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    Temporal prediction and feedforward control in cerebellar ataxia during spontaneous, instructed, and adaptive auditory-motor coupling while walking

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    Auditory-motor coupling, the entrainment of movement to an auditory stimulus, involves processes of temporal prediction and feedforward control. The cerebellum is central to these mechanisms, with deficits contributing to ataxia, characterized by incoordination and increased movement variability. Previous research investigated these mechanisms through perceptual or paced finger-tapping tasks. However, little is known about how these processes interact in complex motor tasks, such as walking, which require feedforward control and voluntary adaptability. Thus, the dynamic interplay between temporal prediction and feedforward control in persons with cerebellar ataxia (PwCA) during walking was assessed in three auditory-motor coupling paradigms (spontaneous, instructed and adaptive), involving walking to music and metronomes at different frequencies. The adaptive paradigm additionally incorporated real-time alignment algorithms. Sixteen PwCA (scale for the assessment and rating of ataxia 3.59 +/- 2.92) and fourteen healthy controls (HCs) participated. Overall, patients showed spared temporal predictions assessed by synchronization accuracy. Yet reduced synchronization consistency and gait modulation was observed in PwCA as compared to HCs, consistent with deficits of feedforward control. The adaptive alignment algorithm may have compensated for feedforward impairments, thereby promoting enhanced synchronization and gait dynamics. This approach warrants further investigation and holds potential for integration into rehabilitation strategies for persons with mild ataxia.Fonds Wetenschappelijk Onderzoek (FWO) project obtained by dr. Lousin Moumdjian, grant number 1295923N. Fonds Wetenschappelijk Onderzoek (FWO) project obtained by Prof. Peter Feys, grant number G082021N

    PAC: Computing Join Queries with Semi-Covers

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    An increased and growing interest in large-scale data processing has triggered a demand for specialized algorithms that thrive in massively parallel shared-nothing systems. To answer the question of how to efficiently compute join queries in this setting, a rich line of research has emerged specifically for the Massively Parallel Communication (MPC) model. In the MPC model, algorithms are executed in rounds, with each round consisting of a synchronized communication phase and a separate local computation phase. The main cost measure is the load of the algorithm, defined as the maximum number of messages received by any server in any round. We study worst-case optimal algorithms for the join query evaluation problem in the constant-round MPC model. In the single-round variant of MPC, the worst-case optimal load for this problem is well understood and algorithms exist that guarantee this load for any join query. In the constant-round variant of MPC, queries can often be computed with a lower load compared to the single-round variant, but the worst-case optimal load is only known for specific classes of join queries, including graph-like and acyclic join queries, and the associated algorithms use very different techniques. In this paper, we propose a new constant-round MPC algorithm for computing join queries. Our algorithm is correct for every join query and its load matches (up to a polylog factor) the worst-case optimal load for at least all join queries that are acyclic or graph-like.This work is partially funded by FWO-grant G062721N

    Silent Messengers: Extracellular Vesicles as Mediators of Blood-Brain Barrier Breakdown in Metabolic Dysfunction-Associated Steatohepatitis

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    Metabool disfunctie-geassocieerde steatohepatitis (MASH) is een progressieve leveraandoening die steeds vaker in verband wordt gebracht met extrahepatische complicaties, waaronder effecten op het centrale zenuwstelsel. MASH gaat gepaard met verstoring van de bloed-hersenbarrière (BBB), wat mogelijk bijdraagt aan neuro-inflammatie. De precieze mechanismen zijn echter nog onduidelijk. Deze studie onderzoekt of extracellulaire vesikels (EVs) afkomstig van de lever bijdragen aan BBB-dysfunctie bij MASH. Muizen kregen een vet- en suikerrijk dieet gedurende 15, 20 of 25 weken om MASH te induceren. Analyse van hersenweefsel toonde transcriptieveranderingen geassocieerd met een gedaalde BBB integriteit, leukocytenadhesie en inflammatie, evenals verhoogde IgG-lekkage in het hersenparenchym. Als endotheelcellen blootgesteld werden aan MASH-lever EVs verslechterde de BBB integriteit, aangetoond door een daling in transendotheliale elektrische weerstand, verminderde VE-Cadherine-expressie en verhoogde VCAM-1-expressie. Deze effecten waren het sterkst na 25 weken, wat wijst op een progressief verband tussen MASH-progressie en BBB verstoring. De resultaten ondersteunen de rol van lever-afgeleide EVs als mediatoren van inter-orgaancommunicatie die bijdragen aan BBB-dysfunctie bij MASH

    Juridische evaluatie van het Vlaamse jeugddelinquentierecht

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    Wat als een kind een strafbaar feit pleegt? Straffen, beschermen of begeleiden? In 2019 koos Vlaanderen met het Jeugddelinquentiedecreet voor een eigen koers. Dit decreet wil niet alleen jongeren verantwoordelijk stellen, maar hen ook kansen bieden om te herstellen en opnieuw hun plaats te vinden in de samenleving – met respect voor kinderrechten. Maar hoe werkt dat precies in de praktijk? Wat zijn de doelen van het decreet, en hoe vertaalt zich dat naar de behandeling van jongeren? Worden zaken snel en eerlijk afgehandeld? Wat betekent ‘proportionaliteit’ of ‘herstelgericht werken’ eigenlijk? En sluiten de Vlaamse regels aan bij wat internationaal wordt verwacht van een kindvriendelijke justitie? Deze thesis neemt je mee in een juridische analyse van het Jeugddelinquentiedecreet, vertrekkend vanuit twaalf toetsstenen. Een blik achter de schermen van een systeem dat tegelijk pedagogisch en juridisch, beloftevol én complex is

    Verkenning van het gebruik van reinforcement learning in de context van progressive glTF 2.0 streaming

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    Mijn masterproef onderzoekt het gebruik van reinforcement learning (RL) om de laadvolgorde van 3D-scènes, opgeslagen in het GLTF-formaat, te optimaliseren op basis van het camerastandpunt van de gebruiker. In plaats van willekeurig of op volgorde te laden, leert een RL-agent welke onderdelen van de scène het eerst geladen moeten worden om de visuele kwaliteit (gemeten met PSNR) zo snel mogelijk te verbeteren. Een aangepaste Gymnasium-omgeving simuleert het laden van scènes en biedt per stap beloningen op basis van de verbetering in beeldkwaliteit. De agent krijgt informatie over de afstand en zichtbaarheid van elk object vanuit het camerastandpunt. De trainingsloop maakt gebruik van MaskablePPO, een algoritme dat ongeldige acties (zoals al geladen objecten) kan uitsluiten. De omgeving communiceert met een rendering engine via WebSockets. Deze engine berekent per stap de PSNR-waarden, die worden gebruikt om de beloning te bepalen. Resultaten tonen aan dat de RL-agent effectief leert om objecten te prioriteren die het meest bijdragen aan de initiële beeldkwaliteit. Dit kan nuttig zijn voor toepassingen zoals progressieve weergave van complexe 3D-scènes in games, simulaties of webtoepassingen

    NLP-Based Hospital Diagnosis Reporting Aid

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    This thesis explores using NLP to automate hospital diagnosis reporting for Atrial Fibrillation patients following European Society of Cardiology guidelines. The two-phase study used English MIMIC-IV dataset (40,000+ records) and Dutch Jessa Hospital data (12,516 records) to develop AF classification and CHA2DS2-VASc score extraction models. For AF classification, XGBoost with TF-IDF achieved 95% accuracy on English cardiology data and 93% on Dutch data. Enhanced n-gram approaches improved Dutch performance from 0.71 to 0.78 F1-score by capturing negation patterns. For score extraction, fine-tuned MedRoBERTa.nl achieved 95% accuracy and 0.82 macro F1-score, excelling at identifying missing scores (0.967 F1-score). Quality analysis revealed documentation gaps: only 44.5% of 1,489 AF patients had documented CHA2DS2-VASc scores, with 26.7% having clinically significant scores requiring anticoagulation consideration. The research demonstrates feasibility of automated clinical text processing, combining traditional ML for classification with transformers for extraction. Results exceeded hypothesized thresholds (90% for classification, 85% for extraction) while highlighting cross-language processing challenges and class imbalance issues. Future work includes multi-label AF classification, improved embeddings, and continuing research on the automated reporting of other quality indicators for patients with AF

    Enhancing the racking resistance of timber shear walls with structural glass: An experimental and computational study

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    This work analyses the behaviour of structural timber-glass wall elements by carrying out experimental shear wall tests and calibrating a finite element model. Hybrid timber-glass diaphragms are a novel structural solution to increase the in-plane stiffness of façades in timber frame buildings. The solution is particularly interesting when large glass façades are desired in buildings with fewer inner structural walls. Therefore, this study investigates a hybrid system that activates the stiffness of the glass windows, using a structural silicone adhesive, to increase the structural stability of the timber façade. For these timber-glass systems, no existing design codes are applicable. A finite element model is developed in this contribution, simulating the mechanical behaviour of the system, including the timber-glass connections. This model is calibrated using small-scale connection tests. Additionally, eight shear experiments are performed on timber-glass façade elements to evaluate the strength and stiffness of the system. The behaviour of the various materials and connections is precisely captured using multiple measurement techniques, including Fibre Bragg Gratings embedded in the glass panes, Digital Image Correlation, and strain gauges. The experimental results are compared to the numerical model to assess its suitability.The authors would like to recognize Dan Dragan and Niels Blocken for their contributions in conducting the experiments. They also extend their thanks to the Special Research Fund (BOF) of Hasselt University for its support of this research under Project Number BOF21DOC17. Special appreciation is given to Dow Silicones Belgium SPRL, especially Valerie Hayez and the laboratory team, for their invaluable assistance in specimen production and technical support. The authors express gratitude to Kömmerling Chemische Fabrik GMBH, particularly Christian Scherer and his team, for their insightful discussions and help with specimen creation. Furthermore, they appreciate the contributions of Soltech NV and Tatjana Vavilkin in the production of solar panels, as well as DUPAC NV for supplying the necessary timber. Lastly, the authors acknowledge the experimental work of Jasper van Berlo and Ruben Wagemans related to their master’s thesis

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