Physical Sciences and Mathematics Commons^™

Aptamer-Based Voltammetric Biosensing For The Detection Of Codeine And Fentanyl In Sweat And Saliva, Rosa Lashantez Cromartie

FIU Electronic Theses and Dissertations

Despite the many governmental and medicinal restrictions created to combat the opioid epidemic in the United States, opioid abuse and overdose rates continue to rise. The development of an aptamer-based voltammetric sensor and biosensor is described in this dissertation. The aim was to develop a low-cost, sensitive, and specific aptamer-based sensor for on-site, label-free determination of codeine and fentanyl in biological fluids. To do this, the surfaces of screen-printed carbon electrodes (SPCE) were modified with gold nanoparticles (AuNPs), followed by the addition of single-stranded DNA aptamers. These were covalently bound to the electrode surface. Operations of the sensors were collected …

A Study Of Magnetism And Possible Mixed-State Superconductivity In Phosphorus-Doped Graphene, Julian E. Gil Pinzon

FIU Electronic Theses and Dissertations

Evidence of superconducting vortices, and consequently mixed-state superconductivity, has been observed in phosphorus-doped graphene at temperatures as high as 260 K. The evidence includes transport measurements in the form of resistance versus temperature curves, and magnetic measurements in the form of susceptibility and magnetic Nernst effect measurements. The drops in resistance, periodic steps in resistance, the appearance of Nernst peaks and hysteresis all point to phosphorus-doped graphene having a broad resistive region due to flux flow as well as a Berezinskii-Kosterlitz-Thouless (BKT) transition at lower temperatures.

The observation of irreversible behavior in phosphorus-doped graphene under the influence of a thermal …

Development Of A Real-Time Single-Lead Single-Beat Frequency-Independent Myocardial Infarction Detector, Harold Martin

FIU Electronic Theses and Dissertations

The central aim of this research is the development and deployment of a novel multilayer machine learning design with unique application for the diagnosis of myocardial infarctions (MIs) from individual heartbeats of single-lead electrocardiograms (EKGs) irrespective of their sampling frequencies over a given range. To the best of our knowledge, this design is the first to attempt inter-patient myocardial infarction detection from individual heartbeats of single-lead (lead II) electrocardiograms that achieves high accuracy and near real-time diagnosis. The processing time of 300 milliseconds to a diagnosis is just at the time range in between extremely fast heartbeats of around 300 …