dataesr/scientific-paragraphs-categorization huggingface dataset:
002, P = 0. 950; see also fig. S6 ). We found no relationship between vegetation openness and the wetland taxa Salix (estimate = 11. 127, P = 0. 213) and Alnus (alder; estimate = -0. 627, P = 0. 919). Across Europe (all grid cells), we found moderate evidence for a relationship between lake size and vegetation openness (estimate = 4. 499 × 10 -5 , P = 0. 024). However, this relationship was driven by the grid cell from Lake Van, Turkey, which is the largest lake in the dataset (table  S2 ). When we excluded this grid cell, we found no evidence of a relationship (estimate = -6. 020 × 10 -5 , P = 0. 353). S1 ), as these taxa are moderately light-demanding and grow opportunistically in open or light woodland areas and areas of recent disturbance  (36, 37). We expected high levels of Quercus and Corylus during the early-temperate because this pattern is characteristic of many of the Last Interglacial pollen diagrams  (24).
MATERIALS AND METHODS We focused our data collection and analyses on the temperate forest biome because we were explicitly interested in the vegetation openness of this bioclimatic region. We defined the temperate forest biome as an oceanic or continental climate zone traditionally considered dominated by temperate deciduous broad-leaved or mixed deciduous broadleaf-evergreen conifer forests (fig. S7  and table S3 )  (58). In addition, we collected pollen data from the adjoining subarctic and Mediterranean biomes to assess European vegetation cover more broadly and to further our understanding of the drivers of vegetation openness (fig. S7  and table  S3 ). We focused on the temperate period of vegetation development during the Last Interglacial period, as it reflects the climatic optimum  (24)  and maximum vegetation biomass development  (26).
Pollen data collection and preparation We collected 96 European pollen records from the European Pollen Database (www. europeanpollendatabase. net/), Pangaea (www. pangaea. de/), Neotoma (www. neotomadb. org/), and individual pollen data contributors (fig. S1  and table S2 ) and applied the vegetation reconstruction method REVEALS  (27). The REVEALS model reconstructs vegetation cover regionally. This is achieved by quantifying background pollen from one or more sites to produce regional vegetation for a 1°× 1°area  (27). REVEALS overcomes the nonlinearity of the pollen-vegetation relationship by accounting for relative pollen productivity (RPP), dispersal, and deposition differences between taxa  (27). The model has been extensively tested and validated at sites across Europe  (59, 60)  and North America  (61) , as well as at the European scale  (62).
To avoid issues of interglacial non-synchronicity across Europe, we used dominant vegetation taxa to classify the Protocratic, Mesocratic (temperate), and Telocratic periods based on defined pollen zones of the Last Interglacial  (24, 25)  following Lang's protocol  (24). Therefore, we examined vegetation openness in the Quercus/Corylus-dominated (first half of the Mesocratic: early-temperate) or C. betulus-dominated (second half of the Mesocratic: late-temperate) periods, rather than at specific times. We implemented REVEALS using the protocol of Githumbi et al. (7)  on the basis of the LRA R package  (66). The REVEALS model uses pollen count data, RPP estimates, and pollen fall speed to reconstruct regional vegetation cover for each taxon in each time slice (Supplementary Materials). The REVEALS model is applied to lake and bog sites separately within each 1°× 1°grid cell and combines results, from several sites when available, to produce a single mean percentage cover estimate (data S1) and mean SE (data S2) for each RPP taxon per grid cell.
Climate data and biomes We used equilibrium simulations of the climate at 127 ka B. P. (the climatic optimum of the Last Interglacial) as in  (68) , from six Earth system models: AWI-ESM-1-1-LR (69), CNRM-CM6-1 (70), GISS-E2-1-G (71), INM-CM4-8 (72), IPSL-CM6-LR  (73) , and MIROC-ES2L  (74). We downscaled the monthly surface air temperature and precipitation from these models to a resolution of 5 km. We then bias-corrected the values of the Last Interglacial simulation by comparing the historical simulations of the same models with the CHELSA V2 high-resolution climate dataset (75) over the period 1981-2010. From the corrected Last Interglacial values, we calculated the mean of the six models and derived bioclimatic variables, as in WorldClim  (76). We determined the climatic biomes of the Last Interglacial period using monthly temperature and precipitation data from each of the six Last Interglacial models and the mean ensemble model to produce the first Köppen-Geiger climate classification maps, as in  (77) , for the Last Interglacial period (fig.
Habitat characterization and specimen Since 2016, twice a year (summer and autumn), SCUBA-diving surveys have been used to monitor the benthic subtidal habitats at Porto Santo island at ten locations (Fig. 1 ). The surveys provided detailed and quantitative observation of seabed habitats at each location. Following the unexpected detection of the Caulerpa species in November 2020 in Porto Santo at 33. 05 • N, 16. 30 • W, more detailed surveys were conducted at this location using the methodology described in  Neves et al. (2021). The processed data was then imported into SIGMa (a GIS platform developed with QGIS Development Team, QGIS org, 2021) and the discovered patches plotted (Fig. 1 ). A total of four surveys were performed in November 2020, July and November 2021, and March 2022. During the first three surveys several specimens were collected and deposited in the Funchal Natural History Museum herbarium (as MADM4080, MADM4083, MADM4084 and MADM4085) and consist of morphological vouchers preserved as herbarium sheet, in 4% formalin, and in 96% ethanol.
mexicana was also previously sequenced and confirmed from Gran Canaria based on the internal transcribed spacers (ITS1 & 2, accession AJ007816 in Genbank,  Olsen et al. , 1998). Interestingly, at its type locality in the Florida Keys, C. ashmeadii generally occurs in sheltered calm areas on soft-bottom within seagrass beds or close to mangroves at shallow depths of 1-2 m  (Pacheco-Cervera et al. , 2009) , but it has also been reported in deeper subtidal zones (e. g. down to 36 m,  Littler and Littler, 2000, although  Caribbean specimens are molecularly unverified to date). Contrastingly, in Porto Santo, C. ashmeadii is only found in deeper habitat where it forms dense patches from 18 m down to 26 m. Regular monitoring carried out by the authors in this island since 2016 allowed the observation of a significant change in the studied mesophotic area depicted in Fig.
long, 0. 5 mm diameter) with rounded (obtuse) apices devoid of apiculi. DNA barcodes generated for the gene tufA for the 4 specimens were all 100% identical (i. e. no base pair variation among specimens). BLASTn analyses of the barcodes on NCBI GenBank matched C. ashmeadii from Florida (type locality, specimen TS1824, KF977086) with 100% identity. Logically, phylogenetic reconstruction positioned the Porto Santo specimens among previously sequenced C. ashmeadii (Fig. 2) and closely related to sister species considered as Western Tropical Atlantic (WTA) endemics, C. floridana W. R. Taylor 1960, C. wysorii T. Sauvage & M. J. Wynne 2021 and an unknown Caulerpa species. These putative WTA endemics are closely related to the amphi-Atlantic species C. prolifera.
Acknowledgements The authors wish to thank  Mar Dourado  and  Porto Santo Sub  for assistance during diving operations and to IFCN park rangers for all the help during Porto Santo survey campaigns. Pedro Neves  was financially supported by the  Oceanic Observatory of Madeira Project  ( M1420-01-0145-FEDER-000001 -Observatório Oceânico da Madeira-OOM). This study received funding from  Programa de Monitorização da CORDECA  and from the Portuguese national funds from  FCT -Foundation for Science and Technology  through project  UIDB/04326/2020  and  LA/P/ 0101/2020  granted to  Centro de Ciências do Mar. Thomas Sauvage thanks  Veronique Verrez-Bagnis  for facilitating the preparation and sequencing of the specimens at the  Ifremer Centre Atlantic. We are also grateful to  Dr. Stefano Draisma  for reviewing earlier version of the manuscript.
2G , Supplementary Figure  2H ). Moreover, the presence of DGATi did not change the physical state of the LDs but decreased the number of LDs to a similar level as without OA (Fig. 2G ). Our data indicate that ongoing TG synthesis determines the efficiency of CE LD formation. To rule out that these findings were specific to the A431 cell line, we also analyzed Cos7 and HeLa cells, loaded with cholesterol or cholesterol and OA. There, we likewise found that the inhibition of DGATs significantly reduced the number of LDs (Supplementary Figure  2J-R ).
The resulting solution was filtered using 0. 2 µm syringe filter and conserved at 4 °C until use. For 1 mM of oleic acid-containing media preparation, 10% of BSA solution in DPBS (#A1595 SigmaAldrich) was mixed with cell culture media at 1/10 v/v ratio. The resulting solution was incubated with pure oleic acid (#O1383 SigmaAldrich) to obtain a final concentration of 1 mM. The resulting mixture was vortexed and then sonicated for a few minutes and incubated at 37 °C for one hour. The resulting solution was filtered using 0. 2 µm syringe filter and conserved at 4 °C until use. Cell culture and lipid manipulations A431 cells (ATCC, Cat# CRL-1555, RRID:CVCL_0037) were maintained in Dulbecco's Modified Eagle's Medium (DMEM) supplemented with 10% FBS, penicillin/streptomycin (100 U/mL each), and L-glutamine (2 mM) at 37 °C in 5% CO 2.
Imaging and image analysis For lipid droplet analysis cells were delipidated and cultured on 384-or 96-well high-content imaging plates (Corning) and imaged with Perkin-Elmer Opera Phenix automatic spinning-disk confocal microscope using 63x water objective, NA 1. 15. Lipid droplets and seipin-sfGFP in control and NE-trap cells were imaged with Nikon Eclipse Ti-E inverted widefield fluorescence microscope using a 40x air objective, NA 0. 75, and 1. 5x zoom. Z-stacks were acquired to span whole cells on LD540 and DAPI channels. Image stacks were deconvolved with Huygens batch processing application (https://svi. nl/HuygensSoftware, v. 22. 10) and image stacks were maximum intensity projected with custom MATLAB scripts (http://www. mathworks. com/products/matlab/, v. 9. 2. 0. 538062; scripts are available upon request).
Simulation protocols Molecular dynamics simulations were performed were performed using Gromacs simulation package v. 2019. 6  51. Charmm36/m forcefield with virtual interaction sites  [52] [53] [54] [55]  was used for the proteins, lipids, water, and counter ions. This was done to enable using a larger integration time step of 4 fs. TIP3P water model was used. The systems were energy minimized, pre-equilibrated under constant pressure and temperature for 1 ns. Nose-Hoover thermostat  56  was used to maintain the temperature at 310 K with a coupling constant of 0. 5 ps while pressure was maintained at 1 atm using the Parrinello-Rahman barostat  57  with a coupling constant of 2 ps. Verlet cutoff scheme was used to update the neighbor list every 10 steps. Covalently bonded hydrogen bonds were constrained using LINCS algorithm  58.
Droplet/membrane partitioning analysis The fluorescence signal of the CE-bodipy was quantified in the bilayer and in the droplet, by fitting a gaussian curve on a line profile in Fiji. The ratio of the maxima in the droplet and in the bilayer is used as an output. In the case of burst DEVs, the fluorescence signal was averaged over a surface. The data have been normalized between the experiments in order to compare the droplet/membrane ratios between the different oils used.
Acknowledgements We thank our teams for their critical discussions,  Anna Uro  and  Bibi Hannikainen  for excellent assistance with experiments, and  Abel Szkalisity  for help with image analysis. A. R. T. was supported by  ANR-18-CE11-0012-01-MOBIL  and  ANR-21-CE11-0032-02-LIPRODYN , E. I. by the  Academy of Finland  grant  324929 ,  Sigrid Juselius Foundation ,  Fondation Leducq and Jane and Aatos Erkko Foundation , L. V. by  Orion research foundation, Paulo foundation, Aarne and Aili Turunen foundation, Alfred Kordelin foundation, Biomedicum Helsinki foundation ,  K. Albin Johansson  foundation,  Emil Aaltonen  foundation,  Maire Taponen  foundation,  Aarne Koskelo  foundation, Waldemar von Frenckell foundation, The  Finnish-Norwegian medical foundation, Paavo Ilmari Ahvenainen foundation ,  Finnish Medical Foundation ,  Paavo Nurmi foundation, The Doctoral Program in Biomedicine at the University of Helsinki.
Sequence analysis and microsatellite selection Glossina brevipalpis sequence data of the following SRA files (SRR653459, SRR653479, SRR681140 and SRR1174181) available in the SRX220378: Whole Genome Sequencing of tsetse fly project at https://www. ncbi. nlm. nih. gov/sra/ were used. In addition, more sequence data of G. brevipalpis were provided by Otto Koekemoer, Agricultural Research Council, Onderstepoort Veterinary Research, South Africa (unpublished data) and used in the analysis. The SRA files were transformed to fastq files using the command "fastq-dump [sra file name]>output file name" in Linux Ubuntu 20. 04. 4 LTS. The fastq sequence data, consisting of 26209954 reads of 200 bp length were assembled with ABYSS assembler  [53]  with the command "abyss-pe k=64 np=16 name= sample1_2 in='1_2.
fastq. gz'". The. fa files were concatenated to one file with the command "cat file1, file2, filexx>all_file". The concatenated file was screened for di-and trinucleotide motifs with a minimum of ten repeats using MSATCOMMANDER 1. 08  [23]  which also enables primer design with the integrated PRIMER3 software. The location of the extracted primers on the G. brevipalpis complete genome (https://vectorbase. org/vectorbase/app/downloads/release-59/ GbrevipalpisIAEA/fasta/data/, accessed on 8 August 2022) and in coding sequence regions (CDC) was determined using Geneious Prime software, version 2022. 2. 2. Microsatellites with dinucleotide motifs were prioritised as they showed higher levels of polymorphism compared to trinucleotide motifs in a previous study on tsetse flies  [4]. A total of 188 primer pairs were selected based on product size (180-380 bp) and the number of repeats (!13 repeats), synthesized by Eurofins Genomics (Ebersberg, Germany), and tested for microsatellite amplification with PCR.
Quality assessment of G. brevipalpis microsatellite markers Raw data reads were processed and allele calling performed in Genemapper version 6 (ThermoFisher Scientific). Allele calls were transformed into a codominant matrix displaying the microsatellite loci and their respective alleles. The genetic data were formatted for Create v. 1. 37 software  [10] , to convert the datasets into the required formats according to the software used. For Mozambique samples, individual traps were considered subpopulations, except for MOZ3, where samples from three traps, located within 50 m distance, were pooled due to the low number of samples per trap. Each of the two traps from South Africa was considered a subpopulation. Quality of data was tested with Fstat v. 2. 9. 4. [28]. Presence of linkage disequilibrium (LD) between each locus pair was checked using G-based tests with 10,000 randomisations  [29].
Measure of genetic differentiation was assessed with Wright's F ST , corrected for the presence of null alleles with the excluding null alleles (ENA) method implemented in FreeNA  [9] , and labelled F ST_FreeNA. The 95% confidence intervals with 5000 bootstraps over loci were also computed with FreeNA. For these computations, missing data were recoded as homozygotes for null alleles, i. e. 999,999, as recommended  [9]. A standardised measure, corrected for the excess of polymorphism, was obtained with F ST_FreeNA 0 = F ST_FreeNA / F ST_Fmax , where F ST_max was calculated using the software Recodedata  [42]. We computed these quantities between each pair of subsamples within the two countries and computed the averages of the means across loci and of the 95% confidence intervals. We also computed  [43] , where H T and H S are total and local genetic diversities  [45]  and n the number of subsamples.
Effective population sizes (N e ) Effective population sizes (N e )roughly the number of reproducing adults in a populationwere estimated for wild tsetse fly samples. We utilised five different methods: linkage disequilibrium  [67]  corrected for missing data  [49]  and molecular co-ancestry  [46]  as computed with NeEstimator v. 2. 1. [22] ; the heterozygote excess method recently proposed by  [15] ) N e = À(1/2F IS ) À (F IS /2(1 + F IS )) the one-and two-locus identity probabilities  [59]  with ESTIM v. 1. 2. [60] ; and Wang's sibship frequency method  [65]  with the software Colony v. 1. 0. 6. 8 (January 5, 2022)  [35]. We then computed the average N e across methods, weighted with the number of usable values (i. e. , values different from 0 or infinity).
This study provides a synthetic overview of thirty years of research devoted to urban climate change in Africa. Which cities in Africa are being researched on the impacts of climate change affecting them? What are the main social and urban issues and how are they linked? Is the development of climate services envisaged for these cities? Related to which local issues? Some answers are drawn by text mining the metadata of more than a thousand articles published in the period and recorded in the Web of Science. The evidences produced are based on the design and exploitation of a taxonomy of keywords forming a set of issues and on their articulation in a network based on their co-occurrences in the articles' metadata. Forty-eight African countries and cities are cited, Cairo, Dar es Salaam, Cape Town, Accra, Lagos, Durban, Nairobi, Addis Ababa, Kampala and Johannesburg being the cities deferring the largest number of studies.
It is also a question of identifying the areas of the continent where this work particularly focuses and any neglected areas. To do this, we use the opportunity offered by the availability of a very large number of scientific articles metadata (including titles, keywords and abstracts of publications) on the Web of Science combined with computerbased text mining, an approach required by the size of the textual corpus collected, by the possibility of future updating of the analysis and by its replicability. The data acquired and their pre-processing are described in Section Data, additional information and pre-processing. The distribution of African countries and cities that have been the subject of studies related to climate change between 1991 and 2021, as well as the main topics covered are presented in Section African city distribution and related issues.
At the city level, the various climate change issues are generally not independent of each other. One way to capture these interactions as they are conceived in research works is to establish a kind of semantic network (based on article metadata). Section Network of African cities and climate change issues sets out this analysis and offers an interpretation of the main evidence produced. A synthesis of these results is made in Section Discussion and conclusion, accompanied by a discussion. It should be noted from the outset that this study does not intend to be a bibliometric analysis of scientific productions, but rather an analysis of the theme of the links between African cities and climate change based on these productions. Data, additional information and pre-processing The analysis of scientific production linking African cities and climate change is based on data made available on the Web of Science platform (hereinafter WoS).
Web of Science and geonames data The Web of Science (WoS) online platform provides metadata for scientific articles on all contemporary research topics. When they are complete, the metadata of an article include in particular the names and affiliations of the authors, the title, year of publication, key expressions and summary of the article, the WoS categories or scientific areas concerned, and various information on the journal, book or scientific event where the article was published or presented. Performed on June 7, 2021, the search for articles using the regular expression "urb * AND clim * " collected the metadata of 24,757 articles, the oldest dating back to the 80's. The text mining of this corpus covers only the titles, key expressions and abstracts of the articles. As will be seen, authors' affiliations are used in a separate analysis.
Several other bibliometric database has been investigated  (Gaston, 2021). The largest ones brought thousands of papers (Isidore : 13,695 papers; the data base of the International Association of Urban Climate: 7,955 papers) but (1) the huge majority of them were already in the WoS data base or (2) the set of metadata was not complete enough to allow the planned information retrieval. We searched also for papers in French but only 64 of them were found on our topic in the ProQuest data base. Always with the same query used with the WoS, Dimensions  (Hook et al. , 2018)  provided 94 papers only. Finally, in order to have homogeneous set of metadata and to ease the replication of the approach, we decided to limit the corpus to WoS meta-data with no constraint put on the publication year. The analysis also requires the use of additional geographic onomastic information: country names, city names, plus words (e.
g. , demonyms, the name of peoples) and forms (e. g. , adjectival forms) derived from these names. The source of this information is the free GeoNames geographical database. The notion of "country" used by the database is geographical rather than political. Thus, for example, the island of La Réunion (French ). ProQuest LLC https://about. proquest. com/ (accessed November , ). See http://www. GeoNamess. org/ (accessed March , ). Frontiers in Sustainable Cities frontiersin. org name) in the Indian Ocean, department of France, or Antarctica, are both considered as "countries. " In order to increase the reliability of computer-based text mining (see Section Lexical information processing), adjectival forms of country names (e. g. ,: Afghanistan -> Afghan; Angola -> Angolan) as well as demonyms (e.
Issues as a taxonomy of keywords Two types of information provide an overview of the content of the research work performed over 30 years on climate change and cities: (a) the scientific disciplines involved and (b) the keywords chosen by the authors of the publications. The first shows the kinds of scientific knowledge mobilized according to their structuring in the academic field, and how collaborations are organized between disciplines to respond to the issues linking cities and climate change. WoS metadata provides direct access to this type of disciplinary mapping. The second type of information, the set of key expressions, constitutes a dense sampling of the thematic field delimited by the initial query used to constitute the textual corpus. To compensate for the extent of the pool of key expressions and its semantic dispersion, these expressions must be grouped into various classes whose labels evoke major socio-ecological or development issues.