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Modeling the effects of acid rain on bacterial growth

Shah et al. | Nov 17, 2020

Modeling the effects of acid rain on bacterial growth

Acid rain has caused devastating decreases in ecosystems across the globe. To mimic the effect of acid rain on the environment, the authors analyzed the growth of gram-negative (Escherichia coli) and gram-positive (Staphylococcus epidermidis) bacteria in agar solutions with different pH levels. Results show that in a given acidic environment there was a significant decrease in bacterial growth with an increase in vinegar concentration in the agar, suggesting that bacterial growth is impacted by the pH of the environment. Therefore, increased levels of acid rain could potentially harm the ecosystem by altering bacterial growth.

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Role of Environmental Conditions on Drying of Paint

Aggarwal et al. | Feb 20, 2021

Role of Environmental Conditions on Drying of Paint

Reducing paint drying time is an important step in improving production efficiency and reducing costs. The authors hypothesized that decreased humidity would lead to faster drying, ultraviolet (UV) light exposure would not affect the paint colors differently, white light exposure would allow for longer wavelength colors to dry at a faster rate than shorter wavelength colors, and substrates with higher roughness would dry slower. Experiments showed that trials under high humidity dried slightly faster than trials under low humidity, contrary to the hypothesis. Overall, the paint drying process is very much dependent on its surrounding environment, and optimizing the drying process requires a thorough understanding of the environmental factors and their interactive effects with the paint constituents.

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Differential privacy in machine learning for traffic forecasting

Vinay et al. | Dec 21, 2022

Differential privacy in machine learning for traffic forecasting

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.

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Music's Effect on Dogs' Heart Rates

Aubin et al. | Oct 03, 2017

Music's Effect on Dogs' Heart Rates

Music can affect the behavior of humans and other animals. In this study, the authors studied five types of music with different tempos and demonstrated how each one affected dogs' heart rates.

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Automated dynamic lighting control system to reduce energy consumption in daylight

Jagannathan et al. | Jun 17, 2024

Automated dynamic lighting control system to reduce energy consumption in daylight
Image credit: Jagannathan and Mehrotra 2024

Buildings, which are responsible for the majority of electricity consumption in cities like Dubai, are often exclusively reliant on electrical lighting even in the presence of daylight to meet the illumination requirements of the building. This inefficient use of lighting creates potential to further optimize the energy efficiency of buildings by complementing natural light with electrical lighting. Prior research has mostly used ballasts (variable resistors) to regulate the brightness of bulbs. There has been limited research pertaining to the use of pulse width modulation (PWM) and the use of ‘triodes for alternating current’ (TRIACs). PWM and TRIACs rapidly stop and restart the flow of current to the bulb thus saving energy whilst maintaining a constant illumination level of a space. We conducted experiments to investigate the feasibility of using TRIACs and PWM in regulating the brightness of bulbs. We also established the relationship between power and brightness within the experimental setups. Our results indicate that lighting systems can be regulated through these alternate methods and that there is potential to save up to 16% of energy used without affecting the overall lighting of a given space. Since most energy used in buildings is still produced through fossil fuels, energy savings from lighting systems could contribute towards a lower carbon footprint. Our study provides an innovative solution to conserve light energy in buildings during daytime.

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Beeing sustainable: Honey as a bioindicator for pollution

Donnellan et al. | Oct 06, 2021

Beeing sustainable: Honey as a bioindicator for pollution

In this study, Donnellan and colleagues investigated how environmental pollution may be affecting honey samples from Chicago apiaries. They found no significant correlation between heavy metal concentration in honey to distance from local industries, suggesting a minimal effect of proximity to industrial pollution on honey contamination.

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