dataesr/scientific-paragraphs-categorization huggingface dataset:
In our 2017 article in Journal of Experimental Social Psychology, we used a new open-source application to present the stimuli. It has come to our attention that some stimuli may not have been presented correctly due to a coding error. However, we have successfully replicated the findings in a high-powered replication study after correcting the error. Thus, the original findings were not affected by the error and the conclusions from the article remain as they were. The new experiment script and the data of our replication are available via https://osf. io/ps9r7/.
Structure modeling The structure of the TetR of pRAS3. 3 was predicted from its primary sequence using I-TASSER version 5. 1  (Yang et al. , 2014). The best predicted model has a C-score of 0. 54 and a TM-score of 0. 79 ± 0. 09. The predicted TetR structure of pRAS3. 3 was aligned using cealign, available in pymol, with a crystallographic model available in the PDB (PDB: 2VPR  (Aleksandrov et al. , 2008) ) to position the tetracycline molecule for visualization purposes.
This suggested that this strain either possess at least one unidentified plasmid carrying multidrug resistance genes or that one or more of the identified plasmids have gained antibiotic resistance genes in comparison to their classic one. To answer this question, the total DNA of strain SHY16-3432 was first sequenced using short-read sequencing which allowed us to characterize the small plasmids carried by the bacterium: pAsa1, pAsa2, pAsa3, pAsal1, and a pRAS3 variant. However, using only the data provided by the short-read sequencing, it was impossible to fully assemble the chromosome, pAsa5 and pAsa9, mainly due to the presence of many repetitive sequences  (Reith et al. , 2008; Tanaka et al. , 2017; Vincent et al. , 2014a). To work around this problem, we also sequenced the genome of the strain SHY16-3432 using long-read sequencing (PacBio SMRT technology), since it has been previously demonstrated that long-read sequencing can help reduce assembly complexity  (Miyamoto et al.
In pRAS3-3432, Reg A and Reg B spots are composed of two and six repeats, respectively (Table  S2 ). There is evidence that the number of these repetitions can modulate the plasmid copy number in the cell  (Loftie-Eaton and Rawlings, 2009). A study made on E. coli revealed that the pRAS3s having a lower copy number represents a lower metabolic burden on cells and can consequently increase the population fitness (Loftie-eaton and Rawlings, 2010). The second distinct element displayed by pRAS3-3432 is a new feature that has never been reported in other pRAS3 variants and even in A. salmonicida subsp. salmonicida. The latter is an additional region of 2 kb inserted between the tetracycline repressor gene tetR and a replication-like protein (Fig. 2 ). A blastn analysis against the nonredundant nucleotide (nr/nt) NCBI database of this region revealed that it is identical to mobile genetic element IScs605 previously listed in Chlamydia suis  (Dugan et al.
, 2004). IScs605 is an insertion element composed of two divergently oriented ORFs. The smaller ORF encodes for a putative IS200 element transposase and has been shown responsible for the mobility of IScs605, while the larger ORF for a putative IS1341 element transposase  (Dugan et al. , 2007; He et al. , 2015). Further investigation on the insertion element IScs605 revealed that it is part of a genomic island responsible for tetracycline resistance in several strains of the pig pathogen C. suis. Named tet(C) island, it is integrated into the chlamydial chromosome (GenBank accession number AY428551. 1) (Dugan et al. , 2007 (Dugan et al. , , 2004)). Dugan et al. (2004)  showed that C. suis tet(C) island shares a high level of nucleotide identity (over 99%) with the plasmid pRAS3. 2. They highlighted that the major difference between pRAS3.
Characterization of pAsa9b Recently, a new plasmid named pAsa9 was discovered and characterized in the A. salmonicida subsp. salmonicida strain 01-B526. As described in  Tanaka et al. (2017) , this large plasmid of 76,7 kb can be divided into four regions respectively carrying replication-associated genes, conjugation genes, ORFs coding for hypothetical proteins and transposase genes. Currently, only the sequence of pAsa9 from strain 01-B526 is available on the NCBI database. Here, with the acquisition of the complete genome of strain SHY16-3432, it allowed us to obtain a second sequence of pAsa9. SHY16-3432 pAsa9 was aligned against the reference plasmid from strain 01-B526, which revealed that the two plasmids shared a high nucleotide identity (over 99,8%) across their length. The only variation between the plasmids is the absence of ISAS5 in SHY16-3432 pAsa9, hence its size of 74.
Acknowledgments This work was supported by the  Natural Sciences and Engineering Research Council of Canada (NSERC)  ( RGPIN-2014-04595 ). MAM and ATV received an  Alexander Graham Bell Canada Graduate Scholarship  from  NSERC. MAM also received a scholarship from the Fonds québécois de la recherche sur la nature et les technologies. SJC is a research scholar of the  Fonds de Recherche du Québec en Santé.
Sequencing and sequence analysis Viral RNAs were extracted from cell culture supernatants with the High Pure Viral RNA kit (Roche Diagnostics). Virus genomes were amplified by RT-PCR with generic primers as previously described  [13] : briefly, for each virus, this amplification step leads to the generation of two large DNA products that together span the whole genome; these two products were mixed together and sequenced on an Illumina platform as already described  [13]. The reads were trimmed and used for de novo assembly of the genomes using CLC Genomics Workbench 9. 0 with parameters already optimized  [14]. Multiple sequence alignments were performed with CLC Main Workbench 8 software (CLC bio) and phylograms were constructed with the MEGA 5 program  [15]. Similarity plots were drawn with the SimPlot software  [16]  using the Hamming distance method (200 nt-wide sliding window, step size of 20 nt).
De novo assembly of EV-D111 full-length genomes Three isolates sequenced during this work (OUP-05-059, NGB-06-107 and BAN-06-150) were by-products of the poliovirus surveillance and were isolated from human stool samples collected in Central African Republic in 2005 and 2006  [10] ; the fourth isolate (TOK-230) came from a stool sample of a healthy child collected in Cameroon in 2008 within the framework of an epidemiological study  [11]. All were previously identified as EV-D111s by a typing method based on the VP1-encoding sequence  [23, 24]  but no other genetic data were available for these isolates. In this work, the whole genome of the four isolates was amplified by using EV generic primers that generated two overlapping amplicons that were subsequently sequenced on an Illumina platform.
For all four samples, de novo assembly gave rise to a contig spanning the complete genome of the studied EV-D111, except few 5' and 3' terminal nt that correspond to the RT-PCR primer binding sites. In the VP1-encoding region, the contigs generated during this study did not differ by more than 3 nt from the sequence previously obtained from the same sample through the Sanger sequencing technique  [10, 11]. Two supernatants were found to contain a mixture of viruses: besides the expected EV-D111, BAN-06-150 contained an echovirus 19 (E-19, Genbank accession number MK032893) and TOK-230 contained an E-19 (Genbank accession number MK032892) and a coxsackievirus B1 (CV-B1, Genbank accession number MK032894). These viruses belong to the species Enterovirus B and had not peculiar genetic relationships with EV-Ds in any parts of their genomes.
Phylogenetic relationships with other EVs The genetic sequences of the four isolates were compared to those of other EV-D111s available in public database. Actually, very few EV-D111s have been detected or isolated and only partial sequences are available (Fig  4 ). KK264 genome was sequenced in the 5'UTR and the VP4-VP2, the VP1 and the 3D regions whereas only the VP1-2A region of 17-04 genome has been published. More recently, the partial sequence of an EV-D111 isolated in Nigeria was released in GenBank: this sequence covers the genome from the very end of VP1 to the beginning of the 3C. In the VP1 region, the EV sequences cluster according to their type. In this region, the 6 EV-D111 strains for which a substantial part of the VP1 sequence is available (i. e. all except Nigeria-2017) formed together a group supported by a 100% bootstrap value (Fig  5 ).
Inside this group, the clustering was similar to that previously observed based on partial VP1 sequences  [11]. It is of note that the EV-D111 strain originating from a simian sample (KK2640) in the one hand and the EV-D111 strains from human samples in the other hand did not form two separate phylogenetic lineages: NGB-06-107, TOK-230 and KK2640  [9]  formed together a branch supported by a high bootstrap value (98%) whereas  17    We also investigated the relationships of EV-D111 strains together and with other EV in other genomic regions. The nt sequences corresponding to the regions 5 0 UTR, 2A, 2B, 2C, 3A, 3B, 3C, and 3D of the genome were used individually in separate BLAST analyses to identify, for each region, the closest sequences available in the GenBank database. In all the genomic regions, the closest sequences were from viruses belonging to the other EV-D types, particularly EV-D94.
This project was supported by the  Fondation Total  (grant  S-CM15010-05B ), by an  ACIP grant  ( ACIP 162-19 ) from  Institut Pasteur Paris  and by the  European Virus Archive  goes global project (EVAg; European Union's  Horizon 2020 research and innovation programme , grant agreement No  653316 ). We are grateful for the financial support of the  World Health Organization.
This service evaluation aimed to use retrospective observational data to evaluate the impact of the presence of an enhanced care team (ECT) on the pre-hospital scene time in the context of penetrating trauma. The primary outcome was to evaluate whether scene times are reduced when an ECT is present. A secondary outcome was whether the presence of an ECT improved compliance with the trust's Major Trauma Decision Tree (MTDT), which mandates that central stabbings be conveyed directly to one of the Major Trauma Centres (MTCs) within the trust's geographical area.
Patient selection Patients were identified using SECAmb's Computer Aided Dispatch (CAD) system, which records incident details. The historical CAD was searched to include all incidents over a one-year period from the 1st April 2017 to the 31st March 2018. All incidents categorised as "stabbing" or "stabbing central" were included. The category assigned to the incident is chosen by the emergency call operator at the time of the call. It is acknowledged within this evaluation that if a stabbing incident was incorrectly categorised, then it could be missing from the dataset. The CAD notes and the (automatically anonymised) patient report form were examined to ensure central penetrating trauma had occurred. For the purpose of the study, and to match with the MTDT, 'central' is defined as proximal to the knees and elbows.
Statistical analysis Data were collated using Microsoft Excel™. Average scene times (the time from the first ambulance response arriving on scene, to the time the patient left scene) were initially expressed using descriptive statistics (median, and interquartile range -IQR), and then any difference between the means of the two groups was tested for significance using an unpaired, two-tailed t-test using GraphPad online software (www. graphpad. com/quickcalcs/catMenu/). Triage decisions (MTC or TU) were expressed initially using descriptive statistics (percentage), and the odds ratio calculated.
Results During the period reviewed, 171 patients met the inclusion criteria, and complete data were available for 165. Patients with partial data are included in the results where appropriate. Baseline characteristics are shown in Table  1. Median total scene time for non-ECTs was 29 min and 30 s (29:30 -IQR 18:00-37:00). For ECTs overall this was 19 min (IQR 12-30 min), 19 min if a CCP was in attendance (IQR 12-30 min), 21 min if HEMS attended (IQR 10-34 min), and 18. 5 min if both ECT units attended (IQR 13. 75-32 min). This is illustrated in Fig. 1. An unpaired, two-tailed t-test was used to compare mean scene times for ECTs overall, with those of non-ECTs; the means here were 26:46 (SD 14:41), and 31:53 (SD 18:00) respectively. There was a significant difference between ECT (standard deviation 14.
Discussion This service evaluation shows a statistically significant correlation between the presence of an enhanced care team, and the improvement in scene times and MTDT compliance in the context of central stabbing. Within the dataset there also appears to be a considerable improvement in the number of patients who are triaged to a MTC when attended by an ECT. Both reduced scene times and triage compliance have been shown to be of benefit to patient outcomes  [4, [21] [22] [23] , so these findings are potentially of clinical significance. The reasons for the results are likely to be multifactorial. It has already been described how the ECTs in this study have a higher level of education compared to non-ECTs. It seems likely that this, coupled with an increased exposure to these incidents, will mean they are better prepared for the challenges which victims of penetrating trauma provide.
Finite element model of the elementary cell The FE model of the EC has been created within the commercial FE code ANSYS R. This model is generated through an ad-hoc script in which the mesh has been properly related to the relevant parameters of the EC to take into account for different geometries. The EC is modelled by means of 20-nodes solid elements (SOLID186). A FE model made of solid elements is needed to provide a realistic representation of the EC geometry and to accurately estimate the 3D stress field generated inside the EC and which strongly influences its macroscopic elastic behaviour.
The results (in terms of displacement, strain and stress fields), provided by the fatigue analysis conducted on the mesoscopic FE model of the EC, have been post-processed by means of a suitable numerical procedure wherein the ANSYS R FE model has been interfaced with inhouse routines (programmed in PYTHON environment). It was observed that a mesh size of 0. 05 mm for a cell size equal to 3 mm is sufficient to properly evaluate the EC fatigue strength.
ACTRIS is composed of observing stations, exploratory platforms, instrument calibration centers, and a data center, and it aims to support atmospheric and environmental science by providing a platform for researchers to combine their efforts more effectively. Different lidar systems are operated at the EARLINET stations but the quality assurance/quality control (QA/QC) programs developed and run within ACTRIS RI (research infrastructure) allow continuous control of the lidar operation and data. Among the considered 28 stations, there are seven continuously measuring Polly instruments  (Althausen et al. , 2009; Engelmann et al. , 2016; Baars et al. , 2016)  operated at Košetice, Limassol (Cyprus), Haifa, Warsaw (Poland), Hohenpeissenberg (Germany), Évora (Portugal), and Finokalia on Crete (Greece).
(2015 'Amico et al. ( , 2016)) ,  Mattis et al. (2016 ), Freudenthaler (2016) ,  Baars et al. (2016) , and  Mamouri and Ansmann (2016, 2017). The EARLINET observations are taken from the EARLINET database (EARLINET, 2019) and selected by careful inspection of the involved lidar teams. The Polly data analysis was performed by following the EARLINET data analysis protocols and procedures. The Raman lidar method  (Baars et al. , 2016)  was used to compute the particle backscatter coefficient from the ratio of elastic backscatter to the respective nitrogen Raman signal. To compute and correct for molecular backscatter and extinction Table  1. Lidar-derived smoke (soot) particle optical and microphysical properties and retrieval input parameters for 532 nm. z bot and z top are the layer base and top height of the detected stratospheric smoke layer, respectively.
The height profiles of the particle backscatter coefficient were used to determine base height z bot and top height z top of the detected stratospheric smoke layers. In the next step, the layer mean and column-integrated smoke optical properties were calculated. The relative uncertainties in the lidar products shown in Sect. 3 are on the order of 10 %-30 % (particle backscatter coefficients), 20 %-50 % (particle extinction estimates and AOT estimates), and 10 %-30 % for the presented smoke layer mean values for the particle depolarization ratio. The smoke layer geometrical properties (base and top heights) may have an uncertainty on the order of 50-150 m. The larger uncertainties describe the data quality for the observational period from October 2017 to January 2018. Signal noise is the main contributor to the large uncertainties.
Particle shape and size characteristics Recently,  Yu et al. (2019)  modeled the optical properties of the Canadian smoke particles. They assumed that in the beginning an external mixture, consisting of (a) socalled fractal BC particles (i. e. , fractal aggregates of BC) coated with organics, causing an overall spheroidal shape, and (b) organic particles without BC, rapidly coagulated and left behind a mixture of organic and BC-containing particles with a typical abundance of 2 % BC. The authors con-Figure  8. Same as Fig. 4a , except only for the southern Polly stations. The Finokalia data set is shown here in green for better identification. The different data sets are shifted against each other by 6 h and the line width is reduced to better see all observations. An ascending structure, first seen over Évora in September (in blue) and then also detected over the eastern Mediterranean in October and November (in green, red, and orange) triggered the discussion about potential aerosol lifting processes and effects.
Spaceborne lidars such as the CALIPSO lidar are complementary to these network observations by providing global 3-D aerosol distributions, but these snapshot-like satellite lidar observations are of limited use in process studies. Future activities should also be undertaken in the direction of harmonization of lidar network observations and data. In this sense, the effort to develop standardized tools for aerosol lidar analysis, as realized in the case of ACTRIS-EARLINET in form of the single-calculus-chain (SCC) software  (D'Amico et al. , 2015 (D'Amico et al. , , 2016;; Mattis et al. , 2016) , and to open its use to non-EARLINET lidar stations and teams is another step forward on the long way to global lidar data harmonization.
Acknowledgements. The authors thank the teams at Košetice observatory (in particular  Vlastimil Hanuš ,  Adéla Holubová Šmejkalová , and Vladimír Ždímal) for their great logistical support. Financial support. The authors acknowledge support through  ACTRIS  under grant agreement no. 262 254  and  BACCHUS  (no. 603445 ) of the  European Commission Seventh Framework Programme  (FP7/2007-2013),  ACTRIS-2  and  EXCELSIOR  under grant agreement nos. 654109  and  763643  from  Horizon   2020, research and innovation program  of the  European Commission , and  HD(CP)2  under grant agreement no. 01LK1502I  with the  Ministry for Education and Research (BMBF). The research leading to these results has also received funding from the  H2020 program  of the  European Commission regarding GRASP-ACE  (grant agreement no.
778349 ) and Spanish funding (ref. CGL2014-55230-R ,  TEC2015-63832-P ,  CGL2017-90884-REDT ,  CGL2016-81092-R , and  MDM-2016-0600 ). This work was also supported by  Ambizione program of the Swiss National Science Foundation  (project no. PZ00P2 168114 ). The lidar data analyses at University of Warsaw were supported by  European Space Agency  grant no. 4000119961/16/NL/FF/mg  (POLIMOS). Évora lidar observations were funded by the  Portuguese Science Foundation (FCT)  within the project  TOMAQAPA  (Ref:  PTDC/CTA-MET/29678/2017 ) and the  European Union  through the  European Regional Development Fund , included in  COMPETE 2020 (Operational Program Competitiveness and Internationalization)  through the  ICT  project ( UID/GEO/04683/2013 ) with reference  POCI-01-0145-FEDER-007690 , and also through  Interreg V-A Spain -Portugal  ( POCTEP) program , through the  CILIFO  project (Ref:  0753_CILIFO_5_E ).
Cork lidar observations were supported by the  Irish Research Council  ( 2014 ) and  Science Foundation Ireland  ( 05/RF/EEB011 ). The Cyprus observations were supported by the  SIROCCO  project, which is co-funded by the  Republic of Cyprus and Structural Funds of the European Union for Cyprus  under the  Research & Innovation Foundation  grant agreement  EXCELLENCE/1216/0217. Haifa lidar observations were funded by the  German-Israeli Foundation  ( GIF grant I-1262 401. 10/2014 ) with support of the  Norman and Helen Asher Fund and Ollendorff Minerva Center. The development of the lidar inversion algorithm used to analyze Lille and Leipzig lidar data was supported by the  Russian Science Foundation  (project  16-17-10241 ). The publication of this article was funded by the  Open Access Fund of the Leibniz Association.
Data availability. EARLINET data are accessible through the AC-TRIS data portal http://actris. nilu. no/ (last access: 10 October 2019) The long-term Polly lidar level-0 data are plotted online at http: //polly. rsd. tropos. de (last access: 10 October 2019); raw data are available at TROPOS upon request (polly@tropos. de). GDAS meteorological data are available via an ARL web page (https://www. ready. noaa. gov/gdas1. php, last access: 20 May 2019, GDAS, 2019). All the analysis products are available from TROPOS upon request (info@tropos. de).
The increased hazard of nano-compared to micro-sized particles is due to their increased surface-to-volume ratio, which consequently leads to a potentially higher release of toxic elements, if present. Additionally, nanoparticles in general can directly enter cells  [16]. Smaller particles are more easily distributed, but may also be more easily excreted from the body  [17]. However, little data exist on tattoo pigment sizes in different human tissues. In this study, synchrotron-based nano-X-ray fluorescence (XRF) was used to analyze human skin and corresponding draining lymph nodes with the aim to establish a database of pigment particle sizes and elemental contaminants deposited in the human body. Data from the skin and lymph nodes of five donors with no known tattoo-related health effects were analyzed and compared to a skin biopsy of a patient with a type IV tattoo allergy and confirmed Ni sensitivity.
Steel particles are being abraded from the tattoo needle by TiO 2 The steel debris found in human tissues alongside tattoos in the nano-XRF analysis may potentially derive from three sources: contaminated inks, contamination during sample preparation (wear from the microtome blades used for tissue sectioning), or wear from tattoo needles. We analyzed 50 tattoo inks from worldwide origins by means of nano-XRF that were either black, white or red and partially contained TiO 2. None of the inks contained metallic Fe particles along with Ni and Cr contamination as the ones discovered in the skin and lymph node samples (data not presented). Furthermore, the microtome blades did not contain Ni, which excluded contamination from sample preparation (Fig. 2 , Additional file 1: Table  S6 ). However, all 12 tattoo needles analyzed contained 15-20% Cr and 6-9% Ni (Fig.
Statistical analysis Data from the quantification of Ni and Cr in pig skin were analyzed using the statistics software GraphPad Prism 6 (Graphpad Software Inc. , La Jolla, CA, USA). A two-way ANOVA with Tukeys multiple comparison test was carried out to determine significant differences between the different groups. For both Ni and Cr ANOVA analyses degrees of freedom were two and three for columns and rows, respectively. The F ratios for the different treatments were 60. 82 for Ni and 100. 1 for Cr.