Digital Commons Network^™

Nonlinear Classifiers For Wet-Neuromorphic Computing Using Gene Regulatory Neural Network, Adrian Ratwatte, Samitha Somathilaka, Sasitharan Balasubramaniam, Assaf A. Gilad

School of Computing: Faculty Publications

The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational principles resemble an artificial neural network (ANN), which can pave the way for the development of wet-neuromorphic computing systems. Genes are integrated into gene-perceptrons with transcription factors (TFs) as input, where the TF concentration relative to half-maximal RNA concentration and gene product copy number influences transcription and translation via weighted multiplication before undergoing a nonlinear activation function. This process yields protein concentration as the …

Plas 439: Organic Farming And Food Systems Faculty-Led Inquiry Into Reflective Scholarly Teaching Benchmark Portfolio, Christian Stephenson

UNL Faculty Course Portfolios

Organic Farming and Food Systems is a senior and graduate level course for students in the Department of Agronomy and Horticulture. This course was previously offered but has been significantly modified as I have taken on responsibility for the course. Goals for the course include student comprehension of the methods of organic and regenerative farming and the impacts of those methods on economic, environmental, and social sustainability. An additional goal is to build student competency in the evaluation of primary, secondary, and tertiary information resources and critical thinking surrounding issues in food production. Assessment for the course was through diverse …

Size-Constrained Weighted Ancestors With Applications, Philip Bille, Yakov Nekrich, Solon P. Pissis

Michigan Tech Publications

The weighted ancestor problem on a rooted node-weighted tree T is a generalization of the classic predecessor problem: construct a data structure for a set of integers that supports fast predecessor queries. Both problems are known to require Ω(log log n) time for queries provided O(n poly log n) space is available, where n is the input size. The weighted ancestor problem has attracted a lot of attention by the combinatorial pattern matching community due to its direct application to suffix trees. In this formulation of the problem, the nodes are weighted by string depth. This research has culminated in …

Comparison Of Methods For Creating Populations Of Models By Solving Stochastic Inverse Problems, Elizabeth Epstein

Theses

Given a parametric family of models and observational data, a researcher may be faced with an inverse problem: what distribution of parameters best creates a set of models that produce the observed data? Traditionally, Markov Chain Monte Carlo (MCMC) has commonly been used as a method to solve these stochastic inverse problems. In recent years, however, Generative Adversarial Networks (GANs) have been employed. The effectiveness of Markov Chain Monte Carlo methods as compared to a conditional generative adversarial network (cGAN) when applied to a family of models produced by a system of ordinary differential equations that model viral load over …

Exploring The Tradeoff Between Data Privacy And Utility With A Clinical Data Analysis Use Case, Eunyoung Im, Hyeoneui Kim, Hyungbok Lee, Xiaoqian Jiang, Ju Han Kim

Faculty, Staff and Student Publications

BACKGROUND: Securing adequate data privacy is critical for the productive utilization of data. De-identification, involving masking or replacing specific values in a dataset, could damage the dataset's utility. However, finding a reasonable balance between data privacy and utility is not straightforward. Nonetheless, few studies investigated how data de-identification efforts affect data analysis results. This study aimed to demonstrate the effect of different de-identification methods on a dataset's utility with a clinical analytic use case and assess the feasibility of finding a workable tradeoff between data privacy and utility.

METHODS: Predictive modeling of emergency department length of stay was used as …

Anion Binding And Sensing Using Cs124-Sensitized Luminescent Terbium Complexes, Alessandro Rizzi, Minhee Lee, Wade Grabow, Olivia Brooks, Helena Nguyen, Neal Yakelis, Clarisse Vanderfeltz

Honors Projects

Two terbium complexes with varying degrees of intramolecular coordination, Tb:DO2A-Cs124 and Tb:DOTA-Cs124, were prepared. Their capacity to detect biologically and environmentally relevant anions through their luminescence changes was investigated. Tb:DOTA-Cs124 demonstrated exceptional selectivity as a sensor for nitrite, while Tb:DO2A-Cs124 detects nitrite, phosphates, and a range of carboxylate-containing anions.

Multi-Class Emotion Classification With Xgboost Model Using Wearable Eeg Headband Data, James Khamthung, Nibhrat Lohia, Seement Srivastava

SMU Data Science Review

Electroencephalography (EEG) or brainwave signals serve as a valuable source for discerning human activities, thoughts, and emotions. This study explores the efficacy of EXtreme Gradient Boosting (XGBoost) models in sentiment classification using EEG signals, specifically those captured by the MUSE EEG headband. The MUSE device, equipped with four EEG electrodes (TP9, AF7, AF8, TP10), offers a cost-effective alternative to traditional EEG setups, which often utilize over 60 channels in laboratory-grade settings. Leveraging a dataset from previous MUSE research (Bird, J. et al., 2019), emotional states (positive, neutral, and negative) were observed in a male and a female participant, each for …

Minimal Specialization: The Coevolution Of Network Structure And Dynamics, Annika King

Theses and Dissertations

The changing topology of a network is driven by the need to maintain or optimize network function. As this function is often related to moving quantities such as traffic, information, etc., efficiently through the network, the structure of the network and the dynamics on the network directly depend on the other. To model this interplay of network structure and dynamics we use the dynamics on the network, or the dynamical processes the network models, to influence the dynamics of the network structure, i.e., to determine where and when to modify the network structure. We model the dynamics on the network …

Math, Chatgpt, And You: The Problem With Mathematical Accuracy In Large Language Models, Alexandre M. Hamel

Computer Science Senior Theses

ChatGPT and other Large Language Models (LLMs) currently do a good job at generating novel text across many domains, but math remains a consistent issue when it comes to the accuracy of answers generated by these models. My research into various ways to manipulate the model have led me to the conclusion that a general closed form solution to help LLMs with math is both unrealistic and likely impossible. LLMs can be trained more successfully as you narrow the problem space, but consideration must be taken on the part of human user to recognize when an LLM is detrimental to …

Emotional Regulation On Modulating Associations Between Depression And Physical Activity As Characterized Via Deep Learning, Franklin Ye Ruan

Computer Science Senior Theses

Emotional regulation and physical activity are known to be associated with depression; however, a deeper understanding of how emotional regulation may strengthen or weaken the bonds between depressive symptoms and physical activity may aid clinicians and researchers in developing cognitive behavioral therapy (CBT) for those adversely affected by depression. As part of the Tracking Depression Study, this analysis uses data collected from 306 participants diagnosed with Major Depressive Disorder. To study their behavior, we analyze actigraphy data, or longitudinal physical activity intensity data, as it relates to depression severity, quantified by the daily PHQ-9 questionnaires. We study these associations through …

Visible-Light Photocatalytic C-H Amination Of Arenes Utilizing Acridine-Lewis Acid Complexes, Matthew R. Lasky, En Chih Liu, Matthew S. Remy, Melanie S. Sanford

Chemistry Faculty Research & Creative Works

This report describes the development of a visible-light photocatalytic system for C(sp²)-H amination that leverages in situ-generated photocatalysts. We demonstrate that the combination of acridine derivatives and Lewis acids form potent photooxidants that promote the C-H amination of electronically diverse arenes upon irradiation with visible-light (440 nm). A first-generation photocatalyst composed of Sc (OTf)₃ and acridine effects the C-H amination of substrates with oxidation potentials ≤ +2.5 V vs SCE with pyrazole, triazole, and pyridine nucleophiles. Furthermore, the simplicity and modularity of this system enable variation of both Lewis acid and acridine to tune reactivity. This enabled …

Molecular-Level Studies Of Nanopatterned Biomolecules With Atomic Force Microscopy, Ashley R. Walker

LSU Doctoral Dissertations

Atomic force microscopy (AFM) is an analytical technique in which a tipped probe is gently scanned across the surface in a raster pattern to generate digital images of a sample at the nanoscale. The AFM instrument has three general operational modes, which are contact, non-contact and tapping-mode, that can be used to examine materials at the atomic level. Single-molecular details of biological molecules and other soft organic materials can be captured with minimal denaturation in either ambient or liquid environments when using tapping-mode AFM. In tapping-mode, the probe is driven to oscillate vertically while the tip is scanned across the …

Crisis Management: Unveiling Information And Communication Technologies’ Revamped Role Through The Lens Of Sub-Saharan African Countries During Covid-19, Ruthbetha Kateule, Egidius Kamanyi, Mahadia Tunga

The African Journal of Information Systems

The management of COVID-19 pandemic has revealed inefficiencies in coordinating global response, particularly in African countries. Therefore, creating an urgent need to examine the literature on Information and Communication Technologies (ICT) in crisis management to appreciate its contextual role. Employing a systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), this paper critically assessed the extent of the use of ICT in crisis management in Africa’s response to COVID-19 to reconstruct its resilience against future crises. Findings indicate that while countries with limited ICT infrastructure faced considerable challenges in utilizing ICT solutions in COVID-19 management, countries …

Dna-Templated Nanofabrication Of Metal-Semiconductor Heterojunctions And Their Electrical Characterization, Chao Pang

Theses and Dissertations

Bottom-up nanofabrication, although still in its early stages with formidable challenges, is considered a potential alternative method to address the limitations of traditional top-down techniques by offering benefits including process simplification, cost reduction, and environmental friendliness. DNA-templated nanofabrication, one of the most powerful bottom-up methods, presents an innovative way to create advanced nanoelectronics. In this approach, nanomaterials with specific electronic, photonic, or other functions are precisely and programmably positioned on DNA nanostructures from a disordered collection of smaller parts. These self-assembled structures offer significant potential for improving many fields such as biosensing, drug delivery and electronic device manufacturing. This dissertation …

Recent Advance In Electrochemical Dehalogenative Deuteration, Peng-Fei Li, Guang-Sheng Kou, Li-Ping Qi, You-Ai Qiu

Journal of Electrochemistry

In recent years, the incorporation of deuterium atoms into organic compounds has emerged as a vital focus in the development of pharmaceutical molecules. This trend is driven by the increasing recognition of the significance of compounds containing deuterium atoms across various domains, including materials and biopharmaceuticals, where they have found widespread applications in mechanistic studies within the realms of chemistry and biology. Meanwhile, organic electrochemistry, as a relatively environmentally friendly catalytic mode with broad adaptability to redox reactions, has emerged as a crucial alternative to traditional halogen-deuterium exchange in the context of the reduction deuteration of halides. This approach circumvents …

Investigation Of Volatility, Composition, And Gas-Particle Phase Partitioning Of Atmospheric Organic Compounds Through Novel Instrumentation And Techniques, Karolina Cysneiros De Carvalho

McKelvey School of Engineering Graduate Student Theses & Dissertations

Atmospheric aerosols are ubiquitous indoors and outdoors and their impact on human life on Earth is extensive. Aerosol particles scatter and absorb solar radiation, are key in the formation of clouds and precipitation, and can affect the abundance and distribution of greenhouse and atmospheric trace gases by physicochemical multiphase processes, thus they play an important role in regulating regional and global climate. On the other hand, poor indoor and outdoor air quality associated with high particulate matter (PM) levels is among the leading health risks worldwide, affecting life quality and expectancy by increasing the risk of cancer, cardiovascular and respiratory …

Novel In Situ Synthesis Of Copper Oxide Nanoparticles In Epoxy Network: Kinetics, Composite Mechanical And Dielectric Properties, Elena Bobina, Maxim Danilaev, Safaa.M.R.H. Hussein, Sergey Karandashov, Vladimir Kuklin, Ivan Lounev, Konstantin Faizullin

Karbala International Journal of Modern Science

>Mechanical properties of polymer composites with dispersed nanoparticles (CDNP) depend on interaction between the nanoparticles and the polymer matrix. Strength of polymer composites significantly decreases when there is no interaction between dispersed nanoparticles and the polymer. This limits the application of functional polymer composites with dispersed nanoparticles. In this study, CDNP based on ED-20 epoxy resin with dispersed copper oxide nanoparticles was obtained.These nanoparticles were synthesized in epoxy resin before curing: the nanoparticles were obtained by decomposition of copper hydroxide by heating its solution in ED-20 resin.The kinetics of copper oxide nanoparticles formation in CDNP samples were studied using two …

Elm And Lightgbm: A Hybrid Machine Learning Technique With Intelligent Iot To Predict The Cardiovascular Disease, Gorapalli Srinivasa Rao, G Muneeswari

Karbala International Journal of Modern Science

Cardiologists can more accurately classify a patient's condition by performing an accurate diagnostic and prognosis of cardiovascular disease (CVD). The clinical diagnosis, and therapies processes within the medical field have been substantially accelerated by ML-based approaches enabled by IoT-based systems. This structure is based on IoT-based system with enabled ML approach. This study investigates an approach known as ensemble categorization, which enhances the precision of weak algorithms by integrating multiple classifiers. For effective CVD classification, we utilized Ensemble learning machine (ELM) and Light GBM. The appropriate traits are chosen to speed up the categorization process using the Gorilla Troops Optimizer …

Stochastic 1-D Reactive Transport Simulations To Assess Silica And Carbonate Phases During The Co2 Reinjection Process In Metasediments, Selçuk Erol

Turkish Journal of Earth Sciences

One proposed method to mitigate carbon emission is to mineralize the CO2 in deep geothermal reservoirs while mixing the coproduced CO2 with the effluent fluid for reinjection. The injection fluid temperature fluctuates due to the mixing process between CO2-charged water and the effluent fluid, and compressor interruptions change the thermodynamic conditions that influence the fluid-rock interaction in the reservoir. Mineral dissolution or precipitations are associated with changes in permeability and porosity that affect the flow and, eventually, the lifespan of the reservoir. A combined stochastic–reactive transport simulation approach is useful for inspection purposes. Moreover, the stochastic algorithm validates the deterministic …

Deposition Of Organic And Inorganic Carbons On The Turkish Continental Margins (1984–1996), Vedat Edi̇ger, Di̇lek Edi̇ger

Turkish Journal of Earth Sciences

This study reevaluates the published total inorganic carbon (TIC) and total organic carbon (TOC) percentages of 695 seafloor sediment samples collected from the continental margins of the Black Sea, Sea of Marmara, Aegean Sea and Mediterranean Sea between 1984 and 1996. An inverse relationship is observed between the average TIC and TOC percentages in the four seas surrounding Türkiye. The explanation for this phenomenon is closely connected to the terrestrial, marine, climatic, and environmental factors of the continental margins from which the samples were collected.

Biotechnology For Sustainable Materials: Innovating Today For A Greener Tomorrow, Shashi Kant Bhatia, Saurabh Bhatia, Maria Eugenia Inda-Webb, Konstantina Kourmentza, Tae Seok Moon, Vijai Singh, Vishal Ahuja, Jingbo Li, Sanjeet Mehariya, Jikai Zhao

School of Earth, Environmental, & Marine Sciences Faculty Publications

No abstract provided.

Bagging Improves The Performance Of Deep Learning-Based Semantic Segmentation With Limited Labeled Images: A Case Study Of Crop Segmentation For High-Throughput Plant Phenotyping, Yinglun Zhan, Yuzhen Zhou, Geng Bai, Yufeng Ge

Department of Statistics: Faculty Publications

Advancements in imaging, computer vision, and automation have revolutionized various fields, including field-based high-throughput plant phenotyping (FHTPP). This integration allows for the rapid and accurate measurement of plant traits. Deep Convolutional Neural Networks (DCNNs) have emerged as a powerful tool in FHTPP, particularly in crop segmentation—identifying crops from the background—crucial for trait analysis. However, the effectiveness of DCNNs often hinges on the availability of large, labeled datasets, which poses a challenge due to the high cost of labeling. In this study, a deep learning with bagging approach is introduced to enhance crop segmentation using high-resolution RGB images, tested on the …

Carbon Sequestration In Peatlands: Using Environmental Proxies To Understand The Impact Of A Changing Climate On Global Carbon Storage, Sarah Schuller, Don Sullivan

DU Undergraduate Research Journal Archive

Peatlands are a type of terrestrial wetland ecosystem in which consistently waterlogged conditions prevent the decomposition of organic matter. These conditions allow for sequestered carbon in plant matter to remain stored in the soil to such a great degree that peatlands store more carbon than all other vegetation types in the world combined. By inhibiting decomposition, the composition of water-rich peat soil remains representative of the environmental conditions during the period in which the peat was formed. The collected peat samples can then be utilized as environmental proxies to determine historical temperature, moisture, and carbon content and extrapolated to predict …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, August Alexander, Kevin Summers, E. Paige Lloyd, Alyssa Aragon, Lauren Wols, Erica Larson, Colton Arciniaga, Lily Baeza, Ellie Barnett-Cashman, Sidney Barbier, Maverick Bartholomew, Ryan Bell, Trevor Briggs, Amanda Brown, Cory Marchi, Maddy Pontius, Jennifer Gallagher, Claire Kwok, Channing Bullock, Alex Mccollister, Kim Gorgens, Daniela Chavez, Yamilet Espinoza Nuñez, Giovanni Valladares Giron, William Christensen, Olivia Kachulis, Daniel Cierasynski, Brandon Cohen, Spenser Dobbs, Lindsay Goolsby, Noah Craver, Nyah Cubbison, Liam Doherty, Nicole Doris, Yan Qin, Alexander Nguyen, Lily Harmon, Shubh Todi, Naichen Zhao, Noah Fagello, Stacia Fritz, Paola Gascot-Chinea, Alex Volkova, Janelyn Geronimo, Elsie Harrington, Shane Simmons, Clarice Hise, Laura Moreno Palmer, Henry Xu, Yesu Leela Pasupula, Emily Fisher, Zachary Hogan, Colin Kleckner, Alyssa Knaus, Erin Kubat, Sam Werkema, Katie Lamberton, Lilliya Larson, Allie Leary, Vanessa Leon-Gamez, James H. Gallagher, E. Dale Broder, Robin M. Tinghitella, Emma Loeber, Alina Mali, Ixchel Marquez, Lauren Mcgrath, Ella Matthews, Grace Naegelen, Audrey Ng, Megan Lucyshyn, Rachel Brough, Alexandra Norman, Joe Ontiveros Rodriguez, Ben Dossett, Ori Miller, Janamejay Sharma, Christopher Reardon, Vincent Pandey, Regan Parish, Ren Pratt, Alisha Pravasi, Sanchari Das, Cari Reichel, Emma Robson, Victoria Rockwell, Jayce Rumsey, Steven Said, Norah Schroder, Alaina Smith, Shannon Murphy, Shujan A. Sharafeldeen, Stanley M. Kanai, James T. Nichols, David E. Clouthier, Macalia R. Augustus, Daniel Silva Rios, Scott Simpson, Anna Sparling, Chase Spurbeck, Kimberly Chiew, Christine Stadnik-Poteroba, Jacqueline Stephenson, Evelyn Stovin, Mia Supan, Lauren Tapper, Will Thrush, Anna Vogt, Michaela Walheim, Jon Weber, Hunter Whitehouse, Kansas Wood, Hayley Sayre, Lydia Mccann, Maread Mclaughlin, Kelly Krumrie, Olivia Wuttke

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

A Systems Theoretic View Of Speculative Realism, Martin Zwick

Complex Systems Faculty Publications and Presentations

Recent developments in Continental philosophy have included the emergence of a school of “speculative realism,” which rejects the human-centered orientation that has long dominated Continental thought. Proponents of speculative realism differ on several issues, but many agree on the need for an object-oriented ontology. Some speculative realists identify realism with materialism, while others accord equal reality to objects that are non-material, even fictional. Several thinkers retain a focus on difference, a well-established theme in Continental thought. This paper looks at speculative realism from the perspective of systems theory. Many of the tenets of speculative realism have long been features of …

Estimating Increased Transient Water Storage With Increases In Beaver Dam Activity, Konrad Hafen, Joseph M. Wheaton, Brett B. Roper, Philip Bailey, William W. Macfarlane, Bethany T. Neilson, Christopher J. Tennant

Watershed Sciences Faculty Publications

Dam building by beaver (Castor spp.) slows water movement through montane valleys, increasing transient water storage and the diversity of residence times. In some cases, water storage created by beaver dam construction is correlated to changes in streamflow magnitude and timing. However, the total amount of additional surface and groundwater storage that beaver dams may create (and, thus, their maximum potential impact on streamflow) has not been contextualized in the water balance of larger river basins. We estimate the potential transient water storage increases that could be created at 5, 25, 50, and 100% of maximum modeled beaver dam capacity …

Reports Of Autosomal Recessive Disease And Consanguineous Mating Within The Human Population, Johnathon L. Schluter

Master's Theses

It is anecdotally evident when investigating published reports of autosomal recessive disease that a substantial number of cases are the result of related (consanguineous) mating. This research seeks to quantify the percent of manuscripts describing autosomal recessive diseases published between 2000 and 2020 in which consanguineous mating is indicated. We analyzed 602 peer-reviewed manuscripts to identify the percentage of cases presented in which consanguineous mating was indicated, the underlying genes (novel gene or new mutation) and geographical region. These papers were accessed through a specific set of parameters on the free access PubMed Central (PMC) database. A total of 552 …

Effect Of Sex On The Accumulation Of Hepatic Mercury In Mallards Wintering In Louisiana, Latorya E. Mason

Master's Theses

The increase in mercury production through anthropogenic activities has led to a global crisis of mercury pollution that poses a significant threat to the health of both humans and wildlife. Aquatic ecosystems are especially at risk due to the creation of methylmercury, a toxic form of mercury, by sulfate-reducing bacteria in anoxic sediments and soils. Methylmercury enters the food chain where it bioaccumulates in individual organisms and then biomagnified with increasing trophic level. Aquatic birds are useful bioindicators of many pollutants, including mercury, due to their abundance and position in the food chain. Previous studies have primarily focused on mercury …

Investigating The Connectedness Of A Gorbonos Insect Swarm, Brendan Perez

Senior Theses

No abstract provided.

A Review Of The Toxicity Of Ingredients In E-Cigarettes, Including Those Ingredients Having The Fda's "Generally Recognized As Safe (Gras)" Regulatory Status For Use In Food., Nada O F Kassem, Robert M. Strongin, Andrea M. Stroup, Marielle C. Brinkman, Ahmad El-Hellani, Hanno C. Erythropel, Arash Etemadi, Vernat Exil, David H. Peyton, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

Some firms and marketers of electronic cigarettes (e-cigarettes; a type of electronic nicotine delivery system (ENDS)) and refill liquids (e-liquids) have made claims about the safety of ingredients used in their products based on the term "GRAS or Generally Recognized As Safe" (GRAS). However, GRAS is a provision within the definition of a food additive under section 201(s) (21 U.S.C. 321(s)) of the U.S. Federal Food Drug and Cosmetic Act (FD&C Act). Food additives and GRAS substances are by the FD&C Act definition intended for use in food, thus safety is based on oral consumption; the term GRAS cannot serve …