arXiv subjects

Sean Elliott

Publications and source records attributed to Sean Elliott.

3 recordsLinked to original sources

arXiv2026

Critical Transit Infrastructure in Smart Cities and Urban Air Quality: A Multi-City Seasonal Comparison of Ridership and PM2.5

Public transit is a critical component of urban mobility and equity, yet mobility and air-quality linkages are rarely operationalized in reproducible smart-city analytics workflows. This study develops a transparent, multi-source monitoring dataset that integrates agency-reported transit ridership with ambient fine particulate matter PM2.5 from the U.S. EPA Air Quality System (AQS) for four U.S. metropolitan areas - New York City, Chicago, Las Vegas, and Phoenix, using two seasonal snapshots (March and October 2024). We harmonize heterogeneous ridership feeds (daily and stop-level) to monthly system totals and pair them with monthly mean PM2.5 , reporting both absolute and per-capita metrics to enable cross-city comparability. Results show pronounced structural differences in transit scale and intensity, with consistent seasonal shifts in both ridership and PM2.5 that vary by urban context. A set of lightweight regression specifications is used as a descriptive sensitivity analysis, indicating that apparent mobility-PM2.5 relationships are not uniform across cities or seasons and are strongly shaped by baseline city effects. Overall, the paper positions integrated mobility and environment monitoring as a practical smart-city capability, offering a scalable framework for tracking infrastructure utilization alongside exposure-relevant air-quality indicators to support sustainable communities and public-health-aware urban resilience.

physics.soc-ph↗

arXiv2020

Correlation Across Environments Encoded by Hippocampal Place Cells

The hippocampus is often attributed to episodic memory formation and storage in the mammalian brain; in particular, Alme et al. showed that hippocampal area CA3 forms statistically independent representations across a large number of environments, even if the environments share highly similar features. This lack of overlap between spatial maps indicates the large capacity of the CA3 circuitry. In this paper, we support the argument for the large capacity of the CA3 network. To do so, we replicate the key findings of Alme et al. and extend the results by perturbing the neural activity encodings with noise and conducting representation similarity analysis (RSA). We find that the correlations between firing rates are partially resistant to noise, and that the spatial representations across cells show similar patterns, even across different environments. Finally, we discuss some theoretical and practical implications of our results.

q-bio.NC↗

arXiv2020

Uncertainty on the Reproduction Ratio in the SIR Model

The aim of this paper is to understand the extreme variability on the estimated reproduction ratio $R_0$ observed in practice. For expository purpose we consider a discrete time stochastic version of the Susceptible-Infected-Recovered (SIR) model, and introduce different approximate maximum likelihood (AML) estimators of $R_0$. We carefully discuss the properties of these estimators and illustrate by a Monte-Carlo study the width of confidence intervals on $R_0$.

stat.ME↗