Browsing by Author "Liu, Yi"
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- Characterization and prediction of tropical cyclone forerunner surgeLiu, Yi; Irish, Jennifer L. (Elsevier, 2019)Forerunner surge, a water level rise ahead of tropical cyclone landfall, often strikes coastal communities unexpectedly, stranding people and increasing loss of life. Surge forecasting systems and emergency managers almost exclusively focus on peak surge, while much less attention is given to forerunner surge. To address the need for fast and accurate forecasting of forerunner surge, we analyze high-fidelity surge simulations in Virginia, New York/New Jersey and Texas and extract physical scaling laws between readily available storm track information and forerunner surge magnitude and timing. We demonstrate that a dimensionless relationship between central-pressure scaled surge and wind-duration scaled time may effectively be used for rapid forerunner surge forecasting, where uncertainty is considered. We use our method to predict forerunner surge for Hurricanes Ike (2008)—a significant forerunner surge event—and Harvey (2017). The predicted forerunner surge 24 to 6 hours before Hurricane Ike’s landfall ranged from 0.4 to 2.8 m, where the observed forerunner surge ranged from 0.4 to 2.6 m. This new method has the potential to be incorporated into real-time surge forecasting systems to aid emergency management and evacuation decisions.
- A comprehensive investigation of Bronze Age human dietary strategies from different altitudinal environments in the Inner Asian Mountain CorridorWang, Wei; Liu, Yi; Duan, Futao; Zhang, Jie; Liu, Xinyi; Reid, Rachel E. B.; Zhang, Man; Dong, Weimiao; Wang, Yongqiang; Ruan, Qiurong; Li, Wenying; An, Cheng-Bang (2020-09)The early presence of crops from East Asia and Southwest Asia in the Inner Asian Mountain Corridor (IAMC) has drawn attention to the Bronze Age mountain archaeology of Central Asia. Namely, the Bronze Age diffusion and utilization of grains in this region remains unknown as contrasts and extremes characterize the territory in environmental terms, especially elevation. Researchers continue to reflect on how, during the second millennium BC, Bronze Age populations used new crops and local animal resources to adapt to different elevation environments of the IAMC. In this study, we analyzed the 41 latest stable carbon and nitrogen isotopic results from human and faunal bones from six Bronze Age sites in the IAMC, 261 previously published stable isotopic datasets, and 12 archaeobotanical and four zooarchaeological results to investigate the dietary strategies of populations from different elevation environments in the Bronze Age IAMC. The results show an altitudinal gradient in dietary choices among Bronze Age populations in the IAMC, with mixed C-4 and C-3 consumption at the low-mid elevations and notable C-3 consumption at the high elevations. Archaeobotanical and faunal remains also support these isotopic results. Our study further highlights that the differentiated dietary strategies adopted by the Bronze Age population in IAMC may have been the product of adaptation to local geographic environments. Social interaction may have also played a role in certain types of special dietary consumption.
- Investigation of the Spatiotemporal Evolution of Tropical Cyclone Storm Surge under Sea Level RiseLiu, Yi (Virginia Tech, 2018-07-31)Storm surges induced by tropical cyclones have been ravaging coastal communities worldwide, where a growing number of people reside. Tremendous life and economic losses are caused by tropical cyclones, contributing to more than half of the damages induced by natural hazards. To improve the resilience of coastal communities to surge hazards, it is of great importance to provide reliable and efficient real time forecasts of the spatiotemporal evolution of storm surge, as well as reliable predictions of the probabilistic surge hazards under future conditions. Three specific goals are addressed in this work. Studies on characterization and prediction of surge before a hurricane landfall show that a dimensionless relationship between intensity scaled surge magnitude and wind-duration scaled surge timing may effectively be used for rapid and reliable forerunner surge forecasting. Investigation of how probabilistic surge hazard changes with sea level rise (SLR) shows that the probabilistic surge with SLR can be 1.0 m larger, while different individual storm's surge with the same magnitude can be 1.5 m larger or 0.1 m smaller, indicating the importance of not relying on results from a limited number of storm surge events to assess the probabilistic surge hazard change to SLR. Finally, studying the temporal evolution of coastal flooding changes with SLR shows forerunner surge responds differently to SLR than peak surge, and that storm forward speed is a key factor determining the forerunner-SLR response.
- SacB-SacR Gene Cassette As the Negative Selection Marker to Suppress Agrobacterium Overgrowth in Agrobacterium-Mediated Plant TransformationLiu, Yiming; Miao, Jiamin; Traore, Sy; Kong, Danyu; Liu, Yi; Zhang, Xunzhong; Nimchuk, Zachary L.; Liu, Zongrang; Zhao, Bingyu Y. (2016)Agrobacterium overgrowth is a common problem in Agrobacterium-mediated plant transformation. To suppress the Agrobacterium overgrowth, various antibiotics have been used during plant tissue culture steps. The antibiotics are expensive and may adversely affect plant cell differentiation and reduce plant transformation efficiency. The SacB-SacR proteins are toxic to most Agrobacterium tumefaciens strains when they are grown on culture medium supplemented with sucrose. Therefore, SacB-SacR genes can be used as negative selection markers to suppress the overgrowth of A. tumefaciens in the plant tissue culture process. We generated a mutant A. tumefaciens strain GV2260 (recA-SacB/R) that has the SacB-SacR cassette inserted into the bacterial genome at the recA gene locus. The mutant Agrobacterium strain is sensitive to sucrose but maintains its ability to transform plant cells in both transient and stable transformation assays. We demonstrated that the mutant strain GV2260 (recA-SacB/R) can be inhibited by sucrose that reduces the overgrowth of Agrobacterium and therefore improves the plant transformation efficiency. We employed GV2260 (recA-SacB/R) to generate stable transgenic N. benthamiana plants expressing a CRISPR-Cas9 for knocking out a WRKY transcription factor.
- Time-Varying Coefficient Models for Recurrent EventsLiu, Yi (Virginia Tech, 2018-11-14)I have developed time-varying coefficient models for recurrent event data to evaluate the temporal profiles for recurrence rate and covariate effects. There are three major parts in this dissertation. The first two parts propose a mixed Poisson process model with gamma frailties for single type recurrent events. The third part proposes a Bayesian joint model based on multivariate log-normal frailties for multi-type recurrent events. In the first part, I propose an approach based on penalized B-splines to obtain smooth estimation for both time-varying coefficients and the log baseline intensity. An EM algorithm is developed for parameter estimation. One issue with this approach is that the estimating procedure is conditional on smoothing parameters, which have to be selected by cross-validation or optimizing certain performance criterion. The procedure can be computationally demanding with a large number of time-varying coefficients. To achieve objective estimation of smoothing parameters, I propose a mixed-model representation approach for penalized splines. Spline coefficients are treated as random effects and smoothing parameters are to be estimated as variance components. An EM algorithm embedded with penalized quasi-likelihood approximation is developed to estimate the model parameters. The third part proposes a Bayesian joint model with time-varying coefficients for multi-type recurrent events. Bayesian penalized splines are used to estimate time-varying coefficients and the log baseline intensity. One challenge in Bayesian penalized splines is that the smoothness of a spline fit is considerably sensitive to the subjective choice of hyperparameters. I establish a procedure to objectively determine the hyperparameters through a robust prior specification. A Markov chain Monte Carlo procedure based on Metropolis-adjusted Langevin algorithms is developed to sample from the high-dimensional distribution of spline coefficients. The procedure includes a joint sampling scheme to achieve better convergence and mixing properties. Simulation studies in the second and third part have confirmed satisfactory model performance in estimating time-varying coefficients under different curvature and event rate conditions. The models in the second and third part were applied to data from a commercial truck driver naturalistic driving study. The application results reveal that drivers with 7-hours-or-less sleep prior to a shift have a significantly higher intensity after 8 hours of on-duty driving and that their intensity remains higher after taking a break. In addition, the results also show drivers' self-selection on sleep time, total driving hours in a shift, and breaks. These applications provide crucial insight into the impact of sleep time on driving performance for commercial truck drivers and highlights the on-road safety implications of insufficient sleep and breaks while driving. This dissertation provides flexible and robust tools to evaluate the temporal profile of intensity for recurrent events.