Medicine and Health Sciences Commons^™

Laboratory Practices And Antimicrobial Resistance In A Florida Hospital, Crispina Marie Sy-Trias

Walden Dissertations and Doctoral Studies

Antibiotic resistance is a health threat affecting millions of Americans. Microorganisms develop resistance to antibiotics, rendering them useless for treating infections. The purpose of this quantitative study was to assess the associations between sample processing time and antibiotic resistance and is based on the health belief model. A retrospective specimen tracking activity of data from November 2019 to November 2020 was obtained by random sampling of 246 bacterial cultures. One hundred ninety-six (80%) samples were processed on time, and 50 (20%) were delayed; 167 (68%) samples were determined to have the presence of antimicrobial resistance (AMR), and 79 (32%) with …

Occupational Risk Perceptions Among Foreign-Born Construction Workers In Central Florida, Matthew Edison Law

Walden Dissertations and Doctoral Studies

Hispanic and Latino foreign-born construction workers in the United States experience higher rates of serious injuries and fatalities in the workplace than their native-born peers. Previous research has pointed to specific vulnerabilities among this population, including birthplace, age of the worker, language barriers, and education level, but little to no research has examined addressable risk factors, such as occupational risk perceptions, among this population. The purpose of this quantitative study was to determine the relationship between birthplace, number of years working in the United States, and occupational risk perceptions while controlling for age of the worker, language barriers, and education …

Autodesc: Facilitating Convenient Perusal Of Web Data Items For Blind Users, Yash Prakash, Mohan Sunkara, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a ‘Query-Results’ page showing the summaries of the items, and ‘Details’ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in …

Msdrp: A Deep Learning Model Based On Multisource Data For Predicting Drug Response, Haochen Zhao, Xiaoyu Zhang, Qichang Zhao, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict drug response in vitro. However, most of these methods capture drug features based on a single drug description (e.g. drug structure), without considering the relationships between drugs and biological entities (e.g. target, diseases, and side effects). Moreover, most of these methods collect features separately for drugs and cell lines but fail to consider the pairwise interactions between drugs and cell …

Comparison Of Physics-Based Deformable Registration Methods For Image-Guided Neurosurgery, Nikos Chrisochoides, Yixun Liu, Fotis Drakopoulos, Andriy Kot, Panos Foteinos, Christos Tsolakis, Emmanuel Billias, Olivier Clatz, Nicholas Ayache, Andrey Fedorov, Alex Golby, Peter Black, Ron Kikinis

Computer Science Faculty Publications

This paper compares three finite element-based methods used in a physics-based non-rigid registration approach and reports on the progress made over the last 15 years. Large brain shifts caused by brain tumor removal affect registration accuracy by creating point and element outliers. A combination of approximation- and geometry-based point and element outlier rejection improves the rigid registration error by 2.5 mm and meets the real-time constraints (4 min). In addition, the paper raises several questions and presents two open problems for the robust estimation and improvement of registration error in the presence of outliers due to sparse, noisy, and incomplete …

Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users' experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via …

Unttangling Irregular Actin Cytoskeleton Architectures In Tomograms Of The Cell With Struwwel Tracer, Salim Sazzed, Peter Scheible, Jing He, Willy Wriggers

Computer Science Faculty Publications

In this work, we established, validated, and optimized a novel computational framework for tracing arbitrarily oriented actin filaments in cryo-electron tomography maps. Our approach was designed for highly complex intracellular architectures in which a long-range cytoskeleton network extends throughout the cell bodies and protrusions. The irregular organization of the actin network, as well as cryo-electron-tomography-specific noise, missing wedge artifacts, and map dimensions call for a specialized implementation that is both robust and efficient. Our proposed solution, Struwwel Tracer, accumulates densities along paths of a specific length in various directions, starting from locally determined seed points. The highest-density paths originating …

Ovulation Prediction Using Random Forest Algorithm On Physiological Data, Kimberly D. Laynes

UNF Graduate Theses and Dissertations

Human infertility rates are on the rise -- studies have shown that one in every four women have trouble conceiving and every year those rates are rising [Halleran22]. This trend motivates procedures such as in-vitro fertilization (IVF) and intrauterine insemination (IUI) to produce a pregnancy. Such procedures are not only intricate and expensive but also carry potential unintended consequences for women's physical and mental well-being. A more profound comprehension of the menstrual cycle and its multiple phases, particularly detecting the ovulation period itself, promotes optimized treatment outcomes and reduces associated risks. To facilitate ovulation detection, new sensing technologies built into …

The Effect Of Metalation On Antimicrobial Piscidins Imbedded In Normal And Oxidized Lipid Bilayers, Ana Dreab, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

Metalation of the N-terminal Amino Terminal Cu(II)- and Ni(II)-binding (ATCUN) motif may enhance the antimicrobial properties of piscidins. Molecular dynamics simulations of free and nickelated piscidins 1 and 3 (P1 and P3) were performed in 3 : 1 POPC/POPG and 2.6 : 1 : 0.4 POPC/POPG/aldo-PC bilayers (POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine: POPG, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol; aldo-PC, 1-palmitoyl-2-(9′-oxo-nonanoyl)-sn-glycero-3-phosphocholine) bilayer models. Nickel(II) binding decreases the conformation dynamics of the ATCUN motif and lowers the charge of the N-terminus to allow it to embed deeper in the bilayer without significantly changing the overall depth due to interactions of the charged half-helix …

Editor’S Note, Deepak Shimkhada

Monsoon: South Asian Studies Association Journal

This special issue of Monsoon is dedicated to the studies honoring the goddess traditions in South Asia. The onset of the Monsoon Season in South Asia typically commences in June and continues until late August and early September. The publication of this issue, therefore, has been strategically timed to coincide with that season, which is a vital source of sustenance for millions of individuals in this part of the world. This anthology consisting of five papers—written by scholars with expertise in the field of goddess and women studies—speak unequivocally about the goddesses or women for their strength, beauty, wisdom, and …

Constructing Jain Goddess Padmavātī In Gujarati Literature, Venu Mehta

Monsoon: South Asian Studies Association Journal

Worship of the goddess Padmāvatī emerged more than a thousand years ago. This article explores three songs about her in Gujarati by Paṇḍit Vīrvijayajī (1773-1852). By analyzing the style and form of his work, one learns a great deal about devotional liturgies that commemorate goddess Padmāvatī’s protection of the Jina Pārśvanātha and, in turn, his protection of her.

Women’S Voices From History: Gond Rani Durgawati And Rani Lakshmibhai, Nandini Sengupta, Moupia Basu

Monsoon: South Asian Studies Association Journal

Two strong women are compared and contrasted in this article. Gond Rani Durgawati (1524-1564) led a resistance movement in Jabalpur against the Mughal rule of Akbar. Rani Lakshmibai (1828-1858) organized the people of Jhansi against Sir Hugh Rose, an officer defending the interests of the British East India Company. Both women continue to be remembered for their bravery and their loyalty to the people they ruled.

Mai Bhago And Amrita Devi Bishnoi: Women Of Strength, Sowmya Ayyar

Monsoon: South Asian Studies Association Journal

Mai Bhago (1670-1720), also known as Bhag Kaur, distinguished herself on the battlefield to defend the Sikh faith. Amrita Devi Bishnoi (d. 1730) is said to have sacrificed her life with 362 others to protect the Khejari trees in the Rajasthan desert. Both women continue to inspire social justice and ecological activism.

An Examination Of Gandhian Economic And Political Thought And Its Relevance To The Empowerment Of Women, Purnima Mehta Bhatt

Monsoon: South Asian Studies Association Journal

Mahatma Gandhi (1869-1948) sought to alleviate poverty and empower women. His commitment to nonviolence and the economic ideal of “small is beautiful” continue to inspire grassroots movements around the globe. This article discusses the Chipko movement of northern India, the protection of rain forests in Kerala’s Silent Valley, the Self Employed Women’s Association (SEWA), and Medha Patkar’s valiant though ultimately futile attempt to save the Narmada River from a massive government damming project. The ongoing legacy of these movements can be found in AWAG, the Ahmedabad Women’s Action Group and Women’s Shanti Sena (Peace Force).

Indigenous Stitch-Arts Of India: Tradition And Revival In A Global Age, Punam Madhok

Monsoon: South Asian Studies Association Journal

Stitch art allows for the creative expression and economic support of countless women throughout India. This article examines four notable styles: chikankari, flora and fauna stitched in white thread on fine white cotton, rabari, the stitching of mirrors into colorful cloth, phulkari, resplendent flowery motifs sewn into shawls in Punjab, and kantha, Bengali patch work yielding quilts and seating mats. In addition to describing each technique, this article discusses how women have been economically empowered through this art by such organizations as Self-Help Enterprise (SHE) in Kolkata and Adithi, a women’s cooperative, in Bihar.

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 …

Autodocking Studies Of Oxygenated Fullerenes As Inhibitors Of The Hiv Protease, Michael Kaminski

All Student Theses and Dissertations

In a previous study, several oxygenated fullerene compounds were produced by ozonation of C60 (Buckminsterfullerene) and were identified by elemental analysis and by SALI (surface analysis by laser ionization). Some of these compounds, especially a batch, SK-5, a mixture of C60O1-8, were shown to inhibit activities of HIV-Protease with IC50 (concentration for 50% inhibition) of 1 mg/mol in the in-vitro studies. The oxygenated fullerenes were shown to have epoxide, ketones, and hydroxyl functionalities. As expected, C60 interacted with ozone with alkene functionality and not as an aromatic compound. It was postulated that C60O had epoxide functionality, as a product of …

Identities Of Women In Indian Art And History, Nalini Rao

Monsoon: South Asian Studies Association Journal

The stereotypical image of Indian women portrayed in the art of stone sculpture is often interpreted as images of beauty that are sensuous, religious as well depict social life. There are historical reasons for depicting her as such. This paper inquires into the changing depiction and social forces that influenced feminine imagery. This paper examines the portrayal of beauty through idealization of female body which has evolved over the centuries in India. It also aims to understand their changing status and explores issues of feminine identity, status, and empowerment largely in ancient and medieval India. It also provides a brief …

Climate And Health: Impact Of Climate Education On Nursing Student Knowledge, Confidence, And Intent To Act, Beth Tremblay, Janice Hawkins

Ellmer School of Nursing Faculty Publications

Background: Because climate change negatively impacts human health, nurses need skills to mitigate climate change and nurse educators need effective educational strategies to teach climate change content in undergraduate nursing programs. To address this need, we embedded an energy efficiency treasure hunt and Climate for Health Ambassador Training into our prelicensure nursing curricula.

Purpose: To evaluate the impact of these educational activities on self-reported knowledge, confidence, and intent to engage in climate action.

Methods: A quasi-experimental one-group posttest design examined the effectiveness of 2 educational interventions on increasing knowledge, confidence, and intent to engage in climate action. A convenience sample …

Segmentation Stability Of Human Head And Neck Cancer Medical Images For Radiotherapy Applications Under De-Identification Conditions: Benchmarking Data Sharing And Artificial Intelligence Use-Cases, Jaakko Sahlsten, Kareem A Wahid, Enrico Glerean, Joel Jaskari, Mohamed A Naser, Renjie He, Benjamin H Kann, Antti Mäkitie, Clifton D Fuller, Kimmo Kaski

Faculty, Staff and Student Publications

BACKGROUND: Demand for head and neck cancer (HNC) radiotherapy data in algorithmic development has prompted increased image dataset sharing. Medical images must comply with data protection requirements so that re-use is enabled without disclosing patient identifiers. Defacing, i.e., the removal of facial features from images, is often considered a reasonable compromise between data protection and re-usability for neuroimaging data. While defacing tools have been developed by the neuroimaging community, their acceptability for radiotherapy applications have not been explored. Therefore, this study systematically investigated the impact of available defacing algorithms on HNC organs at risk (OARs).

METHODS: A publicly available dataset …

Forest Bathing Increases Adolescent Mental Well-Being And Connection To Nature: A Transformative Mixed Methods Study, Jennifer Keller

Antioch University Dissertations & Theses

Previous research has demonstrated that practicing forest bathing has significant positive effects on well-being. However, few studies have investigated whether forest bathing increases adolescent well-being despite the growing adolescent mental health crisis in the United States. Similarly, few studies have explored forest bathing’s impacts on connectedness to nature. Considering the ongoing environmental crisis, determining if forest bathing increases connectedness to nature is a critical expansion of forest bathing research, as connectedness to nature is linked to environmental care and concern. This study investigated the possibility that forest bathing, a nature-based mindfulness practice, could increase adolescent mental well-being and connectedness to …

The Use Of A Habitat Quality Stress Index To Evaluate Stress As An Analog For Proximate Fitness In The American Crow Within A Matrix Of Landcover Characteristics To Assess Its Potential Contribution To Disease Etiologies, Theodore Lee Grabarz

Antioch University Dissertations & Theses

All organisms occur within spatial and temporal environments to maximize proximate fitness (health) and thus life history outcomes. Previous work has examined the temporal and behavioral aspects of proximate fitness on life history outcomes particularly regarding highly perturbed environments (i.e., climate and land use change, resource extraction, agricultural erosion, etc.). My work focuses on the less examined spatial aspect of these perturbed environments. More specifically, this dissertation examines habitat selection and quality as the basis for understanding stress response (negative and positive feedback mechanisms) to environmental stressors within the larger context of regional or gamma (ɣ) biodiversity. Through the lens …

Sun Exposure And Protective Behaviors Among U.S. Hispanic Farmworkers, Claudia Marie Delgado Cebollero

Walden Dissertations and Doctoral Studies

Sun exposure increases the risk of sun-related illnesses and skin cancer among U.S. Hispanic farmworkers. Reinforced by the health belief model, the purpose of this study was to determine the association between socio-demographic factors (i.e., age, educational attainment, gender, income, and marital status) and skin cancer with the level of sun exposure (sun’s effect on skin, sunburn reported) and protective behaviors (use of cap/visor, use of sunscreen) among adult Hispanic farmworkers in the United States. The study included Hispanic farmworkers aged 21 or older (N = 112) who responded to the 2015 National Health Interview Survey. Ordinal logistic regression showed …

Longitudinal Sport Science Implementation In American Collegiate Men’S Basketball, Jason Stone

Graduate Theses, Dissertations, and Problem Reports (ETD)

The expanding opportunities to implement sport science frameworks in elite-level basketball environments coincide with the sport’s increasing global prominence. Concomitant to these opportunities is the continual growth of the sport technology market (e.g., wearables, force plates) and computational power (e.g., data management tools, coding capabilities), which yields solutions and challenges for both athletes and practitioners. Due to the rapid influx of new sport technologies in high performance environments, particularly American Collegiate Men’s Basketball, more formal and ecologically valid research on how to effectively utilize data derived from them, particularly over long periods of time (i.e., multiple seasons) is needed. To …

Application Of A Gene Modular Approach For Clinical Phenotype Genotype Association And Sepsis Prediction Using Machine Learning In Meningococcal Sepsis, Asrar Rashid, Arif R. Anwary, Feras Al-Obeidat, Joe Brierley, Mohammed Uddin, Hoda Alkhzaimi, Amrita Sarpal, Mohammed Toufiq, Zainab A. Malik, Raziya Kadwa, Praveen Khilnani, M. Guftar Shaikh, Govind Benakatti, Javed Sharief, Syed Ahmed Zaki, Abdulrahman Zeyada, Ahmed Al-Dubai, Wael Hafez, Amir Hussain

All Works

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The research used Weighted Gene Co-expression Network Analysis (WGCNA) to establish links between gene expression and clinical parameters in infants admitted to the Pediatric Critical Care Unit with MSS. Additionally, various machine learning (ML) algorithms, including Support Vector Machine (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Decision Tree, Random Forest, and Artificial Neural Network (ANN) were implemented to predict sepsis survival. The findings revealed a transition …

Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette

Electrical & Computer Engineering Faculty Publications

Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …

Adaptive Critic Network For Person Tracking Using 3d Skeleton Data, Joseph G. Zalameda, Alex Glandon, Khan M. Iftekharuddin, Mohammad S. Alam (Ed.), Vijayan K. Asari (Ed.)

Electrical & Computer Engineering Faculty Publications

Analysis of human gait using 3-dimensional co-occurrence skeleton joints extracted from Lidar sensor data has been shown a viable method for predicting person identity. The co-occurrence based networks rely on the spatial changes between frames of each joint in the skeleton data sequence. Normally, this data is obtained using a Lidar skeleton extraction method to estimate these co-occurrence features from raw Lidar frames, which can be prone to incorrect joint estimations when part of the body is occluded. These datasets can also be time consuming and expensive to collect and typically offer a small number of samples for training and …

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …

Comparison Of Machine Learning Methods For Classification Of Alexithymia In Individuals With And Without Autism From Eye-Tracking Data, Furkan Iigin, Megan A. Witherow, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Alexithymia describes a psychological state where individuals struggle with feeling and expressing their emotions. Individuals with alexithymia may also have a more difficult time understanding the emotions of others and may express atypical attention to the eyes when recognizing emotions. This is known to affect individuals with Autism Spectrum Disorder (ASD) differently than neurotypical (NT) individuals. Using a public data set of eye-tracking data from seventy individuals with and without autism who have been assessed for alexithymia, we train multiple traditional machine learning models for alexithymia classification including support vector machines, logistic regression, decision trees, random forest, and multilayer perceptron. …

An Explainable Artificial Intelligence Framework For The Predictive Analysis Of Hypo And Hyper Thyroidism Using Machine Learning Algorithms, Md. Bipul Hossain, Anika Shama, Apurba Adhikary, Avi Deb Raha, K. M. Aslam Uddin, Mohammad Amzad Hossain, Imtia Islam, Saydul Akbar Murad, Md. Shirajum Munir, Anupam Kumur Bairagi

Electrical & Computer Engineering Faculty Publications

The thyroid gland is the crucial organ in the human body, secreting two hormones that help to regulate the human body's metabolism. Thyroid disease is a severe medical complaint that could be developed by high Thyroid Stimulating Hormone (TSH) levels or an infection in the thyroid tissues. Hypothyroidism and hyperthyroidism are two critical conditions caused by insufficient thyroid hormone production and excessive thyroid hormone production, respectively. Machine learning models can be used to precisely process the data generated from different medical sectors and to build a model to predict several diseases. In this paper, we use different machine-learning algorithms to …