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Physical Appearance and Its Effect on Trust

Ledesma et al. | Nov 09, 2020

Physical Appearance and Its Effect on Trust

Do different physical traits affect teenagers’ initial trust of an unknown person? Would they give greater trust to women and people of similar ethnicity? To test these hypotheses, the authors developed a survey to determine the sets of physical characteristics that affect a person's trustworthiness. They found that gender and expression were the main physical traits associated with how trustworthy an individual looks, while ethnicity was also important.

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Are alkaline spices the future of antibiotics?

Jani et al. | Jan 23, 2022

Are alkaline spices the future of antibiotics?

The authors experimented with several commonly available alkaline spices (turmeric, cayenne pepper, and cinnamon) to study their antimicrobial properties, hypothesizing that alkaline spices would have antimicrobial activity. Results showed a zone of inhibition of bacterial growth, with the largest zone of inhibition being around turmeric, followed by cayenne pepper, and the smallest around cinnamon. These results are impactful, as common alkaline spices generally do show antibacterial properties and both bacteriostatic and bactericidal effects correlated with degree of alkalinity.

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Trajectories Between Cigarette Smoking and Electronic Nicotine Delivery System Use Among Adults in the U.S.

Primack et al. | Apr 30, 2020

Trajectories Between Cigarette Smoking and Electronic Nicotine Delivery System Use Among Adults in the U.S.

In this study, the authors characterized the trends of cigarette use amongst people who do and don't use electronic nicotine delivery systems (or ENDS). This was done to help determine if the use of ENDS is aiding in helping smokers quit, as the data on this has been controversial. They found that use of ENDS among people either with or without previous cigarette usage were more likely to continue using cigarettes in the future. This is important information contributing to our understanding of ways to effectively (and not effectively) reduce cigarette use.

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Kinetic Monitoring and Fourier-Transform Infrared (FTIR) Spectroscopy of the Green Oxidation of (-)-Menthol to (-)-Menthone

Surapaneni et al. | Aug 06, 2020

Kinetic Monitoring and Fourier-Transform Infrared (FTIR) Spectroscopy of the Green Oxidation of (-)-Menthol to (-)-Menthone

In an effort to reduce the production of hazardous substances, green chemistry aims to make chemical processes more sustainable. One way to do so is changing solvents in chemical reactions. Here, authors assessed different “green” solvents on the oxidation of (-)-menthol to (-)-menthone using Fourier-transform infrared (FTIR) spectroscopy, optimizing the solvent system for this reaction.

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A Cloud-Enabled Communication Strategy for Wildfire Alerts

Vinaithirthan et al. | Jul 19, 2020

A Cloud-Enabled Communication Strategy for Wildfire Alerts

The traditional alert system in California consists of Wireless Emergency Alerts (WEAs), which lack location specificity, and sign-up-based technology which is limited by the number of sign ups. Those who do not have phones or have a silence option on their devices are most at risk from the current alert system. Here the authors developed cloud-enabled crisis connection for disaster alerts (CRISIS-CONNECT) to mitigate problems associated with the current alert system.

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The effect of sports on teenagers’ depression symptoms during the COVID-19 pandemic

Düzgezen et al. | Jun 12, 2023

The effect of sports on teenagers’ depression symptoms during the COVID-19 pandemic
Image credit: Izuddin Helmi Adnan

Here, seeking to identify the possible role of sports in helping teenagers navigate the troubles associated with societal changes during a pandemic, the authors surveyed 50 adolescents to collect Beck Depression Inventory scores. They found that 9 out of students with severe depressions did not do sports, while no significant relationship between depressive symptoms and either gender or place of exercise was observed.

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A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Ahmed et al. | Jun 09, 2023

A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Several studies have applied different machine learning (ML) techniques to the area of forecasting solar photovoltaic power production. Most of these studies use weather data as inputs to predict power production; however, there are numerous practical issues with the procurement of this data. This study proposes models that do not use weather data as inputs, but rather use past power production data as a more practical substitute to weather-based models. Our proposed models demonstrate a better, cheaper, and more reliable alternatives to current weather models.

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