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Sri Lankan Americans’ views on U.S. racial issues are influenced by pre-migrant ethnic prejudice and identity

Gunawardena et al. | Apr 18, 2022

Sri Lankan Americans’ views on U.S. racial issues are influenced by pre-migrant ethnic prejudice and identity

In this study, the authors examined how Sri Lankan Americans (SLAs) view racial issues in the U.S. The main hypothesis is that SLAs, as a minority in the U.S., are supportive of the Black Lives Matter movement and its political goal, challenging the common notion that SLAs are anti-Black. The study found that a majority of SLAs believe the U.S. has systemic racism, favor BLM, and favor affirmative action. IT also found that Tamil SLAs have more favorable views of BLM and affirmative action than Sinhalese SLAs.

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The Effects of Barley Straw (Hordeum vulgare) Extract and Barley Straw Pellets on Algal Growth and Water Quality

McHargue et al. | Oct 06, 2020

The Effects of Barley Straw (Hordeum vulgare) Extract and Barley Straw Pellets on Algal Growth and Water Quality

Algal overgrowth often threatens to clog irrigation pipes and drinking water lines when left unchecked, as well as releasing possible toxins that threaten plant and human health. It is thus important to find natural, non-harmful agents that can decrease algal growth without threatening the health of plants and humans. In this paper, the authors test the efficacy of barely extract in either liquid or pellet form in decreasing algal growth. While their results were inconclusive, the experimental set-up allows them to investigate a wider range of agents as anti-algal treatments that could potentially be adopted on a wider scale.

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Effect of Increasing Concentrations of Cannabidiol (CBD) on Hatching, Survival and Development of Artemia salina

Rabbani et al. | Jul 27, 2020

Effect of Increasing Concentrations of Cannabidiol (CBD) on Hatching, Survival and Development of <em>Artemia salina</em>

Cannabidiol, or CBD, is a widely available over the counter treatment used for various medical conditions. However, CBD exerts its effects on the endocannabinoid system, which is involved in neural maturation, and could potentially have adverse effects on brain development. Here, the impact of CBD on the development of brine shrimp (Artemia salina) was assessed. Differences in dose responses were observed.

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Effect of environment factors on the expression of soluble PDE8A1 in E. coli

Jiang et al. | Oct 25, 2022

Effect of environment factors on the expression of soluble PDE8A1 in <em>E. coli</em>

PDE8, a type of phosphodiesterase (PDE), is proven to be crucial in various cellular activities and physiological activities by influencing second messenger systems. It is involved in a wide range of diseases, including Alzheimer’s disease and various heart diseases. However, there is limited information about PDE8 selective inhibitors. This work aimed to improve the solubility and yield of PDE8 in the supernatant by exploring suitable culture conditions, including temperatures and different additives.

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Use of yogurt bacteria as a model surrogate to compare household cleaning solutions

Shukla et al. | May 07, 2023

Use of yogurt bacteria as a model surrogate to compare household cleaning solutions
Image credit: CDC

While resources on the safety of household cleaning products are plentiful, measures of efficacy of these cleaning chemicals against bacteria and viruses remain without standardization in the consumer market. The COVID pandemic has exasperated this knowledge gap, stoking the growth of misinformation and misuse surrounding household cleaning chemicals. Arriving at a time dire for sanitization standardization, the authors of this paper have created a quantifying framework for consumers by comparing a wide range of household cleaning products in their efficacy against bacteria generated by a safe and easily replicable yogurt model.

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A comparative analysis of machine learning approaches for prediction of breast cancer

Nag et al. | May 11, 2021

A comparative analysis of machine learning approaches for prediction of breast cancer

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.

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Can Children Acquire Their Parents’ History of Fracture?

Boulis et al. | Sep 24, 2018

Can Children Acquire Their Parents’ History of Fracture?

While the genetic basis of hip fracture risk has been studied extensively in adults, it is not known whether parental history of bone fractures affects their children's fracture risk. In this article, the authors investigated whether a parental history of bone fractures influences the rate of fractures in their children. They found that adolescent children whose parents had a more extensive history of fractures were more likely to have a history of fractures themselves, suggesting that parents' medical histories may be an important consideration in future pediatric health research.

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A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Dey et al. | Oct 31, 2022

A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

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