Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (4 results)

  • Article
  • Peer Reviewed
UC Riverside Previously Published Works (2014)
Herbivore outbreaks, a major form of natural disturbance in many ecosystems, often have devastating impacts on their food plants. Understanding those factors permitting herbivore outbreaks to occur is a long-standing issue in conventional studies of plant-herbivore interactions. These studies are largely concerned with the relative importance of intrinsic biological factors and extrinsic environmental variations in determining the degree of herbivore outbreaks. In this paper, we illustrated that how the time delay associated with plant defense responses to herbivore attacks and the spatial diffusion of herbivore jointly promote outbreaks of herbivore population. Using a reaction-diffusion model, we showed that there exists a threshold of time delay in plant-herbivore interactions; when time delay is below the threshold value, there is no herbivore outbreak. However, when time delay is above the threshold value, periodic outbreak of herbivore emerges. Furthermore, the results confirm that during the outbreak period, plants display much lower density than its normal level but higher in the inter-outbreak periods. Our results are supported by empirical findings. © 2013.
    Cover page: Influence of time delay and nonlinear diffusion on herbivore outbreak
    • Article
    • Peer Reviewed
    Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, Volume 19, Issue 1 (2018)

    Introduction: Medical education is a rapidly evolving field that has been using new technology to improve how medical students learn. One of the recent implementations in medical education is the recording of lectures for the purpose of playback at various speeds. Though previous studies done via surveys have shown a subjective increase in the rate of knowledge acquisition when learning from sped-up lectures, no quantitative studies have measured information retention. The purpose of this study was to compare mean test scores on written assessments to objectively determine if watching a video of a recorded lecture at 1.5x speed was significantly different than 1.0x speed for the immediate retention of novel material.

    Methods: Fifty-four University of Kentucky medical students volunteered to participate in this study. The subjects were divided into two separate groups: Group A and Group B. Each group watched two separate videos, the first at 1.5x speed and the second at 1.0x speed, then completed assessments following each. The topics of the two videos were ultrasonography artifacts and transducers. Group A watched the artifacts video first at 1.5x speed followed by the transducers video at 1.0x speed. Group B watched the transducers video first at 1.5x speed followed by the artifacts video at 1.0x speed. The percentage correct on the written assessment were calculated for each subject at each video speed. The mean and standard deviation were also calculated using a t-test to determine if there was a significant difference in assessment scores between 1.5x and 1.0x speeds.

    Results: There was a significant (p=0.0188) detriment in performance on the artifacts quiz at 1.5x speed (mean 61.4; 95% confidence interval [CI]-53.9, 68.9) compared to the control group at normal speed (mean 72.7; 95% CI- 66.8, 78.6). On the transducers assessment, there was not a significant (p=0.1365) difference in performance in the 1.5x speed group (mean 66.9; CI- 59.8, 74.0) compared to the control group (mean 73.8; CI- 67.7, 79.8).

    Conclusion: These findings suggest that, unlike previously published studies that showed subjective improvement in performance with sped-up video-recorded lectures compared to normal speed, objective performance may be worse. [West J Emerg Med. 2017;1(4)–0.]

     

      Cover page: Does the Podcast Video Playback Speed Affect Comprehension for Novel Curriculum Delivery? A Randomized TrialCreative Commons 'BY' version 4.0 license
      • Article
      • Peer Reviewed
      UC Irvine Previously Published Works (2013)
      In this paper, we consider the optimal scheduling problem for a campus central plant equipped with a bank of multiple electrical chillers and a Thermal Energy Storage (TES). Typically, the chillers are operated in ON/OFF modes to charge the TES and supply chilled water to the campus. A bilinear model is established to describe the system dynamics. A model predictive control (MPC) problem is formulated to obtain optimal set-points to satisfy the campus cooling demands and minimize daily electricity costs. At each time step, the MPC problem is represented as a large-scale mixed integer nonlinear programming (MINLP) problem. We propose a heuristic algorithm to search for suboptimal solutions to the MINLP problem based on mixed integer linear programming (MILP), where the system dynamics is linearized along the simulated trajectories of the system. Simulation results show good performance and computational tractability of the proposed algorithm. © 2013 AACC American Automatic Control Council.
        Cover page: Optimal scheduling of chiller plant with thermal energy storage using mixed integer linear programmingCreative Commons 'BY' version 4.0 license
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2015)
        This work considers the optimal scheduling problem for a campus central plant equipped with a bank of multiple electrical chillers and a thermal energy storage (TES). Typically, the chillers are operated in ON/OFF modes to charge TES and supply chilled water to satisfy the campus cooling demands. A bilinear model is established to describe the system dynamics of the central plant. A model predictive control (MPC) problem is formulated to obtain optimal set-points to satisfy the campus cooling demands and minimize daily electricity cost. At each time step, the MPC problem is represented as a large-scale mixed-integer nonlinear programming problem. We propose a heuristic algorithm to obtain suboptimal solutions for it via dynamic programming (DP) and mixed integer linear programming (MILP). The system dynamics is linearized along the simulated trajectories of the system. The optimal TES operation profile is obtained by solving a DP problem at every horizon, and the optimal chiller operations are obtained by solving an MILP problem at every time step with a fixed TES operation profile. Simulation results show desired performance and computational tractability of the proposed algorithm.
          Cover page: Model Predictive Control of Central Chiller Plant With Thermal Energy Storage Via Dynamic Programming and Mixed-Integer Linear ProgrammingCreative Commons 'BY' version 4.0 license
          Top