dataesr/scientific-paragraphs-categorization huggingface dataset:
Computer-Brain Interface For the CBI subsystem, we relied on biphasic TMS pulses to encode information. For each receiver subject, we identified first a TMS phosphene-producing hotspot in the right visual occipital cortex (approximately 2 cm anterior and 2 cm right from inion, the precise location depending on the subject), which was used for the active condition (to encode the bit value '1'). We achieved the required high precision in relocation and reorientation of the TMS target by using a neuronavigated  [25] [26] [27] [28] , robotized TMS system (Axilum Robotics TMS-Robot, http://www. axilumrobotics. com, piloted by Localite 2. 8 Neuronavigation system using the MagVenture MagPro R30 TMS Stimulator with a ''butterfly'' coil of type Cool-B65-RO). Subjects went through a familiarization period in which we administered several TMS pulses to the chosen right occipital cortex site using various rotations of the coil, and identified the intensity of TMS pulses (range 57-90% of maximum intensity of the coil) that optimally discriminated active (i.
This work was partly supported by the  EU   FP7 FET Open HIVE  project (GR, AR, CG, http://hive-eu. org, FET-Open  grant  222079 , http://cordis. europa. eu/fp7/ict/fetopen/home_en. html), the  Starlab Kolmogorov  project (GR, CG,  SIF-003 , http://starlabint. com), the research group 2009SGR00093 from the  Generalitat de Catalunya  (GR, CG, http://www10. gencat. cat/agaur_web/AppJava/english/a_beca. jsp?categoria = altres&id_beca = 4861), and by the  Neurology Department of the Hospital de Bellvitge (JLA). Co-authors CG, AR and GR were employed by  Starlab Barcelona  during these studies. The funder, Starlab, provided support in the form of salaries for authors CG, AR and GR, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Analysis of hAT Copies Annotated genome sequences for 41 Ascomycota yeast species were retrieved from different databases. The complete list is provided in supplementary table S1, Supplementary Material online. We sequenced the seven Lachancea genomes that were as yet unavailable, using a Roche 454 sequencer and employing a combination of 400-bp paired ends and 8-kb mate pairs. This sequencing strategy allowed the assembly of repeated sequences shorter than 8 kb in the scaffolds, which is the case of all TEs in the Lachancea species. The resulting coverage ranged from 25 to 30Â. Genome assembly of the seven genomes was achieved with Celera Assembler v6. 1  (Myers et al. 2000)  and Newbler v2. 7 (454 Life Sciences) with default parameters. As many scaffolds as chromosomes were obtained; for each species, with the exception of Lachancea mirantina, both Celera and Newbler assemblies turned out to be collinear and congruent with karyotypes visualized on pulsed field gels (data not shown).
In L. mirantina, the misassembly involved two chromosomes, only Newbler being able to produce scaffolds of the expected size. We searched for Rover-like transposases in these genomes with BLASTP and TBLASTN, using annotated Rover elements from L. thermotolerans  (Souciet et al. 2009). To extend our analysis to the whole hAT superfamily, hAT-like transposases were identified using a Pfam v27. 0 scan  (Finn et al. 2014) , with an e-value cutoff of 0. 01 for the 41 proteomes. We searched for the most characteristic domains (i. e. , the BED zinc finger domain PF02892 and the dimerization domain PF5699) that are associated with hAT transposases  (Aravind 2000; Essers et al. 2000). TIRs were then identified by performing pairwise mapping of sequences adjacent to transposase CDSs (dotplots were generated using http:// www.
vivo. colostate. edu/molkit/dnadot/ , last accessed December 19, 2014) and by using TBLASTN to search genome sequences. We also used TBLASTN to search the nonredundant NCBI (National Center for Biotechnology Information) database to check if Rover and Roamer transposases could be found in other species. Sequence similarity between the transposases was computed using GeneDoc v2. 7. 0  (Nicholas et al. 1997) , following sequence alignment using MAFFT v6. 903b  (Katoh et al. 2002)  and manual corrections. Only transposases longer than 500 aa or 800 aa were used for Rover and Roamer, respectively. Heat map and similarity-based clustering of the 48 Rover transposases carrying at least one TIR was produced with R (R Core Team 2014). We checked for the presence of hAT-like conserved domains  (Rubin et al.
2001 ) using a single transposon copy from each Rover family in Lachancea species and using one transposon copy per species for the other species; we also examined 13 Roamer copies. Sequence logos of TIRs were generated by WebLogo v2. 8. 2  (Crooks et al. 2004). DNA secondary structures of MITEs were determined by SantaLucia free energy rules (SantaLucia 1998) using the program mfold v3. 6 with the default settings (http://mfold. rit. albany. edu//?q=mfold/DNA-Folding-Form, last accessed  December 19, 2014; Zuker 2003). Synteny analyses for Rover and Roamer insertion site conservation were performed with CHROnicle/SynChro  (Drillon et al. 2014 , available at http:// www. lgm. upmc. fr/CHROnicle/SynChro. html, last accessed December 19, 2014), with a Delta parameter of 2 or 4, meaning that two adjacent genes are separated by less than two or four genes, respectively, in the absence of orthology.
Phylogenetic Analyses Phylogenetic analyses were conducted on the 41 Ascomycota yeast species where hAT elements were searched for, on hAT elements from diverse eukaryotic lineages, and on the Rover transposases. The general line of analyses was to align sequences with MAFFT v6. 903b  (Katoh et al. 2002)  or MultAlin  (Corpet 1988 ) in case of highly divergent sequences and to draw a phylogeny with the amino acid substitution model recommended by ProtTest v3. 4  (Darriba et al. 2011). The maximum-likelihood algorithm PhyML v3. 0  (Guindon et al. 2010 ) and the Bayesian inference program MrBayes v3. 2. 2  (Ronquist and Huelsenbeck 2003)  were both used except when the substitution model was not implemented in MrBayes, as it is the case for LG model. The species phylogeny was constructed using a set of 104 protein sequences from referenced hemiascomycete genomes (supplementary table S1, Supplementary Material online); these proteins are singletons in all the species considered.
Protein sequences were aligned using MAFFT and subsequently cleaned using Gblocks v. 0. 91b, in which the options Àb3 = 20 and Àb0 = 5 were applied  (Castresana 2000). The 104 alignments were then concatenated, leading to an alignment that was 39,926 residues long. The phylogenetic analysis was performed with PhyML, using the amino acid substitution model LG  (Le and Gascuel 2008)  with estimated proportion of invariable sites (+I) and shape parameter of the gamma distribution (+G). Confidence was assessed in 100 bootstrap replicates. The hAT phylogeny was constructed using transposase amino acid sequences from 46 full-length and potentially active transposases, which were selected because they are associated with known hAT elements or because they were revealed by BLASTP hits in the nonredundant NCBI database (nr) when Rover elements were used as queries.
Analysis of Selection Pressure and dN/dS Ratios To examine the selection pressure acting on the potentially fixed Rover copies, we evaluated the strength of purifying selection on their transposases in comparison with the 104 genes used for phylogenetic reconstructions. Pairwise nucleotide alignments were deduced from MAFFT protein alignments using tranalign from the EMBOSS package  (Rice et al. 2000). The dN/dS ratios were calculated from these alignments using CodeML model with a pairwise run mode from PAML4 package version 4. 4b  (Yang 2007). dS values higher than 1 were removed from the analysis to avoid dS saturation.
inra. fr, last accessed December 19, 2014; supplementary table S4, Supplementary Material online). In the other 25 complete genomes analyzed, no sequences homologous to the Rover transposase or its TIRs were found. An additional homology search was performed using the nonredundant NCBI database and revealed the presence of three degenerate copies in the wine yeast S. cerevisiae strain AWRI1631 (table 1). To broaden our investigation of hAT elements in ascomycota, we used another approach, in which we systematically searched for the transposase Pfam domains PF02892 and PF5699 in the 41 proteomes studied. Using this technique, other groups of hAT elements were identified (supplementary table  S3 , Supplementary Material online). In Naumovozyma castellii, 17 CDSs were found to contain the dimerization domain and 3 of them also contained the BED ZnF domain.
castellii Roamer copies (26-35%) is always slightly higher than the lowest conservation between N. castellii copies (24-100%). Thus, Rover and Roamer elements fulfill all applicable criteria to support the hypothesis of secondary HTs. In addition to Rover and Roamer elements, 52 putative hAT-like elements and other class II elements were found in 35 of the 41 species studied, using the Pfam scan. Eleven are singletons and the others belong to five families that are either species specific or conserved among clades (supplementary table  S3 , Supplementary Material online). For instance, in Taphrina deformans, we identified three hAT-like degenerate copies without TIRs that nonetheless contained the dimerization domain PF05699. Once again, the transposases had already been predicted to be hypothetical proteins, but their coordinates had to be extended.
Survey of Rover and Roamer Structural Features Full-length Rover copies are about 3-kb long; their transposases, which are 800 aa in length on average, harbor a C-terminal dimerization domain (PF05699) that is characteristic of the hAT element superfamily  (Essers et al. 2000)  and an N-terminal DNA-binding domain (PF02892) that is fairly typical of transposases  (Aravind 2000). They have 18 -to 20-bp TIRs flanked by 8-bp target-site duplications (TSDs) (fig. 2 ). Among the 154 copies observed, 19 copies, all belonging to Lachancea species, exhibit perfect TIRs (or nearly perfect in the case of one copy with an identity of 17/18 bp) and encode transposases longer than 724 aa that do not contain any interrupting stop codons or frameshifts and are thus considered to be potentially autonomous.
In our analyses, the Tip group did not appear to be monophyletic, which reflects how difficult it is to generate a robust alignment from highly variable sequences. Additional transposase datasets would be needed to infer a more robust phylogeny. However, the phylogeny showed that the Rover elements formed a monophyletic group, and that along with Roamer, they belong to Ac elements (fig. 3 ). The Rover and Roamer groups' lack of targetsite preferences however distinguishes them from other Ac elements. Indeed, only 7 of the 74 Rover TSDs (9%) and 3 of the 12 Roamer TSDs (25%) have conserved T and A nucleotides at the second and seventh positions, which is a trait that is characteristic of Ac elements  (Arensburger et al 2011). Rover Elements Are Subdivided Into Five Families Roamer copies are homogenous; their transposases have a mean pairwise amino acid similarity of 70%.
1B ). Another FIG. 3. -Phylogenetic tree of transposase sequences from Rover, Roamer, and other groups of hAT elements. A 468-aa alignment of 46 transposases was used to draw a maximum-likelihood tree. Bootstrap values are indicated above branches. Transposases are clustered in three groups, as defined by  Rossato et al. (2014). However, in our tree, the Buster group is nested within the Tip group with however a moderate support. Branches are colored according to taxonomic group: Red for the hemiascomycetes, brown for Taphrinomycotina, orange for members of Pezizomycotina, purple for the basidiomycetes, green for the plants, blue for the insects, and black for the vertebrates. Sequence accession numbers for the representatives in the international sequence databases are provided: gb and gi, GenBank; emb, EMBL; dbj, DDBJ; and tef, TEfam.
Overall, our results show that class II TEs are likely more common than previously thought. They are not easy to identify during genome annotation because transposases are highly variable and therefore are hard to recognize using BLAST-based approaches alone. Our approach of systematically searching our species dataset using characteristic transposase domains and TIRs ended up being very powerful (supplementary table  S3 , Supplementary Material online). In addition to hits corresponding to Rover and Roamer copies, we obtained 52 hits corresponding to singletons or genes in families, in single genomes, or in several closely related species. Given their species distributions, some families are probably very ancient and represented by a few members containing relics of transposase functional domains.
2009 ). However, members of this RSF1 family are weakly conserved among species and most of them contain neither the C-terminal dimerization domain characteristic of the hAT superfamily (PF05699) nor the BED finger DNA-binding motif PF02892 common to different class II elements  (Aravind 2000; Essers et al. 2000). Similarly, YGR071C and its homologs in Saccharomycetaceae might derive from an ancestral hAT element, but distinct from the RSF1 hAT ancestor. Thus, if all the families and singletons that we detected actually arose from hAT elements, they would have come from different hAT ancestors, probably acquired independently, and would have diverged until they had lost almost all their hAT signatures. These examples illustrate the importance of using Pfam domain prediction or similar approaches to track TEs or their relics and, consequently, to improve our knowledge of TE dynamics in yeasts.
Key differences for astronomical correlation wavefront sensing The situation for night-time astronomical AO correlation wavefront sensing is more complicated. A single reference image cannot be used because the shape of each Shack-Hartmann spot is different (defined in part by the distance and angle of the sub-apertures from the laser launch axis). Therefore, a unique correlation image for each sub-aperture must be supplied. Astronomical AO systems generally work in the photonstarved regime, where fluxes and signal-to-noise ratios are low. This is generally also the case when using LGSs primarily because of the increasing cost of more powerful lasers, the desire to operate with high frame rates and at high WFS order. A single frame LGS image is therefore generally noisy, and so the computation of correlation reference images cannot be obtained from a single frame of Shack-Hartmann data since flux is low, and such images would contain significant noise.
Modelling A further technique which can be used to obtain the reference images is using modelling. A small number of LGS wavefront sensor images can be obtained, and these used to derive parameters for a model of the Sodium layer density profile, for example number and separation of sodium density peaks. Alternatively, an external profile monitor could be used. This model can then be used to generate suitable correlation reference images. We do not consider this modelling approach further here, rather concentrating on data driven approaches.
DARC The Durham adaptive optics real-time controller (DARC)  (Basden et al. 2010 ) is a high performance, central processing unit (CPU) based real-time control system for AO, which has been used successfully on-sky with CANARY. DARC has a modular design which affords it great flexibility for developing and testing new algorithms. An advanced correlation wavefront sensing module has been developed, and used both on-sky and for this investigation. The suitability of DARC for use with ELT-scale AO systems has been demonstrated  (Basden & Myers (2012) (b)), and includes the ability to make use of additional computational hardware including field programmable gate arrays (FPGAs), graphical processing units (GPUs) and the Intel Xeon Phi, a manycore hardware accelerator. The DARC system has the ability to use rectangular sub-apertures that are positioned and sized arbitrarily, i.
Statistical Analysis The event rate of exacerbation (number of AECOPD/person-times of follow up) was analysed with a Poisson regression model. Event rates were calculated for categories of patients with or without viral AECOPD and according to number of AECOPD (0, 1, 2 or more AECOPD) during the year preceding the index AECOPD. Cox regression model was used to analyse all-cause mortality and time to first AECOPD, according to the presence or absence of viruses at initial AECOPD. Results are presented as hazard ratios (HR) with 95% confidence intervals (95% CI). All statistical analyses were performed using SPSS (version 15. 0 for Windows, Chicago, IL,) and STATA version 11.
Surface measurements CH 4 and CO 2 eddy covariance and chamber flux measurements were made in Sodankylä, Finland, from 1 July 2012 to 15 August 2012. The eddy covariance system used included a USA-1 (METEK GmbH, Germany) three-axis sonic anemometer/thermometer, a RMT-200 (Los Gatos Research, Inc. , USA) CH 4 analyzer and a LI-7200 (Li-Cor, Inc. , USA) CO 2 /H 2 O gas analyzer. The measurement height was 6 m a. g. l. (above ground level). The length of the inlet tubes for both gases was 8 m for CH 4 and 1 m for CO 2 , with flow rates of 15 and 20 L min -1 , respectively. For more details of the eddy covariance measurement system, see  Aurela et al. (2009). Half-hour flux values were calculated using standard eddy covariance methods. The original 10 Hz data were blockaveraged, and a double rotation of the coordinate system was performed  (McMillen, 1988).
(2005). Very similar to the implementation in the JULES land surface model, the TOP-MODEL hydrological module in HYBRID8 uses a topo-graphical index and interactively computes the wetland fraction in each grid box (f w ), and only saturated soils (determined by f w ) contribute to CH 4 emissions. The fluxes of CH 4 are also parameterised in a very similar way in HY-BRID8 as in JULES. The governing equation for CH 4 production at depth z is P w (CH 4 ) = k(CH 4 )Fps(z) C som (z)Q (T (z)-T 0 )/10 10 , (2) where k(CH 4 ) is the baseline production rate, Fps(z) is the total pore space fraction in a specific layer (a function of soil texture), C som (z) is the soil organic matter at the depth z, and T (z) is the soil temperature. For this study, the following representative parameters were chosen: k(CH 4 ) = 1.
This is possibly because of an under-prediction of wetland extent by both models in this region, which could be linked to the topographical data set used and/or the absence of an organic soil type related to peatlands. Such soils would have very different hydraulic properties to the mineral soil types currently used in JULES and HYBRID8. Water would be retained at or close to the surface increasing the area of wetlands. Model emission fluxes were derived assuming that each grid cell is all wetland. These results were found to be much closer to the aircraft values for both JULES (July-August 2012: median 1. 6 mg CH 4 h -1 m -2 , inter-quartile range 1. 4 to 1. 8 mg CH 4 h -1 m -2 ) and HYBRID8 (2012: median 1. 9 mg CH 4 h -1 m -2 , inter-quartile range 1. 6 to 2. 6 mg CH 4 h -1 m -2 ). This suggests that underestimation of the area of wetlands in both models is probably the ma-   (Melton et al.
Acknowledgements. The  MAMM  project was funded by the  UK Natural Environment Research Council  (grant  NE/I029293/1 ). S. J. O'Shea  is in receipt of a  NERC  studentship and  G. Allen  is a  NERC Fellow  (no. NE/I021276/1 ). Airborne data were obtained using the  FAAM BAe-146 Atmospheric Research Aircraft (ARA)  operated by  Directflight Ltd  (DFL) and managed by the  Facility for Airborne Atmospheric Measurements (FAAM) , which is a joint entity of the  Natural Environment Research Council (NERC)  and the  UK Meteorological Office. The CORINE land cover map was obtained from http://www. eea. europa. eu/data-and-maps/data/corine-land-cover-2006-raster, the copyright holder is the  European Environment Agency (EEA). A. Friend  and  A. Quiquet  received funding from the  European Community 's  Seventh Framework Programme  ( FP7 2007-2013)  under grant agreement no.
A. Expansions using orbital and dominant-products basis sets We use linear combination of atomic orbitals (LCAO) approach  48  and expand the eigenfunctions Ψ E (r) of the one-electron Hamiltonian in terms of atom-centered localized functions f a (r) Ψ E (r) = a X E a f a (r). ( 14 ) The atomic orbitals f a (r) have a predefined angular momentum and radial shape, while the coefficients X E a must be determined by solving the corresponding eigenvalue equation. In this work we have used a basis set of atomic orbitals expanded in terms of Gaussian functions. 49, 50 These basis sets are the same used by most of the Quantum Chemistry codes. We have used NWChem code  46  to perform the ∆SCF coupled-cluster calculations that will be compared with our GW results. In particular, for most calculations we have used two different sets of basis for all our calculations: a correlation-consistent double-ζ (cc-pVDZ) and a triple-ζ (cc-pVTZ) basis.
We focus in the helium atom and the hydrogen dimer. The frequency grid extension is fixed by f ω = 2. 5. The frequency resolution is ∆ω = 0. 1 eV for both QSGW "modes". For SCGW , we report linearly extrapolated IPs from data calculated using ∆ω = 0. 1 and ∆ω = 0. 05 eV, following our discussion in subsection V B. The broadening constant is set to ε = 2∆ω, and the non-local compression is performed with λ thrs = 10 -3. These choices are justified by the tests presented in the subsections V A, V B, V C and V D. The data for the IPs as a function of the basis size are collected in the Table  IV. We present results obtained with our code for "mode A" and"mode B" of QSGW (henceforth QSGW A and QSGW B), and SCGW. Table IV also presents the data computed with the MOLGW code developed by F. Bruneval 58 as well as our reference ionization energies from the CCSD calculations with the NWChem code  46.
Notice that for systems containing two electrons CCSD and CCSD(T) are identical, due to the absence of triple excitations, and become equivalent to full-CI. 59 MOLGW implements (among other methods) the QSGW A algorithm. 18 It is important to stress here that the MOLGW code employs other algorithms than used in this work and its implementation is independent on our implementation. Therefore, the close agreement (maximal deviation of 0. 03 eV) between the QSGW IPs computed with our code and MOLGW is an important cross-check. In agreement with previous studies,  18, 27  the data in Table  IV  illustrate the very slow convergence of the GW results with the basis set size. A more noticeable and unexpected finding is the non-monotonous convergence of the QSGW A method for the two systems considered here.
This is in clear contrast with the behavior observed for both SCGW and QSGW B and, to the best of our knowledge, it had not been reported previously. Notice that the same irregular behavior is produced by our code and by MOLGW. According to our analysis, this poor convergence can be traced back to the combination of two issues, one inherent to the QSGW A scheme, and the other related to the use of atomic orbitals as a basis set. The difficulties arise from the fact that in QSGW A the non-diagonal elements (in the basis set of QP wavefunctions) of the correlation operator (Eq. 12) contain contributions from the self energy evaluated at two different QP energies. Therefore, e. g. , the calculation of the HOMO is influenced by the self energy calculated at all other energies, including energies corresponding to the highest molecular states.