dataesr/scientific-paragraphs-categorization huggingface dataset:
UARS MLS ozone profiles are recommended from 100 to 0. 22 hPa and are retrieved on the same vertical grid as for Aura MLS v2. 2 O 3 ; the vertical resolution is 3. 5-5 km in the stratosphere and 5-8 km in the mesosphere (Table  1a, b ). Estimated random errors are 0. 2-0. 3 ppmv and typical systematic error estimates (2σ ) are ≈ 6 %, degrading to 15 % (or more) near 68-100 hPa, where some high biases vs. correlative data were noted. The official public distribution location for UARS MLS data is at the NASA GES-DISC Mirador website (see Table  1d  for URL).
3 data are provided on a finer grid and down to 261 hPa, but are not recommended overall over v2. 2 because of larger vertical oscillations in the upper troposphere and lower stratosphere (UTLS) at low latitudes (Table  1a ). Aura MLS v2. 2 single profiles are recommended for scientific use in the 215 hPa to 0. 02 hPa range; the vertical resolution is ≈ 3 km (or slightly less) in the stratosphere, degrading to 4-6 km for pressures of 0. 1 hPa or less (Table  1b ). Estimated random errors are 0. 1 to 0. 3 ppmv (≈ 2-15 %) and systematic error estimates (2σ ) are 5-10 % for most of the stratosphere and lower mesosphere (for more details and validation, see  Froidevaux et al. , 2008, and references therein). The official public distribution location for Aura MLS data is at the NASA GES-DISC Mirador website (see Table  1d  for URL).
The GMTR algorithm has been used to analyze the full MIPAS mission and the results are stored into the MIPAS2D database  (Dinelli et al. , 2010 (Dinelli et al. , , 2012)). All these algorithms use the same level-1b data, which is provided by ESA, but differ in some assumptions for the forward model and for the spectral intervals used in the analysis  (Laeng et al. , 2014; Raspollini et al. , 2013a). Recently the full validation of the ozone products of the four cited algorithms  (Laeng et al. , 2014) , an assessment of the long-term stability, and an assessment of the 10 year trend of the IMK/IAA data product  (Eckert et al. , 2014)  have been completed. Overall uncertainties on the ozone profiles range from 35-40 % at 10 km to 8-11 % at around 30 km. Vertical resolution for optimized resolution phase (years 2005-2012) ranges from 2-2.
4 km at 10 km and 3. 2-3. 6 km at 30 km to 5 km at 70 km. Vertical resolution for full resolution phase  (years 2002-2004)  ranges from 4 km around 10 km to 5 km around 30 km, to 8 km at 70 km (Table  1b ). In order to avoid artifacts in trend estimation from two data subsets of different characteristics resulting from the different measurement modes before and after 2004, a dedicated scheme has been developed that is immune to biases between data subsets  (von Clarmann et al. , 2010). The IMK/IAA MIPAS data are accessible at the IMK webpage (see Table  1d  for URL). The ESA MIPAS data are accessible at the ESA webpage (see Table  1d  for URL). The MIPAS2D database is undergoing a validation process  (Casadio et al. , 2013) , but the data is accessible through the ISAC-CNR web site (see Table  1d  for URL).
Acknowledgements. We would like to thank the different agencies that support missions with instruments that measure stratospheric ozone profiles (ESA,  NASA ,  NOAA ,  JAXA ,  NICT ,  CSA ,  SNSB ,  CNES ,  NSO ,  NIES ,  MOE , Eumetsat). We also would like to thank the different national and international agencies that fund groundbased measurements and several databases where ground-based measurements are stored and made accessible (NDACC, WOUDC, SHADOZ). The atmospheric chemistry experiment (ACE) is a Canadian-led mission mainly supported by the  Canadian Space Agency and the Natural Sciences and Engineering Research Council of Canada. SCIAMACHY is jointly funded by  Germany , the  Netherlands  and  Belgium. Work at the  Jet Propulsion Laboratory  was performed under contract with the  National Aeronautics and Space Administration.
Scoring neuronal degeneration and image acquisition For semi-quantitative analyses of 6-OHDA-induced degeneration, worms were examined using a Leica fluorescent dissecting microscope. The absence of all eight dopaminergic neurons in worms was scored as ''complete loss. '' The presence of a complete, intact set of eight dopaminergic neurons was scored as ''no loss. '' Any intermediate situation, for example a damaged or absent subset of dopaminergic neurons or missing dendrite portions, was scored as a ''partial loss. '' Neurodegeneration resulting from cat-2 overexpression was scored using developmentally synchronized worms, as indicated. A DeltaVision microscope (Applied Precision) was used to acquire images. All images were analyzed using softWoRx Suite and softWoRx Explorer software (Applied Precision).
Acknowledgments We are grateful to  Miratul Muqit ,  Jean-Louise Bessereau  and  David Balfour  for critical comments. We also thank  Gartner laboratory members , especially  Bettina Meier  for her technical assistance, and members of  John Rouse's laboratory  for their help and for sharing materials for Y2H analysis and cell culture maintenance. We are also grateful to  Marek Gierlinski ,  Bettina Meier  and  Gregory Minevich  for their advice on statistical analysis. We thank  Shohei Mitani  and the  Japanese National Bioresource Project for the Nematode , the  Million Mutation Project  and the  Caenorhabditis Genome Consortium (CGC)  for providing and distributing tsp-17 alleles.
The low amount of 'background interaction', that is, chimeric religation events between restriction fragments belonging to different species, in the experiment incited us to test whether the genomes of these three bacterial species could be directly assembled de novo from the meta3C data by taking advantage of the presence of ∼80% 'regular' paired-end reads in the library. This relatively high percentage results from the fact that, unlike the Hi-C protocol  (Lieberman-Aiden et al. , 2009) , meta3C does not involve an enrichment step for religated fragments ('Materials and methods'). Using the assembly program IDBA-UD  (Peng et al. , 2012) , a set of 2,436 contigs was generated from the 3C read pairs (N50 = 55 kb, total length 12. 5 Mb). The quality of these contigs was assessed by comparing them with published reference genomes, which showed that the assembled contigs covered respectively 96%, 98%, and 93% of the V.
To test the potential of using meta3C reads for assembling de novo such a complex mix of yeast genomes, we assembled them using IDBA-UD (N50 = 6,914 bp, total length 138 Mb). The breadth of coverage of the 11 genomes by the resulting contigs ranged from 89. 8% (Candida albicans) to 98. 3% (N. castellii), with chimeric contigs (misassemblies) representing ∼20% of the total (37 Mb). This high percentage of chimera contrasted with the very low level of misassemblies observed previously for the mix of three bacterial genomes. To monitor the influence of chimeric pairs of reads (originating from intergenomic 3D contacts) on the generation of chimeric contigs, we performed an assembly on the same library using the Velvet software that considers all reads as independents (i. e. , without pairing them;  Zerbino and Birney, 2008).
A de novo assembly followed by scaffolding using our dedicated program GRAAL (Marie-Nelly et al. , 2014a) was then applied to the pool of contigs identified as belonging to the genome of N. castellii, for which a high-quality reference sequence was available (Figure  2E ;  Gordon et al. , 2011). Since this algorithm involves a splitting procedure of the contigs into restriction fragments, chimeric contigs were broken into nonchimeric parts thereby correcting the assembly errors mentioned above. After processing, 11 superscaffolds were recovered, with the reordered contact map presenting the typical co-localized centromeres regions expected from the Rabl configuration (Figure  2E ; Animation 10). Overall these 11 scaffolds covered 94. 5% of the reference sequence of the 10 chromosomes (chromosome 3 was split into two scaffolds because of the presence of the large, unassembled rDNA array on this chromosome), illustrating the ability of this de novo analysis to correctly assemble and scaffold unknown genomes (see Figure  2 -figure supplement 3).
Research article The following figure supplement is available for figure  3 :. Flowchart representing the computational analysis steps of a meta3C experiment. First, the reads from the sequenced meta3C library are assembled into contigs. The meta3C contact information between the contigs is then used to generate a network of the contacts of all contigs against each other. This contact network is searched for so-called 'communities' (by analogy with social network analysis) using the Louvain algorithm. The significant communities can be annotated by NCBI and correspond principally to sequences from individual species. Ultimately, the contact information can be used to reorder the DNA segments within each community and thus generate the 3D contact map of the corresponding species. In this process contigs can be reassembled by software such as GRAAL, thereby decreasing the percentage of chimeric fragments in the assembly and improving its continuity.
Processing of PE reads The raw data from each 3C experiment were processed as follow: first, reads were demultiplexed using the small tag present at the beginning of each sequence (contained in the custom-made adapters). Then, PCR duplicates were collapsed using the six Ns present on each adapter (Table  1 ). Reads from the raw data used in the present study were aligned using Bowtie 2 in its most sensitive mode  (Langmead and Salzberg, 2012). We used an iterative alignment procedure similar to  Imakaev et al. (2012) , that is, only the first 20 base pairs of the read were initially mapped then the length of the read was progressively increased until the mapping became unambiguous (with a mapping quality superior to 40). Paired reads were aligned independently. Indexes were built in one step and included the genome sequences of all the different organisms.
Generation of contact maps Each mapped read was assigned to a restriction fragment. The matrices were then binned into units of 10 or 200 fragments, resulting in 4292 × 4292 or 2229 × 2229 matrices for the mixtures of three bacteria and 11 yeasts, respectively. Matrices were normalized using the sequential component normalization procedure (SCN) described in  Cournac et al. (2012) , similar to the iterative normalization procedure described in  Imakaev et al. (2012). The SCN procedure ensures that the sum over the column and lines of the matrix equals 1, which reduces the biases inherent to the protocol. Full resolution contact maps are available for bacteria, yeasts, and the environmental sample on the Dryad Digital Repository: http://dx. doi. org/10. 5061/dryad. gv595 (Marbouty et al. , 2014).
Genome assembly Reads containing undetermined bases were removed before the assembly step to retain only goodquality reads. De novo assemblies were then performed using the program IDBA-UB  (Peng et al. , 2012)  with the pre-correction option and default parameters. Quantitative analysis of the meta3C library assemblies Bacterial meta3C assembly 4,040,422 reads were used for assembling the mixture of three bacterial genomes, yielding 2,436 contigs (303 > 5 kb, N50 = 55 kb, total length 12. 5 Mb). More than 95% (∼3,880,000) of the initial reads mapped on the contigs. These contigs were mapped against the reference genomes of the different bacteria using BLAT  (Kent, 2002). Analyzing the output revealed that 30 and 14 of these contigs covered 96. 0% (2,957,563 bp) and 96. 1% (1,071,728 bp) of chromosomes 1 and 2 of V.
For yeast, contigs were left aside, representing in total ∼2% of the number of reads. For the river sediment experiment, ∼15% of the contigs were left aside at the binning step. The contigs in each bin resulting from the 3D binning were characterized using BLAST to determine the dominant species. GRAAL scaffolding of the N. castellii and S. bayanus genomes The program GRAAL (for Genome (Re)-Assembly Assessing Likelihood from 3D) aims at improving incomplete genome assemblies through the probabilistic exploitation of the physical contacts endured by chromosomes within a cellular compartment  (Marie-Nelly et al. , 2014a). The program only needs two datasets for initialization: a set of contigs and a 3C/HiC dataset. Upon initialization and depending on the depth of the HiC dataset, the software splits the contigs into smaller pieces/bins encompassing at least 2 restriction fragments.
The entire program and full source code are freely available online here: https://github. com/ koszullab/GRAAL as well as on the website of RK laboratory. The description of the program and its application are presented in  Marie-Nelly et al. (2014a). We used GRAAL to reassemble the 2,060 contigs (N50 = 16,764 bp) contained in the S. bayanus community identified by the Louvain algorithm. The resulting scaffolding showed a large improvement for all assembly parameters. The N50 length now reached 190,514 bp, and 77% of the total length of the assembly was assembled into regions larger than 50 kb (as compared to 3% before running the software). The result was even more spectacular for N. castellii (probably due to its higher coverage in the meta3C library): after running GRAAL on the 999 contigs (N50 = 27,452 bp) in the community delineated by the Louvain algorithm, N50 length reached 792,652 bp, and 96% of the assembled data was in scaffolds larger than 50 kb (with 11 scaffolds covering 95% of the 10 chromosomes).
Data visualization For general visualization of the meta3C assembly data we used force-directed graph-drawing algorithms. This class of algorithms positions the nodes of a graph by assigning forces among the set of edges according to weighted interactions between the nodes. In our case, the 3C contacts dictated the strength of interactions between nodes. These layouts allowed us to visualize conveniently large clusters of nodes that were subsequently confirmed by the use of the Louvain algorithm. All graphs were visualized using the network software Gephi  (Bastian et al. , 2009; Martin et al. , 2011). Contigs longer than 2. 5 kbp were divided into equal-sized chunks corresponding to several nodes in the graph (to 'normalize' the appearance of the clusters, since otherwise every contig, whatever its size, would be represented by a single point).
Figure4. Flowchart representing the computational analysis steps of a meta3C experiment. First, the reads from the sequenced meta3C library are assembled into contigs. The meta3C contact information between the contigs is then used to generate a network of the contacts of all contigs against each other. This contact network is searched for so-called 'communities' (by analogy with social network analysis) using the Louvain algorithm. The significant communities can be annotated by NCBI and correspond principally to sequences from individual species. Ultimately, the contact information can be used to reorder the DNA segments within each community and thus generate the 3D contact map of the corresponding species. In this process contigs can be reassembled by software such as GRAAL, thereby decreasing the percentage of chimeric fragments in the assembly and improving its continuity.
Acknowledgements We thank  Jean-Yves Coppée ,  Caroline Proux , and  Laurence Ma  from the  Génopole at Institut Pasteur  for technical assistance with Illumina sequencing. Thanks also to  Nienke Buddelmeijer  and  Didier Mazel  for providing us the B. subtilis and V. cholerae strains and to  Frédéric Boccard ,  Olivier Espeli ,  Didier Mazel ,  Marcelo Nollmann , and  Marie-Eve Val  for their constructive comments on the results. We are grateful to  Agnès Thierry  for providing us the yeast strains and for helping us with pulse-field electrophoresis and hybridization of the plasmid F' and the E. coli genome. We are also grateful to  Olivier Jaillon  and to our colleagues from the group Régulation spatiale des génomes for useful comments and discussions. Parts of the computational analyses were performed on the computing cluster of the  Gesellschaft für Wissenschaftliche Datenverarbeitung mbH Göttingen (GWDG).
, 2013). Combining data sets with well-characterised sensitivity and uncertainty estimates can potentially provide the means to generate a consistent long-term record of tropospheric ozone that could be used in chemical composition and climate applications. In addition to the IASI instruments on MetOp-A and -B, an identical instrument will fly on the MetOp-C satellite, due to launch in 2017/18. Furthermore, EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) is currently preparing the next polar-orbiting programme with the Metop Second Generation (SG) satellite series that should be launched around 2020. In this framework, studies are underway for the concept of a new instrument, the IASI-New Generation (IASI-NG), characterised by an improvement of both spectral resolution and radiometric characteristics as compared to IASI  (Clerbaux and Crevoisier, 2013).
The IASI/IASI-NG data record is therefore of particular interest in the context of quantifying long-term changes in tropospheric ozone. In addition, the IASI instruments, unlike TES, provide swath coverage, allowing near-coincident observations of the atmospheric state and enabling comparison between predicted and actual retrieval errors. In this work, we apply the TES ozone retrieval algorithm to radiances from IASI on MetOp-A as a first step towards the goal of creating a consistent long-term record of tropospheric ozone from multiple TIR instruments (while this study is concerned with TES and IASI, instruments such as AIRS and CrIS also have potential to contribute information to such a record). This study concentrates on mid-latitudes in 2008 in order to facilitate comparison of our results with other IASI ozone retrievals as presented in the study by  Dufour et al.
(2012). The focus of this study is the characterisation and validation of the error estimates on the ozone retrievals produced with this algorithm. Section 2 gives the technical details of the IASI instrument. In Sect. 3, a summary of existing IASI ozone retrievals is given, while Sect. 4 describes the retrieval of ozone profiles with optimal estimation theory and the theoretical tools for the characterisation of the profiles used in this study. In Sect. 5, an overview of the different reference data sets for validation is provided, followed by the results in Sect. 6.
There are 30 scans per swath. These 30 individual effective fields of view (EFOVs) are made up of four instantaneous fields of view (IFOVs) arranged in a 2 × 2 pixel matrix resulting in 120 measurements per scan line. The surface footprint of a nadir IFOV is circular, of 12 km diameter. Towards the edge of the swaths, the IFOVs are elliptically elongated to a footprint of 20 km × 39 km. A swath spans 2200 km in width. Global coverage is achieved twice daily. IASI data are processed operationally by EUMETSAT. We obtained IASI Level 1c radiances (geolocated, calibrated, and apodised radiance spectra) via the National Oceanographic and Atmospheric Administration (NOAA) Comprehensive Large Array-data Stewardship System (CLASS). EUMETSAT produces operational retrievals of column in-tegrated ozone, carbon monoxide, nitrous oxide, methane, carbon dioxide, three partial columns of ozone (between the surface and 6, 12, and 16 km altitude), surface temperature, cloud information, and profiles for temperature and water vapour.
Existing IASI ozone data products A number of different groups have previously developed ozone retrieval algorithms for IASI. Operational processing of IASI ozone data for the Level 2 product is done by EU-METSAT with a neural network based approach  (Schlüssel et al. , 2005; August et al. , 2012)  and by the Center for Satellite Applications and Research (STAR), part of the NOAA Satellite and Information Service (NESDIS), with an iterative regularised least squares minimisation algorithm  (Bian et al. , 2007; Pittman et al. , 2009). At LAT-MOS/ULB (Laboratoire Atmosphères, Milieux, Observations Spatiales/Université Libre de Bruxelles), the FORLI (Fast Operational Retrievals on Layers for IASI) algorithm uses an optimal estimation approach  (Hurtmans et al. , 2012). In the future FORLI ozone profiles will be distributed by EUMETSAT with the Level 2 product.
Retrieval input The TES forward model is described in  Clough et al. (2006). Calculations of radiances and Jacobians are performed using a fixed pressure grid of 66 levels. The absorption parameters used in the forward model are pre-calculated using the Line-By-Line Radiative Transfer Model (LBLRTM)  (Clough et al. , 2005)  and the TES_v1. 4 line parameter database (http: //rtweb. aer. com). As mentioned above, the IASI Level 1c radiances are obtained from NOAA CLASS. The measurement noise covariance matrix S ε is a diagonal matrix with the diagonal elements set according to the noise-equivalent spectral radiance (NESR). The NESR in the TIR ozone band around 9. 6 µm has been estimated at 20 nW (cm 2 sr cm -1 ) -1 from a set of representative spectra measured in orbit  (Clerbaux et al. , 2009).
Validation data and selection criteria We have validated the IASI-TOE ozone retrievals against independent measurements from ozone sondes for midlatitudes in 2008. In addition to quantifying the overall bias relative to the sondes, we have focused here on validating the error estimates obtained from the optimal estimation framework. There are three key empirical methods helping to quantify the actual errors of a retrieval: (a) determining the bias of the retrieved profiles with respect to independent measurements, here ozone sondes, (b) determining the root-meansquare (rms) deviation of the IASI profiles with respect to the sonde profiles, and (c) determining the range of the deviation from a mean of an ensemble of quasi-coinciding retrieved profiles, i. e. calculating the so-called sample covariance matrix.
Ozone sondes Ozone sonde profiles have been obtained from the World Ozone and Ultraviolet Data Centre (WOUDC, www. woudc. org) and from the Global Monitoring Division of NOAA (www. esrl. noaa. gov/gmd). The theoretical uncertainty of electrochemical concentration cell (ECC) sondes for a typical mid-latitude ozone profile peaks at the ozone minimum (about 13 km) at about 9 % (WMO, 2011). However, the absolute uncertainty depends on various factors, e. g. the concentration of the potassium iodide solution and the sonde preparation. Through laboratory studies for precision of the sondes as well as comparisons to UV-photometer ozone measurements, the accuracy is estimated to be 10 % or better for ECC sondes and 13 % or better for Brewer-Mast type sondes (only at Hohenpeißenberg) for the altitude range considered in the IASI-TOE comparison (WMO, 2011).
FORLI A detailed description of the FORLI algorithm can be found in  Hurtmans et al. (2012). Briefly, ozone profiles are retrieved on a constant height grid with 1 km thick layers from the surface to 40 km altitude. The absorbance cross-sections are pre-calculated from the HITRAN database  (Rothman et al. , 2005). The spectral range is 1025-1075 cm -1. Only one global ozone a priori profile and corresponding covariance matrix are used for all seasons. Just like for TOE, FORLI utilises the operational Level 2 temperatures and the water vapour profiles as input as well as the emissivity climatology by  Zhou et al. (2011). Also, TOE and FORLI use the same value for the diagonal of the measurement noise covariance matrix, i. e. 20 nW (cm 2 sr cm -1 ) -1  (Clerbaux et al. , 2009). IASI-FORLI ozone profiles were selected around the ozone sounding location with the same selection criteria as for IASI-TOE (although actual ozone sonde measurements were not included in this comparison).