dataesr/scientific-paragraphs-categorization huggingface dataset:
Testing of mannitol production by Ectocarpus sp. M1Pases in Escherichia coli Recombinant E. coli cells expressing native full-length EsM1Pase1 and EsM1Pase2 were obtained as previously described  (Groisillier et al. , 2014). To improve expression in E. coli, gene coding for EsM1Pase1 (Esi0080_0016; UniProt accession number CBJ27643) was codon-optimized (GeneArt Gene Synthesis, Life Technologies, USA), amplified with the forward primer 5'-GGGGGGGGATCCGCGATGAAGCGGACCATACAGG-3' (BamHI site in italic) and the reverse primer 5'-CCCCCCGAATTCTTATTCCCACACCGTCTTCCTGTCC-3' (EcoRI site in italic), and cloned into the vector pFO4 to construct the plasmid pESM1Pase1opt. Sequence of this plasmid was verified by sequencing before transformation into in E. coli. Mannitol production in E. coli BL21 (DE3) cells transformed with plasmid containing full-length native EsM1Pase1, full-length E.
Acknowledgements TT was supported by The  Leverhulme Trust Research project  Grant  RPG-2015-102. The funder had no role in study design, data collection and interpretation, or the decision to submit the work for publication. This work has also benefited from the support of the project  IDEALG  ( ANR-10-BTBR-02 ) " Investissements d'Avenir, Biotechnologies-Bioressources ".
Effect of MV-induced oxidative stress on photosynthetic activity. To characterize oxidative stress damage by MV/light treatment in detail, we next investigated the effects of the treatment on the activities of overall electron transfer, including photosystem II (PSII) and photosystem I (PSI), activities. Overall electron transfer activity was evaluated by measuring the oxygen evolution reaction (OER) rate when CO 2 (NaHCO 3 ) was used as the sole electron acceptor. The ratio of the OER rate for cells incubated with MV versus that obtained for cells incubated without MV is shown in Fig. 3B  and indicates that the OER rate markedly decreased following the addition of MV in the dark condition and decreased even more in higher light intensity conditions. These patterns are consistent with normalized fluorescence data (Fig.
Acknowledgments. We thank  Prof. K. Terauchi  ( Ritsumeikan University ) and  Prof. T. Kondo  ( Nagoya University ) for kindly providing the mutant strains used in this work; and we thank  Prof. K. Tanaka  and  Mr. T. Tsurumaki  ( Tokyo Institute of Technology ) for providing a key suggestion regarding clock-controlled ROS tolerance through a presentation at the 59th Annual Meeting of the  Japanese Society of Plant Physiologists (Sapporo, Japan 2018 ). This work was partially supported by the  Advanced Low Carbon Technology Research and Development Program  ( JPMJAL1402 ) of the  Japan Science and Technology Agency (JST) ,  JSPS KAKENHI  ( 19K22232  and  18J20176 ), and a JSPS oversea research fellowship (201860126).
The method is described in Supplementary Materials (S1). Thermogravimetric analysis (TGA, TA Instrument model SDT Q 600) and atomic absorption spectroscopy (AAS, Perkin Elmer AA200 Atomic absorption spectrometer) measurements are carried out to determine the actual metal loading and composition of catalysts. TEM analyses are performed using a JEOL JEM 2100 (UHR) microscope with a resolution of 0. 19 nm. The Feret's diameters determined on circa 300 isolated nanoparticles (NPs) using the ImageJ free software  [28]  are considered for the statistics. X-ray Diffraction (XRD) patterns are acquired using a PANalytical Empyrean X-ray diffractometer and refined using the Fityk free software  [29]. More details for material characterization are available in Ref. [24]  and in Supplementary Materials (S2).
The ECSA of the bimetallic catalyst could be determined using the method developed by Łukaszewski and Czerwi ński  [42]. A value of 20 m 2 g metal -1 between that of Au/C and that of Pd/C is obtained, which agrees with particle and crystallite sizes determined by TEM and XRD, respectively. Main characterization data are listed in Table  1. The bimetallic Pd 3 Au 7 /C catalyst leads to lower onset potentials of sugar oxidation (circa +0. 100 V vs. RHE and circa+ 0. 150 V vs. RHE for glucose and xylose, respectively) and to higher activities from the sugar oxidation onset potentials to circa +0. 700 V vs. RHE as higher current densities are recorded over this potential range. Elsewhere  [24] , it has been proposed that the high catalytic activity at low potentials of the Pd 3 Au 7 /C catalyst was mainly due to the "ensemble effect"  [43] : the presence of gold at the surface of the catalytic nanoparticles leads to avoid or limit surface poisoning from dissociative adsorption of glucose or xylose into adsorbed CO species on palladium.
However, according to the CLiP database, this line also carried a second insertion (hereafter ins2) in gene Cre24. g755597. t1. 1, an insertion that was similarly confirmed by PCR analysis (Fig. S1B ). To remove the second mutation and to test whether the state transition phenotype co-segregated with the pph1 mutation, the mutant line (pph1;ins2) was back-crossed twice to the parental strain CC5155 (Fig. S1C ). From the first cross, 60 complete tetrads were analyzed for paromomycin resistance and for the presence of pph1 and ins2 insertions, both of which conferred paromomycin resistance. In 8 of these tetrads where the two insertions segregated (non-parental ditypes with four paromomycinresistant colonies pph1 / pph1 / ins2 / ins2), we found that altered state transitions correlated with the insertion in the pph1 gene (Fig.
Membranes were washed 4 times for 8 minutes with TBS-T and then incubated 1 hour at room temperature with horseradishperoxidase conjugated secondary antibody diluted in TBS-T with 5% (w/v) nonfat milk (or 3% (w/v) BSA in case of anti-Phospho Thr immunoblotting). Membranes were washed 4 times for 8 minutes with TBS-T and then revealed by enhanced chemiluminescence (ECL). The data are normalized on the PSII peak at 680 nm. D) State transitions monitored by PAM chlorophyll fluorescence spectroscopy at room temperature. Saturating light flashes were fired every four minutes and fluorescence was measured continuously (no actinic light was applied). Data were normalized on the first Fm' peak. The transition from St 1 to St 2 was induced by sealing the sample chamber to allow respiration to deplete oxygen and cause anoxic conditions, and then the transition from St 2 to St 1 was induced by bubbling air in the sample (at the time indicated with a black arrow).
ACKNOWLEDGMENTS This research was funded by the Marie Curie Initial Training Network project, AccliPhot (grant agreement number PITN-GA-2012-316427), the University of Geneva, the Institute of Genetics and Genomics of Geneva (iGE3), the Swiss National Science Foundation (SNF 31003A_146300), the European FP6 program (SOLAR-H Project STRP516510) and the Agence Nationale pour la Recherche (ChloroPaths : ANR-14-CE05-0041-01). M. C. was supported by a scholarship from the Ministry of Science and Education. We thank Jean-David Rochaix, Jean Alric, Bernard Genty and Gilles Peltier for scientific advice, Pascaline Auroy for technical assistance, Matteo Ballottari for the plasmids expressing LHCBMs, Francis-André Wollman for antiserum against PETO, Yuichiro Takahashi for antisera against CP29, CP26 and LHCBM5, and Nicolas Roggli for help with preparing the figures.
The first of the investigated methods were artificial neural network models which originate in the research carried out in the field of artificial intelligence. Research studies on the structure of the models of basic structures occurring in a brain had significant meaning for their development. These papers aimed mainly at the following characteristic features for biological nervous systems which will enable their practical use in technical issues. The ANN module available in Statistica 13 program was used for construction of the model. When searching for an optimal structure of the network, the number of neurons in the hidden layer was Energies 2020, 13, 5453 6 of 17 changed from 3 to 15. In the structure of the network, linear, logistic, tangential, exponential, and sinusoidal functions were used as a function activating the transitional and output layer.
Description of Research Methodology and Application Before the implementation of the main goal of the work, analyzes were carried out to establish a potential list of explanatory variables. During the research, a very extensive database was created, covering 380 buildings made of prefabricated panels for which energy audits were carried out. In particular, the energy consumption in the existing state before thermal modernization was calculated (Figure  2 ). Energies 2020, 13, x FOR PEER REVIEW 6 of 17 were repeated for three teaching network algorithms, i. e. , the fastest decrease method, the Broydena-Fletchera-Goldfarba-Shanno (BFGS) algorithm, and the conjugate gradient algorithm. The second group covered the regression trees models (CART, CHAID), boosted regression trees (SRT) and support vectors (SV).
Description of Research Methodology and Application Before the implementation of the main goal of the work, analyzes were carried out to establish a potential list of explanatory variables. During the research, a very extensive database was created, covering 380 buildings made of prefabricated panels for which energy audits were carried out. In particular, the energy consumption in the existing state before thermal modernization was calculated (Figure  2 ). For individual buildings the optimum thickness of the insulation layer of individual partitions has been assumed due to the shortest time of return on investment (Figure  3 ). The analyzed buildings are heated from the municipal heating network. Therefore, information was collected (based on thermal energy bills) on the actual consumption of heat for heating during the heating season (before and after thermal improvement).
The table does not show the characteristics of 7 independent variables informing which of the partitions was thermally upgraded. The information concerning heat transfer coefficients contained below refers to the condition before thermo modernization. The variables designated after the initial selection were used to create sets of input variables based on the suitability of alternative regression methods to estimate the energy consumption of the building after performing the thermomodernization procedures. These variables were used to develop 5 sets of input data characterized by varying degrees of impact on energy consumption and the difficulty of acquiring them. Individual sets of variables were created by the authors on the basis of statistical analyses performed so far. Independent variables were required to be statistically significantly correlated with the independent variable.
A similar group of input variables (4 sets) was used to check the suitability of a method using rough set theory (RST) to forecast energy consumption on a group of 109 buildings undergoing thermomodernization  [7]. After a possible list of independent variables was selected the developed data base was divided into the teaching set to which 75% of the investigated buildings and the test set formed from the remaining objects were randomly selected. For the construction of models which enable determination of the annual heat demand and modernization costs for residential apartment buildings, a working space Data Miner available in Statistica (StatSoft ® ) program was applied. A schematic view of the working space with particular blocks were presented in Figure  4. Atw-calculated from exterior measurements total windows area [m 2 ] ISO 12831-1:2017-08 Sets of variables (before thermomodernization) (Recorded in the form of 0-1 information whether the peak wall, external wall, floors, ground floors, windows and flat roof to be thermomodernized).
After a possible list of independent variables was selected the developed data base was divided into the teaching set to which 75% of the investigated buildings and the test set formed from the remaining objects were randomly selected. For the construction of models which enable determination of the annual heat demand and modernization costs for residential apartment buildings, a working space Data Miner available in Statistica (StatSoft ® ) program was applied. A schematic view of the working space with particular blocks were presented in Figure  4. Four areas may be distinguished in the working space presented in Figure  4. In the first one there is a data source used for construction of prognostic models. It includes 380 observations described by the selected 31 parameters. In present paper the artificial neural networks (ANN), general regression trees (CART), exhaustive regression trees (CHAID), support regression trees (SRT), support vectors (SV), and method MARS were selected.
• When assessing the quality of individual methods solely on the basis of the MAPE index (the index most frequently used for assessment) determined for the test set, it can be said that the best quality energy consumption forecasts after thermal rehabilitation were obtained by SRT and ANN methods, for which it was necessary to use the data from the V set as input variables. The error value was 12. 1% and 12. 5% respectively. Slightly worse quality forecasts, because they were burdened with a MAPE error of 14%, were obtained for the IV set of input variables and methods ANN, MARS, and SRT.
With the availability of high-frequency, i. e. , intraday data, research on modelling higher moments has taken new directions, and hence, we use 5-minute futures market data on gold and oil returns, which are then used to compute realized volatility, jumps, realized skewness and kurtosis, over the daily period of December 2, 1997 to May 26, 2017. We then analyze the causal relationship between these metrics for gold and oil markets, using linear, nonparametric and time-varying approaches, with the latter two methods providing robust inferences in the presence of nonlinearity and structural breaks between the variables of concern, which we show to exist based on statistical tests. In addition, we also rely on a moments-based test of causality, which allows us to test for spillovers of returns, variances and quantiles.
The Dataset We use intraday data on gold and West Texas Intermediate (WTI) oil futures that are traded at NYMEX over a 24 hour trading day (pit and electronic), to construct daily measures of returns (r), standard realized volatility (RV), volatility jumps (RJ), and realized skewness (RSK) and realized kurtosis (RKU). The futures price data, in continuous format, are obtained from www. disktrading. com and www. kibot. com. Close to expiration of a contract, the position is rolled over to the next available contract, provided that activity has increased. Daily returns are computed as the end of day (New York time) price difference (close to close). In the case of intraday returns, 5-minute prices are obtained via last-tick interpolation, and 5-minute returns are then computed by taking the log-differences of these prices, which in turn are used to compute the realized moments.
Our data covers the period of December 2, 1997 to May 26, 2017, i. e. , giving us a total of 5762 observations. Figure  A1  in the Appendix plots the various metrics for gold and oil, while Table  A1  summarizes the basic statistics for r, RV, RJ, RSK and RKU of both gold and oil markets. As can be seen from Table  A1 , both gold and oil are negatively skewed and have excess kurtosis, which results in non-normal distributions as indicated by the overwhelming rejection of the null of normality under the Jarque-Bera test. Oil is also found to be more volatile than gold, though the mean returns are similar across the two markets. Further, as seen from Figure  A1 , RV, RJ, RSK and RKU are non-constant, with their magnitudes evolving over time, and hence, provides an initial motivation to analyze the causal relationship between these metrics across the gold and oil markets.
For our dataset, the estimated ARCH parameter for return on gold is 0. 2213, giving the optimal bandwidth 0. 8633; and the estimated ARCH parameter for return on oil is 0. 2142, giving the optimal bandwidth 0. 8815. Therefore, we choose 0. 87 which is close to the optimal bandwidth of returns of both gold and oil. [ INSERT TABLE 2 HERE] shows the p-values of test developed by  Diks and Panchenko (2006)  in both directions, for lags ranging from 1 to 10. For the returns, we can find evidence of causality from gold to oil at lags 4 and 5, but not verse visa. In terms of the RV, we cannot find evidence of causality in most lags. The only evidence of causality can be found from oil to gold at lag 5. Regarding RJ, RSK and RKU, we can find strong evidence of bidirectional causality between gold and oil for all lags.
Concluding Remarks In this paper, we analyze the causal relationship between not only returns and overall variance of gold and oil markets, but also volatility jumps, skewness and kurtosis. In this regard, we use 7 In Table  A5  in the Appendix of the paper, we report the results from the out-of-sample version of Chen's (2016) test, with a spilt of 70% of the data as in-sample and the remaining 30% as the out-ofsample, as in the original paper. As can be seen from Table  A5 , our results are qualitatively similar, with the main conclusion still holding over the out-of-sample period of January 2, 2012 to May 26, 2017. 5-minute futures market data on gold and oil returns, which are then used to compute realized volatility, jumps, realized skewness and kurtosis, over the daily period of December 2, 1997 to May 26, 2017.
Powder X-ray Diffraction Powder X-ray diffraction data were collected on a Siemens D5000 X-ray diffractometer (Bruker, Palaiseau, France) in a Bragg-Brentano configuration with a Cu Kα radiation source. Scans were run over the angular domains 10 • < 2θ < 80 • with a step size of 0. 02 • and a counting time of 2 s/step. Crystalline phases were identified by comparing the experimental diffraction patterns to Joint Committee on Powder Diffraction Standards (JCPDS) files for anatase. The treatment of the diffractograms was performed using the FullProf software  [47]  and its graphical interface WinPlotr  [48]. The average crystallite size D was calculated from the Scherrer formula, D = Kλ/(β cos θ), where K is the shape factor (a value of 0. 9 was used in this study, considering that the particles are spherical), λ is the X-ray radiation wavelength (1.
Transmission Electron Microscopy (TEM) Transmission Electron Microscopy (TEM) bright field observations were performed on a Tecnai G2 microscope (FEI, Hillsboro, Oregon, USA) operating at an accelerating voltage of 200 kV. The Au/TiO 2 powder was deposited directly on a carbon coated copper grid. Metal particle size distributions have been determined from the measurement of about 200 Au NPs. The nanoparticles were found in arbitrarily chosen area of the images using the program ImageJ software.
Acknowledgments: The  TEM facility in Lille (France)  is supported by the  Conseil Régional du Nord Pas de Calais  and the  European Regional Development Fund (ERF). Chevreul Institute  ( FR 2638 ),  Ministère de l'Enseignement Supérieur, de la Recherche et de l'Innovation ,  Région Hauts-de-France  and  FEDER  are acknowledged for supporting and funding partially this work. The authors are grateful to the  University of Artois  for supporting this research through the  Quality Research Bonus (Micro-GC Agilent 490  in 2018).
qE was measured using the NPQ_1 program (2 min at 1000 µmol photons m -2 s -1 ) and calculated with (F o -F m ')/F m ', with F m ' measured during actinic light. For measuring chlorophyll fluorescence of agar-grown cultures, a CCD camera (FluorCam 701MF, Photon System Instruments) was used. F m was measured with a 600 ms saturating pulse of 2300 µmol photons m -2 s -1. For measuring qE, actinic light was provided by two red LED panels, providing 200 µmol photons m -2 s -1 and measured after 2 min light treatment. The redox state of PSI was measured by near infra-red absorption with a Dual-PAM-100 (Heinz Walz, Effeltrich, Germany) according to the method of  Klughammer and Schreiber (1994). The maximum P700 change from the dark-adapted to fully oxidized level (P700 + ) obtained 20 ms after a saturating light pulse was calculated manually in Excel after exporting raw data as the difference between 0-5 ms before and 19-21 ms after starting the saturating pulse.
Analysis of LHCSR3, LHCSR1, PsbS, PsaA, and PsbA protein levels Proteins were extracted from the same cells, or pool of cells, and noninvasively measured (e. g. chlorophyll fluorescence) for data that are shown within the same figure, or related supplementary figure. Total cellular proteins were either extracted in 2% SDS, in 50 mM Tris-HCl, pH 6. 8 (for agar-grown cultures), or in 7 M urea, 2 M thiourea, 20 mM Tris-HCl with 0. 2% (v/v) Triton X-100 (for liquid cultures), in both cases with protease inhibitor cocktail (Complete Mini, Roche Diagnostics, Switzerland), with protein quantification via the bicinchoninic acid or Bradford assay, for the two extraction methods, respectively. Before loading, proteins were denaturated at 85 °C with 0. 1 M DTT and separated by PAGE using 12% acrylamide gels at 40 mA in Tris-glycine-SDS running buffer.
Acknowledgements We thank  Stefano Caffari  ( Aix-Marseille Université, France ) for providing the PsbS antibody, and  Theresa Baur  and  Chantal Kruckenhauser  for helping with LC-MS/MS measurements of RES. Travel support from The  Bundesministerium für Bildung, Wissenschaft und Forschung  ( FR09/2018 ) is gratefully acknowledged.
The pump pulses were typically set to 0. 5 µJ per pulse. To achieve the pump-probe delay of 2 ns, the pump beam was directed over a delay line. The supercontinuum used as probe pulse was generated by passing the second beam of the fundamental 800 nm through a CaF 2 window, with probe intensities falling into the range of hundred nJ. The probe light was split into two beams, one of which was focused through the sample, while the other served as reference. The probe and reference beams were detected by a double-stripe diode array and converted into differential absorption signals using a commercially available detection system (Pascher Instruments AB, Lund Sweden). The recorded data were corrected for the chirp and globally fitted using a sum of three exponential. During the fitting, the pulse overlap region of ±200 fs was excluded to avoid contributions from coherent artefacts  [52].
Funding: This research was supported by the  European Commission 's  Seventh Framework Program  ( FP7/2007-2013)  under grant agreement n  • 306398  ( FP7-IDEAS-ERC , Project PhotocatH 2 ode), the  French National Research Agency  in the framework of the " Investissements d'avenir" program  ( ANR-15-IDEX-02 ,  Labex ARCANE  and  CBH-EURGS ,  ANR-17-EURE-0003 ) and the  Franco-German University.
• helping dispatch operators to propose the cheapest and safest electric mix according to user's consumption and energy availability. • limiting financial risks for electricity distributor buying (respectively, producer selling) PV power on the electricity market. • designing optimal rules for the management of micro-grids including at least a PV system and a battery storage. In particular, intraday horizon forecasts (typically up to 6 h) are required more and more for the grid power reserve management, the increase in intra-day auctions in the electricity market  [6]  and the current worldwide development of micro-grids. Forecasting the surface solar irradiance enables us to forecast PV production using proven models converting GHI into PV power production  [7, 8]. It does not require any PV power historical dataset.