dataesr/scientific-paragraphs-categorization huggingface dataset:
Cell Counting and Growth Cell density was determined using a Neubauer hemacytometer (Hausser Scientific, Horsham, PA, United States). For the comparison between ecotypes, cell densities were determined using a double beam spectrophotometer (Lambda 25, Perkin Elmer). Optical density (OD) was measured at 735 nm and calibration curves prepared for each strain and each condition in order to associate OD to cell density. Calibration curves are reported in Supplementary Figure  1A. Determination of growth rates was obtained using the software CurveExpert Basic 1 through a logistic model fitting (Bolzmann).
Fourier Transform Infrared Spectroscopy Samples were centrifugated at 3,000×g for 10 min, washed twice with a NaCl solution (1,032 mOsmol), vacuum dried for 5 min and stored at -20 • C until use. Samples were resuspended in ultrapure water in order to obtain the desired number of cells ml -1. One µl of the suspension was deposited on a silicon plate and dried at 37 • C for 15 min. The silicon plate was previously carefully washed with isopropanol (Fisher Scientific, >99. 5%) and dried. Three biological samples (three drops) were considered. Infrared (IR) spectra were collected at the Vibrational Spectroscopy platform of the IMMM (Le Mans University) using a FTIR-microscope Spotlight 200i (Perkin Elmer) controlled by the Spectrum TM software (Perkin Elmer). Spectra were collected from eight randomly distributed spots on the drop avoiding the centre (Supplementary Figure  2 ) with a 4 cm -1 spectral resolution and 32 scans per spectrum in transmission modus.
1,230 Vas P=O from phosphodiester of nucleic acids and phospholipids 1,200-900 V C-0-C from polysaccharides 980 P-O-P of Polyphosphates Band assignments are taken from references  Giordano et al. (2001)  and  Mayers et al. (2013). V , symmetric stretching; Vas , asymmetrical stretching; δ , symmetric deformation (bend); δas , asymmetric deformation (bend). manually adjusted to provide optimal brightness and resolution. Fluorescent images were merged and colored using the Zen Blue software (Zeiss). Fiji software 4 (ImageJ v1. 53c) was used to estimate the volume of LDs. Stacks from LSCM images containing only the fluorescence channel were converted to a Z-projection. The diameter of each LD was measured manually and used to calculate the volume of a sphere (assuming that all LDs are spherical).
The instability at lower cellular densities is probably linked to the inhomogeneous distribution of cells inside the drop area (Supplementary Figure  7 ). The stable values observed with the normalization procedure indicates that depositing a specific number of cells is not necessary when remaining between 10 6 and 3 × 10 6 cells. The normalization step corrects sampling and human errors when cell density is FIGURE 5 | Validation of the FTIR methodology using data from a N-starvation experiment conducted in a photobioreactor  (Scarsini, 2021). Correlations between lipids quantified from FTIR absorbance measured at 1,746 cm -1 and lipids concentrations quantified by fluorescence after Nile Red staining considering (A) baseline-corrected spectra and (B) baseline-corrected and normalized spectra.
ACKNOWLEDGMENTS Authors are grateful to the  IMMM platform of Le Mans University  for the service provided for FTIR spectroscopy and confocal microscopy. Authors are also thankful to  Angela Falciatore  from the  Laboratoire de Biologie du Chloroplaste et Perception de la Lumière chez les Microalgues, Institut de Biologie Physico-Chimique (IBPC, Paris, France ) and to  Hanhua Hu  from the  Center for Algal Biology and Applied Research  ( Chinese Academy of Sciences at Wuhan, China ) for sharing their P. tricornutum Pt1 strains. We are also grateful to  Le Mans University  for the Ph. D. grant to MS and the post doctorate position to AT. The " Fondation Banque Populaire de l'Ouest", Le Mans University and the University "Bretagne-Loire" (UBL ) are thanked for financial supports.
Acknowledgments This work was supported by the  JST-ANR  grant  ANR-14-JTIC-0002-01  ( MECANO) , the  ANR  grant  ANR-16-CE29-0027-01  (MAGMA), a public grant overseen by the  French National Research Agency  as part of the  "Investissements d'Avenir" program  ( Labex NanoSaclay , reference:  ANR-10-LABX-0035 ), the  CNRS , the  Université de Strasbourg.
The results are compared with conventional diesel trucks, since diesel is the primary fuel in HDVs. For clarity, emissions of CNG over the whole life cycle will be estimated separately in different parts. Leaks and CO2 emissions from the upstream are presented in Section 3. The leak that occurred during the WtT process will be covered in detail in this section. Emission estimates for hybrid electric trucks are presented in Section 4. The results will be integrated into Section 5 to import a comprehensive evaluation for the entire process. The WtW database would support the transportation electrification, which will be necessary to meet increasingly strict pollution standards.
Acknowledgement This paper is part of a project that has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie  grant agreement No. 765860  (AQUAlity). The paper reflects only the authors' view and the Agency is not responsible for any use that may be made of the information it contains. M. B. and G. M. acknowledge financial support from the  CAP  20e25 I-site project.
Computational details The first-principles calculations are performed using the periodic DFT code "Vienna ab initio simulation package", VASP. 47 We have adopted the generalized gradient approximation density functional PBE-dDsC,  48, 49  which is augmented with a density-dependent dispersion correction. 50 The nuclei and core electrons are described by the projector augmented wave function approach (PAW). 51, 52 A plane-wave basis set with a kinetic energy cuto↵ of 500 eV is used for the valence electrons. The precision setting of VASP is set to "accurate". We used a Fermi smearing corresponding to room temperature (0. 025 eV) and a Monkhorst-Pack 3 ⇥ 3 ⇥ 1 k-point mesh for all the studied surfaces p(2 ⇥ 1), p(3 ⇥ 1) and p(4 ⇥ 1). The convergence criterion for the self-consistency process is set to 10 5 eV for the optimization of the wave function.
This makes the DFT computations slower than usual due to the associated larger numerical noise, but has also been used previously in the context of solvated alkalimetal ions. 54, 55 The Debey screening length is set to 3 Å, which corresponds to a 1 M electrolyte. This is representative for 0. 5 M aqueous H 2 SO 4 solutions typically used in HER experiments. To properly define the work-function (electrochemical potential) of the interface, the dipole moment of the slab needs to be nullified through symmetry. We perform a point symmetrization for all the edges. The central layers are kept frozen in their bulk positions. The potential dependence is studied by varying the number of electrons. 53, 56 In practice, the charge of the system is varied from -1 to +1 in steps of 0. 2 e (see example and script provided in the SI).
Acknowledgement This work was financially supported by  Région Auvergne Rhône-Alpes  through the project  Pack Ambition Recherche 2018 MoSHi. We are very grateful to IFP Energies nouvelles for supporting the  MoSHy  project (N o 1801167601) and to the  IFP Energies nouvelles team ,  Mona Marie Obadia  and  Quentin Cacciuttolo , for fruitful discussions. The authors thank the  SYSPROD  project and  AXELERA Pôle de Compétitivité  for financial support (PSMN Data Center).
Prior to each loading all MoS 2 single crystals were cleaved by peeling off the surface layer using adhesive tape. Then the crystals were mounted onto a tantalum plate electrode and subsequently loaded by electrolysis in a 1 : 1 mixture of phosphoric acid (H 3 PO 4 85%) and glycerol, using a Pt counter electrode. The electrolysis lasted 2 hours at 4 V on one side of the crystal for the nuclear reaction analysis, 4 hours at 4 V on one side for XPS and 4 hours at 3 V on each side for neutron experiments. The structure of MoS 2 shown in Fig. 5  and 12 was plotted using the VESTA 3 software. 29.
Nuclear reaction analysis Hydrogen depth profiles were measured by irradiating the sample with a 15 N ion beam and counting the emitted gamma-rays on the NRRA beamline at RUBION, Bochum, Germany. The underlying reaction is:  15  N + 1 H -12 C + a + g, with a narrow resonance at the energy of 6. 4 MeV, which is used for the detection of hydrogen. In order to reach the resonance energy at different depths inside the sample, the beam energy was varied from 6. 39 MeV to 6. 65 MeV. The maximum beam current was set to 6 nA. Data were collected in two runs, shortly after loading the sample with hydrogen and after four weeks downtime. During the waiting time the sample was held in air under ambient conditions. The depth scale in nm was calculated on a basis of the stopping power of MoS 2. 30, 31 The concentration scale was constructed taking into account the stopping power of both MoS 2 and hydrogen.
The measurements thus show the state of the surface several minutes after the sample had been heated up to a certain temperature. For energy calibration the adventitious carbon peak at the corresponding temperature was used. The background was described by a Shirley step model. 35  The intensities were corrected for the atomic subshell photoionisation cross sections obtained by Yeh and Lindau. 36  Data treatment was performed using the XPST package within the Igor Pro software package (WaveMetrics, Portland, USA).
e. , for 2y = 401 the momentum transfer was perpendicular to the basal planes. The temperatures scanned in the out-of-plane set-up were 3, 100 and 300 K, whereas in the in-plane set-up data at 3, 50, 100, 200, 300, 400, and 500 K were measured. The spectra were measured consecutively with rising temperature up to 500 K and a further spectrum at 300 K in the in-plane set-up was measured after the last 500 K measurements to check for permanent changes of the sample upon heating to 500 K. Spectra at 3 K were used as a resolution function. Data reduction was performed using the Mantid software package. 38 very spectrum was normalised to the beam monitor signal and, after deduction of an empty container spectrum, corrected by a vanadium spectrum to calibrate for variations in detector efficiency.
Neutron spin echo measurement Neutron spin echo (NSE) measurements were performed on the NSE spectrometer IN11 at Institut Laue-Langevin (ILL), Grenoble, France, 39 using the high signal set-up IN11C, which uses a 301 detector bank. 40 Here, we used a wavelength of l = 5. 5 Å for maximum signal. Following the same procedure as in the QENS study, data were collected in two sample orientations with the surface parallel and perpendicular to the scattering vector Q. The spectra were normalised using a standard procedure: all data were divided by a spectrum that was obtained in situ at 2 and 5 K for the in-plane and out-of-plane geometry, respectively. At these temperatures the system can safely be assumed to be static in the dynamic window of the spectrometer. The experiment covered a range of momentum transfers of Q = [0.
Nuclear reaction analysis We commence the description of our experiments with the structural and chemical characterisation of the samples: Fig. 3  shows the hydrogen concentration in dependence of the depth measured by NRA quickly after electrolysis loading of MoS 2 and after four weeks of ageing, respectively. For the freshly prepared sample the data clearly show a high concentration of hydrogen in the surface and sub-surface region and vanishing signal at higher depths (we note that the width of the surface peak is equal to the width dictated by the energy resolution of the incoming beam and, hence, the width of the surface peak gives only an upper limit for the width of the distribution function at the surface). After 4 weeks of ageing in ambient air environment, the surface peak decreased in intensity by half and a significant bulk signal was recorded that remained constant  from a depth of 20 nm up to 100 nm, the maximum penetration depth recorded in our NRA measurements.
The grey dotted lines show the evolution of the binding energies of the two main oxidation states, labelled 1 and 2. For visual clarity a vertical offset is applied to the S and Mo data at elevated temperatures. reduced sections. These sections may be assigned to the surface and subsurface regions respectively. We note, that the analysis depths of the XPS experiment is limited to less than 10 nm. 41 In view of the results of the NRA study, this covers the region, where we expect to find water and hydrogen. The analysis of the Mo and S binding energies suggests that at room temperature the surface consists mostly of clean MoS 2 , i. e. Mo 4+ and S 2À. Heating to 400 K partially reduces the surface, with Mo staying closer to the 4+ state than to 3+. Further increase in temperature prompts a new oxidation process, which results in a significant increase in the binding energy of the more oxidised state (labelled 2 in Fig.
At 500 K the same process continues. It is also important to note that since MoS 2 is considered relatively active for the hydrogen evolution reaction, another source of subsurface H atoms apart from the bulk H exists, namely, catalytically split H 2 molecules. However in the XPS experiment little information can be drawn for hydrogen molecules, since they are not chemisorbed to the host material. The XPS data contain also carbon and oxygen lines. Both elements are likely to be adsorbed from the atmosphere in various forms. Prior measurements utilising deuterium induced gamma emission (DIGE) at RUBION, Bochum, Germany, showed a bulk oxygen content at a level of 0. 5 at%. Hence, oxygen should mostly be located in the surface or subsurface region. The interpretation of the O 1s line requires a careful analysis: molybdenum oxides are expected to create an XPS signal around 530 eV  42, 43  and, thus, are not observed in this study.
In addition, the XPS experiment indicates that H atoms start moving at E400 K, whereas in the QENS data a quasi-elastic broadening can already be observed at room temperature. This signal does not change qualitatively at elevated temperatures, so we conclude that most of the signal in the QENS experiment is caused by H 2 mobility. In view of these considerations the whole set of data at temperatures higher than 200 K was treated by means of the rotational-translational model described in the Theory section above (eqn (  9 )). However, several spectra at low and high Q were not used in further analysis as the lack of data points in the QENS region (Fig. 2 ) made the corresponding analysis statistically unstable. Based on a w 2 analysis and on the behaviour of the residuals function (difference between observed and calculated points weighted for statistical errors) we conclude that our model is sufficient for the description of the data and no extra fitting parameters are required.
Acknowledgements This work is based upon experiments performed at the TOFTOF instrument operated by  Technische Universita ¨t Mu ¨nchen at the Heinz Maier-Leibnitz Zentrum (MLZ), Garching, Germany. This project has received support from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement no. 730872  CALYPSO plus for the work at the  HZB BESSY II synchrotron, Berlin, Germany , and under grant agreement no. 731096 FILL2030  for covering the open access fee. The authors want to thank  HZB  for the allocation of synchrotron radiation beam time at  BESSY II  via project  192-08548  CR. Neutron spin-echo experiments were carried out at  Institut Laue-Langevin (ILL), Grenoble, France. The authors want to thank  HZB ,  MLZ  and  ILL  for the allocation of synchrotron and neutron beam time.
Conclusions In summary, we examined a homoepitaxial b-Ga 2 O 3 thin film in the  18  O isotope composition, deposited on top of a substrate  with  16  O isotope distribution. Polarized micro-Raman spectroscopy was carried out to record Raman spectra of both isotopologues. By probing the (010) and (% 201) planes, we were able to separate all 15 Raman active phonon modes and determine their phonon frequencies for both isotopologues. The replacement of  16  O with the heavier  18  O atoms resulted in a reduction of the phonon frequency. We provided the spectral positions of  18  O Raman modes and quantified the absolute as well as relative frequency shifts compared to  16  O Raman modes. Based on the comparison of experimental data with DFPT calculations of mode frequency shifts and calculation of the relative energy contributions of each lattice site to the total phonon energy, we identified and quantified the atomistic vibrations for each of the five distinct lattice sites which give rise to the 15 different Raman-active phonon modes in b-Ga 2 O 3.
Acknowledgements We acknowledge funding by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) -project number  446185170. This work was performed in parts in the framework of GraFOx, a Leibniz-ScienceCampus partially funded by the  Leibniz association. Computational resources used for the calculations were provided by the  HPC of the Regional Computer Centre Erlangen (RRZE). The authors thank  Maximilian Ries  for fruitful discussions,  Thomas Kure  for experimental support, and  Arne Haeger  for support in graphic design.
ACS Omega higher than the experimental critical surface charge density Z c ≈ 0. 1 nm -2. This implies that the sodium counterions should be in the condensed state, and the effective charge density should be constant in the whole range of the MB surface coverage, which is inconsistent with the experimental curve in Figure  5a. The value of Z COO needs to be checked, and it can be evaluated by dosage of the condensed sodium counterions by ICP-AES, as described in Section 4. 2. The surface density Q Na of sodium counterions condensed on the IONP surface is plotted as a function of the surface density of adsorbed MB, Q eq (or the surface coverage θ) in Figure  5b , for the SC-MB samples. Despite some dispersion in data (related to analytical errors), they seem to collapse onto a straight line, Q Na ≈ Q tot -1.
No. ANR-15-IDEX-01  (projects MANTRA, ImmunoMag, and  MagFilter ) and the  private company Axlepios Biomedical  for financial support. J. Q. C. acknowledges the financial support of  UCA JEDI and Axlepios Biomedical  through the Ph. D. fellowship. BLCF acknowledges Erasmus Mundus through its mobility fellowship.
Acknowledgements A. G. thanks for funding the  CEA PTC Program on Materials and Processes  ( Bio-PAC  project). P. C. , V. A. and B. R. acknowledge support from the  French Agence Nationale de la Recherche (Labex ARCANE , CBH-EUR- GS , and  ANR-17-EURE-0003 ). The research leading to these results has also received funding from the  Fuel Cells and Hydrogen 2 Joint Undertaking (FCH-JU , GAN, under Grant Agreement No. 779366 ). FCH-JU  receives support from the  European Union 's  Horizon 2020 research and innovation programme ,  Hydrogen Europe  and  Hydrogen Europe Research. A. G. , S. L. and P. C. acknowledge ILL and LLB for beam-time allocation and  Alexis Chennevière ,  Jacques Jestin  and  Lionel Porcar  for their help as local contacts.
FEDER-FSE Lorraine et Massif des Vosges 2014-2020; for the financial support. The work carried out at the Universitat de Barcelona has been supported by the Spanish MICIUN RTI2018-095460-B-I00 and María de Maeztu MDM-2017-0767 grants and, in part, to COST Action CA18234. A. M. -G. is thankful to the Juan de la Cierva Incorporación Programme grant IJCI-2017-31979. Computational resources were provided by the LPCT local clusters, the mésocentre EXPLOR of Université de Lorraine (Project 2018CPMXX0602), the Très Grand Centre de Calcul du CEA (TGCC) facilities, Red Española de Supercomputacion (RES) (grant QS-2020-2-0008), and the HPC-Europa3 Transnational Access programme (project number HPC17N1MY8).
' FEDER-FSE Lorraine et Massif des Vosges 2014-2020; for the financial support. The work carried out at the Universitat de Barcelona has been supported by the Spanish MICIUN RTI2018-095460-B-I00 and María de Maeztu MDM-2017-0767 grants and, in part, to COST Action CA18234. A. M. -G. is thankful to the Juan de la Cierva Incorporación Programme grant IJCI-2017-31979. Computational resources were provided by the LPCT local clusters, the mésocentre EXPLOR of Université de Lorraine (Project 2018CPMXX0602), the Très Grand Centre de Calcul du CEA (TGCC) facilities, Red Española de Supercomputacion (RES) (grant QS-2020-2-0008), and the HPC-Europa3 Transnational Access programme (project number HPC17N1MY8).
The variation operators use the following (standard) parameters: SBX operator's probability and distribution p c = 1 and η c = 20 , respectively; polynomial mutation's probability and distribution p m = 1 /n and η m = 20 , respectively, where n is the number of decision variables. Also, since the Pareto set approximation provided by the MOEA typically contains more than 21 solutions, the final population is pruned so that only 21 well-distributed solutions are considered to calculate the HV. Finally, in order to perform appropriate (statistical) comparison of results, the hybrid approach is run 11 times for each instance. The exact method was implemented in GAMS environment (v23. 9. 5) using CPLEX solver v12. 4. 0. 1. For the hybrid approach, SMS-EMOA was implemented in MATLAB language (vR2019a), and the solution of the LP sub-problems is performed using CPLEX solver v12.
The aim of the ISORC/OPTIMISER project is to increase and improve the use of solar thermal energy in district heating networks. One of the main tasks of the project is to develop an optimization tool for the sizing and operation of a solar district heating network. This is the first optimization tool using an open-source interface (Julia, JuMP) and solver (Ipopt) to solve nonlinear problems. This paper presents the multi-period optimization problem which is implemented to consider the dynamic variations in a year, represented by four typical days, with an hourly resolution. The optimum is calculated for a total duration of 20 years. First, this paper presents the modeling of the different components of a solar district heating network production plant: district network demand, storage and three sources, i.
The authors concluded that considerable computational times were required for large networks. Gao et al. [11]  carried out a review of state-of-the-art optimization methods used for energy cogeneration systems, which therefore included DHNs. They noted in particular a growing tendency to use solar heat in new DHNs. Gao et al. [11]  noted that there was a need for more in-depth research on small-scale networks and on the economic models used to optimize DHNs, in order to facilitate their development. Finally, Wang et al. [12]  recently assessed the performances of the optimization methods used in DHNs. They outlined the methods along with their purpose and environment, concluding, like Sameti and Haghighat  [8] , that the MILP approach is most often used in the MATLAB/Simulink environment in order to minimize total costs.
Objectives of the Present Work The tool presented here is written in an open-source language (Julia  [38]  and its optimization package JuMP  [39] ) and uses open-source solvers but with the possibility of using commercial ones. The creation of this tool responds to an industrial demand in order to respond to projects in a more competitive way, i. e. , more precisely. It studies solar district heating networks (SDHNs) with an NLP formulation to model all components more accurately than in MILP approaches. It needs to be fast, open-access and easy to use by different kinds of users (expert or not), such as communities, engineering consultants and companies. This paper presents a nonlinear formulation to model a multisource DHN, including solar thermal energy. Certain production elements can be modeled in more detail due to the NLP approach (storage volume, solar field area, etc.