Medicine and Health Sciences Commons^™

Co-Designing Situated Displays For Family Co-Regulation With Adhd Children, Lucas M. Silva, Franceli L. Cibrian, Clarisse Bonang, Arpita Bhattacharya, Aehong Min, Elissa M. Monteiro, Jesus A. Beltran, Sabrina E. B. Schuck, Kimberley D. Lakes, Gillian R. Hayes, Daniel A. Epstein

Engineering Faculty Articles and Research

Family informatics often uses shared data dashboards to promote awareness of each other’s health-related behaviors. However, these interfaces often stop short of providing families with needed guidance around how to improve family functioning and health behaviors. We consider the needs of family co-regulation with ADHD children to understand how in-home displays can support family well-being. We conducted three co-design sessions with each of eight families with ADHD children who had used a smartwatch for self-tracking. Results indicate that situated displays could nudge families to jointly use their data for learning and skill-building. Accommodating individual needs and preferences when family members …

The Contribution Of Micrornas To Rybp Silencing In Glioblastoma Multiforme, Alex B. Lee

Graduate Theses

Glioblastoma multiforme (GBM) is a highly aggressive and invasive tumor of the central nervous system (CNS). Survival rates are abysmal, with only 7.2% of patients alive 5-years after diagnosis. Because of this, understanding epigenetic alterations that give GBM tumors their aggressive phenotypes is critical for the development of more targeted and effective therapies. These alterations frequently affect a group of proteins called the Polycomb group proteins, which play important oncogenic and tumor suppressive roles in cancer. One Polycomb protein, the RING1- and YY1-binding protein (RYBP), is downregulated in a majority of GBM patients, suggesting a strong tumor suppressive property. In …

Bcl2 Mediated Targeted Drug Delivery For The Treatment Of Kidney Fibrosis And Stomach Cancer, Humayra Afrin

Open Access Theses & Dissertations

Apoptosis, the programmed death of cells, is primarily regulated by a delicate balance between pro-apoptotic and anti-apoptotic signals. The Bcl-2 (B-cell lymphoma 2) family of proteins acts as anti-apoptotic agents, promoting cell survival. Dysregulation of these proteins is a common occurrence in conditions such as cancer and fibrosis, where overexpression of anti-apoptotic members can foster tumor cell survival and fibroblast activation. In this study, our aim was to explore the therapeutic potential of Bcl-2 inhibitors, both as a small molecule (specifically Navitoclax (Navi)), inhibitor and as Bcl-2 siRNA, for targeted treatment. Intravenous administration of Navi often leads to thrombocytopenia, necessitating …

Selective Transfection Of A Transferrin Receptor-Expressing Cell Line With Dna-Lipid Nanoparticles And Synthesis Of Parasite-Derived Glycans As Biomarkers For Leishmaniasis, Irodiel Vinales Lozano

Open Access Theses & Dissertations

Despite notable progress in lipid nanoparticle (LNP)-mediated gene delivery, achieving selective transfection of specific cell types, such as cancer cells, remains a significant hurdle, hindering the advancement of innovative gene therapies. In this study, we engineered an LNP formulation encapsulating plasmid DNA (pDNA) encoding the monomeric Green Lantern (mGL) fluorescent reporter protein. The DT7 peptide ligand targeting human transferrin receptor 1 (hTfR1) was also conjugated to the LNP surface for targeted delivery to hTfR1-expressing cells. Optimization of LNP composition yielded favorable particle diameter, ζ-potential, yield, and pDNA encapsulation efficiency. Evaluation of transfection selectivity using a panel of two engineered cell …

Advancing Brain Tumor Segmentation With Spectral–Spatial Graph Neural Networks, Sina Mohammadi, Mohamed Allali

Engineering Faculty Articles and Research

In the field of brain tumor segmentation, accurately capturing the complexities of tumor sub-regions poses significant challenges. Traditional segmentation methods usually fail to accurately segment tumor subregions. This research introduces a novel solution employing Graph Neural Networks (GNNs), enriched with spectral and spatial insight. In the supervoxel creation phase, we explored methods like VCCS, SLIC, Watershed, Meanshift, and Felzenszwalb–Huttenlocher, evaluating their performance based on homogeneity, moment of inertia, and uniformity in shape and size. After creating supervoxels, we represented 3D MRI images as a graph structure. In this study, we combined Spatial and Spectral GNNs to capture both local and …

Multimode Point Spectroscopy For Food Authentication, Sayed Asaduzzaman, Nicholas Mackinnon, Hossein Kashani Zadeh

SDSU Data Science Symposium

Enhancing food quality measurement is a necessity to guarantee food safety and adherence to health regulations. Current methods involve lab testing which are time-consuming, costly, destructive and require skilled workers. Spectroscopy has the potential to overcome these challenges. This study employs a multi-mode point spectroscopy method to distinguish food products according to their spectral characteristics,. The system records fluorescence, excited at 365 and 405 nm, visible-near infrared (Vis-NIR) and short-wave infrared (SWIR) spectra. The three main subjects of the study are olive oil, milk, and honey. Samples were kept in a transparent cell culture pot, and Gray and White Spectralon …

Market Analysis And Bidding Strategy Of Hybrid Renewable Energy Systems Considering Emissions, Fatma Elzahraa, Mohamed Elnemr, Samir Dawoud

Journal of Engineering Research

The competition in the electricity markets makes it difficult to choose a suitable strategy for maximizing profit while reducing harmful emissions. To have an adequate energy price for consumers while minimizing the harmful emissions to the atmosphere and maximizing profits of all participants in the electricity market needs an aggressive bidding strategy. Developing these bidding strategies with the integration of renewable energy (RE) in the electricity market became important. This research studies various bidding strategies for maximizing profits in the deregulated energy market since participants are keen on developing bidding strategies considering emissions. These bidding strategies will consider the integration …

Recent Progress In Microrna Detection Using Integrated Electric Fields And Optical Detection Methods, Logeeshan Velmanickam, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Low-cost, highly-sensitivity, and minimally invasive tests for the detection and monitoring of life-threatening diseases and disorders can reduce the worldwide disease burden. Despite a number of interdisciplinary research efforts, there are still challenges remaining to be addressed, so clinically significant amounts of relevant biomarkers in body fluids can be detected with low assay cost, high sensitivity, and speed at point-of-care settings. Although the conventional proteomic technologies have shown promise, their ability to detect all levels of disease progression from early to advanced stages is limited to a limited number of diseases. One potential avenue for early diagnosis is microRNA (miRNA). …

Tailored Micromagnet Sorting Gate For Simultaneous Multiple Cell Screening In Portable Magnetophoretic Cell-On-Chip Platforms, Jonghwan Yoon, Yumin Kang, Hyeonseol Kim, Abbas Ali, Keonmok Kim, Sri Ramulu Torati, Mi-Young Im, Changyeop Jeon, Byeonghwa Lim, Cheolgi Kim

Bioelectronics Publications

Conventional magnetophoresis techniques for manipulating biocarriers and cells predominantly rely on large-scale electromagnetic systems, which is a major obstacle to the development of portable and miniaturized cell-on-chip platforms. Herein, a novel magnetic engineering approach by tailoring a nanoscale notch on a disk micromagnet using two-step optical and thermal lithography is developed. Versatile manipulations are demonstrated, such as separation and trapping, of carriers and cells by mediating changes in the magnetic domain structure and discontinuous movement of magnetic energy wells around the circumferential edge of the micromagnet caused by a locally fabricated nano-notch in a low magnetic field system. The motion …

Non-Invasive Monitoring Device For Early Detection Of Breast Cancer Related Lymphedema, Amy Prendergast

Honors Theses and Capstones

Breast Cancer Related Lymphedema (BCRL) is a common co-morbidity in cancer survivors following neoadjuvant therapies such as chemotherapy, radiation, and/or surgery. It is brought about by the disruption in the lymphatic system (think lymph node biopsy) that leads to a buildup of lymphatic fluid in the arm. Current diagnostic strategies for this condition are merely retroactive, and fairly limited in the parameters that are examined to ensure patient well-being long term. We hypothesize that with an approach that mimics bioimpedance spectroscopy analysis, we will be able to provide a clinical support tool that would better determine early stages of lymphedema …

Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

An Investigation Of Match For Lossless Video Compression, Brittany Sullivan-Reicks

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new lossless video compression technique, Match, is investigated. Match uses the similarity between the frames of a video or the slices of medical images to find a prediction for the current pixel. A portion of the previous frame is searched to find a matching context, which is the pixels surrounding the current pixel, within some distance centered on the current location. The best distance to use for each dataset is found experimentally. The matching context refers to the neighborhood of w, nw, n, and ne, where the pixel in the previous frame with the closest matching context becomes the …

Trumpet Directivity From A Rotating Semicircular Array, Samuel D. Bellows, Joseph E. Avila, Timothy W. Leishman

Directivity

The directivity function of a played musical instrument describes the angular dependence of its acoustic radiation and diffraction about the instrument, musician, and musician’s chair. Directivity influences sound in rehearsal, performance, and recording environments and signals in audio systems. Because high-resolution, spherically comprehensive measurements of played musical instruments have been unavailable in the past, the authors have undertaken research to produce and share such data for studies of musical instruments, simulations of acoustical environments, optimizations of microphone placements, and other applications. The authors acquired the data from repeated chromatic scales produced by a trumpet played at mezzo-forte in an anechoic …

Reducing Brain Kynurenic Acid Synthesis Precludes Kynurenine-Induced Sleep Disturbances, Katherine M. Rentschler, Snezana Milosavljevic, Annalisa M. Baratta, Courtney J. Wright, Maria V. Piroli, Zachary Tentor, Homayoun Valafar, Christian O'Reilly, Ana Pocivavsek

Publications

Patients with neurocognitive disorders often battle sleep disturbances. Kynurenic acid is a tryptophan metabolite of the kynurenine pathway implicated in the pathology of these illnesses. Modest increases in kynurenic acid, an antagonist at glutamatergic and cholinergic receptors, result in cognitive impairments and sleep dysfunction. We explored the hypothesis that inhibition of the kynurenic acid synthesising enzyme, kynurenine aminotransferase II, may alleviate sleep disturbances. At the start of the light phase, adult male and female Wistar rats received systemic injections of either: (i) vehicle; (ii) kynurenine (100 mg kg−1; i.p.); (iii) the kynurenine aminotransferase II inhibitor, PF-04859989 (30 mg kg−1; s.c.); …

Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney

Theses and Dissertations

Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …

Survey Of How Irregularities In The Electrical System Of The Human Heart Link To Different Heart Arrhythmias, Jazmine Boloor

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis explores the circuital pathway that a signal takes within the heart throughout a full heartbeat and provides a timing analysis. It then surveys the different pathways that could arise in the electrical system of the heart, and the associated heart diseases linked to the location of each pathway. Common heart arrhythmias such as atrioventricular nodal reentrant tachycardia, atrioventricular reentrant tachycardia, atrial flutter, and atrial fibrillation are surveyed, and their pathways are analyzed. Electrocardiograms are presented to aid in understanding of the timing analysis associated with irregularity in heart function. Finally, this thesis explores an avenue of the heartbeat …

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …

Neurocomputing And Interfacing Digital Tasting System: Research, Design, And Evaluation, Amira J. Zaylaa, Ahmad El Hajj

BAU Journal - Science and Technology

The continuous evolution in computing and interfacing has been extended to develop multi-sensory experiences in many domains such as neurological, auditory, vision, and haptic domains. So far, only a few remarkable system approaches have been approved to be serving the taste sensation digitally. Although taste sensation is linked to the brain, there is a lack of optimal neurocomputing digital taste sensation systems. Our study provides a new neurocomputing method to digitally stimulate the sense of taste by electrical stimulation on the human tongue. We aim to link chemical stimulation and electrical stimulation in order to design an electronic interface for …

How Did The Landscape Of Student Belonging Shift During Covid-19?, Shruti Misra, Neha Kardam, Jennifer Vanantwerp, Denise Wilson

University Faculty Publications and Creative Works

The goal of this study is to understand if and how emergency remote teaching (ERT) used during the COVID-19 pandemic changed the ways in which instructional support and interactions were linked to belonging among engineering students. Belonging is a fundamental human motivation associated with a wide range of positive psychological, educational, social, and job outcomes. Frequent and predominantly conflict-free interactions within a stable, relational framework of caring are required to facilitate belonging. To better understand potential shifts in belonging that occurred from prepandemic to mid-pandemic, this study used survey data from a cross-sectional dataset at a single, large institution comprised …

Dense & Attention Convolutional Neural Networks For Toe Walking Recognition, Junde Chen, Rahul Soangra, Marybeth Grant-Beuttler, Y. A. Nanehkaran, Yuxin Wen

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait disorder where children’s initial contacts show limited or no heel touch during the gait cycle. Toe walking can lead to poor balance, increased risk of falling or tripping, leg pain, and stunted growth in children. Early detection and identification can facilitate targeted interventions for children diagnosed with ITW. This study proposes a new one-dimensional (1D) Dense & Attention convolutional network architecture, which is termed as the DANet, to detect idiopathic toe walking. The dense block is integrated into the network to maximize information transfer and avoid missed features. Further, the attention modules are …

Development Of A Cost-Constrained Intelligent Prosthetic Knee With Real-Time Machine Learning, Predictive Stumble Control, Lucas Jonathan Galey

Open Access Theses & Dissertations

The field of biomechatronics is evolving quickly with advances in computer science, biology, and electrical and mechanical engineering. Coupled with increased interests in machine learning (ML) across all industry sectors, there are opportunities to leverage advanced analytics in uniquely complex problems. This study aimed to deploy real-time ML predictions in a novel microprocessor-controlled prosthetic knee (MPK) device capable of identifying and responding to stumble-events to reduce amputee fall prevalence. Innately, stumbling is a chaotic event. Current MPKs operate by detecting gait characteristics and reacting to preprogrammed states. While these systems are beneficial in significant ways, such as energy expenditure and …

Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …

Development And Implementation Of Telemetry Devices To Identify And Characterize Sources Of Intraocular Pressure Variability In Rats, Christina M. Nicou

USF Tampa Graduate Theses and Dissertations

Eye health depends partially on intraocular pressure (IOP) as abnormal levels can lead to ocular tissue damage. Glaucoma is a neurodegenerative disease that affects nearly 80 million people worldwide [1]. It is associated with elevated IOP, which can lead to irreversible blindness. Relatively little is known about IOP dynamics and the physiological factors that affect it as IOP is typically monitored using tonometry. Tonometry is a common tool used by clinicians and researchers to measure IOP noninvasively. It provides a good estimate of IOP mean but not variance because data collection takes time. Readings can also be influenced by subject …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Split And Join: An Efficient Approach For Simulating Stapled Intestinal Anastomosis In Virtual Reality, Di Qi, Suvranu De

Engineering Faculty Articles and Research

Colorectal cancer is a life-threatening disease. It is the second leading cause of cancer-related deaths in the United States. Stapled anastomosis is a rapid treatment for colorectal cancer and other intestinal diseases and has become an integral part of routine surgical practice. However, to the best of our knowledge, there is no existing work simulating intestinal anastomosis that often involves sophisticated soft tissue manipulations such as cutting and stitching. In this paper, for the first time, we propose a novel split and join approach to simulate a side-to-side stapled intestinal anastomosis in virtual reality. We mimic the intestine model using …

Computer Vision-Based Hand Tracking And 3d Reconstruction As A Human-Computer Input Modality With Clinical Application, Tania Banerjee

Electronic Thesis and Dissertation Repository

The recent pandemic has impeded patients with hand injuries from connecting in person with their therapists. To address this challenge and improve hand telerehabilitation, we propose two computer vision-based technologies, photogrammetry and augmented reality as alternative and affordable solutions for visualization and remote monitoring of hand trauma without costly equipment. In this thesis, we extend the application of 3D rendering and virtual reality-based user interface to hand therapy. We compare the performance of four popular photogrammetry software in reconstructing a 3D model of a synthetic human hand from videos captured through a smartphone. The visual quality, reconstruction time and geometric …

Graphene-Conductive Polymer-Based Electrochemical Sensor For Dopamine Detection, Dipannita Ghosh, Md Ashiqur Rahman, Ali Ashraf, Nazmul Islam

Electrical and Computer Engineering Faculty Publications and Presentations

The central nervous system's (CNS) dopaminergic system dysfunction has been linked to neurological illnesses like schizophrenia and Parkinson's disease. As a result, sensitive and selective detection of dopamine is critical for the early diagnosis of illnesses associated with aberrant dopamine levels. In this research, we have investigated the performance of electrochemical screen-printed sensors for different concentrations of dopamine detection using graphene-based conductive PEDOT: PSS(G-PEDOT: PSS) and Polyaniline(GPANI) inks on the working electrode and compared the sensitivity. SEM characterization technique has been performed to visualize the microstructures of the proposed inks. We have investigated cyclic voltammetry (CV) electrochemical techniques with ferri/ferrocyanide …

Coulomb Blockade-Mediated Field Emission Sources Using Ultra-Nanocrystalline Diamond, Jevin Jensen

Graduate Research Theses & Dissertations

Coulomb Blockade effects in field emission provide interesting means of achieving brighter electron sources for numerous applications, ranging from vacuum electronics to the next generation of electron beam technology. Microelectronics cleanroom methods are presented in this thesis for production of field emission sources moderated by the Coulomb Blockade. The use of common processes is an essential step toward widespread experimentation with Coulomb Blockade-mediated field emission apparatuses. The main feature to be explored is the use of nano-diamond films for their potential applicability for this desired outcome. Ultra-Nanocrystalline Diamond is used in two different ways to achieve this, both as a …

Efficient Training On Alzheimer’S Disease Diagnosis With Learnable Weighted Pooling For 3d Pet Brain Image Classification, Xin Xing, Muhammad Usman Rafique, Gongbo Liang, Hunter Blanton, Zu Zhang, Chris Wang, Nathan Jacobs, Ai-Ling Lin

Computer Science Faculty Publications

Three-dimensional convolutional neural networks (3D CNNs) have been widely applied to analyze Alzheimer’s disease (AD) brain images for a better understanding of the disease progress or predicting the conversion from cognitively impaired (CU) or mild cognitive impairment status. It is well-known that training 3D-CNN is computationally expensive and with the potential of overfitting due to the small sample size available in the medical imaging field. Here we proposed a novel 3D-2D approach by converting a 3D brain image to a 2D fused image using a Learnable Weighted Pooling (LWP) method to improve efficient training and maintain comparable model performance. By …