dataesr/scientific-paragraphs-categorization huggingface dataset:
d PSD shape: The size range considered in the synthetic test cases is (10 2 940) mm. Simulated crystals are sized into 93 equally spaced 10-mm-wide bins, and the number of particles per bin is prescribed by a normal probability density function of the bin midpoint multiplied by a prefactor so that there are approximately 10 000 elements in each population (or data point). The normal distribution parameters-namely, its mean m and standard deviation s-are changed from one data point to the other when generating the synthetic dataset, as detailed below.
d Lower and upper bounds: vectors whose elements are the minimum and maximum theoretical bin reference masses, respectively, found across the dataset d Average bin reference mass [m th 5 (m th,1 m th,2. m th,N )]: vector whose elements are the average of the theoretical bin reference mass (m ref,i ) calculated over the dataset Some quantitative criteria are calculated to estimate the quality of retrieved values: d Mass percent error (PE) is computed for each bin from the retrieved mass value (m i , optimization output) and m th,i : PE i (%) 5 100 m i 2 m th,i the number of bins in the PSD, indicates the accuracy of the mass retrieval process d IWC mean absolute percentage error: IWC MAPE(%) 5 100 P å P i51 jIWC cal;i 2 IWC th;i j IWC th;i , where P is the number of data points in the set, indicates the accuracy of the IWC retrieval process b.
Since 1999, like the other RMOs, EUROMET then EURAMET reached an essential position in the framework of the CIPM MRA  [19] , in particular through its contribution to the organization of regional comparisons of standards and the management of the CMCs, which are periodically submitted by the NMIs or DIs for publication in the key comparison database (KCDB) maintained at the Bureau international des poids et mesures (BIPM)  [23]. The first unfunded EUROMET research projects in the field of EM field, and in projects funded by the EU in the successive 4th and 5th Framework Programmes, showed significant success and demonstrated the power of fruitful collaboration between NMIs (see for example in quantum electrical metrology with the first two funded projects SETamp and Provolt dedicated to single electron transport (SET) devices and programmable Josephson voltage arrays, respectively).
CMC. EURAMET TC-EM maintains a substantial part of the entire CMC set. At the last count (Aug 2016), there were 2095 entries backed by 763 matrices for 28 European countries. The set is organized into 12 service categories, which are specified in the 'classification of services in electricity and magnetism'  [101]  of the BIPM database. The service categories are further divided in sub-and sub-sub-categories (nearly 200 of them). To provide a comparison, the whole CMC set from all regional organizations in all fields amounts to more than 24 000 entries. Since the signing of the MRA, the number of CMC entries continued to rise. This continuous growth is due to a number of factors: the success of the CIPM MRA within the metrology user community, and therefore the demand for more calibration services framed within the CIPM MRA; the continuous improvement in the technical capabilities of the European NMIs and therefore of the number of calibration services technically available from each NMI; the increase in the number of NMI and DI signatories of the CIPM MRA.
Acknowledgments The authors are grateful to all members of the  EURAMET TC-EM  who have taken part in the roadmapping exercises and consequently in the preparation of the strategic research agenda for EM. Special thanks to  Oriano Bottauscio ,  Mark Bieler ,  Mustafa Cetintas ,  Johannes Hoffmann ,  Bernd Ittermann ,  Thomas Kleine-Ostmann ,  Frédéric Pythoud ,  Nick Ridler , and  Alexander Zorin. The authors are also grateful to  Paula Knee ,  Impact Manager  of  MSU/EMRP  for the analysis of the output data of the EMRP JRPs in EM and to  Robert Wynands  and  Volker Wittstock  for provide the airline traceability map.
Acknowledgements The authors would like to thank the  Bavarian-French Academy Center  for a mobility aid for their French-German collaboration. Furthermore, Ph. G. would like to thank for funding by  European Union 's  Horizon 2020 research and innovation program  under grant agreement no. 712721  ( NanOQTech ),  ANR  under grant agreements no. 145-CE26-0037-01  (DISCRYS), and  Nano ' K  project  RECTUS. N. K. would like to thank the  Fonds der Chemischen Industrie for a Liebig Fellowship , the  Deutsche Foschungsgemeinschaft  ( DFG KU 3427/1-1 ) and  Prof. Fässler  for hosting our junior research group. Furthermore, we thank  Sacha Welinski  for photographs of the single crystals used in our TOC graphic and  John G. Bartholomew  for fruitful discussions.
All of the questionings raised in this dossier consider the fact that the construction of what is called "modern science" has been deeply marked by divisions and stereotypes of gender, race and ethnicity, emphasizing locations considered universal, as well as views and characteristics associated to the masculine in the methods of production of knowledge. A characteristic that is still very strong in our field of studies in Brazil is the absence of analyses of broader scope about the inter-relations of gender, science and technology and reflections about ethnic and racial issues in this scientific universe, as was identified by Luzinete Minella (2013), and which is also revealed in the article by Betina Stefanello Lima and Maria Conceição da Costa. The possibility for racial self-identification in the Currículos Lattes [an official database of academic resumes in Brazil] can be a first step in this direction.
The staggering diversity of angiosperms and their flowers has fascinated scientists for centuries. However, the quantitative distribution of floral morphological diversity (disparity) among lineages and the relative contribution of functional modules ( perianth, androecium and gynoecium) to total floral disparity have rarely been addressed. Focusing on a major angiosperm order (Ericales), we compiled a dataset of 37 floral traits scored for 381 extant species and nine fossils. We conducted morphospace analyses to explore phylogenetic, temporal and functional patterns of disparity. We found that the floral morphospace is organized as a continuous cloud in which most clades occupy distinct regions in a mosaic pattern, that disparity increases with clade size rather than age, and that fossils fall in a narrow portion of the space.
Importantly, Ericales also have a comparatively rich fossil record with a series of charcoalified flower fossils from the Late Cretaceous, the geologic period during which the angiosperms began to dominate most terrestrial ecosystems  [36, 38, 40]. As the charcoalification process preserves the three-dimensional shape of floral fossils and only leads to moderate alterations at the morphological level (e. g. shrinkage  [48] ), most of these fossil flowers are extremely well preserved and can be compared directly with their extant relatives  [8, 48]. For this study, we compiled an extensive dataset of extant and fossil ericalean species and built a floral morphospace based on 37 traits capturing the morphology of their flowers. Our first goal was to quantify patterns of morphospace occupation within and among ericalean families and suprafamilial clades.
We tested the hypothesis (i) that various suprafamilial clades do not overlap or only overlap partly in the floral morphospace. This hypothesis derives from the fact that several clades such as, for instance, the ericoid and the primuloid clade, were not considered to be closely related in pre-molecular, largely morphology-based classifications (e. g. [49] ), suggesting divergent floral morphologies. At the same time, we hypothesized (ii) that families that are supported as closely related based on comparative floral structure (such as the balsaminoid families or the polemonioid families), will occupy overlapping areas in the morphospace due to their relatively recent common ancestry. We then used our dataset to investigate (iii) whether floral disparity is coupled with clade age and/or species richness.
For species producing unisexual flowers, characters of androecium and gynoecium organs were only scored for functional organs and not for sterile organs, such as staminodes and pistillodes. Some characters, such as organ number and size, were frequently described as polymorphic in the literature. As the frequencies of these variations were rarely detailed, we choose to code the most common state, when it was documented. For instance, '(4-) 5 (-6) petals' in a description was coded '5' in our dataset. The remaining polymorphic characters (e. g. '4-6 petals') were coded as such, which represents 274 data entries (2. 2% of all data entries; electronic supplementary material, table  S2 ). As most of our analyses do not support polymorphisms, we randomly sampled a matrix (for each analysis), in which each of the rspb.
royalsocietypublishing. org Proc. R. Soc. B 284: 20170066 polymorphic cells was replaced by a value comprised of the cell range (for numerical discrete data) or by one of the possible states (for binary and categorical data). Given the low amount of polymorphic data entries, this matrix sampling had no effect on the statistics calculated nor on data visualization (data not shown). Data were entered and are stored in the online database PRO-TEUS  [54]. Each data entry, user name, source and putative notes are available in electronic supplementary material, table  S2. The detailed description of the characters and character states is given in the electronic supplementary material.
(c) Dissimilarity matrix All our analyses were performed using the software R v. 3. 0. 0 [55]. Scripts are available upon request from M. Chartier and S. Gerber. We calculated pairwise dissimilarities between taxa using the mean character difference (here noted D)  [56]. Let us have two taxa A and B described by N morphological characters. For a character i, the difference d ABi between A and B was calculated in different ways depending on the type of character: -for numerical characters, d ABi was calculated as the absolute value of the difference between the values of the character for A and B, divided by the range of the character in the dataset; -for ordered categorical characters, d ABi was calculated as the number of steps between the values of the character for A and B, divided by the maximum possible step difference for the character in the dataset; -for binary and unordered categorical characters, d ABi took the value f1g if A and B shared the same state, f0g if not; -if the value of a character was missing for A or/and B, this character was removed from the calculation of D.
(h) Comparison of the disparity of floral functional modules In our dataset, the perianth morphospace is based on 12 characters, the androecium space on 13 characters, and the gynoecium space on seven characters. Because these three morphospaces differ in character composition and in size, their respective disparities cannot satisfactorily be compared directly. We first investigated if the disparity for each of the functional modules increased with total disparity in Ericales. To do so, we performed a Mantel test, to test for a correlation between the disparity matrices (D for each taxa pair) calculated for each of the modules' character sets, respectively, and the disparity matrix calculated for the whole character set. Taxa pairs for which D could not be computed for one of the functional modules, due to missing data, were pruned from the matrices before performing the test.
To assess if the perianth, androecium and gynoecium of Ericales are more or less variable than the rest of the flower, we then compared the disparity ( D) of the whole dataset associated with the perianth ( Dper), the androecium ( Dand), and the gynoecium ( Dgyn) to the distributions of D calculated for random character sets of the same sizes (similarly to the method proposed in  [63]  for assessing the significance of the Escouffier' RV coefficient value). Using the total taxon set, each of these distributions was obtained by calculating D for 1000 matrices of respectively 12 (to be compared with the perianth), 13 (to be compared with the androecium) and seven (to be compared with the gynoecium) characters randomly sampled without replacement in the character set. Perianth, androecium and gynoecium were considered as significantly more (or less) variable than the rest of the flower if Dper, Dand and Dgyn were higher (or lower) than 97.
(i) Incorporation of floral fossils In addition to the 381 extant species, nine ericalean floral mesofossils from the Cretaceous were added: Actinocalyx bohrii (Diapensiaceae;  [64] ), Glandulocalyx upatoiensis (Actinidiaceae or rspb. royalsocietypublishing. org Proc. R. Soc. B 284: 20170066 Clethraceae;  [40] ), Parasaurauia allonensis (Actinidiaceae;  [65] ), Paleoenkianthus sayrevillensis (Ericaceae;  [37] ), Paradinandra suecica (Pentaphylacaceae, Theaceae or Actinidiaceae;  [38] ), Pentapetalum trifasciculandricus (Theaceae;  [39] ), Raritaniflora glandulosa, R. sphaerica and R. tomentosa (Ericales;  [36] ). Morphospace and partial disparity were recomputed for the dataset including these fossils.
(a) The morphospace of Ericales Our dataset contains 12 512 data entries. In total, 1927 (13. 4%) data are missing. The average percentage of missing data is 13. 4 + 10. 3 (mean + s. d. ) per taxon and 13. 4 + 12. 2 per character. The floral morphospace of Ericales is organized in a continuous cloud (figure  1c ; electronic supplementary material, interactive three-dimensional figure  S3 ). The first three principal coordinate axes of the space representation summarized 31. 5% of the original variance (15. 8%, 8. 45% and 7. 25% respectively, electronic supplementary material, figure  S3 ), the first two, 24. 2% (figure  1c ). Both three-dimensional and two-dimensional representations gave a fair approximation of the relative dissimilarity among taxa (Pearson's r ¼ 0. 79, p , 0. 001 for three axes; Pearson's r ¼ 0.
(d) Incorporation of floral fossils The nine fossils of Ericales included in our dataset group together near the centre of the morphospace (figure  1e ). Their distribution in the space overlaps with the balsaminoids, the ericoids, the Pentaphylacaceae-Sladeniaceae clade and Mitrastemonaceae (electronic supplementary material, table  S2 ) and they contribute 1. 8% to the total disparity of Ericales. Note that the percentage of missing data in the fossil dataset was 10. 51% (electronic supplementary material, table  S2 ).
(c) Linking function and disparity in the flower Our results indicate that, in Ericales, morphological variation differs considerably among the flowers' three functional modules, probably because of the different selective regimes they are submitted to. The perianth varied significantly less than the rest of the flower, as expected. Contrastingly, the androecium varied marginally more than the rest of the flower, and the gynoecium showed neither less nor more variation than the rest of the flower, although we expected it to show more variation, due to its complex organization. In our dataset, most species are characterized by actinomorphic, whorled, and pentamerous flowers (like most core eudicots  [5, 10] ). In general, the perianth is structurally less complex than the reproductive floral organs  [27]  and the characters we could code for were mostly related to organ number and arrangement (Bauplan;  [81] ).
In the perianth, these characteristics are likely spatially and functionally constrained during development and anthesis and mostly stable at higher taxonomic ranks, with one explanation being that the number of perianth organs and their arrangement depends on meristem size during early development  [10]. Stamen number, however, appears to be much less constrained, ranging from two to several hundred in our dataset (see electronic supplementary material, table  S2 ). Large stamen numbers can easily be accommodated even on a relatively small floral base as the filament bases are generally small  [7]. Polystemony (i. e. flowers with more stamens than perianth organs) has apparently evolved along several separate lineages in Ericales  [35]. In addition to the diversity in stamen numbers, ontogenetic patterns of androecium development and anthetic stamen arrangement are also particularly diverse in Ericales, including complex ring primordia with multiple stamen whorls and stamens arranged in fascicles  [82].
With the exception of early diverging angiosperms, there are probably only few other groups of angiosperms with such labile and diverse patterns of stamen numbers and arrangement as the Ericales. It seems likely that this lability in the androecium has played a major role during the evolutionary history and diversification of the Ericales and has allowed the group to explore new evolutionary paths in connection with different functional groups of pollinators. Finally, the gynoecium, with its multiple functions and complex morphogenesis, is often considered the most complex module of the flower  [7, 32]. All Ericales in our dataset were syncarpous. Syncarpy is relatively stable in angiosperms  [81]  and is believed to have many advantages  [83]. For instance, it allows for the presence of a centralized canal for pollen germination that allows a single pollen load on a stigma to potentially reach all the ovules of the same flower  [83].
g. organ number, organ arrangement), than at the level of floral construction (architecture, mechanical properties) and mode (traits like organ shape and colour). Floral mode often directly concerns interactions with pollinators and is generally highly variable, even at low taxonomic ranks  [81, 84]. Such traits could not be included in our analysis, as most of them would not have been applicable throughout the order. Our dataset is more representative of floral organization and construction, with some exceptions: the most variable characters in the perianth are the union of sepals and of petals (electronic supplementary material, figure  S5 ), typically linked to pollination, allowing for the formation of corolla tubes and a canalized access to floral rewards  [85] , channelling pollinator movements so that they touch stamens and stigmas  [77].
Acknowledgements. We thank  S. Sontag  for helping with literature search,  T. Palme  for creating the three-dimensional pdf figure,  D. Breedlove ,  P. Herendeen ,  D. L. Nickrent ,  T. Rodd  and  A. Weissenhofer  for pictures,  W. L. Crepet  and  K. C. Nixon  for the authorization to reproduce pictures, and  U. Schachner  for proofreading. We thank  A. Dellinger ,  E. Reyes ,  Y. Sta ¨dler ,  B. Kezzim ,  A. van Holt  and  L. Carrive  for data entry. In addition, we are thankful to  L. Mander  and an anonymous reviewer for their critical and helpful comments and suggestions. rspb. royalsocietypublishing. org Proc. R. Soc. B 284: 20170066.
At the same time, significant gaps remain with advancing the development of EWS for specific hazards, particularly for fastest onset hazards such as earthquakes and slowest onset hazards such as droughts and eventually climate change impacts. Most EWS exist for hydrometeorological hazards while they are generally less developed for geophysical hazards (UNISDR 2006b; UNEP 2012) such as landslides which are often triggered by hydrometeorological events. This adds to the challenges of linking these systems together to establish MHEWS. In this regard, international and regional collaboration of multiple stakeholders such as internationally-agreed strategies for data sharing, together with sustainable funding for MHEWS is critically necessary, given the transboundary nature of most natural hazards.
Risk knowledge Need for quality-controlled historical time series of extreme hazard event and disaster occurrences in terms of intensity or magnitude, location, duration, timing, impacts Risk and impact information often not or insufficiently integrated into EWS due to e. g. lack of cooperation between technical agencies responsible for collecting hazard data and stakeholders collecting vulnerability and exposure data as well as a lack of availability or access to (reliable) loss and impact information Even if risk knowledge is incorporated, often still an inadequate representation of all dimensions of vulnerability (e. g. in urban areas, future dynamics) implementation of the Sendai Framework, including with target g), using the Sendai Monitor. The currently proposed indicators (UNISDR 2016a) include the number of countries that have multi-hazard monitoring and forecasting systems, the number of people who are covered by and have access to MHEWS (per 100,000 persons), the number of local governments having a preparedness and/or evacuation plan with SOP, the number of countries that have multi-hazard national risk assessments/information available in an accessible, understandable and usable format and the number of local governments that have multi-hazard risk assessment/risk information available in an accessible, understandable and usable format for stakeholders and people.
Implementation Approach The underpinning strategy for IN-MHEWS is to utilize existing frameworks, partnerships and fora to complement current and emerging strategies for DRR, CCA, and sustainable development with enhanced early warning efforts. IN-MHEWS will also build on the experience, good practice, and achievements of States and the international community in this field (incl. IEWP and PPEW). The Network will provide policy-relevant advice to countries to strengthen the linkages between national technical agencies, providing data on hydrometeorological, geophysical, and other hazards, and national DRM agencies, statistical offices and other relevant institutions providing data on vulnerability, losses and damages. This would include, for example, greater engagement of sectoral/technical agencies, such as National Meteorological and Hydrological Services (NMHSs) or National Ministries of Health, to reinforce the paradigm shift underway from current providers of hazard forecasts and early warnings to providers of impact-based forecasts and risk-informed warnings (WMO 2015) and as more proactive players in DRM.
4 %. The achievable uncertainty of calibration is < 2 % for the two instruments, whereas for the measurements performed with the PSP and NIP it is approximately 3-5 and 1-2 %, respectively  (El-Metwally, 2004; Omran, 2000; El-Wakil et al. , 2001). The datasets of the EMA have been extensively described in  Korany et al. (2016)  and are freely available online at https://doi. pangaea. de/ 10. 1594/PANGAEA. 848804. At PSU, a pyrheliometer (EKO, model MS56) mounted on a sun tracker (EKO, model 22G) was used to measure B n , a shaded pyranometer (EKO, model MS802) to measure the diffuse component (D), and a pyranometer (LSI LASTEM, model DPA 153) to measure G. According to their certificates of calibration, the sensitivities of these instruments are 7. 711±0. 063μv/W/m 2 (± 0. 5 %), 7. 12±0. 012μv/W/m 2 (0.
Acknowledgments: This work is a contribution to the  SUSIE (SUrface Solar Irradiance in Egypt for energy production)  project (# 5404 ) co-funded by the  Science and Technology Development Fund (STDF) of Egypt  and the  French AIRD  and of the  MISRA  project funded by the  French Ministry of Foreign Affairs  (convention n°EJ  2101638786 ) and the  UAE government. The authors thank the  Egyptian Meteorological Authority (EMA)  for generously providing the solar radiation and meteorological measurements. The authors are thankful to the AERONET teams for their effort in establishing and maintaining the AERONET network, and to the  European Copernicus Programme  for establishing and maintaining the  Copernicus Atmosphere Monitoring Service (CAMS). Finally, the authors thank  NASA's Giovanni data system  (http:// giovanni.