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Theory for Dissipative Time Crystals in Coupled Parametric Oscillators.
Phys Rev Lett
December 2024
University of Maryland, College Park, Joint Quantum Institute, Condensed Matter Theory Center and, Department of Physics, Maryland 20742-4111, USA.
Discrete time crystals are novel phases of matter that break the discrete time translational symmetry of a periodically driven system. In this Letter, we propose a classical system of weakly nonlinear parametrically driven coupled oscillators as a test bed to understand these phases. Such a system of parametric oscillators can be used to model period-doubling instabilities of Josephson junction arrays as well as semiconductor lasers.
View Article and Find Full Text PDFRadiogenomic explainable AI with neural ordinary differential equation for identifying post-SRS brain metastasis radionecrosis.
Med Phys
January 2025
Deparment of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Background: Stereotactic radiosurgery (SRS) is widely used for managing brain metastases (BMs), but an adverse effect, radionecrosis, complicates post-SRS management. Differentiating radionecrosis from tumor recurrence non-invasively remains a major clinical challenge, as conventional imaging techniques often necessitate surgical biopsy for accurate diagnosis. Machine learning and deep learning models have shown potential in distinguishing radionecrosis from tumor recurrence.
View Article and Find Full Text PDFThe interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach.
BMC Psychiatry
January 2025
West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
The current DSM-oriented diagnostic paradigm has introduced the issue of heterogeneity, as it fails to account for the identification of the neurological processes underlying mental illnesses, which affects the precision of treatment. The Research Domain Criteria (RDoC) framework serves as a recognized approach to addressing this heterogeneity, and several assessment and translation techniques have been proposed. Among these methods, transforming RDoC scores from electronic medical records (EMR) using Natural Language Processing (NLP) has emerged as a suitable technique, demonstrating clinical effectiveness.
View Article and Find Full Text PDFPrognostic significance of cytokine dysregulation in critically ill COVID-19 patients.
Cytokine
January 2025
Multidisciplinary Health Institute, Federal University of Bahia, Vitória da Conquista 45029-094, Bahia, Brazil. Electronic address:
Background: Understanding the immunopathogenesis of COVID-19 has yielded valuable insights into predicting adverse outcomes-particularly mortality. However, significant gaps persist in our comprehension of the complex interplay among the proposed pathophysiological mechanisms. Here, we aim to investigate the immunological factors associated with mortality in critically ill, unvaccinated COVID-19 patients admitted to the intensive care unit (ICU).
View Article and Find Full Text PDFImproving flood-prone areas mapping using geospatial artificial intelligence (GeoAI): A non-parametric algorithm enhanced by math-based metaheuristic algorithms.
J Environ Manage
January 2025
Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone, XR Research Center, Sejong University, Seoul, Republic of Korea. Electronic address:
Flooding presents substantial dangers to human lives and infrastructure, underscoring the need to map flood-prone areas to implement effective mitigation measures precisely. Although machine learning algorithms have made great strides, their accuracy in flood susceptibility mapping (FSM) remains limited due to data dependence, interpretability, and explainability issues, overfitting, generalization difficulties, and hyperparameter tuning. This study suggests combining the Decision Tree (DT) algorithm with advanced, math-based metaheuristic optimization algorithms to address these limitations.
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