Time-in : promoting school readiness through emotion regulation In Flemish education

Worldwide, there is a high number of early school dropout in both regular and special education. In this regard, especially children with special educational needs are considered at risk for early school dropout since they often exhibit emotional and behavioral difficulties, which have been typically conceptualized as externalizing and internalizing problems. If emotional and behavioral difficulties persist, they may seriously disrupt the educational process and pose a difficult challenge for schools and teachers, who are, in fact, not specifically trained to deal with emotional and behavioral difficulties. Within these circumstances, mainly teachers with limited social and emotional competencies experience a lot of stress, feelings of powerlessness, and loss of control. To regain control, these teachers frequently use behavioral strategies such as time-out as well as disciplinary measures. However, the inappropriate use of these strategies may paradoxically put further pressure on the relationship between the teacher and the child and, moreover, lead to an increase in children’s emotional and behavioral difficulties. At the teacher level, this cascade may ultimately result in chronic stress, exhaustion, burnout, and absenteeism, while at the child-level, in reduced academic performance, suspension, and school exclusion. How can we stop these vicious circles? How can we ameliorate the well-being of these children and their teachers at school? It is aimed to look for some answers in this PhD thesis

Property prediction of fuel mixtures using pooled graph neural networks

Renewable fuels offer a sustainable option for engine applications where electrification is more challenging, not possible. To evaluate the potential of novel fuels it is crucial to first determine their combustion and spray related properties. This can be done experimentally, but during screening of multiple fuel candidates this can be cost and time expensive. Machine learning can be used for rapid, inexpensive, and accurate predictions of fuel mixture properties. To this end a novel function for pooling molecular representations called MolPool has been developed, which was combined with graph neural networks. The new approach processes the input permutation invariant, allowing for application to a varying number of components in the mixture. In this article, three different compression ignition engine related properties were investigated: derived cetane number (DCN), flashpoint, and viscosity. The results show that this novel neural network approach is able to increase the prediction accuracy and the generalizibility compared to traditional blending laws for all investigated properties. MolPool improves the prediction if oxygenated species are present in the mixture resulting non-linear mixture behavior, which is common for renewable fuels. Thus, MolPool shows great potential for prediction of various properties and fuel mixtures

Augmenting clinical trials in asthma through digital technology, decentralised designs, and person-centric endpoints : opportunities and challenges

Digital technologies (eg, smart inhalers, wearables, and sensors) allow for remote, objective, granular, and non-invasive data collection, making them attractive for research evaluating interventions in airways diseases with variable trajectories, such as asthma. Such technologies offer the opportunity to move towards decentralised clinical trials that are done partly or fully outside the classic clinical trial setting and are characterised by remote data collection and monitoring. This approach to evaluating clinical, pharmacological, or behavioural interventions could facilitate recruitment of inclusive and generalisable study populations, enhance personalisation and sustainability, reduce research costs, and accelerate the timeline to novel asthma treatments' market access. This Personal View discusses the application of digital technologies and endpoints within trials; the concept of hybrid and decentralised designs; describes a fully decentralised trial in asthma; and explores the strengths, weaknesses, opportunities, and threats regarding their implementation from the clinician, patient expert, low-resource, and regulator viewpoints

Feed additives for methane mitigation : a guideline to uncover the mode of action of antimethanogenic feed additives for ruminants

This publication aims to provide guidelines of the knowledge required and the potential research to be conducted in order to understand the mode of action of antimethanogenic feed additives (AMFA). In the first part of the paper, we classify AMFA into 4 categories according to their mode of action: (1) lowering dihydrogen (H2) production; (2) inhibiting methanogens; (3) promoting alternative H2-incorporating pathways; and (4) oxidizing methane (CH4). The second part of the paper presents questions that guide the research to identify the mode of action of an AMFA on the rumen CH4 production from 5 different perspectives: (1) microbiology; (2) cell and molecular biochemistry; (3) microbial ecology; (4) animal metabolism; and (5) cross-cutting aspects. Recommendations are provided to address various research questions within each perspective, along with examples of how aspects of the mode of action of AMFA have been elucidated before. In summary, this paper offers timely and comprehensive guidelines to better understand and reveal the mode of action of current and emerging AMFA

Geometric properties of ternary fuzzy relations

Ternary fuzzy relations, and fuzzy betweenness relations in particular, are witnessing increasing attention in recent years. A key reason is that axiomatic properties of ternary fuzzy relations seem to be ideally suited to capture geometric characteristics of the abstract notion of betweenness. In this paper, we introduce several new properties of ternary fuzzy relations, including the Peano property, the Pasch property and the sand-glass property, that can be qualified as geometric properties. We investigate their interrelationships as well as their connections with various types of fuzzy betweenness relations. Additionally, in the context of our study of the Pasch property and the sand-glass property, we introduce the convexity property of ternary fuzzy relations by taking inspiration from the solid theoretical basis of the theory of fuzzy convex structures