Bacteriophages, which infect bacterial cells, have a unique ability to reduce bacterial colonization, particularly in antibiotic-resistant biofilm infections. This study aims to fabricate optimized ...
Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Degrowth argues that high-income economies should reduce harmful production and prioritise wellbeing ...
Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...
Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...
Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...
Cyber losses in terms of number of records breached under cyber incidents commonly feature a significant portion of zeros, specific characteristics of mid-range losses and large losses, which make it ...
2 Department of Clinical Research, Odense Patient Data Explorative Network, University of Southern Denmark, Odense, Denmark 3 Occupational Science, User Perspectives and Community-Based Interventions, ...
Considering the strong non-linear time-varying behavior of dam deformation, a novel prediction model, called Levy flight-based grey wolf optimizer optimized support vector regression (LGWO-SVR), is ...
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