dataesr/scientific-paragraphs-categorization huggingface dataset:
Material. The survey was conducted using Qualtrics® electronic survey software, which recorded the participants' responses and randomly delivered the stimuli. Three types of stimuli were presented: (1) four high-calorie food pictures (two sweet: crepes and churros, and two savoury: pizza and hotdogs); (2) four low-calorie food pictures (two sweet: pineapple and fruit salad, and two salted: tomato and broccoli); and (3) eight non-food pictures with similar characteristics in terms of shape, colours, and luminance to the non-food pictures (see Fig. 1 ). Two additional non-food pictures (of pink towels and a black box) were used for the training trials. All the pictures were taken from the Food-Cal database, which is a controlled database of high-and low-calorie food pictures matched with non-food pictures  43.
The last measure was a 100-point selfevaluation scale ranging from 0 (not at all) to 100 (absolutely), which participants used to evaluate their desire High-Calorie (sweet)  Procedure. The participants were first instructed not to eat in the two hours before the task, to take off their watch, to put their mobile phone away during the experiment, and to hide the clock on the menu bar of their computers to avoid any influence on time perception. They then performed a bisection task composed of three successive phases: pre-training, training, and testing. In the pre-training phase, the participants were exposed to the "short" (400 ms) and "long" (1600 ms) standard duration twice. The temporal stimuli took the form of control stimuli from the Food-Cal database. The participants were also asked not to count during the task, as this is an effective method used to prevent counting  45  , in order to better measure subjective time perception.
Moreover, five intermediate durations (600; 800; 1000; 1200 and 1400 ms) were integrated in addition to the standard durations (400 and 1600 ms). Each food picture was displayed twice for each duration, making a total of 56 experimental trials for each of the high-and low-calorie picture conditions (4 food pictures × 2 repetitions × 7 durations = 56). There was also a third block of 56 trials, in which the eight non-food matched pictures were presented seven times each (once for each probe duration). In all, a total of 168 trials were randomly distributed. Statistical analyses. Data were analysed using SPSS v. 26 (IBM, 2019). First, descriptive statistics (i. t. o. means, standard deviations, skewness, kurtosis) and Pearson correlations were computed for each assessment interval to describe the data, the relationships between the factors, and to test for the assumptions underpinning the use of Repeated-measures analyses of variance (RM ANOVAs).
Greenhouse-Geisser corrections were applied when violations of sphericity occurred. The probability of a "long" response, P(long), was calculated for each individual in each picture condition for each duration in order to obtain psychophysical functions. In line with the traditional logarithmic four parameter sigmoid (L4P) model  46  , we fitted sigmoid functions to the calculated psychophysical curves. This method often provides excellent data fits and reasonable approximations of the BP and WR  47. The data was modelled using Python. The BP is the "psychological mid-point" of the duration range between S and L, representing the duration producing 50% "short" responses and 50% "long" responses. Another parameter, the Weber Ratio (WR), was also calculated. The WR is an index of time sensitivity, and is the difference limen (p(long) = 0.
75 -p(long) = 0. 25) divided by the BP. A high WR indicates low time sensitivity, and a low WR indicates high time sensitivity. The program failed to fit an accurate sigmoid curve on seven psychophysical curves out of a total of 276 (N High-Calorie = 1; N Low-Calorie = 2; N Control = 4). A total of seven participants were therefore rejected from our database. The data for both the WR and the BP did not violate the assumptions of multivariate normality (normal distribution), as absolute values of skewness and kurtosis did not exceed the + 2, to -2 range threshold  48, 49. Additionally, all Mauchly's sphericity tests being non-significant (p > 0. 05), the variances of the difference between all combinations of the within-and between-group factors were equal (i. e. , to test for an increase in Type 1 error).
Statistical analyses. A total of three reproductions were deleted from the database because they were associated with display durations that were 200 ms longer than the stimulus duration which should have been presented. This corresponded to 0. 03% of the data (3 out of 11,648). On average, the presentation time compared to the expected time was accurate (M = 0. 05; SD = 0. 004). The planned analyses were similar to those performed in study 1, and the preliminary analyses allowed us to perform RM ANOVAs. Nonetheless, at this point it is important to mention that Uni-ANOVA comparing the Experiment 1 group with the Experiment 2 group revealed that the populations differed in terms of reported arousal F(  1  Proportion of long responses. Figure  5  shows the proportion of stimuli participants judged to be long (proportion of long responses, p(long)) plotted against the comparison durations for each picture condition.
Statistical Analysis All analyses were performed using SAS software, version 9. 4 (SAS Institute). Descriptive statistics were calculated for participant demographic and clinical characteristics and reported overall and for the participants with self-reported diagnosed and self-reported undiagnosed vitiligo. Comparisons between the participants with self-reported diagnosed and self-reported undiagnosed vitiligo were assessed using t test for continuous variables and χ 2 test for categorical variables. The level of significance was 2-sided P =. 05 and is presented for descriptive purposes. The sample size for this study was chosen to provide reasonable precision around the estimate of prevalence and not to examine differences in these characteristics between the diagnosed and undiagnosed vitiligo participants.
Specifically, 1 large, general population study in the US, conducted 4 decades ago, estimated the prevalence of diagnosed vitiligo at 0. 49%. 6, 8 Additionally, a large database study estimated the prevalence of diagnosed vitiligo at 0. 50%. 7 Other studies on the prevalence in the US only focused on regional US communities (eg, control patients from a case-control study of juvenile rheumatoid arthritis [prevalence estimate of 0. 40%] and Arab Americans [prevalence estimate of 1. 55%]). 10, 11 Lastly, a large administrative claims database study reported a prevalence estimate of 0. 05%, which is inherently reliant on the clinician recording the diagnosis in a claim for reimbursement and, thus, is likely to underestimate the true prevalence. 12 he estimates of point prevalence of undiagnosed vitiligo were 0.
Limitations While this study closely represents the distribution of the US general population with respect to demographic characteristics, there is a potential for selection bias owing to internet accessibility. However, it was estimated by the American Community Survey that the percentage of households in the US with internet access was nearly 90% in 2016. 29 Additionally, because the survey data were self-reported by participants and a low percentage of participants with vitiligo uploaded photographs (20. 1%), the data may be subject to reporting bias. To mitigate some reporting bias, the survey questions included nonclinical terminology next to any clinical terminology, where appropriate. Furthermore, vitiligo status was self-reported by participants and not confirmed with in-person evaluation or diagnostic testing.
However, vitiligo screening questions were developed based on adaptations of published screening tools and feedback from expert dermatologists in the field. Clinician adjudication of self-reported vitiligo was also undertaken using a teledermatology app. The use of telehealth solutions is evolving in epidemiology research, and while user error and photograph quality cannot be closely controlled, advantages include the ability to scale to a large population study, retain a large sample size owing to ease of use, and standardize data collection and submission. Clinician adjudication was performed for only 20. 1% of participants who uploaded photographs, and assumptions of missing at random cannot be confirmed. Nevertheless, the clinicianadjudicated prevalence estimates of vitiligo in this study, with the inclusion of sensitivity analyses, provide a conservative and reliable estimate of the prevalence of vitiligo in the US population with lower prevalence of clinician-adjudicated vitiligo potentially accounting for bias owing to higher selfreporting.
Qualitative and Semi-Quantitative Composition of the Essential Oils The different essential oils (EOs) were analyzed by GC-MS. Based on the previous literature and databases, 47 chromatographic peaks could be annotated (Table  1 ). These compounds corresponded to chromatographic peaks representing from 88% to 97% of the total area of all peaks. These oils were characterized by their richness in sesquiterpene hydrocarbons. This volatile fraction was the most abundant  (29-46%)  in almost all the different EOs (Table  1 ). Monoterpene hydrocarbons were present (5-42%) in all the samples. Oxygenated sesquiterpenes and oxygenated monoterpenes were in 13-37% and 3-9%, respectively. Within all samples, the major compounds detected were: α-pinene (2-13%), β-caryophyllene (8-25%), β-myrcene (0. 1-19%), bornyl acetate (0.
Few or no data exist concerning genetic traits associated with the EO profiles. If P. lentiscus is an allogamous (dioic) species, we can assume that chemotypes were mostly (and naturally) selected essentially based on pedoclimatic traits. In our study, according to the harvest time (season) and place (altitude), various main chemotypes were detected. Except for the precise percentages, some of our main chemotypes correspond to other profiles previously described: caryophyllene  [31, 38] , δ-cadinene  [19] , myrcene  [18, 39] , and α-pinene  [22]. Variations in EO profiles can be of interest. Nevertheless, it is important to determine the origins of variations before expecting a standardized production and a further economical use of such natural products, hence our interest in this littoral and mountain study.
To our knowledge, only one unique study described the influence of the altitudinal gradient on the chemo-variation of P. lentiscus EO composition  [26]. The samples were collected in Algeria, but with only one harvest period (September 2008). Data from our multisite/multiseason results are in accordance with Ait Said et al. [26]. The relationship between altitude and the chemotypes were commonly characterized by caryophyllene and by significant levels of monoterpene and sesquiterpene hydrocarbons.
A full-scan detection for masses (m/z) between 35 and 350 UMA was performed at a rate of 3000 UMA/sec (4. 18 scan per second). Each sample of essential oil was diluted 1000 times in hexane containing pentadecane (1/4000 v/v) as the internal standard. The identification of oil components was assigned by comparison of their retention times and retention indices (RIs). Experimental RIs were calculated as the relative retention times of compounds compared with those of (C10-C40) n-alkanes. Comparison of experimental RIs (RIxp) was conducted with RIs from the literature  [2, 16, 18, 19, 23, 29, 31, 37, 44, 66]  and with those of authentic compounds available in the authors' laboratory. Moreover, identification was confirmed by comparing the mass spectra of each molecule with (i) those available in the NIST 05 library of the GC/MS data system and with(ii) the mass spectra published  [67].
All authors have read and agreed to the published version of the manuscript. Funding: This work was funded by  (1)  the French Ministry of Foreign Affairs through Campus France (file no. 973496A); (2) the "Conseil Régional de Picardie" through the MTV (Métabo-Typage Végétal) project; (3) the University of Picardie Jules Verne through the French Ministry of Higher Education and Research, region "Hauts de France", the European FEDER funds within the so-called CPER programs devoted to equipment acquisitions. This work was also funded by Algerian authorities though the financial support of the Tizi-Ouzou UMMTO University and a social grant attributed to Chabha SEHAKI for her PhD.
Lê, S. ; Josse, J. ; Husson, F. FactoMineR: An R package for multivariate analysis. J. Stat. Softw. 2008, 25, [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18].
Study design and population This study used data from the last three Demographic and Health Surveys (DHS) conducted in Guinea in 2005, 2012 and 2018 by the National Statistics Institute of Guinea (Institut National de la Statistique, INS) with technical assistance from the DHS programme (Program DHS, ICF/USAID). These surveys used two-stage stratified cluster sampling methods (region and place of residence). The weight and height of the children were measured and collected during these repeated cross-sectional studies. Weight was measured using electronic scales (Seca, Hamburg, Germany), while height measurements were taken using graduated height scales. Children under 2 years of age were measured lying down, while older children were measured standing up  (10) (11) (12). Data of children under 5 years of age who had a weight and height measurement available were analysed.
Statistical analysis The data were analysed using the statistical software R version 1. 4. 1106R: A language and environment for statistical computing, and R Foundation for Statistical Computing (URL https://www. R-project. org/). Descriptive analyses of household, child and maternal characteristics were performed separately for each survey. Height-for-age, weight-for-height and weight-for-age Z-scores were calculated for children who had available height and weight measurements, and the height-for-age < -6 or > 6, weight-for-height < -5 or > 5 and weight-for-age < -6 or > 5 were excluded according to the WHO standards  (13). The exclusion was done by Z-score and not by child. Univariate and multivariate logistic regression models were used to identify factors associated with stunting, wasting and underweight.
Ethical considerations The protocol and questionnaires of the DHS-2005, 2012 and 2018 have been approved by the National Ethics Committee and endorsed by the ICF Ethics Committee (International Review Board), and the informed and voluntary consent of the parents was obtained for all children. The data were obtained, following a request on the DHS website (URL: https://www. dhsprogram. com/ data/available-datasets. cfm). However, no formal ethical approval was obtained as the study involved secondary analysis of publicly available data. During the three DHS, more than 70 % of children under 5 years old were included in rural areas. About 17 % of the children lived in the Kankan region and 24 % of the children were from poorest households. The majority of the children were boys (51•4 %) and between 12 and 23 months of age (20•7 %).
In response to these events, several interventions have been implemented by the government, institutions and non-governmental organisations operating in the nutrition and food security sector. For example, the strategic collaboration between the World Food Programme and UNICEF was very dynamic in the period before the Ebola crisis. In addition, representatives of both agencies have been very active and have helped to focus attention on nutrition at the highest level of government. Guinea's membership of Scaling Up Nutrition and Renewed Efforts Against Child Hunger and undernutrition is testimony to their efforts  (18). Analysis of the dataset showed that rural residence, low household socio-economic status, age and sex were the factors associated with stunting in children. Low maternal weight was the only factor associated with wasting.
For this to happen, policymakers must work more to fight poverty in all its forms. Awareness-raising activities on the nutritional practices of parents and children must be intensified. In addition, actions on the promotion of exclusive breastfeeding and the initiation and support of mothers in the diversification of their children's diet must continue to take place. The study has some limitations, mainly the lack of the weight and height data for most of the children surveys, which is due to DHS being household surveys; data are collected for all children under 5 years of age living in the selected households, but weight and height measurements are taken for children present on the day of the survey. In addition, the proportion of missing data was similar in all three surveys. This must be taken into account in future surveys in order to reduce bias in the estimation of prevalence.
Acknowledgements Acknowledgements: The authors thank the  DHS  programme for making the data available. The authors wish to thank  Philip Robinson  ( DRS, Hospices Civils de Lyon ) for manuscript preparation. Financial support: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Conflicts of interest: There are no conflicts of interest. Authorship: S. T. B. contributed to the acquisition, analysis and interpretation of data, drafting of the manuscript and final approval under the supervision of N. K. ; N. K. , M. R. , A. T. , P. V. , A. C. , S. C. , K. J. -J. O. K. , M. C. participated in the revision and final.
The loops connecting elevator and stator domains were adjusted manually using the geometry regularization feature in Coot  49  (Supplementary Data 1). A structural alignment of our in-lipid cryo-EM structure with the AlphaFold model results in an r. m. s. d. of 2. 1 Å between 605 C-alpha atoms. Restricting the alignment to the Q-domain results in a smaller r. m. s. d. of only 1. 2 Å between 136 C-alpha atoms. The differences between the two structures can be best described as a concerted movement of the elevator domain with respect to the stator domain with the elevator assuming a slightly more "downwards" conformation in our experimental structure vs. the computational prediction (Supplementary Fig. 8 ). High-affinity VHHs inhibit sialic acid transport. An alpaca was immunized with DDM solubilized HiSiaQM, and nine distinct VHHs (VHH QM 1-9) were isolated.
4a  and Supplementary Fig. 11 , Supplementary Data 2). An analysis with the PISA server  60  revealed that a combined surface area of ~1980 Å 2 is buried by complex formation. Figure  4b  shows the conservation of this P-QM interface across a large number of different TRAP transporters. In the tripartite HiSiaPQM complex, the N-terminal lobe of HiSiaP is bound to the stator domain of V H HiSiaQM, and the C-terminal lobe is bound to the elevator domain. This arrangement puts the substrate-binding cleft of HiSiaP directly on top of the presumed substrate-binding site of the transporter, as identified by superpositions with substratebound VcINDY (Supplementary Fig. 12 ). This suggests that the N-terminal lobe of the SBP stays fixed on the stator, while its C-terminal lobe can move in concert with the up-and-down movement of the elevator during a transport cycle.
5a, b ). Mutations of highly conserved residues R127A P and R147A P in the P-domain (region I, Fig. 5 ), which are known to be important for substrate binding and were previously described as a substrate-filter  25  , showed comparably small effects in the growth assay. This observation is in accordance with previous data and crystal structures of substrate-bound R147 P variants, where the arginine-carboxylate interaction is mimicked by water molecules  25. It seems that at high substrate concentrations (3. 2 mM in our assay) this can be tolerated by the system. Minor effects were also observed for mutants of the periplasmic loops or the adjacent region of the P-domain (region II, Fig. 5 ). Twelve mutants are located region III (Fig. 5 ), which connects the N-terminal lobe of HiSiaP and the stator of HiSiaQM.
Data are presented as mean values ± SD of n ≥ 3 independent experiments. Source data are provided as a Source Data file. Q178A P N150D M W227R M R484E QR30E M S356Y M E429R M D304A M D521A M Q486A M E235R PD58R PS60R P E172R Q F111A Q E41Q Q E42Q Q E41Q/E42Q M N354Y M S298A Q D114K HiSiaQM. In this region, the strongest effects were seen with mutants E172R P , R30E Q , S356Y M , and E429R M. The variants are spread over a slightly larger area than the interface III mutants. E172R P and S356Y M would again lead to severe steric clashes. The effect of the R30E Q mutant of the strongly conserved R30 Q cannot be explained by steric hindrance in the C i -state of the transporter. However, we noticed that this residue is in the saltbridge distance with the other knock-out mutant E172R P in the C o -state transporter model (Fig.
6o, p ). The TIRF data above is supported by surface plasmon resonance (SPR) experiments where HiSiaQM (in DDM micelles) was immobilized on an SPR chip as described above in the VHHbinding studies. Figure  6r  shows that the closed P-domain interacted with the immobilized transporter (5 mM sialic acid was added to the running buffer). The interaction was clearly weaker in the absence of sialic acid and could be blocked by saturating the immobilized QM-domain with VHH QM 3 (Fig. 6r, s ). Interestingly, the resulting sensorgrams and especially the fast dissociation of the analyte could not be satisfyingly fit with a 1:1 binding model (Fig. 6r ). Hence, the true K D is very likely higher (i. e. weaker) than the average K D of ~1 µM that was determined from a set of four independent SPR experiments.
For each of these three samples, a fresh bilayer was prepared on a new coverslip and n = 30 individual measurements were performed. The underlying data is compiled in Supplementary Table  3. The scale bars equal 3 μm. r Sensorgrams showing the interaction of the P-domain with immobilised QM-domains (HiSiaQM K273C-biotin in DDM) in the absence (red) or presence (green) of sialic acid (5 mM). The green curve was fit with a 1:1 binding model (grey). Four independent experiments were performed. s Competition experiment between the P-domain and VHH QM 3 for the immobilized QM-domains. Green curve: a buffer injection followed by an injection of the P-domain. Orange curve: the chip surface was saturated with VHH QM 3 before the P-domain was added. Single experiment, supported by multiple other experiments in this study (e.
The analytes, the VHHs or the megabody, were added in six injections (30 µl/min, 120 s) with a doubling of the concentration at each step, resulting in single-cycle kinetic titration curves. The binding data were double referenced by blank cycle and reference flow cell subtraction. For epitope binning, the VHHs were tested for competitive binding using an ABA-injection protocol. For characterizing the binding of HiSiaP, biotinylated HiSiaQM (K273C) was immobilized as described above. Single-cycle kinetic titration curves were recorded for eight (0. 078, 0. 156, 0. 312, 0. 625, 1. 25, 2. 50, 5. 00, 10. 00 µM) injections of HiSiaP. The buffer was supplemented with 5 mM sialic acid where indicated. Competitive binding of VHH QM 3 and HiSiaP was assessed by consecutive injections of either buffer or VHH QM 3 (50 nM, 30 µl/min, 180 s) followed by HiSiaP (2.