Physical Sciences and Mathematics Commons^™

Pariette Wetlands Water, Sediment And Plant Total Selenium Concentration, Colleen P. Jones, Paul R. Grossl, Astrid R. Jacobson

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We measured total Selenium in plants from July through November of 2012 and in water, macroinvertebrates, plants, and sediments from July of 2014 from Pariette Wetlands, Utah, U.S.A. to test for spatial, temporal, plant species and plant tissue distribution of Selenium.

An Intercomparison Of Large-Eddy Simulations Of A Convection Cloud Chamber Using Haze-Capable Bin And Lagrangian Cloud Microphysics Schemes, Fan Yang, Fabian Hoffmann, Raymond Shaw, Mikhail Ovchinnikov, Andrew Vogelmann

Michigan Tech Research Data

Recent in-situ observations show that haze particles exist in a convection cloud chamber. The microphysics schemes previously used for large-eddy simulations of the cloud chamber could not fully resolve haze particles and the associated processes, including their activation and deactivation. Specifically, cloud droplet activation is modeled based on Twomey-type parameterizations, wherein cloud droplets are formed when a critical supersaturation for the available cloud condensation nuclei (CCN) is exceeded and haze particles are not explicitly resolved. Here, we develop and adapt haze-capable bin and Lagrangian microphysics schemes to properly resolve the activation and deactivation processes. Results are compared with the Twomey-type …

Data From: Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Systems Science Faculty Datasets

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …

Gis Data: Charles County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Worcester County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions: 1) the …

Gis Data: St Mary’S County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Somerset County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions: 1) the …

Gis Data: Kent County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Baltimore County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Queen Anne’S County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Baltimore City, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Wicomico County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

The Dope Distance Is Sic: A Stable, Informative, And Computable Metric On Ordered Merge Trees, Jose Arbelo, Antonio Delgado, Charley Kirk, Zach Schlamowitz

Mathematics Summer Fellows

When analyzing time series data, it is often of interest to categorize them based on how different they are. We define a new dissimilarity measure between time series: Dynamic Ordered Persistence Editing (DOPE). DOPE satisfies metric properties, is stable to noise, is as informative as alternative approaches, and efficiently computable. Satisfying these properties simultaneously makes DOPE of interest to both theoreticians and data scientists alike.

Kinetics, Products, And Brown Carbon Formation By Aqueous-Phase Reactions Of Glycolaldehyde With Atmospheric Amines And Ammonium Sulfate (Raw Data), David O. De Haan, Alyssa A. Rodriguez, Michael A. Rafla, Hannah G. Welsh, Elyse A. Pennington, Jason R. Casar, Lelia N. Hawkins, Natalie G. Jimenez, Alexia De Loera, Devoun R. Stewart, Antonio Rojas, Matthew-Khoa Tran, Peng Lin, Alexander Laskin, Paola Formenti, Mathieu Cazaunau, Edouard Pangui, Jean-François Doussin

Chemistry and Biochemistry: Faculty Scholarship

The zipped data files are in the following formats: Metadata: Word documents (.docx), Chamber data: Excel spreadsheets (.xlsx) and European Data Format files (.edf), organized by experiment number and instrumentation. “CAPS” files contain cavity attenuated phase shift (CAPS) extinction and scattering data; “SMPS” files contain scanning mobility particle sizing aerosol number and aerosol mass data.

Radar Simulator Output Used For Tracking Isolated Convections, Mariko Oue, Mariko Oue

SoMAS Research Data

No abstract provided.

Sediment Characteristics Of The Chesapeake Bay And Its Tributaries, Virginia Province: Data Files, Gary F. Anderson

Data

During the 1990’s, Dr. Maynard Nichols and colleagues at the Virginia Institute of Marine Science compiled digital databases of sediment observations in the Chesapeake Bay and other coastal bays and rivers. These projects were performed under several cooperative agreements with NOAA, EPA and USGS. This particular dataset covers the Chesapeake Bay for bulk properties and contaminants. Additional references are provided below. The original files and filenames are provided without edit. See the readme.txt file for overall explanation of the datasets and individual .DOC files for the data dictionary and further data processing information for each waterbody.

A Course In Data Science: R And Prediction Modeling, Adam Kapelner

Open Educational Resources

This is a self-contained course in data science and machine learning using R. It covers philosophy of modeling with data, prediction via linear models, machine learning including support vector machines and random forests, probability estimation and asymmetric costs using logistic regression and probit regression, underfitting vs. overfitting, model validation, handling missingness and much more. There is formal instruction of data manipulation using dplyr and data.table, visualization using ggplot2 and statistical computing.

Datadescription-Detection Of Sulfur Dioxide By Broadband Cavity-Enhanced Absorption Spectroscopy (Bbceas), Ryan Thalman, Nitish Bhardwaj, Callum Flowerday, Jaron C. Hansen

ScholarsArchive Data

Files archived include the following:

Figure1.txt This file contains all the data used to make Figure 1 in the paper.

Figure4.txt This file contains all the data used to make Figure 4 in the paper.

Figure5.txt This file contains all the data used to make Figure 5 in the paper.

Figure6.txt This file contains all the data used to make Figure 6 in the paper.

Figure7.txt This file contains the code, written in Igor, that was used to generate this figure.

Figure8.txt This file contains all the data used to make Figure 8 in the paper.

Figure9.txt This file contains …

Attachments To Reports Generated April 2022, Atlantic Richfield Company, Environmental Protection Agency, Trec Inc., A Woodard And Curran Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Air Pollutant Emissions From Natural Gas-Fueled Pumpjack Engines In The Uinta Basin, Seth Lyman

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We measured a comprehensive suite of pollutants emitted from 58 natural gas-fueled pumpjack engines in Utah’s Uinta Basin between January and May 2021, with repeat measurements of five engines in January 2022. We documented the emissions composition of several makes and models of commonly used engines, including Ajax E42, E565, DP60, and DP80 engines; Arrow L795, C101, and C106 engines; and GM Vortec.

New Hampshire Continental Shelf Geospatial Database: Surficial Geology Maps And Sediment Grain Size Data, Larry G. Ward, Zachary S. Mcavoy, Rachel C. Morrison

Data Catalog

The “New Hampshire Continental Shelf Geospatial Database: Surficial Geology Maps and Sediment Grain Size Data” consists of high-resolution surficial geology maps of the continental shelf off New Hampshire to Jeffreys Ledge in the Western Guff of Maine (WGOM) and supporting sediment grain size information. The surficial geology maps cover ~3,250 km² (Figure 1). The maps depict three different classifications based on the Coastal and Marine Ecological Classification Standards (CMECS; FGDC, 2012): Geoforms (major morphologic or physiographic features; Figure 2; Table 1), Geologic Substrate Subclass (Figure 3; Table 2), and Geologic Substrate Group (Figure 4; Table 2). The maps are …

Reverse-Engineering The Design Rules For Cloud-Based Big Data Platforms, Ravi S. Sharma, Purna N. Mannava, Stephen C. Wingreen

All Works

Big Data's 5 V complexities are making it increasingly difficult to develop an understanding of the end to end process. Big Data platforms play a crucial role in many critical systems, combining with Internet-of-Things, Artificial Intelligence and Business Analytics. It is both relevant and important to understand Big Data systems to identify the best tools that fit the requirements of heterogeneous platforms. The objective of this paper is to "discover" a set of design principles and rules for Cloud-based Big Data platforms for complex, heterogeneous environments. The design scope comprises Big Data's significance, challenges and architectural impacts. Using a methodology …

The Cohomology Of The Mod 2 Steenrod Algebra, Robert R. Bruner, John Rognes

Open Data at Wayne State

The dataset contains a minimal resolution of the mod 2 Steenrod algebra in the range 0 <= s <= 128, 0 <= t <= 200, together with chain maps for each cocycle in that range and for the squaring operation Sq^0 in the cohomology of the Steenrod algebra. The included document CohomA2.pdf explains the contents and usage of the dataset in detail (also available as supplemental material in this record).

Dataset is also available at the NIRD Research Data Archive, https://doi.org/10.11582/2021.00077; Data Description also available at arXiv.org, https://doi.org/10.48550/arXiv.2109.13117.

Elemental And Oxidized Mercury In The Atmosphere At Horsepool, Utah, January-July 2019, Seth Lyman

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This is a dataset of elemental and oxidized mercury in the ambient atmosphere at latitude 40.143° N and longitude 109.469° W. This is the location of the Horsepool monitoring station in the Uinta Basin, Utah. We collected these measurements using a dual-channel atmospheric mercury speciation instrument, which is described by Lyman, S. N., Gratz, L. E., Dunham-Cheatham, S. M., Gustin, M. S., & Luippold, A. (2020). Improvements to the accuracy of atmospheric oxidized mercury measurements. Environmental Science & Technology, 54(21), 13379-13388.

Software For A Conformally Invariant Yang-Mills Type Energy And Equation On 6-Manifolds, Lawrence Peterson

Datasets

The author has developed some new computer software and has used it, together with Mathematica and John M. Lee's Ricci software package, to verify many of the results in the article "A Conformally Invariant Yang-Mills Type Energy and Equation on 6-Manifolds" (arXiv:2107.08515). The author's new software is posted here, along with the Ricci package and a special guidelines file. One should read this guidelines file before studying or using the software.

A Divide & Concur Approach To Collaborative Goal Modeling With Merge In Early-Re: Supplemental Material, Kathleen R. Hablutzel, Anisha Jain, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper:
"A Divide & Concur Approach to Collaborative Goal Modeling with Merge in Early-RE"
This paper proposes a formal approach to the problem of merging the attributes of intentions and actors, once these elements have been matched.

Proteome Database, Mariana Rius, Jackie L. Collier, Joshua Rest

SoMAS Research Data

No abstract provided.

Data Relevant To "Going Mobile To Address Emerging Climate Equity Needs In The Heterogeneous Urban Environment", Katia Lamer

SoMAS Research Data

During its first few deployments, the mobile observatory has captured unique observations. Among them are vertical air motion measurements along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY which are shown to hold information critical to improving our understanding of the role of buildings in the ventilation of heat, pollution, and contaminants in urban street channels. Also, air temperature measurements collected during travel along a transect between Suffolk County and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the urban dome across different communities.

Marsh Vulnerability Index And Index Applied To Coastal Shorelines, Molly Mitchell, Donna Marie Bilkovic, Julie Herman, Jessica Hendricks, Evan Hill

Data

The Marsh Vulnerability Index (MVI) is a spatially-resolved assessment of Virginia tidal marsh vulnerabilities from important climate-change drivers – erosion vulnerability, inundation from sea level rise, and salinity intrusion from sea level rise – that can support management decisions. Effects were evaluated for two time-steps (near and longer-term planning horizons): 2050 and 2100.

The Marsh Vulnerability Index Applied to Coastal Shorelines layer extends the MVI evaluation for use in evaluating living shoreline (i.e., created or enhanced shoreline marshes) vulnerability and applies it to tidal shorelines in coastal Virginia. Outputs from this analysis were intended to evaluate the vulnerability of areas …

Sediment Survey: Yr060823, Station 3917, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs

Data

This dataset consists of sediment properties including grain size distribution, percent moisture, percent organic matter, sediment bed erodibility, as well as (in most cases) x-ray images of the sediment structure. Most samples were taken in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.