dataesr/scientific-paragraphs-categorization huggingface dataset:
Data variables, data collection and sources of data Data variables collected in relation to the study objectives included the number of medical admissions each year and the number with a hospital in-patient admission diagnosis of DM collected from the hospital health information system logbooks; age; sex; residence; type of DM; indications for hospital admission; existing complications and hospital discharge outcomes collected from patient medical charts. A data abstraction sheet was prepared into which the relevant data were entered. The data were collected in August 2014 by identifying the medical record number from the Health Management Information System log book, which was then used to trace and access individual patient medical charts. The principal investigator led the abstraction process, aided by local co-investigators.
Public Health Action DM in Addis Ababa, Ethiopia 77 riod, and there was no need for any sampling framework. The study report also followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 14 Limitations included the operational nature of the study and the use of data already collected from patient files, which might have been inaccurate. Moreover, in nearly 10% of the patients registered as having DM in the health information log books, this information was incorrect, and in another 10% the patients' medical charts could not be found. The findings of this study support the belief that DM is a large and growing global public health problem, especially in low-and middle-income countries and in sub-Saharan Africa. 2, 15 The main indication for admission was diabetic foot ulcer/gangrene, especially in patients with type 2 DM, in line with other reports in Africa.
The programme was funded by The Union, MSF, the Department for International Development (DFID, London, UK) and WHO. We also thank the School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia, for financial support. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. In accordance with WHO's open-access publication policy for all work funded by WHO or authored/ co-authored by WHO staff members, the WHO retains the copyright of this publication through a Creative Commons Attribution intergovernmental organisation licence (http:// creativecommons. org/ licenses/by/3. 0/igo/ legalcode) which permits unrestricted use, distribution and reproduction in any medium provided the original work is properly cited. Conflict of interest: none declared.
With the conventional method, information is collected by an assessment team who meets several of the system's stakeholders, including field workers, central institutional organizations and intermediate units. With the flash method, data were collected by the same person, by reviewing the literature and regulations, and through phone discussions and individual meetings with people from central institutional organizations. The required data relate to objectives, structure, targeted population, tools, data management, etc. All data were collected through the OASIS detailed questionnaire, for each component and disease. For each disease, 8-9 experts were selected and brought face-to-face to assess the surveillance system. The chosen experts were the managers of each component, specialists in the disease, epidemiologists and animal health surveillance experts used to implementing OASIS.
† EIA is often tested before a sale in France by an agar gel immunodiffusion test (serological test), especially before auctions, because the purchase may be cancelled if the horse is discovered to be infected by the EIA virus within 30 days of the transaction. ‡ The tests to be performed depend on the destination country and the type of export: temporary or permanent. functional sections of the surveillance systems (e. g. central institutional organization, laboratory, surveillance tools), seven critical control points (CCPs, e. g. sampling, coordination and data analysis) and ten attributes (e. g. timeliness, flexibility, simplicity). A criterion's level of satisfaction is measured by a percentage that represents the score obtained for the criterion out of the maximum possible score. The panel highlighted the main strengths and weaknesses of each network.
3 ), data analysis, communication and coordination between all the parties, which is the lowest-rated CCP (Fig. 2 ). Moreover, none of the systems has any joint STC for existing components. Data management is poor for all three diseases (Fig. 1 ). Indeed, each component has its own independent database and only data about confirmed cases are centralized by the public authorities. Another weak point is data analysis (Fig. 2 ). The data are not analysed as a whole and most of the databases are not well suited to epidemiological analysis. Furthermore, the lack of a joint STC prevents a satisfactory scientific validation of results.
Several specific strengths have also been pointed out regarding surveillance tools. For example, data collection forms have been created by the RESPE regarding EVA and the IFCE regarding EIA, EVA and CEM. It would be advisable to draft a standardized form based on existing models for use by all the surveillance components for all three diseases. Regarding data management, automated data transfers (ADTs) are used by accredited laboratories and the IFCE for breeding stock. These transfers are more reliable and faster than manual entries. Given that all analyses are performed by a network of accredited laboratories (or the NRL), ADTs should be generalized to every component. Furthermore, it is necessary to implement a single relational database or to network the existing ones. Moreover, several investigation teams can be activated either by the animal health authorities, stud books or the RESPE when an EIA, EVA or CEM case is detected (Table  4 ).
In their study, the weighting of each criterion is variable and subjective because it was decided by the assessors themselves, depending on their own area of expertise. Other assessments are based on comparison with a standard surveillance document but do not use a scoring grid  [31]. Some authors developed the SERVAL method, which consists of a tailored collective qualitative assessment  [29]. The assessors select 5-10 evaluation attributes from a list of 22 depending on the surveillance network's objectives. To perform a comparative assessment of surveillance networks by means of SERVAL, it would be necessary to select the same attributes for each network. The SERVAL data collection questionnaire is less detailed than the OASIS one and there is currently no scoring guide. Nevertheless, SERVAL, which may include other analyses such as cost analysis, helps assessors to define the purpose and scope of the evaluation (time, resources, etc.
The different transmission modes and the various regulatory statuses of EIA, EVA and CEM have led to the concurrent implementation of several separate surveillance components. Some of them address other diseases. Therefore, although we focused on three diseases, our evaluation covered all the perennial surveillance components for equine diseases in France. Consequently, if the previously mentioned teams and tools were created and pooled, they could be used to improve surveillance of the other threats too. Furthermore, a single national surveillance system for equine infectious diseases could be implemented. In addition, new components could be created and added if relevant, whether for syndromic surveillance (e. g. data collected by renderers), sampling in abattoirs, surveillance of sentinel herds, surveys or surveillance of vectors, for example.
ACKNOWLEDGEMENTS The authors thank the managers of the surveillance components who assessed the three networks, namely  Marie Grandcollot-Chabot  from  DGAL ,  Aymeric Hans  from  ANSES  (NRL for EIA and EVA),  Sandrine Petry  from  ANSES (NRL for CEM ),  Bénédicte Ferry  from the  IFCE , and  Christel Marcillaud-Pitel  and  Charlène Daix  from  RESPE. We also thank  IFCE, ANSES  and the  French National Institute for Agricultural Research (INRA)  for their support.
Mite identification The collected Phytoseiidae were mounted on slides in Hoyer's medium and identified using a phase and interferential contrast microscope (Leica DMLB, Leica Microsystèmes SAS, Rueil-Malmaison, France) (× 400 magnifications). Females were identified using specific keys (e. g. Tixier et al. 2013 ) and according to the nomenclature of  Chant and McMurtry (2007). The study of  Tixier et al. (2006b)  was used to differentiate between Typhlodromus (Typhlodromus) exhilaratus Ragusa and Typhlodromus (Typhlodromus) phialatus Athias-Henriot. Slides are deposited in the mite collection of Montpellier SupAgro (UMR CBGP) and data compiled in a database.
ACKNOWLEDGEMENTS This study is included within the granted project: " Programme Intégrée de Recherche en Agrofores Terie à Restinclières (PIRAT) ", 1999-2012. We thank the  "Conseil Général de l'Hérault " for annual financial supports since 2000. Thanks are also due to  Mr. Thierry Vacher , the vineyard grower for his open-mind and nice interactions. Finally we thank.
Stripe 82 is also covered by deep (24th magnitude) i-band imaging from the Canada-France-Hawaii Telescope (CFHT) in the CS82 survey  (Moraes et al. 2014, Erben et al. in prep)  with comparable image quality (sub-arcsecond), as well as the deeper coverage from SDSS itself across the equatorial stripe. The combination of moderately deep optical-near-infrared imaging over a wide area is ideal for searches for strong, 'red' gravitational arcs. After serendipitously finding a handful of promising lens candidates through visual inspection, we decided to pass the dataset to SPACE WARPS  (Marshall et al. 2015 , More et al. 2015). SPACE WARPS is a citizen science project to discover gravitational lenses run as part of the Zooniverse family 1 of online projects  (Marshall et al. 2015 , More et al. 2015).
eMERLIN L-band We obtained eMERLIN observations over 10. 25 hrs between 1415 UT 9th January 2014 to 0030 UT 10th January 2014 (during the television broadcast). The target source was interspersed with the phase reference calibrator (J0208-0047) with a cycle time of 10 minutes with 7 minutes on the target and 3 minutes on the phase reference. 30 seconds of data were flagged at the start of each scan to remove corrupted data logged during telescope drives with a resulting total time on the target source of 6. 72 hours. The data were divided into 8 intermediate frequencies (IFs) with a total observing bandwidth of 512 MHz at a centre frequency of 1. 5185 GHz. Data calibration was performed from calibration scans on the resolved flux density calibrator 3C286 (1331+305) and the point source calibrator OQ208 (1407+284).
The flux density scale assumed for 3C286 incorporated the latest coefficients from  Perley & Butler (2013)  and a standard model of spatial resolution of the source as observed by eMERLIN. These were used to derive flux densities for the point source OQ208 which has a rising spectrum across the observed band (IF1: 0. 815 Jy, IF8: 1. 208 Jy), with a value at the central frequency of 1. 0078 Jy. Estimated errors in the flux density scale are at the level of 5-10%. Residual delay corrections for the data throughout the run were derived from all three calibration sources. After performing phase and minor gain corrections derived from the phase calibrator, the target was imaged and several rounds of phase-only self-calibration applied. The data calibration and image processing was performed in AIPS.
Karl G. Jansky Very Large Array C-band Data were obtained during 1st March 2014 using the 3-bit samplers and an advanced mode of the immensely powerful WIDAR correlator at the heart of the Karl G. Jansky Very Large Array (VLA, proposal 13B-458), with eight sub-bands in each of the A1/C1, A2/C2, B1/D1 and B2/D2 basebands. We used the VLA's C-band receivers with the correlator instructed to record a band comprising 1024 × 62. 5 kHz full-polarisation channels centred on the 22. 23508 MHz water line, tracking a barycentric redshift of 2. 5529. We also recorded 31 wider bands to sample continuum emission, each comprising 128×1 MHz dual-polarisation channels, covering 4. 05-7. 96 GHz contiguously, with a few small regions of overlap. To mitigate time smearing, since we used the widest (A) configuration of the VLA, the integration time was set to 2 seconds, which resulted in a total data rate of 62 Gb hr -1 , with 26 × 287 seconds (roughly 2 hours) spent integrating on 9io9, 27 × 31 seconds on the gain calibrator, J0215-0222, and 226 seconds on 0137+331 (3C 48) to set the flux density scale.
The data were calibrated using version 4. 1 of CASA, starting with a pass through the initial stages of the VLA data pipeline, then flagging extensively by hand, then re-starting the pipeline where we had previously paused. CASA was also used for imaging, which required us to map and clean a number of bright, nearby sources to reduce contamination of the region around 9io9 by strong sidelobes. The resulting image of 9io9, centred at 5 GHz, has a 500 × 400 mas beam (PA = 7 • ), with an r. m. s. noise level of 3-4μJy beam -1.
James Clerk Maxwell Telescope SCUBA-2 We obtained a 30 minute observation of 9io9 with the SCUBA-2 camera on the James Clerk Maxwell Telescope (JCMT) on 15th January 2014 as part of Director's Discretionary Time (project M13BD12). SCUBA-2 records both 450μm and 850μm data simultaneously. We employed the DAISY scanning mode, appropriate for point sources, and the zenith opacity at 225 GHz was τ225GHz = 0. 07-0. 1 over the course of the observation. The data were reduced with the dynamic iterative map maker of the SMURF package  (Jenness et al. 2011 , Chapin et al. 2013 ) and optimally filtered for detection of point sources. We applied flux conversion factors (FCFs) of 491 Jy pW -1 and 537 Jy pW -1 at 450μm and 850μm respectively, which are the canonical FCFs derived from observations of hundreds of standard sub-millimetre calibrators observed by SCUBA-2 since operations began  (Dempsey et al.
The RSR is a dual-beam dualpolarization spectrometer, with 38 GHz instantaneous bandwidth, designed to detect molecular gas, typically CO line transitions, from high-redshift galaxies. A 1 hour integration with the RSR was conducted towards 9io9 on 19th January 2014 UT with a measured Tsys at 90 GHz of 85 K. The RSR data were reduced and calibrated using the LMT DREAMPY (Data REduction and Analysis Methods in PYthon) package. A single strong spectral-line was detected at 97. 31 GHz (Figure  3 ). The combination of the photometric redshift of z ∼ 2. 6, determined from the (sub-)millimeter and FIR observations presented in this paper, with the RSR spectrum eliminates alternative redshift solutions and any ambiguity in the measured spectroscopic redshift. We conclude that the detected line at 97.
Calibration data comprised of Argon lamp exposures for wavelength calibration, and Halogen lamp exposures for flatfield calibration. The data were reduced with the IRAF twodspec package, and standard procedures for flat-fielding and sky-subtraction for the nod-on-slit technique were used. The final data product is a twodimensional spectrum of 9io9 with a regular sampling along the spatial and spectral directions. To increase the signal-to-noise ratio we binned the data in spectral direction by a factor of 6× and in the spatial direction by a factor of 4×. The total integrated spectrum of the western arc of the red ring of 9io9 is shown in Figure  4. The redshifted nebular emission lines of Hα+[N II] and (unresolved) [O III]λ4959,λ5007 and [S II]λ6717,λ6731 doublets are detected confirming the CO redshift of 2.
The critical radii from Table  1  can be taken with the lens and source redshifts to calculate the lens velocity dispersion for G1 and G2: σG1 = 316 ± 1 km s -1 and σG2 = 80 ± 4 km s -1. Although the eMERLIN data are of somewhat lower signalto-noise, their higher resolution allows at least preliminary investigation of the radio source structure. Using the galaxy mass model established above for the Ks-band and VLA imaging, we can attempt to reconstruct the eMERLIN data using a parametrised Gaussian fit to represent the source. The results are shown in Figure  7. In general, the source reconstruction is subject to considerable degeneracy because the main constraint provided by the lensing concerns the source distribution around the high-magnification region corresponding to the caustic running across it.
Thus, 9io9 is not consistent with a pure starburst, with significant nuclear activity associated with the growth of the central black hole contributing to the radio emission. The current data allow us to postulate, with a reasonable degree of confidence, the basic nature of the radio source. There are some hints that the radio spectral index is flatter in the core component, α ≈ 0. 2 steepening to α ≈ 1 along the ring. This would be consistent with the classic picture of optically thick emission due to synchrotron self-absorption around a compact, dense nuclear source. The steepening spectrum could indicate aging of the rela-tivistic electron population (which lose their energy as E 2 ) along a possible jet, but a more detailed analysis that takes into account the different visibilities sampled by eMERLIN and VLA, improved sampling of the radio spectrum and a more accurate lens model will be needed to investigate this.
ACKNOWLEDGEMENTS We thank the anonymous referee, whose comments improved the clarity of this work. This result would not have been possible without the help of thousands of volunteers participating in the project through BBC Stargazing Live! and the Zooniverse. We thank all of the Citizen Scientists who participated in SPACE WARPS. The full list of their Zooniverse usernames can be found at the following URL: http://spacewarps. org/#/projects/VICS82/summary. We thank  Zbigniew 'Zbish' Chetnik , one of the volunteers who classified 9io9, who appeared on the Stargazing Live! programme to discuss the object. It is our pleasure to thank the  BBC Stargazing Live production team  for their efforts in making SpaceWarps a success:  Liz Bonnin ,  Mark Thompson  (presenters),  Ross Fiddes ,  Gavin Hesketh ,  Amy Hewer ,  Ben Lucas ,  Abi Rose ,  Adam Toth  (production team),  Holly Salter ,  Lizzie Search ,  Lauren Webber  (production co-ordinators),  Clare Huggins  (production manager),  Laura Davey  (production executive),  Alex Dackevych ,  Simon Mackie  (web team),  Ayo Ajibewa ,  Faran Ismailpour ,  Ivan Lazic ,  Kiki Lawrence ,  Keaton Stone  (researchers),  Alastair Duncan  (assistant producers),  Tom Hewitson ,  Alice Jones ,  Penny Palmer ,  Sarah Sarkhel  (VT directors),  Chris Parkin ,  Paul Vanezis  (producers),  Ian Russell  (director),  Helen Thomas  (executive producer),  Paul King  (series producer).
Based in part on data collected at Subaru Telescope, which is operated by the  National Astronomical Observatory of Japan. This work is based on observations carried out with the VLA. The NRAO is a facility of the  NSF  operated under cooperative agreement by  Associated Universities, Inc. The James Clerk Maxwell Telescope has historically been operated by the  Joint Astronomy Centre  on behalf of the STFC, the  National Research Council of Canada  and the  Netherlands Organisation for Scientific Research. Additional funds for the construction of SCUBA-2 were provided by the  Canada Foundation for Innovation. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration.
Acknowledgments We are grateful to public slaughterhouse in Liege for supplying bovine articular cartilage and to  Catholic University of Louvain , especially  Dr Jean-Emile Dubuc , for supplying OA human articular cartilage samples. We thank the  Laboratory of Tumor and Development Biology at the University of Liege  for the supply of the LightCycler 480. We also are thankful to  Prof. Bellahcène  ( Metastasis Research Laboratory, GIGA-Cancer, University of Liege, Belgium ) for technical support with the western blotting.
Acknowledgements Authors thank  Y. Kihn  ( CEMES-CNRS ) and  C. Galaup  ( SPCMIB-Université de Toulouse ) for their support in electron microscopy and time-resolved luminescence investigations, respectively. The Brazilian agencies  FAPESP  ( 2007/55723-6 ,  2011/21551-0 ),  CNPq ,  CAPES , and the  CAPES-COFECUB Brazil-France cooperation program  for the grant to J. M. A. C. are also acknowledged.
Growth and products formation were monitored by measuring OD 600 and by carrying out HPLC analyses, respectively. We found that only very small amounts of EG (2. 93 ± 0. 23 mM) were produced by the yqhD-deleted strain Pen334, whereas strain Pen205 accumulated 31 mM EG (Fig. 3 ). In addition, strain Pen334 consumed only half of the 70 mM (d)-xylose that were initially present in the medium and was unable to sustain growth above 4 units OD 600 , which suggests that the deletion of yqhD had caused the accumulation of toxic levels of glycolaldehyde or a derivative of this compound. Taken together, these data indicate that YqhD is the major glycolaldehyde reductase in E. coli, and suggest that this enzyme is induced in the presence of the synthetic pathway to detoxify glycolaldehyde to EG.
RNA extraction, microarray analysis, and data treatment A detailed description of the experimental conditions for RNA extraction and microarray analysis is provided in  [8]. Briefly, all experiments were carried on M9 mineral medium containing 10 g/L (d)-xylose as the only carbon source. Wild-type cells, wild-type cells exposed to 10 mM glycolaldehyde, and strain Pen205 were harvested during early exponential phase at an OD 600 of ~1. Glycolaldehyde was added to the cultures 30 min before harvest. Cells were separated from the culture medium by centrifugation (1,500×g, 5 min, Eppendorf 5415D). After discarding the supernatant RNA was extracted from the cells by using the RNeasy Mini Kit (QIAGEN). Quantity and quality of the samples were determined by NanoDrop (Thermo) and Bioanalyzer (Agilent Technologies), respectively.
Strain reference Genotype Protocol. The slides were scanned on a Tecan scanner MS200 and analyzed by Feature Extraction V. 11. 5. 1. 1. RNA was extracted and analyzed from three independent experiments for each condition. Background correction and normalization of the transcriptome data was carried out as described previously  [27] [28] [29]. To produce the heatmap shown in Fig. 2b , the expression levels of the corresponding genes were log2 transformed, and the genes were clustered according to the Euclidean distance between their expression levels using complete-linkage clustering  [30].
Acknowledgements The study was in part financed by the  Toulouse White Biotechnology (TWB)  consortium (Project:  PENTOSYS ). DT was supported by a post-doctoral grant ( Science without borders program ) provided by the  CAPES foundation (Ministry of Education, Brazil ). YC was supported by a post-doctoral grant provided by the  Institut National de la Recherche Agronomique-Region Midi-Pyrénées (INRA, France).
ACKNOWLEDGEMENTS -KJT thanks  NWO  for a Rubicon fellowship. FK acknowledges support by the  Fundacio Cellex Barcelona , the  ERC Career integration  grant  294056  (GRANOP), the  ERC starting  grant  307806  (CarbonLight). FK and JGdA acknowledge support by the  E. C. under Graphene Flagship  (contract no. CNECT-ICT-604391 ). JGdA acknowledges support by  GRARPA. The work at  MIT  has been supported by  AFOSR  grant number  FA9550-11-1-0225 , a  Packard Fellowship , and the  MISTI-Spain program. This work made use of the  Materials Research Science and Engineering Center Shared Experimental Facilities  supported by the  National Science Foundation.