dataesr/scientific-paragraphs-categorization huggingface dataset:
Stimuli Stimuli were images consisting of a combination of an object and a scene background. All images used to create the stimuli (scenes and objects) were downloaded from the image bank Pixabay (https://pixabay. com/) under Creative Commons Zero license, or from Google Images searches of copyright-free pictures. The scenes used as backgrounds were photographs representing either outdoor natural landscapes (e. g. , savannah, field, park ice), or indoor views (e. g. , living room, corridor). They were converted into 256-level grayscale and rescaled to 1024 3 768 pixels. Stimuli were displayed on a 30-in. monitor (Dell Ultrasharp) with a resolution of 2560 3 1600 pixels and a refresh rate of 60 Hz. We estimated the gamma function of the monitor by measuring the luminance values of the display for different values of uniform gray-level stimuli generated in MATLAB (MathWorks, Natick, MA) with a calibration tool (Spyder5ELITE, Datacolor, Rotkreuz, Switzerland).
Stimuli In the same way as for Experiment 1, we used 20 groups of four object-scene associations. Stimuli were created in MATLAB. We first gamma-corrected each object and pasted it on a 1/f noise image. We varied the visibility of the object by manipulating a phasescrambling parameter. For each object, seven versions of the object-on-1/f image were thus created by parametrically adding coherence in the phase structure of the object, using Ales, Farzin, Rossion, and Norcia's (2012) MATLAB function. This function interpolates the phase of the Fourier transformation between the object-on-1/f image and a noise image of the same size. The seven versions ranged from 0% to 80% of phase coherence (100% being the original object on 1/f noise), increasing linearly in 13. 33% steps (Figure  4 ). We chose to limit maximum coherence to 80% in order minimize the ceiling performance observed in Experiment 1 with fully visible objects.
Procedure The experiment was programmed on E-Prime 2. 0 (E-Prime Psychology Software Tools Inc. , Pittsburgh, PA). Stimuli were displayed on the same 30-in. monitor as in Experiment 1. At a viewing distance of 50 cm, the scenes sized 248 of visual angle horizontally and 188 vertically, the larger side of the objects sized 38, and the circular patch sized about 88. The participant's head was supported by a chinrest in order to maintain distance. They were instructed to maintain their fixation on a little white fixation cross, centered on the screen location at which the object was presented (i. e. , at the center of the screen horizontally and in the lower part vertically). The fixation cross was displayed for a random duration from 500 to 1,500 ms (on average ;1,000 ms) in order to disrupt the predictability of trials' rhythm.
Data analysis For each participant, correct RTs were log transformed and then trimmed by removing trials for which the RT was inferior or superior to the condition average 6 2. 5 SDs (0. 34% of trials were excluded). Data used for the analysis of RT only included phase coherence levels for which mCR (averaged across conditions and participants) exceeded 0. 75 at group level (Levels 4, 5, 6, and 7 of phase-coherence). Weibull psychometric functions were fitted to each participant's mCR through maximum likelihood estimation for the congruent and incongruent conditions of the intact and scrambled scene conditions, as well as for the baseline condition, using the Quickpsy package in R  (Linares & Lopez-Moliner, 2016). For each experimental condition, threshold values were derived from the psychometric functions at a mCR of 0.
The proportion of scene-consistent responses averaged across participants was 0. 54 6 0. 04, and was statistically different from chance level (t[17] ¼ 4. 28, p , 0. 001, d ¼ 1. 01), indicating that when they could not identify any object, participants' responses were in part driven by the scene category. Then, we tested the Kendall correlation between the scene-consistent response index and the congruence effect index calculated on threshold values (incongruent minus congruent) of the intact scene condition. There was no correlation between these two variables (r ¼ 0. 16, p ¼ 0. 36; Figure  5 ). To avoid the limitation of concluding on the null hypothesis, we tested a Bayesian correlation using the Psycho package in R  (Makowski, 2018). This Bayesian correlation analysis indicates anecdotal evidence (BF ¼ 1.
Acknowledgments Alexia Roux-Sibilon  was supported by the '' Alpes Grenoble Innovation Recherche '' grant from the pole '' Chimie-Biologie-Santé '' of  University Grenoble Alps  ( AGIR-POLE CBS ). Louise Kauffmann was supported by the  NeuroCoG IDEX UGA (Initiatives D'EXcellence project of University Grenoble Alps ) in the framework of the  Investissements d'avenir program  from the  Agence Nationale de la Recherche  ( ANR-15-IDEX-02 ). We thank  Valerie Goffaux  and  Kevin Parisot  for their help with the stimuli. Commercial relationships: none. Corresponding author:  Alexia Roux-Sibilon. Email: alexia. roux-sibilon1@univ-grenoble-alpes. fr. Address:  University Grenoble Alpes ,  Univ. Savoie Mont Blanc, CNRS, LPNC, Grenoble, France.
Une étude nord-américaine de registres de cancers et d'infections par le VIH a montré un déclin significatif de 2,8% du taux standardisé de l'incidence du CB entre 1996 et 2010, associé à un déclin significatif entre les mêmes périodes de l'estimation du risque de 4,4%  [9]. L'étude de 84 504 PVVIH de la base de données de la fédération hospitalière française (FHDH) confirme ces données avec une diminution du risque de CB dans la période 1997-2000 de 4,7, dans la période 2000-2004 de 3,8, et dans la période 2005-2009 de 2,8  [10]. Les explications possibles de cette réduction du risque du CB chez les PVVIH sont multiples : -un taux médian de CD4 en augmentation chez les PVVIH grâce aux recommandations de traitement antirétroviral de plus en plus précoce, et donc une amélioration sous-jacente de l'immunité antitumorale -une diminution, comme en population générale, de la prévalence du tabagisme actif.
METHODS: We leveraged the availability of a large-scale open NHP imaging resource to provide an initial examination of individual differences in the functional organization of the NHP brain. Specifically, we selected one awake functional magnetic resonance imaging dataset (Newcastle University: n = 10) and two anesthetized functional magnetic resonance imaging datasets (Oxford University: n = 19; University of California, Davis: n = 19) to examine individual differences in functional connectivity characteristics across the cortex as well as potential state dependencies.
This is understandable, as it is often more tolerable for the monkey and allows for longer scan times and higher-quality data. Nonetheless, differences in FC between awake and anesthetized states have been described  (11) (12) (13) (14) , raising the possibility that patterns of individual variation may also differ as a function of scan state. To accomplish our goals, we leveraged previously collected functional MRI (fMRI) datasets made available through the PRIMatE Data Exchange (PRIME-DE)  (15). Specifically, we used three independent data collections: Oxford University (anesthetized), University of California, Davis (UC-Davis) (anesthetized), and Newcastle University (awake). To facilitate comparison with existing findings in humans, which can provide novel insights into the evolutionary roots of interindividual differences, our examination followed the framework for evaluation of individual variation previously established by Mueller et al.
(2). Specifically, we 1) examined the spatial distribution of intersubject variability in FC while controlling for intrasubject variance, technique noise, and cortical structural profiles; 2) compared intersubject variation maps with maps for cortical structural variation (cortical thickness, curvature, sulcal depth, surface area) and T1w and T2w maps; and 3) compared intersubject variation maps with short-range and long-range FC. None of the three datasets included in PRIME-DE contained both awake and anesthetized data in the same subjects. Nonetheless, we attempted to provide initial insights into the potential impact of anesthesia. We accomplished this by identifying findings obtained using the awake dataset (Newcastle) that differed from findings of both of the anesthetized datasets (Oxford, UC-Davis).
Oxford Data (Anesthetized) The full dataset consisted of 20 rhesus macaque monkeys (Macaca mulatta) scanned on a 3T scanner with four-channel coil. The data were collected while the animals were anesthetized without the contrast agent. Nineteen macaques were included (all males, age 4. 01 ± 0. 98 years, weight 6. 61 ± 2. 04 kg); each had a 53. 33-minute (1600 volumes) scan. One macaque was excluded owing to the failure of surface reconstruction of its structural image.
UC-Davis Data (Anesthetized) The dataset consisted of 19 rhesus macaque monkeys (M. mulatta) scanned on a Siemens MAGNETOM Skyra 3T scanner (Siemens Healthcare, Erlangen, Germany) with fourchannel clamshell coil. The macaques were scanned under anesthesia without the contrast agent. Nineteen macaques were included (all female, age 20. 38 ± 0. 93 years, weight 9. 70 ± 1. 58 kg). One resting-state scan (6. 67 minutes, 250 volumes) was included per animal.
Newcastle Data (Awake) The full dataset consisted of 14 rhesus macaque monkeys (M. mulatta) scanned on a Bruker 4. 7T vertical primate scanner (Bruker, Billerica, MA). We restricted our analysis to 10 animals (8 males, age 8. 28 ± 2. 33 years, weight 11. 76 ± 3. 38 kg) for whom two awake fMRI scans (8. 3 minutes, 250 volumes per scan) were required. The details of the data acquisition and procedures were described in previous studies  (16) (17) (18) (19) (20) (21) (22). No contrast agent was used during the scans.
NKI Data (Awake and Anesthetized) The NKI data consisted of 2 rhesus monkeys (M. mulatta) (1 male, age 6 years, weight 6. 4 kg, marked as NKI-R; 1 female, age 7 years, weight 4. 5 kg, marked as NKI-W). They were scanned on a 3. 0T Siemens TIM Trio scanner (Siemens Healthcare) with an eight-channel surface coil. This dataset was not used for variation analysis but as a complementary dataset, which consists of a large amount of awake and anesthetized data within the same monkey. The data had been preprocessed and used in our previous work  (12). Specifically, we included seven sessions (awake: 224 minutes; anesthetized: 196. 7 minutes) for monkey-W and four sessions (awake: 86 minutes; anesthetized: 108 minutes) for monkey-R. All the included data from the NKI site were collected with the contrast agent ferumoxytol, a monocrystalline iron oxide nanoparticle.
Human Data (Awake) and Processing We replicated prior human findings here by using resting-state fMRI data from an HCP dataset (177 unrelated participants, 79 male, age 29. 03 ± 3. 45 years)  (23, 24). The minimal preprocessing HCP data were temporal filtered (0. 01-0. 1 Hz), smoothed (full width at half maximum = 6 mm), and down-sampled to 10k (10,242 vertices) midcortical surface.
FC Profile To account for the intrasubject variance while estimating the intersubject variability, we first split the data into several subsets for each animal. Specifically, for Oxford data, we split the entire session into five subsets (320 volumes per subset). For UC-Davis data, which has fewer time points, we split the data into two subsets (125 volumes per subset). For the Newcastle data, two scans were originally recorded per animal (250 volumes per scan). To limit the intrasubject variation within the scan, we also split each scan into two subsets (125 volumes × 2 subsets × 2 scans). For the human HCP data, we kept the original four restingstate fMRI scans as four subsets (1200 volumes per subset). Similar to earlier human studies  (25) , we first defined the FC profiles at each vertex as a vector of Pearson's correlations between its time series and the time series of all the regions of interest (ROIs).
Interindividual Variation of FC For each data collection selected from PRIME-DE (Newcastle, Oxford, UC-Davis), we estimated interindividual functional variation at each vertex (Supplemental Figure  S1A ), while controlling for intraindividual variation, technical noise, and cortical structural properties (Supplemental Figure  S1B-D ). In each of the datasets, intersubject variability of FC exhibited a heterogeneous spatial distribution across the macaque cortex. We first replicated the prior human findings based on the HCP data (Figure  2A ). The heteromodal association cortex particular frontoparietal network showed higher interindividual variation than the visual and somatomotor networks. Intriguingly, the interindividual variation was specifically high in the association network borders.
10 vs. r = -. 33) in Mueller et al. (2). In the anesthetized samples (i. e. , UC-Davis, Oxford), no similar positive correlations between either long-range or short-range FC and interindividual variation were found in either Oxford (long-range: r =. 25, p corrected =. 132; short-range: r = 0, p corrected = -84) and UC-Davis (long-range: r =. 16, p corrected =. 7; short-range: r = -. 13, p corrected =. 3) data (Figure  4B, C ). Of note, to avoid the geometrical artificial effects as mentioned in Methods and Materials, the FC at geodesic distance <6 mm was not counted in the short-range FC calculation, which may mitigate the correlation between interindividual variation and shortrange FC.
Quantifying Awake Versus Anesthetized State Differences at the Group Level Our findings for interindividual variation pointed to the importance of state-related differences. Though it was not a primary focus of the present study, we examined the impact of state on group-level findings as well. To gain further insight into the state-related functional differences, we examined the similarity of FC profiles derived from awake and anesthetized samples. The similarity was quantified by Pearson's correlation of FC profiles at each vertex (Figure  6 ). Two specific comparisons were used for the assessment of similarity: 1) the first session from Newcastle (awake) and Oxford (anesthetized) data and 2) the second session from Newcastle (awake) and UC-Davis (anesthetized) data. As the site effect confounded with the state differences here, we made such comparisons to test whether the state similarity could be replicable in independent samples (Figure  6A, B ).
The similarity from these two comparisons showed highly similar patterns (r =. 59, p corrected <. 001). FC profiles in unimodal regions (i. e. , visual, somatomotor networks) were more similar (Figure  6A, B ) between awake and anesthetized samples. The heteromodal networks in general showed higher dissimilarity than unimodal regions. Specifically, the limbic (yellow) network exhibited highest dissimilarity, followed by the ventral salience (red) and default mode networks (magenta); the executive network exhibited lowest dissimilarity among heteromodal networks between awake and anesthetized samples (Figure  6A , B), though still higher than the unimodal networks. To provide further corroborating evidence for state differences, we also quantified state similarity within the same animal using data from two macaque subjects collected at NKI.
Finally, it raises cautions about the study of individual differences in the anesthetized state and the need for further attention toward determining which properties are and are not stable across states as scientists work to put together the pieces across studies and species. Interindividual variation of functional connectivity in the human sample from the Human Connectome Project (HCP) (A), awake macaque sample from Newcastle University dataset (B), and anesthetized macaque samples from Oxford University dataset (C) and University of California, Davis (UC-Davis) dataset (D). To emphasize the overall regional differences and improve the signal-to-noise ratio for macaque samples, we visualized the interindividual variation using the architectonic areas from published atlases  (27, 62). The vertexwise maps are demonstrated in Supplemental Figure  S1A.
awake within one macaque from the Nathan Kline Institute (NKI) dataset (monkey-W), which was scanned with the contrast agent ferumoxytol (monocrystalline iron oxide nanoparticle [MION]); (D) anesthetized vs. awake within one macaque from NKI dataset (monkey-R), which was scanned with contrast agent ferumoxytol (MION). The negative r value indicates the opposite pattern of functional connectivity profile between awake and anesthetized samples. We mapped the top 25% of positive r values (the most similar) in red and bottom 25% of positive r values in yellow and.
ACKNOWLEDGMENTS AND DISCLOSURES This work was supported by gifts from  Joseph P. Healey ,  Phyllis Green , and  Randolph Cowen  to the  Child Mind Institute  and the  National Institutes of Health (Brain Research through Advancing Innovative Neurotechnologies Initiative  Grant Nos. R01-MH111439  [to CES and MPM],  P50MH109429  [to CES],  R01-MH107508  [to DAF], and  P60-AA010760 ,  R01-MH115357 ,  R01-MH096773 , and  P50-MH100029  [to DAF]),  National Institutes of Health  (Grant No. P01AG026423 ), and  Yerkes National Primate Research Center Office of Research Infrastructure Programs  (Grant No. OD P51OD11132 ). We thank the investigative teams from  Newcastle University  ( J. Nacef ,  C. I. Petkov ,  F. Balezeau ,  T. D. Griffiths ,  C. Poirier ,  A. Thiele ,  M. Ortiz ,  M. Schmid ,  D.
The patient underwent an axial high-resolution T2W threedimensional (3D) gradient-echo FIESTA-C sequence at 3T (Signa HDxt, General Electric, *BLINDED*), using an eight-channel head coil. This sequence is a sort of modified steady state free precession sequence, which does not require any contrast injection. The study box was placed parallel to the orbital roof, extended from the orbital roof, downwards on 2. 3 cm. The acquisition parameters were as follows: echo time (TE) = 0. 8-1. 2ms, repetition time (TR) = 7ms, field of view (FOV) = 22× 19. 80 cm, frequency × phase = 484 × 484, flip angle = 60°C, number of excitations (NEX) = 1, bandwidth = 83. 3 kHz, partition thickness = 0. 3 × 0. 3 × 0. 3 mm (isotropic voxel). The acquisition time was 7 min 49 s. The reconstruction of the inner ear was performed through a manual segmentation, on the images of the endolymphatic space and of the sensory zones, using the software ITK-Snap  [10, 11].
This knowledge was used to confirm which voxels were to be part of the segmentation in the SCC. Once the whole volume of the membranous labyrinth was segmented, ITK-Snap software was used to obtain a first representation of its external surface, as a stereolithography (STL) file. This STL file contained a triangular surface mesh and was then imported in the Hypermesh software from the Altair Hyperworks software suite. We identified the different structures of the inner ear in the surface mesh, to classify the triangles in different components. The resulting compartmentalization included: the ampullas, the arms of the semicircular canals, the crista and cupula of each ampulla, the short arm of the posterior canal, the common crus, the utricle, the utricular macula, the saccule, and the saccular macula.
Validity study of the geometry of the 3D model of membranous posterior labyrinth We measured the different parts of the model with the Hypermesh software and compared the values with those in the literature (Figure  5 ). Results are shown in Table  1. Each ampullar crista and cupula is 1. 5 mm long and 0. 3 mm wide  [12]. The average diameter of the lateral semicircular canal ampulla is 2. 1 mm. The diameter of the bony lateral canal in the other parts of the canal is about 1. 3 to 1. 4 mm. The average diameter of the anterior bone canal is 0. 8 mm. These dimensions are close to those mentioned by Veillon  [12]  and Curthoys  [6]. The other dimensions, which were not described in the literature, were measured in a histological atlas of human temporal bone  [4]. These are reported in Table  2.
As some canals showed strong curvatures, the first rendering obtained was irregular and rough in certain places. This is why we had to manually rework the SCCs shape using the Hypermesh software. Some elements have been replaced to fill the gaps and create more regular contours. Additional smoothing of the mesh resulted in a final satisfying render. The study of the positioning of the sensory cristas and maculae has benefited from the unique histological atlas of Sick and Veillon  [4]. These histological sections have the advantage of having been carried out in a radiological cutting plane of the lateral canals, which made it possible to carry out a radiological-histological correlation. These histological sections were made from eight fetal temporal bones of at least 7 months. At this age the inner ear is comparable to that of the adult human, since the development of the inner ear reaches adult size around 17 to 19 weeks of gestation  [5].
Conclusion In this study, we describe a 3D reconstruction of the posterior membranous labyrinth, using in vivo 3T MRI-acquired images of the temporal bone region with vestibular schwannoma. In this patient, the geometry of the vestibule is preserved but the elevation of perilymphatic protides generates an increase in contrast with the endolymph, which allows its contouring. The 3D external volume was obtained by manual segmentation, with the ITK-Snap software. We then achieved a mesh of the model used for the compartmentalization of the various structures. The position of the anterior crista, lateral crista, posterior crista, utricular macula and saccular macula are represented. This model of a 3D posterior membranous labyrinth has the specificity of being morphologically accurate. This model is of pedagogical interest for the teaching of anatomy, of vestibular physiology and of positional diagnostic and therapeutic maneuvers.
The analysis demonstrated that the amount of F. nucleatum gradually increased along the bowel subsites from rectum to cecum in CRC. 68 Among the different ways to explore the tumorigenesis mechanisms of F. nucleatum, the classification of the CRC subtypes by significant clinical, pathological, and molecular features favors the treatment of F. nucleatum-associated CRC disease. The impact of F. nucleatum on the clinical prognosis of CRC was also investigated in 2016. The data revealed that a high amount of F. nucleatum was related to shorter survival duration by the examination of over 1000 CRC cases. In addition, F. nucleatum was only related to MSI-high but not to CIMP-high or BRAF mutation. 11 Hence, there is a possibility for F. nucleatum to be used as a prognostic marker. Oh et al  69  investigated the prognostic impacts of F.
Likewise, psychotic symptoms were mentioned often in reports but too few details were available to reliably make the diagnosis of a primary psychotic disorder in most cases. In addition, it is challenging to establish a diagnosis in many cases based on the paucity of details provided in some of the original case reports and the review nature of our study design. Finally, regarding treatment, the number of patients receiving a given treatment was very limited and different doses and durations of treatment were applied. Treatment responses were also not assessed using standardized or validated measures. As such, insufficient data were available to draw firm conclusions about treatment themes. However, ongoing work is dedicated to establishing formal consensus treatment guidelines based on available evidence from the literature and expert clinician experience.