dataesr/scientific-paragraphs-categorization huggingface dataset:
Summary We collected province-level activity data of agriculture, energy and waste and emission factors of CH 4 from the eight major source sectors in mainland China and estimated annual CH 4 emissions from each source sector from 1980 to 2010. Our estimates of CH 4 emissions considered regional specific emission factors, activity data and correction factors as much as possible. In the past decades, the total CH 4 emissions increase from  24. 4 [18. 6-30. 5 ] Tg CH 4 yr -1 in 1980 to  44. 9 [36. 6-56. 4 ] Tg CH 4 yr -1 in 2010. The largest contrib-utor to total CH 4 emissions is rice cultivation in 1980, but this was replaced by coal exploitation after 2005. The increase of CH 4 emissions from coal exploitation and livestock drives the increase of total CH 4 emissions. We distributed the annual province-level CH 4 emissions into 0.
, 2012) , is not investigated in this study. If the detailed monthly activity data and mitigation data for each source sector (see Sect. 2. 2) become available, the full monthly CH 4 emission inventory database could in the future be built based on the bottom-up method used in this study. 6 Data availability CH 4 inventory (PKU-CH4) in this study is publicly available on website (http://inventory. pku. edu. cn/), and the intention is to regularly update it every 2 or 3 years. The Supplement related to this article is available online at doi:10. 5194/acp-16-14545-2016-supplement.
Acknowledgements. This study was supported by the  National Natural Science Foundation of China  (grant number  41671079 ). Shushi Peng  acknowledge supports from the  1000-talent Youth Program. Philippe Ciais  received support from the  European Research Council Synergy  grant  ERC-2013-SyG-610028 IMBALANCE-P. Edited by: Q. Zhang Reviewed by: three anonymous referees.
Material and methods The teeth were extracted by screen-washing the marly sediment from level C36 of unit U2, after dissociation by adding oxygen peroxide. Over 300 kg of sediment was screened in total, yielding 10 812 isolated teeth of numerous taxa, of which only three can be referred to Sauropoda. Imaging was carried out using X-Ray microtomography at the European Synchrotron Radiation Facility (ESRF, Grenoble, France), on beamline ID19. Tomographic specifications used were: pixel size, 1. 4 μm; propagation distance, 50 mm; energy, 20 KeV. Data processing and 3D reconstructions were conducted using Octave, Matlab and VGStudioMax 2, under ESRF and MNHN licences.
We show that the smoothing error of individual clear-sky CO retrievals is less than ±1 ppb and thus this error contribution does not need to be accounted for in the validation considering the much higher retrieval noise. The CO data product is validated against measurements of ground-based Fourier transform infrared spectrometers at 27 stations of the NDACC-IRWG and TCCON network and MOZAIC/IAGOS aircraft measurements at 26 airports worldwide. Overall, we find a good agreement with TCCON measurements with a mean bias T. Borsdorff et al. : SCIAMACHY CO total column measurements (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012).
b = -1. 2 ppb and a station-to-station bias with σ = 7. 2 ppb. The negative sign of the bias means a low bias of SCIA-MACHY CO with respect to TCCON. For the NDACC-IRWG network, we obtain a larger mean station bias of b = -9. 2 ppb with σ = 8. 1 ppb and for the MOZAIC/IAGOS measurements we find b = -6. 4 ppb with σ = 5. 6 ppb. The SCIAMACHY data set is subject to a small but significant bias trend of 1. 47 ± 0. 25 ppb yr -1. After trend correction, the bias with respect to MOZAIC/IAGOS observation is 2. 5 ppb, with respect to TCCON measurements it is -4. 6 ppb and with respect to NDACC-IRWG measurements -8. 4 ppb. Hence, a discrepancy of 3. 8 ppb remains between the global biases with NDACC-IRWG and TCCON, which is confirmed by directly comparing NDACC-IRWG and TCCON measurements. Generally, the scatter of the individual SCIA-MACHY CO retrievals is high and dominated by large measurement noise.
Finally, the CO data set is validated with ground-based measurements of the TCCON (Total Carbon Column Observing Network) and NDACC-IRWG (Network for the Detection of Atmospheric Composition Change -Infrared Working Group) at 27 sites and aircraft measurements close to 26 airports of the MOZAIC (Measurement of Ozone and Water Vapour on Airbus in-service Aircraft) and IAGOS (In-service Aircraft for a Global Observing System) project. Averaging of individual SCIAMACHY CO retrievals is essential for data usage to reduce the retrieval noise to an acceptable level. The required degree of averaging depends on the properties of the considered ground scene and the measurement geometry of the instrument. To illustrate potential data use, we compare the spatial and temporal variation of SCIAMACHY CO fields over biomass burning areas in Africa with model fields of a global chemistry transport model (TM5).
Choosing an appropriate balance between temporal and spatial averaging of individual SCIAMACHY retrievals allows us to obtain useful information about the atmospheric CO concentration. For the first six years of the mission, our SCIAMACHY CO data set compares well with previous work by de  Laat et al. (2010b) , which becomes obvious when comparing the validation of the data sets with collocated ground-based Fourier transform infrared spectroscopy (FTIR) measurements. The retrieval noise statistics in the early years of the mission are comparable but the resulting CO time series of the new data set is more homogeneous due to our calibration approach. Moreover, the main achievement of this study is that a valuable CO data product is provided for the years after 2008 considering the advanced degradation of the SCIA-MACHY instrument in that period.
Furthermore, the southern hemispheric bias mentioned by de Laat et al. (  2010b ) is significantly reduced. The paper is organised as follows: Sect. 2 summarises the inversion approach and in Sect. 3 we discuss the degradation of SCIAMACHY instrument and propose a mitigation approach. The validation of the CO data product against NDACC-IRWG, TCCON and MOZAIC/IAGOS measurements discussed in Sects. 4 and 5 illustrates potential data usage showing a comparison with CO model fields that are simulated by the TM5 global chemistry transport model. Finally, Sect. 6 summarises and concludes the paper.
In this study, specimens of B. puteoserpentis from the Snake Pit vent site were investigated. B. puteoserpentis is a sisterspecies to the well-documented B. azoricus and shares the same symbionts based on their 16S rRNA gene sequence  (Won et al. , 2003b; Duperron et al. , 2006; Faure et al. , 2009). We thus tested two hypotheses. The first was that B. puteoserpentis from the 3500 meter-deep site displayed a higher relative abundance of sulfur-vs. methane-oxidizers compared to the data available for B. azoricus, as can be predicted based on the higher sulfide-to-methane ratio observed at Snake Pit compared to other MAR sites previously investigated  (Halary et al. , 2008; Le Bris and Duperron, 2010). The second was that symbionts displayed similar dynamics in both species when live specimens are exposed to the substrates used by bacteria, given that B.
Estimation of Gill Bacteriocyte Densities and Numbers of Gill-Associated Bacteria For each specimen, five FISH images were acquired of the surface of whole-mount hybridized gill filaments. Bacteriocyte densities (D BC , the number of bacteriocytes per µm 2 of gill surface area) were measured based on bacteriocytes counted using the "cell counter" module of ImageJ. To estimate bacterial number, mean bacteriocyte diameter was inferred by assuming a circle shape on flat images, and the volume of the corresponding sphere (Vol BC ) was calculated. Based on previous studies indicating bacteriocyte volume occupation of 55-58% in Thyasiridae  (Dufour and Felbeck, 2006)  and 52-55% in Vesicomyidae (Decker, pers. comm. ), we assumed that bacteria roughly occupied 50% of the bacteriocyte volume in Mytilidae.
ACKNOWLEDGMENTS We thank the captain, crew and pilots of RV Pourquoi Pas? and  ROV Victor6000  as well as scientists onboard for their help during the cruise BICOSE, in particular chief scientist M-A Cambon-Bonavita. We also thank  E. Roussel  for his input. We thank the reviewers for constructive comments which helped improve the manuscript. The research leading to these results has received funding from  UPMC , from the  European Union Seventh Framework Programme  ( FP7/2007-2013 ) under the  MIDAS  project, grant agreement n • 603418, and through an excellence grant to SD from  Institut Universitaire de France. KS was funded through a  Ph. D. grant from the Marie Curie Actions Initial Training Network  (ITN) SYMBIOMICS (contract number  264774 ). This study did not involve endangered species and no specific permit was required for sampling at the Snake Pit site.
Study population In the spring of 2014, a telephone survey of a random sample representing all the general practitioners (GPs) of France was conducted. This sample was extracted from a national database that identifies all French self-employed GPs in private practice. As of January 1, 2013, this target population consisted of 54,579 GPs. An approximately 1% random sample drawn from this database was used to identify a sample of 1000-plus an extra 230-GPs based on the prediction of a 50% survey response rate. We sought a sufficiently large number to produce valid descriptive statistics on GPs' attitudes (with a margin of error of approximately 5%) while limiting the number of respondents for logistical reasons. The physicians were initially contacted by email and then telephone by a public research institution specialized in this kind of survey (Observatoire Régional de la Santé, Provence-Alpes-Côte d'Azur).
Experimental Stages Each trial included four stages. First, a black screen was displayed for a random time period from 0. 5 to 2. 5 s. Second, the traffic light with all lights off was displayed during 1. 5 s. Then, one of the lights or arrows lit up during 2 s. Each participant had to respond within this 2 s delay by pressing the appropriate key, otherwise the trial was considered a no-response (i. e. , no RT included in the dataset). Finally, mean RT and the cumulative number of incorrect trials, i. e. , wrong key or wrong pedal or no-response trials, were displayed during a feedback period of 3s (although we processed wrong responses and no-responses separately). The information display was reset as early as a new test started. To ensure good understanding of instructions, the participants performed the three tests from the easiest (T1) to the most difficult (T3).
Data Analysis All computations were performed using the R statistical software, the nlme and multcomp packages (R Core Team, 2015) 2. The nlme package can carry out both linear mixed effects models (LMEM) and non-LMEMs. It can easily be linked to the multcomp package for multiple comparison. The LMEM  (Pinheiro and Bates, 2000)  is a statistical tool allowing the combination of numeric covariables with categorical factors (both withinsubject and between-subject factors). Post hoc comparisons are also easily performed. This explains why we selected lme with respect to ANOVA. We successively fitted RT, percentage of wrong responses and percentage no-responses. We used a standard variance-stabilizing transformation for modeling the two percentages  (Fisher, 1921). The same LMEM was performed to test the variables described by the following equation: y(ijk) = M+a(i)+b(j)+ab(ij)+c(ijk)+D(k)+E(ijk) (1) where i represents conditions (T1, T2, T3), j the middle-aged versus the elderly group and k the participants (n = 56).
Statistical analysis For all experiments results were shown as means ± standard deviation (SD) (n = 3). Data were subjected to statistical analysis using the SPSS program, release 11. 0 for Windows (SPSS, Chicago, IL, USA). One-way analysis of variance (ANOVA) and then the Duncan multiple range test were used to study the differences between individual means deemed to be significant at p < 0. 05. EC 50 values were obtained by interpolation from non-linear regression analysis using Microcal (TM) Origin, version 6. 0.
Methods The main study results and methodology have been reported previously (ClinicalTrials. gov number NCT02153190)  [1]. In short, participants from three sites in Montpellier, France, Padua, Italy and Amsterdam, the Netherlands were randomly assigned to receive 8 weeks of evening-and-night closed-loop glucose control using an artificial pancreas (artificial pancreas period) and then 8 weeks of insulin pump with continuous glucose monitoring (sensor-augmented pump period) or vice versa. During the daytime participants randomized to the artificial pancreas period used sensoraugmented pump therapy with their artificial pancreas switched off. Both intervention periods were separated by a 4-week washout-period to minimize carry-over effects. A further description of the artificial pancreas system can be found in Appendix S1.
Semi-structured interviews After completion of both study arms of the main study, participants from the clinical site in the Netherlands were invited to participate in a semi-structured interview. These interviews, based on the technology assessment model  [7] , were performed face-to-face or by telephone, according to the participants' availability. Interviews were performed until no new information or themes were observed in the data and 'saturation' was reached. An overview of the methods used to develop the semi-structured interviews is given in Appendix S1.
Statistical methods Missing data from the HFS-II and DTSQs/c were handled as instructed in the questionnaire guidelines. For the artificial pancreas questionnaire any questionnaires with missing data were discarded. Normality of data distribution was visually assessed. Baseline scores and end scores for the artificial pancreas period and sensor-augmented pump period were calculated and compared using a repeated-measures ANOVA model using paired data only. A multilevel ANOVA model including 'study site' as a covariate was performed to assess between-site differences. A paired t-test was used for comparison of DTSQc scores. P values < 0. 05 were taken to indicate statistical significance. SPSS software (IBM Inc. New York, USA, version 22) was used for data analyses.
Results Figure  1  provides a trial profile. A total of 35 eligible participants were enrolled. One participant dropped out before and two just after randomization as a result of poor artificial pancreas acceptance by the participants. Thus, data from a total of 32 participants were available for analyses, of whom 18 were women. Their mean age was 47 years and mean diabetes duration 29 years (Table  1 ). Before being enrolled in the present study, 14 participants had taken part in one or more previous artificial pancreas studies.
The slides were incubated at 48C overnight with the anti-RXFP1 antibody (Sigma-Aldrich, Saint-Quentin Fallavier, France), 1:50 dilution, or with the anti-nitrotyrosine antibody (Merkmillipore, Fontenay sous Bois, France), 1:100 dilution. Detection was carried out with the novostain universal detection kit (Novocastra Laboratories, Newcastle upon Tyne, UK) and diaminobenzidine as chromogen. Hematoxylin was used as counterstain. RXFP1 and nitrotyrosine were quantified in five to ten given fields per animal. All analyses were performed using image analysis software (ImageJ).
Participants and study design The Whitehall II study is a prospective cohort study of British government employees initially including all London-based office staff, aged 35-55 years, who were working in 20 departments at study entry, 1985-1988. 13 With a response rate of 73%, there were 10 308 participants in the baseline examination. Since this first wave of data collection, self-completion questionnaires and clinical data have been collected from study members every 2-5 years. We used data from waves 1 to 11, the last wave in 2012-2013 (excluding 4th and 10th due to lacking measurements of psychological distress). After complete description of the study to the participants, their written consent was obtained. Ethical approval for the Whitehall II study was obtained from the University College London Medical School and the NHS London-Harrow Health Research Authority committees on the ethics of human research.
Measurement of CHD risk factors We used data on CHD risk factors from the wave 3 (1991-1994) clinical examination. Smoking (yes/no) was based on survey questionnaire. Height was measured to the nearest 0. 5 cm. Weight was measured to the nearest 0. 1 kg. From these, body mass index (BMI) was measured and obesity was defined as a BMI ≥30 kg/m 2. Weekly alcohol use from survey questionnaire was used to categorise alcohol consumption as non-use, alcohol use within recommended limits (women: up to 14 drinks/week; men: up to 21 drinks/week) and alcohol use above recommended limits (women: >14 drinks/week; men: >21 drinks/week). 18 Systolic and diastolic blood pressure was measured twice while seated after a 5 min rest, and means for the two measurements for systolic and diastolic blood pressure were used in the analyses.
The estimates were adjusted for age, sex and socioeconomic status. The full model also included CHD risk factors (smoking, high alcohol use, obesity, hypertension, hyperlipidaemia, diabetes and history of psychological distress) and a sensitivity analysis for the level of psychological distress at wave 3 (with four categories: 0, 1-5, 6-10 and >10 points). GBTM was performed using Stata V. 13 and all other analyses using SAS V. 9. 4.
11 ur study adds new insight by using a relatively large dataset and clinically verified CHD in a middle-aged population. We found that participants with pre-existing CHD had a 1. 9-fold increased risk of ending up on a persistently high and a 1. 7-fold risk of intermediate to low, when compared with persistently low trajectory. There are at least two potential mechanisms that explain these results. According to the vascular depression hypothesis,  5 6 26  long-term symptomatic trajectory may be the result of vascular pathology itself. However, in our cohort, smoking and obesity but not more direct indicators of vascular pathology, such as hypertension and hypercholesterolaemia, were associated with persistently high trajectory. Another viewpoint states that long-term trajectory of symptoms can be a component of prolonged adjustment disorder in response to a severe chronic disease and its impact on the quality of life.
Although we found limited support for the vascular origin hypothesis, it is important to note that CHD and the risk factors were based on one-time assessments at baseline and we did not account for time-varying changes in them. They may change over time, for example, due to new events and new treatment practices. As lipid-lowering drugs became increasingly common over the follow-up, it might have diluted the association with hypercholesterolaemia. A major strength of this study is a long-term follow-up of psychological distress with up to seven measurement points and a valid, clinically ascertained CHD at the baseline. Data on BMI, hypertension, hypercholesterolaemia and diabetes were based on clinical examinations. The study also has limitations. The GHQ-30 is a screening instrument, designed to capture symptoms of depression, anxiety, insomnia and social dysfunction rather than providing a clinical diagnosis of depressive disorders.
This led to a final list of eight attributes presented in Table  2. The second step is to combine attributes into choice sets. Most of time, the combination relies on experimental plan theory since a full factorial design implies proposing too many choices to respondents  [22]  -864 scenarios in our case. Using JMP software, we generated an orthogonal design  [23]  that resulted in 24 scenarios and achieved the properties of orthogonality and level balance. All other analyses are done with STATA. In order.
The fund obtained from the Conseil Regional de Bourgogne did not allow for a survey of more than one region. 5 This point is, however, not particularly concerning as the regional and national values are derived from an administrative database (système national d'information inter-régimes -SNIIR) known to underestimate physicians' activity. The SNIIR includes the very low activity physicians, pulling down the average number of acts. 6 Beyond the choice exercise, supplementary choices and follow-up questions were introduced in the DCE in order to test the internal validity of the data collected. More information on the test procedures used is available upon request. 7 This random part is precisely why RUT can deal with axiomatic violations. The "errors" may come from this stochastic part, which is unexplained by the researcher.
Acknowledgments We thank the two anonymous reviewers for their helpful comments that helped improve this manuscript. We are grateful for comments from  Sophie Béjean  and  Erin Strumpf  on an earlier version of this paper. We thank  Arne Risa Hole  for his advices on his mixlogit Stata command and we thank the  Union régionale des professionnels de santé  for their help with the focus-group meetings and their logistic support for the survey. We are of course in great debt to the GPs who took time to answer the survey. Financial support is acknowledged from the  Regional Council of Bourgogne  ( CPER 2009  and  PARI 2010 ). Usual disclaimers apply.
Methods We used data from a large German cohort study which was set up to investigate childhood cancer risk after exposure to ionizing radiation from computed tomography  [10]. In the participating 20 hospitals we extracted data from Radiology Information Systems for pediatric patients who had at least one CT examination in the age range between 0-<15 years (applying a 6-months latency period, the analyzed age range was 0-14. 5 years). For this study we only considered data from 2001 to 2010 and only included CT examinations for non-cancer patients as multiple CT examinations may be necessary to arrive at a cancer diagnosis, which would lead to increased CT examination numbers in the process compared to other diseases or injuries. Cancer patients were identified through linking the study population with the German Childhood Cancer Registry, and included those children who had a prevalent cancer diagnosis before their first CT examination during the study period or who received a cancer diagnosis within two years after their last CT examination (i.
e. 2-year latency period during follow-up). The collected data included patient's date of birth, sex, postal code of location of residence at time of last know CT examination, as well as number, type and date of CT examination undergone. We used the German Index of Multiple Deprivation (GIMD), which was established based on the method used in the UK to create the Indices of Multiple Deprivation  [18]. The GIMD is based on official socio-demographic, socio-economic and environmental data. Most data are derived from the Federal Statistical Office of Germany and the statistical offices of the German federal states, and were mainly from the year 2006. The indicators based on this data were assigned to seven deprivation domains reflecting aspects of material and social deprivation (i. e. income, employment, education, municipal revenue, social capital, environment and security deprivation).
5 years or the end of the study period (31-12-2010), whichever came first, and was used as a weight in the regression model. Furthermore, we used six categories of body regions to distinguish different types of examination: head and neck, chest, abdomen and pelvis, extremities, multiple regions, and other/unclassifiable. Stratified analysis by type of examination was additionally conducted to assess differences of CT numbers and deprivation categories adjusting for age and sex. Individuals with missing data (sex, address, type of examination) were excluded from analysis. Data management and statistical analyses were done using SAS 9. 3 (SAS Institute, Cary, NC, USA).