The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.
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Cytotoxicity evaluation of Amaranthus extracts compared with AS20 on MCF-7 cancer cells
The authors test the antiproliferative and apoptosis-inducing properties of an extract created from a traditional Indian medicinal plant of the Amaranthus genus.
Read More...Slowing ice melting from thermal radiation using sustainable, eco-friendly eggshells
The authors looked at the ability of eggshells to slow ice melting. They found that eggshells were able to increase ice melting time when crushed showing that they were an effective thermal barrier.
Read More...Managing CO2 levels through precipitation-based capture from seawater and electrochemical conversion
The authors set out to develop an electrochemical device that would have efficient and sustained carbon dioxide capture.
Read More...The Parent-Child Relationship During the College Planning Process
To explore the parent-child relationship during college planning, authors surveyed high school juniors from two private schools (boarding school vs. non-boarding parochial school). After coding, survey answers indicate students at boarding schools were found to have greater fear of parental control and disappointment, while students at non-boarding parochial schoolexpressed a greater need for parental assistance.
Read More...Long-run effects of minimum wage on labor market dynamics
The authors looked at potential downstream effects of raising the minimum wage. Specifically they focused on taxable wages, employment, and firm counts.
Read More...The impact of culturally informed music therapy on visually impaired youth: A Jaffna, Sri Lanka study
The authors looked at the effect of music therapy on visually impaired youth. They found that culturally relevant curricula is an important consideration while also showing that broadly music therapy enhances working memory, emotional well-being and inhibitory control.
Read More...Quantitative analysis and development of alopecia areata classification frameworks
This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.
Read More...Implementing machine learning algorithms on criminal databases to develop a criminal activity index
The authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.
Read More...Solving the Schrödinger equation computationally using the Lanczos algorithm
The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program
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