dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments This research was carried out under Project Number  ENPPS. IPP. 019. 002  in the framework of the  Research Program  of the  Materials innovation institute (M2i ) (www. m2i. nl) and received funding from  Tata Steel Nederland Technology BV  and the  Dutch Research Council (NWO)  in the framework of the  ENW PPP Fund  for the top sectors and from the  Ministry of Economic Affairs  in the framework of the ' PPS-Toeslagregeling '. Acknowledgments L S acknowledges her  Imperial College Research Fellowship  in the Department of Materials and would like to thank  Mr Benjamin T Bowers  and  Dr Soren Scott  for their useful comments on this article. Acknowledgments R B thanks the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (Grant Agreement No.
Acknowledgments Bipolar membrane work at the  University of Oregon  was funded by the  Office of Naval Research  Award No. N00014-20-1-2517 , as well as by the  US Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE)  under the  Fuel Cell Technologies Office (FCTO)  Award No. DE-EE0008841. Work on CO 2 utilization was funded by the  Liquid Sunlight Alliance  under Award No. DE-SC0021266.
In situ sky cameras equipped with fish-eye lenses are able to capture the surrounding sky with a high spatial resolution (see Figure  1 ). From a sequence of sky images, cloud tracking techniques provide a tool for the mod-elling of the cloud cover dynamics used to anticipate incoming clouds  [44]. Furthermore, one can generalise this local prediction to a wider neighbouring area by estimating the cloud induced shadow map and its resulting irradiance map. This can be done using multiple camera observations to produce a 3D model of the cloud cover relative to the ground  [4, 42]. In recent years, increased availability of open source datasets  [41]  and virtual datasets  [26]  have fostered interest in data-driven approaches, which have been shown to outperform traditional methods in many computer vision tasks  [17, 46, 56].
Dataset Sky Images This publicly available dataset was generated at SIRTA's lab over 3 years (2017 to 2019)  [14]. Images of the sky were taken from the ground with an EKO SRF-02 all-sky camera. Each sample comprises two shots taken with different exposition time: 1/100 sec (long exposure) and 1/2000 sec (short exposure) (Figure  1 ). The short exposure provides more details in the circumsolar area (region close to the sun), whereas the long exposure focuses more on the surrounding sky. From the initial 768 × 1024 pixel resolution, sky images are cropped and downscaled to a 128 × 128 pixel resolution as suggested in  [50]. Images are segmented following the methodology detailed below and illustrated in Figure  3. Undistortion Images taken by hemispherical cameras are affected by a strong distortion (Figure  1 ).
Metrics Forecast Skill In solar energy, the traditional approach to assess a forecasting model is to evaluate its performance relative to a reference model. The most common baseline model is the smart persistence model (SPM). The persistence model, which predicts unchanged future irradiance levels over a forecast window ∆T : ŷ(t + ∆T ) = y(t), is adjusted to take into account diurnal changes of the extraterrestrial irradiance (Equation  6 ). The clear sky index k c used to model this variability is based on the clear sky irradiance y clr provided by HelioClim  [3]. ŷ(t + ∆T ) = k c (t) y clr (t + ∆T ) with k c (t) = y(t) y clr (t) (6) For a given metric error, the Forecast Skill (FS) is computed as presented in Equation  7. The generalisation properties of this metric are used to compare model performances between different datasets and different site locations  [58].
For a given alignment, the TDI is defined by the fraction of the corresponding distortion relative to the maximum theoretical distortion. Given the type of temporal distortion observed (late or ahead), this indicator can be further decomposed into two components, in advance (TDI adv ) and late (TDI late )  [52]. TDI = TDI adv + TDI late (8) 95% Quantile. The short horizon of the forecast lead to an unbalance of the dataset towards low changes. Thus, indicators such as the FS based on the averaged errors (RMSE, Mean Absolute Error, etc. ) provide little information on the model's ability to predict rare but critical large errors. To evaluate this aspect of the forecasts, we report the 95% quantile error based on the sorted list of mean absolute errors.
Model Training The dataset used in the study comprises three years. The first two years (2017 and 2018) compose the training set (180,000 samples). The validation set is composed of 30,000 samples from even day numbers of each month from 2019 (day 2, 4, 6, etc. ). The model is tested on 30,000 samples from the remaining odd days from 2019. The TDI metric is evaluated on 200 sequences of 100 consecutive samples (3h20 each) randomly sampled from these test days. The results reported in this paper are averaged over two trainings with different random initialisations.
Results We compare ECLIPSE with three DL architectures on the 2, 4, 6, 8 and 10-min ahead predictions: ConvL-STM  [37] , TimeSFormer  [2]  and PhyDNet  [28]. TimeS-Former is a convolution-free DL model relying solely on attention mechanisms to extract spatiotemporal features directly from a sequence of frame-level patches. PhyDNet makes predictions constrained by partial differential equations in the latent space. This aims at leveraging physical phenomena such as the cloud cover dynamics, which can be described by advection-diffusion equations. All models take the same input data (RGB sky images) and forecast future irradiance levels. In addition, ECLIPSE and PhyDNet predict the corresponding future segmentations.
[47]. Given this distinction, the model we propose focuses on the simulation of the contractual layer, which can be applied to any organization of the physical layer. We call a collective organization of energy exchange a situation where a central entity (e. g. , a marketplace) is responsible for contractual energy exchanges. We call an individ-ualized organization of energy exchange a situation where households exchange energy directly, without the intermediary of a central entity. Current CSC experiments usually use a collective organization of energy exchange  [34]. Our contribution, presented in this article, is a multi-agent multi-level model that can be used to study different ways to organize the contractual layer of exchange in a group of CSC households. This model is built upon the SMACH multi-agent platform of human activity and therefore consider human activity to compute the energy consumption of the households which is a key data to perform energy exchanges.
Moreover, for each inhabitant of each household, the generator provides a provisional daily and weekly schedule containing a list of tasks that an individual tries to perform. For this purpose, SMACH uses data from the Time Uses Surveys (TUS), carried out in France between 2009 and 2010  [40]. These surveys consist in 27,000 notebooks, on which the 18,500 participants wrote their current activity every 10 min over a complete week and weekend day. From these TUS notebooks, SMACH builds a provisional schedule consistent with the profile of each inhabitant of the household. All these elements form a static description of the daily life of a household. However, the provisional schedule alone is not enough to forecast the activities of each simulated individual: these will be decided by the individuals themselves during the multi-agent simulation.
In fact, residents could choose to adapt their activities to skew the use of certain electrical devices such as the washing machine to be in line with the availability of renewable energy. We started to work on this question by developing a skewing strategy in SMACH, but we still need to validate these simulated decision-making processes with field data in real CSC campaigns. Likewise, we are starting to set up policies for the use of storage systems in SMACH, for example with strategies for charging or discharging energy depending on the price of electricity in the group. The impact of energy exchange between households and associations on the energy policy of the association itself must also be considered. An association is a legal entity that will take decisions, for example on the way the collective means of production or storage are used within the association.
The intrinsic activity of the material was investigated by calculating the conversion frequency (TOF) and mass activity at 0. 75 V (vs. RHE). As depicted in Figure  2d , JUC-616 has a TOF of 0. 00623 s -1 , larger than JUC-617 (0. 00493 s -1 ) and JUC-618 (0. 00296 s -1 ), which promotes the adsorption and desorption of O2 and products on the catalyst surface. [27] Additionally, the mass activity of JUC-616 was 3. 98 A g -1 , while the mass activities of JUC-617 and JUC-618 were 3. 15 A g -1 and 2. 13 A g -1 , respectively (Figure  2d ). These obtained results demonstrate unambiguously that Se-doped JUC-616 shows the highest electrocatalytic ORR active among three isomorphic COFs. In addition, Multistep chronoamperometry measurements were also conducted at potentials of 0. 3, 0. 6 and 0. 8 V as displayed in Figure  2f , and the experimental data revealed that the current density of JUC-616 remained almost unchanged at each applied potential throughout the experimental cycle, which demonstrates that JUC-616 has high electrochemical stability in alkaline solution.
Acknowledgments This work was supported by  National Natural Science Foundation of China  ( 52073119 ,  22025504 ,  21621001 , and  21390394 ), "111" project ( BP0719036  and  B17020 ),  China Postdoctoral Science Foundation  ( 2020TQ0118  and  2020M681034 ), and the program for  JLU Science and Technology Innovative Research Team. Q. F. and V. V. acknowledge the collaboration in the framework of of the  Sino-French International Research Network "Zeolites ".
Acknowledgment We want to present our grateful to  Chung Yuan Christian University, Taoyuan City, Taiwan; Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, Taiwan; Department of Civil Engineering Chung Yuan Christian University, Taoyuan City, Taiwan; Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, Taiwan; Center for Environmental Toxin and Emerging-Contaminant Research, Cheng Shiu University, Kaohsiung, Taiwan, ROC ;  Université Grenoble Alpes ,  CNRS, Grenoble INP  ( Institute of Engineering, Université Grenoble Alpes ), LMGP, 38000 Grenoble, France.
Independent and out-of-state generators stopped selling to the three utilities from fear of non-payment. In order to stabilise the market, retail prices were reluctantly increased, which impacted end consumers. PG&E ultimately filed for bankruptcy in April 2001. (Data sourced from US Energy Information Administration website, Subsequent Events California Energy Crisis Report) mechanisms to value transmission is to provide financial transmission rights (FTR) contracts. It is difficult to forecast future value of FTRs over long periods because of the challenges in accounting for changes to the generation resources and transmission system over time. The attention to system reliability is not necessarily at odds with increasing competition and the improved economic efficiency it brings to wholesale power markets.
The transition to an increasingly higher percentage of renewable resources in the generation stack, combined with a recent emergence of distributed energy resources (DERs), is challenging the status quo of today's regulatory market structure. In the longer term, it is important that the measures introduced to encourage low-carbon investment are flexible enough to accommodate future market changes and new technologies. In light of the decentralisation of the power sector, regulators and policy makers must be technology agnostic and carefully reconsider how industry structures at the distribution level affect system planning, coordination, and operation as well as competition, market development, and cost efficiency. The speed of energy technology innovation is only just coming to light as long-term historical data sets become available.
Measurement of PSDs The saponite growth studied in this study was based on the twodimensional extension of the particles in the ab-plane. Zhang et al. (2020 Zhang et al. ( , 2021) )  successfully observed well-dispersed particles of synthetic saponite by STEM and measured the size of a series of particles to obtain their PSDs by taking the mean value of length plus width in the ab-plane. Because saponite particles are generally irregularly shaped, we have developed a new method to measure the particle size of saponite, which is more accurate than that in  Zhang et al. (2020)  (Fig. 1 ). After obtaining well-dispersed saponite particles from STEM images, the area of the abplane of a particle was calculated using Image-ProPlus 6. 0 software package in a manual mode. Then, the obtained area was treated as a circle with a calculable diameter (d) that represents the mean size of the particle.
Acknowledgment We appreciate the financial supports by  National Natural Science Foundation of China  (Grant Nos. 41921003 ,  41825003 ,  42072044 ),  Science and Technology Planning of Guangdong Province, China  ( 2020B1212060055 ), The  European Union (ERDF) , " Région Nouvelle Aquitaine," French « Ministère de l'Enseignement Supérieur et de la Recherche », The Clay Minerals Society , and  China Scholarship Council.
RNA-seq analysis Demultiplexed and adapter-trimmed reads were processed with the Galaxy platform (https://galaxy. sb-roscoff. fr). After read quality filtering using Trimmomatic v0. 38. 0, transcripts were quantified using the pseudo-mapper Salmon v0. 8. 2  [64]  with the Z. galactanivorans Dsij T reference genome (retrieved from the MicroScope platform (  [65] , https://mage. genoscope. cns. fr), "zobel-lia_gal_DsiJT_v2"; Refseq NC_015844. 1). Raw counts for individual samples were merged into a single expression matrix for downstream analysis. Raw and processed data were deposited under GEO accession number GSE189322. Cleaned reads were also mapped on the Z. galactanivorans Dsij T reference genome using Bowtie2 (  [66] , Galaxy Version 2. 3. 2. 2). The mean per nt coverage for the whole transcriptome was assessed using SAMtools v1.
14  [67]  (Supplementary Table  2 ). The mean per nt coverage and normalized read counts (after DESeq2 normalization) for three selected characterized house-keeping genes in Z. galactanivorans Dsij T  [68]  are shown in Supplementary Table  3 , and the coverage map for these three genes and for the wellcharacterized alginate PUL were visualized using the Integrative Genomics Viewer v2. 11. 9  [69]  and shown in Supplementary Fig. 1. These data ensure the expression variability was not caused by low read coverage or promiscuous read mapping. Principal Component Analysis (PCA) and differential abundance analyses were performed on rlog-transformed data using DESeq2 v1. 26. 0 package  [70]  in R v3. 6. 2  [71]. Genes displaying a log2 fold-change | log2FC | > 2 and a Bonferroni-adjusted p value < 0.
Cells on membrane were visualized with a Leica DMi8 epifluorescent microscope (oil objective 63X). Cells on algal tissues were detected with a Leica TCS SP8 confocal microscope (HC PL APO 63X/1. 4 oil objective) using the 488 and 638 nm lasers to detect Alexa488 signal and algal autofluorescence signal, respectively. Z-stack images were collected using 1024 × 1024 scan format (0. 29 μm thick layers, 400 Hz scan speed) and visualized using the surface channel mode of the 3D viewer module (Leica Las X software). Following sequential CARD-FISH, Zobellia and Tenacibaculum cell counts were processed manually from 5 different fields at each time.
The number of CAZymes is highly variable within the genus (between 34 and 102 for the 8 Tenacibaculum genomes available in the CAZy database) but is largely below the 221 CAZymes found in Z. galactanivorans Dsij T  [20]. Tenacibaculum spp. might then lack key genetic Fig. 5  Genes related to oxidative stress response and T9SS are specifically induced by fresh tissue. Mean expression values (n = 3, except for F. serratus n = 2) of selected genes significantly triggered (*) with at least one macroalgae compared to both the purified polysaccharides and maltose (see Supplementary Table  4 ). L. dig: Laminaria digitata; F. ser: Fucus serratus; A. nod: Ascophyllum nodosum; Malt. : Maltose; Algi. : Alginate; FCSP: fucose-containing sulfated polysaccharide. determinants to initiate the algal breakdown but are likely able to use algal compounds.
ACKNOWLEDGEMENTS The authors thank  Tatiana Rochat  for advice during transcriptomic analyses,  Sébastien Colin  for guidance in confocal manipulation,  Bernhard Fuchs  and  Rudolf Amann  for guidance in designing and testing the TEN281 probe,  Philippe Potin  and  Cécile Hervé  for helpful discussions and  Yan Jaszczyszyn  from the I2BC sequencing platform. This work has benefited from the facilities of the Genomer platform and from the computational resources of the  ABiMS bioinformatics platform  ( FR 2424 ,  CNRS-Sorbonne Université, Roscoff ), which are part of the  Biogenouest core facility  network. This work was funded by the  French Government via the National Research Agency programs ALGAVOR  ( ANR-18-CE02-0001-01 ) and  IDEALG  ( ANR-10-BTBR-04 ).
Electrification of OECD Countries: The Rise of Electricity Another interesting but rather silent disruption in the energy industry was the process of massive electrification of modern economies (OECD countries). It can be considered silent because there were no losers: final electricity consumption simply kept increasing over the decades, that is, from 320 Mtoe in 1973  to 820 Mtoe in 2018, mostly without displacing other energy carriers but by creating new energy needs, for example due to a rising diffusion of household appliances such as fridges, TVs, washing machines, dishwashers and air conditioners (see  Fig. 29. 6). Data also shows that the transport sector never gained significant rates of electrification, rail transport being the only notable exception. Massive electrification in the residential and commercial sectors was a result of technology advancements that allowed for low-cost production of household appliances but also for an ever-decreasing cost of producing, transmitting and distributing electricity.
FUNDING The  UMR 1136  was supported by the  Agence Nationale de la Recherche  as part of the  "Investissements d'Avenir" program  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE). The Ph. D. salary of AL-L was provided by a funding from the  Lorraine University of Excellence (LUE). OK was supported by an  SSF grant  ( FFF20-008 ). UPSC was supported by grants from the  Knut and Alice Wallenberg Foundation  ( KAW 2016. 0341  and  2016. 0352 ) and the  Swedish Governmental Agency for Innovation Systems  (VINNOVA;  2016-00504 ).
The CV data were further complemented by chronoamperometry (CA) experiments on the 2/MWNT electrode to gain further insight on its stability as well as to determine the Faradaic efficiency for H 2 production (FE H2 ). CA were performed in the same neutral aqueous conditions but using a twocompartment cell. The electrode was poised at À 0. 49 V vs. RHE to limit the reductive inactivation while still ensuring relatively large currents. The H 2 content of the headspace was continuously assessed using gas chromatography (Figure  5  and S15 ). For 2/MWNT, an initial current density of À 0. 71 � 0. 2 mA cm À 2 was observed, determined at t = 2 min to avoid capacitive current contributions from the MWNT. Indeed, at that point about 27. 5 mC of charge was consumed and ~1 nmol of H 2 was detected which corresponds to negligible faradic efficiency (FE H2 ) of � 0.
Conclusion We report the synthesis and extensive characterization of an original bioinspired [FeFe]-H 2 ase mimic bearing two pyrene moieties, followed by its subsequent integration to MWNT-based electrodes and an evaluation of its performance during electrocatalytic H 2 production in aqueous media. Our data show that pyrene functionalization is efficient for the integration of such [FeFe]-H 2 ase mimics at π-conjugated surfaces. More specifically, it allowed the system to reach high surface loadings, ~30 to 240 times higher than previously obtained through physisorption or covalent grafting. As a result, the grafted system displayed conservative TON H2 value of 4 � 2 × 10 3 after 20 h of bulk electrolysis at À 0. 49 V vs. RHE in neutral aqueous conditions. The stability of the modified electrode was assessed using post operando characterization and showed that the loss of activity was attributable to the loss of iron carbonyl center, while the pyrene anchoring groups remained attached to the MWNT surface throughout long-term electrolysis measurements.
2 M phosphate buffer at pH 7. Chronoamperometry measurments coupled with gas chromatography: Electrolysis were performed in a five-neck glass vessel (volume of working electrode compartment was 55 mL including the headspace) as electrochemical cell. Each neck was sealed with rubber septum to avoid leakage. The cell was separated into two compartments by a glass frit in order to limit oxygen diffusion from the anodic to the cathodic compartment during electrolysis. The cell was deaerated for 20 min with argon before analysis. The cathodic part of the cell was coupled with gas chromatography with continuous argon flow with rate of 5 mL min À 1 to quantify H 2 produced during analysis. The data for gas chromatography was collected at every 1 min interval. CCDC data: 2183292 (for 1)) contains the supplementary crystallographic data for this paper.
Acknowledgements We would like to thanks European Union's  Horizon 2020 research and innovation programme  under grant agreement No. 765376  for their constant support with funding. This work was also partly supported by the  Agence Nationale de la Recherche (Labex ARCANE ,  CBH-EUR-GS ,  ANR-17-EURE-0003 ). We would like to acknowledge support of  Dominique Foix  ( UPPA ) for X-ray photoelectron spectroscopy (XPS) analysis.
230 In this section we present simulations using detailed switching models on Sim-231 scape Electrical from Matlab Simulink. These simulations allow to isolate the control 232 and dynamic response phenomena, while still representative for the remaining power 233 electronic aspects. 234 R 01 0. 001Ω R 1 0. 1Ω C 1 0. 1F R 02 0. 002Ω R 2 0. 001Ω C 2 0. 01F R 03 0. 001Ω R 3 0. 5Ω C 3 0. 1F R 04 0. 0015Ω R 4 0. 01Ω C 4 0. 01F R 05 0. 001Ω R 5 0. 4Ω C 5 0. 1F R 06 0. 0015Ω R 6 0. 01Ω C 6 0. 01F L 1 0. 0033H L 2 0. 0033H L 3 0. 0033H V PV 1000V P n 1MW V DC 1000V V SC 500V V BAT 500V V DC 1000V Table 1: Simulation parameters. Two simulations are presented. The first one is done during 300s of simulation time, irradiance. It can be seen that the output power follows the irradiance variations. Figure.
Statistical analysis of the operating and response variables Principal component analysis (PCA) was carried out to investigate the correlation between the operating variables and response variables, as reported in literature  [44, 45]. Compared with conventional methods of data analysis, PCA reduces the dimensionality of a dataset while preserving statistical information, which allows detailed analysis and comparison  [46]. The values of each variable were standardized to overcome the variation of measurement units. The PCA was conducted using R Studio software (version 1. 1. 456). In PCA biplots, each eigenvector represents an individual operating or response variable. The correlation of any two variables is found by the cosine value of the angle between their respective eigenvectors, which ranges between -1 and 1.