Results 91 to 100 of about 720 (191)

Identification of Major Depressive Disorder Using Multiple Functional Connection Patterns

open access: yesCNS Neuroscience &Therapeutics, Volume 32, Issue 6, June 2026.
We propose a Multiple Functional Connection Pattern Graph Convolutional Network (MFCP) for major depressive disorder identification using resting‐state fMRI. By integrating Pearson correlation, sparse representation, and Granger causality–based brain networks, MFCP captures complementary connectivity information.
Yudi Ruan   +6 more
wiley   +1 more source

Conditional Stochastic Simulations of Flow and Transport with Karhunen-Loève Expansions, Stochastic Collocation, and Sequential Gaussian Simulation

open access: yesJournal of Applied Mathematics, 2014
We derive a new method of conditional Karhunen-Loève (KL) expansions for stochastic coefficients in models of flow and transport in the subsurface, and in particular for the heterogeneous random permeability field.
Mina E. Ossiander   +2 more
doaj   +1 more source

CEBP and ZEB2 alterations define three distinct subtypes of B‐cell acute lymphoblastic leukemia

open access: yesHemaSphere, Volume 10, Issue 6, June 2026.
Abstract B‐cell acute lymphoblastic leukemia (B‐ALL) is a heterogeneous malignancy driven by diverse genetic alterations. Among these, CEBP family genes and ZEB2 are recurrently involved, yet the spectrum of genomic mechanisms and their clinical impact remain incompletely defined.
Rathana Kim   +29 more
wiley   +1 more source

CFD‐Based and Control‐Oriented Modeling of a Counterflow Heat Exchanger With Utilization of Parameter Identification

open access: yesProceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT Counterflow heat exchangers (CHXs) thermally couple consumers and producers to a district heating network (DHN). Fluctuating loads and control actions naturally lead to unsteady operation conditions of the network and its components, posing a challenge for DHN models and CHX parameterizations based on Nusselt correlations that assume steady ...
Marten Klein   +5 more
wiley   +1 more source

Text Mining in Bibliometrics and Science Mapping: A Methodological Review

open access: yesWIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Text mining has become a foundational component of contemporary bibliometrics and science mapping, enabling systematic analysis of the semantic structure, thematic evolution, and cognitive organization of scientific fields. Integrating textual evidence with relational indicators enriches knowledge maps and supports more comprehensive, content‐sensitive
Michelangelo Misuraca
wiley   +1 more source

STOCHASTIC FINITE ELEMENT MODEL UPDATING BASED ON POLYNOMIAL CHAOTIC EXPANSION AND KL DIVERGENCE

open access: yesJixie qiangdu, 2021
Considering the influence of structural parameter uncertainty on response and the problem of large calculation of stochastic model updating, a stochastic finite element model updating method based on polynomial chaotic expansion and KL divergence is ...
XU ZeWei   +3 more
doaj  

Hydrographic Variability and Sound‐Channel Dynamics in the Nordic Seas: Implications for Predicting Acoustic Arrival Structure

open access: yesJournal of Geophysical Research: Oceans, Volume 131, Issue 6, June 2026.
Abstract Warm, saline Atlantic waters and fresher Arctic‐origin waters converge in the central Nordic Seas, creating strong mesoscale and submesoscale variability that influences both hydrography and sound propagation. During the Northern Ocean Rapid Surface Evolution 2022 experiment, high‐resolution temperature and salinity measurements were collected
Megan S. Ballard   +11 more
wiley   +1 more source

Walsh function-based numerical approach for nonlinear stochastic integral equations: Application to stochastic logistic models

open access: yesBoundary Value Problems
The current research study proposes an efficient numerical method for obtaining an approximate solution to nonlinear stochastic integral equations implementing the collocation method and the Walsh operational matrices.
Prit Pritam Paikaray   +3 more
doaj   +1 more source

Can AI‐Based Weather Prediction Models Simulate the Butterfly Effect? The Role of Architecture and Implementation

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.
Abstract Simulations of numerical weather prediction models indicate that the atmosphere possesses an intrinsic limit of predictability. Initial perturbations of tiny amplitude grow quickly in areas of convection and latent heat release, then spread out and move upscale, eventually affecting even the largest planetary scales after about 2 weeks.
T. Selz, G. C. Craig
wiley   +1 more source

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