Results 81 to 90 of about 508,394 (292)
Physics-constrained machine learning for reduced composition space chemical kinetics
Data-Centric EngineeringModeling detailed chemical kinetics is a primary challenge in combustion simulations. We present a novel framework to enforce physical constraints, specifically total mass and elemental conservation, during the reaction of ML models’ training for the ...
Anuj Kumar, Tarek Echekki
doaj +1 more source
Chemical Engineering Transactions, 2013 Batch reactors are widely used in the polymer industry, especially for multi-purpose processes where different types of polymers are produced on demand.
R. Ribeiro Santos +4 more
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On analysis of chemical reactions coupled gas flows in SOFCs [PDF]
, 2009 This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the ...
2nd Micro and Nano Flows Conference (MNF2009) +3 more
core
Parallel implementation of stochastic simulation for large-scale cellular processes [PDF]
, 2005 Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional ...
Burrage, K., Tian, T.
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Hyperosmotic stress induces PARP1‐mediated HPF1‐dependent mono(ADP‐ribosyl)ation
FEBS Letters, EarlyView.Sorbitol‐induced hyperosmotic stress rapidly induces reversible mono(ADP‐ribosyl)ation (MARylation) on PARP1 without the signs of genotoxic signaling. We show that PARP1 autoMARylation is HPF1 dependent and forms hydroxylamine‐resistant O‐glycosidic linkages.
Anna Georgina Kopasz +11 more
wiley +1 more source
Gene Expression and its Discontents: Developmental disorders as dysfunctions of epigenetic cognition [PDF]
, 2009 Systems biology presently suffers the same mereological and sufficiency fallacies that haunt neural network models of high order cognition. Shifting perspective from the massively parallel space of gene matrix interactions to the grammar/syntax of the ...
Wallace, Rodrick
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Reduction of dynamical biochemical reaction networks in computational biology [PDF]
, 2012 Biochemical networks are used in computational biology, to model the static and dynamical details of systems involved in cell signaling, metabolism, and regulation of gene expression.
Gorban, Alexander N. +3 more
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FEBS Letters, EarlyView.Mitochondrial remodeling shapes neural and glial lineage progression by matching metabolic supply with demand. Elevated OXPHOS supports differentiation and myelin formation, while myelin compaction lowers mitochondrial dependence, revealing mitochondria as key drivers of developmental energy adaptation.
Sahitya Ranjan Biswas +3 more
wiley +1 more source
Extreme learning with chemical reaction optimization for stock volatility prediction
Financial Innovation, 2020 Extreme learning machine (ELM) allows for fast learning and better generalization performance than conventional gradient-based learning. However, the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden ...
Sarat Chandra Nayak, Bijan Bihari Misra
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ABC(SMC)$$^2$$: Simultaneous Inference and Model Checking of Chemical Reaction Networks [PDF]
, 2020 We present an approach that simultaneously infers model parameters while statistically verifying properties of interest to chemical reaction networks, which we observe through data and we model as parametrised continuous-time Markov Chains. The new approach simultaneously integrates learning models from data, done by likelihood-free Bayesian inference,
Molyneux, GW, Abate, A
openaire +2 more sources