dataesr/scientific-paragraphs-categorization huggingface dataset:
To facillitate the scoring process, actimetry signals were calculated for the eyes, irises, and bill region and visualized together with the video recordings. NREM sleep was characterized by bilateral eye closure, stable breathing (as visible in the videos and bill actimetry signals), immobility of the eyes, and absence of bill movements other than those related to breathing. REM sleep was characterized by bilateral eye closure with movements of the eyes, bill, and/or the collapse of head feathers held erect during preceding NREM sleep. As described previously  45  , rapid constrictions and dilations of the iris are closely associated with REM sleep. Thus, rapid iris movements were also used to identify bouts of REM sleep and their absence to con rm NREM sleep. EEG data processing. The EEG data was analyzed using custom Matlab (v2020b) scripts.
0. 9), the Analysis of Functional NeuroImages (AFNI, version 20. 0. 09 https://afni. nimh. nih. gov/), and Advanced Normalization Tools (ANTs, http://stnava. github. io/ANTs/) software. A standard pipeline was used to pre-process the rsfMRI data. Prior to any preprocessing steps, the DICOM images were converted to 4D NIFTI data (using the dcm2nii function), and the voxel size was upscaled by a factor of 10 (using the 3dre t function of AFNI). The censoring of high motion frames was applied to estimate the amount of head movement within each resting-state time series  51. The threshold for framewise displacement (i. e. , volume to volume movement) was set as 0. 9 mm (less than 20% of voxel size). The results indicated that only 25 volumes of all 29 rs-fMRI sessions had an FD-value higher than 0.
To consider the respiratory-related artifacts, voxel-wise regressors for physiological noise based on respiratory signals were generated using the PNM tool in FSL  54  by calculating the respiratory phases relative to each volume and slice in the rs-fMRI signals. We then co-registered each rs-fMRI data to the corresponding T2-weighted anatomical images using a ne linear registration (12 degrees of freedom). A population-based template was generated using antsMultivariateTemplateConstruction. sh script  55. After analyzing individual subjects, the results were normalized to the population-based template using FMRIB's Nonlinear Image Registration Tool (FNIRT)  56  for group analysis. For visualizing the results, the group results were non-linearly warped to the highresolution post-mortem anatomical image.
3D MRI images were visualized using the MANGO software (http://ric. uthscsa. edu/mango/, version 4. 1). ROI de nition. The fourth ventricle (IV), its extension into the cerebellum, namely the cerebellar recess (CR), and the gray matter mask were de ned anatomically in the high-resolution anatomical image (from the perfused animal). The brightest voxels in the anatomical image were selected to identify the position of IV and CR. The CSF masks were selected from the bottom slices of the rs-fMRI data to ensure high sensitivity of the 2D rs-RARE images to the CSF through-slice in ow effect as mentioned previously  7, 28. Since there is no blood in the CSF regions, the fMRI signal changes in these regions are mainly due to variations of the in ow of fresh spins into the imaging volume  7, 57. This in ow effect size is much stronger at the edge of the imaging volume because the fresh spins arriving have not yet experienced magnetization saturation due to the radiofrequency pulses  57.
Statistics and All mixed model analyses were performed in R using the lmer package. The other statistical tests were performed in MATLAB (v2020b). The level of statistical signi cance was set to p < 0. 05. The number of NREM and REM sleep bouts in the two analyzed sessions was tested using a paired Student's t-test. To assess whether the sound stimulation (to awaken the birds) in uenced the EEG activity in the hyperpallium (the primary visual area), we calculated the average power in the delta band (0. 5-4 Hz) 20 s before and during the stimulation ( g. S8). The effect of the stimulation was calculated using linear mixed effect models, with the average delta power before, or during the stimulation as the response variable, the condition (stimulation vs non-stimulation) as a predictor, and the bird identity as a random effect.
Code availability FSL (https://fsl. fmrib. ox. ac. uk/fsl/fslwiki/FSL, version 5. 0. 9), the Analysis of Functional NeuroImages (AFNI, version 20. 0. 09 https://afni. nimh. nih. gov/), and Advanced Normalization Tools (ANTs, http://stnava. github. io/ANTs/) software and MATLAB (v2020b, MathWorks, USA) were used to process fMRI and EEG data. Codes for fMRI data processing are available at https://github. com/mehdibehroozi/sleeping_pigeon_fMRI.
Our goal is also to assess the relative sensitivities of climate velocities of the metabolic index to temperature and oxygen changes (e. g. differential climate sensitivity), considering current uncertainties in the trajectory of the SEP OMZ in the warmer climate  (Oschlies, 2018) , in order to explore where changes in habitat are more likely to be temperature or oxygen-driven. While most results are based on a model marine species with a mean ecophysiotype, we contrast them with those of a real species for which sufficient information is available to derive the metabolic index, the shrimp Oplophorus spinosus inhabiting oxygenated waters. Along with the results and sensitivity tests to values of the physiological traits, these are used as material for discussing implications of our work. The paper is structured as follow: Section 2 provides an overview of the dataset and methodology.
In other terms, it is the threshold to maintain a population and as such, delimits geographical viable habitat. A 0 , E 0 and F crit define an ecophysiotype unique to each species. From the most updated database  (Deutsch et al. , 2020) , out of 71 species documented, we found estimates of A 0 , E 0 and F crit for only 6 species present in the SEP: 2 cephalopods (Dosidicus gigas and Octopus vulgaris) and 4 crustacea (Gaussia princeps, Notostomus elegans, Oplophorus gracilirostris and Oplophorus spinosus). As this represents a limited sample, following Penn and Deutsch (2022), we use a mean ecophysiotype: A 0 = 20 atm - 1 , E 0 = 0. 4 eV and F crit = 3 that is representative of a model species with mean traits of real species populating regions not necessarily in the SEP. A 0 and E 0 are the mean values of physiological traits estimated for 71 species (62 for F crit ), benthic and pelagic, of 5 phyla (Annelida, Arthropoda, Chordata, Mollusca, and Cnidaria) in diverse ocean basins and biomes  (Deutsch et al.
, 2020). In addition, we computed F for the shrimp, Oplophorus spinosus (A 0 = 23. 8 atm -1 , E 0 = 0. 19 eV, F crit = 2. 5). Metabolic traits for the shrimp were measured from animals off Hawaii (see database in  Deutsch et al. (2020) ) residing along a depth range of 140-750m with temperatures in the range 5-24°C  (Cowles et al. , 1991). We assume that these A B D C FIGURE 1 Ensemble mean of oxygen and temperature trends between 2006 and 2100. At 200m (A, C) and 26°S (B, D). For oxygen (top panels), the blue lines represent the projected oxygen isocontours (5 and 45 mmol. m -3 ) for the "present" (mean 2006-2036, dashed) and "future" climates (mean 2070-2100, solid). For temperature trends (bottom panels), the black lines represent the projected temperature isocontours (15°C) for present (dashed) and future (plain) climates.
Data availability statement Publicly available datasets were analyzed in this study. Thisdata can be found here: https://github. com/aparouffe/SEP_ habitability. The datasets used in this study are available at: https://www. cesm. ucar. edu/projects/community-projects/ DPLE/datasets. html The scripts for the climate velocity computations areavailable in a GitHub repository: https:// github. com/aparouffe/SEP_habitability.
Participants Forty-three young adults (10 males) between the ages of 18 and 25 years (mean = 22. 21 years, SD = 1. 9) participated in this study. All participants had normal hearing and normal or corrected-to-normal vision and had no history of neurological or psychiatric illness. Of these 43 participants, five were excluded for having insufficient correct responses in the behavioral experiment (see section 2. 5. Data Analysis), leaving 38 participants (10 males) with a mean age of 22. 23 (SD = 1. 95). According to a standardized handedness questionnaire  (Oldfield, 1971) , the majority (n = 34) were right-handed. The study conformed with the Code of Ethics of the World Medical Associations (Declaration of Helsinki) and was approved by the local research ethics committee (Comité de Protection des Personnes Sud Mediterranée III, Avis N°2020-A03056-33).
1 ). The audiovisual condition consisted of the auditory and visual stimuli presented simultaneously and was always congruent in speed and in movement. In static conditions, the size and volume of static stimuli were constant. The visual stimuli were presented in the center of the screen at a viewing distance of ∼80 cm from the eyes of the participants and were generated with MATLAB Version: 9. 13. 0 (R2022b) (MathWorks, 2022) and the Psychophysics Toolbox  (Brainard, 1997). The stimuli consisted of a disk that was either white on a black background or black on a white background, randomized across blocks of trials, and were presented with a 50% contrast. They were symmetrically expanded from 7°to 13°diameter (looming condition) or contracted from 7°to 1°diameter (receding condition). In the slow condition, the expansion and contraction lasted for 500 ms.
In the fast condition, the movement lasted for 250 ms (i. e. , acceleration ×2 of the slow condition). Then static visual information was added at the end of each visual fast stimulus for the other 250 ms. In static conditions, the size of visual stimuli was constant (see Fig. 1A ). The auditory stimuli differed by 2 dB of those used in the original study of  Cappe et al. (2009). They were presented binaurally over insert earphones (Etymotic model ER3XR; Etymotic, 2023), were 1000-Hz tones composed of a triangular waveform and generated with Adobe Audition software (Adobe Systems Inc. , San Jose, CA, USA). To prevent the occurrence of clicks, 10 ms onset and offset ramps composed the auditory stimuli which were sampled at 44. 1 kHz. The intensity of the tones either increased (looming condition) or decreased (receding condition) by 10 dB approximately linearly during 500 ms in the slow condition.
For this purpose, we assessed the ratio Firmicutes/Bacteroidetes, two main phyla commonly found in the gut microbiota. Firmicutes and Bacteroidetes are phyla of bacteria, which are, for the most part, Gram-positive and Gram-negative respectively. In theory, the ratio Firmicutes/Bacteroidetes should be improved by a protocol performing well for the extraction of Gram-positive bacteria  71. Remarkably, this ratio was increased for the four protocols combined with SPD in comparison to their standard versions, in both 16S and SMS data (Table  2  and Supplementary Table  2 ). To quantify more precisely the SPD effect on microbial community composition, DESeq2 was used to test the differential abundance of taxa between standard vs SPD-combined protocols. For each patient, the relative abundance of the Firmicutes phylum increased significantly, whereas the Bacteroidetes phylum decreased significantly with the use of SPD.
1). The median of the Aitchison distance was divided by 1. 01 between QQ (14. 99) and S-QQ (14. 90), 1. 08 between Z (13. 44) and S-Z (12. 40), 1. 22 between MN (14. 70) and S-MN (12. 01) and 1. 09 between DQ (15. 30) and S-DQ (14. 05). S-MN was the most repeatable protocol, closely followed by S-Z. Protocols overall performance. In our study, eight DNA extraction protocols were evaluated using both wet-and dry-lab criteria, with 16S rRNA sequencing read-outs. To help in data interpretation, we ranked the protocols according to a custom designed scoring system which was assigned to each criterion based on the observed 16S rRNA gene profiling results (Fig. 6 ). For each criterion, a score of 0 (the worst result obtained in our dataset), 1 or 2 (the best result obtained in our dataset) was given.
CDI is a burning issue, as Clostridium difficile, a Gram-positive bacterium, is the leading cause for diseases from mild diarrhea to pseudomembranous colitis in hospitalized patients  75. Fecal microbiota transplant (FMT) is emerging as a new option for recurrent CDI  76. Identifying which bacteria are already present (recipient) and have been transferred (donor) is essential and requires the use of highly sensitive, robust and fast metagenomics techniques  70, 77. In our study, a total of 456 and 56 samples were analyzed using 16S rRNA gene sequencing and SMS respectively, allowing to have an important dataset for comparison results. Even if, as expected, SMS is more sensitive in bacterial detection, our present findings indicate good agreement between the two sequencing methods. However, it is to be noted that only one replicate of the SMS experiment was performed and further validation is needed.
Acknowledgements The authors thank  Cécile Chauvel  ( xDATA Unit, BIOASTER ) for her advice on statistical analyses and  Adrien Villain  ( OMICS Unit, BIOASTER ) for critical reading of the manuscript. We thank  Johann Pellet  and  Pierre Veyre (xDATA Unit, BIOASTER)  for their involvement in the data and computing management and the  IN2P3 Computing Center (CNRS, Lyon-Villeurbanne, France)  for the provisioning and excellent performance of computing infrastructure essential to our analyses.
In the first one, the actinometer and/or its photoproducts are intrinsically fluorescent: the fluorescence intensity changes in accordance with the actinometer photoconversion and the actinometer alone is sufficient to retrieve I. This mechanism is simple but its implementation relies https://doi. org/10. 1038/s41592-023-02063-y in the Supplementary Notes 2 and 7, respectively. Table  1  provides information to facilitate the selection of the most optimal actinometer to use for specific scenarios. The tabulated parameters will enable end users to reliably measure light intensity as long as they follow the reported measurement protocols. To further facilitate the use of these actinometers, we provide online access to the actinometer properties (https://chart-studio. plotly. com/~Alienor134/#/) and to codes and user-friendly applications to process the acquired data without specific installation (https://github.
5). As preliminary application, we used Nit and photosynthetic apparatus to characterize the illumination from purple and red-orange light emitting diodes (LEDs), respectively (Extended Data Figs. 3  and 4 ). Then we turned to the more challenging task of measuring the spectral light intensity of a white LED by using DDAO to implement the protocol for transferring information on light intensity (Fig. 5a , Extended Data Fig. 5  and Supplementary Information Sections 2. 2, 2. 5 and 5. 3). We measured the DDAO fluorescence intensity when illuminated by a blue LED previously calibrated with the Dronpa-2 actinometer, and by the white LED. The ratio of the fluorescence signals obtained was used, in combination with the known light intensity of the blue LED, to infer the light intensity of the white LED.
Discussion The measurement of the absolute flux of light at the sample (Working Group 1) and the assessment of the uniformity of illumination (Working Group 3) are key issues of the QUAREP-LiMi community (Quality Assessment and Reproducibility for Instruments and Images in Light Microscopy; https://quarep. org/) made accessible by fluorescent actinometers  6. After a selection relying on the wavelength to investigate and access to chemical or biological facilities, end users should implement the protocol illustrated in Fig. 1a  and detailed in Supplementary Note 2 on using https://github. com/DreamRepo/light_calibration/ releases/. Alternatively, they should use the commercially available DDAO to retrieve the light intensity of their desired light source after calibrating another light source with the actinometer they can access.
plotly. com/~Alienor134/#/) and codes and user-friendly applications for data processing (https:// github. com/DreamRepo/light_calibration) and (  5 ) easy and fast (less than 1 hour, from sample preparation to data processing) transfer of know-how to end users. Their kinetics-based protocol is notably robust with respect to parameters that may affect fluorescence from the sample  43  and the instrument 44 side  13. In particular, the quantum yield of fluorescence of the actinometer does not enter into the expression of the characteristic time τ. Hence, its temperature and possible wavelength dependence are not detrimental as long as the temperature and wavelength of light excitation remain constant over the measurement. With 20% measurement uncertainty, even a spatial gradient of 20 °C over the distance overcome in time τ by the reporting fluorophore, for example rhodamine B  45  , would not affect the result.
Methods The Supplementary Information starts with a list, which indicates the (sub)sections associated with the supplementary elements of the main text, as well as details on statistical parameters and image processing. It is then divided in two parts: (1) sections 1-3 are dedicated to end users, who want to directly implement the reported fluorescent actinometers; and (2) sections 4-9 contain more advanced information as well as the complete validation of the reported fluorescent actinometers. Codes and metadata for the figures in the main text can be found online, as well as user-friendly tools and how to use them: https://github. com/Dream-Repo/light_calibration and in a mirror Zenodo repository (https://doi. org/10. 5281/zenodo. 7966573).
Acknowledgements We thank  N. Gagey  for providing  Cin ,  S. Bujaldon  for providing Chlamydomonas reinhardtii strains,  S. Lahlou  for the seagull picture used for patterning the light and  A. Jawahar  for useful discussions on the protocol implementation. D. Bensimon ,  C. Boccara ,  P. Dedecker ,  G. Ellis-Davies  and  L. Fensterbank  are acknowledged for manuscript reading and discussions. This work was supported by the  ANR  (grant nos. France BioImaging ,  ANR-10-INBS-04 ;  Morphoscope2 ,  ANR-11-EQPX-0029  and  IPGG ,  ANR-10-IDEX-0001-02 PSL ,  ANR-10-LABX-31  and  ANR-19-CE11-0005  for T. L. S. and L. J. ), the  Federal Ministry of Education and Research of Germany (BMBF)  within the  YESPVNIGBEN  project (grant no. 03SF0576A  for Y. N. ), the  European Regional Development Fund project  ' Plants as a tool for sustainable global development'  (grant no.
Data availability The online repository contains representative raw data files corresponding to the methods described. The datasets generated and/or analyzed during the current study and that are not in the online repository due to their profuse nature are available from the corresponding author on request. Absorption and emission spectra of the actinometers: https://github. com/DreamRepo/light_calibration/tree/main/ spectra_plotly and https://chart-studio. plotly. com/~Alienor134/#/. Metadata for the video acquisitions used to produce the main text figures: https://github. com/DreamRepo/light_calibration/tree/main/ imaging_metadata. Simulations of the illumination used in Fig. 2k, l : https://github. com/DreamRepo/light_calibration/tree/main/Macroscope. Simulation of 3D illumination pattern and comparison with 2D imaging: https://github.
Such temperature-driven metal-insulator and insulator-insulator transitions are generally caused by subtle  changes in the crystal lattice and/or magnetic structure. However, magnetic susceptibility measurements show T II is not coupled to any magnetic transition (Supplementary Figs. 11  and 12 ). Variable temperature powder neutron diffraction data recorded for Ce 0. 96 MnAsO 0. 95 F 0. 05 with T II = 104 K confirm there is no change in the nuclear or magnetic structure at T II (Supplementary Figs. 12-14 and Supplementary Tables  5  and 6 ). Heat capacity measurements on the same sample also show no evidence of any transition at T II (Supplementary Fig. 15 ). Furthermore, high-resolution neutron diffraction data recorded for CeMnAsO 1-x F x (x = 0. 00, 0. 035, 0. 050 and 0. 075) at 300 K and 10 K also show that there is no change in crystal symmetry upon cooling (Supplementary Figs.
Diffraction Room temperature powder X-ray diffraction patterns suitable for Rietveld refinement were recorded on a PANalytical Empyrean diffractometer using a Cu Kα1 source (λ = 1. 54059 Å) between 10 < 2θ < 120°with a step size of 0. 013°. Powder neutron diffraction patterns were recorded on the high intensity diffractometer D20 at the Institute Laue Langevin (ILL, Grenoble, France) with a wavelength of 2. 4188 Å. A 1 g sample of Ce 0. 96 MnAsO 0. 95 F 0. 05 was inserted into an 8 mm vanadium can contained in a cryofurnace and data were recorded between 5 and 400 K, with a collection time of ~20 min at each temperature. Data were also recorded on the high-resolution, two-axis diffractometer, D2B between 3. 5 and 290 K in an 8 mm vanadium can with a collection time of ~3 h at each temperature.
EDS analysis EDS analysis was performed using a field emission gun Carl Zeiss Gemini SEM 300 equipped with an AZtec Energy EDS analysis system with an XMax 80 detector and an AZtecHKL EBSD analysis system with a Nordlys Nano EBSD camera (Oxford Instruments Ltd. ). Energy dispersive spectroscopy (EDS) analysis was performed on CeMnAsO 1-x F x (x = 0, 0. 035, 0. 05 and 0. 075) and Ce 0. 97 MnAsO 0. 95 F 0. 05. For each sample, data were collected on 15 randomly selected crystallites.
Physical property measurements The temperature dependence of the DC electrical resistance, Seebeck coefficient and Hall resistivity of the Ce y MnAsO 1-x F x phases were recorded using a Quantum Design physical property measurement system (PPMS) between 4 and 300 K. The measurements were performed with both the 2-probe and 4-probe methods to ensure the transitions were not a result of instrumental error. From ∼20 K above T II , data were also recorded every 0. 25 K in order to obtain high quality and reliable data around the transition and to fully map out the transition. The temperature and frequency dependence of the AC transport of Ce 0. 96 MnAsO 0. 95 F 0. 05 , Ce 0. 97 MnAsO 0. 95 F 0. 05 and CeMnAsO 0. 0965 F 0. 035 were also recorded between 4 K and 300 K on the PPMS with selected frequencies between 1 Hz and 1000 Hz.
Acknowledgements This research was supported by  EPSRC  (Grant no. EP/L002493/1  (A. C. M. )), The  Carnegie Trust for the Universities of Scotland  (PhD scholarship for S. S. (S. S. )) and the  ILL  (PhD studentship for G. B. L. (A. C. M. )). By the membership of the  UK 's  HEC Materials Chemistry Consortium , which is funded by  EPSRC  ( EP/L000202  (A. W. )), this work used the  ARCHER2 UK National Supercomputing Service  (http://www. archer2. ac. uk). We also acknowledge  STFC-GB  for provision of beamtime at the ILL.
The gene expression data were then analyzed with the PanCancer Immune Profiling Advanced Analysis Module. Activity scores of immune pathways and immune cell abundance were analyzed using either ordinary 1-way ANOVA or the Kruskal-Wallis test. Data are expressed as mean ± SEM. P < 0. 05 was considered statistically significant. *P < 0. 05; **P < 0. 01; ***P < 0. 001; ****P < 0. 0001. NS, not significant.