dataesr/scientific-paragraphs-categorization huggingface dataset:
The same metric used for ZG is used for PSL: positive/ negative gradient during CW is around 1625 Pa while CMIP5 models tend to underestimate (for more than 80% of them) this value with 1300 Pa on average. These patterns are less persistent in ERA-Interim (until 7 days before) than in CMIP5 models (Supplementary Fig. 5  Same as Fig. 2  but for downward longwave radiation (RLDS) (ERA-Interim for reanalysis dataset). Units: W/m. 2  Figure  S4  and Fig. 9 ). CMIP5 models simulate very well PSL patterns during CW (r > 0. 9 except fgoals-g2 with 0. 77). Surface wind speed anomalies are closely linked to dynamical patterns of ZG or PSL. Anomalies of some m/s, with a direction North-East/South-West along blocking pressure structures, bring cold air masses from Siberia, Eurasia or the North Pole (not shown).
Acknowledgements We acknowledge the  E-Obs dataset  from the  EU  project  ENSEMBLES  (http:// ensem bles-eu. metoffi ce. com) and the data providers in the  ECA&D  project (http:// eca. knmi. nl). We thank the  ECMWF  for providing  ERA-Interim  (http:// apps. ecmwf. int/ datas ets/ data/ inter im_ full_ daily/). We also acknowledge the  World Climate Research Programme 's Working Group on Coupled Modelling, which is responsible for CMIP5 (http:// cmip-pcmdi. llnl. gov/ cmip5), and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. We would thank  Sébastien Denvil  (IPSL) who, in the frame of  PRODIGUER  project, gave access to CMIP5 outputs on CICLAD server. Finally, we thank  Stéphane Goyette  from the  University of Geneva  for reviewing an early version of this manuscript and for his valuable comments.
Statistical analysis All analyses were performed with R-Studio, version March 1, 1073  (RStudio Team, 2020). Survival of gammarids to laser treatment was analyzed using the Cox Proportional Hazards regression model with survival time as a dependent variable and laser treatment, infection status (infected or uninfected) and the interaction of both as predictors (survival package, v. 2. 44-1. 1; Therneau, 2021). We computed Type-II likelihood-ratio tests for each covariate in the model using "Anova" function in the car package v. 3. 0-11  (Fox and Weisberg, 2019). We also checked model assumption of proportional hazards by visual inspection of scaled Schoenfeld residuals against time, for each covariate. We compared the proportion of evaginated cystacanth in each laser treatment to the unexposed control the using Fisherʼs exact test on contingency table  (stats package, v.
Sporulating cells exposed to divalent cations depletion or lower oxygen availability produce spores with a lower amount of leg in the crust To evaluate the impact of the sporulation conditions on the amount of Leg on the spore surface, crust samples were hydrolyzed,  The conditions affecting the hydrophobicity and adhesion of spores when applied during sporulation were tested on mature spores. Spores were produced in optimal condition (Spo8), washed and suspended in a Spo8 medium modified by removing the NB to prevent spore germination (Spo8 -NB) and subjected to the -CaCl2, -MgSO4, -O2, -O2 + CO2, peracetic acid, H2O2 or pH 5 conditions. After 72 h of incubation, the surface hydrophilic/ hydrophobic property of spores was evaluated by MATH assays. The data presented in the table are the means with SDs of at least three independent experiments.
, 2019b). These data strongly suggest that Rha and Leg play an important role in spore surface and adhesion properties. Therefore, it seems likely that the increased adhesion of spores obtained after sporulation in divalent cations depletion or oxygenlimited conditions is due to a decrease in the amount of a glycan containing Rha and Leg in the crust. On the other hand, the increased adhesion of spores produced under oxidizing conditions cannot be explained by the modification of the crust glycans. We also evaluated the impact of the sporulation conditions on the relative amount of the CotY and CgeA proteins in the crust. CotY is one of the morphogenetic proteins and the main structural protein of the crust of B. subtilis spores  (Bartels et al. , 2019). Indeed, expressed in E. coli, CotY can arrange intracellularly into highly stable honeycomblike structures through processes of self-assembly  (Jiang et al.
Acknowledgement This study was supported by the  French Government  through the  "Investissements d'avenir" (Investment for the Future) program  of the  Agence Nationale de la Recherche (National Agency for Research)  under award number  ANR-10-LABX-22-01-SOLSTICE. This work also received regional support from  H2020   SFERA   III SEP-210489599_WP7  on  Desalination and Water Treatments (DWTs).
Individual data A female was considered adult when she reached menarche. The reproductive state of each adult female was monitored on a daily basis. A female could be assigned as: (i) lactating, for the period until the female resumed cycling after an infant birth; (ii) cycling, including both swollen females in estrus (i. e. , sexually receptive with a perineal swelling) and non-swollen females (i. e. at other stages of their menstrual cycle); (iii) pregnant, with pregnancy being determined post hoc following an infant's birth when field observers were absent around conception, and encompassing the six months between the conceptive cycle and the birth. Alternatively, when observers were present, a conception was determined based on the interruption of cycling combined with the subsequent reddening of female paracallosal skin following the first third of pregnancy, and was usually confirmed by a birth.
2009; Kahumbu and Eley 1991). Females' parity was determined using long-term life history data and defined as: nulliparous (before the birth of her first infant), primiparous (between the birth of her first and second infant) and multiparous (after the birth of her second infant). Female social rank was established annually for each group using ad libitum and focal observations of agonistic interactions between adult females: supplants, displacements, attacks, chases and threats  (Huchard and Cowlishaw 2011). We computed a linear hierarchy using Matman 1. 1. 4 (Noldus Information Technology, 2013) , and then converted to a relative rank to control for group size. Each female was thus assigned one rank per year, ranging from 0 (lowest ranking) to 1 (highest ranking). Each year, we also computed the number of adult females in each group.
Individual reproductive data To test our hypotheses, we considered two measures of female fitness, namely the interbirth interval ('IBI') duration and offspring mortality before weaning, and two measures of the timing of female reproduction, namely the monthly probabilities of conception and of cycle resumption. As baboons are not followed throughout the year at Tsaobis, we had to estimate dates of conceptions, births and cycle resumptions in a number of cases. The dates of those unobserved events-as well as the number of days of uncertainty around those events-were established using a combination of photographs and field observations of infant fur and skin color (ears, eye contours, hands and feet, muzzle, muzzle tip, and ischial callosities), following a protocol detailed in a recent study  (Dezeure et al.
Infants born later than August 2018 were not considered as their survival outcome at 550 days was unknown. Four infants that disappeared between two consecutive field seasons (in the absence of observers) were omitted because we could not establish whether the age of death was before or after 550 days. In our final dataset, a total of 39 of 195 infants died before reaching 550 days of age, with mortality occurring at a median age of 74 days (range 1-284 days, n = 17 known dates of death).
2015). It has previously been used as an indicator of habitat quality for the Tsaobis baboons  (Baniel et al. 2018a; Dezeure et al. 2021b ) and other baboon populations  (Zinner et al. 2001). We computed home ranges for each group using kernel density estimates and the adehabitatHR package ('kernelUD' function)  (Calenge 2006)  based on the daily 30-min GPS locations from 2005-2019 (in Figure  1 , we plotted NDVI values for the J group home range; the two other groups' range showed identical patterns). We then extracted the mean NDVI per 16 day-period on a 500 m × 500 m resolution (these 16-days windows are imposed by the resolution of the NASA datasets) across these periods using the MODIS13A1 data provided by NASA  (Didan et al. 2015)  within these home ranges. Daily NDVI was computed by linear interpolation and then averaged to obtain a monthly value (see also  Dezeure et al.
Models 3 and 4 In the case of Models 3 and 4, because seasonal reproduction is usually characterized by a mating season (determined by the seasonality of female fertility or sexual receptivity) and/or a birth season (determined by the seasonality of conceptions), we tested our hypotheses in relation to both the monthly timing of cycle resumptions, i. e. , the beginning of the mating period for each female (Model 3), and the monthly timing of conceptions (Model 4). We did not analyze births because conceptions and births were highly dependent in our dataset (most conceptions had been estimated based on the dates of birth), and because females should have more flexibility to adjust the timings of conceptions than births. To calculate the 'cycle resumption' response variable (Model 3), we assessed the monthly probability that a female would resume cycling during those time windows in which cycle resumption was possible, i.
Statistical tests Statistical analyses were conducted in R version 4. 0. 2 (R Core Team, 2018). To test our hypotheses with our four mixed models, we used the 'lmer' (for LMM, i. e. Model 1) or 'glmer' (for binomial GLMMs, i. e Models 2, 3 and 4) function of the lme4 package  (Bates et al. 2015). The distribution of residuals were checked using the 'qqPlot' function of the car package for LMMs  (Fox et al. 2019 ) and using 'simulateResiduals' from DHARMa package for binomial GLMMs  (Hartig 2020). All quantitative variables were z-transformed to have a mean of zero and a standard deviation of one in order to facilitate model convergence. When the fits obtained were singular, we double-checked the results by running the exact same models with a Bayesian approach, using the 'bglmer' function from the blme package  (Dorie 2015).
We found that the results were qualitatively similar and this extra step can be found in the code uploaded into the Dryad Digital Repository https://doi. org/10. 5061/dryad. dr7sqvb1n (Dezeure et al. 2022). Uncertainty in the dates of conceptions, births, and cycle resumptions were taken into account in all models, by running 1000 models with randomized dates (Supplement, Section S1). We pooled the 1000 obtained estimates for each fixed effect of each model using Rubin's rules (Van Buuren and Groothuis-Oudshoorn 2011). Briefly, the estimates are simply averaged, but not their standard errors, as both the variation between imputations and within an imputation must be taken into account (see Supplement, Section S1 for more details on such computations). We thus extracted and presented in the Results section (Tables  2 3 4 5 ) the mean estimates and their pooled standard errors, along with their 95% confidence intervals and associated P-values.
Section S2. Characterization of Tsaobis environmental variation We considered four environmental aspects to characterize environmental variation at Tsaobis: the photoperiod (daytime length), temperature, rainfall and vegetation cover (food availability). First, we extracted these four environmental factors as follows: (i) Daily daytime length at Karibib (situated 60km north of Tsaobis) was computed using sunset and sunrise time in this town from a website ('https://dateandtime. info'), then converted into minutes and averaged per month. (ii) Mean daily daytime land surface temperatures over an 8-day period per pixel of 1km*1km resolution were obtained using MODIS data (product MOD11A2) provided by NASA  (Wan et al. 2015). These data were extracted from a rectangular geographic area encompassing the global ranging area of the Tsaobis baboons, computed using GPS locations collected by observers every 30 minutes when following the study groups.
We used the minimal and maximal latitude and longitude recorded between 2005 and 2019, producing a rectangular area of 14km*19km. We extracted the mean pixel value for every 8-period in this area, and further compute the monthly means of the daily temperatures (mean pixel values) across 2004-2019. (iii) Daily rainfall was obtained at 0. 25*0. 25 degree resolution (corresponding to 28*28km at this latitude) from satellite data sensors (product TRMM 3B42)  (Huffman et al. 2016 ) available on the Giovanni NASA website, using the same geographical area as for temperatures. Monthly accumulated rainfalls (summed across daily values) were subsequently averaged between 2004 and 2019. (iv) The method of extraction of NDVI, our proxy of food availability, reflecting vegetation cover, is provided in the main text and in a recently published paper  (Dezeure et al.
During this model selection process, some variables had very close AIC values (ΔAIC < 2, see Table  S2 ) suggesting that they were equally supported. In such cases, we re-ran the final model by including the variable with the second lowest AIC value (instead of the variable with the lowest AIC value) to check whether it would affect our results. We found that the results were qualitatively similar and this extra step can be found in the code uploaded into the Dryad repository).
2021a ). We then added (or removed) to this birth date a proportion s of the deviation (when s equals zero, all birth dates are unchanged, and when s equals 1, all births occur at the mean birth date). By modifying the value of s from 0 to 1, we were able to test the effect of group reproductive synchrony on birth seasonality on an increasing range of population-level reproductive seasonality. The results of these simulations are presented in Figure  S4. The code used for this simulation is available in the following Dryad repository: https://doi. org/10. 5061/dryad. dr7sqvb1n TABLES  We plotted the seasonal NDVI ('NDVI_S') per month in green considering December 2018 as time 0 (and so, for example, December 2017 is indicated with -12). We tested the effect of the mean NDVI_S over the X past months, X going from 0 to 12, on female cycle resumption (Model 3) and conception (Model 4) probabilities.
Acknowledgements We thank all the field research assistants and volunteers who work at the Tsaobis Baboon Project between 2005 and 2019 and contribute to build this long-term dataset. We also would like to thank two anonymous reviewers and the associate editor  Emily Duval  for their valuable comments. This research was carried out with the permission of the  Ministry of Environment and Tourism , the  Ministry of Land Reform , and the  National Commission on Research, Science, and Technology. We further thank the Tsaobis beneficiaries for permission to work at Tsaobis, the  Gobabeb Namib Research Institute  for affiliation, and  Johan Venter  and the  Snyman and Wittreich  families for permission to work on their land. This study was funded by a grant from the  Agence Nationale de la Recherche  ( ANR ERS-17-CE02-0008 ,  2018-2021 ) awarded to EH.
Lactic acid fermentation of plantbased products is commonly applied for improving product palatability and nutritional and health-promoting quality  [6, 20, 45]. Products such as tempeh (fermented soybean) and fermented tofu were not included because they were not originally designed as meat alternatives  [46]. Recently, the use of precision fermentation is emerging to unlock the potential of alternative products through providing targeted ingredients with particular features to deliver a unique dairy/meat-like experience. According to GFI database (https://gfi. org/resource /alternative-protein-company-database/ accessed on 20 September 2022), 151 startups use fermentation in developing plant-based alternatives, where precision fermentation (n = 68, 45%) attracts the highest interest, followed by fermentation to obtain protein-rich biomass (n = 60, 40%) and classic fermentation (n = 23, 15%).
According to our search inquiry on the Scopus database, there has been a significant increase in the number of publications and citations reporting on the application of 3D printing in the food sector over the last decade (Figure  3 ). 3D food printing integrates digital gastronomy with additive manufacturing technology  [161, 162]. Applications of 3D printing in the food sector are gaining increasing relevance due to their high potential in the production of personalized food, the reduction of food waste, and time and energy savings among other benefits  [162] [163] [164]. The combination of 3D food printing with AI can increase exploration of novel protein sources from plants, insects, fungi, and algae  [165]. AI and machine learning can be applied to perform a thorough analysis of ingredients that can be used in the plant-based industry to produce alternative products with similar molecular structure, taste, and texture to products of animal origin  [166, 167].
Plant-Based Foods and Drinks Number of Products and Percentage 1 587 597 611 488 Number of products 253 333 351 453 173 9 6 11 10 23 27 40 49 59 68 96 120 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Foods Bakery 1371 (31. 2%) Dairy alternatives 1152 (26. 3%) • "Yoghurt" 420 (9. 6%) • Hard "cheese" and semi-hard "cheese" 210 (4. 8%) • Soft "cheese" and semi-soft "cheese" 188 (4. 3%) • Processed "cheese" 141 (3. 3%) • Ice cream 100 (2. 3%) • Drinks 50 (1. 1%) • Fresh cheese and cream cheese 35 (1%) • Margarine 8 (0. 18%) Sauces and seasonings 467 (10. 2%) Meat alternatives 378 (8. 6%) Ready-to-eat meals 312 (7. 1%) Vegetables 93 (2. 1%) YearFigure 2. Evolution of launches of fermented plant-based foods in the global market. A search was conducted on Mintel GNPD (Global New Products Database) on 15 September 2022.
Based Foods and Drinks Number of Products and Percentage 1 Foods Bakery 1371 (31. 2%) Dairy alternatives 1152 (26. 3%) • "Yoghurt" 420 (9. 6%) • Hard "cheese" and semi-hard "cheese" 210 (4. 8%) • Soft "cheese" and semi-soft "cheese" 188 (4. 3%) • Processed "cheese" 141 (3. 3%) • Ice cream 100 (2. 3%) • Drinks 50 (1. 1%) • Fresh cheese and cream cheese 35 (1%) • Margarine 8 (0. 18%) Sauces and seasonings 467 (10. 2%) Meat alternatives 378 (8. 6%) Ready-to-eat meals 312 (7. 1%) Vegetables 93 (2. 1%) Drinks Nutritional drinks and other beverages 260 (5. 9%) Carbonated soft drinks 109 (2. 5%) Alcoholic beverages 40 (0. 9%) Juice drinks 39 (0. 9%) Sports and energy drinks 8 (0. 2%) Ready-to-drink beverages 4 (0. 1%) 1 Total of fermented plant-based products = 4379. A search was conducted on Mintel GNPD (Global New Products Database) on 15 September 2022.
A search was conducted on Mintel GNPD (Global New Products Database) on 15 September 2022. Date: from 1 January 1996, to 15 September 2022. The inclusion criteria of the search were as follows: the Super-Category matches Food and Drink, the Claims match one or more of [Vegan/No Animal Ingredients; Plant Based], and Ingredient Search matches Fermented as one of the Ingredients. A total of 4379 products were retrieved.
Data processing and analysis choices In this paper, we study potential 'worst-case' cold winter conditions in Central Europe. We focus our analysis as an illustration on the spatial domain of Germany 2. Our analysis is based on the ERA5 reanalysis dataset  (Hersbach et al. , 2020) , and we analyse daily and seasonal mean (DJF) temperature anomalies. Daily anomalies are computed by subtracting a 31-day moving average seasonal cycle based on the 1981-2010 reference period. Seasonal anomalies are calculated from daily anomalies. The analysis of warming trends across the paper is conducted in terms of global mean warming levels: That is, the trends are estimated as a function of the 4-year smoothed global mean surface temperature in ERA5 similar to World Weather Attribution analyses  (Philip et al.
The first dynamical adjustment approach (dark blue line in Fig. 1 ) uses ERA5 to train the regression model, and the spatial pattern of sea level pressure (SLP) over a circulation domain over Europe and the North Atlantic (45 • W-35 • E, 22 • N-72 • N). This approach is identical to  Sippel et al. (2020). Because of the risk of overfitting when training based on the relatively short ERA5 period, we estimate for each year y, an individual regression model that does not use y and the adjacent years y -1 and y + 1. We use a second dynamical adjustment approach where we train the regression model based on the CESM2-LE  (Rodgers et al. , 2021)  warming. The obtained regression model is fully independent from the observational record (trained on CESM2-LE), and is applied subsequently to the ERA5 dataset for comparison (light blue lines in Fig.
For consistency with the other analyses, results are therefore reported for DJF mean temperatures. All analysis was carried out using the extRemes package in R  (Gilleland and Katz, 2016) ; model fitting was carried out over negative temperatures to ensure stability of the parameter estimates  (Coles, 2001). The distribution of the DJF temperatures is assumed to be dependent on the 4-year smoothed ERA5 Global surface air temperature anomaly (GSAT) with respect to 1981-2010, with the location parameter assumed to be a function of the GSAT anomaly. Alternative nonstationary models, in which the scale or shape parameters were also allowed to vary with GSAT, were also fitted, and likelihood ratio tests used to select the most appropriate model to represent this time series  (Coles, 2001)  (Theorem 2.
7); however, none of the more complex models were found to improve the fit enough to justify the use of an additional parameter. Having estimated the parameters of this nonstationary distribution, we compute the return period of the observed 1963 DJF temperatures at the 2023 GSAT anomaly. A bootstrap procedure is used to estimate a 95% confidence interval for this return period  (Efron and Tibshirani, 1994) : whole years are resampled with replacement to construct a synthetic dataset of the same size as the original, and GEV parameters estimated from the resulting sample are used to compute the 2023 return period of the 1963 DJF temperatures. This procedure is repeated 1000 times, and the 0. 025-and 0. 975-quantiles of the estimated return periods give the bounds of the central 95% confidence interval for the return period of the 1963 event in the 2023 climate.
the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101003469 ('eXtreme events: Artificial Intelligence for Detection and Attribution', XAIDA). We acknowledge the CESM2 Large Ensemble Community Project and supercomputing resources provided by the IBS Center for Climate Physics in South Korea, details provided in Rodgers et al. (2021), doi:10. 5194/esd-12-1393-2021. Furthermore, we acknowledge 'Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS), 17. 07. 2023' and ECMWF for providing 355 ERA5 and ERA-20C data.
Motivation A well-constructed nest is a key element of successful reproduction in most species of birds, and nest-building strategies vary widely across the class. Macroecological and macroevolutionary studies tend to group nest design into a small number of discrete categories, often based on taxonomic inference. In reality, however, many species display considerable intraspecific variation in their nestbuilding behaviour, and broad-level categories may include many functionally distinct nest types. To address this confusion in the literature and facilitate future studies of broad-scale variation in avian parental care, we here introduce a detailed, global comparative database of nest building in birds, together with preliminary correlations between these traits and species-level environmental variables.