dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions In this work, we employed molecular dynamics simulations to study electrode charge and polarization dynamics in gold/NaCl(aq) nanocapacitors. Using equilibrium and nonequilibrium simulations, we investigated the impact of ion concentration and interelectrode distance on the charge dynamics. Specifically, ions induce slower dynamics compared to pure water systems, and more concentrated solutions result in faster charge relaxation. We simulated bulk NaCl(aq) systems to compute the frequency-dependent conductivity and validated the simulation results with extensive experimental datasets. Then, we calculated the frequency-dependent impedance from the electrode charge fluctuations in nanocapacitors. The comparison between the impedance of nanocapacitors and that of bulk showed that the electrode/electrolyte interfacial contribution is essentially capacitive and that the electrolyte response is bulk-like even when the interelectrode distance is only of a few nanometers, provided that the latter is sufficiently large compared to the Debye screening length.
Acknowledgments The authors acknowledge fruitful discussions with  Mathieu Salanne ,  Michiel Sprik ,  Clare Grey  and  Mathijs Janssen. S. J. C. is a  Royal Society  University Research Fellow (Grant No. URF\R1\211144) at the  University of Cambridge. SPN acknowledges funding from the  European Union 's  Horizon 2020 Research and Innovation Program  under Grant Agreement No. 957189  ( BIG -MAP  project). G. P. and B. R. acknowledge funding from the  European Research Council  under the European Union's  Horizon 2020 research and innovation program  (project  SENSES , grant Agreement No. 863473 ). G. P. and B. R. acknowledge access to HPC resources from  GENCI-IDRIS  (grant no. 2022-AD010912966R1 ).
In this device, the change in channel conductance originates from polarization modulation in the ferroelectric gate dielectric layer. Extending incremental bias pulses engenders excellent potentiation and depression characteristics in the device (Fig. 5b ). By using HZO FeFETs, Kim et al. [68]  constructed a two-layer neural network (Fig. 5c ) comprising 400 input neurons used to simulate 20×20 database data and 10 output neurons corresponding to 10 numeric categories (digits 0 to 9). For simulation, they used the multilayer perceptron (MLP) algorithm in the network to update the weights. They reported that after 125 training epochs, the neural network achieved 91. 1% accuracy, which was comparable to the 94. 1% accuracy obtained under ideal conditions (Fig. 5d ).
13c ). They integrated HZO with amorphous In2O3 doped with 1% tungsten (IWO) by using a low-thermal-budget process. The IWO FeFET with an ultrashort channel length of 20 nm achieved a 0. 45 V read memory window, 100 ns write time, and >10 8 endurance cycles. Dutta et al. [122]  also reported 2-bit/cell synaptic weight cells. They used the VGG-8 model to make inferences from the Canadian Institute for Advanced Research (CIFAR)-10 image dataset; their compute-in-memory (CIM) system-level analysis demonstrated that the energy efficiency of the 22-nm-BEOL FeFET with a small array area was three times higher than that of 7-nm-static RAM. Fig. 13d  presents another ferroelectric synaptic array-based CMOS-compatible CIM accelerator. The array unit is based on a composite of indium zinc oxide (IZO) and HfZrOx.
Acknowledgments This work was supported by  National Key Research and Development Program of China  ( 2021YFA1200700 ), The  National Natural Science Foundation of China  ( T2222025  and  62174053 ),  Open Research Projects of Zhejiang Lab  ( 2021MD0AB03 ),  Shanghai Science and Technology Innovation Action Plan  ( 21JC1402000  and  21520714100 ) and the  Fundamental Research Funds for the Central Universities. This manuscript was edited by  Wallace Academic Editing.
667 Overall, the comparison between analog and numer-668 ical experiments shows a reasonable agreement between 669 the two datasets. Both datasets exhibit a power law de-670 pendence of Re with Ra close to the expected law with 671 a 0. 5 exponent value suggested by previous analog, nu-672 merical and theoretical works. To further compare the flow characteristics obtained 675 with the numerical code with those of the laboratory 676 experiments, we computed the spatial spectrum of the 677 velocity field. To do so, we interpolated the data from 678 the numerical code onto the same grid as the exper-679 imental data. We then performed a 3D fast Fourier 680 transform on each component of the velocity field. Fig-  681  ure 9 displays the sum of the power spectral densities, 682 averaged over y and z directions.
The available WET results were assumed to be representative for PW toxicity for all installations on the Dutch continental shelf and the likelihood that the risk was/was not adequately controlled for Fig. 2. The tiered approach to produced water risk-based assessment (after IOGP, 2020). Each Tier involves the assessment of risk following a four-step approach (after OSPAR, 2012). each of the 73 installations was assessed without any further sampling and analysis. No further assessment in a follow-up tier was decided for installations with a likelihood of having an adequately controlled risk greater than 99. 5%. Both examples show that collection and application of reference data together with precautionary assumptions in Tier 0 can be helpful to assess the significance of the risks and to support decisions on any follow-up assessments.
Smit et al. (2011)  describe how the EIF has been applied in Norway as a risk management tool to assess and reduce the environmental risk of offshore discharges. Knudsen et al. (2006)  showed how the EIF was applied to identify a corrosion inhibitor as a major risk contributor and how chronic toxicity data were collected to refine the assessment. The methods from  Parkerton et al. (2018)  and the EIF are still quite conservative as both do not explicitly address exposure duration as part of the assessment. To study the influence of exposure time, Tier 2 assessments can be further refined. Beyer et al. (2011)  assessed the likelihood that exposure to alkylphenols from PW would lead to reduced reproduction in Atlantic cod (Gadus morhua). Broch et al. (2013)  studied the direct effects of PW discharges on the biomass of copepods, Calanus finmarchicus.
WET vs substance-based assessments Under the different regulatory frameworks and across all tier levels, data for deriving toxicity thresholds for PW may be collected through WET testing and/or through a substance-based approach. Several studies tried to compare Tier 2 RBA results based on these two lines of evidence. Parkerton et al. (2018)  showed that the substance-based approach was more conservative than WET for 12 Australian installations, while De Vries et al. (  2022 ) concluded that the WET based approach resulted in a slightly higher predicted hazard than the substance-based approach for 25 Norwegian installations. This finding was supported by  Roex et al. (2012)  based on data for several installations from the OSPAR region, but this study did not include oilfield chemicals. Factors that may explain these variable results might be the substances selected to represent the PW composition, the availability and reliability of toxicity data, the ability to accurately assess toxicity by WET testing, and the applied extrapolation techniques.
g. ,  OSPAR, 2012; USEPA, 2017). Tiered approaches help to scale efforts to the situation depending on location specific circumstances and sensitivities, especially when local regulatory frameworks do not include RBA requirements. The collected studies show there is a large body of data gathered from various regions on PW characteristics, dispersion, exposure and effects, that can be used in such situations. These data could be used in combination with precautionary approaches towards supporting arguments in other regions, as well as building up statistical information to allow risks to be quantified, especially at Tier 0. There is considerable opportunity for these datasets to be harnessed to make RBA a more efficient process and to lower uncertainties, thereby helping to identify the optimum and most sustainable management choices.
Methods The first author of this paper undertook 11 field visits to Ophir plantation between 2009 and 2021 for various organisations and projects (see Appendix 3 for an overview of field visits and a list of recorded stakeholder interviews with reference numbers). The visits in 2009 involved four weeks of fieldwork in Ophir, when the primary aim was to understand how smallholders successfully managed their intensive production systems. The field visits in 2011, 2014, 2016 and 2018 each spanned 7-10 days and were undertaken for different projects. In 2020 and 2021, the first author undertook 42 days of fieldwork in Ophir for a project concerning smallholder replanting strategies. No predetermined research approach for this particular paper had been defined when data collection began. However, extensive fieldwork and repeated visits fostered closeness and trust among interviewees.
Fully quoting exactly what each stakeholder said is limitedly possible as the interview reports mainly contained summaries of statements rather than literal transcriptions. Grey project literature was also collected, including reports written by project implementors and relevant institutions during establishment of the plantation. The large number of recorded interviews, and many more discussions that were not recorded, allowed us to triangulate our findings, which, in turn, provided relevant pointers towards critical action networks. Subsequently a well-informed narrative on developments in Ophir was constructed. Quantitative data involved three components and substantiated the narrative provided by the qualitative data. First, data were collected from cooperatives on yields, production costs, deductions for services, and actual transfers associated with all 2400 smallholder plots in 2009.
Ensemble-based history matching was then conducted using PESTPP-IES  (White, 2018) , which implements an iterative ensemble smoother form of the GLM algorithm  (Chen and Oliver, 2013). PESTPP-IES was selected because it enables history matching of highly-parameterized models at a significantly lower computational burden than sampling methodologies such as Markov Chain 160 parameter posterior variance and fit to observations  (Fienen et al. , 2022). Details on the observation dataset and the measurement noise are provided by  Coulon et al. (2021). History matching was conducted under steady-state conditions, using 500-year simulations with constant boundary conditions (i. e. , sea level, recharge and pumping rates) representative of the average conditions during the 2014-2019 calibration period.
3b ). History matching yielded a current recharge ensemble (Rcurrent, MODFLOW), containing Npost plausible recharge inputs for the groundwater model (both informed by the observation dataset and incorporating possible correlations with the hydraulic conductivity parameters), and conveying parameter and observation uncertainty. The information contained in both ensembles needed to be merged, to obtain a 2050 recharge ensemble (R2050, MODFLOW) containing Npost plausible recharge inputs for the groundwater model, preserving the information acquired through 205 history matching (i. e. , fit to observations, parameter correlations) but also accounting for future climate projections, and therefore conveying parameter, observation and climate uncertainty. A ΔR ensemble was first generated, containing 72 possible recharge variations between current conditions and 2050, i.
6b ), and no prior-data conflicts were observed. These results were similar to those of the deterministic parameter estimation conducted by  Coulon et al. (2021) , which had yielded a final objective function of 1175 and similar patterns in the simulated-to-observed scatterplots (e. g. , an outlier in the municipal well dataset and biased freshwater head observations in deep wells). Hydrogeologically reasonable values were obtained in the posterior parameter ensemble, with the sand dunes generally more permeable than the sandstones, in turn more permeable than the glacial sediments 290 (Table  2 ). Figure  7  presents a random sample of the 173 hydraulic conductivity fields obtained through history matching, and the associated recharge values.
Acknowledgments This work was funded by the  Ministère de l'Environnement et de la Lutte contre les changements climatiques of Quebec , as part of the project  « Acquisition de connaissances sur les eaux   souterraines dans la région des Îles-de-la-Madeleine » (Groundwater characterization project in the Magdalen Islands region ). The authors would like to thank the  OURANOS consortium  and  Marco Braun  for supplying the daily precipitation, minimum and maximum air temperature climate simulations for the Magdalen Islands 470 for the period 1950-2100. A scholarship provided by the  Canadian National Chapter of the IAH (IAH-CNC ) to  Cécile Coulon  helped conduct this study. Jeremy White  was funded by  INTERA Incorporated. https://doi. org/10. 5194/hess-2023-38 Preprint. Discussion started: 7 March 2023 c Author(s) 2023.
Code availability The Python scripts used to implement the workflow and produce figures are available on GitHub at https://github. com/Cecile-A-C/swi2-ensembles and are archived at https://doi. org/10. 5281/zenodo. 7574457 (version1. 0. 0, MIT license). MODFLOW-2005 (version 1. 12. 00) is available at https://www. usgs. gov/software/modflow-2005-usgs-three-dimensional-finite-difference-ground-455 water-model. PESTPP-IES, PESTPP-SWP and PESTPP-MOU are available at https://www. usgs. gov/software/pest-softwaresuite-parameter-estimation-uncertainty-analysis-management-optimization-and and the source code is available at https://github. com/usgs/pestpp/releases (version 5. 1. 13 was used for PESTPP-IES and PESTPP-SWP and version 5. 1. 24 was used for PESTPP-MOU).
Two inclinometers (IS2BP090-I-CL; GEMAC, France) were tied to the tree to measure the root-soil system rotation θ 1r (at the stem base) and the total tree inclination θ 1 (close to the cable attachment point). Data from the load cell and inclinometers were recorded by a logger at a sampling rate of 20 Hz (CR1000X; Campbell Scientific Ltd. , France) and uploaded to a laptop computer for processing. The turning moment M was calculated as follows: M = F x Lcosθ 1 + F y Lsinθ 1 (1) where θ 1 is the total rotation given by the deflection angle of the trunk at the cable attachment point with respect to the vertical, L is the height of the cable attachment point, F x = Fcosθ 2 and F y = Fsinθ 2 are respectively the horizontal and vertical components of the force F measured in the cable, θ 2 the angle of the cable from the horizontal (Fig.
Statistical analysis Statistical analyses were performed using R-software (R Core Team, 2020). We first used ANOVA on lm model to check that there were no difference in the soil water content during pulling tests as well as in the rooting depth of the tree groups (corresponding to each treatment) according to the following model: anova(lm(rooting_depth/water content ~ treatment). In further analysis, we considered the factorial design of our experiment testing the two main effects, thinning and guying, together with their interaction. First, linear mixed effects model (nlme package) with pairing as a random effect was used to assess the effects of thinning, guying and their interaction on mean values of the root system properties displayed in Table  2:   Table 2  P-values of the main effects and their interaction (guying and thinning) of linear mixed effect models (model 1).
No directional anisotropy was detected in the growth of structural roots and the initial root-soil plate stiffness In windy locations, root systems exhibit anisotropic growth with more structural root mass on the leeward side than the windward side of the tree relative to the prevailing wind direction  (Nicoll and Ray, 1996). However data about the directional dependence of mechanical performances of the root-soil plate are lacking. In this study, we measured the initial stiffness of the root-soil plate in two directions: the prevailing wind direction and perpendicular to it. No directional difference was observed in the initial stiffness of the root-soil plate. However, the latter may reflect more the development of fine roots and coherence of the root system with the neighbouring soil than the thickening of structural roots that is involved in later phases of mechanical loading even if both parameters are in general well related  (Jonsson et al.
We therefore looked not only on global properties (stem biomass, root-soil plate mechanical behaviour) but also at growth and the growth allocation between different tree compartments during the four years before and after the treatment to analyse changes in the biomass allocation. Fig. 5b  shows that in thinned trees free to sway the biomass is preferentially allocated to the stem instead of roots, a pattern that is not observed in thinned and guyed trees. Furthermore, growth of both structural roots and the lower part of the stem is highly reduced in unthinned and guyed trees. In our dataset, the effect of thinning and guying was lower in the first year, which was the driest one, for both tree compartments with no delay between the root and the stem growth response (not shown). These results support the hypothesis of a reinforcement of mechanically most stimulated and at risk points and suggest that further developments should investigate how the response is physiologically driven (how can growing cells be coordinated inside the whole tree to prioritize the weakest point) and how the priorities are enhanced in the case of poor light levels or water availability.
Acknowledgements Authors sincerely thank all members of  SilvaTech plateform  and  Sylviculture Pole of SILVA laboratory ,  INRAE Grand-Est  for the technical help on the field and during the stem and root samples characterisation. This work was funded as part of a PhD project by supported by " Région Grand Est " and the  INRAE division ECODIV. This work was also supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE).
Data The Mars Orbiter Laser Altimeter (MOLA) Precision Experimental Data Record (PEDR) dataset includes a total of 8505 profiles, acquired in the mapping and extended phases of Mars Global Surveyor (MGS) from February, 1999 to May, 2001, which spanned approximately a full Martian year  [1]. The PEDR dataset was processed using a MGS orbit trajectory-and a Mars rotational model by GSFC dating back to 2003. Therefore, we reprocessed the MOLA data, incorporating a refined orbit model from [4] and the IAU2015 Mars rotational model  [5]  for new MOLA geolocations. To account for the special relativity effect, a pointing aberration correction has also been applied in the reprocessing [6].
Acknowledgements This project received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie action  (Grant No. 794492 ), the  Fonds AXA pour la Recherche  to SB, the  Doctoral School for Health and Life Sciences of the University of Bordeaux  to JR, the  European Research Council (ERC-SyG ENSEMBLE)  (Grant No. 951294 ),  Human Frontier Science Program  (Grant No. RGP0036/2020 ),  ERA-NET NEURON  (Grant No. ANR-17-NEU3-0005 ), the  Fédération pour la recherche sur le cerveau (FRC) , and  Agence Nationale de la Recherche  (Grant No. ANR-17-CE37-0011 ) to UVN.
The Management and Uncertainties of Severe Accidents (MUSA) project was funded in HORIZON 2020 and is coordinated by CIEMAT (Spain). The project aims at consolidating a harmonized approach for the analysis of uncertainties and sensitivities associated with Severe Accidents (SAs) analysis, focusing on source term figures of merit. The Application of Uncertainty Quantification (UQ) Methods against Integral Experiments (AUQMIE -Work Package 4 (WP4)), led by ENEA (Italy), was devoted to apply and test UQ methodologies adopting the internationally recognized PHEBUS FPT1 test. FPT1 was chosen to test UQ methodologies because, even though it is a simplified SA scenario, it was representative of the in-vessel phase of a severe accident initiated by a break in the cold leg of a PWR primary circuit.
These capabilities are also used to develop accident management strategies. Several models/correlations have been implemented in state-of-theart SA codes and must be set by a code user during the input-deck development. Models/correlations that are implemented in a SA code reflect the state-of-the-art knowledge of SA phenomena/processes. However, even though several experimental campaigns in the field of SA phenomena (OECD/NEA/CSNI, 1992, OECD/NEA/CSNI, 1996, OECD/ NEA/CSNI, 2001, OECD/NEA/CSNI, 2009, OECD/NEA/CSNI, 2014) have been performed and provided a valuable "assessment database"  (Mascari et al. , 2015)  for SA simulation tools, there is the need for reducing some uncertainties still present  (Mascari et al. , 2019a; Mascari et al. , 2019b , Van Dorsselaere et al. , 2016). Therefore, an investigation of phenomena/processes, to date not researched in geometric prototypical experimental facilities with prototypical material, should be addressed.
Uncertain input parameters A database of uncertain input parameters with their range and the corresponding Probability Distribution Functions (PDF) is the output of MUSA WP2. WP4 partners were free to select the uncertain input parameters for the UQ with the following recommendations: • WP4 partners can select the input uncertain parameters form the database assessed in the WP2; • In case WP4 partners may want to use their own uncertainty characterization, they should make it defendable with respect to the ones proposed in WP2; • WP4 partners can use parameters not included in the WP2 database, but their characterization (PDF and range) should be supported by reference or engineering judgement; • Partners are invited to select input uncertain parameters that have the most influence and then rank them within the uncertainty application.
, 1997 , Allison et al. , 1998). Considering the UT, 8 partners adopted DAKOTA  (Adams et al. , 2020 , Dalbey et al. , 2020)  1 partner adopted RAVEN  (Rabiti et al. , 2017) , 3 partners adopted SUNSET (Chojnacki and Baccou), 3 partners adopted SUSA  (Kloos, 2020) , 1 partner adopted URANIE  (Blacard et al. , 2019) , 2 partners performed the UaSA only through Python (Python, 2023) scripts. The nodalizations developed for the calculations of MUSA WP4 depend on the choices made by each partner and on the code used. In fact, in some codes a reference geometry can be integrated directly into the input-deck and in this case, this reference geometry has been used directly without any modification, or else slightly modified by the partner. Otherwise, a complete nodalization is developed. The following list summarizes the main features of the partners nodalizations: • CIEMAT: The PHEBUS-FPT1 MELCOR input deck developed by CIEMAT incorporates data mainly from the PHEBUS-FPT1 final report  (Jacquemain et al.
, 2000). Overall, there are 30 Control Volumes (CVs), 29 Flow Paths (FPs), and 68 Heat Structures (HSs), describing the test-section and down-stream circuit. • EPRI: MAAP has traditionally included the FPT1 experiment as a code benchmark, but the scope of the benchmark was limited to the bundle degradation phase and did not evaluate later phases of the FPT1 experiment. The scope of the uncertainty analysis application in this section include the aerosol release and transport phase of the experiment in addition to the bundle degradation phase, but did not include the washing or chemistry phases. The thermal-hydraulic nodalization has 15 control volumes and 35 heat structures. Table  2  reports the computing environment adopted by the various partners to perform the WP4 calculation. Most of the partners used a workstation based on Windows operative system.