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Air Force Institute of Technology

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Articles 241 - 270 of 2678

Full-Text Articles in Physical Sciences and Mathematics

Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas Mar 2022

Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas

Theses and Dissertations

Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …

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Automated Aircraft Visual Inspection With Artificial Data Generation Enabled Deep Learning, Nathan J. Gaul Mar 2022

Automated Aircraft Visual Inspection With Artificial Data Generation Enabled Deep Learning, Nathan J. Gaul

Theses and Dissertations

Aircraft visual inspection, which is essential to daily maintenance of an aircraft, is expensive and time-consuming to perform. Augmenting trained maintenance technicians with automated UAVs to collect and analyze images for aircraft inspection is an active research topic and a potential application of CNNs. Training datasets for niche research topics such as aircraft visual inspection are small and challenging to produce, and the manual process of labeling these datasets often produces subjective annotations. Recently, researchers have produced several successful applications of artificially generated datasets with domain randomization for training CNNs for real-world computer vision problems. The research outlined herein builds …

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A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr. Mar 2022

A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr.

Theses and Dissertations

This thesis is a response to climate threats identified by DoD report on Climate Change in 2019. A critical review of climate change literature related to coastal infrastructure was conducted to synthesize past research and to inform future research. This review intends to inform how climate change may impact infrastructure systems, how those impacts are evaluated, can the investigation be improved, and what can stakeholders learn from the outcomes. The end goal is to find climate change mitigation strategies and adaptation measures, or identify the easiest path to get to that end. The compiled information will inform civilian and military …

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Climate Change Risk To Coastal Airfield Stormwater Systems, Jedidiah R. Langlois Mar 2022

Climate Change Risk To Coastal Airfield Stormwater Systems, Jedidiah R. Langlois

Theses and Dissertations

Climate change is resulting in rising sea levels and increased rainfall, posing new challenges to stormwater management, particularly along coastlines. The airfield stormwater systems of Tyndall Air Force Base discharge directly into an interior bay of the Gulf of Mexico through tidal canals and ditches, creating a risk of system inundation from high tidewater conditions from sea-level rise (SLR). This study explores the performance and consequences of an inundated stormwater system from SLR during rainfall events using the EPA’s Stormwater Management Model (SWMM). One hundred and fifty-three combinations of SLR and return year storms were applied to a model of …

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Natural Infrastructure Alternatives Mitigate Hurricane-Driven Flood Vulnerability: Application To Tyndall Air Force Base, Kiara L. Vance Mar 2022

Natural Infrastructure Alternatives Mitigate Hurricane-Driven Flood Vulnerability: Application To Tyndall Air Force Base, Kiara L. Vance

Theses and Dissertations

Hurricane frequency and magnitude intensification are expected over the remainder of the twenty-first century. Uncertainty in future projections requires that coastal communities approach adaptation decisions with caution. Traditional approaches are costly and inflexible. Soft policy adaptations are largely unenforceable. Hard, natural adaptations have emerged as an opportunity to partially mitigate the growing risk of extreme flooding, without the large investments required for traditional approaches, where natural infrastructure already exists. Existing literature for natural adaptations has not leveraged intensification expectations for hurricane events. This research uses multihazard damage evaluation software and spatial analysis to investigate placement of dredged sediment as a …

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Characterization Of Environmental Conditioning Of Lithium Hydride Using Spectroscopy And Machine Learning, Ryan E. Pinson Mar 2022

Characterization Of Environmental Conditioning Of Lithium Hydride Using Spectroscopy And Machine Learning, Ryan E. Pinson

Theses and Dissertations

Lithium compounds such as lithium hydride (LiH) and anhydrous lithium hydroxide (LiOH) have various applications in industry but are highly reactive when exposed to moisture and CO2. These reactions create new molecular forms, including compounds such as lithium oxide (Li2O), lithium hydroxide monohydrate (LiOH ·H2O), and lithium carbonate (Li2CO3). These new compounds degrade the effectiveness in applications using these compounds. The negative effects induced by new lithium compounds creates a need for the ability to characterize the in-growth of such compounds. To study these in-growths, this work will present environmental …

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Formulation And Characterization Of Fast-Curing Plastic Scintillators With High-Z Loading, Theodore W. Stephens Mar 2022

Formulation And Characterization Of Fast-Curing Plastic Scintillators With High-Z Loading, Theodore W. Stephens

Theses and Dissertations

Development of novel fast-curing plastic scintillators is highly advantageous due to their potential to be manufactured via 3D printing. Several formulations were developed that exhibit enhanced photon sensitivity, producing modest but discernible photopeaks at an incident gamma energy of 122 keV. The photon sensitivity is achieved via bismuth high-Z loading; however, this practice typically results in diminished light yields. Subsequent formulations, which varied the photoinitiator concentration and curing time, demonstrated successful curing with sufficient plastic hardness, reduced purple discoloration, reduced heat buildup during curing, and resulted in less cracking during the curing process, all of which were correlated with lower …

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Burn Probability And Climate Change: A Quantitative Evaluation Of The Temporal Alterations Of Wildfire, David N. Robinson Mar 2022

Burn Probability And Climate Change: A Quantitative Evaluation Of The Temporal Alterations Of Wildfire, David N. Robinson

Theses and Dissertations

The intensity of extreme weather events, specifically wildfires, along the West Coast has slowly grown overtime due to atmospheric changes caused by climate change. The Air Force, though aware of the threat that is wildfire, does not currently have a quantitative way to assess the hazard to base locations. In this paper, burn probability is quantitatively calculated through the geospatial analysis programs to provide a means of assessing wildfire vulnerability. The FlamMap fire simulator generated burn probabilities for Vandenberg Air Force Base using climate data generated by the remote automated weather station on the base to highlight how the burn …

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Directionally Sensitive Gamma Imaging Using Rotating Scatter Masks And Inexpensive, Scintillation Detectors, Christopher S. Charles Mar 2022

Directionally Sensitive Gamma Imaging Using Rotating Scatter Masks And Inexpensive, Scintillation Detectors, Christopher S. Charles

Theses and Dissertations

This work demonstrates the first instantiation of the FitzGerald Rotating Scatter Mask (RSM) as a proof-of-concept for two-dimensional source direction determination using a single, inexpensive, non-cooled scintillator, as well as an alternate mask design for comparison. A large RSM was additively manufactured from low-Z, acrylic like material, and rotated around the ubiquitous standard 3" x 3" NaI(Tl) or NaI(Tl)/CsI(Tl) phoswich detector, set internally to the mask. Smaller versions of the FitzGerald and alternate RSM designs were 3D printed for testing and used in conjunction with a LaBr detector to characterize the RSM system with a size and weight reduction applied. …

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Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch Mar 2022

Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch

Theses and Dissertations

Any Automated Aerial Refueling (AAR) solution requires the quick and precise estimation of the relative position and rotation of the two aircraft involved. This is currently accomplished using stereo vision techniques augmented by Iterative Closest Point (ICP), but requires post-processing to account for environmental factors such as boom occlusion. This paper proposes a monocular solution, combining a custom-trained single-shot object detection Convolutional Neural Network (CNN) and Perspective-n-Point (PnP) estimation to calculate a pose estimate with a single image. This solution is capable of pose estimation at contact point (22m) within 7cm of error and a rate of 10Hz, regardless of …

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Performance Of Heterogeneous Multi-Agent Systems With Applications In Combined Arms, Robert J. Wilson Mar 2022

Performance Of Heterogeneous Multi-Agent Systems With Applications In Combined Arms, Robert J. Wilson

Theses and Dissertations

Multi-agent systems show great potential for solving problems in complex and dynamic domains. Such systems comprise multiple individual entities called agents. Agents possessing the same behavior or physical form are called homogeneous while agents which differ in these respects are termed heterogeneous. The overall behavior of the system emerges from the many interactions of its component agents. Most multi-agent systems research to date focuses on systems of homogeneous agents, but recent work suggests that heterogeneous agents may improve system performance in certain tasks. This research examines the impact of heterogeneity on multi-agent system effectiveness and investigates the application of multi-agent …

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Smoothing Of Convolutional Neural Network Classifications, Glen R. Drumm Mar 2022

Smoothing Of Convolutional Neural Network Classifications, Glen R. Drumm

Theses and Dissertations

Smoothing convolutional neural networks is investigated. When intermittent and random false predictions happen, a technique of average smoothing is applied to smooth out the incorrect predictions. While a simple problem environment shows proof of concept, obstacles remain for applying such a technique to a more operationally complex problem.

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Obsolescence: Evaluating An Educational Serious Game On Artificial Intelligence Impacts To Military Strategic Goals, Timothy C. Kokotajlo Mar 2022

Obsolescence: Evaluating An Educational Serious Game On Artificial Intelligence Impacts To Military Strategic Goals, Timothy C. Kokotajlo

Theses and Dissertations

Artificial Intelligence (AI) threatens to bring significant disruption to all aspects of military operations. This research develops a Serious Game (SG) and assessment methodology to provide education on the mindsets required for engaging with disruptive AI technologies. The game, Obsolescence, teaches strategic-level concepts recommended to the Department of Defense (DoD) from a compilation of reports on the current and future state of AI and warfighting. The methodology for assessing the educational value of Obsolescence addresses common challenges such as subjective reporting, control groups, population sizes, and measuring abstract or high levels of learning. The games proposed educational value is tested …

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Coupled Orbit-Attitude Dynamics And Control Of A Cubesat Equipped With A Robotic Manipulator, Charles M. Carr Mar 2022

Coupled Orbit-Attitude Dynamics And Control Of A Cubesat Equipped With A Robotic Manipulator, Charles M. Carr

Theses and Dissertations

This research investigates the utility and expected performance of a robotic servicing CubeSat. The coupled orbit-attitude dynamics of a 6U CubeSat equipped with a four-link serial manipulator are derived. A proportional-integral-derivative controller is implemented to guide the robot through a series of orbital scenarios, including rendezvous and docking following ejection from a chief spacecraft, repositioning the end effector to a desired location, and tracing a desired path with the end effector. Various techniques involving path planning and inverse differential kinematics are leveraged. Simulation results are presented and performance metrics such as settling time, state errors, control use, and system robustness …

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Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Joshua Larson, Clark N. Taylor, Thomas Wischgoll Feb 2022

Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Joshua Larson, Clark N. Taylor, Thomas Wischgoll

Faculty Publications

Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding the nearest neighbor of a point in a reference 3D point set is a common operation in ICP and frequently consumes at least 90% of the computation time. We introduce a novel approach to performing the distance-based nearest neighbor step based on Delaunay triangulation. This greedy algorithm finds the nearest neighbor of a query point by traversing the edges of the Delaunay triangulation created from a reference 3D point set. Our work integrates the Delaunay traversal into the correspondences search of …

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Utilization And Efficient Computation Of Polarization Factor Q For Fast, Accurate Brdf Modeling, Samuel D. Butler, Michael A. Marciniak Feb 2022

Utilization And Efficient Computation Of Polarization Factor Q For Fast, Accurate Brdf Modeling, Samuel D. Butler, Michael A. Marciniak

Faculty Publications

The Bidirectional Reflectance Distribution Function (BRDF) is of substantial use in remote sensing, scene generation, and computer graphics, to describe optical scatter off realistic surfaces. This paper begins by summarizing our prior work in relating wave optics and geometric optics models, culminating with the Modified Cook-Torrance (MCT) model. The MCT model is evaluated here against aluminum, Infragold, and silver paint at various wavelengths in the IR. In each case, the MCT model is shown to outperform a standard microfacet model. Then, this paper shows a non-trivial method of computing the primary new term, the polarization factor Q. This optimization …

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Cu2+ And Cu3+ Acceptors In Β-Ga2O3 Crystals: A Magnetic Resonance And Optical Absorption Study, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway [*], Christopher A. Lenyk, J. Jesenovec, J. S. Mccloy, M. D. Mccluskey, Larry E. Halliburton Feb 2022

Cu2+ And Cu3+ Acceptors In Β-Ga2O3 Crystals: A Magnetic Resonance And Optical Absorption Study, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway [*], Christopher A. Lenyk, J. Jesenovec, J. S. Mccloy, M. D. Mccluskey, Larry E. Halliburton

Faculty Publications

Electron paramagnetic resonance (EPR) and optical absorption are used to characterize Cu2+ (3d9) and Cu3+ (3d8) ions in Cu-doped β-Ga2O3. These Cu ions are singly ionized acceptors and neutral acceptors, respectively (in semiconductor notation, they are Cu− and Cu0 acceptors). Two distinct Cu2+ EPR spectra are observed in the as-grown crystals. We refer to them as Cu2+(A) and Cu2+(B). Spin-Hamiltonian parameters (a g matrix and a 63,65Cu hyperfine matrix) are obtained from the angular dependence of each spectrum. Additional electron-nuclear double resonance …

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A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons Jan 2022

A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

Sporadic-E (Es) occurrence rates from Global Position Satellite radio occultation (GPS-RO) measurements have shown to vary by a factor of five between studies, motivating the need for a comparison with ground-based measurements. In an attempt to find accurate GPS-RO techniques for detecting Es formation, occurrence rates derived using five previously developed GPS-RO techniques are compared to ionosonde measurements over an eight-year period from 2010–2017. GPS-RO measurements within 170 km of a ionosonde site are used to calculate Es occurrence rates and compared to the ground-truth ionosonde measurements. The techniques are compared individually for each ionosonde site …

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Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor Jan 2022

Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor

Faculty Publications

This paper presents a method to estimate the covariances of the inputs in a factor-graph formulation for localization under non-line-of-sight conditions. A general solution based on covariance estimation and M-estimators in linear regression problems, is presented that is shown to give unbiased estimators of multiple variances and are robust against outliers. An iteratively re-weighted least squares algorithm is proposed to jointly compute the proposed variance estimators and the state estimates for the nonlinear factor graph optimization. The efficacy of the method is illustrated in a simulation study using a robot localization problem under various process and measurement models and measurement …

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Development Of Advanced Machine Learning Models For Analysis Of Plutonium Surrogate Optical Emission Spectra, Ashwin P. Rao, Phillip R. Jenkins, John D. Auxier Ii, Michael B. Shattan, Anil Patnaik Jan 2022

Development Of Advanced Machine Learning Models For Analysis Of Plutonium Surrogate Optical Emission Spectra, Ashwin P. Rao, Phillip R. Jenkins, John D. Auxier Ii, Michael B. Shattan, Anil Patnaik

Faculty Publications

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of …

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Electromagnetic Multi–Gaussian Speckle, Milo W. Hyde Iv, Olga Korotkova Jan 2022

Electromagnetic Multi–Gaussian Speckle, Milo W. Hyde Iv, Olga Korotkova

Faculty Publications

Generalizing our prior work on scalar multi-Gaussian (MG) distributed optical fields, we introduce the two-dimensional instantaneous electric-field vector whose components are jointly MG distributed. We then derive the single-point Stokes parameter probability density functions (PDFs) of MG-distributed light having an arbitrary degree and state of polarization. We show, in particular, that the intensity contrast of such a field can be tuned to values smaller or larger than unity. We validate our analysis by generating an example partially polarized MG field with a specified single-point polarization matrix using two different Monte Carlo simulation methods. We then compute the joint PDFs of …

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Effect Of Trigonometric Transformations On The Machine Learning Prediction And Quality Control Of Air Temperature, Andrea Fenoglio [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals Jan 2022

Effect Of Trigonometric Transformations On The Machine Learning Prediction And Quality Control Of Air Temperature, Andrea Fenoglio [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Conducting effective quality control of weather observations in real time is vital to the 14th Weather Squadron’s mission of providing authoritative climate data. This study explored automated quality control of weather observations by applying multiple machine learning techniques to 43,487 surface weather observations from 5 years of data at a single location. Temperature predictors were evaluated using recursive feature elimination on linear regression and XGBoost algorithms, as well as using a neural network hyperparameter sweep. Modeling was repeated after calculating trigonometric transforms of temporal variables to give the models insight into the diurnal heating cycle of the Earth. All models …

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Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals Jan 2022

Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

The majority of cyber infiltration & exfiltration intrusions leave a network footprint, and due to the multi-faceted nature of detecting network intrusions, it is often difficult to detect. In this work a Zeek-processed PCAP dataset containing the metadata of 36,667 network packets was modeled with several machine learning algorithms to classify normal vs. anomalous network activity. Principal component analysis with a 10% contamination factor was used to identify anomalous behavior. Models were created using recursive feature elimination on logistic regression and XGBClassifier algorithms, and also using Bayesian and bandit optimization of neural network hyperparameters. These models were trained on a …

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Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals Jan 2022

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

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Studying The Conditions For Magnetic Reconnection In Solar Flares With And Without Precursor Flares, Seth H. Garland, Daniel J. Emmons, Robert D. Loper Jan 2022

Studying The Conditions For Magnetic Reconnection In Solar Flares With And Without Precursor Flares, Seth H. Garland, Daniel J. Emmons, Robert D. Loper

Faculty Publications

Forecasting of solar flares remains a challenge due to the limited understanding of the triggering mechanisms associated with magnetic reconnection, the primary physical phenomenon connected to these events. Studies have indicated that changes to the photospheric magnetic fields associated with magnetic reconnection – particularly in relation to the field helicity – occur during solar flare events. This study utilized data from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI) and SpaceWeather HMI Active Region Patches (SHARPs) to analyze full vector-field component data of the photospheric magnetic field during solar flare events within a near decade long HMI dataset. …

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Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith Dec 2021

Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith

AFIT Patents

A passive microscopic Fabry-Pérot Interferometer (FPI) sensor an optical fiber a three-dimensional microscopic optical structure formed on a cleaved tip of an optical fighter that reflects a light signal back through the optical fiber. The reflected light is altered by refractive index changes in the three-dimensional structure that is subject to at least one of: (i) thermal radiation; and (ii) volatile organic compounds.

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Extending The Quality Of Secure Service Model To Multi-Hop Networks, Paul M. Simon, Scott R. Graham Dec 2021

Extending The Quality Of Secure Service Model To Multi-Hop Networks, Paul M. Simon, Scott R. Graham

Faculty Publications

Rarely are communications networks point-to-point. In most cases, transceiver relay stations exist between transmitter and receiver end-points. These relay stations, while essential for controlling cost and adding flexibility to network architectures, reduce the overall security of the respective network. In an effort to quantify that reduction, we extend the Quality of Secure Service (QoSS) model to these complex networks, specifically multi-hop networks. In this approach, the quantification of security is based upon probabilities that adversarial listeners and disruptors gain access to or manipulate transmitted data on one or more of these multi-hop channels. Message fragmentation and duplication across available channels …

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Comparison Of Seasonal Foes And Fbes Occurrence Rates Derived From Global Digisonde Measurements, Dawn K. Merriman, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons Ii Dec 2021

Comparison Of Seasonal Foes And Fbes Occurrence Rates Derived From Global Digisonde Measurements, Dawn K. Merriman, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons Ii

Faculty Publications

A global climatology of sporadic-E occurrence rates (ORs) based on ionosonde measurements is presented for the peak blanketing frequency, fbEs, and the ordinary mode peak frequency of the layer, foEs. ORs are calculated for a variety of sporadic-E frequency thresholds: no lower limit, 3, 5, and 7 MHz. Seasonal rates are calculated from 64 Digisonde sites during the period 2006–2020 using ionograms either manually or automatically scaled with ARTIST-5. Both foEs and fbEs ORs peak in the Northern Hemisphere during the boreal summer, with a decrease by roughly a factor of 2–3 in fbEs rates relative to foEs rates without …

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Characterization Of The Gut Microbiota Among Veterans With Unique Military-Related Exposures And High Prevalence Of Chronic Health Conditions: A United States-Veteran Microbiome Project (Us-Vmp) Study, Maggie A. Stanislawski, Christopher E. Stamper, Kelly A. Stearns-Yoder, Andrew J. Hoisington, Diana P. Brostow, Jeri E. Forster, Teodor T. Postolache, Christopher A. Lowry, Lisa A. Brenner Dec 2021

Characterization Of The Gut Microbiota Among Veterans With Unique Military-Related Exposures And High Prevalence Of Chronic Health Conditions: A United States-Veteran Microbiome Project (Us-Vmp) Study, Maggie A. Stanislawski, Christopher E. Stamper, Kelly A. Stearns-Yoder, Andrew J. Hoisington, Diana P. Brostow, Jeri E. Forster, Teodor T. Postolache, Christopher A. Lowry, Lisa A. Brenner

Faculty Publications

The gut microbiome is impacted by environmental exposures and has been implicated in many physical and mental health conditions, including anxiety disorders, affective disorders, and trauma- and stressor-related disorders such as posttraumatic stress disorder (PTSD). United States (US) military Veterans are a unique population in that their military-related exposures can have consequences for both physical and mental health, but the gut microbiome of this population has been understudied. In this publication, we describe exposures, health conditions, and medication use of Veterans in the US Veteran Microbiome Project (US-VMP) and examine the associations between these characteristics and the gut microbiota. This …

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Development Of A Magnetic Confinement Attachment For Enhanced Signal In Handheld Laser Induced Breakdown Spectroscopy Soil Analysis, Alfred C. Anderson Dec 2021

Development Of A Magnetic Confinement Attachment For Enhanced Signal In Handheld Laser Induced Breakdown Spectroscopy Soil Analysis, Alfred C. Anderson

Theses and Dissertations

Field techniques for characterizing low levels of heavy elements of less than 100 parts per million in soils tend to be unreliable because of the relatively weak signal of these elements and the large, variable background inherent to analyzing soils with minimal sample preparation. To enhance the detection and analysis capability of a handheld laser-induced breakdown spectroscopy (LIBS) instrument, this work investigates the effects of a unique magnetic confinement apparatus on signal intensities, focusing on five iron lines as well as those from actinides in 11 soil samples. The proposed magnetic confinement apparatus achieved over 0.8 T but did not …

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