In this article, the authors compare different resource-efficient farming methods for the vegetable Lactuca sativa. They compared hydroponics (solid growth medium with added nutrients) to aquaponics (water with fish waste to provide nutrients) and determined efficacy by measuring plant height over time. While both systems supported plant growth, the authors concluded that aquaponics was the superior method for supporting Lactuca sativa growth. These findings are of great relevance as we continue to find the most sustainable and efficient means for farming.
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The Effect of Sunglass Price on Ocular Exposure to Ultraviolet Radiation
Wearing sunglasses may offer protection against the negative health outcomes linked to exposure to ultraviolet waves. In this study, the authors test whether more expensive sunglasses offer better UV protection.
Read More...Purification of Water by Aloe
The authors test the ability of aloe vera gel to purify water of four separate contaminants. Aloe reduced the levels of copper, iron, and phosphate, but not nitrate. Potential applications of this purification system are discussed.
Read More...Which fruit peel helps retain the most soil moisture?
Here, the authors investigated the ability to use fruit peels to help soil retain moisture, a property that is essential to agriculture. Across a 96-hour observation period, orange, banana, and kiwi peel water emulsions were evaluated for their effects on soil moisture. They found that orange peels retained the most moisture, but banana and kiwi peels also offered improvements over their control sample.
Read More...The characterization of quorum sensing trajectories of Vibrio fischeri using longitudinal data analytics
Quorum sensing (QS) is the process in which bacteria recognize and respond to the surrounding cell density, and it can be inhibited by certain antimicrobial substances. This study showed that illumination intensity data is insufficient for evaluating QS activity without proper statistical modeling. It concluded that modeling illumination intensity through time provides a more accurate evaluation of QS activity than conventional cross-sectional analysis.
Read More...Correlation of Prominent Intelligence Type & Coworker Relations
Ashley Moulton & Joseph Rasmus investigate 9 controversial categories of intelligence as predicted by Multiple Intelligence Theory, originally proposed in the mid-1980s. By collecting data from 56 participants, they record that there may not actually be a correlation between these categorical types when it comes to workplace atmosphere and project efficiency.
Read More...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.
Read More...One-step photochemical crosslinking of native proteins is feasible in tyrosine-rich bovine serum albumin
In this study, the authors develop a new hydrogel using photochemical crosslinking with bovine serum albumin and methylene blue. They find that this new hydrogel has some useful applications!
Read More...Evolution of Neuroplastin-65
Human intelligence is correlated with variation in the protein neuroplastin-65, which is encoded by the NPTN gene. The authors examine the evolution of this gene across different animal species.
Read More...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
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