dataesr/scientific-paragraphs-categorization huggingface dataset:
ISO 25178-2 areal surface texture parameters From the measured surface, primary surfaces were obtained by application of an S-filter with a nesting index of 5 μm, to match the resolution chosen when resampling the triangle meshes into height maps after the co-localisation process. An F-operator was then applied (least-squares mean plane removal by subtraction) to provide SF surfaces. SL surfaces were also generated through the use of an L-filter with a nesting index of 0. 8 mm. The index of 0. 8 mm was chosen based upon values used in the existing literature  [14]. Four of the most commonly used ISO 25178-2  [15, 16]  surface texture parameters, Sa, Sq, Ssk and Sku, were then generated and compared for each of the forty acquired surface datasets in the SF and SL cases. Confidence intervals (CIs) of the mean at 95% confidence were estimated for each parameter using t-distributions generated for both surfaces using five repeat measurements acquired using each of the four instruments.
Direct topography comparison A recently developed method for point-by-point comparison of surface topographies  [14]  was applied in this work. Using the five aligned datasets acquired by each measurement system, mean surfaces were computed for each instrument. For the direct topography comparisons, data are not filtered using Gaussian filters as described in section 2. 4. 2, but instrument spatial frequency response bands are intrinsically matched as part of the alignment process (see references  [9, 14, 47] ). CIs for the mean surfaces were then estimated on a point-by-point basis using t-distributions at 95% confidence. Mean width of the CIs was calculated as a repeatability metric, and CIs were plotted on a point-by-point basis, to quantify the variation in repeatability across the surface.
Global discrepancy between instrument pairs was then computed, defined as the percentage of the surface area where CIs do not overlap. It should be noted that discrepancy may also exist in overlapping areas, as this is a statistical test and so is only capable of declaring discrepancy with a specific confidence. As such, CI overlap does not necessarily mean agreement, but rather than disagreement cannot be explicitly disproven. In addition to the use of CI width as an indication of local repeatability, local bias between the examined instruments was assessed by identifying the regions where the CIs of different instruments do not overlap. If the CSI measurement is taken as the metrological reference (i. e. unbiased measurement result), then discrepancy with respect to the CSI data becomes an indication of local bias.
Areal data In Figure  4  and Figure  5 , qualitative overviews of the aligned height maps are provided for both side and top surfaces, respectively. Height maps are presented in these figures in their unlevelled states (i. e. before application of the F-operator). Both types of surface appear to be similar in terms of the topographic formations present, with formations seemingly randomly distributed in both cases. Although side surfaces present a lay that is visible to the naked eye, no discernible lay is visible in either case when visualised in the figures below. Qualitative similarity also exists between instruments, with few obvious visible differences. Zoomed in regions of each dataset are presented in Figure  6 , to show how each instrument reconstructs example features on the surface.
Profile data In Figure  7 , qualitative overviews of example profiles are provided for both side and top surfaces. These profiles are not aligned with one another so should not be identical, but are representative of the set of profiles acquired using each instrument. Profiles have been levelled for this visualisation. As in the areal case, both types of surface appear to be similar in terms of the topographic formations present, with formations seemingly randomly distributed in both cases. Qualitative similarity also exists between instruments, with few obvious visible differences. The CI widths (i. e. repeatability) are similar between each instrument, with CSI consistently returning the smallest CIs. FV was the next-most repeatable, while CM was consistently the least repeatable instrument for texture parameters.
Profile data ISO 4287  [17]  Ra and Rq texture parameters with confidence intervals on the mean, computed at 95% confidence, are plotted for each surface in Figure  9. Statistical disagreement between optical and contact measurements is seen in the side surface case, and in the top surface case when compared to the FV and XCT results. In all cases, the mean parameter values returned by the contact stylus system are lower than those reported for the optical systems. Figure  9 : Filtered ISO 4287  [17]  parameters for side and top surfaces.
Conclusion Measurements of polymer LPBF surfaces have been performed with using contact stylus, CSI, FV, CM and XCT. In all cases, data was acquired with few missing data points and analysis results similar to those acquired using other measurement technologies. Statistical discrepancies between instruments were found between instruments in all cases, but ISO 4287 or 25178-2 parameters generally provided values in similar ballparks for each instrument examined. Examination of local features showed local discrepancies between instruments centred on areas of high slopes. This issue was the case for all optical instruments, including XCT, which acquires fully volumetric data. Discrepancies between instruments were often similar in size to the features on the surface. This study should be used as a tool to better understand how surface measurement instruments behave when measuring polymer surfaces, and as a demonstration of the technologies capable of measuring such surfaces.
These studies suggested SoproLife ® as a useful and superior method in monitoring caries lesions  [6, 8, 11, [13] [14] [15]. Nowadays, we still lack high-quality studies assessing the efficacy of SoproLife ® in monitoring remineralization and changes in the mineral content of caries lesions. The aim of this study is to evaluate the efficacy of SoproLife ® in detecting and quantifying in vitro remineralization using the ImageJ ® software.
Samples A power analysis was conducted using the G*Power Software, Version 3. 1. 9. 2 (Heinrich-Heine-Universität; Düsseldorf, Germany). Taking into account the repeated measures design of the trial, and accounting for an effect size of 0. 2 (small effect size), a 5% level of significance and an 80% power, the required sample size was around 60 teeth. Sixty human teeth (molar: n = 35; premolar: n = 25) extracted for orthodontic and periodontal reasons and having ICDAS II score of 0 to 3 were analysed. To avoid bacterial contamination, the teeth were rinsed with water and stored in a 0. 1% thymol solution at a pH of 7, for 1 hour, and then were rinsed with water and examined for mineral composition targeting their occlusal surface.
SoproLife ® imaging SoproLife ® images were taken on the occlusal surfaces of selected posterior teeth using the diagnostic aid mode with a visible blue light frequency (wavelength 450 nm) and saved in JPEG file format. Only 1 examiner traced all images for baseline and at T1 to allow standardization. The one-month period was chosen to detect any remineralization events. The SoproLife ® images were compared and analysed to quantify the remineralized areas using the open source software -ImageJ ® version 1. 52p (Fiji distribution; National Institute of Health, Bethesda, Meryland, USA). The mean and standard deviation of the grey value distribution from each group was computed. Then, a grey scale histogram displaying the distribution of the grey values in the image, i. e. the number of pixels detected for each grey value, was obtained.
Thus, SoproLife ® may support the patient-practitioner communication; and since it is free of ionizing radiation, it could be useful in the carious lesion detection in children and pregnant women  [35]. As SoproLife ® has shown potential to be used as a sensitive tool to the visual inspection and monitoring of the remineralization of early caries lesions, it would be useful to include algorithm software within the device to analyse the images. Currently, the storage and analysis of the images provided by SoproLife ® use a separate software -Sopro Imaging ® (SOPRO, ACTEON Group, La Ciotat, France) which is not part of the SoproLife ® system. Installing such software allows the clinicians to quantify caries lesions and monitor their remineralization at chair side based on the real-time images acquired, allowing for a greater motivation and initiation of behaviour modification by the patients.
Funding: This research was partly funded by the  China Scholarship Council (CSC) ; grant number  CSC201906880009. The  Agence Nationale de la Recherche  ( ANR agency ) is acknowledged for its financial support through the PhD grants of  Corentin Pigot  ( ANR-17-CE08-0010   DUALITY  project) and  Guillaume Noirbent  ( ANR-17-CE08-0054   VISICAT  project. The  Direction Générale de l'Armement (DGA)/Agence Innovation Defense (AID)  is acknowledged for its financial support through the PhD grant of  Damien Brunel.
Design and study population This is a cross-sectional sub-study using baseline data from the Finnish Health in Teens (Fin-HIT) cohort  [26]. Briefly, Fin-HIT is a representative study of the most populated areas of Finland, for which approximately 11, 400 adolescents and 9900 parents (one per adolescent, mostly mothers) were recruited between 2011 and 2014. The Fin-HIT study protocol was approved by the Ethics Committee of the Hospital District of Helsinki and Uusimaa (169/13/03/00/10), and all participants provided informed consent. Saliva samples from all adolescents were collected and a random subsample (n = 972) had the oral microbiota analysed, maintaining representativeness of the cohort population. Participants whose samples generated less than 2000 sequence reads (n = 83) were excluded.
Variables The type of feeding during the first six months of life was the main exposure of this analysis. At baseline, these data were retrospectively collected using a web questionnaire answered by parents. This variable was dichotomized as follows: (i) No infant formula and (ii) Infant formula (referring to those who received formula, combined or not with breastmilk). Other variables of interest were adolescent's gender (male/female) and age (years); and parent's gender (male/female), age (years), language (Finnish, Swedish/ others) and education level (high school or technical level/university degree). Adolescent's height (nearest 0. 1 cm) and weight (nearest 0. 01 kg) were measured by trained fieldworkers using portable stadiometers (Seca model 217) and portable digital scales (CAS model PB).
MiSeq SOP in the mothur pipeline (version V. 1. 35. 1) was used to process sequences  [28]. The SILVA 16S rRNA database (version V119) and taxonomy were used for alignment and classification of the high-quality sequence reads, which were clustered into operational taxonomic units (OTUs) at a cut-off value > 98% sequence similarity. Detailed procedures of saliva collection and microbial analysis were previously described  [29]. Alpha diversity (Shannon and Inverse Simpson Indices) was calculated per sample and beta diversity between the samples using Bray Curtis dissimilarity indices. Sequencing depths were categorized as (i) low ≤10,000; (ii) medium > 10,000 and ≤ 100,000; (iii) high > 100,000 sequences.
Statistical analysis Kolmogorov-Smirnov test was used to verify normal distribution of variables, which were described with means (standard deviation) or frequency (%). Student t-test and Chi-squared test were used to compare continuous and categorical variables according to feeding type groups. ANCOVA was used to compare alpha diversity between groups. Pearson correlation was employed to test correlations between alpha diversity indices and continuous variables, while Student t-test and ANOVA were used to compare these indices between categories of the other variables. These analyses were performed using Stata Statistical Software (release 12, 2011, StataCorp LP, College Station, TX, USA), and statistical significance was set at the level of 5 %. Permutational analysis of variance (PERMANOVA) was used to test difference in beta diversity between feeding type groups.
STUDY DESIGN To address the research purpose, the investigators designed and implemented a retrospective crosssectional study. The study population was composed of all patients admitted for a mandibular fracture to the Oral and Maxillofacial Department at Lille University Hospital, between November 2018 and April 2020. Patients were excluded as study subjects if they presented an associated Le Fort fracture. Patients without PPF or with a fracture concerning the posterior wall of the maxillary sinus were also excluded from this study. All procedures performed in the study were in accordance with the ethical standards of the Helsinki declaration. According to French law, no institutional review board evaluation was required because of the retrospective nature of the study. All data were anonymized, and Commission Nationale de l'Informatique et des Libert es de France declaration was provided.
Primary predictor variable was the PPF (present or absent). Secondary variables were considered: age, sex, mechanism of the trauma (fall, sport, assault, and traffic accident), side and type of mandibular fracture (symphysis, parasymphysis, corpus, angle, and condyle), side of PPF, volume in cm 3 of each lateral pterygoid muscle, maximum length in mm of each lateral pterygoid muscle, pattern of PPF (described in data collection section), and description of other associated facial fractures.
DATA COLLECTION Evaluation of mandibular fracture types and patterns of PPFs was jointly performed on CT images by 3 different operators. CT images were reconstructed using image processing software (Intellispace PACS; Philips, Foster City, CA), and bone threshold (250 HU) was used to segment these CT images. Mandibular fractures and PPFs were identified from axial, coronal, sagittal, and reconstructed 3-dimensional images (Fig  1 ). To obtain the reconstructed 3-dimensional images of the pterygoid process, the mandible, cervical spine, and rear of the skull, which can obstruct views of the pterygoid process, were removed when necessary. PPFs were then classified using the classification of An et al. 4  Fractures have been classified as follows (Fig 2 ): type I, pterygoid process vertical fracture (simple separation between the medial and lateral plates); type II, pterygoid process transverse fracture, which was further divided into 3 subcategories: II-1, fracture line located within the pterygoid fossa; II-2, fracture line located above the pterygoid fossa, not extending to the floor of the sphenoid sinus; and II-3, fracture line located above the pterygoid fossa and involving the floor of the sphenoid sinus.
DATA ANALYSIS Quantitative variables are expressed as means (standard deviation) in the case of normal distribution or medians (interquartile range, Q1; Q3) otherwise. Categorical variables are expressed as numbers (percentage). Normality of distributions was assessed using histograms and the Shapiro-Wilk test. Study population has been divided into 2 groups: fracture of pterygoid process or the absence of PPF. To evaluate the implication of lateral pterygoid muscle in the pathophysiology of PPF, we compared lateral pterygoid muscle volume, its maximal length, and width between both groups. Patients with bilateral mandibular fractures were excluded from this analysis. Bivariate comparisons in baseline characteristics between the 2 study groups (fracture of pterygoid process vs the absence of PPF) were made using Student t test for Gaussian continuous variables, Mann-Whitney U test for non-Gaussian continuous and ordinal categorical variables, as appropriate.
Data Collection The study population consisted of patients from the special care unit of the Dental University Hospital of Clermont-Ferrand treated under GA between November 2008 and July 2017. Local protocols impose a conservative full-mouth rehabilitation approach with as few extractions as possible. Indications included patients presenting with anxiety disorders and high levels of carious disease, medically compromised patients, patients with a disability (physical, cognitive, or mental), and patients presenting with a severe gag reflex. For all patients, a full record is kept of the dental status and diagnoses at the start of the intervention and of the treatment provided during that session. Patients were excluded if the treatment did not include at least 1 permanent molar treated by full pulpotomy and stainless steel crown placement.
The beginning of the follow-up period (T0) was defined as the date at which the pulpotomy was performed under GA. The immediate postoperative radiograph was collected. After GA, patients are routinely scheduled for a 1-month postoperative appointment. They are then free to come back to the hospital for regular annual checkups. Clinical and radiographic evaluations were undertaken at each checkup appointment. Regular checkups were undertaken in the dental surgery with or without conscious sedation or under subsequent GA depending on the level of patient cooperation. No systematic recall of patients was performed, except for the 1-month postoperative appointment. For each patient, the radiologic and clinical data recorded at the longest follow-up period (T1) were retained to assess pulpotomy outcome.
Outcome Evaluation Criteria Outcome evaluation included a combination of clinical and radiographic examination (Table  1 )  21. Radiographically, the evolution of the PAI  20  was assessed between T0 (postoperative radiograph taken immediately after treatment) and T1 (radiograph taken during the latest checkup appointment). For a tooth with multiple root canals, the root with the highest PAI was taken into account. For immature teeth, further physiological root growth was verified between T0 and T1. Clinical assessment was undertaken by the patient's usual practitioner at a regular checkup appointment. Data regarding the presence of pain, a sinus tract, or swelling were recorded in the patient's medical file. Because of the ethical frame of this observational study, it was not possible to blind the assessors to the collection of clinical data.
Statistical Analysis Descriptive analysis was performed using Excel (Microsoft, Redmond, WA), and the statistics were undertaken using SPSS Statistics Version 25 (IBM Corp, Armonk, NY). Student t tests were used to compare the whole group with the follow-up group with respect to age, average duration of the intervention under GA, and average number of teeth treated under GA. Pearson chi-square tests were used to compare the whole group with the follow-up group regarding sex, patient The condition for ineffective pulpotomy with PAI (T0) 3 and PAI (T1). 3 could be checked only for teeth with PAI (T0) 5 3 because teeth with PAI (T0). 3 were not included in the cohort. typology, and data on the type of treated teeth and also to analyze the impact of etiology, tooth maturity, and endodontic difficulty criteria on pulpotomy outcomes.
Selection of patients and composition of groups We prospectively gathered the data of patients who were registered in the initial examination with oral and/or ocular dryness, evaluated by the same physician in an internal medicine department between January 2015 and June 2018. The initial reason for consultation could be directly dryness symptoms or diverse extraglandular symptoms leading to pSS suspicion. We used a standardized method to collect the following elements: subjective xerophthalmia and xerostomia, UWS flow rate, Schirmer's test, MSGB, and anti-SSA and anti-SSB antibody testing. An ocular staining score (OSS) was given for patients presenting anti-SSA antibodies or a focus score of ≥ 1 in the MSGB (3 points according to the ACR/EULAR 2016 criteria) but negative results in Schirmer's test or in the UWS flow rate.
Statistical analysis The quantitative data are presented in medians and quartiles, compared using an ANOVA or the Kruskal-Wallis test according to distribution normality, which was evaluated using the d'Agostino-Pearson test. The qualitative data were presented as absolute values and as percentages and were compared using a chi-squared test. Diagnostic performances were evaluated by ROC curves with the calculation of the area under the curve (AUC) for continuous variables and by the sensitivity (Se), specificity (Sp), positive predictive values (PPV), and negative predictive values (NPV) for qualitative variables. To determine the UWS flow thresholds of interest among all the values by an interval of 0. 1 mL/15 min, we used ROC curves and Youden's index, defined by Se+Sp-1 (included between -1 in cases of zero sensitivity and specificity and 1 in cases of 100% sensitivity and specificity), in order to appreciate the best pairing of sensitivity/specificity.
1 mL/min to confirm pSS diagnosis. Secondly, to test the new thresholds that we suggested, we adapted the score from the ACR/EULAR 2016 classification criteria (adapted score from ACR/EULAR 2016 criteria) by modifying the level of the UWS flow rate cutoff to give 1 point: a patient presenting a UWS flow lower than or equal to the tested threshold obtained 1 point on the adapted ACR/EULAR 2016 criteria score. The alpha risk was 5%. The indices were presented with a confidence interval of 95%. The analyses were carried out using the GraphPad Prism v6. 01 software (GraphPad Software, Inc. , La Jolla, CA 92037, USA).
They were recruited by the NC health agency within public regional health services and through the council of private dentists. The practitioners were assigned to one or several schools, depending on feasibility criteria that were mostly dependent on geographical locations. Children from the same school were examined by the same practitioner. Prior to the start of the program, all the practitioners underwent a training course consisting of a presentation of the NC OHP program, the sealant application protocol, illustrations with clinical situations and training about the data collection process.
Data analysis Data errors were corrected before analysis. The statistical analyses were performed using the Stata statistical software package, version 13. Retention rates were expressed with 95% confidence intervals (CI). The influence of initial dental status, conditions of sealant placement and the child's profile (gender, school, region) was explored using bivariate analysis. Variations in the distribution of the study variables (retention rates, initial and 2017 dental status, condition of sealant placement, sociodemographic profile, caries increment) depending on the region (an ecological variable representing a major social determinant in NC) were also explored using bivariate analysis. Chi-squared, ANOVA or Student t-tests were used depending on the variables being considered. For the main variables, when p-value was significant, a Tukey-Kramer post-hoc test was performed to take into account multiple comparisons.
Flow Diagram Alba Science clinical research associate pre-screened 98 subjects assessed for eligibility. Three participants were not fulfilling inclusion criteria, and 14 were included but did not wish to complete the study before the beginning of the study. Fifteen participants failed screening (exclusion criteria) and were withdrawn by Alba Science dental surgeon in charge to collect clinical data and microbial samples. Sixty-six participants completed the study (Figure  1 ). They brushed their teeth twice a day for a 4-week period. No adverse events related to the product tested were reported. 63. 6% (21/33) vs. 24. 2% (8/33); p = 0. 002), but values became similar at D14 and D28. Subjects were not carrying all the bacterial and/or fungal species at baseline. The number of subjects carrying a given microbial species at baseline was as follows: Aggregatibacter actinomycetemcomitans 9.