dataesr/scientific-paragraphs-categorization huggingface dataset:
3D MODELLING WORKFLOW A well-controlled workflow  (Murtiyoso & Grussenmeyer, 2018)  made it possible to obtain point clouds with an accuracy of 2 to 3 mm after registration and georeferencing. In order to manage large datasets, the Winter Garden has been subdivided into 6 main parts, which in turn are subdivided into 10 subparts. The commercial software 3DReshaper was used for the meshing job, as it allows to build a manual mesh. The final result was achieved by refining a coarse mesh (with an average distance of 1. 5 to 2 cm between future mesh points) and applying afterwards a smoothing process along with manual corrections. Corresponding tools are available in 3DReshaper. All are explained in the software user manual  [TECHNODIGIT, 2016]. Set to an empirically defined value of 10 -5 , the function "Refining to rope error/ from a point cloud" allowed in particular to minimize errors in the mesh by taking false points into consideration.
The minimum size of triangles was set to 1 mm (which is the resampling value of the global point cloud) in order to avoid too small triangles. A local smoothing was also applied to reduce the noise impact. The best way of doing so is to retain the same refining and smoothing parameters in order to finally get a uniform overall mesh. As 3DReshaper is a commercial software, we had no access to the algorithms implemented and can therefore not explain in detail how they work. After having done so for the 6 main parts, all were put together and combined to form a single block, i. e. the Winter Garden (Figure  2 ). The last processing step consisted in texturing the model by applying the images acquired with the SLR camera. This operation was not carried out globally (for the Winter Garden as a whole).
The different files of the remarkable objects and the volumetry were imported separately in OBJ format into the PhotoScan software. The pre-processed georeferenced texture was then applied. An adequate texture able to maintain all the details without producing too large files was chosen with great care, as well as the sizes (10000x10000 pixels for remarkable objects to get sufficient detail on each one of them, 40000x40000 pixels for the volumetry because it is the maximum texture size that can be calculated by PhotoScan) (Figure  3 ). The main disadvantage of textured mesh models lies in the large size of the resulting files. Two solutions were tested in order to optimize the models. The "Reduce" function of 3DReshaper was the first one, based on a deviation criterion. It was set to 10 -5 m.
Programming Image Processing Image processing solutions aim at correcting the model's texture. This can either be done by programming means (on using dedicated toolboxes) or with specialized software such as the open source GIMP Tool. A histogram equalization was applied to the RAW images taken with the Canon EOS 5DSR camera at the bottom of the fountain to lighten them because they were too dark. The image processing toolboxes of Matlab were used for that purpose, the goal being to smooth out the differences between the textured model at the top (smartphone data acquisition) and at the bottom (Canon pictures processed) of the fountain (Figure  6 ).
Virtual Reality Viewer for an immersive point cloud visualization The second solution consisted in using the point clouds of the Winter Garden and its surroundings for an immersive visualization. The FARO SCENE software and the HTC Vive system made that possible (Figure  8 ). The immersion was implemented by registering point clouds progressively with the cloud to cloud method as no sphere was placed inside the Winter Garden. Figure  8. Immersion in virtual reality in the Winter Garden An average deviation of 1. 3 mm resulted from that registration with a difference being below 4 mm for 79% of the points. This is rather satisfying, considering that the point clouds used came from different acquisition campaigns. The user can thus move freely in all three dimensions to appreciate the feeling of space as well as the detail refinement that the cloud offers.
Interactive virtual visit with Unreal Engine The third option consisted in setting up a virtual visit scenario in the textured model of the Winter Garden and using a video game engine for that, able to manage large files. Interactivity has played an important part since buttons have been created especially to enable the user to consult information about remarkable objects of the Winter Garden and its history (Figure  9 ). Consequently, the HTC Vive system has been finetuned with Unreal Engine to allow a model-user interaction and to program the movements inside the room.
This paper presents a new algorithm (INNOV) capable of generating a mesh of three-dimensional objects containing multiple phases. This mesh can later be imported into commercial or open-source software to perform multiphysics-based simulations based on partial differential equations. While the range of application is large, this algorithm is designed as a post-processing tool of micro/ nanotomography images and electrode mesostructures predicted from CGMD (coarse-grained molecular dynamics) simulations of the electrode fabrication process carried out in LAMMPS software. With INNOV, it becomes possible to import the predicted multiparticle electrode mesostructures into COMSOL Multiphysics in order to simulate electrochemistry and transport in operating lithium-ion batteries.
7] [8] [9]  Used electrode mesostructures are either computer-generated by using random location algorithms (e. g. , GeoDict software) or obtained by computer tomography. However, reported 3D-resolved models rely on oversimplifications, such as an implicit representation of the CBD through the use of effective parameters for porosity and tortuosity  10, 11  or by merging CBD with the active material (AM) as a single solid phase. 12 ecause of the disparate spatial scales, meshing an explicit representation of CBD and AM would be like trying to paint with the same paintbrush a rock and a mountain next to each other. Either the paintbrush is too wide or is too fine. In the first case, the time needed to paint the mountain will be short but the rock geometry will appear as deformed. In the second case, the rock will retain its apparent geometry but the time needed to paint the mountain will be extremely long.
In the case of an adaptive mesh, the complexity relies on assembling a coarser and a finer mesh together. Where the AM and the CBD are in contact, the elements of the mesh of the AM should be finer to match the ones of the CBD. This task is challenging to do at each interface between AM and CBD phases. This work reports a computationally efficient and versatile algorithm capable of meshing multiple phases by using voxelization. The algorithm has been named INdefinite Number Of phases meshing through Voxelization (INNOV). This algorithm is able to import a multiphase volumetric mesh into COMSOL Multiphysics benefiting from the native format improvement in the latest update (COMSOL 5. 4,  13  January 2019). In this paper, INNOV is illustrated through its application to a LIB composite electrodes predicted by using coarse-grained molecular dynamics (CGMD) using LAMMPS software.
RESULTS AND DISCUSSION In this section, we discuss the results of INNOV applied to a three-phased LiNiMnCo electrode (AM + CBD + void) generated from CGMD calculations using LAMMPS software, as explained in the article of Ngandjong et al. 10  and Rucci et al. 16  In this case, the input is a text file with coordinates of the centers and radii of each of the particles (see Figure  S3 ). 2. 1. Meshing. Once the binary stacks of images are generated, a precision of [4 4 3] is set to decrease the computational cost (see Section 4). Time-efficient meshing is achieved due to the simplicity of the operations and an optimization through a matrix formalism in MATLAB. The meshes represented in Figure  1  both have 339 067 nodes, 371 213 faces, and 1 737 665 elements. The unsmoothed mesh has been generated in 4.
CONCLUSIONS We report a flexible MATLAB-based algorithm (INNOV) to tackle the meshing process and importation of multiphase objects in computational frameworks for multiphysics simulations based on sets of partial differential equations. From a selection of input format, INNOV generates a volumetric mesh able to contain an unlimited number of phases. This mesh can then be converted into the desired format to suit a variety of commercial and open-source software. INNOV embeds a set of observables to ensure the geometric integrity of the structure after the meshing step. While designed for the battery field, this algorithm can be applied to a wide spectrum of scientific fields. It offers a time-efficient tool to perform meshing without requiring substantial computational resources.
METHODS The INNOV algorithm embeds as its segmentation method the mathematical approach of Nielson and Franke 19 (Figure  2 ) and a function of the open-source program Iso2Mesh 20 to remove duplicated nodes. This segmentation method has been translated and optimized for MATLAB language and modified to suit the COMSOL Multiphysics meshing importation process. For instance, this new algorithm could lead to considering explicitly the complex CBD morphology in an electrode performance model, which has not yet been reported in the battery field to the knowledge of the authors. 4. 1. Inputs of INNOV. The algorithm takes as input the binary stack of images. Such a stack of images can result from different processes. First, it can be generated from a various selection of imaging tools, such as the segmentation of tomography data.
A trivial one is when all nodes belong to the same phase, no decomposition is needed and the element is retained. The three others occur when the nodes belong to different phases and demand for a decomposition into several more tetrahedrons and the creation of triangular faces to effectively separate the phases. Which means that the more intricate the phases are, the more surface area there is between them, and the higher the number of elements and faces. 4. 5. Importation. A nontrivial step in the modeling process is the importation of a mesh into outside software. Whether due to the formalism of the format or its lack of documentation, one must tread carefully when converting a mesh. The algorithm presented here performs a successful importation of the mesh in the native format (mphtxt) of COMSOL Multiphysics software.
The controller for the original plant P is thus represented by Equation  5. C p (s) = S i N c P + g K(s) (5) Figure  6 : References for (a) σ and (b) θ for a snowake plasma conguration obtained from FBTE  [26]. (c) Pre-programmed plasma boundary (magenta circles), location of the strike points (magenta diamonds) and of the X-points (magenta crosses) in MGAMS  [27] ; poloidal ux map (blue curves) and separatrix (red curves) and location of the magnetic axis (black cross) obtained from the free boundary equilibrium code (FBTE) at a given time instance. The real-time version of the Grad-Shafranov equilibrium reconstruction code LIUQE  [28] , RTLIUQE  [29] , with a sub-ms cycle time (0. 4 ms) provides an estimate of the poloidal ux and magnetic eld at the control points. Figure  5  shows the block diagram representing the implementation of the controller with the TCV coil current controller and RTLIUQE.
The controller formalism assumes, of course, that the estimates of the magnetic elds and poloidal uxes provided by RTLIUQE are accurate. The performance of the controller must be judged entirely on its ability to create shapes that RTLIUQE will reconstruct. Ultimately, however, the performance of any shape controller will be limited by the accuracy of the shape reconstruction itself. The discussion of the accuracy of RTLIUQE is outside the scope of this paper. Figure  6  shows the reference Ohmic SF plasma conguration scenario that is used to characterise the performance of the generalised plasma position and shape controller. The scenario consists of a scan of the σ parameter for the snowake plasma conguration and was developed in FBTE/MGAMS  [26, 27] , the suite of software tools used routinely on TCV to determine the poloidal coil currents and the feedback parameters for a given plasma conguration.
(2017) , we explore the feasibility of estimating CH 4 emissions for individual coal mine ventilation shafts and groups of shafts. To this end, we mounted the EM27/SUN on a truck and we drove transects through the CH 4 plumes in the USCB while driving in stop-and-go patterns. We estimated emissions from the recorded XCH 4 enhancements using a mass balance method, which was assisted by wind information from three wind lidars deployed in the broader region. Section 2 summarizes the campaign setup, describes the de-ployed instruments and the data analysis, and explains the emission estimation method. Emission estimates of CH 4 are summarized in Sect. 3 followed by the analysis of the errors in Sect. 4. We evaluate the suitability of the method used, compare the estimated emissions to the E-PRTR database, and conclude this work with Sect.
For the retrieval of XCH 4 from the FTS measurements we use the software package PROFFIT  (Hase et al. , 2004) , which is in routine use for accurate trace gas retrievals from shortwave-infrared direct-sun absorption spectra (e. g. Gisi et al. , 2012; Frey et al. , 2015; Klappenbach et al. , 2015; Chen et al. , 2016; Butz et al. , 2017; Frey et al. , 2019). Quality filtering, based on the unmodulated (DC) part of the recorded interferograms, removes all measurements that are affected by unstable pointing conditions, e. g. due to intermittent thin clouds disturbing solar tracking (e. g. Klappenbach et al. , 2015). We set the DC fluctuation threshold to 1 % for discarding corrupt interferograms. The spectral bandwidth of the EM27/SUN allows for measurements of H 2 O, O 2 , CO 2 , CH 4 , CO (CO in combination with an additional channel described by  Hase et al.
ec. europa. eu/, 2014), which contains emission data reported annually by industrial facilities over Europe including the coal mining branch. This dataset provides annual mean values of CH 4 emissions for each mining facility registered. The annual means refer to whole mines, which typically have several shafts to ventilate CH 4. We distributed the annual means reported by E-PRTR evenly to all known shafts of every mine. However, our measurements are restricted to a few hours per shaft, and ventilating CH 4 of coal mines is a variable process depending on the concentrations in the mine. Furthermore, turbulent processes influence the shape and position of the plume and therefore the measurements. Thus, comparing our snapshot-like measurements with the disaggregated E-PRTR reports can only provide a rough comparison.
However, reported emissions likely range between 50 kt a -1 (sum of nearest upwind mines < 10 km) and 150 kt a -1 (sum of south-eastern upwind part of the USCB). Our best estimate using the mobile FTS dataset is 109 ± 33 kt a -1. Reported (24. 3 kt a -1 ) and estimated emissions (17 ± 3 kt a -1 ) generally agree for the morning transect of 6 June. The noon transect on 6 June crossed several possible CH 4 sources although the reported emissions are roughly 80 kt a -1. Our best estimate using the mobile FTS data is 81 ± 13 kt a -1 , which includes the reported value in the error range. However, many sources are located upwind in the northern part of the USCB within about 60 km distance of the measurements, which also could have influenced the observations but are not included in the sum of the reported emissions for that day.
Acknowledgements. We acknowledge funding for the CoMet campaign by  BMBF  ( German Federal Ministry of Education and Research)  through  AIRSPACE (FKZ  (grant no. 01LK1701A )). We thank  DLR VO-R  for funding the young investigator research group "Greenhouse Gases". We gratefully acknowledge the constructive comments of two anonymous referees as well as the helpful comments of  Mathieu Quatrevalet  ( DLR-Institute of Atmospheric Physics, Oberpfaffenhofen, Germany ) on an earlier version of the manuscript. Financial support. The CoMet campaign has been supported by  BMBF  ( German Federal Ministry of Education and Research)  through  AIRSPACE (FKZ  (grant no. 01LK1701A )). The article processing charges for this open-access publication were covered by a  Research Centre of the Helmholtz Association.
Trabecular bone score The Trabecular Bone Score (TBS), calculated by the software package TBS iNsight ® (Medimaps Group SA, Geneva, Switzerland), is a unit-less indirect index of trabecular microarchitecture based on pixel grey level variations in the DXA images  [23, 24]. The large clinical database of the Province of Manitoba (Canada), including 29,407 women aged over 50 years at baseline, has been used for several investigations aimed at assessing the ability of TBS in fracture risk prediction. Although TBS (along with BMD and additional clinical risk factors) helps to identify individuals at high risk of fracture and to guide initiation of osteoporosis treatment  [25] , change in lumbar spine TBS is not a useful indicator of fracture risk regardless of osteoporosis treatment  [26]. Another retrospective study on the Manitoba database showed the ability of lumbar spine TBS to predict osteoporotic fractures in patients with type 2 diabetes, whereas BMD was paradoxically increased in these patients  [27].
On this basis, the Hip Structural Analysis (HSA) software was developed to simultaneously evaluate both hip geometrical information and corresponding mineral mass data derived from DXA images  [42]. Whether HSA could be actually useful for clinical assessment of bone fragility is currently under investigation, with few studies showing that some factors, i. e. cortical thickness of the intertrochanteric region  [43] , HAL and neck shaft angle  [44]  might have a role in fracture risk assessment for specific categories of patients.
The selected measured data are finally synthetized in a patient-specific spectrum of the considered bone target, which undergoes an advanced comparison with gender-, age-, site-and BMI-matched reference spectral models extracted from a dedicated database (Fig. 6 ). Actually, the spectral modifications introduced by the physical properties of the bone structure that has backscattered the ultrasound signals are identified by the comparison procedure, resulting in a BMD estimation and in the consequent diagnostic classification as healthy, osteopenic or osteoporotic. The adopted approach is based on the calculation of the Osteoporosis Score, which corresponds to the percentage of analysed spectra that were classified as "osteoporotic" through the dedicated spectral analyses  [97, 98]. Linear equations are then employed to transform Osteoporosis Score into BMD values.
Permeability reduction is mainly documented in the interseismic environment involving chemical processes such as clay alteration  (Menzies et al. , 2016) , fault healing  (Aben et al. , 2017; Gratier & Gueydan, 2007) , and cementation  (Dempsey et al. , 2014). Coseismic reduction of permeability has been observed in the field as a result of clogging of fractures  (Shi et al. , 2018; Yan et al. , 2016)  and can be associated with processes requiring a high level of shaking  (Vucetic, 1994) , notably shear-induced consolidation  (Rutter et al. , 2016; Wang et al. , 2001)  or liquefaction  (Wang, 2007). In this contribution, tidal analysis is performed on data from 161 wells in the Canterbury hydrological network, New Zealand, that have been affected by nine M w 5. 4 or larger earthquakes between 2008 and 2015.
Seismic Data We selected nine M w 5. 4 or larger earthquakes that occurred in New Zealand between 2008 and 2015 (Figure  1 ); each was felt throughout the North and South Islands (Table  1 ). Seismic stations in the New Zealand National Seismograph Network and Strong Motion Network are operated by GeoNet (http:// geonet. org. nz). In this study, we acquired seismic data for each of the nine earthquakes from broadband and strong motion seismographs. The seismic data have a sampling frequency of either 100 or 200 Hz. We applied instrument response corrections and a band-pass filter with transition bands of 0. 10-0. 25 and 24. 50-25. 50 Hz. We then calculated site-specific shaking parameters as described below.
Water Resources Research transducers. There are seven clusters of two or three wells each in which the monitoring sites contain multilevel piezometers or are in very close proximity to each other (<20-m separation). Barometric pressure sensors are distributed throughout the region and installed in monitoring well casings just below ground level. We apply barometric corrections to the nonvented pressure data so that the data set    Water Resources Research analyzed reflects changes in water pressure only. The correction process uses barometric pressure data from the nearest site, usually within a 20-km distance and 300-m elevation of the respective well. Sea level monitoring in the Canterbury region is undertaken by The National Institute for Water and Atmospheric Research. These sites are located in Christchurch and Timaru (Figure  1 ; see the supporting information).
Wells exhibiting water-level fluctuations caused predominantly by S 1 , S 2 , K 1 , or K 2 tend to be dominated by barometric and thermal effects  (Doan et al. , 2006). Water-level fluctuations caused by all but the M 2 and O 1 components are sensitive to thermal and anthropogenic disturbances. Typical amplitudes of the M 2 component are larger than those of the O 1 component  (Wilhelm et al. , 1997). Also, the sea level sites in Canterbury exhibit a larger ocean tide amplitude of the M 2 component (~763 mm) than the O 1 (~28 mm) component (see the supporting information). As a result, only water-level fluctuations caused by the M 2 component were considered in the analysis. We have used the software package Baytap08, modified for application to high-frequency data, to decompose the observed water-level data (h) into constituent tidal signals (h k ).
Whereas the hydraulic response to earth tides is typically of the scale of several tens of centimeters, the amplitudes of oceanic tides can exceed several meters. Ocean tides can induce direct mechanical loading at the coast. Software like SPOTL  (Agnew, 2012)  predicts this mechanical loading from global or regional models of oceanic tides. If ocean tidal gauge time series data are available, the loading can by analytically computed from the Boussinesq equation  (Doan, 2005). Pressure changes associated with ocean tides can also diffuse inland by direct hydraulic connection between the ocean and coastal aquifers. This induces water-level fluctuations in wells  (Ferris, 1951). Analytical solutions (van der  Kamp, 1972)  show that oceanic tides can in some situations propagate tens of kilometers inland  (Merritt, 2004).
With such variability, small precursory earthquake signals are unlikely to be detected, even if present, and these have been ignored. Many wells incurred damage as a result of the Canterbury earthquake sequence. The elevation of several monitoring well heads changed as a result of the buoyant rise of casing and/or ground subsidence, which Water Resources Research affected the measurement of water-levels and necessitated resurveying. Elsewhere, damaged logging equipment and screens were replaced and repumped. New elevations are used here for boreholes where resurveying had been completed; otherwise, it was assumed any anthropogenic influence on the data or data quality were minor or easily identified and corrected for. Absolute ground-water levels are generally known to ±50 cm relative to sea level, once corrected for barometric pressure variations and surveying uncertainties.