dataesr/scientific-paragraphs-categorization huggingface dataset:
data analysis In a first step, descriptive statistics will be realised by calculating mean and SD for quantitative variables, and proportion for qualitative variables to determine the main characteristics of the three clinical groups. Focusing on cerebral malaria and UM children the MS/ MS data will be searched against the databases (UNIPROT and PlasmoDB,  40  the proteins will be considered as positive hits with at least two peptides. The MaxQuant software will be used to compare malaria protein expression between isolates of these two clinical groups. Transcriptomical data will be analysed with Galaxy (https:// usegalaxy. org/) and R software (https://www. r-project. org/). 41 The raw data will be trimmed with Trimmomatic tool for Phred Quality Score Qscore >20, read length >30 bases and ribosome sequences will be removed with tool sortMeRNA.
Reads will be mapped against the P. falciparum 3D7 reference genome combined with var transcript sequences from 7 P. falciparum genomes. Differential expression analysis on RNAseq data will be performed using the DESeq2 42 package considering a one log-fold increase as significant using adjusted p value <0. 05. Data normalisation will be realised with DESeq2 software, with hypothesis that there exists genes overexpressed and underexpressed and that majority of genes are not expressed in a differential way. Transcript expression levels (evaluated with RT-qPCR) will be compared by t-tests and analysis of variance of transformed outcomes. Regarding immune response analysis, potential markers related to inflammation and neurological symptoms will be compared using variance analysis in samples from children from the three groups, CM, UM and non-malarial non-traumatic group.
Recruitment Twelve parent-toddler groups; 11 community centres and migrant support groups; and four general practitioner (GP) practices were selected as individual participant recruitment sites as -according to 2012-2014 Hackney GP practice data provided by The Blizard Institute, Barts and The London School of Medicine and Dentistry (J Robson 2015, personal communication, 13 June) -they had median maternal vaccination uptake rates and a diverse patient population. These recruitment sites were also spread across the borough, were free to attend, and attracted women from a wide range of backgrounds. It was envisaged that the above factors would make the results more generalisable). The four heads of midwifery/immunisation in Hackney were also included. An official invitation letter explaining the study was sent by email to all potential recruitment sites.
Data management and analysis A thematic analysis was conducted to identify, analyse, and report patterns (themes) from the data  [22]. Thematic analysis was used as a 'contextualist' method, acknowledging the ways that individuals perceive and make meaning of their experiences, and, in turn, the ways the broader social context impinges on these meanings  [23]. All interview transcripts were imported into NVivo11; a qualitative data analysis software. RW initially read the transcripts several times to become familiar with the content. They were then organised and coded into manageable text segments with the use of a coding framework and cross-checked by PP and HL. As the study began with some key questions regarding trust in vaccination and health authorities, the coding framework was formulated both deductively (through pre-established concepts guiding the research questions), and inductively (on the basis of salient and recurrent themes identified in the data).
Patients Following institutional review board approval, a consecutive series of AIS patients, operated for progressive Lenke 1 or 2 curves between September 2014 and September 2015, were retrospectively analyzed. The apex and both end vertebrae (upper and lower) of the main thoracic curve were determined by an independent senior spine surgeon. Demographic and surgical data was collected. A minimum 2-year follow-up was required. All patients were evaluated preoperatively, in the early postoperative period (within 1 month), and at latest follow-up. None of the patients had prior spinal surgery.
Statistical analysis Statistical analysis was performed using SPSS version 12. 0 (SPSS Inc, Chicago, IL, USA). Continuous variables were expressed as means and standard deviations. Paired-samples Student's t-tests were used to compare preoperative and postoperative radiological parameters. Pearson test was used to analyze the correlation between the gain in thoracic kyphosis and the axial correction of the apical vertebra (AVR). All statistical tests were 2tailed, and a p-value <0. 05 was considered to be significant.
Limitations This series is retrospective but all data were collected prospectively. AVR correction was only assessed on 3D reconstructions, and rib hump clinical measurement should be added in future studies to compare radiological outcomes and patient's satisfaction. More follow-up remains necessary to evaluate the long-term stability of these hybrid constructs, and evaluate more accurately the pseudarthrosis rate. Last, this study was only radiological and the financial cost of such constructs should be considered, with sublaminar band prices ranging on average from 600 dollars in Europe to 1450 dollars in North America. While many surgeons currently advocate the use of thoracic pedicle screws for optimal care in AIS, sometimes associated with multiple Ponte osteotomies, sublaminar bands should be considered, especially in hypokyphotic patients, in order to reduce complication rates and in particular the risk of intraoperative concave screw failure due to pull-out forces  [42, 43].
We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilise the 2-min cadence TESS data for a sample of 117 stars to classify their behaviour regarding variability and place them in the Hertzsprung-Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74% for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system.
2014 (Ricker et al. , 2015)) , which are in the southern ecliptic hemisphere, provide new insight into pulsation and rotation in intermediate-mass stars (e. g. ,  Cunha et al. 2019; Sikora et al. 2019). The primary mission of TESS follows the groundwork of the Kepler mission, and aims to detect planetary transits in the brightest stars across the sky. TESS data cover almost the entire sky (|b| > 6 deg) at a cadence of 30 min and are publicly available to the community in the form of full frame images. However, a sub-sample of stars were selected to be observed at a 2-min cadence in each TESS observing sector and light curves of these stars are being delivered to the community a few months after observations have been obtained. Therefore, TESS provides a unique homogenous data set to test and constrain much of the currently unknown physics inside main-sequence A and F stars.
(2011)  and  Balona et al. (2012). The TESS sample of HADS and SX Phe stars in Sectors 1 and 2 includes at least 19 stars proposed for 2-min cadence observations based on a review of the ASAS-3  (Pojmański 1997 (Pojmański , 2002) )  database  (Pigulski & Kotysz, in preparation). The sample includes several known HADS, e. g. , ZZ Mic, RS Gru, BS Aqr and SX Phe itself (see  Sect. 6. 3 ). An example of a known HADS star observed by TESS, HD 224852 (TIC 355687188 ), is presented in detail in Sect. 6. 6.
FREQUENCY ANALYSES OF TESS DATA The TESS data analysed in this work are the 2-min 'Simple Aperture Photometry' (SAP) light curves provided by the TESS Science Team, which are publicly available from the Mikulski Archive for Space Telescopes (MAST) 3. As part of the framework of the asteroseismic working group on pulsating stars of spectral type A and F within the TESS Asteroseismic Science Consortium (TASC) 4  , 117 known pulsating stars were allocated observing slots at a 2-min cadence by the TESS Mission in Sectors 1 and 2 of its 1-yr observing campaign in the southern ecliptic hemisphere. There were more δ Sct stars observed in the first two sectors, but for this study we decided to concentrate on those that were allocated to the TASC working group on A and F stars (TASC WG 4). Because g modes have long periods, we did not specifically include known γ Dor stars in our 2-min target list, since these stars will be observed with a cadence of 30 min, which is sufficient to determine their frequencies.
We discuss one star that was not observed during Sectors 1 and 2 later on. This target is the eponymous star γ Doradus and is described in Section 6. 7. We analysed the TESS light curves of our sample in different independent groups, using various frequency extraction software routines. Commonly used programs to perform frequency analysis of light curves are PERIOD04  (Lenz & Breger 2004 ) and SigSpec  (Reegen 2007) , while the KU Leuven and Aarhus University ECHO (Extraction of CoHerent Oscillations) pipelines were used also. We discuss these pipelines in Sections 3. 1 and 3. 2, and conclude that they yield compatible results for peaks in the amplitude spectrum with signal-to-noise (S/N) 4. A comparison of the significant frequencies identified in two stars by the Leuven and Aarhus pipelines is shown in Fig.
ECHO The ECHO program (Extraction of CoHerent Oscillations) was developed at Aarhus University. It extracts coherent signals from photometric light curves using an optimized, iterative pre-whitening technique. Coherent signals are iteratively identified using a Lomb-Scargle periodogram that is calculated using the  Press & Rybicki (1989)  algorithm, which allows a fast computation for unevenly sampled data. The frequency, amplitude and phase of an oscillation is computed using the algorithm described by  Frandsen et al. (1995). The statistical uncertainties on the amplitudes, frequencies and phases are calculated according to  Montgomery & O'Donoghue (1999). The statistical significances of the extracted signals are estimated from the periodogram using Scargle's significance criteron  (Scargle 1982).
New spectroscopic determinations of T eff based on archival data Spectroscopic data were taken from the ESO archive 6. We used medium and high signal-to-noise ratio ( 65) spectra from FEROS (Fiber-fed Extended Range Optical Spectrograph; R∼48000), HARPS (High Accuracy Radial velocity Planet Searcher, R∼115000), and UVES (Ultraviolet and Visual Echelle Spectrograph, R∼65000). Observational details are given in Table  3. We applied two methods to derive spectroscopic parameters for the 14 stars that had available archival data. For the first method we used, the hydrostatic, plane-parallel lineblanketed, local thermodynamic equilibrium ATLAS9 model atmospheres  (Kurucz 1993). The synthetic spectra were generated by using the SYNTHE code  (Kurucz & Avrett 1981). The projected rotational velocities, v sin i, were calculated by fitting the profiles of non-blended metal lines  (Gray 2008).
The Hβ lines were used to derive T eff by considering the minimum difference between the synthetic and observed spectra. In this analysis, a solar metallicity and the obtained v sin i values were fixed. In addition, we assumed log g = 4. 0 (dex). This was done because the hydrogen lines are not sensitive to log g for stars with T eff 8000 K  (Heiter et al. 2002). Our results are listed in Table  4 , with 1σ uncertainties. In addition, the Grid Search in Stellar Parameters (GSSP;  Tkachenko (2015) ) software package was used as an alternative method for determining the atmospheric parameters of our stars. GSSP is a multi-purpose spectrum analysis tool that is designed for precision spectrum analysis of single and binary stars. As the name suggests, the method is based on a grid-search in 6-D parameter space (metallicity [M/H], T eff , log g, micro-(v micro ) and macro-turbulent (v macro ) velocities, and v sin i) utilising atmospheric models and synthetic spectra.
Each synthetic spectrum in a grid is compared to the normalised observed spectrum of a star with the chi-square ( χ 2 ) merit function being used to judge the goodness of fit. Parameter errors are computed from χ 2 statistics by projecting all grid points onto each individual parameter so that correlations are taken into account. GSSP employs the SynthV radiative transfer code  (Tsymbal 1996)  for calculation of synthetic spectra and LLmodels software package  (Shulyak et al. 2004 ) for computation of atmosphere models. Both codes operate under the assumption of local thermodynamical equilibrium and allow for extra functionality such as vertical stratification of elemental abundances in the atmosphere of a star. The log g value is not well constrained in the temperature range in question, which is the reason for fixing it to 4.
03 mas, but found that this correction results in unrealistically low luminosities for A and F stars. They deduce that the zero-point offset may be smaller for bluer stars. Since there is no consensus on the exact correction, we follow  Murphy et al. (2019)  and do not apply any zero-point offset in our analyses. We also note that Arenou et al. (2018)  discourage users of applying the offset to individual parallaxes. The stellar parameters with their respective uncertainties are listed in Table  2. If we compare the absolute magnitudes derived from the Hipparcos and Gaia DR2 data sets using the identical apparent magnitude, reddening and Bolometric correction, we find only three targets for which the deviation is larger than 3σ, specifically ν Pic, BX Ind, and θ Gru. This proves that the Gaia DR2 data have no significant discrepancies (in a statistical sense) when compared to the Hipparcos ones.
EXAMPLES OF VARIABILITY As TESS is observing almost the entire sky, we have the unprecedented opportunity to obtain continuous, highprecision light curves of a variety of pulsating stars as described in Section 1. The 2-min TESS sample in sectors 1 and 2 presented in this work includes some prototypes, i. e. , SX Phe and γ Dor. In this section, we demonstrate the power of TESS data for a variety of different pulsator classes amongst A and F stars and the potential of future asteroseismic modelling. The stars shown here were chosen either because they are eponymous for their classes (SX Phe and γ Dor), very bright (α Pic) or to cover the entire variety of the stars studied here: δ Sct, γ Dor, λ Boo, HADS, pre main-sequence, eclipsing binary stars. The TESS light curve from sector 1 shows HD 210111 to be highly multi-periodic with frequencies in the range 10 -40 d -1 and amplitudes of order 100 -1000 ppm (Fig.
2006)  and is eponymous for an entire class of gravity/Rossby modes pulsators, the γ Dor stars. Although this paper concentrates only on sectors 1 and 2, we decided to make an exception and to also include this prototype in this first-light article. TESS observed γ Dor in sectors 3, 4 and 5. The light curve was extracted by performing aperture photometry on target pixel files downloaded from MAST using the LIGHTCURVE python package  (Barentsen et al. 2019). Bright as it is, γ Dor saturates TESS CCDs. We settled on a classic approach for the preliminary analysis presented here. The photometric data extraction will be refined in the future using the halo photometry technique  (White et al. 2017). The frequency analysis was subsequently done following an iterative pre-whitening procedure with the PERIOD04 software.
fundingby the STFC consolidated grant ST/R000603/1. RMO, SC and DR were supported in this work by the "Programme National de Physique Stellaire" (PNPS) of CNRS/INSU co-funded by CEA and CNES. IS acknowledges the partial support of projects DN 08-1/2016 and DN 18/13-12. 12. 2017. PS acknowledges financial support by the Polish NCN grant 2015/18/A/ST9/00578. MS acknowledges the Postdoc@MUNI project CZ. 02. 2. 69/0. 0/0. 0/16-027/0008360. JPG, JRR and MLM acknowledges funding support from Spanish public funds for research under project ESP2017-87676-C5-5-R and from the State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award for the Instituto de Astrofísica de Andalucía (SEV-2017-0709). JAE acknowledges STFC for funding support (reference ST/N504348/1).
LFM acknowledges the financial support from the DGAPA-UNAM under grant PAPIIT IN100918. DM acknowledges his work as part of the research activity of the National Astronomical Research Institute of Thailand (NARIT), which is supported by the Ministry of Science and Technology of Thailand. MR acknowledges the support of the French Agence Nationale de la Recherche (ANR), under grant ESRR (ANR-16-CE31-0007-01). We acknowledge the International Space Science Institute (ISSI) for supporting the SoFAR international team http://www. issi. unibe. ch/teams/sofar/. SBF acknowledges support by the Spanish State Research Agency (AEI) through project No. 'ESP2017-87676-C5-1-R' and No MDM-2017-0737 Unidad de Excelencia 'María de Maeztu'-Centro de Astrobiología (CSIC-INTA).
ACKNOWLEDGEMENTS We thank the referee for useful comments and discussions. This paper includes data collected by the TESS mission. Funding for the TESS mission is provided by the  NASA   Explorer Program. Funding for the  TESS Asteroseismic Science Operations Centre  is provided by the  Danish National Re-search Foundation  (Grant agreement no. :  DNRF106 ),  ESA PRODEX  ( PEA 4000119301 ) and  Stellar Astrophysics Centre (SAC) at Aarhus University. We thank the TESS and TASC/TASOC teams for their support of the present work. This research has made use of the SIMBAD database, operated at  CDS, Strasbourg, France. Some of the data presented in this paper were obtained from the  Mikulski Archive for Space Telescopes (MAST). STScI is operated by the  Association of Universities for Research in Astronomy, Inc.
, under  NASA  contract  NAS5-2655. Funding for the  Stellar Astrophysics Centre  is provided by The  Danish National Research Foundation  (Grant agreement no. :  DNRF106 ). MC was supported by  FCT -Fundação para a Ciência e a Tecnologia  through national funds and by  FEDER  through  COMPETE2020 -Programa Operacional  Competitividade e Internacionalização by these grants:  UID/FIS/04434/2019 ,  PTDC/FIS-AST/30389/2017 & POCI-01-0145-FEDER-030389. MC is supported in the form of work contract funded by national funds through  FCT  ( CEECIND/02619/2017 ). JDD acknowledges support from the  Polish National Science Center (NCN) , grant no. 2018/29/B/ST9/02803. AGH acknowledges funding support from  Spanish  public funds for research under projects  ESP2017-87676-2-2  and  ESP2015-65712-C5-5-R  of the  Spanish Ministry of Science and Education.
FKA  gratefully acknowledge funding through grant  2015/18/A/ST9/00578  of the  Polish National Science Centre (NCN). JPe acknowledges funding support from the  NSF   REU program  under grant number  PHY-1359195. APi and KK acknowledge support provided by the  Polish National Science Center (NCN)  grant No. 2016/21/B/ST9/01126. This project has been supported by the  Lendület Program of the Hungarian Academy of Sciences , project No. LP2018-7/2018 , and by the support provided from the  National Research, Development and Innovation Fund of Hungary , financed under the K16 funding scheme, project No. 115709. JCS acknowledges funding support from  Spanish  public funds for research under projects  ESP2017-87676-2-2  and  ESP2015-65712-C5-5-R , and from project  RYC-2012-09913  under the ' Ramón y Cajal' program  of the  Spanish Ministry of Science and Education.
The research leading to these results has (partially) received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement N • 670519: MAMSIE), from the  KU Leuven Research Council  (grant  C16/18/005: PARADISE ), from the  Research Foundation Flanders (FWO)  under grant agreement  G0H5416N  ( ERC   Runner Up  Project), as well as from the  BELgian federal Science Policy Office (BEL-SPO)  through  PRODEX grant PLATO. acknowledges support by the  Spanish State Research Agency (AEI)  through project No. ESP2017-87676-C5-1-R  and No MDM-2017-0737  Unidad de Excelencia María de Maeztut-Centro de Astrobiología (CSIC-INTA ). ZsB acknowledges the support provided from the  National Research, Development and Innovation Fund of Hungary , financed under the PD1717 funding scheme, project no.
LFM acknowledges the financial support from the DGAPA-UNAM under grant PAPIIT IN100918. DM acknowledges his work as part of the research activity of the National Astronomical Research Institute of Thailand (NARIT), which is supported by the Ministry of Science and Technology of Thailand. MR acknowledges the support of the French Agence Nationale de la Recherche (ANR), under grant ESRR (ANR-16-CE31-0007-01). We acknowledge the International Space Science Institute (ISSI) for supporting the SoFAR international team http://www. issi. unibe. ch/teams/sofar/. SBF acknowledges support by the Spanish State Research Agency (AEI) through project No. 'ESP2017-87676-C5-1-R' and No MDM-2017-0737 Unidad de Excelencia 'María de Maeztu'-Centro de Astrobiología (CSIC-INTA). This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.
, (2009)  et d'une collaboration avec les partenaires entomologistes du projet 2. La construction de l'environnement de simulation a été réalisée à partir d'enquêtes de terrain menées en 2013 dans plusieurs quartiers de Delhi (Inde) durant les périodes pré et post-mousson. Les données recueillies ont été intégrées dans un système d'information géographique open source (QGIS 2. 6. 1) et couplées avec des données socio-économiques. Le modèle MOMA a été développé avec la plateforme GAMA 1. 6. 1 et les données de simulations analysées avec R (x64 3. 2. 0). MOMA et les bases de données utilisées pour les simulations présentées dans cet article peuvent être téléchargées (DOI : 10. 5281/zenodo. 48252).
Research on this mosquito's living areas is thus necessary to characterize more precisely the areas that need to be monitored and treated. An alternative to field surveys consists of evaluating the characteristics of these living areas through spatialized models. It is in this context that we developed the simulation model MOMA (Model Of Mosquito Aedes aegypti), an agent-based model which integrates a vast set of biological and behavioural knowledge about the mosquito in a simulation environment based on the needs and constraints specific to Aedes aegypti. In this paper, we present MOMA and a study of the effects of local configurations on the dispersion capacity of mosquito cohorts. The simulations in this study were carried out using data from an urban neighbourhood in the city of Delhi (India).
Cette conclusion vient après que la publication de cette méta-analyse ait fait l'objet d'une rétractation des auteurs sur demande du comité éditorial du Lancet pour niveau de preuve insuffisant du bénéfice de trachéotomie précoce sur la mortalité et l'incidence de PAVM. La mise à jour d'une méta-analyse de 2012 de la Cochrane Database (incluant 8 essais, 1977 patients) mettait en évidence un bénéfice en termes de mortalité en faveur de la trachéotomie précoce (dans les 10 premiers jours) sans bénéfice sur le risque de PAVM ni sur la durée de séjour  [9]. Les auteurs pondèrent ces résultats en raison du risque important de biais (biais de publication, hétérogénéité méthodologique des études). Hosokawa et al. , dans une autre méta-analyse publiée en 2015 incluant 142 études avec un total de 2689 patients, montraient qu'une trachéotomie précoce vs tardive (dont les définitions sont variables selon les études) diminuait la durée de ventilation mécanique, la dose totale de sédation, la durée de séjour en réanimation et la mortalité à long terme  [10].