dataesr/scientific-paragraphs-categorization huggingface dataset:
Therefore, dilation as estimated by the model is lower than indicated by the test data. After a thorough re-examination of the test data and procedure, the authors believe that the way volumetric strain was estimated is probably inaccurate. During the tests, circumferential strain was mechanically measured with a ring wire. The volumetric strain was then estimated from that circumferential strain, assuming it was uniform along the height of the sample. Using that method, the volumetric deformation as shown in Figure  19  suggests that the pre-peak dilatancy angle would be approximately 60 o. This value is approximately three times higher than the peak friction angle as shown in Figure  12 , and is deemed to be unrealistic. Niandou et al. (1997)  performed triaxial tests on smaller Tournemire samples (37 mm in diameter, 75 mmm in height, versus 60 mm and 130 mm in this study).
Viscoelastoplastic modelling of creep test The calibrated viscoelastic constants shown in Table  2  were used as input to the finite element model shown in Figure  15  to verify that good agreement was achieved between the COMSOL results and the experimental data from the creep tests. Figure  18  shows the viscoelastoplastic modelling of the unconfined creep behaviour of Tournemire shale with different loading orientations. It is found that the modelling reproduces the test data very consistently. The relaxation time and the Maxwell shear modulus were determined to be 500 s and 3. 5 GPa, respectively, for all three loading orientations. Our results show that a unified set of parameters for the viscoelastic model applies to Tournemire shale, indicating the isotropy in viscoelasticity. This is in agreement with other reports on rheology of anisotropic clay rocks  (Zhang et al.
(g) Statistical analysis Analyses were carried out using the R statistical package (v. 3. 1. 2). To compare survival between uninfected and infected individuals, we used Cox proportional hazards mixed-effect models (coxme, coxme package). To compare the dynamics of bacterial infection, a linear model on log 10-transformed bacterial counts was employed with species, time point and the interaction between species and time point as fixed factors. To analyse the microbial community of both mite species, a linear model on the log 10 -transformed bacteria counts was employed with species and treatment as fixed factors. In both tests, the significance of the explanatory variables was tested using type I ANOVA. Pairwise comparisons between time points or treatments were performed using the lsmeans function of the package lsmeans.
Acknowledgements. We are indebted to several researchers for providing the biological material used here:  Jacek Radwan  ( Jagiellonian University, Poland ) for Sancassania berlesei,  Adriano Henriques  ( ITQB, Portugal ) for Bacillus megaterium and  Olivier Duron  ( MiVEGEC, France ) for the endosymbiont positive controls. We also thank the  Magalha ˜es, Sucena, Beldade and Mirth Labs for discussion ,  Francisco Dionı  ´sio (cE3c, FCUL, Portugal) for generously hosting some of the bacteria experiments,  Jacques Denoyelle  for help with the greenhouse,  Ines Santos  for keeping mite colonies and  Ioannis Livadaras  ( IMBB-FORTH, Greece ) for mite injection. We thank  David Duneau  ( Laboratoire E ´volution et DiversiteBiologique, Toulouse, France ) for suggesting the experiment in figure 4a,b and for comments following the critical reading of the manuscript.
Data reduction New Horizons scanned the LEISA imaging spectrometer across the planet several times on the closest approach date 2015 July 14. So far, two of the five highest spatial resolution scans have been calibrated, obtained from spacecraft slant distances of 112,045 km (#029,917,2014 at 9:33 UTC) and 99,856 km (#029,917,2889 at 9:48 UTC). The resulting sub-spacecraft spatial resolutions are 6. 95 and 6. 2 km/pixel, respectively. In combination, the two images cover the visible disk of Pluto and slightly overlap in the middle. The sub-solar latitude was 51. 55 °N and the sub-solar longitudes 133. 16 °and 132. 57 °E, respectively. The phase angle was 22. 0 °and 22. 8 °, respectively, at the sub-spacecraft point. The spectra of each data cube were reconstructed using the Integrated Software for Imagers and Spectrometers (ISIS) software provided by the United States Geological Survey (USGS).
Preliminary exploration of the data with PCA analysis In order to assess the spectral content of the data set and as a first try to separate the different chemical or physical components present on the surface and map their spatial distribution, we run a Principal Component Analysis with the ENVI © software  ( Jolliffe, 1986 ). We excluded the spectels #1, 2 and 198 (the last one) because they have strong photometric calibration caveats. We also excluded all pixels with incidence angles larger than 85 °as the reflected signal is noisier in this weakly illuminated and strongly shadowed area and the uncertainty on the incidence angle has strong effects on REFF photometry at these grazing angles. The result of this analysis is 9 Principal Components containing significant physical information and accounting for 94.
1% to 5%, its saturation concentration at 40 K) (black-blue-green curves in Fig. 17  and Fig. 18  ). We also ran the model for pure crystalline CH4 ice at 40 K with a series of grain sizes (from 10 μm to 3 cm) using the optical constants of  Grundy et al. (1995 Grundy et al. ( , 2002 ) )  (red curve in Figs. 17  and 18  ). Finally in order to asses any possible interference of water ice the model was run for pure crystalline H2O ice at 40 K with a the same series of grain sizes using the optical constants of  Grundy and Schmitt (1997, 1998 )  (magenta curve in Fig. 18  ). All these laboratory data come from the GhoSST database ( http://ghosst. osug. fr ). Fig. 17  shows that the N2 band depth follows a quite complex pattern with the abundance of CH4, but generally increasing with grain size, except for high CH4 contents ( > 1%) where it gets negative values for grain sizes up to 3 cm.
22 B ). In Fig. 22  A they contribute very little to the high concentration of points with low index ( < 40) that have slightly negative values of N2 band depth, at about the same level as CH4-rich ice. Most of these points have medium to high CH4 band depth ( Fig. 22 B ). These pixels are most probably covered with centimetric/sub-centimetric grained N2-rich ice containing CH4 at high concentration that cannot be distinguished from CH4-rich ice on the basis of both CH4 and N2 band depths, as demonstrated by our simulations ( Figs. 17  and 18  ). Thanks to the CH4 bands position index this type of N2-rich ice can now be readily distinguished from CH4-rich phases. Indeed the laboratory data show that the shift for CH4 diluted at saturation (5%) in N2 ice relative to CH4-rich ice is still -4.
589 μm) of the CO band, situated at the beginning of the wing of the 1. 66 μm CH4 band, is somewhat sensitive to the intensity of this band and to the type of CH4 present (CH4-rich or diluted in N2-rich ice) as a result of the spectral shift of the band. Both modulate the level and curvature of the 'CH4 continuum' below the CO band, and thus also partly the CO band depth as defined in Eq. (3). When Eq. (  3 ) is applied on the raw data the main structure of the CO band depth map can be barely determined only after spatial binning to 12 × 12 pixels (see Fig. 1  C in  Grundy et al. , 2016 ). The full spatial resolution integrated CO band depth map calculated on the CO-PCA reduced noise data cube is presented in Fig. 24. In order to take into account the uncertainties on the continuum we have set a conservative detection threshold at 20% of the near-maximum value (95% of the values), i.
Data references [dataset] Grundy, W. , Quirico, E. , and Schmitt, B. NIR Optical constants spectra of beta-N2 crystal at 4 different temperatures. GhoSST / SSHADE database. 1992. https://sshade. eu/old-ghosst/ experiment/EXPERIMENT _ BS _ 20120925 _ 003. [dataset] Grundy, W. , and Schmitt, B. NIR Optical constants spectrum of H2O liquid at 26 different temperatures (20-270 K). GhoSST / SSHADE database. 1997. https://sshade. eu/old-ghosst/ experiment/ EXPERIMENT_BS_20,120,924_011. [dataset] Grundy, W. , Schmitt, B. , and Trotta, F. Vis-NIR-MIR optical constants spectrum of crystalline CH4-I at 39 K. GhoSST / SSHADE database. 1995. https://sshade. eu/old-ghosst/experiment/ EXPERIMENT _ BS _ 20130219 _ 003. [dataset] Quirico, E. , and Schmitt, B. NIR optical constant spectra of CH4 in solid solution in beta-N2 at 4 different temperatures (36.
Acknowledgments This work was supported by  NASA 's New Horizons Project. B. Schmitt ,  S. Philippe ,  R. Côte  and  E. Quirico  acknowledge the  Centre National d'Etudes Spatiales (CNES)  for its financial support through its " Système Solaire" program. S. Protopapa  gratefully thanks the  NASA Grant and Cooperative Agreement  for funding that supported this work (grant #  NNX16AC83G  ). We acknowledge  M. Gorbacheva  for two illustrations of the paper and  E. Lellouch  and an anonymous referee for their very constructive reviews.
Data collection Within 24 hours of each patient's hospitalization, the geriatrician, as part of routine care, conducted a patient and/or caregiver and general practitioner interview and chart review to collect the following data: sociodemographic details, current medications with the Anatomical Therapeutic Chemical classification (http://www. whocc. no/atc/structure_and_ principles/), chronic diseases, and cognitive abilities. Main reason for admission, drug prescriptions on discharge, and reasons underlying treatment modifications during hospital stay were also specified in the hospitalization chart as part of routine care. All these data were compiled for analysis. PIM was defined as the presence of the drug on one of the following lists: STOPP and START criteria,  16  and BEERS criteria.
statistical analysis We performed descriptive statistics to illustrate the characteristics of the study population. The primary outcome was the prevalence rate of therapeutic modifications (stop, switch, or introduction) with 95% bilateral CI. Multivariate logistic regression analyses were performed to identify the factors associated with therapeutic discontinuation. P-values ,0. 05 were considered statistically significant. All the analyses were performed with STATA 11. 2 software (College Station, TX: StataCorp LP).
Genomic profiling of tumor biopsy DNA and RNA were purified from tumor tissue from the third resection preserved in RNALater (Life Technologies) using total AllPrep DNA/RNA purification kit (Qiagen). For whole-exomesequencing (WES), DNA libraries were prepared by fragmentation on Covaris S2 (Agilent) and adaptor ligation using KAPA HTP Library Preparation Kit. Exomes were enriched with SureSelectXT Clinical Research Exome kit (Agilent). WES was performed as paired-end sequencing using the HiSeq2500 platform from Illumina. RNA-sequencing was done using TruSeq Stranded Total RNA Library Prep Kit, and RNA was sequenced on a NextSeq500 (Illumina). Raw sequencing data from the Illumina sequencing platforms were processed with CASAVA-1. 8. 2. Generated fastq files were analyzed in CLC Biomedical Genomics Workbench (Qiagen) and Ingenuity Variant Analysis (Qiagen).
Microarray analysis CytoScan assay (Affymetrix) was performed on DNA from fresh-frozen specimen achieved by tumor biopsy, according to the manufacturer's instructions. CEL files from CytoScan assay were imported into NEXUS (BioDiscovery) and used for the analysis and visualization of copy number aberrations (CNAs) and loss-of-heterogeneity (LOH). CNAs (loss, gain, biallelic loss or high amplification) and LOH calls for each sample were confirmed by visual inspection and followed by manual interpretation of whole genome profiles. In general, presence of numerical and segmental aberrations was assigned for each chromosome. CEL files are available at the ArrayExpress database under accession numbers E-GEOD-4780 and E-MTAB-1852. RNA isolated as described above was reverse transcribed and used for cRNA synthesis, labeling and hybridization with Human Genome U133 Plus 2.
0 Array (Affymetrix) according to the manufacturer standard protocol available at www. affymetrix. com. Briefly, the arrays were washed and stained with phycoerythrin conjugated streptavidin using the Affymetrix Fluidics Station 450, and the arrays were scanned in the Affymetrix GeneArray 3000 7G scanner to generate fluorescent images. Cell intensity files (. CEL files) were generated in the GeneChip Command Console Software (AGCC; Affymetrix). Raw intensity. CEL files were preprocessed by quantile normalization, and gene summaries were extracted via robust multi-array average  (19)  within the Qlucore Omics Explorer™ software. Expression values for the genes were derived as an average of probe set for the particular gene. Data were randomized using permutation. Difference in the ROS1 gene expression between the patient sample and the external data sets was determined by t-test.
Recent technical advances allow a broad comprehensive examination in order to identify relevant treatment targets in this rare pediatric entity, which can be crucial for the clinical course. In agreement with this, a BRAF V600E mutation was identified in a rhabdoid meningioma in a 6-year-old girl, who showed good clinical response to the BRAF inhibitor dabrafenib  (22). Based on the identification of the fusion transcript in his tumor, our patient was enrolled in the AcSé crizotinib trial (NCT02034981) running in France. This is a phase II basket trial exploring the activity of crizotinib in malignancies with ALK, ROS or MET alterations, other than ALK+ non-small cell lung cancer, in children, adolescents and adults with advanced relapsed or refractory disease  (23). He has now been treated with oral-crizotinib (215 mg/m 2 twice daily) for 14 months with an excellent tolerance and one dose reduction after 4 cycles due to non-symptomatic G3 QTc prolongation.
Acknowledgments We are very grateful to  Dr. David Capper  and the team at  DKFZ ,  Institute of Neuropathology, University Hospital Heidelberg, Germany , for methylation array analysis and indeed to both  Prof. Dr. Werner Paulus ,  Institute of Neuropathology, University of Münster , and  Prof. Dr. Arie Perry , The  Department of Pathology at the University of California, San Francisco, USA , for histopathological review. We thank  Vibeke Blåbjerg  and  Miriam Yan Juk Guo  for excellent laboratory assistance. The AcSé crizotinib trial is sponsored by  Unicancer  with support by the  French National Cancer Institute (INCa)  and  Fondation ARC.
Some studies have focused on the ecology and biology of invasion of the lime leaf miner  [6, 17, 18, 31]. However, nothing is known about its phylogeography and genetics of invasion. Here we studied mitochondrial DNA sequence variation across P. issikii distribution range from its presumable native regions (East Asia) to its most recently invaded regions (Europe, Western Russian and Siberia). Our aim was to identify the haplotypes which most commonly represent in the invaded region and to investigate they occurrence in East Asia. In addition, we gathered morphometric and nuclear data to test whether the different genetic clusters, revealed by the phylogeographic analysis, represent a complex of cryptic species. map showing distribution of P. issikii and its host plant Tilia spp. extracted from various sources  [6, 13, 14, 15, 17, 21, 25, 28, 29, 37, 38, 39, 40, 41, 42].
We studied P. issikii samples from 10 different Tilia host plant species, six species in East Asia (T. mandshurica, T. maximowicziana, T. amurensis, T. japonica, T. taquetii and T. mongolica) and four species in Europe, Western Russia and Siberia (T. cordata, T. sibirica, T. platyphyllos and T. dasystyla); 13 lime trees surveyed in the Russian Far East and in Europe have not been identified to the species level. In total, 155 out of 387 studied specimens (i. e. 40%) were collected from T. cordata (S1 Table ). Detailed collection data and host plant list is provided in S1 Table. In order to avoid sampling the related individuals, whenever possible, a single individual insect was collected per tree, and up to 30 trees were sampled by locations. As no other monophagous species of Phyllonorycter exists on Tilia in the Palearctic, we used the related Nearctic species, Phyllonorycter lucetiella (Clemens, 1859), developing on Tilia, to root the genetic trees.
These two nuclear genes are widely used in reconstruction of the phylogeny of Gracillariidae  [46, 47, 48]  and were used here to assess cryptic diversity. PCR amplification with H3 gene was done at the following conditions: 40 cycles (1 min at 94˚C, 1 min at 45˚C, 1 min at 65˚C) and with 28S 30 cycles (45 s at 94˚C, 50 s at 57˚C, 1 min at 72˚C)  [45]. One specimen of the North American Tilia-feeding Phyllonorycter lucetiella was also sequenced for COI, Histone 3 and 28S genes to be used as outgroup. All specimens were bidirectionally sequenced using BigDye sequencing protocol (Applied Biosystems 3730xl). All electropherograms (for mitochondrial and nuclear genes) were checked manually in CodonCode Aligner ver. 3. 7. 1. (CodonCode Corporation) to assess their quality. Alignment was done in BIOEDIT ver.
7. 1. 7 and each nucleotide variation was double checked to confirm each haplotype  [49]. No pseudogenes or stop codons were detected in the sequences. All COI sequences of P. issikii and the putative new species were trimmed to the same length for a final alignment (618bp). Nuclear gene sequences for both insects represented the whole length, i. e. 328 bp for H3 and 940 bp for 28S. Details on the collecting data for each specimen, as well as a photograph of vouchers, sequence records, trace files, and primer sequences used for PCR amplification, together with GenBank accession numbers are available through the following dataset (dx. doi. org/10. 5883/ DS-TILIAPHY) in BOLD (www. boldsystems. org).
Statistical analysis Sampling area and geographic distribution of COI haplotypes was displayed with an altitudinal background using ArcGIS 9. 3  [51]. For European countries, data were pooled together to represent a particular country, whereas in Russia, given the large size of the country, and in the Eastern Asia, haplotype diversity was indicated for all studied localities. Haplotype diversity was calculated using DnaSP v 5. 10. 1  [52]. Intra-and interspecific genetic distances were estimated using the Kimura 2-parameter model implemented and a barcode gap analysis was carried out within the analytical tools available in BOLD. A neighbor-joining (NJ) tree was constructed using MEGA 6. 0  [53]. Correlation between genetic diversity and number of specimens per location was assessed with nonparametric Spearman rank R (p < 0.
05). Nonparametric Mann-Whitney U test was used to check for differences in genetic diversity between groups of populations (invaded vs. native areas) because the original  To investigate relationship among haplotypes within P. issikii and a putative new species of Phyllonorycter, the median-joining haplotype networks were built with the program TCS 1. 21 implementing a statistical parsimony algorithm  [54]. To identify sources of genetic variance in the COI sequence data, a nested analysis of molecular variance (AMOVA) was applied using the program Arlequin 3. 5. 13 [55]. Two variants of grouping by geographical region have been tested. In the first case, two groups were defined: (i) the presumable invaded area: Europe, Western Russia, Siberia and (ii) the presumable native area: Russian Far East, Japan, South Korea and China.
In the second case, we tested three groups: the first group (the presumable invaded area) remained as above, whereas the second group (the presumable native area) was divided into two: one subgroup represented the Russian Far East, South Korea and China and the other-Japan, from where the insect was originally described. Three sources of variation were taken into account: among groups, among populations within groups and within populations. The significance of the variance components was assessed with the nonparametric permutation method using 10 000 permutations. Dataset of male genital measurements, prior to analysis, was tested for normality by the Shapiro-Wilk and Kolmogorov-Smirnov tests  [56]. Since morphometric data was normally distributed based on fit distribution procedure for each morphometric parameter (length of phallus: Shapiro-Wilk W = 0.
97, p = 0. 48, Kolmogorov-Smirnov D = 0. 06, p > 0. 20; left valva: W = 0. 96, p = 0. 11, D = 0. 88, p > 0. 20; left spine: W = 0. 93, p = 0. 12, D = 0. 83, p > 0. 20; right spine: W = 0. 91, p = 0. 15; D = 0. 13, p > 0. 20), the dataset was processed using a linear discriminant analysis  [57] , with species as categorical dependent variable and four genital characters (length of phallus, left valva, left spine and right spine) as continuous independent variables. Prior to the analysis, 10-fold cross-validation procedure was performed (the averaged Wilks' λ = 0. 26 ± 0. 02, F-value = 29. 16 ± 2. 69, p < 0. 0001; APCC for the training samples = 98. 43 ± 0. 54%, APCC for validation samples = 98. 33 ± 1. 83%), which proved high accuracy of the observed classification  [57]. The analyses were performed in STATISTICA 8.
Morphometric analysis The study of moth wing pattern showed no differences between western and eastern populations of P. issikii neither between P. issikii and the cryptic Phyllonorycter species from East Asia. Nevertheless, morphometric analysis of male genitalia pointed at some differences between geographically remote P. issikii populations. Discriminant analysis based on the morphometry of four genital characters (length of left valva, left spine, right spine and phallus) indicated discrepancy in the analyzed dataset and proved the presence of two clusters (Wilks' λ = 0. 27, F (4; 47) = 34. 02, p < 0. 0001, APCC-average percent of correct classification = 98%). Two out of four genital characters (i. e. length of right spine and phallus) played curial role in delineation of these clusters.
Molecular data (both mitochondrial and nuclear) suggests presence of an undescribed cryptic species of Phyllonorycter in East Asia. Indeed, the minimum pairwise genetic distance between P. issikii and the putative new species (3. 66%) is similar to what we found in other groups of Phyllonorycter  [78]. Specimens of the putative new species, (mines with larvae and pupae), were collected together with those of P. issikii, as they were undistinguishable. Despite both species occur in the same locations and shared same host plants with P. issikii (particularly, T. maximowicziana, T. japonica, T. amurensis, T. mandshurica and T. taquetii), we recorded no case of introgression. Surprisingly, the putative new species is rather abundant in the Russian Far East and Japan. We found it in more locations than P.
Acknowledgments We are grateful to number of colleagues:  G. Deschka ,  H. Deutsch ,  P. Huemer ,  G. Stangelmaier ,  C. Wieser  (Austria),  C. Doorenweerd  (Netherlands),  S. Gomboc  (Slovenia),  T. Gruenewald ,  A. Segerer  (Germany),  P. Ivinskis  (Lithuania),  J. -F. Landry  ( Canada ),  A. Lastuvka  ( Czech Republic ),  M. Mutanen ,  T. Mutanen  (Finland),  L. Szőcs  (Hungary),  V. Anikin ,  A. Bryukhanov ,  S. Gorohova ,  D. Musolin ,  V. Ponomarev ,  J. Timofeeva ,  M. Tomoshevich ,  V. Zolotuhin  (Russia), and  T. Kanbe  ( Japan ) for sharing samples of P. issikii, and/or unpublished barcodes, and  J. -F. Landry  ( Canada ) for sharing the samples of North American species Phyllonorycter lucetiella. We thank  A. Kupryanov  ( Russia ) who allowed us to sample P. issikii specimens in the protected Siberian lime groove in Kuzedeevo (Kemerovskaya oblast, Russia),  S.