Non-Markovian dynamics of a microcavity coupled to a waveguide in photonic crystals

In this paper, the non-Markovian dynamics of a microcavity coupled to a waveguide in photonic crystals is studied based on Fano-type tight binding model. Using the exact master equation, we solve analytically and numerically the temporal evolution of the cavity coherent state and the associated physical observables. A critical transition is revealed when the coupling increase between the cavity and the waveguide. In particular, the cavity field becomes dissipationless when the coupling strength goes beyond a critical value, as a manifestation of strong non-Markovian memory effect. The result also indicates that the cavity can maintain in a coherent state with arbitrary small number of photons when it strongly couples to the waveguide at very low temperature. These properties can be measured experimentally through the photon current flowing over the waveguide in photonic crystals.Comment: 7 pages, 5 figure

10,21-Dimethyl-2,7,13,18-tetraphenyl-3,6,14,17-tetraazatricyclo[17.3.1.18,12]tetracosa-1(23),2,6,8(24),9,11,13,17,19,21-decaene-23,24-diol cyclohexane 0.33-solvate

The title compound, C46H40N4O2·0.33C6H12, was obtained unintentionally as a product of an attempted synthesis of a cadmium(II) complex of the [2,6-{PhSe(CH2)2N=CPh}2C6H2(4-Me)(OH)] ligand. The full tetra­imino­diphenol macrocyclic ligand is generated by the application of an inversion centre. The macrocyclic ligand features strong intra­molecular O—H⋯N hydrogen bonds. The dihedral angles formed between the phenyl ring incorporated within the macrocycle and the peripheral phenyl rings are 82.99 (8) and 88.20 (8)°. The cyclo­hexane solvent mol­ecule lies about a site of symmetry. Other solvent within the lattice was disordered and was treated with the SQUEEZE routine [Spek (2009). Acta Cryst. D65, 148–155]

Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation

Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates

Intestine-Specific, Oral Delivery of Captopril/Montmorillonite: Formulation and Release Kinetics

The intercalation of captopril (CP) into the interlayers of montmorillonite (MMT) affords an intestine-selective drug delivery system that has a captopril-loading capacity of up to ca. 14 %w/w and which exhibits near-zero-order release kinetics

Physics of leptoquarks in precision experiments and at particle colliders

We present a comprehensive review of physics effects generated by leptoquarks (LQs), i.e., hypothetical particles that can turn quarks into leptons and vice versa, of either scalar or vector nature. These considerations include discussion of possible completions of the Standard Model that contain LQ fields. The main focus of the review is on those LQ scenarios that are not problematic with regard to proton stability. We accordingly concentrate on the phenomenology of light leptoquarks that is relevant for precision experiments and particle colliders. Important constraints on LQ interactions with matter are derived from precision low-energy observables such as electric dipole moments, (g-2) of charged leptons, atomic parity violation, neutral meson mixing, Kaon, B, and D meson decays, etc. We provide a general analysis of indirect constraints on the strength of LQ interactions with the quarks and leptons to make statements that are as model independent as possible. We address complementary constraints that originate from electroweak precision measurements, top, and Higgs physics. The Higgs physics analysis we present covers not only the most recent but also expected results from the Large Hadron Collider (LHC). We finally discuss direct LQ searches. Current experimental situation is summarized and self-consistency of assumptions that go into existing accelerator-based searches is discussed. A progress in making next-to-leading order predictions for both pair and single LQ productions at colliders is also outlined.Comment: 136 pages, 22 figures, typographical errors fixed, the Physics Reports versio

Heterodinuclear zinc and magnesium catalysts for epoxide/CO2 ring opening copolymerizations

The ring-opening copolymerization of carbon dioxide and epoxides is a useful means to make aliphatic polycarbonates and to add-value to CO2. Recently, the first heterodinuclear Zn(ii)/Mg(ii) catalyst showed greater activity than either homodinuclear analogue (J. Am. Chem. Soc. 2015, 137, 15078-15081). Building from this preliminary finding, here, eight new Zn(ii)/Mg(ii) heterodinuclear catalysts featuring carboxylate co-ligands are prepared and characterized. The best catalysts show very high activities for copolymerization using cyclohexene oxide (TOF = 8880 h-1, 20 bar CO2, 120 °C, 0.01 mol% catalyst loading) or cyclopentene oxide. All the catalysts are highly active in the low pressure regime and specifically at 1 bar pressure CO2. The polymerization kinetics are analysed using in situ spectroscopy and aliquot techniques: the rate law is overall second order with a first order dependence in both catalyst and epoxide concentrations and a zero order in carbon dioxide pressure. The pseudo first order rate coefficient values are compared for the catalyst series and differences are primarily attributed to effects on initiation rates. The data are consistent with a chain shuttling mechanistic hypothesis with heterodinuclear complexes showing particular rate enhancements by optimizing distinct roles in the catalytic cycles. The mechanistic hypothesis should underpin future heterodinuclear catalyst design for use both in other (co)polymerization and carbon dioxide utilization reactions

Multiple publications: The main reason for the retraction of papers in computer science

This paper intends to review the reasons for the retraction over the last decade. The paper particularly aims at reviewing these reasons with reference to computer science field to assist authors in comprehending the style of writing. To do that, a total of thirty-six retracted papers found on the Web of Science within Jan 2007 through July 2017 are explored. Given the retraction notices which are based on ten common reasons, this paper classifies the two main categories, namely random and nonrandom retraction. Retraction due to the duplication of publications scored the highest proportion of all other reasons reviewed

Supersymmetry, Localization and Quantum Entropy Function

AdS_2/CFT_1 correspondence leads to a prescription for computing the degeneracy of black hole states in terms of path integral over string fields living on the near horizon geometry of the black hole. In this paper we make use of the enhanced supersymmetries of the near horizon geometry and localization techniques to argue that the path integral receives contribution only from a special class of string field configurations which are invariant under a subgroup of the supersymmetry transformations. We identify saddle points which are invariant under this subgroup. We also use our analysis to show that the integration over infinite number of zero modes generated by the asymptotic symmetries of AdS_2 generate a finite contribution to the path integral.Comment: LaTeX file, 31 pages; v2: minor correction; v3: typos correcte

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

<p>Abstract</p> <p>Background</p> <p>Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.</p> <p>Results</p> <p>Experimental results on the phenotype recognition from three benchmarking image sets including HeLa, CHO and RNAi show the effectiveness of the proposed approach. The combined feature is better than any individual one in the classification accuracy. The ensemble model produces better classification performance compared to the component neural networks trained. For the three images sets HeLa, CHO and RNAi, the Random Subspace Ensembles offers the classification rates 91.20%, 98.86% and 91.03% respectively, which compares sharply with the published result 84%, 93% and 82% from a multi-purpose image classifier WND-CHARM which applied wavelet transforms and other feature extraction methods. We investigated the problem of estimation of ensemble parameters and found that satisfactory performance improvement could be brought by a relative medium dimensionality of feature subsets and small ensemble size.</p> <p>Conclusions</p> <p>The characteristics of curvelet transform of being multiscale and multidirectional suit the description of microscopy images very well. It is empirically demonstrated that the curvelet-based feature is clearly preferred to wavelet-based feature for bioimage descriptions. The random subspace ensemble of MLPs is much better than a number of commonly applied multi-class classifiers in the investigated application of phenotype recognition.</p