dataesr/scientific-paragraphs-categorization huggingface dataset:
Global data sets compilation Global oxygen isotopic data sets for the atmospheric and oceanic components have been already compiled for the Late Holocene (LH) and have been compared and discussed with iLOVECLIM results  (Caley and Roche, 2013). Here we compiled δ 18 O data at sites for which the LGM interval is available in order to calculate signal anomalies. Table  1  is a compilation of δ 18 O data from six published records from Greenland ice cores. The ice δ 18 O anomalies are reported as the difference between averaged δ 18 O values computed over the period 20 000-22 000 years BP and over the last 1000 years of each record, using published chronologies. Table  1  also includes calcite δ 18 O data from 12 published speleothem records. We compiled only the speleothem records that cover both the LGM and LH time interval.
, 2005)  (Table  S1  and S2 ). The database composed of planktic and benthic foraminifera calcite δ 18 O measurements of deep-sea cores is available at PANGAEA (Data set doi:10. 1594/PANGAEA. 836033). Concerning planktic foraminifera, we worked with δ 18 O data of the most commonly measured planktic foraminifer species: Globigerinoides ruber white and pink, Globigerinoides sacculifer, Globigerina bulloides, and Neogloboquadrina pachyderma sinistral for the majority of the sites  (Waelbroeck et al. , 2005). Two exceptions occur at sites MD96-2077 and OCE326-GGC5 for which Globorotalia inflata is used (Table  S1 ). We extended our data set with 10 calcite δ 18 O measurements of planktic foraminifera Neogloboquadrina pachyderma sinistral compiled by  Meland et al. (2005). We only selected records for which the LGM level was determined by AMS 14 C and for which LH data (last 3000 years) was available.
4a ). There is probably some bias due to limitation of the model together with the processes operating in the atmosphere, soil zone, epikarst and cave system that hamper a good quantitative data-model comparison for the calcite δ 18 O signal as already observed with a larger database  (Caley and Roche, 2013). To test whether these biases are climate-independent constant terms, the simulated annual mean anomaly between the LGM and the present is then compared to speleothem data (Fig. 4b ). Considering the error bars on the data (Table  1 ), we observe overall positive calcite δ 18 O anomalies except for Solufar Cave and South American caves (Fig. 5 ). For South America, there is a failure in iLOVECLIM to simulate lower δ 18 Op (Fig. 1 ) as also observed in other GCMs  (Jouzel et al. , 2000; Werner et al.
1 ). We computed annual mean calcite δ 18 O from simulated δ 18 Osw and SST and compared the results with deep-sea core data. Data and model results for the present day show an excellent agreement (Fig. 7 ) as already observed with a larger database  (Caley and Roche, 2013). We chose a depth habitat of 0-50 m to calculate calcite δ 18 O anomalies as we previously demonstrated that it was suitable for a comparison with a global and varied data set composed of differ-ent species of foraminifera  (Caley and Roche, 2013)  (Figs. 7  and 8 ). Although ecological effects can also play a role and are more expressed when individual species are considered  (Caley and Roche, 2013)  our strategy based on anomaly calculation limits such potential biases. We observe a good qualitative agreement between data and model results (Fig.
Conclusions We used the fully coupled atmosphere-ocean threedimensional model of intermediate complexity iLOVECLIM to simulate the climate and oxygen stable isotopes (δ 18 O) in the atmospheric and oceanic component during the LGM. We also realized a careful compilation of global oxygen isotopic data sets to assess the model performance and constrain the LGM climate. Model results for the annual mean precipitation δ 18 O show more depleted values in the northern and southern high latitudes during the LGM than at present. The simulated spatial gradient in precipitation δ 18 O over Greenland is in very good agreement with ice core records. We observe a general pattern toward more enriched calcite δ 18 O in the model over the continents at the LGM, in agreement with speleothem data. This can be explained by both a general atmospheric cooling in the tropical and subtropical regions and a reduction in precipitation, as confirmed by reconstructions derived from pollens and plant macrofossils  (Bartlein et al.
Acknowledgements. T. Caley is supported by  NWO  through the  VIDI / AC2ME  project no. 864. 09. 013. D. M. Roche  is supported by  NWO  through the  VIDI / AC2ME  project no. 864. 09. 013  and by  CNRS-INSU. Two anonymous reviewers and the editor  André Paul  are acknowledged for useful comments that helped improve the paper. Institut Pierre Simon Laplace  is gratefully acknowledged for hosting the iLOVECLIM model code under the LUDUS framework project (https://forge. ipsl. jussieu. fr/ludus). This is NWO/AC2ME contribution number  04. Edited by:  A. Paul.
e. that the winds above Titan's lakes and seas were too low at the time of the observations to initiate wave formation. Calculations suggest that the threshold wind speed for wave formation under Titan conditions might be between 0. 4 m/s and 0. 8 m/s  [12, 17]. General Circulation Models (GCMs) generally predict that the winds near Titan's north pole should have been rather quiescent until late northern spring, consistent with the low-wind explanation for Titan's lack of waves thus far  [17, 18]. In this paper, we report evidence for waves on Titan's northern sea, Punga Mare. In the 'Observation' section we describe the Cassini Visual and Infrared Mapping Spectrometer (VIMS) data that we interpret to show the waves in specular reflection. We describe our model for simulating the appearance of roughness-driven specular reflections away from the specular point in the 'Model' section.
Ion trap and Orbitrap maximal injection times were set to 50 ms and 500 ms, respectively. Thermo RAW files were imported into Progenesis LC-MS (version 4. 1, Nonlinear Dynamics, Newcastle upon Tyne, UK). Where necessary, technical replicate (repeat injection) runs were time-aligned using default settings and an auto-selected run as a reference. Peaks were picked by the software using default settings and filtered to include only peaks with a charge state between ϩ2 and ϩ6. Peptide intensities of technical replicates were normalized against the reference run by Progenesis LC-MS. Spectral data were transformed to MGF files with Progenesis LC-MS and exported for peptide identification using the Mascot (version 2. 3. 02, Matrix Science, Boston, MA) search engine. Tandem MS data were searched against translated ORFs from the L.
sigmodontis genome and its Wolbachia symbiont, wLs [obtained from http://nematodes. org/genomes/litomosoides_sigmodontis, release nLs 2. 1. 2, 10,246 protein sequences (M. Blaxter, S. Kumar, G. Koutsovoulos; unpublished); and release wLs 2. 0, 1042 protein sequences  (26) ], together with predicted proteomes for the rodent host (Mus musculus, Uniprot release 2012_08, 16,626 protein sequences; and Meriones unguiculatus, Uniprot release 2012_08, 223 protein sequences) and a general contaminant database (GPMDB, cRAP version 2012. 01. 01, 115 protein sequences). Search parameters included a precursor mass tolerance of 10 ppm, a fragment mass tolerance of 0. 5 Da, and allowance for one missed tryptic cleavage. Carbamidomethylation (cysteine) was set as a fixed modification and oxidation (methionine) set as a variable modification.
Mascot search results were further validated using the machine learning algorithm Percolator embedded within Mascot. The Mascot decoy database function was utilized and the false discovery rate was Ͻ1%, whereas individual percolator ion scores Ͼ13 indicated identity or extensive homology (p Ͻ 0. 05). Mascot search results were imported into Progenesis LC-MS as XML files and analyzed according to the following criteria: at least two unique peptides were required for reporting protein identifications, and an individual protein had to be present in Նtwo biological replicates to be included in the ESP data set. Protein abundance was calculated by the iBAQ method; that is, the sum of all peak intensities (from Progenesis output) divided by the number of theoretically observable tryptic peptides  (27).
Protein abundance was normalized by dividing the protein iBAQ value by the summed iBAQ values for the corresponding sample, and the reported abundance is the mean of the biological replicates. Normalized peptide intensities rather than iBAQ values were used to calculate fold-changes between control and biotinylated worm surface preparations. Mass spectrometric data have been deposited in the ProteomeXchange Consortium database (http://proteomecentral. proteomexchange. org) via the PRIDE partner repository  (28)  with the dataset identifier PXD000756 and DOI 10. 6019/PXD000756. In Silico Analyses of Proteins-The domain content of proteins identified in the ESP was assessed using Pfam (v. 27. 0) with the gathering threshold as a cut-off. A hypergeometric test for enrichment of Pfam domains in ESP proteins compared with the complete predicted proteome of L.
sigmodontis was performed using the phyper toolkit within the R programming environment  (29). The Benjamini & Hochberg step-up FDR-controlling procedure was applied to the calculated, adjusted p values  (30). Structural homologs of abundant uncharacterized proteins were identified through comparison to the National Center for Biotechnology Information non-redundant protein database (delta-blast search; E-value cut-off 1 Ϫ03 ) and to the UniProt database (psi-blast search) via the Phyre 2 protein fold recognition server  (31). The conserved domain structure of selected, abundant ESP proteins was also interrogated in InterProScan 4  (32). Venn diagrams were created using vennture  (33) , whereas for heat-maps, hierarchical cluster analysis was performed using the (1 -r) distance metric in gene-e (http://www.
broadinstitute. org/cancer/software/ GENE-E). Prediction of classical N-terminal signal peptides, nonclassical secretion signatures, mitochondrial targeting sequences, O-glycosylation sites, and propeptide cleavage sites was performed using the SignalP 4. 0 server (34), the SecretomeP 2. 0 server  (35) , MitoProt  (36) , the NetOGlyc 4. 0 server (37), and the ProP 1. 0 server  (38) , respectively. Brugia malayi orthologs of L. sigmodontis proteins were determined using reciprocal blast with a bit score cut-off of 50. ShK domains were identified in the complete predicted proteomes of the filariae B. malayi (9), D. immitis  (10) , L. sigmodontis, Onchocerca ochengi, Acanthocheilonema viteae (draft unpublished genomes available at http://www. nematodes. org/genomes/; Blaxter et al. , unpublished), W.
Distribution of Proteins in ESP Across Parasite Lifecycle Stages-We searched ϳ120,000 MS spectra per lifecycle stage against protein sequences predicted from the L. sigmodontis and wLs genome assemblies. A total of 302 quantifiable filarial proteins (i. e. represented by Ն2 unique peptides in Ն2 biological replicates) were detected in ESP across the five lifecycle stages. A majority of these (195 proteins, 64. 6%) were uniquely identified in gAF (Fig. 1 , supplemental Fig. S1 ). Hierarchical clustering of the proteomic profiles clearly separated ESP and WBE (Fig. 2 ). The vL3 ESP data profile was distinct; not only from that of the other ESP preparations, but also from vL3 WBE (Fig. 2 ). The closer clustering of iMf with pgAF ESP rather than gAF ESP was surprising, but may reflect the much lower complexity of the pgAF and iMf ESP datasets.
sigmodontis. The greatest fold-enrichment scores were observed in the AM ESP, which contained three proteins with a major sperm protein (MSP) fiber protein 2b (MFP2b) domain and 10 proteins with the TTL family domain, "DUF290" (Fig. 3 ). The TTL family was also overrepresented in iMf (seven proteins) and pgAF (nine proteins). Notably, pgAF exhibited significant enrichment for intermediate filament and lamin-tail domains (three members each). The ESP from gAF was enriched for lamin-tail and immunoglobulin I-set domains, as well as two proteasome and two laminin families (Fig. 3 ). To evaluate specifically the propensity of individual proteins to be enriched in ESP relative to WBE, we plotted iBAQ values from the ESP datasets against the WBE datasets for each lifecycle stage. Overall, iMf, AM and pgAF secreted a greater proportion of proteins with relatively low abundance in WBE than did vL3 and gAF (Fig.
Abundant Proteins Released by Larval Parasites-Characterization of ESP from the bMf stage posed special challenges. Despite the two-stage purification process and prolonged culture in vitro, 92. 4% (61 of 66) of proteins robustly quantified in bMf ESP were derived from the rodent host (supplemental Table  S4 ). To characterize Mf-derived ESP in more depth, we harvested iMf from gAF cultures in vitro, separated them from the female nematodes, and proceeded with in vitro incubation. This procedure increased the detection of proteins of nematode origin to 36 (supplemental Fig. S2B ), although as expected, the dominant proteins in iMf ESP closely mirrored the profile of gAF ESP (Fig. 5B ). The vL3 ESP was the least diverse dataset in our study, and was composed largely of previously characterized filarial proteins that are known to be uniquely expressed or enriched in this stage (supplemental Fig.
immitis-The ESP from several lifecycle stages of B. malayi have been described previously  (14, 16, 17) , but the only common stage between these studies was adults [with both sexes cultured together in  (14) ]. Of 297 proteins identified in adult L. sigmodontis ESP, 86. 9% had an ortholog in the B. malayi genome; however, the majority (159) were not observed in the B. malayi secretome (Fig. 7A ). Analysis of Pfam domains failed to indicate any significant enrichment in this unique dataset (data not shown). Conversely, although each B. malayi study revealed a surprising number of laboratoryspecific secreted proteins, orthologs of the proteins reported in all three B. malayi secretomes were also detected in adult L. sigmodontis ESP (Fig. 7A ). This common core included leucyl aminopeptidase, enolase, triosephosphate isomerase, ␤-galactoside-binding protein 1, acetylcholine receptor protein, cyclophilin-5, and macrophage migration inhibitory factor-1.
Importantly, most of the proteins identified in the common core between L. sigmodontis and B. malayi were also present within the set shared by L. sigmodontis and D. immitis, although the latter included a greater number (nine) of TTL family members. Moreover, the abundant L. sigmodontis gAF ESP components that were absent or apparently scarce in the B. malayi datasets (uncharacterized protein nLs_03577, vitellogenin nLs_07321, and the VWD protein nLs_08836) were not detected in D. immitis ESP (supplemental Table  S1 ). As reported by Geary et al. (75) , D. immitis ESP contained several proteins that might be associated with the release of microvesicles, including exocyst complex component-2, ␣-actinin, RhoGAP domain-containing proteins, and several transcription factors. Orthologs of these proteins were not detected.
2005; Dejardin et al. 2005; Blastyak et al. 2006). While occupancy over motifs for these factors is occasionally seen, it is less common genome-wide. Together with the recovery of factor motifs by Polycomb N-ChIP, these results imply that Polycomb may be anchored to PREs through interactions with a specific set of transcription factors, including ADF1. We noted that highly occupied sites within PREs often have closely juxtaposed motifs for multiple factors. Individual DNA fragments detected by MNase-seq data suggest that these sites are simultaneously occupied. We focused on the bxd PRE within the BX-C as an example. The functional core of the bxd PRE has been genetically defined  (Sipos et al. 2007; Kozma et al. 2008 ) and coincides with a highly protected 70-bp segment in MNase-seq data (Fig.
In contrast, TRL and PHO are associated predominantly with overlapping fragments 60-100 bp in length, suggesting that multiple factors bind together on these longer fragments. Although small fragments bound only with ADF1 are detected, this does not necessarily mean that ADF1 is sometimes present alone at the PRE, as smaller fragments may also result from MNase cleavage within a multi-subunit complex. We also note that small fragments detected on the right side of the occupied structure in MNase-seq data are not accounted for in any N-ChIP experiment, implying that an additional factor may bind this site. Finally, as N-ChIP for Polycomb predominantly recovers the larger DNA fragments from the bxd PRE, it appears that Polycomb only stably binds the multifactor complex at the PRE.
We therefore analyzed the recovery of factor-bound fragments in one N-ChIP around called sites of other factors (Fig. 4C ). Midpoint plots around ADF1 sites reveal frequent binding of TRL and PHO. Interestingly, fragments recovered by TRL and PHO N-ChIP tend to be larger (40-80 bp) than the bulk of ADF1-bound sites. Longer fragments are expected from sites where simultaneous binding of multiple factors protects DNA from MNase digest. Similar co-occupancy of longer fragments is apparent at TRL sites and PHO sites, and predominantly with ADF1 in both cases (Fig. 4C ). Thus, at some sites ADF1 promotes the binding of TRL and PHO. Promotion of factor binding by ADF1 is supported by motif analysis of each group of sites. As expected, ADF1 sites called from N-ChIP data display strong enrichment of high-scoring ADF1 motifs (Fig.
ucsc. edu). Previously published MNaseseq data for S2 cells  (Teves and Henikoff 2011)  are available from GEO under accession GSE30755. MNase-seq data for BG3 cells have been deposited with modENCODE (modMine. org), under accession modENCODE_3964. H3K27me3 domains were manually defined in S2 and BG3 cells using modENCODE X-ChIP data for H3K27me3 (S2, modENCODE_298; BG3, modENCODE_297;  Riddle et al. 2011 ) as regions at least 5 kb in length >23 H3K27me3 enrichment. We identified 98 domains in S2 cells and 125 domains in BG3 cells. H3K27me3 domain and domain borders in S2R+ cells were identified from N-ChIP paired-end sequenced data with a calling procedure based on previously described methods  (Li and Zhou 2013). Regions with nucleosome-sized reads (120-160 bp) >23 the genomic average of H3K27me3 N-ChIP signals with gaps <500 bp were designated as H3K27me3 domains, if the regions were at least 5 kb in length.
Motif analysis A window of 650 bp around each N-ChIP called site coordinate was used for motif discovery using MEME  (Bailey et al. 2009). For Polycomb sites, only nonredundant motifs were considered. For ADF1, TRL, and PHO sites, MEME-discovered position weight matrices were compared to existing transcription factor binding motifs in the FlyFactorSurvey database  (Zhu et al. 2011 ) using TOMTOM: Only the best-scoring match (i. e. , the lowest E-value) was considered. Motif instances at individual loci were annotated using FIMO with a threshold of P < 5 3 10 À4 , using the FlyFactorSurvey motif entries together with N-ChIP-discovered motifs.
Acknowledgments We thank  W. Bender  and  J. Kassis  for insightful discussions. We acknowledge  Christine Codomo  for technical assistance. G. A. O. was supported by a  Marie Curie Actions International Outgoing Fellowship (IOF-300710 ) from the  European Union   7th Framework Program ,  Research Executive Agency. This work was supported by the  NIH-NHGRI  modENCODE project ( U01 HG004274 ).
However, it is probable that much of the older data was collected in the 1950:2000 timeframe corresponding to the baseline climate period. As noted in Heap, Culham and Osborne  [17] , the species occurrence data used included data from a low resolution UTM grid that skewed projected biodiversity losses for France  [17]. Consequently, we removed these data and recomputed the ENMs to remove this error source (Figure  1(a) ). From the resulting pool of 4150 species, we extracted probability grids covering just the Iberian Peninsula and Balearics for 3267 Iberian plant species (see Appendix S1 in Supporting Information for a detailed list) under the baseline  and 2020 climate scenarios (Figure  1(b) ). The 3267 studied species represent about 40% of the 8500 Iberian & Balearics flora estimated by Castroviejo  [29]  and each plant species has a known Iberian range principally established from the following sources: Castroviejo  [29] , Casas  [30] , Rivas-Martínez and colleagues  [31] , Euro + Med  [32] , The Plant List [33], Ros and colleagues  [34] , Roskov and colleagues  [35]  & Encyclopedia of Life  [36].
2020 Biodiversity Change Map for Iberian "Protected Areas" A mask representing the 294 Iberian PAs was then prepared using data from the World Database on Protected Areas (http://www. wdpa. org/) and ENMs for the previously defined Iberian plant species were mined to obtain suitable habitat grid cells contained by the polygonal park borders under the baseline climate and near-future climate scenarios (Figure  1(c) ). Suitable habitat was defined by grid cells with values greater or equal to 0. 1 similar to the approach used by Pittman and Brown  [37]. This threshold was consistently applied to all species under both climate scenarios. Morin and Thuiller  [38]  have observed that "at the continental scale, niche-based models have been widely used in the last 10 years to predict the potential impacts of climate change on species distributions all over the world".
As a consequence, meteor detections by military satellites are generally not made public and are eventually lost. After decades of ground-based activities, the times seem now mature to plan the development of a new generation of dedicated, space-based facilities for the detection of meteors. JEM-EUSO is a very good candidate to become the first example of a space mission producing important data for meteor studies, as will be seen in the next Sections. It should also be noted that a very interesting by-product of the observations of meteor-like objects might potentially be the detection of super-heavy exotic particles that could be important components of the so-called dark matter in our Universe. In particular, some neutral strange-quark material particles, called nuclearites, can produce UV emissions which could be comparable to meteor signals.
We estimate that the large aperture of the JEM-EUSO telescope can produce an improvement of about three orders of magnitude over the existing limits for the detection of high-mass nuclearites in only 24 hours of operations. The present paper is organized as follows: in section 2 we summarize some relevant notions concerning meteors. In Section 3 we do the same for nuclearites. In Section 4 we describe in general terms the focal plane assembly of JEM-EUSO, in order to explain the general principles of data acquisition. In Section 5 we describe the body of simulations which have been carried out so far in order to design a reliable strategy for the observations of slow events, primarily meteors. A summary of the obtained results is given in Section 6. In that Section, we focus our attention also on the subject of nuclearites, and we explain why we believe that the general observing strategy designed for the observation of meteors is in principle suitable also for the possible detection of this exotic state of matter.