dataesr/scientific-paragraphs-categorization huggingface dataset:
Corpus callosum agenesis is the most frequent commissural malformation. The false-positive rate of ultrasound screening for this malformation varies from 0 to 22%. It may be over-diagnosed because of its association with ventriculomegaly, which may hinder adequate visualization of the cerebral structures  [42]. Three-dimensional sonography makes it possible to acquire the foetal head volume from the axial view and then, by reconstructing the image with the multiplanar technique, to obtain a suitable view of the corpus callosum without the technical difficulties of 2D-sonography. Second-step complementary NMR remains, however, a clinically valuable adjunct to ultrasound and provides additional information when the ultrasound diagnosis is uncertain  [43, 44]. One limitation of our study is that the CEMC database registers only children in whom malformations have been confirmed after birth or induced abortion, so that it is not possible to analyse the predictive values of the ultrasound screening.
Another limitation may be the absence in our database of reliable data about the mode of dating pregnancies: this information is missing for many women. Nonetheless, in France the national health insurance fund reimburses three ultrasound examinations during pregnancy; the first is performed between 11 and 14 weeks to determine term and measure nuchal thickness as part of trisomy 21 screening. Accordingly, the pregnancy date is most often determined by fetal ultrasound. The national survey perinatal found that only 0. 1% of women had no ultrasound during pregnancy in 2003, and 0. 2% in 2010  [45]. It is therefore unlikely that our results are biased (as ultrasonographic term is correlated with the beginning of pregnancy) by the absence of data about early fetal ultrasound.
A specialised database for storing clinical and family data and information technology support systems is essential for effective provision of services  [8, 30, 31]. Computerised programs should be capable of pedigree drawing, workflow management, production of template letters, archiving data, clinical audits and research. An international database with information on mutations recognised as causing FH  [95]  is available, but should be developed for those countries or healthcare systems adopting DNA testing  [84] [85] [86]. A well-designed and comprehensive clinical registry provides invaluable information for research and audit, as well for improving the quality of care  [26, 150]. A registry can facilitate the co-ordination of cascade screening at a local, community and national level, increasing also the cost-efficiency of DNA testing where a mutation has been previously identified and registered in a family  [150].
Acknowledgements We thank the following experts for completing a brief questionnaire regarding contentious issues in FH:  Pascale Benlian ;  Deepak Bhatnagar ;  Dirk Blom ;  Alberico Catapano ;  Richard Ceska ;  Ada Cuevas ;  John Deanfield ;  Olivier Descamps ;  Mats Eriksson ;  Claude Gagne ;  Anne Goldberg ;  Paul Hopkins David Marais ;  Luis Masana ;  Andre Miserez ;  Jonathan Morrell ;  Dermot Neely ;  Leiv Ose ;  Henry Purcell ;  Alan Rees ;  Handrean Soran ;  Mario Stoll ;  Charles Van Heyningen ;  Kurt Widhalm. Disclosures Some members of the Group have received lecture honoraria, consultancy fees, and/or research funding from:  Abbrie (PPT) ;  Abbott  (GFW, KKL, KGP,.
This code was developed first for the visible light domain, and we imported the optical constants for X-ray wavelengths. Nevertheless, this code does not take into account the interface roughness. To determine the calculated spectral profile with the roughness included, we used the IMD simulation software  [23]  that is a free point-and-click IDL application to calculate reflectivity of multilayer structures. Uncertainties of thicknesses have been estimated by systematic variation of each parameter independently (i. e. for each material). Grazing incidence X-ray reflectometry (GIXR) was made with a commercial grazing incidence reflectometer (BRUKER ® Discover D8) working with Cu Kα radiation at energy E = 8. 048 keV (wavelength λ = 0. 154 nm). A collimating Göbel mirror  [24] , located at the exit of the X-ray tube, provides high flux density and low divergence beam.
75 -10 keV using either Si or InSb crystals in the monochromator. The mirrors were placed in a UHV reflectometer, which provides a 0. 001° angular resolution for the sample and the detector. The typical beam size is 0. 3 mm vertically and 0. 5 mm horizontally. The vertical beam divergence is about 0. 02°. Silicon photodiodes with different apertures and a photon counting detector are mounted on the detector arm. To account variations in the incident monochromatic photon flux, the currents are normalized to the current of a thin photodiode operating in transmission in front of the reflectometer. We analyzed the reflectivity data with the program Leptos ®  [27]  that permits to fit the GIXR and SOLEIL data using a genetic algorithm. The fit of the measured reflectivity curve gives the parameters of the layer thicknesses, materials density and the average interface roughness.
Aperiodic Ni/SiC multilayer In section 3. 1. , we reveal the existence of an important interdiffusion phenomenon between Ni and SiC layers. Our results suggest that a simple model, such as a Ni 5 Si 2 /SiC structure, allows fitting the experimental data with a good precision for periodic multilayer samples with different values of layer thickness. Using the IMD software, we generated optical refractive indexes for the Ni 5 Si 2 chemical compound with a density fixed at 7. 00 g/cm 3. We then optimized a Ni 5 Si 2 /SiC aperiodic multilayer mirror with a reflectivity target spectrum plotted as solid line in Fig. 5. The simulated reflectivity of the optimized MIM is plotted as dash line in Fig. 5. The MIM consists of 80 layers with thickness ranging from 2. 00 to 4. 15 nm. The reflectivity measurement of this sample was performed at PTB under 1.
Acknowledgments All multilayer depositions have been carried out on the deposition machine of  CEMOX (Centrale d'Élaboration et de Métrologie d'Optique X) , a platform of LUMAT federation ( CNRS FR2764 ). The authors would like to thank SOLEIL beamline staff and CEA associates (project submitted to peer review committee: No. 20130059 ) for measurements on the hard X-ray branch of the Metrology and Tests beamline. The authors would like also to thank  Michael Krumrey  and the PTB beamline staff for measurements on the four-crystal monochromator beamline. The authors would like to thank  Regina Soufli  from  Lawrence Livermore National Lab (USA)  for fruitful discussions.
Detection of Conserved Proteins Widespread in Archaea and Bacteria We gathered the protein sequences coded by all publicly available complete genome sequences of archaeal species (using one genome sequence per species to avoid redundancy) as well as those of 117 bacterial species into a local database (for the list of organisms, see supplementary table  S1 , Supplementary Material online). We then carried out sequence similarity searches against the archaeal sequences in this database using BLAST  (Altschul et al. 1997 ) and all the protein sequences coded in the genomes of Nitrosopumilus maritimus and Cenarchaeum symbiosum (Thaumarchaeota) and Caldiarchaeum subterraneum (Aigarchaeota) as queries. These species were chosen as starting point because Thaumarchaeota have been proposed to have an intermediate gene content between those of the classical Euryarchaeota and Crenarchaeota  (Brochier-Armanet et al.
2008) , whereas C. subterraneum represents a lineage distantly related to the Thaumarchaeota  (Nunoura et al. 2011). The BLAST results were filtered to retain only those containing representatives at least four archaeal sequences with an E-value threshold of 1e-05. Partial sequences were also removed at this step. The 4,174 proteins thus identified were submitted to preliminary phylogenetic analysis (see later). The phylogenetic trees obtained were checked manually to retain only those where the species belonging to different archaeal classes (e. g. , Thermococcales, Halobacteriales, Sulfolobales, and so on) were monophyletic, irrespective of the relative order of emergence of the different classes. Data sets with evidence for horizontal gene transfer (HGT) events (i. e. , with archaeal species from different classes intermixed) were also removed, as well as data sets that produced trees with branching patterns suggesting the presence of paralogs (e.
Phylogenetic Analyses Sets of homologous protein sequences were aligned using MAFFT with default parameters  (Katoh and Standley 2013). Conserved positions in the alignments were detected using BMGE with default parameters and the BLOSUM62 substitution matrix, which represents a good compromise between too stringent and too relaxed matrices to deal with sequences with a large range of similarity values as in the case of global archaeal phylogenies  (Criscuolo and Gribaldo 2010). The trimmed alignments were verified by hand using the program NET of the MUST package  (Philippe 1993). Maximumlikelihood (ML) phylogenetic trees were reconstructed upon each individual protein or different concatenated data sets with RaxML v. 7. 2. 4  (Stamatakis 2006 ) and the PROTGAMMALGF model. Tree robustness was estimated using the Rapid Bootstrapping method implemented in RaxML.
We then carried out a phylogenetic analysis of a concatenation of our new markers (38 markers, 6,890 amino acid sites). In sharp contrast with the previous tree based on translation-related proteins, the Bayesian phylogenetic tree based on this new data set was rooted between the whole clade of the Euryarchaeota and a group containing the rest of archaeal species, namely the TACK supergroup (fig. 1B ). This rooting was robustly supported (PP = 1, BP = 99-100%). Moreover, the tree also strongly supported (PP = 1, BP > 90%) the monophyly of most of the archaeal classes commonly accepted to be monophyletic based on phylogenomic and gene-content analyses  (Brochier-Armanet et al. 2011 , Wolf et al. 2012). This suggested that this data set contained exploitable phylogenetic signal. One important difference between the phylogenetic tree based on these proteins and the one based on the ribosomal proteins concerned the length of the branch uniting the Archaea and the Bacteria.
Unexpectedly, despite the presumed high conservation of the ribosomal structure and activity in all living beings, this branch was much longer in the ribosomal proteins tree than in the tree based on the new markers (a 2. 6Â difference, fig. 2 ), indicating that the new markers have kept a higher sequence similarity between these two life domains than the ribosomal proteins. Finally, we analyzed a combined data set containing all the previous markers (translation-related proteins plus our new markers, for a total of 70 markers and 9,540 amino acid sites). The resulting tree (fig. 3 ) was very similar to the one obtained from the analysis of the concatenation of the new markers. In fact, the root was placed between the Euryarchaeota and the rest of archaeal species with strong support, especially by the Bayesian analysis (PP = 1 for all deep nodes in the tree) and moderately by the ML analysis (BP = 79% for the monophyly of the Euryarchaeota and 100% for the TACK group).
0 fb -1 respectively. In this paper we reanalyse the 2011 data using a data driven method that employs the full statistical power of the data set. The detailed formalism of the effective lifetime in B 0 (s) → h + h -decays can be found in Refs. [8]  and  [9]. The decay time distribution of a B 0 (s) → h + h -decay, with equal contributions of both B 0 (s) and B0 (s) at the production stage, can be written as Γ(t) ∝ 1 -A ∆Γ (s) e -Γ (s) L t + 1 + A ∆Γ (s) e -Γ (s) H t , (1) where Γ (s) H = Γ (s) -∆Γ (s) /2 and Γ L = Γ (s) + ∆Γ (s) /2 are the decay widths of the heavy and light mass eigenstates, Γ (s) is the average decay width and ∆Γ (s) is the decay width difference between the mass eigenstates. These in turn are given as linear combinations of the two flavour states with complex coefficients q and p.
Results and conclusions The effective B 0 s → K + K -lifetime is measured in pp interactions using a data sample corresponding to an integrated luminosity of 1. 0 fb -1 recorded by the LHCb experiment in 2011. A data-driven approach is used to correct for acceptance effects introduced by the trigger and final event selection. The measurement evaluates the per-event acceptance function directly from the data and determines the effective lifetime to be τ B 0 s →K + K -= 1. 407 ± 0. 016 (stat) ± 0. 007 (syst) ps, which is compatible with the prediction of 1. 395 ± 0. 020 ps. The measured value is significantly more precise than and supersedes the previous LHCb measurement of this effective lifetime from the same dataset  [7] , but is statistically independent of the result in Ref. [6]. This measurement can be combined with measurements of ∆Γ s and Γ s , given in Ref.
Acknowledgements We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from  CERN  and from the national agencies:  CAPES ,  CNPq ,  FAPERJ  and  FINEP (Brazil) ;  NSFC (China) ;  CNRS/IN2P3  (France);  BMBF ,  DFG ,  HGF  and  MPG (Germany) ;  SFI (Ireland) ;  INFN (Italy) ;  FOM  and  NWO  (The Netherlands);  MNiSW  and  NCN (Poland) ;  MEN/IFA (Romania) ;  MinES  and  FANO (Russia) ;  MinECo (Spain) ;  SNSF  and  SER (Switzerland) ;  NASU (Ukraine) ;  STFC  ( United Kingdom );  NSF (USA). The Tier1 computing centres are supported by  IN2P3 (France) ,  KIT  and  BMBF (Germany) ,  INFN (Italy) ,  NWO  and SURF (The Netherlands),  PIC (Spain) ,  GridPP  ( United Kingdom ).
Statistical analysis Fisher's exact test was used for all analyses in the study. Firstly, the prevalence of S. glossinidius was examined for differences between the three species of tsetse studied in the current work. Secondly, the data was examined to assess if detection of S. glossinidius was associated with trypanosome presence. Finally, the prevalence of trypanosomes was examined to look for statistical differences between and within tsetse species. As T. vivax completes its lifecycle exclusively within the proboscis of the fly it was excluded from the analysis. All analysis was carried out in WinPepi (version 11. 32) and statistical significance was accepted at the 95% confidence level throughout.
ITS-PCR (T. brucei s. l. , T. vivax, T. godfreyi, T. simiae and T. congolense) and SRA-PLC-PCR (T. b. rhodesiense) were used to detect trypanosomes in G. brevipalpis, G. m. morsitans and G. pallidipes from Luambe National Park, Zambia. Number of flies examined has been provided for ITS-PCR and then SRA-PLC-PCR. The latter is lower as flies not positive for PLC were removed from this dataset. detected (38. 3%) involved T. brucei s. l. in partnership with T. vivax, T. congolense, T. godfreyi T. simiae Tsavo or T. simiae. There were nine flies (7. 8%) where DNA from three trypanosome species was amplified, all of which were positive for T. vivax, T. brucei s. l. and T. congolense DNA.
Acknowledgments We would like to thank  John Silutongwe ,  John Mashili  and  Lyson Phiri  ( Kakumbi Field Research Station, Department of Veterinary and Tsetse Control Services, Zambia ) for technical support and  Kepson Chansa  ( Zambian Wildlife Authority ) for logistical support. We would also like to thank  Professor Michael Thrusfield  ( University of Edinburgh ) for his statistical advice and  Professor Ian Maudlin  ( University of Edinburgh ) for discussions on the manuscript. Simon Durkin  acknowledges the  Wolfson Foundation  Intercalated Award for support during is studies on the  Infectious Diseases Honours programme at the University of Edinburgh. Neil Anderson  would like to thank the  Royal Zoological Society of Scotland  for financial and logistical support and the  United Kingdom Department for International Development Animal Health Programme (DFID-AHP)  for financial support.
7 ) 7 ITS-PCR (T. brucei s. l. , T. vivax, T. godfreyi, T. simiae and T. congolense) and SRA-PLC-PCR (T. b. rhodesiense) were used to detect trypanosomes in G. brevipalpis, G. m. morsitans and G. pallidipes from Luambe National Park, Zambia. Number of flies examined has been provided for ITS-PCR and then SRA-PLC-PCR. The latter is lower as flies not positive for PLC were removed from this dataset. detected (38. 3%) involved T. brucei s. l. in partnership with T. vivax, T. congolense, T. godfreyi T. simiae Tsavo or T. simiae. There were nine flies (7. 8%) where DNA from three trypanosome species was amplified, all of which were positive for T. vivax, T. brucei s. l. and T. congolense DNA.
Soil samples Soil samples were provided by the Soil Genetic Resource Conservatory (platform GenoSol, http://www. dijon. inra. fr/ plateforme_genosol,  [41] ) and obtained from the soil storage facility of the RMQS (''Reseau de Mesures de la Qualitedes Sols'' = French Monitoring Network for Soil Quality). The RMQS database consists of observations of soil properties on a 16-km regular grid across the 550000 km 2 French metropolitan territory and was designed to monitor soil properties  [42]. The baseline survey consisting of 2,200 sites (each corresponding to a composite soil sample constituted of 25 soil cores) was completed in 2009. The sites were selected at the centre of each 16616-km cell. In this study, we focused on a subset of 413 sites from the RMQS data set. The samples were organized into four regions: Brittany (131 sites), Burgundy (109 sites), Landes (52 sites) and South-East (121 sites, Fig.
Image analysis. The data were analyzed using the 1D-Scan software (ScienceTec), converting fluorescence data into electrophoregrams, where peaks represented PCR fragments (100 to 110 peaks retained per sample, the resolution limit to avoid considering background noise). The height of the peaks was calculated in conjunction with the median filter option and the Gaussian integration in 1D-Scan, and represented the relative proportion of the fragments in the total products. Lengths (in base pairs) were calculated by using a size standard with bands ranging from 200 to 1659 bp. The data were then converted into a contingency table with prepRISA package in R.
This study was granted by  ADEME (Energy and Environment Management Agency)  and by the  French National Research Agency (ANR). RMQS soil sampling and physico-chemical analyses were supported by a  French Scientific Group of Interest  on soils: the '' GIS Sol '', involving the  French Ministry for Ecology and Sustainable Development (MEDAD) , the  French Ministry of Agriculture (MAP) , the  French Institute for Environment (IFEN) , the  French Agency for Energy and Environment (ADEME) , the  French Institute for Research and Development (IRD)  and the  National Institute for Agronomic Research (INRA). This work, through the involvement of technical facilities of the  GenoSol platform of the infrastructure ANAEE378 Services , received a grant from the  French state via the National Agency for Research  under the program '' Investments for the Future '' (reference  ANR-11-INBS-0001 ), as well as a grant from the  Regional Council of Burgundy.
Retrievals for the stratosphere have only limited data quality and are not extensively validated. A particular advantage of using AIRS radiances instead of retrieved temperatures is that radiance data are available at the nominal sampling grid. In contrast, AIRS operational temperature retrievals have degraded horizontal resolution as 3 × 3 footprints are combined within a cloud-clearing procedure before the retrieval. Hoffmann and Alexander (2009)  developed a dedicated retrieval scheme for high-resolution stratospheric temperature data from AIRS to overcome some of these problems. However, no comparable data set is available for IASI. AIRS radiance measurements have been successfully exploited for a large number of gravity wave studies. For instance,  Alexander and Teitelbaum (2007) ,  Eckermann et al.
(2007) ,  Limpasuvan et al. (2007) ,  Alexander and Teitelbaum (2011) , Niranjan  Kumar et al. (2012) , and  Jiang et al. (2013)  used AIRS data to study orographic waves at hotspots like the Antarctic Peninsula, the Andes, the Greenland topography, and the Himalayas. Eckermann et al. (2009) ,  Lambert et al. (2012) ,  and Orr et al. (2014)  used AIRS observations to study the impact of mountain waves at high latitudes on the formation of polar stratospheric clouds. Hecht et al. (2009) ,  Kim et al. (2009) ,  Grimsdell et al. (2010) ,  Choi et al. (2012) , and  Yue et al. (2013 Yue et al. ( , 2014) )  used AIRS data for case studies of convective waves related to deep convection and hurricanes. Furthermore, AIRS data have also been applied in several climatological studies of stratospheric gravity wave activity.
Hoffmann and Alexander (2010)  presented a climatology of convective waves during the North American thunderstorm season. Eckermann and Wu (2012)  discuss orographic gravity-wave activity in the winter subtropical stratosphere over Australia and Africa. Gong et al. (2012)  presented the first global climatology of gravity wave variances from AIRS. Alexander and Grimsdell (2013)  studied the seasonal cycle of orographic gravity wave occurrence above small islands in the Southern Ocean. Hoffmann et al. (2013)  used AIRS data to identify local hotspots of stratospheric gravity wave activity on a global scale. In contrast, IASI data have not been used for gravity wave research so far. Yet, the measurement characteristics of AIRS and IASI are quite similar. Both instruments operate in nearly polar, sun-synchronous low-earth orbits, have across-track scanning capabilities with similar spatial sampling patterns, and provide hyperspectral radiance measurements covering the mid-infrared spectral region.
059 K for AIRS and NEDT ref = 0. 15 K for IASI, both at T ref = 250 K (see Fig. 6 ). This means the IASI noise at 4. 3 µm is about 2. 4 times larger than the AIRS noise. In other parts of this study we applied the noise scaling curves to determine the noise based on given scene temperatures rather than estimating it individually for each scene. This provides stable results even in scenes with strong wave activity where direct noise estimation from the scene data may fail. Finally, note that we had to carefully screen the AIRS and IASI data for outliers. In particular in the IASI data we found a few individual footprints with unrealistically large deviations in the 4. 3 µm brightness temperatures compared to their direct neighbors. Such individual outliers distort the polynomial fit for background estimation and subsequently cause substantial errors in variance estimation.
For both AIRS and IASI, we evaluated the operational data quality flags to exclude footprints with degraded data quality. However, for IASI we found that the operational data quality flags do not capture all outliers in the 4. 3 µm radiances. In some scenes with very low brightness temperatures, which are often related to deep convective clouds in the line of sight, calibration procedures can fail and physically unrealistic spectra are produced. We identified such spectra by means of a correlation test. We calculated the Pearson linear correlation coefficient ρ between the test spectrum and a mid-latitude clearair reference spectrum in the spectral interval from 2320 to 2370 cm -1. If ρ dropped below a latitude-dependent threshold (0. 0 at the equator, -0. 7 at the poles, and linear interpolation in between) the footprint was excluded from further analyses.