Zobrazeno 1 - 10
of 9 572
pro vyhledávání: '"Menzel, P."'
With increasing emphasis on the study of active solids, the features of these classes of nonequilibrium systems and materials beyond their mere existence shift into focus. One concept of active solids addresses them as active, self-propelled units th
Externí odkaz:
http://arxiv.org/abs/2410.15594
Autor:
Reinken, Henning, Menzel, Andreas M.
Bacterial suspensions and other active fluids can develop highly dynamical vortex states called mesoscale turbulence. Here, we reveal the pronounced effect of non-Newtonian rheology of the carrier fluid, concentrating on shear thinning. Remarkably, t
Externí odkaz:
http://arxiv.org/abs/2409.18576
Autor:
Salem, Nayel Fabian, Nolte, Marcus, Haber, Veronica, Menzel, Till, Steege, Hans, Graubohm, Robert, Maurer, Markus
Publikováno v:
IEEE Access, vol. 12, pp. 165203-165226, 2024
Vehicles in public traffic that are equipped with Automated Driving Systems are subject to a number of expectations: Among other aspects, their behavior should be safe, conforming to the rules of the road and provide mobility to their users. This pos
Externí odkaz:
http://arxiv.org/abs/2409.06607
To provide insight into the basic properties of emerging structures when bacteria or other microorganisms conquer surfaces, it is crucial to analyze their growth behavior during the formation of thin films. In this regard, many theoretical studies fo
Externí odkaz:
http://arxiv.org/abs/2408.11581
Autor:
Singh, Chandan, Ntinas, Vasileios, Prousalis, Dimitrios, Wang, Yongmin, Demirkol, Ahmet Samil, Messaris, Ioannis, Rana, Vikas, Menzel, Stephan, Ascoli, Alon, Tetzlaff, Ronald
This paper introduces an innovative graphical analysis tool for investigating the dynamics of Memristor Cellular Nonlinear Networks (M-CNNs) featuring 2nd-order processing elements, known as M-CNN cells. In the era of specialized hardware catering to
Externí odkaz:
http://arxiv.org/abs/2408.03260
Autor:
Mayo, Perla, Cencini, Matteo, Pirkl, Carolin M., Menzel, Marion I., Tosetti, Michela, Menze, Bjoern H., Golbabaee, Mohammad
Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI for multiparametric tissue mapping. The reconstruction of quantitative maps requires tailored algorithms for removing aliasing artefacts from the compressed samp
Externí odkaz:
http://arxiv.org/abs/2408.02367
Autor:
Mayo, Perla, Cencini, Matteo, Fatania, Ketan, Pirkl, Carolin M., Menzel, Marion I., Menze, Bjoern H., Tosetti, Michela, Golbabaee, Mohammad
The estimation of multi-parametric quantitative maps from Magnetic Resonance Fingerprinting (MRF) compressed sampled acquisitions, albeit successful, remains a challenge due to the high underspampling rate and artifacts naturally occuring during imag
Externí odkaz:
http://arxiv.org/abs/2407.19866
One of the most promising solutions for uncertainty quantification in high-dimensional statistics is the debiased LASSO that relies on unconstrained $\ell_1$-minimization. The initial works focused on real Gaussian designs as a toy model for this pro
Externí odkaz:
http://arxiv.org/abs/2407.18964
Over the last few years, debiased estimators have been proposed in order to establish rigorous confidence intervals for high-dimensional problems in machine learning and data science. The core argument is that the error of these estimators with respe
Externí odkaz:
http://arxiv.org/abs/2407.13575
Autor:
Fischer, Lukas, Menzel, Andreas M.
Calculating by analytical theory the deformation of finite-sized elastic bodies in response to internally applied forces is a challenge. Here, we derive explicit analytical expressions for the amplitudes of modes of surface deformation of a homogeneo
Externí odkaz:
http://arxiv.org/abs/2407.09291