Tootfinder

Hermeus' Prototyp Quarterhorse Mk 1 fliegt erstmals
Das US-Luftfahrtunternehmen Hermeus will Hyperschallflugzuge bauen. Der Prototyp Quarterhorse Mk 1 hat seinen Erstflug absolviert.
https://www.

HyperGaussians: High-Dimensional Gaussian Splatting for High-Fidelity Animatable Face Avatars
Gent Serifi, Marcel C. B\"uhler
https://arxiv.org/abs/2507.02803

HyperGaussians: High-Dimensional Gaussian Splatting for High-Fidelity Animatable Face Avatars
We introduce HyperGaussians, a novel extension of 3D Gaussian Splatting for high-quality animatable face avatars. Creating such detailed face avatars from videos is a challenging problem and has numerous applications in augmented and virtual reality. While tremendous successes have been achieved for static faces, animatable avatars from monocular videos still fall in the uncanny valley. The de facto standard, 3D Gaussian Splatting (3DGS), represents a face through a collection of 3D Gaussian pr…

This https://arxiv.org/abs/2505.05702 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Hypergraph Neural Sheaf Diffusion: A Symmetric Simplicial Set Framework for Higher-Order Learning
The absence of intrinsic adjacency relations and orientation systems in hypergraphs creates fundamental challenges for constructing sheaf Laplacians of arbitrary degrees. We resolve these limitations through symmetric simplicial sets derived directly from hypergraphs, which encode all possible oriented subrelations within each hyperedge as ordered tuples. This construction canonically defines adjacency via facet maps while inherently preserving hyperedge provenance. We establish that the normal…

Downregulation of aquaporin 3 promotes hyperosmolarity-induced apoptosis of nucleus pulposus cells through PI3K/Akt/mTOR pathway suppression
Yuan Sang, Huiqing Zhao, Jiajun Wu, Ting Zhang, Wenbin Xu, Hui Yao, Kaihua Liu, Chang Liu, Junbin Zhang, Ping Li, Depeng Wu, Yichun Xu, Jianying Zhang, Gang Hou
https://arxiv.org/abs/2507.0…

Downregulation of aquaporin 3 promotes hyperosmolarity-induced apoptosis of nucleus pulposus cells through PI3K/Akt/mTOR pathway suppression
Hyperosmolarity is a key contributor to nucleus pulposus cell (NPC) apoptosis during intervertebral disc degeneration (IVDD). Aquaporin 3 (AQP3), a membrane channel protein, regulates cellular osmotic balance by transporting water and osmolytes. Although AQP3 downregulation is associated with disc degeneration, its role in apoptosis under hyperosmotic conditions remains unclear. Here, we demonstrate that hyperosmolarity induces AQP3 depletion, suppresses the PI3K/AKT/mTOR signaling pathway, and…

The ordering of hypertrees and unicyclic hypergraphs by the traces of $\mathcal{A}_{\alpha}$-tensor
Jueru Liu, Lizhu Sun, Changjiang Bu
https://arxiv.org/abs/2507.02650

The ordering of hypertrees and unicyclic hypergraphs by the traces of $\mathcal{A}_α$-tensor
For a real number $α\in[0,1]$ and a $k$-uniform hypergraph $\mathcal{H}$, $\mathcal{A}_α(\mathcal{H})=α\mathcal{D}(\mathcal{H})+(1-α)\mathcal{A}(\mathcal{H})$ is called the $\mathcal{A}_α$-tensor of $\mathcal{H}$, where $\mathcal{D}(\mathcal{H})$ and $\mathcal{A}(\mathcal{H})$ are the degree tensor and adjacency tensor of $\mathcal{H}$, respectively. The sum of the $d$-th powers of all eigenvalues of $\mathcal{A}_α(\mathcal{H})$ is called the $d$-th order $\mathcal{A}_α$-spectral moment …

Cohomology of hypersurfaces of weighted projective space and the intersection form on $H^2$
Anna-Maria Raukh
https://arxiv.org/abs/2506.04094 https://

Cohomology of hypersurfaces of weighted projective space and the intersection form on $H^2$
Given a hypersurface $i \colon X \hookrightarrow \widetilde{P}^n$ in a weighted projective space, we compute the intersection form on the second cohomology $H^2(X, \mathbb{Z})^{\otimes n-1} \to \mathbb{Z}$ for the purpose of identifying Fano manifolds obtained from smoothing singular Fanos. In the process, we describe the integer cohomology groups $H^k(X, \mathbb{Z})$ for $k

Predicting Flow-Induced Vibration in Isolated and Tandem Cylinders Using Hypergraph Neural Networks
Shayan Heydari, Rui Gao, Rajeev K Jaiman
https://arxiv.org/abs/2507.02242

Predicting Flow-Induced Vibration in Isolated and Tandem Cylinders Using Hypergraph Neural Networks
We present a finite element-inspired hypergraph neural network framework for predicting flow-induced vibrations in freely oscillating cylinders. The surrogate architecture transforms unstructured computational meshes into node-element hypergraphs that encode higher-order spatial relationships through element-based connectivity, preserving the geometric and topological structure of the underlying finite-element discretization. The temporal evolution of the fluid-structure interaction is modeled …

This https://arxiv.org/abs/2502.19030 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Sampling nodes and hyperedges via random walks on large hypergraphs
Hypergraphs provide a fundamental framework for representing complex systems involving interactions among three or more entities. As empirical hypergraphs grow in size, characterizing their structural properties becomes increasingly challenging due to computational complexity and, in some cases, restricted access to complete data, requiring efficient sampling methods. Random walks offer a practical approach to hypergraph sampling, as they rely solely on local neighborhood information from nodes…

Hypergraphs accumulate infinitely often
David Conlon, Bjarne Sch\"ulke
https://arxiv.org/abs/2506.03080 https://arxiv.org/pdf/25…

Hypergraphs accumulate infinitely often
We show that the set $Π^{(k)}$ of Turán densities of $k$-uniform hypergraphs has infinitely many accumulation points in $[0,1)$ for every $k \geq 3$. This extends an earlier result of ours showing that $Π^{(k)}$ has at least one such accumulation point.

Classification by Separating Hypersurfaces: An Entropic Approach
Argimiro Arratia, Mahmoud El Daou, Henryk Gzyl
https://arxiv.org/abs/2507.02732 https://…

Classification by Separating Hypersurfaces: An Entropic Approach
We consider the following classification problem: Given a population of individuals characterized by a set of attributes represented as a vector in ${\mathbb R}^N$, the goal is to find a hyperplane in ${\mathbb R}^N$ that separates two sets of points corresponding to two distinct classes. This problem, with a history dating back to the perceptron model, remains central to machine learning. In this paper we propose a novel approach by searching for a vector of parameters in a bounded $N$-dimensi…