dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. The Imaging X-ray Polarimetry Explorer (IXPE) is a joint US and Italian mission. The US contribution is supported by the  National Aeronautics and Space Administration (NASA)  and led and managed by its  Marshall Space Flight Center (MSFC) , with industry partner  Ball Aerospace  (contract  NNM15AA18C ). The Italian contribution is supported by the  Italian Space Agency (Agenzia Spaziale Italiana, ASI)  through contract  ASI-OHBI-2017-12-I. 0 ,agreements  ASI-INAF-2017-12-H0  and  ASI-INFN-2017. 13-H0 , and its  Space Science Data Center (SSDC)  with agreements  ASI-INAF-2022-14-HH. 0  and  ASI-INFN 2021-43-HH. 0 , and by the  Istituto Nazionale di Astrofisica (INAF)  and the  Istituto Nazionale di Fisica Nucleare (INFN) in Italy. This research used data products provided by the  IXPE Team (MSFC, SSDC, INAF , and  INFN ) and distributed with additional software tools by the  High-Energy Astrophysics Science Archive Research Center (HEASARC) , at  NASA Goddard Space Flight Center (GSFC).
Acknowledgments This work would not have been possible without the support of the technical staff at the MPI-DS. The authors would like to thank the biology staff for taking care of the honeybee hives. We would like to thank the experimental technicians for help with setting up the mobile laboratory and pavilion. Additionally, many thanks to the IT and HPC team for the setup of the data servers for file transfer and storage. We would like to express our sincere gratitude to  Alain Pumir  for insightful discussions.
Methods, Results and Discussion The general problem studied in this work is the nonlinear propagation of two types of periodic waveforms, which have already been investigated in the context of linear shaping  [7] : a continuous wave modulated at the frequency fm, yielding an optical spectrum made of a central component and two sidebands at ±fm, and a wave whose spectrum consists of four spectral lines without any continuous background. The data from numerical simulations of the NLSE based on the standard split-step Fourier algorithm is used to train a NN and validate its predictions. We employ a feedforward NN relying on the Bayesian regularisation back propagation algorithm and including three hidden layers. The NN learns the NLSE model from an ensemble of hundreds of thousands simulation data (real and imaginary parts of the spectral field) for the anomalous or normal dispersion regime of the fibre and corresponding to randomly chosen combinations of input parameters: amplitude ratio A of the central frequency component of the optical spectrum to the lateral sidebands, spectral phase offset 𝜑 of the sidebands relative to the central component, normalised propagation length 𝜉, and soliton-order number N.
However, increasing the amount of current through the battery pack and chargingdischarging from a state of partial charge to high or low states of charge might increase the battery aging pack  [10]. Further studies should be carried out where battery degradation effects are taken into consideration when searching for optimal energy management strategies and aircraft operating conditions. Especially, impact of higher currents and depth of discharge limits should be investigated in regards to their impact on aging. Figure  6  presents the full dataset of Fig. 5b  with selections highlighting input values defining the energy management strategies. Particularly, Fig. 6a  indicates that strategies with a linearly decreasing DOH for climb have lower emissions than those with linearly increasing DOH.
6. Acknowledgments This project has received funding from the  European Union 's  Horizon 2020 Research and Innovation programme  under Grant Agreement No  875551. The authors thanks the FutPrint50 Embraer partners,  Ricardo Jose Nunes Dos Reis ,  Felipe Reyes Barbosa , Michelle EASN-2022 Journal of Physics: Conference Series 2526 (2023)  012021  IOP Publishing doi:10. 1088/1742-6596/2526/1/012021 8 Fernandino Westin  and  Ricardo Gandolfi , for their help and expertise for the choice of the mission analysed.
Filtration Tests Frontal filtration experiments were performed using an agitated dead cell (Amicon 8050, Millipore Corporation; Fontenay sous bois, France) with membranes having an active surface area of 13. 4 cm 2 according to a previously described procedure  [29]. The membranes were first conditioned in the test cell with pure water by gradually increasing the pressure to 4 bar for at least 3 h. Then, the cell was connected to a water tank and pressurized to the desired value using compressed air. The mass of permeate passing through the membrane was recorded at regular intervals using SartoConnect software (Sartorius, Göttingen, Germany). Pure water flow rate (PWF) was measured for each membrane by flowing DI water through the membrane system with an applied pressure between 0. 5 and 3.
This is especially true for diagnostic models that are based on the land surface temperature (LST), which can be coupled with cloud computation frameworks, thus providing long-term and consistent ET spatial patterns  37, 38. While cloud computation has engendered groundbreaking advances in wetland hydrology by enhancing the understanding of ooding processes in large areas  39  , here we go further by analyzing the spatio-temporal dynamics of ET in 12 large wetland complexes in South America. We employ a Google Earth Engine algorithm based on the Surface Energy Balance Algorithm for Land (SEBAL)  40  model and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery to generate monthly ET estimates, which are jointly analyzed with a state-of-the-art inundation dataset  41  for the period of 2000-2015.
s -1 ) and k the von Karman's constant (0. 41). To select the hot and cold endmember pixels, we used a simpli ed version adapted from the automated methodology from the METRIC model based on the Calibration using Inverse Modeling at Extreme Conditions (CIMEC) process  73. The CIMEC process considers a population of candidate members based on quantiles of remote sensing estimations of Ts and NDVI to select the hot (dry) and cold (wet) pixels. The 8-day evapotranspiration (ET 8 -day ) is computed with the following steps. Firstly, the 8-day evaporative fraction ( ) is calculated as: MSWEP and MODIS datasets. Linear correlations were performed among the estimated monthly ET, ET anomaly (normalized by monthly averages) and E 0 and environmental variables to understand the drivers of ET processes (Fig.
Acknowledgements The rst author would like to thank  CNPq  for funding this research under grant numbers  141161/2017-5  and  201148/2019-6. The authors would like to gratefully acknowledge the nancial support provided by the  Brazilian Agency for the Improvement of Higher Education (CAPES)  in partnership with the  Brazilian National Water Agency (ANA)  in the context of the research project " Estimating land surface evapotranspiration using remote sensing models for water management in Brazil ", grant number  88881. 178687/2018-01. We are also grateful to AMERIFLUX and LBA-ECO for making micrometeorological and ux data available.
(  13 ) is independent of the excitation level P and can be obtained for any value of P and ω e using the scaling defined in  (12). Eq. (  13 ) is solved numerically with the continuation software MANLAB  [44, 45]  since there is no analytical solution at hand. MANLAB is based on a Harmonic Balance method to compute the periodic solutions. It requires a regularization of the nonsmooth term, which is discussed in Appendix B. Note that in all the numerical simulations with MANLAB, 40 harmonics were considered. Fig. 3  shows the dimensionless frequency response, normalized with respect to the excitation level, of the zeroth (H0), first (H1), and second (H2) harmonics of the periodic solutions of Eq. (  8 ) for different values of β. Note that only H0, H1, and H2 harmonics are considered since they represent the dominant harmonics observed in the numerical simulations, and they will be relevant in the upcoming analysis.
Numerical validation In this section, we numerically validate the frequency response and the optimal parameters of our modified RL-shunt by considering the first twisting mode of the hydrofoil structure that will be tested experimentally in section 4 (see Fig. 17 ). The modal parameters corresponding to this mode are gathered in Table. 3. The numerical results are obtained by solving Eq. (7a,b) with MANLAB, considering 40 harmonics in the simulations. Then, the frequency responses of the first harmonic amplitude of the displacement u H1 , the charge Q H1 , and the PE voltage V H1 are obtained. Note that in what follows, the modal parameters correspond to this particular mode, and thus the subscript i associated with the modal parameters notations is omitted in the remaining of this section.
Acknowledgement This work is funded by the  French National Research Agency (ANR)  and the  Deutsche Forschungsgemeinschaft (DFG ,  German Research Foundation)  in the collaborative project " Composite forming simulation for non-crimp fabrics based on generalized continuum approaches ". Material Forming -ESAFORM 2023 Materials Research Forum LLC Materials Research Proceedings   28  (2023)  285-292  https: //doi. org/10. 21741/9781644902479-31.
In these papers, phase, and amplitude color-coded simulation maps, calculated by varying both the structural parameters and the real frequency of excitation, indicated the presence of a zero of reflectivity and full phase modulation. It has been shown that this condition is guaranteed when radiative losses into the reflection channel prevail over absorption losses  [31]. A similar idea of circulation has been recently proposed in the context of zeros of polarization conversion near exceptional points  [7]. In the following, we analyzed this problem from the non-Hermitian perspective. Scattering problems driven by light sources with complex-valued frequencies are solved using the finite-element-based software package JCMsuite. We then prove that the complex singularities observed in these systems occur at the transition when a zero and pole of a pair become separated by the real frequency axis.
acknowledges financial support by the French National Research Agency ANR Project DILEMMA (ANR-20-CE09-0027). S. C. , P. G. and E. M. acknowledge financial support by the French National Research Agency ANR Project Meta-On-Demand (ANR-20-CE24-0013). P. G. and R. C. acknowledges support from the European Innovation Council (EIC) project TwistedNano (under the grant agreement number Pathfinder Open 2021-101046424). J. Y. D. and P. G. acknowledges financial support by the French National Research Agency ANR SWEET (ANR-22-CE24-0005). K. A. gratefully acknowledges funding from the Swiss National Science Foundation (project PZ00P2_193221). S. F. acknowledge the support of a U. S. AFORS MURI project (Grant No. FA9550-21-1-0312). A. A. and A. O. were supported by the Simons Foundation and the Air Force Office of Scientific Research.
5G key air interface technologies, such as orthogonal frequency division multiple access (OFDMA), massive MIMO and half duplex, will be further enhanced in 6G. For example, modern random access technologies like NOMA, ultra-massive MIMO and in-band full-duplex (IBFD) are expected to achieve further enhancement in the capacity and efficiency of the communication system. In addition, academia and industry are actively exploring new physical dimensions, such as orbital angular OAM, RIS, and holographic RF, to achieve a revolutionary breakthrough in the way of data transmission. What's more, there are a number of new technologies that are expected to be used to increase the capabilities of communication networks. For example, ISAC can give communication systems the opportunity to have converged sensing capabilities.
3) Blockchain: Blockchain technique was first proposed for cryptocurrency in 2008  [491]. Using distributed databases connected by hash pointers, blockchain has the characteristics of decentralization, transparency, anonymity, immutability, traceability, and resiliency  [331]. Because of the flatter structure and more frequent data transformation in 6G network, the traditional centralized security authentication and access control mechanisms will no longer be fully applicable  [492]. Blockchain provides a promising solution to the trust-and security-related issues among distributed and heterogeneous network devices and infrastructures, and, is considered as one of the essential technologies for 6G communication systems  [32] ,  [43] ,  [52]. In 2018 Mobile World Congress Americas (MWCA), FCC outlined their vision for deploying blockchain in future 6G networks.
Parameter database for all spectra and scenarios can be constructed by using channel measurement fitting from existing standardized channel model documents. Considering the cost and limitations of channel measurements, RT and AI/ML-based methods can also be chosen to achieve channel parameter acquisition for different spectra and scenarios to complete the channel model parameter database. By adjusting the parameters of the channel model, the 6GPCM can be simplified to simulate channels for specific spectra and scenarios as special cases. By analyzing the 6GPCM, the complex mapping relationship among channel model parameters, channel characteristics and communication system performance can be investigated thoroughly. The 6GPCM is extremely important for the standardization of 6G channel models, as well as the investigation of theories, technologies, and system integration for the 6G space-air-ground-sea integrated network.
This work was supported by the  National Key R&D Program of China  under Grant  2018YFB1801101 , the  National Natural Science Foundation of China (NSFC)  under Grant  61960206006 , the  Key Technologies R&D Program of Jiangsu (Prospective and Key Technologies for Industry)  under Grants  BE2022067  and  BE2022067-1 , the  EU   H2020   RISE   TESTBED2  project under Grant  872172 , the  EU   H2020   ARIADNE  project under Grant  871464 , and the  EU   H2020 RISE-6G  project under Grant  101017011. Thanks are also extended to  Xichen Mao ,  Yinglan Bu ,  Lijian L. Hanzo  would like to acknowledge the financial support of the  Engineering and Physical Sciences Research Council  projects  EP/W016605/1  and  EP/X01228X/1  as well as of the  European Research Council 's Advanced Fellow Grant QuantCom  (Grant No.
The cooling jacket was equipped with a specific sensor (thermopile, see THR in Fig. 1 ) to perform a direct heat balance on the cooling jacket described hereafter. A Data Acquisition (DAC) system supplied by Agilent, connected to a PC, records temperatures, pressure, flow, and heat balance. The monitoring and recording of all process values (temperature, pressure, flow, heat balance, every 10 s), the control of CO 2 injection, stirring speed and temperature set-point of the heating/cooling unit were done thanks to a VBA in-house software.
Acknowledgements This work was supported by the  French National Research Agency  under the programs  MUSCOFI  ( ANR-18-CE0-0028 ) and  COOLHYD  ( ANR-22-CE50-0001 ), and undertaken in the frame of the  US Partnership for International Research and Education program  ( National Science Foundation  Award Number  1743794 ) and of the  French Research Consortium  '' GDR-2026 Hydrates de gaz ".
A dedicated optical system is designed for the breakdown of the first ITER plasma, when the machine will not be equipped with the equatorial ECRH-launcher. Seven beams from the upper launcher will be transmitted via several in-vessel mirrors through the resonance layer to a beam-dump. The whole system was simulated with the PROFUSION package to obtain the beam parameters, estimate spill-over effects and determine the required polarization in the launcher in order to have X-mode polarization in the resonance.
For the initial plasma breakdown the beams of 7 gyrotrons (1 MW each) will be used. The 3 beams launched by the upper row of the launcher are denoted U1, U2 and U3 respectively. The beams coming from the lower row are denoted L1-L4. For the upper beams, the steering mirror (M4) in the launcher will be modified with a cylindrical surface, and a common in-vessel mirror (UA) is used to direct the beams towards the resonance. The lower beams are directed via one common ellipsoidal in-vessel mirror (LA) and four individual hyperboloid mirrors (LB) towards the resonance. The calculations were done with the PROFUSION code  [4] , which was extended for this project.
Simulation Framework All solvers are part of the PROFUSION code package  [4] , which was developed over more than two decades and contains a large number of routines tools for microwave optics, both for free space and in waveguides. The PROFUSION tools are commandline programs, which are written in C and run on Linux computers. This has the advantage that a calculation is fully defined by the data files (if needed) and the command line. This improves the reproducibility and allows to control even complex simulations (e. g. including parameter scans) by simple shell scripts. PROFUSION also contains a large number of small tools for doing standard calculation (like 3D vector arithmetic, coordinate transformations, evaluation of mathematical expressions), which make it possible to convert the parameters obtained from IO to the values needed by the solvers.
This made it possible to simulate a whole set of beams (U or L) including the analysis in a few hours. During the project, the PROFUSION tools were upgraded with some new features, most notably:  Support for mirrors with irregular (i. e. numerically given) boundaries  Support for passing all coordinates in an arbitrary global coordinate system (TGCS in the ITER case).  Determination of the ellipse rotation angle of the Gaussian fit tool  Implementation of a tool for tracking the polarisation across a sequence of mirrors with Eq. (7)  A tool for generating discretized datasets of mirror surfaces from geometry parameters (cylinder, ellipsoid or hyperboloid).
Comparison with the design values To verify the calculation, the positions of the beam centres were calculated with the Gaussian fit tool (see section 2. 3) and compared with the design values (obtained with the Catia software). Table  1  shows the result for the U-beams at the location of the beam dump. At this location the beam passed 3 mirrors and more than 13 m of free space propagation, so the errors are expected to be the largest there. We can see a very good agreement. The maximum error is 1. 702 mm, which is much smaller than the minor beam radius (57. 309 mm) and therefore negligible compared to other expected errors, e. g. from spurious waveguide modes. In parallel to the PROFUSION simulation, the system was simulated with the commercial Zemax OpticStudio software. Fig. 14  shows the field of the beam U2 after the mirror UA calculated with PROFUSION and Zemax.
For this study, a geometry formed by a piece of metal extending over the surface of a printed circuit board (PCB) was modeled. The height of the antenna is 3. 16 cm, its radius is 0. 1 cm. This structure was realized using the HFSS modeling software and requires 15 min of the simulation time. The figure  4  represents the modeling of the monopole antenna used under HFSS. The simulations were performed in four configurations: • Between the two antennas in free space above a ground plane; • P t : Between the two antennas when the transmitting antenna was mounted on the shaft; • e r et D r : Between the two antennas when both the shaft, stator and rotor were present. • e r et D r : Between the two antennas when both the shaft, stator, rotor and the carcass were present. The location and orientation of the two antennas were identical in all four cases.
Acknowledgments. This work was supported in part by the  Innov'COM Laboratory of Higher School of Telecommunication, University of Carthage Tunisia  and  LAPLACE Laboratory of the National Polytechnic Institute of Toulouse France. Declarations. I confirm that I understand journal Electrical Engineering is a transformative journal. When research is accepted for publication, there is a choice to publish using either immediate gold open access or the traditional publishing route. No, I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper. The results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration (from you or one of your Contributing Authors) by another publisher.
Furthermore, they managed temperature measurements inside the bottle and showed the temperature profile of the preform has an important influence in SBM process. It must be introduced as an initial condition  13  and must be adjusted during the simulation to reproduce the self-heating phenomena. At the same time, our authors proposed a visco-hyperelastic model coupled to temperature  18  and developed an orthotropic version. 6 This model was implemented into the finite element code Abaqus and the simulation can reproduce correctly the SBM process. In addition to the constitutive model, the accuracy of simulation was also upgraded by incorporating the other realistic considerations: i. Menary's group  19, 26  applied the air flow rate as a boundary condition instead of the internal cavity pressure.
Section 3 presents the anisotropic visco-hyperelastic model, which considers the self-heating effect, the strain hardening, and strain rate effects. Then, a parametric study is performed to analyze the influence of each parameter in the model on the geometric characteristics of bubble. Through this work, two parameters, one from elastic part (G 1 ) and the other from viscous part (α 1 ) in the model are identified to play the important role on the bubble shape. Length of the bubble and the ratio between the length and radius in the center part of bubble are chosen for the optimization procedure. For this last part, we use Matlab coupled with Abaqus software for adjusting these two parameters. The optimal values are identified from the four sets of free blowing tests. Using this identified model, the simulation of SBM process provides correctly the wall thickness distribution of bottle on comparing the experimental one: the mean difference does not exceed 10% in the center part of the bottle.
| Optimization of the parameters The model is implemented into the software ABAQUS/ Explicit via a user interface VUMAT. Because the material is rapidly stretched in the process, the conduction effect is neglected in regard of the dissipation effect. Furthermore, we assume that the entropy of rubber networks convection or crystallization is also neglected in regard of the viscous dissipation. Therefore, the major contribution to the self-heating phenomenon is due to viscous dissipation, which is written by σ : D v. The simulation is carried out using axisymmetric shell elements. The thermal simulation is managed at each time step  18  by solving: ρC p T : ¼ σ : D v ð9Þ where ρ the density of PET and C p the specific heat capacity, the product of them is assumed to be constant at this temperature range and equal to ρC p = 1.
In this second step of the optimization procedure, we propose a method to semi-manually readjust the two parameters in the VHE model by coupling Abaqus and Matlab software's. The adjustments of the parameters G 1 and α 1 are necessary to manage the correct simulation that reaches the desired radius R (or the length L) and the ratio L/R. In the case 110 C and 1. 5 bar, in order to get the experimental measures of Table  2 , R = 46 mm and L/ R = 5. 78, G 1 and α 1 are calculated firstly by a linear adjustment from Table  3. With the adjusted values, the simulation of free blowing in Abaqus software provides a first numerical radius R and a ratio L/R. If the difference between experimental geometry parameters and numerical one exceeds 3%, the parameters G 1 and α 1 will be adjusted once again in a new iteration using the "Scatter-edInterpolant" function from the Matlab software.