dataesr/scientific-paragraphs-categorization huggingface dataset:
Melt curve analyses were done by slowly heating the PCR mixtures from 60 to 95° C, and the cycle threshold (Ct) was determined with the StepOne Applied Biosystem software 2. 3. The chosen reference gene was Actin B but all the results were confirmed with glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The standard group was group C at SP point. For several genes, results could only be obtained at Eof point. In this case, the reference group was group C at Eof point. All Cycle thresholds (Ct) were collected. Results are expressed as 2.
Sequencing Analysis All software for analysis of sequenced data was used in the FROGS pipeline developed by the French National Institute of Agricultural Research (INRA, Toulouse, France)  [35]. First the sequences were denoised using the Flash 1. 2. 11 and Cutadapt 1. 7. 1 tools  [36, 37]. Only sequences with sizes between 380 and 500 bp, without ambiguous bases and with the two primers (5' primer ACGGGAGGCAGCAG and 3' primer AGGATTAGATACCCTGGA) were kept. Secondly, the sequences were clustered with Swarm 2. 0  [38]  in two steps, as recommended by Escudié et al. [35]. Swarm uses an iterative growth process to cluster sequences. In each growth step, the sequence of the previous step was used to find the other sequences with a number of differences inferior or equal to the "Aggregation distance".
The first step, or denoising step, served to build very fine clusters with an aggregation distance equal to 1 between the sequences of each crown. After the denoising, a second swarm with an aggregation equal to 3 between seeds from this first clustering was used to delineate OTUs. Next, PCR chimeras were removed using VChime of the Vsearch package  [39]. This step was performed after clustering in order to shorten the analysis time. Next, the remaining clusters were filtered. Only clusters present in at least 2 samples and with an abundance greater than 0. 005% of the total sequences  [40]  were kept. Finally, taxonomic affiliation for each OTU was obtained with BLASTn+  [41]  by blasting the sequences on the Silva128 database  [42].
Statistical Analysis Values given in the text are expressed as means ± SEM. Analyses of the OTU table were performed with the PhyloSeq package  [43]. Relative abundance, Chao1 diversity richness, Shannon and InvSimpson richness were determined. Beta-diversity was determined using nMDS with the Bray-Curtis distance method. Sparse Partial Least Squares Discriminant Analysis (s PLS DA) was performed to determine the most discriminant OTU using the mixOmics package  [44]  with CSS normalization and log transformation of count sequences. A cutoff value of 0. 95 was used to select the discriminant OTUs. Statistical analyses were performed with ANOVA analysis of variance using the R software 3. 3. 1  [45]. Differences were considered as significant when P-value < 0. 05. When significant, differences between treatments were compared using Tukey's test and FDR with BH correction  [46].
S) Table (3). As previously, no effect of probiotic addition during overfeeding was observed on BW, LW, MW and SFW. Feed consumption during overfeeding was expressed as g of raw feed/bird Table  (3). No statistical difference in feed consumption was observed during rearing (data not shown) and the overfeeding period Table  (3) , with or without probiotic supplementation. The fatty liver melting rate (fat loss during cooking) was used to determinate fatty liver quality. Here, probiotic addition had a significant effect on the fatty liver's melting rate. In fact, the melting rate decreased in group A-at Eof point compared to group C at the same point (19. 6±1. 2% vs 12. 7±1. 7%; P<0. 05) (Table  3 ). However, no significant differences were observed between group A-and the other probiotic groups (A+, B-, B+).
ACKNOWLEDGEMENTS We thank the  Conseil Départemental des Landes  ( CD40 ) and the  Comité Inter professionel des Palmipèdes à Foie Gras (CIFOG)  for financing this work. We also thank the technical staff of  INRA Artiguères  for rearing ducks. We also acknowledge the  GetPlage INRA team (in particular Pauline Heuillard)  for providing phyloseq script and for helpful suggestions concerning the use of sequence analysis software. The logistic support from  INRA Toulouse  was deeply appreciated.
Dynamic Impact Tests and Conditions for the Numerical Simulations The sample geometry used for tension-compression test (7. 5 cm diameter and 15 cm height) was considered for dynamic test. In this paper only numerical tests are presented but the associated lab test set-up of the dynamic impact tests is shown on the left of Fig. 2. The loading is manually applied on the specimen with an impact hammer equipped with a load cell (PCB model 086E80). The standing wave modes are measured with an accelerometer (PCB model 353B15) glued to the specimen. During the test, the specimen lays on soft foam to ensure free boundary conditions  [6]. The impact hammer and the accelerometer are connected to the data acquisition system that consists of a signal conditioner (PCB model 482C15), a data acquisition device (NI DAQ USB-6251) and a computer (see Fig.
The Comsol software was used to solve the three-dimensional equation of motion in the frequency domain (Eq. 7): -ρω 2 u -∇. σ = F p e iΦ  (7)  where ω is the angular frequency, ρ is the density, u is the displacement vector, ∇ is the gradient tensor operator, i is complex number defined by i 2 = -1 and σ is the Cauchy stress tensor. F p is the unity load and φ is the phase of the cyclic load. The unity load has been applied to the corresponding point of the hammer impact while the response has been determined at the position of the accelerometer for the three considered modes of vibration (see Fig. 2 ). The simulations were performed at 10 different temperatures every 10 • C from -40 to 50 • C, in a frequency range from 100 to 20,000 Hz considering steps of 20 Hz. Finer analysis with steps of 1 Hz were also carried out around the first resonant frequency for each temperature and for each mode of vibration in order to obtain a better evaluation of the first resonance frequency and of the damping of the material.
Next Generation Sequencing (NGS) RNA from the two PDX HROC32 and HROC39 were sequenced on an Illumina HiSeq2000 instrument in paired-end 2 × 100 nt. Raw read numbers were 80. 3 × 10 6 and 183. 2 × 10 6 for HROC32 and HROC39, respectively. After an initial step consisting of QC and trimming, reads were mapped to the human reference genome hg19 using Bowtie2. Unmapped reads were assembled with CLC Assembler into contigs of 100 nt minimal size. A search for viral and bacterial sequences was done from the contigs using a blastn procedure (best score) on NCBI databases genbank_release_virus and genbank_release_bacteria. From that, hits with an alignment longer than 60 nt were kept and their corresponding sequences were retrieved and used for a second (validation) blastn search, against the entire genbank database.
Statistical Analysis Gaussian distribution was tested by D' Agostino and Pearson omnibus normality test before significances were pointed out by using Mann-Whitney-U-test. Expression levels were compared between different samples as well as between different mERV. Statistical evaluation was performed using GraphPad PRISM software, version 5. 02. The Pearson correlation coefficient was calculated for EcoMLV and EndoPP expression in PDX samples. p-Values lower than 0. 05 were considered statistically significant.
While not exhaustive, we believe our analysis covers most of the crucial production rules followed by cooperative members in the region. Finally, we were also interested in whether or to what extent these production rules are enforced and respected by individual producers. The question of compliance is central in the literature on the commons, but has (surprisingly) not been studied as much as other aspects of the IAD framework  (Siddiki et al. 2012). Producer compliance was evaluated through quantitative data collected in 2015, in combination with insights from focus group discussions and interviews with more than 60 producers and members of cooperatives, including technicians and other stakeholders (NGOs, government representatives). We assigned compliance scores based on the number of cooperative members following a given rule.
All of these scores are best estimates: some rely on quantitative data, while others derive from interviews and focus group discussions. The latter are indicated with an asterisk (*). Quantitative data was collected via a survey conducted to generate baseline data for the FATE project (Feminization, Agrarian Transition and rural Employment), 2  which investigates the effect of export-led agriculture on local livelihoods, rural labour markets, and gender relations at the community and household level. A total of 305 households were included in the survey, covering topics such as rural employment and household livelihoods as well as agricultural decisions and changing agricultural practices related to the quinoa boom. Most of the people responding to the survey were members of the cooperatives SOPROQUI (64%) or ARPAIAMT (28%), while 1% of respondents belonged to CECAOT and 7% did not belong to any cooperative.
The role of cooperatives and rules enforcement Table  3  presents the six rules for quinoa production at the centre of our analysis. The following section discusses both the impact of these rules and the factors influencing estimated compliance with the rules. Information on sanctions was derived from formal rules articulated by cooperatives as well as from semi-structured interviews. In some cases, stakeholders suggested that certain rules could be considered weak and/or are not strongly enforced by the cooperatives. We have tried to explain this in the main text of this article, though it goes beyond the formal ADICO grammar system. b Information on compliance was derived from quantitative survey data collected in the 2013-2014 agricultural cycle (n=305). Information distinguished with an asterisk (*) derives from interviews and is thus estimated.
Capillary electrophoresis All of the CE experiments have been done on a CESI8000 capillary electrophoresis system from Sciex Separation (Brea, CA, USA). Bare fused-silica capillaries (total length 100 cm; 30 µm i. d. ) with a porous end from Sciex Separation (Brea, CA, USA) were positively coated with a commercial PolyEthyleneImine (PEI) coating following the protocol provided by Sciex Separation. A second capillary (total length 80 cm; 50 µm i. d. ) was used to complete the electric line of the separation system. Before each analysis, both capillaries were rinsed at 75 psi during 3 min with 3% acetic acid BGE. The 32 Karat TM (Sciex Separation) software was used for instrument control and data acquisition. Hydrodynamic injection (2 psi for 10 sec) corresponding to a volume of 3 nL (0. 5% of the capillary length) was used to inject the sample.
Mass spectrometry The CE system was hyphenated to a maXis 4G (Bruker, Bremen, Germany) by the sheathless interface. This MS instrument is equipped with a hybrid analyzer composed of hexapoles followed by a time-offlight (TOF) analyzer. Sample were run in denaturating conditions and analyzed in a m/z range from 2500 to 5000. The Otof control 3. 4 software allowed to pilot the nano-ESI source and the settings were the following ones: nanoESI voltage +1500 V, dry gas 3 L/min, ion funnels set at values of 400 and 400 Vpp, isCID energy at 190 eV and source temperature at 150°C. The data acquisition was made in positive mode.
Data analysis MS data have been analyzed with the dissect mode of Data Analysis 4. 2 software (Bruker, Bremen, Germany) with an internal S/N threshold of 3 and a maximum of 10 overlapping compounds. Cut-off intensity of mass spectrum calculation was set at 0. 1 %. After an automatic interpretation of the results, a manual validation has been performed on the results. MS spectra have been extracted from each peak represented on the BPE (Base Peak Electropherogram). Each profile has been selected and deconvoluted between 140 and 160 KDa with the maximum entropy algorithm provided by Bruker's software to calculate the mass of the corresponding compounds. Automatic and manual results have been confronted to detect any mass modifications and get some additional information about the different identified compounds.
Acknowledgments Authors would like to thank  Sciex  and  Bruker Daltonics  for the fruitful collaboration and the support. The authors would like also to express their gratitude to  Dr. E. Wagner-Rousset , ,  MC. Janin-Bussat  and  O. Colas  ( Centre d'Immunologie Pierre Fabre, St Julien en Genevois, France ) for helpful discussions around antibody structural characterization by LC-MS. This work was supported by the  CNRS  ( UMR 7140 ), the  University of Strasbourg , and a doctoral fellowship from  Bruker Daltonics  and the  General Council of Region Grand Est  to JG.
08) and because TM modes tend to be more susceptible to roughness. Since we used the least absolute residual method for fitting in MATLAB when we bound the other variables, it is possible to obtain a confidence interval for the gain variable G. Where appropriate, error bars are extracted from the confidence interval of fitting of both the reflection and transmission spectra. Since we fit the gain variable G = exp(-αL), the error bars are asymmetric when expressed in dB/cm units. When the waveguide width w tends to smaller dimensions, the data (especially for the TM polarization) becomes less clear, resulting in a larger error bar. The results show that our processes induce a notable improvement in propagation loss over other reported in literature. It should also be pointed out that we have previously compared this method of loss estimation with both a method based on use of an IR camera capturing scattered light from above and a cutback-like method  [18]  and found robust agreement.
Computational Efficiency Firstly, the computational efficiency was assessed. We used a laptop as the platform, whose CPU was i5 (2. 6 GHz) and RAM 6 GB. The simulation was carried out in the situation where there were two near-field sources. The array received 100 snapshots, and the number of grids for the spectrum search was 1080. In order to show the influence of the number of sensors, we ran the simulation with four different array configurations made of 5, 7, 9, and 11 sensors respectively. The efficiency of different methods was also shown in MATLAB flops versus the number of sensors, which can directly show the computational complexity. It should be noted that the spectrum search is necessary for SHO and HOP, while the modified ESPRIT-like and LOFNS are search-free methods. For SHO and HOP, we can see from Table  2  that when the number of sources is close to that of the sensors in the array, the subspace calculation is not a main factor of the computational efficiency.
A potentially interesting drug that may ameliorate the hemodynamic profile of septic patients may be represented by dexmedetomidine (α-2 agonist), a sedative drug that has shown a possible reduction in catecholamines release associated with increased blood pressure response to exogenous vasopressors in experimental models of septic shock  [59] [60] [61] [62]. A clinical study has completed its enrollment (Clinical-Trials. gov Identifier: NCT02638545), but more research is warranted before drawing any conclusion. Another drug that has shown improvements of LV diastolic function is levosimendan  [63] , and its properties are unique if compared to catecholamines (which usually worsen LV diastolic function  [64] ) and phosphodiesterase inhibitors (LV diastolic function remaining grossly unchanged)  [65].
Using the luminosity of Hα, we can infer the star-formation rate (SFR) of the host  (Kennicutt 1998). At the redshift of the GRB host, Hα is observed at 21 000 Å where the night sky is very bright. In addition, several bright sky-lines are superposed on the line, making an accurate estimate of the Hα-flux difficult. We obtain a limit on the SFR by numerically integrating the part of Hα free of contamination and correcting for the missing flux using the line profile and obtain F Hα > 4. 1 × 10 -17 ergs -1 cm -2. After converting the  Kennicutt (1998)  relation to a  Chabrier (2003)  initial mass function using  Madau & Dickinson (2014) , 1 https://github. com/jselsing/XSGRB_reduction_scripts we derive a limit of S FR > 7M yr -1. Additionally, based on the width of [O iii], an aperture covering the line is integrated over, where synthetic sky lines  (Noll et al.
Imaging observations and SED analysis In addition to the spectroscopy presented above, we imaged the field of GRB 111117A in multiple broad-band filters using the VLT equipped with FORS2 (gRIz filters) and HAWK-I (JHK s Table  1. Overview of the spectroscopic observations. JH in the slit width refers to observations where a K-band blocking filter has been used. The seeing is determined from the width of the spectral trace of a telluric standard star, taken close in time to the host observation. The spectral resolution, R, is measured from unresolved telluric absorption lines in the spectrum of the telluric standard star. 2013-08-03T07:37 2 × 1200 2 × 1200 8 × 300 1. 0/1. 0/0 All data were reduced, analyzed and fitted in a similar manner as described in detail in  Krühler et al. (2011)  and, more recently, in  Schulze et al.
Assuming a host brightness redshift determination threshold, for between 43 and 71 per cent of sGRB hosts, we would be unable to determine a redshift should they be at a similar redshift as GRB 111117A. This could indicate that potentially, a significant fraction of sGRBs are at high z but missed due to host faintness. Using the age of the universe at the time of explosion allows us to set constraints on the maximal separation between the engine constituents at the time of formation. We find that the maximal separation of two NSs at system formation time is a 0 < 3. 2 R , which excludes some of the formation channels with the longest timescales. All data, code and calculations related to the paper along with the paper itself are available at https://github. com/ jselsing/GRB111117A.
Acknowledgements. We thank  Jens Hjorth  and  Lise Christensen  for useful discussions regarding the interpretation of this event. We thank  Mathieu Puech  for testing the possible contribution from an older stellar population in the SED. TK acknowledges support through the  Sofja Kovalevskaja Award  to  P. Schady. SDV is supported by the  French National Research Agency (ANR)  under contract  ANR-16-CE31-0003  BEaPro JJ acknowledges support from  NOVA  and  NWO-FAPESP  grant for advanced instrumentation in astronomy. NRT and KW acknowledge support from  STFC  Consolidated Grant  ST/N000757/1  CT acknowledges support from a  Spanish National Research Grant of Excellence  under project AYA 2014-58381-P and funding associated to a  Ramón y Cajál fellowship  under grant number  RyC-2012-09984.
03 m/m. Simulations were started by specifying an initial value of inflowing water speed for the streamwise water flow in the x direction and assuming constant flux. The model was implemented in Matlab (version 2016b, The MathWorks, Inc. ). Simulations were run for 500 time steps, in abstract units due to our non-dimensional description of plant growth. To test the regularity of the predicted spatial patterns, we analyzed the resulting distribution patterns of P f through spatial autocorrelation. To test the spatial dependence between the beneficiary species P b and P f , we used spatial cross-correlation. Both auto-and cross-correlation analyses were performed by calculating Moran's I in the "ncf" package in R  (Bjornstad, 2016). To test for self-organization and spatial association among species in the field, we then compared the auto-and cross-correlation functions from the predicted species distribution patterns of coexistence with field observations on the spatial distribution of Groenlandia and Berula around Callitriche (see paragraph 2.
The channels are located along the Rhône River (France), near Serri eres-de-Briord (45. 815311°N, 5. 427477°E) and Fl evieu (45. 766738°N, 5. 479622°E) (see Appendix S3: Fig. S1  for the location of the study sites). The first reach was mainly colonized by Callitriche and Groenlandia, with few patches of other macrophyte species, while the second reach was colonized only by Callitriche and Berula. Aerial pictures of the streambed were taken with a digital camera mounted on a pole at about 2 m height that was moved in the upstream direction along the stretch. Aerial pictures were collected at times of day when the sun was at its highest point, and in the few hours before and after it (between 10:00 and 15:00 h), to minimize glare. Pictures were collected with a slight overlap and afterwards mosaicked using image processing software (Adobe Photoshop CC 2015).
ACKNOWLEDGMENTS This work was supported by the  Research Executive Agency , through the  Seventh Framework Programme  of the  European Union ,  Support for Training and Career Development of Researchers (Marie Curie   -FP7-PEOPLE-2012-ITN ), which funded the  Initial Training Network (ITN) HYTECH "Hydrodynamic Transport in Ecologically Critical Heterogeneous Interfaces ", N. 316546. We thank  Vanessa Gardette ,  Bruno Pyronain  and  Youssouf Sy  for field and laboratory assistance. We thank the  CNR (Compagnie Nationale du Rhône)  for providing access to field sites.
The first ophthalmologic examination was performed at 4 weeks of age, and the subsequent examinations were set by an eye care practitioner according to the development of changes in the retina. Depending on the occurrence and stage of ROP, all newborns were classified into groups 1 and 2 ROP: group 1 ROP -no, stage 1 or 2, group 2 ROP -stage 3, 4 or 5  [23]. On the basis of the medical records of the population of newborns, data on occurrence of risk factors for the development of BPD and ROP were collected, and attempts to identify those which simultaneously affected the occurrence and severity of these two diseases were made. Factors analyzed included gestational age (weeks), birth weight (g), sex, respiratory failure, respiratory distress syndrome (RDS), systemic and intrauterine infections, pneumonia, patent ductus arteriosus (PDA), necrotizing enterocolitis (NEC), intraventricular hemor-rhage (IVH), and anemia.
Statistical analysis Statistical analysis was performed with use of StatSoft, Inc. (  2011 ) STATISTICA (data analysis software system), version 10 (www. statsoft. com). To verify the normal distribution of the quantitative variables (gestational age, birth weight, number of days of mechanical ventilation, number of days in which the concentration of oxygen in the respiratory mixture exceeded 50% and the number of blood transfusions), the Shapiro-Wilk test was used, with the significance threshold level α = 0. 05. A parametric Student t-test was used in comparisons of variables with normal distribution. Variables with a distribution other than normal were analyzed using a nonparametric Mann-Whitney U test. In the case of qualitative variables, statistical difference was tested with a Chi-square test, V-square test or Chi-square test with Yates' correction, depending on the expected sample size.
Preoperative hormonal work-up All patients were investigated with biochemical tests (plasma ACTH-Cortisol cycle, free urinary cortisol/24h urine sample, serum deydroepiandrostenedione sulfate (DHEAS), serum 17-hydroxyprogesterone (17-HP), serum total testosterone, plasma and urinary metanephrines and normetanephrines, chromogranin A, plasma renin and aldosterone concentration) and conventional imaging (CT and/or MRI). Patients with an abnormal circadian cortisol rhythm or elevated urinary free-cortisol level or undetectable ACTH level, were evaluated by 1 mg dexamethasone and standard dexamethasone suppression tests (0. 5 mg every six hours for 2 days). 18 F-FDG PET/CT protocol 18 F-FDG (4 MBq/Kg) was administered intravenously after fasting for 6 hours and acquisition of imaging data was performed at approximately 60 minutes post-injection.