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Articles 1 - 8 of 8
Full-Text Articles in Engineering
Modeling Renal Function During Pregnancy, Christina A. Valtierra
Modeling Renal Function During Pregnancy, Christina A. Valtierra
REU Final Reports
The main goal of this research project is to build a computational model that illustrates the main processes in renal function during pregnancy. The analysis of how pregnancy affects all the factors that take place within the kidney will allow for a better understanding of how pathologies like proteinuria, hypertension, and glomerular endotheliosis develop. This model is a small part of a more complex model that showcases the complete pathophysiology of preeclampsia.
Agent-Based Activity Generation Of Runners For City Infrastructure Planning, Quang Le
Agent-Based Activity Generation Of Runners For City Infrastructure Planning, Quang Le
REU Final Reports
Since the pandemic started, many gyms and indoor classes have been shut down to mitigate the spread of Coronavirus. Many people have been forced to get onto pavement streets to get some fresh air while running around and coping with the new reality. There are over 60 million runners in the U.S., and that number is growing rapidly during this time without any sign of stopping once life gets back to normal. In this project, an agent-based model has been developed to generate a set of routes that runners would take in their daily run in a neighborhood of Portland …
Finding Lonely Routes For Runners And Bikers, Ethan T. Spicher
Finding Lonely Routes For Runners And Bikers, Ethan T. Spicher
REU Final Reports
With COVID-19 raging around the world, personal health is even more important to a lot of people. One way to maintain good physical and mental health is to exercise according to Deslandes [2]. When exercising it may be important to make sure that you are running/biking on trails that are less populated than others, as well as taking into account the distance. This can be solved by creating an algorithm that allows the user to choose the starting and end point, and the algorithm will then find the optimal path between the two points with the distance and popularity of …
Numerical Algorithms For Solving Nonsmooth Optimization Problems And Applications To Image Reconstructions, Karina Rodriguez
Numerical Algorithms For Solving Nonsmooth Optimization Problems And Applications To Image Reconstructions, Karina Rodriguez
REU Final Reports
In this project, we apply nonconvex optimization techniques to study the problems of image recovery and dictionary learning. The main focus is on reconstructing a digital image in which several pixels are lost and/or corrupted by Gaussian noise. We solve the problem using an optimization model involving a sparsity-inducing regularization represented as a difference of two convex functions. Then we apply different optimization techniques for minimizing differences of convex functions to tackle the research problem.
Analyzing Disparities In Ecosystem Services In U.S. Cities: The Relationship Between Tree Cover And Socio-Demographics, Katherine V. Cendrowski
Analyzing Disparities In Ecosystem Services In U.S. Cities: The Relationship Between Tree Cover And Socio-Demographics, Katherine V. Cendrowski
REU Final Reports
It is a generally accepted fact that trees, and vegetation in general, provide many benefits to human beings. What has not been so extensively studied is how those benefits may be distributed across the United States. This research project aims to study that distribution by modeling and analyzing the land use data of US cities and the socio-demographic data available. We are looking specifically at tree cover as presented in the National Land Cover Dataset (NLCD) in order to determine what the general demographics are of those people that live in closer proximity to trees. We are also looking at …
A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne
A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne
REU Final Reports
As wildfires surge in frequency and impact in the Pacific Northwest, in tandem with increasingly traffic-choked roads, personal exposure to harmful airborne pollutants is a rising concern. Particularly at risk are school-age children, especially those living in disadvantaged communities near major motorways and industrial centers. Many of these children must walk to school, and the choice of route can effect exposure. Route-planning applications and frameworks utilizing computational shortest paths methods have been proposed which consider personal exposure with reasonable success, but few have focused on pollution exposure, and all have been limited in scalability or geographic scope. This paper addresses …
Deciphering The Rules Of Cell-To-Cell Coupling By Molecular Modeling And Simulation, Linda D. Lee
Deciphering The Rules Of Cell-To-Cell Coupling By Molecular Modeling And Simulation, Linda D. Lee
REU Final Reports
Intercellular communication is vital for quick adjustments and maintenance for cell function and development. Gap junctions are membranes channel proteins that enable this direct communication between adjacent cells throughout the body. The compatibility of connexins (Cx), which make up a gap junction, determines whether a gap junction can form. Though many studies show which connexins are compatible, the molecular basis is not known (Bai & Wang, 2014). Through computational modeling, we identify the residues that energetically contribute most favorably at the docking interface of homotypic and heterotypic combinations of Cx43, Cx46, and Cx50 gap junctions. However, due to instability of …
Associative Learning In Biochemical Networks, Yasmin S. Sepulveda
Associative Learning In Biochemical Networks, Yasmin S. Sepulveda
REU Final Reports
Emerging evidence suggests that biochemical networks can be modeled by exploiting their ability to learn through associative learning. This type of learning in biomolecular structures gives it a the advantage to be able to be computationally model, and condition. Associative learning in biochemical networks is a developing area of study that once understood, can further develop diagnostic applications, and be used as tools for data analysis. Although it is a open ended project the motive of this research was to find the the best method of association learning being used in current work. After reading current work three associative learning …