Modern airport management is challenged by the task of operating aircraft parking positions most efficiently while complying with environmental policies, restrictions, schedule disruptions, and capacity limitations. This study proposes a novel framework for the stand allocation problem that uses a divide-and-conquer approach in combination with Bayesian modelling, simulation, and optimisation to produce less-pollutant solutions under realistic conditions. The framework presents three innovative aspects. First, inputs from the stochastic analysis module are used in a multivariate optimisation for generating variability-robust solutions. Second, a combination of optimisation and simulation is used to finely explore the impact of realistic uncertainty uncaptured by the framework. Lastly, the framework considers the role of human beings as the final control of operational conditions. A case study is presented as a proof of concept and demonstrates results achievable and benefits of the framework proposed. The experimental results demonstrate that the framework generates less-pollutant solutions under realistic conditions.
Although assessment practices are commonly part of the physical education (PE) curriculum they may often frustrate rather than support students’ basic needs for autonomy, competence and relatedness. Nevertheless, assessment also provides various promising opportunities to support these basic needs and enhance learning in students. In order to address this issue, we developed an in-service teacher training programme that was grounded within contemporary theories on assessment and motivation, and aimed at improving PE teachers’ expertise on motivational assessment practices. In close collaboration with PE teachers and other experts in the field an in-service teacher training programme was developed that covered important topics such as quality assessment, motivation and assessment for learning. Specific attention was directed to the translation of theoretical concepts into practical and applicable tools. The in-service training programme was then provided on-site three times to a total of 33 PE teachers (of whom 20 were male (60%) and 12 were female (40%), teaching experience 3–32 years) representing different PE departments. Through an iterative cycle of development, provision, evaluation and adjustment the programme was gradually optimised. Focus group sessions and questionnaires were employed to evaluate various aspects, and identify barriers and success factors. The in-service teacher training programme is a successful first step in improving the expertise of PE teachers to start and develop higher quality and more motivating assessment practices. Nevertheless, in order to generate durable change within daily PE practice, follow-up training sessions or counselling methods (e.g. through communities of practice) are essential to overcome implementation barriers. Development, adjustment and future directions for assessment are discussed.
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The project STORE&GO aims to investigate all the aspects regarding the integration of large-scale Power-to-Gas (PtG) at European level, by exploiting it as means for long term storage. One of the aspects that should be properly addressed is the beneficial impact that the integration of PtG plants may have on the electricity system.In the project framework, WP6 devoted its activities to investigate different aspects of the integration of PtG in the electricity grid, with the previous delivered reports.This deliverable focused in particular on how integrate the information about the facilities replicating the real world condition into a simulation environment. For doing this, the concept of remote Physical Hardware-in-the-Loop (PHIL) has been used and exploit.Remote simulation with physical hardware appears to be an effective means for investigating new technologies for energy transition, with the purpose of solving the issues related to the introduction of new Renewable Energy Sources (RES) into the electricity system. These solutions are making the overall energy systems to be investigated much more complex than the traditional ones, introducingnew challenges to the research. In fact:• the newly integrated technologies deal with different energy vectors and sectors, thus• requiring interoperability and multidisciplinary analysis;• the systems to be implemented often are large-scale energy systems leading to enormously complicated simulation models;• the facilities for carrying out the experiments require huge investments as well as suitable areas where to be properly installed.This may lead to the fact that a single laboratory with limited expertise, hardware/software facilities and available data has not the ability to secure satisfactory outcomes. The solution is the share of existing research infrastructures, by virtually joining different distant laboratories or facilities.This results in improvement of simulation capabilities for large-scale systems by decoupling into subsystems to be run on distant targets avoidance of replication of already existing facilities by exploiting remote hardware in the loop concept for testing of remote devices.Also confidential information of one lab, whose sharing may be either not allowed or requiring long administrative authorization procedures, can be kept confidential by simulating models locally and exchanging with the partners only proper data and simulation results through the co-simulation medium.Thanks to the realized method it is possible to real time analyse renewable devices at remotepower plants and place them in the loop of a local network simulation.The results reported show that the architecture developed is strong enough for being applied also atnew renewable power plants. This opens the possibility to use the data for research purposed, butalso to act in remote on the infrastructure in case of particular test (for example the acceptance test).
Logistics represents around 10-11% of global CO2 emissions, around 75% of which come from road freight transport. ‘The European Green Deal’ is calling for drastic CO2 reduction in this sector. This requires advanced and very expensive technological innovations; i.e. re-design of vehicle units, hybridization of powertrains and automatic vehicle technology. Another promising way to reach these environmental ambitions, without excessive technological investments, is the deployment of SUPER ECO COMBI’s (SEC). SEC is the umbrella name for multiple permutations of 32 meter, 70 tons, road-train combinations that can carry the payload-equivalent of 2 normal tractor-semitrailer combinations and even 3 rigid trucks. To fully deploy a SEC into the transport system the compliance with the existing infrastructure network and safety needs to be guaranteed; i.e. to deploy a specific SEC we should be able to determine which SEC-permutation is most optimal on specific routes with respect to regulations (a.o. damage to the pavement/bridges), the dimensions of specific infrastructures (roundabouts, slopes) and safety. The complexity of a SEC compared to a regular truck (double articulation, length) means that traditional optimisation methods are not applicable. The aim of this project is therefore to develop a first methodology enabling the deployment of the optimal SEC permutation. This will help transport companies (KIEM: Ewals) and trailer manufactures (KIEM: Emons) to invest in the most suitable designs for future SEC use. Additionally the methodology will help governments to be able to admit specific SEC’s to specific routes. The knowledge gained in this project will be combined with the knowledge of the broader project ENVELOPE (NWA-IDG). This will be the start of broader research into an overall methodology of deploying optimal vehicle combinations and a new regulatory framework. The knowledge will be used in master courses on vehicle dynamics.
Entangled Machines is a project by Mariana Fernández Mora that interrogates the colonial and extractive legacies underpinning artificial intelligence (AI). By introducing slowness and digital kinship as critical frameworks, the project reconceptualises AI as embedded within intricate social and ecological networks, thereby contesting dominant narratives of efficiency and optimisation. Through participatory, practice-based methodologies such as the Material Playground, the project integrates feminist and non-Western epistemologies to articulate alternative models for ethical, sustainable, and equitable AI practices. Over a four-year period, Entangled Machines develops theory, engages diverse communities, and produces artistic outputs to reimagine human-AI interactions. In collaboration with partners including ARIAS Amsterdam, Archival Consciousness, and the Sandberg Institute, the research seeks to foster decolonial and interdisciplinary approaches to AI. Its culmination will be an “Anarchive” – a curated assemblage of artistic, theoretical, and archival outputs – that serves as a resource for rethinking AI’s socio-political and ecological impacts.
CRISPR/Cas genome engineering unleashed a scientific revolution, but entails socio-ethical dilemmas as genetic changes might affect evolution and objections exist against genetically modified organisms. CRISPR-mediated epigenetic editing offers an alternative to reprogram gene functioning long-term, without changing the genetic sequence. Although preclinical studies indicate effective gene expression modulation, long-term effects are unpredictable. This limited understanding of epigenetics and transcription dynamics hampers straightforward applications and prevents full exploitation of epigenetic editing in biotechnological and health/medical applications.Epi-Guide-Edit will analyse existing and newly-generated screening data to predict long-term responsiveness to epigenetic editing (cancer cells, plant protoplasts). Robust rules to achieve long-term epigenetic reprogramming will be distilled based on i) responsiveness to various epigenetic effector domains targeting selected genes, ii) (epi)genetic/chromatin composition before/after editing, and iii) transcription dynamics. Sustained reprogramming will be examined in complex systems (2/3D fibroblast/immune/cancer co-cultures; tomato plants), providing insights for improving tumor/immune responses, skin care or crop breeding. The iterative optimisations of Epi-Guide-Edit rules to non-genetically reprogram eventually any gene of interest will enable exploitation of gene regulation in diverse biological models addressing major societal challenges.The optimally balanced consortium of (applied) universities, ethical and industrial experts facilitates timely socioeconomic impact. Specifically, the developed knowledge/tools will be shared with a wide-spectrum of students/teachers ensuring training of next-generation professionals. Epi-Guide-Edit will thus result in widely applicable effective epigenetic editing tools, whilst training next-generation scientists, and guiding public acceptance.
