dataesr/scientific-paragraphs-categorization huggingface dataset:
VRT 2 is based on the plasma radiative transfer package described in  Broderick & Blandford (2003 , 2004 ) and provides a modular framework for adding novel plasma distributions, radiative transfer mechanism, and spacetime structures. It was the basis for the images generated in, e. g. ,  Broderick et al. (2011)  and used in the analysis of  Broderick et al. (2016). It also natively interfaces with THEMIS, having been written in the same programming language (C++), in a similar style. Models based on VRT 2 within THEMIS include those listed below. In addition, the vacuum ray-tracing and radiative transfer package Odyssey described in  Pu et al. (2016b)  has also been incorporated within THEMIS. Based on the ray-tracing algorithm in  Fuerst & Wu (2004)  and the radiative transfer formula presented in  Younsi et al.
SED-fitted RIAF This is an image at a single wavelength associated with the radiatively inefficient accretion flow (RIAF) models described in  Broderick & Loeb (2006b)  and refined in  Broderick et al. (2011). This model employs a tabulated set of accretion flow parameters, obtained at different black hole spins and inclinations, that reproduce the observed compact radio SED of SgrA *. The model parameters are the dimensionless spin magnitude, a (in the range [0, 1]); the cosine of the inclination, q cos , ([-1, 1]); and the position angle, ξ ([-180°, 180°], as part of a model image). The accretion flow angular momentum is assumed to be aligned with the black hole spin. The intensity normalization may be included via the likelihood (see Section 6. 6). An example image from the THEMIS-integrated VRT 2 package is shown in Figure  3.
External Physical Models There is no intrinsic bar to including additional ray-tracing and radiative transfer packages within THEMIS. Doing so offers a number of benefits, including the ability to rapidly generate new models within THEMIS itself, efficient parallelization, and improved portability. However, native integration is not necessary. It is often initially faster, and occasionally necessary, to externally include modeling software. For THEMIS, this has been done for a number of existing packages: GRTRANS: A publicly available general relativistic, polarized radiative transfer code written in FORTRAN, described in  Dexter (2016)  and  Dexter & Agol (2009). GRTRANS and by extension also THEMIS are coupled to the HARM3D general relativistic, magnetohydrodynamic (GRMHD) code  (Gammie et al.
2003; Noble et al. 2006; Dexter et al. 2009; McKinney et al. 2014 ). ASTRORAY: A significantly extended version of the general relativistic polarized radiative transfer code written in C/C ++ based on Shcherbakov (2014) and substantially extended in  Gold et al. (2017). ASTRORAY and by extension THEMIS are coupled to HARM3D  (Gammie et al. 2003; McKinney et al. 2012 McKinney et al. , 2014))   Mościbrodzka et al. 2009 ) and is GPU capable. BHOSS: A publicly available general relativistic radiative transfer code described in Z. Younsi et al. (2019, in preparation)  written in Fortran 95/2003 (see also  Fuerst & Wu 2004; Younsi et al. 2012 Younsi et al. , 2016)). BHOSS and by extension THEMIS are coupled to the BHAC  (Porth et al. 2017; Olivares et al. 2018 ), HARM3D GRMHD code  (Gammie et al.
Note that "transforms" may be implemented intrinsically within models by choosing a convenient set of parameters. Likelihood evaluation is short-circuited on the evaluation of priors, i. e. , where the prior has zero probability (e. g. , outside the limits of a linear range), the likelihood is not evaluated but rather returns the appropriate vanishing value. This achieves two goals: first, THEMIS is made marginally more efficient by avoiding unnecessary computation, and second, permits priors to be used to avoid unphysical parameter combinations, where models may return nonsensical results, e. g. , negative densities passed to a radiative transfer code or black hole spin outside the range permitted by general relativity. Currently, THEMIS has only implemented priors and transforms of a single variable.
Code Performance As seen in many of the validation tests and example analyses presented in Sections 8 and 9, even for models with modest numbers of parameters, it is typical for the posterior probability distributions to be multimodal. As the models increase in sophistication, introducing additional physical freedoms and addressing various systematic uncertainties, this problem will be compounded by the need to explore high-dimensional parameters spaces. This is further complicated by the computational expense of numerically generating images of realistic astrophysical models. As a result, THEMIS has been designed to exploit the proliferation of modern HPC systems. Here we discuss the ways in which this has been, and may be, implemented, along with a description of THEMIS's scaling efficiency, demonstrating that it can run efficiently on very large machines.
2016 Chael et al. , 2018b , and available at github. com/achael/ eht-imaging). As a result, ρ ranges from 0. 3 to 3. 3, with most of the potential closure amplitude squares having ρ within 11% of unity. Therefore, even without prior knowledge about the visibilities that comprise the numerator and denominator of the closure amplitude, a similar procedure to that used for the closure amplitudes, where ρ≈1 is assumed, is well motivated. Given a value of ρ, either from the station SEFDs or setting it to unity,  Notes. a Ratio of V A,0 /σ A to V B,0 /σ B in the construction of the product distribution. b Maximum absolute difference, measured relative to probability maximum. c Fractional error in the location of the mode. d Fractional error in the width of the region containing 68%/95% of the cumulative probability.
This work was made possible by the facilities of the Shared Hierarchical Academic Research Computing Network (SHARCNET: www. sharcnet. ca) and Compute/Calcul Canada (www. computecanada. ca). Computations were made on the supercomputer Mammouth Parallèle 2 from University of Sherbrooke, managed by Calcul Québec and Compute Canada. The operation of this supercomputer is funded by the Canada Foundation for Innovation (CFI), the ministère de l'Économie, de la science et de l'innovation du Québec (MESI), the Fonds de recherche du Québec-Nature et technologies (FRQ-NT). This work was supported in part by Perimeter Institute for Theoretical Physics. Research at Perimeter Institute is supported by the Government of Canada through the Department of Innovation, Science and Economic Development Canada and by the Province of Ontario through the Ministry of Economic Development, Job Creation and Trade.
A. E. B. thanks the Delaney Family for their generous financial support via the Delaney Family John A. Wheeler Chair at Perimeter Institute. A. E. B. , P. T. , and M. K. receive additional financial support from the Natural Sciences and Engineering Research Council of Canada through a Discovery Grant. R. G. receives additional support from the ERC synergy grant "Black-HoleCam: Imaging the Event Horizon of Black Holes" (grant No. 610058). We thank Jason Dexter for helpful comments and suggestions. We further thank the following organizations and programs: the Academy of Finland (projects 274477, 284495, 312496); the Advanced European Network of E-infrastructures for Astronomy with the SKA (AENEAS) project, supported by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement 731016; the Alexander von Humboldt Stiftung; Black Hole Initiative at Harvard University, through grants from the John.
043. 513 ) and  Spinoza Prize SPI   78-409 ; the  New Scientific Frontiers  with  Precision Radio Interferometry Fellowship  awarded by the  South African Radio Astronomy Observatory (SARAO) , which is a facility of the  National Research Foundation (NRF) , an agency of the  Department of Science and Technology (DST) of South Africa ; the  Onsala Space Observatory (OSO)  national infrastructure, for the provisioning of its facilities/observational support (OSO receives funding through the  Swedish Research Council  under grant  2017-00648 ) the  Perimeter Institute for Theoretical Physics  (research at  Perimeter Institute  is supported by the  Government of Canada  through the  Department of Innovation, Science and Economic Development  and by the  Province of Ontario  through the  Ministry of Research, Innovation and Science) ; the  Russian Science Foundation  (grant  17-12-01029 ); the  Spanish Ministerio de Economía y Competitividad  (grants  PGC2018-098915-B-C21 ,  AYA2016-80889-P ); the  State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa " award for the  Instituto de Astrofísica de Andalucía  ( SEV-2017-0709 ); the  Toray Science Foundation ; the  US Department of Energy (USDOE)  through the  Los Alamos National Laboratory  (operated by  Triad National Security, LLC , for the  National Nuclear Security Administration of the USDOE  (Contract  89233218CNA000001 )); the  Italian Ministero dell'Istruzione Università e Ricerca  through the  grant Progetti Premiali 2012-iALMA  ( CUP C52I13000140001 ); the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No.
Following this rationale, we pooled data from our previous studies and performed simulations to estimate the minimal sample size required to achieve a power level of. 8 for the detection of the effect of suggestion in HHIs at a =. 05 (see supplementary material for details). This procedure revealed a modest effect size of hypnotic suggestion in HHIs (i. e. , R 2 GLMM(m) =. 14), while 13 HHIs were required to attain a power level of. 8 for a =. 05. Our current sample size aligns with these observations. When participants performed the task without occluders during controlled conditions, we aimed to recruit as many online participants as possible from psychology classes at McGill University. In contrast, the subset of individuals asked to complete the control task in our laboratory was comparable in size to both our HHIs and LHIs groups.
Our Adobe Flash® interface recorded, and immediately sent the measures to a php-MyAdmin password protected MySQL TM online database. The program recorded responses when participants depressed keys on a keyboard: the "F", "J", and spacebar keys for counterclockwise, clockwise and directionless motion for triangles and inverted triangles, respectively. Participants completed the task in two separate blocks: The first block comprised only diamond/square trials, while the second one included only the triangle/inverted triangle trials. We opted for this design because we wanted to avoid confusion and ensure that participants only considered the response option of directionless motion during triangle/inverted triangle trials. To ensure that participants understood the task well, we included two short training periods in the pre-assessment of MoTraK.
To ascertain comprehension, the post-assessment of MoTraK included no demonstrations, only three practice trials with feedback. Instructions emphasized both speed and accuracy. The overall task lasted about 15 minutes. Procedure for HHIs and LHIs. First, for testing performance without suggestion, we sent an email to all potential participants providing them with a URL of the web page hosting MoTraK and inviting them to complete the task online in a calm environment of their choice. The online consent forms informed participants of their right to withdraw from the study at any time and that information and data gathered, including response time and accuracy, would be used only for scientific research. We gathered demographic information, as well as IP addresses, which allowed us to identify and exclude participants, who completed the task more than once.
MATLAB© (Mathworks, MA; version R2017B) and the fitglme function fitted all regression models. We opted for the Laplace fitting method and selected the best fitting model via goodness-of-fit Chi-square test over deviance (α =. 05), and by evaluating the Bayesian Information Criterion (BIC). Post-hoc evaluations were performed using permutations pairwise t-tests (i. e. , 10000 permutations). We similarly compared task improvements for HHIs against several control conditions (Figure  2 ). We first compared the performance of HHIs without and with the suggestion against individuals who performed the same task online and in the laboratory. We relied on non-parametric two-tailed permutation tests (i. e. , 10000 permutations) to compare mean accuracy rates. Our goal was twofold: first, to validate that performance was no different between HHIs and a matched-controlled group prior to receiving the suggestion; second, to demonstrate that the improvement in HHIs marked a significant departure from baseline performance following suggestions.
In this way, we contrasted how visual imagery measured up against the actual perception of the occluders. Lastly, note that we further computed the Jeffrey-Zellner-Siow Bayes factor to evaluate evidence in favor of the null hypothesis using the default Cauchy r scaling value of. 707 (Rouder, Speckman, Sun, Morey, & Iverson, 2009). Bootstrapped confidence intervals were computed using Matlab's Bootfun algorithm. Figure  1. A) Schematic of the experimental task where we presented four or three moving lines in the diamond/square and triangle/inverted triangle trials, respectively (see Methods section). In line with the training trials and visual demos, we suggested to both HHIs and LHIs that they imagine the occluders at the vertices of the moving lines. Participants indicated the direction (i.
Acknowledgments M. L. acknowledges a fellowship from  Fonds de Recherche du Québec -Nature et Technologie  and support from the  Bial Foundation. J. D-C. acknowledges a fellowship from  NSERC. This work was supported by a grant from the  Canadian Institute for Health Research , the  Bial Foundation , and  Canada Research Chair program  to A. R. The authors thank  Noémie Aubert-Bonn  and  Alexandra Fischer  for their valuable contribution for coding the task, collecting the data and performing a primary exploration of the results.
The Europlanet-2020 programme, which ended on Aug 31 st , 2019, included an activity called VESPA (Virtual European Solar and Planetary Access), which focused on adapting Virtual Observatory (VO) techniques to handle Planetary Science data. This paper describes some aspects of VESPA at the end of this 4-years development phase and at the onset of the newly selected Europlanet-2024 programme starting in 2020. The main objectives of VESPA are to facilitate searches both in big archives and in small databases, to enable data analysis by providing simple data access and online visualization functions, and to allow research teams to publish derived data in an interoperable environment as easily as possible. VESPA encompasses a wide scope, including surfaces, atmospheres, magnetospheres and planetary plasmas, small bodies, heliophysics, exoplanets, and spectroscopy in solid phase.
This system relies in particular on standards and tools developed for the Astronomy VO (IVOA) and extends them where required to handle specificities of Solar System studies. It also aims at making the VO compatible with tools and protocols developed in different contexts, for instance GIS for planetary surfaces, or time series tools for plasma-related measurements. An essential part of the activity is to publish a significant amount of high-quality data in this system, with a focus on derived products resulting from data analysis or simulations.
Introduction: Modern space borne instruments often produce large and complex datasets, especially on long-lived missions. Detailed data analysis requires new ways to handle the data, in particular to locate specific observing conditions easily and efficiently. Virtual Observatory (VO) techniques have been developed in Astronomy during the past 15 years to address similar issues; they can be adapted to this context provided they are extended to take into account the specificities of Solar System studies. The VESPA (Virtual European Solar and Planetary Access) data access system focuses on applying VO techniques and tools to Planetary Science data, and supports all aspects of Solar System science  (Erard et al. 2018). VESPA was developed in the framework of the EU-funded Europlanet-2020 programme, which started Sept 1 st , 2015 and will be pursued in the recently selected Europlanet-2024 programme for another 4-year period.
The objectives of VESPA are to facilitate searches both in big archives and in sparse databases, to enable data analysis by providing simple data access and on-line visualization functions, and to allow research teams to publish derived data in an interoperable environment as easily as possible. This system relies on studies and developments led in Astronomy (International Virtual Observatory Alliance, IVOA), Solar Physics (HELIO), Space Physics (SPASE), and space data archives (International Planetary Data Alliance, IPDA); it is responsive to FAIR principles and focuses on science-oriented description of data. We hereby provide a summary of achievements at the end of Europlanet-2020. Data services: the VESPA architecture (Fig. 1 ) consists in a new data access protocol, a specific user interface querying the available data services, and intensive usage of standards and tools developed for the Astronomy VO  (Erard et al.
VESPA mostly focuses on derived data, typically associated to publications. Some of these derive from a significant preparation phase, e. g. : DynAstVO which computes orbital parameters for Near Earth Asteroids; APIS which provides data on planetary aurorae derived from several archives; SSHADE which currently gathers 17 experimental databases of spectroscopy of minerals, organics, ices and cosmo-materials in a consistent and very detailed format; solar feature catalogues from the HELIO EU programme; a refined and corrected version of the Robbins & Hynek Mars craters database (being published) will also be accessible, together with the original database. Some large existing data archives also received an additional EPN-TAP interface during the programme, in particular: ESA's Planetary Science Archive (PSA), which gathers data from all European space missions  (Besse et al 2018) ; planets and satellites data collected from the Hubble Space Telescope archive in Canada; planetary plasma data at CDPP, Toulouse, which includes many unique derived products; the IAU Minor Planet Center which distributes the properties of most minor bodies; the Encyclopaedia of Extra Solar Planets, which is the world-wide reference in the field; several ground-based solar archives (currently BASS2000 and CLIMSO) also distribute their data through VESPA.
To favour the emergence of this kind of material, VESPA has organized a yearly call to the community to select projects of interest, typically associated to a publication; 4 or 5 selected teams were invited to a one-week workshop to design and install the service in their institute 2. Several services providing amateur astronomy data were also selected at the onset of the programme for implementation in research institutes, including PVOL (planetary images) in EHU/Bilbao  (Hueso et al 2018)  and RadioJove (Jupiter radio measurements) at Paris Observatory. In addition, a special type of services will gather tables of VOevents produced by alert systems in various fields  (Cecconi et al. 2018b). According to the contributory nature of the VO, any team can publish EPN-TAP services in the IVOA registry.
A validator is available to certify TAP compliance, but manual checks are also performed to ensure consistency of EPN-TAP services prior to publication. By default the VESPA portal uses a local registry listing only services certified by the core VESPA team. The status of published services is monitored automatically through Nagios to inform data providers in case of problems. Data access: EPN-TAP data services are best queried from the VESPA portal (Fig. 2 ), an optimized search interface providing specific user support (http://vespa. obspm. fr). Alternate access modes are discussed below. In the frame of TAP, data services consist in a list of "granules", or data elements, described by a series of parameters. EPN-TAP defines a set of mandatory parameters that introduce metadata for individual granules; this scheme is inspired by the IVOA ObsTAP protocol for observational Astronomy datasets.
EPN-TAP parameters provide the observational and instrumental conditions of acquisition, accounting for the specific diversity and complexity of Planetary Science: ranges along several axes (spatial, temporal, spectral, photometric), measurement type, origin of data, and several references. Localisation can be provided in various coordinate systems (celestial or planetary coordinates, either body-fixed or rotating). Time is provided in Julian days, but also as local time or season if relevant. The benefit of EPN-TAP is that all data services are described uniformly with parameters that are relevant for the science user. The VESPA portal queries all registered data services at once based on the mandatory EPN-TAP parameters, and returns individual granules matching the query; this allows in particular the user to discover unknown data content in the field of interest.
In addition, thematic extensions are defined to describe new fields uniformly (e. g. , lab spectroscopy). Specific parameters may also be made-up to describe individual services with more details; when querying a single service, they can be used to identify granules more precisely. Independently from VESPA and the data distribution context, the EPN-TAP Data Model (Erard et al, submitted to IVOA) can also be used or adapted to describe private databases in a consistent way, e. g. to share proprietary data inside an experiment team. The VESPA portal also supports other query systems. User queries are converted and forwarded to space agencies' PDS (Planetary Data System) archives: ESA and JAXA are queried via the PDAP protocol from IPDA, and NASA through its PDS keyword-search interface. Owing to limitations in these protocols, such queries are performed only at dataset level.
EPN-TAP services can be accessed via other search interfaces. An EPN-TAP library was developed and included in several tools (3DView, CASSIS, and AMDA) to issue direct queries from these environments. Since EPN-TAP relies on the more general TAP mechanism, EPN-TAP data services can also be accessed individually via standard TAP clients; these include general query interfaces (e. g. , TAPHandle) as well as standard VO tools (e. g. , TOPCAT, Aladin, etc). Programmatic access is possible using existing libraries in python (pyvo), IDL (SSW), or shell scripts (TAPsh) -making such data services handy for pipeline processing. Finally, a map-ping app prototype was also developed to explore new types of access from mobile and computer uses. EPN-TAP tables either provide links to data files, or include the data itself when they consist in a small set of scalar quantities.
A variety of tools are available to handle the data in the VO. Adequate VO tools are identified through data description parameters, which not only indicate a file format but also specify dimensions, units, and physical quantities, based on IVOA Data Models adapted for VESPA. For instance, images and spectra will open in different tools, and the spectral tools will recognize spectra in radiance or in reflectance, and handle them differently. Tools: Selected metadata can be transferred from the VESPA portal to VO tools via the SAMP protocol from IVOA. Standard VO tools are connected to the VESPA portal so that they readily display metadata, e. g. , spatial footprints are plotted on a 3D sphere in Aladin or Mizar; other metadata such as local time or instrument modes, can be plotted in 2D or 3D with TOPCAT (Fig.