dataesr/scientific-paragraphs-categorization huggingface dataset:
For the NPIPE dataset, the observations are consistent with the simulations, with p-values higher than 0. 05 for most resolutions. However, the number of components and loops shows mildly significant deviations at N = 32, FWHM = 320. The corresponding deviation for the Euler characteristic exhibits an order-of-magnitude lower value at per mil levels. For the next larger scale, we find that the components and the Euler characteristic are consistent with the base model, while the loops exhibit a mildly anomalous p-value of 0. 03. While emphasizing that the statistics are based on low numbers, we note the contrasting behavior of the different topological descriptors. For the FFP10 dataset, the components and the Euler characteristic exhibit p-values higher than 0. 01 for all resolutions. This is consistent with the observation in Planck Collaboration et al.
(2020c) that the p-values obtained from the combined Minkowski functionals are consistent with the base model within the 99% confidence level. The the number of loops exhibits a significantly anomalous behavior, yielding per mil pvalues, in contrast with the number of components and the Euler characteristic, at N = 16, FWHM = 640. However, we note that this deviation occurs at large smoothing scales, where the numbers involved in computing the statistics are small. Disregarding this anomalous behavior of loops at large scales, which might be affected by low-number statistics, we find that the FFP10 dataset is consistent with the standard model simulations at the 99% confidence level. In summary, while both datasets are largely consistent with the simulations based on the standard model, we find instances of interesting discrepancies in both datasets, which may be difficult to reject summarily as statistical flukes.
The p-values are obtained via the parametric (Mahalanobis distance) and non-parametric (Tukey depth) tests, for different resolutions and smoothing scales for the NPIPE (panel (a)) and the FFP10 (panel (b)) dataset. Marked in boldface are p-values 0. 05 or smaller. Collaboration et al. 2020d), for comparison and completeness. The present paper is a successor to Pranav et al. (2019a), where we investigated the topology of the temperature fluctuation maps based on the intermediate Planck 2015 Data Release 2 (DR2), accompanied by FFP8 simulations. These two investigated topological characteristics of the CMB temperature fluctuation maps for the latest three data releases by the Planck team. The overall trends in the results in the datasets show the consistency of the data processing pipeline and our own methods.
Acknowledgements I am indebted to the anonymous referee, whose incisive, yet extremely insightful comments have helped bring this draft to a balanced place. I am greatly indebted to  Robert Adler ,  Thomas Buchert ,  Herbert Edelsbrunner ,  Bernard Jones ,  Armin Schwarzman ,  Gert Vegter , and  Rien van de Weygaert  for encouraging this solo venture, and for extremely helpful discussions. My gratitude also to  Julian Borrill  and  Reijo Keskitalo  for their patience in clarifying doubts, and their constructive comments on the draft. I also thank  Tal Eliezri  for insightful comments on the artwork. This work is supported by the  ERC advanced grant ARThUs  (grant no:  740021 ; PI:  Thomas Buchert ), with contributing influence from  ERC   advanced grant  URSAT (grant no:  320422 ; PI:  Robert Adler ).
Notes. The p-values are obtained via the parametric (Mahalanobis distance) and non-parametric (Tukey depth) tests, for different resolutions and smoothing scales for the NPIPE (panel (a)) and the FFP10 (panel (b)) dataset. Marked in boldface are p-values 0. 05 or smaller. Collaboration et al. 2020d), for comparison and completeness. The present paper is a successor to Pranav et al. (2019a), where we investigated the topology of the temperature fluctuation maps based on the intermediate Planck 2015 Data Release 2 (DR2), accompanied by FFP8 simulations. These two investigated topological characteristics of the CMB temperature fluctuation maps for the latest three data releases by the Planck team. The overall trends in the results in the datasets show the consistency of the data processing pipeline and our own methods.
Flight Mileage and Aircraft Soot Emissions The FlightRadar24 commercial database of individual flights for January-May in 2019 and 2020 were used to reconstruct the daily spatial distribution (at 1° × 1° resolution) of air traffic and then interpolated into our model grids (at 1. 9° × 2. 5° resolution). The aircraft routes were assumed to follow great circles between the start and the end of the cruising parts of their respective flights. We have assessed the difference in the aircraft routes between using the assumption of shortest (i. e. , great circle) and fastest (i. e. , fuel optimal) routes. For our grid resolution of 1. 9° × 2. 5° the difference is fairly small and has a negligible effect on the distribution of aviation-emitted soot. The Aviation Environment Design Tool (AEDT) data set was used to calculate aircraft soot emissions for 2006, which were developed based on the original flight tracks of each of 31 million commercial flights worldwide  (Barrett et al.
CALIPSO Satellite Observations Observed Ni are derived from co-located observations of the Imaging Infrared Radiometer (IIR) and the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The retrieval technique uses the ratio, β eff , of the effective absorption optical depths in IIR channels 12. 05 and 10. 6 μm and relationships established from SPARTICUS data using the N(D) 1 = 0 assumption  (Mitchell et al. , 2018). The β eff ratios are from the recent Version 4 IIR Level 2 track products  (Garnier et al. , 2021a (Garnier et al. , , 2021b)) , which include improvements with respect to the previous Version 3 that were applied in a previous study  (Mitchell et al. , 2018). Following Version 3, Ni is retrieved for single-layered semi-transparent cirrus clouds with temperature at cloud base altitude colder than 238 K and cloud optical depth larger than about 0.
The effect of the reduction in aircraft emissions due to the COVID-19 pandemic was estimated as the difference between EX_S2 and EX_S1 in 2020. Two cases, EX_L1 and EX_L2, were run to examine the influence of the assumption of a long-term reduction in aircraft flights, These were run for 6 years with winds nudged toward ECMWF reanalysis data using a nudging time of 6 hr for the years 2009-2014. The data for the last five years were used for analysis. The aircraft emissions in EX_L1 are increased by 5% per year from the emissions in 2019, while the aircraft emissions in EX_L2 are decreased from that in EX_L1 by the ratio of flight mileage reduction in April/May 2020 compared to April/May 2019. The difference in the ice crystal number, Ni, and radiation between EX_L2 and EX_L1 is the long-term effect of the aircraft reductions on cirrus clouds.
Decrease in Global Flight Mileage Due To COVID-19 Global aircraft flight mileage increased by ∼5% annually between 2012 and 2019 (based on global aviation fuel use;  Lee et al. , 2021)  due to the rapid expansion of civil aviation  (SABRE, 2020). This pattern of growth was expected to continue for the next two decades before the COVID-19 outbreak according to Airbus's global market forecast  (Airbus, 2019). However, this trend was terminated when international airlines stopped operating flights into and out of China in February 2020. We reconstructed the daily spatial distribution of air traffic using the FlightRadar24 commercial database of individual flights for 2019 and 2020 (Figure  S2  in Supporting Information S1). Flights were reduced in China while fights were still slightly increased in other regions in the early stage of the pandemic (January and February 2020) compared to the same period in 2019, resulting in a 0.
The simulated Ni from January to May in 2018, 2019 and 2020 using the CESM/IMPACT model was evaluated using data from the CALIPSO satellite (Figure  2 ). The observational data is limited to ice water mixing ratios >10 -6 kg/kg and cloud optical depths (COD) between 0. 3 and 3, so model results are restricted to only these values. When the microphysical index of the infrared imaging radiometer onboard CALIPSO is less than the sensitivity limit for measuring large crystals, Ni was assigned to the values corresponding to this sensitivity limit. As a result, the average Ni determined from CALIPSO was thought to be overestimated (see below, however). It is anticipated that the median Ni is more accurate and can be used to evaluate the model. As shown in Figure  2 , the simulated median Ni was close to the observed Ni with an average bias of 21%, and was mostly within the range of the 25th and 75th percentiles of the observations.
Discussion This study examines the radiative effect of the decrease in aircraft flights due to the COVID-19 pandemic and the resulting increase of Ni in large-scale cirrus clouds in the NH using a combination of remote sensing and modeling. The CALIPSO satellite data indicates that there was a significant increase in Ni in April-May 2020 over 30°N ∼ 60°N compared to previous years. The model predicted median Ni is within 21% of that measured by CALIPSO, but because CALIPSO probably misses some homogeneous freezing cases with high Ni, due to the low frequency of homogeneous freezing and long revisit period of CALIPSO, the resulting average Ni is smaller than that in the model. A set of polar orbiting satellites with a higher temporal resolution or a geostationary satellite would be needed in the future to detect average changes in Ni and to examine the cases with homogeneous freezing.
Our model results suggest a significant increase in Ni and a positive radiative effect over most regions in the middle to high latitudes of the NH if flight restrictions last for 5 years. While recent theoretical treatments indicate that the INP efficiency of aircraft soot is quite small  (Kärcher et al. , 2021) , it is not yet clear that such treatments apply to aircraft soot in the atmosphere and its effect on large-scale cirrus clouds. Had we applied such small efficiencies in the model, we would no longer fit the CALIPSO data as well as we do. It might be that the laboratory observations on which  Kärcher et al. (2021)  based their parameterization do not correctly represent the effects of aircraft soot on large-scale cirrus. Thus, the INP efficiency of aircraft soot that has been incorporated in contrails is possibly the dominant uncertainty in the evaluation of the effect of aircraft emissions on cirrus clouds (P.
Importantly, we had several quality check and associations between age and brain structure served as a benchmark. These control conditions support the validity the statistical approach used in our analyses. It is worth noting as well that our studies showing the low replicability of SBB using voxel-based morphometry and the low replicability of SBB using CT estimates were performed in two different datasets. In other words, the poor replication rates of SBB can hardly be attributed to a questionable quality of the datasets, the chosen morphometric measures or to validity of the behavioural variables. In our previous study, we also demonstrated that the same approach used within a clinical population yielded higher replicability rates suggesting that structural variability (atrophy) and symptomatic behaviour can be reliability related to each other  9.
Conclusions, recommendations and available resources. 8] [49]. Many of these recommendations are directly relevant in the context of SBB. First, at dataset level, considering the central role of sample size in the replication crisis  9, 38  , in line with evidence provided in our study, identification of robust links between psychological variables and brain phenotype needs moving towards big data samples, e. g. 50, 51. Second, because false positives appear to occur frequently and be unnoticed when the degrees of freedom and the exact analyses path leading to the published findings are undisclosed  45, 52  , analyses should be documented and disclosure should be increased. Along the same line, the exploratory nature of the analyses should be acknowledged. In particular, considering that the SBB-approach is typically an observational empirical approach, it is frequent that the data has not been acquired for the purpose of the finally reported SBB-analysis.
org/ knitr/) and datalad (https:// www. datal ad. org) can be used to promote transparency and traceability and data sharing platforms such as OpenNEURO (https:// openn euro. org) and Neurovault 56 offer free access to data and results of statistical maps. Finally, for any found significant association, replication studies in an independent dataset should be performed. We note however, that the concretization of this suggested good research practice is highly dependent on the active contributions of publishers and funding organizations by providing incentives for replications effort. While these practices could be seen as time consuming and resource consuming in the short-term, they will all contribute to a better understanding of brain-behaviour relationships in the future, but also more generally contribute to build a more optimistic, fruitful, and ethical scientific culture in the long run.
Materials and methods Participants. Healthy adults' data were selected from the publicly available dataset from the Human Connectome Project (HCP; http:// www. human conne ctome. org/). The data were acquired using protocols approved by the Washington University institutional review board. Informed consent was obtained from subjects and consent to publish was obtained from the Human Connectome Project according to the declaration of Helsinki. In addition, the use of the HCP-data was approved by the local ethics committee of the university of Düsseldorf, Germany. The HCP data comprised from 1206 individuals (656 females), including 298 MZ twins, 188 DZ twins, and 720 singletons, with mean age 28. 8 years (SD = 3. 7, range 22-37). After passing the HCP quality control and assurance standards  57  , structural data of 1113 individuals were released.
Images underwent gradient nonlinearity correction (using acquired B1 bias field) and the two scans of each modality were co-registered and averaged. CT estimates derived using FreeSurfer v5. 3-HCP pipeline (https:// github. com/ Washi ngton-Unive rsity/ HCPpi pelin es/ blob/ master/ FreeS urfer/ FreeS urfer Pipel ine-v5. 3. 0-HCP. sh), were downloaded from the Amazon Web Services. This pipeline  58  is optimized for the HCP data and further incorporates T2-weighted images into the FreeSurfer analysis pipeline. Each individual's derived surfaces were then registered to the fsaverage surface (fsaverage-163,842 vertices per hemisphere), through a non-linear surface-based inter-subject registration procedure that aligns the cortical folding patterns of each subject to a standard surface (fsaverage) space  64.
Acknowledgements This work was supported by the  Deutsche Forschungsgemeinschaft (DFG ,  GE 2835/1-1 ,  EI 816/4-1 ), the  Helmholtz Portfolio Theme 'Supercomputing and Modelling for the Human Brain'  and the  European Union 's  Horizon 2020 Research and Innovation Programme  under Grant Agreement No. 785907  ( HBP SGA2 ). Data were provided by the  Human Connectome Project ,  WU-Minn Consortium  (Principal Investigators:  David Van Essen  and  Kamil Ugurbil ;  1U54MH091657 ) funded by the 16  NIH Institutes  and Centers that support the  NIH Blueprint for Neuroscience Research ; and by the  McDonnell Center for Systems Neuroscience at Washington University.
Data availability Data, used in this manuscript, is acquired by the Human Connectome Project (HCP). Anonymised data are publicly available from ConnectomeDB (db. humanconnectome. org). Certain parts of the data are available subject to restricted data usage terms. All code used to perform the experiments and prepare figures of this manuscript is available upon Email request: Shahrzad Kharabian Masouleh and will be accessible in the following public repository: https:// github. com/ shahr zadkh/ CTSBB_ repli cabil ity.
Historical records and climatic data support this classification, e. g. minimum temperature (T° min) of 6. 6 °C, average annual temperature (T° average/annual) of 14. 8 °C, maximum temperature (T° max) of 25. 2 °C, and total annual rainfall of 1070. 15 mm  [26, 27]. To assess the local climatic conditions, monthly records from the weather station of Nahuatzen, and the regional Mexican offices of the SMN (National Weather Service), were extracted for the four-year period preceding our study (July 2014 to July 2018).
The vegetation was photographed with a Sony Nex-5 digital camera (Sony Ltd. , Japan). Geographic data (coordinates, elevation) were collected in situ using a Global Positioning System (Garmin Montana 680; Garmin Ltd. , Olahe, KS, USA). Water pH and temperatures were measured in situ using an Expresstech @ LCD PH Digital Meter (Expresstech; Kingpow Company Limited, Hong Kong, China).
Morphology Adult Ambystoma specimens captured during the survey were measured at ten morphological parameters, as follows. SVL = snout-vent length (from the tip of the snout to the most posterior opening of the cloacal slit); TL = total length; TAL = tail length (from posterior edge of vent to tail tip); HL = maximum head length; HW = maximum head width; LAL = leg length; SL = snout length; ND = nostril diameter; IS = internostril distance. All measurements were performed with a dial caliper (Louisware LSWCL1810, Louisware Ltd. , USA; 0. 1 mm precision). Individuals were subsequently released. Our morphometric data was compared with the specimens documented in the original description of A. amblycephalum  [22] , which listed three adult females: the holotype EHT-HMS N°16443 [now FMNH 100104 according to 29, see also 14] and the paratypes EHT-HMS N°16442 and EHT-HMS N°16444.
Amplicons were sanger-sequenced at GATC (Konstanz, Germany). We first used BLAST (https://blast. ncbi. nlm. nih. gov/ Blast. cgi) to infer the identity of our Nahuatzen specimen based on the closest hits on GenBank sequences. Second, we harvested and concatenated 16S and CR sequences from published Ambystoma mitogenomes representing 12 different forms/taxa (AY659992-AY659995; AY728218, GU078469-GU078472; KP013120, KP289200). These were completed by a CR haplotype from our target species A. amblycephalum collected in Iratzio, which was independently obtained by two studies [U36403 from 17, DQ241132 from 30]no equivalent data exist for 16S. Sequences were manually aligned and trimmed for analyses in Seaview  [31] , and we obtained a concatenated alignment of 1,296 bp [16S: 541 bp, CR: 755 bp).
Third, we aligned our Nahuatzen CR sequence with those from 32, which included 76 individuals of various Mexican Ambystoma. Phylogenetic reconstructions of the two sequence aligments were performed in BEAST 2. 6  (30]. We applied strick clocks, a birth-death model for the tree prior, and GTR + G + I substitution models, which were those with the lowest AIC criteria for both genes [tested with jModelTest, 33]. The chains were run for 100 million iterations, sampling every 10,000 iterations. Stationarity and effective sample sizes of the parameters were visualized using Tracer  [34]. The first 20% of sampled trees were discarded as burnin, and we used DensiTree  [35]  to visualize the retained trees, as well as the BEAST module TreeAnnotator to summarize them under the maximum-clade consensus method.
, 2015) , but are observed for external perturbations such as eruptions. The analysis was applied to a specific database and shown to explain successfully the observed rain kinematics. However, on average, the ponderomotive force from transverse MHD waves was found to be insufficient to fully explain the observed reduced downward velocities. Another interesting consequence of coronal rain is the excitation of transverse oscillations, particularly targeting the large rain events or "showers" (described further below) for which the mass fraction is large relative to the initial loop mass. Verwichte et al. (2017)  show that the transverse displacement is approximately linearly proportional to the ratio m/M, of rain mass m relative to the loop's mass M, and is expected to be on the order of several hundred km, matching observations.
ACKNOWLEDGMENTS We would like to thank the two referees for their valuable contribution during the reviewing process of this manuscript. CF and PA acknowledge support from the  International Space Science Institute, Bern, Switzerland  to the  International Team on  " Observed Multi-Scale Variability of Coronal Loops as a Probe of Coronal Heating ". CF and PA acknowledge the fruitful discussions and work with the members of both teams. The SST is operated on the island of  La Palma  by the  Institute for Solar Physics of Stockholm University in the Spanish Observatorio del Roque de los Muchachos  of the  Instituto de Astrofísica de Canarias. Hinode is a Japanese mission developed and launched by  ISAS/JAXA , with  NAOJ  as domestic partner and  NASA  and  STFC (UK)  as international partners.
2015). Full shape information has been shown to encode more constraining power than usual BAO and RSD analyses  (Loureiro et al. 2019; Tröster et al. 2020). Pushing to small scales is challenging for future surveys because they are entering the non-linear regime of structure formation where the physics of the dark matter halos becomes relevant. However, there is a wealth of evidence that the halo properties encode cosmological information to constrain dark energy and gravity  (Balmès et al. 2014; Lopes et al. 2018 Lopes et al. , 2019;;  Data and notebooks reproducing all plots and results are available at https://github. com/fabienlacasa/SmallScaleMiracle Contigiani et al. 2019; Ryu & Lee 2020). This has driven a rise in interest in using non-linear scales for cosmological constraints (e. g.
36, and a galaxy number density n(z) ∝ z z 0 2 exp        - z z 0 3/2        , (1) where z 0 = z m / √ 2 with z m = 0. 9 being the median redshift  (Laureijs et al. 2011). The total density is 30 gals arcmin -2 in the redshift range [0,2. 5]. Following Euclid Collaboration (2020), I divide the sample into ten equi-populated redshift bins, whose bin stakes are z = 0. 001,  0. 418, 0. 56, 0. 678, 0. 789, 0. 9, 1. 019, 1. 155, 1. 324, 1. 576, and 2. 5. Throughout the present article, I only show plots for the SKA2 case, as the plots for the Euclid sample are all qualitatively similar, and the scientific conclusions are the same 1. For both surveys, the forecasts are produced with a binning of multipoles, as is customary in data analysis. Specifically, I define 50 bins spaced logarithmically in the range  [30,50 000].
A. 3. Effect of realistic priors The previous subsection is extremely conservative in not setting any prior on the additional parameter. However, we can realistically set a Gaussian prior of width 10% on A P and 20% on R S. Furthermore, the whole article assumes H 0 to be a free parameter, which degrades the cosmological constraints because galaxy clustering alone has extremely poor constraints on H 0. In reality, one would take a prior on H 0 from CMB or supernovae data 2. Therefore, I also consider the case for a prior on H 0 , of width given by the Planck 2018 constraints  (Planck Collaboration VI 2020). Let us first focus on the astrophysical priors. Figure A. 3 shows the impact of the priors on A P and R S on the cosmological errors compared to the base model. These realistic priors provide a very large improvement of the error on σ 8 at low k max , dividing the error by up to a factor 3.