Browse Articles

Plants, and all other multi-cellular organisms, develop through the coordinated action of many sets of genes. The authors here investigate the genes, in a class named KNOX, potentially responsible for organizing a certain part of Aquilegia (columbine) flowers called petal spurs. Through the technique Reverse Transcription-Polymerase Chain Reaction (RT-PCR), they find that certain KNOX genes are expressed non-uniformly in petal spurs, suggesting that they may be involved, perhaps in a cell-specific manner. This research will help guide future efforts toward understanding how many beautiful flowers develop their unique shapes.

Recent declines in the brook trout population of the Lake Champlain Basin have made the genetic screening of this and other trout species of utmost importance. In this study, the authors collected and analyzed 21 DNA samples from Lake Champlain Basin trout populations and performed a phylogenetic analysis on these samples using the cytochrome b gene. The findings presented in this study may influence future habitat decisions in this region.

Biomimicry is the practice of applying models and systems found in nature to improve the efficiency and usefulness of human technologies. In this study, the authors designed helicopter blades with tubercle structures similar to those found on the tails of humpback whales. The authors found that certain arrangements of these tubercle structures improved the windspeed and efficiency of a model helicopter.

Different songs can seem to evoke different emotions. Here the authors demonstrate that different songs can have a significant effect on the heart rate of listeners. A slower song slows heart rate, and a faster song increases it.

Environment affects the progression of life, especially at the cellular level. This study investigates multiple 3-dimensional growth environments, also known as scaffolds or hydrogels, and their effect on the growth of a type of cells called fibroblasts. These results suggest that a scaffold made of collagen and polyethylene glycol are favorable for cell growth. This research is useful for developing implantable devices to aid wound healing.

The authors looked at whether retinal features, specifically lens clarity, optic nerve cupping, and hyperreflective foci, can serve as biomarkers for neuro-ophthalmological diseases, which share pathological mechanisms with neurodegeneration and may indicate broader neurological risk. Using multimodal clinical data and machine learning, they investigated the potential of retinal imaging as a complementary diagnostic tool for more accurate and accessible detection of neurological disorders.

In this study, the authors examine the relationship between ESG (Environmental, Social, and Governance) factors on financial performance of Vietnamese media companies, as measured by ROA and ROE. They find that ESG is positively correlated with financial performance, as is sales growth. They also find that financial leverage is negatively correlated with ROA. Overall, this is a quality study, although the methods section requires more detail.

This article investigates whether induction heating can speed up static recrystallization in AISI 4130 steel compared with traditional radiant heating. It was found that induction-heated samples recrystallized faster, softened more quickly, and showed earlier microstructural changes like grain nucleation and pearlite spheroidization, suggesting induction heating could be a more efficient alternative for industrial metal heat treatments.

Here the authors investigated the potential of plant-derived smoke water to mitigate the negative impacts of abiotic stressors, such as heat, salinity, and water fluctuations, on the germination and growth of various agricultural crops. Their findings suggest that smoke water, specifically from buckwheat, pea, and radish, significantly improves plant resilience against drought and excessive water stress, offering a viable strategy to bolster food security in the face of climate change.

The global issue of water quality has led to the use of machine learning models, like ANN and SVM, to predict water potability. However, these models can be complex and resource-intensive. This research aimed to find a simpler, more efficient model for water quality prediction.