The rise of privately issued digital currencies, which primarily serve as alternative investment assets poses a challenge to the traditional financial instruments traded in the financial market. This study examines the dynamic relationship between the major privately issued digital currency (Bitcoin) and two financial market securities in Nigeria. The paper employed Vector Autoregressive (VAR) model and presents three relevant findings. First, the impulse response function indicates the absence of a significant response of the Nigerian financial market to shocks emanating from the Bitcoin market, implying lower connectedness between the two markets. Secondly, the outcome of the variance decomposition reveals a lower contribution of Bitcoin to changes in stock prices and treasury bills, however, stock prices and treasury bills contributed higher impact to each other compared to the contribution of Bitcoin. Thirdly, a weak bi-directional causality between the Bitcoin and treasury bills was observed and a uni-directional causality running from treasury bills and stocks, implying the existence of portfolio rebalancing from the fixed income to the equities market. Despite the weak connection between digital currency and the financial market, the paper recommends that the Central Bank of Nigeria and the Securities and Exchange Commission should maintain monitoring the development of crypto exchanges and continue reviewing the existing policy restricting cryptocurrency transactions through banks to avoid its unsavoury effects.

Liquidity and its associated issues are one of dominant strands in the market microstructure. In this study, microblogging-based behavioral perspective on economic unrest is linked to the market liquidity. The concept of liquidity is examined in terms of price dispersion relative to the quantity traded. The analysis contains the quantification of multiple linear regression, Gaussian distribution technique, and vector error correction methodology. In the economic stability period, the investor’s mood, either in positive manner or pessimistic context, had an influential role on the price impact volume-based liquidity. Meantime, the probability was higher for occurrence of price impact volume-based liquidity in response to the sentiment indicators. In the economic unrest environments, the positive bias investor’s mood was not vigorous enough to influence the dispersion of asset’s prices and trading quantity. Most importantly, the negative bias investor’s emotion was linked to increase the dispersion of asset’s prices relative to the quantity traded. Investors with a lower amount of trading quantity had declined the liquidity in the market. Additionally, there was a higher probability for occurrence of illiquidity in the pessimistic market periods. However, changes in past sentiment series were not associated with changes in pervious liquidity series, either in short run or long run. The findings may be potentially applicable to manage the behavioral perspective of liquidity risk.

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.

Although docetaxel treatment yields a high survival rate for prostate cancer (PCa), resistance eventually develops in many patients. Understanding the underlying mechanisms of docetaxel resistance is essential for improving treatment strategies. Cytokines, which play a role in cell signaling and immune responses, have been implicated in drug resistance mechanisms. The study revealed that interleukin-8 (IL-8) was consistently overexpressed in both docetaxel-resistant PCa cell lines. Thus, the expression levels of cytokines released from docetaxel-sensitive (PC-3- and DU-145) and resistant (PC-3/R-DU-145/R) PCa cells were compared. IL-8 was found to be commonly expressed in resistant cell lines. This finding led to the hypothesis that IL-8 could play a key role in mediating PCa cell resistance to docetaxel. IL-8 siRNA treatment increased docetaxel sensitivity in both resistant cells. To demonstrate the mechanism of IL-8-related resistance, MDR1 expression was evaluated. After IL-8 siRNA treatment MDR1 expression was reduced in both resistant cells suggesting that IL-8 regulates the docetaxel resistance of PCa cells via modulation of multidrug resistance 1 (MDR1). By expanding the knowledge of the cytokines and their effect mechanisms, novel approaches can be developed for the treatment of docetaxel-resistant prostate cancer. Further investigations into the role of IL-8 in docetaxel resistance could offer valuable insights into the development of effective treatment strategies for PCa patients.

Scientific and technological innovation and human capital savings are important ways to promote the high-quality development of China's economy. On this basis, using the panel data of 30 provinces in China from 2009 to 2017, this paper empathically tests the impact of university research activities on high-quality growth of China's economy, and explores the influence mechanism from two dimensions of talent cultivation and achievement transformation. Based on the spatial perspective, the regional heterogeneity of these influences is analyzed. This paper finds that: First, research and development activities in universities effectively boost the high-quality development of China's economy. Secend, the stimulating effect of university research and development on economic growth. On the one hand, through the talent training function of scientific research activities, it enriches the accumulation of human capital and drives the economic development; On the other hand, constrained by the predicament of scientific research achievement transformation, the stimulating effect of university scientific research activities on economic growth will be limited to a certain extent. Third, there are significant regional differences in the promoting effect of university research activities on high-quality economic development, and this difference may come from the spatial spillover effect of university research activities. This study has important enlightening significance to understand the relationship between university scientific research activities and high- quality economic development.

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.

Entrepreneurs are important actors in economic activities and creators of social wealth. Excellent entrepreneurs contribute their wisdom to the accumulation of social wealth and the promotion of high-quality economic and social development. The business environment is the main manifestation of the soft power of cities and regional economic development, and a better business environment can effectively attract enterprises and promote their sustainable growth. Using data from Chinese A-share listed companies from 2009-2019 as a research sample, the following research conclusions were drawn: (1) A better business environment helps enhance entrepreneurship. (2) A better business environment promotes entrepreneurship by reducing rent-seeking expenses and corporate credit costs. (3) Compared to traditional enterprises, high-tech enterprises are better able to enjoy the benefits brought by business environment optimization and further enhance entrepreneurship. When competition is low, entrepreneurs face lower rent-seeking expenses, which is conducive to stimulating entrepreneurship. The businessenvironment can promote fairness and bring more equal financing opportunities for enterprises, which has a higher impact on entrepreneurship for the group facing higher financing constraints. This study meticulously analyzes the impact ofthebusiness environment on entrepreneurship, providing references for the next steps of optimizing the business environment and enhancing entrepreneurship.

The diplomatic relations between Azerbaijan and Pakistan have undergone significant development since the late 1990s. Despite some studies focusing on diplomatic and political relations, the economic dimension of this partnership has not been systematically covered. In this paper, a robust least squares (RLS) approach is used to model bilateral trade between the two countries and identify statistically significant determinants, including economic, institutional, and cultural factors, after analyzing the main economic and subsectoral trade dynamics of both countries. The results reveal that Azerbaijan's imports from Pakistan are significantly associated with the country's higher income and market size, while Pakistan's elevated exchange rate and trade costs hinder bilateral trade. In addition, Pakistan's rising manufacturing output increases exports to Azerbaijan but decreases imports from Azerbaijan. Among institutional determinants, government effectiveness, the trade freedom index (TFI), and political stability play significant roles in bilateral trade. Lastly, it was found that cultural proximity increases Pakistani exports to Azerbaijan but not imports from Azerbaijan. The analysis also indicates that domestic savings stimulate Pakistani exports. These findings underscore the complex nature of bilateral trade between Azerbaijan and Pakistan and highlight the need for institutional arrangements to harmonize trade flows and boost welfare gains from trade. The results may be of great importance to intergovernmental working groups, domestic policymakers, and businesses.

The present paper empirically examines the validity of the environmental Kuznets curve (EKC) hypothesis, which posits an inverted U-shaped relationship between CO2 emissions and economic growth, in Egypt, India, Mexico, Pakistan, Thailand, and Turkey for the period 1970-2020. The EKC validity is highly debated due to varying results across countries. This study is significant to addresses this controversy by estimating the EKC's robustness while considering the influence of financial development, globalization, and government expenditure. We employ two cointegration techniques, the autoregressive distributed lag (ARDL) and vector error correction model (VECM), also considering potential structural breaks in the data. Out key findings indicate that the EKC hypothesis is supported in India, Pakistan, and Turkey, with carbon emissions eventually declining after reaching a peak. The hypothesis is not supported in Egypt and Thailand, where emissions rise monotonically with economic growth. In Mexico, the results are mixed, with ARDL suggesting a U-shaped relationship and VECM supporting the EKC. From our empirical analysis of the EKC hypothesis, we derive the following policy implications: 1) countries should adopt comprehensive policy strategies that integrate these goals and fully consider the long-term environmental and societal impacts of their decisions; 2) countries should invest heavily in research and development to accelerate the creation of new technologies that can effectively reduce carbon emissions; and 3) countries must actively raise awareness about the environmental repercussions of economic growth.

Since the Industrial Revolution, the emission of carbon dioxide and other greenhouse gases by human production activities has increased year by year, and the greenhouse effect has also increased. A series of problems, such as global warming, melting of the Antarctic continent, sea level rise and frequent occurrence of extreme climate, have attracted the attention of countries all over the world. As a developing country with the fastest economic growth rate, China's rapid economic growth is inseparable from the contribution of manufacturing industry. As an important engine of China's economic development, manufacturing industry inevitably brings environmental problems and a large number of greenhouse gas emissions while promoting rapid economic development. Therefore, manufacturing has become a major area for China to achieve its carbon emission reduction targets. With the "Made in China" to the world, the export trade of manufacturing industry plays a decisive role in China's total export trade and even the global trade. But whether the huge export demands will affect carbon emissions. Through the empirical study on carbon emissions of China's manufacturing export trade, the paper found that the increase of export demand of manufacturing industry will indeed bring a significant increase in carbon emissions, but also affected by some other factors. Finally, it provides reference for the high-quality development and export of China's manufacturing industry under the background of the target of “dual-carbon”.

The dynamic patterns of technology adoption among firms clustered by size are investigated to assess the implications arising from the digital divide. Using data from the “Survey on the Use of Information and Communication Technologies in Enterprises (IUTICE)" dataset for 2003-2022, provided by the Portuguese Institute of Statistics, the research centers on three key variables – internet connectivity, website presence, and computer usage – which are examined across a spectrum of firms’ scales, shedding light on the evolving trends in technology adoption. Employing a combination of descriptive statistical analysis, trend assessment, and cross-sectional comparisons, this research shows noteworthy insights. Interestingly, the adoption rates for all three technology variables exhibit a consistent upward trajectory, indicative of a movement towards digitalization within the business landscape. Smaller firms have demonstrated notable strides, manifesting a reduction in the technology adoption disparity relative to their larger counterparts. The findings underscore the influential roles played by resource constraints and digital competencies in shaping technology adoption trajectories, and their correspondence with the Resource-Based View (RBV) framework underscores the role of organizational resources and capabilities on the digital divide. The ramifications extend beyond individual firms, resonating with the global scholarly discourse and advocating for equitable integration of technology. As firms, irrespective of size, grapple with the challenges posed by the digital era, this study provides deep insights that can guide the formulation of strategies aimed at cultivating an inclusive and technologically empowered business environment.

Financial literacy seems to be more important and focused than ever. Several recent studies have found that Portugal is at bottom of the table compared to the Eurozone countries regarding financial literacy. As it’s a key factor in the development of a country, it appears to be crucial to understand what people know about financial matters when they complete compulsory schooling. With a sample of 296 Portuguese students who enrolled in the polytechnic higher education system for the first time, we studied if they understand simple concepts related to financial issues (such as loans), as well as whether they are aware of the risk of not recovering the money invested that is embedded in some of the most talked-about and common financial products that are available in the market. This last objective seems to be relevant since a lot of fraudulent schemes involving teenagers, young adults, and financial markets have emerged in recent years. From the results, some disturbing conclusions can be drawn. For instance, more than two-thirds of the sample do not know what Euribor is (similar result regarding Spread). About a third of the simple do not understand inflation’s consequences. 16,9% do not know what term deposits are, and derivative products and saving certificates are seen as very alike regarding the risk they represent. Students who chose a business-related course as their first choice when applying showed a higher level of financial literacy, although it is still low compared to what one would expect.

Metadherin (MTDH), also known as LYRIC or AEG-1, is an oncogene that enhances tumor progression, metastasis, drug resistance, and immune escape in various cancers by modulating multiple oncogenic pathways, including NF-κB, PI3K/AKT, Wnt/β-catenin, MAPK, and AMPK. Due to the unknown of the complete structure of MTDH, the deep mechanisms of MTDH and selective inhibitors targeting MTDH remain to be explored. The Protein-Protein interaction (PPI) with the Staphylococcal nuclease domain containing 1 (SND1) is a crucial mechanism underlying the function of MTDH. Current studies have demonstrated that inhibitors, including antisense oligonucleotides, peptides, and small molecules targeting MTDH or MTDH-SND1 interactions, provide novel strategies to inhibit the oncogenetic effects of MTDH. This review summarizes and discusses the structure, function, and regulation of MTDH in cancers, providing the potential therapeutic perspectives of MTDH or MTDH-SND1 PPI for drug discovery.

Gold has been traditionally well recognized as a safe heaven for financial markets. Lately, Bitcoin has been gradually considered as a popular alternative. Since the outbreak of COVID-19 in early 2020, it has become even more necessary and critical to examine the diversification capability of them to hedge financial risks associated with an unexpected crisis comparable to the pandemic. This paper hence employs the wavelet analysis, complemented by the multivariate DCC-GARCH approach, to measure the coherence of the gold and Bitcoin prices with six representative stock market indices, three for developed economies and three for emerging economies, all of which are heavily affected by the pandemic. To have a more balanced and comprehensive analysis, two-year data are used, spanning from 12th April 2019 to 15th April 2021, which covers approximately one year before and one year after the announcement of the COVID-19 pandemic. The results suggest that the returns of both gold and Bitcoin are generally not strongly correlated with the market returns of all six indices, particularly for short-term investment horizons. That is, investors in all six indices can benefit through gold, as well as Bitcoin, in terms of hedging. Meanwhile, compared with Bitcoin, gold shows to be less correlated with the indices, particularly for long-term investment horizons. The findings hence suggest that gold and Bitcoin offer diversification benefits to investors in the market indices during a crisis such as the COVID-19 pandemic, especially for short-term investment horizons. The study also reminds policymakers thinking beyond the pandemic about the future of the earth, including air pollution and health, for sustainable development of the whole world.

This paper provides a thorough review of the shifting landscape of economic analysis, spotlighting recent trends and predicting future paths. While traditional economic models remain key for interpreting economic activity, they are being supplemented by fresh methods and cross-disciplinary viewpoints. The increased attention to inequality studies, using advanced statistical techniques and unique data sources, underscores the growing emphasis on fairness and distribution within economic analysis. The incorporation of behavioral elements into economic models also expands our comprehension of economic decision-making and market results. Notably, the emergence of computational economics-integrating artificial intelligence (AI), big data, and machine learning into economic scrutiny-represents a major development. Often referred to as ’smart economics,’ this field employs technology to formulate, address complex economic dilemmas, and perceive economic activity in unconventional ways. Yet, the application of AI and machine learning in economics introduces new hurdles around data privacy, algorithmic bias, and the transparency of model outcomes. The impact of the digital revolution on economic analysis is significant, as the advent of computational economics and the surge of big data are transforming research techniques and policy implications. Concurrently, the advent of the circular economy indicates a radical shift in our perspective on economic sustainability, carrying considerable implications for environmental policy and business tactics.  In the future, it’s anticipated that these trends will further modify the realm of economic analysis, with AI and machine learning integration, emphasis on sustainability and fairness, and the influence of big data becoming more pronounced. As these changes take place, it’s imperative for researchers, policymakers, and practitioners to remain adaptable and flexible, prepared to capitalize on the opportunities and tackle the challenges these trends present.

Less-Lethal Weapons, including electric Tasers, velocity-reduction bullet-capture projectiles, rubber bullets, beanbag rounds, and other less-lethal projectiles used in police departments, federal and local law enforcement agencies, and military policing operations, as well as for private use, are topics of significant debate in recent years. These weapons can reduce collateral damage, reputational risk, and legal exposure while preventing wrongful and unnecessary deaths caused by conventional bullet wounds. Yet, opponents have highlighted concerns regarding the safety and effectiveness of these weapons, as well as their potential to cause injury or even death. While the primary duty of law enforcement officials is to preserve order and execute the law while protecting individual rights, they ultimately achieve these goals by exercising their coercive authority. Society expects police officers to rely on their professional training and judgment when using physical force to defend citizens and themselves or to apprehend criminal suspects. Because police officers must occasionally participate in physical acts of coercion, it is unavoidable that some of these interactions may result in bodily injuries to individuals, including the officers themselves. These injuries have real costs, such as medical treatment, lost wages, municipal liability, court claims and settlements, riots, and legal or even criminal exposure, as well as less-tangible collateral costs, such as the erosion of police legitimacy and public trust, which are more difficult to quantify but arguably more influential in shaping long-term public perceptions than personal injuries alone. Less lethal technology eliminates some of the concerns raised by lethal weaponry. This study reviews the advantages and disadvantages of these less-lethal weapon technologies versus traditional firearms for use by the police force, federal agencies, and military police while also performing advanced analytics to model the valuation and return on investment for a law enforcement organization implementing such technologies.

This study delves into the intricate interconnections among the financial sector, macroeconomic dynamics, and the advancement of sustainable energy production in South Asia. Utilizing data from 1987 to 2022 in Bangladesh, India, Pakistan, and Sri Lanka, the research employs the Structural Vector Autoregressive (SVAR) method to analyze financial market responses. The findings reveal nuanced insights into the complex relationship between economic and environmental factors, fostering a comprehensive understanding of the region's intricate nexus between financial markets and sustainable energy initiatives. In the Economic Growth model, the negative coefficient for CO2 emissions underscores environmental concerns, indicating an inverse relationship with economic growth. Conversely, positive coefficients for non-fossil energy production, Gross Fixed Capital Formation, stock exchange value, and domestic credit emphasize their positive impact on economic growth. A positive GDP coefficient in the CO2 emission model signifies heightened carbon emissions with economic growth, while a negative coefficient for non-fossil energy production suggests potential environmental benefits. The nearly unitary positive coefficient for Gross Fixed Capital Formation highlights its significant role in driving carbon emissions. The Non-Fossil Energy Production model reveals an inverse relationship between GDP and clean energy, suggesting a potential reliance on fossil fuels during economic growth. Positive coefficients for CO2 emissions, Gross Fixed Capital Formation, stock exchange value, and domestic credit highlight factors influencing non-fossil energy production. Long-run stable coefficients affirm variable significance, while a negative error correction term suggests convergence in developing countries. These models offer nuanced insights into the intricate relationships among economic, environmental, and energy variables, guiding sustainable development policies in South Asia.

Tripartite motif-containing (TRIM) proteins consist of over 80 proteins, the majority of which exhibit E3 ubiquitin ligase activity. E3 ligases have a critical role in various cellular processes by specifically recognizing and ubiquitinating substrate proteins to promote their proteasomal degradation or alter their activities. Numerous studies have indicated that TRIMs are involved in carcinogenesis through various mechanisms. However, the regulatory mechanisms delimitating TRIMs’ function as E3 ligases has not yet been specifically addressed in a previous review article. In this review, we focus on recent advancements in understanding how certain TRIMs function solely as E3 ligases during cancer cell proliferation, apoptosis, and metastasis. We comprehensively summarize the target proteins of TRIMs involved in disordered signaling pathways such as Wnt/β-catenin, PI3K/AKT, NF-κB, p53, ERK, and STAT3, as well as those regulating the cell cycle and glycolysis. Following ubiquitination modification by TRIM E3 ligases, these target proteins either undergo proteasome-mediating degradation, maintain steady levels, or get activated/inactivated. This review provides a foundation for the development of E3 ligase-based cancer treatments.

Purpose: To realize the benefits a Quality Management System (QMS), an organization needs to effectively implement its principles. This includes embracing these principles within an enabling environment. Hence, organizational structure is a critical success factor for adopting quality management systems. This paper aims at understanding how the organizational structure impacts ISO 9001 QMS implementation and vise versa, besides exploring how quality management initiatives affect organizational resilience through parts. Design/methodology/approach: The research deploys a qualitative methodology, with an outsider-insider approach. 32 semi-structured interviews were conducted, plus one final reflective interview. Interview questions dealt with structural constructs: communication, employee engagement, employee empowerment, process/routine-orientation, multidisciplinarity, cross-functionality, expertise-utilization and change-readiness. The questions also dealt with how the organizational structure impacted ISO 9001 implementation and vice versa. Findings: The results show that ISO 9001 implementation was more successful and fruitful under process-orientation and to some degree under semi-process orientation, while it looked inconsistent under routine-orientation. This indicates a significant role played by the organizational structure when it comes to ISO 9001 implementation. More importantly, the results also demonstrate that ISO 9001 implementation managed to improve organizational resilience by consistently driving the organizational structure toward higher levels of process-orientation for process-oriented units, whereas it failed to realize such impact for routine-oriented units. Originality/value: This study is unique as it is the first - within the reviewed literature - to examine the moderating role of the organizational structure between the ISO 9001 standard and organizational resilience. It draws a roadmap for the successful realization of organizational resilience through quality management systems, considering organizational structure constructs.

Background: Bladder cancer (BLCA), particularly invasive BLCA, has become a medical burden worldwide as it is associated with recurrence and easy metastasis. There are specific differences in the expression of various miRNAs in tumor and normal tissues. Hence, miRNAs can be used as biomarkers for tumor diagnosis and prognostic evaluation. The current study aimed to predict the downstream target genes of BLCA-related miRNAs and explore their association with immune infiltration. Method: Data on BLCA-related mRNA and miRNA expression levels were downloaded from The Cancer Genome Atlas. Correlation analysis and Cox regression analysis were performed to validate the miRNA risk model. The infiltration of various immune cells should be compared to determine the distinct differences between the immunological microenvironment of the two risk groups. Results: A predictive framework of BLCA was established using the expression levels of two miRNAs. Cox regression analysis showed that the low-risk group had a better prognosis. Then, the target genes of miRNA were predicted, and the target genes were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Moreover, variations in immune cells and functions between the high- and low-risk groups were assessed. Conclusion: The prognostic features composed of two associated miRNAs (MIR-25, MIR-548AN) may help predict the overall survival of BLCA.