Results 111 to 120 of about 4,846 (159)

Microstructural and Physical Properties of High‐Protein, High‐Overrun Frozen Desserts

open access: yesJournal of Food Science, Volume 91, Issue 3, March 2026.
ABSTRACT Ice cream and frozen desserts fortified with protein often have undesirable physical and textural properties despite their increased nutritional value, and are susceptible to shrinkage during storage. The effects of dairy protein structure on structural and physical properties of the mix and frozen product were identified by studying frozen ...
Samantha R. VanWees   +2 more
wiley   +1 more source

Beyond Normality: Gain‐Probability Analysis for Symmetric Scale Mixture of Normal Distributions

open access: yesAustralian &New Zealand Journal of Statistics, Volume 68, Issue 1, March 2026.
ABSTRACT Gain‐Probability (G‐P) analysis quantifies the probability that a randomly selected individual from one group scores higher or lower than an individual from another group, by varying magnitudes. While G‐P methods have been developed under normality and various skewed distributions, symmetric heavy‐tailed settings remain largely unexplored ...
Tingting Tong   +5 more
wiley   +1 more source

Modern Neural Networks for Small Tabular Datasets: The New Default for Field‐Scale Digital Soil Mapping?

open access: yesEuropean Journal of Soil Science, Volume 77, Issue 2, March–April 2026.
ABSTRACT In the field of pedometrics, tabular machine learning is the predominant method for soil property prediction from remote and proximal soil sensing data, forming a central component of Digital Soil Mapping (DSM). At the field‐scale, this pedometric modeling task is typically constrained by small training sample sizes and high feature‐to‐sample ...
Viacheslav Barkov   +3 more
wiley   +1 more source

A cybersecurity risk analysis framework for systems with artificial intelligence components

open access: yesInternational Transactions in Operational Research, Volume 33, Issue 2, Page 798-825, March 2026.
Abstract The introduction of the European Union Artificial Intelligence (AI) Act, the NIST AI Risk Management Framework, and related international norms and policy documents demand a better understanding and implementation of novel risk analysis issues when facing systems with AI components: dealing with new AI‐related impacts; incorporating AI‐based ...
J.M. Camacho   +3 more
wiley   +1 more source

A standardization procedure to incorporate variance partitioning‐based priors in latent Gaussian models

open access: yesScandinavian Journal of Statistics, Volume 53, Issue 1, Page 364-394, March 2026.
ABSTRACT Latent Gaussian models (LGMs) are a subset of Bayesian Hierarchical models where Gaussian priors, conditional on variance parameters, are assigned to all effects in the model. LGMs are employed in many fields for their flexibility and computational efficiency. However, practitioners find prior elicitation on the variance parameters challenging
Luisa Ferrari, Massimo Ventrucci
wiley   +1 more source

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