dataesr/scientific-paragraphs-categorization huggingface dataset:
Software Packages • R package including ANM, IGCI, PNL, GPI and LiNGAM algorithms available at the URL: https://github. com/ssamot/causality. • Python package including Best mse, RECI, CGNN, ANM, IGCI and LiNGAM algorithms available at the URL: https://github. com/Diviyan-Kalainathan/CausalDiscoveryToolbox.
Gompertz statistical analysis Regression analysis was performed using R studio software (v. 3. 0. 2), with the R Gompertz fitting script that contains grofit package, which can be found at http://cran. r-project. org/package=grofit. grofit package was developed to fit many growth curves obtained under different conditions in order to derive a conclusive dose-response curve. It fits data to different parametric models and in addition provides a model-free spline method to circumvent systematic errors that might occur within application of parametric methods. This attribute increases the reliability of the characteristic parameters (e. g. lag phase, maximal growth rate, stationary phase) derived from a single growth Red dots represent oxidation events. Variants of the same protein ( proteoforms) characterized by stable tertiary structure are intrinsically more resistant to oxidative damage and will experience oxidation with a longer delay, compared with disordered/more flexible proteoforms.
m1, m2 and m3 stand for three proteoforms (as an interpretation of data in figure  6 ) and their intrinsic oxidability is symbolized by the drawings above the figure. royalsocietypublishing. org/journal/rsob Open Biol. 9: 180249 curve  [64]. For the statistical analysis in the R script, time ¼ c variable was obtained experimentally by micromanipulations as the time of death, while mort ¼ c variable, obtained the same way, represented the percentage of death among yeast cells. Plot (MyModel) of the R script outputs three Gompertz parameters (lag phase, maximum growth rate, maximum slope), and their standard error.
Live cell imaging and image analysis for counting protein aggregates The slide was mounted on VOLOCITY software (v. 6. 3; Perkin Elmer)-driven, temperature-controlled Nikon Ti-E Eclipse inverted/UltraVIEW VoX (Perkin Elmer) spinning disc confocal set-up. We also employed the auto-focus system (Perfect Focus, Nikon), and Nano Focusing Piezo Stage (NanoScanZ, Prior Scientific). Images were recorded through 60xCFI PlanApo VC oil objective (NA 1. 4) using coherent solid state 488 nm/50 mW diode laser with DPSS module, and 1000 Â 1000 pixels 14 bit Hamamatsu (C9100-50) electron-multiplied, charge-coupled device (EMCCD). The exposure time was 300 ms, and 5-10% laser intensity was used. The images were analysed by using IMAGEJ software. The number of cells with Hsp104-GFP foci was counted manually.
A total of 466 WT OGT cells during 12 h and 207 petite OGT cells during 35 h were examined. Data accessibility. This article has no additional data. Competing interests. We declare we have no competing interests. Funding. Swiss Fondation Nelia and Amadeo Barletta funded our research from 2012 to 2015. Ira Milosevic (European Neuroscience Institute, Goettingen) funded (Emmy Noether Young Investigator Award from the Deutsche Forschungsgemeinschaft) and supervised the spinning disc fluorescent microscopy of budding yeast aggregates.
Acknowledgements. We are grateful to  Monsieur Jean-Noe  ¨l Thorel, the  Fondation Jean-Noe ¨l Thorel, Naos group and Orbico company  ( Mr Branko Roglic ) for sponsoring MedILS and our research on biological robustness, ageing and diseases in MedILS. We thank  Thomas Nystrom  for the gift of Escherichia coli ribosomal fidelity mutants. M. R. thanks  Matthew Meselson ,  David Grainger ,  Philippe Even ,  Zoran Dermanovic ,  Francois-Xavier Pellay  and  Adam de Graff  for extensive discussions in relation to this paper. Matea Peric ,  Marina Musa ,  Anita Lovric  and  Marina Rudan  participated in the measurement of replicative lifespan for budding yeast strains. Matea Peric  performed the Gompertz equation fitting. Mikula Radman  helped with drawings (figures 1, 3, 4 and 8).
Communication was interrupted during the Martian period, and daily working schedules were emailed. Protocols were set in place in case of medical emergency, but did not need to be implemented. The subjects did not have any medication under confinement except for brief application of topical antiinflammatory (diclofenac topical gel). Measurements and samplings were carried out at eight timepoints: Baseline data collection prior to confinement (B), six time-points for each month of confinement (M1 to M6), and Recovery data collection post-confinement (R). The subjects were trained to perform measurements and samplings by themselves as usually occurs during isolation studies and space missions. Support manual provided step-by-step descriptions and troubleshooting for each procedure. CELSS modules were kept under artificial lighting conditions.
Body Weight, Body Composition, Fluid Compartments, and Plasma Volume Evolution Bio-impedance measurements with multi-frequency impedance device Hydra ECF/ICF 4200 (Xitron Technologies) were performed as described in  Coupe et al. (2013). The subjects were weighed prior to measurements, and body weight data were used for calculations. We estimated lean and fat mass, as well as total, extracellular, and intracellular water content. Percent changes in plasma volume were calculated from changes in hemoglobin (Hb) and hematocrit (Hct) using the Dill and Costill method as described in  Navasiolava et al. (2010) and De Abreu et al. (2017).
Central Hemodynamics and Autonomic Regulation at Rest Finger blood pressure wave and ECG were recorded continuously for 10 min at rest in a seated position. Beat-to-beat heart rate and blood pressure (systolic, diastolic) were calculated from the signal using specific Cardiospace software. Autonomic cardiac modulation in resting state was estimated via HRV markers -normalized low and high-frequency spectrum power (LF, HF) and spontaneous baroreflex sensitivity as detailed in De  Abreu et al. (2017).
Behavioral Activity via Ethological Monitoring Ethological monitoring is based on a quantitative description of spontaneous voco-mimo-posturo-gestual activities during assessment periods. Results of monthly ethological monitoring in CELSS during meals are reported elsewhere  (Tafforin et al. , 2019). The present paper describes ethological data recorded during the monthly measurements using a Cardiospace system. Monitoring was performed only under confinement, so we have no baseline or recovery data. Each set of Cardiospace measurements lasted approximately 4 h per subject. In total, we analyzed about 90 h of video recording (4 h × 4 subjects × 6 time points) using The Observer XT R 14. 0 software  (Tafforin, 2017). We measured occurrences of behavioral descriptors (acts per min) on the total analyzed duration per subject.
Air, Water, and Food Regeneration In this real-scale simulation, 100% of oxygen and ∼99% of water were regenerated, and ∼70% of food was produced within the module. Air recovery and purification, as well as data on toxic trace gases, are detailed in  Dai et al. (2018a,b). Bio-based water recovery is described in  Li et al. (2018). In the water cycle, sanitary and other wastewater went to the nutrient solution storage tank for plants, and condensate water from plants was purified with a modified membrane bio-reactor process  (Li et al. , 2018)  and used for drinking and washing. Plant care was performed daily; workload increased during harvest.
Exercise and Fitness Total number of exercise bouts of different type performed by each subject during 6-month confinement, as well as global exercise time per month, are shown in Figure  3. Detailed individual data on exercise in CELSS (except for tai chi which was not documented) are reported in Supplementary Table  2. Altogether four subjects performed during 6 months 112 exercise bouts of total duration of 3,117 min (52 h). Treadmill was the most frequent exercise under confinement (15 ± 9 bouts per subject with mean bout duration of 27 min). Subjects exercised less at the second half of confinement, with minimum during Martian period at days 72-108 (time spent per subject on exercise fell from 191 ± 103 min/mo -on M1 to 72 ± 31 min/mo -on M6; at M4 (days 91-120) it consisted 36 ± 11 min/mo).
Muscle Tone, Back Pain, and Spine Mobility Masseter tone increased under confinement, with a peak for subject C at M2 (+38%) and for subjects B, C, and D at M5 (+6 to 14%) (Figure  11 ). Paravertebral muscle tone decreased, with a drop in M1 of 10 ± 6% in average for totality of m. erector spinae (15-20% for cervical, 15-25% for thoracic, and 3-6% for lumbar erector spinae), followed by steady state for M2-M6. Of note, one subject (A) had 6% increase in M1 at lumbar level (Figure  11 ). For m. rectus femoris, muscle tone was largely unchanged (data not shown). Three subjects reported periodic back pain with intensity 1 to 5 on a 0-to-10 scale. Pain episodes were related to activities and were relieved by stretching, sleeping, and local analgesics (two subjects applied diclofenac topical gel for 1 week at the beginning of the second month of confinement, in a distance from endothelial assessment at M2 which was at the end of the second month).
Limitations of Direct Comparison With Mars-105 and Mars-520 Studies Both the Mars500 and CELSS facilities were designed as sealed habitats with interconnected modules under artificial light, in absence of natural solar radiation. But direct comparison of the data from these studies is difficult because of major differences in experimental conditions. Mission duration, available space, workload, scenario, nutrition, and operational stress differed. In both Mars500 campaigns, the crew was larger (6 subjects each), international (Mars-520: 3 Russians, 2 West-Europeans, 1 Chinese), and only included males. Furthermore, the Mars500 platform was not designed as a CELSS (although it contained a small experimental greenhouse), so plant care workloads were different (for a typical workday during the Mars-520 simulation, see Supplementary Materials in  Yi et al.
Restricted space is associated with higher level of stress and inactivity and minimizes opportunity to retreat from the group during tense situations  (Pagel and Choukèr, 2016). Caloric intake in Mars500 was more important, predefined depending on age and body weight, and consisted of ∼3,000-3,200 kcal/day (for calculation see  Strollo et al. , 2018) , which meant no or limited caloric decrease. The Mars-520 protocol also included 3-step dietary salt reduction from 12 g to 6 g NaCl. Moreover, Mars-520 was three times longer. Previous data suggest that isolation duration may play a major role in deconditioning  (Pagel and Choukèr, 2016). Chinese Long-Term Confinement in CELSS and an All-Chinese Crew Historically, access to space was provided by American and Russian space programs. The Shenzhou 5 mission in 2003 made China the third country to independently send humans into space.
Aims. We present a comprehensive study of the supernova remnant (SNR) population of the Small Magellanic Cloud (SMC). We measure multiwavelength properties of the SMC SNRs and compare them to those of the Large Magellanic Cloud (LMC) population. Methods. This study combines the large dataset of XMM-Newton observations of the SMC, archival and recent radio continuum observations, an optical line emission survey, and new optical spectroscopic observations. We can thus build a complete and clean sample of 19 confirmed and 4 candidate SNRs. The homogeneous X-ray spectral analysis allows to search for SN ejecta and Fe K line emission, and to measure interstellar medium (ISM) abundances. We estimate the ratio of core-collapse to type Ia supernova rates of the SMC based on the X-ray properties and the local stellar environment of each SNR.
2004; Misanovic et al. 2006) , and the SMC  (Haberl et al. 2012b). A summary of the important steps of the pipeline was given in MHK16. The difference with  Haberl et al. (2012b)  is that data were reprocessed with version 16. 0. 0 of the XMM-Newton Science Analysis Software 1. The resulting event lists and associated good time interval files (gti, one file per detector) were used as the primary source for subsequent analysis.
The FWC images were scaled by f FWC and removed from the science image to create the backgroundsubtracted image. Only FWC exposures in full-frame mode are available for MOS detectors, excluding all other modes from our analysis. We combined all suitable observations of an SNR to produce an image centred on the source. In each band, we merged the images from pn and both MOS. The smoothing of the combined images was done in adaptive mode with the SAS task asmooth. It calculates a library of Gaussian kernels such that the resulting images reach a minimum (Poissonian) signal-to-noise ratio of 5 everywhere. Regions of good statistics (e. g. bright sources) are A&A proofs: manuscript no. smcsnrs_arxiv smoothed with a small kernel, whereas fainter regions are more thoroughly smoothed. The minimum kernel size for adaptive smoothing is either 10 or 20 , depending on the available data and the surface brightness of the SNR under investigation.
X-ray spectra We follow the spectral analysis method described extensively in MHK16: we simultaneously fit source and background spectra (hereafter SRC and BG), where the latter is explicitly modelled rather than subtracted. This is critical for the analysis of faint extended sources such as SNRs in the SMC. We correct the event lists for vignetting with the SAS task evigweight prior to extraction. This accounts for the energy-dependent effective area variation across the extents of SNRs and background regions. The redistribution matrices are produced by the SAS task rmfgen, and the ancillary response files by arfgen. The latter is used in unvignetted mode (equivalent to a flat detector map), returning the on-axis effective area, because the vignetting is already corrected event-wise. We use the same event pattern for spectra as for imaging.
We use the spectral-fitting package XSPEC  (Arnaud 1996)  version 12. 9. 0e, with spectra rebinned with a minimum of 25 counts to allow the use of the χ 2 -statistic. Interstellar absorption is reproduced by the photoelectric absorption model phabs in XSPEC (or vphabs, where the prefix "v" indicates that abundances can vary), using cross-sections set to those of  Balucinska-Church & McCammon (1992). The extraction regions for SRC and BG spectra are defined manually, usually guided by the X-ray contours. Simple shapes (circles, ellipses) are preferred, but an arbitrary shape (e. g. polygonal region) is also used if required. Point sources detected during the pipeline data reduction with the task edetectchain are excluded. Details of the definition of extraction regions are given in MHK16. When defining extraction regions, we also screen out observations not suited for spectroscopy (that might have been used for imaging).
We correct for this by including an ad-hoc multiplicative spline function in the model of the instrumental background. The best-fit models are used in subsequent fits (including astrophysical signal) with no free parameter, as the instrumental background averaged in the FWC dataset matches generally well with the one in the SNR spectra. One component of the background is the SMC diffuse emission. This was studied by  Sturm (2012) , who modeled the diffuse emission with a thermal model : S SMC diff = phabs N Gal H × vphabs N SMC * H , 0. 2Z S SMC apec (1) where S SMC apec is the emission from an apec model 4  at temperature kT SMC and normalisation N SMC. The foreground column density N Gal H at the location of each analysed source is taken from the H i maps of  Dickey & Lockman (1990). N SMC * H is between 0 and N SMC H , the total line-of-sight column density through the SMC  (Stanimirovic et al.
Objects not included We present here a list of objects previously classified as SNR or SNR candidate that, upon closer scrutiny and in light of the new datasets in radio and X-rays, can no longer be bonafide SNRs. Most of these objects were originally suggested to be (possible) SNRs based on a single feature (e. g. radio, Xrays). None were later confirmed by a multi-wavelength detailed study, although they have been since included in SNR samples and compilations. This attempt at "cleaning" the literature will be beneficial for population studies, making sure they do not include such unrelated objects (as e. g. in  Badenes et al. 2010; Auchettl et al. 2019) , which is likely to introduce biases. N S19 / [FBR2002] J004806-730842 : From the ATCA radio catalogue of  Filipović et al. (2005) , this source is the very confused LHA 115-N 19 (hereafter N 19) H ii complex.
The extent of the SNR was measured using both radio and X-ray contours. MCSNR J0103-7201 : This faint SNR is detected as an Hα circular shell (Fig. B. 6) centered on the long-period X-ray pulsar SXP 1323  (Gvaramadze et al. 2019). Deep radio and co-added Chandra data reveal faint radio and X-ray emission of the shell, thus confirming its SNR status  (Haberl et al. , in prep. ). Interestingly, this is the second case in the SMC of an SNR containing a Be X-ray binary after SXP 1062 (see below), both objects harbouring long-period pulsars (> 1000 s). (Haberl et al. 2012c, Fig. B. 8). The central source is an associated Be/X-ray binary, harbouring a long-period pulsar (SXP 1062). In this work we analysed the diffuse X-ray shell, including more observations that were obtained subsequently for the monitoring of the central binary  (Sturm et al.
Acknowledgements. P. M. and J. B. acknowledge support by the  Centre National d'Études Spatiales (CNES). M. S. acknowledges support by the  Deutsche Forschungsgemeinschaft  through the  Heisenberg professor grants   SA 2131/5-1  and  12-1. The  Australian Compact Array  and the  Australian SKA Pathfinder (ASKAP)  are part of the Australian Telescope which is funded by the  Commonwealth of Australia  for operation as National Facility managed by  CSIRO. This paper includes archived data obtained through the  Australia Telescope Online Archive  (http://atoa. atnf. csiro. au). We used the karma and miriad software packages developed by the  ATNF. Operation of ASKAP  is funded by the  Australian Government  with support from the  National Collaborative Research Infrastructure Strategy. ASKAP uses the resources of the  Pawsey Supercomputing Centre.
After optimizing some parameters of the model to represent the average state of the fish community during the 2000-2009 period, the simulated trophic structure was explored and compared to empirical data. The simulated and stable-isotope-derived trophic levels of fish were in relatively good agreement. Intraspecific variability of the trophic level is high in the five stableisotope datasets but is well encompassed by the model. Despite the hypothesis of opportunistic sizebased predation, the simulation showed a decreasing trend of trophic level with size for four benthic species, a pattern observed empirically for a different set of species in the ecosystem. Model exploration showed that this emerging pattern varies spatially and is both explained by the spatial variability of prey availability and by the independence of trophic and size structures of benthic invertebrates.
, 2014)  providing both a detailed vision of prey actually consumed and a general picture of trophic fluxes and food web topology. In parallel with these field studies based on biological sampling and chemical analysis, theoretical work has focused either on predator-prey interactions (e. g. , Lotka-Volterra) or on network complexity and stability  (Belgrano et al. , 2005). The development of holistic models allowed the coupling of theoretical and empirical approaches by conceptualizing the food web structure of a particular ecosystem based on data and simulating its dynamics. Typically, Ecopath models  (Christensen and Pauly, 1992)  aim at balancing the food web structure of an ecosystem of interest based on observed diets and produce network indicators such as the recycling index, average path length and total system throughput  (Heymans et al.
Calibration The model was calibrated using the calibrar R package with the AHR-ES algorithm (Oliveros-  Ramos and Shin, 2016) , an automatic evolutionary algorithm developed for calibrating stochastic models such as OSMOSE. This algorithm explores a range of values for unknown parameters and uses likelihood objective functions to select the optimal values for the catches and biomass to be comprised within ranges of observed values when available. Landings per species have been extracted from the ICES Fisheries Statistics official database (ICES, 2011a) for the ICES area 7d (corresponding to the EEC) over the period 2000-2009. Total stock biomass estimates are directly available from stock assessment reports for sole and plaice (ICES, 2011b), while for whiting, cod, mackerel and herring, total stock biomass estimates were derived from stock assessments covering a wider area  (ICES, 2012 (ICES, , 2011b) )  and were therefore scaled to the EEC proportional to the relative landings in this area.
As the OSMOSE model is based on opportunistic predation, validation patterns could include emerging features linked to the predation process, such as realized diets and associated TLs or food web structures. Here, we used independent data of TLs calculated from nitrogen stable isotope ratios (SI) measured on the same species in the same ecosystem  (Cresson et al. , 2017 (Cresson et al. , , 2018;; Jennings and van der Molen, 2015; Kopp et al. , 2015 , Mialet et al. , 2017). TL calculations are based on the premise that the nitrogen isotopic ratio (δ 15 N hereafter) is gradually enriched at each TL, a phenomenon called trophic enrichment. TL is thus considered as the isotopic difference between the species of interest and a trophic baseline, i. e. , a proxy of the ultimate organic matter source at the base of the food web, divided by the trophic enrichment factor (TEF).
FP7/2007e2013) under Grant Agreement No. 266445 for the project VECTORS of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS), by the French project EMIBIOS (FRB, contract no. APP-SCEN-2010-II), and by the French government and the region Hauts-de-France under the framework of the project CPER 2014-2020 MARCO. The authors acknowledge the Pôle de Calcul et de Données Marines (PCDM, http://www. ifremer. fr/pcdm) for providing DATARMOR storage and computational resources.
( FP7/2007e2013) under Grant Agreement No. 266445 for the project VECTORS of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS), by the French project EMIBIOS (FRB, contract no. APP-SCEN-2010-II), and by the French government and the region Hauts-de-France under the framework of the project CPER 2014-2020 MARCO. The authors acknowledge the Pôle de Calcul et de Données Marines (PCDM, http://www. ifremer. fr/pcdm) for providing DATARMOR storage and computational resources.
Non vertebral fractures were documented by radiographs. BMD of the lumbar spine (L2-L4) and left hip was measured using a Hologic QDR 4500A device (Hologic, Walhtham, MA). Positioning of the patients and analysis of the scans were done according to the manufacturer's recommendations. Quality control of the device was done using a Hologic phantom every day where a patient was scanned and at least 3 times weekly. TBS ® of lumbar vertebrae (L2-L4) was measured by the manufacturer on DXA using TBS iNsight v2. 2. It was also measured by 2 different observers on EOS ® images blinded to the results of BMD. A dedicated TBS ® software was developed for EOS ® images. The TBS-EOS was integrated on an EOS ® software prototype allowing computing and displaying TBS ® values and maps along with sterEOS TM numerical models of the spine.