ICM Articles

Displaying 1 - 5 of 82 records

Vistla: identifying influence paths with information theory.
(Oxford University Press, 2025) Kursa, Miron B.; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw
It is a challenging task to decipher the mechanisms of a complex system from observational data, especially in biology, where systems are sophisticated, measurements coarse, and multi-modality common. The typical approaches of inferring a network of relationships between a system's components struggle with the quality and feasibility of estimation, as well as with the interpretability of the results they yield. Said issues can be avoided, however, when dealing with a simpler problem of tracking only the influence paths, defined as circuits relying on the information of an experimental perturbation as it spreads through the system. Such an approach can be formalized with information theory and leads to a relatively streamlined, interpretable output, in contrast to the incomprehensibly dense 'haystack' networks produced by typical tools.Following this idea, the paper introduces Vistla, a novel method built around tri-variate mutual information and data processing inequality, combined with a higher-order generalization of the widest path problem. Vistla can be used standalone, in a machine learning pipeline to aid interpretability, or as a tool for mediation analysis; the paper demonstrates its efficiency both in synthetic and real-world problems.The R package implementing the method is available at https://gitlab.com/mbq/vistla, as well as on CRAN.
Forecasting SARS-CoV-2 epidemic dynamic in Poland with the pDyn agent-based model
(Elsevier B.V., 2024) Niedzielewski, Karol; Bartczuk, Rafał P.; Bielczyk, Natalia; Bogucki, Dominik; Dreger, Filip; Dudziuk, Grzegorz; Górski, Łukasz; Gruziel-Słomka, Magdalena; Haman, Jerzy; Kaczorek, Artur; Kisielewski, Jan; Krupa, Bartosz; Moszyński, Antoni; Nowosielski, Jędrzej M.; Radwan, Maciej; Semeniuk, Marcin; Tymoszuk, Urszula; Zieliński, Jakub; Rakowski, Franciszek; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; Scientific Research Division, Children’s Memorial Health Institute, Warsaw, Poland; Ontology of Value, Nijmegen, Netherlands; Faculty of Physics, University of Bialystok, Białystok, Poland; Division of Psychiatry, University College London, London, United Kingdom
We employ pDyn (derived from “pandemics dynamics”), an agent-based epidemiological model, to forecast the fourth wave of the SARS-CoV-2 epidemic, primarily driven by the Delta variant, in Polish society. The model captures spatiotemporal dynamics of the epidemic spread, predicting disease-related states based on pathogen properties and behavioral factors. We assess pDyn’s validity, encompassing pathogen variant succession, immunization level, and the proportion of vaccinated among confirmed cases. We evaluate its predictive capacity for pandemic dynamics, including wave peak timing, magnitude, and duration for confirmed cases, hospitalizations, ICU admissions, and deaths, nationally and regionally in Poland. Validation involves comparing pDyn’s estimates with real-world data (excluding data used for calibration) to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time. To assess the accuracy of pDyn’s predictions, we compared simulation results with real-world data acquired after the simulation date. The findings affirm pDyn’s accuracy in forecasting and enhancing our understanding of epidemic mechanisms
OpenFOAM solver for thermal and chemical conversion in porous media
(Elsevier, 2022) Żuk, Paweł Jan; Tużnik, Bartosz; Rymarz, Tadeusz; Kwiatkowski, Kamil; Dudyński, Marek; Galeazzo, Flavio C.C.; Krieger Filho, Guenther C.; Institute of Physical Chemistry, Polish Academy of Sciences; Department of Physics, Lancaster University, Lancaster, United Kingdom; Faculty of Mathematics, Informatics and Mechanics, University of Warsaw; Modern Technologies and Filtration, Warsaw, Poland; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; Department of Mechanical Engineering, University of São Paulo (USP), Brazil; High-Performance Computing Center Stuttgart (HLRS), University of Stuttgart, Stuttgart, Germany
We present the porousGasificationFoam solver and libraries, developed in the open-source C++ code OpenFOAM, for the comprehensive simulation of the thermochemical conversion in porous media. The code porousGasificationFoam integrates gas flow through a porous media with the models of heterogeneous (drying, gasification, pyrolysis, solid combustion, precipitation) and homogeneous (gas combustion) chemical reactions. Inside porous media transport equations are formulated applying the spatial averaging methodology. The mass and enthalpy transfer between solid and gas phases is suitable for systems out of the thermal equilibrium. The convection and radiation modes of the heat transfer are included for gas and solid phases, and the immersed boundary technique is applied for the porous media inside the computational domain. We validate the elements of the model against a set of experimental and theoretical results. Amongst them, Thermogravimetric Analysis experiments of thermal conversions of two wooden particles: one of millimeter size the other of centimeter size. Simulations feature reaction schemes and physical parameters established in the literature. We show the influence of the porous media size on the gasification process. The millimeter particle remains uniform, while for the centimeter setup, the pyrolysis front is reproduced. The spatial patterns in physical conditions modify the course of chemical reactions and influence media composition and structure evolution. Another important example is a gasifier where we obtain a self-sustaining front propagation because of an exothermic heterogeneous reaction.
Spatio-temporal mechanisms of consolidation, recall and reconsolidation in reward-related memory trace
(Cold Spring Harbor Laboratory, 2023) Hamed, Adam; Kursa, Miron Bartosz; Karwicka, Wiktoria; Piwoński, Krzysztof Piotr; Falińska, Monika; Danielewski, Konrad; Rejmak-Kozicka, Emilia; Włodkowska, Urszula; Kubik, Stepan; Czajkowski, Rafał; Laboratory of Spatial Memory, Nencki Institute of Experimental Biology, Polish Academy of Sciences; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; Laboratory of Emotions Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences; BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences. 5 Institute of Physiology, Academy of Sciences of the Czech Republic
The formation of memories is a complex, multi-scale phenomenon, especially when it involves integration of information from various brain systems. We have investigated the differences between a novel and consolidated association of spatial cues and amphetamine administration, using an in-situ hybridisation method to track the short-term dynamics during the recall testing. We have found that remote recall group involves smaller, but more consolidated groups of neurons, which is consistent with their specialisation. By employing machine learning analysis, we have shown this pattern is especially pronounced in the VTA; furthermore, we also uncovered significant activity patterns in retrosplenial and prefrontal cortices, as well as in the DG and CA3 subfields of the hippocampus. The behavioural propensity towards the associated localisation appears to be driven by the nucleus accumbens, however, further modulated by a trio of the amygdala, VTA and hippocampus, as the trained association is confronted with test experience. These results show that memory mechanisms must be modelled considering individual differences in motivation, as well as covering dynamics of the process.
Convexity and Monotonicity in Language Coordination: Simulating the Emergence of Semantic Universals in Populations of Cognitive Agents
(Springer Nature, 2023) Gierasimczuk, Nina; Kalociński, Dariusz; Rakowski, Franciszek; Uszyński, Jakub; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark; Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; National Information Processing Institute, Warsaw, Poland
Natural languages vary in their quantity expressions, but the variation seems to be constrained by general properties, so-called universals. Their explanations have been sought among constraints of human cognition, communication, complexity, and pragmatics. In this article, we apply a state-of-the-art language coordination model to the semantic domain of quantities to examine whether two quantity universals—monotonicity and convexity—arise as a result of coordination. Assuming precise number perception by the agents, we evolve communicatively usable quantity terminologies in two separate conditions: a numeric-based condition in which agents communicate about a number of objects and a quotient-based condition in which agents communicate about the proportions. We find out that both universals take off in all conditions but only convexity almost entirely dominates the emergent languages. Additionally, we examine whether the perceptual constraints of the agents can contribute to the further development of universals. We compare the degrees of convexity and monotonicity of languages evolving in populations of agents with precise and approximate number sense. The results suggest that approximate number sense significantly reinforces monotonicity and leads to further enhancement of convexity. Last but not least, we show that the properties of the evolved quantifiers match certain invariance properties from generalized quantifier theory.

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