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Research in Gender Studies

‘Just Like Everyone Else’: Queer Representation in Post-Millennial Bollywood

 

By Nikki Sylvia

Portrait of Nikki (Paige) Silva

 

I am a Psychology major and member of the Psi Chi honor society. In Spring 2021, I took a course on “Gender and Sexuality in Bollywood Films,” with Professor Anupama Arora (English & Communication; Women’s and Gender Studies). In this course, we watched popular Hindi-language Indian films from the mid-twentieth century to the present. For my final research paper, I focused on two recent films that focused on same-sex love/desire, a subject rarely dealt with in classical Hindi/Indian cinema. I presented a version of this paper at the annual conference of the National Council of Undergraduate Research (NCUR) which was held virtually in April 2022; and I am grateful to the Office of Undergraduate Research at UMassDartmouth and the CAS Dean’s Office for supporting me. Furthermore, along with Prof. Arora, we have developed this paper into a longer co-authored journal-length article, which is currently under review at a scholarly academic journal.

 

The paper is titled “‘Just Like Everyone Else’: Queer Representation in Post-Millennial New Bollywood.” In a film industry where representations of heterosexual romance reign supreme and where explicit or sympathetic portrayals of non-normative desire or sexualities, while existent, have been marginal and few and far between, two recent films in particular stood out to me for their unapologetic expression of gay and lesbian struggles: Shelly Chopra Dhar’s Ek Ladki Ko Dekha Toh Aisa Laga (How I felt When I Saw That Girl, 2019) and Hitesh Kewalya’s Shubh Mangal Zyaada Saavdhan (Be Extra Wary of Marriage, 2020). These films followed in the wake of a historic legislation in India: on September 6, 2018, after decades of queer activism, Section 377 of the Indian Penal Code (the centuries-old law against sodomy) was declared unconstitutional by the Supreme Court of India.

 

The essay examines these two films as milestones of sorts in queer representations in post-millennial Bollywood. It shows how the films seek to disrupt the larger discourse around nonconforming gender/sexual subjects in popular Hindi cinema. Both films bring attention to, and contest, discourses around homosexuality in India that pathologize it – as unnatural, abnormal, filthy/dirty, disease/sickness, a crime, or as a Western import. The films make complex maneuvers to normalize same-sex love, and incorporate queer identity in ways that render it non-threatening to the heteronormative status quo. However, through their intertextual interventions (allusions to many other popular Hindi films and the conventions of this cinema), both these Bollywood “malltiplex” (mall + multiplex) films carry the potential of unsettling the dominant cis-heteropatriarchal order and imperatives of Hindu Indian society reflected in popular cinema. Thus, these recent films, even with some of their shortcomings, are refreshing for breaking the barriers of same-sex visibility in mainstream Indian cinema and can be seen as critical steps toward broader acceptance of queer identities and relationships.

Research in Biology

Determining relative growth rates of bacterial isolates from marine biofilms

This work was conducted in the lab of Dr. Moisander, Department of Biology

By Andrea Pires

Andrea Pires at work in Dr. Moisander’s lab

 

Abstract

Biofilms of marine bacteria develop within hours of any surface submersed in seawater. Over the course of days and weeks these biofilms of bacteria mature to include protists, algae, cyanobacteria, and eventually unicellular and multicellular eukaryotes. Mature biofilms can interfere with marine operations such as boating and aquafarms, at which point they are referred to as biofouling. Antifouling methods have been developed to prevent biofouling, the most common of which involves coating the submersed surface with specialized toxic paint (de Carvalho, 2018). However, current antifouling methods are expensive and can be harmful to the environment. Potential targets for alternative antifouling methods could be found in the formation of biofilms at their early stages. There are many factors that are involved in early biofilm formation such as relative growth rates influencing bacterial fitness. This study focused on characterizing growth rates of 18 strains of marine bacteria recently isolated and identified from marine biofilms in Buzzards Bay. These cultures include bacteria from the Gammaproteobacterial genera Alteromonas, Pseudoalteromonas, Cobetia, Marinomonas, Salinimonas, Oceanobacter and Shewenella. The relative growth rates of the cultures were obtained through a series of 24-hour growth experiments. The estimated growth rates ranged from a minimum of 0.0847 h-1 to a maximum of 0.489 h-1. Significant differences in the growth rates among experiments were found for some strains. Significant differences were also found among the growth rates of strains within the genera Pseudoalteromonas, Salinimonas, and Shewenella but not among strains of Alteromonas sp.

 

Introduction

Biofilms are communities of adhered cells formed by bacteria and other microorganisms that cooperate to increase their chances of survival. In the marine environment, any submersed surface will rapidly develop a biofilm of bacteria that eventually matures to include other microorganisms such as protists, cyanobacteria and algae (de Carvalho, 2018). Advanced biofilms develop into biofouling, whose growth on submersed surfaces such as ship hulls and pipes can interfere with marine operations. For instance, the development of biofouling on ship hulls increases fuel consumption and fossil fuel emissions (Schultz et al., 2011). Various actions have been taken to eliminate biofouling, known as antifouling methods. The most common of these antifouling methods includes specialized toxic paint, which have their own negative impacts through toxicity to surrounding biota (de Carvalho, 2018). However, the costs and environmental impact associated with the development of biofouling and its prevention are substantial. Therefore, it is of interest to investigate the early stages of biofouling for purposes of exploring new potential targets for more affordable and environmentally sustainable antifouling methods.

In the initial stages of biofilm formation marine bacterial organisms colonize the submersed surface allowing for the adherence of successive colonizers such as protists and algae (de Carvalho, 2018). Targeting these initial bacterial colonizers could be an effective way to stop the development of biofouling at the source. However, more knowledge is needed about the growth dynamics of the initial biofouling colonizers. To begin, the relative growth

 

rates of 18 culture isolates of marine bacteria established and identified recently from marine biofilms in Buzzards Bay were investigated. All cultures used are common community members during early colonization of local marine biofilms (Naik et al., 2022). The methods and data from this experiment will help develop model systems for examining growth of initial biofouling colonizers and for designing further studies on impacts of antifouling methods on these bacteria.

 

Methods

 

Experimental Design

Reviving glycerol stocks

All culturing was conducted in a biosafety hood treated beforehand with ultraviolet light for at least 15 minutes. Sterile 5-mL tubes were used to revive the cultures from the glycerol stocks. The tubes were filled with 2.5-mL of marine broth. The glycerol stocks of the cultures were stored at -80ºC. The glycerol stocks of the cultures were kept on ice and using sterile, single-use inoculating loops, a small amount of the stock was obtained and transferred into its corresponding sterile 5-mL tube in the biosafety hood. The inoculated tubes were grown overnight (~24 hours) in a dark incubator at ~25-28ºC on a stirring plate.

 

Measuring Optical Densities (OD)

The next day, the optical densities of the overnight growth cultures were measured, and each strain was streaked on a Marine Agar plate (Fig. 1). 200 µL of each culture were added onto three wells of a non-treated polystyrene plate and read at 600 nm with a plate reader. These optical densities were then used to calculate the dilution factor for an OD of 0.05 and a total volume of 1000 µL. Using the subsequent dilution factors, a specific amount of each culture and Marine Broth were added to 2-mL sterile tubes. The optical densities of these dilutions were then measured again and recorded.

 

24-hour Growth Experiment

To prepare for the 24-hour growth experiment a plate lid was treated with 0.05% Triton X-100 in 20% ethanol to alleviate condensation forming in the lid throughout the 24-hour incubation. Each culture, adjusted to the approximate OD 0.05, further diluted with media to 1:100, was

 

aseptically pipetted to six replicate wells of a 96-well polystyrene plate. Each plate also included six wells with media only, serving as a negative control. The treated plate lid was then placed on top of the plate. The plate was then placed inside the microplate reader and grown at 25ºC. The plate reader program was adjusted to record optical density at 600 nm every 20 minutes for 24 hours. These readings were saved and used to estimate the growth rates of the marine bacterial cultures.

 

Estimating Growth Rates

The optical density readings recorded from the 24h growth experiments were then used to estimate the maximum growth rates of each strain and replicate (each well). The Easy Linear function within the R growthrates package was used to fit a linear model to the log- transformed data to find the maximum growth rate separately for each well, resulting in six separately calculated growth rates per strain per experiment (Petzoldt, 2020).

 

Results

The 24h growth overnight experiment was performed for each of the bacterial cultures at least once and up to seven separate times. The untransformed growth curves obtained by the 24h experiments were plotted for each experiment using the R growthrates package (Fig. 2). The estimated maximum growth rates ranged from a minimum of 0.0847 h-1 to a maximum of 0.489 h-1 across all strains and replicates (Table 1).

One of the aims of the experiments was to assess the methodological repeatability of the growth rate measurements across experiments. The variability in maximum growth rates of strains among experiments was analyzed using a series of one-way ANOVAs (Fig. 3). Growth rates of strains 9214 and 9273 were significantly different across experiments (one-way ANOVA, p < 0.05). Strains 9213, 9212, 9243 and 9275 were tested only once and the remaining strains showed no significant differences across experiments (one-way ANOVA, p>0.05). The growth rates of strains within the same genus were also compared using a series of one-way ANOVA tests. The Pseudoalteromonas genus included strains 9206, 9207 and 9274. There was a significant difference in the growth rates of strains 9206 and 9274 but other strains showed no differences. The Alteromonas genus included strains 9211, 9215, 9239, 9243, 9273, 9282, and 9283, and had no significant differences in their growth rates (p >0.05, Fig. 4). The Shewanella genus included strains 9242 and UMD1 with significantly different growth rates (p<0.05). The Salinimonas strains included strains 9275 and 9278 that also differed significantly in their growth rates.

 

 

Discussion

This study characterized growth rates of 18 recent marine biofilm bacterial isolates in the form of growth curves under standardized conditions. Calculated growth rates were used to examine any differences among the strains with respect to their growth patterns in monocultures. Variability across experiments is indicative of the reproducability and reliability of the growth rates obtained using this method. The data obtained from the growth experiments showed there was variability among experiments and strains within the same genus. However, only a few strains showed significant differences among experiments. For instance, strain 9213 showed significant differences in growth rates among experiments. This could have been influenced by the fact that it was later found to be a mixture of two different bacteria. Sources of variation within a single strain across experiments appear to have stemmed from periodically poor success in initial revival from glycerol or possibly experimental error.

Increasing the number of replicates per strain could help assess sources of variation among experiments.

There were significantly different growth rates among strains of the Pseudoalteromonas, Shewanella and Salinimonas genera but none were seen in the Alteromonas genus. These identified differences are likely due to slight functional differences among the strains but also could indicate more consistent differences among genera. Such differences may play a role in individual strain fitness in marine biofilms and will be of interest in future studies. Alteromonas spp. form a dominant component of early biofilms in local waters, while Shewanella spp. form a more subdominant group (Naik et al. 2022). A generally lower growth rate of Alteromonas was observed compared to Shewanella under the nutrient enriched conditions in these experiments and appears not to support the idea that representatives of Alteromonadaceae win during early biofilm colonization due to their superior growth rates.

Ultimately, these results will inform the growth curve methods and strains used in future experiments investigating biofilm formation along with competition and facilitation in co-cultures.

 

References

de Carvalho, C. C. C. R. (2018). Marine Biofilms: A Successful Microbial Strategy With Economic Implications. Frontiers in Marine Science, 5. https://www.frontiersin.org/article/10.3389/fmars.2018.00126

Naik, A., Smithers, M., & Moisander, P. H. (2022). Impacts of UV-C Irradiation on Marine Biofilm Community Succession. Applied and Environmental Microbiology, 88(4), e02298-21. https://doi.org/10.1128/aem.02298-21

Petzoldt, T. (2020). Estimation of Growth Rates with Package growthrates. https://tpetzoldt.github.io/growthrates/doc/Introduction.html

Schultz, M. P., Bendick, J. A., Holm, E. R., & Hertel, W. M. (2011). Economic impact of biofouling on a naval surface ship. Biofouling, 27(1), 87–98. https://doi.org/10.1080/08927014.2010.542809

Research in History of Art & Architecture

 

Architecture and Morality in Antebellum New Bedford

 

By Kayla Rausch

Does architecture manifest social and moral principles? Can we equate ethics with aesthetics? How can historical architectural styles reveal the values of societies in which they were built? My name is Kayla Rausch, a third-year Art History major, and I am the Fall 2021/Spring 2022 recipient of the New Bedford Art Museum/Artworks! Student Fellowship. Under the supervision of my advisor, Dr. Pamela Karimi, I have been developing my research project entitled Architecture and Morality in Antebellum New Bedford. Because it was home to some of the most affluent in antebellum America, New Bedford, MA, is an ideal location for studying the moral and ethical dimensions of stylistic preferences in American architecture.

My project examines how local architecture was emblematic of the esteemed values upheld by influential and affluent citizens of New Bedford during its Whaling boom in the pre-Civil War era. Amidst such prosperous conditions, the Society of Friends or Quakers—who had fled England to escape religious persecution during the 1600s— embraced simplicity and rejected excess ornamentation in their architecture. Contrasting the opulent Greek and Gothic-revival or the Second Empire styles, which were built and owned by other prosperous New Bedford whaling captions and businesspeople, New Bedford Quakers’ preference for modesty demonstrated that, even within the same society, there were differing ideas of morality and taste.

Examining how the Quakers’ values (which are visually depicted through their architecture) starkly contrasted the elitist ideals promoted through the surrounding structures, I embarked on a tour of the New Bedford Friends Meetinghouse and conducted interviews with experts and members of the Society of Friends. I learned from them how simplicity and transparency are at the heart of their values. Additionally, I have studied how Quakers have long been strong advocates of social activism and committed to racial equality as quintessential components of their faith. Specifically, Quakers played a major role in the abolitionist movement in New England. Though not all Quakers publicly participated in the abolitionist movement, they helped create a safe haven for runaway slaves who came to Massachusetts from the southern states. Quakers also advocated for gender equality, encouraging women to participate in businesses while their men were away and busy with whaling. My research aims to demonstrate how many of these values were manifested in both public and private buildings built and owned by Quakers.

In addition to extensive fieldwork, I have made numerous visits to the New Bedford Free Public Library to investigate nineteenth century society and Quaker history. The library has also afforded me an examination of mainstream nineteenth-century materials, such as architectural pattern books, popular magazines, and early twentieth century New Bedford city atlases. In order to foster a society centered upon the distinguished tastes of the wealthy, many nineteenth century publications worked to promote sophisticated European tastes. These included popular periodicals, such as Godey’s Lady’s Book and architectural pattern books, such as Asher Benjamin’s The Architect. These materials were all popular in antebellum New England and largely accessible to the New Bedford population.

 

By comparing and contrasting a wide range of published materials, I have examined which moral values were predominantly promoted and to what end. Given the significant role the Quakers played in all aspects of life in Antebellum New Bedford, I have further explored the reasons behind the marginalization of the Quaker aesthetic preferences in the mainstream and canonical discourse of American architecture.

I have presented my work to the fellowship committee and have been invited by the Director of Fine Arts at the New Bedford Public Schools to deliver a talk about my work to younger students.

As mentioned above, this project was awarded the 2022 New Bedford Art Museum/Artworks! Fellowship. In addition, I was a recipient of the Winter/Spring 2022 Office of Undergraduate Research (OUR) award. This grant has provided me the opportunity to conduct research about domestic and Quaker architecture of greater New England at the Boston Public Library as an extension of my project through the New Bedford Art Museum/Artworks! Fellowship. According to my mentor, Professor Karimi, “Kayla’s project is a great example of the high quality of research that undergraduate students at UMass Dartmouth undertake.” I soon plan to publish my work to an undergraduate journal. I also hope to go to graduate school to further study architectural and art history.

 

Research In Biology

 

Risk-Induced Behavioral Changes Increase Survival When Exposed to Predators

By Isabella Mancini 

 

     Portrait of Isabella Mancini, her colleagues, and mentor,

Prof. Michael Sheriff, at Benthic Ecology Society’s annual meeting

in Portsmouth New Hampshire

 

Abstract

Predation risk is a pervasive force in ecology, shaping species interactions and community dynamics. When prey are exposed to predators they may alter their behavior, physiology, or morphology. Risk-induced behavioral changes can include changes to prey refuge use and risk aversion behavior. I hypothesized that the strength of these non-consumptive effects and prey behavioral decisions may depend on resource availability or prey state. I tested this by either exposing the dogwhelk, Nucella lapillus, to non-lethal green crabs, Carcinus maenas (rendered non-lethal by gluing their claws together) or not, for 28 days while varying food availability using the basal resource, Mytilus edulis. We measured individual behavior of Nucella every 3 days throughout the experiment. We also measured initial and final tissue weights, shell weights, and shell lengths of each Nucella in order to track growth. We found that risk-exposed Nucella were more risk averse. We also found that food availability increased risk aversion regardless of risk treatment. Food availability also significantly increased individual growth compared to non-food treatments. I found that there was a cost of predation risk on individual growth when compared to non-risk treatments, however initial prey state did not significantly impact risk aversion, nor did growth. These findings support the hypothesis that resources increase prey state enough to decrease risky behavior when faced with predation risk.

 

Introduction

The influence of predation risk on prey species and communities has become an emerging topic of study in the field of ecology. The risk of predation alone (not including consumption or killing) can alter prey phenotype, fitness, and influence species interactions within entire trophic chains (Peacor et al. 2020). These risk-induced responses may also be impacted by the environment in which they occur and may vary based on individual prey state or condition (Matassa et al. 2016). Learning the nuances of these prey responses is important to understanding the trophic relations and population dynamics in these systems.

Using a notable set of predator-prey interactions in the New England intertidal ecosystem, green crabs (Carcinus maenas) and dog whelk snails (Nucella lapillus), we investigate a novel area of this research: how prey decide to allocate their energy to either foraging or antipredator behaviors. Literature on how resource availability may impact refuge use behavior is lacking in its investigation into the decision a prey would make if the resources are outside of the refuge.

A 2016 study on Nucella, using barnacles as a resource, concluded that food outside of the refuge was enticing prey to engage in more risky behavior in the presence of risk and found that prey state did not dramatically affect this result (Matassa et al. 2016). The impact that food quality and handling time could have on this result is still in question. The alternative hypothesis that available resources could increase prey state, allowing them to stay in the refuge more often, has also not been thoroughly explored.  Here we expand upon the Matassa et al. (2016) study to examine individual level risk aversion behavior and growth when prey are exposed to predation risk or not across two different resource levels during a 4-week mesocosm experiment. We considered both resource availability hypotheses and made predictions that would support each.

 

Methods

Experimental design

We tested the influence of resource availability on prey refuge use behavior using a mesocosm laboratory experiment at the UMass Dartmouth School for Marine Science and Technology campus in New Bedford, MA. 15 Nucella, 10 of which were tagged and used for this experiment, (15.6 ± 1.3 mm, mean shell length ± SD) were placed in each of 24 clear-plastic mesocosms (44.45 cm. L x 30.48 cm W x 17.78 cm H) with independent flowthrough sea water (Buzzards Bay, ~ 18℃) and a 20.32cm2 tile refuge elevated 2cm from the mesocosm floor by PCV pipe. The refuge could be accessed by Nucella but was too low for Carcinus to fit under. Snails could also access the top of the wall and underside lid of the mesocosm for refuge, as crabs could not attack them there (tested, but data not shown). 12 of the mesocosms had a single non-lethal green crab (52.2 ± 0.8 mm, mean carapace width ± SD with its claws banded and super glued shut to ensure they could not consume snails) and 12 mesocosms had blue mussels added as a resource (ad libitum) for a fully crossed 2×2 experiment, including: 6 food plus predation risk (FPR), 6 food no risk (FNR), 6 no-food plus predation risk (NFPR), and 6 no food no risk (NFNR) treatments. The experiment was conducted for 28 days from 7/19/21 to 8/18/21

We recorded snail location every 3 days for all tagged snails. Our designation of in a refuge or in the open was based upon those from Matassa et al. 2016, however, we also conducted preliminary feeding trials with crabs to determine where they could access and consume prey by attaching food (fish) to various locations on the wall and underside of the mesocosm lid. Snail location observations were scored as a -1 if snails were on the tile, in the open or low on the wall where they could be eaten, a 0 if snails were mid-way on the wall where crabs had difficulty accessing them, or a 1 if snails were under the tile, at the very top of the wall or the underside of the lid where crabs could not access them. The sum of the scores was used to estimate individual risk aversion scores for each tagged snail over the 28 days of the experiment. Shell and tissue weights of each tagged snail were taken using a non-destructive buoyant weighing technique (Palmer, 1982) and shell length was recorded using digital calipers. The weights and shell lengths were taken at the beginning and end of the experiment, and growth was calculated as the final-initial measurements.

 

Results

Pairwise comparisons were made between treatment groups and risk aversion score averages (Fig1). There was a significant difference between the FR and non-food treatments (FR|NFC p<0.001, FR|NFR p<0.01, Fig1). There was also a significant difference between our food with risk and food with no-risk groups (FR|FC p<0.001, Fig1). Risk and food both independently and combined increased risk aversion score.  Pairwise comparisons were also made between each treatment and each of our growth metrics across the experiment, tissue weight, shell weight, and shell length (Fig2). Food availability significantly increased all growth metrics when comparing each food treatment to it’s corresponding no-food treatment (FC|NFC and FC|NFR p< 0.001, FR|NFC and FR|NFR p=0.003 Fig 2). Predation risk caused a significant cost in growth when comparing the food control and food risk treatments (FR|FR; tissue and shell weight growth p<0.001, shell length growth p=0.002, Fig2). Risk aversion averages were then compared to the initial state of individual based on each growth metric (Fig3). Risk aversion averages were also compared to overall growth across the experiment using each metric (Fig3). Although there appears to be a negative correlation between risk aversion and each metric in both cases, almost all of these trends were not statistically significant (p>0.05, Fig3) and no correlation was found between risk aversion and initial or overall growth (R2 ~0.33).

 

 

Fig 1. Risk Aversion vs Treatment. This graph shows comparisons of each of the four treatment groups to the average risk aversion score of individual snails within that treatment. Asterisks indicate significance (**** p<0.001). Bars show Mean +/- SD.

 

 

 

Fig 2. Growth Metrics vs Treatment. These graphs show comparisons of each of the four treatments groups to the average growth for each growth metric (tissue weight, shell length, shell weight). Bars show Mean +/- SD.

 

Fig 3. Risk Aversion vs Initial State & Growth. These graphs show trends in risk aversion behavior in comparison to trends in individual initial body condition and in each growth metric. None of these comparisons were statistically significant. Lines show Mean +/- SE.

 

Discussion      

We found that food availability increases growth across all metrics. This means prey that have higher resources are able to grow more. This result occurred as expected, however by comparing the food treatment groups to each other, we are also able to show that predation risk causes a cost to growth. That is, the prey in the FR treatment grew less than the prey in the FNR treatment. This finding could easily be attributed to the negative impacts that predation risk is assumed to have on a prey’s ability to forage, however our remaining findings show that this assumption is not as simple as it seems.

A prey’s ability to prioritize and allocate energy between both foraging and antipredator behaviors has major implications for it’s ability to grow and increase it’s fitness. We found that both food and risk being present increase refuge use both independently and together. These results support the hypothesis that food availability increases prey state enough that they do not need to leave the refuge to forage as often. This is contradictory to the hypothesis (supported by the Matassa et al. 2016) that food availability would increase foraging and entice prey out of the refuge therefore decreasing risk aversion. If this was the case in our study, the lowest risk aversion score should’ve been seen in the FC treatment, but that was not the case. Instead we found that the lowest risk aversion behavior and least refuge use occurred in the NFC group.  There are many possible explanations for why our results support this alternative hypothesis in compared to the previous research. More investigation needs to be done into how the quantity and quality of resources available to prey impact their behavioral decisions. Studies considering the natural and baseline levels of refuge use or fear of predation within prey could also help give insight into these types of contradicting behaviors seen across studies and taxa.

§

 

My Experience at the Benthic Ecology Meeting

      Isabella Mancini at the Benthic Ecology Society’s annual meeting in

Portsmouth, New Hampshire

 

I was lucky enough to attend the Benthic Ecology Meeting in Portsmouth, New Hampshire as part of the Sheriff lab this semester and it was a very unique experience. As an undergraduate, being able to attend a conference like this was incredibly valuable. I got to see tons of presentations of other scientists’ work in the field of ecology and network with professionals. Along with presenting my own work as a poster, I was able to discuss my work with others, including the very people I had cited in my paper, which was amazing. This experience helped me to learn how the world of academia really works and allowed me to talk with people at all stages of their careers, which was extremely beneficial to my understanding of the steps it takes to build a career in the field of biology.

 

Research in Animation & Game Arts

Reconstructing the History of the Hoover Dam for Cutting-Edge Pedagogical Purposes

By James Ristaino

 

James Ristaino is shown here helping users with the VR experience he helped

create along with a team of faculty and other student researchers.

 

§

 

My name is James Ristaino. I am a junior majoring in Animation & Game Arts here at the College of Visual and Performinf Arts at UMassD. For the past couple of years I have been a member of an interdisciplinary research team of faculty, graduate, and undergraduate students on a virtual reality (VR) educational game, which we like to call VR “serious game.” This team, which is consisted of a variety of experts from science, arts, humanities, and computer science, focuses on creating an immersive VR environment for Hoover Dam (https://vrhooverdam.com). Our immersive environment tells the story of the dam’s construction from the viewpoint of photographer Winthrop A. Davis, who moved to Las Vegas in the early 1930s to capture the dam’s construction process. A “serious” educational game, the project is focused on the history of the construction of what my group believes to be “one of the most iconic structures in the world.” We combine cutting edge-technologies with scholarship in the field of history to create what my group describes as “an interactive, 4-dimensional game that takes place within the landscape of the 1930s Black Canyon site where Hoover Dam was built.” The project is funded by a grant from the National Endowment for the Humanities and is headed by lead researcher and UMassd Professor of English & Communication, Dr. Anthony Arrigo, as well as Professor Scott Ahrens from UMassD’s Art & Design, Dr. Shakhnoza Kayumova from UMassD’s STEM Education, and Dr. Michelle Turk from the Department of History at UNLV. There are also students in our team, including Matthew Cormier who is a Ph.D. Candidate in Mathematics, Mya Ramirez, who is an Undergraduate Student in Animation & Game Arts, and myself.

 

Work produced by James Ristaino for the NEH-funded, collaborative, and

interdisciplinary research project on the Hoover Dam.

§

I have spent my time on this team as a 3D artist. I was given historic images as reference and was asked to replicate them in 3D. This process consists of importing references into the workspace, selecting a basic shape to begin with(like a cube, cylinder, or sphere), and working simply for as long as possible. Meaning, working in low-detail, then adding high-detail later on. Once the model is complete, then it will need to be UV mapped, which means creating a surface mesh for the textures to be placed. The models are then brought into programs like Substance painter and materials are assigned to those UV maps to achieve the desired texture. An example of my work is the 1930’s Sixty Dozer, with 3 different texture options so that they don’t all look the same throughout the Canyon. I also worked on the Rope and Chair Hoisting system that the High-Scalers used during construction of the Dam, the Wrench that the workers used, and also the employment badge. I used a combination of materials on these models, like rust or metal, and photos to make the items look realistic, like the employment badge.

§

I have enjoyed my experience with the research team so far. I believe that this extracurricular activity has shaped my current career in the arts as well as possibly the future direction of my career in the field. I am grateful for this NEH-funded research opportunity! It is also wonderful to be guided by professors and researchers in learning environments outside the classroom context. I am particularly thankful to professors Arrigo, Ahrens, and Kayumova.

 

Research in Psychology

Self-Care Behaviors as a Mediator of Health Anxiety for Nurses during COVID-19 Pandemic

By Christopher McGuire

 

                      Chris McGuire at the Eastern Psychological 
                            Association’s Research Conference

Introduction

The COVID-19 pandemic has lead to many adverse psychological outcomes, especially in healthcare workers. For example, nurses working with COVID patients report higher symptoms of PTSD, anxiety, and insomnia (Li, 2021; Schierber-Scherr et al., 2021). Health anxiety, another negative outcome, is defined as the preoccupation or obsession with thinking an individual has a serious physiological disease when there are no apparent physical symptoms (Weck & Höfling, 2015). This can develop into a serious mental disorder that overtakes one’s thoughts and emotions if symptoms get out of control, thus interrupting their daily life. To mitigate such adverse outcomes, self-care behaviors are essential to maintain physiological health (Riegel, et al., 2009). In this study, differences in health anxiety levels will be measured in nurses who have worked with COVID-19 patients and nurses who have not, and self-care behaviors will be tested as a moderator of those two variables.

Methods

Participants

For four weeks in October and November, 2021, nurses were invited to participate in our study by taking online surveys promoted through social media and the American Association of Critical Care Nurses Participate in Research Studies webpage. A total of 271 responses were recorded, but only 148 responses were used in the analysis due to missing data. Participants were asked demographic information, including number of years worked as a nurse, age, average number of hours worked per week, and whether or not they have worked directly with patients who had contracted COVID-19.

Measures

Health Anxiety: Participants were asked to complete the Health Anxiety Questionnaire (HAQ) (Lucock & Morley 1996) to measure their levels of health anxiety. The survey consists of 21 questions asking participants about their attitudes towards their own physical health, and health symptomologies. The items can be categorized into four subscales (health worry & preoccupation, fear of illness & death, reassurance seeking behavior, and interference with life) or scored as a full scale. The HAQ uses a 4-point Likert scale (scored 0-3) ranging from “not at all or rarely” to “most of the time” to measure how often the participants feel concern, anxiety, or stress about their own physical health. The average scores were used in the current analyses, with higher scores indicating higher health anxiety.

Self-care: A self-care measure was developed by the researchers for the study to assess  15 self-care activities, including sleep, exercise, diet, stress management, and body monitoring. Items on the self-care measure were loosely based off the Self-care of Heart Failure Index (SCHFI) (Riegel, et al., 2009) which asks a variety of self-care questions using various Likert scales. Higher scores indicate an increased frequency in engaging these behaviors.

Results

Data were analyzed in two steps. The first step was to examine differences in health anxiety. Specifically, a t-test found that nurses who reported treating patients with COVID-19 had significantly higher health anxiety scores (M = 2.77, SD = 0.67) than nurses who did not (M = 2.39, SD = 0.50), t(147) = 3.04, p = .003). The second step was to examine if self-care behaviors moderated the relationship between treating patients with COVID-19 and health anxiety. We tested this using a hierarchical regression controlling for age, number of years working as a nurse, and education. The first step, which included the control variables, if they treated patients with COVID-19, and scores on the self-care scale, accounted for 21.7% of the variance, F(5, 142) = 7.88, p < .001. The second step, which included the interaction term of if they treated patients with COVID-19 and self-care, accounted for an additional 2.2% of the variance, ΔF(1, 141) = 4.07, p = .04. Overall, the model accounted for 23.9% of the variance in health anxiety, F(6, 141) = 7.83, p < .001. Follow-up analyses of the interaction found that the difference in health anxiety between nurses who treated patients with COVID-19 and those who did not decreased as self-care behaviors increased.

Discussion

Working closely with patients with COVID-19 during a national pandemic is significantly related to increased levels of health anxiety in nurses. This finding emphasizes the vulnerability of nurses working with COVID patients to adverse psychological outcomes. Self-care behaviors may be an effective way to lower these levels of health anxiety. Self-care behaviors accounted for a significant amount of variance of health anxiety in nurses that worked with COVID patients. This suggests that engaging in healthy self-care acts can help reduce feelings of health anxiety in nurses working with COVID patients. Lastly, as self-care behaviors increased, the differences in health anxiety decreased between nurses who treated COVID patients and nurses who did not. This suggests self-care behaviors are essential to maintain lower health anxiety levels for all nurses, but that they might be particularly important for nurses who treat patients with COVID-19.

The current study emphasizes the need for nurses to engage in self-care behaviors, especially those working with patients with COVID-19. Limitations of this study include the use of self-report, that the sample is not representative (e.g., geographical area, sample was overwhelmingly White and female), and that it is possible that nurses who were more affected by the COVID-19 pandemic may have been more likely to respond. Future research is needed for more in-depth knowledge of the adverse effects of health anxiety on nurses working with COVID patients.

Presentation at the Eastern Psychological Association’s research conference: A Fulfilling Experience

Walking into the Eastern Psychological Association’s research conference, I was unsure what to expect as this was my first time ever at a conference. I was walking through Times Square to my hotel in Manhattan, a city I have never been before, wondering what kind of experience I would have. Outside, the typical hustle and bustle of New York City was going on in the streets, but on the inside, a solemn sharing of knowledge was taking place. It was a very unique sight, as students, professors, and researchers from around the US met in this somewhat chaotic city to share research, ask questions, and speak with like-minded people.

I had the pleasure of listening to some great speakers and speaking with dedicated students during the two full days of the conference before my own presentation. I particularly enjoyed walking around the poster presentations and seeing what other students were researching. I was truly amazed at the number of undergraduates who were attending their first conference, like myself. Listening to keynote speakers with decades of experience was also fascinating as these researchers are at the top of their field and show me what I can become with dedication and hard work. The highlight of my conference experience was presenting. I was a bit concerned while setting up my poster, but once I started speaking to the viewers, the nerves melted away and it truly felt like having a conversation rather than a “presentation.” Overall, my first conference was a memorable experience and something I will take with me the rest of my career. I learned a lot, was amazed by the environment and amount of knowledge, and was very proud to show my project I have been working on for over a year to viewers. I thank my mentor, Dr. Brian Ayotte, my committee members, Dr. Anna Shierberl Scherr and Dr. Marni Kellogg, the Office of Undergraduate Research, and my family for their support to make this experience happen.

Research in Economics

Using the User Cost of Monetary Assets to Explain the Investment Portion of Gross Domestic Product

 

By Adam Bourgoin-Stone


Over the summer, I have been co-writing a paper with Dr. Biyan Tang on the merits of utilizing the user cost of monetary assets rather than the interest rate in economic research, specifically research into the investment part of Gross Domestic Product. The paper itself is not complete yet, and the current results may change if errors in the regression are detected.  The paper has been submitted to present in a conference hosted by the Midwest Economics Association. This project has been and continues to be an incredible opportunity for me to not only learn more about economics, but also expand my critical reading and research skills.

Gross Domestic Product is often used in economics as an indicator of general economic growth. GDP is equal to Consumption + Investment + Government Spending + Net Exports. According to the Bureau of Economic Analysis, investment has remained at between 16% and 26% since 1947. Since investment is a significant portion of GDP, it is important to understand which factors correlate with it, and which factors can promote its growth. Based on traditional economic theory, the interest rate is negatively related to the level of investment that firms are willing to make. In other words, with a higher interest rate, investment will fall assuming other economic or political conditions remain the same. However, the relationship between the interest rate and investment can be unclear. Some research in the past has found a negative relationship; some has found a positive relationship; one paper found that the correlation changes significantly based on the interest rate level at the time of adjustment. A more intuitive tool for measuring investment as a part of GDP may be the user cost of monetary assets. The user cost is measured by the opportunity cost, or the forgone interest, of holding certain liquid monetary assets (like currency or checking account balance) versus holding pure investment assets. For example, if you held $1000 in cash, the user cost of your monetary asset would be the federal interest rate that you could have earned on the money had you kept it entirely in the form of investment assets such as treasury bonds. The user cost of monetary assets can be separated into the user costs for the various monetary aggregates, such as M1, M2, M3, and M4. A general overview of the monetary aggregates is that M1 contains the most liquid assets, and that each subsequent monetary aggregate contains the previous aggregate plus less liquid assets. For example, M1 contains physical currency, demand deposits, traveler’s checks, and other checkable deposits. M2 contains everything in M1, and also savings deposits, money market securities, mutual funds, and other time deposits.

Barnett (1978) derives a user cost formula for monetary assets:

where pit is the current period user cost of the per capita real balances of monetary asset i during period t, p*t is an aggregate index of the prices of good/services and of the prices of durable goods rental during period t, Rt is the yield on per capital bond holdings during period t, and rit is the nominal yield on monetary asset i during period t. The formula demonstrates that as the benchmark interest rate rises, the forgone interest rate increases with it.

The relationships of different economic factors with investment can be described using the Ordinary Least Squares regression

PriInv = b0 + b1(IntRate) + b2(rGDP) + b3(PubInv) +b4(PriCredit) + b5(CorpTax) + b6(Income) + b7(Inflat) + b8(TreasBond) + b9(Savings)

where the dependent variable is private investment in billions of dollars, and the independent variables are the interest rate, real GDP, public investment, credit available to the private sector, the effective corporate tax rate, aggregate income, the inflation rate, the treasury bond yield rate, and the savings rate. The user cost data was organized by the user costs for the different monetary aggregates (e.g. M1, M2, M3, M4). Two regressions were used, one using the interest rate, and the other replacing the interest rate with the user cost of monetary assets for M1. The adjusted R2, which is the percent of the variance of the dependent variable that is explained by the independent variables, was compared to determine whether the user cost is a better determinant of private investment than the interest rate. Regressions were run with the user cost for each monetary aggregate, with the regression that yielded the highest adjusted R2, the user cost for M1, being compared with the interest rate regression. The t-values of the interest rate and the user cost for each monetary aggregate were used to determine the statistical significance of each variable’s correlation with gross private investment. The statistical significance of each monetary aggregate’s user cost and the interest rate is visualized in Figure 1. Clearly, the interest rate is shown to have the most statistically significant correlation with the investment, and the user cost for M1 is shown to have the most significant relationship out of all of the user costs, though it is still statistically insignificant. Figures 2 and 3 show the interest rate and the user cost of M1 over time with gross private investment, respectively. The user cost and the interest rate are shown to be almost identical in proportion.

Figure 1, t-values of the interest rate and the monetary aggregate user costs

 

Figure 2, gross private investment and the interest rate over time

 

Figure 3, gross private investment and the user cost of M1 over time

 

The coefficients of each of the variables of the regression using the interest rate are shown in Figure 4. In this regression the interest rate is found to have a positive correlation with private investment. While at first glance, this seems contrary to traditional economic theory, this is likely because we did not add a lag to the regression. The relationship is shown to be positive because when investments fall, the federal reserve lowers the interest rate to stimulate investment, and when investment rises again, the federal reserve slowly returns interest rates to their previous values. The effective corporate tax rate was also shown to have a positive correlation, when a higher tax rate would be expected to lower the funds firms have at their disposal to invest, thereby reducing private investment. Figure 5 shows the regression using the M1 user cost (as that is the user cost that had the most significant correlation with investment, and the regression using the M1 user cost yielded the highest adjusted R2). The effective corporate tax rate is shown to have a positive relationship in this regression as well. In fact, most of the variables have similar values to the regression using the interest rate, except for the treasury bond yield rate and the inflation rate.

Figure 4, regression results for the interest rate. Standard errors are below coefficient values. *** – significant at 1% level. ** – 5% level. * – 10% level

 

Figure 5, regression results for the user cost. Standard errors are below coefficient values. *** – significant at 1% level. ** – 5% level. * – 10% level

 

The adjusted R2 of the regression using the interest rate was .9905, and the adjusted R2 of the regression with the user cost was .9881. This result is not unexpected, given the fact that the user cost was found to be statistically insignificant, while the interest rate was found to be significant at the 0.1% significance level, meaning that there is only a 0.1% risk of concluding that it is significant when it isn’t.

According to these results, the interest rate is probably a better variable than the user cost for explaining the variance of investment in the US. Secondary results include the statistical insignificance of the inflation rate when explaining investment, and also the inconsistency of the treasury bond yield rate’s significance. When using the interest rate, it was found to be mostly insignificant, but when using the user cost for M1, it was found to be significant at or above the 1% level. Based on these current results, I cannot conclude that the user cost of monetary assets is a more efficient factor than the interest rate for analysis of the investment part of GDP.

I want to thank the Dean of the UMass Dartmouth College of Arts and Sciences, Dr. Pauline Entin, for the generous stipend that I was granted for my summer project.

Works Cited in Paper

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Ahmed, Afaq, and Muhammad Mubarik. “Impact of Interest Rate and Inflation on Stock Market Index: A Case of Pakistan .” Jan. 2012.

Ajide, Kazeem, and Olukemi Lawanson. “Modelling the Long Run Determinants of Domestic Private Investment in Nigeria.” Asian Social Science, vol. 8, no. 13, 2012.

Akhtar, M. A. “Effects of Interest Rates and Inflation on Aggregate Inventory Investment in the United States.” The American Economic Review, vol. 73, no. 3, June 1983, pp. 319–328.

Albu, Lucian Liviu. “TRENDS IN THE INTEREST RATE–INVESTMENT– GDP GROWTH RELATIONSHIP .” Romanian Journal of Economic Forecasting, vol. 3, Jan. 2006, pp. 5–13.

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Awan, Rehmat, et al. “Rate of Interest, Financial Liberalization & Domestic Savings Behavior in Pakistan.” International Journal of Economics and Finance, vol. 2, no. 4, 2010.

Bagci, Erdem, and Emre Erguven. “Relations between Interest Rate, Inflation, Growth AndInvestment in Turkey, 2002-2015 .” 2016.

Bitros, Georgios, and M. Ishaq Nadiri. “Elasticities of Business Investment in the U.S. and Their Policy Implications : A Disaggregate Approach to Modeling and Estimation .” July 2017.

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Heim, John. “THE INVESTMENT FUNCTION: DETERMINANTS OF DEMAND FOR INVESTMENT GOODS.” Jan. 2008.

Kosma, Olga. “Determinants of Investment Activity: the Case of Greece.” 2015.

Maccini, Louis, et al. “The Interest Rate, Learning, and Inventory Investments.” American Economic Review, vol. 94, no. 5, Dec. 2004, pp. 1303–1327.

Magableh, Sohail, and Sameh Ajlouni. “Determinants of Private Investment in Jordan: An ARDL Bounds Testing Approach.” Dirasat, vol. 43, no. 1, Jan. 2016.

Mueller, Glenn, and Keith Pauley. “The Effect of Interest-Rate Movements on Real Estate Investment Trusts.” Journal of Real Estate Research, vol. 10, no. 3, Feb. 1995, pp. 319–326.

Munir, Rahila, et al. “Investment, Savings, Interest Rate and Bank Credit to the Private Sector Nexus in Pakistan.” International Journal of Marketing Studies, vol. 2, no. 1, 2010.

Noman, Muhammad. “Rate of Interest and Its Impact on Investment to the Extent of Pakistan .” Sept. 2018.

Obamuyi, Tomola, and Sola Olorunfemi. “Financial Reforms, Interest Rate Behaviour and Economic Growth in Nigeria.” Journal of Applied Finance & Banking, vol. 1, no. 4, 2011, pp. 39–55.

Olweny, Tobias. “The Effect of Monetary Policy on Private Sector Investment in Kenya.” Apr. 2012.

Opreana, Alin. “THE LONG-TERM DETERMINANTS OF INVESTMENT: A DYNAMIC APPROACH FOR THE FUTURE ECONOMIC POLICIES.” Studies in Business and Economics, vol. 5, no. 3, Jan. 2010, pp. 227–237.

Oriavwote, Victor, and Dickson Oyovwi. “Interest Rate and Investment Decision in Nigeria: A Cointegration Approach.” American Journal of Business and Management, Mar. 2014.

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Peter, Audu, and Oluwoyo Temidayo. “Testing the Validity of McKinnon-Shaw Hypothesis: Empirical Evidence from Nigeria.” Asian Journal of Economics, Business and Accounting, vol. 2, no. 2, 2017, pp. 1–24.

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Research in Psychology

Behavioral Expression of Anger in Preschoolers

 

by Sophia Baxendale

Over the summer and into the fall, I worked with Dr. Locke-Arkerson to learn to code facial, bodily, and vocal expressions of context-appropriate and inappropriate anger in preschoolers. I was awarded a summer research award for 2020 by the Office of Undergraduate Research, funded by the College of Arts and Sciences. The opportunity to work one-on-one with Dr. Locke-Arkerson has provided me with an excellent opportunity to learn more about behavioral data and research with children. Learning how to code and working with Dr. Arkerson has fostered confidence in my ability to learn different aspects of research, and I look forward to continuing to code this sample to learn more about emotional expression in different contexts.

Background

Anger regulation involves the modification of emotional responses to situational changes (Thompson, 1994). Until now, research on anger expression has been limited to identifying children who show more anger than others in appropriate contexts (e.g., delay of gratification, blocked goals; Brooker et al., 2014; Cole et al., 2011; Gilliom et al., 2002). However, Dr. Locke-Arkerson has also measured anger during threatening and positive situations (context-inappropriate “CI anger”) (Locke et al., 2009; Locke et al., 2015). CI anger has been found to increase the risk of externalizing behavior and peer rejection (Locke & Lang, 2016; Locke et al., 2017; Locke et al., 2015). CI anger uniquely predicts these outcomes above and beyond CA anger. It also differs from the way anger has historically been studied, as its correlation with CA anger is only moderate. Dr. Locke-Arkerson’s research utilizes a novel approach to understanding emotional responses by studying them in distinct contexts to determine which children are unable to regulate anger responses in adaptive and acceptable ways.

The collection of behavioral data in research conducted with children has use beyond what is possible to collect from questionnaires. In order to translate collected behavioral data into ratings, a standardized and objective system of observation must be in place. The individuals rating of behaviors (“coding”) must reach a level of agreement, or interrater reliability. Once reliable, the individual coders can rate behaviors independently and these ratings can be used quantitatively for statistical analysis.

The aim of this project was to learn and become reliable in coding facial, bodily, and vocal expressions of context-appropriate and inappropriate anger in preschoolers. This project met the goal of obtaining acceptable interrater reliability for assessing the level of facial, bodily, and vocal expressions of anger during emotion-eliciting episodes in preschool-age children. CI anger in prior studies focused on facial expressions of anger in response to affective pictures, slides, and videos (Locke et al., 2015), making the data coded in this project unique.

Method

Participants

Participants included 69 four-to-five-year-old children from preschools local to UMass Dartmouth.

Procedures

Data used for this project was collected for a larger study exploring emotional and biological measures associated with behavior problems in children. For this project, I was trained on how to code expressions of anger during an anger-eliciting episode. Training on the coding of behavioral data required regular remote meetings and practice sessions with the master coder, Dr. Locke-Arkerson. Prior to training, Dr. Locke-Arkerson developed our training manual for the anger episode. I also filled out the coding sheets with the begin and end times of the episode for each individual subject. Dr. Locke-Arkerson reviewed the episode-specific manual and the System for Identifying Affect Expressions by Holistic Judgments coding system (AFFEX; Izard, Dougherty, & Hembree, 1989) manual with a graduate student, Samantha Clark, and myself. We were then assigned practice cases to code independently, and to discuss together. Samantha and I met several times to compare our codes, and then brought our discrepancies to Dr. Locke-

Arkerson. We reviewed the discrepancies as a group and worked together to determine our sensitivity level to minute expressions of anger. This training process took approximately 127 hours, which was followed by reliability coding, in which I was assigned cases to code independently for all four variables. My codes were compared to the Master Codes created by Dr. Locke-Arkerson and were reviewed to understand where we disagreed. Through the training and reliability process, Dr. Locke-Arkerson and I were able to completely code 24 participants and partially code 17 more for the anger-eliciting episode.

Measures

Context-Appropriate and Inappropriate Anger. Children were videotaped during episodes of the Laboratory Assessment Battery (LabTAB; Goldsmith et al., 1999), which were used to assess appropriate and inappropriate anger in distinct contexts (positive, threatening, frustrating).

Anger episode. The anger episode that was used for reliability training was the I’m Not Sharing game. During the I’m Not Sharing game, the experimenter shares candy with the child and will give themselves more candy than the child. In the end, the experimenter gives the child two pieces of candy.

Behavioral scoring. Coders rated anger facial, bodily, and vocal expressions during the episode using the LabTAB and Affex coding systems.

Pictured: A child playing I’m Not Sharing game.

Results

Dr. Locke-Arkerson assigned me reliability coding for the different variables after an intensive training period. Agreement between my codes and the master codes were determined through a calculation of hits and misses for each variable: presence for vocalizations and bodily resistance, intensity for bodily and facial expressions of anger. The minimum Cohen’s Kappa score to be reliable was .7, or approximately 90% agreement with the Master codes. I was assigned 10 cases for each variable until I was reliable according to the calculated Cohen’s Kappa. I required 10 cases to reach a Cohen’s Kappa of .7 for bodily resistance, or instances where the child attempted to stop the episode. I required 21 cases to reach a Cohen’s Kappa of .7 for vocalizations of anger. I required 20 cases to reach a Cohen’s Kappa of .74 for bodily expressions of anger. I required 20 cases to reach a Cohen’s Kappa of .73 for facial expressions of anger. This means that I will be able to code reliably for the rest of the episode and other episodes moving forward to produce qualitative data that can be used quantitatively for data analysis to address study hypotheses. The coding completed through training and reliability amounted to around 60% of the total data set being at least partially coded for the I’m Not Sharing episode.

Discussion

Over the course of this project, I accomplished my goal of becoming a reliable coder and leading to the near completion of coding all participants for the I’m Not Sharing anger-eliciting episode. With Dr. Locke-Arkerson’s commitment to this project and my training, I was able to learn how to code and become reliable. Given that we were unable to meet in person, my training required modifications to be the most effective for a remote modality. This meant meeting with Dr. Locke-Arkerson several times a week for up to three hours at a time to make sure that we were identifying the same behaviors as anger. The process of learning such a skill was exciting, as it enhanced my working relationship with Dr. Locke-Arkerson and allowed me to see a side of research that I had misunderstood in an academic setting previously. I did not understand the value of behavioral data, as I believed it to be too subjective. After going through such an intense and rigorous training process, I now have a better understanding of how behavioral data can be quantified. It was also exciting to be able to identify slight tells of anger in children, something I was not able to pick up explicitly when I helped administer the episodes prior to the pandemic. While I may have been able to sense frustration, I was not able to identify specific incidences of anger prior to watching the episode as a trained coder with an understanding of slight expressions of anger, especially in the body and face.

I anticipate being able to complete coding of our sample for I’m Not Sharing soon, to be followed by positive and non-social fear episodes. The positive episodes that may be coded include the Surprise! and Popping Bubbles episodes. The non-social fear episode that will be coded is the Scary Mask episode. I am excited to see how our sample expresses anger in contexts that would not be considered appropriate, allowing for more questions to be asked. The completion of coding will allow Dr. Locke-Arkerson and her lab to use the data to enhance the literature on child behavioral and emotional expression, as well as assisting findings in Dr. Locke-Arkerson’s ongoing study. This data will become a resource for myself and future research assistants to use for poster presentations and manuscripts. Specific analyses that this data set can be used for include assessment of the association between behavioral measures and a parent-report measure of CI anger (Locke & Lang, 2016). This data set may also be used to supplement an ongoing manuscript that Dr. Locke-Arkerson, Samantha Clark, and I are working on regarding children who withdraw.

Learning how to code and becoming reliable is a skill has been invaluable to my understanding of hands-on data processing and I am incredibly grateful for the opportunity to build on my research experience. It has been rewarding to gain perspective from both data collection and coding that I have had the opportunity to be a part of in Dr. Locke-Arkerson’s Child Emotion Lab. Thank you to the Office of Undergraduate Research and the College of Arts and Sciences, especially Dean Entin for expressing interest in this project and awarding me the funds to pursue it. The time invested in this project has and will continue to propel progress in our lab and the research program. Thank you to Dr. Locke-Arkerson for committing to this project and taking the time to strengthen my confidence in attention to detail.

References

Arsenio, W., Cooperman, S., & Lover, Anthony. (2000). Affective predictors of preschoolers’ aggression and peer acceptance: Direct and indirect effects. Developmental Psychology. 36. 438-48. doi: 10.1037//0012-1649.36.4.438.

Brooker, R. J., Buss, K. A., Lemery-Chalfant, K., Aksan, N., Davidson, R. J., & Goldsmith, H. H. (2014). Profiles of observed infant anger predict preschool behavior problems: Moderation by life stress. Developmental Psychology, 50(10), 2343-2352.

Cole, P. M., Tan, P. Z., Hall, S. E., Zhang, Y., Crnic, K. A., Blair, C. B., & Li, R. (2011). Developmental changes in anger expression and attention focus: Learning to wait. Developmental Psychology, 47(4), 1078–1089. doi: 10.1037/a0023813.

Cole, P.M., Martin, S.E. and Dennis, T.A. (2004), Emotion regulation as a scientific construct: Methodological challenges and directions for child development research. Child Development, 75: 317-333. doi:10.1111/j.1467-8624.2004.00673.x.

Cole, P. M., Michel, M. K., & Teti, L. O. (1994). The development of emotion regulation and dysregulation: A clinical perspective. Monographs of the Society for Research in Child Development, 59(2-3), 73–100, 250–283. doi: 10.2307/1166139.

Gilliom, M., Shaw, D. S., Beck, J. E., Schonberg, M. A., & Lukon, J. L. (2002). Anger regulation in disadvantaged preschool boys: Strategies, antecedents, and the development of self-control. Developmental Psychology, 38(2), 222–235. doi: 10.1037/0012-1649.38.2.222.

Goldsmith, H. H., Reilly, J., Lemery, K. S., Longley, S., & Prescott, A. (1999). The Laboratory Temperament Assessment Battery (Lab-TAB): Preschool Version 1.0. Technical manual. Madison: University of Wisconsin, Department of Psychology.

Izard, C. E., Dougherty, L. M., & Hembree, E. A. (1989). A system for identifying affect expressions by holistic judgments (Affex) (rev. ed.). Newark: University of Delaware, University Media Services.

Locke, R. L., Davidson, R. J., Kalin, N. H., & Goldsmith, H. H. (2009). Children’s context inappropriate anger and salivary cortisol, Developmental Psychology, 45(5), 1284-1297. doi: 10.1037/a0015975.

Locke, R. L., & Lang, N. J. (2016). Emotion knowledge and attentional differences in preschoolers showing context-inappropriate anger. Perceptual and Motor Skills, 123(1), 46-63. doi: 10.1177/0031512516658473.

Locke, R. L., Lemery-Chalfant, K., Brooker, R., Davidson, R. J., & Goldsmith, H. H. (2017, April). Physiological and behavioral outcomes associated with anger dysregulation. Paper presented at the Biennial Meeting of the Society for Research in Child Development, Austin, TX.

Locke, R. L., Miller, A. L., Seifer, R., & Heinze, J. E. (2015). Context-inappropriate anger, emotion knowledge deficits, and negative social experiences in preschool. Developmental Psychology, 51(10), 1450-1463. doi: 10.1037/a0039528.

Thompson, R.A. (1994). Emotion regulation: A theme in search of definition. Monographs of Society for Research of Child Development. 59. 25-52. doi: 10.1111/j.1540- 5834.1994.tb01276.x.

Research in Biology

Anthropogenic Road Noise Effects on Small Mammals

 

by Alyssa Giordano

Over the summer I worked on an experiment that investigated the effects of chronic road (anthropogenic) noise on free-living small mammals. I was a recipient of the 2020 summer research award from the Office of Undergraduate Research (OUR), which helped me greatly to pursue this research under the supervision of Dr. Michael Sheriff. I have always felt a strong connection to ecology and conservation biology, and this project has captivated me and rooted me further to this field, propelling me to pursue this kind of research in my career. This opportunity has helped me in deciding to continue my education to earn a master’s degree. I hope to pursue further projects related to anthropogenic effects, with implications to ecology and wildlife management.

Background:

Predators can alter prey populations through direct killing and consumption, but also through non-consumptive, risk effects (Peacor et al. 2020; Sheriff et al. 2020). Such effects include changes to behavior, physiology, fecundity, and survival. Small mammals for example are known to respond to predation risk by changing their habitat use, activity patterns, and foraging behavior (Lima 1998).

Chronic traffic (anthropogenic) noise has shown dramatic increases over the last few decades with the expansion of resources and transportation (Shannon et al. 2016). For example, the United States’ population increased by about one third and traffic nearly tripled between 1970 and 2007 (Barber et. al. 2010). Road noise can affect prey’s ability to perceive predation risk cues and, thus, alter their risk responses which can be critical to survival (Francis and Barber 2013; Shannon et al. 2016). Road noise is hypothesized to alter prey responses to predation risk in three distinct ways, i) mask auditory cues of predation resulting in greater antipredator responses, as prey have more difficulty detecting their predators and find the area riskier (Barber et. al. 2010), ii) mask and distract prey due to the excess of auditory signals resulting in a reduction in antipredator responses, as prey do not perceive the area as risky given they cannot detect their predators (Blumstein 2014, Chan et. al. 2010), or iii) be perceived as a threat itself, with increased antipredator responses above that with which prey respond to risk alone (Shannon et. al. 2016, Tyack et. al. 2011). Within this research I tested each of these hypotheses by examining the food intake and foraging behavior of free-living deer mice concurrently exposed to both road noise and predation risk. I predicted that if road noise resulted in an increase in antipredator behavior, small mammals would find the area to be riskier and forage less. If road noise resulted in a decrease in antipredator behavior, small mammals would be distracted by the excess sound and forage more. If road noise resulted in an increase in antipredator behavior when not concurrently treated with predation risk, small mammals would find the road noise itself risky and forage less.

Methods:

To conduct my experiment, I used audio playbacks to manipulate the acoustic environment of free-living deer mice and other small mammals. My audio treatments consisted of non-predatory control, avian predators, road noise, and road noise + avian predators. Each treatment was played for three days, with a two day buffer between treatments to avoid contamination of effects from one treatment to the next. To measure foraging activity, I set up giving-up density (GUD) trays. GUDs are based on the marginal value theorem (Charnov 1976), such that the return of a foraging patch diminishes and the cost increases the more an animal forages, ultimately the animals ‘give up’ and move on (Brown et. al. 1999). The point at which an animal gives up has been shown to be impacted by predation risk (Brown 1988). Plastic foraging trays were filled with 2.5g of millet seed and 2 cups of sand (figure 1). Six trays were placed into the field for 2 consecutive 24 periods beginning at 0700h on days 2 and 3 of a treatment. Motion detecting cameras (purchased as part of the OUR grant) were deployed at 3 of the GUDs to measure foraging behavior. Each treatment was replicated three times and the total duration of the experiment occurred from July 1st to September 13th, 2020.

I analyzed the foraging data using 2-way ANOVAs and a tukey test with treatment and night as fixed effects (RStudio Desktop 1.3.1093).

Results:

I found that there was a significant effect of treatment and of night (Table 1) on the amount of food eaten by small mammals (Fig. 2). When exposed to predation risk small mammals decreased the amount of food eaten, when exposed to predation risk and road noise small mammals ate a similar amount, and when exposed to road noise alone small mammals slightly increased the amount that they ate compared to the control treatment.

I also found that small mammals ate more on night 2 compared with night 1 (Fig. 2).

Discussion:

This data supports the hypothesis that road noise will cause prey to reduce their antipredator responses to predation risk. (Chan et al. 2010) found something similar, that during noise exposure Caribbean hermit crabs allowed simulated predators to get closer, suggesting they had an impaired ability to respond. This may occur because prey have a harder time perceiving risk cues when also exposed to noise, creating a clouded soundscape. This will have consequences to prey by exposing them to predators more, as the prey will not engage in antipredator responses as much or as fast.

I still need to analyze the behavioral data from the motion detecting cameras with footage taken over 2.5 months. The video footage will be analyzed for the number of visits to the GUDs, the time spent during each visit, and the time spent being vigilant. This portion of the project will delve deeper into the specific effects on animal risk response when exposed to chronic road noise and predation. I have determined the general effect of chronic road noise, but it will be very interesting to see their true behavior, and if it shows anything that the preliminary foraging data cannot.

A special thanks to the Office of Undergraduate research and the College of Arts and Sciences for providing me with funding for my project. Though the analysis is not yet fully complete, the funding has given me an invaluable opportunity to explore an important wildlife conservation topic in depth. Finally, I’d like to acknowledge and thank Dr. Michael Sheriff for the support and guidance throughout my project.

References:

Barber, J. R., Crooks, K. R., & Fristrup, K. M. (2010). The costs of chronic noise exposure for terrestrial organisms. Trends in ecology & evolution, 25(3), 180-189.

Blumstein, D. T. (2014). Attention, habituation, and antipredator behaviour: implications for urban birds. Avian urban ecology, 41-53.

Brown, J.S., Laundre, J.W., & Gurung, M. 1999. The ecology of fear: optimal foraging, game theory, and trophic interactions. Journal of Mammalogy 80: 385-399.

Brown, J.S. 1988. Patch use as an indicator of habitat preference, predation risk, and competition. Behavioral Ecology and Sociobiology 22: 37-47.

Chan, A. A. Y. H., Giraldo-Perez, P., Smith, S., & Blumstein, D. T. (2010). Anthropogenic noise affects risk assessment and attention: the distracted prey hypothesis. Biology letters, 6(4), 458-461.

Charnov, E. L. (1976). Optimal foraging, the marginal value theorem.

Francis, C. D., & Barber, J. R. (2013). A framework for understanding noise impacts on wildlife: an urgent conservation priority. Frontiers in Ecology and the Environment,11(6), 305-313.

Lima, S.L. 1998. Nonlethal effects in the ecology of predator-prey interactions. What are the ecological effects of anti-predator decision-making? BioScience 48: 25-34.

Peacor, S. D., Barton, B. T., Kimbro, D. L., Sih, A., & Sheriff, M. J. (2020). A framework and standardized terminology to facilitate the study of predation‐risk effects. Ecology, e03152.

Shannon, G., Crooks, K. R., Wittemyer, G., Fristrup, K. M., & Angeloni, L. M. (2016). Road noise causes earlier predator detection and flight response in a free-ranging mammal. Behavioral Ecology, 27(5), 1370-1375.

Sheriff, M. J., Peacor, S. D., Hawlena, D., & Thaker, M. (2020). Non‐consumptive predator effects on prey population size: A dearth of evidence. Journal of Animal Ecology.

Tyack, P. L., Zimmer, W. M., Moretti, D., Southall, B. L., Claridge, D. E., Durban, J. W., … & McCarthy, E. (2011). Beaked whales respond to simulated and actual navy sonar. PloS one, 6(3).

Research in Chemistry and Biochemistry

Neuronal Protection Effects of Blueberries through Inhibition of Key Enzymes involved in the Neurogenerative Diseases

 

By Chelsea Spitz

This past summer, I was awarded a grant from the Office of Undergraduate Research (OUR) to conduct research in the Chemistry Department under the guidance of Dr. Shuowei Cai. The purpose of this research is to study the neuronal protection effects of blueberries against neurodegenerative diseases and develop the extraction method for blueberries. I also planned on identifying active compounds in blueberries and develop a LC-MS based method to fingerprint the blueberry extract from other extraction methods. Unfortunately, due to the ongoing pandemic, I could not get access to LC-MS system, therefore, my research is mainly focusing on development of extraction method and study the neuronal protection effects of blueberries through inhibition of key enzymes involved in the neurodegenerative disease, including the inhibition kinetics, to understand the mechanism of the neuronal protections of blueberries.

Alzheimer’s disease (AD), the most common form of dementia, is a neurodegenerative disease affecting the structural integrity of the brain. Individuals suffering from AD undergo both steady memory loss and significant cognitive decline as a result of the progressive neuronal damages leading to the death of neurons in brain. AD accounts for 60 to 80 percent of dementia cases, while vascular dementia, due to microscopic bleeding and blood vessel blockage in the brain, is the second most common cause of dementia (Alzheimer’s Association, Alz.org). It is estimated that one in 10 Americans over 65 years of age is currently living with symptomatic AD, and worldwide, 50 million people live with symptomatic AD. AD puts a huge burden on both caregivers and the health system. In 2018, the direct costs to American society for caring of those with AD totaled $277 billion, and it is projected to over $1 trillion by 2050 (Alz.org). Yet, there is no cure for AD and only a handful of drugs have been approved by FDA to manage the symptoms that includes cholinesterase inhibitors and N-methyl-D-aspartate receptor (NMDA) receptor antagonist (i.e. memantine). There is even no treatment that can slow down the progresses of the disease. This may be partly due to the lack of knowledge of the mechanism of AD.

Based on the differences seen in AD’s brains, several potential causes have been hypothesized: deficits in the cholinergic transmission; beta-amyloid plagues (Aβ); tau tangles; oxidative damage and mitochondrial dysfunction; neuronal inflammation; synapse loss; vascular changes; endosomal abnormalities, among others. Several of those hypotheses have been found to be connected to each other, and collectively, they lead to the neuron death. For example, acetylcholinesterase (AChE) is a critical enzyme to regulate the level of the neurotransmitter, acetylcholine. Both Aβ and abnormally hyperphosphorylated tau (p-tau) can increase AChE expression. The increased AChE further influences PS1 and tau-protein kinase GSK-3β. GSk-3β induces hyperphosphorylated tau (P-tau), while PS1 affects the APP processing and Aβ production. Inhibition of AChE not only can rescue the deficit of cholinergic transmissions, but also can potentially reduce Aβ and P-tau.

Tyrosinase is a key enzyme in the biosynthesis of melanin. It catalyzes two reactions: the hydroxylation of tyrosine to L-DOPA and the subsequent oxidation of L-DOPA to dopaquinone. This enzyme may also oxidize dopamine to form melanin pigments through the formation of dopamine quinone, a reaction results in the formation of highly reactive oxygen or nitrogen species (ROS) capable of inducing neuronal cell death. Oxidation stress links to both inflammation and endosomal abnormalities, which hold key for neurodegenerative diseases, including AD.

Our research, therefore, is focusing on examination of neuronal protection effects of blueberries through their inhibition of AChE and tyrosinase. Most phytochemicals are extracted from plants using methanol-based solvent. Residual methanol is highly toxic for human consumption. To explore a safer solvent for extraction of phytochemicals from blueberries, we investigate using ethanol as the extraction solvent. Over the course of the summer, we extract the polar components from blueberries using three different types of solvent system: ethanol alone; methanol alone, and methanol/acetone/water/formic acid (40/40/19/1). Our lab has been used the methanol/acetone/water/formic acid extraction system for extraction of blueberries, and our aim is to compare the biological activities of the blueberry extract using ethanol with those with methanol-based extraction. The activity of AChE was examined using the Ellman method, the tyrosinase activity is determined using L-DOPA as the substrate and monitored the enzymatic product at 490 nm. Both assays were carried out using 96-well microplate, and each sample was run triplicate. To further study the mechanism of inhibition on tyrosinase, we carried out the inhibition kinetics with the blueberry extract from ethanol. The kinetics of tyrosinase was measured every 20 s in 3 min to obtain the initial velocity rate. The contraction of blueberry extract used for inhibition kinetic measurement was 0.25 mg/ml and 0.15 mg/ml.

As shown in Figures 1,2 and 3, the extracts from all three solvent systems showed strong inhibition on AChE and tyrosinase. The extract from methanol/acetone/water/formic acid solvent showed the strongest inhibition on both enzymes. The USDA solvent mixture inhibited the enzymes approximately double that of the other two solvents while the USDA MDS and USDA EDS extracts inhibited relatively close to one another. The methanol-based extract however was still slightly stronger than the ethanol-based extract but overall, they were relatively the same. The IC50s show that the USDA Solv mixture is a much stronger inhibitor than the other two solvents because it requires a lower concentration of the extract to inhibit 50% of the enzyme.

Table 1: IC50 Values For Tyrosinase and AChE

Solvent Mix MDS EDS
Tyrosinase 0.17 mg/mL 1.66 mg/mL 1.14 mg/mL
AChE 0.72 mg/mL 3.48 mg/mL 6.89 mg/mL

 

While blueberry extract from ethanol showed less potent as that from methanol-based solvent, it still showed strong inhibition on two key enzymes that related to neurodegenerative diseases. Here, we demonstrated that ethanol can be a safe alternative to extract the bioactive phytochemicals. We further examined the inhibition kinetics of blueberry extract from ethanol to understand the inhibition mechanism on tyrosinase. As shown in Figure 4, the blueberry extract inhibits tyrosinase in a non-competitive manner (mixed mode inhibition). The inhibition constant Ki and Ki’ are 0.056 mg/ml and 0.82 mg/ml, respectively (Table 2). This suggested that the compounds in blueberry both directly interact with the active site of tyrosinase the substrate-enzyme complex.

Table 2: Inhibition Constant of Blueberry Extract

KI (mg/ml) KI’ (mg/ml)
0.25 mg/ml 0.060 0.079
0.15 mg/ml 0.051 0.085
Average 0.056 (0.006)* 0.082 (0.005)

*: the figure in parenthesis is the standard deviation from the two concentrations of blueberry extract

 

Future Plan:

The plan to continue this project consists of continuing to perform more kinetics assays using USDA MDS extract and to try and see if the data is reproducible. We also plan to work on modeling and studying the structure of the enzyme more closely as well as the compounds found in the extracts from the LC-MS data. Once we gain the access to LC-MS instrument, we will identify the compounds in the ethanol extract, and compare with those from methanol-based extracts. We will further be using NMR to confirm the compounds identified from LC-MS.

The research grant I received from the Office of Undergraduate Research allowed me to learn new skills in the lab such as the enzyme kinetics assays as well as help me find my footing for my research goals. I would like to thank my research advisor Dr. Shuowei Cai for guiding me along the way. As well as the Dean to the College of Arts and Sciences, Dean Entin, and the Office of Undergraduate Research for funding my research this summer.

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