Participants

Note: Talks are five minute five slide presentation, Posters are three minute single slide presentations

Kimberly Calix, Biochemistry Major
Mentor: Dr. Yvonne Gindt, Department of Chemistry and Biochemistry
Presentation: Poster; Can We Make Thermophilic Proteins Work Better Using Some Heat Pretreatment?
Abstract: Thermophilic, or heat-loving, proteins are found in organisms that live and thrive at high temperatures; these proteins are ubiquitous in the biotechnology industry due to their special ability to maintain function at high temperatures. These proteins are manufactured using genetically engineered bacteria called E. coli, which grow optimally at 37 C. In our studies, we find that our thermophilic protein that is produced at these moderate temperatures appears to be not folded in its most optimal structure, or what can be referred to as a metastable state. We are able to make this conclusion because our protein is unusual since it contains a colored cofactor, or small molecule, that reports the protein structure by its absorption spectrum. We have found that our thermophilic protein appears to assume a more stable structure when it is briefly heat annealed at higher temperatures. This conclusion is based on our findings that the heat annealed protein is more resistant to chemical denaturation, indicating that the heat annealed protein is more stable. We are now investigating to see if we can use a small amount of chemical denaturant to make the protein slightly unfold and then refold it into a state similar to what we observed with the heat annealing treatment. Increased stability of heat-treated thermophilic proteins could have enormous economic significance to the biotechnology community.
John Notte, Physics Major
Mentor: Dr. Rodica Martin, Department of Physics and Astronomy
Presentation: Poster; A better look at the universe: Low-loss Faraday isolators for the A+ upgrade
Abstract: The current LIGO detectors are undergoing a significant upgrade called the Advanced LIGO Plus project, or A+, that will increase their sensitivity to make more frequent detections and observe much fainter signals from further away gravitational-wave sources. Increased sensitivity requires low-loss Faraday isolators, which are devices that limit scattered light from building up and creating noise in the detectors. One of our tasks in this project was to characterize the individual high-precision optics for these low-loss Faraday isolators, each with their own purpose and challenges. In this talk I will present optical measurements of reflectance and polarization on a variety of optical components and will show that for perfect alignment we can achieve ~ 0.4% total losses, much less than the A+ requirement of the device of 1%. This work was supported by the National Science Foundation through awards PHY-1806839 and CIT 75-S434395.
Anthony Gachetti, Earth & Environmental Science Major
Mentor: Dr. Ying Cui, Department of Earth & Environmental Studies
Presentation: Talk; Using Earth’s Paleoclimate Record to Predict Future Climate Change
Abstract: The goal of our project is to fill in a critical research gap in Earth’s past climate records. Most contemporary climate models are based on recent climate records and are insufficient in predicting the degree, speed and impacts of future climate change. We collected 480 rock samples from a site formed 56 million years ago, known as the Paleocene-Eocene Thermal Maximum or the PETM, when a rapid global warming happened caused by significant carbon emissions. This is the most analogous event in Earth’s paleoclimate history to the modern condition but there are still massive gaps in our understanding of the period. One of the most significant sources of heat and moisture during the event was the Tethys sea, (the precursor to the modern Mediterranean). 90% of organic carbon is buried in shallow marine environment like the eastern Tethys, but it is also a very poorly studied region. Therefore, we selected this location to study the responses of the shallow ocean to rapid global warming. Our degree of precision is very high as samples were collected at 10cm increments covering 200,000 years over the course of the event. We used a mass spectrometer to gather major element data, trace element data and isotopic data for carbon, oxygen and nitrogen. Using these values as proxies, we can reconstruct the nutrient condition of the ocean, the amount of oxygen in the water and the sea surface temperatures. It is also important to verify the site we studied indeed record the PETM in detail. By using a microscope to identify calcareous nannofossils from the samples collected, we were able to verify this is a high-resolution record indicative of the PETM. Through this process we will be able to make much more accurate predictions for contemporary climate change by solidifying the paleoclimate records.
Katherine Schaffer, Chemistry Major
Mentor: Dr. Glen O’Neil, Department of Chemistry and Biochemistry
Presentation: Poster; Light Addressable Electrochemical Sensors for Imaging Neurotransmitters
Abstract: Light-addressable electrochemical sensors (LAESs) are a class of sensors that use light to activate an electrochemical reaction on the surface of a semiconducting photoelectrode. Here, we investigate semiconductor/metal (Schottky) junctions formed between n-type Si and Au nanoparticles as light addressable electrochemical sensors. To demonstrate this concept, we prepared n Si/Au nanoparticle Schottky junctions by electrodeposition and characterized them using scanning electron microscopy, cyclic voltammetry, and electrochemical impedance spectroscopy. We found that the sensors behaved almost identically to Au disk electrodes for the oxidation of an outer-sphere redox couple (ferrocene methanol) and two inner-sphere redox couples (potassium ferrocyanide and dopamine). In buffered dopamine solutions, we observed broad linear ranges and submicromolar detection limits. We then used local illumination to generate a virtual array of electrochemical sensors for dopamine as a strategy for circumventing sensor fouling, which is a persistent problem for electrochemical dopamine sensors. By locally illuminating a small portion of the photoelectrode, many measurements of fouling analytes can be made on a single sensor with a single electrical connection by moving the light beam to a fresh area of the sensor. Altogether, these results pave the way for Schottky junction light-addressable electrochemical sensors to be useful for a number of interesting future applications in chemical and biological sensing.
Sarah Acquaviva, Mathematics Major
Mentor: Dr. Deepak Bal, Department of Mathematics
Presentation: Poster; An Analysis of the Montclair State Course Enrollment Network
Abstract: We examine the student networks obtained by considering the course enrollments at Montclair State University across various semesters in order to understand the extent to which capping class sizes has an effect on the networks. Specifically, we simulate a simple model of viral spread (“bootstrap percolation”) on our networks to investigate the likelihood of a viral outbreak if our university were to impose various maximum class sizes. Additionally, we examine average shortest path length, which measures how many steps it takes to get from one student to another, within our networks in order to study the impact that capping class sizes has on the interconnectivity of our student population. Overall, we determine that capping class sizes does have a clear effect on both the likelihood of an outbreak within our student network under our basic viral spread model and some of the interconnectivity properties of our student network. In order to have the most significant effect, though, class sizes should be relatively small, which is not entirely practical.
Hope Diamantopoulos, Computer Science Major
Mentor: Dr. Weitian Wang, Department of Computer Science
Presentation: Talk; YOU ARE IN MY HEART: Worker Emotion Understanding for Future Worker-Robot Collaboration-Safety Improvement
Abstract: Smart manufacturing, which has attracted an increasing number of investors in recent years, plays a key role in the fourth industrial revolution, with prominent characteristics such as mass customization and high flexibility. Human worker-robot collaboration is inevitable in smart manufacturing as industries push towards a more efficient and innovative future. Enabling collaboration between workers and robots allows robots to handle the repetitive and mind-numbing tasks that might lead to human boredom or, worse, error. It is imperative that robots are able to thoroughly understand worker-robot collaboration dynamics, especially workers’ subjective feelings, and adjust actions accordingly. This allows human workers to provide input on and control the more difficult endeavors and ensures a safe future in which workers feel comfortable. However, few studies have been conducted on the issues of human subjective factors in worker-robot collaboration. In an effort to ensure safe worker-robot collaboration in smart manufacturing tasks, we teach a collaborative robot to understand 7 different human emotions. In this presentation, our development process, the robot learning algorithm, and real-world experimental results will be shown and discussed. This project works on real-time on-site human emotion understanding, so it would prove quite useful in manufacturing environments where collaborative robots are already being utilized (and will continue to be utilized more and more with time). Our approach can enable the robot to accurately understand different worker emotions. By way of example, if the worker seems upset or hesitant, the robot will slow down, and if the worker seems to be upbeat or in a good mood, the robot will pick up the pace, matching the human worker’s energy. This allows for safe collaboration in worker-robot partnerships, fostering efficient working environments, improving ergonomics, and empowering future workforce. A future roadmap of this work and its potential commercial value will also be discussed.
Evelyn Visan, Molecular Biology Major
Mentor: Dr. Nina Goodey, Department of Chemistry and Biochemistry; Dr. Kirsten Monsen, Department of Biology
Presentation: Poster; The Road to a Portable, Accurate, Rapid Aptamer Test
Abstract: There is a great need for rapid, accurate diagnostic tests for pathogens that can be done in real time to aid in the prevention of disease transmission. Aptamers are stable, single stranded DNA molecules capable of folding into 3D structures that bind to a target such as a virus. Because aptamers are inexpensive, stable in a variety of temperatures, and easily modified, they will exceed current testing methods and have many advantages over protein- based tests. Aptamers that were selected to specifically bind to Ranavirus (a highly contagious and lethal virus affecting amphibians, fish, and reptiles) were enriched using a selection process called SELEX. The objective of this study is to identify patterns of nucleotide order among the aptamers and predict how they fold. The specific 3D shapes these aptamers fold into will control how tightly and specifically they bind to Ranavirus. Three bioinformatic programs were used to understand the patterns present in the enriched aptamer library. A bioinformatic tool called MEME Suite was utilized to pinpoint significant motifs in the enriched aptamer libraries, resulting in identification of 25 significant motifs. Next, a multiple sequence alignment program was used to group aptamers into clusters based on their shared nucleotide patterns. Finally, the program RNA Fold was used to predict the 2D structures of the aptamers in every cluster to identify structural commonalities. Now that these patterns and structures have been identified, the next step is to conduct binding assays to determine binding affinity of the aptamers to the Ranavirus target. Ultimately, this research can be utilized to create a quick, dipstick style field test for Ranavirus. Additionally, this research can be used to develop rapid, point-of-care diagnostic tests for a variety of viral pathogens.
Allison Conlon, Applied Math and Statistics Major
Mentor: Dr. Youngna Choi, Department of Applied Math and Statistics
Presentation: Poster; Tax Cuts and Jobs Act of 2017 and Its Effects
Abstract: In December of 2017, the Tax Cuts and Jobs Act (TCJA) was passed to implement new tax cuts and a uniform, lower corporate tax of 21%. We used publicly available data and statistics from the Census, IRS Statistics, Survey of Consumer Finances of 2019, etc. We discovered that certain populations did not get a tax cut but actually experienced an increase after the TCJA. For instance, people between the individual tax bracket from $157,000 to $191,650 saw their tax rate go up from 28% to 32% in 2018 which shows that the act was not in favor of everyone as it had claimed. The data also show that the income and wealth gap have increased among the top 10% and the bottom 90%. In addition, the government was not financially ready for the TCJA as we were in the highest deficits since the post WWII era and the deficit has continued to rise to date. A positive result of the act is that the wage gap between White Americans and Black and Hispanic Americans has decreased. Nevertheless, the individual tax cuts do expire in 2025, after which, those who benefit from the tax cuts could be worse off as people will have to pay more taxes which they may not be aware of now, and the wage gap between the races may start to increase again. On the other hand, the corporate tax cut stays and the ultra-rich are going to continue to reap the benefits of it while also increasing their gap. In conclusion, the TCJA may not be the best for our country as it has been claimed because it seems to have more disadvantages for ordinary people and the federal government.
Paolo Turano, Biology Major
Mentor: Dr. Carlos Molina, Department of Biology
Presentation: Talk; Coconut Oil Contributes to Nonalcoholic Fatty Liver Disease (NAFLD) In A Gender Dependent Manner
Abstract: Obesity is one of the leading health problems in today’s society, over 40% of the US population is considered obese. Obesity has been shown to cause a wide array of diseases, including nonalcoholic fatty liver disease (NAFLD). NAFLD is the most common chronic liver disease worldwide, characterized by the accumulation of fat within liver cells which, over time leads to inflammation and scarring of the liver. With obesity leading to so many health problems, various fads promising fast weight loss, such as coconut oil products, are rising in popularity. Although coconut oil has been thought to help in weight loss, there is no conclusive evidence that it can do so. Given the lack of knowledge on the matter, this study aimed to find out whether or not a coconut based diet would lead to weight loss as well as NAFLD. In order to investigate the effects of coconut oil, C57BI/6 mice were used as a model organism and the study was split into 2 phases. In phase 1, the animals were fed one of the following: standard rodent chow, a high-fat lard (HFL), a low-fat lard (LFL), a high-fat coconut (HFC) and a low-fat coconut (LFC) diet. In phase 2, the animals were placed on a HFL diet for 14 weeks after which the animals were switched to one of the following diets: HFC, LFC, and LFL for an additional 16 weeks. Results showed that there was no difference in weight loss between switching to a LFC or a LFL diet. This suggests that switching to a LFC diet will not result in any more weight loss compared to switching to a LFL diet. Liver tissue in HFC males showed significant signs of fibrosis as well as inflammation whereas liver tissue in HFC females was not as inflamed or fibrotic.