Engineering Commons^™

Active Deep Learning Method To Automate Unbiased Stereology Cell Counting, Saeed Alahmari

USF Tampa Graduate Theses and Dissertations

Cell quantification in histopathology images plays a significant role in understanding and diagnosing diseases such as cancer and Alzheimers. The gold-standard for quantifying cells in tissue sections is the unbiased stereology approach. Unfortunately, in unbiased stereology current practices rely on a well-trained human to manually count hundreds of cells in microscopy images. However, this human-based manual approach is time-consuming, labor-intensive, subject to human errors, recognition bias, fatigue, variable training, poor reproducibility, and inter-observer error. Thus, the lack of high-throughput technology for automating unbiased stereology analyses remains a major obstacle to further progress in a wide range of neuroscience and cancer …

Hyaluronic Acid Coated Targeted Lipid Micellar Nanoparticle As A Delivery Vehicle For Lapatinib And Ketoconazole In Egfr Mutated Lung Cancer, Nadia Tasnim Ahmed

USF Tampa Graduate Theses and Dissertations

Background: According to the American Cancer Society, lung cancer was accountable for over 142,000 deaths in the USA in 2019. Common mutations related to lung cancer mainly occur in TP53, EGFR, and KRAS genes. Lapatinib is a small molecule tyrosine kinase inhibitor which acts reversibly on both epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2). Overexpression of EGFR leads to increased production and signaling of proteins that cause upregulation of cellular proliferation, cholesterol synthesis and resistance to apoptosis. Ketoconazole is an imidazole antifungal agent which works principally by inhibiting the enzyme cytochrome P450 14α-demethylase (CYP51A1) …

In Vivo Biosynthesis Of Inorganic Nanomaterials Using Eukaryotes - A Review, Ashiqur Rahman, Julia Lin, Francisco E. Jaramillo, Dennis A. Bazylinski, Clayton Jeffryes, Si Amar Dahoumane

Life Sciences Faculty Research

Bionanotechnology, the use of biological resources to produce novel, valuable nanomaterials, has witnessed tremendous developments over the past two decades. This eco-friendly and sustainable approach enables the synthesis of numerous, diverse types of useful nanomaterials for many medical, commercial, and scientific applications. Countless reviews describing the biosynthesis of nanomaterials have been published. However, to the best of our knowledge, no review has been exclusively focused on the in vivo biosynthesis of inorganic nanomaterials. Therefore, the present review is dedicated to filling this gap by describing the many different facets of the in vivo biosynthesis of nanoparticles (NPs) using living eukaryotic …

Toward Precision Medicine With Nanopore Technology, Trang Andrea Vu

Theses and Dissertations

Currently, when patients are diagnosed with cancer, they often receive a treatment based on the type and stage of the tumor. However, different patients may respond to the same treatment differently, due to the variation in their genomic alteration profile. Thus, it is essential to understand the effect of genomic alterations on cancer drug efficiency and engineer devices to monitor these changes for therapeutic response prediction. Nanopore-based detection technology features devices containing a nanometer-scale pore embedded in a thin membrane that can be utilized for DNA sequencing, biosensing, and detection of biological or chemical modifications on single molecules. Overall, this …

"Thinking Across Borders." 13th Annual Research Week: Event Proceedings, Office Of Research And Sponsored Projects Operations

Excellence Summit (Research Week) Archived Proceedings

Poster and podium presentations of research by students and faculty of University of the Incarnate Word.

Smart Environments For Assisted Living: A Multidisciplinary Collaboration In Engineering And Architecture Education, Adriana Rios-Santiago, Anabel Pineda-Briseno, Jesus A. Gonzalez-Rodriguez, Uriel Saul Huerta

Manufacturing & Industrial Engineering Faculty Publications

This paper presents a description of a collaborative project based on the integration of technology development in the built environment for assisted living. The multidisciplinary collaboration is developed as a cooperative commitment to provide support for cross-border, collective projects. It was initiated as a project-based learning setting between undergraduate engineering students, and four years later the program shifted to include undergraduate architecture students and engineering master’s students. The learning experience opens the gate to a completely new collaborative setting, yet to be established, independent from its predecessor setting of project-based learning, focusing now towards an interdisciplinarity setting in cross-border collaboration. …

Non-Invasive Peripheral Venous And Arterial Line Air Detector For Embolization Prevention, Alexandria Kwong, Kevin Shu, Dylan Meinster

Biomedical Engineering

The scope of this project includes designing a non-invasive bubble detector for peripheral venous and arterial lines. For minimally invasive cardiac procedures, arterial and venous access is necessary for these procedures as is constant flow through the tubing to prevent clotting and to administer drugs. Air bubbles are common in these lines and can be consequential if enough air is introduced into the human system. Air embolisms are the most common and relevant issues during these procedures. The goal of this device is to create an attachable detector for air bubbles in saline that can also terminate flow and alert …

Nature-Inspired Electrode Materials For Next Generation Sustainable Energy Storage, Mikhail Miroshnikov

Dissertations, Theses, and Capstone Projects

Despite revolutionizing the world of portable electronics, the contemporary lithium-ion battery (LIB) suffers from challenges associated with the cost, safety, and environmental impact of transition metal oxide-based intercalation cathodes. To alleviate these issues, naturally occurring organic molecules may serve as sustainable alternatives to traditional inorganic cathode materials. The electrochemical properties of organic compounds are derived from redox-active functional groups containing oxygen, nitrogen and sulfur. Additionally, these functional groups are capable of coordinating metal ions beyond lithium, allowing for compatibility with sodium-ion batteries (SIBs) and other earth abundant metal-based energy storage systems. However, despite competitive performance against commercialized cathode materials, much …

Mining User-Generated Content Of Mobile Patient Portal: Dimensions Of User Experience, Mohammad Al-Ramahi, Cherie Noteboom

Research & Publications

Patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. The incorporation of patient portals provides the promise to deliver excellent quality, at optimized costs, while improving the health of the population. This study extends the existing literature by extracting dimensions related to the Mobile Patient Portal Use. We use a topic modeling approach to systematically analyze users’ feedback from the actual use of a common mobile patient portal, Epic’s MyChart. Comparing results of Latent Dirichlet Allocation analysis with those of human analysis validated the extracted …

Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang

USF Tampa Graduate Theses and Dissertations

The world’s population is rapidly aging and the increasing demand for home and health care services from this aging population brings unprecedented challenges to the economy and society. Ambient-assisted smart homes, residences equipped with ambient sensors to monitor the resident’s daily activities in a continuous and unobtrusive way, present great potential to manage the growing care service needs of this older population segment, and enable them to age-in-place.

Despite growing research, using ambient sensor data from private homes to monitor daily activities, health and wellness still faces significant challenges. To study ambient sensor data from private homes where annotated data …

Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran

LSU Master's Theses

Music and Serious Games are separately useful alternative therapy methods for helping people with a cognitive disorder, including Attention Deficit Hyperactivity Disorder (ADHD). The goal of this thesis is to explore the effect of background music on children with and without ADHD. In this study, a simple Tetris game is designed with Beethoven, Mozart music, and no-music. There are different brainwave techniques for recording; among others, the electroencephalography (EEG) allows for the most efficient use of BCI. We recorded the EEG brain signals of the regular and ADHD subjects who played the Tetris we designed according to our protocol that …

Non-Obstetrical Robotic-Assisted Laparoscopic Surgery In Pregnancy: A Systematic Literature Review., Courtney Capella, Joseph Godovchik, Thenappan Chandrasekar, Huda B. Al-Kouatly

Department of Urology Faculty Papers

Urologic and gynecologic surgeons are the top utilizers of robotic surgery; however, non-obstetrical robotic-assisted laparoscopic surgery (RALS) in pregnant patients is infrequent. A systematic literature review was performed to ascertain the frequency, indication and complications of RALS in pregnancy. Results showed thirty-eight pregnancies from eleven publications between 2008-2020. Five cases were for urologic indication and thirty-three for gynecologic indication. Minimal surgical alterations were required. Although no adverse maternal-fetal outcomes were reported, there are not enough cases published to determine safety. This review demonstrates the feasibility of RALS for the pregnant population in the hands of competent robotic surgeons.

Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons, Charles D. Smith, Linda J. Van Eldik, Gregory A. Jicha, Frederick A. Schmitt, Peter T. Nelson, Erin L. Abner, Richard J. Kryscio, Richard R. Murphy, Anders H. Andersen

Neurology Faculty Publications

Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70-78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a …

Screening And Characterization Of A Pan-Gtpase Inhibitor, Leyla Akhadov

Biomedical Engineering ETDs

Abnormal functioning of small GTPases is implicated in a variety of diseases, ranging from neurological and developmental diseases to cancer. In fact, mutant GTPases are found in up to 30% of cancers. Thus, small GTPases are a highly relevant target in drug discovery and development. High-throughput targeted screening of small molecules is the most productive method of discovering compounds that can give insights into drug development. This thesis describes improvements made to a high-throughput GTPase-targeted screening method to minimize confounding systematic error. It also describes the follow-up characterization of a compound that was identified in a high-throughput screen. The compound …

Using Case-Level Context To Classify Cancer Pathology Reports, Shang Gao, Mohammed Alawad, Noah Schaefferkoetter, Lynne Penberthy, Xiao-Cheng Wu, Eric B. Durbin, Linda Coyle, Arvind Ramanathan, Georgia Tourassi

Kentucky Cancer Registry Faculty Publications

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence-for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

Implementation Of A Computer-Vision System As A Supportive Diagnostic Tool For Parkinson’S Disease, Diego Machado Reyes

Honors Theses

Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and it is predicted that the number will keep increasing. Parkinson’s disease is difficult to diagnose due to its similarity with other diseases that share the parkinsonian symptoms and the subjectivity of its assessment, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools to improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified into two main …

Development Of Fluorescent Hyaluronic Acid Nanoparticles For Intraoperative Tumor Detection, Nicholas E. Wojtynek

Theses & Dissertations

Surgical resection remains to be the primary treatment for the majority of solid tumors, including breast cancer. The complete removal of the primary tumor, local metastases, and metastatic lymph nodes dramatically improve a patient’s treatment outcome and prognosis. Nevertheless, surgeons are limited to tactile and visual cues in distinguishing malignant and healthy tissue. This can result in a positive surgical margin (PSM), which occurs when tumor goes undetected and is left behind in the surgical cavity. PSMs decreases a patient’s prognosis and necessitate additional treatment in the form of surgery, radiation, and chemotherapy. An emerging imaging modality, known as fluorescence-guided …

Pilot Study Exploring The Effect Of Targeted Cox-2 Inhibition In Macrophages Responding To Neuronal Injury; Promoting Enhanced Axonal Regeneration, Alyssa Brauckmann

Electronic Theses and Dissertations

Celecoxib nanoemulsion (CXB-NE) has been developed as a macrophage targeted analgesics by Dr. Janjic and her team at Duquesne University, (Janjic et al, 2018; Liu et al, 2020; Saleem et al, 2019b; Vasudeva et al, 2014). The CXB-NE nanoemulsion carrying a Nonsteroidal Anti-inflammatory (NSAID) inhibitor of COX-2 activity result in a reduction in PGE2 expression in macrophages. Using CXB-NE in rats that have peripheral nerve injury constricting the sciatic nerve relieves hypersensitivity, a pain-like behavior. The treatment also decreases inflammation associated with this chronic constriction injury (Janjic et al, 2018; Saleem et al, 2019b; Stevens et al, 2019). In this …

A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz

Computer Science and Computer Engineering Undergraduate Honors Theses

Effective monitoring of adherence to at-home exercise programs as prescribed by physiotherapy protocols is essential to promoting effective rehabilitation and therapeutic interventions. Currently physical therapists and other health professionals have no reliable means of tracking patients' progress in or adherence to a prescribed regimen. This project aims to develop a low-cost, privacy-conserving means of monitoring at-home exercise activity using a gym mat equipped with an array of capacitive sensors. The ability of the mat to classify different types of exercises was evaluated using several machine learning models trained on an existing dataset of physiotherapy exercises.

Tri-State Mining District, Ecological System, And Human Health: Systematic Literature Review Analysis, Jihyun Jane Min

Posters

Objective: Although extensive research exists on corrosive environments in the Tri-State Mining District (TSMD), there has been a lack of research on how such harmful effects in the TSMD could affect residents living in those areas. However, quite recently, such research regarding relationships between the health conditions of low-income residents and toxic elements in TSDM began to grow. Therefore, the increase of empirical studies means greater complexity of the findings that require a more intricate understanding.

Methods: To meet the necessity of the study, this research was conducted by an extensive systematic review of the literature on the harmful effects …

A New Spatially-Resolved Method To Sample Biofilms From Drinking Water Fountains, Yi Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

A drinking fountain, also called a water fountain, is a facility designed to provide drinking water in public space. It consists of a basin and a spout. The users need to bend down to the stream to collect or drink water. The history of water fountains can be traced back to ancient Rome. Even before potable water was provided to individual homes, water for drinking was already made available to citizens through access to public fountains. Nowadays, drinking water fountains usually exist in public places, like schools, hospitals, and libraries. Many jurisdictions in the United States require drinking fountains to …

Characterizing Statin Use Among Prediabetic Patients With Predictive Analytics, Alexandra Gentile

Industrial Engineering Undergraduate Honors Theses

Diabetes is one of the leading causes of death in the United States and can cause severe impairments to those diagnosed. Prediabetes is a state when a patient has higher fasting plasma glucose levels than a non-diabetic person but is not quite high enough to be considered diabetes. Both diabetic and prediabetic patients are at higher risk for cardiovascular diseases (CVD), which is the leading cause of death in the United States. The primary form for prevention and treatment of CVD is through statin therapy. Statins are a class of medications used to treat and prevent CVD by limiting cholesterol …

Redesign And Quantitative Assessment Of An Accelerated Venous Valve Fatigue Apparatus, Megan Kueh

Biomedical Engineering Undergraduate Honors Theses

Chronic venous insufficiency (CVI) is a form of cardiovascular disease that is caused when valves in the leg become incompetent. Current treatment methods serve to manage symptoms, but there are currently no ways to treat the underlying cause of CVI. A venous valve prosthetic made from a xenograft of a bovine jugular vein is one possible treatment method currently in the research phase. Prosthetic valves must be tested with an accelerated wear tester prior to approval for clinical testing. Although such testers exist for heart valves, physiological differences between heart and venous valves restrict the use those testers on venous …

Modified Stent Design For A Coronary Bifurcation Lesion, Abigail Nowell

Biological Sciences Undergraduate Honors Theses

Currently, 18.2 million adults aged 20 and older are diagnosed with Coronary Artery Disease (CAD) (Benjamin et al., 2019). Stenosis is the most common intervention. However, when a patient has a bifurcated artery, treatment becomes more difficult and is often unsuccessful. This project created a new stent and balloon complex that was tested in vitro using a gel phantom artery model. Two separate prototypes have been created and tested so far, with improvements made upon each. Testing is still underway with Prototype 2.

A Reinforcement Learning Based Control Approach For Propofol-Induced Burst Suppression, Jason C. Huang, Scott C. Tadler, Brian J. Mickey, Keith Jones

Utah Space Grant Consortium

High-dose propofol is being investigated for its potential antidepressant effect. Propofol is titrated to induce burst suppression, a specific EEG pattern. However, propofol is difficult to dose due to uncertainty in each patient’s pharmacokinetics (PK) and pharmacodynamics (PD), and the lack of a commercially available monitor of propofol concentration. Clinicians currently infer the proper drug dose after observing the EEG response to the given dose. In this report we share our development of an automated controller to optimally administer propofol-induced burst suppression. We designed a deep deterministic policy gradient (DDPG) algorithm, which includes two deep neural networks and relates a …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross-sectional nature of training and prediction processes. Finding temporal patterns in EHR is especially …

Evaluation Of Tracing Techniques In The Rat Spinal Cord Using A Custom Matlab Application., Rachel M. Zalla

Electronic Theses and Dissertations

The objective of this research project is to evaluate the efficiency of traditional chemical tracing compared to dual-viral tracing for labeling long ascending propriospinal neurons (LAPNs) in the uninjured rat spinal cord, and to develop a MATLAB program which will accurately quantify this labeling.

To evaluate chemical tracing, Fluoro-Ruby (FR) was injected at the level of the axon terminals, and the number of ipsilateral labeled cell bodies at lumbar level was quantified. Similarly, two dual-viral systems were evaluated, by either injecting retro-AAV-Cre or HiRet-Lenti-Cre unilaterally in combination with a Cre-dependent adeno-associated virus. The HiRet-Lenti and FR groups labeled significantly greater …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is …

Relative Contribution Of Arms And Legs Through Repetitive Assisted Sit-To-Stand Motion In Individuals With Incomplete Spinal Cord Injury, Abd Aziz Musfirah

Student Works (2020-2029)

Sit-To-Stand (SitTS) exercise is one of important prerequisites to achieve some functional independence goals in everyday life especially for individuals undergoing rehabilitation In general, the execution of SitTS in spinal cord injury (SCI) patients involves motor function in both upper and lower extremities. The use of arm support in particular is a very significant element while executing SitTS movement for SCI population. In addition, application of functional electrical stimulation (FES) onto the quadriceps muscles is one of the prescribed management for incomplete SCI to improve muscle action for simple lower limb movements. However, the relative contribution of upper and lower …