SOURCE 2025 (Program and Zoom Links)

Seasonal precipitation patterns in the Great Lakes region of the Midwest are becoming increasingly unpredictable, with spring floods and extreme summer heat creating challenges to terrestrial plant life. Disruptions in climatic conditions can impact environmental conservation efforts and agriculture within the region. As a major exporter of corn and soybeans, the unprecedented effects faced in the Midwest will have a large influence on agricultural production and food availability. We simulated the effects of these extremes in precipitation on 100 Arabidopsis thaliana recombinant inbred lines (RIL) to investigate gene-by-environment interactions on five growth and development phenotypes (days to germinate, bolt, leaf, seed maturity, and flower). We also performed a quantitative trait locus (QTL) analysis to identify regions of the genome that have effects on these traits. Through this QTL analysis, we were able to identify two QTL for time-to-flower and three QTL for time-to-bolt. The long-term goal of the project is to identify genes with an effect on plant survival and fitness in 21st century Indiana.

Drought stress on plants has increased in intensity, time span, and effected areas in recent years as our climate continues to change. Many plants have stress response adaptations to aid in plant survival through these abiotic conditions such as the abscisic acid hormone or increased anthocyanin synthesis. While these are two known stress responses, it is not yet known whether there is any correlation between these responses that are typically activated in drought environments. This study used a chromatography test on purple hairy-stemmed Brassica rapa plants that underwent drought conditions, with the experimental group receiving an excess concentration of abscisic acid and the control receiving the same treatment amount but of water instead. A significant difference was found between the plants treated with ABA and the control without additional ABA; t(18) =6.69, p=0.001. This study shows that there is a significant positive correlation between the stress hormone abscisic acid and anthocyanin pigmentation when a plant undergoes an abiotic stress, specifically drought. While a significant correlation was found, further studies could explore the exact pathway interactions between these two responses.

Infectious diseases are cited as one of the main causes of death worldwide. Many drugs to treat such illnesses were discovered in the mid-1900s, but this type of research has declined in recent years. At the same time, antimicrobial-resistant “superbug” infections are on the rise, including superbug biofilms present in the oral cavity, which are responsible for diseases such as tooth decay, gum disease, and implant failure. Therefore, I have been working to explore various plants from a medicinal garden on the Valparaiso University campus to screen extracts against common disease-causing oral bacteria with the goal of discovering novel compounds to fight these illnesses. Several of these extracts have shown promising antimicrobial effects specifically against Gram-positive bacteria, and the results will be presented in this poster. Future work will focus on separating several promising extracts using column chromatography to identify novel plant compounds relevant in dental health. This is a self-proposed project that I have received internal funding to work on via a CWR Guild Undergraduate Research Expense grant from my institution. I am very excited about this work due to my ambition to attend dental school.

This study tested the behavior of Northern Indiana’s bee populations using two common bee attractants. The aim was to determine which attractant drew the most bees to the wood pollinator boxes (beehives). Three hives were used as the control groups (left untreated), three were treated with Mason Bee Attractant Spray (lemongrass oil as active ingredient), and three were treated with Lemongrass Oil diluted to a 10% oil-to-water ratio. The boxes were attached to six foot metal poles placed in the ground. The poles were spaced roughly three feet apart from each other. The boxes were observed for a one month period. During this period, observations were conducted twice daily, excluding weekends, to track the number of bees constructing combs within the hive boxes. The data tracked over the month-long period was then analyzed. An ANOVA showed that there was no significant difference in bee preference between the treatments (p-value=0.723912). These results show that the bee boxes are attractive on their own, and there is no benefit to buying commercial attractants. This research was cut short due to facilities management on campus completely negligently removing all of the foliage from the test site. Once the foliage was removed, there were no bees observed.

Myiasis, the infestation of living tissues by Dipteran larvae, is a key component in cases of abuse and neglect in humans in forensic entomology. Temperature is a key factor in maggot growth and development. In this study, we aimed to determine the temperature that maggots experience during myiasis. Specifically, we are interested in determining if the temperature is closer to ambient, or body temperature. Approximately 20 larvae were put on a piece of liver in a piece of foil shaped into a cup, that was placed inside a glass container in a water bath set to 37°C to simulate human body temperature. Data loggers were used to record hourly temperatures of the water, air, and inside the bait cups for the duration of the experiment. The experiment lasted approximately 6 days, and concluded when the larvae reached the migration stage of their life stage development. After three trials there were various results found. In the first trial it was found that between bait cup one and cup two were statistically significant from each other, as well as the ambient temperature (p<0.00001). This is potentially due to the placement of the temperature probe within bait cup one. The temperature probe was deeper in the bait cup and was touching the aluminum closest to the hot water bath. We changed how the temperature probes were placed for trials two and three, and both were statistically significant from the ambient temperature (p<0.00001), but not from the other bait cup (p=0.993, p=0.346). Future experiments will add additional bait cups as well as continue to troubleshoot issues such as escaping maggots and keeping the temperature probes in a consistent location.

Plant life is facing unprecedented challenges due to erratic weather patterns in the Great Lake Region of the Midwest, characterized by its spring floods and extreme summer heat. We simulated the effects of these extremes in precipitation on 100 Arabidopsis thaliana recombinant inbred lines (RIL) to investigate the quantitative genetics of five phenotypes (days to germinate, bolt, leaf, seed maturity, and flower). We also conducted quantitative trait locus (QTL) mapping to localize genomic regions influencing the phenotypic variation observed in these traits. We identified five QTLs, heritability and gene-by-environment interactions. We are in the process of identifying candidate genes that improve plant resilience to the Midwest’s precipitation extremes.

Nervous system functionality depends on the generation and maintenance of the proper numbers of neurons. However, the molecular mechanisms that control the number of neurons produced during development and support long term neuronal survival are not fully understood. Nell2 is a multi-modular extracellular glycoprotein predominantly expressed in the nervous system. Nell2 exerts diverse functions in neural development, including regulation of neuronal proliferation and differentiation, and neuronal network formation. Our previous study has shown that Nell2 acts as an inhibitory guidance cue for retinal axons in the eye-specific visual (retinogeniculate) projection. In this study, we investigated the function of Nell2 in neuronal survival by using chick in ovo electroporation and Nell2 knockout mice. Nell2 is strongly expressed in retinal ganglion cells (RGCs) of chick embryos and in mice. Overexpression of Nell2 in the developing chick retina significantly increased RGC numbers, whereas Nell2 knockdown reduced them. Nell2 did not significantly affect neuronal proliferation. However, Nell2 promoted survival of RGCs in the developing retina by preventing apoptosis. In Nell2 knockout mice, the numbers of RGC significantly decreased in the developing retina, due to increased apoptosis. A continuous decrease in RGC numbers and increase in apoptotic RGCs were found in the aging Nell2 knockout mice. Furthermore, we detected Ros1 expression, a receptor tyrosine kinase that binds to Nell2, in RGCs by immunohistochemistry. These results suggest that Nell2 acts as a survival promoting factor essential for production and maintenance of proper numbers of RGCs, and that Ros-1 may be a receptor for Nell2 in RGCs.

The commensal fungus Candida albicans can change its morphology to a pathogenic filamentous form under certain conditions and cause systemic infections in critically ill (with elevated estrogen levels) or immunocompromised patients. Pregnant women are also more likely to develop vulvovaginal candidiasis. Both of these observations point to increased estrogen (E2) levels as filament inducing. Several studies have previously investigated the effects of E2 and found conflicting results. However, these studies differ in methods of evaluating filamentation. We aim to provide clarity to estrogen’s effect on C. albicans filamentation by studying C. albicans grown in liquid media exposed to estrogen concentrations near the pathophysiological range using quantitative PCR. We used fetal bovine serum (FBS) as a positive control as FBS is a well established promoter of filamentation. We used the hyphal-wall protein 1 (HWP1) gene, whose expression increases during filamentation, as a filamentous reporter. We set up five experimental conditions: a negative control (yeast media alone), 1 nM estrogen, solvent (EtOH), 10% FBS vol/vol, and both 1 nM E2 and 10% FBS vol/vol. Expression of HWP1 was evaluated using qPCR normalized to expression of 26S rRNA. Our results show a twofold increase in relative HWP1 expression in the presence of estrogen, as well as with FBS (positive control). We found an additive effect of E2 when combined with FBS, producing a threefold increase in relative HWP1 expression. Our preliminary results suggest that estrogen alone may be capable of causing C. albicans filamentation and represent a cue to becoming pathogenic.

Candida albicans is an opportunistic commensal fungus that can respond to the stress of low-shear modeled microgravity by exhibiting phenotypes associated with increased virulence. In previous studies, C. albicans have demonstrated increased resistance to amphotericin B under microgravity conditions, but no change in resistance to caspofungin. Here, we investigated how microgravity (3 and 5 days) influences the resistance of two C. albicans strains (SC5314 and from Carolina) to clotrimazole (200 µg/µl) and amphotericin B (250 µg/µl). Resistance was evaluated by measuring the zone of inhibition (ZOI) around the treatment discs after 24 hours of exposure to the drugs in the presence or absence of microgravity. We used a clinostat to create microgravity. In summary, we found that on minimum plates, 3 days of pre-exposure to microgravity increased sensitivity to antifungal drugs, which reversed after 5 days of pre-exposure to microgravity. On YEPD plates, 3 days microgravity did not change drug sensitivity, but at 5 days we observed an increase resistance to amphotericin B for SC5314 and increase sensitivity for the Carolina strains.

The successful germination and growth of native plant species in ecological restoration efforts are not well-characterized. Native seed mixes are often used in restoration efforts, but oftentimes the success of these seed mixes are not known and factors enhancing this success are neglected. We studied how well native restoration plants grow in low competition, high competition monocultures and mixed. We studied three native plant species, P. digitalis, C. lanceolata, and A. tuberosa. Growth performance was measured by wet and dry biomass of the plants after 5 weeks of growth when planted in low density monocultures, and high density mono and mixed cultures. We found that plants in low competition conditions grew better than those in high competition conditions. All three species showed significantly lower dry weight in high density monocultures (p<0.0167). P. digitalis performed worse in high competition mixed species than in high competition monocultures (p<0.167), while A. tuberosa showed no significant difference between these conditions (p>0.167). C. lanceolata showed mixed results. A. tuberosa is likely a strong competitor in mixed species restoration; however, P. digitalis appears more sensitive to competition, which could impact its success in restoration mixes or when facing invasive species.

Polypropylene microplastics are some of the most abundant plastic pollutants in the environment. These microplastics provide ideal surface area for the formation of biofilms that can increase the spread of harmful contaminants, such as heavy metals, pathogens, and antibiotics. The current study examines the differences in how pristine microplastics and UV-light aged microplastics affect microbe biofilm formation and production of antibiotics in a 96-well microplate. While many laboratory studies utilize pristine microplastics to determine their effects, pristine microplastics are not always representative of the natural environment. The quick UV aging process allows us to examine how biofilms may form on microplastics that have existed in the environment and degraded naturally for longer periods. Various combinations of a locally sampled soil microbe suspension in water and Streptomyces pure culture were filled in a control condition 96-well microplate and absorbance readings were taken on a weekly basis. Experiments in process include six microplates with added plastics to compare biofilm growth. Each week after reading, successive plates will be scraped out and dilution plated to compare absorbance readings with counted colonies to validate the microplate method over a three-week growth period. Meanwhile, the scraped biofilms will be utilized in several zone of inhibition tests to qualitatively assess antibiotic production.

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 array 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 focuses on screening under explored medicinal plants in hopes of discovering novel antimicrobial drugs. To accomplish this, we have been testing extracts of plants found in the Valparaiso University medicinal garden for their effects against 12 microorganisms, both fungal and bacterial, of interest. To date, methanolic and hexane extracts of aerial, reproductive, and root portions of 15 unique plants have been screened, with five plants showing promising activity levels, including chokeberry, raspberry, lavender, yarrow, and calendula. Antimicrobial activities of the most active plant extracts are presented herein. Chokeberry methanol extracts have begun to be separated using column chromatography techniques to determine the specific antimicrobial compounds through analytical chemistry methods. These data highlight the importance of plants as an invaluable pharmaceutical resource at a time when antimicrobial drug discovery has plateaued.

Microplastic pollution has become an increasing issue within our rapidly developing world, particularly concerning its potential effects on both environmental and ecological populations. In collaboration with Dr. Sara Dick this study was done to examine the effects of microplastics on microbial populations from watershed and sand environments under pH 5 and pH 9 conditions. The soil samples were serial diluted to 10^-5 to isolate individual colonies. Individual colonies were plated using a three streak method, incubated at 37? and allowed to grow. Colonies were removed from the plates and incubated in pH 5 and pH 9 agar tubes and exposed to microplastics. Growth was assessed through qualitative visual inspection and quantitative spectrophotometry. The results have indicated varied responses between different colonies and their respective conditions. Some showing inhibited growth in the presence of microplastics, particularly under the acidic conditions of pH 5. No evidence has been observed of potential microplastic degradation under any colony or condition. Future research will focus on statistical analysis on the growth patterns between conditions in order to determine statistical significance, as well as further diversification of microplastic types and different colonies to determine which microorganisms are particularly effected by microplastic pollution.

Novel antimicrobial agents are crucial due to rising superbugs and declining drug development, threatening millions by 2050. In addition to being a terrestrial cause for concern, antimicrobial resistant microbes threaten the health of individuals during space travel. Recent studies show several opportunistic bacteria and fungi have colonized the International Space Station (ISS), and many strains possess antimicrobial resistance. Additionally, reports have highlighted how space travel may alter the immune system, placing astronauts at higher risk of infection. Therefore, our research focuses on testing bacterial and fungal pathogens that have been isolated on the ISS against methanolic and hexane extracts of various medicinal plants, such as Argemone mexicana. From previous work by our group, several antimicrobial compounds were isolated from the roots and leaves of A. mexicana, including berberine, chelerythrine and sanguinarine (work published in PLOS ONE in 2021). Since then, we have synthesized multiple rationally-designed variants of these original phytocompounds (over twenty berberine and four chelerythrine variants) and have tested these A. mexicana-inspired phytocompounds for altered antimicrobial activities. In this poster, we present the results from two novel berberine-variant compounds of particular interest due to their increased antibacterial effects against gram-positive bacteria, yet reduced toxicity against the eukaryotic fungal cell lines tested. Antimicrobial trends and mechanism alterations (via an alkaline phosphatase assay) for these unique compounds, as well as changes in drug potency in a simulated microgravity environment (using a clinostat) are presented herein. This work is funded through an Indiana Space Grant Consortium (INSGC) NASA grant.

Pd0-catalyzed trimethylenemethane (TMM) cycloaddition reactions have been used extensively to generate substituted 5-membered rings with high levels of regioselectivity, chemoselectivity, and stereoselectivity. These rings have many practical applications, such as polymer and pharmaceutical molecule synthesis. We aim to improve upon existing methodologies by introducing an epoxide functional group into the TMM precursor molecule, which should yield more highly functionalized products. A three-step synthesis of a TMM precursor has been achieved in 20% overall yield, quantified by structure and mass analysis at each step. Efforts are underway to determine the reactivity of this precursor in Pd0-catalyzed cycloaddition reactions with ?,?-unsaturated carbonyl compounds.

CooA is a protein found in Rhodospirillum rubrum (Rr) and Carboxydothermus hydrogenoformans (Ch) and naturally acts as a carbon monoxide (CO) sensor and transcription factor. When CO binds to the CooA heme, the protein undergoes a conformational change that enables it to bind to DNA. The broader goal of this research is to obtain a mechanistic understanding of how the CooA heme, along with the amino acids that are located near the heme, enable CooA to act as a CO-specific sensor. Our current project is to determine if a cysteine amino acid that is close to the heme group alters the specificity of the regulatory gas during the activation mechanism. Preliminary results from electronic absorbance spectroscopy indicate that this cysteine influences the coordination chemistry of the CooA heme, possibly enabling other gases like nitric oxide to activate the DNA binding function.

Pathogenic bacterial and fungal infections are some of the leading causes of death in the population at large. Antimicrobial-resistant “superbugs” have become a growing issue worldwide as well as on the International Space Station, and there is a great need to explore new and alternative pathways for fighting these diseases. Through a collaborative project, we have explored extracts of the Argemone mexicana plant to isolate antimicrobial agents found within this plant. We have already identified three key molecules, notably berberine, which give this plant antimicrobial properties. Guided by the structures of the plant-derived molecules, our current work is focused on designing and synthesizing new variants of these bioactive molecules in the hopes of discovering new, more potent, drugs. Thus far, several of our synthetic variants have shown promising activity over the original phytochemicals isolated from the plant. Trends have emerged showing enhanced antibacterial activity with more hydrophobic variants.

Zeolites are a class of materials that are composed of oxygen, silicon, and aluminum with channels embedded in the crystalline structure. Zeolites have many applications, some of which include water purification, biomass conversion, or as molecular sieves. The zeolite’s crystal structure allows them to act as a host for smaller guest molecules without chemical bonding between the host and guest molecules. An example of a guest dye molecule is Brooker’s Merocyanine. Brooker’s Merocyanine is zwitterionic, where there are opposite charges on each end, and is a unique property that could be used to enhance the dye organization within the channel. By combining the host zeolite with the guest molecule Brooker’s Merocyanine, the dye is expected to go into the zeolite channels by a cation exchange process, based on previous work. This project focused on a zeolite known as Mordenite, chosen due to this lab’s previous work with other similar zeolites studied with Brooker’s Merocyanine that included LTL and ZSM-5. The purpose of this project was to optimize the combination of the Mordenite and Brooker’s Merocyanine. We used UV-Visible spectroscopy to confirm the dye is interacting with the zeolite. Dye loading Mordenite was most successful when refluxing the sample in acidic aqueous dye solution in the dark overnight with stirring. Through these experiments, we found that Mordenite can interact with Brooker’s Merocyanine more than LTL or ZSM-5.

Indoor air quality is often overlooked, yet it plays a critical role in human health, particularly for communities located in industrial zones where air pollution is prevalent. Exposure to volatile and semi-volatile organic compounds (VOCs) can contribute to a range of health problems, including respiratory issues, neurological effects, and long-term chronic diseases. Understanding both indoor air quality and personal exposure to these pollutants is essential for evaluating public health risks, especially in residential areas near pollution-emitting industries. This study aims to assess VOC levels in both indoor environments and personal exposure in Northwest Indiana, particularly near industrial zones, with comparisons to areas not located near such pollution sources. VOCs, including common pollutants like phthalates, toluene, alkanes (e.g., hexadecane, octane, decane), and alcohols (e.g., 2-n-propyl-1-heptanol), were assessed through two passive sampling techniques: solid-phase microextraction (SPME) and silicon wristbands. SPME fibers, coated with polydimethylsiloxane (PDMS) and divinylbenzene, were used to monitor indoor air quality by passively absorbing airborne compounds in residential homes. Silicon wristbands were used to track personal exposure by absorbing chemicals from both indoor and outdoor air when worn by volunteers. After the sampling period, the fibers were analyzed using gas chromatography-mass spectroscopy (GC-MS) to identify and quantify the VOCs. This dual approach–combining SPME fibers for indoor air monitoring and wristbands for personal exposure–provides a non-invasive, cost-effective, and sustainable method for assessing air quality and individual exposure levels. It also enables frequent monitoring and comparison between indoor and outdoor pollutant levels, contributing to a more comprehensive understanding of the health impacts of air pollution.

The quality of the air that we breathe has tremendous impacts on our health; bad air quality can lead to short-term eye, nose, and throat irritation, and long-term chronic respiratory conditions. It is important to monitor air quality and understand what metrics indicate potential hazards, in attempts to better measure the healthiness of communities and indirectly its’ individuals. Not all air sensors are calibrated to measure metrics the same, and this study will compare values across air sensors via the PM2.5 air quality standard. In this study we focus on measuring particulate matter – which can come from dust kicked up on roads from cars, vehicle exhaust, wildfires, industrial site emissions, and more – using PurpleAir sensors located across Northwest Indiana. PurpleAir does not release proprietary information regarding the formulation of parameters included in the Air Quality Index that is posted on their publicly-available website. Due to potential discrepancies between standardized air sensors and PurpleAir instruments, we are evaluating the accuracy of our measurements against industry standard air sensors. In order to more confidently determine PurpleAir measurements’ validity for air quality metrics, we compared them to commercial-grade sensors such as the TSI DustTrak, Thermo Fisher pDR-1500, & DRUMAir cascade impactor using qualitative graphical and quantitative statistical tools. These sensors are of the caliber used by government agencies such as the EPA, and these research efforts provide a novel and necessary service to communities that depend on these sensors as their only local full time air quality measurement. We expect relative trends in particulate matter concentration to be well reproduced amongst the sensors and absolute comparisons to require scaling factors. As part of our community projects, we also study archived air quality measurements in our attempts to inform future community health and policy decisions.

Bacterial and fungal infections are among the greatest causes of death worldwide. With the continued growth of drug-resistant antimicrobials comes a greater challenge fighting these “superbugs”. Because of this, the need for new and alternative pathways for fighting these diseases is both necessary and prevalent. Previous work from our lab has explored extracts of the Argemone mexicana plant to identify key molecules that give the plant its antimicrobial properties. Our current work centers around berberine, one of the key molecules, and designing and synthesizing structural variants. Several of our prior variants showed marked improvement over the plant-derived compound against gram-positive bacteria. The goal is to continue generating new and more potent antimicrobial drugs. Much of the recent work is focused on expanded hydrophobic units in the variant structures. The compounds discovered in this work may lead to the development of more selective antimicrobial drugs.

We present a proof of concept demonstration of solar thermochemical energy storage. The James Markiewicz Solar Energy Research Facility (SERF) at Valparaiso University uses concentrated sunlight to reduce hematite at 1500 ?, evolving oxygen and producing magnetite. Magnetite can then be dissolved in water at pH 5 using hydroxyethylidene diphosphonic acid (HEDP). Aqueous Fe²⁺ serves as the anode for the reduction of water to hydrogen, as demonstrated by a visual H₂ detection assay. Finally, alkaline solutions of Fe³⁺ + HEDP upon concentration produce a precipitate characterized as goethite ?-FeOOH by Raman spectroscopy, completing the cycle.

Although Christian characters and themes appear fairly frequently within western media, this occurs less so with Japanese media. The population of Christians in Japan has remained fairly consistent in the past century, occupying approximately one percent of the population. For centuries prior to the Meiji Restoration (1868), Christianity was made illegal by daimy? Hideyoshi. As a country with few Christian—as well as a history of Christian persecution—Japanese media tend to have a more surface level understanding of Christianity, if Christianity is even referenced at all. Popular Japanese media (particularly anime, the focus of this research) tends toward the aesthetic use of Christianity, but within those uses, as well as the more significant uses of Christian characters and themes, we can observe the underlying cultural attitudes toward Christians and Christianity. These cultural attitudes, outside of the aesthetic, tend toward negative portrayals and thus a general negative perception of Christianity, although the extent of negativity broadly correlates with the level of power an individual or entity has within the Christian hierarchy. For instance, laypeople exist on the spectrum of somewhat sympathetic yet naïve victim characters to abusers, while supernatural entities like angels exhibit broader levels of corruption and debauchery, if their corruption does not extend to wanting to destroy humanity. While it remains unclear if the negativity of these portrayals exists as purposeful decisions by the stories’ creators or unintentional happenstances, they reflect the persistence of negativity toward Christianity from the time of Jesuit missionaries and the anti-Christian edicts of daimy? Hideyoshi.

Against the backdrop of civil war threatening the United States, a push for patriotism and virtue surged throughout the North. Educating Americans, especially Northern white women, became the ultimate solution for both the social and economic gain of the United States. Americans realized that a mother was a child’s first teacher, so women needed to be educated themselves in order to pass on that learning to their children. This is a concept entitled in this paper as New American Motherhood. This movement stemmed from the ideology of Republican Motherhood, the 18th century belief that motherhood was a civic virtue and responsible for creating the next generation of upstanding citizens. In the mid-to-late 19th century, New American Motherhood ushered white American women into the college classroom, and institutions began to address this new need. The most innovative of these being coeducational colleges. Accordingly, the Northwest Indiana Conference of the Methodist-Episcopal Church formed a college that invited not only men but also women to take part in a complete, thorough educational and intellectual experience. Henceforth, the Valparaiso Male and Female College (1859-1871) came into existence. Scholarship, however, fails to include the Midwestern coeducational institutions that made these radical strides in women’s educational experience, focusing more on Northeastern women’s colleges. This paper expands into the study of nineteenth-century women’s education by uplifting the stories of Midwestern women in a coeducational institution. Moreover, this paper dissects the cultural context of women at the Valparaiso Male and Female College; and, in doing so, it explores how this new opportunity gave women a voice in the social and political machine, especially as the nation entered the Progressive Era and 20th century. The New American Mother, educated at a coeducational college, was indeed a woman rearing children for their success, her own success, and the success of future women.

Though a social media influencer’s overnight success is a new phenomenon, its theoretical foundation is not and is explainable by Max Weber and Sigmund Freud. The case of Andrew Tate, a kickboxer turned social media influencer, is illustrative. Despite his misogynistic and discriminatory claims, Tate’s radical statements and cult-like following echo Weber’s nineteenth-century description of charismatic authorities and their followers. While the label of charismatic authority is a start, Weber’s theories alone do not sufficiently explain some questions of why anyone would adhere to Tate’s claims and how he gained popularity. Fortunately, Sigmund Freud’s pleasure principle describes an instinctive desire that is in contention with the reality principle of societal rules. Tate’s countercultural statements create a space for people to freely engage under the pleasure principle, making his behavior attractive to many. Further interpretation of the Tate phenomenon can be built through what Verena Wieser, a Weberian sociologist, calls charismatic entrainment. Charismatic entrainment argues that the interaction between a brand leader, consumer-followers, and consumer-critics creates prominent charismatic authorities. Through an online platform, Hustler’s University, Tate, the brand leader, allows his immediate fans, the consumer-followers, to spread his message and engage in discourse with others. This discourse often invites those who disagree with Tate, the consumer-critics, to bash Tate for his statements, but these protests produce only more publicity for Tate. Andrew Tate will not be the last influencer to engage in this process. Thus, society must understand these processes to halt a more detrimental influencer in the future.

Films over the last 25 years such as The Legend of Bagger Vance and The Hunger Games have paired black characters along with the movie’s white lead in an attempt to promote better representation of African Americans in cinema. While these films make small strides toward more positive representations, their use of a black character to advance the growth of a white protagonist classifies them as ‘Magical Negro’ (MN) films. The MN trope within cinema is problematic because it testifies to society’s perception of unbalanced power between black and white Americans. This paper aims to critique the tolerance of semi-positive and seemingly harmless portrayals of African Americans in film through an analysis of the MN trope. After investigating the common elements and patterns within MN films, the paper argues that these stereotypes negatively impact the audience. This relationship between harmful characterizations and real-world impact as demonstrated with MN films warrants attention because cinema is an influential tool for enforcing racial attitudes that should be held accountable.

Much of Virginia Woolf scholarship focuses on the damage of gender roles on women and their relationships, with little emphasis or acknowledgement on her thoughts on men and male roles. She does, however, write regarding both. This paper examines how gender roles shaped the success or failure of the friendships between William Bankes and the characters of Mr. Ramsay and Lily Briscoe in To the Lighthouse. The generational aspect of the novel lends itself to a comparison of Victorian and Modern gender roles and expectations. By examining Ramsay, Bankes and Briscoe within the context of these roles and expectations, it becomes clear that for Woolf Victorian standards impede the creation of deep friendships. In both the Modern and Victorian era, marriage was a priority for both men and women. Mr. Ramsey embodies a male gender norm, serving as the provider and “superior” in his marriage. He prioritizes this over developing an emotionally deep friendship with Bankes. At the same time, Ramsay is stuck in the past, choosing to repeat his past successes in this role instead of pursuing a satisfying reciprocal friendship. Briscoe, conversely, has no interest in a marriage deemed necessary by societal norms and is self-sufficient. As a result she is able to have a rich friendship with Bankes. Bankes himself is a widower, also unimpeded by gender norms, allowing him to pursue deeper friendships that exceed those norms. Bankes and Briscoe embody Woolf’s idea of an “androgynous mind” from A Room of One’s Own. Ramsey lacks this androgynous mind. However, he is able to approach this state by the end of the novel after the death of his wife, showing a newfound potential to create true reciprocal friendships.

In transportation engineering, accurate traffic counts are essential for transportation planning and infrastructure design, enabling policymakers and designers to make informed decisions about future development plans, safety improvements, and resource allocation. This research project investigates the ability of traditional traffic counting devices, counting tubes, to effectively count horse and buggy traffic. Traffic counting tubes, commonly used for monitoring vehicle flow, detect vehicles based on tire contact with a pneumatic tube. Lighter or slower vehicles are known to be miss-counted by these devices. This research focuses on the ability of traffic counters to recognize horse and buggy traffic, with data collected on local county roads in Elkhart County, Indiana, particularly County Road 37, which is centered in an Amish community where horse-drawn transportation remains an integral part of the local lifestyle. Elkhart County has a significant Amish population resulting in a high volume of horse and buggy traffic along certain corridors. Counting and differentiating buggy traffic allows the county to plan and prioritize road repairs and improvements to better address this user base. In order to assess the capabilities of traffic tube counters, data collected from the tube counters was compared to manual traffic counts derived from video of the count locations. The results of this study aim to provide insight for Elkhart County into the reliability of current traffic counting practices. Ultimately, this research will contribute to the ongoing effort to improve traffic data accuracy and provide more inclusive and comprehensive data collection techniques.

Start-up lost time refers to the duration it takes for the first few vehicles in a queue to respond to a green light at a signalized intersection. This delay contributes to inefficiencies and impacts queuing, particularly at intersections that are operating at full capacity. We conducted a study to assess whether traffic signals equipped with a countdown timer for the green light significantly reduce start-up lost time. Utilizing video footage from signalized intersections in the Dominican Republic that feature a countdown timer, we measured the interval between the moment the light turned green and the time the first vehicle in each lane began to move. This timing will be compared to start-up lost times at signals in the United States without a countdown timer to determine the efficacy of countdown timers in decreasing total vehicle delay at signalized intersections.

This paper evaluates the need and potential benefits of creating micromobility routes on the Valparaiso University campus. Student education on college campuses is supported by not only the faculty and staff who run the campus, but by the infrastructure that enables its daily functions. A crucial part of this infrastructure comes in the form of transportation routes, including: sidewalks, walking paths and roads. On these routes, diverse modes of transportation interact, at times with varying levels of cohesiveness. Challenges can occur when these modes of transportation conflict, leading to a decrease in user comfort and safety. With its vast and luscious green spaces across maturing landscapes, Valparaiso University has created an above-average campus environment, appealing and accessible to pedestrians and vehicles alike. One mode of transportation in growing demand that was not planned for on VU’s campus is micromobility, which includes electric scooters, one-wheels and other electric powered options, as well as bicycles. Oftentimes, micromobility users are required to use either walking paths or roads to get around, and in doing so they interfere with pedestrians and vehicles respectively. The addition of a micromobility routes across Valparaiso University’s campus will provide safe routes for these users. This would also encourage more outdoor activity, and reduce transportation time for pedestrians or bus riders. This paper highlights the importance and benefits to implementing routes on campus and proposes possible routes offering students, faculty, staff, and our community a safe and efficient transit route that is accessible for all.

Campus infrastructure plays an important role in student mobility, safety and overall quality of life. This study compares pedestrian travel times to Valparaiso University’s proposed nursing building site compared to two alternative locations. The objective is to evaluate pedestrian flow and travel times to the three sites. Using VISSIM, micro-simulations were done to analyze walking routes and travel times for students accessing all three locations from the campus student union, dorms and commuter parking lots. Results indicate that the university’s proposed site would increase pedestrian travel times and expose walking students to conflicting vehicle traffic and potentially impact adjacent campus buildings with added cut-through traffic. In contrast, relocating the nursing building at one of the alternative site would reduce walking distances, improve student safety by minimizing street crossings, and enhance pedestrian flow across campus. These findings suggest that careful site selection can significantly impact student convenience and campus walkability, contributing to a more efficient and accessible university environment.

Accurate surveying of detention basins is essential for stormwater management. This study evaluates traditional surveying techniques versus the use of drones and advanced imaging technology for detention basin assessment. Conventional surveying methods rely on GPS and manual measurements, which can be time-intensive and subject to human error. In contrast, drone-based surveying utilizes high-resolution aerial imagery to rapidly collect topographic data. This study compares the accuracy and efficiency of both methods by conducting surveys of on-campus detention basins using each approach. The collected data is analyzed and assessed to determine the advantages and limitations of drone-based surveying in comparison to traditional techniques. Best practices for the use of drones in this application are also recommended.

No two people have the exact same childhoods or nostalgic connections, but common themes, colors, and some experiences can be shared and are seen as nostalgic by many. Big Top Performer is a poseable art doll built from a wire skeleton with clay features and a soft, fabric body paired with a colorful canvas board backdrop and thematic accessories. The doll itself depicts a weasel in clown garb. The primary inspiration for the piece was childhood nostalgia. The doll itself resembles a toy or trinket while the backdrop reflects the imaginary story or setting of the toy. Without the backdrop, the doll is reduced to just a toy, but paired with the backdrop the doll is given “life.” The viewer, ideally, will form a nostalgic connection with the piece. This connection is not necessarily positive–clowns are a common fear, for example–but any sort of emotional response tied to childhood is the goal. The backdrop, which is abstract, sets the scene rather than dictating the mood or connection with the viewer. The doll exists and lives in a “play-land” that the viewer happens to witness.

How does your mind and body connect? Do your actions and thought process reflect each other? How often does your body and mind agree with each other? What’s on your mind? is a series of 4 oil paintings on smaller scale canvases. The main theme of the series is to show that the human mind can vastly differ from the presentation of the body. The series contains different poses with different inanimate objects as heads to show how stagnant the body is compared to the mind. My inspiration for this is my own transition and how I think about identity. Pretty much nothing about my body is correspondent to how I imagine myself to be, which is where the disconnect comes from. With this body of work, I hope to get people thinking about just how much they connect with themselves and their body compared to the connection they have with their own mind.

Fiber art is a medium that stretches across generations of people and continues to connect the past to the present. My project is called The Things that Connect Us: Fiber Arts with an Artistic Lens. Crochet has been part of my life since I was 10 years old and is still a big part of who I am as an artist. This technique is unique because it can only be done by hand. With my piece, I wanted to use this medium and put it on a canvas like how paint is traditionally applied. I took a lot of inspiration from Miriam Schapiro and the femmage movement. This movement wanted to highlight the importance of art traditionally done by women who were given less respect by other fine artists and to give them a platform to create. I want people to see crochet as more than just being done for utility without any artistic purpose and for it to not be dismissed by people who feel that it can’t and shouldn’t be fine art.

“No water, no life. No blue, no green.” ~ Sylvia Earle

The focus of my artwork is on the effects of pollution on not only the sea, but also ourselves. Humans use the ocean for many things: transportation, food, water. We rely on it, yet we are the first to abuse it. My work, called Tidal Wound, is a mixed media collage that uses recycled material and environmentally friendly paints. The main focus is the ocean and the endangered sea life as a result of pollution. My goal is to create a cohesive piece that depicts beauty, but also makes people think. I want the viewer to look closer, see the devastation caused by harmful materials in the ocean, and feel a sense of discomfort and unnaturalness from recycled sea life. My hope is that this project will generate awareness as well as inspire viewers to work for a brighter, cleaner, and safer future.

Writer’s Block is a mixed-media piece created using a shadow box, collage, and a variety of found/chosen materials. The piece is inspired by my favorite authors and artists, who all embraced dadaism and experimental ways of creating their work. My goal for this piece is to provoke viewers into seeing creative expression and writing as a cathartic experience, as well as something that isn’t bound to societal norms/constraints. I believe that art is best in its rawest and most honest form—untouched by outside influences and sometimes even absent of reason.

Since the beginning of the new presidency, there have been massive cuts to many government departments. In addition, recent executive orders are also seen with such scrutiny. These orders and cuts are what many Americans believe to be bizarre. Animals in the Sky, is a reflection of the uncertainty and instability that is happening within our government. The piece showcases a variety of animals flying through the sky; a pig with wings, a jackal with wings, a monkey with a dragon’s tail, and a seal with a jetpack. This work is inspired mainly by the surrealist movement and the Mexican channel De Película, a movie channel my grandmother would watch occasionally. The absurdity of our political climate is akin to the impossible suddenly happening. Animals in the Sky is a playful reflection of the current administration and invites the audience to contemplate the current decisions the government is making, rather than pushing it aside. Nevertheless, the work also serves as a standalone piece that is separated from politics.

Inspired by story telling and my interests in multiple different art mediums, I decided upon a creative project utilizing both photography and comic/graphic novels to act as a memoir and documentary of my semester abroad in Japan. While I was there I spent time studying the concept of the “Medium is the Message” and through this project I continued to explore what that really looked like. I took photos and kept a diary while in Japan. Upon coming back, I started the comic book process of storyboarding, making a script, drawing/coloring, and finally editing. Simultaneously I organized my photos and curated a selection of ones to present and then hung them in the exhibit. The comic acts as a more personal and direct commentary of my experience while the photos work to bring them to places I traveled and provoke the feeling of what life was like. My purpose with this project was to make two separate bodies of work to compliment each other when presented together as one as well as encouraging others to do things like study abroad and share their story. Hopefully with this project I can further encourage more interdisciplinary dialogue.

Do you ever feel drained by everyday life and reflect on a moment of joy to remind yourself that there is light in life? This collection of works is titled “Small Moments of Joy”. These pieces are inspired by varying images of memories that draw out feelings of happiness for what was and pain for what will no longer be. Whether they are images of my parents’ past or took place within the past year, gazing at these stills provides an escape from reality and allows me to connect with the moment in the photo. The concept of memory draws many emotions that are reflected on when personally recreating these images. All pieces in this collection were created in standard photo sizes to mimic the feeling of looking at a picture wall in one’s house. Viewers can reflect on their own moments that bring them joy throughout their life and remind them that life is worth living for the small moments.

The inspiration for these paintings has been brewing inside my head for quite some time now. I wanted to make a project about how crushing it feels when you just can’t seem to understand. That time you got angry at yourself and even those around you for not understanding the statistics homework after three people tried to help you. Pent up anger, or sadness. That time you threw your phone at the wall because of a cyclical, frustrating argument. A ‘cherry-on-top’ outburst that comes from a place complete frustration. As well as a place of fear. Is that a fear of being taken advantage of? Is it a fear of being stupid? A fear of being weak? Being “too” emotional makes people feel vulnerable, or even weak. When you’re emotions are so large, it feels like they’re taking up too much space. Like they might get in the way of perfectly good things. Words and poetries, textures, images of the female body and human flesh and flowers are all representative of vulnerability and are used to do so in this project. Choosing to be vulnerable in comfortable environments can be freeing and necessary. That is, only when it is you who chooses to make you feel vulnerable.

The Spectrum of Feminism is a series of oil paintings with collages that address three points on the feminism spectrum. These pieces are meant to explore stereotypes and reasoning for the three identities and experiences of the points I am addressing on the feminism spectrum. The three points on the feminism spectrum within this collection are misogyny, feminism, and radicalism. I am highly inspired by my experiences as a woman and the current political climate. I address each piece with sides of reasoning for pro and anti views. My goal is to get viewers to question why these perspectives exist, and whether or not they hold similar views with any of the pieces.

Abstract: Between the Earth and Sky

How do you find balance? In these days, balance is necessary, more than ever. My project is a 3-part series of mixed media portraits, called Between the Earth and Sky, based on a poem I wrote of the same name. The subject is a personal one, about going back and forth between emotions, and trying to navigate the ebb and flow of everyday life as though it were a stormy sea. However, both this project and my poem was meant to represent the inner balance that I was able to find. Balance between experiencing all of the seasons of life, both the good and the bad, both the thorny vines and the red roses. I hope that the viewer will walk away remembering there is peace to be found within the tides of dark and light, and we can always find this peace within ourselves.

Vulnerability exists in a dichotomy; a Paradox.

Paradox is an oil painting on canvas that involves a sculptural element through wire and beading. This piece explores vulnerability and the paradoxical nature that surrounds it. There is a certain sense of safety in not being vulnerable with the ppl around you, however it also serves as an isolating cage. I am inspired by other artists, such as artist Nick Cave, who combines mediums into whimsical , weable pieces of art. My goal is to inspire an introspection among viewers. What aspects of your life do you keep to yourself? Is this detrimental to your relationships? This piece comments on these questions.

Reflections of the People explores the concept of human connection, empathy, and how people perceive themselves. Through the colored mirrors, viewers can see themselves in a different individual and see that as people we have something in common with every person we meet. The audience should take a moment to look deep within themselves and recognize their own characteristics, which can be broken down into fragments and correlate them with other people. The symbolism of the colors is that they are associated with various emotions and personality traits that make up an individual. As you can see some of the fragments are not transparent, just like there are aspects about others that will never be uncovered. As humans, we have the emotional power to connect with each other and build relationships.

The X3 Guitar Processor is a software adaptation of the Rockman X100 headphone amplifiers and stompbox pedals made popular in the 1980s. This project, which is still in progress, implements a comprehensive signal path to convert a dry input signal from a guitar into a fully developed tone ready for performance. The signal chain includes an adjustable input gain control, a compressor, a distortion generator, a complex filter for cabinet simulation, and an optional stereo chorus effect. This software was built using the JUCE framework, a set of C++ libraries designed to create and manage audio applications. Further development will focus on completing the distortion generator and fine-tuning the sound to closer match the original hardware that inspired it. Currently, all effects have been implemented, with one of the three amp modes being fully completed. Additionally, in its current state, the app is compatible with many Digital Audio Workstations (DAWs) and live performance software environments.

As time progresses, the implementation of website security and accessibility are often seen as a priority for most website and application development. Website security focuses on the protection of the website, and web accessibility focuses on the inclusivity and usability for everyone regardless of their disabilities. Although thee two mostly have differing objectives, there is some significant overlap between the two when it comes to implementation. Something as simple as not having the appropriate headers on a website could lead to severe vulnerabilities that could lead to attacks such as Cross-site scripting or SQL injection, and also conflict with screen readers ability to read the header as well, causing issues for the visually impaired. A series of penetration and web accessibility tests were done to full stack applications developed by other fellow classmates, in order not to find any of these security and accessibility flaws, but how much they affect each other as well.

This study presents a model to investigate the effect of temperature control systems on energy efficiency and thermal comfort in aging residential buildings. The model addresses how heating systems, such as radiators and thermostats, interact with building elements and occupant behaviors to influence energy consumption. Focusing on variables such as building age, insulation quality, and outdoor temperature, the model simulates the dynamics of energy use within older structures. Drawing from datasets on energy consumption and existing simulation frameworks like NetLogo, the model incorporates the role of insulation, structural integrity, and occupant habits in determining energy efficiency. The simulation results reveal that buildings with poorer insulation experience more erratic energy consumption, particularly with traditional radiator-based heating systems, which lead to greater energy waste. Conversely, thermostat-regulated heating systems maintain a more stable temperature, significantly reducing energy consumption. Occupant behavior, such as opening windows during extreme temperatures, remains a critical factor influencing energy efficiency, even with temperature control systems in place. The study highlights the importance of integrating better insulation, optimized heating strategies, and informed occupant behavior to achieve sustainable energy management in aging buildings. The results also suggest areas for future model improvements, including the integration of additional environmental factors and more complex occupant behavior simulations to refine predictions and enhance real-world applicability.

This research investigates the technical vulnerabilities that enable successful Evil Twin attacks, focusing on automated bypass techniques for captive portals and the effectiveness of Virtual Private Networks (VPNs) in mitigating such attacks. Understanding these vulnerabilities is crucial for developing robust security measures. Instead of relying on human subjects accessing different wireless networks, a controlled lab environment was established to simulate realistic network connections and to analyze traffic patterns. This approach allowed for precise control and repeatability of experiments. To emulate client device behavior, an automated Python script was developed. This script attempted various methods to bypass captive portal authentication, including common credential submission techniques and exploitation of potential weaknesses in portal implementation. Wireshark was used to analyze the impact of browser security features, such as HTTPS enforcement and certificate validation, on the success of bypass attempts. The results demonstrate the possibility of a full-tunnel VPN being able to bypass the initial credential sniffing attack often associated with Evil Twin setups. However, the captive portal will still appear in all tested Wireless Security protocols, indicating that while VPNs can protect data in transit, they do not inherently prevent exposure to malicious portals. Further research is needed to explore methods for completely circumventing captive portal redirection in Evil Twin scenarios.

The aim of this project is to build a website for finding interchangeable hydraulics parts and providing links to verified suppliers at the request of an expert in the hydraulics industry, as there are many hydraulics parts that can be substituted for each other, but no way of easily identifying them. This application will support customers’ ability to acquire parts from various suppliers via entering the name of a part into a public-facing website. The software shall search through its database and return a list of compatible parts with links to where they can be obtained. This project was created using the Agile Development Model, and authored using HTML, CSS, and PHP, with a SQL database. The database backend was populated using Python to scrape information from hydraulics catalogs and upload relevant technical data. Challenges included parsing and scraping data from PDF files with varying formats which raised the complexity of identifying and collecting key information. Considerations also included the ability to support regular updates to these information sources as manufacturers adjust and expand their product line. This project was built to be extended with a larger database and more options for users to search and filter parts.

Sensit Technologies, a Valparaiso-based company that manufactures gas leak detection equipment, requested an application to reduce manufacturing complexity. Our goal with the Swiss Army Programmer (SAP) App is to simplify the firmware uploading process for the operator through the integration and consolidation of these complex configurations and tasks done by the application without user input. The new application is authored using C# and Windows Presentation Foundation to enable loading of single-board computers with firmware. The complexities of pairing Printed Circuit Boards (PCBs) to appropriate loaders creates additional, avoidable tasks for assembly technicians, requiring them to juggle more than 5 software tools, each with unique file navigation systems and user interfaces. This application aims to provide Sensit with a uniform suite to support all of their PCBs, thereby reducing that workload and specific task complexity. As opposed to the PCB configurations for all of the different software (each of which has a unique process for identifying the type of PCB and its configuration), the SAP App aims to allow an operator to simply select a product and the type of microcontroller the product uses and start/stop the download process. One of the challenges this project faced included the need for physical hardware and products used for testing purposes. In addition, the lack of resources on this highly specialized domain provided the challenge of creating extensive and from-scratch software for unique device detection, PCB and product configuration, and loading protocols.

Retail businesses rely heavily on data-driven decision-making, yet extracting valuable insights from raw sales data can be quite challenging. In collaboration with Family Express, we created an AI-driven analytics platform that utilizes data science algorithms to convert sales data into valuable business intelligence.

We began the analysis with data preprocessing and cleaning, where missing values were handled using forward filling, backward filling, and interpolation methods. To further reduce any inconsistencies in the data, techniques like window smoothing were used. A correlation analysis was performed to examine relationships between gas sales and in-store purchases across all locations, providing insights on how fuel transactions effect inside-store sales.

Time series analysis was conducted on coffee sales, with forecasting implemented using ARIMA and Exponential Smoothing models to predict future demand for all stores. This analysis helps Family Express plan their inventory. Additionally, a store performance comparison was carried out, evaluating impact of CTO activations (opening of hot food items inside store) on sales across locations to identify high-performing stores and areas requiring operational improvements.

Large Language Models (LLMs) were run locally to not send any sensitive data to third-party organizations like OpenAI and to generate AI-ready prompts, enabling smart data interactions and simplifying complex business queries. This allows end-users without technical expertise to get insights through natural language interactions.

Finally, by integrating correlation models, time series forecasting, and AI-driven insights, this platform equips Family Express with data backed strategies to enhance operational efficiency, improve sales forecasting accuracy, and support informed decision-making.

Yaggy Road Roasting Co currently relies on a largely-manual system to track coffee orders, supplies, and production status. This creates additional overhead, as order fulfillment and production planning are not seamlessly integrated, leading to increased labor and potential delays. Without an automated system, tracking inventory levels, scheduling roasting, and ensuring timely fulfillment requires significant manual effort that is prone to error.

This project aimed to develop a fully automated tracking and fulfillment system to optimize resource utilization, reduce labor costs, and improve overall operation. A key objective was to integrate order demand with real-time inventory levels, allowing for more precise scheduling of time-sensitive roasting processes. Automating these functions enables the company to maintain better stock control, reduce waste, and ensure that coffee production aligns more closely with incoming orders.

To improve the overall functionality and usability of this product, we implemented it into a website, thereby allowing higher platform independence for the software. Primary goals for the project included a sleeker design, usage logging, and better product inventory management to help aid future coffee roasting needs. These goals derive from the existing, limited solution.

Several challenges had to be addressed during the project, including working within a constrained timeline, assessing whether to keep, replace, or extend the company’s existing partial solution, and gaining a deep understanding of their current workflow. By tackling these issues, the goal was to create a streamlined system that enhances efficiency, reduces manual effort, and ultimately improves the overall workflow of Yaggy Road Roasting Co.

Backend design requires a deeper understanding of systems and technologies in a software project. In Sales Data Insights Project for Family Express, we designed and developed a secure, modular, and scalable backend system to support the analysis of multi-year, multi-store retail and fuel sales data. It also enables automation of data workflows to enhance strategic decision-making.

The system infrastructure supports data analysis by pre-processing and transforming data into a suitable format for effective analysis and insight generation. The backend is designed to deliver analytical output for frontend visualization while ensuring secure, reliable, and high-performance access through authorization controls. A well-structured backend architecture enables the dynamic routing of analytical data based on timeframe and location filters, with FastAPIimplemented for clarity, scalability, and efficient routing. To address secure authentication challenges, APIs are equipped with token management and refined permission layers using secure JWT-based authentication and role-based access control. Generative AI-based reasoning posed challenges, particularly when using externally hosted cloud models, leading to access restrictions, latency issues, and reduced flexibility. The developed architecture integrates generative AI tools to provide narrative insights, leveraging locally hosted models on platforms like LM Studio and LLaMA3 for greater customization, privacy, and control.

In this project, we designed and developed a structured backend system that effectively bridges data analysis with user-facing tools, while coordinating multiple backend components seamlessly, incorporating machine learning algorithms and AI-reasoning into the project. Our design serves as a practical reference for future projects requiring coordinated data analytics, automation, AI-reasoning, and insight delivery.

This project defines and develops a framework for evaluating Java applications generated by large language models (LLMs) in terms of their ability to withstand cyber-attacks. It integrates OWASP-supported tools for vulnerability detection and the NIST Risk Management Framework for standardized risk assessment. This study aims to assess how effectively LLMs can produce secure code and establish a reproducible methodology that connects AI-assisted development with industry security standards.

The framework begins by selecting a pool of LLMs and constructing prompts that vary in emphasis on secure coding practices and attack vectors. This variance allows the study to assess both the inherent security of AI-generated code and the influence of prompt engineering. Prompts with explicit security considerations are compared to neutral ones to evaluate model responsiveness to secure design guidance.

The applications are analyzed using a layered framework based on the OWASP Top 10, which outlines significant web application security risks. Static analysis with SpotBugs and FindSecBugs identifies issues like injection flaws and weak cryptography. OWASP Dependency Check detects known vulnerabilities in third-party libraries. OWASP ZAP simulates real-world attacks to uncover runtime risks like Broken Access Control and Cross-Site Scripting (XSS).

The NIST API then processes all identified vulnerabilities, standardizing the results and assigning risk levels based on threat source, likelihood, and impact. These assessments reveal how securely each LLM performs under different prompting conditions.

The framework highlights the impact of prompt design and model choice on security outcomes, offering a structured method for evaluating AI-generated software against industry benchmarks.

A well-designed frontend ensures easy navigation and interaction, allowing users to find what they need quickly and efficiently. Businesses rely significantly on data-driven decision-making to remain competitive in the fast-paced retail environment and the frontend of the associated software is the opening of that software. In this project, we have created an interactive online application that facilitates turning the raw sales data into insightful business information. It combines cutting-edge technologies with contemporary user interface design.

Our application has an intuitive user interface that makes use of predictive modelling and real-time data visualization. It displays complicated sales data in an understandable and approachable manner by utilizing interactive chart frameworks like Chart.js and D3.js, as well as React.js for a dynamic front-end. This integration presents several challenges, primarily stemming from the libraries differing approaches to Document Object Model (DOM) manipulation and data handling.

In order to improve the operational efficiency, we help the firms to examine sales patterns, spot trends, and make well-informed findings.And also have the feature that enables businesses in multiple locations to analyse their sales performance and optimise the inventory distribution. Furthermore, we have AI-driven insights that automatically analyse sales patterns and provide predictive recommendations. This empowers business to optimise operations and maximise profitability. We also put a key feature in our system that is the admin dashboard,which enables administrator to manage the user access by approving or denying the requests for accessing this site.

Usability is what we considered as the top priority, thus developing a responsive and user-friendly design that adjusts effortlessly across devices was designed. By integrating the modern frontend technology with a well-structured interface, our platform enables businesses to make informed decisions, streamlining the processes, and maximise efficiency. This project highlights the importance of frontend development in providing data-driven insights via an intuitive and an interactive user interface.

Enterprise level applications are notoriously complex to design, implement, and maintain, oftentimes burdened by the intricate nature of enterprise architecture. This project investigated the applicability of enterprise design patterns, drawn from Martin Fowler’s Patterns of Enterprise Application Architecture, within a simulated enterprise environment, focusing on their impact on complexity and maintainability for a single-person development team. The project, “Melin”, a full-stack web application enabling students and faculty to manage academic references (import/export, DOI/ISBN search, manual creation, cloud storage, citation/bibliography generation), was developed over 14 weeks using an iterative Scrum/Kanban approach with 3-week sprint cycles. While implementing the Repository and Unit of Work patterns presented unnecessary complexity, patterns such as the Service Layer, Data Transfer Objects (DTOs), and Model-View-Controller (MVC) demonstrably improved code maintainability and reduced coupling between modules. This project found that while Repository and Unit of Work patterns have their uses in specific situations the modern web application framework oftentimes includes a layer of abstraction that implements one or both of these patterns. Meanwhile other patterns provided significant advantages in terms of code organization and maintainability, even within a solo-development context. These findings suggest that even when enterprise scale solutions are performed by smaller teams, they can still be used to reduce the overall complexity of the application, thus making the longevity of the project longer.

Corn production is significantly impacted by pests and diseases, leading to substantial yield losses and economic damage. Traditional detection methods are time-consuming, labor-intensive, and rely on expert knowledge. Artificial Intelligence (AI), specifically machine learning and computer vision techniques, can provide an efficient solution for pest and disease detection in corn. This study explores the use of AI models for automated detection and classification of pests and diseases affecting corn plants.

The dataset used for this research is the Corn Leaf Disease Dataset, which includes a total of 4188 images for classifying four types of corn leaf conditions: Common Rust (1306 images), Gray Leaf Spot (574 images), Blight (1146 images), and Healthy (1162 images). This dataset, derived from the PlantVillage and PlantDoc datasets, is publicly available for research and provides valuable resources for developing AI models aimed at detecting and classifying plant diseases in corn. Using this dataset, we trained AI models, particularly Convolutional Neural Networks (CNNs), to detect and classify plant health issues. Various AI algorithms were tested for accuracy and efficiency in real-time disease identification.

By integrating AI into pest and disease detection, this research could contribute to the advancement of precision agriculture, reducing the need for chemical treatments, optimizing resource utilization, and enhancing sustainable farming practices.

Sensit Technologies, based in Valparaiso, IN, manufactures gas leak detection equipment. They currently utilize a locally-developed Manufacturing Execution System to gather production data for analytics, but they desire a replacement with additional features such as providing work instructions (currently paper-based) and gathering more detailed information. This project sought to create a more fully featured version of the existing locally built suite, known as MESS (Manufacturing Execution Software System). This new version of MESS is a web-based application with an SQL database and is developed using C#, Blazor, and ASP.NET Core Identity. New features include allowing operators to record their part of a product’s assembly step by step, documenting failures, and automatic step timing. As an additional customer need, MESS 2.0 has enhanced batch part number entry with a QR code scanner and access to work instructions in multiple formats. Incorporated into MESS 2.0 is “Phoebe,” an additional administration interface that manages users, configures product lines, and controls workstation access. The enhanced system should also provide customer service representatives with increased part traceability features to track components for recalls and support. MESS 2.0 will enable optimized assembly processes while maintaining Sensit Technologies’ commitment to quality workmanship and rapid turnaround by integrating real-time production balancing (rebalance) and structured work instruction management. Primary software engineering challenges faced in this project were understanding the customers’ in house vocabulary and finding solutions that meet existing software needs while simultaneously accommodating for new requirements.

Since the 1980s, the United States has seen income increasingly accrue to firm and capital owners. Business productivity has grown 2.7 times as much as worker pay, indicating a growing percentage of profits that go to firm owners and shareholders – those who own capital in the economy. This trend is coupled with growing income inequality: the top 1% of earners, who own 54 percent of public equity markets, have seen their share of overall income double from 10% to 20%. The United States economy has gradually shifted away from labor during this period, with the labor share of income falling to 56% in 2019, down 7% from 1980. Given businesses’ role in these phenomena, investigating the impacts of corporate taxation is relevant. Corporate taxes have nominally declined from 46% to 21%, and significantly as a percentage of GDP, from 2.6% to 1%. Naturally, questions arise regarding corporate tax cuts’ contributions to rising income inequality. This paper first examines the literature on corporate taxes’ effects on inequality and welfare. It explores potential mechanisms behind this relationship: the share of labor and capital income, firm investment response, firm behavioral response, and tax incidence theory. Using data across 24 countries from the World Inequality Database and OECD from 1994-2023, it empirically investigates the relationship between corporate taxes and income inequality, with the expectation that lower corporate taxes increase income inequality. It finally discusses where corporate taxes may fall short as a mechanism to address income inequality, and policy gaps for future research.

This paper investigates the impact of paid maternity leave on the reentry rates of women into the labor force after the birth of a child. Paid maternity leave policy refers to a government benefit that allows women, and oftentimes their partners, to take time off work following the birth or adoption of a child. Additionally, the duration of this leave is also a significant factor in influencing women’s return to work.. The International Labor Organization has recommended that 18 weeks is the optimal duration of leave for the well-being of the mother and child. According to the Bureau of Labor Statistics, around 70% of women in the US do not have access to paid maternity leave of this recommended length. Researchers (Anderson, Binder, Krause 2002) have labeled the disadvantages manifest in the form of reduced career advancement opportunities and wage disparities as the “motherhood penalty.” The motherhood penalty can be attributed to the lack of paid maternity leave. Using cross-country data from the Bureau of Labor Statistics, The World Bank, and the Organization for Economic Co-operation and Development, for the time period 1995 to present day, this paper conducts a comparative analysis of the impact of paid maternity leave policies on labor force participation rates of women in the US and other countries. The findings of this paper will have significant policy implications for both the duration of paid maternity leave as well as the wage replacement rates for new mothers.

The idea for this project is to see if using games and movement in a lesson will help students’ comprehension of a lesson. I wanted to test this because students sitting for a long period of time will start to zone out and lose interest. When students zone out and you go to do an assessment the student won’t remember as well because they weren’t engaged in the lesson. The theory I used for research is Vygotsky’s theory because it is about using play-based learning in the classroom and having a collaborative approach to learning. My hypothesis for this project is that movement and games help students’ comprehension. First, I introduced a reading passage to the students and then the next day after reading it I had them take an assessment that asked 5 questions of all multiple choice. Then I read the students the passage again the next day and then I played a jeopardy game with them, they answered questions based on the passage while working in teams. The students came up one at a time against someone with the opposing team and whoever answered correctly first got the points for their team. After the game was finished, I gave them the same assessment with the same questions. Lastly I compared their results before and after the game. When I tested this, I actually found positive results. The scores improved from the first time so playing a game and moving around helped them comprehend the passage better.

After meeting with my cooperating ESL teacher and having a conversation with her, I became curious about the connection between speech errors and ELLS. Upon further research I found that there is often a misrepresentation of ELLs in special education programs due to errors they make when speaking. The purpose of this study is to find out whether the speech errors made by ELLs are a result of articulation differences between their first language (L1) and English (L2). Through the implementation of a series of phonics interventions in small groups, I collected written and audio data to analyze to see if the original articulation errors were related to natural differences between language articulation.

The intersection of English Language Learners (ELL) and students receiving Special Education services (SPED) presents challenges in the identification and assessment processes, often leading to misidentification or delayed interventions. This problem arises from linguistic and cultural factors, which can cause language barriers to be mistaken for learning disabilities and vice versa. As a result, ELL and SPED students may not receive the appropriate services or may be placed in unsuitable programs, slowing their academic success. This paper examines how these overlapping categories affect the identification and assessment of students, highlighting the need for more integrated, culturally responsive approaches. Through an analysis of existing literature, case studies, and best practices, the paper states the importance of adapting educational systems to better support these students. The research explores how language proficiency tests, academic assessments, and special education evaluations may be affected by language barriers and cultural differences. It also proposes strategies such as early intervention, professional development for educators, and culturally responsive assessments to improve identification accuracy and ensure timely support. By having collaboration among educators and focusing on the needs of dual-identified students, this study aims to better educational experiences for ELL and SPED students, ultimately leading to more equitable and effective educational opportunities.

I will be asking the following question of how implementing CREW in the class’s morning routine affects student behavior throughout the day. At Edgewood Elementary school teachers are required to conduct a morning meeting referred to as CREW, which addresses social emotional learning foundations with the class. They have stated in staff meetings that schools who implement CREW time effectively often see a reduction in disciplinary problems and improved attendance. Students are less likely to act out when they feel supported emotionally, have strong peer relationships, and see school as a positive environment that meets their social and emotional needs.Content of CREW is different each school day, addressing topics from bullying, identifying emotions, and using inclusive terminology. I decided to use this as my research topic since many staff and students have expressed that the recent lack of CREW time in the classroom routine has shown an increase in bullying, emotional outbursts, and the lack of opportunity to set the day in a positive manner. Many students struggle with negative interactions not only in the classroom, but during specials, recess, and other school activities. A number of students also struggle to identify how they are feeling when confronted with strong emotions, allowing them to build it up rather than express it and counteract it. Since time seems to be the main issue with dedicating time to CREW, I am going to plan small interventions throughout the day that students can interact with. I am most interested in seeing how these small interventions will limit classroom disruptions, negative talk between students, and self talk. Implementing CREW routine back into the routine these principles create a classroom environment where students feel safe, valued, and motivated, which helps to minimize negative behaviors while encouraging positive ones.

What systemic and instructional barriers prevent the effective integration of ELL students’ cultural backgrounds and interests into classroom instruction, and what strategies can educators use to overcome these challenges?

My research exapands on the direct influence of incorporating hands-on, interactive science experiments into the elementary science curriculum. My research is based on student engagement and understanding of key scientific concepts. Through surveys and classroom-based observations, data was collected from three different elementary teachers and their students to compare outcomes between hands-on learning and directly lectured based instruction through a book. This study showed students who engaged in interactive science experiements demonstrated higher engagement and comprehension of science topics. Hands on lessons were reported by teachers to have increased test scores, morale, engagement, and understanding. It was also reported that this study showed collaboration with others, boosting students building off of each other during interactive science experiements. Teachers that filled out the survey stressed that they value hands on learning, and it directly showed within data collected.

Teacher induction is a type of program which provides support to new teachers during their first few years of teaching. Induction programs can vary in content and format; components of an induction program can include new teacher orientation and seminars, mentorship, instructional coaches, and collaboration with other teachers and colleagues. Many new teachers leave their schools or the teaching profession because they feel overwhelmed, isolated, and unsupported. A comprehensive induction program can be beneficial to novice teachers by helping them build their confidence and competence in the classroom. The purpose of this study was to examine the effectiveness of induction programs for new teachers and the perceptions they have of their induction support.

This case study explored the induction experiences of seven novice teachers who were all graduates of the same alternative certification program. Quantitative research analyzed survey responses through descriptive statistics. Qualitative research analyzed responses to open-ended interview questions. Interrater analysis was used to identify codes for the open-ended interview questions and six themes emerged from the interview responses: (a) collaboration, (b) support, (c)observation, (d) training/meetings, (e) self-efficacy, and (f) mentor support. Findings from this study have implications for induction design and structures to help to promote novice teacher development.

The BCON-2 satellite mission aims to enhance downlink time by utilizing the receive-only ground stations of the Satellite Networked Open Ground Station SatNOGS network and optimizing the scheduling of satellite passes along its orbital footprint. Due to the physical constraints of the mission, it was not possible to develop a deployable ultra-high frequency antenna while also ensuring that the antenna operated with enough gain at a center frequency of 435 megahertz. To address this challenge, a Square Koch Fractal Slot Antenna was designed and developed as a compact and effective alternative.

The Square Koch Fractal Slot Antenna is formed using two second-iteration square Koch curves, each consisting of eight segments. The use of fractal geometries allows for miniaturization while maintaining effective operation within the ultra-high frequency band, making it a suitable solution for small satellite missions with significant design constraints. Building upon previous research, this work demonstrates how fractal slot antennas can provide optimized performance in restricted physical spaces. The antenna was designed, simulated, and fabricated to validate its effectiveness for communication applications in the BCON-2 satellite mission.

This student-led project, in partnership with NearSpace Education, focuses on designing, constructing, and programming a payload for integration into an existing satellite platform. The payload is built to fit within a 0.5U CubeSat form factor measuring 10 cm × 10 cm × 5 cm and serves as a testbed for autonomous downlink scheduling through the SatNOGS network, a global open-source ground station network.

To develop this, the team utilizes the open-source COMMS architecture by the Libre Space Foundation. This allows for hands-on experience in small spacecraft payload integration, mission operations planning, and communications subsystem design. The project also draws on tools and protocols developed by AMSAT to support amateur satellite communications.

The primary goal is to develop and validate flight software capable of autonomously scheduling and executing downlink passes, optimizing communication opportunities without requiring manual intervention. This approach aims to improve satellite-ground coordination, particularly for receive-only networks like SatNOGS.

This poster highlights the conceptual foundations of autonomous satellite communication, the technical challenges faced in limited-volume payload design, and the software development process. Future phases of the project will focus on in-orbit testing and refining the downlink optimization algorithm to support broader applications in small satellite missions.

The purpose of this project is to research, test, design, and fabricate a custom microchip. The focus is on CMOS VLSI with an emphasis on digital logic design, design methodology, and testing techniques. The microchip is designed using Verilog and simulated using a suite of tools and testbenches such as Cocotb, GTKWave, and Icarus Verilog. Once verified, the design is submitted to Tiny Tapeout for fabrication.

The chip functions as a base-60 binary clock that displays time in a 12-hour format using 16 LEDs. The time can be set using a switch and a few control buttons, allowing it to be synchronized with the real-world time. This project demonstrates the full workflow from digital design to physical chip fabrication, with a key objective of validating the design before production.

The expected outcome is a functional, fabricated microchip that successfully implements the binary clock design. Through this work, insights are gained into the design process of ASICs, from an HDL to real-world hardware. This research contributes to the undesrtanding of digital design and chip prototyping methods.

The Valparaiso University Satellite Project is developing a 0.5U CubeSat payload in partnership with Near Space Launch (NSL). This abstract highlights the NSE Bus Emulator, a critical testing platform that replicates the NSL ThinSat bus interface.

Our emulator consists of a custom-designed PCB, fabricated through JLCPCB with SMD components pre-assembled, integrated with an Arduino Mega. The hardware provides identical mounting and connector configurations to the actual ThinSat bus, supplying regulated power rails (3.3V, 5V, and BUSS6-9V) with current measurement capabilities and software-controlled power switches.

The software builds upon NSL’s proprietary Arduino code, enhanced by our faculty advisor to improve power switching control and transmission command handling. These modifications enable accurate simulation of the ThinSat bus behavior.

This emulator is essential for testing our satellite’s communications system, which uses both NSL’s Iridium-based S4 radio and a custom antenna for downlinking data to SatNOGS ground stations. Through the emulator, we can simulate uplink commands, test payload responses, and verify power consumption before integration with flight hardware.

Beyond its technical function, the emulator provides students with practical experience in PCB design, embedded systems programming, and hardware-software integration. As we progress toward launching our first satellite, the NSE Bus Emulator remains critical for final validation testing, ensuring mission success while building capacity for future space science research at Valparaiso University.

This ten-minute, five-person play explores the afterlife of four ghosts from all different walks of life and their intersection with a living girl, all in the same apartment. This comedic play exhibits the importance of cooperation, understanding, and empathy, as well as discussing the philosophical ideas of life and death. Unfinished Business stays true to its title by discussing what business people may leave behind, and how important may be to finish it.

This paper focuses on the sorority experience at Valparaiso University in order to reveal how traditional gender roles and expectations influenced housing disparities and geographies that still exist today. From their inception, collegiate fraternities and sororities have fostered a sense of place, personal development opportunities, increased retention for universities, and other social benefits that are unique to each member. While they serve similar purposes, they are governed by separate rules and expectations, resulting in vastly different experiences. Sorority culture at Valparaiso University diverged from other schools in the early 1960s when the sororities collectively moved into Scheele Hall, an on-campus dormitory. Designating Scheele Hall as the home for Valparaiso University’s sororities initiated a paradigm shift in the culture of sorority life that is still embodied today. As a symbol of Greek life, Scheele Hall facilitated visibility, leadership, and community that made Valparaiso University’s sorority life real and helped keep the culture alive for over a century. Today, the physical and cultural geography of Valparaiso University is changing. Mid-twentieth-century buildings are aging, enrollment demographics are shifting, and the liberal arts curriculum is weakening. These changes will culminate in university-wide cultural changes, which will undoubtedly impact the institution’s role in the sorority complex’s landscape. Therefore, the future of sorority life is dependent on the culture wars being fought today.

This project analyzed soil parameters from multiple locations owned by the Shirley Heinze Land Trust in Porter County, Indiana, some of which are being ecologically restored or have been restored in the past. The samples were collected from prairie, forested wetland, riverine wetland/floodplain ecological areas, and current agricultural areas that are to be restored to each of those same environmental types. To measure the effectiveness of the rehabilitation mentioned above, this project compared bulk density, soil chemistry, organic matter, aggregate stability, and particle size analysis from the agricultural area to those from restored and natural settings. This allowed the estimation of targets and a baseline to assess the effectiveness of future rehabilitation projects. The results helped us to learn more about restoration projects on plots of land that have been used for agriculture for an extended period of time and can help other environmental projects find effective ways of rehabilitating formerly cultivated land.

This paper examines the life and groundbreaking contributions of the underrecognized Dr. Mary Leakey to the field of paleoanthropology. This paper focuses on Mary’s role in reshaping the understanding of human evolution. It begins by examining her early life to identify the reasons behind her passion for paleoanthropology before leading to knowledge known before Mary’s work began in the 1930s. This recognition assists in explaining what was known before Mary’s involvement, as the field of paleoanthropology was still in its early stages, with limited fossil evidence and a fragmented understanding of human origins. After establishing what was known before Mary’s career, the paper shares the pivotal discoveries made over her five-decade career, including the Proconsul africanus from 18 million years ago, the Laetoli hominin footprints from 3.75 million years ago, and some of the most significant of the fifteen new species Mary discovered. By focusing on Mary’s achievements, this paper seeks to highlight her underrecognized contributions, often overshadowed by her husband, Louis Leakey, and argue for her significant role in the development of modern paleoanthropology. This paper will also explore her impact on paleoanthropology by examining how Mary found critical fossils of early hominins that changed ideas about human evolution and will conclude with an explanation of Mary’s achievements in the field and an insight into how modern paleoanthropologists continue building on Mary’s work.

One aspect of being an undergraduate is being able to reflect on student’s leadership journey’s at Valpo. Because of this, I wanted to work with CITAL and other departments to figure out a way for the university to continue and bring into conversation student leadership and make it a part of the curriculum. As a student who has been involved in over a half a dozen organizations and been a student president of three at the same time, I want to be able to use my knowledge of Valpo and quantify that experience so that other students can maximize their leadership time at VU. I am also looking at other schools and finding out that having a leadership portfolio built into the CORE curriculum is not very common, and as Beacons, we should be trailblazers in providing an education that surpasses other instiutions.

The financial valuation of NFL running backs has become a critical aspect of team management, with contracts often sparking debate over player worth. This study examines the relationship between in-game performance metrics and salary outcomes to develop a predictive model for running back compensation. Using historical data, I analyze key performance indicators—including rushing yards, touchdowns, carries, and yards per attempt—alongside financial factors such as contract value, average annual salary, and guaranteed money.

Through machine learning techniques, specifically Linear Regression and Random Forest models, I identify the most significant predictors of running back salary. These results will hopefully help give a better understanding as to why teams are both undervaluing and overvaluing certain players based on on-field performance

Traffic congestion is a significant issue in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. Traditional traffic management methods, such as fixed traffic signal timings and manual interventions, often fail to adapt dynamically to changing traffic conditions. This study explores the application of predictive analytics and machine learning techniques to optimize traffic flow and reduce congestion. By leveraging historical traffic data, real-time traffic monitoring systems, and external factors such as weather conditions and road incidents, predictive models can be developed to forecast congestion levels and suggest optimal traffic management strategies.

The methodology involves data collection from multiple sources, processioning for quality enhancement, and the application of machine learning algorithms, including decision trees, random forests, and neural networks, to predict traffic patterns. These models will help in dynamic traffic signal control, congestion mitigation, and route optimization. The anticipated outcome is a smart traffic management system that enhances urban mobility, reduces delays, and contributes to sustainable transportation infrastructure. This research can potentially aid city planners, transportation agencies, and policymakers implement data-driven solutions for improving urban traffic efficiency.

Abstract:
The Lotka-Volterra model, introduced by Alfred Lotka and Vito Volterra, is fundamental in mathematical biology and ecology, describing predator-prey interactions through differential equations. While insightful, its practical application is often complicated by uncertainties in data due to noise or incompleteness. Traditional deterministic methods struggle with such variability, making Bayesian statistical methods a powerful alternative for robust ecological modeling.

In this study, we generate synthetic population data using the classical Lotka-Volterra equations with added Gaussian noise to simulate real-world measurement error. We apply Bayesian inference, implemented via the PyMC3 probabilistic programming library, to estimate model parameters. Priors are assigned to each parameter, and a likelihood function is constructed under the assumption that measured data follows a normal distribution around the model output. Using Markov chain Monte Carlo (MCMC) sampling, we obtain posterior distributions for parameters, offering a comprehensive representation of their probable values and uncertainties.

Our results demonstrate the efficacy of Bayesian methods in handling uncertainty and enhancing ecological modeling. Unlike traditional point estimates, Bayesian inference provides full posterior distributions, particularly useful when data is noisy or scarce. This approach aligns with modern trends in probabilistic programming and computational statistics, as seen in Carpenter et al. (2017) on Stan. By integrating traditional ecological models with advanced statistical techniques, this framework improves the adaptability of the Lotka-Volterra model in contemporary research.

Keywords:
Lotka-Volterra Model, Predator-Prey Dynamics, Bayesian Inference, Ecological Modeling, PyMC3, MCMC Sampling, Computational Statistics, Posterior Distributions

Abstract: Fraud Detection in Health Insurance Claims Using Machine Learning

This project focuses on detecting fraudulent health insurance claims using machine learning techniques. The dataset includes various patient attributes, claim amounts, and medical details, which were preprocessed by handling missing values, encoding categorical features, and standardizing numerical data. Fraud detection was formulated as a classification problem, where claims in the top 5% of the cost distribution were labeled as potentially fraudulent. Several models, including Logistic Regression, Random Forest, and XG Boost, were trained and evaluated, with Random Forest providing the best performance after tuning.

To gain deeper insights, multiple visualizations were created to analyze fraud patterns based on age, region, smoking habits, blood pressure levels, and feature correlations. While initial models exhibited overfitting, techniques such as feature selection, SMOTE balancing, and adjusting fraud detection thresholds improved generalization. The final optimized model achieved a balance between high precision and recall, making it suitable for real-world applications. Though deployment was initially considered, the project concluded with a locally usable model for fraud prediction, ensuring robust, data-driven decision-making for healthcare fraud detection.

Keywords:

• Insurance Claims Classification
• Predictive Analytics
• Fraud Detection
• Machine Learning Models
• Random Forest Classifier
• Claim Amount Prediction
• Data Preprocessing
• Feature Importance Analysis
• Logistic Regression
• XG Boost

Chronic diseases like cardiovascular diseases and diabetes account for a considerable proportion of worldwide mortality rates, and early detection and prevention?are pivotal. The purpose of this project is to create a model that predicts the onset of?chronic disease using available physiological data from wearable devices. The system aims to apply machine learning and deep?learning methodologies to generate early warning alerts for the patient and their caretakers, as well as personalized preventive care based on continuous health monitoring of the patient. Wearable technologies, despite?the current battery life and device bulkiness limitations, represent a promising avenue for collecting and analyzing health data at scale(Yanagita, M. (2023)).

The project also includes a web platform that will promote a community where patients, doctors, and other healthcare professionals can share knowledge and?provide and receive support. It would be a central site for tracking risk factors, providing health alerts,?and enabling early treatment. In the?longer run, this two-phase program is intended to transform chronic disease management by providing users with accurate prediction, to help to reduce dependence on expensive traditional tests and placing the power in the users’ hands to enable them take responsibility of their health(Yanagita, M. (2023)).

Keywords: Chronic disease prediction, wearable health devices, early detection, preventive healthcare, machine learning, deep learning, real-time monitoring, health analytics, digital health platform, personalized medicine, health forecasting, cardiovascular disease, diabetes, health data integration, patient engagement.

References:

[1] Sato, Y., Silina, K., van den Broek, M., Hirahara, K., & Yanagita, M. (2023). The roles of tertiary lymphoid structures in chronic diseases. Nature Reviews Nephrology, 19(8), 525-537.
[2] Jomova, K., Raptova, R., Alomar, S. Y., Alwasel, S. H., Nepovimova, E., Kuca, K., & Valko, M. (2023). Reactive oxygen species, toxicity, oxidative stress, and antioxidants: Chronic diseases and aging. Archives of toxicology, 97(10), 2499-2574.

Wearable health monitoring systems, integrated with data-driven predictive models, are transforming personalized healthcare by enabling early disease detection and proactive intervention. Traditional health monitoring relies on rule-based thresholds and prior medical knowledge, limiting adaptability to individual variations. This project leverages machine learning models—Random Forest, Support Vector Machines (SVM), and Neural Networks—to analyze physiological data from wearable devices, enhancing predictive accuracy in detecting conditions like heart disease and sleep apnea.

The study addresses the growing need for real-time, personalized health monitoring, particularly as populations age and chronic diseases become more prevalent. Arizona serves as a testbed for validating model performance under real-world conditions.

Data is collected from pulse ellipsoid levels, sleep wave patterns, ECG readings, and blood oxygen saturation (SpO?) measurements. A structured preprocessing pipeline ensures data quality, employing missing value imputation, normalization, and feature engineering to enhance model performance.

Evaluation metrics, including accuracy, precision, F1-score, and cross-validation, validate the models. A key challenge—performance deterioration with new data—is mitigated through retraining strategies. Live health monitoring with alert mechanisms further enables real-time detection of abnormalities and early medical intervention.

Findings demonstrate that machine learning-based predictive models outperform traditional methods in detecting health risks and enabling preventive care. This study concludes that integrating predictive analytics into wearable devices enhances personalized healthcare, improving patient outcomes and reducing emergency health events.

Bitcoin was designed to be a decentralized peer-to-peer cash system, which creates scarcity in two ways: the total supply of Bitcoin available, and the block size of each block. The blocks, which form what is called the Bitcoin Blockchain, can contain at most 4 MB of data. Since the size of blocks is limited, and each transaction takes up some size, the number of transactions included in a block is necessarily limited. To combat this, users incentivize their transaction to be included in a block through a transaction fee, or the price the transactor pays a miner to include their transaction in a mined block. The miner, by validating the transaction and including it in a block can claim the fee as compensation. This price is typically quoted in satoshis per virtual byte or sat/vB. This will be the primary target unit for our fee estimation algorithm. What we propose is combining several data sources of current blockchain activity to predict the optimal fee. This approach is purely empirical, not relying on a theoretical model or explicitly estimating the time that the next block will be found. Additionally, we will also display the results of said algorithm to a monitor, utilizing MLFlow, so as to best visualize our results. This will enable us to better predict the costs of Bitcoin mining.

This project presents a movie recommendation system that leverages machine learning algorithms to suggest movies based on user input. By combining features such as lead actors, genres, and directors, the system creates a comprehensive profile for each movie. Using Count Vectorization and cosine similarity, the system calculates the similarity between movies and provides recommendations. The system normalizes movie titles to ensure robust search functionality and retrieves the most similar movies based on user searches. Implemented with Flask for the web interface and FlaskUI for desktop deployment, this system demonstrates the potential of machine learning in enhancing user experiences through personalized recommendations in the entertainment industry. The project showcases how integrating multiple features and advanced algorithms can significantly improve the accuracy and relevance of movie recommendations, making it easier for users to discover new movies that match their preferences.

In the nearly three years since the Ukrainian-Russian war officially began, it has become increasingly clear that neither country can obtain a total military victory. That is, some type of negotiated, or arbitrated, outcome must be achieved. In this presentation we explore what a solution obtained by the Nash Arbitration Method (NAM) might look like.

Fanfiction, particularly on the platform Archive of Our Own (AO3), offers a vast and
unique dataset for studying how individuals reinterpret narratives and portray marginalized identities. AO3 is notable for its lack of traditional content moderation, allowing for a broad range of unfiltered self-expression. Its user base is also demographically distinct, with significantly higher representation of non heteronormative and female identities compared to the general population. This provides a valuable opportunity to analyze trends in representation, identity, and objectification within fan communities, particularly with the focus on how media types developed in a female and LGBTQ-dominated community represent relationships. This research investigates the intersection of fetishization and identity on AO3 by analyzing its tagging system and metadata. Using re-processed data from AO3’s selective statistic dump, methods such as Chi-Squared and Bayesian Modeling are used to assess the size and significance of prevalence of fetishization-related tags across genres and ratings. Additionally, natural language processing is used to identify thematic groupings and trends in content. A key focus is on understanding how different subsets of marginalized identities are sexualized in comparison to broader author demographics, revealing potential biases in fan-created media. One notable trend is the prevalence of homoerotic fanfiction, which appears at a disproportionately high rate compared to author demographics. Despite a majority-female user base, homoerotic fiction is significantly more common than other relationship dynamics and is more likely to contain sexual content. This understanding contributes to recognizing and addressing issues with representation and objectification in digital fan spaces.

Computational fluid dynamics (CFD) is used to model objects based on the principle of fluid mechanics, with governing equations built in to understand how the fluid moves in the object. This study seeks to understand the fluid motion (air) of a Boeing 737 airfoil, a commonly used aircraft by airline companies, under different conditions in different stages of flight: takeoff, cruising, and landing. The primary objective is to compare steady state versus unsteady state due to velocity and turbulence at various stages of flight. Causes of unsteady state flow are weather, jet stream, mountain waves, and interaction of the surrounding during takeoff and landing. From my CFD model, I expect to see turbulence depend more on the velocity and the pressure when the airfoil is taking off and landing, compared to cruising. With this, comparing the lift coefficient at each of the stages of flight, the lift coefficient had a greater impact on the airfoil during takeoff and landing than cruising.

Adaptive switches are crucial in the field of assistive technology and enable people with mobility challenges to interact with their environment. However, the high cost of adaptive switches limits accessibility. While additive manufacturing has reduced cost, existing designs primarily focus on functionality over innovation. The failure to address different types of sensory issues and cost reduction has led to a limited market. The goal of this project was to develop accessible, low-cost options that considered sensory processing issues. We studied materials, electrical and mechanical components, and types of manufacturing to optimize the design and functionality for an adaptive switch. We developed two open-source, cost-effective, adaptive switches with the use of additive manufacturing: one basic model and one premium model. The basic switch consists of a simple push button design consisting of springs and a switch sensor with a removable push button plate, with an estimated cost of $10. This basic switch mirrors pre-existing switches, but at a lower cost while maintaining functionality, quality build, and user-friendliness. The premium switch consists of switch sensors, a removable push button plate, a speaker, and the ability to add different textures to the surface of the push button, with an estimated cost of $30. This premium switch focuses on addressing tactile and auditory sensory challenges while maintaining user-friendliness. These prototyped switches are cost-effective, functional switches, and enhance future innovation due to their open-source availability. This work demonstrates potential advances in making assistive technology more accessible.

Adaptive and assistive technology is an important field that allows for devices that can greatly improve an individual’s life. The GoBabyGo program empowers 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 create a step-by-step guide to modify basic cars for children with conditions such as cerebral palsy, spina bifida and chromosomal disorders. This guide outlines key modifications, including the electrical adaptations for accessible controls, structures for posture stability, and other changes that could be made for individual children. To ensure effectiveness, we have researched existing modification techniques and collaborated with occupational therapists to address common challenges in adaptive technology. This guide will help provide parents, therapists and engineers with a clear understanding of how to modify and customize a specific ride-on car, empowering children with increased mobility and independence. This guide will also allow for further modifications to meet individual children’s needs.

Conveying bioengineering disciplines is challenging given younger students’ limited understanding of engineering. While electromyography (EMG) signal model exist mainly when studying sports-related activities, there is no simple model for an entry-level student to understand who does not have prior knowledge. Our design exemplifies the basics of how electromyography signals are captured and turned into code that is used to power an electrical robot arm through a software called BioPac Student Laboratory. Our system consists of two interconnected breadboards,, each incorporating two EMG signal processing channels designed with IC148 logic gates. The circuit will be powered by +-5V and include key components such as capacitors (C21, C22, C23, C26) and resistors (R25-R374). The expected outcome of this research is to provide an approachable introductory hands-on experience to EMG technology, which will inspire interest in biomedical engineering and highlight the department’s work in signal processing.

Modern airplanes typically have a line of spoilers on the back edge of the wing that when extended disrupt airflow over the surface of the airfoil. The broken-up air flow reduces the lift force and increases the drag force which slows down the plane. I am seeking to model the airflow around the wings that leads to the change in forces. Computational fluid dynamics (CFD) applications can model the flow around objects and find characteristics of the flow such as pressure, velocity, temperature, and force distributions. I made the Airbus A320 and Boeing 737 midspan airfoils in SolidWorks and imported their geometries into SimScale software for CFD analysis. Spoilers are usually deployed during the landing of the aircraft to decrease speed, and with that important function, it is vital to know the fluid flow around the airplane wing when spoilers are and are not deployed. I am conducting a CFD analysis in SimScale to model the airflow around both airfoils with and without the spoiler extended. The goal is to compare the effects of a change in geometry with the effects of spoiler extension on airflow velocity around both airfoils. This study gives a greater understanding of spoiler effect on airflow and how much airflow characteristics can be modified with changes in airflow geometry.

Liposomes are small, spherical vesicles created from cholesterol and phospholipids which show potential for oral drug administration. In order to investigate how liposome characteristics impact their stability in gastrointestinal environments, their transport across the gut epithelium, and subsequent drug access to the lymphatic system, control over liposome properties is required. The goal of this research is thus to identify synthesis conditions that allow for control of liposome size and charge, and to synthesize a panel of liposomes over a broad size range which will be used to investigate the impact of liposome properties on lymphatic uptake of orally administered drugs. Liposomes were composed of two different phosphatidylcholines (DPPC and DOPC) and cholesterol and were synthesized using the thin-film hydration method. Liposome diameter and zeta potential were characterized using a Malvern dynamic light scattering instrument. Control of product size was tested by varying synthesis conditions like the molar ratio of phosphatidylcholine and cholesterol and resuspension concentration. The impact of processing methods like sonication and filtration were also assessed. This project improves our understanding of how synthesis conditions impact liposome characteristics, enabling future testing of the impact of these characteristics on drug access to the lymphatic system.

Our goal is to develop a real-time cavitation detection system for centrifugal pumps that prevents damage without requiring prohibitively low pressures. We use acoustics for detection by recording the noise produced by cavitation with an Integrated Circuit Piezoelectric (ICP) microphone (130D20, PCB Piezotronics) and analyzing the frequency domain of the data. Computational Fluid Dynamics (CFD) models are created at different inlet pressures to compare empirical results and understand pressure drops in the turbine. Data is acquired using a National Instruments Data Acquisition (NI DAQ) system and Laboratory Virtual Instrument Engineering Workbench (LabVIEW) software on a PC. We hypothesize that cavitation is signaled by a large magnitude of noise at a specific frequency.

The study uses a two-inch polyvinyl chloride (PVC) pipe that carries water from a centrifugal pump to a heat pump tank. Initially, the microphone is held by hand, but later it is fixed using a 3D-printed fixture bolted around the pipe. We collect multiple 5-second sound recordings at pressure differences ranging from 5 pounds per square inch (PSI) to 50 PSI, with the test pressure controlled via a butterfly valve and pressure gauge. The recorded data is analyzed in Matlab for deconvolution, comparing normal pressure conditions (5 PSI) to different pressure deviations.

The analysis shows that cavitation can be detected acoustically, with distinct peaks in the Fast Fourier Transforms (FFTs) of deconvolved samples at higher pressure deviations. We then develop a Matlab program that identifies cavitation by searching for repeated peaks in the deconvolved frequency domain plots. Cavitation is detected both qualitatively and quantitatively across multiple frequencies. The system successfully detects cavitation, preventing damage and serving as an educational tool.

To better understand the effects bracing structures have on guitar sound quality, we are investigating how adding weight to an acoustic guitar’s soundboard affects its resonant frequency. Based on the typical mass of a guitar soundboard (200 to 250 grams), we predict that even a few grams of additional weight will yield measurable differences in the frequency peaks. Our objective is then to determine the minimum mass required to produce noticeable changes. We measure resonant frequencies by striking the guitar bridge with an impact hammer and recording the resulting frequency by measuring the displacement of the soundboard with a capacitor probe. This approach has provided consistent and reliable data throughout the years this experiment has been performed. Our next experiments will build on this foundation, in which we will incrementally adhere weights directly to the soundboard, increasing the mass with each set of tests. Previous data suggests that the system is sensitive enough to detect subtle variations. We hypothesize that adding small masses suffices to alter the resonant frequency, but the challenge of determining the minimum mass required remains. By systematically altering the weight, we aim to identify the threshold where frequency changes become significant. Future experiments will expand on this work by exploring how different weight distributions and placement locations on the soundboard influence resonant frequency. These investigations will contribute to a deeper understanding of how physical modifications, such as the bracing design, affect acoustic performance.

Ruth Cook (Mechanical Engineering), Thane Martin (Mechanical Engineering), Chris Noga (Physics) Advisors: Pete Johnson, Andy Richter, Rob Swanson

VAM (volumetric additive manufacturing) is a method of 3D printing that produces 3D geometries using projected light and resin. Using VAM produces layerless prints in minutes. Current methods only use a UV projector to produce a geometry. Our method of VAM aims to use projection methods of much lower power to produce comparable final objects. Due to the nonlinear nature of VAM resin, we attempt to use an ambient light source to reduce the power output of projection. The resin cures only in regions that pass a light dose threshold. The reaction of the resin could almost be viewed as if the light “freezes” the resin with the addition of enough light. Similarly, SLS (selective light sintering) uses just enough laser light to melt powder in the outline of an object. SLS uses a heated chamber just below the melting point. This allows the laser required to create the final object to have relatively lower power requirements than without. This same principle enables a lower power projector to be used in VAM, lowering the cost of such a device. Our experimentation required the creation of a standard VAM 3D printing setup as a baseline. This was done using modified consumer electronics to achieve 405 nm projection. An adjustable 405 nm LED light source with a custom lens is used to create evenly disturbed ambient light. Together, this allows for controllable printing conditions. Lower printing times and lower required projection intensity in printing are expected.

Spoilers are a common implement on modern automobiles due to their enhancement of vehicle stability and performance. Spoilers are majorly utilized in motor sports due to the introduced drag they provide that creates a downforce on the vehicle. The downforce pulls the car towards the road, increasing stability and traction. This study analyzes the effects that rear spoilers have on automobiles by utilizing computational fluid dynamics (CFD) simulations to confirm the benefit of these added forces on modern automobiles. Using Sim-Scale, a web based CFD modeling software, 3-D models of automobiles with and without a rear spoiler are simulated to compare the effects of aerodynamic drag utilizing velocity and pressure gradients. Comparing the simulated results will show the quantitative differences in forces between automobiles with and without an added spoiler. The increase in pressures introduced on the rear of the vehicle due to the added spoiler increases the aerodynamic drag of said automobile. This creates a negative lift force that provides greater traction and stability when driving at higher speeds. However, the increased drag may have a slight effect on fuel efficiency when compared to the car without a spoiler, as the drag introduced requires more power to get the vehicle up to the same speed.

This project utilizes Computational Fluid Dynamics (CFD) to analyze the accuracy and behavior of a pitot tube in measuring the speed of a moving bicycle. A pitot tube is a common device for measuring fluid velocity by comparing the stagnation pressure of a moving fluid to the static pressure. CFD can simulate the fluid flow using governing equations of conservation of mass, momentum, and energy. The CFD is done using SimScale, a free to use, cloud-based software. By simulating riding conditions, this project will examine the aerodynamic interactions between the pitot tube and the surrounding airflow. Values such as the stagnation pressure can be extracted while also investigating a more detailed view of the behavior of the air inside the pitot tube. Fluctuating pressure measurements have been observed in an experimental setting, so the goal of this project is to test 3 different diameters of the pitot tube for their steadiness in the measured pressure. The results of this study help determine the feasibility of using pitot tubes on bicycles and provide insight into the measurements that the pitot tube is making in the real world.

Cavitation occurs in centrifugal pumps, and with this occurrence it can impair the performance, efficiency, and damage the pump’s components. Researching this phenomena is crucial in mitigating damages and optimizing pump design and operations. This research will utilize Computational Fluid Dynamics (CFD) models to analyze cavitation. With a CFD approach to simulate various boundary conditions such as different inlet pressures, velocity, or flow rate, to see pressure drops and fluid flow. Utilizing basic fluid principles such Bernoulli’s equation, comparing like researches online, and comparing experimentally will be methods of validation of the developed models. The CFD models do indicate that with high rotational turbine speeds and increasing inlet flow rates, there are significant pressure drops at the blades of the turbine. With the increased pressure drops about the fins, the static pressure drops far enough to vaporize water, forming cavitation bubbles, and when pressure needed to collapse the bubble is met about the turbine it causes them to implode causing small microcracks at the blades.

Biosignal acquisition and processing are fundamental skills for students in bioengineering fields. However, existing tools fall into two main categories. Low-cost biosignal sensors are accessible and affordable, but suffer from a large amount of noise which inhibits effective learning. On the other hand, high-end laboratory-grade systems provide clean and reliable signals but are prohibitively expensive, impractical for widespread use, and are designed as “black box” systems, with fully encapsulated signal processing and noise rejection circuits. This disconnect limits students’ abilities to learn and engage with EMG and other biosignal processing techniques, especially students with limited background knowledge of electronics and complicated circuit diagrams. To address this issue we propose a modular and scalable biosignal learning platform designed to bridge the gap between low-cost and high-end systems. The prototype uses an advanced lab kit that records EMG signals to control a prosthetic gripper. The learning platform integrates a printed circuit board (PCB) for each signal processing stage (e.g., amplification, notch filtering, low-pass filtering), with clearly marked inputs and outputs that allow students to visualize the effect of each stage on the biosignal. This setup allows students to individually test stages or build other systems using preexisting PCBs. This modular architecture allows students of all skill levels to gain hands-on experience with signal processing while tracking the different stages that the signal goes through without the need to be an expert in electronics and circuit design.

A common issue with guitars is the variability in the sound they can produce as a result of their construction. Past research shows trends in listening-based studies, such as using the same brand of instrument, new strings, and pre-picked notes and chords played by a professional musician for repeatability of the recordings. This research aims to find specific keywords for describing a guitar’s sound and an outline for a questionnaire to give to a specific test group to coincide with future research regarding the quality of cheap and expensive guitars. This is achieved through the study of relevant prior research papers about the vibrational properties of guitars and previous listening-based experiments. Each of these papers has a predetermined test group and specific questions regarding important differentiations in the sound of instruments. This research presents comprehensive questions based on important factors in guitar acoustics, as well as the backgrounds that our test group should have. Research suggests that the test group should be split into two parts, one of them music majors and the other a mix of professional degrees. In addition, the best keywords to use in the questionnaire to get the most accurate response from individuals were “bright”, “balance of sound”, “rich”, “clarity”, and “sustain”.

Composers use musical composition as a form of autobiographical writing, both intentionally and unintentionally. Musical works can reflect the lived experiences of their creators even when the works themselves are not intended as personal revelations. Especially when it comes to the life and works of Franz Schubert, scholars such as Susan Youens and Lorraine Byrne Bodley have researched Schubert’s songs through the lenses of memoirs and journals, discovering certain heightened emotional aspects in his choice of lyrics and deliberate harmonic structures that appear to reflect autobiographical experiences. By regarding his songs as a reflection of his inner struggles, such as at the end of his life during his battle with syphilis, we hear an artist’s private statement about his life and relationships that he could not otherwise utter publicly. Based on my findings, I have discovered these autobiographical experiences within Schubert’s music tell a linear narrative of his life, and when one listens to his scores in order of publication, they discern a unique tale. Through a musical analysis of Schubert’s intentional text painting, this study delves deeper into Schubert’s seemingly simple lieder and probes the depths of how his personal life experiences, such as the death of his mother or his personal relationships with Josef Spaun and Franz von Schober, affected his musical creation in such a profound way.

Social Isolation in Older Adults Transitioning to Assisted Living Facilities

Background: Social isolation describes the objective state of being lonely, whereas loneliness is a subjective feeling based on relationships (Rohr et al., 2022). In a meta-analysis, 33% of an elderly population experienced social isolation (Ran et al., 2024). Based on the framework of loneliness, social isolation, and associated health outcomes (Barnes et al., 2020), the purposes of this study were to describe experiences of social isolation, loneliness, and strategies that decreased these experiences in older adults following a move to assisted living.

Methods: Using a qualitative approach, residents 65 and older (N=10), without cognitive deficits who moved to a facility within the past 3-12 months were interviewed. Participants completed the Mini-Cog© for inclusion prior to answering nine open-ended questions. After each interview, participants completed the UCLA loneliness scale. Constant comparison was used to identify major categories.

Results: Participants 70-92 years (M=82.20, SD=7.64) were female (80%) and a widow/widower (60%). Three main categories emerged: (a) resolved to leave home, (b) trust in a safe system to meet needs, and (c) having to accept a new normal. UCLA scores demonstrated a moderate degree of loneliness (M=38.25, SD=15.56).

Conclusions: Early detection of social isolation is essential to improve quality of life (Ran et al., 2024) and prevent illness in older adults (Jansson et al., 2021). While loneliness and the need to move impacted these older adults, their involvement in the choice and receiving a tailored experience improved their transition (Sun et al., 2021).

Background: Children with cancer face significant challenges impacting their quality of life (QoL). Two common interventions amongst this population are play-based interventions and exercise-based interventions. Although they are independently studied, there are currently limited studies on the comparison of these interventions related to QoL. This modified systematic review aimed to answer the question: for children with cancer, how do play-based interventions compare to exercise-based therapy interventions in improving quality of life?

Methods: Four independent researchers conducted a comprehensive search across major databases (CINAHL, EBSCO, MEDLINE, and PUBMED) to identify studies published within the last ten years. Inclusion criteria of the study were articles involving children diagnosed with cancer who received either a play-based intervention or an exercise-based therapy and the study was conducted in the last 10 years. Studies were excluded if they were systematic reviews, meta-analyses, dissertations, or presentations or if interventions were unrelated to QoL or focused solely on cancer survivors. Data extraction focused on intervention type, participant demographics, and QoL outcomes.

Results: The review included 20 studies comparing play-based and exercise-based interventions. Preliminary findings suggest that play-based interventions demonstrated stronger improvements in emotional well-being and social engagement, while exercise-based therapies yielded better physical functioning outcomes and reduced fatigue. Both intervention types showed positive effects on overall QoL, albeit through distinct mechanisms.

Conclusion: Combining these approaches may provide a comprehensive strategy for enhancing QoL in pediatric cancer patients. Further research is recommended to explore optimal intervention combinations and long-term effects.

Children with autism spectrum disorder often receive ABA therapy to improve occupational performance limited by sensory processing deficits. However, sensory integration interventions have also been proven effective within this population. This modified systematic review examined “How does sensory integration therapy compare to behavioral interventions (e.g., ABA) in children diagnosed with ASD to improve occupational performance?” Our initial comprehensive search consisted of an extensive database search for relevant studies using the following search terms: children, autism spectrum disorder or ASD, ABA, sensory integration, and occupational performance. Searches yielded a broad range of articles, which were then further examined in meeting the inclusion criteria of articles consisting of participants of ages between preschool (3/4yrs) to 18yrs and diagnosed with ASD, that are peer-reviewed, published in English, published between February 1, 2015- now, and that evaluate/utilize sensory integration based or behavioral-based interventions to analyze occupational performance/occupation-based related outcomes. Excluded articles consisted of systematic reviews, meta-analyses, and dissertations, and studies that were not published in English, included participants older than adults and were not diagnosed with ASD, published before February 1, 2015, and that did not evaluate/utilize sensory integration based or behavioral-based interventions to analyze occupational performance or occupation-based related outcomes. Overall, 15 articles were selected and included in the review, demonstrating moderate to low levels of evidence. The findings revealed potentially positive outcomes of ABA therapy/sensory integration in improving occupational performance and displayed receptiveness in incorporating more sensory-driven activities within the practice. Additional research is needed to address the benefits of ABA therapy and sensory integration in improving occupational performance in children with Autism.

Background: Multiple Sclerosis (MS) is a chronic disease that breaks down the protecting covering of nerves, known as myelin (Mayo Clinic Staff, 2024). Those who are diagnosed with MS are typically between the ages of 20-40 years old, and women are more likely than men to have MS (Mayo Clinic Staff, 2024). At the time of the publication of these articles, there is no cure for MS, but evidence has shown that exercise can help manage its symptoms. The focus of this modified systematic review aimed to assess whether a structured exercise program would enhance overall function, beyond just physical function, in individuals with MS when compared to an intervention.

Methods: The inclusion criteria for the study encompassed all individuals with MS, regardless of the type, and exercise interventions. Studies must have been conducted within the last 10 years and be peer-reviewed. The exclusion criteria included systematic reviews, meta-analyses, case studies, conference proposals, conference presentations, and articles not published in English. The sources for the study were databases such as EBSCO, PubMed, and MEDLINE.

Results: In the 15 articles that were included in the review, exercise programs showed positive outcomes for managing strength, fatigue, motor and cognitive function.

Conclusion: The studies reviewed suggest that exercise could be beneficial for individuals diagnosed with Multiple Sclerosis. However, additional research is needed to fully comprehend the long-term effects of exercise programs on overall function and disease management in those with MS.

This paper tackles the Incoherent perspectives on video games within church communities, where polarized views among churchgoers – complete rejection or unrestricted acceptance – prevail. I promote a balanced approach, merging narrative and systematic theology to cultivate a discerning lens. Rejecting sweeping generalizations, the study advocates for a contextual evaluation of each game, emphasizing content, thematic depth, and age suitability. By integrating these theological frameworks, the paper posits that video games can serve as avenues for moral development and even divine encounters, echoing the Jesuit principle of “finding God in all things.” I draw upon Aristotelian virtue ethics and the exemplary life of Saint Carlo Acutis; my research underscores the importance of moderation and informed decision-making. Through case studies of titles I have personally engaged with, such as Red Dead Redemption 2 and the Persona series, I try to illustrate how engaging with game narratives can foster ethical reflection and spiritual growth. Ultimately, my research proposes a shift from fear-driven prohibitions to intentional, faith-guided interaction, transforming the digital realm into a space for meaningful exploration and personal enrichment.

Keywords:

– Narrative Theology

– Systematic Theology

– Virtue Formation

– Discernment

– Metanarrative

– Ludology

– Narratology

– Moderation

– Contextual Evaluation

– Incoherent Metanarrative

The Advanced Laser Interferometer Gravitational Wave Observatory (aLIGO) made its first detection of gravitational waves in 2015. Since then, the rate of event detection has only increased, with a detection being made every 2-3 days during the current observing run, O4. This rapid influx of data has the potential to create bottle-necks in data analysis efforts, and can delay the scientific progress which requires it.

Traditional gravitational wave data analysis techniques, such as matched filtering, have thus far proven to be moderately effective. Requiring extremely large template banks and preprocessing of the data, this technique is computationally intensive and given the amount of effort this analysis takes, the results leave much to be desired.

With recent advances in machine learning, many of the bottle-necks afflicting “big data” have been effectively resolved. In gravitational physics, machine learning neural networks have already demonstrated the ability to flag signal buried deep in noise, denoise time-series data and extract the signal, and make accurate parameter estimates. However, the majority of these neural networks still rely on the preprocessing or transformation of data before the analyze it.

This thesis covers the development, performance, and analysis of a neural network that, given a time-series of raw-noisy, unprocessed signal from a laser interferometer, can accurately predict the chirp mass of the binary black hole (BBH) system that produce the signal. This advancement has the capability of significantly increasing the computational efficiency of gravitational wave data analysis and yielding more accurate parameter estimates than current techniques.

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.

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.

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.

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 Hubble Space Telescope Heritage 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.

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 compare them to observed UIE lines to try to determine where the UIEs come from. Our goal is to observe how ionization and nitrogen or 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 nitrogen and oxygen 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, C-C stretching and both in-plane and out-of-plane C-H bending modes. Oxygen and nitrogen substitutions tend to increase the intensity of of the C-C stretching and C-H in-plane bending modes. We also 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 possible candidates for PAHs that can reproduced the major UIE peaks in planetary nebulae spectra.

Probing the gluon’s contribution to proton spin is an important goal of the STAR experiment at the Relativistic Heavy Ion Collider (RHIC) located at Brookhaven National Laboratory. We aim to refine our knowledge of the gluon spin contribution to aid in solving the proton spin puzzle as the contributions of the proton’s constituent parts to its spin remain uncertain. In this analysis, we utilize 52 pb-1 of longitudinally polarized proton-proton (p+p) collision data taken by the STAR experiment at ?s = 200 GeV. Our measurement uses the Endcap Electromagnetic Calorimeter (EEMC), which is stationed at a pseudorapidity range of 1.1 < ? < 2.0 and can detect photons from the decays of neutral pions (?0s). A new data quality assurance (QA) method has been implemented, which increases the number of entries in QA histograms such as the reconstructed ?0 mass, signal fraction, and number of towers hit in the EEMC. The original QA method suffered from accidental numerical losses of ?0 candidates due to ROOT command line methods, while the new method recovers them using full STAR libraries. The revised data will be used to calculate the spin-dependent asymmetry of ?0 production (ALL), which is sensitive to the gluon’s contribution to the proton’s spin. The status and impact of the new quality assurance method will be presented, along with prospects for the ALL measurement.

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.

The Solenoidal Tracker at RHIC (STAR) experiment, located at Brookhaven National Laboratory, uses collisions of longitudinally polarized proton beams produced in the Relativistic Heavy Ion Collider (RHIC) to study the gluon contribution to the proton spin. While the proton spin is known to be 1/2 ?, the contribution from gluon spin is not precisely known. Our analysis uses 300 pb-1 of ?s = 510 GeV collisions to determine the asymmetry of spin-dependent production of neutral pions (?0) and eta (?) mesons. This asymmetry is sensitive to the gluon contribution to the spin of the proton. Collisions at ?s = 510 GeV have enhanced sensitivity to low x gluons, where x is the fraction of the proton’s momentum carried by the gluon, compared to other STAR analyses. ?0s and ?s are produced within the STAR detector via collisions of longitudinally polarized protons provided by RHIC. The ?0s and ?s rapidly decay into two photons, which are detected by the Endcap Electromagnetic Calorimeter stationed at a pseudorapidity range of 1.1 < ? < 2.0. An invariant mass spectrum is constructed from the photon pairs. From this, the total number of ?0s and ?s can be determined. Various quality assurance checks are performed to ensure a thorough understanding of the performance of the STAR detector system and to confirm the robustness of data collection at STAR. The current status of the asymmetry analysis, focusing on the 2013 dataset, will be presented.

The neutron Electric Dipole Moment (nEDM) experiment at Los Alamos National Laboratory is designed to search for the nEDM at the level of 10^-27 e*cm. The experiment will make use of the Ramsey method of separate oscillatory fields at room temperature. To minimize statistical and systematic uncertainties, the experiment is enclosed in a five layer Mu-metal magnetically shielded room (MSR). The performance of the MSR can be characterized by the shielding factor, the ratio of the magnetic field measured in the absence of the MSR to the magnetic field measured inside the MSR. A set of solenoidal coils was used to produce a magnetic field and construct a new measurement of the shielding factor to compare with previous measurements of different methods. Results of the new shielding factor measurement will be presented.

Since enduring colonization by the Spanish and Portuguese and neocolonialism under United States capitalism-hungry policies, Latin American countries have been objectified for their material resources for centuries. The 21st century has seen a shift in investment and attention to another global superpower as China has stepped in to implement numerous foreign direct investment (FDI) infrastructure projects. As the US scrambles to reconcile China’s investment trends, Latin American countries have emerged as a point of political and economic competition between the eagle and the dragon. This matter of FDI relationship gives rise to the question: does US FDI reactively follow Chinese FDI in Latin American countries? This article compiles data from the US Bureau of Economic Analysis, the Inter-American Dialogue and Boston University Global Development Policy Center, and other sources in an analysis of Chinese and US government FDI in Latin America as a region and in individual countries from 2007 to 2023. Through statistical analysis of US direct investment positions abroad and loans from China’s development finance institutions, I test the data for correlation between US changes in FDI levels in relation to previous Chinese FDI trends. The correlation demonstrated that the US increased FDI spending in countries where China had invested the most two years prior. With these findings, Latin American countries could exploit FDI patterns to negotiate improved FDI deals and gain traction on the world stage.

This exploratory study investigates bias-motivated incidents in and around the City of Valparaiso, Indiana, over the past 30 years. The study aims to examine patterns and trends in such incidents, defined broadly as “bias-motivated incidents” rather than the more narrowly defined “hate crimes.” While hate crimes, according to the FBI, involve criminal offenses motivated by bias against race, religion, disability, sexual orientation, or ethnicity/national origin, bias-motivated incidents encompass any behavior expressing hostility toward individuals or property based on these characteristics, regardless of whether they rise to the level of criminal activity. The research analyzes reports of these incidents as documented in regional newspaper coverage, focusing on the frequency, location, type, and severity of incidents. The study does not include other sources and is therefore exploratory in nature, suggesting that further research using a broader range of data sources is necessary for a more comprehensive understanding. This investigation seeks to highlight patterns in bias-motivated incidents and encourage future studies to develop a more complete database of such occurrences.

Buddhism has long been linked to peace, mindfulness, and self-awareness, yet its philosophies have increasingly been used in military settings. This paper explores the weaponization of Buddhist practices in psychotherapy, particularly in the military, where militarized forms of mindfulness-based stress reduction therapy (MBSR) are used to strengthen soldiers’ mental resilience and combat readiness. While MBSR has been recognized for its therapeutic benefits, its use in the military raises ethical concerns about whether religious practices are being repurposed in secular settings that go against their original purpose. Through a review of existing research, this paper examines how Buddhist principles—traditionally meant to thrive through the acceptance of suffering—are instead used to help soldiers handle stress, stay focused, and perform better under pressure during active duty. This paper outlines the basic principles of Buddhism, the differences between psychotherapy mindfulness and Buddhist mindfulness, and the ethical concerns of using a secularized form of mindfulness in settings like the military. The discussion draws from Buddhist ethics, military psychology, and modern critiques of mindfulness. Ultimately, this review aims to reveal the reconfiguration of spiritual traditions in psychotherapy and military environments and questions whether these adaptations stay true to Buddhism’s core values or simply become tools for improving military strategy. Future use of secular mindfulness, especially in military settings, should be approached with greater cultural awareness and ethical consideration, ensuring that these practices are not stripped of their historical and moral contexts but are instead applied in ways that respect their origins and support mental wellbeing.

Research shows that romantic relationships significantly impact health, with stable relationships enhancing well-being and high-stress relationships increasing risk for depression, anxiety, and substance use disorders. Relationship discord is common in couples where one or both partners exhibit ADHD symptoms, but little research examines the factors mediating ADHD and low relationship satisfaction. Given that attribution patterns affect relationship satisfaction, we aim to explore how ADHD-related attribution patterns mediate the link between ADHD symptoms and relationship satisfaction in affected romantic partners. We plan to use a quantitative approach grounded in attribution psychology to survey participants on relationship distress, attributional locus of control, and attributional patterns. Currently, we have obtained IRB approval, and plan to collect online data via Qualtrics and Prolific beginning in the summer. We hypothesize that attribution patterns and locus of control mediate the link between ADHD symptom differences and relationship satisfaction. Specifically, couples attributing negative behaviors to stable, global factors (e.g., “they always forget because they are lazy”) will report lower satisfaction than those who see behaviors as situational (e.g. “they forgot because they had a long day”). We expect more ADHD-related differences to increase maladaptive attributional patterns, heightening relationship discord. The implications of this study include identification of potential strategies for clinicians serving couples where ADHD impacts relationship dynamics and addressing the gap in the literature surrounding neurodivergent relationships.

For this proposal we plan to evaluate recent changes to the Indiana juvenile competency statute. Until December of 2022, Indiana had no juvenile competency statute which does not align with best practice. This poster will review the statute and compare it to Larson & Grisso (2011) statutory guidelines manual which is based on research evidence in psychology. Replicating the Panza (2020) methods, we will compare Indiana to other states’ compliance with statutory adherence to Larsons & Grisso (2011) recommendations.

Prosocial behavior is essential for fostering empathy, cooperation, and social harmony. Promoting kindness, sharing, and helping others enhances relationships and community well-being. Engaging with prosocial concepts helps children develop emotional intelligence, moral reasoning, and responsibility. Books are a common way to teach these lessons, entertaining while conveying important moral values (Romaniuc & Vechiu, 2023). Encouraging prosocial behavior early on leads to more compassionate adults and healthier societies.

While books are vital to children’s learning, the language within them is often underexplored. Books expose children to various concepts, and they apply the knowledge they gain to real-world situations (Strouse et al., 2018). Our study focuses on the number of prosocial words in picture books.

We analyzed the top 50 picture books from four Indiana counties (N=200) based on library circulation data. Two counties are urban, and two are rural. After transcribing the books, we used LIWC to identify prosocial terms.

Given that children in urban areas likely have more opportunities to socialize, we predict that books from urban counties will contain more prosocial terms. We test this hypothesis using paired samples t-tests, along with frequency and descriptive statistics, to examine the prevalence of prosocial references in the picture books.

Videos are an undeniably useful and accessible way to share information. This can be especially important for parents and caregivers looking for information related to their child’s development, or for organizations wanting to share this information with the general public. There is little information on the types of videos people enjoy watching, or that they can retain the most information from. To look into this, we ran a focus group consisting of 2 sessions with 5 students each. They were shown previously made informational videos about talking, reading, and singing to children through the Talking is Teaching campaign in Porter County, IN. The findings indicated that participants were especially interested in topics such as sorting and categorization, multilingualism, and talking and singing in the car. Ratings from the videos were collected in order to improve videos made in the future for the Talking is Teaching campaign.

Purpose: Children connect images in books to real-life objects when the pictures are highly iconic, or realistic looking, known as iconicity (Ganea et al., 2008; Simcock & DeLoache, 2006). However, it is unknown to what extent children’s books include highly realistic images. While iconicity benefits learning, do parents select books that feature images with high iconicity? This study examines the level of iconicity in the most frequently checked-out books from libraries in six Indiana counties.

Procedure: Based on circulation data from 2023, the top 100 picture books from each library were selected (N=600). We are using an existing coding scheme for the level of detail developed by Wagner (2017). Books are classified as simple lines, basic drawings, detailed drawings, photographs, or mixed.

Results: The majority of books contain basic drawings. Of the 405 total books coded; 217 are basic drawings, 150 are detailed drawings, 10 are mixed styles, 16 are photographs, and 12 are simple line drawings.

Conclusions: The results of this study recognize the importance of iconicity in children’s books. The study aims to determine whether parents buy books with detailed images that are more supportive of learning. Very few books contained highly iconic images – photographs. We also see that detailed images occurred less than basic drawings. Parents, caregivers, educators, and book publishers should know about book image features that foster children’s learning. These findings could influence parents’ choices, early childhood education, and library programming.

Previous research indicates that music produces changes in brainwave patterns. However, the specific pattern and location of these changes are unclear. This study examines alterations in brainwave patterns within the alpha spectrum between individuals completing a memory task in a music condition or a no music condition. The Barcelona Music Reward Questionnaire was administered to 27 participants, from which 18 participants with scores indicative of a pleasurable music listening experience were selected. The 18 participants were assigned to one of the two conditions, music or no music, with the no music condition functioning as the control. All participants were connected to a multichannel EEG machine for the duration of memory task administration. Fast Fourier spectral analysis was used to identify alpha patterns. Increases in alpha power were found in the music condition when compared with the no music condition, but the pattern of changes varied according to the specific location in the brain being measured. One possible explanation for this occurrence is that the participants in the music condition found the music relaxing, accounting for the increase in alpha power within the music condition and absent from the no music condition.

The American Academy of Pediatrics (2021) recommends daily reading for children from birth. While the importance of books is clear, little is known about the language used in them. Books expose children to concepts that shape their real-world understanding (Strouse et al., 2018). In languages like English, many terms are male-biased, which can reinforce gender stereotypes and inequalities (Vainapel et al., 2015). We predict that male representation in children’s books will outnumber female representation.

This study assesses the top 50 picture books from four Indiana counties (N=200), based on circulation data. We used LIWC to examine gender references in these books. Preliminary results from two counties indicate a male bias, with males represented more than females (M=2.91, SD=3.72 vs. M=1.54, SD=2.76). We will conduct a mixed ANOVA to test if this pattern holds, using county as a between-group factor and gender as a within-group factor.

Gender representation influences life outcomes, with women holding only 25% of US Senate seats, 10.6% of Fortune 500 CEO positions, and 32.8% of university presidencies (Schaeffer, 2023). This study helps understand current gender disparities and guide efforts for more equitable representation. The findings will be useful for parents, teachers, and librarians seeking to promote gender equality in children’s literature.

Language development, occurring prenatally and throughout childhood, is a stage that significantly impacts one’s abilities to produce and understand language throughout their lifetime. The goal of this study is to find an accessible way to equip caregivers with video-training to help them set their child up for success during language development. Parent’s understanding of childhood development is related to their child’s efficiency in moving through stages, specifically in relation to the acquisition of language (Booth, 2018). Existing literature has shown the power of video-training, such that parents who received it could implement new activities with their children, increasing the development of language-related skills (Blom-Hoffman, 2008).Thus, a video-training program containing facts and activities related to language development is a resource caregivers can use to better understand their child’s needs during this stage. Research about video formating with college students has found that participants learn best from combined audio and visual aspects that included social cues from footage of the instructor speaking (Brünken, 2002; Kizilcec, 2015). These features can be present in both live-action and animated formats; therefore this study focuses on finding out if individuals learn better from a live-action or an animated format. We compare learning outcomes from live-action videos compared to a closely matched animation, seeing if one is more effective in relaying memorable information. Findings from this research will give insight to what types of videos are the most effective to equip parents with the knowledge they need to support their child during language development.

Anthropomorphism, the attribution of human characteristics to animals or objects, is often present in children’s literature. Research has shown personification of non-human entities affects the way children experience the world and their thinking about non-human entities (Ganea et al., 2014). The rates of anthropomorphism that children are exposed to is unknown. Therefore, in our study, we analyzed the prevalence rates of anthropomorphism in children’s literature from the 100 most checked out books from two Indiana counties: Porter and Stark (a rural and an urban county), based on circulation data from 2023. To analyze the prevalence of anthropomorphism in children’s books, we developed a coding scheme that characterizes the main character’s species, environment, and features. We expect anthropomorphism to be very prevalent in children’s books. We created a composite score to indicate the amount of variation in anthropomorphism present across the books, ranging from 0 to 12, with higher scores indicating more anthropomorphic features. Once all 200 books are coded, we will run a t-test to determine if there is a difference in the composite score between counties. We will also run a chi square test to understand if there are similar rates of the types of main characters among the counties. This study is foundational in understanding the base rate of anthropomorphism in children’s literature, which will allow researchers to explore the impacts that this has on children’s view of the world.

The criminalization of homelessness is a phenomenon that took root in the United States during the late 20th century, making people experiencing homelessness more likely to face legal issues. Because people experiencing homelessness are more likely to experience a myriad of mental health problems, they sit at the intersection of the criminalization of poverty and of mental illness. As such, when they make contact with the criminal justice system, they may have more involvement with competency to stand trial (CST) cases– an evaluation used to determine if a defendant is able to defend themselves and to comprehend the charges they face. This is one of the factors hypothesized to contribute toward the national competency crisis– where there are too few evaluators for the number of CST cases. This study aims to investigate the relationship between homelessness, CST referrals, and CST outcomes. Using the Odyssey Public System, this study had access to a population of over 4000 CST evaluations in one Midwestern state and sampled 139 of these evaluations for the current research question. Using mycase.in.gov, student research assistants coded additional data about the case (including specific charges, whether the defendant was homeless, and the outcome of CST in those cases). This presentation will review the background of this growing problem, identify how many CST evaluations involve homeless individuals, and examine the outcomes of those cases. The study anticipates that people experiencing homelessness will both be more likely to experience CST referrals and incompetent evaluations.

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 qualitative and quantitative 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 chronic and preventable disease in these communities. Some findings of interest from this sample of participants were that the main reason for immigrating to Costa Rica as 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.

In response to each wave of the feminist movement, there have been waves of antifeminist backlash, with the contemporary waves largely taking place online. While prior research has examined specific aspects of the most recent wave of this countermovement, none have focused on how we can characterize the antifeminist movement as a whole. To contribute to a more complete understanding, this study sought to determine how the current wave of the antifeminist movement presents itself as a whole online. Using a content analysis of all Tweets posted in a three-month time period under top antifeminist hashtags, this research characterizes the antifeminist movement thematically. I created five categories based upon thematic commonalities among the Tweets, coding each Tweet as belonging to up to three of the categories. The data reveal that a disproportionate number of Tweets contained explicitly misogynistic language, critiqued equality gains for women, and, surprisingly, were majority informational in nature, with authors drawing on academic research and news articles to support the ideas they were promoting. This has important directions for future research, including implications for what the goals of the antifeminist movement are and how the movement chooses to mobilize itself.

There is limited research exploring how women evaluate the costs and benefits associated with different expressions of femininity. However, sorority life offers a clear example of a space where women actively contemplate their roles and the type of gender performance they wish to embody. Drawing on 10 interviews with women in sororities at a small, private, religious institution, I investigated how they negotiate their femininities. Replicating Ispa-Landa and Oliver’s (2020) study, I hypothesized that sororities maintain an agreed-upon tier system, where top-tier sororities are expected to adhere to social constraints and expectations to be deemed more desirable. In contrast, middle- and bottom-tier sororities have greater freedom but are perceived as less desirable for not conforming to these top-tier standards. To build on their research, I explored whether faith plays a role in women’s decision-making processes. While the interviews revealed evidence of sorority rankings and the negotiation of different ideal versions

Though sociologists have extensively documented gender discrepancies in physical activity participation and attitudes among adults, differences by gender in gym-related activity among college students remains understudied. This study explores differences in behaviors, motivations, and barriers to gym attendance and participation among college students using quantitative survey analysis. Based on previous literature, this study expected to find that women have more negative experiences surrounding their participation than men. Surprisingly, and in contrast to previous literature, I find few differences in behaviors between men and women. Some difference nevertheless persist, with men reporting higher levels of motivation to attend the gym and women reporting more barriers to attendance. These finding suggest that women still experience disadvantages related to their physical activity, though this study does not find as many disadvantages as previous studies.

This research investigates whether there is a connection between gender and perceptions of military professionalism. The military is a highly-masculinized workplace which women have not occupied for long; as such, this research aims to discover whether military members perceive women in the military as professional. To do so, the researcher used a survey with both quantitative and qualitative questions to discover what a sample of Army National Guard soldiers’ self-perceptions reveal about their views of women in the military. The researcher also covertly observed two weeks of Army National Guard training to learn whether the sample’s behavior toward women in the military aligned with their self-perceptions. Quantitative survey results suggested that soldiers’ self-perceptions do not demonstrate gendered views of professionalism, but qualitative results from the survey and participant observation demonstrated remaining stereotypes and structural issues which undermine views of women’s military professionalism. The researcher concludes that while conscious perceptions of women’s professionalism in the military may be improving, symptoms of the military’s highly-masculine culture seem to subconsciously affect these perceptions.