Search Results (114)

This paper examines the relationship between economic growth and rural unemployment in Brazil and Mexico, incorporating the effects of climate variability and spatial interactions. Okun’s Law serves as the theoretical framework, and a dynamic spatial panel model is applied to estimate short-term causal effects. The analysis uses data from Brazil’s IBGE, Mexico’s INEGI, and the U.S. NCEI. The results indicate that Okun’s Law is only partially validated in Mexico, where lagged income growth reduces rural unemployment, while in Brazil, the relationship is not statistically confirmed. Climate variables also play a critical role: higher local temperatures reduce unemployment in Brazil and, with a lag, in Mexico, although temperature increases in neighboring regions raise unemployment in Mexico. Rainfall has a consistent positive effect on rural unemployment in both countries, highlighting the disruptive impact of extreme weather events. From a spatial perspective, no contemporaneous effects are observed. However, lagged spatial effects are negative in Brazil and positive in Mexico, suggesting different adjustment dynamics across territories. Overall, the findings reveal that climate variability influences the growth-unemployment nexus differently depending on the national context and temporal dimension. These results underscore the importance of designing public policies that integrate territorial coordination, address the differentiated impacts of climate variability, and strengthen the adaptive capacity and resilience of rural areas in Latin America. Full article

Breaking barriers to sustainable jobs and promoting inclusive employment are key goals of the 2030 Agenda, with SDG8 Target 8.5 aiming to achieve decent work for all, including persons with disabilities (PWDs). This paper contributes to the scholarly debate by empirically examining how various regulatory areas, including credit market regulation, labor market regulation, business regulation, and the freedom to compete, influence the informal employment of PWDs in 15 countries between 2007 and 2022. The empirical investigation is conducted for the entire population with disabilities, as well as for adults and youth with disabilities. The analysis employs a dynamic labor demand function estimated through the two-step system GMM method to account for adjustment costs within the labor market. In addition, the Feasible Generalized Least Squares method is employed to assess the robustness of the results. The findings reveal significant heterogeneity in the effects of regulation on the informal employment of PWDs, with substantial differences between adults and youth. At the aggregate level, greater flexibility in most regulatory areas reduces informal employment of PWDs, except for labor market regulation. Upon examining age cohorts, the outcomes for adults exhibit similarities to the aggregate analysis. In contrast, more flexible regulations increase informal employment among young people with disabilities, except for business regulations, which exert negative impacts, and credit market regulations, which demonstrate no significant effects. This study recommends that policymakers support formal business development for PWDs and implement anti-discrimination laws. For youth with disabilities, targeted initiatives, including financial inclusion and wage subsidies, are essential to convert regulatory flexibility into formal employment opportunities. Full article

Nowadays, with the continuous development of corporate ESG ratings, greenwashing has occurred continuously. In order to clarify the influence of the environmental protection tax (EPT) on corporate ESG greenwashing, this paper employs the implementation of the Environmental Protection Tax Law (EPTL) as a quasi-natural experiment, based on the sample data of Shanghai and Shenzhen A-share listed companies during 2015–2022. Using a Difference-in-Differences model to analyze the effect and mechanism of the EPT on corporate ESG greenwashing, we obtain the following findings: (1) The EPT can curb corporate ESG greenwashing, and this effect is more obvious in non-state-owned enterprises, non-labor-intensive enterprises, low-competitive industries, and enterprises located in the east-central region of China. (2) From a mechanistic perspective, reducing information asymmetry and promoting green transformation are two important paths. (3) Higher ESG ratings increase the inhibition of the EPT towards corporate ESG greenwashing. Full article

This study explores the comparative employment laws related to migrant worker protection in Indonesia and Malaysia, with a focus on the socioeconomic inequalities faced by migrant workers in both countries. The study identifies key challenges in law enforcement, including migrant workers’ vulnerability to exploitation, poor recruitment procedures, and limited access to adequate legal education and information. A qualitative–interpretive methodology is used to explore in-depth issues related to employment laws and the socio-economic conditions of migrant workers. The study shows that Indonesia’s decentralized system results in fragmented and inconsistent law enforcement across regions, exacerbated by weak institutional capacity, legal gaps, and bureaucratic inefficiencies. Meanwhile, Malaysia’s centralized but pro-employer governance prioritizes economic growth over labor rights, leaving migrant workers—especially in the domestic and informal sectors—exposed to exploitation, wage discrimination, debt bondage, and limited access to social protection. To address these inequalities, bilateral cooperation between Indonesia and Malaysia is needed, including stronger law enforcement and equal protection for local and migrant workers. The study’s key finding is that these institutional weaknesses not only perpetuate migrant workers’ vulnerability, but also deepen structural socioeconomic inequalities between workers, agents, and employers. The study underscores the need for stronger law enforcement, formalization of the informal sector, harmonization with international labor conventions, and stronger bilateral cooperation. This study contributes to labor law studies and policy debates by offering insights into the institutional reforms necessary for more equitable and sustainable migrant worker governance in Southeast Asia. Full article

This article examines the effects of maternity leave (Law 1822 of 2017) on the Colombian women’s labor market. Using biannual cohorts during the working life cycle of women (18 to 57 years old) reveals that the law’s implementation reduced the hours worked and the real hourly wage for younger women compared to older women. Average treatment effects show that the difference between the hours worked after 2017 was 0.917 (treatment vs. control), and before, it was 1.714 h worked (treatment vs. control). Differences show a reduction of 41 h per cohort and year (approximately one week worked). Synthetic control analysis shows that young cohort experienced a reduction of 0.007 U$ cents in 2017 and a reduction of 2.2 h worked in 2017. Our results highlight the importance of differential policies related to maternity leave by age (cohort) when analyzing the incorporation of women into the labor market. Full article

Global agriculture is confronting unprecedented pressures from population growth, diminishing arable land, and severe rural labor scarcity, necessitating the advancement of intelligent agricultural equipment. As a core component of precision farming, unmanned agricultural tractors demand highly accurate and robust path tracking control. However, conventional methods often fail to cope with unstructured terrain and dynamic wheel slip under real field conditions. This paper proposes an extended state observer (ESO)-based improved Stanley guidance law, which incorporates real-time sideslip angle observation, adaptive preview-based path curvature compensation, and a sliding mode heading controller. The ESO estimates lateral slip caused by varying soil conditions, while the modified Stanley law utilizes look-ahead path information to proactively adjust the desired heading angle during high-curvature turns. Both co-simulation in Matlab-Carsim and field experiments demonstrate that the proposed method significantly reduces lateral tracking error and overshoot, outperforming classical algorithms such as fuzzy Stanley and sliding mode controller, especially in U-turn scenarios and under low-adhesion conditions. Full article

Work is historically evolving due to technological advancements, posing challenges for individuals and institutions. The actual Fourth Industrial Revolution, marked by AI, biotechnology, and nanotechnology, has rapidly increased these advancements, while the COVID-19 pandemic has anticipated future expected changes in the labor market. In this context, Higher Education Institutions must match their curricula with this dynamic labor market to equip graduates with relevant skills. However, the slow pace of educational transformation, partly due to a lack of data, hinders this alignment. This research introduces Future-oriented Higher Education Degree Employability (Fo-HECE) as an evaluation tool for the adherence of undergraduate degrees to the demands of the labor market in the next decade. We used a novel approach, combining the Operationalization of a social phenomenon with Multi-Criteria Decision-Making, with the participation of nine experts. As a use case, we applied the new approach to assess the future employability of ten undergraduate programs with the most enrolled students from one of the largest Brazilian universities. As a result, the indicators considered most relevant to measure Fo-HECE are Student-to-Job Ratio, Employment Balance, and Wage Premium. The degrees with the highest Fo-HECE grades were Law and Medicine, while Physical Education had the lowest grade. The Fo-HECE approach, as demonstrated in this case study, shows potential applicability to other HEIs and countries, provided that comparable labor market data are available. Full article

High-Voltage Alternating Current (HVAC) transmission systems form the backbone of modern power grids, enabling efficient long-distance and high-capacity power delivery. In Saudi Arabia, ongoing initiatives to modernize and strengthen grid infrastructure demand advanced solutions to ensure system reliability, operational stability, and the minimization of economic losses caused by faults. Traditional fault detection and classification methods often depend on the manual interpretation of voltage and current signals, which is both labor-intensive and prone to human error. Although data-driven approaches such as Artificial Neural Networks (ANNs) and Deep Learning have been applied to automate fault analysis, their performance is often constrained by the quality and size of available training datasets, leading to poor generalization and physically inconsistent outcomes. This study proposes a novel hybrid fault detection and classification framework for the 380 kV Marjan–Safaniyah HVAC transmission line by integrating Deep Learning with Physics-Informed Neural Networks (PINNs). The PINN model embeds fundamental electrical laws, such as Kirchhoff’s Current Law (KCL), directly into the learning process, thereby constraining predictions to physically plausible behaviors and enhancing robustness and accuracy. Developed in MATLAB/Simulink using the Deep Learning Toolbox, the proposed framework performs fault detection and fault type classification within a unified architecture. A comparative analysis demonstrates that the hybrid PINN approach significantly outperforms conventional Deep Learning models, particularly by reducing false negatives and improving class discrimination. Furthermore, this study highlights the crucial role of balanced and representative datasets in achieving a reliable performance. Validation through confusion matrices and KCL residual histograms confirms the enhanced physical consistency and predictive reliability of the model. Overall, the proposed framework provides a powerful and scalable solution for real-time monitoring, fault diagnosis, and intelligent decision-making in high-voltage power transmission systems. Full article

Increasing labor costs, labor shortage, high environmental impact, and low productivity levels are the main reasons that have led the construction industry to search for sustainable alternatives to conventional traditional construction techniques, such as Additive Construction. Large-scale concrete 3D printing has emerged as a viable alternative, which can address these major challenges. Through the high material efficiency, design flexibility, and automation levels provided, 3D printing can revolutionize the way buildings are designed and built. The seismic behavior of 3D-printed load bearing elements remains generally underexplored. To that scope, the structural design of a two-story building is investigated. The proposed methodology involves finite element models and stress analysis of critical structural members. The performance of the studied walls is further investigated using 3D solid element models and nonlinear constitutive laws to validate structural adequacy. Different printing patterns and structural details of unreinforced and reinforced 3D-printed concrete walls are analyzed through parametric analyses. The results indicate the acceptable response of 3D-printed load bearing elements, under certain construction configurations, as required by the existing regulatory framework. The proposed methodology could be applied for the design of such structures and for the optimization of printing patterns and reinforcing details. Full article

Prior economic research emphasized land, labor and physical capital as the primary drivers of growth, but contemporary work highlights the pivotal role of human capital. Investments in education, health and governance are now regarded as central to sustainable development; yet important questions remain regarding their effectiveness and context-specific impact. This study investigates how human capital investment influences labor force participation and income growth within the ASEAN nine economies for the period from 2000 to 2022 which provides a rich example of contrast in economic and governance outcomes within a single geographic region. Impacted units of measurement of labor force participation and income growth are evaluated using the Bayesian Additive Regression Trees model to select the most important variables, the Bayesian Dynamic Nonlinear Multivariate panel model to estimate regional effects, and the Time-varying Seemingly Unrelated Regression Equations model to evaluate country-specific dynamics, which considers not just the influence of investments in health and education but also the context of rule, law, and governance. The findings indicate that human capital investments exhibit heterogenous effects across economic tiers and the need for strategies and future study of preconditions to improve returns particularly in low-tier economies. Accordingly, mid-tier, emerging economies exhibit the greatest benefit from human capital investments while top-tier exhibit the probable impact of the law of diminishing returns as their human capital development is already well underway. Despite the limited scope, this study still has the potential to draw constructive theoretical and practical implications. Full article

In recent years, experts have associated forecasts of global energy consumption with energy transitions. This paper presents the research results of the paths and trajectories of the global transformations of world energy, including demographic, technological, energy, transport, and communication changes. After demonstrating the long-term trends in global energy consumption, fossil and renewable energy sources, and nuclear energy using neuroforecasting methods, this study explains global demographic development and its relationship with global innovation and technological processes as explained by the flow of global patent applications. The relationship between energy transition and the previously mentioned two factors is also justified based on the trajectories developed by the neural network forecasting. By leveraging the fundamental laws of energy conservation, robust patterns in the evolution and development of global energy could be identified. It is demonstrated that mankind has entered the era of four closely interconnected global transitions: demographic, energy, technological, and political–economic, all at once. According to the results, civilizational changes are currently taking place in global energy advancement, indicating an energy transition to a new quality of energy development. The permanent growth patterns of the energy density of energy sources used and their impact on labor productivity and the speed of movement of people and goods in the economy are also discussed. Finally, the contour of future developments in energy technologies is determined. It is also forecast that future energy technologies are expected to be largely associated with the exploration of outer space, development of robotics, and the expansion of artificial intelligence capabilities. Full article

To address the problems of the time consumption, labor intensiveness, easy contamination, uneven drying, and impact on the medicinal efficacy of Fritillaria ussuriensis in the traditional drying method, the hot-air-drying characteristics of Fritillaria ussuriensis were studied. The changes in the moisture ratio and drying rate of Fritillaria ussuriensis under different hot-air-drying conditions (45 °C, 55 °C, 65 °C) were compared and analyzed. Six common mathematical models were used to fit the moisture change law, and it was found that the cubic model was the most suitable for describing the drying characteristics of Fritillaria ussuriensis. The R² values after fitting under the three temperature conditions were all greater than 0.99, and the maximum was achieved at 45 °C. Based on the principle of hot-air drying, a drying device for Fritillaria ussuriensis with a processing capacity of 15 kg/h was designed. It adopted a thermal circulation structure of inner and outer drying ovens, with the heating chamber separated from the drying chamber. The structural parameters were optimized based on Fluent simulation analysis. After optimization, the temperature of each layer was stable at 338 K ± 2 K, and the pressure field and velocity field were evenly distributed. The drying process parameters of Fritillaria ussuriensis were optimized based on response surface analysis, and the optimal process parameters were obtained as follows: inlet temperature: 338 K (65 °C), inlet air velocity: 3 m/s, and drying time: 10 h. The simulation results showed that the predicted moisture content of Fritillaria ussuriensis under the optimal working conditions was 12.58%, the temperature difference of Fritillaria ussuriensis at different positions was within 0.8 °C, and the humidity deviation was about 1%. A prototype of the drying device was built, and the drying test of Fritillaria ussuriensis was carried out. It was found that the temperature and moisture content of Fritillaria ussuriensis were consistent with the simulation results and met the design requirements, verifying the rationality of the device structure and the reliability of the simulation model. This design can significantly improve the distribution of the internal flow field and temperature field of the drying device, improve the drying quality and production efficiency of Fritillaria ussuriensis, and provide a technical reference for the Chinese herbal medicine-drying industry. Full article

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

Daoist robes in the Ming Dynasty literature underwent a marked transformation from exclusive religious vestments to widespread secular attire. Originally confined to Daoist priests and sacred rites, these garments began to appear in everyday work, entertainment, and ceremonies across social strata. Drawing on a hand-coded corpus of novels that yields robe related passages, and by analyzing textual references from Ming novels, Daoist canonical works, and visual artifacts, and applying clothing psychology and semiotic theory, this study elucidates how Daoist robes were re-coded as secular fashion symbols. For example, scholar-officials donned Daoist robes to convey moral prestige, laborers adopted them to signal upward mobility, and merchants donned them to impersonate the educated elite for commercial gain. By integrating close textual reading with cultural theory, the article advances a three-stage model, sacred uniform, ritual costume, and secular fashion, that clarifies the semantic flow of Daoist robes. In weddings and funerals, many commoners flaunted Daoist robes despite sumptuary laws, using them to assert honor and status. These adaptations reflect both the erosion of Daoist institutional authority and the dynamic process of identity construction through dress in late Ming society. Our interdisciplinary analysis highlights an East Asian perspective on the interaction of religion and fashion, offering historical insight into the interplay between religious symbolism and sociocultural identity formation. Full article

This study explores the drivers and evolution of the shadow economy in Bosnia and Herzegovina—a transitional, post-conflict country facing persistent institutional fragility. Using the Multiple Indicators and Multiple Causes (MIMIC) model, an extension of Structural Equation Modeling, the paper estimates the size and dynamics of the shadow economy from 1996 to 2022. The model integrates macroeconomic indicators (employment rate, GDP per capita, tax revenues) and institutional variables (rule of law, control of corruption), with data primarily sourced from the World Bank. The results show that institutional quality, tax burden, and labor market conditions are significant determinants of the informal sector. The model demonstrates strong statistical validity (CFI = 0.986, RMSEA = 0.05), supported by robustness checks including unit root tests, structural break analysis, and the exclusion of controversial benchmarking methods. The shadow economy responds markedly to major shocks such as the 2008 global financial crisis and the 2014 floods. Findings provide valuable policy insights: strengthening institutions, simplifying tax systems, and encouraging formal labor market participation can significantly reduce informality. The study supports evidence-based reforms to enhance transparency, resilience, and sustainable development in Bosnia and Herzegovina. Full article