Results 31 to 40 of about 14,640 (111)
This study explores the origins of life by linking prebiotic chemistry, the emergence of information‐carrying molecules such as RNA and proteins, and philosophical questions about consciousness. The study emphasizes the role of molecular evolution in the Central Dogma and provides insights into the chemical origins of biology and the basis of life's ...
Harald Schwalbe +5 more
wiley +2 more sources
Tackling nonlinear price impact with linear strategies
Abstract Empirical studies in various contexts find that the price impact of large trades approximately follows a power law with exponent between 0.4 and 0.7. Yet, tractable formulas for the portfolios that trade off predictive trading signals, risk, and trading costs in an optimal manner are only available for quadratic costs corresponding to linear ...
Xavier Brokmann +3 more
wiley +1 more source
Isomorphic extensions and applications
If $\pi:(X,T)\to(Z,S)$ is a topological factor map between uniquely ergodic topological dynamical systems, then $(X,T)$ is called an isomorphic extension of $(Z,S)$ if $\pi$ is also a measure-theoretic isomorphism.
Downarowicz, Tomasz, Glasner, Eli
core
Large‐Dimensional Cointegrated Threshold Factor Models: The Global Term Structure of Interest Rates
ABSTRACT In this paper we extend the two‐level factor model to account for cointegration between group‐specific factors in large datasets. We propose two nonlinear specifications: (i) a threshold vector error correction model (VECM) that allows for asymmetric adjustment across regimes; and (ii) a band VECM that captures state‐dependent adjustment which
Daniel Abreu, Paulo M. M. Rodrigues
wiley +1 more source
Likelihood Estimation for Stochastic Differential Equations with Mixed Effects
ABSTRACT Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. When time series are observed for several experimental units, it is often the case that some of the parameters vary between the individual experimental units.
Fernando Baltazar‐Larios +2 more
wiley +1 more source
Efficient Deconvolution in Populational Inverse Problems
ABSTRACT This work is focused on the inversion task of inferring the distribution over parameters of interest, leading to multiple sets of observations. The potential to solve such distributional inversion problems is driven by the increasing availability of data, but a major roadblock is blind deconvolution, arising when the observational noise ...
Arnaud Vadeboncoeur +2 more
wiley +1 more source
This study compares positron emission particle tracking (PEPT), magnetic particle tracking (MPT), and DEM–SPH simulations to analyze grinding media dynamics in a horizontal stirred mill. It highlights the strengths of PEPT's precision, MPT's cost‐effectiveness, and DEM–SPH's versatility, offering insights into tracking and simulation methodologies ...
Sherry Bremner +5 more
wiley +1 more source
Regional Adjustments to NGA‐West2 Ground‐Motion Models for Turkey
ABSTRACT This paper presents a ground‐motion model updating (GMMU) framework to adjust NGA‐West2 models for predicting a set of intensity measures in Turkey, including peak ground acceleration (PGA), peak ground velocity (PGV), and pseudo‐spectral acceleration (PSA) at periods ranging from 0.01 to 10 s. The GMMU framework integrates bias identification
Mao‐Xin Wang, Gang Wang
wiley +1 more source
Downscaling Daily Discharge to Sub‐Daily Scales for Alpine Glacierized Catchments
Abstract Hydrological dynamics in glacierized catchments of the Alps are shaped by temperature‐driven processes, including snow and ice melt as well as precipitation, leading to diel streamflow cycles that vary in intensity within‐ and among‐the seasons.
Anne‐Laure Argentin +9 more
wiley +1 more source
ABSTRACT In this paper, we propose a new test for the detection of a change in a non‐linear (auto‐)regressive time series as well as a corresponding estimator for the unknown time point of the change. To this end, we consider an at‐most‐one‐change model and approximate the unknown (auto‐)regression function by a neural network with one hidden layer. It
Claudia Kirch, Stefanie Schwaar
wiley +1 more source

