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Articles 1 - 9 of 9
Full-Text Articles in Life Sciences
Biophysical Model Of Retraction Motor Neurons And Their Modification By Operant Conditioning, Maria Rasheed
Biophysical Model Of Retraction Motor Neurons And Their Modification By Operant Conditioning, Maria Rasheed
Dissertations & Theses (Open Access)
Operant conditioning (OC) is a form of associative learning in which an animal modifies its behavior based on the consequences that follow that behavior. Despite its ubiquity, the underlying mechanisms of OC are poorly understood. Insights into the mechanisms of OC can be obtained by studying Aplysia feeding behavior as it can be modified by OC. This behavior is mediated by a central pattern generator (CPG) network in the buccal ganglia that contains a relatively small number of neurons. This CPG generates rhythmic motor patterns (BMPs) that move food into the gut by closing a tongue-like structure (i.e., radula) during …
Faa Medical Reform, Dana Rose
Faa Medical Reform, Dana Rose
Honors Projects
This project investigates the challenges and implications of obtaining medical certification for pilots with a history of childhood misdiagnoses, focusing on Attention-Deficit/Hyperactivity Disorder (ADHD). Misdiagnoses in childhood can lead to significant obstacles in the aviation industry's medical certification process, posing unique hurdles for aspiring pilots. The study examines the current FAA guidelines and procedures for medical certification, particularly the evaluation requirements for individuals with ADHD. It also explores common challenges faced by pilots, the effects of childhood misdiagnoses on their eligibility, and the impact of the FAA's ADHD evaluation process.
Through interviews with Aviation Medical Examiners (AMEs), this project identifies …
A Ground-Based L-Band Radar System For Monitoring Forest Temporal Dynamics, Xingjian Chen
A Ground-Based L-Band Radar System For Monitoring Forest Temporal Dynamics, Xingjian Chen
Doctoral Dissertations
L-band FMCW radar is implemented for monitoring forest dynamics. It took short-term and long-term measurements with an internal calibration system that guarantees stability and precision. The radar data is compared to in-situ measurement, which infers causal relationships between radar backscatter signal and forest physiology index such as tree dielectric. This paper explains the relationship between radar signals and environmental components such as precipitation based on the measurement. The radar demonstrates some interesting observations, for example, trees' daily activity and freeze-thaw process.
Development Of An Integrated Workflow For Nucleosome Modeling And Simulations, Ran Sun
Development Of An Integrated Workflow For Nucleosome Modeling And Simulations, Ran Sun
Doctoral Dissertations
Nucleosomes are the building blocks of eukaryotic genomes and thus fundamental to to all genetic processes. Any protein or drug that binds DNA must either cooperate or compete with nucleosomes. Given that a nucleosome contains 147 base pairs of DNA, there are approximately 4^147 or 10^88 possible sequences for a single nucleosome. Exhaustive studies are not possible. However, genome wide association studies can identify individual nucleosomes of interest to a specific mechanism, and today's supercomputers enable comparative simulation studies of 10s to 100s of nucleosomes. The goal of this thesis is to develop and present and end-to-end workflow that serves …
Applicability Of Using Bio-Receptive Concrete For Building Facades In Egypt, Gina Roupheil
Applicability Of Using Bio-Receptive Concrete For Building Facades In Egypt, Gina Roupheil
Theses and Dissertations
The significant increase in carbon dioxide emissions caused by the construction industry is detrimental to our planet. This is rapidly increasing with the urbanization of cities that is gradually taking its toll on the available green spaces, which help in balancing such emissions. Recently, researchers have been trying to make use of bio-receptivity to create biomaterial systems that could be spread on building envelopes and support the growth of small plant species and microorganisms to establish on. Out of those materials, comes the concrete as a promising material for bio-colonization.
Within this context, this study aims at investigating the applicability …
Rational Design Of Peptide-Based Materials Informed By Multiscale Molecular Dynamics Simulations, Dhwanit Rahul Dave
Rational Design Of Peptide-Based Materials Informed By Multiscale Molecular Dynamics Simulations, Dhwanit Rahul Dave
Dissertations, Theses, and Capstone Projects
The challenge of establishing a sustainable and circular economy for materials in medicine and technology necessitates bioinspired design. Nature's intricate machinery, forged through evolution, relies on a finite set of biomolecular building blocks with through-bond and through-space interactions. Repurposing these molecular building blocks requires a seamless integration of computational modeling, design, and experimental validation. The tools and concepts developed in this thesis pioneer new directions in peptide-materials design, grounded in fundamental principles of physical chemistry. We present a synergistic approach that integrates experimental designs and computational methods, specifically molecular dynamics simulations, to gain in-depth molecular insights crucial for advancing the …
The Ecological Responses To Hydroperiod Of Wetland Plant Species Determined By Manipulated Soil Surface Elevation (Marsh Organs), Brandon Wolff
The Ecological Responses To Hydroperiod Of Wetland Plant Species Determined By Manipulated Soil Surface Elevation (Marsh Organs), Brandon Wolff
LSU Master's Theses
As sea level rise, subsidence, and abandonment of natural deltaic processes due to a highly engineered Mississippi River continue to threaten Louisiana’s coastal wetlands, the need for a system-wide understanding of natural wetland land-building and preservation processes has never been greater. A key component of any wetland is the ever-changing water environment that periodically floods and dries the marsh platforms. The flooding depth, duration, and frequency, known as the hydroperiod, along with salinity and soil fertility are key determining factors of vegetation and marsh types at a particular location. Different types of vegetation will have different growth characteristics such as …
Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas
Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas
Theses and Dissertations--Chemical and Materials Engineering
Hydrophobic deep eutectic solvents (DESs) have emerged as excellent extractants. A major challenge is the lack of an efficient tool to discover DES candidates. Currently, the search relies heavily on the researchers’ intuition or a trial-and-error process, which leads to a low success rate or bypassing of promising candidates. DES performance depends on the heterogeneous hydrogen bond environment formed by multiple hydrogen bond donors and acceptors. Understanding this heterogeneous hydrogen bond environment can help develop principles for designing high performance DESs for extraction and other separation applications. This work investigates the structure and dynamics of hydrogen bonds in hydrophobic DESs …
Language Models For Rare Disease Information Extraction: Empirical Insights And Model Comparisons, Shashank Gupta
Language Models For Rare Disease Information Extraction: Empirical Insights And Model Comparisons, Shashank Gupta
Theses and Dissertations--Computer Science
End-to-end relation extraction (E2ERE) is a crucial task in natural language processing (NLP) that involves identifying and classifying semantic relationships between entities in text. This thesis compares three paradigms for end-to-end relation extraction (E2ERE) in biomedicine, focusing on rare diseases with discontinuous and nested entities. We evaluate Named Entity Recognition (NER) to Relation Extraction (RE) pipelines, sequence-to-sequence models, and generative pre-trained transformer (GPT) models using the RareDis information extraction dataset. Our findings indicate that pipeline models are the most effective, followed closely by sequence-to-sequence models. GPT models, despite having eight times as many parameters, perform worse than sequence-to-sequence models and …