dataesr/scientific-paragraphs-categorization huggingface dataset:
Technical Validation The oBS gridded dataset. The OBS gridded dataset was constructed utilizing daily rainfall and temperature data from 481 and 147 stations, respectively. In order to validate the quality of the OBS data, we employed the methodology presented in Nguyen-Xuan et al. 36  by randomly selecting 12 stations in the sub-climatological regions in Vietnam (see Fig. 1  and Supplementary Figure  S1 ). These 12 stations were removed from the set of stations used to interpolate the OBS gridded dataset; and with the remaining set of stations, we applied the same interpolation algorithm to create a testing dataset, which we refer to as OBS-WT-12. Monthly rainfall and temperature data from OBS and OBS-WT-12 at these 12 stations during the period of 1980-2014 were compared with the gridded datasets typically used in the study region (Fig.
2 ). These datasets include: (1) the monthly Global Precipitation Climatology Centre (GPCC)  37  , (2) the daily Asian Precipitation -Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE)  38  , (3) the monthly Climate Research Unit (CRU) data  39  , and (4) the daily ERA5-Land data (hereafter called ERA5)  40  , which is the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis. Noting that GPCC only provides rainfall data, while only CRU and ERA5 provide data on daily maximum and minimum temperatures. The horizontal resolution of OBS, OBS-WT-12, and ERA5 is 0. 1°, while APHRODITE has a resolution of 0. 25°, and GPCC and CRU have a resolution of 0. 5°. Figure  2  illustrates the superior performance of OBS over the other datasets based on statistical parameters, namely the root mean square error (RMSE) and correlation (CORR), when compared to in-situ data from the 12 selected stations.
Even without the use of inputs from these 12 stations, OBS-WT-12 outperforms the remaining datasets. For temperature, the correlations of OBS and OBS-WT-12 with in-situ data are approximately equal to 1, while for rainfall, they are greater than 0. 9 across most stations. Meanwhile, the correlation of the remaining datasets is lower, particularly for rainfall across all stations and for temperature at stations numbered 9-12 (Table  2 ), located in the central and southern parts of Vietnam. The value of RMSE varies across stations, with OBS performing the best. For rainfall, OBS-WT-12 has a smaller RMSE than the other remaining datasets, except for the MongCai station where the OBS_WT-12 RMSE is slightly higher. For temperature, the OBS and OBS-WT-12 RMSE outperform the other datasets. At the SinHo station, the RMSE value is much higher than other stations, possibly due to its high altitude of 1529 m, leading to the fact that the observed temperature at SinHo does not represent the temperature of the entire grid.
Noting that we have adjusted the temperature value with its topography dependence when applying the Kriging interpolation method by using an environmental lapse rate of 0. 65 °C/km. In brief, the results from Fig. 2  demonstrate that OBS performs well not only in grids with monitoring stations but also significantly better than the commonly used gridded datasets in the study region over the grids where there are no stations for rainfall and temperature. The CMIP6-VN dataset. Spatial distribution. Figure  3  displays the spatial distribution of observed and modeled 2m-temperature and their difference over Vietnam. The modeled 2m-temperature is derived from the ensemble mean of the 35 BCSD downscaled CMIP6 GCMs described in Table  1  (hereinafter referred to as BCSD-ENS). There are high similarities between the BCSD-ENS and OBS in both training and testing periods.
Usage Notes The sample scripts and the CMIP6-VN products are available for download. The GCM input variables (pr, tas, tasmax, and tasmin) and the gridded observation dataset should be prepared following the guidelines provided together with the script and dataset (please refer to the file readme. txt in the GitHub link). The step-by-step guide to the BCSD process is also described in detail in the readme. txt file. It should be noted that the sample script is prepared for downscaling the ACCESS-CM2 outputs for the 2015-2099 period under the SSP5-8. 5 scenario. The script can be applied for any GCM and any historical/SSP scenario at any time frame with minor adjustments. The CMIP6-VN dataset provides high resolution and multiple climate change scenarios, but it is important to acknowledge its limitations.
Population This is a retrospective analysis performed on a prospectively collected database including all consecutive patients admitted in the single tertiary intensive care unit of hospital Cochin in Paris (France) following cardiopulmonary resuscitation and ROSC. For the present. analysis, we included adult patients still comatose (as defined by a Glasgow Coma Scale [GCS] ≤ 8 with a GCS motor component < 3 and a Richmond Agitation-Sedation Scale RASS ≤ -4) 48 hours after sedation weaning, who undergone a standard EEG for neuroprognostication. We excluded patients investigated for brain death diagnosis, patients awake before EEG, and patients who died within 48 hours after CA before a reliable neurological examination could be performed.
Data collection Data regarding patients' characteristics, pre-admission and ICU management were collected following the Utstein style. In addition, pre-exposure to beta blockers, ongoing sedation and/or catecholamines at the time of EEG/ECG acquisition were also recorded, as well as length of stay in ICU, vital and neurological status at ICU discharge and cause of death. In a subset of patients, day 3 NSE serum levels and SSEP recordings (at least 48h after sedation discontinuation) were performed and collected.
EEG and ECG quantitative analysis ECG were band-pass filtered between 0. 5 and 20Hz and EEG were band-pass filtered between 0. 5 and 45Hz using Butterworth filters of order 6 and 8 respectively and notch filters were applied at 50Hz and 100Hz. EEG data were re-referenced to an average reference. Independent component analysis (ICA) was applied to EEG (after 1Hz high-pass filtering) using Preconditioned ICA for Real Data (Picard) algorithm and resulting components were visually inspected. ICA components capturing large artifacts (notably eye movements and blinks and cardiac-field artifacts) were subtracted if any and the resulting artifact-free EEG was compared to the original recording to assess the quality of the reconstruction (adequate removal of artifacts and preservation of brain EEG signals).
Softwares EEG and ECG data were preprocessed using python and the MNE-python package. Brain-heart coupling was computed using MATLAB R2018b MathWorks) and Fieldtrip Toolbox and statistics were performed using R version 3. 6. 3 (2020-02-29) (R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www. R-project. org/) and MATLAB R2018b (MathWorks). Clinical and neurophysiological data analyzed in the current study are available from the corresponding author upon reasonable request.
It should also be noted that our study is a retrospective analysis of a prospectively collected database. Although our population is homogeneous and treated in the same way throughout the entire period this could have biased the follow-up of patients. ANS could also be influenced or modified by sedation or exposure to beta-blockers, yet it is important to highlight that our results suggest that brain-heart interplay does not differ depending on exposure to these different potential confounders. Lastly, although it is difficult to demonstrate and it was not the main aim of our study, it is still possible that this ANS dysfunction predisposes to several short or long-term complications such as cardiac arrhythmia, hemodynamic failure, maladaptive immune response, and cognitive sequelae in survivors.
Here, we address the question: how does variation in the development of skull shape influence mammalian cranial evolution? To do so, we apply a 3D geometric morphometric approach, using 69 landmarks, to quantify skull morphology through ontogeny with the largest dataset assembled to date, spanning the full phylogenetic breadth of mammals and ranging from fetal to adult specimens (22 species and 165 specimens) (Figure  2 ). Full details of the dataset, morphometric data collection, and analyses can be found in the STAR Methods section. Across this developmentally and ecologically diverse dataset of 22 extant mammalian taxa, we quantify the ontogeny of cranial morphological variation and estimate ancestral patterns of cranial shape development. With these results, we reconstruct the.
Cranial mmorphology A principal-component analysis (PCA) of the adult-only specimens within the dataset (n = 22) was first performed to assess cranial morphological variation captured from the species included in this dataset. The first principal component (PC) explained 29. 37% of overall variation and was associated with shape change in rostrum length (Figure  3A ; Table  S5 ). The positive end of PC1 reflected an elongated rostrum, exemplified by Phacochoerus africanus, Ornithorhynchus anatinus, and Dasypus novemcinctus. The negative end of PC1 represented the brachycephalic skull morphologies of species such as Sapajus apella, Felis catus, and Bradypus tridactylus. PC2 explained 18. 37% of overall variation and predominantly reflected shape change in the cranial vault, in particular the frontal bone.
The positive end of PC2 was associated with an elongated, flattened cranial vault, the result of a smaller and more anteriorly positioned frontal bone, as in Talpa europaea. The negative end of PC2 represented a rounded cranial vault, with an increased ventral-dorsal height from an enlarged frontal bone (as well as jugal and squamosal bone enlargement), as observed in Sapajus apella. S3 , and symbol shape indicates infraclass. Therian mammal clades (Marsupialia, Xenarthra, Afrotheria, Euarchontoglires, and Laurasiatheria) overlapped extensively in the central region of the PC1-PC2 morphospace (Figure  3A ), as would be expected from a PC1-PC2 morphospace and given the diverse sampled dataset. For the taxa sampled within the dataset, placental mammals (n = 15) occupied a larger morphospace area than marsupials (n = 6), although placental mammals were represented by more than double the number of species than marsupials.
It is also worth noting the small size of this adult dataset given the developmental focus of the study; therefore, a large proportion of the mammalian morphospace, consisting of approximately 6,000 species, is not sampled here. 73  Of the placental superorders, Laurasiatheria occupied a large region of the morphospace (Procrustes variance [PV] = 0. 026), spanning the length of PC1 and PC2 and thus varying greatly in both rostrum length and cranial vault shape. Euarchontoglires were positioned toward the negative end of PC1 (PV = 0. 025), mostly displaying a shortened rostrum, but overlapped with Marsupialia in the central region of PC1. Sapajus apella deviated most in cranial shape from the other euarchontoglirans. Despite only three species being sampled across Xenarthra and the absence of the unusual Myrmecophaga (giant anteater) from the dataset, xenarthran morphospace occupation was large (PV = 0.
026). Similarly, Afrotheria presented with high overall disparity (PV = 0. 027), which is notable as both Xenarthra and Afrotheria were represented by far fewer species than the less diverse Marsupialia clade (PV = 0. 016). Marsupialia occupied a small region of the PC1-PC2 morphospace and had significantly lower morphological disparity than all placental clades (PV = 0. 016, p < 0. 01), despite being represented by several species spanning the phylogenetic breadth of Marsupialia. This marsupial region bridged all other placental mammal superorders. The only monotreme in the dataset (Ornithorhynchus anatinus) falls in the upper right quadrant of the PCA, displaying an elongated rostrum and cranial vault with a small frontal bone. Ornithorhynchus anatinus did not overlap in morphospace occupation with any other taxa sampled here, reflecting the unique cranial morphology of this species.
On PC1-PC2, species largely clustered into distinct regions of morphospace based on their position along the altricial-precocial spectrum (divided into five categories from highly altricial to precocial, see STAR Methods, and referred to here as developmental strategy) (Figure  3B ). Interestingly, the altricial-precocial spectrum did not appear to align linearly with either PC1 or PC2; highly altricial species clustered centrally along PC1 and PC2, whereas other developmental strategies exhibited more extreme morphologies on these axes. A pMANOVA of shape and developmental strategy (five categories), identified developmental strategy as having a significant and relatively large effect on shape variation, in the adult-only dataset, following allometric and phylogenetic correction (R 2 = 0.
308, p = 0. 004). Subdividing the dataset into placental mammals only indicated that species with different developmental strategies (ranging from altricial,    S1  and S2. A 3D version can also be found on the associated GitHub. 74  semi-altricial, and semi-precocial to precocial in placental mammals) did not overlap in cranial morphospace. Within placentals, developmental strategy was also significantly associated with skull shape after accounting for phylogenetic relationship (pMANOVA: R 2 = 0. 407, p < 0. 001). S6 ). PC1 accounted for 31. 16% of overall variation and was associated with change in rostrum length whereas PC2 accounted for 14. 12% of overall variation and was associated with shape change in the cranial vault, again dominated by the relative size and position of the frontal bone.
As the z axis indicates continuous age (relative adult size), the smallest specimens at the bottom of this axis are, as expected, the small and thus altricial and highly altricial species (including neonate marsupials). In contrast, fetal specimens of some species are relatively larger and more similar in size, relative to their respective adults, than some infant and juvenile specimens of other species. Species with larger fetal specimens are some of the more precocial taxa within the dataset (Phataginus tricuspis, Macroscelides proboscideus, Cyclopes didactylus, and Bradypus tridactylus). Consequently, a disconnect between the discrete age categories and relative adult size (continuous age metric) exists, which is linked to position along the altricial-precocial spectrum. Furthermore, developmental strategy (position on the altricial-precocial spectrum) was significantly associated with skull morphology for the full developmental dataset, following allometric correction (R 2 = 0.
Allometry and ontogenetic trajectories The influence of size on multivariate shape was calculated across the full dataset (n = 165). Allometry (size-related shape change) was found to be a significant contributor to overall skull shape variation across all specimens (R 2 = 0. 156, p < 0. 001) and differed significantly across the 22 species (R 2 = 0. 070, p < 0. 001). Multivariate allometry was then compared pairwise across species. A high proportion of significant differences between species' allometries were identified following Bonferroni corrections (77 significant differences from 231 pairwise comparisons, p < 0. 001; Figure  S4A ; Table  S7 ). Marsupial taxa showed the greatest number of significant differences, with both placentals and other marsupials, except for Phascolarctos cinereus, which showed very few significant differences with other taxa.
The sole monotreme in the dataset (Ornithorhynchus anatinus) showed both acceleration and post-displacement from the ancestral mammal, although it should be noted that no fetal or early post-natal stages were available for this taxon. The placental and therian mammal ancestral slopes were almost overlaid, with near identical slopes (placental slope = 0. 218; therian slope = 0. 203). In contrast, the estimated ancestral marsupial presented with a decelerated slope (slope = 0. 161) and an earlier onset of growth (pre-displacement), compared with the ancestral therian mammal slope (Figures  6A  and S9 ; Table  S9 ). All species of marsupial display a small degree of deceleration in comparison to the ancestral marsupial and ancestral mammal estimates, with the exception of Sminthopsis macroura that shows slight acceleration in relation to the ancestral marsupial (Figures  S5A  and S5C ; Table  S9 ).
DISCUSSION Heterochrony is a primary mechanism of evolutionary change. Thus, ascertaining the distribution and polarity of heterochronic shifts across the tree of life is critical for understanding the evolution of morphological diversity. Here, we employed 3D geometric morphometrics to quantify cranial shape change through ontogeny for the largest comparative ontogenetic dataset for mammals to date (22 species, 165 specimens). We identified a morphologically conserved region for fetal specimens, a coneshaped pattern of cranial development, and a significant impact of the altricial-precocial spectrum (developmental strategy) on cranial morphology across the dataset and for placentals only. Reconstructed ancestral states for cranial shape development demonstrated that pedomorphic shifts localized on the marsupial lineage have resulted in a more derived pattern of cranial development in marsupials than in placentals.
83  The only fetal specimens to fall outside the highly conserved morphological region were those of Phacochoerus africanus. Nevertheless, the morphological variation exhibited across all fetal stages was still substantially smaller than that of the juvenile and adult stages. Phacochoerus africanus is the most precocial taxon within the dataset. 9,10 Therefore, the prenatal fetal stages of Phacochoerus africanus displayed cranial morphologies more similar to that of their adults, further supported by the similarity in morphospace position of Phacochoerus africanus fetal specimens to that of juveniles of other species (Figure  4B ). Across the fetal-to-adult transition, a clear cone-shaped pattern of cranial shape ontogeny is visible and is reflective of the upper half of the developmental hourglass model  76, 77  (Figure  7 ).
Phenotypic diversity occurring during the course of ontogeny could be linked to differential rates of bone deposition and growth along cranial sutures. 85  In contrast, early diversity, reflected by the lower half of the hourglass model, is thought to be driven by developmental mechanisms that occur prior to ossification and bone development, such as organogenesis and neural folding. 79  As our study focused on post-ossification morphology, this earlier ontogenetic diversity was not sampled. Therefore, we cannot test whether the bottom half of the hourglass model, and thus whether the full hourglass model, is supported in this dataset. However, our dataset does provide new understanding of the pace of differentiation following the conserved period of development, with phenotypic diversity established quickly during the infant period.
Nevertheless, we do not observe the same ontogenetic changes across the entire skull; in different cranial regions, species follow different ontogenetic changes. For example, all sampled species follow similar ontogenetic trajectories in skull elongation (as captured on PC1) but diverge in the development of the cranial vault (captured on PC2). Interestingly, the neurocranium has been suggested to have a greater degree of developmental lability than the facial region,  86  most likely to support brain growth through development and thereby facilitating evolutionary change. [87] [88] [89]  Adult phenotypic diversity, arising from this variation in cranial shape across ontogeny, is represented in the uppermost region of the hourglass model. Given the nature of our dataset, this cone-shaped pattern of development is focused on post-ossification patterns.
As an example of Cranial morphospace cone-shaped pattern of development reflects the upper half of the developmental hourglass model. 76, 77  Data for this PCA are presented in Figure  4B  and overlaid with the developmental hourglass model here. See also Figure  4  and Table  S6. this relationship, not sampled within our dataset, the altricial Mesocricetus auratus (golden hamsters) undergoes rapid ossification toward the end of a short gestation period,  90  compared with lengthy cranial ossification during the gestation of the precocial Loxodonta africana (African elephant). 91  With further work, it would be interesting to identify whether variation in ossification rate has knock-on implications for specimen position within the cone-shaped pattern of development identified here. The altricial-precocial spectrum has an underappreciated role in determining skull morphological variation within placentalia Altriciality and precociality have evolved independently multiple times across placental mammals,  10  resulting in convergent developmental strategies between distantly related species and diverse developmental strategies within each placental superorder.
32  While ontogenetic trajectories follow similar directionality for PC1, there is a large degree of variation across species' allometries, possibly owing to the ecological diversity captured within the dataset. Extensive variation in cranial ontogenetic trajectories has also been reported in other vertebrate systems-such as slendersnouted crocodylians,  32  nightbirds,  43  and mammals  42, 96  -and even in closely related species of mammals  97, 98  including variation of cranial ontogenetic trajectories between domesticated species and their wild counterparts. 42  Moreover, variation in trajectory length was observed, with marsupials starting smaller and experiencing a prolonged period of growth (hypermorphosis), compared with placentals. This observation of hypermorphosis, or extended post-natal growth, may be expected given that previous studies of marsupials have reported indeterminate or continuous growth,  99, 100  as well as extended post-natal growth.
The ancestral marsupial displayed a clear signal of pedomorphosis (deceleration) and predisplacement (Figure  6B ), which may be linked to reduced marsupial morphospace occupation and diversity observed here and known marsupial morphological constraint. 46  Our results support the conclusions drawn by the limited dataset of Smith,  21  where it is stated that ''the developmental trajectory of all cranial tissues [for marsupials] seems to be shifted. '' Beyond this heterochronic shift on the marsupial lineage, we also identified pedomorphosis for Phacochoerus africanus, most likely due to its precocial developmental strategy,  9, 10  and acceleration for the Talpa europaea and Mus musculus trajectories. The accelerated growth of Talpa europaea may be linked to its rapid ossification of cranial elements, 113 while accelerated growth in Mus musculus could be ascribed to its altricial state at birth, as well as its short gestation period.
93, 114  The decelerated pace of marsupial cranial development observed here provides empirical support for the lesser supported hypothesis that marsupial development is more derived than that of placentals. 20, 21, 111, 112  Nevertheless, it is worth highlighting here that due to the difficulties of obtaining ontogenetic data, our dataset, although large, still only represents 22 mammalian species, which are occasionally represented by only four specimens and may result in truncated trajectories. We have highlighted in the results some limitations of the ancestral state estimations, in particular the lack of early developmental stages for Ornithorhynchus anatinus and variation in the number of placental and marsupial taxa used to estimate ancestral nodes, although we still identify differences between the ancestral marsupial and the ancestral therian and ancestral placental when these factors are accounted for.