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A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

A machine learning approach for abstraction and reasoning problems without large amounts of data

While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.

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An Exploration of a Honey-Ginger Supplement as an Antimicrobial Agent

Phillips et al. | Jul 10, 2016

An Exploration of a Honey-Ginger Supplement as an Antimicrobial Agent

Due to the increase in antimicrobial resistance, alternative medicinal therapies are being explored. Studies have shown that honey and ginger alone have antimicrobial effects on the genera Staphylococcus and Escherichia, including S. epidermidis and E. coli. The authors of this study tested whether a honey-ginger supplement, Jengimielâ„¢, could be used as an antimicrobial agent against S. epidermidis and E. coli K-12.

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Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Dao et al. | Jun 27, 2021

Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Engineered bacteria that degrade oil are currently being considered as a safe option for the treatment of oil spills. For this approach to be successful, the bacteria must effectively express oil-degrading genes they uptake as part of an external genoming vehicle called a "plasmid". Using a computational approach, the authors investigate plasmid-bacterium compatibility to find pairs that ensure high levels of gene expression.

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The effects of early probiotic supplementation on the germination of Arabidopsis thaliana

Gambino et al. | Oct 25, 2020

The effects of early probiotic supplementation on the germination of <em>Arabidopsis thaliana</em>

The use of fertilizers is associated with an increase in soil degradation, which is predicted to lead to a decrease in crop production within the next decade. Thus, it is critical to find solutions to support crop production to sustain the robust global population. In this study, the authors investigate how probiotic bacteria, like Rhizobium leguminosarum, Bacillus subtilis and Pseudomonas fluorescens, can impact the growth of Arabidopsis thaliana when applied to the seeds.They hypothesized that solutions with multiple bacterial species compared to those with only a single bacterial species would promote seed germination more effectively.

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Bacterial Richness of Soil Samples from Southern New Hampshire

Chalasani et al. | Sep 21, 2016

Bacterial Richness of Soil Samples from Southern New Hampshire

Advancement in DNA sequencing technology has greatly increased our understanding about the role of bacteria in soil. The authors of this study examine the microbial content of soil samples taken from three locations in southern New Hampshire with varying pH and plant composition.

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