Gap deformation and classical wave localization in disordered two-dimensional photonic band gap materials

By using two ab initio numerical methods we study the effects that disorder has on the spectral gaps and on wave localization in two-dimensional photonic band gap materials. We find that there are basically two different responses depending on the lattice realization (solid dielectric cylinders in air or vise versa), the wave polarization, and the particular form under which disorder is introduced. Two different pictures for the photonic states are employed, the ``nearly free'' photon and the ``strongly localized'' photon. These originate from the two different mechanisms responsible for the formation of the spectral gaps, ie. multiple scattering and single scatterer resonances, and they qualitatively explain our results.Comment: Accepted for publication in Phys. Rev.

Subaru Deep Survey V. A Census of Lyman Break Galaxies at z=4 and 5 in the Subaru Deep Fields: Photometric Properties

(abridged) We investigate photometric properties of Lyman Break Galaxies (LBGs) at z=3.5-5.2 based on large samples of 2,600 LBGs detected in deep (i'~27) and wide-field (1,200 arcmin^2) images taken in the Subaru Deep Field (SDF) and the Subaru/XMM Deep Field (SXDF). The selection criteria for the LBG samples are examined with 85 spectroscopically identified objects and by Monte Carlo simulations. We find in the luminosity functions of LBGs (i) that the number density of bright galaxies (M_{1700}<-22; corresponding to SFR_{corr}>100 Msolar yr^{-1}) decreases significantly from z=4 to 5 and (ii) that the faint-end slope of the luminosity function may become steeper towards higher redshifts. We estimate dust extinction of z=4 LBGs with M<M^* from UV slopes, and obtain E(B-V)=0.15+/-0.03 as the mean value. The dust extinction remains constant with apparent luminosity, but increases with intrinsic luminosity. We find no evolution in dust extinction between LBGs at z=3 and 4. We investigate the evolution of UV-luminosity density at 1700A, rho, and find that rho does not significantly change from z=3 to z=5, i.e., rho(z=4)/rho(z=3)=1.0+/-0.2 and rho(z=5)/rho(z=3)=0.8+/-0.4, thus the cosmic star-formation rate (SFR) density remains constant. We find that the stellar mass density estimated from the cosmic SFR is consistent with those derived directly from the stellar mass function at z=0-1, but exceeds those at z~3 by a factor of 3. We find that the ratio of the UV-luminosity density of Ly-a emitters (LAEs) to that of LBGs is ~60% at z=5, and thus about a half of the star formation at z=5 probably occurs in LAEs. We obtain a constraint on the escape fraction of UV-ionizing photons produced by LBGs, f_{esc}>~0.13.Comment: 41 pages, 22 figures, ApJ in press. Paper with high resolution figures is available at http://hikari.astron.s.u-tokyo.ac.jp/~ouchi/work/astroph/SDS_V_VI/SDS_V.pdf (PDF

Structural Basis for Receptor-Mediated Selective Autophagy of Aminopeptidase I Aggregates

SummarySelective autophagy mediates the degradation of various cargoes, including protein aggregates and organelles, thereby contributing to cellular homeostasis. Cargo receptors ensure selectivity by tethering specific cargo to lipidated Atg8 at the isolation membrane. However, little is known about the structural requirements underlying receptor-mediated cargo recognition. Here, we report structural, biochemical, and cell biological analysis of the major selective cargo protein in budding yeast, aminopeptidase I (Ape1), and its complex with the receptor Atg19. The Ape1 propeptide has a trimeric coiled-coil structure, which tethers dodecameric Ape1 bodies together to form large aggregates. Atg19 disassembles the propeptide trimer and forms a 2:1 heterotrimer, which not only blankets the Ape1 aggregates but also regulates their size. These receptor activities may promote elongation of the isolation membrane along the aggregate surface, enabling sequestration of the cargo with high specificity

Garbage In, Garbage Out? Do Machine Learning Application Papers in Social Computing Report Where Human-Labeled Training Data Comes From?

Many machine learning projects for new application areas involve teams of humans who label data for a particular purpose, from hiring crowdworkers to the paper's authors labeling the data themselves. Such a task is quite similar to (or a form of) structured content analysis, which is a longstanding methodology in the social sciences and humanities, with many established best practices. In this paper, we investigate to what extent a sample of machine learning application papers in social computing --- specifically papers from ArXiv and traditional publications performing an ML classification task on Twitter data --- give specific details about whether such best practices were followed. Our team conducted multiple rounds of structured content analysis of each paper, making determinations such as: Does the paper report who the labelers were, what their qualifications were, whether they independently labeled the same items, whether inter-rater reliability metrics were disclosed, what level of training and/or instructions were given to labelers, whether compensation for crowdworkers is disclosed, and if the training data is publicly available. We find a wide divergence in whether such practices were followed and documented. Much of machine learning research and education focuses on what is done once a "gold standard" of training data is available, but we discuss issues around the equally-important aspect of whether such data is reliable in the first place.Comment: 18 pages, includes appendi

Oligo-DNA Custom Macroarray for Monitoring Major Pathogenic and Non-Pathogenic Fungi and Bacteria in the Phyllosphere of Apple Trees

BACKGROUND: To monitor the richness in microbial inhabitants in the phyllosphere of apple trees cultivated under various cultural and environmental conditions, we developed an oligo-DNA macroarray for major pathogenic and non-pathogenic fungi and bacteria inhabiting the phyllosphere of apple trees. METHODS AND FINDINGS: First, we isolated culturable fungi and bacteria from apple orchards by an agar-plate culture method, and detected 32 fungal and 34 bacterial species. Alternaria, Aureobasidium, Cladosporium, Rhodotorula, Cystofilobasidium, and Epicoccum genera were predominant among the fungi, and Bacillus, Pseudomonas, Sphingomonas, Methylobacterium, and Pantoea genera were predominant among the bacteria. Based on the data, we selected 29 major non-pathogenic and 12 phytopathogenic fungi and bacteria as the targets of macroarray. Forty-one species-specific 40-base pair long oligo-DNA sequences were selected from the nucleotide sequences of rDNA-internal transcribed spacer region for fungi and 16S rDNA for bacteria. The oligo-DNAs were fixed on nylon membrane and hybridized with digoxigenin-labeled cRNA probes prepared for each species. All arrays except those for Alternaria, Bacillus, and their related species, were specifically hybridized. The array was sensitive enough to detect 10(3) CFU for Aureobasidium pullulans and Bacillus cereus. Nucleotide sequencing of 100 each of independent fungal rDNA-ITS and bacterial 16S-rDNA sequences from apple tree was in agreement with the macroarray data obtained using the same sample. Finally, we analyzed the richness in the microbial inhabitants in the samples collected from apple trees in four orchards. Major apple pathogens that cause scab, Alternaria blotch, and Marssonina blotch were detected along with several non-phytopathogenic fungal and bacterial inhabitants. CONCLUSIONS: The macroarray technique presented here is a strong tool to monitor the major microbial species and the community structures in the phyllosphere of apple trees and identify key species antagonistic, supportive or co-operative to specific pathogens in the orchard managed under different environmental conditions

Nucleotide Polymorphisms in the Canine Noggin Gene and Their Distribution Among Dog (Canis lupus familiaris) Breeds

Noggin (NOG) is an important regulator for the signaling of bone morphogenetic proteins. In this study, we sequenced the complete coding sequence of the canine NOG gene and characterized the nucleotide polymorphisms. The sequence length varied from 717 to 729 bp, depending on the number of a 6-bp tandem repeat unit (GGCGCG), an insertion that has not been observed in other mammalian NOG genes investigated to date. It results in extensions of (Gly–Ala)3–5 in the putative NOG protein. To survey the distribution of these tandem repeat polymorphisms, we analyzed 126 individuals in seven dog breeds. We identified only three alleles: (GGCGCG)3, (GGCGCG)4, and (GGCGCG)5. Although the allele frequencies were remarkably different among the breeds, the three alleles were present in all seven of the breeds and did not show any deviation from Hardy–Weinberg equilibrium