dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements This work was supported by grants from:  Fundação para a Ciência e a Tecnologia (ARI) , Portugal;  A. E. Berger ,  The Crafoord Foundation, G. E. Kock's Foundation , The  Gyllenstiernska Krapperup Foundation , The  Royal Physiographic Society in Lund, Swedish National Stroke Foundation , and the  Swedish Research Council  grant no. 2012-2229  (TD), Sweden; The  Danish Independent Research Council , and  The Lundbeck Foundation (SI-N), Denmark; Brødrene Hartmann Fond (BHC) ,  Savvaerksejer Jeppe Juhl og Hustru Ovita Juhls Mindelegat  (KLL), and  The Lundbeck Foundation  (BHC and KLL),  Denmark; Agency for Research and Innovation, Council for Health Research  (RK supported by a grant to  Trevor Owens ),  Denmark. We thank  Tadeusz Wieloch  for the valuable support, particularly with respect to modeling stroke in vivo and subsequent behavioral analysis,  Kerstin Beirup  for technical assistance,  Trevor Owens  and  Bente Finsen  for critical reading of the manuscript, and  Hakon Leffler  for kindly providing an anti-Gal-3 antibody.
For this purpose, cells were suspended in 100 µL of Dulbecco's PBS 1X at a concentration of 1 × 10 6 cells. Afterwards, they were incubated with 5 μL of each antibody for 15 min at 4 °C in the dark. They were finally washed with Dulbecco's PBS 1X (centrifugation at 800 g for 7 min) and re-suspended in 500 μL of Dulbecco's PBS 1X for FACS analysis. FACS data were further analyzed using FCS Express V4 software. Their secreting activity was also evaluated by ELISA assay in culture supernatant. Nearly all (>95%) were CD3 positives and CD19 negatives, and after activation with PMA (100 µg• mL -1 ) associated with ionomycin (500 µg• mL -1 ), more than 95% of CD3+ were activated (measured by flow cytometry detection of CD69 expression). Prior to the injection, cellular samples (cell viability >95%, evaluated by trypan blue staining) were re-suspended at a cell concentration of 10 6 cells per 100 µL in fresh culture medium containing stimulants.
This model facilitates both homogeneous temperature regulation within the whole microfluidic chamber and linear temperature profiles with a high degree of accuracy. The low thermal conductivity of the PDMS vessel ensures the control and stability of a uniform temperature profile within the microfluidic cell  [31]. The heat was generated by two copper electrodes placed onto the ITO-coated glass slide above the microfluidic device when an electric field was applied across the ITO-coated glass slide. Thermoregulation was done through a thermistor whose head was glued on the surface of the ITO-coated glass slide (R ~ 15 Ω) and on which some thermal paste was added to ensure good thermal conduction. The system was PC-controlled by thermoregulation LabVIEW software mainly composed of a PID controller.
Afterwards, a mix of 150 μL of 2. 5 µM C12-resazurin and 150 μL of 25 nM SYTOX Green in Dulbecco's 1X PBS was applied on the biochip which was thereafter incubated for 15 min at 37 °C with 5% CO2. After the incubation period, 1 mL of Dulbecco's 1X PBS was added and the biochip immediately observed with Olympus BX60 Epifluorescence Microscope equipped with a CCD camera (Olympus, Rungis, France) and Image-Pro Plus software.
On-Chip Cytokine Detection The cytokine secretions were analyzed on the one hand continuously by SPRi and, on the other hand by immunofluorescence after on-chip cell capture and culture (24 h). The SPRi data were acquired at regular intervals upon cell injection and capture on their specific antibodies. Areas of interest were drawn on the biochip surface corresponding to grafted antibody probes and raw data were corrected by every probe sensitivity given by the plasmon curve. The reflectivity variations of each grafted probe triplicates were averaged and plotted upon time after rectification by the subtraction of the negative control signals (i. e. , mouse IgG and/or anti-CD3 mixed with mouse IgG) to eliminate the general bulk solution index shift and the SPR signal from the cells. The immunofluorescence detection of cytokines secreted and bound to their specific antibodies on the biochip was performed in an immunosandwich assay after on-chip cell capture and culture and subsequent washing away of cells.
300 µL of biotinylated anti-human IL-2 or IFN-γ diluted to 1:300 in 1X PBS were applied on the biochip for 1 hour at room temperature, followed by a profusely wash in Dulbecco's 1X PBS and 15 min of conjugation with 100 µL of 5% streptavidin-phycoerythrin. After further washing in Dulbecco's 1X PBS, the fluorescence was observed with an exposure time of 0. 04 s and gain ×4 using Olympus BX60 Epifluorescence Microscope equipped with a CCD camera (Olympus, Rungis, France) and Image-Pro Plus software. The fluorescence image of each probe pattern was recorded and later analyzed by averaging the grey level (mean fluorescence intensity) of each pixel contained in a region of interest, matching each individual probe pattern. An area of the biochip without a probe pattern was used as control of the background noise.
Live-cell imaging Acquisitions were performed on a Ti inverted (Nikon) or an Axio Observer microscope (Carl Zeiss) at 37°C, with 5% CO 2 atmosphere, using a 10× dry objective (NA 0. 30 phase), a 20× dry objective (NA 0. 5 phase), or a SFluor 20× objective (NA 0. 75 without phase ring) for the mass measurements. Images were acquired using MetaMorph (Molecular Devices) or Axio Vision (Carl Zeiss) software. The excitation source was either a mercury lamp (Intensilight; Nikon) or a LED illumination (SPE CTRA X light; Lumencor or Zeiss Colibri). Images were acquired with a CoolSNAP HQ2 camera (Photometrics) for fluorescence or a PHA SICS camera (PHA SICS) for mass measurements.
Acknowledgments We thank  Kévin Carvalho ,  Joël Lemière , and  Fabrice Valentino  for the production of GUVs. We thank  Jean-François Joanny ,  Pierre Recho , and  Buzz Baum  for fruitful discussions;  Rémy Fert  for micromilling of the chamber molds; and  Lamya Ghenim-Ziman  for PC3 cells. The authors greatly acknowledge the  Nikon Imaging Centre  and the PICT-IBI SA plateform at the  Institut Curie-Centre National de la Recherche Scientifique. S. Monnier  was supported by the  Fondation Pierre-Gilles de Gennes. E. Zlotek-Zlotkiewicz  was supported by a PhD fellowship from  Institut Multi-Organismes Cancer  (Plan Cancer 2009-2013). This work was supported by an  Institut National du Cancer  grant ( PLB IO 11-IC-1 ) and a  European Research Council   consolidator grant  ( PRO MICO-311205 ) to M.
Acknowledgments This paper was jointly supported by grants from the  NSFC  ( 31110103909 ,  31101730 ), the  National Key Technology Research and Development Program of the Ministry of Science and Technology of China  ( 2012BAD39B00 ),  Chinese Academy of Sciences and Knowledge Innovation Project  ( CXJQ120113-1 ),  Chinese Academy of Sciences President 's  International Fellowship Initiative Grant  (No. 2015VBA009 ,  2013T2S0014 ),  China Postdoctoral Science Foundation  funded project (2014M552022). Tianyong Zhang from from  Henan Guang 'an  Biology Technology Co. Ltd contributed materials for the completion of the study, Tian-zheng.
4 million CMASS galaxies in the entire BOSS footprint. In Figure  6 , we show the different CFHTLS fields. The positions of CMASS galaxies in subsample A within these fields are indicated by black dots. The quantities needed for shape estimate of each galaxy image, its ellipticity, calibration factors, and weight are provided in the CFHTLenS catalog  (Heymans et al. 2012; Erben et al. 2013; Miller et al. 2013). The two ellipticity components in the celestial coordinate system, (e 1 , e 2 ), were estimated from the i -band data of each galaxy image using the lensfit software, which is based on a Bayesian model-fitting method  (Miller et al. 2007 ) for a model with two components. The ellipticity is defined as e = (ab) / (a + b), where a and b are the major and minor axes of the ellipse, respectively.
Therefore an over-subtraction of the sky might be a possible origin of B(R) < 1 at the small radii. Magnification can also affect the observed counts of galaxies near bright objects. Duncan et al. (2014)  showed a deficit is expected for the similar magnitude depth 15. Because of the difficulty in identifying the origin of possible systematic errors on small scales, in the following analysis we do not use data at scales smaller than 100 h -1 kpc (we use different cuts for other subsamples, which are described later). On the other hand, as shown on the plot, the boost factor is consistent with unity at scales larger than 100h -1 kpc, meaning that a contamination of physically-associated galaxies with CMASS 14 priv. comm. with T. Erben. 1 On the other hand, they showed an excess as expected for a bright sample mag i < 21.
2013) , this correction rests on the assumption that the distribution of lens galaxies is uncorrelated with residual systematics in the shape measurements. This assumption holds in our analysis because the lens catalog and the shape measurements are taken from completely different datasets, the SDSS and CFHTLenS data. The size of correction is consistent with zero at small radii, and increases to 10-15% of the measured signals at large radii at R ∼ 10 h -1 Mpc.
DISCUSSION AND CONCLUSIONS In this paper, we have shown the clustering and lensing measurements of the SDSS-III/CMASS galaxies at z 0. 53. In our analysis, we constructed a subsample of galaxies so that it constitutes an approximately stellar mass limited sample (log M * /h -2 70 in [11. 10, 12. 0]) over the redshift range z ∈ [0. 47, 0. 59], with approximately constant number density (subsample A). This subsample of galaxies was used to measure the projected clustering signal with a total signal-tonoise ratio of 56 for scales 0. 85 h -1 Mpc < ∼ r p < ∼ 80 h -1 Mpc (see Figure  4 ). We then made use of the publicly available galaxy shape and photometric redshift catalogs compiled by the CFHTLenS collaboration based on deeper, higher quality imaging data from the CFHTLS. This imaging catalog has an overlap of a mere 105 deg 2 with the BOSS footprint, but it allows measurement of the weak gravitational lensing signal of the BOSS galaxies, selected in the same way to our fiducial subsample, with a signal-to-noise ratio of 26 for 0.
ACKNOWLEDGMENTS We greatly thank  Hong Guo ,  Anatoly Klypin ,  Francisco Prada ,  Ramin Skibba , and  Simon White  for useful comments during the SDSS internal review. HM and RM greatly thank  Alexie Leauthaud ,  Melanie Simet ,  Lance Miller ,  Catherine Heymans ,  Ludovic Van Waerbeke , and  Hendrik Hildebrandt  for useful discussion about the CFHTLenS catalog. HM is supported by  Japan Society for the Promotion of Science (JSPS)   Postdoctoral Fellowships for Research Abroad and JSPS Research Fellowships for Young Scientists. MT is supported in part by  JSPS KAKENHI  (Grant Number:  23340061 ), by  World Premier International Research Center Initiative  ( WPI Initiative ),  MEXT, Japan , and by the  FIRST program  ' Subaru Measurements of Images and Redshifts (SuMIRe) ',  CSTP, Japan. RM is supported in part by the  Department of Energy Early Career Award program.
This work was supported in part by the  National Science Foundation  under Grant No. PHYS-1066293  and the hospitality of the  Aspen Center for Physics. Funding for SDSS-III has been provided by the  Alfred P. Sloan Foundation , the Participating Institutions, the  National Science Foundation , and the  U. S. Department of Energy Office of Science. The  SDSS-III  web site is http://www. sdss3. org/. SDSS-III is managed by the  Astrophysical Research Consortium  for the Participating Institutions of the  SDSS-III Collaboration  including the  University of Arizona , the  Brazilian Participation Group ,  Brookhaven National Laboratory, University of Cambridge, Carnegie Mellon University, University of Florida , the  French Participation Group , the  German Participation Group, Harvard University , the  Instituto de Astrofisica de Canarias , the  Michigan State/Notre Dame/JINA Participation Group ,  Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington , and  Yale University.
Statistics To account for factors of replicate/round and treatment, we used two-way ANOVA to analyse total foraging activity, pollen foraging activity and individual foraging loads; we conducted LSD Student's t test post hoc analyses on significant results  (Sokal & Rohlf, 1995)  using JMP Pro v. 10 (SAS, Cary, NC, U. S. A. ). Because foraging load data are categorical, we analysed the distributions of foraging loads collected with three-way and two-way contingency tables using a custom chi-square contingency table (http://vassarstats. net/newcs. html). Replicates were conducted on different days over a 10-day interval and thus encompassed variance across days and individual nucleus colony differences. Significant differences in foraging activity across replicates in experiment 1 may be due to differences in forage availability, as replicates were conducted on different days over a 10-day period.
There was no significant interaction of treatment and replicate (G test: G 9 ¼ 0. 02, P ¼ 1. 0). However, there was a significant interaction of treatment and type of foraging load collected (G 9 ¼ 43. 4, P < 0. 001) and a significant interaction of treatment, foraging load and replicate (G 54 ¼ 158. 36, P < 0. 001). Since there was no significant interaction of treatment and replicate, we pooled the count data across replicates (Fig. 4 ) and conducted a 4Â4 contingency table analysis. Treatment significantly influenced the type of load collected (chi-square test: c 2 9 ¼ 44. 2, P < 0. 001). We assessed total foraging activity and pollen foraging activity to examine treatment effects at the colony level. We also quantified individual foraging loads of nectar and pollen to determine whether treatment influenced the load size or sucrose concentration collected.
Acknowledgments We thank  C. S. Brent  and two anonymous referees for helpful comments on the manuscript and  O. Kaftanoglu  for technical assistance. This research was supported by the  Agriculture and Food Research Initiative Competitive  Grant No. 2012-67011-19925  from the  U. S. Department of Agriculture, National Institute of Food and Agriculture. This study complies with current U. S. laws regarding animal care and use.
An rpoB Mutation away from the Active Site of the RNAP also Restores GE Given that rpoB mutations in codon 572 converged in phenotype toward restorative GE, we sought to know if additional mutations in rpoB had similar effects. To address this question, we constructed a single mutant, rpoB I966S, which alters one of the two parallel -helices of the Eco flap domain of RNAP  (Opalka et al. 2010 ). The I966S mutation was found in 15 of our high-temperature adapted clones  (Tenaillon et al. 2012) , and its fitness advantage at 42 C was confirmed by competition experiments (Rodr ıguez-Verdugo et al. 2014). We obtained RNAseq data from two replicates of this mutant at 42 C and performed the same GE analyses. We observed a global pattern of GE change similar to that for the I572F, I572L, and I572N mutants.
6A ). Knowing that the evolved clones grew more quickly and to higher yields than the single mutant I572L at 42 C, we sought to identify GE changes that could explain their improved growth. We obtained RNA-seq data from each high-temperature adapted clone (two replicates per clone) grown at 42 C. We then contrasted the GE from each clone against the GE of the first-step mutation I572L at 42 C. To our surprise, we observed very few genes that were differentially expressed (q < 0. 001): 7 for clone 27 in addition to 56 genes with no measurable GE (fig. 6B  and supplementary table  S5 , Supplementary Material online) and 16 for clone 97 (supplementary fig. S5 , Supplementary Material online). Furthermore, the high-temperature adapted clones maintained the general pattern of restoration back to the ancestral physiological state previously observed for the mutant I572L (slope ofÀ0.
S8 , Supplementary Material online). Three estimates of m max were obtained for each genotype. The duration of the effective lag phase, , was defined as the time elapsed before the maximal growth rate was reached. Because this definition measure may include some of the initial period of exponential growth, we also explored an alternative definition to estimate the end of the lag phase as the intersection point between the initial cell density and the linear regression fitted to the data measured in exponential phase. The final yield was estimated from the cell counts at the end of the exponential phase.
mRNAseq Data Analyses Reads were mapped to the E. coli B REL606 genome reference (CP000819. 1) using bwa 0. 6. 2 (Li and Durbin 2009) , using default parameters (http://bio-bwa. sourceforge. net/bwa. shtml). Only unique, perfectly matching reads to the 4,204 annotated coding regions were retained for further analyses (supplementary table S9, Supplementary Material online). Differential expression analysis was performed using the DESeq R package  (Anders and Huber 2010). We used the P values adjusted by the Benjamini and Hochberg approach (q values), which controls for false discovery rate. Genes with q less than 0. 001 were considered significantly differentially expressed. For the GO term enrichment analyses, we used the Enrichment analysis tool from http://geneontology. org/page/ go-enrichment-analysis.
Acknowledgments We thank  P. McDonald  and  R. Gaut  for technical assistance. This work was supported by the  National Science Foundation  grant  DEB-0748903  to B. G. O. T. was supported by  European Research Council  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013/ERC Grant 310944 ). A. R. V. was supported by the  University of California Institute for Mexico  and the  United States-Consejo Nacional de Ciencia y Technolog ıa (Mexico)  Fellowship and by the  Chateaubriand Fellowship in Science, Technology Engineering , and  Mathematics (STEM).
This strain is not missing the 16-kb fragment previously identified in strain 930029 and is discriminated from strain 930029 based on 19 SNPs. Therefore, strain 930029 presents features different from the two other isolates of the B. atrophaeus species, 1942 and CIP77:18, such as the conspicuous absence of genes involved in extracellular peptide signaling and endospore development. Despite this deletion, strain 930029 is easy to grow and sporulate in vitro. This raises the question of strain variations during long-term propagation and of standardization issues for tests and evaluations in biodefense. Nucleotide sequence accession number. The draft genome sequence for strain 930029 has been deposited at GenBank under the accession no. CUWS00000000.
Voxel-based morphometry analysis Data were processed using the Statistical Parametric Mapping Software version 8 (SPM8; 〈http://www. fil. ion. ucl. ac. uk/spm/soft ware/spm8〉; Wellcome Department of Imaging Neuroscience, Lon don, UK) and the VBM8 Toolbox. Customised tissue probability maps were produced using the matched template approach of the Template-O-Matic Toolbox for SPM8, with each participant's age and gender as defining variables. First, all T1-weighted images were checked for scanner-and individual-based artefacts. Individual images were then corrected for bias-field inhomogeneities, segmen ted and spatially normalised (affine-only transformation) with reference to customised tissue probability maps. Segmentation accuracy was visually checked for each participant. Based on individual registered grey matter (GM) and white matter (WM) segmentations, an average DARTEL (Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra) template of all participants was created in the MNI space  (Ashburner and Friston, 2000).
Strain (PA 461) was cultured on trypticase soy agar plate at 37°C for 24 hours, and identification was confirmed by matrix-assisted desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) (Microflex; Bruker Daltonics, Bremen, Germany) with FlexControl software, as previously described  [4]. Antibiotic susceptibility testing performed on Mueller-Hinton agar by standard disk diffusion method as recommended by the European Committee on Antimicrobial Susceptibility Testing (EUCAST; http://www. euca st. org/), showed that the isolate was resistant to almost all antibiotics, including β-lactams, as well as fluoroquinolones and rifampicin, but remained susceptible to aminoglycosides and colistin. Phenotypic detection of carbapenemase by modified Hodge test and imipenem-ethylene diamine tetra-acetic acid test, performed as previously described  [5] , were negative.
The presence of MBLs genes, investigated by PCR as previously described  [6] , confirmed that this isolate did not produce a carbapenemase. Amplification of the oprD gene using previously described primers  [3, 6]  resulted in PCR product of 2. 6 kb instead of 1332 bp. Sequence analysis of the 2668 bp product revealed insertion of a sequence of 1336 bp at position 610 in oprD. Within the sequence, an open reading frame of 1227 bp was found and corresponded to ISPa1328 from P. aeruginosa (GenBank accession AY539833). This insertion sequence (IS) was bordered by two terminal imperfect repeats and flanked on both sides by direct repeat sequences of 7 bp (CCAAGAG) (Fig. 1 ). Multilocus sequence typing, performed as previously described (http://pubmlst. org/paeruginosa), showed a novel sequence type (ST1797) and thus a novel clone of P.
Object reconstruction and event selection The data were collected during 2012 using triggers requiring either an electron or a muon with transverse momentum relative to the beam axis, p T , greater than 24 GeV. The triggered electron or muon must also satisfy loose isolation requirements. These triggers are supplemented by triggers without isolation requirements, but with higher p T thresholds of 60  (36)  GeV for electrons (muons). Only data taken while the ID, calorimeters, and MS were functioning normally are considered. Events are required to have a reconstructed primary vertex having at least three associated tracks with p T > 400 MeV, consistent with the beamspot envelope. If more than one such vertex is found, the vertex with the largest p 2 T of its associated tracks is chosen as the hard-scatter primary vertex.
The left (right) plot shows the limits assuming 100% branching fraction to e/ν e (µ/ν µ ). The solid line shows the observed limit. The dashed line shows the median expected limit for a background-only hypothesis, with green and yellow bands indicating the expected fluctuations at the ±1σ and ±2σ levels. The limit is evaluated in 3 GeV intervals. [GeV] Figure  6 : 95% CL upper limits on the type-III seesaw production cross section. The left (right) plot shows the limits assuming 100% branching fraction to e/ν e (µ/ν µ ). The solid line shows the observed limit. The dashed line shows the median expected limit for a background-only hypothesis dataset, with green and yellow bands indicating the expected fluctuations at the ±1σ and ±2σ levels. The limit is evaluated in 3 GeV intervals. fiducial volume, fid.
A detailed report on further analyses of the draft genome sequences will be released in a future publication. Nucleotide sequence accession numbers. The annotated draft whole-genome sequences of these O26:H11 strains were deposited in DDBJ/ENA/GenBank under the accession numbers LDXB00000000 to LDXG00000000 and LDXI00000000 (Table  1 ). The versions described in this paper are the first versions, LDXB01000000 to LDXG01000000 and LDXI01000000.