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ABSTRACT Fossil fuel subsidy reform(s) support the deployment of low‐carbon technologies, yet fossil fuel subsidies remain stubbornly high, while money allocated by governments to renewable energy continues to grow. In the transport sector, this tension is observed between biofuels that still rely on national policies and gasoline/diesel subsidies. Using a global Computable General Equilibrium (CGE) model, we study how phasing out gasoline and diesel subsidies would impact global biofuel mandates. We find that where they are implemented, Fossil Fuel Subsidy Reforms increase biofuel competitiveness and lower the cost of achieving the mandates. The fiscal benefit is therefore twofold with savings on fossil and bio‐based energy subsidies. In a multilateral reform scenario, we simulate the rise in fiscal revenue from phasing out the fossil fuel subsidies to be 25% higher when the avoided spending on biofuels' support is accounted for. In the rest of the world, however, the biofuel targets become costlier to achieve as the price of fossil fuels drops. Considering that global biofuel 2030 targets are achieved, governments' support for biofuel falls by $6 billion in regions phasing gasoline and diesel subsidies but increases by $600 million in the rest of the world.

Bioenergy with carbon capture and storage (BECCS) is a crucial element in most modelling studies on emission pathways of the Intergovernmental Panel on Climate Change to limit global warming. BECCS can substitute fossil fuels in energy production and reduce CO _2 emissions, while using biomass for energy production can have feedback effects on land use, agricultural and forest products markets, as well as biodiversity and water resources. To assess the former pros and cons of BECCS deployment, interdisciplinary model approaches require detailed estimates of technological information related to BECCS production technologies. Current estimates of the cost structure and capture potential of BECCS vary widely due to the absence of large-scale production. To obtain more precise estimates, a global online expert survey ( N = 32) was conducted including questions on the regional development potential and biomass use of BECCS, as well as the future operating costs, capture potential, and scalability in different application sectors. In general, the experts consider the implementation of BECCS in Europe and North America to be very promising and regard BECCS application in the liquid biofuel industry and thermal power generation as very likely. The results show significant differences depending on whether the experts work in the Global North or the Global South. Thus, the findings underline the importance of including experts from the Global South in discussions on carbon dioxide removal methods. Regarding technical estimates, the operating costs of BECCS in thermal power generation were estimated in the range of 100–200 USD/tCO _2 , while the CO _2 capture potential was estimated to be 50–200 MtCO _2 yr ^−1 by 2030, with cost-efficiency gains of 20% by 2050 due to technological progress. Whereas the individuals’ experts provided more precise estimates, the overall distribution of estimates reflected the wide range of estimates found in the literature. For the cost shares within BECCS, it was difficult to obtain consistent estimates. However, due to very few current alternative estimates, the results are an important step for modelling the production sector of BECCS in interdisciplinary models that analyse cross-dimensional trade-offs and long-term sustainability.

Objectives To train, test and validate the performance of a convolutional neural network (CNN)-based approach for the automated assessment of bone erosions, osteitis and synovitis in hand MRI of patients with inflammatory arthritis.Methods Hand MRIs (coronal T1-weighted, T2-weighted fat-suppressed, T1-weighted fat-suppressed contrast-enhanced) of rheumatoid arthritis (RA) and psoriatic arthritis (PsA) patients from the rheumatology department of the Erlangen University Hospital were assessed by two expert rheumatologists using the Outcome Measures in Rheumatology-validated RA MRI Scoring System and PsA MRI Scoring System scores and were used to train, validate and test CNNs to automatically score erosions, osteitis and synovitis. Scoring performance was compared with human annotations in terms of macro-area under the receiver operating characteristic curve (AUC) and balanced accuracy using fivefold cross-validation. Validation was performed on an independent dataset of MRIs from a second patient cohort.Results In total, 211 MRIs from 112 patients (14 906 region of interests (ROIs)) were included for training/internal validation using cross-validation and 220 MRIs from 75 patients (11 040 ROIs) for external validation of the networks. The networks achieved high mean (SD) macro-AUC of 92%±1% for erosions, 91%±2% for osteitis and 85%±2% for synovitis. Compared with human annotation, CNNs achieved a high mean Spearman correlation for erosions (90±2%), osteitis (78±8%) and synovitis (69±7%), which remained consistent in the validation dataset.Conclusions We developed a CNN-based automated scoring system that allowed a rapid grading of erosions, osteitis and synovitis with good diagnostic accuracy and using less MRI sequences compared with conventional scoring. This CNN-based approach may help develop standardised cost-efficient and time-efficient assessments of hand MRIs for patients with arthritis.

Abstract The Renewable Energy Directive (RED II) by the European Union (EU) provides an updated framework for the use of renewable energy in the EU transport sector until 2030, and bans the use of biofuels with a high risk of causing indirect land‐use change in high carbon stock areas (high ILUC‐risk criteria). The only biofuel feedstock affected by this criterion is palm oil. We employ the computable general equilibrium (CGE) model DART‐BIO for a scenario‐based policy analysis and evaluate a phase‐out of palm oil‐based biodiesel, and an additional phase‐out of soy oil‐based biodiesel in the EU. Our results show that the palm phase‐out has only a relatively small impact on global palm fruit production and total crop land use in tropical and subtropical regions, while the soy phase‐out leads to a comparable stronger decrease in global soy production, and a reduction in total cropland use in soy‐producing regions. Both policies lead to increased oilseed production in the EU. Therefore, farmer in Malaysia and Indonesia face a significantly reduced income. While European farmers profit the most, EU firms and households are confronted with higher expenditures. Finally, this study indicates that unilateral demand‐side regulations for a single good in a single sector is not sufficient for effective environmental protection. Enhanced binding sustainability criteria and certification schemes for the use of all vegetable oils in every sector and industry as well as improved protection schemes for sensible forest areas are necessary.

Abstract Background We describe and evaluate a deep network algorithm which automatically contours organs at risk in the thorax and pelvis on computed tomography (CT) images for radiation treatment planning. Methods The algorithm identifies the region of interest (ROI) automatically by detecting anatomical landmarks around the specific organs using a deep reinforcement learning technique. The segmentation is restricted to this ROI and performed by a deep image-to-image network (DI2IN) based on a convolutional encoder-decoder architecture combined with multi-level feature concatenation. The algorithm is commercially available in the medical products “syngo.via RT Image Suite VB50” and “AI-Rad Companion Organs RT VA20” (Siemens Healthineers). For evaluation, thoracic CT images of 237 patients and pelvic CT images of 102 patients were manually contoured following the Radiation Therapy Oncology Group (RTOG) guidelines and compared to the DI2IN results using metrics for volume, overlap and distance, e.g., Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD95). The contours were also compared visually slice by slice. Results We observed high correlations between automatic and manual contours. The best results were obtained for the lungs (DSC 0.97, HD95 2.7 mm/2.9 mm for left/right lung), followed by heart (DSC 0.92, HD95 4.4 mm), bladder (DSC 0.88, HD95 6.7 mm) and rectum (DSC 0.79, HD95 10.8 mm). Visual inspection showed excellent agreements with some exceptions for heart and rectum. Conclusions The DI2IN algorithm automatically generated contours for organs at risk close to those by a human expert, making the contouring step in radiation treatment planning simpler and faster. Few cases still required manual corrections, mainly for heart and rectum.

The replacement of fossil resources with renewable biomass in a bioeconomy is seen as a major contribution to climate change mitigation. This transformation will affect all members of society, making it crucial to consider the views of different stakeholders to ensure a socially acceptable transition towards a sustainable bioeconomy. To explore potential outcomes of bioeconomy strategies assuming different future pathways, a scenario analysis is a tool to inform decision-makers about policy impacts and trade-offs. The inter- and transdisciplinary research project “BioNex – The future of the biomass nexus” is the first project to develop bioeconomy scenarios together with stakeholders from politics, industry, and civil society in an iterative co-design process. As a result, three storylines describing diverging potential global futures are developed and quantified: Towards sustainability, business as usual, and towards resource depletion. The futures are driven by different assumptions on climate policy, cropland expansion, productivity growth in agriculture, prices of fossil energy, and consumption behaviour. Additionally, in the co-design process, three bioeconomy policies are developed: policy as usual, stronger development of the bioeconomy, and no policies. Besides presenting the results of the stakeholder workshops, this paper evaluates the strengths and shortcomings of a stakeholder approach in terms of policy-oriented research. According to the experience made within this study, it provides valuable insights for researchers and funding authorities they can use to optimise the employment of stakeholder-based research approaches.