Physical Sciences and Mathematics Commons^™

Cellular Sorting Of The Dictyostelium Discoideum Slug, Erin Flowerday

Theses and Dissertations

Dictyostelium discoideum (Dd) cells are amoeba cells that feed on soil or plant leaf matter bacteria. They divide freely in the presence of food. When starved, cell division is ended, and cells transition from unicellular to multicellular organisms initiated by a chemoattractant, cyclic adenosine monophosphate (cAMP). This study intricately examines cellular sorting within the Dd slug, focusing on individual cell dynamics. Represented as oriented ellipsoids, these cells maintain constant volume through a viscoelastic structure. Applying force to specific semi-axes reveals predictable deformations, highlighting the relationship between force and deformation rate. Manipulating damping coefficients and spring constants uncovers insights into cell …

Modular Approach To Soft Mobile Robots, Dimuthu Kodippili Arachchige

College of Computing and Digital Media Dissertations

Soft robot locomotion is a highly promising but under-researched subfield within the field of soft robotics. The compliant limbs and bodies of soft robots offer numerous benefits, including the ability to regulate impacts, tolerate falls, and navigate through tight spaces. These robots have the potential to be used for various applications, such as search and rescue, inspection, surveillance, and more. The state-of-the-art still faces many challenges, including limited degrees of freedom, a lack of diversity in gait trajectories, insufficient limb dexterity, limited payload capabilities, lack of control methods, etc. To address these challenges, this research introduces a modular approach to …

Bootstrap Methods For Bias-Correcting Probability Distribution Parameters Characterizing Extreme Snow Accumulations, Kenneth Pomeyie, Brennan Bean

Mathematics and Statistics Student Research and Class Projects

Accurately quantifying the threat of collapse due to the weight of settled snow on the roof of a structure is crucial for ensuring structural safety. This quantification relies upon direct measurements of the snow water equivalent (SWE) of settled snow, though most weather stations in the United States only measure snow depth. The absence of direct load measurements necessitates the use of modeled estimates of SWE, which often results in the underestimation of the scale/variance parameter of the distribution of annual maximum SWE. This paper introduces a novel bias correction method that employs a bootstrap technique with regression-based models to …

Investigating Cloth Sculpting For Simulation Control In Virtual Reality, Matthew S. Bishop

Theses and Dissertations

Artists require control and predictability over physically based simulations to create their required animation. This control can lead to reduced iteration time to get the desired simulation results. Controlling cloth simulations can require manual effort to create goal keyframes for control algorithms to match. Current techniques and research utilize a keyboard and mouse to create these goal keyframes. Other research has looked at using a virtual reality (VR) head-mounted display with controllers to improve the experience of completing similar animation tasks. However, we are not aware of any research that attempts to use VR as a tool to assist artists …

De Novo Synthetic Studies On Tetracyclic Triterpenoid Systems: Stereoselective Preparation, Biological Evaluation And Total Syntheses Of Euphol And Tirucallol, Joshua Nicholson

Dartmouth College Ph.D Dissertations

Tetracyclic triterpenoids have a rich history in biology, medicine, and chemistry. In terms of pharmaceutical relevance, compounds with this scaffold are one of the most successful classes with over 100 FDA approved examples. Despite this success, the vast majority of compounds within this class are prepared through semisynthesis. While this approach is undeniably successful, judged by the sheer number of medications generated, it also has limitations. Namely, semisynthesis requires the use of complex starting materials that have fixed absolute stereochemistry and often sparse functionality. One approach to address the inherent limitations with semisynthesis is through de novo synthesis. Recently, our …

Ai-Based Methods For Detecting And Classifying Age-Related Macular Degeneration: A Comprehensive Review, Niveen Nasr El-Den, Mohamed Elsharkawy, Ibrahim Saleh, Mohammed Ghazal, Ashraf Khalil, Mohammad Z. Haq, Ashraf Sewelam, Hani Mahdi, Ayman El-Baz

All Works

This paper explores the advancements and achievements of artificial intelligence (AI) in computer vision (CV), particularly in the context of diagnosing and grading age-related macular degeneration (AMD), one of the most common leading causes of blindness and low vision that impact millions of patients globally. Integrating AI in biomedical engineering and healthcare has significantly enhanced the understanding and development of the CV application to mimic human problem-solving abilities. By leveraging AI-based models, ophthalmologists can improve the accuracy and speed of disease diagnosis, enabling early treatment and mitigating the severity of the conditions. This paper presents a comprehensive analysis of many …

A Review Of Stable, Traversable Wormholes In F(R) Gravity Theories, Ramesh Radhakrishnan, Patrick Brown, Jacob Matulevich, Eric Davis, Delaram Mirfendereski, Gerald Cleaver

Physics & Astronomy Faculty Publications

It has been proven that in standard Einstein gravity, exotic matter (i.e., matter violating the pointwise and averaged Weak and Null Energy Conditions) is required to stabilize traversable wormholes. Quantum field theory permits these violations due to the quantum coherent effects found in any quantum field. Even reasonable classical scalar fields violate the energy conditions. In the case of the Casimir effect and squeezed vacuum states, these violations have been experimentally proven. It is advantageous to investigate methods to minimize the use of exotic matter. One such area of interest is extended theories of Einstein gravity. It has been claimed …

A Machine Learning Based Approach For The Identification Of Fake Bills, Tianyang Lu, Hongyang Pang

Rose-Hulman Undergraduate Mathematics Journal

Fake or counterfeiting currency, which has been around as long as money has existed, is a major economic problem. Since the US dollar is the most popular form of currency globally, it is the most popular currency to counterfeit. The United States Department of Treasury estimates that between $70 million and $200 million in fake bills are in circulation. The Federal Reserve Bank uses special banknote processing systems to count each bill deposited by the bank and examine them for the possibility of counterfeits. These machines have sensors designed to detect general quality of the bills, including paper type, quality …

Charlotte: A Modern Tool For Cave Surveying, Luca Tringali Mr., Giacomo Canciani Dr., Alexander Debenjak, Tecla Tripari

International Journal of Speleology

The future of cave surveying is a full 3D scan, as automatic as possible, capturing all morphologically relevant details. However, the vast majority of cavers are still using tools designed more than 15 years ago. The advancements in tools for architects, CAD designers, programmers of VR and robotics could be helpful also for the caving community. That’s why Charlotte, a cheap DIY 2.5D scanner designed for cave surveying, was developed and built. To demonstrate its capabilities, a new survey of Grotta Regina del Carso cave (cad. nr. 2328/4760VG), the biggest cave in the Gorizia Karst, has been realized and published. …

Maximizing Legged Accelerations: A Matter Of Force, Time, And Gravity, Lance Brooks

Applied Physiology and Wellness Theses and Dissertations

Sprint running accelerations require runners to apply surface forces that: support body weight by pushing downward, accelerate the body horizontally by pushing backward, and align the direction of the push with the body’s mass center to maintain balance and posture, which imposes an upper limit on the average forward acceleration force equal to the average gravitational force (1.0 G) acting on the runner. This expectation arises from the mechanical constraints imposed by the need to generate sufficient vertical force to support body weight against gravity while simultaneously producing horizontal force to accelerate forward and aligning the push through the center …

Uncertainty Quantification In Machine Learning Models Via Gaussian Process Regression: A Comparative Study, Ayorinde E. Olatunde, Weiqi Yue, Pawan K. Tripathi, Roger H. French, Anirban Mondal

Faculty Scholarship

As the use of Machine learning models in science and engineering continues to increase, there is an increasing need for quantifying the uncertainties inherent in the predictions of these models. The more complex a model is, the more the uncertainties in its predictions increase. Amongst the plethora of methodologies used in quantifying uncertainties lies Gaussian Process Regression (GPR). GPR surmounts some of the popular shortfalls of other state-of-the-art methodologies. Although GPR has some quick wins in its application for uncertainty quantification, it is plagued with some shortfalls, such as scalability issues when the feature space increases as well as an …

Constraints On Solar Axions Using The Profile Likelihood Ratio Method With The Supercdms Experiments, Shilun Liu

Physics Theses and Dissertations

Dark matter plays an essential role in understanding modern physics and particles beyond the Standard Model. Evidence suggests that dark matter accounts for approximately 85% of the universe’s matter, and 26.8% of its mass-energy composition. Key candidates for dark matter include unidentified subatomic particles like Weakly Interacting Massive Particles (WIMPs) and axions. The Super Cryogenic Dark Matter Search (SuperCDMS) employs direct detection methods to identify these elusive particles using cryogenic technologies. Su- perCDMS Soudan is the latest completed CDMS experiment in Minnesota, in preparation for the next phase experiments of SuperCDMS SNOLAB in Sudbury, Canada. At SNOLAB, the Cryogenic Underground …

Projected Climate Change Impacts On The Number Of Dry And Very Heavy Precipitation Days By Century’S End: A Case Study Of Iran’S Metropolises, Rasoul Asfari, Mohammad Nazari-Sharabian, Ali Hosseini, Moses Karakouzian

Civil and Environmental Engineering and Construction Faculty Research

This study explores the impacts of climate change on the number of dry days and very heavy precipitation days within Iran’s metropolises. Focusing on Tehran, Mashhad, Isfahan, Karaj, Shiraz, and Tabriz, the research utilizes the sixth phase of the Coupled Model Intercomparison Project (CMIP6) Global Circulation Models (GCMs) to predict future precipitation conditions under various Shared Socioeconomic Pathways (SSPs) from 2025 to 2100. The study aims to provide a comprehensive understanding of how climate change will affect precipitation patterns in these major cities. Findings indicate that the SSP126 scenario typically results in the highest number of dry days, suggesting that …

Bayesian And Deep Generative Modeling In Immunology, Yuqiu Yang

Statistical Science Theses and Dissertations

Due to the accumulation of a large volume of data of different natures such as sequencing data, proteomics data, and clinical data, statistical methods and deep learning algorithms have become increasingly important in the field of immunology. By leveraging the diverse datasets as well as interdisciplinary knowledge from areas like biology and public health, these quantitative methods have revolutionized this field by providing powerful tools for data analysis, modeling, and prediction. This has led to a deeper understanding of the immune system, accelerated the development of novel therapies, and paved the way for personalized and precision medicine approaches in immunology. …

Atlantic Richfield Company Discharge System 2023 Data Quality Assessment Berkeley Pit And Discharge Pilot Project Silver Bow Creek/Butte Area Npl Site Butte Mine Flooding Operable Unit, Wsp Environment & Infrastructure, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Knowledge Management And Semantic Reasoning: Ontology And Information Theory Enable The Construction Of Knowledge Bases And Knowledge Graphs, Quynh D. Tran, Ozan Dernek, Erika I. Barcelos, Laura S. Bruckman, Roger H. French

Researchers, Instructors, & Staff Scholarship

FAIR (Findable, Accessible, Interoperable, Reusable) principles are guidelines Wilkinson, et. al. (2016) proposed for data governance and stewardship. Ontology is a powerful tool that can achieve many aspects of all four FAIR principles. Unfortunately, there is a misconception about ontology that it is only useful for establishing FAIR data. We need to think beyond data to answer the question “So what?” after an ontology is developed. It is critical to apply FAIR principles to results, analysis, and models, which is where the concept of digital thread comes in. FAIRified results, analysis, and models can be stored in a knowledge base …

Knowledge Management Of Historical Data: Ontology Development For Chemical Reactions, Quynh D. Tran, Alexander Harding Bradley, Balashanmuga Priyan Rajamohan, Jonathan E. Gordon, Van D. Tran, Kiefer Lin, Erika I. Barcelos, Laura S. Bruckman, Roger H. French

Researchers, Instructors, & Staff Scholarship

Knowledge management of the literature and historical data is critical to accelerated drug and materials discovery. Currently, literature knowledge is scattered in journal articles in various formats: diagrams, texts, plots, etc. Historical data from past experiments are saved in a number of local computers under confusing folder structures with ambiguous file names. To manage and organize historical data and knowledge, our group (SDLE) at CWRU follows FAIR (Findable, Accessible, Interoperable, Reusable) principles, which outline the best practices for data stewardship and data provenance, and ontology, a formal representation of terms and concepts and their relationships, as a tool to improve …

Bayesian Variational Inference In Keyword Identification And Multiple Instance Classification, Yaofang Hu

Statistical Science Theses and Dissertations

This dissertation investigates (1) Variational Bayesian Semi-supervised Keyword Extraction and (2) Variational Bayesian Multimodal Multiple Instance Classification.

The expansion of textual data, stemming from various sources such as online product reviews and scholarly publications on scientific discoveries, has created a demand for the extraction of succinct yet comprehensive information. As a result, in recent years, efforts have been spent in developing novel methodologies for keyword extraction. Although many methods have been proposed to automatically extract keywords in the contexts of both unsupervised and fully supervised learning, how to effectively use partially observed keywords, such as author-specified keywords, remains an under-explored …

A Fair Ontology For Aps Beamline Experiments, Gabriel Ponón, Balashanmuga Priyan Rajamohan, Mohommad Redad Mehdi, Finley Holt, Erika Barcelos, Pawan K. Tripathi, Roger H. French

Student Scholarship

Data produced at the 1-ID beamline APS are often serialized in large, disconnected tables, which can impede the effective reuse and replication of analysis performed for cutting edge research and instrumentation conducted at the facility. This poster describes an alternative approach of utilizing component-based FAIR (Findable, Accessible, Interoperable, and Reusable) ontologies as a framework for organizing and connecting experimental variables. Three packages were developed to facilitate the creation and connection of component ontologies into a fully connected FAIR ontology for an experiment. An ontology-based workflow is also discussed for beamline scientists and users to visualize and connect collected values alongside …

Enhancing Fundraising Strategies In Higher Education Through Machine Learning, Laith Alatwah

Electrical Engineering Theses

This thesis presents a comprehensive application of machine learning techniques, namely Fine Gaussian SVM and RUS Boosted Trees, to enhance fundraising strategies in higher education institutions. Analyzing a rich dataset from Blackbaud Raiser's Edge NXT, spanning 2012 to 2022, the study focuses on donor profiles, including demographics, donation history, and engagement patterns. Key demographic insights include the increasing engagement of younger donors (20-29 age group) and significant contributions from older donors (70-99 age group). Geographical trends are also examined, revealing distinct patterns based on donors' city, state, and ZIP code. The Fine Gaussian SVM model demonstrates moderate discriminatory power, with …

I. Degradable Polymers And Networks Based On Furan-Maleimide Diels-Alder Reactions Of Silyl Ether Derivatives And Maleimides, And Ii. The Michael Addition Of Amines To 1,3,5-Triacryloylhexahydro-1,3,5-Triazine (Tat) As A Synthetic Route To Novel Chelating Agents, Reyad Alkhazalah

Chemistry Theses and Dissertations

Degradable Polymers and Networks Based on Furan-Maleimide Diels-Alder Reactions of Silyl Ether Derivatives and Maleimides. I.

I. Part 1. Two groups of silyl ether monomers, A and B, were synthesized, each containing four different monomers. The monomers of group A were obtained by reacting furfuryl alcohol with four dichlorosilanes with varying siloxane spacers. The monomers of group B were obtained by reacting n-(2-hydroxyethyl)maleimide (HEMI-1c) with the same four dichlorosilanes. Each monomer from group A was individually reacted with each monomer from group B via a Diels-Alder reaction to produce a series of sixteen degradable linear polymers with a variety …

Investigation Of The Prevalence Of Fentanyl Analogs In A Drug Testing Population Using Liquid Chromatography Tandem Mass Spectrometry (Lc-Ms-Ms), Ivan Cordova

Student Theses

This study serves to determine the prevalence of novel fentanyl analogs that are present within a drug testing population in New York State. Samples were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS) to qualitatively determine the presence of various possible fentanyl analogs. The sample preparation of this assay consisted of a simple dilute and shoot. This method of sample preparation can be quicker, eliminating sample preparation times as well as being less financially strenuous to clinical laboratories as it eliminates the need for various solvents and solid/liquid phase cartridges. The assay was aimed to see if analytes can be …

A ‘Nuclear Bomb’ Or Just ‘A Joke’? Groundwater Models May Help Communicate Nuanced Risks To The Great Salt Lake, Matthew D. Laplante, Piyush Dahal, Shih-Yu Simon Wang, Kirsti Hakala, Avik Mukherjee

Plants, Soils, and Climate Faculty Publications

The Great Salt Lake entered the zeitgeist of environmental concern in 2022 when a coalition of scientists and activists warned in a highly publicized report that the lake might be just five years away from complete desiccation, a possibility one state official warned was tantamount to an “environmental nuclear bomb”. Shortly thereafter, an unpredicted and unprecedented pluvial winter resulted in an increase in inflow, temporarily halting the lake’s decline and prompting Utah’s governor to mock the dire prediction as “a joke”, an outcome that speaks to the tension between agenda-setting and trust-building that researchers face when sharing worst-case warnings, particularly …

Enhancing Clinical Relevance Of Pretrained Language Models Through Integration Of External Knowledge: Case Study On Cardiovascular Diagnosis From Electronic Health Records

Faculty, Staff and Student Publications

Background: Despite their growing use in health care, pretrained language models (PLMs) often lack clinical relevance due to insufficient domain expertise and poor interpretability. A key strategy to overcome these challenges is integrating external knowledge into PLMs, enhancing their adaptability and clinical usefulness. Current biomedical knowledge graphs like UMLS (Unified Medical Language System), SNOMED CT (Systematized Medical Nomenclature for Medicine-Clinical Terminology), and HPO (Human Phenotype Ontology), while comprehensive, fail to effectively connect general biomedical knowledge with physician insights. There is an equally important need for a model that integrates diverse knowledge in a way that is both unified and compartmentalized. …

Influence Of Phosphate And Boron Addition To Mixed Liquid Fertilizer On The Growth And Yield Of Red Chili Cultivated In The Subsoil Layer, Stefina Liana Sari, Emma Trinurani Sofyan, Anni Yuniarti

Jurnal Kultivasi

This study assesses the impact of adding phosphate and boron in a mixed liquid fertilizer (MLF) on the growth and yield of red chili plants cultivated in a subsoil environment. The experiment was conducted to comprehend how these nutrients affect the performance of red chili plants, particularly when cultivated in less ideal conditions such as subsoil, a remnant of excavation for brick production. The research was carried out at the Ciparanje Garden of the Faculty of Agriculture, Universitas Padjadjaran. The research design employed a Randomized Completely Block Design with the following treatments: A = Control (degraded soil without fertilizer), B …

Application Of Machine Learning For Multi-Omics Data Integration, Dhoha Abid

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditionally, machine learning (ML) is used to train a model to predict scores for instances that were not seen by the model during training. In this conventional use of ML, the model is trained to learn general patterns that relate features to labels, so it can predict accurate scores for unseen data. Here, we use ML, unconventionally, to integrate different types of noisy data. Specifically, for biological investigations, in which there is no mean to measure a ground truth. We propose to train a ML model to predict scores on the same instances that were used in its training. In …

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Applications For Metabolomics, Darcy Cochran, Robert Powers

Robert Powers Publications

Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (10⁵–10⁶) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the …

Madelung Mechanics And Superoscillations, Mordecai Waegell

Mathematics, Physics, and Computer Science Faculty Articles and Research

In single-particle Madelung mechanics, the single-particle quantum state Ψ(⃗x, t) = R(⃗x, t)eiS(⃗x,t)/h is interpreted as comprising an entire conserved fluid of classical point particles, with local density R(⃗x, t)2 and local momentum ⃗∇S(⃗x, t) (where R and S are real). The Schrödinger equation gives rise to the continuity equation for the fluid, and the Hamilton–Jacobi equation for particles of the fluid, which includes an additional density-dependent quantum potential energy term Q(⃗x, t) = − ¯h2 2m ⃗∇R(⃗x,t) R(⃗x,t) , which is all that makes the fluid behavior nonclassical. In particular, the quantum potential can become negative and create a …

On Q^*-Closed Sets In Fuzzy Neutrosophic Τopology: Principles, Proofs, And Examples, Hajar Y. Mohammed, Fatimah M. Mohammed, Ghada Al-Mahbashi

Neutrosophic Systems with Applications

This paper aims to present a new concept of sets known as fuzzy neutrosophic Q^*-closed sets in fuzzy neutrosophic topology. In this study, we explore and investigate more novel properties of these classes by some new definitions, theorems, and propositions. Therefore, a group of examples is presented and discussed to clarify the relationships between the new study of Q^*-closed sets with other sets.

Evaluation Of Mechanical Vapor Recompression And Easy Multi-Effect Desalination Systems In Different Climate Conditions-Sensitivity And 7e Analysis, Hamed Kariman, Mehdi Khiadani, Siamak Hoseinzadeh, Shahin Shoeibi, Abdellah Shafieian

Research outputs 2022 to 2026

Evaporative desalination systems, such as Multi-Effect Desalination (MED) and Mechanical Vapor Recompression (MVR), play important roles in addressing this challenge. Although large-scale desalination systems possess limitations in catering to the water demands of remote regions and islands and entail the cost of water transportation to residential areas, it is imperative to concentrate on studying the feasibility of employing centralized evaporative water production systems. Firstly, in this study, the initial focus is on conducting energy and exergy analyses of MVR and Easy MED systems, with a goal of enhancing knowledge about the energy consumption, exergy destruction and exergetic efficiency of these …