dataesr/scientific-paragraphs-categorization huggingface dataset:
Our centering method has been delivered and integrated in the SPHERE Data Center (see Appendix D for more details and results). After this pre-reduction step, raw observations were assembled in calibrated A(S)DI datasets. Each pre-reduced IRDIS observation is composed of L = 2 spectral channels that are processed both independently (i. e. , akin to ADI sequences) and jointly (i. e. , akin to ASDI sequences). Each pre-reduced IFS observation is composed of L = 39 spectral channels that are processed jointly. All pre-reduced datasets are first processed by the PACO pipeline (see Sect. 4. 3), whose byproducts are then used by the proposed PACOME algorithm, see Sects. 4. 4 and 4. 5.
Reduction with PACO The calibrated A(S)DI datasets described in Sect. 4. 2 were processed with the PACO algorithm to produce, for each epoch, the a t,ℓ and b t,ℓ maps. These outputs serve as inputs of the PACOME algorithm (see Sect. 2. 1). As discussed in Sect. 2. 2, for the reduction of ASDI datasets, it is possible to enforce one or multiple spectral prior(s) γ ∈ R T L to boost the S/N of detection of pointlike sources having a similar spectra 11. For ASDI processing of IRDIS observations, we chose seven spectral priors for the source corresponding to slopes of 0. 25, 0. 5, 0. 75 and their opposites, namely, priors (1, 1), (1, 0. 25), (0. 25, 1), (1, 0. 5), (0. 5, 1), (1, 0. 75), (0. 75, 1). For the IFS observations, we chose 23 spectral priors that are representative of the variety of potential exoplanets spectra, as described in  Chomez et al.
Description of the datasets and of the injected orbits To quantify the efficiency of PACOME, we tested it on a semisynthetic benchmark. We built "fake epochs" by resorting to the injection of synthetic sources on a dataset of HR 8799 observed with IRDIS in 2016-11-18 (see Table  4  for the observations logs). By selecting individual frames from this reference dataset, we built nine fake epochs totalling 5. 12 h of observation time and spanning over 59 yr. The ADI rotation angles of each fake epoch were chosen in the opposite direction of the original ones, so that signals from real exoplanets were not constructively coadded via the derotation and stacking of the individual frames. The total field of view rotation was set to ∆ par = 67. 34 • for each epoch. We injected four sources, denoted as (1), (  2 ), (3), and (4) in the following, on known orbits at the corresponding epochs via a PACO subroutine using the measured off-axis PSF of the reference cube.
Results of the search To detect multiple sources, we adopted a simple greedy strategy: finding the brightest of the four planets with a first search, estimating its orbit, masking its footprint in PACO's byproducts, b t,ℓ , restarting the search for next brighter source, and so on. A summary of the explored search space for the four soughtfor sources is given in Table  6. We used the best cubic cardinal spline derived in Sect. 3. 4. 1 for the interpolation process. In total, N orb ≈ 17 × 10 10 orbits were tested, taking 44 h of CPU time on our local computer using 12 threads. For each search, the first N opt = 10 3 best on-grid orbits were optimized locally and the best of all was retained as the most plausible orbital candidates. The volume of the data is fixed and totals about 10 6 pixels per epoch for IRDIS.
Finally, Fig. 9  shows the cost function maps around the optimal solution estimated by PACOME. All signals in the field that are not at the source positions combine weakly (from blue to white colors, below the set confidence level at ρ = 2. 33 × 10 -12 ). However, because the sought-for signals are very faint and that the hypothesis of independent spectral channels is not perfectly verified, we sometimes recombine noise or speckles in the background. We show in Sect. 4. 5. 2 that explicitly accounting for the spectral correlations reduces this side effect. In any case, the optimal solution found by PACOME still matches its best with the ground truth. It is worth noticing that the method is very efficient at recovering injected sources that would have remained undetected otherwise. In particular, those are (  2  In this section, we demonstrate the efficiency of the method on real A(S)DI data of HR 8799 acquired with SPHERE-IRDIS.
0, 2. 2, 2. 4, 2. 3 and their multi-epoch S/N are 18. 5, 9. 9, 10. 5, 10. 2, from source (1) to (4), respectively. This means that switching from monoepoch to multi-epoch yields a mean S/N gain of about 4. 5, which behaves (as theoretically expected) as the square root of the number of degrees of freedom ( √ T × L = √ 18 ≈ 4. 2). This illustrates a key property of PACOME: it is indeed able to combine optimally the source signals of single-epoch datasets. For completeness, we notice in practice that the values of the criterion associated with the optimal orbits found by PACOME are very slightly larger than the theoretically expected ones for the injected orbits. This is due to the presence of noise in the data. Indeed, the algorithm maximizes the signal around the optimal positions found and, thus, it captures the random noise realizations that co-add positively with the signal.
It is worth noticing that the method is very efficient at recovering injected sources that would have remained undetected otherwise. In particular, those are (2), (3), and (4), whose S/N values are below 5 for all individual epochs. In this section, we demonstrate the efficiency of the method on real A(S)DI data of HR 8799 acquired with SPHERE-IRDIS. The four exoplanets have already been detected in each of the individual epochs and spectral channels, hence, the following results show the ability of the algorithm to find matching orbits, rather than to (re)detect the sources. The orbital elements search space is summarized in Table  8. It was deliberately chosen to cover a wide field of view encompassing all four known exoplanets. The cost function was evaluated for 20. 5 × 10 9 orbits in total.
Benefits of accounting for spectral correlations At the end of Sect. 4. 4. 2, we discuss the fact that PACOME still managed to find the ground truth even though the hypothesis of independent spectral channels was not perfectly verified. The spectral correlations were in fact negligible because SPHERE-IRDIS data only feature L = 2 spectral channels. On the other hand, SPHERE-IFS data have L = 39 different spectral channels; thus, the spectral correlations are much stronger and it becomes essential to take them into account before carrying out the multi-epoch combination. To illustrate the importance of whitening the data spectrally, we show in Fig. 14  the 2D maps of the multi-epoch criterion centered on the positions of HR 8799 c, d, and e, described in the section above for IFS data combined with and without the spectral correlation corrections.
When we are not taking the spectral correlations into account, a larger number of structured patterns (noise and/or speckles) are combined positively and increase the A38, page 18 of 30  Dallant, J. , et al. : A&A, 679, A38 (2023)   background signal, thereby going above the prescribed detection level. Explicitly accounting for the spectral correlations reduces this side effect greatly so that solely the real known sources lie above the set detection limit. We quantified the importance of accounting for the spectral correlations of the data by counting the number of false alarms (considering circular patches of the size of the FWMH) in the criterion map of the multi-epoch SPHERE-IFS dataset of HR 8799. This study was carried by accounting for the spectral correlations and by ignoring them for different confidence levels and the results are plotted in Fig.
Search for a fifth planet Several dynamical studies suggested that a fifth companion could orbit HR 8799 either in the outer region of the system (beyond HR 8799 b) between 90 and 110 au  (Zurlo et al. 2022)  or in the innermost part (before HR 8799 e) between 7. 5 and 9. 7 au  (Wahhaj et al. 2021). We probed these two regions with PACOME to seek a potential candidate or to put constraints on its potential presence. Derivation of the multi-epoch contrast. Building contrast curves is not straightforward when combining multi-epoch direct imaging observations and should be considered with care. With mono-epoch datasets, the achievable 5σ contrast is classically quantified at a given angular separation; whereas in a multiepoch framework the combined contrast is computed for a given orbit where the angular separation of the source may vary along its trajectory.
The computed mono-epoch and multi-epoch 5σ contrasts curves are given in Fig. 16  and compared to  Wahhaj et al. (2021)  who presented the deepest contrast limits to date constraining the presence of a potential additional inner planet. Their datasets consist of 4. 5 h of observations in K1-K2 band with IRDIS and Y-H band with IFS. Our work combines more datasets (23 for IRDIS, 15 for IFS) and achieves an even deeper contrast at all separations. Outer part. The search in the outer part was carried out in ASDI mode with the SPHERE-IRDIS data because the region is not covered by the field of the IFS. We used a combination of (i) the 13 spectrally whitened dual-band datasets reduced with a flat prior spectrum and (ii) the first spectral channel of the 10 remaining broad-band datasets (as both channels carry more of less the same information).
Inner part. For the search in the inner part of the system, we used the 15 SPHERE-IFS data described in Table  4. The three known visible sources were masked. Similarly, a part of the region under the coronagraph (80%) was masked since the transmission is very low in this area. In total, N orb = 5. 44 × 10 8 orbits were explored, probing the semi-major axis parameter A38, page 19 of 30  Dallant, J. , et al. : A&A, 679, A38 (2023)  IFS IRDIS Fig. 16. Mono and multi-epoch 5σ contrast curves of the IRDIS (left) and IFS (right) datasets of HR 8799 in ASDI mode with flat spectral priors. The multi-epoch contrast is computed as a function of the separation assuming face-on circular orbits and a source flux constant over the epochs. The 5σ contrasts found in  Wahhaj et al. (2021)  were extracted and overplotted for comparison.
space from 122 to 246 mas, eccentricities from 0 to 0. 5 and the same as the outer search for the remaining orbital elements. The confidence level was set to ρ = 0. 1/N orb = 1. 8 × 10 -10 yielding a detection threshold of Q corr 15 (1ρ) ≈ 69. 5. The multi-epoch contrast limit is σ(µ) = 2. 4 × 10 -6 for these separations (see Fig. 16 ). Among the 23 spectral priors used for the IFS data reduction step, only 4 (respectively one flat, two bi-modal, and one tri-modal priors) show optimized orbits with multi-epoch scores 2 to 11% greater than the prescribed detection threshold. None of the best orbits found for each spectral prior are alike or have the same projected positions on the detector. A closer inspection reveals that for each of the four identified priors the multi-epoch score is only driven by a handful of epochs (two or three).
No signals were found above the detection threshold considering the 13 dual-band datasets only. Taking the broad-band ones into account led to a few multi-epoch detections but all were ruled out because only driven by a mono-epoch false alarm detection near the coronagraphic mask in the 2017-10-12 epoch. Again, PACO suffers from the above-mentioned phenomenon close to the coronagraph, so if there is a false detection in a mono-epoch PACO map, it will inevitably yield a false alarm in the multi-epoch case.
We obtained a gain in terms of detection sensitivity very close to the square root of the number of epochs, which corresponds to an optimal combination of the available information. As a case-study example, we applied PACOME on 23 VLT/SPHERE observations of the HR 8799 star. From these observations, we were able to re-detect the four known exoplanets at unprecedented levels of confidence (from S/N = 231 for planet e to 530 for planet b). In addition, we obtained the deepest level of contrast especially at close angular separation (3. 0 × 10 -6 for IFS and 1. 7 × 10 -6 for IRDIS at 0. 125 ′′ ) by combining all the available VLT/SPHERE datasets for this system. We believe that the high detection sensitivity of PACOME opens the door to a massive re-exploration of the archived high contrast observations, possibly from different instruments.
D. 3. Implementation details of the fitting procedure The satellite spots are extracted in 30 pixels-wide squares (i. e. , P = 900) centered on their theoretical positions (≃ 14 λ/D away from the theoretical rotation center). For IRDIS data, if a satellite fit does not converge 13  , a median spatial filtering is applied to the extracted sub-images, d, of the satellite spots and the fit is reprocessed on them. For IFS data, the nuisance component is stronger so the median spatial filter is always applied. A circular mask is also systematically applied to the extracted sub-images, d, of the satellite spots to reduce the effects of stellar leakages in the corners. If some satellite spots are not fitted correctly, the rotation center is estimated from the remaining ones. Given the information on the spots orientation (" + " or "+" shape) and on the width of the spectral band (dual band or broad band) retrieved from the dataset header, some parameters are fixed in the optimization procedure (e.
D. 3. 1. Application on SPHERE/IRDIS datasets We illustrate the importance of a proper centering with two datasets from HR 8799 acquired with the IRDIS instrument: an observation of 2015-07-30 in the J2-J3 spectral band, and an other of 2015-07-31 in K1-K2. More information regarding these observations can be found in Table  4. We applied our centering method to both datasets, and we measured for each frames the distance of their rotation center with respect to the theoretical rotation center. The obtained results are given in Figs. D. 2a and D. 2b. In addition to these measurements, the gain in terms of S/N of detection after post-processing with the PACO algorithm of the datasets before and after centering are given in Tables D. 3. 1 and D. 3. 1). For the observations of 2015-07-30, about a third of the ASDI sequence is offset by half a pixel, which strongly impacts the overall S/N of the four sources.
Indeed, the centering procedure leads to a gain in S/N ranging from 4. 3 % to 15. 7 % in the two spectral channels. The observation of 2015-07-31 displays smaller, but yet non-negligible, gains in the overall S/N with the recentered dataset (0. 8 % to 2. 9 %) due to the fewer number of frames impacted by a significant shift. Notes. The S/N maps were computed with PACO before (denoted "Old") and after (denoted "New") centering the IRDIS HR 8799 datasets of 2015-07-30 and 2015-07-31, see Table  4  for observation logs. A38, page 26 of 30 and 529. 9. For the first case, the S/N gain brought by PACOME is very close to the theoretical gain in √ T that is expected when combining optimally T (independent) datasets. For the second case, the gain does not scale as √ T but, again, this is expected as the data is very heterogeneous in quality (see Sect.
This work has been supported by the  French National Programs (PNP and PNPS) , and by the  Action Spécifique Haute Résolution Angulaire (ASHRA) of CNRS/INSU  co-funded by  CNES. This work used ESO archive data for HR8799 from various observing programms with ESO-IDs listed in Table 4. A38, page 22 of 30 Dallant, J. , et al. : A&A, 679, A38 (2023).
All the observations are performed with the apodized Lyot coronagraph (APLC; Carbillet et al. 2011) of the VLT/SPHERE instrument. Both seeing and coherence time come from SPARTA estimations except for the observations of 2014 and 2016 where ESO's Astronomical Site Monitor estimations were used. The central wavelengths of the J, H, H2, H3, K1 and K2 filters are λ = 1. 245, 1. 625, 1. 593, 1. 667, 2. 110, and 2. 251 µm respectively. The IRDIS epoch in boldface is used in Sect. 4. 4 as a reference dataset to build nine semi-synthetic epochs. References. (1) Zurlo et al. (2016); (2) Langlois et al. (2021); (3) Biller et al. (2021); (4) Wahhaj et al. (2021); (5) Zurlo et al. (2022).
In the actual demonstration, each frame was directly projected onto the DM and was replayed, not projected on the LDFC control modes. The closed-loop speed was ∼30 Hz, which included injecting the aberration, taking an image, deriving, and applying the DM command for the correction. Because we implemented the closed-loop tests using Python, the loop speed was limited by ∼30 Hz. However, the loop speed can easily be increased up to a few tens of kilohertz using the CACAO open-source package. For comparison, we show open-and closed-loop images, each with an average of 1000 images in Fig. 17. The quasi-static speckles are significantly removed in the closed-loop case. The residual small amplitude speckles remain. They are caused by noisy higher modes, which can be optimized by the modal cutoff and binning.
Acknowledgements. This work was supported by  NASA's   Strategic Astrophysics Technology (SAT) exoplanet program  (grant # 80NSSC19K0121 ). The development of SCExAO was supported by the  Japan Society for the Promotion of Science  ( Grant-in-Aid for Research  # 23340051 , # 26220704 , # 23103002 , # 19H00703  & # 19H00695 ), the  Astrobiology Center of the National Institutes of Natural Sciences, Japan , the  Mt Cuba Foundation  and the director's contingency fund at  Subaru Telescope. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Mauna kea has always had within the Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. K. A. acknowledges funding from the  Heising-Simons Foundation.
| Participants The SAGE survey initially included 3056 young adults (including 1834 men; mean age 20. 4 years, standard deviation 1. 4; median age 20). In the present study, we included those aged between 18 and 21, who had consumed alcohol at least once and had at least three Caucasian grandparents (to limit genomic background heterogeneity). Subjects who were adopted were excluded, as well as subjects with no information available for gender, or with non-exploitable DNA. As a result, the studied subsample counted 1841 young adults (see Supporting information, Figure  S1 ). For each subject, incoherent data between questions were censored (7842 values out of a total of 984 032 values, 0. 80%). All participants signed a written consent to participate after a detailed explanation of the protocol.
| Analyses Statistical analyses were performed using R version 4. 0. 4 and R Studio software version 1. 4. Qualitative variables were described as numbers (N) and percentages (%). Quantitative variables were described as mean ± standard deviation (SD). To account for multiple comparisons, we applied Holm-Bonferroni correction. Allele carrier frequencies were compared between subjects with and without addictive disorders (i. e. , harmful alcohol use, nicotine dependence or cannabis dependence), as well as between subjects with or without potential risk factors of harmful alcohol use (i. e. , gender and school absenteeism), by using chi-squared tests and odds ratios (95% confidence intervals). To test allele frequencies in nicotine dependence or cannabis dependence, the subsamples were limited to the 1354 or 928 subjects who had ever consumed nicotine or cannabis, respectively (nicotine subsample mean age = 19.
90 ± 0. 8; cannabis subsample mean age = 19. 95 ± 0. 8). Furthermore, as quantitative risk factors did not systematically have normal distributions, means were compared between allele carriers and non-carriers by using Mann-Whitney U tests. Haplotypic analyses were performed using Haploview software version 4. 2 for the SNPs that showed a significant association with harmful alcohol use (i. e. , DRD2 rs6277 and DRD2 rs1800498). Haplotype frequencies were compared between subjects with and without harmful alcohol use, nicotine dependence or cannabis dependence. Linkage disequilibrium was also computed to assess the non-random association of DRD2 rs6277 and DRD2 rs1800498 on chromosome 11. A D 0 value close to 1 indicated a strong linkage disequilibrium.
Socio-economic and clinical characteristics (potential risk factors) in subjects with and without harmful alcohol use were compared using either chi-squared tests for qualitative variables or logistic regressions for quantitative ones. Interactions between significant risk factors and the DRD2 SNPs were tested with a logistic regression. Finally, structural equation modelling (SEM) was used to model relationships between the dependent variable (harmful alcohol use) and independent variables. This multivariate statistical analysis technique, which includes simultaneous regressions, enables to test the direct and indirect effects on pre-supposed causal relationships. 36 In the present study, we performed a path analysis (which is a specific SEM) using the R package 'Lavaan' to model the effects of DRD2 gene on harmful alcohol use.
We included in the model the dependent variable (harmful alcohol use) and the independent variables that were significantly associated with harmful alcohol use and with the DRD2 gene variants. These variables were normalized before being included in the model. The 'Lavaan' package uses the maximum likelihood estimation method to get maximum likelihood parameter estimates, handle missing data and provide goodness-of-fit indices. A series of measures were used to evaluate model fit: comparative fit index (CFI) > 0. 95, Tucker Lewis index (TLI) > 0. 95, root mean square error of approximation (RMSEA) < 0. 05 and standardized root mean square residual (SRMR) < 0. 08.
Second, our data come from self-questionnaires. This is once again due to practical reasons, because data had to be collected in just a couple of days from a large number of participants. However, all of these questionnaires are validated and commonly used, which should reduce the risk of bias. Third, we had no data about the timeline of psychiatric and addictive disorders, preventing us from determining which disorder came first and whether harmful alcohol use caused or resulted from the associated disorders. Fourth, it would have been interesting to see the role of DRD2 rs1800498 in genome-wide association study (GWAS). However, because of its moderate effect size in our study and especially as its effect involves other factors, we would not be surprised if this SNP had a very small odds ratio.
Individuals afflicted by neurodegenerative conditions such as amyotrophic lateral sclerosis may eventually reach a point where they lose the ability to communicate with the outside world through conventional muscular pathways. In these cases, brain-computer interfaces (BCIs) can be a suitable alternative, as they directly transform brain activity into external commands. A P300-based speller is a BCI for communication purposes. The most popular software platforms used to develop spellers are BCI2000 and Open-ViBE. However, these platforms can be relatively complex to set up without advanced technical knowledge. For this reason, the UMA-BCI Speller platform was recently developed, intended to facilitate the control of the system. Hence, the objective of this research was to assess and compare the user-friendliness of the three platforms put forth.