Physical Sciences and Mathematics Commons^™

Effects Of Different Colored Sticky Traps On Capture Of Alfafa Thrips, Li Zhao, Ling Zhang, Feng Wang

IGC Proceedings (1993-2023)

No abstract provided.

Effects On Bird Cherry‐Oat Aphid Resistance To Drunken Horse Grass By Neotyphodium Endophyte Infection, Xingxu Zhang, Chunjie Li

IGC Proceedings (1993-2023)

No abstract provided.

Forecast Of Alfalfa Yield Losses Caused By Leaf Spot Disease, Liang Zeng, Qinghua Yuan

IGC Proceedings (1993-2023)

No abstract provided.

Robust Lag Weighted Lasso For Time Series Model, Tahir R. Dikheel, Alaa Q. Yaseen

Journal of Modern Applied Statistical Methods

The lag-weighted lasso was introduced to deal with lag effects when identifying the true model in time series. This method depends on weights to reflect both the coefficient size and the lag effects. However, the lag weighted lasso is not robust. To overcome this problem, we propose robust lag weighted lasso methods. Both the simulation study and the real data example show that the proposed methods outperform the other existing methods.

Avulsions Drive Ecosystem Services And Economic Changes In The Brazilian Pantanal Wetlands, Rômullo O. Louzada, Ivan Bergier, Fabio O. Roque, Michael M. Mcglue, Aguinaldo Silva, Mario L. Assine

Earth and Environmental Sciences Faculty Publications

The Pantanal wetland is a mosaic of landscapes that brings together rich biodiversity with the valuable activities of fishing, tourism and ranching. Human occupation and land use in the headwaters have intensified the rate of channel avulsions in the lower reaches of the largest megafan on the Taquari River. This study evaluates the long-term changes of landscapes in the active depositional lobe of the Taquari megafan from the perspective of local communities of pantaneiros. Maps derived from multiple decades of multispectral Landsat data have proven useful for studying land cover changes through the relationship between dry (terrestrial vegetation and …

Data From: A Sandwich-Type Cluster Containing Ge@Pd3 Planar Fragment Flanked By Aromatic Nonagermanide Caps, Alexander I. Boldyrev, Nikolay Tkachenko

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Sandwich-type clusters with the planar fragment containing a heterometallic sheet have remained elusive. In this work, we introduce the [K(2,2,2-crypt)]4{(Ge9)2[η6-Ge(PdPPh3)3]} complex that contains a heterometallic sandwich fragment. The title compound is structurally characterized by means of single-crystal X-ray diffraction, which reveals the presence of an unusual heteroatomic metal planar fragment Ge@Pd3. The planar fragment contains a rare formal zerovalent germanium core and a peculiar bonding mode of sp2-Ge@(PdPPh3)3 trigonal planar structure, whereas the nonagermanide fragments act as capping ligands. The chemical bonding pattern of the planar fragment consists of three 2c-2e Pd-Ge σ-bonds attaching Pd atoms to the core Ge …

Grizzly Bears Mortalities And The Survival Of The Species, Courtney Swanson

Senior Seminars and Capstones

In this paper we aim to understand what is happening in the grizzly bear population mortalities from the year 2010 to 2020. We are performing Classical and Regression Tree (CART) methods and Correspondence Analysis on data provided by the U.S. Geological Survey (USGS). We found certain variables in the data set to be important through CART methods. Correspondence Analysis then allowed us to compare these variables to determine their relationships and association to one another. Most of the grizzly bear deaths are human caused and mainly over land and resources such as food and habitat. This aligns with some of …

Groundwater Level Assessment And Prediction In The Nebraska Sand Hills Using Lidar-Derived Lake Water Level, Nawaraj Shrestha, Aaron R. Mittelstet, Aaron R. Young, Troy E. Gilmore, David C. Gosselin, Yi Qi, Caner Zeyrek

School of Natural Resources: Faculty Publications

The spatial variability of groundwater levels is often inferred from sparsely located hydraulic head observations in wells. The spatial correlation structure derived from sparse observations is associated with uncertainties that spread to estimates at unsampled locations. In areas where surface water represents the nearby groundwater level, remote sensing techniques can estimate and increase the number of hydraulic head measurements. This research uses light detection and ranging (LIDAR) to estimate lake surface water level to characterize the groundwater level in the Nebraska Sand Hills (NSH), an area with few observation wells. The LIDAR derived lake groundwater level accuracy was within 40 …

Characterization Of Extracellular Vesicles Derived From Mesenchymal Stromal Cells By Surface-Enhanced Raman Spectroscopy., Nina M Ćulum, Tyler T Cooper, Gillian I Bell, David A Hess, François Lagugné-Labarthet

Chemistry Publications

Extracellular vesicles (EVs) are secreted by all cells into bodily fluids and play an important role in intercellular communication through the transfer of proteins and RNA. There is evidence that EVs specifically released from mesenchymal stromal cells (MSCs) are potent cell-free regenerative agents. However, for MSC EVs to be used in therapeutic practices, there must be a standardized and reproducible method for their characterization. The detection and characterization of EVs are a challenge due to their nanoscale size as well as their molecular heterogeneity. To address this challenge, we have fabricated gold nanohole arrays of varying sizes and shapes by …

Characterization Of Extracellular Vesicles Derived From Mesenchymal Stromal Cells By Surface-Enhanced Raman Spectroscopy., Nina M Ćulum, Tyler T Cooper, Gillian I Bell, David A Hess, François Lagugné-Labarthet

Chemistry Publications

Extracellular vesicles (EVs) are secreted by all cells into bodily fluids and play an important role in intercellular communication through the transfer of proteins and RNA. There is evidence that EVs specifically released from mesenchymal stromal cells (MSCs) are potent cell-free regenerative agents. However, for MSC EVs to be used in therapeutic practices, there must be a standardized and reproducible method for their characterization. The detection and characterization of EVs are a challenge due to their nanoscale size as well as their molecular heterogeneity. To address this challenge, we have fabricated gold nanohole arrays of varying sizes and shapes by …

Characterization Of Extracellular Vesicles Derived From Mesenchymal Stromal Cells By Surface-Enhanced Raman Spectroscopy., Nina M. Culum, Tyler T. Cooper, Gillian I. Bell, David A. Hess, François Lagugné-Labarthet

Chemistry Publications

Extracellular vesicles (EVs) are secreted by all cells into bodily fluids and play an important role in intercellular communication through the transfer of proteins and RNA. There is evidence that EVs specifically released from mesenchymal stromal cells (MSCs) are potent cell-free regenerative agents. However, for MSC EVs to be used in therapeutic practices, there must be a standardized and reproducible method for their characterization. The detection and characterization of EVs are a challenge due to their nanoscale size as well as their molecular heterogeneity. To address this challenge, we have fabricated gold nanohole arrays of varying sizes and shapes by …

Revised Fractional Abundances And Warm-Season Temperatures Substantially Improve Brgdgt Calibrations In Lake Sediments, Jonathan H. Raberg, David J. Harning, Sarah E. Crump, Gregory De Wet, Aria Blumm, Sebastian Kopf, Áslaug Geirsdóttir, Gifford H. Miller, Julio Sepúlveda

Geosciences: Faculty Publications

Distributions of branched glycerol dialkyl glycerol tetraethers (brGDGTs) are frequently employed for reconstructing terrestrial paleotemperatures from lake sediment archives. Although brGDGTs are globally ubiquitous, the microbial producers of these membrane lipids remain unknown, precluding a full understanding of the ways in which environmental parameters control their production and distribution. Here, we advance this understanding in three ways. First, we present 43 new high-latitude lake sites characterized by low mean annual air temperatures (MATs) and high seasonality, filling an important gap in the global dataset. Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) …

Toward An Intelligent Driving Behavior Adjustment Based On Legal Personalized Policies Within The Context Of Connected Vehicles, Fatma Outay, Nafaa Jabeur, Hedi Haddad, Zied Bouyahia, Hana Gharrad

All Works

The advent of Connected Vehicles (CVs) is creating new opportunities within the transportation sector. It is, indeed, expected to improve road traffic safety, enhance mobility, reduce fuel consumption and gas emissions, as well as foster economic growth via investments and jobs. However, to motivate the deployment of CVs and maximize their related benefits, policymakers must create appropriate neutral legal frameworks. These frameworks should promote the innovation of current road infrastructures, support cooperation and interoperability between transportation systems, and encourage fair competition between companies while upholding consumer privacy as well as data protection. We argue that policymakers should also support innovative …

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney

Articles

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …

Data From: Novel Strongly Correlated Europium Superhydrides, Alexander I. Boldyrev, Nikolay Tkachenko

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We conducted a joint experimental–theoretical investigation of the high-pressure chemistry of europium polyhydrides at pressures of 86–130 GPa. We discovered several novel magnetic Eu superhydrides stabilized by anharmonic effects: cubic EuH9, hexagonal EuH9, and an unexpected cubic (Pm3n) clathrate phase, Eu8H46. Monte Carlo simulations indicate that cubic EuH9 has antiferromagnetic ordering with TN of up to 24 K, whereas hexagonal EuH9 and Pm3n-Eu8H46 possess ferromagnetic ordering with TC = 137 and 336 K, respectively. The electron–phonon interaction is weak in all studied europium hydrides, and their magnetic ordering excludes s-wave superconductivity, except, perhaps, for distorted pseudohexagonal EuH9. The equations of …

Data From: Chemical Bonding Analysis Of Excited States Using The Adaptive Natural Density Partitioning Method, Alexander I. Boldyrev, Nikolay Tkachenko

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A novel approach to chemical bond analysis for excited states has been developed. Using an extended adaptive natural density partitioning method (AdNDP) as implemented in AdNDP 2.0 code, we obtained chemically intuitive bonding patterns for the excited states of H2O, B5+, and C2H4+ molecules. The deformation pathway in the excited states could be easily predicted based on the analysis of the chemical bond pattern. We expect that this new method of chemical bonding analysis would be very helpful for photochemistry, photoelectron spectroscopy, electron spectroscopy and other chemical applications that involved excited states.

Archaeology And Seasonality Of Stock Island (8mo2), A Glades-Tradition Village On Key West, Ryan M. Harke

USF Tampa Graduate Theses and Dissertations

Later Glades-period cultures (ca. 500–1760 CE) of south Florida and the Florida Keys are understudied and thus poorly understood, especially those that pre-date the arrival of Spaniards to the New World. Recent archaeological models of their sociopolitical organization suggest that by the Glades I-II transition (750/800 CE), south Florida peoples were organized into what appear to be regional population centers (e.g., Pineland and Mound Key, Granada, Turner River) and smaller hinterland towns in the Everglades (e.g., Cane Patch, Bear Lake) and the Florida Keys (e.g., Stock Island, Clupper Site). Smaller towns are hypothesized to be sedentary, heterarchically-organized, simple chiefdoms from …

Data From: Stability, Electronic, And Optical Properties Of Two-Dimensional Phosphoborane, Alexander I. Boldyrev, Nikolay Tkachenko

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The structure and properties of two-dimensional phosphoborane sheets were computationally investigated using Density Functional Theory calculations. The calculated phonon spectrum and band structure point to dynamic stability and allowed characterization of the predicted two-dimensional material as a direct-gap semiconductor with a band gap of ~1.5 eV. The calculation of the optical properties showed that the two-dimensional material has a relatively small absorptivity coefficient. The parameters of the mechanical properties characterize the two-dimensional phosphoborane as a relatively soft material, similar to the monolayer of MoS2. Assessment of thermal stability by the method of molecular dynamics indicates sufficient stability of the predicted …

Biogenic Sinking Particle Fluxes And Sediment Trap Collection Efficiency At Ocean Station Papa, Margaret Estapa, Ken Buesseler, Collen A. Durkin, Melissa Omand, Claudia Benitez-Nelson, Montserrat Rocca-Martí, Elly Breves, R. P. Kelly, Steve Pike

Faculty Publications

Comprehensive field observations characterizing the biological carbon pump (BCP) provide the foundation needed to constrain mechanistic models of downward particulate organic carbon (POC) flux in the ocean. Sediment traps were deployed three times during the EXport Processes in the Ocean from RemoTe Sensing campaign at Ocean Station Papa in August–September 2018. We propose a new method to correct sediment trap sample contamination by zooplankton “swimmers.” We consider the advantages of polyacrylamide gel collectors to constrain swimmer influence and estimate the magnitude of possible trap biases. Measured sediment trap fluxes of thorium-234 are compared to water column measurements to assess trap …

Covid-19: A One Health Issue, Karen Gruszynski

Cumberland Mountain Naturalist

COVID-19 has very rapidly become part of modern societal lexicon as the disease highlights the importance understanding zoonotic diseases and the impact they can have on human life. With a 177million human cases and 3.82million deaths globally at the time of this publication, the "One Health" nature of the disease has had a lasting impact across the planet. As the disease spread rapidly, it highlighted the dissemination of information through social media and other sources. With this in mind, Dr. Gary Vroegindewey, Director for One Health at LMU-CVM, put forth the idea to have students collect and summarize information about …

Numeric And Dynamic B-Stability, Exact-Monotone And Asymptotic Two-Point Behavior Of Theta Methods For Stochastic Differential Equations, Henri Schurz

Journal of Stochastic Analysis

No abstract provided.

Mining Energy Consumption As A Function Of Ore Grade Decline: The Case Of Lead And Zinc, Ricardo Magdalena, Alicia Valero, Jose-Luis Palacios, Antonio Valero

Journal of Sustainable Mining

Demand for raw materials is increasing exponentially. To satisfy that demand, more minerals need to be mined from the Earth’s crust. As a result, minerals are being exhausted, and ore grades decline. Lower ore grade mines also mean more energy, which in turn entails fossil fuel emissions and more climate change. This paper estimates the specific energy for the beneficiation process of metals lead and zinc as case studies. The evaluation is performed with specialized software, HSC Chemistry which assesses the specific energy for every stage: comminution, flotation, and refining. Different scenarios have been established to simulate the behavior of …

The Allelopathy Of 3 Companion Weeds With Alfalfa, Y. L. Yin, H. X. Li, J. Wang, D. S. Zhang, Y. X. Yu, Z. Q. Qi

IGC Proceedings (1993-2023)

No abstract provided.

Molecular Authentication Of The Eospalax Of Myospalax By Analyzing Cytochrome B Sequences, Hongshan Yang, Genzhu Chang, Xiaoqin He

IGC Proceedings (1993-2023)

No abstract provided.

Spatial Heterogeneity Of The Weed Community In A Manilagrass Lawn, Xinming Xie, Wei Tang, Pinting Zhong, Masae Shiyomi

IGC Proceedings (1993-2023)

No abstract provided.

A Generalized, Modular Approach To Treating Moving Tumors With Ion Beams, Michelle Jennifer Lis

LSU Doctoral Dissertations

Despite advancements in cancer therapy, certain indications continue to have a poor prognosis, including cancers of the thorax. Existing methods for treating moving tumors with carbon ions have shown promise, but require technologically complex facilities and still have inherent limitations to mitigating tumor motion. The goal of this dissertation was to develop and test a safe, portable, and modular motion-synchronized dose delivery system (M-DDS) and its peripheral components as a framework for studying motion mitigation with ion beams.

We designed and integrated a motion-synchronized radiotherapy approach, called multi-phase 4D delivery (MP4D), as modular units of a clinical dose delivery system. …

Exploration Of Fluorinated Α,Β-Dehydroamino Acids And Their Structure, Austin Lesueur

Undergraduate Honors Theses

This thesis explores the synthesis of fluorinated α,β-dehydroamino acids, specifically a fluorinated dehydrovaline derivative. Previous work has been done on the equivalent dehydrovaline derivative without fluorine present and this work builds toward the fluorinated version with the goal of comparing the two structurally. The synthesis presented here pulls from previous synthetic strategies employed for dehydrovaline while also exploring the synthetic impact of the electronegative fluorine atoms.

St-V-Net: Incorporating Shape Prior Into Convolutional Neural Netwoks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Shreyasee Amin, Elizabeth J. Atkinson, Lan-Juan Zhao, Michael J. Serou, Chaoyang Zhang, Hui Shen, Hong-Wen Deng, Weihua Zhou

Faculty Publications

We aim to develop a deep-learning-based method for automatic proximal femur segmentation in quantitative computed tomography (QCT) images. We proposed a spatial transformation V-Net (ST-V-Net), which contains a V-Net and a spatial transform network (STN) to extract the proximal femur from QCT images. The STN incorporates a shape prior into the segmentation network as a constraint and guidance for model training, which improves model performance and accelerates model convergence. Meanwhile, a multi-stage training strategy is adopted to fine-tune the weights of the ST-V-Net. We performed experiments using a QCT dataset which included 397 QCT subjects. During the experiments for the …

Interpretable Fine-Grained Visual Categorization, Pei Guo

Theses and Dissertations

Not all categories are created equal in object recognition. Fine-grained visual categorization (FGVC) is a branch of visual object recognition that aims to distinguish subordinate categories within a basic-level category. Examples include classifying an image of a bird into specific species like "Western Gull" or "California Gull". Such subordinate categories exhibit characteristics like small inter-category variation and large intra-class variation, making distinguishing them extremely difficult. To address such challenges, an algorithm should be able to focus on object parts and be invariant to object pose. Like many other computer vision tasks, FGVC has witnessed phenomenal advancement following the resurgence of …