Publications by authors named "L K Hedges"
The standardized mean difference (sometimes called Cohen's d) is an effect size measure widely used to describe the outcomes of experiments. It is mathematically natural to describe differences between groups of data that are normally distributed with different means but the same standard deviation. In that context, it can be interpreted as determining several indexes of overlap between the two distributions.
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- The study focuses on measuring cerebrospinal fluid (CSF) velocity in real time to better understand the glymphatic system's role in neurodegenerative diseases like Alzheimer's and Parkinson's.
- Current imaging methods struggle with accurately capturing slow CSF movements, prompting this research to develop a new way to quantify CSF flow using functional MRI (fMRI).
- The results showed a successful nonlinear relationship between CSF flow and fMRI signals, indicating that this novel method can provide deeper insights into CSF dynamics and its potential impact on brain health.
Article Synopsis
- - Sire is an open-source Python/C++ library designed for developing new algorithms and facilitating data exchange between molecular simulation programs, making it easier for researchers to integrate different tools and libraries.
- - It enables users to execute a single script to perform multiple tasks, such as loading molecular data, conducting searches, parameterizing molecules, running simulations, and visualizing results all within a user-friendly interface.
- - By incorporating a robust search engine and an integrated computer algebra system, Sire allows researchers to manipulate and analyze molecular data effectively, while supporting interoperability with popular programs like GROMACS and NAMD for advanced molecular modeling workflows.
We present in this work the package (https://github.com/chemle/emle-engine)─the implementation of a new machine learning embedding scheme for hybrid machine learning potential/molecular-mechanics (ML/MM) dynamics simulations. The package is based on an embedding scheme that uses a physics-based model of the electronic density and induction with a handful of tunable parameters derived from properties of the subsystem to be embedded.
View Article and Find Full Text PDFestimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory gated approaches, such as 4D flow MRI, cannot capture CSF movement in real time due to limited temporal resolution and in addition deteriorate in accuracy at low fluid velocities. Other techniques like real-time PC-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability even in research settings.
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