Here, seeking to better understand the effects of altered day-night cycles, the authors considered the effects of an altered photoperiod on Daphnia magna. By tracking possible stress responses, including mean heart rate, brood size, and male-to-female ratio they found that a shorter photoperiod resulted in altered mean heart rates and brood size. The authors suggest that based on these observations, it is important to consider the effects of photoperiod alterations and the stress responses of other organisms.
Nolt and Elwonger examine how different types of music impact our emotional and physical states. They found that music can influence a subject's emotional state, with sad music inspiring sadness and exciting music bringing excitement. They were not able to find a clear relationship between heart rate and music type. Music's effect on emotional state can be useful when designing novel therapies for emotional and mental disorders.
Understanding how bacteria respond to other bacteria could facilitate their ability to initiate and maintain their infectiousness. The phenomenon by which bacteria signal to each other via chemical signals is called quorum sensing, which could be targeted to deter bacterial infection in some cases if better understood. In this article, the authors study how a bacterium called V. fischeri uses quorum sensing to change bioluminescence, an easy readout that facilitates studying quorum sensing in this strain.
The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.
There are complex interactions between water and outside forces such as magnetic fields. This study aims to examine the effects of magnetic forces on the flow rate of water. The alteration of flow rate by magnets could have exciting applications in many fields.
In this article the authors looked at different attributes of apps within the Google Play store to determine how those may impact the overall app rating out of five stars. They found that review count, amount of storage needed and when the app was last updated to be the most influential factors on an app's rating.
Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.
This article describes the relationship between socioeconomic factors and the extent of how the COVID-19 Pandemic affected communities. Factors such as infection rate, vaccination rate, and economic status were all evaluated within the context of this article.
In this study, the authors examine how knowledge, lack of knowledge, and deception affect the rate of perceived exertion and actual performance of teenagers in sprint training. Their results suggest that fully informing athletes about workout duration yields the fastest and most consistent speeds.
The consumption of sugar substitute non-nutritive sweeteners (NNS) has dramatically increased in recent years. Despite being advertised as a healthy alternative, NNS have been linked to adverse effects on the body, such as neurodegenerative diseases (NDs). In NDs, neural stem cell function is impaired, which inhibits neuron regeneration. The purpose of this study was to determine if the NNS acesulfame potassium (Ace-K) and neotame affect planaria neuron regeneration rates. Since human neurons may regenerate, planaria, organisms with extensive regenerative capabilities due to stem cells called neoblasts, were used as the model organism. The heads of planaria exposed to either a control or non-toxic concentrations of NNS were amputated. The posterior regions of the planaria were observed every 24 hours to see the following regeneration stages: (1) wound healing, (2) blastema development, (3) growth, and (4) differentiation. The authors hypothesized that exposure to the NNS would slow planaria regeneration rates. The time it took for the planaria in the Ace-K group and the neotame group to reach the second, third, and fourth regeneration stage was significantly greater than that of the control. The results of this study indicated that exposure to the NNS significantly slowed regeneration rates in planaria. This suggests that the NNS may adversely impact neoblast proliferation rates in planaria, implying that it could impair neural stem cell proliferation in humans, which plays a role in NDs. This study may provide insight into the connection between NNS, human neuron regeneration, and NDs.
