dataesr/scientific-paragraphs-categorization huggingface dataset:
Irma, Saint-Martin, reconstruction post-catastrophe, éducation, adolescents Keywords : Irma, Saint-Martin, post-disaster recovery, education, teenagers Thèmes : Sur le Champ -Sur le Terrain AUTEURS ANNABELLE MOATTY Annabelle Moatty, amoatty@yahoo. fr, est chercheur post-doctorante ANR Tirex (ANR-18-OURA-0002) & Projet Cascira, Laboratoire de Géographie Physique (UMR 8591). Elle a récemment publié : -Barraqué B. , et Moatty A. , 2019. The French Cat' Nat' system: improving post-flood recovery but not so much resilience? Environmental Hazards [En ligne], Special Issue Financial Schemes for Flood Recovery and their Impact on Flood Resilience, p. 1747-7891. DOI: https://doi. org/ 10. 1080/17477891. 2019. 1696738 -Moatty A. , Grancher D. , Virmoux C. , Cavero J. , 2019. Bilan humain de l'ouragan Irma à Saint-Martin : la rumeur post-catastrophe comme révélateur des disparités socio-territoriales.
Mots- clés : clés Irma, Saint-Martin, reconstruction post-catastrophe, éducation, adolescents Keywords : Irma, Saint-Martin, post-disaster recovery, education, teenagers Thèmes : Sur le Champ -Sur le Terrain AUTEURS ANNABELLE MOATTY Annabelle Moatty, amoatty@yahoo. fr, est chercheur post-doctorante ANR Tirex (ANR-18-OURA-0002) & Projet Cascira, Laboratoire de Géographie Physique (UMR 8591). Elle a récemment publié : -Barraqué B. , et Moatty A. , 2019. The French Cat' Nat' system: improving post-flood recovery but not so much resilience? Environmental Hazards [En ligne], Special Issue Financial Schemes for Flood Recovery and their Impact on Flood Resilience, p. 1747-7891. DOI: https://doi. org/ 10. 1080/17477891. 2019. 1696738 -Moatty A. , Grancher D. , Virmoux C. , Cavero J. , 2019. Bilan humain de l'ouragan Irma à Saint-Martin : la rumeur post-catastrophe comme révélateur des disparités socio-territoriales.
Meta analysis The study is a meta-analysis based on data collated from isotopic C enrichment experiments conducted across the world. The data was obtained from peer-reviewed journal articles published between 1985 and 2016. The journal articles were obtained from academic databases (Google Scholar, Refseek, Science Direct, SciFinder, Scopus, Springer Link and Web of Science) using key words and phrases, singly and/or in combination, such as "isotopic pulse labelling", "C allocation", "plant carbon sequestration", "rhizodeposition" and "plants/soil/microbial respiration". The literature survey considered studies reporting the allocation of C to plant shoots and roots, soil pools and proportions of the respired C as either percentages or absolute quantities. Thirty-three journal articles (Table  1 ) detailing different studies were obtained using the above criteria providing 227 observations from different experiments, globally (Fig.
Nelson (1976: 138)  mentions similar conditions for technological variability in East Africa. In the last 20 years, new research, especially by French colleagues, has significantly enhanced the available database. This has initiated new interpretations of cultural developments during the LSA  (Bon et al. 2013; Assefa et al. 2014; Ménard et al. 2014; Pleurdeau et al. 2014). By giving a detailed description of the lithic artefacts from the DEN12-A01 rockshelter we want to enable high comparability with other LSA assemblages in the Horn of Africa. We thus focus here on the following three questions. 1. Is there a significant chronological change in technology and typology apparent in the DEN12-A01 sequence? 2. Are LSA sites from the southwestern Ethiopian highlands different from lowland sites in terms of their lithic assemblages? 3.
Only sixteen pairs of types are significantly different from each other. For further statistical testing of the typology an increase of sample size is necessary. Nevertheless, taking the other attributes like retouch into account it seems feasible to use the types for the DEN12-A01 assemblage. For this data analysis R was used (R Core Team 2018) with the packages normtest  (Gavrilov and Pusev 2014)  and rcompanion  (Mangiafico 2019). Backed tool types appearing in the DEN12-A01 assemblages are illustrated in Figure  7  and defined in Table  5.
For the Maloti-Drakensberg region a synthesis of palaeoclimatic and palaeoenvironmental data also suggests that it was a refugium for humans during unstable, arid periods  (Stewart and Mitchell 2018). For the Dendi caldera, climatic data from the local lake cores point towards a similar scenario (Figure  5 ;  Wagner et al. 2015). The second part of our discussion compares the lithic typology and technology of DEN12-A01 with other assemblages from the Horn of Africa. As a tentative impression, it seems that backed microliths were an element of most assemblages since the beginning of the early Holocene, mainly in the shape of pieces classified by us as micro-points. From this time Laas Geel is the only site in the region with numerous segments. However, the radiocarbon dates here derive from ostrich eggshell and are problematic as mentioned by  Gutherz et al.
Geometric backed microliths are abundant within Holocene LSA assemblages. In the Pleistocene Later Stone Age, they are not present. These changes might be valid for the Horn of Africa, but the database is still too weak for well-grounded conclusions. The comparison with other stone tool assemblages shows a high inter-and intra-site variability throughout the Holocene. Concerning our second research question, characteristics specific to the highlands are not visible in terms of the lithic artefacts found. The restricted range of tool types with an emphasis on micro-points and segments nevertheless points to short-term stays by small groups of hunters, as is also suggested by the fact that only wild species are present among the faunal remains recovered. Hunting trips might have been combined with other activities, such as the procurement of obsidian.
Notre terrain d'étude, la vallée du Bastan, surnommée « la vallée aux catastrophes »  (Métailié, 1993a) , a connu deux crues centennales en un peu plus d'un siècle (1897 et 2013) mais ces deux évènements se sont produit dans des contextes socio-environnementaux bien différents. L'objectif de cette étude est de coupler les méthodes géohistoriques et hydrogéomorphologiques pour identifier et comprendre l'évolution de la dynamique hydrosédimentaire depuis © Sud-Ouest Européen, n o 49, 2020 la fin du petit âge glaciaire (fin du xix e siècle) et ses facteurs de contrôle. Pour cela, les dynamiques des deux crues centennales du Bastan seront comparées sur la base de données anciennes et actuelles et mises en perspective de leurs contextes socio-environnementaux, de manière à quantifier les ajustements morpho-.
Constitution du corpus documentaire Le corpus documentaire s'est constitué à partir de photographies anciennes obliques montrant les versants soumis à une érosion superficielle, les torrents actifs, des crues majeures ou autres paysages clés de la compréhension de la dynamique hydrosédimentaire. Elles sont issues des travaux géohistoriques sur les risques naturels dans les Pyrénées et son piémont du laboratoire GEODE  (Peltier, 2005 ; Métailié, 1986 Métailié, , 1993 Métailié, et 2006 ; ; Antoine, 1992 Antoine, et 2011)) , de la base de données du laboratoire (bipt. univ-tlse2. fr), de collections mises à disposition sur internet (fonds Delcampe, fonds Campagne) et des archives départementales des Hautes-Pyrénées et de la Haute-Garonne (fond RTM). Ces archives iconographiques ont été localisées afin de mettre en place une démarche de comparaison photographique.
Pour la crue de 2013, les rapports et photographies postcrue des services de l'État et des gestionnaires, le fond photographique constitué par le laboratoire GEODE (crues-pyr2013. canalblog. com) et les orthophographies IGN ont été utilisés. Par ailleurs, les annuaires statistiques de France (gallica. bnf. fr), les bases de données de population (Ldh/EHESS/Cassini jusqu'en 1999 puis Insee à partir de 2006) et la base de données en ligne RTM ont été utilisés pour reconstituer respectivement la démographie et la fréquence des crues à l'échelle du bassin versant. De plus, l'évolution du taux de boisement du bassin versant du Bastan a été reconstruite sur trois dates  (1920, 1959 et 2012)  à partir de la « Monographie de la vallée de Barèges »  (Rondou 1900 (Rondou -1934)) , de la vectorisation des formations forestières d'après la photographie aérienne du parc naturel des Pyrénées de 1959 puis de la BD Corine Land Cover 2012.
Remerciements Cette étude a été réalisée dans le cadre du programme interdisciplinaire DYNHAPYR, financé par l'ancienne région  Midi-Pyrénées (aujourd'hui Occitanie) et l'université Toulouse -Jean Jaurès. Elle fait partie d'un travail plus large mené dans le cadre d'une thèse de l'université Toulouse -Jean Jaurès sur la torrentialité dans les Pyrénées centrales.
These data are nevertheless essential for measuring the impact of environmental changes on the functioning and sustainability of riparian forests. A dendrochronological and dendro isotopic study was carried out on trees bordering the Milo River in order to test the effectiveness of these techniques for obtaining such data. A difficulty with the use of dendrochronology in tropical environments is that few species form annual rings. Of thirteen tree species studied half form more or less distinct ring boundaries but three species showed clearly visible ring boundaries. These species are Pericopsis laxiflora, Tamarindus indica and Tectona grandis. This study shows that it is possible to estimate the age (15 to 102 years) and radial growth rates (0. 26 to 1. 39 cm/year) for species with discernible rings.
Conflits d'intérêts Les auteurs déclarent que l'étude a été réalisée sans conflit d'intérêts. In order to assess the phenotypic diversity of camels in Mauritania, body dimensions were measured on 131 adult camels brought to Nouakchott slaughterhouse from all across Mauritania. On average, body measurements (in cm) were 51. 5 ± 2. 0 (head length), 21. 5 ± 1. 5 (head width), 108. 4 ± 6. 6 (neck length), 65. 6 ± 4. 9 (neck circumference), 184. 7 ± 8. 1 (height at withers), 197. 8 ± 8. 2 (chest girth), 147. 1 ± 9. 3 (body length), and 76. 8 ± 5. 2 (thigh circumference). After cluster analysis, it was possible to identify five phenotypes ranging from animals with small body size and thin, short necks, to medium-sized animals distinguished by large limbs or heads, and to large, slender animals. Compared to data in the literature, these phenotypes appear to be very close to the breeds described in Maghreb countries and more generally to African breeds, and unlike the Asian breeds, which are taller and more productive.
Editorial: Making water smart Wherever we measure we gather data, wherever we have data we have information, and wherever we have information we have potential knowledge. However, we cannot assume that this knowledge is useful just by ensuring that we measure. The continual growth of data volume, velocity and variety has necessitated the development of tools that can assure its veracity to meet the criteria defined by its ultimate use. Where these tools provide computational functionality that are outside the abilities of a human operator, are non-routine and handle data large or complex in characteristics, we can define them as 'smart'. This and analogous terminology, such as 'intelligent' or 'cyber physical', has become ubiquitous within the data science community and has been embraced by manufacturing and processing industries as the 4th Industrial Revolution (Industry 4.
In this special issue of Water Science and Technology, 11 papers were selected that contribute to a broad discussion and demonstration of state-of-the-art for integration of digitalisation and water management processes. Therrien et al. () provide an excellent introduction to the concepts embraced in this issue, highlighting the necessary steps required to extract applicable intelligence from raw data in water resource recovery systems. Sit et al. () undertake a more focused review of contemporary deep learning techniques, which considers not only the process and challenges but governance and ethical management of data as a resource. Icke et al. () developed and tested an Artificial Intelligence approach at the Integrated Validation Plant of Singapore's National Water Agency. With a self-learning feedforward algorithm that uses load prediction and machine learning for nutrient removal control, they achieved up to 15% reduction of aeration compared with conventional feedback control.
Using long-term datasets, Jones et al. () identify benefits of using real-time sensors in small community water systems, where limited compliance monitoring can miss elevated nitrate concentrations, and large community water systems that need decision-support tools to initiate nitrate management strategies. Carriço et al. () provide an overview of the information systems used by Portuguese water utilities to collect, store and manage data and propose a possible solution for data integration from different information systems to facilitate assessment. An initial platform has been presented; however, the authors provide the caveat that scalability problems are a risk, depending on the chosen technology. Cardenes et al. () demonstrate how a hybrid linear and multi-objective optimisation approach can be used to identify key energy consumption elements in a water supply system, and evaluate the amount of investment needed to achieve significant operational gains at those points in the supply network.
Les photographies acquises sont par la suite traitées via une suite logicielle (Photoscan 21 pour la réalisation des nuages de points denses et des modèles 3D et CloudCompare 22 pour l'acquisition des données métriques). Les différentes variables métriques présentées ont ensuite fait l'objet d'une analyse multivariée (analyse en composantes principales). L'ensemble des traitements et analyses statistiques ont été réalisés avec R version 3. 6. 3 (2020-02-29) 23   21 AgiSoft PhotoScan Professional 2016. 22  CloudCompare (v. 2. 10. 1) 2019. 23 R Core Team 2020. [1] :  Harris & Beam (1983) ,  Halpenny (1995)  ; [2] :  Ledoux & Boudadi-Maligne (2015). L = longueur ; l = largeur. et des packages complémentaires suivants : dplyr 24 , FactoMineR 25 , ggplot2 26 , tidyr 27. Des données ichnométriques générales ont également été recueillies à des fins de morphologie comparative pour le léopard africain 28 , le lion africain 29 , le grand félin des cavernes 30 , l'hyène brune 31 et l'hyène des cavernes (Fosse inédit, à partir de 2 empreintes relevées sur élastomère provenant de la grotte d' Aldène ; archives L.
Materials & Methods Due to their global coverage, data from both MODIS and VGT were selected as the principal inputs for this study. To reduce potential data volume and to follow in the steps of earlier studies, vegetation indices from the 2 sensors were selected (listed in Table  1 ). These included the EVI, the fraction of green vegetation cover (FCOVER), and the Leaf Area Index (LAI). While each index serves as a proxy for photosynthetic activity, the indices differ greatly in what they are supposed to estimate. EVI is designed to "quantify the 'green' vegetation signal across a global range of vegetation conditions while minimizing canopy influences associated with intimate mixing by non-vegetation related signals"  (Huete et al. 1999). FCOVER is described as "the fraction of green vegetation covering a unit area of horizontal soil […] correspond  [ing]  to the gap fraction in the nadir direction," and "a very good candidate for substitution of classical vegetation indices"  (Camacho et al.
1999). Lastly, LAI "is defined as half the developed area of photosynthetically active elements of the vegetation per unit horizontal ground area"  (Baret & Weiss 2014). (Lillesand et al. 2007 ). However, to ensure comparability between the MODIS-and VGT-derived data, only data corresponding to the temporal overlap between the sensors was used. That corresponded to the almost 12 year period spanning July 2002 (following the launch of MODIS Aqua) through March 2014 (just prior to SPOT-5's end of mission). The data represented acquisitions from approximately 4,292 days, but which were analyzed in terms of the 141 constituent months, facilitating the handling of a large volume of data. Also, the MCD43B4 data were resampled from 500 m spatial resolution to match the, 1 km resolution of the other datasets.
Reflectance data While the VGT data was already readily available in the form of pre-processed indices (i. e. FCOVER, LAI), in the case of MODIS, the EVI data had to be derived from the raw reflectance data. Nadir BRDF-corrected reflectance estimates from MODIS (the MCD43B4 product, collection 5) for French Guiana (tile h12v08 in the MODIS reference system) were acquired for the period indicated. MCD43B4 is based on reflectance estimates from both MODIS Aqua and MODIS Terra, and the quality is considered better than products derived from only a single satellite. Data were filtered using the quality assessment-quality control (QA/QC) data from the corresponding MCD43B2 dataset, whose archive had also been acquired. Quality of the input data was assured by selection of only "best quality, full inversion" reflectance data  (Schaaf et al.
2002). Since the MCD43B4 data was available as 424 overlapping 16-day datasets (and not as monthly data), that data was 'compressed' into monthly data: (i) the 141-month archive, and (ii) a compressed 12-month archive representing mean monthly reflectances over a calendar year. For instance, in the latter case, mean September reflectance would refer to the reflectance averaged from September data for all the years analyzed  (i. e. 2002-2013). To reduce noise in the latter dataset, the monthly means were extracted by taking the minimum reflectance for each 16 day period for all spectral bands, with the exception of the near infrared band, from which the maximum reflectance was extracted to remove noise, following an approach presented in an earlier study  (Hansen et al. 2003). This was done because in most spectral bands, cloud cover and aerosols increase spectral reflectance, but in the near-infrared band, the effect is the opposite  (Jensen, 2006).
Vegetation indices EVI was extracted from the monthly MCD43B4 reflectance data using the blue, red, and near-infrared bands. MODIS LAI data were also extracted from the MCD15A2 product, an 8-day product also using observations from both MODIS instruments. For the MCD15A2 data, quality assessment flags were used to ensure the extraction of only the highest quality observations. To allow for comparison with the earlier French Guiana satellite-based phenology study, EVI data from the MOD13A2 product was also extracted, for the time-period considered  (Pennec et al. 2011 ). This study examined VI variation across 5 forest types mapped via unsupervised classification. The MOD13A2 data included here would thus be equivalent to agglomerating the VI trends from those 5 types, and is thus in essence a re-creation of the data from  Pennec et al.
(2011). Data from all sources were originally acquired at the scale of the Guiana Shield and subsequently subset to French Guiana. Additional filtering to derive monthly data was unnecessary for the VGT-derived FCOVER and LAI data, as the data already represent 30-day observations. To limit the analysis to forest, data from other vegetation types was masked out, using a forest mask derived from unsupervised classification of MCD43 reflectance data. The mask was similar to the approach used in the earlier study  (Pennec et al. 2011). Statistical analyses were done to determine (i) whether there were statistically significant differences between monthly VI estimates (using the Kruskal-Wallis multiple comparison test), and (ii) the extent to which the different VIs were correlated to each other (using the Pearson product-moment correlation coefficient).
VI variation at the scale of French Guiana Comparison of the mean monthly values for the different VIs -derived from ~12 years of data -show what appear to be distinct seasonal patterns (Figure  2 ). In general, the patterns appear more distinct for the 4 BRDF-corrected VIs shown, as compared to the single uncorrected VI shown, with the latter being essentially a reproduction from the data presented in an earlier study  (Pennec et al. 2011). The 2 MODIS-derived products (EVI and LAI) indicate that the peak of 'greenness' / vegetation vigor is in September. By comparison, the VGT-derived products (FCOVER and LAI) and the EVI estimate not corrected for BRDF, all indicate a peak in October. It is noted, however, that there are differences in magnitude between the MODIS-and VGT-derived LAI estimates.
The MODIS-derived LAI mean ranges from 4. 39 to 5. 99, while the VGT-derived LAI has a lower range, from 3. 67 to 5. Nevertheless, correlation analysis indicated that the two LAI datasets were highly correlated, with a correlation coefficient of 0. 83. The effect of the BRDF correction can also be noted by comparing the monthly variation between the BRDFuncorrected and the BRDF-corrected EVI data. For instance, the BRDF-uncorrected EVI has an overall range from 0. 43 to 0. 52, while the range of the BRDFcorrected EVI is higher, from 0. 51 to 0. 6. Additionally, the overall form of the mean 'greenness' trends for the indices differ. The variation in the BRDF-uncorrected EVI, for instance, is more or less flat between January and July, after which it starts to increase, while the BRDF-corrected EVI has peaks in both April and September, with the latter peak being larger.
FCOVER shows a distinct pattern reaching a minimum value in May and a maximum in October. Nevertheless, there is a clear correlation between the two VIs (coefficient of correlation of 0. 69). Overall, the median FCOVER values for the months of September and October are significantly higher than the wet season months (Kruskal-Wallis test; P-value < 0. 05). Similar trends are revealed in analyses of the EVI and LAI data, with the EVI data also showing September and October's median values to be significantly different overall from the wet season months. For the LAI data (from both MODIS and VGT), August, September and October have significantly higher values than the wet season months, in general (results not shown). In terms of the site-level analysis, clouds caused large data gaps in the wet season data for EVI, and VGTderived FCOVER and LAI.
Hence, the only index for which a full archive for all sites could be generated was the MODIS-derived LAI (Figure  4 ). While LAI for the 4 sites is shown to display an overall trend similar to that for all of French Guiana, the differences in trends between sites are quite pronounced, and that to (i) magnitude, (ii) greenness peaks, and (iii) overall form of the trend. For instance, in terms of the overall form of the trend, for both Montagne Plomb and Waki, the trend is steeper, suggesting a greater distinction in leaf flushing between the earlier and later parts of the year, compared to the Arawa and Kaw sites. More significantly, the timing of greenness at each of the sites is different. For example, the data indicate that for both Montagne Plomb and Kaw, the peak of greenness is in September, while for Arawa, the peak is a few months earlier, in July, and Waki has its peak greenness in October.
While there is some overlap in terms of the magnitude of LAI, overall, the ranges are distinct. For instance, in Montagne Plomb the LAI ranges from 3. 39 to 5. 35, while for Waki, LAI ranges from 3. 82 to 5. 34. The ranges of LAI for both Arawa and Kaw is overall higher than that of the other two sites, with Arawa's LAI ranging from 4. 51 to 5. 63, and Kaw's being the highest overall LAI range, from 4. 56 to 5. 76. Using Kaw as an example, it can also be seen that there is a great deal of month-to-month variance in terms of the LAI estimates (Figure  5 ). A closer examination of the LAI data indicates that Kaw's peak greenness, mainly occurred in  September (e. g. 2003 September (e. g. , 2006 September (e. g. , 2007 September (e. g. , 2008 September (e. g. , 2009 September (e. g. , 2012 September (e.