dataesr/scientific-paragraphs-categorization huggingface dataset:
Li, Zhou, and Ng's approach is also different from ours in that they do not attempt to induce common representations useful for both tasks or for many languages, and as such cannot be regarded as multi-task, nor as multilingual, learning. Synchronous grammars provide an elegant way to handle multiple levels of representation. They have received much attention because of their applications in syntaxbased statistical machine translation  (Galley et al. 2004; Chiang 2005; Nesson and Shieber 2008)  and semantic parsing  (Wong and Mooney 2006, 2007). Results indicate that these techniques are among the best both in machine translation and in the database query domain. Our method differs from those techniques that use a synchronous grammar, because we do not rewrite pairs of synchronized non-terminals, but instead synchronize chunks of derivation sequences.
Acknowledgments The authors would particularly like to thank  Andrea Gesmundo  for his help with the CoNLL-2009 shared task. The research leading to these results has received funding from the  EU   FP7 programme  ( FP7/2007-2013)  under grant agreement no. 216594  ( CLASSIC  project: www. classic-project. org),and from the  Swiss NSF  under grants  122643  and  119276.
RESAOLAB developed an open-source Laboratory Information and Management System (Lab-Book) for monitoring all daily surveillance activities (from requests for analysis to reporting). Based on jointly defined reference terms, Lab-Book contains an epidemiological application for reporting laboratory data; in collaboration with WHO/AFRO, RESAOLAB conducted a regional workshop to discuss use of the new tool, including the role of the laboratory in reporting epidemiological data to surveillance databases. Fifteen laboratories in each country are expected to participate in a pilot launch of Lab-Book. The network also proposed computer and other equipment, Internet services, and training that will be necessary for integrating Lab-Book across the region.
Conclusion RESAOLAB grew from national and regional dialogue around the need for harmonized tools and processes. It serves as a model for groups of neighboring countries that would like to strengthen the laboratory component of their disease surveillance infrastructure by jointly developing and implementing trainings and other activities and by harmonizing and linking national databases into integrated regional systems. As described elsewhere in this special issue of Emerging Health Threats, other regions, like South East Europe, are taking similar steps to strengthening disease surveillance laboratory capacity  (11).
The differential phenotypic characteristics with other Bacillus species are summarized in Table  2. Matrix-assisted laser-desorption/ionization timeof-flight (MALDI-TOF) MS protein analysis was carried out as previously described  [8, 43]  using a Microflex spectrometer (Bruker Daltonics, Germany). Spectra were compared with the Bruker database that contained the main spectra from 3,769 bacteria including 129 spectra from 98 validly named Bacillus species. No significant score was obtained, thus suggesting that our isolate was not a member of a known species. We incremented our database with spectrum from strain JC6 T (Figure  4 ). Finally, the gel view allows us to highlight the spectra differences with other Bacillus genera members Figure  5.
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to other members of the genus Bacillus, and is part of a study of the human digestive flora aiming at isolating all bacterial species within human feces  [1, 2]. It was the 268 th genome of a Bacillus species, and the first genome of B. massiliosenegalensis sp. nov. The Genbank accession number is CAHJ00000000 and consists of 102 contigs. Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [44].
Genome annotation Open Reading Frames (ORFs) were predicted using Prodigal  [45]  with default parameters. However, the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank  [46]  and Clusters of Orthologous Groups (COG) databases using BLASTP. tRNAs and ribosomal RNAs were predicted using the tRNAScanSE  [47]  and RNAmmer  [48]  tools, respectively. Lipoprotein signal peptides and numbers of transmembrane helices were predicted using SignalP  [49]  and TMHMM  [50] , respectively. ORFans were identified if their BLASTP E-value was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05. Such parameter thresholds have already been used in previous works to define ORFans.
Negative for indole. Presence of catalase activity. Using the API 50CH system, positive reactions are observed for aesculin, D-cellobiose, D-glucose, D-maltose, Nacetyl-glucosamine and D-trehalose. Using the API ZYM system, a positive reaction is observed for αglucosidase and weak reactions are observed for alkaline phosphatase, esterase lipase, valine arylamidase and trypsin. Using the API 20E system, a positive reaction is observed for nitrate reduction and a negative reaction is observed for urease. B. massiliosenegalensis is susceptible to amoxicillin, ceftriaxone, imipenem, trimethoprim/sulfamethoxazole, gentamicin, ciprofloxacin, rifampicin and vancomycin, but resistant to metronidazole and erythromycin. The G+C content of the genome is 37. 60%. The 16S rRNA and genome sequences are deposited in Genbank and EMBL under accession numbers JF824800 and CAHJ00000000, respectively.
Raw data for gene expression signals was extracted using the Affymetrix GeneChip Operating Software (version 1. 4). For further data collection and assessment, R language version 2. 15 (bioconductor project) was used. Probe signal values were subjected to GeneChip-robust multiarray average algorithm (GC-RMA;  Wu and Irizarry, 2004). Probes which were below the background signal in all samples were not considered for further analysis. The results were analyzed by the following linear model using the lmFit function in the limma package in the R environment: S gyr = GY gyt + R r + ε gyr , where S is log 2 expression value, GY, genotype:time interaction, and random factors; R is biological replicate; ε, residual. The eBayes function in the limma package was used for variance shrinkage in calculating the p-values and the Storey's q-values were calculated using the q-value function in the q-value package from the p-values  (Storey and Tibshirani, 2003).
01 and >2-fold change; Cluster 3), and the Arabidopsis genomic background (background). Statistical significance of the t-values generated by POBO was calculated using the linked Graphpad application for a two-tailed comparison: *Comparison of Cluster 2 and background (p < 0. 0001); *Comparison of Cluster 2 and Cluster 3 (p < 0. 0001); *Comparison of Cluster 3 and background (p < 0. 0001). Analysis of gene ontology (GO) terms for the 250 RRS1-dependent genes was performed using Agrico 3. Microarray data have been submitted to the Gene Expression Omnibus database (GEO accession no. GSE50019).
ACKNOWLEDGMENTS We thank our colleagues for helpful discussions. This work was supported by The  Max-Planck Society , a  Deutsche Forschungsgemeinschaft  grant in SFB 670 ( Jane E. Parker ,  Katharina Heidrich ,  Jaqueline Bautor ) and a  BMBF-funded Plant-KBBE Trilateral "BALANCE" project grant  ( Jane E. Parker ,  Servane Blanvillain-Baufumé ). Katharina Heidrich  was recipient of an IMPRS PhD fellowship.
Once enrolled in a specific clinic, HIV-infected patients are requested to get all future treatment -provided at no charge -at that same clinic each month. Their contact numbers (if available) and information related to their clinic visits are recorded in their clinic record. To identify the outcome of patients lost to follow-up, study investigators called the patient's telephone number listed in the clinic record or his attendant's telephone number if this existed in the record. Patients were classified into two groups with respect to the time between the beginning of ART and loss of follow-up: early (less than or equal to 6 months) and late (more than 6 months). Data were collected using a form validated by the Togolese National AIDS Program that had been tested in five clinics in Lomé. Six teams were deployed for data collection.
Each team included two medical students who received two days of training on how to review patient's records in the HIV clinics; for each team, the two medical students reviewed the same patients' records and then the study team reconciled inconsistencies in the information collected by individual abstractors Data were recorded using the software Epi Info version 3. 5. 1. For continuous variables, medians and interquartile ranges were calculated while for categorical variables we calculated proportions and respective 95% confidence intervals. Our main outcome variable was loss to follow-up at less than or equal to 6 months compared to loss to follow-up at greater than 6 months. The chisquare test or Fisher´s exact test were used when appropriate in bivariate analysis. Multivariate backwards stepwise logistic regression analysis was performed to identify independent risk factors for the dichotomous outcome lost to follow up or not lost to follow up.
Limitations As with many retrospective studies, data were missing from many patients, particularly for information collected during the phone follow-up component. Consequently, we likely did not fully evaluate some important risk factors. Additionally, data may have been incompletely recorded in medical records. This could have affected risk factor data (e. g. , incorrect or missing CD4 counts) or outcome data (e. g. , lack of accurate recording of death or change of residence for patients on ART). This is a necessary limitation for our study, where we aimed to determine risk factors for lost to followup in actual practice. While we could have performed a prospective study with periodic patient tracking (e. g. , weekly) this design would have altered usual care seeking behaviors.
DNA Sequence analysis Mitochondrial sequences for cytochrome oxidase I (CoI), tRNA-leu and the 5'-end of cytochrome oxidase II were obtained for 13 H. t. thelxinoe and 3 H. t. tristero specimens using primers and PCR conditions described in  (Dasmahapatra et al. , 2010)  (Table  S1 ). Mitochondrial sequences were obtained from GenBank for H. melpomene (Table  S1  and S2 ), for species in the cydno-group  (H. t. timareta, H cydno, H. heurippa, H. t. tristero, H. pachinus)  and for the outgroup species H. numata (accession numbers in Table  S2 ). Nuclear sequences of the sex-linked gene triosephosphate isomerase (Tpi) were amplified and sequenced for 3 H. t. thelxinoe (primers and PCR conditions as in  (Dasmahapatra et al. , 2010) , and additional sequences for the other taxa were obtained from GenBank (Table  S1  and S2 ).
Sequences generated for the present study are available on GenBank (Accession number: KC435427 to KC435446). Phylogenetic relationships were inferred using maximum likelihood with RAxML Blackbox  (Stamatakis, P. Hoover & Rougemont, 2008)  and Bayesian inference in Beast 1. 6. 2 (Drummond & Rambaut, 2007). In maximum-likelihood and Bayesian inference, each gene was analysed with a GTR+G model, as suggested by the model testing done with jModel Test 1. 1  (Posada, 2008)  and parameters of this model were estimated independently for each gene. In Bayesian inference, the tree prior was set to the Yule speciation process. Branch lengths were modelled under a relaxed clock assumption with an uncorrelated log-normal distribution. Default parameters were used for all priors. We ran the analyses for 10 million generations, and sampled every 1000 generations.
The size and shape of red and yellow colour patches characteristic of the so-called "postman" pattern of this pair of mimetic species, and hereafter called "colour patch", were described by the 2D coordinates of a subset of 10 landmarks placed at the intersection of the outline of the colour patches and veins (Fig. 2C : #16 to 25 and #41 to 49). Colour patch landmarks were taken on both dorsal and ventral sides. Wing and colour patch data were analysed jointly and separately. Landmark coordinates were scored by the same person using TpsDig2  (Rohlf, 2010). Landmark coordinates were superimposed using a general procrustes analysis  (Rohlf & Slice, 1990; Bookstein, 1991; Goodall, 1995; Bookstein, 1996; Dryden & Mardia, 1998; Zelditch et al. , 2004). Standard tests of repeatability were done by taking the landmarks five times per wing on subsamples of five butterflies from a single species, population and sex.
All subsets of wing shape and colour patch shape (FW and HW ventral and dorsal side) were analysed separately and then pooled. The overall phenotypic similarities between species were depicted using a neighbour-joining tree computed from the matrix of Malahanobis' D² distances. Species identity was first assessed by eye and confirmed by microsatellite genotype data for 160 samples out of 202. Differences between H. timareta and H. melpomene were first explored using only the 160 genotyped specimens and a linear discriminant analysis (LDA). This LDA was computed on a combined dataset of all the landmarks on both forewing and hindwing (cross-validation: CV= 100%). A predictive LDA was then used to identify the nongenotyped specimens. The confidence with which a specimen is assigned to one of the two groups corresponds to the posterior probabilities of classification, which depends on the relative distance of the specimens to the group means (Table  S1 ).
Mitochondrial data and nuclear DNA Bayesian and maximum likelihood analyses on a combination of mtDNA and nuclear DNA support the existence of two well-supported clades, an H. melpomene clade including H. m amaryllis and H. m. aglaope, and a clade containing H. cydno and related species H. heurippa, H. timareta, and H. t. tristero, and including our H. t. thelxinoe specimens (Fig. 3A ). This is consistent with the phylogeny based on genome-wide RAD markers presented in  (Heliconius Genome Consortium, 2012) , and confirms the identity of this population as a member of the cydno clade, closely related to H. t. timareta from Ecuador, which is also the geographically nearest cydno cognate in our dataset.
Acknowledgments We thank  Benigno Calderón ,  Nicolas Chazot ,  Jae-Woo Chung ,  Mathieu Chouteau ,  Stéphanie Galluser ,  Mélanie McClure ,  Owen McMillan ,  Jérôme Murienne ,  Ronald Mori Pezo ,  Joel Pintado ,  Lisa de Silva ,  Armando Silva Vásquez ,  Fraser Simpson ,  Cesar Ramirez ,  Neil Rosser  for their help at various stages of fieldwork and  URKU Estudios Amazónicos  for their support in Tarapoto. We thank the  Ministerio de la Agricultura (ex-INRENA) , the  SERNANP-Bosque de Protección Alto Mayo  and  PEHCBM-Area de Conservacion Regional Cordillera Escalera  for collection and export permits. We are very grateful to  Chris Jiggins ,  Richard Merrill  and  Blanca Huertas  for access to specimens and wings,  Michel Baylac  for the latest version of Rmorph and  Neil Rosser  for maps.
Study Population and Clinical Data The International Collaboration on Endocarditis-Prospective Cohort Study (ICE-PCS) is a prospective, multicenter, international registry of patients with IE. 35, 36  Data based on standard definitions were collected prospectively between January 1, 2000, and December 31, 2006, from 64 sites in 28 countries. The study was approved by the institutional review boards or ethics committees at all participating sites. Inclusion criteria for this study cohort were patients diagnosed with definite PVE based on the modified Duke criteria. 37 atients with the following characteristics were excluded: native and nonnative valve IE (eg, pacemaker IE), receipt of surgery before admission, and missing values for sex, receipt and/or date of surgery, length of initial hospitalization, inhospital death, and death at 1-year follow-up.
Standard Univariate and Multivariable Analysis Baseline characteristics and outcomes of patients with PVE who received early surgery were compared with those receiving medical therapy alone using the Wilcoxon rank sum test for continuous variables and the χ 2 test for categorical variables. Unadjusted HRs were computed using a univariate Cox proportional hazards model. A multivariable Cox proportional hazards model with IPTW was performed to identify independent predictors of inhospital and 1-year mortality (see the IPTW and Adjustment for Survivor Bias subsection below). This model included 19 clinically relevant variables (Supplement [eTable]). All of the variables used in the multivariable model had data collected for 97% or more of patients. Missing values for clinical outcomes were imputed with the negative category for categorical variables.
A recent study reported in the Society of Thoracic Surgery database 40 showed a low operative mortality in IE (8%), but the study did not specifically evaluate PVE, and surgery during the active stage of IE was associated with a 2-fold higher operative mortality. In our study, early surgery was not associated with a mortality benefit in the overall cohort after adjusting for treatment selection and survivor bias. The findings of our subgroup analysis support the American Heart Association guidelines because patients with the highest predicted probability of surgery (ie, those with the surgical indications mentioned above) had lower mortality rates when they received surgery vs medical therapy. However, these findings should be interpreted cautiously as results of a post hoc subgroup analysis that did not adjust for survivor bias.
Previous studies of PVE have found conflicting results regarding the effect of surgery. In a previous study by the International Collaboration on Endocarditis Investigators 41 of retrospectively merged IE databases with propensity matching, surgery and medical therapy had similar in-hospital mortality rates, but longer-term outcome was not evaluated. In planning the present study, we had hypothesized that a survival benefit of surgery may not be apparent during the initial hospitalization given the higher operative risk of patients with PVE. However, after adjusting for selection and survivor bias in the surgical group, mortality rates remained similar even at 1 year after PVE for both treatment groups and were strongly related to host factors, pathogen, and particularly complications of PVE (heart failure, stroke, and paravalvular complications).
The timing of PVE diagnosis relative to the date of prosthetic valve implantation was not evaluated because of missing data. Data regarding the presence of surgical indications in medically treated patients and the reason for not undergoing valve surgery were also unavailable for most patients in the cohort. However, other variables included in these analyses, such as health careassociated infection and causative organism (staphylococcal), correlate with early PVE characteristics. Data regarding surgery after hospital discharge were not routinely collected; among 252 of 392 patients (64%) who received medical therapy and survived to hospital discharge, only 24 of 252 patients (10%) had undergone surgery at 1-year follow-up. In conclusion, approximately one-third of patients with PVE die within 1 year after diagnosis, with mortality strongly associated with other chronic illness, health care-associated infection, S aureus, and complications of PVE.
For every spectrum, a maximum of 100 peaks at most were compared with the spectra in database. The resulting score enabled the identification of tested species: a score ≥ 2 with a validly publsihed species enabled identification at the species level, a score ≥ 1. 7 but < 2 enabled identification at the genus level, and a score < 1. 7 did not enable any identification. No significant MALDI-TOF score was obtained for strain JC301 T against the Bruker database, suggesting that our isolate was not a member of a known genus (Figures  4  and 5 ). We added the spectrum from strain JC301 T to our database. sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from the Gene Ontology project  [33]. If the evidence is IDA, then the property was directly observed for a live isolate by one of the authors or an expert mentioned in the acknowledgements.
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to other members of the suborder Micrococcineae, and is part of a "culturomics" study of the human digestive flora aiming at isolating all bacterial species within human feces. It was first genome of Timonella senegalensis gen. nov. , sp. nov. A summary of the project information is shown in Table  3. The Genbank accession number is CAHH00000000 and consists of 78 contigs. Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [35].
Genome annotation Open Reading Frames (ORFs) were predicted using Prodigal  [36]  with default parameters but the predicted ORFs were excluded if they were spanning a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank database  [37]  and the Clusters of Orthologous Groups (COG) databases using BLASTP. The tRNAScanSE tool  [38]  was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer  [39]  and BLASTn against the GenBank database. Signal peptides and numbers of transmembrane helices were predicted using SignalP  [40]  and TMHMM  [41]  respectively. ORFans were identified if their BLASTP E-value was lower than 1e -03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05.
Such parameter thresholds have already been used in previous works to define ORFans. To estimate the mean level of nucleotide sequence similarity at the genome level between T. senegalensis strain JC301 T , Sanguibacter keddieii strain ST-74 T (GenBank accession number CP001819) and Cellulomonas fimi strain ATCC 484 (GenBank accession number CP002666), we identified orthologous proteins using the Proteinortho software (version 1. 4) and the following criteria: 30% amino acid identity and a E-value of 1e -05. The average percentages of nucleotide sequence identity between corresponding orthologous sets were then determined using the Needleman-Wunsch algorithm global alignment technique. Artemis  [42]  was used for data management and DNA Plotter  [43]  was used for visualization of genomic features.
Genome comparison with Sanguibacter keddieii and Cellulomonas flavigena We compared the genome of T. senegalensis strain JC301 T with those of Sanguibacter keddieii strain ST-74 T (GenBank accession number CP001819)  [45]  and Cellulomonas fimi strain ATCC 484 T (GenBank accession number CP002666). The T. senegalensis genome is smaller in size than those of S. keddieii and C. fimi (3. 0, 4. 5 and 4. 2 Mb, respectively). The G+C content of T. senegalensis is lower than that of S. keddieii and C. fimi (61. 40%, 71. 90% and 74. 72%, respectively). The gene content of T. senegalensis is also lower than S. keddieii and C. fimi (2,793, 3,800 and 3,875 genes, respectively). Moreover, T. senegalensis presented a lower ratio of genes per Mb than S. keddieii and C. fimi (917, 931 and 922, respectively) and a comparable number of genes assigned to COGs (69.
Susceptible to amoxicillin, imipenem, ciprofloxacin and gentamicin but resistant to trimethoprim/sulfamethoxazole and metronidazole. The potential pathogenesis of the type strain JC301 T is unknown. The type strain is JC301 T (= CSUR P167 = DSMZ 25696) was isolated from the fecal flora of a healthy patient from Dielmo (a rural village in the Guinean-Sudanian zone in Senegal). The genomic DNA G+C content of the type strain is 61. 4 mol%. The 16S rRNA gene sequences were deposited in GenBank with the accession number JN657220. The whole-genome shotgun sequence of T. senegalensis strain JC301 T has been deposited in GenBank/DDBJ/EMBL under accession number CAHH00000000.