dataesr/scientific-paragraphs-categorization huggingface dataset:
To implement the soft drop procedure described in Sec. 2, jets are reclustered using exclusive C/A  [110, 111]  to return the same jet. The soft drop code will be made available as part of the FastJet contrib project (http://fastjet. hepforge. org/ contrib/). We start by considering the case α = 2, which corresponds to the familiar case of the jet mass distribution. In Fig. 3  we show results for qq → qq scattering for different values of angular power β in the soft-drop declustering procedure (β = 0 is the mMDT already studied in Ref. [59] ). The plot on the left has been obtained from Pythia 8, while the one on the right has been obtained with the analytic resummation, evaluated numerically by freezing the strong coupling in the infrared (see App. A). Dashed curves correspond to MLL accuracy Eq.
Acknowledgments We thank the organizers of the  ESI Program on Jets and QFT  and of Boost 2013 for stimulating workshops during which this project was started. We acknowledge useful discussions with  Mrinal Dasgupta ,  Gavin Salam  and  Jeff Tseng. S. M. would like to thank  IPhT Saclay  for hospitality during the course of this project. A. L. and J. T. are supported by the  U. S. Department of Energy (DOE)  under cooperative research agreement  DE-FG02-05ER-41360. J. T. is also supported by the  DOE Early Career research program   DE-FG02-11ER-41741  and by a  Sloan Research Fellowship  from the  Alfred P. Sloan Foundation. S. M. is supported by the  UK Science & Technology Facilities Council (STFC). G. S. is supported by the  French Agence Nationale de la Recherche , under grant  ANR-10-CEXC-009-01  and by the  EU   ITN grant LHCPhenoNet ,  PITN-GA-2010-264564.
Data on genotypic diversity of Mycobacterium tuberculosis complex (MTBC) is important to understand its epidemiology, human adaptation, clinical phenotypes, and drug resistance. This study aimed to characterize MTBC clinical isolates circulating in a predominantly pastoralist area in Ethiopia, a country where tuberculosis is the second leading cause of mortality. Culture of sputum samples collected from a total of 325 pulmonary TB suspects was done to isolate MTBC. Spoligotyping was used to characterize 105 isolates from culture positive slopes and the result was compared with an international database. Forty-four spoligotype patterns were observed to correspond to 35 shared-types (SITs) containing 96 isolates and 9 orphan patterns; 27 SITs containing 83 isolates matched a preexisting shared-type in the database, whereas 8 SITs ( = 13 isolates) were newly created.
Data Collection. A semi-structured, pretested questionnaire was used to collect data on basic sociodemographic characteristics as well as clinically relevant symptoms. Three sputum samples (spot-morning-spot) were collected and smear microscopic examination for AFB was done at the respective health facilities according to the national TB and Leprosy control programme guideline  [15]. The rest of the sputa were stored at +4 ∘ C and transported to Aklilu Lemma Institute of Pathobiology (ALIPB), Addis Ababa University, within 1 week. Participants were tested for HIV according to the national guideline  [16].
Spoligotyping and Database Comparison. Spoligotyping of 105 isolates was performed using a commercially available kit from Ocimum Biosolutions Company, Iisselstein, The Netherlands, according to the company's instructions and as described previously  [9, 18]. Briefly, the direct repeat (DR) region was amplified by a Thermal Cycler PCR machine (VWR International) using oligonucleotides and primers derived from this region. The amplified product was hybridized to a set of 43 immobilized oligonucleotides, each corresponding to one of the unique spacer. Hybridized DNA was detected by chemiluminescence method (Amersham Biosciences, Little Chalfont, UK) and by exposure to X-ray film (Hyperfilm ECL, Amersham Biosciences), as specified by the manufacturer. The hybridization patterns were converted into binary and octal formats and compared with previously reported strains in the in-house SITVIT2 proprietary database of Institut Pasteur de la Guadeloupe, which is an updated version of the recently released SITVITWEB database  [19].
In this database, a Spoligotype International Type (SIT) designates a pattern shared by 2 or more patient isolates, whereas "orphan" represents a pattern reported for a single isolate. At the time of this comparison, SITVIT2 contained genotyping data on more than 110,000 MTBC clinical isolates from 160 countries of patient origin, and >3500 SITs. Major phylogenetic clades were essentially assigned according to signatures provided earlier  [19] ; these included specific signatures for various MTBC members as well as rules defining major lineages/sublineages for M. tuberculosis sensu stricto. The latter included the Beijing clade, the Central-Asian (CAS) clade and its 2 sublineages, the East-African-Indian (EAI) clade with its 9 sublineages, the Haarlem clade and its 3 sublineages, the Latin-American-Mediterranean (LAM) clade and its 10 sublineages, the "Manu" family and its 3 sublineages, the IS6110-low banding X clade and its 3 sublineages, and the ill-defined T clade and its 5 sublineages.
The high phylogeographical specificity of LAM10-CAM prototype SIT61 for Cameroon has led to its designation as the Cameroon lineage  [20] , whereas LAM7-TUR lineage was tentatively reclassified as the Turkey lineage  [21]. We also studied the worldwide distribution of all major spoligotyping clusters in our study (clusters containing 3 or more isolates) by interrogating the database for their distribution in macrogeographical regions and subregions according to the United Nations (http://unstats. un. org/unsd/ methods/m49/m49regin. htm; for further details please refer to the footnote of Table  3 ). Lastly, the distribution of predominant spoligotype patterns in this study ( = 105 strains) was further compared to all other strains reported from Ethiopia in the international database ( = 1507 strains excluding the present study) as well as the five African subregions ( = 13656 strains), and the neighboring Western Asian countries ( = 4790 strains; for further details please refer to the footnote of Table  4 ).
Minimum spanning trees (MSTs) illustrating evolutionary relationships between the M. tuberculosis spoligotypes and various sociodemographic variables were constructed using BioNumerics software version 6. 6 (Applied Maths, Sint-Martens-Latem, Belgium). MST is an undirected network in which all of the samples are linked together with the fewest possible linkages between nearest neighbors. Lastly, Spoligoforest trees which represent another way to illustrate probable strain evolutionary relationships between spoligotypes were drawn  [22, 23]  using spolTools online utilities available through http://www. emi. unsw. edu. au/spolTools. As opposed to the MSTs, the spoligoforest trees are directed and only evolve by loss of spacers. GraphViz software (http://www. graphviz. org/ [24] ) was used to color the strains based on their lineages on the spoligoforest trees.
Statistical Analysis. Chi-square test using STATA software version 12 was used to evaluate whether or not significant association may exist between lineages or SITs with sociodemographic and epidemiological characteristics. Pearson's Chi-square test was used when more than 80% of data had an expected value greater than 5 and Fisher's Exact Test for remaining data with smaller expected values (at least 20% of data having values less than 5). values less than 0. 05 were considered as statistically significant.
Genetic Diversity and Distribution of Isolates. Overall, 103 (98. 1%) isolates had spoligotypes characteristic of M. tuberculosis complex and 2 (1. 9%) isolates had spoligotypes characteristic of M. bovis. A total of 9 isolates showed orphan patterns (Table  1 ), whereas 16 strains were unique making the total number of unclustered isolates to be 25 (23. 81%). On the other hand, 19 SITs containing 80 isolates (76. 19%) were clustered within this study (2 to 10 isolates per cluster). Besides, a total of 44 spoligotype patterns were observed and, therefore, the overall diversity of the isolates was 41. 9%. A total of 27 SITs containing 83 isolates matched a preexisting shared-type in the SITVIT2 database, whereas 8 SITs ( = 13 isolates) did not match any of the previous isolates in the database and hence were newly created (Table  2 ).
The majority (76. 19%) of the isolates belonged to the following three dominant lineages: T ( = 43, 40. 95%), Manu ( = 20, 19. 05%), and CAS ( = 17, 16. 19%). The other minor lineages in this study include X ( = 6, 5. 71%), Haarlem ( = 4, 3. 81%), EAI ( = 4, 3. 81%), LAM ( = 3, 2. 86%), BOV ( = 2, 1. 90%), AFRI ( = 1, 0. 95%), Turkey ( = 1, 0. 95%), and S ( = 1, 0. 95%) (Table  2 ). Three isolates (2. 86%) had patterns with signatures that do not belong to any of the major lineages described in the database and hence labelled as "unknown" (Tables  1  and 2 ). No Beijing strains were identified in this study. The dominant SITs in this study included SIT 149 of the T3-ETH lineage, SIT 37 of the T3 lineage, SIT 53 of the T1 lineage, and SIT 54 of the Manu2 lineage all together accounting for 36.
2% of the isolates (Table  3 ). On comparing the dominant isolates from this study with the isolates in the SITVIT2 database from Ethiopia, the five African regions, and neighboring Western Asia, statistically significant differences were observed (Table  4 ). Significantly higher proportions of T2 ( < 0. 01), X1 ( < 0. 01) and H ( = 0. 024) lineages/sublineages were found among isolates in this study compared to their representations in the SITVIT2 database from Ethiopia. Notably, the Manu lineage was significantly higher compared to previous isolates from Africa and neighboring Western Asia ( < 0. 01). Besides, this lineage has not been reported to SITVIT2 database from Ethiopia so far. * * Lineage designations according to SITVIT2 using revised SpolDB4 rules; "unknown" designates patterns with signatures that do not belong to any of the major lineages described in the database.
* * * Clustered strains correspond to a similar spoligotype pattern shared by 2 or more strains "within this study"; as opposed to unique strains harboring a spoligotype pattern that does not match with another strain from this study. Unique strains matching a preexisting pattern in the SITVIT2 database are classified as SITs, whereas in case of no match, they are designated as "orphan" (see Table  1 ). On the other hand, there was no significant difference in the distribution of T1, T3, T3-ETH, and CAS1-Delhi lineages compared to previous isolates from Ethiopia ( > 0. 05). A minimum spanning tree (MST) illustrating evolutionary relationships among the strains has been constructed (Figure  1 ). In this evolutionary tree, MANU strains were closest to the central node of the unrooted tree which is represented by SIT53, whereas CAS strains are further away from the central node of the tree.
Discussion Analysis of strain diversity and comparison with international database is key to have an insight into the global distribution of M. tuberculosis strains. In this regard, we describe the strain diversity of M. tuberculosis complex among clinical isolates of pulmonary TB patients from a predominantly pastoralist area in Northeast Ethiopia and compared the strains with SITVIT2 database strains. Among 105 isolates, the majority (98. 1%) of the isolates were identified as M. tuberculosis complex with only 2 (1. 9%) isolates being M. bovis. This finding is in agreement with previous reports from Ethiopia  [25, 26]. Unlike a previous study from Ethiopia  [27]  which reported a significant contribution (17%) of bovine TB among TB lymphadenitis patients, the contribution of M. bovis to human TB seems to be minimal and mainly restricted to the pastoral communities as supported by current evidence  [25, 26].
However, Manu has not been reported from Ethiopia in other previous studies  [7, 8, 11]  as well as in the SITVIT2 database in which SIT 54 (Manu2) has been mainly reported from South and East Asia, Middle East including Egypt, and America. Furthermore, a recent study on a relatively large number of isolates mainly from Djibuti  [34]  did not find Manu lineage. The diverse distribution of strains in the study areas included in Ethiopia so far implies the need to map the distribution of Mycobacterium tuberculosis in the country. Interestingly, Manu2 lineage was found to be significantly associated with HIV infection although the reason for such association is not apparent from the current study. Regarding the evolutionary relationship among strains, as opposed to CAS strains, the Manu strains in the MST tree are the ones closest to the dominant T lineage as reported before  [33].
Description of 35 shared-types (SITs;  = 96 isolates) and corresponding spoligotyping defined lineages/sublineages starting from a total of 105 M. tuberculosis strains isolated in Addis Ababa (Ethiopia). A total of 27/35 SITs containing 83 isolates matched a preexisting shared-type in the database, whereas 8/35 SITs ( = 13 isolates) were newly created. A total of 19/35 SITs containing 80 isolates were clustered within this study (2 to 10 isolates per cluster) while 16/35 SITs containing 16 strains were unique (for total unique strains, one should add to this number the 9 orphan strains which brings the number of unclustered isolates in this study to 25/105 (23. 81%) and clustered isolates to 80/105 (76. 19%)). Note that SITs followed by an asterisk indicates "newly created" SITs due to 2 or more strains belonging to an identical new pattern within this study or after a match with an orphan in the database; SIT designations followed by number of strains: 3896.
Distribution in Ethiopia and neighboring subregions of 11 predominant spoligotype patterns in this study (clusters containing 3 or more isolates), as seen through the updated SITVIT2 database a significant differences ( < 0. 05) as compared to the total number of strains for a given pattern in this study ( = 105 strains). For statistical comparison of differences observed, note that Pearson's Chi-square test was used when more than 80% of data had an expected value greater than 5, and Fisher's Exact Test for remaining data with smaller values (at least 20% of data having values less than 5). Kenya, Madagascar, Malawi, Mauritius, Mozambique, Reunion, Tanzania, Uganda, Zambia, and Zimbabwe; AFRI-N: Algeria, Egypt, Libyan Arab Jamahiriya, Morocco, Sudan, and Tunisia; AFRI-W: Benin, Burkina Faso, Gambia, Guinea, Guinea-Bissau, Ivory Coast, Mali, Mauritania, Nigeria, Senegal, and Sierra Leone; AFRI-M: Cameroon, Central African Republic, Chad, and Democratic Republic of Congo; AFRI-S: Botswana, Namibia, South Africa, and Swaziland; ASIA-W: Armenia, Azerbaijan, Georgia, Iraq, Israel and Palestinian territories, Oman, Saudi Arabia, Turkey, and Yemen (SITVIT2 database comparison made on August 21st 2013 by David Couvin and Nalin Rastogi).
Acknowledgments This study was supported by the  Norwegian Programme for Development, Research and Education (NUFU)  (Project no. NUFUPRO. 2007/10198 ), and the  Norwegian Research Council  (Project no. 196397/S50 ). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the paper. The authors' sincere gratitude goes to  Mr. Adane Worku  at  Aklilu Lemma Institute of Pathobiology  for carrying out spoligotyping. Laboratory technicians working at the respective health facilities deserve our sincere gratitude for collecting samples. The authors would like to acknowledge participants for consenting to participate in the study.
51 ASIA-E 38. 46, AFRI-E 19. 23, EURO-W 11. 54, EURO-E 7. 69, EURO-N 5. 77, ASIA-W 5. 77, AMER-N 5. 77, EURO-S 3. 85 ASIA-E 27. 08, ASIA-SE 16. 67, AMER-N 10. 42, EURO-W 8. 33, ASIA-W 8. 33, AFRI-W 8. 33, AFRI-E 6. 25, AFRI-S 4. 17 AFRI-E 75. 0, AMER-N 25. 0 % in study versus database 2. 04 2. 07 0. 14 3. 56 0. 65 0. 64 0. 26 0. 28 5. 77 6. 25 75 Nb (%) in study 10 (9. 52) 10 (9. 52) 9 (8. 57) 9 (8. 57) 6 (5. 71) 4 (3. 81) 4 (3. 81) 3 (2. 86) 3 (2. 86) 3 (2. 86) 3 (2. 86) SIT (Lineage) Octal number spoligotype description 37 (T3) 777737777760771 149 (T3-ETH) 777000377760771 53 (T1) 777777777760771 54 (Manu2) 777777777763771 52 (T2) 777777777760731 25 (CAS1-Delhi) 703777740003171 26 (CAS1-Delhi) 703777740003771 119 (X1) 777776777760771 121 (H3) 777777775720771 523 (Manu ancestor) 777777777777771 3897 (Manu2) 777347777763671 *Worldwide distribution (analysis made on August 18, 2013) is reported for regions with more than 3% of given SITs as compared to their total number in the SITVIT2 database.
The definition of macrogeographical regions and subregions (http://unstats. un. org/unsd/methods/m49/m49regin. htm) is according to the United Nations; regions: AFRI (Africa), AMER (Americas), ASIA (Asia), EURO (Europe), and OCE (Oceania), subdivided in: E (Eastern), M (Middle), C (Central), N (Northern), S (Southern), SE (South-Eastern), and W (Western). Furthermore, CARIB (Caribbean) belongs to Americas, while Oceania is subdivided in 4 subregions, AUST (Australasia), MEL (Melanesia), MIC (Micronesia), and POLY (Polynesia). Note that in our classification scheme, * *The 3-letter country codes are according to http://en. wikipedia. org/wiki/ISO3166-1 alpha-3; countrywide distribution is only shown for SITs with ≥3%of given SITs as compared to their total number in the SITVIT2 database.
85) 3/105 1/1507 (2. 86) (0. 07) 3/105 7/1507 (2. 86) (0. 46) 3/105 0/1507 (2. 86) (0. 00) 3/105 0/1507 (2. 86) (0. 00). Octal code (SIT) lineage 37 (T3) 777737777760771 149 (T3-ETH) 777000377760771 53 (T1) 777777777760771 54 (Manu2) 777777777763771 52 (T2) 777777777760731 25 (CAS1-Delhi) 703777740003171 26 (CAS1-Delhi) 703777740003771 119 (X1) 777776777760771 121 (H3) 777777775720771 523 (Manu ancestor) 777777777777771 3897 (Manu2) 777347777763671 Comoros, Ethiopia, a Asterisk denotes statistically bThe definition of subregions is according to the United Nations (http://unstats. un. org/unsd/methods/m49/m49regin. htm). The table summarizes distribution in this study ( = 105) versus all strains reported from Ethiopia in the international database ( = 1507, excluding the present study), the five African subregions ( = 13656),.
ANATOMICAL STUDY The MR protocol was carried out with a 3-Tesla wholebody system (Siemens, Erlangen, Germany) at the Center for Neuroimaging Research (CENIR), Brain and Spine Institute (ICM) in Paris. Lesion analysis was performed by an expert neurologist (RM) and a master student (FB) trained to read brain scans. Lesion extent was determined for each patient by selecting those brain scans that showed the greatest extent of damage (hypointense lesions on T1-weighted images). The lesion borders were directly drawn onto the original native 3D MRI, using MRIcro software  (Rorden and Brett, 2000, www. mricro. com ) and a graphic tablet (WACOM Intuos A6, Vancouver, Washington, USA). Afterwards, in order to plot all the patients' lesions in the same standard space, the 3D brain scans and lesion volumes were normalized to the standard Montreal Neurological Institute (MNI) brain template in Statistical Parametric Mapping 8 (http:// www.
fil. ion. ucl. ac. uk. gate2. inist. fr/spm) running under Matlab 7. 13 (http://www. mathworks. com). In particular, to reduce lesion-induced registration errors, spatial normalization was performed using a mask that excluded the damaged areas of the brains, thereby preventing these areas from biasing the transformation. After normalization, brain lesions were segmented and their borders redefined in the normalized brain. MRIcron software  (Rorden et al. , 2007)  (http://www. mccauslandcenter. sc. edu/ mricro/mricron/) was used to measure the extent of the lesion. For patient 2, who could not undergo MRI, because of the presence of surgical metallic clips, the lesion was delineated using a similar procedure. Lesions were first drawn from high-resolution CT scans and then manually transposed onto the standard MNI brain template (for the methodology see also  Bourgeois et al.
The mean time of testing for the included patients was 4. 6 months since stroke onset (SD, 1. 7 months). For statistical analysis, we used MRIcron and non-parametric mapping, which is part of the MRIcron software package  (Rorden et al. , 2007). We contrasted MN patients and control groups (VN and H, both without MN) by using non-parametric voxel-based lesion symptom mapping (VLSM) analysis  (Bates et al. , 2003) , and plotting all the lesions on the same (right) hemisphere. We used the Liebermeister test, which is a non-parametric implementation test of a two-group comparison on a binary variable (for details see also  Heydrich and Blanke, 2013). Only voxels damaged in at least 20% of individuals were considered. We corrected the results for multiple comparisons using false discovery rate (FDR).
ACKNOWLEDGMENTS The authors thank  Marika Urbanski ,  Alexia Bourgeois  and  Marine Lunven  for help in the recruitment of patients and  Michel Thiebaut de Schotten  for the useful discussion on lesion localization. The research leading to these results has received funding from the program " Investissements d'avenir "  ANR-10-IAIHU-06  and from a translational research grant  Inserm-AP-HP  to PB.
Seawater collection, experimental set up and sampling Seawater was collected, using a 10 L Niskin water bottle through a 1. 3 × 1. 1 m hole in the sea ice, from 25 m depth and placed initially into three sterilized 25 L water containers on the 19th April 2010. In each container the carbonate chemistry was manipulated using HCl and NaHCO 3 based on measurements of pH and alkalinity (Table  1 ) and calculated using the Seacarb program  (Lavigne and Gattuso, 2010)  as detailed in the EPOCA Guide to Best Practices  (Riebesell et al. , 2010). The carbonate system was manipulated so that there were three atmospheric CO 2 concentration scenarios: "ambient-CO 2 " (∼400 ppm), "mid-CO 2 " (∼880 ppm), and "high-CO 2 " (∼1800 ppm). After the manipulations were made, seawater was decanted into three replicate 2 L incubation bottles (Thermo Scientific Nalgene polycarbonate narrow-mouth bottle) for each treatment.
Sequence processing Illumina reads were first pre-processed through the MG-RAST quality-control pipeline  (Meyer et al. , 2008). The reads were retrieved from the MG-RAST server and were analyzed using QIIME v1. 6  (Caporaso et al. , 2010b). Putative chimeric products were detected using UCHIME v4. 2  (Edgar et al. , 2011)  and were removed from subsequent analyses as well as reads shorter than 75 nucleotides. Resulting reads were then clustered into operational taxonomic units (OTUs) with UCLUST, part of the USEARCH v6. 0 software suite  (Edgar, 2010) , using a 97% sequence identity cutoff. OTUs consisting of only a single read in the entire data set (singletons) were discarded. In addition, one sample triplicate (Mid-CO 2 , attached fraction, replicate 2) was composed of less than 100 reads passing all filtering steps and was removed from the study.
PHYLOGENETIC DIVERSITY OF NATURAL AND CO 2 -TREATED ARCTIC MICROBIAL COMMUNITIES Our final 16S sequence dataset was composed of more than 7 million quality-controlled reads totaling ∼30 k OTUs, across all samples (Supplementary Table  1 ). Clustering and principal coordinate analyses (PCoA) on both weighted and unweighted UniFrac distances indicated that size fraction (i. e. , free-living vs. attached) mainly drove the phylogenetic beta-diversity across microbial assemblages (Figure  1  and Supplementary Figure  2 , respectively). Weighted and unweighted distance clustering clearly separated the two size fractions, indicating their distinct phylogenetic compositions (Figure  1A  and Supplementary Figure  2A ). Moreover, the PCoA showed that phylogenetic compositions of communities from the attached fraction were remarkably more varied compared to those of the free-living communities (Figure  1B  and Supplementary Figure  2B ; along principal coordinate 2).