Cardiovascular disease is still a disease with high incidence rate and mortality. Although advanced technology continues to increase our understanding of cardiovascular disease, its diagnosis and treatment still have limitations. As an emerging interdisciplinary method, nanotechnology has shown enormous clinical application potential. Nanomaterials have unique physical and chemical properties, which help to improve the sensitivity and specificity of biosensor technology and molecular imaging technology in the diagnosis of cardiovascular diseases. This paper first summarizes the versatility of nanomaterials, the physicochemical adjustability of biomolecular engineering, the design strategy of nanoparticles in cardio cerebral Vascular disease, the application of nanomaterials in the diagnosis and treatment of common cardiovascular diseases, and the use of nanomaterials can significantly improve the diagnostic sensitivity, specificity and therapeutic effect. Subsequently, the article summarized various nanomaterials. Finally, the article demonstrated the potential of the antioxidant/anti-inflammatory and photoelectric/photothermal properties of nanomaterials to be directly applied to the treatment of cardiovascular diseases.

Investment funds are increasingly focusing on ESG issues, seeking to contribute to improving environmental, social, and governance concerns. ESG-focused investing involves promoting good ESG performance and may result in a decrease in expected financial returns. This may lead to a conflict between solely profit-focused shareholders and ESG-focused investors, who may respond accordingly. As such, a firm's ESG commitment may trigger several events that can affect the stock price. A firm's ESG commitment may increase its stock price; however, the end of such commitment may also positively affect the stock price. Hedge funds may consider this in their activism which may reshape the way hedge funds target firms and influence their actions accordingly.

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.

Despite the advantages of nanoscale drug delivery systems, traditional nanoparticles often encounter challenges such as detection and elimination by the immune system. To circumvent these limitations, scientists have created biomimetic nanoparticles that extend circulation time, decrease clearance rates, and optimize drug delivery. The integration of cell membranes onto nanoparticle surfaces yields Cell Membrane-coated Nanoparticles (CMNPs) that exhibit behavior akin to actual cells while offering superior structural robustness and stability. A variety of cell membranes, including those of red blood cells, white blood cells, and cancer cells, lend unique properties and targeting capabilities to CMNPs. This review outlines the diagnostic and therapeutic roles of CMNP-based drug delivery systems in oncology and contemplates their possible clinical impact.

This study explores the cause and effect of endogenous risk aversion in land pricing, where state intervention through taxation remains a general practice. Using a consumption-based asset pricing model incorporating taxation, it is shown that high taxation, due to the indexation effect, supporting land prices and reducing individuals' risk expectations, could lead to an endogenous decrease in risk aversion, which could result in market dysfunction because risk aversion plays a key role in the market mechanism. China, with its wholly state-owned land and the general use of land sales to cover financial deficits, is a typical case for empirical tests. The tests confirm that there, the rise in land prices was driven by the increase in reserve prices set by local governments, a strong means of taxation, and not by the market, indicating the endogenous decrease in risk aversion.

Cryptocurrencies have gained popularity over the past five to six years. Most recently, events like the FTX bankruptcy fueled the interest in regulation. Moreover, it is possible that the FTX event disrupting the cryptocurrency market was a factor in Silicon Valley Bank's failure. While several countries consider regulation, from soft regulation, like Japan, to more rigid standards, like the total ban in China, we study the effect of other news or events on cryptocurrency prices. This paper looks at historical closing prices for Bitcoin, the largest of the cryptocurrencies, and how prices react to various events. Then we focus on modeling the time series considering an 'event,' China's ban on cryptocurrency exchanges, using intervention analysis. We find that intervention analysis provides a reliable approach to quantifying the impact regulation may have on cryptocurrency pricing.

This paper intends to analyze efficiency, in its weak form, in the stock markets of Austria (ATX), Poland (WIG), the Czech Republic (PX Prague), Hungary (BUX), Croatia (CROBEX), Serbia (BELEX 15), Romania (BET), and Slovenia (SBI TOP), from February 16, 2018, to February 15, 2023. To achieve the research aim, we intend to answer the following research question: i) Have events in 2020 and 2022 heightened the persistence of Central European stock markets? Results suggest that persistence in returns has increased significantly during the first wave of Covid-19 and the Russian invasion in the year 2023, but we also saw that most stock markets already exhibit long memories, implying that the research question has been partially validated. This research can provide valuable insights to investors, policymakers, and others interested in financial risk management.

This paper evaluates the treatment effect of high-speed rail (HSR) operation on city consumption using the dataset of Chinese cities from 2003 to 2019. Firstly, the applicability of observations is discussed; secondly, observations with no appropriate contrast samples are dropped for more precise empirical results. Then, propensity score matching (PSM) is implied to have the database much more balanced and suitable for the difference-in-difference (DID) framework, that is, the PSM-DID approach. The main results find a novel phenomenon of Simpson's paradox regarding the HSR-consumption nexus, which indicates that even though we can observe the positive effect on the whole, the results argue negative relationships between HSR and consumption within subclass cities. In addition, a dose-response assessment (DR) and some other checks have been proposed to demonstrate robust estimation results.

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.

We employ the joint production decomposition model to conduct a full decomposition of CO2 emission among 36 industrial sectors in China from 1998 to 2011, under the framework of growth accounting. The results show that: (1) the average CO2 emission increases at an annual rate of 3.01%, and production technology progression is the main driving force, while the transformation toward clean production effectively curb the rapid growth of CO2 emissions; (2) the effect of technology changes on CO2 emission is larger during the "10th Five-Year Plan" compared with the "11th Five-Year Plan", which makes the annual growth rate of CO2 emission during the "11th Five-Year Plan" 1% lower than its counterpart; This study has important theoretical and practical significance for understanding the driving factors of CO2 emission and the corresponding emission reduction measures.

 In the past, researchers investigated the immune response acting against mycobacterial antigens in tuberculosis (TB). Several ELISA tests have been conducted for the diagnosis of tuberculosis. Other researchers manipulated 16 kDa antigen from Mycobacterium Tuberculosis to develop a tuberculosis diagnostic test while some others studied the subspecies of M. tuberculosis. In the present study, we explored the possibilities of detecting 16 kDa protein derived from M. tuberculosis, on an interdigitated electrode (IDE). Measurements with Electrochemical impedance spectroscopy and current-volt systems were demonstrated using antibody as the probe.  Further, the involvement of gold nanoparticle for the signal-enhancement and high-performance are evidenced. The specificity in the serum containing samples is used to show the clinical relevancy. 16 kDa antigen used in this experiment is highly reliable for TB diagnosis as it largely expresses and can be implemented in other sensing system.

Transition metal sulfides/transition metal phosphides (TMS/TMP) has shown great potential in cancer diagnosis and treatment due to its unique structural, optical, acoustic and magnetic properties. TMS/TMP can be formed from sulfur/phosphorus source and metal into binary compounds, or from the interaction of hydrogen sulfide (or hydrogen sulfuric acid) with metal oxides or hydroxides. It has a series of unique properties, such as high conductivity, metalloid properties, a variety of valence states and adjustable structure and so on. These advantages make it have great potential in biomedical applications, such as diagnostic imaging, disease therapy and drug/gene delivery. This review presents the latest research progress of TMS/TMP on tumor imaging, diagnosis and treatment. Here, we first illustrate the synthesis approaches and surface modification of TMS/TMP. Then, its emerging applications in tumor diagnosis and therapy are highlighted. Moreover, the challenges of TMS/TMP-mediated diagnosis/treat are provided and the prospective for this field are discussed.

With the improvement of people's living standards and the increasing emphasis on health, new and higher demands are also placed on the medical industry. The diagnosis and treatment methods combining artificial intelligence and medicine are bound to receive more and more attention and promotion. At present, drug design is stepping into the era of artificial intelligence, and academia and industry are actively applying artificial intelligence technology to all aspects of drug research and development, including drug screening, molecular characterization, drug activity and druggability optimization, chemical reaction design, etc. Relying on the big data information of millions of patients, the artificial intelligence system can quickly and accurately mine and screen out suitable drugs. Through computer simulations, artificial intelligence can make predictions about drug activity, safety, and side effects, and find the best drug that matches the disease. This technology will shorten the drug development cycle, reduce the cost of new drugs and improve the success rate of new drug development.

Innovation has received a great attention in the creative industries literature. We propose in this study a bibliometric method to examine the literature on innovation in creative industries (ICI). A file of 656 manuscripts published on ICI between 1998 and 2022 was retrieved from the Web of Science Core Collection for analysis. The results highlight the evolution of study volume, authors, affiliated institutions and countries, author networks, keyword co-occurrences, and keyword networks. The study also includes a thematic map that highlights four types of research: driving themes (e.g., digital technology, cultural innovation, performing arts, product innovation, innovation management); core and cross-cutting themes (e.g., creativity, digitization, technology, copyright); emerging themes (e.g., gender, artificial intelligence, sustainability); and specialized and peripheral themes (e.g., gender, blockchain, digital music). We finally conclude by proposing future perspectives and a research agenda in this area.

The COVID-19 pandemic has changed the everyday ways of life across the world. The objective of this study is to understand the impacts of nationwide lockdown restrictions on female workforce of New Zealand. To conduct this study three subsets were selected: working mothers, essential workers and women in high-risk industries. New Zealand has a gender segregated workforce, and more women on the frontline as essential workers who faced risks from COVID-19. A quantitative approach based on secondary data published by the Government of New Zealand was employed in this study. The analysis was carried out under three themes: family wellbeing, essential workers and women in high-risk industries. All the themes point to the fact that the working women of New Zealand indeed have been critically impacted compared with working men.

In this paper I will show that budget deficit (or fiscal deficit) is necessary to achieve full employment under constant prices or inflation, using a model of endogenous growth in which consumers hold money for the reason of liquidity and live forever. Budget deficit need not be offset by future budget surpluses. I consider the continuous time case by taking the limit of the discrete time case when the time interval approaches zero. A continuous time dynamic model seems to be more general than a discrete time model. When the actual budget deficit is greater (smaller) than the value which is necessary and sufficient for full employment under constant prices, an inflation (a recession) occurs. The main argument of this paper is that a growing economy requires the continuation of budget deficit, and that we should not think of paying off the resulting government debt with taxes.

This paper explores how digital technology reduces trade costs using bilateral trade data from RCEP member countries and a panel fixed effects model. The findings show that digital technology significantly lowers trade costs, a conclusion that holds even after accounting for lag effects and various robustness checks. The impact of digital technology on trade costs follows an inverted U-shape: the effect is most significant in the current period, especially with a one-period lag, and diminishes over time. Larger economies and higher export levels strengthen this negative impact due to their reliance on exports and continuous improvements in domestic digital technology. The study recommends investing in digital infrastructure, formulating reasonable internet access policies, supporting digital skills development, and enhancing digital connectivity to bridge the digital divide, thereby promoting trade facilitation and efficiency.

This study empirically examines the influence of corporate financialization on trade credit financing, focusing on non-financial companies listed in China's A-share market from 2010 to 2022. The results indicate that as corporate financialization increases, companies will obtain less trade credit financing. Further incorporating moderating factors like market position and financing constraints, we find that a higher market position effectively mitigates the negative impact of corporate financialization on trade credit financing, whereas higher financing constraints exacerbate the adverse effects of corporate financialization on trade credit financing. Additional analysis shows that corporate financialization negatively affects trade credit financing by crowding out main business performance and increasing operational risks. Moreover, corporate financialization more strongly inhibits trade credit financing in state-owned companies.

We study analytically the conflict of goals between stabilizing economic activity and public debt sustainability, for the fiscal authorities. In the short run, an active and expansionary fiscal policy, increasing public investment or reducing the labor taxation rate, is growth enhancing. However, as these short term fiscal policies also decrease government revenue and increase the public debt, budgetary and fiscal multipliers are reduced in the long run. In the framework of a potential ZLB constraint for monetary policy, an expansionary fiscal policy is thus appropriate only if long term labor and consumption taxation rates are small, and if the share of public expenditure in GDP is high. On the contrary, fiscal policy should be contractionary, in order to insure the sustainability of the long term public debt, if long term labor and consumption taxation rates are high. A contractionary fiscal policy is then also all the more appropriate as the sensitivity of government expenditure to the public debt is high, and as the labor share in the production function is high.

Environmental degradation is becoming a fundamental issue as it is directly associated with human lives and environmental sustainability. This research particularly highlights the significance of green transportation taxes in achieving environmental sustainability due to limited available literature considering the environmental sustainability and green transportation taxes nexus. By employing the newly developed QARDL approach, this study is unfolding the linkages of green transportation taxes on transport-based CO2 emissions for Chinese economy spanning 1992 to 2020. The results infer that green transportation taxes to enhance environmental sustainability in the long-run for the highest quantiles, i.e., 0.70 to 0.95. Though, green transportation taxes enhance environmental sustainability in all quantiles in the short-run. Based on these results, the study suggests that the Chinese government and policymakers should increase green transportation taxes that help in combating CO2 emissions, which ultimately enhances environmental sustainability.