Results 61 to 70 of about 10,579,206 (300)
Discovering causal models for structural, construction and defense-related engineering phenomena
Causality, the science of cause and effect, has made it possible to create a new family of models. Such models are often referred to as causal models. Unlike those of mathematical, numerical, empirical, or machine learning (ML) nature, causal models hope
M.Z. Naser
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Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
A practical method to control spatiotemporal confounding in environmental impact studies
Separating natural spatiotemporal variation from the impact of human activities has long been a challenge in environmental impact studies. To overcome this problem, a causal modelling method based on spatiotemporal data, integrated with existing ...
Rezvan Hatami
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The human gut microbiome across the life course
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
wiley +1 more source
Degradation mechanism of the von Willebrand factor A2 domain by nattokinase
Nattokinase, a natto‐derived protease, exhibits potent antithrombotic effects. This study demonstrates that nattokinase directly cleaves the von Willebrand factor (vWF) A2 domain in vitro. Unlike the native regulator ADAMTS13, nattokinase degrades folded vWF independently of shear stress.
Ryuichi Hyakumoto +3 more
wiley +1 more source
A semantics for counterfactuals in quantum causal models
We introduce a formalism for the evaluation of counterfactual queries in the framework of quantum causal models, generalising Pearl’s semantics for counterfactuals in classical causal models, thus completing the last rung in the quantum analogue of Pearl’
Ardra Kooderi Suresh +2 more
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We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Practically effective adjustment variable selection in causal inference
In the estimation of causal effects, one common method for removing the influence of confounders is to adjust the variables that satisfy the back-door criterion. However, it is not always possible to uniquely determine sets of such variables.
Atsushi Noda, Takashi Isozaki
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Individual Causal Inference with Structural Causal Model
Individual causal inference (ICI) uses causal inference methods to understand and predict the effects of interventions on individuals, considering their specific characteristics / facts. It aims to estimate individual causal effect (ICE), which varies across individuals.
openaire +2 more sources
Structure and Parameter Learning for Causal Independence and Causal Interaction Models
Appears in Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI1997)
Christopher Meek, David Heckerman
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