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Articles 121 - 150 of 3959
Full-Text Articles in Physical Sciences and Mathematics
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
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Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …
Systematics, Taxonomy, And Ecology Of Neotropical Tachinidae (Diptera) With Focus On The Tribe Polideini, Juan Manuel Perilla López
Systematics, Taxonomy, And Ecology Of Neotropical Tachinidae (Diptera) With Focus On The Tribe Polideini, Juan Manuel Perilla López
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The diverse family of flies Tachinidae are a significant component of insect communities in nearly all terrestrial systems from deserts to tropical forests to the high arctic. Due to their parasitoid habit, tachinids are important enemies of a variety of other insect groups. Despite the apparent importance of this group, current studies—including ecological and biogeographic studies—are limited by taxonomic and systematic impediments, including unknown phylogenetic frameworks for most tribes, poorly known generic limits, and a large number of undescribed tropical species. Here I present studies in taxonomy, systematics, phylogenetics and ecology of the Polideini of the Neotropical region organized in …
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
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Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
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Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …
Path-Safe: Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
Path-Safe: Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
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Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …
Quantifying The Effects Of Dredged Sediment Application On Soil Properties And Plant Responses In Combination With Common Agricultural Field Management Practices, Ashley N. Julian
Quantifying The Effects Of Dredged Sediment Application On Soil Properties And Plant Responses In Combination With Common Agricultural Field Management Practices, Ashley N. Julian
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Successful crop production relies on soils with balanced physical, chemical and biological properties. Demand for greater crop yields has led to the breakdown of soil properties through detrimental agricultural practices. To combat soil degradation, farmers employ field management practices including cover crop application, crop rotation strategies and organic soil amendment addition. These practices, used independently or in combination, can improve soil stability, increase soil nutrient content and functions of beneficial soil microbiota while increasing crop yield. Despite showing promise as an organic soil amendment, dredged sediments are still not well understood, due in part to the fresh or weathered conditions …
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
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Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …
Understanding And Enhancing The Efficiency And Efficacy Of Machine Learning-Assisted Software Vulnerability Detection, Daniel J. Grahn
Understanding And Enhancing The Efficiency And Efficacy Of Machine Learning-Assisted Software Vulnerability Detection, Daniel J. Grahn
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As our world has become dependent upon software for nearly every aspect of modern society, software security has followed as an essential feature. The first line of defense against vulnerabilities is secure coding. While today’s programmers are carefully taught secure coding best practices, they can make mistakes or intentionally introduce vulnerable code. The traditional backstop to human errors and insider threats is the adoption of automated security analysis tools. These analysis tools have limitations. Static analysis suffers from high false positive rates that may cause annoyance and complacency among developers. Dynamic analysis can be difficult to set up and very …
Hamilton Cycles In Bidirected Complete Graphs, Arthur Busch, Mohammed A. Mutar, Daniel Slilaty
Hamilton Cycles In Bidirected Complete Graphs, Arthur Busch, Mohammed A. Mutar, Daniel Slilaty
Mathematics and Statistics Faculty Publications
Zaslavsky observed that the topics of directed cycles in directed graphs and alternating cycles in edge 2-colored graphs have a common generalization in the study of coherent cycles in bidirected graphs. There are classical theorems by Camion, Harary and Moser, Häggkvist and Manoussakis, and Saad which relate strong connectivity and Hamiltonicity in directed "complete" graphs and edge 2-colored "complete" graphs. We prove two analogues to these theorems for bidirected "complete" signed graphs.
Drug Abuse Ontology To Harness Web-Based Data For Substance Use Epidemiology Research, Usha Lokala, Francois Lamy, Raminta Daniulaityte, Manas Gaur, Amelie Gyrard, Krishnaprasad Thirunarayan, Ugur Kursuncu, Amit Sheth
Drug Abuse Ontology To Harness Web-Based Data For Substance Use Epidemiology Research, Usha Lokala, Francois Lamy, Raminta Daniulaityte, Manas Gaur, Amelie Gyrard, Krishnaprasad Thirunarayan, Ugur Kursuncu, Amit Sheth
Computer Science and Engineering Faculty Publications
Background: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. Objective: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web …
Submillimeter-Wave Cornea Phantom Sensing Over An Extended Depth Of Field With An Axicon-Generated Bessel Beam, Mariangela Baggio, Aleksi Tamminen, Joel Lamberg, Roman Grigorev, Samu-Ville Pälli, Juha Ala-Laurinaho, Irina Nefedova, Jean-Louis Bourges, Sophie X. Deng, Elliott R. Brown, Vincent P. Wallace, Zachary D. Taylor
Submillimeter-Wave Cornea Phantom Sensing Over An Extended Depth Of Field With An Axicon-Generated Bessel Beam, Mariangela Baggio, Aleksi Tamminen, Joel Lamberg, Roman Grigorev, Samu-Ville Pälli, Juha Ala-Laurinaho, Irina Nefedova, Jean-Louis Bourges, Sophie X. Deng, Elliott R. Brown, Vincent P. Wallace, Zachary D. Taylor
Physics Faculty Publications
The feasibility of a 220 - 330 GHz zero order axicon generated Bessel beam for corneal water content was explored. Simulation and experimental data from the 25-degree cone angle hyperbolic-axicon lens illuminating metallic spherical targets demonstrate a monotonically decreasing, band integrated, backscatter intensity for increasing radius of curvature from 7 - 11 mm, when lens reflector and optical axis are aligned. Further, for radii >= 9.5 mm, maximum signal was obtained with a 1 mm transverse displacement between lens and reflector optical axes arising from spatial correlation between main lobe and out of phase side lobes. Thickness and permittivity parameter …
Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang
Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang
Computer Science and Engineering Faculty Publications
Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …
Machine Learning For Aiding Blood Flow Velocity Estimation Based On Angiography, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang
Machine Learning For Aiding Blood Flow Velocity Estimation Based On Angiography, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang
Computer Science and Engineering Faculty Publications
Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …
Metal-To-Insulator Transition In An Anderson Insulator With Kondo Impurities, Weidong Zhang, Elliott R. Brown, Richard P. Mirin
Metal-To-Insulator Transition In An Anderson Insulator With Kondo Impurities, Weidong Zhang, Elliott R. Brown, Richard P. Mirin
Physics Faculty Publications
We report a voltage-controlled critical behavior observed in a GaAs epitaxial structure containing a dense array of ErAs nanoparticles. When fabricated with metal electrodes, the structure displays a voltage- and temperature-dependent metal-to-insulator transition and strong hysteresis in the current versus voltage and versus temperature characteristics, with critical temperatures as high as 77 K. Furthermore, we observed a diverging rms deviation of the electrical conductance with respect to the critical bias voltage, which further supports the existence of a phase transition. The insulating phase is governed by Efros-Shklovskii variable range hopping, and the conductance reduces beyond instrument limits as the temperature …
Toward Mental Effort Measurement Using Electrodermal Activity Features, William Romine, Noah Schroeder, Tanvi Banerjee, Josephine Graft
Toward Mental Effort Measurement Using Electrodermal Activity Features, William Romine, Noah Schroeder, Tanvi Banerjee, Josephine Graft
Computer Science and Engineering Faculty Publications
The ability to monitor mental effort during a task using a wearable sensor may improve productivity for both work and study. The use of the electrodermal activity (EDA) signal for tracking mental effort is an emerging area of research. Through analysis of over 92 h of data collected with the Empatica E4 on a single participant across 91 different activities, we report on the efficacy of using EDA features getting at signal intensity, signal dispersion, and peak intensity for prediction of the participant's self-reported mental effort. We implemented the logistic regression algorithm as an interpretable machine learning approach and found …
Leveraging Natural Learning Processing To Uncover Themes In Clinical Notes Of Patients Admitted For Heart Failure, Ankita Agarwal, Krishnaprasad Thirunarayan, William Romine, Amanuel Alambo, Mia Cajita, Tanvi Banerjee
Leveraging Natural Learning Processing To Uncover Themes In Clinical Notes Of Patients Admitted For Heart Failure, Ankita Agarwal, Krishnaprasad Thirunarayan, William Romine, Amanuel Alambo, Mia Cajita, Tanvi Banerjee
Computer Science and Engineering Faculty Publications
Heart failure occurs when the heart is not able to pump blood and oxygen to support other organs in the body as it should. Treatments include medications and sometimes hospitalization. Patients with heart failure can have both cardiovascular as well as non-cardiovascular comorbidities. Clinical notes of patients with heart failure can be analyzed to gain insight into the topics discussed in these notes and the major comorbidities in these patients. In this regard, we apply machine learning techniques, such as topic modeling, to identify the major themes found in the clinical notes specific to the procedures performed on 1,200 patients …
Electromagnetic Wave Absorption Of Coconut Fiber-Derived Porous Activated Carbon, Jemilat Yetunde Yusuf, Hassan Soleimani, Noorhana Yahya, Yekinni Kolawole Sanusi, Gregory Kozlowski, Andreas Öchsner, Lawal Lanre Adebayo, Fatai Adisa Wahaab, Surajudeen Sikiru, Bashiru Bolaji Balogun
Electromagnetic Wave Absorption Of Coconut Fiber-Derived Porous Activated Carbon, Jemilat Yetunde Yusuf, Hassan Soleimani, Noorhana Yahya, Yekinni Kolawole Sanusi, Gregory Kozlowski, Andreas Öchsner, Lawal Lanre Adebayo, Fatai Adisa Wahaab, Surajudeen Sikiru, Bashiru Bolaji Balogun
Physics Faculty Publications
In this study, porous carbon has been prepared through potassium hydroxide (KOH) activation of coconut fiber (CF) and subsequent carbonization in the presence of an inert gas. The activated carbons (AC) were prepared via carbonization of the precursor at different temperatures. Subsequently, their electromagnetic wave absorption (EMWA) performance was investigated at X-band frequency. The phase crystallinity, porous features, and degree of graphitization of the activated carbons were studied using XRD, nitrogen adsorption/desorption isotherm, and Raman spectroscopy, respectively. Using the BET method, the activated carbon prepared at 750 °C displayed a high specific surface area of 602.9 m2 g−1 and an …
Improving The Factual Accuracy Of Abstractive Clinical Text Summarization Using Multi-Objective Optimization, Amanuel Alambo, Tanvi Banerjee, Krishnaprasad Thirunarayan, Mia Cajita
Improving The Factual Accuracy Of Abstractive Clinical Text Summarization Using Multi-Objective Optimization, Amanuel Alambo, Tanvi Banerjee, Krishnaprasad Thirunarayan, Mia Cajita
Computer Science and Engineering Faculty Publications
While there has been recent progress in abstractive summarization as applied to different domains including news articles, scientific articles, and blog posts, the application of these techniques to clinical text summarization has been limited. This is primarily due to the lack of large-scale training data and the messy/unstructured nature of clinical notes as opposed to other domains where massive training data come in structured or semi -structured form. Further, one of the least explored and critical components of clinical text summarization is factual accuracy of clinical summaries. This is specifically crucial in the healthcare domain, cardiology in particular, where an …
Numerical Solutions To The Robin Inverse Problem With Nonnegativity Constraints, Weifu Fang, Fu-Rong Lin
Numerical Solutions To The Robin Inverse Problem With Nonnegativity Constraints, Weifu Fang, Fu-Rong Lin
Mathematics and Statistics Faculty Publications
We present iterative numerical methods for solving the inverse problem of recovering the nonnegative Robin coefficient from partial boundary measurement of the solution to the Laplace equation. Based on the boundary integral equation formulation of the problem, nonnegativity constraints in the form of a penalty term are incorporated conveniently into least-squares iteration schemes for solving the inverse problem. Numerical implementation and examples are presented to illustrate the effectiveness of this strategy in improving recovery results.
Improving Pain Assessment Using Vital Signs And Pain Medication For Patients With Sickle Cell Disease: Retrospective Study, Swati Padhee, Gary K. Nave Jr, Tanvi Banerjee, Daniel M. Abrams, Nirmish Shah
Improving Pain Assessment Using Vital Signs And Pain Medication For Patients With Sickle Cell Disease: Retrospective Study, Swati Padhee, Gary K. Nave Jr, Tanvi Banerjee, Daniel M. Abrams, Nirmish Shah
Computer Science and Engineering Faculty Publications
Background: Sickle cell disease (SCD) is the most common inherited blood disorder affecting millions of people worldwide. Most patients with SCD experience repeated, unpredictable episodes of severe pain. These pain episodes are the leading cause of emergency department visits among patients with SCD and may last for several weeks. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting a patient's pain intensity level. Objective: This study aims to learn deep feature representations of subjective pain trajectories using objective physiological signals collected from electronic health records. Methods: This study used electronic health record data collected …
Characterization Of A Family Of Rotationally Symmetric Spherical Quadrangulations, Lowell Abrams, Daniel Slilaty
Characterization Of A Family Of Rotationally Symmetric Spherical Quadrangulations, Lowell Abrams, Daniel Slilaty
Mathematics and Statistics Faculty Publications
A spherical quadrangulation is an embedding of a graph G in the sphere in which each facial boundary walk has length four. Vertices that are not of degree four in G are called curvature vertices. In this paper we classify all spherical quadrangulations with n-fold rotational symmetry (n ≥ 3) that have minimum degree 3 and the least possible number of curvature vertices, and describe all such spherical quadrangulations in terms of nets of quadrilaterals. The description reveals that such rotationally symmetric quadrangulations necessarily also have a pole-exchanging symmetry.
Entity-Driven Fact-Aware Abstractive Summarization Of Biomedical Literature, Amanuel Alambo, Tanvi Banerjee, Krishnaprasad Thirunarayan, Michael Raymer
Entity-Driven Fact-Aware Abstractive Summarization Of Biomedical Literature, Amanuel Alambo, Tanvi Banerjee, Krishnaprasad Thirunarayan, Michael Raymer
Computer Science and Engineering Faculty Publications
As part of the large number of scientific articles being published every year, the publication rate of biomedical literature has been increasing. Consequently, there has been considerable effort to harness and summarize the massive amount of biomedical research articles. While transformer-based encoder-decoder models in a vanilla source document-to-summary setting have been extensively studied for abstractive summarization in different domains, their major limitations continue to be entity hallucination (a phenomenon where generated summaries constitute entities not related to or present in source article(s)) and factual inconsistency. This problem is exacerbated in a biomedical setting where named entities and their semantics (which …
An Interactive Game With Virtual Reality Immersion To Improve Cultural Sensitivity In Healthcare, Paul J. Hershberger, Yong Pei, Timothy N. Crawford, Sabrina M. Neeley, Thomas Wischgoll, Dixit B. Patel, Miteshkumar M. Vasoya, Angie Castle, Sankalp Mishra, Lahari Surapaneni, Aman A. Pogaku, Aishwarya Bositty, Todd Pavlack
An Interactive Game With Virtual Reality Immersion To Improve Cultural Sensitivity In Healthcare, Paul J. Hershberger, Yong Pei, Timothy N. Crawford, Sabrina M. Neeley, Thomas Wischgoll, Dixit B. Patel, Miteshkumar M. Vasoya, Angie Castle, Sankalp Mishra, Lahari Surapaneni, Aman A. Pogaku, Aishwarya Bositty, Todd Pavlack
Computer Science and Engineering Faculty Publications
Purpose: Biased perceptions of individuals who are not part of one’s in-groups tend to be negative and habitual. Because health care professionals are no less susceptible to biases than are others, the adverse impact of biases on marginalized populations in health care warrants continued attention and amelioration. Method: Two characters, a Syrian refugee with limited English proficiency and a black pregnant woman with a history of opioid use disorder, were developed for an online training simulation that includes an interactive life course experience focused on social determinants of health, and a clinical encounter in a community health center utilizing virtual …
Chemical Thermodynamics—A Practical Wonderland, Rubin Battino, Trevor M. Letcher
Chemical Thermodynamics—A Practical Wonderland, Rubin Battino, Trevor M. Letcher
Chemistry Faculty Publications
Chemical thermodynamics is frequently thought of as being a hard subject and quite abstract. In fact, it is one of the most practical of subjects when you consider that the field of chemical engineering (responsible for endless useful applications) is effectively applied chemical thermodynamics. In this essay, examples of these applications are given, especially with respect to sustainability. The essay first considers the limits of thermodynamics and the constraints put on it in terms of the rigorous definitions of the principal function’s energy, entropy, and Gibbs energy.
Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Josh Larson, Scott L. Nykl, Clark N. Taylor, Thomas Wischgoll
Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Josh Larson, Scott L. Nykl, Clark N. Taylor, Thomas Wischgoll
Computer Science and Engineering Faculty Publications
Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding the nearest neighbor of a point in a reference 3D point set is a common operation in ICP and frequently consumes at least 90% of the computation time. We introduce a novel approach to performing the distance-based nearest neighbor step based on Delaunay triangulation. This greedy algorithm finds the nearest neighbor of a query point by traversing the edges of the Delaunay triangulation created from a reference 3D point set. Our work integrates the Delaunay traversal into the correspondences search of …
A History Of Wright State University's Department Of Geological Science, Paul J. Wolfe
A History Of Wright State University's Department Of Geological Science, Paul J. Wolfe
Earth and Environmental Sciences Faculty Publications
A history of Wright State University's disbanded and reintegrated Department of Geological Sciences written by department faculty member Paul J. Wolfe. Wolfe describes the development of the program, the faculty throughout the years, and the programs offered through the department.
Harmful Algal Blooms In Caesar Creek Lake And Their Relationship To Riparian Cover, Morgan C. Grunden
Harmful Algal Blooms In Caesar Creek Lake And Their Relationship To Riparian Cover, Morgan C. Grunden
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Caesar Creek Lake (CCL) in Warren County, OH has recently been experiencing harmful algal blooms (HABs) which are most likely attributed to an excess of phosphorus (P) from fertilizers and manures applied to surrounding fields. Sediments act as a sink for P later supplying a source of P in lakes for HABs when waters become thermally stratified and anoxic. This study seeks to determine the relationship between HABs in CCL and riparian cover at the main tributaries, Anderson Fork and Caesar Creek. In order to do this, sediment samples were collected from four sample sites along Anderson Fork and three …
Establishing A Machine Learning Framework For Discovering Novel Phononic Crystal Designs, Drew Feltner
Establishing A Machine Learning Framework For Discovering Novel Phononic Crystal Designs, Drew Feltner
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A phonon is a discrete unit of vibrational motion that occurs in a crystal lattice. Phonons and the frequency at which they propagate play a significant role in the thermal, optical, and electronic properties of a material. A phononic material/device is similar to a photonic material/device, except that it is fabricated to manipulate certain bands of acoustic waves instead of electromagnetic waves. Phononic materials and devices have been studied much less than their photonic analogues and as such current materials exhibit control over a smaller range of frequencies. This study aims to test the viability of machine learning, specifically neural …
Covalent Attachment Of Tadf Chromophores To Thermally Stable Poly(Arylene Ether)S, Samuel Farrar
Covalent Attachment Of Tadf Chromophores To Thermally Stable Poly(Arylene Ether)S, Samuel Farrar
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The covalent attachment of a blue emitting, benzothiazole based TADF chromophore into poly(arylene ether) backbone polymers was explored. A benzothiazole derivative, 2-(2,4-difluorophenyl)-benzothiazole (2,4-diF-BTZ), was synthesized to form the electrophilic component of the host polymer. Two polymers were synthesized to have chromophore incorporated, using 2,4-diFBTZ and 4,4-dihydroxydiphenyl ether (DPE) or 4,4’-biphenol (BP). The chromophore was covalently incorporated at a 10% molar ratio into the polymer backbone by copolymerization with 2,4-diF-BTZ and BP, utilizing nucleophilic aromatic substitution (NAS). Structural characterization was provided via NMR spectroscopy and GC/MS analysis. The polymer syntheses provided high molecular weight materials that were able to be cast …
Mercury Methylation In Oxic Sub-Polar Marine Regions Linked With Nitrification, Marissa Collins Despins
Mercury Methylation In Oxic Sub-Polar Marine Regions Linked With Nitrification, Marissa Collins Despins
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Methylmercury (MeHg) is a neurotoxin that bioaccumulates to potentially harmful concentrations in Arctic marine wildlife and in those that consume them. Monitoring and modeling MeHg bioaccumulation and biogeochemical cycling in the ocean requires understanding of the mechanisms behind net mercury (Hg) methylation. The key functional gene for Hg methylation, hgcAB, is widely distributed throughout ocean basins and spans multiple microbial phyla. While multiple microbially-mediated anaerobic pathways for Hg methylation are known, in the ocean, the majority of hgcA homologs have been found in oxic subsurface waters, in contrast to other ecosystems. In particular, microaerophilic Nitrospina, a genera of nitrite-oxidizing bacteria …