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The research presents a methodological framework to support strategy developers in designing innovative supply chain concepts for a circular bio-economy. Focus is placed on the PESTEL method (hereinafter PESTEL+I) that considers the huge variety of macro-environmental factors influencing intermediate carbon carrier (ICC) supply chains. The method significantly shifted the emphasis of strategic decisions to the market uptake of individual innovations compared to the basic method.

01 augustus 2023, Contains fulltext : 294969.pdf (Publisher’s version ) (Open Access), OBJECTIVES: We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics. METHODS: This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated. RESULTS: Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives. CONCLUSIONS: Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.

Background With sustainable bioenergy in the European energy mix, intermediate bioenergy carriers (IBC) become of growing importance, as they can ensure a more efficient utilisation of biomass feedstocks from agricultural and forest residues. A high potential for market uptake is foreseen for fast pyrolysis bio-oil (FPBO), one of several IBCs. While facing the chicken and egg problem in market entry, the aim of this study was the development of adequate strategies to support market implementation. The case study findings and methodological approach can provide policymakers, industry, and a broader audience with a vision for addressing similar challenges in market adoption of innovations in the bioeconomy and beyond. Therefore, we tested a new PESTEL + I approach and its practical applicability to an IBC value chain. Results With an adopted PESTEL method, we analysed a promising value chain in which FPBO is produced from sawdust in Sweden and Finland, transported to the Netherlands and upgraded and marketed as a marine biofuel. Our results show that the market uptake of IBCs such as FPBO and subsequently produced biofuels is above all driven by the European Renewable Energy Directive II (RED II). In Annex IX Part A, sawdust is listed as a feedstock for advanced biofuels, which can be double counted towards the 14% renewable energy share goal in the transport sector in 2030. To support the use of advanced biofuels in the maritime and aviation sector, the proposal for revision of RED II 2021 contains a new multiplier (1.2x) for fuels delivered to these sectors, while all other multipliers are deleted. These legal European obligations and implementation into national law of member states create strong incentives for many downstream market actors to use advanced biofuel. However, technological challenges for FPBO use still hamper fast market introduction. Conclusions Overcoming technology challenges and the creation of long-term validity of guidelines and regulatory fram

Indirect land use changes (iLUC) pose a significant challenge to the sustainable production of biomass and bioenergy. The implementation of sustainability certification has the potential to manage this risk effectively. However, there remains an open question regarding how to extend certification schemes to create a credible and reliable approach for accounting for iLUC risks. This study focuses on low iLUC risk biomass production, which can be achieved through the adoption of additionality practices by individual producers. To support the sustainable use of such practices, this study examines whether existing assessment instruments of voluntary certification schemes for trade-offs that might arise from the use of such practices are based on scientific evidence. We found trade-offs that are preferentially addressed by the schemes, and considerable gaps for certain trade-offs. Biomass cultivation on unused land could be determined as the most promising additionality practice in terms of addressing trade-offs. This study contributes to the need to implement additionality practices in low iLUC certification approaches without compromising sustainability by identifying trade-offs as required by European Union low iLUC legislation. Finally, this study presents a decision support tool tailored to certification schemes to verify that certification instruments addressing a particular trade-off are based on scientifically sound methods.

Background Innovations and new supply chain concepts are crucial for establishing a sustainable and circular bio-economy that reduces carbon emissions and lowers negative environmental impacts. PESTEL-based concept development provides information about positive, negative and neutral external factors of the macro-environment and their influence on supply chains. The primary data were collected at a stakeholder workshop and gaps in understanding the critical details were closed through expert interviews. The information gathered was organised using a data management software and coded by following a deductively formed system based on predefined PESTEL categories (political, economic, social, technological, ecological, legal). Stakeholders that used the method on intermediate carbon carriers (ICC) grappled with identifying the obstacles that hinder the market uptake of innovations. The workshop revealed a substantial demand for additional information. Infrastructural aspects were considered key to adequately understanding all of the segments along a supply chain. Using PESTEL alone, without taking infrastructural aspects into consideration, meant that the macro-environment that surrounds and affects the ICC supply chain remained a black box. This paper developed docking-related approaches to the basic PESTEL method in order to improve its output for the development of strategic concepts and to improve the market uptake of bio-economy-centred innovations. Results The expanded PESTEL method (hereinafter PESTEL + I) significantly shifted the emphasis of strategic decisions to the marketing of individual innovations compared to the basic method. Docking information gathering onto infrastructure (+ I) should be considered in order to expand existing strategy development concepts for bio-economy value chains. Testing the market uptake of innovations was beyond the scope of this study. Conclusions PESTEL + I not only increased the utility, but also the complexity and the tim

The valorisation of municipal and household biowaste as a relevant component of the EU’s Circular Economy Strategy is currently under discussion. However, there are several legal, technical and economic challenges associated with biowaste valorisation. This paper aims to pinpoint factors affecting biowaste supply chains using the PESTEL+I method and stakeholder workshops. Our analysis focuses on the macro-environment of an integrated biowaste conversion and valorisation concept in the region of Wallonia, Belgium. One key influencing factor is the EU’s legal framework on waste, which describes the end-of-waste status and defines criteria for biowaste reuse. While the analysis shows that EU regulations support biowaste valorisation, its transposition into national and regional law is lagging behind. The technological development of biowaste concepts might be hampered and many questions related to the marketisation of bio-based products remain unanswered. We therefore suggest that legal procedures for biowaste management have to be facilitated at the regional level. The region of Wallonia should establish a category for biowaste that would include standardized procedures for biowaste valorisation and products. It is essential that such regional barriers be overcome to establish the necessary cooperation with local stakeholders and to transfer biowaste supply chains to the market.

Contains fulltext : 252037.pdf (Publisher’s version ) (Open Access), OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms. METHODS: Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC). RESULTS: Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons