This chapter focuses on how pupil’s scientific understanding can be studied. The principles of a complex dynamic systems approach are highlighted.
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Albeit the widespread application of recommender systems (RecSys) in our daily lives, rather limited research has been done on quantifying unfairness and biases present in such systems. Prior work largely focuses on determining whether a RecSys is discriminating or not but does not compute the amount of bias present in these systems. Biased recommendations may lead to decisions that can potentially have adverse effects on individuals, sensitive user groups, and society. Hence, it is important to quantify these biases for fair and safe commercial applications of these systems. This paper focuses on quantifying popularity bias that stems directly from the output of RecSys models, leading to over recommendation of popular items that are likely to be misaligned with user preferences. Four metrics to quantify popularity bias in RescSys over time in dynamic setting across different sensitive user groups have been proposed. These metrics have been demonstrated for four collaborative filteri ng based RecSys algorithms trained on two commonly used benchmark datasets in the literature. Results obtained show that the metrics proposed provide a comprehensive understanding of growing disparities in treatment between sensitive groups over time when used conjointly.
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Energy Valley cluster and internationalisation.There is a need for more dynamic approaches to strategy development for clusters due to the complex internal and external environments that are part of clusters. The research introduced complex adaptive systems (CAS) approach to cluster theory where contextual analysis of clusters are an essential part of understanding cluster development. In-depth analyses of cluster dynamics and drivers of change in the context of the cluster would provide deeper understanding of cluster developments that will then feed into strategy development processes.
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With increasing penetration rates of driver assistance systems in road vehicles, powerful sensing and processing solutions enable further automation of on-road as well as off-road vehicles. In this maturing environment, SMEs are stepping in and education needs to align with this trend. By the input of student teams, HAN developed a first prototype robot platform to test automated vehicle technology in dynamic road scenarios that include VRUs (Vulnerable Road Users). These robot platforms can make complex manoeuvres while carrying dummies of typical VRUs, such as pedestrians and bicyclists. This is used to test the ability of automated vehicles to detect VRUs in realistic traffic scenarios and exhibit safe behaviour in environments that include VRUs, on public roads as well as in restricted areas. Commercially available VRU-robot platforms are conforming to standards, making them inflexible with respect to VRU-dummy design, and pricewise they are far out of reach for SMEs, education and research. CORDS-VTS aims to create a first, open version of an integrated solution to physically emulate traffic scenarios including VRUs. While analysing desired applications and scenarios, the consortium partners will define prioritized requirements (e.g. robot platform performance, dummy types and behaviour, desired software functionality, etc.). Multiple robots and dummies will be created and practically integrated and demonstrated in a multi-VRU scenario. The aim is to create a flexible, upgradeable solution, published fully in open source: The hardware (robot platform and dummies) will be published as well-documented DIY (do-it-yourself) projects and the accompanying software will be published as open-source projects. With the CORDS-VTS solution, SME companies, researchers and educators can test vehicle automation technology at a reachable price point and with the necessary flexibility, enabling higher innovation rates.
Inhalation therapy is essential for the management of respiratory conditions such as asthma and chronic obstructive pulmonary disease. However, current inhalation systems face limitations, including polydisperse aerosols that reduce drug delivery efficiency and complex treatment regimens that affect patient adherence. To improve drug targeting and efficacy, Gilbert Innovation B.V. is developing a next-generation soft-mist inhaler based on electrohydrodynamic atomization (EHDA), which produces uniform micrometer sized droplets. Effective drug delivery requires high flow rates and precise aerosol discharge to ensure deep lung deposition while minimizing losses to the device and oropharynx. To achieve this, the device employs a multi-nozzle system for increased flow and corona discharge needles for charge neutralization. However, ensuring uniform neutralization across multiple nozzles and maintaining stable electrospray operation remain key challenges. COSMIC aims to increase system robustness by optimizing neutralization efficiency, refining material selection, and controlling electrospray stability under varying conditions. The electrospray control system will incorporate advanced strategies leveraging computer vision, machine learning and big data analytics. These innovations will increase efficiency, accessibility and patient comfort in inhalation therapy.
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.
