Dynamic network model of banking system stability

This paper presents a dynamic model of banking interactions, which uses interbank connections to study the stability of the banking system. The dynamic model extends previous work on network models of the banking system taking inspiration from large scale, complex, interconnected systems studied within the domain of engineering. The banking system is represented as a network where nodes are individual banks and the links between any two banks consist of interbank loans and borrowing. The dynamic structure of the model is represented as a set of differential equations, which, to the best of our knowledge, is an original characteristic of our approach. This dynamic structure not only allows us to analyse systemic risk but also to incorporate an analysis of control mechanisms. Uncertainty is introduced in the system by applying stochastic shocks to the bank deposits, which are assigned as an exogenous signal. The behaviour of the system can be analysed for different initial conditions and parameter sets. This paper shows some preliminary results under different combinations of bank reserve ratios, bank capital sizes and different degrees of bank inter-connectedness. The results show that both reserve ratio and link rate have a positive effect on the stability of the system in the presence of moderate shocks. However, for high values of the shocks, high reserve ratios may have a detrimental effect on the survival of banks. In future work, we will apply strategies from the domain of control engineering to the dynamic model to characterise more formally the stability of the banking network

How do digital lives affect resident mental health in the digital era? Empirical evidence based on Chinese general social survey

Having good mental health means we are better able to connect, function, cope and thrive. The widespread application of digital technology in daily life provides new ways and promising tools for residents to maintain their mental health. Given the importance of mental health for everyone, and the fact that mental health problems are prevalent worldwide, this study discusses how digital lives affects the mental health of residents. The results suggest that digital lives are significantly and positively associated with mental health. Mechanisms analysis identifies personal perceptions (self-rated physical exercise and subjective wellbeing) as the important paths for digital lives to promote mental health, while social perceptions (social trust and social fairness) play a suppressing effect on the relationship between them. The results of further discussion show that the degree of the influence of digital lives on mental health of individuals is heterogeneous among different regions. Due to the difference in development level, the positive impact of digital lives is greater in urban areas than in rural areas, and it is stronger in western regions than in eastern and central regions. This study enriches the nascent research stream of digitalization, explores new paths of harnessing digital technologies for mental health, and offers useful insights for the government to guide them in formulating digital development strategies and achieving the Healthy China Strategy

Study of the Banking System's Stability Using Control Theory

The 2007-2009 financial meltdown reflected the failure of the regulators to address financial fragility and it has clearly showed that regulating banks on an individual basis was an ineffective approach to prevent financial crises. Before the crisis, financial regulation was primarily focused on managing the risk of individual banks by requiring them to keep sufficient reserves to safeguard themselves from the inherent risk of their own investments. Since they ignored the risks that are generated by links between the banks, i.e. interbank borrowing and lending, a failure in a small number of banks could spread to other banks, and cause the paralysis of the whole banking system. Therefore, there is the need to give special emphasis to systemic risk, rather than consider the risk at an individual level. From an academic research point of view, the 2007-2009 financial crisis renewed the interest in finding new ways of studying financial systems. More specifically, since then new modelling frameworks have been proposed that incorporate the interconnected nature of the banking system. Network models have been used to investigate the stability of the banking system under different conditions, e.g. different banks' size and connectivity. This thesis proposes a new dynamic network model based on ordinary differential equations, which represents the banking system and seeks to interface the network model approach with control engineering. Control theory is an interdisciplinary branch of engineering, which is used to study the behaviour of dynamical systems, and how their behaviour can be modified by feedback mechanisms to achieve a desirable performance. In this work control theory is applied for the first time to analyse a model of the banking system and to propose feedback mechanisms, which preserve the stability of the system and that can ultimately inform financial regulators

Are Large Language Models Good Fact Checkers: A Preliminary Study

Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as superior in handling various natural language processing tasks compared to other language models. In this paper, we present a preliminary investigation into the potential of LLMs in fact-checking. This study aims to comprehensively evaluate various LLMs in tackling specific fact-checking subtasks, systematically evaluating their capabilities, and conducting a comparative analysis of their performance against pre-trained and state-of-the-art low-parameter models. Experiments demonstrate that LLMs achieve competitive performance compared to other small models in most scenarios. However, they encounter challenges in effectively handling Chinese fact verification and the entirety of the fact-checking pipeline due to language inconsistencies and hallucinations. These findings underscore the need for further exploration and research to enhance the proficiency of LLMs as reliable fact-checkers, unveiling the potential capability of LLMs and the possible challenges in fact-checking tasks

S3C: Semi-Supervised VQA Natural Language Explanation via Self-Critical Learning

VQA Natural Language Explanation (VQA-NLE) task aims to explain the decision-making process of VQA models in natural language. Unlike traditional attention or gradient analysis, free-text rationales can be easier to understand and gain users' trust. Existing methods mostly use post-hoc or self-rationalization models to obtain a plausible explanation. However, these frameworks are bottlenecked by the following challenges: 1) the reasoning process cannot be faithfully responded to and suffer from the problem of logical inconsistency. 2) Human-annotated explanations are expensive and time-consuming to collect. In this paper, we propose a new Semi-Supervised VQA-NLE via Self-Critical Learning (S3C), which evaluates the candidate explanations by answering rewards to improve the logical consistency between answers and rationales. With a semi-supervised learning framework, the S3C can benefit from a tremendous amount of samples without human-annotated explanations. A large number of automatic measures and human evaluations all show the effectiveness of our method. Meanwhile, the framework achieves a new state-of-the-art performance on the two VQA-NLE datasets.Comment: CVPR202

Spatial distribution of tuberculosis and its association with meteorological factors in mainland China

BACKGROUND: The incidence of tuberculosis (TB) remains high worldwide. Current strategies will not eradicate TB by 2035; instead, by 2182 is more likely. Therefore, it is urgent that new risk factors be identified. METHODS: An ecological study was conducted in 340 prefectures in China from 2005 to 2015. The spatial distribution of TB incidence was shown by clustering and hotspot analysis. The relationship between the distribution patterns and six meteorological factors was evaluated by the geographically weighted regression (GWR) model. RESULTS: During the 11 years of the study period, TB incidence was persistently low in the east and high in the west. Local coefficients from the GWR model showed a positive correlation between TB incidence and yearly average rainfall (AR) but a negative correlation with other meteorological factors. Average relative humidity (ARH) was negatively correlated with the incidence of TB in all prefectures (p \u3c 0.05). CONCLUSION: Meteorological factors may play an important role in the prevention and control of TB

Causal associations between COVID-19 and atrial fibrillation: A bidirectional Mendelian randomization study

Background and aims: Observational studies showed that coronavirus disease (2019) (COVID-19) attacks universally and its most menacing progression uniquely endangers the elderly with cardiovascular disease (CVD). The causal association between COVID-19 infection or its severity and susceptibility of atrial fibrillation (AF) remains unknown. Methods and results: The bidirectional causal relationship between COVID-19 (including COVID-19, hospitalized COVID-19 compared with not hospitalized COVID-19, hospitalized COVID-19 compared with the general population, and severe COVID-19) and AF are determined by using two-sample Mendelian randomization (MR) analysis. Genetically predicted severe COVID-19 was not significantly associated with the risk of AF [odds ratio (OR), 1.037; 95% confidence interval (CI), 1.005–1.071; P = 0.023, q = 0.115]. In addition, genetically predicted AF was also not causally associated with severe COVID-19 (OR, 0.993; 95% CI, 0.888–1.111; P = 0.905, q = 0.905). There was no evidence to support the association between genetically determined COVID-19 and the risk of AF (OR, 1.111; 95% CI, 0.971–1.272; P = 0.127, q = 0.318), and vice versa (OR, 1.016; 95% CI, 0.976–1.058; P = 0.430, q = 0.851). Besides, no significant association was observed for hospitalized COVID-19 with AF. MR-Egger analysis indicated no evidence of directional pleiotropy. Conclusion: Overall, this MR study provides no clear evidence that COVID-19 is causally associated with the risk of AF

Vascular endothelial growth factor and the risk of venous thromboembolism: A genetic correlation and two-sample Mendelian randomization study

Background: The relationship between vascular endothelial growth factor (VEGF) and the risk of venous thromboembolism (VTE) has always been one of the concerns in the medical field. However, the causal inferences from published observational studies on this issue may be affected by confounders or reverse causality. We performed a two-sample bidirectional Mendelian randomization (MR) to infer the associations between VEGF and VTE. Methods: Summary statistics from genome-wide association studies (GWAS) for VEGF and VTE were obtained from published meta-analysis studies and the FinnGen consortium, respectively. Independent genetic variables significantly associated with exposure were selected as instrumental variables. Linkage disequilibrium score regression (LDSC) and five robust MR analytical approaches were conducted to estimate the genetic correlations and causal inference. The MR-Egger intercept, Cochran’s Q, and MR pleiotropy residual sum and outlier (MR-PRESSO) were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on outcomes. Notably, replication analyses were performed using different subgroups of VTE. Results: LDSC failed to identify genetic correlations between VEGF and VTE. Based on 9 SNPs, the circulating VEGF level was positively related to the risk of VTE using inverse variance weighting (IVW) method (odds ratio (OR) = 1.064, 95 % confidence interval (CI), 1.009 – 1.122). Reverse MR analyses showed that genetic liability for VTE was not associated with increased VEGF level (β = -0.021, 95 % CI, -0.087-0.045). Pleiotropy-robust methods indicated no bias in any estimates. Conclusions: Our findings failed to detect coheritability between VEGF and VTE. The suggestive positive effect of the higher VEGF level on the VTE risk may have clinical implications, suggesting that VEGF as a possible predictor and therapeutic target for VTE prevention need to be further warranted

Plant-based diets and body composition in Chinese omnivorous children aged 6–9 years old: A cross-sectional study

Evidence suggests that plant-based diets are beneficial for alleviating metabolic diseases. Childhood is a crucial period for body growth and development. However, it is unknown whether adherence to a plant-based diet is related to a healthy body composition in children. We aimed to assess the relationship between a plant-based diet and body composition in children. A total of 452 Chinese children aged 6–9 years old participated in this cross-sectional study. Lean mass (LM), fat mass, and fat mass percentage (FMP) were assessed via dual-energy X-ray absorptiometry. An age- and sex-specific abdominal FMP ≥85th percentile was defined as abdominal obesity. Handgrip strength was measured using a hydraulic hand dynamometer. A validated 79-item food frequency questionnaire was used to collect dietary information. Overall plant-based diet index (PDI), healthful plant-based diet index (hPDI), and unhealthful plant-based diet index (uPDI) scores were calculated. After adjusting for potential covariates, a higher hPDI score (per 10-score increment) was associated with a higher LM in the android area (0.038 kg, 3.2%), gynoid area (0.048 kg, 1.9%), and trunk (0.102 kg, 1.2%) and with a lower FMP (1.18%) in the android area. In contrast, a higher uPDI score (per 10-score increment) was associated with a lower LM in the trunk (0.091 kg, 1.1%) and android area (0.023 kg, 1.9%) and with a higher FMP (0.74%) in the android area. No significant associations were observed between the overall PDI and body composition or abdominal obesity. After stratifying by sex, higher (vs. lower) hPDI scores was associated with lower abdominal obesity risk in girls and higher handgrip strength in boys. In conclusion, in this cross-sectional study, we found that stronger adherence to a healthful plant-based diet, and less adherence to an unhealthful plant-based diet was associated with better body composition in Chinese omnivorous children aged 6–9 years old. Our results highlight the need to distinguish between healthy and unhealthy plant foods within investigating how to obtain a healthy body composition in children