dataesr/scientific-paragraphs-categorization huggingface dataset:
LASERSCANNING The static laser acquisition has been performed using a 3D Terrestrial Laser Scanner (a LEICA C10 device) with a station every 30 meters along the ledge of the tunnel. The scanning approach is based on a time-of-flight technology. The field-of-view is 360 • by 270 • and the scanning resolution is 1 point every 5 mm at a distance of 12 m. A scan records 90 millions of points at every station and lasts 40 minutes (see Fig. 5 ). We adopt, at least, a 30% overlap between two adjacent scans in order to facilitate scan strips registration  (Bornaz et al. , 2003). 15 stations are necessary to collect the laser data of the entire tunnel (1. 5 billion points). Data post-processing consists in building a global terrestrial reference model of the tunnel from different point clouds. In this work, we have chosen a two-step approach.
This approach aims at computing an optimal model of a scene from multiple views, by minimizing a quadratic error between actual positions of points in an image and predicted positions obtained by back-projection. Note that this classical technique is a non-linear optimization problem that jointly minimizes the errors in all views  (Szeliski, 2010). The algorithm is applied to a set of corresponding points that can be identified in several images. These points are called targets or visual marks, that have been previously georeferenced. These control points are also employed to enforce the model to be straight, to match the actual geometry of the tunnel: without these points, the model tends to be curved, due to local error accumulations. The photogrammetric 3D model of the tunnel was created with the commercial software PhotoModelerScanner (PMS).
RESULTS AND DISCUSSION The accuracy assessment has been performed on five datasets. The number of points for each dataset is given in Tab. 1. The first two datasets have been built to evaluate accuracy using the pointto-point approach. Dataset 1 is employed to check the accuracy of the TLS point cloud by comparing it to georeferenced points. The six points corresponds to the Leica Geosystems spherical targets, surveyed both by TLS and tacheometry, and regularly spaced along the tunnel. The results give a maximum difference equal to 1. 7cm that ensures the reliability and the good dispersion of the lasergrammetric model. Therefore, the TLS model can be considered as a reference. Dataset 2 is created by taking 2 points on each of 51 metallic angle brackets scattered all along the tunnel. The comparison refers to the photogrammetric and TLS model.
We determine an accuracy as the maximum distance between the two models. The obtained value is 4 cm, which seems very promising. The last three datasets have been constituted to evaluate accuracy  between pairs of point clouds with large and different sizes, using cloud-to-mesh or cloud-to-cloud method. Datasets 3 and 4 are two successive portions of the tunnel starting from its entrance. Note that in dataset 5, the lasergrammetric point cloud has been resampled as explained in Sect. 4. 1. This last dataset, describing the whole 475 meters of the tunnel, presents high disparities in cloud density. It may be noticed that these three datasets correspond to the rightmost half-vault of the tunnel as the photogrammetric model has only been implemented on this part. The results of the cloud-to-mesh approach are shown in Tab.
2. The 3 accuracies, comprised in the range [4. 1cm, 5. 8cm], are homogenous and analogous to the accuracy observed for dataset 2. However, it may be observed that dataset 5 gives an accuracy which is fairly lower than for the two others. This difference can be explained by the resampling and the fact that the whole tunnel was considered. In the cloud-to-cloud approach, two parameters have to be evaluated: the octree subdivision level and the accuracy measurement. In theory, the choice of the octree subdivision has no impact on the distance computation between clouds. Actually, we observe some accuracy variations according to the subdivision level, but the results are globally homogenous (see Tab. 3). Further investi-  gations should be necessary to explain these differences. For the moment, we have chosen, a number of 7 octree levels, since it is the least time consuming.
The evaluation on the datasets 3-5, taking the laser model as reference, (Tab. 4) shows that the accuracy of the photogrammetric model spans the range 4. 1 cm -5. 5 cm. We observe that the tunnel can be quite accurately reconstructed with a photogrammetric model. It may be observed that, for equivalent results, the computation time using cloud-to-cloud method is lower than using cloud-to-mesh approach. For example, in the case of dataset 5, the accuracy analysis lasts 24 minutes with cloud-to-mesh algorithm whereas it consumes 8. 6 minutes with the octree structure (7 levels) in the cloud-to-cloud method. These results are promising in terms of reliability of photogrammetry approach when images have been dynamically acquired in a long canal-tunnel.
CONCLUSIONS AND FUTURE WORK This paper has introduced several methods for point cloud comparison in 3D in the case of canal tunnels. Given two datasets (assuming the clouds are expressed in the same reference frame) acquired either by photogrammetric or lasergrammetric devices, an accurate comparison relying on distance is possible. Speed constraints are tackled using a specific octree subdivision and an appropriate resampling of the point clouds. The first method (point-to-point comparison) allows us to check the quality and reliability of the TLS model. Then, this model can be considered as reference and cloud-to-cloud or cloud-to-triangular mesh techniques can be applied to huge datasets. The results show that the accuracy of the photogrammetry model is around 5 cm compared to lasergrammetric model considered as the reference.
While the dimension of P grows linearly with m and n, there is to the authors knowledge no analytic expression to estimate the resulting number of vertices n v. However, the upper bound on n v will usually grow exponentially with the dimension and the number of constraints q, which definitely restricts the class of tractable problems. One way to construct the saturation matrix S is to compute all vertices of P by using external vertex enumeration algorithms, e. g. , as they are included in the CDD package  [5]. On the other hand, some double description based packages like Polylib  [15]  compute the vertices, and in some cases even S itself, automatically when constructing the constraint polyhedron P. We do not discuss the construction of S and the underlying vertex enumeration problem here in detail and refer the reader to the relevant literature, e.
Numerical Examples In order to compare our algorithm with the one from  [6] , we implemented and tested Algorithm 1, Algorithm 2, and two additional versions of Algorithm 2 that combine the saturation matrix pruning with the symmetry exploitation techniques from Section 3. 2. The saturation matrix S was constructed by computing the vertices of the constraint polyhedron with the MPT extreme point solver extreme() using CDD via cddmex  [7]. Several mpQP problems have been solved, related to varying horizon linear MPC open-loop optimal control problems for the following two example systems. All computations were performed on a 3 GHz Dual Core PC with 8 GB RAM, running MATLAB 7. 11 and MPT 2. 6. 3. More details and numerical results can be found in  [3]  and, for the saturation matrix case, in  [4].
Cell culture and knockdown of gene expression with small interfering RNAs HeLa cells were cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal bovine serum and 1 mM sodium pyruvate. Ten microliters of a 100 mM siRNA solution (Eurogentec, Seraing, Belgium) was added to the cell suspension (10 7 cells in serum-free medium), and electro-transformation was performed with a Gene Pulser at 250 V and 950 mF in a 4-mm cuvette (Bio-Rad, Hercules, CA, USA). Different 21 mer siRNAs, whose efficiency was verified by quantitative polymerase chain reaction (qPCR), were used to knockdown expression of the following human protein genes: RPS10 (GenBank accession number: NM_001014): 5 0 -GAACCG GAUUGCCAUUUAUdTdT-3 0 (siRNA rps10); RPS15 (GenBank accession number: NM_001018): 5 0 -UCACCU ACAAGCCCGUAAAdTdT-3 0 (siRNA rps15); RPS20 (GenBank accession number: NM_001023): 5 0 -GGUGU GUGCUGACUUGAUAdTdT-3 0 (siRNA rps20); RPL26 (GenBank accession number: NM_000987): 5 0 -GTCCAG GTTTACAGGAAGAdTdT-3 0 (siRNA rpl26); PES1 (GenBank accession number: NM_014303): 5 0 -GGCCTT GAGAAGAAGAAGTdTdT-3 0 (siRNA pes1); RIO2 (GenBank accession number: NM_018343): 5 0 -ACAUGG UGGCUGUAAUAAAdTdT-3 0 (siRNA rio2); XRN2 (GenBank accession number: NM_012255.
3): 5 0 -GCCTA CCATTCACATTTGAdTdT-3 0 (siRNA xrn2); NOB1 (GenBank accession number: NM_014062. 2): a mixture of 5 0 -CGCCCUGGAGCCAAUCUUCAAdTdT-3 0 (siRNA nob1Q1), 5 0 -UUGCCCAACAUCGAUCAUGA AdTdT-3 0 (siRNA nob1Q2) and 5 0 -UUGCCCAACAUC GAUCAUGdTdT-3 0 (siRNA nob1E3). Experiments on transfected cells were performed 48 h after transfection of the siRNAs, except for hNOB1 knockdown, in which case the cells were treated for 6 days with siRNAs (three transfections at Day 0, 2 and 4). Control cells were electro-transformed with a scramble siRNA (siRNAnegative control duplex; Eurogentec). Anti-RRP6 and anti-hNOB1 antibodies were kindly provided by Dr Dominique Weil (CNRS, Paris) and Dr Ulrike Kutay (ETH Zu¨rich), respectively.
After phenol extraction and ethanol precipitation, digestion products were suspended and loaded onto an 8% polyacrylamide gel containing 7 M urea. After migration, the gel was dried and exposed. Signals were acquired with a PhosphorImager (FLA2000, Fuji, Stamfort, CT, USA) and quantified using the ImageGauge software. The 3 0 -RACE (Rapid Amplification of cDNA Ends) analysis was adapted from Kiss and Filipowicz  (23). Primer ITS1-Hs-RACE (5 0 -CGCGAATTCGATCATTA ACGGAGCCCGGAG-3 0 ), which spans the 18S-ITS1 junction up to nucleotide 11 in the ITS1, was used for PCR amplification. The amplified fragments were sub-cloned and automatically sequenced.
Such tails were also found, although to a lesser extent, in sequences from control cells or rio2 siRNAtreated cells (22 and 20%, respectively). In contrast, only 4% of sequences had U tails in pre-RNA from siRNA rps15-treated cells (Supplementary Figure  S4 ). Correlation of poly-uridine tail enrichment with accumulation of 18S-E pre-rRNA in the cytoplasm was confirmed by 3 0 -RACE on RNAs from cell fractionation: 23% of cytoplasmic sequences presented U tails, whereas only 7% of nuclear sequences had a U tail (data not shown). When 3 0 -RACE experiments were performed to study the 3 0 -end of the 21S pre-rRNA in cells treated with siRNAs rps10 or rps20 or in control cells, no U tails were found (data not shown), allowing us to exclude that poly-U stretches were artefacts because of the experimental procedure.
ACKNOWLEDGEMENTS The authors are grateful to  Dr Miche`le Caizergues-Ferrer ,  Dr Marle`ne Faubladier ,  Dr Je´roˆme Cavaille´ ,  Dr Anthony Henras ,  Dr Yves Henry ,  Dr Tamas Kiss ,  Dr Herve´Seitz  and their colleagues at  LBME  for fruitful discussions, technical advice and reagents. FUNDING CNRS; University of Toulouse;  French National Research Agency  ( ANR-RIBOCRASH  project);  Institut Universitaire de France. Funding for open access charge:  ANR.
UPLC-ESI-MS analyses Aqueous samples (taken from the photoreactor) were analyzed for organic species using Quadrupole-Time-of-Flight Mass Spectrometry and Ion Mobility Spectrometry (Synapt G2 HDMS, Waters, MA, USA) combined with electrospray ion (ESI) source and coupled with an Acquity UPLC system (Waters). The mass spectrometer was used in its resolution mode, up to 18 000 FWHM (Full width at half maximum) at 400 Da and allowed the determination of elemental composition of some organic species, using the I-FIT software. The I-FIT isotope predictive filtering is a strategy to reduce the number of proposed elemental compositions using algorithms to estimate the number of carbon, oxygen or sulfur atoms in an unknown molecule based on the mass of the molecular ion and the relative intensity of the 1st and 2nd isotopes  (Hobby, 2005).
The lock-mass syringe pump was operated at 7 µL min -1. A solution of sodium formate (CO 2 HNa, Waters Q-ToF product) was infused daily in the ESI source to calibrate the instrument. Optimum ESI conditions were found using a 2. 5 kV capillary voltage, 40 V sample cone voltage, 450 • C desolvation temperature, 120 • C source temperature, 20 L h -1 cone gas flow rate and 800 L h -1 desolvation gas flow rate. The ESI source has been optimized directly with the samples. These parameters allow increasing the signal to noise ratio, keeping soft ionization technique. Data were collected from 50 to 1800 Da in the positive and negative ionization modes. All products were detected as their protonated molecules ([M + H] + ) or sodium adducts ([M + Na] + ) in the positive mode, and their deprotonated molecules ([M -H] -) in the negative mode.
The obtained mass accuracy was as low as 2-5 ppm, and better for peaks with a relative intensity above 0. 5 %  (Makarov et al. , 2006). For our moderately complex mixture (∼ 6000 peaks), containing only O, C, H, and Na, unambiguous elemental formula assignments were established below 350 Da within 1 mDa using a custom computer software (Attributor v1. 05) developed by Orthous-Daunay (2011) and described in  Danger et al. (2013). It is based on a suite of scripts that allow to evaluate the most probable attribution of a high resolution peak, based on its mass, the presence and relative intensity of isotopic peaks, as well as chemical rules (nitrogen rule, even electron ions, etc. ) Using a Kendrick analysis  (Hughey et al. , 2001)  based on the MVK pattern (i. e. , C 4 H 6 O) found by  Liu et al.
NMR spectroscopy One of the experiments A was analyzed using NMR spectroscopy (Table  1 ). The instrument used was a Bruker Avance 500 MHz equipped with a 5 mm inverse-triple tuned (TXI) 1 H/ 13 C/ 15 N with z gradient coil probe. For 1-D 1 H-Spectra, 128 scans were collected with an impulsion time of 7. 5 µs, a relaxation delay of 5 s, an acquisition time of 4. 67 s, a spectral window of 5000 Hz and 64 K data points zero filled to 128 K before Fourier transformation with 0. 3 Hz line broadening. For 2-D homonuclear (COSY and TOCSY) and heteronuclear ( 1 H/ 13 C HSQC and HMBC) experiments were performed with quadrature phase detection in both dimensions, using state-TPPI or QF detection mode in the indirect one. For each 256 (homonuclear experiments) or 512 (heteronuclear experiments) increments in the indirect dimension, 2 K data points were collected and 16 or 32 transients were accumulated in the direct dimension.
Acknowledgements. We thank the  National Research Agency ANR  (project  Cumulus ), AXA insurances and  CNRS-INSU  for funding this research. We also thank  Barbara Ervens  ( CIRES, University of Colorado, Boulder and Chemical Sciences Division, National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA ) and  Gaëlle Gosset  ( Aix Marseille Université, CNRS, ICR UMR7273, 13397, Marseille, France ) for valuable scientific discussions on this topic. Edited by:  M. Ammann.
Back Close Full We used the LMDZ-ORCHIDEE-INCA atmospheric general circulation model to study the interactions between the atmosphere, aerosols, and snow-covered areas in the Himalaya. This model consists of three coupled modules. The LMDZ general circulation model represents the atmospheric component  (Hourdin et al. , 2006). The OR-CHIDEE land surface model describes exchanges of energy and water between the atmosphere, the soil and the biosphere  (Krinner et al. , 2005)  and includes a dynamic snow module. The coupling between LMDz and ORCHIDEE is described in  Hourdin et al. (2006). INCA (interactions between chemistry and aerosols) describes gasand aqueous-phase chemistry  (Hauglustaine et al. , 2004)  as well as aerosol physical properties such as size and hygroscopicity  (Balkanski et al.
ACPD  ACPD ACPD ACPD ACPD ACPD ACPD ACPD ACPD ACPD ACPD Acknowledgements. This work was supported by the  Agence Nationale de la Recherche  under contract  ANR-09-CEP-005-02/PAPRIKA. We thank the " Commissariat à l'Energie Atomique et aux Energies Alternatives " and  GENCI  for providing computer time for the simulations  ACPD ACPD ACPD ACPD ACPD ACPD ACPD.
Background: Trypanosoma vivax is the earliest branching African trypanosome. This crucial phylogenetic position makes T. vivax a fascinating model to tackle fundamental questions concerning the origin and evolution of several features that characterize African trypanosomes, such as the Variant Surface Glycoproteins (VSGs) upon which antibody clearing and antigenic variation are based. Other features like gene content and trans-splicing patterns are worth analyzing in this species for comparative purposes. Results: We present a RNA-seq analysis of the bloodstream stage of T. vivax from data obtained using two complementary sequencing technologies (454 Titanium and Illumina). Assembly of 454 reads yielded 13385 contigs corresponding to proteins coding genes (7800 of which were identified). These sequences, their annotation and other features are available through an online database presented herein.
Gene Ontology analysis shows that this group is enriched in proteins related to the translation machinery (e. g. ribosomal proteins, elongation factors). Conclusions: This is the first RNA-seq data study in trypanosomes outside the model species T. brucei, hence it provides the possibility to conduct comparisons that allow drawing evolutionary and functional inferences. This analysis also provides several insights on the expression patterns and levels of protein coding sequences (such as VSG gene expression), trans-splicing, codon patterns and regulatory mechanisms. An online T. vivax RNA-seq database described herein could be a useful tool for parasitologists working with trypanosomes.
library preparation and sequencing Library was prepared using the GS Titanium DNA library preparation kit (Roche) according to the manufacturer's protocol starting with 2. 5 μg of cDNA. The emPCR was done with GS Titanium SV empPCR kit (Roche) according to manufacturer's instructions. We used GS Titanium Sequencing Kit XLR70 (Roche) to sequence 1/2 GS Titanium PicoTiterPlate kit 70 × 75 in 454 Genome Sequencer FLX System (Roche). Illumina sequencing was carried out in a GAIIx on the same cDNA library which was re-fragmented and universal Illumina adaptors were added. Raw data were deposited in the NCBI database under submission number SRA056332.
Bioinformatics and data analysis Data quality analysis The details of sequence data obtained by 454 and Illumina sequencing are presented in Additional file 1: Table  S1. For the first technology 187491 reads, with an average length of 295 nt. were obtained. This corresponds to 54 Mb of sequence data. For the second technology, 37 million of reads (36 nt), corresponding to 1332 megabases were obtained. Several quality tests were carried out. In the first place, the percentage of contaminating reads present in the sample (i. e. corresponding to the host) was determined. For this purpose the reads were mapped into the sheep genome using Blastn. By doing this it was possible to establish that only 433 reads (i. e. 0. 20%) were of host origin. A similar figure was obtained for Illumina reads (in this case mapped using Bowtie  [13] ).
In addition, this methodology does not restrict the isolated RNA to mature mRNA either, as it can be inferred from the fact that other types of RNA molecules are quite abundant in the sample. In effect, transcripts derived from the kinetoplast genome are relatively abundant (Additional file 1: Table  S1 ). For the case of maxicircle, it was possible to identify them using simple homology search, given that these genomes are relatively conserved among trypanosomatids. But, such strategy was not suitable for minicircle derived RNA identification because of their lack significant conservation. Therefore the incidence of this latter group was not determined. To evaluate the genome coverage of RNA-seq data produced in this work, 454 and Illumina reads were mapped to genomic sequences (retrieved form GenBank) in order to estimate the sequencing depths of the top, middle and botton 1000 expressed genes.
Assembling and functional annotation Assembling of 454 reads was conducted using two different computer programs Mira  [15]  and Newbler (Roche, Switzerland). The two resulting assemblies were compared to each other, in order to assess their qualities and determine which one was more appropriate for subsequent analyses. The quality of the assembly was assessed by comparing the assembled contigs with a reference set containing well defined mRNA sequences. To assess quality, two variables were measured, the proportion of the reference mRNA that is well reconstructed (P) and the number of contigs falling in each mRNA reconstruction fraction (N), so that the overall quality of the assembly is given by: Q ¼ X i N i P i. This comparison was done using a reference set consisting of protein coding sequences available in GenBank that are putatively expressed in the bloodstream stage.
These were identified on the basis that their T. brucei orthologs are unambiguously expressed in this stage. In turn, the latter condition was determined by testing which T. brucei protein coding genes are observed in the bloodstream EST collection. It should be noted that this collection was built using traditional Sanger sequencing from poly A + RNA, which due to the low sensitivity of the method, contains mainly unequivocally transcribed genes. The results obtained allowed us to draw two useful conclusions. In the first place Mira outperforms Newbler, yet by a narrow margin; provided that the contigs built by Mira reconstruct better the mRNA (i. e. the Q statistics is higher). Secondly, more than 92% of the putatively expressed mRNAs are tagged (either by contigs containing several reads, or by individual reads), hence indicating the 454 derived sequence dataset is a good picture of the transcriptional state of the parasite (Additional file 3: Table  S2 ).
Functional annotation of RNA derived contigs was carried out using a set of complementary tools: ESTscan  [16] , Blast2Go  [17] , InterProScan  [18]  and AnEnPi  [19]. In the first place, to identify T. vivax genes encoding proteins with a known or unknown function, it was necessary to obtain high quality virtual translation of contigs. This translation is not always the straightforward exercise of mechanically applying the genetic code to possible ORFs. Instead, contigs often contain serious translation problems derived from sequencing errors that may change the reading frame (frameshifts). To handle this complication the ESTscan program was used. This application employs a Hidden Markov Model (that uses the distribution of codons) to restore the correct frame by introducing indels. The program needs to be calibrated (trained) in such a way that it recognizes possible alteration in the ORFs on the basis of their statistical properties  [16].
For training the ESTscan HMM, T. vivax coding and intergenic sequences were retrieved from public databases. After this step, functional annotation of the translated contigs was done combining the results of Blastp against nr NCBI (all non-redundant GenBank CDS translations plus other well curated databases) and a domain analysis based on Interproscan. Results of both sources were integrated using Blast2Go, which allows assigning GO terms to the entries by using simple annotation rules. Because B2G is quite conservative to assign ontology terms, the analysis was complemented with a simple Blastp search against translated nr NCBI. Besides the AnEnPi pipeline  [19]  was used on KEGG in order to predict possible metabolic pathway that are active in the bloodstream stage of Trypanosoma vivax.