The authors describe the design and testing of new guide RNAs targeting the DMPK gene, which is responsible for myotonic dystrophy.
Read More...Designing gRNAs to reduce the expression of the DMPK gene in patients with classic myotonic dystrophy
The authors describe the design and testing of new guide RNAs targeting the DMPK gene, which is responsible for myotonic dystrophy.
Read More...Forecasting air quality index: A statistical machine learning and deep learning approach
Here the authors investigated air quality forecasting in India, comparing traditional time series models like SARIMA with deep learning models like LSTM. The research found that SARIMA models, which capture seasonal variations, outperform LSTM models in predicting Air Quality Index (AQI) levels across multiple Indian cities, supporting the hypothesis that simpler models can be more effective for this specific task.
Read More...An alternative to textile dyes: Synthesizing and applying PMMA nanoparticles to create structural coloration
The authors looked at developing a PMMA nanoparticle fabric dye that would be more sustainable compared to traditional fabric dyes. They were able to create PMMA based dyes in different colors that were also durable (i.e., did not fade quickly on fabric).
Read More...Do self-expression values affect global jazz popularity? An analysis of postmaterialism and political activity
Jazz music is a unique American art form that has spread around the world. Iyer and Iyer study this spread through a computational sociology project examining how jazz popularity is correlated with postmaterialism (an ideology that values self-expression) and political activity.
Read More...Vineyard vigilance: Harnessing deep learning for grapevine disease detection
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.
Read More...The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer
Here, in an effort to identify alternatives to oil-based plastic, the authors sought to investigate the effects of plasticizers on the mechanical properties and chemical composition of gelatin bioplastic matrices. Through measurements of their tensile strength and elongation at break, along with FTIR spectroscopy, they identified 3% w/v polyethylene glycol film as having the best performance in their study..
Read More...Nature’s reset: The effect of native and invasive plant forage on honey bee nutrition and survival
The authors looked at survival of honey bees over the winter in regards to native and invasive plant availability. They found that native plants provided greater survivability and overall health compared to environments where there was an abundance of invasive plants.
Read More...The effect of common food preservatives on the heart rate of Daphnia magna
The authors test the effects of common food industry preservatives on the heart rate of the freshwater crustacean Daphnia magna.
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...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.
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