An explicit derivation of the Mori-Zwanzig orthogonal dynamics of observables is presented and leads to two practical algorithms to compute exactly projected observables (e.g., random noise) and projected correlation function (e.g., memory kernel) from a molecular dynamics trajectory. The algorithms are then applied to study the diffusive dynamics of a tagged particle in a Lennard-Jones fluid, the properties of the associated random noise, and a decomposition of the corresponding memory kernel.
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http://dx.doi.org/10.1063/1.4868653 | DOI Listing |
Electronics (Basel)
December 2024
Department of Mechanical Engineering, City College of New York, New York, NY 10031, USA.
Cardiovascular disease is a leading cause of death worldwide. The differentiation of human pluripotent stem cells (hPSCs) into functional cardiomyocytes offers significant potential for disease modeling and cell-based cardiac therapies. However, hPSC-derived cardiomyocytes (hPSC-CMs) remain largely immature, limiting their experimental and clinical applications.
View Article and Find Full Text PDFOphthalmol Sci
November 2024
Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California.
Objective: To quantitatively assess the retinal vascular tortuosity of patients with sickle cell disease (SCD) and retinopathy (SCR) using an automated deep learning (DL)-based pipeline.
Design: Cross-sectional study.
Subjects: Patients diagnosed with SCD and screened for SCR at an academic eye center between January 2015 and November 2022 were identified using electronic health records.
Brain Commun
January 2025
Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome 00179, Italy.
Alzheimer's disease is a disabling neurodegenerative disorder for which no effective treatment currently exists. To predict the diagnosis of Alzheimer's disease could be crucial for patients' outcome, but current Alzheimer's disease biomarkers are invasive, time consuming or expensive. Thus, developing MRI-based computational methods for Alzheimer's disease early diagnosis would be essential to narrow down the phenotypic measures predictive of cognitive decline.
View Article and Find Full Text PDFPeerJ
January 2025
Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States.
Motivation: As data sets increase in size and complexity with advancing technology, flexible and interpretable data reduction methods that quantify information preservation become increasingly important.
Results: Super Partition is a large-scale approximation of the original Partition data reduction algorithm that allows the user to flexibly specify the minimum amount of information captured for each input feature. In an initial step, Genie, a fast, hierarchical clustering algorithm, forms a super-partition, thereby increasing the computational tractability by allowing Partition to be applied to the subsets.
J Biomed Opt
January 2025
Lund University, Department of Physics, Lund, Sweden.
Significance: The spatial distribution of the photosensitizing drug concentration is an important parameter for predicting the photodynamic therapy (PDT) outcome. Current diffuse fluorescence tomography methods lack accuracy in quantifying drug concentration. The development of accurate methods for monitoring the temporal evolution of the drug distribution in tissue can advance the real-time light dosimetry in PDT of tumors, leading to better treatment outcomes.
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