The authors looked at the ability to grow S. platensis on a larger scale with reduced cost given that it is currently quite expensive to grow, but poses as an important food source in the future.
Read More...Heterotrophic culture of Spirulina platensis improved its growth and the study of its nutritional effect
The authors looked at the ability to grow S. platensis on a larger scale with reduced cost given that it is currently quite expensive to grow, but poses as an important food source in the future.
Read More...Motivation’s impact on high-level high school students’ ability to balance academic and athletic stress
The authors looked at the relation between stress and motivation in high school students with 4+ AP classes that also played a varsity sport. No distinct correlation was observed, however, results indicated that there are other factors at play that influence both stress and motivation.
Read More...The effect of neuroinflammation and oxidative stress on the recovery time of seizures
Neuroinflammation and oxidative stress are both known to play a role in the occurrence and severity of seizures. This study tested effects of oxidative stress from seizures by evaluating the longevity, egg-laying, and electroshock resilience of C. elegans. Results revealed that oxidative stress and neuroinflammation diminish longevity and reproductivity while also increasing recovery time after seizures in C. elegans. This research can help lead to future studies and may also lead to finding new therapeutics for epilepsy.
Read More...Analysis of Milorganite’s ability to sustain growth of Ocimum basilicum in simulated Martian soil
The authors test whether basil can grow in a simulated Martian soil improved with a waste-based fertilizer called Milorganite.
Read More...A Crossover Study Comparing the Effect of a Processed vs. Unprocessed Diet on the Spatial Learning Ability of Zebrafish
The authors compared the short-term effects of processed versus unprocessed food on spatial learning and survival in zebrafish, given the large public concern regarding processed foods. By randomly assigning zebrafish to a diet of brine shrimp flakes (processed) or live brine shrimp (unprocessed), the authors show while there is no immediate effect on a fish's decision process between the two diets, there are significant correlations between improved learning and stress response with the unprocessed diet.
Read More...Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset
Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.
Read More...The presence of Wolbachia in Brood X cicadas
Here, seeking to understand a possible cause of the declining popluations of Brood X cicadas in Ohio and Indiana, the authors investigated the presence of Wolbachia, an inherited bacterial symbiont that lives in the reproductive cells of approximately 60% of insect species in these cicadas. Following their screening of one-hundred 17-year periodical cicadas, they only identified the presence of Wolbachia infection in less than 2%, suggesting that while Wolbachia can infect cicadas it appears uncommon in the Brood X cicadas they surveyed.
Read More...A machine learning approach for abstraction and reasoning problems without large amounts of data
While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.
Read More...The Effect of Bead Shape and Texture on the Energy Loss Characteristics in a Rotating Capsule
Industrial process are designed to optimize speed, energy use and quality. Some steps involve the translation of product-filled barrels, how far and fast this happens depends on the properties of the product within. This article investigates such properties on a mini-scale, where the roll of bead size, texture and material on the distance travelled by a cylindrical capsule is investigated.
Read More...What Can You See in the Dark? The Effects of Contrast, Light, and Age on Contrast Sensitivity in Low Light
Many of us take our vision for granted, but rarely do we measure how well we can see. In this study, the authors investigate the ability of people of different ages to read progressively fainter letters in dark light. They find that the ability to see in dim light drops drastically after age 30. The ability to read fainter letters worsens after age 30 as well. These findings should help inform lighting decisions everywhere from restaurants to road signs.
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