dataesr/scientific-paragraphs-categorization huggingface dataset:
Such a monthly dataset would also permit to disentangle sub-monthly variability from interannual variability, as opposed to the monthly climatology. Combining the UOSI climatology with a surface buoyancy flux climatology would help to estimate the contribution of lateral buoyancy fluxesincluding those due to submesoscalesto the upper ocean restratification (e. g. ,  Johnson et al. , 2016) , and to analyze in detail the large variability of upper ocean stratification occurring in spring. Finally, the sensitivity of our method to defining a lower limit for the detection threshold should be investigated to better understand differences between the upper limit of the UOP and the MLD estimates in the North Atlantic.
Data availability statement The ISAS dataset  (Kolodziejczyk et al. , 2021)  and the permanent pycnocline climatology  (Feucher et al. , 2018)  analyzed in this study use data from the Argo program Argo (2022). All the dataset are available on the SEANOE platform at https://www. seanoe. org/(see the corresponding DOI in the references). The UOP dataset generated for this study can also be found on the SEANOE platform at https:// www. seanoe. org/data/00798/91020/ (Seŕazin et al. , 2022).
Data and methods We select events from the GCMT catalog located in the vicinity of Mayotte Island in 2018. This selection gives a total of 27 events with M w ≥ 4. 8, occurring mostly at the beginning of the crisis (i. e. in May-June 2018). We use teleseismic and regional waveforms from stations with an epicentral distance from 0°to 90°. We use a combination of 150 channels from GEOFON  [IS, GE, TT; GEOFON Data Centre, 1993]   Nyblade, 2017]. Waveform data has been validated at long period by comparing with synthetics from large teleseismic earthquakes. We do not use the YTMZ strong motion station from the French RESIF-RAP network, which was the only station on Mayotte Island at the beginning, due to large errors in the internal clock during the studied time-period. For each earthquake, we manually reject noisy records and data with dubious metadata.
After data screening, moment tensor solutions are obtained using 23 channels in average. The time window used for the waveform inversion starts at the P-wave arrival and includes the first group of surface waves (R1 and L1). For specific stations, we manually change the time window duration to exclude clipped signals in the inversion. A causal bandpass Butterworth filter of order 4 is applied to the data. To mitigate long-period seismic noise, the filter corner periods are adapted as a function of the earthquake magnitude and the epicentral distance of the stations (see Tables  1  and 2 ). Using the resulting long-period waveforms, we then perform point source inversions to invert for CMT parameters (i. e. , moment tensor elements, rupture duration, and centroid location in time and space).
We use a modified version of the W-phase inversion method by  Duputel and Rivera [2019]. This algorithm relies on a grid-search approach to find the pointsource mechanism, time and location that minimizes the root mean square (RMS) waveform misfit. In this study, we assume three different levels of generality for the moment tensor: (1) Full moment tensor (FMT; i. e. , six independent elements of the symmetric moment tensor), (2) Deviatoric moment tensor (DMT; i. e. , assuming no net volume change during the rupture) and (3) Double-Couple (DC; i. e. , assuming a pure shear rupture). While FMT and DMT inversions are linear for a given centroid location, DC solutions are estimated by grid-searching for strike, dip and rake angles corresponding to the minimum RMS misfit. For the sake of consistency, FMT and DC inversions are performed using the same dataset, time shift (T s ) and centroid location as those estimated for the DMT solution.
Acknowledgments We thank two anonymous reviewers and the editors for their useful comments during the revision process. Dr. Lise Retailleau  comments also helped us to improve the manuscript. This work was supported by the  Initiative d'Excellence (IDEX)  funding framework ( Université de Strasbourg ). This project has also received funding from the  European Research Council  ( ERC , under the European Union's  Horizon 2020 research and innovation program  under grant agreement No. 805256 ) and from  Agence Nationale de la Recherche  (project  ANR-17-ERC3-0010 ). CMY acknowledges funding from  ANID/FONDECYT 3220307  and the "anillo precursor project"  ANID PIA Anillo ACT192169. We wish to thank the network and station operators for their commitment to collect high-quality seismic data and the  Computational Infrastructure for Geodynamics  (http://geodynamics.
Sampling Some of the genetic data used in the present work were generated by  Marí-Mena et al. (2016 , 2019) , but we now add data from eight new sites. Adult males were attracted by sexual synthetic pheromone  (Millar et al. 2010 ) and caught with hand-held aerial nets during the flying season 2010. Overall, the present work uses samples from 17 sites (Pinus sylvestris woodland) (Fig. 1  and Table  1 ). The five core sites are located within the boundaries of the Ordesa y Monte Perdido National Park (OMPNP). The remaining samples were collected in sites outside the OMPNP, four of them within its buffer zone (protected), two sites within its socioeconomic influence zone (not protected and referred as "peripheral" hereafter), and six sites far off the OMPNP. We will use the following codes to refer to sampling sites: a one-letter prefix indicating its proximity to the OMPNP ([C]ore, [B]uffer, [P]eripheral, [F]ar) followed by a three-letter abbreviation of the name.
Since G. isabellae exclusively uses P. sylvestris as its host plant in the study area, we filtered patches described as Pinus sylvestris stands, and included P. sylvestris cover values as a proxy of patch suitability. The database includes the dominant and additional tree species for each path, and cover values expressed in percentage of the total area. The vector layer was rasterized to a 0. 5 km grid, and cell values calculated as cost for dispersal. We transformed cover values into discrete values of impedance (i. e. , dispersal cost for the species to the nearest cell). Total cover of P. sylvestris (90-100%) were classified as Weight = 1. Weight increased one unit of impedance for each 10% interval for all cover values were higher than 40%, therefore weight ranged in the interval 1-6. All other cells were considered unsuitable, and given Weight = 10, and in a second analysis Weight = 100.
This allowed us to consider a neutral weight for unsuitable habitat with the same proportion of tree cover for the 1-10 weights (hereafter impedance_10), or a high-costly unsuitable barrier for the 1-100 weights (impedance_100). We used the Least-Cost Path extension for QGIS 3. 24. 2 software (www. qgis. org) to calculate the least cost route for each pair of sampling locations and generated a symmetric matrix for each of the two analyses. Significance of each Mantel test was assessed based on 10,000 permutations. A higher correlation between the genetic distance and the least-cost matrices (than the one obtained between the genetic and Euclidean distances) would point to connectivity as an important element determining dispersal pathways (see  Coulon et al. 2004 ) for the Spanish Moon Moth.
After preliminary runs, delta values were tuned individually to obtain acceptance rates within 40-60% of the total  (Faubet et al. 2007 ) as follows: Δa = 0. 35, Δf = 0. 95, and Δm = 0. 95. Ten independent runs with different random starting seeds were performed to assess MCMC convergence and evaluate the consistency of the results. TRACER 1. 7. 1  (Rambaut et al. 2018 ) was used to visualise MCMC simulations and confirm convergence of chains among runs. We used the R script provided by  Meirmans (2014)  to calculate the Bayesian deviance for each run to determine the run that best fit the data (the one with the lowest deviancy).
Dataset quality We obtained multilocus genotypes for the whole set of 402 individuals. The number of individuals analysed from each sampling site varied from four at C-URB to 32 at F-CAB (Table  1 ). After the sequential Bonferroni correction, only two out of the 153 site-locus combinations (1. 31%) showed significant deviation from Hardy-Weinberg equilibrium (HWE). Specifically, locus GRAISA25 did not conform HWE in F-BEL, and locus GRAISA15 in B-DIA (Table  S1 ). In both cases, departure from HWE as due to a heterozygote deficit, but no deviations from HWE were detected at locality level by the global tests (Table  1 ). Null allele frequencies were low, varying from 0. 010 to 0. 165 across loci (Table  S2 ). In detail, only two loci exhibited a high null allele frequency (above 0. 2 according to  Chapuis and Estoup (2007) ) in specific sites, GRAISA17 in B-BUJ and C-URB, and GRAISA25 in F-BEL (Table  S1 ).
Population structure The overall genetic differentiation among sites was low (F ST = 0. 038), with pairwise estimates between sites in the range (-0. 013, 0. 134) (Table  2 ). F ST values revealed: (i) differentiation of F-BEL and F-REN (the westernmost and easternmost localities of the sampling, respectively) with most of the remaining sites; (ii) connectivity among F-JUA/F-AGU/F-CAB/B-LIN/B-BUJ/P-FON; and (iii) connectivity of F-BAN (south of the park, Fig. 1  Mantel tests always rejected the null hypothesis of absence of relationship between the genetic and geographic dissimilarity matrices. In addition, Mantel's r was always higher when using the geographic distance considering constrains from tree cover (whole dataset: Euclidean distance, r M = 0. 585, P = 0. 004, impedance_10: r M = 0.
764, P = 0. 000; impedance_100: r M = 0. 703, P = 0. 000). However, the association between genetic and geographic distance decreased at the small scale (11 sites dataset: Euclidean distance: r M = 0. 242, P = 0. 035; impedance_10: r M = 0. 577, P = 0. 001; impedance_100: r M = 0. 664, P = 0. 001). The influence of tree cover constrains on genetic distance is additionally supported by the partial Mantel tests controlling for geographic distance (whole dataset: impedance_10, r M = 0. 645, P = 0. 002; impedance_100, r M = 0. 544, P = 0. 005; 11 sites: impedance_10 r M = 0. 622, P = 0. 002; impedance_100, r M = 0. 644, P = 0. 008). Dispersal was restricted within 6 km, as indicated by the significant and positive autocorrelation in the first distance class regardless of the number of distance classes used to calculate the correlogram (Fig.
S3 ). On the other hand, the Bayesian spatial clustering method implemented in TESS was also used for seeking population structuring along the OMPNP dataset (OMPNP, buffer, and peripheral zones). According to the Deviation Information Criterion (DIC), K = 2 was the best clustering provided by TESS for the data (Fig. S4 ). TESS assigned individuals to each of the two inferred clusters similarly to STRU CTU RE, unravelling again a clinal variation between westernmost and easternmost locations of the park, with the moths captured in the eastern localities showing similar membership coefficients for both groups (Fig. 4 ). Lastly, the sPCA found a significant global spatial structure (global Monte Carlo test P = 0. 002) across all sampling sites, while there was no evidence of local structures (local Monte Carlo test P = 0.
This two-scale sampling resulted beneficial for different analyses, such as the correlations between genetic and geographic distances. Also, it was helpful to overcome the difficulty of Bayesian clustering algorithms to distinguish between a pattern of IBD and discrete population structure in continuously distributed organisms exhibiting IBD but not properly sampled  (Anderson et al. 2010). The most popular clustering method, STRU CTU RE, is sensitive to patterns of IBD and may overestimate a number of clusters where there is only a single large area with IBD. Indeed, several partitions (K = 4 for the protected area and K = 5 and K = 10 for the whole dataset, Fig. S1 ) supported by the most commonly used evaluation methods did not add any relevant information to K = 2.
Acknowledgements We thank  N. Remón  for her valuable help in the laboratory. J. C. Bellver ,  F. Carmena ,  O. Decker ,  M. Drago ,  G. Fernández ,  F. Goussard ,  G. Horcajada ,  M. Martínez ,  P. Lincango ,  J. Sevilla ,  S. Uceira , and  M. Villanueva  contributed to fieldwork with their advice, assistance, and equipment. We appreciate the support provided by the staff of the  Ordesa y Monte Perdido National Park , especially  E. Villagrasa ,  V. Sanz , and  F. Villaespesa. This work benefited from the discussions held with  E. Murria-Beltrán ,  H. Naveira  and  L. Torrado-Blanco. We thank the two anonymous reviewers who carefully read our manuscript for their many insightful comments and suggestions. All samples were collected with appropriate licenses. Figure S3 was adapted from " Mapa de Hábitat de Aragón " by  J.
| Bilinear rotation decoupling In 1982, Garbow et al. [36]  first published a pure chemical shift spectrum of organic liquids and discussed possible applications to strongly coupled systems by using a bilinear rotation decoupling (BIRD) element where active and passive spins are separately manipulated. The BIRD element selectively inverts the spins of  12  C bound protons (passive spins) leaving the  13  C bound protons (active spins) unaffected. The latter are selectively inverted by means of a hard π pulse placed at the center of a delay t 1. This delay is then incremented to generate the full free induction decay (FID) by collecting the first point of the FID for each τ value. [39] A more detailed review of this approach can be found in Meyer and Zangger. [20, 21] We note here that in the case of the BIRD method, the pure shift FID has often been reconstructed point by point from the indirect domain of a standard 2D experiment, which is time consuming if only the 1D pure shift spectrum calculated from the indirect domain of this dataset is pursued.
| Slice-selective Zangger-Sterk decoupling In 1997, Zangger and Sterk created a new method (the ZS method)  [19]  to record broadband homonuclear decoupled spectra, which tackles the two fundamental issues addressed above: (1) performing simultaneously a homonuclear decoupling of all proton sites to generate a pure shift spectrum where all signals can be acquired at the same time and (2) acquiring a dataset that allows for reconstructing a pure shift signal in a limited amount of time. First, Zangger and Sterk have proposed to use a gradient-encoded homonuclear decoupling element composed of a selective π pulse ("soft" pulse) applied together with a weak pulsed field gradient (PFG), which is F I G U R E 2 Schematic representation of the pulse sequence designed for recording 1 H NMR pure shift spectra.
To optimize the decoupling efficiency, J-couplings are actually exactly refocused in the middle of the data chunk. [41] The overall pure shift evolution of all active spins is thus reconstructed from the acquisition of a series of chunks that are recorded for incremented durations of the homonuclear decoupling element until the desired acquisition delay is achieved. This ZS method allows for recording the whole pure shift spectrum in an amount of time that is shorter than the above-mentioned point-by-point acquisition approach. It has made the concept of pure shift spectroscopy a reliable approach for analyzing "real" complex mixtures, among which biological samples. A more detailed review of this approach can be found in Meyer and Zangger. [20, 21] owever, because each pure shift signal from the resulting spectrum is generated by a restricted region in the sample, the sensitivity of the ZS element is low compared to that of the standard 1 H NMR spectrum that can be recorded on the same sample.
The pure shift 1D signal is then generated by the 45 projection of the diagonal peaks from the anti z-COSY 2D map, using a suitable signal processing to remove unwanted peaks. Although this method allows for recording a clean pure shift spectrum, it should be noted that (1) it yields a reduced sensitivity and (2) it requires the implementation of more complex acquisition schemes as well as data processing. A more detailed review of this approach can be found in Adams. [43] As for the ZS method, the inherent limitations of this approach have prevented its widespread use in metabolomics, although it has been successfully applied to obtain the pure shift spectrum of biologically relevant compounds such as quinine or the steroid dehydroisoandrosterone. [42]  In the following, we will describe how the concept of the implementation of a low-flip angle pulse as a method for refocusing J-couplings, and its combination with an averaging process to suppress unwanted signals, allows for recording pure shift spectra in a very efficient manner.
The combination of these chirp pulses with a pulsed field gradient allows for selecting the desired pure shift signal while modulating the phase of unwanted ones throughout the sample, which leads to their cancelation. As for the Zangger-Sterk method, PSYCHE experiment is recorded using an interferogram mode. The outcome of the acquisition is a series of data chunks from which the pure shift signal can be reconstructed. A more detailed review of this approach can be found in Foroozandeh et al. [23]  One key feature of the PSYCHE method is the tradeoff that has to be found between spectral purity and sensitivity, which can be critical for some complex samples. First, while pure shift signals in PSYCHE have intensities proportional to sin 2 β, they are flanked by intrinsic artifacts arising from an imperfect decoupling with intensities proportional to sin  4  β.
| Real-time decoupling pure shift experiment As described above, most of the pure shift spectra are recorded using an interferogram method, which allows for limiting the overall acquisition time needed to F I G U R E 3 Schematic diagram of PSYCHE pulse sequence. On the proton channel ( 1 H), black rectangles correspond to a hard π pulse. The trapezoids with diagonal arrows correspond to frequency-swept (chirp) pulses from the homonuclear decoupling block. On the pulsed field gradient channel (PFG), the rectangular shape is a weak gradient pulse. gather all the data chunks that are necessary to reconstruct a pure shift signal. Another acquisition scheme has gained attention in recent years, which is based on a windowed acquisition of the data chunks. The particularity of this method also known as real-time decoupling is that the signal is recorded in a single experiment.
| Comparison of the main pure shift methods: Lineshape and sensitivity As stated above, resolution enhancement is the key feature of pure shift methods, which can clearly benefit countless applications. Although most of the studies performed in the field of metabolomics to date are using standard  1  H NMR experiments for metabolic profiling purposes, there is an emergent community that is exploring the benefits of using complementary datasets such as spectra yielded by J-resolved or pure shift pulse sequences. Figure  4  shows the comparison between the standard 1 H spectrum and the pure shift 1 H spectra that were recorded using the most robust techniques presented above, on a model mixture of 14 metabolites: the 1D projection of a J-resolved spectrum (1D pJ-res) and the spectra recorded using the PSYCHE and PSYCHE-SAPPHIRE pulse sequences.
The authors have analyzed samples prepared with tea extracts and honey samples dissolved in deuterated buffer to address adulteration or food origin issues. They have shown that the identification of the major components present in these samples is greatly improved on PSYCHE pure shift spectra (Figure  5a ). It should however be noted that although a large fraction of the observed resonances could be successfully identified and assigned, the lower sensitivity of PSYCHE data (tenfold lower than for a standard experiment) and the presence of periodic sidebands resulting from the chunck acquisition scheme have limited the identification of minor components. Nevertheless, the statistical analyses that were made on pure shift data showed the same quality as the ones led on standard data (Figure  5b ).
Furthermore, Stark et al. [45]  showed that data binning, which is a key step of the data pre-processing that is needed for a statistical analysis, can benefit from the resolution enhancement that is achieved in pure shift experiments. They have performed a uniform bucketing of PSYCHE NMR data recorded on methanolic plant extracts and tested three different common bucket sizes used in metabolomics. They have shown that the data reduction provided by pure shift experiments simplifies the data exploration because one bucket contains typically only one signal (Figure  6 ). Despite the reduction of noisy variables, the quality of the multivariate models calculated from these data was found to be equivalent to those generated from standard 1D 1 H NMR spectra, probably due to the selected bucketing protocol.
ACKNOWLEDGMENTS X. C. acknowledges support from the  China Scholarship Council  for her PhD studentship funding (No. 201906810024 ). This work was supported by a grant from  ITMO Cancer of Aviesan  ( 21CP089-00 ) within the framework of the 2021-2030 Cancer Control Strategy, on funds administered by  Inserm  to N. G. The authors thank funding SESAME 2017 through convention EX023598 for MétaboParis-Santé. The authors thank  Veronique Baud  and  Aurélie Montagne  ( NF-κB, Différenciation et Cancer, Université Paris Cité, F-75006 Paris, France ) for scientific discussions and providing samples that supported the mentioned applications.
This made it possible to constitute a reference base for the invertebrates in the ponds by linking the reference specimens with their morphotaxon names. Each specimen of each sample was then identified using books, websites and the reference base. All specimens were counted by morphotaxa for each sample. Determination of water and sediment quality parameters, including trace elements and organic pollutants Samples were used to determine the main physicochemical parameters, including major and TE as well as organic contaminants (PAH, pesticides and pharmaceuticals) as described in  Nélieu et al. (2020). For water samples, the following determinations were measured directly on site with probes: pH, conductivity, temperature, dissolved oxygen (DO) and turbidity. Other data were obtained rapidly in the laboratory (mainly within a day of sampling) using standardised methods: dissolved organic carbon (DOC) by thermic oxidation and IR analysis of carbon dioxide, chemical oxygen demand (COD, norm NF EN ISO 15705), suspended solids (SS, norm NF EN 872), nitrates (NO3 -, norm NF EN ISO 10304-1), nitrites (NO2 -, , NF EN ISO 26777), total nitrogen (TN) from the addition of Kjeldahl nitrogen (Kjeldahl method, norms NF EN 25663 and NF EN ISO 11732) with nitrates and nitrites, total phosphorus (P, norm NF EN ISO 15681-2 and NF EN ISO 6878.
Statistical analysis Prior to the data analysis, the invertebrate samples collected from both points in each pond were pooled. This allowed us to produce a contingency table containing the number of each morphotaxon for each pond and each sampling date. For the water quality parameters, TE and organic pollutants, we computed the mean of the two sample point values. All statistical analyses were performed with R 3. 6. 1  (Team, 2020). To explore invertebrate community diversity, we computed the morphotaxa richness (alpha diversity), Shannon diversity index and evenness for each pond and each field campaign with the specnumber function in vegan 2. 5-6  (Oksanen et al. , 2019). We tested the effect of individual ponds and field campaign on these parameters with an analysis of variance followed by a pairwise comparison with Tukey's HSD test.