Asymptomatic individuals (agents) have the potential to influence epidemic spread significantly but are difficult to portray accurately. Current models either ignore realistic human behavior or spatial interactions. Here, we introduce an open-source framework that combines spatial agent-based modeling, real-world geospatial network construction, and an explicit representation of asymptomatic transmission within an SEIR model. Agents are initialized into demographic categories based on census data, including age distributions, employment status, and household structures. Each agent then follows realistic, individualized daily schedules derived from data-driven patterns. Agents navigate a graph-based network with nodes constructed from real-world locations connected by streets, walking, and cycling paths with edge weights representing travel times. Initially calibrated for COVID-19, our model is robust and readily adaptable to simulate other infectious diseases with minimal modifications. The model allows users to choose any U.S. city to deploy simulations. The model can be used to evaluate mitigation efforts like quarantine policies, targeted closures, and vaccination status. Preliminary results indicate that our novel coupling of realistic geospatial networks with an explicit asymptomatic transmission within a modified SEIR model that accounts for data-driven agent mobility substantially alters outbreak dynamics – yielding substantially improved alignment with empirical data compared to traditional approaches.

In recent decades, the rise of machine learning and artificial intelligence has reshaped the landscape of statistical and computational research. As these fields continue to evolve and overlap, understanding how research output has shifted over time can offer insights into the subfields driving innovation today and those projected to grow tomorrow. This project explores historical trends in statistical and computational research from the 1990s to 2024 by analyzing over 130,000 research papers from the arXiv preprint repository. The data was cleaned, categorized into statistical and computational domains, and analyzed to address three key questions: which fields have grown the most, how publication patterns have shifted over time, and which areas are likely to expand in the near future. Growth was measured using both year-over-year percentage change and relative proportions, while short-term projections were generated using time series models built with the skforecast package and LightGBM regressors. Results show that subfields such as Machine Learning and Artificial Intelligence have consistently led in publication output, with projected short-term growth in areas like Neural and Evolutionary Computing. These findings offer a snapshot of how the research landscape has developed over the past three decades and may help guide future academic focus, funding decisions, and institutional priorities.

Morrey's and Iwaniec's conjectures remain a challenge whose resolution will have an impact on the Harmonic Analysis as well as on the Calculus of Variations. This project turns the original conjecture into a weaker minimization problem. We illustrate how the steepest descent method can be used to solve this problem, and we illustrate this approach's implications on the original conjecture under certain assumptions.

Field-enhancing nanostructures can be utilized to augment optical field emission and the underlying process of electron rescattering, leading to brighter electron beams and shorter high-harmonic generation pulses. While these cathodes are typically illuminated with a single wavelength, further control can be achieved by adding a second harmonic where its relative phase and amplitude may be tuned for various applications. In this work, we analyze numerically the vacuum dynamics of electrons emitted from a cathode by a two-color laser. While maintaining a constant total illumination intensity, we demonstrate that higher electron emission energy, scattering energy, and the associated chirp can be achieved by carefully choosing the relative intensities and phases of the first and second harmonics.