Tootfinder

Parametric design and adaptive sizing of lattice structures for 3d additive manufacturing
Jorge Manuel Mercado-Colmenero, Daniel Diaz - Perete, Miguel Angel Rubio- Paramio, Cristina Martin-Donate
https://arxiv.org/abs/2507.18318

Parametric design and adaptive sizing of lattice structures for 3d additive manufacturing
The present research is developed into the realm of industrial design engineering and additive manufacturing by introducing a parametric design model and adaptive mechanical analysis for a new lattice structure, with a focus on 3D additive manufacturing of complex parts. Focusing on the land-scape of complex parts additive manufacturing, this research proposes geometric parameterization, mechanical adaptive sizing, and numerical validation of a novel lattice structure to optimize the final prin…

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing
Ramona Rubini, Siavash Khodakarami, Aniruddha Bora, George Em Karniadakis, Michele Dassisti
https://arxiv.org/abs/2509.20349

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing
Accurate time-series forecasting for complex physical systems is the backbone of modern industrial monitoring and control. While deep learning models excel at capturing complex dynamics, currently, their deployment is limited due to physical inconsistency and robustness, hence constraining their reliability in regulated environments. We introduce process-informed forecasting (PIF) models for temperature in pharmaceutical lyophilization. We investigate a wide range of models, from classical ones…

Manifestations of flow topology in a quantum driven-dissipative system
Kilian Seibold, Greta Villa, Javier del Pino, Oded Zilberberg
https://arxiv.org/abs/2508.16486 https://

Manifestations of flow topology in a quantum driven-dissipative system
In driven-dissipative bosonic systems, the interplay between coherent driving, inter-particle interactions and dissipation leads to a rich variety of non-equilibrium stationary states (NESS). In the semiclassical limit, the flow topology of phase-space dynamics governs the stability and structure of these dynamical phases. Consequently, topological transitions occur when the number of NESS, their chirality, or their connectivity changes, reflecting global reorganization in the system's dynamica…

A Lightweight Group Multiscale Bidirectional Interactive Network for Real-Time Steel Surface Defect Detection
Yong Zhang, Cunjian Chen, Qiang Gao, Yi Wang, Bin Fang
https://arxiv.org/abs/2508.16397

A Lightweight Group Multiscale Bidirectional Interactive Network for Real-Time Steel Surface Defect Detection
Real-time surface defect detection is critical for maintaining product quality and production efficiency in the steel manufacturing industry. Despite promising accuracy, existing deep learning methods often suffer from high computational complexity and slow inference speeds, which limit their deployment in resource-constrained industrial environments. Recent lightweight approaches adopt multibranch architectures based on depthwise separable convolution (DSConv) to capture multiscale contextual …

Projective Kolmogorov Arnold Neural Networks (P-KANs): Entropy-Driven Functional Space Discovery for Interpretable Machine Learning
Alastair Poole, Stig McArthur, Saravan Kumar
https://arxiv.org/abs/2509.20049

Projective Kolmogorov Arnold Neural Networks (P-KANs): Entropy-Driven Functional Space Discovery for Interpretable Machine Learning
Kolmogorov-Arnold Networks (KANs) relocate learnable nonlinearities from nodes to edges, demonstrating remarkable capabilities in scientific machine learning and interpretable modeling. However, current KAN implementations suffer from fundamental inefficiencies due to redundancy in high-dimensional spline parameter spaces, where numerous distinct parameterisations yield functionally equivalent behaviors. This redundancy manifests as a "nuisance space" in the model's Jacobian, leading to suscept…

Temperature-Resilient Reconfigurable PUF with Dual-Pulse Modulation based on SOT-MRAM Chip
Min Wang, Chuanpeng Jiang, Zhaohao Wang, Zhengyi Hou, Zhongkui Zhang, Yuanfu Zhao, Hongxi Liu, Weisheng Zhao
https://arxiv.org/abs/2508.16405

Temperature-Resilient Reconfigurable PUF with Dual-Pulse Modulation based on SOT-MRAM Chip
In the Internet of Things (IoT) era, hardware-based security solutions have become an emerging choice for enhancing end-terminal information security. As one of the hardware technologies, physical unclonable functions (PUFs) utilize the inherent variations in the manufacturing process to generate cryptographic keys. Reconfigurable PUFs (rPUFs), characterized by updating cryptographic keys, offer enhanced security ability for protecting massive amounts of data in dynamic operational scenarios. T…

Lang2Morph: Language-Driven Morphological Design of Robotic Hands
Yanyuan Qiao, Kieran Gilday, Yutong Xie, Josie Hughes
https://arxiv.org/abs/2509.18937 https://

Deterministic Frequency--Domain Inference of Network Topology and Hidden Components via Structure--Behavior Scaling
Xiaoxiao Liang, Tianlong Fan, Linyuan L\"u
https://arxiv.org/abs/2509.19857

Deterministic Frequency--Domain Inference of Network Topology and Hidden Components via Structure--Behavior Scaling
Hidden interactions and components in complex systems-ranging from covert actors in terrorist networks to unobserved brain regions and molecular regulators-often manifest only through indirect behavioral signals. Inferring the underlying network structure from such partial observations remains a fundamental challenge, particularly under nonlinear dynamics. We uncover a robust linear relationship between the spectral strength of a node's behavioral time series under evolutionary game dynamics an…

Probing metric fluctuations with the spin of a particle: a quantum simulation with bimodal optical cavities
Jiannis K. Pachos, Patricio Salgado-Rebolledo, Martine Schut
https://arxiv.org/abs/2507.18351

Probing metric fluctuations with the spin of a particle: a quantum simulation with bimodal optical cavities
Exploring potential empirical manifestations of quantum gravity is a challenging pursuit. In this study, we utilise a lattice representation of a (2+1)D massive gravity toy model interacting with Dirac fermions that can support specific spacetime fluctuations. We focus on the evolution of the fermion's spin due to its coupling to spacetime fluctuations. To monitor their dynamics a minimal model is required that comprises two bosonic modes describing spacetime geometry fluctuations coupled with …

Vision-Free Retrieval: Rethinking Multimodal Search with Textual Scene Descriptions
Ioanna Ntinou, Alexandros Xenos, Yassine Ouali, Adrian Bulat, Georgios Tzimiropoulos
https://arxiv.org/abs/2509.19203

Vision-Free Retrieval: Rethinking Multimodal Search with Textual Scene Descriptions
Contrastively-trained Vision-Language Models (VLMs), such as CLIP, have become the standard approach for learning discriminative vision-language representations. However, these models often exhibit shallow language understanding, manifesting bag-of-words behaviour. These limitations are reinforced by their dual-encoder design, which induces a modality gap. Additionally, the reliance on vast web-collected data corpora for training makes the process computationally expensive and introduces signif…