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

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 B→πB\to\pi form factors in kTk_T factorization

We calculate the three-parton twist-3 contribution to the $B\to\pi$ transition form factors in the $k_T$ 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 $B$ meson decays in the $k_T$ 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 β-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 (rmpA−) [33.3% (7/21)], and non-ESBL-KP rmpA− 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 rmpA−, and non-ESBL-KP rmpA− 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 rmpA– ESBL-KP and non-ESBL-KP strains

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