This study focuses on the impact of trade in environmental goods (green trade) on the environment. We found that green trade can decrease pollution levels by exploiting a panel of 277 Chinese cities from 2004 to 2013 and using the instrumental variable (IV) strategy. However, total trade openness is far less favorable to the environment. We also found that both green imports and exports are conducive to the Chinese environment, while ordinary green trade performs better than green processing trade. Nevertheless, the effects of green trade are restricted by a city's purchasing power and absorptive capacity, as well as the classifications of environmental goods. Furthermore, green trade mainly promotes local green technological progress to benefit the environment.

This paper analyses the influence of Information and Communication Technologies (ICT) on organizational change in SMEs that have yet to be internationalized. A Likert scale questionnaire was applied to 78 SMEs in the change process. The significance level was sought in an ANOVA (analysis of variance) by linking variables concerning ICT, on the one hand, and the effects of ICT on organizational change, on the other hand, as well as specific issues that may promote or hinder the implementation of organizational change. The findings of this study show that both the frequency and the intensity of the ICT backlog were the most influential elements in change management. The main conclusion is that backwardness can be advantageous in specific economic contexts, mainly when the SMEs are oriented toward a part of the population with less experience in the use of technologies or the company is in a country where ICT consumption is not maximized because ICT has exceeded the needs and expectations of the population.

Based on provincial panel data from 1998-2018, this paper estimates research and development (R&D) factors, and a stochastic frontier analysis (SFA) model is constructed to examine the effects of R&D factors on regional total factor productivity (TFP). The results show that both R&D capital stock and R&D personnel can significantly promote regional TFP, but the productivity-enhancing effect of R&D factors is different between regions. Specifically, R&D capital and R&D personnel can promote TFP in eastern and central provinces, and the promotion effect is not significant in western provinces. In addition, compared with investment-driven regions, innovation-driven regions are more likely to enhance TFP by R&D factors.

Breast cancer, as a malignant tumor with easy metastasis and poor prognosis, threatens the health of women around the world. Increasing studies have shown that the Bcl-2 family of apoptosis-related proteins is often expressed abnormally in breast cancer. The Bcl-2 homology 3 (BH3) mimetic peptide can bind and neutralize Bcl-2, preventing its binding to the apoptosis "effector" proteins Bak and Bax, thereby promoting the apoptosis process. However, there is a lack of effective intracellular delivery system for BH3 to exert its biological activity. Therefore, this study utilized an activatable supercharged polypeptide (ASCP) tumor-targeted delivery platform based on pH and protease response to achieve the targeted release of BH3 at the tumor site. Ultimately, intracellular delivery of BH3 was achieved and induced apoptosis of breast tumor cells, preventing the development of breast cancer.

In this paper, we develop a model in which a monopolistic firm manufactures and sells a digital product, by incorporating digital rights management (DRM), quality degradation of pirated products, and government copyright enforcement into the consumer’s utility function. We determine the monopolist’s optimal pricing strategies and the appropriate DRM protection level through mathematical deduction. Our results show that when the government copyright enforcement is moderate and the quality of pirated products is relatively high, implementing a DRM system is optimal for the monopolist. However, in most other cases, DRM-free is better for the monopolist. This result may explain why DRM is not very popular in some industries. Our results suggest that choosing the right price, focusing on content innovation, and weakening DRM protection may be a better strategy for firms now. The results also indicate that DRM-free may be more prominent in the digital music industry than in the software and video games industries.

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.

The digital economy industry plays a transformative role in reshaping the global production networks, the local division of production, and the integration and innovation of business forms. However, to what extent the industry enables the high-quality development and upgrading of urban economies is unclear. Based on the census data of digital economy enterprises in Hangzhou in 2008, 2013 and 2018, this paper verifies the characteristics of the digital economy industry and its enabling mechanism for high-quality urban economic development. It is found that: firstly, the digital economy industry has three main forms for the economy, namely, the sharing, scale and scope economy. Secondly, the industry has four major mechanisms to improve the quality of urban economies. That is, it can restructure the global industrial division of labor and value chains, promote the transformation of scale economy from the supply side to the demand side, enable the softening and servitization of industrial structure, and generate the scale of economies. This paper thus contributes to understanding the evolution of enterprise organizational structure and industrial competitiveness and the endogenous technological change under the digital economy.

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.

To make an assessment of ratemaking proposals, this article proposes that regulators should consider applying a logical decision-making process, such as multi-criteria decision analysis (MCDA), that selects or modifies those rate mechanisms that come closest to achieving the public interest, as defined by regulators. MCDA seems like an fitting tool to improve regulatory decisions by making more explicit the relationship between different rate mechanisms and the public interest. This article provides a simplified version of MCDA to demonstrate how regulators can apply this tool to evaluate new rate mechanisms in terms of the public interest. As far as the author knows, the MCDA methodology applied to utility ratemaking has not appeared in the literature. While regulators may not want to or lack the resources to execute all the steps presented in this article, MCDA can provide direction to regulators in evaluating different rate mechanisms and ultimately reaching decisions that are more rational and aligned with the public interest. After all, evaluating rate mechanisms is one of the major functions of utility regulators. Doing it wrongly can have a consequential effect on society’s welfare.

With the continuous advancement of technological revolution and industrial transformation, digital finance supported by big data and artificial intelligence has become an important engine for promoting carbon neutrality. We measured the industrial structure transformation index (ISU) of 30 provinces in China, and discussed the spatial spillover effect and transmission mechanism between digital finance and ISU using the spatial Durbin model. The research results demonstrate that the digital finance development can significantly improve the local ISU. Interestingly, the impact of digital finance on the ISU of adjacent areas has a significantly negative spatial spillover effect, which still exists under the different spatial weight matrix. Digital finance can improve ISU by improving green technology innovation, upgrading industrial structure, and alleviating capital allocation. We also found that the higher degree of marketization and environmental regulation can increase the positive influences of digital finance on ISU. This research proves the effectiveness of the digital finance in improving energy efficiency, and it encourages policymakers around the world to rely on digital finance to promote ecological governance and achieve high-quality economic development.

Based on fully considering the actual differences in statistical indicators between Hong Kong, Macao, and the nine cities in the Pearl River Delta, this paper constructs a high-quality urban development evaluation system that is suitable for the actual development of the Guangdong-Hong Kong-Macao Greater Bay Area. The Entropy Weighted TOPSIS two-step method is used to process data and systematically investigate the changes in the high-quality development index of 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2013 to 2020. The study found that the Guangdong-Hong Kong-Macao Greater Bay Area has thoroughly implemented the new development concept, and the level of high-quality development has continued to improve. The profound integration effect of the Guangdong-Hong Kong-Macao Greater Bay Area has appeared, and it has promoted the high-quality development of the region in coordination. The construction of the Guangdong-Hong Kong-Macao Greater Bay Area has strongly promoted the great practice of "one country, two systems" to achieve stability and prosperity.

This research investigates the determinants of women's empowerment within households in a developing country. The investigation specifically focuses on the impact of employment and fertility, considering constraints imposed by family rules that play a pivotal role in shaping women's empowerment. The theoretical framework outlined in this study posits a simplistic model demonstrating that, within the prevailing family structure and household composition, earned income and fertility may bear significant relevance. Utilizing data extracted from the Pakistan Social and Living Standards Measurement Survey, we engage in estimating the level of female empowerment, operationalized as the extent of female authority over household expenditures. Notably, our empirical approach accounts for the endogeneity of employment and fertility through a two-stage estimation process. This involves leveraging information on family rules—representative of a family's cultural norms—pertaining to work and childbearing. Our empirical findings affirm the viability of family-specific rules as instruments to estimate and subsequently predict employment and fertility. Importantly, the evidence gleaned underscores the critical role of selecting valid threat options in theoretical analyses of women's empowerment.

This study employs empirical analysis using an econometric model that examines the interdependence among environmental degradation, exports, and economic development with energy use. It also provides an environmental Kuznets curve (EKC) for selected South Asian economies utilizing time-series data. The findings reveal a long-term, stable equilibrium link between energy demand and pollution. There exists a positive relationship between structural factors and pollution. Moreover, this study constructs a model of exports and pollution from an interdependent perspective. The three perspectives are tested: the scale and structure of energy consumption considering the twin constraints of export-trade and pollution, and the scale of pollution in export-trade constraint. These results show that the increase in energy use leads to higher CO2 emissions amidst export volume. However, in the presence of income, the scale of effect lowers a little. The analysis also supports the presence of Kuznets curve for south-Asian economies. The results imply substantial scope for development in the energy use and pollution structure within South Asia's current export trade process. This development can be attained by regulating energy use and enhancing system efficacy without necessitating changes to the scale effect or structural effect.

The use of cloud computing by firms can be expected to go hand in hand with higher productivity, more innovations, and lower costs, and, therefore, should be positively related to export activities. Empirical evidence on the link between cloud computing and exports, however, is missing. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union taken from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate this link. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), we find that firms which use cloud computing do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated cloud computing premium for extensive margins of exports is statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of this premium can be considered to be large. Extensive margins of exports and the use of cloud computing are positively related.

This paper evaluates the use of macro-level insurance to finance post-disaster recovery and reinstatement by investigating the case of the National Disaster Insurance policy implemented by Sri Lanka. The national scheme provided cover for all properties in the country against hazards such as flooding and provided compensation for those affected. Analysis of secondary data obtained from the organisations that managed the scheme showed that the scheme has delivered a much higher return compared to the total insurance premium paid, suggesting that the scheme has delivered a net positive benefit compared to the cost of the premium and can be considered a viable option. However, the existing secondary data did not reveal the values of other costs and indirect benefits associated with the scheme to compute a meaningful benefit-to-cost ratio. Further rigorous, evidence-based cost-benefit analysis is required to assess the cost-effectiveness of a scheme of this nature. A cost-benefit analysis approach based on an analytical hierarchy process is proposed as a possible solution to assess the cost-effectiveness of the scheme, which could be used by government organisations as an alternative, where analytical and research resources may be limited, to evaluate a range of disaster recovery financing options using stakeholder opinion.

Even though policy coordination is one of the oldest challenges that governments have to confront, as problems evolve and "New Public Management" concepts emerge, it has become even more essential. The current literature on policy coordination among government agencies, however, shows little regarding the way coordination is managed under centralized political systems. This study, based on the science and technology (S&T) policy documents issued by China's central government agencies between 1978 and 2020, provides a quantitative and dynamic analysis of the coordination of policies in China and presents a comprehensive overview of policy coordination paths and processes in centralized political systems. As a result, it provides a way that contributes to the analytical methods available for quantitatively analyzing policy documents. On the other hand, the key findings of the study show that, first, state council-administered ministries have taken the lead in coordinating policy while other types of organizations have collaborated in more subordinate capacities. Second, national themes that are democratic and driven by demand have been the core concern of coordination activities, such as social development, high-tech industrialization, and rural S&T. Third, policy coordination has evolved continuously and has mostly contributed to interpreting macrostrategies and implementing more specific implementation measures.

Nanomaterials have shown great potential in anti-tumor applications and are currently the focus of research. This review article aims to provide a comprehensive overview of the challenges encountered in oncology treatment and how nanomaterials are being utilized to overcome these obstacles. The authors discuss the limitations of conventional treatments, including limited efficacy, side effects, and toxicity issues. They highlight the importance of early tumour diagnosis and personalized treatment plans, as well as the need for innovative therapeutic approaches such as targeted therapy, immunotherapy, and gene therapy. The article primarily focuses on how nanomaterials can be engineered to achieve specific recognition and aggregation within tumour tissues through surface modifications involving targeting molecules such as antibodies, peptides, and receptor ligands. This surface modification technique facilitates improved targeting in the targeting of photodynamic therapy, while minimizing harm to normal tissues. The authors also discuss the potential and future prospects of nanomaterials in tumour therapy, including breakthroughs in their application, biosafety concerns, biocompatibility issues, preparation processes, clinical translation challenges, interdisciplinary cooperation, international exchange, relevant regulations and ethical guidelines. Overall, this review highlights the substantial potential of nanomaterials in oncology treatment, emphasizing the need for careful consideration of safety concerns to ensure their safe and effective application. The authors conclude that strengthening interdisciplinary cooperation and international exchange will contribute to the healthy development of nanomaterials in oncology treatment.

Nanozyme with biomimetic enzyme activity has the advantages of good catalytic performance, high stability, and is not easily affected by temperature. However, the application of tumor microenvironment (TME) in the tumor is limited due to its low catalytic activity. Herein, a multifunctional nanozyme based on CuCoP with multivalent metal ions (Cu+/Cu2+ and Co2+/ Co3+) provides an innovative strategy for constructing acid-responsive cancer therapy. CuCoP has excellent photothermal properties (photothermal conversion efficiency of 66.9%) as well as glutathione (GSH) peroxidase activity and high photo-enhanced peroxidase-like (POD) enzyme activity in weak acid TME. CuCoP can consume the overexpressed GSH, thus alleviating the antioxidant capacity of the tumor, and reduces Cu2+/ Co3+ to Cu+/ Co 2+. Subsequently, the generated Cu+/Co2+ will react with endogenous H2O2 to generate cytotoxic hydroxyl radical (•OH), which have high catalytic efficiency in weakly acidic TME. Crucially, the synergistic effect of PTT and the cascade reaction of bimetallic atoms with GSH and H2O2 can effectively reduce antioxidant capacity, inhibit tumors and trigger effective immune cell death (ICD) process, which caused a strong immune response and inhibit tumor recurrence and metastasis. As a novel bimetallic sulfide nanoenzyme triggered by TME, CuCoP has great research value in cancer therapy.

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.

The long-term low level of residents' property income is not only detrimental to the wealth accumulation of farmers, but also aggravates the urban-rural income imbalance. This paper uses an empirical approach to explore the mechanism of digital literacy's impact on farm households' property income. The main findings of this paper are as follows: (1) Digital literacy and its sub-dimensions can significantly increase the level of farmers' property income, with the strongest contribution of digital information acquisition literacy. (2) Digital literacy has a greater boosting effect on the property income of farm households with low education level heads, low physical capital households, and villages with better economic development. (3) Digital literacy increases the property income of farm households mainly through expanding social capital and improving risk preferences. The innovation of this paper is to construct a digital literacy evaluation index system based on a micro perspective that fits the behavioral characteristics of farmers, and reveal the impact and mechanism of digital literacy and its sub-dimensions on farmers' property income. This study expands the theoretical research related to digital literacy and farmers' property income, and provides a scientific basis for the choice of strategies to enhance the digital literacy of the majority of farmers, which is important for promoting wealth accumulation of farmers and achieving common prosperity.