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IMAGE: Researchers analyzed Washington, D.C. because of its availability of wide-open data, including built environment data and the maturity of its shared mobility market. view more
Credit: Florida Atlantic University
Electric scooters or e-scooters are taking over cities worldwide and have broad appeal with tourists. Although e-scooter use declined during the COVID-19 pandemic, its popularity could rebound rapidly, especially if travelers start to substitute scooters for transit on some shorter trips. Shared e-scooters in particular, are a rapidly emerging mode of transportation, but present a host of regulatory challenges from equitable distribution to parking infrastructure to pedestrian safety, among others.
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CHICAGO - Public attitude toward COVID-19 and its treatments is more infectious than the disease itself, according to a new Northwestern Medicine study using Artificial Intelligence (AI) to analyze tweets about the virus. Researchers studied the influence of Twitter on COVID-19 health beliefs as well as the competing influence of scientific evidence versus the speeches of politicians.
The study s key findings:
People s biases are magnified when they read tweets about COVID-19 from other users, and the more times it has been retweeted, the more they tend to believe it and retweet it themselves.
Scientific events, such as scientific publications, and non-scientific events, such as speeches of politicians, equally influence health belief trends on social media.
Credit: Peter the Great St.Petersburg Polytechnic University
A painful tradeoff between a number of infected and negative economic impact must be considered before deciding on the lockdown strategy within a city. As national economies continue to crumble, citizens wonder whether their governments did a good job at regulating the lockdown measures.
Russian city of St. Petersburg is at the frontlines of this ongoing war with Covid-19. To combat this situation effectively, Russian government allocated significant funds for the research. Results followed. Scientists from Peter the Great St.Petersburg Polytechnic University (SPbPU) modified the existing SIR class pandemic prediction model. Now it is better.
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IMAGE: High-throughput total RNA-seq profile for PLCγ1 and PLCβ subfamily gene expression in the cortex view more
Credit: KBRI
Korea Brain Research Institute (KBRI, President Suh Pann-ghill) announced that the research team led by Dr. Jae-Yeol Joo discovered new cryptic splice variants and SNVs in PLCg1 gene of AD-specific models for the first time using Splice-AI.
This research outcome was published in
PNAS, a world-renowned academic journal. (Title) Prediction of Alzheimer s Disease-Specific phospholipase c gamma-1 SNV by Deep Learning-Based Approach for High-Throughput Screening Alternative splicing variant regulates gene expression and influences diverse phenotypes. Especially, genetic variants arising due to RNA splicing are frequently found in individuals having neurodevelopmental disorders.
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Clinical research requires that data be mined for insights. Machine learning, which develops algorithms to find patterns, has difficulty doing this with data related to health records because this type of information is neither static nor regularly collected. A new study developed a transparent and reproducible machine learning tool to facilitate analysis of health information. The tool can be used in clinical forecasting, which can predict trends as well as outcomes in individual patients.
The study, by a researcher at Carnegie Mellon University (CMU), appears in
Proceedings of Machine Learning Research. Temporal Learning Lite, or TL-Lite, is a visualization and forecasting tool to bridge the gap between clinical visualization and machine learning analysis, explains Jeremy Weiss, assistant professor of health informatics at CMU s Heinz College, who authored the study. While the individual elements of this tool are well known, their integration into an interactive cl