dataesr/scientific-paragraphs-categorization huggingface dataset:
The temperature was monitored by type-J thermocouples connected to the heat exchangers. For high resolution voltage and temperature measurement a Keysight 34972A data acquisition system with an equipped multiplexer unit was used. The cell current and voltage during the experiment was controlled by a Basytec CTS cycler. Entropy change measurements were preceded by 3 galvanostatic cycles between 0. 020 and 1. 500 V at a current density of 37. 2 mA/g (C/10, where C = 372 mAh/g, i. e. the theoretical capacity of LiC 6 ) under a controlled temperature of 25 ºC, to ensure stable solid electrolyte interphase (SEI) formation and to validate the electrochemical behaviour. We separately verified that the galvanostatic results from the coin cells at constant temperature gave comparable results to the three electrode cell measurements as described in section 2.
Root-cap shape and determination of sharpness index Col-0, fez-2, and smb-3 lines were grown in a 0. 2% single-layer medium and at 5 d old primary roots were extracted and placed on a microscope slide. The roots were stained with 10 µg ml -1 propidium iodide (PI, Sigma Aldrich) and observed using a LSM 800 laser-scanning microscope (Zeiss) coupled to an Apochromat X20 lens. To characterize the root-cap size and shape of each genotype, the length of the vertical section, L R , the diameter of the root at the quiescent centre, D R , and the area of the radial section of the root cap, A R , were measured in longitudinal sections of the medium using the ImageJ software  (Schneider et al. , 2017)  (Fig. 2 ). An inverse Sharpness Index (iSI) of the root cap was calculated according to the following equation: iSI = A R -(L R D R )/2 L R D R /2 (4) The closer iSI is to 0, the more the root cap is pointed.
Maximal root growth forces The maximal axial force the roots were able to apply on the two-layer medium interface before reorientation of the root apex was estimated for Col-0, fez-2, and smb-3 roots grown in 0. 2/0. 3 medium. After contact between the root and the interface, root axial growth induced a deflection of this interface until the root curved or the root apex deviated. The shape of the interface just before root apex reorientation was traced using ImageJ software and the maximal deflection, d, of the interface was measured with regards to its initial position (i. e. before contact with the root). The shape of the tip of the root cap was fitted by a circle of radius R. The maximal force before root reorientation, F crit , applied on the interface by the root apex was then estimated using the theory of elastic contact between a sphere and a half-space medium  (Hanaor et al.
Time-lapse photography and image processing Root growth and orientation were subjected to time-lapse imaging from 5 d after sowing. Two Nikon D7100 cameras equipped with macro lenses (AF-S micro NIKKOR 60mm f/2. 8G ED) and controlled by DigiCamControl software were placed on a rack in front of the culture chambers. Images of the roots growing in the two-layer media were recorded every 5 min for at least 24 h. Only the roots remaining in the focal plane of the objectives were analysed. All images were pre-treated using the Rawtherapee software (v4. 2. 1; https://rawtherapee. com/) and were analysed using the RootStem Extractor software developed by the PIAF laboratory  (Chauvet et al. , 2016). Briefly, the software enabled extraction of the topological skeleton of each root by screening the pictures perpendicularly to the root axis with a step of 0.
3 pixels. The length of the root on each picture and the local inclination as a function of the curvilinear abscissa can be computed from the coordinates of the skeleton. The root length as a function of time enabled us to calculate root growth rate by linear fit. Curvature intensity along the root was obtained by deriving the local inclination as a function of time and space. The curvature intensity data are presented in graphs composed of three dimensions: a vertical axis corresponding to root length from the beginning of the measurement, a horizontal axis corresponding to time, and a colour bar that depicts curvature intensity. On the spatio-temporal graphs, the green colour indicates a straight section of the root, while the red and blue colours depict the highest positive and negative curvatures, respectively.
Gravitropic responses of the roots Col-0, fez-2, and smb-3 roots were grown vertically into a 0. 5% Phytagel single-layer medium for 5 d. The culture chambers were tilted by 90° (i. e. horizontal) and images of the primary roots were then recorded every 10 min for 22 h. Analysis of the time-lapse images with RootStem Extractor was used to measure root length and root-tip angle over time (Supplementary Fig. S3 ). These data were used to calculate the gravitropic response by applying the equation described by  Chauvet et al. (2016).
Statistical analysis All data were analysed using R software (RStudio, R. 3. 3. 4; www. rstudio. com) and are presented as means (±SD) in the Results. The Shapiro-Wilk test was used to test for normal distribution of the data and the Bartlett test was used to test for homoscedasticity. One-or two-way ANOVA were used to determine whether the effect of each factor was significant. When significant differences were observed, post-hoc analyses based on Tukey's test were applied to the data.
Once Penetration ability is represented by the percentage of roots that were able to penetrate the 0. 2%, 0. 3%, and 0. 5% lower layers of the Phytagel media. The upper layer was 0. 2% in each case. For each genotype and interface, 10 roots in each of six replicate preparations of growth medium were observed 8 d after germination, and the data are presented as means (±SD), n=60. Different letters show significant differences as determined using two-way ANOVA followed by Tukey's test (P<0. 05). Fig. 5. Growth and gravitropic responses of Arabidopsis Col-0, fez-2, and smb-3 root apexes. (A) Length of the growth zone from the quiescent centre to the end of the elongation zone, estimated using a kinematic analysis. (B) Growth rates of roots growing in compliant 0. 2% Phytagel single-layer medium.
Acknowledgements We would like to thank  Ben Scheres  and  Viola Willemsen  ( University of Utrecht, The Netherlands ) for donating the mutant lines. We thank  Evelyne Kolb  and  Marie-Bogeat-Triboulot  for fruitful discussion. This research received financial support from the  French Space Agency (CNES)  and  INRA  programs. JR received a doctoral grant from the  French National Ministry of Education and Research. HC received a Postdoctoral grant from the  Auvergne-Rhône Alpes Council  with co-funding from  FEDER. FB received a Postdoctoral grant from the  CNES.
Methods for uncovering cultural models via Green-Win stakeholder workshops Following  Kempton et al. (1995) , we sought to build a profile of cultural models based on stakeholders' propositions about "their city" in terms of sustainability and socialenvironmental change. To build these propositions, we used preliminary data gathered from approximately 40 semi-structured stakeholder interviews in China and Turkey in 2016 (although such interviews unfortunately could not be carried out in Beirut) and content analysis of relevant urban planning documents in each city. This data gathering was conducted in the national language of the city by members of the research team native to that country, who worked with the broader team to translate them into English. Next, we extracted key propositions about sustainability and adaptation gathered from coding those sources and grouped them according to how they relate to the enabling environment conditions (vision, cultural-cognitive, formal-institutional, organizational, and economic; see Table  1 ).
REAL-TIME APPLICATION (SHORTEST PATH) Some RT simulations in Matlab have been performed with the aim of testing the advantages that the PGD-Vademecum approach offers. An omnidirectional mobile robot has been modelled that navigates in a 5x5m square environment guided by a harmonic potential field approximated by the PGD with 50× 50 nodes, r = 0. 7 and n = 200. For a realistic implementation, only as small Region Of Interest (ROI) is reconstructed in each algorithm execution. The ROI is composed of the surrounding nodes of the current robot position and its size depends on the maximum robot velocity. In the present example, for particular Start and Target configurations, the robot selects the shortest streamline, which is a straight line heading to the Target. Figure  5  depicts different trajectories followed by the robot beginning at the starting point S = (1, 4) to subsequent target points T = (4, 1), (3, 4), (2, 1), (4, 3).
CASE STUDY: BREAKTHROUGH STARSHOT We apply the previously developed framework to a gram-sized spacecraft for a mission to another star, which is currently under development by the Breakthrough Starshot program  (Lubin, 2016). We will first apply the breakthrough dimensionnovelty matrix to this technology and subsequently, briefly address the question of whether or not this is a potential breakthrough technology. The data for this case study was collected from a conceptual feasibility study of the Initiative for Interstellar Studies (i4is) prior to the announcement of the Breakthrough Starshot program in March 2016. The lead author of this article participated in this study as the system architect. A team of 14 people has collaborated virtually for a week to analyze various concepts for sending a spacecraft with a mass of 23 grams to the Alpha Centauri star system.
The results of the feasibility study  (Hein, Long, et al. , 2017)  were subsequently reviewed by members of the Breakthrough Starshot committee and informed the Breakthrough Starshot program. As data sources, published reports, internal documents, and personal accounts from team members were used. The concept for the Breakthrough Starshot mission was proposed in  Lubin (2016). The spacecraft consists of a power subsystem (small-scale nuclear battery), communication subsystem (laser optical communication), camera payload, and further typical spacecraft subsystems. In addition, a thin, highly reflective surface is attached to the spacecraft, which is intended to reflect an incoming laser beam. This sail-like structure is called laser sail. By reflecting the laser beam, thrust is generated. The laser beam is emitted by a ground-based laser beaming infrastructure with a beam power of about a hundred gigawatts.
Discharge simulation and integrated scenario modelling Predictive simulation of plasma discharges is the basis of the preparation of the experiment and the preliminary step for other analyses: MHD stability, sub-systems performance, and control strategies. Extensive scenario evaluation and preparation have been done using free-boundary equilibrium codes, such as ACCOME  [7]  (including NBI sources) and TOSCA  [8]. Global discharge simulations, producing time evolution of all the physical quantities, including magnetic equilibrium and radial profiles, are better done by fast simulators and indeed systematic analyses have been carried out with the METIS code  [9]  and reported in  [2]. A much more accurate evaluation can be done if limited to particular phases Table  2. Main parameters of the JT-60SA reference scenarios.
This has been accomplished by an advanced modelling framework  [20]  combining in an iterative way: TOPICS  [10]  and OFMC  [18]  for the evaluation of the NBI induced torque, and the 3D neoclassical code FORTEC-3D  [21]  and the 3D equilibrium code VMEC  [22]. An example of the toroidal rotation computed by means of this modelling framework for a high-current (5. 5 MA) H-mode scenario of JT-60SA is shown in figure 3. In the left panel, red, green, and blue curves respectively display the profiles of toroidal rotation velocity without the NTV effect, with the NTV due to magnetic ripple and also including the effect of an n=3 RMP induced by 10 kA current in each of the EFCC, with even parity. In the right panel, the NTV torque (with and without RMP) is shown, together with the radial electric field.
The discharge parameters on TCV were optimised to (i) minimise the absorption of EC stray radiation by in-vessel components by minimising the plasma breakdown time and maximising the absorption of power over the duration of the conditioning discharge, and to (ii) improve the discharge homogeneity and wall coverage, in particular towards the inboard surfaces where JT-60SA plasmas will be initiated. The main control parameters in this study are the addition of a poloidal magnetic field to the nominal toroidal field, the discharge pressure, and the EC power. In order to extrapolate these results to future JT-60SA ECWC experiments and routine use, modelling has been carried out by means of the TOMATOR-1D code  [24]. This one-dimensional reactiondiffusion-convection code has been developed to simulate plasma production by radio-frequency waves inside a tokamak, using the Braginskii continuity and heat balance equations.
Predictive modelling of EC-assisted breakdown could significantly speed up the search for optimised breakdown configurations, however it requires a complex simulation framework, combining free-boundary equilibrium equations, balance equations for the time evolution of energy, particles (with ionisation/recombination terms and impurities) together with the circuit equation for the plasma current, and EC wave propagation equations, including at least the first wall reflection. To this end, a dedicated modelling workflow has  been developed and is being validated on experiments  [27]. It combines the breakdown code BKD0  [28] , the beam-tracing code GRAY  [25]  and CREATE-BD, a specific version of the free-boundary equilibrium code CREATE  [29] , which integrates and optimises the active circuit currents, taking into account eddy currents in the passive structures for developing the plasma breakdown scenario.
Both transient conditions, such as plasma start-up and flat-top scenarios have been taken into consideration. Moreover, the expected stray power density distribution in the vessel and particularly around the potentially critical areas such as diagnostics windows or pumping ducts has been evaluated. An adequate detection system to limit the risks related to stray radiation is presently considered. After breakdown and burnthrough are obtained, the current and density ramp-up is a crucial phase for the establishment of high-performance scenarios while saving central solenoid flux: X-point formation, high shaping control, H-mode transition, and in particular the access to the safety factor profiles typical of JT-60SA advanced regimes (hybrid and steady state). Earlier simulations of this phase have been performed with the MECS code  [35, 36]  and benchmarked  [37]  with the CREATE-NL code  [38].
A way to improve the accuracy of this type of simulation is to couple a freeboundary equilibrium code with a plasma model including the main ingredients of integrated modelling, i. e. , heat and particle transport, current diffusion, and H&CD modules. Although some examples of such a combination of codes exist in the literature, the required computation time is usually extremely large. In order to keep it at a level that makes this type of modelling practical and useful for preparing experimental scenarios, the fast integrated modelling code METIS  [9]  is used as plasma module and has been coupled to two different free-boundary equilibrium codes, for alternative uses: CREATE-NL  [38]  and FEEQS  [39]. FEEQS is used in inverse mode in conjunction with METIS to compute the premagnetisation phase and to initialise and optimise the plasma scenario, verifying the coil limits.
Flat-top plasma sustainment: density, power loads, and radiation Density control is a key ingredient for long pulse regimes and in particular for access to high-density scenarios, close to the Greenwald limit. The two main actuators of such control will be the divertor cryopump system  [5]  and the pellet fuelling system, which is being designed  [6]. This will be an advanced system, conceived for combined fuelling and ELM pacing using two extruders. Detailed modelling of pellet ablation, using the HPI2 code  [40] , has been carried out in order to determine the optimum pellet injection location and parameters for all the reference scenarios and optimise the system design. The same code has been used in conjunction with the integrated modelling suite JINTRAC, appropriately set up for JT-60SA simulations  [15] , in order to assess the feasibility of combined fuelling and ELM pacing.
The second key element for long pulse regimes is the control of power loads on the divertor during the strong heating phase, which can be attained by divertor radiation associated with controlled impurity seeding strategies. Systematic studies of the relevant scenarios, but in a simplified geometry, have been performed by means of the COREDIV code, both for C-PFC  [41] [42] [43]  and W-PFC  [42, 44]. Simulations combining the core, SOL, and divertor have been performed for a scenario similar to Scenario 5-1, but at reduced heating power, using JINTRAC coupled to the edge code EDGE2D and the Monte Carlo code for the neutrals EIRENE  [45]. A comparison of COREDIV and EDGE2D carbon radiation patterns for Scenario 3 (high density) are shown in figure 8. In the case of EDGE2D-EIRENE the boundary conditions on the core side are taken from the COREDIV results.
This has motivated the development of a fast ion loss detection system for JT-60SA, which is being designed  [56, 57]  and will be installed for the high-power phase of the machine programme. In addition to the detailed analysis of the Alfvén eigenmode stability and related energetic particles (EPs) transport of single time slices  [53] , faster tools for a survey-type analysis are needed for scenario modelling and optimisation. An automated workflow wrapper around the linear-gyrokinetic code LIGKA  [58, 59]  has been developed in order to process many different equilibria in a reasonably short computation time (typically 1-3 min per equilibrium for ten toroidal mode numbers, trivially parallelisable). A hierarchy of reduced models can be chosen (local/global, analytical/numerical coefficients for velocity-space integrals).
In figure 9 the local damping rates of all toroidal Alfvén eigenmodes (TAE) with mode numbers n=1-10 (colour code), including Landau damping and a model for radiative damping, are shown as function of the on-axis safety factor q 0 (as a model for current profile evolution during current ramp-up). Due to off-axis NB heating, the steepest EP gradients are expected between ρ=0. 2-0. 4 (positive EP gradient) and ρ=0. 5-0. 6 (negative EP gradient)  [2]. Clearly, inner core TAEs are less damped compared to outer core TAEs, and different q-profiles favour the stability of different toroidal mode numbers. Adding energetic ions (modelled as a hot Maxwellian with an equivalent EP pressure) leads to the stability diagram plotted in figure  10. Here the scenario parameters are taken from the CRONOS simulation of the hybrid scenario presented in  [13] , in which the EP distribution has been computed by the NEMO/SPOT Monte Carlo module.
MHD instabilities and transient events control Controllability of JT-60SA scenarios will require avoidance or prompt reaction to a number of MHD instabilities and transient events, both in the stationary and in the ramp-up, ramp-down phases. Preparation of adequate control strategies has to be supported by deep understanding of the physical phenomena involved, in view of future application to ITER and DEMO. A distinctive example is the issue of disruptions, which should be accurately predicted, if possible avoided, and otherwise mitigated. This motivated the development of a disruption predictor for JT-60SA, which has undergone first tests on JT-60U data  [63]  and of a two-valve massive gas injection system  [64]  procured by EU and that will be available after the machine commissioning phase.
ELM studies Not only disruptions should be avoided or mitigated in ITER and DEMO, but also in ELMs: the search for no-ELM or small-ELM regimes is one of the main objectives of the JT-60SA programme. Such regimes have been found empirically, but first-principle simulation of the non-linear ELM dynamics is fundamental to gain insight into the conditions for the access to these regimes or for active ELM control. To this end, the 3D non-linear MHD code JOREK  [65, 66]  has been applied to H-mode JT-60SA scenarios. The model contains all pedestal-relevant plasma flows, including twofluid diamagnetic effects, neoclassical poloidal velocity, and toroidal rotation. Linear stability was first benchmarked with the linear MINERVA-DI code  [67] , then non-linear simulations were performed for ballooning mode numbers n=4-22 and various values of the plasma resistivity.
A plasma response mode provided by the CarMa code  [71]  has been implemented for simulations of RWM feedback control with the most unstable n=1 and n=2 modes, where n is the toroidal mode number  [72]. This model includes a realistic description of the active coils, with both RWM control coils (RWMCC) and EFCC represented as single turn conductors. The stabilising plate is also described with all its 3D features, while an axisymmetric vacuum vessel is assumed. This is enough to introduce a significant degree of realistic detail, since the stabilising plate is the closest conducting structure interacting with the RWMs (r/a∼1. 2, where a is the minor radius). The structure of an n=1 eigenmode computed by the CarMa code on an axisymmetric surface in the stabilising plate position is shown in figure  13  (right panel).
The 3D features of the stabilising plate however introduce a destabilising effect and a splitting of the modes into multiple unstable eigenvectors. For this reason, ongoing work is aiming at developing a multimodal simulator for RWM control  [72]. EPs, an ubiquitous element of the JT-60SA highperformance scenarios, are also expected to have an impact on RWM dynamics. In order to study these effects, a hybrid kinetic-MHD model has been developed and extended to include both EPs and toroidal plasma rotation in the MINERVA/RWMaC code  [73]. The case of Scenario 5-1 (high beta steady state) has been considered, in particular to analyse the effect of the NBI parameters on the RWM stability: the injected beam energy E a and the ratio of the parallel to the total velocity of the injected beam v // /v (pitchangle parameter).
e. q=3/2 and q=2); (ii) modulation capability in the kHz range. In order to predict the EC power required for NTM reduction or suppression, the effect of ECCD with the actual design of the antenna configuration has being investigated by solving the generalised Rutherford equation  [74] , where several terms affecting NTM stability (such as bootstrap, curvature, polarisation, non-inductive driven current, heating, wall, etc. ) are included. Equations for the time evolution of the mode phase and frequency  [75]  are also solved and the wave propagation, absorption and driven current are computed by the beam-tracing code GRAY  [25]. All these elements are combined in a workflow  [76]  allowing systematic evaluation of the JT-60SA scenarios, as reported elsewhere  [77]. Here the case of the 2/1 mode for Scenario 2 is illustrated in figure  15.
Acknowledgements This work has been carried out within the framework of the  EUROfusion Consortium  and has received funding from the  EURATOM  research and training programme 2014-2018 and  2019-2020  under grant agreement no. 633053. The views and opinions expressed herein do not necessarily reflect those of the  European Commission. The authors gratefully acknowledge members of the JT-60SA  Integrated  Project Team for data exchange and fruitful discussions.