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Lectin Properties Of Synthetically Produced Glucuronate, Alginate, And Related Boronates, Vanessa Angel
Lectin Properties Of Synthetically Produced Glucuronate, Alginate, And Related Boronates, Vanessa Angel
Honors Theses
In the nineteenth century, researchers discovered that some proteins had the ability to agglutinate red blood cells (Goldstein, 1980). These proteins were found mainly in the seeds of leguminous plants and were named phytohemagglutinins or hemagglutinins. Particular hemagglutinins were able to agglutinate red blood cells (RBCs) of a specific blood type. Now a days, these proteins are more widely known as Lectins. Lectins are proteinaceous macromolecules of nonimmune origin, capable of interacting with carbohydrates to form complexes (Goldstein, 1980). Lectins sources derive mainly from leguminous plants, animals, fruiting bodies of fungi, and bacteria. This research focuses on identifying the lectin …
The Relationship Between The Prevalence Of Hiv/Aids And Associated Socioeconomic And Behavioral Factors, Viktoria Kolpacoff
The Relationship Between The Prevalence Of Hiv/Aids And Associated Socioeconomic And Behavioral Factors, Viktoria Kolpacoff
Honors Theses
Human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) are a global epidemic affecting almost 40 million people. Studies show that the spread of HIV is associated with numerous and complex factors such as poverty, religious beliefs, hygiene practices, and gender inequalities. I analyzed the relationship between the prevalence of HIV and four socioeconomic and behavioral factors: per capita Gross Domestic Product, the Globalization Index, the Social Institutions and Gender Index, and literacy rates. I used logistic regression to regress the log-odds of becoming infected with HIV against the four associated factors and calculated an odds ratio for each …
Mobile Application For Biosensor Colorimetric Analysis, Eui Bin You
Mobile Application For Biosensor Colorimetric Analysis, Eui Bin You
Honors Theses
Inexpensive paper-based biosensors can be valuable screening tools to test for various illnesses, but it is often challenging to design them to produce a visual change that can easily be identified by untrained users. This research examines one method of compensating for the lack of distinct visual cues by developing and testing a mobile application that uses a machine learning algorithm (k-Nearest Neighbors) to analyze a picture of a sensor and determine whether it shows a positive or negative result. The machine learning algorithm was trained on a set of labeled sensor images and k-fold cross-validation was used to analyze …