dataesr/scientific-paragraphs-categorization huggingface dataset:
Methodology A systematic review was conducted to synthesise the use of theories in empirical SVRA research following the PRISMA guidelines  (Page et al. , 2021). As the boundary of this field of research is hardly defined, we identified relevant papers through keyword searches containing SVRA and hazard-related keywords (Box 1) based on previous similar searches  (Ejeta et al. , 2015; Oktari et al. , 2020). The search was restricted to peer-reviewed articles written in English that included the search keywords in their title, abstract, or keywords. No lower boundary time constraints were used, but only articles published until December 31st 2020 were considered. Review articles, commentaries, and opinion pieces were excluded. Based on these criteria, 4432 records were retrieved from the Web of Science (WoS) database (Fig.
g. testing a theory) and/or inductively 3  (e. g. developing a theory based on empirical observations) (Fig. 2);  (2) the study design (e. g. experimental, longitudinal); and (3) the data collection methods (survey, interview, focus group or workshop, Box 1 : Search string used to retrieve relevant articles in Web of Science. Topic=("coping capacit*" OR "adaptive capacit*" OR "social resilience" OR "adaptive resilience" OR "community resilience" OR "household resilience" OR "adaptive behavio*" OR "social vulnerab*" OR preparedne*) AND Abstract, Title or Author keywords =(flood* OR inundation OR "storm wave*" OR "storm surge*" OR " tidal surge*" OR "storm tide*" OR "hurricane tide*" OR "tropical surge*" OR drought* OR heatwave* OR "heat wave*" OR "extreme heat" OR landslide* OR mudslide* OR mudflow* OR rockslide* OR "debris flow" OR lahar* OR earthquake* OR tsunami* OR "seismic sea wave" OR bushfire* OR wildfire* OR "forest fire*" OR "volcanic eruption*" OR "volcanic ash*" OR magma* OR lava OR volcano* OR "volcanic hazard*") before screening participant observation, document analysis, indicator-basedapproaches, and computer modelling).
The data collection methods were selected based on the co-authors' experience. Information on the investigated hazards and mentioned theories were extracted using text pattern matching. Results were supplemented and validated by the coauthors. In addition, we pragmatically grouped theories according to their foci, including (1) theories with a focus on individual decision-making processes stemming mostly from behavioural sciences, economics, and psychology (e. g. bounded rationality and prospect theory); (2) theories with a focus on micro-macro processes, groups and/or networks often referred to in sociology, anthropology and human geography (e. g. PAR, networks and social capital, Cultural Theory etc. ) and (3) theories with a focus on social-ecological systems (e. g. resilience, complex systems etc.
Trends in SVRA research A total of 2716 potentially relevant articles addressing SVRA were retrieved by our search (Fig. 1 ). Since 1992, the number of SVRA articles has increased by more than two orders of magnitude (Fig. 3A ). This increase is exponential even when normalising the data by the yearly number of all articles included in the WoS database. Regarding the hazard types, most articles addressed floods (47. 9%), followed by earthquakes (27. 8%) and droughts (17. 0%) (Fig. 3B ). Out of the 2716 potentially relevant articles, 413 (15. 2%, 95% CI [13. 8%, 16. 6%]) mentioned at least one of the 29 theories investigated (i. e. theories mentioned in 5 or more articles -SM1) (Fig. 4 ). We considered a paper as theoretically grounded only if the authors specifically mentioned that they used or tested a theory.
, 2012; Snel et al. , 2019). The pressure-and-release (PAR) model was mentioned in several studies (n = 28). However, it was only applied in 5 articles that investigated, among others, how poverty and/ or other specific pressures translate into vulnerable conditions. Grounded theory was used quite often (n = 47). This methodological procedure is prominent in qualitative interpretative research to structure the data and inform, ideally, a process of theorising. Grounded theory, thus, does not represent a theory in our understanding as it makes no assumptions about the relationship between variables and constructs. It rather allows scientists to investigate how individuals or groups define a phenomenon via their social interaction (da Silva  Barreto et al. , 2018). As such, researchers often use this inductive approach to interpret results about individuals' social and psychological aspects that shape their SVRA.
, 2017; Bubeck et al. , 2018; van Valkengoed and Steg, 2019). Theories focusing on collective social processes (e. g. Hazards of Place, DPSOR, Social Capital, Cultural Theory and PAR) and social or socio-ecological systems (e. g. Resilience Theories and Diffusion Innovation Theory) were less prominent in our sample, with 50 and 20 articles, respectively. Despite their low uptake, these theories have the potential to provide a deeper understanding of complex relationships and processes underlying SVRA. Nevertheless, they often require extensive data  (Kiesling et al. , 2012)  or are rather time-consuming to apply  (MacDougall et al. , 2014) , which might explain why they were used less often. Grounded theory is a "false friend" in our sample. Although it mentions the term "theory", it is not considered a theory according to the understanding of this paper.
Therefore, we contend that explicit engagement with theories in SVRA research is required to ensure studies' (1) transparency, (2) incremental or revelatory advancements, (3) comparability of findings, and (4) thus informing and influencing decision-making processes on the policy level. (1) The explicit use of theories reduces ambiguities and contributes to transparency Whether explicated or not, theories influence the research design, including deciding which variables are elicited and how data are collected, analysed and interpreted. Explicitly referring to a theory/ theories can help readers understand why scholars focus on specific SVRA aspects or why they chose certain factors (and, by doing so, exclude others). Making theoretical considerations salient thus supports understanding design choices in the empirical analysis and opens them up for scrutiny.
A Bayesian binomial model was developed to analyse the large datasets coming from the multi-centre study in order to determine concentration-response estimates and to assess variability in mortality under different test conditions. Overall the results obtained validate the bottle method to produce the data needed to assess mosquito susceptibility to insecticides and establish DCs for compounds which are not suitable for use on filter papers. This method can be used, with the DCs recently established  [22] , to monitor for resistance to these compounds in wild mosquito populations.
After validating the test protocols, we conducted a multi-centre study with serial concentrations of the insecticides to generate concentration-response data for each insecticide-species combination. For insecticides with a killing action, the first step of the study (Step 1) comprised preliminary bioassays to scope the range of insecticide concentrations that would kill between 0 and 100% of the tested mosquito colonies using a small number of mosquitoes (n = 50 per concentration). Based on Step 1, a range of six insecticide concentrations were chosen to produce a complete set of bioassays in triplicate (Step 2) (n = 300 per concentration). Based on the results, we estimated the lethal concentrations that would kill 50% and 99% (LC 50 and LC 99 ) of the tested mosquito colonies using a statistical model specifically developed for analysing complex toxicological datasets (see details in section Statistical analysis).
Model variability Model variability was estimated by computing the absolute difference in mortality or OI of each individual data point from the best fit line for each MCMC iteration at the insecticide, species and location level. The median of all iterations for each insecticide, species and location was computed to generate a measure of variability, which is interpreted as the percentage variability in mortality or OI from the best fit line. This measure allows the amount of within-bioassay variability to be quantified in terms of mortality or OI. Estimates were generated for each mosquito species-insecticide combination, with the variability reflecting the average within-bioassay variability between different laboratories with its 95% confidence intervals. Where multiple institutions provided data for specific insecticide and species combinations, the mean of the fitted estimates from these different institutions was computed when generating estimates for the insecticide and species levels.
albopictus) and five major malaria vectors in several regions (An. gambiae s. s, An. funestus s. s, An. stephensi, An. minimus s. s and An. albimanus) were tested with the WHO bottle bioassays, making this, to our knowledge, the largest mosquito toxicological dataset ever produced. Our findings showed that the WHO bottle bioassay was adequate to perform concentration-response analysis and calculate the toxicity (i. e. LC 50 /OI 50 and LC 99 /OI 99 ) of various insecticide class groups, namely the pyrethroids metofluthrin, prallethrin and transfluthrin; the neonicotinoid clothianidin; the pyrrole chlorfenapyr; the juvenile hormone mimic pyriproxyfen; and the butenolide flupyradifurone. Despite the promising results obtained and some very consistent results, a marked variability in LC 50 and LC 99 Fig.
g. mosquitoes and sand flies). In this study we also validated a new Bayesian binomial model using a 5-parameter logistic function developed at Imperial College London to analyse large and complex bioassay datasets. The model offers a flexible Bayesian alternative to common probit or log-probit analysis methods  [29] , allowing the integration of prior knowledge and generating novel ways to summarise the data. Overall, the model was shown to be adequate to produce concentration-response estimates and assess the variability in endpoints for different insecticides with particular modes of action. The model highlighted the high variability in estimates generated at different laboratories for some mosquito species-insecticide combinations and differences were observed in both the LCs and distribution of the LCs.
Conclusion This study provides strong evidence to support the use of the WHO bottle bioassay for assessing mosquito susceptibility to certain new public health insecticides that have the potential for use in vector control but that cannot be impregnated onto filter papers due to technical reasons. The method and the datasets presented in this study have been used recently to establish and validate 17 new WHO DCs for insecticides against either Aedes spp. or Anopheles spp. (  [22] ; Additional file 4: Table  S3 ). The WHO bottle bioassay and the DCs determined in this study (see Additional file 4: Table  S3 ) can now be widely used to monitor baseline susceptibility of wild populations of vectors of malaria and Aedes-borne diseases.
Acknowledgements We acknowledge the contributions of all investigators of the participating institutions (IRD,  NIH-Colombia, LNRE, CDC, FIOCRUZ-IOC, Swiss TPH, IPR, LSTM, LSHTM, ICL, CREC, IRSS, NICD, ICMR-NIMR New Delhi and Bengaluru, ICMR-VCRC, VCRU, NEA, MU, KU, KCMC, OCEAC, UANL)  for their technical and administrative assistance during the study. We are also grateful to the technical staff of these institutions for their contribution in producing mosquitoes for the studies, including the BEI Resources of the MR4 Repository. We also thank the insecticide manufacturers ( Bayer CropScience, Leverkusen, Germany ;  BASF, Ludwigshafen am Rhein, Germany  and  Sumitomo Chemical Co. Ltd. , Tokyo, Japan)  for providing the insecticide active ingredients and the surfactant (MERO ® ) at no cost.
MDK, BL and TSC acknowledge funding from the  MRC Centre for Global Infectious Disease Analysis  (reference  MR/ R015600/1 ), jointly funded by the  UK Medical Research Council (MRC)  and the  UK Foreign, Commonwealth & Development Office (FCDO) , under the  MRC/ FCDO  Concordat agreement, and is also part of the EDCTP2 programme supported by the  European Union. We also thank the  Institut de Recherche pour le Développement (IRD)  and the  Worldwide Insecticide Resistance Network  ( WIN ) for their technical support (https:// win-netwo rk. ird. fr/).
Sampling and blood film examination The seriema was a juvenile individual, unwilling to move, and had evidence of dog bites such as abrasions, bruises and holes in the body. Upon arrival, we physically restrained the specimen and collected 1 mL of blood through the ulnar vein. This material was used to prepare two blood smears on glass slides, which were fixed with 100% methanol for 3 min and stained with 10% Giemsa (pH = 7. 2) for 70 min. The remaining blood was stored in 70% ethanol inside a refrigerator for subsequent DNA extraction and molecular analysis. We analysed the blood smears using an Olympus CX31 microscope. Digital images were captured using an Olympus Qcolor 5 camera and processed with QCapture software. Measurements were made digitally using ImageJ  (Schneider et al. , 2012).
DNA sequences were checked for the presence of mixed infections (presence of double peaks in the electropherogram), edited using ChromasPro 2. 0. 6 (Technelysium Pty Ltd, Helensvale, Australia) and compared with data available in the public databases GenBank (http://www4. ncbi. nlm. nih. gov) and MalAvi  [Bensch et al. (2009) , http://mbio-serv2. mbioekol. lu. se/ Malavi/]. In addition to this protocol, the extracted DNA was also screened for the presence of haemosporidians using a nested-PCR protocol that targets the complete parasite cytb gene (1131 bp) with external (AE298 and AE299) and internal primers (AE064 and AE066) described by  Pacheco et al. (2018a Pacheco et al. ( , 2019)). Using this protocol, sequencing the PCR-amplified products from the primary and the nested PCRs confirmed the presence of H.
Both strands of 3-5 clones were sequenced at Genewiz from Azenta Life Sciences (New Jersey, USA). Inconsistencies between the clones were not found. The mtDNA genome sequences obtained in this study were identified as Leucocytozoon and Haemoproteus using BLAST  (Altschul et al. , 1990)  and submitted to GenBank under accession numbers OQ915109 (H. catharti), OQ915110 (H. pulcher) and OQ915111 (L. cariamae n. sp. ).
Phylogenetic analysis Phylogenetic relationships between the nearly complete mtDNA genomes of the new Leucocytozoon sp. , H. pulcher, H. catharti and other haemosporidians were inferred on a mtDNA alignment constructed using ClustalX v2. 0. 12 and Muscle as implemented in SeaView v4. 3. 5  (Gouy et al. , 2010)  with manual editing. This alignment (5096 bp excluding gaps) included 74 partial mtDNA genome sequences belonging to 4 genera (Leucocytozoon, Haemoproteus, Haemocystidium and Plasmodium) available from GenBank  (Benson et al. , 2013)  plus the 3 new sequences obtained in this study. Then, the phylogenetic relationships were inferred on this alignment using 6 partitions  (Pacheco et al. , 2018b). A tree was estimated using a Bayesian method implemented in MrBayes v3. 2. 7 with the default priors  (Ronquist and Huelsenbeck, 2003).
The best model that fitted the data, as estimated by MEGA v7. 0. 14  (Kumar et al. , 2016) , was a general time-reversible model with gamma-distributed substitution rates and a proportion of invariant sites (GTR + Γ + I). Bayesian support was inferred for the nodes in MrBayes by sampling every 1000 generations from 2 independent chains lasting 4 × 10 6 Markov chain Monte Carlo steps. The chains were assumed to have converged once the value of potential scale reduction factor was between 1. 00 and 1. 02, and the average standard deviation of the posterior probability was <0. 01. Then, 25% of the samples were discarded once convergence was reached as a 'burn-in'. GenBank accession numbers of all sequences used in this analysis are shown in the phylogenetic tree. In addition, the average evolutionary distance over all sequence pairs of Leucocytozoon spp.
Cytb gene BLAST analysis The result of BLASTn using the partial cytb sequence of L. cariamae n. sp. as query returned 100% identity and 100% coverage in relation to the CARCRI01 lineage (OK086053) also found in seriemas sampled in the Brazilian Cerrado  (Carvalho et al. , 2022). The most closely related Leucocytozoon lineage reported (GenBank acc. no. KX832566) has 0. 035 genetic distance in relation to L. cariamae n. sp. and was found in common wood pigeons (Columba palumbus) from the UK (see Fig. 1  in  Carvalho et al. , 2022). Leucocytozoon cariamae n. sp. has 0. 042 genetic distance in relation to Leucocytozoon podargii described infecting tawny frogmouths (Podargus strigoides) in Australia  (Jiang et al. , 2019) , and to Leucocytozoon californicus infecting American kestrel (Falco sparverius) in California, USA  (Walther et al.
mtDNA phylogenetic analysis Given that a comprehensive phylogenetic analysis using partial cytb gene sequences was already published in 2022 (see Fig. 1  in  Carvalho et al. , 2022) , here we focus on the Bayesian phylogenetic hypothesis using the nearly complete mtDNA genomes (Fig. 3 ; Supplementary Fig. S1 ). The parasite with the closest relationship to L. cariamae n. sp. that has been sequenced at the mtDNA genome level is Leucocytozoon sp. TFUS14 (genetic distance = 0. 101 ± 0. 005), which was detected in a great thrush (Turdus fuscater, GenBank acc. no. KT162002) from Colombia. These 2 Leucocytozoon parasites, together with Leucocytozoon quynzae (from Heliangelus amethysticollis sampled in Colombia, KF479480) and Leucocytozoon majoris (from Zonotrichia leucophrys oriantha sampled in North America, FJ168563) are part of a monophyletic group that share a common ancestor with a clade of diverse Leucocytozoon fringillinarum lineages (from several hosts; Fig.
cariamae n. sp. was not detected using the protocol described by  Pacheco et al. (2018a Pacheco et al. ( , 2018b) )  to target the same gene. Although costly, the use of several PCR protocols combined with microscopy should be favoured in avian haemosporidian studies  (Feldman et al. , 1995; Jarvi et al. , 2002; Richard et al. , 2002; Valkiūnas et al. , 2008; Braga et al. , 2011; Clark et al. , 2014). The Bayesian phylogenetic analysis performed with nearly complete mitochondrial genomes (Fig. 3 ; Supplementary Fig. S1 ; Table  2 ) showed that L. cariamae does not share a recent common ancestor with the fringillinarum group. This supports our morphological findings and previous phylogenetic results obtained using the cytb gene fragment  (Carvalho et al. , 2022). The closest Leucocytozoon cytb lineage (GenBank acc.
Acknowledgements. We thank the entire  CETAS-BH team  of professionals and volunteers for supporting the research and helping with the collection phase. Author's contribution. Conceived and designed the experiments: L. M. C. V. , F. C. F. and E. M. B. Performed the experiments: L. M. C. V. , P. H. O. P. and M. A. P. Analysed the data: L. M. C. V. , I. L. , M. A. P. , A. A. E. , F. C. F. and E. M. B. Contributed reagents/materials/analysis tools: D. A. R. V. , E. M. B. , M. A. P. and A. A. E. Wrote the paper: L. M. C. V. , M. A. P. , A. A. E. , F. C. F. and E. M. B. Financial support. This work was supported by  Fundação de Amparo à Pesquisa do Estado de Minas Gerais -FAPEMIG  (grant number  APQ-00645-18 );  Conselho Nacional de Desenvolvimento Científico e Tecnológico -CNPq  (grant number  304334/2019-7 ) and  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
Additional hosts: Unknown. Type locality: Rural area of Mateus Leme (19°59 ′ 09 ′′ S, 44°2 5 ′ 40 ′′ W), Minas Gerais, Brazil. Type specimen: Hapantotype was deposited in the biological collection of the Muséum Nation d'Histoire Naturelle, Paris, France; the intensity of parasitaemia is 0. 005%, collected by Lis Marques in the CETAS-BH, Minas Gerais, 13 December 2021. DNA sequences: The partial mitochondrial cytochrome b fragment (478 bp) obtained corresponded in 100% identity to the lineage CARCRI01 (GenBank acc. no. OK086053 from 3 specimens of red-legged seriemas, C. cristata). The nearly complete mtDNA genome (acc. no. OQ915111) corresponded to the same genetic lineage that is already deposited in GenBank (acc. no. KX832566). Site of infection: Blood cells, for which origin could not be identified due to the marked deformation caused by L.
The X-axis represents the time. Different information can be obtained from the drying profiles, that is: 1. The WC capacity can be obtained after 24 h of SC stabilization at 100% relative humidity. WC can be obtained when data is registered directly after the 100% RH stabilization. This corresponds to the point at the beginning of the drying process (Figure  2  Low GWL% values are correlated to good waterholding capacities. In order to evaluate the effect of solar radiations on dehydration kinetics (Irr-SC) and the impact of adding SSLs at the surface of the SC (Ctrl SC + SSLs and Irr-SC + SSLs) or irradiation through a SSLs layer; (SC-Irr-SSLs) WC, water retention (WR), and LTWH of all drying kinetics profiles are plotted in Figure  3A  for WC, Figure  3B  for WR, and Figure  3C  for LTWH.
Statistical analysis Data analyses were carried out with the R software (version 3. 3. 3; R Core  Team, 2017). We tested a total of 120 observer females. Observer females that showed a strong side-bias independently from the fact that we swapped the males in the middle of the mate-choice test, i. e. , whose total time spent on the mate-choice zone of one side represented more than 90% of the total time spent in the two mate-choice zones during the first mate-choice test, were removed from our study. This is a common criterion in mate-copying experiments (e. g. ,  Witte and Noltemeier, 2002; Witte and Ueding, 2003). Fifteen females (14 AB, 1 TL) were excluded from the analysis because they showed a side bias in the first mate-choice test or did not move at all. Overall, we tested 105 females successfully: 65 in mate-copying experiments (30 AB, 35 TL) and 40 in control experiments (20 AB, 20 TL).
Acknowledgements This study was supported by the  French Laboratory of Excellence  project  TULIP  ( ANR-10-LABX-41 ;  ANR-11-IDEX-0002-02 ) and was funded by the  French funding agency ANR  (project  Soc -H2 ANR-13-BSV7-0007-01  to ED). SN acknowledges IAST funding from the  French National Research Agency (ANR)  under the Investments for the  Future (Investissements d ′ Avenir) program  ( ANR-17-EUR-0010 ). We would like to thank members of  Patrick Blader's lab  for help in raising the wildtype zebrafish.
Study information The U-BIOPRED adult study is a multicentre observational investigation recruiting asthmatics and healthy non-smoking controls from 16 clinical centres in 11 European countries between January 2011 and December 2013  [11]. The study (ClinicalTrials. gov NCT01976767) was approved by the ethics committees at the clinical sites, and participants provided written informed consent. This report includes the 576 participants with complete data for urinary steroid metabolites: 302 nonsmoking and 106 smoking or ex-smoking patients with severe asthma (SA), 70 patients with mildto-moderate asthma (MMA) and 98 healthy controls (HC). Their baseline characteristics are displayed in Table  1. The diagnosis of severe asthma followed ERS/ATS guidelines  [15]. The SA group was required to use ⩾1000 μg fluticasone propionate per day or equivalent dose of other corticosteroids, and MMA <500 μg daily.