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Full-Text Articles in Physical Sciences and Mathematics
Exploring Beaver-Facilitated Restoration In Grassland Channelized Streams, Jessica L. Sikora
Exploring Beaver-Facilitated Restoration In Grassland Channelized Streams, Jessica L. Sikora
Graduate Research Theses & Dissertations
Freshwater streams provide vital ecosystem services, but their ecological function is gravely impacted by agricultural practices especially in grassland ecosystems. Though there is evidence that the re-introduction of beavers can help restore the ecological function of streams, little is known about their restorative impacts in grasslands. At Nachusa Grasslands Preserve in Franklin Grove, IL, we investigated the presence and impact of beaver dams on their waterways. With increasing beaver dam volume, we found an increase in sediment retention and less sediment retention with increasing beaver dams upstream from a dam. Though we did not find evidence that beaver dam volume …
Bioanalytical Studies Of Disease Protein Profiles: Maldi-Tof Ms, Prajkta Satish Chivte
Bioanalytical Studies Of Disease Protein Profiles: Maldi-Tof Ms, Prajkta Satish Chivte
Graduate Research Theses & Dissertations
Coronavirus disease-2019 (COVID-19), which is caused by a novel coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has ravaged the world for the past 3 years. Even today, there still exists a need for rapid, accurate, economical and non-invasive diagnostic testing platforms that yield high specificity and sensitivity towards the constantly mutating SARS-CoV-2. Research has consistently indicated saliva to be a more amenable specimen type for early detection of SARS-CoV-2, compared to the oral and nasopharyngeal swabs. Considering the limitations and high demand of the existing COVID-19 testing platforms, this dissertation work studies used MALDI-ToF MS (matrix-assisted laser desorption/ionization-time of …
A State Space Modeling Approach To Eeg Artifact Removal, Patrick B. Rafael
A State Space Modeling Approach To Eeg Artifact Removal, Patrick B. Rafael
Graduate Research Theses & Dissertations
In this work, a state space modeling approach is applied to an Electroencephalography(EEG) recording for the purpose of artifact removal, and is compared against Independent Components Analysis (ICA), the current gold standard. Issues of model identifiability are touched on, and Hamiltonian Monte Carlo (HMC) is used to estimate a linear non-Gaussian state space model. Results show that estimating such a model is a nontrivial matter, and the full utility of the state space approach remains to be demonstrated.
The Role Of Machine Learning And Network Analyses In Understanding Microbial Composition In An Experimental Prairie, Ali Eastman Oku
The Role Of Machine Learning And Network Analyses In Understanding Microbial Composition In An Experimental Prairie, Ali Eastman Oku
Graduate Research Theses & Dissertations
Machine learning and network analyses are powerful modern tools can process and map out connections between large amount of ecological data from complex environmental communities. Random forests, an ensemble machine learning algorithm, are particularly powerful as they can capture complex patterns in data while remaining easily interpretable. These tools are specifically useful in experimental settings where different types of data are collected. The aim of this study was to demonstrate the utility of machine learning models and network analyses at analyzing diverse ecological data from dynamic plant-soil microbial communities in a prairie ecosystem. Our experimental system is an experimental prairie …