dataesr/scientific-paragraphs-categorization huggingface dataset:
For instance, words like "seethe, " "whirlwind, " "spleen, " and "wrath" are commonly used to express Anger in the early modern England but are not included in LIWC bag-of-words for Anger. Thus, when performing analysis of texts from the past, the two main challenges are (1) to flexibly develop tools adapted to the dimensions and time periods that we wish to investigate and (2) to ensure that the extracted measures empirically relate to psychological and social constructs of interest. In this manuscript, we describe a pipeline with a series of recommendations for researchers doing analysis of texts from the past. First, we recommend using the flexibility of Python/R NLP tools to generate semantic vector spaces, which can then be used to develop historically appropriate bags of words. Then, we review several techniques, which can be used to validate the instrumental measures regarding both their internal coherence and their ecological validity.
MATERIALS First and foremost, conducting research of historical texts requires a quality source dataset. One of the most used datasets for diachronic analysis is google ngram (https://books. google. com/ngrams/info). This dataset is useful for modern analyses, but the coverage decreases as the time window moves further into the past. Another useful source for relatively recent texts, including novels, movie scripts, and spoken dialogue, can be obtained in the dataset CoCa, but these have similar limitations in terms of historical coverage (https://www. english-corpora. org/movies/). Alternatively, source texts can be obtained from medieval and early modern periods e. g. , in English (https://emed. folger. edu/ corpus-search, https://www. folgerdigitaltexts. org/download, https://quod. lib.
umich. edu/e/eebogroup/, https://quod. lib. umich. edu/e/ecco/), French (http://www. theatre-classique. fr/pages/programmes/PageEdition. php), or Latin (https:// comphistsem. org/home. html). Working with the source texts from the past has the advantage that the user can directly verify the preprocessing quality and make necessary adjustments with custom scripts. The procedures and techniques for text preprocessing fall outside of the scope of this manuscript, as they have been extensively covered by other manuals and tutorials and can be performed by standard Python and R toolboxes  (Hardeniya et al. , 2016; Welbers et al. , 2017). Examples of raw and preprocessed texts for the early modern period, and the respective Phyton scripts, can be found in https://osf. io/emxqw/. The steps enumerated below are implemented with Python toolboxes for NLP and R toolboxes for statistical analysis.
g. , cooperation and social orientation in LIWC)? Does it correctly distinguish between text genres known to vary in particular dimensions (e. g. , tragedies are more violent than comedies)? (9) Diachronic analysis. We can test: (left) the temporal relationship between the ratio AvB and socioeconomic variables using cross-correlation and lag analyses; (right) the influence of historical events in psychology by comparing ratio means (or growth rates) pre and post event. using WordNet (Princeton University, 2010; WordNet Interface, n. d. ), one can obtain the following synonym/hyponym list of "strength" (e. g. , script in https://osf. io/h5vcq/:) ["ruggedness, " "hardiness, " "long-suffering, " "brawniness, " "staying_power, " "heartiness, " "huskiness, " "muscularity, " "dynamism, " "muscle, " "stoutness" "immunity, " "indomitability, " "might, " "brawn, " "robustness, " "stalwartness, " "heftiness, " "capacity, " "soundness, " "power, " "firmness, " "toughness, " "endurance, " "stamina, " "sturdiness, " "vigor, " "validity, " "lustiness, " "tolerance, " "legs, " "good_part, " "sinew, " "vigor, " "sufferance, " "invincibility, " "mightiness, " "long-sufferance, " "invulnerability, " "strength"].
However, for other proxies, it is harder to find meaningful lists of synonyms/hyponyms. For instance, using the same WordNet procedure with the word "authoritarianism" returns the list ["police_state, " "authoritarianism"]. An alternative strategy to derive seed words is to survey the literature for psychometric tools used to evaluate the psychological dimension of interest. In this example, the words "obedience, " "strength, " and "authority" are central in questionnaires assessing authoritarian preferences  (Toharudin et al. , 2012). Thus, these can be explored as seed words complementing dictionary approaches using WordNet. Step 3. Generate Historical Semantic Maps (Word2vec) The approach above describes the exploration of psychometric tools and dictionaries developed for modern language use.
The rapid expansion of datasets of historical socioeconomics  (Maddison Project Database, 2018; Clio Infra|Reconstructing Global Inequality, 2019; Our World in Data, 2019)  enables the assessment of simple relationships between the psychology of the past and environmental conditions. Mixed models can be used to test how the variation of cultural variables AvB is affected by socioeconomics (e. g. , script in https://osf. io/h5vcq/): AvB = socioeconomic variable 1 + socioeconomic variable 2 +. + year + (1 | author) Two important controls can be added in this analysis. First is the random effect of author. If certain authors wrote many historical documents, they could excerpt a disproportional influence in the statistics of year-by-year cultural change. In this case, cultural dynamics could not be attributed to historical change, but rather to the idiosyncratic features of one person.
DISCUSSION Recent advances in digital humanities and historical economics have enhanced the possibility to rigorously test the relationship between culture, psychology, and socioeconomics throughout history. Understanding the processes of social change and mapping their underlying regularities and constraints can be crucial for policy making. In this manuscript, we briefly reviewed some of the tools and databases, which can be used for this kind of analysis and proposed a pipeline, which avoids the major pitfalls that arise when conducting historical text analysis. This procedure allows a robust estimation of psychological constructs and how they change throughout history. Together with historical economics, it also increases our power in testing the relationship between environmental change and the expression of psychological traits from the past, whichever the directionality.
We successfully used this pipeline in a recent publication in which we demonstrated that the expression of prosocial preferences and values in theater plays were on the rise before the English and French revolutions, and that prosociality in this period was predicted by living standards  (Martins and Baumard, 2020). In addition, we applied the same procedure to investigate the evolution of romantic love and of numeric cognition in the early modern period with promising results (https://osf. io/ b9msn/, https://osf. io/ka3th/). To facilitate access to our tools and techniques for early users of natural language processing, we made our pipeline explicit and uploaded example scripts and datasets. With this contribution, we hope to facilitate the extension of this kind of research to other questions concerning the relationship between socioeconomics, history, culture, and psychology.
, 2003; Sponheimer et al. , 2003)  and are strongly water dependent. They live in savanna habitats within the vicinity of water bodies, namely the valley wetlands and savanna floodplains of sub-Saharan Africa  (Estes, 1991; Kingdon, 2013). There are two extant African genera, the large-bodied waterbuck and kobs (genus Kobus), and the smaller reedbucks (genus Redunca). Enamel stable carbon isotope data suggest that reduncins from the Shungura Formation had a diet ranging from C 3 -C 4 mixed-feeding to C 4dominated between ~3-1 Ma  (Negash et al. , 2015 (Negash et al. , , 2020)) , whereas they had C 4 -dominated diets at most other Plio-Pleistocene sites of eastern Africa  (Bedaso et al. , 2013; Wynn et al. , 2016). However, isotopic ecology offers one line of dietary evidence-reflecting only photosynthetic pathway-and we do not currently know what types of plants Shungura reduncins fed on.
Comparative dataset Our comparative dataset represents the main dietary axes in ruminants-grazers, mixed feeders, browsers, and frugivores  (Hofmann and Stewart, 1972; Hofmann, 1973; Gagnon and Chew, 2000). These broad categories reflect only a portion of ruminant dietary diversity and the full extent of spatiotemporal dietary variation of African bovids  (Codron et al. , 2007; Louys and Faith, 2014). However, our diet reconstruction by proxies at different temporal scales in an individual's lifetime (DMTA, MWS, enamel stable carbon isotopic data) allow us to better detect subtle variability in reduncin dietary ecology through the Shungura Formation. DMTA was applied to 178 wild-shot individuals of ten extant species of ruminants (Table  3, S2 ). The southern savanna buffalo (Syncerus caffer caffer, n = 27), the hartebeest (Alcelaphus buselaphus, n = 29), the waterbuck (Kobus ellipsiprymnus, n = 19), the kob (Kobus kob, n = 13), and the bohor reedbuck (Redunca redunca, n = 7) are C 4 grazers  (Estes, 1991; Cerling et al.
The present-day ruminant specimens we analyzed are housed in collections from the institutions listed in Appendix S2. While we know that these wild specimens come from different regions of Africa, their precise geographic origin is not always indicated in museum collection records except for some specimens (Appendix S2). For dental mesowear analyses, we used the same extant species as described above for the DMTA dataset, with the exception of K. kob. Mesowear patterns of extant species derived from the dataset published by  Fortelius and Solounias (2000). Following their approach, all taxa constituting a comparative dataset should have a reasonable sample size and thus taxa with fewer than 14 individuals sampled are excluded. Our comparative dataset of extant species comprises 439 wild-shot specimens representing nine species (Table  1 ).
In contrast to  Blondel et al. (2018) , a 200 × 200 μm surface was generated from this area, leveled and mirrored in Z using LeicaMap 7. 4 (Leica Microsystems) for all studied specimens (Figs. 2  and 3 ). The few missing points were replaced with a smooth shape calculated from neighboring points. Aberrant peaks were automatically erased (see supplementary material in  Merceron et al. , 2016 for details). Artifacts such as adhering dust or sediment particles on the enamel surface were removed manually and then replaced with a smooth shape calculated from the neighboring points before proceeding to a final leveling of the surfaces with Mountains software  (Blondel et al. , 2018). Further analysis to generate DMTA variables was conducted with Toothfrax and Sfrax (Surfract, www. surfract. com) following procedures and settings shown in  Scott et al.
4 , Table  1  and Table 2B ). No significant difference is detected between reduncins from Member E (Table  2B ) and all extant species in our dataset, whereas reduncins from Member F differ significantly from the mixed feeder A. melampus and the three browsers, but are close to A. buselaphus (Fig. 4 , Table  1 ). In Member G, reduncins show significant differences in MSW with the grazer A. buselaphus and the three browsers, as in Member C (Fig. 4 , Table  1  and 2B ). Reduncins from Member H differ significantly from the grazer A. buselaphus in MWS (Table  2B ) but are close to S. caffer and Member B specimens (Fig. 4 , Table  1 ). No significant difference is detected between reduncins and tragelaphins from the same members except in Member F and Member G (HSD test, Table  2C ).
Diets of extant ruminants in our dataset ANOVAs detect significant differences in MWS across the extant ruminant species (Table  2 ). In general, we observe a continuum from browsers to mixed feeders to grazers with frugivores plotting within the range of the latter (Fig. 4 , Table  1 ). The lowest MWS is obtained by G. camelopardalis, a browser that has a diet dominated by leaves (Leuthold and  Leuthold, 1978; Estes, 1991) , followed by the two others browsing bovids (L. walleri and T. scriptus) and mixed feeding A. melampus. Among mixed feeders, browser-grazer intermediates such as A. melampus focus more on dicot and monocot foliage (30-70%,  Gagnon and Chew, 2000) , whereas generalists differ from browsergrazer intermediates by feeding on more fruits and seeds. The MWS of the frugivore C.
The discrepancy between mesowear (long-term dietary signal) and microwear (shortterm dietary signal) could indicate that the specimens of T. scriptus in our dataset had a browsing diet during their adult life, but that they fed on grasses or semi-woody plants such as scandent plants during their last few meals or during seasonal changes  (Davis and Pineda-Munoz, 2016). Previous studies  (Smits, 1986; MacLeod et al. , 1996)  indicate that bushbucks feed on plants of high nutritive value and can be considered as selective browsers. They have a wide distribution across sub-Saharan Africa, which may be due to their versatile diets that sometimes include grasses in addition to leaves, buds, and fruits  (Castello, 2016). During the wet season, bushbucks prefer tender new grasses and during the dry season they prefer leaves of shrubs and trees  (Estes, 1991; Plumptre and Wronski, 2013).
She concluded that this species might have fed on tender and soft vegetation distributed homogeneously in areas with little seasonal variations. The δ 13 C values of tooth enamel (n = 10, mean δ 13 C = -1. 3‰, Negash et al. , 2020)  suggest that Reduncini from Member H had a C 3 /C 4 to pure C 4 diet. Together, data from these proxies indicate that Member H reduncins consumed probably soft C 4 grasses. Recent studies in fossil artiodactyls  (Bibi et al. , 2013; Souron et al. , 2012) , primates  (Martin et al. , 2018; Wynn et al. , 2020) , and other herbivorous taxa  (Cerling et al. , 2015; Negash et al. , 2020)  detected two dietary shifts in the eastern African fossil record. The first occurs around 2. 8 Ma (between Member B and Member C) and the second around 2. 32 Ma (between Member E and Member F).
Acknowledgements We thank the  Authority for Research and Conservation of Cultural Heritage (ARCCH)  for granting us permission to sample bovid dental remains from the Omo collections. We thank  Enquye Negash  for helping to collect mesowear samples. We thank the  French Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation (UFR SFA ,  Université de Poitiers ). This research was funded in the framework of the  Omo Group Research Expedition (Agence Nationale pour la Recherche:  project  OLD ANR-CE27-0009-02 ;  Ministère de l'Europe et des Affaires Étrangères ;  CNRS ;  Centre Français des Etudes Ethiopiennes ; Fyssen Fundation; and  Laboratoire Paléontologie Évolution Paléoécosystèmes Paléoprimatologie ). This study was also financed by the Project  ANR   TRIDENT  ( ANR-13-JSV7-0008-01 , PI:  G.
Acknowledgement and application of one assessment could be applied, for example via the PIC/S organization or mutual recognition of existing GMP inspections, so waiving the need for each (and many) individual country inspection  [25]. We realize that worldwide reliance is a considerable challenge, in particular with regards to large extent of local regulations. However, we see that many agencies were able to quickly introduce emergency approval procedures in the COVID-19 pandemic, thus demonstrating there can be rapid agreement to new legislation to help bring vaccines to patients. Despite legal challenges, developing reliance mechanisms by leveraging the WHO ''Good Reliance Practices in the regulation of medical products"  [21] , offers many advantages. It can lead to a more efficient way to streamline the initial licensing process and the subsequent PAC approvals, making the best use of scarce resources, preventing vaccine shortages and, most importantly, meeting the needs of global patients waiting for a vaccine.
Discourseold XPs are those that relate to information previously made available, via e. g. a deictic/anaphoric expression as in (1) above. No relation to the antecedent context is entertained by discourse-new XPs, and among them, Focus implies a contrast to other potential values (see the illustrations provided below). The results from the analysis are as follows. We start with the data from the less formal text, the Year Books. Results 3 from dialogue is presented in Table  1 , and those from narration in Table  2. Included are subordinates under bridge verbs such as say, since these are assumed to behave like main clauses.
Computational Results In this section, we compare the performance of the different families of Benders cuts presented in Section 3 using the branch-and-Benders-cut algorithm (denoted as B&BC). All our computational experiments were performed on a computer equipped with a Intel Core i5-7300 CPU processor, with 2. 50 gigahertz 4-core, and 16 gigabytes of RAM memory. The operating system is 64-bit Windows 10. Codes were implemented in Python 3. 8. These experiments have been carried out through CPLEX 12. 10 solver, named CPLEX, using its Python interface. CPLEX parameters were set to their default values and the models were optimized in a single threaded mode. For that, t denotes the average value for solution times given in seconds, gap denotes the average of relative optimality gaps in percent (the relative percent difference between the best solution and the best bound obtained within the time limit), LP gap denotes the average of LP gaps in percent and cuts is the average of number of cuts generated.
Performance of algorithms on benchmark instances We start by analyzing the Sevilla instance. Tables  12  and 13  show some results for this instance solved with BD CW+CS. Based on this case, figures in Tables  12  and 13  show the solution graphs for different parameter values. Points not connected in these graphs refer to those nodes that have not been built. The O/D pairs involving some of these nodes are thus not covered. They have been drawn to represent these not covered areas. Data corresponding to each case is collected at the bottom of its figure, in which v(ILP) refers to the objective value. For model (M C), parameter cost represents the cost of the network built, and, for (P C), G cov makes reference to the demand covered. For (M C), we observe that smaller values of C max carry larger solution times as in random instances.
Given that network design problems are strategic decisions, having the best quality decision is often more important than the computational times. However, having efficient exact methods as the ones proposed in this article, allows decision makers to perform sensitivity analysis with optimality guarantees in reasonable times. We also tested our algorithms on benchmark instances Germany50 and Ta2 form SNDLib (http: //sndlib. zib. de/). We observed that adding cuts at the root node is beneficial for Germany50. We think that this behavior is due to the fact that Germany50 has a denser potential graph (in particular, Germany50 is not a planar graph). The rest of the results obtained for these instances are aligned with the results obtained for Sevilla and Sioux Falls instances. For the sake of shortness, this analysis is included in the supplementary material in http://github.
Acknowledgments Víctor Bucarey  and  Martine Labbé  have been partially supported by the  Fonds de la Recherche Scientifique -FNRS  under Grant(s) no PDR  T0098. 18. Natividad González-Blanco  and  Juan A. Mesa  are partially supported by  Ministerio de Economía y Competitividad (Spain) / FEDER(UE)  under grant  MTM2015-67706-P  and  Ministerio de Ciencia y Tecnología(Spain) / FEDER(UE)  under grant  PID2019-106205GB-I00.
Official data on international visits to London for 2020 and 2021 are not yet available, but VisitBritain (2021c), as of May 2021, was expecting to record a decline of international tourism to the UK of 75% for 2020, as well as a decline in domestic tourism of 60% for overnight and 64% for leisure day trips. Data for Paris are similar, with Ile-de-France Region estimating that the region has lost 78% of its tourism in 2020 (Comité Régional du Tourisme). While acknowledging the disastrous impacts of the pandemic on a human level as well as on the tourism industry, during the first few months of the pandemic particularly, the sudden slump in international travel triggered a wealth of discussions within academia, industry and the media on whether and how the crisis could be seen as an opportunity to build back better and to trigger a positive transformation of tourism towards a more responsible and sustainable path (for example,  Ateljevic, 2020; Higgins-Desbiolles, 2020).
A list of interviewees is provided in Table  2. In Paris we also analysed the verbatim transcripts of three forums organized in the framework of the General Assembly for the relaunch of tourism in Paris (Assises du tourisme de Paris), which took place between March to June 2021 and brought together major Parisian stakeholders. All qualitative data (Delphi study answers, interview and forums transcripts) were coded and analysed by the authors of this paper in accordance with established thematic analysis procedures  (Flick, 2018). All London data were collected and analysed in English, while Paris data were collected and analysed in French (this was possible because the researchers were fluent in both languages). Investigator triangulation (as all authors contributed to the empirical analysis) contributed to enhancing the descriptive validity of the results  (Yin, 2013).
Measurement precision was better than ±0. 1‰ for δ 13 C and ±0. 2‰ for δ 15 N. Climatic data, interpolated surfaces based on climate data from individual weather stations, were obtained from WorldClim 1. 4  (Hijmans et al. , 2005) , with site aridity indices from  Trabucco and Zomer (2009). Due to the low density of climate observation stations and high topographic heterogeneity in the study region, only generalised definitions of climate gradients are feasible. Statistical analyses were carried out using PAST  (Hammer et al. , 2001). To explore our data we used non-parametric tests of difference (Mann-Whitney and Kruskall-Wallis) to assess differences in isotopic values between biomes or between plant functional types. To consider isotopic-climatic relationships we used site average foliar and soil data (as will be shown later, inter-sample (plot scale) variability was relatively high) and we report the Pearson correlation coefficients between isotopic values and climatic parameters from the WorldClim data.
Foliar δ 13 C and δ 15 N Foliar δ 13 C across the total dataset ranges between -13. 2‰ and -30. 6‰. Considered by biome/ecoregion the mean values (and standard deviations) are -26. 1 ± 3. 1‰ (n = 45) and -24. 9 ± 4. 1‰ (n = 24) for the Montane and Lowland Fynbos respectively, and -22. 4 ± 4. 7‰ (n = 135) for the Succulent Karoo Biome (Fig. 1 ). Most Lowland and Montane Fynbos foliar δ 13 C is within the anticipated range of C 3 plants, with a minority of specimens (7 of 69 specimens) producing values higher than -20‰ (Fig. 1 ). Succulent Karoo foliar δ 13 C spans a range from -29. 4 to -13. 2‰. The difference between the Fynbos and Succulent Karoo biomes is statistically significant (i. e. Fynbos vs. Succulent Karoo Biome Mann-Whitney U = 2561, p = < 0. 001), while there is no significant difference between the Montane and Lowland Fynbos foliar δ 13 C (Mann Whitney U = 454, p = 0.