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.

Utilizing a 2021 nationally representative sample of 7,504 White-owned employer businesses (WOBs) in the United States of America (USA), the extent, and the determinants of WOB business registration are estimated. Business registration is employed as a proxy for business in/formality. Approximately one-fifth (22.5%) of all employer WOBs are unregistered or informal business concerns hidden from government purview. The primary determinants of employer WOB informality are business size (annual revenues under $500,000 and few paid employees), a business owner with less than a four-year college degree, and an upbringing in a lower- or middle-class environment, among other findings. Notably, this research reveals the white lie of the magnitude of White-owned employer business informality in the USA.

This study empirically examines the effect of corporate governance on the relation between CEO power and firm leverage. Results from OLS and industry fixed effects regressions show that CEO power is positively associated with firm leverage. However, this association is driven by the strength of corporate governance as powerful CEOs tend to choose higher levels of debt only when corporate governance is strong. When corporate governance is weak, CEO power does not seem to have any effect on firm leverage. Overall, results indicate that strong corporate governance mitigates the severity of manager-shareholder conflicts and induces powerful CEOs to choose higher leverage.

Advanced Air Mobility (AAM) may, in the coming decades, result in tens of thousands of new jobs and billions of dollars in additional economic activity. While much of the discussion surrounding AAM focuses on the technical aspects of the nascent industry, estimates of the potential economic impact vary significantly. Much less attention has been paid in the literature to potential externalities, positive and negative, and how these externalities may impact estimates of economic impact. We argue that much work remains to be done before policy advisors and decisions makers can formulate and implement strategies based on the projections of future economic impact of AAM.

The global financial crisis has affected all countries during the period 2007-2014. Tourist companies, especially in Italy, play a significant role in the economy of a country. The performance of tourism companies, and in particular hotels and travel agencies and tour operators, will be analysed in this paper, relative to the period of the crisis. The aim of this paper is to analyze profitability dynamics of the aforementioned tourist companies, to check whether they have suffered the effects of the global crisis. To this end, data from AIDA database relating to Italian companies in the sector were used. The profitability of these companies has been analyzed using the main profitability ratios, ROI and ROS ratios. An analysis of the trends and ANOVA of these ratios was carried out for the period 2007-2015. In this way, it has been verified whether the global crisis has affected profitability dynamics of hotels and travel agencies and tour operators in Italy. There is a parallelism in the trends of the main operators' indices in the three Italian macro-regions. The best performance is in the South, in a less developed economic context. The crisis has reduced the income indices in the first three years, even if the figure remains positive. Since 2012 there is a clear recovery, especially for hotels; intermediaries, on the other hand, suffer from competition from websites. However, the indices confirm the close relationship between travel agencies, tour operators and hotels. ROI mainly rewards first, while ROS intermediaries.

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.

In his 1922 review for Cambridge Magazine of Keynes's A Treatise on Probability, and again in his 1926 review "Truth and Probability" (published in 1931 and republished in Kyburg and Smokler's 1980 edition), Ramsey provided examples critiquing Keynes's logical theory of probability. However, these examples do not disprove Keynes's theory as all of them are flawed. The flaws arise because all the pairs of propositions that Ramsey used to substantiate his criticisms are irrelevant to each other. Such irrelevant propositions are explicitly excluded from Keynes's theory in pages 4-6 of his A Treatise on Probability. This paper highlights that Ramsey's examples, which involve irrelevant propositions, do not disprove Keynes's Boolean, relational logic. The only other defense of Keynes's theory, put forth by Watt in 1989, was found to be deficient by Brady in 2022.

The presence of electrical harmonics in low voltage networks causes many problems for customers, the most important of which is the decrease in the power quality beyond the permissible limits, which leads to a decrease in voltage for long periods, a decrease in power factor and a large losses in the electrical network due to the deformation of the electric waveform of voltage and current. The aim of this paper is to design an optimal passive filter and its optimal location to suppress the harmonic distortion in the distribution system that results from nonlinear loads. This filter will use single objective functions and multi objective functions that will minimize the proposed filter cost, the real power losses, total harmonic distortion "THD" and individual harmonic distortion "IHD". This will be done under the equality constraint of power balance and some inequality constraints such as filter parameters limits, quality factor limits, voltage limits, harmonic distortion limits. The optimal passive filter parameters and location will be calculated using the modern optimization techniques such jellyfish optimization technique. IEEE 33 bus radial system will be used for demonstrating results obtained by the proposed method.

Cloud computing is one of the fastest growing domains of the IT industry, however, the growth rates for each of the models on a global and local (Russian) scale have not been generalized, despite the obvious value of such analysis. Modern business and industry in Russia is going through another period of instability and at the same time is forced to follow the trend of digitalization. That is why a balanced scientific analysis and forecast of the development of cloud technologies is needed, as the main factor in improving business efficiency. The purpose of the study: is to review the main models of cloud services for modern business and industry, describing their capabilities separately and the prospects for the market as a whole. The materials for the study were analytical reports of leading consulting companies and materials from specialized web-sites. Result: The article considers cloud technologies as the main global technological trend, describes popular models of cloud services, their opportunities for business and industry. Russian and global leaders in the provision of cloud services are also described, the growth rates of these markets for each of the models are indicated. The most popular and promising cloud service models in 2022 are: UCaaS, CaaS, SaaS, IaaS, RPAaaS, PaaS. The cloud technology market will show strong growth until 2030, generating both hybrid and absolutely new service models. The private business, industrial and public sectors will increasingly move to cloud services. The main trends in the development of cloud technologies until 2030 are: hybrid cloud, artificial intelligence (AI) and cloud computing, deployment of cloud services in the planetary orbit. The results obtained are very valuable for analysts and industry experts. The above trend analysis provides valuable predictive data to research economists, investors, business and industry leaders and other stakeholders on how the cloud services market will grow in the next 5-7 years. The results of the study also have a general theoretical nature, substantiating the importance of further forecasting the development of this market (especially using mathematical methods).

We develop a four-party model involving banks, merchants, consumers, and platform firms to explain why large shopping malls can offer interest-free installment services to consumers. Using a collaboration between an online shopping platform firm and multiple banks to issue co-branded credit cards as a natural experiment, we find that consumers’ spending on the platform fulfills the requirements for merchants and banks to choose a four-way model. This study highlights the pivotal role of platform firms in the credit card market.

How does democracy relate to the initial economic policy responses to Covid-19? Using a cross country analysis, we find that countries with a higher degree of democracy have stronger economic policy responses than their peers. However, when we separate monetary and financial policies from fiscal policy, democracy is not associated with the latter when we control for the income level of a country. Finally, for countries with lower levels of labor participation, high levels of income inequality are associated with weaker policy responses.

This study aims to examine the effects of student loan debt on the decisions of U.S. married households to invest in stocks located in non-retirement accounts. Using longitudinal datasets from the 2011 to 2017 U.S. Panel Study of Income Dynamics and a fixed effects logit model, the results show mixed findings. The presence of student debt decreases the probability that married households will own stocks, but the amount of student debt does not show a statistically significant effect. The findings suggest that the incidence of student debt raises the perception of liquidity constraints and debt burden among married households.

Machine learning is playing an increasingly important role in the healthcare industry by transforming the way cancer is diagnosed and treated. By analyzing patient data, genomic data, and imaging data, machine learning algorithms can identify molecular signatures that distinguish cancer patients from healthy patients. Biomarkers that can accurately detect and diagnose cancer can be identified through analysis of these data sources. Additionally, personalized cancer therapies can be developed by identifying the most effective treatments based on individual patient characteristics and cancer type. Some of the machine learning techniques used for cancer biomarker discovery include deep learning and support vector machines, which can respectively identify complex patterns in data and classify data to identify relevant biomarkers. The benefits of using machine learning for cancer biomarker discovery are significant, including more precise and personalized treatments, improved patient outcomes, and the potential to transform cancer diagnosis and treatment. However, there are also challenges associated with using machine learning for cancer biomarker discovery, such as data collection and privacy issues, as well as the need for more powerful computational resources. This article explores the potential of machine learning in cancer biomarker discovery and argues that ongoing research in this field has the potential to revolutionize cancer diagnosis and treatment. Future research directions should focus on further developing machine learning algorithms and effective data collection and privacy protocols.

A high inflation period of seven years (1978-1985) in Israel, which turned into a hyperinflation, puzzled Israeli economists, who tried to understand its causes and mechanisms. As a result, they provided fourteen different explanations. Although all of the explanations were based on the same data, the researchers’ conclusions were either different or contradictory. This situation provides a virtual laboratory for the study of the ways and methods of economic thought; it is a classical Ceteris patribus situation. This laboratory further raises other subjects and questions. Are there principal differences between the economists' explanations? Is it possible to classify these differences? How do economic explanations for inflation differ from non-economic ones? In this article, I classified thirteen economic studies and one non-economic study into five clusters. This was the methodological tool used to inquire into the economic thought in this virtual laboratory.

The latent transforming growth factor-beta (TGF-β) binding protein 1 (LTBP1) has been implicated in various cellular processes, but its role in triple-negative breast cancer (TNBC) remains unclear. In this study, we investigated the impact of LTBP1 on TNBC progression and its underlying mechanisms. Analysis of online datasets revealed elevated LTBP1 mRNA expression in breast cancer tissues compared to normal adjacent tissues. Kaplan-Meier Plotter analysis indicated that high LTBP1 expression was negatively correlated with relapse-free survival (RFS), distant-metastasis free survival (DMFS), and overall survival (OS) of breast cancer patients. Additionally, LTBP1 mRNA levels were associated with chemotherapy resistance. Functional assays in TNBC cells demonstrated that LTBP1 knockdown suppressed cell proliferation, induced apoptosis, and attenuated migration and invasion. In vivo studies confirmed that LTBP1 knockdown inhibited tumor growth in a xenograft mouse model. Mechanistically, LTBP1 positively correlated with genes involved in signaling regulation and organelle organization, with significant associations to GTPase binding and the RhoA/ROCK pathway. LTBP1 knockdown reduced RhoA activity and phosphorylation of Myosin Light Chain 2 (MLC2), suggesting inhibition of the RhoA/ROCK signaling pathway. Moreover, activation of the RhoA/ROCK pathway partially rescued the effects of LTBP1 knockdown on TNBC cell proliferation, apoptosis, migration, and invasion. In conclusion, our findings suggest that LTBP1 promotes TNBC progression through activation of the RhoA/ROCK signaling pathway, highlighting its potential as a therapeutic target for TNBC.

Objective: The paper, specifically examines whether the recently formed Regional Comprehensive Economic Partnership (RCEP) can potentially facilitate minimising the constraints to renewable energy goods exports at the regional level in Asia. Data, Methodology and Findings: Using the panel data from 11 RCEP members from 2006 to 2014, this study has applied the ‘meta frontier stochastic gravity frontier’ methodology and confirms that the establishment of RCEP has the potential to improve trade in renewable energy commodities within the RCEP region. Policy Implications: The policy implication is that when countries work together, it will lead to enormous benefits for national, regional, and worldwide prospects of a more sustainable energy future. Practical Policy Implications: In terms of practical policy implications, the developed RCEP member countries should actively engage in promoting R&D activities and protecting intellectual property rights concerning renewable energy production, which are essential for countries to integrate with the world market and to lift the export frontiers of both the developed and developing RCEP member countries to reach the unrestricted export of renewable energy technology.

Keeping in view the concept of agglomeration economies and the New Economic Geography (NEG) angle, this paper makes an attempt to examine the rural to urban population movement at the district level in India. The findings do not favour a strong positive association between levels of urbanization and migration rates.  However, there exists a cluster of districts which are able to attract migrants on a large scale in spite of being already urbanized. The work participation rate, share of services and construction work, and literacy rate all form parts of this positive nexus, indicating that opportunities exist with increased levels of urbanization which in turn prompt people to migrate. The positive spill-over effects of higher levels of urbanization are not limited to the urban spaces only as the adjoining rural areas also seem to have undergone   a significant transformation. The land use pattern and activities are changing and some of the developmental impact is evident. However, the regional variations in this respect are evident. There are sharp differences in the relationship between urbanization level and migration rates across regions. The nature of urbanization and its determinants and the outcome variables of urbanization and migration also unravel regional variations. Besides, there are many districts with higher levels of urbanization; yet, they are not able to attract migrants at a rapid pace. New investment opportunities can be created in these spaces to reduce the cost of growth and make employment generation process more effective, facilitating the rural population to take the benefits of agglomeration economies.

This paper examines the impact of COVID-19 on Small and medium-sized enterprises (SMEs) deposits across 13 African nations from 2016 to 2022, using a seven-year dataset and Ordinary Least Squares estimator. Notably, it uncovers a significant positive link between the pandemic and SMEs deposits, indicating heightened reserves amidst economic uncertainty, potentially driven by risk mitigation or government support. Associations between gross domestic product (GDP), inflation, unemployment, foreign direct investment (FDI), exchange rates, and SMEs deposits were evident, showcasing higher GDP aligning with increased deposits, while inflation and unemployment linked to reduced ones. FDI showed a positive influence, and exchange rate fluctuations notably affected SMEs deposits, especially for those in international trade. These findings emphasize policy reconsideration for crisis strategies supporting SMEs reserves during uncertainty and interventions addressing inflation, unemployment, and exchange rate risks. Future research exploring regional nuances and global comparisons could further enrich policymaking for resilient SMEs amid evolving economic landscapes.

In developing countries, the dependence on traditional biomass for domestic energy consumption is one of the major causes of deforestation and environmental poverty. This paper investigates the impact of women’s education on the probability of using Unsustainable Biomass Cooking Technologies (UBCT) as the household main fuel of cooking instead of clean energy. Combining data from four rounds of Nigeria DHS conducted between 2003 and 2018, we take advantage of a natural experiment, the implementation of Uni-versal Primary Education policies in 1970, to obtain an exogenous variation in women’s education levels. Using an instrumental variable approach to control for the endogeneity issues, we find that women with higher levels of education are less likely to use UBCT as their primary source of cooking. This result implies that environmental policies in developing countries should rely not only on income transfers policies as suggested in the literature but also on increasing women's human capital to reduce women’s dependence on unsustainable biomass cooking practices.

Given the rapid development of live streaming commerce in China, this study focuses on the interactivity and sociability of live streaming shopping activities and explores online consumers’ real-time interaction intentions and trust-building behaviours with online merchants. To discover the real-time interaction between online consumers and online merchants, this study builds a research model based on the Theory of Planned Behaviour (TPB). Through the data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the key findings state that, three factors, including attitude, subject norm, and perceived control, positively affect online consumers’ real-time interaction intentions and lead them to build trust with online merchants. Meanwhile, control variables, including gender, age, and educational background, demonstrate insignificant effects across the model. Unlike existing literature, the current study pays much attention to the interactive characteristics of live streaming shopping activities and can provide some valuable suggestions both for online consumers and online merchants, which can promote the co-development of the commercial and social aspects of live streaming platforms.