dataesr/scientific-paragraphs-categorization huggingface dataset:
C2. 3 Sensitivity analysis In the original algorithm, the thresholds must all be satisfied in the same gridpoint. However, it was used on ERA-Interim data interpolated onto a 1°× 1°grid, whereas ERA5 data presents itself with 0. 25°× 0. 25°grid points. One can expect this higher resolution might allow for the formation of an eye in the circulation, so that all the thresholds might be verified in the wall rather than in the center of the circulation. We test 7 values for r thresholds : 0°(thresholds must be passed at the center), 0. 5°, 1°. The 350km range in  Bell et al. 2018 corresponds to 3°, whereas the [400; 600km]  range in  Tory et al. 2013 correspond to [3. 5°; 5. 5°]. In UZ, the range is set to 8°. We test r range values between 3 and 8°. To assess the sensitivity of the detection to these thresholds, we compute the number of tracks detected.
Acknowledgements. The research is supported by public funding to the  CEA  and  CNRM. S. Bourdin  and  S. Fromang  were also financially supported by the  EUR IPSL-Climate Graduate School  through the  ICOCYCLONES  project. J. Cattiaux ,  F. Chauvin  and  W. Dulac  were also financially supported by the  CNRS/INSU  trough the  LEFE/CYPRESSA  project. The authors are grateful to  K. Hodges  for providing the TRACK dataset, for insightful scholar discussion and literature provision and for his review of an earlier version of this manuscript. The authors thank to  P. Ullrich  and  C. Zarzycki  for their help regarding TempestExtremes.
time t i that are located closer than 300 km from the point d i. Of course, it is possible that such points do not exist in O. The subset of points of O that have been associated with any point in D is noted O D-paired. It is composed of |O D-paired | elements. There are three possibilities: Consider the case of a given detected track D composed of n points (d 1 , d 2 ,. d n ) defined at times (t 1 , t 2 ,. , t n ). The observations O consist of a database of tracks and can be seen as a collection of points at given times. For each point d i (t i ) of the track D, we associated those points of O at.
Code and data availability. ERA5 data is available on the Copernicus Climate Change Service Climate Data Store (CDS, https://cds. climate. copernicus. eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels). The IBTrACS database is provided by NOAA at https://www. ncdc. noaa. gov/ibtracs/. All the scripts used to produce the present paper's results are available at https://doi. org/10. 5281/zenodo. 6424432. These include the code to run the UZ and OWZ trackers and the original TRACK and CNRM databases, the code for the post-treatment and the tracks matching python scripts for the whole analysis, the code to reproduce the figures, and finally, a copy of the v. 0. 5 of the dynamicoPy package used in the python scripts (https://github. com/stella-bourdin/dynamicoPy). DetectNodes (or equivalent) Local extremum Candidates criteria Merge distance UZ SLP minimum SLP closed contour 2 hPa in 5.
, 2015). The fraction of dimers formed in the lag phase of aggregation is by increasing order WT < A53T < A30P as measured by FRET. The A30P variant generates the largest population of B oligomers at the end of the lag phase of fibrillation  (Tosatto et al. , 2015). These data  (Lv et al. , 2015; Tosatto et al. , 2015)  taken together indicate a significant structural difference between A30P dimers compared to WT and A53T dimers. Differences between WT and mutant dimers were also observed by single-molecule AFM force spectroscopy at low pH (promoting aggregation)  (Krasnoslobodtsev et al. , 2013). Mutiple segments' interactions between the monomers are favored in A53T and E46K compared to the WT as reflected by a larger number of multiple rupture force events  (Krasnoslobodtsev et al. , 2013) , whereas A30P favored single segment dimerization compared to the WT  (Krasnoslobodtsev et al.
(2021). Each trajectory was started with 2 fully unfolded monomers separated by a distance of 25 Å. The integration time step in UNRES is 4. 9 fs corresponding to an effective actual time step of about 4. 9 ps  (Khalili et al. , 2005). The convergence of each trajectory was monitored by computing the probability density of contacts of each residue, resulting in 30 million steps (effective time scale of 147 microseconds) of consolidated data out of 84 million steps (effective time scale of 412 microseconds) of simulation for each trajectory. The Cartesian coordinates of C α and SC beads were saved for every 1,000 integration steps. Only structures at 300 and 310 K (40 trajectories) are reported here as they are close to the physiological temperature. Since the simulations are performed on two monomers, both isolated non-interacting monomer conformations and aggregated monomers were observed in the converged MD trajectories.
A dimeric conformation was defined as two monomers with more than 10 pairs of residues with at least one intermolecular distance between their C α atoms smaller than 5 Å. This cut-off value was chosen because the average distance between two residues in an intermolecular β-sheet of an α-syn fibril is 4. 8 Å (PDB ID: 2n0a). With this dimer definition, the fraction of dimers out of all the conformers simulated at 300 and 310 K is 31% for the WT, 23% for A30P, 29% for A53T, and 35% for E46K, respectively. The formation of dimers is increased for the E46K variant and is reduced for A30P (significantly) and A53T (weakly) mutants. The dimeric state of each protein is finally described here by about 300,000 structures extracted every 1,000 integration steps from the converged part of the replica exchange MD trajectories at 300 and 310 K, representing a sampling on an effective time scale of 1.
Therefore, we compare the mean contact curves with the location of intermolecular βsheets computed by CUTABI in two different experimental in vitro structures of WT α-syn fibrils (PDB IDs: 6ssx and 2n0a) in Figure  2. The peaks at Y39 and V49-A53 in MD are within a region of β-sheets in both experimental WT fibril structures and the peaks at A76 and I88-A90. A more precise comparison between intermolecular β-sheets found in MD and these structures will be examined in Figures  6, 8.
Dimers With Fibril Native Contacts (Dfncs) Contact maps of the WT and mutants show contacts along their diagonal as in the experimental structures of fibrils (PDB IDs: 6ssx and 2n0a). To identify conformations belonging to the diagonal of the contact maps, we extracted from the dimer statistics a sub-ensemble of dimers with Nfcs. We define a dimer with fibril-like native contacts (Dfncs) as a dimer conformation that has at least 5 consecutive intermolecular contacts made between residues with the same indices at a contact distance less than 5Å. This value was chosen as the distances between native contacts in fibrils are 4. 9Å and 4. 7Å in the measured structures with PDB IDs 6ssx and 2n0a. We may consider the Dfncs ensemble as conformations that are the most probable pre-formed fibrils in the present work.
expasy. org/protscale/) using a window of 15 residues and a linear interpolation with a weight of 0. 10 for the window edges is also represented (dotted line) for the WT. The red and green rectangles on the upper dotted bars describe the locations of the intermolecular β-sheets identified by CUTABI in the experimental structures of α-syn fibrils with the PDB IDs 6ssx and 2n0a, respectively. peaks with a probability near 1 meaning residues pertaining to this type of secondary structure in all Dfncs conformations. On the contrary, all residues above position 50 have a totally negligible probability to form an intra-molecular β-sheet in Dfncs. Unlike the ensemble of WT dimers for which intermolecular β-sheets can be found nearly everywhere along the sequence (Figure  6 ), in the Dfncs sub-ensemble, they are found only for residues 43-51 (N-terminal region), 69-95 (NAC region), and 99-100 and 134-135 (C-terminal region).
, 2013). These experiments were performed at low pH to increase the aggregation propensity of α-syn and with the additional mutation A40C needed to hang one of the monomers on the AFM tip and the other on the surface. Contour lengths of the  dimers were extracted from force-distance curves. They were interpreted as total lengths of stretchable parts of α-syn molecules that are not involved in dimeric interaction and, thus, as the sum of the total length from the C-terminal anchor point to the first residue of a dimerization region in each monomer. The data show a multi-peak distribution of contour lengths  (Krasnoslobodtsev et al. , 2013) , which might reflect the multiple minima observed in Figure  1 , as the contour length of a dimer conformation is related to the number of intra-molecular and intermolecular contacts.
, 2021) , as α-helices and β-sheets have been well described by Raman fingerprints. Such data are not available so far. In the present simulations, the ensemble of heterogeneous dimer conformations is divided in a majority of disordered dimers and a complementary minority of Dfncs for both the WT and mutants. Dfncs could be identified by spectroscopy. Indeed, the percentage of parallel intermolecular β-sheets is characteristic of Dfncs as it is significantly larger than the one in monomers and in disordered dimers (Table  2 ). This result agrees with FTIR spectroscopy measurements indicating that WT α-syn fibrils have a majority of parallel β-sheets, contrary to oligomers which show a majority of anti-parallel β-sheets  (Chen et al. , 2015). The total amount of β-sheets estimated from FTIR  (Chen et al.
FUNDING The calculations were performed using HPC resources from  DSI-CCuB (Centre de Calcul de l'Université de Bourgogne ) and 588-processor Beowulf cluster at the  Baker Laboratory of Chemistry and Chemical Biology, Cornell University. This work is part of the project  NANO-NEURO-MED  ( 2019-2022 ) supported by the  EIPHI Graduate School  (contract  ANR-17-EUR-0002 ), the  Conseil Régional de Bourgogne Franche-Comté , and the  European Union  through the  PO FEDER-FSE  Bourgogne  2014/2020  programs. This work is supported by a grant from the  National Institutes of Health  (Grant no. R01GM14312 ).
NLB also act as the main contact author/corresponding author of the present study. We devised an a priori protocol, as recommended. This can be accessed upon written request to the corresponding author. Stage 2: Identification of relevant literature and literature search strategy Two major scholarly electronic databases were consulted: namely, MEDLINE (accessed via PubMed's freely available interface) and Scopus (Elsevier). They were mined since the inception of the infectious outbreak, with no language restrictions. The search string consisted of two major components: para-athletes/athletes with disabilities and COVID-19, with synonyms/variants properly linked by using Boolean operators. "Medical subject headings" (MeSH) terms and wild-card (truncated words) options were used when appropriate.
Any study design was eligible for inclusion: retrospective, prospective, questionnaire-or test-based, quantitative, qualitative, or mixed-method studies (S). Stage 4: Mapping out the data, data charting, and extraction An Excel spreadsheet contained information on how and which relevant data to extract. Then, we utilized the "Research Electronic Data Capture" (REDCap) software to store the retrieved articles (both deemed eligible for inclusion and those finally included in the present scoping review) and assist/ facilitate data extraction. REDCap is a secure, web-based platform that efficiently supports and enhances data capture for research purposes  (Westphaln et al. , 2021). Moreover, since our team is highly multidisciplinary and diverse, REDCap allows the inclusion of multiple users within projects.
Search strategy item Details for tracking and monitoring data manipulation and exportation. Also, REDCap supports and facilitates data exportation into many types of statistical software for their further processing and analysis  (Westphaln et al. , 2021). These functions allow REDCap to properly accommodate all the processes of full-text review and data extraction/manipulation for large and diverse research teams. Data extraction quality was checked by computing the pooled kappa statistics as a quantitative measure of the inter-rater reliability/agreement, as recommended by  Tricco et al. (2015). Stage 5: Data collating, summary, synthesis, and reporting Data extracted were tabulated and synthesized in a narrative fashion. Major topics/themes were identified by means of thematic analysis and overviewed qualitatively.
Furthermore, we followed the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) extension for scoping reviews (PRISMA-Scr)  (Tricco et al. , 2018). Stage 6: Expert consultation/"consultation exercise" Our team identified experts on the topic of sports and disability, as well as on the topic of COVID-19. For this, we used cues from the identified literature, as well as cues from electronic databases (such as Scopus) which enable the visualization of a list of the top-cited and most productive scholars on a given topic. Some of these experts were consulted during the preparation of the manuscript to provide critical feedback on our work.
Outcomes of the literature search strategy The initial literature search yielded a pool of 123 items, by searching PubMed/MEDLINE and Scopus. After removing duplicates, seventy items were examined and 54 items were further discarded based on title and/or abstract. Sixteen studies were considered potentially eligible and were read in full text. Two studies were subsequently discarded with reason: one because it did not contain any original data concerning paraathletes  (Håkansson et al. , 2020) , and one because the population did not meet inclusion criteria (people with disabilities, but not athletes with disabilities)  (Kamyuka et al. , 2020). Subsequently, fourteen articles were retained in the present scoping review. Two further studies were retrieved by searching Google Scholar. The final number of included studies was sixteen.
11 ± deaf, 14%) 13. 70 years (with disabilities), 40. 23 ± 13. 73 years (able-bodied) Hu et al. (2021) Qualitative United States NA 29; 18 F, Thirteen different Athletic ↑ multiplicity of study (in-depth, 11 M; Paralympic sports (boccia, identity roles ↑ mental semistructured 18-62 years cycling, equestrian, (Disability adaptation interviews) fencing, goalball, Sport Athletic paracanoeing, Identity) powerlifting, rugby, sitting volleyball, swimming, taekwondo, wheelchair racer, and wheelchair tennis) Kaneda et al. Questionnaire- Japan From 16 April to 39 (20 with Para swimmers Mental health ↑ mental health ↑ (2021) based study 24 May 2020 disabilities; and apathy apathy 19 able- bodied); 8 F, 11 M Kaneda et al. Databased- Japan From August 17 to NA Paralympic athletes (versus COVID-19 ↑ than able- (2022) based September 5 and Olympic athletes) infection rate bodied athletes epidemiological from July 13 to survey August 8 Kubosch et al.
g. , NASA's James Webb Space Telescope  [100]  and ESA's EUCLID  [101] ). The most relevant ALADInO instrumental figures of merit are summarized in Table  1. Geometrical and acceptance estimations have been obtained using a simulation of the instrument detectors generated with the Generic Geant4 Simulation (GGS) package  [102]. The discussion of the technological solutions to achieve the target requirements of the ALADInO detector is part of the latter section of this document.
Each section of the ALADInO tracker roughly corresponds in terms of number of sensors, number of readout channels, and amount in silicon microstrip area, to the whole AMS-02 tracker. The exploitation of the AMS-02 heritage, consequently, strongly supports the need of a contained R&D activity to enable the construction of the ALADInO tracker. The sensor readout pitch, together with low-noise FEE, will ensure a position resolution more accurate than 5 µm for vertically crossing particles. Better performances have already been obtained by the PAMELA collaboration using shorter ladders but with a very similar implant pitch  [142]  (see Figure  10 , left). The AMS-02 collaboration has instead demonstrated the possibility to use long detector modules (up to 60 cm, similar to the 66. 5 cm length planned for ALADInO), obtaining a resolution better than 10 µm (5-8 µm) for Z = 1 (Z > 1) particles  [143].
At the time of writing, power consumption as low as 20 mW/cm 2 has been measured for payloads on instrumented areas as large as hundreds of cm 2. Prototypes of next-generation Fully Depleted MAPS are available with power consumption reduced to 5 mW/cm 2 for squared pixel layouts and <1 mW/cm 2 for striplike sensing elements (typical dimensions of 25 µm × 500 µm)  [155]. A striplike geometry is particularly relevant for an application where different spatial resolutions are required-for example, in ALADInO-to measure bending and nonbending coordinates. A number of features of MAPS are already used to further reduce power consumption. For instance, analog front-end and discriminator can be continuously active allowing to power the digital readout only for regions of interest for data acquisition.
Time-of-Flight (ToF) The ALADInO ToF system is designed to (a) measure the particle velocity magnitude, with an accuracy of O(%), and direction; (b) independently measure the particle charge at the entrance and exit surfaces of the tracking volume; and (c) provide the charged-particle fast-signal used to trigger the data acquisition. The design of the ToF system is based on previous PAMELA  [169]  and AMS  [170]  plastic scintillator ToF systems that had similar purposes. Plastic scintillator counters are detection devices ubiquitous in high-energy particle physics that allow for fast signal, high light-yields, long durability, and low cost. The ALADInO ToF system baseline design is composed by two rings above and below the tracking volume (i. e. , the outer and inner ToF). Each ToF ring is constituted by 10 identical planar detection units, i.
The ALADInO concept meets the constraints of space vectors that are available today for transport to L2, independently on the advances to improve the performances and carrying capabilities of space vectors. Considering the current propitious conditions that are already available nowadays in terms of instrumentation technology, space operation heritages, and space vectors, it is possible to envisage that the ALADInO pathfinder could be operating in the 2030s, opening the way for ALADInO operations in the 2040s. In a few years of operations, by 2050, ALADInO will have provided unique data to improve our understanding and possibly solve two of the most subtle yet prominent puzzles of the century: the missing antimatter in the Universe and the nature of Dark Matter. region far apart from the region where the particle deposits its ionization energy.
Figure6. Expected measurement by ALADInO (red points) for the flux of D (left) and 3 He ((right) as a function of kinetic energy per nucleon, in the scenarios of DM models (blue lines) consistent with available antiproton data [81, 112]  and astrophysical background with its uncertainties [113]. The best current upper limits are also shown [114, 115]. Antideuteron searches are and will be performed by AMS-02 and GAPS during the coming years. These instruments combined will leave untested a significant region of parameter space of DM models. The dotted lines show the ALADInO sensitivity level, for 5 years of exposure, over its optimal range of detection. The ALADInO measurements for the flux of 3 He in case of astrophysical background only are not shown since the 3 He flux would be approximately compatible with the ALADInO sensitivity.
Introduction The ITER divertor design has been supported by SOLPS calculations  [1] , which simulate plasma only in a domain restricted to the main scrape-off layer (SOL) connecting the inner and outer divertor targets, and do not extend to the first wall (FW)  [2]. Although active development is on-going to include this capability into the latest SOLPS-ITER version  [3] , to-date, plasma backgrounds for ITER on a numerical grid extending to all main chamber walls have been produced by extending an existing SOLPS main-SOL solution with the OEDGE code suite  [4]. As a consequence, no self-consistent solution for the whole ITER plasma boundary was available. The objective of this work is to provide such self-consistent up-to-the wall ITER simulations with the SOLEDGE3X fluid code  [5] , which by default includes a numerical grid extended to all plasma-facing components.
The output therefore includes the plasma background in the far-SOL, which is a key input for FW erosion and impurity migration studies  [6] [7] [8]. The SOLEDGE3X code is a multispecies fluid plasma solver including a Zhdanov fluid closure  [9, 10] , coupled to EIRENE  [11]  for kinetic neutrals. It can be used in 3D or 2D, both of which either in turbulent or mean-field transport mode. In the present work, only the 2D mean-field transport mode is used, assuming cylindrically symmetric plasma-facing components (no FW or divertor shaping included). This study is a follow-up to the first ITER cases executed with SOLEDGE3X  [12] , but goes further, focusing on the impact of enhanced far-SOL transport. It also includes two significant improvements: firstly, the plasma-neutral interaction model has been refined with the activation of neutral-neutral collisions in EIRENE, which were found to be essential when modelling the ITER divertor with SOLPS  [13] ; and secondly, the FW contour and magnetic equilibrium have been updated to match more recent machine design and scenario specifications.
This case is run on an updated geometry: the magnetic equilibrium is now taken from a recent DINA scenario  [16] , and the inner wall contour is radially displaced inwards to reflect a thickening of the inboard blanket for the purposes of neutron shielding. The simulation cases can be found with IMAS identifiers #135011 run 7 and #116000 run 2 respectively in the public ITER scenario and machine description databases. To provide some perspective on SOLEDGE3X results, a brief comparison with SOLPS-ITER is shown for the reference case with uniform coefficients in Fig. 1. This comparison has been performed with both codes using the previous magnetic equilibrium and wall contour (as used in  [14]  for example), since SOLPS-ITER simulations using the new equilibrium adopted here for the SOLEDGE3X work and wall have not yet been published.
Acknowledgements This work was performed under the auspices of the  ITER  Scientist Fellow Network and received funding from an  ITER Organization Implementing Agreement  (No. IO/IA/20/4300002306 ). The views and opinions expressed herein do not necessarily reflect those of the ITER organization. This work has been carried out within the framework of the  EUROfusion Consortium , funded by the  European Union  via the  Euratom Research and Training Programme  (Grant Agreement No  101052200 -EUROfusion ). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the  European Union  nor the  European Commission  can be held responsible for them.
In the past decades, huge efforts were devoted to collecting experimental data. Above all, we recall the test campaigns carried out at the Icing Research Tunnel (IRT), at the NASA Glenn Research Center. These experiments led to the establishing of a database including a large number of ice shapes that can accrete on aircraft wings in different operating conditions  [16] [17] [18] [19]. The comparison of numerical predictions against observations allows for model testing and for their fine-tuning  [20] [21] [22] , including the investigation of wind tunnel effects on ice accretion experiments  [23]  and the investigation of the aerodynamics of a swept wing with leading-edge ice accretion  [24] [25] [26] [27] [28]. Unfortunately, our understanding of reality is unavoidably affected by uncertainty which questions the credibility of both computational models and experiments.