Liu, Jing

The Louisiana coastal ecosystem is experiencing increasing threats from human flood control construction, sea-level rise (SLR), and subsidence. Louisiana lost about 4,833 km2 of coastal wetlands from 1932 to 2016, and concern exists whether remaining wetlands will persist while facing the highest rate of relative sea-level rise (RSLR) in the world. Restoration aimed at rehabilitating the ongoing and future disturbances is currently underway through the implementation of the Coastal Wetlands Planning Protection and Restoration Act of 1990 (CWPPRA). To effectively monitor the progress of projects in CWPPRA, the Coastwide Reference Monitoring System (CRMS) was established in 2006. To date, more than a decade of valuable coastal, environmental, and ground elevation data have been collected and archived. This dataset offers a unique opportunity to evaluate the wetland ground elevation dynamics by linking the Rod Surface Elevation Table (RSET) measurements with environmental variables like water salinity and biophysical variables like canopy coverage. This dissertation research examined the effects of the environmental and biophysical variables on wetland terrain elevation by developing innovative machine learning based models to quantify the contribution of each factor using the CRMS collected dataset. Three modern machine learning algorithms, including Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), were assessed and cross-compared with the commonly used Multiple Linear Regression (MLR). The results showed that RF had the best performance in modeling ground elevation with Root Mean Square Error (RMSE) of 10.8 cm and coefficient of coefficient (r) = 0.74. The top four factors contributing to ground elevation are the distance from monitoring station to closest water source, water salinity, water elevation, and dominant vegetation height.

Troponin I is a contractile protein and plays an important role in cardiac function.
We have generated cTnl knockout and cTnI(R192H) transgenic mouse models. All of
cTnl knockout homozygous mice die at 17-18 days after birth. Some of cTnI(R192H)
transgenic mice die at early life stages, some mice develop heart failure at late stages.
High-resolution ultrasound imaging and Doppler echocardiography have been used to
evaluate cardiac function on cTnl deficient mice and cTnl(R192H) transgenic mice.
cTnI mice have damaged relaxation with gradually decreased E/A ratio(E/A<1). FS
and cardiac output dramatically decrease on 17-day-o1d cTnI mice indicating severe
cardiac dysfunction. We find that the damaged heart function is correspondent with the
Tnl expression level decline. 6-8 weeks transgenic mice have shown that the dimension
of left and right atria increase. In 15-month-old transgenic mice, the E/A ratio shows a
pseudonormal pattern indicating a diastolic dysfunction. This study demonstrate that
damaged heart function is tightly associated with Tnl levels in the heart.