Results 11 to 20 of about 141 (99)

Residual Strength Prediction of Chemically Reactive Two‐Phase Nanofluid Flow in a Bingham–Papanastasiou Rheological Theory Using a Morlet‐Based Wavelet Neural Network Approach

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The behavior of nanofluid flow involving a zero‐mass flux condition has received considerable interest because of a realistic scenario. In reality, this condition confines the optimistic accumulation or disappearance of nanoparticles past a sheet, constructing a more physically realistic demonstration through several applications, such as heat
Umair Khan, Hamza Rauf, Aurang Zaib, J. K. Madhukesh   +3 more
wiley   +1 more source

Kernel Bounds for Parabolic Operators Having First‐Order Degeneracy at the Boundary

Mathematische Nachrichten, EarlyView.
ABSTRACT We study kernel estimates for parabolic problems governed by singular elliptic operators ∑i,j=1N+1qijDij+cDyy,cγ+1>0,γ=qN+1,N+1,$$\begin{equation*} \sum _{i,j=1}^{N+1}q_{ij}D_{ij}+c\frac{D_y}{y},\qquad \frac{c}{\gamma }+1>0, \quad \gamma =q_{N+1,N+1}, \end{equation*}$$in the half‐space R+N+1={(x,y):x∈RN,y>0}$\mathbb {R}^{N+1}_+=\lbrace (x,y ...
L. Negro, C. Spina
wiley   +1 more source

A Detailed and Comprehensive Account of Fractional Physics‐Informed Neural Networks: From Implementation to Efficiency

Artificial Intelligence for Engineering, EarlyView.
Caputo‐based fPINNs accurately solve fractional ODEs and PDEs while exposing an accuracy–cost trade‐off driven by the history‐dependent fractional derivative. Temporal collocation and shorter time windows are the most effective strategies for improving early‐time accuracy without unnecessary spatial refinement.
Donya Dabiri, Joshua DaRosa, Milad Saadat, Deepak Mangal, Safa Jamali   +4 more
wiley   +1 more source

Update on Non‐Biological and RNA‐Based Therapeutics in Chronic Inflammatory Diseases: Precision Medicine Through Small Molecules: An EAACI Position Paper

Allergy, EarlyView.
ABSTRACT In the last decades, critical advancements in research technology and knowledge on disease mechanisms steered therapeutic approaches for chronic inflammatory diseases towards unprecedented target specificity. For allergic and chronic lung diseases, biologic drugs pioneered this goal, acquiring on the way—through the clinical use of monoclonal ...
F. Roth‐Walter, I. M. Adcock, C. Benito‐Villalvilla, R. Bianchini, L. Bjermer, G. Caramori, L. Cari, K. F. Chung, Z. Diamant, I. Eguiluz‐Gracia, E. F. Knol, M. Jesenak, F. Levi‐Schaffer, G. Nocentini, L. O'Mahony, O. Palomares, F. Redegeld, M. Sokolowska, B. Van Esch, M. Zurlo, C. Stellato   +20 more
wiley   +1 more source

Computing Skinning Weights via Convex Duality

Computer Graphics Forum, EarlyView.
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

Computer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source

Controllable Intrinsic Surface Pattern Generation Using Slime Mold Simulations

Computer Graphics Forum, EarlyView.
Abstract Surface‐based pattern simulations have proven valuable for texture design and scientific visualization, but existing methods face several limitations. Most simulations either target a narrow range of pattern types (e.g. spots, branching) or support a broad range of patterns at the cost of time‐consuming parameter tuning.
Jeffrey Layton, Faramarz Samavati, Adam Runions   +2 more
wiley   +1 more source

Mesh Processing Non‐Meshes via Neural Displacement Fields

Computer Graphics Forum, EarlyView.
Abstract Mesh processing pipelines are mature, but adapting them to newer non‐mesh surface representations—which enable fast rendering with compact file size—requires costly meshing or transmitting bulky meshes, negating their core benefits for streaming applications.
Yuta Noma, Zhecheng Wang, Chenxi Liu, Karan Singh, Alec Jacobson   +4 more
wiley   +1 more source

Circles of Confidence for Multi‐Label Geometry Completion

Computer Graphics Forum, EarlyView.
Abstract Inside–outside classification is widely used for geometry processing tasks such as surface reconstruction, geometry completion, and calculating signed distance fields. We introduce a new integral formulation of this problem, which assigns confidence scores that points are inside or outside, given incomplete boundary geometry.
Z. Wei, C. Hafner, A. Kalinov, P. Heiss‐Synak, C. Wojtan   +4 more
wiley   +1 more source

Medial Axis Aware Learning of Signed Distance Functions

Computer Graphics Forum, EarlyView.
Abstract We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump set of the gradient of the SDF, which coincides with the medial axis of the surface, is explicitly taken into account through a higher‐order variational formulation that enforces linear growth ...
Samuel Weidemaier, Christoph Norden‐Smoch, Martin Rumpf   +2 more
wiley   +1 more source