Rhizopus stolonifer is a mold commonly found growing on bread that can cause many negative health effects when consumed. Preservatives are the well-known answer to this problem; however, many preservatives are not naturally found in food, and some have negative health effects of their own. We focused on honey as a possible solution because of its natural origin and self-preservation ability. We hypothesized that honey would decrease the growth rate of R. stolonifer . We evaluated the honey with a zone of inhibition (ZOI) test on agar plates. Sabouraud dextrose agar was mixed with differing volumes of honey to generate concentrations between 10.0% and 30.0%. These plates were then inoculated with a solution of spores collected from the mold. The ZOI was measured to determine antifungal effectiveness. A statistically significant difference was found between the means of all concentrations except for 20.0% and 22.5%. Our findings support the hypothesis as we showed a positive correlation between the honey concentration and growth rate of mold. By using this data, progress could be made on an all-natural, honey-based preservative.

This study aimed to assess the role of 25-hydroxyvitamin D3 solution, at varying concentrations, in protecting vertical transmission of diabetic-like phenotypes. We hypothesized that the highest concentration of vitamin D solution (55 ng/mL) would be most effective in having a protective role. The results indicated that the hypothesis was partially supported; overall, all three concentrations of the vitamin D solution administered to the flies reared on HSDs had a protective effect, to varying extents.

Mainstream cancer treatments, which include radiotherapy and chemotherapeutic drugs, are known to induce oxidative damage to healthy somatic cells due to the liberation of harmful free radicals. In order to avert this, physiological antioxidants must be complemented with external antioxidants. Here the authors performed a preliminary phytochemical screen to identify alkaloids, saponins, flavonoids, polyphenols, and tannins in all parts of the Amaranthus spinosus Linn. plant. This paper describes the preparation of this crude extract and assesses its antioxidant properties for potential use in complementary cancer treatment.

Here, seeking to better understand on the effects of social isolation during the COVID-19 pandemic, the authors used a survey during April and May of 2020 of participants primarily in Long Island, NY to assess the physical and mental health of the general population. They found negative impacts to physical health and increases in depressive symptoms and feelings of loneliness across all groups. More significant increases in negative mental health symptoms were observed in younger age groups and amongst women.

Here the authors test the ability of the bacterium Bacillus subtilis to degrade the polyethylene from plastic waste in various aquatic environments. They determined that degradation can occur among all samples while it was the highest in fresh water and lowest in ocean water.

This study investigated how fashion brand personalities are similar to people’s personalities and whether people may prefer a particular clothing brand based on their own personal traits. All together, Stevenson and Scott found that the Big Five Personality Factors are generally not related to participants’ preferred brand personalities. Generally, brands should consider different factors besides the Big Five Personality Factors for identifying potential customers.

Neural networks are used throughout modern society to solve many problems commonly thought of as impossible for computers. Fountain and Rasmus designed a convolutional neural network and ran it with varying levels of training to see if consistent, accurate, and precise changes or patterns could be observed. They found that training introduced and strengthened patterns in the weights and visualizations, the patterns observed may not be consistent between all neural networks.

Physical activity when performed regularly has beneficial effects on all systems of the body, including pulmonary functions. This study, conducted at Springdales School in Dhaula Kuan, New Delhi, aimed to determine the effect of sports and singing on the vital capacity (the maximum amount of air a person can expel from the lungs after a maximum inhalation), an important measure of pulmonary health.

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.

This study tested the proficiency of different concentrations of the antimicrobial sorbic acid to inhibit the probiotic Lactobacillus casei Shirota. It was hypothesized that sorbic acid’s use as a bacterial deterrent would also target this bacterial strain of Lactobacillus. The results supported the hypothesis, with the colony count of L. casei Shirota having significant decreases at all concentrations of sorbic acid. These results additionally suggest that even under the FDA sorbic acid restrictions of 0.03% concentration, damaging effects could be seen in L. casei Shirota.