Behavioral & Social Sciences

Layla Sisca

This experiment will focus on whether higher or lower temperatures are more beneficial for sleep quality. This will be determined by drosophila melanogaster and then will be related back to humans, finding a solution for sleep amnesia and sleep difficulties. This experiment will obtain two vials and around five drosophila melanogaster with be in each. One vial will be placed in a climate around 85 degrees and another vial in a temperature around 65 degrees. I would then put cameras on each one and observe for three days. The three days of film will be watched and then determined if the flies slept more in the higher or lower temperature. The drosophila melanogaster sleep quality will be determined by at least five minutes of no movement. After observing which flies slept more, the data collected will then be related it to humans, determining whether higher or lower temperatures are better for sleep quality.

Alina Mitev

60% of greenhouse gas emissions come from daily household activities directly and indirectly. Although most are aware that climate change is a serious crisis, very few change their actions. Some scientists propose that the education people receive is not accurate and targeted enough to have the knowledge necessary to actually target behavior change. Even then, education has also proved to be insufficient. There have been many models proposed to predict intention to implement climate change mitigation behavior. The Protection Motivation Theory is unique in the way that it was originally proposed to increase motivation to institute healthy personal habits (like putting on sunscreen), but has found to also work in the context of climate change mitigation. Yet, it fails to take into account an important element in instigating actual behavior change - habit. Protection Motivation Theory proposes that appraisal of threat and appraisal of efficacy of behavior change will increase behavior change. Habit interventions will target the automic reactions cued by specific environments, such as goal setting, and collective accountability. Combining both types of interventions might prove more effective than simply using Protection Motivation Theory Interventions.

Erin Byrne

Artificial intelligence-generated audio, images, and video synthesis (known as deep fakes) that were previously exclusive to advanced special effects technology, are becoming increasingly accessible every day. Recent studies indicate that A.I. faces are now not only indistinguishable from human faces, but in some cases perceived as more realistic, a phenomenon called hyperrealism. General Adversarial Networks (GANs) are popular deep learning architectures that pit two artificial neural networks (a generator and discriminator) against each other. Starting with random pixels, these generators iteratively learn to create artificial faces until they are indistinguishable from the human ones of their training image data set. This study aims to determine whether human participants can distinguish A.I. faces from real human faces. Additionally, participants will participate in multiple trials with new stimuli to observe if their scores improve after being presented with their results from the previous trial.