![A colorimetric investigation of copper(II) solutions](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBdHNPIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--be4551a273fcc9a601ac541683af1d1e3a4297ef/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--33b2b080106a274a4ca568f8742d366d42f20c14/Hsu,%20JEI%20Figure%204.png)
In this study, the authors investigate the effects of acetone on the color of copper chloride (CuCl2) solution, which has important implications for detecting copper in the environment.
Read More...A colorimetric investigation of copper(II) solutions
In this study, the authors investigate the effects of acetone on the color of copper chloride (CuCl2) solution, which has important implications for detecting copper in the environment.
Read More...Utilizing 25-Hydroxyvitamin D3 to prevent the appearance of diabetic-like phenotypes in Drosophila melanogaster
This study aimed to assess the role of 25-hydroxyvitamin D3 solution, at varying concentrations, in protecting vertical transmission of diabetic-like phenotypes. We hypothesized that the highest concentration of vitamin D solution (55 ng/mL) would be most effective in having a protective role. The results indicated that the hypothesis was partially supported; overall, all three concentrations of the vitamin D solution administered to the flies reared on HSDs had a protective effect, to varying extents.
Read More...Does Gaming Improve Cognitive Skills?
Playing video games may improve mental performance by encouraging practicing logical reasoning skills. Students who played video games in between two tests tended to perform better on the second test than those that did not play video games.
Read More...Effects of cleaning agents on bacterial growth on refrigerator surfaces
The authors test the effectiveness of various cleaning agents on refrigerator shelves.
Read More...The effect of activation function choice on the performance of convolutional neural networks
With the advance of technology, artificial intelligence (AI) is now applied widely in society. In the study of AI, machine learning (ML) is a subfield in which a machine learns to be better at performing certain tasks through experience. This work focuses on the convolutional neural network (CNN), a framework of ML, applied to an image classification task. Specifically, we analyzed the performance of the CNN as the type of neural activation function changes.
Read More...An explainable model for content moderation
The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.
Read More...The most efficient position of magnets
Here, the authors investigated the most efficient way to position magnets to hold the most pieces of paper on the surface of a refrigerator. They used a regression model along with an artificial neural network to identify the most efficient positions of four magnets to be at the vertices of a rectangle.
Read More...Rubik’s cube: What separates the fastest solvers from the rest?
In this study, the authors assess the factors that allow some speedcubers to solve Rubik's Cubes faster than others.
Read More...The Effect of Sunglass Price on Ocular Exposure to Ultraviolet Radiation
Wearing sunglasses may offer protection against the negative health outcomes linked to exposure to ultraviolet waves. In this study, the authors test whether more expensive sunglasses offer better UV protection.
Read More...Using two-stage deep learning to assist the visually impaired with currency differentiation
Here, recognizing the difficulty that visually impaired people may have differentiating United States currency, the authors sought to use artificial intelligence (AI) models to identify US currencies. With a one-stage AI they reported a test accuracy of 89%, finding that multi-level deep learning models did not provide any significant advantage over a single-level AI.
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