Here the authors examined a population of Massachusetts marine isopods, seeking to classify them based on comparison of their morphology, movement, and seaweed preference compared to those of known species. In this process they found that they were most similar to Idotea balthica. The authors suggest that this knowledge combined with monitoring populations of marine biology such as these isopods in different physical and ecological areas can provide useful insight into the effects of climate change.
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Psychosocial impact of home-based learning among students during the COVID-19 Pandemic in Singapore
In this study, the authors surveyed a number of students in Singapore to determine how their experiences changed after the implementation of home-based learning during the COVID-19 pandemic.
Read More...Electromagnetic Radiation From Electronics Does Affect Plant Growth
Plants are the main producers of oxygen and organic compounds. Ensuring the health of these organisms is vital, as recent technologies could be damaging them. The purpose of this study was to find out if electromagnetic (EM) radiation from electronics affects plant growth.
Read More...Assessing Materials’ Short-term Effectiveness on Controlling Zebra Mussel (Dreissena polymorpha) Attachment
Zebra mussels are an aquatic invasive species. They attach to essential industrial structures and harm the native ecosystem, costing millions of dollars each year to control. This study explored the effectiveness of two nontoxic materials (Sharklet & Netminder) in combating zebra mussel attachment.
Read More...An Aqueous Solution Containing Soluble Substances From PVC Char Has No Effect on the Rate of Transformation in E. coli Cells
PVC is a widely used plastic that poses harmful health hazards when burned. In this study, the authors ask whether or not burned PVC (PVC char) affects bacterial transformation.
Read More...Machine learning on crowd-sourced data to highlight coral disease
Triggered largely by the warming and pollution of oceans, corals are experiencing bleaching and a variety of diseases caused by the spread of bacteria, fungi, and viruses. Identification of bleached/diseased corals enables implementation of measures to halt or retard disease. Benthic cover analysis, a standard metric used in large databases to assess live coral cover, as a standalone measure of reef health is insufficient for identification of coral bleaching/disease. Proposed herein is a solution that couples machine learning with crowd-sourced data – images from government archives, citizen science projects, and personal images collected by tourists – to build a model capable of identifying healthy, bleached, and/or diseased coral.
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