Digital Commons Network^™

Detection Of Co2 Locally Generated By Formate Dehydrogenase Using Carbonate Ion-Selective Micropipette Electrodes, Seol Baek, Salvador Gutierrez-Portocarrero, Rokas Gerulskis, Shelley D. Minteer, Sean R. German, Henry S. White

Chemistry Faculty Research & Creative Works

Many technologies involve immobilizing catalysts such as enzymes on surfaces, and the catalytic activities or functional efficiencies of these surface-bound catalysts can vary depending on orientations, localized binding sites, active sites, and intrinsic molecular nature. Accurate and rapid quantification of reaction products from surface-immobilized catalysts is crucial for understanding the selectivity, mechanisms, and reaction dynamics of catalytic systems and for revealing heterogeneous catalytic activities and reaction sites for applications such as biosensors and energy conversion/generation systems. Here, we demonstrate the feasibility of localized enzymatic activity measurements using microscale carbon dioxide (CO₂)-sensitive ion-selective electrode (ISE) pipettes (0.5-2.5 μm tip …

Neural Network-Based Renewal Reward Theory (Rrt) For Optimal Maintenance Scheduling, Samiksha Aryal, Abhijit Gosavi, Susan L. Murray

Miners Solving for Tomorrow Research Conference

No abstract provided.

Unsupervised Contrastive Learning Based Clustering For Robust Emotion Classification, Nozaer Omar, Sanjay Kumar Madria

Miners Solving for Tomorrow Research Conference

No abstract provided.

A New Weighting Scheme To Optimize The Full Fisher Information In Multi-Tracer Surveys Of The Large-Scale Structure, Cole Rischbieter, Shun Saito

Miners Solving for Tomorrow Research Conference

No abstract provided.

On The Robustness Of Adaptive Resonance Theory Neural Networks, Shane Cairns, Leonardo Enzo Brito Da Silva, Sasha Petrenko, Donald C. Wunsch

Miners Solving for Tomorrow Research Conference

No abstract provided.

2025 - 1st Annual Miners Solving For Tomorrow Research Conference- Graduate, Joshua Gray, Joseph Akor, Rajarshi Kar, Ali Fasihi, Songtao Zhang, Cole Rischbieter, Jacob Ortega, Julia Mcintyre, Elizabeth Pritchett, Ugochukwu Ewuzie, Maryam Shariff Paroushi, Milad Aghayi Anaraki, Sutapa Bhattacharya, Sara Mccauley, Mohammad Hossein Afsharmovahed, Bahaa Chammout, Haodao Li, Tong Zhou, Yafang Hei, Mahmuda Akter, Shane Cairns, Nuzaer Omar, Nathan Tibbetts, Syed Talha Riaz, Eyuel Getahun, Kolawole Arowoogun, Effat Eskandari, Adeyinka Olaseinde, Amaneh Babaee, Abid Hasan Rafi, Niloofar Zendehdel, Khosor Ghorbani Zadeh, Rushikesh Magdum, Jacob Hauck, Gracie Boyer, Alireza Fallahi, Matik Heskin, Ranjit Joy, Emmanuel Olugbade, Mehedi Hasan Tusar, Mobashir Ahmed, Carter Glynn, Weston Hartzell, Mahsa Moradi, Aamir Iqbal, Amitav Sen, Collin Gentry, Kiernan O'Boyle, Jennifer Harrell, Lucas Greiner, Ahmad Heidari, Samiksha Aryal, Prithbey Dey

Miners Solving for Tomorrow Research Conference

No abstract provided.

Amorphous Metal Transparent Conducting Oxide P-Type Semiconductors, Joshua Santy

Miners Solving for Tomorrow Research Conference

No abstract provided.

Radiative Energy And Mass Shifts Of Quantum Cyclotron States, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

Abstract: We discuss relativistic and radiative corrections to the energies of quantum cyclotron states. In particular, it is shown analytically that the leading logarithmic radiative (self-energy) correction to the bound-state energy levels of quantum cyclotron states is state independent and must be interpreted as a magnetic field-dependent correction to the electron's mass in a Penning trap.

Phases And Dynamics Of Quantum Droplets In The Crossover To Two-Dimensions, Jose Carlos Pelayo, George Bougas, Thomás Fogarty, Thomas Busch, Simeon I. Mistakidis

Physics Faculty Research & Creative Works

We explore the ground states and dynamics of ultracold atomic droplets in the crossover region from three to two dimensions by solving the two-dimensional and the quasi-two-dimensional extended Gross-Pitaevskii equations numerically and with a variational approach. By systematically comparing the droplet properties, we determine the validity regions of the pure two-dimensional description, and therefore the dominance of the logarithmic nonlinear coupling, as a function of the sign of the averaged mean-field interactions and the size of the transverse confinement. One of our main findings is that droplets become substantially extended upon transitioning from negative-to-positive averaged mean-field interactions. This is accompanied …

Generic Transverse Stability Of Kink Structures In Atomic And Optical Nonlinear Media With Competing Attractive And Repulsive Interactions, S. I. Mistakidis, G. Bougas, G. C. Katsimiga, P. G. Kevrekidis

Physics Faculty Research & Creative Works

We demonstrate the existence and stability of one-dimensional (1D) topological kink configurations immersed in higher-dimensional bosonic gases and nonlinear optical setups. Our analysis pertains, in particular, to the two- and three-dimensional extended Gross-Pitaevskii models with quantum fluctuations describing droplet-bearing environments but also to the two-dimensional cubic-quintic nonlinear Schrödinger equation containing higher-order corrections to the nonlinear refractive index. Contrary to the generic dark soliton transverse instability, the kink structures are generically robust under the interplay of low-amplitude attractive and high-amplitude repulsive interactions. A quasi-1D effective potential picture dictates the existence of these defects, while their stability is obtained numerically and analytically …

Synergy In Materials: Leveraging Phosphosilicate Waste Forms For Electrochemical Salt Waste, Jonathan S. Evarts, Brian J. Riley, Charmayne E. Lonergan, Michaella S. Harris, Jincheng Bai, Eric W. Bohannan, Iheanyichukwu Ajoku, Saehwa Chong, John S. Mccloy

Materials Science and Engineering Faculty Research & Creative Works

Waste forms containing glassy and crystalline phosphate and silicate phases were produced to immobilize salt waste simulants from pyro processing and characterized by using Raman spectroscopy, Mössbauer spectroscopy, X-ray diffraction, scanning electron microscopy, heat capacity, and chemical durability measurements. In this work, a phosphosilicate waste form is presented to leverage the benefits of both borosilicate glasses and iron phosphate glasses. To improve waste loading, prior to immobilization, salt simulants were successfully dechlorinated using ammonium dihydrogen phosphate, mixed with a borosilicate frit (5–30 wt. %) and Fe2O3, and vitrified. Additions of 2.5–15 wt. % borosilicate glass (NBS3) improved normalized release rates …

Local Structure Of Zinc-Indium-Tin Oxide Films Via Grazing-Incidence X-Ray Pair-Distribution Functions And Theoretical Methods, G. B. González, C. J. Benmore, Julia E. Medvedeva, J. S. Okasinski, C. Riegger, O. Medina, M. M. Stulajter, T. Bsaibes, G. Cardenas, S. Cone, K. Edlund, M. Osorio, T. Holmes, I. Zhuravlev

Physics Faculty Research & Creative Works

A detailed experimental and theoretical study on the local (r ≤ 4.5 Å) atomic structure of amorphous and crystalline zinc-indium-tin oxide (ZITO) thin films using grazing-incidence x-ray Pair-Distribution Functions (PDFs), ab initio Molecular Dynamics (MD), and Empirical Potential Structure Refinement (EPSR) Monte Carlo simulations is presented. High-energy synchrotron x rays, a two-dimensional detector, and different incident angles were used to probe the depth uniformity of five (ZnO)0.15 (In2O3)0.70 (SnO2)0.15 films that were deposited via pulsed-laser deposition at growth temperatures (TG) ranging from 25 to 300 °C. Films deposited at TG ≤ 150 °C were amorphous. The partially crystalline (TG = …

Experiment-Based Superposition Thermal Modeling Of Laser Powder Bed Fusion, Cody S. Lough, Tao Liu, Robert G. Landers, Douglas A. Bristow, James A. Drallmeier, Ben Brown, Edward C. Kinzel

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Parts experience significant local thermal variations during the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process, providing a potential source of defects. Near real-time thermal predictions can enable better process planning and facilitate corrections on subsequent layers to enable the engineering of laser parameter and scan path combinations that avoid defect inducing scenarios. This paper considers an experiment-based Discrete Green's Function (DGF) thermal model for temperature field prediction in LPBF. An analytical framework is developed and used to calculate an experimental DGF (i.e., powder bed's single pulse temperature response) from spatiotemporal Short-Wave Infrared (SWIR) camera data. The extracted …

Irreducible Three-Loop Vacuum-Polarization Correction In Muonic Bound Systems, Gregory S. Adkins, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

Three-loop electronic vacuum-polarization corrections due to irreducible diagrams are evaluated for two-body muonic ions with nuclear charge numbers 1≤Z≤6. The corrections are of order α3(Zα)2mr, where α is the fine-structure constant and mr is the reduced mass. Numerically, the energy corrections are found to be of the same order of magnitude as the largest of the order α2(Zα)6mr corrections, and are thus phenomenologically interesting. Our method of calculation eliminates numerical uncertainty encountered in other approaches.

Reflections On Linear B, (Part 9): The Sycamore Fig Tree In Ancient-Egyptian Mythology, Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

Linear B sign 30 and its antecedent (Linear A 60) — both shaped like a tree -- have already been connected with figs, and their visual representation would be that of a fig tree rather than the fruit itself. Like several other Linear B signs, Linear B 30 and its Linear A antecedent may reflect ancient Egyptian religious mythology -- in this case the sycamore fig tree, which was associated with the goddesses Isis and Hathor and which provided nourishment to people in the afterlife. There is also the remarkable ritual of Isis or Hathor assuming the guise of a …

Understanding The Underlying Trends In Us Construction Labor Wages: A Data-Driven Mixed-Method Computational Approach, Bahaa Chammout, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Precisely forecasting construction costs is crucial for maintaining financial stability for contractors and the broader construction sector. Nonetheless, this task has long been acknowledged as challenging. Recent global events and inflationary pressures have notably driven up construction labor expenses. While existing research examined labor shortages, there remains a gap in understanding the diverse labor wage trends. This paper addresses this research gap following a multistep methodology, which included: (1) gathering construction labor data from 1999 to 2023; (2) conducting trend and statistical analyses to discern the underlying patterns in labor trends; (3) employing clustering analysis to categorize construction occupations based …

Structure-Property Relations Of Binary Ferrite Melts, C. J. Benmore, C. Shi, O. L.G. Alderman, J. P. Harvey, D. Lipke, J. K.R. Weber

Materials Science and Engineering Faculty Research & Creative Works

Molten ferrite systems are used in the smelting and refining processes in steelmaking, to reduce the loss of metals in slags and to accelerate reaction rates. Here, high-energy x-ray diffraction experiments have been performed on aerodynamically levitated molten spheres of 43BaO-57FeOX and 43SrO-57FeOX at 1873 K using laser beam heating. The composition was varied within the range of x = 1-1.5 by changing the oxygen partial pressure of the levitation gas. The corresponding x-ray pair distribution functions have been interpreted using empirical potential structure refinement (EPSR) modeling. In oxygen-rich melts (x = 1.5), our EPSR models indicate very similar structures …

Power System Operations Modeling And Optimization Using Pyomo, Ahmad Heidari, Rui Bo

Graduate Student Research & Creative Works

"The energy sector has witnessed transformative advancements over the past few decades. Power systems, which form the backbone of modern society, have grown increasingly complex with the integration of renewable energy sources, energy storage, and emerging technologies. As these systems evolve, so does the need for efficient operation and optimization strategies to ensure reliability, sustainability, and economic performance.

Optimization plays a central role in solving real-world challenges such as balancing power generation and demand, minimizing operational costs, and managing grid constraints. However, many existing resources tend to focus either on theoretical aspects of optimization or rely on expensive, proprietary software …

A Comprehensive Survey Of Data-Driven Solutions For Lorawan: Challenges And Future Directions, Poonam Maurya, Abhishek Hazra, Preti Kumari, Troels Bundgaard Sørensen, Sajal K. Das

Computer Science Faculty Research & Creative Works

Long-range Wide-area Network (LoRaWAN) is an innovative and prominent communication protocol in the domain of Low-power Wide-area Networks (LPWAN), known for its ability to provide long-range communication with low energy consumption. However, the practical implementation of the LoRaWAN protocol, operating at the Medium Access Control layer and specially built to work upon the LoRa physical layer, presents numerous research challenges, including network congestion, interference, optimal resource allocation, collisions, scalability, and security. To mitigate these challenges effectively, the adoption of cutting-edge data-driven technologies such as Deep Learning (DL) and Machine Learning (ML) emerges as a promising approach. Interestingly, very few existing …

Terminator: A Software Package For Fast And Local Optimization Of His-Tag Placement For Protein Affinity Purification, Rokas Gerulskis, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Although the use of affinity tags can greatly improve purification of expressed enzymes, the placement of affinity tags can significantly impact the expression, solubility, and function of recombinant proteins. To facilitate the optimal design of 6xHis-tagged constructs for protein purification, we developed Terminator, a Python-based software package, which takes a UniProt ID or existing protein sequence as input, identifies related sequences, maps sequence conservation retrieved from ConSurf onto protein 3D structures retrieved from the PDB and SWISS-MODEL, and analyzes proximity to cavities and functional sites to recommend the N- or C-terminus for placement of 6xHis fusion tags 86-100% accuracy in …

Few-Shot Transfer Learning For Individualized Braking Intent Detection On Neuromorphic Hardware, Nathan A. Lutes, V. Sriram Siddhardth Nedendla, K. Krishnamurthy

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a Brain Chip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. Approach. Data are collected from participants operating an NVIDIA JetBot on a testbed simulating urban streets for three different scenarios. Participants receive a braking indicator in the form of: (1) an audio countdown in a nominal baseline, stress-free environment; (2) an …

Uav-Based Phytoforensics: Hyperspectral Image Analysis To Remotely Detect Explosives Using Maize (Zea Mays), Paul V. Manley, Stephen M. Via, Joel G. Burken

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Remnant explosive devices are a deadly nuisance to both military personnel and civilians. Traditional mine detection and clearing is dangerous, time-consuming, and expensive. And routine production and testing of explosives can create groundwater contamination issues. Remote detection methods could be rapidly deployed in vegetated areas containing explosives as they are known to cause stress in vegetation that is detectable with hyperspectral sensors. Hyperspectral imagery was employed in a mesocosm study comparing stress from a natural source (drought) to that of plants exposed to two different concentrations of Royal Demolition Explosive (RDX; 250 mg kg−1, 500 mg kg−1). Classification was accomplished …

Assessing The Impact Of Radar-Rainfall Uncertainty On Streamflow Simulation, Nicolás Velásquez, Witold F. Krajewski, Bong Chul Seo

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Hydrological models and quantitative precipitation estimation (QPE) are critical elements of flood forecasting systems. Both are subject to considerable uncertainties. Quantifying their relative contribution to the forecasted streamflow and flood uncertainty has remained challenging. Past work documented in the literature focused on one of these elements separately from the other. With this in mind, we present a systematic approach to assess the impact of QPE uncertainty in streamflow forecasting. Our approach explores the operational Iowa Flood Center (IFC) hydrological model performance after altering two radar-based QPE products. We ran the Hillslope Link Model (HLM) for Iowa between 2015 and 2020, …

Oxidation–Reduction Of Ti-6al-4v In Direct Energy Deposition Subject To Minimum Argon Consumption, Bharadwaja Ragampeta, Prashansa Ragampeta, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Ti-6Al-4V is a well-known alloy for its low density and excellent corrosion resistance, making it popular in aerospace, marine, medical, and automotive applications. However, at elevated temperatures, the alloy forms oxides, leading to embrittlement. In additive manufacturing, particularly in the direct energy deposition (DED) process, which involves high temperatures, the alloy experiences oxidation. An inert gas chamber provides shielding during the process but limits the size of the manufactured components, and deposition in a vacuum chamber can alter the chemical composition of the alloy. Local shielding is a technique generally used for such applications, but it uses a high volume …

Impurity Behavior In Cast Copper Anodes: Implications For Electrorefining In A Circular Economy, Agustin Morales-Aragon, Daniel Sánchez-Rodas, Guillermo Ríos, Michael S. Moats

Materials Science and Engineering Faculty Research & Creative Works

The behavior of impurities in cast copper was investigated to simulate production with increased utilization of secondary sources within the framework of a circular economy. The incorporation of impurities, particularly Ni, Sn, and Sb, from recycled Cu may significantly impact the electrorefining process. In this study, commercial anodes were doped with Ni, Sn, and Sb concentrations of 2500–6500 g/t, 300–900 g/t, and 450–950 g/t, respectively. Anode concentrations of Pb and Bi were maintained at 1000 g/t and 350 g/t, respectively. As concentrations were examined at two levels, 860 or 1700 g/t, depending on the commercial anode used to create the …

Simulation-Based Models For Postearthquake Response: A Survey And Research Directions, Abhijit Gosavi, Lauryn A. Spearing, Lesley H. Sneed

Engineering Management and Systems Engineering Faculty Research & Creative Works

Computer simulation is increasingly being used by emergency planners as a tool to improve disaster response given that it can model real-world scenarios, such as earthquakes. Although there has been an increase in simulation research focused on disaster response, much of this literature is from disparate fields and across disaster scenarios. To bridge this gap, this paper surveys simulation-based models for post-earthquake response from the year 2000 onward. Advantages of simulation over closed-form statistical models are discussed. Three main subproblems in post-earthquake response models are explored: (1) service distribution (e.g., food, water), (2) infrastructure restoration (at the building and transportation …

Application Of Convolutional Neural Network For Seismic Event Classification: Impact Of Dataset Quality, Distribution, And Human-In-The-Loop Feedback, Yanwei Zhang, Stephen S. Gao, Xiaoyi Fan, Shaohui Zhou, Junhao Qu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Convolutional neural networks (CNNs) have gained popularity in geophysical research due to their exceptional performance in various areas. However, achieving reliable results with CNNs typically requires a significant amount of high-quality data for training. In this study, we develop a CNN to classify natural earthquakes, mine collapses, and explosions using seismic waveforms from 287 stations in Shandong Province, China. The dataset comprises 1035 earthquakes, 159 mine collapses, and 586 explosions. To address the impact of unreliable measurements, we employ cross validation to screen, manually correct, or discard measurements with inconsistent labels assigned by human experts and CNN. By refining the …

Collision-Free Exploration By Mobile Agents Using Pebbles, Sajal K. Das, Amit Kumar Dhar, Barun Gorain, Madhuri Mahawar

Computer Science Faculty Research & Creative Works

In this paper, we study collision-free graph exploration in an anonymous network. The network is modeled as a graph G = (V, E) where the nodes of the graph are unlabeled, and each edge incident to a node v has a unique label, called the port number, in {0, 1, ⋯, d - 1}, where d is the degree of the node v. Two identical mobile agents, starting from different nodes in G have to explore the nodes of G in such a way that for every node v in G, at least one mobile agent visits v and no …

Elastic Scheduling For Graceful Degradation Of Mixed-Criticality Systems, Zhuoran Sun, Marion Sudvarg, Christopher Gill

Computer Science Faculty Research & Creative Works

Many mixed-criticality system models drop all jobs of low-criticality tasks when a criticality mode switch occurs, ensuring that high-criticality tasks still can meet their deadlines in the new mode. However, this means that even important low-criticality tasks are discarded, which may not be acceptable in some systems in practice. This paper addresses that distinction between criticality and importance through a new Inelastic Graceful Earliest Deadline First with Virtual Deadlines (IG-EDF-VD) scheme that upon a criticality mode switch only discards the least important low-criticality tasks necessary to ensure feasibility. Moreover, we consider elastic scheduling within our mixed-criticality model (EG-EDF-VD), using compression …

Circadian And Age-Related Variations Of Amino Acids Levels In Drosophila Brains: Correlations And Descriptive Dimensions, Sandrine Parrot, Jacob Crehan, Chloé Aman, Philippe De Deurwaerdère, Matthew S. Thimgan, Laurent Seugnet

Biological Sciences Faculty Research & Creative Works

A comprehensive view of whole-brain amino acid levels holds the potential to provide valuable insights into the brain's state, given the mutual interconnections through metabolism, food intake, and neurotransmission. We tested this concept by evaluating free amino acid levels in single Drosophila brains across 24 h and at two different ages. A large proportion of these amino acids displayed time-of-day variations, and a subset exhibited age-dependent variations. Cross-correlation analysis of the data sets confirmed broad time-of-day and age dependent interconnections between amino acids. Factor Analysis of Mixed Data revealed further data structuration along key amino acids. For example, 50% of …