Entrepreneurship and Growth: Evidence from China

This paper examines the impact of entrepreneurship on economic growth by using a panel data set of 29 provinces in China over 20 years. Two indicators of entrepreneurship are defined and introduced into the traditional growth regression framework that is estimated using the system generalized method of moments. We also use the ratio of staff and workers of state-owned enterprises and per capita sown land area as the instrumental variables to identify the causal effect of entrepreneurship on economic growth. Our results suggest that entrepreneurship has a significant positive effect on economic growth and this finding is robust even after we control for other demographic and institutional variables. Our study provides some evidence that may be used as a basis for evaluating the effect of China’s policy on private business which has been increasingly relaxed since the late 1970s.

Optimum quantum resource distribution for phase measurement and quantum information tapping in a dual-beam SU(1,1) interferometer

Quantum entanglement is a resource in quantum metrology that can be distributed to two conjugate physical quantities for the enhancement of their measurement sensitivity. This is demonstrated in the joint measurement of phase and amplitude modulation signals in quantum dense metrology schemes. We can also devote all the quantum resource to phase measurement only, leading to the optimum sensitivity enhancement. In this paper, we experimentally implement a dual-beam sensing scheme in an SU(1,1) interferometer for the optimum quantum enhancement of phase measurement sensitivity. We demonstrate a 3.9-dB improvement in signal-to-noise ratio over the optimum classical method, and this is 3-dB better than the traditional single-beam scheme. Furthermore, such as cheme also realizes a quantum optical tap of quantum entangled fields and has the full advantages of an SU(1,1) interferometer, such as detection loss tolerance, making it more suitable for practical applications in quantum metrology and quantum information

Experimental Study on the Influence of Slickwater on Shale Permeability

There are two diametrically opposite views of the influence of slickwater on shale permeability among scholars at home and abroad. We used the shale outcrops rock samples from the Lower Silurian Longmaxi Formation in Sichuan Basin. The permeability of these dry samples before and after immersion in different solution systems were tested by pulse attenuation method. The experimental results show that the impregnation of different slickwater components and standard salt solution can promote the increase of the permeability of shale samples. The stress sensitivity of shale samples after liquid immersion is medium weak to weak. The sample stress sensitivity is weak after soaked by the synergist solution and Drag reducing agent solution, and the sensitivity of the sample stress is medium weak after immersed by the standard saline solution, defoamer solution and antiswelling solution; The Ki/K0 of the shale sample after liquid immersion on σi/σ0 is consistent with the exponential stress sensitive evaluation model. With the increase of soaking time, the increase of sample permeability increases first and then decreases

OpenFE: Automated Feature Generation beyond Expert-level Performance

The goal of automated feature generation is to liberate machine learning experts from the laborious task of manual feature generation, which is crucial for improving the learning performance of tabular data. The major challenge in automated feature generation is to efficiently and accurately identify useful features from a vast pool of candidate features. In this paper, we present OpenFE, an automated feature generation tool that provides competitive results against machine learning experts. OpenFE achieves efficiency and accuracy with two components: 1) a novel feature boosting method for accurately estimating the incremental performance of candidate features. 2) a feature-scoring framework for retrieving effective features from a large number of candidates through successive featurewise halving and feature importance attribution. Extensive experiments on seven benchmark datasets show that OpenFE outperforms existing baseline methods. We further evaluate OpenFE in two famous Kaggle competitions with thousands of data science teams participating. In one of the competitions, features generated by OpenFE with a simple baseline model can beat 99.3\% data science teams. In addition to the empirical results, we provide a theoretical perspective to show that feature generation is beneficial in a simple yet representative setting. The code is available at https://github.com/ZhangTP1996/OpenFE.Comment: 23 pages, 3 figure

Serum hsa-miR-98-5p and RORC may be new biomarkers related to esophageal cancer

This study aims to use bioinformatics methods to discover new serum miRNA markers for esophageal cancer, and provide a theoretical basis for early diagnosis of esophageal cancer. We used GEO2R to analyze the differential serum miRNAs in esophageal cancer based on GSE112264 from the GEO database. Then target genes of top 10 differential miRNAs were predicted. Obtain RNA-Seq data of esophageal cancer from the TCGA database, and use R software for analysis of differential expression. Overlap the predicted target genes with the differentially down-regulated genes, then perform analysis of GO and KEGG enrichment. Use GEPIA and UALCAN databases to perform verification of expression and prognostic analysis of key genes in the pathway. The results showed there are 2565 differential miRNAs in the serum of esophageal cancer patients. The top 10 up-regulated miRNAs predicted 1676 target genes, then 63 overlapped genes were obtained from target genes and 1642 down-regulated genes. GO enrichment obtained 14 biological processes, and KEGG enrichment obtained the circadian rhythm pathway. Only RORC is related to the poor prognosis of patients with esophageal cancer. Our study concluded serum hsa-miR-98-5p and its target gene RORC may be new biological markers for early diagnosis and treatment of esophageal cancer