In this study, the influence of fluid mixing on temperature and geochemistry of hot spring fluids is investigated. Yellowstone National Park (YNP) is home to a diverse range of hot springs with varying temperature and chemistry. The mixing zone of interest in this paper, located in Geyser Creek, YNP, has been a point of interest since at least the 1960’s (Raymahashay, 1968). Two springs, one basic (~pH 7) and one acidic (~pH 3) mix together down an outflow channel. There are visual bands of different photosynthetic pigments which suggests the creation of temperature and chemical gradients due to the fluids mixing. In this study, to determine if fluid mixing is driving these changes of temperature and chemistry in the system, a model that factors in evaporation and cooling was developed and compared to measured temperature and chemical data collected downstream. Comparison of the modeled temperature and chemistry to the measured values at the downstream mixture shows that many of the ions, such as Cl⁻, F⁻, and Li⁺, behave conservatively with respect to mixing. This indicates that the influence of mixing accounts for a large proportion of variation in the chemical composition of the system. However, there are some chemical constituents like CH₄, H₂, and NO₃⁻, that were not conserved, and the concentrations were either depleted or increased in the downstream mixture. Some of these constituents are known to be used by microorganisms. The development of this mixing model can be used as a tool for predicting biological activity as well as building the framework for future geochemical and computational models that can be used to understand the energy availability and the microbial communities that are present.
2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.