dataesr/scientific-paragraphs-categorization huggingface dataset:
Indeed, the parameters of the NLINC parametrization are very stable for FM-A, and the same is true for the Rayleigh-cloudy HLOS wind error statistics. This confirms that NWP model data can be used for instrument characterization under the condition that instrument settings and performance are stable over time. For operational use it is important that the parameter values of the parametrization of the NLINC, Equation (7), do not change rapidly over time. Indeed, from Figure  5 , for the 2020 period, the parameter values are rather stable. The much larger variations of the parameters in the 2019 period are largely explained by the many changes of the range bin settings, and hence changes in the atmospheric sampling and different sampling of atmospheric scenes with clouds and aerosols. In the case of a gradual change of the parameters, for operational implementation, one could determine the parameters from measured data of a previous period and use it for the coming period.
RR increments based on linearity (LINC) and nonlinearity (NLINC) assumptions of the RR sensitivity to the scattering ratio have been considered. The linearity assumption has been implemented in the level-2 processing, but was found to provide biased winds in atmospheric conditions with strong Mie backscatter (clouds and dense aerosol). It has been found that a simple nonlinear exponential parametrization well fits the RR increment both in moderate aerosol conditions (scattering ratio close to 1) and strong scattering conditions, such as clouds with scattering ratio values much larger than 1. The frequency-dependent parameters of the parametrization were estimated on a monthly base for a 1 year period. In general, the parameters are stable in time, which makes the parametrization suitable for operational use; for example, by using parameters obtained from data of a previous period for the coming period.
(2021). The NLINC parametrization is less sensitive to imperfections in the estimates of the scattering ratio as long as these imperfections are consistent over time. The scattering ratio estimate imperfections project into the values of the parameters of the NLINC parametrization, which can thus well handle similar scattering ratio imperfections to correct for Mie contamination when new data arrive. The potential addition of a fourth dimension (scattering ratio) to the RR look-up table was briefly mentioned in Section 2. Some preliminary investigations have been performed, but the operational use also requires an unbiased estimate of the scattering ratio, which is lacking and is the main limitation for implementing this option in the L2Bp until now. One may wonder how strong the impact of the NWP model data used is on the correction parameters of the parametrized Rayleigh response increment.
ence Cluster (DISC) consortium. The work presented includes reprocessed data from the second reprocessing activity, which covered the June 2019-October 2020 period. Upcoming reprocessing activities will include the parametrization to correct for Mie contamination and provide improved quality Rayleigh-cloudy winds. The processor development, improvement, and reprocessing activities are performed by the Aeolus DISC, which involves the German Aerospace Centre, DoRIT, ECMWF, Royal Netherlands Meteorological Institute (KNMI), Centre National de la Recherche Scientifique, S&T, ABB, and Serco, in close cooperation with the Aeolus Payload Data Ground Segment. It should be noted that the idea of NWP calibration is predominantly based on many years of experience in scatterometer ocean-surface wind processing at KNMI and the successful application of the methodology to Aeolus Mie winds by the first author.
F Global distribution of Rayleigh-cloudy winds for August 2019. This period was characterized by wildfires over Siberia and polar stratospheric clouds over the Antarctic, which both show up in the distribution of Rayleigh-cloudy winds near (80 • N, 120 • E) and (80 • S, 60-90 • W) respectively. forward-modelled observation equivalent, denoted b (also known as background, which is a short-term model forecast), is obtained from the AUX_MET dataset. The Aeolus wind product contains, besides the HLOS wind itself, an estimate of the wind error standard deviation, which is important to give correct weight to the observation when used in data assimilation. The error of Rayleigh winds is dominated by Poisson noise on the measured signal in Rayleigh channels A and B. Details of the estimation of the wind error standard deviation are found in Rennie et al.
measured Rayleigh response RR meas is the result after accumulating from measurement to observation level. As already discussed, we use two options in cloudy conditions; that is, accumulating only those measurements classified as cloudy and accumulating all measurements. As such, for each Rayleigh-cloudy wind location we obtain two values for RR meas and corresponding ΔRR(𝜌, Δf The result is a total of 32 bins for 𝜌. Figure2shows an example of ΔRR(𝜌, Δf NWP (𝑗)) for the frequency bin, Δf NWP (𝑗), centered at 0 MHz (capturing close to zero HLOS winds). For each 𝜌 bin with value 𝜌 i the corresponding dataset of RR increments ΔRR(𝜌 i , Δf NWP (𝑗)) is extracted from the complete (1 month) dataset from which the mean value and its standard deviation are calculated. The result is the 32 crosses in Figure NWP ), each with a different value for 𝜌.
Participants and recruitment There were five groups of participants in this study: pregnant women, postpartum women, companions, potential companions, and health care providers and administrators. We prespecified the target sample size for each type of participant, as informational power suggests that high quality data collection, variability of participant experience and background, and sample sufficiency are critical factors to determining appropriate sample sizes in qualitative research  [17]. Pregnant and postpartum women aged 18 to 49 years who received antenatal and postpartum care in the study health facilities were invited to participate in indepth interviews. Postpartum women who gave birth in the study health facilities in the previous 24 h were also invited to participate. The health workers facilitated contact with women during their visit or stay to the health facility.
Data collection and tools Data were collected by four female social scientists who had experience in qualitative research. They received a 3-day training prior to data collection. Data were collected in February 2020. Each potential participant was provided with information about the study and invited to participate by the data collector. In-depth interviews (IDIs) took between 30 and 90 min to complete, and took place in a comfortable and convenient location, such as a private room of the hospital, which was free from interruptions. Sociodemographic information was collected for each participant. Pregnant and postpartum women received soaps as compensation for the time devoted to the interview. The semi-structured discussion guide for each six participant groups was developed based on previous work   [16].
Prior to conducting the data collection, all members of the maternity care unit at each health facility were briefed on the purpose of the activity, what the readiness assessment entailed, and how they could assist during the data collection. A semi-structured form was used to observe service delivery context in each facility settings. The key topics covered by the readiness assessment were: (1) Inventory of physical space and resources; (2) Health workforce and model of care; (3) Protocols and guidelines for managing clinical care during labor and childbirth; (4) Continuous education and quality improvement; (5) Assessment of facility medical records and data management systems; and (6) Labor companionship in practice  [16]. The topics related to facilitators and barriers to labor companionship, such as the physical environment in labor room and postpartum room, were integrated in this paper.
Data management and analysis All transcripts were imported into NVIVO 11 software (QSR international, Doncaster, Australia). The data analysis was conducted in French, with quotes for this paper translated to English at the time of writing. A bilingual locally based social scientist member of the research team was responsible for translation of quotes from French to English to minimize the interpretation lost. A thematic analysis approach was used  [18]. This analysis is appropriate to understand a set of experiences, thoughts, or behaviors within the data  [18]. The analysis was performed according to the following steps: (a) organizing the data; (b) generating categories, themes, patterns; (c) testing emergent hypotheses; (d) searching for alternative explanations and deviant cases. We used a combined inductive and deductive approach.
The deductive approach was used by generating a codebook based on the objectives and themes from the guides. Then, codes from the codebook were applied to the data. An inductive approach was used for initial coding to identify other themes that emerged naturally from the data. Responses to the topics in the readiness assessment were combined with the findings from the qualitative research to identify barriers and to develop considerations for implementation of the WHO companionship model. Key themes emerging from the qualitative analysis were used to inform the analysis of data from the readiness assessment. The readiness assessment consisted primarily of short answer and open-ended questions, which were analyzed descriptively to provide more information about the hospital context and environment.
Funding This research was conducted under the grant by the  European Union 's  Horizon 2020 research and innovation programme  (Grant Agreement No. 847567 ) and was funded by the  UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP) , a cosponsored programme executed by the  World Health Organization (WHO). MAB is supported by an  Australian Research Council   Discovery Early Career Researcher Award  ( DE200100264 ) and a  Dame Kate Campbell Fellowship  ( University of Melbourne Faculty of Medicine, Dentistry , and  Health Sciences ). The contents of this article are solely the responsibility of the authors and do not reflect the views of the  EU, UNDP ,  UNFPA ,  UNICEF ,  WHO , the  World Bank , or the  Australian Research Council.
Meticulous analysis of SORBET spectra via a stowed electric antenna The data discussed in this work were obtained serendipitously during the MSB1 and MSB2 by PWI, but only from the nondeployed electric dipole antenna known as Wire Probe anTenna (WPT, spherical probes of 60 mm diameter just at the out-side of the spacecraft side panel but behind MOSIF) and connected to the SORBET radio receiver in the band [2. 5-640] kHz, called TNR band, hereafter. The question arises as to why this measurement is serendipitous. During both MSB1 and MSB2, PWI/SORBET was switched 'on' to check the HF measurements of the high-frequency part of a search coil. However, because SORBET delivers two inseparable synchronised channels in the TNR band, we also got the signal from the stowed WPT antenna in the same telemetry packets; while the WPT preamp was switched on too (we note it was not the case during the near Earth flyby in March 2020 but during all other flybys).
Magnetohydrodynamic 3D simulations for the global picture We used the PLANET-MAG-AMRVAC code  (Pantellini et al. 2015)  to run 3D magneto-hydrodynamic simulations of Mercury's magnetosphere. The code is based on the generic MHD solver of MPI-AMRVAC 1. Numerical settings and equations solved are described in  Aizawa et al. (2021). The simulation domain is delimited by two spherical shells at distances 0. 8 R M and 16 R M from the planet's center (R M = 2440 km is the radius of Mercury). The equations are solved on a spherical grid 1 http://amrvac. org/ A174, page 3 of 8  Notes. We assume a electron-proton plasma so that n e = n p. M is the sonic Mach number and β the ratio of the thermal pressure to the magnetic pressure. 2 2 : 0 0 : 0 0 2 2 : 3 0 : 0 0 2 3 : 0 0 : 0 0 2 3 : 3 0 : 0 0 0 0 : 0 0 : 0 0 0 0 : 3 0 : 0 0 BepiColombo MSB1, October 1-2, 2021 Selected values are inspired by recent measurements by  Dakeyo et al.
Those boundaries delimit three regions: (1) the magnetosheath, (2) the magnetic cavity, and (3) the closed field lines region with a much higher electron density than in the magnetosheath (plasmasphere). W. Exner). After the closest approach, the orientation of the IMF may have changed significantly. We shall not comment MSB2 further as no clear correspondence could be established between the plasma boundaries observed during MSB2 (as shown on Fig. 3 ) and the boundaries in the simulations. This data against simulation comparison demonstrates that the electron density will be a key element of the analysis of the Hermean boundaries when BepiColombo arrives at Mercury in 2025 and the antennas of Mio were deployed. In fact, studying the boundaries only with magnetic field data -which are the only data continuously provided by the MESSENGER spacecraft -may be tricky on the night side of Mercury.
Acknowledgements. The authors thank the  BepiColombo teams at JAXA ,  ESA  and  CNES , especially  J. Benkhoff ,  G. Murakami ,  K. Amsif  and  A. Jean-Antoine Piccolo. In particular, the authors thank the  PWI team , the  MPPE/MEA  team including  N. André  and  S. Aizawa  and the MAG team, especially  D. Heyner  and  W. Exner , for fruitful discussions.
Added value of this study In the current analysis of data from multiple African sites in three phase 2 studies, the primary outcome was the vaccineelicited Ebola virus glycoprotein-binding antibody response to the two-dose, heterologous Ad26. ZEBOV, MVA-BN-Filo vaccine regimen administered in a 56-day interval. Immunogenicity was measured at a single analytic laboratory using the validated Filovirus Animal Nonclinical Group enzyme-linked immunosorbent assay. Ebola virus glycoprotein-binding antibody concentrations were measured at 21 or 28 days, depending on the study, after the second dose and at month 12 after the first dose in adults and paediatric participants. While there were differences in antibody geometric mean concentrations (GMCs) across countries (Sierra Leone, Mali, Liberia, Guinea, Burkina Faso, Côte d'Ivoire, Uganda, and Kenya), the overall GMCs were generally similar in adults and within paediatric age groups at each timepoint.
Trial designs and participants The phase 2, randomised, placebo-controlled EBL2002 study (ClinicalTrials. gov identifier: NCT02564523) evaluated the safety and immunogenicity of Ad26. ZEBOV followed by MVA-BN-Filo 28, 56, and 84 days later in healthy adults, human immunodeficiency virus (HIV)infected adults, and children aged 4-17 years at seven sites in four African countries (Uganda, Kenya, Burkina Faso, Côte d'Ivoire). 10, 11 Enrolment began on 9 November 2015 for adults and 26 February 2016 for paediatric participants; the last visits for these groups for immunogenicity occurred on 12 February 2019 and 28 November 2018, respectively. All samples were analysed by Q 2 Solutions between July 2017 and March 2019. EBL2004/PREVAC was a randomised, double-blind, placebo-controlled, phase 2 trial (NCT02876328) conducted at six sites in Guinea, Liberia, Mali, and Sierra Leone.
12, 15 Healthy individuals aged ≥1 year were eligible to participate and were randomised to one of five study arms. Enrolment began on 16 April 2018 and the last visits for immunogenicity occurred on 25 November 2019 for adults and 12 December 2019 for paediatric participants. Additional details of the EBL2004 study design are provided in the Supplementary methods. Serum aliquots from a subset of participants in EBL2004, at selected timepoints, were sent to Q 2 Solutions laboratory for FANG ELISA analysis. Data presented here from the Ad26. ZEBOV, MVA-BN-Filo (56-day interval) and matching placebo arms are based on this subset of samples analysed by Q 2 Solutions. All samples were analysed by Q 2 Solutions between July 2020 and September 2021. EBL3001 (NCT02509494) evaluated the safety and immunogenicity of Ad26.
EBOV GP-binding antibody GMCs at month 12 in paediatric participants The overall binding antibody GMC at 12 months postdose 1 in EBL2002 was 541 EU/mL (95% CI: 433-678; percent responders: 90%) for adolescents and 637 EU/ mL (529-767; 98%) for older children (Supplementary Figure  S4a  and b , Supplementary Table  S4 ). 11 t month 12, the overall GMC in EBL2004 was 731 EU/mL (95% CI: 589-907; percent responders: 77%) in adolescents, 739 EU/mL (585-933; 94%) in older children, and 1139 EU/mL (905-1432; 100%) in younger children (Supplementary Figure  S4a-c , Supplementary Table  S4 ). Data were not available at this timepoint from Liberia. In EBL3001 stage 2, the overall binding antibody GMC at month 12 was 386 EU/mL (95% CI: 326-457; percent responders: 70%) in adolescents, 436 EU/mL (375-506; 71%) in older children, and 750 EU/mL (629-894; 96%) in younger children.
16 he strength of the current analysis is that it included data from several sub-Saharan African countries and provided a detailed overview of immune responses across the region. Furthermore, the variation in GMC responses in adult and paediatric participants was shown to be largely due to participant characteristics rather than between-study variance. A limitation of the analysis is that no concrete conclusions can be made on whether there were differences in response by country or study. This is due to the small sample size of the subgroups when participants were stratified by study, country, and age group. In addition, the study timeframes and analysis of samples occurred in different  years. Although samples were analysed by the same laboratory in all studies, and the laboratory performed stability monitoring of the FANG ELISA assay, it is possible that laboratory drift may have occurred over time and responses could vary over time.
BK contributed to the conduct and data analysis of EBL2004 and EBL3001, conception and design of the pooled analysis, data interpretation and presentation, manuscript first draft, and manuscript review. SE contributed to the design and conduct of the Ivorian studies, which contributed to this analysis; had full access to the data; and reviewed the final version of the manuscript. HK contributed to the conduct of EBL2002, which contributed to the analysis; had full access to the data; and reviewed the final version of the manuscript. OA contributed to the collection of primary data and reviewed the manuscript prior to submission. EDO contributed to the design, conduct, and data collection for the EBL2004 study, contributed to the manuscript first draft, and reviewed the final version of the manuscript.
BL was the site principal investigator of the EBL3001 study and reviewed the data and the final version of the manuscript. RT contributed to design and conduct of EBL2002 as EBOVAC2 coordinator, data interpretation, and the manuscript. BG and DW-J contributed to the design and conduct of the Sierra Leonean studies and to the EBL2004/PREVAC study which contributed to this analysis; reviewed the data; had full access to the data; and reviewed the final version of the manuscript. MD and KL contributed to the design and conduct of the EBL2002, EBL3001, and EBL2004 studies; and data interpretation and presentation. CR contributed to the individual study conception and conduct, data analysis and interpretation, and manuscript preparation. All authors had full access to the data and approved the final draft for publication.
Acknowledgements The authors thank the  EBL2002 ,  EBL2004/PREVAC , and  EBL3001  study teams and the participants who consented to the trials. We are grateful to the  Ministries of Health of Burkina Faso, Côte d'Ivoire, Guinea, Kenya, Liberia, Mali ,  Sierra Leone , and  Uganda  who permitted the conduct of the trials, and we furthermore thank  The Alliance for International Medical Action (ALIMA)  and all site collaborators for their contribution in the implementation of this EBL2004/PREVAC trial. Medical writing and editorial support were provided by  Kimberly Fuller, PhD , and  Courtney St. Amour, PhD , of  Lumanity Communications Inc. , and were funded by  Janssen Vaccines & Prevention BV. Publication coordination was provided by  Sónia Silva  and  Valérie Oriol Mathieu  ( Janssen Vaccines & Prevention, Leiden, The Netherlands ).
The  EBL2002  and  EBL3001  studies received funding from  Janssen Vaccines & Prevention BV  and the  Innovative Medicines Initiative  2 (www. imi. europa. eu) Joint Undertaking  ( IMI2JU ) under grant agreements No  115854  ( EBOVAC1 ) and No  115861  ( EBOVAC2 ). These Joint Undertakings receive support from the  European Union 's  Horizon 2020 research and innovation programme  and the  European Federation of Pharmaceutical Industries and Association (EFPIA). The dissemination represents only the authors' views and IMI2JU is not responsible for any use of the information contained in the dissemination. Janssen Vaccines & Prevention BV  provided the vaccines for the conduct of  EBL2002  and  EBL3001. The EBL2004/PREVAC research was supported in part by the  National Institutes of Health (NIH) ,  Institut national de la santé et de la recherche médicale (Inserm) , and by the  London School of Hygiene and Tropical Medicine (LSHTM)  through funding from the  IMI2JU  under grant agreement No  115854  ( EBOVAC1 ).
Acknowledgments This work was supported by a public grant as part of the  Investissement d'avenir project , reference  ANR-11-LABX-0056-LMH ,  LabEx LMH. This work was also supported by  Guangdong Basic and Applied Basic Research Foundation  (Grant No. 2019A1515110177 ),  Guangdong Provincial Key Laboratory  (Grant No. 2020B121201001 ), the  Program for Guangdong Introduc-.
E This study aims to explore the potential of Montessori's pedagogy in promoting peace education in the Philippines. Using a qualitative research design, the study collected data from 10 participants, including teachers, parents, and Montessori school administrators. The findings of the study suggest that Montessori's approach can contribute to peace education by promoting a child-centered and experiential learning environment, which can foster critical thinking skills and empathy towards others. Moreover, the study identified several challenges to implementing Montessori's pedagogy in the Philippine context, such as the lack of awareness and understanding of the approach among educators and parents, limited availability of trained Montessori teachers, and the lack of resources and support for implementing the approach in schools.
This study also adhered to ethical principles and guidelines, including obtaining informed consent from the participants, maintaining confidentiality and anonymity, and ensuring the safety and well-being of the participants. The study also followed ethical standards for research involving human subjects. While this study provides a comprehensive investigation of the potential of Montessori's pedagogy to promote peace education in the Philippines, it has several limitations. These limitations include the use of a single case, which may limit the generalizability of the findings. Additionally, self-report data from the participants were used, which may be subject to biases and limitations. Lastly, the study was limited by the availability of participants and resources to conduct the research.