Digital Commons Network^™

Probiotic Characteristics Of Streptococcus Thermophilus And Lactobacillus Bulgaricus As Influenced By New Food Sources, Ashly Castro, Ricardo S. Aleman, Miguel Tabora, Shirin Kazemzadeh, Leyla K. Pournaki, Roberto Cedillos, Jhunior Marcia, Kayanush Aryana

Faculty Publications

The current research aimed to evaluate the potential effects of Solanum mammosum, Dioon mejiae, and Amanita caesarea on Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus survival and performance after exposure to different harsh conditions such as bile, acid, gastric juice, and lysozyme to mimic the digestive system from mouth to the intestine. Probiotic protease activity was observed to evaluate the proteolytic system. Probiotics were cultured in a broth mixed with plant material, and after incubation, the results were compared to the control sample. Therefore, plant material’s total phenolic compound, total carotenoid compound, antioxidant activity, sugar profile, and acid profile were …

Effects Of Weevil (Rhynchophorus Palmarum), Teosinte (Dioon Mejiae) And Caesar’S Mushroom (Amanita Caesarea) On The Properties Of Lactobacillus Acidophilus La-K, Ricardo S. Aleman, Dany Avila, Allan Avila, Jhunior Marcia, David Picha, Kayanush Aryana, Ismael Montero-Fernández

Faculty Publications

Weevil (Rhynchophorus palmarum) powder, teosinte (Dioon mejiae) and Caesar’s mushroom (Amanita caesarea) flour have bioactive compounds with significant nutritional applications. This paper aimed to examine the influence of weevil, teosinte, and mushroom powders on the protease activity, acid tolerance, bile tolerance, lysozyme tolerance, and gastric juice resistance ability of Lactobacillus acidophilus LA-K. Acid tolerance was determined by adjusting the pH of MRS broth to 2.0 for L. acidophilus incubated under aerobic conditions at 37 °C. Bile tolerance was determined by incorporating 0.3% of oxgall. Protease activity was determined spectrophotometrically at 340 nm. Resistance to 100 mg/L of lysozyme in an …

Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—I: Underlying Motivation And Current Methods, Dan Gabriel Cacuci

Faculty Publications

The mathematical/computational model of a physical system comprises parameters and independent and dependent variables. Since the physical system is seldom known precisely and since the model’s parameters stem from experimental procedures that are also subject to uncertainties, the results predicted by a computational model are imperfect. Quantifying the reliability and accuracy of results produced by a model (called “model responses”) requires the availability of sensitivities (i.e., functional partial derivatives) of model responses with respect to model parameters. This work reviews the basic motivations for computing high-order sensitivities and illustrates their importance by means of an OECD/NEA reactor physics benchmark, which …

Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—Ii: Introducing The Second-Order Adjoint Sensitivity Analysis Methodology For Computing Response Sensitivities To Functions/Features Of Parameters, Dan Gabriel Cacuci

Faculty Publications

This work introduces a new methodology, which generalizes the extant second-order adjoint sensitivity analysis methodology for computing sensitivities of model responses to primary model parameters. This new methodology enables the computation, with unparalleled efficiency, of second-order sensitivities of responses to functions of uncertain model parameters, including uncertain boundaries and internal interfaces, for linear and/or nonlinear models. Such functions of primary model parameters customarily describe characteristic “features” of the system under consideration, including correlations modeling material properties, flow regimes, etc. The number of such “feature” functions is considerably smaller than the total number of primary model parameters. By enabling the computations …

Meta Echo: Using All-Payers Claims Data Analysis As Part Of A Multi-Layered Approach To Plan An Evaluate Echo Programs, Marcy Doyle, Erica Plante

Faculty Publications

No abstract provided.

Cybercompetitions: A Survey Of Competitions, Tools, And Systems To Support Cybersecurity Education, Tyler Balon, Ibrahim (Abe) Baggili

Faculty Publications

Over the last decade, industry and academia have worked towards raising students’ interests in cybersecurity through game-like competitions to fill a shortfall of cybersecurity professionals. Rising interest in video games in combination with gamification techniques make learning fun, easy, and addictive. It is crucial that cybersecurity curricula enhance and expose cybersecurity education to a diversified student body to meet workforce demands. Gamification through cybercompetitions is one method to achieve that. With a vast list of options for competition type, focus areas, learning outcomes, and participant experience levels we need to systematize knowledge of attributes that ameliorate cybercompetitions. In the wake …

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 …

Reinvigorating Engineered Noise Controls: A Systems Approach, Jeremy Slagley, Adam Dudarewicz, Pawlaczyk-Łuszczyńska Małgorzata, Francis Slagley

Faculty Publications

Excerpt: Hearing loss is a major worldwide health issue affecting an estimated 1.5 billion people. Causes of hearing loss include genetics, chemicals, medications, lifestyle habits such as smoking, and noise. Noise is probably the largest contributing factor for hearing loss. Noise arises from the workplace, ambient environment, and leisure activities. The easiest noise sources to control are workplace and environmental. Workplace noise is unique in that the employer is responsible for the noise and the worker. Also, workers may be exposed to much higher levels of noise than they would accept elsewhere. Employers follow the traditional hierarchy of controls (substitution/engineering, …

Dose–Response Of Creatine Supplementation On Cognitive Function In Healthy Young Adults, Terence Moriarty, Kelsey Bourbeau, Katie Dorman, Lance Runyon, Noah Glaser, Jenna Brandt, Mallory Hoodjer, Scott C. Forbes, Darren G. Candow

Faculty Publications

To determine if creatine (Cr) supplementation could influence cognitive performance and whether any changes were related to changes in prefrontal cortex (PFC) activation during such cognitive tasks, thirty (M = 11, F = 19) participants were evenly randomized to receive supplementation with Cr (CR10:10 g/day or CR20:20 g/day) or a placebo (PLA:10 g/day) for 6 weeks. Participants completed a cognitive test battery (processing speed, episodic memory, and attention) on two separate occasions prior to and following supplementation. Functional near-infrared spectroscopy (fNIRS) was used to measure PFC oxyhemoglobin (O2Hb) during the cognitive evaluation. A two-way repeated measures ANOVA was used to …

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 …

Machine Learning For Low Signal-To-Noise Ratio Detection, Fred Lacy, Angel Ruiz-Reyes, Anthony Brescia

Faculty Publications

Sensor networks collect data that is often contaminated by noise. Therefore, it is often necessary to analyze sensor data to determine if a signal is present. This research project utilizes a machine learning algorithm that is able to detect a signal in the presence of noise. The algorithm incorporates the long short-term memory (LSTM) method to determine the presence or absence of a signal in the midst of white Gaussian noise. This machine learning approach was tested with computer generated data and has an accuracy of at least 98% for signal-to-noise levels greater than -12 dB. Furthermore, this algorithm can …

Simultaneous Multistep Transformer Architecture For Model Predictive Control, Junho Park, Mohammad Reza Babaei, Samuel Arce Munoz, Ashwin N. Venkat, John Hedengren

Faculty Publications

Transformer neural networks have revolutionized natural language processing by effectively addressing the vanishing gradient problem. This study focuses on applying Transformer models to time-series forecasting and customizing them for a simultaneous multistep-ahead prediction model in surrogate model predictive control (MPC). The proposed method showcases improved control performance and computational efficiency compared to LSTM-based MPC and one-step-ahead prediction models using both LSTM and Transformer networks. The study introduces three key contributions: (1) a new MPC system based on a Transformer time-series architecture, (2) a training method enabling multistep-ahead prediction for time-series machine learning models, and (3) validation of the enhanced time …

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 …

Using T He Carbon Atom Method T O Determine Mean Oxidation Number O F Organic Carbons, Pong Kau Yuen, Cheng Man Diana Lau

Faculty Publications

The notion of oxidation number acting as an electron-counting concept is crucial for balancing redox reactions, and for understanding organic and biological redox conversions. Chemical formula methods are widely used for counting oxidation numbers. There are three types of chemical formula methods. They are molecular formula method, structural formula method, and Lewis formula method. Each type has its own rules and procedures, and they are difficult for students to fully understand and remember. In addition, the capability of the molecular formula method to assign mean oxidation number of organic carbons for organic molecules or molecular ions is limited. To overcome …

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 …

On The Evaluation Of Entropy Threshold For Debonding During Crack Prorogation Using Dic Technique, A. Mahmoudi, M. R. Khosravani, M. M. Khonsari, Tamara Reinicke

Faculty Publications

The accumulated entropy at the crack tip of a semi-circular bending (SCB) specimen is investigated to obtain a threshold for material fracture and interatomic debonding. The presented approach uses the experimental data obtained from the Digital Image Correlation (DIC) technique and strain maps superposed to SCB specimens to measure the plastic flow at the crack tip. The Swift strain hardening model is utilized to calculate the stress domain at the crack tip and, consequently, the plastic strain energy and entropy accumulation. Results show that the crack surface propagates when the generated entropy at the crack tip reaches a critical limit. …

On The Injectivity Of Integral Operators Related To The Euler–Poisson–Darboux Equation And Shifted K-Plane Transforms, Boris Rubin

Faculty Publications

We study injectivity of integral operators which map the Cauchy initial data for the Euler–Poisson–Darboux equation to the fixed time measurement of the solution of this equation. These operators generalize the well-known spherical means and are closely related to the shifted k-plane transforms, which assign to functions in L^p(Rⁿ) their mean values over all k-planes at a fixed distance from the given k-planes. Several generalizations, including the Radon transform over strips of fixed width in R² and a similar transform over tubes of fixed diameter in R³ , are considered.

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 Review On Membrane Fouling Prediction Using Artificial Neural Networks (Anns), Waad H. Abuwatfa, Nour Al Sawaftah, Naif Darwish, William G. Pitt, Ghaleb A. Husseini

Faculty Publications

Membrane fouling is a major hurdle to effective pressure-driven membrane processes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO). Fouling refers to the accumulation of particles, organic and inorganic matter, and microbial cells on the membrane’s external and internal surface, which reduces the permeate flux and increases the needed transmembrane pressure. Various factors affect membrane fouling, including feed water quality, membrane characteristics, operating conditions, and cleaning protocols. Several models have been developed to predict membrane fouling in pressure-driven processes. These models can be divided into traditional empirical, mechanistic, and artificial intelligence (AI)-based models. Artificial neural networks …

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 …

Family Experiences Of Engagement In Inclusive Childcare Programs For Toddlers, Julianna Lieb, Audra Classen, Lindsay Wright, Hollie Filce

Faculty Publications

Previous research has explored family engagement experiences and practices in childcare programs. The purpose of this study was to explore family members’ experiences related to their engagement in decision-making processes across various inclusive, toddler childcare programs. Five early educators and eight parents participated in the study. Four parents had a child with a diagnosed disability or developmental delays, were at-risk for developmental delays, and/or received speech, occupational, or physical therapy. Eligible early educators participating in the study taught toddlers (18 to 30 months) in a private, faith-based, or university childcare program. A semi-structured interview style was used to collect family …