Shanghai Jiao Tong University

About: Shanghai Jiao Tong University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Population & Cancer. The organization has 157524 authors who have published 184620 publications receiving 3451038 citations. The organization is also known as: Shanghai Communications University & Shanghai Jiaotong University.

Trade-Off and Pecking Order Theories of Debt

Abstract: Taxes, bankruptcy costs, transactions costs, adverse selection, and agency conflicts have all been advocated as major explanations for the corporate use of debt financing. These ideas have often been synthesized into the trade-off theory and the pecking order theory of leverage. These theories and the related evidence are reviewed in this survey. A number of important empirical stylized facts are identified. To understand the evidence, it is important to recognize the differences among private firms, small public firms and large public firms. Private firms seem to use retained earnings and bank debt heavily. Small public firms make active use of equity financing. Large public firms primarily use retained earnings and corporate bonds. The available evidence can be interpreted in several ways. Direct transaction costs and indirect bankruptcy costs appear to play important roles in a firm's choice of debt. The relative importance of the other factors remains open to debate. No currently available model appears capable of simultaneously accounting for all of the stylized facts.

Sparse whole-genome sequencing identifies two loci for major depressive disorder

Abstract: Genomic analysis of 5,303 Chinese women with recurrent major depressive disorder (MDD) enables the identification and replication of two genome-wide significant loci contributing to risk of MDD on chromosome 10: one near the SIRT1 gene; the other in an intron of the LHPP gene.

RACE: Large-scale ReAding Comprehension Dataset From Examinations

Abstract: We present RACE, a new dataset for benchmark evaluation of methods in the reading comprehension task. Collected from the English exams for middle and high school Chinese students in the age range between 12 to 18, RACE consists of near 28,000 passages and near 100,000 questions generated by human experts (English instructors), and covers a variety of topics which are carefully designed for evaluating the students’ ability in understanding and reasoning. In particular, the proportion of questions that requires reasoning is much larger in RACE than that in other benchmark datasets for reading comprehension, and there is a significant gap between the performance of the state-of-the-art models (43%) and the ceiling human performance (95%). We hope this new dataset can serve as a valuable resource for research and evaluation in machine comprehension. The dataset is freely available at http://www.cs.cmu.edu/~glai1/data/race/and the code is available at https://github.com/qizhex/RACE_AR_baselines.