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Scoot over! Study reveals E-scooter use in Washington D.C.

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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.
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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. ....

United States , White House , District Of Columbia , Yiming Xu , Louisa Merlin , Xilei Zhao , Xiang Yan , Department Of Civil , University Of Florida , Charlese Schmidt College Of Science , Southeastern Transportation Research , Transportation Research Part , Us Department Of Transportation , University Transportation Center Grant No , Florida Atlantic University , Regional Planning , General Bikeshare Feed Specification , Coastal Engineering , Transportation Center , Algorithms Models , Social Behavioral Science , Transportation Travel , Information Management Tracking Systems , Management Science Operations Research , ஒன்றுபட்டது மாநிலங்களில் , வெள்ளை வீடு ,

AI shows public attitude toward COVID-19 is more 'infectious' than disease itself

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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. ....

Northwestern University , United States , Yikuan Li , Hanyin Wang , Meghan Hutch , Andrew Naidech , Northwestern University Clinical , Driskill Graduate Program , Translational Sciences Institute , Journal Of Medical Internet Research , Northwestern Medicine , Artificial Intelligence , Yuan Luo , Augmented Intelligence , Northwestern University Feinberg School , Medical Internet , Translational Sciences , National Library , National Institutes , Algorithms Models , Medicine Health , Infectious Emerging Diseases , Social Behavioral Science , Mass Media , Robotry Artificial Intelligence , வடமேற்கு பல்கலைக்கழகம் ,

Covid-19: How to do lockdown? Russian scientists may have an answer

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. ....

Sankt Peterburg , Great St Petersburg Polytechnic University Spb , Great St Petersburg Polytechnic University , Mathematics Statistics , Algorithms Models , Calculations Problem Solving , Health Care Systems Services , Infectious Emerging Diseases , Public Health , Software Engineering , நன்று ஸ்டம்ப் பீட்டர்ஸ்பர்க் பாலிடெக்நிக் பல்கலைக்கழகம் ஸ்ப்ப் , நன்று ஸ்டம்ப் பீட்டர்ஸ்பர்க் பாலிடெக்நிக் பல்கலைக்கழகம் , கணிதம் புள்ளிவிவரங்கள் , கணக்கீடுகள் ப்ராப்லம் தீர்க்கும் , ஆரோக்கியம் பராமரிப்பு அமைப்புகள் சேவைகள் , தொற்று வளர்ந்து வருகிறது நோய்கள் , பொது ஆரோக்கியம் , மென்பொருள் பொறியியல் ,

Predicts the onset of Alzheimer's Disease (AD) using deep learning-based Splice-AI

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IMAGE: High-throughput total RNA-seq profile for PLCγ1 and PLCβ subfamily gene expression in the cortex
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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. ....

South Korea , Suh Pann Ghill , Jae Yeol Joo , National Research Foundation Of Korea , Korea Brain Research Institute , President Suh Pann Ghill , Deep Learning Based Approach , Fourth Industrial Revolution , National Research Foundation , Cell Biology , Health Care , Algorithms Models , Medicine Health , தெற்கு கொரியா , தேசிய ஆராய்ச்சி அடித்தளம் ஆஃப் கொரியா , கொரியா மூளை ஆராய்ச்சி நிறுவனம் , ஆழமான கற்றல் அடிப்படையிலானது அணுகுமுறை , நான்காவது தொழில்துறை புரட்சி , தேசிய ஆராய்ச்சி அடித்தளம் , செல் உயிரியல் , ஆரோக்கியம் பராமரிப்பு , மருந்து ஆரோக்கியம் ,

New machine learning tool facilitates analysis of health information, clinical forecasting

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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 ....

Jeremy Weiss , Carnegie Mellon University , Amazon Web Services , Heinz College , Proceedings Of Machine Learning Research , Machine Learning , Learning Lite , Health Care , Algorithms Models , Medicine Health , Health Care Systems Services , Health Professionals , Medical Scientific Ethics , Technology Engineering Computer Science , ஜெர்மி வெயிஸ் , கார்னகி மெலந் பல்கலைக்கழகம் , அமேசான் வலை சேவைகள் , ஹெய்ன்ஸ் கல்லூரி , இயந்திரம் கற்றல் , கற்றல் லைட் , ஆரோக்கியம் பராமரிப்பு , மருந்து ஆரோக்கியம் , ஆரோக்கியம் பராமரிப்பு அமைப்புகள் சேவைகள் , ஆரோக்கியம் ப்ரொஃபெஶநல்ஸ் , மருத்துவ அறிவியல் நெறிமுறைகள் , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் ,