dataesr/scientific-paragraphs-categorization huggingface dataset:
Open access to publications impacts mainly the dissemination section but research data management planning has more diverse impacts, e. g. on ethics, on the project management work package or on the share of roles and responsibilities between partners. Discussing these aspects as early as the pre-award grant writing phase is far from being unnecessary since we have met several examples of projects in which conflicts arose because partners could not agree on the level of data sharing or on the tools to share and manage data. Whenever contacted by researchers, we ask them to send us their proposal, even as an incomplete draft. Then, we arrange a meeting with them to discuss their project in order to know which level of openness they would like to go to and which kind of strategy they could establish to achieve it.
We also ask questions on different aspects related to Open Access and data management. This interview is conducted in a rather systematic way but with flexibility to accommodate project needs. On the one hand, we try to identify specific issues that could cause difficulties during the project or at the submission stage, such as: big volume of data, sensitivity of data, different culture of data sharing between partners and we help the researcher to make the way these issues will be dealt with more explicit. On the other hand, we spot what could be showcased with data management, such as the constitution of very interesting data sets or an ambitious data sharing policy. We also help them to identify other university services they should go to, such as the Data Protection Officer or the IT services.
Supporting Research Data Management Support to research data management is the component of the set of services on which we are less experienced since few H2020 projects are coordinated by researchers of our University and because the ANR has set up a data management policy only for projects funded since 2019. We currently follow two ANR projects funded in 2018, which committed to draft a data management plan, though they did not have to do so, and we supported two individual H2020 projects to write their data management plan (one ERC-Advanced and one Marie Curie Individual Fellowship). Though research data is a more and more commonly discussed topic, researchers are still quite reluctant to formalize their practices and not at ease with writing them down. Data management plan (DMP) writing is still considered by some researchers as a loss of time to produce a document that seems to make more sense for the funder than for the project consortium.
For instance, we propose that researchers upload a dataset into a repository with underlying data of each of the project publication, and open up the metadata even if they keep the datasets with time-specified embargoed access. It is an easy way to make them describe their datasets and preserve their data on public and secured infrastructures. This pragmatic approach is quite successful. The ERC-Advanced researcher we provide support to, has already uploaded two datasets in Zenodo since the beginning of October 2019, while he had never done it before. 8 He now plans to upload systematically a dataset in Zenodo for each publication related to his ERC project.
As shown in Figure  2 , we are helping Liber Quarterly Volume 29 2019 a growing number of researchers when writing a grant proposal. The new requirements adopted by the ANR in 2019 explain the important increase in the number of projects supported during the 1 st semester of this year. So far, about two thirds of the supported projects have been applying for an ANR grant and one third for a H2020 funding. The number of ongoing projects we are following is also increasing (see Figure  3 ), but at a slower pace and with a lag compared to the number of projects helped that received bidding assistance, as it takes several months between the submission date and the starting date of projects. For  Coordinators will be informed of acceptance or rejection in July and the selected projects will start between October and April 2020, which gives the time to the Library to anticipate the projects' needs.
New Skills for Librarians Being integrated into research projects has been a good opportunity to develop new skills in writing grant proposals, such as defining an Open Science strategy, identifying risks related to data management in various disciplines, knowledge of the rules of eligibility for funding, the compatibility between resources and objectives. We also learned a lot about how to manage research projects, how to inform and train partners with diverse interests and with different implications in a project (coordinator, work package leaders, other researchers). We now have a better understanding of the language of funders and how research projects are assessed by reviewers and monitored by project officers. We also developed new partnerships in our own institution with the Grant Office and other staff in research units and learned how to use funders' tools such as the OpenAIRE services, the Participant Portal or the Cordis database.
2 FTE in September 2019, shared on three members of the staff. To scale these services up, it will be necessary to widen the number of colleagues involved. From January 2020, we plan to train more colleagues to take part in the monitoring of the compliance with Open Access requirements. We also intend to move from a project by project approach to a more collective one, with common training sessions for example. But, building a strong relationship with coordinators will remain crucial. It is also Liber Quarterly Volume 29 2019 necessary that projects rely more and more on their own resources to meet their needs on research data management.
Conclusion Funders' mandates are often considered as one of the most important incentives to develop Open Science. This article presents the services dedicated to project coordinators developed by the Lille University Library. These services can be grouped in three components: help writing grant proposals, support to disseminate publications in Open Access and to manage research data of ongoing projects. It has proven to be a very efficient way to improve projects' compliance with Open Science obligations and to help them manage their project. Helping projects from the submission stage opens up many opportunities for libraries, because taking part in projects allows librarians to work with researchers from the design of their research and reach researchers who are leaders in their field. It is also an opportunity to gain new skills and to collaborate with other university services.
Multisite extracellular recordings from 60 electrodes were performed using the MEA-system, purchased from Multi-Channel Systems (Reutlingen, Germany). Data acquisition was controlled through MC_Rack software (Multi-Channel Systems Reutlingen, Germany), setting the threshold for spike detection at -30 µV and sampling at 10 kHz. Experiments were performed in a non-humidified incubator at 37°C and with 5% CO2, without replacing the culture medium. Before starting the experiments, cells were allowed to stabilize in the non-humified incubator for 90 seconds; then the spontaneous activity was recorded for 2 minutes. Bursts analysis was performed using Neuroexplorer software (Nex Technologies, Littleton, MA, USA) after spike sorting operations. A burst consists of a group of spikes with decreasing amplitude, thus we set a threshold of at least 3 spikes and a minimum burst duration of 10ms.
We set interval algorithm specifications such as maximum interval to start burst (0. 17 sec) and maximum interval to end burst (0. 3 sec)  (Gavello et al. , 2012; Gavello et al. , 2018). Burst analysis was performed by monitoring the following parameters: mean frequency, number of bursts and mean burst duration. Cross correlation probability values were obtained by means of Neuroexplorer software using ± 2 s and 5 ms bin size. The number of experiments is given considering the number of MEA (NMEA), each of those consisting of 59 recording electrodes. Where indicated we provided the total number of recording electrodes (Nchannels).
After 30 minutes of equilibration in the microscope objective holder time lapse images were acquired over a Spinning Disk microscope (Olympus / Andor technology) with a 40x air objective, recording for 15 minutes at 150 ms intervals. Images were automatically corrected for drifting using the built-in Fiji function "Linear stack alignment with SIFT"  (Schindelin et al. , 2012). Single cell borders were manually generated as separate ROI (Regions of Interest) on a custom MATLAB script. Each ROI was used to acquire BAPTA fluorescence intensity as the mean of intensity within each ROI area by frame, resulting in a matrix of single cell time series of BAPTA fluorescence signals as a readout of Ca 2+ cytoplasmic concentration. Matrices were corrected by moving average  (Anderson, 1975)  normalizing each timepoint with the average of 60 seconds for each cell to generate a constant baseline over the progressive signal loss due to the progressive BAPTA bleaching.
As a cut off to detect actively bursting cells, we discarded from the analysis cells whose distribution of intensity for each time frame arranged more than 40% of the frames above the first quarter of maximum corrected fluorescence intensity. For the remaining selected timeseries, Ca 2+ bursts were detected filtering BAPTA intensity on a threshold of 3 standard deviations. The bursting frequency of every selected cell was measured dividing the number of bursts above threshold by the sum of intervals between each burst. To evaluate coordination of activity, we counted the ratio of bursts occurring across cells in an interval of 3s normalized by the total number of bursts. All time-lapse analysis was performed using a custom MATLAB script.
Biocytin (1. 5 -2 mg ml -1 ) was added to the intracellular solution for post-hoc immunohistochemistry. Neurons were visualized with an upright microscope (Zeiss Axio Examiner D1) equipped with an Evolve 512 EMCCD Camera (Photometrics) using a 63X/1. 0nA water-immersion objective (Zeiss) and infrared DodT contrast imaging. Recording pipettes (6-10MΩ) were pulled from borosilicate glass using a Narishige P-10 puller. Data was acquired using a Dagan BVC-700A Amplifier, low-pass filtered at 3kHz and sampled at 20kHz with ITC16 (Instrutech) and AxoGraph X software. Membrane voltage was recorded in the bridge mode. To determine the excitability of pyramidal neurons, we performed 800ms square current steps of 10pA from -100pA to +150pA. The rheobase was defined as the minimum somatic current required to elicit an action potential (AP) from the resting membrane potential of the neuron.
Microscopy and image analysis Imaging was performed using a Zeiss 710 confocal microscope equipped with a 405nm diode, an argon ion, a 561nm DPSS and a 647 HeNe lasers. Z-stacks of fixed cortical sections were imaged using a LD-LCI Plan-Apo 25x/0. 8 NA or a LD Plan-Apo 63x/1. 4 NA oil immersion lenses. Images from IF experiments were analyzed by using Fiji-ImageJ Software  (Schindelin et al. , 2012) : cell counter plug-in was used to assess the number of cells expressing specific proteins, while measurement tools were used to determine signal intensity or Axonal Initial Segment (AIS) features such as length and distance from the soma. For the AIS average diameter measurement, we took advantage of IMARIS software's tool filament tracer. AISs were semi-automatically reconstructed and an average diameter automatically measured for every AIS individually.
Statistical tests Principal component analysis (PCA) was performed on R software using Factominer and the following parameters: Vrest, Rin, Rheobase, Vthreshold, APamplitude, APhalf-width, latency, Sag and ISI. In PCA plots, ellipses represent the 95% confidence and the square the center of mass for each cluster. Hierarchical clustering was performed with Euclidean distance, using both average burst frequency and correlation per condition. In Figure  2 , we used 2 way ANOVA to determine relevant parameters driving differences for burst frequency, coordination and frequency variability, post-hoc testing was performed using Welch Two-samples test. In Figure  6A , we performed Welch's unequal variances t-test analysis correcting the P-value for multiple testing using the Benjamini-Hochberg procedure, false discovery rate = 0.
ACKNOWLEDGMENTS We thank  Dr. Marteen Kole  and  Dr. Nathalie Dehorter  for critical reading of the manuscript and members of the  Studer and Frick laboratories  for stimulating discussions. We also thank  Guillermina Lopez-Bendito  for insightful suggestions. We are grateful to the  iBV PRISM Microscopy facility  and the  Bordeaux Imaging Center (BIC) , supported by  Labex-BRAIN  ( ANR-10-LABEX-43 ), for the acquisition of some imaging data. The authors also thank the animal-and genotyping facilities of the  Neurocentre Magendie  (supported by  INSERM and LabEX-BRAIN   ANR-10-LABX-43 ) and of the iBV. This work was funded by an  ANR  ( Agence National de la Recherche ) grant #  ANR-13-BSV4-0011-01  to M. S. and X. L, by the  "Fondation Recherche Médicale ; Equipe FRM 2015 grant # DEQ20150331750  to M.
S. ; by an '' Investments for the Future'' LabEx SIGNALIFE  (grant  ANR-11-LABX-0028-01 ) to M. S. , by the  "Initiative d´Excellence (IdEx) de l´Université de Bordeaux" fellowship  to I. D. P. , and by the  Inserm endowment  to  A. F. Address  of the corresponding author: Michele. studer@unice. fr( iBV -Institut de Biologie Valrose, Univ. Nice Sophia Antipolis, Centre de Biochimie ; UFR Sciences, Parc Valrose, 28 avenue Valrose, 06108 Nice Cedex 2, France ).
Catalog of laboratory parameters During our analysis, we found that some of the oscillator strength values for molecular hydrogen that we took from the  compilation of  Malec et al. (2010)  are wrong, most likely due to a missing factor coming from the statistical weights. We thus calculated the correct values following  Morton (2003)  and created a new data file which is available under the following link: https: //doi. org/10. 5281/zenodo. 1442558. While the values for the oscillator strength f and the damping constant Γ, are still better than anything that can be currently measured, the wavelength or frequency positions are taken from the most recent lab experiments  (Bailly et al. 2010 , see their Table  11  & 12).
Finally, given the column densities or their derived upper limits of molecular hydrogen, we calculate the molecular gas fraction f (H 2 ) = 2N(H 2 )/(2N(H 2 )+N(H i)). The complete data set is presented in Table A. 3 and in Fig. 13  we show pairwise scatter plots and histograms of the most important properties. By color and symbol, we differentiate between four Table  2. Upper limits on the CO column density in the six H 2 bearing GRB DLAs as well as the N(CO)/N(H 2 ) ratios. Also listed are the values for GRB 080607 as taken from  Prochaska et al. (2009).
Discussion The two main questions we aimed to address in this paper are: (1) if (and why) there might be a lack of H 2 bearing GRB-DLAs, and (2) how GRB-DLAs compare to QSO-DLAs. To answer the first question: there is no lack of H 2 bearing GRB-DLAs. While the fraction of H 2 bearing systems in the general population of QSO-DLAs is only about 10% or less  (Ledoux et al. 2003; Noterdaeme et al. 2008; Balashev et al. 2014; Jorgenson et al. 2014) , we here find evidence for absorption from H 2 in 6/22 (27%) or even 9/22 (41%) of our GRB spectra, when including the tentative detections. Furthermore, when only comparing those QSO and GRB-DLAs that are at redshift 2 < z < 4 and behind large neutral hydrogen column densities log N(H i) > 21. 7, and therefore likely probe sight-lines that are associated with the central region of a galaxy, the fractions are very similar: 7/9 (78%) H 2 In case molecular hydrogen is detected, the data points are colored (GRB-DLAs in red, QSO-DLAs in green and blue, as labeled).
At metal column densities larger than log N(H i) + [X/H] > 20. 0 and redshifts 2 < z < 4, we detect H 2 in 6 of 13 (46%) systems, or 9 of 13 (69%) when including the tentative detections. For the QSO-DLAs from N08 this fraction is 4/9 (44%) and for the QSO-ESDLAs from N15 it is 5/7 (71%). So, also when selecting GRB and QSO-DLAs based on their metal column densities, the fraction of H 2 bearing systems are similar. Additionally, looking at the data points from both QSO and GRB-DLAs, there seems to be a slight, positive trend of increasing dust depletion with increasing metal column density. The red line indicates the best linear fit and the dashed lines the corresponding 3-σ confidence intervals. The fit was performed with a Bayesian linear regression and the posteriors on slope and intercept were computed using PyMC.
To account for outliers we use a Cauchy distribution    2018 ) (B18). In case molecular hydrogen is detected, the data points are colored (GRB-DLAs in red, QSO-DLAs in green and blue, as labeled). The symbol size represents the overall molecular fraction log f , and in case of a non-detection the corresponding upper limit. The GRB-DLAs at z > 4 are additionally marked with a cross. The solid and dashed lines indicate the best fit linear model and corresponding 3-σ errors. Above and to the right of the scatter plot we also show the histograms for our GRB and the N08 QSO-DLA samples. Again, systems with H 2 detections are colored as labeled. Upper limits are not included for the histograms. for the errors on [Y/Fe]. For slope and intercept we use normal priors centered on the best estimates from a simple first fit using scipy.
Acknowledgements. The lead author acknowledges support from a studentship at the  European Southern Observatory in Chile  and thanks the many astronomers who dedicated their time observing the numerous GRBs with VLT/X-shooter. P. S. acknowledges support through the  Sofja Kovalevskaja Award  from the  Alexander von Humboldt Foundation of Germany , and J. B. acknowledges support through this award. K. E. H. and P. J. acknowledge support by a  Project Grant  ( 162948-051 ) from  The Icelandic Research Fund. J. J. acknowledges support from  NOVA  and  NWO-FAPESP  grant for advanced instrumentation in astronomy. Finally, we are indebted with  Thomas Krühler  for providing code to create synthetic GRB afterglow spectra.
The data model Data collected from the source was structured in a relational database, with a fix, predetermined data model, based, with more or less rigor to the CIDOC CRM. It is visible that our mapping is, on several levels, very approximative, sometimes basing ourselves on vague categories, or mapping several different types of entities to the same CIDOC-Entity. We knew this was a first approach in order to get our hands-on data and its manipulation. In a similar manner, we worked with 22 relationships mapped again more or less rigorously to CIDOC-CRM Properties in order to create our relationships. The database enable for data entry with the profile of n-quads (as for in n-triples format), dedicated to the source of the data. This way, we were able to link every data entry in our relationship database to the source document containing the assertion.
Models combining With those two modellings, one focused on (very rough) geometry and another one on conceptually representing the life of the site, we thought is we had enough for a first implementation. We produced a Unity application containing the various models and a temporal slider, as can be seen in 2. We restricted the access on the database to very simple information : The name of the building (if it changed with time), and the shape of  This worked great, but we were not able to go any further on this path for two main reasons: • The connection of a SQL database with the Unity game engine was achieved with an Unity extension, that was no longer maintained and got depreciated with the next Unity update: we were completely dependent on others to continue to work with this pipeline. • Our very rough conceptual and geometrical approach was not satisfying anymore.
Database change This change reflects more a will on our side to explore linked data technology in order to integration ontology formatted data from reference sources (such as BnF (French National Library) and DBPedia, for now). Since our data was already more or less formatted with standardized vocabulary the transition was not so painful as it could be if starting from more personalized data structure. We then used Jena, an open-source library from the Apache foundation to manipulate our graph data. This system was thought from the beginning to be multi-user, so in order to avoiding any duplication of information, we added a step into our process: hashing our triple. With this we still are working with our n-quads system, but this time, the 4 components added to the triples is not the source of the data, but a unique ID.
3D data in our database A big gap remaining in our data integration is the decoupling of the geometrical shapes and the more text-based data. The 3Dontolgoy was a complete rdf implementation of the X3D file format : it was the a perfect vocabulary in order to improve our heterogeneous integration. Adding a triple containing a simple geometry (we made our first tests with a X3D light shape of a Deer that was openly accessible as an example by the X3D community), we were able to : • prompt the 3D data and color from our database interface • basically manipulate the data (rotation, translation, zoom) • select specific points on the geometry to which we could link a comment or metadata (point selection + metadata specification led to the creation of a new triple which subject was the specific point) A trivial example of this operation can be seen in 7.
NEXT STEPS To sum things up, we now have a database management sysdealing with graph data, that prompts and let us manipulate indiscriminately 3D data, their metadata or more conceptual modeling of our heritage site. The discontinuity of our 3D vocabulary is a heavy problem that we have to tackle as an urgent priority. The first tests that we performed convinced us that such an integrated approach makes sense. We now need to rely on community of practicionners and ontologists that share our views in order to have a stable data management system in the long run. Taking a step back, it appeared to us that our efforts until now led to a proper data management concept, but has not really been of much help for building of our analysis. Our incremental approach made us refine our geometries and classification, but nothing huge appeared in our heritage analysis.
Maybe such systems can be of better help in the processes of comparisons. With the case study of the Series of Meridian Telescope, we intend to test this hypothesis. Another next step that we want to take on the Observatoire du Pic du Midi is altering the interface of our database, in order to simultaneously be able to prompt regular text triples, 3D data and automatic produced time lines, in order for our system to become a richer way to explore and analyze data.
In particular, given an initial set of constraints G expressed over a set of variables X, we obtain another formula F such that G(X) = ∃Y F (X, Y ). Therefore, we are concerned with sampling over solutions of F projected over a subset of variables (such as X in this case). In other words, we are concerned with sampling over Σ 1 1 formulas. Conditioned Sampling. Given a boolean formula Φ and a partial assignment σ, conditioned sampling refers to sampling from the models of Φ that satisfy σ. Conditioning has interesting applications in testing where one is interested in fuzzing the system with inputs that satisfy certain patterns (preconditions). Conditioning has been applied in the past for fault diagnosis  [23] , conformant planning  [46]  and databases  [15]. Typically, practical applications require sampling techniques that can handle all the above formulations.