Results 71 to 80 of about 11,660 (201)

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Modeling and Forecasting Volatility of the Malaysian and the Singaporean stock indices using Asymmetric GARCH models and Non-normal Densities [PDF]

This paper examines and estimate the three GARCH(1,1) models (GARCH, EGARCH and GJR-GARCH) using the daily price data. Two Asian stock indices KLCI and STI are studied using daily data over a 14-years period.
Abu Hassan, Ahmed Shamiri
core  

Imaging the later‐life white matter pathologies of repetitive head impacts: A novel pattern revealed through T2 FLAIR MRI

Alzheimer's &Dementia, Volume 22, Issue 4, April 2026.
Abstract INTRODUCTION Repetitive head impacts (RHI) from contact sports may cause a unique pattern of white matter hyperintensities (WMH) on T2‐weighted fluid‐attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), termed RHI‐associated WMH (RHI‐WMH).
Jenna R. Groh, Annalise E. Miner, Mohamad J. Alshikho, Chad Farris, Anna Cui, Erika Pettway, Jacob Labonte, Sydney Mosaheb, Yorghos Tripodis, Charles H. Adler, Laura J. Balcer, Charles Bernick, Robert C. Cantu, Michael J. Coleman, David W. Dodick, Nicholas J. Ashton, Henrik Zetterberg, Kaj Blennow, Elaine R. Peskind, Christopher Nowinski, Monica Ly, Caroline Altaras, Steven Lenio, Gil D. Rabinovici, Breton Asken, Howard Rosen, Yann Cobigo, Jan Krzysztof Blusztajn, Andrew E. Budson, Katherine Turk, Wei Qiao Qiu, Lee Goldstein, Brett Martin, Joseph N. Palmisano, Diane Dixon, Greta Schneider, Eric G. Steinberg, Yi Su, Hillary Protas, Ofer Pasternak, Inga Koerte, Sylvain Bouix, Jeffrey L. Cummings, Eric M. Reiman, Martha E. Shenton, Robert A. Stern, Ann C. McKee, Thor D. Stein, Adam M. Brickman, Jesse Mez, Michael L. Alosco   +50 more
wiley   +1 more source

Comparison of Symmetrical; Asymmetrical; and Logarithmic Models Using GARCH; GJR-GARCH; and EGARCH Method in Forecasting Indonesia–USA Currency Volatility

Ekonometria
Aim: The main object of this study was to present a comparison between GARCH models, i.e. the standard GARCH model, asymmetric GJR-GARCH, and logarithmic EGARCH on exchange rate (IDR/USD) volatility.
Juwita Suwondo, Rern-Jay Hung, Eko Yuni Prihantono, Renaldi   +3 more
doaj   +1 more source

GARCH models with leverage effect : differences and similarities [PDF]

In this paper, we compare the statistical properties of some of the most popular GARCH models with leverage effect when their parameters satisfy the positivity, stationarity and nite fourth order moment restrictions.
Esther Ruiz, María José Rodríguez
core  

Postoperative Pain Management After Lumbar Discectomy. A Systematic Review With Meta‐Analyses and Trial Sequential Analyses

European Journal of Pain, Volume 30, Issue 4, April 2026.
ABSTRACT Background Inadequate postoperative pain management after lumbar discectomy may delay recovery, increase the risk of chronic pain, and prolong hospitalization. Effective analgesic strategies must balance pain control with minimal adverse effects.
Josephine Zachodnik, Rachid Bech‐Azeddine, Magnus Sandberg, Rebecca Scherwin, Rikke Malene Hartvigsen Grønholm Jepsen, Louise Møller Jørgensen, Kasper Højgaard Thybo, Anja Geisler   +7 more
wiley   +1 more source

Forecasting Malaysian gold using a hybrid of ARIMA and GJR-GARCH models

Applied Mathematical Sciences, 2015
An effective way to improve forecast accuracy is to use a hybrid model. This paper proposes a hybrid model of linear autoregressive moving average (ARIMA) and non-linear GJR-GARCH model also known as TARCH in modeling and forecasting Malaysian gold.
Ahmad, Maizah Hura, Pung, Yean Ping, Yaziz, Siti Roslindar, Miswan, Nor Hamizah   +3 more
openaire   +2 more sources

Contagion between Islamic and Conventional Banking: A GJR DCC-GARCH and VAR Analysis

International Business Research, 2016
<p>This study aims testing the presence of contagion through Islamic and conventional banking systems during the subprime crisis. Specifically, we examine how far a shock striking conventional or Islamic banks is exported from one group to another or remain limited.
Mohamed Amin Chakroun, Mohamed Imen Gallali   +1 more
openaire   +1 more source

Model Selection and Testing of Conditional and Stochastic Volatility Models [PDF]

This paper focuses on the selection and comparison of alternative non-nested volatility models. We review the traditional in-sample methods commonly applied in the volatility framework, namely diagnostic checking procedures, information criteria, and ...
Massimiliano Caporin, Michael McAleer
core   +3 more sources

Modelling and forecasting of Nigeria stock market volatility

Future Business Journal
This study models and forecasts the volatility of the Nigerian Stock Exchange (NSE) using advanced econometric techniques, focusing on examining the asymmetric volatility and the leverage effect. Daily data from the NSE All Share Index spanning from 30th
Olufemi Samuel Adegboyo, Kiran Sarwar
doaj   +1 more source