Red yeasts from leaf surfaces and other habitats : three new species and a new combination of Symmetrospora (Pucciniomycotina, Cystobasidiomycetes)

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On-sky observations with an achromatic hybrid phase knife coronagraph in the visible

CONTEXT: The four-quadrant phase mask stellar coronagraph, introduced by D. Rouan et al., is capable of achieving very high dynamical range imaging and was studied in the context of the direct detection of extra-solar planets. Achromatic four-quadrant phase mask is currently being developed for broadband IR applications. AIMS: We report on laboratory and on-sky tests of a prototype coronagraph in the visible. This prototype, the achromatic hybrid phase knife coronagraph, was derived from the four-quadrant phase mask principle. METHODS: The instrumental setup implementing the coronagraph itself was designed to record the pre- and post-coronagraphic images simultaneously so that an efficient real-time image selection procedure can be performed. We describe the coronagraph and the associated tools that enable robust and repeatable observations. We present an algorithm of image selection that has been tested against the real on-sky data of the binary star HD80081 (* 38 Lyn). RESULTS Although the observing conditions were poor, the efficiency of the proposed method is proven. From this experiment, we derive procedures that can apply to future focal instruments associating adaptive optics and coronagraphy, targeting high dynamic range imaging in astronomy, such as detecting extra-solar planets

IsoSeq transcriptome assembly of C3 panicoid grasses provides tools to study evolutionary change in the Panicoideae

The number of plant species with genomic and transcriptomic data has been increasing rapidly. The grasses—Poaceae—have been well represented among species with published reference genomes. However, as a result the genomes of wild grasses are less frequently targeted by sequencing efforts. Sequence data from wild relatives of crop species in the grasses can aid the study of domestication, gene discovery for breeding and crop improvement, and improve our understanding of the evolution of C4 photosynthesis. Here, we used long-read sequencing technology to characterize the transcriptomes of three C3 panicoid grass species: Dichanthelium oligosanthes, Chasmanthium laxum, and Hymenachne amplexicaulis. Based on alignments to the sorghum genome, we estimate that assembled consensus transcripts from each species capture between 54.2% and 65.7% of the conserved syntenic gene space in grasses. Genes co-opted into C4 were also well represented in this dataset, despite concerns that because these genes might play roles unrelated to photosynthesis in the target species, they would be expressed at low levels and missed by transcript-based sequencing. A combined analysis using syntenic orthologous genes from grasses with published reference genomes and consensus long-read sequences from these wild species was consistent with previously published phylogenies. It is hoped that these data, targeting underrepresented classes of species within the PACMAD grasses— wild species and species utilizing C3 photosynthesis—will aid in future studies of domestication and C4 evolution by decreasing the evolutionary distance between C4 and C3 species within this clade, enabling more accurate comparisons associated with evolution of the C4 pathway

XNAT-PIC: Extending XNAT to Preclinical Imaging Centers

Molecular imaging generates large volumes of heterogeneous biomedical imagery with an impelling need of guidelines for handling image data. Although several successful solutions have been implemented for human epidemiologic studies, few and limited approaches have been proposed for animal population studies. Preclinical imaging research deals with a variety of machinery yielding tons of raw data but the current practices to store and distribute image data are inadequate. Therefore, standard tools for the analysis of large image datasets need to be established. In this paper, we present an extension of XNAT for Preclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-source platform for securely hosting, sharing, and processing of clinical imaging studies. Despite its success, neither tools for importing large, multimodal preclinical image datasets nor pipelines for processing whole imaging studies are yet available in XNAT. In order to overcome these limitations, we have developed several tools to expand the XNAT core functionalities for supporting preclinical imaging facilities. Our aim is to streamline the management and exchange of image data within the preclinical imaging community, thereby enhancing the reproducibility of the results of image processing and promoting open science practices

COMPARING GEOSTATISTICAL METHODS ON FLOOD RISK TO INFRASTRUCTURE IN SOUTHEAST ASIA USING GOOGLE STREET VIEW IMAGERY: A MASTER’S THESIS

Urban flooding poses a serious challenge to development and the lives of people, particularly the residents of the rapidly expanding towns and cities in developing countries. Floods affect people\u27s livelihood in Southeast (SE) Asia, ranging from death and injury to damaged homes, infrastructures, and agricultural land. In addition, floods expose infrastructure to more risks of structural damage, wearing them out, and aging them quickly, thus increasing maintenance and replacement costs. Presented study found associations between such infrastructure elements as sill height, floors, building structures (e.g., attached vs. detached), slope, drainage, land-use, and street conditions. The study used Mechanical Turk method to collect data for comparative analysis using Kernel Density Estimation, Hotspot Analysis (Gedis-Ord Gi*), and Thiessen Polygon to define the best visualization of the flood vulnerability in five major cities in Southeast Asia