Because of the COVID-19 pandemic, people are missing important appointments because they are viewed as nonessential, possibly including children's pediatric dentist appointments. This study aims to determine how the COVID-19 pandemic has effected parents' willingness to allow children to visit pediatric dental practices and what safety measures would make them feel more comfortable visiting the dentist. The authors found a weak positive correlation between parents' unwillingness to allow their child to visit the dentist, however overall anxiety towards visiting the dentist during the pandemic was low.

The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.

Climate change is one of the most controversial challenges humans face. Here the authors investigate the dual role of clouds - to reflect incoming light away from the Earth and to reflect heat energy back toward the Earth's surface. They find that the amount of incident light energy and surface temperature decreases as the sky becomes cloudier. These results will inform longer-term studies that may compare against the amount of energy clouds reflect back toward the Earth.

Solar and radio frequency harvesters serve as a viable alternative energy source to batteries in many cases where the battery cannot be easily replaced. Using specifically designed circuit models, the authors quantify the reliability of different harvested energy sources to identify the most practical and efficient forms of renewable energy.

White pieces make the first move in chess games, and there are several opening strategies and consequent defense strategies that white and black pieces, respectively, can take . The author of this paper investigated whether taking a specific opening and defense strategy, as well as playing as white vs. black, can increase the chances of winning the game, by playing against various human and computer opponents.

Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.

In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.

In this study, the authors present proposed cryptographic controls for election sites with the hypothesis that this will mitigate risk and remediate vulnerabilities.

This paper presents findings on Carcharhinus leucas (bull shark) and Carcharhinus amblyrhynchos (grey reef shark) aggression towards humans at Beqa Adventure Divers in Shark Reef Marine Reserve, Fiji. We hypothesized that grey reef sharks would receive more prods than bull sharks because grey reef sharks are typically more aggressive than bull sharks. The results supported our hypothesis, as an individual grey reef shark received 2.44 prods on average per feed, while a bull shark had an average of 0.61. These findings are meaningful not only to the world’s general understanding of shark aggression, but also to human protection against grey reef sharks as well as public education on bull sharks and the conservation of the species.