In light of recent events, there has been a surge in discussions of defunding police. On one hand, policy that reduces police presence aims to reduce frequency of police violence. On the other hand, downsizing the police force triggers concerns of public safety and police response time. In this work, we use spatial analysis to examine the impact a reduced police force may have on response time. Modeling the transportation system of Chicago as a network, we simulate the response of police officers from stations to incidents. We then use this simulation to calculate the impacts of resource re-allocation from police to alternate responders. Using Chicago's large, open-source police incident response database, we use our simulation to predict how the response time changes subject to various crime and policing scenarios. Our model suggests that the current response time distribution can be maintained with a 30-60% reduction in police staffing levels if some incidents are re-allocated to alternate responders.

Predicting the chemical and physical processes occurring in Lithium-ion cells with high-fidelity electrochemical models is today a critical requirement to accelerate the design and optimization of battery packs for automotive and aerospace applications. One of the common issues associated with electrochemical models is the complexity of parameter identification, particularly when relying only on experimental data obtained via non-invasive techniques. This paper presents a novel approach to improve the common methods of parameter calibration that consists of matching the predicted terminal voltage to test data via optimization methods. The study is conducted for an NMC-graphite cell, modeled using a reduced order Extended Single Particle Model (ESPM). The proposed approach relies on using a large-scale Particle Swarm Optimization (PSO), modified by including a term that accounts for the parameter sensitivity information, such that the rate of convergence and robustness of the algorithm to obtain a consistent solution in the presence of uncertainties in the initial conditions are significantly improved.

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