Search Results (50)

Objectives: While the previous literature has established that meteorological conditions are associated with COVID-19 mortality fluctuations, the relative effect of each of these highly correlated factors remains unclear. This study aims to conduct a comparative analysis to determine which of three main meteorological variables—Ambient Temperature, Ultraviolet (UV) Index, and Sunlight Duration—have the strongest negative association with COVID-19 mortality. The objective is to quantify and rank their impact over a 7-to-21-day biological exposure window. Methods: We conducted retrospective spatiotemporal analyses in the form of panel Poisson Distributed Lag Models (PDLMs) regression using daily data from 21 January 2020 to 10 January 2023, spanning 129 distinct geographical regions worldwide. To ensure a direct and fair comparison of effect sizes, all meteorological and environmental variables were Z-score standardized. We estimated three independent PDLMs—each focusing separately on UV Index, Ambient Temperature, and Sunlight Duration—with lags ranging from 7 to 21 days. These models controlled for overarching time trends and utilized a categorical variable to account for Region Fixed Effects modeling time-invariant regional health and socioeconomic determinants (e.g., obesity, age demographics, healthcare capacity). Furthermore, distributed lags of daily PM2.5 (air pollution) and relative humidity were explicitly included in each model as dynamic confounders. Results: The comparison of PDLM results reveals that the UV Index has the strongest negative association with COVID-19 mortality. A one standard deviation increase in the UV Index corresponds to a massive, highly significant cumulative reduction in deaths observed 1 to 3 weeks later (p < 0.001). Sunlight Duration is the second-strongest protective meteorological factor, whereas Ambient Temperature has the weakest effect. The distributed lags of particulate matter (PM2.5) and relative humidity were found to be statistically insignificant when modeled alongside the meteorological variables. Conclusions: After standardizing variables and controlling for dynamic environmental confounders like air pollution and humidity, the study findings provide robust empirical evidence that meteorological conditions have a strong significant association with COVID-19 mortality fluctuation with a temporal delay, overcoming the confounding effects of merely dry or clear-air conditions. Full article

Amidst the polycrisis of 2018–2024, Asia-Pacific trade flows exhibited a structural resilience that contrasts with traditional theoretical predictions of severe trade contraction under high uncertainty. This study investigates these resilience dynamics using a structural gravity model estimated via the Poisson Pseudo Maximum Likelihood (PPML) approach. The analysis utilizes a balanced panel of 14 key regional economies (N = 4914), explicitly disaggregated into geographic (ASEAN-6 vs. non-ASEAN) and global value chain (high vs. low GVC intensity) subgroups to capture heterogeneous responses. The empirical results confirm that economic policy uncertainty (EPU) acts as a significant trade friction (β = −3.371), consistent with the wait-to-invest mechanism of real options theory. However, this effect is heterogeneous and significantly mitigated by institutional frameworks. We identify a robust institutional shield effect, where participation in trade agreements effectively neutralizes the adverse transmission of policy shocks (interaction coefficient = 3.396). Furthermore, this study uncovers a structural break during periods of extreme geopolitical conflict, characterized by a convex U-shaped relationship between uncertainty and trade. This pattern provides macro-level evidence of a behavioral shift in regional supply chains from a just-in-time cost-efficiency optimization model to a just-in-case security maximization paradigm, consistent with precautionary inventory accumulation. These findings underscore the critical role of modern trade pacts as institutional credibility anchors and the necessity of adaptive strategies in navigating heightened macroeconomic volatility. Full article

We examine whether aggregate “music mood” derived from globally popular songs can help forecast primary equity issuance. We build a Friday-anchored weekly panel that merges SEC EDGAR counts of priced Initial Public Offerings (IPOs) with features from the Spotify Daily Top 200 (audio descriptors such as valence, energy, danceability, tempo, loudness, etc.) and Genius-scraped lyrics. We extract lyric sentiment by tokenizing Genius-scraped lyrics and aggregating lexicon-based affect scores (valence and arousal) into popularity-weighted weekly indices. To address sparsity and regime shifts in issuance, we train a leakage-safe Long Short-Term Memory (LSTM) network on a smoothed target—the forward 4-week sum of IPOs—and obtain next-week forecasts by dividing the predicted sum by 4. On a chronological holdout, a single LSTM with look-back K = 8 outperforms strong baselines—reducing MAE by 13.9%, RMSE by 15.9%, and mean Poisson deviance by 27.6% relative to the best baseline in each metric. Furthermore, we adopt SHapley Additive exPlanations (SHAP) to explain our LSTM model, showing that IPO persistence remains the dominant driver, but music and lyrics covariates contribute incremental and robust signal. These results suggest that aggregate music sentiment contains economically meaningful information about near-term IPO activity. Full article

Background and Objectives: Cardiometabolic diseases are rising in Latin America, yet rural Amazonian populations remain understudied. We aimed to characterize the prevalence and factors associated with a simple composite cardiometabolic risk in rural Amazonian adults. Materials and Methods: We conducted an analytical cross-sectional study during community screenings in San Martín, Peru, in 2025, enrolling adults aged ≥ 18 years. The outcome was present when ≥2 biological/anthropometric alterations were identified at the same visit (hypertension, dyslipidemia, hyperglycemia, hyperuricemia, general obesity, abdominal obesity, or elevated waist-to-hip ratio). Behaviors included current tobacco use, alcohol risk (AUDIT), and physical activity (IPAQ). We summarized variables (univariate), compared groups (bivariate: chi-square; Fisher for alcohol), and fitted modified Poisson regression with robust errors to estimate prevalence ratios (PRs); variables with p ≤ 0.20 in bivariate analysis entered multivariable models. Results: We enrolled 205 adults; 70.2% met the composite outcome. In multivariable models, abdominal obesity (adjusted PR [aPR] 1.70; 95% CI 1.40–2.10), hyperglycemia (1.65; 1.25–2.17), hyperuricemia (1.38; 1.19–1.61), dyslipidemia (1.25; 1.07–1.46), and general obesity (1.21; 1.04–1.40) were independently associated with cardiometabolic risk. Hypertension (1.06; 0.88–1.29) and elevated waist-to-hip ratio (1.20; 0.88–1.63) were not. Physical activity differed crudely but showed no independent association; tobacco and alcohol were not associated. Conclusions: In this rural Amazonian population, we observed a high prevalence of composite cardiometabolic risk and found that central adiposity and metabolic derangements, not blood pressure or self-reported behaviors, were the main correlates. Simple measures such as waist circumference, fasting glucose or HbA1c, a basic lipid panel, and serum urate may help flag adults at higher cardiometabolic risk in similar low-resource primary-care settings, but prospective studies are needed to evaluate their predictive value and screening performance. Full article

This study investigates the relationship between green trade, economic complexity, and green indicators in Asian countries using a Poisson Pseudo Maximum Likelihood (PPML) fixed effects model. This study uses panel data from 33 countries in the Asia region, focusing on the national level of each country from 2010 to 2023. The analysis explores how economic sophistication and environmental indicators influence the capacity of economies to engage in sustainable trade. The findings reveal that economic complexity significantly enhances green trade, underscoring the role of knowledge-intensive production structures in fostering environmentally friendly export performance. Among the green indicators, green economic opportunities demonstrate a positive and significant effect on green trade, which indicates that economies allocating greater financial resources to renewable energy and sustainable infrastructure are better positioned to expand their participation in eco-friendly markets. This signals strong trade readiness and market-driven incentives. Conversely, green innovation shows a negative and significant effect, indicating that innovation is not yet translating into export competitiveness, is still costly, and is in an early phase. Moreover, economic complexity and renewable energy show positive and significant effects, reflecting that higher complexity enables the adoption of green technologies, the embedding of sustainability in value chains, and the export of high-value green products. These results suggest that green economic opportunities and regional dynamics play a complementary role in shaping outcomes, with proximity to innovation hubs amplifying the capacity for sustainable trade. The study contributes to the literature by linking economic complexity with green trade in the Asian context, offering evidence-based recommendations to enhance sustainability-driven growth. Full article

The cores of honeycomb panels are usually made of hexagonal cells. Due to their structure, they create anticlastic surfaces that are difficult to use in furniture design. Synclastic surfaces in lightweight sandwich panels are typically associated with auxetic cores characterized by a negative Poisson’s ratio. This study aimed to transform the hexagonal cell cores into cells with a negative or positive Poisson’s ratio (NPR, PPR), enabling these cores to form synclastic surfaces. New core structures for synclastic furniture sandwich honeycomb panels were modeled numerically and experimentally. It has been demonstrated that reentrant cells with NPR create synclastic surfaces, and new shapes of core cells, created by transforming hexagonal cells with PPR, also enable the formation of synclastic surfaces. Cores’ synclasticity was assessed in two orthogonal planes using physical models and Finite Element Analysis (FEA). A new and original discovery is the demonstration that not only auxetic but also modified hexagonal cells with Poisson’s ratios of ${\nu }_{xy}$ = 0.545 and ${\nu }_{yx}$ = 0.512, respectively, exhibit excellent synclastic properties. The agreement between FEA and experiment was very high. The results show that not only NPR but also cell topology provides a practical route to the synclastic formation of cores without the use of auxetic materials. Full article

This paper suggests a theoretical framework to summarise the empirical literature on the relationships between sports and both religious and secular ethics, and it suggests two interrelated theoretical models to empirically evaluate the extent to which religious and secular ethics, as well as sports policies, affect achievements in sports. I identified two national ethics (national pride/efficiency) and two social ethics (social cohesion/ethics) by measuring achievements in terms of alternative indexes based on Olympic medals. I referred to three empirical models and applied three estimation methods (panel Poisson, Data Envelopment, and Stochastic Frontier Analyses). I introduced two sports policies (a quantitative policy aimed at social cohesion and a qualitative policy aimed at national pride), by distinguishing sports in terms of four possibly different ethics to be used for the eight summer and eight winter Olympic Games from 1994 to 2024. I applied income level, health status, and income inequality, to depict alternative social contexts. I used five main religions and three educational levels to depict alternative ethical contexts. I applied country dummies to depict alternative institutional contexts. Empirical results support the absence of Olympic ethics, the potential substitution of sport and secular ethics in providing social cohesion, and the dependence of sports on politics, while alternative social contexts have different impacts on alternative sport achievements. Full article

This study explores the key factors driving corporate social responsibility disclosure (CSR_DISC) by Takaful insurance companies (TKIs) in Saudi Arabia during and after the COVID-19 pandemic. We use content analysis and follow an unweighted scoring method to score the CSR_DISC index. Based on a sample of 26 Saudi-listed TKIs, for the period 2020–2024, we employ Poisson panel and negative binomial panel models to examine the interdependent relationships between CSR_DISCs and a set of corporate governance factors. We find that Saudi TKIs increased their CSR_DISCs in their financial reporting during and after the COVID-19 crisis. These findings confirm that board and firm size have a significant and negative effect on corporate CSR_DISC. However, the number of independent board members and female directors positively affect the extent of CSR_DISCs. Finally, the size of the audit committee and the Shariah supervisory board, frequency of board meetings, and profitability do not affect CSR_DISCs. Full article

Background: Existing research highlights the necessity of tailoring cost-containment policies to specific treatments due to the varying benefits across different diseases. This study contributes additional insights by examining the impact of such policies on a non-acute condition—cataracts. Methods: Leveraging 16 years of national health insurance claim data, this research assesses the influence of three prevalent cost-containment payment schemes on healthcare service utilization. Outcome variables for analysis include the decision to adopt intraocular lens (IOL) insertion, outpatient visit volume, and healthcare expenditures. The robustness of the findings is enhanced through the use of statistical methods, such as logit, Poisson, negative binomial, and panel fixed-effect models. Results: Global budgeting reduces the likelihood of procedure adoption and negatively impacts the volume of outpatient consultation services. Cost sharing does not affect procedure adoption but significantly impacts outpatient service volume. The prospective payment scheme for cataract IOL treatment shows no long-term effects on service utilization, with treatment rates stabilizing after a few years of policy implementation. Despite reimbursement points remaining unchanged for over two decades, there is no evidence of the under-provision of treatment. Conclusions: This study underscores the significant responsiveness of both patients and providers to policy reforms in the non-acute disease category. Manipulating payment schemes can lead to cost savings, particularly when treatment plans and procedures exhibit increased elasticity in their provision. Full article

This study examines the potential of grain trade within the context of global commerce, highlighting its role as a primary component of the worldwide agricultural market and a crucial factor in ensuring global food security and price stability. To achieve the research objectives, we utilized panel data from Russia, a leading player in the grain market, and employed a gravity model along with Poisson pseudo-maximum likelihood (PPML) to analyze the impact of demand factors and the economic openness of importing countries, as well as the effects of distance, sea access, borders, language, trade unions, and tariffs on exports. Our research challenges the notion that an increase in the wealth of countries leads to a corresponding rise in trade between them. In the case of grain, evidence indicates a negative contribution of GDP per capita in importing countries. The gravity model and PPML enabled us to assess individual country effects and quantitatively evaluate the potential for increasing Russian grain exports to Asian and African nations. We propose recommendations for enhancing domestic grain production and improving the effectiveness of marketing strategies in countries with underutilized export potential. Full article

The Asia-Pacific region has gradually become a driver of global economic growth, with economic integration agreements (EIAs) and climate distance playing increasingly important roles in the agri-food trade in the 21st century. The recent signing and implementation of the Regional Comprehensive Economic Partnership (RCEP) and the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) have garnered global attention. This study examines the roles of different types of regional trade agreements and climate distance in the agri-food trade in the Asia-Pacific region and constructs a trade system involving 19 member countries of the RCEP and the CPTPP by analyzing panel data from 2003 to 2022. The Poisson pseudo-maximum likelihood estimator is employed to estimate an augmented gravity model that considers domestic trade flows, endogeneity issues, reverse causality, globalization effects, long-term effects, and overlapping membership. The empirical findings demonstrate that partial scope agreements and EIAs significantly promote bilateral agri-food trade, whereas temperature distance acts as a barrier and precipitation distance has a negligible effect. Overlapping members of the RCEP and CPTPP exhibit cumulative positive effects three years after the implementation of EIAs, resulting in an approximately 52.1% increase in the bilateral agri-food trade after ten years. Additionally, overlapping membership mitigates the long-term negative impact of temperature distance. This study reveals that the seven overlapping members of the RCEP and CPTPP in the Asia-Pacific region achieve greater benefits more quickly through EIAs, suggesting that overlapping membership can be an effective adaptive strategy for dealing with climate change. Full article

In survival analysis, interval-censored data and panel count data represent two prevalent types of incomplete data. Given that, within certain research contexts, the events of interest may simultaneously involve both data types, it is imperative to perform a joint analysis of these data to fully comprehend the occurrence process of the events being studied. In this paper, a novel semiparametric joint regression analysis framework is proposed for the analysis of interval-censored data and panel count data. It is hypothesized that the failure time follows an additive–multiplicative hazards model, while the recurrent events follow a nonhomogeneous Poisson process. Additionally, a gamma-distributed frailty is introduced to describe the correlation between the failure time and the count process of recurrent events. To estimate the model parameters, a sieve maximum likelihood estimation method based on Bernstein polynomials is proposed. The performance of this estimation method under finite sample conditions is evaluated through a series of simulation studies, and an empirical study is illustrated. Full article

Owing to its enhanced production efficiency, roller hemming has become the mainstream process for forming and joining metal sheets in the automotive industry. This study investigates the roller hemming process of a specific car door panel through a combination of experimental analysis and finite element analysis (FEA) on both straight-edge and curved-edge flat surfaces. Consequently, the mechanical properties of the door panel, including tensile strength, yield strength, modulus of elasticity, and Poisson’s ratio, were estimated through tensile testing and then underwent finite element modeling. The simulation results demonstrated the varying distribution of stress during the rolling hemming process, with the highest stress concentration observed in the bending area. Additionally, creepage and growing results were acquired from both simulation and experimental data to validate the precision of the numerical model. A comparison was made between the experimental and simulation results of the external forces exerted by the roller on the panel. In both straight- and curved-edge sections, the external force during final hemming exceeded that during pre-hemming, as revealed by experimental measurements of both normal and tangential external forces, surpassing their corresponding simulated values. Full article

This paper presents a numerical study of a blast-resistant design of reinforced concrete panels with a novel auxetic reinforcement layout inspired by auxetic materials, which have a negative Poisson’s ratio, i.e., shrink under compression and expand under tension. A series of two-way supported panels reinforced with re-entrant auxetic-shaped rebars were numerically tested under a TNT explosion. The high-fidelity multi-physics explicit solver of LS-DYNA was utilized to analyze the efficiency of the proposed design. Firstly, the incident pressure of a TNT explosion data and the structural response of a conventional reinforced concrete panel under a TNT explosion were successfully validated by comparing with the experimental and empirical results. Secondly, the blast-resistant capacity of the proposed model was evaluated in comparison to two different conventional designs. Moreover, a parametric study was carried out to reveal the driving parameters of the newly proposed auxetic-shaped reinforcement design. It has been proved that the proposed auxetic reinforcement layout significantly reduces the spalling radius and increases the energy absorption capacity of panels. As a result of the parametric study, the increased reinforcement volume ratio was ineffective on the spalling radius, although the cell size of auxetic reinforcement was found to be quite effective for the blast-resistant design of concrete panels. Overall, the proposed re-entrant auxetic reinforced panel performed far better than conventional designs under blast load. With the recent developments in 3D printing technology, the proposed auxetic reinforcement layout is a strong candidate to deal with blast-resistant designs of concrete panels. Full article

In the context of digital transformation and economic globalization, R&D (research and development) internationalization is essential for enterprises to utilize global resources and achieve technological innovation. This study examines Chinese A-share-listed industrial companies with active overseas R&D from 2010 to 2022 using a Poisson panel fixed-effects model to assess how digital transformation influences R&D internationalization. The findings confirm that digital transformation significantly enhances the depth and breadth of R&D internationalization, even when controlling for endogeneity. The analysis identifies financing constraints and information communication efficiency as key mediators in this process. Additionally, the impact varies by the type of digital technology and the geographical location of the enterprises. This research not only deepens understanding of the link between digital transformation and R&D internationalization but also aids policy formulation for governments and businesses. Full article