Can carbon finance promote high quality economic development: evidence from China.

Utilizing provincial panel data from China spanning 2000 to 2020, this study constructed an indicator system for high-quality economic development by incorporating 35 indicators. These indicators stem from five domains: innovative, coordinated, green, open, and shared development. To assess carbon finance development, an evaluation system was created using twelve basic indicators derived from three categories: financial environment, energy efficiency, and scientific and technological progression. The entropy weight method facilitated the computation of indices such as the economic quality development, innovative development, coordinated development, green development, open development, shared development, and carbon finance development indices. Both static and dynamic panel models served to empirically ascertain the specific influence of carbon finance on high-quality economic development. Additionally, regional and temporal variances in carbon finance's impact on high-quality economic development were scrutinized. Findings indicate that provinces like Beijing, Shanghai, Jiangsu, and Guangdong, known for advanced economic development, exhibit elevated levels of high-quality economic and carbon finance development. Nonetheless, disparities among provinces are evident. While carbon finance significantly bolsters China's high-quality economic growth, its influence is not uniformly observed across all five development domains. It primarily augments coordinated, green, and shared development. Furthermore, the role of carbon finance in boosting China's high-quality economic development exhibits regional and temporal variations. The promotion of high-quality economic growth can be achieved by fostering an amenable carbon finance environment, addressing aging, maximizing governmental influence, enhancing transportation infrastructure, propelling new urbanization, and refining education standards.

The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones.

In the context of "space of flows", city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a large number of innovation resources. Here our report is to provide new ideas for improving the innovation capability of high-tech zones and accelerating the construction of Chinese high-quality innovation system. Here we take 142 cities with high-tech zones as research samples, and explore the characteristics and influencing factors of spatial network of city-based innovation correlation in China, through modified gravity modelsocial, network analysis and QAP analysis. The results show that city-based innovation network is not closely connected, the number of redundant connection channels is low efficiency, showing a four-level spatial pattern of "Z" shaped spindle. Among them, degree centrality of cities in eastern China is higher than that in the western region, the core cities in central China play a bridging role, and western remote cities are easily affected by related cities. Moreover, there are four innovation cohesion subgroups, including the northern hinterland subgroup, the eastern coastal subgroup, the southern subgroup and the western cooperation subgroup. Furthermore, the results of the influencing factors analysis show the differences in administrative level, economic development level, openness to the outside world, and investment in technology are conducive to the innovation association between cities, while the similarities in spatial adjacency and industrial structure will promote the strong innovation association between cities.

Research on the impact of inclusive finance on agricultural green development: Empirical analysis of China's main grain producing areas.

In order to study the impact of inclusive finance on agricultural green development, This paper uses both static panel and dynamic panel (system GMM model) estimation methods to make empirical analysis of the impact of inclusive financial development on agricultural green development. The results both find that there is a significant positive correlation between the level of inclusive financial development, real GDP per capita, the proportion of the added value of agriculture, forestry, animal husbandry and fishery in GDP and agricultural green development. This paper puts forward some countermeasures and suggestions to promote agricultural green development, including vigorously developing inclusive finance, promoting economic growth, promoting the development of agriculture, forestry, animal husbandry and fishery, and increasing environmental protection expenditures.

Modality alignment contrastive learning for severity assessment of COVID-19 from lung ultrasound and clinical information.

The outbreak of COVID-19 around the world has caused great pressure to the health care system, and many efforts have been devoted to artificial intelligence (AI)-based analysis of CT and chest X-ray images to help alleviate the shortage of radiologists and improve the diagnosis efficiency. However, only a few works focus on AI-based lung ultrasound (LUS) analysis in spite of its significant role in COVID-19. In this work, we aim to propose a novel method for severity assessment of COVID-19 patients from LUS and clinical information. Great challenges exist regarding the heterogeneous data, multi-modality information, and highly nonlinear mapping. To overcome these challenges, we first propose a dual-level supervised multiple instance learning module (DSA-MIL) to effectively combine the zone-level representations into patient-level representations. Then a novel modality alignment contrastive learning module (MA-CLR) is presented to combine representations of the two modalities, LUS and clinical information, by matching the two spaces while keeping the discriminative features. To train the nonlinear mapping, a staged representation transfer (SRT) strategy is introduced to maximumly leverage the semantic and discriminative information from the training data. We trained the model with LUS data of 233 patients, and validated it with 80 patients. Our method can effectively combine the two modalities and achieve accuracy of 75.0% for 4-level patient severity assessment, and 87.5% for the binary severe/non-severe identification. Besides, our method also provides interpretation of the severity assessment by grading each of the lung zone (with accuracy of 85.28%) and identifying the pathological patterns of each lung zone. Our method has a great potential in real clinical practice for COVID-19 patients, especially for pregnant women and children, in aspects of progress monitoring, prognosis stratification, and patient management.

The impact of the inclusive financial development index on farmer entrepreneurship.

Based on the calculation of the inclusive financial development level of 22 provinces and 4 municipalities in China from 2004 to 2017, this paper uses the Kernel density estimation method to further analyze the evolution of the inclusive financial index. Based on the above analysis, we make empirical analysis of the impact of China's inclusive financial inclusion development index on farmers' entrepreneurship using static panel and dynamic panel estimation method. The empirical conclusions show that there are certain differences in inclusive financial inclusion development level in various provinces in China. Improving the inclusion development level of inclusive finance can better promote farmers' entrepreneurship. Urbanization level, economic openness and regional economic development level have a significant positive effect on farmers' entrepreneurship, while farmers' income and education level have a significant negative effect on farmers' entrepreneurship. It is possible to promote farmers' entrepreneurship by improving the inclusive development level of inclusive finance, combining urbanization, increasing government investment in productive fixed assets, increasing economic openness and improving regional economic development.

The long-term effect of community-based health management on the elderly with type 2 diabetes by the Markov modeling.

The aim of this study was to assess the long-term effects of community-based health management on elderly diabetic patients using a Markov model. A Markov decision model was used to simulate the natural history of diabetes. Data were obtained from our randomized trials of elderly with type 2 diabetes and from the published literature. One hundred elderly patients with type 2 diabetes were randomly allocated to either the management or the control group in a one-to-one ratio. The management group participated in a health management program for 18 months in addition to receiving usual care. The control group only received usual care. Measurements were performed on both groups at baseline and after 18 months. The Markov model predicted that for every 1000 diabetic patients receiving health management, approximately 123 diabetic patients would avoid complications, and approximately 37 would avoid death over the next 13 years. The results suggest that the health management program had a positive long-term effect on the health of elderly diabetic patients. The Markov model appears to be useful in health care planning and decision-making aimed at reducing the financial and social burden of diabetes.

Stock volatility as a risk factor for coronary heart disease death.

AIMS: The volatility of financial markets may cause substantial emotional and physical stress among investors. We hypothesize that this may have adverse effects on cardiovascular health. The Chinese stock markets were extremely volatile between 2006 and 2008. We, therefore, examined the relationship between daily change of the Shanghai Stock Exchange (SSE) Composite Index (referred as the Index) and coronary heart disease (CHD) deaths from 1 January 2006 to 31 December 2008 in Shanghai, the financial capital of China. METHODS AND RESULTS: Daily death and stock performance data were collected from the Shanghai Center for Disease Control and Prevention and SSE, respectively. Data were analysed with over-dispersed generalized linear Poisson models, controlling for long-term and seasonal trends of CHD mortality, day of the week, Index closing value, weather conditions, and air pollution levels. We observed a U-shaped relationship between the Index change and CHD deaths: both rising and falling of the Index were associated with more deaths and the fewest deaths coincided with little or no change of the index. We also examined the absolute daily change of the Index in relation to CHD deaths: in a 1-day lag model, each 100-point change of the Index corresponded to 5.17% (95% confidence interval: 1.71, 8.63%) increase in CHD deaths. Further analysis showed that the association was stronger for out-of-hospital CHD death than for in-hospital death. CONCLUSION: We found that CHD deaths fluctuated with daily stock changes in Shanghai, suggesting that stock volatility may adversely affect cardiovascular health.