dataesr/scientific-paragraphs-categorization huggingface dataset:
 For set C, the client specification had tighter accuracy requirements, which can be reasonably applied. They would be error for temperature of 0. 1 °C, flow measurement of 0. 01 m•s -1 and power to 5W. Table  2. Considered values for the error on the input parameters. For both datasets, the most significant sources of error are related to the heat capacities of the ground and the concrete (refer to Figure  8  which represent the distribution of Δ terms). As expected, temperatures and power play a more significant role for set B, where the standards are less restrictive. Errors on the pile diameter affect the inner parameters Rb and x significantly. The error on the ground thermal conductivity is 0. 06 W•K -1 •m -1 for set C (about 4%) and 0. 20 W•K -1 •m -1 for set B (about 6%) reflecting the more restrictive standards for set C.
Therefore we propose that by using the RC model the combination of a short BHE TRT and an additional short TRT on one of the constructed piles may provide the best solution. One TRT is performed on a BHE having a small radius (e. g. , rb = 8 cm) to determine λm within a few days, while simultaneously a TRT is performed on the PHE to obtain the inner parameters for the RC model. This undertaking assumes that the ground is relatively homogeneous and lateral variations of composition and ground properties can be overlooked. This approach is illustrated with respect to datasets B and C. The best-fit values of λm are assumed to have been obtained independently from a BHE TRT. In this case values of 3. 24 W/mK and 1. 43 W/mK are used, respectively, for sets B and C, based on the results in Section 3.
The RC model is then optimized for the pile TRT data with only two rather than three unknowns. The fitted values of x and Rb start to stabilize around tmax ≈ 30-40 h for set B at x ≈ 0. 56-0. 58 and Rb = 0. 080 K•m•W -1 and tmax ≈ 100 h for set C at x ≈ 0. 76-0. 78 and Rb = 0. 121-0. 124 K•m•W -1 (Figure  10 ). For both datasets, the difference, with the value of Rb determined in Section 3, does not exceed 4%. It is desirable to determine the minimum test duration tmax beyond which the determined values of Rb and x are reliable. Here we use as a criteria the ability of the RC model to forecast the evolution of the fluid temperature at the very end of the data record, from tmin' to from tmax'. A second RMSE indicator ε' is build considering tmin' = 80 h and tmax' = 100 h for set B, and tmin' = 300 h and tmax' = 350 h for set C.
Usually, the conduction band position of n-type semiconductors is 0. 1 V above the flat band levels  [37]. So, the conduction band (E = -5. 19 eV/0. 44 V) indicates that the CB is composed mainly of oxides derived from Orbital 3D. Hence, the energy of the valance band (E = E -E = -7. 99 eV/3. 24 V). The diagram of electrochemical impedance spectroscopy (EIS) of the junction ZnBi2O4/NaOH electrolyte is modeled to an equivalent electrical circuit using the software Zview (Figure  8  Inset), corresponding to the contribution of the bulk, grains boundary, and ions diffusion. The Nyquist diagram is the plot of the imaginary part (Zim) versus the real part (Zre) related to the presence of a constant phase element (CPE)  [61] : Z = Q(jW) ; 𝑛 = (14) where Q is a frequency-independent constant, n is the homogeneity factor (0 < n ≤ 1) related to the phase angle φ = (nπ/2).
(Figure  8 ) illustrated the Nyquist diagram with the modeling results of the equivalent electrical circuit, which represent a semicircle associated with the charge transfer resistance (Rs = 1 kΩ cm 2 ) in series with a Constant Phase Element  (  = 3. 79 × 10 ,  = 0. 3198) and Warburg Element  (  = 36315,  = 4. 469,  = 0. 78123), in parallel with Rp the electrolyte solution (49 kΩ cm 2 ). The chisquared and weighted sum of squares are 0. 00186, 0. 0392 respectively. The process is also represented in the Bode plan (log Z vs. log frequency) (Figure  S9  in the Supplementary Data). The decrease in Z increasing the frequency indicates an enhanced electrical conductivity and a lowering of the potential barrier  [57]. The diagram of electrochemical impedance spectroscopy (EIS) of the junction ZnBi 2 O 4 / NaOH electrolyte is modeled to an equivalent electrical circuit using the software Zview (Figure  8  Inset), corresponding to the contribution of the bulk, grains boundary, and ions diffusion.
Microalgae cells were detected by chlorophyll a auto-fluorescence. Chlorophyll a was excited at 639 nm and was detected using a low pass filter 615 nm. A custom script running in Fiji  44, 45  was used to extract from the z-stacks the quantitative parameters used to characterize biofilm architecture: biovolume, maximal and mean thickness, roughness and the area occupied by the cells in each layer of a biofilm. The structural parameters were calculated according to the computation (1) τ = 6Qµ wh 2 described in COMSTAT 2. 1 (Technical University of Denmark;  42  ), but the thresholding was performed using the Otsu algorithm  46  considering the histogram of the whole stack. In order to quantitatively compare the biofilm growth curves, they were fitted using the logistic function as described in Wang et al.
The displacement of each detected cell was calculated (in µm) as the distance between the last and the first position of the track in time  50. After the applications of the filters, a number of cell tracks comprised typically between 50 and 300 was obtained for each video. Three videos were acquired in random positions of each channel in a flow-cell (e. g. inlet, middle and outlet). The displacement of the cells in the biofilms at the different shears was visualized by pooling the log-transformed data at each condition and using the Kernel density plot  51  in order to estimate the probability density function of cell population. Cohesiveness-Erosion test. The cohesion of the biofilms cultivated at different hydrodynamic regimes was tested using a protocol similar to the one described in Paul et al.
Statistics. Statistics was performed using GraphPad prism 5. 0 (San Diego, CA, USA) and the R software  52. Each experiment was conducted on at least three independent biofilms and data are reported as mean and standard deviation. To evaluate the significance of mean differences among shear conditions, One-way and Two-way ANOVA followed by the Tukey's post-hoc test for multiple comparisons were conducted. Conditions sharing the same letter combinations are not statistically different whereas conditions presenting no letter in common are statistically different. The level of significance was always set at 5%.
FUNDING This work was supported by  ETH Zürich , the  University of Cambridge , and, in part, by an interdisciplinary grant from the  Swiss National Science Foundation  (Grant Number  CR22I2_166110 ) to BN as well as a career grant from the  Swiss National Science Foundation  (Grant Number  P2EZP2_199843 ) to NL. SB's Ph. D. grant is funded by the  ARED Région Bretagne  (Grant Number  COH20020 ) and the  Sorbonne Université. The authors acknowledge open access funding by  ETH Zürich.
Morphology of the samples was studied by scanning electron microscopy (SEM) with an S-4700 Hitachi instrument (Hitachi, Marunouchi, Chiyoda-ku, Tokyo, Japan) at 20 kV and morphological features were examined by using the software ImageJ (Version 1. 51). Grazing incidence X-ray diffraction (GIXRD), X-ray reflectivity (XRR) and X-ray absorption spectroscopy (XAS) experiments were carried out at the Spanish CRG synchrotron beamline BM25-SpLine at the European Synchrotron Radiation Facility (ESRF), in Grenoble (France). GIXRD and XRR measurements were carried out in a high precision six-circle diffractometer (HUBER Diffraktionstechnik GmbH & Co. KG, Rimsting, Germany) in vertical geometry [33] at room temperature using a photon wavelength of 0. 826 Å (hν = 15 keV) to ensure the access to a wide reciprocal space region.
XAS experiments were performed at the Fe K-edge (7112 eV) at room temperature in fluorescence mode using a 13-elements Si(Li) detector from e2V Scientific Instruments (Sirius House, Watery Lane, Wooburn Green, High Wycombe, Buckinghamshire, UK) located 90 • with respect to the incoming X-ray beam. Spectra of reference standards (Fe foil, FeO, Fe 3 O 4 and α-Fe 2 O 3 ) were measured for comparison in transmission mode with two ionization chambers as detectors. XAS data were analyzed using Demeter package (Version 0. 9. 26)  [34, 35]. X-ray photoelectron spectroscopy (XPS) measurements were carried out on the Fe 2p and Au 4f core levels using a standard monochromatic X-ray tube with a Mg Kα radiation anode (hν = 1253. 6 eV). The binding energy of XPS spectra was calibrated considering the C 1s binding energy of a small residual amount at 284.
Funding: This work has been supported by the  Ministerio Español de Ciencia e Innovación (MICINN)  and the  Consejo Superior de Investigaciones Cientificas (CSIC)  through the projects  PIE-2010-OE-013-200014 ,  PIE 2021-60-E-030  and  RTI2018-095303-A-C52. The  ESRF, MICINN  and  CSIC  are acknowledged for the provision of synchrotron radiation facilities. A. S. acknowledges financial support from  Comunidad de Madrid for an "Atracción de Talento Investigador " Contract ( 2017-t2/IND5395 ). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
X-ray absorption near edge structure (XANES) XANES experiments were performed at sector 10-BM of the Materials Research Collaborative Access Team (MRCAT) at the Advanced Photon Source (APS, Argonne National Laboratory). The samples were mixed with boron nitride in the weight ratio of 1:5, ground well, and then pressed into a sample holder containing cylindrical hole of 0. 12 cm 2 cross-sectional area. The measurements were performed in transmission mode at Fe K-edge (7112 eV) and Ni K-edge (8333 eV). Each measurement on the samples was coupled with X-ray absorption spectra of the corresponding metal foil in order to calibrate the data for any shift in X-ray energy.
Acknowledgments The  DDP-LAC  project is financed by the  IADB Sustainable Energy and Climate Change Initiative fund  ( RG-T3028 ), the  IADB French Climate Fund  ( RG-T3193 ), the 2050  Pathways Platform , and the  Agence Fran-çaise de Déeveloppement (AFD). The authors thank and acknowledge  Ivan Pharabod  for the design of our figures. IDDRI gratefully acknowledges its ongoing support from the  French National Research Agency , Grant Number:  ANR-10-LABX-14-01.
10 cycles (400 min) of degradation. Embedding metal  NPs (Fe, Co, Ni, Mn ) into N-doped-CNF can be considered as an effective strategy to produce electrocatalysts for the removal of organic dyes. Shortly, the CNFs electrodes will be tested for the removal of other organic matters such as antibiotics drugs (e. g. , tetracycline, amoxicillin), pesticides, and microplastics from effluents to enlarge their application fields. Acknowledgments: We are grateful to the  Egypt-France Joint Program  (Imhotep, Project No. 43990SF ,  2020-2022 ) for funding Ahmed Barhoum's (Project  PI ,  Egyptian Side ) research work in  France. Ahmed Barhoum  ( NanoStruc Research Group, Helwan University ) would also like to thank the  Irish Research Council  (hereinafter referred to as 'the Council') for financing his research stay at the  School of Chemical Sciences, Dublin City University  under grant number (Project  ID :  GOIPD/2020/340 ).
Numerical model Calculated variables T and were obtained using the commercial software COMSOL Multiphysics 5. 6. First, a preliminary parametric study on the triangular mesh was carried out in the first study case (i. e. , without insulation) for three meshes comprising 2569 elements (mesh #1), 2873 elements (mesh #2), and 5553 elements (mesh #3). Since the impact of mesh size on the results were extremely limited, mesh #2 with 2873 elements was used. Fig. 4a  shows a mesh consisting of 2873 elements for the first study case and 5431 for the second (Fig. 4b ), both refined at the interfaces between water and evaporation material, as well as the interface between air and the evaporation material, with 100 elements. The rest of the mesh is created automatically by the software, depending on the physics involved.
Sideroflexins (SLC56 family) are highly conserved multi-spanning transmembrane proteins inserted in the inner mitochondrial membrane in eukaryotes. Few data are available on their molecular function, but since their first description, they were thought to be metabolite transporters probably required for iron utilization inside the mitochondrion. Such as numerous mitochondrial transporters, sideroflexins remain poorly characterized. The prototypic member SFXN1 has been recently identified as the previously unknown mitochondrial transporter of serine. Nevertheless, pending questions on the molecular function of sideroflexins remain unsolved, especially their link with iron metabolism. Here, we review the current knowledge on sideroflexins, their presumed mitochondrial functions and the sparse-but growing-evidence linking sideroflexins to iron homeostasis and iron-sulfur cluster biogenesis.
Sideroflexins Are Mitochondrial Transporters Implicated in One-Carbon Metabolism SFXNs possess four to six predicted transmembrane domains composed by α-helices revealed by in silico modeling  [1, 6, 7]. These proteins share several highly conserved motifs, including a HPDT motif and an asparagine-rich sequence (Figure  1 )  [1, 6]. The functions of those conserved motifs have not been uncovered yet. Recently, Gyimesi and Hediger performed an in silico analysis of human SFXN1-5 sequences and described six wellconserved regions that could be important for SFXNs activity  [11]. Whether these conserved regions are essential for metabolite transport need to be further confirmed at the bench. To date, no crystal structure has been released for SFXNs. We thus tried to model SFXN tridimensional structure using the trRosetta software  [12].
However, our model is rather in agreement with a TM domain composed of six alpha helices, and if this predicted structure is correct, the N and C termini could be in the same mitochondrial compartment (Figure  2 ). The CryoEM structure of SFXN1 is thus needed to precise the three-dimensional structure of this carrier. Moreover, two recent studies investigated the mechanisms of SFXN1 mi- Left panel: Phylogenetic tree obtained using the MultiAlin software (http://multalin. toulouse. inra. fr/multalin/) [10]. Right panel: scheme of the SFXN1 protein and its conserved motifs. (B). Alignment of human SFXNs protein sequences. Red amino acids are for high consensus levels (90%), the blue ones are for low consensus levels (50%). Meaning of symbols found in the consensus line: "!" is for Ile or Val, "$" is for Leu or Met, "%" is for Phe or Tyr," #" is anyone of Asn, Asp, Glu, Gln.
Conserved motifs are shown and highlighted using an HMM logo created using Skyline (http://skylign. org/) with consensus colors for amino acids according to the ClustalX coloring scheme. Left panel: Phylogenetic tree obtained using the MultiAlin software (http://multalin. toulouse. inra. fr/multalin/) [10]. Right panel: scheme of the SFXN1 protein and its conserved motifs. (B). Alignment of human SFXNs protein sequences. Red amino acids are for high consensus levels (90%), the blue ones are for low consensus levels (50%). Meaning of symbols found in the consensus line: "!" is for Ile or Val, "$" is for Leu or Met, "%" is for Phe or Tyr," #" is anyone of Asn, Asp, Glu, Gln. Conserved motifs are shown and highlighted using an HMM logo created using Skyline (http://skylign. org/) with consensus colors for amino acids according to the ClustalX coloring scheme.
Model Localization Experiment Due to their predicted structure, showing several hydrophobic alpha helices, and their mitochondrial location, sideroflexins were proposed to be mitochondrial metabolite transporters. Rat Sfxn3 was presumed to be a tricarboxylate carrier (TCC), and later, Sfxn5 (also known as BBG-TCC) was reported to transport citrate in vitro  [21, 22]. However, it was only recently that a function of mitochondrial serine transporter was reported for SFXN1  [8]. By a bioinformatic analysis, the S. cerevisiae Fsf1 (YOR271cp) was proposed to be a candidate alpha-isopropylmalate transporter but no experimental data ascertained this function  [23]. Similarly, the predicted Fsf1 protein from Schizosaccharomyces pombe, Spac17g6. 15c, is annotated as a serine transporter in the database Pombase (https://www.
Recently, SFXN1 was shown to participate in LPS-induced ferroptosis in H9c2 cardiomyocytes, a process depending of NCO4A-mediated ferritinophagy  [91]. Li et al. showed an LPS-and NCOA4-dependent upregulation of SFXN1 and documented the role of SFXN1 in LPS-induced ferroptosis. Briefly, in LPS-treated H9c2 cardiomyocytes cells, knockdown of SFXN1 increased cell viability, restored intramitochondrial iron basal levels, inhibited mitochondrial ROS production, decreased lipid peroxidation and levels of PTGS2 (also known as cyclooxygenase-2) and MDA. Collectively, these data suggest that SFXN1 promotes LPS-induced ferroptosis, however the molecular mechanisms are far from being clear. Li et al. explained this role by SFXN implication in the iron mitochondrial import, which has not been proven yet.
Li et al. used immunofluorescence to show this DFO-mediated downregulation of SFXN1 and this must be confirmed using Western blot. The iron-mediated regulation of SFXN1 levels is intriguing and we wondered if iron could regulate translation or mRNA stability by IRP-dependent molecular mechanisms. We hypothesize that IRP proteins, which are major regulators of iron homeostasis acting at the post-transcriptional levels, could modulate SFXN levels through binding to cis-regulatory IRE response elements in SFXN1 transcripts. We thus searched for IRP-binding sites in SFXN transcripts. The IRE found in some of the iron-regulated transcripts are shown in Figure  7. Canonical IRE are motifs composed of a six-nucleotide apical loop (5 -CAGWGH-3 )  [95]. Using an IRE prediction tool ("SIREs Web Server 2.
0" (http://ccbg. imppc. org/ sires/)  [96] , we retrieved putative IRE in all human SFXN1 variant transcripts except for one (Table  4 ). One IRE of high quality and a second one of low quality are found, respectively, at the end of the SFXN1 coding sequence and in the 3 UTR (Figure  8 ). Additionally, human SFXN2 transcripts possess one putative medium-quality IRE and SFXN5 transcripts contain a putative high-quality IRE, at their 3 UTR. Interestingly, no IREs are predicted neither in SFXN3 nor in SFXN4 mRNAs. As SFXN1 and SFXN3 are closely related and seem to have highly similar three-dimensional structure, it is tempting to hypothesize that they can be differentially regulated depending on iron levels. In Drosophila, no putative IREs are predicted in any of the two mRNAs encoding dSfxn1/3 and dSfxn2, the SFXN orthologues found in flies.
The presence of putative IREs at the 3 UTR of some of SFXN transcripts is suggestive of their IRP-mediated stabilization. We thus expect an increase of SFXN1 levels under low iron levels, when IRP1 lacks its Fe-S cluster and IRP2 is degraded. The latter is not in agreement with the DFO-mediated downregulation of SFXN1 levels reported by Li et al. [91]. IRE motifs found in SFXN transcripts are non-canonical IRE motifs derived from IRE sequences identified in IRP-interacting mRNAs uncovered in the genome-wide SELEX experiments  [97] [98] [99]. Having found IRE in SFXN1 transcripts is in favor of an ironmediated regulation of SFXN levels, however, whether the IREs found in SFXN1, SFXN2 and SFXN5 transcripts are functional, is a point that needs to be further investigated. [97] [98] [99]. Having found IRE in SFXN1 transcripts is in favor of an iron-mediated regulation of SFXN levels, however, whether the IREs found in SFXN1, SFXN2 and SFXN5 transcripts are functional, is a point that needs to be further investigated.
Conclusions and Open Questions SFXN/SLC56 is a new family of mitochondrial proteins that have important roles in amino acid transport and in iron homeostasis. Several studies associate SFXN depletion with an increase in mitochondrial iron, deficiencies in carbon metabolism and RC activity and ferroptosis, in cell culture, in animal models and in human pathology, thus making the SFXN an interesting target for tissue degeneration therapy. However, even though those links seem to be clear and reproducible, nothing is known about the mechanism of action of SFXN. Do all the isoforms have the same functions (different members are expressed in different tissues)? As there are several transcripts for each isoform, do those different transcripts generate different proteins with different kinetic properties? If SFXN are not iron transporters, how can they control mitochondrial iron levels? How can they control mRNA and/or protein levels of some key heme regulators (CPOX, FECH and ALAS)? Some SFXN present putative IRE, but others do not; are all SFXN sensitive to iron content and to IRP1/2 regulation? (sc-91814, Santa Cruz Biotechnology, INC) using Interferin™ transfection reagent (Polyplustransfection Inc.
Acknowledgments: We acknowledge all the members of the  LGBC lab  for their support and their contribution to the good atmosphere at work. We are particularly grateful to  Juliette Bertheault de Noiron  who helped with Fiji macros,  Sebastien Szuplewski  for its interesting scientific speeches,  Christine Wintz  for technical assistance and  Marie-Pierre Golinelli  for giving us DFO. And finally, many thanks to the people who support our research by donating at the  UVSQ Foundation.
Funding: This research was funded by  UVSQ, EPHE  and private funding collected by the  UVSQ Foundation. NL received a grant from the  UVSQ  ( AAPSI2019  for the  MITOSIDERO  project). This work was partly funded by ' NeurATRIS   ANR-11-INBS-0011  , of the  French Investissements d'Avenir Program  run by the  Agence Nationale pour la Recherche. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
This time step allows not only to describe the daily fluctuations of energy demand and availability, but also to decrease the number of optimization variables from 52 860 (1 h time step) to 4380 (12 h time step), which enables to reduce the CPU time for solving the problem. Indeed, the optimizations lasted around 24 h in a computer with an Intel® Xeon® Silver processor and were performed within MAT-LAB® software using the fmincon function and the SQP (sequential quadratic programming) algorithm. Some basics about the algorithm could be found in Chapter 18 of Nocedal and Wright  [51]. This algorithm was selected because of its speed of convergence. Moreover, SQP algorithm can be effectively used if nonlinearities are included in the objective functions and/or the constraints, e. g. by adding part-load efficiencies or economies of scale within the energy system model.
To limit the number of results obtained, we also included keywords combined with the Boolean NOT to exclude articles about forest and agriculture because they do not fit the definition of LLCS we used. Overall, our query yielded an initial total of 34 002 unique publications on WOS and Scopus in June 2019. We chose this rather extensive search string over more focused alternatives for matters of comprehensiveness and given the availability of a machine learning pipeline for streamlined evidence screening and selection (see below). Although the search string is extensive, we recognize several shortcomings of our search strategy. First, we focused on English publications only, but recognise the existence of relevant articles on carbon lockin in other languages. Second, we focused on the two bibliographic databases WoS and Scopus, but these do not cover the entire academic literature and miss grey literature entirely.