1,547 research outputs found
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Because of their superior ability to preserve sequence information over time,
Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with
a more complex computational unit, have obtained strong results on a variety of
sequence modeling tasks. The only underlying LSTM structure that has been
explored so far is a linear chain. However, natural language exhibits syntactic
properties that would naturally combine words to phrases. We introduce the
Tree-LSTM, a generalization of LSTMs to tree-structured network topologies.
Tree-LSTMs outperform all existing systems and strong LSTM baselines on two
tasks: predicting the semantic relatedness of two sentences (SemEval 2014, Task
1) and sentiment classification (Stanford Sentiment Treebank).Comment: Accepted for publication at ACL 201
Detecting gravitational waves from highly eccentric compact binaries
In dense stellar regions, highly eccentric binaries of black holes and
neutron stars can form through various n-body interactions. Such a binary could
emit a significant fraction of its binding energy in a sequence of largely
isolated gravitational wave bursts prior to merger. Given expected black hole
and neutron star masses, many such systems will emit these repeated bursts at
frequencies within the sensitive band of contemporary ground-based
gravitational wave detectors. Unfortunately, existing gravitational wave
searches are ill-suited to detect these signals. In this work, we adapt a
"power stacking" method to the detection of gravitational wave signals from
highly eccentric binaries. We implement this method as an extension of the
Q-transform, a projection onto a multiresolution basis of windowed complex
exponentials that has previously been used to analyze data from the network of
LIGO/Virgo detectors. Our method searches for excess power over an ensemble of
time-frequency tiles. We characterize the performance of our method using Monte
Carlo experiments with signals injected in simulated detector noise. Our
results indicate that the power stacking method achieves substantially better
sensitivity to eccentric binary signals than existing localized burst searches.Comment: 17 pages, 20 figure
Multi-entity Video Transformers for Fine-Grained Video Representation Learning
The area of temporally fine-grained video representation learning aims to
generate frame-by-frame representations for temporally dense tasks. In this
work, we advance the state-of-the-art for this area by re-examining the design
of transformer architectures for video representation learning. A salient
aspect of our self-supervised method is the improved integration of spatial
information in the temporal pipeline by representing multiple entities per
frame. Prior works use late fusion architectures that reduce frames to a single
dimensional vector before any cross-frame information is shared, while our
method represents each frame as a group of entities or tokens. Our Multi-entity
Video Transformer (MV-Former) architecture achieves state-of-the-art results on
multiple fine-grained video benchmarks. MV-Former leverages image features from
self-supervised ViTs, and employs several strategies to maximize the utility of
the extracted features while also avoiding the need to fine-tune the complex
ViT backbone. This includes a Learnable Spatial Token Pooling strategy, which
is used to identify and extract features for multiple salient regions per
frame. Our experiments show that MV-Former not only outperforms previous
self-supervised methods, but also surpasses some prior works that use
additional supervision or training data. When combined with additional
pre-training data from Kinetics-400, MV-Former achieves a further performance
boost. The code for MV-Former is available at
https://github.com/facebookresearch/video_rep_learning
W boson mass in the NP models with extra gauge group
The precise measurement of the W boson mass is closely related to the
contributions of new physics (NP), which can significantly constrain the
parameter space of NP models, particularly those with an additional
local gauge group. The inclusion of a new gauge boson and gauge couplings
in these models can contribute to the oblique parameters , , and W
boson mass at tree level. Taking into account the effects of kinetic mixing, we
calculate and analyze the oblique parameters , , and W boson mass in
such NP models in this study. It is found that the kinetic mixing effects can
make significant contributions to the W boson mass, which can satisfy the
recently measured W boson mass at CDF II or ATLAS by choosing appropriate
values of gauge coupling constants and extra group charges of leptons or
scalar doublets. In addition, if the leptonic Yukawa couplings are invariant
under the extra local gauge group, these contributions can be eliminated
by redefining the gauge boson fields through eliminating the neutral currents
involving charged leptons, even with nonzero kinetic mixing effects.Comment: 11 pages, 2 figure
Low temperature and high magnetic field spectroscopic ellipsometry system
We report on the design and implementation of a spectral ellipsometer at near-infrared wavelength (700-1000 nm) for samples placed in high magnetic fields (up to 14 T) at low temperatures (~4.2 K). The main optical components are integrated in a probe, which can be inserted into a conventional long-neck He dewar and has a very long free-space optical path (~1.8 mĆ2). A polarizer-sample-(quarter-wave plate)-rotating analyzer configuration was employed. Two dielectric mirrors, one before and one after the sample in the optical path, helped to reflect the light back to the analyzer and a two-axis piezo-driven goniometer under the sample holder was used to control the direction of the reflected light. Functional test results performed on an intrinsic GaAs wafer and analysis on the random error of the system are shown. We obtained both amplitude and phase ellipsometric spectra simultaneously and observed helicity transformation at energies near the GaAs exciton transitions in the phase spectra. Significant shifts of them induced by magnetic fields were observed and fitted with a simple model. This system will allow us to study the collective magneto-optical response of materials and spatial dispersive exciton-polariton related problems in high external magnetic fields at low temperatures
Postchallenge responses of nitrotyrosine and TNF-alpha during 75-g oral glucose tolerance test are associated with the presence of coronary artery diseases in patients with prediabetes
<p>Abstract</p> <p>Background</p> <p>Meta-analysis has demonstrated an exponential relationship between 2-hr postchallenge hyperglycemia and coronary artery disease (CAD). Pulsatile hyperglycemia can acutely increase proinflammatory cytokines by oxidative stress. We hypothesized that postchallenge proinflammatory and nitrosative responses after 75 g oral glucose tolerance tests (75 g-OGTT) might be associated with CAD in patients without previously recognized type 2 diabetes mellitus (T2DM).</p> <p>Methods</p> <p>Serial changes of plasma glucose (PG), tumor necrosis factor-alpha (TNF-Ī±), interleukin-6 (IL-6) and nitrotyrosine levels were analyzed during 75 g-OGTT in 120 patients (81 male; age 62 Ā± 11 years) before coronary angiography. Patients were classified as normal (NGT; 42%), impaired (IGT; 34%) and diabetic (T2DM; 24%) glucose tolerance by 75 g-OGTT.</p> <p>Results</p> <p>Postchallenge hyperglycemia elicited TNF-Ī±, IL-6 and nitrotyrosine levels time-dependently, and 2-hr median levels of TNF-Ī± (7.1 versus 6.4 pg/ml; <it>P </it>< 0.05) and nitrotyrosine (1.01 versus 0.83 <it>Ī¼</it>mol/l; <it>P </it>< 0.05), but not IL-6 or PG, were significantly higher in patients with CAD in either IGT or T2DM groups. After adjusting risk factors and glucose tolerance status, 2-hr nitrotyrosine in highest quartiles (OR: 3.1, <it>P </it>< 0.05) remained an independent predictor of CAD by logistic regression analysis.</p> <p>Conclusions</p> <p>These results highlight postchallenge proinflammatory and nitrosative responses by 75 g-OGTT, rather than hyperglycemia <it>per se</it>, are associated with CAD in patients without previous recognized diabetes.</p
Imaging of Renal Tuberculosis in Eastern Taiwan: Correlation with Clinical Course and Different Communities
Hualien, located in eastern Taiwan, is a relatively isolated district. The population is composed of different ethnic communities. Our hospital is the only medical center in eastern Taiwan, so is the most important referral hospital for epidemic diseases. After reviewing our collected cases of renal tuberculosis (TB), we observed a great diversity in staging and outcomes. The aim of this study was to classify different imaging presentations and clinical outcomes in the ethnic communities represented by these cases (non-aboriginal and aboriginal). We retrospectively reviewed 22 cases from 1991 to 2001. We reviewed laboratory data, radiologic reports, and clinical outcomes. Before TB was proved by biopsy or culture, patients were not treated with an anti-TB regimen. Roentgenography showed that 68% of patients had renal calcification, 59% had dilated calyces, 55% had lung involvement, and 41% had auto-nephrectomy. The proportion of mild and severe forms was significantly different between aboriginal and non-aboriginal groups (0.05 > p ā„ 0.00409). From this series, we recommend routine plain film roentgenography, including chest roentgenography and kidney, ureter, and bladder or abdominal roentgenography, followed by intravenous urography or computerized tomography as investigative tools for renal TB. Based on the significantly different outcomes of the disease between aboriginal and non-aboriginal groups, a stronger health education program for the isolated district in eastern Taiwan is necessary
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