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Effects of spices on rice spoilage

Govindaraj et al. | Aug 15, 2022

Effects of spices on rice spoilage

In this work, based on centuries of history where spices have been used and thought to have antimicrobial properties that prolong the shelf life of food, the authors investigated if several spices used in Indian cooking could delay the spoilage of cooked white rice. Based on changed in appearance and smell, as well as growth on agar plates, they found that cinnamon was the most effective in delaying spoilage, followed by cumin, pepper, garlic, and ginger. Their findings suggest the ability to use spices rather than chemical food preservatives to prolong the shelf life of foods.

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Investigating KNOX Gene Expression in Aquilegia Petal Spur Development

Hossain et al. | Feb 03, 2014

Investigating KNOX Gene Expression in Aquilegia Petal Spur Development

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.

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Measuring Exoplanetary Radii Using Transit Photometry

Tang et al. | May 07, 2019

Measuring Exoplanetary Radii Using Transit Photometry

Studying exoplanets, or planets that orbit a star other than the Sun, is critical to a greater understanding the formation of planets and how Earth's solar system differs from others. In this study the authors analyze the transit light curves of three hot Jupiter exoplanets to ultimately determine if and how these planets have changed since their discovery.

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A comparative analysis of machine learning approaches for prediction of breast cancer

Nag et al. | May 11, 2021

A comparative analysis of machine learning approaches for prediction of breast cancer

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.

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Defying chemical tagging: inhomogeneities in the wide binary system HIP 34407/HIP 34426

Còdol et al. | Oct 05, 2023

Defying chemical tagging: inhomogeneities in the wide binary system HIP 34407/HIP 34426
Image credit: Pixabay

This assessed the hypothesis that stars in wide binary systems are chemically homogeneous because of their shared origin. Abundances of the HIP 34407/HIP 34426 binary were obtained by analyzing high-resolution spectra of the system. Discrepancies found in the system’s elemental abundances might be an indicator of the presence of rocky planets around this star. Thus, the differences found in chemical composition might demonstrate limitations in the assumptions of chemical tagging.

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A Novel Method for Assessment of Proprioception

Trevithick et al. | Jun 22, 2018

A Novel Method for Assessment of Proprioception

Trevithick & Park were interested in whether proprioception, the sense of the relative position of body parts and movement, differed between varsity and non-varsity athletes, as well as between the sport practiced. The authors found that there was no correlation between athleticism and better proprioception, but that dancers had superior proprioceptive abilities compared to those that practiced other sports.

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Comparing the Effects of Different Natural Products on Reducing Tumor Growth in a Drosophila Model

Ganesh et al. | May 31, 2020

Comparing the Effects of Different Natural Products on Reducing Tumor Growth in a <i>Drosophila</i> Model

In this work, the authors compared the effects of common natural products, including sesame, cinnamon, garlic, moringa and turmeric on tumor growth in Drosophila eyes. The data showed that these natural products cannot be used to reduce tumor growth once it has completely formed. However, the data suggested that some natural products can reduce cancer cell growth when tumors are treated early.

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