dataesr/scientific-paragraphs-categorization huggingface dataset:
Boundary Conditions The symmetry at the axis r = 0 leads to: ∂T ∂r r=0 = 0 (6a) ∂ → V w ∂r r=0 = → 0 (6b) At the vertical wall which corresponds to r = R: → V w (t, r = R, z) = → 0 (6c) -2πrH λ w ∂T ∂r r=R = q 0 (6d) Energies 2022, 15, 818 6 of 18 At the bottom of the cylinder (z = 0) and at the upper surface of mixture (z = H): ∂T ∂z z=0 = 0 (6e) ∂T ∂z z=H = 0 (6f) 2. 5. Computational Fluid Dynamics (CFD)Modeling and Mesh Generation 2. 5. 1. CFD Modeling The conservation Equations (  1 )-(  4 ) have been resolved using COMSOL Multiphysics software which is based on the finite element method. Indeed, the time derivative of the continuous phase (fluid) was discretized by an implicit scheme of second order using the backward differentiation formula. Then, the problem was solved using the PARDISO solver combined with the α-generalized solver by considering relative tolerances of 10 -3.
CFD Modeling The conservation Equations (  1 )-(  4 ) have been resolved using COMSOL Multiphy ics software which is based on the finite element method. Indeed, the time derivative the continuous phase (fluid) was discretized by an implicit scheme of second order usi the backward differentiation formula. Then, the problem was solved using the PARDIS solver combined with the α-generalized solver by considering relative tolerances of 10 The heat equation was discretized by linear elements whereas fluid velocity and pressu were determined using quadratic (P2) and linear (P1) elements, respectively  [26]. Final the trajectory of the particles was simulated based on the calculation of velocity an pressure in the continuous phase (water).
For the mass spectrometer conditions, a Heated Electrospray Ionization source II (HESI II) was used. Nitrogen was used as the drying gas. The mass spectrometer conditions were optimized as follows: spray voltage 2. 8 kV, capillary temperature 350 °C, sheath gas flow rate 60 units, aux gas flow rate 20 units, and S lens RF level 50. Mass spectra were registered in full scan mode from m/z 100 to 1,500 in negative ion mode at a resolving power of 70,000 FWHM at m/z 400. The automatic gain control (AGC) was set at 1e6. The MS/MS spectra were obtained by applying a relative higher energy collisional dissociation (HCD) energy of 25%. The identification of the compounds of interest was based on their retention time, accurate mass, elemental composition, MS fragmentation pattern, and comparisons with available standards and the advanced mass spectral database, m/z Cloud, https://www.
mzcloud. org. Data were acquired with the XCalibur 4. 2 software (Thermo Fisher Scientific Inc. ) and processed with the compound discoverer 2. 1 and the Skyline 20. 1 software (MacCoss Lab. ). For quantification, standard stock solutions of caffeic acid, caffeoylquinic acid, kaempferol, quercetin, protocatechuic acid and gallic acid (Sigma Aldrich, St. Louis, MO, United States) were dissolved in methanol at a concentration of 1 mg/mL. A mixed stock solution containing 10 μg/ml of each polyphenol standard was prepared in methanol and then diluted in 0. 1% formic acid to obtain the desired calibration curves ranging from 10 to 4,000 ng/ ml. After linear regression calculation, the analyte concentrations were determined and expressed in mg/g of dried plant (calibration curves of each standard polyphenol had a correlation coefficient (R2) of 0.
lanceolatum aqueous extract at the MNTC (0. 3125 g/L) or E3 medium (Control), for 7 days. For dexamethasone exposure, 3-dpf amputated eleutheroembryos were incubated with 0. 4% ethanol in E3 medium (Vehicle), 500 µM of dexamethasone (DEX) or dexamethasone and H. lanceolatum aqueous extract treatment at 0. 3125 g/L (DEX + HL), for 3 days. Every solution was changed each day and images were taken, under anesthesia, at 0 and 3 dpl. Three independent experiments were performed on 20-39 eleutheroembryos/condition. The area of regenerated fins was semi-quantified by using Image J software.
Microscopy Pictures were acquired using a Nikon eclipse 80i equipped with a Hamamatsu camera, a Nikon SMZ18 stereomicroscope equipped with a Nikon DS-Fi3 Camera and the respective NIS elements software. Images were analyzed using the ImageJ software (https:// imagej. nih. gov/ij/). Quantification of regenerated fin area, fluorescence intensity and cell numbers were performed by two different users blinded to the treatment, and then the results were averaged.
Although this chemical antioxidant assay is of no pharmacological relevance, it provided an "IC 50 -like" antioxidant capacity estimated to 0. 86 ± 0. 1 g/L, which is ~10 times less than the positive control ascorbic acid (Table  2 ). In a second step, the H. lanceolatum aqueous extract was analyzed for its polyphenolic composition by LC-MS/MS analysis. The results revealed that H. lanceolatum is indeed rich in a wide variety of polyphenols, including phenolic acids and flavonols. LC-MS/MS allowed the identification of 23 polyphenolic compounds, in comparison with standards and databases (Figure  1 ). Among the main polyphenols identified, we observed the presence of 5-caffeoylquinic acid (chlorogenic acid), quercetin glycosides and kaempferol glycosides (see Table  3 ). Quantification showed a high content in caffeoylquinic acid isomers (83.
The Aqueous Extract of H. lanceolatum Modulates Oxidative Stress and Inflammation in vivo To the best of our knowledge, there are no data documenting the antioxidant and anti-inflammatory effects of H. lanceolatum in vivo. In order to ascertain these properties in physiological conditions, we tested the impact of H. lanceolatum treatment on a tail injury model in zebrafish. First, in order to test the effects of H. lanceolatum aqueous extract on oxidative stress, we performed a caudal fin amputation in adult zebrafish and used the oxidative stress probes DCFH-DA and DHE that become fluorescent after their oxidation by hydrogen peroxide and superoxide anion, respectively. In contrast to uninjured fish, the amputated tail was strongly stained with the fluorescent oxidized probes (data not shown).
The therapeutic treatment (immediately after the amputation), did not modulate oxidative stress (data not shown). We consequently examined the preventive antioxidant properties of H. lanceolatum extract by pretreating the fish for 4 h before tail injury. As clearly evidenced, our results showed a consistent decrease in the fluorescence of oxidized DHE and DCFH-DA probes reflecting the antioxidant properties of the H. lanceolatum extract (Figure  6 ). In a similar way, we investigated the therapeutic effects of H. lanceolatum extract on immune cell recruitment, which occurs at the early phase of inflammatory response. Unfortunately, due to technical issues, we were unable to label immune cells in adult tail following injury. Consequently, to achieve this aim, we reproduced a tail injury model in 3-dpf eleutheroembryos    (Miskolci and Squirrell, 2019).
Spatial skewness is a continuous variable that describes the pixel gray level distribution characterizing the relative dominance of vegetation over bare soil and is strongly related to spatial pattern configuration with increasing skewness from spots (< -0. 5) to labyrinths (-0. 5 to 0) to gaps (> 0)  (Deblauwe et al. 2011). See  Deblauwe et al. (2011)  for more detailed information about classifying vegetation patterns. We overlaid these classified vegetation patterns (ca 410 m resolution) with time series (2001-2020) of enhanced vegetation index (EVI)  (Didan 2015)  and standardized precipitation evapotranspiration index (SPEI) (Vicente-Serrano et al. 2010) using the 'raster' package  (Hijmans 2018)  in R (<www. r-project. org>). All spatial data was downloaded using Google Earth Engine  (Gorelick et al.
2017 ) and aggregated to 16-day intervals. SPEI is a commonly used index that takes into account both rainfall and evapotranspiration as a measure of water availability to plants. The EVI and SPEI data were detrended at the pixel level to remove seasonal trends to be able to avoid bias in the comparison of temporal indicators across sites  (Dakos et al. 2012a). EVI time series were detrended by subtracting the mean EVI value of each 16-day period. SPEI time series were constructed using the 'SPEI' package using a log-logistic distribution function and a time scale of 1 month. A 1-month lag was chosen because of the short response of dryland vegetation to moisture availability  (Vicente-Serrano et al. 2013). Precipitation data was extracted from the climate hazards group infraRed precipitation with station data (CHIRPS) at ca 5 × 5 km ground resolution  (Funk et al.
2004 , Dakos et al. 2011)  where trends in these statistics have been suggested to serve as leading indicators of ecosystems approaching shifts to desertification. We reported trends for all indicators from all runs as 5, 50 and 95 percentiles. We solved the model using a semi-implicit method in a 128 × 128 cells lattice representing a 400 × 400 m landscape  (Janssen et al. 2008). Environmental stochasticity was added using an Euler-Murayama integration method with Ito calculus. We assumed periodic boundaries. Model simulations and statistical analyses were performed in MATLAB R2017b (MathWorks 2017).
Funding -This paper is a product of the  AfricanBioServices  Project funded by the  European Union 's  Horizon 2020 research and innovation program  under grant agreement no. 641918. R. M. G. was supported by  FAPESP  through grants  2019/24433-0 ,  2019/05523-8  and  ICTP-SAIFR 2016/01343-7 , by  Instituto Serrapilheira  through grant Serra-1911-31200, and by the  Simons Foundation.
METHODS Data from the STREAM Stage 1 trial were used, as previously described. 6 The Union's Ethics Advisory Group and all national and local ethics committees approved the trial. All participants provided written informed consent; they were randomised in a ratio of 2:1 in favour of the Short regimen, which was identical to that used by Van Deun and colleagues in Bangladesh,  3  except that moxifloxacin was substituted for GFX because quality-assured GFX was not available. Randomisation was stratified by centre and HIV status. All participants were followed up to 132 weeks post-randomisation to determine the primary outcome. The pre-specified primary and secondary outcomes are published in the main report. 6 riables included in the analysis The following characteristics were collected from participants at baseline: age, sex, weight, body mass index, presence of diabetes, HIV infection status, smoking status (current smoker, ex-smoker, nonsmoker) and haemoglobin level.
Corpus We analyzed data from the Languages and Social Networks Abroad Project (LANGSNAP) corpus  (Mitchell et al. , 2017). 2 The LANGSNAP team followed two cohorts of undergraduate students based in the United Kingdomone majoring in Spanish (n = 27), the other in French (n = 29)-over a period of 21 months, during which time each student spent an academic year in a target-language environment (9 in Mexico, 18 in Spain, 29 in France). All the participants were enrolled at the same British university at the beginning of the project, which coincided with the end of the second year of their degree program. For our analysis, we considered data from all participants who reported English to be their only native language, which corresponded to 25 Spanish and 25 French majors. 3 These participants included nine men and 41 women whose mean age was 20.
Thus, this variable operationalized proficiency not as specific levels (i. e. , intermediate, advanced, etc. ), but in relative terms. LANGSNAP researchers met with the participants six times. For our project, we focused on production data collected prior to the immersion experience (prestay: May 2011) and 1 year later, at the end of the 9-month stay abroad (end-stay: May 2012). At each data collection session, the participants wrote an approximately 200-word argumentative essay, participated in a semiguided interview, and completed a story retelling task. Because the story retelling data contained few instances of N/ADJ combinations, our analysis relied on data from the other two tasks. For the argumentative essay, the same topic, which asked the participants whether they thought that same-sex couples had the right to get married and adopt children, was used at prestay and end-stay.
Data Coding We manually identified all instances where the participants had produced a noun modified by an adjective within the same noun phrase. We embraced a broad understanding of the category adjective that included comparative and superlative forms (Example 2a) and what  Durrant and Schmitt (2009, p. 166)  called semideterminers (Example 2b). Example 2 a. French: la chose plus importante "the more important thing" Spanish: la cosa más importante "the most important thing" b. French: toutes les choses "all things"; deux choses "two things"; la même chose "the same thing" Spanish: muchísimas cosas "many things"; tantas cosas "so many things"; la primera cosa "the first thing"; ciertas cosas "certain things" Before coding the dataset, we removed all instances from the written data where the learners had used the N/ADJ combination "same-sex couple" (couple/homosexuel in French; pareja/gay in Spanish) that had appeared in the prompt to which they had responded.
The final dataset contained 4,808 N/ADJ pairs (2,240 in French, 2,568 in Spanish). Using a reference corpus, we coded each N/ADJ pair for three dependent variables that enabled us to investigate important usage-based determinants of language learning, one tapping input frequency and the two others, delta P noun→adj and delta P adj→noun , reflecting cue contingency. As we noted in the literature review, there exist numerous measures that reflect cue contingency. We opted for delta P because of the importance of taking directionality of association into account (see  Ellis & Ferreira-Junior, 2009; Ellis et al. , 2016; Gries, 2013). To analyze the French and Spanish data in a single analysis, it was important to choose reference corpora that were comparable in size and construction. The corpora created through the Web-As-Corpus Kool Yinitiative (2009) provided such resources.
In particular, we chose the Ten-Ten family of corpora  (Jakubíček et al. , 2013) , which offer multibillionword web-crawled corpora developed according to the same criteria for numerous languages. We used similar sized corpora compiled during the period of the LANGSNAP data collection for Spanish (esTenTen11 European Spanish + American Spanish: 9,497,213,009 words) and French (frTenTen12: 9,889,689,889 words). The three dependent variables required three queries per N/ADJ combination: lemmatized frequency of the N, the ADJ, and the N/ADJ combination. 5  For each search, we specified part-of-speech. In our N/ADJ combination searches, we respected the order N + ADJ or ADJ + N in which the learner produced the combination. Moreover, we allowed for up to one word to separate the N and ADJ, given that other elements can separate an adjective from the noun that the adjective modifies.
For the categorical variables, we designated one category as the reference category, meaning that the model assessed differences with respect to that reference point. The reference categories were prestay for time, interview for task, French for target language, and N + ADJ for phraseological unit. The random-effects structure of the models included participant as a random intercept; we explored random slopes but ultimately removed them because they did not significantly improve the models. We fit each model using the package lme4 in RStudio (RStudio Team, 2020). We then used the function dredge() from the MuMIn package to select the best model, based on the Bayesian information criterion (BIC), a goodness-of-fit metric  (Kass & Raftery, 1995). 7 The BIC balances between good fit and simplicity by placing a penalty on more complex models, thus guarding against overfitting  (Stoica & Selen, 2004).
When the BICs of two models were less than 6 points, we opted for the simpler model in the spirit of statistical parsimony. Once we had identified the final models, we used the relaimpo package to calculate the relative importance metric LMG  (Grömping, 2006). The R code that we used for this analysis and its output are available via IRIS  (Edmonds & Gudmestad, 2022). We assessed the fit of each model by considering its marginal and conditional R 2 values. The marginal and conditional R 2 values reflect, respectively, how much of the overall variance is explained only by the fixed effects and how much is accounted for by the whole model, that is, both fixed and random effects.
Omidian et al. suggested that the lack of significant trends reflected the considerable individual differences in the production of V/N combinations. In comparison, Siyanova-Chanturia and Spina (2020) attributed the decrease in N/ADJ frequency and cue contingency to the learners' growing (lexical) experimentation: It seems that, following extended exposure to the L2, as learners become more able language users and as they acquire more extensive (single word) vocabularies, they also tend to experiment more with word combinatorial mechanisms and, as a result, produce less idiomatic, less nativelike word sequences. (p. 451) Strikingly, these comparable studies of the same dataset have provided strong evidence of differences in learning trajectories as a function of lexical combination type. This observation suggests that care must be taken when comparisons are made across studies, as phraseological development appears to be sensitive to type of phraseological unit.
The results from our study provide further evidence in favor of the influence of phraseological unit on usage patterns. Because French and Spanish show two possible orders for N/ADJ combinations within a noun phrase, we included phraseological unit, that is, N + ADJ versus ADJ + N, as an independent variable in this study. Some researchers may argue that our dataset presents a set of collocations that happen to have two linear orders. This is particularly the case for approaches that define phraseological units as cooccurring word combinations independent of word order (e. g. ,  Paquot, 2019). However, the fact that linear word order was both significant and the most important predictor in all three analyses signals that ADJ + N and N + ADJ combinations had different usage properties in this corpus, raising the question as to whether they should be considered to be different collocations entirely.
Notes 1 The term additional languages refers to any language learned after the first language. 2 The corpus is available at http://langsnap. soton. ac. uk and https://slabank. talkbank. org/access. 3 We excluded Participant 122 because a complete dataset was not complete. 4 Information concerning the age of Participants 150 and 175 was not available, nor was the number of years that Participant 150 spent studying Spanish. 5 For interlanguage forms, if the target form was clearly recognizable, our corpus searches were based on the target form. This was the case for examples like provoca reacciones diferentes en distintas personas y distintas demográficas "It provokes different reactions in different people and different demographics" where the learner used the adjective demográficas instead of the target-like nominal form demografías.
Our corpus search for this item used demografía in combination with the adjective distinto. 6 Following  Field et al. (2012, p. 192) , we reversed the scores prior to transformation to preserve their directionality. For the transformation, we used the following equation: 1/(X highest -X). For example, the combination bueno + ejemplo ("good" + "example") had a delta P nouns→adj score of 0. 00036640. We began by reversing the score, so that it became negative (-0. 000366). To calculate the denominator, we then subtracted this score from the highest delta P noun→adj score in the dataset (0. 732326): 0. 732326 -(-0. 000366) = 0. 732692. This number was then plugged into the equation, resulting in: 1/0. 732692 = 1. 36483 7 To maintain statistical parsimony, when more than one model had the same BIC, we selected the model with the fewest predictors.
Protocol for taking tests and writing production activities To measure the deafness of the subjects concerned, we proceeded in two ways: (1) by applying audiometric tests using an audiometer. This screening and diagnostic test establishes hearing acuity in each ear. It was submitted according to a strict protocol, a standard test. We used the Audiometric device from Electronica Technologies, model 600 M, composed of a Sennheiser HD200 Pro headset with high sound insulation, an audiometric box, a 1 m USB cable, multi-user software running on Windows and accessible in multiple languages on a USB stick. Before proceeding with the diagnosis and hearing assessment, we filled out a form with the name of the school, the teacher, the class, the student's sex, the date and the time of the test. No information relating to the student's identity will be mentioned here.
Our observations at the Mennonite School were not too different. This institution accommodates children whose parents are mostly absent. In addition to being a traditional school, it is a vocational training center where children board to learn a trade. Some are very old (up to 22 years old), compared to the level of basic education. It has a population of 75 deaf and hard-of-hearing students. The duration of the data collection was not the same for the two schools. Data were collected over three months in Institution 1, while in Institution 2, the process lasted 18 months, from October 2018 to March 2020.
1 and 8. 2). Classes by the number of students by sex, the total number of students, and the number of teachers. Sampled on the basis of our study objective, the students of this school made it possible to collect data relating to the phenomenon of disability and the ideas held about them and their situation. Among the children concerned, 38 were diagnosed with total deafness, including unilateral and bilateral deaf, 23 with profound deafness, and 2 with severe deafness. Tables 8. 3-8. 5 summarize the data we collected from this student population. Indicators relating to the variables: code, date of birth, age, sex, level of study, intensity, type, and degree of deafness are considered. The duration of the data collection was not the same for the two schools. Data were collected over three months in Institution 1, while in Institution 2, the process lasted 18 months, from October 2018 to March 2020.
In both schools, grade 3 included pupils whose age was well beyond the normal school age. Most have complete hearing loss. Comparing the variables "type of deafness" and "Hearing degree", the data provide a basis to discuss disability or difference about this category of students. Many students in grade 4 are over the age of basic education. As shown in Table  8. 3, majority of them have complete hearing loss. Comparing the variables "type of deafness" and "Hearing degree," the data provide a basis to discuss disability or difference about this student's category. The data presented in Tables 8. 3-8. 5 mainly provide information on the degree of hearing loss. Comparing the variables "Type of deafness" and " Hearing degree,", the data provide a basis to discuss disability or difference about this category of students.