This study presents a quantitative microbiological risk assessment (QMRA) model to evaluate the public health, economic, and environmental implications of microbiological sampling plans for Salmonella spp. in chicken patties. The farm-to-fork model includes production, processing, storage, cooking, and consumption modules, and incorporates a sampling algorithm that simulates batch-level testing under the current EU microbiological criterion (n=5, c=0) as well as alternative sampling intensities. Coupling exposure estimates with a dose-response model allows quantification of expected salmonellosis cases per sampling regime. Economic impact is quantified as the net societal return, calculated as the avoided economic burden of salmonellosis minus the costs of microbiological testing and batch rejection, while environmental impact is measured as discarded batches and associated food waste. Sampling reduced illness risk only modestly across all evaluated scenarios. Within the practically relevant range (n=0-10), risk reductions remained negligible, while both economic cost and food waste increased proportionally with sampling intensity. Higher sampling levels (n≥30) produced slightly larger reductions in predicted cases but still resulted in limited absolute public health gains relative to the escalating monetary and environmental costs. Sampling was more effective in high-contamination production systems, where detection is more likely, and far less impactful in modern high-performance facilities with low baseline contamination. By simultaneously quantifying public health, economic, and environmental outcomes, the proposed model provides a harmonized basis for risk-benefit and sustainability assessments. The results highlight that the effectiveness of sampling is context-dependent and may benefit from risk-based optimization within One Health decision-support frameworks.

A case study on optimizing thermal bridges in integrated insulation and decoration exterior walls: Balancing thermal performance and economic cost

Life cycle assessment as a tool for eco-design of modified materials for water treatment

Exploring the societal cost of major lower limb amputations in patients with type 2 diabetes - A nation-wide and matched register study using difference in difference analysis.

Energy infrastructure constitutes not merely technical hardware but a fundamental determinant of socioeconomic transformation and industrial evolution. While the engineering attributes of Ultra-High Voltage (UHV) transmission have been extensively documented, its role in shaping corporate behavior and catalyzing industrial upgrading remains underexplored. UHV transmission, operating at direct-current voltages of 800 kV and above or alternating-current voltages of 1000 kV and above, has been systematically deployed across China since 2007 to bridge the structural spatial mismatch between inland energy production centers and coastal consumption hubs. This study investigates the sociotechnical nexus between energy systems and firm-level innovation, employing China's large-scale UHV expansion (2007–2024) as an empirical setting with implications for global energy transition strategies. Integrating energy economics with organizational behavior theory, we adopt a staggered difference-in-differences approach to examine how enhanced energy accessibility influences automation innovation. The findings demonstrate that reliable energy infrastructure functions as a catalyst for intelligent manufacturing, operating primarily through the restructuring of business environments via cost reduction, risk mitigation, and the realization of economies of scale. Importantly, the analysis reveals substantial heterogeneity: policy effects are amplified among state-owned enterprises and regulated industries, reflecting the interplay between institutional arrangements and technology adoption. Furthermore, this study uncovers a significant resource redistribution effect whereby firms in net electricity-importing regions derive disproportionately greater benefits, suggesting that strategic infrastructure deployment can compensate for regional resource disadvantages. By situating these findings within a broader analytical framework, this research offers actionable insights for policymakers seeking to leverage energy infrastructure investments as instruments for advancing industrial modernization and fostering sustainable business practices. • Ultra-High Voltage (UHV) expansion significantly drives corporate automation. • Cost reduction and economies of scale mediate the impact. • Electricity-importing regions benefit more from the grid. • Effects are amplified in SOEs and regulated industries. • Energy infrastructure serves as a tool for industrial upgrading.

The European Union's Deforestation-Free Regulation (EUDR), approved in 2023 and set to take effect in December 2026, mandates plot-level traceability and physical segregation of compliant from non-compliant products in supply chains linked to deforestation. This paper assesses the economic and environmental impacts of EUDR compliance costs on Brazil's soybean supply chain. Using a dynamic multiregional computable general equilibrium (CGE) model with integrated land-use transitions, we simulate counterfactual outcomes from 2026 to 2035 under two policy scenarios: (i) Legal Amazon–only coverage (S1-AMZN) and (ii) nationwide coverage (S2-BRA). Compliance costs are modeled as production-tax equivalents, scaled by the regional share of EU-bound soybean-equivalent exports. Results show cumulative export losses of US$ 85.1 billion (S1-AMZN) and US$ 216.3 billion (S2-BRA), with corresponding real GDP shortfalls of US$ 409.9 billion and US$ 1.167 trillion. Avoided deforestation ranges from 51,466 to 105,899 ha, though leakage effects emerge under S1-AMZN. Estimated abatement costs are US$ 133–207 per ton of CO₂e, while forgone GDP per hectare of avoided deforestation ranges from US$ 58,630 to US$ 171,652. These findings suggest that clearing the EU's soy supply chain of deforestation alone delivers limited environmental benefits at high economic cost, underscoring the need to complement trade-based measures with robust domestic land-use governance and enforcement policies. • EUDR lowers Brazil's GDP slightly and deepens regional income disparities • Soy export losses drive land and labor shifts toward corn, cotton, and other crops • Welfare gains for the poorest and richest, losses for middle incomes • Modest avoided deforestation at high economic cost • National versus Amazon-only enforcement yields similar macro but less leakage

Advances in metal-organic framework-based drug delivery system in cuproptosis-mediated cancer therapy.

Cigarette butts constitute the most ubiquitous plastic litter worldwide, serving as a persistent source of microplastic fibers and toxic chemical leachates in terrestrial and aquatic ecosystems. Primarily made of cellulose acetate, discarded butts degrade slowly via physicochemical processes, liberating cigarette butt-derived microplastics alongside hazardous additives such as nicotine, heavy metals, and polycyclic aromatic hydrocarbons. This PRISMA-guided narrative review consolidates evidence on the environmental prevalence, transport, and fate of these microplastics, rigorously appraises progress in analytical detection methods, and evaluates their ecotoxicological impacts across food web levels. Studies reveal induction of behavioral changes, elevated mortality, and bioaccumulation in aquatic species, with particles functioning as carriers for persistent organic contaminants and metals. The review also addresses the considerable economic costs of cigarette butt pollution and scrutinizes mitigation options, including cutting-edge removal techniques, extended producer responsibility schemes, and circular-economy pathways such as cellulose acetate reclamation and composite sorbent fabrication. Persistent gaps exist in long-term degradation patterns, realistic exposure limits, and practical remediation efficacy, necessitating focused research to support evidence-based policies and sustainable waste management.

Assessment of the inaccuracy associated with the quantification of phenolic compounds using UHPLC-DAD and HPLC-MS/MS.

Seismic design codes typically adopt the Life Safety (LS) performance level using a high response modification factor (R), allowing structures to undergo inelastic deformations during strong earthquakes. However, higher performance objectives such as Immediate Occupancy (IO) require lower R values, resulting in higher design forces and increased construction costs. This study investigates the impact of reducing the response modification factor from R = 8 (LS) to lower values (R = 3, 2, and 1) on building construction costs. A reinforced concrete building was modeled and analyzed using finite element methods under identical loading conditions, with only the R factor varied. Results show that reducing R from 8 to 1 increases total construction cost by approximately 52%, primarily due to significant increases in concrete volume and structural member sizes. The findings highlight a clear trade-off between seismic performance and economic cost, providing valuable insight for performance-based seismic design decisions.Using a lower response reduction factor (R = 3) slightly increases initial costs (under 16%) but is justified by lower future maintenance and repair costs due to improved earthquake resistance.

Knowing how to implement emergency material scheduling and transportation during emergency rescues, such as major and critical emergencies, has become a research hotspot in academia and industry in recent years. To leverage the speed and terrain-insensitive advantages of aviation, the weak limitations of geographical conditions must be addressed, and the material scheduling efficiency of aviation rescue centers in disaster-stricken areas needs to be improved. In this study, CRITIC and cloud model theory were integrated to evaluate the urgency of emergency material demands in different flood-stricken areas under catastrophic flood disaster risks. Furthermore, a mathematical model for a single aviation emergency rescue center to dispatch emergency materials to multiple disaster-stricken sites was designed based on the optimized ant colony algorithm. A penalty function was then incorporated to formulate a multi-objective aviation scheduling model, aiming to minimize both total rescue time and total cost. The model was solved using an improved genetic algorithm. Taking rainstorm-induced flood disasters in the megacity of Zhengzhou, China, in 2021 as the empirical research case, the operating paths for the aviation emergency rescue center to serve multiple demand points were optimized. The impact of material demand urgency on scheduling decisions was analyzed. Results revealed that when material demand urgency is considered, aircraft complete deliveries according to urgency rankings and return to the center. All tasks can be completed within the required time via four routes. Although total time increases, economic cost is significantly reduced, and disaster loss is mitigated. The findings obtained from this study provide a decision-making reference for improving the efficiency of aviation emergency rescue and enhancing urban risk management capabilities in response to major and critical emergencies.

Abstract Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

The outbreak of the Ukraine war in 2022 marked a fundamental turning point in the geopolitical equations of Central Europe and significantly reshaped the region’s security order. In this context, Slovakia— a small yet strategically located country at the heart of Europe, sharing a direct border with Ukraine and holding membership in the European Union, the Eurozone, and the North Atlantic Treaty Organization (NATO)—has assumed a distinctive position that necessitates a redefinition of its role and status within the regional geopolitical and security structure. Adopting an analytical–explanatory approach and drawing upon the frameworks of critical geopolitics and small state theory, this article examines Slovakia’s geopolitical position in Central Europe following the outbreak of the Ukraine war. It argues that recent developments have simultaneously generated new opportunities and challenges for the country. From a geographical perspective, Slovakia lies at the intersection of major East–West European corridors and functions as a connecting link between the Carpathian region, the Danube basin, and the geopolitical space of Eastern Europe. Sharing borders with Ukraine, Poland, the Czech Republic, Austria, and Hungary, Slovakia is situated at the center of a dense network of security, energy, and transit interactions. The Ukraine war has transformed this structural geographic feature into an active geopolitical variable. Slovakia has become one of the principal routes for the transfer of military and humanitarian assistance to Ukraine and a focal point for the reinforcement of NATO’s presence on the Alliance’s eastern flank. The deployment of multinational NATO forces on Slovak territory and the expansion of defense cooperation with the United States reflect the country’s increased strategic importance within Western deterrence strategies vis-à-vis Russia. In the energy domain, Slovakia’s historical dependence on Russian gas and oil has represented a major geopolitical vulnerability. With the intensification of EU sanctions against Russia and disruptions in energy flows, Slovakia has been compelled to diversify its energy supply sources and reconsider its transmission infrastructure. Although this transition has imposed short-term economic costs, it may strengthen Slovakia’s long-term position as a transit hub within Central Europe’s evolving energy network. Moreover, the country’s location along North–South and East–West transport corridors—particularly within the framework of the Three Seas Initiative and EU cohesion policies—has gained renewed significance in the context of regional restructuring. Politically, the Ukraine war has generated fractures within the Visegrád Group (V4). While Poland and the Czech Republic adopted firm pro-Ukr aine stances, Hungary pursued a more cautious and comparatively Russia-leaning approach. Slovakia, amid domestic political fluctuations and changes of government, has sought to balance its Euro-Atlantic commitments with internal socio-economic pressures. This dynamic demonstrates that Slovakia’s geopolitical position is shaped not only by structural external variables but also by domestic political developments, public opinion, and party competition. The rise of populist and Eurosceptic discourses may influence the direction of the country’s foreign and security policies, potentially complicating its strategic alignment. The findings suggest that the Ukraine war has relatively elevated Slovakia’s geopolitical weight in Central European affairs, yet this elevation has been accompanied by increased risks and vulnerabilities. Slovakia now stands on the frontline of NATO’s deterrence posture, and any further escalation between Russia and the West could have direct security implications for the country. At the same time, EU and Eurozone membership provide institutional and economic stability that enhances Slovakia’s resilience against geopolitical shocks. At the macro level, Slovakia’s geopolitical status appears to have shifted from a “peripheral–transit” position to a “frontline–strategic” one. This transformation necessitates a recalibration of the country’s security doctrine, energy policy, and development model within the context of Europe’s evolving order. The future trajectory of Slovakia’s geopolitical position will largely depend on the continuation or resolution of the war, the internal cohesion of the European Union, the level of U.S. commitment to European security, and domestic political developments within Slovakia. Ultimately, Slovakia represents a compelling case study of how major geopolitical transformations affect small states in the contemporary international system—states that, despite limited material capabilities, may exercise influence disproportionate to their size when structural conditions shift in their favor.

ABSTRACT The increasing integration of renewable energy sources into smart grids presents substantial challenges in solving the nonlinear and nonconvex optimal power flow (OPF) problem. This paper proposes a comprehensive OPF model that incorporates conventional thermal generators, solar photovoltaic generators, and hydroelectric power generators, while effectively addressing the uncertainties associated with renewable power generation. A lognormal probability distribution models solar irradiance variability in solar generators, while a Gumbel distribution captures water availability fluctuations in hydro generators. The paper proposes a novel hybrid optimization approach, hybrid osprey‐salp swarm optimization (HOSSO), to solve this complex OPF problem. The HOSSO leverages the exploration–exploitation balance of Osprey Optimization alongside the adaptive leadership and follower dynamics of Salp Swarm Optimization. The proposed methodology is validated on Institute of Electrical and Electronics Engineers 30‐, 57‐, and 118‐bus test systems across five distinct optimization scenarios: economic cost minimization, emission cost minimization, combined economic–environmental cost minimization, voltage deviation penalty cost minimization, and renewable generation uncertainty penalty cost minimization. The model incorporates reserve and penalty costs for renewable generation uncertainty and integrates carbon emission taxation to enhance grid reliability and sustainability. Comparative analysis against classical and hybrid optimization techniques demonstrates the superior performance of HOSSO across most test scenarios, consistently achieving competitive solutions while satisfying system constraints and stability requirements. The algorithm delivers improvements ranging from 0.4% to 17% in cost minimization, 3%–23% in voltage deviation minimization, and 2%–8% in uncertainty management over competing methods, with performance advantages becoming increasingly pronounced as system scale grows. The algorithm exhibits rapid convergence within 20–50 iterations, effectively avoids local optima, and proves well‐suited for both single‐ and multiobjective OPF problems in renewable energy‐integrated power systems. The results highlight HOSSO's potential for real‐time power system applications and its adaptability to smart grids with high renewable energy penetration.

Urban environmental noise has emerged as a critical public health risk globally due to its extensive impact on human life and health. This study conducts a comprehensive assessment of Urban Environmental Noise (UEN) and Urban Traffic Noise (UTN) across 36 major Chinese cities from 2007 to 2023, integrating spatiotemporal analysis, Disability-Adjusted Life Years (DALYs), and economic valuation. Results indicate that UTN (median 66 to 70dB) consistently exceeds UEN (median 52 to 56dB), with significant spatial differentiation observed across the studied cities. Spatially, high-density hub cities (such as Beijing, Shijiazhuang, and Chongqing) bear a substantially higher health burden from noise pollution. Furthermore, the estimated health burden is dominated by sleep disturbance (YLDHSD), which consistently outweighs noise annoyance (YLDHA). Nonlinear relationships were also observed between noise levels and the attributable environmental burden. The annual economic loss attributed to traffic noise across these cities is estimated at 3.59 billion USD, representing a significant economic cost to sustainable urban development that has previously been overlooked. These findings suggest that noise pollution prevention and control in China need to shift from compliance-based monitoring to health-centric interventions and localized noise management strategies are urgently required.

Abstract Background Australia has adopted two policies that the World Health Organization (WHO) recommends as best practice for tobacco control: it has steeply increased tobacco taxes since 2010 and only allowed access to nicotine vapes for medical use. Argument The rate of decline in tobacco smoking in Australia has slowed in the past decade but may have recently increased. At least half of all tobacco cigarettes and most vapes in Australia are now purchased from an illicit market that exceeds the size of the combined Australian illicit markets for cannabis, cocaine, heroin and ecstasy (MDMA). An estimated $7 billion in tobacco excise and arson attacks on tobacco retailers have prompted large increases in law enforcement funding. Based on the experience from other illicit markets, increased enforcement will at best limit sales but at likely enormous social and economic cost and, specific to nicotine, constraining access to vapes and thus potentially leading to more smoking. New Zealand, which allows vapes to be sold as consumer products under public health‐oriented regulations, has shown a faster decline in the prevalence of cigarette smoking than Australia. It also has high tobacco taxes but a much smaller illicit tobacco market. Conclusions Punitive taxes on cigarettes and restricted access to lower‐risk nicotine products have diverted Australians who use nicotine into illicit markets and may also have increased cigarette smoking among young people. Australia should allow easier consumer access to less harmful alternative nicotine products to help bring the illicit tobacco and nicotine markets under better control.

Routine data quality audits (RDQA) are a critical activity conducted by many country malaria programs to assess the reliability of reported malaria data, but it requires significant human and financial resources. In collaboration with the Zambia National Malaria Elimination Centre, PATH's Malaria Control and Elimination Partnership in Africa (MACEPA) proposed a framework for identifying cost efficiencies in RDQAs. To demonstrate this approach, previously collected RDQA data from Zambia was used as a case study. A systematic, replicable framework to identify cost efficiencies in malaria RDQA interventions was developed by applying health economic evaluation principles and micro-costing methods. The framework consists of four sequential stages: (1) Conduct a costing analysis to estimate costs of the RDQA interventions by estimating financial and economic costs of all RDQA phases (planning, orientation, audit, feedback); (2) Identify cost drivers of RDQA interventions through comparative analysis of total costs, cost per health facility catchment area (HFCA), and proportional contribution of each cost category, activity, and phase across multiple RDQA interventions; (3) Develop resource-optimized scenarios by adopting the lowest-cost feasible practices; (4) Evaluation of cost-efficiency of scenarios using incremental cost per additional HFCA audited compared to the base-case implementation. Nine RDQA interventions implemented by four projects in Zambia (2022-2024) covering 10 provinces, 91 districts, and 1,189 HFCAs were evaluated. The proposed framework estimated the average economic costs of $24,938 per intervention ($205 per HFCA), with personnel (64%) and transportation (25%) as primary cost drivers of RDQAs in Zambia. Optimized scenarios incorporating virtual orientation meetings, streamlined audit team composition, and harmonized allowances reduced total costs by 41%. Transition to digital RDQA tools projected additional savings of up to 52%. This structured four-stage framework provides a practical methodology for identifying substantial cost efficiencies in RDQA interventions while maintaining or expanding coverage and quality. The analysis has strong implications for policy makers, funders and implementers of malaria programs on optimizing resource utilization for maintaining high-quality routine malaria data. The approach can extend to other disease-specific interventions or analogous activities, such as supportive supervision visits, enabling more sustainable implementation in countries facing similar resource constraints in health programs.

This study addresses the inconsistent understanding of how Information and Communication Technology (ICT) impacts deeply entrenched corruption, specifically nepotism and bribery, which impose significant global economic costs. Academic research is sparse on how e-government solutions mitigate these issues, particularly in regions like the Middle East where localized corruption, such as Kuwait's 'wasta' (nepotism), is pervasive. The authors investigate this using Kuwait's “Sahel” application, a unified e-government platform. Through a custom-designed user perception questionnaire, the research explores whether the availability and use of official IT applications help overcome these distinct forms of corruption. The authors hypothesize that poor informational privacy and information overload positively correlate with both nepotism and bribery. Furthermore, they posit that bribery can act as a catalyst for nepotism.

Motor vehicle exhaust in urban tunnels can cause nitric oxide (NO) to accumulate, severely degrading air quality both inside the tunnel and in the surrounding environment. Photocatalytic technology is an efficient, secondary-pollution-free approach with clear potential for treating tunnel exhaust; however, parametric analyses for practical tunnel engineering applications remain limited. Using computational fluid dynamics (CFD), this study developed a numerical model to simulate photocatalytic NO degradation in a congested tunnel and examined how the surface reaction rate, coating extent, and longitudinal coated section affect NO reduction performance. The results show that NO reduction efficiency increased with the surface reaction rate; however, once the surface reaction rate constant exceeded 2.11 × 10−4 m/s, further gains diminished and the efficiency approached a plateau due to mass-transfer limitations. With respect to the coating extent, full four-wall coating (sidewalls, ceiling, and road surface) provided the best performance, followed by three-wall coating (excluding the ceiling). Moreover, because the road surface lies in a region of high pollutant concentration and low air velocity, coating on the road surface achieved a markedly stronger reduction effect than coating on the sidewalls or the ceiling. In the simulated 500 m tunnel, the downstream coated section achieved a markedly higher NO reduction efficiency in the ambient environment outside the tunnel (5.9%) than the upstream coated section (1.0%), approaching that of the full-length (500 m) coated section (6.6%). Therefore, in practical engineering applications, priority should be given to coating strategies targeting the downstream section and the road surface in order to balance NO reduction performance and economic cost. Such a strategy is beneficial not only for improving tunnel air quality, but also for promoting sustainable pavement and tunnel-surface engineering by reducing unnecessary coating area and enabling a more resource-efficient and cost-effective use of photocatalytic materials. These findings provide theoretical and methodological support for the sustainable design and application of photocatalytic coating systems in urban tunnels.

Implant failure is equivalent to the loss of the implant, which entails biological and economic costs and reduces patient's trust in healthcare professionals. The objective of this study was to estimate the cumulative failure rate of 1,308 implants and identify patient-related and surgical factors associated with implant failure. Data for this retrospective multicentre study were extracted from six private clinics between June 2006 and December 2022. Patient-related factors, surgical techniques, and implant-related variables were evaluated. Multivariate mixed Cox proportional hazards models and Lasso regularisation were employed to identify predictors of implant failure. A total of 1,308 implants (510 patients) were inserted, with a failure rate of 2.4% over a mean follow-up period of 38.31±32.54 months. The selected mixed Cox regression models showed that three variables were independently associated with implant failure: Postoperative implant infection (Hazard Ratio [HR]=6.6 [95% CI: 1.8-23.9]; p=0.004), previous implant failure (HR=8.3 [95% CI: 2.6-26.6]; p<0.001), and heavy smoking (>20 cigarettes per day) (HR=99.3 [95% CI: 30.7-321.3]; p<0.001). With the limitations of the present study, the cumulative implant failure rate was low (2.4%). Nevertheless, strict control of smoking habits and infection risk factors is essential, since implant replacement after failure constitutes and independent risk factor for subsequent failure.