Digital Commons Network^™

Study Of Anomalous Variations In Seismic And Non-Seismic Parameters Using Machine Learning Techniques To Develop The Earthquake Forecasting Model In The Himalayan Belt, Senthil Kumar M

Theses and Dissertations

Understanding and forecasting earthquakes is not just about science it’s about saving lives, even as the dynamic and hidden nature of Earth's tectonic processes makes this an intricate challenge. The Himalayan belt is one of the most seismically active regions globally due to the collision of the Indian and Eurasian tectonic plates. Investigating this region is essential for understanding highly complicated tectonic mechanisms and reducing substantial hazards posed to millions of people by persistent and intense seismic events. This study aims to enhance forecasting methodologies by applying machine learning techniques while dealing with the inherent challenges of geological complexity and …

Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud

Karbala International Journal of Modern Science

The food sector must contend with issues such as pathogen resistance to some of the available chemical agents, environmental pollution, and climate change to provide healthy food for livestock and people. The application of atmospheric pressure plasma jets (APPJs) is one potential solution for such problems. Plasma is appropriate for effective surface decontamination regarding food products and seeds, surface decontamination, and achieving improved agricultural production yields. The impact of plasma-activated water (PAW) produced by plasma jet discharge (PJD) system on in vitro-cultivated wheat seeds is examined in this work. For this aim, a plasma jet system was constructed with a …

On The Solutions Of Difference Equations Of The Volterra Type, Hakan Adigüzel

Turkish Journal of Mathematics

In this paper, we conduct a thorough analysis of the qualitative behavior of solutions to three different types of difference equations of the Volterra type. Utilizing the principles of discrete calculus and various well-known inequalities, we have presented our findings. To conclude our theoretical findings, we provide several examples that illustrate full alignment with the findings.

Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson

Doctoral Dissertations and Projects

The purpose of this descriptive qualitative applied study is to define and explain through analysis the reasonable person standard as it relates to prosecution and sentencing computer crime cases involving digital identities while addressing the problem of digital anonymity. This has been done by analyzing computer crime cases with the advent of current and planned technologies, and surveying potential jurors to understand the current state of knowledge of digital attribution. This descriptive qualitative research method analyzed the problem through the use of criminological theories of control and social learning theory to better understand the reasonable person standard in computer crime …

Relightable Neural Radiance Fields For Novel View Synthesis, Malena I. Mahoney

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper describes relighting neural radiance fields for novel view synthesis. View synthesis is the problem of using input images with corresponding camera angles to produce a photorealistic 3D model of an environment and its objects. Neural radiance fields (NeRFs) were created as a solution to view synthesis. Neural radiance field models work well for generating realistic 3D models from 2D image inputs; how-ever, they do not support changing the lighting or placing the objects from the input images into different environments. The problem comes from the fact that NeRFs rely on a neural network that is essentially overfitted to …

A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz

All Works

Accurate prediction of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) is critical for tailoring treatment strategies and improving patient outcomes. This study introduces a novel deep learning-based framework that integrates multi-parametric magnetic resonance imaging (MRI) (i.e., T1, T2, STIR, and DWI), along with clinical and molecular subtype markers, to classify tumor response into pathological complete response (pCR), partial response (PR), and stable disease (SD). First, tumor regions are delineated across MRI modalities and then modeled using a translation-invariant Markov-Gibbs random field (MGRF) with analytical parameter estimation to capture modality-specific spatial appearance patterns correlated with NAC response. Subsequently, diffusion-weighted MRI …

Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai

Pepperdine Dispute Resolution Law Journal

Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …

Spatiotemporal Responses To A Rural Highway By Four Mammal Species, Caitlin K. Brett, Anna Rose Mehner, John H. Young Jr., Sarah E. Lehnen, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Roads can negatively impact the wildlife communities they transect. Road mortalities from wildlife-vehicle collisions are one direct effect, but roads may also indirectly affect wildlife behavior, movement, or local distribution. Quantifying the spatial extent of these road-effects is important for understanding how roads indirectly affect species of concern, identifying potential sources of disturbance, and for estimating the effectiveness of road mitigation structures. Farm-to-Market Road (FM)106, which transects part of the Laguna Atascosa National Wildlife Refuge in Cameron County, Texas, has been identified as a potential source of wildlife road mortalities, particularly for one of the two remaining breeding populations of …

Synthesis Of Cancrinite Zeolite From Toraja Natural Bentonite For Heavy Metal Removal From Wastewater, Yuli Astuti, Paulina Taba, Siti Fauziah, Syarifuddin Liong, Yusafir Hala, Nur Umriani Permatasari, Satria Putra Jaya Negara, Fadliah Fadliah

Karbala International Journal of Modern Science

This study explores the production of cancrinite (CAN) zeolite from bentonite found in Toraja (a place in South Sulawesi Province, Indonesia) and its effectiveness in removing Pb²⁺ and Fe³⁺ ions from wastewater. The synthesis was carried out using a hydrothermal method with varying NaOH concentrations, where a single phase of zeolite was formed at 5 M, as confirmed through XRD analysis. FTIR results showed the characteristics of CAN zeolite with typical absorption peaks at 676, 622, and 565 cm^-1, as well as the presence of carbonate groups (CO₃^2-) at 1300-1400 cm^-1. SEM …

Machine Learning Crime Prediction Models And The Gap Between Research And Implementation: A Systematic Review, Ricardo Huamantingo, Miguel Cano-Lengua, Ciro Rodriguez

Karbala International Journal of Modern Science

A crime is an illegal or violent act committed by one individual against another. The increasing crime rate has become a major concern as it negatively affects people's quality of life and generates significant social and economic costs. This study aims to identify the most widely used machine learning (ML) models for crime prediction, determine evaluation metrics for assessing model performance, and analyze key data characteristics to enhance real-world implementation. The study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A search string was formulated using the population, intervention, comparison, and outcomes (PICO) framework and applied …

"...Anything My Friend Shares, I Would Want To Support Them By Clicking On It": Co-Designing Story-Based Interventions Against Clickbait For Teenagers, Ankit Shrestha, Audrey Flood, Bryson Hackler, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Teenagers' lack of digital sophistication and cyber hygiene makes them vulnerable to social engineering attacks, especially as they start using social media. Clickbait, one of such attacks, is primarily performed through social media to trick users into clicking on malicious links. With teenagers' increasing use of social media, clickbait poses a substantial threat to their online safety. The existing online safety measures for teens mainly focus on parental mediation, which can be perceived as restrictive and privacy-invasive. To this end, researchers recommended empowering teens to deal with online risks. In order to design such interventions for clickbait, we conducted co-design …

Dose Characterization Of Galactic Cosmic Rays In The Human Brain: A Phits-Based Study With A Segmented Anatomical Phantom, Shanice N. Manning

LSU Master's Theses

Astronauts aboard the International Space Station (ISS) are chronically exposed to a complex space radiation environment composed of galactic cosmic rays (GCR), solar particles, and Earth's trapped radiation. These high-energy particles interact with spacecraft shielding, producing secondary particles that can penetrate inside and deposit energy in sensitive tissues. Although animal studies have been useful in assessing space radiation risks, anatomical and physiological differences limit their applicability to human anatomy especially neuroanatomy. To address this gap, we developed a computational framework to model radiation dose distribution within the human brain using Monte Carlo simulations in Particle and Heavy Ion Transport code …

Research And Education In Robotics: A Comprehensive Review, Trends, Challenges, And Future Directions, Mutaz Ryalat, Natheer Almtireen, Ghaith Al-Refai, Hisham Elmoaqet, Nathir Rawashdeh

Michigan Tech Publications

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is …

Nanoporous Gold Nanoparticles And Model Membrane Systems Applied To The Study Of Lipopolysaccharide (Lps), Dhanbir Lingden

Dissertations

Lipopolysaccharide (LPS), a key structural component of Gram-negative bacteria, is a major trigger of sepsis and septic shock, the systemic inflammatory conditions responsible for millions of deaths annually. Even at concentrations as low as 1 ng/mL, LPS can activate the immune system and initiate inflammatory cascades. According to the Global Burden of Disease Study 2017, sepsis accounted for 48.9 million cases globally, with 11 million deaths, emphasizing the urgent need for improved diagnostic and therapeutic strategies.

Accurate and rapid detection of LPS is vital for early intervention and improved clinical outcomes. While traditional detection methods are still widely used, modern …

Integrating Belowground Recovery Into Tropical Forest Restoration Design And Monitoring, Lauren Toro, Leland K. Werden, Shalom D. Addo-Danso, Kelly M. Andersen, Sarah Batterman, Matilde M. Bragadini, Pooja Choksi, Rebecca J. Cole, Liza S. Comita, Daniela Cusack, Daisy H. Dent, Lee H. Dietterich, Joshua B. Fisher, Katrin Fleischer, Lucia Fuchslueger, Nohemi Huanca-Nunez, Janey R. Lienau, Lindsay A. Mcculloch, Ember M. Morrissey, Jennifer S. Powers, Mareli Sánchez-Juliá, Oscar Valverde-Barrantes, Anita Weissflog, Michelle Y. Wong

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

There is growing recognition that tropical forest restoration is key for sequestering carbon and enhancing ecosystem resilience. Soils, roots, and soil biota are central to ecosystem function and services, but belowground recovery is largely overlooked in restoration monitoring frameworks. Here, we outline current understanding of the links between above- and belowground recovery in tropical forests by examining how belowground properties before and after intervention influence recovery; by evaluating whether aboveground recovery can serve as a proxy for belowground dynamics; and by proposing a blueprint for monitoring dynamic soil physical (bulk density, aggregate stability), chemical (organic matter or carbon, pH), and …

Spike Timing-Dependent Plasticity And Random Inputs Shape Interspike Interval Regularity Of Model Stn Neurons, Thoa Thieu, Roderick Melnik

School of Mathematical & Statistical Sciences Faculty Publications

Background/Objectives: Neuronal oscillations play a key role in the symptoms of Parkinson’s disease (PD). This study investigates the effects of random synaptic inputs, their correlations, and the interaction with synaptic dynamics and spike timing-dependent plasticity (STDP) on the membrane potential and firing patterns of subthalamic nucleus (STN) neurons, both in healthy and PD-affected states. Methods: We used a modified Hodgkin–Huxley model with a Langevin stochastic framework to study how synaptic conductance, random input fluctuations, and STDP affect STN neuron firing and membrane potential, including sensitivity to refractory period and synaptic depression variability. Results: Our results show that random inputs significantly …

Neurophysiology And Endocrine Responses To Hunger And Satiety Mechanisms: The Brain-Gut Crosstalk, Nour Shakir Rezaieg, Muthanna M. Awad

Karbala International Journal of Modern Science

Background: Obesity is a main public health problem which substantially increases the risk of many diseases. The complex neural circuitry controls energy homeostasis and food consumption by the incorporation of hormonal and neural signals. Circulating hormones, in specific the gut hormones, have been found to be very important in appetite regulation. These hormones transfer energy situation signs to the brain throughout three principle paths: the circulation system, activation of the vagus nerve, and direct modification of main brain regions such as the hypothalamus and brainstem. The control of food eating is not exclusively dependent on the homeostatic processes, rather it …

A Novel Chaotic Dna-Based Image Cryptosystem Leveraging Euclidean Division, Dynamic Josephus Traversal, And Reservoir Computing, Ahmed Kareem Shibeeb, Salah Albermany, Sadiq A. Mehdi

Karbala International Journal of Modern Science

This study presents a new chaotic DNA-based image cryptosystem that combines Euclidean division, dynamic Josephus traversal (DJT), and reservoir computing to address the weaknesses of current methods. Old chaotic DNA cryptosystems usually have problems such as using the same keys for different messages, simple DNA processes, and being vulnerable to attacks where the attacker can choose the input or try many options. The cryptosystem in this study uses a 7D hyperchaotic system that starts with keys created from SHA-512 hashes to produce changing keystreams based on the plaintext, making it very strong against such attacks. The proposed cryptosystem uses a …

Location Selection Of Migrating Beetles Under Neutrosophic Model With Sensitivity And Comparative Analysis, Rabih Sbera, Ahmed A El-Douh, Darin Shafek, Tareef S. Alkellezli

Neutrosophic Systems with Applications

Location Selection of Migrating Beetles has different criteria to select the best location. So, multi-criteria decision making (MCDM) is used to deal with different and numerous criteria in this study. This study proposes an MCDM methodology to rank the locations and select the best criterion. The average method is used to compute the criteria weights. The locations are ranked using the root assessment method (RAM). This study uses eight criteria and 20 locations. We use the single valued neutrosophic numbers (SVNNs) to overcome uncertainty and vague information. The RAM methodology is used under the SVNNs. The results show that Availability …

Type-2 Neutrosophic Numbers For Artificial Intelligence Software Choice For Cybersecurity Testing, O.M. Akash, We’Am Adel Talafha, Mamdouh Gomaa

Neutrosophic Systems with Applications

The choice of artificial intelligence (AI) software for cybersecurity testing is a multi-criteria decision-making approach (MCDM) due to it including different criteria. Evaluation decision making problems include uncertainty and vague information. So, the neutrosophic set is used in this study to overcome this uncertainty and vague information. It has three functions such as truth, indeterminacy, and falsity functions. Type-2 neutrosophic numbers is a type of neutrosophic set that includes nine membership functions. This study uses the average method of computing the criteria weights. The CoCoSo method is used to rank alternatives. Six experts and decision makers created the decision makers …

Neutrosophic Numbers For Selection Best Strategy For Dual Supply Chains With Green And Non-Green Products, Nada A. Nabeeh, Waleed Abd Elkhalik, Gawaher Soliman Hussein

Neutrosophic Systems with Applications

Dual supply chains with green and non-green products are an important aspect of supply chain management, which enable companies to balance traditional operations with ethical and eco-friendly practices to reduce carbon emissions. This study proposed a novel approach that combines the Probabilistic Simplified Neutrosophic Set (PSNS) with the Ranking of Alternatives Method (RAM) for the selection of best strategy selection for dual supply chains with green and non-green products. The novel approach uses PSNS as a representation of uncertainty, by incorporating probabilistic degrees of truth, indeterminacy, and falsity, which occurred in real life situations. Furthermore, RAM illustrates efficient ranking and …

Risk Management Of The Open Data Services Industry In Digital Transformation Under Neutrosophic Sets, Fadhl Ehsan Hadi, Mohammed Musa Mohammed, Noorhan Waleed Abdullah, Baraa Hasan Hadi

Neutrosophic Systems with Applications

The open data services industry is very important for artificial intelligence and digital transformations. The open data services industry has different risks and challenges, so this study proposed a multi-criteria decision making (MCDM) approach for risk management in open data services industry. This study uses the average method to compute the criteria weights and the WASPAS method to rank the alternatives. The triangular neutrosophic set (TNS) is used in this study to overcome uncertainty and vague information. It has three membership functions such as truth, indeterminacy, and falsity. This study uses nine criteria and 18 risks to be evaluated. The …

Cilia In The Brain Display Region-Dependent Oscillations Of Length And Orientation, Roudabeh Vakil Monfared, Sherif Abdelkarim, Pieter Derdeyn, Kiki Chen, Hanting Wu, Kenneth Leong, Tiffany Chang, Justine Lee, Sara Versales, Surya M. Nauli, Kevin Beier, Pierre Baldi, Amal Alachkar

Pharmacy Faculty Articles and Research

In this study, we conducted high-throughput spatiotemporal analysis of primary cilia length and orientation across 22 mouse brain regions. We developed automated image analysis algorithms, which enabled us to examine over 10 million individual cilia, generating the largest spatiotemporal atlas of cilia. We found that cilia length and orientation display substantial variations across different brain regions and exhibit fluctuations over a 24-h period, with region-specific peaks during light-dark phases. Our analysis revealed unique orientation patterns of cilia, suggesting that cilia orientation within the brain is not random but follows specific patterns. Using BioCycle, we identified rhythmic fluctuations in cilia length …

Occurrence Of Pesticides In Oregon Coastal Waters And Effects On The Intertidal Sea Anemone, Anthopleura Elegantissima, Gabriella Mae Bleil

Dissertations and Theses

Pesticides are used globally for a wide range of applications including agricultural, forestry, roadsides, freshwater systems, and personal use. While pesticides have ensured efficient crop production, they are frequently transported away from application sites and are ubiquitous in terrestrial and aquatic environments. Pesticides are often detected in watersheds and rivers globally, which can have unintentional toxic effects on non-target organisms by interfering with cellular processes, behavior, feeding, reproduction, and disrupting endocrine processes. The aggregating anemone, Anthopleura elegantissima, is an important species along the North American Pacific coast due to its symbiotic relationships that contribute to high productivity, and its …

Investigation Of Subcellular Damage And Long-Term Non-Cancerous Cardiovascular Effects Following Whole-Body Photon Irradiation, Nousha Afshari

LSU Doctoral Dissertations

Current radiobiological models focus primarily on nuclear DNA damage and fail to fully explain radiation-induced noncancerous health effects. This dissertation investigates whether non-nuclear subcellular structures contribute to radiation-induced biological damage through experimental biomarker analysis and computational microdosimetry. The central hypothesis posits that whole-body photon irradiation results in subcellular non-nuclear damage, specifically increased circulating mitochondrial DNA concentrations, that correlates with radiation dose and long-term noncancerous effects such as cardiovascular disease.

Specific Aim 1 measured mitochondrial and nuclear DNA concentrations in banked blood samples from 72 Chinese rhesus macaques that previously received whole-body photon irradiation ($0-10$ Gy) from Cobalt-60 or LINAC sources. …

An Upper-Mesopelagic-Zone Carbon Budget For The Subarctic North Pacific, Brandon M. Stephens, Montserrat Roca-Martí, Amy E. Maas, Vinícius J. Amaral, Samantha Clevenger, Shawnee Traylor, Claudia R. Benitez-Nelson, Philip W. Boyd, Ken O. Buesseler, Craig A. Carlson, Nicolas Cassar, Margaret Estapa, Andrea J. Fassbender, Yibin Huang, Phoebe J. Lam, Oliver Marchal, Susanne Menden-Deuer, Nicola L. Paul, Alyson E. Santoro, David A. Siegel, David P. Nicolson

Faculty Publications

Mesopelagic zone (MZ) carbon budgets comparing supply with demand can be difficult to constrain due to the temporal and spatial offsets between key sources and sinks, their associated uncertainties, and potential sampling biases. To address these challenges, the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) campaign increased the number and variety of simultaneous measurements to monitor temporal variability in the MZ carbon budget using both a Lagrangian frame of reference and long-term autonomous observations. In this study, we collate a comprehensive combination of new and previously published organic carbon supply and demand measurements collected from the surface (5 …

Artificial Turf Versus Natural Grass: A Case Study Of Environmental Effects, Health Risks, Safety, And Cost, Iman S. Cumberbatch, Leonard Richardson, Emma Grant-Bier, Mustafa Kayali, Mutanu Mbithi, Roberto F. Riviere, Eline Xia, Hailey Spinks, Gabrielle Mills, Amy R. Tuininga

PSEG Institute for Sustainability Studies Publications

While natural grass has been a reliable recreational surface for decades, artificial turf has gained popularity due to its durability, supposed ability to save water, and lower associated costs for municipalities and schools. Growing environmental and health concerns associated with artificial turf have prompted a necessary comparison of the environmental impact, chemical exposure, injury rates, surface heat, and costs of turf with natural grass. The township of Verona, New Jersey, engaged the PSEG Institute for Sustainability Studies’ Green Teams Program interns to perform an environmental impact assessment, literature review, and cost–benefit analysis to determine if the township should restore an …

Concentration And Composition Of Organic Contaminants In Blackfin Tuna, Yellowfin Tuna, And The Common Clubhook Squid In The Western Gulf Of Mexico, Lisa Rose-Mann

USF Tampa Graduate Theses and Dissertations

Cephalopods are an important component of pelagic food webs. They play ecological roles not only as predators but also as prey. However, their role as prey in the trophic transfer of organic contaminants to apex predators such as tunas in the Gulf of Mexico (GoM) is not well known. To investigate the importance of cephalopods in tuna diets, stomach samples were collected in February 2020 from tunas caught by rod and reel aboard the F/V Gulf Eagle near two large offshore floating oil/gas platforms in the northwestern GoM. Cephalopod samples were obtained from gut content analysis of 41 tunas caught …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Kabe Aberle, Nadia Kako, Kateri Mcrae, Brooke Agulnek, Sky Palmon, Yasmine Ramirez, Francisca Aguirre Beltran, Ashley Juarez, Bridget Kim, Tessa Appel, Sterling Kerr, Spencer Ingley, Gabe Meyer, Robin Tinghitella, Dale Broder, Lily Baeza, Chloe Beers, Julia Coakley, Whitney Kelsey, Sydney Gainforth, Gabi Wing, Audrey Martin, Aaliyah Amore Berry, Brooke Watley, Kiruthika Venkatesan, Rachel Bienstock, Annabella Brotherston, Madison Bryant, Mia Burgener, Emma P. Lieb, Rachel A. Johnson, Jennifer L. Hoffman, Kania Campbell, Kiena Campbell, Courtney Cassidy, Sage Krzyzkowski, Maddox Jones, Skylar Abookire, Luke Hawkins, Sunnah Yoon, Andrea Chu, Yan Qin, Nyah Cubbison, Brian Gearity, Daniel Mcintosh, Mariely Cruz, Edward Garrido, Grady Dionne, Nicole Doris, Lyndsie Salvagio, Ann-Charlotte Granholm-Bentley, Anna Dymov, Hannah Eckert, Gabrielle Welsh, Erica Larson, Charlie Ernst, Anna Zhou, Sarah Watamura, Larissa Fedorovich-Klein, Georgie Fields, Kimberly A. Guevara, Aven Mccall, Ben Peltier, Feruz Yahia, Patrick Flores, Jadyn Floyd, Sophia Forcier, J. Von R. Monteza, Peter Sokol-Hessner, Gwendolyn Geiger, Scott Nichols, Camryn Gunter, Kendal Hengst, Charlie Bednarz, Issy Garside, Addison Baker, Rachel Mina, Brooke Hermanson, Amanda Klingler, William Highfill, Sydney Jaques, Kerstin Lewey, Allison Grossery, Daniel Linseman, Ethan Lim, Jagger Livengood, Owen Mantelli, Gabby Pappas, Abby Mcdonald, Madeleine Dierking, Eve Miller, Emma Loeber, Anna Marlow, Michael Kerwin, Ella Mathews, Hillary Hamann, Khadija Mohamed, Vivian Nguyen, Gabri Notov, Ifunayachi Ogbonna-Ukuku, Sunil Kumar, Charles Baysah, Sarah Olson, Don Sullivan, Anna Paradiso, Jay Parrish, Mira Pronobis, Alisha Pravasi, Kerstin Haring, Diego Ramirez, Christopher Reardon, Juliana Ramirez, Casey Doherty, Ella Kestner, Teagan Weindel, Cate Billings, Pablo Torre-Walter, Lucy Rand, Samantha Reynolds, Mark Siemens, Khadeeja Rashid, Laine Satterlee, Piper Heilbronner, Lily Pound, Ben Whitehurst, Anna Respet, Lizzie Lesoing, Sydney Hertel, Aya Saad-Masri, Brooke Ballenger, Max Proske, Hannah Rosenberg, Ellia Nakahara, Sophia Espinoza, Ivan Woolhouse, Simon Ruland, Gorkem Er, Timothy Sweeny, Melaku Saketa, Michela Schenk, Maren Lynch, Madi Hamm, Grace Schroeder, Michelle Rozenman, Rana Seif, Jackson Hall, Marisela Simental, Daniel Paredes, Aaron Mena, Preston Spaan, Evelyn Stovin, David Andrew Swartz, Anh Tran, Daniel Pittman, Luke Farchione, Emily Boyer, Ukari Verner, Lacey Conrad, Jonathan Velotta, James Weiner, Jagger Gossett, Noah Sherry, Sam Proud, Ben Block, Avi Narayana, Zoey Weiss, Alyssa Wilson, Gabrielle Walsh, David Zonana, Keely Wright, Kena Riveria, Lillybelle Deer, Jena Doom, Elysia Davis, Isabelle Yaremenko, Caitlyn Young

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

Planetary Thinking: Hellbenders As Emissaries Of Appalachia, Tierra R. Curry

Critical Humanities

Hellbenders are prehistoric salamanders that have thrived in cold rivers since before the continents divided. Once found throughout Appalachian watersheds, due to exploitation and habitat degradation only a few dozen healthy populations survive. Monstrous yet fascinating, hellbenders were often reviled historically, but in recent decades they have gained iconic status and are now celebrated as charismatic indicators for clean rivers. Hellbenders are symbols of the wild because of their ancient history, elusive nature, and contribution to ecosystem resilience. The same forces that drove the decline of these amphibian sentinels have sacrificed public health in Appalachia. Their demise echoes the struggle …