dataesr/scientific-paragraphs-categorization huggingface dataset:
Postreplication repair (PRR) tracts PRR tract detection in human cells was adapted from Daigaku et al. , who first performed the technique in budding yeast  (27). Briefly, upon UV irradiation the cells received medium with 100 ng/ml of nocodazole (Sigma-Aldrich) for 24 h. For the last 4 h, 10 M BrdU (Sigma-Aldrich) was added to the medium. Glass slides were prepared as for the DNA fiber assay (described above). ss-DNA was stained with mouse anti-ssDNA antibody (Millipore) and anti-mouse Alexa Fluor 594, and BrdU was detected with rat anti-BrdU and anti-rat Alexa Fluor 488. The slides were mounted using Fluoroshield (Sigma-Aldrich) and DNA fibers were imaged using a fluorescent microscope (Axiovert 200, Zeiss) at a magnification of 1000×. Analyses were performed using Zeiss LSM Browser Software.
Initiated by Human Mutation, the first journal to demand their use, strong support is coming from many journals making the use of HGVS nomenclature for sequence variant descriptions mandatory. All major variant databases support HGVS nomenclature and professional organizations have started to demand its use in clinical diagnostic reporting  [Gulley et al. , 2007; Richards et al. , 2015]. However, in specific disciplines HGVS nomenclature is used less frequently and alternative nomenclature systems survive [e. g. Berwouts et al. , 2011; Kalman et al. , 2015]. EQA providers have detected the problem  [Tack et al. , 2016]  and started to more actively promote HGVS nomenclature by asking participants to follow the recommendations and subtracting marks when labs fail to do so correctly. In this respect it should be noted that excellent open source support tools have been developed that make it very easy to check whether correct HGVS descriptions are reported  [Wildeman et al.
Deans Z. C. , Wolstenholme N, Patton S, Dequeker E. M. C. 2016. What's in a name? A co-ordinated approach towards the correct use of a uniform nomenclature to improve patient reports and databases. 2016. Hum Mutat 37:xxx-yyy. [NOTE TO PRODUCTION: THIS ARTICLE WILL PUBLISH IN THE SAME ISSUE. PLEASE INSERT PAGE NUMBERS] Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL, ACMG Laboratory Quality Assurance Committee. 2015. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17:405-424. Wildeman M, van Ophuizen E, den Dunnen JT, Taschner PEM. 2008. Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker.
ACKNOWLEDGMENTS We gratefully acknowledge everyone who has, over the years, contacted the HGVS to point out problems with the recommendations, errors/inconsistencies on the web pages and those who have participated in the recent round of Community Consultation of the SVD-WG. Special thanks go to the late  Dick Cotton , a pioneer in the uniform nomenclature movement, a strong supporter and warm motivator for the committee and, as  Co-Editor of Human Mutation , the first to make HGVS nomenclature mandatory in publications. Finally, we thank  William Hong  (Melbourne) with building the newly designed http://www. HGVS. org/varnomenwebsite and the  Human Variome Project  ( HVP, International Coordinating Office ) for administrative support establishing and operating the Sequence Variant Description Working Group (SVD-WG).
■ ACKNOWLEDGMENTS We acknowledge financial support from the  Research Foundation-Flanders (FWO , Grant G. 0990. 11, G. 0855. 14, G. 0197. 11, G. 0962. 13 , postdoctoral fellowship to H. Y. , E. D. , K. J. , C. S. and G. L. );  KU Leuven Research Fund  ( GOA2011/ 03 ,  OT/12/059 ); the  Flemish government  through long-term structural funding Methusalem (Meth/ 08/04 )-the Hercules foundation ( HER/08/021 ,  HER/11/14 )-the  Belgian Federal Science Policy Office  ( IAP-VI/27 )-the EC through the  Marie Curie ITN  project  iSwitch  ( GA-642196 ); and the  ERC  projects  FLUOROCODE  ( GA-291593 ),  LIGHT  ( GA-307523 ), and  PLASMHACAT  ( GA-280064 ). H. U. acknowledges the  Japan Science and Technology Agency PRESTO program  for financial support. P. S. acknowledges the  International Center for Frontier Research in Chemistry (icFRC).
Visualizing 2C-Cas9-mediated gene inactivation In order to explore the possibility of directly visualizing protein loss, we sought to induce eye-specific loss-of-function at the parvalbumin 6 (pvalb6) locus, coding for a calcium-binding protein expressed in a subpopulation of amacrine cells (ACs) in the inner nuclear layer (INL) and retinal ganglion cell layer (GCL) of the differentiated retina (Fig. 4A ). The pvalb6 gene is the only paralog expressed in mature retinal neurons as reported by the ZFIN in situ database  (Sprague et al. 2008). This gene represents an ideal target for unbiased detection of locus disruption, since its expression can be easily revealed by immunohistochemistry with a commercially available antibody  (Nevin et al. 2008). To achieve pvalb6 inactivation, we first generated a pUAS:Cas9T2ACre;U6:pvalb6sgRNA1;U6: pvalb6sgRNA1 vector.
FACS Fluorescent Cas9-expressing cells were isolated from wild-type cells by fluorescence-activated cell sorting. 3 dpf embryos were dissociated as previously described by  Manoli and Driever (2012). Cell sorting was performed on FACS Aria (BD Biosciences), and data were analyzed using FACSDiva version 6. 1. 2 (BD Biosciences). The GFP fluorescence was detected in the gfpBlue-B-530/30-A channel. GFP-positive and -negative cells were sorted in lysis buffer provided in the NucleoSpin Tissue Kit (Macherey-Nagel), and genomic DNA was extracted with the same kit. PCR on target genomic loci and DNA sequencing were performed as described above.
Microscopy Low magnification images were acquired with a Leica MZ FLIII stereomicroscope (Leica) equipped with a Leica DFC310FX digital camera (Leica). Whole-eye pictures were taken with a Leica upright wide-field epifluorescence microscope using a 20× oil immersion objective. A Zeiss LSM 780 confocal microscope (Zeiss) was used for confocal microscopy, employing a 40× water immersion or 10× objective. Z-volumes were acquired with a 1-to 2-μm resolution, and images were processed using ImageJ, Adobe Photoshop, and Adobe Illustrator software.
Acknowledgments We thank  Allison Bardin ,  Allison Mallory ,  Yohanns Bellaiche ,  Christoph Gebhardt ,  Shahad Albadri ,  Celine Revenu , and  Valerie Bercier  for critical reading of the manuscript. We also thank  Herwig Baier ,  Estuardo Robles ,  Joachim Wittbrodt ,  Koichi Kawakami ,  Claire Wyart ,  Nadine Peyriéras , and  Georges Lutfalla  for sharing reagents and transgenic lines. We thank all members of the  Del Bene lab  for fruitful discussions. We thank the  Developmental Biology Curie imaging facility (PICT-IBiSA@BDD, Paris, France ,  UMR3215/U934 ) member of the France-BioImaging national research infrastructure for their help and advice with confocal microscopy and the  Flow Cytometry and Cell Sorting Platform at Institute Curie  for their expertise. The  Del Bene laboratory "Neural Circuits Development" is part of the Laboratoire d'Excellence (LABEX)  entitled  DEEP  ( ANR -11-LABX-0044 ), and of the  École des Neurosciences de Paris Ile-de-France network.
V. D. D. was supported by a doctoral fellowship of the  Fondation Pierre-Gilles de Gennes pour la recherche and Fondation Recherche Medicale  (FRM) 4th year doctoral fellowship. F. D. S. was supported by a doctoral fellowship of the  Curie International PhD program. T. O. A. was supported by a  Boehringer Ingelheim Fonds PhD  fellowship. H. S. was funded through  FPU12/03007. This work has been supported by an  ATIP/AVENIR program  starting grant (F. D. B. ),  ERC-StG  # 311159-Zebratectum  (F. D. B. ),  ANR-II-INBS-0014  (J. P. C. ),  CNRS ,  INSERM, Institut Curie  (F. D. B), and  Muséum National d'Histoire Naturelle (J. P. C)  core funding, the  Fundación CNIC Carlos III  (N. M. ), the  Fundación ProCNIC  (N. M. ), the  Spanish Ministry of Economy and Competiveness (Tercel  and  BFU2011-25297 ) (N.
Data access The sequences of mutant tyr clones from this study have been submitted to the NCBI GenBank (http://www. ncbi. nlm. nih. gov/ genbank/) under accession numbers KU751772-KU751776. The sequences and the maps relative to the plasmids pUAS: Cas9T2AGFP;U6:sgRNA1;U6:sgRNA2 and pUAS:Cas9T2ACre;U6: sgRNA1;U6:sgRNA2 are available in Addgene (https://www. addgene. org). Plasmid numbers are #74009 and #74010.
Acknowledgements This research is funded in part by the  Gordon and Betty Moore Foundation  through grants #  GBMF2758  and  GMBF4827  (to FA), the  French Agence Nationale de la recherche (Photo-Phyto ,  ANR-14-CE02-0018 ) and the  PIA EMBRC France (F-YB). Thanks are extended to  E Bertrand  and  A Allen  for providing CCMP632,  B Brahamsha  for discussion of experimental results,  K Barbeau  and lab members  S Hogle  and  R Bundy  for providing Rugeria sp.
Method Participants. Ninety adults were recruited through Amazon Mechanical Turk (28 females; M = 30 years; 87 native speakers of English) and were compensated $0. 50 for their participation. We excluded subjects who participated in both conditions of the experiment (n = 3). This resulted in 44 participants in the also-condition and 43 participants in the plural-condition. Data collection was stopped when each of the conditions had at least 40 participants. The number of participants was established before data collection began. Procedure and display. Similar to Experiment 1, except that each trial now included 4 learning exemplars and 6 test items. Conditions. Each participant saw 8 test trials and 16 filler trials. Test trials. As schematized in Fig  4 , each test trial contained 4 learning exemplars (LE1, LE2 and LE1', LE2').
Funding: ID was supported by a  Graduate Fellowship  from the  Direction Générale de l'Armement  (PhD program Frontières du Vivant). The research was supported by grants from the  European Research Council  under FP/2007-2013-ERC n°3 13610 to EC, and from the  Agence Nationale de la Recherche   ANR-10-IDEX-0001-02 ,  ANR-10-LABX-0087  for the facilities provided by the  Departement d'Etudes Cognitives. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
g. , the Breeding Bird Survey), ensuring considerable political interest in these schemes, and (4) this effort coincided with citizen science becoming fashionable in France. With the success of the national bird monitoring effort, two new schemes were put in place to develop capacity for monitoring other taxa. The first was based on the same logic as the Breeding Bird Survey: training and motivating skilled amateurs to collect data following a protocol and a sampling design for butterflies, bats plants, and dragonflies. The second program was developed to train and coordinate efforts of the general public to monitor garden butterflies and snails, bumblebees, birds, flower-dwelling insects, and wild plants in cities. All these schemes are coordinated by the same scientific team based at the MNHN, but each also relies on a specific NGO partner, which is dedicated to the success of the (specific) participant network.
The NGO partner trains participants, ensures that each new scheme capitalises directly on preceding experience to maximise the chance for joint data analysis, and coordinates all efforts with MNHN. Several characteristics have made this effort an outstanding success: (1) different monitoring schemes for different species groups were integrated from the beginning, (2) the same research group was involved in citizen science schemes for both skilled amateurs and the general public, (3) strong involvement of researchers in designing citizen science projects maximised the chances that the future database will allow sophisticated and robust statistical analyses of the large datasets and (4) development and training of personnel in the use of technology to facilitate reliable data where detection or identification is difficult (e.
In particular, northern areas of Canada, Greenland and Russia have very limited biodiversity monitoring, whereas areas in northern Scandinavia, the Bering Sea, Aleutian Islands and Iceland have relatively intense, on-going biodiversity monitoring (Fig. 13. 4) and in many cases, long-term datasets. Given that the area in question is 32 million km 2 (three times the size of Europe) and is comprised of largely remote and extreme ecosystems, it is not surprising that current biodiversity monitoring efforts are seen as inadequate. Indeed, recent issues regarding state finances and priorities have made it more difficult to sustain even existing efforts. The current situation facing the Arctic demands a well-designed, scaled, pan-arctic, ecosystem-based approach that not only identifies trends in biodiversity, but also identifies underlying causes of these trends.
In order to connect the diversity of biodiversity observing networks, such as scientific field stations, community-based monitoring programs, theme-based monitoring networks (e. g. , caribou) operating at different scales across the Arctic, the CBMP is establishing four Expert Monitoring Groups representing major Arctic themes (Marine, Freshwater, Terrestrial and Coastal). Each group, representing a diversity of disciplines, is tasked with developing and implementing pan-arctic integrated biodiversity monitoring plans with a focus on harmonizing existing monitoring networks and methodologies, as well as rescuing and aggregating existing data to establish historical baselines. well as a web-based data portal (Arctic Data Service www. abds. is; http://www. youtube. com/watch?v=ONdmmIcuqNE) that is improving metadata and the discovery, access, and interpretation of data to bridge the science-policy gap.
Central America Key Biodiversity Areas (KBAs) are sites of global importance for conservation of biodiversity. As an important tool in conservation planning, these areas are considered critical for the persistence of one or more globally threatened species and are identified using simple standardised occurrence data  (Eken et al. 2004 ). This approach has been modified to identify important sites for different taxonomic groups, such as important bird areas (developed by BirdLife-www. birdlife. org); plant areas  (Anderson 2002) , butterfly areas (van Swaay and Warren 2003), or for specific biomes (e. g. , freshwater key biodiversity areas;  Darwall et al. 2011). This is an international effort currently led by the International Union for the Conservation of Nature (IUCN). This same process is also being used at the national scale.
In Central America, the NGO Conservation International identified a local partner institution in each of the seven countries and built up their capacity to identify KBAs in each country. This required gathering occurrence data for species assessed as Vulnerable, Endangered, or Critically Endangered by the IUCN Red List, using as many sources as possible globally. This, in turn, provided each country with a more complete set of records for species of interest. With the help of Conservation International, each institution involved then defined the KBAs for these species, while also defining monitoring objectives. All collected information is entered into a global database-the World Biodiversity Data Base, currently managed by BirdLife International-and shared with the relevant authorities of the different countries and regional bodies (e.
It also contains a species database with more than 85,000 national assessments for over 60,000 species. This has also sparked gap analyses in the global coverage of National Red Lists, which can help in prioritising funding for National Red List development  (Zamin et al. 2010). While this centralisation has provided a good starting point for promoting National Red Lists and Action Plans, information flows much more effectively if regional hubs are established as well, again requiring the recruitment and training of local personnel. Efforts have recently been made to formalise the development of National Red Lists (NRLs) under the auspices of the ZSL and IUCN via the newly created National Red List Alliance (NRLA). The Alliance builds on previous steps taken at international congresses, e.
Horseradish peroxidase conjugated secondary antibodies were from Thermo Fisher Scientific. Chemiluminescence signal was captured using the ChemiDoc MP Imaging System (Bio-Rad). Resultant images were quantified using ImageJ software  [54]. Glyceraldehyde 3-phosphate dehydrogenase (GAP) loading controls were immunoblotted on the same membrane as the immunoblotted protein. All representative immunoblots in figures represent proteins immunoblotted on the same membrane as the loading control GAP.
8, 4% SDS, 30% (v/v) glycerol, 0. 02% bromophenol blue). Standards and samples were applied to a 12% polyacrylamide gel. Gel electrophoresis was performed using the Bio-Rad Mini Protean III system. Each fluorescent gel was scanned using the ChemiDoc MP Imaging System (Bio-Rad) for fluorescence, with wavelengths set at excitation 485 nm, emission 520 nm for FLM and excitation 595 nm, emission 610 nm for Texas red. The bands were quantified by densitometry using ImageJ version 1. 41 software  [54]  using the integrated density function, after first removing the background. To assess the reversible protein thiol oxidation state of specific protein bands, dominant bands were compared against FLM and Texas red using in-gel standard curves using polynomial regression. Non-labelled samples were run in parallel in the same gel, and after gel scanning, gels were stained with Coomassie brilliant blue, scanned and specific protein bands of interest were excised for mass spectrometry.
The HPLC mobile phase consisted of 0. 1% (FA and 2% ACN in water (A) and 0. 1% FA and 2% water in ACN (B). Gradient elution was performed with 2% B for 3 min, increased to 40% B at 15 min, then ramped to 98% B by 16 min and held for 1 min before reduced back to 2% B within 1 min. Column temperature was 40 °C. Positive electrospray ionization mode was operated to acquire MS data by informationdependent acquisition (IDA), where only the top 20 MS peaks between 400 and 1250 m/z were selected for further MS/MS scan. Mass tolerance was 50 mDa. BSA calibration was conducted before a batch of samples was run. Parent mass peaks (mass range m/z 800-3000 from combined MS and MS/MS spectra) were submitted to the MASCOT database for identification of peptides, using the following search conditions: Swissprot database, all mammalian species, trypsin digest with allowance for up to one missed cleavage per peptide, no fixed modifications, variable modification of oxidation on methionine residues, MS tolerance of 1.
By playing these musical transcriptions with a standard sound software (Midi Composer), the author affirms that 'we cannot perceive a difference that would give more validity to one of the two'  (Bouët, 1997, p. 119 ). Bouët did not run perceptual tests in order to determine if Romanian listeners could distinguish one version from the other, and this conclusion is based only on his personal familiarity with Transylvanian rural music. Even if the author did not perform timing analyses to this purtata, he argues that different S:L proportions coexist and alternate in a same tune, and claims therefore that we cannot have a strict and unique conception of the aksak model. The problem of aksak can be related to current research on non-isochronous rhythms  (Temperley, 2000; Polak, 2010; London, 2012; Polak & London, 2014).
In all three cases, we assumed that the ending point of one rhythmic unit corresponded to the beginning of the next rhythmic unit. Time markers have been placed on the waveform, and then the running time code was extracted by using the Audacity 'extract markers time codes' option. A simple Excel function has then been used to calculate the time durations of S and L (in seconds), the S:L ratio for each period, and the mean S:L value over 44 periods, which corresponds to the entire tune. Fig. 3. Audacity (ver. 2. 0. 6) window. The upper part shows the viola wave signal of the Gypsy song of sorrow 'CM' (Audio Ex2). The bottom part shows three different possibilities for determining the starting points of the rhythmical units S and L, named respectively 'Perceptual Onset (PO)', 'Peak Amplitude Onset (PAO)', and 'Minimum Amplitude Onset' (MAO).
DATA CODING The two musicians were standing at the center of a circular region of 2,5 m radius, surrounded by the six infrared-emitting cameras attached to six tripods, 2 m from the ground on each side of the subject, at a distance of 3 m from each subject's body. The movements of 38 retro-reflective markers (15 mm in diameter), placed at various anatomical locations on the body, were measured using an optoelectronic device, Smart (BTS, Milan, Italy). Kinematic parameters in three dimensions (X, Y, and Z) were calculated from successive frames taken at 10 ms intervals. Kinematic variables were low-pass filtered using a digital second-order Butterworth filter at a cutoff frequency of 5 Hz. This computation allows obtaining a mathematical model of the markers' trajectories in space, which can be viewed in 3 dimensions with the software 'SMART Viewer'.
DATA CODING The movements of the marker placed at the top of the violin bow have been now compared to the movements of the marker placed at the top of the viola bow (see Figure  5 , top). These patterns were projected on the time axis in order to obtain a musical transcription of both the melody and the harmonic accompaniment (see Figure  5 , bottom). The violin technique, which involves the use of distinct bow strokes for each single note, makes the task easier: almost every variation in the direction of the violin bow corresponds to the beginning of a new note. The interactive animation 'Jouer la jale' (see Animation Ex1, page 'swing') shows how this plot was obtained with the software 'SMART Viewer'. The trajectories in space of the two bows allow to qualitatively observe the asynchronies between the melody and the accompaniment (see Figure  5 , bottom).
Comparison among the different columns of these tables allows to observe if synchronization varies according to the musical structure and the musicians' expressive intentions. Table  6. Types and measures of asynchronies (in percentage of the corresponding rhythmic unit) detected, for each period, in three different recordings of the same Gypsy song of sorrow, played with different expressive intentions (Duo12 and Duo13 'without sweetness', Duo14 'with sweetness'). N stands for 'data not available'.
Acknowledgements Filippo Bonini Baraldi  conducted field research in Transylvania thanks to a CNRS ( French National Center of Scientific Research) doctoral grant  and a 'E. Fleischmann' post-doctoral grant of the  Ethnology Society (Nanterre, France ). The laboratory sessions were held at  INSERM  ( U1093   Cognition ,  Action and Sensorimotor Plasticity) ,  Université de Bourgogne (France) , thanks to financial support from the  CNRS 'Music, Cognition, Societies' scientific network. The drawing up of this article was possible thanks to a CREM-LESC financial support and a  CAPES   Visiting Professor fellowship  (PVE) at  Federal University of Paraíba (UFPB, Brazil ). The authors are grateful to  Yves Ballay  and  Yannick Gerard  for the computation of the motion capture data, to  Florent Manneveau  for the help with the musical transcriptions, to  Philippe Jobet  for the realization of the interactive animations, to  Laurence Fayet  for her revision of the English text, to  Speranţa Rădulescu  and  Justin London  for their commentaries on previous versions of this manuscript.