dataesr/scientific-paragraphs-categorization huggingface dataset:
Or again, as in the new MASS (Module for the Analysis of SurSaUD and Sentinelles' data) system  [69]  designed by Santé Publique France, combining 3 statistical methods and 3 different data sources, used since January 2016 to define the public health alerts. Finally, the epidemiologic analysis and interpretation steps (figure  1 ) were not fully automated. Some work still needs to be done, especially the whole Sentinelles data extraction process. Some similar job was done before on another project  [97] [98].
While preparing an essay for the catalogue accompanying the exhibition Lawrence Alma-Tadema: At Home in Antiquity, the British scholar Alistair Grant learned that the French could supply these replicas to the South Kensington Museum just as easily as their English competitors Elkington could. Thus, Alma-Tadema, as a regular visitor to that museum, bought his expensive replicated antiquities close to home and used them again and again. This is just one example, and there are many more on the horizon. As we locate more of the objects enumerated in the 1913 auction catalogue, it would be ideal to bring them together in a virtual world-a database to which we all could add information, and around which we could discuss issues and raise questions of mutual interest. The Alma-Tadema project has also inspired me to consider the furnishings of the studio-house of the painter Christofel Bisschop (1828-1904).
research. sickkids. ca/ oasis/greatnetwork-pc-api/) Data Centre of the OASIS built an electronic and online tool using RedCap © (Research Electronic Data Capture; https://redcap. vanderbilt. edu/). Participating GARD countries can use the system with internet access; no specific software or hardware installation is required. Data will be securely transmitted and stored in the Research Institute of the Hospital for Sick Children, Ontario, Canada-the home of the GREAT Data Centre. Alternatively, aggregated data could be sent to the GREAT Data Centre by email, regular mail or fax using a fillable PDF or hard copies of completed indicator forms (such as Figures  1  and 2 ).
Step 4: generating common statistics and metrics for comparisons If individual patient level data are submitted on an ongoing basis, a quarterly report will be generated by the GREAT Data Centre and sent to participating countries and sites for their information. The quarterly report is based on aggregating the patient data, so no individual patient level data will be released, thereby safeguarding patient privacy and protecting data confidentiality. Each participating GARD country and site will see their site-specific statistics. Annually, based on data submitted by all participating GARD countries, an overall GARD CRD Indicator report will be generated showing the distribution of CRD burden by indicator and by country. A sample report is shown in Figure  S2. This report will highlight areas for GARD countries to target for intervention and disease management in order to reduce the CRD burden.
These reports will be presented annually during the GARD General Meeting, given to the WHO, and may result in a peer-reviewed publication. The GREAT Data Centre has the mission of (I) establishing and promoting a methodological strategy for outcome evaluation; (II) supporting uniform data collection and statistical analyses at country and regional levels; (III) encouraging cross-country and global comparisons; and (IV) assessing the impact of activities undertaken in support of GARD objectives. As well, since 2010, the GREAT Data Center has been providing students, trainees, clinicians, researchers and policymakers with a platform for knowledge transfer and exchange. The Center will offer ongoing support to GARD activities through hosting a platform for learning (methods), sharing and exchanging (experiences and challenges), generation of knowledge through health policy investigative research.
Discussion In this paper, we proposed a strategy for CRD surveillance and the evaluation of CRD interventions in GARD countries. This strategy is implemented through four steps: (I) adopting evidence-based indicators to assess CRD quality of care; (II) identifying reliable data sources for populating CRD indicators; (III) uploading data for analysis; and (IV) generating common statistics and metrics for comparisons. We also recommended the use of a simple standardized and platform-free tool (PC-API) to measure and compare asthma quality of care. The GREAT Data Centre will provide ongoing support to centralize collection and reporting of data, and will also facilitate cross-country comparisons of CRD burden over time. For every country interested in developing a GARD action plan, these indicator data should be collected and reported on an ongoing basis for the population-level surveillance of CRDs, as well as prior to and following the implementation of interventions.
ACKNOWLEDGEMENTS This work was supported by  HHMI , the  NIH  grant  R01 GM29169  (to J. F. ), and the  ANR @RAction program  grant for  CryoEM80S ,  ANR-14-ACHN-0024 , and this work benefits from funding from the state, managed by the  French National Research Agency as part of the Investments for the Future program  (to Y. H. ).
Public key server is a simple yet effective way of key management in secure end-to-end communication. To ensure the trustworthiness of a public key server, transparent log systems such as CONIKS employ a tamper-evident data structure on the server and a gossiping protocol among clients in order to detect compromised servers. However, due to lack of incentive and vulnerability to malicious clients, a gossiping protocol is hard to implement in practice. Meanwhile, alternative solutions such as EthIKS are not scalable. This paper presents Trusternity, an auditing scheme relying on Ethereum blockchain that is easy to implement, scalable and inexpensive to operate.
APPROACH We developed Trusternity as an extension to CONIKS  [6] , the first transparent log key management solution for end users. In CONIKS, a user runs a client software to upload their public keys to a CONIKS server. Our Trusternity extension allows the CONIKS server to disseminate a public verifiable proof to the blockchain. When a client downloads public keys from the server, it can cross-check this proof value from the blockchain with the downloaded data to ensure the integrity of the key server. We depict Trusternity architecture in Figure  1. Our system contains four modules: Server, Smart Contract, Storage and Client. (1) Trusternity server: A Trusternity serverT S is a transparent key server that enables auditing via Ethereum. T S consists of three components: a CONIKS Server S, a Trusternity extension for server Sx and an Ethereum wallet W.
EVALUATION We evaluated Trusternity and compared the results with EthIKS. Security: Trusternity is an extension of CONIKS. Thus, we retain the proven security of the CONIKS client/server data structures and protocols. After each Publish call, T SC holds ST R e of epoch e on Ethereum transaction logs. If T S maliciously updates PK Al ice without informing Alice, Alice can query the log to discover the change in ST R. Even when TC uses a light wallet, the adversary can neither trick TC into accepting a fake transaction nor modify any published ST R due to the immutability property of the blockchain. Network overhead: We theoretically computed the client network overhead by reusing assumptions from EthIKS and Ethereum yellow paper. In particular, we assume a total number of users U = 2 32 and consider that u = 2 21 users update their keys every epoch.
This paper is devoted to the bipartite ranking problem, a classical statistical learning task, in a high dimensional setting. We propose a scoring and ranking strategy based on the PAC-Bayesian approach. We consider nonlinear additive scoring functions, and we derive nonasymptotic risk bounds under a sparsity assumption. In particular, oracle inequalities in probability holding under a margin condition assess the performance of our procedure, and prove its minimax optimality. An MCMC-flavored algorithm is proposed to implement our method, along with its behavior on synthetic and real-life datasets.
The work presented in the present paper is more general as we consider nonlinear scoring functions and derive non-asymptotic risk bounds in probability. Our procedure relies on the construction of a high dimensional yet sparse (pseudo-)posterior distribution (Gibbs distribution, introduced in Section 2). Most of the aforecited papers studying PAC-Bayesian strategies rely on Monte Carlo Markov Chain (MCMC) algorithms to sample from this target distribution. However, very few discuss the practical implementation of an MCMC algorithm in the case of (possibly very) high dimensional data, to the notable exception of  [3] ,  [22]  (both through MCMC) and  [31]  (Sequential Monte Carlo). We adapt the point of view presented in  [22]  and implemented in the R package pacbpred  [21] , which is inspired by  [9, 29].
Risk bounds are presented to assess the merits of our procedure and exhibit explicit non-parametric rates of convergence. To illustrate the practical potential of PAC-Bayesian high dimensional binary ranking, Section 5 presents our MCMC algorithm to compute our estimator, coupled with numerical results on both synthetic and real-life datasets. Conclusive comments on both theoretical and practical merits of our work are summed up in Table  6. Finally, proofs of the original results claimed in the paper are gathered in Section 7 for the sake of clarity.
We now compare our PAC-Bayesian procedure to two state-of-the-art methods, on real-life datasets. Since our work investigates nonlinear scoring functions, we restricted the comparison with similar methods. The Rankboost  [19]  and TreeRank  [7, 15]  algorithms appear as ideal benchmarks. We have conducted a series of experiments on the following datasets: Diabetes, Heart, Iono, Messidor, Pima and Spectf. All these datasets are freely available online, following http://archive. ics. uci. edu/ml/ and serve as classical benchmark for machine learning tasks. Our results are wrapped up in Table  2  (where TRT, TRl and TRg denote the TreeRank algorithm trained with decision trees, linear SVM and gaussian SVM, respectively). For most datasets, our PAC-Bayesian estimators compete on similar ground with the four other methods, intercalating between the less and most performant method, while being the only ones supported by ground theoretical results.
Conclusion We study in the present paper the problem of bipartite ranking in its theoretical and algorithmic aspects, in a high-dimensional setting through the PAC-Bayesian approach. Our model is nonlinear and assumes a sparse addi-. A salient fact is that our results significantly extend previous works  [12] , in that our inequalities hold in probability (instead of inequalities in expectation). A summary of all our theoretical claims is presented in Table  3. Next, we propose an implementation of the PAC-Bayesian estimators through a transdimensional MCMC. Its performance on synthetic and real-life datasets  Faster rates with margin assumption, generic prior Theorem 4 Faster rates with margin assumption, sparsity-inducing prior Theorem 5 On Sobolev spaces, no margin assumption Theorem 6 On Sobolev spaces, with a margin assumption competes with other nonlinear ranking algorithms.
The leaf economics spectrum, one of the most studied axes of trait associations, describes the range from (1) acquisitive strategies with fast return on investment of resources in leaves characterized by high specific area, nutrient concentrations, metabolic rates and short lifespan, to (2) conservative strategies with a slow return on investment characterized by low metabolic rates and expensive leaf construction and defence costs allowing a longer lifespan  1, 3. The validity of this pattern among species at the global scale has been demonstrated using trait databases  3. However, its validity at finer scales is an emerging question: correlated traits can differ in their sensitivity to genetic variation, environmental gradients and ontogeny  6  , and observed patterns in interspecific variation do not necessarily hold within species  17.
This expression is positive if the parts due to species turnover and ITV vary in the same direction, negative otherwise. These analyses were conducted for each forest type separately, using the trait. flex. anova function  12. Categorical traits did not, or very marginally, vary within species, either because the trait is inherent to the species (legumes or not), the method of data collection only considered a single value per species (phenological habit), or recorded values varied very little within species (leaf compoundness and pubescence). To assess correlation between the community values for these traits and successional age, we used quasi-binomial generalized linear models (to account for overdispersion) with a logit link (GLM). We included successional age, forest type and their interaction as explanatory variables and did a backward selection.
We included species as a random factor, both on the intercept of the model and on the slope of H/Hmax (to test if the effect of ontogeny was dependent on the species). Although crown illumination is expected to increase with increasing size, in our dataset the correlation between H/Hmax and CII is low (Kendal rank-order correlation, Tau = 0. 077, P = 0. 033). This allowed us to include both H/Hmax and CII in the models to disentangle changes with ontogeny and with light environment. We used the Akaike information criterion to select the structure of the random part of the model and the variables retained in the fixed part. Only species for which we had Hmax, CII and at least one individual sapling in two different height classes of the same forest type were included.
Acknowledgements We thank  Daniel Perez Aviles ,  Christina Smith  and  Erick Calderon Morales  for great help with data collection,  Helen Simpson  and  Sarah Chesworth  for help with lab analyses,  Christopher Baraloto  for interesting comments on the protocol,  Stéphane Dray  for advice on RLQ analysis,  Bonnie Waring ,  Davey Jones ,  Paul Withers  and  Andrew Smith  for discussion on soil data and  Roger Blanco  and  Maria Marta Chavarria Diaz  ( Area de Conservación de Guanacaste ) for help in obtaining research permits. The chronosequence was set up by  Justin Becknell  and  JSP , and supported by an  NSF   CAREER Grant  ( DEB-1053237 ) to JSP. The soil moisture data were collected by  Bonnie Waring  and  Lisa Rosenthal. This study was supported by the  European Commission  under the  FONASO Erasmus Mundus doctorate  programme and by the  Coalbourn Trust.
T hree recent international randomized phase 3 trials evaluating 4-month fluoroquinolone-containing regimens in adults with pulmonary, drug-susceptible tuberculosis failed to achieve non-inferiority compared with the standard 6-month control regimen (OFLOTUB  1  , ClinicalTrials. gov number NCT00216385; REMoxTB 2 , ClinicalTrials. gov number NCT00864383; RIFAQUIN  3  , ISRCTN number 44153044). These trials evaluated later-generation fluoroquinolones (gatifloxacin and moxifloxacin) as single substitutions for ethambutol or isoniazid in multidrug regimens with the objective of shortening treatment duration from 6 to 4 months. In each of the three trials, the 4-month regimen did not satisfy the criteria for non-inferiority. However, the experimental 4-month regimens did cure approximately four-fifths of the participants, suggesting that a large proportion of global tuberculosis cases could be successfully treated with shorter duration  [1] [2] [3].
In this pooled analysis of individual participant datasets from these high-quality, contemporary trials, we sought to identify characteristics of those participants who were cured with 4-month regimens and, conversely, of those with hard-to-treat phenotypes of tuberculosis, who might require longer treatment durations. We evaluated both baseline characteristics and on-treatment markers of risk, including dosing frequency and adherence, for their ability to stratify the study population into easy-or hard-to-treat phenotypes of tuberculosis.
Nature MediciNe analyses of the OFLOTUB 1 , REMoxTB 2 , and RIFAQUIN 3 trials; 6 participants were excluded from the current analyses due to inability to verify treatment allocation in source databases. The external validation dataset (DMID 01-009; see ref. 9  ) includes 193 study participants treated with a 4-month experimental regimen (no fluoroquinolone) and 193 study participants treated with the standard 6-month regimen (Fig. 1 ). Baseline characteristics of participants did not differ across the experimental and control groups within analysis datasets, with the exception of race and enrollment at sites in the country of Senegal (both P < 0. 001; Table  1 ); 12% of the participants were infected with HIV. Primary outcome analysis. Multivariate Cox analysis of baseline risk factors for unfavorable outcomes included 3,154 of 3,405 participants (93%) with no missing baseline covariates; 1,843 of 2,001 participants (92%) were allocated to one of the 4-month experimental regimens, and 1,311 of 1,404 participants (93%) were allocated to the control regimens (Supplementary Tables  1 2 3 ).
In participants assigned to 4-month experimental regimens, baseline smear grade of 3+ relative to negative or 1+ grade and HIV seropositivity were the two major baseline clinical risk factors for unfavorable outcomes, with an adjusted hazard ratio (HR) of 1. 4 (95% confidence interval (CI), 1. 1-1. 9) and 1. 4 (95% CI, 1. 1-1. 9), respectively, Fig. 1  | Analysis and validation populations. Individual participant data from three trials were pooled for analysis. The original results were published in ref. 1  (OFLOTUB), ref. 2  (REMoxTB) and ref. 3  (RIFAQUIN). Data from a fourth trial, DMID 01-009, were used for external validation and previously published in ref. 9. The modified intent-to-treat population was used for the analysis. a For the validation dataset, the time-to-event analysis population in the original publication was used.
Articles Nature MediciNe Race was missing for all OFLOTUB study participants; black race was assigned to all study participants given all OFLOTUB sites were in Africa. b Age was missing for 5 study participants. c BMI was defined as the weight in kilograms divided by the squared height in meters. Height was missing for 291 study participants; median height for females and males were used to calculate BMI for those participants. d HIV status was missing for 9 study participants. e CD4 + cell count cutoff was variable across trials (described in Supplementary Table  2 ). CD4 + cell count summary statistics were based only on study participants co-infected with HIV but were missing for 79 HIV co-infected study participants. f Cavitation status was missing for 200 study participants. g Smear grade was based on clinical trial-defined grading but readjusted so all data were on the same scale.
3a ). In a hard-to-treat phenotype of tuberculosis consisting of participants with 3+ smear and cavitary disease that constituted 34% of the study population (1,162 of 3,405 participants), the 4-month regimens were clearly inferior. External validation. Using an independent dataset available from the DMID 01-009 trial in patients with non-cavitary disease, the patient population eligible for a 4-month rifampin-containing regimen was validated, confirming that for study participants with low to moderate smear grade, a standard regimen shortened to 4 months was non-inferior to the standard 6-month regimen. We confirmed that study participants with high smear grade were the driver of high rates of unfavorable outcomes in the 4-month DMID 01-009 regimen (Fig. 3b ). Impact of dosing frequency. Kaplan-Meier estimates show that study participants who fully adhered to a dosing regimen of 6 of 7 days per week (6/7) had a higher probability of unfavorable outcome than those who adhered to and completed a dosing regimen of 7 of 7 days per week (7/7) (HR, 2.
Our definitions of tuberculosis phenotypes were validated in an independent trial dataset of patients with non-cavitary disease. Whereas this trial was stopped early due to higher rates of unfavorable outcomes in the experimental 4-month regimen, we confirmed that a 4-month regimen would be effective for patients with negative, 1+ or 2+ smears in non-cavitary disease at baseline. We also confirmed that participants with high smear grade (3+ ) at baseline were more likely to fail treatment regardless of whether they received 4-or 6-month regimens, compared with those with lower smear grades at baseline. Given the established importance of cavitation in disease prognosis and treatment response  5, 10, 11  , we included this characteristic in the analyses of non-inferiority for various subgroups, despite the fact that cavitation was not a significant variable in the multivariate analysis and was only marginally significant in the univariate analysis (Supplementary Tables  8 9 10 ).
Nature MediciNe was not standardized across the included trials. Future protocols should use minimum dataset standards, compliant with Clinical Data Interchange Standards Consortium standards (https://www. cdisc. org), to allow robust pooled analyses. Second, chest radiograph interpretation was not uniform, and as such, we could not analyze size and number of cavities in all three studies (Supplementary Figs. 1  and 2 ). Third, very few pharmacokinetic data were available, hampering our ability to explore dosing, drug exposure and outcome relationships. We advocate for the inclusion of population pharmacokinetics in phase 3 trials to address the variability in responses across geographic regions and populations. Our comparison of 6/7 with 7/7 dosing was a comparison between trials rather than within trials and therefore may be confounded by other study differences.
Finally, only 12% of participants had HIV co-infection, and many were not on effective antiretroviral therapy regimens; thus, caution should be used in generalizing our findings to immunocompromised populations. Strengths of our analyses include the inclusion of large datasets from four international registration-quality phase 3 trials conducted across diverse human populations in high-tuberculosis-burden settings in South America, sub-Saharan Africa and Asia; performance of microbiologic assays by quality-controlled laboratories; and the careful recording of study treatment under direct observation. In sum, our validated analyses of individual participant data from contemporary randomized clinical trials provide three major findings. First, we show that low smear grades at baseline or the absence of cavitation identifies a population at low risk for recurrence in whom 4-month rifampin-containing regimens may be effective.
A fourth independent tuberculosis treatment-shortening trial sponsored by the National Institute of Allergy and Infectious Diseases and conducted by the National Institutes of Health-funded Tuberculosis Research Unit compared a 4-month standard regimen (with no fluoroquinolone) with a 6-month standard regimen in adults with non-cavitary disease and 2-month negative culture status (DMID 01-009; ClinicalTrials. gov number NCT00130247)  9. Th  pooled analyses are focused on data from participants receiving the 4-month experimental regimens and 6-month standard regimens and do not include the once-weekly (in continuation phase) fluoroquinolone 6-month experimental regimen in the RIFAQUIN trial. The three trials that compared four fluoroquinolone-based tuberculosis regimens to a 6-month standard regimen provided data for identifying markers and models for risk stratification, while the DMID 01-009 trial data were used for external validation.