dataesr/scientific-paragraphs-categorization huggingface dataset:
Analysis Desirability ratings were converted to session-wise z scores. The first goal of the study was to assess whether MD (the difference in standardized desirability rating between G vs NG conditions) was lower in ASD than control participants. We used t tests to compare MD, ratings in the desire attribution task, and performance in the recognition task between groups (ASD vs controls). The data of the recognition task was missing for one participant due to an error in testing. The second goal was to test whether MD was associated with clinical features of ASD. We looked for Pearson's correlations between MD in the ASD group and the following variables: social and physical anhedonia scores and depression and social judgment scores. p values of correlations were not corrected for multiple testing since none did even reach the uncorrected threshold.
Accuracy and speed were equally emphasized. Historical events. Thirty-six historical events were used (Fig. 1B ; Table  1 ). Past events were public and well-known events to avoid subjectspecific recollection bias as much as possible; similarly, future events were highly probable events, such as future construction sites or upcoming sport events to reduce the impact of event probability with temporal distance. The final set of historical events covered a span of 54 years centered on 2013 (year at which fMRI data were collected) and 320 angular degree of longitude centered on Paris (experiment location). During the fMRI scans, historical events were distributed uniformly across dates and longitudes and according to the imagined self-position and the dimension: for example, when participants imagined themselves 9 years ago and made a temporal judgment, the event set was centered on the year 2004 and comprised 24 events.
Similarly, when participants imagined themselves in Cayenne and produced a spatial judgment, the event set was centered on Cayenne and comprised 24 events (Fig. 1C ). MRI data acquisition and analysis. Anatomical MRI and fMRI were acquired using a 3T MRI scanner (TIM Trio; Siemens). Each participant underwent 7 min anatomical imaging using a T1-weighted MPRAGE sequence (160 slices; repetition time, 2300 ms; echo time, 2. 98 ms; FOV, 256; voxel size, 1 ϫ 1 ϫ 1 mm 3 ) and four sessions of 15-20 min of functional imaging with a 32-channel head-coil and high-resolution multiband imaging  (Xu et al. , 2013)  with multiband factor ϭ 3, GRAPPA factor ϭ 2, 69 interleaved axial slices, voxel size 2 ϫ 2 ϫ 2 mm 3 , repetition time ϭ 1. 5 s, echo time ϭ 30 ms. We used statistical parametric mapping (SPM8; Wellcome Trust Centre for Neuroimaging, London; http:// www.
A behavioural design approach (BDA) software was developed as a simple case to valid the applicability of this method. However, there are still many problems demanding further research. Such as, how to categorize disparate users, e. g. specialists, experienced, "normal" users and newcomers, how could the designer acquire more knowledge of the user, and so on. Due to the final operator of product is user not the customer, we propose that developer and designer can develop a knowledge base in the initial design stage not only for customer, but also for user. Beyond the customer and user requirements, this type of database should include various information about user such as user's gender, age, region, experience, etc.
The major aim of the current paper is to present an individual analysis of two physical parameters -duration (ms) and intensity (dB) -on four survey areas of Brazilian Portuguese spoken in the north of Brazil: Belém, Baião, Mocajuba and Curralinho. The selected data for this analysis stem originally from AMPER-POR database normalized by zscore. Formerly, statistics analysis has shown that duration and intensity play a secondary role in the modal intonation characterization. These results comply with the main analysis performed on intensity in prosody studies of Portuguese by the AMPER project where it emerges not as strong parameter in modal intonation discrimination. Contrastingly, 'duration' has shown up as a vigorous physical parameter for the characterization of modal intonation.
Introduction Despite the fact that fundamental frequency (henceforth F0), intensity and duration are regarded as the main physical factors related to intonation, there is an agreement indicating that intensity and duration are not strong factors for the characterization of modal intonation among descriptions of prosodic variation in Portuguese  (Moutinho & Coimbra 2010; Moutinho et al. 2008; Abraçado et al. 2007). The variety of Brazilian Portuguese (henceforth BP) spoken in the state of Pará is being mapped by the UFPA 1  team committed to the AMPER-POR 2  project (Atlas Multimédia Prosodique de l'Espace Roman for the Portuguese Language) since 2007  (Cruz et al. 2012). As a direct contribution to the AMPER North project, nine survey areas from the state of Pará have been already mapped by the referred team, namely, the municipalities of Abaetetuba  (Remédios 2013) , Baião  (Lemos 2015) , Bragança  (Castilho 2009) , Cametá  (Santo 2011) , Curralinho (Freitas Neto 2013), Mocajuba  (Costa 2015) , Mosqueiro  (Guimarães 2013) , Santarém  (Lima Forthcoming)  and Belém  (Cruz & Brito 2014).
All methodological procedures established by the AMPER-POR project's overall coordination are applied to both the formation of corpora and the processing of data. The purpose of using the same corpus for all Portuguese varieties is to enable a comparative analysis of the target varieties and to contribute to a deeper understanding of prosodic variation of the Portuguese language. The description of the intonation modality and the identification of a prosodic pattern, jointly, correspond to the main objectives of the investigations associated to the AMPER project. The target modalities in this study primarily comprise the declarative (denoted by A) and yes/no question (denoted by I) sentences. The prosodic analysis focuses both on initial (pre-nuclear) and final (nuclear) nominal phrases of sentences.
TXT files in ascii format containing the acoustic measurements of vowel segments and the. TextGrid files of PRAAT software containing the phonetic segmentation of audio files. We selected speech samples from six speakers, which are part of the corpora constituted by 4 selected survey areas to undergo the intradialectal analysis proposed here. The speakers profiles are described in Table  2  below. The statistical analysis of 1. 728 data areas (12 sentences x 2 intonation modalities x 3 best repetitions x 4 survey areas x 6 speakers) that comprise the total corpus of this work, demanded an automated data processing. The F0 measures in Hz on segmentation of the vowel nuclei presented at the TXT files have been stylized by the Prosogram 3  software. This has resulted in a stylization of intonation curve perceived as a set of straight lines.
Conclusion This paper presented the results of a research work linked to AMPER project. Four survey areas from a northern Brazilian state named Pará, where BP is spoken, were analyzed -Belém, Baião, Curralinho and Mocajuba. Our main purpose was to carry out an individual analysis of two physical parameters -duration and intensity -by means of an intradialectal analysis. Considering all 4 target survey areas comprise AMPER corpus, a comparative analysis was enabled. Therefore, a balanced corpus of 1. 728 data (12 sentences x 2 modalities x 3 repetitions x 4 survey areas x 6 speakers) was composed. The entire corpus was normalized by Prosogram software (F0 plots, intensity and V-to-V duration). Data reveal similarities among the spoken varieties in the north of Brazil with regard to modal intonation.
Acknowledgments It is worthwhile remarking that in order to present these results, this paper has received funding from the  Federal University of Para (UFPA)  through its  PIAPA Program. We would also like to thank  Rosinele Lemos ,  Sebastiana Costa ,  João Freitas Neto  and  Camila Brito  for making their data available for this study. Special thanks go to  Heliana Mello  ( UFMG ) and  Tomasso Raso  ( UFMG ) for the organization of the IX Lablita/IV LEEL workshop and for their further support.
The PCR products were visualized on a 1% agarose gel stained with Gel Red (Biotium, Hayward, CA, USA) and purified using a PCR purification kit (Bioneer). The purified PCR products were sequenced with a 3130-XL Automatic Sequencer (Applied Biosystems) at the Sequencing and Genotyping Service of FCEN-UBA. Sequences were inspected, trimmed if necessary and aligned using ClustalW  (Thompson et al. , 1994). We also checked that the sequences had no gaps or stop-codons that would alter the reading frame, using MEGA v6  (Tamura et al. , 2013). All sequences were deposited at GenBank (see Table  S1  for voucher specimens and accession numbers (AN. )). The most closely related species Wasmannia rochai was used as an outgroup (GenBank AN. EF459824).
Phylogenetic analysis and gene tree estimation Unique haplotypes were determined using DNAsp v5. 0  (Librado & Rozas, 2009). Phylogenetic relationships between haplotypes were inferred using both maximum parsimony (MP) and probabilistic (Bayesian Analysis (BA)) criteria. The MP analysis was performed using TNT v1. 1  (Goloboff et al. , 2008). Nodal supports were assessed by bootstrap resampling (1000 replicates). The BA was implemented in BEAST v1. 6. 2  (Drummond & Rambaut, 2007; Heled & Drummond, 2010). This software allowed us to co-estimate phylogeny and divergence times of the main clades within W. auropunctata. We inferred that the best model of sequence evolution under Akaike's information criterion was TrN+I+G using JMODELTEST2  (Darriba et al. , 2012). To further establish the relationships among haplotypes, we constructed a haplotype network using TCS v1.
Genetic diversity Number of haplotypes (h), haplotype diversity (H d ) and nucleotide diversity (p)  (Nei, 1987)  were determined for each haplogroup identified in the haplotype network. To detect possible patterns of geographic structure, COI genetic distances were mapped on the landscape using Alleles in Space (AIS) v1. 0  (Miller, 2005). This program was created to analyse from a geographical point of view the genetic diversity of species with a continuous and wide distribution, as is the case for W. auropunctata. The software can be used without defining the populations a priori because it only requires sample collection of specimens in different localities throughout the landscape under study. The Delaunay triangulation-based connectivity network was used to link neighbouring sampling locations together and to calculate genetic distances (see Guzm an et al.
, 2012 for further explanations). The AIS program displays a three-dimensional graph representing a landscape of these genetic distances, which are expressed as surface heights. Residual genetic distances were used to avoid possible effects of isolation by distance. For the total area covered (2204 km 2 ), we specified an 89 9 24 grid and 0. 5 as a distance-weighting parameter. To better visualize the AIS height output, we imported the output file into DIVA-GIS v7. 1. 7  (Hijmans et al. , 2004)  and created a two-dimensional colour hotspot map overlaid on the geographic study area, with colours corresponding to heights of genetic distance between points.
Microsatellite data To corroborate if nuclear information supported mtDNA results, we analysed the genotypes of 151 individuals (111 workers and 40 queens) from the data set of  Rey et al. (2012). Our data set consisted of 68 individuals from clade A and 83 from clade B, of which 79 samples were from Argentina, 20 from Brazil, 30 from French Guiana and 22 from Costa Rica. To avoid any impact of the nest/colony structure on the results, we only used two workers and one queen per nest for clonal colonies and two workers and two queens per nest for sexual colonies. The genotypes consisted of the 12 microsatellite loci designed by  Fournier et al. (2005b). The microsatellite matrix is available in Appendix S2. We employed the Bayesian clustering method implemented in STRUCTURE v2. 3. 4  (Pritchard et al.
Ecological niche modelling in the Quaternary: past and current distributions To estimate W. auropunctata distribution models across Quaternary climatic fluctuations, we implemented the maximum entropy machine-learning algorithm using MAXENT v3. 3. 3  (Phillips et al. , 2006). This program uses presence-only data and environmental variable layers for the studied area. It generates an estimate of probability of species presence ranging from 0 to 1, where 0 is the lowest and 1 the highest probability. Although it is recognized that species distribution is usually controlled by more complex biological processes such as interactions among species, dispersal history and resource heterogeneity (see  Fitzpatrick et al. , 2007;  for limitations of ENMs), the usefulness of these models is contingent on their appropriate use  (Ara ujo & Peterson, 2012).
, 2011 (Werneck et al. , , 2012)). All bioclimatic variables available were tested for multicolinearity by examining cross-correlations among variables (Pearson correlation coefficient, r) within the geographical space based on the occurrence records. LGM layers were at a 2. 5 arc-minute resolution. We trained the model including: a) species occurrence data sets within the native range (i. e. excluding locations where the species was introduced), and b) occurrence data sets only for native clade B populations. Data included records from our GPS (Table  S2 ) and Antweb (http://www. antweb. org/bigMap. do?-taxonName=myrmi cinaeWasmannia%20auropunctata&project=allantweba nts). This analysis requires the clade identity of each sample and clade A could not be analysed separately because of the small, insufficient number of specimens that clearly belonged to this clade.
We clipped the bioclim rasters to a polygon containing a reasonably estimated native range of W. auropunctata and then projected onto this same area to determine the potential distribution areas. We repeated this analysis with LIG-and LMG-based projections. In MAXENT, we used the default convergence threshold (10-5) and increased maximum iterations to 1000; the program automatically selected regularization values and functions of environmental variables. For each run, we used 75% of the localities to train the model and randomly selected 25% of the localities to test the model. We evaluated model performance using a threshold-independent method based on the area under the curve (AUC) of receiver-operating characteristics curve (ROC)  (Swets, 1988). The AUC value ranges from 0. 5 (random accuracy) to a maximum value of 1 (perfect discrimination).
Bayesian phylogeographic analysis An animation of the inferred distribution changes of W. auropunctata through time can be viewed in http:// mlandis. github. io/phylowood/ by opening the txt matrix (Appendix S1). Bayesian phylogeographic inference suggested that the common ancestor of clades A and B would have lived in central Brazil (Tocantins state) 3. 92 million years before present (My BP) (95% highest posterior density 2. 67-5. 19) (red star in Fig. 7a ). A dispersal event from this area would have occurred northward to the Amazon rainforest and southward to the Del Plata river basin and the Atlantic rainforest, giving rise to clades A and B, respectively, between 3. 92 and 1. 26 My BP (Figs  7a  and 8 ). The common ancestor of clade A was most probably located in the eastern state of Par a in Brazil, at about 1.
Acknowledgments We are grateful to  Cristian Tomatis  and Noelia Guzm an for laboratory assistance; to  Laura Varone ,  Priscila Hanisch  and  Francisco Sola  for providing some of the samples; and to  John Heraty ,  Edward Lebrun ,  Dietrich Gozek  and  Silvia Pietrokovsky  for their helpful comments and suggestions on the manuscript. This research project was supported by grants from  Universidad de Buenos Aires, ANPCyT  and  CONICET ,  Argentina , and from  USDA-ARS-Pacific Basin Agricultural Research Center. OR is also grateful to the  French Minist ere de l'Ecologie et du Developpement Durable  ( ECOTROP program ) and the  French Agropolis foundation (RTRA-Montpellier ,  BIOFIS  project  1001-001 ) for financial support.
Sequencing of Asterias rubens radial nerve transcriptome Radial nerve cords (approx. 30 mg) dissected from a male adult specimen of A. rubens were used for RNA isolation (Total RNA Isolation System, Promega). Library preparation (TruSeqv2 kit, Illumina) was performed at the QMUL Genome Centre and sequencing was performed on an Illumina HiSeq platform at NIMR (Mill Hill), with cBot used to generate clusters. A total of 168 776 495 Â 100 bp reads were obtained and raw sequence data (SRP068147; http:// www. ncbi. nlm. nih. gov/sra/SRP068147) were assembled using SOAPDENOVO-TRANS v. 1. 0 (http://soap. genomics. org. cn/SOAPdenovo-Trans. html), a short-read assembly method developed by the Beijing Genomics Institute  [35]. Contigs were assembled from reads with an overlap greater than 31 bp, which were then mapped back to the raw reads.
BLAST-based identification of neuropeptide precursors in Asterias rubens To search for transcripts encoding putative neuropeptide or peptide hormone precursor proteins in A. rubens, the sequences of neuropeptide or peptide hormone precursors previously identified in the sea urchin S. purpuratus  [5, 6, 11, 16, 17, 37, 38] , the sea cucumber A. japonicus  [10]  and the starfish species Asterina pectinifera  [39]  were submitted individually as queries in tBLASTn searches of the contig database with the BLAST parameter e-value set to 1000. Contigs identified as encoding putative precursors were analysed after translation of their full-length DNA sequence into protein sequence using the ExPASy TRANSLATE tool (http:// web. expasy. org/translate/). Proteins were assessed as potential precursors of secreted bioactive peptides by investigating: (i) the presence of a putative N-terminal signal peptide rsob.
Analysis of the sequences of neuropeptide precursor transcripts identified in Asterias rubens The protein sequences of candidate neuropeptide precursors and polypeptide hormone precursors were annotated in colour as follows. The N-terminal signal peptide, identified using SIGNAlP v. 3. 0, was coloured blue; putative dibasic or monobasic cleavage sites were coloured green; and the putative neuropeptide(s) or peptide hormone(s) derived from the precursor was coloured red, with C-terminal glycine residues (when present) shown in orange. Figures compiling the colour-coded precursor sequences were prepared (figures 2, 9, 18 and 21). The DNA sequences of transcripts encoding precursor proteins were also compiled, together with the underlying encoded protein sequence (see electronic supplementary material, figures S1 -S40).
The sequences of A. rubens precursor proteins or the putative neuropeptides/polypeptide hormones derived from them were aligned with homologous proteins/peptides in other bilaterian species, some of which were identified here for the first time. Alignments were generated and edited using JALVIEW  [47]  and MAFFT  [48]  with JABAWS web service  [49] , employing default settings (gap opening penalty at local pairwise alignment ¼ 22, similarity matrix ¼ Blosum62, gap open penalty ¼ 1. 53, group size ¼ 20, groupto-group gap extension penalty ¼ 0. 123). GENEDOC (http:// genedoc. software. informer. com) was used to annotate the alignments and prepare alignment figures.
3. 1. Discovery of starfish neuropeptide precursors that provide new insights into neuropeptide evolution at the superphylum level 3. 1. 1. Precursor of two kisspeptin-type peptides (ArKPP) A kisspeptin (KP)-type neuropeptide precursor in A. rubens (ArKPP) was identified as a 149-residue protein comprising a predicted 24-residue N-terminal signal peptide and two putative KP-type peptides-ArKP1 and ArKP2 (figure  2a ; GenBank: KT601705). In common with human KP, ArKP1 has a C-terminal NxxSxxLxF-NH 2 motif, but unlike human KP, ArKP1 has two cysteine residues in its N-terminal region, which may form a disulfide bridge. ArKP2 is similar to ArKP1 but it lacks the N-terminal pair of cysteine residues present in ArKP1 and it has additional residues in its C-terminal region. Discovery of ArKPP is important because it is the first KP-type precursor to be identified in a nonchordate species, consistent with the occurrence of KP-type receptors in non-chordates  [5, 6].
Precursor of a melanin-concentrating hormone-type peptide (ArMCHP) A melanin-concentrating hormone (MCH)-type neuropeptide precursor in A. rubens (ArMCHP) was identified as an 88residue protein comprising a predicted 24-residue N-terminal signal peptide and a C-terminal 28-residue MCH-type peptide with two cysteine residues, which is preceded by a putative dibasic cleavage site (figure  2b ; GenBank: KT601706). ArMCHP was identified on account of its sequence similarity with Spnp14, a putative neuropeptide precursor in the sea urchin S. purpuratus  [9]. However, comparison of ArMCHP with vertebrate neuropeptides revealed sequence similarity with MCH-type peptides, as illustrated in figure  4. Furthermore, the location of the putative neuropeptide ArMCH in the C-terminal region of ArMCHP is likewise a characteristic of MCH-type precursors in vertebrates, providing further evidence of orthology  [66].
Precursor of a somatostatin-type peptide (ArSSP) A somatostatin (SS)-type neuropeptide precursor in A. rubens (ArSSP) was identified as a 132-residue protein comprising a predicted 24-residue N-terminal signal peptide and a 13-residue SS-type peptide that is preceded N-terminally by a putative dibasic cleavage site (figure  2d ; GenBank: KT601708). ArSSP was identified based on its sequence similarity with Spnp19, a putative neuropeptide precursor previously identified in the sea urchin S. purpuratus  [9]. However, comparison of ArSSP and Spnp19 (SpSSP) with known neuropeptide precursors revealed similarity with vertebrate SS/cortistatin-type precursors. For example, both ArSS and SpSS share a CxxxFxxxxxxC motif with human SS and cortistatin (figure  6 ). In vertebrate SS/cortistatin-type peptides, the two cysteine residues form an intramolecular disulfide bridge  [98] , and therefore it is likely that the same post-translational modification occurs in the starfish and sea urchin SS-type peptides.
Precursor of two pigment-dispersing factor-type peptides (ArPDFP) A pigment-dispersing factor (PDF)-type neuropeptide precursor in A. rubens (ArPDFP) was identified as a 104residue protein comprising a predicted 22-residue N-terminal signal peptide and two putative PDF-type neuropeptides bounded by dibasic/tribasic cleavage sites: ArPDF1, a 35residue polypeptide with a C-terminal glycine residue that may be a substrate for amidation, and ArPDF2, a 29-residue polypeptide (figure  2e ; GenBank: KT601709). ArPDFP was identified on account of its sequence similarity with a protein in the sea urchin S. purpuratus, which was reported previously as a corticotropin-releasing hormone (CRH)-type neuropeptide precursor  [6]. However, three observations lead us to conclude that ArPDFP is, as its name implies, a PDF-type precursor.
Precursor of a corticotropin-releasing hormone-type peptide (ArCRHP) A CRH-type neuropeptide precursor in A. rubens (ArCRHP) was identified as a 130-residue protein comprising a predicted 28-residue N-terminal signal peptide and a 41residue CRH-type peptide sequence bounded by dibasic/ tribasic cleavage sites (figure  2f ; GenBank: KT601710). An N-terminal glutamine residue and a C-terminal glycine residue may be substrates for post-translational modifications that give rise to an N-terminal pyroglutamate residue and a C-terminal amide group in the mature peptide. As highlighted above, neuropeptides in echinoderms purported to be CRHtype peptides have been reported previously  [5, 6, 10] , but further analysis here has revealed that these are in fact PDFtype peptides. Therefore, ArCRHP is the first bone fide CRHtype precursor to be identified in an echinoderm.