This paper outlines an investigation into the updating of fatigue reliability through inspection data by means of structural correlation. The proposed methodology is based on the random nature of fatigue fracture growth and the probability of damage detection and introduces a direct link between predicted crack size and inspection results. A distinct focus is applied on opportunities for utilizing inspection information for the updating of both inspected and uninspected (or uninspectable) locations.
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We need educators to be constantly updating their skills and knowledge, and evidenced-informed practice is central to this; yet it is far from universal in our schools. Kristin Vanlommel and Chris Brown draw on their international research to show how EIP can be achieved based on three core principles. With this article, we consider the engagement by teachers and school leaders in educational practices that are ‘evidence-informed’ - across school systems and world-wide. There is a growing consensus that effective teaching and leadership is based on evidence-informed practice (or EIP), and that EIP results in improving student learning and achievement.
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This study provides ERP and oscillatory dynamics data associated with the comprehension of narratives involving counterfactual events. Participants were given short stories describing an initial situation ("Marta wanted to plant flowers in her garden...."), followed by a critical sentence describing a new situation in either a factual ("Since she found a spade, she started to dig a hole") or counterfactual format ("If she had found a spade, she would have started to dig a hole"), and then a continuation sentence that was either related to the initial situation ("she bought a spade") or to the new one ("she planted roses"). The ERPs recorded for the continuation sentences related to the initial situation showed larger negativity after factuals than after counterfactuals, suggesting that the counterfactual's presupposition - the events did not occur - prevents updating the here-and-now of discourse. By contrast, continuation sentences related to the new situation elicited similar ERPs under both factual and counterfactual contexts, suggesting that counterfactuals also activate momentarily an alternative "as if" meaning. However, the reduction of gamma power following counterfactuals, suggests that the "as if" meaning is not integrated into the discourse, nor does it contribute to semantic unification processes.
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Automation is a key enabler for the required productivity improvement in the agrifood sector. After years of GPS-steering systems in tractors, mobile robots start to enter the market. Localization is one of the core functions for these robots to operate properly on fields and in orchards. GNSS (Global Navigation Satellite System) solutions like GPS provide cm-precision performance in open sky, but buildings, poles and biomaterial may reduce system performance. On top, certain areas do not provide a dependable grid communication link for the necessary GPS corrections and geopolitics lead to jamming activities. Other means for localization are required for robust operation. VSLAM (Visual Simultaneous Localization And Mapping) is a complex software approach that imitates the way we as humans learn to find our ways in unknown environments. VSLAM technology uses camera input to detect features in the environment, position itself in that 3D environment while concurrently creating a map that is stored and compared for future encounters, allowing the robot to recognize known environments and continue building a complete, consistent map of the environment covered by its movement. The technology also allows continuous updating of the map in environments that evolve over time, which is a specific advantage for agrifood use cases with growing crops and trees. The technology is however relatively new, as required computational power only recently became available in tolerable cost range and it is not well-explored for industrialized applications in fields and orchards. Orientate investigates the merits of open-source SLAM algorithms on fields - with Pixelfarming Robotics and RapAgra - and in an orchard - with Hillbird - preceded by simulations and initial application on a HAN test vehicle driving in different terrains. The project learnings will be captured in educational material elaborating on VSLAM technology and its application potential in agrifood.
