Investigate the Λ\Lambda and Λˉ\bar{\Lambda} polarization splitting effect with combined mechanisms

The significant splitting of $\Lambda$ and $\bar{\Lambda}$ polarization measured in STAR's Au+Au 7.7GeV collisions seems to be huge and unable to be described satisfactorily by any single mechanism, thus we revisit and combine there different mechanisms together on the basis of our PICR hydrodynamic model, to explain the experimental data. The three mechanisms, i.e. the meson field mechanism, the freeze-out space-time mechanism, and the QGP's magnetic field mechanism, lie on different stage of high energy collisions, and thus are not contradicted with each other. We find that the meson field mechanism is dominat, while the QGP's magnetic field mechanism is rather trivial, and freeze-out time effect is restricted by the small FZ time difference, leading to a hierarchy of $\Delta P_J \gg \Delta P_t \gg \Delta P_m$. Besides, the combination of different mechanisms could promote the mean value of polarization splitting from about 3\%-4\% to 4.5\%, which is more close to the experimental measured mean value of 5.8\%

Research on the Status Quo of Entrepreneurship and Policy Support System of Returning College Students Under the Background of Rural Revitalization Strategy:Based on Research in Zhejiang Province

In recent times, the proportion of college students returning to their hometowns to start businesses has increased year by year, but the success rate of college students returning to their hometowns to start a business is not impressive. Based on questionnaire surveys and case interviews of college students who have returned to start a business in Zhejiang Province, this article finds that the financing loan policy for college students to return to their hometown to start a business is not yet sound, and the policy supply is out of balance with actual demand; the application conditions and approval process for entrepreneurial subsidies are complicated and it is difficult to obtain subsidies. The satisfaction of entrepreneurs in townships is low; the entrepreneurs who return to their hometowns of college students have little understanding of the content of various policies, and the government does not promote the policies in place. In this regard, it is necessary to increase policy publicity and expand the scope of policy influence, establish financial credit support policies that meet the actual needs of returning home entrepreneurs college students, broaden financing channels, improve entrepreneurship training systems, improve entrepreneurship environment and enhance return home entrepreneurship college students’ satisfaction. Keywords:Rural revitalization,College Students,Return home to start a business,Entrepreneurship policy. DOI: 10.7176/EJBM/12-23-01 Publication date:August 31st 2020

Compromise and Coordination: An Experimental Study

This paper experimentally studies the role of a compromise option in a repeated battle-of-the-sexes game. We find that in a random-matching environment, compromise serves as an effective focal point and facilitates coordination, but fails to improve efficiency. However, in a fixed-partnership environment, compromise deters subjects from learning to play alternation, a more efficient but also more complex strategy. As a result, compromise hurts efficiency in the long-run by allowing subjects to coordinate on the less efficient outcome. We explore various behavioral mechanisms and suggest that people may fail to use an equal and efficient strategy if such a strategy is complex

Compromise and Coordination: An Experimental Study

This paper experimentally studies the role of a compromise option in a repeated battle-of-the-sexes game. We find that in a random-matching environment, compromise serves as an effective focal point and facilitates coordination, but fails to improve efficiency. However, in a fixed-partnership environment, compromise deters subjects from learning to play alternation, a more efficient but also more complex strategy. As a result, compromise hurts efficiency in the long-run by allowing subjects to coordinate on the less efficient outcome. We explore various behavioral mechanisms and suggest that people may fail to use an equal and efficient strategy if such a strategy is complex

LLM4DyG: Can Large Language Models Solve Problems on Dynamic Graphs?

In an era marked by the increasing adoption of Large Language Models (LLMs) for various tasks, there is a growing focus on exploring LLMs' capabilities in handling web data, particularly graph data. Dynamic graphs, which capture temporal network evolution patterns, are ubiquitous in real-world web data. Evaluating LLMs' competence in understanding spatial-temporal information on dynamic graphs is essential for their adoption in web applications, which remains unexplored in the literature. In this paper, we bridge the gap via proposing to evaluate LLMs' spatial-temporal understanding abilities on dynamic graphs, to the best of our knowledge, for the first time. Specifically, we propose the LLM4DyG benchmark, which includes nine specially designed tasks considering the capability evaluation of LLMs from both temporal and spatial dimensions. Then, we conduct extensive experiments to analyze the impacts of different data generators, data statistics, prompting techniques, and LLMs on the model performance. Finally, we propose Disentangled Spatial-Temporal Thoughts (DST2) for LLMs on dynamic graphs to enhance LLMs' spatial-temporal understanding abilities. Our main observations are: 1) LLMs have preliminary spatial-temporal understanding abilities on dynamic graphs, 2) Dynamic graph tasks show increasing difficulties for LLMs as the graph size and density increase, while not sensitive to the time span and data generation mechanism, 3) the proposed DST2 prompting method can help to improve LLMs' spatial-temporal understanding abilities on dynamic graphs for most tasks. The data and codes will be open-sourced at publication time

An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model

The paper selects the daily trading data of three stocks in the agricultural sector of the Chinese stock market from 1st September 2015 to 31st August 2021. It uses the DCC-GARCH model to study the correlation between these stocks to examine the volatility and conductivity of their risks. The results show that the correlation between the Shanghai Composite Index and stocks of agriculture of China exhibits time-varying characteristics and dynamic. The fluctuations in correlation are large. This study fills the blank of comparative study on risk volatility and correlation between different stocks in the same stock market by using DCC-GARCH mode

An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model

The paper selects the daily trading data of three stocks in the agricultural sector of the Chinese stock market from 1st September 2015 to 31st August 2021. It uses the DCC-GARCH model to study the correlation between these stocks to examine the volatility and conductivity of their risks. The results show that the correlation between the Shanghai Composite Index and stocks of agriculture of China exhibits time-varying characteristics and dynamic. The fluctuations in correlation are large. This study fills the blank of comparative study on risk volatility and correlation between different stocks in the same stock market by using DCC-GARCH mode

Association between blood heavy metal exposure levels and risk of metabolic dysfunction associated fatty liver disease in adults: 2015–2020 NHANES large cross-sectional study

BackgroundThe relationships between heavy metals and fatty liver, especially the threshold values, have not been fully elucidated. The objective of this research was to further investigate the correlation between blood heavy metal exposures and the risk of Metabolic dysfunction Associated Fatty Liver Disease (MAFLD) in adults.MethodsLaboratory data on blood metal exposure levels were obtained from National Health and Nutrition Examination Survey (NHANES) data for the period 2015 to 2020 for a cross-sectional study in adults. Associations between blood levels of common heavy metals and the risk of MAFLD in adults were analyzed using multifactorial logistic regression and ranked for heavy metal importance using a random forest model. Finally, thresholds for important heavy metals were calculated using piecewise linear regression model.ResultsIn a multifactorial logistic regression model, we found that elevated levels of selenium (Se) and manganese (Mn) blood exposure were strongly associated with the risk of MAFLD in adults. The random forest model importance ranking also found that Se and Mn blood exposure levels were in the top two positions of importance for the risk of disease in adults. The restricted cubic spline suggested a non-linear relationship between Se and Mn blood exposure and adult risk of disease. The OR (95% CI) for MAFLD prevalence was 3.936 (2.631–5.887) for every 1 unit increase in Log Mn until serum Mn levels rose to the turning point (Log Mn = 1.10, Mn = 12.61 μg/L). This correlation was not significant (p > 0.05) after serum Mn levels rose to the turning point. A similar phenomenon was observed for serum Se levels, with a turning point of (Log Se = 2.30, Se = 199.55 μg/L).ConclusionBlood heavy metals, especially Se and Mn, are significantly associated with MAFLD in adults. They have a non-linear relationship with a clear threshold