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International audience; Purpose: Geant4 is a multi-purpose Monte Carlo simulation tool for modeling particle transport in matter. It provides a wide range of settings, which the user may optimize for their specific application. This study investigates GATE/Geant4 parameter settings for proton pencil beam scanning therapy.Methods: GATE8.1/Geant4.10.3.p03 (matching the versions used in GATE-RTion1.0) simulations were performed with a set of prebuilt Geant4 physics lists (QGSP_BIC, QGSP_BIC_EMY, QGSP_BIC_EMZ, QGSP_BIC_HP_EMZ), using 0.1mm-10mm as production cuts on secondary particles (electrons, photons, positrons) and varying the maximum step size of protons (0.1mm, 1mm, none). The results of the simulations were compared to measurement data taken during clinical patient specific quality assurance at The Christie NHS Foundation Trust pencil beam scanning proton therapy facility. Additionally, the influence of simulation settings was quantified in a realistic patient anatomy based on computer tomography (CT) scans.Results: When comparing the different physics lists, only the results (ranges in water) obtained with QGSP_BIC (G4EMStandardPhysics_Option0) depend on the maximum step size. There is clinically negligible difference in the target region when using High Precision neutron models (HP) for dose calculations. The EMZ electromagnetic constructor provides a closer agreement (within 0.35 mm) to measured beam sizes in air, but yields up to 20% longer execution times compared to the EMY electromagnetic constructor (maximum beam size difference 0.79 mm). The impact of this on patient-specific quality assurance simulations is clinically negligible, with a 97% average 2%/2 mm gamma pass rate for both physics lists. However, when considering the CT-based patient model, dose deviations up to 2.4% are observed. Production cuts do not substantially influence dosimetric results in solid water, but lead to dose differences of up to 4.1% in the patient CT. Small (compared to voxel size) production cuts increase execution times by factors of 5 (solid water) and 2 (patient CT).Conclusions: Taking both efficiency and dose accuracy into account and considering voxel sizes with 2 mm linear size, the authors recommend the following Geant4 settings to simulate patient specific quality assurance measurements: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (in the phantom and range-shifter) and 10 mm (world); best agreement to measurement data was found for QGSP_BIC_EMZ reference physics list at the cost of 20% increased execution times compared to QGSP_BIC_EMY. For simulations considering the patient CT model, the following settings are recommended: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (phantom/range-shifter) and 10 mm (world) if the goal is to achieve sufficient dosimetric accuracy to ensure that a plan is clinically safe; or 0.1 mm (phantom/range-shifter) and 1 mm (world) if higher dosimetric accuracy is needed (increasing execution times by a factor of 2); most accurate results expected for QGSP_BIC_EMZ reference physics list, at the cost of 10-20% increased execution times compared to QGSP_BIC_EMY.

Earth System Models (ESMs) project climate change, but they often contain biases in their estimates of contemporary climate that propagate into simulated futures. Land models translate climate projections into surface impacts, but these will be inaccurate if ESMs have substantial errors. Bias concerns are relevant for terrestrial physiological processes which often respond non-linearly (i.e. contain threshold responses) and are therefore sensitive to absolute environmental conditions as well as changes. We bias-correct the UK Met Office ESM, HadGEM2-ES, against the CRU–JRA observation-based gridded estimates of recent climate. We apply the derived bias corrections to future projections by HadGEM2-ES for the RCP8.5 scenario of future greenhouse gas concentrations. Focusing on South America, the bias correction includes adjusting for ESM estimates that, annually, are approximately 1 degree too cold, for comparison against 21st Century warming of around 4 degrees. Locally, these values can be much higher. The ESM is also too wet on average, by approximately 1 mm·day−1, which is substantially larger than the mean predicted change. The corrected climate fields force the Joint UK Land Environment Simulator (JULES) dynamic global vegetation model to estimate land surface changes, with an emphasis on the carbon cycle. Results show land carbon sink reductions across South America, and in some locations, the net land–atmosphere CO2 flux becomes a source to the atmosphere by the end of this century. Transitions to a CO2 source is where increases in plant net primary productivity are offset by larger enhancements in soil respiration. Bias-corrected simulations estimate the rise in South American land carbon stocks between pre-industrial times and the end of the 2080s is ∼12 GtC lower than that without climate bias removal, demonstrating the importance of merging historical observational meteorological forcing with ESM diagnostics. We present evidence for a substantial climate-induced role of greater soil decomposition in the fate of the Amazon carbon sink.

Summary Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate.We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf‐ and ecosystem‐level observations.SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem‐level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root‐mean‐square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites.SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors., See also the Commentary on this article by Anderegg & Venturas, 226: 1535–1538.

Robust estimates of CO₂ budget, CO₂ exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO₂ emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: “top-down” atmospheric inversions and “bottom-up” biosphere models. Since the first studies were undertaken, these ap-proaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmos-phere–biosphere CO₂ exchange. Here, we conducted a thorough comparison of CO₂ budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO₂ budgets. Our set of atmospheric inversions and bio-sphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO₂ budgets in the 2000s. Regionally, improved agreement in CO₂ budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO₂ budgets: (a) to increase repre-sentation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink–source compensation between regions (dipoles) in atmospheric inversion so that their esti-mates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO₂ budgets.

The UK has low breastfeeding rates, with socioeconomic disparities. The Assets‐based feeding help Before and After birth (ABA) intervention was designed to be inclusive and improve infant feeding behaviours. ABA is underpinned by the behaviour change wheel and offers an assets‐based approach focusing on positive capabilities of individuals and communities, including use of a Genogram. This study aimed to investigate feasibility of intervention delivery within a randomised controlled trial (RCT). Nulliparous women ≥16 years, (n = 103) from two English sites were recruited and randomised to either intervention or usual care. The intervention – delivered through face‐to‐face, telephone and text message by trained Infant Feeding Helpers (IFHs) – ran from 30‐weeks' gestation until 5‐months postnatal. Outcomes included recruitment rates and follow‐up at 3‐days, 8‐weeks and 6‐months postnatal, with collection of future full trial outcomes via questionnaires. A mixed‐methods process evaluation included qualitative interviews with 30 women, 13 IFHs and 17 maternity providers; IFH contact logs; and fidelity checking of antenatal contact recordings. This study successfully recruited women, including teenagers, from socioeconomically disadvantaged areas; postnatal follow‐up rates were 68.0%, 85.4% and 80.6% at 3‐days, 8‐weeks and 6‐months respectively. Breastfeeding at 8‐weeks was obtained for 95.1% using routine data for non‐responders. It was possible to recruit and train peer supporters to deliver the intervention with adequate fidelity. The ABA intervention was acceptable to women, IFHs and maternity services. There was minimal contamination and no evidence of intervention‐related harm. In conclusion, the intervention is feasible to deliver within an RCT, and a definitive trial required.

Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long-term atmospheric CO₂ concentration measurements at Anmyeondo Station (36.53°N, 126.32°E) located in the western coast. The influence of terrestrial carbon flux on atmospheric CO₂ concentrations (ΔCO₂) is estimated from the difference of CO₂ concentrations that were influenced by the land sector (through easterly winds) and the Yellow Sea sector (through westerly winds). We find a significant trend in ΔCO₂ of -4.75 ppmv decade⁻¹ (p < 0.05) during the vegetation growing season (May through October), suggesting that the regional terrestrial carbon uptake has increased relative to the surrounding ocean areas. Combined analysis with satellite measured normalized difference vegetation index and gross primary production shows that the enhanced carbon uptake is associated with significant nationwide increases in vegetation and its production. Process-based terrestrial model and inverse model simulations Estimate that regional terrestrial carbon uptake increases by up to 9.9 and 4.2 Tg C decade⁻¹, accounting for 13.4 and 5.7% of annual domestic carbon emissions averaged for the study period, respectively. Atmospheric chemical transport model simulations indicate that the enhanced terrestrial carbon sink is the primary reason for the observed ΔCO₂trend rather than anthropogenic emissions and atmospheric circulation changes. Our results highlight the fact that atmospheric CO₂ measurements could open up the possibility of detecting regional changes in the terrestrial carbon cycle even where anthropogenic emissions are not negligible.

This paper is the result of the INTERnational Conference on AtMosphere–BIOsphere Interactions (INTERCAMBIO), held in Medellin, Colombia, in October–November 2016. INTERCAMBIO was funded by Universidad de Antioquia, Universidad Eafit, the Purdue Research Foundation (PRF), ICETEX, the Purdue Climate Change Research Center (PCCRC), the Colombia–Purdue Initiative (CPI), and the Colombian Student Association at Purdue (CSAP). Partial funding for JCV, JFS, AMR, PAA, DM‐B, and JAP was provided by Colciencias through “Programa de investigacion en la gestion de riesgo asociado con cambio climatico y ambiental en cuencas hidrograficas” convocatoria 543‐2011. Funding for LM was provided by the Ayudar Foundation from the UK University of Exeter's College Benefactors. Partial support for JSD was provided by the US Department of Agriculture's National Institute of Food and Agriculture, through Hatch project 1000026.

Context Medical schools are increasingly using novel tools to select applicants. The UK Clinical Aptitude Test (UKCAT) is one such tool and measures mental abilities, attitudes and professional behaviour conducive to being a doctor using constructs likely to be less affected by socio-demographic factors than traditional measures of potential. Universities are free to use UKCAT as they see fit but three broad modalities have been observed: ‘borderline’, ‘factor’ and ‘threshold’. This paper aims to provide the first longitudinal analyses assessing the impact of the different uses of UKCAT on making offers to applicants with different socio-demographic characteristics. Methods Multilevel regression was used to model the outcome of applications to UK medical schools during the period 2004–2011 (data obtained from UCAS), adjusted for sex, ethnicity, schooling, parental occupation, educational attainment, year of application and UKCAT use (borderline, factor and threshold). Results The three ways of using the UKCAT did not differ in their impact on making the selection process more equitable, other than a marked reversal for female advantage when applied in a ‘threshold’ manner. Our attempt to model the longitudinal impact of the use of the UKCAT in its threshold format found again the reversal of female advantage, but did not demonstrate similar statistically significant reductions of the advantages associated with White ethnicity, higher social class and selective schooling. Conclusion Our findings demonstrate attenuation of the advantage of being female but no changes in admission rates based on White ethnicity, higher social class and selective schooling. In view of this, the utility of the UKCAT as a means to widen access to medical schools among non-White and less advantaged applicants remains unproven.

Context The challenge of ensuring ‘fair’ selection processes confronts all medical schools around the globe. In the UK, historical analyses suggest applicants who are male, non-White, and from less advantaged socio-economic and school backgrounds have been less likely to be offered a place at medical school. We provide a contemporary population-based longitudinal analysis of the likelihood of receiving an offer to read medicine in the UK stratified by key socio-demographic characteristics. Methods We calculated the likelihood of receiving an offer among applicants to UK medical schools during 1996–2012, adjusted for sex, ethnicity, schooling, parental occupation, educational attainment and year of application. To investigate differences across time, models were fitted with interactions between application year and each of the other explanatory variables. Results There were 154 957 applicants, including 86 361 females (55.7%) and 68 596 males (44.3%). The majority of applicants were White (n = 94 519, 61.0%). The most common parental occupation category was higher managerial and professional (HMP) (n = 60 167, 38.8%) and 68 313 (44.1%) applicants came from grammar and independent schools. The likelihood of receiving an offer to study medicine varied three-fold across the study period, peaking in 2001 against the 1996 baseline (odds ratio [OR] 2.94, 95% confidence interval [CI] 2.78–3.11; p