Alice Missud
email: missud.a@parisnanterre.fr

INVESTIGATING THE DISTRIBUTIONAL PROPERTIES OF RIVAL -AGE SUFFIXATION AND VERB TO NOUN CONVERSION IN FRENCH 1

RESUME

Les travaux sur la compétition en morphologie dérivationnelle en français se sont principalement focalisés sur l'identification des propriétés sémantiques des suffixations rivales en -age, -ment et -ion construisant des noms d'événements à partir de verbes. Cependant, un autre schéma rival jusque-là non pris en compte est la conversion de verbe à nom, qui dérive également des noms événementiels. Cet article présente une étude de la rivalité entre la conversion de verbe à nom et la suffixation en -age en s'attardant sur les propriétés distributionnelles de leurs dérivés. En utilisant des méthodes quantitatives et des modèles de sémantique distributionnelle (DSM), nous montrons que le degré de dispersion et spécificité sémantique des nominalisations diffère d'un schéma à l'autre. 1 We are grateful to the participants of ISMo 2019

INTRODUCTION

Research in derivational morphology has long sought to explain the reasons for the coexistence of rival morphological schemas that select the same bases to construct similar meanings. In French, the rivalry between -age, -ment and -ion suffixations that derive deverbal event nouns has received the most attention (see, for example, [START_REF] Dubois | Etude sur la dérivation suffixale en français moderne et contemporain[END_REF][START_REF] Martin | The semantics of eventive suffixes in French[END_REF][START_REF] Uth | The rivalry of the French nominalization suffixes -age and -ment from a diachronic perspective[END_REF][START_REF] Fradin | La variante et le double[END_REF][START_REF] Fradin | Competition in derivation: What can we learn from French doublets in-age and -ment ?[END_REF][START_REF] Dal | Toile versus dictionnaires: Les nominalisations du français en -age et en -ment[END_REF][START_REF] Wauquier | Contributions of distributional semantics to the semantic study of French morphologically derived agent nouns[END_REF]. However, another important rival in this competition that has not been considered as such is verb to noun conversion (henceforth "V to N conversion"), which has been shown to derive a significant proportion of event nouns from verbs [START_REF] Tribout | Noun to verb and verb to noun conversions in French[END_REF] as in (1).

(1) survoler 'to fly over' → survol 'hovering', baisser 'to drop' → baisse 'drop', secouer 'to shake' → secousse 'shake' venir 'to come' → venue 'coming'

This neglect is mostly due to its belated recognition as a derivational morphology schema (see section 1). Our work is rooted in the theoretical background of lexemic morphology [START_REF] Aronoff | Morphology by Itself[END_REF], for which verb to noun conversion is considered a lexeme-formation process similar to affixal ones, except for the phonological part of the derivation, since conversion is characterized by a phonological identity between the two lexemes (or, more precisely, between a stem of the base verb and the stem of the derived lexeme).

There are many factors (phonological, morphological, syntactic, semantic, pragmatic, etc.) that may shed light on the competition between two morphological processes. The literature devoted to the morphological rivalry that constructs deverbal event nouns has mostly focused on the semantic features that can differentiate them by investigating the base verbs and the aspectual and argumental properties of the derived nouns. For example, with regard to the case of rivalry we are interested in, some deverbal converted nouns ending in ée (arrivée 'arrival', plongée 'diving', traversée 'crossing') have already been compared with -age suffixed nouns in order to find distinctive syntactic and aspectual properties [START_REF] Ferret | Rivalry between French -age and -ée: the role of grammatical aspect in nominalization[END_REF][START_REF] Ferret | L'aspect grammatical dans les nominalisations en français: les déverbaux en -age et -ée[END_REF]. Our research goes further and takes all types of event deverbal converted nouns into account and not only those ending in ée. In addition, we are studying semantic issues that have not yet been addressed. Thus, for the purpose of introducing V to N conversion as a rival in the competition that opposes deverbal event nouns in French, this paper investigates the semantics of -age suffixation and V to N conversion as a first step by looking at the distributional properties of the lexemes they derive.

In this paper, we explore the distributional properties of derived nouns using Distributional Semantics Models (DSMs). Such models, based on the distributional hypothesis [START_REF] Harris | Distributional structure[END_REF][START_REF] Firth | A synopsis of linguistic theory, 1930-1955[END_REF], allow for quantitative analyses of the semantics of words by converting nouns into word vectors that represent their distribution in a corpus. Word vectors can then be used to calculate semantic similarities between words by measuring the cosine distance between vectors. Advanced word vectors generated by Word2Vec neural network-based models [START_REF] Mikolov | Efficient estimation of word representations in vector space[END_REF] have recently been used to discriminate French rival nominalization schemas. Notably, [START_REF] Wauquier | Contributions of distributional semantics to the semantic study of French morphologically derived agent nouns[END_REF] provided evidence that -age, -ment and -ion suffixations could be semantically discriminated based on the semantic similarity between morphologically related nouns. By computing word similarities, they showed that suffixed nouns attract an overwhelming majority of nouns that are derived from the same schema. We aim to investigate if this holds for -age suffixation versus V to N conversion, as well as for discriminating converted nouns based on their stem.

Apart from distinctive semantic properties between rival schemas, word vectors can also be used to measure the semantic dispersion of lexemes in order to get a sense of the extent to which they semantically cluster together depending on the schema they derive from. In the case of morphological rivalry, Lindsay and [START_REF] Aronoff | Natural selection in self-organizing morphological systems[END_REF] argued that two rival schemas can be discriminated by their degree of specialization and versatility. This suggests that schemas will therefore self-organize in order to coexist while remaining productive: one will be more specialized by investing a specific niche while the other will be more versatile. Consequently, we measured the degree of specialization of -age suffixation and V to N conversion by investigating the semantic niches that lexemes might occupy and the degree of semantic relatedness they maintain with their pairs using word vectors.

We believe that the results obtained by manipulating word vectors need to be verified scrutinizing them from various angles The series of experiments that are presented in this paper form part of this perspective as their results intersect and complement each other. First, we present the data and the DSM we used as well as the frequency distribution of the data according to the schema they derive from. The second section of this paper presents results

showing that -age suffixation and V to N conversion (and its different types) differ in terms of semantic relatedness with their pairs by computing word similarities. The following section proposes a method for predicting the semantic dispersion of lexemes depending on their schema. The results are then used in Section 4 to categorize the different semantic niches that N-age and V to N converted nouns occupy.

DATA

Conversion, a particular case of lexical derivation

Our work is rooted in the perspective that conversion is a derivational morphological process (see, among others, [START_REF] Plag | Word-formation in English (CAMBRIDGE TEXTBOOKS IN LINGUISTICS)[END_REF][START_REF]Categories in the Lexicon[END_REF][START_REF] Bauer | The Oxford Reference Guide to English Morphology[END_REF]and, for French, Corbin 1987;[START_REF] Kerleroux | Identification d'un procédé morphologique: la conversion[END_REF][START_REF] Tribout | Noun to verb and verb to noun conversions in French[END_REF][START_REF] Tribout | Verbal stem space and verb to noun conversion in French[END_REF][START_REF] Tribout | Problèmes de compositionnalité en morphologie dérivationnelle: le cas de la conversion[END_REF]. The arguments for this position are based on properties such as: conversion involves substitution of a new inflectional paradigm, new syntactic properties (new word-class), and new semantic properties. Thus, according to these properties, the same form is interpreted as a different lexeme and conversion is part of lexical derivation (see Valera 2014 for a summary of these questions). The specificity of conversion with regard to affixation, for example, lies in the formal identity between the base and the derivative (which poses specific problems in determining the directionality of the process). By postulating that conversion is a word-formation process that results in unmarked (by affixes) word-class change, we reject other approaches that attribute another status to conversion, in particular: (i) the one that views conversion as "zero-derivation" or "zero-affixation"; (ii) the one that considers conversion as a non-derivational lexical creation that consists of a second introduction of an existing word within a different category in the lexicon (as for Lieber 2005) and (iii) the one that denies the derivational or lexical process because it considers that word-class change does not exist: according to this view, lexical items are unspecified as regards word class and may be specified as members of different categories according to the context (see Distributed Morphology, Marantz 1997, for example).

French N to V and V to N conversion: the issue of phonological identity

The confusion surrounding the recognition of V to N French conversion as a derivational process dates back to [START_REF] Darmesteter | De la création actuelle des mots nouveaux dans la langue française et des lois qui la régissent[END_REF] and was reproduced by [START_REF] Nyrop | Grammaire historique de la langue française III[END_REF] which have long served as a reference. This is due in particular to the difficulty in recognizing a phonological identity between verb and noun (see [START_REF]Morphologie dérivationnelle et structuration du lexique[END_REF][START_REF] Kerleroux | Identification d'un procédé morphologique: la conversion[END_REF]. While formal identity between the base and the derived lexeme is an important condition for conversion, it may fail to apply in many languages where formal changes appear nevertheless: for example, stress shift between English nouns and verbs (torm´entV -t´ormentN; constr´uctV -c´onstructN) [START_REF] Plag | Word-formation in English (CAMBRIDGE TEXTBOOKS IN LINGUISTICS)[END_REF]; or formal differences between the base verbal lexeme and the converted noun lexeme in German (AntwortenV -AntwortN; FragenV -FrageN) [START_REF] Alexiadou | Conversion[END_REF] or in Italian (caminareV 'to walk' -camminoN 'walking'; sostareV 'to stop, to rest' -sostaN 'stopping, rest') [START_REF] Marzo | Italian verb to noun conversion: the case of nouns in -a deriving from verbs of the 2 nd and 3rd conjugation[END_REF]. French V to N conversion also presents the same kind of phonological difference: because of a noticeable stem allomorphy of French verbs, and the decision to represent the verbal lexeme by the infinitive form, the base verbal lexeme is not phonologically identical to the converted noun lexeme (see examples in (2)). To account for it, we follow Tribout's analysis (2010Tribout's analysis ( , 2012) ) based on [START_REF] Aronoff | Morphology by Itself[END_REF] and Bonami and Boyé (2003)'s treatment of allomorphy for which each verb has a list of indexed morphemic stems. In this perspective, inflectional and derivational morphological formations select one of these stems to construct either a word form or a lexeme. Tribout showed how stem spaces can be used in derivation to account for verb to noun conversion. She demonstrated that the French verbal stem space contains fourteen stems, and that "each of them is potentially available to be the input of deverbal lexeme-formation processes" (Tribout 2012: 122). Her work proposed that three sorts of stems are available to derive deverbal converted nouns: stem 0 (2a), (also used to inflect, for example, the present singular forms of 1 st conjugation verbs), stem 12 (2b) (also used to inflect the past participle forms of verbs), and stem 13 (2c) (hidden to inflection and only used in derivation for deverbal -if, -eur/rice and -ion suffixations) (see more examples in Tribout 2012).

(2) a. marcherV 'to walk' /maʁʃ/ → marcheN 'walk' /maʁʃ/ b. sortirV 'to go out' /sɔʁti/ → sortieN 'exit/outing' /sɔʁti/ c. défendreV 'to defend' /defɑ s/ → défenseN 'defence' /defɑ s/ Thus, French V to N conversion can be characterized by a phonological identity between the base and the derivative where the variety of stems involved is considered instead of the phonological form of the lexeme. Stem selection in V to N conversion is crucial for the present research as we aim to investigate the hypothetical semantic distributional differences between converted nouns depending on the stem they select.

Word vectors

Following Firth's intuition that "You should know a word by the company it keeps" (1957), the distributional hypothesis stipulates that words that have similar meanings share similar contexts. The idea that the meaning of a word can be inferred by knowing the words that surround it has been widely used in the field of natural language processing. Distributional semantics models (DSMs) such as Latent Semantic Analysis [START_REF] Landauer | An introduction to latent semantic analysis[END_REF] operationalize this principle by representing words with word vectors. These vectors are the result of a transformation from textual (actual word) to numerical (vector) that captures the contextual-meaning usage of words, where each dimension represents the frequency of cooccurrence of a target word with others in a given corpus. In derivational morphology, DSMs have proven successful in predicting the directionality of verb to noun conversion in English [START_REF] Kisselew | Predicting the direction of derivation in English conversion[END_REF] or the lack of semantic regularity in derivation as opposed to inflection in French [START_REF] Bonami | Inflection vs. derivation in a distributional vector space[END_REF].

More recently, predictive models generated by neural network-based tools such as Word2Vec [START_REF] Mikolov | Efficient estimation of word representations in vector space[END_REF] have been popularized because of their high performance in computing word similarities or analogies. While they rely on the same principle, these models generate dense vectors (or word embeddings) through unsupervised machine learning techniques. Although they can provide results that are close to accurate semantic intuitions, the opacity of word embeddings' dimensions makes the interpretation tricky and results need to be complemented by qualitative analyses when investigating linguistic phenomena.

This study was undertaken from this perspective with the idea that morphologically related lexemes that have the same distribution might cluster because they share at least one specific morpho-semantic property. We used a CBOW model from Word2Vec trained on a concatenation of three massive French corpora extracted from the web: frCOW [START_REF] Schäfer | Building large corpora from the web using a new efficient tool chain[END_REF]Schäfer 2015: 9 billion words in 2016), frWaC [START_REF] Baroni | The WaCky wide web: a collection of very large linguistically processed web-crawled corpora[END_REF] 1.9 billion words in 2009) and frWiki (178 million words, a dump of Wikipedia encyclopedic pages from 2007). The model was trained on words with a frequency of at least 5 using default parameters (window of 5; negative sampling, 5 items).

Collecting the lexicons

Data collection was subject to several constraints in order to find a balance between quantity and quality while manipulating word vectors.

A first constraint is that the quality of word vectors depends on the number of examples that is found in the corpus that the model is trained on. Consequently, highly frequent words are better represented as they appear in many contexts. Zipf's law states that the frequency of words in a corpus is inversely proportional to their rank. In other words, we expect to find few high-frequency words and many low-frequency ones. Therefore, the number of frequent derivatives that we can select to ensure the quality of the vectors is rather limited.

Another constraint lies in the extraction of converted nouns. Converted lexemes pose four major challenges for computational linguistics. First, as no affix is involved, their identification in corpora cannot rely on spotting an additional and specific phonological sequence. Secondly, inflected nouns and verbs are sometimes phonologically identical (marcheV / marcheN, avancéeV / avancéeN). Their identification therefore relies on the quality of morphosyntactic tagging, which is usually subject to many errors when it comes to participles in French. Another major problem is the direction of derivation (verb to noun or noun to verb), which is sometimes impossible to predict. As stated by [START_REF] Tribout | Problèmes de compositionnalité en morphologie dérivationnelle: le cas de la conversion[END_REF] for French, the orientation of conversion is always questionable since no information can be truly reliable to assess which lexeme appeared first (dating, phonetics, semantic interpretation, semantic range, frequency of occurrence). Lastly, converted nouns are not necessarily eventive and can have multiple semantic interpretations such as instrument, agent or location [START_REF] Tribout | Noun to verb and verb to noun conversions in French[END_REF][START_REF] Tribout | Problèmes de compositionnalité en morphologie dérivationnelle: le cas de la conversion[END_REF]. Instead of extracting converted nouns automatically, we had to rely on existing annotated datasets.

As a result, we collected a total of 300 nouns that have at least one eventive interpretation (some polysemous nouns can also denote results). 150 of them are -age suffixed nouns extracted from VerNom [START_REF] Missud | VerNom: une base de paires morphologiques acquise sur très gros corpus[END_REF], a lexical database consisting of 25 857 verb-noun pairs acquired from frCOW [START_REF] Schäfer | Building large corpora from the web using a new efficient tool chain[END_REF][START_REF] Schäfer R | Processing and querying large web corpora with the COW14 architecture[END_REF], a massive corpus from the French web that dates back to 2016 and that covers a wide variety of texts (press, forums, encylopedias...). The other 150 are converted nouns taken from Tribout's lexicographic database (2010). Tribout's data come from two online dictionaries: Trésor de la Langue Française informatisé and Le Petit Robert Electronique. The data were given an annotation for the stem (0, 12 or 13), the semantic interpretation (action, result, agent, location...), as well as the orientation of conversion when it has been retrieved (verb to noun, noun to verb or unknown). Only nouns that were annotated as deverbal and eventive were selected. Among them, 71 are derived from stem 12 of their base verb (sortie 'exit', complainte 'lamentation', huée 'booing'), 67 from stem 0 (attaque 'attack', mépris 'contempt', retard 'delay') and 12 from stem 13 (course 'race', défense 'defence', plagiat 'plagiarism'). Although we tried to balance out the number of converted nouns of each type, this distribution reflects the one that is found in Tribout's dataset. The derivatives we selected are the most frequent event nouns we could find in frCOW (see appendix for the word frequency list). We excluded doublets (in our case, situations where two morphological processes select the same verbal base to derive at least three different event nouns, as in porter 'to carry, to convey' → port 'carrying', portée 'scope', portage 'portage') to focus on the prototypical base selection behavior of each schema that distinguishes both of them by making sure that the verbal bases were exclusively selected by one schema to construct event nouns. Each derivative was then assigned a 100-dimensional vector from the Word2Vec model. Note that only a small portion of converted nouns have low frequency (découple 'decoupling', 2 occurrences) and were kept in our data as we needed the same amount of N-age and converted nouns.

Token frequency of lexemes according to their schema

In order to get a sense of the frequency distribution of our data, we compared the frequencies of the derivatives according to the schema they derive from and the stem selected for conversion. The token frequency of each noun was extracted from frCOW's word frequency list. Figure 1 shows a boxplot 2 that represents the distribution of the frequencies of nouns; the Y-axis shows the frequency and the boxes in the X-axis each indicate a schema (-age suffixation '-age', conversion on stem 0 'stem 0', conversion on stem 12 'stem 12' and conversion on stem 13 'stem 13'). The larger the box, the higher the frequency for a specific type of noun.

The results show that -age suffixation and stem 12 conversion comprise the least frequent derivatives. As shown by the median situated at 15 000,age suffixed nouns have the lowest frequencies. Half of them have a token frequency that ranges from 10 000 to 30 000. Stem 12 converted nouns follow the same trend: 50% have a frequency that goes from 5 000 to 60 000, with a median of 10 000. Stem 13 and stem 0 converted nouns are the ones that have the highest frequencies in comparison. 50% of stem 13 converted nouns (the most frequent in our data) have a token frequency that ranges from 15 000 to 370 000 and half of them have frequencies that go beyond 75 000 as shown by the median. Stem 0 converted nouns are the second most frequent: 50% of them have a frequency that ranges from 15 000 to 180 000. Overall, the most frequent converted nouns that we found in Tribout's data are more frequent than the most frequent -age suffixed nouns that are found in frCOW.

As proposed by [START_REF] Resnik | Using information content to evaluate semantic similarity in a taxonomy[END_REF], the token frequency of a word can correlate with its informational content: as highly frequent words are more likely to appear in various contexts than low-frequency ones, they are likely to lose semantic specificity and be more generic and polysemous. Considering this hypothesis and the distribution observed in Figure 1, we would expect converted nouns (especially those derived from stems 0 and 13) to be more polysemous and generic than -age suffixed nouns. Additionally, as pointed out by [START_REF] Baayen | Quantitative aspects of morphological productivity[END_REF], the productivity of a schema can have an effect on the token frequency of its lexemes: highly productive schemas will construct many nonce-formations with compositional meanings and low frequency, while unproductive schemas will concentrate frequencies around a small portion of highly frequent derivatives. While -age suffixation is the second most productive deverbal suffixation that derives event nouns according to the data available on the French web [START_REF] Missud | VerNom: une base de paires morphologiques acquise sur très gros corpus[END_REF], there is no evidence for the productivity of conversion. Although this paper does not aim to measure the productivity of conversion, we would expect -age suffixation to be more productive than V to N conversion when deriving event nouns since converted nouns display higher frequencies overall. In the following sections, we investigate the hypothesis of a lack of homogeneity among converted nouns compared to -age derivatives by manipulating word vectors. largest data points. Points that are shown outside the box and the lines are outliers, i.e. marginal datapoints that lie outside the pattern of the distribution.

SEMANTIC DISCRIMINATION OF MORPHOLOGICAL SCHEMAS

Our first task was to investigate the semantic relatedness between derivatives according to their morphological schema. Because we are manipulating word embeddings, semantic relatedness between lexemes can be measured by computing the cosine similarity between two word vectors. This measure gives a similarity score that ranges from -1 (diametrical opposition) to 1 (strict similarity) to a pair of vectors. As an example, the cosine similarity of nettoyage 'cleaning' and lavage 'washing' is 0.85, which means that nettoyage and lavage are remarkably similar in our model. In contrast, the cosine similarity of nettoyage and fricassée 'fricassee' is 0.4, meaning that their semantic similarity is low in comparison.

Cosine similarity can be used to determine how semantically related the lexemes that belong to a certain morphological group are on average. Consequently, we searched the corpus for word similarities in order to elucidate the semantic homogeneity of derivatives of each type. For example, if -age suffixed nouns are more semantically similar to their pairs than to V to N converted nouns, there could be a proper semantic identity that differentiates N-age from other eventive nouns. Similarly, if V to N converted nouns are closer to each other than they are to N-age, converted nouns might present specific semantic properties related to the schema they derive from. Differences between -age suffixation and V to N conversion could be found in the degree of semantic relatedness their derivatives share with their pairs. Moreover, the different types of V to N converted nouns can be investigated as well. Although [START_REF] Tribout | Noun to verb and verb to noun conversions in French[END_REF] showed that the semantic interpretation of converted nouns globally remained the same regardless of the stem selected for derivation, DSMs could help find discrepancies in the distributional properties of converted nouns that have not yet been examined. By discriminating V to N converted lexemes based on the stem they are derived from, we explore the hypothesis that there might be a semantic differentiation between stem 0, stem 12 and stem 13 V to N conversion and aim to address several questions: do V to N converted nouns have higher semantic similarity scores with converted nouns that are derived from the same stem? Do some stems group more semantically homogeneous V to N converted nouns than others; for example: are stem 12 converted nouns closer to their counterparts than stem 0 converted nouns are?

First, we present a study of the semantic attraction of derivatives based on their closest semantic neighbors. Then, we complement this study by examining the degree of attraction for each schema.

-age suffixation vs. V to N conversion

The n-closest neighbors of a given word are the n words that have the highest cosine similarity scores with the word, ranked from the most similar to the least similar (among the n most similar). For example, the 10 closest neighbors of nettoyage 'cleaning' are shown in (3).

( Here, lavage 'washing' is the closest neighbor of nettoyage 'cleaning', with a cosine similarity score of 0.85. The last neighbor, polissage 'polishing' is the one that has the lowest similarity score (0.7) among the 10 closest neighbors. For the purpose of this study, we computed the 10 closest neighbors of each derivative (except for stem 13 converted nouns that were too few in number to be considered for this experiment). In order to calculate the morphosemantic attraction between the lexemes, we counted the number of neighbors that belonged to the same morphological category as the tested derivative (-age suffixation, V to N conversion, stem 0 V to N conversion or stem 12 V to N conversion). For example, with (3), as all the neighbors are also N-age, nettoyage has an attraction score of 10/10, because all ten of its closest neighbors are derived from the same morphological schema. Each derivative was given an attraction score based on its neighbors. To make sure that the tested stem 0 and stem 12 converted nouns (for which fewer examples were collected compared to N-age) had equal chances of finding N-age or converted nouns derived from different stems in their neighbors, we downsampled the number of other derivatives. For example, when 71 stem 12 V to N converted nouns were tested, the cosine similarity scores were calculated on a sample of 71 stem 12 V to N converted nouns and 71 randomly chosen derivatives of other types.

We compared the distribution of attraction scores for -age suffixation, V to N conversion, stem 0 and stem 12 V to N conversion. If attraction scores are high for a great majority of lexemes of a certain type, semantic unity could be attributed to the schema they derive from.

Table 1 shows the attraction scores of the derivatives depending on their schema. The first row ("Range") shows the range of scores that lexemes derived from a schema can have. IQR ("interquartile range") shows the scores that are situated between the first and third quartile of the distribution (i.e. middle 50% of the lexemes' scores). The median is the value that separates the data into two halves: a median at 5 for a schema indicates that 50% of the scores are below 5 and that 50% are above 5. The last row indicates the average score (arithmetic mean) for each schema. The results in Table 1 show that N-age are the derivatives that attract their pairs the most. The total N-age in our data can have 8 to 10 N-age in their closest neighbors while 50% have 9 to 10 (IQR). The median of 10 indicates that in most cases, no V to N converted noun can be found among the closest neighbors of N-age. On average, 91% of their neighbors are -age suffixed nouns as well.

Additionally (not shown in Table 1), we calculated the average proportion of stem 0, stem 12 and stem 13 V to N converted nouns that are found in -age suffixation's closest neighbors. On average, we found 6.4% of stem 0, 1.8% of stem 13 and 0.5% of stem 12 V to N converted nouns. Stem 0 converted nouns are by far the most frequent converted lexemes among the 10 closest neighbors of N-age, while stem 12 V to N converted nouns only appear marginally. Note that stem 13 converted nouns are underrepresented in our data (12 items) and are therefore less likely to appear among the neighbors or any derivative than N-age, stem 0 and stem 12 converted nouns. Their striking representativity among the closest neighbors of -age derivatives is thus more significant than that of stem 12 V to N converted nouns. These results indicate that stem 12 V to N converted nouns might not share -age derivatives' distributional properties, while stem 0 and stem 13 V to N converted nouns could have some semantic properties in common.

Although attraction scores are not as high for V to N conversion as a whole, the results in Table 1 show that a majority of V to N converted nouns are found among their 10 closest neighbors as well. While the number of V to N converted nouns among V to N converted nouns' neighbors ranges from 0 to 10, 50% of converted nouns have 5 to 10 converted nouns among their neighbors. With a median of 10, most converted nouns only attract converted nouns. On average, 77% of their neighbors are V to N converted nouns. Overall, V to N converted nouns attract their pairs, but not as strikingly as Nage do. Compared to V to N conversion, -age suffixation appears as more semantically homogeneous, a feature that has already been observed when comparing N-age with N-ment and N-ion (Wauquier et al. 2019, forthcoming).

Nonetheless, the results for stem 0 and stem 12 V to N converted nouns indicate that the semantic homogeneity varies greatly from one stem to the other. Stem 0 V to N converted nouns can only be slightly discriminated from the other derivatives in our data. The number of stem 0 V to N converted nouns among the neighbors ranges from 1 to 10. As the median shows, 50% of stem 0 converted nouns have more than 6 stem 0 converted nouns among their neighbors. With an average of 63%, stem 0 V to N converted nouns do not attract their pairs as significantly as V to N converted nouns in the general case. Stem 12 V to N converted nouns have much higher scores in comparison. The number of stem 12 converted nouns found in the 10 closest neighbors ranges from 5 to 10, with 50% of them having 8 to 10 stem 12 V to N converted nouns among their neighbors. The median shows that half of stem 12 V to N converted nouns attract more than 9 of their pairs. On average, 84% of their neighbors are stem 12 converted nouns. Stem 12 conversion attraction scores are closer to those of -age suffixation than to those of V to N conversion (without discriminating stems).

While [START_REF] Tribout | Noun to verb and verb to noun conversions in French[END_REF][START_REF] Tribout | Problèmes de compositionnalité en morphologie dérivationnelle: le cas de la conversion[END_REF] showed that the semantic classes to which converted nouns belonged were not strikingly distinguishable depending on the stem selected for derivation, these preliminary results reinforce our hypothesis that V to N converted nouns can in fact be discriminated. In the following section, we investigate the degree of attraction that lexemes maintain with each other depending on the schema they derive from.

Degrees of semantic attraction between the closest lexemes

As we are manipulating a small amount of data it is usual to come across closest neighbors that have low similarity scores with the tested derivative. For example, in the 10 closest neighbors of regain 'revival' (stem 0), we find renouveau 'renewal' (stem 0), with a satisfactory cosine similarity score of 0.63, but also dégoût 'disgust' (stem 0) with a score of 0.42, which would not intuitively be considered as semantically close to regain as renouveau. To get a better sense of the actual semantic relatedness of the neighbors of a derivative, the average cosine similarity scores of the neighbors of each derivative must be measured and compared according to the schema it derives from. This would help gain clearer insight into whether N-age' neighbors have higher similarity scores with their pairs at each position than V to N converted nouns' neighbors, thereby supporting the intuition that -age suffixation derives nouns that are more semantically homogeneous than conversion.

For each schema, we computed the average cosine similarity score at each position for all the neighbors that derive from the same schema. Neighbors are ranked from the closest (position 1) to the farthest among the 10 closest (position 10). For example, with -age suffixation, the cosine similarity scores of all N-age that appeared among N-age' neighbors were averaged at each position (1 to 10). When no N-age could be found for a position, the position was given a score of 0. This gave us a list of 10 scores for -age suffixation that we could compare with the same lists of scores obtained for V to N conversion, stem 0, stem 12 and stem 13 conversion. This enables several questions to be addressed: on average, does the closest neighbor of an N-age have a higher similarity score than that of a stem 12 V to N converted noun? Do the closest neighbors of stem 12 converted nouns have higher similarity scores than stem 0 converted nouns? Although there are few of them, what are stem 13 converted nouns' similarity scores with their pairs?

Figure 2 shows the difference between schemas according to the average similarity scores of their neighbors. The X-axis indicates the position of the neighbors (from 1 to 10) and the Y-axis the average cosine similarity of the neighbors that appear at a certain position. Each schema is represented by a curve. A higher curve at each position means that the average cosine similarity of the neighbors derived from the same morphological schema is greater for a schema, therefore the semantic relatedness between nouns derived with the same morphological schema is higher. When the curve declines at a position before rising (as in position 2 for stem 12 V to N converted nouns), it indicates that few derivatives of the same schema are found at one position among the neighbors.

The results show that N-age are by far the ones that maintain the highest similarity scores with their -age suffixed neighbors regardless of the position. Their closest neighbors (in position 1) have an average score of approximately 0.7. The average cosine similarity scores do not fall below 0.55 (position 10). The other curves indicate the scores of converted nouns according to the stem they select. Among them, stem 12 V to N converted nouns are the ones that have the highest similarity scores with their neighbors at each position, the highest similarity score being at position 1 with a little more than 0.5 and the lowest score below 0.4 at position 9. Comparatively, stem 0 converted nouns have lower similarity scores at each position, with their highest score reaching 0.3 at position 1. Their scores can fall below 0.2 at position 6. Finally, stem 13 V to N converted lexemes are the ones with the lowest similarity scores. Their highest average similarity score reaches 0.2 at position 1. Unsurprisingly, as few stem 13 V to N converted nouns are taken into account, half of the positions (3, 4, 5, 7 and 8) have a score of 0 which means that no stem 13 converted noun could be found in the neighbors at these positions.

These results correlate with the ones presented in the previous section (Table 1). On average, N-age derivatives have the highest semantic proximity with their -age suffixed neighbors: they attract them more than the other schemas, and the ones they attract have high similarity scores. Converted nouns maintain a lower semantic proximity with their pairs in comparison. However, stem 12 V to N converted nouns stand out as they are more likely to attract their pairs with which they have the highest similarity scores. The semantic consistency observed among N-age and stem 12 converted nouns led us to hypothesize that the two schemas might occupy distinct semantic niches. In order to consolidate our intuition that the distributional properties of N-age and stem 12 V to N converted nouns might not overlap, we also looked at the farthest neighbors of N-age with the expectation that we would find a majority of stem 12 converted nouns.

The farthest neighbors of N-age

The 10 farthest neighbors of -age suffixed nouns include the derivatives that have the lowest cosine similarity scores, i.e. the nouns with which N-age have the least in common. For example, the 10 farthest neighbors of nettoyage are given in (4). According to our data, pensée is the derivative that has the lowest similarity score (-0.17) with nettoyage.

(4)

1. pensée 'thinking': -0.17 ; 2. vocalise 'singing exercise': -0.16 ; 3. revue 'magazine': -0.15 ; 4. huée 'booing': -0.15 ; 5. feinte 'feint': -0.13 ; 6. promesse 'promise': -0.13 ; 7. défaite 'defeat': -0.13 ; 8. dictée ; dictation': -0.12 ; 9. embrouille 'confusion': -0.11 ; 10. venue 'arrival': -0.1

We calculated the number of stem 0, stem 12 and stem 13 V to N converted nouns that were found among the 10 farthest neighbors of all N-age in our data. Table 2 shows the proportion of derivatives according to the schema they derive from. Unsurprisingly, the proportion of N-age does not exceed 2 and is closer to 0 as shown by the median. Of all V to N converted nouns, those that are derived from stem 13 are the ones that are the hardest to find. As shown in Table 2, there are as many N-age as stem 13 V to N converted nouns in the farthest neighbors (0 to 2); however, this may be due to their poor level of representativeness. Among stem 0 V to N converted nouns, between 0 and 7 appear in the farthest neighbors. In 50% of cases, we find 2 to 4 stem 0 V to N converted nouns (with a median of 3). Finally, stem 12 V to N converted nouns are the most numerous: 61% of the least similar derivatives of N-age in our data are stem 12 converted nouns. With a median of 6, the number of stem 12 V to N converted nouns found in the farthest neighbors ranges from 2 to 10. 50% of N-age have between 5 and 8 stem 12 V to N converted nouns among their farthest neighbors. Stem 12 V to N conversion is the type of conversion that has the least in common with -age suffixation.

N-age

Stem 0 V to N conversion Stem 12 V to N conversion Stem 13 V to N conversion Range 0-2 0-7 2-10 0-2 IQR 0-1 2-4 5-8 0-1 Median 0 3 6 0 Mean 3% 30% 61% 4%

Overview

Our results provided evidence in favor of -age suffixation's semantic homogeneity: N-age predominantly attract their pairs and maintain the highest semantic similarity with them. Although V to N converted nouns are not as semantically homogeneous, stem 12 V to N converted nouns stand out as more likely to attract other stem 12 converted nouns with which they have the highest scores compared to other types of conversion. The results in Table 2 show that stem 12 V to N converted nouns are the derivatives that appear the most among N-age' farthest neighbors, which indicates that the two can be discriminated. These results are consistent with the hypotheses that were made in 1.4 regarding the potential homogeneity of less frequent N-age compared to highly frequent converted nouns. One reason could be that the two schemas occupy distinct semantic niches that do not overlap while stem 0 and stem 13 V to N conversion are more semantically versatile. To explore this idea further, we investigated how derivatives scatter or cluster depending on the schema they derive from.

SEMANTIC DISPERSION

In this section, we investigate the semantic dispersion of derivatives in order to explore whether schemas can be discriminated based on the degree of scattering and clustering of the lexemes that they construct. This experiment aims to confirm the quantitative observations given in Section 2. Considering previous results, N-age and stem 12 V to N converted nouns were expected to cluster the most with their pairs, while stem 0 and stem 13 converted nouns were expected to show a wider spread.

In order to quantitatively assess the semantic distribution of our lexemes, we built a classifier that discriminates schemas based on the dispersion of their lexemes using the cosine similarity scores that were presented in Section 2. If our intuitions are correct, we expect that a classifier based solely on attraction scores will confuse N-age with stem 12 V to N converted nouns as both behave in a similar fashion, and stem 0 converted nouns with stem 13 converted nouns as they are more semantically dispersed. We also expect that the classifier will be able to easily discriminate N-age and stem 12 V to N converted nouns from stem 0 and stem 13.

The classifier takes lists of scores as input vectors and predicts the schema of a noun by comparing its vector with centroid vectors of the same dimensions. For each derivative, we constructed an 11-dimensional vector: the first dimension corresponds to the proportion of nouns derived from the same morphological schema in the 10 closest neighbors of the derivative (as computed in 2.1.). For example, the first dimension of nettoyage 'cleaning' would be 1.0 as 10 out of its 10 neighbors are N-age (cf. 'prop.' in Table 3). The other 10 dimensions of the vector correspond to the cosine similarity scores of the 10 closest neighbors of the derivatives ranked from closest to farthest among the closest (n1, ..., n10 in Table 3). Neighbors that are not derived from the same schema are assigned a score of 0.0. To predict a schema for a noun, the classifier computes the Euclidean distance (2-norm distance) between its input vector (as in Table 3) and 4 centroid vectors representing each schema. In our case, a centroid vector is the average of all input vectors of nouns derived from the same schema, except for the input vector of the noun that is tested 3 . For example, stem 12 conversion's centroid vector will be the average of all stem 12 converted nouns' input vectors. The prediction is based on the smallest Euclidean distance between the input and the centroid vectors. Thus, if an input vector is closer to -age suffixation's centroid than to stem 0, stem 12 or stem 13 conversion's centroids, the noun corresponding to the input vector will be classified as an -age derivative.

Table 4 shows the results of the classifier through a confusion matrix. The rows indicate the schema predicted by the classifier and the columns the actual schema. Values in bold are the true positives (nouns that were correctly predicted by the classifier).

-age suffixation results

As shown in Table 4, the classifier predicted that 149 derived nouns were N-age as their input vectors were closer to -age suffixation's centroid vector. Among them, 127 are indeed N-age, while 5 are actually stem 0 V to N 3 We used cross-validation to compute centroids that did not include the tested input vector.

- Additionally, we calculated the precision, recall and F-1 scores using the results in Table 4. Precision is a measure that evaluates the sensitivity of a classification for a class (in our case, a schema) by dividing the number of correctly predicted instances by the number of predicted instances. Recall, on the other hand, measures the specificity; it is the fraction of the total amount of correctly predicted instances. Here, -age suffixation has a precision score of 85.2% and a recall score of 84.6%. The F1-score (or F-measure) is the weighted harmonic mean of precision and recall, which gives 84.8% for -age suffixation, meaning that the classifier is able to predict N-age correctly.

Stem 0 conversion results

51 stem 0 V to N converted nouns were predicted by the classifier. Among them, 34 are indeed stem 0 converted nouns, 5 are N-age and 11 are stem 12 V to N converted nouns while only one was confounded with stem 13 conversion. The classifier obtains a precision of 66.6%, a recall of 50.7% and an F1-score of 57.5% for this class, which is only slightly better than random guessing (50%).

Stem 12 conversion results

In total, 66 nouns were classified as stem 12 V to N converted nouns. 38 were correctly predicted, while 18 were N-age and 10 were stem 0 V to N converted nouns. As for -age suffixation, none were confused stem 13 converted nouns. The scores are slightly lower than those of stem 0 conversion: with a precision of 57.5%, a recall of 53.5% and an F1-score of 55.4%, the classification is not significantly better than random guessing.

Stem 13 conversion results

Lastly, the classifier predicted 34 stem 13 V to N converted nouns. Among them, 11 stem 13 converted nouns in our data were correctly predicted. 5 were actually stem 12 V to N converted nouns and 18 were stem 0 converted nouns. No stem 13 converted noun was mistaken for an N-age. Stem 13 conversion obtains a precision of 32.3%, a recall of 91.6% and an F1-score of 47.7%. Stem 13 converted nouns are the ones that the classifier is the least able to predict.

Conversion results

The performance of the classifier on converted nouns as a whole was measured by combining stem 0, stem 12 and stem 13 conversion results. The precision score for conversion is 84.7%, while the recall is 85.3%. As for -age suffixation, conversion obtains an F1-score of 84.9% which shows that the classifier can easily discriminate the two schemas.

For the most part, our classifier based on closest neighbors' attraction scores successfully predicted the schema of a noun when the noun is highly clustered with its pairs and when it is highly dispersed. Consequently, -age suffixation (the most homogeneous) and stem 13 conversion (the most scattered) are the schemas for which the classifier exhibits the highest recall scores. As expected, the classifier has trouble discriminating between -age suffixed nouns and stem 12 converted nouns, which is not surprising as both attract a great proportion of their pairs with high similarity scores. Stem 12 converted nouns that the classifier mistakes for -age suffixed nouns are the ones that cluster the most (traversée 'crossing', randonnée 'hike', découverte 'discovery', fricassée 'fricassee', gelée 'frost', étuvée 'steaming'). The -age suffixed nouns that are confounded with converted nouns (mostly stem 0 and stem 13) are those that are less clustered such as blocage 'blocking', apprentissage 'learning', vernissage 'coating, vernissage' or témoignage 'testimony'. Unsurprisingly, stem 0 converted nouns that are scattered are predicted as stem 13 converted nouns. Stem 0 converted nouns can sometimes be mistaken with stem 12 converted nouns when they are clustered (dégonfle 'letting down', démerde '(action of) getting by', débrouille '(action of') dealing with it'). Again, the results obtained with the classifier show that the least frequent (N-age and stem 12 converted nouns) and the most frequent kinds of derivatives (stem 0 and stem 13 converted nouns), as shown in 1.4., are the ones that are the most frequently confounded.

Overall, the results show that the dispersion of lexemes differs significantly depending on the schema (although not always depending on the stem selected for conversion, as stated by Tribout 2010), thus confirming our intuitions that the semantic behavior of lexemes can be quantitatively discriminated. In the following section, we present a qualitative analysis of the semantic niches that were found for each schema.

SEMANTIC NICHES

We hypothesize that the groupings observed in the distribution of derivatives are motivated by the sharing of common semantic values related to the morphological schema the lexemes are derived from. Here, we define a semantic niche as an ensemble of lexemes derived from the same schema that gather semantically (in terms of cosine similarity) and that share a common semantic property that we identified.

Semantic niches of -age suffixation

The distribution of N-age led us to identify a semantic property characteristic of these nominalizations: these event nouns seem to systematically imply either a concrete object for the realization of the process denoted by the base verb, or the linking of objects. The object concerned can be either an instrument (5) or an object (which can be a place) used as a container or a storage place (6). The linking of objects mainly concerns humans who are linked to one another via what the N-age denotes (7).

( The -age suffixed nouns in our corpus comprise very few pure event nouns that do not imply an object. This result is in line with Wauquier et al. (forthcoming) that studies the semantic distinction between -age and -ion deverbals in French (also using DSMs) and that highlights the technical nature of N-age, which are more related to the fields of industry, agriculture or crafts4 . This is also consistent with Fradin (2014)'s results showing that Nage, compared to N-ment, combine preferentially with complements denoting concrete objects.

Semantic properties of V to N conversion

The examination of the distribution of deverbal converted nouns showed the opposite: these are usually generic event nouns. However, they can be grouped into semantic clusters, especially depending on the stem of the base verb on which they are built.

Deverbal converted nouns deriving from stem 12

The conversion selecting stem 12 of the base verb provides the most clustering next to pure event nouns (16).

-Pure event nouns Investigating the distributional properties of converted nouns using word vectors has highlighted their genericity compared to N-age, a distinctive property that the analysis of the semantic outputs of V to N conversion andage suffixation has not been able to show [START_REF] Tribout | Problèmes de compositionnalité en morphologie dérivationnelle: le cas de la conversion[END_REF]. Such genericity allows converted nouns to cluster with more specific N-age when some semantic properties of converted nouns resemble the prototypical ones of an N-age.

Overview

So far, our observations show that the schemas that are the most dispersed and the least semantically specific are also the schemas that group the most frequent derivatives (stem 13 and stem 0 conversion), while the ones that are the most specific and clustered comprise the least frequent lexemes (-age suffixation and stem 12 conversion). Although this correlation could be due to the inherent properties of each schema (including the different stems that are selected for conversion), another reason could be that some converted nouns are more lexicalized than others, as proposed by [START_REF] Resnik | Using information content to evaluate semantic similarity in a taxonomy[END_REF]. Such a hypothesis could explain why stem 12 converted nouns, the least frequent converted nouns in our data, cluster together away from other more frequent converted nouns. On the other hand, the potential polysemy of stem 13 and stem 0 converted nouns, which may be the consequence of their advanced lexicalization reflected by high frequencies, could explain why they can be found among -age suffixed nouns and stem 12 converted noun clusters: some of their semantic interpretations, far from the original (compositional) ones, might have something in common with nouns that are found in -age suffixation and stem 12 conversion clusters. These results lead us to consider that a discrimination based on distributional properties between converted nouns depending on the stem selected for derivation might depend on the degree of lexicalization of the converted nouns rather than on their semantics.

CONCLUSION

In this paper, we have proposed quantitative and qualitative analyses of the distributional properties of -age suffixed nouns and verb to noun converted nouns by manipulating word embeddings. Our methods, applied on a small set of data and based on word similarities, allowed us to measure the semantic dispersion and relatedness of these lexemes while ensuring the interpretability of the results. We provide evidence that -age suffixation and verb to noun conversion have different semantic properties and distributional behaviors, and that converted nouns can be discriminated by the stem they derive from when looking at their distributional properties regardless of their semantic outputs. First, we showed that -age suffixation is the most semantically homogeneous schema as -age suffixed nouns mostly attract their pairs and have high semantic similarity scores with them. This is consistent with the frequency distribution of our data that shows that N-age are generally less frequent than converted nouns, which implies that -age suffixation might be more productive and therefore derive nouns that have a compositional meaning that is less influenced by the consequences of lexicalization compared to converted nouns. We also demonstrated that -age suffixed nouns cluster together and occupy semantic niches that we categorized. A semantic value that is specific to N-age is that the event nouns they denote imply, in one way or another, a concrete object. In comparison, V to N converted nouns appeared less homogeneous and more scattered at first glance. However, when differentiating them based on the stem they select, some regularities were found. V to N converted nouns that derive from stem 12 actually behave in a similar fashion to N-age: they attract a majority of their counterparts and cluster together to occupy distinct semantic niches that do not overlap with the ones invested by -age suffixation. Unlike N-age, stem 12 converted nouns denote event or result nouns that do not imply the use of a concrete object, a feature that is also found in the other converted nouns in our data. The other types of converted nouns, based on stem 0 and stem 13, lack semantic homogeneity and show a much wider spread. While their versatility could be consistent with the idea that rival schemas adjust their degree of specialization in order to coexist (Lindsay & Aronoff 2013) and could be an inherent property of both schemas, we hypothesize that another reason for such dispersion is that stem 0 and stem 13 converted nouns are more lexicalized because of their high frequencies and generic semantic interpretation. So far, although V to N converted nouns can be discriminated based on their stems, it appears more likely that they constitute a unique morphological schema that is preferentially used by selecting stem 12 when deriving event nouns, while stem 0 and stem 13 selection could have become obsolete. To evaluate this hypothesis, the productivity of V to N conversion and the different stems that are selected must be thoroughly investigated. As for the rivalry between -age suffixation and V to N conversion, their semantic relatedness and dispersion features will need to be compared with those of other rival nominalizations such as -ion, -ment, -ance, -ade, -ure and -aison and be matched against morphological, phonological and syntactical properties in order to clarify the distribution that allows them to coexist.

Figure 1 .

 1 Figure 1. -Token frequency of the nouns depending on the schema

N

Figure 2 .

 2 Figure 2. -Average cosine similarity scores of the neighbors according to their position

Table 1 .

 1 -Distribution of attraction scores

Table 2 .

 2 -Proportion of derivatives among the 10 farthest neighbors of -age suffixed nouns

Table 3 .

 3 -Example of an input vector (nettoyage 'cleaning')

		prop.	n1	n2	n3	n4	n5	n6	n7	n8	n9	n10
	nettoyage	1.0	0.85 0.77 0.75 0.73 0.73 0.72 0.71 0.71 0.71 0.7

Table 4 .

 4 -Confusion matrix of the classifier's prediction converted nouns and 17 are stem 12 converted nouns in our data. None of them are stem 13 converted nouns.

		age stem 0 stem 12 stem 13 total
	-age	127	5	17	0	149
	stem 0	5	34	11	1	51
	stem 12	18	10	38	0	66
	stem 13	0	18	5	11	34
	total	150	67	71	12	300

  5) freinage 'braking', étiquetage 'labelling', patinage 'skating, polishing', broyage 'shredding', raffinage 'refining', forage 'drilling'

	-	Cluster referring to malicious acts (15)
	(15) cambriolage 'burglary', braquage 'hold-up', sabotage 'sabotage', pillage
		'pillaging'
	(6)	remplissage 'filling', compostage 'composting', stockage 'storage',
		entreposage 'storing', garage 'garage', archivage 'archiving', recyclage
		'recycling'
	(7)	mariage 'wedding', concubinage 'cohabitation', parrainage 'patronage',
		jumelage 'twinning'
	For N-age involving an instrument, several semantic clusters can be
	observed:
	-Cluster referring to body care (8)
	-Cluster referring to the organization/disorganization of data (13)
	(13) décryptage	'decoding',	décodage	'decoding',	paramétrage
		'configuration', filtrage 'filtering', brouillage 'jamming'
	-Cluster referring to the manufacture of films, movies (14)
	(14) doublage 'dubbing', visionnage 'viewing', mixage 'mixing', montage
		'editing', bruitage 'sound effects', coloriage 'coloring', reportage 'report'

(8) rasage 'shaving', gommage 'exfoliation', massage 'massage', modelage 'body massage', bronzage 'suntan' -Cluster referring to household activities (9) (9) lavage 'washing', rinçage 'rinsing', nettoyage 'cleaning', séchage 'drying' -Cluster referring to waste management (10) (10) ramassage 'collection', broyage 'shredding', désherbage 'weeding', compostage 'composting', recyclage 'recycling' -Cluster referring to cultivation, gardening (11) (11) arrosage 'watering', élagage 'pruning', épandage 'spreading', abattage 'felling', hivernage 'wintering' -Cluster referring to vehicles (12) (12) décollage 'takeoff', démarrage 'start-up', atterrissage 'landing', mouillage 'anchorage', allumage 'ignition'

A boxplot is a graphical tool for visualizing the distribution of data through their quartiles. The colored box, delimited by the first (lower bound) and third (upper bound) quartiles, indicates where 50% of the data are concentrated. The bold line inside the box corresponds to the median that separates the data into two halves. The lines extending from the boxes each indicate the concentration of 25% of the data, and their endpoints show the lowest and

[START_REF] Uth | The rivalry of the French nominalization suffixes -age and -ment from a diachronic perspective[END_REF] suggests that this semantic affinity between N-age and things of technical nature is linked to the multiplication of the suffix in the 19th century, during the industrial revolution.

Only two semantic clusters appear, depending on whether the converted nouns are grouped with N-age or converted nouns deriving from stem 12: the semantic cluster of nouns referring to psychological acts when grouped with N-age (23) and the semantic cluster referring to the price of a purchase when associated with converted nouns deriving from stem 12 (24).

(23) dégoût 'distaste ', mépris 'contempt', rejet 'rejection', repli 'withdrawal', aveu 'confession' (24) enchère 'bid', détaxe 'tax reduction', rabais 'discount'

Deverbal converted nouns deriving from stem 13

The converted nouns that select stem 13 of the base verb also form pure event nouns, although they are very rare and always grouped either with Nage (25) or with converted nouns deriving from stem 12 (26):

(25) suspense 'suspense', plagiat 'plagiarism'


Morgane Colombert
email: morgane.colombert@eivp-paris.fr

Marie Gantois
email: marie.gantois@paris.fr

Laurent Jacquet
email: l.jacquet@elioth.fr

Alexia Leseur
email: alexia.leseur@cdcclimat.com

Guillaume Meunier
email: g.meunier@elioth.fr

Hypatia Nassopoulos
email: hypatia.nassopoulos@eivp-paris.fr

Jean-Luc Salagnac
email: jean-luc.salagnac@cstb.fr

Integration of adaptation to climate change within the design process of urban planning

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

This article summarizes some of the results of the research project ADAPTATIO which addresses the integration of adaptation to climate change within the design process of urban planning projects. During this project, financed by the French ministry for ecology and sustainable development, EIVP (a French engineering school), the City of Paris, CSTB (the French Scientific and Technical Centre for Building), CDC Climat research (think tank supported by Caisse des Dépots dedicated to research in the field of climate economics) and EGIS Concept (an engineering firm) have cooperated to propose new ideas on adaption to climate change both in terms of tools and methodologies.

Built environment and climate: a long interaction re-examined by the evolution of energy prices and climate projections

The built environment, with buildings and networks (surface, underground and overhead) connecting them, is inherently exposed to climatic agents. A key function of the buildings is the protection of the human group against climate vicissitudes, isn't it? Storms, thunderstorms, flooding, flood runoff, heat and cold have been, are and will be the common lot of cities according to their geographical location. These very old and unstoppable relationships have led to constructions adapted to climatic characteristics [START_REF] Colombert | Le climat et la ville : la nécessité d'une recherche croisant les disciplines[END_REF]: igloos, patio houses, compact buildings with sloping roofs, or underground areas are some of the many examples confirming the link between local climate and the built environment. Furthermore, climate impacts often exceed the scale of the concentrated built environment (urban area) or dispersed (rural) to affect entire regions.

Until the late nineteenth century, the construction of building was based mainly on the use of locally available materials. The coming of new construction processes and new technologies and equipment from the late nineteenth century and during the twentieth century (reinforced concrete, float glass, air conditioners, elevators, etc.) opened the field of possibilities and profoundly changed the built environment (especially urban) with the arrival of high buildings, sometimes with almost completely glazed facades.

Traditional and modern buildings are suitable because they provide the primary function of protecting people and property from the hazards of climate-induced effects. With the enrichment of society, new functions are expected. Maintaining an equal indoor climate in buildings at every time of the year became possible due to an energy expenditure easily granted because of the modest cost of energy in the twentieth century.

The likely emergence of a new climate in the short term (to scale of the previous secular periods during which the built environment has been adapted to the local climate) and changes in energy prices carry with them the factors which can lead to new changes, new developments.

Current consideration of climate change in urban development projects

On the scale of urban design and urban planning, actions may be engaged and allow to adapt to climate change (CC) without display this ambition. This is what we wanted to check through the tools now used on this scale. We have analyzed the following tools: "HQE aménagement", LEED ND, BREEAM Communities, sustainable planning framework of the City of Paris, urban development framework called AURA (in French: "Améliorer l'Urbanisme par un Référentiel d'Aménagement") -Sustainable development Guide of Montpelier, HQE2R method and ISDIS system, RST02, environmental approach to urban planning (AEU), Eco-district French approach (Ecoquatier), @d aménagement durable® and CBDD®2013.

Morgane Colombert

ICUC9 -9 th International Conference on Urban Climate jointly with 12 th Symposium on the Urban Environment This analyze has helped to highlight or reinforce a number of points:

• First, the importance or, at least, the strong presence of the theme 'climate change' and its various issues (mitigation & adaptation) -particularly through the emergence of international climate policy, national and local -influenced the methods used by urban design professionals to describe, analyze their projects. Nevertheless, if the issue of mitigation, including energy efficiency, is strongly present, adaptation to CC is more discrete and / or indirectly included. Adaptation is nevertheless still present. This presence is based primarily on bioclimatic architecture and urbanism items (local and climate data, like soil, wind, rain, sun, etc., are taken into account to improve outdoor and indoor comfort at a lower energy cost) where adaptation of an urban planning or a building to its environment and its climate are a key element. There are also references and objectives for the reduction of the urban heat island, for the management, the preservation or the restoration of water (rainwater, water bodies, etc.) and green spaces, the climate risk management, or limiting the cooling requirements. Prevention of risks of flooding and submersion; Action for the comfort of buildings (bioclimatic architecture) in context of increased temperatures; Taking into account the behavior of soils and subsoils; Arrange the green and blue network; Work on the porosity, shapes, colors and materials, air movement, the vegetation and evapotranspiration to help limit urban heat island and improve the thermal comfort of outdoor spaces and control their exchanges with outside areas, etc.). " o The CBDD®2013 guide has also a specific issue dedicated to adaptation to CC that specifies:

"The prospective scenarios predict a high increase of average temperatures in 2030 and 2050.

In a sustainable development perspective, it comes to search, today, scalability and adaptability of structures (buildings and infrastructure) to those risks. These climate change phenomena could lead for example to: an amplification of heat wave/ cold wave/ drought phenomena; floods; an increase in the intensity and / or frequency of storms; moisture; weakening or lesser strength material, due to temperature changes; changes in the landscape, vegetation and soils. We need to try to estimate the potential effects of climate change on the project. These effects can influence: the building itself; users; local residents. We must understand the needs and desires of future generations to a quality of life without paying an excessive tribute to climate change and without having to suffer the effects. To achieve positive results in terms of sustainable development, it is important that future generations are involved in the right choices, starting today. Take it into account will also promote the economic and social aspects of sustainable development. " o Sustainable development Guide of Montpelier clearly highlights the following challenge:

"preservation of water resources and the strengthening of the green belt in order to fight against the phenomenon of urban heat island and thus adapt our living environment to foreseeable climate change by fifty years, which the city of Montpellier will be very exposed "and binds it to criteria such as waterproofing coefficient, canopy and summer climate comfort, water resources, vegetation integration, potable water consumption. o The sustainable planning framework of the City of Paris questions the adaptation of buildings to global warming -"Improving building comfort in extreme temperatures. How to do? Replace, when necessary, external joinery by efficient double or triple glazed windows. Insulate from the inside or outside roofs and facades of buildings, according to their characteristics. Install a motorized or natural ventilation system. Revegetate facades or roof terraces. "-and focuses also on the fight against the urban heat island. • Actions to adapt urban planning to future climate warming may be similar to those for address today the issue of summer comfort. It appears that summer comfort is one of the main themes in the analyzed guides and methods. Indeed, the issue of summer comfort or the problem of heat islands is addressed in all the studied documents. The relationship between comfort and thermal vegetation is also an element highlighted in most methods. Water is addressed as resources rather than as a climatic comfort element. • The relationship between mitigation and adaptation to CC is never explained, despite the need to think jointly these two issues. This is also the case of mal-adaptation.

• Most methodologies are more interested in climate adaptation (present situation) than in adaptation to climate change (future situation). In addition, some methods such as "HQE aménagement" will prefer to talk in general of adaptability and scalability, thereby addressing the environmental changes but also socioeconomic changes: "The 21st century will experience a series of changes, some of which are already initiated: technology transition, ecological transition, aging population, proliferation of networked communications, ... The planning will have to adapt to these changes. " Current tools do not therefore all encourage reflection on the adaptation to CC during the design of a new urban development.

Approach and results of the project ADAPTATIO

Project background

The project ADAPTATIO examines the medium-term consequences of a new climate and of an increase of energy prices. It helped to think about the means available today to address in the design of urban projects the issue of both adaptation to CC and mitigation. For this, the fact to be adapted has been defined with two key resources for tomorrow -water and energy -and on the economic evaluation of these two needs. Indeed, today, the calculation of energy consumption is based solely on the current temperature data. That means that the energy quality of urban planning is evaluated with the past climate and not with the future climate. In the project ADAPTATIO, the reflections enabled both developing a simple tool for representing energy and water consumption of an urban project under different climate scenarios and discuss a new organization of reflection on energy issues during a project by involving all the stakeholders of a project in the innovation process (cf. [START_REF] Nassopoulos | Design thinking and urban planning projects: towards new climatic services for climate change adaptation?[END_REF].

To develop our methodology, we choose a real urban project: the Tolbiac Chevaleret sector which is on the ZAC Paris Rive Gauche in the 13th arrondissement of Paris and occupies about 12 hectares. A literature review and the meeting with the project manager of the city of Paris has helped to highlight the fact that different urban and architectural choices have not been designed with a view to adaptation to CC. Nevertheless, the project takes into account the concern of current climate adaptation including implementation of regulations, and special attention is given to interactions of urban development project with its components (buildings, green spaces, etc.) and its environment, and the environmental impact of Tolbiac Chevaleret sector.

To complete this analysis focuses on the Tolbiac sector and to understand if adaptation to climate change is taken into account or not in the design and operation of urban projects, and directly or indirectly, we also interviewed several Project Managers of Parisian urban development. Overall, the findings are similar to those on the Tolbiac sector: adaptation to climate change in itself is not treated, but the bio-climatisme, the fight against urban heat islands, or more generally energy issues and climate, are among the issues included in the urban design.

Evaluation of energy, water and economic vulnerabilities for the case study

To analyze the vulnerability of a urban development to CC, and provide tangible information to the actors of urban planning during the design of a project, we proposed several simulations and analyzes applied to Tolbiac Chevaleret. The model developed by Egis Clim'Elioth Concept for the scale of the building has been modified to respond to the needs of ADAPTATIO project. The ENVI-met model allowed to approach the issue of microclimatic changes related to urban form and materials. Economic impacts related to energy and water needs were also assessed. We cross these analyzes with the construction of a toolbox to highlight by simple manipulations effects of CC as of adaptation solutions 1 . Three types of solutions were analyzed and compared to a reference case of Tolbiac Chevaleret with a "very high" performance (from an energy point of view):

• Sensitivity tests on the performance parameters of the building,

• Tests on scenarios needs under different bioclimatic principles "building" or "urban space" solutions,

• And the choice of production systems (heating / cooling) with the calculation of consumption and associated costs. The first series of tests were on building's performance. The aim was to test the impact of changes in key performance parameters of the envelope on energy demand of buildings (impact on energy needs). We have assumed that for these tests, thermal comfort strategy was a complementary use of air conditioning and natural ventilation.

• 1: generic links to "click" to access one of 3 results publishers • 2: Choice of the "desired future climate" scenario (A1B and A2). • 3: Scenario Selection "sensitivity parameters to test." When choosing a parameter, the others are automatically fixed to the median value.

• 4: Choice of the scenario "type of needs to test" (heating needs or cooling needs).

• 5: Scale Indication of needs (Scale adjusts automatically when scenario changes)

• 6: Display of the results depending on the floor and orientation of inside spaces.

• 7: The gray levels indicate (for information) the floors of shops and activity programs (not studied in our project).

• 8: Cursors to compare results for different year (2000, 2050 or 2100).

• 9: Cursors to compare different values of performance parameter chosen according to the climate target year (2000, 2050 or 2100). As seen above, the cursor has 5 graduations which describes a value-performance center, one extreme to + 50% and another 50%.

10: Indicator results displayed on average for the entire building program.

Figure 1: Manual of the toolbox

The results of this sensitivity analysis are available through the toolbox (Figure 1). It allows to instantly view the impact of any change in simulated settings on the following output indicators: heating needs, cooling needs, heating and cooling Pmax. Each of these indicators is given in total annual average value, in kWh / m².year for the needs and W / m² for maximum powers, but also by a color scale indicating an average for each direction and each floor.

The impact of these indicators on the basis of the current climate can then be visualized and compared to future (2050 and 2100) according to the two selected climate scenarios (A1B and A2).

The instructions in Figure 1 show how to use the results tab "toolBox_Sensibilité" of the toolbox. All results are displayed in real time on the test page when the user selects scenarios.

Using the toolbox allows to show, for a same building, increasing cooling requirements due to climate change, but also the reduction of heat requirements; and this more or less pronounced depending on the selected scenario (A1B and A2) 2 .

Results

The tab "toolBox_Besoins" of the toolbox represents the changing needs depending on choice of climatic equipment (air conditioning + natural ventilation, or exclusive air conditioning (without possibility of natural ventilation), or air conditioning + natural ventilation + Canadian well) or modification of the urban planning.

If we change climatic equipment (but without urban planning changes), we see with climate change a slight increase of total consumption (heating and cooling) except if the choice of an exclusive air conditioning is done

Conclusion

In summary, the project ADAPTATIO had not ambition to understand in their entirety the systemic issues raised by the process of adaptation to climate change. The available resources were devoted to the examination of two topics: the impact of a new climate on water and energy consumption especially in a warmer climate.

The exploration of contrasting futures was preferred to show the consequences, including economic, of those choices. We proposed different solutions: actions on the building envelope, on equipment and on the immediate environment of the buildings. For each solution there are an investment, operating costs and maintenance, and a very specific lifetime.

In the defined limits, the reflections with urban professional have led to two observations:

• First, the adaptation to CC is not listed in the specifications of current or planned in the short term projects, the course and the daily follow up are already very complex. The uncertainty surrounding the intensity of future climate change does not facilitate their consideration during projects. • Second, this relative distance from adaptation, due to the significance of the operational aspects of the conduct of operations, however, is accompanied by an appetite to have tangible factors, including quantified, to appreciate the scale and urgency of possible adaptation measures. The toolbox developed under ADAPTATIO is designed to meet the wishes of professionals to have synthetic indicators associated with the qualification of indoor and outdoor comfort at the neighborhood level. An approach of the associated cost is also available to complete the analysis. Various workshops and discussions with operators confirmed that the scope of the toolbox ADAPTATIO lies in its ability to raise awareness of the issues associated with a new climate. It allows creating the conditions for an exchange without pretending to substitute for detailed study and simulation tools operationally mobilized by the actors of urban development. Special care will have to be made to the interface that further tests will lead to improvement. His current limits are to require a complete new data entry (geometry and description of buildings and their environment) for each new district studied.

The objective under ADAPTATIO was however reached: to make possible an exploration by professionals in the incidence of future climate on water and energy consumptions of a group of buildings actually made in the Tolbiac Chevaleret sector.

This project opens up many perspectives:

• Organizing the exchange between scientists and professionals to develop an operational approach of adaptation to climate change, • Refine the economic approach on adaptation in exploring contrasting scenarios of influential factors,

• Integrate other indicators such as greenhouse gas emission level associated with the technical solutions, • Open the possibility of involving future users of the district to the choice of adaptation options through enhanced visualization capabilities and an educational effort on presentation of simulation results, • Create the conditions for the mobilization of "design-thinking"3 methods by enhancing tools like ADAPTATIO toolbox as a support to the intervention of specialized designers that help facilitate discussion and innovation.

•

  The most likely methods to take account of the adaptation to CC and to develop meaning are also the latest methods (Ecoquartier approach, CBDD®2013) or those developed by local authorities themselves (sustainable development Guide of Montpelier, sustainable planning framework of the City of Paris). A more complete analysis of all the methods developed today would nevertheless be necessary to confirm this. The inclusion of territorial features (urban heat island, Mediterranean climate) and latest European or French strategic documents on the issue of adaptation to CC may come partly explain this finding.

o The 16th commitment of the "Ecoquartier" approach is thus "Reduce greenhouse gas emissions, adapt to climate change" and specifies actions like: "Anticipate and adapt to climate change (see French national climate change adaptation plan came out in June 2010 and Territorial climate Plans; specific actions for the reduction of the phenomena of urban heat island;

This tool processes the results of simulation software on the one hand at the scale of the building (CLIM'ELIOTH. Ecodesign tool developed by Egis Concept and addressing energy issues and comfort of buildings), on the other hand to the neighborhood level (ENVI-MET: simulation tool of urban comfort particularly taking into account the evapotranspiration of vegetation phenomena). This software uses meteorological data for

2050-2100 provided in the project by Meteonorm.

Water consumption has been restricted to public use (watering green spaces, ponds feeding).

Design thinking is a participatory process based on the collective creativity, empathy of stakeholders, and abductive reasoning encouraged to think outside the box. The margin for error is recognized and seen as a success factor to reach innovation that lies at the crossroads of user needs, the possibilities offered by technology and its viability in the marketplace.

Acknowledgment

The project team wants to thank the French ministry for ecology and sustainable development for funding ADAPTATIO.

(with no possibility to ventilate naturally) then in this case consumption increases significantly. It also highlights the most efficient solution for energy: to couple air conditioning, natural ventilation and Canadian well.

Regarding the scale of urban planning four scenarios were modeled:

• Greening scenario where vegetated surfaces are increased and watered optimally (scenario S2)

• Reflecting scenario where the physical properties of roofs are changed without touching the walls (S3 scenario) • Reflecting scenario where the physical properties of the opaque walls and roofs surfaces are changed (S3 bis scenario) • And finally, a story addition on building (S4 scenario). All scenarios are tested to assess their impact in terms of energy. Only the scenario S2 "maximized vegetation" is tested to assess impacts in terms of water needs in the Tolbiac Chevaleret sector. The results of these tests on the energy needs were also integrated within the "toolBox_Besoins" tab of the toolbox.

Figure 2: Principles of reasoning for the analysis of the extra cost

To evaluate associated costs, many simplifying assumptions have been made (no discount rate, no rebound effect, changes in energy prices in connection with the modeling of the European commission, a constant flat-rate subscription cost, etc.), we consider the cost difference between the "adapted" situation and "not-adapted" situation, so regardless of the remaining costs. We therefore consider the additional costs due to water or energy consumption, installation and maintenance of a not adapted situation compared to the level of these costs in an adapted situation.

For each studied solution we have analyzed the cost of installation, maintenance costs, costs related to water and energy consumption and the required number of rotation of the installation. Our analysis for each pair of tested solutions to have the information is explained in Figure 2.

The toolbox allows you to compare two by two situations making choices in both:

• Air conditioning and natural ventilation • Production systems (heating / cooling) A priori no solution allows to minimize all costs throughout the project lifetime. It is thus necessary to make choices between time and the amount of costs to be supported (excluding the entity that supports these costs and other considerations such as social or political acceptability).


MD Paul Guedeney
email: paul.guedeney@aphp.fr

MD Gabriel Chevrot

MD, PhD Jean-Philippe Philippe Collet

VARC3 criteria: adding prognosis to injury

Disclosure

-Prof. Collet reports the following disclosure from AstraZeneca, Boston Scientific, Bristol-Myers Squibb, COR2ED, Lead-Up, Medtronic, WebMD.

The other authors do not report any disclosure How to best define periprocedural myocardial infarction (PPMI) in the setting of transcatheter aortic valve replacement (TAVR) remains challenging. PPMI is inevitable with transapical TAVR as a result of direct myocardial mechanical trauma. It is the mainstay with other vascular approaches consequent to hypotension, valve delivery mechanical trauma, calcific embolization, acute bleedings or valvular prosthetic coronary artery obstruction, occurring in frail patients commonly burdened with underlying coronary artery disease [START_REF] Guedeney | Impact of coronary artery disease and percutaneous coronary intervention in women undergoing transcatheter aortic valve replacement: From the WIN-TAVI registry[END_REF]. The valve academic research consortium (VARC) was precisely initiated to provide with standardized consensus definitions, paving the way for randomized controlled trials (RCT) and observational studies ever since. Back in 2011, the VARC-1 defined PPMI as an acute ischemic event associated with documented and clinically significant myocardial necrosis occurring within 72h of the procedure(2). Cardiac necrosis was defined by the continuous elevation of cardiac biomarkers on consecutive samples, preferably, creatinine kinase-MB (CK-MB) (Figure 1). In 2012, the VARC criteria were updated and PPMI characterization was simplified, with only one post-procedural abnormal sample required, while the threshold values were adjusted to account for different use of CK-MB or cardiac troponin (cTn) [START_REF] Holmes | ACCF/AATS/SCAI/STS expert consensus document on transcatheter aortic valve replacement[END_REF].

Interestingly enough, this updated definition of PPMI was not consistently associated with adverse outcomes following TAVR, suggesting that different thresholds could be considered [START_REF] Sinning | The prognostic value of acute and chronic troponin elevation after transcatheter aortic valve implantation[END_REF][START_REF] Dagan | Periprocedural Myocardial Injury and Coronary Artery Disease in Patients Undergoing Transcatheter Aortic Valve Replacement[END_REF].

Following numerous controversies on MI definition in RCT, the VARC-3, released in 2021, proposed a pragmatic and exhaustive interpretation on myocardial lesions adapted from the 4 th universal, SCAI and ARC-2 definitions [START_REF] Varc-3 Writing Committee: | Valve Academic Research Consortium 3: Updated Endpoint Definitions for Aortic Valve Clinical Research[END_REF]. PPMI is rendered as occurring within 48h of the procedure with a clear distinction between type 4a, subsequent to percutaneous coronary intervention (PCI)-related MI, when performed, and type 5, subsequent to SAVR or TAVR.

Both types now include increased thresholds of cardiac biomarkers to characterize myocardial injury, with 10 and 70 times the upper reference limit for CK-MB and cTn respectively, to account for the large use of high-sensitivity cTn (hs-cTn), or half the amount if associated with clear electrical, angiographic or imaging signs of myocardial injury.

In this issue of the journal, Real and coauthors provide the first external validation of the updated VARC 3 PPMI definition, using a prospective international cohort study [START_REF] Real | Myocardial Injury After Transcatheter Aortic Valve Replacement According to VARC-3 Criteria[END_REF]. They included 1394 consecutive patients undergoing TAVR from 2015 to 2022, as this time period corresponds to the implementation of hs-cTn in both participating centers. In this cohort, 193 (14%) patients presented PPMI according to VARC-3 criteria, versus 817 (59%) according to VARC-2 criteria. Interestingly, the occurrence of PPMI according to VARC-3 criteria was associated with an increased all-cause mortality at both 30 days and one year (HR: 2.69, 95%CI: 1.50 to 4.82, and HR: 1.54, 95%CI: 1.04 to 2.27, respectively), as well as cardiovascular (CV) mortality at one year, conversely to the VARC-2 criteria for PPMI which were not significantly associated with neither all-cause nor CV death. Consistently, the authors reported the optimal cut-off value of hs-cTn elevation to define PPMI to be 82-fold, which is much in range of the VARC-3 rather than the VARC-2 criteria. Of note, it should be noted that the impact on mortality of the VARC-3 criteria PPMI is quite similar to what has been reported following post-PCI, with consistent definition of PPMI [START_REF] Garcia-Garcia | Impact of Periprocedural Myocardial Biomarker Elevation on Mortality Following Elective Percutaneous Coronary Intervention[END_REF].

What conclusion should we draw from this study? First, it validates the VARC-3 PPMI criteria with the use of a hs-cTn troponin threshold that is adapted to current clinical practice.

Second, PPMI is rarer with this updated definition but more impactful in term of prognosis.

Much more remains to be done to better assess if PPMI is a marker of risk or a risk factor with potential preventable upstream actions. Indeed, the only independent determinants of VARC-3 PPMI in the present study were female sex and peripheral artery disease. The Direct Transcatheter Aortic Valve Implantation (DIRECTAVI) reported the use of systematic balloon aortic valvuloplasty prior to Edward Sapien 3 valve implantation to increase the risk of VARC-2 PPMI by 2.8 fold [START_REF] Leclercq | Prior Balloon Valvuloplasty Versus Direct Transcatheter Aortic Valve Replacement: Results From the DIRECTAVI Trial[END_REF][START_REF] Akodad | Myocardial Injury After Balloon Predilatation Versus Direct Transcatheter Aortic Valve Replacement: Insights From the DIRECTAVI Trial[END_REF]. In the present study, both pre and post-dilatation were associated with a higher risk of VARC-3 PPMI, albeit not reaching statistical significance with p-values of 0.053 and 0.059 respectively, warranting further investigation. Consistently the impact of the occurrence of PPMI on post-TAVR left ventricle ejection fraction evolution should be investigated in larger dedicated studies to confirm the statistically significant, yet potentially clinically irrelevant, observed improvement in the present study. Finally, pre-TAVR CT features might be key players further adding prognosis to injury with potentially preventive approaches.

Figure 1 VARC:

 1 Figure 1