Browsing by Author "McCalla, Scott G."

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Advising caution in studying seasonal oscillations in crime rates
(2017-09) Dong, Kun; Yunbai, Cao; Wilber, Matthew; McCalla, Scott G.
Most types of crime are known to exhibit seasonal oscillations, yet the annual variations in the amplitude of this seasonality and their causes are still uncertain. Using a large collection of data from the Houston and Los Angeles Metropolitan areas, we extract and study the seasonal variations in aggravated assault, break in and theft from vehicles, burglary, grand theft auto, rape, robbery, theft, and vandalism for many years from the raw daily data. Our approach allows us to see various long term and seasonal trends and aberrations in crime rates that have not been reported before. We then apply an ecologically motivated stochastic differential equation to reproduce the data. Our model relies only on social interaction terms, and not on any exigent factors, to reproduce both the seasonality, and the seasonal aberrations observed in our data set. Furthermore, the stochasticity in the system is sufficient to reproduce the variations seen in the seasonal oscillations from year to year. Researchers should be very careful about trying to correlate these oscillations with external factors.
Chickensplash! Exploring the health concerns of washing raw chicken
(AIP Publishing, 2022-03) Carmody, Caitlin D.; Mueller, Rebecca C.; Grodner, Benjamin Michael; Chlumsky, Ondrej; Wilking, James N.; McCalla, Scott G.
The Food and Drug Administration recommends against washing raw chicken due to the risk of transferring dangerous food-borne pathogens through splashed drops of water. Many cooks continue to wash raw chicken despite this warning, however, and there is a lack of scientific research assessing the extent of microbial transmission in splashed droplets. Here, we use large agar plates to confirm that bacteria can be transferred from the surface of raw chicken through splashing. We also identify and create a phylogenetic tree of the bacteria present on the chicken and the bacteria transferred during splashing. While no food-borne pathogens were identified, we note that organisms in the same genera as pathogens were transferred from the chicken surface through these droplets. Additionally, we show that faucet height, flow type, and surface stiffness play a role in splash height and distance. Using high-speed imaging to explore splashing causes, we find that increasing faucet height leads to a flow instability that can increase splashing. Furthermore, splashing from soft materials such as chicken can create a divot in the surface, leading to splashing under flow conditions that would not splash on a curved, hard surface. Thus, we conclude that washing raw chicken does risk pathogen transfer and cross-contamination through droplet ejection, and that changing washing conditions can increase or decrease the risk of splashing.
Modelling radicalization: how small violent fringe sects develop into large indoctrinated societies
(2017-08) Short, Martin B.; McCalla, Scott G.; D'Orsogna, Maria R.
We model radicalization in a society consisting of two competing religious, ethnic or political groups. Each of the \'sects\' is divided into moderate and radical factions, with intra-group transitions occurring either spontaneously or through indoctrination. We also include the possibility of one group violently attacking the other. The intra-group transition rates of one group are modelled to explicitly depend on the actions and characteristics of the other, including violent episodes, effectively coupling the dynamics of the two sects. We use a game theoretic framework and assume that radical factions may tune \'strategic\' parameters to optimize given utility functions aimed at maximizing their ranks while minimizing the damage inflicted by their rivals. Constraints include limited overall resources that must be optimally allocated between indoctrination and external attacks on the other group. Various scenarios are considered, from symmetric sects whose behaviours mirror each other, to totally asymmetric ones where one sect may have a larger population or a superior resource availability. We discuss under what conditions sects preferentially employ indoctrination or violence, and how allowing sects to readjust their strategies allows for small, violent sects to grow into large, indoctrinated communities.
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
(The Royal Society, 2023-07) Liu, Yuxuan; McCalla, Scott G.; Schaeffer, Hayden
Particle dynamics and multi-agent systems provide accurate dynamical models for studying and forecasting the behaviour of complex interacting systems. They often take the form of a high-dimensional system of differential equations parameterized by an interaction kernel that models the underlying attractive or repulsive forces between agents. We consider the problem of constructing a data-based approximation of the interacting forces directly from noisy observations of the paths of the agents in time. The learned interaction kernels are then used to predict the agents’ behaviour over a longer time interval. The approximation developed in this work uses a randomized feature algorithm and a sparse randomized feature approach. Sparsity-promoting regression provides a mechanism for pruning the randomly generated features which was observed to be beneficial when one has limited data, in particular, leading to less overfitting than other approaches. In addition, imposing sparsity reduces the kernel evaluation cost which significantly lowers the simulation cost for forecasting the multi-agent systems. Our method is applied to various examples, including first-order systems with homogeneous and heterogeneous interactions, second-order homogeneous systems, and a new sheep swarming system.