dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion The genetic characterization of Zebus from Mayotte and Madagascar (MAY and ZMA), two geographically closely related island cattle populations from the Western Indian Ocean, showed that they share a similar recent and rather complex demographic history. In particular, we detected in these two populations a weak African taurine ancestry and a predominant indicine ancestry. The indicine ancestry in MAY and ZMA was even higher than in the East-African zebu breed, the African continental breed with the highest estimated indicine ancestry proportion in our dataset. This pattern had already been reported for ZMA in some previous studies  (Hanotte 2002; Gautier et al. 2009 ) but still remained difficult to explain from an historical point of view. Our demographic inference, in the form of admixture graph construction, demonstrated that the higher indicine ancestry in the MAY and ZMA populations, as compared to other African continental zebus, could actually be explained by a second pulse of Indian Zebu introgression, limited to the island populations, into an already admixed African taurine x Zebu population of likely East-African origin that traces back to the 12th century.
67P/Churyumov-Gerasimenko is a Jupiter-family comet that was the target of the Rosetta mission, the first mission to successfully orbit and land a probe on a comet. This mission was accompanied by a large ground-based observing campaign. We have developed a pipeline to calibrate and measure photometry of comet 67P during its 2016 perihelion passage, making use of all visible wavelength broad-band imaging collected across a wide range of facilities. The pipeline calibrates the brightness of the comet to a common photometric system (Pan-STARRS 1) using background stars within the field allowing for compilation and comparison of multiple data sets. Results follow the predictions based on previous apparitions: 67P shows no obvious change in acti vity le vels from orbit-to-orbit and coma colours remain constant throughout the apparition.
2012 ). It works by cross-referencing the source list with the Pan-STARRS DR1 (PS1) catalogue. Using the WCS coordinates of sources within the frame it finds matching PS1 sources and then estimates the calibration constant with colour correction. Table  2  displays the colour terms used in the calibrations for each filter in each data set. Before calibrating the magnitudes, the pipeline remo v es an y sources with a PS1 PSF -Kron magnitude greater than 0. 05. These sources are likely to be galaxies and therefore cannot be used as calibrators. (v) The comet is identified by finding the source with the WCS coordinates that most closely match the coordinates from JPL    A1. Horizons, within 4 arcsec. Photometry is then measured with a fixed aperture of 10 000 km radius using the geocentric distance from JPL Horizons and appropriate pixel scale from the WCS to calculate the corresponding radius in pixels.
These data formed the backbone of our comparison and we used this as a 'true' representation of the light curve. The colours obtained from the LT were also used as our starting point when approaching colour calibration of the remaining data. The NOT/ALFOSC data presented an issue; noisy edges left o v er from the data reduction process. These noisy edges were sometimes incorrectly identified as sources by Astrometry. net causing it to fail to solve. We initially tried masking the edges but the problem persisted even after masking. We concluded that then it must have been an issue with the fields of stars themselves. We took the decision to discard these images rather than adapt the pipeline to mask the specific noise pattern since this affected only around 12 per cent of the images in the NOT data, and even fewer in the data set as a whole.
Despite this, it is one of the most well calibrated and comprehensive data sets in both r -and g -bands. 32 images taken by CAFOS on the Calar Alto Observatory (CA) 2. 2-m telescope had noisy artefacts, similar to the NOT, which caused the pipeline to fail. Again, we took the decision to simply discard these frames. The calibration of some of these data has wide variations within nights due to the small number of calibration stars within the field of view. This led to some differing estimations of the zero-point in each frame as CALVIACAT tried to fit a line to a small number of points. The large number of exposures taken each night allowed us to remo v e outliers in the calibration. While this data set is large it is concentrated on small groups of consecutive nights separated by weeks rather than long-term monitoring.
The Lowell data set has good co v erage around perihelion, but somewhat inconsistent calibration due to varying quality between frames. Several frames contained dead pixels which sometimes would lie on top of a star, making the calibration less accurate. The 43 frames where the dead pixels lay within the comet aperture were discounted. Table  3. Summary table of data processed through the pipeline. Frames input is the original number of images passed to the pipeline. Frames processed is the number of frames successfully calibrated by the pipeline, images causing the pipeline to fail, or images manually remo v ed from the final data are not included in this number.
9-m/CCD - - - - 78 78 - - - - - - - - - - LCOGT/Sinistro - - - - - - - - - - 42 36 - - - - Gemini N/GMOS - - - - - - - - 17 17 42 42 12 12 12 12 IRTF/MORIS - - - - - - - - - - 113 0 - - - - The European Space Agency (ESA) Optical Ground Station (OGS) data contained 18 frames which were discounted due to being pointed towards the wrong area of the sky. Another 37 frames did not have enough background stars to perform calibration. The pipeline failed to run on Infrared Telescope Facility (IRTF), New Technology Telescope (NTT), and NOT/STANCAM data due to the small field of view in the images. There were few stars within the field which meant astrometry and photometry calibrations failed. It is worth mentioning the William Herschel Telescope (WHT), LULIN Observatory One-Meter Telescope (LOT), Telescopio Nazionale Galileo (TNG), Isaac Newton Telescope (INT), and Bolshoi Teleskop Alt-azimutalnyi (BTA).
Without these conditions the comet identification and calibration becomes increasingly inaccurate. A limitation highlighted by the NOT/ALFOSC and CA/CAFOS data is that the pipeline has no way of adjusting for any noisy edges or artefacts that may remain after data reduction. This noise often was misidentified as sources by SEXTRACTOR and Astrometry. net which caused them either to fail or give inaccurate results. The other limitation is the pipeline only does simple aperture photometry around the comet and does not take into account any contribution of the background flux from nearby bright stars that are outwith the aperture. We decided against implementing a fix for both of these issues because of the small proportion of images they affect.
Offset between telescopes around low phase angles A peculiar effect we see in our data is a significant shift in r -band magnitudes at low phase angles between different telescopes (Fig. 3  ). The TRAPPIST data is the best example of this, it follows the MNRAS 517, 4305-4316 (2022) o v erall brightness trend but is shifted relative to the curve around low phase angles, the bump in the light curve around MJD 57450 when the comet was at opposition in 2016. Initially, we thought it was an effect of the slight bandpass differences between the Sloanr and Johnson/Cousins R filters. Some other data sets that use Johnson/Cousins filters, e. g. OSN, OGS, and CAFOS, appear to align better with TRAPPIST; ho we ver, this is not true of all data taken in this filter, for example the NOT data does not have an offset and follows the trend of the majority of the data.
Outburst of 2015 August 22 We can confirm the outburst seen in the comet coma morphology by  Boehnhardt et al. ( 2016 )  in our analysis of the 67P photometry. The date and time of this event corresponds to an outburst seen by the NavCam instrument onboard Rosetta: outburst #16 from  Vincent et al. ( 2016 ) , which was observed on 2015 August 22 06:47:04 UTC. Outburst #16 could be connected to our outburst, it is bright and occurs immediately before the brightness increase seen in the ground-based data at 2015 August 22 11:17:19 UTC. The data taken with NavCam is uncalibrated so we do not know exactly how bright it is compared to the other outbursts seen with OSIRIS. Judging the images by eye we can see that the outburst is as bright as, if not brighter than, the other outbursts and shares morphological similarities with the brightest outbursts seen with OSIRIS.
Comparison to 2021-2022 apparition We made a comparison to data taken taken during the 2021-2022 apparition, where the viewing conditions were a lot more fa v ourable. Despite the better viewing conditions, there was not as an intensive monitoring campaign for this apparition. Sharma et al. ( 2021 )  observed two outbursts using the 70-cm GROWTH-India Telescope on 2021 October 29 and 2021 No v ember 17. The second outburst was also observed and confirmed by the LCO Outbursting Objects Key Project  (Kelley et al. 2021 ; Lister et al. 2022 ). These outbursts came 4 d before and 15 d after perihelion respectively. This lends credence to the fact that acti vity le vels remain similar between   A3. orbits since it was at this point around perihelion in the 2015-2016 apparition where Rosetta detected the highest rate of outbursts.
The authorisations regarding PPPs in France are managed by ANSES: the French Agency for Food, Environmental and Occupational Health & Safety. The study is based on data gathered and analysed in the Mendeley data repository at https://data. mendeley. com/datasets/dk8gsx2r4j/9. Raw data on PPPs are available at htt ps://ephy. anses. fr/. The French exposure to natural substances with hormone-like effects, i. e. , genistein and daidzein, is calculated from measurements on food found in France and from a specific inquiry performed in supermarkets on current soy-based foodstuffs.
Calculation of exposure to endocrine-disrupting pesticides The EU pesticide database (https://ec. europa. eu/food/plant/pestici des/eu-pesticides-database/public/?event=homepage&language=EN) was screened for EDs. The data selection followed the process described in Fig. 1 -PPP-selection-scheme of the Mendeley data repository associated with this study (https://data. mendeley. com/datasets/dk8gsx2r4j/ 9). On the 1426 entries, the 460 substances approved in France (htt ps://ephy. anses. fr/) were retained. Next, 379 fungicides, insecticides, acaricides, herbicides, and growth substances and their Maximum Residue Limits (MRLs) were considered in various fruits and vegetables. They are allowed in 1666 formulas in France. See table "French PPP-ED" at https://data. mendeley. com/datasets/dk8gsx2r4j/9.
Seventy EDs were found by combining the name of each substance with the word "endocrine" and/or "disruption" and/or "disruptor" on the PubMed database, Google Scholar database, and Google. Consumption data were obtained from the official French websites https://www. lesfruits etlegumesfrais. com/ and https://agreste. agriculture. gouv. fr/agreste-web/disaron/!searchurl/searchUiid/search/ in March 2020, which describe the annual consumption of fruits and vegetables by the French population. The population data were obtained in March from the Official French statistic service, Insee (https://www. insee. fr/f r/statistiques/1892086?sommaire=1912926). EDs in the different categories of PPPs, i. e. , insecticides, fungicides, herbicides, and growth substances, were determined using the scientific literature, and the list of references for this classification can be found at https://data.
mendele y. com/datasets/dk8gsx2r4j/9 in "French-PPP-ED". For the calculation, 64 fruits and vegetables for which consumption data were available on the websites previously mentioned, were selected. The number of formulas containing ED-PPP substances allowed in France for these fruits and vegetables were entered into the table "PPP-French usage-ED" found at https://data. mendeley. com/datasets/ dk8gsx2r4j/9.
Number of products For each of these 64 fruits and vegetables, the annual national consumption is reported per day and per capita in the table "Exposurecalculation-ED," found in the data repository at https://data. mendeley. com/datasets/dk8gsx2r4j/9. The annual consumption was reported for 64 million French consumers. This number includes all declared citizens according to the Insee website in 2019 and does not include children below 3-years-old (2,150,000 children) and elderly individuals over 89years-old (912,000 individuals). For each foodstuff, the potential amounts of ingested pesticides were calculated from the legal MRLs obtained from the EU pesticide database and using a factor that takes into account the "popularity" of the substance for the considered use (i. e. , same plant and same use).
Materials Genistein and daidzein measurements were performed on 140 foodstuffs from French supermarkets and allocated to 9 different categories (see file "Genistein and Daidzein values-ED" at https://data. me ndeley. com/datasets/dk8gsx2r4j/9. For ELISA measurements, all salt reagents were from VWR-France. Antibiotics used for the digestion buffer, penicillin G (ref. P-3032).
Isoflavone exposure estimation A survey of soy-based foodstuffs available in France was performed in spring 2020 by looking at the seven main French supermarket websites, i. e. , Carrefour®, Auchan®, Leclerc®, Intermarché®, Super U®, Lidl®, and Monoprix®, as well as a few specialized shops. The entire list of products registered during this survey is given under "Phyto-Product-Enquiry-ED", at https://data. mendeley. com/datasets/dk8gsx2r4j/9. Each product was recorded with its composition only once, even if it was found on several websites. This survey gave a general picture of the percentages of the different types of products sold and consumed in France (Fig. 1 ). To obtain the exposure to isoflavones for each type of foodstuff, a mean dose, determined from isoflavone measurements, was calculated (Table  1 ).
See "Genistein-Daidzein values-ED" at https://data. mendeley. com/datasets/dk8gsx2r4j/9 to find the individual genistein and daidzein measurements in the foodstuffs and the mean and SEM calculations. According to the Sojaxa and GEPV websites, the current human consumption of soy in France is 185,000 tons, broken into 118,400 tons used as hidden soy in elaborated dishes and 66,600 tons used to produce well-identified soy-based foodstuffs. According to GEPV (2019) the number of products containing hidden soy on the French market represent 64% of the total soy product consumption, i. e. , 584 products. Meanwhile, well-identified soy-based foodstuffs accounted for 329 food products, i. e. , 36% of soy consumption. The isoflavones (genistein and daidzein) exposure was calculated from the mean of isoflavones measurements (µg/g) in nine categories of soy foodstuffs at https://data.
mendeley. com/datasets/dk8gsx2r4j/9 in "Genistein-Daidzein values-ED". A percentage of consumption was assigned to each soy food category and a mean percentage of soy in the final products was also calculated. The exposure calculations consider the mean amount of soy consumed per day and per capita in France, which is 8 g/d (https:// data. mendeley. com/datasets/dk8gsx2r4j/9), the mean amount of isoflavones per gram of the different food type (Table  1 ) and, for better accuracy, the percentage of each food category present on the French market (Fig. 1 ). Two exposures were estimated: one for soy food consumers (60% of the population) and one for soy food non-consumers (40% of the population) who only ingest isoflavones through foodstuffs with hidden soy.
Estimation of exposure to synthetic endocrine disruptors used as PPP As mentioned previously, the full calculation can be found in "Exposure calculation-ED" at https://data. mendeley. com/datasets/dk8 gsx2r4j/9. A total of 64 foodstuffs were retained because (1) they were cited either in the European or the French website for PPP applications and (2) consumption data were found on reliable French websites. The calculation led to a final fruits and vegetables mean consumption of 503 g/d, including rice. Seventy substances were detected as potential EDs as mentioned in "French PPP-ED" at https://data. mendeley. com/datasets/dk8gsx2r4j/ 9. Some EDs were de facto not allowed in France since all the formulas containing them are forbidden. Among the selected substances, 52 had an effect in vivo and 18 had an effect only in vitro.
The overall exposure to potential EDs was estimated at 509 µg/d, as shown at https://data. me ndeley. com/datasets/dk8gsx2r4j/9 in "Exposure calculation-ED". According to this estimation reported at "Exposure summary-ED", the products reaching French citizens include 147 µg/d of potential oestrogens, 118 µg/d of potential anti-oestrogens, 3. 2 µg/d of potential androgens, 353 µg/d of potential anti-androgens, 113 µg/d of potential pro-thyroid substances, and 73. 8 µg/d of potential anti-thyroid substances. Finally, there were several substances with unclassified effects, like anti-PPARγ, anti-cholesterase, anti-FSH, or anti-LH effects. They account for 87. 3 µg/d of potential ED exposure. Adding these figures leads to an exposure higher than 509 µg/d since some PPPs exhibit more than one effect.
Exposure to isoflavones with hormone-like action In the French diet, genistein and daidzein, with hormone-like activities, are essentially introduced by soybean and soy-based foodstuffs. In March 2020, 329 soy-based foodstuffs were found on French supermarket websites (see https://data. mendeley. com/datasets/dk8gsx2r4j/ 9, "Phyto-Product-Inquiry-ED"). Steaks and "elaborated dishes" containing meat-like products based on soy were the most popular soy-based foodstuffs, followed by desserts, creams, and drinks (Fig. 1 ). Based on the French consumption data, it was found that the global population had 8 g of soy/d/capita in 2020. Soy-consumers had 10 g/d/ capita while the soy non-consumers had 5 g/d/capita through foodstuff with hidden soy. The mean content of genistein and daidzein in each soy-based food category is given in Table  1.
The mean concentration of isoflavones per gram of soy is calculated from the measurements made for this study and gathered in the data repository at https://data. mende ley. com/datasets/dk8gsx2r4j/9 in "Genistein and Daidzein values-ED". The measurements showed that, for hidden soy, the amount of isoflavones per gram of soy is lower than in soy-based foodstuffs due to different processing. Following the genistein and daidzein measurements performed in the food investigated in this study, 3 values can be given: (1) global amount of isoflavones per gram of soy used for French foodstuffs (845 µg/g); (2) mean isoflavones content per gram of soy in identified soy-based foodstuffs (1800 ± 275 µg/g); and (3) mean isoflavones amount per gram of soy in foodstuffs with hidden soy (310 ± 65 µg/g). See Fig.
2 -Isoflavone-food-content-2020 at https://data. me ndeley. com/datasets/dk8gsx2r4j/9 for more details. These values were obtained by combining isoflavones measurement and claimed soy percentage in foodstuffs. Associating these data with the total soy consumption by soy consumers (60% of the French population) and the proportion of products with hidden soy (64%), an isoflavone daily exposure was calculated for each soy-based food category (Fig. 3 ). This estimated daily exposure of soy-consumers to genistein + daidzein was found to be 6915 ± 1220 µg/d, with 4590 ± 855 and 2320 ± 470 µg/d of genistein and daidzein expressed in equivalent-aglycone, respectively. Equivalent-aglycone is the amount of aglycone compounds contained in the total glycosidic forms measured. Glycosidic forms can be glucoside, acetyl or malonyl forms.
Reliability of the estimation of ED-PPPs exposure. The pesticides that were selected here are only potential EDs since they do not match the criteria that were recently defined by OECD and EFSA -ECHA  (Andersson et al. , 2018). Our definition includes more substances than those potentially retained following the recent definition. Certain compounds exert direct effects through hormone receptors or on the bioavailability of the hormones via an interaction with liver or kidney enzymes (see "French-PPP-ED" for details at https://data. mende ley. com/datasets/dk8gsx2r4j/9). Several times, in vivo deleterious effects on organs involved in endocrine processes were found, while the mechanisms of these effects were not always understood  (Andersson et al. , 2018). Because alterations of such tissues are likely to induce deleterious endocrine effects, those substances were retained.
Reliability and limits of the estimation Enterolignans that are oestrogenic only after gut flora transformation were not included in this study. Indeed, to evaluate oestrogenic enterolignan exposure, gut flora competence characterisation at the population level should be known. Such data are not available in France or in any other country. Also, enterolignans act more as SERMs (selected oestrogen receptor modulators) rather than EDs  (Carreau et al. , 2008)  and, when tested in rodents, enterolignans antagonise the proliferative effects of isoflavones on breast cancer cells  (Power et al. , 2006). The present analysis estimates the isoflavones intake by French soyconsumers at 6915 ± 1220 µg/d, i. e. , 13. 5 times higher than the estimated exposure to ED-PPP. In soy non-consumers, the exposure is estimated at 1930 ± 410 µg/d, which is 3.
mendeley. com/datasets/dk8gsx2r4j/9 and Fig. 3  from  Lee et al. , 2019). The figures show that the soy-intake is mostly a recent practice in France and that the main week-intake is 1 to 3 portions. However, a significant proportion of women has more than 9 portions per week (2. 2% has more than 25 portions /week) and this leads to a significant proportion of women being exposed to 50 mg isoflavone per day or more, expressed in aglycone equivalent. The highest exposure recorded in this study was 120 mg/day. Such doses are of the same order of magnitude as the highest dosages in food supplements and are active in women. In France, the dosages of isoflavones in food supplements were, until recently, far higher than those found in food  (Vergne et al. , 2007). However, nowadays, the food industry produces increasing amounts of soy-food based on textured soy-proteins.
e. , the canonical receptors ERα and ER β  (Kuiper et al. , 1998)  and GPER  (Petrie et al. , 2013). Isoflavones also interact with thyroid hormone synthesis  (Nakamura et al. , 2017)  and receptor binding at doses achievable dietarily (https://data. mende ley. com/datasets/dk8gsx2r4j/9). These endocrine effects can be beneficial or deleterious, depending on the physiological status of the consumer. Hence, in some cases isoflavones can be qualified as EDs or as drugs, and should be used under medical supervision. The National Toxicology Program (NTP) in the USA demonstrated in multigenerational studies the oestrogenic and reprotoxic effects of genistein and its carcinotoxicity on the mammary and pituitary glands in Wistar rats  (National Toxicology Program, 2008a; National Toxicology Program, 2008b).
Comparison of in vitro effects When ED effects are studied in vitro, it is found that genistein and daidzein are usually more potent oestrogens and thyroid disruptors than synthetic compounds that are now banned in European countries. See "Table  for  comparisons" in the Mendeley data repository at https://data. mendeley. com/datasets/dk8gsx2r4j/9. This table gathers data obtained in different in vitro systems by four different authors and genistein and oestradiol can be considered as reference compounds. In all cases except for 4-nonyl-phenol, an alkyl-phenol found in cleaning products with strong anti-thyroid activity, the effect of genistein was greater than that recorded for other synthetic compounds.