Browse Articles

A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Ahmed et al. | Jun 09, 2023

A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Several studies have applied different machine learning (ML) techniques to the area of forecasting solar photovoltaic power production. Most of these studies use weather data as inputs to predict power production; however, there are numerous practical issues with the procurement of this data. This study proposes models that do not use weather data as inputs, but rather use past power production data as a more practical substitute to weather-based models. Our proposed models demonstrate a better, cheaper, and more reliable alternatives to current weather models.

Read More...

Decolorization of textile dyes by edible white rot fungi

Lin et al. | Apr 29, 2022

Decolorization of textile dyes by edible white rot fungi

As fast fashion explodes in popularity, the fashion industry remains one of the most prominent industries responsible for pollution. This pollution includes a lack of treatment for textile dyes that remain toxic or carcinogenic as they persist in wastewater. To resolve this, the authors of this study set out to determine the efficacy of using edible white rot fungi for cell-based biodegradation of textile dyes into harmless chemicals. This method takes advantage of fungi found in excess from the fungi industry, decreasing food waste while addressing textile waste in tandem.

Read More...

Effect of Gram-positive bacteria on antibiotic resistance in Gram-negative bacteria

Willem et al. | Mar 12, 2024

Effect of Gram-positive bacteria on antibiotic resistance in Gram-negative bacteria

Antibiotics are one of the most common treatments for bacterial infections, but the emergence of antibiotic resistance is a major threat to the control of infectious diseases. Many factors contribute to the development of antibiotic resistance. One is bacterial conjugation from Gram-positive to Gram-negative bacteria where there is a transfer of resistance genes from Gram-positive to Gram-negative bacteria that could increase antibiotic resistance in the latter. In light of these observations, we decided to test whether Gram-negative bacteria that came into contact with Gram-positive bacteria had a higher resistance to the antimicrobial properties of spices than Gram-negative bacteria that did not come into contact with Gram-positive bacteria.

Read More...

Testing Simarouba amara’s therapeutic effects against weedicide-induced tumor-like morphology in planarians

Thiagarajan et al. | Apr 26, 2024

Testing Simarouba amara’s therapeutic effects against weedicide-induced tumor-like morphology in planarians

According to the World Health Organization, cancer is a leading cause of death globally. The disease’s prevalence is rapidly increasing in association with factors including the increased use of pesticides and herbicides, such as glyphosate, which is one of the most widely used herbicide ingredients. Natural antioxidants and phytochemicals are being tested as anti-cancer agents due to their antiproliferative, antioxidative, and pro-apoptotic properties. Thus, we aimed to investigate the potential role of S. amara extract as a therapeutic agent against glyphosate-induced toxicity and tumor-like morphologies in regenerating and homeostatic planaria (Dugesia dorotocephala).

Read More...

A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood

Adami et al. | Sep 20, 2023

A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Image credit: National Cancer Institute

Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.

Read More...

Willingness to visit the pediatric dentist during the COVID-19 pandemic

Rossitch et al. | Mar 24, 2022

Willingness to visit the pediatric dentist during the COVID-19 pandemic

Because of the COVID-19 pandemic, people are missing important appointments because they are viewed as nonessential, possibly including children's pediatric dentist appointments. This study aims to determine how the COVID-19 pandemic has effected parents' willingness to allow children to visit pediatric dental practices and what safety measures would make them feel more comfortable visiting the dentist. The authors found a weak positive correlation between parents' unwillingness to allow their child to visit the dentist, however overall anxiety towards visiting the dentist during the pandemic was low.

Read More...

Search Articles

Search articles by title, author name, or tags

Clear all filters

Popular Tags

Browse by school level