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A small town with low crime rates and relatively high education levels usually gives the perception of a safe and comfortable community. This study explored the connection between this perception, as defined by public opinion, and reality, as defined by US Census and FBI crime data.

Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.

Gun violence has been a serious issue in the South Side of Chicago for a long time. To intervene, regulators have passed legislation they hoped to curb -if not completely eradicate- the issue. However, there is little analysis done on how effective the various laws have been at reducing gun violence. Here the authors explore the association between firearm purchase laws passed between 1993-2018 and the incidence of gun homicide in Chicago's South Side. Their analysis suggests that some laws have been more effective than others, while some might have exacerbated the issue. However, they do not consider other contributing factors, which makes it difficult to prove causation without further investigation.

In this study, the authors develop an architecture to implement in a cloud-based database used by law firms to ensure confidentiality, availability, and integrity of attorney documents while maintaining greater efficiency than traditional encryption algorithms. They assessed whether the architecture satisfies necessary criteria and tested the overall file sizes the architecture could process. The authors found that their system was able to handle larger file sizes and fit engineering criteria. This study presents a valuable new tool that can be used to ensure law firms have adequate security as they shift to using cloud-based storage systems for their files.

In this work, the authors investigate the accuracy with which two different population growth models can predict population growth over time. They apply the Malthusian law or Logistic law to US population from 1951 until 2019. To assess how closely the growth model fits actual population data, a least-squared curve fit was applied and revealed that the Logistic law of population growth resulted in smaller sum of squared residuals. These findings are important for ensuring optimal population growth models are implemented to data as population forecasting affects a country's economic and social structure.

Here, the authors considered the stretching behavior of rubber bands by exposing the rubber bands to increasing loads and measuring their stretch response. They found that a linear stretch response was observed for intermediate loading steps, but this behavior was lost at lower or higher loads, deviating from Hooke's Law. The authors suggest that studies such as these can be used to evaluate other visco-elastic structures.

Dynamic viscosity is a quantity that describes the magnitude of a fluid’s internal friction or thickness. Traditionally, scientists measure this quantity by either calculating the terminal velocity of a falling sphere or the time a liquid takes to flow through a capillary tube. However, they have yet to conduct much research on finding this quantity through viscous damped simple harmonic motion. The present study hypothesized that the relationship between the dynamic viscosity and the damping coefficient is positively correlated.

In this experiment, the authors modify the heat equation to account for imperfect insulation during heat transfer and compare it to experimental data to determine which is more accurate.

Counterintuitive in nature, the Mpemba effect asserts that hot liquid freezes faster than cold liquid. While noted throughout history by scientific minds like Aristotle, the phenomenon remains in contention with varying hypotheses for the effect proposed alongside the effect’s rise in popularity. Contributing to the research efforts surrounding the Mpemba effect, the authors in this article explore the effect in different liquids ranging in physical properties and intermolecular forces to determine potential parameters attributable to producing the Mpemba effect.

The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.