Genome-wide investigation and expression analyses of the pentatricopeptide repeat protein gene family in foxtail millet

Orthologous relationships of the PPR genes between foxtail millet and those of other grass species. (TIF 5719 kb

Mode control and loss compensation of propagating surface plasmons

ABSTRACT Plasmonic devices can be used to construct nanophotonic circuits and are very promising candidates for next-generation information technology. The functions of plasmonic circuits rely on the rigorous control of plasmon modes. Two different methods were proposed to control the propagation of surface plasmons (SPs) supported by Ag nanowires (NWs). The first one is modulating the beat period of the near-field distribution pattern, which can be realized by depositing Al 2 O 3 layer or changing the refractive index of surrounding medium. The beat period increasing by 90 nm per nanometer of Al 2 O 3 coating or by 16 μm per refractive index unit was obtained in experiments. The second one is introducing local structural symmetry breaking to realize mode conversion of SPs. Three typical structures including NW-nanoparticle (NP) structure, branched NW and bent NW were used to investigate the mode conversion. It's revealed that the mode conversion is a scattering induced process. The lossy characteristic of SPs at optical frequencies typically limits the propagation length and hinders the further development of integrated plasmonic circuits. CdSe nanobelt/Al 2 O 3 /Ag film hybrid plasmonic waveguide was proposed to compensate the loss of SPs by using an optical pump-probe technique. Compared to the measured internal gain, the propagation loss was almost fully compensated for the TM mode. These results for mode control and loss compensation of propagating SPs are important for constructing functional nanophotonic circuits

Quasispecies distribution of Eigen model

We study sharp peak landscapes (SPL) of Eigen model from a new perspective about how the quasispecies distribute in the sequence space. To analyze the distribution more carefully, we bring forth two tools. One tool is the variance of Hamming distance of the sequences at a given generation. It not only offers us a different avenue for accurately locating the error threshold and illustrates how the configuration of the distribution varies with copying fidelity $q$ in the sequence space, but also divides the copying fidelity into three distinct regimes. The other tool is the similarity network of a certain Hamming distance $d_{0}$, by which we can get a visual and in-depth result about how the sequences distribute. We find that there are several local optima around the center (global optimum) in the distribution of the sequences reproduced near the threshold. Furthermore, it is interesting that the distribution of clustering coefficient $C(k)$ follows lognormal distribution and the curve of clustering coefficient $C$ of the network versus $d_{0}$ appears as linear behavior near the threshold.Comment: 13 pages, 6 figure

B(s)→D(s)∗∗B_{(s)} \rightarrow D^{**}_{(s)} form factors in HQEFT and model independent analysis of relevant semileptonic decays with NP effects

The form factors of $B_{(s)}$ decays into P-wave excited charmed mesons (including $D^*_0(2300)$, $D_1(2430)$, $D_1(2420)$, $D^*_2(2460)$ and their strange counterparts, denoted generically as $D^{**}_{(s)}$) are systematically calculated via the QCD sum rules in the framework of heavy quark effective field theory (HQEFT). We consider contributions up to the next leading order of heavy quark expansion and give all the relevant form factors, including the scalar and tensor ones only relevant for possible new physics effects. The expressions for the form factors in terms of several universal wave functions are derived via heavy quark expansion. These universal functions can be evaluated through QCD sum rules. Then, the numerical results of the form factors are presented. With the form factors given here, a model independent analysis of relevant semileptonic decays $B_{(s)} \rightarrow D^{**}_{(s)} l \bar{\nu}_l$ is performed, including the contributions from possible new physics effects. Our predictions for the differential decay widths, branching fractions and ratios of branching fractions $R(D^{**}_{(s)})$ may be tested in more precise experiments in the future.Comment: 38 pages, 8 figures, 12 table

Autoencoder Based Feature Selection Method for Classification of Anticancer Drug Response

Anticancer drug responses can be varied for individual patients. This difference is mainly caused by genetic reasons, like mutations and RNA expression. Thus, these genetic features are often used to construct classification models to predict the drug response. This research focuses on the feature selection issue for the classification models. Because of the vast dimensions of the feature space for predicting drug response, the autoencoder network was first built, and a subset of inputs with the important contribution was selected. Then by using the Boruta algorithm, a further small set of features was determined for the random forest, which was used to predict drug response. Two datasets, GDSC and CCLE, were used to illustrate the efficiency of the proposed method