dataesr/scientific-paragraphs-categorization huggingface dataset:
For this comparison and all related D-statistics hereafter, Pervasive hybridization in radiated Tillandsia significance was assessed using a jackknife procedure with 200kb window size, and familywise error rate (FWER) was calculated and corrected for multiple comparisons following the Holm-Bonferroni method with the p. adjust function in R (R Core Team 2020). To further characterise the relationships among clades, we examined the consistency of clade monophyly within our set of window-based trees using the check_monophyly function in the ETE Toolkit v. 3  (Huerta-Cepas et al. 2016). A cloudogram of ML trees was visualised using ggdensitree from the R package ggtree v. 3. 4. 0  (Yu 2020). Trees were modified using R packages phytool v. 1. 0-3  (Revell 2012) and treeio v. 1. 20. 0 (Wang et al.
0. 2  (Martin and Van Belleghem 2017). This method considers all the possible topologies relating several taxonomic groups and quantifies the contribution of each individual taxon topology to the full tree, enabling to locate genomic regions that are associated with certain topologies. We focused on the three largest clades and reduced the number of possible topologies by   Martin and Van Belleghem (2017). Subtrees were produced by partitioning the VCF with the biostar497922 script from Jvarkit  (Lindenbaum 2015)  and ML trees were inferred for each window as described above. A summary of all topologies and visualisation of topologies along genomic coordinates were produced using the plot_twisst. R script, modified to avoid averaging the signal over regions with high rates of missing data  (Martin and Van Belleghem 2017).
Characterising Hybridization and Introgression To quantify the rates of hybridization between all species in our dataset, we obtained a genome-wide signal of introgression using the original implementation of the D-statistic and estimates of admixture fraction f (henceforth: ƒ 4 -ratio) in Dsuite v. 0. 5r45  (Malinsky et al. 2021). We additionally computed D-statistic for each reference chromosome, obtaining pvalues using a jackknife procedure with windows of 150 SNPs. Given a certain level of uncertainty regarding the true relationship between species, we set no a priori knowledge of taxon relationships. Instead, Dsuite ordered each trio so that the BBAA pattern is more common, principally to focus on topologies with minimal discordant patterns. Since groups that are involved in hybridization may share branches on a phylogenetic tree, a single hybridization event can present multiple correlated instances of significantly elevated D-statistic.
Pervasive hybridization in radiated Tillandsia incongruent with a monophyly of the previous inferred 'clade K. 2'). The assignment of species to clades and all other relationships between sub-clades remained overall congruent with previous phylogenies (Granados  Mendoza et al. 2017; Vera-Paz et al. , 2023). Several within-clade topological differences appeared in trees inferred with different methods, especially within the T. fasciculata clade. The latter were highly supported in the concatenated tree yet coupled with high levels of gene tree incongruence (see below), suggesting substantial allele sharing and high rates of gene flow within this clade. Gene tree discordance was widespread within the dataset, affecting both deep and shallow nodes (Fig. 1 ; Supporting Fig. S3 ). The relationships between the South American species and the T.
Correlated and Widespread Gene-flow Events D-statistics results for trios arranged to maximise the observed number of BBAA patterns indicated that all species in our dataset were involved in potential hybridization (Fig. 2 ). Out of 7,141 tests in total, 4,331 returned significantly elevated values, with D values ranging between 0. 021 and 0. 581. Chromosome-by-chromosome analyses found that the signal was not localised to a specific chromosome (Supporting file 2). A prominent signal revealed introgression between species in the T. utriculata clade and all other Central American clades. Notable gene-flow signals were also indicated within the T. fasciculata clade. ƒ4ratio scores ranged between 0. 0017 and 0. 357, but in most hybridization events the proportion of the genome involved was estimated as smaller than 10% (Supporting Fig.
Discussion Hybridization is widely researched for its different roles in plant speciation. Based on a multi-species genomic dataset and phylogenomic approaches we highlight here the genus Tillandsia as a striking example of a highly reticulated radiation. The radiation likely proceeded in the presence of rampant inter-specific gene-flow, rather than by refined reproductive barriers  (Loiseau et al. 2019; Koch et al. 2022; Vera-Paz 2023). An abundance of sequencing data tends to generate high branch support in both concatenated alignments and a coalescent-based tree-building method  (Pease et al. 2016; Salichos and Rokas 2013 ), yet a detailed investigation in Tillandsia subg. Tillandsia revealed that a bifurcating tree offers an incomplete picture of the true relationships between species.
Acknowledgements This research was supported with funding from the  Christian Lexer professorship  start-up  BE772002  at the  University of Vienna , and the  FWF  grant  P35275  to O. P. The analyses took advantage of the  Vienna Scientific Cluster (VSC). We thank  Magnus Nordborg ,  James Pease  and  Hannes Svardal  for insightful discussions and advice. We thank the members of  Swiss SNSF Sinergia  project  CRSII3_147630  and  Juan P. Pinzón  for accession sampling.
Data collection The study protocol was pre-registered prior to data collection at Clinicaltrials. gov (NCT04909372). Participants were recruited using the PanelSens database declared to the relevant French authority (Commission Nationale Informatique et Libertés; CNIL; n°1,148,039). To be eligible for this study, participants were to be aged between 18 and 65 years, to be responsible for a substantial proportion of household grocery shopping, to be fluent in French, to have no dietary restrictions, to have no uncorrected eye problems and not to be aware of symptoms of dizziness when wearing a virtual reality headset. Recruitment was stratified by gender (50% male, 50% female) and age (33% 18-35 years, 33% 36-50 and 33% 51-65). A 10€ voucher was given to the participants who completed the study.
Study design This study was a randomised controlled trial in a virtual reality supermarket with two experimental arms: (1) no front-of-pack environmental labelling (no label condition) and (  2 ) front-of-pack environmental labelling (environmental label condition). A 1:1 2-block randomisation sequence (for male and female) was generated before recruitment using the Random Allocation Software  [29]  and research assistants were blinded to the labelling condition in which each participant was allocated. Regardless of the labelling condition, each participant in the virtual supermarket performed two tasks: 1/ choice of three meal components among 66 products (e. g. , lentils, carrots, ham, egg) for a composed meal, 2/ choice of one ready-to-eat meal among 30 products (e. g. , beef lasagne, risotto).
Virtual reality functionalities The virtual supermarket environment was inspired by recent work by Melendrez-Ruiz and colleagues (2021)  [30]  and was designed by the firm Strategir (https:// www. Fig. 1  Experimental design for the virtual reality tasks performed by the participants strat egir. com/ fr/) using Unity software under the VR headset Oculus Quest 2. Participants saw real size packaged food products on the supermarket shelves. With a hand controller, the participants were able to navigate the shelves, seize and examine products. When a product was seized, it could either be selected and put in the shopping basket or be placed back on the shelf.
Recorded data Food choices were recorded for each task within the VR headset. Each participant had to rate the eight food products selected for their level of familiarity (frequency of consumption of a similar product, ranging from 1 = "never" to 5 = "very often") and liking (continuous sale, ranging from 1 = "I do not like [the food product] at all" to 10 = "I like [the food product] very much").
Environmental label Calculation of the environmental score The environmental impact, measured by the Environmental Footprint single score (EF single score), of the 96 foods items included in the virtual supermarket was retrieved from the open-access Agribalyse database  [31]. The EF single score has been recommended by the European Commission when studying the environmental impact of food products  [32]. It aggregates 16 indicators derived from life cycle analysis (see supplementary file for details on the EF single score calculation, Note S2). We also considered three individual indicators retrieved from the Agribalyse database: greenhouse gas emissions (kg CO2 eq/kg of food product), ozone depletion (kg CFC-11 eq/kg of food product) and particulate matter (disease incidence/kg of food product) for sensitivity analyses.
These three individual indicators had the highest robustness in the Agribalyse database  [31]. A five-level environmental impact score (ranging from A to E) was calculated based on the EF single score of the products. Levels cut-offs were calculated separately for the 66 meal components and the 30 ready-to-eat meals. They were defined as the quintile values from a larger selection of similar foods from the Agribalyse database. Details regarding the five-level environmental impact score calculation are presented in supplementary file (Note S3). The food products were distributed in the five environmental impact scores as follows for meal compo-.
Sample size We powered the primary analyses in order to detect a d = 0. 50 effect size of labelling condition on EF single scores based on the results of a previous randomised controlled trial that tested the effect of an environmental label on canned soup choices  [14]. A sample size of 122 participants was required for 80% power at α = 0. 05 (SAS 9. 4). We aimed to recruit a sample of 130 participants to account for potential data loss due to technical problems and drop-outs.
Acknowledgements We thank the  ChemoSens platform  for the help with the recruitment of participants, in particular  C. Martin  and  F. Durey. We thank  V. Feyen  and  L. Ben Sussan  for their help with data collection and  K. Pagnat  for his help with the development of the virtual supermarket. We also thank  L-G. Soler  and  L. Muller  for their valuable inputs on the protocol.
Prototyping and Support Tool To support this phase, we have developed LADStudio  [Sadallah and Gilliot, 2023] , a tool that allows generating LAD prototypes through a declarative specification resulting from the ideation phase (Figure  2 ). It is provided as a web service integrating an instance of the Grafana visualization tool for rendering. The specification module allows progressively describing a LAD (Figure  2b ). This description can be a translation of the specifications made during the ideation phase (e. g. , using PaDLAD). Sequential screens compose a scenario: (1) description of the target context and intended use; (2) definition of the main goal of the LAD; (3) description of the monitoring, understanding, and projection views; and (4) generation of a LAD specification that can be displayed on the Grafana module (Figure  2d ).
Methodology Two qualitative studies were conducted to evaluate the two tools. Fifteen participants took part in the PaDLAD study, which focused on the ideation phase and involved teachers, researchers, and instructional designers with no specific knowledge in Educational Technology. Thirteen participants participated in the LADStudio study, which focused on the prototyping phase and involved teachers, researchers, and instructional designers with technical knowledge in learning dashboards and Human-Computer Interaction (HCI) in the context of Educational Technology. Although LADStudio was intended for developers, participants with technical knowledge were recruited due to the difficulty of finding enough LAD developers to participate in the study. The socio-demographic data of the participants are presented in Table  2.
INTRODUCTION XRP Ledger is one of the oldest, well-established cryptocurrencies. In 2022 it ranked seventh by market capitalization. The XRP Ledger aims to provide high transaction throughput whilst maintaining security against Byzantine failures. The XRP Ledger Consensus Protocol is a Federated Byzantine Agreement protocol  [28] , in which each participant selects a Unique Node List (UNL) of validators. These validators are not necessarily trusted individually but are believed not to collude as a collective. Servers running the rippled software join into a single peer-topeer network. The peer-to-peer network's topological structure affects the blockchain's security, resilience, and efficiency. By design, there are no direct incentives to run rippled software  [4]. Those who participate do so because they are interested in the long-term health of or are participants on the XRP Ledger.
A corpus of research focuses on the study of structural properties of Bitcoin  [14, 23]  and Ethereum  [17, 26, 31]. To the best of our knowledge, there are no works examining the overlay network of the XRP Ledger. The overlay network is uniquely suited for study. Unlike other blockchains that focus on hiding their topology, XRP Ledger natively supports network crawling  [3]. The public availability of data enables researchers to determine the accurate topology of the network. In this paper, we provide an in-depth analysis of the graphtheoretic properties of the XRP Ledger overlay network. Our main contributions are as follows: • We measure the structural properties of the network, as well as their evolution over time. We discover a central component of the network. • We examine the stability of the nodes and their uptime.
BACKGROUND The XRP Ledger consists of nodes running the rippled [16] software. The interconnected rippled servers form the decentralized peer-topeer overlay network. The node owners configure it to accept some number of inbound and outbound connections. Each outgoing connection corresponds to an incoming connection at another node. When nodes connect, the communication over the link is bidirectional. We, therefore, represent the overlay network as a directed graph. The direction of an edge identifies the node that initiated the connection. A node gets initial entry into the overlay network by connecting to several hardcoded bootstrapping hubs. These hubs share the addresses of other nodes with available inbound connections. The node continues to establish links to others until it reaches the desired limit of outgoing connections.
NETWORK ANALYSIS Network Topology. We used the XRP Ledger Crawler  [15]  to discover the nodes in the overlay network. The crawler starts by querying the peers of a single rippled server 1. It adds the new nodes to a list and calls every node with a known IP address. The crawler repeats this process until it no longer discovers new nodes. We enriched the snapshot data with Autonomous System information. We collected the XRP Ledger network snapshot for two months, between 05/01/2022 and 01/03/2022. We crawled the network topology at one-hour intervals. In two months, we collected 1,290 snapshots. We made the datasets available online for further research  [5]. Size. The network is relatively small. We observed 948 nodes and 15,010 links on average. In comparison, Bitcoin has 50,000 nodes and Ethereum 12,000 nodes  [26].
Single Network We conducted an in-depth analysis of a single XRP Ledger network snapshot. We selected the sample whose node and edge counts are the closest to the mean of the dataset. In the remainder of this Section, we discuss our findings. Degree Distribution. The network degree distribution impacts many of its properties, such as message propagation delay and the resilience of the network  [8]. Random networks have binomial degree distributions, whereas real-world networks contain a small number of highly connected nodes that cannot be accounted for by random models  [9]. In Figure  1a , we illustrate the percentage of nodes (y-axis) with a given number of combined incoming and outgoing connections (x-axis). The distribution's shape is similar to a gamma distribution with a long right tail.
It has been shown that only models including rotation-induced processes were able to reproduce the correct Li-depletion over evolution (e. g. Palacios et al. 2003; Somers & Pinsonneault 2016; Charbonnel et al. 2020; Eggenberger et al. 2022; Paper I) , impacting predictions for the different stellar evolutionary steps, and pointing the inconsistency of classical models. In this work, we explore the evolution of the angular momentum transport efficiency from MS to SGB and RGB phases, and how it impacts the Li (and beryllium) surface abundance evolution. We extend models, that we already explored and validated for the specific case of the MS solar-type stars in a previous study (Paper I), to evolved low-mass stars at different masses. In Sect. 2, we present the observational data that we used to constrain the processes involved in our models.
In Sect. 3, we describe the input physics of the stellar models and the different processes implemented in the evolution code STAREVOL used for this work. In Sect. 4, we estimate the transport efficiency that is required to reproduce the core rotation rate of a sample of nine stars (eight SGB and one RGB) for which we have access to the rotation asteroseismic analysis. We study the effects and the relevance of a time-dependent additional viscosity related to the azimuthal magneto-rotational instability (AMRI) defined by  Spada et al. (2016) , and successfully used by  Moyano et al. (2023) , and explore our model predictions. We apply these models for a grid (0. 8-1. 5 M , step of 0. 1 M ) at solar metallicity, and explore the Li and beryllium abundance evolution in Sect. 5. In Sect. 6, we summarise our results, discuss model predictions, and present our conclusions.
Observational data To constrain the evolution of the angular momentum transport, we gathered a sample of SGB and RGB stars for which core rotation rates constraints are available from asteroseismic analysis. We have no access to stars for which both a seismic analysis and Li abundance determination have been done. We then completed our analysis with the compilation of another sample of low-mass stars for which we have access to Li and beryllium (hereafter, Be) abundances determinations from the MS phase to the RGB bump.
(2014 Deheuvels et al. ( , 2020)) , one RGB star from Di  Mauro et al. (2016) , and a large sample of RGB stars from  Gehan et al. (2018). The effective temperature and surface gravity of the eight SGB stars, and of KIC 44487777, are taken from the reference papers and given in Table  1. We used the Mikulski Archive for Space Telescopes (MAST database 1  ) for the sample analysed by  Gehan et al. (2018).
Input physics We used version 4. 0 of the stellar evolution code STAREVOL, as described in Paper I (for general information and previous versions, see  Siess et al. 2000; Palacios et al. 2006; Decressin et al. 2009; Lagarde et al. 2012; Amard et al. 2019)  and we refer to this work for further details and references. The models presented in this work were computed with the same inputs physics (equation of state, opacities, nuclear reactions, model atmosphere, and mass loss) as in Paper I. We used the same constant value for the mixing length parameter (classical model: α MLT = 2. 1100, models including rotation: α MLT = 2. 2236, assuming the Schwarzschild criteria for convective stability) and the initial abundances that resulted from model calibrations on the Sun (reference abundances from  Asplund et al.
Acknowledgements. This work was supported by the  European Union (ChETEC-INFRA , project no. 101008324 ). The author thanks  A. Bonhomme ,  M. Pinsonneault , and  M. Cantiello  for helpful discussions, and the anonymous referee for constructive comments on the manuscript. Special thanks go to  J. Kerutt  for discussions all along this work. The author also thanks the  Department of Astronomy of the University of Geneva  for hosting and support during part of this work. This research has made use of  NASA 's Astrophysics Data System Bibliographic Services. A119, page 13 of 14.
We study the basic algebra of catoids and present a series of examples, including categories and non-categories. Most of these results have been formalised with the Isabelle/HOL proof assistant. (See https://github. com/gstruth/catoids. ) It turns out that the locality laws s(x ⊙ s(y)) = s(x ⊙ y)a n dt(t(x) ⊙ y)=t(x ⊙ y) of catoids, which have previously been studied at the level of modal semigroups, semirings and quantales  [6, 7, 8, 15] , are equivalent to the composition pattern of categories, namely that x ⊙ y is defined, and hence not ∅, if and only if t(x)=s(y) (for categories, the order of composition is usually reversed). Indeed, local catoids based on partial semigroups are (small) categories. As a second step, we generalise the standard definitions of domain and codomain for modal semirings and quantales to convolution algebras.
Along similar lines it seems possible to define higherdimensional globular catoids as generalisations of 2-categories and prove correspondence results with respect to the higher globular Kleene algebras introduced for higher rewriting  [2]. Ultimately, this should lead to ω-catoids as generalisations of ω-categories and the corresponding ω-quantales, which would share features of modal and concurrent quantales, in combination with axioms for globular structure. Further, the relevance of the weakened domain and codomain quantales of Section 10 for the verification of quantitative computing systems, in particular stochastic and probabilistic ones, remains to be explored. We also aim at a categorification of the approach in terms of monoidal categories with Day convolution. While this adds generality, we have chosen a simpler algebraic approach in this work with a view on software verification applications with proof assistants like Isabelle, where reasoning with monoidal categories, coends or coherence conditions seems currently unwieldy.
Relational monoids, catoids and the construction of convolution quantales have already been formalised with Isabelle  [9] ; Isabelle verification components for separation logic use a less general approach with partial abelian monoids and generalised effect algebras instead of catoids  [10]. Last, but not least, Jónsson-Tarski duality should be related to the convolution algebra setting and the role of the weight algebras should be explained. Funding Information Open access funding provided by NTNU Norwegian University of Science and Technology (incl St. Olavs Hospital -Trondheim University Hospital) Data availability statement Data generated for this study is available at https:// github. com/gstruth/catoids. which is valid in some, but not all function systems. They point out that all axioms except (3c), which has subsequently been called twisted axiom, hold of binary relations.
Since there is no public dataset and smartphones are commonly used as tools to take pictures, it might then be conceivable for farmers to use them to categorize the infection level of their crops. In this work, we developed a system called CactiVIT that instantly determines the health status of cacti using the Visual image Transformer (ViT) model. We also provided a new image dataset of cochineal infested cacti. 1 Finally, we developed a mobile application that delivers the classification results directly to farmers about the infestation in their fields by showing the probabilities related to each class. This study compares the existing models on the new dataset and presents the results obtained. The VIT-B-16 model reveals an approved performance in the literature and in our experiments, in which it achieved 88.