Nonparametric estimation of conditional survival function with time-varying covariates using DeepONet. [PDF]
Hu B, Nan B.
europepmc +1 more source
Experimental methods in chemical engineering: Atomic absorption spectrometry—AAS
Abstract Elements absorb electromagnetic radiation (light) of a specific wavelength in proportion to the number of atoms in its path. As the atoms absorb this light energy, electrons rise from the ground state to an excited state. In atomic absorption spectrometry (AAS), high temperatures produce clouds of atoms from the sample (atomization) and ...
Emily Cintia Tossi de A. Costa +4 more
wiley +1 more source
Identity-Based Efficient Secure Data Communication Protocol for Hierarchical Sensor Groups in Smart Grid. [PDF]
Feng Y, Sun Y, Cao Y, Xu B, Li Y.
europepmc +1 more source
Restricted Tweedie stochastic block models
Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Spectral quantum algorithm for passive scalar transport in shear flows. [PDF]
Pfeffer P +3 more
europepmc +1 more source
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni +2 more
wiley +1 more source
A Decentralized Signcryption Scheme Based on CFL. [PDF]
Shi L, Liu M.
europepmc +1 more source
Partial identification with categorical data and nonignorable missing outcomes
Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley +1 more source
A robust zero-watermarking and signcryption scheme for image copyright protection and license verification. [PDF]
Hung PT, Thanh TM.
europepmc +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source

