dataesr/scientific-paragraphs-categorization huggingface dataset:
The full model of extinction probability used a binomial distribution and a logit link (SAS Institute, Inc 2008), and included initial population size (a categorical variable with two levels, small and large), and evolution treatment (evolving or control), and environment (favorable or poor), and all their interactions. Block was included as a fixed effect, as there were only two temporal blocks. The augmentation approach is known to have problems as an all-purpose method, particularly when replication is low  (Agresti & Yang 1987; Heinze & Schemper 2002). To evaluate its performance, we compared results from the full model with the augmented dataset to a reduced model that excluded the affected treatment combinations. The relative estimated probabilities of extinction among treatment combinations were the same to ±0.
03, and estimated confidence interval widths differed by <2%. The augmented dataset approach thus performed quite satisfactorily in this case with large sample size. For the treatment combinations with no extinction, we took the estimated probability and one side of the confidence limit to be zero (negligibly different from the estimated confidence limit in practice) and drew the upper confidence limit from the augmented data analysis. As a further check of these confidence limits, we also calculated exact 95% confidence widths for the affected treatment combinations as 1 -exp(ln(0. 05)/n), where n is the number of trials, assuming that trials are independent (in contrast the GLMM does not assume independence). The exact intervals were slightly smaller than the intervals estimated by the GLMM using the augmented dataset, suggesting that the estimated GLMM intervals are conservative, with the full model accounting for extra variation.
The unaugmented dataset was used to estimate p-values for the main effects of genetic background and founding size (as the separation problem did not occur for the main effects), while the augmented dataset was used to estimate the p-values for their interactions. We estimated odds ratios and their confidence intervals to examine differences between treatments. We also evaluated the time it took for those populations that went extinct to go extinct, focusing on populations from the poor environment. Time to extinction (in generations) was log transformed prior to analysis to improve the normality of residuals. Factors in the model were founding size and evolution treatment, with block as a fixed effect. One of the most important characteristics of populations that managers track is population size.
ACKNOWLEDGEMENTS Funding for this research was provided by the  US National Science Foundation  grants  DEB-0949619  to RAH,  DEB-0949595  to BAM, and  DMS-1016268  and  DUE-1130115  to SJT. We thank  Michael Antolin ,  Don Estep ,  John Moore  and  Colleen Webb  for helpful discussions. We appreciate the thoughtful and helpful reviews provided by two anonymous reviewers, as well as input from the handling editor. Additional support came from the  United States Department of Agriculture via the Colorado Agricultural Experiment Station.
57 he impact expression of the PIM serine/threonine kinase family members have been extensively studied in cancer and AML. 58, 59 PIM kinases are FLT3-ITD targets dependent on -at least for PIM1 -STAT5 activity that controls several oncogenic relays including transcription, protein translation, cell cycle, apoptosis, and cell migration. 58 1] [62]  Several groups reported a significant antileukemic activity of PIM inhibitors in preclinical models of AML,  [63] [64] [65]  and currently a clinical trial is ongoing with the LGH447 pan-PIM kinase inhibitor in AML regardless of their FLT3 mutational status (NCT02078609). We recently observed that PIM kinases overexpression decreases the efficacy of FLT3 TKI due to a direct action of PIM kinases on FLT3-ITD receptors. In AML cells resistant to TKI, PIM kinase inhibition by RNA interference or by the pan-PIM kinase inhibitor LGB321 (similar to LGH447) restored the cytotoxic activity of FLT3 TKI against these cells, providing the molecular basis to understand the synergy between FLT3 and PIM kinase inhibition in FLT3-ITD + AML.
40 In addition, evidence suggests that, in contrast to cytotoxic chemotherapy, treatment with hypomethylating agents such as 5-azacytidine may prevent the release of FLT3-L. On the basis of these observations, several clinical trials are currently ongoing combining Vidaza to different TKI molecules in FLT3-ITD AML. 17  An interesting approach to bypass FLT3-L-induced resistance to therapy is the development of anti-FLT3 antibodies. These antibodies bind FLT3 regardless the concentration of FLT3-L and induce cytotoxicity mainly through antibody-dependent cell-mediated cytotoxicity. 68 FLYSYN is such a therapeutic antibody that will be used in clinical trials to target minimal residual disease in AML in complete remission (NCT02789254).
Phenotypic data Phenotypic data for agronomic traits measured over several years were available at each location. We gathered existing data for seven of these quantitative traits: onset of flowering time (FD, date when 2-3% of flowers observed in F stage), onset of ripening time (MD, date when 2-3% of fruits were mature), fruit development period (FDP, number of days between FD and MD), percentage of red overcolor on the fruit skin (PSC, by visual estimation of the surface covered), titratable acidity of the fruit flesh (TA, meq/100 ml in the juice of at least five ripe fruits), soluble solid content of fruit flesh (SSC, average brix degrees measured in a drop of at least five ripe fruits) and fruit weight measured as the average of 10 random peaches sampled from each tree (FW, grams). The traits and number of years of observations varied per progeny (Table  1 ).
When available, observations for two or more years were compared and analyzed for consistency; those ranking the individuals in ordinal positions differing by more than 50% between years were removed. Following, outlying observations within progenies and years were identified and removed as described by  [23]. Subsequently, the year with more observations per trait and progeny was selected for the analysis. A correlation analysis was conducted to evaluate the representativeness of the selected data. In general correlations were moderate (average r = 0. 72, median r = 0. 76) (Additional file 1). Data for most of the traits followed a normal distribution (Additional file 2), with moderate skewness (skew ≤ 0. 5), with only two of them (FD and TA) deviating from normality with positive skew. To evaluate the environment effect introduced in the analysis by combining data from different locations, we also conducted the analysis after standardizing the raw observations following two statistical methods.
1 Kbp/cM. The raw genotypes obtained from GenomeStudio® software were filtered using a pre-release of ASSIsT  [27]. Monomorphic SNPs in all progenies or with null alleles were discarded (3142 out of 8144). The SNPs that passed the filters were grouped in haploblocks (HBs) of 1 cM, and haplotyped with PediHaplotyper  [28]  to reduce the computation time of the analysis and to facilitate visual inspection of markers across pedigrees.
QTL mapping methodology FlexQTL TM software was used for the QTL analysis  [15]  (https://www. wur. nl/en/show/FlexQTL. htm). FlexQTL TM uses bi-allelic QTLs model that allow three different genotypes (QQ, Qq, and qq whereby Q associates with high phenotypic values), and a continuous uniform distribution to assign prior QTL positions along the genome and a 2 cM binning of the genome. In this study we considered only additive effects with normal prior distribution. The models analyzed were set with a prior mean number of 15 QTLs and maximum of 20 QTLs, with the exception of the FD trait, where the mean and maximum number of prior QTLs was 25 and 40, respectively. Additionally, "year and location" and "maturity date" were included in the model as nuisance variables, considered to follow either uniform (for the nominal "year and location" variables) or normal (for "maturity date") distribution.
QTL detection: number, position and additive effects, genotype probabilities, breeding values and description accuracy FlexQTL TM software was used to detect QTLs for each of the seven traits by conducting an integrated analysis of phenotypic and genetic data of all progenies. The number of individuals analyzed per trait varied between 570 for red skin coloration (PSC) to more than 1160 for the QTLs responsible for FD and MD. Analyses were performed with original and both standardized observations (STD1 and STD2). The estimated narrow-sense heritability of the traits (h 2 ) was lower with the original data than after standardization which brought h 2 up to 0. 63 for SSC to 0. 94 for MD, with an average of 0. 83. All putative QTLs detected with at least positive evidence (2lnBF > 2) with the original data and in one or both standardizations; or those with decisive evidence (2lnBF > 10) in one of the three data sets were considered for further examination and discussion (Fig.
25' had higher positive GBV (20. 2 and 19. 6 days, respectively), while the highest ability in shortening fruit development period was assigned to 'Earlygold' (GBV = -43. 6 days). The overall Correlation between progenies phenotypes and their estimated genome-wide breeding values (GBV) (accuracy) was obtained for a flowering date (FD), b maturity date (MD), c fruit development period (FDP), d percentage of red skin color on the fruit skin (PSC), e titratable acidity of the fruit flesh (TA), f soluble solid content of the fruit flesh (SSC) and g weight of the whole fruit (FW)) GBV of progenies correlated well with observations. When considering all progenies, data correlations were 0. 94. The progeny for which prediction accuracy was lowest was RSx25 (0. 33 for raw data, 0. 92 for STD1 and 0.
The parents with lower GBV were the sub-acid varieties 'Rebus 028' and 'Zephyr' (0. 5 and 0. 6, respectively), while those increasing the acidity more were 'Oro A' and 'Rome Star' (GBV = 10. 2 and 7. 9, respectively). To minimize a possible epistatic effect of the maturity date on TA content we included MD data as a nuisance variable in the genetic model. All QTLs except qTA6. 1 (with low effect in the initial analyses) were maintained. The correlation between GBV and TA was high (r 2 = 0. 91). The model was able to better predict the breeding value for the BbxNl (accuracy 0. 98), MxR028 and JxF (both with accuracy of 0. 94) progenies. Predictions were worst for PxF, although, as previously, they increased after standardizations.
QTL-discovery data were previously published for eight of the 18 families currently analyzed: BxO  [40] , BbxNl  [46] , PxF  [47] , JxF  [43, 48] , BC2  [22] , and TxE and T1E  [8]. We counted the QTLs of these publications that were consistent (found in at least two years or locations and mapping at sites compatible to those found in this study): only 22 (47%) of the 47 QTLs detected by FlexQTL had previously been identified. The remaining 25 QTLs were only present in the other ten families or segregated in these eight families but remained below the significance threshold when using a conventional biparental approach. Examples of the latter for strong to decisive QTLs are qFD8. 2, qTA6. 1, qMD3, qFDP1, qFDP3, qFDP6. 3 and qSSC4 for TxE and T1E and qFD5, qFD8. 2, qMD5, qPSC5 and qFW5 for JxF, where heterozygous parents are predicted by the model (see Fig.
Conclusions Based on the use of the FlexQTL software in a large set of families our results provide a more comprehensive view of the genetic variability of some of the most relevant agronomic characters of peach, and a deeper knowledge of their genetic basis, with the detection of many more QTLs, and identification of their effects and map positions with higher precision than with single population experiments. In addition, specific information on the parental QTL genotypes and their breeding values provides an efficient tool for parent selection in breeding programs. Our results indicate that genetic variability can come from non-commercial genotypes even for agronomic characters. Such exotic material was generally used for the introgression of resistant factors to biotic stresses in breeding programs  [55]  but considered as a break to recover good fruit quality.
The human centromeric protein CENP-B is derived from transposases of pogo DNA transposons  37       A phylogenetic tree was built from 308 PMDs from 33 species representing the diversity of this motif in angiosperms (Supplementary Data 3). The three clades A, B, C are indicated. The species codes are given in Supplementary Table  1. The colour code is the following: green for dicotyledonous species, orange for monocotyledon species, blue for the basal Amborella trichopoda and yellow for the two species that are basal to the grass lineage. Names of the TE sequences extracted from the Repbase database are presented in parenthesis. PMDs associated with TEs are highlighted in violet, blue or green depending on their clade and a schematic representation of their organization is shown. Other PMDs are associated with non-TE PCGs.
Read statistics are listed in Supplementary Table  2. Expression of loci was determined by calculating reads per kilobase per million mapped reads (RPKM). Pvalues to detect differential expression were calculated by Fisher's Exact test. False discovery rate (FDR) correction was calculated using the Benjamini-Hochberg correction. Differentially expressed loci were defined by log2 RPKM mutant/ WT42 (upregulated) or o À 2 (downregulated) and a FDRo0. 01. Only loci defined as differentially expressed in both biological replicates were retained. Re-analysis of previously published RNA-seq datasets from leaf tissue of mom1-2 (two replicates; GSM938356 and GSM938357), atmorc6-3 (one replicate; GSM925646) and their corresponding WTs (GSM938341, GSM938342 and GSM925644) was performed as described above, with the exception that all loci defined as differentially expressed in the single atmorc6-3 replicate were retained.
13b ) or H3K9me2 (Abcam ab1220; Diagenode C15410060; 2 mg). Four microlitre per 100 ml purified DNA was used for real-time PCR amplification using the Eco Real-Time system (Illumina) and SYBR Premix Ex Taq II (Tli RnaseH Plus) (TaKaRa) in a final reaction volume of 15 ml. Data were collected from three to five biological replicates, and relative enrichment was expressed as percentage of input. Immunocytology and DAPI-staining. Rosette leaves from 4-week-old plants were fixed for 2 h in 4% formaldehyde in PBS and subsequently chopped on a glass slide. Tissues were covered with a coverslip, manually squashed and frozen in liquid nitrogen for 10 s before rapidly removing the coverslip. Slides were washed in PBS and pre-incubated with 3% BSA in PBS for 30 min at 37 °C. Slides were incubated overnight at 4 °C with primary antibodies diluted in 3% BSA in PBS (Diagenode anti-H3K9me2 (C15410060) diluted 1:100, Diagenode anti-H3K27me1 (C15410045) diluted 1:500 or Millipore anti-H3K27me1 (#07-448) diluted 1:100).
Slides were washed in PBS and incubated with the secondary antibody (goat antirabbit Alexa 488, A-11008; ThermoFisher Scientific) for 1 h at 37 °C. After three washes in PBS, DNA was counterstained with DAPI in Vectashield mounting medium (Vector Laboratories). Nuclei were visualized using a Zeiss Axio Imager Z. 1 epifluorescence microscope (Carl Zeiss AG) with a PL Apochromat Â 100/1. 40 oil objective. Z-stack images were captured with a Zeiss AxioCam MRm camera using the Zeiss ZEN software. The relative heterochromatin area was computed for each nucleus by calculating the ratio of the sum of chromocenter areas over that of the entire nucleus using the ImageJ software. To analyse nuclear localization of MAIL1 and MAIN, immunostaining was performed as described above using ProMAIL1:MAIL1-GFP (ref.
ethanol) after boiling. To detect cell death, stained material was incubated in chloral hydrate solution (2. 5 g ml À 1 chloral hydrate in water) for 3 days (ref. 45). Flow cytometry. Nuclei were prepared using the CyStain UV Precise P kit (Partec), according to the manufacturer's recommendations. Flow cytometry profiles were obtained on an Attune Acoustic Focusing Cytometer (Applied Biosystems) and analysed with the Attune Cytometric software (Applied Biosystems). Histone extraction and immunoblot. Two grams of 4-week-old seedlings were ground in liquid nitrogen and transferred to 25 ml extraction buffer 1 (EB1: 0. 4 M sucrose, 10 mM Tris-HCl pH 8, 10 mM MgCl 2 , 5 mM b-mercaptoethanol, 0. 1 mM phenylmethylsulfonyl fluoride and protease inhibitor tablet (Roche)). The suspension was filtered twice through a layer of Miracloth and centrifuged at 3,000g for 20 min at 4 °C.
jgi. doe. gov/pz/portal. html). Each time a new PMD was found in a given species, it was itself used as a query in a new BLAST search. To build the phylogenetic tree, we selected PMDs from 33 representative species (see Supplementary Table  1  for a list of species). All PMDs from PCGs from these 33 species were collected as well as representative versions of TE-associated PMDs when present. This led us to collect initially 464 proteins from the 33 species. We next performed a preliminary phylogenetic analysis of PMDs independently for each species. From these individual analyses, we were able to select PMDs that are truly representative of the diversity within each of our 33 species leading to the 308 proteins that were aligned and used to build our final phylogenic tree (Supplementary Data 3).
Sequences were aligned using the multiple sequence comparison by log-expectation (MUSCLE v3. 7) software  46. Trees were reconstructed using the fast maximum likelihood tree estimation program PHYML  47  using the LG amino acids replacement matrix  48. Statistical support for the major clusters were obtained using the approximate likelihood-ratio test (aLRT)  49. To confirm the association of a PMD motif with a TE, we first used the Repbase database (http://www. girinst. org/) to identify PMD-containing Gypsy and PMD-containing MULE annotated in this database and present in our selected species. These sequences were used as references to identify putative new TE-associated PMDs in our phylogenic analysis. Each time a PMD clustered with at least one annotated TE in our phylogenic analysis, the genomic sequences surrounding the PMD were collected and translated (using Fgenesh available at http://www.
Figure6| MAIL1 and MAIN contain a TE-related plant mobile domain. A phylogenetic tree was built from 308 PMDs from 33 species representing the diversity of this motif in angiosperms (Supplementary Data 3). The three clades A, B, C are indicated. The species codes are given in Supplementary Table1. The colour code is the following: green for dicotyledonous species, orange for monocotyledon species, blue for the basal Amborella trichopoda and yellow for the two species that are basal to the grass lineage. Names of the TE sequences extracted from the Repbase database are presented in parenthesis. PMDs associated with TEs are highlighted in violet, blue or green depending on their clade and a schematic representation of their organization is shown. Other PMDs are associated with non-TE PCGs. MAIL1 and MAIN proteins are indicated with arrow heads.
Acknowledgements We thank  L. Lopez-Gonzalez  ( UniversiteClermont Auvergne ) and  M. Fujii  ( Okayama University ) for technical assistance,  T. Hirayama  ( Okayama University ) for experimental support and helpful discussions, and  N. Suzuki  ( Okayama University ) for support with confocal microscopy analysis. This work was supported by a grant from the  European Research Council  ( ERC ,  I2ST 260742  to O. M. ), an  EMBO Young Investigator award  (to O. M. ), a  Young Researcher grant  from the  Auvergne Regional Council  (to O. M. ), and the  Max Planck Society  and  DFG  ( SFB 1101  to D. W. ). Y. I. was supported by the  Japan Society for the Promotion of Science (JSPS)  postdoctoral fellowship for research abroad, a  Grant-in-Aid for Research Activity Start-up  ( 26891018 ) and for Young Scientists B ( 15K18578 ), and Program to Disseminate Tenure Tracking System, MEXT, Japan.
Against this backdrop, graduate students at Princeton University and the University of California, Los Angeles (UCLA) were asked to produce seasonal forecasts of winter 2016 precipitation P, temperature T, and snow water equivalent (SWE) at a set of stations across the region. Specifically, they were asked to provide their best forecasts for an effective date of 1 January 2016, using methods of their choice, and using only data and/or model output available to them as of the forecast effective date. The Princeton University students were enrolled in a stochastic hydrology course while the UCLA students were enrolled in a physical hydrology course, which influenced the methods used to some extent. For both groups, however, the experiment challenged the students to apply and use seasonal forecast information from both dynamical and statistical models and combinations thereof.
b. Observations The observations for the 10 P and T stations (average record length 80 years) used for the forecast challenge were obtained from the University of Washington/UCLA Surface Water Monitor (SWM;  Wood and Lettenmaier 2006). The stations were selected to have a relatively uniform spatial distribution across the western United States (Tables  S1  and S2  and Fig. S1  in the supplemental material). Ten SWE stations (average record length 67 years) were taken from Natural Resources Conservation Service (NRCS) archives and were paired (i. e. , chosen to be relatively close to) the P and T stations. Gridded observations from the SWM (at 1/168 spatial resolution) were used to study the relationship between the Niño-3. 4 signal and precipitation and temperature anomalies. We used meteorological data from the NCEP-NCAR reanalyses  (Kalnay et al.
Acknowledgments. N. W. was supported by the  Netherlands Organisation for Scientific Research (NOW)   Rubicon Fellowship   825. 15. 003  (Forecasting to Reduce Socio-Economic Effects of Droughts). E. F. W. was supported by the  NOAA Climate Program Office  under grant  NA15OAR4310075. D. P. L. was supported by the  NOAA Climate Program Office  under grant  NA14OAR4310293. E. F. W. and D. P. L. designed the forecast experiment and initiated the experiment. X. G. H. and K. J. W. collected and aggregated the  Princeton University  and  UCLA  student forecasts. M. X. collected all the observations and made them available. A. B. , X. G. H. , H. H. , A. K. , Z. T. M. , B. R. P. , L. Q. P. , N. V. , K. J. W. , M. X. , S. Z. , and N. W. produced the forecasts. N. W. , E. F. W. , and D. P. L. contributed to the design of the figures and all contributed to the writing of the manuscript.
Wall geometry The polygon mesh for JET wall components that was used in this work is shown in figure  3  and was provided by the PFCFlux code  [20]  and post-processed for ERO2. 0 requirements, e. g. redundant polygons at the backsides of PFCs were removed. The inset in the red box is a magnification of the three limiter tiles investigated in the earlier ERO1. 0 modeling  [9] , and also shows the edges of the polygons in order to illustrate the typical polygon resolution of ca. 0. 7cm edge length. The polygons can in principle be subdivided in order to increase the resolution, however a sensitivity scan showed that the impact on surface-integrated results (e. g. the total number of eroded atoms) is negligible, so the resolution shown in the figure is sufficient. However, some very fine details such as the castellation of Be tiles  [21]  or bolt holes  [2]  are not described by the polygon mesh and are therefore neglected in this work.