Results 151 to 159 of about 165 (159)

Emotion Differentiation and Dynamics Predicting Suicide Outcomes in High‐Risk Adults

Suicide and Life-Threatening Behavior, Volume 56, Issue 2, April 2026.
ABSTRACT Objectives Negative emotions have been well studied in relation to suicidal thoughts and behaviors (STBs); however, little research in these areas have been informed by affective science frameworks that consider the complex and time varying nature of STBs.
Elizabeth C. Hoelscher, Sarah E. Victor, Sheri L. Johnson, Jason Van Allen, Leslie Brick   +4 more
wiley   +1 more source

Stochastic Modelling of Daily Precipitation in Semi‐Arid Regions Using Markov Chains and Parametric Distributions

International Journal of Climatology, Volume 46, Issue 4, 30 March 2026.
This study applies stochastic rainfall models combining Markov Chains with gamma and mixed exponential distributions to a semi‐arid climate in Northeast Brazil. Model structures were evaluated using Bayesian Information Criterion (BIC), with maximum likelihood (MLM) for parameter estimation and cumulative distribution functions (CDFs) for validation ...
Gabriel Magno Cavalcante Calado, Mayke Feitosa Progênio, José Adalberto da Silva Filho, Ialy Rayane de Aguiar Costa, Severino Martins Neto, Artur Paiva Coutinho   +5 more
wiley   +1 more source

Correction of Climate Model Winds With Preserved Spatio‐Temporal and Directional Consistency

Geophysical Research Letters, Volume 53, Issue 6, 28 March 2026.
Abstract Systematic biases in climate model outputs, particularly in extremes, limit their reliability for wind‐related applications. This study applies the Wavelet Bias Correction (WBC) method to daily near‐surface wind components (uwnd and vwnd) from three CMIP6 models (ACCESS‐CM2, HadGEM3‐GC31‐LL, and UKESM1‐0‐LL) over current (1979–2014) and future
Cilcia Kusumastuti, Rajeshwar Mehrotra, Ashish Sharma   +2 more
wiley   +1 more source

Physics‐Constrained Network for Enhanced Extended‐Range Precipitation Forecasting in East Asia

Geophysical Research Letters, Volume 53, Issue 6, 28 March 2026.
Abstract The complex summer weather in East Asia poses significant challenges of precipitation forecasting. Despite the promising capabilities of deep learning models in conventional forecasting tasks, their black‐box nature limits physical interpretability.
Yudan Wang, Huimin Chen, Hao Wu, Jane Liu, Huiling Yuan, Shuya Cao, Tijian Wang, Bingliang Zhuang   +7 more
wiley   +1 more source

Plume‐Coupled Long‐Range Spotting Drove the Explosive Spread of the 2018 Camp Fire

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 6, 28 March 2026.
Abstract Extreme fire spread during the 2018 Camp Fire in northern California was driven by organized long‐range spotting tightly coupled to plume dynamics. Doppler radar and satellite observations reveal distinct regions of ember lofting and downwind fallout within the convective column, forming direct pathways for firebrand transport several (up to ...
N. P. Lareau
wiley   +1 more source

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Discrete mollification in Bernstein basis and space marching scheme for numerical solution of an inverse two-phase one-dimensional Stefan problem

Numerical Algorithms, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
S. Bodaghi, A. Zakeri, A. Amiraslani, A. H. Salehi Shayegan   +3 more
openaire   +2 more sources

Approximate solution of hyperbolic conservation laws by discrete mollification

Applied Numerical Mathematics, 2009
The authors propose explicit schemes for one-dimensional linear and nonlinear hyperbolic conservation laws. Combination of these methods with discrete mollification yields new methods with the following properties: Large time steps are allowed and stability is preserved.
Acosta, Carlos D., Mejía, Carlos E.
openaire   +2 more sources

Regularization of a nonlinear inverse problem by discrete mollification method

2021
Summary: In this article, the application of discrete mollification as a regularization procedure for solving a nonlinear inverse problem in one dimensional space is considered. Illposedness is identified as one of the main characteristics of inverse problems. It is clear that if we have a noisy data, the inverse problem becomes unstable.
Bodaghi, Soheila, Zakeri, Ali, Amiraslani, Amir   +2 more
openaire   +1 more source

A numerical scheme based on discrete mollification method using Bernstein basis polynomials for solving the inverse one-dimensional Stefan problem

Inverse Problems in Science and Engineering, 2020
This paper concerns a one-phase inverse Stefan problem in one-dimensional space. The problem is ill-posed in the sense that the solution does not depend continuously on the data.
Soheila Bodaghi, Ali Zakeri, Amir Amiraslani   +2 more
openaire   +1 more source