dataesr/scientific-paragraphs-categorization huggingface dataset:
Adult patients were stratified by the DLCN criteria prior to genetic testing as recommended by the guidelines of the Consensus Statement of the European Atherosclerosis Society (EAS). 8 The highest known LDL-C level was used for scoring. A diagnosis of FH was considered "possible" (3-5 points), "probable" (6-8 points), or "definitive" ( > 8 points). Patients who could not be scored due to missing data were excluded. The pediatric population consisted of children or adolescents < 20 years of age in whom FH was suspected on the basis an elevated LDL-C level ( > 4 mmol/L [155 mg/dL]) and a family history of hypercholesterolemia and/or premature coronary artery disease (CAD).
Collection of data Clinical and biological data were collected from medical records, as were the DLCN scores calculated by clinicians. Demographics (age and sex), family or personal histories of hypercholesterolemia and cardiovascular events, evidence for the presence of lipid deposits (tendon xanthomas, xanthelasmas, and corneal arci), lipid profiles, any lipid-lowering therapy at the time of genetic analysis, and genetic test results were recorded. The maximum LDL-C was the highest recorded LDL-C level. Blood samples for lipid profiling were obtained after a 12 h fast. Serum levels of total cholesterol (TC), triglycerides (TG), and HDL cholesterol (HDL-C) were quantified enzymatically on an autoanalyzer (AU5800, Beckman). LDL-C levels were obtained using either the Friedewald equation 10 (when TG < 3.
Genetic analysis All EDTA-containing blood samples were sent to the laboratory of Saint-Antoine Hospital (Paris, France). Genomic DNA was extracted from peripheral leukocytes using a QI-Asymphony DSP DNA Midi Kit (Qiagen, Hilden, Germany). Sanger sequencing included the promoter region, all 18 exons, the flanking intronic sequences of LDLR , and exon 26 of APOB. Of patients with no identified variant in LDLR or APOB , 59 underwent multiplex ligation-dependent probe amplification (Salsa MLPA Kit P062, MRC-Holland, Amsterdam, the Netherlands) to search for large LDLR rearrangements and 49 underwent PCSK9 sequencing. Sequencing was performed using a 3500xL Dx Genetic Analyzer (Applied Biosystems, Thermo Fisher Scientific, USA) and the chromatograms were analyzed using SeqScape software (Applied Biosystems, Thermo Fisher Scientific).
All identified variants were sought in the Leiden Open Variation Database (LOVD v. 3. 0, www. lovd. nl/) and ClinVar (www. ncbi. nlm. nih. gov/clinvar/). Functional prediction was performed using Sorting Intolerant From Tolerant software (SIFT 4. 0. 3, sift. bii. a-star. edu. sg/)  12  , Polymorphism Phenotyping software (Polyphen2, genetics. bwh. harvard. edu/pph2/),  13 utation Taster (www. mutationtaster. org/)  14 and Combined Annotation Dependent Depletion (CADD, cadd. gs. washington. edu/)  15 o evaluate missense variants. Human Splicing Finder (HSF, www. umd. be/HSF3/)  16 was employed to predict the effects of splice variants. All variants were evaluated in terms of pathogenicity following the recommendations of the American College of Medical Genetics (ACMG). 17 Only pathogenic variants, likely pathogenic variants, and variants of uncertain significance (VUS) are reported here.
Statistical analyses Categorical variables are presented as numbers (n) with percentages (%). Differences between groups were compared using the Pearson chi-square test (or the Fisher exact test when values < 5 were expected). The distributions of continuous data were tested employing the Shapiro-Wilk test. Normally distributed continuous variables are reported as means with standard deviations (SDs) and differences among groups were analyzed via one-way ANOVA. Nonnormally distributed parameters were compared using the Kruskal-Wallis test and are described as medians with interquartile ranges (IQRs). The significance level (alpha) was set to 0. 05. All statistical analyses were performed using Rcmdr ver. 2. 7-1. The Proc package was used to draw receiver operating characteristic (ROC) curves and the DeLong test was employed to compare areas under the ROC curves (AUROCs).
Populations A total of 166 subjects genetically tested in terms of monogenic FH were eligible (according to their DLCN scores); 19 were excluded because of missing data. The final study population thus consisted of 147 individuals including 26 children. Acquired causes of hypercholesterolemia were investigated. One instance of uncontrolled hypothyroidism, one of cholestasis, and 12 cases taking medications that could impact the LDL-C level were noted among the adults. Table  1  lists the characteristics of the adult population (n = 121, age 20 to 77 years, 38. 8% males). Family histories of hypercholesterolemia and/or premature CAD were found in only 82. 1% of cases (no data for four patients). As expected, the lipid profiles obtained at the time of genetic testing revealed increases in serum concentrations of LDL-C and premature CHD in 24% of patients, but the groups did not differ significantly in terms of the DLCN score (p = 0.
Analyses statistiques Le critère de jugement principal a été calculé en établissant le rapport entre le nombre de patients en SP ayant bénéficié de PAPs et le nombre de patients suivis en SP dans les 12 mois écoulés. Les statistiques descriptives ont été réalisées avec le logiciel lime survey. Les comparaisons statistiques ont été réalisées à partir du logiciel biostaTGV, avec l'aide des personnes-ressources du département de médecine générale. Les données quantitatives ont été comparées à l'aide de test de Student, ou d'un test non paramétrique de Mann-Whitney-Wilcoxon en cas d'effectif < 30 patients. Les données qualitatives ont été comparées à l'aide de test du Chi 2 , ou de test exact de Fisher en cas d'effectif < 5 patients.
7 Circulating KIR3DL2+ SC ≥ 200 mm À3 was used to define KIR3DL2-positive status. 8 For each patient, all skin biopsy samples performed were included. LCT was histologically defined by the presence in the lymphocytes' infiltrate of > 25% or aggregates/nodules of large cells (more than four times the diameter of a small lymphocyte). 3, 4 Haematoxylin-, eosin-and safran-stained slides were then digitized and an analysis using HALO software was performed. All blood samples from patients with flow cytometry data between 2015 and 2020 were included for FSC/SSC analysis. This study received the Institutional Review Committee agreement (LYM-PHOTEQ reference: CPP 2019-AO1158-49). In total, 117 patients were included with a median followup of 41 months (interquartile range 1-81). Overall, 6% (six of 100) and 16% (18 of 112) of patients were diagnosed with LCT on skin biopsy samples at diagnosis and during follow-up, respectively.
Il est à noter que l'ordinateur peut aussi bien avoir un système d'exploitation Linux que Windows. Mais surtout la plate-forme SDR elle-même est formée de matériel et de logiciel support de bas niveau, qui dans certains contextes (au-delà de la perspective décrite ici) peut être un objet de formation. Il y a maintenant une multitude de plates-formes SDR d'émission-réception, de plus en plus petites et de plus en plus abordables financièrement, pour les chercheurs et finalement pour l'enseignement. Pour faire un rapide point de la situation actuelle, citons un exemple à chaque échelle de prix dans le TABLEAU I. La Fig. 1  montre une vue des cartes TNT RTL-SDR, HackRF One et USRP N210. On peut bien sûr trouver des plates-formes plus chères, ayant des caractéristiques plus élargies, comme des antennes 4x4 (4 antennes d'émission et 4 antennes de réception) pour faire du MIMO, accompagnées de FPGA pour fournir la puissance de calcul adéquat comme pour l'USRP N310 qui vaut alors 10 k€.
On peut aussi expliquer par la pratique ce qu'est la radio logicielle et c'est ce qui est illustré ici. Dans ce cas, un objectif important du TP est à la fois de faire manipuler plusieurs environnements logiciels sur une même plate-forme et d'utiliser plusieurs plates-formes avec un même environnement logiciel. Ainsi nous utilisons un exemple de chacune des deux catégories d'environnements logiciels évoqués précédemment, à savoir SDR# (qui repose sur une interface déjà faite) et GNU Radio Companion (qui permet la conception de la chaîne de traitements radio que l'on souhaite sous forme de schéma bloc) qui ont l'avantage d'être tous les deux gratuits et que les étudiants peuvent installer sur leur propre ordinateur (Linux ou Windows). Nous utilisons ces deux environnements logiciels sur 3 plates-formes, en allant par ordre de performance : -la plus simple : clef TNT RTL-SDR qui ne fait que réception, -HackRF qui peut émettre ou recevoir (en half duplex) -USRP N210 qui peut émettre ou recevoir en FDD (full duplex) Les applications radio développées en TP Pour concevoir des systèmes d'émission-réception, on utilise l'environnement GNU Radio Companion (GRC) sous Windows qui a l'avantage d'être installé très rapidement.
Mann-Whitney tests were used to compare nonparametric biological values between patients in crisis and patients in steady-state (control cohort). In contrast, the Wilcoxon test was used to compare patients in crisis at different time points. Statistical analyses were performed using SPSS (IBM Statistics) and GraphPad Prism software. All P values were two-sided and statistical significance was defined as P < 0. 05. The baseline characteristics of the group in crisis and the control group are detailed in Table  1. Half of the patients with VOCpresented with fever (>38°C). Patients in crisis demonstrated significantly higher CRP levels (P < 0. 0001), higher leukocytosis with higher neutrophil counts, and higher monocyte counts (P< 0. 0001, P = 0. 0001, and P = 0. 0048, respectively) than patients from the control cohort.
DATA PROCESSING The distribution of intensity Training duration was determined using the coaches' planned training schedule. Heart rate data was only considered when the player wore the heart rate monitor at least 75% of the time for each week. This data was recorded using Polar Team System software® (Polar Electro, Kempele, Finland) which calculates the percentage of time spent in each of the predefined HR zones. This data was then used to determine the intensity of each training week in three intensity zones (Zone 1 ≤ SV1; Zone 2 > SV1 and < SV2; Zone 3 ≥ SV2). The two ventilatory thresholds, for tennis training, were established on the basis of the results of the TEST procedure  (Brechbuhl et al. , 2016a (Brechbuhl et al. , , 2016b)). Based on the results of a study of 14-15 year old triathletes with a comparable training volume  (Birat et al.
DATA ANALYSIS All data were expressed as mean ± standard deviation and were analysed using RStudio (RStudio v1. 3. 1093, US). The normality of the data distribution was checked by the Shapiro-Wilk test. The distribution of training intensity was compared for each assessment method (programmed (trainer) vs. measured (HR) vs. estimated (RPE)) and for each intensity zone (Zone 1 vs. Zone 2 vs. Zone 3) using a twofactor ANOVA (assessment method and intensity zone). If a significant difference was found, a pairwise comparison (Bonferroni method) was used as a post-hoc test. The significance level was set at p <0. 05 for all analyses.
RESULTS On average, each week, the scheduled intensity is distributed as follows: more than 9 h of training in Zone 1, about 3 h in Zone 2 and 1 h in Zone 3 (Figure  2A ). The heart rate data show that the players spent on average just under 12 h in Zone 1, just over 2 h in Zone 2 and 30 min in Zone 3 each week (Figure  2B ). Regarding the distribution of intensities achieved according to the RPE, the players perceived their effort, on average per week, more than 4 h in Zone 1, about 5 h in Zone 2 and 3 h in Zone 3 (Figure  2C ). As the training programme was planned for each player according to tournaments (singles and doubles matches), fitness and injuries, we chose to represent the training load of two players, representative of the inter-individual variability. In total, 18 matches were played with an average win rate of 61.
Participants The data consist of oral productions by 18 Mexican Spanish learners of both L2 English and L3 Russian (experimental group), six American English speakers, five Russian speakers and six Mexican Spanish speakers (control groups). The learners (10 males and eight females) were attending L2 English and L3 Russian (henceforth L2Eng and L3Rus respectively) courses at the National Autonomous University of Mexico (UNAM) at the time of the experiment. All the learners were born in monolingual Spanish-speaking households. All of them were pursuing Bachelor's/ Master's degree studies in different domains (Mathematics, Administration, Philology, etc. ). Their ages ranged from 21 to 39 years (mean = 26. 11, SD = 4. 84). As we pointed out in section 2. 3, Spanish-speaking students experience great difficulty in acquiring vowel reduction in L2Eng.
Data collection and acoustic analyses Participants were recorded in a quiet room at the UNAM using the integrated microphone of a MacBookPro 15-inch (MacBook 8,2, late 2001). Several test audio files had been produced beforehand in order to ascertain appropriate quality of the recordings. The participants listened to the stimuli through headband headphones Sony XB950 (F102 dB/mW sensitivity, 24 Ω impedance, 3,000 Hz to 28,000 Hz frequency response) connected to the computer with a cord. All the audio files were saved as. wav files (Mono, 44100Hz, 16-bits) and acoustically examined by a phonetician (the second author) in order to guarantee the required acoustic quality for formant detection. All the data were manually transcribed and segmented by the first author in Praat  (Boersma and Weenink 2001).
Statistical analysis The statistical analyses were carried out in R (version 3. 6. 0, R Core Team 2018) with different linear mixed-effects models via the lme4 package  (Bates et al. 2015). We built separate models for each of the two dependent variables (ED and DURATION) and for each group (L1Spa, L1Eng, L1Rus, L2Eng and L3Rus) resulting in 10 different models in total. The fixed effects in all these models were PROSODIC CONDITION (stressed vs. unstressed), TASK (word repetition vs. sentence completion) and VOWEL (letters a vs. e/э vs. o). All the interactions among fixed effects were also estimated. Please note that it was decided to build different models for each group since our expectations for the groups differed, as detailed in Section 2. 4. The random effects considered were PARTICIPANT (accounting for inter-participant variability) and WORD (accounting for potential lexical effects on ED and DURATIONS).
The structure of the random effects was that of maximal specification  (Barr et al. 2013) , including random intercepts for all random effects, and by-speaker random slopes for PROSODIC CONDITION, TASK and VOWEL. All the variables were coded with sum-to-zero contrasts 3  in order to obtain meaningful values  (Schielzeth 2010)  and the statistical significance of our predictors was determined by calculating p-values via Satterthwaite's approximation for the estimation of the degrees of freedom with the aid of the lmerTest package  (Kuznetsova et al. 2017 ). 4 Finally, post-hoc comparisons were performed using the package emmeans (version 1. 3. 0) with false discovery rate (fdr) correction for multiple comparisons.
A somewhat similar pattern was also revealed in the L3Rus. Our data show that Mexican learners are capable of producing L3Rus schwas with similar native spectral values when they were associated with the letters a and o in words like победа and ребё ́нок, but not in the letter э in words like экипаж. Russian speakers produced clear centralisations in the schwas represented by the letter a, but not in those represented by the letters э and o, in which differences did not reach statistical significance. Unexpectedly, these findings appear to be in contradiction with the description of vowel reduction in Russian provided by  Avanesov (1956) ,  Knyazev and Pozharitskaya (2005)  and  Iosad (2012). We argue that that this may be due to inherent acoustic properties of the schwa in Russian. According to our metrics, unstressed Russian vowels may result in a different kind of centralised vowel [ə] from English.
Russian schwas are further away from the acoustic centre of the participants' vowel space with respect to their stressed counterparts, suggesting that this vowel is more anterior than the typical [ə]. However, a higher number of Russian speakers and more controlled data may be needed to corroborate this hypothesis. Another interesting observation in terms of the L2Eng and L3Rus data is that learners experienced considerable difficulty in producing the schwa represented by the letter e. A possible explanation of these findings could be the phonetic and perceptual proximity of /e/ and /ə/ in L2Eng and L3Rus in the minds of Mexican learners, which may make both phonemes assimilate into a unique category /e/ in their interlanguage (see the SLM by  Flege 1995 Flege , 2005)) , whereas this is not the case for the rest of the phonemes.
4  The lmer package does not provide p-values. In order to obtain them, we first performed Likelihood ratio tests of full and reduced models via ANOVA () performance. However, given the complexity of our models, we ran into convergence issues for reduced models. We thus used Satterwaite's method to obtain p-values for the predictors. 99 BARKOV, SANTIAGO AND PERALTA https://doi. org/10. 1017/cnj. 2022. 6 Published online by Cambridge University Press.
These developments about multimodality have important implications for Higher Education as regards L2 learning/training. In fact, instructional designers need to be aware of L2 meaning making as the result of a whole process engaging all the modes present in the learning environments. Knowledge of meaning making possibilities of each mode separately and in combination is essential, since learners make choices based on the ensemble. As argued by  Royce (2002) , L2 teachers should develop students' multimodal communicative competence. This call has become urgent today in the web 2. 0. era  (Early et al. , 2015). This means that teachers should have themselves developed such competence-or at least gained awareness of the multimodal nature of communication. To comply with these requirements, the language department in Le Conservatoire National des Arts et Métiers (Cnam 1  ) in Paris, has carried out research to explore L2 English learners and teachers' awareness of multimodality in a digital (Moodle) learning environment specifically developed by Cnam teachers and offering learners professionally-oriented tasks to be carried out individually.
In short, The Rebranding of Newcastle as a Smart City. Cui Bono? Angles, 15 | 2022 it collects and uses data to provide "smart" infrastructure connecting the supplies and demands of people, organisations and objects in supposedly new, more efficient ways. Indeed the argument is that smart technology will improve the lives of the 45 million people living in the UK's towns and cities, making urban areas at once more efficient, more sustainable and safer, since smart cities will be able to monitor air quality to reduce pollution, use real time traffic data to ease congestion and tackle crime using analytic software (Los Angeles Police Department has been using social media monitoring tools provided by tech start up Voyager Labs to predict criminal behaviour, Los Angeles Times 3 July 2019). The 2013 European Parliament report "Mapping Smart Cities in the EU" develops the concept of smart city along six dimensions: smart economy; smart mobility; smart environment; smart people; smart living; and smart governance  (European Parliament 2013).
These online services are said to have reduced calls to the Council from about 60 per month to three and saved the equivalent of about £25,000 per year in staff time (Newcastle City Council 25 May 2018). But the smart cities agenda presupposes both the availability of the new technologies in all areas of the city and the readiness of residents to use them. As one resident asked: "who accesses the App to find parking?". 29 This in turn raises the issue of the use of the data collected. Indeed, one of the foundations of the smart city approach is that it gives access to real-time information at the level of individual citizens' choices and actions. The development of information systems in urban environments has created opportunities to capture information which was not previously accessible.
The government's argument is that "[leading cities] are examining how to generate more powerful insights and value by using potentially more sensitive datasets (including data on vulnerable groups) in order to improve their understanding of citizens' needs and to provide better services, while respecting data privacy and security" (Department for Business, Innovation and Skills 2013: 37). This can be very useful in enabling the detection of patterns of behaviour, as demonstrated by innovations to tackle the impact of the Covid-19 pandemic, for example with the creation of www. howbusyistoon. com, a web-based application developed by Newcastle University's Urban Observatory in partnership with the National Innovation Centre for Data (NICD), which used real-time data to check how easy it was for residents to maintain social distancing in the city centre.
" Some US cities, such as San Francisco in 2019, Boston in 2020, or Minneapolis in 2021, have banned facial recognition software over concerns that local authorities were stealthily collecting data on citizens through video surveillance (New York Times 14 May 2014) 13 , while in the UK the Surveillance camera code of practice is currently under review "to enable operators of surveillance camera systems to make legitimate use of available technology in a way that the public would rightly expect and to a standard that maintains public trust and confidence" (UK Government 2021). The Urban Observatory recognises this risk and The Rebranding of Newcastle as a Smart City. Cui Bono? Angles, 15 | 2022 promises that "data authority and governance will be an important point of discussion in future Smart City development".
U A Une implémentation sur Android a été réalisée afin de mettre à l'épreuve la faisabilité du modèle. Le choix de la plateforme Android n'est pas anodin. En effet en 2019, Google a annoncé avoir atteint les 2,5 milliards de terminaux Android actifs. Ce qui en fait le système d'exploitation le plus répandu. De plus, le système est conçu pour les objets connectés tels que les smartphones, tablettes tactiles, ordinateurs, télévisions (Android TV), voitures (Android Auto), Chromebook et autres montres connectées (Wear OS). Ce panel de produits illustre parfaitement les types d'appareils les plus à même d'être porteur de capteurs et d'effecteurs dont les usages ne sont pas mutualisés. Afin de mettre en place ce modèle générique, nous avons basé la phase d'implémentation sur la plateforme « Software Kit for Ubiquitous Agent Development » (SKUAD) qui permet de créer des agents ambiants capables de manipuler des capteurs et des effecteurs  [10]  dont les performances et la conception permettent un usage embarqué.
Un site (https://c2dh. github. io/popkult60/fr/), un blog (https:// c2dh. github. io/popkult60/de/blog/), des podcasts (https://c2dh. github. io/popkult60/ fr/podcast) et bientôt une exposition virtuelle sont également accessibles en ligne. Du point de vue de la recherche, deux axes sont à souligner : le choix revendiqué de faire des cultures populaires un objet d'étude privilégié, et l'accent mis sur les circulations transnationales. Faire de la culture populaire (Populärkultur) le fil directeur du projet apparaît déjà révélateur, dans un espace géographique longtemps marqué par l'influence de l'École de Francfort, dénonciatrice des industries culturelles et de la pop culture, mais qui connaît, depuis les années 1990 et 2000, un profond renouvellement historiographique, notamment sur les musiques populaires  5.