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📰 "Incremental Model Order Reduction of Smoothed-Particle Hydrodynamic Simulations"
arxiv.org/abs/2501.10748 #Physics.Flu-Dyn #Matrix #Force

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arXiv.orgIncremental Model Order Reduction of Smoothed-Particle Hydrodynamic SimulationsEngineering simulations are usually based on complex, grid-based, or mesh-free methods for solving partial differential equations. The results of these methods cover large fields of physical quantities at very many discrete spatial locations and temporal points. Efficient compression methods can be helpful for processing and reusing such large amounts of data. A compression technique is attractive if it causes only a small additional effort and the loss of information with strong compression is low. The paper presents the development of an incremental Singular Value Decomposition (SVD) strategy for compressing time-dependent particle simulation results. The approach is based on an algorithm that was previously developed for grid-based, regular snapshot data matrices. It is further developed here to process highly irregular data matrices generated by particle simulation methods during simulation. Various aspects important for information loss, computational effort and storage requirements are discussed, and corresponding solution techniques are investigated. These include the development of an adaptive rank truncation approach, the assessment of imputation strategies to close snapshot matrix gaps caused by temporarily inactive particles, a suggestion for sequencing the data history into temporal windows as well as bundling the SVD updates. The simulation-accompanying method is embedded in a parallel, industrialized Smoothed-Particle Hydrodynamics software and applied to several 2D and 3D test cases. The proposed approach reduces the memory requirement by about 90% and increases the computational effort by about 10%, while preserving the required accuracy. For the final application of a water turbine, the temporal evolution of the force and torque values for the compressed and simulated data is in excellent agreement.

📰 "Biophysical and biochemical signatures of pancreatic stellate cell activation: insights into mechano-metabolic signalling from atomic force microscopy and Raman spectroscopy"
doi.org/doi:10.1186/s12964-025
pubmed.ncbi.nlm.nih.gov/407599
#Mechanical #Force #Cell

BioMed CentralBiophysical and biochemical signatures of pancreatic stellate cell activation: insights into mechano-metabolic signalling from atomic force microscopy and Raman spectroscopy - Cell Communication and SignalingBackground Pancreatic fibrosis is a key pathological feature of chronic pancreatitis and pancreatic cancer, driven by the persistent activation of pancreatic stellate cells. These cells, normally quiescent, undergo profound phenotypic changes in response to environmental cues, yet the interplay between mechanical forces and metabolic reprogramming during this transition remains poorly understood. As the stromal microenvironment actively communicates with epithelial and vascular compartments, understanding this mechano-metabolic signalling axis is critical for uncovering novel mechanisms of tissue remodelling. Methods To investigate the biomechanical and biochemical alterations during stellate cell activation, we employed atomic force microscopy and Raman spectroscopy to measure changes in cell stiffness, morphology, and molecular composition. These data were complemented by transcriptomic analyses to evaluate gene expression profiles related to lipid metabolism and autophagy. Quantitative statistical tests, including ANOVA and Kruskal-Wallis tests with appropriate post hoc corrections, were applied. Results Activation of human pancreatic stellate cells led to progressive cytoskeletal remodelling, increased cellular stiffness, and a flattened morphology. Raman spectroscopy revealed an expansion of the cytoplasmic area, changes in nucleic acid signal, and significant increases in lipid content, particularly in unsaturated lipids and triacylglycerols. Gene expression analysis demonstrated upregulation of lipid elongation and desaturation pathways, along with enhanced autophagy, suggesting a coordinated metabolic adaptation. These changes support the myofibroblast-like phenotype and may influence intercellular signalling by altering extracellular matrix composition, mechanical tension, and the release of signalling molecules that affect the surrounding microenvironment. Conclusions Our findings reveal that pancreatic stellate cell activation involves a tightly coupled shift in mechanical and metabolic states, highlighting an integrated signalling process that may modulate stromal–vascular and stromal–epithelial communication. This mechano-metabolic axis represents a potential therapeutic target in fibrotic and neoplastic pancreatic diseases, where aberrant stromal signalling contributes to disease progression.

📰 "Inferring biological processes with intrinsic noise from cross-sectional data"
arxiv.org/abs/2410.07501 #Physics.Bio-Ph #Q-Bio.Qm #Cs.Lg #Force #Cell

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arXiv.orgInferring biological processes with intrinsic noise from cross-sectional dataInferring dynamical models from data continues to be a significant challenge in computational biology, especially given the stochastic nature of many biological processes. We explore a common scenario in omics, where statistically independent cross-sectional samples are available at a few time points, and the goal is to infer the underlying diffusion process that generated the data. Existing inference approaches often simplify or ignore noise intrinsic to the system, compromising accuracy for the sake of optimization ease. We circumvent this compromise by inferring the phase-space probability flow that shares the same time-dependent marginal distributions as the underlying stochastic process. Our approach, probability flow inference (PFI), disentangles force from intrinsic stochasticity while retaining the algorithmic ease of ODE inference. Analytically, we prove that for Ornstein-Uhlenbeck processes the regularized PFI formalism yields a unique solution in the limit of well-sampled distributions. In practical applications, we show that PFI enables accurate parameter and force estimation in high-dimensional stochastic reaction networks, and that it allows inference of cell differentiation dynamics with molecular noise, outperforming state-of-the-art approaches.

📰 "Zone-sectored organic crystals with spatially resolved exciton dynamics"
arxiv.org/abs/2507.21294 #Cond-Mat.Mtrl-Sci #Physics.Optics #Dynamics #Force #Cell

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arXiv.orgZone-sectored organic crystals with spatially resolved exciton dynamicsAmong the organic semiconductors, rubrene stands out in terms of hole mobility, luminescence yield and exciton migration distance. A novel type of rubrene microcrystal is prepared in the orthorhombic phase, exhibiting zone-sectored tabular domains with distinct photoluminescence (PL) characteristics. These sectors exhibit distinct PL spectra and time-evolution, arising from differences in the in-plane orientation of the orthorhombic unit cell relative to the crystal surface. A combination of polarised optical microscopy, fluorescence lifetime imaging microscopy (FLIM), and atomic force microscopy (AFM) is used to characterise the samples in terms of crystal orientation, fluorescence lifetime, and photoluminescence spectra. Spatially resolved PL spectroscopy reveals that the redshifted 650 nm emission band has polarisation along the transition dipole moment and is associated with high photon absorption due to the alignment of excitation polarisation and transition dipole moment and selectively localized within specific sectors of the crystal. The detected photon originates from direct emission of a geminate coherent triplet pair, or from its fusion. This band exhibits pure mono-exponential dynamics with 3.7 ns lifetime. The triplet fusion behaviour in the succeeding time regimes can be treated in the framework of power law scaling and random walk. The emission kinetics are modelled using rate equations describing geminate and non-geminate exciton fusion processes, enabling a quantitative interpretation of the spatially resolved PL kinetics. These findings introduce a material-based strategy, opening novel routes for photonic applications and light harvesting.