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Effects of Ocean Acidification on the Photosynthetic Ability of Chaetoceros gracilis in the Monterey Bay

Harvell et al. | Jan 16, 2020

Effects of Ocean Acidification on the Photosynthetic Ability of <i>Chaetoceros gracilis</i> in the Monterey Bay

In this article, Harvell and Nicholson hypothesized that increased ocean acidity would decrease the photosynthetic ability of Chaetoceros gracilis, a diatom prolific in Monterey Bay, because of the usually corrosive effects of carbonic acid on both seashells and cells’ internal structures. They altered pH of algae environments and measured the photosynthetic ability of diatoms over four days by spectrophotometer. Overall, their findings indicate that C. gracilis may become more abundant in Monterey Bay as the pH of the ocean continues to drop, potentially contributing to harmful algal blooms.

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Fire and dry grass: Effects of Pennisetum villosum on a California native, Nassella pulchra, in drought times

Chang et al. | Jan 23, 2022

Fire and dry grass: Effects of <i>Pennisetum villosum</i> on a California native, <i>Nassella pulchra</i>, in drought times

Invasive species pose a significant threat to many ecosystems, whether by outcompeting native species and disturbing food webs, or through increasing risks of natural disasters like flooding and wildfires. The ornamental grass species Pennisetum villosum R. Br. was previously identified by the California Invasive Plant Council as being potentially invasive; this experiment was conducted to determine if P. villosum displays characteristics of an invasive species when grown in a California chaparral environment. Reults found that in both conditions, the two species had similar germination rates, and that P. villosum grew significantly larger than N. pulchra for around 95 days.

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Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules

Sikdar et al. | Jan 10, 2023

Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules

Current drug discovery processes can cost billions of dollars and usually take five to ten years. People have been researching and implementing various computational approaches to search for molecules and compounds from the chemical space, which can be on the order of 1060 molecules. One solution involves deep generative models, which are artificial intelligence models that learn from nonlinear data by modeling the probability distribution of chemical structures and creating similar data points from the trends it identifies. Aiming for faster runtime and greater robustness when analyzing high-dimensional data, we designed and implemented a Hybrid Quantum-Classical Generative Adversarial Network (QGAN) to synthesize molecules.

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The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

Cahill et al. | Feb 15, 2021

The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

In healthy ecosystems, organisms interact in a relationship that helps maintain one another's existence. Stress can disrupt this interaction, compromising the survival of some of the members of such relationships. Here, the authors investigate the effect of stress on the interaction between anemones and their microbiome. Their study suggests that stress changes the composition of the surface microbiome of the anemone D. lineata, which is accompanied by an increase in mucus secretion. Future research into the composition of this stress-induced mucus might reveal useful antimicrobial properties.

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How does light affect the distribution of Euglena sp. and Tetrahymena pyriformis

Singh et al. | Mar 03, 2022

How does light affect the distribution of <em>Euglena sp.</em> and <em>Tetrahymena pyriformis</em>

In this article, the authors explored the locomotory movement of Euglena sp. and Tetrahymena pyriformis in response to light. Such research bears relevance to the migration and distribution patterns of both T. pyriformis and Euglena as they differ in their method of finding sustenance in their native environments. With little previous research done on the exploration of a potential response to photostimulation enacted by T. pyriformis, the authors found that T. pyriformis do not bias in distribution towards areas of light - unlike Euglena, which displayed an increased prevalence in areas of light.

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Do Attractants Bias the Results of Malaise Trap Research?

Martinez et al. | Jan 22, 2020

Do Attractants Bias the Results of Malaise Trap Research?

Malaise traps are commonly used to collect flying insects for a variety of research. In this study, researchers hypothesized the attractants used in these traps may create bias in insect studies that could lead to misinterpreted data. To test this hypothesis two different kinds of attractant were used in malaise traps, and insect diversity was assessed. Attractants were found to alter the dispersion of insects caught in traps. These findings can inform future malaise traps studies on insect diversity.

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Access to public parks, drinking fountains, and clean public drinking water in the Bay Area is not driven by income

Zaroff et al. | Jul 15, 2021

Access to public parks, drinking fountains, and clean public drinking water in the Bay Area is not driven by income

Access to green space—an area of grass, trees, or other vegetation set apart for recreational or aesthetic purposes in an urban environment—and clean drinking water can be unequally distributed in urban spaces, which are often associated with income inequality. Little is known about public drinking water and green space inequities in the Bay Area. For our study, we sought to understand how public park access, drinking fountain access, and the quality of public drinking water differ across income brackets in the Bay Area. Though we observed smaller-scale instances of inequalities, in the park distribution in the Bay Area as a whole, and in the Southern Bay’s water quality and park distribution, our results indicate that other factors could be influencing water quality, and park and fountain access in the Bay Area.

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Effect of Fertilizer on Water Quality of Creeks over Time

Chen et al. | May 02, 2021

Effect of Fertilizer on Water Quality of Creeks over Time

Fertilizers are commonly used to improve agricultural yield. Unfortunately, chemical fertilizers can seep into drinking water, potentially harming humans and other forms of life. Here, the authors investigate the effect of fertilizer on the water quality of Saratoga Creek over time. They find that fertilizers can alter the acidity of the creek's water, which can be harmful to aquatic species, as well as increase the levels of nitrates temporarily.

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Predicting college retention rates from Google Street View images of campuses

Dileep et al. | Jan 02, 2024

Predicting college retention rates from Google Street View images of campuses
Image credit: Dileep et al. 2024

Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.

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The comparative effect of remote instruction on students and teachers

Ng et al. | Jan 16, 2022

The comparative effect of remote instruction on students and teachers

In this study, high school students and teachers responded to a survey consisting of Likert-type scale, multiple-choice, and open-ended questions regarding various aspects of remote instruction. After analyzing the data collected, they found that remote learning impacted high school students academically and socially. Students took longer to complete assignments, and both students and teachers felt that students do not learn as much in remote learning compared to in-person instruction. However, most high school students demonstrated a comprehensive understanding of the topics, and an overall negative impact on students' grades was not detected.

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