dataesr/scientific-paragraphs-categorization huggingface dataset:
Indeed, Cory's Calonectris diomedea borealis, Scopoli's Calonectris diomedea diomedea, sooty Puffinus griseus and manx Puffinus puffinus shearwaters have been reported in inshore waters of the Gulf of Guinea during their autumnal migration, or are known to winter partly in this region despite its eccentricity from the major migratory paths of these species  (González-Solís et al. 2007 , Passavy 2011 , Hedd et al. 2012 , Péron and Grémillet 2013 , de Boer and Saulino 2017). In addition, migrating long-tailed skuas can stage in the Gulf of Guinea, especially in October and November  (Gilg et al. 2013). However, no radar data was exploitable in October, November and December, thus excluding the period during which migrating individuals could have been most probably recorded. Still, Arctic terns may have been recorded during their postbreeding migration, as some individuals follow the west African coast to reach their wintering area in the southern Atlantic  (Egevang et al.
Acknowledgements -The authors are grateful to Orthongel for allowing the recording of purse-seiner radar images. The authors are thankful to  P. Dewals  and  A. Damiano , who collected the data and supervised their transfer, as well as  P. Bach ,  P. Kouadio ,  J. Lebranchu ,  P. Taconet ,  N. Billet ,  P. Cauquil  and  P. Sabarros  for their help in logistics for data acquisition and transfer.
Because of the popularity of Swiss dairy goats in both Uganda  (NAADS, 2005)  and Korea  (Kim et al. , 2019) , crossbreeding again is the most likely explanation. We conclude that the Y-chromosomal haplotype distribution reveals expansion and crossbreeding events, as observed also for the human paternal lineages  (Poznik et al. , 2016; Batini and Jobling, 2017) , and illustrates the power of Y-chromosomal markers for inferring the genetic origin of mammalian populations. The SRA data are in the public domain. Members of the Econogene Consortium: BDBLB03 SRX2982563 Black Bengal Y2B [1] CNNCH04 CNSHD04 SRX2982510 Shandong Yimeng black Y1AB [1] CNNCH06 CNXIN06 SRX2982522 Xinjiang Y1AB [1] CNNCH14 CNQIN14 SRX2982537 Qinghai Y1AB [1] CNNCH15 CNQIN15 SRX2982502 Qinghai Y1AB [1] CNNCH16 CNQIN16 SRX2982503 Qinghai Y1AB [1] CNNCH17 CNQIN17 SRX2982504 Qinghai Y1AB [1] CNNCH18 CNQIN18 SRX2982511 Qinghai Y1AB [1] CNNCH19 CNQIN19 SRX2982507 Qinghai Y1AB [1] CNNCH20 CNQIN20 SRX2982487 Qinghai Y1AB [1] CNSCH09 CNRAO09 SRX2982486 Raoshan Henan Y1AA [1] CNTCH01 CNTIB01 SRX2982520 Tibetan Y1AB [1] CNTCH02 CNTIB02 SRX2982521 Tibetan Y2B [1] CNTCH03 CNTIB03 SRX2982513 Tibetan Y2B [1] CNTCH04 CNTIB04 SRX2982514 Tibetan Y1AB [1] CNTCH05 CNTIB05 SRX2982515 Tibetan Y1AB [1] FRCH06 FRPTV06 SRX2982542 Poitou Y1AB [1] NLCH01 NLLNR01 SRX2982482 Dutch Landrace Y1B [1] NLCH03 NLDSA03 SRX2982490: Dutch Saanen Y1B [1] PKCH05 PKBBL05 SRX2982568 Beetal Black Y2A [1] SDCH03 AFSD03 SRX5417024 Sudan Y2A [1] SDCH05 AFSD05 SRX5417026 Sudan Y2A [1] FRCH05 FRALP05 SRX2982481 Alpine Y1B [1] KOSAA04 ERX2360419 Korean Saanen Y1B2 [2] KOSAA05 ERX2360420 Korean Saanen Y1B2 [2] KOSAA08 ERX2360423 Korean Saanen Y1B [2] KOSAA09 ERX2360424 Korean Saanen Y1B [2] KOSAA10 ERX2360425 Korean Saanen Y1B2 [2] KOKOR01 ERX2360430 Korean Saanen Y1B [2] KOKOR02 ERX2360431 Korean Saanen Y1AA [2] KOKOR08 ERX2360437 Korean Saanen Y1B [2] KOKOR10 ERX2360439 Korean Saanen Y1B [2] KOKOR11 ERX2360440 Korean Saanen Y1B [2] KOKOR281 ERX2360442 Korean Saanen Y1B [2] KOKOR282 ERX2360443 Korean Saanen Y1B [2] KOKOR04 ERX2360445 Korean Saanen Y2B [2] IRCH04 IRA04 ERX286352 Iran Y2A [3] IRCH06 IRA06 ERX286345 Iran Y2A [3] IRCH10 IRA10 ERX286355 Iran Y1AA [3] IRCH14 IRA14 ERX286363 Iran Y2A [3] IRCH16 IRA16 ERX286347 Iran Y2A [3] IRCH19 IRA19 ERX313213 Iran Y1AB [3] IRCH20 IRA20 ERX313216 Iran Y1AB [3] Table  3.
Codes and SRA accession numbers of WGS data used for Fig. 1. MCCH01 MOR01 ERX194212 Moroccan Y2A [3] MCCH02 MOR02 ERX194211 Moroccan Y2A [3] MCCH03 MOR03 ERX204035 Moroccan Y2A [3] MCCH04 MOR04 ERX204033 Moroccan Y2A [3] MCCH05 MOR05 ERX204019 Moroccan Y2A [3] MCCH08 MOR08 ERX204026 Moroccan Y2A [3] MCCH10 MOR10 ERX204034 Moroccan Y2A [3] MCCH11 MOR11 ERX204027 Moroccan Y2A [3] MCCH12 MOR12 ERX207043 Moroccan Y2A [3] MCCH15 MOR15 ERX208812 Moroccan Y2A [3] MCCH17 MOR17 ERX220684 Moroccan Y2A [3] MCCH23 MOR23 ERX272615 Moroccan Y1AB [3] MCCH24 MOR24 ERX286410 Moroccan Y1AB [3] MCCH25 MOR25 ERX286408 Moroccan Y2A [3] MCCH26 MOR26 ERX286419 Moroccan Y2A [3] MCCH28 MOR28 ERX286420 Moroccan Y2A [3] MCCH29 MOR29 ERX286403 Moroccan Y1AB [3] MCCH31 MOR31 ERX288658 Moroccan Y2A [3] MCCH33 MOR33 ERX288657 Moroccan Y2A [3] MCCH37 MOR37 ERX288652 Moroccan Y2A [3] MCCH38 MOR38 ERX288656 Moroccan Y1AB [3] MCCH39 MOR39 ERX288926 Moroccan Y2A [3] MCCH40 MOR40 ERX291909 Moroccan Y2A [3] MCCH41 MOR41 ERX306478 Moroccan Y2A [3] MCCH42 MOR42 ERX306471 Moroccan Y2A [3] MCCH43 MOR43 ERX313276 Moroccan Y2A [3] MCCH44 MOR44 ERX286409 Moroccan Y2A [3] [1] Z.
Methodologies and Corpus Establishment Foundation of the Acquire Documents The textual analysis is based on a database that was established on the official propaganda after the 18th NPC (2013), which, for the first time, officially adopted Xieshang minzhu. Our data sources are originally derived from the official databases with the title="Xieshang minzhu (协商 民主)" or keywords="Xieshang minzhu" with a total of 2,018 items 11 through advanced (fuzzy) search. 12 Although the authors did not sort the data before 2013, clearly, before the 18th National Congress, the official interpretation of Xieshang minzhu was not systematically engaged; notably, it was mainly conducted by scholars within the academia discussion. In contrast, after the 18th National Congress, academic discussion and official propaganda increased positively.
I. The five most authoritative official media (newspapers) in China 13 are the People's Daily (Renmin ribao 人民日报) for 458 reports, Guangming Daily (Guangming ribao 光明日报) for 560 reports, Xinhua Daily(Xinhua ribao 新华日报 447 reports), China Comment (Bnayutan 半月谈 320 reports), Qiushi (Qiushi 求是 37 reports, formerly known as Red Flag (Hongqi 红旗 86 reports)). II. The top leaders' series of important speech databases with 95 items. 14 III. Official documents on the subject of Xieshang or Xieshang minzhu in the Party-Building Database with 15 items. 15 Although the antitheses between China and the West are not the focus of this article, we still carried out a rhetorical and semantic analysis of the Chinese indigenous studies with the English literature by establishing a database on deliberative democracy (the elucidation in the first part is a mirror case).
Given that the Western literature of Xieshang minzhu does not appear in Pinyin, the keywords are "deliberative democracy," or "deliberation," or "consultation. " The main source of the database comes from the Bibcnrs 16  and Google Scholar, with 124 articles (including overlap) related to the topic and processed in the same way. 13 To date, given that the Xieshang minzhu is a political term, thus, the authoritative official media chosen are target to the political newspaper and media by CCP. These China's largest-circulation newspaper and also known as the propaganda of the CCP (Dangmei 党媒), the published articles and reports that expressed the CCP's official views. To note, the overlapping part that among the various newspapers and social media have, for example, the People's Daily and the Guangming Daily may jointly report the same content at the same time.
" Facing simply too many political texts, scholars are rarely able to manually read all the texts in even moderately sized corpora. Hence, in this article, we try to conduct a systematic analysis of the large-scale text collections based on the automated content analysis outlined, within the following three stages: I. Establishment of the corpus (see the aforementioned description of the foundation of the acquired documents both in Chinese and English for the official discourse). II. Statistical analysis (1): WordCloud-Pre-treat the Chinese data: decoding, tokenizing, cleaning stop or functional words in the data, analyzing the texts, and visualizing the keywords according to the frequency in the text by Logiciel R and Python. The cloud that filled with massive words in different sizes represents the frequency or the importance of the keywords 17 ; 2).
Xieshang minzhu with Chinese Characteristics The authors adopt Chinese Pinyin with Xieshang minzhu for further demonstration instead of English or other linguistical translations, mainly because the Xieshang minzhu per se is quite ambiguous in translation, especially the correspondence and affiliation between Chinese and other languages. 19 Indigenization of Chinese political scholarship is also increasingly inclined to abandon the rhetoric and linguistic disputes and turn to the analysis of xieshang minzhu with Chinese characteristics. It can be seen from the WordCloud and Histogram above that "Specialism (Te'se 特色)" and.
Global analysis of the proteomic data As described by Eymard-Vernain  [26] , the proteomic responses to nanoparticles of 3610 Bacillus subtilis strain, grown on a soft agar LB plate to promote the swarming motion during the formation of biofilm, has been studied by shotgun mass spectrometry. The data are available at the PRIDE repository (data set identifier PXD006444). In order to assess the divergence between the different biological states investigated a global analysis by hierarchical clustering, specifically the abundance data provided by the proteomic study, was performed on 728 proteins. The results displayed in Fig  1 , clearly show that the controls stood apart from all treated bacteria. The second division separated cells treated with titanium dioxide (n-TiO 2 ) from cells treated with zinc.
Stringent response In the study published by Luche and coll. [25] ,where the bacterial cells were grown in liquid medium, we showed that n-ZnO and ZnSO 4 affected the abundance of at least nine proteins involved in the stringent response. In a solid medium growth condition, with n-ZnO, TiO 2 and ZnSO 4 , the abundance of at least 17 proteins increased, compared to the control condition (Fig 6A and Pride repository PXD006444). In stressful conditions, the translation process, including the expression of ribosomal proteins themselves, is controlled by the stringent response. The intracellular (p)ppGpp (the guanosine penta-or tetra-phosphate) level is the central regulator of the stress response. Three main enzymes control its concentration, i. e. RelA, SasA and SasB. SasA and SasB were not detected by the proteomic analysis while the abundance of RelA was unchanged along the different conditions.
This work was funded by the  CNRS, The University of Grenoble Alpes. This work is a contribution to the  Labex Serenade  ( n˚ANR-11-LABX-0064 ) funded by the  «Investissements d'Avenir» French Government program  of the  French National Research Agency (ANR)  through the A �  MIDEX  project (n˚ANR- 11-IDEX-0001-02 ).
| Zooplankton migration and depth selection under ice An acoustic Doppler current profiler (ADCP; Nortek Signature 1,000 kHz with echo sounding mode) was frozen in the ice facing downward, and acoustic data were collected continuously over the 3 days of the study (sampling interval 4 Hz, vertical resolution 5 cm). The data were analysed for temporal and vertical changes in the intensity of the backscatter signal (mean volume backscattering strength  [dB] ) to determine the presence, timing, and movements of large particles under the ice. Given the frequency of the ADCP, the acoustic signal was best reflected to 480 μm particles with a lower limit of 25 μm. The acoustic signal was converted into the mean volume backscattering strength using the sonar equation, thereby correcting for the attenuation of the acoustic signal with the distance from the emitter-receiver.
3 μg/L) was well below the average concentration (5. 8 μg/L) computed for 118 stations in the synthesis by  Hampton et al. (2017) , and was also one order of magnitude lower than the chlorophyll a concentrations measured in summer in Lake Onego (3 μg/L, Tekanova & Syarki, 2015). However, when accounting for the latitudinal range of lakes within the dataset of  Hampton et al. (2017) , the chlorophyll a concentration measured in Lake Onego during winter 2017 corresponded to those expected for lakes above 60° latitude (median value = 0. 3 μg/L, Figure  6a ). The estimated ratio of winter to summer chlorophyll a fell within the lowermost range of observed ratios for the corresponding latitudes (Figure  6b ), as a likely consequence of the light limitation of photosynthesis by the coloured nature of the waters of Lake Onego.
Level of specificity validation Only 11 laboratories of the 38 laboratories that had implemented testing indicated having validated the specificity of the implemented test against the six additionally known HCoVs and other common respiratory pathogens. For 15 laboratories, specificity validation was still in progress at the time of data submission. Seven laboratories indicated to have only partially validated the implemented test(s) while five laboratories had not (yet) performed any validation. The questionnaire was send out before the first 2019-nCoV cases appeared in Europe (Figure  1 ) and positive clinical specimens were assumed to be not available to the European laboratories. Therefore, the level of validation for clinical sensitivity was not assessed.
Acknowledgements We thank all survey participants:  Medical University of Vienna, Vienna, Austria; Sciensano, Brussels, Belgium; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria; University Hospital for Infectious Diseases Dr. Fran Mihaljevic´, Zagreb, Croatia; Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus; University of Cyprus, Nicosia, Cyprus; Ostrava Institute of Public Health, Ostrava, Czech Republic; National Institute for Public Health, Prague, Czech Republic ;  Statens Serum Institut, Copenhagen, Denmark ;  Health Board Laboratory of Communicable Diseases, Tallinn, Estonia; University of Helsinki and HUSLAB, Helsinki, Finland; Finnish Institute for Health and Welfare, Helsinki, Finland; Aix Marseille University, Marseille, France; Institute Pasteur, Paris, France; Institut für Virologie, Marburg, Germany; Institute of Virology, Charite -Universitätsmedizin Berlin, Berlin, Germany; Robert Koch Institute, Berlin, Germany; Department of Microbiology, Aristotle University of Thessaloniki, Thessaloniki, Greece; Hellenic Pasteur Institute, Athens, Greece; Nemzeti Népegészségügyi Központ, Budapest, Hungary; Landspitali-National University Hospital, Reykjavik, Iceland ;  National Virus Reference Laboratory-U.
In order to understand whether the mean growth rate of high-elevation forests over the MTP is stimulated by warming or suppressed by moisture limitation, we developed a tree-ring width (TRW) dataset using 40 forest sites with 6 genera at elevations ⩾3700 m a. s. l. The TRW data were processed following standard dendrochronology methods  (Fritts 1976)  to compute the local high-elevation forest growth index (HEFGI, see section 2). All local HEF-GIs were averaged to estimate the mean HEFGI of the MTP. Local and MTP HEFGIs were calibrated to climate variables to test the climate-growth patterns at local scale and across the MTP.
Our study domain is bounded by 75-104 • E, 27-33 • N and is thus under the monsoonal regime. This area is also the most forested region of the Tibetan Plateau. Monthly climate data, including precipitation, self-calibrated Palmer drought severity index (scPDSI), minimum and mean temperature (MinT and MeanT, respectively) covering 1950-2010 were obtained from the Climate Research Unit (CRU) TS4. 02 dataset  (Harris et al 2014) , which is a 0. 5 • by 0. 5 • gridded interpolation of existing instrumental data from meteorological stations. CRU data before 1950 is interpolated from distant meteorological stations and was not used.
Tree ring width data and HEFGI construction We collected tree-ring width (TRW) measurements from 159 sites over the MTP (Filled circles in figure  1 ). Among them, 71 are from our own dataset, and 88 are from the International Tree Ring Data Bank (https://www. ncdc. noaa. gov/data-access/ paleoclimatologydata/datasets/tree-ring). Sampling sites with elevations ⩾3700 m a. s. l were defined as high-elevation forests (red circles in figure  1 ), as 3700 m a. s. l corresponds to the lowest alpine treeline elevation recorded over the MTP  (Singh 2018 , Shi et al 2019). This resulted in 40 out of the 159 sites being selected as high-elevation forests. The trees at high elevations of MTP are almost all conifers, mainly Abies and Juniper (28 out of 40 sites); Picea, Larix, Tsuga and Sabina can also be found (12 out of 40 sites).
The TRW data from each site were detrended and standardized into site-chronologies using the signal-free regional curve standardization (sf-RCS) with the CRUST software  (Melvin and Briffa 2014a, 2014b). On average 18% and 35% of trees' start year fall in the first 50 and 100 years of each chronology, respectively (Table  S1 ). After selecting the periods with EPS (Expressed Population Signal) values >0. 85  (Wigley et al 1984) , the chronologies of six different genera were Z-score normalized (subtracted by the mean value and divided by standard deviation) and averaged into one record representing the highelevation forest growth index (HEFGI) of the entire MTP. By pooling data from 40 high-elevation forest sites with six genera, we assume that the local nonclimatic signals inherent in the TRW records, such as species competitions, growth release and topography changes are largely cancelled out, and thus that the common climate signal is strengthened.
The low correlations observed with moisture availability could also due to the inaccuracy of gridded datasets to represent the high spatial variability in moisture availability. Furthermore, the mean HEFGI is closely related to the MTP averaged MinT at interannual and decadal time scales, despite the increasing temperature, decreasing precipitation, and accelerating drought stress shown by the instrumental records in recent decades (supplementary figure  3 ). We thus conclude that the drying and warming trends over the MTP have not reached the level beyond which overall high-elevation tree growth show signs of hydrological stress, although warming-induced drought stress and associated growth declines were reported at some alpine treeline forests in the Himalayan region  (Liang et al 2014).
Acknowledgments This study was supported by the  Second Tibetan Plateau Scientific Expedition and Research Program (STEP) , Grant NO. 2019QZKK0301 ;  National Natural Science Foundation of China  ( 31971667 );  Academy of Finland Decision  no. 256991  and  JPI  Climate no. 291581 ; The  National Key Research and Development Plan  ( 2017YFC0504004 );  Other National Natural Science Foundation of China  ( 31770490  and  41661144045 ); The  Fundamental Research Funds for the Central Universities from Beijing Forestry University. LS was supported by the  Belmont Forum  and  JPI-Climate, Collaborative Research Action INTEGRATE: An integrated datamodel study of interactions between tropical monsoons and extratropical climate variability and extremes  ( BMBF grant   01LP1612A ); PC acknowledges support from the  European Research Council  Synergy project SyG-2013-610028  IMBALANCE-P  and the  ANR CLAND Convergence Institute.
Data availability statement The climate data used are available at http://www. cru. uea. ac. uk/data. Part of tree-ring width data are available at the International Tree-Ring Data Bank (ITRDB, https://www. ncdc. noaa. gov/data-access/ paleoclimatology-data/datasets/tree-ring). The rest tree-ring width data that support the findings of this study are available from the corresponding author upon reasonable request.
Bait expression, localization and induction of biotinylation were assessed by immunoblotting and immunofluorescence (see below). A pilot immunofluorescence study (using transient transfection in HEK293T cells; data not shown) indicated that several SARS-CoV-2 bait proteins localized generally to cytoplasm, but many proteins were instead clearly associated with the endoplasmic reticulum (ER), Golgi apparatus, mitochondria, and possibly other intracellular membranes. Leveraging our previous study on the subcellular organization of a human cell  20  (in which 192 subcellular markers were profiled by BioID in HEK293 cells, using the classic BirA* enzyme), 17 ER, Golgi, mitochondria and other organellar membrane and non-membrane "marker" ORFs were also cloned into the miniTurbo lentiviral vector, and BioID conducted as above.
Catalytically inactive mutants of the proteases NSP3 (C857A) and NSP5 (C145A) were also created via mutation of active site residues, as previously described  6. Together, our dataset thus comprises the proximity interactomes of 27 WT virus baits, mutant versions of NSP1, NSP3 and NSP5, and 17 host baits (Supplementary   In addition to profiling the proximity interactome of each of the SARS-CoV-2 proteins, we assessed their subcellular localization using immunofluorescence microscopy in A549 cells. This revealed the localization of 11 baits to the endoplasmic reticulum (NSP4, E, ORF8), the Golgi (ORF3B, ORF7A) or both compartments (NSP6, S, ORF3A, M, ORF6, ORF7B); Fig. 1b-c ; Extended data Fig. 2a, b ; Supplementary Table  1 ). NSP2 and Nucleocapsid (N) exhibited nuclear exclusion, ORF9B localized to mitochondria localized to the nucleus.
NSPs 7-16 exhibited non-discrete localization, distributing throughout the cell. We note that some baits (including ORF3A, ORF7A, ORF14 and ORF8) were detected in different compartments depending on tag location. This is not completely surprising since ORF3A is a multipass membrane protein and ORF7A and ORF8 contain an N-terminal signal sequence. Overall, our results agree to a large extent with previous reports of the subcellular localization of these proteins, and suggest that the miniTurbo tag does not dramatically affect localization. All viral baits, host subcellular markers and negative controls were profiled (≥2 biological replicates) by BioID and mass spectrometry (see Methods). The dataset was analyzed using Significance Analysis of INTeractome (SAINTexpress  23  ), identifying 7810 high-confidence (i.
e. Bayesian FDR ≤1%) proximity interactions (after merging N and C-terminal data) for the WT viral baits, with 2242 unique human proteins (Fig. 1d ; Supplementary Table  2 ). The viral proteins recovered between 6 (NSP12) and 938 (M) proximity interactions, with a median of 205, consistent with the localization of many of these proteins to membranous compartments, which tend to produce rich BioID profiles  20. Across the entire dataset, including host subcellular markers (and without merging the viral bait orientations), 16503 high-confidence proximity interactions with 2715 unique prey proteins were uncovered.
Comparison to other datasets We next compared our BioID results with those of recently reported AP-MS results  [6] [7] [8]  , as annotated in BioGRID  24. A relatively high proportion (21. 7%) of previously reported SARS-CoV-2 AP-MS interactions was recapitulated in our study (Fig. 1e , Supplementary Table  3 ). However, this value varied widely between baits, ranging from 0 (e. g. NSP14) to 43. 9% (for ORF8) of previously reported interactions recovered (Extended data Fig. 3 ). At least 10% of previously reported interactions were recovered for 13 different virus proteins. This group of interactions, cross-validated in multiple approaches, may represent promising therapeutic targets (specific examples discussed below). As expected, BioID expands upon the previously reported AP-MS interactions (1976) to include 7810 proximal interactions, which encompass both direct interactors and proteins residing in the vicinity of the bait protein.