dataesr/scientific-paragraphs-categorization huggingface dataset:
Karagodin et al. Karagodin et al. (2020)  recently demonstrated an improved delineation of cardiac structures, including the LAA, with a new tissue transparency trans-illumination tool when visualising 3D echocardiographic images, comparing to standard 3D rendering in a system developed by Philips (Andover, MA). Most of these imaging tools to explore 3D LAA anatomies are based on stand-alone software but webbased frameworks with cloud-based engines are becoming modern and more flexible alternatives for medical image visualisation and analysis. The Virtual Implantation and Device selection in left Atrial Appendages (VIDAA) platform was recently developed, providing a clinician-friendly web-based tool to support the pre-operative planning of LAAO interventions  Aguado et al. (2018). It allows clinicians to interactively explore the LA geometry as a 3D mesh with different Computer-Aided Design (CAD) LAAO models, together with some morphological indices and the original CT images in MPR format.
(2018)  or sinus venous defects  Tandon et al. (2019) ;  Southworth et al. (2020). Nam et al. Nam et al. (2020)  used new functionalities of the 3D-Slicer Open-Source software (i. e. , link with VR headsets) to develop a tool for the virtual testing, selection and placement of trans-catheter device closures of atrial and ventricular septal defects. Narang et al. Narang et al. (2020)  recently demonstrated a reduction in measurement variability and time required when exploring 3D echocardiography and CT images in different cardiac pathologies, with users reporting easy manipulation of VR models, diagnostic quality visualisation of the anatomy and high confidence in the measurements. As for LAAO devices, the EchoPixel True 3D Virtual Reality Solution (EchoPixel, Inc. , Mountain View, California, United States) allows to visualise CT scans and perform a "device-in-anatomy" simulation for LAAO preprocedural planning  Sanon and Lim (2019).
Clinical data The clinical data used in this work were provided by Hospital Haut-Lévêque (Bordeaux, France), including AF patients that underwent a LAAO intervention and with available pre-procedural high-quality CT scans. Five of them were randomly selected. The study was approved by the Institutional Ethics Committee; patients gave the informed consent for having their data used for research purposes, including tasks such as the ones presented in this study. Cardiac CT studies were performed on a 64-slice dual source CT system (Siemens Definition, Siemens Medical Systems, Forchheim, Germany). Tube current was set to 120kV in patients with body mass index (BMI) > 27 and 100kV in those with BMI <27. Acquisition was set on end-systole using prospective ECG triggering, the delay being set in percentage of the RR interval in patients in sinus rhythm, and in ms in those with arrhythmia.
VIDAA: web-based exploration of 3D imaging Both CT scans and the LA meshes were introduced to the VIDAA platform for visualisation (as MPR and 3D, respectively) and morphological analysis (see Figure  2 ). The 3D surface mesh of the LA can be visualised with different levels of transparency, both in solid and wire-frame formats. Some landmarks relevant to LAA interventions such as the circumflex artery, can be manually selected by the user. The centreline of the LAA was computed with the Python's VMTK library 2  from the centre of the LA mesh to a point on the LAA tip, the latter interactively selected by the user. Perpendicular 2D contours along the resulting centreline were then obtained to estimate morphological measurements on the LAA (i. e. , maximum and minimum LAA diameters). These measurements were also visualised in 2D maps and a graph along the centreline depth to better identify local size variations in the LAA.
Its cost was of 1,239 euros. Image processing outside the platform was performed using Python libraries. Once uploaded into VRIDAA, the user can interact with the 3D meshes by using the HTC Vive Pro controller to freely move it (6 degrees of freedom, i. e. , rotations and translations) or zoom it in order to navigate inside the patient's LA. In its current implementation, the VRIDAA platform is intended to be used with the possibility of moving within the virtual environment. Thus, a clear space of around 2 m x 1. 5 m is required, as can be seen in Figure  4. All meshes and images were uploaded to VRIDAA be- fore the practical session with participants. In VRIDAA, the centreline was not selected by the user; each case had a centreline previously generated in the web-based VI-DAA platform, as well as the measurements and the proposed devices, which were transferred into the VR platform.
In-silico fluid simulations The participants were presented with the visualisation of in-silico fluid simulations in the studied LA anatomies and including any possible LAAO device to be implanted, using the Ansys Discovery Live (ANSYS Inc, USA) software, under the Academic License (i. e. , free of charge). It includes a GPU-based Lattice Boltzmann method that allows almost real-time simulations, once each case was set-up. Therefore, the participants could manually choose a given device (i. e. , type, size) and place it in a given position to analyse resulting blood flow patterns, iterating as many times as desired. The volumetric meshes required for the fluid simulations were generated from the 3D surface models using the Gmsh 4. 5. 4 software 3. The final meshes were around 800 thousand elements for all cases.
Afterwards, the web-based VIDAA platform followed, since it is similar to some of the most advanced software solutions commercially available in the market (e. g. , 3mensio). Next, 3D printing and VRIDAA were presented to incorporate data visualisation with enhanced depth perception, starting with 3D printing since most physicians are more familiar with it. Finally, the in-silico simulations were shown in the Ansys Discovery Live software to include functional information complementary to the structural knowledge provided by the other technologies.
CT imaging The visualisation of CT medical images was optional since some of the physicians do not work on their daily basis with CT measurements. Although it was not assessed in SUS questionnaire, CT visualisation was offered since it is the gold-standard technique to explore LA anatomy, thus useful to plan LAAO interventions. Moreover, there were questions related to CT use in the general questionnaire. Physicians could explore the CT medical images with the Open-Source ITK-Snap software 4 to: (1) browse through the CT slices for inspecting the LAA shape and other anatomical landmarks such as the circumflex or the ostium; and (2) take measurements of these anatomical landmarks.
e. , which device was implanted, clinical output). Most participants (5/6) were familiar with 3D printing, having tested it before. Moreover, only one participant did not know about the use of any of these technologies for LAAO planning, while only one knew about all of them. Not a single participant had tested the VIDAA and VRI-DAA platforms before the practical session and only two physicians had some experience with fluid simulations beforehand, although not with the Ansys Discovery Live software.
Additionally, based on the SUS questionnaire, VIDAA was fast and intuitive, with several manual steps but with a fast learning curve. Participants stressed the added value of the web-based platform in complex cases, proposing to incorporate functional information from fluid simulations for a more complete solution. The current commercial solutions comparable to VIDAA include stand-alone 3mensio Structural Heart software (Pie Medical Imaging, Bilthoven, the Netherlands),or Materialise Mimics (NV, Leuvren, Belgium) which include MPR visualisation, 3D rendering and 3D surface visualisation and FEops (FEOPSnv, Gent, Belgium), which provides simulations of device deployment. The VIDAA platform provides a more comprehensive and interactive morphological characterisation of the LAA, as well as interaction with 3D models of the LAA devices in a web-based environment that does not require any software installation and easily allows multi-centric studies and collaborative decisions.
Acknowledgements The authors of this manuscript want to thank the physicians,  Dr L. S. ,  Dr X. M. ,  Dr L. A. ,  Dr P. L. and  Dr V. A. , who accepted our invitation to take part in this study as participants. This work was supported by the  Spanish Ministry of Science, Innovation and Universities  under the Retos I+D ( RTI2018-101193-B-I00 ), the  Maria de Maeztu Units of Excellence  ( MDM-2015-0502 ), the  Formation of Doctors  ( PRE2018-084062 ). Additionally, this work was supported by the  H2020  EU  SimCardioTest  project (Digital transformation in Health and Care  SC1-DTH-06-2020 ; grant agreement No. 101016496 ).
NetSquid is a software tool which provides a platform for simulating quantum networks and quantum computing systems  18. This software enables simulation of quantum networks considering various aspects such as physical layer characteristics and control plane. The design of NetSquid is based on discrete-event simulation, which provides us a powerful tool to simulate the decoherence of quantum states by time and analyse the noise in quantum systems accurately. For instance, time-dependent noise affecting the quantum states stored in a quantum memory can be simulated effectively. In this paper, we use NetSquid to simulate several quantum protocols and analyse their performance in the presence of various imperfections in the system. In the following sections, benchmarking of quantum money protocol, W-state based anonymous transmission, VBQC, and QDS are presented.
Such multiscale methodology allows to simulate with atomic resolution the evolution of liquid-solid interfaces during LA, enabling one to account for all types of features which cannot be captured using a fully continuum description. The formalism presented here is applicable to any system where the atoms kinetics depends strongly on an external space-and/or time-dependent field, such as temperature or strain. First, we present the theoretical details of the methodology. Then, a benchmark against continuum phase-field models and experimental data for an LA process of a Si(001) surface is provided, which validates the approach. The code is then applied to study the LA process in the two cases of homogeneous and inhomogeneous nucleation, varying laser fluence or pulse duration, revealing how the liquid Si nuclei evolve during laser irradiation, leading to coalescence for high nuclei densities.
KMC model The KMC formalism used in our multiscale method is implemented in the MulSKIPS code  30. The solid-liquid interface evolution in MulSKIPS KMC framework is regulated by the balance between solidification and melting events, whose rates are expressed as  39, 40  : ν ls ¼ ν ls ðr; tÞ ¼ ν 0 Á f ðTÞ Á exp À2E n k B T M ( 3 ) ν sl ¼ ν sl ðr; tÞ ¼ ν 0 Á exp Àn Á ðΦ s À Φ l Þ k B Tðr; tÞ (4) where ν 0 is a constant prefactor, T M is the melting temperature (T M = 1688K for Si), n is the number of bonds which an interface site forms with atoms in the solid phase, and Φ s -Φ l is the difference between the bond energy of two atoms binding in the solid (Φ s ) and liquid phases (Φ l ) (Φ s -Φ l = 0. 96 eV for Si  41  ). E n is the energy barrier needed to solidify a liquid atom in a ncoordinated KMC site, with E n = 2 ≡ Φ s -Φ l to ensure equilibrium for a flat interface at T = T M.
The sequence in Fig. 4a  (see also Supplementary Movie 1) shows that the melting front drops ~50 nm along z after roughly 170 ns since the beginning of laser irradiation. It can be seen that the interface, as expected given the homogeneous nucleation, remains quite flat for the whole pulse duration, also during the resolidification. In Fig. 4b  the maximum value of temperature T max ðtÞ in the whole FEM domain is plotted as a function of time, for three values of laser energy density, namely 1. 8, 2. 0, and 2. 1 J cm -2. Such maximum is located in air right above the initial solid Si surface. These profiles are plotted together with the corresponding curves obtained with standard 1D phase-field simulations performed with the same geometry and optical parameters, using the technology computer-aided design (TCAD) simulation package LASSE Innovation Application Booster (LIAB)  17.
8 nm size along z, was used for the simulations with 1. 6-2. 1 J cm -2. This was enlarged up to 108. 8 nm to enable 2. 2-2. 3 J cm -2 and to 160. 2 nm to enable 2. 4-2. 5 J cm -2 , while keeping the cell xy-area constant. We find that the results of the FEM-KMC simulations are in reasonably good agreement with experiments over the whole regime of fluences. The slight deviations of FEM-KMC and 1D phase-field results from experiments may be attributed to the likely larger uncertainty in meltdepth determination close to the melting threshold and/or to the occurrence of non-ideality in the measured samples. From a numerical point of view, an important advantage of the code relates to the computation of the heat exchanged during melting throughout the self-consistent FEM-KMC cycle. As already mentioned in "Results: multiscale FEM-KMC approach", here the main difference with respect to other LA models is that the latent heat Q(t) exchanged at every time step can be computed exactly by tracking the phase-changing volume ΔΩ(t) at every KMC step, which is now directly accessible with atomic resolution.
METHODS Simulations The multiscale simulation tool developed in this work is distributed as part of the MulSKIPS software package  [30] [31] [32]. Internally, it is based on an electromagnetic-thermal solver, implemented with a finite element method (FEM) within the FENICS computing platform  29  , and a KMC solver, implemented with the MulSKIPS Fortran engine, coupled to the FEM solver by means of PyMulSKIPS, a Python interface distributed with MulSKIPS. The 1D phase-field simulations are performed using the TCAD simulation package LIAB  17.
The paper briefly describes the tight-packed lattice experimental program performed at the Valduc Research Centre, which is at the origin of these concerns. Then it proposes a simple model on which to apply simulations of rod positioning to be performed with MORET 5 Monte Carlo code using the Prométhée tool. Results demonstrate that use of Monte Carlo methodologies provide more realistic uncertainty estimates in fuel pitch that are consistent with repeatability/ reproducibility experiments. The current comparisons use light water reactor systems, which is directly relevant to some small modular reactor designs. However, accurate prediction and estimate of uncertainties in pitch for advanced reactor systems is also relevant. The application of unrealistic uncertainty analysis methods can incur larger margins in advanced reactor design, safety, and operation than are necessary.
The MORET 5 monte carlo code Calculations were performed using the MORET 5 continuous energy Monte Carlo code. It is a 3D MC code for neutron transport developed at IRSN for criticality safety assessments. It employs continuous energy cross sections derived from JEFF-3. 1 evaluated nuclear data files  (Koning et al. , 2006). Typically, each calculation k eff was run to achieve a precision of ±. 00010 Δk eff (±10 pcm). The bold values are the total uncertainty, which was derived from the individual component uncertainties listed above them in the table.
Description of prométhée tool Prométhée is a grid computing environment designed to provide engineering methodologies relevant for any available code. The Prométhée system is composed of a Graphical User Interface (GUI) designed to provide ergonomics features for a computing software input data engineering algorithms (for instance uncertainties propagation methods). Then, calculations are remotely performed on servers. The parameterization of rods' location in the lattice was performed using Prométhée.
Monte Carlo sampling with MORET 5/ Prométhée Two kinds of MC simulations were tested during this work. The first one uses the MORET 5 code combined with the Prométhée workbench to do the MC sampling. A first step consisted in comparing the traditional method varying the pitch value according with a chosen distribution law. The variation was then propagated in terms of Δk eff for 100 different rod positioning maps corresponding to 100 different simulations. Then, the distribution of k eff was observed. A second step consisted in comparing the traditional method with a simulation on the position of rod according to ISO GUM S1 standard procedure. Instead of increasing artificially the distance between rods of the same quantity, the position of  rods in their holes was sampled independently 100 times (this number was chosen arbitrarily but was found sufficient to have a Gaussian distribution, as shown in Figure  7 , which was confirmed by the value of the bootstrap) for the 35 × 35 array and propagated in terms of Δk eff using the ISO GUM S1 standard procedure, which corresponded to a more realistic approach.
Traditional and refined traditional methods The MORET 5 results for the three lattice pitches of the benchmark are given in Table  4. The JEFF-3. 1 evaluation is used for the nuclear data library. Quite similar results are obtained with the two traditional methods, the results of the refined traditional being a little lower. Moreover, for a same pitch variation, the propagated 1σ uncertainty is greater for the lowest pitch, which was predictable since a tight-packed lattice of rods is more sensitive to a pitch variation than a lattice at the moderation optimum.
Comparison of the different methods For the three pitches of the benchmark and a shift of the position of rods corresponding to the 1σ uncertainty of rod position, calculations were performed with the continuous energy Monte Carlo MORET 5 code and the various methods presented beforehand. These results are reported in Figure  9. It can be shown that the traditional methods lead to higher Δk eff values than the methods based on MC sampling or the URAN card in MCNP6. The reduced uncertainty using the URAN card with MCNP is consistent with similar comparison studies performed for the Neutron Radiography (NRAD) reactor  (Bess, Maddock, and Marshall 2014). The discrepancy is more important for smaller pitches. In fact, at moderation optimum, the MC sampling methodology is not necessary since quite consistent results are obtained.
Comparison with experimental results A way to have access to this information is to make comparisons with experimental results. Repeatability/reproducibility experiments can allow such comparison. This was done for another proprietary program called MIRTE (Matériaux en Interaction et Réflexion Toutes Epaisseurs)  (Leclaire et al. , 2014)  whose aim was the validation of the calculation of structural materials in thermal energy spectrum. This program involved the same UO 2 rods, with a 1. 6-cm square pitch (moderation optimum). The reproducibly experiment consisted in draining the water level from the tank, unloading the baskets containing the rod lattices, shake them, reload them and then perform a new critical approach. Such experiments addressed different uncertainties amongst them such as the critical height uncertainty and the rod position uncertainty.
Consequences of correlation factors 6. 1 Definition of correlation factors Correlation factors between experiments or between cases of an experimental series are key values for the determination of biases due to nuclear data. For many years now, various tools such as TSURFER for the SCALE 6 package (Wieselquist, Lefebvre, and Jessee 2020), WHISPER for MCNP, and MACSENS  (Fernex and Leclaire, 2022)  for the CRISTAL package  (Gomit et al. , 2015)  have implemented (or are implementing for MORET) a sensitivity on k eff capability and the Generalized Linear Least Squares Methodology (GLLSM) to evaluate biases due to nuclear data  (Broadhead et al. , 1999). To correctly assess the bias, one needs to know the correlation between experiments (or cases). These values strongly influence the result of the adjustment procedure and therefore the bias.
The impact of uncertainties in rod positioning is only one component of many that will need to be properly understood to satisfy regulatory requirements prior to advanced reactor deployment and operations. Ultimately, the uncertainties addressed in this paper might improve assessment of modular transportation of microreactors or fuel and their ultimate disposal; understanding biases and associated uncertainties when utilizing various methodologies and codes is imperative  (Tardy, 2019). The impact of rod positioning has been tested with various methods: the traditional one recommended historically by the ICSBEP working group, modifications to the traditional method, MC sampling using the MORET 5 code and the Prométhée computing environment, and the MCNP6 code with the URAN card to simulate the uncertain position of rods inside their grids.
At last, the validity of MC sampling calculations is ensured by the comparison with experimental results. Indeed, repeatability/ reproducibility experiments were performed in the framework of the MIRTE (Matériaux en Interaction et Réflexion Toutes Epaisseurs) program involving similar rods in a 1. 6-cm square-pitched lattice. It can be shown that the uncertain position of rods in their baskets leads to a Δk eff less than ± 0. 00020, which is in accordance with the results obtained via MC sampling with MORET 5/Prométhée or MCNP6/URAN. Monte Carlo sampling techniques show improvement in better prediction of actual uncertainties in light water reactor systems, which is directly applicable to many small modular reactor concepts in development. However, the application of such methodologies can apply towards advanced reactor design concepts, including microreactors, to mitigate overestimation of margins supporting safety and operations.
We present See360, which is a versatile and efficient framework for 360 • panoramic view interpolation using latent space viewpoint estimation. Most of the existing view rendering approaches only focus on indoor or synthetic 3D environments and render new views of small objects. In contrast, we suggest to tackle camera-centered view synthesis as a 2D affine transformation without using point clouds or depth maps, which enables an effective 360 • panoramic scene exploration. Given a pair of reference images, the See360 model learns to render novel views by a proposed novel Multi-Scale Affine Transformer (MSAT), enabling the coarse-to-fine feature rendering. We also propose a Conditional Latent space AutoEncoder (C-LAE) to achieve view interpolation at any arbitrary angle. To show the versatility of our method, we introduce four training datasets, namely UrbanCity360, Archinterior360, HungHom360 and Lab360, which are collected from indoor and outdoor environments for both real and synthetic rendering.
These views are then interpolated using a trained neural network. Many public synthetic datasets  [32] -  [34]  are used for this task. In contrast with both 360 • video and novel view rendering, but bridging the gap between them, our goal is to achieve camera centered, 360 • panoramic novel view interpolation. More precisely, our method allows using a single, ordinary camera to capture a few reference views of the real world and predict the intermediate views in between, achieving horizontal 360 • view synthesis from this sparse input. Hence we refer to our proposed approach as See360. Note that as opposed to 360 • video, we do not need any complex device to capture omnidirectional views for scene understanding. Our method also differs from novel view rendering since our goal is to capture the 3D structure of the surroundings rather than the structure of a single object.