dataesr/scientific-paragraphs-categorization huggingface dataset:
Flux measurements and data processing All four-study sites adhered to the protocols of the CarboEurope network  (Aubinet et al. , 2000; www. carboeurope. org) and the data processing schemes of Fluxnet  (Papale et al. , 2006; Reichstein et al. , 2005; Moffat et al. , 2007). The EC setup includes a meteorological tower equipped with an EC system to measure the net exchanges of CO 2 , H 2 O and energy between the ecosystem and the atmosphere  (Aubinet et al. , 2000). Atmospheric fluxes of water vapor (latent heat, LE, further this is called actual evapotranspiration and abbreviated as E) and net ecosystem exchange of CO 2 (NEE) were measured using the eddy covariance (EC) technique. The Lochristi experimental site was installed in 2010, and EC measurements were made according to the same methodology.
, 1980)  for density fluctuations of the open-path CO 2 analyzer data and the Schotanus correction for the sonic temperature,  (Schotanus et al. , 1983). Meteorological data were continuously recorded with automatic weather stations. Gap filling and NEE partitioning in gross primary production (GPP) and total ecosystem respiration (TER) were made using the online software Eddyproc (2010) (http://gaia. agraria. unitus. it/. database/eddyproc/EddyInputForm. html) according to the methodology proposed by  Reichstein et al. (2005). The same gap filling procedure was applied to the data from all four sites. The footprint analyses for the three CarboEurope sites were described in  Göckede et al. (2008). The analysis of  Göckede et al. (2008)  addressed the spatial representativeness of the flux measurements, the instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method.
Acknowledgments Research at the Brasschaat and the Pueachabon sites was financially supported by the Fifth (CARBOEUROFLUX, contract # EVKL-CT-1999 ) Sixth (CARBO-EUROPE IP, contract # GOCE- CT-2003-505572 ) and Seventh (GHG-Europe, contract # 244122 ) Framework Programs of the  European Commission (EC). Research at the Lochristi site has received funding from the  European Research Council  as  ERC  Advanced Grant agreement # 233366  (POPFULL) and from a  Marie Curie International Reintegration Grant (IRG)  as grant agreement # 268257  under the  EC's Seventh Framework Program  (FP7/2007-2013). Further funding was provided by the  Flemish Hercules Foundation  as Infrastructure contract # ZW09-06 , by the  Flemish Methusalem Program  and by the  Research Council of the University of Antwerp.
Back Close Full In Sect. 2, the CALIOP/CALIPSO, MODIS/Aqua and POLDER3/PARASOL data are presented, and algorithms, theoretical basis, and main characteristics are summarized. Comparison methodology of CDNC between CALIOP and MODIS and the corresponding results are given in Sect. 3. Impacts of cloud entrainment/drizzling, horizontal heterogeneity, and r e are discussed in Sect. 4, and conclusions are drawn in Sect. 5.
Data and algorithms In our study, collocated data from official level 2 CALIOP/CALIPSO, MODIS/Aqua and POLDER3/PARASOL products extracted along the CALIOP track (CALTRACK data from ICARE Data and Service Centre, Zeng, 2011) are being considered for the period from November 2007 to December 2008. We provide hereafter a brief summary of the CDNC products used and the algorithm theoretical basis used for their retrievals.
Figs. 1 and 2, which indicate, despite using very different techniques for the retrievals, that CDNCs derived from the two sensors are quite similar with the MODIS values larger than the CALIOP ones. Although it is still hard to determine at this stage which sensor represents the most accurate CDNC values, their spatial and seasonal distributions can at least be observed consistently from both datasets. This allows us to quantitatively determine regions of highest CDNC compared to others.
Acknowledgements. M. K. thanks the  University of Tokyo (AORI)  for giving her the opportunity to start this work during her stay at AORI as invited professor in November 2010-January 2011. This work was then expanded and discussed following a number of conferences, in particular the INTIMATE workshop on deglaciation held in Copenhagen in November 2011. This work was also developed for the  ERC   TracSymbols  project (FP7/2007-2013)/ ERC  grant agreement no. 249587 ). U. M. received funding through the  DFG-Research Center/Excellence Cluster  "The Ocean in the Earth System". A. A. acknowledges the support by the  Environment Research and Technology Development Fund  ( S-10 ) of the  Ministry of the Environment, Japan. G. L. and X. Z. received funding through the  Helmholtz programmes PACES  and REKLIM.
Acknowledgements. The authors thank  Dr. G. Dubreuil ,  Centre International de Recherche Medicale de Franceville, Gabon , for making the rodents available. Dr E. P. Hoberg ,  USNPC, Beltsville , and  Dr F. Moravec ,  Institute of Parasitology, Academy of Sciences of the Czech Republic , C ˇeskeBude ˇjovice, are thanked for the loan of specimens. Notes by  Kerstin Junker: Sadly ,  Dr Odile Bain  passed away on October 16, 2012, shortly after having finalized the manuscript for this paper. I would like to acknowledge her for her unsurpassed expertise in her chosen field of study and for having been such an encouraging and inspiring colleague, friend and mentor, who could not have been more generous and less self-serving in sharing her vast knowledge and skills.
Data selection Local installations of the MySQL Ensembl databases version 49 and the relative API  (34)  were used to extract sequences and annotations from the next Olfactores genomes: Mus musculus, Homo sapiens, Canis familiaris, Danio rerio, Takifugu rubripes, Gasterosteus aculeatus, Oryzias latipes, Ciona intestinalis, Ciona savignyi (see Supplementary Table  S1  for information about the used Ensembl core databases and the relative genome builds). Species were divided into three groups according to their phylogenetic classification: mammals, fishes and tunicates. For each group, a representative organism was chosen and its sequences used as the reference genome in VISTA analysis as well as in inter-group analysis. The representative organisms are M. musculus, T. rubripes and C. intestinalis for mammals, fishes and tunicates, respectively.
The selection of genes was conducted in each group independently. Basically, using the annotation from Ensembl Compara  (35)  we selected all the genes containing an homolog classified as ortholog_one2one inside all the species of the group, which led us to collect 14 201, 12 896, 5786 groups of orthologous genes loci for mammals, fishes and tunicates, respectively. For each gene, we extracted the whole genomic repeat-masked sequence containing the transcriptional unit and the flanking sequences up to the preceding and following gene. If there were nested genes present in the locus, they were not taken into consideration to determine the extent of sequence to analyze. The regions were extracted from Ensembl and the 5 0 -3 0 sequence of the locus was stored in a custom database having always the determining gene on the positive strand.
Identification of rCNEs To define regionally conserved non-coding elements (rCNEs), analyses were conducted independently in each collection of orthologous genes for each group. Global multiple alignments in each group were performed on each collection of homologous genes using MLAGAN  (37)  with default parameters. The multiple alignments thus obtained were parsed using VISTA  (38)  and perl scripts with the next parameters according to the following groups: Mammals and fishes: sliding 20 bp; minimum length 100 bp; minimum identity 80%; minimum length after three species overlap 100 bp. Tunicate: sliding 20 bp; minimum length 100 bp; minimum identity 60%. Resulting conserved regions were then filtered stringently to distinguish 'known genic' (having evidence of transcription) from 'non-genic' (not having evidence of transcription) into Ensembl and to discard redundant sequences.
Basically, all the conserved sequences were screened against the annotations of overlapping complementary DNAs (cDNAs), proteins, ESTs and predictions from the Ensembl core, other features and eventually cDNAs databases of the reference organisms. In the case of overlap, the elements were considered 'genic' and excluded from the remaining analysis. Finally, in cases in which the upstream region of an analyzed gene coincided with the downstream region of another analyzed gene, rCNEs were counted only once and associated to the locus showing the highest score or the longest transcript in case of equal scores.
Homology analysis We collected all the Ensembl genes mapped in intervals up to 2 Mb (1 Mb upstream and downstream) around each element in every representative genome per group. For each gene, we collected the evolutionary relationship from Ensembl Compara. We took into consideration the following relationship from the database: ortholog_one2one, ortholog_one2many, ortholog_many2many, between_spe-cies_paralog and apparent_ortholog_one2one. For each gene in the interval, we also calculated the number of bystander genes as the number of genes intervening between the gene and the conserved element. We verified within the 1 Mb intervals upstream and downstream of each element, in each pair of species, the presence of evolutionarily related genes as opposed to unrelated genes, taking into account as syntenic conserved oCNEs only those showing a maximum of four bystander genes between the conserved fragment and the closest pair of orthologous genes.
Aniseed annotation integrations The next transcript models and annotations were downloaded from the ANISEED database  (40) : JGI version 1, KYOTOGRAIL2005, KH and ENSEMBL. Data were downloaded from the webpage http://bit. ly/12oO1NL that redirects to the respective archives. Transcript models and annotations were parsed and joined together to form a unique collection, and a MySQL database containing all the information downloaded and generated was used to collect and manage the data using custom perl scripts. Annotations were attached to the data in the pipeline by using the Ensembl transcript ID that represented the ID common to the two sets of data (Ensembl and Aniseed).
oCNEs search in Oikopleura and amphioxus Oikopleura genome assembly version 3 was downloaded at JGI from http://bit. ly/VPjaD7 with relative annotations from http://bit. ly/TYKrTY and proteome from http:// bit. ly/V5Q8yC. Amphioxus genome version 2 was downloaded at JGI from http://bit. ly/12oNxXJ with relative annotations from http://bit. ly/UcbKOg and proteome from http://bit. ly/ZievBL. oCNE multiple alignments containing the sequences of all the analyzed organisms were used to build Hidden Markov Models (HMMs) using the program HMMB from the HMMER tool version 1. 8. 5  (41). The program HMMFS was then used to search the HMMs against the entire Oikopleura and the amphioxus genomes on both strands. A cutoff score of 20 bits was used to determine whether an oCNE was conserved. This score indicates that a selected match is 2 20 -fold more likely to represent an authentic match than to occur by chance.
Ultraconserved elements and enhancer browser data overlap The genomic coordinates of the set of extended ultraconserved elements (UCEs) by Stephen et al. (47)  were kindly provided by John S. Mattick. Overlap analyses were performed between the human coordinates of oCNEs and the coordinates of the 5404 vertebrate UCEs. oCNEs overlapping a UCE for at least 50% of their length were considered to be derived from this family of conserved elements. To analyze the overlap of oCNEs with validated UCEs, we downloaded all the elements found in the enhancer browser database  (48) , together with the functional validation results on 14 November 2012 from http://enhancer. lbl. gov/. The database was composed of 1756 elements. Mouse oCNEs sequences were searched in the downloaded sequences by using Blastn.
eRNAs overlap The genomic coordinates related to intergenic transcribed enhancers (eRNAs) were extracted by the supplementary material associated to the article by Kim et al. (49). The dataset contained 5117 single nucleotide positions related to intergenic enhancers of which 2052 were classified as transcribed and 3065 as non-transcribed. oCNEs and vCNEs were considered to overlap eRNAs if their genomic coordinates were overlapping within a 1. 5-Kb interval upstream/downstream of the eRNA single-nucleotide position.
ENCODE/CSHL Long and Short RNA-seq overlap analysis Human oCNEs sequences were mapped on the hg19 version of the human genome by using the liftOver tool. A custom perl script was then used to query the public instance of the UCSC MySQL database of the human genome version hg19 at the host genome-mysql. cse. ucsc. edu (53). The script queried all the tables pertaining to the ENCODE/CSHL Long and Short RNA-seq data  (54, 55)  publicly available at the moment of the analysis to test for the overlap of the 183 oCNEs human sequences in every sample. The tables analyzed correspond to 182 samples.
Domain analysis We collected all the Ensembl genes mapped in intervals up to 2 Mb upstream and downstream around each element in every representative genome per group. For each gene, we collected the domains composition from the Ensembl core annotations and looked for domains common to all the three groups. The same analysis was executed on a set of randomly sampled genomic regions from the three groups of the same dimension as the oCNEs dataset. To avoid methodological biases, the randomly sampled genomic regions were selected in the next way: vCNEs conserved between mammals and fishes were randomly selected and associated to randomly selected Tunicate rCNEs. We considered three different intervals around the conserved elements (500, 1000 and 2000 Kb) and performed the Fisher exact text comparing the proportion of common domains between the real oCNEs set and the random vCNEs/rCNEs associations for each interval and for each domain.
TFBS analysis oCNEs sequences from M. musculus, T. rubripes and C. intestinalis were analyzed for their composition in transcription factor binding sites. We used the FAMILY collection of matrices from the 2008 version of the Jaspar4 database  (56)  together with the TFBS perl API  (57). A threshold of 80% was used to map binding sites on sequences. To avoid methodological biases, the same TFBS scanning procedure was performed, for each species, on a set of randomly selected regions of the same length and number of oCNEs extracted from the set of vCNEs (mouse ad fugu) or rCNEs (Ciona) and the results compared using the Fisher exact text. P-values were corrected using the Benjamini and Hochberg method. Only binding sites significantly enriched in all the three organisms tested were kept into consideration.
GO analysis We considered the association of the conserved elements to the genes determining the genomic regions selected in the data-selection phase. GO functional enrichment analyses were performed on the set of mouse and Ciona genes associated to oCNEs. For the mouse set, we compared the following: (i) functional annotation of the vCNEs with the mammalian rCNEs; and (ii) functional annotation of the vCNEs with the oCNEs by using DAVID  (58)  and FATIGO  (59). The Ciona GO annotations are not present in the above tools nor in the official GO release; therefore, we extracted them from the Aniseed database  (40). We then compared the set of genes retaining tunicate rCNEs with the set of genes retaining oCNEs. For each class, we used the Fisher exact text and the P-values were corrected using the Benjamini and Hochberg method.
Discovery of mammalian, fish and tunicate conserved non-coding elements (Olfactores CNEs) CNEs between vertebrates and tunicates have never been reported so far  (15). Therefore, we developed a novel highly sensitive, highly stringent, progressive pipeline to be able to identify the presence of vertebrate CNEs in Ciona (see 'Material and Methods' section and Figure  1A ). The pipeline used the following combinations of three groups of genomes: (i) Mammals: M. musculus, H. sapiens, C. familiaris; (ii) Fishes: T. rubripes, G. aculeatus, O. latipes; and (iii) Tunicates: C. intestinalis, C. savignyi. We took into consideration all genes for which there were predicted 1-to-1 orthologs within the Ensembl database  (34)  in all the genomes within each group, which led to the analysis of 14 201, 12 896 and 5786 groups of orthologous loci for mammals, fishes and tunicates, respectively.
We began by selecting elements conserved in a collinear manner within each single group using MLAGAN and VISTA  (38, 60). The results were filtered stringently to discard 'known genic' regions (potentially transcribed regions overlapping annotated genes, proteins, EST and predictions) and eliminating redundancies from 'non-genic' regions. The analysis produced 92 435, 27 145 and 4525 non-redundant, non-genic, collinearly conserved elements in mammals, fish and tunicates, respectively. We will refer to these initial dataset as rCNEs because they are conserved collinearly within each group. We then proceeded to use these data in a multi-step local and multiple alignment strategy to progressively search for conserved elements among groups, allowing non-collinear conservation and using randomization steps to exclusively select significantly conserved regions with a FDR <0.
In vertebrates, the majority of the oCNEs are found directly flanking or overlapping orthologous genes and they are also found in prevalence in large syntenic blocks. Only seven elements in mouse show the presence of one unrelated gene and three are separated by two unrelated genes from their putative target gene. In fugu, three elements show one unrelated gene. Overall, >85% of the elements analyzed contain >1 pair of evolutionarily related genes in the analyzed interval, >50% of the elements contain >5 pairs and $20% contain >10 pairs. We performed the same check comparing the mouse and the Ciona genomes, and no element could be classified as syntenically conserved. To further verify this finding, we manually screened the genes flanking and overlapping (if any) oCNEs after having integrated the automatically verified Ensembl Ciona annotations with the ones downloaded from the Aniseed database  (40).
The curated annotations can be found in Supplementary Table  S6. We noticed that, using the integrated annotations, a single oCNEs from the whole dataset can be considered as syntenic between vertebrates and ascidians. The element is found in an intron of the FoxP1 gene in both groups. The homology relationship between the two genes was not present in the version of the Ensembl database used in the analyses; therefore, it was classified as non-syntenic. We could not find any other missing relationship. We also looked for specific duplication of oCNEs elements to check if duplicated elements could be found close to missing orthologous genes. This analysis allowed us to identify 14 duplicated elements of which three are present in all the vertebrate genomes analyzed, two are only found in mammals, two only in fishes, four exclusively in zebrafish (due to additional duplications of loci containing them) and three only in tunicates (see Supplementary Table  S7 ).
Among the total set of 5786 analyzed Ciona gene loci, 3957 (68%) have an annotated ortholog in the set of fish analyzed loci (4107 in mammals), while of the 121 loci containing oCNEs, 61 (50%) have an annotated ortholog in fish (63 in mammals), but no conservation outside the coding exons could be detected between syntenic vertebrate and tunicate orthologous loci. The difference between the proportions is significant (P = 2. 1e-05, Fisher exact test) suggesting that our results are not a random sampling of the starting dataset. These results indicate that oCNEs are found in regions showing significantly less annotated orthologous genes.
8e-09) pointing out that this is an oCNEs-specific enrichment. It is important to point out that such overlap could also be partially explained by our multi-steps procedure, which progressively selects for the highest conserved segments within each group. However, the usage of stringent parameters in the randomization steps rejects the hypothesis that these elements are conserved merely by chance. Extensive information about the functional validation of UCEs can be found in the enhancer browser  (48). The database is composed of 1756 elements of which 50% (887) resulted to be positive as enhancers at the developmental stage tested. We calculated the overlap of these elements with the set of oCNEs. The results show that 85 out of 183 oCNEs overlap a conserved element tested in the enhancer browser.
Of these, 66%  (56)  resulted to be functional enhancers in mouse. The difference between the two proportions is significant (P = 3. 9E-03) indicating that oCNEs are enriched for elements found to be functional enhancers in mouse at developmental stage 11. 5E. Several studies indicate that enhancers and UCEs can also be transcribed  (49, 70, 71). To verify the possibility that oCNEs could act also at the transcript level, we tested the overlap between them and the published set of transcribed enhancers by Kim et al. (49). They showed that a subset of stimulus-dependent enhancers from mouse cortical neurons also show activity-regulated RNAPII binding, and therefore they are transcribed  (49). The total set of intergenic functional enhancers contains 5117 genomic positions; of these, 2052 are also transcribed and are named eRNAs, while 3065 are not transcribed.
5 (Figure  3C ). Transcription of the three elements in C. intestinalis at the tail-bud stage showed expression of elements E2 and E3 (Figure  3D ). These findings suggest that the identified oCNEs can be expressed during development in Olfactores and that the transcripts are produced at low levels as already shown for eRNA and more generally non-coding RNAs  (49, 72). Overlap analyses of zebrafish oCNEs against recently published dataset of RNA-seq data  (73, 74)  did not give significant results, suggesting that their weak expression levels could need higher depth of sequencing to be detected. To better understand if oCNEs transcripts could be associated to short or long RNAs, we analyzed the overlap of oCNEs with the UCSC human genome browser tracks collecting transcribed contigs from the ENCODE/CHSL RNA-seq data on Long (98 samples, 117 388 194 transcribed contigs) and Short (84 samples, 5 452 981 transcribed contigs) RNAs  (53) (54) (55).
The number of contigs overlapping each element indicates the number of samples in which an oCNEs overlap a transcribed region supporting the putative transcription of the element. Mapping of the oCNEs was compared with the mapping of a similar number of randomly selected elements. The results obtained indicate that 158 oCNEs overlap 4866 RNA contigs from the Long RNA-seq dataset, while 147 random elements overlap 3191 contigs. The difference between the two dataset is significant (P = 2. 5E-77). The average number of samples in which each oCNEs result expressed in the Long RNA-seq dataset is $30, while it is $20 in the random set (Supplementary Figure  S4 ). In the same analysis, using the Short RNA-seq data the oCNEs resulted to map on 18 contigs, while random regions overlap with seven; this difference is not significant (P = 0.
The HTH domain is a common denominator in basal and specific transcription factors from the three superkingdoms of life and is frequently present in homeobox genes  (76). Then, to check if oCNEs may indicate a common conserved regulatory mechanism, we performed a similar analysis focused on transcription factor binding site enrichments taking into account as significant only binding sites significantly enriched in all the groups of organisms. To this aim we used the transcription factor binding matrices from the Jaspar Family database  (56) , which provides generic matrixes for major families of transcription factors. We found common significant enrichments for binding sites recognized by the homeobox (Ciona adjusted P = 1. 0E-13), the high mobility group (HMG; Ciona adjusted P = 4. 3E-05) and the forkhead (Ciona adjusted P = 1.