Impact of Zhengzhou Subway System on Adjacent Migrant Neighborhoods

Subway has advantages of large capacity, fast speed, punctuality, less pollution, low energy consumption and so on. It has become a chief means of public transportation and an important approach to solve the traffic problems in big cities. The purpose of this research is to investigate the impacts of the new subway lines (Line 1 and Line 2) in Zhengzhou on adjacent migrant neighborhoods. To study the impacts of Zhengzhou subway system, I conducted door-to-door surveys and interviews on household level in the two target communities (West Guanhutun and Yanzhuang). The major findings of this research reveal the negative impact of the subway system on migrant neighborhoods. The introduction of subway system in Zhengzhou provided more commute options, but since the two lines have not formed a mature subway network, the subway did not significantly shorten local residents’ commute time. Meanwhile, though the emergence of subway system brought added value to surrounding properties, the rapid increase in rent aggravated migrants’ living burden and further led to shifts in property use and local demographic composition. The vulnerability of migrant group is rooted in China’s household registration system, and connected with local development policies. The findings of this research show the importance of taking minority group’s voice into policy-making process and would be helpful for future development of metro system in the city

Thermal Transport for Probing Quantum Materials

Thermal transport is less appreciated in probing quantum materials in comparison to electrical transport. This article aims to show the pivotal role that thermal transport may play in understanding quantum materials: the longitudinal thermal transport reflects the itinerant quasiparticles even in an electrical insulating phase, while the transverse thermal transport such as thermal Hall and Nernst effect are tightly linked to nontrivial topology. We discuss three types of examples: quantum spin liquids where thermal transport identifies its existence, superconductors where thermal transport reveals the superconducting gap structure, and topological Weyl semimetals where anomalous Nernst effect is a consequence of nontrivial Berry curvature. We conclude with an outlook of the unique insights thermal transport may offer to probe a much broader category of quantum phenomena.Comment: A short review article with 6 figures. Comments are welcome

TVStoryGen: A Dataset for Generating Stories with Character Descriptions

We introduce TVStoryGen, a story generation dataset that requires generating detailed TV show episode recaps from a brief summary and a set of documents describing the characters involved. Unlike other story generation datasets, TVStoryGen contains stories that are authored by professional screen-writers and that feature complex interactions among multiple characters. Generating stories in TVStoryGen requires drawing relevant information from the lengthy provided documents about characters based on the brief summary. In addition, we propose to train reverse models on our dataset for evaluating the faithfulness of generated stories. We create TVStoryGen from fan-contributed websites, which allows us to collect 26k episode recaps with 1868.7 tokens on average. Empirically, we take a hierarchical story generation approach and find that the neural model that uses oracle content selectors for character descriptions demonstrates the best performance on automatic metrics, showing the potential of our dataset to inspire future research on story generation with constraints. Qualitative analysis shows that the best-performing model sometimes generates content that is unfaithful to the short summaries, suggesting promising directions for future work

Controllable Paraphrase Generation with a Syntactic Exemplar

Prior work on controllable text generation usually assumes that the controlled attribute can take on one of a small set of values known a priori. In this work, we propose a novel task, where the syntax of a generated sentence is controlled rather by a sentential exemplar. To evaluate quantitatively with standard metrics, we create a novel dataset with human annotations. We also develop a variational model with a neural module specifically designed for capturing syntactic knowledge and several multitask training objectives to promote disentangled representation learning. Empirically, the proposed model is observed to achieve improvements over baselines and learn to capture desirable characteristics.Comment: ACL 2019 Lon

The Non-Perturbative Quantum Nature of the Dislocation-Phonon Interaction

Despite the long history of dislocation-phonon interaction studies, there are many problems that have not been fully resolved during this development. These include an incompatibility between a perturbative approach and the long-range nature of a dislocation, the relation between static and dynamic scattering, and the nature of dislocation-phonon resonance. Here by introducing a fully quantized dislocation field, the "dislon"[1], a phonon is renormalized as a quasi-phonon, with shifted quasi-phonon energy, and accompanied by a finite quasi-phonon lifetime that is reducible to classical results. A series of outstanding legacy issues including those above can be directly explained within this unified phonon renormalization approach. In particular, a renormalized phonon naturally resolves the decades-long debate between dynamic and static dislocation-phonon scattering approaches.Comment: 5 pages main text, 3 figures, 10 pages supplemental material