dataesr/scientific-paragraphs-categorization huggingface dataset:
3 and balancing all reactions for mass and charge accordingly. The curation of small molecule data is an integral part of the Rhea curation workflow, and Rhea curators have submitted thousands of new compounds to ChEBI during its development. Each set of reaction participants is associated to four potential directions: left to right (LR, =>), right to left (RL, <= ), bidirectional (BI, <=>) and undefined (UN, <?>), each with its own unique reaction identifier. Rhea reactions can be used to annotate the preferred direction ( =>, <= , <=>) of experimentally characterized enzymatic reactions in knowledgebases, to describe metabolic networks and derived models where reaction fluxes are not defined a priori (<?>), and to link knowledgebases and models. Knowledgebases that use Rhea for the annotation of enzyme and metabolite data include the SwissLipids knowledgebase for lipid biology  (7) , the EBI Enzyme portal (8), the Metabo-Lights repository of metabolomics data  (9)  and IntEnz  (5).
Rhea reaction classification The EC uses a hierarchy of exactly four levels to classify enzyme activities according to a single representative reaction (referred to hereafter as the 'representative reaction of the IUBMB'). Rhea (like other reaction databases) aims to provide complete coverage of all representative reactions of the IUBMB as well as other additional reactions described in the literature (whether or not these are related to an EC number). To improve the annotation and classification of enzyme functions using Rhea we recently introduced a simple hierarchical reaction classification that covers representative reactions of the IUBMB as well as these additional reactions. This reaction classification uses 'is a' relationships to link 'child' reactions to their (more generic) 'parent' reactions, and allows any number of levels in order to facilitate the classification of extant and ancestral enzyme functions in ways that are meaningful to biologists.
Rhea website Since our last publication we have developed and deployed a new website at http://www. rhea-db. org. This website provides the same options for interactive and programmatic access as the previous version  (1). Users can search for reaction and compound identifiers and names, EC numbers, UniProtKB/Swiss-Prot accession numbers, bibliographic citations and identifiers from external cross-referenced resources at http://www. rhea-db. org/advancedsearch. Reaction data can be downloaded in BioPax2  (24) , RXN and RD  (25)  formats at http://www. rhea-db. org/download, which also provides access to the newly introduced reaction relations (described above) in tab-delimited form. Individual reactions can be bookmarked by adding the required identifier to the URL template http://www. rheadb.
ACKNOWLEDGEMENTS The authors would like to thank  Jerven Bolleman  and  Sebastien Gehant  of the Swiss-Prot group of SIB for stimulating discussions on many areas of development including RDF and database design and  Simone Badoer  of the Web Production team of  EMBL-EBI  for invaluable technical assistance. We would also like to thank the  Cheminformatics  and  Metabolism Team  at the  European Bioinformatics Institute  for their invaluable work in maintaining and developing ChEBI. We gratefully acknowledge the software contributions of ChemAxon [https://www. chemaxon. com/products/marvin/].
These difficulties may be overcome through the combined use of observations and deposition parameterizations in observation-based box models  (Vayenas et al. , 2005). As these models cannot integrate the whole complexity at stake in the atmosphere, CTMs are still needed to assess the nitrate formation regime and the PM response to precursors changes, but they require in turn validation by experimental data. This paper aims at investigating the variability and sources of both HNO 3 and NH 3 , as well as the associated NH 4 NO 3 formation regime in the Paris megacity and the ability of the CHIMERE regional CTM to reproduce it. To this end, an important experimental effort, in the framework of the PARTIC-ULES and FRANCIPOL projects, has recently made available a large database of fine aerosol chemical compounds (e.
Model configuration As shown in Fig. 1 , three nested domains are used for all simulations -a large (LAR), a medium (MED), and a fine (FIN) domain -with horizontal resolutions increasing from 0. 5 × 0. 5 • (roughly 50 × 50 km), 9 × 9 km and 3 × 3 km, respectively. A discretization of eight levels, from 40 m to 5 km a. g. l. , is applied on the vertical dimension. Meteorological inputs are provided by PSU/NCAR MM5 simulations  (Dudhia, 1993)  using boundary conditions and large-scale data coming from the Final Analyses (FNL) data from the National Centers for Environmental Prediction (NCEP) (http://rda. ucar. edu/datasets/ds083. 2). Gaseous and aerosol emissions in all domains come from the so-called TNO-MP (MP for MegaPoli) inventory. De-   (Hansen et al. , 2000)  and apportioned according to the type of land use  (Menut et al.
Uncertainties associated with thermodynamic equilibrium Bias and RMSE are much lower for TNO 3 (NMB of +71 %, NRMSE of 121 %) than for HNO 3 , because the CHIMERE model overestimates the HNO 3 / TNO 3 fraction (on average 68 % for the model against 51 % observed from experimental data during the period with available observations of NO - 3 and HNO 3 ). Partitioning errors may derive from uncertainties in the ISORROPIA thermodynamic model (e. g. , model formulation, chemical compounds included, activity coefficients treatment) or in its input data. Apart from CHIMERE, the ISORROPIA model is used in many other CTMs, including LOTOS-EUROS  (Schaap et al. , 2008) , REM-CALGRID  (Stern, 2003) , CAMx, FARM, or CMAQ. It has been validated in various studies based on comparisons with observations  (Moya et al.
This condition is defined as  (Ansari and Pandis, 1998)    with K being the equilibrium constant that depends on various parameters, including temperature and RH. It is obvious here that the errors in TNO 3 and TNH 3 can partly compensate each other. On average, the left-hand term is 3. 6 and 2. 5 ppb 2 based on observations and simulation, respectively, which corresponds to a NMB of -31 %, thus much lower than the NMB affecting the different species (+71, -56 and +48 % for TNO 3 , TNH 3 , and TS). This result thus suggests that the formation of nitrates is slightly less thermodynamically favored in the model than in the reality, which would be consistent with a moderate negative bias in nitrates. Due to possible artifacts, our data set does not allow a complete assessment of the nitrate formation.
4. 3. 2) by a too slow NO x -to-HNO 3 conversion rate compared to the efficient dispersive conditions. In the CHIMERE model, the negative bias for TNH 3 and the positive biases for TNO 3 and SO 2- 4 result in a significant underestimation of modeled GR. On average, the model simulates a GR slightly above unity (1. 2). Daily values continuously alternate between the NH 3 -rich and NH 3 -poor regimes with 48 % of simulated daily values remaining below unity (47 % considering the whole data set). The diurnal profile given by CHIMERE indicates that the GR regime changes within a single day, the lowest GR values (below 1) being simulated at 12:00 UTC (between the maximum TNO 3 occurring at 08:00 UTC and the minimum TNH 3 simulated at 15:00 UTC). Therefore, due to significant errors in gaseous precursors (and to a lesser extent in sulfate), the CHIMERE model fails half of time at correctly simulating the HNO 3limited regime for nitrate formation in Paris on a daily basis.
Chem. Phys. , 16, 10419-10440, 2016 suggest that agricultural activities are a major driver of the NH 3 day-to-day variability within the Paris megacity. Rather low HNO 3 concentrations were measured (below 1. 5 ppb on daily average), despite the large amounts of gas precursors (NO x ) emitted by the traffic in the city of Paris. Some elevated HNO 3 episodes were observed during anticyclonic conditions (high temperature, low-to-moderate wind) and suggest a substantial local formation from the NO x emitted within Paris. However, our data set does not allow quantitatively assessing the relative contributions of this local formation as compared to imports. These experimental results lead to a NH 3 -rich regime in the Paris urban environment (as indicated by high GR values), as already observed in previous studies over Europe but only in rural areas (i.
e. , closer to agricultural activities). However, sensitivity tests with the ISOR-ROPIA thermodynamic model indicate that, in the specific environment of Paris (in terms of RH, temperature and inorganic compounds concentrations), the NO - 3 formation remains equally influenced by decreases of TNH 3 and TNO 3. Considering the size of the Paris megacity and the intensity of NO x emissions, one would have primarily expected higher HNO 3 and lower NH 3 in the Paris center. This work thus sheds a new light on the topical debate relative to the respective responsibility of traffic and agriculture in the formation of NH 4 NO 3 , by highlighting substantial amounts of agricultural NH 3 and relatively low concentrations of HNO 3 in the city. This detailed experimental data set has also offered the opportunity to evaluate for the first time the ability of the CHIMERE chemistry-transport model to simulate the NH 3 -HNO 3 -NO - 3 system.
Acknowledgements. This work is funded by a  PhD DIM (domaine d'intérêt majeur) grant  from the  Île-de-France region. The  PARTICULES  project has been funded by the  French state , the  Île-de-France region , and the city of Paris. The FRANCIPOL projet has received funding from  PRIMEQUAL ,  CNRS ,  CEA , the  Île-de-France region, ACTRIS , and  DIM R2DS. The authors gratefully acknowledge  Jean-Charles Dupont  and the SIRTA (sirta. ipsl. fr)for the useful boundary layer height data. The other meteorological data at Montsouris site have been kindly provided by  METEO France. Edited by: C. H. Song Reviewed by: three anonymous referees.
We develop and optimise an open Python code to compute this distance. The metric is applied to the dispersion of cesium-137 of the Fukushima-Daiichi nuclear power plant accident. We discuss of its application in model-to-model comparison but also in the verification of model simulation against a map of observed deposited cesium-137 over Japan. As hoped for, the Wasserstein distance is less penalising, and yet retains some of the key discriminating properties of the root mean square error indicator.
, 2012; Terada et al. , 2012; Winiarek et al. , 2012; Saunier et al. , 2013; Winiarek et al. , 2014; Katata et al. , 2015). The meteorological conditions are also identified as being an important source of uncertainties  (Korsakissok et al. , 2013; Arnold et al. , 2015; Sekiyama et al. , 2015). In these studies, the quantification of the model-to-data discrepancies is based on the classical statistical indicators initially proposed by  Chang and Hanna (2004). The usual indicators proved to be inefficient to express the agreement/ disagreement between simulations and observations, and there is a need to find new indicators to better express the performance of models to simulate the dispersion of an accidental release. The Institute for Radiological Protection and Nuclear Safety (IRSN) developed a database gathering the radiological measurement data of any type from multiple sources into a single resource, ensuring the traceability of the measurement campaigns and simplifying the data mining to end users  (Que´rel et al.
Outline In Section 2, we first provide a mathematical and conceptual introduction to the optimal transport theory, as well as the definition of the Wasserstein distance. In Section 3, building on  Papadakis et al. (2014) , we describe a numerical algorithm that allows to compute the optimal transport map and the related Wasserstein distance. We explain how we have extended this algorithm to account for tracer transport specifics. We also describe and point to an openly available python code of the algorithm. This is an improved and extended declination of that provided by  Papadakis et al. (2014) , which we refactored to be fast enough for the purposes of this study. In Section 4, we apply the technique to the comparison of simulation outputs of the Fukushima-Daiichi radionuclides atmospheric dispersion event.
Code All the schemes used in the algorithm rely heavily on basic linear algebra routines and on variants of the FFT. Those are handled well and efficiently by the python language. Our code was initially inspired by the MATLAB † code (github. com/gpeyre/2013-SIIMS-ot-splitting) but later diverged significantly in terms of optimisation and new functionalities. Our python code is object-oriented and rely on several standard scipy library modules: scipy. fftpack, scipy. interpolate, scipy. integrate and numpy: numpy. linalg, numpy. meshgrid, numpy. tensordot, etc. that considerably accelerate the main algorithmic operations. The code is not parallelised and run on a single CPU core. Most of the main steps of the algorithms could actually be parallelised to deal with higher dimensional spaces. As an indication, we give in Table  1  the wall-clock time taken to run 10 3 iterations of the DR and PD solvers for a d 01 and a d 02 optimal transport problems for several resolutions, using our code.
Setup We use the same model setup as in  Winiarek et al. (2014). In particular the Polyphemus chemical transport model  (Que´lo et al. , 2007)  is run over a 120)120 grid of resolution 0. 058 )0. 058 and 15 vertical levels. The meteorological fields as well as the parameterisations used in the model, such as transport, wet and dry deposition, are described in  Winiarek et al. (2014). We use the source term for cesium-137 estimated in Section 3. 4 of the same article, as in  Que´rel et al. (2016). Our optimal transport code can handle 1D and 2D fields. Hence, the 4D simulations of the radionuclides plumes, 3D in space plus the (real) time dimension, need to be projected onto a space of lower dimension. We have considered: (1) the activity concentrations at ground level and fixed time, with a threshold of 10 (3 Bq.
Comparison to deposition data As mentioned in the introduction, a cesium-137 activity deposition map has been extracted from the observation database of IRSN. These observations were obtained from airborne campaigns  (Sanada et al. , 2014)  and soil sampling campaigns  (Endo et al. , 2012; Saito et al. , 2015b). This map is shown in Fig. 9  using deposition values in logarithmic scale. Illustration of the deformation induced by optimal transport of cesium-137 plumes at ground level at 7:00 UTC on 25 March 2011, between simulations 1 and 3 using normalisation (top panels), between simulations 1 and 6 using normalisation (middle panels), and simulations 1 and 6 using the reservoir technique (bottom panels). The deformation of the plumes are shown at five time steps, the first one being the concentration field of the first simulation, and the last one being the concentration field of the second simulation.
This method utilizes a Bmesh-to-mesh value,^a single value which quantifies the difference of two meshes (models) in millimeters, though it is not necessarily a simple average of the distances between the two models. Still, the lower a mesh-to-mesh value, the more similar two models, or meshes are. The algorithms used to determine a mesh-to-mesh value are based on Iterative Closest Point (ICP) comparison algorithms  [16]. For the initial manual MVC method, using LMI Technologies Flexscan 3D software, other, unknown, proprietary algorithms are also involved in mesh-to-mesh value creation. To account for this, we designed an automated MVC method using an add-on for the software program Viewbox 4 (dHAL Software, Kifissia, Greece), in which the algorithms used to compare mesh similarity could be controlled and the process sped up.
Materials A total of 45 well-preserved humeri from three different populations (G1, G2, and G3) were used for this study, to insure coverage of multiple time periods and geographical locations. Thirty-one humeri were scanned via computed tomography (CT) and 14 humeri were three-dimensional surface scanned. The main difference between the CT and 3D surface scan data was that the 3D surface data does not include the internal structures of the objects which were scanned  [20]. Ten known pairs of humeri (G1) originated from the Ballumbie and St. Andrews medieval Scottish collections (fifteenth to seventeenth century) held by the University of Edinburgh  [21, 22]. Eleven humeri (G2), including four pairs and three individual humeri, originated from the archaeological Ibizan cathedral collection (thirteenth to early nineteenth century) in Spain, held by the Ibizan city hall  [23].
Scanning protocols CT scans of G1 were taken at the Clinical Research Imaging Centre, University of Edinburgh, using a Toshiba Aquilion ONE 320 Detector Row Computed Tomography system, a multidetector CT scanning system. Data were collected using a slice thickness of 0. 5 mm and a matrix of 512 × 512 pixels. CT scans of G2 were taken at the Can Misses Hospital, Ibiza, using a GE Medical System HiSpeed NX/I Computed Tomography Scanner. Data were collected using a slice thickness of 1. 5 mm and a matrix of 512 × 512 pixels. All data were saved as a Digital Imaging and Communications in Medicine (DICOM) format. Three-dimensional surface scans of the humeri in G3 were made using a two camera system, each 1. 9 megapixels, with a ScanProbe Standard structured light scanner at the University of Bologna.
Mesh-to-mesh value comparison methodmanual The manual MVC method utilized LMI Technologies' Flexscan 3D to compare all the humeri. The protocol for comparison is as follows: All right humeri were mirror-imaged using the free software NetFabb basic. All mirror-imaged humeri were then loaded into the Flexscan3D software. One left humerus at a time was then also loaded into the software for comparison against all of the mirrored humeri. All 22 left humeri were subsequently compared to all 23 mirrored-right humeri. To compare any two humeri, both scans were roughly lined up on top of each other using the mouse. Then, the "fine alignment" feature was used in order to obtain a mesh-to-mesh value, which was recorded for comparison (see Fig. 1  for an example). The mesh-to-mesh values were used as a proxy for pairmatching, where the lowest agreed-upon value indicated the best match.
Mesh-to-mesh value comparison methodautomated The automated MVC method utilized Viewbox 4 for comparison. The following settings were used, comparing all meshes to each other from a single folder. The estimated overlap for the scans was 100 %, while the initial position for rough alignment was set at 20. The rough alignment used the nearest neighbor search BApproximate (fast)^with a point sampling of 1 %. It matched point to point, with one hundred iterations. The fine alignment used the nearest neighbor search BExact with normal compatibility^with a point sampling of 100 %. It matched point to plane, with one hundred iterations. The program then automatically generated an Excel spreadsheet of all of the mesh-to-mesh values for analysis. It should be noted that as this program cannot yet handle comparing 3D surface scans to full CT scan data, the 31 CT scan models were internally hollowed before comparison.
Results For the manual version of MVC, the sensitivity and specificity were 100 % and 100 %, respectively (Table  2 ). Additionally, the type of scan data did not seem to affect the accuracy of the manual MVC version. For the automated version of MVC, the sensitivity and specificity were 95 % and 60 %, respectively (Table  3 ). This was because, although the automated version correctly identified all of the true negatives in the sample, it mistakenly paired Td-46L (44) with StA-75R (63) and indicated that StA-75L (3) and Td-46R (39) did not have pairmatches present; in other words, that StA-75 L (3) and Td-46R (39) were negatives. The mesh-to-mesh values of both versions were analyzed to see if a single threshold value could be used to match pairs instead of the entire Excel sheet matrix. For the manual MVC method, the average mesh-to-mesh value of all of the true matches was 0.
As the MVC method does not require biological landmarking, it also reduces error across different practitioners. Additionally, another advantage of the method is that it is sex-, population-, and chronology-independent. This drastically simplifies the work of forensic experts when dealing with unclear sets of commingled remains, which can potentially be of different populations or from different time periods. Finally, if the MVC pair-matching method could be applied to mass disasters, it could significantly reduce the cost and burden of DNA testing every bone or bone fragment. As for a hypothesis regarding why the automated version of MVC is less accurate than the manual version, there are several possible factors. First, though the Flexscan 3D software is based on ICP, from brief experimentation with the software, it also uses additional algorithms to prioritize which surfaces are matched together.
Given that the automated MVC method failed to correctly match complete specimens of two different scan types and groups (G1 and G2), the lack of these unknown additional algorithms seems plausible. These algorithms could simply be those for prioritization as mentioned before, or could be other, unknown ones. As the software and its algorithms are proprietary, the exact algorithms may never be known. Second, though different settings for Viewbox, such as point-to-point comparison versus point-to-plane comparison and all of the different iterations of rough and fine alignment, have been tested, other settings, such as different percentages of overlap for cases of fragmentation  [26] , still need to be investigated. Thus far, the results do not seem to be overly sensitive to the settings, beyond the expected drastic decrease in accuracy of 1 versus 100 % point sampling during the fine alignment stage, but this may change as all of the possibilities of the software are fully explored.
It must also be noted that though the MVC method was tested using two commercial software programs, there is the possibility that the method works just as well on other, free software programs. LMI Technologies, for example, have just released K-Scan, a free program which seems to be identical to Flexscan 3D. Similarly, other common modeling programs such as Mesh Lab or CloudCompare may also work. Most of the bones tested in this study were complete and in good taphonomic condition, with no visible markers of  pathology. This means that the extent and range of the effects of taphonomy, pathology, and fragmentation must be tested how they impact both the manual and automated MVC method in the future, before it can be applied in the field. Additionally, scan quality is of the utmost importance when using a method which relies on the accuracy of said scans.
Any issues which change the surface quality of a scan, such as improper hole filling from 3D surface scans or CT scan slices that are too thick, will negatively affect the comparison process. Similarly, in our brief experimentation so far, it appears that taphonomy and fragmentation can affect scan quality and thus comparison. Therefore, more research into the extent of these effects must be done before guidelines for scan quality can to be set in order to ensure consistency of results. Furthermore, the deviation analysis feature in the Flexscan3D software could be explored to help quantify and catalogue different types and prevalence rates of bilateral asymmetry in addition to the MVC method. Once a meshto-mesh value has been created, the deviation analysis feature color-codes the regions of distance between two mesh (such as all of the locations where mesh A is 0.