Results 161 to 170 of about 85,238 (262)

Clarifying Fundamental Role of Symbol Coding in Cognitive Networks in Schizophrenia and Healthy Controls Leveraging Gaussian Graphical Models and Bayesian Networks. [PDF]

Schizophr Bull
Zhang Y, Sun Y, Lu Z, Zhao G, Sun J, Zhang X, Yang Y, Kang Z, Feng X, Yuan R, Liao Y, Zhu Y, Guo J, Yue W.   +13 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools. [PDF]

Front Syst Biol
Canonaco F, Gaudillo J, Astrologo N, Stella F, Acerbi E.   +4 more
europepmc   +1 more source

Farmers' Preferences for Gene Editing Crops and Influencing Factors

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Gene editing (GE) is gaining momentum worldwide, but limited data on UK farmers' preferences hinders our understanding of its potential impact amid deregulation debates. Based on a survey of 200 English arable farmers, we employ a Latent Class Analysis and Multinomial Logit regressions to investigate current preferences for GE crops.
Bertolozzi‐Caredio Daniele, Vigani Mauro   +1 more
wiley   +1 more source

Integrating Machine Learning and Dynamic Bayesian Networks to Identify the Factors Associated with Subsequent Intrapulmonary Metastasis Classification After Initial Single Primary Lung Cancer. [PDF]

Cancers (Basel)
Liu W, Chang ATC, Chan JWY, Chan JCS, Lau RWH, Mok TSK, Ng CSH.   +6 more
europepmc   +1 more source

Differentiated Impacts of EU Rural Development Measures: A Finite Mixture Evaluation of Italian Olive Farms

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT This paper examines the relationship between participation in the EU Rural Development Program and the economic performance of Italian olive farms using a finite‐mixture model with inverse‐probability‐weighted regression adjustment. Based on 2010–2022 FADN panel data, it estimates heterogeneous treatment effects while correcting for selection ...
Francesco Caracciolo, Marilena Furno
wiley   +1 more source

Bayesian networks and structural equation models reveal genetic causal relationships between productivity, defense, and climate-adaptability traits in interior lodgepole pine. [PDF]

G3 (Bethesda)
Cappa EP, Klutsch JG, Benowicz A, Munilla S, Mansfield SD, Erbilgin N, Thomas BR, El-Kassaby YA.   +7 more
europepmc   +1 more source

Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?

Agribusiness, EarlyView.
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley   +1 more source

Using Dynamic Causal Bayesian Networks to Assess the Role of Patient-Centered Care and Individual-Level Barriers on Viral Suppression Changes Among a Cohort of People with HIV. [PDF]

AIDS Behav
Trepka MJ, Gonzales S, Ward MK, Fennie KP, Sheehan DM, Jean-Gilles M, Devieux J, Gray A, Ladner R, Yoo C.   +9 more
europepmc   +1 more source

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

Agribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley   +1 more source