dataesr/scientific-paragraphs-categorization huggingface dataset:
However, FAMEs yield decreased at high DIC treatment time, probably because of a possible thermal degradation of oil. Experimental data of FAMEs yield proved the importance of DIC treatment with 6. 1 ± 0. 3 and 4. 9 ± 0. 8 g/100 g db for initial water content of 100% and 30%, respectively, compared to 3. 7 g/100 g db for raw material. RSA results show an optimum value of FAMEs at 6. 3 and 5. 8 g/100 g db that could be achieved from DIC treatment of samples with initial water content of 100% and 30%, respectively, at P = 0. 41 MPa, t = 47 s and P = 0. 41 MPa, t = 40 s. By contrast, the variation in extract compositions after in situ extraction was investigated from LC-FID analysis. A typical graph is shown in Figure  6 ; LC-FID Iatroscan can be used as an accurate way to obtain a preliminary description of lipids and FAMEs formation and identification.
94 min. From Figure  7 , it is noted that the extract of DIC-treated microalgae sample contains more lutein compared to the crude extract of the raw untreated material. The results in Figure  4  showed that an increase of about 143. 9% in lutein could result when using DIC as a pretreatment of microalgae material. The effect of DIC processing variables on lutein extractability is shown in Figure  8. The significance of DIC parameters on lutein yield is estimated from the RSA. The analysis of the data indicates that both DIC heating time and steam pressure have significant positive effects on lutein yield. The most significant effect in terms of lutein yield is relevant to the processing steam pressure. It was found experimentally that the yield of lutein extracted from the DIC-treated samples is higher (ranging from 4.
Given the current knowledge on A. macleodii and its potential in lab culture, this model organism was chosen in the present study. We performed our experiments with two strains of A. macleodii isolated from contrasting environments and maintained in the Microbial Observatory Laboratoire Arago (MOLA) culture collection. The oceanic strain, MOLA377 (GenBank accession number: AM990654), was isolated from surface waters (5 m) of the oligotrophic South Pacific gyre (Sta. GYR4 of the Biogeochemistry and Optics South Pacific Experiment transect; 114u129W, 26u249S) where concentrations of nitrate (, 0. 01 mmol L 21 ), phosphate (0. 11 mmol L 21 ), and chlorophyll a (0. 029 mg L 21 ) were particularly low in surface waters. The concentration of DFe was 0. 10 nmol L 21 at 5 m  (Blain et al. 2008 ). The coastal strain, MOLA60 (GenBank accession number: AM990835), was isolated from surface waters (3 m) at the Service d'Observation du Laboratoire Arago (Sta.
At the beginning of the exponential growth phase, subsamples of the bacterial cultures (, 5 mL) were transferred into clean, gas-tight chambers. Triplicate subsamples were collected from each biological replicate, and three consecutive respiration measurements, each lasting for 10 min, were done on every subsample. The concentration of O 2 was monitored continuously over time (one measurement every 5 s) during the 10 min and data were subsequently visualized by the software MicOx (Unisense). Between measurements in one set of replicate subsamples, the electrode was transferred for 15 min into a control chamber with 0. 2 mm-filtered modified Aquil saturated in O 2 (medium was bubbled during 10 min before sealing the chamber with the cap). This protocol allows drift correction of the electrode if any drift occurs.
In total for the two strains, 27 gels were realized: six gels for each condition (i. e. , +Fe and 2Fe) plus three additional gels for spot excision. After staining, the gels were scanned with the fluorimager ProXpress from Perkin Elmer, and images were analyzed by the software SameSpots 4. 0 (Nonlinear Dynamics) for normalization of the gels and statistical analyses. The twodimensional (2D) gels were superimposed to form a standard image. The different standard gels for +Fe and 2Fe conditions were then compared for differential expression analysis. Volumes of spots were automatically normalized by the software and a statistical analysis was performed to compare the corresponding reference gels of the two conditions (+Fe and 2Fe). In this study, the statistical criteria used were as follows: analysis of variance (ANOVA) significance and q value , 0.
05, P (power analysis). 0. 8, and a volume difference $ to 1. 6. For the ANOVA, only spots whose average normalized volume was $ 65,000 were considered. Database analysis-The protein spots that had a significantly different expression following 2D gel analysis were manually excised and subjected to in-gel digestion with MultiPROBE II (Perkin Elmer) using trypsin, as previously described in  Sulaeman et al. (2012) , to be then analyzed in liquid chromatography coupled with tandem mass spectrometry (MS 2 ), and OrbiTrap. The peak lists from the MS 2 spectra obtained were compared to the National Center for Biotechnology Information database in 2010 and 2011 (restricted to bacteria) using the Mascot Daemon search program (http://matrixscience. com). Identified proteins were localized into metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes pathway database (http://www.
genome. jp/kegg/pathway. html) and were linked together using the Search Tool for the Retrieval of Interacting Genes/Proteins database (http://string-db. org). Bacterial abundance and biovolume-Bacterial cell abundance was monitored by flow cytometry. Cells were fixed (2% formaldehyde, final concentration) for 15 min at 4uC and stored frozen at 280uC until processed. For enumeration, bacteria were stained with SYBRH Green I and counted using a Becton Dickinson fluorescence-activated cell-sorting Calibur flow cytometer  (Marie et al. 1997 ). Specific growth rates were calculated from the slope of loglinear regression over time during the exponential phase. For the determination of the biovolume, formaldehydefixed cells were filtered onto 0. 2 mm polycarbonate filters (Millipore) and stained with 49,6-diamidino-2-phenylindole (2 mL mL 21 in a 4 : 1 mixture of Citifluor : Vectashield, Vector Laboratories).
The bacterial cell volume was determined by epifluorescence microscopy (Olympus Provis AX70), using an image analysis system (Microbe Counter software;  Cottrell and Kirchman 2003). Ten fields of view, each containing on average 150 cells, were counted per filter. Mean biovolumes of each biological replicate for Fe-replete and Fe-limited cultures were determined. Statistical analysis-All statistical comparisons between +Fe and 2Fe treatments were performed using a twotailed, unpaired Student's t-test (Microsoft Excel Analysis ToolPak). Differences were considered statistically significant at p # 0. 05.
Gel comparison among treatments (i. e. , 2Fe and +Fe) allowed us to determine that in MOLA377 152 spots (102 overexpressed and 50 underexpressed) and in MOLA60 98 spots (44 overexpressed and 54 underexpressed) were affected by the growth conditions. MS 2 analysis followed by sequence matching on the protein database resulted in the identification of 88 and 99 of these differentially expressed proteins and protein isoforms by the oceanic (MOLA377) and the coastal strain (MOLA60), respectively (see Web Appendix, Tables A1-A4, Figs. A1  and A2 , www. aslo. org/lo/toc/vol_59/issue_2/0349a. html). Table  1. Biochemical composition, respiration, and growth rates of the oceanic strain (MOLA377) and the coastal strain (MOLA60) of Alteromonas macleodii grown under Fe-replete (+Fe) and Fe-limited (2Fe) conditions.
Acknowledgments We thank  Laurent Intertaglia  for providing the Alteromonas macleodii strains,  Jocelyne Caparros  for the analyses of particulate organic carbon and nitrogen, and  Isabelle Schalk  and  Valerie Geoffroy  for helpful discussion. We thank two anonymous reviewers for critical comments on a previous version of the manuscript. This research was funded by the  Agence Nationale de la Recherche  ( ANR , A biomolecular approach to the cycling of carbon and iron in the ocean [project  BACCIO ],  ANR-08-BLAN-0 309 ).
These values are not meant to represent accurately concrete sectors of the economy, even though they do not differ much from the two sectors modeled by  Lecocq et al. (1998). We use them to carry out illustrative experiments, which help draw more general conclusions. We solve this simple model using a linear programing algorithm provided by GAMS  (Brook et al. , 1988). The source code also uses Scilab  (Scilab Consortium, 2011). Code and data are available on the corresponding author's web page. Results may be verified using the spreadsheet model provided on the corresponding author's web page.
Acknowledgments We thank  Nils Axel Braathen ,  Patrice Dumas ,  Marianne Fay ,  Michael Grubb ,  Céline Guivarch ,  Jean Charles Hourcade ,  Fabian Kesicki ,  Camille Mazas ,  Guy Meunier ,  Julie Rozenberg , the audiences at the  International Energy Workshop , at the  European Association of Environmental and Resource Economists Conference , at the  International Association of Energy Economics  and at the.
g. , materials, emissions) from the processes occurring in the life cycle of an EGS plant, is based on the one proposed by  Lacirignola and Blanc (2013). This paper is mainly based on technical data from the Soultz-sous-Forêts site. It also presents a multi-criteria environmental assessment of ten alternative plant setups, with two or three wells and a final power output ranging from 0. 8 to 3. 1 MW. Data regarding background processes, such as raw material extraction or transports are retrieved from the ecoinvent database v2. 2 (Ecoinvent Centre 2010). The characterization factors used to calculate the GHG are based on the IPCC reports  (Bernstein et al. 2008).
Reference model's equation The reference model's equation (  3 ) is obtained by developing Equation 1, as represented in Figure  1. The numerator of Equation 1 (GHG emissions of the EGS power plant) can be expressed as the sum of the contribution of the four parts of the model (as detailed in section 'Generation of an explicit LCI model': wells, ORC, pumps and enhancement phase). GHG emissions are calculated from data regarding life cycle input and outputs of materials and energy flows (reported in Additional file 1 section 1) and their IPCC GHG characterization factors. The denominator of Equation 1 (electricity produced) can be expressed by Equation  2. Hence, we obtain Equation 3: In this equation, z is the borehole depth (m), f is the total produced flow rate (kg/s), Nw is the number of wells, d represents the amount of fuel for drilling (MJ per meter drilled), LF is the load factor (dimensionless), LT is the lifetime (years), SFe is the enhancement factor (dimensionless), P ORC is the ORC power output (kW), and P p is the specific power of the pumps (kW/(kg/s)).
Catalyst characterization This characterization was carried out with the aid of different spectroscopic techniques such as infrared, to know the superficial groups in different catalyst. The sample was analyzed through a red spectrometer Nicolet IR-200 with software EzOmnic 32. The number of scans was 32 at a resolution of 16cm -1 /s; X-ray diffraction, to determine whether there is presence of crystalline phases formed during the activation phase through a diffract meter RIGAKU 2200 with radiation CuKα = 1,54056 every 0. 02 degrees and at a fixed time of 0,3 seconds in a range of 20 -80 (2θ); transmission electronic microscopy (TEM), to identify the morphology, distribution, and particle size in an electronic microscope Jeol 1200 EX; determination of the superficial area to find out the texture of the catalyst through a SE micro meter ASAP 20110; and finally, program temperature reduction (PTR) to know the reduction temperature for each of the metals present in the catalyst.
Cell biovolume C. watsonii cells were harvested in exponential phase, 2 hours after the beginning of the dark period, onto 0. 4 mm polycarbonate membranes, and incubated overnight into a fixative with adjusted osmolarity (3% glutaraldehyde in 0. 1M cacodylate pH 7. 4, NaCl 1. 75%). Membranes were then washed, post-fixed for 1 h with 1% osmium tetroxide in 0. 1M cacodylate buffer with 1. 75% NaCl, and then dehydrated with graded increasing concentrations of ethanol (50, 70, 96, 100%) and critical point dried (CPD 7501, Quorum Technologies). Finally, membranes were mounted on stubs, gold-sputtered (Scancoat Six, Edwards) and observed with a conventional SEM (Scanning Electron Microscope, Cambridge Stereoscan S260). Pictures were analysed with ImageJ software  [41]  in order to determine cell diameters and biovolumes.
Acknowledgments We would like to thank  Manon Tonnard  and  Benjamin Ledoux  for helping with some data acquisition. We also thank  Matthieu Bressac  and  Cecile Guieu  ( LOV, Villefranche sur Mer, France ) for dFe measurements by  FIA  and  Philippe Catala  ( ARAGO, OOB, Banyuls sur Mer, France ) for analyses by flow cytometry. Michae ¨l Trichet (Scanning Electron Microscopy service,  FRE3595 ,  UPMC, Paris, France)  is acknowledged for the preparation of MEB samples and his help during MEB observation sessions. We are thankful to HerveRybarczyk ( MNHN, Paris, France ) for sharing his helpful knowledge on statistics and  Bill Sunda  ( NOAA, US ) for its precious help in the Fe9 calculation. Tamara Barriquand  and  Fauzi Mantoura  are acknowledged for their careful proofreading. We are grateful to  Sophie Bonnet  ( MIO, Marseille, France ) for providing Crocosphaera watsonii WH8501 strain.
Acknowledgments The authors acknowledge funding from  Neste Oil (Finland) , the  French Research Institute for Exploration of the Sea (Ifremer) , the  Faculty of Health and Life Sciences, Linnaeus University (Sweden) , and the Strategic funding from the  Swedish Research Council (Formas) , -Ecosystem dynamics in the Baltic Sea in a changing climate perspective-ECOCHANGE‖. We wish to thank  Alice Newton  for providing workplace at the  University of Algarve, Portugal ,  Bruno Fragoso  for practical arrangements, the staff at  Necton  for help and assistance during the experiments and  Alexis Avril  at the  Faculty of Health and Life Sciences, Linnaeus University , for help with statistical analyses. This is a contribution to the  LnU Centre for Ecology and Evolution using Microbial models Systems (EEMiS).
graphpad. com). The percentage of iron atoms released was determined by measuring the absorbance of the iron-chelator complex and assuming that the initial concentration of the ironbound RIC is 100%. The following extinction coefficients were used: e 420nm = 2. 9610 3 M 21 cm 21 and e 522nm = 8. 7610 3 M 21 cm 21 for desferrioxamine-Fe(III) and 2,29-dipyridyl-Fe(II), respectively  [19, 20]. This model could be used as the data did not indicate, within the experimental errors, a biphasic behavior attributable to the two iron ions of the cluster. Hence, at this stage and as a first approximation, it was assumed that both sites have identical binding constants and that they behave independently of each other. The actual dissociation constant of iron from RIC, Kd RIC , was then calculated using the equation Kd RIC = 1/(Kd RIC-chelator x Ka chelator ), in which Ka chelator = [Chelator-Fe]/[Chelator][Fe] and correspond to the affinity constants of desferrioxamine-FeIII (,10 31 M 21 ) or 2,29-dipyridyl-FeII (10 17 M 21 ), respectively  [21, 22].
Reconstitution of the Fe-S center of ferredoxin The formation of the Fe-S center in ferredoxin assisted by RIC was first monitored by UV-visible spectroscopy. Anaerobic incubation of the apo-ferredoxin (25 mM) with RIC (50 mM) was done in the presence of DTT, IscS and L-cysteine. The final reaction mixture presented a brownish color and a visible spectrum with major bands at 415 and 460 nm (Figure  1A ); starting with the apo-ferredoxin, the absorbance at those wavelengths increased with time and reached a maximum after 75 min. These bands are characteristic of a [2Fe-2S] 2+/1+ center typically present in the oxidized form of the spinach ferredoxin (Figure  1A , bold line). This spectrum shows that under the conditions used the binuclear center was oxidized, presumably a result of its quite low reduction potential (2400 mV,  [23] ), and in agreement with the EPR data described below.
Considering the absorption of the 415 nm band of the spectrum recorded after 75 min, we determined that approximately one (ca 70%) Fe-S center was reconstituted in the spinach ferredoxin. The formation of the Fe-S center of ferredoxin in a reaction containing DTT, IscS, L-cysteine and E. coli RIC was also analyzed by EPR spectroscopy. The spectrum of oxidized ferredoxin is EPR silent (data not shown), indicating, in concordance with the optical data, that the Fe-S centers are oxidized; therefore, all the samples were reduced by the addition of dithionite and analyzed before and after reduction. The rhombic species observed for reduced reconstituted ferredoxin, obtained in the presence of E. coli RIC or ferrous iron, with g values of 1. 89, 1. 92 e 2. 04, is identical to that of the reduced native protein (Figure  1B ).
Release of iron from E. coli RIC The above data indicates that RIC donates iron for the reconstitution of Fe-S centers. To further evaluate this process, we determined the iron binding dissociation constants of RIC in the as-isolated and fully reduced forms. Desferrioxamine and 2,29dipyridyl were used as FeIII and FeII chelators, respectively, and the intensities of the 420 nm absorption band for the desferrioxamine-FeIII complex and of the 522 nm band for the dipyridyl-FeII complex were utilized to calculate the amount of iron released. Furthermore, several concentrations of chelator were tested in independent reaction mixtures that were incubated under aerobic and anaerobic conditions for desferrioxamine and 2,29dipyridyl, respectively (Figure  3 ). Incubation of the as-isolated RIC with each chelator released approximately 7463% of FeIII and 2162% of FeII with similar dissociation constants (Kd RIC-chelator ) of ,30610 26 M towards the chelators (Figure  3A-B , Table  1 ).
Anaerobic incubation of the fully reduced form of RIC with 2,29-dipyridyl led to the release of 9664% of FeII with a dissociation constant of 151611610 26 M in relation to the chelator (Figure  3C  and Table  1 ). Furthermore, the data indicate that the two iron sites have similar dissociation constants. The constants associated with the binding of iron ions to RIC (Kd RIC ) were then determined using the values above indicated (Kd RIC-chelator ) and the equations described in Material and Methods. The data showed that in the as-isolated RIC, the FeIII is more tightly bound (Kd RIC = 461610 227 M) than FeII (Kd RIC = 461610 213 M). Moreover, the strength of the FeII binding does not vary significantly when the protein is fully reduced, in which case the Kd RIC is 0. 761610 213 M (Table  1 ).
The work was funded by  PEst-OE/EQB/LA0004/2011 ,  FCT  projects  PTDC/BBB-BQB/0937/2012  (LMS),  PTDC/QUI-BIOQ/111080/2009  (MT) and by the following Fundaca ˜o para a  Ciencia e Tecnologia fellowship   SFRH/SRFH/BPD/69325/2010  (LN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Adsorption isotherms For dye-adsorption experiments, samples of wet gels are left in contact with aliquots of 2000 L of Rhodamine B aqueous solution in different concentrations (1-50 M, previously adjusted to pH 7. 0). To quantify the concentration of Rhodamine B (RhB), the UV-vis spectrometer was calibrated to a concentration range between 0. 1 and 1. 0 M at a wavelength of 554 nm, which corresponds to the absorption maximum of RhB. The concentration of dye in solution is measured spectrophotometrically at = 554 nm. The fraction of dye adsorbed on the silica matrix is calculated from the difference between the concentration in solution at t = 0 and after the systems had reach the equilibrium. Experimental data are fitted to the Freundlich model: S = FC n e (1) where S is the mass of adsorbate by mass of adsorbent, F is the Freundlich constant of adsorption, C e is the dye concentration in solution at equilibrium and n is a constant that varies from 0 to 1.
Acknowledgements This work was performed in the frame of the  ECOS-Sud A12B02 program  and has been supported by the  University of Buenos Aires  ( UBACyT 20020100100636 ), the  National Agency for Science and Technology Promotion of Argentina  ( PICT-2012 ( PICT- -1167 )), the  National Research Council of Argentina  ( CONICET PIP 11220110101020 ) and  Brazilian Syncrotron Light Laboratory  ( SAXS1-13426 ).
Aggregation state analysis Size-Exclusion Chromatography experiments (SEC) was performed with a Superdex 200 analytic Increase (GE Healthcare) equilibrated in 100 mM Tris-Cl pH 8, 200 mM NaCl, 5 mM TCEP. Calibration has been performed using bovine serum albumin (BSA). Separations were performed at 20 • C with a flow rate of 0. 5 ml. min -1. Note that 50 l of a protein solution at a concentration of 7 mg. ml -  were injected. Online MALLS detection was performed with a DAWN-EOS detector (Wyatt Technology Corp. , Santa Barbara, CA,USA) using a laser emitting at 690 nm. Protein concentration was measured online by refractive index measurements using a RI2000 detector (Schambeck SFD) and a refractive index increment 0. 185 ml. g -1. Data were analyzed and weight-averaged molecular masses (Mw) were calculated using the software ASTRA V (Wyatt Technology Corp.
Spectroscopic measurements UV-visible absorption spectra were recorded in quartz cuvettes (optic path 1 cm) under anaerobic conditions in a glove box on a XL-100 Uvikon spectrophotometer equipped with optical fibers. M össbauer spectra were recorded at 4. 2 K on a low field M össbauer spectrometer equipped with a Janis SVT-400. Spectrometers were operated in a constant acceleration mode in transmission geometry. The isomer shifts were referenced against that of a room temperature metallic iron foil. Analysis of the data was performed with the program WMOSS (WEB Research). X-band EPR spectra were recorded on a Bruker ESP-300E EPR spectrometer operating with an ER-4116 dual mode cavity and an Oxford Instruments ESR-9 flow cryostat. Resonances were quantified under non-saturating conditions.
Experimental set-up Here we focus on the VKS experiment, consisting of a von Kármán swirling flow of liquid sodium. The dynamo is generated in a cylinder of radius R 0 = 289 mm by the motion of two coaxial discs of radius R imp = 154. 5 mm, counter-rotating at a frequency F. We define the magnetic Reynolds number as: Rm = 2πµ 0 σR imp R 0 F where σ = 9. 6 × 10 6 Ω • m -1 is the sodium electrical conductivity and µ 0 the permeability of vacuum. In the sequel, we use data from the 8 configurations obtained by changing the material of the impellers and of the cylinder as shown in Fig. 2  and described in  [12]. Magnetic fields are recorded using four arrays of ten 3-axis Hall effect sensors inserted in radial shafts, as shown in  The method can be described as follows. First of all, the extremes of the magnetic field are extracted by using the so called block maxima approach which consists in dividing the series | B(t)|, t = 1, 2,.
We then turned back to configurations R, U, V, and found that a cubic fit of the κ l values such that Rm < Rm * provides an extrapolated threshold value Rm e that is close to the Rm * determined via real data. We thus run this cubic extrapolation technique to Q', S and T, and obtain value of Rm e that are reported in the table. The extrapolated values found here are generally smaller than the one found by Miralles et al. [12] , but in both cases the extrapolation presents great uncertainty. In this article, we have tested a methodology for the detection of dynamo threshold based on EVT using datasets produced in the VKS experiment. This technique, applied here for the first time to an experimental dataset, confirms the theoretical expectations of  [14]  and allows for detecting hysteretic behaviors.