2020 Abstracts

Vasquez, Cesar; Dockstader, Patrick; Havertz, Brett; Phillips, Justin (Dixie State University)
Faculty Advisor: Chellamuthu, Vinodh (Dixie State University, Mathematics)

For any business, understanding the customer’s behavior is vital to maximizing income and minimizing costs. Our work aims to create an algorithm that analyzes the historical data from the customers and determines the target customers in an optimal way. We take on a data set from a transmission shop in California and seek out which factors produce higher potential for client value. We created a mathematical model that classifies the clients as low, medium, or high potential using this historical data. Furthermore, we demonstrated the model utility using the transmission shop’s data to compute the correlation of paying customers and customer history. The correlations are then used to create a conditional probability distribution which served to predict an expected rating score. Moreover, our results are validated by comparing the predicted ratings with the actual ratings in varying train and test cases from the data set. Our results show that the proposed algorithm is fast, simple, and intuitive, which could be utilized by the transmission shop in the future.

Waldron, Connor; Moley, Laura; Isom, S. Clay (Utah State University)
Faculty Advisor: Isom, S. Clay (College of Agriculture and Applied Sciences; Animal, Dairy, and Veterinary Sciences Department)

In vitro maturation (IVM) is a process that immature oocytes undergo before in vitro fertilization is performed. During IVM, immature oocytes are extracted through aspiration from follicles and receive the necessary hormones to resume meiosis in culture. Success rate of IVM is significantly lower compared to in vivo maturation of oocytes. Oocytes selected for IVM are extracted from small ovarian follicles (1-3mm), which are 4-6 weeks away from complete maturation and subsequent ovulation. During that period, the DNA of the oocyte is undergoing the process of DNA methylation, the addition of a methyl group to cytosines within a CpG context. DNA methylation is an epigenetic change that causes modification to gene expression where methylated gene promoters turn off gene expression. Proper oocyte gene expression is very important in the development of a healthy embryo. Incomplete methylation of aspirated oocytes may be another factor contributing to the low success rates of IVM. We hypothesize that there is a difference in the amount of methylation between oocytes from small ovarian follicles that are further from natural ovulation and oocytes from large ovarian follicles which are developmentally closer to ovulation, with higher levels of methylation in oocytes from large ovarian follicles. To test our hypothesis, large porcine ovarian follicles (7mm and larger) and small porcine ovarian follicles (1-3mm) will be aspirated for ovaries. The oocytes will be stained the two stains, one to visualize the nucleus of the oocyte indicating the presence of DNA and the other to visualize DNA methylation. Fluorescent images will be taken of the oocytes, and the small and large follicle oocyte groups will be compared for genome wide methylation levels.

Mark Langeveld (University of Utah)
Faculty Advisor: Langeveld, Mark (University of Utah, Engineering)

Introduction:

The risk of getting type 2 diabetes has been widely found to be associated with lower socioeconomic position across countries. Not only the financial burden but also the clinicians often having the long waitlists for one-on-one assessment of chronic disease patient's behavior makes it difficult for timely treatment and monitoring supplies. Among the top 10 diseases that are causes of death, Diabetes is the most self-manageable chronic disease. Type 2 diabetes patients often require insulin therapy as well as self-managing on eating well and exercising. A mobile app can be applied as a self-managing mechanism that treats chronic complications of diabetes. I will describe my work to analyze five commercially available mobile apps that are effective in improving diabetes-related outcomes.

Method:

I analyzed with technology reviews of iterative mobile app design of each mobile app(Glucose Buddy, Diabetes care4Life, Diabetes Diary, BlueStar Diabetes, Gather Health) and reviewing comments from peer and public review. I organized the findings by test process with diabetes patients through three categories for this report: 1. App features (on which platform that the app is available, what the app does, cost, etc.) 2. App usability and quality of tracking presented as an average of three scores given by the University of Utah healthcare researchers 3. Summary of the evidence from the evaluation of each category of patients who are motivated and who were not: monitoring glycemic control, glucose control, blood pressure, HbA1c improvement, weight, and diabetes treatment satisfaction

Result:

The record comprised 30 patients, of which 10 completed the mobile app module for 6 weeks. Demographics were similar for users and nonusers. Of the application users, the behavior improvement of pre-test and posttest scores were better for users compared with non-users (+1.8%). Of the users, 92% reported that the application had significant improvement (p < 0.05) in an outcome compared with HbA1c and glycemic control. The usability score of each app evaluated by healthcare researchers was (Glucose Buddy: 72.3 (out of 100), Diabetes care4Life: 45, Diabetes Diary: 16, BlueStar Diabetes: 85, Gather Health: 60) Without additional support from a health care provider, 5 mobile apps demonstrated an improvement in fasting blood glucose, 2-hour post-breakfast blood glucose, diabetes knowledge, and self-care behaviors compared with controls.

Conclusion:

I have analyzed and created a prototype of a mobile app that fills the gap between efficacy, cost, and features from the limited statistical evidence. Patients were satisfied with the use of the mobile health app for Diabetes, and the use of the program significantly improved their behavior and knowledge retention. Tailoring the traceable evaluation of mobile app to patient preferences and needs and updating the tools could empower and guide the patients to effective mobile apps in improving diabetes outcomes.

Hunt, J. Porter; Wilding, Kristen M.; Barnett, R. Jordan; Robinson, Hannah; Soltani, Mehran; Cho, Jae; Bundy,Bradley C. (Brigham Young University)
Faculty Advisor: Bundy, Bradley (Brigham Young University, Chemical Engineering)

In this research, a cell-free protein synthesis (CFPS) platform is used to create a biosensor aimed towards detecting concentrations of amino acids or enzymes in a sample. A CFPS biosensor is an effective method to detect these molecules due to its rapid, high-throughput nature. Additionally, the biosensor analysis can be done on-site. Potential applications of this assay include monitoring dietary health, adjusting cancer treatments, and the diagnosis of the onset of certain disease.

Howlett, Dylan (Brigham Young University)
Faculty Advisor: Fullwood, David (Brigham Young University, Mechanical Engineering); Bowden, Anton (Brigham Young University, Mechanical Engineering)

Identifying motion of the human spine, and irregularities in movement can be vital for diagnosing a back injury patient. Modern methods of identifying injuries include an expensive X-ray or MRI scan, simple inspection by a trained professional, or very primitive two point instruments. We have developed a strain gauge with high flexibility that is able to withstand repeated high-strain. This gauge is able to properly measure the motion of the lumbar spine, allowing health professionals and patients to monitor the state of their back. This paper presents a survey of different manufacturing methods for these gauges, including screen printing, extrusion and compression molding. The gauges are analyzed for their piezoresistivity vs strain and optimized for the desired application.

Keyser, Michael A.; Jiang, David; Timmins, Lucas H. (University of Utah)
Faculty Advisor: Timmins, Lucas (University of Utah, Biomedical Engineering)

Coronary heart disease is one of the leading causes of death in the United States and is caused by a buildup of atherosclerotic plaque blocking blood flow in a coronary artery. Stents are used to restore blood flow to affected regions by reopening the blocked artery. Failure among stents is common, and a 3D reconstruction of a stent can be used to investigate the cause of failure. We have previously established a 3D stent reconstruction technique that utilizes optical coherence tomography (OCT) and micro-computed tomography imaging data to provide a high-spatially resolved stent reconstruction. However, analysis revealed that each OCT image was subjected to a curvature induced rotational drift due to the imaging process. Thus, the purpose of this study was to examine the relationship between vessel curvature and OCT image drift. Four separate channels of constant curvatures, 0, 1/60, 1/30, and 1/20 mm^-1 were drilled out of Delrin using a CNC machine resulting in a 'U' shaped channel. Each channel was imaged, and the rotational drift for the curvature of that channel was determined by calculating the average change in image orientation. The orientation of an image was the angle of the top edge of the 'U' with respect to a horizontal line. Results demonstrated the rotational drift was -0.172, -0.598, -0.927, and -1.124 degrees for curvatures of 0, 1/60, 1/30, and 1/20 mm^-1 .We discovered the relationship between the curvature of the channel and the rotational drift of an image to be _=-19.12_-0.227 where _ is the curvature of the channel _ is the rotational drift of the OCT image in degrees. In conclusion, we demonstrated that there is a linear relationship between curvature and OCT image circumferential drift that can be used to improve the overall accuracy of the reconstruction.

Parkinson, Bethany; Andrews, David; Magleby, Spencer (Brigham Young University)
Faculty Advisor: Magleby, Spencer (Brigham Young University, Mechanical Engineering)

Increasing worldwide urbanization is leading to a rising population of people living in apartments. Apartments typically have short leases, which lead to a high turnover rate, or number of renters that move in per year. For example, the 2018 turnover rate in New York City was 30.5%. People who move this often usually buy cheap furniture each time they change apartments, because carrying furniture on public transportation is impractical. The goal of our research is to create furniture that allows people who move often to avoid re-purchasing furniture. This goal leads to three design requirements. First, the furniture should be easily collapsed and deployed. This permits the furniture to be conveniently stored and transported. Ideally, the furniture could be deployed with one hand. Second, the furniture should be inexpensive, both in manufacturing processes and material selection. Lastly, the furniture should be aesthetically pleasing. We have utilized origami as a method to achieve these design objectives, because it can be deployed in one motion.

There are significant challenges to designing and implementing origami-inspired furniture. For example, any joints between the legs, seat, table, and back of the furniture need to allow not only for the furniture to be stable in its deployed state, but also to be flat in its non-deployed state. Additionally, the employed joints must account for the thickness of the material. Each type of joint that is adaptable to thick materials was therefore considered and analyzed in the specific loading situation of a chair. Using these criteria and three unique types of joints, a variety of chairs were conceptualized. After prototyping, each type of chair was expanded to create an entire family of furniture, including a table, stool, and couch. The principles and design approaches developed in this project have generated origami-inspired furniture that is easily transportable, functional, inexpensive, comfortable, and aesthetic.

Howell, Ashley (Brigham Young University)
Faculty Advisor: Killpack, Marc (Ira A. Fulton College of Engineering, Mechanical Engineering); Salmon, John (Ira A. Fulton College of Engineering, Mechanical Engineering)

Human-robot co-manipulation of objects to complete specific tasks, such as carrying a stretcher in a search and rescue operation, is an open ended problem in the foreseeable future. Since many motions of the shared object, like rotation and translation, initially feel identical, it can create disagreement between the human and the robot on where to move the object. Programming a robot to determine what kind of movement a human is suggesting and acting accordingly requires extensive data on how humans interpret such communications. This project focuses on designing and constructing a stretcher like object that will be used in a series of experiments in which two humans will carry it through a random arrangement of obstacles. Sensors on the object will gather data on the different ways humans move and interact with it through forces and torques. Indications of these movements will be used to instruct a robot on how to "follow" with the goal of adding no additional cognitive load to the human leader.

Wheeler, Isaac; Lignell, David (Brigham Young University)
Faculty Advisor: Lignell, David (Brigham young University, Chemical Engineering)

Turbulence remains one of the great unsolved problems of classical physics; for this reason it remains one of the primary focuses of study in computational fluid dynamics. Numerically, the governing equations for fluid flow can be solved, but to accurately simulate a turbulent flow (as found in combustion, drag calculations, and a variety of other situations) the equations must be solved at small enough length scales to describe very small structures present in turbulent phenomena. Hierarchical parcel swapping (HiPS) is a proposed model for turbulent mixing; the model is computationally cheaper than a numerical simulation at similar length scales, and allows for variation in diffusion coefficients (Schmidt number Sc). In my presentation I will discuss the implementation of HiPS and its agreement with established turbulent phenomena.

Bundy, Bradley C; Mills, Heather; Nelson, Andrew (Brigham Young University)
Faculty Advisor: Bundy, Bradley (Brigham Young University, Chemical Engineering)

Many advantages are associated with cell-free protein synthesis. It is the fastest way to obtain a protein from a gene, and large amounts can be produced.

A common challenge in cell-free protein synthesis is inconsistency in reaction results, when protein yields appear to vary significantly between trials of the same reaction. Correcting this problem by focusing on and adjusting laboratory technique was the platform of this specific research project. Such adjustments aimed to increase the precision with which reagents were measured and the accuracy of the spectrophotometer results; and to decrease potential error created by air bubbles and non-uniformly mixed reagents.

Overall, amounts of protein yield became more consistent as procedural steps were performed with greater focus on laboratory technique. These results indicate that adjusting laboratory technique could potentially help to increase consistency in yield amounts and reduce error in cell-free protein synthesis reactions. Further direction for the research includes using the improved and more accurate CFPS reactions to produce protein therapeutics, which is used in the treatment of various diseases.

Brad Bundy; Nelson, Andrew; Welton, Meagan (Brigham Young University)
Faculty Advisor: Bundy, Brad (Brigham Young University, Chemical Engineering)

Cell-free protein synthesis (CFPS) is the process of making proteins without the limiting environment of a cell. The CFPS system allows us to modify and engineer proteins in ways that have not been done before. This technology has the potential to significantly impact the fields of protein therapeutics, unnatural amino acid insertion, and biosensors. Our research looks into optimizing the process of CFPS. Specifically, we want to understand what the impact of adding bubbles to a cell-free reaction is on CFPS yields. We want to know if adding bubbles to the CFPS mixture prior to incubation will increase the oxygenation of the reaction and affect protein production rates. This knowledge will help us optimize the CFPS process for future applications.

Jensen, Sally; Lignell, David (Brigham Young University)
Faculty Advisor: Lignell, David (Ira A. Fulton College of Engineering, Chemical Engineering)

Radiative heat transfer is central to many chemical engineering processes. Turbulent combustion accounts for 80% of the world's energy. Understanding radiative heat transfer is important for efficient design, regulating pollutant emissions, and doing hazard analyses of these processes. Radiation depends on temperature as well as local composition fields. It is important for combustion because it affects heat transfer to surrounding environments. This in turn impacts fire spread in wild fires as well as heat transfer in power plant boilers and other such applications. Radiation also directly affects the temperature field. The temperature field in turn feeds back to the radiation and impacts the formation of pollutants, such as soot, NOx and other species. Modeling is difficult because computing the absorption coefficient depends on the spectral properties of molecules. Computing these requires millions of spectral bands, which is too expensive to compute for normal applications. A common method that is currently used to predict radiation is the Weighted-sum-of-gray-gases model. Doctors Solovjov and Webb developed a new method called the Rank Correlated Integration of the Spectral Line Weighted-sum-of-gray-gases (rcSLW) model. It is a complex model that is difficult to implement, but it is accurate. It has been implemented in python and in C++. The model has been provided on github to allow for easy access by the community. We will present an overview of the rcSLW model and code interface as well as show selected results applied to systems of interest with respect to combustion.

Wheeler, Jesse; Bean, Brennan; Schwartz, Sam; Christensen, Randy; Moon, Kevin (Utah State University)
Faculty Advisor: Moon, Kevin (College of Science, Mathematics and Statistics Department)

Unmanned aerial vehicles (UAV) often rely on GPS for navigation. GPS signals, however, are very low in power and are easily jammed or otherwise disrupted. Precise measurements of initial position and motion at the time of GPS signal loss would allow navigation for UAV navigation in GPS denied regions. This work presents a method for determining the navigation errors present at the beginning of a GPS-denied period by utilizing data from a synthetic aperture radar (SAR) system. This is accomplished by comparing an online-generated SAR image with a reference image obtained a priori. The distortions relative to the reference image are learned and exploited with a convolutional neural network to recover the initial navigational errors, which can be used to recover the true flight trajectory throughout the synthetic aperture. Our neural network approach outperforms traditional navigation recovery methods as well as other machine learning models.

Pulsipher, Kyle; Despain, Dillon; Wood, David; Fullwood, David T.; Bowden, Anton E. (Brigham Young University)
Faculty Advisor: Bowden, Anton (Brigham Young University - Ira A. Fulton College of Engineering, Mechanical Engineering); Fullwood, David (Brigham Young University - Ira A. Fulton College of Engineering, Mechanical Engineering)

Design and Testing of Flexible Wiring Systems in Biomechanical Devices
Kyle Pulsipher, Dillon Despain, David Wood, David T. Fullwood, Anton E. Bowden
A major challenge to wearable electronic devices is the implementation of required wiring and hardware that can accommodate large deformations and strain. For example, several current biomechanical engineering projects utilize a nanocomposite, wide-range, wearable strain sensing technology developed at BYU. Our research challenge was to create a wearable system of conductive links between a multi-sensor system and a microcontroller, while keeping the system low-profile, inexpensive, and functional when experiencing strains of at least 60%.

Several solutions were hypothesized and tested, including experimental silicone composite solutions with dispersed conductive nanofillers. Mechanical solutions were also contemplated, in the form of geometrically positioning a traditional wire in such a way that it could strain the required amount.

Our final solution utilizes a fine-gauge wire shaped into a sine curve, whose period and amplitude are controlled, such that the stretched length (the arc length of the sine curve) is a required strain factor longer than the period of the function. The wire is coated in an elastic silicone body that maintains the wire at the unstrained shape and length. Our implementation provides 130% of the wiring system and accommodates 16 independent sensor connections.

The wiring system is positioned in such a way that the wires are hidden in the artistic form of the sensing system. This electrical structure is both highly practical and aesthetically pleasing.

Bailey J. McFarland, Cheng Chen, Asfand Yar Khan, Harley Cragun, Justin A. Jones and Yu Huang (Utah State University)
Faculty Advisor: Huang, Yu (College of Engineering, Biological Engineering Department); Jones, Justin (College of Science, Biology Department)

Neurological diseases are the largest cause of disability worldwide. Tissue engineering approaches are desirable as they can be used to treat these diseases by replacing damaged and non-repairable brain tissues with engineered materials. Electrospinning of bioactive molecules is a promising materials engineering method to culture neurons and support nervous tissue growth. This suitability for neural cell culture is due to the electrospun material's fibrous and porous structure that mimics the structure of the extracellular matrix. The electrospinning process also allows for the controllable development of complex 3D cell culture, which is key to the creation of viable neural connections. In addition, the formation of both aligned and unaligned layers of fibers allows for intricate guiding of cell morphology that improves outcomes in neural cultures. Finally, the choice of appropriate bioactive materials can improve neurological cell culture. Spider silk, a bioactive protein, contains sequences of amino acids that support nerve cell binding and scaffolding, in complement to which, chitosan fibers have been shown to promote the healthy growth of neural cells.

This project develops a novel method of electrospinning a fibrous scaffold for neural tissue engineering from solutions of recombinant spider silk protein and chitosan. Preliminary results in this study are promising and add to the body of research in neural tissue engineering. These bioactive materials paired with the morphological benefits of electrospinning allow an opportunity to create a substrate that can improve stem cell differentiation into healthy neurons.

Oldham, Keturah; Lignell, David; Stephens, Victoria (Brigham Young University)
Faculty Advisor: Lignell, David (Brigham Young University, Chemical Engineering)

Soot is an important but computationally expensive aspect of modeling combustion. To thoroughly predict the way that soot acts, it is necessary to know the number and size of every soot particle in a situation. Since that is clearly not practical, there are a variety of methods to approximate the soot size distribution: the method of moments, assuming monodispersion, and a sectional method. To facilitate the incorporation of these soot models into various applications, a C++ library including these models was created. As part of this C++ library, a sectional model was implemented. This splits the overall soot size distribution into discrete sections, then calculates the soot chemistry involved with these sections. To implement this into the library, a partial sectional model (including only coagulation) was first implemented in Python and compared to verified values. This model was then written in C++, expanded to include the various other soot mechanisms (e.g., growth, oxidation), and incorporated into the larger soot library. The sectional model as part of the soot library will be tested for validity. In summary, to enable the combustion simulation community to more easily simulate soot, a soot library that includes several models was created and expanded to include a sectional model. The use of these models enables modeling to be more accurate due to the easy inclusion of soot in a comparatively computationally inexpensive manner.

Liu, Xintong (University of Utah)
Faculty Advisor: Ji, Mingyue (College of Engineering, Department of Electrical and Computing Engineering)

One of the significant challenges of the machine learning faces today is how to deal with the privacy constraint of the user in a large-scale and distributed communication network. A myriad of data produced by billions of distributed devices need to be sent into the central cloud and to be managed, but what happens if the user does not want to send his/her data to the central cloud. It is reasonable that many users expect the data they send is being protected and maintain privacy. So, we are thinking about whether it is possible to create an individual machine learning in the application of Federated Learning so that the user's data will be protected from the privacy constraints. In this case, the raw data will not be known by anyone except the owner of these data. So, there would be all unknown input data pass through the private machine learning model, and the generated result, which is still hidden data will be sent back to the user. The main topic of the presentation is the designed codes which produces a private configuration with non-linear computation for the learning model and enable privacy constraints for the user's data.

Moulton, Benjamin (Utah State University)
Faculty Advisor: Hunsaker, Doug (College of Engineering, Mechanical and Aerospace Engineering Department)

A morphing allows for more efficient controlled flight. Morphing wings induce a continuous deflection of control surfaces. Deflection can be caused by compliant mechanisms and composite materials. Factors contributing to efficient morphing wings range from a continuous morphing trailing edge to stiffness and flexure. Wing stiffness supports aerodynamic loading. Wing flexure supports transverse deflection, or twist of the wing trailing edge. Graduate students in the USU Aerolab have written an algorithm to optimize where these deflections should occur on the wing. The student seeks to build a morphing wing to demonstrate the success of the optimization code. Different manufacturing methods are explored. 3D printing provides the most promising results. The 3D printing of thermoplastic materials allows for shear and deflection.