dataesr/scientific-paragraphs-categorization huggingface dataset:
All environmental data were interpolated linearly on a 0. 1° spatial grid, in the Northern Hemisphere. Environmental values were extracted for the year and month corresponding to each occurrence data. Climate models. To make future predictions, environmental variables (see above) were considered under Intergovernmental Panel on Climate Change (IPCC)'s RCP8. 5 scenario using four climatic models (HadGEM2-CC, HadGEM2-ES, ACCESS1. 0 and ACCESS1. 3) considered as performant (reasonably simulating recent past climate) when predicting future Arctic climates, in particular the cryosphere  17. Modeling little auk distributions. We used a model averaging approach in the 'biomod2' package in R  46  with Boosted Regression Tree (BRT), Random Forest (RF), Classification Tree Analysis (CTA) and Flexible Discriminant Analysis (FDA) algorithms which deal in the same way with pseudo-absences parametrization  54.
Beyond existing presence data, we generated five sets of 1000 random pseudo-absences outside of current range (SRE method) and ten sets of 100 random pseudo-absences outside of a 2° area around each presence data, for wintering and for summer nesting/foraging distribution modeling, respectively. Pseudo-absences were time-stamped using the same temporal distribution as occurrence data, and environmental variables were extracted according to each location and date. We performed three runs for each set of pseudo-absences, with each distribution modeling and each 'biomod2' algorithm. For each run, outputs were assessed with the True Skill Statistic (TSS) and the importance of each environmental variables was calculated. Finally, for each distribution model, all obtained models (number of algorithms *3*number of pseudo-absence data sets) were weighted with TSS, and averaged to yield a single ensemble model.
Acknowledgements We warmly thank all providers of the GBIF, OBIS-SEAMAP, NPPSD databases and  Sébastien Descamps  for access to the data set "Seabird colonies of the Barents Sea,  White Sea  and  Kara Sea". We also thank the  French Polar Institute Paul Emile Victor  for funding the  ADACLIM program  (IPEV program  388 ). Many thanks to  Nicolas Courbin  and  Clara Péron  for their advice. Finally, thanks to  Junya Watanabe  for insights on little auks in the Pacific Ocean.
g. , Refs. [67] [68] [69]. Current models of the GMF like those of Refs. [70] [71] [72]  reproduce the Faraday RM data and synchrotron emission maps to which they were fitted, although the GMF morphology differs substantially between these models. This implies, e. g. , that it is at present not possible to correct the deflection of a UHECR by the GMF in a model-independent way. In contrast, CR propagation at lower energies depends mainly on global features of the GMF, as, e. g. , the average escape time from the Galactic disk, and the differences between these models play a smaller role. Despite the variations between current GMF models and the relative large uncertainties in the estimates of their parameters, we can draw a few important conclusions: First, a significant contribution to the total field strength is the anisotropic turbulent (also called "ordered random" or "striated") field whose fluctuations have typical length scales larger than a pc.
Medium scale anisotropies. Combining the data of the AGASA, HiReS, Yakutsk, SUGAR, and other experiments after rescaling their energies to a common scale, Ref. [367]  found in 2005 medium scale anisotropies with 20-25 degrees scale at the 3σ confidence level. Anisotropies on such scales were seen later in the experimental data from the next generation experiments TA  [368, 369]  and PAO  [370]. In Fig. 34 , we show a sky map combining events with E > 5. 7 × 10 19 eV from these two experiments. The arrival directions are smeared on circles with radius 25 • and the colour code  indicates the local significance of an over-or under-fluctuation. The most significant feature of this map is the "TA hotspot", which is centered at R. A. 150 • and dec 40 •. This direction points towards the Ursa Major supercluster; note also that the Supergalactic plane indicated by the thin line is close to the hot spot.
Therefore the signature of the transition in the composition is the disappearance of the (Galactic) iron, and the increase of a light or intermediate extragalactic component. An additional powerful constraint comes from anisotropy measurements which limit a light or intermediate Galactic component. From the data presented in the previous section, the following conclusions can be drawn: Using only the composition data, the limits on the iron fraction from Fig. 31  imply that the Galactic contribution to the observed CR spectrum has to die out before 7 × 10 17 eV. The confidence in this conclusion is strengthened considerably, if one combines the composition and anisotropy measurements: In Ref. [300] , it was shown that a light (intermediate) Galactic CR flux leads to a dipole of order 20% (10%), overshooting clearly the limits which are on the percent level  [174].
But a reduction of the proton flux would in turn reduce the neutrino flux and the model will fall short of explaining the IceCube data. In contrast, the scenario including photo-disintegration reproduces the X max and RMS(X max ) data well, taking into account the systematic uncertainties. Finally, let us comment briefly on some other recent extragalactic CR models which attempt at the same time to account for the diffuse neutrino flux observed by IceCube. The authors of Ref. [388]  explain the IceCube neutrinos by CR interactions in the galaxy clusters surrounding UHECR sources. This scheme may be considered as a concrete physical model of the "only hadronic" scenario presented above. The CR flux in this model has however no ankle feature and requires therefore a second extragalactic component.
A multitude of models for Galactic CRs has been developed which can explain one or several of these features. In order to distinguish between them, additional experimental data are necessary. For instance, the confirmation of a power law-like positron spectrum with a steepening by ∆α = 1 at 300 GeV would support the idea of a 2-3 Myr old local source where the positrons are produced during propagation  [215]. The related suggestion that the positrons are produced close to a younger source would lead instead to a steeper break in the positron spectrum at higher energy, E ∼ 1 TeV  [253, 255]. In contrast to this high-energy suppression, the reacceleration model of Ref. [247]  predicts a rise of the positron flux with energy. If the positrons are connected instead to nearby pulsars, several bumps related to the steep high-energy cutoff of the nearest pulsars may become visible in the positron spectrum.
Its direction points away from the Galactic centre and is roughly consistent, taking into account deflections in the GMF and with an overdensity in the local galaxy distribution. On smaller scales, the most prominent deviation from isotropy is the TA hot spot. Additionally, the PAO claims evidence for correlations of the UHECR arrival directions with specific types of CR sources, as e. g. starburst galaxies. At present it is however unclear if these correlations do not simply reflect the nearby large-scale structure. Three pieces of evidence can be used to determine the energy at which the transition from Galactic to extragalactic CRs takes place. First, the behaviour of the dipole anisotropy suggests that the transition starts at 10 17 eV. Second, the disappearance of the iron component at 5×10 17 eV in the PAO composition data signals the end of the Galactic CR spectrum.
Acknowledgments It is a pleasure to thank  Gwenal Giacinti ,  Oleg Kalashev ,  Andrii Neronov , and  Sergey Ostapchenko  for fruitful collaborations on topics related to this review. We are grateful to  Carmelo Evoli ,  Kazunori Kohri ,  Dmitry Podorozhniy ,  Günter Sigl ,  Nicola Tomassetti  and  Michael Unger  for providing updated figures and data for this review. Last but not least we would like to thank  Markus Ahlers ,  Katia Ferrière ,  Yutaka Fujita ,  Gwenael Giacinti ,  Kazunori Kohri ,  Paolo Lipari ,  Igor Moskalenko ,  Sergey Ostapchenko ,  Peter Tinyakov ,  Nicola Tomassetti , and  Michael Unger  for valuable comments on this article.
Antibodies The primary antibodies used for immunofluorescence and/or western blot hybridization were H2AX (rabbit, Cell Signaling, #7631), ␥ H2AX (mouse, Millipore, #05-636), cyclin B1 (rabbit, Santa Cruz Biotechnology, #sc-752), histone H3 (rabbit, Abcam, #ab1791), cyclin E1 (mouse, Cell Signaling, #4129), ATM (rabbit, Genetex, #GTX111106), pATM (rabbit, Abcam, #ab81292), pATM (mouse, Cell Signaling, #4526), ATR (rabbit, Genetex, #GTX128146), pATR (rabbit, Cell Signaling, #58014), Nbs1 (rabbit, Abcam, #ab23996), pNbs1 (rabbit, Cell Signaling, #3001), pChk1 (rabbit, Cell Signaling, #2341), pChk2 (rabbit, Cell Signaling, #2197), pRPA (rabbit, Bethyl, #A300-246A), TopBP1 (mouse; Santa Cruz Biotechnology, #sc-271043), Mre11 (rabbit, Novus Biologicals, #Nb100-142), B23 (mouse, Sigma, #B0556), Nucleolin (rabbit, Sigma, #N2662), UBF (mouse, Santa Cruz Biotechnology, #sc-13125), Ki67 (rabbit, Cell Signaling, #9129), CHD4 (mouse, Abcam, #ab70469), Treacle/TCOF1 (rabbit, Sigma, #HPA038237), S9.
After lysis, the slides were washed three times for 5 min in PBS and incubated in 1× TBE (Tris-Borate-EDTA buffer) for 20 min at 4 • C. Electrophoresis was performed in a Trevigen electrophoresis system (#4250-050-ES) for 10 min at 4 • C and 1 V/cm in 1× TBE. The comets were counterstained with SYBR Green for 1 h (1:3000; Thermo Scientific, #S7563). The comets were visualized at four magnification using an inverted Nikon Eclipse Ti-E fluorescence microscope equipped with a Nikon Intensilight C-HGFI light source (objective: Nikon Plan Fluor 4/0. 13; camera: DS-Qi2). The images of the comets were analyzed using CellProfiler software (version 2. 1. 1 rev 6c2d896).
Statistical analysis ChIP and RT-PCR data are reported as mean values from at least three biological replicates, with error bars denoting SD. Immunostaining and comet assay images were analyzed by CellProfiler software; the measurements obtained are presented in box-whisker plots. At least 500 cells were analyzed in each experiment. Comparisons between two groups were performed using a paired two-tailed Student's t-test using IBM SPSS Statistics 20.
Data are represented relative to the input. Values are the means ± SD from at least three independent replicates. (C) HeLa cells were subjected to hypoosmotic stress (OS) for 30 min or 3 h and stained with antibodies against ␥ H2AX (green) and UBF (red). Control represents HeLa cells that were not exposed to hypoosmotic stress. The DNA was stained with DAPI (blue). Structured illumination microscopy (SIM) analysis was performed. The co-localization analysis was performed on the merged images. The graphs illustrate the quantification in arbitrary units of the distribution of UBF and ␥ H2AX fluorescence along the lines shown in the merged panels. Scale bar: 5 m. loops under hypoosmotic stress conditions has been provided by immunostaining analysis (Figure  4D ) and ChIP (Figure  4E ) with the RNA:DNA hybrid-specific antibody S9.
Analyses of Fluorescence Intensity and Morphological Characteristics Quantitative analysis of fluorescence intensity was performed using NIH ImageJ 1. 52 software as previously described  [31]. First, the background signal intensities were measured from regions without any cells and subtracted from all the images, and the remaining signals of cells were used to define total cell areas. To define the morphological characteristics of cultured mesencephalic neuronal processes, individual TH-positive neurons were randomly selected and analyzed by Sholl analysis  [42, 43]. Sholl analysis was performed using the Sholl tool of Fiji J  [44]  to quantify the number of intersections at 10 µm intervals from the soma  [45]. Statistical analysis was performed by comparing the number of intersections of the cultured mesencephalic neurons derived from FABP3 -/-mice with those from cultured mesencephalic neurons from wild type mice for each 10 µm interval using GraphPad Prism 8 (GraphPad Software, CA, USA).
Statistical Analyses All values are expressed as mean ± standard error of mean (SEM). Statistical significance was tested by one-way analysis of variance (ANOVA) with post-hoc Tukey's multiple comparison test or two-way ANOVA with post-hoc Bonferroni's multiple comparison test. A p value < 0. 05 was considered as statistically significant. All the statistical analyses were performed using GraphPad Prism 8 (GraphPad Software, CA, USA). Supplementary Materials: Supplementary materials can be found at http://www. mdpi. com/1422-0067/20/21/ 5358/s1. Author Contributions: Investigation and data analysis, I. K. and K. F. ; Reagent synthesis, L. B. and R. M. ; Writing-original draft preparation, I. K. ; Writing-review and editing, K. F. ; Funding acquisition, K. F. , I. K. , and R. M.
This research was funded by the Strategic Research Program for Brain Sciences from Japan Agency for Medical Research and Development, AMED (JP18dm0107071 and JP19dm0107071) to K. F. , Japan Society for the Promotion of Science, KAKENHI (19K07097), Kobayashi Foundation, Intelligent Cosmos Academic Foundation to I. K. and the Centre National de la Recherche Scientifique, the Fondation Simone et Cino Del Duca of the Institut de France, the Fondation Bettencourt-Schueller, the Fondation Recherche Médicale (Contract DEQ 20160334896), and the EC Joint Programme on Neurodegenerative Diseases TransPathND, ANR-17-JPCD-0002-02 to R. M.
Funding: This research was funded by the Strategic Research Program for Brain Sciences from Japan Agency for Medical Research and Development, AMED (JP18dm0107071 and JP19dm0107071) to K. F. , Japan Society for the Promotion of Science, KAKENHI (19K07097), Kobayashi Foundation, Intelligent Cosmos Academic Foundation to I. K. and the Centre National de la Recherche Scientifique, the Fondation Simone et Cino Del Duca of the Institut de France, the Fondation Bettencourt-Schueller, the Fondation Recherche Médicale (Contract DEQ 20160334896), and the EC Joint Programme on Neurodegenerative Diseases TransPathND, ANR-17-JPCD-0002-02 to R. M.
Comparative Genomics and Analysis of CRISPR Loci CRISPR systems were searched in a selection of 52 mollicutes genomes (Supplementary Table  S1 ) available in the MolliGen database  (Barré et al. , 2004)  or in GenBank  (Benson et al. , 2017)  using (i) Blastp  (Johnson et al. , 2008)  search of Cas proteins, (ii) analysis of direct repeats at the CRISPR database  (Grissa et al. , 2007)  with the included CRISPR finder tool  (Couvin et al. , 2018). A manual analysis of all candidates was then achieved to get a precise annotation of the loci. In order to predict DR/tracrRNA hybrid secondary structure, sequences of DR and tracrRNA were concatenated and the secondary structures of the hybrids were simulated using the mfold software  (Zuker, 2003)  available at http://unafold. rna. albany. edu/.
Spacer Analysis Several custom databases were built to perform spacer sequences analyses. First, a custom database was assembled from the complete genomes of the NCBI referenced with the Taxonomy identifier as tenericutes (taxid = 544448). 445 complete genomes were retrieved and used to build two custom databases composed of a complete set of CDSs and a collection of intergenic regions, respectively. A prophage database was also built by retrieving sequences from the European Nucleotide Archive (contains 2480 phage sequences) and the prophage and virus database 1 https://weblogo. berkeley. edu/ (Last update: 2017) provided by  Zhou et al. (2011). Using these three databases, blastn (ncbi-blast-2. 7. 1 + version) analyses were carried out to search sequences similar to the spacers sequences (562 unique sequences) retrieved from mollicutes CRISPR arrays.
Search for Mobile Genetic Elements in Mollicutes Genomes GenBank genome files of selected mollicutes were downloaded from NCBI Website. (1) Integrative and conjugative elements (ICEs) were identified following the method described in  Tardy et al. (2015). Briefly, tblastn searches were conducted using four genes as queries  (CDS 5, 17, 19, 22  from Mycoplasma agalactiae PG2 ICEs and Mycoplasma capricolum subsp. capricolum ATCC 27343 ICEs). Hits were manually analyzed and located on the related chromosome. Co-location of the 4 CDS and consistent blast results were interpreted as signs for the presence of complete ICE. Co-location of 2 or 3 CDS and consistent blast results were considered as revealing degraded or atypical ICEs. (2) Insertion sequence were identified using IS finder  (Siguier, 2006)  at https://isfinder.
biotoul. fr/. (3) Restriction systems were predicted using the Rebase database  (Roberts et al. , 2015)  at http://rebase. neb. com/ rebase/rebase. html. When several genes were missing, manual check of the region was perform with a Blastp to identify if the system was complete or not. (4) Phage detection was performed using PHAST  (Zhou et al. , 2011)  at http://phast. wishartlab. com/. Additional manual comparisons between mollicutes bacteriophages described in the literature and mollicutes genome sequences were performed using tblastn.
Cas9 from reference bacteria were chosen from  Fonfara et al. (2014) ; proposed subtypes were also defined according to this work; * and * * refer to the two Cas9 from S. thermophilus also described in this work. Cas9 from mollicutes are highlighted in gray. Cas9 accession numbers are available in Supplementary Table  S1. other CRISPR/Cas systems from mollicutes for which a csn2 gene has been predicted.
Cas9 Proteins of Mollicutes and S. aureus Have Similar Domains Except the PAM-Interacting Domains We compared predicted Cas9 proteins from mollicutes with structurally characterized Cas9 using HHpred. In all cases, the best hit was SaCas9 from S. aureus (PDB ID 5CZZ), with 100% probabilities and e-values ranging from 4. 9E-146 to 2. 6E-103. HHpred alignments were extended over all the proteins except for the Type II-C Cas9 of S. apis B31, S. syrphidicola EA1 and Ca. H. crinochetorum Av for which the highly significant alignments stopped after the RuvC-III domains. Still with SaCas9, similarity ranged from 31% to 58%, with the best similarities observed for the Cas9 of A. palmae (concatenation of the two protein parts predicted from the ORF interupted by a mismatch), S. helicoides and S. litorale.
The logo plot designed from the 11 DR from mycoplasmas evidenced an internal motif GTACAAT conserved at position 12-18 in all species except M. mobile 163K. All 17 consensus DR sequences from mollicutes were submitted to an automated classification process using CRISPRMap tool. By comparing mollicutes DR with a database of 4719 consensus repeats covering 24 families and 18 structural motifs, CRISPRMap assigned all DR to superclass F except DR from Ca. H. crinochetorum which was not assigned. Superclass F gather DR from various bacteria with a high level of sequence diversity. Notably, this superclass includes Family F13 to which DR from the typical S. pyogenes CRISPR/Cas Type II system has been assigned. In Type II CRISPR, pairing between the typical antirepeat region of the tracrRNA and the DR from the pre-crRNA is essential for the RNAse III processing of the hybrid structure into a mature dual-guide RNA  (Deltcheva et al.
Some Spacers From Mollicutes CRISPR Arrays Target Phage and Bacterial Genes In order to get some insights on the potential origin of the spacers present in CRISPR loci of mollicutes, all spacers were retrieved from the 17 identified CRISPR arrays and potential corresponding protospacers were searched in mollicutes (database of 224 genomes) and prokaryotic phages (database of 2480 phages) using a blastn approach. Out of the 595 spacers retrieved, 562 were unique (Supplementary Table  S5 ). Repeated spacers were observed in CRISPR arrays of M. apis B31 (1 repeat), M. palmae J233 (8 repeats), M. gallisepticum S6 (1 repeat), M. dispar ATCC27140 (1 repeat), M. ovipneumoniae NM2010 (5 repeats), M. hyosynoviae NPL1 (1 repeat), M. arthritidis 158L3_1 (2 repeats), M. mobile 163K (2 repeats), and Ca.
H. crinochetorum Av (2 repeats). Most spacers did not have any hits in the databases used, however, for 15 of them, highly similar sequences were retrieved. Each potential protospacer was manually checked. One spacer from the CRISPR array of S. apis B31 (spacer 24) had a perfect hit in a CDS of the Spiroplasma floricola 23-6 genome (SFLOR_RS04885). Interestingly, this CDS is part of a predicted ICE and is homologous to CDS19 described in other ICE from various mollicutes species. A total of 5, 1 and 2 spacers targeting phage and prophage sequences were identified in the CRISPR arrays of M. cynos C142, M. canis PG14 and M. arthritidis 158L3_1, respectively. A detailed analysis was conducted on these species. Comparison of the genomes of M. cynos C142 and 210 strains showed that the complete CRISPR/Cas locus identified in C142 was replaced by genes encoding a Type III restriction/modification system in strain 210 (Figure  5 ).
The air heat exchanger will be a baffled cross-flow fluidized bed. Air will be heated in an in-bed finned-tube bundle. Air will be fed at 5. 8 bar and ~ 270°C. The hydrodynamics and heat transfer characteristics of the air heat exchanger were experimentally investigated towards bubble properties and heat trasnfer coefficient. The bed to tube heat transfer coefficient was measured for different pipe geometries at bed temperatures up to 700 °C, exceeding 2 kW/m 2 K for a twin-bore finned tube but only about 650 W/m²K for the bare tube of equal outside diameter. The heat transfer coefficient from the tube wall to the turbulent air flow inside the tube (~ 325 W/m 2 K) determines the design. NEPTUNE_CFD software was used to perform 3D-numerical simulations of the fluidized bed hydrodynamics via an Eulerian n-fluid approach.
Neptune_ Code Description Three-dimensional numerical simulations used the code NEPTUNE_CFD. This Eulerian n-fluid unstructured parallelized multiphase flow software has been developed in the framework of the NEPTUNE project financially supported by the "Commissariat à l'Energie Atomique", by "Electricité de France", by the "Institut de Radioprotection et de Sureté Nucléaire", and by AREVA-NP  8. The modelling approach for poly-dispersed fluid particle flows is implemented by the "Institut de Mécanique des Fluides de Toulouse". The numerical solver was developed for High Performance Computing  9. The Eulerian n-fluid approach used is a hybrid method 10 in which the transport equations are derived by grouped averaging conditioned by the phase presence for the continuous gaseous phase and by use of the kinetic theory of granular flows supplemented by fluid effects for the dispersed phase.
CONCLUSIONS The use of a crossflow bubbling fluidized bed with in-bed tubular array was experimentally investigated towards hydrodynamics (bubbling) and heat transfer. Bubble sizes and frequencies were measured from high speed imaging and correlated, with and without tubular array being present. The geometry of the tube bundle is important. The heat transfer coefficient from the bed to the finned tube wall exceeds 2kW/m 2 K. The heat transfer coefficient from the tube wall to the turbulent air flow (~325 W/m 2 K) hence determines the heat exchanger design. NEPTUNE_CFD software simulation and experimental results were in very fair agreement, stressing the capability of mathematical models to predict the behaviour of a cross-flow bubbling fluidized bed.