17,820 research outputs found
Two-dimensional universal conductance fluctuations and the electron-phonon interaction of topological surface states in Bi2Te2Se nanoribbons
The universal conductance fluctuations (UCFs), one of the most important
manifestations of mesoscopic electronic interference, have not yet been
demonstrated for the two-dimensional surface state of topological insulators
(TIs). Even if one delicately suppresses the bulk conductance by improving the
quality of TI crystals, the fluctuation of the bulk conductance still keeps
competitive and difficult to be separated from the desired UCFs of surface
carriers. Here we report on the experimental evidence of the UCFs of the
two-dimensional surface state in the bulk insulating Bi2Te2Se nanoribbons. The
solely-B\perp-dependent UCF is achieved and its temperature dependence is
investigated. The surface transport is further revealed by weak
antilocalizations. Such survived UCFs of the topological surface states result
from the limited dephasing length of the bulk carriers in ternary crystals. The
electron-phonon interaction is addressed as a secondary source of the surface
state dephasing based on the temperature-dependent scaling behavior
Behavior of hybrid FRP-concrete-steel tubular columns : experimental and theoretical studies
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition
In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion
IK-FA, a new heuristic inverse kinematics solver using firefly algorithm
In this paper, a heuristic method based on Firefly Algorithm is proposed for inverse kinematics problems in articulated robotics. The proposal is called, IK-FA. Solving inverse kinematics, IK, consists in finding a set of joint-positions allowing a specific point of the system to achieve a target position. In IK-FA, the Fireflies positions are assumed to be a possible solution for joints elementary motions. For a robotic system with a known forward kinematic model, IK-Fireflies, is used to generate iteratively a set of joint motions, then the forward kinematic model of the system is used to compute the relative Cartesian positions of a specific end-segment, and to compare it to the needed target position. This is a heuristic approach for solving inverse kinematics without computing the inverse model. IK-FA tends to minimize the distance to a target position, the fitness function could be established as the distance between the obtained forward positions and the desired one, it is subject to minimization. In this paper IK-FA is tested over a 3 links articulated planar system, the evaluation is based on statistical analysis of the convergence and the solution quality for 100 tests. The impact of key FA parameters is also investigated with a focus on the impact of the number of fireflies, the impact of the maximum iteration number and also the impact of (a, ß, ¿, d) parameters. For a given set of valuable parameters, the heuristic converges to a static fitness value within a fix maximum number of iterations. IK-FA has a fair convergence time, for the tested configuration, the average was about 2.3394 × 10-3 seconds with a position error fitness around 3.116 × 10-8 for 100 tests. The algorithm showed also evidence of robustness over the target position, since for all conducted tests with a random target position IK-FA achieved a solution with a position error lower or equal to 5.4722 × 10-9.Peer ReviewedPostprint (author's final draft
Ellagic acid, a phenolic compound, exerts anti-angiogenesis effects via VEGFR-2 signaling pathway in breast cancer
Anti-angiogenesis targeting VEGFR-2 has been considered as an important strategy for cancer therapy. Ellagic acid is a naturally existing polyphenol widely found in fruits and vegetables. It was reported that ellagic acid interfered with some angiogenesis-dependent pathologies. Yet the mechanisms involved were not fully understood. Thus, we analyzed its anti-angiogenesis effects and mechanisms on human breast cancer utilizing in-vitro and in-vivo methodologies. The in-silico analysis was also carried out to further analyze the structure-based interaction between ellagic acid and VEGFR-2. We found that ellagic acid significantly inhibited a series of VEGF-induced angiogenesis processes including proliferation, migration, and tube formation of endothelial cells. Besides, it directly inhibited VEGFR-2 tyrosine kinase activity and its downstream signaling pathways including MAPK and PI3K/Akt in endothelial cells. Ellagic acid also obviously inhibited neo-vessel formation in chick chorioallantoic membrane and sprouts formation of chicken aorta. Breast cancer xenografts study also revealed that ellagic acid significantly inhibited MDA-MB-231 cancer growth and P-VEGFR2 expression. Molecular docking simulation indicated that ellagic acid could form hydrogen bonds and aromatic interactions within the ATP-binding region of the VEGFR-2 kinase unit. Taken together, ellagic acid could exert anti-angiogenesis effects via VEGFR-2 signaling pathway in breast cancer. © 2012 The Author(s).published_or_final_versio
Different mechanisms of cis-9,trans-11- and trans-10,cis-12- conjugated linoleic acid affecting lipid metabolism in 3T3-L1 cells
Conjugated linoleic acid (CLA) has been shown to reduce body fat mass in various experimental animals. It is valuable to identify its influence on enzymes involved in energy expenditure, apoptosis, fatty acid oxidation and lipolysis. We investigated isomer-specific effects of high dose, long treatment of CLA (75.4 Μmol/L, 8 days) on protein and gene expression of these enzymes in cultured 3T3-L1 cells. Proteomics identified significant up- or down-regulation of 52 proteins by either CLA isomer. Protein and gene expression of uncoupling protein (UCP) 1, UCP3, perilipin and peroxisome proliferator-activated receptor (PPAR) α increased whereas UCP2 reduced for both CLA isomers. And eight-day treatment of trans-10,. cis-12 CLA, but not cis-9,. trans-11 CLA, significantly up-regulated protein and mRNA levels of PKA (P<05), CPT-1 and TNF-α (P<01). Compared to protein expression, both isomers did not significantly influence the mRNA expression of HSL, ATGL, ACO and leptin. In conclusion, high-dose, long treatment of cis-9,. trans-11 CLA did not promote apoptosis, fatty acid oxidation and lipolysis in adipocytes, but may induce an increase in energy expenditure. trans-10,. cis-12 CLA exhibited greater influence on lipid metabolism, stimulated adipocyte energy expenditure, apoptosis and fatty acid oxidation, but its effect on lipolysis was not obvious. © 2010 Elsevier Inc.postprin
Generation of Functional CLL-Specific Cord Blood CTL Using CD40-Ligated CLL APC
PMCID: PMC3526610This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
New Mechanics of Traumatic Brain Injury
The prediction and prevention of traumatic brain injury is a very important
aspect of preventive medical science. This paper proposes a new coupled
loading-rate hypothesis for the traumatic brain injury (TBI), which states that
the main cause of the TBI is an external Euclidean jolt, or SE(3)-jolt, an
impulsive loading that strikes the head in several coupled degrees-of-freedom
simultaneously. To show this, based on the previously defined covariant force
law, we formulate the coupled Newton-Euler dynamics of brain's micro-motions
within the cerebrospinal fluid and derive from it the coupled SE(3)-jolt
dynamics. The SE(3)-jolt is a cause of the TBI in two forms of brain's rapid
discontinuous deformations: translational dislocations and rotational
disclinations. Brain's dislocations and disclinations, caused by the
SE(3)-jolt, are described using the Cosserat multipolar viscoelastic continuum
brain model.
Keywords: Traumatic brain injuries, coupled loading-rate hypothesis,
Euclidean jolt, coupled Newton-Euler dynamics, brain's dislocations and
disclinationsComment: 18 pages, 1 figure, Late
Observation of the Fractional Quantum Hall Effect in Graphene
When electrons are confined in two dimensions and subjected to strong
magnetic fields, the Coulomb interactions between them become dominant and can
lead to novel states of matter such as fractional quantum Hall liquids. In
these liquids electrons linked to magnetic flux quanta form complex composite
quasipartices, which are manifested in the quantization of the Hall
conductivity as rational fractions of the conductance quantum. The recent
experimental discovery of an anomalous integer quantum Hall effect in graphene
has opened up a new avenue in the study of correlated 2D electronic systems, in
which the interacting electron wavefunctions are those of massless chiral
fermions. However, due to the prevailing disorder, graphene has thus far
exhibited only weak signatures of correlated electron phenomena, despite
concerted experimental efforts and intense theoretical interest. Here, we
report the observation of the fractional quantum Hall effect in ultraclean
suspended graphene, supporting the existence of strongly correlated electron
states in the presence of a magnetic field. In addition, at low carrier density
graphene becomes an insulator with an energy gap tunable by magnetic field.
These newly discovered quantum states offer the opportunity to study a new
state of matter of strongly correlated Dirac fermions in the presence of large
magnetic fields
Spin and valley quantum Hall ferromagnetism in graphene
In a graphene Landau level (LL), strong Coulomb interactions and the fourfold
spin/valley degeneracy lead to an approximate SU(4) isospin symmetry. At
partial filling, exchange interactions can spontaneously break this symmetry,
manifesting as additional integer quantum Hall plateaus outside the normal
sequence. Here we report the observation of a large number of these quantum
Hall isospin ferromagnetic (QHIFM) states, which we classify according to their
real spin structure using temperature-dependent tilted field magnetotransport.
The large measured activation gaps confirm the Coulomb origin of the broken
symmetry states, but the order is strongly dependent on LL index. In the high
energy LLs, the Zeeman effect is the dominant aligning field, leading to real
spin ferromagnets with Skyrmionic excitations at half filling, whereas in the
`relativistic' zero energy LL, lattice scale anisotropies drive the system to a
spin unpolarized state, likely a charge- or spin-density wave.Comment: Supplementary information available at http://pico.phys.columbia.ed
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