dataesr/scientific-paragraphs-categorization huggingface dataset:
Tree plantation in genetic trials The international series of genetic trials presented in the BeechCOSTe52 database were established in two different series (years sown/trial planted: 1993/95 and 1996/98) to study genetic variation of European beech across its distribution range  8. The planning of the international series of beech trials was principally coordinated by researchers from the Institute of Forest Genetics in Grosshansdorf, Germany, including Mirko Liesebach, Georg von Wuehlisch and Hans Muhs, in liaison with the international trial-site holders, and supported by the Concerted Action of the Commission of the European Communities (AAAIR3 Programme, Grant No. CT94-2091). Previous plantations of genetic trials of beech exist but mostly with local provenances, which precludes the study of genetic variation across the species range.
Phenotypic traits measurement Phenotypic trait measurements included tree height, basal diameter, diameter at breast height, mortality, bud burst phenology in spring and autumn leaf senescence, and in some cases the causes of damage related to mortality. Trait data was collected on an individual-trees basis in consecutive years following plantation, including measurements from 2-to-15 year-old trees, thus providing information through different ontogenic stages. We give an example of how the database can be plotted and further analysed according to trait and ontogenic stage (Fig. 2 ).
Data compilation A succession of national and international projects have allowed the collection of data from the trial sites (Additional Information. zip, Data Citation 1 and 1 st Meeting 9 ). In 2004, various preliminary databases of individual French, German and Italian provenances were gathered during the DYNABEECH project (Additional Information. zip, Data Citation 1). Later on, a European Concerted Research Action designated as COST Action E52 "Evaluation of Beech Genetic Resources for Sustainable Forestry" came into force in 2006, running until 2010, in order to consolidate and interpret the data collected from the two series of beech trials set up in 1995 and 1998, and to bring together the participants from countries that were managing trials to pool their expertise. The stated aim of the COST Action was "to make predictions of the future distribution range of beech forest ecosystems under the assumption of certain scenarios of climate change, based on the analysis of the reaction pattern of European beech populations".
An introductory COST Action E52 Working Group and Management Committee meeting took place in Zvolen (Slovakia 2006), with plenary meetings during the subsequent three years as well as various Working Group meetings  10. Some partial analyses were done during this period, considering one  [11] [12] [13] [14] [15] [16] [17] [18]  or several trials  [19] [20] [21] [22] [23]. One striking quality of the BeechCOSTe52 database presented here is that it has been made possible through the coordinated effort of researchers and foresters from many countries across Europe, who have managed and maintained the trial sites over an extended period of time and have altruistically contributed to the efforts of data collection and coordination over a long time period. The compilation of the phenotypic information from all the genetic trials included in the BeechCOSTe52 database only refers to trials and provenances in which traits have been measured repeatedly (Table  1 ).
Code availability R code to merge phenotypic trait measurements, geographical coordinates of the trials and geographical coordinates of the provenance locations is included (merge-trial-prov-coords_individualmeasurements. R). Mapping phenotypic traits by provenances and trials as shown in Figs. 1  and  2 can be reproduced using the following scripts: Hplot. R & Plot_Trial-Prov_locations. R. Likewise, individual data by trial and trait can be extracted from the global database using the specific script Subset_by_trial. R and Subset_by_trait. R, respectively.
Data Records The database is structured in three independent files that can be merged using the code identifier for the provenance and the code combining the trial and provenance codes ("Trial" and "ID_ProvCode", respectively). These data files together with the metadata descriptor document are available at Zenodo data repository (BeechCOSTe52_metadata_descriptor. docx, Data Citation 1). The first file contains individual measurements of phenotypic traits (Fsylvatica. csv, Data Citation 1): height, basal diameter, diameter at breast height, mortality, spring phenology, autumn leaf phenology, and associated damage causing to tree mortality. The second file contains the description of the trials including their geographical locations (Trials_coord. csv, Data Citation 1) and the third file describes the locations of the seed sources (Prov_coord.
Technical Validation The database has been checked for consistency at different stages by various researchers. During the COST Action E52 (2006 to 2010) raw data were submitted by each country and harmonized in electronic format for the first time. Results from the individual trial sites were sent to Georg von Wuehlisch until 2008. In 2008 and 2009 this information was assimilated into electronic form and standardised by Diana Barba and T. Matthew Robson. At that time, it was decided to have one database by genetic trial, harmonised among trials and checked for consistency. The geographical locations, names and identities of trial sites and provenances were rechecked, and the management and biogeographical history of provenances considered. In a workshop (19 th -23 rd January 2009) the data evaluation working group met in Valsain, Spain, where the database was checked for completeness and consistency of data collected by the members of the COST Action E52.
Likewise, there was large variation in the timing of bud burst and leaf flush in spring, when data collected using different scales among sites were harmonised and considered both in terms of day-of-the-year and degree-hours of forcing prior to bud burst  25. Finally, in 2017, the originally-compiled trial-site database was checked again for consistency of entries and fields in R by Marta Benito Garzón prior to harmonization of all the trial sites into the single  phenotypic database presented here. Outliers and errors in the database were checked by calculating descriptive statistics of quantitative traits for each trial averaged by provenance.
Acknowledgements The establishment of the trial series was supported by the  Concerted Action of the Commission of the European Communities  ( AAAIR3 Programme , Grant No. CT94-2091 ). The compilation and harmonization of the database was supported by the  COST Action E52  ( 2006-2010 ). We are very grateful to all the technicians and researchers that measured trials over years in the field. The final compilation was funded by the Investments for the  Future IDEX Bordeaux  ( ANR-10-IDEX-03-02 ).
High-throughput sequencing libraries containing small noncoding RNAs (e. g. , miRNAs or Piwi-interacting RNAs) were generated using 1 mg of total RNA and an Illumina TruSeq small RNA library preparation kit (Illumina, Inc. ). Individually barcoded fetal libraries were pooled and sequenced (100 bp-end reads) on a single HiSequation 2000 flow cell lane running version 3 chemistry. Illumina CASAVA software was used to carry out BCL to Fastq conversion. All the samples were passed through quality control and sequences with poor base qualities were removed. The adaptor sequences were removed using the clip_adaptors. pl module of mirdeep (v2. 0. 0. 5)  (Friedlander et al. 2012). Raw reads were collapsed based on sequence identity using the collapse_reads_md. pl module of mirdeep2. Collapsed reads were further annotated for miRNA by mapping to miRBase version 21  (Griffiths-Jones et al.
2008; Kozomara and Griffiths-Jones 2011; Friedlander et al. 2012 ) using the miraligner module of seqbuster  (Pantano et al. 2010). IsomiRs were identified using the R isomiRs (v1. 3. 0) package of seqbuster. Pairwise differential expression was performed among different groups using DESEQ2 (v1. 12. 4)  (Love et al. 2014).
5 (Figure  1B , chi square P , 0. 05). To determine if open cranial features were a hallmark of Prkra mutants, and if they are affected by the Tarbp2 locus, we analyzed cranial morphology using microCT in 8-week-old animals. We consistently observed open cranial sutures in Prkra 2/2 mutants, and reduction in Tarbp2 gene dosage further exacerbated this phenotype, as exemplified in Tarbp2 2/+ ; Prkra 2/2 mutants (Figure  S2D ). These data indicate that the structurally similar dsRBPs, TARBP2 and PRKRA, genetically interact. miRNA processing is altered in Tarbp 2/2 but not Prkra 2/2 mutants The difference in phenotypes between Dicer, Tarbp2, and Prkra single and double mutants led us to ask whether TARBP2 and PRKRA influenced DICER-mediated miRNA biogenesis in vivo. We collected total RNA from E15.
The simian immunodeficiency virus (SIV)/macaque model of human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome pathogenesis is critical for furthering our understanding of the role of antibody responses in the prevention of HIV infection, and will only increase in importance as macaque immunoglobulin (IG) gene databases are expanded. We have previously reported the construction of a phage display library from a SIV-infected rhesus macaque (Macaca mulatta) using oligonucleotide primers based on human IG gene sequences. Our previous screening relied on Sanger sequencing, which was inefficient and generated only a few dozen sequences. Here, we re-analyzed this library using single molecule, real-time (SMRT) sequencing on the Pacific Biosciences (PacBio) platform to generate thousands of highly accurate circular consensus sequencing (CCS) reads corresponding to full length single chain fragment variable.
CCS data were then analyzed through the international ImMunoGeneTics information system ® (IMGT ® )/HighV-QUEST (www. imgt. org) to identify variable genes and perform statistical analyses. Overall the library was very diverse, with 2,569 different IMGT clonotypes called for the 5,238 IGHV sequences assigned to an IMGT clonotype. Within the library, SIV-specific antibodies represented a relatively limited number of clones, with only 135 different IMGT clonotypes called from 4,594 IGHV-assigned sequences. Our data did confirm that the IGHV4 and IGHV3 gene usage was the most abundant within the rhesus antibodies screened, and that these genes were even more enriched among SIV gp140-specific antibodies. Although a broad range of VH CDR3 amino acid (AA) lengths was observed in the unpanned library, the vast majority of SIV gp140-specific antibodies demonstrated a more uniform VH CDR3 length  (20 AA).
Sequencing primer annealing and P6 polymerase binding were performed using the recommended 20:1 primer:template ratio and 10:1 polymerase:template ratio, respectively. scFv SMRTbell libraries were loaded onto SMRT cells at a concentration of 50 pM. SMRT sequencing was performed on the PacBio RS II system using the C4 sequencing kit with magnetic bead loading and 6-h movies. Circular consensus sequencing (CCS) reads were generated using Arrow and the CCS2 protocol as a part of SMRTLink version 4. 0; CCS reads were filtered by both quality (Q30, 99. 9% accuracy) and size, retaining only sequences that ranged from 700 to 1,200 bp based on expected scFv size distribution. Resultant FASTA files were used for downstream analyses. These filtered CCS reads have been submitted to the Sequence Read Archive under submission SUB3223332 entitled "Macaca mulatta-derived SIV-gp140-specific scFv circular consensus sequences" and can be retrieved using accession number SRP125114.
Data filtering was applied with the following criteria to be fulfilled for each of the two V domains: (i) >85% of identity of the V-REGION of the V domain with the V-REGION of the closest germline IMGT gene and allele (  58 ) and (ii) in-frame V-(D)-J junction. Filtered sequences were then analyzed to identify the closest V, D (for VH) and J IMGT genes and alleles, in order to characterize the amino acid (AA) junction and to give a complete description of the scFv with IMGT labels, using the IMGT/V-QUEST algorithm for scFv, implemented in IMGT/HighV-QUEST. Here, we report the statistical and IMGT clonotype analysis for each domain for the unpanned library (Pan0) and the fourth round SIV Env gp140 panned library (Pan4). In order to ensure that the breadth and depth of the data generated by a single SMRT cell per sample was not limiting the characterization of the complex scFv pools, a comparative analysis was done pooling data generated from three SMRT cells run for a single sample.
We also obtained additional and less pronounced products between 800 and 1,700 bp (Figures  1A, B ) with the 1,700 bp fragment corresponding to scFv dimers. Furthermore, peaks at 50 and 17,000 bp were also observed and corresponded to the lower and upper ladder of the Agilent 12000 DNA Kit, respectively (Figure  1B ). In order to focus our analyses on highly accurate, full-length scFv fragments, SMRT sequencing data were processed using the latest CCS2 algorithm and filtered by size (700-1,200 bp) and accuracy (99. 9%, QV30) (Figure  1C ). Table  1  summarizes the total number of sequences and IMGT clonotype-respective assignments of the VH and VL domains to the IGHV, IGKV, and IGLV genes observed. The total number of sequences assigned to an IMGT clonotype was independent of PCR template DNA concentration and similar between Pan0 (3,837, 3,159, and 5,238) and Pan4 (4,594, 4,594, and 3,884).
IGHV Pan0, which reflects a broad representation of total antibody genes in this macaque, was highly diverse with a single gene (IGHV1-1, IGHV4-2, and IGHV7-1) representing the IGHV1, IGHV4, and IGHV7 subgroups, two genes (IGHV2-1 and IGHV2-2) for the IGHV2 subgroup and 10 genes (IGHV3-5, IGHV3-6, IGHV3-7, V genes and alleles, and complementarity determining regions 3 (VH CDR3 and V-LAMBDA CDR3) were determined using IMGT/V-QUEST with scFv functionality  (57). Somatic hypermutation frequencies [SHM (%)] represent the nucleotide sequence divergence from the closest germline in IMGT/V-QUEST  (54). scFv binding specificity was determined by enzyme-linked immunosorbent assay (ELISA). F, functional; AA, amino acid. Filtered CCS reads (≥99. 9% accuracy and 700-1,200 bp in length) generated from SMRT sequencing data were analyzed using IMGT/HighV-QUEST in order to determine V, D, J gene sequence, allele assignment and functionality  (53, 54).
IMGT/HighV-QUEST output files were processed through IMGT statistical and clonotype analysis to determine the number of assigned sequences and clonotypes. The number of sequences assigned to an IMGT clonotype corresponds to in-frame sequences [C104, W118 for VH and C104, F118 for VL (V-KAPPA or V-LAMBDA)] from "1 copy" + "More than 1," "Single allele" and "Several alleles" (or genes)  (41)   2A ). Individually, IGHV4-2 was the most represented gene in the Pan0 dataset, with 1,734 (33. 14%) assigned sequences. From a subgroup perspective, IGHV3 was the most represented with a total of 2,165 (41. 31%) assigned sequences. Within IGHV3, three genes, IGHV3-6, IGHV3-9, and IGHV3-7, were the most abundant with 562, 498, and 462 assigned sequences, respectively. Overall, the number of assigned IMGT clonotypes was proportional to the number of sequences, as observed for IGHV4-2 (36.
Batch Analysis of Triplicate SMRT Cell Outputs When screening a highly variable library, a limitation of the PacBio RSII system is the relatively low read depth per SMRT cell, as compared to other NGS technologies. We observed this when running single SMRT cells per sample in our experiments. However, this can be countered by running multiple SMRT cells per sample to increase read depth and the ability to detect low level variants within a population. As the IMGT statistical and clonotype analysis tool functions with batched data, including multiple SMRTcells (up to one million sequences), we performed a batch analysis for triplicate, pooled samples from Pan0 and Pan4 (Table  1 ). In this batched dataset, for IGHV, the number of sequences assigned to an IMGT clonotype was increased (two-to fourfold) for Pan0 and almost threefold in Pan4 as compared to those sequences generated with a single SMRT cell per sample (Pan0_1, Pan0_2, and Pan0_3 or Pan4_1, Pan4_2, and Pan4_3).
Here, we evaluated the ability of SMRT sequencing technology to generate full length scFv sequencing reads for the analysis of phage display libraries. We obtained thousands of highly accurate (≥99. 9%) sequence reads, each containing productive VH-VL combinations. As previously reported for this rhesus macaque  (11) , SIV Env gp140-specific scFv were dominated by the usage of IGHV4-2 and IGHV3-9. However, we observed far fewer IGHV1-1-containing scFvs in the Pan4 library than expected. We also observed more IGHV3-9-contaning scFv sequences than those with IGHV4-2, despite the latter being more abundant in the unpanned library. Together, these data suggest that the SMRT sequencing approach will be useful for the characterization of scFv libraries as more comprehensive rhesus V gene databases are being developed  (60, 61).
It has also been observed that the IGHV1 (34. 4%) and IGHV4 (26. 15%) subgroups were the most dominant among naïve IgM libraries in human adults but that these representations could be altered during early (40 days) or advanced (8 months) HIV-1 infection with differences between IgM and IgG frequencies, as well as between peripheral blood mononuclear cells (PBMC) and bone marrow (BM) compartments  (63)   (63). The complexity of these data suggest that analyses of multiple animals and infection time points are needed, as well as a comparative analyses of these data compared to those generated using scFv libraries constructed with rhesus specific-primers to ensure that any rhesus-specific IG populations are included  (9, 12). These additions, as well as leveraging the growing rhesus databases (60, 61) will be necessary moving forward to ensure the most comprehensive analysis of polyclonal antibody responses during SIV infection in rhesus macaques.
Another caveat that could impact our V-(D)-J characterization of SIV gp140-specific antibodies was the use of the IMGT database for classification and analyses, as it possesses an incomplete representation of macaque IG germline sequences. In their study  Dai et al. address this concern by comparing antibody V-(D)-J compositions obtained via their in-house "CS germline-gene database" to that of the IMGT database, observing a more diversified VH family composition (mostly VH1, VH2, and VH3) using their in-house tool, while IMGT-generated data were skewed toward VH1 and VH4. Although we exclusively used IMGT analyses in this study, we also found that VH3 and VH4 family genes were among the most represented within the SIV gp140-specific antibodies. These two families were followed by VH1 albeit to a lesser level than what was observed by  Dai et al.
or our previous study  (11). It is possible that the differences between our results and those from Dai et al. were individual specific, or due to the varied panning antigens used. Using Sanger sequencing, we have previously observed VH4-skewed usage in gp120-specific antibodies from the same animal examined in this current study  (11). Most importantly, we are currently working with IMGT to expand their macaque IG germline database, as to eliminate this caveat in future studies. To note, Dai et al. also observed similar patterns of VH CDR3 lengths and SHM levels between IMGT and their own "CS germline-gene database" results. Here, we also observed a wide range of VH CDR3 lengths in the context of differential clonotype identities, which is probably more relevant for functional antibody classification.
Life cycle inventory SimaPro 8 software and ecoinvent 3 database have been used. In Table  2 , the components/materials of the studied configurations are presented: (A) indicates scenario A (configuration without PCM) while (B) indicates scenario B (configuration with PCM). From Table  2  it can be seen that certain components are common (in terms of the type of the material and in terms of the quantity) for both configurations (without/with PCM) and these are indicated with (A, B). Table  2  includes the materials needed for the collectors as well as the additional components of the system.
03 kg CO 2. eq /kWh, for the case without recycling and for the case with recycling, respectively. From the above mentioned it can be seen that, in general, there is quite good agreement between the present results and those of  Kalogirou (2009). However, a direct comparison is not possible due to differences between the present study and the study of  Kalogirou (2009)  (differences in terms of: the technical characteristics of the studied systems, the boundaries, the assumptions, the adopted databases, etc. ). For example, the present investigation is based on CO 2. eq emissions while the study of  Kalogirou (2009)  evaluates CO 2 emissions. In addition, it should be taken into account that in the present study the calculations include gutter (aluminium) which accounts for a considerable part of the total CED and GWP of the system.
This is because aluminium is an energyintensive material (SimaPro 8; ecoinvent 3 database) and the total mass of aluminium needed for the gutter of the 35 collectors is 25. 47 kg (Table  2 ). It should be highlighted that the gutter could not be considered as part of the collectors because if classic flatplate collectors were adopted, the building could also include gutters. More comparisons of the proposed BIST (without PCM) with results from the literature can be found in authors´ previous study  Lamnatou et al. (2015d).
, 2016). Moreover, it should be taken into account the issue that it was previously discussed (subsection 3. 3) about the component of gutter (that it could not be considered as part of the solar system). Concerning the material that has been adopted for the calculations of the impact of the PCM, it is fatty acid (SimaPro 8; ecoinvent 3 database). During the production of the selected fatty acid, vegetable oils (such as palm oil and coconut oil) are utilized, showing a considerable contribution to the total impact of fatty-acid production. Certainly, the inputs needed for the production of the above mentioned oils (for example, energy and fertilizers necessary for the cultivation of the related crops) remarkably contribute to the total impact of the fatty acid. About palm-oil production, details can be found in the study of  Noël et al.
1) Cumulative Energy Demand V1. 08 / Cumulative energy demand 2) IPCC 2013 GWP 20a V1. 00; IPCC 2013 GWP 100a V1. 00; IPCC 2013 GWP 500a V1. 00 (Sources: SimaPro 8; ecoinvent 3 database). Cumulative energy demand (CED) includes characterization factors for the energy resources divided in 5 impact categories: The categories of «Non-renewable» include fossil (1) and nuclear (2) while the categories of «Renewable» include biomass (3), wind/solar/geothermal (4) and water (5). On the other hand, IPCC 2013 is an update of the method IPCC 2007 which has been developed by the IPCC (intergovernmental panel on climate change). It should be noted that the above mentioned method lists the climate change factors of IPCC based on a timeframe of 20, 100 and 500 years (PRé, 2014).
PCM offers an EPBT reduction of around half year which is mainly related with the fact that it allows the utilization of lower flow rate. However, if the inputs for pumping/auxiliary heating are not taken into account, both configurations (with/without PCM) show almost the same EPBT value (around 1. 3 years). For pump/auxiliary heating, it has been considered the electricity mix of France (SimaPro 8; ecoinvent 3 database). By taking into account the inputs for pumping/auxiliary heating (as additional inputs during operational/maintenance phase for E O&M. a ), the EPBT results show 4. 2 years for the configuration without PCM and 3. 7 years for the configuration with PCM. Thereby,.