| Dr. Ben Bagozzi, UD Department of Political Science Pt. II | Dr. Ben Bagozzi, UD Department of Political Science Pt. II | Ewing 336 | Title: Modeling Political Event Data: Opportunities and Challenges Part II
<br></br>
Abstract: Political event data measure "who did what to whom (and where/when)" for a wide number of actors (e.g., diplomats, police, military members, civilians, or NGOs) and actions (e.g., verbal threats, expressions of intents to cooperate, bombings, or atrocities). These data are typically machine coded from international newswires reports, and now encompass millions of (daily, geo-located) events arising both between and within all countries of the world. This talk will introduce political event data, their structure, and their most common uses. The talk will then detail a series of methodological challenges that arise in efforts to model and predict political event data. Here, special attention will be given to the (spatio-temporal and network) structure of event data, the inherent rarity of most events of interest (e.g., political violence), underlying measurement error issues, and the discrete (mixture) properties of many commonly analyzed event data variables. A selection of proposed modeling solutions to these challenges will then be presented in finer detail. | 4/25/2018 3:15:00 PM | 4/25/2018 4:15:00 PM | False | |
| Seth Cowall, Dept of Mathematical Sciences, UD | Seth Cowall, Dept of Mathematical Sciences, UD | Ewing 336 | Title: Data-Driven Modeling of Phytoplankton Blooms in the Ocean<br></br>
Abstract: Phytoplankton are the base of the marine food web. They are also responsible for almost half of the oxygen we breathe and they remove carbon dioxide from the atmosphere. A macroscale plankton ecology model is constructed consisting of coupled, nonlinear reaction-diffusion equations with spatially and temporally changing coefficients. An example of an NPZ model, this model simulates biological interactions between nutrients, phytoplankton and zooplankton. It also incorporates seasonally varying, physically driven forces that affect the phytoplankton growth: solar radiation and depth of the ocean’s upper mixed layer. The model’s predictions are dependent on the parametric functional behavior of the model. The model is analyzed using seasonal oceanic data with the goals of understanding the model’s dependence on its parameters and of understanding seasonal changes in plankton biomass. The model is tested on different regions of the world’s oceans so that appropriate choices can be made for parameters that correspond to physical/biological quantities in those regions. A study of varying parameter values and the resulting effects on the solutions, stability, and the timing of blooms is carried out. This modeling effort can be helpful for understanding the ecological structure of plankton communities and the timing of seasonal phytoplankton blooms, which are debated topics in oceanography. | 4/18/2018 3:15:00 PM | 4/18/2018 4:15:00 PM | False | |
| Prof. Ben Bagozzi, UD Department of Political Science | Prof. Ben Bagozzi, UD Department of Political Science | | Title:Modeling Political Event Data: Opportunities and Challenges<br></br>
Abstract:Political event data measure "who did what to whom (and where/when)" for a wide number of actors (e.g., diplomats, police, military members, civilians, or NGOs) and actions (e.g., verbal threats, expressions of intents to cooperate, bombings, or atrocities). These data are typically machine coded from international newswires reports, and now encompass millions of (daily, geo-located) events arising both between and within all countries of the world. This talk will introduce political event data, their structure, and their most common uses. The talk will then detail a series of methodological challenges that arise in efforts to model and predict political event data. Here, special attention will be given to the (spatio-temporal and network) structure of event data, the inherent rarity of most events of interest (e.g., political violence), underlying measurement error issues, and the discrete (mixture) properties of many commonly analyzed event data variables. A selection of proposed modeling solutions to these challenges will then be presented in finer detail. | 4/11/2018 3:15:00 PM | 4/11/2018 4:15:00 PM | False | |
| Dr Eric Kmiec, Helen F. Graham Cancer Center & Research Institute, Christiana Care Health System | Dr Eric Kmiec, Helen F. Graham Cancer Center & Research Institute, Christiana Care Health System | Ewing 336 | Title: CRISPR-directed Human Gene Editing: Clinical Application for Sickle Cell Disease
<br></br>
Abstract: The capacity to genetically modify a human chromosome has increased
significantly with the introduction of programmable nucleases, including
Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) and
Cas9/Cpf1 Nucleases. CRISPR-directed gene editing of human cells is
revolutionizing the treatment of inherited diseases including Sickle
Cell Disease (SCD). This seminar will outline the clinical and
developmental program aimed at repairing the mutation in SCD patient
cells currently taking place at the Gene Editing Institute at Christiana
Care Health System. In addition, the novel clinical approach for
treating non-small cell lung cancer (NSCLC), using CRISPR-directed gene
editing to disable functionally key genes responsible for
chemo-resistance in humans being carried out at the same institution,
will also be discussed. | 2/21/2018 4:15:00 PM | 2/21/2018 5:15:00 PM | False | |
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