The progression in nanotechnology has revolutionized the biomedical sciences for diagnosis and treatment of diseases like cancer. There have been many kinds of nanomaterials but Inorganic nanomaterials have been considered potential candidates for anticancer activities due to their high biocompatibility, less toxicity, high stability, and high precision in targeting affected cells. Several synthesis approaches have been used to prepared these nanoparticles, such as physical, chemical, and biogenic methods. Due to higher toxicity and adverse effects of chemical methods, eco-friendly way such as biosynthesized inorganic nanomaterials have attained much attention for multiple application particularly treatment of diseases. This review presents a comprehensive and updated knowledge (2015-2023) regarding the cancer treatment. The article first categorizes biogenically synthesized inorganic nanoparticles into three main groups: metallic nanoparticles, metal oxide nanoparticles, and quantum dots and then successful stories related to cancer treatment. This will also provide very effective platform for researchers and academia to detail the biogenically synthesized inorganic nanoparticles’ morphology, their characterization, targeted cancer cells.

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.

With the advancement of science and technology and the advent of the digital economy, the digital economy has become a new driving force for economic development, and the digital economy industry at home and abroad is facing new opportunities for survival and development. However, due to the special development model and profit mode of the digital economy industry, the traditional performance evaluation method is no longer applicable, so it is particularly important to improve the previous performance evaluation method. This paper first adjusts the customer value assessment (CLV) model according to the characteristics of the digital economy industry, and then analyzes the traditional EVA based on the adjusted user value assessment (ULV) model of the digital economy industry. The performance evaluation system is improved, and the representative enterprises of Alibaba, JD and Pinduoduo in the digital economy industry are selected for performance evaluation and analysis, and the user value performance evaluation model of the digital economy industry is integrated, innovated and standardized, in order to provide reference and reference for the follow-up research and practice of performance evaluation in the digital economy industry.

Poland has experienced a very sharp rise in income and wealth inequality after the economic transition. We measure the relative persistence of income inequality and intra-generational income mobility in Poland during the period 2008-2015. Our research is based on the panel survey data, our subsample includes 501 households. To measure the persistence of income inequality we calculate Shorrocks’s R coefficient. We find that if inequality is measured by the Gini index the relative persistence of income inequality in Poland is similar to Western Europe. In the case of the Theil index and the Mean Log Deviation (MLD), the relative persistence is higher than in a majority of Western Europe countries and similar to the United Kingdom or the United States. The income distribution in Poland is rather stable. Income mobility is lowest at the bottom and at the top of the income distribution. In the middle (3rd) quintile upward mobility is higher than downward mobility. The short-term income mobility in Poland has not changed during and after the Great Financial Crisis and is still medium in comparison with the rest of Europe.

The paper focuses on younger online viewers’ motivation to watch video game live streaming on live streaming platforms. Unlike existing scholars, it analyses younger online viewers’ watching motivation through a positive perspective and draws on the Play-Others-Downtime theory (P-O-D theory) and the motivation theory to establish the research model. By analysing 397 samples based on the variance-based structural equation modelling and partial least squares path modelling (SEM-PLS), the results present that younger viewers’ entertainment, social and leisure purposes positively affect their watching motivation. Control variables (i.e., gender, education background, and income level) demonstrate insignificant effects across the model. Considering the influence of the COVID-19 pandemic, watching video game live streaming is essential entertainment and social activities for younger adults. Future studies should identify the positive impact of video game live streaming and guide younger viewers to participate appropriately in this activity.

The low-carbon city pilot is an important policy for promoting sustainable development and addressing climate change. The level of green technological innovation is a significant driving force for China's transition to high-quality development and the realization of carbon peaking and carbon neutrality goals. This essay takes the panel data of 30 provinces in China from 2008 to 2020 as the research sample, regards the number of urban green invention patent applications as a quantifiable indicator of the level of urban green technological innovation, and takes the policy of low-carbon city pilot as a quasi-natural experiment, and uses the difference-in-differences model to test the impact of low-carbon city pilot on the level of urban green technological innovation, and to investigate the mechanism of action within. The main conclusions are as follows: (1) The policy of low-carbon city pilot has an outstanding promotion effect on the level of urban technological innovation. (2) Using the mediating effect to analyze, it is found that the low-carbon city pilot policy can improve the level of urban green technological innovation through the development of green finance.

Green innovation, as a sustainable development approach, can synergistically promote high-quality economic and social development. We select China's A-share-listed manufacturing corporations from 2011 to 2021 as the research sample to empirically study the impact of executive academic experience on green innovation in manufacturing corporations. Further, we test the relationship between executive academic experience and green innovation in manufacturing corporations under the mediating role of corporate social responsibility and the moderating role of heterogeneous environmental regulations. The study shows that (1) executive academic experience helps to promote green innovation in manufacturing corporations; (2) executive academic experience is conducive to promoting the fulfillment of social responsibility by manufacturing corporations; (3) corporate social responsibility plays a mediating role between executive academic experience and green innovation in manufacturing corporations; (4) environmental regulation positively moderates the relationship between executive academic experience and green innovation in manufacturing corporations, and both formal environmental regulation and informal environmental regulation positively moderated the promotion of green innovation in manufacturing corporations by executive academic experience.

The impact of international tourism on emerging markets has been overwhelmingly beneficial. Despite the obvious benefits of tourism, it comes at a high price for the environment in the form of pollution. Brazil's annual tourist influx has the potential to boost economic development and damage the country's ecosystems. The objective of this investigation is to analyze, using time series data ranging from 1990 to 2019, the effects of tourism and economic growth (GDP) on carbon dioxide (CO₂) emissions in Brazil. The stationarity of the data was examined by employing unit root tests, and an autoregressive distributed lag (ARDL) technique was used to investigate the link between the factors, taking both the long- and the short-run into consideration. This research shows that there are long-term and short-term ties between Brazil's tourism industry, GDP, and CO₂ emissions. Yet, both tourism and economic expansion have had serious negative effects on Brazil's ecology. These results indicate that in order to maintain environmental quality in Brazil, policymakers need to pursue more eco-friendly economic expansion as well as environmentally conscious tourist regulations.

In the UK, a concern of prejudice, as well as a lack of gender identity and sexual orientation documentation, implies that LGBT persons mostly hidden to health-care providers. One of a review was carried out to examine primary literature on the psychological support requirements of LGBT cancer patients when receive treatment and after. Important findings: Key topics that have been mentioned include the negative impact on mental health, health care professional education and the absence of inclusive support groups, the pervasiveness of discriminatory practices within healthcare services. The research demonstrates how LGBT cancer patients are being failed by healthcare professionals in terms of psychological support, resulting in unmet requirements. There are some suggestions use to guarantee an LGBT inclusive atmosphere in cancer care, as well as the development of support programmes for LGBT people with cancer. Practical connotation: LGBT wellness and awareness education should be offered for HCP personnel. The registration and tracking of gender identity and sexual orientation is critical to ensuring that LGBT persons are not 'invisible' in cancer, radiation, and continued studies. LGBT cancer groups and services should be established, since information from the study indicated that LGBT individuals are actively seeking these services.

This research investigates the determinants of women's empowerment within households in a developing country. The investigation specifically focuses on the impact of employment and fertility, considering constraints imposed by family rules that play a pivotal role in shaping women's empowerment. The theoretical framework outlined in this study posits a simplistic model demonstrating that, within the prevailing family structure and household composition, earned income and fertility may bear significant relevance. Utilizing data extracted from the Pakistan Social and Living Standards Measurement Survey, we engage in estimating the level of female empowerment, operationalized as the extent of female authority over household expenditures. Notably, our empirical approach accounts for the endogeneity of employment and fertility through a two-stage estimation process. This involves leveraging information on family rules—representative of a family's cultural norms—pertaining to work and childbearing. Our empirical findings affirm the viability of family-specific rules as instruments to estimate and subsequently predict employment and fertility. Importantly, the evidence gleaned underscores the critical role of selecting valid threat options in theoretical analyses of women's empowerment.

Protein S-nitrosylation (SNO), emerging as an important posttranslational modification, involves covalent addition of nitric oxide (NO) to the sulfur atom of cysteine in proteins. Accumulated evidence suggests that protein SNO plays crucial roles in pathophysiological mechanisms in cancer, which is attracting great attention. However, there are still controversies about whether S-nitrosylated proteins act as oncogenic proteins or tumor suppressors in cancer. In this review, we provide an overview of the early and latest evidence regarding the underlying mechanism and dual roles of SNO in cancer, in an effort to clarify its contribution in tumor progression. It has been well established that S-nitrosylated proteins restrain tumor progression in several types of cancer, while they have exhibited activities in promoting cell proliferation and inhibiting apoptosis in some other kinds of cancer. Interestingly, emerging evidence also has highlighted both its anti-cancer and pro-tumorigenic roles in several other cancer diseases. Finally, current limitations and future research prospects are presented. The overview of targeting SNO in cancer will provide new opportunities for drug development through in-depth exploration of SNO-mediated signaling pathways.

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.

Financial development and industrial structure optimization are two-wheeled engines for promoting high-quality development, but the causal identification of the two is still poorly understood. This paper addresses this research gap by comprehensively analyzing the relationship between them. Regional economic growth is a necessary condition for achieving high-quality development. Taking China as an example, this study empirically examines the role of financial development and industrial structure optimization in high-quality development using the entropy method, fixed effects, mediation effects and instrumental variable regression. The study results show that (i) financial development has actively promoted regional economic growth. (ii) The driving effect on the central and western regions is greater than that on the eastern region. (iii) There are differences in the mediating effect of industrial structure optimization and rationalization between different levels of financial development and economic growth. (iv) In addition, the mediating effect of industrial structure optimization is larger in the eastern region than in the central and western regions. (v) The mediating effect of industrial structure rationalization is not obvious in the eastern region, but has a masking effect in the central and western regions. Our findings provide new strategies for financial development and industrial structure optimization in developing countries.

As the underlying institutional design for enterprise risk management, it is important to study whether and how internal control affects enterprise technological innovation in the current context of increased economic policy uncertainty. Based on the principal-agent theory and information asymmetry theory, this paper explores the impact of internal control on corporate technological innovation using the listed company data from 2009-2019 CSMAR database, and obtains the following research conclusions: (1) the quality of internal control positively affects the corporate technological innovation. (2) The operational risk plays an intermediary role in the relationship between the internal control affecting the corporate technological innovation. (3) The degree of market competition positively moderates the impact of internal control on enterprise technological innovation. (4) Relative to non-stateowned enterprises and non-high-tech enterprises, the quality of internal control of state-owned enterprises and high-tech enterprises has a more significant impact on enterprise technological innovation. This paper enriches the consequences of the study of internal control on the one hand, and on the other hand, it provides a new perspective for improving technological innovation, and it provides certain guidance for further improving the level of corporate governance.

Nanomaterials have shown great potential in anti-tumor applications and are currently the focus of research. This review article aims to provide a comprehensive overview of the challenges encountered in oncology treatment and how nanomaterials are being utilized to overcome these obstacles. The authors discuss the limitations of conventional treatments, including limited efficacy, side effects, and toxicity issues. They highlight the importance of early tumour diagnosis and personalized treatment plans, as well as the need for innovative therapeutic approaches such as targeted therapy, immunotherapy, and gene therapy. The article primarily focuses on how nanomaterials can be engineered to achieve specific recognition and aggregation within tumour tissues through surface modifications involving targeting molecules such as antibodies, peptides, and receptor ligands. This surface modification technique facilitates improved targeting in the targeting of photodynamic therapy, while minimizing harm to normal tissues. The authors also discuss the potential and future prospects of nanomaterials in tumour therapy, including breakthroughs in their application, biosafety concerns, biocompatibility issues, preparation processes, clinical translation challenges, interdisciplinary cooperation, international exchange, relevant regulations and ethical guidelines. Overall, this review highlights the substantial potential of nanomaterials in oncology treatment, emphasizing the need for careful consideration of safety concerns to ensure their safe and effective application. The authors conclude that strengthening interdisciplinary cooperation and international exchange will contribute to the healthy development of nanomaterials in oncology treatment.

Credit scoring remains one of the most important subjects in financial risk management. Although the methods in this field have grown in sophistication, further improvements are necessary. These advances could translate in major gains for financial institutions and other companies that extend credit by diminishing the potential for losses in this process. This research seeks to compare statistical and artificial intelligence (AI) predictors in a credit risk analysis setting, namely the discriminant analysis, the logistic regression (LR), the artificial neural networks (ANNs), and the random forests. In order to perform this comparison, these methods are used to predict the default risk for a sample of companies that engage in trade credit. Pre-processing procedures are established, namely in the form of a proper sampling technique to assure the balance of the sample. Additionally, multicollinearity in the dataset is assessed via an analysis of the variance inflation factors (VIFs), and the presence of multivariate outliers is investigated with an algorithm based on robust Mahalanobis distances (MDs). After seeking the most beneficial architectures and/or settings for each predictor category, the final models are then compared in terms of several relevant key performance indicators (KPIs). The benchmarking analysis revealed that the artificial intelligence methods outperformed the statistical approaches.

A large body of research has been dedicated to the study of relationships between social or cultural capital and educational outcomes in Western countries. However, few studies have examined these associations in a Chinese context, and even fewer have examined the effects of both forms of capital on educational outcomes simultaneously within a familial context in China. This study offers a reformulation of the associations between family social capital and family cultural capital on the educational outcomes of adolescents in both rural and urban China. Using the structural equation modelling approach and the China Education Panel Survey, this study sheds some new insights – the presence of significant compositional differences in both family social capital and family cultural capital between rural and urban Chinese adolescents, and differential effects of both forms of capital on educational outcomes were found. Family social capital presented larger positive effects on the academic effort and educational aspiration of rural adolescents while having no positive effects in facilitating the academic achievement of both rural and urban adolescents. Meanwhile, family cultural capital presented larger positive effects for urban adolescents on all educational outcomes as compared to their rural counterparts.

Nanozyme with biomimetic enzyme activity has the advantages of good catalytic performance, high stability, and is not easily affected by temperature. However, the application of tumor microenvironment (TME) in the tumor is limited due to its low catalytic activity. Herein, a multifunctional nanozyme based on CuCoP with multivalent metal ions (Cu+/Cu2+ and Co2+/ Co3+) provides an innovative strategy for constructing acid-responsive cancer therapy. CuCoP has excellent photothermal properties (photothermal conversion efficiency of 66.9%) as well as glutathione (GSH) peroxidase activity and high photo-enhanced peroxidase-like (POD) enzyme activity in weak acid TME. CuCoP can consume the overexpressed GSH, thus alleviating the antioxidant capacity of the tumor, and reduces Cu2+/ Co3+ to Cu+/ Co 2+. Subsequently, the generated Cu+/Co2+ will react with endogenous H2O2 to generate cytotoxic hydroxyl radical (•OH), which have high catalytic efficiency in weakly acidic TME. Crucially, the synergistic effect of PTT and the cascade reaction of bimetallic atoms with GSH and H2O2 can effectively reduce antioxidant capacity, inhibit tumors and trigger effective immune cell death (ICD) process, which caused a strong immune response and inhibit tumor recurrence and metastasis. As a novel bimetallic sulfide nanoenzyme triggered by TME, CuCoP has great research value in cancer therapy.

This study compares return and volatility performance of exchange-traded funds (ETFs) with high-ESG (Environment, Social, and Governance) rating vs. low-ESG rating. The paper also examines time-series data predictability by identifying their positive dependence and volatility asymmetry properties, and examines the performance of two combinations of short-memory models i.e., autoregressive moving average and exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); autoregressive moving average and asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH) and two long-memory models, autoregressive moving average and fractionally integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIGARCH); and autoregressive fractionally-integrated moving average and asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-APARCH). The study found that low-ESG rating ETFs on average have slightly significant higher returns and also lower volatility compared to their high-ESG rating counterparts. Evidence of asymmetric volatility properties are also present on both high-ESG and low-ESG rating ETFs returns. The study also observed that for both high-ESG and low-ESG rating ETFs denote a stationarity, but non-invertible process in their returns. Results can provide fresh understanding in the topic of leverage effects and volatility that can open future research channels to academicians.