dataesr/scientific-paragraphs-categorization huggingface dataset:
Our proposed survey, conducted within a single space mission, will be as sensitive as ten CMB-S4 experiments. The survey will complement the frequency coverage in the gaps between atmospheric windows, and make observations above 300 GHz with angular resolution matching that of the ground experiments. This complementarity will be key to separate the mixture of SZ effects and CIB emission into their individual contributions. • Data from other cosmological probes, most notably LSST, will tighten constraints on the cosmological model; Consistency tests using data from different probes are essential for establishing confidence in a cosmological model. Complementary probes also help lift parameter degeneracies. Our proposed survey builds on the technological developments currently ongoing for the next generation experiments in CMB observations and line intensity mapping.
(27) C1 deficiency is a rare disease, and therefore its natural history and genotype-phenotype relationships have not been characterized in large, genetically defined cohorts. We therefore aimed to provide detailed insights into the natural history and genotype-phenotype associations and to assess the effect of SBD on native liver survival (NLS). Since 2017, we have been collecting patient data in a global consortium: NAPPED (NAtural course and Prognosis of PFIC and Effect of biliary Diversion). NAPPED has become a large, international initiative that aims to characterize the natural course of disease in severe FIC1 (and severe BSEP deficiency) to assess the effect of genetic, clinical, and therapeutic parameters on long-term outcome.
Data collection, patient selection, and genetic categorization Since its start in 2017, NAPPED has collected retrospective data on patients with FIC1 deficiency (and severe BSEP deficiency caused by mutations in ATP-binding cassette, subfamily B, member 11 [ABCB11], data which have recently been published  (28)  ). The Childhood Liver Disease Research Network (ChiLDReN) collected data prospectively. NAPPED currently comprises 68 referral centers from Europe, North America, South America, Africa, Asia, and Australia. Data for the present study were collected conforming to the guidelines of the 1975 Declaration of Helsinki. Data collection and management used a prespecified case-record form and was captured using Research Electronic Data Capture (REDCap). (29) Demographic, clinical, and outcome data were collected by investigators within each center, who identified all consecutive patients who had ever been under pediatric care (age 0-18 years) since 1981.
From ChiLDReN, all cases of FIC1 deficiency enrolled in the Longitudinal Study of Genetic Causes of Intrahepatic Cholestasis (LOGIC) since 2007 were included. Data reported in the present manuscript were exported from REDCap May 1, 2020. Patients with pathological compound heterozygous or homozygous ATP8B1 mutations were selected from the database. ) (32)  Patients without available genetic reports or with mutations of no identifiable pathological significance were excluded. Included patients were further categorized based on their genotype vis-à-vis predicted protein truncating mutations (PPTMs) (i. e. , splice site, frameshift due to deletion or insertion, nonsense, duplication); FIC1-A patients harbored no PPTMs, FIC1-B patients harbored one PPTM, and FIC1-C patients harbored two PPTMs.
We further categorized patients with homozygous mutations based on the location of their mutations in the FIC1 protein. Biochemistry at presentation in the tertiary center, as well as prior to SBD and between 2 months and 1 year after SBD, were analyzed. If such information was available from the medical file, pruritus was scored as "absent," "mild to moderate," or "severe" at the discretion of the participating center, which, for statistical purposes, was dichotomized later into "absent" or "present. " Effect of SBD on pruritus was noted as "no improvement in pruritus," "transient (partial or complete) relief of pruritus," or "sustained (partial or complete) relief of pruritus. " Analyses were performed with regard to important clinical events in the form of SBD, LT, or death. Extrahepatic features have not (yet) been documented in the NAPPED REDCap database and are hence not analyzed in the present paper.
Statistical evaluation Continuous variables are expressed as medians and interquartile range (IQR). Non-normally distributed data were analyzed using the appropriate nonparametric methods, including Mann-Whitney and Kruskal-Wallis tests. Differences between categorical variables were assessed using χ 2 , McNemar, or Mantel's test for trend, as appropriate. Unadjusted differences in disease-free survival (DFS) and NLS between patient subgroups were assessed by using Kaplan-Meier estimates and compared using the log-rank test. The following factors were included in the analyses: sex, birth year, age at first visit at referral center, use of medical therapy prior to first visit (e. g. , ursodeoxycholic acid [UDCA], rifampicin, phenobarbital, cholestyramine, antihistamines), occurrence of hepatocellular carcinoma (HCC), serum bile acids (sBAs) (not standardized for fasting/post-prandial state), total serum bilirubin (TSB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyltransferase (GGT), and platelet count (PLT).
Prior to SBD, pruritus had been present in 28 of 29 patients (97%). Post-SBD (i. e. , at least 2 months and maximum 1 year after SBD), pruritus was present in 23 of 29 patients (79%) (P = 0. 13). Retrospective analysis on pruritus data should be interpreted with caution. Nevertheless, some could be derived from the patient files and could provide information of some relevance. In those patients for whom long-term pruritus data were available (n = 23), half seemed to (partially) benefit from SBD: In 11 of 23 patients (48%), no improvement of pruritus was reported, whereas Paired biochemistry data, pre-and post-SBD, were analyzed. We noted a decrease in sBAs (230 [125-282] to 74 [11-177] μmol/L; median 49% decrease; P = 0. 005; Fig. 4 ). There were no statistically significant differences in the post-SBD sBA levels between FIC1-A (81 [7-191]   μmol/L), FIC1-B (74 [12-296] μmol/L), and FIC1-C (44 [4-136] μmol/L) patients (P = 0.
Discussion This study aimed to define the natural history of FIC1 deficiency and assess the effect of the presence of PPTMs, sBA concentrations, and SBD on long-term outcome. NAPPED herewith presents the largest cohort of genetically defined, FIC1 deficiency patients to date. The present data indicate that less than half of patients with FIC1 deficiency are alive with their native liver by the time they reach adulthood. Surprisingly, the genotype of FIC1 deficiency patients, with respect to presence of PPTMs, did not seem to reliably predict the phenotype. sBA concentrations at baseline (i. e. , <194 µmol/L or 194 µmol/L) and after SBD (i. e. , <65 µmol/L or 65 µmol/L) may provide clinicians some prognostic information during counseling. For example, the proportion of patients who reach 15-year survival with native liver is 3-fold higher in patients with an sBA concentration at presentation below the threshold of 194 µmol/L than in those with sBA concentrations above the threshold.
Accepted Article This article is protected by copyright. All rights reserved We realize that FIC1 deficiency extends beyond the liver, due to expression in tissues such as intestine, pancreas, lungs, and inner ear. 8) 21)  Currently, extrahepatic manifestations of FIC1 deficiency are not documented in our REDCap database, and therefore they could not be analyzed in the present paper. Some results in the present study should therefore be interpreted with caution because we cannot exclude the possibility that factors other than the hepatic phenotype have contributed to decisions regarding SBD or LT. Future research initiatives of NAPPED will focus on elucidating the extrahepatic features and their impact on the disease, both before and after LT. For example, therapy-resistant diarrhea may complicate the posttransplant disease course.
Acknowledgment: We thank  Daan van Wessel  for study concept and design, acquisition of data, analysis and interpretation of data, statistical analysis, drafting of the manuscript, and obtaining funding;  Richard Thompson ,  Emmanuel Gonzales ,  Irena Jankowska ,  Benjamin L. Shneider , and  Etienne Sokal  for study concept and design, acquisition of data, and critical revision of the manuscript for important intellectual content;  Tassos Grammatikopoulos ,  Agustina Kadaristiana ,  Anne Spraul ,  Piotr Czubkowski ,  Patryk Lipiński ,  Nathalie Rock ,  Mohammad Shagrani ,  Dieter Broering ,  Talal Algoufi ,  Nejat Mazhar ,  Emanuele Nicastro ,  Deirdre Kelly ,  Gabriella Nebbia ,  Henrik Arnell ,  Björn Fischler ,  Jan Hulscher ,  Daniele Serranti ,  Cigdem Arikan ,  Dominique Debray ,  Florence Lacaille ,  Cristina Goncalves ,  Loreto Hierro ,  Gema Muñoz Bartolo ,  Yael Mozer-Glassberg ,  Amer Azaz ,  Jernej Brecelj ,  Antal Dezsőfi ,  Pier Luigi Calvo ,  Dorothee Krebs-Schmitt ,  Ekkehard Sturm ,  Wendy van der Woerd ,  Jian-She Wang ,  Liting Li ,  Özlem Durmaz ,  Nanda Kerkar ,  Marianne Hørby Jørgensen ,  Ryan Fischer ,  Carolina Jimenez-Rivera ,  Seema Alam ,  Mara Cananzi ,  Mathias Ruiz ,  Cristina Targa Ferreira ,  Felipe Ordonez ,  Heng Wang ,  Kyungmo Kim ,  Huey-Ling Chen ,  Elisa Carvalho ,  Alexandre Faber ,  Jesus Quintero Bernabeu ,  Estella M.
In addition, the SWW fluctuations have mainly been studied in a latitudinal context, without taking account the influence of the Andes along a W-E longitudinal transect. Some interpretations of Westerlies fluctuations made on the western side of the Andes are indeed located in areas close to the eastern side generating contradictory results with previous studies  (Lamy et al. , 2010). Therefore, this study aims to document environmental and climate variability, mainly related to the SWW influence, in a North Eastern Patagonian sector over the last millennium. The Lake Jeinimeni location provides a unique laminated record that contributes to better understanding the variability of SWW-related precipitation over the last centuries. Both sedimentological (i. e. , varve thickness) and geochemical data (represented by the two first principal components) are correlated with local meteorological data (i.
Axio Imager A2 (Zeiss, Germany) microscope was used to investigate thin sections under nonpolarized and polarized light at the University of Gdanks. After establishing a preliminary model of laminae succession representing annual sedimentation, couplets of laminae were counted on scanned images of thin sections. Counting was done twice by a single person for the whole sediment core with additional third counting restricted only to difficult core sections, in order to avoid possible misinterpretation. Finally, unclear couplets of laminae were included in the chronology as half a year and the counting uncertainty was increased by ±0. 5 years, respectively. Following this step, the uncertainty was cumulatively summed along the chronology. The age model was corroborated by applying 210 Pb, 226 Ra, 232 Th and 137 Cs data that were measured in the upper 16 cm of core LJe14b at EPOC (Univ.
Elemental core scanning An X-Ray imaging system composed with an X-ray tube and a linear X-Ray camera has been used at the EPOC laboratory (Univ. De Bordeaux, France) to obtain an X-Ray image of the core, and gray-scale level of the sediment (data SCOPIX). Both measurements were performed on the archive half-core section. Sediment core scanning was done at a resolution of 2 mm an Avaatech XRF core scanner  (Richter et al. , 2006; Rothwell et al. , 2006)  equipped with a Rh tube on the Al boxes at the EPOC laboratory (Univ. Bordeaux, France). The XRF core scanning was done at 10, 30 and 50KV and 15, 20 and 25s exposure time, respectively. Fifteen elements have been measured: Al, Si, S, K, Ca, Ti, Mn, Fe, Zn, Br, Rb, Sr, Y, Zr and Ba. Semiquantitative concentration profiles of the elements are plotted along the sediment core based on the variations of their peak areas on the XRF core scanner spectra.
Statistic section Geochemical elements obtained from XRF core scanner were analysed through Principal Component Analysis (PCA). PCA produces new sets of variables, called Principal Components (PCs) and only the PCs with eigenvalues >1 explain significantly the total variance of the dataset. Moreover, all the elements do not significantly contribute to the PCs and only those characterized by a communality values ≥ 0. 5 are usually retained for PCA  (Davis 2002). Geochemical data series are compared to monthly-averaged temperature and precipitation records from the local Chile Chico meteorological station, which began reporting in AD 1960  (Hepp et al. , 2018).
In the following section the PCA scores of the main PCs (PC1, PC2) will be reported along core depth to track for lacustrine environmental variability. Among the XRF core scanner dataset, some elements (e. g. , Al, Si, K, Ti and Fe) display similar trends (Fig. 2  and SM Fig. 2 ), and by applying a multivariate statistical analysis such as Principal Component Analysis (PCA), it is possible to disentangle the forcing mechanisms behind the temporal variability (e. g. ,  Avsar et al. , 2014). Four Principal Components (PC) were identified representing 70. 3% of the total variance (Table  3 ). However, according to the communality values, the contribution of Mn (0. 19) is lower than the other elements and was therefore removed from the analysis. After its exclusion, the four PCs explain 74. 6% of the total variance, with 42.
1750AD), in agreement with tree-ring records and glacial advances reported in North Patagonia, and quantitative precipitation reconstructions derived from lacustrine laminated sequences from both North Patagonia and Central Chile. Volcanic Zone (SVZ) as reported in  Stern et al. (2015). Moreover, the glass chemistry is consistent with the signature of the Hudson 1991 eruption (data from  Naranjo and Stern 2004 ). On the right panel, Scanning Electron Microscope photographs and elemental EDX composition of representative glassy samples with circular or elongated gas bubbles: A. E1 4. 5-5 cm, B -E2 7. 4-7. 9 cm. The EDX major chemistry of the observed glasses from both E1 and E2 layer is consistent with a plagioclase composition. underlines the interval characterized by the thickest varves. Its estimated age ca.
calibration curve  (Hogg et al. , 2013). Samples were measured at the Gadam Radiocarbon Laboratory. Table  3. Results of principal component analysis (PCA) on raw XRF core scanner dataset. The table gives the contribution of each principal component in total variance. PCA was performed without Mn because its communality value was lower than 0. 5. Table  5. Overview of regional paleoenvironmental information deduced from published climate archives reported over a 20° latitudinal transect from 33° to 53°S in South America.
Acknowledgements We thank  Jorge Félez  and  Alex Henríquez  from  University of Concepcion  for their help in elaboration of the geological and bathymetric maps;  Isabel Israde Alcantara  from the  University of Morelia (Mexico)  for diatom identification;  Frederic Boulvain  for thin section observation. This research was funded by  WBI-Chile  bilateral collaboration project and by  Chilean Fondecyt  funding  1201277. In addition,  Roberto Urrutia  thanks the project  ANID/FONDAP/15130015  and  Pablo Pedreros the Fondecyt Postdoctoral  funding  3180356.
Viral abundance, production, and life strategy Virus abundances were determined on glutaraldehyde fixed samples (0. 5 % final concentration; grade II; Sigma-Aldrich, St Louis, MO, USA) stored at -80 • C until analysis. Flow cytometry analysis was performed as described by  Brussaard (2004). Briefly, samples were thawed at 37 • C, diluted in 0. 2 µm filtered autoclaved TE buffer (10 : 1 Tris-EDTA; pH 8) and stained with SYBR Green I (0. 5 × 10 -4 of the commercial stock; Life Technologies, Saint Aubin, France) for 10 min at 80 • C. Virus particles were discriminated based on their green fluorescence and suspended sediment concentration (SSC) during 1 min analyses (Fig. S1 ). All cytogram analyses were performed with the Flowing Software freeware (Turku Center for Biotechnology, Finland). Viral production and bacterial losses due to phages were assessed by the virus reduction approach  (Weinbauer et al.
, 2010) , and the V4-V5 region of the 16S rRNA (∼ 411 bp), using the primers 515F-Y (5 -GTGYCAGCMGCCGCGGTAA) and 926R-R (5 -CCGYCAATTYMTTTRAGTTT;  Parada et al. , 2016). Following PCRs, DNA amplicons were purified, quantified and sent to Genotoul (Toulouse, France) for high throughput sequencing using paired-end 2 × 250 bp Illumina MiSeq. Note that although we used universal primer, archaea were mostly not detected, and the prokaryotic heterotrophic communities corresponded essentially to eubacteria; therefore, the taxonomic description referred to the general term bacterial communities. All reads were processed using the Quantitative Insight Into Microbial Ecology 2 pipeline (QIIME 2 v2020. 2; Bolyen et al. , 2019). Reads were truncated at 350 bp based on sequencing quality, denoised, merged, and chimera checked using DADA2 software  (Callahan et al.
, 2016). A total of 714 and 3070 amplicon sequence variants (ASVs) were obtained for 16S and 18S, respectively. Taxonomy assignments were made against the database SILVA 132  (Quast et al. , 2013)  for 16S and PR2  (Guillou et al. , 2013)  for 18S. All sequences associated with this study have been deposited under the Bio-Project ID no. PRJNA693966.
Statistics Alpha and beta diversity indices for community composition were estimated after randomized subsampling to 26 000 reads for 16S rDNA and 19 000 reads for 18S rDNA. Analyses were run in QIIME 2 and in the Primer v. 6 software package  (Clarke and Warwick, 2001). Differences between the samples' richness and diversity were assessed using Kruskal-Wallis pairwise test. Beta diversity was run on the Bray-Curtis dissimilarity. Differences between the samples' beta diversity were tested using PERMANOVA (permutational multivariate analysis of variance) with a pairwise test and 999 permutations. The sequences contributing most to the dissimilarity between clusters were identified using SIM-PER (similarity percentage). A linear mixed model was per-formed with R software (R Core Team, 2020), using the nlme package  (Pinheiro et al.
All effects might be generally enhanced in future climate scenarios. The impact of dust deposition on metabolic processes and the consequences for the carbon and nitrogen cycles and the biological pump based on these minicosm experiments are further discussed in  Gazeau et al. (2021b)  and  Ridame et al. (2022) , and the in situ effect of a wet dust deposition event is explored in  Van Wambeke et al. (2021)  in this special issue. Data availability. The PEACETIME dataset will be available at https://doi. org/10. 17882/75747 (Guieu et al. , 2020b)  upon the publication of all papers in the special issue (2022). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/bg-19-1303-2022-supplement. Author contributions. FG and CG designed the experiment.
All authors participated in the sampling or sample processes. JD analyzed the data and wrote the paper, with contributions from all authors. Competing interests. At least one of the (co-)authors is a member of the editorial board of Biogeosciences. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare. Disclaimer. Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Special issue statement. This article is part of the special issue "Atmospheric deposition in the low-nutrient-low-chlorophyll (LNLC) ocean: effects on marine life today and in the future (ACP/BG interjournal SI)". It is not associated with a conference.
Acknowledgements. We gratefully acknowledge the onboard support from the captain and crew of the R/V Pourquoi Pas? and our chief scientists  Cécile Guieu  and  Karine Desboeuf. We also thank  Kahina Djaoudi ,  Julia Uitz ,  Céline Dimier ,  Philippe Catala ,  Barbara Marie , and  María Perez-Lorenzo , for their assistance in the sampling and analysis of pigments, microbial abundance, DOC concentration, and primary production. We thank the two referees, for their input. Financial support. This study is a contribution to the  PEACE-TIME  project (http://peacetime-project. org, last access:  26 January 2022 , https://doi. org/10. 17600/17000300 ), a joint initiative of the MERMEX and ChArMEx components supported by  CNRS-INSU ,  IFREMER ,  CEA , and  Météo-France  as part of the program MISTRALS, which is coordinated by  INSU.
PEACETIME was endorsed as a process study by GEOTRACES and SOLAS. Part of this research has been funded by the  ANR CALYPSO  attributed to ACB (grant no. ANR-15-CE01-0009 ). Emilio Marañón  has been supported by the  Spanish Ministry of Science, Innovation, and Universities  (grant no. PGC2018-094553B-I00 ). Julie Dinasquet has been funded by a  Marie Skłodowska-Curie Actions International Postdoctoral Fellowship  (grant no. PIOF-GA-2013-629378 ). Review statement. This paper was edited by  Christine Klaas  and reviewed by two anonymous referees.
Statistical analyses For the analyses of both experiments -validation of the judgment bias paradigm (Experiment 1) and the judgment bias test in the tert -/-mutants (Experiment 2) -we used the R software  [27]  packages "lme4"  [28]  and "afex"  [29]  for the linear mixed effects models (GLMM), and the "emmeans" package  [30]  for planned comparisons. Details of R codes used and the original datasets can be found online  [31]. The response variables were the latencies to respond to stimuli, that is, the time it took the fish to enter the experimental arms [positive (P), near positive (NP), ambiguous (A), near negative (NN), negative (N) in experiment 1 and P, A and N in experiment 2] of the behavioural apparatus. Latencies were restricted to the interval between 0 and 60 seconds and were log-transformed.
Acknowledgements The authors thank the  Fish Facility Platform of the Instituto Gulbenkian de Ciência, (Portugal)  for animal care. This work was supported by the  BIAL Foundation  through the grant #  130/12  to R. F. O. F. E. was supported by a  Marie Skłodowska-Curie Actions -Individual Fellowship  ( H2020-MSCA-IF/703285 ) under the  Horizon 2020 Framework Programme  ( H2020 ).
EV Sound synthesis The EV sounds were synthesized using the mathematical modeling software Matlab and the additive synthesis technique. In order to generate different but plausible sounds for an electric car, after an analysis of current sounds of different carmakers  (Misdariis et al. , 2012)  and personal propositions  (Petiot et al, 2013) , four main components of the sound were considered. • Component C1 "A thermic motor sound". This component synthesizes the first harmonics of a classical 4-stroke internal combustion engine (H0. 5, H1, H1. 5, H2, H4, H6), • Component C2 "A Harmonic Sound". This component synthesizes different musical 'notes', harmonic, that constitute a major chord (chord with 3 notes), • Component C3 and C4: "A broad band Noise". These components synthesize two filtered noises.
Biogenic volatile organic compounds (BVOCs) emitted from the terrestrial vegetation into the Earth's atmosphere play an important role in atmospheric chemical processes. Gridded information of their temporal and spatial distribution is therefore needed for proper representation of the atmospheric composition by the air quality models. Here we present three newly developed high-resolution global emission inventories of the main BVOC species including isoprene, monoterpenes, sesquiterpenes, methanol, acetone and ethene. Monthly mean and monthly averaged daily profile emissions were calculated by the Model of Emission of Gases and Aerosols from Nature (MEGANv2. 1) driven by meteorological reanalyses of the European Centre for Medium-Range Weather Forecasts for the period of 2000-2019. The dataset CAMS-GLOB-BIOv1.