Every week, some of our senior researchers in each department at ASDRP give public seminar presenting the current state of the field, and disseminating how their research at ASDRP fits into the broader context of the frontiers of modern science and engineering. Colloquia are public events, and anyone can join. Simply click the Google Calendar link to add the event to your calendar.
Department of Chemistry, Biochemistry & Physics
Fridays @ 8:00 - 9:00 PM PST
Friday, December 11, 2020
Role of Piperine as a bio enhancer in Thymoquinone encapsulated Nanolipid carrier.
Thymoquinone (TQ) is a constituent of black seed that has been found to have antioxidant, anti-inflammatory, and anti-cancer properties. Though it has considerable therapeutic potential, it is characterized by poor bioavailability, meaning that it is inefficient in reaching blood circulation when administered. A potential solution is loading TQ into a drug delivery system to transport TQ to its target. With the increased interest in the application of nanotechnology to medicinal chemistry, we utilized nanostructured lipid carriers to encapsulate TQ. Piperine (PP), an alkaloid isolated from Piper nigrum, has similar antioxidant and anti-inflammatory properties to those of TQ and has been found to enhance the bioavailability of other drugs when used in combination. The current research in the field on thymoquinone and its therapeutic effects will be discussed as well as the benefits of lipid-based drug delivery systems. Additionally, our laboratory progress in synthesizing the nanolipid carrier formulations and characterizing them using in vitro and in vivo methods to evaluate the bio-enhancing effects of PP on TQ will be presented.
Caitlyn T., Irvington High School
Renganathan Research Group
Department of Computer Science & Engineering
Wednesdays @ 8:00 - 9:00 PM PST
Wednesday, December 9, 2020
House Price Calculation With Image Analysis.
The real estate market plays a significant role within the economy and can dictate the quality of one’s life. For example, houses are infamously known for being US residents’ top expenses which can lead to poor living conditions or even bankruptcy. Many prospective home buyers rely on real estate agents and other property owners to dictate and provide the prices of houses which may lead to house price inflation, as the entire market is controlled by opinion. To find a stable and reliable method of calculating home prices, my team and I have been training a program using image analysis and machine learning. Using image classification, this model will be designed to analyze pictures to determine the cost of a house, whilst emulating an unbiased human. As of current, our model can accurately distinguish the various portions of a house. In the future, we plan to implement a cost calculating algorithm for each portion of the house to produce a sum that demonstrates how much a house genuinely costs.
Vibhu K., Alyson Jiang., Subhon G.
Subramaniam Research Group