Digital Commons Network^™

Alignment Of Optical Backscatter Measurements From The Exports Northeast Pacific Field Deployment, Zachary K. Erickson, Ivona Cetinić, Xiaodong Zhang, Emmanuel Boss, P. Jeremy Werdell, Scott Freeman, Lianbo Hu, Craig Lee, Melissa Omand, Mary Jane Perry

Faculty Publications

Backscattering of light is commonly measured by ocean observing systems, including ships and autonomous platforms, and is used as a proxy for the concentration of water column constituents such as phytoplankton and particulate carbon. Multiple on-going projects involve large numbers of independent measurements of backscatter, as well as other biologically relevant parameters, to understand how biology is changing in time and space throughout the global ocean. Rarely are there sufficient measurements to test how well these instruments are inter-calibrated in real-world deployment conditions. This paper develops a procedure to align multiple independently calibrated backscatter instruments to each other using nearby …

Correlational Networking Guides The Discovery Of Unclustered Lanthipeptide Protease-Encoding Genes, Dan Xue, Ethan Older, Zheng Zhong, Zhou Shang, Nanzhu Chen, Nolan Dittenhauser, Lukuan Hou, Peiyan Cai, Michael D. Walla, Shi-Hui Dong, Xiaoyu Tang, Hexin Chen, Prakash Nagarkatti, Mitzi Nagarkatti, Yong-Xin Li, Jie Li

Faculty Publications

Bacterial natural product biosynthetic genes, canonically clustered, have been increasingly found to rely on hidden enzymes encoded elsewhere in the genome for completion of biosynthesis. The study and application of lanthipeptides are frequently hindered by unclustered protease genes required for final maturation. Here, we establish a global correlation network bridging the gap between lanthipeptide precursors and hidden proteases. Applying our analysis to 161,954 bacterial genomes, we establish 5209 correlations between precursors and hidden proteases, with 91 prioritized. We use network predictions and co-expression analysis to reveal a previously missing protease for the maturation of class I lanthipeptide paenilan. We further …

Developing An Optimized Policy Tree-Based Reservoir Operation Model For High Aswan Dam Reservoir, Nile River, Erfan Goharian, Mohamed Shaltout, Mahdi Erfani, Ahmed Eladawy

Faculty Publications

The impacts of climate change on the Nile River and Grand Ethiopian Renaissance Dam (GERD) along with the increased water demand downstream suggest an urgent need for more efficient management of the reservoir system that is well-informed by accurate modeling and optimization of the reservoir operation. This study provides an updated water balance model for Aswan High Dam Reservoir, which was validated using combined heterogeneous sources of information, including in situ gauge data, bias-corrected reanalyzed data, and remote sensing information. To investigate the future challenges, the spatial distribution of the annual/seasonal Aswan High Dam Reservoir surface air temperature trends over …

Developing An Optimized Policy Tree-Based Reservoir Operation Model For High Aswan Dam Reservoir, Nile River, Erfan Goharian, Mohamed Shaltout, Mahdi Erfani, Ahmed Eladawy

Faculty Publications

The impacts of climate change on the Nile River and Grand Ethiopian Renaissance Dam (GERD) along with the increased water demand downstream suggest an urgent need for more efficient management of the reservoir system that is well-informed by accurate modeling and optimization of the reservoir operation. This study provides an updated water balance model for Aswan High Dam Reservoir, which was validated using combined heterogeneous sources of information, including in situ gauge data, bias-corrected reanalyzed data, and remote sensing information. To investigate the future challenges, the spatial distribution of the annual/seasonal Aswan High Dam Reservoir surface air temperature trends over …

Image Classification Based On Sparse Representation In The Quaternion Wavelet Domain, Long H. Ngo, Nikolay Metodiev Sirakov, Marie Luong, Emmanuel Viennet

Faculty Publications

In this study, we propose a novel sparse representation learning method in the Quaternion Wavelet (QW) domain for multi-class image classification. The proposed method takes advantages from: i) the QW decomposition, which promotes sparsity and provides structural information about the image data while allowing approximate shift-invariance, to extract meaningful features from low-frequency QW subbands, ii) the dimensionality reduction method using Principal Component Analysis (PCA) for reducing the complexity of the problem, and iii) the sparse representation of the generated QW features to efficiently learn and capture the meaningful and compact information of this data. After the QW decomposition, the features …

Maintenance Cost Minimization Models For Offshore Wind Farms: A Systematic And Critical Review, Md Imran Hasan Tusar, Bhaba R. Sarker

Faculty Publications

Feasible and sustainable source of power is a burning question nowadays. The offshore wind farms can be a solution to power generation problem, but it is relatively more expensive. Its installation cost is more than twice of its similar size onshore counterpart. The cost that matters most is the operations and maintenance (O&M) cost. Expensive and sophisticated transfer vehicles as well as highly skilled technicians are needed to conduct O&M activities, which results in a remarkably higher O&M cost for an offshore wind farm project. Few researchers proposed some strategies that could resolve the problem nicely, although there is no …

Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam

Faculty Publications

Lack of instrument sensitivity to low electron density (N_e) concentration makes it difficult to measure sharp N_e vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region N_e from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the …

Accountability As A Key Virtue In Mental Health And Human Flourishing, John R. Peteet, Charlotte Vanoyen-Witvliet, C. Stephen Evans

Faculty Publications

We propose that accountability plays an implicit, important, and relatively unexamined role in psychiatry. People generally think of accountability as a relation in which one party is held accountable by another. In this paper, we examine accountability as a virtue, drawing on philosophy, psychiatry, and psychology to examine what it means to welcome being accountable in an excellent way that promotes flourishing. When people manifest accountability as a virtue, they are both responsive to others they owe a response, and they are responsible for their attitudes and actions in light of these relationships. Psychiatric treatment often aims to correct disordered …

Accountability And Autonomy, Motivation, And Psychiatric Treatment, John R. Peteet, Charlotte Vanoyen-Witvliet, C. Stephen Evans

Faculty Publications

No abstract provided.

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell Us About Aerosol Composition, Meloe S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, Gregory L. Schuster

Faculty Publications

Improvements in air quality and Earth's climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine aerosol composition measurements from ground-based networks are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types …

What Will And Won’T Happen When Abortion Is Banned, Michelle Oberman

Faculty Publications

For the past fifty years, abortion opponents have fought for the power to ban abortion without little attention to how things might change when they won. The battle to make abortion illegal has been predicated on three nebulous assumptions about how abortion bans work. First, supporters believe banning abortion will deter it. Second, they hope bans will send a message about abortion—specifically, that abortion is immoral. And third, they expect bans to be competently implemented and enforced.

Drawing on empirical work from within and outside of the U.S., this Article offers an evidence-based assessment of each of these assumptions. Part …

A Comparison Of Square-Wave Voltammetry Models To Determine The Number Of Electrons Exchanged In Metal Deposition, Ranon Fuller, Tyler Williams, Mark H. Schvaneveldt, Devin Rappleye

Faculty Publications

A comparison of square-wave voltammetry models for calculating the number of electrons exchanged in a metal deposition reaction. Experiments were conducted for silver deposition on platinum in an aqueous HNO₃ solution and for nickel and lanthanum deposition on platinum in molten LiCl. Diffusion coefficients for Ni²⁺ and La³⁺ in LiCl at 700^oC are calculated. Accuracy of soluble-soluble models versus a soluble-insoluble model is discussed. A simple method for determining the number of electrons exchanged under the constraint of well-compensated ohmic drop is proposed and evaluated.

Flood Depth Estimation During Hurricane Harvey Using Sentinel-1 And Uavsar Data, Sananda Kundu, Venkat Lakshmi, Raymond Torres

Faculty Publications

In August 2017, Hurricane Harvey was one of the most destructive storms to make landfall in the Houston area, causing loss of life and property. Temporal and spatial changes in the depth of floodwater and the extent of inundation form an essential part of flood studies. This work estimates the flood extent and depth from LiDAR DEM (light detection and ranging digital elevation model) using data from the Synthetic Aperture Radar (SAR)–Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and satellite sensor—Sentinel-1. The flood extent showed a decrease between 29–30 August and 5 September 2017. The flood depths estimated using the …

A Molecular Dynamics Study Of Monomer Melt Properties Of Cyanate Ester Monomer Melt Properties, Rebecca T. Haber, Andrea R. Browning, Bayleigh R. Graves, William P. Davis, Jeffrey S. Wiggins

Faculty Publications

The objective of this work was to computationally predict the melting temperature and melt properties of thermosetting monomers used in aerospace applications. In this study, we applied an existing voids method by Solca. to examine four cyanate ester monomers with a wide range of melting temperatures. Voids were introduced into some simulations by removal of molecules from lattice positions to lower the free-energy barrier to melting to directly simulate the transition from a stable crystal to amorphous solid and capture the melting temperature. We validated model predictions by comparing melting temperature against previously reported literature values. Additionally, the torsion and …

An Algorithm To Bias-Correct And Transform Arctic Smap-Derived Skin Salinities Into Bulk Surface Salinities, David Trossman, Eric Bayler

Faculty Publications

No abstract provided.

Consistent Gauge-Fixing Conditions In Polymerized Gravitational Systems, Kristina Giesel, Bao Fei Li, Parampreet Singh, Stefan Andreas Weigl

Faculty Publications

For classical gravitational systems the lapse function and the shift vector are usually determined by imposing appropriate gauge-fixing conditions and then demanding their preservation with respect to the dynamics generated by a canonical Hamiltonian. Effective descriptions encoding quantum geometric effects motivated by loop quantum gravity for symmetry-reduced models are often captured by polymerization of connection (or related) variables in gauge-fixing conditions as well as constraints. Usually, one chooses the same form of polymerization in both cases. A pertinent question is if the dynamical stability of the effective gauge-fixing conditions under the effective dynamics generated by the polymerized canonical Hamiltonian is …

Constraints On Dark Photon Dark Matter Using Data From Ligo’S And Virgo’S Third Observing Run, Ligo Scientific Collaboration, Virgo Collaboration, Kagra Collaboration, Tiffany Z. Summerscales

Faculty Publications

We present a search for dark photon dark matter that could couple to gravitational-wave interferometers using data from Advanced LIGO and Virgo’s third observing run. To perform this analysis, we use two methods, one based on cross-correlation of the strain channels in the two nearly aligned LIGO detectors, and one that looks for excess power in the strain channels of the LIGO and Virgo detectors. The excess power method optimizes the Fourier transform coherence time as a function of frequency, to account for the expected signal width due to Doppler modulations. We do not find any evidence of dark photon …

Low Exposure Long-Baseline Neutrino Oscillation Sensitivity Of The Dune Experiment, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monnsalve, M. Alrashed, C. Alt, A. Alton, P. Amedo, J. Anderson, C. Andreopooulos, M. Andreotti, M. P. Andrews, F. Andrianala, S. Andringa, N. Anfimov, Roberto Petti, Sanjib R. Mishra Ph.D., Et. Al.

Faculty Publications

The Deep Underground Neutrino Experiment (DUNE) will produce world-leading neutrino oscillation measurements over the lifetime of the experiment. In this work, we explore DUNE’s sensitivity to observe charge-parity violation (CPV) in the neutrino sector, and to resolve the mass ordering, for exposures of up to 100 kiloton-megawatt-calendar years (kt-MW-CY), where calendar years include an assumption of 57% accelerator uptime based on past accelerator performance at Fermilab. The analysis includes detailed uncertainties on the flux prediction, the neutrino interaction model, and detector effects. We demonstrate that DUNE will be able to unambiguously resolve the neutrino mass ordering at a 4⁢𝜎 (5⁢𝜎) …

Water Circulation Driven By Cold Fronts In The Wax Lake Delta (Louisiana, Usa), Qian Zhang, Chunyan Li, Wei Huang, Jun Lin, Matthew Hiatt, Victor H. Rivera-Monroy

Faculty Publications

No abstract provided.

A Statistical Principal Component Regression-Based Approach To Modeling The Degradative Effects Of Local Climate And Traffic On Airfield Pavement Performance, Evan M. Fortney, Steven J. Schuldt, Sarah L. Brown, James P. Allen, Justin D. Delorit

Faculty Publications

Airfield pavement systems support the global economy, passenger travel, and national defense. Accurate pavement degradation predictions are critical inputs for maintenance and repair decisions, and when skillful, they may reduce the need for time-intensive, costly physical inspections that disrupt airfield operations. Existing airport pavement management systems (APMS) compute expected degradation as a function of pavement type and age, but they do not account for local climate and traffic conditions and they are not built to adapt to future changes in either mode of variability. This paper implements a bias-reduced statistical model that reveals the effects of local conditions using observed …

The Ability To Classify Patients Based On Gene-Expression Data Varies By Algorithm And Performance Metric, Stephen Piccolo, Avery Mecham, Nathan P. Golightly, Jérémie L. Johnson, Dustin B. Miller

Faculty Publications

By classifying patients into subgroups, clinicians can provide more effective care than using a uniform approach for all patients. Such subgroups might include patients with a particular disease subtype, patients with a good (or poor) prognosis, or patients most (or least) likely to respond to a particular therapy. Transcriptomic measurements reflect the downstream effects of genomic and epigenomic variations. However, high-throughput technologies generate thousands of measurements per patient, and complex dependencies exist among genes, so it may be infeasible to classify patients using traditional statistical models. Machine-learning classification algorithms can help with this problem. However, hundreds of classification algorithms exist—and …

Lakshadweep High Propagation And Impacts On The Somali Current And Eddies During The Southwest Monsoon, Paul A. Ernst, Bulusu Subrahmanyam, Corinne B. Trott

Faculty Publications

Climatological eddies in the Arabian Sea (AS), including the Lakshadweep High (LH) and the Great Whirl (GW), play major roles in the regional fluxes of upper ocean properties. For the first time, we apply an eddy tracking algorithm to the LH using altimetric sea surface height observations from 1993 through 2019. We additionally analyze the LH's water mass composition throughout its life cycle using the 1/12° Global eddy resolving physical ocean and sea ice reanalysis (GLORYS12). We observe that the second annual downwelling coastal Kelvin wave's (CKW) arrival during the winter monsoon is primarily responsible for generating the LH. In …

Pemnet: A Transfer Learning-Based Modeling Approach Of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems, Luis A. Briceno-Mena, José A. Romagnoli, Christopher G. Arges

Faculty Publications

Widespread adoption of high-temperature electrochemical systems such as polymer electrolyte membrane fuel cells (HT-PEMFCs) requires models and computational tools for accurate optimization and guiding new materials for enhancing fuel cell performance and durability. While robust and better suited for extrapolation, knowledge-based modeling has limitations as it is time-consuming and requires information about the system that is not always available (e.g., material properties and interfacial behavior between different materials). Data-driven modeling, on the other hand, is easier to implement but often necessitates large datasets that could be difficult to obtain. In this contribution, knowledge-based modeling and data-driven modeling are combined by …

Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple

Faculty Publications

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …

Determinants Of Covid-19 Vaccinations Among A State-Wide Year-Long Surveillance Initiative In A Conservative Southern State, Lídia Gual-Gonzalez, Maggie S.J. Mccarter, Kyndall Dye-Braumuller, Stella Self, Connor H. Ross, Chloe Rodriguez-Ramos, Virginie G. Daguise, Melissa Nolan Ph.D., Mph

Faculty Publications

By the end of 2021, the COVID-19 pandemic resulted in over 54 million cases and more than 800,000 deaths in the United States, and over 350 million cases and more than 5 million deaths worldwide. The uniqueness and gravity of this pandemic have been reflected in the public health guidelines poorly received by a growing subset of the United States population. These poorly received guidelines, including vaccine receipt, are a highly complex psychosocial issue, and have impacted the successful prevention of disease spread. Given the intricate nature of this important barrier, any single statistical analysis methodologically fails to address all …

Cluttering In The Speech Of Young Men With Fragile X Syndrome, Katherine Bangert, Kathleen Scaler Scott, Charley Adams, Jessica S. Kisenwether, Lisa Giuffre, Jenna Reed, Angela John Thurman, Leonard Abbeduto, Jessica Klusek

Faculty Publications

Purpose: Cluttering is a fluency disorder that has been noted clinically in individuals with fragile X syndrome (FXS). Yet, cluttering has not been systematically characterized in this population, hindering identification and intervention efforts. This study examined the rates of cluttering in male young adults with FXS using expert clinical opinion, the alignment between expert clinical opinion and objectively quantified features of cluttering from language transcripts, and the association between cluttering and aspects of the FXS phenotype.

Method: Thirty-six men with FXS (aged 18-26 years; M = 22, SD = 2.35) contributed language samples and completed measures of nonverbal cognition, autism …

Automated Machine Learning: A Case Study Of Genomic “Image-Based” Prediction In Maize Hybrids, Giovanni Galli, Felipe Sabadin, Rafael Massahiro Yassue, Cassia Galves, Humberto Fanelli Carvalho, Jose Crossa, Osval Antonio Montesinos-López, Roberto Fritsche-Neto

Faculty Publications

Machine learning methods such as multilayer perceptrons (MLP) and Convolutional Neural Networks (CNN) have emerged as promising methods for genomic prediction (GP). In this context, we assess the performance of MLP and CNN on regression and classification tasks in a case study with maize hybrids. The genomic information was provided to the MLP as a relationship matrix and to the CNN as “genomic images.” In the regression task, the machine learning models were compared along with GBLUP. Under the classification task, MLP and CNN were compared. In this case, the traits (plant height and grain yield) were discretized in such …

Madfam: Microarchitectural Data Framework And Methodology, Tor J. Langehaug, Scott R. Graham, Christine M. Schubert Kabban, Brett J. Borghetti

Faculty Publications

In the aftermath of Spectre and Meltdown researchers have proposed a variety of attack detection solutions by applying machine learning to data collected from hardware performance monitoring units. Although many microarchitectural attack detection systems provide high-accuracy detection results, the behavior of the underlying data collection mechanisms is not well described or understood. This research introduces the MicroArchitectural Data Framework And Methodology (MADFAM) to prescribe a systematic approach to collecting and preserving the information available in sequences of microarchitectural data. The proposed framework focuses on hardware performance counters (HPCs) as the primary data source. HPC configuration is complex, which makes it …

Spin-Nernst Effect In Time-Reversal-Invariant Topological Superconductors, Taiki Matsushita, Jiei Ando, Yusuke Masaki, Takeshi Mizushima, Satoshi Fujimoto, Ilya Vekhter

Faculty Publications

We investigate the spin-Nernst effect in time-reversal-invariant topological superconductors, and show that it provides smoking-gun evidence for helical Cooper pairs. The spin-Nernst effect stems from asymmetric, in spin space, scattering of quasiparticles at nonmagnetic impurities, and generates a transverse spin current by the temperature gradient. Both the sign and the magnitude of the effect sensitively depend on the scattering phase shift at impurity sites. Therefore the spin-Nernst effect is uniquely suitable for identifying time-reversal-invariant topological superconducting orders.

Search For Lepton Flavor Violation In ϒ(3S) → E±Μ∓, J. P. Lees, V. Tisserand, A. Palano, G. Eigen, D. N. Brown, Yu. G. Kolomensky, M. Fritsch, H. Koch, T. Schroeder, R. Cheaib, C. Hearty, T. S. Mattison, J. A. Mckenna, R. Y. So, V. E. Blinov, A. R. Buzykaev, V. P. Druzhinin, V. B. Golubev, E. A. Kozyrev, Milind Purohit, Jeffery R. Wilson, Et. Al.

Faculty Publications

We report on the first search for electron-muon lepton flavor violation (LFV) in the decay of a b quark and b antiquark bound state. We look for the LFV decay ϒ(3S) → e ^± μ^∓ in a sample of 118 million ϒ(3S) mesons from 27 fb⁻¹ of data collected with the BABAR detector at the SLAC PEP-II e⁺e⁻ collider operating with a 10.36 GeV center-of-mass energy. No evidence for a signal is found, and we set a limit on the branching fraction B[ϒ(3S) → e ^± μ^∓]< 3.6 × 10^{−7 …}