150,873 research outputs found
Groups Accuse Apple Supplier in China of Labor Violations
This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.CLW_2014_Report_China_groups_accuse.pdf: 44 downloads, before Oct. 1, 2020
Ricci flow and the metric completion of the space of Kahler metrics
We consider the space of Kahler metrics as a Riemannian submanifold of the
space of Riemannian metrics, and study the associated submanifold geometry. In
particular, we show that the intrinsic and extrinsic distance functions are
equivalent. We also determine the metric completion of the space of Kahler
metrics, making contact with recent generalizations of the Calabi-Yau Theorem
due to Dinew, Guedj-Zeriahi, and Kolodziej. As an application, we obtain a new
analytic stability criterion for the existence of a Kahler-Einstein metric on a
Fano manifold in terms of the Ricci flow and the distance function. We also
prove that the Kahler-Ricci flow converges as soon as it converges in the
metric sense
Theoretical study of impurity-induced magnetism in FeSe
Experimental evidence suggests that FeSe is close to a magnetic instability,
and recent scanning tunneling microscopy (STM) measurements on FeSe multilayer
films have revealed stripe order locally pinned near defect sites. Motivated by
these findings, we perform a theoretical study of locally induced magnetic
order near nonmagnetic impurities in a model relevant for FeSe. We find that
relatively weak repulsive impurities indeed are capable of generating
short-range magnetism, and explain the driving mechanism for the local order by
resonant eg-orbital states. In addition, we investigate the importance of
orbital-selective self-energy effects relevant for Hund's metals, and show how
the structure of the induced magnetization cloud gets modified by orbital
selectivity. Finally, we make concrete connection to STM measurements of
iron-based superconductors by symmetry arguments of the induced magnetic order,
and the basic properties of the Fe Wannier functions relevant for tunneling
spectroscopy.Comment: 10 pages, 4 figure
On universal partial words
A universal word for a finite alphabet and some integer is a
word over such that every word in appears exactly once as a subword
(cyclically or linearly). It is well-known and easy to prove that universal
words exist for any and . In this work we initiate the systematic study
of universal partial words. These are words that in addition to the letters
from may contain an arbitrary number of occurrences of a special `joker'
symbol , which can be substituted by any symbol from . For
example, is a linear partial word for the binary alphabet
and for (e.g., the first three letters of yield the
subwords and ). We present results on the existence and
non-existence of linear and cyclic universal partial words in different
situations (depending on the number of s and their positions),
including various explicit constructions. We also provide numerous examples of
universal partial words that we found with the help of a computer
Effects of Vanadium doping on BaFe2As2
We report an investigation of the structural, magnetic and electronic
properties of Ba(Fe(1-x)V(x))2As2 using x-ray, transport, magnetic
susceptibility and neutron scattering measurements. The vanadium substitutions
in Fe sites are possible up to 40\%. Hall effect measurements indicate strong
hole-doping effect through V doping, while no superconductivity is observed in
all samples down to 2K. The antiferromagnetic and structural transition
temperature of BaFe2As2 is gradually suppressed to finite temperature then
vanishes at x=0.245 with the emergence of spin glass behavior, suggesting an
avoided quantum critical point (QCP). Our results demonstrate that the avoided
QCP and spin glass state which were previously reported in the superconducting
phase of Co/Ni-doped BaFe2As2 can also be realized in non-superconducting
Ba(Fe(1-x)V(x))2As2.Comment: 5 pages, 6 figure
Intertwined magnetic and nematic orders in semiconducting KFeAgTe
Superconductivity in the iron pnictides emerges from metallic parent
compounds exhibiting intertwined stripe-type magnetic order and nematic order,
with itinerant electrons suggested to be essential for both. Here we use X-ray
and neutron scattering to show that a similar intertwined state is realized in
semiconducting KFeAgTe (KFeAgTe) without
itinerant electrons. We find Fe atoms in KFeAgTe form
isolated blocks, separated by nonmagnetic Ag atoms. Long-range
magnetic order sets in below K, with magnetic moments
within the Fe blocks ordering into the stripe-type configuration. A
nematic order accompanies the magnetic transition, manifest as a structural
distortion that breaks the fourfold rotational symmetry of the lattice. The
nematic orders in KFeAgTe and iron pnictide parent
compounds are similar in magnitude and how they relate to the magnetic order,
indicating a common origin. Since KFeAgTe is a
semiconductor without itinerant electrons, this indicates that local-moment
magnetic interactions are integral to its magnetic and nematic orders, and such
interactions may play a key role in iron-based superconductivity.Comment: supplemental material available upon request, to be published in PR
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Crisis Event Extraction Service (CREES) - Automatic Detection and Classification of Crisis-related Content on Social Media
Social media posts tend to provide valuable reports during crises. However, this information can be hidden in large amounts of unrelated documents. Providing tools that automatically identify relevant posts, event types (e.g., hurricane, floods, etc.) and information categories (e.g., reports on affected individuals, donations and volunteering, etc.) in social media posts is vital for their efficient handling and consumption. We introduce the Crisis Event Extraction Service (CREES), an open-source web API that automatically classifies posts during crisis situations. The API provides annotations for crisis-related documents, event types and information categories through an easily deployable and accessible web API that can be integrated into multiple platform and tools. The annotation service is backed by Convolutional Neural Networks (CNNs) and validated against traditional machine learning models. Results show that the CNN-based API results can be relied upon when dealing with specific crises with the benefits associated with the usage word embeddings
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