dataesr/scientific-paragraphs-categorization huggingface dataset:
Parker Solar Probe The measured electron distribution functions are subject to instrumental as well as environmental effects. An important issue on the instrumental side is the determination of sensitivities of each of the azimuth anodes. The sensitivity coefficients used for our analysis were obtained through in-flight calibration described in the work of  Halekas et al. (2019). The effects of the space-1 Link to the data archive: http://helios-data. ssl. berkeley. edu crafts own magnetic field and electric charge on the particle trajectories were studied by  McGinnis et al. (2019). They show that, even though the spacecraft magnetic field is relatively large (it was predicted to reach the strength of 500 nT), the effect on some of the plasma moments, is small (see Table  2  in  McGinnis et al.
(1997b) ;  Štverák et al. (2009) ;  Berčič et al. (2019)  the core electrons are modelled with a 3-dimensional bi-Maxwellian distribution function: f c (v ⊥1 , v ⊥2 , v ) = = A c exp (v ⊥1 -∆v ⊥1 ) 2 w 2 ⊥ + + (v ⊥2 -∆v ⊥2 ) 2 w 2 ⊥ + (v -∆v ) 2 w 2 (1) where ∆v ⊥1,⊥2, are the drift velocities corresponding to three axes of the magnetic field aligned frame. The fits were preformed on the full 3-dimensional VDFs using a least-square minimisation algorithm 2  provided by Scipy Optimization package for Python programming language  (Virtanen et al. 2019). Because the VDF values span over several orders of magnitude (see Fig. 2 ) the fitting was carried out in logarthimic space (ln(f c )). This technique decreases the large difference in the weight of fitted data points, giving more importance to the low VDF values.
Helios 1 The same two parameters to characterise the strahl electrons, PAW and T s , were obtained from the Helios 1 observations. The PAWs as well as some other parameters like the core electron density (n c ) and temperature (T c ,⊥ ), velocity of the protons (v p ), and magnetic field (B), have already been used and are described in our previous work  (Berčič et al. 2019). The strahl temperature is determined in a similar way as described for the PSP, however, the Helios 1 mission did not have a heat shield and the 2D electron instrument was able to point straight at the Sun, thus using the f max,i parameter from the PAW fits is not necessary. Instead we limit the data set to instances when magnetic field lies within one of the eight azimuth bins and fit the Eq. 10 to the data points from this azimuth bin (marked in blue in Fig.
4 (a) ). We use a full measured distribution function in this bin, and not the strahl distribution presented in  Berčič et al. (2019) , which was obtained by subtraction of the core and the halo from the measured VDF (f strahl = f measured -f core -f halo ). The full distribution was used to unify the methods of T s calculation between PSP and Helios data set. This process is illustrated in Fig. 4  (b). From the Helios data set, it is not as obvious that the strahl parallel VDF can be modelled by a Maxwellian. The VDFs appear noisier and especially further from the Sun (lighter blue values Fig. 4 (b) ) may exhibit traces of high energy tails, previously modelled by Kappa-like distribution functions  (Maksimovic et al. 1997a; Štverák et al. 2009). However, for a certain energy range (between ∼ 200 and 800 eV) strahl VDFs still present a straight line in the ln f (v 2 ) parameter space and give us the information about the strahl parallel temperatures.
Nevertheless, the irregularities do not exceed the statistical error and thus do not change any conclusions of the present work. Both plots in Fig. 5  show the increase of PAW with β ec. For the lower two β ec cases, the PAW decreases with electron energy reaching down to 30 o , while for the highest β ec case the PAW stays more or less constant with a value ∼ 55 o for the energies above ∼ 200 eV. This high-β ec regime where the strahl appears to be more affected by the scattering mechanisms was found for 26 % of electron spectra during the encounter 1 and for 13 % during encounter 2. For all cases a fast increase of PAW is observed for the low electron energies, denoting the presence of the electron core population below the energy of ∼ 200 eV. No radial dependence was found during the encounter periods (from 35 to 60 R S ), most likely as a consequence of the for now limited PSP data set.
It appears that the type of the solar wind we observe has more effect on PAW than the radial distance. Strahl temperatures obtained from Helios and PSP data sets are presented separately in Fig. 6  and 7. The results from Helios data set are the outcome of binning several years of solar wind measurements while for the PSP we use the data obtained over less than 6 months. Nonetheless, during the PSP encounter periods the data rate is very high and we were lucky to have already sampled different types of solar wind providing us with a satisfactory statistics. For Helios data set sampled distances range from 65 to 215 R S , while for the PSP the radial coverage is much smaller, from 35 and 58 R S (first two encounters). Similarly, measured proton velocities in the PSP data set have a smaller span than in the Helios data set.
Using the sub-spacecraft points in combination with the synoptic map of the Sun allows us to follow the time evolution of the T s and compare it with current state of solar corona (Fig. 8 ). Through comparison with the PFSS modelling of the magnetic field line topology during the first orbit of PSP presented in the study by  Badman et al. (2019) , we crudely separated the strahl temperature data into 3 bins. The coldest T s (T s < 75 eV) were observed at times when measured magnetic field lines appear to connect to a bigger equatorial coronal hole encountered just after the first PSP perihelion. During the first encounter when a period of high-speed solar wind implies connectivity to the smaller coronal hole (Fig. 8 (b) ) the strahl temperatures appear a bit higher temperature, 75 eV < T s < 85 eV.
CONCLUSIONS The PAW data obtained during the first two orbits of PSP agrees well with the results obtained from Helios data set presented by  Berčič et al. (2019). We find the same PAW dependence on β ec : in high-β ec solar wind the strahl appears broader than in the low-β ec solar wind. For the measured energy range the PAW was found to decrease with electron energy reaching down to 30 o for the lower two β ec bins representing the majority of measurements. We present for the first time observations of T s from both, PSP and Helios missions. An anti-correlation was found between T s and the solar wind velocity (v p ), while T s was observed to be constant over radial distance (r). These findings lead us to conclude that the strahl carries the information about the coronal electron temperature at the point of its origin and can be used as a good proxy for the connectivity studies involving remote sensing and in-situ data.
A. PITCH-ANGLE WIDTH -FOV EFFECTS The combined FOV of SPAN-E instruments is not uniform  (Kasper et al. 2016; Whittlesey et al. 2020). Electrons are detected by two instruments and the azimuth anodes of each of them have two possible angular widths, 6 o and 24 o. Part of the full solid angle is not sampled, and part blocked by the heat shield (see Fig. 1 ). We investigated how much the nonuniform FOV affects our data analysis. We identified two extreme configurations of the magnetic field vector in the FOV. The measurement is the most precise when the magnetic field vector lies within part of the FOV covered by the small azimuth anodes of SPAN-A. The most problematic measurement of the strahl electrons happens when the magnetic field is aligned with the radial direction, because in this case the strahl electrons get blocked by the heat shield which is during the encounter time directed directly towards the Sun.
We are grateful for the reviewers comments which were constructive and helped to improve the quality of the present work. This work was supported by the  Programme National PNST of CNRS/INSU  co-funded by  CNES. All the analysis was done, and the plots produced using open source  Python libraries NumPy, Matplotlib, Pandas, and SciPy. We also acknowledge all members of the Helios data archive team (http://helios-data. ssl. berkeley. edu/team-members/)to make the Helios data publicly available to the space physics community.
scRNA-seq pre-processing scRNA-Seq data analyses were performed by GenoSplice technology (www. genosplice. com). Sequencing data quality analysis was performed using FastQC v0. 11. 2 on 6 NMR epidermal cells samples, 3 from a Y NMR group (samples 1J, 5J, 6J) and 3 from an A NMR group (samples 2V, 3V, 4V). For read alignment and unique molecular identifiers (UMI) quantification, CellRanger software v3. 0. 2 was used on Heterocephalus glaber genome HetGla_female_1. 0 with default parameters and gene annotation from Ensembl 96. The 6 expression matrices containing the UMI counts were merged, and only the genes with UMI ≥ 1 in at least one cell were kept. The following filters were applied to generate a global matrix used in further analysis: cells with UMI ≥ 2000, number of detected genes ≥ 700, and cells with UMI in mitochondrial genes ≤ 25%.
Enrichment analysis Using the Cytoscape v3. 7. 2 software and BiNGO plugin (binomial statistical test and Bonferroni correction, threshold with adjusted p<0. 01), we determined which Gene Ontology (GO) categories are statistically overrepresented in a set of genes of a biological network in the newly defined metaclusters on Mus Musculus annotations. For specific analysis, a Fisher exact-test was performed on a list of genes compiled from REACTOME (ROS) and GO terms (aging and wound healing) databases. Results with uncorrected pvalue ≤ 0. 05 were considered enriched.
Histology and immunohistochemistry Four A and 4 Y NMR skin samples were collected under anesthesia by performing 5mm skin punch biopsies on their back skin. The skin was then immerged in formalin for 12 to 24 hours at 4°C, and embedded either in paraffin or OCT compound for sectioning. Formalin-fixed paraffin-embedded skin sections (5 µm) were stained with Hematoxylin and Eosin, Sirius Red and Masson's Trichrome using standard procedures. Epidermal, dermal thickness and number of epidermal layers and cells were measured using Image J software. Cells were counted in 10 -3 mm 2 randomized surface squares in the epidermis of each specimen. Quantifications were done on various parts of the skin, dissected in a gridded fashion and 3 different sectors were analyzed; for each different sector of the skin, 3 different areas of 10 -3 mm 2 were counted.
Wound healing procedure Eight NMR were anaesthetized and punch biopsy devices were used to create four 5 mm surgical wounds on the backs of the animals. All tissues above the panniculus carnosus were excised. Wounds were left uncovered until harvesting. Standardized images of the wounds were obtained at various time points, with a Sony Cybershot 10. 1megapixel DSC-W180 digital camera (Sony, Tokyo, Japan). The images were used to measure the wound closure rate using ImageJ software every 2-3 days.
ACKNOWLEDGMENTS General: We thank  Genosplice Technology  (www. genosplice. com)for scRNA-Seq data analyses and  Daniel Vaiman ,  Dany Nassar ,  Bénédicte Oulès ,  Maria Sbeih  and  Mathieu Castela  for helpful discussions. We also thank  Aude Fert ,  Michèle Oster ,  Sandrine Lamblin ,  Romain Morichon  ( Imaging Platform UMS30 LUMIC ),  IMAG'IC and HISTIM platforms of Institut Cochin , and  Thomas Lilin  ( Ecole nationale vétérinaire d'Alfort ) for their technical support.
Life span The lifespan of fish spans more than two orders of magnitude, from a few weeks in gobies and a few months in annual killifish to 9 years for the damselfish Chromis chromis, and up to several centuries in the Greenland shark  [30] [31] [32] [33]. The lifespan of A. percula has been estimated to be about 30 years  [34]. Sahm and collaborators (2019) performed a survey of anemonefish lifespan data in the wild and in captivity, in which they identified at least two additional species (A. ocellaris and A. melanopus) with a lifespan of over 20 years  [35]. Because this lifespan is longer than other teleost fish of the same size, anemonefish could become an experimental model for long-lived vertebrates  [34]. For example, recently, anemonefish have been used to understand the genetic architecture underlying differences in lifespan  [35].
Since the fish show strong fidelity to their sea anemone, they can be found at the same place after several months, except in the relatively rare case of mortality. Then, every two years, this team traveled to Kimbe to collect new recruits in the various sea anemone and determine who are their parents. Since all breeding pairs present in Kimbe were fingerprinted, they observed that 50% of new recruits are coming from outside the island, 8-10 km away. This demonstrated that A. percula larvae can effectively travel over long distances. Such a unique data set, accumulated over 10 years, also enabled to compare the survival of local recruits (e. g. whose parents come from Kimbe) vs. outsiders and to show the absence of trans-generational fidelity to sea anemone species  [63, 64]. Because long term genealogical trees can now be constructed, this unique Kimbe dataset offers a great perspective to investigate the heritability of specific traits such as body size, pigmentation traits, etc.
The genomes of 11 Amphiprion and Premnas species have been sequenced (Table  1 ) and are available in the NCBI's reference sequence database. Moreover, transcriptomes of 6 Amphiprion species have also been sequenced (Table  1 ). Most anemonefish species and their color pattern mutants are directly provided by pet shops. However, no standard strains are maintained and shared yet between the anemonefish research lab community. Moreover, a website providing information on the features, geographic distribution and images of each species is available (https ://amphi prion ology. wordp ress. com). A community portal should be completed in the coming months, which will include protocols, pictures of adult and developing fish, organization of international meetings, and a community forum.
Acknowledgements We would like to express our deepest appreciation to  Serge Planes  and  David Lecchini  from the  CRIOBE  lab that have been instrumental in our interest in coral reef fish and in particular anemonefish as model systems and have been tremendously helpful to develop our research. We are also thankful to  Timothy Ravasi ,  David Lecchini  and  Marleen Klann  who carefully read this manuscript and helped us to improve it. We would like to thank the Aquariological service of the " Observatoire océanologique de Banyuls sur mer " who take care of the anemonefish husbandry and rearing of our group.
Patient samples and clinical database In this study, three independent cohorts of BC patients from Sun Yat-sen Memorial Hospital (SYSMH) were enrolled. Breast cancer patients (aged 32 to 81) without any distant metastasis at first diagnosis between 1 June 2004 and 31 May 2018 were enrolled as Cohort 1 (n = 113). Paraffin-embedded BC tissue samples and paired non-tumor tissue samples in Cohort 1 were collected for in situ hybridization (ISH), immunohistochemical staining (IHC) or immunofluorescence (IF). In addition, serum samples from two other cohorts of SYSMH were collected for droplet digital PCR (ddPCR) detection (Cohort 2 was a retrospective cohort collected from 1 March 2017 to 30 September 2017, containing 14 benign patients, 30 early breast cancer (EBC) patients and 18 metastatic breast cancer (MBC) patients; Cohort 3 was a prospective cohort from 1 June 2015 to 1 April 2019, in which only MBC patients at first diagnosis were enrolled).
Statistical analysis Statistical analyses were performed using GraphPad Prism 5 software. Student's t-test or one-way ANOVA was performed to test differences between groups in both in vivo and in vitro experiments. X 2 -test was applied to analyze the correlations between circCDYL expression and clinicopathological characterization of BC patients. Kaplan-Meier plots and Log-rank tests were used for survival analysis. The univariate analyses were analyzed by Cox proportional hazards model. The correlations were analyzed using Pearson's correlation coefficients. P < 0. 05 was considered statistically significant.
712, linear CDYL: r = 0. 298) (Fig. 2b , Fig. S3B ). The expression of circCDYL and linear CDYL was increased up to 2. 2 and 1. 2 folds in LC3-dots More tissues, when comparing with LC3-dots Less tissues (Fig. 2c , Fig. S3C ). A Kaplan-Meier analysis indicated that patients with high circCDYL had a poorer disease-free survival (DFS) (HR 2. 85, 95% CI 1. 415-5. 739, P = 0. 0036, Fig. 2d ), but expression of linear CDYL had no effect on DFS of BC patients (Fig. S3D ). These results suggested that circCDYL may play more important role in breast cancer than linear CDYL. Next, BC patients' serum from Cohort 2 and Cohort 3 were collected. Droplet digital PCR (ddPCR) were performed to verify the abundance of circCDYL in serum of these patients. Clinical data from Cohort 2 showed that circCDYL was the most abundant in the serum from metastatic breast cancer (MBC) patients, compared to early breast cancer (EBC) and benign patients (Fig.
Acknowledgements We would like to thank for the  Department of Hepatobiliary Surgery at the Sun Yat-sen Memorial Hospital (Guangzhou, China)  to provide HEK-293 T cell line. We are appreciated that the grant of  Jeunes Talents France-Chine  supported the academic exchanges in  Institut Necker-Enfants Malades (INEM)  and  Université Paris Descartes-Sorbonne Paris Cité. We are appreciated that our research was partly supported by  Fountain-Valley Life Science Fund of University of Chinese Academy of Sciences Education Foundation.
INTRODUCTION The notion of good data stewardship (i. e. , maximizing the opportunities for the efficient discovery and reuse of research outputs) has been around for decades and many implementation choices have already been made by pioneering communities to extend stewardship with the notion of machine-actionability. The FAIR principles can be seen as a consolidation of these earlier efforts and emerged from a multi-stakeholder vision of an infrastructure supporting machine-actionable data reuse, i. e. , reuse of data that can be processed by computers  [1] , which was later coined the "Internet of FAIR Data and Services" (IFDS)  [2]. The FAIR principles are intended as a guide to enable digital resources to become more Findable, Accessible, Interoperable and Reusable for machines and thus also for humans.
These four foundational principles are more explicitly and measurably described by 15 FAIR guiding principles. Any interpretation or implementation of the FAIR principles may in essence be chosen as long as they lead to machineactionable results. This purposely means that individual stakeholder communities can define their own solutions and that these can be adapted over time as technologies evolve. While this freedom of choice may have contributed to the rapid and widespread adoption of the FAIR principles by stakeholders encompassing scientists, publishers, funding agencies and policy makers (for an overview see Budroni et al. [3] ), it has also brought the inherent risk of incompatible solutions between stakeholder communities. To reach the goal of an Internet of FAIR Data and Services  [2] , a global convergence towards accessible, robust, widespread and consistent FAIR implementations is required  [4].
The first step is to share a common, high-level interpretation of the FAIR principles. Mons et al. [5]  discussed early emerging misinterpretations of the FAIR foundational principles and clarified their original intent and interpretation. They emphasize that "FAIR is not a standard … FAIR is not equal to RDF, Linked Data, or the Semantic Web … FAIR is not just about humans being able to find, access, reformat and finally reuse data … FAIR is not equal to Open … FAIR is not a Life Science hobby". Moreover, a desire to expand the purposely limited scope of the principles has led to suggestions to extend the FAIR acronym with additional letters  [6] , often unrelated to the specific objective of facilitating data reuse by machines. Thus, a more detailed and common understanding of the scope, aim and representative implementation choices for each FAIR principle would be helpful to improve their stepwise application by diverse stakeholders, and stimulate FAIR adoption in more geographies and new scientific communities  [7]   [8].
There are several alternative routes towards the implementation of the FAIR principles, some specialized for different types of digital resources. Communities have already published documents that can guide implementation choices. Examples are: "the FAIR metrics"  [9]  and the follow-up Maturity Indicators  [10] , "the FAIRy tale"  [11] , "Top 10 FAIR Data & Software Things"  [12] , the RDA FAIR Data Maturity Model  , the EC report on "turning FAIR into reality"  [13] , and the "FAIR principles explained" described on the GO  https://www. rd-alliance. org/groups/fair-data-maturity-model-wg.
FAIR Principles: Interpretations and Implementation Considerations substrate for machine learning and AI approaches, in keeping with the interim advice to the US' National Institutes of Health (NIH) where it is stated that data should be "AI-Ready" . This has implications for all four foundational principles: • Findability: Digital resources should be easy to find for both humans and computers. Extensive machine-actionable metadata are essential for automatic discovery of relevant datasets and services, and are therefore an essential component of the FAIRification process  [14]. • Accessibility: Protocols for retrieving digital resources should be made explicit, for both humans and machines, including well-defined mechanisms to obtain authorization for access to protected data. • Interoperability: When two or more digital resources are related to the same topic or entity, it should be possible for machines to merge the information into a richer, unified view of that entity.
In the original paper  [1] , it is stated that data is used to refer to all digital resources (not just data in the restricted sense, but also, for example, software tools). Metadata is any description of a resource that can serve the purpose of enabling findability and/or reusability and/or interpretation and/or assessment of that resource. Avoiding the "one person's metadata is another person's data" confusion, FAIR addresses this by treating every data/metadata pair in-isolation; that is, metadata is the descriptor, and data is the thing being described, unambiguously, within the context of that pair. Therefore, this holds true even if, in another context, the thing being described is, itself, metadata. This inherently implies that metadata must also be a FAIR digital resource in its own right.
1) Interpretation Principle F1 states that digital resources, i. e. , data and metadata, must be assigned a globally unique and persistent identifier in order to be found and resolved by computers. This is the most fundamental of the FAIR principles, as globally unique and persistent identifiers are essential elements found in all of the other FAIR principles. Globally unique means that the identifier is guaranteed to unambiguously refer to exactly one resource in the world (please note that global should be interpreted as universal as there are digital assets outside the world). Therefore, it is insufficient for it to be unique only locally (e. g. unique within a single, local database). Persistence refers to the requirement that this globally unique identifier is never reused in another context, and continues to identify the same resource, even if that resource no longer exists, or moves.