Digital Commons Network^™

Artificial Neural Network-Based Prediction Assessment Of Wire Electric Discharge Machining Parameters For Smart Manufacturing, Itagi Vijayakumar Manoj, Sannayellappa Narendranath, Peter Madindwa Mashinini, Hargovind Soni, Shanay Rab, Shadab Ahmad, Ahatsham Hayat

Department of Electrical and Computer Engineering: Faculty Publications

Artificial intelligence (AI), robotics, cybersecurity, the Industrial Internet of Things, and blockchain are some of the technologies and solutions that are combined to produce “smart manufacturing,” which is used to optimize manufacturing processes by creating and/or accepting data. In manufacturing, spark erosion technique such as wire electric discharge machining (WEDM) is a process that machines different hard-to-cut alloys. It is regarded as the solution for cutting intricate parts and materials that are resistant to conventional machining techniques or are required by design. In the present study, holes of different radii, i.e. 1, 3, and 5mm, have been cut on Nickelvac-HX. …

Predicting Site‑Specific Economic Optimal Nitrogen Rate Using Machine Learning Methods And On‑Farm Precision Experimentation, Alfonso De Lara, Taro Mieno, Joe D. Luck, Laila A. Puntel

Department of Agronomy and Horticulture: Faculty Publications

Applying at the economic optimal nitrogen rate (EONR) has the potential to increase nitrogen (N) fertilization efficiency and profits while reducing negative environmental impacts. On-farm precision experimentation (OFPE) provides the opportunity to collect large amounts of data to estimate the EONR. Machine learning (ML) methods such as generalized additive models (GAM) and random forest (RF) are promising methods for estimating yields and EONR. Twenty OFPE N trials in wheat and barley were conducted and analyzed with soil, terrain and remote-sensed variables to address the following objectives: (1) to quantify the spatial variability of winter crops yield and the yield response …

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 …

Analysis And Design Of Lateral Framing Systems For Multi-Story Steel Buildings, Husam Al Dughaishi, Jawad Al Lawati, Moad Alosta, Shaker Mahmood, Mohamed Faisal Al-Kazee, Nur Izzi Md Yusoff, Abdalrhman Milad

Durham School of Architectural Engineering and Construction: Faculty Publications

This study focused on identifying the most appropriate structural system for multi-story buildings and analyzing its response to lateral loads. The study analyzed and compared the different structural systems to determine the most suitable option. The study aims to utilize three lateral framing systems (moment, braced, and diagrid) in order to investigate which system needs the least amount of steel to meet the design requirements. Thus, in order to determine the estimated steel savings of this system as compared to the moment and braced frames, the four-story and eight-story buildings that are 96' × 96' in the plane and utilize …

Graph Convolutional Network Using Adaptive Neighborhood Laplacian Matrix For Hyperspectral Images With Application To Rice Seed Image Classification, Jairo Orozco, Vidya Manian, Estefania Alfaro, Harkamal Walia, Balpreet K. Dhatt

Department of Agronomy and Horticulture: Faculty Publications

Graph convolutional neural network architectures combine feature extraction and convolutional layers for hyperspectral image classification. An adaptive neighborhood aggregation method based on statistical variance integrating the spatial information along with the spectral signature of the pixels is proposed for improving graph convolutional network classification of hyperspectral images. The spatial-spectral information is integrated into the adjacency matrix and processed by a single-layer graph convolutional network. The algorithm employs an adaptive neighborhood selection criteria conditioned by the class it belongs to. Compared to fixed window-based feature extraction, this method proves effective in capturing the spectral and spatial features with variable pixel neighborhood …

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 …

Differentiating Between Urban Flood Risk As A Unitary Problem And As A Strand In A Braided Problem Set: Implications For Administrative Coordination, Sarah Michaels

Department of Political Science: Faculty Publications

Flood protection is a leading priority for urban water sustainability. Making cities more resilient to flooding has become urgent as the climate changes and as cities increasingly become the loci of human population and resources. Reducing the risk of future flooding in cities often necessitates different jurisdictions working together. They may do so because they confront a shared problem. This was the case in the City of Lincoln, Nebraska, USA, when partnering agencies shared a single focus on reducing flood risk from Beal Slough to the Nebraska State Penitentiary. In contrast, entities may band together to confront braided problems, intertwined …

Deep Reinforcement Learning For Articulatory Synthesis In A Vowel-To-Vowel Imitation Task, Denis Shitov, Elena Pirogova, Tadeusz A. Wysocki, Margaret Lech

Department of Electrical and Computer Engineering: Faculty Publications

Articulatory synthesis is one of the approaches used for modeling human speech production. In this study, we propose a model-based algorithm for learning the policy to control the vocal tract of the articulatory synthesizer in a vowel-to-vowel imitation task. Our method does not require external training data, since the policy is learned through interactions with the vocal tract model. To improve the sample efficiency of the learning, we trained the model of speech production dynamics simultaneously with the policy. The policy was trained in a supervised way using predictions of the model of speech production dynamics. To stabilize the training, …

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 …

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 …

Evaluation Of Peroxyacetic Acid, Liquid Buffered Vinegar, And Cultured Dextrose Fermentate As Potential Antimicrobial Interventions For Raw Chicken Livers, Leslie Pearl M. Cancio, Mary-Grace C. Danao, Gary Sullivan, Byron D. Chaves

Department of Nutrition and Health Sciences: Faculty Publications

This study aimed to evaluate the use of peroxyacetic acid (PAA), buffered vinegar (BV), and cultured dextrose fermentate (CDF) to reduce Salmonella on artificially inoculated raw chicken livers, one of the most consumed offal around the world. Samples were inoculated with a 5-strain cocktail of poultry-borne Salmonella to obtain 10⁶ CFU/g and immersed for 90 s with agitation in one of the following treatments: distilled water (control), 450 ppm PAA, 2.0% (w/v) BV, or 1.5% (w/v) CDF, prior to storing at 4^oC. Salmonella was enumerated on XLD agar and monitored for 14 days. Data were analyzed using …

Protocol To Engineer Nanofilms Embedded Lipid Nanoparticles For Controlled And Targeted Drug Delivery (Nectar), Rashi Porwal, Stephen L. Hayward, Srivatsan Kidambi

Department of Chemical and Biomolecular Engineering: Faculty Publications

We present a protocol to engineer a substrate-mediated delivery platform comprising hyaluronic acid-coated lipid nanoparticles (HALNPs) embedded into polyelectrolyte multilayer (PEM) films. This platform allows controlled spatiotemporal release of lipid nanoparticles (LNP) by embedding them within the polyelectrolyte multilayer films matrix. HALNP conjugate with antibodies also adds the ability for targeted delivery. The use of LNP enables this platform to encapsulate both hydrophobic and hydrophilic drugs. This platform can easily be reproduced and utilized for various biomedical drug delivery applications. For complete details on the use and execution of this protocol, please refer to Hayward et al. (2015, 2016a, 2016b), …

Engagement In Water Governance Action Situations In The Lake Champlain Basin, Patrick Bitterman, Christopher Koliba

School of Global Integrative Studies: Faculty Publications

Water quality governance encompasses multiple “wicked” interacting problems that manifest within social-ecological systems. Concerned governments, institutions, and actors concerned with addressing these issues must wrestle with complex systems that span time, space, and scale. This complexity of connected systems requires the participation of multiple actors across political boundaries, problem areas, and hydrologic domains. In Lake Champlain (US), frequent cyanobacteria blooms negatively affect property values, recreational activities, and public infrastructure, in addition to their impacts on the aquatic ecosystem. Through a survey of actors working on water quality in the Lake Champlain Basin, we analyze how actor participation in structured issue …

Computational Discovery Of Active And Selective Metal- Nitrogen-Graphene Catalysts For Electrooxidation Of Water To H2O2, Payal Chaudhary, Iman Evazzade, Rodion Belosludov,, Vitaly Alexandrov

Department of Chemical and Biomolecular Engineering: Faculty Publications

A direct electrosynthesis of H₂O₂ from either O₂ or H₂O is an attractive strategy to replace the energy-intensive industrial anthraquinone process. Two-electron water oxidation reaction (2e-WOR) offers several advantages over the oxygen reduction reaction such as better mass transfer due to the absence of gasphase reactants. However, 2e-WOR is a more challenging and less studied process with only a handful of metal oxides exhibiting reasonable activity/selectivity properties. Herein, we employ density-functional-theory calculations to screen a variety of metal-nitrogen-graphene structures for 2e-WOR. As a consequence of scaling between the adsorption energies of reaction intermediates, we …

Spoilage Pseudomonas Survive Common Thermal Processing Schedules And Grow In Emulsified Meat During Extended Vacuum Storage, Samuel C. Watson, Rebecca A. Furbeck, Samodha C. Fernando, Byron D. Chaves, Gary Sullivan

Department of Animal Science: Faculty Publications

Some Pseudomonas species are common meat spoilage bacteria that are often associated with the spoilage of fresh meat. The recently reported ability of these bacteria to also spoil cooked and vacuum packaged meat products has created the need to investigate all potential routes of spoilage they may be able to utilize. The objective of this experiment was to determine if spoilage Pseudomonas spp. survive thermal processing and grow during refrigerated storage under vacuum. Pseudomonas spp. isolates collected from spoiled turkey products were inoculated into a salted and seasoned meat emulsion that was vacuum sealed and thermally treated to final temperatures …

Editorial: Inter-Organ Crosstalk During Exercise In Health And Disease: Extracellular Vesicles As New Kids On The Block, Kenneth Verboven, Ivan Jose Vechetti Jr

Department of Nutrition and Health Sciences: Faculty Publications

Within exercise physiology, the study of factors potentially mediating interorgan crosstalk during and after exercise is a fascinating field of research. As exercise activates a plethora of metabolic pathways in several tissues, organs and systems, examining the underlying biological mechanisms contributing to exercise related metabolic benefits is imperative. Since two decades, the skeletal muscle is known to secrete humoral factors into the circulation in response to exercise, originally described as “myokines” by Pedersen et al. (2003). These myokines are now well known and extensively studied in the field of exercise science (Pedersen and Febbraio, 2012). Interestingly, exercise also triggers other …

Plant Breeding Advancements With “Crispr-Cas” Genome Editing Technologies Will Assist Future Food Security, M. Ahmad

Center for Plant Science Innovation: Faculty Publications

Genome editing techniques are being used to modify plant breeding, which might increase food production sustainably by 2050. A product made feasible by genome editing is becoming better known, because of looser regulation and widespread acceptance. The world’s population and food supply would never have increased proportionally under current farming practices. The development of plants and food production has been greatly impacted by global warming and climate change. Therefore, minimizing these effects is crucial for agricultural production that is sustainable. Crops are becoming more resilient to abiotic stress because of sophisticated agricultural practices and a better understanding of the abiotic …

Midwest Roadside Safety Facility Expansion For Enhanced Research Capabilities, Joseph (Lj) Hajduch, Isaac Hansen, Jeff Schroeder, Hozhin Sleman, Ben Wortman

Honors Program: Senior Projects (Public)

As Civil Engineering students, this group was tasked with designing and proposing an engineering solution to a real-world problem. In this case, the Midwest Roadside Safety Facility in Lincoln, Nebraska was looking for a planned proposal to add an additional building to their property for the purpose of additional research and office space. The group decided on the name Zana Engineering – Zana translating to “highly educated” in Kurmanji – to function as the organization responsible for creating this proposal and presentation. Zana Engineering designed this plan on several key factors, most significantly utility, affordability, safety, sustainability, functionality, longevity, and …

Disturbances In Primary Visual Processing As A Function Of Healthy Aging, Seth D. Springer, Tara D. Erker, Mikki Schantell, Hallie J. Johnson, Madelyn P. Willett, Hannah J. Okelberry, Maggie P. Rempe, Anthony Wilson

Department of Agricultural and Biological Systems Engineering: Faculty Publications

For decades, visual entrainment paradigms have been widely used to investigate basic visual processing in healthy individuals and those with neurological disorders. While healthy aging is known to be associated with alterations in visual processing, whether this extends to visual entrainment responses and the precise cortical regions involved is not fully understood. Such knowledge is imperative given the recent surge in interest surrounding the use of flicker stimulation and entrainment in the context of identifying and treating Alzheimer’s disease (AD). In the current study, we examined visual entrainment in eighty healthy aging adults using magnetoencephalography (MEG) and a 15 Hz …

Spectral Features Of Non-Nutritive Suck Dynamics In Extremely Preterm Infants, Steven M. Barlow, Chunxiao Liao, Jaehoon Lee, Seungman Kim, Jill L. Maron, Dongli Song, Priya Jegatheesan, Balaji Govindaswami, Bernard J. Wilson, Kushal Bhakta, John P. Cleary

United States Public Health Resources

Background: Non-nutritive suck (NNS) is used to promote ororhythmic patterning and assess oral feeding readiness in preterm infants in the neonatal intensive care unit (NICU). While time domain measures of NNS are available in real time at cribside, our understanding of suck pattern generation in the frequency domain is limited. The aim of this study is to model the development of NNS in the frequency domain using Fourier and machine learning (ML) techniques in extremely preterm infants (EPIs).

Methods: A total of 117 EPIs were randomized to a pulsed or sham orocutaneous intervention during tube feedings 3 times/day …

Architecture And New Urbanism’S Relationship To Biomimicry And Floral Design, Alycia Timmerman

Honors Program: Senior Projects (Public)

The craft of floral design is classified as an art and a science. Similarly, architecture is rooted in the two disciplines. After conducting research and exploring biomimicry through the design process, it became evident that the process of design for architecture and floral design are similar. This relationship can also be extended into the field of planning and the New Urbanism movement. This study explores the integration of floral design and biomimicry with architecture and New Urbanism at the scale of the building and city block.

Characterization Of Bubble Transport In Porous Media Using A Microfluidic Channel, Ryan Haggerty, Dong Zhang, Jongwan Eun, Yusong Li

Department of Civil and Environmental Engineering: Faculty Publications

This study investigates the effect on varying flow rates and bubble sizes on gas–liquid flow through porous media in a horizontal microchannel. A simple bubble generation system was set up to generate bubbles with controllable sizes and frequencies, which directly flowed into microfluidic channels packed with different sizes of glass beads. Bubble flow was visualized using a high-speed camera and analyzed to obtain the change in liquid holdup. Pressure data were measured for estimation of hydraulic conductivity. The bubble displacement pattern in the porous media was viscous fingering based on capillary numbers and visual observation. Larger bubbles resulted in lower …

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 …

Social Science Researchers' Perceptions Of Inclusive Research Practices For Transgender And Gender Diverse Communities, Christen Seyl

Honors Program: Senior Projects (Public)

Social sciences research has historically excluded or marginalized of transgender and gender diverse (TGD) people. Although TGD affirming research materials can help improve relationships with TGD communities, these sorts of materials are not standard practice. The present study aimed to determine what factors influence social science researchers’ (SSR) willingness to incorporate affirming practices into their research. We hypothesized that more culturally competent SSR will view TGD affirming research materials as more affirming and be more willing to use similar materials in their work. In this study, SSR (n = 32) viewed and rated affirmation and willingness to use five affirming …

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 …