Income Distribution and Public Transfers as Social Safety Nets in Korea

Using 5-year balanced household panel data, this paper shows that the inequality of per capita income in Korea aggravated during the financial crisis in 1998. The decomposition analysis of income inequality by factor component shows that the dominant positive effect on the income inequality is by the asset income. Next is the wage income, followed by the other income. Furthermore, this paper shows that social safety net programs were not yet in place during the initial period of the crisis. Public transfers were not effective social safety net devices and did not contribute in decreasing income inequality. Private transfers, on the other hand, were effective devices and narrowed the disparity in household income.

Electron and phonon band-structure calculations for the antipolar SrPt3_{3}P antiperovskite superconductor: Evidence of low-energy two-dimensional phonons

SrPt3P has recently been reported to exhibit superconductivity with Tc = 8.4 K. To explore its superconducting mechanism, we have performed electron and phonon band calculations based on the density functional theory, and found that the superconductivity in SrPt3P is well described by the strong coupling phonon-mediated mechanism. We have demonstrated that superconducting charge carriers come from pd\pi-hybridized bands between Pt and P ions, which couple to low energy (~ 5 meV) phonon modes confined on the ab in-plane. These in-plane phonon modes, which do not break antipolar nature of SrPt3P, enhance both the electron-phonon coupling constant \lambda and the critical temperature Tc. There is no hint of a specific phonon softening feature in the phonon dispersion, and the effect of the spin-orbit coupling on the superconductivity is found to be negligible.Comment: 5 pages, 5 figures, 1 tabl

Interfacial chemical bonding-mediated ionic resistive switching.

In this paper, we present a unique resistive switching (RS) mechanism study of Pt/TiO2/Pt cell, one of the most widely studied RS system, by focusing on the role of interfacial bonding at the active TiO2-Pt interface, as opposed to a physico-chemical change within the RS film. This study was enabled by the use of a non-conventional scanning probe-based setup. The nanoscale cell is formed by bringing a Pt/TiO2-coated atomic force microscope tip into contact with a flat substrate coated with Pt. The study reveals that electrical resistance and interfacial bonding status are highly coupled together. An oxygen-mediated chemical bonding at the active interface between TiO2 and Pt is a necessary condition for a non-polar low-resistance state, and a reset switching process disconnects the chemical bonding. Bipolar switching mode did not involve the chemical bonding. The nature of chemical bonding at the TiO2-metal interface is further studied by density functional theory calculations

Continuous Decomposition of Granularity for Neural Paraphrase Generation

While Transformers have had significant success in paragraph generation, they treat sentences as linear sequences of tokens and often neglect their hierarchical information. Prior work has shown that decomposing the levels of granularity~(e.g., word, phrase, or sentence) for input tokens has produced substantial improvements, suggesting the possibility of enhancing Transformers via more fine-grained modeling of granularity. In this work, we propose a continuous decomposition of granularity for neural paraphrase generation (C-DNPG). In order to efficiently incorporate granularity into sentence encoding, C-DNPG introduces a granularity-aware attention (GA-Attention) mechanism which extends the multi-head self-attention with: 1) a granularity head that automatically infers the hierarchical structure of a sentence by neurally estimating the granularity level of each input token; and 2) two novel attention masks, namely, granularity resonance and granularity scope, to efficiently encode granularity into attention. Experiments on two benchmarks, including Quora question pairs and Twitter URLs have shown that C-DNPG outperforms baseline models by a remarkable margin and achieves state-of-the-art results in terms of many metrics. Qualitative analysis reveals that C-DNPG indeed captures fine-grained levels of granularity with effectiveness.Comment: Accepted to be published in COLING 202