This study investigates the likelihood of time to bank failures in the US between 2001 and April 2023, based on data collected from the Federal Deposit Insurance Corporation's report on "Bank Failures in Brief - Summary 2001 through 2023". The dataset includes 564 instances of bank failures and several variables that may be related to the likelihood of such events, such as asset amount, deposit amount, ADR, deposit level, asset level, inflation rate, short-term interest rates, bank reserves, and GDP growth rate. We explore the efficacy of machine learning survival models in predicting bank failures and compare the performance of different models. Our findings shed light on the factors that may influence the probability of bank failures with a time perspective and provide insights for improving risk management practices in the banking industry.

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.

Background: Hepatocellular carcinoma (HCC) stands out as one of the most lethal cancers globally, given its complexity, recurrence following surgical resection, metastatic potential, and inherent heterogeneity. In recent years, researchers have systematically elucidated the significance of long non-coding RNA (lncRNA) in the initiation and progression of HCC. The introduction of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases has significantly enhanced the prognostic assessment of HCC. However, the association between HCC and cell senescence has been infrequently explored in the literature. Method: We downloaded liver hepatocellular carcinoma (LIHC)-related messenger RNA and lncRNA expression levels from TCGA. Correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to validate the lncRNA risk model associated with cellular aging. Comparing the infiltration of diverse immune cells enabled the identification of distinct differences in the immunological microenvironments of the two risk groups. Subsequently, we conducted a real-time polymerase chain reaction (qPCR) experiment to confirm the accuracy of the selected lncRNAs. Results: A predictive framework for HCC was constructed based on the expression levels of five lncRNAs. Multivariate and univariate Cox regression analyses revealed that lncRNA signatures associated with senescence were independently correlated with an increased risk of HCC. Additionally, the nomogram also provides a more refined and sensitive model. Further investigation into the variations in immune cells and functions between the high-risk and low-risk groups was conducted. Subsequently, a qPCR experiment results revealed underexpression of AC068756.1, AC090578.1, AC145343.1, and LINC0022 in Huh7 and LM3 cells. In contrast, AP003392.4 did not exhibit a significant difference between Huh7 and control cells. Conclusion: The prognostic features and nomogram, consisting of five aging-related lncRNAs (AC068756.1, AC090578.1, AC145343.1, AP003392.4, and LINC00221), may be useful in predicting the overall survival of HCC.

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.

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.

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.

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.

Historically, increased credit union competition in Idaho and Montana has caused commercial banks to offer higher deposit rates to savers and lower loan rates to borrowers. Data are collected for the second quarter of 2018 to examine whether that pattern still holds true. Unlike prior studies, empirical results indicate that credit union competition no longer exerts statistically reliable impacts on deposit rates or loan rates in this northern Rocky Mountain region of the United States. Potential contributing factors include bank and thrift consolidation in recent years, the low interest rate environment prevailing during the late 2010s, and greater emphasis on non-interest forms of intermediary competition in the banking markets that comprise this regional economy.

The UK fully legalised open market share repurchases in 1981, and to our knowledge no study has investigated the business cycle’s influence on repurchase decision-making. We address this aspect and investigate the period 1985-2014. This is relevant as the business cycle factors impact the firm-specific variables such as cash flow, profitability, dividends and capital structure, and these factors traditionally influence repurchase decisions. This forms the paper’s theoretical intuition, and the empirical objectives test the business cycle’s influence on the decision to undertake a repurchase, and also its influence on repurchases values. The results find that the business cycle influences both the decision of undertaking repurchases and repurchases’ values, and this influence has aggregately remained positively associated with economic prosperity. Thus, the frequency of repurchase announcements by British firms is more probable during prosperous economic circumstances. The results also reveal that the repurchase-business cycle relationship witnessed a structural break in 1996:Q2, and the real difference following this break is the increase in the business cycle’s influence on the decision regarding repurchase values. The paper thus contributes to existing literature by directly testing the UK’s repurchase-business cycle relationship, and providing detailed empirical evidences that business cycle conditions strongly impact the repurchase decision-making.

The COVID-19 pandemic wreaked havoc on economies everywhere, affecting everything from supply chain networks to international trade as a direct result of the increased vulnerability of more nations and the disruption of the activities of key traders. This research study examines how COVID-19 affected the supply chain on a worldwide and regional scale, as well as the systemic policy and economic steps governments and businesses took to rebound and maintain resilience. COVID-19 has had a significant influence, prompting governments and businesses to take steps to fortify their operations and businesses against disruptions, highlight the necessity for resilience in supply chains and emphasize the importance of managing risk. The supply value chain is at risk from the prolonged implementation of COVID-19 trade measures like border closure, export restrictions, and import sanctions. Many businesses are transitioning from a "recovery mode" to a resilient and sustainable mode" and are beginning to plan for the future. The study suggests that corporate and government leaders should prioritize proactive and adaptable policy, economic, and structural adjustment. This research will be useful to policymakers and industry leaders in their efforts to lessen the effect of COVID-19 on the global supply chain by enforcing governmental, economic, and business reforms built on resilient supply chains and mitigating economic risks during tough times.

The objective of this study is to explore the link between the financial sector, macroeconomic fluctuations, and sustainable energy production in South Asia. It evaluates existing research, identifies gaps, and suggests future directions. The study emphasizes the need to understand how economic activities influence the environment and how environmental factors impact economic and financial outcomes. It also examines financial market responses to understand the manifestation of economic and environmental factors, using data from Bangladesh, India, Pakistan, and Sri Lanka spanning 1987 to 2022. The results show that investment in green energy is essential for developing countries. The study suggests that the relationship between the region's stock market, GDP, carbon emissions, and green energy is complex, with a negative response to domestic credit indicating potential obstacles to investment, such as policy barriers or insufficient incentives. Mixed responses highlight the need for credit directed towards sustainable projects. Variations in responses across economic indicators may indicate policy challenges or structural issues, necessitating a reassessment of government policies to incentivize sustainable investments and promote green technology adoption. These results imply that policymakers should precisely assess the environmental ramifications of economic growth and stock market activities. This presents an opportunity to craft policies that guide investments toward cleaner technologies and industries, aligning economic growth with sustainable practices. Policymakers and financial institutions should explore ways to incentivize green energy investments and promote sustainable economic growth.

The digital economy based on digital technology is an important force for high-quality economic growth and industrial transformation, and has great potential for value creation. Based on the data of 30 provinces in China from 2007 to 2017, this paper uses entropy method to calculate the industrial green transformation (IGT), and empirically analyzes the impact of Digital economy on IGT. The DE can significantly reduce IGT of local and neighboring areas after excluding the influence of macro system factors and replacing the spatial weight matrix. The DE can indirectly reduce the IGT by accelerating the accumulation of human capital, and green technology innovation. The impact of digital economy on IGT is a non-linear relationship. With the further improvement of environmental regulation, financial development and intellectual property protection, the role of digital economy in IGT is more obvious. To this end, it is necessary to speed up the construction and improvement of digital infrastructure, build an integrated layout of "digital infrastructure", give full play to the radiating role of the digital economy, and implement differentiated development paths based on regional comparative advantages.

China's carbon emission trading market has been formally established, but few studies have been conducted to analyze the impact of this policy on the regional urbanization level. Therefore, this paper evaluates whether the carbon trading pilot policy can enhance the regional urbanization level in China through the difference-in-differences method and analyzes the mediating role of industrial structure upgrading in this process. The results prove that the carbon trading market policy can accelerate the transformation and upgrading of industrial structure in the region so that it promotes the development of regional urbanization. Moreover, the effects of the policy are concentratedly manifested in the eastern region of China.

The paramount prerequisite for effective anti-cancer drugs is their ability to eradicate malignant cells while sparing non-cancer cells. The divergence in properties between malignant and non-cancer cells establishes a "therapeutic window," a critical consideration for achieving desirable treatment outcomes. Central to this is the imperative of a cancer drug's "selectivity and specificity." Taxanes, a pivotal class of successful anti-cancer drugs, continue to serve as the linchpin of cancer treatment due to their efficacy across a spectrum of cancer types. Operating as broad-spectrum chemotherapeutic agents, taxanes exert cytotoxic effects on proliferative cancer cells by binding to and stabilizing microtubules, disrupting mitosis, inducing mitotic catastrophe, and resulting in cell death. The distinct proliferative nature of cancer cells, as opposed to less proliferative non-cancer cells, affords taxanes a measure of specificity and selectivity. Nevertheless, sporadic yet recurring evidence suggests that taxanes also operate through non-mitotic mechanisms. Taxanes' binding and stabilization of microtubules lead to micronucleation and subsequent cell death, impacting both mitotic and non-mitotic cells. Recent discoveries indicate that the flexible and weakened nuclear envelope of malignant cells renders them sensitive to taxane-mediated micronucleation and cell death during various phases of the cell cycle. Conversely, non-cancerous cells typically exhibit a more robust and sturdy nuclear envelope, rendering them more tolerant to taxane-induced nuclear envelope fragmentation and subsequent micronucleation and cell death. The expression levels of nuclear envelope structural proteins, particularly Lamin A/C, emerge as indicators of taxane sensitivity. This evolving understanding underscores that nuclear envelope malleability, in conjunction with a high proliferation rate, is a pivotal determinant of taxane specificity and selectivity against malignant cells. These insights necessitate reconsidering oncological strategies to augment taxane efficacy, overcome resistance, and mitigate side effects.

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.

The aim of this article is to model a negotiation between shareholders in high-technology-risk industries and local residents on the safety investments to be implemented. The methodology used is a Nash bargaining model, with a DE curve representing shareholders' dividend demands and an NS curve representing the safety demands of local residents' associations. The model is used to determine the level of safety investment required. One of the main results is that the estimation of a higher accident risk is accompanied by both a higher safety investment and a higher dividend payout. The most obvious implication of this result is that it is undoubtedly necessary to give greater weight to local residents in investment decision-making, in order to improve the well-being of all stakeholders.

This paper examines the link between informality and corruption, two interlinked phenomena that have negative impacts on economic development. The paper presents a neoclassical model simulation that illustrates how informality can drive corruption in the economy, emphasizing the incentives for corruption in an economy with informal and formal sectors. The model provides insights into the mechanisms that promote corruption and how policymakers can reduce it through formalisation. The paper reviews the existing literature on informality and corruption, highlighting the empirical evidence and theoretical models that support the relationship between the two. The research finds that countries with larger informal sectors tend to have higher levels of corruption. The study contributes to the ongoing debate on how to reduce corruption and promote formalisation, which are crucial for sustainable economic growth.

The claim that “there is no third way” besides the economic models of capitalism and communism has faced a challenge from a new and growing body of research into a “third way” economic paradigm known as democratic planning. In this paper, we explore one of these democratic planning models–Robin Hahnel and Michael Albert’s model of a participatory economy, focusing in particular on its allocation mechanism–a non-market, non-command-planning procedure known as “participatory planning.” This procedure has recently been implemented in computer programs to explore its feasibility, the encouraging results of which have been published elsewhere and which we summarize here. But I present here for the first time the detailed algorithms and related pseudocode powering all of these computer programs for others to consider, examine, and build as their own programs. I also describe future directions for this avenue of research.

The development of digital economy is becoming an important path to promote the kinetic energy of China's tax revenue development. Based on the panel data from 2011 to 2018, this paper uses Gini coefficient to analyze the regional differences of China's digital economy, and uses fixed effect model, spatial Durbin model, multi-period double difference model and other empirical methods to examine the tax effects of digital economy development. The results show that the regional disparity is the main reason for the regional disparity of digital economy development in China. The development of digital economy directly increases the tax amount of local digital industry, and at the same time it also radiates and drives the increase of local total tax revenue; The tax effect of digital economy has a negative spatial spillover, showing a "siphon effect" to neighboring areas; Mechanism analysis shows that the development of digital economy mainly promotes the increase of local tax revenue through growth effect.

Bank deposit is closely related to systemic risks. In addition, considering that resident deposits in China have significant seasonal characteristics, this paper focuses on which component of deposits drives the systemic risk volatility, that is, it can supplement the existing forecast information. We use X-13ARIMA-SEATS to decompose deposit into three subsequences. The research findings show that the forecast effect of subsequence models is better than that of benchmark series. Most importantly, the model with trend component has the best forecast performance.