Globally, the cultivation of 77.8 million tons of grapes each year underscores their significance in both diets and agriculture. However, grapevines face mounting threats from diseases such as black rot, Esca, and leaf blight. Traditional detection methods often lag, leading to reduced yields and poor fruit quality. To address this, authors used machine learning, specifically deep learning with Convolutional Neural Networks (CNNs), to enhance disease detection.
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Converting SiO2 wafers to hydrophobic using chlorotrimethylsilane
Semiconductors are the center of the fourth industrial revolution as they are key components for all electronics. Exposed wafers made of silicon (Si), which can easily oxidize, convert to silicon dioxide (SiO2). The surface of SiO2 wafers consists of many Si-OH bonds, allowing them to easily bond with water, resulting in a “wet” or hydrophilic condition. We sought to determine a way to modify the surface of SiO2 wafers to become hydrophobic to ensure safe wet cleaning.
Read More...Exploring the possibilities for reactions between SiW and alkaline solutions to be renewable energy sources
The authors looked at hydrogen gas production and how reaction temperature, concentration and alkaline solution used impacted the overall reaction with silicon. They found that all alkaline solutions tested would be viable options for using silicon waste to produce hydrogen gas to be used a renewable energy source.
Read More...Quantifying kitchen appliances’ phantom loads using a shifted gamma distribution model
In this article the authors look at phantom loads of common kitchen appliances and found that the appliances looked at have a phantom load of 10.9%. Understanding phantom loads is important as it can reduce energy grid usage and energy bill costs for homeowners.
Read More...Impacts of the gut microbiota on arginine synthesis
In this article the authors looked at arginine synthesis across different bacteria commonly found in different regional diets. They found that B. megaterium and C. sporogenes both caused a higher pH to occur on their agar plates compared to other bacteria tested indicating a greater amount of arginine synthesis.
Read More...Analyzing the relationships between years of experience and performance anxiety in teen volleyball players
Athletes with performance anxiety may struggle to play their best and enjoy the game. Various factors may impact how much anxiety an athlete feels, including how much experience they have in the sport. Concha-Ortiz and Navins survey teenage club volleyball players to look for relationships between years of experience and performance anxiety symptoms.
Read More...Color photometry and light curve modeling of apparent transient 2023jri
Observing transients like supernovae, which have short-lived brightness variations, helps astronomers understand cosmic phenomena. This study analyzed transient 2023jri, hypothesizing it was a Type IIb supernova. By collecting and analyzing data over four weeks, including light and color curves, they confirmed its classification and provided additional insights into this less-studied supernova type.
Read More...Comparing and evaluating ChatGPT’s performance giving financial advice with Reddit questions and answers
Here, the authors compared financial advice output by chat-GPT to actual Reddit comments from the "r/Financial Planning" subreddit. By assessing the model's response content, length, and advice they found that while artificial intelligence can deliver information, it failed in its delivery, clarity, and decisiveness.
Read More...A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis
Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.
Read More...Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.
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