dataesr/scientific-paragraphs-categorization huggingface dataset:
There are now three such models, M27-M29. As one can see from Table  4 , among these three models there is a model, M29, that is better than both the model with one more predictor (M23) and the other models with the same number of predictors (M27 and M28). It is noteworthy that model M29 is the one model among the three that does not include adult WF. In other words, leaving adult WF out of the model improves the model's fit to the data. If one takes away one of the two predictors of the latter and so far best model, M29, one ends up with two models that were already presented, M14 and M17. As the model that includes as predictors SP and the quadratic effect of a word's age of acquisition (i. e. , M29) yields a poorer fit than the simpler model that includes only SP as a predictor (M14), one can conclude that the only word descriptor that can be used on this data set to explain FR deviance is SP.
If not, a genuine effect of WF will be found, be it accompanied by an effect of SP or, more probably, without any significant effect of SP. In any case, given its potential effect on FR, SP has to be a predictor in the statistical model that tests for the effect of WF on FR performance. Experiment 1 has quite some shortcomings but we decided to include it for a reason that we discuss here. Firstly, as can be deduced from the FR performance, the task was quite hard, maybe because there were 36 words to memorize. The first four words of the lists used occurred always in the same order and thus had to be discarded, stripping the participants' data of the primacy effect; the backward counting task the participants had to carry out after completion of the presentation of the list of words was quite extensive, which led to no recency effect being present.
Suppose the frequencies in the former are (in this order)  2. 75, 13. 74, 20. 23, and for the latter 594. 45, 927. 41, 1,349. 40. If for the first word of a list we use the lowest WF in the database as the lower bound for the interval involved in the computation of SP (see computation of SP), the SP values are 0. 8, 1. 11, 0. 48 for the LF list words, and 3. 22, 3. 41, 3. 58 for the HF list words. If one considers that in the HF list condition as the second word is presented participants' brain realizes that only HF words are presented and thus changes its expectations accordingly, we can alter the computation of SP by using as lower bound for the interval involved in the computation of SP the WF of the first word that was presented. This yields then for the HF list words the following SP values: 3.
Acknowledgments We wish to express our gratitude to  Bernard Ans ,  Marc Brysbaert ,  Amy Criss ,  Alessandro Guida ,  Ian Neath ,  Michael Ramscar  and  Stéphane Rousset  for valuable discussions that helped to improve this manuscript. We are grateful to PB for the handling of our manuscript, to the reviewers for their remarks and interest and to  Gary Jones , for raising some very interesting points during the review process. SM is indebted to colleagues  Virginie Dodeler  and  Alessandro Guida  for their support.
We do not assume the linguistic experience of all participants is identical, quite to the contrary. However, we had to make this simplification in order to be able to compute SP, and thus we used a WF database (although this simplification entails considering that all participants have the same linguistic experience). Making this simplification leads to SP values that are slightly different from what they would be if we had the "WF database" for each participant and could compute SP with all the possible precision. It is psychometric common knowledge that error in the measuring of a variable (here, SP) leads to an underestimation of its effect. Because an underestimation of the effect of SP on FR performance runs counter to our hypothesis, it only makes our approach more conservative.
g. ,  Bedrossian et al. 2017; Steel et al. 2017)  or assuming constant catabolic energy yield for biomass generation (such as in  Ray et al. 2021). Using this model, we obtain estimates of a priori credible amino acid and cell abundances in the plume under the assumption of methanogenesis, as well as estimates corresponding to a biomass stock and production best matching methane and dihydrogen measurements in the plume. In doing so, we show how previous data from the Cassini mission, as well as current knowledge of serpentinization systems, can be used to formulate assumptions and models of Enceladus's hydrothermalism and provide quantitative, testable predictions. This could help design the experiments that could yield the best possible scientific return from a future mission to Enceladus.
Here the prior probability of B has been decomposed as P B P B H P H , 3 0 ( ) ( | ) ( ) ( ) = where P(H) is constrained by evaluating the viability of the modeled population over the distribution of environmental parameters in Table 2  (Affholder et al. 2021). For visualization and integration purposes, the simulated samples are used to perform a Gaussian kernel density estimate implemented in Python's scipy package  (Virtanen et al. 2020 ), a standard method to approximate densities.
To highlight this effect, we show the value of E P B P B H U 0,1 ( ( )) ( | ) [ ] ~on the horizontal axis of Figure  5(b). As an example, if a future mission estimated that the concentration of glycine in the ocean plume were [Gly] = 7 × 10 -6 mol L -1 , we would reject biotic production with high confidence under the assumption that life emergence is a rare event (P(B) < 0. 05; Figure  5(a) ). However, people convinced that life emergence is not rare could remain hopeful in that scenario, as the posterior probability of biotic glycine production remains relatively large for higher values of the prior P(B) (about 0. 25 for P(B) = 0. 35 in the case of our hypothetical measure of [Gly] = 7 × 10 -6 mol L -1 ; Figure  5(a) ). If we further impose the analysis of these hypothetical data to be consistent with data gathered by the Cassini mission (assuming that no abiotic source of methane matching these data better than methanogenesis would have been found), then even life emergence optimists would face a problem inferring biotic glycine production under this hypothetical measure, as a biosphere producing amounts of methane that match Cassini observations is unlikely to produce so little glycine in the ocean plume.
This does not concern the authors considering the relatively low level of SM muscle activity observed during the different feeding tasks. The second part of this study, an in-vivo study on horses that have received laryngeal reinnervation using the spinal accessory nerve, will confirm or not this hypothesis. Studying the SM muscle activity in lunged and ridden horses was performed to possibly define training strategies that would accelerate rehabilitation of the dorsal cricoarytenoid muscle following selective laryngeal reinnervation with the spinal accessory nerve. In the case of ridden horses at trot and gallop and lunged horses at gallop, a mild increase was noted, on the circle, in the outside SM muscle. Unlike the quantitative analysis of the acquired EMG data in ridden horses, an increase in SM muscle activity could not be observed in the lunged horses at trot.
Data analysis To characterize tree structure and diversity in the Catacamas landscape, we performed an analysis of diameter distribution by abundance class and total basal area. We also analyzed the total diversity of the landscape. In order to understand the distribution and structure of tree diversity in the Catacamas landscape, we generated distributions per diameter class per hectare for each land use, for species density, tree density and basal area. The expected species density per hectare in each diameter class was estimated by the rarefaction method  [41]. We used the average number of trees per hectare for each diameter class as the number of individuals for the rarefaction (sample size) (Supplementary Information, Table  S1 ). To visualize the distribution of species abundance, we built rank-abundance curves for each of the land uses.
Acknowledgements This study was funded by the  CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA ). This research was carried out by CATIE as part of the  CRP-FTA. The aim of the program is to improve the management and use of forests, agroforestry and tree genetic resources across the landscape, from forests to plantations. CATIE is part of the  CRP-FTA program  in partnership with Bioversity,  CIRAD ,  CIFOR ,  CIAT ,  INBAR, Tropenbos and ICRAF. We would like to thank all the nancial partners who supported this research through their contributions to the  CGIAR Fund. To view a list of donors to the Fund, visit: https://www. cgiar. org/funders/. We would nally like to thank our English language scienti c editor,  Kate Roberts , for her thorough review of our manuscript.
COMPLEXITY This section focuses on establishing the complexity of exploring the symbolic state graph of Delayable Timed Petri Net. Symbolic state space of timed models are usually based on difference bound matrix (DBM) representing the union of timed domains as in state class  (Berthomieu and Diaz, 1991 ) for Merlin's TPN. The computation of a successor state class, based on the Floyd-Warshall's algorithm, is, in general, of complexity O(n 3 ) with regard to the number n of transitions in the net. In  (Boucheneb and Rakkay, 2007) , the authors have reduced this complexity to O(n 2 ). In the case of the DTPNs, DBMs are not necessary because as shown in Section 4, only one value per transition is sufficient to describe the symbolic state. Thus, the data structure of the vector of dynamic delays ∆ greatly simplifies the computation of successor.
Yet, the computation of symbolic successor remains of complexity O(n). Eventhough the successors can be computed efficiently, the size of the symbolic state graph remains exponential in the number of transitions, as for Timed Petri Net. The complexity of the algorithm building the symbolic state graph is then clearly not linear. However, thanks to the data structure of the vector of dynamic delays, some required algorithms are of complexity O(n) with n the number of transitions. This is the case of the computation of subsumption relation between symbolic states of Definition 11.
known to be true for n ∈ {1, 2}. Some evidence for such a claim is related to the observation, in large databases of CY 3 , that most of them admit an elliptic fibration, while in  [77]  it is proven that the number of elliptically fibred CY 3 is finite. A last line of thought regarding finiteness consists in finding upper bounds on certain central charges  [78]  (see also  [1, 79] ), or on the rank of the allowed gauge groups  [14, 80, 81] , thus restricting the possible gauge groups and field content in quantum gravity effective theories. Finally, recent works on the topic, including  [82] [83] [84] [85] , have provided further interesting insights and formulations of the finiteness conjecture. Finally we consider the combination of the finiteness conjecture and the cobordism conjecture, and try to formulate the former in the language of bordisms.
Acknowledgements We are particularly grateful to  D. Fiorenza  and  M. Montero  for illuminating discussions and valuable comments on an earlier version of the manuscript. We also thank  R. Blumenhagen ,  H. Skarke , and  F. Thuillier  for useful exchanges at various stages of this project. N. Carqueville is supported by the  DFG Heisenberg Programme. The work of  N. Cribiori  is supported by the  Alexander von Humboldt Foundation  and was supported by an  FWF  grant with the number P 30265 at the initial stage of this project.
Ethical considerations and trial registration This clinical trial is approved by the Ethics Committee of Lille (Comité de Protection des Personnes Nord-Ouest IV, Lille University Hospital, N°CPP 12/05) and the French competent authorities (ANSM, N°2011-A01129-32). It is registered at ClinicalTrials. gov under identifier NCT02086214  [25]. According to the Declaration of Helsinki, written informed consent is obtained from both parents of the child before enrollment. On the consent form, participants will be asked if they agree to use their data should they choose to withdraw from the trial. Participants will also be asked for permission for the research team to share relevant data with people from the Universities taking part in the research or from regulatory authorities, where relevant. This trial does not involve collecting biological specimens for storage.
The consent form and information material are written in French and are available on request, from the corresponding author. This protocol follows French regulations regarding biomedical research on medical devices. The trial sponsor did not judge necessary to establish a Data Safety Monitoring Board regarding the absence of specific risk. Serious adverse reactions are collected during the whole course of the trial and systematically reported to the principal investigator and safety department of the clinical trial sponsor. Any modification to this protocol is agreed by the ethics committee before implementation and notified to the health authorities in accordance with local rules.
Demographic data The following demographic data are collected for each participant: age, sex, impaired side, medical history, and current treatments (usual medications, botulinum toxin injections, rehabilitation therapies). The presence of unilateral neglect, presence, and type of cognitive troubles and level of intelligence quotient (IQ) are also collected, as well as the level of scholarship and adaptations needed (special needs assistant for example). Functional profile of the child is classified using Gross Motor Function Classification Scale (GMFCS)  [28]  and Manual Abilities Classification System (MACS)  [29]. GMFCS is commonly used to describe the gross motor function, notably because it has strong discriminative validity  [30]. It focuses on describing gross motor function in self-initiated movements and, in particular, during sitting and walking.
In this context and according to French regulations, it will not be mandatory to address a Medical Device Reporting process and a Data Safety Monitoring Board report to conduct this study. To perform this safety assessment, parents will be asked to daily report AEIs and other problems occurring during the Lycra ® sleeve pressure garment during wearing period on a parental self-report diary logbook. The diary logbook will be carefully checked by the investigator before the physical examination at each hospital visit (i. e. , 3 months and 6 months) using a structured interview. AEIs will be classified at posteriori by the investigator using Bégaud et al. classification (minor/moderate/serious) usually used for drug clinical trial report  [43]. Cutaneous events were defined as itchy contact dermatitis, red skin rash, and spots; compression events will be defined as mechanical swelling, arm pain, "Blue hand," tingling, discomfort, sore thumb, and tightness complaint from a child.
Conduct of the trial Multicenter trial The trial takes place in 7 French pediatric rehabilitation centers. Patients are recruited in medical or medico-social structures that usually hosts children with cerebral palsy and are situated in the Study visits There are 4 study visits (V1 to V4). Visit duration is 2 h for V1 and V3 and 4 h for V2 and V4. The study schedule is presented in Table  2. Flow of participants and timeline are presented in Fig. 2. After giving their consent, participants are recruited and randomized during the inclusion visit (V1) which happens 1 month before the beginning of the intervention. The occupational therapist or investigator, specifically formed, takes precise measurements of the child's arm, following the manufacturer's instructions. The investigator sends the measurement data to Medical Z®, so that the confection of the sleeve can begin by the manufacturer according to randomization list (active sleeve or placebo sleeve), on condition of anonymity.
Baseline and final testing are realized without wearing the splint. AHA, the primary outcome, is assessed by a certified occupational therapist. QUEST is assessed by the same experienced occupational therapist, following the QUEST manual  [35]. Neuro-orthopedic examination is conducted by the investigator following the report form of the study. SEP are recorded by an experienced neurophysiology technician. PedsQL™ 3. 0 CP Module questionnaire is completed by the child's parents. Anthropometric measurements occur at V2, V3, and V4. Compliance is monitored in a diary, specifically developed for the study purpose. Compliance data are checked at V3 and V4. Adverse reactions are recorded as well during V3 and V4.
Data collection All data will be recorded by trained clinical investigators and/or by the study site coordinator using an electronic case report form (eCRF Ennov EDC ® , Ennov 33270 Floirac, France; https://ecrf. chru-lille. fr/EnnovClinical). Data safety and security measures will be taken into account for the different study sites (restricted staff access, password protection, firewall, and virus spyware protection). To ensure the data quality, a study monitor from the trial sponsor will verify and cross-check all data against the investigator's source document records. The essential data necessary for monitoring the primary and secondary endpoints has been identified and will be.
Missing data (whatever the reason) will be handling using the multiple imputation procedure  [49, 50]. Imputation procedure will be performed using main baseline characteristics and treatment group under missing at the random assumption by using regression switching approach (chained equation with m = 20 imputations) with a predictive mean matching method for continuous variables, logistic regression models (binary, ordinal or polynomial) for categorical variables. Imputation procedure will be performed using the baseline characteristics and allocated group. Treatment effect estimates obtained in multiple imputed data sets will be combined using the Rubin's rules  [51]. Complete case analysis will be performed as a sensitivity analysis  [52].
Methods. Participants. The power analysis in G*Power 3. 1 showed that to detect an effect size R 2 = 0. 02 in our model 647 participants are required. Participants were recruited through Prolific. At one point during data collection a server failure occurred; we excluded all the data collected during that time. 661 participants completed the experiment. Consistent with our pre-registration, we excluded those participants who failed more than one attention check, resulting in the targeted final sample of 647 individuals included in the analysis (age:  M = 35. 6 ± 12. 6 s. d. ; gender: 371 women; Table  1 ). All participants gave informed consent and were paid £1. 75 for their participation. The experiment and procedures were approved by the Royal Holloway, University of London Ethics Committee, and the experiment was performed in accordance with relevant guidelines and regulations.
Acknowledgements We would like to thank  M. Carroll  ( Pituvik Landholding Corporation, Québec ) for permissions for fieldwork and sample collection. The ideas contained herein were clarified by discussions and debates with  W. Bleeker ,  J. O'Neil ,  R. Carlson , and  D. Francis. We thank  P. Morino ,  N. Cates ,  E. Bell ,  F. Thibon ,  S. Davey ,  M. Guitreau ,  J. Oulton ,  A. Roth , and  D. Trail  for assistance in the fieldwork, and  O. Müntener  and  A. Bénard  for fruitful discussions during the writing of this paper. The paper benefited from reviews by  J. Pearce  and  K. Szilas  that greatly improved the manuscript and from editorial handling by T. L. Grove.
The absolute energy was calibrated in advance of the data taking with a high-resolution grating spectrometer in the upstream photon diagnostics section. UV pulses were generated by frequency-tripling the output of the FLASH pump-probe laser  [29]. With a central wavelength of 810 nm (26 nm bandwidth FWHM) and a pulse duration of 55 fs FWHM, this resulted in a central UV wavelength of 271 nm (2. 5 nm bandwidth FWHM) with about 22 μJ pulse energy. A prism compressor installed in the 271 nm beam path was used to partially compress the UV pulse to approximately 100 fs FWHM. The laser beam was focused to approximately 50 μm (1/e) diameter by an out-of-vacuum lens and was coupled into the experimental chamber via a drilled in-vacuum mirror, resulting in an intensity of approximately 10 13 W/cm 2.
The molecular beam, the FEL beam, and the UV beam were overlapped in the center of a double-sided VMI spectrometer  [24, 32]. Ions and electrons created from photoionization were guided by electric fields towards opposite sides of the spectrometer onto two microchannel-plate (MCP) detectors coupled to phosphor screens and were detected simultaneously. The momentum distributions of all resulting fragment ion hits on the MCP/phosphor detector (chevron configuration, P47 scintillator) were recorded using the PImMS2 camera  [33, 34]  outside of vacuum. The data contain flight times + peaks with n = 0, 1, 2 are overlapping due to their kinetic energy. Water contamination originates from the residual gas in the experimental chamber; it is strongly reduced at 139 eV photon energy due to the ionization cross section being approximately four times lower compared to those at 67 and 70 eV.
Velocity-map images for a given fragment were mirrorsymmetrized and Abel-inverted using the pbasex algorithm  [36]  to retrieve the central slice of the crushed Newton sphere. Kinetic-energy distributions were extracted by angular integration of the inverted images. The kinetic energy was calibrated by simulating the trajectories of the photoions in the spectrometer using the simion software package  [37]. Delaydependent data were not inverted due to insufficient statistics in each delay step. The selection of low-energy ions to generate the data set shown in figure  7  was achieved by applying radial gates to the velocity-map images, which correspond to a projection of the 3D momentum distribution. Photoelectrons were recorded on a second MCP detector (chevron configuration, P42 scintillator) using a chargecoupled device camera.
The latter provides a good estimate for the photoionization cross section of the CH 2 BrI molecule. A high-resolution XUV absorption spectrum measured for gaseous CH 2 BrI between 46 and 73 eV  [16]  is in good qualitative agreement with the data shown in figure  3. The broad, intense peak centered around 94 eV corresponds to photoionization of the I(4d) shell-the so-called giant resonance. The features around 53 and 71 eV (labelled A and B in figure  3 ) can be assigned to core excitations of I(4d) and Br(3d) electrons, respectively  [16]. The averaged spectral profiles of the FEL pulse used in this work are also indicated in figure  3. We estimate cross sections of 12 Mb at 67 eV, 16 Mb at 70 eV, and 10 Mb at 139 eV for CH 2 BrI. At 139 eV, the strongest fragmentation is observed, which can be rationalized when considering the average charge state produced by single photoabsorption at each of these photon energies.
Moreover, the data at 139 eV were recorded at a higher XUV pulse energy, but for a shorter total acquisition time, leading to lower statistics in this data set. We therefore doubt the significance of the seemingly slower rise time of the step functions at 139 eV, since our charge-transfer model gives no reason to expect a photon-energy dependence for a given charge state. The colored triangles in each panel of figure  7  indicate the delays at which critical internuclear distances for electron transfer are reached in different scenarios (see also figure  6 ). Blue triangles correspond to electron transfer from the carbon atom of a rotating CH 2 Br, black triangles to electron transfer from the bromine atom (the rotation is practically irrelevant in this case, as the center of mass lies very close to Br).