Topological Gaseous Plasmon Polariton in Realistic Plasma

Nontrivial topology in bulk matter has been linked with the existence of topologically protected interfacial states. We show that a gaseous plasmon polariton (GPP), an electromagnetic surface wave existing at the boundary of magnetized plasma and vacuum, has a topological origin that arises from the nontrivial topology of magnetized plasma. Because a gaseous plasma cannot sustain a sharp interface with discontinuous density, one must consider a gradual density falloff with scale length comparable to or longer than the wavelength of the wave. We show that the GPP may be found within a gapped spectrum in present-day laboratory devices, suggesting that platforms are currently available for experimental investigation of topological wave physics in plasmas

Toeplitz operators with radial symbols on weighted holomorphic Orlicz space

Peer reviewe

Anisotropic step-flow growth and island growth of GaN(0001) by molecular beam epitaxy

GaN(0001) thin films are grown using radio frequency plasma assisted molecular beam epitaxy. By changing the growth temperature, anisotropic growth rate behavior is observed in both the step-flow growth mode and the 2D island growth mode. Tunneling scanning microscopy reveals, in the step-flow growth mode, strong influences from the growth anisotropy on the shape of the terrace edges, resulting in striking differences between hexagonal and cubic films. In the 2D nucleation growth mode, triangularly shaped islands are formed. The significance of growth anisotropy to growing high quality GaN films is discussed.published_or_final_versio

Localized surface optical phonon mode in the InGaN/GaN multiple-quantum- wells nanopillars: Raman spectrum and imaging

An interesting phonon mode at around 685-705 cm -1 was clearly observed in the Raman spectra of InGaN/GaN multiple-quantum-wells nanopillars with different diameters at room temperature. The Raman peak position of this mode is found to show a distinct dependence on the nanopillar size, which is in well agreement with theoretical calculation of the surface optical (SO) phonon modes of nanopillars. Moreover, this kind of SO phonon was evidenced to be located on the pillar surface by using scanning confocal micro-Raman microscopy. © 2011 American Institute of Physics.published_or_final_versio

Quorum Regulated Resistance of Vibrio cholerae against Environmental Bacteriophages.

Predation by bacteriophages can significantly influence the population structure of bacterial communities. Vibrio cholerae the causative agent of cholera epidemics interacts with numerous phages in the aquatic ecosystem, and in the intestine of cholera patients. Seasonal epidemics of cholera reportedly collapse due to predation of the pathogen by phages. However, it is not clear how sufficient number of the bacteria survive to seed the environment in the subsequent epidemic season. We found that bacterial cell density-dependent gene expression termed "quorum sensing" which is regulated by signal molecules called autoinducers (AIs) can protect V. cholerae against predatory phages. V. cholerae mutant strains carrying inactivated AI synthase genes were significantly more susceptible to multiple phages compared to the parent bacteria. Likewise when mixed cultures of phage and bacteria were supplemented with exogenous autoinducers CAI-1 or AI-2 produced by recombinant strains carrying cloned AI synthase genes, increased survival of V. cholerae and a decrease in phage titer was observed. Mutational analyses suggested that the observed effects of autoinducers are mediated in part through the quorum sensing-dependent production of haemaglutinin protease, and partly through downregulation of phage receptors. These results have implication in developing strategies for phage mediated control of cholera

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Since the read lengths of high throughput sequencing (HTS) technologies are short, de novo assembly which plays significant roles in many applications remains a great challenge. Most of the state-of-the-art approaches base on de Bruijn graph strategy and overlap-layout strategy. However, these approaches which depend on k-mers or read overlaps do not fully utilize information of paired-end and single-end reads when resolving branches. Since they treat all single-end reads with overlapped length larger than a fix threshold equally, they fail to use the more confident long overlapped reads for assembling and mix up with the relative short overlapped reads. Moreover, these approaches have not been special designed for handling tandem repeats (repeats occur adjacently in the genome) and they usually break down the contigs near the tandem repeats. We present PERGA (Paired-End Reads Guided Assembler), a novel sequence-reads-guided de novo assembly approach, which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds using paired-end reads and different read overlap size ranging from Omax to Omin to resolve the gaps and branches. By constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. When the correct extension cannot be determined, PERGA will try to extend the contig by all feasible extensions and determine the correct extension by using look-ahead approach. Many difficult-resolved branches are due to tandem repeats which are close in the genome. PERGA detects such different copies of the repeats to resolve the branches to make the extension much longer and more accurate. We evaluated PERGA on both Illumina real and simulated datasets ranging from small bacterial genomes to large human chromosome, and it constructed longer and more accurate contigs and scaffolds than other state-of-the-art assemblers. PERGA can be freely downloaded at https://github.com/hitbio/PERGA.published_or_final_versio

Formation of large low shear velocity provinces through the decomposition of oxidized mantle.

Large Low Shear Velocity Provinces (LLSVPs) in the lowermost mantle are key to understanding the chemical composition and thermal structure of the deep Earth, but their origins have long been debated. Bridgmanite, the most abundant lower-mantle mineral, can incorporate extensive amounts of iron (Fe) with effects on various geophysical properties. Here our high-pressure experiments and ab initio calculations reveal that a ferric-iron-rich bridgmanite coexists with an Fe-poor bridgmanite in the 90 mol% MgSiO3-10 mol% Fe2O3 system, rather than forming a homogeneous single phase. The Fe3+-rich bridgmanite has substantially lower velocities and a higher VP/VS ratio than MgSiO3 bridgmanite under lowermost-mantle conditions. Our modeling shows that the enrichment of Fe3+-rich bridgmanite in a pyrolitic composition can explain the observed features of the LLSVPs. The presence of Fe3+-rich materials within LLSVPs may have profound effects on the deep reservoirs of redox-sensitive elements and their isotopes

Charge density waves and Fermi surface reconstruction in the clean overdoped cuprate superconductor Tl2Ba2CuO6+δ.

Hall effect and quantum oscillation measurements on high temperature cuprate superconductors show that underdoped compositions have small Fermi surface pockets whereas when heavily overdoped, a single much larger pocket is found. The origin of this change in electronic structure has been unclear, but may be related to the high temperature superconductivity. Here we show that the clean overdoped single-layer cuprate Tl2Ba2CuO6+δ (Tl2201) displays CDW order with a remarkably long correlation length ξ ≈ 200 Å which disappears above a hole doping of pCDW ≈ 0.265. We show that the evolution of the electronic properties of Tl2201 as the doping is lowered may be explained by a Fermi surface reconstruction which accompanies the emergence of the CDW below pCDW. Our results demonstrate importance of CDW correlations in understanding the electronic properties of overdoped cuprates

Predicting the response to sorafenib in hepatocellular carcinoma: where is the evidence for phosphorylated extracellular signaling-regulated kinase (pERK)?

The approval of sorafenib and active development of many other molecularly targeted agents in hepatocellular carcinoma (HCC) have presented a challenge to understand the mechanism of action of sorafenib and identify predictive biomarkers to select patients more likely to benefit from sorafenib. The preclinical study by Zhang and celleagues published this month in BMC Medicine provides preliminary evidence that baseline phosphorylated extracellular signaling-regulated kinase (pERK) may be a relevant marker to reflect the level of constitutive activation of the RAF/mitogen-activated protein kinase kinase (MEK)/ERK signaling pathway and has the potential value in predicting response to sorafenib. The clinical data from the initial single arm phase II study and preliminary report from the randomized phase III study also suggest the correlation of baseline archived tumor pERK levels and time to tumor progression in HCC patients. Whether baseline pERK will prove to be a useful predictive biomarker of response and clinical benefits for sorafenib in HCC will need to be validated in future large prospective studies

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201