In this study, the authors use quantitative digit ratio measurements and a survey of personality traits to evaluate the potential relationship between sex and levels of conscientiousness.
Read More...The relationship between digit ratio and personality: 4D:5D digit ratio, sex, and the trait of conscientiousness
In this study, the authors use quantitative digit ratio measurements and a survey of personality traits to evaluate the potential relationship between sex and levels of conscientiousness.
Read More...Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues
Understanding the techniques used to improve the adhesion strength of the epoxy resin is important especially for consumer applications such as repairing car parts, bonding aluminum sheeting, and repairing furniture or applications within the aviation or civil industry. Selleys Araldite epoxy makes specific strength claims emphasizing that the load or weight that can be supported by the adhesive is 72 kg/cm2. Nguyen and Clarke aimed to test the strength claims of Selley’s Araldite Epoxy by gluing two steel adhesion surfaces: a steel tube and bracket. Results showed that there is a lack of consideration by Selleys for adhesion loss mechanisms and environmental factors when accounting for consumer use of the product leading to disputable claims.
Read More...Deep learning for pulsar detection: Investigating hyperparameter effects on TensorFlow classification accuracy
This study investigates how the hyperparameters epochs and batch size affect the classification accuracy of a convolutional neural network (CNN) trained on pulsar candidate data. Our results reveal that accuracy improves with increasing number of epochs and smaller batch sizes, suggesting that with optimized hyperparameters, high accuracy may be achievable with minimal training. These findings offer insights that could help create more efficient machine learning classification models for pulsar signal detection, with the potential of accelerating pulsar discovery and advancing astrophysical research.
Read More...Drought prediction in the Midwestern United States using deep learning
The authors studied the ability of deep learning models to predict droughts in the midwestern United States.
Read More...Ultraviolet exposure and thermal mass variation on surface temperature responses in building materials
The authors studied the response of various construction materials to UV solar radiation and heat.
Read More...Impact of TCERG1 SNP on gene expression and protein interactome in Huntington’s disease
The authors assess a genetic variant within a well-known interaction partner of huntingtin that has been linked to modifying the age of onset of Huntington's disease.
Read More...Growth of Staphylococcus epidermidis and Escherichia coli when exposed to anti-acne vitamin A
The authors looked at the impact of vitamin A (retinol) on growth of S. epidermidis (most abundant bacterium on the skin) and E. coli (found in the gut microbiome, but not on the skin).
Read More...Examining the impact of the sympathetic nervous system on short-term memory
The authors looked at how activation of the sympathetic nervous system impacts short-term memory.
Read More...Stock price prediction: Long short-term memory vs. Autoformer and time series foundation model
The authors looked the ability to predict future stock prices using various machine learning models.
Read More...An assessment of controllable etiological factors involved in neonatal seizure using a Monte Carlo model
The authors used Monte Carlo simulations to assess the impacts of various factors on neonatal seizure risk.
Read More...