dataesr/scientific-paragraphs-categorization huggingface dataset:
Method and Computational Details Samples with up to 28 million atoms, 100a 0 × 100a 0 cross-section, and a length up 1400a 0 (with a 0 = 2. 87 Angstrom, the lattice constant) were simulated using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics code  [29]. The interactions between atoms were modeled through the embedded atom model (EAM) formalism  [30, 31] , where the iron model was a modified version of the Ackland potential  [20] , which was successfully used to address both plasticity and phase transition in iron  [5, 19, 26]. The sample was thermalized at a 50 K initial temperature, then dynamic ramp-wave compression was realized by driving an effective infinite-mass wall piston with an imposed velocity v(t) along the z-axis, oriented along the [001] crystallographic direction, while periodic boundary conditions were used for the transverse directions.
In order to investigate strain-rate effects, the piston velocity was increased linearly from 0 to 1600 m•s -1 with a rise time varying from 15 to up to 150 ps. The corresponding loading rates were about 1-10 × 10 9 s -1 , which is comparable with that reported under picosecond laser dynamic compression  [15] [16] [17] [18]. The local thermodynamic and mechanical properties, such as longitudinal stress σ z , shear stress, temperature, etc. , were evaluated within a spatial planar bin (of 3-lattice constant width) perpendicular to the wave propagation direction in the same manner as our previous work  [5, 26, 27]. Finally, local structural analysis was performed by adaptative common neighbor analysis (CNA), centrosymmetry, and DXA, as implemented in OVITO software (https://www. ovito. org, accessed on 18 January 2023)  [32].
7 eV). An initial analysis was carried out to analyse the corresponding elements (wide scan: step energy 1 eV, dwell time 0. 1 s, pass energy 80 eV) and high resolution analysis was carried out (detail scan: step energy 0. 08 eV, dwell time 0. 1 s, pass energy 30 eV) with an electron exit angle of 90°. Fitting of the XPS data was done using CasaXPS 2. 3. 16 PR 1. 6 software. TGA measurements were performed with a TGA Q500 (TA Instruments) under N 2 atmosphere. The samples were introduced inside a platinum crucible and equilibrated at 100 °C followed by a 10 °C min -1 ramp between 100 and 800 °C.
Data analysis The results of pH measurements and biochemical assays carried out on liquid media of fungal cultures were statistically analysed with two-way ANOVA using the GO concentration, the incubation time, and their interaction as categorical predictors. Raman spectra of GO treated with fungal cultures were elaborated in R environment to remove spikes and to correct the spectra baseline with polynomial baseline function and smoothing algorithms. The spectra were standardised within a 0-1 range and the intensity (I) of D and G bands as well as their ratio [I (D) /I (G) ] was calculated and statistically analysed with two-way ANOVA as explained before. The Raman spectra of the three GRMs treated with LiP or Lac in the second and third experiment, respectively, were pre-processed as explained before and statistically analysed with one-way ANOVA using the treatments (i.
Acknowledgements This work was supported by the  Graphene Flagship Core 2  and 3 grant agreement (no. 785219  and  881603 ), which covered the activity of  Dr. Lorenzo Fortuna ,  Dr. Marina Garrido , and  Dr. Fabio Candotto Carniel. The activity of  Dr. Davide Zanelli  was covered by the doctoral scholarship " DOTTAMBIENTEVITA34-18 " of the  University of Trieste. This work was partly supported by the  Agence Nationale de la Recherche (ANR)  through the  LabEx project Chemistry of Complex Systems  ( ANR-10-LABX-0026_CSC ) and by the  Spanish Ministerio de Ciencia e Innovación  (Project  PDC2021-120735-I00 ). We wish to acknowledge the  Centre National de la Recherche Scientifique (CNRS)  and the  International Center for Frontier Research in Chemistry  (icFRC). The authors thank  Dr. Alejandro Criado  ( Universidade da Coruña, Centro de Investigacións Científicas Avanzadas ) for XPS analyses.
The database consists of 50 different simulations with random initial conditions of position q and linear momentum p of both masses m 1 and m 2 around a mean position and linear momentum of q 1 = (4. 5, 4. 5) m, p 1 = (2, 4. 5) kg•m/s, and q 2 = (-0. 5, 1. 5) m, p 2 = (1. 4, -0. 2) kg•m/s respectively. The masses of the double pendulum are set to m 1 = 1 kg and m 2 = 2 kg, joint with springs of a natural length of λ 0 1 = 2 m and λ 0 2 = 1 m and thermal constant of C 1 = 0. 02 J and C 2 = 0. 2 J and conductivity constant of κ = 0. 5. Note that the double pendulum constitutes a closed system as a whole, but this is not the case for each one of the simple pendula. Both start from a temperature of 300 K. The simulation time of the movement is T = 60 s in N T = 200 time increments of t = 0. 3 s.
We use this graph-based framework to learn the self contribution of the dynamics, i. e. the first two terms of Eq. (  16 ). The boundary terms are learned using a standard structurepreserving neural network  [46]  with the additional input of the external forces applied to the beam. The dimensions of the beams are H = 10, W = 10 and L = 40. The finite element mesh from which data are obtained consisted of N e = 500 hexahedral linear brick elements and N = 756 nodes. The constitutive parameters are C 10 = 1. 5 • 10 5 , C 01 = 5 • 10 3 , D 1 = 10 -7 and ḡ1 = 0. 3, ḡ2 = 0. 49, τ 1 = 0. 2, τ 2 = 0. 5 respectively. A distributed load of F = 10 5 is applied in 52 different positions with an orientation perpendicular to the solid surface. Simulations were quasi-static and included N T = 20 time increments of t = 5 • 10 -2 s.
Acknowledgements This material is based upon work supported in part by the  Army Research Laboratory  and the  Army Research Office  under contract/grant number  W911NF2210271. This work has also been partially funded by the  Spanish Ministry of Science and Innovation ,  AEI /10. 13039/501100011033 , through Grant number  PID2020-113463RB-C31. And by the  Primeros Proyectos Grant  from  Polytechnic University of Madrid ,  ETSII-UPM22-PM01. The support of  ESI Group  through the Chairs at  ENSAM Paris and Universidad de Zaragoza  is also gratefully acknowledged.
Finite-difference time-domain simulation Finite-difference time-domain (FDTD) simulations were used to calculate the electric field distribution. Oscillating dipoles are used to simulate point sources such as fluorescent molecules. The simulation volume is a 1 × 1 × 1 μm 3 with the 3D uniform grids, and a minimum mesh size is 0. 25 nm. Non-physical reflections on the simulation walls are suppressed by perfectly matched layer (PML) boundary conditions along the x-, yand z-axis. Once the 3D uniform mesh grids have been created, electric field vectors can be extracted in the Lumerical FDTD scripting window or in MATLAB. Emitted intensity distribution of the dipole source and a vector plot of the electric field distribution were calculated by a xz-plane power monitor. A 1D plot of the dipole's emission intensity distribution was extracted from a 1D x-power monitor placed at z = 100 nm and y = 0 nm.
Acknowledgment: YUL, AD, and JWW conceived the research. KRC and MK performed the experiment. All authors analyzed the data and contributed to the scientific discussion. All authors wrote the paper. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Research funding:  YUL  acknowledges  National Research Foundation of Korea  for funding ( 2022R1C1C1006040 ,  2017R1E1A1A01075394 ,  2014M3A6B3063708 ). JWW thanks  Ewha Womans University  for support through  Ewha  academic achievement award 2020. KRC  acknowledges  National Research Foundation of Korea  for funding ( 2022R1A6A3A01087064 ). This work was supported by  Regional Innovation Strategy (RIS)  through the  National Research Foundation of Korea (NRF)  funded by the  Ministry of Education (MOE)  ( 2021RIS-001 ).
Numerical simulations Simulations are carried out in this section to quantify the performance of correlation sidelobe suppression and the errors in the reconstructed responses. The proposed CS-based method is assessed under a range of conditions, including different noise bandwidths, faults sizes, noise spectra and distances between faults. The CS convex optimization problem in Eq. (  7 ) is solved with convex programming modeling software CVX  [38]. In the simulations, noise sources are randomly distributed within a pipe following the uniform distribution, and 500 noise source locations are realized by different trails of Monte Carlo simulations. The length and diameter of the pipeline are 1000 m and 150 mm, respectively. The wave speed is assumed as 1000 m/s, and the attenuation coefficient 𝛼 is 0.
10. Previous experiments have measured the wave speed in this pipeline network as 1107 m/s  [33]. In the field experiment, a data acquisition system was plugged into the hydrant to measure the ambient pressure noise in this water pipeline network. The acquisition system is composed of a type 102A07 piezoelectric pressure sensor, a NI 6212 data acquisition board and a laptop-based user interface. The pressure sensor has a flat sensitivity response (-215 dB re 1 V∕μPa), and it can only capture dynamic pressure changes between 0. 1 Hz and 100 kHz. The NI board converts analog outputs of the pressure sensor into digital signals with a 1 kHz sampling rate and the measurement data were saved to the laptop hard drive. The whole system, apart from the laptop, was powered by Lithium-ion batteries and was placed in a trolley case.
The 0. 002 s time difference between the active and passive results again indicates the good accuracy of time instants extracted by the CS framework. Similar processing was carried out for the noise data measured after the gate valve between hydrant A and B was partially closed. In Fig. 14a , severe oscillation is again found in the auto-correlation results from hydrant A, which introduces difficulties in identifying the response of true faults using correlations without prior information. Similarly, for the auto-correlations from hydrant  B (Fig. 14b ), three strong positive peaks can be observed in the auto-correlation results from hydrant B. Additional mild peaks are also found between these strong peaks, and it is challenging to distinguish the real faults from correlation sidelobes. After applying the proposed CS framework, the strong oscillations in Fig.
Acknowledgements The research leading to these results has received funding from the  CoEC  project under the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  952181. This work was performed using HPC resources from  GENCI-TGCC  (Grant  2022-A0112B10157 ). The authors thank  Professor Deanna Lacoste  for fruitful discussions on plasma-assisted combustion experiments.
Another practice to support reproducibility and third-party validation is the publication of raw datasets. Indeed, the creation of community-led, open databases has already been considered in the battery field  47, 48. Another option could be to encourage the adoption of a "limitations of the study" section in peerreviewed scientific articles as a standard practice, similar to that applied in other fields, notably the social sciences  49, 50. In this way, the scientists can clearly discuss methodological limitations, and the authors can clarify what remains outside the scope of their study in the article itself.
Acknowledgements U. U. would like to acknowledge  Nissan Motor Co. , Ltd. Japanese team , i. e. ,  Tabuchi Yuichiro ,  Takaichi Satoshi ,  Hosaka Kenji ,  Aotani Koichiro ,  Kotaka Toshikazu ,  Nakayama Ken , for the enriching discussions during the writing process. U. U. would also like to acknowledge  Prof. Dan Steingart  from  Columbia Engineering  for the valuable discussions, particularly on the lithium and silicon energy contents, and the Rho Motion research analyst team for the valuable discussions during the manuscript revision. M. J. L. would like to acknowledge  David Raymand ,  Matilda Klett , and  Pontus Svens at Scania CV AB  for valuable discussions. J. T. F. would like to acknowledge BloombergNEF,  Logan Goldie-Scot ,  Albert Cheung , and  Daixin Li  for their general guidance and for allowing the reproduction of data from BloombergNEF.
Initially built for telecommunication tasks, the tower was habilitated as met masts by placing meteorological sensors at 20 m and 50 m, follow- The remote measurement station at Telchac Puerto (TCP), located at 21 • 02 54" N and 89 • 38 38" W, was part of a state network of stations along the Yucatan coast controlled and monitored from a central station. Initially built for telecommunication tasks, the tower was habilitated as met masts by placing meteorological sensors at 20 m and 50 m, following the methodology presented in the Wind Resource Assessment Handbook  [37]. Although this network of stations was in operation from 2007 to 2012, only the data measures from January to June 2009 were used, since in this period there were reliable continuous measurements. The parameters measured were wind speed (WS) and wind direction (WD), air temperature (T air ), and atmospheric pressure (P atm ).
The database contains average values every 10 min on digital hard drives. Table  1  presents the technical characteristics of the sensors and the height at which they were installed. These parameters were used to perform the data validation. Wind resource assessments typically consider longer periods of measurement. Previous studies have been conducted to quantify the wind potential at the study site before the wind farm installation in the zone  [32, 33]. For this reason, the present research study focuses on the relationship between atmospheric stability and energy production budget, rather than contributing to resource assessment based on traditional techniques. Although a 6-month measurement database consisting of 24,192 values was obtained, only some of the data was reliable due to several factors.
These factors include failure of the instruments' power supply, invalid standard deviation values of each variable (outliers), and unusual records generated by errors in the measurement sensors (for example, an air temperature of 999 • C). Therefore, a quality check was necessary to obtain a reliable database used in the present study. For these variables, the corresponding filtering criteria followed the IEC 61400-12 standard regarding the frequency of acquisition and treatment of data  [15]. These criteria are as follows: WD 0-360 • ±3 • 1 • 20 m, 50 m T air CSI 108 -5 • C to 95 • C -5 to 95 ±0. 2 • C 0. 1 • C 20 m,.
• Wind speed (WS) must remain in the range of 0 m/s ≤ WS ≤ 30 m/s; higher values are discarded because they are unusual for this region. • Wind direction (WD) must span within 0 • ≤ WD ≤ 360 •. • Abrupt changes in wind direction (for example, from 90 • to 270 • from one instance to another) are not considered. After applying the criteria, the new database for the study preserved 91% of the data.
Although not focused on displacement monitoring, these applications would clearly benefit from a data availability increase. In most scientific works regarding RFID localization, the presented datasets show smooth and correctly-sampled measurements that correspond to laboratory-controled FIG. 1  Map of the RFID-instrumented sites across France and Switzerland, represented as red dots. experiments  [13] -  [21]. In real-life scenarios such as retail environments  [2]  or outdoor landslide monitoring  [1] ,  [22] , the acquired data is inevitably noisier and intermittent. At the same time, RFID generally yields abundant and redundant data that can enhance the data from each tag  [23] ,  [24]. In many cases the objects are monitored by multiple tags, multiple antennas or through multiple carrier frequencies, with the objective of forming tag arrays or yielding more robust data.
A. RFID Instrumentation This study will discuss the RFID data from 4 landslides, that all share the same measurement scheme. Several RFID tags (Confidex Survivor) are continuously read by an acquisition system consisting of an interrogator (Impinj SR420 or equivalent) and at least two reader antennas. A micro-computer and a modem ensure continuous data acquisition and transfer. The measurement rate depends on the site and the available power : autonomous stations relying on solar/wind energy use a lower acquisition frequency than power-grid-connected stations. On average the available data gives a minimum of 100 phase readings per day and per tag. Both the Phase of Arrival (PoA) and the Received Signal Strength (RSSI) are measured, in order to estimate the quality of the received phase signal.
b) Absolute reference measurement: When at least one absolute reference measurement (tacheometry, GPS or extensometer) is available on a field, it is used to help unwrap the whole dataset. This was the case in the Pont-Bourquin landslide where absolute displacement data was available (although scarce in time) via an extensometer. If the reference data is continuous in time, guided unwrapping can be performed. If not, discrete corrections are performed either automatically or by manually correcting the phase. This approach allows keeping track of long-term displacements, as shown in Figure  6.
The PEDOT:PSS channel width, length, and overlap were measured through optical microscopy (Nikon) while the channel thickness was extracted with a mechanical profilometer (Dektak XT, Veeco). NaCl (100 mm) in deionized water was used as the liquid electrolytic medium, and a Ag/AgCl pellet as the gate electrode. A three-electrode configuration was used for the electrochemical impedance spectroscopy (EIS) measurements (Metrohm), with platinum and Ag/AgCl counter and reference electrodes, respectively. The source and drain electrodes were shorted together, and the channel was used as the working electrode. In OECTs, the wiring of the OECT is illustrated in Figure  1a , in a common source configuration, and tested using a National Instruments (NI) PXI system and custom LabView software. The drain bias was applied using a NI PXIe-4145 Source-Measure unit.
Acknowledgements The authors gratefully acknowledge the funding from the  Agence Nationale de la Recherche (ANR)  under the Grant  ANR-20-CE06-022 , supporting the collaborative research project  MASTERMIND. This work was in part performed within the framework of the  Centre of Excellence of Multifunctional Architectured Materials "CEMAM"  under the  ANR-10-LABX-44-01  Grant. G. S. , P. R. , and S. S. acknowledge supports from the  Centre National de la Recherche Scientifique (CNRS)  at the  UMR5279-LEPMI  and  UMR5819-SyMMES  labs and from the  Université Grenoble Alpes  at  UMR5819-SyMMES labororatory , respectively.
The electrochemical experiments were performed using Kel-F (PCTFE) cells containing approximately 350 µl of the electrolyte and equipped with counter and pseudo-reference electrodes made of platinum. The cells were cleaned prior to each experiment using a solution of sulphuric acid (H2SO4) and hydrogen peroxide (H2O2) in the volume ratio 2:1, then concentrated nitric acid (HNO3), and finally rinsed several times in boiling ultra-pure water  [36]. The Pt pseudo-reference was calibrated before each experiment (+0. 75 V vs SHE). The working electrode area was 0. 16 cm² delimited by an O-ring. The experiments were performed using a PicoStat bi-potentiostat and the Picoscan software from Agilent Technologies. The electrolytes were a 10 mM HCl aqueous acid solution of pH 2. 3 as the reference solution without the inhibitor and a 10 mM HCl + 0.
6 eV). The binding energy was calibrated by referring to the Fermi level of the sample. A 900 µm diameter X-ray spot size was used, and the take-off angle of the collected photoelectrons was 90°. Survey spectra were recorded with a pass energy of 100 eV at a step size of 1 eV and high-resolution spectra of the C 1s, O 1s, N 1s, S 2p, Cu 2p, Cl 2p core levels and Cu LMM Auger transition were recorded with a pass energy of 20 eV at a step size of 0. 1 eV. Decomposition of the spectra was performed with the Thermo Fischer scientific software Avantage using an iterative Shirley-type background subtraction. The CasaXPS software was used to decompose the Cu Auger spectra. The values of the photoionization cross-sections at 1486. 6 eV were taken from the Scofield database  [37] , the transmission function of the analyser was provided by Thermo Fisher, and the inelastic mean free paths were calculated using the TPP-2M formula  [38].
ToF-SIMS analysis was performed using a ToF-SIMS 5 spectrometer (IonTof -Munster Germany) operating at a pressure of 5 x 10 -9 mbar. Data acquisition and post-processing analysis were performed using the SurfaceLab software v6. 5. Analysis was done in high current (HC) bunched mode using Bi + primary ions of 25 keV energy at a target current of 1. 2 pA over an area of 100 x 100 µm². Depth profiles were obtained by interlacing analysis with sputtering using a Cs + ion gun of 0. 5 keV delivering a 20 nA target current over a 500 x 500 µm² area. The combined use of Bi + primary ions and Cs + sputtering ions enabled us to analyse both the organic and inorganic surface layers. Both ion beams were at an incidence angle of 45° with respect to the sample surface and were well-aligned to ensure analysis at the centre of the sputtered crater.
Next, we examined the energy-level alignment of Ag-CZTSSe, CdS, and ZTO buffer layers by UPS measurement. It has been investigated that if the conduction band offset (CBO) is negative (CB of the buffer layer < the CB of the absorber) which results in a "cliff type" band alignment that upsurges the carrier recombination rate at CZTSSe/buffer layer interface, thus lower Voc of the resulting solar cells. [19, 33] Conversely, a more positive CBO (>0. 3 eV) leads to "spike type" alignment that blocks the photocurrent and causes lower J SC and PCE. So, the favorable CBO is determined to be marginally positive or nearly zero (0-0. 3 eV). [19, 33] In this work, the bandgap (E g ) of Ag-CZTSSe, CdS, was obtained from EQE data while E g of ZTO was obtained from transmittance spectra (Figure  S6 , Supporting Information) while the CBO was obtained from UPS data analysis (Figure  S7 , Supporting Information).
Atomic force microscopy (AFM) images were obtained by NT-MDT system using semi-contact mode. CPD was measured by Kelvin probe force microscopy (KPFM) (Dimension Icon, Bruker) with SCM-PIT probe under KPFM-AM scan mode. Thermo Fischer Xi+ system was utilized to conduct X-ray photoelectron spectroscopy (XPS). Transmission electron microscopy (TEM) analysis was performed by FEI Titan Cubed Themis G2 300 microscope. Ultraviolet photoelectron spectroscopy (UPS) was executed by PHI 5000 Versa Probe III with He I source (21. 22 eV) under an applied negative bias of 9. 0 V. The dark and illuminated J-V characteristics were measured by Keithley 2400 and Zolix SS150, and standard test condition (AM 1. 5) was used to calibrate the solar simulator. External quantum efficiency (EQE) data were obtained using Zolix solar cell EQE/IPCE system with calibrated Si and InGaAs as references.
Acknowledgements N. A. and Y. Z. contributed equally to this work. This work was supported by the  National Natural Science Foundation of China  ( 62074102  and  62204067 ) China, the  Science and Technology Plan Project of Shenzhen (20220808165025003) China. Guangdong Basic and Applied Basic Research Foundation  ( 2022A1515010979 ) China. The authors wish to acknowledge the assistance on (TEM/STEM/FIB) received from the  Electron Microscope Center of Shenzhen University.