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Articles 1 - 2 of 2
Full-Text Articles in Life Sciences
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Michigan Tech Publications
The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …
Mechanobiology In The Comorbidities Of Ehlers Danlos Syndrome, Shaina P. Royer, Sangyoon J. Han
Mechanobiology In The Comorbidities Of Ehlers Danlos Syndrome, Shaina P. Royer, Sangyoon J. Han
Michigan Tech Publications
Ehlers-Danlos Syndromes (EDSs) are a group of connective tissue disorders, characterized by skin stretchability, joint hypermobility and instability. Mechanically, various tissues from EDS patients exhibit lowered elastic modulus and lowered ultimate strength. This change in mechanics has been associated with EDS symptoms. However, recent evidence points toward a possibility that the comorbidities of EDS could be also associated with reduced tissue stiffness. In this review, we focus on mast cell activation syndrome and impaired wound healing, comorbidities associated with the classical type (cEDS) and the hypermobile type (hEDS), respectively, and discuss potential mechanobiological pathways involved in the comorbidities.