dataesr/scientific-paragraphs-categorization huggingface dataset:
67 was used  [20] , i. e. the reduced dose was considered non-inferior when the lower limit of the two-sided 95% CI of the GMR was greater than this cut-off. In the same way, GMRs were also calculated at day 49 for VNA titres against Wuhan and Delta variants. The proportion of participants with responses higher than the lower limit of detection were calculated for SARS-CoV-2 anti-RBD IgG at days 0, 21 and 49, and for VNA titres at days 21 (Wuhan) and 49 (Wuhan, Delta, Omicron) with 95% CI calculated by the binomial exact method. They were compared between the reduced and the full dose groups using the Fisher's exact test. Data below the lower limit of detection were given a value equal to half of the threshold before transformation. Comparisons of primary and secondary outcomes were evaluated by linear mixed-effect model adjusting for age, gender, and baseline titre of SARS-CoV-2 anti-RBD IgG (for days 21 and 49) or naïve/not naïve category (for day 0) as fixed factors and study sites as random factor.
Correlations between SARS-CoV-2 anti-RBD IgG and VNA titres (Wuhan), and between VNA against Wuhan and Delta variants were evaluated by Pearson correlation coefficients. Concerning cellular responses, the proportion of participants with responses higher than 0 in IFN-γ ELISpot and with a positive response in flow cytometry was computed at day 49 with 95% CI calculated by the binomial exact method. Fisher's exact test was used to compare reduced and full dose groups. For IFN-γ ELISpot analysis, data equal to 0 were given a value of 1 before transformation, and for flow cytometry, negative frequencies were given a value of 0. 0001 before transformation. Comparisons of GMTs were evaluated by linear mixed-effect model adjusting for age, gender, and baseline titre of SARS-CoV-2 anti-RBD IgG as fixed factors and study sites as random factor.
Acknowledgments DK is a Clinical Master Specialist Applicant to a Ph. D. of the  Fonds de la Recherche Scientifique-FNRS. A. M. is Research Director of the  FRS-FNRS, Belgium. We thank  Martine Delaere ,  Kristine Massez ,  Isabelle Maufort  and  Jody Serre  ´for their dedicated work as study nurses. We also thank  Caroline Rodeghiero ,  Fabienne Jurion ,  Elfriede Heerwegh ,  Celien Van Oostveldt ,  Vincent Martens ,  Valerie Acolty ,  Inès Vu Duc ,  Sara Cuman ,  Robin Van Naemen ,  Maria Lara Escandell ,  Sandra Coppens ,  Ann Ceulemans  and  Koen Bartholomeeusen  for their help in the laboratory, as well as  Murat Gonen  and  Jonathan Masala  for their logistical support. We thank.
All these compounds were also found at least once in F. hirta receptive fig odours  [16]. The non-metric multidimensional scaling (NMDS) (stress = 0. 124) applied to the Ficus triloba dataset (i. e. , the relative proportion of each VOC in the odour emitted by each studied sample) showed that, while many point overlapped among locations, the odours of receptive figs differed significantly among locations (Fig. 1 ; Permutational multivariate analysis of variance (PERMANOVA): F (2;31) = 3. 6554, P = 0. 001). Pairwise comparisons using permutation MANOVAs on the pairwise distance matrix between localities showed differences between all the localities (P < 0. 05). The dispersion of the VOC profiles was significantly heterogeneous among the three locations sampled (F 2,29 = 4. 3772, P = 0. 03), but not between Shimen and DHS (F 1,26 = 0.
VOC analysis The samples were analysed using gas chromatography coupled with mass spectrometry and the compounds were identified as detailed in Deng et al. 2021. We obtained a global dataset, where the composition of the odour extracted from each sample is expressed by the relative proportions of each VOC in the emitted odour (semi-quantitative data). This dataset was complemented by previous data obtained from Ficus hirta  [16]  to compare the odours of the two species, and from F. hispida (subgenus Sycomorus) (Deng et al. submitted) another sympatric species to provide an outgroup. Divergence in chemical profiles across locations was estimated with non-metric multidimensional scaling (NMDS) in two dimensions, based on a Bray-Curtis similarity matrix, using the R-package vegan  [42]. Pairwise distance between individuals for relative proportions of VOCs was calculated using the Bray-Curtis dissimilarity index, which ranges between 0 and 1.
Chemical distance matrices were calculated with the function "vegdist" between locations and between species, using available data for F. hirta  [16] , Two-dimensional plots were constructed using the "metaMDS" function algorithm after data standardization with "decostand" function in R (v. 3. 5. 1). A stress value is given, indicating how well the particular configuration represents the distance matrix (stress values < 0. 2 are desirable). To test if the variation in chemical composition between locations was significant, we carried out permutational multivariate analysis of variance tests (PERMANOVA) on the distance matrix using the function "adonis" in the vegan package  [42]. The model used 999 permutations, and we FDR corrected p-values to control for multiple comparisons. Multivariate homogeneity of group dispersions (variances) was tested using the "betadisper" function.
Funding This work was supported by the  National Natural Science Foundation of China  ( 3215010364 ;  31971568 ) and  Province Natural Science Foundation of Guangdong  ( c20140500001306 ) and by the  International Research Project (IRP)-CNRS-MOST. Xiaoxia Deng  was supported by a Grant from the  China Scholarship Council  No. (2017)3109. Chemical analyses were conducted at the platform PACE which is supported by  LabEx CeMEB , an  ANR  " Investissements d'avenir" program  ( ANR-10-LABX-04-01 ).
Sample Collection Samples from 228 A. regius individuals were collected between 2019 and 2020 from landings by local fishermen and fish imports from eight locations of geographical areas in proximity of known spawning areas from the North-East and Eastern Central Atlantic: Gironde (1 location, France), Tagus (3 locations-offshore Vieira de Leiria, Tagus estuary, and Sado estuary-Portugal), Algarve (2 locations-offshore Olhão and Guadiana estuary-Portugal), and Mauritania-Morocco (2 locations, Morocco and Mauritania) (Figure  1  and Table  1 ). To simplify, hereafter, the geographical areas in the proximity of known spawning areas will be referred to as spawning areas. Fin clips were stored in 98% alcohol. 1. Table  1. Sampling data for Argyrosomus regius individuals analyzed in this study.
6 units of My Taq TM DNA polymerase (Bioline, London, UK), 1. 2 µL of 5× My Taq Reaction Buffer (Bioline), 0. 4 µM for each primer, and ultrapure water. The PCR reactions were run for 27-35 cycles on a Bio-Rad1 thermal cycler and included an initial activation step at 95 • C for 15 min, denaturation at 94 • C for 30 s, primer annealing at 60 • C for 90 s, extension at 72 • C for 60 s, and final extension at 72 • C for 10 min. Samples were subsequently genotyped in an ABI PRISM ® 310 Genetic Analyzer and fragments were sized with GeneScan™-500 LIZ™ Size Standard. Allele sizes were determined using the GeneMapper TM 3. 7 software (Applied Biosystems, Waltham, MA, USA) (Supplementary Table  S1 ).
Data Analyses The presence of null alleles, stuttering, and allele dropout were tested for all loci using the MICRO-CHECKER v. 2. 2. 3  [24] , and the data were subsequently visually examined for correction. Departures from Hardy-Weinberg equilibrium and linkage equilibrium were assessed using ARLEQUIN v. 3. 5. 2. 2  [25]  (10 4 permutations). The pairwise F ST values from the original data and the data with null alleles correction were obtained using FREENA  [26]  (10 4 permutations) and compared to verify the influence of the null alleles in the analyses. Regarding genetic diversity, the mean number of alleles (Mna), the mean number of private alleles (MNp), the mean observed (Ho), expected (He), and unbiased expect (uHe) heterozygosities were calculated with GenAlEx v. 6. 5  [27]. The mean allelic richness (Ar) and the inbreeding coefficient (F IS ), with 95% confidence intervals (10 4 bootstrap replicates), were estimated with the diveRsity package in R v.
Contemporary effective population sizes (Ne) were calculated based on linkage disequilibrium (LDNe, single-sample approach) and heterozygote excess methods in NeEstimator v. 2. 01 [34], assuming random mating and a critical frequency threshold value of 0. 05. Additionally, to assess relative gene flow, the experimental divMigrate function of diveRsity package in R v. 4. 1  [28]  was used, based on F ST measure.
Genetic Diversity and Differentiation Signs of null alleles, as a consequence of the excess of homozygotes, are detected in PT-SAD for UBA5, in MOR for Soc423, in PT-GUA for soc412, and in all location sites except MOR for UBA42. In addition to this, signs of stuttering are also detected in PT-LEI and PT-TJ for UBA42. However, no consistent departure from Hardy-Weinberg equilibrium is detected in any location site. Similar pairwise F ST values are obtained using either the original data or the data with null alleles correction (difference ranging between -0. 0029 and 0. 0037; Supplementary Table  S2 ), indicating low influence of the null alleles. Therefore, all further analyses were performed using the original genotypic data for the fifteen microsatellite loci. The number of alleles per locus ranges between 3 (Soc156) and 27 (Soc35).
Acknowledgments: The authors wish to thank  Docapesca-Portos e Lotas, SA, MARL-Mercado Abastecedor da Região de Lisboa  (particularly  Pérola Mirante ), TUNIPEX company,  Ricardo Gonçalves ,  Marie-France Gassian ,  François Gassian , and  Marie-Laure Acolas  for their assistance in the sample collection.
Funding: This study was supported by  National Funds through FCT (Foundation for Science and Technology)  via the project " MIGRACORV-Integrated approach to study the movement dynamics of the meagre Argyrosomus regius " ( PTDC/BIA-BMA/30517/2017 ), through the strategic project  UIDB/04292/2020  awarded to MARE and through project  LA/P/0069/2020  granted to the  Associate Laboratory ARNET. Catarina S. Mateus was funded by  FCT  via the project " EVOLAMP-Genomic footprints of the evolution of alternative life histories in lampreys " ( PTDC/BIA-EVL/30695/2017 ) and  Bernardo R. Quintella  through  FCT Scientific Employment Stimulus Programme  ( 2020. 02413. CEECIND).
2 ). The southern population is more heat tolerant (7-31℃ range) than the northern population (-1. 4 to 21℃ range)  [31] , and the daily and seasonal temperature uctuations vary widely between populations  [31, 33]. Thus, we calculated E values for a range of acclimation temperatures for northern and southern killi sh based on data from an extensive killi sh acclimation experiment  [34]. To calculate MRR values associated with future projects, we substituted contemporary SSTs with predicted SSTs based on a novel coastal SST dataset we developed for the 2050s and 2100s. We implemented a downscaling approach built on averaging three coupled model intercomparison project phase 5 (CMIP5) model outputs (Representative Concentration Pathways (RCP)2. 6,4. 5,8. 5; Supplementary Table  S1 ). Subsequently, the model allowed a sh population in a given habitat (0.
Species-speci c E value calculation Species-speci c E values were calculated using collected sh routine or standard metabolic rate data published between 2000-2018. Data available in the University of Maine Aquatic Science and Fisheries Abstract and Web of Science databases were used in this calculation. This study only considered the metabolic rate data of sh treated in three or more acute/acclimatory temperature treatments  [54]. Metabolic rate data collected as a function of temperature, CO 2 , or Salinity were considered in the study after removing metabolic rate data collected at projected scenarios. Respective authors were contacted personally to obtain metabolic rate data unless data weren't available online. Species-speci c E values were calculated using the Arrhenius-Boltzmann [46] (Eq.
Atlantic Killi sh habitat distribution data Atlantic Killi sh probability distribution data were downloaded from the AquaMaps (www. aquamaps. org). AquaMaps generates Atlantic Killi sh native range probability distribution (0-1) in 0. 5º×0. 5º grid resolution (Fig. 1  and Supplementary Table  S1 ). Contemporary coastal Sea Surface Temperature (SST) High resolution (0. 05º×0. 05º×daily) reprocessed global SST data (59/55) between 1982-2018 were downloaded from Marine Copernicus (https://marine. copernicus. eu) server for the model domain of 20º-60ºN and 100º-54ºW. Atlantic Killi sh mostly inhabits estuaries and saltmarshes  [31]. Therefore, we assume that Atlantic killi sh inhabits within the 0-10m depth range and extracted SST data between 0-10m depth contours using very highresolution ETOPO2v2 bathymetry data (Supplementary Table  S1  nomenclature is based on the rip nomenclature (r -realization, i-initialization, and p-physics).
Model condition 3: If T max >32℃ or T max (future) ≥ T max (contemporary) and MRR (future) ≥ MRR (contemporary), the inhabited sh population moves to the nearest grid location where MRR (contemporary) ≤ MRR (future). Model building, running, and mapping (m_map toolbox v1. 4 [58]) were completed using the MATLAB R2020a version (University of Maine academic license 358411). Cartesian climate data grids were re-gridded into regular latitude and longitude grids using area-weighted bilinear interpolation in Climate Data Operators (CDO v. 1. 9. 9  [59] ). Fish E value calculation, statistical analysis, and thin-plate spline interpolation ( elds library v. 11. 6 [60]) were conducted in R v 4. 0. 3 (www. r-project. org).
Data Availability AquaMaps habitat probability data and temperature envelope data can be found at: https://www. aquamaps. org/. Contemporary and the IPCC CMIP5 predicted future SST data are available at the Marine Copernicus database: https://marine. copernicus. eu/ and https://esgf-node. llnl. gov/projects/cmip5/ respectively. ETOPO5 v2 bathymetry data are available at the https://www. ngdc. noaa. gov/ web link. Fish standard/routine metabolic rates are available in the main/supplementary sections of the respective manuscripts or by contacting the respective authors of each manuscript. All the processed data will be shared upon the manuscript acceptance. PIBCM code is available from the corresponding author upon reasonable request. Codes compiled to downscale CMIP5 SST data are available at the GitHub repository https://github.
Plant material and experimental design The material evaluated includes 18 accessions, of which two are from cultivated eggplant S. melongena (ANS26 and MEL2) and 16 from eight wild species of eggplant relatives from the primary, secondary and tertiary gene pools. Data on the materials used are summarised in Table  1. All materials are stored at the germplasm bank of Universitat Politècnica de València. Seeds of all accessions were germinated according to the protocol of  Ranil et al. (2015). Once germinated in Petri dishes, seeds were transferred to trays containing Humin-substrat N3 (Klasmann-Deilmann, Germany) substrate in a climatic chamber with a 14 h light/10 h dark photoperiod and a 25 • C (light)/18 • C (dark) temperature regime, until plantlets reached a height of 6-8 cm; then, they were transferred to 1.
Statistical analysis Data were analysed using the program Statgraphics Centurion XVI (Statgraphics Technologies, The Plains, VA, USA). All mean values throughout the text are based on five biological replicates. A two-way ANOVA was performed considering as factors the treatment, the accession (genotype) and their interaction and post hoc comparisons were made using Tukey's HSD test at p < 0. 05. A multivariate principal component analysis (PCA) was performed for standardised data of all traits using pairwise Euclidean distances among means for combinations of accession and treatment.
Acknowledgments This work was undertaken as part of the initiative " Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives ", which is supported by the  Government of Norway. The project is managed by the  Global Crop Diversity Trust  with the  Millennium Seed Bank of the Royal Botanic Gardens ,  Kew  and implemented in partnership with national and international gene banks and plant breeding institutes around the world. For further information, see the project website: http://www. cwrdiversity. org/. Funding was also received from grant  RTI-2018-094592-B-I00  funded by  MCIN/AEI/ 10. 13039/501100011033 / and by " ERDF A way of making Europe ", and from  European Union 's  Horizon 2020 Research and Innovation Programme  under Grant Agreement No. 677379  ( G2P-SOL  project: Linking genetic resources, genomes and phenotypes of Solanaceous crops).
LAMP Primer Design Based on the analysis of mitochondrial genome sequences (unpublished data) from T. japonensis, Thecodiplosis sp. and mitochondrial genome sequences in NCBI from three other gall midges (Mayetiola destructor, Orseolia oryzae and Rhopalomyia pomum), a partial COI sequence region was chosen as a target region to design LAMP primers. Nine COI sequences containing the target region were downloaded from GenBank and NCBI (see Supplementary File S2) from the closely related gall midges. For comparative analysis, COI sequences were aligned using MEGA 7. Six LAMP primers were manually designed targeting eight DNA regions and synthesized by a commercial company (SinoGenoMax, Beijing, China). Potential primer-dimer interactions of LAMP primers were analyzed.
Species-Specific PCR Assay A pair of T. japonensis-specific primers, named COI-F and COI-R, were designed by Primer 5. 0 according to the difference in COI gene sequence between T. japonensis and related gall midges. The Primer-BLAST found in the NCBI database showed that the primer set only matched the COI gene fragment of T. japonensis. The primers were synthesized by a commercial company (SinoGenoMax, Beijing, China). For SS-COI PCR, Prime Star Mix (Tsing Ke, cat#R045) was used together with two SS-COI primers (COI-F and COI-R) following the protocol: 94 • C for 2 min followed by 35 cycles of 94 • C for 30 s, 61 • C for 30 s and 72 • C for 1 min. The serial dilution of gDNA extracts was the same as the LAMP assay. PCR fragments were separated by 1. 0% agarose gel and checked under UV light with GelRed.
Species-Specific PCR Assay A pair of T. japonensis-specific primers, named COI-F and COI-R, were designed by Primer 5. 0 according to the difference in COI gene sequence between T. japonensis and related gall midges. The Primer-BLAST found in the NCBI database showed that the primer set only matched the COI gene fragment of T. japonensis. The primers were synthesized by a commercial company (SinoGenoMax, Beijing, China). For SS-COI PCR, Prime Star Mix (Tsing Ke, cat#R045) was used together with two SS-COI primers (COI-F and COI-R) following the protocol: 94 °C for 2 min followed by 35 cycles of 94 °C for 30 s, 61°C for 30 s and 72 °C for 1 min. The serial dilution of gDNA extracts was the same as the LAMP assay. PCR fragments were separated by 1. 0% agarose gel and checked under UV light with GelRed.
). To ensure the reliability of aging predictions, this paper describes a detailed analysis of the neutron H. B. Robinson-2 reactor pressure vessel dosimetry benchmark. The results indicate that VACS shows satisfactory accuracy when the ENDF-B/VII. 1 or JEFF-3. 3 nuclear data libraries are used in the attenuation calculation. However, the use of ENDF-B/VIII. 0 leads to significantly worse results.
In order to validate the numerical predictions using experimental dosimeter data from ex-core locations, a detailed analysis of the H. B. Robinson-2 (HBR-2) RPV dosimetry benchmark  [11]  was conducted. This benchmark was chosen because it includes measurements performed for an operating PWR using in-vessel (capsule location) and ex-vessel (reactor cavity) dosimeters. This feature is of major interest because it allows the accuracy of aging predictions to be characterized, not only for in-vessel applications but also, to some extent, for ex-vessel ones. In addition, the HBR-2 benchmark provides a fission neutron source term which is intended to be directly used to validate the accuracy of the neutron attenuation calculation only (second step). However, the data provided were used to analyze the accuracy of both steps of the calculation scheme (fission neutron source term and attenuation) and thus to provide a complete validation.
The H. B. Robinson-2 Reactor Pressure Vessel Dosimetry Benchmark The H. B. Robinson-2 (HBR-2) neutron dosimetry benchmark  [11]  from the SINBAD database  [12]  is widely used in the scientific community for the validation of calculation schemes designed to predict vessel aging, as shown in  [13] [14] [15] [16]. It features in-vessel (surveillance capsule) and ex-vessel (reactor cavity) dosimetry data acquired during the 9th cycle of the H. B. Robinson-2 reactor.
These elements can be found in Figure  2 , which is taken from  [14]  and presents a simplified view of an eighth of the reactor. On the one hand, the dimensions of the majority of the components at or above assembly scale (assembly, baffle, barrel, thermal neutron shield, RPV, etc. ) are provided in the benchmark data  [11]. On the other hand, the dimensions of some components below the assembly scale (fuel pins, guide tubes, etc. ) are not specified in  [11]  but can be found in  [17]. Descriptions of the materials constituting the main elements of the reactor (fuel, baffle, cladding, thermal neutron shield, vessel, etc. ) are also provided in the benchmark data  [11]. The HBR-2 reactor has four groups of black control banks and one bank of shutdown rods. The insertion layout of these banks can be found in  [17].
From this data, it is possible to know that the HBR-2 reactor did not operate at nominal power during cycle no. 9, but operated for most of the time at 80% of its nominal power (NP) and experienced numerous power drops. The average power of the reactor over the cycle was equal to 75. 2% NP, which corresponds to roughly 1729. 6 MWth. At such power levels, it is very likely that the control rods were partially inserted during the cycle. However, in the absence of information on the insertion sequence of the control-rod banks, it is not possible to reconstruct the average insertion position of each rod bank over cycle no. 9. Other data included in the benchmark  [11]  give the average power distribution of the reactor over cycle no. 9. This power distribution is provided at the assembly level for the entire core and at the fuel-pin level for the upper right quarter.
Here, the spatial dependency of the fission neutron source term (R f • ν product) is evaluated by means of core-following calculations performed using a deterministic approach, coupling the CASMO5  [20]  and SIMULATE5 codes. The CASMO5 code is used to generate the fuel-assembly homogenized 8-group macroscopic cross-section data. Then, the SIMULATE5 code uses these data as a multi-parametric database (since the energygroup cross sections depend on moderator density, boron concentration, etc. ) to compute the full-core fission neutron source term. On the CASMO5 side, the 2D stationary transport equation (the axial dimension being considered as infinite) is solved for assemblies in an infinite lattice, using a 586-group data library based on the ENDF/B-VII. 1 nuclear data  [24]. Firstly, the collision probability (P ij ) method  [25]  is used with 586 energy groups, on a coarse spatial mesh.