![Awareness of plastic pollution and adoption of green consumer lifestyles among students from high school](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbThJIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--5f40a4f907a2325ecff9dba659978818debe4d89/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/pexels-anete-lusina-4792658.jpg)
In this study, the authors test ways to increase knowledge of green consumerism amongst high school students. Their knowledge was measured based on the New Ecological Paradigm Scale.
Read More...Awareness of plastic pollution and adoption of green consumer lifestyles among students from high school
In this study, the authors test ways to increase knowledge of green consumerism amongst high school students. Their knowledge was measured based on the New Ecological Paradigm Scale.
Read More...The Effect of Wind Mitigation Devices on Gabled Roofs
The purpose of this study was to test devices installed on a gabled roof to see which reduced the actual uplift forces best. Three gabled birdhouse roofs were each modified with different mitigation devices: a rounded edge, a barrier shape, or an airfoil. The barrier edge had no significant effect on the time for the roof to blow off. The addition of airfoil devices on roofs, specifically in areas that are prone to hurricanes such as Florida, could keep roofs in place during hurricanes, thus reducing insurance bills, overall damage costs, and the loss of lives.
Read More...Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance
In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.
Read More...A computational quantum chemical study of fluorinated Allopurinol
In this study, the impact of fluorination of heterocyclic drug Allopurinol on its stability and other chemical properties is investigated.
Read More...How Ya Doin'? with COVID-19
In this study, the authors survey students and adults about how the COVID-19 pandemic has impacted their sleep patterns, eating habits, mood, physical activity, and screen time.
Read More...Measuring the efficiency of greenhouse gases to absorb heat
In the age of global warming, these authors studied which of the four major greenhouse gases (water vapor, carbon dioxide, and nitrous oxide) change the most with increased temperature.
Read More...Using explainable artificial intelligence to identify patient-specific breast cancer subtypes
Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.
Read More...Antimicrobial properties of common household spices on microbes cultured from two kitchen locations
The number of bacterial infections in humans is rising, and a major contributor is foodborne illnesses, which affect a large portion of the population and result in many hospitalizations and deaths. Common household cleaners are an effective strategy to combat foodborne illness, but they are often costly and contain harmful chemicals. Thus, the authors sought to test the antimicrobial effectiveness of spices (clove, nutmeg, astragalus, cinnamon, turmeric, and garlic) on microbes cultured from refrigerator handles and cutting boards. Results from this study demonstrate long-lasting, antimicrobial effects of multiple spices that support their use as alternatives to common household cleaners.
Read More...Application of arbuscular mycorrhizal fungi to inhibit nitrogen uptake of weeds within crop fields
In this study, the ability of arbuscular mycorrhizal fungi to limit the growth of an agricultural weed Cirsium arvense is tested. This has important implications for developing natural herbicides.
Read More...Environmentally-friendly graphene conductive ink using graphene powder, polystyrene, and waste oil
In this article, the authors propose an effective, environmentally-friendly method of producing conductive ink using expired waste oil, polystyrene, and graphene.
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