dataesr/scientific-paragraphs-categorization huggingface dataset:
This should complement data obtained from Argo floats implemented with sensors for near-surface measurements at high vertical resolution (S. Riser 2013, personal communication). Acknowledgments. This effort is part of ESA SMOS calibration and validation projects, and is supported nationally in France by CNES/TOSCA with the GLOSCAL project; in Spain, at ICM/CSIC by the Spanish national R1D plan (Projects AYA2010-22062-C05 and CSD2008-00077). In Germany funding was provided by BMBF to CEN under Contracts 50EE0934 and 50EE1245, as well as by the DFG in the frame of SFB512. The deployments and recoveries of drifters were done from a large array of national research vessels and opportunity merchant or sailing vessels to whom we are highly indebted. The validated SVP-BS and ICM/CSIC drifter data can be retrieved under ''regions'' (http://www.
Salinity Jumps Examples of variability when a Surplas float was attached to the drifter illustrate the issue on how to detect erroneous salinity jumps. In Fig. A1 , there is a sudden jump in S on 23 June that is associated with a small change in T (on the order of 0. 058C). There is a second jump in S on 24 June associated with a slightly larger change in T, and a third one on 26 June with no clear change in T. We did not correct it, on the basis of later comparisons to Argo data. This jump is also found in the Surplas data (not shown, as they start to present large fouling) and thus is real. However, it would have been mistakenly identified as erroneous without these data or the later comparison to later collocated Argo floats. Furthermore, if the temperature records had only a resolution of 0.
058C or less as on early drifters, the 24 June jump could also have been mistakenly identified as artificial. Figure  A2  shows other examples of salinity variability. It presents two low salinity events associated with rainfall on 25 and 29 July 2011. These are associated with T changes and would have been identified as real. Then, there is a negative jump in S on 28 July, a period of noisy data on 30 July, and a positive jump on 31 July. As there was no temperature change associated with the decrease of S on 28 July or the increase on 31 July, the hypothesis would have been (correctly) that the drop was accidental (object stuck in the cell) and the following record would have been shifted upward until 31 July (with the noisy data on 30 July removed). In this particular case, later portions of the record present no bias compared to collocated Argo data, and thus without the Surplas record the corrections would still have been done correctly.
The SMOS maps suggest large time variability of the freshwater pattern in this region during June. The example presented for 14-23 June illustrates that the drifter had indeed been along the edge of the freshwater, which is inshore of its trajectory typical of the North Brazil Current separation, and that on 18 June it crosses a freshwater tongue in the SMOS maps. The observed SSS variability in drifter data seems thus coherent with the SMOS mapped situation, although the deviations with the mapped data can be locally on the order of 1 psu. The other example shown for drifter PG73226 on 10-20 September 2010 (Fig. B2 ) also presents a huge freshwater tongue, which in this case is clearly associated with the North Brazil Current retroflection. The SMOS map and the drifter find SSS values less than 30 psu in this tongue, although local deviations between the two datasets can reach 1 psu.
Literature review of international and regional scenarios There are a broad range of scenario sets from international and regional levels that have been developed by the academic, policy and private sectors, with varying timescales and using a range of processes and participants. A comprehensive review through a desk-based study was carried out on these, while at the same time compiling data and information on emerging trends that could help build pictures of potential future scenarios. Based on their relevance to the development of natural resources and underlying drivers such as climate change and economic choices with large scale impacts, a total of eight sources were selected for further in-depth analysis. Most of these sources have defined several detailed scenarios or scenario groups (Table  1 ).
The process of cross-scalar analysis Table  3  summarises the features of the scenarios at different scales. Using the data collected at each scale, all the drivers featured in the narratives and their associated trends, were coded into a database. Then, through a visual mapping exercise, all 101 scenario drivers were organised according to emergent themes. The approach adopted was inspired by Grounded Theory  (Charmaz, 2006)  where no a priori hypothesis was in place before the mapping exercise took place. Mapping commenced with the local drivers of change, where drivers sharing similar themes were grouped together. This was followed by national drivers, and then regional and international level drivers. The process involved extensive discussions between researchers over three iterative cycles of analysis.
INSERT TABLE 3 Since there were a large number of scales, themes and trends involved in the analysis, and to triangulate the initial qualitative assessment, we performed a Factorial Correspondence Analysis (FCA) on the data. Hierarchical Ascendant Classification (HAC) was then carried out on the coordinates of the modalities in the factorial space, considering the first three axes, using the Ward criterion. This criterion is based on the minimum of variance within each class  (Lebart et al. , 1997; Sanders, 1989). These analyses were carried out using the Statistica 7 software.
INSERT TABLE 9 Similar results were found from carrying out FCA on our datasets. The first three axes accounted for 42. 7% of the total inertia of the data. Interpretation of these axes (following  Sanders, 1989 and Lebart et al. , 1997)  show that Axis 1 relates to local scale vs. global scale, Axis 2 is bound to 'worst' case vs. 'best' case scenarios, and the weaker Axis 3 is linked to regional (and rather negative) scenarios versus 'intermediate' (between 'worst' and 'best' case scenarios) global scenarios. This third axis might be underlining main incoherencies between regional and global scales. In our HAC analyses, the first cut-off point used for distinguishing classes was ten classes. By going through each class individually, similarities and inconsistencies were identified which led to the aggregation of some classes and a final number of seven.
Genotyping was performed on the strain using multi-spacer sequence typing (MST)  [6] , a technique based on the variability of ten intergenic sequences. The genotype MST 21 was identified and confirmed by BLAST of the genome  [7]  against Cox sequences (10). We compared the Dog Utad strain to the seven available strains. A comparison of the COG categories showed that Dog Utad follows the same trend as the other available C. burnetii genomes, but with more similarities with CbuG_Q212, a genome previously deposited in GenBank corresponding to a strain from a Canadian man presenting with Q fever endocarditis and having the same genotype (MST21). Coxiella burnetii Dog Utad reads best covered (98%) the Coxiella burnetii CbuG_Q212 genome with a maximum coverage of 1482 and an average coverage of 173.
The training sessions in the field on the fourth day included household selection and enumeration only. The eyelids and cornea were first examined for deviated lashes and/or corneal opacities. When such signs were found, visual acuity was measured using Snellen E optotypes. If there was visual loss, trachoma accountability was sought (presence of conjunctival trachomatous scarring (TS), TT and/or pannus). The upper eyelids were routinely everted and examined using a binocular loupe (magnification 2. 5), under good light conditions. Those with blindness or visual impairment were reviewed by a senior ophthalmologist to make sure the situation was imputable to trachoma. The diagnosis of both eyes was recorded on the data collection form. The surveyors (trachoma graders) ensured that the data collection form was completed in accordance to protocol requirements before proceeding to the next person.
Data management and analysis Data were entered into database using the EpiInfo software for analysis. Data were cleaned, and entries missing or invalid data, particularly on age, were not included in the final analysis. When calculating the overall prevalence in the region or prevalence by sex, samples were weighted according to the proportion of population in each district among the total population in 2010 in the region projected from the 2005 national census with an annual growth rate of 2. 6%  [11]. The 95% confidence intervals (CIs) of the prevalence were calculated with the Wilson score method without continuity correction  [16] , using the CI calculator (available: http://vl. academicdirect. org/applied_statistics/binomial_distribution/ref/ CIcalculator. xls). Differences in prevalence of trachoma were compared using the Chi-squared test in EpiInfo (version 7.
Study population A total of 30,881 children aged 1-9 years were enumerated from the selected households, and 30,562 were examined in the 15 HDs surveyed. This represents a participation rate of 99. 0%. A total of 25,095 people aged 15 and above were identified and 24,864 were examined, representing a participation rate of 99. 1%. Table  1  shows the demographic data of the surveyed population in each district. In total, 55,976 persons were identified and 55,426 were examined, an overall participation rate of 99. 0%. The females represented 55. 7% in the total number of people aged 15 years and above examined and 48. 5% in the total number of children aged 1-9 years examined.
Potential energy surface Calculations of the HCl(X 1 + )-H 2 PES is described in detail in our previous paper  (Lanza et al. 2014, hereafter Paper I). We only present here a short description of the PES. Ab initio calculations of the PES of HCl-H 2 van der Waals complex were carried out at the coupled cluster with single, double and perturbative triple excitation [CCSD(T)]  (Hampel, Peterson & Werner 1992; Watts, Gauss & Bartlett 1993)  level of theory using the MOLPRO 2010 package  (Werner et al. 2010). The calculations were performed in the rather large augmented correlation-consistent quadruple zeta (aug-cc-pVQZ) basis set  (Dunning 1989 ) augmented with bond functions defined by  Williams et al. (1995). Then, in order to solve the close-coupling equations for scattering, the PES was expanded over angular functions using the expression of  Green (1975).
Results including the hyperfine structure will be presented elsewhere since HCl hyperfine resolved rate coefficients can be crucial in detailed models of radiative transfer  (Daniel, Cernicharo & Dubernet 2006; Cernicharo et al. 2010a). Recent scattering calculations have been published in Paper I. We refer the reader to Paper I for scattering calculation details. In summary, scattering calculations were performed with the MOLSCAT program  (Hutson & Green 1994 ) using the close coupling approach  (Green 1975). Calculations were carried out for total energies ranging from 0. 5 to 3000 cm -1 for collisions of HCl with para-H 2 and ortho-H 2. We considered transitions between the first 11 (j 1 = 0-10) rotational states of HCl. In all the calculations, the H 2 rotational basis included j 2 = 0-2 and j 2 = 1-3 for para-H 2 and ortho-H 2 , respectively.
AC K N OW L E D G E M E N T S This research was supported by the Agence Nationale de la Recherche (ANR-HYDRIDES), contract ANR-12-BS05-0011-01. Support by the CNRS national programme 'Physique et Chimie du Milieu Interstellaire' is also acknowledged. We also thank the CPER Haute-Normandie/CNRT/Energie, Electronique, Matériaux.
The mesh for the shallow sedimentary basin is adjusted to reflect its complex geometry and sharp lateral velocity contrasts. The grid resolution at the surface is about 545 m, which is sufficient to resolve topography and tomography data for simulations accurate up to 1. 0 Hz. The ROS is also an infrastructural service, making online earthquake simulation feasible. Users can conduct their own earthquake simulation by providing a set of source parameters through the ROS webpage. For visualization, a ShakeMovie and ShakeMap are produced during the simulation. The time needed for one event is roughly 3 min for a 70 s ground motion simulation. The ROS is operated online at the.
All of these requirements make regional earthquake simulations even more difficult to be realized in real-time. In this study, we built an accurate SEM mesh model for Taiwan using up-to-date geophysical and geological data first. This new SEM mesh model covers a much larger region than previous efforts. Several synthetic benchmarks are carried out to investigate performance of different resolution of SEM mesh models. The possibility of real-time earthquake simulation for RMT (Real-time Moment Tensor monitoring system  (Lee et al. , 2013) ) events is then discussed. According to these results, we develop a Real-time Online earthquake Simulation system, or ROS (http://ros. earth. sinica. ed. tw). The purpose of the ROS system is to provide a visualization of ground shaking (a so-called ShakeMovie) and a peak ground motion distribution (a so-called ShakeMap) in real-time ($5 min) once an earthquake occurs.
These source parameters are forwarded to the ROS system once an earthquake is detected. More details about the RMT are discussed in  Lee et al. , 2013. For user-inputted source parameters, people can use their own computer and login to the ROS via the ROS webpage (http://ros. earth. sinica. edu. tw) to design their own simulations. A set of source parameters can be selected and submitted to the ROS server. Source parameter inputs (double-couple point sources) are: (1) seismic moment magnitude, (2) hypocenter location (longitude, latitude and depth) and (3) focal mechanism (strike, dip and rake angles). When the system receives the inputs from RMT or worldwide users, the large scale velocity model and SEM mesh data are generated from a data grid server. Once all components (source, wave-speed and meshes) are incorporated, the simulation based on SEM is carried out on a high-performance computing cluster (currently the Green cluster in the Institute of Earth Sciences, Academia Sinica).
The same phenomenon can also be found in offshore areas associated with rapid variations in bathymetry. This is due to topographic amplification effects, Fig. 6. Flowchart of the ROS system. When the system receives the input source parameters from RMT or worldwide users, the large scale velocity model and SEM mesh data are generated from a data grid server. Once all components (source, wave-speed and meshes) are incorporated, the simulation based on SEM is carried out on a highperformance computing cluster. Output from the simulation is subsequently analyzed by another server, and the results are stored into the data grid server that becomes a part of the numerical earthquake database. At the same time, the user can see visualized simulation results on the screen, including the ShakeMovie and ShakeMap that are created at the end of simulation.
Observations versus synthetics In order to evaluate the quality of ROS simulations, we compare observed and synthetic waveforms for the 22 September 2011 Hualian earthquake. Source parameters (hypocentral location and moment tensor) are obtained from the RMT report. Since the RMT used low frequency signals of real-time broadband data in the CMT inversion, we first analyze BATS (Broadband Array in Taiwan for Seismology) waveforms in the pass band T = 10-50 s (the same as that used in RMT). Results show that the fit is excellent for low frequency signals for all three components (Fig. 8a-c ). For the period range T = 6-50 s (Fig. 8d-f ), the fit is also good at most of the stations, with a few exceptions (ANPB, WFSB and TWKB) which have a low signal-to-noise ratio in this frequency band. However, when going to higher frequencies (T = 3-50 s), as expected, the fit between observations and synthetics becomes worse (Fig.
Acknowledgements We used the open source SPECFEM3D software package (www. geodynamics. org,last accessed April 2013) developed by Komatitsch et al. (2004) in this study. We would thank  Dr. Carl Tape  for his comment and suggestions, which significantly improved the quality of the paper. We would also like to thank  Mr. C. L. Tsai  for technical support of the ROS webpage. All online simulations and visualizations were carried out on IES's Green cluster. This research was support by  Academia Sinica (AS)  funded through the  Taiwan Numerical Earthquake Model (TNEM)  project with grant number  102-Investigator Award-02. The study was also supported by the  Taiwan Earthquake Research Center (TEC)  funded through the  National Science Council (NSC)  Grant number  NSC   100-2628-M-001-007-MY3.
Data Our initial sample consists of all CB issues listed in the monthly information bulletins of the Autorité des Marchés Financiers (AMF)  2  conducted by French public companies between January, 1990 and December, 2007 on the Paris stock exchange. It amounts to 231 offerings. Note however that our final sample consists of 133 issues conducted by 121 companies as a result of using the following filters: 1. The issuing firm must be an operating company (31 offerings excluded); 2. No subscription warrant, option or right should be attached to the CB being offered (18 offerings excluded).
3. Issuing firms' daily stock prices must be available on Datastream database for the two years surrounding the offering date. Similarly, and for matching purposes, issuers' accounting data must be available on Worldscope database for the fiscal year preceding the offering (17 offerings excluded). 4. Finally, some firms are multiple issuers of CBs. Because we examine the multi-year pre and post-issue performances, a CB offering is kept in the sample insofar as it is neither preceded by a CB offer during the last three years, nor followed by another CB offer in the three subsequent years. Such restriction aims to accommodate dependence for statistical tests which would be induced by overlapping abnormal returns (32 offerings excluded).
Finally, the choice of the last matching characteristic; namely, ROA, is motivated by the fact that previous empirical evidence has shown that convertible debt issuers experience a significant pre-issue performance, suggesting that firms tend to issue CBs over periods of high earnings and stock price performance (e. g. ,  McLaughlin et al. , 1998; Lewis et al. , 2001). In this paper, ROA is computed as EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) on total assets. Recall that the control firm is the firm with the smallest distance metric from the issuing firm. Note that when the control firm is delisted from Datastream database while the issuer is still trading, a replacement matching firm is spliced in on a point-forward basis. Note also that when an issuing firm gets delisted, we remove at the same time its control firm.
Our control sample consists of all French companies meeting the following criteria. The control firm should be listed on Datastream database and should not have carried out any offer of CBs during the six years surrounding the date of the CB offering conducted by the corresponding issuing firm. To be consistent with the CB issuer sample selection criteria, we exclude financial firms from the control sample. Finally, owing to the existence of extreme observations in our sample, two non-parametric tests are used to test the statistical significance of the differences in performance between the issuing firms and their matched counterparts; namely, the bootstrapped t-test and the Wilcoxon test.
Methods study design and patients We performed retrospective matched cohort analyses using de-identified patient information (1996-2010) from. 450 primary care practices throughout the UK subscribing to the General Practice Research Database (now in the Clinical Practice Research Datalink)  17  and approximately 300 practices subscribing to the Optimum Patient Care Research Database. 18 These two large electronic datasets, described in detail elsewhere,  [17] [18] [19] [20] [21]  are frequently used for observational research. Patient characteristics were crossreferenced between the two datasets to avoid duplication of individuals. The two analyses examined patients prescribed their first ICS treatment (initiation sample) and those prescribed an increase in ICS dose (step-up sample) for COPD as either extrafine beclomethasone (Qvar; Teva Pharmaceuticals, Petach Tikva, Israel) or a commonly prescribed large-particle ICS, fluticasone (Flixotide; GlaxoSmithKline plc, London, UK), by pressurized metered-dose inhaler.
Outcome measures Exacerbation rate and odds of COPD treatment success were the two coprimary effectiveness measures. An exacerbation was defined as the occurrence of any one of the following: acute use of oral corticosteroids; unscheduled hospital admission or emergency department (ED) attendance for COPD or respiratory-related event; lower respiratory tract infection treated with antibiotics; or prescription for antibiotics with a lower respiratory database code within a ±5 day window. The absence of an exacerbation during the outcome period defined COPD treatment success. Secondary effectiveness measures included the time to first exacerbation and treatment stability, defined as no treatment change plus no exacerbation. Treatment change was defined as an increase in ICS dose (of $50%) and/or additional therapy (new since baseline year).
Other outcomes examined included the hospitalization rate for lower respiratory causes; mortality rate after the study; oral candidiasis (coded diagnosis or therapy, namely, oral antifungal prescriptions); and two definitions of pneumonia: 1) unconfirmed cases with coded pneumonia diagnosis, and 2) pneumonia confirmed by chest radiograph or hospitalization within 1 month of diagnosis code. All outcome measures were derived from GP-provided Read codes in the electronic databases. All ICS doses were standardized to equivalency with extrafine beclomethasone doses for the analyses, using a 1:1 ratio for extrafine beclomethasone and all fluticasone propionate formulations, and for both the latter a 1:2 dose ratio relative to budesonide and larger-particle chlorofluorocarbonor hydrofluoroalkane-beclomethasone (Clenil Modulite; Chiesi Ltd, Cheadle, UK).
(Patients had to be alive during the full 2 year outcome period to be eligible for the study). To account for multiple comparisons, we controlled for false discovery rate if more than one of the co-primary endpoints were significant. The composite outcome measures and analyses were prespecified according to standard operating procedures of the research group. 23 All analyses were carried out using IBM SPSS Statistics version 19 (IBM Corporation, Armonk, NY, USA), SAS version 9. 2 (SAS Institute Inc. , Cary, NC, USA), and Microsoft Excel 2007 (Microsoft Corporation, Redmond, WA, USA). We defined statistically significant results as P,0. 05.
Recorded GOLD severity data were available for 277 (83%) and 264 (79%) patients in extrafine beclomethasone and fluticasone initiation cohorts, respectively, and for 152 (80%) and 155 (82%) patients in extrafine beclomethasone and fluticasone step-up cohorts, respectively; d the doses of ICS were standardized to equivalence with extrafine beclomethasone and fluticasone; thus, baseline doses of large-particle beclomethasone and budesonide were halved. unmatched patients without a treatment change during the outcome period were similar to findings in the main analyses (Tables  S5  and S6 ). There was no significant difference between the two treatment cohorts of initiation or step-up samples in all-cause mortality after the outcome period (Table  S7 ).