dataesr/scientific-paragraphs-categorization huggingface dataset:
Life cycle assessment The environmental performance of energy piles should be compared with that of a conventional heating and cooling system to demonstrate its benefits from an environmental point of view. In this study, the LCA methodology is adopted to evaluate the potential environmental impacts while taking into consideration the material extraction, transportation, execution, use, and disposal. The analyses are performed by implementing the LCA model in the software SimaPro 8. 0. 3  [32]. The international standards ISO 14040, 2006  [33]  and ISO14044  [34]  describe the LCA methodology and the related analysis phases such as goal and scope definition, life cycle inventory (LCI), life cycle impact assessment (LCIA), and interpretation, which are followed in this study. The goal and scope definition step includes the definition of the functional unit (measure of the function of the system), the reference flow (quantitative reference unit required to satisfy the functional unit), and the boundaries of the system.
The flows between the investigated system and the environment, in terms of input and output products, resources, wastes, and emissions, were identified during the LCI. The input data of the LCI are reported in Tables 3 and 4 for the conventional system and energy piles, respectively. The amount of materials was obtained following the geotechnical design of the group of piles  [35]. The transportation distance was hypothesised as 50 km while the drilling time was obtained in consultation with a specialised company. With respect to the use phase, the amount of energy required in terms of natural gas or electricity was obtained while considering the available heating and cooling demands and the results of the finite element analysis simulation reported in Fig. 3. Scheme of a GSHP system. Subsection 3.
1. The latter allowed for the estimation of the geothermal energy that can be exploited by the thermal activation of the piles for the considered scenarios. According to the different heating and cooling demands and in situ temperature of the ground, the GSHP system behaves differently for each considered city, and therefore, the corresponding impact on the environment differs. With respect to the electricity supply, national flows were selected with respect to the three reference cities. The disposal scenario takes into consideration the recycling of all the involved materials, while assuming the recycling rates of the construction and demolition waste for the corresponding countries  [36]. The last column of Tables 3 and 4 reports the selected environmental flow from the LCI database ecoinvent  [37].
A LOT-Oriel solar simulator, equipped with an AM1. 5G filter and set to 0. 1 W/cm 2 incident irradiance power, was used as the illumination source. J-V curves were recorded at 20 mV/s scan rate. For the EIS measurements under illumination, the photoanodes were sampled in the selected potential range at 50 mV intervals, employing an FRA2. v10 frequency response analyzer controlled by software Nova 1. 10. A 10 mV amplitude sinusoidal perturbation, the frequency of which ranged between 100 kHz and 0. 1 Hz, was used. The EIS data were fitted by means of the equivalent circuit reported in Figure  S13D  using the ZView software, with typical relative errors lower than 15%. Nanosecond TAS was carried out using pump pulses with 355 nm wavelength and ca. 500 μJ/cm 2 fluence. The spectra were collected both under open-circuit potential V OC and under anodic bias in a twoelectrode configuration using a Pt wire as a counter electrode.
Reference powder samples of hematite, magnetite, rutile, anatase, brookite, ilmenite, and pseudobrookite were also measured in transmission mode. The pretreatment process for all XAFS spectra was performed using the Athena program of IFEFFIT software package. 18 The pre-edge features were fitted with Gaussian profiles using the Fityk package. 19 The EXAFS spectra were analyzed using the Artemis code 18 using simulated scattering paths calculated using FEFF 6. 0. TEM analyses were conducted on specimens prepared by scratching the photoanodes surface with a scalpel and collecting the powder by adherence onto a copper TEM grid coated by a holey carbon film. 20 The employed instrument was a ZEISS LIBRA200 FE electron microscope equipped with an in-column Ω-filter analyzer. ESI (electron spectroscopy imaging) elemental maps for Ti and Fe were collected at the L 2,3 edge (at energy loss 462 and 708 eV, respectively) by a three-windows methods.
Acknowledgements This project received financial support from  German Research Foundation (DFG)  through grant  STR 596/4-1  ('' Pt-Stability '') and grant  STR 596/5-2  (''In situ  TEM KAT'') , the  German Federal Ministry of Education and Research (BMBF)  through grant  03SF0531B  ('' HT-linked '') and grant  03XP0251  (''KorrZellKat'') and the  Alexander von Humboldt foundation, Bonn, Germany. We thank  ESRF  and  BESSY II  for allocation of synchrotron radiation beamtime and  I. Zizak  and  T. Merzdorf  for their help during beamtimes. ZELMI of  Technical University Berlin  is acknowledged for their support with TEM measurements.
The hand blower was used to blow away the loose particles. The X-ray photoelectron spectrometry (XPS) was performed on a Kratos AXIS Supra spectrometer with a non-monochromatic Al X-ray source under vacuum (< 10 -8 Pa) at 90° take-off angle. Each analysis started with a survey scan from 0 to 1200 eV, pass energy of 160 eV at steps of 0. 5 eV with 1 sweep. For the high resolution analysis, the number of sweeps was increased while the pass energy was lowered down to 20 eV (steps: 100 meV). The XPS spectra were calibrated in binding energy with C 1s (285 eV). The C1s, O1s, Zr3d and Fe2p lines were recorded for each specimen and further on, the O1s and Fe2p lines were subjected to additional fitting procedure with XPSPEK4. 1 software. The FT-IR spectra were recorded on a VERTEX 70/70v spectrophotometer (BRUKER) in transmission mode between 400 and 4000 cm -1.
" and = /! #$ -$ 0 ' The ISS flight experiment (reactors A1, A4, B1, B4) was reproduced on ground at the same time with the same hardware (i. e. ground reactors GM1, GM2, GM3, GM4). Each of the reactors was run following the same timeline and the same incubation conditions. During the experiment, 4 batches were run and for each batch the timeline was decomposed in several stages: batch incubation (Batch1: 14d; Batch 2: 6d; Batch 3: 8d; Batch 4: 6d); automated sampling (30') followed by manual reservoir replacement by the crew (2h). and Algebraic Equations simultaneously using Matlab® R2015a ODE15s solver.
Reactor A4 showed no measurable biomass production for the start up first batch. The growth started at the end of batch 2 with a low-pressure increase profile in the last 2 batches (number 3 and 4), which looks like the pressure profile of reactor A1-batch1 but with a crushed shape. Inspection of the reactor after its return on Earth indicated a pressure leak from 1. 15 bar. The biomass profiles of reactor A4 -batches3, 4-were similar to the A1-batch1. For reactor B4, the growth stopped after 290h, and biomass decay was then observed. Medium renewal for the batch 2 did not permit to restore the culture. No gas production was recorded potentially due to a malfunctioning pressure sensor or of the pressure release valve. The online monitoring data of the 4 ground reactors, namely GM1, GM2, GM3 and GM4 are presented in Figure  7.
A complete model of pH reconstruction using element and electrolytes balances was derived and used to reconstruct post-fight the pH profiles of the cultures. The model predicted a max pH threshold value of 11. 3-11. 4 for biomass and oxygen production both on ISS and on ground, to avoid an unrecoverable biomass death. Except for reactors showing stirring difficulties, oxygen productivity and therefore biomass growth were comparable on ground and in microgravity experiments. The model also fits both on ground and microgravity experiments except when high pH conditions (above 11) were reached. In microgravity the growth in such bicarbonate-pH limiting condition was less affected than in ground conditions, maybe due to higher CO2 fraction in the gas used to flush the IEC on ISS. The experiment had been planned with 16 batches in order to obtain enough data for comparison of the growth and oxygen production on-board ISS and on ground.
Acknowledgement This work is co-financed by the  European Space Agency and the Belgian Science Policy (Belspo)  and is part of the  MELiSSA  project (http://www. melissafoundation. org). The Arthrospira-B flight experiment was part of the  ArtEMISS  project of  ESA  ( ESA-AO2004-085 ) lead by  SCK•CEN (Belgian Nuclear Research Centre ). The ArtEMISS scientific team thanks the  ESA  and  NASA  astronauts, and all the teams of  QinetiQ ,  ESA ,  MUSC , and BIOTESC who made the space flight experiment possible.
Simulation of Experimentation with COSAC COSAC (Simplified Optical Calculations for Combination Analysis) is a program in FORTRAN 77 developed by François Hénault  [7]  as part of a work on concentrated solar energy and optical space instruments. It is a raytracing program which allows to simulate hexagonal facets or focusing heliostat of a solar power plant. Reflection and refraction of rays are calculated for each optical surface, which are defined by an instruction file read by the program. Its performances are equivalent to the existing professional software. COSAC was chosen because of the simplicity of outputting the brightness maps which are used to compute the slopes and for the freedom and opportunity to access the source code to modify it as needed. However, COSAC does not have the same graphic representation as ZEMAX or CODE V.
The Measured and Analytical Sun Profiles Used for the Simulations To simulate the reflection of a heliostat of a concentrated solar power plant, we need to generate a source which will act as the Sun. The Sun profile was already measured and its global appearance is relatively known, but it depends on the weather conditions of the experiment. In this context and for the experimentations and studies, the Sun's profile was measured, averaged (Fig. 5 ) and then used as input in COSAC software. The Sun profile contains points, each corresponding to a solar angle and a brightness value, and a threshold is applied to remove the signal on the circumsolar which is weaker than the noise measurement [Fig. 5 ]. The noisy Sun profile contains residual signal from the noise measurement of the camera and from the weather conditions.
FUNDING AND ACKNOWLEDGEMENTS This project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  727762 ,  Next-CSP  project and was supported by the  French "Investments for the future" ("Investissements d'Avenir")  programme managed by the  National Agency for Research (ANR)  under contracts  ANR-10-LABX-22-01  ( Labex SOLSTICE ) and  ANR-10-EQPX-49  (Equipex SOCRATE).
In addition, thermocouples were located at key points of the loop: in the fluidization air before and after preheating, exhaust gas before and after the cooler, fines from the cyclone, and particles in the cold and hot tanks. All the measuring instruments were connected to a data logger, Graphtec midi Logger GL800, that was connected to a laptop. The measuring data were recorded with a frequency of 1 Hz through a dedicated software developed with LabVIEW.
However, the use of a cavity makes it difficult to determine the aiming location, as a small offset of a heliostat at the focal plane may move its beam suddenly inside or outside the cavity. The cavity aperture acts as an optical diaphragm, or a letterbox, through which the appropriate flux at the appropriate location must be controlled (Fig. 7 ). In addition, the size of the effective aperture may change by moving the shutter placed in front of the main cavity aperture. Notably not depicted here: the additional beam interceptions by the doors of the solar furnace. The problem was solved using a hybrid simulation-experimental method. The flux distribution on the reactor front wall for each heliostat at each considered offset location (heliostat flux distribution with offsets database) was measured to create a database.
Then, a simulation tool was created to select the heliostat configurations in this database to reach the targeted mean flux density with a given constraint on the minimum and maximum local flux density (to avoid hot spots) and the standard flux deviation (to represent homogeneity). To produce the flux distribution database, each heliostat was scanned at the focal plane, and the actual flux distribution inside a mockup cavity (a diffusive-reflective target placed at the location of the reactor) was measured with a calibrated camera (Fig. 8 ). The camera-based flux measurement system was adapted in order to cope with the camera installed inside the cavity, which used a fisheye lens that produced strong optical aberrations requiring adapted correction. The camera required an internal instead of an external position because it was impossible to see the complete receiver front wall through the smaller cavity aperture.
The enthalpy of the calcination reaction was calculated by assuming that the reaction occurred in the whole reactor at the average temperature of particle. The enthalpy of reaction ∆HR is given in Joule per mole of CaCO3 by Equation (  4 ), with the temperature T expressed in Kelvin. This formula was obtained by regression of the tabulated variations of enthalpy for the reaction CaCO3 → CaO + CO2, calculated with the data from Robie and Hemingway, 1995. For example, this equation shows 0. 525 kWh/kg of CaCO3 converted at 800 °C. In Equations (  5 ) and (  6 ) the coefficients are respectively taken from  Robie and Hemingway, 1995, and Hilsenrath et al. , 1955. The solar power entering the cavity was calculated with data processing of measurements at the cavity aperture. For each configuration of heliostats, the whole range of aperture degree of the cavity was considered.
Acknowledgements This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No. 654663 ,  SOLPART  project. This work was supported by the  French Investments for the Future program  managed by the  National Agency for Research  under contract " ANR-10-EQPX-49-SOCRATE" (Equipex SOCRATE ). The authors thank  Philippe Dumont  ( NLD ) for providing the chemical analysis of the samples.
Acknowledgements The authors acknowledge nancial support from the  Fonds National de la Recherche (FNR) Luxembourg  via the  INTER/ NSF /MAT/11/01   VISICAT  project. The authors are also thankful to  Dr Yves Fleming  for the XPS, XRD and XRR measurements, as well as to  P. Grysan  and  Dr S. Girod  for the AFM measurements. Dr O. Ishchenko  expresses her acknowledgement to  Dr G. Garry  ( TE-OX ) for the fruitful discussions.
Acknowledgments We acknowledge  Dr. F. Jomard  ( GEMaC ) for SIMS measurements. Hagar Mohammed would like to acknowledge Cultural Affairs and  Massion Sector ,  Egyptian Ministry  for  Higher Education  for her fellowship giving possibility work in France. APT acknowledges  Agencia Estatal de Investigación (AEI)  and  Fondo Europeo de Desarrollo Regional (FEDER)  under contract  ENE2015-74275-JIN. The ICN2 is funded by the  CERCA programme / Generalitat de Catalunya  and by the  Severo Ochoa  programme of the  Spanish Ministry of Economy, Industry and Competitiveness (MINECO , grant no. SEV-2017-0706 ).
The standard ISO/IEC 17043  34  was taken as guideline for the evaluation of the participants' results, as already done in previous similar exercises for PV. 23, 25  initiator of the RR within the CHEETAH project, Helmholtz-Zentrum Berlin (HZB) acted as the coordinator (but not as the official provider in the sense of ISO/IEC 17043  34  ) of the RR PT, although it was also a PT participant. This double role of one participant is usually avoided in PTs organised by official PT providers for testing laboratories, in order to assure unbiased results assessment. However, two elements allowed considering HZB position not detrimental to the good development of this specific RR. First, HZB's double role had been taken into account within the CHEETAH project, with no objection by any participant. Second, although the participants' results were submitted to both the coordinator and ESTI, the data analysis of the overall RR PT was made by ESTI, with no disclosure of the RMPT calibration value before the end of the project.
From the conducted sensitivity analysis, which cannot be generalized for other heliostat types, three experimental images spread along a single day (i. e. , morning, noon, and afternoon) were selected. A larger number of images increases the computation time without guaranteeing a more accurate result. In the absence of a precise measurement of the solar position and pedestal tilt, a methodology to determine the heliostat aimpoint was developed. This procedure was verified against data from heliostat tracking encoders. By considering the increments in azimuth and elevation angles between consecutive time instants, the deviation between the model inference and encoder was 0. 0439 • on average, equivalent to less than 6 encoder counts. The proposed methodology was validated with four selected heliostats, which were recanted according to the deviations resulting from the optimization.
Acknowledgments We thank the  CNRS-PROMES laboratory ,  UPR 8521 , belonging to the  French National Center for Scientific Research (CNRS) , for providing access to its facilities, the support of its scientific and technical staff, and the financial support of the  SFERA-III  project (Grant Agreement No. 823802 ). We thank the technical help provided by  Yann Volut ,  William Baltus , and  Antoine Pérez. The research project  VISHELIO-CM-UC3M  has been funded by the  call "Programa de apoyo a la realización de proyectos interdisciplinares de I+D para jóvenes investigadores de la Universidad Carlos III de Madrid   2019-2020 " under the framework of the " Convenio Plurianual Comunidad de Madrid-Universidad Carlos III de Madrid ". This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No.
Simulation Results In order to examine the performance of the proposed control strategy and verify the reported performance, we consider a typical hybrid system with bidi-rectional ZSI. The system is modeled in MATLAB/Simulink taking into consideration irradiation and load changes. The ZSI, PVG, DG, and ESS simulation parameters are given in Table  1. modes and for the same load profile as illustrated in Fig. 13 , the PVG output powers are the same with a better response time in the DG-on mode. To evaluate the efficiency of the proposed control strategy, a sudden load change is applied at t = 2s respectively for the two operating modes (Fig. 13 ). As shown in Fig. 15   need to be significantly decreased to ensure the shoot-through duty cycle required for the MPPT tracking. Therefore, as expected, the AC output voltages are impacted by this change.
C. , with A. Be. and E. T. -L. ), FD (led by A. Bu. , with J. F. and M. A. ), mitochondrial encephalopathy, lactic acidosis and stroke-like episodes (MELAS) (led by M. M. , with J. F. ), type IV collagen (COL4)A1/2 (led by H. C. , with A. Be. and E. T. -L. ) and retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations (RVCL-S) (D. H. ). Each working group leader executed a comprehensive search strategy to November 2018 in the MEDLINE database. Only English language studies were included. Each leader screened citations, reviewed full-text papers for inclusion, appraised study quality and abstracted the data. Consensus was achieved for inclusion of papers by discussion within working groups (Fig. 1 ). Finally, each group provided a list of queries to be voted on, as well as the references used to address the specific disease (File S1), which was distributed to all experts.
Acknowledgements The authors thank  Lyndsey Butterworth  from the  mitochondrial disease patient advocacy group Lily Foundation  for participation in the meeting. M. M. is grateful to Telethon and MITOCON association for support ( GUP09004  and  GSP 16001 ). H. S. M. is supported by an  NIHR   Senior Investigator award  and his work is supported by  Cambridge University Hospitals NIHR Biomedical Research Centre.
The retention time applied was 15 days and the feeding of ALD was performed using a peristatic pump (Figure  1 ). Climatological data in Lescar region were extracted from the website of "Meteo France" (http://www. meteofrance. com/accueil). Microalgae growth was daily monitored by determining Optical Density (OD) at 680 nm with a UV-visible spectrometer (7315, Jenway, United Kingdom), after proper dilution with deionized water to obtain absorbance values between zero and one. In parallel, the microalgae growth was measured by counting cells system using Malassez method (Absher, M. 1973, Blaubrand ® , Germany). Briefly, Malassez method consists of a thick glass microscope slide (Malassez) with a rectangular indentation that creates a chamber of a well-known volume, so the number of contained cells can be determined.
Climatological data in Lescar region were extracted from the website of "Meteo France" (http://www. meteofrance. com/accueil). Microalgae growth was daily monitored by determining Optical Density (OD) at 680 nm with a UV-visible spectrometer (7315, Jenway, United Kingdom), after proper dilution with deionized water to obtain absorbance values between zero and one. In parallel, the microalgae growth was measured by counting cells system using Malassez method (Absher, M. 1973, Blaubrand ® , Germany). Briefly, Malassez method consists of a thick glass microscope slide (Malassez) with a rectangular indentation Appl. Sci. 2020, 10, 3890 6 of 19 that creates a chamber of a well-known volume, so the number of contained cells can be determined. Light microscopy was carried out using a Zeiss Axioskop 2 equipped with an AxioCam MRc camera.
Acknowledgements  C. M. Sanchez-Sanchez  thanks the funding of  Sorbonne Université -China Scholarship   Council program 2017 and Labex Matisse program  ( ASDB/2017-12 ) for the PhD contract of  L. Zhang , as well as the  ECOS Sud-Chile CONICYT program  (Project  C17E10 ). Thanks for the help of  Dr. F. J. Recio Cortes  and  Dr. R. Venegas  in  Pontificia Universidad Católica de Chile. I. Merino-Garcia  would like to thank his Post-doctoral contract in the frame of Research Project  PTDC/EQU-EPQ/29579/2017 , financed by " Programa Operacional Regional de Lisboa, na componente FEDER " and " Fundação para.
Most decisions indeed must be made in situations in which some events do not have an obvious, unanimously agreed-on, probability assignment. This might be because too little information is available or because different predictions exist, resulting from different models or datasets or from different experts' opinions. The evaluation of climate policy is generally performed using decision criteria that, like the standard expected utility theory criterion developed by von  Neumann and Morgenstern (1947)  and  Savage (1954) , do not distinguish between risk and uncertainty but actually reduce any kind of uncertainty to risk. As the treatment of uncertainty has recently received a great deal of attention in climate policy, 1  an increasing number of concerns have been raised about the use of standard techniques, originally developed to deal with risk, in problems involving uncertainty.