dataesr/scientific-paragraphs-categorization huggingface dataset:
Stimuli We acquired our stimulus from the Chicago Face Database (CFD;  Ma et al. 2015). The CFD is a publicly available database of facial photographs categorised into Braces^1 and with extensive norming data, including objective measures (dimensions of facial traits, luminance, etc. ) as well as subjective ratings (age, attractiveness, dominance, trustworthiness, etc. ). Trustworthiness was asessed there on a 1-7 scale (1not at all; 7 extremely); assessments were elicited by the following instruction: BNow, consider the person pictured above and rate him/her with respect to other people of the same race and gender. (For example, if you indicated that the person was Asian and male, consider this person on the following traits [here: trustworthiness] relative to other Asian males in the United States)^and yielded a very high reliability (α =.
99; more details:  Ma et al. (2015). Subjective ratings for the original CFD were done by a convenience sample of 1087 raters, out of which 552 were female (and 227 did not report their sex). The raters self-reported diverse racial backgrounds, but the majority were White (516 White, 117 Asian, 74 Black, 72 biracial or multiracial, 57 Latino, 18 other and 233 did not report their racial background). The CFD version 2. 0. 3 used in the current study is an extended version of the database described in  Ma et al. (2015)  and includes updated norming data and a greater number of White and Black faces relative to the earlier version, as well as facial photographs of Asians and Latinos. We used stimuli from all of these Braces^. For many faces in the CFD, several emotional facial expressions are available, but for our analyses, we used only faces with a Bneutral^facial expression.
In the Chicago Face Database, used in the current study, the self-reported ethnic background of the raters was mixed, so many of the raters were exposed to faces of outgroups. It has been shown that racial identity may influence the activity of the brain regions responsible for emotional reactions (i. e. amygdala, which was also shown to activate during assessing trustworthiness of faces;  Engell et al. 2007; Winston et al. 2002)  when exposed to facial stimuli characteristic of outgroups  (Hart et al. 2000; Phelps et al. 2000). As the neurophysiological correlates of amygdala activation include negative emotions such as fear and aggression, it cannot be ruled out that trustworthiness ratings in the CFD were influenced by the ethnic mismatch of the raters and stimuli. If this was the case, the association between trustworthiness and subtle morphological facial features such as sclera size might have been outweighed by a relatively strong effect of racial membership.
Stimulation consisted of 1-15 s trains of blue light pulses (2 ms duration; ~0. 25 mW) delivered at 10 Hz, repeated ten times every 60 s in each cell. Electrophysiological signals were recorded using a Multiclamp 700B amplifier (Molecular Devices, Sunnyvale, CA) connected to a Digidata 1440A digitizer (Molecular Devices). Signals were low-pass filtered at 3 kHz before being digitized at a rate of 10 kHz and stored on a personal computer. Signal acquisition and analysis was carried out with pClamp 10 (Molecular Devices). Spikes were detected using the threshold crossing method. In each cell, spike fidelity was calculated by dividing the number of light-evoked spikes by the number of blue light stimuli and expressed as a percentage. Behavioral tests. All experimental females were brought into behavioral estrus by ovariectomy (OVX) in adulthood and combined treatment with estradiol (E) through a silastic capsule and an acute injection (3 h before testing) with progesterone (P), unless stated otherwise (for all details on hormone treatments, see Supplementary Table  1 ).
nNOS-ir and BL+ nNOS-ir cell bodies were counted unilaterally in eight to ten sections containing the VMHvl (Bregma -1. 34 to -1. 94 according to ref. 63. Cell counts are expressed as mean number per section for each experimental condition. Statistical significance was determined using Bonferroni's multiple comparison test. Statistics. Randomization was not used in this study and no statistical methods were used to predetermine sample size. Investigators were blinded to the group allocation during experiments or data analysis. Data were analyzed using the GraphPad Prism 7 software. For all statistical comparisons, we first analyzed the data distribution with the Shapiro-Wilk test for normality. Preference score data were analyzed by comparison to hypothesized mean (H0: mean equal 0) using a non-directional one-sample two-tailed t test (Figs.
Acknowledgements We thank  Ramona Grünewald  for providing excellent technical assistance. This work was supported by grants from the  Dutch Science Foundation (Nederlandse Organisatie voor Wetenschappelijk Onderzoek ;  NWO-VICI 453-08-003 ) and the  Belgian Fonds National de la Recherche Scientifique  ( FNRS-PDR T. 0207. 13 ) to J. B. , and the  German Science Foundation (Deutsche Forschungsgemeinschaft)  through grants  SPP1392  and  BO1743/6  to U. B. V. H. was also supported by two short-term missions from  COST action   BM1105 , " GnRH deficiency: Elucidation of the neuroendocrine control of human reproduction ". J. B. is a research director at the FNRS.
All DOSY (Diffusion Ordered Spectroscopy) measurements were performed at 298 K on a Bruker Avance III HD 400 spectrometer operating at 400. 33 MHz and equipped with a 5 mm Bruker multinuclear z-gradient direct cryoprobe-head capable of producing gradients in the z direction with a strength of 53. 5 G cm -1. For each sample, 3 mg was dissolved in 0. 4 μL of DMSO-d 6 for internal lock and spinning was used to minimize convection effects. DOSY spectra were acquired with the ledbpgp2s pulse program from the Bruker topspin software. The duration of the pulse gradients and the diffusion time were adjusted in order to obtain full attenuation of the signals at 95% of the maximum gradient strength. The values were 2. 0 ms for the duration of the gradient pulses and 300 ms for the diffusion time. The gradient strength was linearly incremented in 16 steps from 5% to 95% of the maximum gradient strength.
A delay of 3 s between echoes was used. The data were processed using 8192 points in the F2 dimension and 256 points in the F1 dimension with the Bruker topspin software. Field gradient calibration was accomplished at 25 °C using the self-diffusion coefficient of H 2 O + D 2 O at 19. 0 × 10 -10 m 2 cm -1. Dimethylformamide soluble polymers were first solubilized in concentrations of 1 mg mL -1 and their masses were determined by size exclusion chromatography (SEC) in DMF at 50 °C using a refractive index (RI) detector (Varian). Analysis was performed using a three-column set of TSK gel TOSOH (G4000, G3000, and G2000 with pore sizes 20, 75, and 200 Å respectively, connected in series). A Bruker spectrometer was used for ATR-FTIR analysis. Hydrodynamic diameters (D h ) and size distributions of the SCNPs were determined by DLS on a Malvern Zetasizer Nano ZS system operating at 20 °C with a 4 mW He-Ne 633 nm laser module.
Samples were filtered through a 0. 2 µm PTFE filter prior to measurement and quartz cuvettes were used. Measurements were made at a detection angle of 173°(back scattering), and the data were analyzed using the Malvern DTS 6. 20 software, using the multiple narrow modes setting. All measurements were made in triplicate, with 10 runs per measurement. TEM analyses were performed on a JEOL 2011 (LaB 6 ) microscope operating at 200 keV, equipped with a GATAN UltraScan 1000 digital camera. The conventional bright field conditions were lacey carboncoated copper grids (Agar Scientific, 400 mesh, S116-4) coated with a thin layer of graphene oxide. SCNP solutions were diluted to 2 mg mL -1 in MeOH before 4 µL of each sample were drop-deposited onto the graphene oxide coated grids, blotted immediately and allowed to air dry.
Ambient conditions were used for measurements with a sample to detector distance of 2 m. The prepared solutions (concentration: 1 mg mL -1 , THF as solvent) were added into capillaries of 2 mm thickness and fixed perpendicularly to the beam. The data were corrected by subtracting the result of the blank capillary filled with the same THF employed for preparing the samples and applying the proper transmission corrections. All the SAXS measurements were carried out by Warwick Scientific Services.
QUANTIFICATION AND STATISTICAL ANALYSIS Statistical analyses were performed with the InfoStat package version 2009 (Grupo InfoStat, FCA, Universidad Nacional de Cordoba, Argentina). To determine if data met the criteria for ANOVA analysis normality was tested using Shapiro-Wilks test and the homogeneity of variance was assessed with Levene's test. p < 0. 05 was considered statistically significant. In the cases were data did not meet these criteria, transformations were. If transformations were not sufficient to meet the criteria, non-parametric analysis were performed. For the analysis of pupation curves, each independent replicate, i. e. , each vial with 60 initial larvae, was adjusted to a Gompertz non-linear regression model, and the median time to pupation was estimated. The statistical tests, number of replicates and special requirements for each experiment, as well as type of data transformation performed if necessary are detailed in the legends of the corresponding figures.
ACKNOWLEDGMENTS We thank the  Bloomington Stock Center  and the  Vienna Drosophila RNAi Center  for fly stocks. We acknowledge  Christine Arnould (Plateforme DImaCell, INRA, UniversiteBourgogne Franche-Comte), Aymeric Fabre, Serge Loquin, Cindy Menage, Kevin Piffaretti , and JoseSolonot for their technical assistance. We thank  Dr. Bill Hansson  and  Dr. Markus Knaden  of the  Max Plank Institute for Chemical Ecology (Jena, Germany)  for access to the resources used to perform experiments at their laboratory. We also thank  Dr. Nuria Romero  of the  Institute de Biologie Valrose at Parc Valrose (Nice, France ) for discussions about the data related to this article. We thank  Pr. David Featherstone  and  Dr. Anna Ziegler  for their assistance and discussions. Research in.
This allowed for instance to reveal the role of individual effectors from the bacterial pathogen Xanthomonas axonopodis pv. manihotis in virulence  (Mutka et al. , 2016). High-throughput image-based plant phenotyping proved valuable in crop breeding and for research purposes  (Araus and Cairns, 2014; Fahlgren et al. , 2015; Coppens et al. , 2017). There is therefore a need to improve our ability to generate large datasets of quantitative plant disease measurements at low cost, low footprint and reduced human intervention  (Czedik-Eysenberg et al. , 2018). Because it is generally nondestructive, image-based disease measurement also gives access to the dynamics of disease progression. This enabled for instance to study the spatial and temporal distribution of pathogens in plants tissues  (Mutka et al.
The density of non-synonymous SNPs specific to Lip-0 and Rub accessions per gene followed an exponentially decreasing distribution (Fig. 3B ). Three genes harbored at least four non-synonymous SNPs in Lip-0 and Rub but not any non synonymous SNP in Nok-1, Sha or Rld-2 (Fig. 3C, Table 1 ). This includes AT1G23935, encoding an uncharacterized protein with similarity to apoptosis inhibitory proteins, AT2G33090, encoding an uncharacterized member of the transcription elongation factor IIS family, and AT5G44870 encoding LAZ5, a disease resistance protein of the TIR-NBS-LRR (NLR) family with similarity to RPS4 and CSA1  (Palma et al. , 2010). The five nonsynonymous SNPs present in the dataset from  (Atwell et al. , 2010)  resided in the NB and the LRR domain of LAZ5 (Fig. 4A ). Two additional non-synonymous SNPs are present in the Lip-0 allele of LAZ5 according to data from http://signal.
Inoculations were performed as described in  (Badet et al. , 2017b) , using PDA plugs of 5mm diameter colonized by the fungus placed upside down on the adaxial surface of leaves (mycelium in contact with the leaf). The experiment was repeated three times independently and results from the three replicates were combined for analysis. Statistical analyses were performed using R software and the 'car' library for type II ANOVA and pairwise t test with Benjamini and Hochberg p-value correction  (Benjamini and Hochberg, 1995; R Core Team, 2014). Distributions of LDT were normalized by log transformation. Plots were made using the 'ggplot2' library  (Wickham, 2010). Image analysis pipeline. The area of necrotic disease lesions was computed by numeric method for each individual leaf at each time point.
We designed is a thresholding method based on color analysis using the scikit-image python image analysis toolbox  (van der Walt et al. , 2014). The method splits images of an infected leaf into three layers corresponding to the background, the lesion and the leaf. The 'background' corresponded to pixels with a saturation value superior or equal to 0. 3 in HSV color space. The lesion corresponded to pixels with red component higher than green value in RGB color space. The area of disease lesions was computed as the sum of pixels in the 'lesion' layer. The remaining pixels were attributed to the 'leaf' layer. Image analysis allowed the collection of lesion area values over time. Every kinetics was fitted by a polynomial regression. The latency time and lesion doubling time were extracted from the fit.
Design of the Analysis of polymorphisms and identification of candidate genes. We used a dataset of 214,000 SNPs on 1,196 A. thaliana accessions  (Atwell et al. , 2010; Horton et al. , 2012)  to search for non-synonymous mutations present in Lip-0 and Rubezhnoe accessions but not in Col-0, Nok-1, Shahdara and Rld-2. The functional consequences of SNPs were predicted automatically using a script derived from the BioPython library  (Cock et al. , 2009)  provided as Supplementary file 2. For this, gene models from TAIR version 9 were used. Predictions were verified manually for the top candidates using ExPASy translate tool and http://signal. salk. edu/atg1001/ genome browser.
Acknowledgements We are grateful to past and present members of the  QIP lab  for stimulating discussions and suggestions. This work was supported by a starting grant of the  European Research Council  ( ERC-StG 336808  project  VariWhim ) to S. R. and the  French Laboratory of Excellence  project  TULIP  ( ANR-10-LABX-41 ;  ANR-11-IDEX-0002-02 ).
The microfabrics were analyzed by polarized light microscopy and scanning electron microscopy (SEM), including electron backscattered diffraction (EBSD) measurements and energy dispersive spectroscopy (EDS) using a field emission microscope (SU5000 Hitachi) at Ludwig-Maximilians University, Munich, Department of Earth and Environmental Sciences. The sections for EBSD measurements were polished by an alkaloid colloidal suspension (Syton) prior to carbon coating. EDS and EBSD signals were acquired using the Aztec software (Oxford technology). For EDS measurements a working distance of 10 mm and for EBSD a working distance of 20-25 mm was applied at an acceleration voltage of 20 kV. For EBSD measurements we used a pre-tilted holder with the specimen at an angle of 70° to the beam. Processing of the data was performed with the Channel 5 software (Oxford technology).
10 to 12 spots were measured per sample with an acquisition time of 5 s. Background correction and peak fitting of the G band (1580 cm -1 ), D1 band (1350 cm -1 ) and D2 band (1620 cm -1 ) was performed using the software Peakfit (Version 4. 06). Since we used a similar setting for the measurements as  Rahl et al. (2005)  temperatures were calculated by their equation using R1, which is the ratio of peak heights (D1/G), and R2, the ratio of peak areas (D1/(G + D1 + D2)). By this method, metamorphic peak temperatures can be predicted to ± 50 °C  (Rahl et al. 2005). A comparison with temperatures calculated using only R2 after  Beyssac et al. (2002) , showed no significant differences for the four samples measured (Table  2  in supplementary data). The standard deviation of the obtained temperatures from 10 measurements per sample was generally higher using the equation by  Rahl et al.
Acknowledgements This study was funded by the  Deutsche Forschungsgemeinschaft  ( DFG Grant  no. TR534/5-1 ). Wolfgang Dörr ,  Jochen Krahl ,  Gernold Zulauf ,  Bernhard Stöckhert  and  Jens Nüchter  are gratefully acknowledged for discussions. We thank  Melanie Kaliwoda  for the opportunity and her support to use Raman spectroscopy and  Namvar Jahanmehr ,  Michael Herrmann  and  Vladimir Ruttner  for preparation of thin sections. Uwe Ring ,  Jeffrey Rahl  and  Soumyajit Mukherjee  are gratefully acknowledged for constructive reviews that greatly improved the quality of the manuscript. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://creat iveco mmons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
The EMSC information system includes websites, a smartphone app and a Twitter quakebot, all of which act at the interface between the two feedback loops shown. These three channels collect data from eyewitnesses, automatically curate, analyze and collate them, integrating them with seismically derived information. The system then produces publicly accessible and timely information, which, in turn, attracts more eyewitnesses and, subsequently generates more data. This facilitates the continuous development and improvement of the EMSC products based on ongoing user feedback and observed effectiveness. product quality, generating a fast and positive feedback loop (Fig. 1 ). There are two types of collected data from eyewitnesses: crowdsourced data (felt reports, comments, and geo-located pictures and videos which are voluntarily shared by users.
A close-up (below) shows that users start launching the LastQuake app within around 12 s of the earthquake occurrence. The traffic increase was automatically detected in 21 s from the app traffic and in 36 s from websites traffic. There was no detection of increase of earthquake related publication on Twitter. FYR of Macedonia is the only country where the traffic on mobile website is not prevailing. This activity was recorded after two series of felt earthquakes in 2016 (Fig. 4 ) and 2017 which heightened anxiety in a country wary of a possible re-occurrence of the 1963 earthquake which flattened Skopje the capital city  [19]  and facilitated high adoption levels of the LastQuake app. surge in the number of tweets (i. e. , messages published on Twitter) containing the keyword "earthquake" in various languages  [20, 21]  and secondly, the analysis of traffic generated by LastQuake app launches, which works in a similar way to that of website traffic analysis by detecting concomitant app launches (Fig.
4 ). LastQuake Twitter quakebot is essential for engaging with social network users and driving them to visit the website and share their felt experience in a way that enables automatic processing for product Fig. 3. Crowdsourced earthquake detections are automatically published on the different components of the public information system: our websites, the Twitter quakebot @LastQuake and the eponym smartphone app. The tweet contains the word "earthquake" in the local language to increase visibility to searches engines and a link allows eyewitnesses to report their experience on our website. Eyewitnesses visiting our websites are invited to download the app. As of October 2017, the LastQuake Twitter account has 50,000 followers, and there are 260,000 apps in operation around the globe. Websites traffic remains highly dependent on seismic activity.
Reported effects and their dissemination Felt reports describing the observed effects are automatically curated -notably the ones reporting massive damage are automatically excluded as being far-fetched-and merged in a situation map which is regularly updated on the information system (Fig. 7 )  [23]. After a slight adjustment, determined by comparing with reference datasets, results prove to be as reliable as the ones obtained from more traditional online questionnaires. However, the collection of felt reports through cartoons is faster and the number of collected reports is greater  [23]. Felt reports are also statistically analyzed to produce a curve representing the average variations of the shaking level relative to epicentral distance and to estimate the number of people subjected to the different levels (Fig.
The spatial distribution of ground shaking estimated from magnitude, earthquake location and ground-motions prediction equations is compared to the number of inhabitants (determined from the Landscan database of global population  [27] ), building stock inventory and related vulnerability. The impact results are calibrated on past destructive earthquakes  [16]. On the app, the destructive earthquakes, as defined by the impact assessment tool, appear in red, while felt but non-damaging earthquakes appear in color ranging from green to orange as a function of the number of people who reported it and the maximum degree of shaking reported. Additionally, a tsunami logo appears when tsunami information has been released by an authoritative source, as well as a link to tsunami information resources.
Acknowledgments Parts of the work presented represent the results of the  CARISMAND  project. The  CARISMAND  project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement  N°653748. The present article reflects only the authors' view and the  European Commission  is not responsible for any use that may be made of the information it contains. Over the years, the LastQuake initiative has received support from many partners including the  Fondation MAIF , the  Fondation THALES, the Ministère de la Transition écologique et solidaire (MTES) -Direction générale de la prévention des risques (DGPR) , the  EMSC members, Digital Element  (for providing IP locations) as well as suggestions from participants.
Data collection The data were collected using a questionnaire. One of the researchers (V. M. ) coordinated the data collection with regular online meetings and email interactions to ensure that the method was consistently followed. The questionnaire required participants to report up to five words or phrases that immediately come to mind while thinking about hearing loss. 396 of the 404 respondents (98%) provided five words or phrases. Seven of the participants provided four associations and one person provided only two. The method is known as the free association task, which is frequently used to access the semantic content of social representation. This is a well-established method and has been used in several studies  (Linton et al. 2013; Danermark et al. 2014). The object of representation (i.
Data analysis For this article data from all four countries were combined, and analysed together in order to investigate differences based on demographic factors. First, the responses from free association task were analysed using qualitative content analysis  (Graneheim and Lundman 2004). This step involved grouping of words and phrases that have the same meaning into categories. The data analysis from all countries was done mainly by one of the researchers (V. M. ) and cross-checked by another researcher (P. G. ). If the meaning of the words or phrases was not clear, or consensus was not reached, the researchers who collected and translated data in the respective countries were consulted. Second, a cluster analysis was done with the Reinert algorithm  (Reinert 1983 (Reinert , 1990;; Ratinaud and Marchand 2012).