dataesr/scientific-paragraphs-categorization huggingface dataset:
Ethical considerations This descriptive analysis used routine surveillance data collected by the MOH and MSF. Data were not nominative, and authorization for using the data was obtained from the MOH. This data was exempt from review by the MSF Ethical Review Board (ERB) and the national ERB in Kinshasa as routinely collected data were used. During vaccine coverage surveys, verbal informed consent was obtained from each head of household visited  [12]. Privacy and confidentiality of patients were ensured by ensuring that no identifying information was recorded.
The HZ of Sakania, adjacent to Zambia, reported an increase in cases at the end of 2010, and the HZ of Dilolo (Katanga) and Kamonia (Kasai Occidental), both bordering Angola, reported increase in cases between weeks 36 and 46-2010. Nonetheless, several caveats about the data should be highlighted. First, the attack rates presented are calculated using population estimates based on the 1984 census. For many reasons, these population estimates, based on an annual growth of 3%, are likely inaccurate. Use of population projections is a known weakness and in countries without accurate population data, and contributes to difficulties in assessing coverage. This is particularly evident when examining administrative vaccination coverage (number of doses administered divided by the presumed target population), where rates of over 100% are often reported  [15].
However, they are the standard figures used in the DRC, and remain the most rational option until a new census is conducted. Secondly, the case fatality ratios should also be interpreted with caution. They were low compared with other African settings  [16] [17] [18] [19]. In the DRC, where access to care is limited, the low CFR is likely due to an underreporting of deaths, many of which happen outside of health structures. At the same time, measles cases may have been overestimated using the clinically confirmed case definition, as some provinces had concurrent rubella epidemics. Finally, the surveillance system in DRC is still a work in progress: line lists were not completed in most districts, and only aggregate age information was recorded. The completeness of data is weak, and the sensitivity of the surveillance system has not been formally evaluated  [14].
Prior information Our system exploits some prior information x b which combines different standard and recent inventories (Table  1 ). The anthropogenic emissions of CH 4 are drawn from the Emission Database for Global Atmospheric Research EDGAR v4. 2  (Olivier and Berdowski, 2001)  and biomass burning emissions are from the interannual Global Fire and Emission Database GFED3 (van der  Werf et al. , 2010) , both valid for 2008. No effort is made here to adapt these inventories to the years of the study  (2009 and 2010). Other sources are added to these emissions: termites from a study of  Sanderson (1996) , ocean from  Lambert and Schmidt (1993)  and wetlands from  Kaplan (2002)  which have been rescaled by P. Bergamaschi (personal communication, 2009). Soil uptake is based on  Ridgwell et al.
(1999). The 3-D concentrations of OH are obtained from a previous simulation of the full atmospheric chemistry model LMDz-INCA  (Hauglustaine et al. , 2004). MCF emissions are described by the EDGAR v3. 2 database and are extrapolated for the years 2009 and 2010 based on a former atmospheric inversion  (Bousquet et al. , 2005) , which has been updated. Current bottom-up inventories range between 223 Tg yr -1 and 469 Tg yr -1 for the global methane natural sources and between 296 Tg yr -1 and 353 Tg yr -1 for the global methane anthropogenic sources  (Kirschke et al. , 2013) , implying large uncertainties of methane emissions. The standard deviation of the errors of grid-point weekly CH 4 prior emissions are defined here as a percentage (120 %) of the maximum value of the prior emissions between the 8 nearest neighbours in the corresponding month for each grid point  (Pison et al.
e. between June and September. Another underestimation of the emissions in region South American Tropical is seen as well, also due to a lack of IASI retrievals over this region between November 2009 and March 2010. This does not allow inferring the high emissions found by TANSO-FTS and the surface data during the drought of 2010. The three observing systems (TANSO-FTS, IASI and the surface sites) still show good consistency in terms of emissions, meaning we can trust the main information retrieved from them. However, in the Southern Hemisphere the fit is not improved for the sites optimized during the surface-based inversions. Interestingly, we found a similar problem when inverting CO emissions from the Measurements Of Pollution In The Troposphere (MOPITT) on board NASA's Terra satellite  (Fortems-Cheiney et al.
Acknowledgements. The first author is funded by  CNES  and  CEA. This work was performed using HPC resources from  DSM-CCRT  and [CCRT/CINES/IDRIS] under the allocation 2012-t2012012201 made by  GENCI  ( Grand Equipement National de Calcul Intensif ). We also thank the computing support team of the LSCE led by  F. Marabelle. We aknowledge the contributors to the  World Data Center for Greenhouse Gases  for providing their data of methane and methyl-chloroform atmospheric mole fractions. The authors thank in particular  S. Piacentino  (ENEA),  T. Kawasato  (JMA) and  S. Nichol  ( NIWA ). NOAA authors receive partial funding for their measurements and research from the  Atmospheric Chemistry ,  Carbon Cycle , and  Climate  ( AC4 ) Program. Edited by: A. Pozzer The publication of this article is financed by  CNRS-INSU.
a b s t r a c t One hundred and forty patients who had undergone hematopoietic stem cell transplantation (HSCT) for myelodysplastic syndrome (MDS) or acute myelogenous leukemia (AML) transformation after treatment of severe aplastic anemia (SAA) were identified in the European Group for Blood and Marrow Transplantation (EBMT) database. The median age at HSCT was 29 years (range, 1 to 66 years). The transplant donor was related in 49% cases and unrelated in 51% cases. The 5-year probability of relapse was 17%, and that of nonrelapse mortality was 41%. The 5-year overall survival was 45% AE 9%, better for patients untreated and patients in remission compared with patients with refractory disease. Our data indicate that allogeneic HSCT leads to prolonged survival in close to one-half of the patients transforming to MDS or AML from SAA.
PATIENTS AND METHODS This study was conducted by the Severe Aplastic Anemia Working Party (SAAWP) and the Chronic Malignancies Working Party (CMWP) of the European Group for Blood and Marrow Transplantation (EBMT). For each transplantation performed, a center reports minimum essential data (MED-A) to a central database. Many centers report a more comprehensive dataset (MED-B) as well. Informed consent was obtained locally according to the regulations applicable at the time of transplantation. Since January 1, 2003, the EBMT has required centers to confirm that written informed consent has been obtained before data acceptance. The study included 140 patients from 77 EBMT centers who underwent transplantation over a 22-year period (1987 to 2009).
RESULTS One-hundred and forty patients, including 81 males (58%), were identified in the EBMT database of the CMWP. The median age at time of HSCT was 29 years (range, 1 to 66 years). The median interval from diagnosis of SAA to transformation was 65 months (range, 3 to 214 months), and that from diagnosis of MDS to HSCT was 6 months (range, 2 to 30 months). Of the 140 patients, 104 (74%) were diagnosed with MDS, and 36 (26%) had transformed to AML. MDS was classified as refractory anemia (RA) in 37 cases (26%), refractory anemia with ringed sideroblasts (RARS) in 18 (13%), RAEB/refractory anemia with excess of blasts in transformation (RAEBt) in 7 (5%), chronic myelomonocytic leukemia (CMML) in 4 (3%), and unclassified in 36 (26%). At the time of HSCT, 27 patients (19%) were in any complete remission, 48 (34%) were untreated, 41 (29%) were refractory, and 24 (17%) were other/unclassified.
After two successive rounds of capture, >90% of the resulting cDNAs were GH11 sequences, of which 70% (38 among 53 sequenced genes) were full length. Between 1. 5 and 25% of the cloned captured sequences were expressed in Saccharomyces cerevisiae. Sequencing of polymerase chain reaction-amplified GH11 gene fragments from the captured sequences highlighted hundreds of phylogenetically diverse sequences that were not yet described, in public databases. This protocol offers the possibility of performing exhaustive exploration of eukaryotic gene families within microbial communities thriving in any type of environment.
Moreover, explorative probe design strategies using appropriate software such as HiSpOD  10  or KASpOD 11 allow recovering not yet described homologous sequences. 9 These probes are synthesized as biotinylated RNA oligonucleotides and hybridized, in solution, to the target gene sequences diluted among a majority of non-target DNA fragments. The hybrid molecules (biotinylated probes þ target sequences) are then specifically captured by affinity binding on streptavidin-coated paramagnetic beads. SHS can be repeated several times successively to increase the enrichment in desired sequences by a factor of up to 1. 7 Â 10 5 times. 9 In environmental microbiology, the captured DNA fragments can be subjected to high-throughput sequencing. In silico assembly of the reads not only leads to the reconstruction of the full-length sequences of the different members of the targeted gene family, but also of their genomic environment and could therefore facilitate operon reconstructions.
21 Despite these obvious interests, very few environmental genomics studies specifically focus on soil eukaryote functional diversity. 22 o promote such studies, we developed and evaluated in the present report an original adaptation of the SHS for the efficient recovery of full-length functional fungal cDNAs synthesized from soil RNA. Successful development of this technique was favoured by the ever increasing number of available fungal genomes that provide a correspondingly large number of members of specific gene families for the design of hybridization probes. 23 The fungal gene family targeted in this study is the Glycoside Hydrolase 11 (GH11) family which encode endo-b-1,4-xylanases (E. C. 3. 2. 1. 8) (CAZY Carbohydrate Active Enzymes database, http://www. cazy. org). 24 As xylan is the second most abundant polysaccharide in nature and one of the major structural polysaccharide in the plant cell wall, such enzymes have an obvious importance for soil ecology and for the degradation of plant hemicelluloses.
Capture probe design and synthesis As in July 2012, all publicly available GH11 DNA coding sequences of eukaryotic origin were identified by BLAST searches  30  and collected from GenBank (http://www. ncbi. nlm. nih. gov/genbank/), the Joint Genome Institute database (http://jgi. doe. gov/), the Broad Institute genome database (http://www. broadinstitute. org/) and CAZy (http://www. cazy. org/). A set of thirty-five 31-mers, degenerate capture probes, targeting the catalytic domain of the encoded proteins ( pfam no. PF00457, 540 nucleotide long; Supplementary Fig. S1 ), was designed from a collection of 342 coding DNA sequences using the KASpOD software. 11 Individual probe coverage ranged from 7 to 54% of the 342 sequences, leading to a probe set coverage of 90% (four allowed mismatches).
Phylogenetic analyses Sequences obtained from plasmid inserts were manually edited and corrected. Deduced amino acid sequences were aligned using MUSCLE  39  to GH11 amino acid sequences obtained from public databases. Maximum likelihood phylogeny analyses were generated with the PhyML 3. 0 program using the WAG substitution model as implemented in SeaView v. 4. 40  Phylogenetic trees were drawn in MEGA v. 6. 41.
GH11 cDNA capture As in July 2012, we identified and collected 342 fulllength eukaryotic GH11 DNA coding sequences from public databases, from 113 fungal species and from 2 non-fungal ones. Seventy-two percent of these sequences were from Ascomycotina (85 species), 20% from Basidiomycotina (26 species) and 7% from other taxonomic groups. Prevalence of sequences from Ascomycotina is likely to reflect a greater genome sequencing effort in this taxonomic group, rather than a higher occurrence of the GH11 family among Ascomycotina. 23 Among the publicly available sequences, those putatively full-length sequences ranged in size from 639 to 2,099 bp. Occurrence of carbohydrate-binding motives or of C-terminal, non-catalytic extensions in the encoded polypeptides accounted for most of these size variations.
Selectivity of the SHS GH11 capture To evaluate the diversity of GH11 sequences at each step of the capture protocol, we performed a highthroughput Illumina MiSeq sequencing of GH11 amplicons obtained from all four cDNA samples, prior (H0) and after one (H1) or two (H2) cycles of SHS capture. Paired-end sequence reads were assembled to reconstitute the ca. 281-bp-long amplicons. Altogether, the total data set contained 334,161 full-length amplicon sequences that were clustered at a 95% nucleotide sequence identity threshold to produce a total number of 1,458 clusters, of which 1,001 (69%) were singletons (data summarized in Table  2  for each sample). Each of the 12 sequence data sets (4 cDNA samples Â the 3 steps of the SHS) was characterized by few dominant clusters encompassing most of the sequences and a large number of clusters each containing a few, or even a single, sequences (illustrated in Fig.
3A  for the PUE sample). None of the sequences obtained were identical to sequences deposited in databases. Only 17 of the sequence clusters, of which 14 exclusively from the BEW site, were. 90% identical (maximum value of 97. 5%) at the nucleotide level over their entire length to GH11 genes from either the Basidiomycota Tulasnella calospora or the Ascomycota Nectria haematococca and Pyrenophora teres. Figure  3  also showed that the most abundant sequence clusters obtained after one (H1) and two (H2) cycles of capture did not, for a majority of them, correspond to the most abundant clusters present before capture (H0). Venn diagrams drawn using only these most prominent sequence clusters, encompassing altogether 90-93% of sample sequences, showed that there existed a larger overlap between the postcapture samples H1 and H2 than between the precapture samples H0 and H1 or H2 (Fig.
Thanks to the ever increasing number of published fungal genomes, representative of the phylogenetic diversity of this taxonomic group; explorative probe design strategies could be carried out to unravel the metabolic capacities of these microorganisms within different ecosystems. Besides GH11 sequences, SHS capture can be implemented for any other gene family of interest, allowing a comprehensive taxonomic or functional description of the studied microbial community. As mentioned in the introduction, sequence capture presents the advantage over PCR to give access to the full-length gene sequence, including facultative modules, not always associated to the studied catalytic domain. This was indeed the case for the GH11, for which we estimated that 72% of the captured sequences were full length and that 15% of them processed a C-terminal, fungal-specific, CBM1 module (see the CAZy database, http://www.
cazy. org). A discrepancy however existed between the estimated fraction of full-length captured GH11 cDNA and the systematically lower fraction of cDNAs which produced a functional enzyme upon expression in S. cerevisiae. The absence of expression in yeast can be attributed to a number of independent factors such as bias in codon usage, non-recognition by S. cerevisiae of the protein signal peptide necessary for correct secretion, protein misfolding or hyperglycosylation. Some of these problems could be addressed by using expression plasmids including a yeast signal peptide downstream of the cloning site and/or by using a different yeast species for protein production. Sequencing of PCR fragments amplified from captured cDNAs also indicate that altogether the four captured cDNA samples obtained in this single study encompass a greater number of novel and different GH11 sequences than have been deposited and are available in public databases over several decades.
Countless subtleties (such as the C'-profile, a C-profile with abolished lung sliding) will be included in the extended BLUE-protocol, a definitive version of the BLUE-protocol, which must be considered as a preliminary approach using simplicity. Auscultation data, echocardiographic data also will be included. Regarding rare, double, absent causes, read  [42]. Falsepositives and false-negatives are of interest, because ultrasound provided data that questioned a posteriori the value of the "gold standard"  [36]. Let us remind that, more than simple CT (which isolated does not have a perfect discriminatory power for a given disease), the "gold standard" was the final diagnosis of the hospitalization report.
• The product retailer stores the product data on the user's smartphone, thus personalizing the secure element and the applications. • The validator can initiate a control with the smartphone of the user when he is traveling in the transport system, in order to check the authenticity and the validity of his pass. Note that the service operator, application retailer and product retailer are usually different entities. For instance in our context, the application retailer could be a telecommunication operator that installs the application into its own secure element, which we refer to as the UICC (for Universal Integrated Circuit Card) but is also known as the SIM (for Subscribe Identity Module) card. Then, the product retailer could be an external seller of e-tickets that needs the involvement of the application retailer in order to load these tickets into the UICC/SIM card or that uploads itself the etickets directly into the UICC/SIM card by relying on cryptographic material provided by the application retailer.
The T&T service is one of the first contactless mobile ticketing services. A user must first subscribe to the service by showing his identity along with the information about his bank account. Afterwards, he gets a user number and a PIN that allows to use the T&T application. To travel from a station A to a station B, the user must start the T&T application upon departure by using a touchpoint if one is available at the station, relying on the GPS as captured by his smartphone or based on the location based on the network cell. Once he has reached his destination (e. g. , station B), the user must indicate to the application that this is the end of his trip. When controlled, the T&T application generates and displays a QR code to prove that the payment for the trip has been done. Regarding the privacy aspect of T&T, Pirker and Slamanig  [17]  have pointed that T&T stores the list of all the recent trips in a centralized database.
( 17 ) (C 1 , C 2 ) ← ([sk u ]G 1 , [sk u ]G 2 ) C 1 ,C 2 -------If e(C 1 , G 2 ) = e(G 1 , C 2 ) Then: µ -------µ ← Signature(sk o , C 1 ) Store (C 1 , C a $ ← -Z p A ← [a]G 1 B ← [y]A C ← [x](A + D) A,B,C,D --------D ← [a. y]C 1 Store (user, C 1 ) in DB t Table  1. Protocols for the registration phase. 2) The opening authority verifies that these computations are correct. More precisely, the opening authority checks if e(C 1 , C 2 ) = e(G 1 , G 2 ). If this verification succeeds, it means that C 1 and C 2 are commitments on the same secret value (sk u here). In this case, the opening authority sends back a signature µ of C 1 and stores the triplet (C 1 , C 2 , µ) in the database DB o , which has to remain private and secure. Then, upon receiving the signature µ, the m-pass cardlet sends (C 1 , µ) to the transport authority, which then checks the validity of the signature using pk o.
If the signature is valid, the transport authority computes and sends a CL-certificate  [35]  (A, B, C, D) on the private key of the user (recall that CL-signature schemes allow a signature to be issued on the messages that are not known to the signer, but to which the signer only knows a commitment). The transport authority also saves (ID user , C 1 ) inside his database DB t. The databases DB o and DB t will be used only for deanonymizing or blacklisting of users as detailed later in Sections 6. 3 and 6. 4. Once the registration phase is finished, the user is registered in both the transport and opening authorities databases. In addition, he is now able to use his m-pass application to access the transport service. M-pass validation. The validation of the m-pass, described in Table  2 , is used by the user to prove his legitimacy to use the transport service without disclosing his identity.
Based on this signature and the secret database DB o , the opening authority searches for the triplet (C 1 , C 2 , µ) such that e(J, C 2 ) matches with e(K, G 2 ). If the equality holds, this means that C 2 and K are two commitments on the same secret value (i. e. , sk u in this case). Then, it replies with the corresponding C 1. Finally, based on the database DB t and the received C 1 , the transport authority finds out the identity of the user ID user.
Blacklist management The blacklisting procedure, described in Table  4 , allows the transport authority to revoke an m-pass such that it cannot access anymore to the transport service. For example, a user that has lost his smartphone can ask the transport authority to blacklist his m-pass, or in case of a fraud the de-anonymized m-pass can be blacklisted by the transport authority. If the transport authority wants to exclude a user, the authority seeks for the relevant commitment, C 1 , of the user in the database DB t and sends it to the opening authority. Upon receiving C 1 , the opening authority retrieves the corresponding commitment C 2 and computes, for all the possible bsn starting from the time the m-pass is blacklisted, e(H 1 (bsn), C 2 ). The number of computed e(H 1 (bsn), C 2 ) could appear to be large, but it stays limited as we propose to renew regularly the group public keys to implement the validity duration of all m-passes, as explained in Section 6.
After that, C 1 is recovered and the transport authority has the corresponding identity in his database. Unlinkability is only achieved partially. Indeed the value K = [sk u ]H 1 (bsn), which is involved in the signature computation, is a deterministic function of the bsn value sent by the validator. Unlinkability is therefore only ensured across periodically refreshed bsn values. Consequently, if the validator is malicious and always sends the same value bsn during the validation, the m-pass can be tracked with the value J. This malicious validator could then use the logs from those readers and track the entries and the exits of a user thanks to the occurrence of the value H 1 (bsn). Note that the m-pass cardlet could detect such an attack by a simple comparison between the previously received value (or possibly the list of the previous values of bsn if enough memory is available) and the current one.
Implementation In this section, we describe the prototype implementing the proposed protocol. We implemented all the steps of a transport service including the user registration, the product registration and the contactless validation. The software components involved in the transport service are represented in Figure  2. The transport authority is a Tomcat application deployed on a web server. The validator is simulated by a Java swing application connected to an NFC reader using the ISO14443B protocol. The cardlet is embedded in an smartcard that supports javacard applications. We used a regular Galaxy S3 smartphone running Android 4. 1. 2. The Android system does not need any modification as the Seek for Android patch  [36]  has been already added by Samsung in order to access secure elements.