dataesr/scientific-paragraphs-categorization huggingface dataset:
Study Overview The data used for this paper's analyses were collected as part of a larger online study that took place from June 2019 to July 2020 and explored the effects of gamification on cognitive constructs vital for smoking cessation  [7]. Participants were recruited via posters in public places in London, United Kingdom, and posts on various social media channels such as Facebook and Instagram. Interested participants were asked to fill out a screening questionnaire to assess eligibility. Eligible participants (Table  S1 , Multimedia Appendix 1) were assigned 1 of 2 smoking cessation apps; this paper focuses on users of Kwit, a gamified mobile app designed to help smokers quit smoking using cognitive behavior therapy  [9]. Participants had to use the app at least once a week for 4 weeks and complete a questionnaire before (baseline), 2 weeks after (mid-study), and 4 weeks after app use (end of study).
Participants who selected other responses ("Yes, just a few puffs"; "Yes, between 1 and 5 cigarettes"; and "Yes, more than 5 cigarettes") were categorized as smokers. Aside from self-reported data, objective in-app metrics were also used in the analysis. Kwit SAS routinely collects and maintains a database of app usage statistics, including various user interactions with specific features and the app overall. Kwit SAS provided in-app metrics for the participant identification numbers shared with them. The metrics included the number of times the app was opened, levels completed, smoking diaries logged, achievements unlocked, and motivation cards viewed. Additional information on the in-app metrics is presented in Table  S2  (Multimedia Appendix 1).
Statistical Analysis The statistical software Stata 16 (StataCorp) was used for the analysis. Descriptive statistics were used to present general participant characteristics, nicotine dependence, and 7-day abstinence. Mean (SD) values were calculated for the in-app metrics. Unadjusted logistic regression models were run for each in-app metric to explore its association with 7-day abstinence. The specifications of the adjusted logistic regression model were based on an iterative process that considered collinearity. Significance was set at the 5% level (P<. 05), and 95% CIs were presented.
This was also the case for SU 615. Its location next to SU 613, added to the rest of its features, leads one to believe that it was part of the same activity area. Therefore, SU 613 and SU 615 -as well as SU 604 -could be the result of the palimpsest effect and the superposition of different structures that were possibly recurrently used. The archaeobotanical data showed higher densities of charcoal by volume (again, most of them corresponding to Quercus sp. ), and the presence of pinecone scales that were radiocarbon dated (Fernández-López de  Pablo et al. 2023). These two findings build on our hypothesis according to which SU 613 contains the remains of a combustion structure in situ, even though one affected by sediment homogenisation and soil dynamics. A last question to be discussed regarding the combustion and function of the El Arenal hearth-pits is the evidence of opaque charcoal with altered porosity.
Raman spectroscopy A Jobin Yvon Horiba T640000 Raman microspectrometer equipped with 50 × magnification objective was employed to examine the helmet using a 633 nm laser with a laser power of 0. 1 mW. Spectra were recorded in the spectral range of 100-1500 cm -1 with four accumulations of 30 s each. The data were post-processed using OMNIC software.
Acknowledgements The  HELIX (Investigating metal bioremediation for the preservation of historical metal artworks)  project  2020-2024 , is funded by the  Swiss National Science Foundation (SNSF) , grant number  205121_188755. The authors would like to acknowledge  Nathalie Guichard from the laboratory Chimie et Interdisciplinarité, Synthèse, Analyze, Modélisation (CEISAM ) and  Jean-Yves Mevellec  from  Institut des Matériaux de Nantes  for (2023) 138:569 their contribution to the AAS analyses and Raman spectroscopy. We are grateful to  Michel Chaillou  from  Nantes Diocese  and  Virginie Dupuy  from  Grand Patrimoine Loire Atlantique  for the provision of objects. A special thank you to  Aymeric Raimon  for his help on the case studies and to  Lidia Mathys  for her help in microbial labwork.
Once the model is well validated, prediction is employed for unknown samples. Such operations are performed using KNN, Soft Independent Modeling of Class Analogy, SIMCA, or PLS-DA  [30]. One of the key feature of LIBS measurements is the combined molecular and elemental data obtained from the same spectrum. The advantage over other elemental analysis methods is that it allows, when combined, a multivariate analysis to discriminate between very similar samples such as polymers, synthetics, and genuine leather  [7, 24]. The objective of this work was to identify and highlight very subtle variations in the LIBS spectra of synthetic leather, genuine leather, and polymers (as these are employed to produce synthetic leather) combined with chemometric methods. For this purpose, LIBS spectral data from 104 samples, including 34 polymers, 60 leather, and 10 synthetic leather data were acquired.
The respective spectral ranges and resolutions are: 190-365 nm with FWHM of 0. 18 nm, 365-620 nm with FWHM of 0. 24 nm, and 620-950 nm with FWHM of 0. 35 nm. The delay time between the laser pulse and signal integration is variable between 250 ns and several µs. The integration time is also variable in the millisecond range. Signal measurements were obtained from grids of spots, typically 12 spots covering a 2 × 2 mm surface. This grid is repeated on five different locations on the target surface to ensure representative measurement. All acquired spectra were converted into an Excel file treated by xlstat software (Addinsoft (2022)-XLSTAT New York, NY, USA). The normalization procedure is similar to that employed in previous work  [4].
LIBS Parameters Optimization The selection of the tracers specific to each type of material (polymer, leather, and synthetic leather) relies also on the careful selection of LIBS parameters to obtain maximum information and reliable data from the samples. Since the spectra of most samples are complex, as seen from previous discussion, the selection of parameters is crucial. To highlight the difference between polymers and leathers, the sensitivity optimization should improve the molecular information, and the selection of data should not be hindered Sensors 2023, 23, 2648 7 of 14 by titanium or iron interferences. The LIBS device was used in the gated mode, and integration time and delay were evaluated. The delay and integration times available on the Z300 handheld instrument typically range from 250 ns to 10 µs for the delay and from 1 ms to 18 ms for the integration time.
LIBS Parameters Optimization The selection of the tracers specific to each type of material (polymer, leather, and synthetic leather) relies also on the careful selection of LIBS parameters to obtain maximum information and reliable data from the samples. Since the spectra of most samples are complex, as seen from previous discussion, the selection of parameters is crucial. To highlight the difference between polymers and leathers, the sensitivity optimization should improve the molecular information, and the selection of data should not be hindered by titanium or iron interferences. The LIBS device was used in the gated mode, and integration time and delay were evaluated. The delay and integration times available on the Z300 handheld instrument typically range from 250 ns to 10 µ s for the delay and from 1 ms to 18 ms for the integration time.
Study of Molecular LIBS Information Leather is a protein-based material, containing natural polymers such as collagen or keratin. These proteins are polyamides, and are, in fact, very similar to nylon. A typical spectrum of each sample type is presented in Figure  5a ,b; the complete ranges of 360-390 nm and 500-520 nm are presented, and the relevant lines and molecular bands are identified. As the molecular signals from C2, CN, CH, O, H, are likely to distinguish between polymer types  [7] , a first unsupervised principal component analysis (PCA) plot using the spectral intervals containing the molecular information is employed. The preprocessing of the dataset involved background correction and normalization by the total spectra intensity as it reflects the small variations due to shot-to-shot instrumental variations.
keratin. These proteins are polyamides, and are, in fact, very similar to nylon. A typical spectrum of each sample type is presented in Figure  5a ,b; the complete ranges of 360-390 nm and 500-520 nm are presented, and the relevant lines and molecular bands are identified. As the molecular signals from C2, CN, CH, O, H, are likely to distinguish between polymer types  [7] , a first unsupervised principal component analysis (PCA) plot using the spectral intervals containing the molecular information is employed. The preprocessing of the dataset involved background correction and normalization by the total spectra intensity as it reflects the small variations due to shot-to-shot instrumental variations. As presented from Figure  6a , molecular information provided by the C, H, O, and N lines, as well as the C2 and CN bands, and the common ratios usually employed for polymer discrimination  [30]  allows to partially distinguish between polymers and leather samples; blue circles representing leather are low on the PC1 axis (<0), while polymers are high in this axis.
Combination of Molecular and Elemental Information The data provided by the complete spectra are often employed in LIBS spectroscopy to discriminate between samples. In the case of leather, the complex fingerprint caused by titanium occurrence in many leathers could bias the discrimination with PC only based on the Ti information. A supervised selection of elements and wavelengths minimizes this risk. The 44 lines and molecular bands selected according to their sensitivity and resolution from other lines are presented in Table  2. Many elements were detected in leather, probably due to the pigments employed to obtain very bright colors, which are often applied for fish leather or snake leather (purple, yellow, bright orange). Large additions of calcium, magnesium, sodium, or barium salts are also visible from yellow-and turquoise-colored snake and crocodile skins.
Diego Rinallo Emlyon Business School, France Based on his analysis of the Pentecostal consumption field in Ghana,  Appau (2021)  advanced the notion of a divine economic system, consisting of three interdependent forms of religious exchanges (with the church as an institution, among church members, and direct sacred exchanges with God). This system is qualified as divine 'not because the system itself is divine but because it is centralized and legitimized by the divine, rather than by the market or by social norms  ' (p. 194 ). Appau's work has undeniable merits, as it brings religion back to the centre of religious consumption and marketing research, thus offering a useful theoretical vantage that respects consumers' worldviews. This is in line with  Ozanne and Appau's (2019)  exhortation to take seriously into consideration consumers' metaphysical conceptions of reality, even when they clash with researchers' own and the politics of the publication game, which often requires to marginalize and explain away data that does not fit well with a secularist social science standpoint.
Acknowledgments We thank  Peter Czaban ,  Arthur Parzygnat ,  Richard Samuelson ,  Rob Spekkens ,  Elie Wolfe  and  Fabio Zanasi  for discussions and helpful feedback on a draft. Special thanks are due to  Fabio Gadducci  for a long email exchange and copious help with the literature on gs-monoidal categories. Acknowledgements We thank  Andreas Klingler  for discussions and fruitful collaboration on [13]. The first.
Acknowledgement The research presented here has been financed by the research project DETECt: Detecting Transcultural Identity in European Popular Crime Narratives (Horizon 2020, 2018-2021) (Grant agreement number 770151). Front de Libération Nationale, was an Algerian nationalist movement that was active from the 1950s to the 1990s and that campaigned, sometimes violently, for Algerian independence and an end to the colonial yoke. On 17 October 1961, the French federation of the FLN organized a peaceful demonstration in Paris against the curfew imposed only on "French Muslims". It was put down in blood by the CRS police force led by the infamous Paris police prefect Maurice Papon. 2. "Roman archéologique", Viart, 2009: 12, our translation. All translations are ours unless stated otherwise.
Acknowledgements. We would like to thank  Rebecca Stacey  and  Aleks McClain  for their insightful comments on this manuscript. We would like to thank the  Sorprintendenza  for giving access to these ceramic materials for analysis. All necessary permits were obtained for the described study from the  Soprintendenza dei Beni culturali e ambientali di Palermo , which complied with all relevant regulations. We are grateful to the two reviewers whose insightful comments contributed to the improvement of this article.
Randomization procedure The study used a randomized controlled wait-list design. All participants attended an initial evaluation of 1 h at inclusion (T0), which consisted of a non-directive interview focused on the patient's experience of the disease, followed by an initial emotional regulation assessment (T0). After the initial evaluation, each participant was randomized within one of the two following groups: immediate intervention group (G1) and delayed intervention group (G2). The randomization list was created with Microsoft Excel software by the statistician, without blocking, before the investigators made the inclusions. Staff who included participants and made treatment allocations were blinded to this list until the initial evaluation was completed, after which the trial was conducted in an open-label fashion.
Quantitative analysis The characteristics of the study population were described using descriptive statistics. The analysis was performed with an intent-to-treat approach, i. e. on all patients randomized to the initial group regardless of their participation in activities. Missing data regarding the outcome were dealt with by implementing a multiple imputation approach with a predictive mean matching method. Five datasets were generated and pooled in the analysis. Data were described with frequency or percentage for qualitative variables, and with mean and standard deviation for quantitative variables. Data from the DERS questionnaires were described by item and the overall score and sub-scores were calculated. The comparison of groups G1 and G2 between T1 and T0 was carried out by calculating the difference in means in the overall DERS score within each group.
A qualitative content analysis was undertaken, which involved a continuous inductive analysis carried out to establish categories that go further than the ones based on the initial hypotheses of the DERS, in order to better understand and explain changes in emotional regulation. All interviews (n = 112) were audiotaped with the permission of the participants, transcribed in verbatim, and later processed independently by two analysts (a research coordinating engineer and the coordinating investigator) using a thematic analysis. In order to avoid influence from DERS classification, we chose a conventional content analysis approach to identify themes  [32]. The analysis was conducted in an inductive manner to produce themes from the material. The analysis was conducted according to the following steps: (i) the transcribed interviews were read thoroughly, in order to achieve an overview of data and approach experimental themes; (ii) units of meanings linked to emotional regulation were identified and coded; (iii) coded data was condensed and abstracted within each of the categories, which were simultaneously elaborated, and (iv) the content of each interview was organized between each category  [33].
Ethics and regulation All the requirements of French Law were fully complied with. An ethics committee (Comité de Protection des Personnes -Tours -Région Centre-Ouest 1) endorsed the protocol on June 28, 2016. The protocol and the database were registered on May 12, 2016 by the French National Data Protection Committee (CNIL) according to the requirements of the declaration of conformity. The protocol was registered on Clinical Trials under the reference NCT02911207.
Acknowledgements The authors would like to thank the following contributors for their essential participation to this study:  Mathilde Bourgueil ,  Catherine Greffier ,  Erwan Rabiller ,  Myrtille Richard ,  Cécile Ferriot ,  Clément Le Glatin ,  Claire Fesquet ,  Pierre Caillault ,  Marianne Bourdon ,  Lise Gross  and everyone at the  Fabrique Créative de Santé.
pseud(o)-complement/argument of noun as in ψευδάγγελος psevðàgelos, lit. pseudoangel 'who announces lies', or in ψευδολόγος psevðológos 'who tells lies, liar'. These formations can be glossed by a corresponding phrase. 2. pseudo(-) specifier/adjunct in cases which we cannot easily paraphrase by using corresponding phrases: ψευτοδουλεύω pseftoðoulévo, lit. pseudowork, does not mean 'work in a false/artificial way' but 'work a little' or 'pretend to work' (see  Efthymiou 2017b: 5-11). The first path is still at work in Modern Greek and even if rare, it is not negligible: we encounter it with lexicalized units as ψευδομάρτυρας psevðomártiras 'false witness, perjurer' and within the scientific vocabulary as ψευδοκύστη psevðokísti 'pseudocyst'. The second path, the dominant one in our corpus data and in general, is very prolific/productive, in line with the affixoids' Modern Greek paradigm.
Corpus The data extraction both in Greek and French was motivated by the need to cover as many registers as possible. For French, we consulted the following three corpora: first, the literature database Frantext gave back 1,441 tokens of pseudo from 1610 to 2019. Secondly, the fra_mixed_2012 corpus, available on the Leipzig Corpora Collection -Wortschatz, composed of various texts (from newspapers, webcrawls, etc. ), returned 9,582 tokens of pseudo and pseudos, from which we retrieved the first 200 tokens of each form. This corpus also allowed us to extract a list of 1,370 words composed on the scheme pseudo* or pseudo-* 11. Thirdly, we found 121,673 tokens of pseudo (excluding pseudonyme) in the French Web 2017 Corpus (frTenTen17), from which we retrieved a random sample of 400 tokens and a list of 997 words composed on the scheme pseudo* or pseudo-*.
As expected, the results in these corpora and databases contained some noise, since pseudo(-) can be used to designate, by truncation, a pseudonym, which was manually eliminated and relevant tokens were not considered in the analysis. For Greek, we also consulted three corpora: in the first place, we used the Thesaurus Linguae Graecae (TLG) to register the initial uses of pseudo(-), diachronically speaking, as already mentioned in 2. 2 above, but we do not further exploit in this paper the tokens found in this base (see  Fotiadou et al. forthcoming). For Modern Greek, we used the Greek Web.
Still, much work remains to be done. We need to analyze the interesting double marking on pseudo(-) (i. e. , pseudo(-) in quotation marks or parenthesis: "pseudo"-scientist or (pseudo)-scientist) that could reveal a form of linguistic insecurity towards its status, as shown in Section 2, along with an indication of a subjective designation. More research must be also conducted by examining in a systematic and quantitative way the pairing between pseudo  (-)  and X examples appearing in the second position of the structure in order to reveal fine-grained affinities, recurrences and preferences of pseudo(-) and to provide statistics about the distribution of the readings. For instance, our corpus data do not include general nouns like thing, action, movement, noise, smell, gesture, etc. in the X position.
Petrographic analysis As a first approach to determine the types of inclusions present in our samples, we made petrographic observations by means of a polarizing microscope (Leica Microsystems, Wetzlar, Germany) with 2. 5 × to 20 × objectives, coupled to a Leica DM2500 camera. This system uses the Leica Application Suite v3 imaging processing software. Thin sections were prepared to a thickness of 30 µm and metallographically polished by mechanical methods. Plane polarized light (PPL) and cross polarised light (CPL) images were taken at different magnifications to identify the nature of the inclusions present in the ceramic pastes and to define the petrographic groups. To determine the percentage of inclusions, present in the samples, the comparative chart for visual estimation of percentages of minerals in rocks was used  (Terry and Chilingar 1955).
8 ). The presence of secondary calcite can generate a wrong interpretation of the results, providing a higher value on CaO than the one that may correspond to the ceramic. Therefore, removing this compound from a statistical review is highly advisable. Considering the impact on the statistical data treatment provided by the previous elements, a new relatively low vt value of 0. 67 is calculated, suggesting a low heterogeneity in the compositional dataset. According to ICP-MS results (18. 45 % Al 2 O 3 , 67. 40 % SiO 2 , 2. 43 % MgO, 3. 60 % CaO, 0. 71 % TiO 2 and 5. 47 % Fe 2 O 3 ), it is evident that the set of Armatambo ceramics is not calcareous and contains a relatively high amount of silica (Table  4 , supplementary materials). With these results, it was decided to perform a statistical treatment on the 61 samples retained from the ICP-MS analysis (Table  2 , supplementary materials).
A cluster analysis was performed using R software and the multivariate statistical approach developed in the ArchFlow package (R Core  Team, 2014; Calparsoro, 2019 and references therein) , which uses the squared Euclidean distance and the centroid algorithm after centered log-ratio transformation of the analytes retained after the matrix variation calculation to identify and plot chemical similarities among samples on the subcomposition (Al 2 O 3 , Rb, Sr, Pb, Sn, Zr, Nb, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, Th, U, Na 2 O, MgO, SiO 2 , K 2 O, TiO 2 , V, MnO, Fe 2 O 3 ). Therefore, Fig. 9  summarizes the multivariate statistical approach, showing 6 clusters, where the clusters on the left side of the dendrogram are formed by a single individual. However, a compact cluster formed by most of the individuals in the study is in the center and a cluster formed by 4 individuals is on the right side of the graph.
Acknowledgments This work was carried out in the framework of a doctoral research program under supervision of two laboratories in two universities:  University Bordeaux Montaigne  and  University of the Basque Country. The laboratories involved are Archeosciences Bordeaux -UMR 6034, laboratory from  UBM  and  GPAC  and  IBea  from  UPV/EHU. We would like to thank all the staff for great support in analytical sessions. The authors thank for technical and human support provided by  SGIker (UPV/EHU/ ERDF, EU). Special thanks to  Dante Casareto  of the  Museum of Anthropology, Archaeology, and History of Peru in Pueblo Libre  for his advice and unconditional support. We also thank the editors and anonymous reviewers for all the constructive comments that have greatly improved this work.