Search Results (133)

As a critical raw material in the semiconductor and new energy sectors, antimony is a strategic mineral resource for nations to safeguard industrial chain security. However, the scarcity of its resources and the complexity of its trade pattern underscore the urgency of antimony-related research. This study aims to reveal the structural characteristics of the global antimony trade network and explore the external factors influencing trade. Based on global antimony trade data from 2007 to 2022, the characteristics of the antimony trade network were analyzed using the complex network analysis method, and the influencing factors of antimony trade were examined via the fixed effects model. The results show that the global antimony trade network maintains a density of 0.05–0.06, with an average path length of 2.4–2.7 and a network diameter that mainly fluctuates between 5 and 6. The average clustering coefficient fluctuates within the range of 0.35–0.45. Overall, the network exhibits the characteristics of stable transmission efficiency, loose overall connectivity, and local agglomeration without a consistent upward or downward trend. Countries such as Germany, China, and the United States occupy core positions in the network. The fixed effects model indicates that GDP and LOGISTICS development are key factors promoting trade, while TARIFFS and REGULATORY policies have a significant inhibitory effect on trade. Therefore, ① Focus on the High-End Development of the Antimony Industry Chain and Promote the In-Depth Integration of Antimony Trade with the Semiconductor and New Energy Industries; ② Improve the Cross-Border Logistics and Warehousing System for Antimony Trade to Ensure the Efficient Circulation of Strategic Resources; ③ Promote; Promote Tariff Liberalization in Antimony Trade and Eliminate Market Access Barriers; ④ Strengthen the Government’s Strategic Support for the Antimony Industry to Enhance Global Discourse Power in Antimony Trade; Trade; ⑤ Maintain Macroeconomic Stability and Flexibly Manage Exchange Rates to Safeguard the Resilience of Antimony Trade. Full article

This study investigates how global monetary and oil shocks propagate across advanced and pegged oil economies, focusing on the United States, Germany, the United Kingdom, Saudi Arabia, and the United Arab Emirates over the period 2015–2023. It examines which transmission channels—liquidity, credit, or equity—serve as the dominant conduits of spillovers under fixed exchange rate regimes. To address this question, this paper develops a hybrid causal–computational framework that integrates high-frequency identification of monetary and oil shocks with econometric benchmarks (Local Projections and Time-Varying Parameter VARs) and a Graph Neural Network-based Causal Shock Network (GNN-CSN) enhanced with SHAP explainability. The results show that global monetary shocks significantly raise interbank funding costs in Saudi Arabia and the UAE, while sovereign credit spreads remain largely stable, indicating that liquidity—not credit—constitutes the main transmission channel. Equity markets absorb much of the external adjustment, reflecting sectoral sensitivity to global cycles. By combining causal identification, dynamic estimation, and explainable machine learning, the framework improves predictive accuracy and transparency, offering new evidence on how external shocks shape financial dynamics in resource-dependent, dollar-pegged economies. Full article

To address low energy utilization efficiency and severe exergy destruction from direct discharge of high-temperature turbine exhaust, this study proposes a supercritical CO₂ Brayton cogeneration system with a series-connected hot water heat exchanger for stepwise waste heat recovery. Based on finite-time thermodynamics, a physical model that provides a more realistic framework by incorporating finite temperature difference heat transfer, irreversible compression, and expansion losses is established. Aiming to maximize exergy output rate under the constraint of fixed total thermal conductance, the decision variables, including working fluid mass flow rate, pressure ratio, and thermal conductance distribution ratio, are optimized. Optimization yields a 16.06% increase in exergy output rate compared with the baseline design. The optimal parameter combination is a mass flow rate of 79 kg/s and a pressure ratio of 5.64, with thermal conductance allocation increased for the regenerator and cooler, while decreased for the heater. The obtained results could provide theoretical guidance for enhancing energy efficiency and sustainability in S-CO₂ cogeneration systems, with potential applications in industrial waste heat recovery and power generation. Full article

Background: Unicompartmental knee arthroplasty (UKA) represents a well-recognized treatment option for isolated medial compartment osteoarthritis; however, the debate regarding the superiority of fixed-bearing versus mobile-bearing designs continues. We aimed to evaluate the mid- to long-term outcomes of medial UKA comparing mobile- versus fixed-bearing designs within a single institution over an average 10-year follow-up. Methods: This retrospective study included 81 consecutive patients who underwent primary medial UKA (45 fixed-bearing and 36 mobile-bearing) with a minimum five-year follow-up. Clinical outcomes were measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score and range of motion (ROM). Radiological measurements included hip-knee-ankle axis angle (HKA) and osteoarthritis progression. Implant survivorship was evaluated using Kaplan–Meier analysis, with failure defined as either conversion to total knee arthroplasty (TKA) or polyethylene (PE) exchange. Results: At a mean follow-up of 10.6 years, WOMAC scores, ROM, and radiological outcomes showed no statistically significant differences between the fixed-bearing and mobile-bearing groups. Significantly higher failure rates were observed in the mobile-bearing group, both when considering conversion only (p = 0.041) and when including conversion or PE exchange (p = 0.009). Survival analysis demonstrated 10-year rates of 97.8% for fixed-bearing and 88.9% for mobile-bearing with TKA conversion defined as failure (p = 0.066). Using combined failure criteria of TKA conversion or PE exchange, 10-year survival rates were 97.8% for fixed-bearing and 83.3% for mobile-bearing (p = 0.015). Conclusions: At a mean 10.6-year follow-up, clinical and radiological outcomes were comparable, but fixed-bearing UKA demonstrated superior survivorship. Full article

More energy efficient heat pumps can be designed if the industry is able to identify reliable optimization schemes able to predict how a fixed amount of money is best spent on the different individual components. For example, how to optimally design and size the different heat exchangers (HEs) in a heat pump with respect to cost and performance. In this work, different optimization algorithms and HE area integral approximations are compared for heat pumps with two and three HEs, with or without ejectors. Since the main goal is to identify optimal numerical schemes, not optimal designs, heat transfer is simplified, assuming a constant U-value for all HEs, which reduces the computational work significantly. Results show that high-order HE area approximations are $10-400$ times faster than conventional trapezoidal and adaptive integral methods. High-order schemes with $45$ grid points ($N$) obtained $80-100$% optimization success rates. For subcritical processes, the LMTD method produced accurate results with $N\le 5$, but such schemes are unreliable and difficult to extend to real HE models with non-constant U. Results also show that constrained gradient-based optimizations are $10$ times faster than particle swarm, and that conventional GA optimizations are extremely inefficient. This study therefore recommends applying high-order HE area approximations and gradient-based optimizations methods developing accurate optimization schemes for the industry, which include realistic heat transfer coefficients. Full article

In quantum key distribution (QKD), public discussion over the authenticated classical channel inevitably leaks information about the raw key to a potential adversary, which must later be mitigated by privacy amplification. To limit this leakage, a one-time pad (OTP) has been proposed to protect message exchanges in various settings. Building on the security proof of Tomamichel and Leverrier, which is based on a non-asymptotic framework and considers the effects of finite resources, we extend the analysis to the OTP-protected scheme. We show that when the OTP key is drawn from the entropy pool of the same QKD session, the achievable quantum key rate is identical to that of the reference protocol with unprotected error-correction exchange. This equivalence holds for a fixed security level, defined via the diamond distance between the real and ideal protocols modeled as completely positive trace-preserving maps. At the same time, the proposed approach reduces the computational requirements: for non-interactive low-density parity-check codes, the encoding problem size is reduced by the square of the syndrome length, while privacy amplification requires less compression. The technique preserves security, avoids the use of QKD keys between sessions, and has the potential to improve performance. Full article

Introduction: The use of modular components provides several advantages in total knee arthroplasty (TKA), including exchange of the polyethylene insert while retaining the stable components in the revision TKA. Compared to full, non-modular component revision TKA, isolated polyethylene exchange (IPE) has the advantage of decreased morbidity, faster rehabilitation, and acceptable outcomes. Methods: A review of published literature on revision TKA was conducted, with a specific focus on studies evaluating the use of IPE for managing complications such as stiffness, instability, and periprosthetic joint infection (PJI). Results: IPE with downsizing may be considered for patients with mild stiffness and stable, well-positioned implants that have increased polyethylene thickness, though expectations for motion gain should be cautious. There is no clear consensus on IPE for instability. Some studies report high re-revision rates, while others show clinical and functional improvement when the TKA is well-aligned, well-fixed, and intraoperative gap balance is achieved. Additionally, irrigation and debridement with polyethylene exchange (IDPE) may be effective for acute TKA PJI management, particularly within the first two weeks of symptom onset. Conclusions: Based on current literature, IPE in aseptic TKA revisions may be effective for stiffness or instability when implants are well-fixed and well-aligned—particularly if polyethylene constraint can be adjusted for instability or downsized for stiffness. The role of IDPE in acute TKA PJI is better defined in the literature, with strong emphasis on its time-sensitive effectiveness—most notably within the first two weeks of symptom onset. Full article

Integrated Hydrogen–Energy Systems (IHES) have attracted widespread attention; however, distributed energy sources such as photovoltaics (PV) and wind turbines (WT) within these systems exhibit significant uncertainty and intermittency, posing key challenges to scheduling complexity and system instability. As a core mechanism for the integrated operation of IHES, electricity price regulation can promote the absorption of renewable energy, optimize resource allocation, and enhance operational economy. Nevertheless, uncertainties in IHES hinder the formulation of accurate electricity prices, which easily lead to delays in scheduling responses and an increase in cumulative operating costs. To address these issues, this study develops lifespan models for Proton Exchange Membrane Electrolyzers (PEMELs) and Proton Exchange Membrane Fuel Cells (PEMFCs), constructs dynamic equations for the demand side and response side, and proposes a fuzzy-weighted dynamic pricing strategy. Simulation results show that, compared with fixed pricing, the proposed dynamic pricing strategy reduces economic indicators by an average of 15.3%, effectively alleviates energy imbalance, and optimizes the energy supply of components. Additionally, it reduces the lifespan degradation of PEMELs by 21.59% and increases the utilization rate of PEMFCs by 54.8%. Full article

This research explores the complex relationships between tourism, economic factors, environmental sustainability, and transportation infrastructure within the European Union (EU), as the tourist scene changes globally. Our research uses a comprehensive model to investigate the factors that influence the number of tourists arriving in the EU, focusing on the years 1990 to 2022. The model considers transportation infrastructure, environmental sustainability indices, and economic variables as major determinants of tourism flows. Economic variables encompass exchange rates, the Consumer Price Index (CPI), and per capita income, while environmental sustainability indicators include carbon footprint and renewable energy usage. Additionally, the model considers transportation infrastructure by assessing the quality and availability of transportation modes. We use a two-way fixed effect to account for any unobserved heterogeneity. Fixed effects give control over nation-specific factors that might affect tourism, as they are a reliable method to deal with potential biases in the estimated parameters. Our study aims to provide insightful information about the sustainable growth of tourism in the European Union, providing policymakers, scholars, and industry stakeholders with a comprehensive understanding of the variables influencing visitor arrivals. This research contributes to the tourism literature by integrating CE principles with behavioral insights from the theory of planned behavior, highlighting how tourists’ pro-environmental attitudes, social norms, and perceived behavioral control influence travel choices. In the framework of the circular economy, the authors hope to inform policy choices and advance a more environmentally conscious travel industry in the EU by examining the points where economic, environmental, and transportation aspects converge. Full article

This paper examines the relationship between currency misalignment and income inequality across 70 countries from 1998 to 2021. Currency misalignment occurs when the actual exchange rate diverges significantly from the equilibrium exchange rate. Using fixed-effects and random-effects regressions, we find that currency overvaluation is associated with higher income inequality, while undervaluation is linked to lower income inequality. These findings are strongest in emerging markets and upper-middle-income countries, where undervalued currencies may be associated with stronger tradable-sector activity and narrower income gaps. In contrast, lower-income countries experience increasing levels of inequality during the early stages of development, even with growth, which is consistent with the Kuznets hypothesis. For advanced markets and higher-income nations, currency misalignment is not statistically related to income inequality, which is likely due to the presence of stronger financial systems and more stable institutions that reduce the effects of currency misalignment. The results are robust across the two grouping methods—development level (IMF) and income level (World Bank). Overall, the study highlights that while undervaluation may be associated with equitable growth in emerging markets, its benefits likely depend on a country’s development stage and are more likely when accompanied by appropriate social and economic policies to mitigate potential risks. Full article

Chronic respiratory diseases claim nearly four million lives annually, making them the third leading cause of death worldwide. Extracorporeal membrane oxygenation (ECMO) is often the last line of support for patients with severe lung failure. Still, its performance is limited by an incomplete understanding of gas exchange in hollow fiber membrane (HFM) oxygenators. Computational fluid dynamics (CFD) has become a robust oxygenator design and optimization tool. However, most models oversimplify O₂ and CO₂ transport by ignoring their physiological coupling, instead relying on fixed saturation curves or constant-content assumptions. For the first time, this study introduces a novel physiologically informed CFD model that integrates the Bohr and Haldane effects to capture the coupled transport of oxygen and carbon dioxide as functions of local pH, temperature, and gas partial pressures. The model is validated against in vitro experimental data from the literature and assessed against established CFD models. The proposed CFD model achieved excellent agreement with experiments across blood flow rates (100–500 $\mathrm{mL}/\min$ ), with relative errors below 5% for oxygen and 10–15% for carbon dioxide transfer. These results surpassed the accuracy of all existing CFD approaches, demonstrating that a carefully formulated single-phase model combined with physiologically informed diffusivities can outperform more complex multiphase simulations. This work provides a computationally efficient and physiologically realistic framework for oxygenator optimization, potentially accelerating device development, reducing reliance on costly in vitro testing, and enabling patient-specific simulations. Full article

Cryptocurrency is often viewed as a hedge against economic instability, yet the extent to which economic risk drives digital asset adoption remains unclear. This study asks to what extent does economic risk shape global cryptocurrency adoption? To address this question, the research investigates how variables such as inflation, corruption, unemployment, and exchange rate volatility influence adoption patterns. Using panel data from 41 countries between 2019 and 2024, the study employs country fixed-effects regression models and Principal Component Analysis. A novel Regulatory Permissiveness Index is introduced to evaluate the role of national regulatory environments. The findings show that cryptocurrency adoption is primarily associated with structural enablers such as GDP per capita, internet penetration, and regulatory clarity. Among the economic risk indicators, higher corruption and lower unemployment significantly predict adoption. Other economic factors, such as inflation and exchange rate volatility, are not consistently significant. The results suggest that economic development and digital infrastructure, rather than reactive responses to economic crises, are the main drivers of cryptocurrency adoption. Nonetheless, the significance of corruption highlights the role of institutional dissatisfaction in adoption behaviour, even in economically stable settings. Full article

Micro-crack defects on the surfaces of plate heat exchanger sheets often exhibit a linear grayscale pattern when clustered. In defect detection, traditional methods are more suitable than deep learning models in controlled production environments with limited computing resources to meet stringent national standards, which require low miss rates. However, deep learning models commonly suffer feature loss when detecting individual, small-scale defects, leading to higher leak detection rates. Moreover, in grayscale image line detection using traditional methods, the varying direction, width, and asymmetric grayscale profiles of defects can result in filled grayscale valleys due to width-adaptive smoothing coefficients, complicating accurate defect extraction. To address these issues, this study establishes a theoretical foundation for parameter selection in variable-width defect detection. We propose a directional gradient-based algorithm that mathematically constrains the Gaussian template width to cover variable-width defects with a fixed σ, reframing the detection defect from ridge edges to centrally symmetric double-ridge edges in gradient images. Experimental results show that, when tested in the defective boards library and under simulated factory CPU conditions, this algorithm achieves a miss detection rate of 14.55%, a false detection rate of 21.85%, and an 600 × 600 pixel image detection time of 0.1402 s. Compared to traditional line detection and deep learning object detection methods, this algorithm proves advantageous for detecting micro-crack defects on plate heat exchanger sheets in industrial production, particularly in data-scarce and resource-limited scenarios. Full article

The impact of Environmental, Social, and Governance (ESG) scores on financial performance remains a subject of debate, as the literature reports mixed evidence regarding their effect on stock returns. This research aims to examine the relationship between ESG ratings and the change in ESG scores, or ESG Momentum, concerning both returns and risk of a large sample of stocks traded on U.S. exchanges. The study examined a sample of 3856 stocks traded on U.S. exchanges, considering 20 years of quarterly data from December 2002 to December 2022. We applied multi-factor models and tested them through pooled ordinary, fixed effects, and random effects panel regression methods. Our results show negative relationships between ESG scores and stock returns and between ESG Momentum and volatility. Contrarily, we find positive associations between ESG Momentum and returns and between ESG scores and volatility. Although high ESG scores are generally associated with lower long-term stock returns, an increase in a company’s ESG rating tends to translate into immediate positive returns and reduced risk. Accordingly, investors may benefit from strategies that focus on companies actively improving their ESG performance, while firms themselves stand to gain by signaling continuous advancement in ESG-related areas. Full article

As participants in sustainable development, corporations face the important and controversial issue of whether they can promote corporate sustainability through environmental, social, and governance (ESG) practices. To address this issue, we examine the relationship between ESG performance and corporate sustainability, measured by green total factor productivity (GTFP). Using a panel dataset of 17,559 firm-year observations from non-financial firms listed on the Shanghai and Shenzhen stock exchanges in China between 2011 and 2019, we employ fixed-effects regression models and two-stage least squares (2SLS) with instrumental variables to empirically test the impact of ESG ratings on GTFP, identify the underlying mechanisms, and examine potential heterogeneity across firms. The results show that higher ESG ratings are significantly associated with increased GTFP. Mediation analysis further reveals that this positive relationship operates through reduced financing constraints and enhanced green innovation. Notably, the mediating role of financing constraints is more pronounced for firms with greater reliance on external capital. Heterogeneity analysis indicates that ESG ratings exert stronger effects in eastern regions, pollution-intensive sectors, and state-owned enterprises. These findings provide empirical support for the role of ESG performance as an effective mechanism to advance corporate sustainability through ethics-driven financial access and innovation capability. Full article