Physical Sciences and Mathematics Commons^™

Deconstructing The Software Factory: A Practical Application Of Interorganizational Network Analysis, Zachary O. Ryan, Mark Reith, Clay Koschnick

Faculty Publications

Over the past 5 years, the number of DoD software organizations that employ nontraditional organizational structures has increased. These organizations, commonly referred to as software factories, often employ the network-based organizational structures found within high-technology industries. This article details ways in which network analysis techniques can be used to create a big picture view of these nontraditional organizations. Drawing on methodologies employed by network researchers, the authors develop and present an interorganizational analysis process that highlights a program's social and economic structures. Following the case history approach, they demonstrate the applicability of this approach by analyzing an emergent DoD software …

Geographic Differences In The Magnitude Of Black-White Disparities In Having Obesity, Steven A. Cohen, Monique J. Brown, Furong Xu, Caitlin C. Nash, Mary L. Greaney

Faculty Publications

Background

Obesity disparities in the United States are well documented, but the limited body of research suggests that geographic factors may alter the magnitude of these disparities. A growing body of evidence has identified a “rural mortality penalty” where morbidity and mortality rates are higher in rural than urban areas, even after controlling for other factors. Black-White differences in health and mortality are more pronounced in rural areas than in urban areas.

Objective

Therefore, the purpose of this study was to explore how rural-urban status and region moderate Black-White health disparities in obesity.

Methods

Data were abstracted from the 2012 …

Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken

Faculty Publications

Purpose: Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Design/Methodology/Approach: Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lighting prediction.

Findings: The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

Abstract © Emerald Publishing …

Evaluating A Large Language Model’S Ability To Solve Programming Exercises From An Introductory Bioinformatics Course, Stephen R. Piccolo, Paul Denny, Andrew Luxton-Reilly, Samuel H. Payne, Perry G. Ridge

Faculty Publications

Life scientists frequently write computer code when doing research. Computer programming can aid researchers in performing tasks that are not supported by existing tools. Programming can also help researchers to implement analytical logic in a way that documents their steps and thus enables others to repeat those steps. Many educational resources are available to teach computer programming, but this skill remains challenging for many researchers and students to master. Artificial-intelligence tools like OpenAI’s ChatGPT are able to interpret human-language requests to generate code. Accordingly, we evaluated the extent to which this technology might be used to perform programming tasks described …

Precision E- Beam Polarimetry At An E-E+ B Factory Using Tau-Pair Events, J. P. Lees, V. Poireau, V, Tisserand, E. Grauges, A. Palano, G. Eigen, D. N. Brown, Yu. G. Kolomensky, M. Fritsch, H. Koch, R. Cheaib, C. Hearty, T. S. Mattison, J. A. Mckenna, R. Y. So, V. E. Blinov, A. R. Buzykaev, V. P. Druzhinin, Milind Purohit, Et. Al.

Faculty Publications

We present a new technique, “tau polarimetry,” for measuring the longitudinal beam polarization present in an e⁺e⁻ collider through the analysis of e⁺e⁻ → τ⁺τ⁻ events. By exploiting the sensitivity of τ decay kinematics to the longitudinal polarization of the beams, we demonstrate that the longitudinal polarization can be measured with a 3 per mil systematic uncertainty at the interaction point using a technique that is independent of spin and beam transport modeling. Using 424.2 ± 1.8 fb⁻¹ of BABAR data at √ s = 10.58 GeV, the average longitudinal …

What Is Microbial Dormancy, Mark D. Mcdonald, Carlos Owusu-Ansah, Jared B. Ellenbogen, Zachary D. Malone, Michael P. Ricketts, Steve E. Frolking, Jessica G. Ernakovich, Michael Ibba, Sarah C. Bagby, J. L. Weissman

Faculty Publications

Life can be stressful. One way to deal with stress is to simply wait it out. Microbes do this by entering a state of reduced activity and increased resistance commonly called ‘dormancy’. But what is dormancy? Different scientific disciplines emphasize distinct traits and phenotypic ranges in defining dormancy for their microbial species and system-specific questions of interest. Here, we propose a unified definition of microbial dormancy, using a broad framework to place earlier discipline-specific definitions in a new context. We then discuss how this new definition and framework may improve our ability to investigate dormancy using multi-omics tools. Finally, we …

Comparison Of A Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Densities With Ionosondes And Firi, Dylan J. Shaver, Dong L. Wu, Nimalan Swarnalingam, Anthony L. Franz, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

High-frequency skywave propagation can be heavily impacted by D- and E-region dynamics requiring accurate global measurements to optimize performance. A standard measurement technique is to use ionosondes, but they are unable to measure below 1 MHz and are only available at a limited number of land-locked sites around the globe. In contrast, the Global Navigation Satellite System radio occultation (GNSS-RO) bottom-up method is a new approach specifically designed to generate electron density profiles in the D- and E- region ionosphere. It takes advantage of satellite constellations that currently provide over 20,000 daily measurements and global coverage. In this paper, GNSS-RO …

Ironnetinjector: Weaponizing .Net Dynamic Language Runtime Engines, Anthony J. Rose, Scott R. Graham, Jacob Krasnov

Faculty Publications

As adversaries evolve their Tactics, Techniques, and Procedures (TTPs) to stay ahead of defenders, Microsoft’s .NET Framework emerges as a common component found in the tradecraft of many contemporary Advanced Persistent Threats (APTs), whether through PowerShell or C#. Because of .NET’s ease of use and availability on every recent Windows system, it is at the forefront of modern TTPs and is a primary means of exploitation. This article considers the .NET Dynamic Language Runtime as an attack vector, and how APTs have utilized it for offensive purposes. The technique under scrutiny is Bring Your Own Interpreter (BYOI), which is the …

Speciation Of Elements Via A Sequential Extraction Procedure In Municipal Wastewater Biosolids From Three Rural Wwtp In East Texas (Usa), Kefa K. Onchoke

Faculty Publications

In this data article, the bioavailability of elements in municipal wastewater sludge (also known as biosolids) in samples collected from three treatment plants in East Texas, USA was evaluated. Although detailed speciation of the metals were assessed by using inductively coupled plasma optical spectroscopy (ICP-OES), and were discussed in the research article titled “Evaluating bioavailability of elements in municipal wastewater sludge (Biosolids) from three rural wastewater treatment plants in East Texas (USA) by a sequential extraction procedure” [1], this report presents the absolute raw concentrations and fractionations of the 26 metals from the biosolids (Nacogdoches Wastewater Sludge, Lufkin Wastewater Sludge, …

Utilizing Low-Cost Sensors To Monitor Indoor Air Quality In Mongolian Gers, Callum Flowerday, Jaron C. Hansen, Phil Lundrigan, Christopher Kitras

Faculty Publications

Air quality has important climate and health effects. There is a need, therefore, to monitor air quality both indoors and outdoors. Methods of measuring air quality should be cost-effective if they are to be used widely, and one such method is low-cost sensors (LCS). This study reports on the use of LCSs in Ulaanbataar, Mongolia to measure PM_2.5 concentrations inside yurts or “gers”. Some of these gers were part of a non-government agency (NGO) initiative to improve insulating properties of these housing structures. The goal of the NGO was to decrease particulate emissions inside the gers; a secondary result …

Reply To: Contribution Of Carbon Inputs To Soil Carbon Accumulation Cannot Be Neglected, Feng Tao, Benjamin Z. Houlton, Serita D. Frey, Johannes Lehmann, Stefano Manzoni, Yuanyuan Huang, Lifen Jiang, Umakant Mishra, Bruce A. Hungate, Michael W. I. Schmidt, Markus Reichstein, Nuno Carvalhais, Philippe Ciais, Ying-Ping Wang, Bernhard Ahrens, Gustaf Hugelius, Toby D. Hocking, Xingjie Lu, Zheng Shi, Kostiantyn Viatkin, Ronald Vargas, Yusuf Yigini, Christian Omuto, Ashish A. Malik, Guillermo Peralta, Rosa Cuevas-Corona, Luciano E. Di Paolo, Isabel Luotto, Cuijuan Liao, Yi-Shuang Liang, Vinisa S. Saynes, Xiaomeng Huang, Yiqi Luo

Faculty Publications

In the accompanying Comment1, He et al. argue that the determinant role of microbial carbon use efficiency in global soil organic carbon (SOC) storage shown in Tao et al. (2023)2 was overestimated because carbon inputs were neglected in our data analysis while they suggest that our model-based analysis could be biased and model-dependent. Their argument is based on a different choice of independent variables in the data analysis and a sensitivity analysis of two process-based models other than that used in our study. We agree that both carbon inputs and outputs (as mediated by microbial processes) matter when predicting SOC …

Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte

Faculty Publications

The adoption of whole slide image (WSI) scanners in clinical practice was accelerated by US Food and Drug Administration approval in 2017, which allowed primary pathologic diagnoses to be made on scanned images. Images in the digital domain allow the application of pathology artificial intelligence (AI), including clinical decision support with algorithms performing specific diagnoses.1,2 These algorithms, if trained properly, could go beyond the ability of human observation to detect and quantify features that are not recognizable by human perception.1,3,4

Season, Not Long-Term Warming, Affects The Relationship Between Ecosystem Function And Microbial Diversity, Melissa S. Shinfuku, Luiz A. Domeignoz-Horta, Mallory J. Choudoir, Serita D. Frey, Kristen M. Deangelis

Faculty Publications

Across biomes, soil biodiversity promotes ecosystem functions. However, whether this relationship will be maintained under climate change is uncertain. Here, using two long-term warming experiments, we investigated how warming affects the relationship between ecosystem functions and microbial diversity across seasons, soil horizons, and warming duration. The soils in these warming experiments were heated +5 °C above ambient for 13 or 28 years. We measured seven different ecosystem functions representative of soil carbon cycling, soil nitrogen cycling, or nutrient pools. We also surveyed bacterial and fungal community diversity. We found that the relationship between ecosystem function and bacterial diversity and the …

Thermal Blooming With Laser-Induced Convection: Radial Basis Function Simulation, Benjamin F. Akers, Steven T. Fiorino, Jonah A. Reeger

Faculty Publications

The propagation of a high energy laser through a nearly stagnant absorbing medium is studied. The absorption values and time scale of the problem are such that the laser induces convective heat currents transverse to the beam. These currents couple to the laser via the refractive index, causing time dependent thermal blooming. A numerical method is developed and applied to the model in [ J. Electromagn. Waves Appl. 33, 96 (2019) ], using radial basis functions for spatial differencing, which allows for irregular point spacings and a wide class of geometries. Both the beam and laser-induced fluid dynamics are …

Anomaly Detection In The Molecular Structure Of Gallium Arsenide Using Convolutional Neural Networks, Timothy Roche, Aihua W. Wood, Philip Cho, Chancellor Johnstone

Faculty Publications

This paper concerns the development of a machine learning tool to detect anomalies in the molecular structure of Gallium Arsenide. We employ a combination of a CNN and a PCA reconstruction to create the model, using real images taken with an electron microscope in training and testing. The methodology developed allows for the creation of a defect detection model, without any labeled images of defects being required for training. The model performed well on all tests under the established assumptions, allowing for reliable anomaly detection. To the best of our knowledge, such methods are not currently available in the open …

Core States Of Neutron Stars From Anatomizing Their Scaled Structure Equations, Bao-Jun Cai, Bao-An Li, Zen Zhang

Faculty Publications

Given an Equation of State (EOS) for neutron star (NS) matter, there is a unique mass–radius sequence characterized by a maximum mass MNS max at radius Rmax. We first show analytically that the MNS max and Rmax scale linearly with two different combinations of the NS central pressure Pc and energy densityεc, by dissecting perturbatively the dimension less Tolman–Oppenheimer–Volkoff (TOV) equations governing NS internal variables. The scaling relations are then verified via 87 widely used and rather diverse phenomenological as well as 17 microscopic NS EOSs with/without considering hadron–quark phase transitions and hyperons, by solving numerically the original TOV equations. …

Spectral Broadening Effects On Pulsed-Source Digital Holography, Steven A. Owens, Mark F. Spencer, Glen P. Perram

Faculty Publications

Using a pulsed configuration, a digital-holographic system is setup in the off-axis image plane recording geometry, and spectral broadening via pseudo-random bit sequence is used to degrade the temporal coherence of the master-oscillator laser. The associated effects on the signal-to-noise ratio are then measured in terms of the ambiguity and coherence efficiencies. It is found that the ambiguity efficiency, which is a function of signal-reference pulse overlap, is not affected by the effects of spectral broadening. The coherence efficiency, on the other hand, is affected. As a result, the coherence efficiency, which is a function of effective fringe visibility, is …

Complexity Heliophysics: A [New] System Science That Transcends The Previous Boundaries Of Our Field, Ryan M. Mcgranaghan, Seebany Datta-Barua, Jeffrey Thayer, Joe Borovsky, Jay R. Johnson, Simon Wing, Dan Baker, Massimo Materassi

Faculty Publications

Synopsis

1. The 21st century is the time of complexity. We delineate it and its importance as necessary to solve ‘wicked problems.’

2. Inherently transdisciplinary, trans-scale, and interconnected to living systems, the solution to Heliophysics’ identity crisis and to unlock the next generation of scientific discovery may be to embrace complexity.

3. With the right foresight, direction, and incentive over the next ten years, Heliophysics can become a beacon for how all of society thinks about and does complexity science.

Propagation Of Spatiotemporal Optical Vortex Beams In Linear, Second-Order Dispersive Media, Milo W. Hyde Iv, Miguel A. Porras

Faculty Publications

In this paper, we study the behaviors of spatiotemporal optical vortex (STOV) beams propagating in linear dispersive media. Starting with the Fresnel diffraction integral, we derive a closed-form expression for the STOV field at any propagation distance z in a general second-order dispersive medium. We compare our general result to special cases published in the literature and examine the characteristics of higher-order STOV beams propagating in dispersive materials by varying parameters of the medium and source-plane STOV field. We validate our analysis by comparing theoretical predictions to numerical computations of a higher-order STOV beam propagating through fused silica, where we …

The Emergence Of Convergence, Shana M. Sundstrom, David G. Angeler, Jessica G. Ernakovich, Jorge H. Garcia, Joseph A. Hamm, Orville Huntington, Craig R. Allen

Faculty Publications

Science is increasingly a collaborative pursuit. Although the modern scientific enterprise owes much to individuals working at the core of their field, humanity is increasingly confronted by highly complex problems that require the integration of a variety of disciplinary and methodological expertise. In 2016, the U.S. National Science Foundation launched an initiative prioritizing support for convergence research as a means of “solving vexing research problems, in particular, complex problems focusing on societal needs.” We discuss our understanding of the objectives of convergence research and describe in detail the conditions and processes likely to generate successful convergence research. We use our …

Wave Optics Approach To Solar Cell Brdf Modeling With Experimental Results, Madilynn Compean, Todd V. Small, Milo W. Hyde Iv, Michael Marciniak

Faculty Publications

Light curve analysis is often used to discern information about satellites in geosynchronous orbits. Solar panels, comprising a large part of the satellite’s body, contribute significantly to these light curves. Historically, theoretical bidirectional reflectance distribution functions (BRDFs) have failed to capture key features in the scattered light from solar panels. In recently published work, a new solar cell BRDF was developed by combining specular microfacet and “two-slit” diffraction terms to capture specular and periodic/array scattering, respectively. This BRDF was experimentally motivated and predicted many features of the solar cell scattered irradiance. However, the experiments that informed the BRDF were limited …

A Hybrid Metaheuristic And Computer Vision Approach To Closed-Loop Calibration Of Fused Deposition Modeling 3d Printers, Graig S. Ganitano, Shay V. Wallace, Benji Maruyama, Gilbert L. Peterson

Faculty Publications

Fused deposition modeling (FDM) is one of the most popular additive manufacturing (AM) technologies for reasons including its low cost and versatility. However, like many AM technologies, the FDM process is sensitive to changes in the feedstock material. Utilizing a new feedstock requires a time-consuming trial-and-error process to identify optimal settings for a large number of process parameters. The experience required to efficiently calibrate a printer to a new feedstock acts as a barrier to entry. To enable greater accessibility to non-expert users, this paper presents the first system for autonomous calibration of low-cost FDM 3D printers that demonstrates optimizing …

Hyperspectral Point Cloud Projection For The Semantic Segmentation Of Multimodal Hyperspectral And Lidar Data With Point Convolution-Based Deep Fusion Neural Networks, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

The fusion of dissimilar data modalities in neural networks presents a significant challenge, particularly in the case of multimodal hyperspectral and lidar data. Hyperspectral data, typically represented as images with potentially hundreds of bands, provide a wealth of spectral information, while lidar data, commonly represented as point clouds with millions of unordered points in 3D space, offer structural information. The complementary nature of these data types presents a unique challenge due to their fundamentally different representations requiring distinct processing methods. In this work, we introduce an alternative hyperspectral data representation in the form of a hyperspectral point cloud (HSPC), which …

The Characteristics Of Successful Military It Projects: A Cross-Country Empirical Study, Helene Berg, Jonathan D. Ritschel

Faculty Publications

In the armed forces, successful digitalization is crucial to ensure effective operations. Much of the existing literature on project factors during the planning and execution phases of public IT projects do not focus specifically on military sector projects. Therefore, the paper aims to provide empirical insights into the characteristics of successful military IT projects. Data from such projects in NATO countries and agencies were collected through interviews and project documents. The findings relating to the main variable of interest, “delivery of client benefit,” supported previous findings on IT project performance. Medium-sized projects performed better than small and large projects, and …

Short-Term Responses Of Soil Carbon, Nitrogen, And Microbial Biomass To Cover Crop Mixtures And Monocultures, Igor Alexandre De Souza, Amanda B. Daly, Jorg Schnecker, Nicholas D. Warren, Adalfredo Rocha Lobo Jr., Richard G. Smith, Andre Fonseca Brito, A. Stuart Grandy

Faculty Publications

Increasingly, cover crops are being adopted for the purpose of improving soil health, yet the timescale and magnitude by which living annual cover crops might modify soil chemical and biological aspects of soil health is not well understood. At the same time, there is growing interest among farmers in cover crop mixtures due to perceptions that species-rich cover crop communities will enhance soil health relative to monocultures. In a field experiment in southeast New Hampshire, we investigated how groups of cover crops grown as monocultures and mixtures for specific seasonal niches (winter/spring, summer, and fall) influenced levels of soil nitrogen …

The Sound Of Geological Targets On Mars From The Absolute Intensity Of Laser-Induced Sparks Shock Waves, C. Alvarez-Llamas, J. Laserna, J. Moros, P. Purohit, L. García-Gómez, S. M. Angel Ph.D., P. Bernardi, B. Bousquet, A. Cadu, E. Dauson, O. Forni, T. Fouchet, O. Gasnault, X. Jacob, G. Lacombe, N. L. Lanza, C. Larmat, J. Lasue, R. D. Lorenz, P. Y. Meslin, D. Mimoun, F. Montmessin, N. Murdoch, A. M. Ollila, P. Pilleri, N. Randazzo, A. L. Reyes-Newell, S. Schröder, A. Stott, J. Ten Cate, A. Udry, D. Vogt

Faculty Publications

Inspection of geological material is one of the main goals of the Perseverance rover during its journey across the landscape of the Jezero crater in Mars. NASA's rover integrates SuperCam, an instrument capable of performing standoff characterization of samples using a variety of techniques. Among those tools, SuperCam can perform laser-induced breakdown spectroscopy (LIBS) studies to elucidate the chemical composition of the targets of interest. Data from optical spectroscopy can be supplemented by simultaneously-produced laser-produced plasma acoustics in order to expand the information acquired from the probed rocks thanks to the SuperCam's microphone (MIC) as it can be synchronized with …

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl

Faculty Publications

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …

Cost Estimation Trends For Major Defense Acquisition Programs, Sammantha Jones, Edward D. White, Jonathan D. Ritschel, Shawn M. Valentine

Faculty Publications

The authors use both descriptive and inferential techniques to investigate average and standard deviation trends in cost estimates for major defense acquisition programs (MDAPs) grouped into decades from the 1970s to 2010s. For total program-cost-growth factors (CGFs), the 2010s exhibited lower CGFs compared to the 1990s. For the program-acquisition-unit cost (PAUC) CGFs, the 2010s appear lower than the 1990s and borderline lower than the 1970s. A statistically significant decreasing trend in the standard deviations of total program CGFs throughout the decades was identified. This lowering variability trend also appeared for PAUC CGFs from the 1980s onward. This finding appears to …

Scalable Preparation Of The Masked Acyl Cyanide Tbs-Mac, Haley Hinton, Jack Patterson, Jared Hume, Krunal Patel, Julie Pigza

Faculty Publications

This paper describes the three-step synthesis of TBS-MAC, a masked acyl cyanide (MAC) and a versatile one-carbon oxidation state three synthon. We have developed a scalable and detailed synthesis that involves: (1) acetylation of malononitrile to form the sodium enolate, (2) protonation of the enolate to form acetylmalononitrile, and (3) epoxidation of the enol, rearrangement to an unstable alcohol, and TBS-protection to form the title compound. Both the sodium enolate and acetylmalononitrile are bench-stable precursors to the intermediate hydroxymalononitrile, which can be converted to other MAC reagents beyond TBS by varying the protecting group (Ac, MOM, EE, etc.).

A Comparison Of Quaternion Neural Network Backpropagation Algorithms, Jeremiah Bill, Bruce A. Cox, Lance Champaign

Faculty Publications

This research paper focuses on quaternion neural networks (QNNs) - a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. Previous studies have shown that QNNs outperform real-valued neural networks in basic tasks and have potential in high-dimensional problem spaces. However, research on QNNs has been fragmented, with contributions from different mathematical and engineering domains leading to unintentional overlap in QNN literature. This work aims to unify existing research by evaluating four distinct QNN backpropagation algorithms, including the novel GHR-calculus backpropagation algorithm, and providing concise, scalable implementations of each algorithm using a …