The Public Distribution Systems of Foodgrains and Implications for Food Security: A Comparison of the Experiences of India and China

public distribution system, food security, poverty, food subsidy, India, China

Income Inequality in Rural China: Regression-based Decomposition Using Household Data

inequality decomposition, regression, income generating function, China

Electronic Structure and Linear Optical Properties of Sr2_{2}CuO2_{2}Cl2_{2} Studied from the First Principles Calculation

First-principles calculations with the full-potential linearized augmented plane-wave (FP-LAPW) method have been performed to investigate detailed electronic and linear optical properties of Sr$_{2}$CuO$_{2}$Cl$_{2}$, which is a classical low-dimensional antiferromagnet (AFM) charge transfer ({\it CT}) insulator. Within the local-spin-density approximation (LSDA) plus the on-site Coulomb interaction $U$ (LADA+$U$) added on Cu 3d orbitals, our calculated band gap and spin moments are well consistent with the experimental and other theoretical values. The energy dispersion relation agrees well with the angle resolved photoemission measurements. Its linear optical properties are calculated within the electric-dipole approximation. The absorption spectrum is found to agree well with the experimental result.Comment: 5 pages, 5 figure

Imprints of Schwinger Effect on Primordial Spectra

We study the Schwinger effect during inflation and its imprints on the primordial power spectrum and bispectrum. The produced charged particles by Schwinger effect during inflation can leave a unique angular dependence on the primordial spectra.Comment: 27 pages, 13 figures, JHEP accepted versio

Multi-Document Summarization via Discriminative Summary Reranking

Existing multi-document summarization systems usually rely on a specific summarization model (i.e., a summarization method with a specific parameter setting) to extract summaries for different document sets with different topics. However, according to our quantitative analysis, none of the existing summarization models can always produce high-quality summaries for different document sets, and even a summarization model with good overall performance may produce low-quality summaries for some document sets. On the contrary, a baseline summarization model may produce high-quality summaries for some document sets. Based on the above observations, we treat the summaries produced by different summarization models as candidate summaries, and then explore discriminative reranking techniques to identify high-quality summaries from the candidates for difference document sets. We propose to extract a set of candidate summaries for each document set based on an ILP framework, and then leverage Ranking SVM for summary reranking. Various useful features have been developed for the reranking process, including word-level features, sentence-level features and summary-level features. Evaluation results on the benchmark DUC datasets validate the efficacy and robustness of our proposed approach