Physical Sciences and Mathematics Commons^™

Influences Of Hillslope Biogeochemistry On Anaerobic Soil Organic Matter Decomposition In A Tundra Watershed, Michael Philben, Neslihan Taş, Hongmei Chen, Stan D. Wullschleger, Alexander Kholodov, David E. Graham, Baohua Gu

Chemistry & Biochemistry Faculty Publications

We investigated rates and controls on greenhouse gas (CO₂ and CH₄) production in two contrasting water‐saturated tundra soils within a permafrost‐affected watershed near Nome, Alaska, United States. Three years of field sample analysis have shown that soil from a fen‐like area in the toeslope of the watershed had higher pH and higher porewater ion concentrations than soil collected from a bog‐like peat plateau at the top of the hillslope. The influence of these contrasting geochemical and topographic environments on CO₂ and CH₄ production was tested in soil microcosms by incubating both the organic‐ and mineral‐layer …

Pyrocumulonimbus Stratospheric Plume Injections Measured By The Ace‐Fts, C.D. Boone, Peter F. Bernath, M. D. Fromm

Chemistry & Biochemistry Faculty Publications

The Atmospheric Chemistry Experiment (ACE) is a satellite‐based mission that probes Earth's atmosphere via solar occultation. The primary instrument on board is a high‐resolution infrared Fourier transform spectrometer (Atmospheric Chemistry Experiment Fourier Transform Spectrometer, ACE‐FTS), providing altitude‐resolved volume mixing ratio measurements for numerous atmospheric constituents, including many biomass burning products. The ACE mission has observed the aftermath of three major pyrocumulonimbus events, in which extreme heat from intense fires created a pathway for directly injecting into the stratosphere plumes of gaseous and aerosol pollutants. These three events were associated with severe Australian bushfires from 2009 and 2019/2020, along with intense …

Topical Review Of Vulnerability Management For Local Hampton Roads Industry, Gregory W. Hubbard Jr., Matthew Eunice

OUR Journal: ODU Undergraduate Research Journal

The progress towards an interconnected digital world offers an exciting level of advancement for humanity. Unfortunately, this “online” connection is not safe from the threats and dangers typically associated with physical operations. With the foundation of Cyber Command of DoD cyberspace, the United States Government is taking a prominent stance in cyberspace operations. Like the federal government, both industries and individuals are not immune and are oftentimes unknowingly at risk to cyberattack. This report hopes to bring awareness to common vulnerabilities in multi-user networks by describing a historical background on cyber security as well as outlining current methods of vulnerability …

Vertical Processes And Resolution Impact Ice Shelf Basal Melting: A Multi-Model Study, David E. Gwyther, Kazuya Kusahara, Xylar S. Asay-Davis, Michael S. Dinniman, Benjamin K. Galton-Fenzi

CCPO Publications

Understanding ice shelf–ocean interaction is fundamental to projecting the Antarctic ice sheet response to a warming climate. Numerical ice shelf–ocean models are a powerful tool for simulating this interaction, yet are limited by inherent model weaknesses and scarce observations, leading to parameterisations that are unverified and unvalidated below ice shelves. We explore how different models simulate ice shelf–ocean interaction using the 2nd Ice Shelf–Ocean Model Intercomparison Project (ISOMIP+) framework. Vertical discretisation and resolution of the ocean model are shown to have a significant effect on ice shelf basal melt rate, through differences in the distribution of meltwater fluxes and the …

Analysis Of Iron Sources In Antarctic Continental Shelf Waters, Michael S. Dinniman, Pierre St-Laurent, Kevin R. Arrigo, Eileen E. Hofmann, Gert L. Van Dijken

CCPO Publications

Previous studies showed that satellite‐derived estimates of chlorophyll a in coastal polynyas over the Antarctic continental shelf are correlated with the basal melt rate of adjacent ice shelves. A 5‐km resolution ocean/sea ice/ice shelf model of the Southern Ocean is used to examine mechanisms that supply the limiting micronutrient iron to Antarctic continental shelf surface waters. Four sources of dissolved iron are simulated with independent tracers, assumptions about the source iron concentration for each tracer, and an idealized summer biological uptake. Iron from ice shelf melt provides about 6% of the total dissolved iron in surface waters. The contribution from …

20th Century Multivariate Indian Ocean Regional Sea Level Reconstruction, Praveen Kumar, Benjamin Hamlington, Se-Hyeon Cheon, Weiqing Han, Phillip Thompson

CCPO Publications

Despite having some of the world's most densely populated and vulnerable coastlines, Indian Ocean sea level variability over the past century is poorly understood relative to other ocean basins primarily, due to the short and sparse observational records. In an attempt to overcome the limitations imposed by the lack of adequate observations, we have produced a 20th century Indian Ocean sea level reconstruction product using a new multivariate reconstruction technique. This technique uses sea level pressure and sea surface temperature in addition to sea level data to help constrain basin‐wide sea level variability by (1) the removal of large spurious …

Residual Control Chart For Binary Response With Multicollinearity Covariates By Neural Network Model, Jong-Min Kim, Ning Wang, Yumin Liu, Kayoung Park

Mathematics & Statistics Faculty Publications

Quality control studies have dealt with symmetrical data having the same shape with respect to left and right. In this research, we propose the residual (r) control chart for binary asymmetrical (non-symmetric) data with multicollinearity between input variables via combining principal component analysis (PCA), functional PCA (FPCA) and the generalized linear model with probit and logit link functions, and neural network regression model. The motivation in this research is that the proposed control chart method can deal with both high-dimensional correlated multivariate data and high frequency functional multivariate data by neural network model and FPCA. We show that the neural …

Investigating The Numerical Stability Of Using An Impedance Boundary Condition To Model Broadband Noise Scattering With Acoustic Liners, Michelle E. Rodio, Fang Q. Hu, Douglas M. Nark

Mathematics & Statistics Faculty Publications

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for achieving aircraft noise reduction and are characterized by a frequency-dependent impedance value. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners. A Broadband Impedance Model will be discussed in which the liner impedance …

Tunable-Focus Liquid Lens Through Charge Injection, Shizhi Qian, Wenxiang Shi, Huai Zheng, Zhaohui Liu

Mechanical & Aerospace Engineering Faculty Publications

Liquid lenses are the simplest and cheapest optical lenses, and various studies have been conducted to develop tunable-focus liquid lenses. In this study, a simple and easily implemented method for achieving tunable-focus liquid lenses was proposed and experimentally validated. In this method, charges induced by a corona discharge in the air were injected into dielectric liquid, resulting in “electropressure” at the interface between the air and the liquid. Through a 3D-printed U-tube structure, a tunable-focus liquid lens was fabricated and tested. Depending on the voltage, the focus of the liquid lens can be adjusted in large ranges (−∞ to −9 …

Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …

Shipbuilding Supply Chain Framework And Digital Transformation: A Project Portfolios Risk Evaluation, Rafael Diaz, Katherine Smith, Rafael Landaeta, Antonio Padovano

VMASC Publications

Program portfolio managers in digital transformation programs have a need for knowledge that can guide decisions related to the alignment of program investments with the sustainability and strategic objectives of the organization. The purpose of this research is to illustrate the utility of a framework capable of clarifying the cost-benefit tradeoffs stemming from assessing digitalization program investment risks in the military shipbuilding sector. Our approach uses Artificial Neural Network to quantify benefits and risks per project while employing scenario analysis to quantify the effects of operational constraints. A Monte Carlo model is used to generate data samples that support the …

Smart Communities: From Sensors To Internet Of Things And To A Marketplace Of Services, Stephan Olariu, Nirwan Ansari (Editor), Andreas Ahrens (Editor), Cesar Benavente-Preces (Editor)

Computer Science Faculty Publications

Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government that seeks to create a sustainable human-centric society by putting to work recent advances in technology: sensor networks, edge computing, IoT ecosystems, AI, Big Data, robotics, to name just a few. The main contribution of this work is a vision of how these technological advances can contribute, directly or indirectly, to making Society 5.0 reality. For this purpose we build on a recently-proposed concept of Marketplace of Services that, in our view, will turn out to be one of the cornerstones of Society 5.0. Instead of …

Smartcitecon: Implicit Citation Context Extraction From Academic Literature Using Unsupervised Learning, Chenrui Gao, Haoran Cui, Li Zhang, Jiamin Wang, Wei Lu, Jian Wu

Computer Science Faculty Publications

We introduce SmartCiteCon (SCC), a Java API for extracting both explicit and implicit citation context from academic literature in English. The tool is built on a Support Vector Machine (SVM) model trained on a set of 7,058 manually annotated citation context sentences, curated from 34,000 papers in the ACL Anthology. The model with 19 features achieves F₁=85.6%. SCC supports PDF, XML, and JSON files out-of-box, provided that they are conformed to certain schemas. The API supports single document processing and batch processing in parallel. It takes about 12–45 seconds on average depending on the format to process a …

Acknowledgement Entity Recognition In Cord-19 Papers, Jian Wu, Pei Wang, Xin Wei, Sarah Rajtmajer, C. Lee Giles, Christopher Griffin

Computer Science Faculty Publications

Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, AckExtract based on open-source text mining software and evaluate our method using manually labeled data. AckExtract uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F₁=0.92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to …

Effect Of User Involvement In Supply Chain Cloud Innovation: A Game Theoretical Model And Analysis, Yun Chen, Lian Duan, Weiyong Zhang

Information Technology & Decision Sciences Faculty Publications

Cloud innovation has become increasingly important to supply chain innovation and performance. User involvement is a crucial part of cloud innovation. However, the effect of user involvement in supply chain cloud innovation has not been thoroughly studied, particularly its effect on product cost and optimal price. In this paper, the authors attempted to bridge this major gap in the literature. The authors reviewed the relevant literature to define cloud innovation and user involvement in supply chain cloud innovation. Then the authors developed a game model based on the Bertrand model. Analysis of the model showed that user involvement affects product …

Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu

Electrical & Computer Engineering Faculty Publications

This paper reports a new side-channel attack to smartphones using the unrestricted magnetic sensor data. We demonstrate that attackers can effectively infer the Apps being used on a smartphone with an accuracy of over 80%, through training a deep Convolutional Neural Networks (CNN). Various signal processing strategies have been studied for feature extractions, including a tempogram based scheme. Moreover, by further exploiting the unrestricted motion sensor to cluster magnetometer data, the sniffing accuracy can increase to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only …

Gold/Qds-Embedded-Ceria Nanoparticles: Optical Fluorescence Enhancement As A Quenching Sensor, Nader Shehata, Effat Samir, Ishac Kandas

Electrical & Computer Engineering Faculty Publications

This work focuses on improving the fluorescence intensity of cerium oxide (ceria) nanoparticles (NPs) through added plasmonic nanostructures. Ceria nanoparticles are fluorescent nanostructures which can emit visible fluorescence emissions under violet excitation. Here, we investigated different added plasmonic nanostructures, such as gold nanoparticles (Au NPs) and Cadmium sulfide/selenide quantum dots (CdS/CdSe QDs), to check the enhancement of fluorescence intensity emissions caused by ceria NPs. Different plasmonic resonances of both aforementioned nanostructures have been selected to develop optical coupling with both fluorescence excitation and emission wavelengths of ceria. In addition, different additions whether in-situ or post-synthesis have been investigated. We found …

Opening Books And The National Corpus Of Graduate Research, William A. Ingram, Edward A. Fox, Jian Wu

Computer Science Faculty Publications

Virginia Tech University Libraries, in collaboration with Virginia Tech Department of Computer Science and Old Dominion University Department of Computer Science, request $505,214 in grant funding for a 3-year project, the goal of which is to bring computational access to book-length documents, demonstrating that with Electronic Theses and Dissertations (ETDs). The project is motivated by the following library and community needs. (1) Despite huge volumes of book-length documents in digital libraries, there is a lack of models offering effective and efficient computational access to these long documents. (2) Nationwide open access services for ETDs generally function at the metadata level. …

Mementoembed And Raintale For Web Archive Storytelling, Shawn M. Jones, Martin Klein, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

For traditional library collections, archivists can select a representative sample from a collection and display it in a featured physical or digital library space. Web archive collections may consist of thousands of archived pages, or mementos. How should an archivist display this sample to drive visitors to their collection? Search engines and social media platforms often represent web pages as cards consisting of text snippets, titles, and images. Web storytelling is a popular method for grouping these cards in order to summarize a topic. Unfortunately, social media platforms are not archive-aware and fail to consistently create a good experience for …

Rotate-And-Press: A Non-Visual Alternative To Point-And-Click, Hae-Na Lee, Vikas Ashok, I. V. Ramakrishnan

Computer Science Faculty Publications

Most computer applications manifest visually rich and dense graphical user interfaces (GUIs) that are primarily tailored for an easy-and-efficient sighted interaction using a combination of two default input modalities, namely the keyboard and the mouse/touchpad. However, blind screen-reader users predominantly rely only on keyboard, and therefore struggle to interact with these applications, since it is both arduous and tedious to perform the visual 'point-and-click' tasks such as accessing the various application commands/features using just keyboard shortcuts supported by screen readers.

In this paper, we investigate the suitability of a 'rotate-and-press' input modality as an effective non-visual substitute for the visual …

Outlier Profiles Of Atomic Structures Derived From X-Ray Crystallography And From Cryo-Electron Microscopy, Lin Chen, Jing He, Angelo Facchiano

Computer Science Faculty Publications

Background: As more protein atomic structures are determined from cryo-electron microscopy (cryo-EM) density maps, validation of such structures is an important task. Methods: We applied a histogram-based outlier score (HBOS) to six sets of cryo-EM atomic structures and five sets of X-ray atomic structures, including one derived from X-ray data with better than 1.5 Å resolution. Cryo-EM data sets contain structures released by December 2016 and those released between 2017 and 2019, derived from resolution ranges 0–4 Å and 4–6 Å respectively. Results: The distribution of HBOS values in five sets of X-ray structures show that HBOS is sensitive distinguishing …

Psu At Clef-2020 Arqmath Track: Unsupervised Re-Ranking Using Pretraining, Shaurya Rohatgi, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

This paper elaborates on our submission to the ARQMath track at CLEF 2020. Our primary run for the main Task-1: Question Answering uses a two-stage retrieval technique in which the first stage is a fusion of traditional BM25 scoring and tf-idf with cosine similarity-based retrieval while the second stage is a finer re-ranking technique using contextualized embeddings. For the re-ranking we use a pre-trained robertabase model (110 million parameters) to make the language model more math-aware. Our approach achieves a higher NDCG0 score than the baseline, while our MAP and P@10 scores are competitive, performing better than the best submission …

Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through five passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level rf system configured such that a cavity fault triggers waveform recordings of 17 rf signals for each of the eight cavities in the cryomodule. Subject matter experts are able to analyze the collected time-series data and identify which of the …

Abiotic Formation Of Dissolved Organic Sulfur In Anoxic Sediments Of Santa Barbara Basin, Hussain A. Abdulla, David J. Burdige, Tomoko Komada

OES Faculty Publications

Sulfurization has been found to enhance organic matter preservation and petroleum formation in marine sediments. However, we do not yet have a comprehensive understanding of sulfurization mechanisms. In this study, we investigated several possible mechanisms of dissolved organic sulfur (DOS) formation in the top 4.5 m of anoxic sediments of Santa Barbara Basin (SBB), California Borderland. Using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS), we identified chemical formulas of potential dissolved organic matter (DOM) precursors to these DOS compounds. We also examined how the formulas of abiotically formed DOS changed as a function of depth across a major redox …

Deep Equatorial Pacific Ocean Oxygenation And Atmospheric Co2 Over The Last Ice Age, Franco Marcantonio, Ryan Hostak, Jennifer E. Hertzberg, Matthew W. Schmidt

OES Faculty Publications

Ventilation of carbon stored in the deep ocean is thought to play an important role in atmospheric CO₂ increases associated with Pleistocene deglaciations. The presence of this respired carbon has been recorded by an array of paleoceanographic proxies from various locations across the global ocean. Here we present a new sediment core from the Eastern Equatorial Pacific (EEP) Ocean spanning the last 180,000 years and reconstruct high-resolution 230Th-derived fluxes of 232Th and excess barium, along with redox-sensitive uranium concentrations to examine past variations in dust delivery, export productivity, and bottom-water oxygenation, respectively. Our bottom-water oxygenation record is compared to …

Metabolic Profiling Reveals Biochemical Pathways Responsible For Eelgrass Response To Elevated Co2 And Temperature, Carmen C. Zayas-Santiago, Albert Rivas-Ubach, Li-Jung Kuo, Nicholas D. Ward, Richard C. Zimmerman

OES Faculty Publications

As CO₂ levels in Earth’s atmosphere and oceans steadily rise, varying organismal responses may produce ecological losers and winners. Increased ocean CO₂ can enhance seagrass productivity and thermal tolerance, providing some compensation for climate warming. However, the metabolic shifts driving the positive response to elevated CO₂ by these important ecosystem engineers remain unknown. We analyzed whole-plant performance and metabolic profiles of two geographically distinct eelgrass (Zostera marina L.) populations in response to CO₂ enrichment. In addition to enhancing overall plant size, growth and survival, CO₂ enrichment increased the abundance of Calvin Cycle and …

An Oceanographic Perspective On Early Human Migrations To The Americas, Thomas C. Royer, Bruce Finney

OES Faculty Publications

Early migrants to the Americas were likely seaworthy. Many archaeologists now agree that the first humans who traveled to the Americas more than 15,000 years before present (yr BP) used a coastal North Pacific route. Their initial migration was from northeastern Asia to Beringia where they settled for thousands to more than ten thousand years. Oceanographic conditions during the Last Glacial Maximum (18,000-24,000 yr BP) would have enhanced their boat journeys along the route from Beringia to the Pacific Northwest because the influx of freshwater that drives the opposing Alaska Coastal Current was small, global sea level was at least …

Quantifying Seagrass Distribution In Coastal Water With Deep Learning Models, Daniel Perez, Kazi Islam, Victoria Hill, Richard Zimmerman, Blake Schaeffer, Yuzhong Shen, Jiang Li

OES Faculty Publications

Coastal ecosystems are critically affected by seagrass, both economically and ecologically. However, reliable seagrass distribution information is lacking in nearly all parts of the world because of the excessive costs associated with its assessment. In this paper, we develop two deep learning models for automatic seagrass distribution quantification based on 8-band satellite imagery. Specifically, we implemented a deep capsule network (DCN) and a deep convolutional neural network (CNN) to assess seagrass distribution through regression. The DCN model first determines whether seagrass is presented in the image through classification. Second, if seagrass is presented in the image, it quantifies the seagrass …

Towards Sustained Monitoring Of Subsidence At The Coast Using Insar And Gps: An Application In Hampton Roads, Virginia, Brett Buzzanga, David P.S. Bekaert, Ben D. Hamlington, Simran S. Sangha

OES Faculty Publications

Hampton Roads is among the regions along the U.S. Atlantic Coast experiencing high rates of relative sea level rise. Partly to mitigate subsidence from aquifer compaction, Hampton Roads is injecting treated wastewater into the underlying aquifer. However, the GPS (Global Positioning System) station spacing (∼30 km) is too coarse to capture the spatial variability of subsidence and potential uplift from the injection. We present a cost‐effective workflow for generating an InSAR (interferometric synthetic aperture radar) and GPS combined displacement product. We leverage a live, open‐access archive of InSAR products generated from Sentinel‐1 data. We find an overall subsidence rate of …

Bacterial Biofilms Colonizing Plastics In Estuarine Waters, With An Emphasis On Vibrio Spp. And Their Antibacterial Resistance, Amanda L. Laverty, Sebastian Primke, Claudia Lorenz, Gunnar Gerdtz, Fred Dobbs

OES Faculty Publications

Since plastics degrade very slowly, they remain in the environment on much longer timescales than most natural organic substrates and provide a novel habitat for colonization by bacterial communities. The spectrum of relationships between plastics and bacteria, however, is little understood. The first objective of this study was to examine plastics as substrates for communities of Bacteria in estuarine surface waters. We used next-generation sequencing of the 16S rRNA gene to characterize communities from plastics collected in the field, and over the course of two colonization experiments, from biofilms that developed on plastic (low-density polyethylene, high-density polyethylene, polypropylene, polycarbonate, polystyrene) …