dataesr/scientific-paragraphs-categorization huggingface dataset:
Among diatom-specific families, a single CYP5021 exists in all the three diatoms. CYP5022 and CYP5023 exist in T. pseudonana and F. cylindrus, while CYP5165 exists in P. tricornutum and F. cylindrus. In order to examine whether these families are indeed lineage-specific, we explored the transcriptomic database MMETSP  (Keeling et al. 2014 ) and 1KP (https://db. cngb. org/onekp) to see the CYP distribution in related species. In close stramenopile relatives (Bolidomonas pacifica (?) close to diatoms and Vaucheria litorea (?) close to brown algae), identified CYP did not cluster with any lineage-specific CYPs (Fig. S2 ). Performing BLAST against 1KP database further supported that the brown algae-specific CYP families were only found in brown algae, CYP5023 was not found in the database, whereas diatoms' CYP5021, CYP5022 and CYP5165 were also found in other lineages, such as Haptophytes, suggesting they are not restricted to diatoms (Table  S2 ).
P450 evolutionary dynamics in brown algae and diatoms Based on naming and classification of families and subfamilies, further dynamics study was performed to assess the P450 evolutionary history within photosynthetic stramenopiles ochrophytes. Using the Dollo parsimony principle  (Farris 1977; Almeida et al. 2016) , combined with the results from 1KP transcriptome database, we estimated the P450 families that were gained or lost at each node of the algae tree(Fig. 3 ). In the common ancestor of brown algae and diatoms, there were six P450 families, including CYP51, CYP97, CYP5160, CYP5021, CYP5022, and CYP5165. Then, three families, that is, CYP5021, CYP5022, and CYP5165 were lost in brown algae. CYP5161, CYP5162, and CYP5164 were acquired in the ancestor of brown algae, followed by acquisition of CYP5163 in the ancestor of E.
Transcriptome analysis and evolution of two critical steps in the oxylipin synthesis pathway among stramenopiles We used publicly available microarray datasets from E. siliculosus  (Dittami et al. 2009; Ritter et al. 2014) , diatoms  (Ashworth et al. 2016 ) and our RNA-seq datasets of the three life stages o f S. japonica including sporophytes, male gametophytes and female gametophytes to investigate the expression profiles of P450 genes. Among the fifteen P450s of S. japonica, four genes were not expressed in all the three life stages, two of which are truncated pseudogenes (Fig. 5a ). The other two (CYP5161C3 and CYP5164B3) may have become pseudogenes after duplication or evolved new function not identified in our study, such as expression induced by herbivore grazing, as it may occur with other kelps  (Ritter et al.
The branches are colored to show their different taxonomic groups of oomycetes, brown algae, diatoms and N. gaditana, respectively. The number on the tree node means bootstrap (1000 replicates) values above 50%. Each of the color frame represents a synthetic pathway in one lineage. This is a single-species lineage for A. thaliana and E. siliculosus, whereas genomic and metabolomic data are pooled for two species from the same genus for Saccharina and Thalassiosiria. The peroxidation step in orange is always carried out by a LOX enzyme, wherease the hydroperoxilyase activity (in purple) can be carried out either by a P450 (Arabidopsis and the two brown algae) or by an enzyme from a different family in Thalassiosiria (blue frame). S1  Statistics of P450 number in each species. Table  S2  Results of BLAST against 1KP transcriptome database using CYPs only occurring in brown algae (CYP5161, CYP5162, CYP5163 and CYP5164) and CYPs only occurring in diatoms (CYP5021, CYP5022 and CYP5165) Table  S3  CYP list, showing the CYP name, protein length, subcellular location, and transmembrane helix number (TH).
j a p o n i c a w e r e d o w n l o a d e d f r o m N C B I https://www. ncbi. nlm. nih. gov/. Sequences of F. cylindrus were downloaded from JGI https://genome. jgi. doe. gov/portal (Grigoriev et al. 2014). Sequences of P. tricornutum, T. pseudonana, a n d N. gaditana w e r e d o w n l o a d e d f r o m E N S E M B L http://protists. ensembl. org/info/website/ftp/index. html (Kersey et al. 2018). Besides, the publicly available P450 sequences from two oomycetes Phytophthora sojae and Phytophthora ramorum, and other species (CYP51 and CYP97 from animal, plants, fungi, b a c t e r i a ) w e r e r e t r i e v e d f r o m t h e P 4 5 0 h o m e p a g e http://drnelson. uthsc. edu/CytochromeP450. html ( N e l s o n 2 0 0 9 ). A d d r e f h e r e t o transcriptomic datasets.
Results of BLAST against 1KP transcriptome database (https://db. cngb. org/onekp)usingCYPsonly occurring in brown algae (CYP5161, CYP5162, CYP5163 and CYP5164) and CYPs only occurring in diatoms (CYP5021, CYP5022, CYP5023 and CYP5165). TableS3CYP list, showing the CYP name, protein length, subcellular location, and transmembrane helix number (TH).
Acknowledgements This work was supported by  Central Public-interest Scientific Institution Basal Research Fund CAFS  ( 2017HY-YJ01 );  National key Research and Development Plan  ( 2016YFC1402102-2 );  National Natural Science Foundation of China (41676145) ;  Shandong key Research and Development Plan ;  Qingdao Municipal Science and Technology plan project  ( 17-1-1-96-jch );  Special Scientific Research Funds for Central Non-Profit Institutes ,  Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences  ( 20603022016010 ,  20603022016001 );  China Agriculture Research System  ( CARS-50 ); Taishan Scholars Funding;  AoShan Talents Program  (No. 2015ASTPES03 ); the  Science Fund for Distinguished Young Scholars of Shandong Province  ( JQ201509 ); and  Projects of International Exchange and Cooperation in Agriculture, Ministry of Agriculture and Rural Affairs of China-Science, Technology and Innovation Cooperation in Aquaculture with Tropical Countries along the Belt and Road.
Suggesting that the equity market premium is partially driven by the comovement of agents' marginal utility and the price process for stocks in times of disaster (i. e. jump risk),  Wachter (2013)  shows mathematically that timevarying disaster risk contributes to the equity premium in the form of compensation for jump risk. Given this perspective, one can argue that time-varying rare disaster risks also contribute to the presence of jumps in oil excess returns in the form of a compensation for consumption shocks such that an increase in the risk of rare disasters increases return and volatility in the oil market. To that end, the analysis can provide insight to the effect of oil price shocks on stock market returns and volatility from a novel angle. The goal of this paper is to examine the predictive power of rare disaster-risks for the return and volatility dynamics of West Texas Intermediate (WTI) oil prices using a long span of historical data over the period 1918:01-2013:12.
Data The empirical analysis utilizes monthly data for WTI oil prices and the dummy variables capturing various types of disaster risks over the period of 1918:01 to 2013:12. The start and end dates are governed purely by the availability of data on disaster risks. Oil price data is sourced from the Global Financial Database, with returns computed as the monthly logarithmic change of oil prices multiplied by 100 to convert the returns into percentages. Since WTI oil price data is available from 1859:09, we do not lose the first observation while computing oil returns. Figures  1(a ) and 1(b) present the plot of monthly oil returns and the histogram of the series along with the summary statistics, respectively. We observe that the oil return data is skewed to the left with excess kurtosis, resulting in the null of normality under the Jarque-Bera test being overwhelmingly rejected at the highest level of significance.
[Insert Figure 1] Next we turn our attention to our measure of disaster risks of rare events as obtained from the International Crisis Behavior (ICB) database. ICB database started in 1975 and covers comprehensive information regarding 464 international political crises that occurred during the period of 1918 to 2013 at monthly frequency, involving 1,036 crisis actors. Brecher and Wilkenfeld (1997)  provide detail discussion on the ICB database, definition and construction of variables. The ICB data has been used in series of books and empirical research papers in many disciplines, including economics, war and political sciences (see for example,  Blomberg, et al. , (2004) ;  Berkman, et al. , (2011 Berkman, et al. , ( , 2017)) ;  Huang et al. , (2015) ) 1. The underlying motive of the ICB database is to develop a comprehensive list of international political crisis since World War I.
As per the ICB database, the breakpoint of a crisis is an event, act or changes characterized by following three conditions: (a) a threat to basic value, (b) excessive chances of involvement in military hostilities, and (c) time pressure for response. ICB database covers a wide range of alternatives to measure the severity of any crisis and, consequently gives us more information to identify the seriousness of the crisis. Note that, to the best of our knowledge, the ICB database is the only available source that compiles data on all major international international political crises, which are likely to cause changes in perceived rare disaster probabilities. The ICB database distinguishes each crisis on the basis of 81 dimensions including the control variables and crisis mediation, with the possibility of tracing the background of each crisis in detail from the website of ICB database.
Further, the ICB database considers those crises only in which the crisis actor is a sovereign entity and has significant participation in any of political conflict. As indicated above, the ICB database covers comprehensive dimensions of each crisis and we take into account many of these dimensions, following  Berkman, et al. , (2011 Berkman, et al. , ( , 2017)) , to analyze the impact of international political risk on oil returns and volatility. The foremost variable of our study is total number of crisis (Crisis) in any month t. Some crisis can be more severe than others, therefore it is expected that more devastating crisis may have stronger effect. Following the  Berkman, et al. , (2011 Berkman, et al. , ( , 2017)) , we created the following crisis variables: (1) violent break (Violent Break) includes all the crisis that starts with violent act, (2) violent (Violent) crisis includes all the crisis that comprises either serious clashes or full scale war, (3) war (War) includes all the crisis that involves full-scale wars, (4) all crisis that involves grave value threats (Grave Threat), (5) protracted conflicts (Protracted) includes all the crisis with protracted conflict, protracted and crisis outside this conflict, and (6) major power (Major Power) includes the crisis only if at least one superpower or great power is there in both side of conflict.
[Insert Table 4] As explained earlier in the data description, the findings reported in Tables  3  and 4  utilize dummy variables that represent various definitions of rare disaster risks. In addition to these dummy variables, the ICB dataset also provides the monthly count for the risk variables under the various categories as well as information on their start and end dates, i. e. the span of the crisis. Therefore, as a robustness check, we repeat our analysis using the monthly counts for various risk categories instead. The findings in Table  5  further confirm our previous results in Table  3  that are based on the crisis dummy variables, indicating strong evidence of predictability for both oil returns and volatility over the entirety of the respective conditional distributions. The causal effects from rare disaster risks are found to be significant irrespective of what phase the month is classified as, i.
[Insert Table 5] As additional robustness checks, we also used the news-based measures of implied volatility (NVIX) as developed by  Manela and Moreira (2017)  3 and geopolitical risks (GPRs) of  Caldara and Iacoviello (2017)  4 , as possible alternative measures of rare disaster risks. The NVIX and the GPRs indexes also contain information about possible disaster risks (see, Footnotes 3 and 4 respectively in this regard) and hence, serves as an alternative to the ICB database. The NVIX and the GPRs are used to check for the robustness of our results obtained using the ICB database, which in turn, is popularly used for capturing rare disaster risks in the associated literature. Even though the NVIX and GPR indexes are based on news on various types of risks in the US newspapers, they do cover global disaster news as well and hence, is likely to be important for a global market like oil.
Also note, since we are analyzing the WTI market, US-based risks should also matter, besides global disaster risks, which the ICB aims to capture. 3 The news dataset to construct the NVIX includes the title and abstract of all front-page articles of the Wall Street Journal. Manela and Moreira (2017)  focus on front-page titles and abstracts in order to ensure feasibility of data collection, and also because these are manually edited and corrected following optical character recognition, which in turn, improves their earlier sample reliability. The NVIX data is found to peak during stock market crashes, times of policy-related uncertainty, world wars, and financial crises. The reader is referred to  Manela and Moreira (2017)  for further details, who also discuss how they decompose the aggregate NVIX into its components.
The NVIX components capture uncertainty stemming from (with the words searched for in brackets) government policy (tax, money, rates, government, plan), intermediation (banks, financial, business, bank, credit), natural disaster (fire, storm, aids, happening, shock), securities markets/stock markets (stock, market, stocks, industry, markets), and wars (war, military, action,world war, violence). There is also available data for an "unclassified" component (U. S. , special, Washington, treasury, gold). The data is available for download from: http://apps. olin. wustl. edu/faculty/manela/data. html. 4 Caladara and Iacoviello (2017) construct a long-span monthly GPR index dating back to 1899, based on terms related to geopolitical risks covered in three newspapers namely, the New York Times, Chicago Tribune, and the Washington Post.
Conclusion This paper extends the literature on the effect of rare disaster risks on financial market returns to the commodity market, in particular crude oil. Unlike other applications to stock and bond returns, we provide a novel perspective to the predictive ability of rare disaster risks for returns and volatility in the WTI oil market using a k-th order nonparametric quantile-based methodology that allows to capture nonlinear causal effects. Using monthly data on oil returns and various disaster risk proxies for the period of 1918:01 to 2013:12, we first show that standard linear causality tests yield insignificant results in terms of the predictive power of rare disasters over WTI returns. However, additional tests reveal strong evidence of nonlinearity and regime changes in the relationship between oil returns and the rare disaster risk proxies, indicating that the linear Granger causality test is misspecified, thus the results cannot be relied on.
Acknowledgements This work is supported by  Shandong Province Natural Science Foundation  (No. ZR2016BB15 ),  The Youth Science Fund of Shandong Academy of Sciences  (No. 2016QN006 ),  National Natural Science Foundation of China  (no. 61377068 , no. 61361166004 ),  Research Grants Council of Hong Kong  ( N_PolyU505/13 ,  PolyU 5334/12E ,  PolyU   152184/15E ,  PolyU 509513  and  PolyU 152127/17E ), and  Hong Kong Polytechnic University  (grants G-YN07,  G-YBBE ,  G-YBPR , 4-BCAL, 1-ZVAW,  1-ZE14 ,  A-PM21 ,  1-ZE27  and  1-ZVGH ).
2 μm, Whatman) to separate the catalyst powder from the liquid aliquot that was subsequently examined with EPR. X-ray absorption spectroscopy (XAS) at the Fe K-edge was measured in transmission mode at Pohang Accelerator Laboratory (7D-XAFS beamline). A mass of 0. 1 g catalyst was mounted in a sample holder (w×l×d=3×8×2 mm 3 ). The XAS energy scale was calibrated using a Fe foil before and after the measurement to verify the lack of or correct for any energy shift during data acquisition. For extended X-ray absorption fine structure (EXAFS) analysis, Artemis implemented in Demeter program package (0. 9. 23) was utilized after the data processing in Athena 2. EXAFS amplitudes and phase shifts were calculated by FEFF7. The many body attenuation factor (S0 2 ) was determined as 0. 82 from the fit of the EXAFS of reference materials.
The presence of iron and nitrogen was confirmed with Gatan Quantum ER dual Electron Energy-loss Spectroscopy (EELS) system. X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS) data acquisition were carried out using a Sigma Probe (Thermo VG Scientific) equipped with a microfocused monochromator X-ray source. The XPS data were analysed using the XPSPEAK41 software with ±0. 1 eV deviation in binding energy. The binding energies used for deconvoluting the XPS-N1s spectra were 398. 5 eV for pyridinic-N, 400. 1 eV for pyrrolic-N, 401. 1 eV for graphitic-N and 403. 7 eV for pyridinic-oxide, respectively  4. The binding energies used for deconvoluting the XPS-O1s spectra were 531. 2 eV for C=O and 533. 0 eV for C-O, respectively  5, 6. UPS data were analysed with He I radiation.
Electrochemical reduction of H2O2-treated FeNC-1 and FeNC-0. 5. Electrochemical reduction of the carbon surface on FeNC-1-20, -50 and -70 and FeNC-0. 5-70 was carried out by cyclic voltammetry (CV) in an Ar-saturated 0. 5 M NaCl electrolyte, a method similar to that employed for electrochemical reduction of graphene oxide to graphene  9, 10. 100 cycles were progressed between 0 and -1. 6 VAg/AgCl with a scan rate of 100 mV s -1. The lower potential limit was selected to avoid significant hydrogen evolution at even lower potential, leading to active-layer detachment. Computational methods. We performed first-principle DFT calculations coupled with the Poisson-Boltzmann (PB) implicit solvation effect on models for active sites with different environments as shown in Fig. S7a. We used the Vienna Ab-initio Simulation Package (VASP) 11 , with the exchange-correlation function of revised Perdew-Burke-Ernzerhof (RPBE)  12.
The electron-ion interaction was considered in the form of the projector-augmentedwave (PAW) method with a plane wave up to energy of 600 eV. The active site models combined with a 20 Å vacuum layer along the z-axis were fully minimized under a gamma centered k-point grid of (4×4×1). A dipole correction was applied to all calculation cases to avoid unwanted electrostatic interaction between periodic images along the z-direction. To calculate the solvation energy, the PB implicit solvation model, which is implemented in the VASP program  13  , was used under a dielectric constant ε = 80 for water (we neglect the cavitation energy contribution). We also calculated the vibrational internal energy and entropy terms for adsorbate molecules by taking account partial Hessian analysis. The partial density of states (PDOS) data was calculated with the conditions of tetrahedron method with Blöchl corrections and manipulated with p4vasp software.
Acknowledgements The research leading to these results was supported by  ANR  under contract  2011 CHEX 004 01 , by  Creative Materials Discovery Program  through the  National Research Foundation of Korea (NRF)  funded by  Ministry of Science and ICT  ( NRF-2017M3D1A1039376 ) and by the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement CREATE No. 721065. C. H. C. acknowledges the support by the  National Research Foundation of Korea (NRF)  grant funded by the  Korea government (MSIP)  ( NRF-2017R1C1B2002918 ). P. S. acknowledges support by the  European Commission ,  H2020 ,  Fuel Cell Hydrogen Joint Undertaking  ( FCH-JU 2 ) programs.
Microscopy Brightfield and fluorescence images were obtained using an Axioimager M2 fitted with Axiocam HRc Camera (Carl Zeiss Microscopy, Marly le Roi, France). Fluorescence was visualized with HBO 100 mercury lamp and Plan-Apochromat 63×/1. 40 Oil objective (Zeiss). Images were captured with AxioVision Rel 4. 8 software. For fluorescence visualization, the filters were as follows: chlorophyll, excitation BP560/55, and emission BP645/75; AC-202, excitation BP365/50, and emission BP450/65; BODIPY, excitation BP470/40, and emission BP540/50. For quantification of fluorescence, cells were analyzed using an Apotome Z1 fitted with Axiocam MRM Camera (Zeiss). Fluorescence was visualized with HBO 100 mercury lamp Plan-Apochromat 63×/1. 40 Oil objective (Zeiss). Images were captured using Zen 2012 Software.
Model Overview Simplified models of the absorber tube and cavity were developed in order to supplement experimental results by predicting temperatures where measurements are not taken, such as particle temperature within the tube and tube temperature at various heights. The models were developed in MATLAB, and have varying degrees of complexity, in terms of discretization and the comprehensiveness of the heat transfer modeling. All models have a symmetry condition relative to the north-south vertical plan, and 20 discrete slices from top to bottom (over 1m for slice heights of 5 cm). The geometry is detailed in Fig. 2.
This indicates that the heat transfer from wall to DPS is conditioned by the particle exchange between the annulus and the core. Simplified models that consider a plug-flow were developed in MATLAB. The Monte Carlo ray-tracing method was used to determine the distribution factors in the receiver cavity. A 2D and 3D model, neglecting or not the vertical heat transfer were coded. Two meshes were tried. Using a refined or coarse mesh leads to differences much greater than between the 2D and 3D models. Therefore working with the 2D model and a refined mesh is a good option for a simple use combined with a good precision. For further improvement of the model, the mesh will have to be even more refined. The plug-flow simplification renders the model unable to predict accurately the tube temperature because it does not consider the DPS temperature close to the wall, while it is with the particles at this temperature that the wall exchanges heat.
ACKNOWLEDGMENTS This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under two grants agreements No 654663 and No 727762 projects acronym SOLPART and Next  CSP , respectively. The facility was supported by the  French "Investments  for the future" program managed by the  National Agency for Research  under contracts  ANR-10-EQPX-49  (SOCRATE).
The ettringite system based on sulfoaluminate binder (CSA clinker and anhydrite) was aerated by addition of aluminum powder and calcium hydroxide (Ca(OH) 2 ), the reaction of the latter (foaming process) releasing hydrogen gas which increased the volume of the paste and generated porosity  [53, 54]  (Figure  8 ). The heat storage capacity of this improved material was tested using the closed loop heat storage prototype under nitrogen gas. A model based on the energy and mass balance in the cementitious material was developed and simulated in MatLab software, and was able to predict the spatiotemporal behavior of the storage system  [55]. This enabled a first thermochemical reactor prototype to be built for heat storage tests in both the charging and discharging phases. This first reactor was a cylindrical adsorber (d = 11 cm, l = 13 cm) equipped with an axial copper pipe (d = 1 cm)  [55].
Epifluorescence and confocal microscopy Cells grown on glass coverslips were incubated with 25 nM mitochondrial selective probe MitoTracker 1 Red CMXRos (Invitrogen) for 30 min and fixed in 10% formalin solution (Sigma-Aldrich) for 10 min at 37˚C. Nuclei were stained with Hoechst 33342 (1 μg/mL) for 5 min. Coverslips were mounted in a Citifluor AF2 solution (Biovalley) and cells were examined by epifluorescence under a Nikon confocal microscope. Image treatment was done using Nikon EZ-C1 software.