Search Results (261)

Background/Objectives: Vertebral fractures (VFs) are a global health issue caused by traumatic or pathological factors that compromise spinal integrity. The burden of VFs is increasing, particularly in older adults. Methods: Data from the Global Burden of Disease 2021 were analyzed to estimate the prevalence, mortality, and years lived with disability due to VFs from 1990 to 2021. Estimates were stratified according to age, sex, and region. Bayesian meta-regression models were used to generate age-standardized rates, and projections for 2050 were calculated using demographic trends and the sociodemographic index. Das Gupta’s decomposition assessed the relative contributions of population growth, aging, and prevalence changes to future case numbers. Results: In 2021, approximately 5.37 million people (95% Uncertainty Interval [UI]: 4.70–6.20 million) experienced VFs globally, with an age-standardized prevalence of 65 per 100,000. Although the rates have declined slightly since 1990, the absolute burden has increased owing to population aging. VF prevalence was the highest in Eastern and Western Europe and in high-income regions. Males had higher VF rates until 70 years of age, after which females surpassed them, reflecting postmenopausal osteoporosis. Falls and road injuries were the leading causes of VF. By 2050, the number of VF cases is expected to increase to 8.01 million (95% UI: 6.57–8.64 million). Conclusions: While the age-standardized VF rates have decreased slightly, the global burden continues to increase. Targeted strategies for the early diagnosis, osteoporosis management, and fall prevention are necessary to reduce the impact of VFs. Full article

Over the past decade, multifactor models have shown enhanced capability compared to single-factor models in explaining asset return variability. Given the common assertion that higher risk tends to yield higher returns, this study empirically examines the augmented human capital six-factor model’s performance on thirty-two portfolios of non-financial firms sorted by size, value, profitability, investment, and labor income growth in the Indian market over the period July 2010 to June 2023. Moreover, the current study extends the Fama and French five-factor model by incorporating a human capital proxy by labor income growth as an additional factor thereby proposing an augmented six-factor asset pricing model (HC6FM). The Fama and MacBeth two-step estimation methodology is employed for the empirical analysis. The results reveal that small-cap portfolios yield significantly higher returns than large-cap portfolios. Moreover, all six factors significantly explain the time-series variation in excess portfolio returns. Our findings reveal that the Indian stock market experienced heightened volatility during the COVID-19 pandemic, leading to a decline in the six-factor model’s efficiency in explaining returns. Furthermore, Gibbons, Ross, and Shanken (GRS) test results reveal mispricing of portfolio returns during COVID-19, with a stronger rejection of portfolio efficiency across models. However, the HC6FM consistently shows lower pricing errors and better performance, specifically during and after the pandemic era. Overall, the results offer important insights for policymakers, investors, and portfolio managers in optimizing portfolio selection, particularly during periods of heightened market uncertainty. Full article

This paper examines the impact of carbon capture and storage (CCS) deployment on national carbon intensity (CI) across 43 countries from 2010 to 2020. Using a dynamic common correlated effects (DCCE) log–log panel, we estimate the elasticity of CI with respect to sectoral CCS facility counts within four income-group panels and the full sample. In the high-income panel, CCS in direct air capture, cement, iron and steel, power and heat, and natural gas processing sectors produces statistically significant CI declines of 0.15%, 0.13%, 0.095%, 0.092%, and 0.087% per 1% increase in facilities, respectively (all p < 0.05). Upper-middle-income countries exhibit strong CI reductions in direct air capture (–0.22%) and cement (–0.21%) but mixed results in other sectors. Lower-middle- and low-income panels show attenuated or positive elasticities—reflecting early-stage CCS adoption and infrastructure barriers. Robustness checks confirm these patterns both before and after the 2015 Paris Agreement and between emerging and developed economy panels. Spatial analysis reveals that the United States and United Kingdom achieved 30–40% CI reductions over the decade, whereas China, India, and Indonesia realized only 10–20% declines (relative to a 2010 baseline), highlighting regional deployment gaps. Drawing on these detailed income-group insights, we propose tailored policy pathways: in high-income settings, expand tax credits and public–private infrastructure partnerships; in upper-middle-income regions, utilize blended finance and technology-transfer programs; and in lower-income contexts, establish pilot CCS hubs with international support and shared storage networks. We further recommend measures to manage CCS’s energy and water penalties, implement rigorous monitoring to mitigate leakage risks, and design risk-sharing contracts to address economic uncertainties. Full article

Over the past decade, China has vigorously supported the development of renewable energy and has initially established the electricity–carbon–certificate multi-market. As a typical market-oriented demand-side management model, studying the optimization process and cases of virtual power plants (VPPs) under the multi-market has significant importance for enhancing the operation level of VPPs, as well as promoting corresponding experiences. Based on the mechanisms and impacts of the electricity–carbon–certificate multi-market, this manuscript takes a VPP project in southern China as a case, constructs a sequential decision-making optimization model for the VPP under a diversified market, and solves it using reinforcement learning and Markov decision theory. The case analysis shows that, compared to energy supply income, although the proportion of income from certificate trading and carbon trading in the multi-market is relatively limited, participating in the electricity–carbon–certificate multi-market can significantly enhance VPPs’ willingness to accommodate the uncertainties of renewable energy and can significantly improve the economic and environmental performances of VPPs, which is of great significance for improving the energy structure and accelerating the process of low-carbon energy transformation. Full article

The COVID-19 pandemic significantly disrupted higher education worldwide, imposing strict isolation measures, transitioning learning online, and exacerbating existing social and economic inequalities. This literature review examines the pandemic’s impact on the mental health of college students, with a focus on those belonging to minority groups, including racial, ethnic, migrant, gender, sexuality-based, and low-income populations. While elevated levels of anxiety, depression, and loneliness were observed across all students, findings indicate that LGBTQ+ and low-income students faced the highest levels of psychological distress, due to compounded stressors such as family rejection, unsafe home environments, and financial insecurity. Racial and ethnic minority students reported increased experiences of discrimination and reduced access to culturally competent mental healthcare. International and migrant students were disproportionately affected by travel restrictions, legal uncertainties, and social disconnection. These disparities underscore the need for higher education institutions to implement targeted, inclusive mental health policies that account for the unique needs of at-risk student populations during health crises. Full article

Why should we prepare for a flood which might never happen? Uncertainty around potential future hazards significantly limits citizens’ disaster preparedness, as it influences decision-making and action-taking greatly. To bridge this knowledge–action gap, we developed a novel, no-regrets framework for sustainable flood preparedness under uncertainty, building on a systematic literature review (PRISMA method) and an integrative review of preparedness actions. The review of 364 articles revealed that while no-regrets principles are widely applied in climate policy and risk management, they are not tailored to personal preparedness. Our resulting framework defines clear no-regrets criteria for individual and household-level preparedness (robustness, flexibility, cost-effectiveness, co-benefits, and ease of implementation) and categorizes 80+ flood preparedness actions according to four levels of uncertainty, from unknown futures to imminent hazards. Notably, we found that long-term preparedness actions remain underutilized, psychological preparedness is largely absent, and existing guidance is biased toward physical risk reduction in high-income contexts. This framework offers a practical tool for practitioners, local authorities, and community groups to promote actionable, context-sensitive flood preparedness worldwide and can be adapted to other hazards in future work. Full article

The volatility and uncertainty of wind power output pose significant challenges to the safe and stable operation of power systems. To enhance the economic efficiency and reliability of day-ahead scheduling in wind farms, this paper proposes a day-ahead planning and scheduling method for wind/storage systems based on multi-scenario generation and Conditional Value-at-Risk (CVaR). First, based on the statistical characteristics of historical wind power forecasting errors, a kernel density estimation method is used to fit the error distribution. A Copula-based correlation model is then constructed to generate multi-scenario wind power output sequences that account for spatial correlation, from which representative scenarios are selected via K-means clustering. An objective function is subsequently formulated, incorporating electricity sales revenue, energy storage operation and maintenance cost, initial state-of-charge (SOC) cost, peak–valley arbitrage income, and penalties for schedule deviations. The initial SOC of the storage system is introduced as a decision variable to enable flexible and efficient coordinated scheduling of the wind/storage system. The storage system is implemented using a 1500 kWh/700 kW lithium iron phosphate (LiFePO₄) battery to enhance operational flexibility and reliability. To mitigate severe profit fluctuations under extreme scenarios, the model incorporates a CVaR-based risk constraint, thereby enhancing the reliability of the day-ahead plan. Finally, simulation experiments under various initial SOC levels and confidence levels are conducted to validate the effectiveness of the proposed method in improving economic performance and risk management capability. Full article

We examine how institutional saving mechanisms influence retirement saving decisions under bounded rationality and income risk. Using a life-cycle experiment with habit formation and loss aversion, we test mandatory and voluntary binding savings under deterministic and stochastic income. Voluntary commitment improves saving performance only when income is predictable; under uncertainty, it fails to improve performance. Mandatory savings do not raise total saving, as participants reduce voluntary contributions. These results emphasize the role of income smoothing in enabling behavioral interventions to improve long-term financial outcomes. Full article

Crop cultivation planning is vital for optimizing agricultural productivity and sustainable land use under farming uncertainties. This study developed a decomposition-based stochastic multilevel binary optimization model for agricultural plot management. Using land and crops as the division standard, the complex problem of agricultural land management was broken down into manageable sub-modules, which were efficiently solved using a greedy algorithm. In order to verify the actual effectiveness of the model, this study conducted an empirical analysis based on the production practice scenario in the mountainous areas of North China from 2023 to 2026. The performance of the model was verified through dimensions such as agricultural income accounting, the assessment of planting dispersion, and the optimization of legume crop rotation patterns. The stability of the system was also tested using sensitivity tests for multiple variables. To further evaluate the performance of the model, we compared it with two single-factor benchmark models that only considered uncertainty or only considered the land constraints. The results showed that in the multi-year and multi-income scenarios, our comprehensive model was significantly better than the two benchmark models in terms of optimization performance, which proves the necessity of considering land constraints and uncertainty at the same time. Full article

This analysis was conducted in the context of the crisis caused by the COVID-19 pandemic, when the uncertainty and demand for food modified consumption patterns. Therefore, this study aimed to analyze variations in the expenditures allocated to pasteurized and powdered milk during and after the pandemic, considering the socioeconomic and demographic factors influencing these choices. A cross-sectional ordinary least squares (OLS) regression model was implemented using data from the National Household Income and Expenditure Survey for 2018, 2020, and 2022. The model evaluated variables such as income, household size, educational level, and gender of the household head, as well as the presence of minors and older adults at the regional level. The findings demonstrated that, in 2020, expenditure on pasteurized milk exhibited an elasticity of 0.888, suggesting heightened sensitivity to income during the pandemic period. In contrast, the elasticity of powdered milk was lower, with a value of 0.013 between 2018 and 2020, and negative values by 2022. Additionally, households headed by women, households with a higher level of education, and households with children spent more on pasteurized milk. These findings confirm the importance of milk as an essential commodity and highlight the substitute role of powdered milk in low-income households. Full article

At present, the high complexity of the environment, the uncertainty of income, and the choice of strategies have attracted extensive attention from all walks of life who are committed to studying the game of collaborative innovation between government and industry–university–research. Based on this, first of all, with the help of stochastic evolutionary game theory and fuzzy theory, this paper constructs a multi-party stochastic evolutionary game model of green technology innovation about the government guidelines and the joint promotion of industry, universities, and research institutes. Secondly, it discusses the evolution law of behavior strategies of each game subject and the main factors to maintain the alliance’s stability under fuzzy income. The numerical simulation results show the following: (1) Reputation gains have a significant positive correlation with the evolution stability of alliance behavior, and the incorporation of reputation gains or losses will effectively maintain the cooperation stability of the alliance. (2) Under the influence of product greenness, government subsidies, and long-term benefits, it will promote the pace consistency of cooperative decision-making between industry, universities, and research institutes, and accelerate the evolution of alliances. (3) The enterprise’s ability and the research party’s ability will restrict each other. When one party’s ability is low, its willingness to choose a cooperation strategy may be slightly low due to technology spillover and other reasons. When the two parties’ abilities match, their behavior strategies will increase their willingness to cooperate with their abilities. Compared with the traditional evolutionary game, this study fully considers the uncertainty of the environment and provides theoretical support and practical guidance for the high-quality development strategy of the industry–university–research green technology innovation alliance. Full article

Market liberalization and the growth of renewable energy sources have enabled the rise of generation companies (GENCOs) managing diverse generation portfolios, creating a dynamic market environment that necessitates innovative energy management strategies to enhance operational efficiency and economic viability. Investing in the energy storage system (ESS), which, in addition to participating in the energy and ancillary services markets and in joint operations with other GENCO facilities, can mitigate the fluctuation level from renewables and increase profits. Besides the optimal operation and bidding strategy, determining the optimal size of the ESS aligned with the GENCO’s requirements is significant for its market success. The purpose of the ESS impacts both the sizing criteria and the sizing techniques. The proposed sizing method of ESS for a GENCO daily operation mode is based on the developed optimization operation model of GENCO with utility-scale energy storage and a cost-benefit analysis. A GENCO operates in a market-oriented power system with possible penalties for undelivered energy. The proposed method considers various stochastic phenomena; therefore, the optimization calculations analyze the GENCO operation over a long period to involve multiple potential combinations of uncertainties. Numerical results validate the competencies of the presented optimization model despite many unpredictable parameters. The results showed that both the battery storage system and the pumped storage hydropower plant yield a higher net income for a specific GENCO with a mixed portfolio, regardless of the penalty clause. Considering the investment costs, the optimal sizes for both types of ESS were obtained. Full article

The axiomatic framework of quantum game theory gives us a new platform for exploring economics by resolving the foundational problems that have long plagued the expected utility hypothesis. This platform gives us a previously unrecognized tool in economics, the statistical ensemble, which we apply across three distinct economic spheres. We examine choice under uncertainty and find that the Allais paradox disappears. For over seventy years, this paradox has acted as a barrier to investigating human choice by masking actual choice heuristics. We discover a powerful connection between the canonical ensemble and neoclassical economics and demonstrate this connection’s predictive capability by examining income distributions in the United States over 24 years. This model is an astonishingly accurate predictor of economic behavior, using just the income distribution and the total exergy input into the economy. Finally, we examine the ideas of equality of outcome versus equality of opportunity. We show how to formally consider equality of outcome as a Bose–Einstein condensate and how its achievement leads to a corresponding collapse in economic activity. We call this new platform ‘statistical economics’ due to its reliance on statistical ensembles. Full article

The relationship between inflation and foreign direct investment (FDI) is not clear-cut in theory. In the U.S., rising inflation coupled with increased economic recovery boosted FDI immediately after the COVID-19 pandemic but suppressed it afterwards. To shed light on the relationship between inflation and the resulting contractionary monetary policy and FDI, three key propositions were put forth for investigation. The propositions rely on relevant scientific literature showing that (1) although the connection between FDI and inflation is complex, a high and sustained inflation depresses incoming FDI due to increases in uncertainty and guarding government policies; (2) there exist significant location-based differences in how this connection manifests; and (3) high inflation and subsequent policies motivate FDI-related strategic action. Thus, we propose that new FDI is expected to be negatively affected by the rising entry cost associated with an inflationary economy that adopts anti-inflationary policies. Second, there exists heterogeneity in the effects of inflation on new FDI across subnational economies with various local characteristics. Third, existing FDI demonstrates strategic actions and expansion at the subnational location and beyond, even under inflationary pressure. We employ a positive comparative analysis based on descriptive statistics and qualitative interpretation of data to examine the status and activities of both new FDI (using subnational aggregated data) and existing foreign businesses (using firm-level data) in the state of New Hampshire during the recent inflation surge of 2022–2023. Our analysis provides empirical evidence supporting our propositions. Key implications are that, during challenging times of inflation and recovery, business leaders and economic development professionals should anticipate strategic actions to expand markets, products, operations, and partnerships. Leaders and professionals should act to take advantage of business actions outside the subnational location, as more companies look to strengthen and diversify their national and international networks. Full article

Biocomposite materials respond to market trends and regulatory pressures for environmentally friendly packaging. Few studies have assessed the social life cycle assessment (SLCA) using stakeholder indicators across the entire supply chain. The objective of this study is to provide reliable indicators and data to compare the SLCA of jar lid biocomposites filled with post-harvest banana fibers (BFs) in Colombia. Methodologies from the United Nations Environment Programme, the relevant literature, and Colombian regulations were used to select indicators. A comprehensive survey involved all stakeholders in the supply chain and consumer responsibility during the use phase. The data collected were integrated, scored, and weighted. This approach aimed to reduce uncertainty in comparing different scenarios and contribute to the standardization and integration of SLCA methods. The study highlights the significant benefits of incorporating banana fibers (BFs) into jar lids. Lids composed of 40% BFs provide notable social advantages, particularly within the agricultural sector. They contribute to improving the economic income and quality of life for farmers, transporters, and intermediaries while promoting equity among them. Additionally, these lids help preserve cultural heritage in local communities. From a corporate perspective, beyond financial gains, companies enhance their sustainability visibility by offering a product that is environmentally friendly, naturally sourced, and directly connected to farmers. Furthermore, these lids strengthen the overall social impact of the supply chain and business sector by utilizing renewable and locally available resources. Full article