Physical Sciences and Mathematics Commons^™

The Δ¹³C Signature Of Dissolved Organic And Inorganic Carbon Reveals Complex Carbon Transformations Within A Salt Marsh, Meagan J. Eagle, Kevin D. Kroeger, John W. Pohlman, Joseph J. Tamborski, Zhaohui Aleck Wang, T. W. Brooks, Jennifer O. Keefe Suttles, Adrian Mann

OES Faculty Publications

Coastal wetlands have high rates of atmospheric CO₂ uptake, which is subsequently respired back to the atmosphere, stored as organic matter within flooded, anoxic soils, or exported to the coastal ocean. Transformation of fixed carbon occurs through a variety of subsurface aerobic and anaerobic microbial processes, and results in a large inventory of dissolved carbon. Carbon source and the roles of aerobic respiration, sulfate reduction, and methane cycling were evaluated within salt marsh peat and the underlying sandy subterranean estuary. There is a large increase in dissolved inorganic carbon (DIC, 7,350 ± 3,900 μmol L^-¹), dissolved organic carbon …

Characterization Of Microbial Biofilms On Marine Plastics: Community Development And Density Implications For Vertical Transport Dynamics, Gregory M. Joern, Rut Pedrosa-Pàmies, Xiangtao Jiang, Zhanfei Liu, Alexander B. Bochdansky

OES Faculty Publications

Marine plastic pollution poses a significant and escalating threat to ocean ecosystems, with microbial colonization on plastics playing a critical role in determining their environmental fate. Despite the recognized importance of microbial biofilms, their composition, dynamics, and functional contributions on buoyant plastics remain poorly understood. In this study, we leveraged a novel integrative approach by simultaneously employing 16S, 18S, and ITS sequencing alongside microscopy, lipidomics, pigment analysis, adenosine triphosphate and biogenic silica quantification. This comprehensive methodology allowed for a thorough characterization of microbial growth and community dynamics on plastic debris in a mid-latitude, tidal sub-estuary. Our analyses consistently identified diatoms, …

The Effect Of Temperature And Salinity On Margalefidinium Polykrikoides Group Iii Va, Usa Strain Growth, Eduardo Pérez-Vega, Margaret R. Mulholland, Katherine E. Crider, Kimberly E. Powell, P. Dreux Chappell, Alexander Bochdansky

OES Faculty Publications

Margalefidinium polykrikoides is a cosmopolitan dinoflagellate that blooms in coastal waters. Despite genomic evidence that it belongs to Group III and so closely related to isolates from Puerto Rico, Malaysia, North America, and Central America, M. polykrikoides blooms in the Chesapeake Bay at warmer temperatures and lower salinities than in coastal ecosystems occupied by its closest relatives. In this study, the effect of temperature and salinity on the growth rate and total cell yield of an M. polykrikoides VA culture isolate were examined and compared with environmental observations made during M. polykrikoides blooms in the Chesapeake Bay. M. polykrikoides group …

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 …

Yucatan Hurricane Activity Highlights Common Era Tropical Cyclone Dipole, Richard M. Sullivan, Peter J. Van Hengstum, Elizabeth J. Wallace, Sloan Coats, Jeffrey P. Donnelly, Robert Korty, Shawna N. Little, Martin G. Maas Vargas, Luis Mejia-Ortiz, Eduard G. Reinhardt, Courtney Schumacher, Anne E. Tamalavage, Tyler S. Winkler

OES Faculty Publications

Tropical cyclone (TC) impacts along the western Atlantic and Caribbean margin are not spatially uniform. Proxy based reconstructions of Common Era TC activity highlight this non-uniform distribution at centennial-millennial timescales. However, the sparse geographic scope of these reconstructions impedes our assessment of TC landfalls across broader spatial domains. This work presents a compilation of new and existing TC reconstructions from the Yucatan Peninsula for comparison with a contemporaneous compilation from New England, showing that these regions occupy distal nodes of a low-frequency TC dipole. Increased Yucatan (New England) storminess is closely linked to intervals of Northern Hemisphere warming (cooling) and …

Impact Of Submarine Groundwater Discharge On Microbial Communities In A Highly Anthropized Coastal Lagoon (Mar Menor, Se Spain), Daniel Romano-Gude, Júlia Dordal-Soriano, Júlia Rodriguez-Puig, Andrea G. Bravo, Irene Alorda-Montiel, Aaron Alorda-Kleinglass, Marc Diego-Feliu, Cristina Romera-Castillo, Rebeca Mallenco-Fornies, Javier Gilabert, Jordi Garcia-Orellana, Valentí Rodellas, Clara Ruiz-González

OES Faculty Publications

Submarine groundwater discharge (SGD) supplies large quantities of nutrients and other terrestrial elements to coastal ecosystems, impacting marine biota and ecosystem functioning. Despite the relevance of prokaryotes for marine biogeochemistry, little is known about their responses to groundwater inputs. Here we explored the impact of SGD on the spatiotemporal patterns of prokaryotic communities from the Mar Menor (Murcia, Spain), a highly anthropized hypersaline coastal lagoon that receives large amounts of nutrient-polluted SGD. Using 16S rRNA amplicon sequencing, activity assays, and flow cytometry, we investigated the dynamics of prokaryotic communities across the lagoon and its connected environments (freshwater streams, groundwater, soils, …

The Next Frontier In Computer Science, Trends And Research Opportunities, Mostafa Abdulghafoor Mohammed, Z. T. Al-Qaysi, Tahsien Al-Quraishi

Mesopotamian Journal of Computer Science

No abstract provided.

Woa-Covid-19: Whale Optimization Algorithm For Selection Of Multi-Examination Features Based On Covid-19 Infections, Karrar Hameed Abdulkareem, Mazin Abed Mohammed, Zaid Abdi Alkareem Alyasseri, Dawood Zahi Khutar, Osama Ahmad Alomari

Mesopotamian Journal of Computer Science

Since its emergence in late 2019, COVID-19 (Coronavirus Disease 2019) has become one of the most critical global health threats, claiming millions of lives and placing many more at serious risk. The complexity of diagnosing COVID-19 lies in the wide range of clinical and examination features involved, prompting researchers to explore various advanced diagnostic methods. However, one of the main challenges is identifying the most relevant features that can streamline and improve diagnostic accuracy. In this study, we propose a feature selection approach based on the Whale Optimization Algorithm (WOA) to identify key examination indicators associated with COVID-19. We used …

Purification Of Recombinant His6-Gfp-Preptin Fusion Protiens, Apoorva Kollaram

Theses and Dissertations

Preptin, a 34-amino-acid peptide derived from proinsulin-like growth factor II, has emerged as a promising therapeutic candidate for both Type 2 diabetes mellitus and osteoporosis. Its dual functionality—stimulating insulin secretion without inducing hypoglycemia and promoting osteoblast proliferation—positions it as a unique alternative to traditional sulfonylureas and osteogenic agents. In this study, we developed a purification protocol for green fluorescent-preptin fusion proteins. These fusion proteins will be used to investigate the functional significance of residues Pro17, Val18, Gly19, Trp27, Lys28, and Gln29 in rat preptin, which shares high sequence similarity with the human form. Site-directed mutagenesis was performed using NEB Q5 …

Qlorax: Heuristic-Guided Fine-Tuning Of Llama-2 For Domain Adaptation In Entrepreneurship, Gaurob Saha

Theses and Dissertations

This thesis presents a study on the fine-tuning of large language models (LLMs) for domain-specific applications using limited data. We fine-tuned the LLaMA-2 (7B) model on a curated entrepreneurial dataset containing 3,545 human-written question-answer pairs, of which 3,095 were used for training and 450 were reserved for evaluation. A complete fine-tuning and evaluation pipeline was developed, which included clustering human-written answers, generating centroid-based summaries for each cluster, and evaluating the model's generated responses through cosine similarity.

Training was carried out over five epochs, with model performance evaluated after each epoch. The fine-tuned model demonstrated strong semantic alignment with human-written content, …

Synthesizing Deception: Countering Large Language Model-Generated Phishing Campaigns Through Adaptive Semantic Anomaly Detection, Bekim Fetaji, Debabrata Samanta

Mesopotamian Journal of Computer Science

The paper fills in a gap in the literature that demonstrates an insufficient number of sturdy detection schemes that can recognize the small semantic aberrations inherent in LLM-generated deceptive text. Our proposed co-design hybrid model is Semantic Anomaly Detection with Isolation Forest (SADI) model that combines the synergistic mixture of a fine-tuned transformer-based LLM for deep semantic feature extraction with Isolation Forest algorithm that detects anomalies efficiently. This study introduces SADI, an adaptive semantic-anomaly detector for large-language-model phishing emails. Using a corpus of 10 000 messages, SADI attains an F1 score of 0.981 (95 % CI 0.978–0.984) and processes a …

Towards Achieving The Un Sustainable Development Goals: The Role Of Ai In Municipality Services, Thabit Sultan Mohammed, Karim Mohammed Aljebory, Ahmed Thabit Sultan

Mesopotamian Journal of Computer Science

In 2015, the United Nations adopted the Sustainable Development Goals (SDGs) to end poverty, protect the planet, and ensure global peace and prosperity by 2030. However, progress has been hindered by challenges like the COVID-19 pandemic, climate change, funding shortages, political instability, and data limitations. Municipal services, crucial to achieving the SDGs, provide essential functions like waste management, healthcare, and public safety. Artificial Intelligence (AI) offers innovative solutions to enhance these services, improving urban sustainability and fostering public-private collaboration. This research examines AI's role in municipal services, analyzing its applications, benefits, challenges, and future potential through case studies and expert …

Enhancing Routing Efficiency In Vanets By Leveraging 5g To Mitigate Congestion, Yusor Rafid Bahar Al-Mayouf, Omar Adil Mahdi, Heba Hussain Hadi, Suleman Khan, Mazin Abed Mohammed

Mesopotamian Journal of Computer Science

Transportation networks impact millions of people daily. Their efficiency immediately affects travel time, safety, and environmental sustainability. Unfortunately, various issues hinder the expected performance and efficiency of these networks. Traffic congestion is an up-to-date issue in the urban environment. Fuel consumption is high because travel time has increased, which has a passive environmental impact. Extensive research has been conducted to progress the intelligent transportation systems installed on communication networks and information to treat this congestion. However, there is a significant amount of affront residue in combining real-time data, estimation analytics, and 5G abilities effectively. This paper offers a novel routing …

Enhanced Tea Algorithm Performance Using Affine Transformation And Chaotic Arnold Map, Nada Hussein M. Ali, Mays M. Hoobi, Sura Abed Sarab Hussien

Mesopotamian Journal of Computer Science

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing …

Lightweight Deep Reinforcement Learning Model For Energy-Efficient Resource Allocation In Edge Computing, Ghassan A. Abed, Mohanad A. Al-Askari

Mesopotamian Journal of Computer Science

A lightweight digital twin model for a single 6G cell operating in the D-band (140 GHz) with a 1 GHz bandwidth is presented in this work with the goal of assessing the cell's capacity, coverage, and terminal time in order to support extended reality (XR) applications. With a tangent dispersion of 3 dB and a path exponent of n = 2.2, the model is based on the free-space loss equation as per ITU-R Recommendation P.525. The instantaneous capacity is determined using the Shannon-Hartley theorem. Three XR sessions are created every minute using a Poisson method, and their durations are determined …

Automated Video Colorization Techniques For Enhanced Visual Realism And Computational Efficiency, Zahoor M. Aydam, Nidhal K. El Abbadi

Mesopotamian Journal of Computer Science

Automatic video colorization remains a challenging computer vision task, particularly when ensuring semantic accuracy and temporal coherence across dynamic, multi-scene content. Existing methods often rely on a single fixed reference image, which fails to adapt to abrupt scene changes or variations in lighting and texture. This study presents a hybrid deep learning framework that dynamically selects multiple reference images per scene using adaptive thresholds derived from the Structural Similarity Index Measure (SSIM) and deep features extracted via a ResNet50 backbone with Generalized Mean Pooling (GeM). The framework integrates three specialized modules pre-processing, reference image processing, and attention-based colorization—operating in the …

Enhanced Iot Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection And Adaptive Smote, Sura Abed Sarab Hussien, Mustafa S. Ibrahim Alsumaidaie, Nada Hussein M. Ali

Mesopotamian Journal of Computer Science

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrate that GWO reduces features from 32 …

Using Wearable Technology For Context-Aware Of Pilgrimage Management System During/Post-Pandemic Of Covid-19, Fatina Shukur, Ahmed Al-Fatlawi, Safaa Jasim Mosa, Nasir Ibrahim

Mesopotamian Journal of Computer Science

Hajj is an annual event placed in Saudi Arabia. It is one of the largest religious gatherings, such that it gathers millions of pilgrims from all around the world. The pandemic of Covid-19 is not over yet, and could likely be part of our life for a long time. Also, it is negatively affecting such mass gatherings. The aim of this research is to facilitate the overall hajj event while maintaining peoples’ health, safety, and security. Therefore, we use a technology that helps to reduce direct contact between pilgrims themselves as well as with other entities, such that human interaction …

Highly Sensitive Diffractive Optical Structures For Detection Of Volatile Organic Compounds, Faolan Radford Mcgovern

Doctoral

From aerospace to agriculture, sensors play a fundamental role in many aspects of modern life. Sensors form an integral part of the complex systems and devices required for the continued functioning and development of services and industries across society. The use of sensors is paramount in areas affecting human health, one such area being the monitoring of indoor air quality, in particular the detection of volatile organic compounds (VOCs). Human contact with VOCs has been associated with many health complications, including skin and eye irritation, cardiovascular damage, and cancers. Optical, electrical, gravimetric, and chemical sensors have been developed for VOC …

A Modern Optimization Approach With Data-Driven Analytical Modeling For The Healthcare Business Segment (Hbs) From The S&P 500, Aditya Chakraborty, Chris Tsokos

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Introduction: The S&P consists of eleven business segments, which are classified according to the type of industry. The current study focuses on developing a non-linear analytical model for the Healthcare Business Segment (HBS) of the S&P 500, as a function of different economic & financial indicators. Materials and Methods: The analytical model used six financial indicators together with four economic indicators to predict the weekly average closing price (WCP) of HBS stocks. Johnson’s SB transformation corrected skewness, while desirability-based optimization identified indicator values maximizing WCP. The model’s performance and generalizability were validated through repeated 10-fold cross-validation. Results: All attributable contributors …

Pediatric Cancer Incidence, Temporal Trends, And Mortality In The United States By Health Disparities Indicators, Seer (1973-2014), Prachi P. Chavan, Laurens Holmes Jr.

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pediatric cancer incidence has been increasing in the United States, despite improvement in pediatric cancer survival. This steady increase in incidence trends is not completely understood but maybe associated with social and environmental factors. In this study we aimed to assess the cumulative incidence, temporal trends, and mortality rates in pediatric cancer. Additionally, we examined sub-group variability in both incidence and mortality rates. Methods: Data from Surveillance, Epidemiology, and End Results (SEER) −18 from 1973–2014 were used for the purpose of analysis in this study. Age-adjusted incidence rates were used to assess temporal trends in cancer among children aged < 1–19 years. Univariable and multivariable binomial regression models were used to examine the association between race and cancer mortality while adjusting for potential confounders. Results: There were 92,594 cancer diagnoses during this period. White children comprised 74,758, (80.7%), black children 10,030, (10.8%), and other races 6648, (7.2%). Overall the age-adjusted cumulative incidence was slightly higher among white children (16.4%) than black children (12.4%) and other (13.0%). Children aged 15–19 years and those in metropolitan regions were more likely to be diagnosed with pediatric cancer. Relative to females, males were 16% more likely to die from the disease [adjusted Risk Ratio (aRR): 1.16, 95% Confidence Interval (CI): 1.09–1.22]. Additionally, compared to white children, black children had higher mortality rates [(aRR): 1.37, 99% CI: 1.23–1.52]. Conclusions: There is an increasing trend in pediatric cancer incidence; while white children have the highest incidence, black children and males indicated a survival disadvantage, indicative of racial and sex variability in overall pediatric cancer in the United States.

Structural Optimization And Stability Enhancement Of Uba(2) And Ntl9 Using The Computational Tool: Emcast, Bahar Ghazi Esfahani

Graduate Student Theses, Dissertations, & Professional Papers

This study enhances protein stability prediction by refining EmCAST (Empirical C-Alpha Stability Tool), a computational tool used to identify stabilizing mutations in protein domains. We applied EmCAST to two model proteins: the α-helical ubiquitin-associated domain 2 (UBA(2)) and the α/β N-terminal domain of ribosomal protein L9 (NTL9). Protein stability is critical for proper function, and mutations can lead to misfolding and disease. To validate EmCAST’s predictions, guanidine hydrochloride-induced denaturation was monitored using circular dichroism (CD) spectroscopy for both wild-type and mutant variants. Results guided refinements to EmCAST’s algorithm, incorporating new experimental datasets to improve accuracy. Additionally, we examined the assumption …

Development Of Fast And Comprehensive Approaches For Gunshot Residue Interpretation Using Ambient Ionization, Mass Spectrometry, And Microparticle Sampling Studies, Thomas Dimmey Ledergerber

Graduate Theses, Dissertations, and Problem Reports (ETD)

The information derived from the forensic examination of gunshot residue (GSR) can be critical during the investigative and trial stages in the criminal justice system. However, the complexity of the GSR deposition, transfer, and persistence mechanisms calls for meticulous handling and identification processes. Novel advances in evidence interpretation and analysis via instrumental methods are current areas of growing interest that must be pushed along the chain from research to practice in a timely manner. Therefore, this research focuses on developing both rapid and comprehensive methods for detecting gunshot residue evidence and effectively communicating its significance to the investigators or trier …

3d Printed Microfluidic Platforms For Elisa-Based Diagnostics: Advancing Toward Point Of Care, Brandi Marie Binkley

Graduate Theses, Dissertations, and Problem Reports (ETD)

Protein biomarker detection is a critical analytical method for quantifying proteins in biological samples. It is relevant not only in medical diagnostics and research but also numerous other fields such as environmental monitoring, pharmacology, food safety, and biotechnology. Sensitive detection at picogram-per-milliliter (pg/mL) levels is essential for diagnosing diseases, monitoring progression, and tailoring treatments, especially for low-abundance biomarkers like troponin, interleukin 6, carcinoembryonic antigen (CEA), activin A, and vascular endothelial growth factor (VEGF). Immunoassays, particularly enzyme-linked immunosorbent assays (ELISAs), are the gold standard for protein biomarker detection due to their high specificity and sensitivity. The development of point-of-care (POC) diagnostic …

Do Dung Beetles Sink Or Swim: Exploring Dung Beetle Response To Precipitation, Lauren T. Cheshire

Graduate Theses, Dissertations, and Problem Reports (ETD)

Global climate change constitutes a major threat to biodiversity and ecosystem services of many taxa. The Mid-Atlantic region of the US is expecting to see an increase in extreme precipitation events and flooding. Dung beetles (Scarabaeinae) can tunnel below the soil surface allowing for water to dissipate into the soil rather than sit on the surface and add to flooding conditions. They also can decrease methane emission by burying dung and reduce outbreaks of pests that prefer the moist environment of dung. They contribute roughly $380 million in ecosystem services annually in the United States, yet their services may be …

Developing Consensus-Based Methods For The Examination And Interpretation Of Contemporary Vehicle, Architectural, And Portable Electronic Device Glasses By Micro-X-Ray Fluorescence Spectrometry, Zachary Bailey Andrews

Graduate Theses, Dissertations, and Problem Reports (ETD)

Glass is a trace material that is commonly encountered during investigations of violent crimes. When glass is recovered at crime scenes, it can be used to establish links between suspects, victims, and the scene itself. The most discriminatory form of analysis for glass evidence is elemental analysis, and micro-X-ray fluorescence spectrometry (µXRF) is becoming an increasingly common technique used for this purpose. Recent advances in µXRF technology, such as the introduction of silicon drift detectors (SDD) and improved polycapillary optics are promising in enhancing the capabilities for the examination of glass evidence in forensic investigations. However, along with these advances …

Community-Wide Impacts Assessment Of Silver Carp (Hypophthalmichthys Molitrix) In The Ohio River, Luka Marques

Graduate Theses, Dissertations, and Problem Reports (ETD)

Invasive species can cause measurable impacts on the properties of recipient ecosystems, with effects that often vary spatially and temporally. One of the most complex and pressing invasion cases in the United States involves invasive carp. Invasive carp have quickly expanded throughout the Mississippi River Basin, with ecological impacts that may vary across space and time. Silver Carp has the potential to provoke community-wide impacts on native fish abundances and food webs of native fish communities. My study area ranged from the confluence of the Mississippi River and the Ohio River to R.C. Byrd Lock and Dam. The Ohio River …

Modeling Energetic Electron Precipitation: Radiation Belt Loss, Its Drivers, And Atmospheric Impacts, Zhi Gu Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

Energetic electrons in the terrestrial outer radiation belt present significant hazards to spacecraft systems and human operations in space. The intensity of these electrons can vary rapidly and dramatically during geomagnetic storms, governed by a complex competition between acceleration and loss processes. Among these, precipitation into the atmosphere via resonant wave-particle interaction acts as a key loss mechanism. This dissertation focuses on improving the quantification of energetic electron precipitation using physics-based modeling constrained by low-altitude satellite observations.

We begin by developing and validating the Drift-Diffusion model, which simulates low-altitude electron dynamics while accounting for azimuthal drift, pitch-angle diffusion, and atmospheric …

Functionalized Carbon Nanohoops: Synthesis, Structural Insights, And Pathways To Carbon Nanobelts, Liu Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

The development of structurally defined carbon nanostructures has gained significant attention due to their unique electronic, optical, and mechanical properties. Cycloparaphenylenes (CPPs), also known as carbon nanohoops, and carbon nanobelts (CNBs) represent key molecular segments of carbon nanotubes (CNTs), offering a bottom-up approach to precise nanotube construction. This dissertation focuses on the synthesis, structural characterization, and functionalization of CPPs, as well as the development of novel synthetic pathways for CNBs. A series of functionalized CPPs, including [9]-, [12]-, [15]-, and [18]CPPs, were synthesized using a modular approach involving a Diels-Alder adduct formation followed by a Ni(cod)2/bpymediated macrocyclization reaction. The influence …

Individual And Collective Properties Of Tunable Photochemical Belousov-Zhabotinsky Micro-Reactors, Kudakwashe Benedict Shumba

Graduate Theses, Dissertations, and Problem Reports (ETD)

Cell-like model chemical systems are powerful tools that can be used to explore the role of intercellular coupling on population level behaviors in communities of biological cells. Firstly, we present a new method for fabricating such micro-reactors using the photosensitive Belousov–Zhabotinsky (BZ) reaction system employed in silica microparticles. These BZ micro-reactors have a tunable response to photochemical coupling, varying from a fully excitatory response to a fully inhibitory response. Their response can be tuned through variations in either the reactive mixture or, on an individual micro-reactor level, by changes in the synthesis temperature used during the fabrication of the silica …