dataesr/scientific-paragraphs-categorization huggingface dataset:
Determination of binary and ternary VLE for the synthetic mixture at reduced pressure The working pressure of the batch distillation process of 15 kPa was defined by the industrial partner taking into account the vapour pressure model of DMC available in DPPR database (see Table  2 ) and fixing the condensation temperature of the distillate product at 313. 15K (the DMC boiling temperature at 15 kPa). Due to the closeness between the boiling and dew temperature curves at high composition of DMC in Fig. 4a  and 4c , potential loss of α-pinene and eucalyptol could happen during the DMC recovery by batch distillation process. The loss of these aroma molecules in the distillate will decrease the olfactive quality of the concrete recovered into the reboiler at the end of the batch distillation process.
Hence, reliable predicted values are expected because the molecule can be represented by simple chemical groups CH2, CH3, C=C and OH whose contribution parameters are well established based on the vast experimental data of molecules including these chemical groups. Normal boiling temperature of 429. 7 K is reported by Weast and Grasselli (1989) while Joback and Reid model (1987) provided 433. 02 K, which agrees well with the experimental value. 3. 2. 2 Vapour -liquid equilibrium database 3. 2. 2. 1 Thermodynamic modelling of the VLE of the synthetic mixture of six aroma compounds and DMC Thermodynamically speaking, natural plant extracts behave as non-ideal mixture due to the formation of hydrogen bonds, the dipole/dipole interactions between polar chemical functional groups such as hydroxyl group, ketones group, ester group, cyclic oxygen atom, Table 2 were determined from predicted values.
Performance assessment The NAS system has been designed for determining the total neutron yield during the DT operation. The system must provide also time-resolved measurements of the global neutron source strength and evaluation of the fusion power. Measurement of absolutely calibrated neutron flux and fusion power will be performed. Various tools are used for carrying out the analysis: • MCNP v. 5 (Monte Carlo N-Particle) transport code is used for the calculation of neutron fluxes and neutron energy spectra at the designated locations for the irradiation. • FENDL-2. 1 (Fusion Evaluated Nuclear Data Library) is used as the material database for the MCNP calculation • FISPACT-2007 is used for the inventory of neutron induced activation of the sample materials. • EAF-2007 (European Activation File) is used for the source of cross-section data for FISPACT-2007 • Lite series (A-lite, B-lite, and C-lite) 40° sector ITER geometrical model with a fusion plasma neutron source is used for the MCNP calculation.
Another requirement is to provide supplementary neutron flux data with a crude temporal resolution of about 10 s, when necessary for a backup or calibration of other flux measurement systems, such as Microfission Chambers (MFC) and neutron flux monitors (NFM). Thus, the activities of various samples are calculated with the irradiation of 10 s, and the result is shown in Figure  16. Neutron Activation System for ITER Tokamak http://dx. doi. org/10. 5772/intechopen. 75966 The activation desired for a sample should be similar to that provided by a standard source used for absolute calibration of the gamma-ray detectors. A typical maximum value for modestly safe handling would be 100 μCi. Figure  17  shows the fusion power needed to create 100 μCi samples assuming 10-s irradiation and 20-s cooling at a irradiation location D.
To position Corsicans in the context of their geographic neighbours we used an unsupervised clustering approach  31  implemented in the program ADMIXTURE  32. At the level of lowest cross-validation index (K = 6), Corsicans and geographically related populations are composed mainly by three ancestry components -"Sardinian", "Northern and Eastern Europe", "Caucasus and Middle East" (dark blue, light blue, and lime green respectively; Fig. 2 , Supplementary Figs  S2, S3 ). Corsicans are most similar to North-Central Italian populations (Piedmont, Lombardy, Tuscany), displaying a slightly larger proportion of a modal component in Sardinians. This similarity in ADMIXTURE profiles remains throughout higher levels of K values, even when further components appear (Fig. 2 , Supplementary Fig. S2 ).
Materials and Methods Sampling. A total of 49 DNA samples were genotyped for the current study. Sixteen Corsican samples were selected from a larger dataset  12  in order to maximize geographic coverage (Supplementary S1) and DNA quality criteria. All samples have grandparental origin in the geographic micro-regions of sampling locations. These Corsican samples have been analyzed previously in Y-chromosome surveys  12, 43, 44. To extend the comparative dataset, additional samples were analysed: ten Portuguese, five French samples from Provence, eleven Italian samples from Piedmont and seven Italian samples from Tuscany. Samples from Piedmont and Tuscany have been studied for Y chromosome  45  and Tuscany samples also for mitochondrial DNA  46. DNA samples have been collected from healthy unrelated individuals and all donors have provided informed consent.
Experiments were carried out in accordance with the relevant guidelines and regulations of collaborative institutions. The research has been approved by the Research Ethics Committee of the University of Tartu. Genome-wide SNP data. DNA was extracted from blood/saliva samples and genotyping was carried out on Illumina 660 K platform (Human660W-Quad BeadChip). New samples were combined with data from previous studies  [47] [48] [49] [50] [51] [52] [53] [54] [55]. In total, 892 individuals from 67 populations were analysed (Supplementary Table  S1 ). The merged dataset was preprocessed with PLINK v1. 9  56  in order to include only autosomal SNPs with minor allele frequency > 0. 005% and genotyping success > 97%. The cryptic relationships between samples of 1st and 2nd degree) were controlled with software KING v1.
ADMIXTURE. Maximum likelihood unsupervised clustering algorithm implemented in ADMIXTURE  32  was used to infer putative ancestral components in the Corsican population in a worldwide context. Clustering was performed 100 times at K = 2 to K = 15 (Supplementary Fig. S2 ). Convergence between runs was assessed using log-likelihood scores (LL). According to a low level of variation in LL scores (LLs < 1) within the top 10% fraction of runs with the highest LLs, the global maximum was assumed to be reached at K = 2 to K = 6, K = 9, K = 11 and K = 13 (Supplementary Fig. S3B ). The lowest cross-validation (CV) index, which points to the predictive accuracy of the model at a given K, was observed at K = 6 (Supplementary Fig. S3A ). f St. Mean population pairwise F ST and standard deviation values were calculated using software EIGENSOFT v.
ChromoPainter and fineSTRUCTURE. The haplotype-based structure of Corsicans and other European populations was explored by applying the ChromoPainter/fineSTRUCTURE pipeline  34. First, genotype data was phased with SHAPEIT v. 2 61 using default parameters and the HapMap phase II b37 genetic map. Subsequently, the painting profile of each individual was inferred using ChromoPainter. The nuisance parameters n and m were inferred by running ChromoPainter with -in -iM flags for 10 E-M iterations. Given the high computational requirements, the analysis has been carried out only on a subset of the data, using an approach similar to Montinaro et al. 2015  62. In detail, five (where available, otherwise using all the possible samples) individuals were randomly selected from each population. The inferred parameters were finally used in ChromoPainter specifying all the available samples as donors and recipients.
Projecting ancient Europeans into modern Eurasian variation. In order to contextualise the genetic variation of modern individuals in a European pre-Iron Age context, a PCA analysis was performed in which the ancient genotype data were projected into the PCA inferred on modern Eurasians (Fig. 5A ). For ancient samples, genotype data released by Lazaridis et al. 2017  63  and Olalde et al. 2018  64  were used, from which non relevant individuals and all the samples with more than 70% of missingness were removed. After the final filtering 222 samples were retained (Supplementary Table  S1B ). For modern samples, 568 West Eurasian Individuals were retained. In order to prevent the shrinkage bias in ancient individuals, the "autoshrink: YES" option was used. qpADM. The admixture profile of all the analysed populations was reconstructed with qpADM  39  , which harnesses a combination of f4 describing the relationship of "target" and "sources" with a set of outgroups.
Acknowledgements We thank all volunteers who donated their DNA samples. We would like to thank  Bayazit Yunusbayev  for helpful discussions,  Viljo Soo  for his help in genotyping and  Tuuli Reisberg  for assistance in data management. Computational analyses were performed at the  High Performance Computing Center of the University of Tartu. This research was supported by institutional research funding  IUT  ( IUT24-1 ) of the  Estonian Ministry of Education and Research (ET, EP) ; the  Estonian Research Council  grants  PUT (PRG243 ) (EP, MM) and  PUT  ( PUT1339 ) (AK); the  European Union  through the  European Regional Development Funds  with projects No. 2014-2020. 4. 01. 16-0030  (MM, FM) and No. 2014-2020. 4. 01. 15-0012  (MM); the  European Union  through  Horizon 2020  grant no. 810645  (MM); the  University of Pavia  strategic theme "Towards a governance model for international migration: an  interdisciplinary and diachronic perspective " (MIGRAT-IN-G) (OS); the  Italian Ministry of Education, University and Research (MIUR) :  Dipartimenti di Eccellenza Program  ( 2018-2022 ),  Dept.
Overview On 8 January 2018, the four MMS spacecraft observed a forward IP shock while approaching apogee (~25 R E ) beyond the bow shock very near the Sun-Earth line in the pristine solar wind. The orientation of the observed magnetic field provides evidence that the spacecraft were not magnetically connected to the Earth's bow shock at the time of the shock's passage. The event occurred during an interval along the MMS orbit when the highest time resolution (burst-mode) data were collected. Figure  1  shows lowertime-resolution MMS observations of the global-scale structure of the shock, which crossed the spacecraft at approximately 06:41:10. 7 UT (indicated by the vertical dashed line). In addition to the clear transitions between the unshocked and shocked plasmas, Figure  1  highlights the response of energetic particles to the shock.
Statistical analyses. We analysed the effects of herbivore species, season and their interaction on dung quality (C, N, P concentrations and ratios) with two-way unbalanced ANOVAs due to differences in number of dung samples per herbivore species and/or season. We performed a box-cox transformation on the dung quality data and we obtained type II Sums of Squares using the function ' Anova' in the 'car' package in R 29 (version 3. 4. 2). For the dung samples of the five herbivore species used in the mesocosm experiment these ANOVAs were followed by Tukey-Kramer HSD tests. The evenness of the experimental plant community was calculated based on Pielou's evenness index  28. To test for the effects of herbivore dung type and dung quantity on the evenness and total biomass of the experimental plant community we used two-way unbalanced ANOVAs due to the missing mesocosms (again type II SS with function ' Anova').
Acknowledgements We greatly acknowledge staff of the nature management organizations for permission for and help with herbivore dung sampling, in particular  Esther Rodriguez Gonzalez  ( Kennemerduinen) ,  Peter Boelens  and  Perry Cornelissen  (Oostvaardersplassen) and  Chris Dictus  ( Zwarte Beek Vallei ). We thank  Ruth de Groot  for help with dung sampling,  Marco Palombelli ,  Luisa Ramirez ,  Rahele Dezfulian  and  Martine Claeys  for help with harvesting, and  Claire Mourgues  and  David Verstraeten  for help with chemical analyses. We acknowledge feedback and suggestions to improve the manuscript from  Helmut Hillebrand ,  Elizabeth Borer ,  Elina Kaarlejärvi  and  Antje Van Laethem. J. S. was financially supported by a postdoc grant of the  Research Foundation Flanders (FWO) , grant  12N2615N.
Methods The REsect study, a retrospective analysis of the SIR-FLOX study patient cohort, was designed to determine the quasi-objective change in resectability of CRLM from baseline to follow-up after first-line treatment with mFOLFOX6 chemotherapy (oxaliplatin, folinic acid and fluorouracil regimen) with or without bevacizumab (control arm) or mFOLFOX6 with or without bevacizumab plus SIRT (SIRT arm) with 90 Y-labelled resin microspheres (SIR-Spheres ® ; Sirtex Medical, Sydney, New South Wales, Australia). As REsect relied on existing CT hepatic imaging data from SIRFLOX and no new data were acquired for the analysis, no formal ethics committee approval was needed. The SIRFLOX study was conducted in accordance with the Declaration of Helsinki, and approval was obtained from the relevant institutional review boards for each participating centre.
Patients All patients who had received first-line treatment for CRLM in the SIRFLOX study were eligible for inclusion in the REsect study. Patients had to have evaluable CT data at baseline and follow-up, and have received the allocated treatment. For enrolment in SIRFLOX, patients had to have histologically confirmed adenocarcinoma of the colon or rectum, with or without the primary tumour in situ, with proven liver-dominant metastatic disease. Patients had to be chemotherapy-naive, have a WHO performance status of 0-1, and a life expectancy of more than 3 months. Predefined stratification factors included the presence of extrahepatic metastases (liver-only versus liver-dominant metastatic colorectal cancer), hepatic tumour burden (25 per cent or less versus more than 25 per cent), intent to use bevacizumab, and treatment centre.
The protocol for this trial, with secondary resection rate and disease-free survival following resection as co-primary endpoints, is currently in development. M. Gilmour of ESP Bioscience (Crowthorne, UK), funded by Sirtex, during preparation of this article. This study was supported by Sirtex Medical (Sydney, Australia). Where patient data can be anonymized, the authors will share all individual participant data that underlie the results reported in this article with qualified researchers who provide a valid research question. Study documents, such as the study protocol and clinical study report, are not always available. Proposals should be submitted at www. sirtexgrants. com, and will be assessed by a scientific review board. Data are available from 6 months to 5 years after publication of this study; after this time, only raw data may be available.
On this basis, the t lag values calculated here are almost certainly minimum estimates. We note that, for our purposes, the calculation of t lag is not compromised by the Sadler effect  (Sadler, 1981). To further explore the stratigraphic response of SRSs to abrupt hydrological change, we utilize a one-dimensional (1-D) sediment transport model (see the GSA Data Repository 1 ). The model solves for the change in topography due to the transport of sediment downslope, which is a function of both local slope and surface water discharge  (Armitage et al. , 2016). Precipitation rate is increased from a baseline of 0. 5 m yr -1 following a box profile with a time to peak precipitation of 5 k. y. reflecting the time scale of PETM onset  (Westerhold et al. , 2018).
RESULTS The analysis shows that the Tendrui, Claret, and Campo sections exhibit a stratigraphic offset, but that the Esplugafreda section does not (Fig. 2 ). The calculated durations of the stratigraphic offset (t lag ) are: Tendrui, t lag = 13-24 k. y. ; 1 GSA Data Repository item 2019059, details of the 1-D sediment transport model and values used to calculate the duration of stratigraphic offset, is available online at www. geosociety. org/pubs/ft2019. htm, or on request from editing@geosociety. org. Claret, t lag = 9-16 k. y. ; Esplugafreda, t lag = 0 k. y. The lower rates of sediment accumulation at the Esplugafreda section (0. 1 m yr -1 ) has led to a reduced level of stratigraphic completeness  (Sadler, 1981; Straub and Esposito, 2013) , inhibiting proxy record preservation and precluding the identification of a resolvable t lag  (Foreman and Straub, 2017).
If consent is withdrawn, no data about the patient will be used unless the subject states in writing that he/she does not object. data collection, confidentiality, storage and archiving of study documents Data will be collected in an e-CRF, via a web browser with access restricted to investigators. Data will be completed by investigators for each follow-up visit with the help of an independent clinical research technician. Data from the hospital discharge database will be extracted directly from the hospital's information system. Patient identifiers will be removed and replaced by the inclusion number before transfer to the statisticians in charge of the cost-effectiveness analysis. All personnel involved in data analysis will be masked. Only the sponsor and statisticians will have access to the final data set.
statistical methods Since BLUE-CarbA is a non-inferiority study, the analysis of the primary end point will be performed on per-protocol population (all randomised patients without major protocol deviation or those who withdrew consent). 40 A sensitivity analysis will be performed following the intention-to-treat (ITT) principle (all randomised patients, except those who withdrew consent). Analysis will be performed blind to treatment groups. Missing data will be not replaced except for the principal criteria for the sensitivity analysis on ITT population. Missing value will be considered an event whatever the randomised group. Categorical variables will be reported per group as numbers and percentages, while continuous variables will be summarised using means (±SD) or medians (IQR) for normally and non-normally distributed data, along with their respective 95% CIs.
dissemination policy The results of the study will be released to the participating physicians and microbiologists and medical community through presentation at scientific conferences and publication in a peer-reviewed journal. The publication will acknowledge the sponsor (Clinical Research and Development Department of Assistance Publique-Hôpitaux de Paris, APHP, France) and the financier (Programme Hospitalier de Recherche Clinique 2015, French Ministry of Health). This study is registered on clinicaltrials. gov (NCT03147807). According to data-sharing policy, patient-level data that support the findings of this study will be available from the authors on reasonable request and with permission of the sponsor (Clinical Research and Development Department of Assistance Publique-Hôpitaux de Paris, APHP, France), owner of the data.
For each group of genes, normalized coverage (tag/nt) for each gene was piled up, and the average signal was plotted. The shading surrounding each line denotes the 95% confidence interval. (E) Snapshot of ChIP-Seq signals at the divergent GLT1/UGA3 promoter region. Densities (tag/nt) are shown for the untagged (black line) and DAL80-MYC 13 (blue line) strains. Genes are represented as grey arrows. The position (and orientation) of each GATA site is represented by vertical segments above (sense GATA sites) or below (antisense GATA sites) the locus line. The snapshot was produced using the VING software  [94]. (F) Number of GATA (GATAA, GATAAG or GATTAG) sites in the promoter of Dal80-unbound and promoter-bound genes. The analysis was performed using RSAT  [95] , across the -500 to -1 region (relative to the ATG codon of the downstream ORF).
1 (FV078; blue line) strains. Genes and tRNA are represented as grey and black arrows, respectively. The snapshot was produced using the VING software  [94]. (B) UGA4 expression in a DAL80ΔLZ mutant strain. WT (25T0b), DAL80-MYC 13 (FV078), dal80Δ (FV080) and DAL80ΔLZ-MYC 13 (FV136) cells were grown in proline-containing medium. Total RNA was isolated and UGA4 mRNA levels were quantified by qRT-PCR using UGA4 O1-O2 primers as in S1A Fig. (C) Occupancy of the UGA4 locus by Pol II. WT (25T0b), DAL80-MYC 13 (FV078), dal80Δ (FV080) and DAL80ΔLZ-MYC 13 (FV136) cells were grown in proline-containing medium. ChIP-qPCR analysis was performed as described in S3B.
P < 0. 00001 upon Chi-square test of independence. (F) Snapshot of RNA-Seq signals for the NCR-sensitive, Dal80-activated gene UGA3. RNA-Seq signals are visualized as a heatmap. The upper and lower panels show the signals for the + and-strands, respectively. The color turns from yellow to dark blue as the signal increases (scale on the right). The UGA3 mRNA is highlighted using the red box. The neighboring genes (YDL173W, GLT1 and YDL169C) are also indicated. The snapshot was produced using the VING software [94]. https://doi. org/10. 1371/journal. pgen. 1007999. g002 revNCR; Fig 4A; see also S4A Fig) and Dal80-regulated genes (Dal80-activated and -repressed; Fig 4B; see also S4B Fig) were significantly more represented in the P&O class compared to the Dal80-unbound class.
This work has benefited from the facilities and expertise of the  NGS platform of Institut Curie , supported by the  Agence Nationale de la Recherche  ( ANR-10-EQPX-03 ,  ANR10-INBS-09-08 ) and the  Canceropole Ile-de-France. AM's lab is supported by the  Agence Nationale de la Recherche  ( DNA-Life ) and the  European Research Council  ( EpincRNA starting grant, DARK consolidator grant ). Work by IG and ED is funded by the  CoCoF and FNRS  ( FRFC 2. 4547. 11 ). Work by AR was funded by a  FRIA  fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Sequence data can be accessed at the NCBI Gene Expression Omnibus using accession numbers GSE86307 and GSE86325. Genome browsers for visualization of processed ChIP-Seq and RNA-Seq data are accessible at http://vm-gb. curie. fr/dal80. Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Isabelle Georis (igeoris@ulb. ac. be). All other data are within the paper and supporting information files.
Availability of data and materials Sequence data can be accessed at the NCBI Gene Expression Omnibus using accession numbers GSE86307 and GSE86325. Genome browsers for visualization of processed ChIP-Seq and RNA-Seq data are accessible at http://vm-gb. curie. fr/dal80. Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Isabelle Georis (igeoris@ulb. ac. be). Bioinformatics and genome wide dataset requests could also be addressed to antonin. morillon@curie. fr for rapid processing.
914 • 2π/c, where d and c denote the intra-dimer Ir-Ir distance and the lattice constant, respectively. The spectra show a pronounced even/odd behavior with respect to m, reflecting the sinusoidal q dependence. Note that the elastic peak is suppressed in π polarization for a scattering angle of 2θ = 90 • , and that the data for 4Q to 7Q were measured at 2θ = 52 • , 67 • , 83 • , and 101 • , respectively. Accordingly, the elastic peak is strongest for 4Q. (B,C) Interference patterns in the RIXS intensity as a function of q. The data cover about 3. 5 periods in Q, equivalent to more than 20 Brillouin zones (top axis). The intensity was integrated over the energy-loss ranges indicated in the figure and normalized by the width ∆E of the respective energy range. Data in (B) were measured at 10 K with lower energy resolution of 0.