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Articles 1 - 16 of 16
Full-Text Articles in Physical Sciences and Mathematics
College Of Natural Sciences Newsletter, Spring 2024, College Of Natural Sciences
College Of Natural Sciences Newsletter, Spring 2024, College Of Natural Sciences
College of Natural Sciences Newsletters and Reports
Page 1 Dean's Message
Page 2 New Faculty and New Club on Campus
Page 3 2024 URSCAD Awards
Page 4 Day of Scholars 2024
Page 5 SDSU's First Representation at the Association for Anatomy's 2024
Annual Conference
Page 6-7 2024 Honor's College Convocation
Page 8 Other Student Activities
Page 9 Faculty Awards
Page 10-11 Other News
Page 12 2024 Drone Day and American Association of Geographers Convention - Hawaii
Page 13 55th Annual Geography Convention
Page 14 2024 Stethoscope Ceremony
Page 15 Open PRAIRIE Data
Plants Reduced Nitrous Oxide Emissions From A Northern Great Plains Saline/Sodic Soil, Sharon A. Clay, Thandiwe Nleya, David E. Clay, Deepak Joshi, Dwarika Bhattarai, Shin-Yi Marzano, Bhanu Prakash Petla
Plants Reduced Nitrous Oxide Emissions From A Northern Great Plains Saline/Sodic Soil, Sharon A. Clay, Thandiwe Nleya, David E. Clay, Deepak Joshi, Dwarika Bhattarai, Shin-Yi Marzano, Bhanu Prakash Petla
Agronomy, Horticulture and Plant Science Faculty Publications
The slowly establishing salt-tolerant perennial grasses reduced nitrous oxide (N2 O- N) emissions from saline/sodic soil compared to barren areas. Other salt-tolerant species may accelerate vegetative establishment and reduce N 2 O-N emissions. In a greenhouse study, barley (Hordeum vulgare L.), Florida broadleaf mustard (Brassica juncea L.), and Kernza intermediate wheatgrass [Thinopyrum intermedium (Host) Barkworth & D. R. Dewey] were grown for 63 days to compare shoot biomass and chemical composition, N 2 O-N emissions, and the soil microbiome between saline/sodic and productive (non-salt impacted) soils. Emissions were measured six times daily from 1 to 22 and 42 to 63 …
Session 8: Machine Learning Based Behavior Of Non-Opec Global Supply In Crude Oil Price Determinism, Mofe Jeje
Session 8: Machine Learning Based Behavior Of Non-Opec Global Supply In Crude Oil Price Determinism, Mofe Jeje
SDSU Data Science Symposium
Abstract
While studies on global oil price variability, occasioned by OPEC crude oil supply, is well documented in energy literature; the impact assessment of non-OPEC global oil supply on price variability, on the other hand, has not received commensurate attention. Given this gap, the primary objective of this study, therefore, is to estimate the magnitude of oil price determinism that is explained by the share of non-OPEC’s global crude oil supply. Using secondary sources of data collection method, data for target variable will be collected from the US Federal Reserve, as it relates to annual crude oil price variability, while …
Predicting Crop Yield Using Remote Sensing Data, Mary Row, Jung-Han Kimn, Hossein Moradi
Predicting Crop Yield Using Remote Sensing Data, Mary Row, Jung-Han Kimn, Hossein Moradi
SDSU Data Science Symposium
Accurate crop yield predictions can help farmers make adjustments or changes in their farming practices to optimize their harvest. Remote sensing data is an inexpensive approach to collecting massive amounts of data that could be utilized for predicting crop yield. This study employed linear regression and spatial linear models were used to predict soybean yield with data from Landsat 8 OLI. Each model was built using only spectral bands of the satellite, only vegetation indices, and both spectral bands and vegetation indices. All analysis was based on data collected from two fields in South Dakota from the 2019 and 2021 …
Principal Component Analysis With Application To Credit Card Data, Eleanor Cain, Semhar Michael, Gary Hatfield
Principal Component Analysis With Application To Credit Card Data, Eleanor Cain, Semhar Michael, Gary Hatfield
SDSU Data Science Symposium
Principal Component Analysis (PCA) is a type of dimension reduction technique used in data analysis to process the data before making a model. In general, dimension reduction allows analysts to make conclusions about large data sets by reducing the number of variables while retaining as much information as possible. Using the numerical variables from a data set, PCA aims to compute a smaller set of uncorrelated variables, called principal components, that account for a majority of the variability from the data. The purpose of this poster is to understand PCA as well as perform PCA on a large sample credit …
Session 6: Model-Based Clustering Analysis On The Spatial-Temporal And Intensity Patterns Of Tornadoes, Yana Melnykov, Yingying Zhang, Rong Zheng
Session 6: Model-Based Clustering Analysis On The Spatial-Temporal And Intensity Patterns Of Tornadoes, Yana Melnykov, Yingying Zhang, Rong Zheng
SDSU Data Science Symposium
Tornadoes are one of the nature’s most violent windstorms that can occur all over the world except Antarctica. Previous scientific efforts were spent on studying this nature hazard from facets such as: genesis, dynamics, detection, forecasting, warning, measuring, and assessing. While we want to model the tornado datasets by using modern sophisticated statistical and computational techniques. The goal of the paper is developing novel finite mixture models and performing clustering analysis on the spatial-temporal and intensity patterns of the tornadoes. To analyze the tornado dataset, we firstly try a Gaussian distribution with the mean vector and variance-covariance matrix represented as …
Session 6: The Size-Biased Lognormal Mixture With The Entropy Regularized Algorithm, Tatjana Miljkovic, Taehan Bae
Session 6: The Size-Biased Lognormal Mixture With The Entropy Regularized Algorithm, Tatjana Miljkovic, Taehan Bae
SDSU Data Science Symposium
A size-biased left-truncated Lognormal (SB-ltLN) mixture is proposed as a robust alternative to the Erlang mixture for modeling left-truncated insurance losses with a heavy tail. The weak denseness property of the weighted Lognormal mixture is studied along with the tail behavior. Explicit analytical solutions are derived for moments and Tail Value at Risk based on the proposed model. An extension of the regularized expectation–maximization (REM) algorithm with Shannon's entropy weights (ewREM) is introduced for parameter estimation and variability assessment. The left-truncated internal fraud data set from the Operational Riskdata eXchange is used to illustrate applications of the proposed model. Finally, …
College Of Natural Sciences 2023 Year-End Publication, College Of Natural Sciences
College Of Natural Sciences 2023 Year-End Publication, College Of Natural Sciences
College of Natural Sciences Newsletters and Reports
Page 1 Dean's Message
Page 3 Department Highlights
Page 4 One Day for State
Page 5 Noble Prize Winner Speaks on Campus
Page 6-7 Faculty Excellence
Page 8-9 Student Excellence
Page 10 Outreach Program
Page 10 Events and Traditions
Page 11 Connections Abroad
Page 12 Student Spotlight
Page 13 Alumni Spotlight
Page 14 First Ever Drone Day
Page 15 Grand Opening of POET Bioproducts Center
Page 16 Work Anniversaries
Can Phytoremediation-Induced Changes In The Microbiome Improve Saline/Sodic Soil And Plant Health?, Achal Neupane, Duncan Jukubowski, Douglas Fiedler, Liping Gu, Sharon A. Clay, David E. Clay, Shin-Yi Marzano
Can Phytoremediation-Induced Changes In The Microbiome Improve Saline/Sodic Soil And Plant Health?, Achal Neupane, Duncan Jukubowski, Douglas Fiedler, Liping Gu, Sharon A. Clay, David E. Clay, Shin-Yi Marzano
Agronomy, Horticulture and Plant Science Faculty Publications
Increasing soil salinity and/or sodicity is an expanding problem in the Northern Great Plains (NGP) of North America. This study investigated the impact of phytoremediation on the soil microbiome and if changes, in turn, had positive or negative effects on plant establishment. Amplicon sequencing and gas chromatograph/mass spectrometer analysis compared root metabolites and microbial composition of bulk vs. rhizosphere soils between two soil types (productive and saline/sodic). Beta-diversity analysis indicated that bacterial and fungal communities from both the bulk and rhizosphere soils from each soil type clustered separately, indicating dissimilar microbial composition. Plant species also influenced both root-associated bacterial and …
Impact Of Solar Radiation On Perchlorate Formation In The Atmosphere: Evidence From Ice Core Measurements, Bishnu Kunwar
Impact Of Solar Radiation On Perchlorate Formation In The Atmosphere: Evidence From Ice Core Measurements, Bishnu Kunwar
Electronic Theses and Dissertations
Perchlorate, which derives from both anthropogenic and natural sources in the current environment, poses a substantial health hazard to humans as it competes with iodine uptake in the thyroid gland. Consequently, there has been considerable concern about minimizing human exposure to environmental perchlorate by restricting its release from man-made sources. However, the absence of a clear understanding regarding the respective contributions of man-made and natural sources has hindered widespread regulation efforts. A 300-year (1700–2007) Summit, Greenland ice core record from a previous study showed relatively stable perchlorate concentrations in Greenland snow prior to 1980, with some elevated perchlorate levels associated …
Portable X-Ray Fluorescence Spectrometry For Sensing Salinity And Sodicity In Glacial Northern Great Plains Soils With Machine Learning Models, Adam Devlin
Electronic Theses and Dissertations
Saline and sodic soils are an increasing concern across the Northern Great Plains (NGP) due to factors of climate change and land management that are drawing geologically derived salts to the land surface. Traditional laboratory assessments, such as electrical conductivity (EC) and sodium adsorption ratio (SAR), are time and resource consumptive. Portable X-ray fluorescence (PXRF) may be a viable proximal sensing alternative, as it is able to provide elemental data in minutes, in situ or ex situ, and can directly quantify salinity-associated elements like Ca, Mg, and S. PXRF paired with predictive models has proven useful for a range of …
Contrastive Learning, With Application To Forensic Identification Of Source, Cole Ryan Patten
Contrastive Learning, With Application To Forensic Identification Of Source, Cole Ryan Patten
Electronic Theses and Dissertations
Forensic identification of source problems often fall under the category of verification problems, where recent advances in deep learning have been made by contrastive learning methods. Many forensic identification of source problems deal with a scarcity of data, an issue addressed by few-shot learning. In this work, we make specific what makes a neural network a contrastive network. We then consider the use of contrastive neural networks for few-shot learning classification problems and compare them to other statistical and deep learning methods. Our findings indicate similar performance between models trained by contrastive loss and models trained by cross-entropy loss. We …
Effects Of Low-Cost, Low-Tech Tools For Riparian Restoration On Prairie Streams In Western South Dakota, James Andrew Joseph Bolyard
Effects Of Low-Cost, Low-Tech Tools For Riparian Restoration On Prairie Streams In Western South Dakota, James Andrew Joseph Bolyard
Electronic Theses and Dissertations
Despite making up less than two percent of the overall landscape in the arid and semi-arid western US, riparian areas are a crucial resource for agriculture, livestock, and wildlife. However, many have impaired function and reduced riparian cover. Low-Cost, Low-Tech Tools (LCLTT) are a subset of Process-Based Restoration (PBR) used for riparian restoration that were chosen for their cost-effectiveness and minimal technical requirements. LCLTT has been tested in mountainous areas of the western US but only recently implemented in the Northern Great Plains (NGP). Given their novelty as an approach toward restoration for the region, professional restoration and landowner communities …
The Hutton Project: Long-Term Agricultural Impacts On Soil Loss And Carbon Dynamics In Eastern South Dakota, Eli Halverson
The Hutton Project: Long-Term Agricultural Impacts On Soil Loss And Carbon Dynamics In Eastern South Dakota, Eli Halverson
Electronic Theses and Dissertations
Long-term and intensified agricultural land management has resulted in increased rates of soil erosion and has altered much of the carbon cycle at regional and global scales. Anthropogenic degradation of soil resources is a barrier to sustainable production, soil functioning, and ecosystem services. It is difficult to quantify the scope of pedogenic changes due to the lack of legacy data and short temporal scales. This study utilized decades to century-old soil information to quantify historical soil erosion losses and changes in soil carbon pools of eastern South Dakota soils. The results show that soils in the region have been significantly …
Rado Numbers For Two Systems Of Linear Equations, Anthony Glackin
Rado Numbers For Two Systems Of Linear Equations, Anthony Glackin
Electronic Theses and Dissertations
For any positive integer n and any equation E of either the form x1+x2+· · ·+xn = x0 or x1 + x2 + n = x0, the two-color Rado number R2(E) is the least integer such that any 2-coloring of the natural numbers 1 through R2(E) will contain a monochromatic solution to E. Let Ek be a system of k equations of the aforementioned form, where Ei represents the ith equation in Ek and the set I = {1, 2, . . . , k} is the set of indices of these equations. This thesis shows that the two-color Rado …
Species Distribution Modeling Of Aquilegia Brevistyla (Ranunculaceae): A Critically Imperiled Black Hills Disjunct Species, Eric Daniel Puetz
Species Distribution Modeling Of Aquilegia Brevistyla (Ranunculaceae): A Critically Imperiled Black Hills Disjunct Species, Eric Daniel Puetz
Electronic Theses and Dissertations
Unchecked human activity is contributing to rising levels of greenhouse gas emissions, changes in land use, altered disturbance/fire regimes, spread of invasive species, and loss of biological diversity and related breakdown of ecosystem services. Additionally, climatic shifts may lead to phenological mismatches between species and their environments if these changes outpace a species’ ability to adapt or migrate to a more suitable habitat. Isolated mountain populations are particularly threatened by unpredictable climatic conditions, as they may have limited migration corridors and often lower levels of genetic diversity to move or adapt, respectively. As these negative feedbacks compound on the landscape, …