dataesr/scientific-paragraphs-categorization huggingface dataset:
Transmission electron microscopy (TEM) was performed using a JEOL 2010 electron microscope operating at 200 kV. Samples for analysis were crushed and homogeneously dispersed in ethanol by ultrasonication and a drop of the suspension was deposited on a carbon-coated copper grid and evaporated. Up to 200 individual Au particles were counted for each catalyst and the mean metal particle sizes are given as the surface areaweighted average (d) according to (1)   where n i is the number of particles of diameter d i. XPS spectra were collected on a SPECS (Phoibos MCD 150) X-ray photoelectron spectrometer using an Al Kα (hν = 1486. 6 eV) X-ray source. The binding energies (BE) were calibrated with respect to the C-C/C-H component of the C 1s peak (BE = 284. 7 eV). Spectral processing was performed using the Casa XPS software package.
Participants and procedure Adult patients who underwent partial or complete insular resection for control of drug-resistant epilepsy in our epilepsy service, during the period extending from November 2004 to June 2014, were all invited to participate in a study on the neuropsychology of the insula, except for one patient who presented with behavioral problems prior to his surgery. All of the 19 patients accepted our invitation. Two were excluded after data collection because they had an additional resection involving a significant part of the PFC that may have affected their results, and four additional patients were excluded because they had temporal lobe resection in addition to insular resection. Figure  1  depicts resection overlap among insular patients. These patients were matched with a group of patients who had their epilepsy surgery in the anterior temporal lobe that spared the insula.
g. (learning phase raw score/2) vs (test phase raw score/3)] using Wilcoxon non-parametric tests. Finally, we used Chi-square tests to compare the proportions of participants in each group failing to show any preference for advantageous over disadvantageous decks on the IGT (i. e. sum of raw score for trials 41-100 0) and obtaining a raw score of 3 or less in sensitivity to EV for the gain and loss conditions on the Cups Task. Statistical analyses were performed using SPSS 22. 0 software (SPSS, Chicago, IL).
Generation of Genetically Modified Arabidopsis Plants Using the CRISPR/Cas9 Genome Editing System The AtSTP1 gene was targeted using the CRISPR/Cas9 system  (Jinek et al. , 2012)  using a protocol adapted from  Fauser et al. (2014). CRISPR  PLANT (Xie et al. , 2014)  and RGEN TOOLS  (Park et al. , 2015)  softwares were used to design a 20 bp spacer sequence complementary to a region located in the third exon of AtSTP1 gene (Supplementary Figure  1A , Supplementary Table  1 ). This sequence was inserted into the BbsI restriction site of the pEn-Chimera plasmid  (Fauser et al. , 2014). The customized sgRNA cassette was then transferred into the pDe-Cas9 vector  (Fauser et al. , 2014 ) using a single site Gateway LR reaction. The resulting plasmid was transferred into A. tumefaciens GV3101 (pMp90) strain by heat shock for subsequent floral dipping transformation in Col-0 plants  (Clough and Bent, 1998).
Primary transformants (T1) were selected according to their Basta resistance. To genotype AtSTP1 lines, genomic DNA was extracted from 100 T2 plants coming from 2 independent T1 lines. The detection of the T-DNA was performed by PCR using primers located on the Cas9 gene (Supplementary Table  1 ). 26 T-DNA-free plants were selected and tested for the presence of mutations in the target locus by High Resolution Melting-curve (HRM) analysis (data not shown). Three plants exhibiting divergent meltingcurves from the wild type were regarded as edited, and mutations were confirmed via Sanger sequencing (BigDye Terminator v3. 1, Applied Biosystems). Mendelian inheritance of mutations and lack of the T-DNA were confirmed in T3 generation by sequencing and basta resistance (Supplementary Figure  1B ).
ACKNOWLEDGMENTS We thank  Dr. Puchta  and his team ( Botanical Institute II, Karlsruhe Institute of Technology, Karlsruhe, Germany ) for kindly providing the CRISPR/Cas9 vectors. We are grateful to  Vincent Lebeurre  and  Bruno Faure  for helping us to produce the plants used in this study, to  Marina Perez Benitez  for her help in the correction of the manuscript, to  Cécile Vriet  for help with CRISPR/Cas9 vectors, and to our colleagues for inspiring discussions.
This paper presents measurements of distributions of charged particles which are produced in proton-proton collisions at a centre-of-mass energy of √ s = 8 TeV and recorded by the ATLAS detector at the LHC. A special dataset recorded in 2012 with a small number of interactions per beam crossing (below 0. 004) and corresponding to an integrated luminosity of 160 µb -1 was used. A minimum-bias trigger was utilised to select a data sample of more than 9 million collision events. The multiplicity, pseudorapidity, and transverse momentum distributions of charged particles are shown in different regions of kinematics and chargedparticle multiplicity, including measurements of final states at high multiplicity. The results are corrected for detector effects and are compared to the predictions of various Monte Carlo event generator models which simulate the full hadronic final state.
Furthermore, low-p T processes, arising from pile-up in which there is more than one interaction per beam crossing, may also affect the topologies of events involving an interaction with a high p T scale. An understanding of soft QCD processes is therefore important both in its own right and as a means of reducing systematic uncertainties in measurements of high-p T phenomena. The measurements presented in this paper use a methodology similar to that used at lower centre-of-mass energies at ATLAS  [18]. Events were selected from data taken in 2012 with a trigger overlapping with the acceptance of the tracking volume. This corresponds to a minimum-bias dataset based on inelastic pp interactions. The term minimum bias is taken to refer to trigger and event selections which are as unrestrictive as possible for the pp-induced final states.
The integrated luminosity of the data sample under study is 160 µb -1. Owing to improvements in understanding the material inside and around the ATLAS inner detector (ID), the uncertainties in the measured spectra are reduced by as much as 30-50 % compared to the analogous measurements at 7 TeV centre-of-mass energy  [18]. The following distributions are measured: 1/N ev • dN ch /dη , 1/(2πp T N ev ) • d 2 N ch /(dη dp T ) , 1/N ev • dN ev /dn ch , and p T vs n ch. Here, η is the particle's pseudorapidity, 1 p T is the component of the charged-particle momentum which is transverse to the beam direction, 2 n ch is the number of primary charged particles in an event, N ev is the event yield for a given event selection, and N ch is the total number of primary charged particles in all selected events in the data sample.
• Qgsjet-II  [35]  using the default tune. This model provides a phenomenological treatment of hadronic and nuclear interactions within a Reggeon field theory framework, and includes soft and semihard parton processes within the "semi-hard pomeron" approach. Qgsjet-II was also developed for the simulation of cosmic rays. Qgsjet-II and Epos calculations do not rely on the standard PDFs as used in the Pythia generators. The Pythia 8 A2, Pythia 6 AMBT2B and Epos LHC models were used to generate event samples which were processed by the Geant4-based  [36]  ATLAS simulation framework  [37]. The simulation also takes into account inactive and inefficient regions of the ATLAS detector. The resulting datasets were used to derive corrections for detector effects and to evaluate systematic uncertainties.
8 mm, was applied in order to minimise correlations between the trigger and vertex efficiency corrections. The trigger efficiency was calculated as the ratio of events triggered by the control trigger, in which the MBTS trigger also accepted the event, to the total number of triggered events in the control sample. It was determined separately for the trigger requirement in which the signal in at least one or two of the MBTS modules was above threshold. In order to maximise the recorded data yield, both triggers were combined such that either of the two triggers was required to trigger the event, in which case the corresponding trigger efficiency was applied; this was done due to pre-scale factors that evolved differently for each trigger during the run. The result for the trigger requirement in which the signal in at least one of the MBTS modules was above threshold is presented in Figure  3 (a) as a function of n BS sel for the most inclusive phase space.
Conclusion Measurements were made of distributions of primary charged particles produced in minimum-bias pp collisions at √ s = 8 TeV with the ATLAS detector at the LHC. The results are based on a dataset corresponding to an integrated luminosity of 160 µb -1. Distributions of primary-charged-particle multiplicities as well as pseudorapidity and transverse momentum spectra are shown. With the fiducial definition of primary charged particles that was used in this study (τ > 300 ps), the central primary-charged-particle multiplicity at η = 0 per event and unit of pseudorapidity was measured to be 5. 64 ± 0. 10 in events containing n ch ≥ 2 primary charged particles with transverse momentum p T > 100 MeV, and 2. 477 ± 0. 031 in events with n ch ≥ 1 and p T > 500 MeV. Using an extrapolation factor for short-lived charged particles with a lifetime between 30 < τ < 300 ps, the central primary-charged-particle multiplicity was measured to be 5.
Figure10: Data and MC simulation distributions of the average number of hits per reconstructed track as a function of pseudorapidity, η, in (a) the innermost layer of the Pixel detector, (b) the whole Pixel detector, and (c) the SCT detector (adding the average number of hits and inactive modules per track). The MC simulation distributions, made with Pythia 8 using the A2 tune, have been reweighted to match the reconstructed p T spectrum in data.
In addition, individual groups and members have received support from  BCKDF , the  Canada Council, CANARIE ,  CRC ,  Compute Canada, FQRNT , and the  Ontario Innovation Trust ,  Canada ;  EPLANET ,  ERC ,  FP7 ,  Horizon 2020  and  Marie Skłodowska-Curie Actions ,  European Union ;  Investissements d'Avenir Labex  and The ATLAS Collaboration.
Introduction In modern and future trains a huge amount of wireless communication devices is operating. Wireless communication is needed in terms of train-to-train (T2T) and train-toground (T2G) communication for safety like train collision avoidance and railway management or customer oriented services such as passenger internet access. Therefore, wireless communication is a key technology to increase railway transport efficiency and safety. Furthermore, to reduce costs and maintenance time, replacing wired connections with wireless communications is foreseen. Wireless connections may be used for simple sensors up to connecting whole train consists for the Train Control and Management System (TCMS). Applications like Closed Circuit Television (CCTV) especially may need connections with data rates in the Gbit/s domain.
The Wiedemann traffic model was implemented to describe road traffic for different scenarios. The second part was the modelling of the environment, where a stochastic model was chosen to draw the environmental surroundings such as buildings, parked vehicles, and trees. The third and last part is the modelling of the wave propagation. Here, ray tracing was used to simulate the multipath propagation from the transmitter to the receiver. A carrier frequency of 5. 2 GHz was used in the simulation. Results were validated against measurement data obtained using a RUSK ATM vector channel sounder operating at the same carrier frequency. The comparison between measurement and simulation showed that the proposed deterministic channel model fits well to measurement results and real-life scenarios. Ray tracing for T2G environments was investigated in the mm-wave band in  [57] , where a HST environment was considered including a transmitter mounted on the top of a fence while the receiver antenna was located on the top of the train.
All these data confirm that the PHY-US417 secreted by roots of the transgenic lines is active and able to release Pi from PA supplied to the growth medium. The ePHY-US417 overexpressing lines exhibited improved growth and Pi contents under Pi-limited conditions The growth rates of the ePHY US417 overexpressing lines were assessed on either MS or MS-P+PA media for 2 weeks. Under such Pi-limited conditions, the growth of wild-type control plants is significantly decreased compared to those grown on MS medium. By contrast, the transgenic lines (e4, e5 and e9) were only slightly affected when PA was supplied instead of Pi (Figure  2a ) and showed longer roots (>2-fold) and higher biomass levels (>2-fold), compared to control plants (Figure  2b, c ). Consistently, when grown on MS-P+PA medium, all three transgenic lines accumulated more Pi in their shoots than the wild-type plants.
Real-time quantitative PCR Total RNA free of residual genomic DNA was prepared from root tissues using the RNeasy extraction kit (Qiagen) and RQ1 RNAsefree DNAse (Promega). cDNA was synthesized from 2 lg total RNA using an oligo (dT) primer and M-MLV reverse transcriptase (Promega). Real-time quantitative reverse-transcription PCR (qPCR) was performed with a LightCycler 480 Real-Time PCR System using SYBR green dye technology (Roche) and specific primers as described by  Rouached et al. (2011). Data were analysed using the Roche LC480 software. Quantification of the relative transcript levels was performed using the comparative CT method  (Livak and Schmittgen, 2001; Rouached et al. , 2008). The relative expression of each gene was normalized to the level of ubiquitin10 transcript (UBQ10: At4 g05320) and expressed as relative values against wild-type plants grown in complete MS medium.
Context. Measurement of IGF-I is essential for diagnosis and management of patients with disorders affecting the somatotropic axis. However, even when IGF-I kit manufacturers follow recent consensus guidelines, different kits can give very different results for a given sample. Objectives. We sought to establish normative data for six IGF-I assay kits, based on a large random sample of the French general adult population. Subjects and Methods: In a cross-sectional multicenter cohort study (ClinicalTrials. gov Identifier: NCT01831648), we measured IGF-I in 911 healthy adults (18-90 years) with six immunoassays (iSYS, LIAISON XL, IMMULITE, IGFI RIACT, Mediagnost ELISA, and Mediagnost RIA). Pairwise concordance between assays was assessed with Bland-Altman plots for both IGF-1 raw data and standard deviation scores (SDS), as well as with the percentage of observed agreement and the weighted Kappa coefficient for categorized IGF-I SDS.
Healthy subjects The subjects were part of a large cohort of French healthy adults (VARIETE). The VARIETE cohort was an open, prospective, national, multicenter, non randomized study of healthy volunteers, designed to establish normative data for IGF-I and other hormones in the French general adult population representing all age groups (about 100 subjects per decade from 18 to 90 years) (ClinicalTrials. gov Identifier: NCT01831648). A total of 972 healthy subjects with BMI values between 19 and 28 kg/m² were recruited in 10 centers throughout France between 2010 and 2011. Our objective of including 1000 subjects was not achieved due to difficulties for obtaining an accurate number of subjects in the older age categories (>70 years) fulfilling all the inclusion criteria and without exclusion criteria before the end of our inclusion period.
Statistical methods The distribution of IGF-1 values obtained with each assay was skewed, and was thus first normalized by means of sex-and age-specific Box-Cox power transformation. Student's t test and Levene's test were then used to assess equality of means and homogeneity of variances between men and women in each age group. As men and women had significantly different IGF-1 levels, centile curves were constructed separately for each sex. Age-and sex-specific centile curves were constructed for each assay by using the LMS method  (12)  implemented in the GAMLSS software package version 4. 3-1 (15) of R software version 3. 1. 2 (2014-10-31) (R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.
Pairwise concordance between assays was assessed with scatter plots and Bland-Altman plots for both IGF-1 raw values and SDS values, as well as with the percentage of observed agreement (total number of agreements divided by the total number of patients tested with both assays) and the linearly weighted Kappa coefficient for categorized IGF-1 SDS  (16, 17). An overall kappa coefficient (  16 ) and Friedman's test were computed for global comparison of all assays at the same time. Landis and Koch's table was followed for interpretation of Kappa values  (18). Unless otherwise stated, SAS software was used for all statistical analyses (Statistical Analysis System, version 9. 4, SAS Institute, Cary, N. C. , USA).
In this study, as expected, the largest inter-centile intervals (and highest values) were obtained with the two assays calibrated with the old standard IRP 87/518 (IMMULITE and IGFI RIACT). Moreover, the three automated methods (iSYS, Liaison XL and IMMULITE), which should theoretically be the most reproducible, did not yield narrower reference intervals. For example, the iSYS automated method and the Mediagnost RIA manual method gave very similar intervals for both men and women in all age groups. Thus, the main source of variation does not appear to be analytical reproducibility. Using the same iSYS method and a similar transformation for normalizing data and constructing specific centile curves in the LMS method, our 2. 5 th and 97. 5 th percentiles were generally slightly higher and our intervals generally narrower than those reported by Bidlingmaier et al.
Acknowledgments The study was supported by a grant from  Programme Hospitalier de Recherche Clinique ,  French Ministry of Health ,  N° P081216 / IDRCB 2009-A00892-55  and by a grant from  Fond National Suisse  ,  P1GEP3_155694 , to  Dr Maria Mavromati. We thank for  Dr Hélène Agostini  and  Prof. Bruno Falissard  for their helpful comments. We also thank  Cisbio International , DiaSorin, IDS, Mediagnost, and  Siemens  for the kind donation of IGF-I kits.
Fluorescence measurement and data processing. Images were taken every 5 min with a digital camera (Canon, EOS D600). A light emitting diode (CoolLED pE-2, 550 nm) was used for the excitation of fluorophores. The recorded intensity in the red channel was found to be proportional with the dye concentration in the relevant range (0-100 mM). Images were analysed with homemade scripts using the standard toolbox in Matlab. Flow-induced target delivery. We used two independent dyes (fluorescein and resorufin). Solutions of fluorescein (alternatively resorufin) are prepared as followed: a mixture of oil and surfactant (at 1%(w/w) concentration) is prepared and equilibrated for several days with a fluorescein (alternatively resorufin) solution at 100 mM in a closed vessel. At the end of the incubation, the oil is recovered and loaded in a syringe.
Acknowledgements J. -C. B. acknowledges the financial support by the  SFB-755 Nanoscale Photonic Imaging , the  ERC  ( FP7/2007-2013 /ERC Grant  agreement  306385-SofI ), the  IdEx Bordeaux  and the  'Region Aquitaine '. B. R. acknowledges the  IMPRS for Physics of Biology and Complex Systems  for financing her fellowship. A. J. and K. S. aknowledge the support by the  IAESTE. P. G. and B. R. acknowledge additional support from the  GGNB doctoral school. Fruitful discussions with  Dr B. Hutchison ,  Dr E. Mayot  and  Dr V. Taly  are warmly acknowledged as well as the experimental support from  Dr E. Akoury  and  Dr M. Prior  and the technical support of the chemistry facility at the  Max Planck Institute for Biophysical Chemistry (Goettingen, Germany)  and at the  Centre de Recherche Paul Pascal (Pessac, France ).
AGRADECIMIENTOS Al CONICET, a la ANPCyT y al programa ECOS por el apoyo económico. Al IBR por el espacio y por la preocupación constante hacia el crecimiento profesional de todos. A Fito, por confiar en mí para este trabajo de tesis, y por enseñarme y ayudarme en este camino de formación. Gracias por darme la confianza para hacer preguntas y por permitirme siempre exponer lo que pensaba y formar mi opinión con criterio. A Leandro por dirigirme en su laboratorio y colaborar con mi proyecto. A los Fitomejoradores por su buena onda y compañía. A Nah por estar predispuesto a resolver cualquier problema que surgía, por las correcciones en mis trabajos, por enseñarme a mirar desde otros puntos de vista y por hacerme reír tanto. A Robi por ser mi compañera todos estos años, forjando una amistad que trascendió siempre lo laboral.
Se midió Pulsed Electron DOuble Resonance (PELDOR) entre las sondas para estimar la distancia entre dominios, tanto en forma libre como unida a ARN. La calidad de los datos obtenidos no permitió modelar con precisión la posible distribución de distancias. Por otro lado, se realizaron experimentos de Relajación Paramagnética Electrónica (PRE) midiendo la relajación producida en cada núcleo, la cual está relacionada con la distancia entre dichos núcleos y la sonda. Para la generación de estructuras posibles se trabajó con los programas Modeller y Rosetta, utilizando como molde estructuras cristalográficas disponibles en bases de datos. Con las medidas experimentales se seleccionó una subpoblación de estructuras que ilustra la dinámica entre los dominios cuando están libres utilizando código generado con el lenguaje Python.
Estudios bioinformáticos Para los estudios bioinformáticos se trabajó con en lenguaje Python 2. 7 (Python Software Foundation (http://www. python. org). Los códigos fueron escritos y ejecutados dentro del entorno de Jupyter notebook (https://jupyter. org/). Parte de los códigos utilizados se muestra en el anexo (sección 7. 3). Para la visualización de estructuras en tres dimensiones y para los alineamientos estructurales se utilizó el programa PyMOL (The PyMOL Molecular Graphics System, Version 2. 0 Schrödinger, LLC. ).
Construcción in silico de conformaciones posibles y selección de estructuras Para el modelado de estructuras de HYL1 con LBTs se utilizó el programa Modeller v 9. 19  86. Para la construcción del ensamble se trabajó con la herramienta PyRosetta  87  (http://www. pyrosettaorg/). La misma es una interfase para el programa de modelado molecular Rosetta basada en el lenguaje de programación Python. El proceso de generación de clusters a partir de cada matriz de distancia fue realizado con la librería de Python scipy. cluster. hierarchy. linkage con el modo "ward". La base de datos Uniprot  88  fue elegida para realizar la búsqueda inicial dado que es líder mundial en el almacenamiento de información sobre proteínas. Entre sus características se destaca que es de acceso libre, está curada (en particular los registros de UniProtKB/Swiss-Prot están curados manualmente), y que cuenta con una interfaz gráfica de fácil manejo.