Traveling-wave deceleration of SrF molecules

We report on the production, deceleration and detection of a SrF molecular beam. The molecules are captured from a supersonic expansion and are decelerated in the X$^2\Sigma^+ (v=0, N=1)$ state. We demonstrate the removal of up to 40% of the kinetic energy with a 2 meter long modular traveling-wave decelerator. Our results demonstrate a crucial step towards the preparation of ultracold gases of heavy diatomic molecules for precision spectroscopy

Tiled fuzzy Hough transform for crack detection

Surface cracks can be the bellwether of the failure of any component under loading as it indicates the component's fracture due to stresses and usage. For this reason, crack detection is indispensable for the condition monitoring and quality control of road surfaces. Pavement images have high levels of intensity variation and texture content, hence the crack detection is difficult. Moreover, shallow cracks result in very low contrast image pixels making their detection difficult. For these reasons, studies on pavement crack detection is active even after years of research. In this paper, the fuzzy Hough transform is employed, for the first time to detect cracks on any surface. The contribution of texture pixels to the accumulator array is reduced by using the tiled version of the Hough transform. Precision values of 78% and a recall of 72% are obtaining for an image set obtained from an industrial imaging system containing very low contrast cracking. When only high contrast crack segments are considered the values move to mid to high 90%

Road Damage Detection Acquisition System based on Deep Neural Networks for Physical Asset Management

Research on damage detection of road surfaces has been an active area of re-search, but most studies have focused so far on the detection of the presence of damages. However, in real-world scenarios, road managers need to clearly understand the type of damage and its extent in order to take effective action in advance or to allocate the necessary resources. Moreover, currently there are few uniform and openly available road damage datasets, leading to a lack of a common benchmark for road damage detection. Such dataset could be used in a great variety of applications; herein, it is intended to serve as the acquisition component of a physical asset management tool which can aid governments agencies for planning purposes, or by infrastructure mainte-nance companies. In this paper, we make two contributions to address these issues. First, we present a large-scale road damage dataset, which includes a more balanced and representative set of damages. This dataset is composed of 18,034 road damage images captured with a smartphone, with 45,435 in-stances road surface damages. Second, we trained different types of object detection methods, both traditional (an LBP-cascaded classifier) and deep learning-based, specifically, MobileNet and RetinaNet, which are amenable for embedded and mobile and implementations with an acceptable perfor-mance for many applications. We compare the accuracy and inference time of all these models with others in the state of the art

A gas cell for stopping, storing and polarizing radioactive particles

A radioactive beam of 20Na is stopped in a gas cell filled with Ne gas. The stopped particles are polarized by optical pumping. The degree of polarization that can be achieved is studied. A maximum polarization of 50% was found. The dynamic processes in the cell are described with a phenomenological model.Comment: 16 pages, 6 figure

The Atlantic Bonito ( Sarda sarda,Bloch 1793) Transcriptome and Detection of Differential Expression during Larvae Development

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Integrated annotation and analysis of genomic features reveal new types of functional elements and large-scale epigenetic phenomena in the developing zebrafish

Zebrafish, a popular model for embryonic development and for modelling human diseases, has so far lacked a systematic functional annotation programme akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish developmental functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and reanalysed published genomics data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements in development, including novel classes with distinct features dependent on their activity in time and space. We delineated the distinction between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of how they relate to each other. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals

The Tetraodon nigroviridis reference transcriptome: Developmental transition, length retention and microsynteny of long non-coding RNAs in a compact vertebrate genome

Pufferfish such as fugu and tetraodon carry the smallest genomes among all vertebrates and are ideal for studying genome evolution. However, comparative genomics using these species is hindered by the poor annotation of their genomes. We performed RNA sequencing during key stages of maternal to zygotic transition of Tetraodon nigroviridis and report its first developmental transcriptome. We assembled 61,033 transcripts (23,837 loci) representing 80% of the annotated gene models and 3816 novel coding transcripts from 2667 loci. We demonstrate the similarities of gene expression profiles between pufferfish and zebrafish during maternal to zygotic transition and annotated 1120 long non-coding RNAs (lncRNAs) many of which differentially expressed during development. The promoters for 60% of the assembled transcripts result validated by CAGE-seq. Despite the extreme compaction of the tetraodon genome and the dramatic loss of transposons, the length of lncRNA exons remain comparable to that of other vertebrates and a small set of lncRNAs appears enriched for transposable elements suggesting a selective pressure acting on lncRNAs length and composition. Finally, a set of lncRNAs are microsyntenic between teleost and vertebrates, which indicates potential regulatory interactions between lncRNAs and their flanking coding genes. Our work provides a fundamental molecular resource for vertebrate comparative genomics and embryogenesis studies

Tiling Histone H3 Lysine 4 and 27 Methylation in Zebrafish Using High-Density Microarrays

BACKGROUND: Uncovering epigenetic states by chromatin immunoprecipitation and microarray hybridization (ChIP-chip) has significantly contributed to the understanding of gene regulation at the genome-scale level. Many studies have been carried out in mice and humans; however limited high-resolution information exists to date for non-mammalian vertebrate species. PRINCIPAL FINDINGS: We report a 2.1-million feature high-resolution Nimblegen tiling microarray for ChIP-chip interrogations of epigenetic states in zebrafish (Danio rerio). The array covers 251 megabases of the genome at 92 base-pair resolution. It includes ∼15 kb of upstream regulatory sequences encompassing all RefSeq promoters, and over 5 kb in the 5' end of coding regions. We identify with high reproducibility, in a fibroblast cell line, promoters enriched in H3K4me3, H3K27me3 or co-enriched in both modifications. ChIP-qPCR and sequential ChIP experiments validate the ChIP-chip data and support the co-enrichment of trimethylated H3K4 and H3K27 on a subset of genes. H3K4me3- and/or H3K27me3-enriched genes are associated with distinct transcriptional status and are linked to distinct functional categories. CONCLUSIONS: We have designed and validated for the scientific community a comprehensive high-resolution tiling microarray for investigations of epigenetic states in zebrafish, a widely used developmental and disease model organism

Zebrafish Whole-Adult-Organism Chemogenomics for Large-Scale Predictive and Discovery Chemical Biology

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology