2022 Summer Undergraduate Research Grant Recipients: Participants in the Fall Edition of CURCA

Carly Kocurek’s article “Women’s History For Games: A Manifesto and a Way Forward” aligns with the topic of my research project as it discusses the hidden and overlooked stories of women in the industry and how illuminating them can be ground breaking. The author calls for further research to be done on this topic and my research project would do just that: “The work of women’s history and other area studies is vital, but we have an opportunity right now to integrate that type of valuable work into the primary work of the field. And it is essential that we do so, not only because it will enable us to produce the most valuable historical work possible, but because at a moment when toxic gaming culture is making headlines, we can intervene by enabling an accurate understanding of the complexities of gaming’s past.” (Kocurek, 15)

According to the International Game Developers Association (IGDA), 71% of game developers globally are men while just 24% are women and 3% are non-binary. And when it comes to race and ethnicity, just 2% of developers are Black while 69% identify as white. A game developer survey in 2021 found that the share of female game developers is up from 21 percent in 2017. Approximately eight percent of game developers did not identify as either men or women. These statistics refer to the current state of the industry, but these inequalities were even more severe when Weisbecker first started working in games.

The specific aim of this project is to record an oral history from Joyce Weisbecker, the first ever female game developer, and to conduct detailed research on the games she created and worked on. The expected outcomes of this project include the audio recording of that oral history, a transcription of it, and an essay about Weisbecker’s contributions and her impact on the history of games and computing. Lastly, and perhaps most importantly, this extensive research will serve as the beginning of Joyce’s biography, a project that I hope to complete with Dr. Jim Brown’s help and guidance.

The goal of the present study is to determine how well participants can discriminate between real and AI produced faces. We aim to collect data using a database of sample participants from different ages, ethnicities, and backgrounds. We will also test a second and third hypothesis: that people are better able to discriminate real from artificial faces if those faces are from a similar ethnic background and gender as the participant; and a third the extent to which perception of attractiveness in the faces influences participants’ ability to discriminate real from artificial faces.

Participants will be recruited from the Prolific subject pool – a paid subject pool in which people agree to participate in research studies for a fee. Participants will see a total of 48 faces split evenly between real and artificial faces. Within each set 25 will be male, 25 will be female, and they will vary in ethnicity and age. On each trial, participants will see a face. They will have to make a judgment as to whether the face is real, how trustworthy they find the face, how attractive they find the face and how usual does the face look. We will be measuring accuracy and reaction time on each trial. Once they have completed all trials, they will be asked demographic questions such as age, gender, and race. Our major independent variables will be A: Whether the face is real or artificial, B: Gender of face, C: Age of face, D: Gender of Participant, E: Age of participant, F: Ethnicity of participant, with the independent variable being A: whether or not the participants made a correct estimate of the face, B: Strength of confidence in that estimate, C: Reaction time in making the assessment. The data will be analyzed using analysis of variance and regression with the statistics program JAMOVI.

Ferroelectric materials are of great interest due to their switchable spontaneous polarization when below the critical temperature, called the Curie Temperature. Ferroelectrics have the unique ability to switch the orientation of the polarization by external stimulus, making them suitable for interesting applications such as memory storage devices and transducers. There are a variety of classes of ferroelectrics classified by the mechanism that gives rise to spontaneous polarization. The focus of this proposal will be on organic charge transfer ferroelectric co-crystals. These crystals consist of electron donor (D) and acceptor (A) molecules which arrange in a mixed stack, ADADA or DADAD. Below the Curie Temperature, the acceptor and donor do not share charge and are said to be in a neutral phase, but above the Curie Temperature, the donor gives up electrons to the neighboring acceptor.

This creates a separation of charge and hence a net polarization. By application of an external electric field, the donor can be coerced to give up its electrons to the opposite neighbor, thereby changing the direction of the polarization. The fact that the switchable polarization is mediated by electrons, implies the potential to control the direction of polarization with visible light through photoinduced phase transitions (cite). These transitions are typically unstable due to only local areas of the crystal being affected by the incident light, thereby allowing the surrounding unaffected crystal to restore the polarization of the irradiated area to its original orientation. In this work, we propose a potential method to circumvent the instability of the photoinduced transition. By reducing the size of isolated crystal domains to the micron and nano scales, entire crystal domains could possibly switch polarization without the coercive background of the unirradiated area. Two methods of producing nano and micron-sized crystalline domains are being proposed: (1) sublimating the co-crystals by heat and collecting the condensate on a substrate placed above the heater and (2) by matrix-assisted pulsed laser evaporation (MAPLE).

This paper focuses on the display and presentation of antiquities in Istanbul, Trabzon, and Philadelphia. I will explain the historical context around both the Penn Museum and Istanbul Archeology Museum, which will help aid in understanding how they came to be and what they represent in today’s world. There will also be a deep dive into who is credited for the museum’s creations and fundings and who is left out from that history. It is important to understand why certain groups and people were left out of the museum’s history, and I will go over what the intentions of each museum were in their exclusions whether it be personal or political. This paper will also compare and contrast how the Penn Museum and Istanbul Archeology Museum present their antiquities, and through this we will see how government and local social attitudes affect their presentations and displays. I will then shift focus onto Turkish national identity origins and purpose. Understanding Turkish national identity is crucial in understanding why antiquities and historical monuments are displayed as they are. With the understanding of Turkish national identity, I will then give examples of how that identity is shown through my visits to historical landmarks. This paper will be concluded with my final thoughts on the presentations of antiquities, my experience as a visitor in all these museums and landmarks, and my own expectations versus the reality while conducting research.

First-generation college students come to college where they strive to forge new relationships with peers, professors, and other staff members while tackling many challenges assimilating to the college atmosphere. In entering a new social space, with less knowledge of anything about college and facing persistent negative stereotypes and underrepresentation they may wonder whether they will fit in. The concept of belonging is important and has consequences for these students such as their academic success and retention. Therefore, to protect this sense of belonging, we propose that nostalgia is a psychological factor that promotes positive beliefs about belonging and succeeding in college among this particular group of students. In the first study, we tested whether nostalgic induction would elicit a greater sense of college belonging than the control induction among first-generation students; indeed, nostalgic reflection bolstered feelings of college belonging. Specifically, first-generation students in the nostalgia condition reported higher levels of college belonging than students in the control condition. The results of this study support the notion that nostalgia’s capacity to promote belonging can be applied to first-generation students to make them feel more at home. In the second study, we directly replicated the effect of nostalgia on college belonging and extended the findings of Study 1 by testing the downstream benefits of nostalgia’s capacity to encourage college belonging among first-generation students for academic optimism. The findings of this study demonstrated that first-generation students, when nostalgic or think about a nostalgic experience (compared to an ordinary experience), feel more upbeat about the future. Thus, nostalgic experience is highly social and fosters a greater sense of belonging and academic optimism among first-generation college students.

Our aim was to create a machine learning model that would identify individual characteristics of on-road vehicles with higher precision than currently available models. An application for this model would be to improve accessibility for the blind to vehicles, and vehicle-based services like Uber or Lyft.

To begin with, we needed a comprehensive dataset containing commonly seen on-road vehicles but the kind of dataset we were looking for did not exist. CARLA simulator was utilized to generate the dataset needed. CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. 62 unique keypoints were created for each of the 16 selected vehicle models. We also included several vehicles that had only 2 doors, hence had 8 fewer keypoints. We then used various sensors to collect data under different weather and time conditions on 5 different prebuilt maps.

Before we choose a model to train and test, we needed to pick a test/train split. We chose 3 maps and 8 weather and time conditions for our test dataset. The remaining 2 maps and 5 weather and time conditions for reserved for the test dataset. Instead of building a model from ground up, we decided to use a pre-existing state-of-the-art model for keypoint detection called ViTPose. ViTPose is a simple vision transformer that uses plain and non-hierarchical vision transformers as backbones to extract features for a given person. While ViTPose was designed for human pose estimation both in 2D and 3D space, we believe it should work well enough for static objects like vehicles. The largest annotations do not seem to use more than 20 keypoints for an object. This does pose a challenge to accommodate 62 keypoints using this model. The model uses MS COCO keypoint format for its input and output. MS COCO is used for large scale keypoint detection which suits our purpose as we have a far greater number of keypoints than the model was tested under. We converted our gathered dataset into MS COCO format.

So far, we have managed to successfully train our dataset with the model and the results show that the model is training on our dataset well. We have also created a vehicle skeleton by joining keypoints that belong to a specific vehicle part such as handles, doors, and license plates. We are currently working on testing our trained model on the simulation dataset. We are working on tweaking the model’s performance and experimenting with different precision and recall values. Once we have satisfactory test results, we will move on to testing the model on real-world images.

Forests play fundamental roles in ecosystem processes, including carbon uptake, climate regulation, and nutrient cycling. Despite its importance, they are rapidly been exposed to human driven disturbances, which are affecting their biodiversity, structure, and function. Forests are interconnected to aquatic ecosystems through the exchange of living organisms (e.g., insects) and dead material (litter), which serves as food resources to aquatic insects. Litter decomposition in aquatic systems is a fundamental ecosystem process that support aquatic food webs and helps nutrient cycling. Despite the importance of these terrestrial and aquatic links, we know little about the influences of forest management on the functioning of these linked aquatic ecosystems. This experimental study focuses on the effects of fire, used as a management strategy, on terrestrially linked aquatic ecosystems, particularly decomposition rates of organic matter. To test the effects of fire on decomposition rates in aquatic ecosystems, we are using artificial aquatic microcosms to experimentally replicate natural aquatic ecosystems. To evaluate how decomposition rates respond to fire, we are using decomposition bags that include three types of bags (fine mesh, coarse mesh, and no mesh) containing calico cotton (a standardized substrate) located within each aquatic microcosm. These bags allow us to test the effects of microbes and macroinvertebrates in the decomposition process. This experiment is also part of a global study in which 86 research teams from 32 different countries collaborate and replicate a type of microcosm experiment in both managed and unmanaged forests. The overall aim of this replicated experiment is to test the impacts of human-driven effects on forest ecosystems at a global scale.

Structural variants (SVs), large genomic alterations, are often responsible for tumor development. Most studies focus on single-nucleotide mutations and leave SVs aside due to the difficulties in their analysis. We have utilized the result of a recent effort to sequence a cohort of patients with multiple myeloma. We used two main computational tools to locate and visualize SVs after comparing two different genomes (normal and tumor). The first one was the Genome Rearrangement OmniMapper (GROM), a variant caller with superior speed, sensitivity, and precision used to identify the variants [1]. The second tool was the Variant Navigator (VN) to visually examine the reads and compare SVs in tumor samples with corresponding normal samples; this tool is more convenient than other popular ones as it collects multiple SVs from a single sample in a data table and allows us to efficiently go through the data. Visualization of the variants enables us to validate the type and location of mutation, and genes overlapping or near the variant. We found many common SVs present in tumor (but not normal) samples affecting a range of genes that are related to various functions, for example, increased tumor incidence, tumor growth, innate immunity and inflammation, etc. Finding these genes helps us identify the proteins involved in tumorigenesis and this analysis may further allow us to find potential drug targets.

Ongoing human activities are causing major global environmental changes (e.g., warming, nutrient enrichment, and shifts in precipitation levels), which are negatively affecting the structure and functioning of Earth’s ecosystems. These environmental changes have been shown to intensify or weaken plant-pathogen interactions and the extent of diseases they cause. To date, however, a comprehensive quantitative synthesis of the effects of major global environmental changes on plant-pathogen interactions is still lacking. Here, we are evaluating the effects of nutrient enrichment, warming, drought, and major global environmental changes on the susceptibility and severity of diseases caused by plant pathogens. To date, we have compiled data of 183 cases of study from 18 papers and performed a meta-analysis of the effects of nutrient enrichment, warming, and drought, on wild-plant diseases caused by a variety of pathogens including bacteria, fungi, and viruses. Insights from this meta-analysis may help better predict how anthropogenic changes may be driving the prevalence of these plant-pathogen interactions. Understanding how global change drivers affect plant-pathogen interactions is crucial to better predict the outcome of infectious plant diseases and to improve our ability to mitigate their effects.

The relationship between gun availability and gun-related death has been extensively studied and debated, with researchers employing various proxy measures of legal and illegal gun availability, as well as exploring the effect of various state-wide policies on gun violence. The line of inquiry is as important as ever, following surging rates of gun violence in the United States in 2020 and record setting gun sales. This is especially notable in Philadelphia, where I live. In this study, I will be using what John Lott (2021) describes as “the only really hard data” we have pertaining to gun ownership, the number of concealed carry permit holders. I will conduct a county-level analysis to assess the bidirectional relationship between concealed handgun permit holders and gun-related deaths since 2006 in the United States. This study has significant implications for policies pertaining to the issuance of concealed handgun licenses and will help to ascertain a) whether increasing gun ownership has driven increases in different types of homicide equally, specifically whether an increase risk to intimate partners exists and b) whether increased gun ownership plus the stress of the pandemic in 2020 has widened the racial gap in gun-death burden.

Markov Chain Monte Carlo (MCMC) is a sophisticated sampling method. It was originally invented for Bayesian statistics, but since then it has been widely used for scientific computations. In fact, it is impossible to do justice to the depth, breadth, and quality of work of MCMC methods in statistics since 1990. These methods have appeared in almost every area of natural and social science, and have also proved to be intrinsically interesting to mathematicians, especially probabilists [1].

The goal of MCMC is to produce a sufficient number of samples to accurately estimate the parameters of a multivariate distribution. However, MCMC has some significant limitations. For instance, it is very difficult for MCMC to sample from non-concave distributions, such as distributions with multiple modes or mixtures of several distributions. More complex versions of MCMC exist, but they are fairly complicated to use. These are often problem-specific and require expert tuning. Also, the Gibbs Sampler, a precursor to MCMC, can only sample from known distributions.

For these reasons, Dr. Yuchung Wang and his colleagues invented the Global Likelihood Sampler (GL) that can simply and accurately sample from any distribution, including multimodal distributions [2]. One benefit of GL is that it can sample from the kernel of the distribution, since calculating the relative likelihood of each point is the same regardless of the normalizing constant. In addition, GL can be easily implemented in R, a statistical programming language. Here, GL was tested on a bivariate, bimodal distribution whose conditional distributions are normal, as proposed in Gelman and Meng [3]. The results of GL are compared to those of the Gibbs Sampler. The mean, standard deviation, and variability of these statistics were compared, as were the distributions generated by each sample. Regression equations generated by each method for one variable given another were also compared to the regression equation of the parent graph. It turns out that GL can accurately estimate every statistic of interest. Overall, this method has much promise for the future.

References:

1. M. Richey, The Evolution of Markov Chain Monte Carlo Methods, The American Mathematical Monthly, 117(5) (2010) 383–413.
   https://doi.org/10.4169/000298910×485923

2. Y.J. Wang, J. Ning, Y. Zhou, Global Likelihood Sampler for Multimodality, unpublished (2017).

3. A. Gelman, X.L. Meng, A Note on Bivariate Distributions That Are Conditionally Normal, The American Statistician, 45(2) (1991) 125–126. https://doi.org/10.2307/2684374

Since the Industrial Revolution, our planet has been subject to significant environmental changes. The impact of human activities on our planet are predicted to continue increasing at alarming rates potentially posing a risk for human well-being. Particularly two global change drivers, warming and nutrient deposition, are major processes that threaten the functioning of Earth’s ecosystems. Many studies have investigated the effects of temperature and nutrients on terrestrial ecosystems; however, current research shows that there is a lack in understanding of the overall interactive effects of warming and nutrient enrichment on ecosystems. To address this knowledge gap, we integrated information from an ongoing meta-analysis on the consequences of warming and nutrient inputs on decomposition rates, a key ecosystem function, and a field mesocosm experiment. Results from our meta-analysis showed that warming and nutrients increase decomposition rates, although there was no significant difference in the magnitude of the effects between these drivers. Our field experiment showed that decomposition rates did not increase with warming, but that increases in fertilization by the manure treatment decreased decomposition by microbes. These results suggest that detritivore presence can negatively impact microbial biomass, decreasing the decomposition of organic matter. These findings can help us improve our understanding of how increases in temperature and nutrients interactively affect ecosystem functioning, which in turn can negatively impact human well-being.

The purpose of this project is to (1) determine to what socioeconomic extent the Jewish people had an effect on economies in the European states in which they resided during the early modern world through their influence and occupations; (2) determine to what extent there was antisemitic behavior and if it was prevalent enough to affect states’ domestic or foreign policy objectives; (3) determine if there are stereotypical connections towards Jewish people in an aforementioned manner between the states of the early modern world and more contemporary geopolitical attitudes; (4) determine how Jews were able to communicate over networks that transcended the state and how these networks were formed.

The goal of this project is to produce a meta-review analysis focused on the field of the mathematical modeling of cancer. Mathematical modeling of cancer is a large field that is made from different communities ranging from computational scientists, applied mathematicians, biophysicists, and more. Having a wide range of research is required as cancer is complex surrounding several different diseases with many mathematical methods proposed to approach these large areas to cover in cancer. This research was to conduct a survey of surveys from the analysis of many literature review papers from the communities for mathematical modeling of cancer. For the analysis an extensive list of supporting review literature was gathered to assist in looking for overlap and disjoint activities within the communities.

While reading the literature can bring a depth of knowledge of the field as a whole, looking into aspects of the papers like keywords authorship, and citations can help to reveal more dynamics about the community. Using different graphs of networks from these things such as keywords can show how connected or disjoint aspects of the community have been over time. The research purpose helps to describe the different research communities for this broad and important topic while also looking at the scholarly production of the field, various approaches that are proposed, and how the community has evolved over time. The overall effect of the research can help bring communities together and ideas which can help advance the field for the mathematical modeling of cancer.

Non-invasive sampling methods are preferred when analyzing cultural heritage materials to determine chemical composition; common techniques include infrared (IR) spectroscopy utilizing external reflectance (ER) or attenuated total reflectance (ATR). However, in some instances, the complex three-dimensional shape of the object prevents the application of these techniques. For this study, the possibility of utilizing diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) was evaluated. Specifically, various grits of sandpaper, 600 (coarsest) to 2000 (finest), were employed. Known polymers, including high density polyethylene (HDPE), polystyrene (PS), poly(methyl methacrylate) (PMMA), and Nylon 6,6 were abraded by the sandpaper; both systematic rubbing of the polymer against the sandpaper and rubbing of the sandpaper against the polymer were evaluated. The smallest possible amount of sample should be utilized; hence, microgram (μg) quantities were collected and measured using a microbalance. The quality of the resulting IR spectrum was carefully evaluated for each polymer. The major bands (peaks) of each IR spectrum were recorded and compared with reference spectra of the known polymers. The possible use of sandpaper in diffuse reflectance IR spectroscopy was investigated as a sampling method for polymer materials found in cultural heritage collections. The results using this method will be compared with the major vibrational modes (bands) detected using ER and ATR sampling techniques.

Polymersomes, which are fully synthetic vesicles self-assembled from diblock copolymer amphiphiles, have great potential to encapsulate and deliver molecular cargo for a vast amount of applications. These spherical vesicles have two distinct compartments: an aqueous lumen and a hydrophobic bilayer membrane. By incorporating plasmonic gold nanoparticles (AuNPs) into the hydrophobic bilayer, this then allows for the nanovesicles to be light responsive due to localized surface plasmon resonance (LSPR). LSPR is an optical phenomenon in which when light waves interact with nanoparticles smaller than the wavelength of incident it creates an oscillating electric field which excites the conduction/surface electrons and causes them to oscillate in tandem with the electric field generating localized heating. The unique aspect of conductive NPs is that the size they have can be controlled and tuned which can allow for different wavelengths of light to be absorbed. Which has practical application since red light (640 nm) and blue (400 nm – 490 nm) can penetrate skin. The work presented herein is designed to test light activated release (Nano polymersomes have been shown to have self-healing capabilities after sustaining damage this in turn can limit the amount of cargo being released depending on the amount of poration in a given time) and rupture using a PULSE laser. This all together leads to high spatiotemporal control of cargo delivery.

Creation of nanopores on DNA origami with spatiotemporal control is important for the controlof smart carriers. Plasmonic nanomaterials such as gold nanoparticles (AuNP) can use its plasmonic properties to modify the surfaces of nanostructures upon laser irradiation. Laser irradiation the gold nanoparticle will heat up and directly transfer the thermal energy from the gold nanoparticle to the DNA origami structure and the gold nanoparticle will dissociate from the original nanostructure. This heat transfer will cause an expansion of the origami and the formation of nanopores. To control the exact placement of these nano pores gold nanoparticles will be placed in specific areas of the origami. Currently the study of DNA dissociation via gold nanoparticles needs to be further studied Currently the size of the gold nanoparticle can affect the size of the pores formed. Another factor that can control both the length, width, and deepness of the hole is the type of laser being used. The pulse duration and wattage both play a major role in the ability for pores to form on the origami surface. So far the pore formation is directly related to the assembly of the gold nanoparticle attaching to the origami surface. The use of nano pores on nanostructures can be useful in the biomedical research by having a smart carrier deliver therapeutics to specific areas of the body with the therapeutic not reacting with unintended organs and organ systems.

When looking at history through a wide lens, acknowledging pandemics as frequent and unavoidable is not difficult to do. Since the origin of organic life, disease has been a prominent feature. Therefore, it is also not much trouble to imagine that humanity will experience additional pandemics in the future. Knowing this, it is clearly important to investigate past pandemics and modern pandemics in order to garner information that will affect our response to future pandemics: medically, legislatively, socially, physically, emotionally, and psychologically. Conveniently, investigating the psychological effects of past and modern pandemics can lead to information on how to cope with future pandemics in all other potential areas of life as well. Psychology dictates the majority of what non-sentient aspects of life cannot, and therefore deserves to be delved into.

Through my research, I studied and compared how those living during both the Black Death Pandemic and the COVID-19 Pandemic handled subjects such as quarantines, religious influences, prejudice, scapegoating, economic changes, governmental decisions, and much more. I discovered that 14th-century Europeans had much more in common with 21st century Americans and Europeans than one might originally think. For example, both groups of people found quarantine policies and enforcement to have an incredible psychological weight to them. The strain of isolation and changes in daily routine weighed on everyone involved. Another example of similarity between time periods can be seen in terms of workers’ rights movements. The Black Death Pandemic led to an end of serfdom and feudalism just as the COVID-19 Pandemic led to immense demand from employees for higher wages and increased respect.

One similarity between the effects of both pandemics that desperately requires changing, however, is preparation for the future. 14th century Europe did little to nothing to truly prepare themselves for the inevitable next pandemic to come, just as the modern United States has done. Most importantly, in order to prepare for our next pandemic, we need to increase public knowledge of how mass disease works, and how they can influence the future as to avoid issues society encountered with COVID-19, such as understaffing nearly everywhere, a lack of adequate medical equipment, distrust in leaders and policies, and ignorance about what a pandemic really entails in all aspects of life.

The purpose of the research was to test the impact of college meaning (i.e., deriving a sense of meaning in life from educational pursuits in college) on students’ academic self-efficacy. In Study 1, 378 undergraduate students completed measures of college meaning and academic self-efficacy. The study revealed that college meaning was positively associated with academic self-efficacy. Study 2 tested the impact of college meaning on academic self-efficacy using an experiment. In Study 2, 308 undergraduate students completed a college meaning or control manipulation, followed by a measure of academic self-efficacy. It was found that students who completed a writing prompt which had them reflect on how college gives their life meaning reported stronger academic self-efficacy when compared to students who completed a control writing prompt. Getting students to consider the existential importance of college appears to be one way of inspiring positive beliefs about their ability to succeed in college.

This project draws on scholarship, local public history resources, and oral histories to explore the historical experiences of Black people, especially Black families, in the South Jersey/Philadelphia region. The project explores Black history through various aspects of Black life – recreation, work, art, travel, education, community building, homeownership, and so on. As a result of being the last Northern state to abolish slavery, Black New Jerseyans experienced anti-Black laws and a tougher Jim Crow. Most Black people who arrived in New Jersey came by means such as the Great Migration, the Underground Railroad into New Jersey or buying their own freedom. For example, I interviewed Sam Still III, a man who has been preserving his own family history since he was twelve years old, and later, his family’s home in Medford. His ancestors are the Stills, namely James Still – the Black Doctor of the Pines. A life that is not uncommon to other Black lives but extraordinary nonetheless. As a self-taught herbalist, Dr. Still aided people, hospitals, and other doctors all over the South Jersey and Philadelphia region during the latter half of the 1800s. He is an example of many who had to teach themselves their passions because the opportunity to learn elsewhere was denied. Black business owners, performers, and families alike had to navigate the Chitlin’ Circuit here on the East coast to find the venues and locations safe for them to lay their heads at night, feed themselves, and make a living. Shamele Jordon, a professional genealogist from Lawnside, NJ I had the chance to interview, has an uncle who famously owned a bar in the Circuit – the Tippin Inn in Winslow Township. James Toomer, related to the late Jean Toomer, Black Harlem Renaissance poet, writer, and activist. After just a few interviews with connections I made, I was able to fill in a few pieces in the puzzle of Black history. That is what I believe the purpose of this project is – to help educate and fill in the blanks for those who want to know more and for those who feel the similar duty as I to preserve our history like our ancestors did.