dataesr/scientific-paragraphs-categorization huggingface dataset:
A1. 7. Parcels Parcels is an experimental prototype code aimed at exploring novel approaches for Lagrangian tracking of virtual ocean tracer particles in the petascale age. Parcels, which is currently under development, is designed from the ground up to be efficient and fast for the next generation of ocean circulation models. These ocean models are so big and massively parallel, and they produce so much data, that in a few years we may face a situation where many of the Lagrangian frameworks cannot be used on the latest data any more (see also Section 5. 1). The user interface of Parcels is written in python, while the computational intensive integration is Just-In-Time (JIT) compiled into C. The code is formed around a flexible and customisable API that allows rapid model development, based on discrete time-stepping algorithms (Section 3.
A2. 3. MITgcm The Massachusetts Institute of Technology General Circulation model  (MITgcm Marshall et al. , 1997b; 1997c ) is a generalized level coordinate ocean model with a wide range of configuration possibilities. The MITgcm includes a package for Lagrangian particle advection. The Lagrangian package, named flt, is however poorly documented and not described in the literature. Nevertheless, this package provides a convenient way to integrate Lagrangian analysis into existing MITgcm setups, thereby taking advantage of the MPI parallelism of the model. Numerically, floats are advected using RK4. A fixed memory buffer is allocated for floats on each tile, implying that memory is wasted for sparse particle ensembles. Because of MITgcm's "offline mode"  (Adcroft et al. , 2014) , which enables loading of velocity fields from files, MITgcm can be effectively used as a generalpurpose Lagrangian model.
A2. 4. HYCOM HYCOM (the HYbrid Coordinate Ocean Model) is a generalized (hybrid) vertical coordinate ocean model (isopycnal, terrain following, and/or pressure). It is isopycnal in the open stratified ocean, but reverts smoothly to a terrain-following coordinate in shallow coastal regions, and to pressure coordinates near the surface in the mixed layer  (Bleck, 2002; Chassignet et al. , 2003; 2006). HYCOM includes online code designed to follow numerical particles during model run time  (Halliwell and Garraffo, 2002; Wallcraft et al. , 2009). In addition to the ability to follow a fluid particle in three dimensions, one can also release both isobaric and isopycnic floats. Isobaric floats remain at prescribed pressure levels while isopycnic floats remain on prescribed density surfaces. Because of the generalized (or hybrid) vertical coordinate of HYCOM, one has to be especially attentive when performing vertical and horizontal interpolations/advections.
org/) is a free surface, hydrostatic primitive equations ocean model with terrainfollowing vertical coordinates that allow differential stretching  (Shchepetkin and McWilliams, 2005; Haidvogel et al. , 2008). It is an open source parallel Fortran code coupled to several models including biogeochemestry, waves, sediments, bio-optical and sea ice. It offers great flexibility for configuration and is widely used by the scientific community for a diverse range of applications. ROMS includes a module called floats, which allows the release and tracking of numerical particles during model run time. Passive floats can be of 3 different types: neutral density 3D Lagrangian, isobaric (remain at prescribed pressure level) or geopotential (remain at prescribed depth). The numerical scheme used to time-step simulated floats trajectories is a fourth-order Milne predictor and fourth-order Hamming corrector.
Acknowledgements This review paper is the result of very fruitful discussions during the " Future of Lagrangian Ocean Modelling " workshop, held at  Imperial College London, UK , in September 2015. Funding for this workshop was provided through an  EPSRC   Institutional Sponsorship grant  to  EvS  under reference number  EP/N50869X/1. EvS has received funding from the  European Research Council (ERC)  under the European Unions  Horizon 2020 research and innovation programme  (grant agreement No  715386 ). This research for PJW was supported as part of the  Energy Exascale Earth System Model  ( E3SM )  project, funded by the  U. S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Funding for HFD was provided by Grant No. DE-SC0012457  from the  US Department of Energy.
The 3D volume reconstructed from the outlines was placed in the Talairach stereotactic coordinate system relative to the intercommissural line and sectioned in three stereotactic planes to produce color-coded nuclear maps. This 3D coordinate-based atlas was coregistered to the Montreal Neurological Institute (MNI-152) space. The current report proposes a simplified nomenclature of the motor-related thalamic nuclei, presents images of selected histological sections and stereotactic maps illustrating topographic relationships of these nuclei as well as their relationship with adjacent somatosensory afferent region. The data are useful in different applications such as functional MRI and diffusion tractography. The 3D dataset is publicly available under an open license and can also be applicable in clinical interventions in the thalamus.
This report demonstrates selected images of computer processed histologic sagittal sections containing motor thalamic nuclei, corresponding color-coded maps showing these nuclei in three stereotactic coordinate planes, and their placement within MNI space. The entire atlas and volumetric MNI version of the dataset are available at www. humanmotorthalamus. com. Moreover, the MNI version integrated into an open source deep brain stimulation analysis software is available at www. lead-dbs. org (Horn and Kühn, 2015).
All sections were collected and placed in individual numbered compartments to maintain the sequence. Entire section series was mounted on slides, stained with thionin and used for analysis of cytoarchitecture. For imaging and 3D reconstruction, one series of sections through the thalamus of one female brain was chosen. Criteria for choice were the quality of sections and tissue preservation, completeness of the section series, as well as the length of the AC-PC line, i. e. , intercommissural line, of 23 mm. This length was comparable to that of the brain used for demonstration of sagittal sections in the Schaltenbrand and Bailey atlas (23. 5 mm) thus facilitating comparisons of coordinates of different structures in the two datasets. The choice of the sagittal section plane was determined by the following considerations.
The outlines were closed using mathematical morphology operation called dilation to make the outlines thicker and closed and transferred to ImageJ where they were filled with varying colors (Fig. 2 ). These color-coded images were used for 3D reconstruction. Processing was done with Amira software (FEI Software). Stacks were loaded as a 3D volume in the physical space calibrated in millimeters based on the 250-m section thickness and the pixel size derived from the original length of intercommissural line measured from the posterior end of AC to anterior end of PC in one of medial sections, in which the needle tracks were perfectly parallel and the outlines of the commissure markings clear. Each structure was segmented by successive 3D thresholding of each color, slightly smoothed, and converted to a 3D surface (Fig.
1C, D ). The volume composed of all surfaces was rotated manually under Amira to align it within Cartesian coordinate planes in Amira physical space. The latter was made visible by the creation of a reference stacks containing axes created under MATLAB (MathWorks). Finally, millimeter graduations were placed on the axes. Volumes in cubic millimeters (Table  1 ) were extracted using the material measurements of Amira directly from the 3D segmented labels and computed as the number of voxels in each volume of interest multiplied by the volume of one voxel in cubic millimeters. To illustrate histology, images of each group of five adjacent sections were merged in Adobe Photoshop resulting in 250-m-thick digital sections in which general outlines of major nuclei became more evident. The latter were further emphasized using contrast and brightness adjustments.
Reconstruction of 3D version and registration to MNI space To reconstruct a 3D version of the human motor thalamus atlas that may be nonlinearly deformed to subject-/ patient-specific anatomy in both neuroimaging and surgical applications, labels derived from stacks of histology-based sagittal maps were digitized and converted to a volume in NIfTI-1 format. A coronal T2-weighted MRI scan of the histologic stacks was acquired and equally converted to NIfTI-1 format. Histology-informed labels and T2-weighted MRI blocks were linearly coregistered (6-DOF) using 3D Slicer software (www. slicer. org). Both were then manually coregistered to the MNI-152 2009b NLIN ASYM normative brain template  (Fonov et al. , 2009)  using the same 12-DOF affine transform. To refine precision, in the first step the MRI block was nonlinearly registered to the T2-weighted version of the MNI template using Advanced Normalization Tools (ANTs; http://stnava.
github. io/ANTs/; Avants et al. , 2008)  as implemented in the "effective (low variance)" preset in Lead-DBS software (www. lead-dbs. org; Horn and Kühn, 2015). The nonlinear deformation was then applied to the histologyinformed labels using ITK Generic Label interpolation as implemented in ANTs. In the second refinement step, the pseudo-MRI registration approach introduced and validated by  Chakravarty et al. (2006 Chakravarty et al. ( , 2008) )  was applied. Specifics of the multispectral multi-iterative version of the approach applied here are described in detail elsewhere  (Ewert et al. , 2018). Briefly, intensity-matched pseudo-MRIs were created from histology-derived labels by assigning each label the average intensity under its volume defined in the T1-, T2-, and PD-weighted MNI templates.
Results The focus of the study was on parcellation of functionally different territories of the motor thalamus and their topographic relationships, therefore only selected digital images of Nissl-stained sagittal sections and computer generated nuclear maps illustrating these relationships in three stereotactic planes are presented in this report. For the entire dataset containing also some nuclei and fiber bundles of the basal ganglia, subthalamic region, and midbrain, see www. humanmotorthalamus. com. Successive mediolateral levels shown in Figures  3 4 5 6 7 illustrate the extent of the major territories of distribution of nigral, pallidal, and cerebellar afferent projections in the human thalamus. Regarding the types of nerve cells and their distribution patterns in the homologous motor thalamic nuclei, there is no difference between human and rhesus monkey (Kultas-  Ilinsky et al.
Discussion The main accomplishment of this study is a demonstration of the full extent of reliably identified human motorrelated thalamic nuclei in three stereotactic planes derived from one brain. To our knowledge, this is the first demonstration of this kind. This report shows only selected images. The entire section series through the thalamus and adjacent structures at 250-m intervals with all nuclei present as well as supporting materials are available on a dedicated Internet site (www. humanmotorthalamus. com) linked to the Society for Neuroscience database (NIF; https://neuinfo. org). The MNI version of the atlas is available within Lead-DBS software www. lead-dbs. org. In the present publication, we discuss only major subcortical afferent zones of the motor thalamus, namely nigral, pallidal, and cerebellar in the light of existing con-troversies and discrepancies as evidenced by publications in the fields of functional neurosurgery and brain imaging studies.
, 2006). On the other hand, the GAD65 staining pattern in the area outlined as Vop in Hassler's maps is Movie 1. 3D relationships of motor thalamic nuclei and some other structures within MNI space. VL appears first followed by VAn and VAp. In the next sequence, all three appear together and then some other structures of particular relevance to deep brain stimulation such as medial and lateral globus pallidus, subthalamic nucleus, substantia nigra, and red nucleus are added. For unlabeled nuclei, refer to color-code in Figure  2. [View online] identical to that in the area outlined as Vim, indicating that both are part of the cerebellar afferent territory except for a narrow strip at the anterior end of Vop, which together with Voa displays staining pattern characteristic for pallidal afferent territory (Kultas-  Ilinsky et al.
, 2005; Klein et al. , 2010; Kincses et al. , 2012; Mang et al. , 2012) , one can see that while the anteroposterior sequence of the zones is similar, their neuroanatomical orientation, shapes, and relative sizes differ in the two datasets. The most striking and substantial difference is that the zones in those probabilistic maps are oriented mediolaterally at an almost 90°a ngle to the midsagittal plane implying that they only partially overlap with subcortical afferent territories and do not accurately follow the distribution of terminals of corticothalamic fibers as known from experimental studies in nonhuman primates. The simplest explanation is the difference in the spatial resolution of the neuroanatomical and DTI techniques. DTI reveals mainly the fiber bundles whereas anatomic pathway tracing and specific immuno-staining patterns expose the terminal zones.
e. , to MD nucleus where the prefrontal cortex efferents terminate. Thus, the maps of the thalamic nuclei in three stereotactic planes demonstrated here as well as the full sets of atlas plates available separately provide the common ground on which the correlation between the results of probabilistic and deterministic DT imaging studies on one hand and neuroanatomical experimental data on another can be built. Above and beyond demonstrating clear afferent domains in the human motor thalamus in volumetric fashion, the atlas established in the present study can be of great use for neuroimaging studies as well as stereotactic surgery, based on the possibility to nonlinearly register our atlas to individual brains via the use of the MNI template. In case of the former, results of fMRI studies on task activation or diffusion-weigher tractography studies may be assigned to finer subregions  (Behrens et al.
Dropout is accounted for by censoring at the time of the last study visit. Differences between arms in the diagnostic/therapeutic management, health economics, and patient-centered outcomes will be evaluated with a c 2 test, t-test, or Mann-Whitney test whichever is appropriate. Longitudinal trends of the diagnostic/therapeutic management, health economics, and patient-centered outcomes will be studied by mixed effects analyses that allow for patient-specific and center-specific effects and that can be applied to interval, dichotomous, and count data. Point estimates will be presented together with 95% Wald confidence intervals. Bonferroni corrections for multiple testing will be applied when appropriate. Data will be censored after a major protocol deviation.
Indeed, patients with SCD have different needs than those with cognitive/functional impairment, and recent efforts are moving toward the creation of the so-called "brain health clinics/services"  [48] , clinical facilities with specific aims and missions We acknowledge that in some participating clinics, an extensive biomarker workup (e. g. , CSF) is done on the first visit, before the patient can be screened for AMYPAD-DPMS. We stipulate that these patients can be enrolled in the study, but, if assigned to ARM1, the results of that workup will not be made available to the managing physician before they will be informed of the amyloid-PET result. dealing with healthy people and SCD. Data collected within AMYPAD-DPMS will provide unique evidence that brain health clinics/services will use to implement risk assessment and communication protocols.
Acknowledgments This work has received support from the  EU-EFPIA Innovative Medicines Initiatives 2 Joint Undertaking  (grant no. 115952 ). G. B. F. is a principal investigator of industry-sponsored trials funded by  AbbVie ,  Acadia, Altoida, Amoneta, Araclon, Biogen ,  Janssen ,  Novartis , and Piramal; has received funding for investigator-initiated trials from  GE, Piramal , and  Avid-Lilly ; and has received speaker fees from a number of pharma and imaging companies. F. B. reports grants from  AMYPAD (IMI) ,  EuroPOND  ( H2020 ),  UK MS Society, Dutch MS Society, PICTURE (MDI-NWO) ,  NIHR UCLH Biomedical Research Center (BRC) , and EC-TRIMS-MAGNIMS; reports personal fees from  Bayer-Schering Pharma, Biogen-Idec ,  TEVA ,  Merck-Serono ,  Novartis ,  Roche ,  Jansen Research ,  Genzyme-Sanofi, IXICO Ltd, GeNeuro ,  Apitope Ltd , and Lundbeck; and is supported by the  NIHR UCLH BRC.
M. B. has received research grants from Piramal and served as a paid member of advisory boards for Eli Lilly. A. Z. reports research funding from  Siemens Healthcare, GE Healthcare, Lilly/AVID, and Piramal  and grant funding from the  German Research Foundation (DFG)  and the  European Union. G. F. is a fulltime employee of  GE Healthcare. R. G. is a full-time employee of Piramal Imaging. F. J. reports grants from  Eli Lilly, Biogen , Axovant, and  Boehringer  and personal fees for consultancy from  Eli Lilly ,  Roche ,  Merck ,  Janssen Pharmaceutica, Biogen , and AC Immune. J. L. M. is a principal investigator of trials funded by  Lundbeck ,  Merck ,  Novartis ,  Janssen , and  Boehringer  and reports personal fees from  Eli Lilly ,  Merck ,  Janssen ,  Biogen ,  Novartis ,  Roche ,  Roche Diagnostics ,  Eisai ,  Lundbeck , Axovant, and Oryzon.
The models are also advanced to six-dimensional multivariate Gaussians that capture full correlations in the XY ZU V W distribution of members, including those in mixed spatial-kinematic coordinates. Two versions of the BANYAN Σ code (IDL 2  and python 3  ) are made publicly available  (Gagné et al. 2018b,a) , and a web portal is made available for singleobject queries  4. Most previously available classification tools rely on time-consuming algorithms, such as numerical integrals, which make it challenging to analyze large datasets such as the upcoming full Gaia release, and use various approximations in converting observables and kinematic models to probabilities that affect their classification performance. In BANYAN Σ, most of these approximations are removed, and Bayesian marginalization integrals are solved analytically.
(8) All terms in Ω i , Γ i and τ i,k can be described as scalar products induced by the inverse covariance matrix σ -1 ij,k , such as: X, Ȳ k = ij σ -1 ij,k X i Y j , (9) where the k index will be omitted in the remainder of this work for simplicity. Equation (  8 ) can be further simplified from the fact that the covariance matrix is symmetric by definition. With these two simplifications we get: M 2 (ν, ) = Ω, Ω ν 2 + Γ, Γ 2 + 2 Ω, Γ ν -2 Ω, τ ν -2 Γ, τ + τ , τ. ( 10 ) This completes the coordinate change of the Bayesian likelihood: P o ({O i }|H) dν d = 4 e -1 2 M 2 (ν, ) (2π) 6 Σ dν d. ( 11 ) 5 This display of the T matrix follows the column major convention (e. g. , IDL or Forftran). Because Python follows the row major matrix convention, T must be transposed in that language. In IDL, the T matrix is en- coded with T = [[-0.
New Bona Fide Members New bona fide members that could be defined as such based on Gaia-DR1 data are described in this section, and are listed in Table  6. The candidate members of THA identified by  Kraus et al. (2014)  were cross-matched with Gaia-DR1. Seven were found to have a parallax measurement: three of them did not match any moving group in BANYAN II and were therefore rejected (2MASS J02000918-8025009, 2MASS J02105538-4603588 and 2MASS J05332558-5117131), and the other 4 were confirmed as new bona fide members of THA (2MASS J02303239-4342232, 2MASS J04000382-2902165, 2MASS J04000395-2902280, 2MASS J04021648-1521297). A similar cross-match of the Malo et al. (  2014 ) candidate members missing a distance measurement with Gaia-DR1 yielded 21 matches, 16 of which were confirmed as new bona fide members (5 in βPMG, 8 in THA, 2 in ABDMG and one in COL).
15 × 10 6 stars). In doing this, we assume that most young associations are complete at this fraction; this approximation only affects the FPR and MCC values reported in this work. The values N k are listed for each young association in Table  1. The resulting TPR, FPR and MCC values for each young association, using each possible set of observables, are reported in Table  9 , as the range of possible values within P t ∈ 85-95% and centered on P t = 90%. They demonstrate how members of distant associations are much easier to distinguish from field objects because of their narrower distribution on the sky, with smaller FPRs and larger MCCs. Both the IDL and Python implementations of BANYAN Σ specify as an output for each star the TPR and FPR of a sample that would be constructed with only candidate members that have membership probabilities equal or higher than those of the star in question.
1% in membership probability and measurements of the optimal distance and radial velocity. The new BANYAN Σ tool includes all of the 27 currently known young associations within 150 pc, for which the current census of bona fide members is updated. It is also made publicly available in IDL and Python at www. exoplanetes. umontreal. ca/banyan/ banyansigma. php. Additional figures and information on this work can be found on the website www. astro. umontreal. ca/ ~gagne. We strongly encourage users to investigate the position of candidate members in appropriate colormagnitude diagrams using the BANYAN Σ optimal distance when no parallax measurements are used as inputs, as candidate lists generated without them suffer from ∼ 100 times more false positives in comparison (See Section 8 and Figure  10 ).
A second version of the BANYAN Σ software with such improved models will be released in a future work that will aim at furthering the census of young association members based on Gaia-DR2. The authors would like to thank the anonymous referee and the AAS statistics consultant for valuable and detailed comments that significantly improved the quality of this paper. We thank Bruno S. Alessi and Eric Bubar for sharing data. We thank Noé Aubin-Cadot, Joel Kastner, Thierry Bazier-Matte, Simon Gélinas, Jean-François Désilets and Brendan Bowler for useful comments, as well as the anonymous referee of  Gagné et al. (2015c) , who suggested the inclusion of a parallax motion correction in the BANYAN tools. This research made use of: the SIMBAD database and VizieR catalog access tool, operated at the Centre de Données astronomiques de Strasbourg, France  (Ochsenbein et al.