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Lehigh University


A mechanistic and probabilistic method for predicting wildfires

Lehigh researchers develop new method to predict wildfires by analyzing power system ignition risk, considering mechanical behavior of conductor cables under strong winds. The study finds that encroachment probability is highly sensitive to vegetation clearance and wind intensity, providing valuable insights for decision makers and pol...

SourceLehigh University·JournalScientific Reports·DateMar 14, 2023

U.S. COVID Study: Asians, lower-income households reported less confidence in access to services

A national COVID-19 study found that Asians and lower-income households reported less confidence in accessing community resources crucial for their health and wellbeing during the pandemic. The study also revealed disparities related to sociodemographic characteristics and health-related characteristics, emphasizing the need for target...

SourceLehigh University·JournalHealthcare·TypeSurvey·DateFeb 7, 2023

Catalyzing clean energy

Researchers at Lehigh University have secured $13.2 million in funding to improve hydrogen generation and carbon capture/sequestration technologies through a partnership with Georgia Tech's UNCAGE-ME Center. The goal is to develop catalysts that can mitigate the degradation of these technologies in real-world conditions.

Off-axis high-temperature hydrothermal field discovered at the East Pacific Rise 9°54'N

Researchers from Lehigh University discovered a new, high-temperature, off-axis hydrothermal vent field called YBW-Sentry. The field covers an area equivalent to a football field, roughly twice the size of nearby active vents, and is hotter than any other studied along this section of the East Pacific Rise.

SourceLehigh University·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateJul 18, 2022

Accelerating the pace of machine learning

A new distributed learning technique, GD-SEC, reduces communication requirements in wireless architecture, improving efficiency and reducing computational cost. The method employs data compression to transmit only meaningful, usable data, enhancing the impact of machine learning while minimizing its limitations.

SourceLehigh University·JournalIEEE Journal of Selected Topics in Signal Processing·DateMay 18, 2022

How COVID-19 increases challenges for youth with ADHD

New research reveals that youth with ADHD are more likely to experience COVID-19 symptoms, sleep problems, and anxiety related to infection risk. The study found that these individuals are less responsive to factors like parental monitoring and school engagement that may mitigate the impact of pandemic school closures.

SourceLehigh University·JournalJournal of Attention Disorders·DateJan 18, 2022

Studying thermophoresis in space

A multidisciplinary team of Lehigh University researchers will conduct experiments on thermophoresis in complex fluids for bioseparations at the International Space Station. The team hopes to understand how temperature gradients affect particles and improve virus separation techniques with potential societal impact.

Mapping the evolution of materials

Lehigh University researchers are developing a model to understand the impact of grain growth on material properties. The project aims to create new materials informatics methods, innovative stochastic differential equations, and models of grain growth to improve material performance and reliability.