The authors explore factors affecting graduation rates of students learning English as a second language across Florida counties.
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A natural language processing approach to skill identification in the job market
The authors looked at using machine learning to identify skills needed to apply for certain jobs, specifically looking at different techniques to parse apart the text. They found that Bidirectional Encoder Representation of Transforms (BERT) performed best.
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...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
Read More...Optimizing surface contact area and electrolyte type to develop a more effective rechargeable battery
Rechargeable batteries are playing an increasingly prominent role in our lives due to the ongoing transition from fossil energy sources to green energy. The purpose of this study was to investigate variables that impact the effectiveness of rechargeable batteries. Alkaline (non-rechargeable) and rechargeable batteries share common features that are critical for the operation of a battery. The positive and negative electrodes, also known as the cathode and anode, are where the energy of the battery is stored. The electrolyte is what facilitates the transfer of cations and anions in a battery to generate electricity. Due to the importance of these components, we felt that a systematic investigation examining the surface area of the cathode and anode as well the impact of electrolytes with different properties on battery performance was justified. Utilizing a copper cathode and aluminum anode coupled with a water in salt electrolyte, a model rechargeable battery system was developed to test two hypotheses: a) increasing the contact area between the electrodes and electrolyte would improve battery capacity, and b) more soluble salt-based electrolytes would improve battery capacity. After soaking in an electrolyte solution, the battery was charged and the capacity, starting voltage, and ending voltage of each battery were measured. The results of this study supported our hypothesis that larger anode/cathodes surface areas and more ionic electrolytes such as sodium chloride, potassium chloride and potassium sulfate resulted in superior battery capacity. Incorporating these findings can help maximize the efficiency of commercial rechargeable batteries.
Read More...Sex differences in sleep disorders of Parkinson’s disease patients associated with a genetic risk variant
The authors use known Parkinson's disease-associated genetic variants to compare the prevalence of sleep dysfunction between males and females diagnosed with Parkinson's disease.
Read More...Upward social comparison on standardized test performance in adolescents and adults
The authors test the effect of test score comparison on the self-efficacy of adolescents versus adults.
Read More...Unveiling bias in ChatGPT-3.5: Analyzing constitutional AI principles for politically biased responses
Various methods exist to mitigate bias in AI models, including "Constitutional AI," a technique which guides the AI to behave according to a list of rules and principles. Lo, Poosarla, Singhal, Li, Fu, and Mui investigate whether constitutional AI can reduce bias in AI outputs on political topics.
Read More...Survival analysis in cardiovascular epidemiology: nexus between heart disease and mortality
In 2021, over 20 million people died from cardiovascular diseases, highlighting the need for a deeper understanding of factors influencing heart failure outcomes. This study examined multiple variables affecting mortality after heart failure, using random forest models to identify time, serum creatinine, and ejection fraction as key predictors. These findings could contribute to personalized medicine, improving survival rates by tailoring treatment strategies for heart failure patients.
Read More...The correlation between bacteria and colorectal cancer
The authors looked at abundance of bacteria in stool samples from patients with colorectal cancer compared to controls. They found different bacteria that was more prevalent in patients with colorectal cancer as well as bacteria in control patients that may indicate a beneficial gut microbiome.
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