DEA-BCC model, and multivariate econometric methods. Resilience is treated as a theoretical perspective and a constraint on scale decisions; it is interpreted indirectly through the scale responses of the two groups to disaster shocks rather than measured using a standalone resilience index. The results identify distinct efficiency-based appropriate-scale ranges: 1–3 mu (approximately 0.07–0.20 hm²) for ordinary farm households and 100–200 mu (approximately 6.67–13.33 hm²) for family farms, with lower net profit per unit area at intermediate scales. Economic rationality and institutional constraints show marked heterogeneity across producer types: commercialization, land titling, subsidies, and credit access are more strongly associated with the scale expansion of family farms, whereas non-farm employment opportunities play a more decisive role for ordinary farm households; household labor and social networks contribute to scale expansion in both groups, and their between-group differences are not statistically significant. Disaster impact is associated with a significant reduction in the operational scale of ordinary farm households, whereas in the subgroup estimates the operational scale of family farms shows no significant association with disaster impact, suggesting that family farms are better able to maintain their operational scale. Digital technology also operates through differentiated pathways: it primarily alleviates information and factor constraints among ordinary farm households while strengthening efficiency, financial access, and organizational coordination among family farms. These findings support differentiated scale and digital-agriculture policies in economies characterized by heterogeneous farm structures. Full article