Digital Commons Network^™

Chromium Removal From Tannery Wastewater Via A Hydroponic Technique With Vetiver Grass (Vetiveria Zizanioides), Ismot Zereen, Zainul Abedin, Siddikur Rahman, Debasish Pandit

Applied Environmental Research

This research aimed to investigate the effects of hydroponically cultivated vetiver grass (Vetiveria zizanioides) on the treatment of tannery wastewater for chromium (Cr) removal in Bangladesh. The field experiment involved 9 containers, which were separated into 3 groups: tannery wastewater with hydroponically planted vetiver, tannery wastewater without vetiver (control), and a group with vetiver grown in tap water. The tap water group was used solely for plant growth assessment, whereas only the control and hydroponic vetiver groups were evaluated for Cr and water quality parameters. Throughout the 45-day trial period, Cr and other water quality parameters were analyzed …

Exploring The Co-Composting Potentials Of Raw Grease Trap And Grease Trap-Derived Soaps: Insights Into Grease Trap Modification, Calcium Supplementation, And Microbial Community Analysis, Pokchat Chutivisut, Panaya Kotchaplai, Bualuang Faiyue, Nattapong Tuntiwiwattanapun

Applied Environmental Research

Managing waste with grease traps poses a challenge because of the potential environmental issues associated with its disposal. In this study, two approaches were investigated to increase the biodegradability of grease trap waste: 1) converting raw grease trap waste into soap and 2) supplementing grease trap soap as inoculum with calcium material. The preparation of grease trap soap was optimized to attain a soap yield of 103% by utilizing a water-to-ethanol ratio of 9:1 at 80 °C for a processing time of 3 hours. A comparison of the composting results revealed higher nitrate yields with increased ratios of grease trap …

Microplastic Contamination In Commercially Important Bivalves Of Sorsogon Bay, Philippines, Sarina M.B. Arciga, Charmaine A. Malon, Kenneth N. Ballaran

Applied Environmental Research

Sorsogon Bay, a key fishing ground in the Philippines, is known for its commercially important bivalve species: Perna viridis, Atrina pectinata, and Paphia undulata. Despite their ecological and economic value, limited research has been conducted on microplastic contamination in bivalves harvested from this area. This study aimed to assess the abundance and types of microplastics in commercially important bivalves (P. viridis, A. pectinata, and P. undulata) from Sorsogon Bay, Philippines. Commercial bivalve samples were randomly collected, digested with 10% w/v potassium hydroxide (KOH) solution, filtered (8 µm), and examined under a compound microscope. …

Exploration Of Indigeneous Biosurfactant-Producing Bacillus Sp. From Petroleum Hydrocarbon-Contaminated Soil In Indonesia, Rizky Danang Susetyo, Wahyu Wilopo, Suwarno Hadisusanto, Endah Retnaningrum

Applied Environmental Research

Hydrocarbonolastic bacteria are valuable for the remediation of petroleum-polluted environments. The production of biosurfactants by such bacteria significantly enhances hydrocarbon bioavailability and increases remediation efficiency. One genus of hydrocarbonolastic bacteria with the potential to produce biosurfactants is Bacillus, yet strain-level diversity and local adaptations remain underexplored.Tthis study aimed to isolate and characterize hydrocarbonolastic bacteria belonging to the Bacillus genus from soil samples collected at Geopetroleum Teksas Wonocolo, Kedewan District, Bojonegoro Regency, Indonesia, which is a historically underreported hydrocarbon site. Additionally, the capacity of Bacillus to synthesize biosurfactants was examined. Bacillus strains capable of biosur-factant production were identified via a polyphasic …

Plasmonic Nanopore Sensing For The Characterization Of Viruses And Biomolecules, Scott Renkes

Bioengineering Dissertations - Archive

The rapid advancement of nanomedicine has enabled increasingly precise nanotherapeutic platforms, including targeted nanoparticles, monoclonal antibodies, and viral gene delivery vectors. As these technologies mature, quality control and analytical characterization have emerged as critical bottlenecks, particularly in systems where functional outcomes depend on one-to-one molecular or particle–biological interactions. Conventional ensemble-averaged techniques obscure heterogeneity that is often central to therapeutic efficacy, safety, and manufacturability. A prominent example is adeno-associated virus (AAV)–based gene therapy, where production yields heterogeneous populations of empty, partially loaded, and fully loaded capsids. Genome fill percentage and integrity directly influence therapeutic efficacy and dosing accuracy, while limited understanding …

Microwave Photonics-Assisted Interrogation Of Fiber-Optic Interferometric Sensors With Joint Frequency-Time Domain Analysis, Ruimin Jie, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber-optic interferometers are widely used in localized sensing applications due to their compact size, high sensitivity, and immunity to electromagnetic interference. In this paper, we propose and experimentally demonstrate a novel interrogation scheme for fiber-optic interferometric sensors, utilizing microwave photonics (MWP) and joint frequency-time domain analysis. As a proof of concept, a miniature fiber in-line Fabry-Perot interferometer (FPI) is integrated with a microwave photonic single-passband filter, enhanced by a dispersion compensation module to improve sensing performance. By applying an inverse Fourier transform to the system's complex frequency response, the time-domain representation of the signal is obtained, translating spectral shifts of …

Mapping Biomedical Ontology Terms To Ids: Effect Of Domain Prevalence On Prediction Accuracy, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

This study evaluates the ability of large language models (LLMs) to map biomedical ontology terms to their corresponding ontology IDs across the Human Phenotype Ontology (HPO), Gene Ontology (GO), and UniProtKB terminologies. Using counts of ontology IDs in the PubMed Central (PMC) dataset as a surrogate for their prevalence in the biomedical literature, we examined the relationship between ontology ID prevalence and mapping accuracy. Results indicate that ontology ID prevalence strongly predicts accurate mapping of HPO terms to HPO IDs, GO terms to GO IDs, and protein names to UniProtKB accession numbers. Higher prevalence of ontology IDs in the biomedical …

Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Normalization of medical concepts to an ontology is a key aspect of the natural language processing of biomedical text. It enables the mapping of medical expressions to standardized ontology terms and their identifiers, thereby enhancing the interoperability and computability of medical concepts. Although large language models (LLMs) can identify and standardize medical terms, they may struggle to accurately map ontology terms to their corresponding ontology identifiers. These challenges arise from the stochastic nature of LLMs, their limited exposure to uncommon ontology identifiers during training, and their lack of an integrated lookup mechanism. We generated test sets of synthetic terms to …

Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea

Electrical and Computer Engineering Faculty Research & Creative Works

Cardiovascular disease (CVD) is a leading cause of global mortality, highlighting the need for accurate diagnostic methods. This study benchmarks centralized and federated learning (FL) algorithms for heart disease binary classification using the UCI dataset, which includes 920 patient records from four hospitals in the USA, Hungary, and Switzerland. Our benchmark is supported by Shapley-value as well as Local Interpretable Model-agnostic Explanations (LIME) interpretability analyses to quantify feature importance for classification. In the centralized setup, various classification algorithms are trained on pooled data, with the Naive Bayes classifier achieving the highest test accuracy of 81.1%. Further, FL algorithms with four …

Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Cholesteryl ester hydrolase (CEH) is a critical enzyme in cholesterol ester hydrolysis, influencing cholesterol metabolism and efflux. This study demonstrates that CEH overexpression promotes free cholesterol efflux from macrophages, thereby reducing the lipid burden in existing atherosclerotic plaques. To enable targeted delivery, galactose-functionalized polyamidoamine (PAMAM) dendrimeric nanoparticles were utilized as nanocarriers for hepatic delivery of the CEH expression vector. The therapeutic potential of CEH plasmid-loaded dendrimeric nanoparticles was evaluated in Ldlr-/- mice. Results showed a significant reduction in total lesion area (21%) and aortic arch lesion area (23%) compared to baseline. Lesion component analysis revealed marked decreases in total cholesterol …

Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu

Chemistry Faculty Research & Creative Works

Bone tissue engineering (BTE) aims to repair bone defects using biocompatible materials with tailored geometries and pore structures, providing appropriate mechanical support and control over biodegradation kinetics to promote bone growth. In this study, we utilized digital light processing (DLP) 3D printing to fabricate scaffolds with varying pore sizes using polymer–ceramic slurries composed of polylactic acid (PLA) as the main polymer matrix, incorporated with hydroxyapatite (HA) and bioactive borate glass (BBG) at various ratios. We studied the effect of composition on rheological behavior, printability, mechanical properties, bioactivity, degradation rate, and biocompatibility. While HA increased viscosity and reduced printing accuracy, it …

Advances In Conductive Polymer-Based Flexible Electronics For Multifunctional Applications, Md Abdus Shahid, Md Mostafizur Rahman, Md Tanvir Hossain, Imam Hossain, Md Sohan Sheikh, Md Sunjidur Rahman, Nasir Uddin, Scott W. Donne, Md Ikram Ul Hoque

Michigan Tech Publications

The rapid developments in conductive polymers with flexible electronics over the past years have generated noteworthy attention among researchers and entrepreneurs. Conductive polymers have the distinctive capacity to conduct electricity while still maintaining the lightweight, flexible, and versatile characteristics of polymers. They are crucial for the creation of flexible electronics or gadgets that can stretch, bend, and adapt to different surfaces have sparked momentous interest in electronics, energy storage, sensors, smart textiles, and biomedical applications. This review article offers a comprehensive overview of recent advancements in conductive polymers over the last 15 years, including a bibliometric analysis. The properties of …

Development Of Self-Healing Polymer From Bio-Based Benzoxazine Blend With Poly(Ethylene Glycol) For Anti-Biofouling Applications, Pharaporn Yodkum

Chulalongkorn University Theses and Dissertations (Chula ETD)

Biofouling remains a significant challenge in marine industries, as conventional coatings often lose their antifouling efficacy once they become damaged. Incorporating self-healing capabilities into antifouling coatings has therefore emerged as a promising strategy to extend service life and maintain long-term performance. In this study, self-healing polymers were developed based on a bio-derived benzoxazine resin (E-fa), synthesized from renewable precursors including eugenol (a phenol source), furfurylamine (an amine source), and paraformaldehyde, and subsequently blended with poly(ethylene glycol) (PEG). The blends were formulated with varying weight ratios (95/5, 90/10, 85/15, and 80/20 wt/wt%) and PEG molecular weights (PEG-600, PEG-1500, and PEG-4000). This …

The Effect Of Liquid Conductivity On A Helium Plasma Jet And The Hydrogen Peroxide Production, Edwin A. Oshin, M. Ziaur Rahman, Chunqi Jiang

Bioelectrics Publications

Understanding plasma-liquid interactions and the impact of the electrical conductivity (σ) of liquid on plasma is important for plasma applications in water treatment and medicine. Ultrapure water, phosphate-buffered saline (PBS) solution, biological media, and sodium chloride (NaCl) solutions at various concentrations were used in this study to provide a broad range of conductivity values ranging from 0.055 μS cm⁻¹ to 222 mS cm⁻¹. A helium atmospheric pressure plasma jet (APPJ) impinging on liquid was generated in ambient air using a hollow-needle electrode that was powered by 200 ns, 7 kV pulses at a pulse repetition frequency of …

Food Waste Crisis In The United States Of America: The Known, The Overlooked And The Undisclosed, Sagarika Srivastava, David J. Tonjes

Technology & Society Faculty Publications

With a loss of 1,250 calories per day per person or 140 kg/p/yr, the United States (U.S.) has a large problem with food waste. The later a product is wasted in the supply chain, the greater its environmental cost. Many food waste mitigation efforts focus on the retail and consumer stages, but there is also considerable food waste in the production phase, which includes growing, harvesting, transportation, storage and processing. The study is conducted in two steps: a bibliometric analysis of 218 articles on food waste in the U.S., followed by an investigation of options to meet food waste recovery …

Bio-Inspired Sutures: Localizing Damage By Isolating Strain Energy, Diana A. Chen, Melissa M. Gibbons

School of Engineering: Faculty Scholarship

This study draws upon bio-inspiration from anatomical sutures found in hard structures, such as turtle shells, to explore if impact energy can be dissipated through geometric parameterization rather than relying on energy-absorbing materials. While previous finite element analysis studies identified optimal dovetail suture geometries for maximizing the global stiffness and toughness of archway structures, this paper explores how different suture geometries might optimize localization effects through segmentation to isolate damage caused by the propagation of strain energy. We compare the global toughness of each suture geometry to its scaling factor, defined as the ratio of strain energy in the center …

Introducing Catalizer: A Framework For Prototyping Models Of Biological Systems, Andy M. Day

Honors Theses

Modeling the light response system of Nannochloropsis oceanica brings

a set of challenges that make modeling difficult. Notably, potential models

may contain a large number of chemical species. A large number of

species creates a quadratic explosion in the number of potential pathways.

In addition, mathematically defining these pathways is error prone, yet

follows a surprising simple set of rules. We seek to create a domain specific

language which can precisely define these chemical reaction networks.

Once the networks have been defined, they can be exported as procedures

defined in popular programming languages for further analysis.

Salinity Effects On Cu(Ii) Bioremediation By Chlamydomonas Reinhardtii Microalgae, Jennifer Hughes

Honors Undergraduate Theses

Microalgae offer a sustainable approach to wastewater treatment by removing pollutants such as excess nutrients, CO₂, and heavy metals. Among various species, Chlamydomonas reinhardtii shows strong potential in removing Cu(II) ions from wastewater. In addition, salinity stress in C. reinhardtii has been linked to morphological and metabolic changes that enhance lipid and phytochemical production. While salinity stress has been studied for enhancing biofuel production, its impact on microalgal removal of heavy metals, particularly Cu(II), remains largely unexplored. Understanding how varying salinity conditions affect both algal growth and the efficiency of Cu(II) remediation could provide critical insights for improving integrated wastewater …

A Century Of Sediment Metal Contamination Of Mar Menor, Europe's Largest Saltwater Lagoon, Irene Alorda-Montiel, Valentí Rodellas, Ariane Arias-Ortiz, Albert Palanques, Andrea G. Bravo, Júlia Rodriguez-Puig, Aaron Alorda-Kleinglass, Carlos Green-Ruiz, Marc Diego-Feliu, Pere Masqué, Javier Gilabert, Jordi Garcia-Orellana

OES Faculty Publications

Coastal enclosed ecosystems, such as lagoons, are vulnerable to anthropogenic impacts because they favor the accumulation of contaminants from the surrounding watersheds, particularly in their sediments. Europe's largest saltwater lagoon, the Mar Menor (SE, Iberian Peninsula), is a highly impacted ecosystem and the first in the continent to be granted personhood rights. Based on a high-resolution spatial and temporal dataset, we present the historical reconstruction of metal contamination in this ecosystem during the last century. Our results highlight that sediment metal contamination has been mainly driven by the development of the mining industry in the nearby Sierra Minera de Cartagena-La …

Ensemble Machine Learning Approaches For Bathymetry Estimation In Multi-Spectral Images, Kazi A. Islam, Omar Abdul-Hassan, Hongfang Zhang, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

OES Faculty Publications

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs …

Traction Force Microscopy Using An Epifluorescence Microscope: Experimental Considerations And Caveats, Zaria Booth, Mazen Mezher, Rudra Patel, Venkat Maruthamuthu

Mechanical & Aerospace Engineering Faculty Publications

Forces exerted by cells due to their internal contractility play fundamental roles in a host of processes, including adhesion, migration, survival and differentiation. Traction force microscopy (TFM) enables the determination of forces exerted by cells or cell collectives on their environment, which is typically taken to be an extra-cellular matrix (ECM)-coated substrate. Sample preparation for TFM involves the plating of cells onto an environment embedded with fiducial markers. The imaging of these fiducial markers in the presence and absence of the cells then enables calculation of the displacement of localized regions of the environment, and, consequently, the spatial distribution of …

Existence And Stability Of A Mathematical Model Solution Of Classical Brain Metabolite Variations In The Circadian Rhythm, Eman A. A. Ziada

Mansoura Engineering Journal

This research aims to study an important model in view of its applications to brain metabolite variations in the circadian rhythm. We will discuss the solution existence and stability of the general form of this model and give its solution by using numerical and analytical methods. The numerical method is the proposed numerical method (El- Sayed method), and two analytical methods, the Adomian decomposition method (ADM) and the Picard method (PM). The uniqueness of the solution will be proved, the convergence of the series solution will be discussed, and an error analysis will be given. The numerical solution of the …

Influence Of Unmanned Aerial Vehicle (Uav) Payloads And Flight Speeds On Pesticide Droplet Deposition: Indoor Testing Rig Study, Siti Amni Ismail, Azmi Yahya, Ahmad Suhaizi Mat Su, Anas Mohd Mustafah, Norhayu Asib

ASEAN Journal on Science and Technology for Development

This study aims to determine droplet deposition resulting from dynamic change in payloads and flight speeds of Unmanned Aerial Vehicle (UAV) during operation. The study was conducted at Universiti Putra Malaysia, Serdang, Malaysia. The Advansia A1 hexacopter was first set to fly at combinations of 3 payloads (3.3, 6.6, and 9.9 kg) with 3 flight speeds (3, 5 and 7 m/s) to collect individual rotor RPM, which will later be used to set the rotors’ speed during indoor testing experiment. During the experiment, actual pesticide (Alosa EC) was used at 0.5% concentration in the spray deposition test. The droplet deposition …

Optimization Of Persulfate Activation System Using Ferrous Sulfate For Toc Removal From Real Domestic Wastewater, Mohamed Fouad, Mohamed Mossad, Mohamed Gar Alalm, Mahmoud Samy

Mansoura Engineering Journal

The reuse of treated wastewater is increasingly recognized as a sustainable solution to address global water shortage. This study investigates the effectiveness of a persulfate-based advanced oxidation process (AOP) using sodium persulfate (Na2S2O8) activated by ferrous sulfate (FeSO4) as a tertiary treatment for secondary effluents. Real municipal wastewater was collected from Agouzain Wastewater Treatment Plant (WWTP) in Kafr El-Sheikh, Egypt. A Box Benkhen design (BBD) was employed to optimize three key variables: FeSO4 dose (0.5–2.0 g/L), Na2S2O8 dose (0.5–2.0 g/L), and pH (3.0–9.0), with total organic carbon (TOC) removal as the main response. Under optimized conditions (0.50 g/L FeSO4, 2.00 …

A Large Electroencephalogram Database Of Freewill Reaching And Grasping Tasks For Brain Machine Interfaces, Bhoj Raj Thapa, John Boggess, Jihye Bae

Electrical and Computer Engineering Faculty Publications

Brain machine interfaces (BMIs) offer great potential to improve the quality of life for individuals with neurological disorders or severe motor impairments. Among various neural recording modalities, electroencephalogram (EEG) is particularly favorable for BMIs due to its noninvasive nature, portability, and high temporal resolution. Existing EEG datasets for BMIs are often limited to experimental settings that fail to address subjects’ freewill in decision making. We present a large EEG dataset, containing a total of 6808 trials, recorded from 23 healthy young adults (eight females and 15 males with an age range from 18 to 24 years) while performing reaching and …

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Social Engineering Scenario Generation For Awareness-Based Attack Resilience, Jade Webb

Master's Projects

Social engineering is found in a strong majority of cyberattacks today, as it is a powerful manipulation tactic that does not require the technical skills of hacking. Calculated social engineers utilize simple communication to deceive and exploit their victims, all by capitalizing on the vulnerabilities of human nature: trust and fear. When successful, this inconspicuous technique can lead to millions of dollars in losses. Social engineering is not a one-dimensional technique; criminals often leverage a combination of strategies to craft a robust yet subtle attack. In addition, offenders are continually evolving their methods in efforts to surpass preventive measures. A …

Cca Analysis Using Computer Vision Techniques, Rahul Thakur

Master's Projects

Coral reefs are an essential part of the marine ecosystem. They perform a wide variety of tasks, some directly and others indirectly. They can produce oxygen, absorb carbon dioxide, along with supporting ocean habitat. Crustose Coralline Algae (“CCA”) plays an important role in helping provide structural support to Coral Reef ecosystems. However, global warming is causing ocean water to become more acidic resulting in coral bleaching. This is leading to changes in coral environments and causing coral deaths at alarming rates. Object detection using computer vision techniques, specifically deep learning, can help to monitor coral reef health and identify CCA …

Retrieval-Augmented Generation For Survival Analysis In Cancers: Methods And Evaluation On The Surveillance, Epidemiology, And End Results Database, Jyothi Vaidyanathan

Master's Projects

Healthcare is one of the most important fields that benefits from advancements in Artificial Intelligence (AI). From classic models like linear regression to cuttingedge transformers, AI is applied across various healthcare subdomains, such as drug discovery, predictive analytics, and personalized medicine, to name a few. These techniques enable medical practitioners to make more informed decisions, significantly improving both the speed and accuracy of diagnoses and treatments. Machine learning has played a transformative role in oncology, especially in areas like early detection, diagnosis, treatment planning, and patient monitoring, by analyzing medical images, clinical information, genomic data, sensor information. Our research aims …

Florida Statewide Coastal Restoration Guide, Melinda J. Donnelly, Matthew Martin, Christen Fleming, Kelly Kibler, Linda Walters, Patrick Shearer, Lauren Jennison, Erika Lin, George Zaragoza

Faculty Scholarship and Creative Works

The Statewide Coastal Restoration Guide (SCRG) is a comprehensive planning resource developed through a collaboration between Florida Department of Environmental Protection (FDEP), University of Central Florida (UCF), and Resource Environmental Solutions (RES) to strengthen and unify shoreline restoration efforts across Florida. With over 4,500 miles of estuarine shoreline, Florida’s coasts are vital to the state’s ecological health, economic prosperity, and community resilience. However, they face increasing threats from sea level rise, stronger storms, erosion, habitat degradation, and development. The SCRG responds to these challenges by providing science-based, non-regulatory guidance for implementing resilient, nature-based restoration strategies that protect both ecosystems and …