dataesr/scientific-paragraphs-categorization huggingface dataset:
Cloud particle measurements The Small Ice Detector Mark 3 (SID-3) records the spatial distribution of forward-scattered light from single cloud particles as 2-D scattering patterns  (Hirst et al. , 2001; Vochezer et al. , 2016). The SID-3 allows deriving the cloud particle number size distribution and the resulting number concentration (NDro) and diameter (DDro) in the 5 -45 µm diameter range (https://doi. org/10. 1594/PANGAEA. 900261;  Schnaiter and Järvinen, 2019b). In the present work, this range was reduced to 10 -45 µm. The liquid water content (LWC) was calculated from the size distribution assuming droplet sphericity and a water density of 1 g cm -3. LWC derived from SID-3 was then compared with the bulk LWC measured by a standard Nevzorov heated wire probe assuming a collection efficiency of 100%  (Korolev et al.
, 1998). For the majority of clouds presented in this study, the LWC derived from the SID-3 data agreed with the LWC measured from the Nevzorov probe well within 10% (NIce) was calculated according to circularity as in  Crosier et al. (2011). The ice water content (IWC) was calculated with the mass-diameter relationship defined by  Brown and Francis (1995). The mass fraction of ice water (IWF) was calculated as the ratio of IWC over the total water content (TWC). The latter was calculated as the sum of IWC measured by the CIP and LWC measured by the SID-3. It must be noted that the size detection range of the SID-3 and CIP did not overlap. The Airborne Mobile Aerosol Lidar (AMALi) system installed on board of Polar 5 was used to derive the cloud top height. Previous works provide technical details on the operation principle  (Stachlewska, 2005) , data processing for noise reduction  (Stachlewska et al.
, 2010)  and Arctic airborne deployment  (Nakoudi et al. , 2020). Briefly, the AMALi is a backscatter multichannel lidar covering the UV (1 unpolarized channel) and visible region (1 perpendicular and 1 parallel polarized channel). Downward probing of the atmosphere allowed identifying clouds below the aircraft from the attenuated backscatter coefficients in the 532 nm parallel channel. Cloud conditions were defined for backscattering coefficients 5 times higher than cloud-free sections. Cloud top height with a 10 seconds time resolution are available on PANGAEA database (https: //doi. org/10. 1594/PANGAEA. 899962;  Neuber et al. , 2019). We will solely discuss the cloud top height data acquired during collocated flights of Polar 5 with Polar 6 occurred on 27-29 June and 02-05-08-13-17 June.
Aerosol particle measurements All aerosol particle data presented in this work were acquired with online single-particle instruments description of calibration standards and procedure is given by  Moteki and Kondo (2010) ,  Gysel et al. (2011)  and  Laborde et al. (2012). By laser-induced incandescence, the SP2 is capable of quantifying the mass of absorbing and refractory material contained in aerosol particles passing through the high-intensity continuous-wave, intra-cavity laser beam at a wavelength of 1064 nm  (Stephens et al. , 2003). The incandescence light detector was calibrated with a fullerene soot standard from Alfa Aesar (stock no. 40971, lot no. FS12S011), size selected with a differential mobility analyser (SMPS; TSI, Shoreview, MN, USA). The SP2 installed on the Polar 6 provided the number concentration (NrBC), mass concentration (MrBC) and size distribution of rBC particles in the 0.
50 + 0i) while the refractive index of rBC cores was set to be 1. 90+0. 8i. This value, being lower than previous Arctic studies (2. 26 + 1. 26i;  Raatikainen et al. , 2015; Kodros et al. , 2018; Zanatta et al. , 2018)  and higher than measurements in continental Europe (1. 75 + 0. 43i;  Yuan et al. , 2021) , allowed the mass equivalent diameter of rBC core to match its optical diameter. The coating thickness was quantified for rBC particles having a DrBC between 200 nm and 300 nm. It must be noted that the scattering detector failed on 07 June 2017; hence no LEO-fit analysis was performed on the following flights. rBC data acquired with the SP2 are publicly available at https://doi. pangaea. de/10. 1594/PANGAEA. 899937 with the temporal resolution of 3s  (Zanatta and Herber, 2019b). The Ultra High Sensitivity Aerosol Spectrometer (UHSAS; DMT, Longmont, CO, USA) measured the number concentration (NAP) and size distribution of aerosol particles in the optical diameters range of 60-1000 nm  (Cai et al.
Acknowledgements The authors thank  Christof Lupkes  ( Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar-und Meeresforschung (AWI), Bremerhaven, Germany ) and and  Roland Neuber  ( 1  Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar-und Meeresforschung   (AWI), Potsdam, Germany ) for the valuable technical and scientific discussion. Financial support We gratefully acknowledge the funding by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation )project  ID 268020496 -TRR 172 , within the  Transregional Collaborative Research Center "ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC )3". Marco Zanatta  acknowledges funding by the  Deutsche Forschungsgemeinschaft (DFG ,  German Research Foundation , grant no. Projektnummer 457895178 ).
( Figure S 1). Considering the good agreement with the LWC measured with the Nevzorov probe and the low concentration of ice crystals, all the cloud particles detected by the SID-3 were considered to be liquid droplets. Although not extensively presented here, LWC data derived from the Nevzorov instrument are accessible at PANGAEA (https://doi. org/10. 1594/PANGAEA. 906658; Chechin, 2019). The Cloud Imaging Probe (CIP, DMT, Longmont, CO, USA; Baumgardner et al. , 2001) is based on the acquisition of twodimensional black and white images of particles via the linear array technique which allows quantifying the dimension and shape of cloud particles. Due to the large uncertainties in the probe's sensitive area for the smallest particle sizes, the nominal detection size range was reduced in the present work to 75 -1550 µm.
The statistical significance of NrBC-res and DrBC-res vertical trend was verified with T-test analysis. T-test was applied to sub-datasets representing adjacent vertical layers, from the bottom to the top of the cloud. The hypothesis of equal averages, for both number concentration and diameter of rBC particles is respected only for the first two layers (Zn below 0. 4), indicating that no trend was statistically significant across the two lowermost cloud layers. Otherwise, the layer-by-layer difference was statistically significant for the upper cloud layers (Zn above 0. 4). Hence, the rBC residual population appeared to be significantly different, at least, at cloud bottom and cloud top. These results show a very defined stratification of cloud phase and properties of rBC residuals, with a dominant liquid phase and smaller rBC residuals at cloud top and enriched ice phase and larger rBC residuals at cloud bottom.
Study cases Three vegetation canopies (Fig. 3 ) are studied. 1) Homogeneous turbid scene: 1 m high, LAI = 1, spherical LAD, nadir observation and solar direction (θ s = 30 • , ϕ s = 225 • ). 2) Maize crop field: 7. 5 m × 5 m scene, 600 maize plants, 0 • -180 • oriented rows and 40 cm spaced, 15 cm within row plant distance, LAI = 1. 9, three viewing directions (nadir; Tree plot: 10 m × 10 m scene, 10 randomly distributed trees with branch and trunk reflectance from the DART spectral database ("populus_-tremuloides_bran"), LAI = 1. 9, nadir viewing direction and (θ s = 30 • , ϕ s = 225 • ). Simulations are over [400-850 nm] with 451 bands (Δλ = 1 nm) for the homogeneous site and maize field, and 45 bands (Δλ = 10 nm) for the tree plot. Atmosphere (gas model: USSTD76, aerosol model: RURALV23), leaf biochemistry and structure (Table  1 ), and ground reflectance "loam_gravelly_brown_dark" from the DART database.
Study sites In 2011-2012, we selected 53 plantations in the Massif Central (stand elevation varied between 547 and 1552 m, Table  1 , Fig. 2 ). They were 6 to 25 years-old and distant from at least two kilometers from each other. In these young plantations, thinning less than 5 years old was only observed in four plots  (#12619, 12645, 12718, 12723). We included in this study as controls four additional stands corresponding to older plantations (48 to 126 years old) unaffected by the 1982 storm. We collected site and plantations descriptors (age, altitude, height of dominant trees, density, topography, site humidity; Table  4  in Appendix). We scored site atmospheric humidity indirectly using data on tree density, site topography and environment. We attributed a score of zero to all sites where air circulation between trees is sufficient to impede accumulation of humidity (e.
Acknowledgements We thank  Luc Pâques  ( INRAE ) for fruitful discussions on larch tree provenances,  Johan Cros  and the correspondent-observers of " Département de la Santé des Forêts ,  Ministère de l' Agriculture et de la Souveraineté Alimentaire"  for forest epidemiological surveys and  Thierry Belouard Département de la Santé des Forêts ,  Ministère de l' Agriculture et de la Souveraineté Alimentaire ) for drawing Fig. 2. Genotyping was conducted at the  Genome Transcriptome Facility of Bordeaux.
Asteroids The asteroid spectra used here are compiled from various online repositories and publications (refer to Appendix A). The compilation and dataset are described in detail in  Mahlke et al. (2022). From this dataset, we select visible-near-infrared (VisNIR) spectra from 0. 45 to 2. 45 µm of asteroids classified as K-types and A94, page 2 of 13 L-types in  Mahlke et al. (2022, meaning  that the probability to be K-or L-type is larger than any other class probability) as well as of confirmed Barbarian asteroids following the census presented in  Devogèle et al. (2018). The Barbarian asteroids are not necessarily classified as K-or L-types in  Mahlke et al. (2022) , as is the case for S-type (980) Anacostia. Spectra with low signal-to-noise ratio in particular towards the near-infrared (NIR) are rejected following visual inspection.
Meteorites A total of 41 reflectance spectra of 40 individual chondrites are analysed in this study, including 15 CO and 24 CV spectra, the latter of which are divided into 10 CV OxA , 8 CV OxB , and 6 CV Red , as shown in Fig. 2. The majority of the spectra were presented in  Eschrig et al. (2019a Eschrig et al. ( ,b, 2021) )  and are available online in the SSHADE database (Schmitt et al. 2018) 2,3. We further add one spectrum for each of the CV OxA chondrites Allende and Y-86751 from the RELAB database  (Pieters & Hiroi 2004 , respective specimen IDs: MT-TJM-071 and MP-TXH-009). These spectra are used in  Sunshine et al. (2008)  and  Devogèle et al. (2018)  to study the mineralogical abundances of L-type asteroids and therefore allow us to compare our results to those studies. We do not add more spectra from RELAB as we aim for consistent sample treatment and measurement conditions for the meteorite spectra in order to reduce the spectral variability introduced by changes in observation geometry and sample properties such as the grain size  (Cloutis et al.
Possible Barbarians Based on the spectral similarities between CV OxA chondrites and Barbarian asteroids, it may be worthwhile investigating the Barbarian nature of the remaining four asteroids that show significant similarities to the chondrites, which are the K-types (1903) Adzhimushkaj, (2957) Tatsuo, (3028) Zhangguoxi, and L-type (4917) Yurilvovia. To our knowledge, no polarimetric phase curves have been observed for these targets. We recommend prioritising them in order to confirm or rule out their Barbarian nature. A larger comparison of K-types and CK chondrites using a consistent meteorite dataset could strengthen this link.
Acknowledgements. The authors thank the referee  Julia de León  for the thorough and constructive review which improved the manuscript. The authors further thank  Cateline Lantz  for providing the data of the irradiation experiments. MM acknowledges funding from the  European Space Agency  in the framework of the  Network Partnering Initiative. The view expressed in this publication can in no way be taken to reflect the official opinion of the  European Space Agency. Parts of this work have been funded by the  ERC  grant  SOLARYS ERC-CoG2017-771691. All (or part) of the data utilised in this publication were obtained and made available by the  MITHNEOS MIT-Hawaii Near-Earth   Object Spectroscopic Survey. The IRTF is operated by the  University of Hawaii  under contract  80HQTR19D0030  with the  National Aeronautics and Space Administration.
As mentioned earlier, at the surface of mature flavivirus particles, E is always dimeric at neutral pH. We found that YFV sE makes a similar head-to-tail dimer only under a The fit of the ITC raw data yields the change in enthalpy upon binding and the dissociation constant. G is calculated as RTln(K D ), -TS is calculated as G minus H. N is the stoichiometry of the reaction and C is the ratio of the ligand concentration and the dissociation constant  (24). Errors are fitting errors given by the Microcal Origin software (Microcal software, Northampton, MA, USA) for ITC and by the Biacore T200 software. crystallization conditions (which require a very high protein concentration), as observed for sE of DENV and JEV  (22, 28, 29). In the case of DENV, we had previously identified a cysteine mutation (at position 259 in sE from DENV1, 2, and 4, and position 257 in DENV3) that locks the protein as a head-to-tail dimer as on mature virions  (30).
Structural analysis The polar contacts in Table  S2 , the accessible surface area (ASA) and the buried surface area (BSA) in Table  S3 , were computed with the "Protein interfaces, surfaces, and assemblies" server PDBePISA (37) (http://www. ebi. ac. uk/pdbe/prot_int/pistart. html). The multiple sequence alignments in Fig. 1  were calculated using DALI (http:// ekhidna2. biocenter. helsinki. fi/dali)  (38)  and displayed with ESPript (http://espript. ibcp. fr). The figures of the structures were prepared using the PyMOL molecular graphics system (Schrodinger) (pymol. sourceforge. net). Electrostatic surfaces were computed using APBS, PDB2PQR, and PROPKA softwares via the server (39) (https://server. poisson boltzmann. org).
ACKNOWLEDGMENTS We thank the staff at beamlines PX1 and PX2 at  SOLEIL synchrotron (St. Aubin, France ) and at PX beamlines at the  ESRF (Grenoble, France) ;  Franz X. Heinz  and  Karin Stiasny  from  Center for Virology, Medical University of Vienna, Austria , for the gift of DENV pr protein and the plasmid for the production of ZIKV PF13 sE protein;  Fabrice Agou  from the  Chemogenomic and Biological Screening platform at Institut Pasteur , where the MALS experiments were conducted with the help of  Alix Boucharlat ;  Pablo Guardado-Calvo  and  Ignacio Fernandez  from the  Rey lab  for helping with the MALS experiments; and  Alexander Rouvinski  for help with the setting of the fusion experiments. We acknowl edge the help of  Sylviane Hoos  from the  Molecular Biophysics platform of IP  for help with the ITC experiments.
The authors are grateful to the staff of the  Institut Pasteur Crystallography platform  for robot-driven crystallization screening. This work was supported by the  French ANR (Agence Nationale de la Recherche)  to FAR, grants  ANR-17-CE15-0031-01 FLAVIMMUNITY  to GBS, and by the  Argentinian National Agency for the Promotion of Research, Technological Development and Innovation  grant  PICT-PRH-2019-0017  to MD. The authors declare no competing interests.
DATA AVAILABILITY Coordinates and structure factor amplitudes for YFV strain Asibi pr/sE and sE dimer have been deposited in the Protein Data Bank, respectively, under the accession numbers 6EPK and 8OFN. The accession numbers are as follows: tick-borne encephalitis virus (TBEV, strain Neudoerfl), GenBank accession number U27495; dengue virus type (DENV2, strain 16681), GenBank accession number M19197; and yellow fever virus (YFV, strain Asibi), GenBank accession number AY640589.
The methodology combines urban material flow analysis with multi-regional input-output database to extend the urban metabolism beyond the administrative boundaries of cities. We then calculated the absolute and per capita material footprints of the two cities and its material disaggregation. We compared these results with domestic material consumption. Further analysis of the urban material footprint was performed by spatializing the flows in the global economy to understand the extent of consumption due to cities. The results show that on average the material footprint is 2. 4 times larger than the domestic material consumption in Gothenburg and 1. 9 times larger in Nantes-Saint-Nazaire. A decoupling between material footprint and domestic material consumption can be observed, as the material footprints grew much faster than the domestic material consumption.
, 2015; Pincetl, 2012; Zhang et al. , 2017)  and less on other types of cities, and very rarely with MF indicators. For this study, we chose the specific case of port cities, as we have previously shown that they form nodes in the metabolic relations with their hinterlands  (Bahers et al. , 2020) , hinterlands being spaces from which resources (mineral, organic, energy) are extracted to be ultimately consumed in the city  (Billen et al. , 2012; Krausmann, 2013). To be able to quantify the DMC and MF for the cities, we developed a methodology that consisted in combining an urban material flow analysis with a multi-regional input-output database to extend the quantification beyond the administrative boundaries of cities, which has never been done on the urban scale. By understanding the relationship between the material flows of cities and the material footprints connected to them, we question the externalization and the outsourcing of the metabolism of cities.
Method: from urban material flows analysis to material footprints We chose to combine two methodological approaches for measuring the material footprint of cities. Our aim was to combine the data obtained through an urban material flows analysis with the data contained in a multi-region input-output database, in order to extend the urban metabolism beyond the administrative boundaries of cities. When accounting for materials, we therefore want to explicitly include indirect flows linked to the materials and energy (from extraction, distribution, manufacturing) necessary for import and export  (Athanassiadis et al. , 2016; Eisenmenger et al. , 2016; Lutter et al. , 2016; Schaffartzik et al. , 2014a). Integrating material footprint data leads us to produce critical indicators that go further than methodological cityism  (Wachsmuth, 2012).
Transforming domestic material consumption into a material footprint To be able to capture indirect flows, we need to incorporate in the DMC of cities all the resources used to enable them. We therefore also calculated the raw material consumption (RMC) that corresponds to the material footprint of consumption  (Eisenmenger et al. , 2016; Fischer--Kowalski et al. , 2011; Schaffartzik et al. , 2014a). This indicator takes indirect flows of imports and exports into account, making it "a consumption-based indicator of resource use"  (Wiedmann et al. , 2015). It highlights the material effort beyond the city limits. This indicator reveals the materiality of goods to be allocated to the consumer. We chose the EORA database, a multi-region input-output database containing data from 1970 with indicators that evolve over time  (Schandl et al.
, 2018). We preferred this database to the Input-Output tables from Eurostat  (Zhang et al. , 2014) , since the Eurostat dataset only starts in 2008, and to the Wuppertal Institute Coefficient approach  (Bahers et al. , 2019)  since the Wuppertal dataset is static  (Lutter et al. , 2016). The EORA database has been used many times in very robust studies for different purposes  (Giljum et al. , 2019; Schandl et al. , 2018; Wiedmann et al. , 2015 Wiedmann et al. , , 2020) )  and has also been used by the International Resource Panel  (IRP, 2019). The EORA database is calculated at the level of nations. We therefore calculated coefficients calculated using the raw trade balance (RTB), which corresponds to imports in raw material equivalent minus the exports in raw material equivalent  (Eurostat, 2018) , already used in other studies  (Cahen-Fourot and Magalhães, 2020; Magalhães et al.
Spatial analysis of the material footprints We performed a further analysis of the flows of materials related to material footprints by spatializing world flows. This made it possible to understand the extent of outsourcing of consumption due to cities. For this analysis, we used the category non-metallic minerals. The import data used came from Eurostat and concerned imports via the two ports in 2017  (Eurostat, 2019). We linked these data with the Comtrade trade database ("UN Comtrade: International Trade Statistics," 2022) between countries. In addition, we chose two materials within the category of non-metallic minerals: cement and sand. These two materials are among the most important by weight and enable a more detailed analysis. We consequently identified not only the main import flows of cement and sand, but also indirect flows of sand that feed the countries that export cement (because sand is one of the main components of cement).
In Gothenburg, the increase in DMC was slight, whereas the increase  in the MF was very large. The DMC started at 4. 9 million tons in 1996 and ended at 11 million tons in 2011. At its lowest point in 1996, the MF was 13. 8 million tons, while at its last and highest point in 2011, it was 23. 8 million tons. The question then is, what happened after 2011? According to national indicators (from the EORA database), the DMC in Sweden remained stable while the MF continued to increase strongly. This therefore points to a case of a very high externalization of the metabolism explained by the increasing supply from outside the Gothenburg borders. Thus, the supply from international sources represents twice the supply from national sources (the rest of Sweden) (averaged over the period) (cf. Table  1 ).
It would be interesting to extend this analysis by identifying the environmental conflicts related to the extraction of this material around the world. The EJAtlas database 7  could be used for this purpose (Martinez-Alier, 2021). However, we currently lack the data needed to connect countries of origin with extractive companies. This would make it possible to identify links with the conflicts listed in the EJAtlas but would require a dedicated investigation like the study of the supply chains of corporations  (Goldstein and Newell, 2019, 2020)  to identify the companies listed in the conflicts as exporting materials to Gothenburg and Nantes-Saint-Nazaire.
Species distributions We extracted species distribution data from the International Union for Conservation of Nature (IUCN)  55  for amphibians, mammals and reptiles, and from Birdlife 56 for birds. We only kept records of species where presence was defined as extant, possibly extinct or extinct; origin as native or reintroduced and seasonality as resident or breeding season. For species without a direct match between phylogeny and occurrence data, we used the R package taxize to look up synonyms in the Integrated Taxonomic Information System (ITIS; functions get_tsn it isitis_getrecord, package taxize v0. 9. 99 (refs. 57,58)). In addition, we used the function synonymMatch (package rangeBuilder v1. 5 (ref. 59)), which looks up synonyms in AmphibiaWeb  60  , the reptile database  61  , the BirdLife Taxonomic Checklist (v8.