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The ‘Self’ has a prioritized cognitive status, attributed to an automatic bottom-up attentional enhancement for self-relevant stimuli. Two predictions follow if self-relevant information is automatically boosted. First, processing should be enhanced for self- compared to other-relevant targets. Second, interference should be greater for self- compared to other-relevant distractors. To investigate these predictions, we adapted a motion reproduction task. Participants first learned to associate a colour (blue, pink) with themselves and a stranger (other), then viewed a label (YOU or OTHER) and two different coloured superimposed random dot kinematograms (RDKs; blue, pink). A response dial recorded participants’ reproduced direction of motion for the coloured RDK associated with the presented label. Facilitation and interference for self- and other-labelled features was assessed by the angular difference between the reported and true direction of motion (signed error magnitude). There was a small, but reliable response bias in direction of distractor motion showing that attentional selection was imperfect. Further regression-based analyses quantified the degree to which self and other-related stimuli influenced responses (decision weights). As predicted, decision weights for target stimuli showed a significant advantage for self- compared with other-relevant motions. By contrast distractor weights did not differ significantly between self- and other-relevant features, suggesting self-relevance did not modulate the degree of interference and self-relevant stimuli did not automatically capture attention. Overall, we show that feature-based attention is enhanced for self-associated sensory input, but only when task-relevant.

Abstract The European Commission requested the EFSA Panel on Plant Health to prepare and deliver risk assessments for commodities listed in Commission Implementing Regulation (EU) 2018/2019 as ‘high risk plants, plant products and other objects’. Taking into account the available scientific information, including the technical information provided by the applicant country, this Scientific Opinion covers the plant health risks posed by the following commodities: Sorbus aucuparia bare‐root plants and rooted plants in pots up to 7 years old and specimen trees in pots up to 15 years old imported into the EU from the UK. A list of pests potentially associated with the commodities was compiled. The relevance of any pest was assessed based on evidence following defined criteria. Three EU quarantine pests (Entoleuca mammata and Phytophthora ramorum (non‐EU isolates), Erwinia amylovora), were selected for further evaluation. For two of the selected pests (E. mammata and P. ramorum), the risk mitigation measures implemented in the UK and specified in the technical dossier were evaluated taking into account the possible limiting factors. For these pests, an expert judgement is given on the likelihood of pest freedom taking into consideration the risk mitigation measures acting on the pest, including uncertainties associated with the assessment. The degree of pest freedom varies between the pests evaluated, with P. ramorum being the pest most frequently expected on the imported S. aucuparia plants. The Expert Knowledge Elicitation indicated, with 95% certainty, that between 9812 and 10,000 bare‐root S. aucuparia plants per 10,000 will be free from P. ramorum.

Effective waste management is crucial for sustainable industrial operations. This paper introduces a state-of-the-art digital tool designed for the circular economy. Primarily it pinpoints and quantifies symbiotic possibilities between industries with liquid waste streams, emphasising the most lucrative inter-industry connections. In practice, the tool takes in data such as waste stream volumes, material concentrations within these streams, market prices of materials, and industries’ raw material consumption rates. Utilising these, its algorithm identifies and assesses the most profitable material exchanges among the specified industries. This assessment considers the market value of materials and the costs associated with recovering those materials from liquid waste streams. One of the major challenges, the estimation of recovery costs, is addressed using an innovative Sherwood plot analysis. This analysis draws a correlation between a material’s recovery cost and its concentration within a liquid medium. The tool’s output provides a detailed list of potential transactions complemented by illustrative graphs that detail mass flows, profit margins, and environmental advantages for each industry. Collectively, these details offer insights both for individual industries and the industrial ecosystem as a whole. One of the tool’s most significant revelations is its ability to uncover potential “bridges” linking industrial waste streams to resource needs, unearthing previously unnoticed economic and ecological gains. By calculating economic and environmental benefits of “waste” reuse, this tool offers a compelling rationale for the adoption of industrial symbiosis. Ultimately, it uncovers the transformative potential of aligning industrial activities with a balance that fosters both economic growth and ecological responsibility.