While physics-based modeling of electrosurgical procedures is essential for most laparoscopic simulation systems, we present such a system for the first time in this paper. We have implemented a physics-based model of electrosurgery to control the temperature distribution on the tissue as a function of time. Then, we evaluate the algorithm within a complete graphics-haptics-physics-based system.
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J Cheminform
December 2024
Department of Computer Science, Aalto University, 02150, Espoo, Finland.
Machine learning (ML) systems have enabled the modelling of quantitative structure-property relationships (QSPR) and structure-activity relationships (QSAR) using existing experimental data to predict target properties for new molecules. These property predictors hold significant potential in accelerating drug discovery by guiding generative artificial intelligence (AI) agents to explore desired chemical spaces. However, they often struggle to generalize due to the limited scope of the training data.
View Article and Find Full Text PDFNpj Imaging
December 2024
Data Sciences Platform (DSP), Broad Institute of MIT and Harvard, Cambridge, MA USA.
Voltage imaging is a powerful technique for studying neuronal activity, but its effectiveness is often constrained by low signal-to-noise ratios (SNR). Traditional denoising methods, such as matrix factorization, impose rigid assumptions about noise and signal structures, while existing deep learning approaches fail to fully capture the rapid dynamics and complex dependencies inherent in voltage imaging data. Here, we introduce CellMincer, a novel self-supervised deep learning method specifically developed for denoising voltage imaging datasets.
View Article and Find Full Text PDFPhys Rev E
October 2024
Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA.
Biological sequences do not come at random. Instead, they appear with particular frequencies that reflect properties of the associated system or phenomenon. Knowing how biological sequences are distributed in sequence space is thus a natural first step toward understanding the underlying mechanisms.
View Article and Find Full Text PDFPNAS Nexus
November 2024
Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, Garching bei München, 85748 Germany.
The use of public transport systems is a striking example of complex human behavior. Modeling, planning, and managing public transport is a major future challenge considering the drastically accelerated population growth in many urban areas. The desire to design sustainable cities that can cope with a dynamically increasing demand requires models for transport networks since we are not able to perform real-life experiments before constructing additional infrastructure.
View Article and Find Full Text PDFSci Robot
November 2024
IRIDIA, Université Libre de Bruxelles, Brussels, Belgium.
We present the self-organizing nervous system (SoNS), a robot swarm architecture based on self-organized hierarchy. The SoNS approach enables robots to autonomously establish, maintain, and reconfigure dynamic multilevel system architectures. For example, a robot swarm consisting of independent robots could transform into a single -robot SoNS and then into several independent smaller SoNSs, where each SoNS uses a temporary and dynamic hierarchy.
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