The rapid growth of renewable solar and wind energy necessitates extensive, long-term energy storage solutions to stabilize the electric grid and address the intermittent nature of these sources. In the absence of cost-effective long-duration, large-scale (LDLS) energy storage, there is a risk of increased disruptive blackouts and brownouts as intermittent energy sources approach 50% of electricity generation. Our analysis underscores volumetric energy density as a pivotal determinant in LDLS energy storage solutions, which is particularly crucial during periods of diminished renewable resource availability, such as the rainy season. Despite emphasis on conventional electric batteries and mechanical storage technologies such as compressed air and pumped hydro for LDLS, their costs pose a significant obstacle to widespread adoption, especially in emerging economies. In this study, we present a groundbreaking approach to LDLS: on-demand electricity generation from carbon-neutral renewable oil, known as "green oil," leveraging Reliance’s innovative catalytic hydrothermal liquefaction (R-CAT-HTL) technology. Our investigation evaluated two distinct sources of green oil production: organic waste streams (e.g., municipal solid waste, agricultural-waste, etc.) and on purpose production of algal biomass. We demonstrate that burning renewable green oil to produce electricity offers a cost-effective solution for large-scale (GWh) long-duration (many days) energy storage, ensuring the stability, reliability, and resiliency of the electric grid. We also demonstrate that minimum 14 days, ideally 30 days energy storage is needed for continuous uninterrupted service, especially critical for manufacturing facilities. Through a meticulous levelized cost of storage (LCOS) analysis comparing green oil with other LDLS technologies reported in literature, we demonstrate the cost effectiveness of green oil. In this model, green oil serves as stored energy, functions akin to a battery and is efficiently converted into electricity through conventional reciprocating engines or next-generation more efficient turbines. Our findings suggest that green oil derived from diverse organic sources is the most economically viable option for GWh-scale storage, particularly when storage requirements extend beyond a single day. This research thus presents a transformative cost-effective solution to the pressing challenge of LDLS energy storage, accelerating a sustainable and resilient energy future.

The high price of energy due to green energy policy will cause adjustments across the US economy predicted in the present general equilibrium model that includes energy Btu input with capital and labor to produce manufactures and services. This same model in trade theory examines the effects of a tariff on an imported factor of production such as a natural resource or capital.  Corresponding error correction estimates of the reduced form equations of the model in annual 1970-2018 data prove robust and suggest model modifications. A parametric approach to noncompetitive pricing based on unit cost diminishing with output brings the model much closer to the estimates. Manufactures are revealed to have a higher degree of noncompetitive pricing than services. Assuming constant elasticity of substitution production, a weak degree is revealed to provide the best fit to the error correction estimates. The high price of green energy will cause an inelastic decrease in energy input resulting in increased energy revenue. Outputs of both sectors fall, more in manufactures due to its energy intensity. The capital return and wage also fall given the weak substitution of capital and labor relative to the price of energy. The wage rises slightly in the model but falls considerably in the error correction estimate. The only clear winner is energy input with increased revenue. The government owns a large share of hydrocarbon reserves and will benefit from a higher price of energy.

The digital economy based on digital technology is an important force for high-quality economic growth and industrial transformation, and has great potential for value creation. Based on the data of 30 provinces in China from 2007 to 2017, this paper uses entropy method to calculate the industrial green transformation (IGT), and empirically analyzes the impact of Digital economy on IGT. The DE can significantly reduce IGT of local and neighboring areas after excluding the influence of macro system factors and replacing the spatial weight matrix. The DE can indirectly reduce the IGT by accelerating the accumulation of human capital, and green technology innovation. The impact of digital economy on IGT is a non-linear relationship. With the further improvement of environmental regulation, financial development and intellectual property protection, the role of digital economy in IGT is more obvious. To this end, it is necessary to speed up the construction and improvement of digital infrastructure, build an integrated layout of "digital infrastructure", give full play to the radiating role of the digital economy, and implement differentiated development paths based on regional comparative advantages.

This study provides insight into CEO compensation dynamics in the public sector and private sector publicly listed firms in New Zealand. This research uses descriptive statistics, OLS regression, and the difference-in-difference method to analyze the compensation-performance relationship for the period 2005 to 2012. Our findings show that CEOs in the private sector publicly listed firms are receiving higher remuneration benefits. Our results suggest that firm sales and past compensation are the most important determinants of CEO cash-based as well as total compensation. Firms with a larger board size and the presence of a formal remuneration committee are likely to provide higher cash compensation than those without.

In order to avoid the real economy development lags behind and the deterioration of ecological problems in the process of traditional urbanization, China has been promoting city-industry deep integration, but the connection between city-industry integration and green economic growth, especially the spatial effect, has not been systematically explained. Based on the panel data from 2007 to 2018, this paper constructs an evaluation index system and uses the SEEA method to measure city-industry integration (CII) level and green economy growth (GEG) level. Then, by employing spatial Durbin model and intermediary effect model, it further systematically investigates the spatial impact of CII on GEG and the potential mechanism. The study found that: (1) On the whole, CII shows “slow-steady integration” trend, but regional heterogeneity was obvious and accompanied by “slow gap expansion”. GEG experienced “sharp increase” with “polarization” characteristic. (2) CII can directly promote regional GEG (with a marginal effect of 0.689), more effectively than traditional urbanization, and CII has obvious spatial spillover effects on GEG in both “local effect” and “neighboring effect”. (3) Interestingly, technological innovation and consumption structure upgrading are significant mediating mechanisms. (4) The direct positive effect of CII shows the regional imbalance characteristic. Finally, the corresponding policy implications are put forward.

Based on the income poverty level differences and multi-dimensional poverty perspective in China, this paper compares the performance of education poverty alleviation, employment poverty alleviation, and industry poverty alleviation. The hypothesis was tested by quantile regression and ordered probit model. The results show that: in the short term, the effect of poverty alleviation through education is not significant; however, the effect of poverty alleviation through employment and industry is significant, increasing the income of poor households to a certain extent. The effect of poverty alleviation through employment is high. In the long term, the effect of poverty alleviation through industry is good. For the deep poor households, the effect of poverty alleviation through employment is more significant in the short term. For the marginal poor, only industry poverty alleviation has a significant effect on poverty alleviation. Education poverty alleviation and industry poverty alleviation are conducive to improving multi-dimensional poverty. In the alleviation of multi-dimensional poverty, employment poverty alleviation and education poverty alleviation have a certain synergy.

The policy of ethnic equality and solidarity aims to narrow the ethnic gap and develop harmoniously. At the level of higher education, it should promote the equity of ethnic education. This paper uses the administrative data of undergraduate students from 2008 to 2015 in a liberal arts university in southwest China to study the differences, causes and dynamic trends in the scores of college students from different nationalities. The results show that compared with Han students, the average GPA of ethnic minority students is 0.13 points lower (equivalent to 0.23 and 0.3 standard deviations of the scores of ethnic minority and Han students), the fourth grade scores are 0.28 standard deviations lower, and 7.3% lower. This difference is more significant in the western region, especially in Xinjiang, Yunnan, Hubei and other provinces inhabited by ethnic minorities; Kazak and uygur are the nationalities with the biggest gap with han students; The difference between girls is more significant than that between boys. The "peer effect" and cultural distance between roommates are important reasons for this difference. Further analysis shows that although the ethnic differences in academic performance are gradually expanding, the growth rate tends to converge. The above conclusions are helpful to clarify the object and time of making national higher education policy, and also have important reference significance for primary and secondary education.

On the basis of the background of the global green development wave, this paper studies the mechanism between ecological value transformation and urban-rural common prosperity as well as selects 24 data indicators in relation to ecological value transformation, i.e., green development level from 2008 to 2017, calculate the comprehensive score of China's green development level by entropy method, measures the gap between the rich and the poor between urban and rural areas by urban-rural income ratio, and using correlation analysis, she examines the relationship between green development level and the urban-rural income ratio. Moreover, through empirical analysis, there is a significant negative correlation between the level of green development and the ratio of urban to rural income, according to the findings. The improvement of the level of green development will assist narrow the income gap between urban and rural residents as well as achieve common prosperity.

The objective of this study is to explore the link between the financial sector, macroeconomic fluctuations, and sustainable energy production in South Asia. It evaluates existing research, identifies gaps, and suggests future directions. The study emphasizes the need to understand how economic activities influence the environment and how environmental factors impact economic and financial outcomes. It also examines financial market responses to understand the manifestation of economic and environmental factors, using data from Bangladesh, India, Pakistan, and Sri Lanka spanning 1987 to 2022. The results show that investment in green energy is essential for developing countries. The study suggests that the relationship between the region's stock market, GDP, carbon emissions, and green energy is complex, with a negative response to domestic credit indicating potential obstacles to investment, such as policy barriers or insufficient incentives. Mixed responses highlight the need for credit directed towards sustainable projects. Variations in responses across economic indicators may indicate policy challenges or structural issues, necessitating a reassessment of government policies to incentivize sustainable investments and promote green technology adoption. These results imply that policymakers should precisely assess the environmental ramifications of economic growth and stock market activities. This presents an opportunity to craft policies that guide investments toward cleaner technologies and industries, aligning economic growth with sustainable practices. Policymakers and financial institutions should explore ways to incentivize green energy investments and promote sustainable economic growth.

This study investigates the impact of inventor CEOs on firm performance using a manually collected database of firms' inventors. Our findings reveal that, on average, firms with inventor CEOs experience a one- and two-percentage-point increase in ROA and ROE, respectively, compared to firms with noninventor CEOs. To address potential endogeneity issues, we employ turnover analysis, an instrumental variable approach, and propensity score matching. The estimation results suggest that inventor CEOs significantly enhance firm performance by fostering innovation and total factor productivity. This research contributes novel evidence on the relationship between inventor CEOs and firm performance.

The construction and optimization of a portfolio is a complex process that has been a historically active research area in finance. For portfolios with highly correlated assets, the performance of traditional risk-based asset allocations methods such as the mean-variance (MV) model is limited when numerous assets are correlated. A novel clustering-based asset allocation method, called Hierarchical Risk Parity (HRP), provides an opportunity to mitigate these limitations in portfolio construction. HRP utilizes the hierarchical relationships between the covariance of assets in a portfolio to determine weight distributions, eliminating the need for the inversion of the covariance matrix that is required by most traditional risk-based asset allocation methods. This research examines the viability of Hierarchical Risk Parity (HRP) method in portfolio construction of a US equity portfolio and compares the performances of HRP to traditional asset allocation methods exemplified by the mean-variance (MV) method. The results of this research show that the performance of the HRP method is comparable to the performance of the MV method. Given these findings, HRP provides an advantageous approach for portfolio construction in practical scenarios where correlated assets are present in the portfolios.

Peripheral nerve injury is a serious and disabling disease prevalent in the world. It caused by trauma is often accompanied with soft tissue injuries, fractures, infections, etc., and can cause permanent damage. The treatment methods of peripheral nerve injury mainly include traditional microsurgical repair, neurotrophic drug treatment, as well as cuttingedge nerve conduit treatment, nerve stimulation, cell therapy, etc. However, more than 30% of patients with peripheral nerve injury still have poor recovery, including partial loss or complete loss of motor and/or sensory function, muscle atrophy，chronic pain and severe disability, among can lead to permanent disease. Phenolic compounds are secondary metabolites which is the most abundant in plants, consisting of an aromatic ring and one or more hydroxyl substituents, the main groups including flavonoids, phenolic acids, tannins, stilbene and lignans. A lot of studies have shown that natural phenolic compounds have various properties, such as antioxidant, anti-infective, anticancer, anti-inflammatory, etc., and have broad applications in the prevention of heart disease, cancer, diabetes, oxidative stress-related diseases, and neuroprotection prospect. This review discusses the potential applications and molecular mechanisms of natural phenolic compounds its polymer derivatives in the treatment of peripheral nerve injury.

Economic globalization has intensified economic volatility around the world, and the importance of economic resilience has become increasingly prominent in the face of rising uncertainty due to frequent domestic and foreign shocks. Based on provincial panel data in China from 2008-2019, a comprehensive indicator system is constructed to measure regional economic resilience (RER), and the impact of financial driver (FD) on RER is explored from staged, pathway and non-linear perspectives. The main findings are as follows. (1) Both national and regional levels of FD and RER show an upward trend, and the impact of FD on RER has an “inverted-U” shape: as the capacity of FD increases, its impact on regional economic resilience shifts from promoting to inhibiting. The RER has significant spatial agglomeration characteristic. (2) Interestingly, staged analysis shows FD can significantly promote RER only when it is in the “recovery stage”. (3) The pathway analysis of its effect on regional economic resilience shows the following characteristics: financial scale > financial efficiency > financial deepening. (4) From different regions, there are significant differences in the effect of FD on the promotion of regional economic resilience: central region > western region > eastern region. Finally, the corresponding suggestions were provided.

We examine the impact of environmental provisions in regional trade agreements (RTAs) on the environmentally harmful exports. Results show that environmental clauses in RTAs help reduce “dirty” exports, whereas RTA depth promotes exports. The exporting country may divert its polluting exports to its trading partner if it faces more environmental provisions with other countries.

This study compares return and volatility performance of exchange-traded funds (ETFs) with high-ESG (Environment, Social, and Governance) rating vs. low-ESG rating. The paper also examines time-series data predictability by identifying their positive dependence and volatility asymmetry properties, and examines the performance of two combinations of short-memory models i.e., autoregressive moving average and exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); autoregressive moving average and asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH) and two long-memory models, autoregressive moving average and fractionally integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIGARCH); and autoregressive fractionally-integrated moving average and asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-APARCH). The study found that low-ESG rating ETFs on average have slightly significant higher returns and also lower volatility compared to their high-ESG rating counterparts. Evidence of asymmetric volatility properties are also present on both high-ESG and low-ESG rating ETFs returns. The study also observed that for both high-ESG and low-ESG rating ETFs denote a stationarity, but non-invertible process in their returns. Results can provide fresh understanding in the topic of leverage effects and volatility that can open future research channels to academicians.

Banks operating within a free economic environment and with constructive regulatory frameworks can function with enhanced efficiency, augmenting their profitability. This study aimed to examine the influence of economic freedom and financial restrictions on banks' profitability within the Organization of Islamic Cooperation member nations. The study used a sample of 1453 banks, collecting panel data spanning 13 years. The System-GMM methodology was justified based on the enduring characteristics of the data and the profitability metrics. The dependent variables, namely the Net Income Margin, Return on Average Assets, and Return on Average Equity were individually examined. The research findings indicate that most economic freedom indicators, except for investment freedom, harm bank profitability. The influence of the rule of law on profitability indicators is mostly adverse, although regulatory quality within the financial system has a comparatively favorable effect on profitability. Furthermore, bank-specific performance indicators had a negative impact on profitability, except for bank size. Moreover, country-specific variables substantially impact banks' profitability, including inflation, tax, and interest rates. The presence of Islamic banking has been shown to substantially impact the profitability performance of banks within the Organization of Islamic Cooperation. OIC banks' profitability is adversely impacted by the ongoing health crises, including the Covid-19 pandemic.

Understanding the economic trends and demographic dynamics of a country is crucial for policymakers and researchers to formulate effective strategies and policies. This study aims to examine the GDP trends and aging index dynamics in Portugal from 2011 to 2021, with a focus on regional disparities and their implications for demographic challenges. The findings highlight the relationship between regional GDP and the aging index, indicating that regions with higher GDP values tend to have a relatively younger population, while regions with lower GDP values have a relatively older population. The study contributes to the existing literature on population aging by providing insights into the demographic, economic, and social implications of an aging society. It provides valuable insights into the demographic, economic, and social implications of population aging in Portugal. The findings contribute to the existing literature and can inform policymakers and stakeholders in developing targeted strategies and policies to address the specific challenges faced by each region.

In this paper, a portfolio analysis is carried out using the Sharpe ratio to identify the optimal market portfolio. The measure of investment performance with a Sharpe ratio is compared to results obtained with bootstrapped resamples of the Sharpe ratio. The results indicate that the choice of the market portfolio is highly affected by the uncertainty regarding the estimation of the expected returns and the variance-covariance matrix between the returns, that is, the estimation risk associated with these parameters.

The stages of liver fibrosis can reflect the severity of chronic viral hepatitis and the probability of liver cancer. Biopsy is still regarded as the reference for staging fibrosis, but the invasive method is not suitable for first-line screening. In recent years, noninvasive methods for detecting virus-driven liver fibrosis have been developed rapidly, which mainly include biological (serum biomarkers indexes) and physical (imaging assessment of liver stiffness) strategies. In this review, we introduce these noninvasive methods, enumerate their diagnosis performances and discuss the role of ferroptosis. At last, we propose directions for future researches.

The purpose of the study is to determine the relationships between the factors, attitude towards food consumption and green purchase intention in organic food markets of Pakistan. A Total of 301 sample data was analyzed by SPSS and PLS-SEM. These statistical techniques were used to test the hypotheses. The study was supported the theories include theory of Reasoned Action, Planned Behavior, and expectancy-value model of attitude theory. It also enhances the intention of purchase to buy organic food. The study found that environment, consciousness of health, and safeties of food have significantly direct and indirect influence on Intention of purchase while, taste of food, and exposure of media only have significantly indirect effect on Intention of purchase. The study recommended that retailers should advertise organic food via social media or channels as media persuasively increase the chances to grab the consumer attention to buy the product.