88 research outputs found
Model-Independent Predictions for Low Energy Isoscalar Heavy Baryon Observables in the Combined Heavy Quark and Large Expansion
Model-independent predictions for excitation energies, semileptonic form
factors and electromagnetic decay rates of isoscalar heavy baryons and their
low energy excited states are discussed in terms of the combined heavy quark
and large expansion. At leading order, the observables are completely
determined in terms of the known excitation energy of the first excited state
of . At next-to-leading order in the combined expansion all heavy
baryon observables can be expressed in a model-independent way in terms of two
experimentally measurable quantities. We list predictions at leading and
next-to-leading order.Comment: 7 pages, LaTe
Excited baryon resonances in large QCD
We summarize results obtained in the expansion method for the masses
of baryon resonances belonging to the multiplet. They
represent an extension of our previous studies from two to three flavors. A
better approach to mixed symmetric states of any angular momentum and parity is
also outlined.Comment: 4 pages, 1 figure, uses espcrc2.sty (included), based on a talk given
by N. Matagne at the 13th International QCD Conference, QCD06, Montpellier,
France, 3-7th July 200
Excited Heavy Baryons and Their Symmetries III: Phenomenology
Phenomenological applications of an effective theory of low-lying excited
states of charm and bottom isoscalar baryons are discussed at leading and
next-to-leading order in the combined heavy quark and large expansion.
The combined expansion is formulated in terms of the counting parameter
; the combined expansion is in powers of
. We work up to next-to-leading order. We obtain
model-independent predictions for the excitation energies, the semileptonic
form factors and electromagnetic decay rates. The spin-averaged mass of the
doublet of the first orbitally excited sate of is predicted to be
approximately . It is shown that in the combined limit at leading and
next-to-leading order there is only one independent form factor describing
; similarly, and
decays are described by a single independent form factor. These form factors
are calculated at leading and next-to-leading order in the combined expansion.
The electromagnetic decay rates of the first excited states of and
are determined at leading and next-to leading order. The ratio of
radiative decay rates is predicted to be approximately
0.2, greatly different from the heavy quark effective theory value of unity.Comment: 21 pages, 2 figure
Threshold effects in excited charmed baryon decays
Motivated by recent results on charmed baryons from CLEO and FOCUS, we
reexamine the couplings of the orbitally excited charmed baryons. Due to its
proximity to the [Sigma_c pi] threshold, the strong decays of the
Lambda_c(2593) are sensitive to finite width effects. This distorts the shape
of the invariant mass spectrum in Lambda_{c1}-> Lambda_c pi^+pi^- from a simple
Breit-Wigner resonance, which has implications for the experimental extraction
of the Lambda_c(2593) mass and couplings. We perform a fit to unpublished CLEO
data which gives M(Lambda_c(2593)) - M(Lambda_c) = 305.6 +- 0.3 MeV and h2^2 =
0.24^{+0.23}_{-0.11}, with h2 the Lambda_{c1}-> Sigma_c pi strong coupling in
the chiral Lagrangian. We also comment on the new orbitally excited states
recently observed by CLEO.Comment: 9 pages, 3 figure
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition
Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data. Deep learning, although a breakthrough for Image classification and showing promise for videos, has still not clearly superseded action recognition methods using hand-crafted features, even when training on
massive datasets. In this paper, we introduce hybrid video classification architectures based on carefully designed unsupervised representations of hand-crafted
spatio-temporal features classified by supervised deep networks. As we show in our experiments on five popular benchmarks for action recognition, our hybrid
model combines the best of both worlds: it is data efficient (trained on 150 to 10000 short clips) and yet improves significantly on the state of the art, including
recent deep models trained on millions of manually labelled images and videos
Negative Parity 70-plet Baryon Masses in the 1/Nc Expansion
The masses of the negative parity SU(6) 70-plet baryons are analyzed in the
1/Nc expansion to order 1/Nc and to first order in SU(3) breaking. At this
level of precision there are twenty predictions. Among them there are the well
known Gell-Mann Okubo and equal spacing relations, and four new relations
involving SU(3) breaking splittings in different SU(3) multiplets. Although the
breaking of SU(6) symmetry occurs at zeroth order in 1/Nc, it turns out to be
small. The dominant source of the breaking is the hyperfine interaction which
is of order 1/Nc. The spin-orbit interaction, of zeroth order in 1/Nc, is
entirely fixed by the splitting between the singlet states Lambda(1405) and
Lambda(1520), and the spin-orbit puzzle is solved by the presence of other
zeroth order operators involving flavor exchange.Comment: 31 pages, 3 figure
An Efficient Human Activity Recognition Technique Based on Deep Learning
In this paper, we present a new deep learning-based human activity recognition technique. First, we track and extract human body from each frame of the video stream. Next, we abstract human silhouettes and use them to create binary space-time maps (BSTMs) which summarize human activity within a defined time interval. Finally, we use convolutional neural network (CNN) to extract features from BSTMs and classify the activities. To evaluate our approach, we carried out several tests using three public datasets: Weizmann, Keck Gesture and KTH Database. Experimental results show that our technique outperforms conventional state-of-the-art methods in term of recognition accuracy and provides comparable performance against recent deep learning techniques. It’s simple to implement, requires less computing power, and can be used for multi-subject activity recognition
Preliminary clinical study of left ventricular myocardial strain in patients with non-ischemic dilated cardiomyopathy by three-dimensional speckle tracking imaging
<p>Abstract</p> <p>Background</p> <p>Non-ischemic dilated cardiomyopathy (DCM) is the most common cardiomyopathy worldwide, with significant mortality. Correct evaluation of the patient's myocardial function has important clinical significance in the diagnosis, therapeutic effect assessment and prognosis in non-ischemic DCM patients. This study evaluated the feasibility of three-dimensional speckle tracking imaging (3D-STE) for assessment of the left ventricular myocardial strain in patients with non-ischemic dilated cardiomyopathy (DCM).</p> <p>Methods</p> <p>Apical full-volume images were acquired from 65 patients with non-ischemic DCM (DCM group) and 59 age-matched normal controls (NC group), respectively. The following parameters were measured by 3D-STE: the peak systolic radial strain (RS), circumferential strain (CS), longitudinal strain (LS) of each segment. Then all the parameters were compared between the two groups.</p> <p>Results</p> <p>The peak systolic strain in different planes had certain regularities in normal groups, radial strain (RS) was the largest in the mid region, the smallest in the apical region, while circumferential strain (CS) and longitudinal strain (LS) increased from the basal to the apical region. In contrast, the regularity could not be applied to the DCM group. RS, CS, LS were significantly decreased in DCM group as compared with NC group (<it>P </it>< 0.001 for all). The interobserver, intraobserver and test-retest reliability were acceptable.</p> <p>Conclusions</p> <p>3D-STE is a reliable tool for evaluation of left ventricular myocardial strain in patients with non-ischemic DCM, with huge advantage in clinical application.</p
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