This study investigates the impact of digital financial inclusion (DFI) on banking sector performance (BSP) in high income economies, with a focus on the moderating role of institutional quality. Using a balanced panel dataset of 45 high income economies over 2011-2021, the study constructs composite indices for DFI, BSP, and institutional quality via Principal Component Analysis (PCA). The two-step System GMM estimator is employed to address endogeneity, dynamic persistence, and unobserved heterogeneity. The findings reveal that DFI significantly enhances BSP, while institutional quality does not significantly moderate this relationship, indicating that strong governance in advanced economies already supports effective digital financial adoption. Foreign bank presence also positively contributes to performance, whereas macroeconomic controls are largely insignificant. These results highlight the central role of DFI in promoting efficiency, profitability, and stability in mature banking systems.

The research examines the role of the pharmaceutical industry in achieving Sustainable Development Goal 9 in the low- and middle-income countries (LMICs). The economic and environmental aspects of pharmaceutical industrialization are measured with the help of two composite measures: Sustainability in pharmaceutical industry (SPI) and Pharmaceutical Economic performance Index. The endogeneity, the dynamics of time, and heterogeneity of countries are tackled using a dynamic System Generalized Method of Moments model that is estimated using ten LMICs panel data covering timeframe of 2013–2023. Findings indicate that sustainability remains an issue that persists: a lagged SPI (SPI t−1) has a positive influence on the present sustainability. Sustainability is also increased with economic performance and foreign direct investment and a detrimental effect is exerted by urbanization. Significant positive results are evident in the Government environmental taxes and the government expenditure on environmental protection. These results put a major emphasis on the roles played by industrial performance, policy tools, and technological transfer to enhance sustainable pharmaceutical industrialization in LMICs.

Achieving Sustainable Development Goal 2 (Zero Hunger) necessitates novel approaches that improve food security via knowledge-based economic development. This research examines at the influence of the knowledge-based economy (KBE) on achieving zero hunger in 44 Asian developing nations and the G7 economies between 2000 and 2024. A composite Knowledge Economy Index based on education, innovation, information and communication technology, and the economic and institutional regime is compared to a Zero Hunger Index using second-generation panel econometric approaches. This empirical investigation includes use of cross-sectional dependency and slope homogeneity tests, the Cross-sectionally Augmented IPS (CIPS) unit root test, the Westerlund cointegration test, Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) estimate, and Dumitrescu-Hurlin panel causality analysis. The results reveal a strong long-term link between the knowledge-based economy and zero hunger in groups both of countries. Improvements in the knowledge-based economy greatly reduce hunger, with a greater impact shown in G7 nations than in Asian developing countries. Renewable energy and foreign direct investment improve food security, whereas growing urbanization exacerbates hunger-related issues. The error correction estimates support a quick convergence to long-run equilibrium, whereas bidirectional causation between the KBE and Zero Hunger suggests a mutually supporting connection. The study suggests that enhancing education, innovation, digital infrastructure, and institutional quality is critical for improving food security. It will speed up the progress toward SDG 2, particularly in Asian developing nations and G7.

Structural changes in an economy depend on the development of physical infrastructure, which is crucial for the socioeconomic growth of any country and drives the demand for cement. Cement is a vital component for all sectoral transformations, such as the building industry, residential construction, and large-scale infrastructure projects. In light of rapid physical infrastructure development, this research employs the Cobb-Douglas production function to carry out a comparative analysis of coal-gas substitution in the cement sector’s output from 1990 to 2022. For both the long and short-run relationships, the study uses Error Correction Models based on the Cobb-Douglas production function. The results of the long-run and short-run models indicate a unidirectional causality effect from coal and natural gas consumption to output growth. Additionally, the statistically significant substitution effect from natural gas to coal consumption at the rotary kiln process reveals that coal conservation policies will reduce the growth performance of the cement sector, which is associated with environmental degradation, and lead to a decline in economic development. In contrast, the use of natural gas in the cement sector has the least influence on carbon dioxide emissions levels and is a more sustainable option. To achieve sustainable growth for physical infrastructure development, the Government of Pakistan should provide relative cost incentives to cement producers to shift their consumption patterns from coal to natural gas.

In recent decades, the digital economy has played a pivotal role in driving global economic growth. Developing countries in Asia also fuel their economic development through the digital economy. However, these countries have inefficient technical infrastructure, limited access to modern technology, and inadequate investment in innovation and communication. Therefore, this study was conducted to empirically explore the determinants of the digital economy in Asia's developing countries from 2001 to 2021. The results of diagnostic tests suggest the use of a cross-sectionally augmented autoregressive distributed lags (CS-ARDL) model. The results of the CS-ARDL show that technical infrastructure is statistically significant in both the short run and the long run. When technical infrastructure increases by 1 percent, the related outcome increases by 0.61percent. However, in the short run, all other variables, such as access to modern technology, return on telecom investment, and technological innovations, have statistically insignificant effects. However, these variables play a crucial role in the long run, like return on telecom investment has a strong positive effect with a coefficient of 0.25, technological innovation has a coefficient of 0.20, and modern technology access has a negative coefficient of -0.30, but significant, and shows that extensive access might seem helpful at first, but leads to oversaturation. The result also shows that the model is dynamically stable, and any short-run disequilibrium can be corrected in the long run. Ultimately, the study presented several valuable suggestions for policymakers.

Tourists play a vital role in the development of sustainable tourism by boosting the local economy, preserving culture, and reducing environmental degradation. However, tourists’ decisions to visit destinations and promote sustainable tourism are influenced by reliable infrastructure, safety, security, and trust in institutions. A well-developed infrastructure, a peaceful environment, and efficient tourism management encourage tourism and sustainability. Therefore, this research examines the effect of tourism, infrastructure, institutions, and place attachment on sustainable tourism. Additionally, the study examines the role of infrastructure, institutions, and place attachment on tourists’ satisfaction in Khyber Pakhtunkhwa. Primary data were collected through surveys and Google forms from five tourist districts, Swat, Abbottabad, Mansehra, Upper Dir, and Lower Dir of Khyber Pakhtunkhwa. A total of 250 responses were collected from tourists using a proportionate random sampling technique. The data were analyzed using the partial least square structural equation modeling (PLS-SEM) technique. The results show that place attachment and tourist satisfaction positively affect sustainable tourism, while infrastructure, place attachment, and trust in institutions positively affect tourist satisfaction. Furthermore, sustainable tourism was more influenced by tourist satisfaction, and tourist satisfaction was more influenced by trust in institutions and infrastructure. The study also confirmed that infrastructure mediates the relationship between trust in institutions and sustainable tourism and between trust in institutions and tourist satisfaction. The study provides valuable insight to policymakers in assessing tourists’ behavior and sustainable tourism.

The rising global energy demand, coupled with the pressing need to address climate change, has positioned energy efficiency as a top priority on policy agendas worldwide. The study empirically analyses the impact of digitalization and trade openness on energy efficiency across low-, middle-, and high-income countries by applying a two-step system Generalized Method of Moments (GMM) approach on a balanced panel dataset covering the period from 2008 to 2021. This paper estimates energy efficiency through the application of Stochastic Frontier Analysis (SFA). The outcomes of SFA demonstrate that average energy efficiency scores of 77%, 86%, and 92% for low-, middle-, and high-income nations, respectively, indicating substantial potential for further improvement across all income levels. The findings of GMM reveal that both digitalization and trade openness significantly enhance energy efficiency, with high income countries benefiting from larger coefficients, likely due to advanced infrastructure, stringent regulations, and access to energy-efficient technologies. The study highlights the disparities in energy efficiency drivers between income groups and suggests that low- and middle-income nations could adopt best practices from high income countries to boost their energy efficiency. These insights provide crucial implications for global energy policy, especially in the pursuit of sustainable development and the shift toward a low-carbon economy.

Sustainable consumption behaviour can address environmental, social, and economic problems created by unsustainable consumption behaviour, whereas socio-economic factors are crucial factors which influence human consumption behaviour. Therefore, this study conducted a comparative analysis of urban-rural Khyber Pakhtunkhwa regarding the effects of socio-economic factors on sustainable consumption behaviour. The Krejcie and Morgan method was used to determine the sample size, and the multistage cluster sampling technique was used to form the whole sample from the target population. Data from sampled respondents were collected through self-administered questionnaires. Partial Least Squares Multigroup Analysis (PLS-MA) was used to analyse the data. The findings of this study demonstrate that all socio-economic factors included in this study, except Gender, significantly affect sustainable consumption behavior. The coefficients of Gender (β=0.15, P<0.05), education (β=0.44, P<0.05), and income (β=0.35, P<0.05) are positive and statistically significant, which means these variables have positive effects on sustainable consumption behaviour. The coefficient of Gender (β= 0.08, P= 0.43) is positive; however, it is statistically insignificant. The coefficient of employment status (β=-0.22, P <0.05) is negative, which implies that employed people are more sustainable than unemployed people. The results further show that the effects of socioeconomic factors on sustainable consumption behaviour are more potent in urban areas than in rural areas. Finally, the study presents some valuable recommendations for policymakers and businesses.

Income convergence refers to the idea that poor countries grow more quickly than rich ones and catch up in terms of per capita income; as a result, the per capita income of integrated nations eventually converges. Beta convergence suggests that less developed nations grow more quickly than more developed ones and reach their average per capita income level by growing more quickly. Meanwhile, sigma convergence suggests that the per capita income disparity among the countries in a regional block narrows over time.The objective of this study is to test income convergence through beta and sigma convergence for Central and South Asia integration using data from 1990 to 2022. Sigma convergence is tested through the standard deviation and coefficient of variation of average per capita income, while beta convergence is tested using panel unit root tests. The results of the study confirm the beta convergence and sigma convergence, which implies income convergence for the integration of Central and South Asia.The implications of this study are manifold. It recommends that Central and South Asian countries ensure economic, political and social cooperation with one another. This is possible by eliminating trade restrictions and decreasing import taxes to increase free trade. Additionally, ensuring free labor, capital, and technology movement between Central and South Asia will be beneficial for ensuring economic integration, facilitating income convergence, and reducing income inequality between these regions. This study contributes to the income convergence literature by focusing on integration between Central Asia and South Asia.

Transition towards renewable and low-carbon energy is now the core objective of energy policy of all countries striving to achieve sustainable development goals. This necessitates the understanding of accelerating factors of energy transition. Therefore, this study investigated the influence of technological diffusion on energy transition using data from South Asia and G20 countries from 2000 to 2022. The data estimation starts with cross-sectional dependence and unit root test, and both these tests suggest the use of the feasible generalized least square method as the primary estimation technique. The feasible generalized least square findings show that technological diffusion positively and significantly affects energy transition in South Asia and G20 countries. The results also demonstrate that the effect of technological diffusion on energy transition is stronger in G20 countries than in South Asia. Findings further show that globalization and governance accelerate energy transition, but the effect of governance on energy transition in South Asia is statistically insignificant. In contrast, Income per capita has an inverted U-shaped relationship with energy transition in both countries. Finally, this study makes some recommendations for further enhancing energy transition in light of the findings of this study.

In the modern era, surging economic activities heighten energy demand, depleting traditional reserves and harming the environment. Renewable energy emerges as a vital alternative but faces technical, economic, and policy challenges. This study explores the impact of factors like energy grid, government incentives, CO2 emissions, economic growth, and electricity prices on renewable energy adoption in Pakistan from 1990Q1 to 2022Q4. Results reveal a U-shaped relationship between the energy grid and renewable energy penetration in the short and long terms. National support initially boosts green energy but diminishes over time. Economic incentives initially hinder adoption (i.e., 7.445, p G 0.000) but increase in the long run (i.e.,-2.881, p G 0.000). Energy prices suppress adoption in the short term (i.e.,-0.084, p G 0.050). Income correlates positively in the short term (i.e., 0.006, p G 0.000) but negatively in the long term (i.e., 0.019, p G 0.000). Policy-induced incentives and energy prices drive adoption, with impacts on income observed. Causal relationships and variance decomposition analysis highlight key factors influencing renewable energy integration in Pakistan, thereby informing policy and strategic decisions to foster sustainable energy practices.

The COVID-19 epidemic is the most significant global health disaster of this century and the greatest challenge to humanity since World War II. One of the most important research issues is to determine the effectiveness of measures implemented worldwide to control the spread of the corona virus. A dynamic simulated Autoregressive-Distributed Lag (ARDL) approach was adopted to analyze the policy response to COVID-19 in the ASEAN region using data from February 1, 2020, to November 8, 2021. The results of unit root concluded that the dependent variable is integrated of order one while the independent variables are stationarized at the level or first difference, and the use of a dynamic simulated ARDL technique is appropriate for this paper. The outcomes of the dynamic simulated ARDL model explored that government economic support and debt/contract relief for poor families is substantially important in the fight against COVID-19. The study also explored that closing schools and workplaces, restrictions on gatherings, cancellation of public events, stay at home, closing public transport, restrictions on domestic and international travel are necessary to reduce the spread of COVID-19. Finally, this study explored that public awareness campaigns, testing policy and social distancing significantly decrease the spread of COVID-19. Policy implications such as economic support from the government to help poor families, closing schools and public gatherings during the pandemic, public awareness among the masses, and testing policies must be adopted to reduce the spread of COVID-19. Moreover, the reduction in mortality shows that immunization could be a possible new strategy to combat COVID-19, but the factors responsible for the acceptability of the vaccine must be addressed immediately through public health policies.

Wheat is a major food crop in the study area. However, wheat yields continue to remain very low in this region mainly due to the use of poor-quality seed. The purpose of this study is to explore the impact of certified wheat seeds on food security, a case study of district Karak (Khyber Pakhtunkhwa) Pakistan. The multistage sampling technique was applied to collect data from 100 formers through a face-to-face interview, and a well-structured questionnaire was used to collect information from the respondents. Analysis of Covariance (ANCOVA) was used to determine the factors that influence household food security. The results of our study revealed that certified seed, age, access to credit, irrigation, education, off-frame employment, livestock size, and operated area have a positive and significant impact on household food security, but household size has a negative and significant effect on household food security. The policies should be set to promote the use of the certified seed, enhance the level of education, increase the irrigated area, and foster employment opportunities as they have a significant impact on food security. This study also recommended that government and non-government agencies should intensify efforts on the importance of family planning and advocate small family size in rural areas.

Effect of CJ-13,610 on Wnt-target genes in the PML/RARα-positive cell line NB4.

Climate change is considered the greatest threat to human life in the 21st century, bringing economic, social and environmental consequences to the entire world. Environmental scientists also expect disastrous climate changes in the future and emphasize actions for climate change mitigation. The objective of this study was to explore the influence of climate mitigation finance on climate change in the region most vulnerable to climate shock, i.e., South Asia, in the period from 2000 to 2019. The panel autoregressive distributed lag model was used to estimate the influence of climate mitigation finance on climate change. The findings of this study demonstrate that, in the long-run, climate mitigation finance has a significant role in mitigating climate change, while in the short-run, climate mitigation finance has an insignificant effect on climate change. The result also shows that, in the long-run, climate change has a negative causal relation with GDP and globalization, but it has a positive causal relationship with energy consumption. The short-term effects of all independent variables are insignificant. Finally, based on the outcome of this study, several policy measures are recommended in order to mitigate climate change.

The (3 + 1)-dimensional fractional modified Zakharov Kuznetsov (mZK) equation is one of the nonlinear models to indicate the impact of magnetic fields on weak ion-acoustic waves in plasma; made up of cool and hot electrons. The primary goal of the present study is to use the (m+G′G)-expansion technique to seek the solutions of mZK equation. The solutions are gained in the form of kink, dark, singular periodic and W-type soliton solutions. The influence of the fractional parameter on waveforms has also been examined by representing 2D and 3D graphs for distinct values of fractional-order β. Moreover, we utilize Hamiltonian system properties to confirm the stability of the solution. The (m+G′G)-expansion technique can also be used to examine the nonlinear evolution models being developed in various scientific and technological fields, such as mathematical physics and plasma physics. The soliton solutions attained by using the above technique have not been derived yet.

Effect of Zileuton on stem cell capacity in PML/RARα positive HSPCs.