Patients with cleft palate frequently struggle with speech issues such as nasal or congested speech. Lin and Parkinson conduct a meta-analysis to determine how two common types of cleft palate repair surgery compare in terms of their effects on patient's speech.
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The effects of social media on STEM identity in adolescent girls
Social media is widely used and easily accessible for adolescents, it has the potential to increase STEM (Science, Technology, Engineering, and Math) identity in girls. We aimed to investigate the effects of exposure to counter-stereotypical portrayals of women in STEM on social media on the STEM identity of adolescent girls. The study concluded that social media alone may not be an effective tool to increase STEM identity in girls. Social media can still be used as a complementary tool to support and encourage women in STEM, but it should not be relied upon solely to address the gender disparity in STEM fields.
Read More...The effect of financial and food-based incentives on math test performance
The authors looked at the effect of monetary vs. food incentives on math test performance. They found that financial incentives did increase student performance, but not necessarily food incentives.
Read More...Are Asian foods healthier than Western foods: Evidence collected from St. Louis area grocery stores
The authors compare nutritional content of foods found in Western versus Asian grocery stores to determine whether one cultural diet is healthier than the other.
Read More...Osmotic characteristics of water retention structures of Bursera microphylla in relation to soil salinity
This study hypothesized that sodium chloride was taken up through plant root structures to facilitate water transportation, and that sodium chloride accumulation was directly proportional to the soil salinity. Results showed that most cells within the “bulb” structures were isotonic at a concentration approximately twice as high as that of root tissue and ambient soil salinity, therefore supporting the presented hypothesis.
Read More...Post-Traumatic Stress Disorder (PTSD) biomarker identification using a deep learning model
In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.
Read More...Association of depression and suicidal ideation among adults with the use of H2 antagonists
In this study, the authors investigate associations between use of histamine H2 receptor antagonists and suicidal ideation in different age groups.
Read More...EEG study of virtual learning demonstrates worsened learning outcomes and increased mirror neuron activation
In this article, Choi and Rossitto investigated the limitations of virtual learning by examining in-person dance learning compared to virtual dance learning while wearing EEG headsets. They found that in-person learners outperformed virtual learners and that virtual learners had higher mirror neuron activity as assessed by Mu rhythm power.
Read More...Evaluation of Microplastics in Japanese Fish Using Visual and Chemical Dissections
Does the overuse of plastic in Japan poses an ecological risk to marine species and their consumers? Using visual and chemical dissection, all fish in this study were found to have microplastics present in their gastrointestinal tract, including two species that are typically eaten whole in Japan. Overall, these results are concerning as previous studies have found that microplastics can carry persistent organic pollutants. It is presumed that the increasing consumption of microplastics will have negative implications on organ systems such as the liver, gut, and hormones.
Read More...Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease
Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).
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