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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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Methanotrophic bioremediation for the degradation of oceanic methane and chlorinated hydrocarbons

Lee et al. | Oct 08, 2021

Methanotrophic bioremediation for the degradation of oceanic methane and chlorinated hydrocarbons

Seeking an approach to address the increasing levels of methane and chlorinated hydrocarbons that threaten the environment, the authors worked to develop a novel, low-cost biotrickling filter for use as an ex situ method tailored to marine environments. By using methanotrophic bacteria in the filter, they observed methane degradation, suggesting the feasibility of chlorinated hydrocarbon degradation.

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Innovative use of recycled textile fibers in building materials: A circular economy approach

Gupta et al. | Feb 19, 2026

Innovative use of recycled textile fibers in building materials: A circular economy approach
Image credit: Gupta and Gupta

Textile waste from the fashion industry is a major environmental pollutant, but recycling waste into novel building material is a strategy to reduce the negative effects. This manuscript characterized five different binders that can be used to repurpose textile waste into bricks for construction purposes. Water-based glue, cement, white cement, plaster of Paris, and epoxy resin were mixed with shredded textile waste, and the mechanical characteristics and thermal insulation of each brick type were measured. Bricks with increased mechanical strength had the poorest thermal resistance, and the contrasting properties would suit different building purposes. This work provides a first step in generating recycled textile bricks for construction in a circular economy framework.

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Evaluating machine learning algorithms to classify forest tree species through satellite imagery

Gupta et al. | Mar 18, 2023

Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Image credit: Sergei A

Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

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