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Comprehensive and confident identifications of metabolites and other chemicals in complex samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent advances,…

This paper introduces a novel constraint adaptive filtering algorithm based on a relative logarithmic cost function which is termed as Constrained Least Mean Logarithmic Square (CLMLS). The proposed CLMLS algorithm elegantly adjusts the…

Systems and Control · Computer Science 2018-01-22 Vinay Chakravarthi Gogineni , Subrahmanyam Mula

The behavior of some stochastic chemical reaction networks is largely unaffected by slight inaccuracies in reaction rates. We formalize the robustness of state probabilities to reaction rate deviations, and describe a formal connection…

Computational Complexity · Computer Science 2009-01-28 David Soloveichik

The metabolic state of a cell, comprising fluxes, metabolite concentrations and enzyme levels, is shaped by a compromise between metabolic benefit and enzyme cost. This hypothesis and its consequences can be studied by computational models…

Molecular Networks · Quantitative Biology 2022-10-05 Wolfram Liebermeister

In the modeling of complex biological systems, the use of power-law models (such as S-systems and GMA systems) often provides a remarkable accuracy over several orders of magnitude in concentrations, an unusually broad range not fully…

Biological Physics · Physics 2019-11-22 Benito Hernández-Bermejo

Despite their topological complexity almost all functional properties of metabolic networks can be derived from steady-state dynamics. Indeed, many theoretical investigations (like flux-balance analysis) rely on extracting function from…

Molecular Networks · Quantitative Biology 2009-11-13 Carsten Marr , Mark Mueller-Linow , Marc-Thorsten Huett

Bayesian multinomial logistic-normal (MLN) models are popular for the analysis of sequence count data (e.g., microbiome or gene expression data) due to their ability to model multivariate count data with complex covariance structure.…

We present the Distributed and Localized Model Predictive Control (DLMPC) algorithm for large-scale structured linear systems, wherein only local state and model information needs to be exchanged between subsystems for the computation and…

Optimization and Control · Mathematics 2020-09-14 Carmen Amo Alonso , Nikolai Matni

As an essential attribute of organic compounds, polarity has a profound influence on many molecular properties such as solubility and phase transition temperature. Thin layer chromatography (TLC) represents a commonly used technique for…

Real-world (bio)chemical processes often exhibit stochastic dynamics with non-trivial correlations and state-dependent fluctuations. Model predictive control (MPC) often must consider these fluctuations to achieve reliable performance.…

Machine Learning · Computer Science 2025-12-16 Eike Cramer

The high penetration of distributed energy resources, resulting in backfeed of power at the transmission and distribution interface, is causing conventional underfrequency load shedding (UFLS) schemes to become nonconforming. Adaptive…

Systems and Control · Electrical Eng. & Systems 2026-03-20 Muhammad Hamza Ali , Amritanshu Pandey

In the wake of the intense effort made for the experimental CILEX project, numerical simulation cam- paigns have been carried out in order to finalize the design of the facility and to identify optimal laser and plasma parameters. These…

Computational Physics · Physics 2016-04-20 Arnaud Beck , Jacob Trier Frederiksen , Julien Dérouillat

Modeling the dynamical flows on networks of biomolecular machines often entails computing node populations and edge fluxes with Master Equations and correlating machine performance with entropy production. But this alone is not sufficient…

Statistical Mechanics · Physics 2026-05-12 Ying-Jen Yang , Ken A. Dill

Learning to integrate non-linear equations from highly resolved direct numerical simulations (DNSs) has seen recent interest for reducing the computational load for fluid simulations. Here, we focus on determining a flux-limiter for shock…

Fluid Dynamics · Physics 2023-03-31 Nga Nguyen-Fotiadis , Michael McKerns , Andrew Sornborger

We develop a novel data-driven framework as an alternative to dynamic flux balance analysis, bypassing the demand for deep domain knowledge and manual efforts to formulate the optimization problem. The proposed framework is end-to-end,…

Machine Learning · Computer Science 2024-10-21 Santanu Rathod , Pietro Lio , Xiao Zhang

This paper presents a load balancing strategy for reaction rate evaluation and chemistry integration in reacting flow simulations. The large disparity in scales during combustion introduces stiffness in the numerical integration of the PDEs…

In topology optimization of compliant mechanisms, the specific placement of boundary conditions strongly affects the resulting material distribution and performance of the design. At the same time, the most effective locations of the loads…

Computational Engineering, Finance, and Science · Computer Science 2025-02-05 Lee R. Alacoque , Anurag Bhattacharyya , Kai A. James

We introduce a rigorous method to microscopically compute the observables which characterize the thermodynamics and kinetics of rare macromolecular transitions for which it is possible to identify a priori a slow reaction coordinate. In…

Biomolecules · Quantitative Biology 2015-06-05 P. Faccioli , F. Pederiva

This paper proposes an optimization-based task and motion planning framework, named "Logic Network Flow", that integrates temporal logic specifications into mixed-integer programs for efficient robot planning. Inspired by the…

Robotics · Computer Science 2025-09-30 Xuan Lin , Jiming Ren , Yandong Luo , Weijun Xie , Ye Zhao

Chemical kinetic models are an essential component in the development and optimisation of combustion devices through their coupling to multi-dimensional simulations such as computational fluid dynamics (CFD). Low-dimensional kinetic models…

Chemical Physics · Physics 2023-06-21 Mark Kelly , Mark Fortune , Gilles Bourque , Stephen Dooley
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