Browse Articles

Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

Read More...

Anticancer, anti-inflammatory, and apoptotic activities of MAT20, a poly-herbal formulation.

Kashyap Jha et al. | Mar 29, 2022

Anticancer, anti-inflammatory, and apoptotic activities of MAT20, a poly-herbal formulation.

Kashyap Jha et al. look at the formulation of MAT20, a crude extract of the moringa, amla, and tulsi leaves, as a potential complementary and alternative medicine. Using HeLa cells, they find MAT20 up-regulates expression of inflammation and cell cytotoxicity markers. Their data is important for understanding the anti-cancer and anti-inflammatory properties of MAT20.

Read More...

Effect of Fertilizer on Water Quality of Creeks over Time

Chen et al. | May 02, 2021

Effect of Fertilizer on Water Quality of Creeks over Time

Fertilizers are commonly used to improve agricultural yield. Unfortunately, chemical fertilizers can seep into drinking water, potentially harming humans and other forms of life. Here, the authors investigate the effect of fertilizer on the water quality of Saratoga Creek over time. They find that fertilizers can alter the acidity of the creek's water, which can be harmful to aquatic species, as well as increase the levels of nitrates temporarily.

Read More...

Specific Transcription Factors Distinguish Umbilical Cord Mesenchymal Stem Cells From Fibroblasts

Park et al. | Aug 16, 2019

Specific Transcription Factors Distinguish Umbilical Cord Mesenchymal Stem Cells From Fibroblasts

Stem cells are at the forefront of research in regenerative medicine and cell therapy. Two essential properties of stem cells are self-renewal and potency, having the ability to specialize into different types of cells. Here, Park and Jeong took advantage of previously identified stem cell transcription factors associated with potency to differentiate umbilical cord mesenchymal stem cells (US-MSCs) from morphologically similar fibroblasts. Western blot analysis of the transcription factors Klf4, Nanog, and Sox2 revealed their expression was unique to US-MSCs providing insight for future methods of differentiating between these cell lines.

Read More...

Search Articles

Search articles by title, author name, or tags

Clear all filters

Popular Tags

Browse by school level