dataesr/scientific-paragraphs-categorization huggingface dataset:
), thereby covering the essential topics that nurses usually assess during hospital visits. All data are sent to a MySQL relational database stored in the secure environment of the hospital server. Parents have visual feedback of their baby's weight trend, plotted and continuously updated on the basis of the answers on the periodic questionnaires. Another important feature is the option of exchanging email messages with the nurses, making it possible to raise doubts and answer questions about baby care. 3. Staff Area: by logging in, neonatal nurses and pediatricians can access their special area, where they can monitor parents' answers to the questionnaires retrieved from the database, shown in dynamic Flash charts (see Multimedia Appendix 4). After evaluating the baby's data, nurses can write a message directly from the website to the parents to provide advice and comments about the newborn's care.
Acknowledgments The authors wish to thank  Dr. Gemma Ginovart , Director of the  Neonatal Unit of the Hospital de la Santa Creu i de Sant Pau ,  Dr. Eduard Carreras , Director of the Pediatrics Service, and  Ms. Meritxell Cucala ,  Department of Nursing Innovation and Projects , for their encouragement and support in developing and implementing this telemedicine application. The authors thank  Mr. Vito Luigi Orlando  for his valuable comments and suggestions on the cost analysis.
Methods. Combining deep wide field multi-epoch panchromatic images obtained at various obervatories over up to 14 years, we derive accurate proper motions for the sources present in the field of the survey. The datasets cover ≈80 square degrees, centered around the Seven Sisters. Results. Using new tools, we have computed a catalog of 6 116 907 unique sources, including proper motion measurements for 3 577 478 of them. The catalogue covers the magnitude range between i =12∼24 mag, achieving a proper motion accuracy <1 mas y -1 for sources as faint as i=22. 5 mag. We estimate that our final accuracy reaches 0. 3 mas yr -1 in the best cases, depending on magnitude, observing history, and the presence of reference extragalactic sources for the anchoring onto the ICRS.
The DANCe Project: Taking advantage of the wide field surveys performed in the early 2000, we are performing a comprehensive study of kinematics in a number of nearby ( 1 kpc) associations and clusters. A preliminary list of targets with publicly available archival observations is given in  Bouy et al. (2011) , and we are welcoming suggestions and proposals of collaborative studies for other associations and clusters of particular interest. The initial surveys reached sensitivities well beyond the substellar limit at the age and distance of these associations. Complementing these archival data with new sensitive wide field observations, we are compiling a multi-epoch panchromatic database encompassing large (several tens of square degrees) areas of young nearby associations. This database is used to derive accurate proper motions for all sources with multi-epoch detections.
Archival Data In an effort to compile the most complete dataset -both in terms of spatial and time coverage -we searched the Subaru Telescope, the Isaac Newton Telescope (INT), the United Kingdom Infrared Telescope (UKIRT), the Cerro Tololo Inter-American Observatory (CTIO, at NOAO), the Kitt Peak National Observatory (KPNO, at NOAO), the Canada France Hawai'i Telescope (CFHT) and the European Southern Observatory (ESO) public archives for wide-field images within a box of 10 • ×10 • centered on the Pleiades. Figure  1  and Table  1  give an overview of the properties and coverage of the various datasets and instruments. The filter sets used for these observations are described in Fig. 2  1. The data were obtained with 9 different instruments at 5 observatories. A summary of their characteristics is given in the following sections.
• INT Telescope: We retrieved the detrended individual Wide Field Camera (WFC, Ives 1998) images from the ING public archive. About 88% of these observations were obtained under photometric ambient conditions, as described by the INT data quality control system, and the nightly photometric zeropoints provided by the ING were applied. • UKIRT Telescope: The cluster was observed in the near-infrared (near-IR) with the Wide Field CAMera (WFCAM,  Casali et al. 2007 ) in the course of the UKIRT InfraRed Deep Sky Surveys (UKIDSS,  Lawrence et al. 2007 ). The UKIDSS survey provides a homogeneous coverage of the association in the Z,Y,J,H and Ks filters. The UKIDSS release (DR9) includes observations performed between September 2005 and January 2011, and are described in  Lodieu et al. (2007a)  and  Lodieu et al.
• KPNO Mayall Telescope: We searched and retrieved NOAO Extremely Wide Field Infrared Imager (NEWFIRM)  (Autry et al. 2003)  and MOSAIC-1  (Wolfe et al. 2000)  images in the NOAO Science Archive. The MOSAIC1 images were processed following standard procedures using the mscred package within IRAF 2  and the relevant calibration frames, as recommended in the User's manual. The detrended and sky-subtracted NEWFIRM images and their respective confidence maps were retrieved from the NOAO archive  (Swaters et al. 2009 ). The NEWFIRM J-band photometry was then tied to the UKIDSS one.
• CTIO Blanco Telescope: MOSAIC2 is a clone instrument of the MOSAIC1 installed on the Blanco telescope at CTIO. We retrieved the raw images from the NOAO Science Archive, and processed them following standard procedures using the mscred package within IRAF and the relevant calibration frames, as recommended in the User's manual. Although in most cases sets of several consecutive and dithered images were obtained, we chose to perform the analysis on the individual images rather than on stacks. While individual images do not go as deep as stacks, this choice ensures that the PSF (and hence the astrometric accuracy) and noise are not affected by the stacking process. As we will see, using individual images offers other advantages, in particular a more efficient rejection of problematic frames or measurements, and an opportunity to reach out for faster moving objects.
Astrometric analysis The astrometric analysis involves vast amounts of multiepoch, multi-instrument, multi-wavelength datasets, and requires highly automatized tools; all our processing is done using the AstrOmatic 3  software suite  (Bertin 2010). The whole process is decomposed into the following steps, which we describe in detail in the next sections: V+R (Broad) CTIO / MOSAIC2 Fig. 2  Transmission of the various filters used in this study. In the z-band, the sensitivity is limited by the CCD quantum efficiency, which typically drops at 900∼1000 nm.
Modeling the Point Spread Function with PSFEx The first step in making precise measurements of the positions of individual sources is to compute an accurate model of the (variable) PSF for every chip of every exposure. A large fraction of the images (those with good seeing) are significantly undersampled with some of the instruments, especially WFCam and Mosaic2. This requires the PSF to be modeled at the sub-pixel level. The PSFEx software  (Bertin 2011 ) has been specifically designed to work with undersampled images and arbitrary PSF shapes. Briefly, PSFEx fits the image of every point-source p s with a projection on the local pixel grid of the linear combination of basis vectors φ b by minimizing the χ 2 function of the coefficient vector c χ 2 PSF (c) = s p s -ps (c) T W s p s -ps (c) , ( 1 ) where ps is the PSF model sampled at the location of star s: ps (c) = f s R(x s ) b c b φ b.
Cataloging All sources with more than 3 pixels above 1. 5 standard deviations of the local background are extracted with the SExtractor package  (Bertin & Arnouts 1996). We measure fluxes and positions using the new Sérsic model-fitting option in SExtractor  (Bertin 2011) , which relies on the empirical PSF model previously derived by PSFEx. In practice, PSF-convolved Sérsic model fits offer a level of astrometric accuracy comparable to that of pure PSF fits for point sources, while making it possible to measure galaxy positions (see §7. 10) and offering a better match to short asteroid trails (see §11. 2). Contrary to fast iterative Gaussian centroiding (the so-called WIN estimates), they are largely immune to the spatial discretization effects caused by undersampling. Moreover, model-fitting allows saturated pixels to be censored without degrading excessively the positional accuracy on (moderately) saturated stars, thereby significantly increasing the fraction of bright sources suitable for astrometry.
Computing a global astrometric solution The global astrometric solution is computed with version 2. 0 of the SCAMP software package  (Bertin 2006). SCAMP is itself a mini-pipeline performing various operations before and after computing the global solution per se. These operations are described in details in the SCAMP documentation; in the following we focus only on those that are especially important for this study. The global solution computed by SCAMP is the result of minimizing the quadratic sum of differences in position between overlapping detections from pairs of catalogs, an approach pioneered by  Eichhorn (1960) : χ 2 astrom = s a a>b 1 σ 2 s,a + σ 2 s,b ||ξ a (x s,a ) -ξ b (x s,b )|| 2 , ( 9 ) where s is the source index, a and b are catalog indices, and σ s,a is the positional uncertainty for source s in catalog a.
Experience shows that the static part of the distortion pattern changes from run to run, sufficiently enough to undermine the global solution. The same goes with filter changes. Therefore the count of "astrometric instruments" entering Eq. (  10 ) far exceeds that of cameras, because what matters is eventually the combination camera/filter/run. Relying on header information and logbooks, we identified 94 such combinations for the whole dataset, taken with 9 cameras through 30 filters. For the minimum of χ 2 astrom to be unique, the solution must be anchored on the sky. SCAMP does that by forcing one of the catalogs in Eq. (  9 ) to be a catalog of astrometric references with fixed ξ coordinates. We selected 2MASS  (Skrutskie et al. 2006 ) as a reference catalog, because of its suitable depth, good homogeneity, and tight range of observation epochs.
5 ). Even though the astrometric precision is considerably worse for extended objects compared to point sources, the large number of resolved extragalactic sources allows a statistically meaningful and accurate calculation of the offset to the ICRS. We select all sources with a SPREAD MODEL indicative of an extended object that display a proper motion less than 30 mas yr -1 in both R. A and Dec (≈379 000 sources), and compute their median proper motion within boxes of 1 • ×1 •. Figure  10  shows the spatial distribution of median apparent proper motions µ α cos δ and µ δ. A gradient pointing towards the galactic plane is clearly seen in both components, which we interpret as the contribution of galactic stars to the overall astrometric solution derived by our algorithm. To correct for these systematic motions, we fit a 4 th order polynomial surface to apparent motions in our "extragalactic" dataset and use it to correct all individual measurements.
5 ), iv) rejecting outliers in the proper motion fit (see section 7. 9). artefacts produced by saturated stars (such as deformed point spread functions, streaks and bleeding due to pixel over- This effect is minimized by carefully setting the saturation levels in SExtractor input parameter files. We note that SExtractor PSF fitting module is capable of adjusting a PSF to the non-saturated pixel of a source, extending the dynamic range of our study above the saturation and nonlinearity regime of the instruments used in this survey. The corresponding astrometry, although less precise, is nevertheless often good enough to derive relatively accurate proper motion, as illustrated in Fig. 13. extragalactic sources and nebulosities are often extended and their centroid position can be wavelength dependent.
Comparison with other astrometric catalogues In the following, we compare our measurements to various astrometric databases found in the litterature and check the consistency of our results. Several of these catalogues are not tied to any absolute reference frame (e. g UCAC4, UKIDSS), and a direct comparison with the DANCe catalogue (anchored on background galaxies) is therefore not strictly correct. We nevertheless note that the difference can in general be approximated to a simple offset.
Tycho The Tycho catalogue  (Høg et al. 2000)  provides proper motion measurements precise to about 2. 5 mas yr -1 and derived from a comparison of the ESA Hipparcos satellite measurements with the Astrographic Catalogue and 143 other ground-based astrometric catalogues. These catalogues are unfortunately limited to V T 12. 5 mag, very close to the saturation or non-linear regime of the datasets used to build the DANCe catalogue. With this limitation in mind, we compare the results obtained for the 3665 common sources. The agreement is good within the large uncertainties, as shown in Fig. 13. As expected, the difference between the Tycho and DANCe measurement displays a clear dependance on the luminosity, fainter sources being in general in better agreement than bright sources.
The "horizontal outliers" are in general bright sources, and we interpret them as erroneous or inaccurate measurements due to saturation and/or non-linearity of the DANCe datasets. As expected, the distribution of sources is asymetric, with significantly more sources along the direction of the solar antapex (µ α cosδ >0 and µ δ <0), which coincidently also corresponds to the Pleiades cluster's mean motion direction. 10. 3. PPMXL  Roeser et al. (2010)  derived improved mean positions and proper motions on the ICRS system by combining USNO-B1. 0 and 2MASS astrometry. The catalog is complete from the brightest stars up to about V ≈20 mag over the entire sky. Typical individual errors of the proper motions range between 4-10 mas yr -1. Figure  15  compares the proper motion measurements in RA and Dec for the PPMXL and DANCe surveys as a function of the PPMXL uncertainty.
2012 ) make it much more sensitive to the presence of deviant and high leverage points and translates into large numbers of errors. The presence of corrupted frames in the UKIDSS DR9 release (discarded by our quality assurance but not by the UKIDSS quality assurance, M. Read private comm. ) probably also result in a number of problematic measurements. By using the individual UKIDSS images rather than stacked UKIDSS mosaics, and by including a robust regression algorithm for the proper motion fit,   some proper motion measurements are more reliable than others, and the uncertainty does not always reflect the reliability. Parameters useful to evaluate the reliability of an individual proper motion measurement include in particular (but not exhaustively): the number of astrometric measurements used for the fit, the maximum time baseline, the reduced-χ 2 of the fit measurements errors, unknown systematics and problematic measurements present in any large scale astrometric catalogue most likely always affect the completeness of studies based on their proper motion measurements and should be carefully discussed While a universal rule to assess the quality of a given measurement cannot be given, we have found that the following proper motion measurements should be considered with caution: sources close to or above the saturation or linearity limit of the instruments (in the case of the current dataset, i ≈13 mag), or sources with small numbers of measurements used for the proper motion fit (NPOS_OK attribute) sources with large reduced-χ 2 (CHI2_ASTROM attribute) In general, and whenever possible, a visual inspection of the individual images is the most robust way to discard problematic measurements.
The Pleiades cluster A detailed scientific analysis of the Pleiades cluster kinematics based on the DANCe catalogue will be presented in a future article  (Bouy et al. , 2012, in prep. ). In this section, we give a brief and general overview of the results obtained. Figure  17  shows the vector point diagram of stellar motions obtained with the dataset described above. The group of co-moving cluster members appears clearly around (20,-40) mas yr -1. The DANCe catalogue also offers a unique photometric database. In the case of the Pleiades dataset presented here, a total of 29 photometric instruments covering the spectral range between 0. 37 µm (Sloan u-band) and 2. 2 µm (UKIRT K-band). Figure  18  shows a i vs ri color magnitude diagram using the photometry extracted from the MegaCam and UKIDSS images.
Solar system bodies Solar system bodies have typical velocities in the range between ≈2 hr -1 (trans-neptunian objects, hereafter TNO) and ≈20 hr -1 (main belt asteroids, hereafter MBA). Most observations used in this study are made of several consecutive and dithered images of the same field. Fast moving sources such as solar system bodies can therefore be easily identified. Minor planets are expected to be extremely numerous in the direction of the Pleiades cluster, as it lies close to the ecliptic plane. A Fig. 17  Vector point diagram of stellar motions obtained with the datasets described in this article. The Pleiades locus is visible in the lower right quadrant. Its slight elongation may be interpreted as a perspective effect related to the depth of the cluster. detailed analysis of the solar system bodies encountered in the DANCe dataset will be presented in a future article  (Bouy et al.
in prep)  and we only give a brief overview of the capabilities of our algorithms for solar system studies. A basic selection of all sources with a proper motion greater of ≈20 hr -1 gave 11404 candidate minor planets. A request on SkyBot  (Berthier et al. 2006)  indicates that only 2837 have a counterpart within a radius of 1 in the database of known solar system bodies as of August 2012, all of them main belt asteroids. A visual inspection of ≈100 random candidates shows that 5% are false detections due to artefacts (cosmic ray or ghost coincidence, false detection, etc. ). After inspection and rejection of these artefacts, the astrometric and photometric measurements will be submitted to the IAU Minor Planet Center. The high precision astrometry (with a typical accuracy better than 10 mas on individual epochs) will be extremely valuable to refine the orbital solutions.
Conclusions and future prospects We have presented a set of tools capable of deriving high precision relative proper motions using large numbers (several thousands) of ground-based images originating from various in-struments. We apply these tools on multi-epoch panchromatic datasets of the nearby Pleiades cluster, and compare to other astrometric catalogues. The results demonstrate our ability to derive accurate proper motion with an estimated accuracy better than 1 mas yr -1 for sources as faint as i=22∼23 mag, depending on the luminosity and observational history (time baseline, number and quality of the frames, as well as presence and number of reference extragalactic sources for the anchoring on the ICRS). The DANCe project will use this method to conduct a survey of the most nearby star forming regions and clusters.
Acknowledgements. We are thankful to our anonymous referee for a thorough and constructive review which helped significantly improve this article. H. Bouy is funded by the the  Ramón y Cajal fellowship program  number  RYC-2009-04497. H. Bouy acknowledges funding and support of the  Université Joseph Fourier 1, Grenoble, France. This research has been funded by  Spanish  grants  AYA2012-38897-C02-01 ,  AYA2010-21161-C02-02 ,  CDS2006-00070  and  PRICIT-S2009/ESP-1496. E. Moraux  ackowledges funding from the  Agence Nationale pour la Recherche program  ANR  2010 JCJC 0501 1  " DESC (Dynamical Evolution of Stellar Clusters )". J. Bouvier  acknowledges funding form the  Agence Nationale pour la Recherche program ANR 2011 Blanc SIMI 5-6 020 01 ("Toupies "). J. Bouvier  and  E. Moraux  acknowledge support from.
The coupling of chromosome conformation capture (3C) with next-generation sequencing technologies enables the high-throughput detection of longrange genomic interactions, via the generation of ligation products between DNA sequences, which are closely juxtaposed in vivo. These interactions involve promoter regions, enhancers and other regulatory and structural elements of chromosomes and can reveal key details of the regulation of gene expression. 3C-seq is a variant of the method for the detection of interactions between one chosen genomic element (viewpoint) and the rest of the genome. We present r3Cseq, an R/Bioconductor package designed to perform 3C-seq data analysis in a number of different experimental designs. The package reads a common aligned read input format, provides data normalization, allows the visualization of candidate interaction regions and detects statistically significant chromatin interactions, thus greatly facilitating hypothesis generation and the interpretation of experimental results.
In addition, these tools do not facilitate the analysis of replicate experiments. To address these needs, we have developed an R/Bioconductor package called r3Cseq, a publicly available bioinformatics software package for 3C-seq studies, to perform the analysis of data generated by 3C-seq technology. The package provides a comprehensive workflow that starts with the aligned reads and ends with an interpretable visualization of regions of interaction. It can analyze data from various experimental designs, with or without a control experiment, and it supports in-depth data analysis of replicate experiments. It enables 3C-seq data normalization and statistical analysis for the identification of cis and trans interactions (i. e. interactions between regions on the same chromosome and interactions between different chromosomes, respectively), using both restriction fragment-based and window-based methods.
These functions will allow scientists to compare different ways of analyzing their data set and select the most suitable analysis for the interpretation of their data. Finally, r3Cseq produces a range of plots specifically designed for the visualization of genomic regions that physically interact with the selected genomic regions of interest. The output generated by r3Cseq consists of simple text and bedGraph (16) files compatible with visualization using other tools, such as the UCSC Genome Browser  (16)  and IGV  (17).
MATERIALS AND METHODS Principles of the 3C-seq procedure and r3Cseq data analysis workflow The 3C-seq experimental procedure is outlined in Figure  1 , and the subsequent r3Cseq data analysis workflow is shown in Figure  2. Isolated cells are treated with a cross-linking agent to preserve in vivo nuclear proximity between DNA sequences. The DNA isolated from these cells is then digested using a primary restriction enzyme, typically a 6-bp cutting enzyme, such as HindIII, EcoRI or BamHI. The digested products are then ligated under diluted conditions to favor intra-molecular over inter-molecular ligation events. This digested and ligated chromatin yields composite sequences representing (distal) genomic regions that are in close physical proximity in the nuclear space. The digested and ligated chromatin is then de-cross-linked and subjected to a second restriction digest using a four-cutter (e.
After trimming, reads are mapped against a reference genome using alignment software, such as Bowtie  (18). Our r3Cseq package has been developed in the R statistical framework  (19)  as part of Bioconductor  (20). It uses binary alignment/map (BAM)-aligned read files as input  (21) , which are generated by commonly used alignment software and carries out operations, such as class initialization, counting aligned reads per restriction fragment or per window size, read count normalization, statistical analysis of interactions in both cis and trans, data visualization and data export of the identified contacting regions. Figure  2  shows the main features and the sequential steps of the r3Cseq pipeline.