DATA SCIENCE INITIATIVE

Speakers:

Albert Kabanda, PhD Candidate, Earth and Planetary Sciences, Northwestern University

Crustal Structure of the East African Rift System, in Uganda from Receiver Function Analysis
Abstract: Studies of Moho depth heterogeneity beneath the western branch of the East African Rift System (EARS) are limited to regions and localities where temporary seismic arrays had been installed. Our temporary seismic array of 19 stations covers the western branch from the Rhino Graben in the north to the Toro-Ankole Volcanic Province in the south. We apply P-wave receiver function (RF) analysis to our data to estimate crustal thickness and Poisson ratios along this part of EARS. We present preliminary results of RF analysis of seismic data from thirty teleseismic earthquakes closer than 90° and with magnitudes of 6 and higher. We calculated the P-wave RFs for each seismic station using the iterative time-domain deconvolution method by deconvolving the radial component of the seismogram by the vertical component to obtain the P to S converted waves. We used the H–$\kappa$ stacking method to transform the time domain waveforms into the depth-velocity ratio domain, which gives estimates for both the crustal thickness (Moho depths) and constitution ($\alpha$/$\beta$ ratio). The preliminary results show that the crustal thickness and crustal velocity ratio vary both along and across the rift branch. Away from the rift branch the crust is generally 35-40 km thick, which is typical for tectonically stable continental crust. Along the rift the crust is significantly thinner, showing additional along-rift variation. Velocity ratio heterogeneity exists on similar scales. We will continue to analyze additional data from the field and present results on crustal thickness and velocity ratios. In addition, we will invert the updated RFs to extract an S-wave velocity model beneath each station starting from the continental ak135 model.

Neelam Modi, PhD Candidate, Industrial Engineering & Management Sciences, Northwestern University

Modeling the “Who” and “How” of Social Influence in the Adoption of Health Practices
Abstract: Overpopulation in developing countries threatens the economy, environment, food supply, and more. The inadequate utilization of modern contraceptives (MCs) in these regions has prompted extensive exploration of supply-side barriers, but there is a crucial gap in understanding demand-side obstacles, such as personal or partner opposition. Our research addresses this gap by focusing on the sociocultural factors influencing contraceptive decision-making in communities with low modern Contraceptive Prevalence Rates (mCPR). Utilizing the novel Structured Influence Process (SIP) framework, we examine - and quantitatively assess - how an individual's social relations and exposure to persuasive messaging, either in favor of or against MC use, jointly influence their decision to adopt or reject contraceptives.

Maria Warns, PhD Candidate, Engineering Sciences & Applied Mathematics, Northwestern University

Identifiability Analysis of Wastewater Surveillance and Public Health Data
Abstract: Wastewater-based surveillance is an increasingly available data stream which may improve calibration of disease models. Unlike traditional public health measures, wastewater samples reflect the entire population in a sewershed community since individuals infected with SARS-CoV-2 shed viral RNA in their stool regardless of symptomology. But the utility of these measurements to inform models is unknown and depends on both functional characteristics of the chosen disease model and quality of measurements. We compare the utility of wastewater surveillance data with traditional public health data for the calibration of parameters in compartmental disease models using structural and practical identifiability analysis.

Sign Up:

Sign up to present at one of our future Lightning Talk sessions. NICO Lightning Talks are open to graduate students, postdoctoral fellows, and visiting scholars.

Location:

In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/91878654083
Passcode: NICO24

About the Speaker Series:

Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems, data science and network science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.

NOVEMBER MEETING: Tuesday, November 26, 2024 at 5:20pm (US Central)

LOCATION:
In person: Chambers Hall, Lower Level
600 Foster Steet, Evanston Campus

AGENDA:
5:20pm - Meet and Greet
5:30pm - Talk by Stefan Pate, Interdisciplinary Biological Sciences Program
6:15pm - Q&A

SPEAKER:
Stefan Pate, PhD student, Interdisciplinary Biological Sciences Program, Northwestern University

ABSTRACT:

Tapping Underground Enzymatic Functions to Understand and Direct Metabolic Evolution
Characterizing “underground” functions of enzymes will aid our understanding of basic physiology & evolutionary biology, and will expand our bioengineering capabilities. Underground catalytic functions (1) make metabolic networks robust to loss-of-function mutations that compromise major fluxes, (2) figure prominently into hypotheses on the evolution of metabolic diversity, and (3) permit bioengineers to access novel chemistries with a tractable amount of modification to extant amino acid sequences. I'll share work on a machine learning model that predicts unobserved catalytic functions of enzymes, and  a method designed to efficiently generate multi-enzyme synthesis networks inclusive of predicted catalytic functions.

DATA SCIENCE NIGHTS are monthly talks on data science techniques or applications, organized by Northwestern University graduate students and scholars. Aspiring, beginning, and advanced data scientists are welcome! For more information: http://bit.ly/nico-dsn