Fall Internship and Research Symposium (FIReS) Presentation Abstracts

Adaptive and assistive technology is an important and ever growing field that allows for technological devices to greatly affect individual’s daily lives for the better. The GoBabyGo program allows for children to use modified ride-on cars to better interact with their environment in an independent and therapeutic way. The goal of this project is to work closely with occupational therapists to modify cars for children with conditions such as cerebral palsy and spina bifida for their individual needs. In order to further our understanding, we researched common modifications that have been made to ride-on toys in the past, including electrical modifications, physical support modifications, and the integration of different existing assistive devices. We also have met with the individual kids who applied for these modified devices, and worked closely with the occupational therapists to evaluate and assess each child’s individual needs in order for their car to have the greatest impact. We will use this information to then modify cars for each child specifically, and present the cars to them on a GoBabyGo build day, where they can test out the cars and we can make any modifications if necessary. This project integrates both bioengineering and occupational therapy in order to bring assistive technology into the lives of those who need it the most.

According to the W.H.O., infectious diseases account for three of the top ten global causes of death. Antimicrobial drug discovery surged in the mid-twentieth century but has sharply declined in recent years. At the same time, antimicrobial-resistant “superbug” infections are on the rise. Plants produce a robust supply of novel metabolic compounds including many antimicrobial agents. However, with the advent of modern antibiotic drugs, natural plant-derived antibiotic sources have largely been left unexplored. Therefore, our work is focused on screening poorly explored medicinal plants in the hopes of discovering novel antimicrobial drugs. To do this, we have been testing extracts of plants found in the Valpo medicinal garden for their effects against twelve microorganisms of interest. To date, methanolic and hexane extracts of aerial, reproductive, and root portions of twelve plants have been screened, with five plants showing especially promising activities. Both raspberry leaf and yarrow flower methanol extracts were seen to inhibit growth of Gram-positive and Gram-negative bacteria, with little activity against the fungal organisms tested. Chokeberry leaf methanol extracts had similar trends, but with less activity overall. Additionally, both lavender and raspberry root methanol extracts demonstrated broad spectrum antimicrobial activity, while yarrow, chokeberry, and calendula root methanol extracts showed similar trends, but with less overall activity. We have begun separating several promising extracts using column chromatography techniques to determine the specific antimicrobial compounds via analytical chemistry techniques. These data highlight the importance of plants as an invaluable pharmaceutical resource at a time when antimicrobial drug discovery has plateaued.

In the colon, the Cl-driven fluid secretion is dependent on the basolateral Na+ K+ Cl- cotransporter 1 (NKCC1). Activation of protein kinase C (PKC) causes the internalization of NKCC1. However, the PKC-dependent signal causing NKCC1 internalization is not known. We hypothesize that ubiquitin may be the signal responsible. We used Madin-Darby Canine Kidney (MDCK) cells expressing eGFP-tagged NKCC1 to monitor its internalization using fluorescent microscopy. We used phorbol 12-myristate 13-acetate (PMA) which activates PKC and PYR-41 (dissolved in DMSO) to inhibit ubiquitin ligase. Finally, we combined both PYR+PMA to test whether inhibiting ubiquitin ligase will reduce the effect of PKC on NKCC1 internalization. We used FIJI to count the number of internalized NKCC1 vesicles and the number of nuclei. Our results, calculated as vesicles per cell, were as follows: control (3.6±0.6 vesicles/cell, n=18), DMSO (2.4±0.5, n=18), PMA (12.6±3.7 vesicles/cell, n=12), PYR (5.6±0.8 vesicles/cell, n=30), and PYR+PMA (4.5±0.4 vesicles/cell, n=18). A one-way ANOVA found a significant difference between our conditions (p=<0.001). A Tukey’s post-hoc test showed that PMA significantly increased internalization compared to control (p=<0.001), PYR+PMA had significantly less internalization than PMA alone (p=<0.001), and control vs PYR was not significant (p=0.7). Our results suggest that ubiquitin may be the signal responsible for the internalization of NKCC1 during PKC activation.

About 353 million tons of plastic waste is generated each year. Of that number about 23% is mismanaged, getting leaked to the environment through various means. While in the environment these plastics can get oxidized by exposure to UV radiation from the sun. In order to determine if this oxidation was topical, or if it occurred throughout the entire sample, we gathered plastics from Indiana Dunes State Park and Miller Beach. This was done by sieving the sand and collecting the plastic that remained behind. These samples were then analyzed using infrared (IR) spectroscopy and sorted by polymer type, with the majority being either polyethylene or polypropylene, then into two categories: oxidized (weathered) and unoxidized (clean) plastic. Plastic pieces from each of the four categories were then used to create nanoplastic mixtures. This was done by mixing a plastic sample in a vial with 15 mL of distilled deionized (DDI) water and 45 µL of n-dodecane. The plastic sample was then removed from the mixture and dried in the oven at 60ºC overnight. This process was repeated 4-6 times for each plastic sample, with the sample being analyzed using IR after each solubilization. The carbonyl index was used to measure the level of surface oxidation for the sample after each solubilization. The IR data showed that the carbonyl index decreased after each solubilization. Data from analysis using RAMAN spectroscopy also showed a decrease in surface oxidation.

Air quality makes up a large portion of pollution. An important metric is particulate matter (PM), which can vary in sizes less than one micron and greater than ten microns and is measured in micrograms per cubic meter. Time was dedicated to measuring the concentration of PM using low-cost PurpleAir (PA) sensors in Northwest Indiana (NWI), locating the particles origins, reading articles and papers for appropriate conversion factors (CF), and running experiments on the PA sensors. The PA sensors take one data point every ten seconds. That equates to more than three million data points per sensor per year, while multiple PA sensors are operating in NWI. Previous work has relied on Excel for generating monthly and yearly plots and distributions of PM concentration. Utilizing Python for data processing has significantly reduced the time to get to the analyze step. Other issues surrounding the PA sensors is whether they are providing a correct and unbiased concentration to other commercial and scientific grade instruments. This has led to searching and optimizing for the best CF equation(s) and running high-grade sensors alongside PA sensors. Many questions surround the PA instruments whether they are a high-quality tool for air quality research. Comparing PA data alongside the Indiana Department of Environmental Managements sensors is vital and has revealed issues in IDEMs lack of data points. Air quality is also being measured by TEMPO, a satellite currently measuring NO₂, O₃, and formaldehyde hourly across the US from Canada to Mexico.

Bacterial and fungal infections are among the greatest causes of death worldwide. With the development of more adept antimicrobials comes resistant superbugs. Because of this, the need for new and alternative pathways for fighting these diseases is both necessary and prevalent. Previous students have worked with extracts of the Argemone mexicana plant to identify key molecules that give the plant its antimicrobial properties. Our work centers around berberine, one of the key molecules, and designing and synthesizing variants. The goal is to create and test bioactive molecules in order to discover new, more potent, antimicrobial drugs. Through different coupling reactions, reductions, aminations, etc. we have created new variants of berberine. We have tested different pathways and reaction conditions to enhance our product and yield. The reactions we perform will lead us to the development of new variants and new antimicrobial drugs.

Indoor air quality plays a crucial role in human health and wellbeing, as personal exposure increases in areas where people spend a lot of time, like inside their homes. This study utilized solid-phase microextraction (SPME) as an efficient and non-invasive passive sampler to absorb analytes from indoor air. Coated with polydimethylsiloxane and divinylbenzene, SPME fibers are used to capture a range of volatile and semi-volatile organic compounds found in indoor air, some of which being phthalates and toluene. The fibers were employed in residential areas across Northwest Indiana near areas of greater industrial presence. The fiber is then retracted and set into the injection port of gas chromatography-mass spectroscopy (GC-MS) to quantify and identify pollutants, with some being presumptively identified as alkanes (hexadecane, octane, decane) and alcohols (2-n-propyl-1-heptanol, 2-decanol). The sensitivity to volatile organic contaminants, cost-effectiveness, and sustainability make SPME fibers a promising method for frequent indoor air quality monitoring and assessment, as well as offer the potential of sampling outdoor air to compare pollution levels inside and outside homes, and grow a greater knowledge base for personal exposure to hazardous air pollutants.

Temporal knowledge graphs are one of the main subjects in research due to their abilities to detail events and the dates of which these events occur [2] [3] [4] [5] [6]. These graphs are useful in studying how historical events occur within a certain timespan [2] [3] [4] [5] [6]. This paper will delve into the implementation process of Neo4j to study how to use temporal knowledge graphs to observe the characteristics of protests [2] [3] [4] [5] [6]. Furthermore, the paper will describe the results and conclude with a discussion about the next tasks to take to further our study on protest behaviors [2] [3] [4] [5] [6].

During the Summer of 2024, I served as a Communications Intern at Grünewald Guild in Leavenworth, WA as part of my placement as a member of the CAPS Fellows Program. I have exponentially grown to further refine my vision for my vocation as I approach the final year of my academic career at Valparaiso University. The mission of the guild is highlighted through the three core values of art, faith, and community and I initially thought I would gravitate my attention mostly towards the value of art. Surprisingly, that was not that case and I started to primarily focus upon the aspect of community involvement and how it uniquely manifests itself at this non-profit organization.Through my daily tasks at Grünewald Guild, I was able to gain this sense of community through doing morning check-ins to supply the studios with art supplies, sitting with the students and guest artists at mealtimes, and engaging in their matins and vespers services. There is one simple question that has been asked many times throughout the vast majority of mealtimes and miscellaneous lulls of leisure and, at first, I thought that this question seemed very superficial and not exceptionally meaningful. Due to the clientele being art lovers, I have learned that this question has a lot more gravity associated with it than I originally expected. The question is, “What is your favorite color?” and an individual’s answer to this question acts as the key to learning a lot about them and their outlook on life.

This past summer I participated in the Calling and Purpose in Society (CAPS) program, interning at Heartland Alliance, a refugee resettlement organization in Chicago. I was challenged to transform my expectations about the pressure that faces Heartland and the refugees it works with, as well as the kind of role Heartland plays in the lives of newly arrived refugees in Chicago. I learned about the challenges that refugees face during their first months in the country, while simultaneously experiencing the obstacles that Heartland confronts as a non-profit in refugee resettlement. Neither the staff at Heartland nor the refugees have room for excuses – only solutions, as the short acclimation window that refugees have in the United States carries consequences that wait for no one. To support the refugees’ acclimation, Heartland utilizes a ‘strength-based approach’, aiming to inspire each individual to see their own agency in determining their life trajectory and success in their new home. The summer presented me with opportunities to be part of solutions to real problems, which was a unique position for an intern. I was asked to navigate situations that had real-life consequences for other people. Through observation and experience, I cultivated knowledge about large issues on a micro scale, while improving my adaptability and communication abilities. It was valuable to experience how Heartland operated to overcome demanding circumstances, and it inspired me to create change beyond what they can achieve as a non-profit organization as I go forward to pursue a degree in public policy.

Nuclear physics students and faculty at Valparaiso University worked on two experiments: the STAR Experiment, and the nEDM Experiment. A major goal of the STAR Experiment at Brookhaven National Laboratory is understanding the gluon’s contribution to the proton’s spin. A proton contains quarks and gluons whose individual spins contribute to an overall spin of ½ ?. At the Relativistic Heavy Ion Collider (RHIC) high energy polarized proton beams are collided, producing a large number of neutral pions (?⁰) and eta (?) mesons. These particles promptly decay into two photons whose energies and positions are measured by the Endcap Electromagnetic Calorimeter (EEMC). Pairs of photons are combined to calculate the invariant mass of the particles from which they decayed. Our mission was to perform quality assurance on the data taken in 2013 and 2015 to ensure it is good for further analysis. Our quality-assured data will then be used to calculate the asymmetry of ?⁰ and ? particles produced in the polarized proton beam collisions. These calculations can then be used to determine the gluon’s contribution to the proton’s spin. Results from the quality assurance of the data will be presented.

The neutron Electric Dipole (nEDM) experiment at Los Alamos National Laboratory is designed to search for the nEDM at the level of 10^-27 e*cm. The experiment is enclosed in a magnetically shielded room (MSR) to null external magnetic fields. A shielding factor characterizes the performance of the MSR. Discussion of the progress on the shielding factor measurement and optimization of neutron delivery will be presented.

Planetary nebulae are the ejected outer layers of dying stars. At the center of these planetary nebulae remains the cores of the dead stars that created them. These remaining cores eventually become what we call white dwarfs. In order to understand planetary nebulae, white dwarfs, and their origins we can study the remaining core, or central star, inside the planetary nebula. We can do this by determining the physical properties of these central stars. One way to do this is if the central star has a companion—is in a binary star system. So I modeled the central star of the planetary nebula PN G012.1-11.2 which has a binary star system at its center. Using the PHOEBE modeling software I was able to create models that I qualitatively matched to the light curve (brightness variations) of this system. These models allowed me to find a range of radii, masses, and temperatures for the stars along with the inclination of the system’s orbit. I will present the results of my modeling as well as discuss what it tells us about this particular object and how it helps us understand planetary nebulae and white dwarfs more broadly.

Planetary nebulae are one of the last stages of stellar evolution for low-mass stars, those that have a mass of less than about eight times the mass of the Sun. As the star ejects its outer layers at the end of its life, the high temperature of the remaining core, what we call the central star, can ionize the gaseous ejected layers and make them glow. Many complex carbon-based and oxygen-based molecules can form in these ejected layers, and their presence can be detected through spectroscopy. Also detected in some planetary nebulae are binary central stars, where another object is in orbit with the central star of the planetary nebula. We gathered previously published data about binary planetary nebulae, as well as previously published data about planetary nebulae with detection and measurements of carbon and oxygen. We are looking for correlations between pieces of data such as the amount of carbon and oxygen, the shape, whether the planetary nebula is a binary, and the masses of the two stars for these systems, and how they compare in the context of the overall sample.

As current and next-generation gravitational wave detectors strive for greater sensitivity, higher beam powers result in more thermal absorption within the interferometer cavities and test masses. This causes mirror deformation and scattering of the incident beam into higher order modes (HOMs), effects that are not fully understood. While attempts have been made to model these phenomena using the FINESSE software package, its modal basis for constructing optical fields requires an exponentially increasing number of HOMs for high accuracy results, leading to computational inefficiency and the impossibility of truly accurate results. Therefore, we model these thermal effects using the linear canonical transform (LCT) framework. This grid-based numerical approach yields high spatial-frequency results and scales more effectively than FINESSE with increasingly complex optical fields. I present a discussion and analysis of the modeling of these thermal effects in a LIGO detector arm cavity.

This project is the first step in determining precise temperatures for hot white dwarf stars using ultraviolet spectra from the Hubble Space Telescope. A way to get the temperature of a hot white dwarf is through performing binary modeling. This project used a list of hot white dwarfs that was obtained from our Hubble Space Telescope project named, “A Treasury Far Ultraviolet Survey of the Hottest White Dwarfs”, and evaluated if there was periodic variation in brightness or not. The list contained coordinates, which were put into the database Zubercal to obtain photometric (brightness) data and a light curve (or plot of brightness over time). The photometric data was used to determine if there was brightness variability present and whether that variability was periodic, or changed in a regular repeating pattern. For any white dwarfs that showed periodic variability, their photometric data was used with a Python code to get a more accurate and precise period. If the white dwarf still showed signs of periodic variability, then it was plotted to the period that was found along with a fitted sine curve.

The Undergraduate ALFALFA Team’s (UAT) main goal was to measure the dark matter present in galaxies within the Pisces Perseus Supercluster. To do that we needed to fix any inconsistencies present within UAT’s initial galaxy measurements. Our project involved measuring emissions from neutral hydrogen (HI) in galaxies in the PPS using the Green Bank Radio Telescope, which detects radio emissions from space. These measurements allowed us to calculate the galaxies’ recessional velocity (how fast they move away from us), rotation velocity, and mass. We then used these measurements to contribute to an improved measurement of the Baryonic Tully-Fisher Relations (BTFR), which is a relationship between the mass of regular (baryonic) matter in galaxies and how fast they are rotating. This allows us to use the rotation rates we measure to estimate the distances to galaxies. Based on our investigation, we potentially might have improved how these galaxies are portrayed on the BTFR plot as we can now determine how far the galaxies are from the PPS, and thus its gravitational tug on the individual galaxies. We hope to eventually contribute to the first-ever measurement of the total dark-matter mass in a galaxy supercluster.

The white dwarf GD 803 is known to be a non-eclipsing close-binary system. It has an orbital period of less than a day, a hot white dwarf as the central star, and a cool main sequence star as the companion. Using luminosity data, in our case, luminosities in the SDSS-g and SDSS-r filters, light curves showing how the luminosity changes over time were created. Model light curves can be generated through adjustable parameters using the PHOEBE binary star modeling software. These model curves can then be compared to the data. By altering parameters to get generated light curves that are as close as possible to the data, information about the system can be estimated. The temperatures, masses, and radii of both the white dwarf and main sequence star, as well as the albedo of the main sequence and the inclination of the system are what we attempt to narrow down with this method.

The Cosmic Infrared Background Experiment-2 (CIBER-2) is a sounding rocket payload that utilizes HAWAII-2RG sensors to observe faint and diffuse sources in the extragalactic background light. In these detector arrays, each pixel is an individual light-sensing diode. The capacitance across each pixel is dependent on the changing voltage across the pixel as electrons are liberated from the detector material and pass into the readout system. To investigate the relationship between capacitance and voltage in the CIBER-2 detectors and effectively correct for non-linearities induced by the increasing voltage on capacitance, we developed algorithms to model the relationship between capacitance and voltage for each pixel in the detectors using a close-to-flat source of illumination in the laboratory. A model is fit to the C(V) curve in each pixel, which can then be used to correct for non-linear effects. This work will form the basis of a module used to analyze flight data collected by the CIBER collaboration.

Planetary Nebulae emit unidentified infrared Emission (UIE) lines that come from an unknown source. A proposed source for these UIE lines is polycyclic aromatic hydrocarbons (PAHs) which are composed of fused carbon rings. We have calculated the absorption spectra from various PAHs and compared them to observed UIE lines to try to determine where the UIEs come from. Our goal is to observed how ionization and nitrogen and oxygen heteroatom substitutions affect the Infrared (IR) spectrum. We used the Gaussian 09 program to calculate the structures and IR absorption spectra for about ninety different PAHs. These include linear and non-linear fused ring structures and oxygen and nitrogen substitutions, both in neutral and ionized states. We determined the vibrational modes associated with each of the peaks observed in the IR spectra. These modes involve C-H stretching and both in-plane and out-of-plane C-H bending modes. Ionization results decreased intensity for C-H stretching but increased intensity for C-C stretching and C-H in-plane bending modes. We also have determined that PAH molecules must have hydrogen atoms with specific numbers of neighboring hydrogen atoms in order to match the observed UIE bands. While none of the molecules we have studied match the UIE bands exactly, our results limit the possible candidates for PAHs that can reproduce the major UIE peaks in planetary nebulae.

During Valparaiso University’s annual service learning trip to Costa Rica in March 2024, five public health clinics were conducted in the communities of La Carpio, Boca Arenal, and San Gerardo, which held a combined population of approximately 69,000 at the time, most of which were Nicaraguan immigrants. These clinics were led by students and translators, small groups of which were sent out each day to conduct home visits within these neighborhoods to gather quantitative and qualitative data, including demographic information, details about the home environment, health insurance status, reasons for immigrating to Costa Rica, and perception of health threats from their members. Participants’ blood pressures were also collected. A total of seventy-nine families provided us with invaluable information, which helped us answer questions surrounding the impact of social determinants of health on Nicaraguan immigrants in Costa Rica in several areas, as well as gain insight into the perception and prevalence of preventable and chronic disease in these communities. Some findings of interest from this sample of participants were that the main reason for immigrating to Costa Rica was poor economic conditions in Nicaragua, the average blood pressure was 130/78, and that the two are potentially related. We were also able to obtain an understanding of the perception of Nicaraguan immigrants towards the Costa Rican public healthcare system. It is hoped that more data can be collected on how to assist the three above mentioned communities and better their health status in the future.