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A common form of Acne is caused by a species of bacterium called Cutibacterium acnes. By using a predictive algorithm and structural analysis, the authors identified 5 small molecules with high affinity to growth factors in Catibacterium acnes. This has potential implications for supplemental skincare products.

In this study, the authors engineer a cost-effective and bio-friendly water purification system using limestone, denitrifying bacteria, and sulfate-reducing bacteria. They evaluated its efficacy with samples from Eastern PA industrial sites.

The authors investigate the effects of popular media consumption on the public's opinion on nuclear power. They find that regardless of education level or positive/negative bias of the article, participants are willing to modify their opinions on nuclear power after consuming a single article.

We conducted this research as our start-up's research that addresses the problem of biogas production in cow-dense regions like India. We hypothesized that the thermophilic temperature (45-60^oC) would increase biogas production. The production process is much faster and more abundant at temperatures around 55-60^oC.

The authors analyzed the heat transfer of different containers in the microwave aiming to identify the most optimal material of container to reduce heating time.

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.