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The Effect of Poverty on Mosquito-borne Illness Across the United States

Kar et al. | Feb 25, 2021

The Effect of Poverty on Mosquito-borne Illness Across the United States

Mosquito-borne diseases are a major issue across the world, and the objective for this project was to determine the characteristics that make some communities more susceptible to these diseases than others. The authors identified and studied characteristics that make communities susceptible to mosquito-borne diseases, including water in square miles, average temperature, population, population density, and poverty rates per county. They found that the population of a county is the best indicator of the prevalence of mosquito-borne diseases.

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The Effect of Various Liquid Mediums on the Transport of Photonic Energy and its Impact on the Quantum Efficiency of Photovoltaic Cells

Payra et al. | May 05, 2015

The Effect of Various Liquid Mediums on the Transport of Photonic Energy and its Impact on the Quantum Efficiency of Photovoltaic Cells

A photovoltaic cell (PV cell), or solar cell, converts the energy of light into electricity and is the basis for solar power. In order to increase the efficiency of PV cells, the authors in this study used common household items as photon transmissions mediums and measured their effects on the temperature and voltage output of the PV cells.

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Examination of the underlying chemical physics of the Mpemba effect in water and other liquids

Khan et al. | Apr 20, 2023

Examination of the underlying chemical physics of the Mpemba effect in water and other liquids
Image credit: D koi

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.

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Investigating the functionality of an Eco-Cooler made of plastic bottles

Tong et al. | Jul 22, 2026

Investigating the functionality of an Eco-Cooler made of plastic bottles
Image credit: Tong, Tong, and Migenes

In the study, the authors looked at an environmentally friendly alternative to A/C systems/cooling. They wanted to test the effectiveness of this cooling system called the Eco-Cooler as well as see if they could improve it. They found that the Eco-Cooler had minimal cooling, while their altered Eco-Cooler system had some cooling. This results shows the use of water helps cool the environment a lot more.

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Modelling effects of alkylamines on sea salt aerosols using the Extended Aerosols and Inorganics Model

Chang et al. | Apr 29, 2022

Modelling effects of alkylamines on sea salt aerosols using the Extended Aerosols and Inorganics Model

With monitoring of climate change and the evolving properties of the atmosphere more critical than ever, the authors of this study take sea salt aerosols into consideration. These sea salt aerosols, sourced from the bubbles found at the surface of the sea, serve as cloud condensation nuclei (CCN) and are effective for the formation of clouds, light scattering in the atmosphere, and cooling of the climate. With amines being involved in the process of CCN formation, the authors explore the effects of alkylamines on the properties of sea salt aerosols and their potential relevance to climate change.

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Monitoring drought using explainable statistical machine learning models

Cheung et al. | Oct 28, 2024

Monitoring drought using explainable statistical machine learning models

Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.

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