dataesr/scientific-paragraphs-categorization huggingface dataset:
We adopt a strongly elevated heat flow of 140 mW m -2 for areas with active volcanoes and a moderately elevated heat flow of 80 mW m -2 for regions that experienced Holocene volcanic activity  [71]. Combining surface heat flow data with surface temperature data (Fig. 3 ) allows us to extrapolate subsurface temperatures to the required depths. For the surface temperature, we use annual continental mean surface temperatures recorded between 1950 and 2000 from the WorldClim Global Climate Database from Hijmans et al. [72]. We combine this data with the model of Kalnay et al. [73]  for surface temperatures of Antarctica and with the model of Boyer et al. [74]  for ocean surface temperatures. As reference level, we use the ETOPO1 elevation and bathymetry model (Fig. 4 ) from Amante and Eakins  [75].
In this paper, the nonlinear dynamics of a PV-fed high-voltage-gain single-switch quadratic boost converter loaded by a grid-interlinked DC-AC inverter is explored in its parameter space. The control of the input port of the converter is designed using a resistive control approach ensuring stability at the slow time-scale. However, time-domain simulations, performed on a full-order circuit-level switched model implemented in PSIM c software, show that at relatively high irradiance levels, the system may exhibit undesired subharmonic instabilities at the fast time-scale. A model of the system is derived, and a closed-form expression is used for locating the subharmonic instability boundary in terms of parameters of different nature. The theoretical results are in remarkable agreement with the numerical simulations and experimental measurements using a laboratory prototype.
A Glimpse at the Solar PV System Behavior from Its Complete Mathematical Model Let us take a quick glimpse at some of the typical operating dynamic behaviors of the system in terms of different parameter values. The numerical simulations are performed using PSIM c software using the detailed switched model of the complete system consisting of the DC-DC quadratic boost converter performing MPPT and interlinked to the grid-connected DC-AC inverter as depicted in Figure  2. The nonlinear PV panel model is implemented using the physical model of the solar module in the renewable energy package of PSIM c. The set of parameter values shown in Table  3  is used for the quadratic boost converter, those in Table  1  for the PV module, and the ones in Table  2  for the DC-AC inverter. The inductance values were selected to guarantee continuous conduction mode (CCM), and the capacitance values were chosen to get acceptable voltage ripple amplitudes.
However, it was observed that partial saturation of the inductors and the drop of their inductance values with the operating currents  [41] , is the main factor. Next, the saturability of the inductors will be taken into account. The variation of the inductance values versus their operating DC currents was experimentally determined. An LCR meter and a current source, both controlled by a LabView c software program, were used to measure the values of the inductances for different current levels. The experimental data obtained and a regression analysis based on least squared error revealed that in the range of current values used, the following linear expressions, relating the inductances L 1 and L 2 and their currents, can be used: L 1 ≈ L * 1 -σ 1 I L1 , L 2 ≈ L * 2 -σ 2 I L2 , (42) where L * 1 = 138 µH and L * 2 = 5.
5 mH are the inductance values under no load condition, σ 1 = 3 µH/A, σ 2 = 1. 2 mH/A, and I L1 and I L2 are given by  (14). The previous equations were used in both the theoretical expression  (41)  and in the numerical results. The theoretical results from (41) are depicted in Figure  15  in the solid curve and those from numerical simulations using PSIM c software are indicated by. After taking into account the inductances drop with the inductor current, a remarkable agreement among the experimental, theoretical and numerical results was obtained. The waveforms of the inductor currents i L1 and i L2 at both sides of the subharmonic instability boundary are represented in Figure  16  together with the ramp signal and the control voltage. By comparing the waveforms in this figure and those in Figure  10 , one can observe a good agreement between the measured and the simulated system dynamics.
Funding: This research was funded by the  Spanish Agencia Estatal de Investigación (AEI)  and the  Fondo Europeo de Desarrollo Regional (FEDER)  under grant  DPI2017-84572-C2-1-R  ( AEI/FEDER, UE). Abdelali El Aroudi  and  Mohamed Al-Numay  extend their appreciation to the  International Scientific Partnership Program ISPP  at  King Saud University  for funding this work through ISPP#  00102.
Acknowledgements This work was supported by the  FCH Joint Undertaking (CRESCENDO Project , Grant Agreement n°779366) and the  French National Research Agency  ( Labex programme, ARCANE ,  ANR-11-LABX-0003-01 ). Goran Drazic  from the  National Institute of Chemistry, Ljubljana, Slovenia , is acknowledged for his work on the HR-STEM microscopy on the  Fe-N-C catalyst  from  Centre National de la Recherche Scientifique (CNRS).
As the simulations support our interpretation that catalytically active sites are indeed efficiently created by SHI irradiation we investigated our samples using X-ray photoelectron spectroscopy (XPS) to obtain information on the elemental composition and chemical state of the catalyst surface. The data for non-irradiated and irradiated MoS 2 samples (the same irradiation conditions as before) are shown in Fig. 5. In both cases we measured a signal originating from the Mo 3d 5/2 and Mo 3d 3/2 peaks of MoS 2 (blue) and MoO 3 (green). 45 In the case of non-irradiated MoS 2 (Fig. 5(a) ) the MoO 3 contributes ∼20% to the overall Mo signal. This can be attributed to the already oxidized edges of the grown MoS 2 flakes as for the XPS measurements the samples had to be exposed to ambient conditions.
Further XPS data and analysis can be found in the ESI. † To test the extent to which the ion irradiation influences the catalytic activity of MoS 2 , we performed linear sweep voltammetry (LSV) measurements on non-irradiated and irradiated MoS 2 in an aqueous 0. 5 M H 2 SO 4 solution (Fig. 6(a) ). For these experiments glassy carbon was chosen as a substrate due to its high conductivity and inert behaviour during hydro-gen evolution reaction (HER) measurements. The ion fluence for glassy carbon/MoS 2 samples used for electrochemical characterization was chosen slightly higher, i. e. 40 ions per µm 2 , while the angle of incidence was kept at 1°. From the AFM analysis these parameters were estimated to yield a sufficiently high sulfur vacancy density without compromising sample integrity due to excessive overlapping of rifts.
Acknowledgements M. S. and L. M. acknowledge funding of the  NU-TEGRAM  project within the  FLAG-ERA program  by the  Deutsche Forschungsgemeinschaft (DFG)  ( SCHL 384/16-1 ). B. R. C. , I. Z. , and Y. -W. C. acknowledge financial support from the  Cluster of Excellence RESOLV at RUB  ( EXC 1096 ), funded by the  DFG. S. K. acknowledges financial support from the  Max Planck Research School for Interface Controlled Materials for Energy Conversion (IMPRS-SurMat ). M. Q. Z. , C. H. N. , and A. T. C. H. acknowledge the support from the  U. S. National Science Foundation (NSF)  Grant  EFRI 2-DARE 1542879. We thank  U. Hagemann  from the  Interdisciplinary Center for Analytics on the Nanoscale  (ICAN, core facility funded by the  German Research Foundation, DFG)  for support with the XPS measurements.
Acknowledgements This work was supported by an  ERC   Consolidator Grant  " MatEnSAP " (D. H. N. , J. Z. Z. ,N. H. ,E. R. ), the  University of Cambridge (Vice-Chancellor and Winton scholarships  to V. A. ), the  Royal Society (Newton fellowship  to N. K. ), the  Christian Doppler Research Association and OMV Group  (A. W. , E. R. ), the  EPSRC  (Ph. D. s tudentship to K. P. S. ;  NanoDTC , E P/G037221/1 , and  EP/L015978/1  to K. N. , S. H. , and E. R. ), the  National Research Foundation of Korea  ( NRF-2015R1A3A2066191  to D. H. N. , C. B. P. ), and the  German Research foundation (DFG)  within the cluster of excellence EXC 314, " UniCat " (I. Z. ). We thank  Prof. A. William Rutherford  and  Dr Andrea Fantuzzi  ( Imperial College London ) for providing as ample of PSII,  Prof. Dominic S.
Acknowledgements S. W. , N. G. , C. M-C. , F. N. , A. T. , N. S. , and C. S. acknowledge the financial support of the  European Community  within the  Seventh Framework Programme  ( FP7)  under Grant Agreement No. 295775  (Project SoTherCo). T. K. and T. U. acknowledge the financial support from  CREST-JST  and  JSPS KAKENHI  Grant Number  JP16H06517  ( Coordination Asymmetry ). M. W. , N. R. , S. D. -V. , and G. M. thank  Institut Universitaire de France  for its support and the financial support of  ANR-13-SEED-0001-01  " Chesdens " project. Measurements at the ROCK synchrotron beamline of SOLEIL was supported by a public grant overseen by the  French National Research Agency (ANR)  as a part of the  "Investissements d'Avenir" Program  ( ANR-10-EQPX-45 ). The EPR measurement was supported by  IR Renard ,  FRE CNRS 3443.
They should address all aspects of the energy sector, including renewable energy, energy efficiency, energy infrastructure, supply security, energy research and innovation, affordability of energy and the competitiveness of companies. The set of indicators could thus provide a fact-based overview of the status of the implementation of the energy transition. The development of comparable indicators requires systematic preparation and in-depth discussions which will also have important consequences for the development of a comprehensive, validated international database. A careful calibration of indicatorsharmonised, while nevertheless taking different national circumstances into account -offers several advantages: It would substantially improve the reliability of the interpretations of national developments, provide data for the scientific evaluation of policy impacts and extend the evidence base of policy-makers without restricting their political choices.
Implementation Overview An independent Expert Advisory Commission should be established for the G20. The proposed expert commission should be mandated to fulfil the following tasks: 1. Inform: Build a comprehensive, validated international database which recognises differences between countries, serves as a basis for monitoring and evaluation, and can be utilised for policy advice. 2. Monitor: Identify harmonized methodologies and develop indicators to provide policymakers with a neutral benchmark tailored to national circumstances. 3. Evaluate: Undertake a stock-take of relevant policy approaches, analyse the status of the implementation of policy measures and evaluate their impact. 4. Exchange: Assess the individual national success factors of impactful policies and create a toolkit for policy-makers consisting of leading practice policy options.
Independent Expert Advisory Group on a Data Revolution for Sustainable Development (IEAG) concludes in its culmination report A World That Counts: Mobilising a Data Revolution for Sustainable Development that "without high-quality data providing the right information on the right things at the right time; designing, monitoring and evaluating effective policies becomes almost impossible" (United Nations 2014). 7 About the Independent Expert Advisory Group, UN Data Revolution Group website: The global importance of a reliable database has been recognised at the highest level. It is underlined by the creation of two important groups: The Independent Expert Advisory Group on the Data Revolution for Sustainable Development, appointed by former UN Secretary-General Ban Ki-moon on 29 August 2014, and the High-level Group for Partnership, Coordination and Capacity-Building for statistics for the 2030 Agenda for Sustainable Development, convened on 6 March 2015 by the United Nations Statistical Commission.
2013; Maurer et al. 2015; Lengliné et al. 2017 ) and geochemical surveys  (Dezayes et al. 2014; Sanjuan 2016 ) have been already established to identify permeable zones and the hydraulic connections between GRT-1 and GRT-2 wells. The knowledge of the Rittershoffen site is also completed by the huge database collected in the nearby Soultz-sous-Forêts site. Five permeable zones have been currently identified in the granite reservoir, but none in the sediments  (Vidal et al. 2016b). As already demonstrated for the Soultz-sous-Forêts research site, numerical modelings can provide significant insights to better understand the hydrothermal circulation or the rock physics of EGS reservoirs  (Jain et al. 2015; Kolditz and Clauser 1998; Pruess 1990; Sanyal 2000; Tomac 2017 ). Numerical reservoir models can typically be classified according to different aspects (Willis-Richards and Wallroth 1995): (i) the description of the complex fracture network geometries they integrate via stochastic distribution  (Baujard and Bruel 2006; Cacas et al.
The 2D reservoir model includes all major THM couplings. The equations governing THM processes are solved by a finite element approach using the Code_Aster software. The reservoir is homogenized at the scale of 100 m. The fluid rheology (e. g. , density, viscosity, heat capacity) is considered as dependent on temperature and fluid pressure as shown by laboratory measurements  (Zaytsev and Aseyev 1992; Kestin et al. 1981; Rowe and Chou 1970). We include different a priori settings: (i) the main geological structures of the sedimentary cover  (Aichholzer et al. 2016 ) and the basement  (Vidal et al. 2016a ), (ii) the temperature-depth profiles through the deep boreholes GRT-1 and GRT-2  (Baujard et al. 2017 ), (iii) the distribution of the natural radioactivity  (Rummel 1992; Pribnow et al. 1999; Pribnow and Schellschmidt 2000) , (iv) the regional stress-state  (Evans et al.
Each parameter p is taken from a uniform a priori distribution called prior distribution in the range [p min , p max ] chosen to be wider than experimental values (see Table  1 ). The main benefit of our back analysis is that the inversion procedure based on deterministic method is less numerically intensive than the stochastic methods. However, the inversion procedure is sensitive to the initial conditions of the back analysis such as the prior distributions of the rock properties. Nonetheless, the prior distributions are well constrained thanks to databases from Rittershoffen and Soultz-sous-Forêts sites. In the current study, we aim to estimate four rock properties : permeability, thermal conductivity and elastic moduli (i. e. , Young's modulus and Poisson's ratio) by inverting the observed temperature and stress profiles with depth using the THM model as the forward model.
Comparison with the hydrothermal characterization of the GRT-1 and GRT-2 wells The study of  (Baujard et al. 2017)  analyzes the database obtained after stimulation and circulation testing of GRT-1 and GRT-2 wells in the Rittershoffen reservoir. In particular, a double porosity model area has been carried out with AQTESOLV software  (Baujard et al. 2016)  from the hydraulic data of the pumping tests. The reservoir thickness is assumed to be about 500 m and the model includes a fracture area 40 m thick. We aim to compare the results from our modeling approach with their interpretations of production and circulation tests. Fracture and matrix permeabilities of, respectively, 5. 34 × 10 -14 m 2 and 9. 2 × 10 -15 m 2 have been evaluated from interpretations of GRT-2 hydraulic testing  (Baujard et al.
Acknowledgements The present work has been done under the framework of the LABEX  ANR-11-LABX-0050-G-EAU-THERMIE-PROFONDE  and benefits from a state funding managed by the  French National Research Agency (ANR)  as part of the  "Investments for the Future" program. It has also been funded by the  EGS  Alsace Grant from  ADEME. The authors would like to thank  Christoph Clauser ,  Albert Genter ,  Clément Baujard ,  Thomas Kohl ,  Chrystel Dezayes ,  David Bruhn ,  Nima Gholizadeh Doonechaly ,  Bernard Sanjuan ,  Benoit Valley ,  Judith Sausse ,  Philippe Jousset ,  Dominique Bruel ,  Eva Schill ,  Patrick Baud ,  Mike Heap ,  Luke Griffiths ,  Alexandra Kushnir ,  Olivier Lenglinè ,  Coralie Aichholzer ,  Philippe Duringer  and  François Cornet  for very fruitful discussions. We thank also the anonymous reviewers and the editorial team for their comments.
System Boundaries The study system is agricultural production in France including vegetal and livestock production. The study focuses on the energy and nitrogen flows associated with the production at the farm gate level. The system boundaries embrace all utilized agricultural area in France and include imported feed. Food processing and retailing are excluded. The analysis covers the period from 1882 to 2013 and builds on a continuous and consistent data set combining data from national statistics (Ministère de l'  Agriculture 1898 Agriculture , 1936 Agriculture , 1947 Agriculture to 1969;; INSEE 1961 INSEE , 1990;; Agreste 2017 ) and from the Food and Agricultural Organization (FAO) production and international trade statistical databases (FAOSTAT 2017).
N NP = N NPP e + N LV × 1 - 1 NCE + N Feed imp (3) The BNF rate (BNF r in kilograms [kg] of N/ha [hectare]) in leguminous meadows and grasslands is subject to change with agricultural practices. There are no available data on BNF. BNF is estimated as a function of agricultural yields for each fixing grass type from equation (4). BNF rates are then integrated on total fixing area. BNFr i = Yi / NHIi × N i (4) where Y i is the harvested yield (kg/ha), N i the N content of each vegetal material and NHI i the N harvest index taken at 60% for leguminous meadows  (Anglade et al. 2015)  and at 80% for grasslands. N in imported feed is calculated from international trade data (FAOSTAT 2017). Atmospheric N deposition is estimated for a uniform deposition rate of 5 kg of N/year/ha of agricultural area.
2. Akaganeite nanorods show a weak paramagnetic behavior (dashed red line) at room temperature (T≈300K), as previously reported for nanorods of near similar size  17, 37  and with Néel temperature (corresponding to antiferromagnetic-paramagnetic transition) about 37,38 T N =260K. The initial volume magnetic susceptibility (estimated as 0 ( / ) H dM dH χ ρ = = assuming the particle density equal to the one of the bulk akaganeite, ρ≈3. 5 g/cm 3 ) is about , as inferred from the initial slope of the Langevin fit of the magnetization data of that paper). The synthesized iron oxide nanorods showed a much stronger magnetic behavior (solid curve in Fig. 2 ). The saturation magnetization M S was estimated as an intercept of a linear extrapolation of the M versus 1/H dependency with the ordinate axis, as suggested by Rosensweig 39.
ACKNOWLEDGEMENTS The authors are grateful to  J. Persello ,  A. Bée  and  D. Talbot  for helpful discussions,  S. Pagnota  ( UCA ) for TEM imaging,  G. Monge  ( Mines ParisTech ) for XRD analyses,  N. Guigo  ( UCA, ICN ) for TGA,  E. Briot  for BET analysis,  J. -M. Guigner  for cryo- TEM (IMPMC, Sorbonne University ) and  P. Boustingorry  for providing the polymers (Chryso).
Funding P. K. and O. S. received funding for equipment from  French "Agence Nationale de la Recherche"  (project  Future Investments UCAJEDI ref. n°  ANR-15-IDEX-01  and project MagnetoChemoBlast, ref n°  ANR-13-BS08-0017 ); J. A. M received funding for postdoctoral fellowship from  Brasilian "Ministério da Ciência, Tecnologia e Inovação -Conselho Nacional de Desenvolvimento Científico e Tecnológico" (CNPq , ref. n°  203100/2014-0 ); A. P. received funding from  German "Deutsche Forschungsgemeinschaft" (DFG , ref. n°  SE 2714/2-1 ).
Data analysis FTIR spectra (4000-500 cm -1 ) were preprocessed by transforming to 2nd derivative form with the Savitzky-Golay (S-G) method (2nd degree polynomial, windows size 15), followed by Extended Multiplicative Scatter Correction (EMSC) with linear and quadratic components  [26]. Principal component analysis (PCA) of the EMSC corrected FTIR data and auto-scaled GC fatty acid data was performed in The Unscrambler X, V10. 5 (CAMO, Oslo, Norway). Partial Least Square Regression (PLSR) between FTIR data (S-G and EMSC) and GC fatty acid data was performed with a leave-one-biological-replicate-out cross validation scheme, and with limiting the maximum number of PLS factors to ten.
PC2 explains 9% of the variance. The ratio of protein  (7, 8)  and phosphate  (12, 14, 16)  is responsible for the separation of strains in PC2. Mucor species have predominantly negative PC2 scores, which can be explained by their very high polyphospate content in their cell wall  [32]. The FTIR data indicated that Mucor/Amylomyces and Rhizopus have lower total lipid content on average than Absidia, Umbelopsis, Cunninghamella and Mortierella genera, which is in accordance with the GC measurement results (see also Fig. 6c ). FTIR spectra of Mucoromycota strains were used to estimate the lipid content in the mycelium (measured by GC-FID analysis). Univariate methods were tested for the whole set of studied strains and individually for each genus, and were compared to the multivariate method (PLSR)  [23].
). Wall grown biomass weight can exceed the weight of the submerged biomass weight (data not shown). In the current study, the wall-grown biomass was not collected, therefore, the reported biomass concentration should be considered as the submerged biomass concentration or a 'minimum' value. In some cases the reported biomass values are, therefore, severely underestimated, affecting also other reported fermentation parameters (e. g. total lipid; g/L, yield values; g/g) (Fig. 6d-f , Additional file 1: Table  S1 , S2). To solve wall growth of filamentous organisms in MTP, addition of glass beads or carboxypolymethylene to the medium, and mutation to pellet morphology have been successfully applied  [37, 38, 40, 41]. Reproducibility of total lipid content measurement (wt%) was estimated by performing three times the extraction-transesterification-GC-FID procedure on a Mucor flavus CCM 8086 and Absidia glauca CCM 451 biomass samples (i.
Intensities were measured with a Sol-XE Si(Li) solid state detector from Baltic Scientific Instruments using CuKα radiation over the range 2-50 • 2θ using a step-size of 0. 04 • and a counting time of 6 s per step for oriented slides. XRD data were collected at 40% relative humidity (% RH) for Ca-AD and Ca-EG and at 5% RH for K-AD, K-150, and K-350 samples. The sizes of the divergence slit, the two Soller slits and the antiscatter slit were 0. 3 • , 2. 5 • , 2. 5 • and 0. 3 • respectively. Preparation of 50-2 µm fractions for XRD analysis was performed by milling with ethanol in a McCrone micronizing mill for 8 minutes and random powder XRD was performed on front-loaded preparations using the Bruker D8 over the range 3-90 • 2θ with step-size of 0. 026 • and a counting time of 8 s per step.
Simulation of XRD Patterns Mineral identification and full-profile modelling of the XRD profiles of 50-2 µm fractions was carried out using the Rietveld method and the Profex interface for BGMN software  [44]  over the range 8-90 • 2θ. Refined parameters include unit-cell parameters, size of the coherent scattering domains (CSD), site occupancy and preferred orientation. Background was fitted with a six-parameter polynomial. For 2-0. 2, 0. 2-0. 05 and <0. 05 µm subfractions simulation was performed between 3. 5 and 50 • 2θ using the Sybilla program developed by Chevron™  [45]  from the mathematical formulation reported by Drits and Tchoubar  [46]. This modelling is based on the direct comparison between experimental and calculated 00l XRD reflections, and fitting was done via trial-and-error determination of structure factors to arrive at a single structure model which fits the profiles obtained from both Ca-AD and Ca-EG treatments according to the multi-specimen technique  [23, 25, [35] [36] [37] [38].