dataesr/scientific-paragraphs-categorization huggingface dataset:
This dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS). The Bois de Bouis estate is a private property of 870 ha in the heart of the Plaine des Maures in the town of Vidauban in the Var Department (83). This dataset corresponds to species data from the Ecological Quality Index (EQI) expertise on the golf course in 2012. This dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS). The Bois de Bouis estate is a private property of 870 ha in the heart of the Plaine des Maures in the town of Vidauban in the Var Department footprintWKT county modified dataGeneralisations identificationVerificationStatus A categorical indicator of the extent to which the taxonomic identification has been A Well-Known Text (WKT) representation of the shape (footprint, geometry) that defines the Location.
A Location may have both a point-radius representation (see decimalLatitude) and a footprint representation and they may differ from each other. The full, unabbreviated name of the next smaller administrative region than stateProvince (county, shire, department etc. ) in which the Location occurs. The most recent date-time on which the resource was changed. Actions taken to make the shared data less specific or complete than in its original form. Suggests that alternative data of higher quality may be available on request. verified to be correct. family The full scientific name of the family in which the taxon is classified. establishmentMeans Statement about whether an organism or organisms have been introduced to a given place and time through the direct or indirect activity of modern humans (note: empty in this dataset).
sex The sex of the biological individual(s) represented in the Occurrence (note: empty in this dataset). lifeStage The age class or life stage of the Organism(s) at the time the Occurrence was recorded (note: empty in this dataset). reproductiveCondition The age class or life stage of the Organism(s) at the time the Occurrence was associatedMedia A list (concatenated and separated) of identifiers (publication, global unique identifier, URI) of media associated with the Occurrence (note: empty in this dataset). behaviour A description of the behaviour shown by the subject at the time the Occurrence Column label Column description idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019".
Column label Column description idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce Data set name: Download URL: https://doi. org/10. 15468/qtax2u Data set name: Download URL: https://doi. org/10. 15468/parzzs Column label Column description 2018-2019" 2018-2019". Data format: Darwin Core Archive was recorded (note: empty in this dataset). occurrenceStatus A statement about the presence or absence of a Taxon at a Location. Download URL: doi. org/10. 15468/gvpgea Data format: Darwin Core Archive Description: Column label Column description idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019".
Column label Column description idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019". Description: This dataset contains data from a Serapia grassland survey acquired between 2018 idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ATBI) Bois de Bouis estate -Insect interception trap data. Description: This dataset was acquired in the framework of the partnership between Domaine Bois de Bouis -Données algues d'eau douce 2018-2019". the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and Data set name: Données espèces-Expertise Indice de Qualité Ecologique (IQE) Download URL: https://doi.
org/10. 15468/48jh8f PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre secteur Est du domaine 2013/Ecological Quality Index East Bois de Bouis 2013. and 2019. Data format: Darwin Core Archive national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory Download URL: https://doi. org/10. 15468/f2tpby (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var). recorded (note: empty in this dataset). Data format: Darwin Core Archive Description: coordinateUncertaintyInMetres maximumDepthInMetres The greater depth of a range of depth below the local surface, in metres (note: empty in this dataset). minimumDepthInMetres The lesser depth of a range of depth below the local surface, in metres (note: empty in this dataset).
locationRemarks Comments or notes about the Location (note: empty in this dataset). InformationWithheld Additional information that exists, but that has not been shared in the given record (note: empty in this dataset). institutionCode The name (or acronym) in use by the institution having custody of the object(s) or information referred to in the record (note: empty in this dataset). associatedReferences A list (concatenated and separated) of identifiers (publication, bibliographic reference, global unique identifier, URI) of literature associated with the Occurrence (note: empty in this dataset). samplingProtocol The names of, references to, or descriptions of the methods or protocols used during an Event (note: empty in this dataset). identificationRemarks Comments or notes about the Identification (note: empty in this dataset).
Download URL: https://doi. org/10. 15468/vnunwj Data format: Darwin Core Archive Description: Data set name: Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données lichens 2017-2021/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Lichen data 2017-2021. Download URL: https://doi. org/10. 15468/vrybab Data format: Darwin Core Archive Description: This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var).
The dataset contains lichen data acquired between 2017 and 2021. Data set name: Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données nématodes 2018-2019/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Nematode data 2018-2019. Download URL: https://doi. org/10. 15468/j7ezgn Data format: Darwin Core Archive Description: Data set name: Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données opportunistes/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Opportunistic data. Download URL: https://doi. org/10. 15468/w65gbj Data format: Darwin Core Archive Description: This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var).
This dataset contains opportunistic data acquired between 2011 and 2021. Description: This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (Download URL: https://doi. org/10. 15468/9s77nz Data format: Darwin Core Archive Description: This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var).
This dataset contains Orthoptera monitoring data acquired between 2017 and 2019. Data set name: Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données historiques/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Historical data. This dataset contains historical fauna and flora data acquired between 1990 and 2009. Data set name: Données espèces-Expertise Indice de Qualité Ecologique (IQE) Bois de Bouis 2012/Ecological Quality Index Bois de Bouis 2012. Download URL: https://doi. org/10. 15468/vzgjp5 Data format: Darwin Core Archive Description: Data set name: Données espèces-Expertise Indice de Qualité Ecologique (IQE) Golf de Vidauban 2014/Ecological Quality Index Vidauban Golf course 2014. Download URL: https://doi. org/10. 15468/cykff2 Data format: Darwin Core Archive Description: This dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS).
Ecologie 68: 105-119. URL: http://iqe-patrinat. mnhn. fr/wp-content/uploads/sites/ 12/2015/11/Delzons-et-al. -Rev. -Ecol. -Terre-et-Vie-2-2013. pdf • Desjonqueres C (2016) Ecologie et diversité acoustique des milieux aquatiques: exploration en milieux tempérés. [Acoustic diversity and ecology of freshwater environments : exploration in temperate environments]. Muséum national d'Histoire Naturelle, 246 pp. URL: https://theses. hal. science/tel-01563282 • Dusoulier F (2016) Note sur les orthoptères et les hémiptères du Bois de Bouis (Vidauban, Var). Muséum d'Histoire Naturelle de Toulon et du Var. Report, 14 p. • European Topic Centre On Biological Diversity (2008) European Nature Information System (EUNIS) Database. Habitat types and Habitat classifications. ETC/BD-EEA, Paris. URL: https://www.
This work was supported by grants from ANR (APATE, ANR-22-CE39-0016), Horizon Europe VERA. AI (No. 101070093), Région Île-de-France and UDOPIA (ANR-20-THIA-0013). Centre Borelli is also a member of Université Paris Cité, SSA and INSERM. The GOP structure, which defines different types of frames and their order in a video, plays a crucial role in video encoding  [18] , and can be exploited in forensics  [2] ,  [19]. Frames called intra pictures (I-frames) are encoded independently of the other frames; the predicted pictures (P-frames) only encode changes relative to the previous frame; finally, bidirectional predicted pictures (B-frames) encode changes relative to its previous and subsequent frames. These frames have different properties: I-frames are the least compressible and independent of their neighbors, while B-and P-frames are more compressible and also dependent on neighboring frames.
EXPERIMENTS To compare the proposed method with  [15] -  [17] , we first selected 19 uncompressed YUV sequences 1. Each video was clipped to no more than 400 frames. Following the settings in  [16]  and  [17]  and using ffmpeg software with libx264 encoder, the first compression was processed with different constant bitrates B1 ∈ {300, 700, 1100} kbps and GOP sizes G1 ∈ {10, 15, 30, 40}, while for the second compression the bitrates were B2 ∈ {300, 700, 1100} kbps and the GOP sizes were G2 ∈ {9, 16, 33, 50}. Note that the higher the bitrate, the lower the compression. In total, the constructed dataset has 228 singly compressed videos and 2736 doubly compressed videos. Considering that the compared methods only work on videos without B frames, the videos were first compressed only with I and P frames for comparison.
Methods To assess our method, we evaluated 166 individuals from the ADNI database, including amyloid-beta negative and positive cognitively normal subjects, patients with mild cognitive impairment, and patients with Alzheimer's disease dementia. We used the clustering coe cient and the global e ciency to measure the functional network topology and assessed their relationship with amyloid and tau pathology measured by positron emission tomography, as well as cognitive performance using tests measuring memory and global cognition.
Weiner, MD. The primary goal of ADNI has been to test whether serial MRI, PET, other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of MCI and early AD. ADNI is conducted in accordance with the ethical standards of the institutional research committees and with the 1975 Helsinki declaration and its later amendments. Written informed consent was obtained from all subjects and/or authorized representatives and study partners. Ethical permits have been obtained at each participating site of ADNI and we have signed the data user agreements to analyze the data.
Network analysis We used two network measures, namely the clustering coe cient and the global e ciency, to assess the global topology of the individual connectivity networks. The clustering coe cient (illustrated in Fig. 2a ) is a measure of network segregation that is calculated as the fraction of closed triangles around a node and increases with the number of local connections. In contrast, the global e ciency (illustrated in Fig. 2g ) re ects the level of network integration and it increases when the paths connecting any two nodes in the network become shorter. All graph measures were calculated using the Brain Analysis using Graph Theory software (34) (BRAPH, http://braph. org/).
UMAP visualization after merging the total dataset or per condition displayed similar distributions of cells into clusters, both in the control and in the two IR conditions over time, which indicated the absence of obvious batch effects due to sample processing or sequencing, thus underlining the reproducibility of the single cell experimental procedure and analysis (Fig. 1b , Supplementary Fig. 1a-c ). We used cell type-specific markers from recently published scRNA-seq datasets  [12] [13] [14]  to annotate major populations. This resulted in the identification of 18 main cell types (Fig. 1b, c ): non-immune cells, which comprise 4 epithelial cell populations (AT2 cells, AT1 cells, club cells, and ciliated cells), 3 mesenchymal cell clusters (fibroblasts, smooth muscle cells -SMC-and mesotheliocytes), 1 endothelial cell -EC-cluster and several clusters of immune cells, which include 7 myeloid compartments (monocytes, alveolar macrophages -AM-, interstitial macrophages -IM-, dendritic cells -DC-, plasmacytoid dendritic cells -pDC-, neutrophils and basophils) and 3 lymphoid compartments (T cells, natural killer -NK-cells and B cells).
An interactive web-based interface to study lung responses to irradiation This work describes some of the key features occurring after radiation injury in the lung at the cellular and molecular level. Nevertheless, due to a large amount of generated data, not all the cell types were described, nor all the molecular alterations that occur during fibrogenesis were studied. For this reason, we have built a dedicated website that is accessible to the scientific community, so that anyone can explore our murine single-cell atlas of the lung response to radiation injury and use it for their own research (Supplementary Fig. 7 ). This open-access website (https:// lustra. shinyapps. io/Murine_RIPF_Atlas/), built using the R package ShinyCell  25  , allows the investigation of all the different lung cell populations, as well as the changes in gene expression after the different time points and doses of IR.
In addition, four different visualization methods are available to study the gene expression: Violin plot (Fig. 7e ), boxplot, bubble plot (Fig. 7f ), and heatmap (Violinplot/Boxplot tab and Bubbleplot/Heatmap tab), which allow the comparison of the expression of genes along the different conditions, thus, providing insightful information about radiationinduced fibrosis. These multiple options allow a wide range of methods for data visualization that can be adapted to the user's needs. In conclusion, this web-based interface presents a rich dataset that permits the scientific community to investigate the response of the lung to radiation injury for their features of interest with no need of previous bioinformatic knowledge. Raw data is also available at GSE211713 for deeper analysis.
Discussion We have built a murine single-cell atlas illustrating the early and late responses of the lung to radiation. The dataset contains more than 100,000 cells from 20 different lungs from non-irradiated as well as IR 10Gy and IR 17Gy mice. Cell type annotations based on published studies identify the 21 main lung cell populations already described using scRNA-seq approaches  [26] [27] [28]. This study revealed, in each lung population, the progressive transcriptional changes occurring in the months following radiation injury from the acute inflammatory phase to the development of pulmonary fibrosis after exposure to fibrogenic dose of radiation. The comparison of the molecular alterations induced by a non-fibrogenic (IR 10Gy ) versus a fibrogenic dose (IR 17Gy ) allowed to uncover the physiopathological features of radiation injury in the lung.
These foamy macrophages have been found in different mouse models of lung-induced injury as well as in patients with fibrotic lung diseases  30. Interestingly, our spatial smFISH analysis in lung tissue after radiation injury indicates that these foamy macrophages tend to aggregate in fibrotic foci with an increased cell volume and a high level of endogenous fluorescence. These observations corroborate with data from other groups showing that clusters of M2 macrophages are detected after IR, contribute to fibrosis development, and are controlled by adenosine signaling  34, 35. Concomitantly to the bronchiolization and the destruction of alveoli observed during fibrosis development, the progressive disappearance of AT2 is associated with profound changes in the transcriptome of remaining AT2 cells.
These results support the idea that radiation triggers EndoMT phenotype coupled to increased interactions with myofibroblasts, suggesting that endothelial cells may contribute as a source in the expansion of myofibroblasts during the development of RIPF. In summary, this study describes the transcriptional changes occurring at the single-cell level in the lung in the months following radiation injury. This large and comprehensive dataset provides a starting resource to explore and characterize molecular mechanisms underlying the different physiological and pathological steps occurring after IR (e. g. , from acute wound healing to fibrosis development). To facilitate data visualization and interrogation, a user-friendly web-based interface is accessible to the scientific community without the need for specific computational skills.
1. 5-2% isoflurane was used to anesthetize the mice, which were maintained on a PMMA vertical stand in the vertical upright position. The 3D reconstruction of the images was calculated from 1,440 projections using the integrated software Murislice (XStrahl). Then, ImageJ/FIJI (ImageJ, NIH, Bethesda, MD) was used to reconstruct the slices. This analysis allowed to determine the level of fibrosis of the mice. Further details can be found in ref. 42.
scRNA-seq data analysis First, raw sequencing was processed using the 3. 0. 2 Cell ranger pipeline (10x Genomics). Briefly, Illumina sequencing files (bcl2) were demultiplexed and mapped onto the mm10 reference genome. This allows the creation of a count matrix table for each of the samples. Then, the count matrices were individually loaded in R (4. 0. 5) and analyzed using Seurat package v4. 0. 1  43. In order to remove the contamination from the "soup" of cell-free RNAs, we used SoupX  44. This tool is able to remove ambient RNA contamination from droplet-based scRNA-seq experiments. Briefly, first SoupX estimates the mRNA expression profile from empty droplets. Then it estimates the contamination fraction and the fraction of UMIs originating from the background in each cell. Finally, it corrects the expression of each cell using the ambient mRNA expression profile and estimated contamination.
In a second step, each cell population was cleaned in more details by removing the cells that presented a high percentage of mitochondrial genes, a low nCounts, or that expressed markers characteristic of other cell types, which suggests the presence of doublets. All quality controls are present on the web interface. Then, cell-type marker genes for each cluster were identified using the function FindAllMarkers of Seurat. Cell clusters were named based on cell type-specific markers from recently published scRNA-seq datasets  [12] [13] [14]. For each of the analyzed clusters, we performed differential expression analysis using the function FindMarkers with the MAST package (two-sided test), which identifies differentially expressed genes between two groups of cells using a hurdle model tailored to scRNA-seq data  47.
We studied the genes with a logFC threshold of >1 or <-1 and an adjusted p-value threshold of <0. 05 using the Gene Set Enrichment Analysis (GSEA) computational method, which defines if a set of genes shows statistically significant, concordant differences between two states. Violin plots and Heatmaps were generated with Seurat for specific significant differentially expressed genes. To calculate the single cell data score, first a dataset corresponding to a cell state or biological process is chosen. Then, the table of expression of these genes by each cell is extracted. For each gene, the expression data is centered and normalized. Finally, for each cell, we computed the mean of the centered normalized gene expression. This gave us an expression score for each cell which was then plotted with UMAP.
smFISH probes design and preparation The design of smFISH probes was performed with the R-package Oligostan  51. For a given target mRNA, Oligostan outputs a list containing all the potential probe sequences fulfilling these requirements: length between 26 nt and 32 nt, score around ΔG 37 °C value of 90%, minimal distance between probes of 2 nt, GC percentage between 40 and 60%, 5 different criteria for probe composition (nucleotide composition in A < 28%, no AAAA stacks, C nucleotide composition between 22 and 28 %, no CCCC stacks in any six consecutive nucleotides in the first 12 positions and no 4 nonconsecutive C in any 6 consecutive nucleotides in the first 12 positions). To each RNA-specific sequence, a shared readout sequence (FLAP Y, 27 nt) was added, and probes with the highest scores were selected.
Image acquisition For each sample, 54 three-dimensional image stacks were captured with an interval of 0. 3 µm (total of 16. 2 µm) on a widefield microscope (Upright Widefield Apotome Zeiss) equipped with a 63 × 1. 4 numerical aperture (NA) objective and a CCD camera (CoolSNAP HQ2) and controlled with ZEN microscope software (ZEISS Microscopy). Three lasers were used to excite DAPI (excitation time 40 ms) and smFISH probes labeled with Cy3 (excitation time 300 ms) and Cy5 (excitation time 300 ms). When acquiring tiles with a 5 × 5 FOV, 16 threedimensional image stacks were captured with an interval of 0. 3 µm (total of 4. 8 µm).