Results 61 to 70 of about 338,472 (315)
The directions of perspective research in the field of analysis and modeling of the dynamics of time series of processes in complex systems with the presence of the human factor are described. The dynamics of processes in such systems is described by nonstationary time series. Predicting the evolution of such systems is of great importance for managing
E. G. Andrianova +4 more
openaire +3 more sources
Structural biology of ferritin nanocages
Ferritin is a conserved iron‐storage protein that sequesters iron as a ferric mineral core within a nanocage, protecting cells from oxidative damage and maintaining iron homeostasis. This review discusses ferritin biology, structure, and function, and highlights recent cryo‐EM studies revealing mechanisms of ferritinophagy, cellular iron uptake, and ...
Eloise Mastrangelo, Flavio Di Pisa
wiley +1 more source
Insights on Streamflow Predictability Across Scales Using Horizontal Visibility Graph Based Networks
Streamflow is a dynamical process that integrates water movement in space and time within basin boundaries. The authors characterize the dynamics associated with streamflow time-series data from 64 U.S.
Ganesh R. Ghimire +4 more
doaj +1 more source
Against the Flow of Time with Multi-Output Models
Recent work has paid close attention to the first principle of Granger causality, according to which cause precedes effect. In this context, the question may arise whether the detected direction of causality also reverses after the time reversal of ...
Jakubík Jozef +3 more
doaj +1 more source
Estimation of Power System Inertia Using Nonlinear Koopman Modes
We report a new approach to estimating power system inertia directly from time-series data on power system dynamics. The approach is based on the so-called Koopman Mode Decomposition (KMD) of such dynamic data, which is a nonlinear generalization of ...
Hamasaki, Ryo +2 more
core +1 more source
Training Echo State Networks with Regularization through Dimensionality Reduction [PDF]
In this paper we introduce a new framework to train an Echo State Network to predict real valued time-series. The method consists in projecting the output of the internal layer of the network on a space with lower dimensionality, before training the ...
Bianchi, Filippo Maria +2 more
core +2 more sources
Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
Simplicial Multivalued Maps and the Witness Complex for Dynamical Analysis of Time Series [PDF]
Topology based analysis of time-series data from dynamical systems is powerful: it potentially allows for computer-based proofs of the existence of various classes of regular and chaotic invariant sets for high-dimensional dynamics.
Alexander, Zachary +3 more
core
Dual targeting of RET and SRC synergizes in RET fusion‐positive cancer cells
Despite the strong activity of selective RET tyrosine kinase inhibitors (TKIs), resistance of RET fusion‐positive (RET+) lung cancer and thyroid cancer frequently occurs and is mainly driven by RET‐independent bypass mechanisms. Son et al. show that SRC TKIs significantly inhibit PAK and AKT survival signaling and enhance the efficacy of RET TKIs in ...
Juhyeon Son +13 more
wiley +1 more source
Power-laws in recurrence networks from dynamical systems
Recurrence networks are a novel tool of nonlinear time series analysis allowing the characterisation of higher-order geometric properties of complex dynamical systems based on recurrences in phase space, which are a fundamental concept in classical ...
Donges, J. F. +8 more
core +1 more source

