Digital Commons Network^™

Comparative Analysis Of Task Scheduling In Multi-Tier Fog-Cloud Computing: From Classical Approaches To Greedy Multi-Objective Optimization, Zafril Rizal M. Azmi, Najmul Haque, Saydul Akbar Murad

Faculty Publications

Fog computing extends cloud services to the network edge, enabling low-latency processing for time-sensitive applications. However, scheduling complexity significantly increases due to heterogeneous resources, dynamic workloads, and strict Quality-of-Service (QoS) constraints. Although numerous scheduling techniques have been proposed, existing studies often assess only a narrow subset of algorithms or rely on offline metaheuristics unsuitable for real-time environments. This paper presents a comprehensive comparative evaluation of twelve scheduling algorithms, including five classical, one heuristic, and six metaheuristic-inspired approaches, within a realistic 20-node multi-tier fog-cloud topology. Across 1,365 experiments spanning seven utilization levels, we analyze each algorithm’s deadline adherence, load distribution, and …

An Abundant Lack Of Introspection, Jonathan Adler

Faculty Publications

In this review Jonathan Adler critiques Abundance authors Klein and Thompson's analysis of how regulation is holding back progress in decarbonization, America's housing supply crisis, and innovation. While agreeing with the authors' assessment that regulation policy is hampering efforts in these areas, Adler objects to the book's proposals for improving regulatory bottlenecks, arguing the authors of Abundance refuse to acknowledge the role of market institutions in creating abundant supply or to admit the fault in their assumption that the failures of centralized government decision making can be repaired while maintaining centralized government decision making.

This abstract has been constructed from …

Atomistic Simulations Of Crystallographic Anisotropy And Defects In Shock Loading, Benjamin P. Helman, Andre Archer, Logan Nagy, Samuel C. Wagers, Douglas E. Spearot, Adib J. Samin

Faculty Publications

The impact of crystallographic orientation, select grain boundaries, and vacancies on the shock response of aluminum was investigated using molecular dynamics simulations. Shock loading in the [001], [011], and [111] directions was explored, revealing anisotropic behavior in shock speed, generated dislocation density, and melting. The Hugoniot elastic limit (HEL) in the [100], [110], and [111] directions were calculated as 18.7 GPa, 17.8 GPa, and 22.5 GPa, respectively. These results were found to be an order of magnitude larger than the uniaxial compressive yield strengths computed at high strain rate using an affine loading scheme. Metastable melting in the [011] and …

Generation Of Khz-Rate Complex-Structured Liquid Targets For Relativistic Laser–Plasma Interactions, Michael L. Dexter, Stephen J. Hageman, Gregory Ngirmang, Kyle D. Frische, Joseph Snyder, John T. Morrison, Enam A. Chowdury, Anil K. Patnaik

Faculty Publications

With the rise of high repetition rate ultra-intense laser systems, there is a need for solid density targets to study relativistic laser–plasma interactions that can operate at the same repetition rate. Flowing liquid targets are attractive because they are self-replenished, debris free, cost effective and easy to use. Liquid targets have been used for high-repetition rate (up to kHz rate) generation of electrons, protons, x rays, and neutrons by our group and elsewhere. In this Letter, we demonstrate a kHz-rate generation of a variety of dynamically shaped complex-structured targets from the interaction of a 10¹⁶ W/cm² focused laser …

Boiling Flow Estimation For Aero-Optic Phase Screen Generation, Jeffrey W. Utley, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Aero-optic effects due to turbulence can reduce the effectiveness of transmitting light waves to a distant target. Methods to compensate for turbulence typically rely on realistic turbulence data, which can be generated by i) experiment, ii) high-fidelity computational fluid dynamics (CFD), iii) low-fidelity CFD, and iv) autoregressive methods. However, each of these methods has significant drawbacks, including monetary and/or computational expense, limited quantity, inaccurate statistics, and overall complexity. By contrast, the boiling flow algorithm is a simple, computationally efficient model that can generate atmospheric phase screen data with only a handful of parameters. However, boiling flow has not been widely …

Active Learning Of Constraint Boundaries Using Expected Magnitude Of Incorrectness And Neural Networks, Atticus Beachy, Ramana V. Grandhi

Faculty Publications

This research proposes an acquisition function for constraint boundary identification, with applications to hypersonic air vehicles. Hypersonic vehicles endure extreme thermal loads caused by aerodynamic heating, resulting in a strong coupling between structural performance and aerothermodynamics. However, modeling coupled system behaviors requires simultaneous consideration of both aerodynamic and structural design variables, increasing the dimensionality of the design trade space and the difficulty of accurately modeling the constraints. Several active learning schemes have been proposed to accelerate identification of the composite feasible region that satisfies all constraints. Some of these require integrating the surrogate model over the entire design space with …

Assessing Planetiq Gnss-Ro Ionospheric Electron Density And Tecusing Ground-Based Ionosondes And Cosmic-2, Mohammed Alheyf, Mohamed S. Yamany, Ibrahim F. Ahmed

Faculty Publications

Radio occultation (RO) has become a key technique for monitoring the ionosphere by deriving electron density (Ne) profiles and total electron content (TEC) from GNSS signals. This study assesses the newly deployed PlanetiQ GNOMES constellation by validating its ionospheric Ne profiles and profile-based TEC against collocated measurements from ionosondes and the COSMIC-2 mission under both quiet and disturbed geomagnetic conditions. Data matching for the statistical validation uses conservative spatial thresholds of less than 1◦ in latitude and longitude and temporal limits of 30 min for ionosondes and 1 hfor COSMIC-2, supported by a dedicated sensitivity analysis, whereas storm-time case studies …

Using Ai To Add Tables Of Contents To Cataloging Records, Marissa Bischoff, Lance Hansen

Faculty Publications

A table of contents and summary are important metadata that improve the discoverability and description of our materials. They are optionally included in catalog records, though, because transcribing these by hand is time intensive.

We sought the most efficient way to scan and AI format the table of contents pages for inclusion in the 505 field of catalog records.  We explored different AI software, iterative prompting and the time-effectiveness of the process, in comparison to hand-typed metadata fields.

Matching Two Long Interferometric Pathlengths Using Low Temporal Coherence Light For Finding Hong–Ou–Mandel Dip, Keith A. Wyman, Noah S. Everett, Anil K. Patnaik

Faculty Publications

Hong–Ou–Mandel (HOM) dip from a biphoton source in a two-photon interferometer provides a myriad of quantum tools for quantum communication and sensing. But the stringent requirements for spatial coherence between the photon pair makes it prohibitively difficult to observe high-fidelity HOM dip in long-distance free-space implementations, e.g., for the photon pairs involved in quantum communication need to match the two path lengths within a few 10 s of micron because of the short coherence width of the two-photon wave-packet. While many techniques for the pathlength balancing of two interferometric arms have been studied and applied extensively, such balancing is further …

Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive three-dimensional (3D) density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a …

Mapping The Tar Vrna Interaction With Hiv-1 Integrase, Jian Sun, Rahul Yadav, Tolga Catmakas, Luke Fisher, Nicholas C. Fitzkee, Jacques J. Kessl

Faculty Publications

A series of critical interactions within the viral core between viral RNA (vRNA) and HIV-1 Integrase (IN) has previously been reported. In these studies, contact points between vRNA and IN were identified using RNA-seq and MS-based protein foot-printing approaches. Several IN amino acids located in its C-terminal domain (CTD) were found to be essential for vRNA binding, and their alanine substitution severely impacted the correct morphogenesis of the mature viral core. Here, we have used the TAR element to extend these studies by performing a comprehensive mapping of the interaction by deploying RNA crosslinking and NMR methodologies. Together, these approaches …

Backscattering By Particles Of Sizes <0.2 Μm In Seawater, Xiaodong Zhang, Yuanheng Xiong

Faculty Publications

We measured the angular scattering functions at 517 nm in different size fractions, including bulk and very small particles (VSP for diameters <0.2 μm), in a variety of waters ranging from coasts to open oceans and from surface to depths as deep as 3,000 m. The measurements revealed a strong covariation in backscattering between VSP and bulk particle populations. The fractional contribution by VSP decreases from 60% in clear oceanic water where bulk particle backscattering coefficient bbp is on the order of 0.001 m⁻¹ to <2% in turbid coastal water where bbp ∼0.1 m⁻¹. An empirical model is developed (r² = 0.89) to estimate bbp for VSP from the bulk bbp, which can now be routinely obtained from satellite observations.

The Impact Of Dispatch Weight Restrictions On Derivative Aircraft Propulsion Technology Evaluation, Timothy T. Takahashi

Faculty Publications

This paper arises from an ARPA-E-sponsored project seeking design opportunities to retrofit existing aircraft with hybrid electric propulsion systems. Engineers typically configure aircraft to fly a given payload over a long range, which is subject to field performance constraints. In practice, operators fly transport aircraft (civilian and military) in a manner where dispatch consciously trades payload and/or range to enable safe operations to and from short runways. This work describes a simple yet novel analytical process suitable for inclusion in conceptual design or technology portfolio trade study evaluations to assess the impacts of weight-restricted dispatch upon usable payloads. We find …

Advanced Finite Element Modeling And Design Enhancement Of Slender Square Concrete-Filled Double-Skin Steel Tubular Columns, Mahmoud T. Nawar, Ayman El-Zohairy, Mohamed Emara, Raghda I. Halima

Faculty Publications

Limited research exists on the behavior of square CFDST slender columns, especially under the consideration of the relation global buckling and confinement effect. This study evaluates square concrete-filled double-skin steel tubular (CFDST) columns using nonlinear finite element analysis (FEA) to simulate structural behavior under axial and eccentric loads until failure. Parametric analyses of extensive specimens of square CFDST pinended columns evaluate various parameters, providing design insights for engineering applications. The study was conducted over a wide range of slenderness ratios. Four concrete varieties with compressive strengths were tested: normal concrete (NC), engineered cementitious composites (ECCs), high-strength concrete (HSC), and ultra-high-strength …

Effects Of Niobium On The Mechanical And Oxidation Properties Of Additively Manufactured Tungsten, Alexander Lesieur, Cayla Eckley, Ryan A. Kemnitz

Faculty Publications

Although additive manufacturing presents a novel and customizable approach to fabricating tungsten (W) alloys, the layer-by-layer production technique presents a unique set of processing challenges which are further exacerbated by the metal’s refractory properties. In this study, additions of niobium (Nb) were found to improve the mechanical properties and oxidation resistance of additively manufactured W. Microstructural investigation revealed the effect of Nb on the cracking, grain size, and texture in the as-built material. Mechanical compression testing showed significant improvement in ductility with increasing Nb content. The low concentrations of Nb used did not induce large changes in the yield strength …

Radio Frequency Resonate And Fire (Rf-Raf) Neurons Supporting Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti

Faculty Publications

Radio Frequency Fingerprinting (RFF) enables passive physical-layer device authentication by exploiting unintentional hardware variations in wireless transmitters. Neuromorphic implementations are attractive, given their potential for low-latency, energy-efficient inference capability under Size, Weight, and Power (SWaP) constraints at the edge. A new RFF capability is demonstrated here using recently introduced Radio Frequency Resonate-and-Fire (RF-RAF) neurons and eight WirelessHART devices. Performance is evaluated for RF-RAF-generated fingerprints against the established Gabor Transform (GTX) baseline using three classifier architectures: Random Forest (RndF), Convolutional Neural Network (CNN), and a Time-Incremented Spiking Neural Network (TI-SNN). The results show that RF-RAF fingerprints achieve an average classification accuracy …

Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih

Faculty Publications

Protecting public health from infectious diseases requires collective action, as individual behaviors—such as vaccination and mask-wearing—directly influence disease dynamics. During the COVID-19 pandemic, unexpected public responses often undermined the effectiveness of interventions, highlighting the need to understand collective behavioral patterns and motivations to design more effective mitigation strategies. This study presents an agent-based simulation model that captures how individuals adjust self-protective behaviors based on evolving opinions about disease risk and examines how these decisions interact with external factors, such as public health interventions, to shape collective outcomes. To improve the representativeness of the simulated population, multiple datasets were integrated to …

Inconsistencies Emerge Between Regional And Local-Scale Water Security Metrics At Military Installations, Abigail Birnbaum, Michael L. Berg, Caitlin Grady, Daniel J. Weeks, Christopher M. Chini

Faculty Publications

Recent United States federal policy for military installations has emphasized the importance of developing a standardized approach for water security assessment to monitor changes in water resources and the ability for an installation to meet both its civilian and mission needs. For military installations in the United States, these assessments must consider demands both inside and outside the installation’s fence line, as regional resources are required to meet mission readiness. Focusing on physical water scarcity, this study compares four water security metrics with unique formulations and spatial resolutions, including an installation-scale metric and multiple regional metrics defined for either baseline …

Analysis Of Approximations In Flash Thermal Diffusivity Measurements Using High‑Fidelity Simulations, Tage T. Burnett, Jakob G. Bates, Matthew R. Jones, Christopher R. Dillon, John Tencer

Faculty Publications

Thermal diffusivity is an important material property for understanding and characterizing transient behavior in many heat transfer applications. This study investigates the accuracy and approximations of inverse mathematical models for measuring thermal diffusivity of materials via the widely used Flash Method. High-fidelity simulations of the Flash Method in copper, silicon carbide, silicon, and glass were performed as numerical experiments and included physics such as in-depth absorption, radial conduction, and surface convection. Data from those numerical experiments were used to estimate material thermal diffusivity using seven traditional and new inverse models. Parker’s original model had relative errors 𝜖< 5% when the approximations it makes were enforced in numerical experiments. Newer models performed well even when experimental restrictions were relaxed. Models that include radial heat conduction were capable of accurately measuring thermal diffusivity (𝜖< 1%) when a Gaussian energy source was used. Models with radial conduction and in-depth material absorption of the laser source could calculate thermal diffusivity for semi-transparent materials such as silicon (𝜖< 1%) and even transparent materials like glass (𝜖< 10%). Convective losses from the material’s front surface had a negligible impact on measurements except for very low thermal diffusivity materials. Using temperatures from many locations of the test material’s surface increased resilience to noise, reducing the distribution of thermal diffusivity measurements by more than an order of magnitude. The models developed in this study could enable a more relaxed Flash Method experimental setup that maintains thermal diffusivity accuracy and extend the utility of the Flash Method to semitransparent materials.

Ai Need Not Make One Slothful, Roy A. Kaelin Jr

Faculty Publications

As National Louis University seeks to plan and advance its way amid the potential perils and pitfalls of so-named artificial intelligence, one finds that with reasonable workflows and guard rails, the use of AI proposes both potential promise and prospect, to assist and augment the natural intelligence that students and teachers bring to the classroom, encouraging them to pursue STEM-related activities with the preparation and deployment of focused and directed AI-bots. This paper presents examples and a case study of that directed and focused approach, the incremental lessons learned to date, and a proposed path to advance worthwhile AI …

Wrky Transcription Factors: Integral Regulators Of Defence Responses To Biotic Stress In Crops, Dongjiao Wang, Ruize Zhang, Wenhui Zou, Yuanyuan Zhang, Wanying Zhao, Tingting Sun, Qibin Wu, Zheng Qing Fu, Youxiong Que

Faculty Publications

Crops are continually challenged by biotic stresses, including fungal, bacterial and viral pathogens and insect pests, which cause substantial yield and quality losses worldwide. WRKY transcription factors constitute a plant-specific and functionally diverse family that is central to immune regulation. Recent advances in genomic resources and multi-omics approaches have accelerated the identification and functional characterisation of WRKYs in crops. This review summarises the structural features and classification of WRKY genes and their genome-wide distribution across crop species. It also synthesises WRKY-centred regulatory modules that mediate resistance to major classes of biotic stress. In antifungal defence, WRKYs reinforce pattern- and effector-triggered …

Statutory Backups For Endangered Constitutional Rights, Aaron-Andrew P. Bruhl

Faculty Publications

This Article concerns the phenomenon of “statutory backup rights,” or statutes that provide protections parallel to constitutional rights that are believed to be at risk of judicial abrogation. Proposals for backup rights gained attention in the aftermath of the Supreme Court’s 2022 decision in Dobbs v. Jackson Women’s Health Organization, which not only eliminated the constitutional right to abortion but called into question some other constitutional rights as well. Shortly after Dobbs, Congress enacted a limited statutory backup for same-sex marriage. States have created backup rights across a range of topics, some of which appeal mostly to those …

Measurements And Scaling Of Ion Propulsion Impulse During Driven Magnetic Reconnection, Fatima Ebrahimi, Nicholas A. O'Gorman, Kush Maheshwari, Jongsoo Yoo, Alexandre Sainterme, Hantao Ji

Faculty Publications

Impulse scaling during magnetic reconnection, the magnetic energy conversion to kinetic energy, via direct Mach probe measurements in Magnetic Reconnection Experiment is examined. Ion exhaust velocity and impulse scalings with reconnecting magnetic field during the push phase of driven reconnection are presented. The outflows and impulse measurements are compared with global MHD simulations. Both measurements and simulations reveal a favorable scaling, greater than linear, of impulse with reconnecting field. These scaling results establish that magnetic reconnection could be utilized for plasma propulsion.

Examining The Psychometric Structure Of An Instrument To Measure Students’ Interests And Motivation In Science Learning: Factor Analysis And Measurement Invariance, Fuhui Tong, Shifang Tang, Zhuoying Wang, Beverly J. Irby

Faculty Publications

In this study, we examined the psychometric properties (reliability, validity, and underlying factor structure) and measurement invariance of a researcher-developed instrument: Motivated Strategies for Science Learning (MSSL). Data were collected from 2765 fifth-grade students across [state withheld] school districts. Results from exploratory and confirmatory factor analyses suggested satisfactory psychometric properties of MSSL. We further identified strong evidence to support configural, metric, scalar, and strict invariance across school location groups (i.e., rural and non-rural), confirming that the instrument can accurately capture the construct of science learning motivation among fifth-grade students from both rural and non-rural Texas schools. The study provides the …

The Great Depression And Canada's Major Originalist Decade, Preston Jordan Lim

Faculty Publications

Few periods of Canadian history have been as momentous or terrible as the Great Depression. The Dominion and provincial governments’ inability to combat financial and environmental catastrophe led many Canadians to openly question the appropriateness of their constitutional framework. As legal historians have since documented, many leading jurists of the time believed that a strong central government could, through the institution of national programs, contain the Great Depression; in the eyes of these 1930s jurists, the Judicial Committee of the Privy Council—then Canada’s apex court—had sapped the federal government of its powers by misinterpreting the British North America Act, 1867 …

Libraries And Librarians Get After Participatory Science, Catherine Wong, Megan Bresnahan

Faculty Publications

No abstract provided.

Temperature Determination And Scene Change Artifact Mitigation When Using Fourier-Transform Spectroscopy On Targets With Time-Varying Temperature, Kode A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz

Faculty Publications

Fourier-transform spectroscopy is a widely used technique for determining the spectral and thermal properties of a target. However, target temperature variations during measurement can compromise the spectral accuracy. Temperature fluctuations induce oscillations superimposed on the target spectrum. These oscillations, referred to as scene-change artifacts, degrade the spectral accuracy. The literature is divided, with theoretical predictions suggesting negligible artifacts and growing experimental evidence reporting significant artifacts. This paper presents a theory and experimental validation of scene-change artifacts originating from target temperature variations. Traditionally, the interferogram offset is assumed to be constant, an invalid assumption for a changing scene. The error is …

Roles Of Mads-Box Transcription Factors In Plant Responses To Abiotic And Biotic Stresses, Na Liu, Zihao Liu, Guangxiang Tian, Shijia Zhao, Hao Chu, Yiheng Hu, Yingfan Zhao, Yanyan Zhang, Kun Cheng, Daowen Wang, Wenming Zheng, Zhengqing Fu, Xu Wang

Faculty Publications

Plants deploy sophisticated adaptive mechanisms to mitigate the detrimental effects of abiotic stresses (drought, salinity, temperature extremes, and heavy metals) and biotic stresses (pathogens and senescence) on growth and productivity. Central to these responses are transcription factors (TFs) that orchestrate stress-responsive gene networks. Among TF families, MADS-box proteins, characterized by their evolutionarily conserved DNA-binding domain, function as pivotal regulators of developmental plasticity and stress adaptation. While recent advances have clarified their roles in abiotic stress tolerance, a systematic integration of their functions in biotic stress responses has yet to be achieved. This review synthesizes current knowledge on how MADS-box TFs …

Impact Of Collodion Thickness On Fission Track Generation Within Lexan Employed For Nuclear Forensic Analyses, Ryan K. Chapman, Zachary P. Meisel, Abigail A. Bickley

Faculty Publications

We report results from a computational study of fission track damage within a Lexan substrate caused by ²³⁵U suspended within a collodion film of varied thickness. MCNP6.3 was used to model energy deposition and displacements per atom within a Lexan film coated by a film of collodion, located within the air-filled 6 inch dry tube of a TRIGA reactor. The collodion layer was varied between 20 and 100 μm thickness, resulting in an 8.8% difference in energy deposition and 12% difference in displacements-per-atom within the Lexan substrate. These findings indicate that collodion adhesive thickness has a moderate impact on …

Tunable Shock And Vibration Damping In Metal Laser Powder Bed Fusion Components Via Controlled Post-Print Compaction Of Particle Damper Cavities, Joud N. Stame, Yanzhou Fu, Samuel Roberts, Austin Downey, Tianyu Zhang, Lang Yuan, Daniel Kiracofe

Faculty Publications

Components manufactured by Laser Powder Bed Fusion (LPBF) can incorporate particle dampers (PDS) by retaining unfused powder within internal pockets, providing inherent vibration suppression without added mass or separate damping components. This study investigates the damping performance of such LPBF-integrated PDs through two complementary approaches: (1) quantifying the effect of post-printing volume compression on energy absorption by mechanically indenting the damper pocket, and (2) evaluating how variations in particle packing density influence the dynamic response under both sinusoidal and transient impulse excitation. Experimental results from shaker and shock testing demonstrate that increased packing density, whether by compression or tighter confinement, …