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The paper gives a description of wave propagation in discrete-periodic one-dimensional media with block structure. For one-dimensional problems mathematical models are proposed that describe block structures in the form of a mass chain or…
We describe how to consistently incorporate solar model uncertainties, along with experimental errors and correlations, when analyzing solar neutrino data to derive confidence limits on parameter space for proposed solutions of the solar…
Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions…
ICME approaches provide decision support for materials design by establishing quantitative process-structure-property relations. Confidence in the decision support, however, must be achieved by establishing uncertainty bounds in ICME model…
Monte-Carlo nuclear reaction and transport codes are widely used to devise accelerator-based nuclear physics experiments; at the same time, many experiments are performed to validate the Monte-Carlo codes, which can be used for the design…
We discuss the bounds on the mass of Dark Matter (DM) particles, coming from the analysis of DM phase-space distribution in dwarf spheroidal galaxies (dSphs). After reviewing the existing approaches, we choose two methods to derive such a…
In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining…
The fidelity of a model relies both on its accuracy to predict the physical phenomena and its capability to estimate unknown parameters using observations. This article focuses on this second aspect by analyzing the reliability of two…
Accurate overland runoff and infiltration predictions are critical for effective water resources management, in particular for urban flood management. However, the inherent uncertainty in rainfall patterns, soil properties, and initial…
The next generation of double-beta decay experiments have an excellent chance of providing data on the neutrino mass pattern. This presentation is a summary of what is currently known about the mass pattern and expectations from experiment.…
This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be…
Deep neural networks have shown great success in prediction quality while reliable and robust uncertainty estimation remains a challenge. Predictive uncertainty supplements model predictions and enables improved functionality of downstream…
The status of experiments on determination of level density and partial widths of the nuclear reaction products emission in diapason of nucleon binding energy is presented. There are analyzed the sources and magnitude of probable…
The entropic uncertainty measures of the multidimensional hydrogenic states quantify the multiple facets of the spatial delocalization of the electronic probability density of the system. The Shannon entropy is the most adequate uncertainty…
We analyze the viability of the Zee-Babu model as an explanation of observed neutrino masses and mixings and the possibility that the model is confirmed or discarded in experiments planned for the very close future. The allowed parameter…
We found an analytical solution for the neutrino mass matrix in the most general case of the Zee model. Using the recent data on the neutrino parameters besides generating neutrino masses at 1-loop level we fit also the masses of the…
We present a Zee model with a family dependent $Z_2$ symmetry for radiative neutrino masses. Our motivation is to get a model that correctly describes neutrino oscillation phenomena, while at the same time offers definite predictions. The…
We investigate the impact of non-linear corrections on dark energy parameter estimation from weak lensing probes. We find that using halofit expressions, suited to LCDM models, implies substantial discrepancies with respect to results…
In light of recent positive results from the DAMA experiment, as well as new null results from CDMS Soudan, Edelweiss, ZEPLIN-I and CRESST, we reexamine the framework of inelastic dark matter with a standard halo. In this framework, which…
We report an evaluation of a semi-empirical quantum chemical method PM7 from the perspective of uncertainty quantification. Specifically, we apply Bound-to-Bound Data Collaboration, an uncertainty quantification framework, to characterize…