Strain-induced Evolution of Electronic Band Structures in a Twisted Graphene Bilayer

Here we study the evolution of local electronic properties of a twisted graphene bilayer induced by a strain and a high curvature. The strain and curvature strongly affect the local band structures of the twisted graphene bilayer; the energy difference of the two low-energy van Hove singularities decreases with increasing the lattice deformations and the states condensed into well-defined pseudo-Landau levels, which mimic the quantization of massive Dirac fermions in a magnetic field of about 100 T, along a graphene wrinkle. The joint effect of strain and out-of-plane distortion in the graphene wrinkle also results in a valley polarization with a significant gap, i.e., the eight-fold degenerate Landau level at the charge neutrality point is splitted into two four-fold degenerate quartets polarized on each layer. These results suggest that strained graphene bilayer could be an ideal platform to realize the high-temperature zero-field quantum valley Hall effect.Comment: 4 figure

Generation-side power scheduling in a grid-connected DC microgrid

Preprin

Exciton swapping in a twisted graphene bilayer as a solid-state realization of a two-brane model

It is shown that exciton swapping between two graphene sheets may occur under specific conditions. A magnetically tunable optical filter is described to demonstrate this new effect. Mathematically, it is shown that two turbostratic graphene layers can be described as a "noncommutative" two-sheeted (2+1)-spacetime thanks to a formalism previously introduced for the study of braneworlds in high energy physics. The Hamiltonian of the model contains a coupling term connecting the two layers which is similar to the coupling existing between two braneworlds at a quantum level. In the present case, this term is related to a K-K' intervalley coupling. In addition, the experimental observation of this effect could be a way to assess the relevance of some theoretical concepts of the braneworld hypothesis.Comment: 15 pages, 3 figures, final version published in European Physical Journal

Caloric restriction augments radiation efficacy in breast cancer.

Dietary modification such as caloric restriction (CR) has been shown to decrease tumor initiation and progression. We sought to determine if nutrient restriction could be used as a novel therapeutic intervention to enhance cytotoxic therapies such as radiation (IR) and alter the molecular profile of triple-negative breast cancer (TNBC), which displays a poor prognosis. In two murine models of TNBC, significant tumor regression is noted with IR or diet modification, and a greater regression is observed combining diet modification with IR. Two methods of diet modification were compared, and it was found that a daily 30% reduction in total calories provided more significant tumor regression than alternate day feeding. At the molecular level, tumors treated with CR and IR showed less proliferation and more apoptosis. cDNA array analysis demonstrated the IGF-1R pathway plays a key role in achieving this physiologic response, and multiple members of the IGF-1R pathway including IGF-1R, IRS, PIK3ca and mTOR were found to be downregulated. The innovative use of CR as a novel therapeutic option has the potential to change the biology of tumors and enhance the opportunity for clinical benefit in the treatment of patients with TNBC

Artificial graphene as a tunable Dirac material

Artificial honeycomb lattices offer a tunable platform to study massless Dirac quasiparticles and their topological and correlated phases. Here we review recent progress in the design and fabrication of such synthetic structures focusing on nanopatterning of two-dimensional electron gases in semiconductors, molecule-by-molecule assembly by scanning probe methods, and optical trapping of ultracold atoms in crystals of light. We also discuss photonic crystals with Dirac cone dispersion and topologically protected edge states. We emphasize how the interplay between single-particle band structure engineering and cooperative effects leads to spectacular manifestations in tunneling and optical spectroscopies.Comment: Review article, 14 pages, 5 figures, 112 Reference

POSYDON: A General-Purpose Population Synthesis Code with Detailed Binary-Evolution Simulations

Most massive stars are members of a binary or a higher-order stellar systems, where the presence of a binary companion can decisively alter their evolution via binary interactions. Interacting binaries are also important astrophysical laboratories for the study of compact objects. Binary population synthesis studies have been used extensively over the last two decades to interpret observations of compact-object binaries and to decipher the physical processes that lead to their formation. Here, we present POSYDON, a novel, binary population synthesis code that incorporates full stellar-structure and binary-evolution modeling, using the MESA code, throughout the whole evolution of the binaries. The use of POSYDON enables the self-consistent treatment of physical processes in stellar and binary evolution, including: realistic mass-transfer calculations and assessment of stability, internal angular-momentum transport and tides, stellar core sizes, mass-transfer rates and orbital periods. This paper describes the detailed methodology and implementation of POSYDON, including the assumed physics of stellar- and binary-evolution, the extensive grids of detailed single- and binary-star models, the post-processing, classification and interpolation methods we developed for use with the grids, and the treatment of evolutionary phases that are not based on pre-calculated grids. The first version of POSYDON targets binaries with massive primary stars (potential progenitors of neutron stars or black holes) at solar metallicity.Comment: 60 pages, 33 figures, 8 tables, referee's comments addressed. The code and the accompanying documentations and data products are available at https:\\posydon.or

Research on the relation of EEG signal chaos characteristics with high-level intelligence activity of human brain

Using phase space reconstruct technique from one-dimensional and multi-dimensional time series and the quantitative criterion rule of system chaos, and combining the neural network; analyses, computations and sort are conducted on electroencephalogram (EEG) signals of five kinds of human consciousness activities (relaxation, mental arithmetic of multiplication, mental composition of a letter, visualizing a 3-dimensional object being revolved about an axis, and visualizing numbers being written or erased on a blackboard). Through comparative studies on the determinacy, the phase graph, the power spectra, the approximate entropy, the correlation dimension and the Lyapunov exponent of EEG signals of 5 kinds of consciousness activities, the following conclusions are shown: (1) The statistic results of the deterministic computation indicate that chaos characteristic may lie in human consciousness activities, and central tendency measure (CTM) is consistent with phase graph, so it can be used as a division way of EEG attractor. (2) The analyses of power spectra show that ideology of single subject is almost identical but the frequency channels of different consciousness activities have slight difference. (3) The approximate entropy between different subjects exist discrepancy. Under the same conditions, the larger the approximate entropy of subject is, the better the subject's innovation is. (4) The results of the correlation dimension and the Lyapunov exponent indicate that activities of human brain exist in attractors with fractional dimensions. (5) Nonlinear quantitative criterion rule, which unites the neural network, can classify different kinds of consciousness activities well. In this paper, the results of classification indicate that the consciousness activity of arithmetic has better differentiation degree than that of abstract