dataesr/scientific-paragraphs-categorization huggingface dataset:
In addition, some sites could not be processed when L1C with cloud coverage below 90% were too sparse along time (i. e. , Ilorin, Minsk, Moscow, Yekaterinburg, Tomsk, Yakutsk). Moreover, MAJA's approach that consists of a linear combination of the LUT computed for each CAMS aerosol model is not compatible with the occurrence of high absorbing aerosols due to pollution or biomass burning. The regions prone to the presence of such aerosols are processed with the default continental aerosol model. In the ACIX-II dataset, it corresponds to eleven sites (i. e. , Alta Floresta, Beijing, Cairo, Chiang-Mai, Chiayi, Dalanzadgad, Dushanbe, Gandhi College, Luang Namtha, Mexico City, and Zinder Airport). It is worth mentioning that four reference samples show a significant shift of the distribution of surface reflectances below zero in the blue band, while tending to overestimate the reflectances as compared to MAJA in the red and near infrared, as illustrated for Luang Namtha site for 6 March, 2018, in Figure  1 , or, e.
The agricultural rotation of three crops every two years, maize, winter wheat, and intermediate cover, respectively, leads to a significant intra-and inter-annual variation of land surface reflectances, at the cost of a stronger cloud coverage as compared to the first two sites. The combination of these three datasets provide insightful results on the performance of MAJA. The in situ measurements used in this second approach consist in time series of ROSAS acquisitions over La Crau and Gobabeb from July, 2017, to December, 2021, as well as the first set of acquisition of the Fr-Lam ROSAS station during a complete cycle of maize growth, senescence, and harvesting in the year 2021. Since the full daytime measurement sequence requires 140 min of cloud-free sky, any dataset affected by sparse cloud-cover in the data acquisition interval are removed at the post-processing stage.
The ROSAS datasets over La Crau and Gobabeb have been reprocessed to account for an improved calibration of the photometer instrument water vapour band provided by CIMEL in 2022. This leads to 181 quality controlled measurements for Gobabeb and 166 for La Crau. As Fr-Lam is a recent site, and more prone to clouds than the other two sites, the number of samples available for validation is limited to 13 from June to November, 2021. To match Sentinel-2 MSI bands, the surface reflectances obtained from the photometer are resampled using a third order spline interpolation. The ROSAS photometer performs measurements of upwelling radiance up to 60 degrees off nadir, which leads to a 34 m diameter circle footprint at ground level, and a 26 m diameter circle footprint at maximum maize canopy height for the Fr-Lam site.
Within this area, the surface cover is assumed homogeneous by the processor although it might not be exact in reality, each measurement of angular configuration (θ, φ) being assimilated to the observation of the exact same surface from a different point of view. A BRDF following Roujean's model (  [29] ) is applied to derive the nadir surface reflectance comparable to MAJA's output. The MAJA surface reflectance values of the 10 m resolution Sentinel-2 bands are averaged over 50 by 50 m square centred on the photometer mast. The errors associated with ROSAS surface reflectances were estimated considering all the sources of uncertainties along the processing chain, photometer noise, calibration of the photometer collimators based on Rayleigh scattering and Bouguer-Langley methodology, BRDF fitting, and spectral interpolation.
For clear sky conditions along a day, the surface reflectance estimation error varies from 3. 5 to 5% for La Crau and 3 to 4. 5% for Gobabeb depending on the spectral band. For a more turbid day, this budget is only slightly increased by less than 1% because of the data quality filtering before processing. The Region Of Interest (ROI) used to compare ROSAS with Sentinel-2 was a 50 m × 50 m square centred on the photometer. The error compared to the 30 m × 30 m ROI covered by the photometer was estimated using PLEIADE data and is on average <1% for La Crau and <0. 5% for Gobabeb. The slightly higher error at La Crau compared to Gobabeb is explained by the higher heterogeneity within the instrument footprint at La Crau. For Fr-Lam, an early estimate using the first acquisitions suggests an error of up to 7%, but since the calibration improves along time, the error is expected to decrease as the data collection increases.
The methodology for the ROSAS uncertainty estimation is presented in  [30, 31]. For the purpose of this comparison, we processed a time series of Sentinel-2 L1C products available from July, 2017, to December, 2021, for tile 31TFJ and 33KWP for La Crau and Gobabeb, respectively, and from June to November, 2021, for tile 31TCJ for Fr-Lam, applying the default adjacency and topographic correction. Therefore, the following MAJA L2A ground reflectances are nominal products (as opposed to the previously used ρ S MAJ A i,λ uncorrected for adjacency and topographic effects). For the sake of comparison, two sets of L2A products are computed with and without using the CAMS aerosols auxiliary data.
MAJA and ROSAS Inter-Comparison In this case, the validation is site-specific, and relies on time series of in situ ROSAS acquisitions at La Crau, Gobabeb, and Fr-Lam stations. Both La Crau and Gobabeb datasets cover the period ranging from July, 2017, to December, 2021, while the recent Fr-Lam station dataset ranges from June to November, 2021. Only quality controlled ROSAS data are used for validation, leading to 166 samples on La Crau, 181 on Gobabeb and only 13 on Fr-Lam. The results presented on Figure  3  compare MAJA L2A ground reflectances using auxiliary CAMS aerosols data, as well as topography and adjacency effects corrections (nominal settings of MAJA), with quality-controlled ROSAS ground reflectances. The overall RMSEs are well in line with the expected MAJA uncertainties for Sentinel-2 bands 2 to 4, but are not as good for higher wavelengths.
The differences between MAJA and ROSAS surface reflectances account for both the calibration specification of Sentinel-2 (within 3% for TOA reflectances  [32] ), the error budget of the ROSAS protocol (within 5%  [10] ) and the errors from MAJA itself. MAJA's multi-temporal approach assumes that the surface reflectance at the shortest wavelength does not vary rapidly with time, so MAJA tends to adjust the AOD to match this assumption. It is therefore expected that the RMSE for the visible bands will be lower than for the shortwave infrared bands. The slightly higher RMSE over La Crau as compared to Gobabeb can be explained by the stronger heterogeneity of the footprint of the ROSAS instrument. The higher RMSE for Sentinel-2 band 8 can also be linked to the spectral resampling needed to compare the MSI bands with the CIMEL sun-photometer of the ROSAS station, since Sentinel-2 band 8 is centred at 842 nm while the nearest CIMEL band is centred at 870 nm.
6 m early August. With an inter-row spacing of 50 centimetres, the signature evolves from mostly clear clay bare soil to a dense green vegetation. Although the North-South pattern of the rows induces directional effects, these are smoothed by the BRDF model. Although not quantified in this study, the Rounjean BRDF might in such cases over-simplify the actual BRDF and, thus, contribute to the uncertainties of the derived surface reflectances. The harvesting occurred the 20th of September, before the maize reaches its senescence stage as it was intended for silage, and left the soil surface mostly covered by vegetation debris. According to the Figure  3 , MAJA and ROSAS show better agreement when the vegetation is low over Fr-Lam. It should be noted that the quality of the AOD estimates of MAJA can be affected by the presence of large gaps in the the time-series of Sentinel-2 images due to clouds.
As the period from June to July was particularly cloudy over the Fr-Lam station, the hypothesis of a change in TOA reflectance explained by a change in AOD, on which MAJA partly relies on, is weakened as the available observations become sparse. Although MAJA detected the sudden increase in AOD on 7 September, it failed to catch its actual amplitude. The use of the CAMS Global Atmospheric Composition Forecast with MAJA is considered the nominal configuration. However, users willing to process Level 1 products without it can still use the default continental aerosol definition, by deactivating the CAMS option. For the sake of comparison, the time series of products over La Crau, Gobabeb and Fr-Lam were processed with the default continental aerosol and compared to ROSAS. Table  2  summarises the actual benefits of CAMS auxiliary data over the continental aerosol when compared to ROSAS stations data, with improvements in terms of RMSE of the order of 0.
Discussion The performance metrics of this study do not cover the retrieval of the water vapour by MAJA, since it was already addressed in ACIX-II, together with detailed indicators on the uncertainties in the retrieval of the AOD. Ref. [18]  reported an RMSE of MAJA's AOD of 0. 135 for all AERONET sites together. The RMSEs on AOD reported in Table  2  for the La Crau and Gobabeb time series of ROSAS acquisitions are overall lower, but do not cover the large variety of contexts addressed by the AERONET network. In addition, the Table  2  illustrates the benefit of the auxiliary CAMS aerosols data on the estimation of the AOD by MAJA, although more significant over La Crau than Gobabeb. When compared to other AC processors within ACIX-II (Figure  5 ), the uncertainties obtained when comparing the MAJA products without adjacency and topographic correc-tion to the reference dataset are overall slightly higher than the ones of FORCE, LaSRC, or Planet.
Although the ACIX-II reference dataset should, by design, give a non negligible advantage to 6SV-based atmospheric correction processors, such as LaSRC or Planet, the performance of MAJA fits well within the expected specifications spec = 0. 05ρ + 0. 005 defined by  [15]. The uncertainties of the SR computed by MAJA remain under 0. 01 for the red, NIR and SWIR bands, and below 0. 011 for the blue band. With the exception of a limited number of locations worldwide, the use of CAMS aerosols data provide SR in good agreements with the reference ones. Lower performances are expected in areas with strong aerosols, as observed over Asian cities sites. Moreover, rainforest areas are more prone to errors in the estimation of AOD and derived SR, mainly because of the strong and continuous cloud coverage which weakens the multi-temporal approach of MAJA.
[18]  for various AC processors, extended with MAJA uncertainties obtained from Section 2. 2. The major interest of this first AERONET-based approach is to assess AC processors against a large variety of contexts in terms of both land cover and atmospheric properties, though it remains a comparison with indirect observations of ground reflectances. The occurrence of lower than zero reflectances in the reference dataset illustrates the presence of biases inherent to this approach, which remains sensitive to uncertainties in the estimation of atmospheric quantities by AERONET stations. The second approach based on the ROSAS stations is complementary. The complexity and cost of the instrumental setup limit the number of observation sites to three stations. On the other hand, the continuous record of the surface reflectances for any angle of observation with a spectral sampling close to Sentinel-2 specifications provides unique time series of validation data.
At the time of this study, no other in situ network provides equivalent datasets over land. The recent addition of the Fr-Lam station combined with stronger cloud occurrences over the Lamasquere region limited the number of qualitychecked observations on this site, leading to poorer validations results. Further studies remain necessary to estimate the impact of heterogeneity within the instrument footprint, as the vegetation coverage of this station can range from bare soil to three meters high maize. The discrepancies observed between the wide Sentinel-2 842 nm band 8 and the corresponding narrower 870 nm CIMEL band suggest that the Fr-Lam instrument requires further calibration. This calibration is part of the ROSAS protocol, and is linked to the length of available time-series of quality-proofed observations, which was very limited for the period under consideration.
The nearly continuous five-years long records available for the La Crau and Gobabeb stations provide a significant amount of validation samples. Overall, the RMSEs obtained comparing ROSAS SR against MAJA SR are slightly lower than the uncertainties retrieved from the ACIX reference datasets, especially for the blue band 2. Moreover, the RMSEs tend to increase for NIR and SWIR bands, as opposed to the observed behaviour with the AERONET approach. Such higher RMSEs, as, e. g. , for Sentinel-2 band 8, could be attributed to the spectral resampling of the CIMEL sensor used under the ROSAS protocol, whose bands central wavelength and width do not fit well with the Sentinel-2 one. La Crau and Gobabeb uncertainties however remain within reasonable bounds as compared to the results obtained for the Fr-Lam station, who will need further calibration.
The comparison of the surface reflectances between MAJA and ROSAS stations also demonstrates the benefits of the use of the CAMS aerosols auxiliary data for SR computation, mainly over La Crau. However, as suggested by the results in Table  2 , the performances of MAJA using the single continental aerosol definition as a substitute to the use of CAMS remains within the aforementioned specifications. Although the use of the single continental aerosol is not considered as the nominal use of MAJA, it proved to remain an alternative for some very specific regions of the globe subject to strong absorbing and non-absorbing aerosols mixing. A new approach to better account for aerosols mixing is planned for an upcoming publication. These validation results demonstrate the adequate performance of MAJA for the production of high-quality Sentinel-2 surface reflectance products, combined with highquality cloud masks, as shown in  [21].
Data Availability Statement: The dataset of MAJA surface reflectances uncorrected for adjacency or topographic effects generated for this study is available at: https://doi. org/10. 5281/zenodo. 7564889 (accessed on 15 May 2023). The datasets of ACIX-II reference surface reflectances are available on the ACIX portal at: https://calvalportal. ceos. org/acix-ii-land (accessed on 15 May 2023). The SR data for La Crau and Gobabeb are distributed on the RadCalNet portal at https://www. radcalnet. org/ (accessed on 15 May 2023). The Fr-Lam data are still under qualification process. The scripts used to generate the results of the APU metrics are available on GitHub at https://github. com/jeromecolin/mtools (accessed on 15 May 2023). The open source code of MAJA is available online at https://www.
Introduction Post-Variscan tectonics resulted in the formation of a series of Permo-Carboniferous strike-slip and extensional basins in central and western  Europe (e. g. , McCann et al. , 2006). Many of these basins are filled with latest Carboniferous coal-bearing sediments and early Permian lacustrine deposits  (McCann et al. , 2006; Mercuzot et al. , 2022). Elongated Permo-Carboniferous coal-bearing basins are also present in the basement of the North Alpine Foreland Basin (NAFB; Fig. 1 ) (e. g. ,  Bachmann et al. , 1987; Madritsch et al. , 2018). The extension and sedimentary infill of the Permo-Carboniferous grabens are poorly known. This is because high resolution seismic data illuminating the grabens are scarce and only very few wells penetrated the graben deposits. The most intensively studied graben structure is named the Constance-Frick Trough and is located in northern Switzerland  (Diebold et al.
Probably the lake sediments were deposited in a complex and extensive early Permian lakescape  (Matter, 1987). Grey and subsequently red coarse-grained clastic sediments representing alluvial fans follow above the lacustrine deposits (1252. 07-1058. 03 m). Fine-grained red-coloured playa sediments (1058. 03-991. 50 m) are the youngest Permian deposits preserved  (Diebold, 1988). Random vitrinite reflectance (%Rr) data of the Weiach-1 well was provided by  Leu et al. (2001) and NAGRA (2002). Vitrinite reflectance increases from ~0. 7 %Rr at the top of the Permo-Carboniferous succession to ~1. 25 %Rr at 1950 m depth. Mazurek et al. (2006) ,  Leu (2012)  and  Omodeo-Salé et al. (2021)  used these reflectance data to calibrate the heat flow history of the Weiach area. Based on these models, it is likely that Permian heat flow was high (125 mW/m 2 ;  Omodeo-Salé et al.
The sample was injected in split mode with a split ratio of 20 at 260 • C using helium as carrier gas. The spectrometer was operated in the EI (electron ionization) mode with a mass-to-charge ratio (m/z) scan range from m/z 50 to m/z 650 (0. 7 s total scan time). Xcalibur and Chromeleon data systems were used for data processing. Identification of individual compounds was based on their respective retention time within the mass spectra or total ion current (TIC) chromatogram and comparing the mass spectra with published data as reference. From the distinct compound groups in the aliphatic and aromatic fraction, absolute concentrations were determined using peak areas in the TIC chromatograms comparable to that of internal standards while in the case of mass chromatograms, response factor were used to correct the intensities of the fragment ions used for quantification of the total ion abundance per sample.
Thermal maturity Thermal maturity was deduced using T max values from the entire studied succession and vitrinite reflectance data from the main coal seam and the main shale interval. T max values increase in the depth interval from 1300 to 1850 m from ~440 to 465 • C. Random vitrinite reflectance in the main shale interval (1326. 95-1339. 20 m) is lower (0. 56-0. 78 %Rr, avg. 0. 66 %Rr) than in the main coal seam (#6; 1585. 0-1591. 2 m; 0. 91-0. 95%Rr). This range of T max and random vitrinite reflectance values agrees well with the increase of vitrinite reflectance in the same depth interval (1300-1850 m) from ~0. 70 to 1. 15 %Rr  (NAGRA, 2002). In the following maturity issues are discussed separately for Carboniferous coals and the Permian lacustrine series.
Acknowledgments The authors thank SwissTopo for the permission to take core samples from the Weiach-1 well, at the SwissTopo core shed located in Hochdorf (Switzerland), in the framework of the  UNCONGEO  project. The authors also thank  François Baudin  from  Sorbonne University  for some rock eval analysis and scientific discussion. Careful reviews by the journal reviewers  P. Hackley  and  B. Katz  helped to improve the paper significantly.
The Extra Y refers to the excess Y entities besides of those designated to form stoichiometrically YAG with Al entities. the confirmed P presence, the EDX measurements confirmed the presence of Y in an excess quantity as expected. Larger amount of extra Y and P addition (i. e. , a total Y/Al ratio of 1. 0 and a P/Al ratio of 0. 193) induced further structural changes as is clear from the peaks related to PO 4 in the FTIR spectra that evolved into a more single-component peak at 1012 cm -1 (Figure  3a ), indicating a more crystallized PO 4 -based environment. The nature of this crystalline phase was revealed by the appearance of two peaks situated ≈25. 8 and 51. 7° 2-theta (XRD, Figure  3b ), identified as Yttrium (III) phosphate (monazite type tetragonal YPO 4 , JCPDS 00-011-0254) phase according to the JCPDS database.
Nevertheless, the attribution of this peak is uncertain due to the lack of literature reference, and therefore is not subject to discussion in this paper. From this data we conclude that the addition of extra Y and P has at least converted the environment of Ce from Ce1-type to Ce2-type, suggesting a transition in chemical coordination numbers  [30]  or physical distortion environments. [31] The former could be a result of an intimate contact between Ce and PO 4 species, since the coordination number of the Ce in a monazite structure is 9 instead of 8 if Y is partly substituted by Ce. [32, 33]  The latter distortion could be a result of an internal dispersion of PO 4 inside of YAG host. In order to confirm the inclusion of Ce and PO 4 and also the role of excess Y in the YAG lattice, long-scanned PXRD data were collected on Ce-free YAG and YAG:Ce3% NPs Small 2023, 2208055 synthesized with different P/Al and Y/Al atomic ratios.
Acknowledgements Y. Y. conceptualized, synthesized, and characterized the nanoparticles, participated to the manuscript writing, A. M. resolved the crystallographic structure, L. K. did the EPR, C. B. , N. B. , O. E. contributed on the electron microscopy experiments, C. L. the solid-state NMR, A. C. B, M. A. H. , M. R. K. participated to the luminescence measurements, F. L. and F. C. contributed on the synthesis and characterization of the particles, S. P. conceptualized, analyzed the data, wrote the article. All authors had given approval to the final version of the manuscript. This work was supported by  Seaborough Research BV , under the umbrella of a Eurostars grant (Project E! 12268 EUROLED),  Ecole Normale Supérieure de Lyon, CNRS  and University Lyon 1. The authors thank  The Département de Chimie Moléculaire, Université Grenoble Alpes , for providing resources to perform an EPR measurement at Helium temperature.
Experimental procedure and method In order to study the OPG process in PPLT crystals, we used the experimental setup shown in Fig. 1. We used 1D-PPLT nonlinear photonic crystals fabricated by using the electric poling technique  [9]. The grating periods Λ studied, here, are: 8. 082µm, 8. 295µm, 8. 43µm, 8. 52µm and 12µm. The samples are pumped by a Q-switch doubled Nd:YAG pump laser at 532nm and mounted onto a temperature controller where the crystal temperature can be set between 40°C and 200°C with an accuracy of ±0. 1°C. For each sample, we measured the spectra of the optical parametric generation, with a resolution of 0. 5nm, obtained for temperatures ranging from 40°C to 200°C with a step of 2°C at a pump energy of 15µJ and 25µJ. Then we developed a specific Matlab code that makes it possible to simultaneously adjust all the experimental curves of the OPG according to the temperature for the different periods.
Such a result is to be expected as, in the critical case of (  12 ), a stability result without constructive estimate has already been established by F. Seuffert in  [31]. to the project MTM2014-52240-P (Spain) and by the E. U. H2020 MSCA programme, grant agreement 777822, by the Project EFI (ANR-17-CE40-0030) of the French National Research Agency (ANR), by the DIM Math-Innov of the Region Île-de-France and by the "Fondation Mathématique Jacques Hadamard". The authors thank an anonymous referee for his detailed reading, comments and suggestions. c 2022 by the authors. This paper may be reproduced, in its entirety, for non-commercial purposes.
Acknowledgments. M. B. has been supported by the Projects  MTM2017-85757-P  and  PID2020-113596GB-I00  ( Ministry of Science and Innovation, Spain)  and the  Spanish Ministry of Science and Innovation , through the " Severo Ochoa Programme for Centres of Excellence in R&D"  ( CEX2019-000904-S ) and by the  E. U. H2020 MSCA programme , grant agreement  777822. J. D. has been supported by the Project  EFI  ( ANR-17-CE40-0030 ) of the  French National Research Agency (ANR). N. S. has been supported by the  Spanish Ministry of Science and Innovation , through the  FPI-grant   BES-2015-072962 , associated.