dataesr/scientific-paragraphs-categorization huggingface dataset:
Funding This project was funded by the  Indian Ocean Health Agency  ( N. G. , PhD  fellowship), the  INTERREG FEDER   TROI 2018-2020  (E. C. ) and the grant L' Oréal-UNESCO For Women in Science 2019  (N. G. ). A. R. was financially supported by l' Agence Nationale pour la Recherche  ( JCJC MUSEOBACT  contrat  ANR-17-CE35-0009-01 ), the  European Regional Development Fund (ERDF  contract  GURDT I2016-1731-0006632 ) and  Région Réunion.
Nitrous oxide (N 2 O) is the fourth most important greenhouse gas in the atmosphere and is considered the most important current source gas emission for global stratospheric ozone depletion (O 3 ). It has natural and anthropogenic sources, mainly as an unintended by-product of food production activities. This work examines the identification and quantification of trends in the N 2 O concentration from the middle troposphere to the middle stratosphere (MTMS) by in situ and remote sensing observations. The temporal variability of N 2 O is addressed using a comprehensive dataset of in situ and remote sensing N 2 O concentrations based on aircraft and balloon measurements in the MTMS from 1987 to 2018. We determine N 2 O trends in the MTMS, based on observations. This consistent dataset was also used to study the N 2 O seasonal cycle to investigate the relationship.
Our objective is to use these observations to evaluate the N 2 O trend from the middle troposphere to the middle stratosphere (MTMS), and compare it with the trend obtained with surface and satellite observations. This paper is structured as follows. Section 2 describes the different datasets (aircraft, balloon) and the use of statistical analysis to provide quality control on the data. Section 3 presents and discusses the results for the temporal variability and the seasonal zonal mean values of N 2 O derived from aircraft/balloon measurements. We end with Section 4, which summarizes the results and puts the historical observed abundance in perspective with future projections.
Aircraft and Balloon Observations The data we have compiled here represent the most extensive dataset among those available from research aircraft and balloon campaigns; they are listed in Appendix A. Almost 2. 5 million measurements from 53 research campaigns have been collected from 1987 until 2018 at pressure levels ranging from 600 to 5 hPa. This unique dataset includes measurements from stratospheric balloon flights, the Space Shuttles, instrumented commercial aircraft, and several research aircraft campaigns. The research aircraft campaigns include measurements using the ER-2, Global Hawk and DC8 (managed by NASA Armstrong (Dryden) Flight Research Center, USA), WB57 (managed by NASA Johnson Space Center, USA), the Learjet (managed by Enviscope GFD, Germany) and HALO and Falcon (managed by DLR, Germany), the NSF/NCAR HIAPER Gulfstream GV (Broomfield, Colorado, USA, managed by EOL's Research Aviation Facility), and the Geophysica M55 (produced by Myasishchev Design Bureau, Zhukovsky, Russia).
6% of the total. These data are not only outliers but potentially also special dynamic cases such as tropical or tropospheric intrusions, stratospheric descents, etc. , which would lead to biases in calculating the means. In total, 2,435,700 N 2 O measurements are extracted that way (97. 4% of the original total) for all latitudes and pressures between 600 and 5 hPa. Figure  4  shows the number of measurements (points) in 10 • latitude bins, 60 pressure levels, and for the four seasons: DJF (December, January, February), MAM (March, April, May), JJA (June, July, August), and SON (September, October, November). The plot shows good coverage of the Northern Hemisphere with more than 200 measurements per box for the four seasons. The lower stratosphere is well represented with over 1000 points per box for all latitudes.
Data Handling From the curated dataset, we create a 3D grid of latitudes, pressures, and time with latitudes for South and North Polar areas (±[90-60] • N), northern and southern midlatitudes (±[60-30] • N) and tropics (±30 • ), and with 24 pressure levels (from 600 hPa to 5 hPa) and seasons of each year (1987-2018), i. e. , 5 latitudes boxes × 23 pressure boxes × 4 seasons × 32 years as 14,720 "boxes. " To take into account that some measurements are more precise than others in the same box, the instrumental error-weighted average is calculated following this equation: μ = n ∑ i=1 x i × w i ( 3 ) where n is the number of measurements in one box, w i ∝ 1/err 2 i is the normalized weight with ∑ n i=1 w i = 1, and x i is the N 2 O concentration for the measurement i associated with the instrumental error err i.
5 ). Then, considering the adjusted datasets, instrumental error-weighted averages are calculated in latitude boxes of 10 • width (for all longitudes) and 60 pressure levels (from 600 hPa to 5 hPa). The dataset shows good coverage of latitudes, except for high southern latitudes (above 60 • S) in DJF, MAM, and JJA. N 2 O concentrations vary between 320 and 340 ppb throughout the troposphere. This observation is consistent with the location of N 2 O sources, mainly at the surface (biological sources from soil and water, and anthropogenic sources mainly agricultural soil and animals breeding) and sinks present in the stratosphere (photodissociation and reaction with excited oxygen atoms, O( 1 D)), see  [50]  and reference therein. As observed in the study of Kuttippurath et al. [12] , which shows N 2 O zonal means for ASUR data, the influence of the stratospheric transport on the N 2 O zonal mean is also visible.
Summary and Outlook This paper presents the first compilation of the majority of existing N 2 O balloon and aircraft measurements performed between 1987 and 2018, ranging from the middle troposphere to the middle stratosphere. First, we pre-processed the data by blind source separation to exclude particular dynamic cases and outliers. This approach avoids the need for binning the data by latitude and longitude to identify anomalous profiles. With this dataset, we calculated instrumental error-weighted averages in boxes over a wide range of latitudes (North and South Pole, midlatitudes, tropics) and over 10 • latitude boxes for pressure levels ranging from 600 hPa to 5 hPa. We extracted trends between 1987 and 2018 (a linear trend is applied for the entire period) and revealed an increase in N 2 O concentration of 0.
89 ± 0. 07 ppb/yr in the upper troposphereand 0. 96 ± 0. 15 ppb/yr in the lower stratosphere. The growth of this potent greenhouse gas, as observed at the ground and remotely by satellites, is confirmed in situ in the UTLS, the most important region of the atmosphere for the Earth's radiative balance. We extracted the zonal mean from the whole dataset and illustrated its evolution with seasons DJF, MAM, JJA, and SON. The N 2 O zonal mean highlights, as explained in other studies, the atmospheric circulation, with an increase in tropical upwelling during DJF and stratospheric polar descent during northern (or boreal) winter. With the decrease in halocarbon concentrations, N 2 O emissions will become the primary ozone-depleting substance in the future  [6]. However, the impact of N 2 O depends on the levels of CO 2 and, to a lesser extent, CH 4  [57, 58].
That is, they become increasingly unstable and sensitive to minor details in the data. To perform blind source separation, we store our data in a rectangular matrix, in which rows correspond to pressure levels and columns to individual records. This matrix has many data gaps because each record has a different pressure range. Unfortunately, our mode decomposition cannot handle sparse data. To overcome this problem, we start by interpolating them, using missing imputation  [122]. Missing imputation is routinely used in statistics to identify missing values in a self-consistent way. Here we use a variant of the method that is closely related to blind source separation because it relies on the consistency of the concentration profiles to fill in missing data  [123]. The method is iterative: it determines the modes, uses them to fit the profiles and replace missing data, and starts over again to estimate the missing modes from the augmented dataset (observations + interpolated data).
Figure7depicts the zonal mean N 2 O binned by latitude and pressure for 2018, including all the data (balloon and aircraft) from 1987 to 2018, which were normalized to 2018 for DJF, MAM, JJA, and SON. For that normalization, the average trend observed in the troposphere in Figure6of 0. 89 ppb/yr is used to calculate the N 2 O concentration for each measurement and adjusted to 2018 as explained in Section 2. 3, Equation (5). Then, considering the adjusted datasets, instrumental error-weighted averages are calculated in latitude boxes of 10 • width (for all longitudes) and 60 pressure levels (from 600 hPa to 5 hPa). The dataset shows good coverage of latitudes, except for high southern latitudes (above 60 • S) in DJF, MAM, and JJA. N 2 O concentrations vary between 320 and 340 ppb throughout the troposphere.
Acknowledgments: A. R. R. acknowledges the  Le Studium Advanced Institute of Loire Valley  for a  Research Professorship. The MIPAS, SPIRALE, BONBON balloons teams thank the  Centre National d'Etudes Spatiales (CNES)  launching team and the  Swedish Space Corporation team at Esrange  for excellent balloon operations and the  Free University of Berlin  for meteorological support. The ASUR team thanks the  NASA Dryden Flight Research Center (DFRC)  including the DC-8 crew, and the  German Aerospace Center (DLR) at Oberpfaffenhofen  with the Falcon crew, for their outstanding support during the flight campaigns. Part of this research was performed at the  Jet Propulsion Laboratory, California Institute of Technology , under contract with  NASA. Donald R. Blake  from the  University of California, Irvine ,  Steve Montzka  from  NOAA GML , and  Lance E.
Funding: This work was funded by the  PIVOTS  project provided by the  Région Centre-Val de Loire  ( ARD 2020 program  and  CPER 2015-2020 ), and  Labex VOLTAIRE  ( ANR-10-LABX-100-01 ). HALO N 2 O data were funded as part of the  German science foundation (DFG)   SPP 1294  under grants  HO 4225/7-1 ,  HO 4225/8-1 ,  EN 367/13-1. ASUR-related work was largely funded by the  European Commission (EC) , the  National Aeronautics and Space Administration (NASA) , and the  Federal Ministry of Education and Research (BMBF). EA acknowledges support of grants from the  NASA   Upper Atmospheric Research Program  and the  NSF   Atmospheric Chemistry Program. European Community's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement n603557-Project  STRATOCLIM. The MIPAS-B related work was funded in part by the  European Space Agency (ESA)  and the  German Aerospace Center (DLR).
Data Availability Statement: All raw data are available either by contacting instrument PIs or by direct download in server website as "aeris-data. fr", "espo. nasa. gov", accessed on July 2021. HIPPO data are available at https://www. eol. ucar. edu/field_projects/hippo, accessed on July 2021. The data use for the plots in the Figures  6  and 7  are available in the AERIS database (https://doi. org/10. 2 5326/428, accessed on July 2021).
Acknowledgement ITER is a Nuclear Facility  INB-174. The views and opinions expressed herein do not necessarily reflect those of the  ITER Organization. One of the authors  Junli  is very grateful for the help of the J-TEXT team. This work is supported by the  National Magnetic Confinement Fusion Energy Research Project  ( 2017YFE0301805 ) the  National Natural Science Foundation of China  ( 11905030 ,  11775090  and  51821005 ). Also, this work was partially supported by " PLADyS" ,  JSPS Core-to-Core Program , A. Advanced Research Networks.
a b s t r a c t The Mandrillus Project is a long-term field research project in ecology and evolutionary biology, monitoring, since 2012, a natural population of mandrills ( Mandrillus sphinx; primate) located in Southern Gabon. The Mandrillus Face Database was launched at the beginning of the project and now contains 29,495 photographic portraits collected on 397 individuals from this population, from birth to death for some of them. Portrait images have been obtained by manually processing images taken in the field with DSLR cameras: faces have been cropped to remove the ears and rotated to align the eyes horizontally. The database provides portrait images resized to 224 × 224 pixels associated with several manually annotated labels: individual identity, sex, age, face view, and image quality.
Data format Raw (JPG) Description of data collection The Mandrillus Face Database contains 29,495 portrait photos of wild mandrills taken between 2012 and 2021, stored in jpg format with a 224 × 224 pixel resolution. These individuals are daily monitored by field assistants, who take pictures and record individuals' identity directly in the field. Pictures are taken on both sexes of all ages (infants, juveniles, adolescents and adults). Data were normalized by manually cropping faces and rotating images to align the eyes along a horizontal line.
Value of the Data • This is the first public database that contains annotated face pictures of wild mandrills living in their natural environment. To our knowledge, this is also the largest photographic portrait database for non-human animals in the wild regarding the number of sampled individuals and the time frame (397 individuals totaling 29,495 pictures taken during 10 years) • Pictures are labelled by experts in primatology for applications in Computer Vision, Machine Learning/Deep Learning, Data Science. • The database is specifically designed to benchmark methods of individual recognition, face verification, sex recognition, and age prediction in a non-human primate.
The database includes 26,846 frontal and 2,649 profile pictures. FaceQual (type 'categorical): this column indicates the quality of the picture, ranging from 0 to 3 (or -1: when the quality has not been evaluated because the individual is in profile view). 0: pictures of bad quality and for which experienced field assistants are unable to recognize the individual from the picture alone, without the contextual information. 1: pictures of average quality for which experienced field assistants are able to recognize the individual from the picture alone, with some difficulties but without any contextual information. 2: pictures of good quality for which individual recognition is straightforward but the portrait does not meet the criteria of quality 3. 3: pictures of high quality for which individual recognition is straightforward, and the face has a neutral expression and is in perfect frontal view, with no shadow, bright spot or partial occlusion ("id card-like" portraits).
The majority of the portraits are of quality 2 and 3 (see Fig. 4  ). Shootdate (type 'date'): date of shooting ("YYYYMMDD"). The database includes 191 females, 203 males and 3 individuals of unknown sex (infants aged less than a year, only). Fig. 2   The database contains individuals from birth to 23 years old. The age is calculated as the difference between the shooting date ("Shootdate" column) and the date of birth ("dob" column). Fig. 3  provides the histogram of the age distribution of the portrayed individuals with infants (0-1 year) corresponding to 20% of the total number of pictures. The Fig. 4  represents the number of pictures collected per year (extracted from the "Shoot-Date" column). Most pictures were taken from 2018 onward (more than 87% of the pictures). Finally, Fig. 5  represents the number of photos per quality score ("FaceQual" column).
Experimental Design, Materials and Methods The database includes 29,495 photographic portraits collected on 397 individuals from the only wild social group of mandrills habituated to human presence. This group, which roams in the Lékédi Park and its surroundings, in southern Gabon (near to the village of Bakoumba), is daily monitored by the Mandrillus Project  [1]  ( www. projetmandrillus. com ) for researches in ecology and evolution (see for examples:  [ 2 , 3 ] ). The group was founded after the release of 65 semi-captive individuals (born and raised at CIRMF; Centre International de Recherches Médicales de Franceville, Gabon), in 2002 (36 individuals) and 2006 (29 individuals  [4]  ). Starting as early as 2003, wild males joined the group to reproduce with released females. In 2021, most of the individuals of the group ( > 95%) were wild-born.
Photos were taken directly in the forest by field assistants while following the study group. Since the beginning of the project, field assistants have used different models of DSLR cameras and long-focal lenses (varying from 70 to 500 mm, depending on camera models and distance to the subjects). Photos are uploaded on a computer regularly, and renamed by the assistants using the syntax presented above. Co-authors of this article (BRT, MH, MJEC, LS), who know the identity of the studied mandrills, monthly validated the names of the individuals depicted on all pictures from the database. Pictures were then processed using Adobe Photoshop Lightroom Software version 10. 1. 1. Images were first oriented to align the pupils of the eyes horizontally, and then centered and cropped to keep only the face (removing the neck and the ears).
represents the number of males and females as a function of the number of pictures collected on them, and the number of pictures per sex. On average, females are represented by 85 ±72 pictures and males by 65 ±64 pictures (here average are distorted by extreme values: as the boxplot shows, there are several individuals represented by only one picture, and one individual with 488 pictures). Fig. 2 also illustrates that the database contains numerous individuals with a few pictures, although 323 individuals are represented by more than 20 pictures.
Acknowledgments We are grateful to past and present field assistants of the Mandrillus Project who took photographic portraits, and to the  SODEPAL-COMILOG society (ERAMET group ) for their long-term logistical support and contribution to the Mandrillus Project. This study was funded by several grants that allowed long-term collection of data:  Deutsche Forschungsgemeinschaft ( DFG ,  KA 1082-20-1  ),  SEEG Lékédi ( INEE-CNRS  ) to MJEC, and  Agence Nationale de la Recherche  to  MJEC  (  ANR SLEEP 17-CE02-0 0 02  ) and to JPR (  ANR-20-CE02-0 0 05-01  ). This is a Project Mandrillus publication number  31  and  ISEM 2023-010-SUD.
Introduction: There is little understanding of long-term treatment persistence in patients receiving anti-vascular endothelial growth factor (anti-VEGF) injections for diabetic macular edema (DME), particularly relating to treatment intervals. The aim of this study was to investigate the association between treatment interval and discontinuation rate after 24 months of unilateral anti-VEGF treatment in patients with DME under routine clinical care in the USA. Methods: This was a non-interventional, retrospective cohort study to review the health insurance claims of adults with DME linked with the IBM MarketScan Ò Commercial and Medicare Supplemental databases, who were continuously.
Study Design and Population Selection We conducted a non-interventional, retrospective cohort analysis of health insurance claims data of patients from the USA who received anti-VEGF treatment for DME for the first time between 1 July 2011 and 30 June 2017 (inclusive). The study period was from 1 January 2011 to 30 June 2020 and data analysis was conducted from October 2021 to February 2022. This study followed Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. Data for this analysis were extracted from the IBM MarketScan Ò Commercial and Medicare Supplemental databases  [17]. Authors received permission to use and access the database from the database owner. These databases provide unique identifiers that allow enrollees to be followed up across institutions and clinicians, and over time, while preserving their full anonymity.
Adults with DME, who were continuously enrolled in a health plan for at least 6 months prior to the date of their first anti-VEGF treatment (cohort entry date) and for a duration of at least 24 months following cohort entry (exposure assessment window; Study Design in Fig. 1 ; adapted from  Schneeweiss et al. 2019)  were included  [20]. The cohort was restricted to patients with DME who did not receive anti-VEGF treatment at any time (at least 6 months) prior to cohort entry. This ensured the exclusion of heterogeneous data from patients who had received multiple lines of treatment over the long term  [21]. Time was counted from the first anti-VEGF injection. Patients were grouped on the basis of their injection interval at 24 months. Covariates (age at first anti-VEGF injection, sex, treatment interval group, Charlson Comorbidity Index [CCI] score [0, 1, 2, 3?], treatment type [bevacizumab, aflibercept, or ranibizumab]), and baseline conditions were assessed within the 6 months prior to or at cohort entry.
Sex was defined as the gender of the patient on admissions, services, outpatient claims and prescription drug claims, of covered life on populations. Evidence of bilateral treatment and treatment interval groups were assessed during the 24-month exposure assessment window. Medication is attributed to a patient in the database, not to an eye, so it is not possible to assess treatment interval for patients treated bilaterally. Consequently, patients with evidence of bilateral use of anti-VEGF within 24-month exposure assessment window, defined as the presence of at least one period of B 15 days between any two anti-VEGF injections, were excluded from the analysis. Treatment interval at 24 months was defined in the remaining unilateral patients as the average treatment interval over the last three intervals in the exposure assessment window.
Statistical Analyses Demographic and clinical characteristics were descriptively summarized. The Kaplan-Meier method was used to estimate time-to-Fig. 1  Study design. The study design is adapted from Schneeweiss et al. 2019  [20]. The study period was from 1 January 2011 to 30 June 2020. Eligibility criteria and data on covariates and baseline characteristics were assessed in the 6 months prior to the cohort entry date (date of the first anti-VEGF injection). Treatment interval groups and evidence of bilateral treatment were assessed during the 24-month exposure assessment window. The follow-up window began on the day following the exposure assessment window and continued until the end of the study period, end of continuous health plan enrollment, or discontinuation of anti-vascular endothelial growth factor treatment.
Identification of factors associated with treatment persistence and reasons for discontinuation treatment burden, lack of continued efficacy) and the associated exit strategies (e. g. , switch to corticosteroid therapy) can be helpful in developing strategies to improve the visual function of patients with diabetes. As reasons for discontinuations were not available from our database, we investigated instead factors associated with treatment persistence. Treatment interval patterns during the last three intervals before 24 months show that 27. 4% patients from our study were on a longer ([ 12 weeks) treatment regimen at 24 months after the start of the anti-VEGF treatment. Patients in this [ 12-week interval subgroup were twice as likely to discontinue treatment compared with the 8-week interval group.