3,259 research outputs found
Dynamical Instability of Holographic QCD at Finite Density
In this paper we study the dynamical instability of Sakai-Sugimoto's
holographic QCD model at finite baryon density. In this model, the baryon
density, represented by the smeared instanton on the worldvolume of the probe
D8-\overline{D8} mesonic brane, sources the worldvolume electric field, and
through the Chern-Simons term it will induces the instability to form a chiral
helical wave. This is similar to Deryagin-Grigoriev-Rubakov instability to form
the chiral density wave for large N_c QCD at finite density. Our results show
that this kind of instability occurs for sufficiently high baryon number
densities. The phase diagram of holographic QCD will thus be changed from the
one which is based only on thermodynamics. This holographic approach provides
an effective way to study the phases of QCD at finite density, where the
conventional perturbative QCD and lattice simulation fail.Comment: 18 pages, 6 figures;v2. add thermodynamics discussion; v4. Treatment
of the instanton energy changed and QGP analysis added. Some figures replaced
and added, including the phase diagra
Novel CMOS RFIC Layout Generation with Concurrent Device Placement and Fixed-Length Microstrip Routing
With advancing process technologies and booming IoT markets, millimeter-wave
CMOS RFICs have been widely developed in re- cent years. Since the performance
of CMOS RFICs is very sensi- tive to the precision of the layout, precise
placement of devices and precisely matched microstrip lengths to given values
have been a labor-intensive and time-consuming task, and thus become a major
bottleneck for time to market. This paper introduces a progressive
integer-linear-programming-based method to gener- ate high-quality RFIC layouts
satisfying very stringent routing requirements of microstrip lines, including
spacing/non-crossing rules, precise length, and bend number minimization,
within a given layout area. The resulting RFIC layouts excel in both per-
formance and area with much fewer bends compared with the simulation-tuning
based manual layout, while the layout gener- ation time is significantly
reduced from weeks to half an hour.Comment: ACM/IEEE Design Automation Conference (DAC), 201
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Cryo-EM Studies of TMEM16F Calcium-Activated Ion Channel Suggest Features Important for Lipid Scrambling.
As a Ca2+-activated lipid scramblase and ion channel that mediates Ca2+ influx, TMEM16F relies on both functions to facilitate extracellular vesicle generation, blood coagulation, and bone formation. How a bona fide ion channel scrambles lipids remains elusive. Our structural analyses revealed the coexistence of an intact channel pore and PIP2-dependent protein conformation changes leading to membrane distortion. Correlated to the extent of membrane distortion, many tightly bound lipids are slanted. Structure-based mutagenesis studies further reveal that neutralization of some lipid-binding residues or those near membrane distortion specifically alters the onset of lipid scrambling, but not Ca2+ influx, thus identifying features outside of channel pore that are important for lipid scrambling. Together, our studies demonstrate that membrane distortion does not require open hydrophilic grooves facing the membrane interior and provide further evidence to suggest separate pathways for lipid scrambling and ion permeation
Three-parton contribution to the form factors in factorization
We calculate the three-parton twist-3 contribution to the
transition form factors in the factorization theorem. Since different
mesons are involved in the initial and final states,
two(three)-parton-to-three(two)-parton amplitudes do not vanish. It is found
that the dominant contribution arises from the diagrams with the additional
valence gluon attaching to the leading-order hard gluon. Employing the
three-parton meson distribution amplitudes from QCD sum rules, we show that
this subleading piece amounts only up to few percents of the form factors at
large recoil of the pion. The framework for analyzing three-parton
contributions to meson decays in the factorization is established.Comment: 8 pages, 3 figure
Regulator of the mucoid phenotype A gene increases the virulent ability of extended-spectrum beta-lactamase-producing serotype non-K1/K2 Klebsiella pneumonia
BackgroundTo determine whether the presence of a capsule regulator gene [i.e., regulator of mucoid phenotype A (rmpA) gene] contributes to virulence on extended-spectrum ÎČ-lactamase-producing Klebsiella pneumoniae (ESBL-KP) with serotype non-K1/K2 strains.MethodsTwenty-eight ESBL-KP and non-ESBL-KP isolates were collected from the Tri-Service General Hospital (Taipei, Taiwan). The impact of the virulent rmpA gene in different capsular polysaccharide serotypes on ESBL-KP and non-ESBL-KP isolates was studied by a neutrophil phagocytosis reaction, a serum bactericidal assay, and an animal survival model.ResultsResistance to broad spectrum antibiotics was more prevalent in ESBL-KP strains than in non-ESBL-KP strains (p < 0.01). The ESBL-KP strains had different molecular patterns from non-ESBL-KP strains, based on pulsed-field gel electrophoresis. The frequency of serum-resistant isolates was the highest among ESBL-KP strains with rmpA (i.e., rmpA+) [71.4% (5/7)] than among of non-ESBL-KP rmpA+ strains [42.8% (6/14)], ESBL-KP strains without rmpA (rmpAâ) [33.3% (7/21)], and non-ESBL-KP rmpAâ strains [14.2% (2/14)]. The most significant increase in neutrophil resistance occurred in the ESBL-KP rmpA+ strains in comparison to the non-ESBL-KP rmpA+, ESBL-KP rmpAâ, and non-ESBL-KP rmpAâ strains (p < 0.01). The results of the animal survival model were compatible with the neutrophil phagocytosis reaction and serum bactericidal assay.ConclusionWe conclude that the pathogenic potential is greater in rmpA+ ESBL-KP strains than in rmpAâ ESBL-KP and non-ESBL-KP strains
DNIC-mediated analgesia produced by a supramaximal electrical or a high-dose formalin conditioning stimulus: roles of opioid and α2-adrenergic receptors
Structural and Thermodynamic Factors of Suppressed Interdiffusion Kinetics in Multi-component High-entropy Materials
We report multi-component high-entropy materials as extraordinarily robust diffusion barriers and clarify the highly suppressed interdiffusion kinetics in the multi-component materials from structural and thermodynamic perspectives. The failures of six alloy barriers with different numbers of elements, from unitary Ti to senary TiTaCrZrAlRu, against the interdiffusion of Cu and Si were characterized, and experimental results indicated that, with more elements incorporated, the failure temperature of the barriers increased from 550 to 900°C. The activation energy of Cu diffusion through the alloy barriers was determined to increase from 110 to 163 kJ/mole. Mechanistic analyses suggest that, structurally, severe lattice distortion strains and a high packing density caused by different atom sizes, and, thermodynamically, a strengthened cohesion provide a total increase of 55 kJ/mole in the activation energy of substitutional Cu diffusion, and are believed to be the dominant factors of suppressed interdiffusion kinetics through the multi-component barrier materials
Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection
Multi-label image classification is a fundamental but challenging task
towards general visual understanding. Existing methods found the region-level
cues (e.g., features from RoIs) can facilitate multi-label classification.
Nevertheless, such methods usually require laborious object-level annotations
(i.e., object labels and bounding boxes) for effective learning of the
object-level visual features. In this paper, we propose a novel and efficient
deep framework to boost multi-label classification by distilling knowledge from
weakly-supervised detection task without bounding box annotations.
Specifically, given the image-level annotations, (1) we first develop a
weakly-supervised detection (WSD) model, and then (2) construct an end-to-end
multi-label image classification framework augmented by a knowledge
distillation module that guides the classification model by the WSD model
according to the class-level predictions for the whole image and the
object-level visual features for object RoIs. The WSD model is the teacher
model and the classification model is the student model. After this cross-task
knowledge distillation, the performance of the classification model is
significantly improved and the efficiency is maintained since the WSD model can
be safely discarded in the test phase. Extensive experiments on two large-scale
datasets (MS-COCO and NUS-WIDE) show that our framework achieves superior
performances over the state-of-the-art methods on both performance and
efficiency.Comment: accepted by ACM Multimedia 2018, 9 pages, 4 figures, 5 table
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