Biomedical Engineering and Bioengineering Commons^™

Evaluating Human Eye Features For Objective Measure Of Working Memory Capacity, Yasasi Abeysinghe, Enkelejda Kasneci (Ed.), Frederick Shic (Ed.), Mohamed Khamis (Ed.)

Computer Science Faculty Publications

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an …

Ultrasensitive Tapered Optical Fiber Refractive Index, Erem Ujah, Meimei Lai, Gymama Slaughter

Electrical & Computer Engineering Faculty Publications

Refractive index (RI) sensors are of great interest for label-free optical biosensing. A tapered optical fiber (TOF) RI sensor with micron-sized waist diameters can dramatically enhance sensor sensitivity by reducing the mode volume over a long distance. Here, a simple and fast method is used to fabricate highly sensitive refractive index sensors based on localized surface plasmon resonance (LSPR). Two TOFs (l = 5 mm) with waist diameters of 5 µm and 12 µm demonstrated sensitivity enhancement at λ = 1559 nm for glucose sensing (5-45 wt%) at room temperature. The optical power transmission decreased with increasing glucose concentration due …

Making Sense Of Big (Kinematic) Data: A Comprehensive Analysis Of Movement Parameters In A Diverse Population, Naomi Wilma Nunis

University of the Pacific Theses and Dissertations

OBJECTIVE

The purpose of this study was to determine how kinematic, big data can be evaluated using computational, comprehensive analysis of movement parameters in a diverse population.

METHODS

Retrospective data was collected, cleaned, and reviewed for further analysis of biomechanical movement in an active population using 3D collinear resistance loads. The active sample of the population involved in the study ranged from age 7 to 82 years old and respectively identified as active in 13 different sports. Moreover, a series of exercises were conducted by each participant across multiple sessions. Exercises were measured and recorded based on 6 distinct biometric …

Breast Density Classification Using Deep Learning, Conrad Thomas Testagrose

UNF Graduate Theses and Dissertations

Breast density screenings are an accepted means to determine a patient's predisposed risk of breast cancer development. Although the direct correlation is not fully understood, breast cancer risk increases with higher levels of mammographic breast density. Radiologists visually assess a patient's breast density using mammogram images and assign a density score based on four breast density categories outlined by the Breast Imaging and Reporting Data Systems (BI-RADS). There have been efforts to develop automated tools that assist radiologists with increasing workloads and to help reduce the intra- and inter-rater variability between radiologists. In this thesis, I explored two deep-learning-based approaches …

Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson

Psychology Faculty Articles and Research

Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their reactions. To address this, we developed a paradigm using elements of performance magic to emulate future neurotechnologies. We led 59 participants to believe that a (sham) neurotechnological machine could infer their preferences, detect their errors, and reveal their deep-seated attitudes. The machine gave participants randomly assigned positive …

Chitosan Oligosaccharides As A Nanomaterial Platform: Biological Properties And Applications In The Biomedical And Pharmaceutical Fields, Muhamad Alif Razi

Makara Journal of Science

Chitosan oligosaccharides (COS) have been introduced as marine-derived biomaterials with potential health benefits and good water solubility properties. This study presents an overview of the promising nanomaterial platform for biomedical and pharmaceutical applications of COS. The health benefits of COS, primarily their antioxidant and protective effects, anti-inflammatory activity, antidiabetic properties, and cholesterol-lowering effects are discussed. Furthermore, the promising recent articles on specific topics such as drug delivery systems and nanobiomaterials, are highlighted

Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving …

The Rise Of Terrorism In Africa And What It Means For U.S. Policymakers, Bridget Mary Hughes

Master's Theses

This thesis utilizes three case studies to measure the rise of terrorism in Africa. This qualitative data leads the reader to one ultimate question: what does the rise in terrorism in Africa mean for the United States (U.S.) and U.S. policymakers, National Security academia, students in National Security, if anything at all? The answer is: if civilian and military compounds are being targeted by these violent extremists, as these three case studies demonstrate, it is my recommendation that U.S. policymakers cease sending troops to the African theater and, instead, allocate funding to the citizens and nonprofits of the countries whom …

Improving Detection And Classification Of Steady-State Visual Evoked Potentials In Brain-Computer Interfaces, Hadi Habibzadeh

Legacy Theses & Dissertations (2009 - 2024)

Brain-computer interfaces (BCIs) provide an alternative communication channel to send computer commands without requiring any voluntary muscle control. They benefit people with limited communication capabilities due to motor function deficits, spinal cord injuries, and neurological disorders. They may also have applications for healthy individuals.

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Infrastructure Development For Personalized Risk Prediction To Reduce Cardiovascular Disease In Childhood Cancer Survivors, Suman Shrestha

Dissertations and Theses (Open Access)

Although childhood cancer survivors have lengthy life expectancies, they run the risk of experiencing long-term health issues as a result of their treatment. The most frequent non-cancerous cause of morbidity and mortality for these survivors is cardiac disease. Radiation therapy (RT) has been linked in numerous cohort studies to a higher chance of developing a late cardiac disease in these survivors, and this risk rises with higher mean heart doses and increased RT exposure to larger cardiac volumes. Since, the heart is a heterogeneous organ made up of several distinct substructures, RT dose received by the entire heart does not …

Frequency Domain Diffuse Optics Spectroscopies For Quantitative Measurement Of Tissue Optical Properties, Sadhu Moka

USF Tampa Graduate Theses and Dissertations

Tissue oxygen saturation, blood flow and blood volume are physiological bio-markers of tissue health. Diffuse Optical Spectroscopy(DOS) and Diffuse Correlation Spectroscopy (DCS) are two complementary approaches to measure tissue oxygen saturation and blood flow respectively. Quantitative Diffuse Optical Spectroscopy (DOS) uses multi-spectral intensities of near-infrared light that have been modulated at RF frequencies to estimate static tissue optical properties and hence concentrations of oxygenated and de-oxygenated hemoglobin. Diffuse Correlation Spectroscopy estimates tissue dynamics - i.e., blood flow, by measuring temporal intensity auto-correlation function of backscattered light diffusing through the tissue. Conventionally, DCS instruments use coherent light sources with constant intensity. …

Reducing Instrumentation Barriers Of Diffuse Correlation Spectroscopy For Low-Cost Deep Tissue Blood Flow Monitoring, Arindam Biswas

USF Tampa Graduate Theses and Dissertations

Cerebral blood flow (CBF) is a good indicator of brain health as blood carries necessary nutrients, oxygen, and metabolic byproducts. Quantitative blood flow information can be used in several clinical and therapeutic applications such as stroke detection, measuring autoregulation, evaluating brain injury, or determining neuronal activity. Over the past few decades, light-based deep tissue hemodynamic detection modalities have become popular for non-invasive CBF measurements. In particular, noninvasive Diffuse Correlation Spectroscopy (DCS), has become a tool of choice for research and clinical applications due to its depth sensitivity (>1 cm), portability, validity against other technologies such as Magnetic Resonance Imaging …

Predicting Insulin Pump Therapy Settings, Riccardo L. Ferraro, David Grijalva, Alex Trahan

SMU Data Science Review

Millions of people live with diabetes worldwide [7]. To mitigate some of the many symptoms associated with diabetes, an estimated 350,000 people in the United States rely on insulin pumps [17]. For many of these people, how effectively their insulin pump performs is the difference between sleeping through the night and a life threatening emergency treatment at a hospital. Three programmed insulin pump therapy settings governing effective insulin pump function are: Basal Rate (BR), Insulin Sensitivity Factor (ISF), and Carbohydrate Ratio (ICR). For many people using insulin pumps, these therapy settings are often not correct, given their physiological needs. While …

Morton-Ordered Gpu Lattice Boltzmann Cfd Simulations With Application To Blood Flow, Gerald Gallagher, Fergal J. Boyle

Conference Papers

Computational fluid dynamics (CFD) is routinely used for numerically predicting cardiovascular-system medical device fluid flows. Most CFD simulations ignore the suspended cellular phases of blood due to computational constraints, which negatively affects simulation accuracy. A graphics processing unit (GPU) lattice Boltzmann-immersed boundary (LB-IB) CFD software package capable of accurately modelling blood flow is in development by the authors, focusing on the behaviour of plasma and stomatocyte, discocyte and echinocyte red blood cells during flow. Optimised memory ordering and layout schemes yield significant efficiency improvements for LB GPU simulations. In this work, comparisons of row-major-ordered Structure of Arrays (SoA) and Collected …

Design Of Novel Metalloenzymes And Investigation Of Protein-Metal Interactions, Alona Kulesha

Dissertations - ALL

Metalloproteins are the proteins that utilize metals or metal complexes as cofactors and exhibit a wide range of functions from oxygen transport and regulation of transcription to hydroxylation of alkanes and water splitting, even though they employ a limited set of metals and metal-binding ligands. The investigation of metalloprotein amino acid sequence, structure and function relationships can uncover the principles behind natural metalloprotein design and opens the possibility of their implication as scaffolds for the design of novel catalysts and biomaterials. Protein engineering is a set of techniques that allows to install new functionalities into existing proteins or to design …

Plasmonic Nanomaterials-Based Point-Of-Care Biosensors, Rohit Gupta

McKelvey School of Engineering Graduate Student Theses & Dissertations

Point-of-care (POC) biosensors, although rapid and easy-to-use, are orders magnitude less sensitive than laboratory-based tests. Further they are plagued by poor stability of recognition element thus limiting its widespread applicability in resource-limited settings. Therefore, there is a critical need for realizing stable POC biosensors with sensitivity comparable to gold-standard laboratory-based tests. This challenge constitutes the fundamental basis of this dissertation work– to expand access to quality and accurate biodiagnostic tools. At the heart of these solutions lies plasmonic nanoparticles which exhibit unique optical properties which are attractive for label-free and labelled biosensors.Firstly, we improve the stability and applicability of label-free …

Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biological understanding of complex diseases such as stroke and obesity is critical for the advancement of medicine. Further knowledge discovery can provide effective biomarkers to improve disease diagnosis and prognosis, identify driver mutations, predict individual genetic susceptibility for early prevention and effective disease management, and facilitate development of personalized drugs. Stroke is the second leading cause of death and long-term disability in the world. Thus, stroke management is a time-sensitive emergency. The initial hours after stroke onset map the trajectory of subsequent neurologic complications. Cerebral edema develops hours to days after acute ischemic stroke and may result in midline shift …

Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros

McKelvey School of Engineering Graduate Student Theses & Dissertations

Proton radiotherapy has the potential to treat tumors with better conformal dose distribution than competing modalities when the rapid dose falloff at the end of the proton-beam range is correctly aligned to the edge of the clinical target volume (CTV). However, its clinical potential is dependent on the accurate localization of the Bragg-peak position from predicted stopping-power ratio maps. The method that is most commonly used in today’s clinical practice for predicting stopping-power ratio (SPR) consists of a stoichiometric calibrationtechnique based on single-energy CT (SECT) for direct estimation of patient-specific SPR distribution from vendor-reconstructed Hounsfield Unit (HU) images. Unfortunately, this …

Development Of The Assessment Of Clinical Prediction Model Transportability (Apt) Checklist, Sean Chonghwan Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Clinical Prediction Models (CPM) have long been used for Clinical Decision Support (CDS) initially based on simple clinical scoring systems, and increasingly based on complex machine learning models relying on large-scale Electronic Health Record (EHR) data. External implementation – or the application of CPMs on sites where it was not originally developed – is valuable as it reduces the need for redundant de novo CPM development, enables CPM usage by low resource organizations, facilitates external validation studies, and encourages collaborative development of CPMs. Further, adoption of externally developed CPMs has been facilitated by ongoing interoperability efforts in standards, policy, and …

Advancing The Portability, Field Of View, And Spatiotemporal Resolution Of Multi-Parametric Photoacoustic Microscopy, Fenghe Zhong

McKelvey School of Engineering Graduate Student Theses & Dissertations

Capable of structural, functional, molecular, and metabolic imaging with high spatial resolution in vivo, photoacoustic microscopy (PAM) is an emerging tool in biomedical research. Further, recent advances in multi-parametric acquisition and analysis make PAM uniquely capable of simultaneously mapping the total concentration of hemoglobin (CHb), oxygen saturation of hemoglobin (sO2), and blood flow speed. However, there are multiple major limitations, including, the large footprint, low imaging speed, limited imaging contrast, and insufficient axial resolution, which impedance its applications in basic and translational research. In this dissertation, I presented potential solutions to overcome the limitations above.In the first part of this …

Development Of A Reverse Engineered, Parameterized, And Structurally Validated Computational Model To Identify Design Parameters That Influence American Football Faceguard Performance, William Ferriell

All Dissertations

Traumatic brain injury (TBI) continues to have the greatest incidence among athletes participating in American football. The headgear design research community has focused on developing accurate computational and experimental analysis techniques to better assess the ability of headgear technology to attenuate impacts and protect athletes from TBI. Despite efforts to innovate the headgear system, minimal progress has been made to innovate the faceguard. Although the faceguard is not the primary component of the headgear system that contributes to impact attenuation, faceguard performance metrics, such as weight, structural stiffness, and visual field occlusions, have been linked to athlete safety. To improve …

Role Of Deep Learning Techniques In Non-Invasive Diagnosis Of Human Diseases., Hisham Abouelseoud Elsayem Abdeltawab

Electronic Theses and Dissertations

Machine learning, a sub-discipline in the domain of artificial intelligence, concentrates on algorithms able to learn and/or adapt their structure (e.g., parameters) based on a set of observed data. The adaptation is performed by optimizing over a cost function. Machine learning obtained a great attention in the biomedical community because it offers a promise for improving sensitivity and/or specificity of detection and diagnosis of diseases. It also can increase objectivity of the decision making, decrease the time and effort on health care professionals during the process of disease detection and diagnosis. The potential impact of machine learning is greater than …

Utilization Of Finite Element Analysis Techniques For Adolescent Idiopathic Scoliosis Surgical Planning, Michael A. Polanco

Mechanical & Aerospace Engineering Theses & Dissertations

Adolescent Idiopathic Scoliosis, a three-dimensional deformity of the thoracolumbar spine, affects approximately 1-3% of patients ages 10-18. Surgical correction and treatment of the spinal column is a costly and high-risk task that is consistently complicated by factors such as patient-specific spinal deformities, curve flexibility, and surgeon experience. The following dissertation utilizes finite element analysis to develop a cost-effective, building-block approach by which surgical procedures and kinematic evaluations may be investigated. All studies conducted are based off a volumetric, thoracolumbar finite element (FE) model developed from computer-aided design (CAD) anatomy whose components are kinematically validated with in-vitro data. Spinal ligament stiffness …

A Protein-Based Therapeutic Combination For The Treatment Of Hard-To-Heal Wounds, Graham L. Strauss

USF Tampa Graduate Theses and Dissertations

Chronic wounds present many clinical challenges in relation to the successful treatment and closure of the damaged tissue. Most current treatment methods focused on one or two aspects to drive wound closure, while most chronic wounds are multifactorial environments with many of those dependencies relying on the termination of one another to effectively gain tissue construction, closure, and full skin thickness and composition. Natural wound healing processes allude to potential biologics that can impede the chronic breakdown of tissue, while restoring deposition of new tissue, and effectively leading to a healed wound. Proteases secreted by the body’s immune system lay …

Positive Rate-Dependent Action Potential Prolongation By Modulating Potassium Ion Channels, Candido Cabo

Publications and Research

Pharmacological agents that prolong action potential duration (APD) to a larger extent at slow rates than at the fast excitation rates typical of ventricular tachycardia exhibit reverse rate dependence. Reverse rate dependence has been linked to the lack of efficacy of class III agents at preventing arrhythmias because the doses required to have an anti-arrhythmic effect at fast rates may have pro-arrhythmic effects at slow rates due to an excessive APD prolongation. In this report we show that, in computer models of the ventricular action potential, APD prolongation by accelerating phase 2 repolarization (by increasing I_Ks) and decelerating …

Examining Metal Contents In Primary And Secondhand Aerosols Released By Electronic Cigarettes, Kashala Fabrice Kapiamba, Weixing Hao, Stephen Adom, Wenyan Liu, Yue-Wern Huang, Yang Wang

Chemistry Faculty Research & Creative Works

The usage of electronic cigarettes (ECs) has surged since their invention two decades ago. However, to date, the health effects of EC aerosol exposure are still not well understood because of insufficient data on the chemical composition of EC aerosols and the corresponding evidence of health risks upon exposure. Herein, we quantified the metals in primary and secondhand aerosols generated by three brands of ECs. By combining aerosol filter sampling and inductively coupled plasma mass spectrometry (ICP-MS), we assessed the mass of metals as a function of EC flavoring, nicotine concentration, device power, puff duration, and aging of the devices. …

Optimal Design Of Bacterial Carpets For Fluid Pumping, Minghao W. Rostami, Weifan Liu, Amy Buchmann, Eva Strawbridge, Longhua Zhao

Biology and Medicine Through Mathematics Conference

No abstract provided.

A Versatile Python Package For Simulating Dna Nanostructures With Oxdna, Kira Threlfall

Computer Science and Computer Engineering Undergraduate Honors Theses

The ability to synthesize custom DNA molecules has led to the feasibility of DNA nanotechnology. Synthesis is time-consuming and expensive, so simulations of proposed DNA designs are necessary. Open-source simulators, such as oxDNA, are available but often difficult to configure and interface with. Packages such as oxdna-tile-binding pro- vide an interface for oxDNA which allows for the ability to create scripts that automate the configuration process. This project works to improve the scripts in oxdna-tile-binding to improve integration with job scheduling systems commonly used in high-performance computing environments, improve ease-of-use and consistency within the scripts compos- ing oxdna-tile-binding, and move …

Exploring The Effects Of Varied Land Use On Elemental Concentrations Within Streams, Logan Jennings

Biological and Agricultural Engineering Undergraduate Honors Theses

It is well documented that human activity influences the chemistry of surrounding waters. As such, it is possible that there is a link between land use within a watershed and the chemical composition of the stream. The objectives of this study are to determine if varied land use does affect the concentrations of macronutrients and trace elements present in the streams of Northwest Arkansas, and if so, to determine what extent urban and agricultural development are responsible for these changes. Water samples were collected across 19 streams in the Northwest Arkansas region between January and March of 2022. Water samples …