Negation Processing in Children with ADHD: The Generic Problem of Using Negation in Instructions

Recent studies have suggested that negation comprehension falls back onto inhibitory brain systems that are also crucial for impulse control and other non-linguistic control domains (Beltran et al., 2018, 2019; de Vega et al., 2016; Liu et al., 2020). Against this backdrop, the present pilot study investigated the use of negation within directional instructions (i.e., “not left”, “now left”, “not right”, “now right”) in children with ADHD and a control group. The results indicate that children in general have a long response delay following negative compared to affirmative instructions. Additionally, there was a tendency for this effect to be more pronounced in the ADHD group. Together, these results suggest that negation processing might indeed demand inhibitory control processes, which are differently available across different subgroups. Thus, the current study provides evidence that using negation in imperatives or instructions is generally rather critical and should be avoided if possible, but that negation use is probably even more problematic in specific clinical populations. Potential implications of these results will be discussed.

On the Probabilities of Environmental Extremes

Environmental researchers, as well as epidemiologists, often encounter the problem of determining the probability of exceeding a high threshold of a variable of interest based on observations that are much smaller than the threshold. Moreover, the data available for that task may only be of moderate size. This generic problem is addressed by repeatedly fusing the real data numerous times with synthetic computer-generated samples. The threshold probability of interest is approximated by certain subsequences created by an iterative algorithm that gives precise estimates. The method is illustrated using environmental data including monitoring data of nitrogen dioxide levels in the air.

Plant Classification and Position Estimation for Autonomous Field Robots

This work presents new approaches to plant classifcation and plant position estimation to enable feld robot based precision agriculture. The developed methods are designed for challenging real world feld situations with small crop plants, presence of close-to-crop weed and overlap of plants. The plant classifcation system is able to distinguish two or more plant classes in feld images without the need for error-prone plant or leaf segmentation. The plant position estimation pipeline solves the generic problem of determining the position of both crop and weed plants only from image data. The combination of both methods allows feld robots to autonomously determine the type and position of plants in the feld to realize precision agriculture tasks such as single plant weed control. Experiments with a feld robot prove the applicability of the presented methods for challenging feld scenarios encountered for example in organic vegetable farming. Contents Symbols and Abbreviations . . . . . ...

Identification of Strategic Molecules for Future Circular Supply Chains Using Large Reaction Networks

Networks of chemical reactions represent relationships between molecules within chemical supply chains and promise to enhance planning of multi-step synthesis routes from bio-renewable feedstocks. This study aims to identify <i>strategic molecules</i>in chemical reaction networks that may potentially play a significant role within the future circular economy. We mine a commercially available database in order to assemble a network of chemical reactions. We describe molecules within the network by a portfolio of graph theoretical features, and identify strategic molecules with an isolation forest search algorithm. In this work we have identified a list of potential strategic molecules and indicated possibilities for reaction planning using these. This is exemplified by a potential supply chain of functional molecules from bio-waste streams that could be used as feedstocks without being converted to syngas. This work extends the methodology of analysis of reaction networks to the generic problem of development of new reaction pathways based on novel feedstocks.