Additional file 1: of A large two-centre study in to rates of influenza and pneumococcal vaccination and infection burden in rheumatoid arthritis in the UK

Vaccination questionnaire. (DOCX 184 kb

Appendix A. Data sources used in the DNDC (denitrification–decomposition) model for both China and the United States.

Data sources used in the DNDC (denitrification–decomposition) model for both China and the United States

Re-estimating NH₃ Emissions from Chinese Cropland by a New Nonlinear Model

Ammonia (NH₃) released to the atmosphere leads to a cascade of impacts on the environment, yet estimation of NH₃ volatilization from cropland soils (<i>V</i>_NH₃) in a broad spatial scale is still quite uncertain in China. This mainly stems from nonlinear relationships between <i>V</i>_NH₃ and relevant factors. On the basis of 495 site-years of measurements at 78 sites across Chinese croplands, we developed a nonlinear Bayesian tree regression model to determine how environmental factors modulate the local derivative of <i>V</i>_NH₃ to nitrogen application rates (<i>N</i>_rate) (VR, %). The <i>V</i>_NH₃–<i>N</i>_rate relationship was nonlinear. The VR of upland soils and paddy soils depended primarily on local water input and <i>N</i>_rate, respectively. Our model demonstrated good reproductions of <i>V</i>_NH₃ compared to previous models, i.e., more than 91% of the observed VR variance at sites in China and 79% of those at validation sites outside China. The observed spatial pattern of <i>V</i>_NH₃ in China agreed well with satellite-based estimates of NH₃ column concentrations. The average VRs in China derived from our model were 14.8 ± 2.9% and 11.8 ± 2.0% for upland soils and paddy soils, respectively. The estimated annual NH₃ emission in China (3.96 ± 0.76 TgNH₃·yr^–1) was 40% greater than that based on the IPCC Tier 1 guideline

Re-estimating NH₃ Emissions from Chinese Cropland by a New Nonlinear Model

Ammonia (NH₃) released to the atmosphere leads to a cascade of impacts on the environment, yet estimation of NH₃ volatilization from cropland soils (<i>V</i>_NH₃) in a broad spatial scale is still quite uncertain in China. This mainly stems from nonlinear relationships between <i>V</i>_NH₃ and relevant factors. On the basis of 495 site-years of measurements at 78 sites across Chinese croplands, we developed a nonlinear Bayesian tree regression model to determine how environmental factors modulate the local derivative of <i>V</i>_NH₃ to nitrogen application rates (<i>N</i>_rate) (VR, %). The <i>V</i>_NH₃–<i>N</i>_rate relationship was nonlinear. The VR of upland soils and paddy soils depended primarily on local water input and <i>N</i>_rate, respectively. Our model demonstrated good reproductions of <i>V</i>_NH₃ compared to previous models, i.e., more than 91% of the observed VR variance at sites in China and 79% of those at validation sites outside China. The observed spatial pattern of <i>V</i>_NH₃ in China agreed well with satellite-based estimates of NH₃ column concentrations. The average VRs in China derived from our model were 14.8 ± 2.9% and 11.8 ± 2.0% for upland soils and paddy soils, respectively. The estimated annual NH₃ emission in China (3.96 ± 0.76 TgNH₃·yr^–1) was 40% greater than that based on the IPCC Tier 1 guideline

Additional file 1: of Does intensive management improve remission rates in patients with intermediate rheumatoid arthritis? (the TITRATE trial): study protocol for a randomised controlled trial

SPIRIT Checklist figure. (PPTX 333 kb