Geology topics

Xiaojian Zhang

Publications and source records attributed to Xiaojian Zhang.

3 recordsLinked to original sources

USGS2025

Simulating human behavior under earthquake early warning

Earthquakes are a rapid-onset hazard where advance planning and learning plays a key role in mitigating injuries and death to individuals. Recent advances in earthquake detection have resulted in the development of earthquake early warning (EEW) systems. These systems can provide advance warning to predetermined geographic regions that an earthquake is in progress, which may result in individuals receiving warning seconds before significant shaking is felt at their location. This additional time could allow individuals to take more effective protective actions during the immediate disaster. To demonstrate this, we created an agent-based simulation of a basic apartment that allowed us to randomly and repeatedly simulate an individual receiving and responding to an EEW message. The results of our preliminary simulation show that, in our study environment, earthquake early warning alerts have the potential to allow for sufficient time for individuals to take protective actions.

Washington↗

USGS2024

Modeling protective action decision-making in earthquakes by using explainable machine learning and video data

Earthquakes pose substantial threats to communities worldwide. Understanding how people respond to the fast-changing environment during earthquakes is crucial for reducing risks and saving lives. This study aims to study people’s protective action decision-making in earthquakes by leveraging explainable machine learning and video data. Specifically, this study first collected real-world CCTV footage and video postings from social media platforms, and then identified and annotated changes in the environment and people’s behavioral responses during the M7.1 2018 Anchorage earthquake. By using the fully annotated video data, we applied XGBoost, a widely-used machine learning method, to model and forecast people’s protective actions (e.g., drop and cover , hold on , and evacuate ) during the earthquake. Then, explainable machine learning techniques were used to reveal the complex, nonlinear relationships between different factors and people’s choices of protective actions. Modeling results confirm that social and environmental cues played critical roles in affecting the probability of different protective actions. Certain factors, such as the earthquake shaking intensity and number of people shown in the environment, displayed evident nonlinear relationships with the probability of choosing to evacuate . These findings can help emergency managers and policymakers design more effective protective action recommendations during earthquakes.

Scientific Reports↗

USGS2019

Aerosol transmission of gull-origin Iceland subtype H10N7 influenza A virus in ferrets

Subtype H10 influenza A viruses (IAVs) have been recovered from domestic poultry and various aquatic bird species, and sporadic transmission of these IAVs from avian species to mammals (i.e., human, seal, and mink) are well documented. In 2015, we isolated four H10N7 viruses from gulls in Iceland. Genomic analyses showed four gene segments in the viruses were genetically associated with H10 IAVs that caused influenza outbreaks and deaths among European seals in 2014. Antigenic characterization suggested minimal antigenic variation among these H10N7 isolates and other archived H10 viruses recovered from human, seal, mink, and various avian species in Asia, Europe, and North America. Glycan binding preference analyses suggested that, similar to other avian-origin H10 IAVs, these gull-origin H10N7 IAVs bound to both avian-like alpha 2,3-linked sialic acids and human-like alpha 2,6-linked sialic acids. However, when the gull-origin viruses were compared with another Eurasian avian–origin H10N8 IAV, which caused human infections, the gull-origin virus showed significantly higher binding affinity to human-like glycan receptors. Results from ferret experiment demonstrated that a gull-origin H10N7 IAV replicated well in turbinate, trachea, and lung, but replication was most efficient in turbinate and trachea. This gull-origin H10N7 virus can be transmitted between ferrets through the direct contact and aerosol routes, without prior adaptation. Gulls share their habitat with other birds and mammals, and have frequent contact with humans; therefore, gull-origin H10N7 IAVs could pose a risk to public health. Surveillance and monitoring of these IAVs at the wild bird-human interface should be continued.

Journal of Virology↗