I present a theoretical model and an empirical approach for jointly estimating the effectiveness of fiscal policy and the stochastic process of sovereign interest rate shocks. The theoretical model has features relevant to small open and emerging economies. Interest rate shocks affect the ability of firms to finance payroll expenses. This theoretical feature creates a propagation mechanism for interest rate shocks and affects government spending multipliers. This paper proposes a strategy for jointly estimating government spending multipliers and the interest rate shock process parameters.

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.

This study underscores the chronic issue of gender pay disparity that prevails across different STEM fields and educational qualification levels in Australia. Despite instances where women's incomes may align or even surpass men's, the broader pattern of inequality remains undeniable. The study advocates for targeted strategies to address gender pay gaps, particularly in fields like Engineering and Science, and emphasises the significance of cultivating inclusive work environments that recognise and reward contributions regardless of gender. This study serves as a critical call to action to rectify these inequities and promote a more balanced and equitable STEM landscape.

We extend the Shariah-compliant digital assets and Islamic Fintech literature through exploring the time-frequency associations between the volatility index (VIX) and cryptocurrencies (both Islamic and traditional). Employing wavelet-based technique, we find that Islamic cryptocurrencies demonstrate low or no coherency with stock market volatility compared to traditional cryptocurrencies (except Tether) during the whole time and frequency bands, highlighting the hedging capabilities of Islamic cryptocurrencies. Tether also serves the same against VIX, as there is a low or favorable link between these variables. Finally, our findings would be prolific to digital currency traders and investors in designing the portfolio strategies.

This research delves into the temporal dynamics of a nation's pursuit of a targeted GDP per capita level, employing five different survival machine learning models, remarkably Deep Learning algorithm (DeepSurv) and Survival Random Forest. This nuanced perspective moves beyond static evaluations, providing a comprehensive understanding of the developmental processes shaping economic trajectories over time. The economic implications underscore the intricate balance required between calculated risk-taking and strategic vulnerability mitigation. These findings guide policymakers in formulating resilient economic strategies for sustained development and growth amid the complexities inherent in contemporary economic landscapes.

Ferroptosis, a recently identified form of programmed cell death, is characterized by the accumulation of lipid peroxidation, reactive oxygen species, and elevated free iron levels, involving the regulation of glutathione metabolism, iron metabolism, lipid metabolism, and oxidative stress biology. Tumor metastasis, a critical hallmark of malignancy and a key contributor to cancer recurrence and mortality, has been extensively linked to iron dysregulation, highlighting the potential of agents inducing iron-mediated cell death as promising strategies for preventing and treating metastasis. This review offers a comprehensive understanding the regulatory mechanisms underlying ferroptosis and its crucial role in the three distinct stages of metastasis: invasion, circulation, and colonization.

Macrophages are a type of white blood cells that can exist in two different functional states, known as M1 and M2. M1 macrophages secrete pro-inflammatory cytokines that can promote tumor growth and metastasis, whereas M2 macrophages secrete anti-inflammatory cytokines that can inhibit tumor progression. This phenomenon, referred to as macrophage polarization, has been implicated in the development and progression of cancer. Furthermore, macrophage polarization is currently being investigated in the context of COVID-19 severity. It is believed that M1 macrophages may contribute to the excessive inflammation observed in severe COVID-19 cases, while M2 macrophages may confer protection against the disease. Hence, comprehending the role of macrophage polarization in both cancer and COVID-19 has the potential to enhance treatment strategies for both conditions.

The implementation of environmental protection strategy necessarily requires mapping the amount of capital stock of environmental infrastructure. Through the Weibull distribution function and hyperbolic age-decreasing efficiency model, the provincial environmental infrastructure capital stock in China from 1980 to 2018 is measured cautiously, and its spatial dynamics with the generated pollutants is analyzed using the center of gravity method. It is found that: the spatial distribution of environmental infrastructure capital stock is uneven, and the unevenness in the east-west direction is greater than that in the north-south direction, but the unevenness in the east-west direction is narrowing while the north-south direction is widening; the spatial and temporal distribution of environmental infrastructure capital and environmental pollution vary greatly, and the spatial management of environmental pollution is less accurate.

We quantify financial returns to backers in reward-based crowdfunding projects on Kickstarter and show that such investments provide profitable opportunities in addition to non-monetary benefits. The average unconditional annualized return is 11.5% and the average return on successful projects is 30%. Hence, backing money near the end of a campaign, when the probability of success is already high, is a profitable strategy. The most attractive is the Design category, where successful projects yield 73%, on average. Short-term projects are more profitable than long-term ones. Financial return is an important type of extrinsic motivation in reward-based crowdfunding, which has generally been neglected in academic literature. Reward-based crowdfunding outperforms other forms of crowdfunding and other common alternative investments.

This paper provides an overview of the existing literature on the use of artificial intelligence (AI) in various fields, including economics, finance, mining, manufacturing, and innovation. The paper identifies the drivers and effects of AI deployment in the context of innovation and highlights the challenges and opportunities that arise from the use of AI. The studies reviewed in this paper cover various topics related to forecasting, including the impact of AI on professional skills, hybrid forecasting techniques for predicting commodity prices, and novel deep reinforcement learning algorithms for crude oil price forecasting. The paper’s contribution lies in its systematic and comprehensive approach to reviewing the literature, which allows for a better understanding of the impact of AI on various fields and the identification of strategies to address the challenges that arise from its deployment.

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.

Metastasis is the major cause of cancer-related mortality. Metastasis is a process through which cancer spreads from its initial location to other sections of the body. Cancer cells' epithelial-mesenchymal transition (EMT), anoikis resistance, cell migration, and angiogenesis are all well-known steps in this process. Investigating the molecular processes that govern cancer metastatic progression may lead to more effective diagnostic and treatment strategies. Long non-coding RNAs (lncRNAs) have recently discovered to have a vital more than 200 nucleotides. A rising body of research indicates that lncRNAs have a role in a wide range of biological processes and diseases, including cancer. The usage of LncRNA in cancer metastasis has been widely researched. However, according to current studies, lncRNA is mostly associated with the EMT process. This review focuses on the processes behind lncRNA involvement in cancer metastasis.

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.

Cancer, a pervasive threat to human health, presents formidable challenges to traditional treatment approaches. Tumor immunotherapy has emerged as a promising strategy for combating malignancies by bolstering the body's immune response to thwart tumor metastasis and recurrence. Nonetheless, the intricacies of tumors, patient heterogeneity, and the presence of tumor-immunosuppressive microenvironments have limited the overall efficacy of immunotherapy, achieving only approximately a 20% success rate. In recent years, nanomaterials have garnered increasing attention in the realm of tumor immunotherapy due to their inherent advantages, such as excellent biocompatibility, precise targeting, and controlled drug release. Nanomaterials empower immunostimulatory molecules and therapeutic agents with the ability to specifically target tumors, amplify drug accumulation at tumor sites, facilitate local immune modulation, alleviate immunosuppressive microenvironments, and thereby enhance the effectiveness of tumor immunotherapy. This review provides an overview of the current state of immunotherapy and offers insights into the ongoing research progress surrounding various nanomaterials aimed at augmenting the efficacy of immunotherapy.

We offer an extensive analysis of the significance of information within the realm of Gaussian quadratic economies. We build upon the seminal papers of Morris and Shin (2002, 2007) and consider a signal game of incomplete information. Particularly, we question the suitability of partial transparency portrayed by fragmented information in addition to the private signal in terms of welfare effects. We can summarize our findings in two main points. First, fragmented information, in conjunction with a private signal, can reduce the reliance on public signals. Second, a conflicting effect arises between increasing full disclosure and increasing the precision of fragmented (semi-public) information when examining different complex scenarios, involving for example endogenous private information or imperfect correlated signals. For a critical threshold, an optimal communication strategy designed by fragmented information should be implemented whenever that kind of information is acquired at a high precision.

Approximately 28 million individuals in the United States face the risk of developing precancerous colonic adenomas (polyps) and potentially progressing to colorectal cancer (CRC). While a promising strategy for CRC prevention involves pharmacological intervention, such as cancer chemoprevention or interception, currently, there are no FDA-approved drugs capable of preventing the formation or progression of adenomas to adenocarcinoma. Numerous clinical, epidemiological, and preclinical studies have offered compelling evidence supporting the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) in CRC chemoprevention. However, the prolonged use of NSAIDs is not FDA-approved due to potential life-threatening toxicities resulting from cyclooxygenase (COX) inhibition and the depletion of physiological prostaglandins. Despite indications that the COX inhibitory activity of NSAIDs may not be essential for their antineoplastic effects, the absence of a well-defined target impeded the development of derivatives that do not inhibit COX. Earlier research suggests that the inhibition of cyclic guanosine monophosphate phosphodiesterase (cGMP PDE) may be responsible, at least in part, for the antineoplastic activity of the NSAID sulindac. This could potentially offer a novel target for CRC chemoprevention. To identify the cGMP PDE isozyme(s) contributing to the antineoplastic activity of sulindac, we synthesized a chemically diverse library of over 1500 compounds, all sharing the indene scaffold of sulindac. Subsequently, we screened these compounds for their impact on cancer cell growth and PDE inhibitory activity. From this screening, a series of lead compounds emerged. These compounds lacked COX-1 and COX-2 inhibitory activity, surpassing sulindac in potency to inhibit CRC cell growth. Importantly, they demonstrated greater selectivity by not affecting normal cell growth. Through chemical optimization, we identified several development candidates that selectively inhibit PDE5 and/or PDE10. These compounds activate cGMP/PKG signaling, suppressing Wnt/β-catenin transcription. This action counters the growth advantages resulting from APC or CTNNB1 mutations, which are responsible for most human CRCs. This review delves into the scientific literature supporting PDE5 and/or PDE10 as potential targets for CRC chemoprevention or interception. Our findings suggest a promising avenue for developing drugs that may effectively intervene in the progression of colorectal cancer, offering hope for improved preventive strategies in the future.

Access to electricity, a fundamental element of contemporary life, is essential for economic success. Its impact extends to the fundamental foundations of industrial development and has the power to improve a wide range of industries, including healthcare, transportation, utilities, and education. This article aims to analyse the effect of electricity access on primary education in Central Africa over the period 1997-2019. To this effect, we employ data mainly from the World Development indicator on 9 countries of Central Africa. Using the pooled ordinary least squares estimation technique, the results indicate that access to electricity contributes positively and significantly to primary educational attainment in Central Africa during the study period. The results are Robust to the use of alternative estimation strategy and eventual endogeneity problems in the results are account through the two stage least square estimation techniques which confirm our baseline results as well as the nature of the relationship between access to electricity and primary education in Central Africa. These results have important implications for policies in overcoming barriers to electricity access.

This paper examines the information content of selected US industries focusing on the dynamic linkages among these industries, the stock market and a number of fundamental variables. The period of investigation spans from January 1960 to December 2021. The empirical strategy includes several methodologies such as regressions, vector autoregressions and volatility models. The idea is to investigate the dynamic linkages among these series at both the mean and the volatility levels. The results point to significant industry returns’ explanatory power for many predictors of economic activity including the stock market. Further, time-varying analysis of the linkages among the industries and the stock market’s returns reveal that certain industries such as Oil and Financials provide consistent information leadership over other industries and across decades. Further, upon assessing the industry–market return volatility spillovers, it was found that a market risk–return profile may not always be economically significant and timely for investors. Finally, crises, financial or otherwise, affect industries but to differing degrees.

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.

Parkinson’s Disease (PD) is a prevalent progressive neurodegenerative condition affecting millions globally. Research has found that individuals with PD have a reduced risk of certain cancers, such as colon, lung, and rectal cancers, but an increased risk of brain cancer. Therefore, there is an urgent need for the development of advanced PD diagnostic methods and for investigating the relationships between risk factors, such as lifestyle due to handedness associated with various types of cancers. Recent ad- vancements in magnetic resonance imaging have enhanced PD diagnosis, reducing misdiagnosis and facilitating more accurate disease progression monitoring. Nevertheless, challenges exist, particularly in the distinction of PD between left-handed and right-handed patients over time. This survey provides an overview of contemporary deep learning-based imag- ing analysis methodologies, encompassing both non-longitudinal and lon- gitudinal contexts. We also explore existing limitations and prospects for refinement to gain deeper insights. These insights are poised to inform the development of personalized treatment strategies for PD patients while elucidating the current disparities between deep learning models and their efficacious implementation in clinical practice.