Digital Commons Network^™

Conversion Of Fat To Cellular Fuel—Fatty Acids 𝛽-Oxidation Model, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Marissa Miller, Beata J. Wysocki, Paul Davis, Tadeusz A. Wysocki

School of Computing: Faculty Publications

𝛽-oxidation of fatty acids plays a significant role in the energy metabolism of the cell. This paper presents a 𝛽-oxidation model of fatty acids based on queueing theory. It uses Michaelis–Menten enzyme kinetics, and literature data on metabolites’ concentration and enzymatic constants. A genetic algorithm was used to optimize the parameters for the pathway reactions. The model enables real-time tracking of changes in the concentrations of metabolites with different carbon chain lengths. Another application of the presented model is to predict the changes caused by system disturbance, such as altered enzyme activity or abnormal fatty acid concentration. The model has …

Diverse Portfolios: Investing In Tributaries For Restoration Of Large River Fishes In The Anthropocene, Kristen L. Bouska, Brian D. Healy, Michael J. Moore, Corey G. Dunn, Jonathan J. Spurgeon, Craig P. Paukert

Nebraska Cooperative Fish and Wildlife Research Unit: Staff Publications

Rehabilitation of large Anthropocene rivers requires engagement of diverse stakeholders across a broad range of sociopolitical boundaries. Competing objectives often constrain options for ecological restoration of large rivers whereas fewer competing objectives may exist in a subset of tributaries. Further, tributaries contribute toward building a “portfolio” of river ecosystem assets through physical and biological processes that may present opportunities to enhance the resilience of large river fishes. Our goal is to review roles of tributaries in enhancing mainstem large river fish populations. We present case histories from two greatly altered and distinct large-river tributary systems that highlight how tributaries contribute …

From Laboratory To Field: Unsupervised Domain Adaptation For Plant Disease Recognition In The Wild, Xinlu Wu, Xijian Fan, Peng Luo, Sruti Das Choudhury, Tardi Tjahjadi, Chunhua Hu

School of Computing: Faculty Publications

Plant disease recognition is of vital importance to monitor plant development and predicting crop production. However, due to data degradation caused by different conditions of image acquisition, e.g., laboratory vs. field environment, machine learning-based recognition models generated within a specific dataset (source domain) tend to lose their validity when generalized to a novel dataset (target domain). To this end, domain adaptation methods can be leveraged for the recognition by learning invariant representations across domains. In this paper, we aim at addressing the issues of domain shift existing in plant disease recognition and propose a novel unsupervised domain adaptation method via …

A Plea For Scale, And Why It Matters For Invasive Species Management, Biodiversity And Conservation, Nicholas A. Mcmillan, Samuel D. Fuhlendorf, Craig A. Davis, Robert G. Hamilton, Landon. K. Neumann, Samantha M. Cady

Department of Agronomy and Horticulture: Faculty Publications

1. Invasive species are suspected to be major contributors to biodiversity declines worldwide. Counterintuitively, however, invasive species effects are likely scale dependent and are hypothesized to be positively related to biodiversity at large spatial scales. Past studies investigating the effect of invasion on biodiversity have been mostly conducted at small scales (<100 m²) that cannot represent large dynamic landscapes by design. Therefore, replicated experimental evidence supporting a negative effect of invasive plants on biodiversity is lacking across many landscape types, including large grasslands.

2. We collected data across eight large (333–809 ha) grassland landscapes managed with pyric herbivory—that is the recoupling …

   ---

   Go to article

Graphene Twistronics: Tuning The Absorption Spectrum And Achieving Metamaterial Properties, Ammar Armghan, Meshari Alsharari, Khaled Aliqab, Osamah Alsalman, Juveriya Parmar, Shobhit K. Patel

Department of Mechanical and Materials Engineering: Faculty Publications

Graphene twistronics using multilayer graphene is presented in such a way that it provides a metamaterial effect. This manuscript also analyzes the prediction of behavior using machine learning. The metamaterial effect is achieved by twisting the graphene layers. Graphene twistronics is a new concept for changing the electrical and optical properties of bilayer graphene by applying a small angle twist between the layers. The angle twists of 5^o, 10^o, and 15^o are analyzed for the proposed graphene twistronics design. Tuning in the absorption spectrum is achieved by applying small twists to the angles of the …

Heterogeneous Sensor Data Fusion For Multiscale, Shape Agnostic Flaw Detection In Laser Powder Bed Fusion Additive Manufacturing, Benjamin Bevans, Christopher Barrett, Thomas Spears, Aniruddha Gaikwad, Alex Riensche, Harold (Scott) Halliday, Prahalada Rao

Department of Mechanical and Materials Engineering: Faculty Publications

We developed and applied a novel approach for shape agnostic detection of multiscale flaws in laser powder bed fusion (LPBF) additive manufacturing using heterogenous in-situ sensor data. Flaws in LPBF range from porosity at the micro-scale (< 100 μm), layer related inconsistencies at the meso-scale (100 μm to 1 mm) and geometry-related flaws at the macroscale (> 1 mm). Existing data-driven models are primarily focused on detecting a specific type of LPBF flaw using signals from one type of sensor. Such approaches, which are trained on data from simple cuboid and cylindrical-shaped coupons, have met limited success when used for detecting multiscale flaws in complex LPBF parts. The objective of this work is to develop a heterogenous sensor data fusion …

Invertebrate Metrics Based On Few Abundant Taxa Outperform Functional And Taxonomic Composition As Indicators Of Agricultural Impacts In Atlantic Rainforest Streams, Rafael Feijó‑Lima, Steven A. Thomas, Flavia Tromboni, Eugenia Zandonà, Eduardo F. Silva‑Junior, Timothy P. Moulton

School of Natural Resources: Faculty Publications

Metacommunity studies have demonstrated that local macroinvertebrate communities are structured not only by local environmental conditions but also by spatial processes. Effective bioassessment tools should account for spatial processes while doing so with the least amount of cost. In this study, we applied variance partition techniques based on redundancy analysis to assess the performance of three sets of benthic invertebrate metrics in detecting agricultural land-use effects in a SE Brazil rainforest watershed. Macroinvertebrate data were analyzed separately regarding their taxonomic, functional structure and bioindicator metrics developed for the study region. We stipulated that groups of metrics most sensitive to land-use …

Carbon Farming: A Preliminary Economic Analysis Of Carbon Credits For No-Till And Cover Crops, Drew Havens, Richard K. Perrin, Lilyan E. Fulginiti

Cornhusker Economics

Summary Based on experimental data about the amount of carbon sequestered and estimated implementation costs, our preliminary results show that the average cost of sequestering carbon via no-till (about $22 per ton of CO₂e) appears to be much lower than the $51 per ton social value of sequestering that ton. In contrast, our preliminary results show that the average costs of sequestration via adoption of cover crops is much higher, about $60 per ton. Depending on how accurate soil carbon models are in predicting sequestration on individual fields to qualify them for enrollment, reimbursement costs for planting cover …

Prominent Size Effects Without A Depolarization Field Observed In Ultrathin Ferroelectric Oxide Membranes, Haoying Sun, Jiahui Gu, Yongqiang Li, Tula R. Paudel, Di Liu, Jierong Wang, Yipeng Zang, Chengyi Gu, Jiangfeng Yang, Wenjie Sun, Zhengbin Gu, Evgeny Y. Tsymbal, Junming Liu, Houbing Huang, Di Wu, Yuefeng Nie

Department of Physics and Astronomy: Faculty Publications

The increasing miniaturization of electronics requires a better understanding of material properties at the nanoscale. Many studies have shown that there is a ferroelectric size limit in oxides, below which the ferroelectricity will be strongly suppressed due to the depolarization field, and whether such a limit still exists in the absence of the depolarization field remains unclear. Here, by applying uniaxial strain, we obtain pure in-plane polarized ferroelectricity in ultrathin SrTiO₃ membranes, providing a clean system with high tunability to explore ferroelectric size effects especially the thickness-dependent ferroelectric instability with no depolarization field. Surprisingly, the domain size, ferroelectric transition …

Federated Learning Framework Integrating Refined Cnn And Deep Regression Forests, Daniel Nolte, Omid Bazgir, Souparno Ghosh, Ranadip Pal

Department of Statistics: Faculty Publications

Predictive learning from medical data incurs additional challenge due to concerns over privacy and security of personal data. Federated learning, intentionally structured to preserve high level of privacy, is emerging to be an attractive way to generate cross-silo predictions in medical scenarios. However, the impact of severe population-level heterogeneity on federated learners is not well explored. In this article, we propose a methodology to detect presence of population heterogeneity in federated settings and propose a solution to handle such heterogeneity by developing a federated version of Deep Regression Forests. Additionally, we demonstrate that the recently conceptualized REpresentation of Features as …

Federated Learning Framework Integrating Refined Cnn And Deep Regression Forests, Daniel Nolte, Omid Bazgir, Souparno Ghosh, Ranadip Pal

Department of Statistics: Faculty Publications

Predictive learning from medical data incurs additional challenge due to concerns over privacy and security of personal data. Federated learning, intentionally structured to preserve high level of privacy, is emerging to be an attractive way to generate cross-silo predictions in medical scenarios. However, the impact of severe population-level heterogeneity on federated learners is not well explored. In this article, we propose a methodology to detect presence of population heterogeneity in federated settings and propose a solution to handle such heterogeneity by developing a federated version of Deep Regression Forests. Additionally, we demonstrate that the recently conceptualized REpresentation of Features as …

Projected Long-Term Climate Trends Reveal The Critical Role Of Vapor Pressure Deficit For Soybean Yields In The Us Midwest, Wenguang Sun, David Fleisher, Dennis Timlin, Chittaranjan Ray, Zhuangji Wang, Sahila Beegum, Vangimalla Reddy

Nebraska Water Center: Faculty Publications

Extreme climate events including heat waves and droughts are projected to become more frequent under future climate change conditions. However, the mechanisms between soybean yields and climate factors, specifically involving variable rainfall and high heat episodes, are still unclear, particularly with respect to spatial trends in the United States (US) Midwest. A recently modified version of the model GLYCIM was used to evaluate rainfed soybean production across 12 states at a 10 km spatial resolution for three time periods (2011–2020, 2051–2060, 2091–2099) under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5. Results showed that except for the northernmost Midwest counties, …

Efficient Two-Stage Analysis For Complex Trait Association With Arbitrary Depth Sequencing Data, Zheng Xu, Song Yan, Shuai Yuan, Cong Wu, Sixia Chen, Zifang Guo

School of Computing: Faculty Publications

Sequencing-based genetic association analysis is typically performed by first generating genotype calls from sequence data and then performing association tests on the called genotypes. Standard approaches require accurate genotype calling (GC), which can be achieved either with high sequencing depth (typically available in a small number of individuals) or via computationally intensive multi-sample linkage disequilibrium (LD)-aware methods. We propose a computationally efficient two-stage combination approach for association analysis, in which single-nucleotide polymorphisms (SNPs) are screened in the first stage via a rapid maximum likelihood (ML)-based method on sequence data directly (without first calling genotypes), and then the selected SNPs are …

How Do Land Use And Land Cover Changes After Farmland Abandonment Affect Soil Properties And Soil Nutrients In Mediterranean Mountain Agroecosystems?, Estela Nadal-Romero, Makki Khorchani, Leticia Gaspar, José Arnáez, Erik Cammeraat, Ana Navas, Teodoro Lasanta

School of Natural Resources: Faculty Publications

Mediterranean mountains are sensitive agroecosystems that have suffered intense land use and land cover changes (LULCC) during the last century. From the middle of the twentieth century, most of the cultivated lands in Mediterranean mountains were abandoned, allowing the recovery of vegetation (through natural revegetation and afforestation programmes). To examine the effects of farmland abandonment, secondary succession (natural revegetation) and afforestation, an intensive soil sampling was carried out in the Aragu´as catchment (Central Spanish Pyrenees) including sparsely vegetated areas (badlands), grasslands, shrublands and afforested sites. LULCC were mapped, and soil physico-chemical properties were analysed in reference sites (unaltered areas during …

Formal Conjugacy Growth In Graph Products I, Laura Ciobanu,, Susan Hermiller, Valentin Mercier

Department of Mathematics: Faculty Publications

In this paper we give a recursive formula for the conjugacy growth series of a graph product in terms of the conjugacy growth and standard growth series of subgraph products. We also show that the conjugacy and standard growth rates in a graph product are equal provided that this property holds for each vertex group. All results are obtained for the standard generating set consisting of the union of generating sets of the vertex groups.

The Concentration Of Heavy Metals In Lincoln Nebraska's Tap Water, Evan Neuhaus

Honors Program: Senior Projects (Public)

Heavy metals are commonplace in nature, and are typically found in scarce quantities in all drinking sources. However, in high enough concentrations, they can have a myriad of negative health effects. This study seeks to find the concentrations of such metals in the Lincoln water supply utilizing the resources of the Water Center at the University of Nebraska at Lincoln. To test for discrete concentrations of trace elements, a method of using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was implemented. ICP-MS uses plasma to ionize and atomize a sample which is then filtered into a series of cones into a …

Drought Affects Sex Ratio And Growth Of Painted Turtles In A Long-Term Study In Nebraska, Larkin A. Powell, Ellen P. Dolph, Charrissa R. Neil

School of Natural Resources: Faculty Publications

Climate forecasts suggest the Great Plains of North America have increased risk of droughts during global warming. Environmental factors have potential to influence turtle populations in aquatic habitats through temperature-dependent sex determination and influences on food availability. Long-term studies are critical to evaluate the influence of climatic variation on turtles. We used a 12-year set of mark-recapture data collected from painted turtles (Chrysemys picta, n = 162) in a pond in Keith County, Nebraska during 2005–2016 to assess variation in sex ratio and growth dynamics. Southwest Nebraska experienced two periods of drought during our study (Palmer Hydrologic Drought …

The Influence Of Complex Coastlines On The Sea Breeze And Convection Initiation In Coastal North Carolina, Logan Howard, Adam L. Houston

Honors Program: Senior Projects (Public)

The sea breeze is a common phenomenon in coastal regions around the world. Their development and propagation can be treated as a density current. It is well known that many factors influence density current propagation, including wind. Depending on the orientation, the wind speed and shear can enhance or inhibit the development of the sea breeze. In places like eastern North Carolina, complex coastal geography can create river and sound breezes that, upon collision, have the potential to initiate thunderstorms. Using Cloud Model 1, simulations were conducted to model the behavior of the sea breezes in eastern North Carolina and …

Math Education Project And Rso Creation, Keegan Oldani

Honors Program: Senior Projects (Public)

Reflection on Math Education Senior Honors Project and RSO Creation

Using Game Theory To Model Tripolar Deterrence And Escalation Dynamics, Grace Farson

Honors Program: Senior Projects (Public)

The study investigated how game theory can been utilized to model multipolar escalation dynamics between Russia, China, and the United States. In addition, the study focused on analyzing various parameters that affected potential conflict outcomes to further new deterrence thought in a tripolar environment.

A preliminary game theoretic model was created to model and analyze escalation dynamics. The model was built upon framework presented by Zagare and Kilgour in their work ‘Perfect Deterrence’. The model is based on assumptions and rules set prior to game play. The model was then analyzed based upon these assumptions using a form of mathematical …

A Multiscale Mechanistic Model Of Human Dendritic Cells For In-Silico Investigation Of Immune Responses And Novel Therapeutics Discovery, Sara Sadat Aghamiri, Bhanwar Lal Puniya, Rada Amin, Tomáš Helikar

Department of Biochemistry: Faculty Publications

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype. Computational models open novel frontiers in research by integrating large-scale interaction to interrogate the influence of complex biological behavior across scales. The ability to model large biological networks will likely pave the …

The Earliest Dipodomyine Heteromyid In North America And The Phylogenetic Relationships Of Geomorph Rodents, Joshua X. Samuels, Jonathan J.-M. Calede, Robert M. Hunt Jr.

Department of Earth and Atmospheric Sciences: Faculty Publications

Dipodomyine heteromyids (kangaroo rats and mice) are a diverse group of aridadapted ricochetal rodents of North America. Here, a new genus and species of a large dipodomyine is reported from early Miocene-aged deposits of the John Day Formation in Oregon that represents the earliest record of the subfamily. The taxon is known from a single specimen consisting of a nearly complete skull, dentary, partial pes, and caudal vertebra. The specimen is characterized by a mosaic of ancestral and highly derived cranial features of heteromyids. Specifically, the dental morphology and some cranial characteristics are similar to early heteromyids, but other aspects …

Systematic Review Of Reflection Spectroscopy-Based Skin Carotenoid Assessment In Children, Saima Hasnin, Dipti Dev, Taren Swindle, Susan B. Sisson, Stephanie Jilcott Pitts, Tirna Purkait, Shari C. Clifton, Jocelyn Dixon, Virginia C. Stage

Department of Child, Youth, and Family Studies: Faculty Publications

Assessing children’s skin carotenoid score (SCS) using reflection spectroscopy (RS) is a non-invasive, widely used method to approximate fruit and vegetable consumption (FVC). The aims for the current review were to (1) identify distributions of SCS across demographic groups, (2) identify potential non-dietary correlates for RS-based SCS, (3) summarize the validity and reliability of RSbased SCS assessment, and (4) conduct meta-analyses of studies examining the correlation between RS-based SCS with FVC. A literature search in eight databases in June 2021 resulted in 4880 citations and peer-reviewed publications written in English that investigated children’s (2–10 years old) SCS using RS. We …

Planning For The Lake Izabal Basin Research Endeavor (Libre) Continental Scientific Drilling Project In Eastern Guatemala, Jonathan Obrist-Farner, Andreas Eckert, Peter M. J. Douglas, Liseth Perez, Alex Correa-Metrio, Bronwen L. Konecky, Thorsten Bauersachs, Susan Zimmerman, Stephanie Scheidt, Mark Brenner, Steffen Kutterolf, Jeremy Maurer, Omar Flores, Caroline M. Burberry, Anders Noren, Amy Myrbo, Matthew Lachniet, Nigel Wattrus, Derek Gibson, The Libre Scientific Team

Department of Earth and Atmospheric Sciences: Faculty Publications

As Earth’s atmospheric temperatures and human populations increase, more people are becoming vulnerable to natural and human-induced disasters. This is particularly true in Central America, where the growing human population is experiencing climate extremes (droughts and floods), and the region is susceptible to geological hazards, such as earthquakes and volcanic eruptions, and environmental deterioration in many forms (soil erosion, lake eutrophication, heavy metal contamination, etc.). Instrumental and historical data from the region are insufficient to understand and document past hazards, a necessary first step for mitigating future risks. Long, continuous, well-resolved geological records can, however, provide a window into past …

Pan-Arctic Soil Moisture Control On Tundra Carbon Sequestration And Plant Productivity, Donatella Zona, Peter M. Lafleur, Koen Hufkens, Beniamino Gioli, Barbara Bailey, George Burba, Eugénie S. Euskirchen, Jennifer D. Watts, Kyle A. Arndt, Mary Farina, John S. Kimball, Martin Heimann, Mathias Göckede, Martijn Pallandt, Torben R. Christensen, Mikhail Mastepanov, Efrén López-Blanco, Albertus J. Dolman, Roisin Commane, Charles E. Miller, Josh Hashemi, Lars Kutzbach, David Holl, Julia Boike, Christian Wille, Torsten Sachs, Aram Kalhori, Elyn R. Humphreys, Oliver Sonnentag, Gesa Meyer, Gabriel H. Gosselin, Philip Marsh, Walter C. Oechel

Daugherty Water for Food Global Institute: Faculty Publications

Long-term atmospheric CO₂ concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance …

Predicting Mobility Using Limited Data During Early Stages Of A Pandemic, Michael T. Lash, S. Sajeesh, Özgür M. Araz

Department of Marketing: Faculty Publications

The COVID-19 pandemic has changed consumer behavior substantially. In this study, we explore the drivers of consumer mobility in several metropolitan areas in the United States under the perceived risks of COVID-19. We capture multiple dimensions of perceived risk using local and national cases and death counts of COVID-19, along with real-time Google Trends data for personal protective equipment (PPE). While Google Trends data are popular inputs in many studies, the risk of multicollinearity escalates with the addition of more relevant terms. Therefore, multicollinearity-alleviating methods are needed to appropriately leverage information provided by Google Trends data. We develop and utilize …

Socioeconomic Factors In The Diagnosis And Treatment Of Malignant Melanoma In Hispanic Vs. Non-Hispanic Patients: A National Cancer Database (Ncdb) Study, Julia Griffin, Sarah J. Aurit, Timothy Malouff, Peter Silberstein

Department of Statistics: Faculty Publications

Background: The incidence of melanoma is rapidly increasing in the United States. There is a paucity of research of how melanoma affects the Hispanic population, the quickest growing population.

Objective: To identify and understand how socioeconomic factors affect a Hispanic patients health outcome and treatment of malignant melanoma with comparisons to white, non-Hispanic (WNH) patients.

Methods: A retrospective study utilizing the National Cancer Database (NCDB) was completed investigating Hispanic patients (n=2282) and WNH patients (n=190,469) with Stage I-IV malignant melanoma. Outcome and socioeconomic variables were identified and compared across groups. Data was analyzed with SPSS and SAS …

Estimating The Prevalence Of Two Or More Diseases Using Outcomes From Multiplex Group Testing, Md S. Warasi, Joshua M. Tebbs, Christopher S. Mcmahan, Christopher R. Bilder

Department of Statistics: Faculty Publications

When screening a population for infectious diseases, pooling individual specimens (e.g., blood, swabs, urine, etc.) can provide enormous cost savings when compared to testing specimens individually. In the biostatistics literature, testing pools of specimens is commonly known as group testing or pooled testing. Although estimating a population-level prevalence with group testing data has received a large amount of attention, most of this work has focused on applications involving a single disease, such as human immunodeficiency virus. Modern methods of screening now involve testing pools and individuals for multiple diseases simultaneously through the use of multiplex assays. Hou et al. (2017, …

Penguins Go Parallel: A Grammar Of Graphics Framework For Generalized Parallel Coordinate Plots, Susan Vanderplas, Yawei Ge, Antony Unwin, Heike Hofmann

Department of Statistics: Faculty Publications

Parallel Coordinate Plots (PCP) are a valuable tool for exploratory data analysis of high-dimensional numerical data. The use of PCPs is limited when working with categorical variables or a mix of categorical and continuous variables. In this article, we propose Generalized Parallel Coordinate Plots (GPCP) to extend the ability of PCPs from just numeric variables to dealing seamlessly with a mix of categorical and numeric variables in a single plot. In this process we find that existing solutions for categorical values only, such as hammock plots or parsets become edge cases in the new framework. By focusing on individual observations …

Simulation Of Monthly Mean And Monthly Base Flow Of Streamflow Using Random Forests For The Mississippi River Alluvial Plain, 1901 To 2018, Benjamin J. Dietsch, William H. Asquith, Brian K. Breaker, Stephen M. Westenbroek, Wade H. Kress

United States Geological Survey: Water Reports and Publications

Improved simulations of streamflow and base flow for selected sites within and adjacent to the Mississippi River Alluvial Plain area are important for modeling groundwater flow because surface-water flows have a substantial effect on groundwater levels. One method for simulating streamflow and base flow, random forest (RF) models, was developed from the data at gaged sites and, in turn, was used to make monthly mean streamflow and base-flow predictions at 162 ungaged sites in the study area. Daily streamflow observations and computed base flow from 247 streamgages were used as the basis for the development of these RF models. RF …