Cognitive abilities, insurance decisions, and labor supply behavior: evidence from rural China

IntroductionHow cognitive abilities affect financial and economic decision is an important issue that has attracted the attention of economics.MethodThis paper uses the China Family Panel Studies (CFPS) 2010, 2014, and 2018 survey data to empirically test the impact of cognitive skills on the insurance participation decisions in rural China.Results and discussionThe results show that higher word ability is correlated to higher social health insurance participation and both word and math ability leads to higher social pension participation. Mechanism analysis reveals that individuals with higher cognitive skills are more likely to be affected by peers in insurance decision, and higher cognitive skills increase personal income that enables them to enroll in the social insurance. Further investigation of labor supply behavior suggests that while cognitive skills positively affect non-agricultural labor participation, cognitive skills amplify the negative effect of social security on labor supply

Filling the Image Information Gap for VQA: Prompting Large Language Models to Proactively Ask Questions

Large Language Models (LLMs) demonstrate impressive reasoning ability and the maintenance of world knowledge not only in natural language tasks, but also in some vision-language tasks such as open-domain knowledge-based visual question answering (OK-VQA). As images are invisible to LLMs, researchers convert images to text to engage LLMs into the visual question reasoning procedure. This leads to discrepancies between images and their textual representations presented to LLMs, which consequently impedes final reasoning performance. To fill the information gap and better leverage the reasoning capability, we design a framework that enables LLMs to proactively ask relevant questions to unveil more details in the image, along with filters for refining the generated information. We validate our idea on OK-VQA and A-OKVQA. Our method continuously boosts the performance of baselines methods by an average gain of 2.15% on OK-VQA, and achieves consistent improvements across different LLMs.Comment: Accepted to EMNLP2023 Finding

A bioinformatics approach to the identification of hub genes of Huo Xin Pill (HXP) for the treatment of acute myocardial infarction

Purpose: To apply bioinformatics for the identification of potential genes associated with Huo Xin Pill (HXP), a traditional Chinese medicine (TCM) used for the treatment of acute myocardial infarction AMI).Methods: Mouse AMI expression profile dataset GSE153485 and HXP-treated mouse AMI expression profile dataset GSE147365 were downloaded from GEO database. Then, R software was used to screen differentially-expressed genes in AMI and differentially-expressed genes in HXP-treated AMI. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, Venn diagrams, and protein-protein interaction (PPI) analysis were carried out on the hub genes linked to the effect of HXP on AMI.Results: Six hub genes were identified. Based on the differential analysis of the sham and AMI groups, GSE153485 and GSE147365 had 840 and 2116 differentially-expressed genes, respectively (p < 0.05). The GO and KEGG analyses revealed enrichments in actin filament organization, membrane repolarization, and regulation of the actin cytoskeleton. Differential analysis of the use of HXP on AMI showed that GSE147365 had 380 differentially-expressed genes, comprising 96 up-regulated genes and 284 down-regulated genes (p < 0.05). Thirteen potential acting target genes were obtained using a enn diagram, while 6 key acting genes were obtained via final screening.Conclusion: Six (6) hub genes linked to HXP and AMI have been identified using bioinformatics: Egr2, Tubb2a, Col4a2, Cnn2, Lmna, and Col4a1. This study provides a partial experimental basis for the use of HXP in the treatment of AMI. In addition, it provides new potential targets for the treatment of AMI

CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction

Recent advances in neural reconstruction using posed image sequences have made remarkable progress. However, due to the lack of depth information, existing volumetric-based techniques simply duplicate 2D image features of the object surface along the entire camera ray. We contend this duplication introduces noise in empty and occluded spaces, posing challenges for producing high-quality 3D geometry. Drawing inspiration from traditional multi-view stereo methods, we propose an end-to-end 3D neural reconstruction framework CVRecon, designed to exploit the rich geometric embedding in the cost volumes to facilitate 3D geometric feature learning. Furthermore, we present Ray-contextual Compensated Cost Volume (RCCV), a novel 3D geometric feature representation that encodes view-dependent information with improved integrity and robustness. Through comprehensive experiments, we demonstrate that our approach significantly improves the reconstruction quality in various metrics and recovers clear fine details of the 3D geometries. Our extensive ablation studies provide insights into the development of effective 3D geometric feature learning schemes. Project page: https://cvrecon.ziyue.cool

An Analysis of the Principles in Formulation and Implementation of University Constitution from the Perspective of the Spirit of Law

Under the background of university constitution construction,the formulation and implementation of the university constitution need to be divided into three parts, the legal effect,the regulatory mechanism,the power inside and outside of the university and the legal relationship, these three areas need further improvement. This paper will analyze the principles of university constitution from three aspects: constitution formulation, rights and interests protection and procedure implementation conditions