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Methods allowing the synthesis of realistic cell shapes could help generate training data sets to improve cell tracking and segmentation in biomedical images. Deep generative models for cell shape synthesis require a light-weight and…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 David Wiesner , Julian Suk , Sven Dummer , David Svoboda , Jelmer M. Wolterink

The propagation of detonation waves in reactive media bounded by an inert, compressible layer is examined via computational simulations in two different geometries, axisymmetric cylinders and two dimensional, planar slabs. For simplicity,…

Fluid Dynamics · Physics 2015-04-16 Jianling Li , XiaoCheng Mi , Andrew J. Higgins

This study investigates the propagation of detonations along a layered configuration where a reactive gas is weakly confined by a hotter inert layer. CFD simulations are performed using a single-step, non-Arrhenius reaction model designed…

Fluid Dynamics · Physics 2026-03-27 Youssef K. Wahba , XiaoCheng Mi , Charles B. Kiyanda , Andrew J. Higgins

Patterns of different symmetries may arise after solution to reaction-diffusion equations. Hexagonal arrays, layers and their perturbations are observed in different models after numerical solution to the corresponding initial-boundary…

Soft Condensed Matter · Physics 2015-09-10 Vladimir Mityushev

It is a popular hypothesis in neuroscience that ganglion cells in the retina are activated by selectively detecting visual features in an observed scene. While ganglion cell firings can be predicted via data-trained deep neural nets, the…

Machine Learning · Computer Science 2024-01-04 Yasaman Parhizkar , Gene Cheung , Andrew W. Eckford

Learning representations of molecular structures using deep learning is a fundamental problem in molecular property prediction tasks. Molecules inherently exist in the real world as three-dimensional structures; furthermore, they are not…

Machine Learning · Computer Science 2024-01-22 Daiki Koge , Naoaki Ono , Shigehiko Kanaya

The dynamics of the particle-size distribution (PSD) of the polydispersed fuel is important for evaluation of the combustion process. In this paper we unfold the mystery of the dynamics represented by the PSD and gain new insight for the…

Soft Condensed Matter · Physics 2020-02-20 Shlomo Hareli , OPhir Nave , Vladimir Gol'dshtein

We propose a correspondence between certain multiband linear cellular automata - models of computation widely used in the description of physical phenomena - and endomorphisms of certain algebraic unipotent groups over finite fields. The…

Dynamical Systems · Mathematics 2024-04-22 Jakub Byszewski , Gunther Cornelissen

Two-dimensional (2D) mechanical models of confluent tissues have related the mechanical state of a monolayer of cells to the average perimeter length of the cell cross sections, predicting floppiness or rigidity of the material. For the…

Soft Condensed Matter · Physics 2025-01-30 Jairo M. Rojas , Mayisha Z. Nakib , Vivian W. Tang , William M. Brieher , Sascha Hilgenfeldt

The task of deducing three-dimensional molecular configurations from their two-dimensional graph representations holds paramount importance in the fields of computational chemistry and pharmaceutical development. The rapid advancement of…

Biomolecules · Quantitative Biology 2025-01-09 Bobin Yang , Jie Deng , Zhenghan Chen , Ruoxue Wu

The objective of this study is to determine the critical conditions for a detonation wave formation following a Mach reflection of two incident shocks. This problem is central to the propagation mechanism of cellular detonations, where such…

Fluid Dynamics · Physics 2023-12-11 Farzane Zangene , Matei Radulescu

Diffusion generative models have emerged as a powerful framework for addressing problems in structural biology and structure-based drug design. These models operate directly on 3D molecular structures. Due to the unfavorable scaling of…

Biomolecules · Quantitative Biology 2024-05-10 Ian Dunn , David Ryan Koes

Data-driven cell tracking and segmentation methods in biomedical imaging require diverse and information-rich training data. In cases where the number of training samples is limited, synthetic computer-generated data sets can be used to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 David Wiesner , Julian Suk , Sven Dummer , Tereza Nečasová , Vladimír Ulman , David Svoboda , Jelmer M. Wolterink

A subcell technique for calculation of optical properties of graphene with the finite-difference time-domain (FDTD) method is presented. The technique takes into account the surface conductivity of graphene which allows the correct…

Mesoscale and Nanoscale Physics · Physics 2017-02-01 Ilya Valuev , Sergei Belousov , Maria Bogdanova , Oleg Kotov , Yurii Lozovik

One of the most important and difficult parts of constructing a multidimensional numerical simulation of flame acceleration and deflagration-to-detonation transition (DDT) in a reacting flow is finding a reliable and affordable model of the…

Fluid Dynamics · Physics 2017-09-04 Carolyn R. Kaplan , Alp Ozgen , Elaine S. Oran

Generative models of graphs based on discrete Denoising Diffusion Probabilistic Models (DDPMs) offer a principled approach to molecular generation by systematically removing structural noise through iterative atom and bond adjustments.…

Machine Learning · Computer Science 2025-11-03 Matteo Ninniri , Marco Podda , Davide Bacciu

The space-time adaptive ADER-DG finite element method with LST-DG predictor and a posteriori sub-cell ADER-WENO finite-volume limiting was used for simulation of multidimensional reacting flows with detonation waves. The presented numerical…

Fluid Dynamics · Physics 2024-09-23 I. S. Popov

In this fluid dynamic video we present simulations of converging two-dimensional detonation in a radially expanding supersonic flow of ideal reactive gas. The detonation is found to be unstable and leads to formation of characteristic…

Fluid Dynamics · Physics 2012-10-18 A. Kasimov , S. Korneev

Since the advent of graphene, two-dimensional (2D) materials become very attractive and there is growing interest to explore new 2D beyond graphene. Here, through density functional theory (DFT) calculations, we predict 2D wide-band-gap…

Mesoscale and Nanoscale Physics · Physics 2016-10-31 Xue-Jing Zhang , Bang-Gui Liu

We present a three-dimensional graph convolutional network (3DGCN), which predicts molecular properties and biochemical activities, based on 3D molecular graph. In the 3DGCN, graph convolution is unified with learning operations on the…

Machine Learning · Computer Science 2019-08-08 Hyeoncheol Cho , Insung S. Choi