Physical Sciences and Mathematics Commons^™

R Shiny's Self-Organizing Map, Zury Betzab Marroquin, Joshua Walsh, Trenton Wesley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Modeling Of Breast Cancer Cell Mcf-7 Growths Due To Curcumin Treatments, Widodo Samyono, Hildana Assefa, Kana Kassa

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Poliomyelitis Virus Vs Smallpox: An Ordinary Differential Equation Model Comparison, Kate Mcgough

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Modeling And Analysis Of Covid-19 Epidemic With Vaccination, Caitlin Seibel, Tina Huang, Jackson Reisman, Erika Johanna Martinez Salinas, Viswanathan Arunachalam, Moatlhodi Kgosimore, Anuj Mubayi, Padmanabhan Seshaiyer, Allen Bone Sehunelo

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Age-Dependent Ventilator-Induced Lung Injury, Quintessa Hay

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Using Adaptive Research Design To Define The Proper Methodology To Use A Data Peek For Power: Step By Step Process, Tom Wasser

Advances in Clinical Medical Research and Healthcare Delivery

When planning or conducting research in the hospital setting, often termed Real-World Environment (RWE), therapeutic assumptions and outcomes are often different than in the Randomized Clinical Trial (RCT) where medications, devices and therapies are tested and developed. This is because RWE research has a lack of experimental control, additional confounding due to patient complications and comorbid conditions, lack of pure patient selection and compliance with therapy in the patients being treated and many other factors as well. However, when RWE experiments are conducted, sample size determination using data from the RCT is common because that is the only data that …

Biotinylation As A Tool To Enhance The Uptake Of Small Molecules In Gram-Negative Bacteria, Ankit Pandeya, Ling Yang, Olaniyi Alegun, Chamikara Karunasena, Chad Risko, Zhenyu Li, Yinan Wei

Chemistry Faculty Publications

Antibiotic resistance is a major public health concern. The shrinking selection of effective antibiotics and lack of new development is making the situation worse. Gram-negative bacteria more specifically pose serious threat because of their double layered cell envelope and effective efflux systems, which is a challenge for drugs to penetrate. One promising approach to breach this barrier is the “Trojan horse strategy”. In this technique, an antibiotic molecule is conjugated with a nutrient molecule that helps the antibiotic to enter the cell through dedicated transporters for the nutrient. Here, we explored the approach using biotin conjugation with a florescent molecule …

Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Within condensed matter, single fluorophores are sensitive probes of their chemical environments, but it is difficult to use their limited photon budget to image precisely their positions, 3D orientations, and rotational diffusion simultaneously. We demonstrate the polarized vortex point spread function (PSF) for measuring these parameters, including characterizing the anisotropy of a molecule’s wobble, simultaneously from a single image. Even when imaging dim emitters (∼500 photons detected), the polarized vortex PSF can obtain 12 nm localization precision, 4°–8° orientation precision, and 26° wobble precision. We use the vortex PSF to measure the emission anisotropy of fluorescent beads, the wobble dynamics …

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Legacy Scout Tickets from Pure Oil Company

No abstract provided.

Investigating The Growth Of Algae Under Low Atmospheric Pressures For Potential Food And Oxygen Production On Mars, Leena M. Cycil, Elisabeth M. Hausrath, Douglas W. Ming, Christopher T. Adcock, James Raymond, Daniel Remias, Warren P. Ruemmele

Geoscience Faculty Research

With long-term missions to Mars and beyond that would not allow resupply, a self-sustaining Bioregenerative Life Support System (BLSS) is essential. Algae are promising candidates for BLSS due to their completely edible biomass, fast growth rates and ease of handling. Extremophilic algae such as snow algae and halophilic algae may also be especially suited for a BLSS because of their ability to grow under extreme conditions. However, as indicated from over 50 prior space studies examining algal growth, little is known about the growth of algae at close to Mars-relevant pressures. Here, we explored the potential for five algae species …

Deep Learning For Multiclass Classification, Predictive Modeling And Segmentation Of Disease Prone Regions In Alzheimer’S Disease, Maryamossadat Aghili

FIU Electronic Theses and Dissertations

One of the challenges facing accurate diagnosis and prognosis of Alzheimer’s Disease (AD) is identifying the subtle changes that define the early onset of the disease. This dissertation investigates three of the main challenges confronted when such subtle changes are to be identified in the most meaningful way. These are (1) the missing data challenge, (2) longitudinal modeling of disease progression, and (3) the segmentation and volumetric calculation of disease-prone brain areas in medical images. The scarcity of sufficient data compounded by the missing data challenge in many longitudinal samples exacerbates the problem as we seek statistical meaningfulness in multiclass …

Evaluating Changes In Visible To Short-Wave Infrared Spectral Reflectance Of Arctic Mosses In Response To Experimental Drying To Find The Best Predictors Of Moisture Content, Steven L. Unger

FIU Electronic Theses and Dissertations

Mosses are a dominant understory component in the Arctic and because of sparse canopy cover, contribute to spectral signals used in remote sensing estimates of various ecologically important characteristics such as productivity, phenology, and vegetation mapping. However, little is known about their contributions to community level spectra or how moisture content influences those spectral signals. Unlike vascular plants, mosses cannot actively regulate moisture content and are highly susceptible to desiccation. Previous research has shown that moss reflectance is sensitive to tissue moisture content. Here, a lab-controlled drying experiment was conducted to identify the best spectral predictors of moisture content of …

Non-Adiabatic Excited State Molecular Dynamics Using Ehrenfest And Modulated X-Ray Absorption In Titania, Alexander Matthew Meyer

LSU Doctoral Dissertations

This dissertation contains two separate sections aside from an introduction (Chapter 1): theory and methods (Chapter 2), time dependent density functional theory with Ehrenfest for excited state lifetimes in materials (Chapter 3), and simulated field modulated X-ray absorption in titania (Chapter 4).

Excited state lifetime in insulators and semiconductors can be difficult to compute using quantum chemistry due to their dense excited states. Non-radiative decay in these materials requires the use of non-adiabatic effects to dissipate energy through the means of electron-nuclear coupling such as coherent phonon generation. One method of approaching this challenge in these materials is using Ehrenfest …

Treatment Selection Using Prototyping In Latent-Space With Application To Depression Treatment, Akiva Kleinerman, Ariel Rosenfeld, David Benrimoh, Robert Fratila, Caitrin Armstrong, Joseph Mehltretter, Eliyahu Shneider, Amit Yaniv-Rosenfeld, Jordan Karp, Charles F. Reynolds, Gustavo Turecki, Adam Kapelner

Publications and Research

Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. While both paradigms have shown promising results, each of them suffers from important limitations. In this article, we propose a novel deep learning-based treatment selection approach that is shown to strike a balance between the two paradigms using latent-space prototyping. Our approach is specifically tailored for domains in which effective prototypes and sub-groups of patients are assumed to exist, but groupings relevant to the training objective are not …

Facilitating Heuristic Evaluation For Novice Evaluators, Anas Abulfaraj

College of Computing and Digital Media Dissertations

Heuristic evaluation (HE) is one of the most widely used usability evaluation methods. The reason for its popularity is that it is a discount method, meaning that it does not require substantial time or resources, and it is simple, as evaluators can evaluate a system guided by a set of usability heuristics. Despite its simplicity, a major problem with HE is that there is a significant gap in the quality of results produced by expert and novice evaluators. This gap has made some scholars question the usefulness of the method as they claim that the evaluation results are a product …

Experimental Analysis Of Gbm To Expand The Time Horizon Of Irish Electricity Price Forecasts, Conor Lynch, Christian O'Leary, Preetham Goving Kolar Sundareshan, Yavuz Akin

NIMBUS Articles

In response to the inherent challenges of generating cost-effective electricity consumption schedules for dynamic systems, this paper espouses the use of GBM or Gradient Boosting Machine-based models for electricity price forecasting. These models are applied to data streams from the Irish electricity market and achieve favorable results, relative to the current state-of-the-art. Presently, electricity prices are published 10 h in advance of the trade day of interest. Using the forecasting methodology outlined in this paper, an estimation of these prices can be made available one day in advance of the official price publication, thus extending the time available to plan …

Managing Incomplete Data In The Patient Discharge Summary To Support Correct Hospital Reimbursements, Fadi Naser Eddin

USF Tampa Graduate Theses and Dissertations

The patient discharge summary is a document that conveys the patient's story to other healthcare practitioners, external users, and, most importantly from a financial perspective, health insurers. A defect or incompleteness in the patient's discharge summary will result in delays in the collection process through denial of the entire or partial reimbursement claim or, in the best-case scenario, delay until the discharge summary issue is resolved. The purpose of this project is to address the issue of the incompleteness of discharge summary from the perspective of healthcare providers, with the goal of understanding, diagnosing, and intervening in the research problem. …

Selected Tropical Cyclone Satellite Analyses With An Emphasis On 37 Ghz Color Composite Imagery, Margaret Kieper

FIU Electronic Theses and Dissertations

This research expanded the understanding of the 37 GHz color composite imagery of tropical cyclones (using the Naval Research Lab Monterey image archive), by improved identification of precipitation types uniquely observed on this imagery, aided by creation of a conceptual model. This model distinguished between stratiform and convective rain, and identified the cyan color on this imagery as being warm rain from shallow and moderate convection, or "SAM." Patterns of SAM on this imagery uniquely identify tropical cyclone features: an early indicator of the onset of rapid intensification and early eyewall replacement cycles, both previously unobserved. These are identified by …

In-Vitro Micropropagation And Acclimatization Of Selected Florida Native Orchids, Andrew Mullin

FIU Electronic Theses and Dissertations

Florida is home to 106 native orchid species with the majority of them being endangered or critically imperiled, according to the International Union for Conservation of Nature (IUCN) and the Institute for Regional Conservation (IRC). In nature orchid germination rates are very low because they lack an endosperm, instead depending on an obligate relationship with a mycorrhizal fungus for nutrients. Most orchid seeds can be germinated in-vitro without the need for specific mycorrhizal fungi and therefore high rates of germination can be achieved. This study aims are a) to establish the fastest and most efficient in-vitro seed germination media and …

Soil Accretion And Mass Accumulation In A Scrub And Fringe Mangrove Forest In Biscayne Bay, Florida, Jessica A. Jacobs

USF Tampa Graduate Theses and Dissertations

This study estimated soil accretion and mass (organic carbon (OC), total nitrogen (TN), and total soil) accumulation in a scrub and fringe mangrove forest in Biscayne Bay, FL, to assess how forests of different morphologies (scrub vs. fringe) have kept pace with recently accelerating rates of sea-level rise. Accretion rates (AR) were estimated using the Constant Initial Concentration (CIC) model of lead-210 deposition and it was determined that the scrub forest has accreted at 1.3 ± 0.2 mm yr-1 over 75 years and the fringe forest at 2.8 ± 0.4 mm yr-1 over 92 years. The fringe forest estimate met …

Novel Approach To Integrate Can Based Vehicle Sensors With Gps Using Adaptive Filters To Improve Localization Precision In Connected Vehicles From A Systems Engineering Perspective, Abhijit Vasili

USF Tampa Graduate Theses and Dissertations

Research and development in Connected Vehicles (CV) Technologies has increased exponentially, with the allocation of 75 MHz radio spectrum in the 5.9 GHz band by the Federal Communication Commission (FCC) dedicated to Intelligent Transportation Systems (ITS) in 1999 and 30 MHz in the 5.9 GHz by the European Telecommunication Standards Institution (ETSI). Many applications have been tested and deployed in pilot programs across many cities all over the world.

CV pilot programs have played a vital role in evaluating the effectiveness and impact of the technology and understanding the effects of the applications over the safety of road users. The …

New Methods For The Synthesis, Activation, And Application Of Thioglycosides, Samira Escopy

Dissertations

From their ubiquitous presence in Nature to their vital roles in biology and medicine, carbohydrates (sugars or glycans) are essential molecules of life, which are made and/or utilized by every living organism. Our cells are coated with sugars that are involved in almost every biological process and defensive mechanism in our body. To mention some of their crucial biological functions, carbohydrates are essential source of energy, they participate in blood coagulation, immune defense, cell growth, cell-cell interaction, and anti-inflammatory processes. Understanding of glycan functions and structure is crucial for the development of vaccines and therapeutics. Producing complex carbohydrates in sufficient …

California Drought Outlooks Based On Climate Change Models’ Effects On Water Availability, Lauren Lynam, Thomas Piechota

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Future streamflow in California is evaluated based on eight climate projections models and the effects on water availability. The unimpaired projected streamflow for eleven California rivers, collected from Cal-Adapt, are compared with unimpaired historical flows (1950–2015) using eight climate model projections (2020–2099) identified as representative as possible future scenarios; Warm Dry RCP 4.5, Average RCP 4.5, Cool Wet RCP 4.5, Other RCP 4.5, Warm Dry RCP 8.5, Average RCP 8.5, Cool Wet RCP 8.5, and Other RCP 8.5. Projected drought deficits (or magnitudes), durations, and intensities are statistically tested against historical values to determine significance of differences between past streamflow …

Covariant Ergodic Quantum Markov Semigroups Via Systems Of Imprimitivity, Radhakrishnan Balu

Journal of Stochastic Analysis

No abstract provided.

Regional Expansion And Evaluation Of Potential Chemical Control For Invasive Apple Snails (Pomacea Maculata) In Southwest Louisiana, Julian M. Lucero

LSU Master's Theses

The integration of monitoring and chemical control is an efficient strategy for managing invasive apple snails, Pomacea maculata, in the rice (Oryza sativa L.) and crawfish systems of southwest Louisiana. However, their current distribution, expansion rates, and susceptibility to chemical control methods in this area are not well known. This study evaluated the expansion of P. maculata in southwest Louisiana and assessed potential chemical control for P. maculata among toxicity assays using various application rates. The effects of potential chemical control were also assessed on a non-target species, the red swamp crawfish (Procambarus clarkii). P. maculata …

Spatial Variations Of Stochastic Noise Properties In Gps Time Series, Xiaoxing He, Michael Simon Bos, Jean-Philippe Montillet, Rui Fernandes, Timothy I. Melbourne, Weiping Jiang, Wudong Li

Geological Sciences Faculty Scholarship

The noise in position time series of 568 GPS (Global Position System) stations across North America with an observation span of ten years has been investigated using solutions from two processing centers, namely, the Pacific Northwest Geodetic Array (PANGA) and New Mexico Tech (NMT). It is well known that in the frequency domain, the noise exhibits a power-law behavior with a spectral index of around −1. By fitting various noise models to the observations and selecting the most likely one, we demonstrate that the spectral index in some regions flattens to zero at long periods while in other regions it …

Interspecific And Local Variation In Tern Chick Diets Across Nesting Colonies In The Gulf Of Maine, Keenan Yakola, Adrian Jordaan, Stephen Kress, Paula Shannon, Michelle D. Staudinger

United States Geological Survey: Staff Publications

The Gulf of Maine, USA is home to four colonial co-nesting tern species: Least Tern (Sternula antillarum), Common Tern (Sterna hirundo), Arctic Tern (Sterna paradisaea), and the federally endangered Roseate Tern (Sterna dougallii). Over three decades of visual observations of chick provisioning were compiled for a comparative dietary study in the region, including the first detailed descriptions of Least and Roseate Tern chick diets. Three prey groups comprised the majority of chick diets among tern species between 1986–2017: hake (Urophycis spp. or Enchelyopus cimbrius) 28–37% frequency of occurrence (FO), sand lance …

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Legacy Scout Tickets from Pure Oil Company

No abstract provided.

Exploring Dft+U Parameter Space With A Bayesian Calibration Assisted By Markov Chain Monte Carlo Sampling, Pedram Tavadze, Reese Boucher, Guillermo Avendaño-Franco, Keenan X. Kocan, Sobhit Singh, Viviana Dovale-Farelo, Wilfredo Ibarra-Hernández, Matthew B. Johnson, David S. Mebane, Aldo H. Romero

Faculty & Staff Scholarship

The density-functional theory is widely used to predict the physical properties of materials. However, it usually fails for strongly correlated materials. A popular solution is to use the Hubbard correction to treat strongly correlated electronic states. Unfortunately, the values of the Hubbard U and J parameters are initially unknown, and they can vary from one material to another. In this semi-empirical study, we explore the U and J parameter space of a group of iron-based compounds to simultaneously improve the prediction of physical properties (volume, magnetic moment, and bandgap). We used a Bayesian calibration assisted by Markov chain Monte Carlo …

Learning From Mistakes - A Framework For Neural Architecture Search, Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie

Machine Learning Faculty Publications

Learning from one's mistakes is an effective human learning technique where the learners focus more on the topics where mistakes were made, so as to deepen their understanding. In this paper, we investigate if this human learning strategy can be applied in machine learning. We propose a novel machine learning method called Learning From Mistakes (LFM), wherein the learner improves its ability to learn by focusing more on the mistakes during revision. We formulate LFM as a three-stage optimization problem: 1) learner learns; 2) learner re-learns focusing on the mistakes, and; 3) learner validates its learning. We develop an efficient …