
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.
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.
Read More...Developing a neural network to model the mechanical properties of 13-8 PH stainless steel alloy
We systematically evaluated the effects of raw material composition, heat treatment, and mechanical properties on 13-8PH stainless steel alloy. The results of the neural network models were in agreement with experimental results and aided in the evaluation of the effects of aging temperature on double shear strength. The data suggests that this model can be used to determine the appropriate 13-8PH alloy aging temperature needed to achieve the desired mechanical properties, eliminating the need for many costly trials and errors through re-heat treatments.
Read More...The Effect of Positive and Negative Reinforcement on Sixth Graders’ Mental Math Performance
What type of motivation is more effective: reward or punishment? In this study, the authors assess the effects of positive or negative on the math scores of sixth graders.
Read More...The impact of environmental noise on the cognitive functions and mental workload of high school students
Authors examine the impact of environmental noise on cognitive processes in teenagers, focusing on five different noise conditions: two types of noise (aircraft and construction) at two different decibel levels (30 dBA and 60 dBA) and a quiet condition.
Read More...Does Gaming Improve Cognitive Skills?
Playing video games may improve mental performance by encouraging practicing logical reasoning skills. Students who played video games in between two tests tended to perform better on the second test than those that did not play video games.
Read More...The sweetened actualities of neural membrane proteins: A computational structural analysis
Here, seeking to better understand the roles of glycans in the receptors of active sites of neuronal cells, the authors used molecular dynamics simulations to to uncover the dynamic nature of N-glycans on membrane proteins. The authors suggest the study of theinteractions of these membrane poreins could provide future potential therapeutic targets to treat mental diseases.
Read More...Emotional and Psychological Effect of Music on People
Nolt and Elwonger examine how different types of music impact our emotional and physical states. They found that music can influence a subject's emotional state, with sad music inspiring sadness and exciting music bringing excitement. They were not able to find a clear relationship between heart rate and music type. Music's effect on emotional state can be useful when designing novel therapies for emotional and mental disorders.
Read More...Testing HCN1 channel dysregulation in the prefrontal cortex using a novel piezoelectric silk neuromodulator
Although no comprehensive characterization of schizophrenia exists, there is a general consensus that patients have electrical dysfunction in the prefrontal cortex. The authors designed a novel piezoelectric silk-based implant and optimized electrical output through the addition of conductive materials zinc oxide (ZnO) and aluminum nitride (AlN). With further research and compatibility studies, this implant could rectify electrical misfiring in the infralimbic prefrontal cortex.
Read More...Understanding the battleground of identity fraud
The authors looked at variables associated with identity fraud in the US. They found that national unemployment rate and online banking usage are among significant variables that explain identity fraud.
Read More...A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
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%.
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