dataesr/scientific-paragraphs-categorization huggingface dataset:
8-10); they confirm the extraordinary character of the 1302-1307 drought events. If we focus on the precipitation indices only, we get for IT (Fig. 2 ) a dense picture demonstrating a sustained, almost 24 months long dry period that is not at all represented by the PDSI values from the Old World Drought Atlas (OWDA,  Cook et al. 2015). The case of Italian OWDA data is special, as only a handful of dendrochronological series from the Alps and Calabria are available for the period in question. This nourishes previously formulated doubts about the reliability of simulated precipitation values  (Bothe et al 2019) , as the OWDA is calculated for large parts of Italy on the basis of only a few tree-ring series. The precipitation indices for FR (Fig. 3 ) are scarce, and yet they show a pronounced drought pattern in the growing seasons of 1304-06.
In regard to IT, we lack information on the continuity of this drought over the non-growing seasons (1303/04 to 1306/7). But the general tendency is fitting with available OWDA data, except for the summers of 1293 and 1311. The most interesting results are the precipitation indices for CE (Fig. 4 ). They have to be stacked, as CE covers a row of quite different sub-regions, yet the tendency is the same in all of those regions. Furthermore, they are mostly consistent with OWDA data points, and if indices seem to differ (e. g. 1291/92, 1294/95, 1305/06), they provide precipitation data on the non-growing season which is not covered by tree-rings. If we aim for a qualitative description of weather patterns, documentary data provides a clear, reliable and very dense picture (see SI 2) of meteorological conditions over the period in question.
Agricultural production in France and England From the accounting documentation of the Bresse region (Eastern France), we have reconstructed wheat and wine yields for the period 1300-1330. For each of these reconstructions, raw data of different castellanies, i. e. administrative units under the control of a steward, have been extracted and then compiled in aggregate series indexed on the year 1307. Cereal yields have been estimated from the revenue perceived on seignorial lands located in the territories of two castellanies, i. e. Jasseron and Treffort. This information is indirect, as it refers only to taxes perceived on these lands which were cultivated by tenants, and not to direct indication of cereal quantity harvested each year. Being said, if that induces a limit in the interpretation, the reliability of the reconstructed series is not to dismiss entirely.
Yet, the correlation of low PDSI values and blazes in the same years (Fig. 11 ) is very weak, if not nonexistent (r = -0,06). What is surprising, is the totally different outcome of the correlation between droughts and blazes for CE, calculated one time from the OWDA-data -with a very bad correlation -and the other time from the drought-indices based on written sources, where the correlation is much better (respectively r = -0,06 and r = 0,379). The data for blazes stayed the same in both calculations. Here, the discrepancy between the reconstruction from the OWDA on the one hand and the drought indices, on the other hand, comes into play: The OWDA (even more so the maps provided with it) shows a lot more dry periods than documentary data, that mirror mainly outstanding ones. Regarding the misleading picture the OWDA gives for Italy (in comparison with a reconstruction on the basis of written sources, see 3.
Acknowledgments We thank  Andreas Görlitz  ( Siegen ) for help with cross-correlation techniques and advice on statistical issues. Furthermore, we're grateful that we could use the unpublished climate historical collection of  Emanuela Guidoboni (Bologna)  for the Italian case studies. Finally, we are thankful for input from and discussion with colleagues from the  PAGES Working Group CRIAS , esp. Chantal Camenisch ,  Rudolf Brázdil  and  Andrea Kiss  during the October 2019 workshop of  CRIAS in Leipzig (Germany).
The most detailed records on the bee fauna of the island were compiled by Mavromoustakis in a series of eight papers that summarised his Cyprus records which included 237 currently valid species  (Mavromoustakis 1949 (Mavromoustakis ["1948 (Mavromoustakis "], 1951 (Mavromoustakis , 1952 (Mavromoustakis , 1953 (Mavromoustakis , 1954 (Mavromoustakis , 1955 (Mavromoustakis , 1957a (Mavromoustakis , 1958 (Mavromoustakis ["1957"]"] ). The first paper in the series is commonly cited according to its imprint date of 1948, but its date of publication as established for nomenclatural purposes by  Evenhuis (2003)  is  14 January 1949. Some other Mavromoustakis papers also have ICZN dates postdating their imprint dates as notes. Mavromoustakis' data included in his eight Cyprus-specific papers are currently available in an accessible online database  (Varnava and Stavrinides 2015) , which includes data on the location, month and plant species on which bees were collected.
esting variation within the taxon. In addition, collection localities are provided for all specimens from the Mavromoustakis collection. Virtually all GPS coordinates for type specimens and specimens from the Mavromoustakis collection represent the centre of the administrative region of the village / city from where samples were collected, as no GPS data were available at the time of collection. For the unpublished records, the horizontal distance (30 m) from the given decimal latitude and decimal longitude describe the smallest circle containing the whole of the location. The global distribution of each species is reported based on IUCN (2019) with additional data from  Ascher and Pickering (2018)  in cases where IUCN data did not list all continents from which a species was reported. Ascher and Pickering (2018)  data were used to include additional continents in the distribution but not to amend the distribution data at country level for continents reported in  IUCN (2019).
Megachile (Eutricharaea) rotundata (Fabricius, 1787) References. Mavromoustakis (1939b Mavromoustakis ( , 1952)). Mavromoustakis localities. Chiflicoudia marshes, Erimi, Salipes marshes near Akrotiri. Distribution. Cyprus, Widespread in Europe, Northern Africa, Western Asia (Turkey, Georgia, Azerbaijan), Central Asia, Southern Asia (Iran, Pakistan, India), Eastern Asia (China, Mongolia), Australia, New Zealand.
While the role of wild bees in pollinating agricultural crops has never been studied before on Cyprus, it is very likely that they support and enhance agricultural production, especially in areas where honeybee populations are low. Conserving wild bees requires the establishment of a monitoring program to assess the most significant pressures on their populations and to identify effective conservation practices. Climate change and/or other anthropogenic pressures including agricultural intensification and conversion of natural areas to urban fabric are prominent factors that need to be studied, but without more recent data on population trends it is almost impossible to design effective conservation practices. Many of the original locations where Mavromoustakis sampled for bees have been or are being converted into urban areas.
Acknowledgements We thank  Thomas Wood (UK) (Andrena) ,  Gerard Le Goff  (FR),  Andreas Müller  (CH) and  Christophe Praz (CH) (Megachilidae), Achik Dorchin (IL) (Eucera), Erwin Scheuchl (DE), Bogdan Tomozei (RO) (Andrena), Michael Kuhlmann (DE) (Colletes), Alain Pauly (BE) (Halictidae), Pierre Rasmont (BE) (Anthophorini) ,  Göran Holmström  (SE) and  Holger Dathe (DE) (Hylaeus) , and  Jan Smit  (NL) (Nomada), for the identification, comments, and suggestions on the species of the catalogue;  Nicolas J. Vereecken  for the photos; and we acknowledge the support of the  COST Action FA 1307 Sustainable Pollination in Europe (SUPER-B ) and the projects STEP -Status and Trends in European Pollinators ( FP7)  and  ALARM -Assessing Large-scale environmental Risks  with tested Methods (FP6). We want to acknowledge  Christian Schmid-Egger  (DE),  Martin Jenner ,  Sophie Bagshaw ,  Nick Owens (UK) ,  Elli Tzirkalli  (CY),  Stavroulla Louka  (CY), and  Yiannis Varnava  ( CY ) for their contribution in providing data and  Ong Xin Rui  for her recommendations.
The model is organized into seven components: database load, classification panel, multivariate analysis, concurrency, origin-destination, points of interest and itinerary. The model was implemented as a test case for the waste collection service of the city of Pasto in the southwest of Colombia. It is shown that the model based on visual analysis is a promising approach that should be further enhanced. The analyses are oriented in such a way that they provide practical information to the agents or experts of the service. The model is available on the site https://github. com/MerariFonseca/AVIMEU-visualanalytics-for-movement-data-in-R.
Specifically, the work is guided by the following questions. Could visual analysis, applied to movement data, be a useful approach to create a more flexible tool for different data structures and formats, to better understand the operation of an urban waste collection service? Does the visual analytic approach in movement data of an urban waste collection service allow to spatially determine the location where the service is provided in an unusual way? Could such an approach be useful in exploring relationships between abnormal waste collection behavior and the urban structure?.
Visual analytics for movement data The development of smart cities has created a suitable environment for the development of new spatial-temporal data visualization techniques in urban studies. Huang et al. (2016)  proposes a model that integrates graph modeling and visual analysis to study urban mobility patterns. The proposed model is TrajGraph and its main contribution is the introduction of a control panel to identify regions of interest. The COOC system is a model proposed by  (Kong et al. , 2019)  to explore concurrent patterns in urban mobility. The model is based on establishing regional relationships and is designed to study taxi trajectories. The limitation of the COOC system is that it requires a lot of data processing. This step is important as it would allow it to be adapted to different study contexts and types of database.
Overview of the model approach Movement databases capture and label the position of objects that are moving in space through time  (Trajcevski et al. , 2006). Thus, a movement database must have at least the variables that denote the time marker and the variables that express the spatial position of the entity at each moment in time. Additionally, in the case of solid waste the database should include the attributes relevant to the context of study, such as vehicle identification, speeds, truck capacity. The first step is to establish a data structure (Figure  1 ). Define in an abstract way the tasks to be performed by the model.
Deployment of the model The User-centered Analysis-Task driven model, called AVIMEU, presents an analysis framework organized in 7 components: database loading, classification panel, multivariate analysis, concurrency analysis, origin-destination, points of interest and itinerary analysis. The data loading component allows for a selection according to whether the data is implicit or explicit, which is a problemdependent characteristic. For example, it is related to how the data were collected and the equipment available in the company or municipality that operates the service. The model automatically classifies the variables according to their nature (categorical, quantitative, temporal or spatial). The second component of the model allows the user to modify variables, when not satisfied with the suggested automatic classification.
To analyze the movement of objects in terms of speed, spatial cluster analyses are performed to define nodes. Applying the equations, the average speeds are obtained and displayed by means of graphs with different colors and sizes. In this way, points of interest characterized by unusual speeds are determined. Finally, a panel of tracks is proposed whose objective is to visualize paths, allowing filtering by dates and geographic scales. In addition, it allows contrasting trajectories in different color codes and to add new calculated variables. The model was implemented in the statistical software R because of its ability to process complex data  (Team, 2019)  and it was complemented with the R Shiny library  (Chang et al. , 2019).
Therefore, the model is meeting the objective of detecting service situations that are not easily observable without a data-based approach. In order to explore if the visual and interactive data analysis approach can be used to compare structure of the city and behavior of trucks, a trial was conducted using data from the period 1 May to 31 May 2019. The area marked within a red rectangle in the figure  7  is interesting due to its central role in the road network. Concurrency analyses were carried out to explore if there is indeed, from the data-based perspective, concurrence in these locations, to characterize the moment in which the events occur and if there are similarities in the origin of the trajectories. The concurrency graph for case B suggests that, for the period and area of study, the trajectories of trucks with the same origin (same color) are converging mainly at 10 a.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume VI-4/W2-2020, 2020 5th International Conference on Smart Data and Smart Cities, 30 September -2 October 2020, Nice, France This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper. https://doi. org/10. 5194/isprs-annals-VI-4-W2-2020-111-2020 | © Authors 2020. CC BY 4. 0 License.
At the early stage of symbiosis and before translocation, certain Nops can be secreted upon flavonoid induction into the symbiotic area or stay in contact with rhizobial appendages  15. Some of them have been identified as putative cell-wall degrading proteins whose action could facilitate effector translocation  20. One of them, NopAA (previously named as GunA) is conserved in five Bradyrhizobium japonicum strains, as well as in Sinorhizobium fredii USDA257 and HH103 with which it shares 100% protein sequence identity  21  but not in NRG234  19, 21. The N-terminal end of NopAA contains Type III secretion signals and the C-terminal domain of NopAA has been classified in glycoside hydrolase family 12 (GH12) of the CAZY database. Recombinant NopAA from B. diazoefficiens USDA 110 was shown to have cellulase activity  22  , although it is not crucial for the nodulation process.
In Sinorhizobium fredii HH103, GunA has been shown to possess also a cellulase activity but it also plays an important role in host specificity as its inactivation differently affects symbiosis with soybean and with cowpea  23. The structure, function and regulation of T3SSs in animal-and phytopathogenic bacteria have been extensively studied in last decades but little is known about T3SSs mechanism and role in rhizobia. In order to decipher the molecular function of this Nop in symbiotic association with host-plant we started structural analysis of NopAA from Sinorhizobiun fredii USDA257 (Accession number JX135409), an ortholog of GunA in B. diazoefficiens and Sinorhizobium fredii HH103. In this study we report the enzymatic characterization and the atomic structure of NopAA, which is the first high resolution structure of a rhizobial T3E.
NopAA shows the structural basis for specific xyloglucan recognition. To provide more insight onto the interaction of NopAA with xyloglucan substrate we simulated the complex between NopAA and the substrate of BlXG12 which possesses four xylose moieties attached to the glucose units in subsites -3, -2, +1 and +2  29. This simulation revealed that NopAA can accommodate the xyloglucan in its active site (Fig. 3a, b ). Superimposition of NopAA structure with the structure of the two known structures of xyloglucanases from GH12 in complex with xyloglucan, namely the xyloglucan-specific endo-β-1,4-glucanase (XEG) from Aspergillus aculeatus in complex (PDB ID code 3VL9  30  ) and that from Bacillus licheniformis (BlXG12, PDB ID code 2JEN  29  ) showed strong similarity within their active sites.
4a ). As expected the ten SAXS ab initio envelopes computed with DAMMIF  33  (fitting the experimental data with χ 2 between 2. 35 and 2. 54) showed that NopAA is organized in two domains (Fig. 4b):  -a globular domain fitting the C-terminal xylogulanase domain of the enzyme -a disordered dynamic N-terminal domain emerging from the catalytic domain and that has been clearly identified as the secretion domain when compared with SAXS envelope obtained for NopAAΔ48 (Data not shown). The average model as well as the most typical model computed by DAMAVER are represented in Fig. 4b. To go further in the description of the secretion domain, an atomic model of NopAA was computed using AllosMod-FoXS, a software combining small-angle x-ray scattering (SAXS) data and high-resolution protein structure  34.
The protein solutions of NopAA 20 mg. ml -1 , NopAAΔ48 20 mg ml -1 alone or supplemented with cellobiose powder (Merck) were submitted to crystallization trials. Crystal suitable for further experiments were obtained only for NopAAΔ48 in the presence of cellobiose at 293 K. Crystallization information is provided in Supplementary Table  S2. Data collection and processing. For data collection NopAAΔ48/cellobiose crystals were flash-cooled in crystallization reservoir solution. X-ray diffraction experiment was conducted on the ESRF microfocus synchrotron beamline Id23-2 (Grenoble, France) at 100 K with a MarMOSAIC 225 mm CCD detector. All diffraction data were processed with XDS/XSCALE Package  37. Statistics are shown in Table  1. Structure determination and refinement. The structure of NopAAΔ48 in complex with cellobiose was determined by molecular replacement with PHASER 38 using a set of 8 superposed enzymes structures belonging to CAZY glycoside hydrolase family12 (GH12) as starting model (Chain A of PDB codes 1OA3 39 , 2JEM 29 , 2JEN  29  , 1OA4  39  , 1W2U 40 , 2NLR  41  , 4NPR (unpublished), 3VL9  30  , Supplementary Table  S2 ).
The structure of the four molecules of NopAAΔ48 present in the asymmetric unit and the addition of glucose units was manually corrected using COOT  42. The initial structure was refined with the program REFMAC5  43  and PHENIX  44. A set of 5% randomly selected reflections was set aside from refinement process to calculate the R free factors throughout the refinement. The missing parts of the protein structure as well as water molecules were built, automatically with REFMAC-ARP/wARP. Refinement statistics are presented in Table  1. Polder map  45  has been computed using PHENIX  44. enzymatic activity assays. Preliminary carboxymethylcellulose (CMC) gelose assay combined with congo-red staining were performed using the protocol described in  23. To determine the specificity of NopAAΔ48, we monitored during one hour the degradation of the following substrates: carboxymethylcellulose 4 M (CMC), mixed-linked glucan (MLG, also referred to as β-glucan from barley, which contains a ratio of 1/4 β-1,3/β-1,4 linkages), tamarind xyloglucan (Xlg), glucomannan from konjac (Glm, which contains a ratio of 3/1 mannose/ glucose units), and laminarin (Lam).
1 to 1. 2 mM as standard. The kinetic parameters were determined using a non-linear regression program (R program). Fluorophore-assisted carbohydrate electrophoresis (FACE) was also performed to confirm the activity of NopAAΔ48 on xyloglucan. The fluorophore used in this assay, 8-aminonaphthalene-1,3,6-trisulfonate (ANTS) is negatively charged and is used for both the migration and the revelation of the poly/oligosaccharides. The reaction was carried out by adding 10 µL NopAAΔ48 (2. 4 µM final) in 70 µL xyloglucan 0. 5% in acetate 30 mM, NaCl 50 mM pH 5. 5 during 4 h at 20 °C. The samples were heated to 90 °C to inactivate the enzyme and then dried under vacuum. They were resuspended with 2 µL of 150 mM 8-aminonaphthalene-1,3,6-trisulfonate (ANTS) and 2 µL NaBH 3 CN (1 M in DMSO) and incubated overnight at 37 °C.
SAXS data collection and analysis. Protein sample solution was centrifuged for 10 min at 10,000 rpm prior to X-ray analysis in order to eliminate all aggregates. SAXS experiments were conducted on the SWING beamline at Synchrotron SOLEIL (λ = 1. 033 Å). The monodispersed samples of proteins were injected onto a size exclusion column (SEC-3, 150 Å; Agilent) using an Agilent HPLC system and eluted directly into the SAXS flowthrough capillary cell at a flow rate of 0. 2 ml min -1 47. Then 50 µl of protein samples were injected for SAXS measurements. The elution buffer consisted of PBS (pH 7. 4), 150 mM NaCl, and 10% glycerol. Data reduction to absolute units, frame averaging, and subtraction were done using FOXTROT  47. All subsequent data processing, analysis, and modelling steps were carried out with programs of the ATSAS suite  48  (Fig.
4 , Table  2 ). The radius of gyration was derived by the Guinier approximation using PRIMUS  49  and the pair-distance distribution function was computed by GNOM  50. Ten ab initio models were computed from the experimental data using the program DAMMIF  33  and were averaged using DAMAVER  51  and SUPCOMB  52  to determine both common structural features and most typical shape of the protein. The program AllosMod-FoXS 34 was used to model the disordered N-terminal secretion domain of NopAA from the X-ray crystallography structure of NopAAΔ48 and SAXS data of NopAA full length. Molecular modelling. Refined structure of NopAA was used as the target in order to model the putative binding poses of xyloglucane. A genetic algorithm was used for the search step within a sphere of 10 Å centred on the carboxylate moiety of the catalytic Glu216 residue.
Acknowledgements We acknowledge the local contact for support during data collection at beamline  ID23-2 ,  ESRF  ( European Synchrotron, Grenoble, France ) and  Aurélien Thureau  for his help in using SWING beamline in SOLEIL synchrotron. We thank  Murielle Jam  from  LBI2M  for her precious help with additional enzymatic assays during the review process. We are indebted to the  Research Federation FRABio (Université de Lille ,  CNRS ,  FR 3688 ,  FRABio, Biochimie Structurale et Fonctionnelle des Assemblages Biomoléculaires ) for providing the scientific and technical environment conducive to achieving this work.
4) No. ligand atoms 35 (30. 4) Ramachandran plot (%) Favored 97. 49 outliers 0. 68 RMSD from ideal values Bond distances (Å) 0. 016 Bond angle (°) 1. 19 Ligand occupancy Glucose (chain A) 0. 3 Cellobiose (chain D) 0. 3 PDB code 6SDU collection and refinement statistics for NopAAΔ48/cellobiose complex (Values in parentheses are for the highest resolution shell (2. 47-2. 36 Å)).
Herschel 70 µm Resolved 70 µm data from Herschel observed as part of the HOBYS survey were used. The final images were obtained using procedures from the HOBYS team (F. Motte, private communication), and details of the reduction process can be found in  Schneider et al. (2016). These data were taken with the Photodetector Array Camera and Spectrometer (PACS  Poglitsch et al. 2010)  in the parallel mode of the telescope at a scan speed of 20 arcsec s -1. This speed produces a more symmetrical PSF (6. 51 × 5. 44) with fewer artefacts than data scanned at 60 arcsec s -1 , which has a 12. 58 × 5. 85 PSF  (Lutz 2012; Olguin et al. 2015). A zoom on AFGL 2591 is shown in Fig. 1  and provides the highest resolution in the far-IR to date. Table  1  lists the observed size of the 70 µm emission as obtained from a 2-D Gaussian fit to the data, which shows that the source is well resolved by Herschel and that the Gaussian position angle is also close to the E-W outflow direction.