https://luck.synhera.be/handle/123456789/109 Sun, 13 Sep 2026 11:40:29 GMT 2026-09-13T11:40:29Z https://luck.synhera.be:443/bitstream/id/e18e01fc-2547-46d2-a665-a1250c115ca5/ https://luck.synhera.be/handle/123456789/109 https://luck.synhera.be/handle/123456789/3138 Casimir scaling in glueballs in SU(��) and Sp(2��) gauge theories: Hints from constituent approaches Buisseret, Fabien; Semay, Claude; Mathieu, Vincent; Chevalier, Cyrille Xe have shown that the ratio of the glueball masses on their large N mass in SU(N) and Sp(2N) gauge theories dominantly scales according to the Casimir scaling hypothesis. This result is in agreement with previous findings in the mesonic sector. Such scaling laws may help to put constraints on effective models parameters, as we have shown in the case of constituent gluons approaches, where the observed scaling law favours adjoint strings as the best candidate to model interactions between constituent gluons. A simple two-body spinless Salpeter Hamiltonian with funnel potential is able to model the SU(∞) and Sp(∞) ��=+ low-lying spectrum provided constituent gluons are seen as transverse particles. A three-body Y-junction generalization of this Hamiltonian leads to a ��=− low-lying spectrum with the expected global features but show-ing extra states with respect to the lattice QCD spectrum. Sat, 10 Jan 2026 00:00:00 GMT https://luck.synhera.be/handle/123456789/3138 2026-01-10T00:00:00Z https://luck.synhera.be/handle/123456789/3137 t si le cerveau utilisait la physique fondamentale pour piloter nos gestes ? Du Brulle, Christian; Boulanger, Nicolas; Buisseret, Fabien; Dierick, Frédéric; White, Olivier Saisir une tasse, écrire son prénom, tendre la main. Des gestes simples, presque automatiques. Derrière cette apparente évidence se cache une question : comment le cerveau choisit-il un mouvement précis parmi une infinité de possibilités pour réaliser ces tâches ? Fri, 08 May 2026 00:00:00 GMT https://luck.synhera.be/handle/123456789/3137 2026-05-08T00:00:00Z https://luck.synhera.be/handle/123456789/3086 From brain to motion: harnessing higher-derivative mechanics for neural control White, Olivier; BUISSERET, Fabien; DIERICK, Frédéric; Boulanger, Nicolas Optimal Feedback Control provides a theoretical framework for goal-directed movements, where the nervous system adjusts actions based on sensory feedback. This theory assumes that there exists a cost function that is optimized throughout one's movement. It is natural to assume that mechanical quantities should be involved in cost functions, but this does not imply that the mechanical principles that govern human voluntary movements are necessarily Newtonian. We argue that integrating principles from Lagrangian and Hamiltonian higher-derivative mechanics, i.e. dynamical models relying on a Lagrangian of the form $L\left(\vec x,\dot{\vec x},\ddot{\vec x},\dots,\vec x^{\, (N)}\right)$, with $N\geq 2$ and where $\vec x^{\, (i)}$ denotes the $i^{\rm th}$ time-derivative of the position $\vec x$, provides a more natural framework to study the constraints hidden in human voluntary movement within Optimal Feedback Control theory. Tue, 25 Nov 2025 00:00:00 GMT https://luck.synhera.be/handle/123456789/3086 2025-11-25T00:00:00Z https://luck.synhera.be/handle/123456789/3084 Stress on the stride: How treadmill walking reveals gait variability differences in children, young adults, and seniors? Buisseret, Fabien; Sanso, Aline; Sen, Eda nur; White, Olivier; Boulanger, Nicolas; Dierick, Frédéric The assessment of gait variability is a valuable approach for characterizing an individual’s walking pattern over extended time scales. Variability parameters, such as the coefficient of variation, the Hurst exponent, and the Minkowski fractal dimension of the attractor, are influenced by factors like age, dual-task performance, and neurodegenerative conditions. Treadmill walking, a compact and widely used method, enables precise data collection when combined with measurement devices. However, differences between treadmill and overground variability raise questions about its applicability to real-life gait analysis. This study investigates how treadmill walking, as an external stressor, reveals gait variability differences among children, young adults, and seniors by analyzing the center of mass trajectory. Fifteen children (median age: 11 years), 24 young adults (median age: 22.5 years), and 16 seniors (median age: 60 years) participated. Variability was assessed using stride intervals and phase-space metrics. Results indicate that young adults demonstrate “optimal” gait variability, characterized by minimal coefficients of variation and maximal fractal dimension. In contrast, children and seniors exhibit less predictable and less complex gait patterns, with differences in Hurst exponents distinguishing these groups. These findings highlight the nontrivial integration of age, fear of falling, and neurological maturation in gait variability. Practical implications for rehabilitation and clinical assessments are discussed, underscoring the need for protocol standardization and cautious interpretation of treadmill-based variability data. Thu, 25 Sep 2025 00:00:00 GMT https://luck.synhera.be/handle/123456789/3084 2025-09-25T00:00:00Z