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The Effects of Confinement on the Associative Learning of Gallus gallus domesticus

Jaworsky et al. | Dec 23, 2019

The Effects of Confinement on the Associative Learning of <em>Gallus gallus domesticus</em>

This study aimed to determine if confinement affects associative learning in chickens. The research found that the difference in time lapsed before chickens began to consume cottage cheese before and after confinement was significant. These results suggest that confinement distresses chickens, as it impairs associative learning without inducing confusion.

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Heavy Metal Contamination of Hand-Pressed Well Water in HuNan, China

Long et al. | Oct 20, 2019

Heavy Metal Contamination of Hand-Pressed Well Water in HuNan, China

Unprocessed water from hand-pressed wells is still commonly used as a source of drinking water in Chenzhou, the “Nonferrous Metal Village” of China. Long et al. conducted a study to measure the heavy metal contamination levels and potential health effects in this area. Water samples were analyzed through Inductively Coupled Plasma Optical Emission Spectroscopy (ICPOES) and the concentrations of 20 metal elements. Results showed that although none of the samples had dangerous levels of heavy metals, the concentrations of Al, Fe, and Mn in many locations substantially exceeded those suggested in the Chinese Drinking Water Standard and the maximum contaminant levels of Environmental Protection Agency (EPA). The authors have made an important discovery regarding the water safety in HuNan and their suggestions to install water treatment systems would greatly benefit the community.

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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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Do elders care about eHealth? A correlational study between eHealth consumption and literacy

Liang et al. | Jul 19, 2023

Do elders care about eHealth? A correlational study between eHealth consumption and literacy
Image credit: Liang and Sposa

As digital tools become more prevalent in medicine, the ability for individuals to understand and take actions based on what they read on the internet is crucial. eHealth literacy is defined as as the ability to seek, find, understand, and evaluate health information from electronic sources and apply the knowledge gained to addressing or solving a health problem. In general, Americans have low eHealth literacy rates. However, limited research has been conducted to understand the eHealth literacy level among older Chinese adult immigrants in the U.S. To determine the eHealth literacy of elderly Chinese immigrants, we sent out an eHealth survey and relevant computer skills survey using a modified version of the eHEALS (eHealth Literacy Scale) health literacy test. We hypothesized that elders who consumed more electronic health content would have a higher eHealth literacy score. The results of this survey showed that there was a positive correlation between the frequency of electronic health information consumption and the participant's eHealth literacy rate. In addition, the results of our computer literacy test show that the frequency of consumption and computer literacy are positively correlated as well. There is a strong positive correlation between the level of computer skills and eHealth literacy of participants. These results reveal possible steps individuals can take to reduce health misinformation and improve their own health by attaining, understanding, and taking action on health material on the internet.

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Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Choudhary et al. | Jul 26, 2021

Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.

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