141 research outputs found
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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
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