Physical Sciences and Mathematics Commons^™

Reducing Short-Chain Pfas Levels In California Water Supplies, Manu Prabandham

Pomona Senior Theses

This thesis proposes twelve specific policies based on precedents set by prior regulation of persistent organic pollutants (such as PCBs), the costs and benefits of short-chain PFAS, technologies available to remove and destroy short-chain PFAS, and the roles and limitations of California’s regulatory institutions. The twelve policies are chosen to be politically and financially feasible, effective at removing short-chain PFAS from water supplies, and equitable towards lower-income and minority Californians, who suffer the most from the consequences of PFAS and other environmental pollutants. The new definitions, education campaigns, studies, taxes, bans, standards, testing, and filtration systems proposed are intended to …

Mechanisms Of Dendritic Shorting In Lithium Metal Batteries With Li7la3zr2o12 Solid Electrolytes, Lukas Karapin-Springorum

Pomona Senior Theses

Energy storage will play a crucial role in efforts to mitigate the effects of climate change caused by greenhouse gas emissions from human activity. Lithium metal batteries using solid electrolytes like Li₇La₃Zr₂O₁₂ have higher energy density than lithium-ion batteries, which may enable a more rapid and complete electrification of transportation. However, lithium metal batteries suffer from undesirable short-circuiting when metallic lithium deposits connect the two electrodes. It has been debated whether these lithium dendrites generally grow directionally from the anode or are generated by the reduction of lithium ions inside the solid electrolyte, …

Generative Adversarial Networks For Music Generation, Harry Berman

Pomona Senior Theses

In this paper, we aim to harness a machine learning model called Genera- tive Adversarial Networks (GAN) in order to produce AI generated musical strands. The “Generative” part of the model’s name implies that its goal is to create something – music in the case of this paper – and the “Adversarial Networks” refer to the fact that there are two neural networks that learn from each other. One network attempts to trick the other one by creating music that it believes sounds real while the other tries to discern the real from the fake music. After training for long …

Multiview Outlier Filtered Pediatric Heart Sound Classification, Sagnik Dakshit

Computer Science Faculty Publications and Presentations

The advancements in deep learning has generated a large-scale interest in development of black-box models for various use cases in different domains such as healthcare, in both at-home and critical setting for diagnosis and monitoring of various health conditions. The use of audio signals as a view for diagnosis is nascent and the success of deep learning models in ingesting multimedia data provides an opportunity for use as a diagnostic medium. For the widespread use of these decision support systems, it is prudent to develop high performing systems which require large quantities of data for training and low-cost method of …

Concept Of Multifactor Method And Non-Functional Requirements Solution To Increase Resilience Through Functional Safety With Cybersecurity Analysis, Emilian Piesik, Marcin Sliwinski, Nary Subramanian, Janusz Zalewski

Computer Science Faculty Publications and Presentations

In the process of designing safety systems, an integrated approach in safety and cybersecurity analysis is necessary. The paper describes a new technique of increasing resilience through integrated analysis of functional safety and cybersecurity. It is a modeling methodology based on the combination of the multifactor method utilizing modified risk graphs, used previously for Safety Integrity Level (SIL) assessment, and the Non-Functional Requirements (NFR) approach. The NFR approach, based on the analysis of graphical representation of conceptual and physical components of the system, contributes a technique to include cybersecurity through the Softgoal Interdependency Graph. The assessment methodology is outlined in …

Fuzzy Convolution Neural Networks For Tabular Data Classification, Arun D. Kulkarni

Computer Science Faculty Publications and Presentations

Recently, convolution neural networks (CNNs) have attracted a great deal of attention due to their remarkable performance in various domains, particularly in image and text classification tasks. However, their application to tabular data classification remains underexplored. There are many fields such as bioinformatics, finance, medicine where non-image data are prevalent. Adaption of CNNs to classify non-image data remains highly challenging. This paper investigates the efficacy of CNNs for tabular data classification, aiming to bridge the gap between traditional machine learning approaches and deep learning techniques. We propose a novel framework fuzzy convolution neural network (FCNN) tailored specifically for tabular data …

Using Virus Like Particle Conjugates Of Synthetic Targeting Compounds To Deliver Chemotherapeutic Drugs To Cancer Stem Cells, Austen W. Kerzee

Chemistry Theses

Cancer stem cells are a type of cell that have the properties of both cancer cells and stem cells. They can differentiate into other types of cancer cells, are resistant to conventional chemotherapeutics, and seem to contribute greatly to the metastasis and recurrence of cancer. Due to these properties, eliminating cancer stem cells would be greatly beneficial in the treatment of cancer. While there have been approved therapeutic methods for the removal of a few of the cancer stem cells types, treatment for most types of cancer stem cells are still in the experimental phase and have yet to be …

On Stratified Single-Valued Soft Topogenous Structures, Fahad Alsharari, Yaser Saber, Hanan Alohali, Mesfer H. Alqahtani, Mubarak Ebodey, Tawfik Elmasry, Jafar Alsharif, Amal F. Soliman, Florentin Smarandache, Fahad Sikander

Branch Mathematics and Statistics Faculty and Staff Publications

This paper presents novel concepts including stratified single-valued neutrosophic soft topogenous (stratified svns-topogenous), stratified single-valued neutrosophic soft filter (stratified svns-filter), stratified single-valued neutrosophic soft quasi uniformity (stratified svnsq-uniformity) and stratified single-valued neutrosophic soft quasi proximity (stratified svnsq-proximity). Additionally, we present the idea of single-valued neutrosophic soft topogenous structures, formed by integrating svns-topogenous with svns-filter, and discuss their properties. Furthermore, we explore the connections between these single-valued neutrosophic soft topological structures and their corresponding stratifications.

A Compact Exploration Of Turiyam Neutrosophic Competition Graphs, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Graph theory, a branch of mathematics, examines relationships between entities using vertices and edges. Within this field, Uncertain Graph Theory has emerged to model uncertainties in real-world networks. A notable concept in this area is the competition graph, which captures interactions by connecting vertices that “compete” for the same neighbor, represented by directed edges indicating common neighbors in a digraph. This brief paper introduces the concept of the Generalized Turiyam Neutrosophic Competition Graph and explores its relationships with other graph classes.

Numerical Investigation And Statistical Analysis Of The Flow Patterns Behind Square Cylinders Arranged In A Staggered Configuration Utilizing The Lattice Boltzmann Method, M. Abid, N. Yasin, M. Saqlain, S. Ul-Islam, S. Ahmad

Mathematics & Statistics Faculty Publications

Flow past bluff bodies like square cylinders is important in engineering applications, but flow patterns behind staggered cylinder arrangements remain poorly understood. Existing studies have focused on tandem or side-by-side configurations, while offset orientations have received less attention. The aim of this paper is to numerically investigate flow dynamics and force characteristics behind two offset square cylinders using the single relaxation time lattice Boltzmann method. The effects of changing both the Reynolds number (Re = 1-150) and gap spacing ratio (g* = 0.5-5) between the cylinders are analyzed. Instantaneous vorticity contours, time histories of drag and lift coefficients, power spectra …

Shadow Hands: Solutions For Fermi Questions, September 2024, John Adam

Mathematics & Statistics Faculty Publications

The article titled "Shadow hands: Solutions for Fermi Questions, September 2024" discusses the enigmatic statement made by authors Dave Lynch and Bill Livingston in their book "Color and Light in Nature." The statement explains that the fuzzy outer edge of a shadow, known as the penumbra, is always a constant fraction of about 1/112 of its width divided by its distance from the object casting the shadow. The article provides a solution to Question 1, which asks for an explanation of this statement using elementary geometry. It also offers a solution to Question 2, which asks why the shadow of …

The Flesh And Silicon Mesh: A New Materialist Conception Of Advanced Digital Machines, Joshua Nieubuurt

English Faculty Publications

Digital machines, including artificial intelligence (AI), have long been held as potential agents of social change. From their binary role in cultural productions to the real-world implementation of such, digital machines have typically been considered within the Heideggerian “readiness-to-hand” category of Being. This paper seeks to alter conceptually this dynamic through the use of new materialism and Morton’s concept of the “mesh” to provide a new understanding of the social and pragmatic roles advanced digital machines play in ecologies in which they dwell and continue to emerge. Through briefly tracing the complex intermingling of advanced digital machines in the realms …

B(C₆F₅)₃ Co-Catalyst Promotes Unconventional Halide Abstraction From Grubbs I To Enhance Reactivity And Limit Decomposition, Austin W. Medley, Diya Patel, Calvin Utne, Trandon A. Bender

Chemistry & Biochemistry Faculty Publications

Ruthenium based Grubbs metathesis has become a commonplace reaction for synthetic chemists. Development of new generations of catalysts evolving from Grubbs I (GI) have led to greater stability, functional group compatibility, and superior reactivities. However, these advancements lead to increased costs. To this end, we report here how the addition of the commercially available tris(pentafluorophenyl)borane Lewis acid, which has become a common place catalyst in its own right, leads to enhanced reactivity of GI. Moreover, the increased reactivity arises via halide abstraction rather than traditional phosphine dissociation, providing ring-opening metathesis polymerization products that are divergent from those synthesized without the …

Toxicity Of Crude Oil-Derived Polar Unresolved Complex Mixtures To Pacific Herring Embryos: Insights Beyond Polycyclic Aromatic Hydrocarbons, Maxwell L. Harsha, Yanila Salas-Ortiz, Alysha D. Cypher, Ed Osborn, Eduardo Turcios Valle, Jacob L. Gregg, Paul K. Hershberger, Yuri Kurerov, Sarah King, Aleksandar I. Goranov, Patrick G. Hatcher, Anastasia Konefal, T. Erin Cox, Justin B. Greer, James P. Meador, Matthew A. Tarr, Patrick L. Tomco, David C. Podgorski

Chemistry & Biochemistry Faculty Publications

Crude oil toxicity to early life stage fish is commonly attributed to polycyclic aromatic hydrocarbons (PAHs). However, it remains unclear how the polar unresolved complex mixture (UCM), which constitutes the bulk of the water-soluble fraction of crude oil, contributes to crude oil toxicity. Additionally, the role of photomodification-induced toxicity in relation to the polar UCM is not well understood. This study addresses these knowledge gaps by assessing the toxicity of two laboratory generated polar UCMs from Cook Inlet crude oil, representing the readily water-soluble fraction of crude oil and photoproduced hydrocarbon oxidation products (HOPs), to Pacific herring (Clupea pallasii …

Antarctic Polar Stratospheric Cloud Analysis Of Ace-Fts Data From 2005 To 2023, M. Lecours, C. D. Boone, P. F. Bernath

Chemistry & Biochemistry Faculty Publications

We present an analysis of Antarctic polar winters from 2005 to 2023 as observed by the Atmospheric Chemistry Experiment (ACE). The unique broad band infrared spectral features in ACE “residual” spectra are used to classify the spectra of polar aerosols by composition into polar stratospheric clouds (PSCs) and sulfate aerosols. The spectra of PSCs are further classified into nitric acid trihydrate, supercooled ternary solutions, supercooled nitric acid, ice-mix, and mixtures of PSCs. A breakdown of PSC composition is presented for each year. Antarctic winter seasons with unusual compositions are: 2011, in which volcanic ash mixed with PSCs was observed from …

Machine-Learning-Enabled Diagnostics With Improved Visualization Of Disease Lesions In Chest X-Ray Images, Md. Fashiar Rahman, Tzu-Liang (Bill) Tseng, Michael Pokojovy, Peter Mccaffrey, Eric Walser, Scott Moen, Alex Vo, Johnny C. Ho

Mathematics & Statistics Faculty Publications

The class activation map (CAM) represents the neural-network-derived region of interest, which can help clarify the mechanism of the convolutional neural network’s determination of any class of interest. In medical imaging, it can help medical practitioners diagnose diseases like COVID-19 or pneumonia by highlighting the suspicious regions in Computational Tomography (CT) or chest X-ray (CXR) film. Many contemporary deep learning techniques only focus on COVID-19 classification tasks using CXRs, while few attempt to make it explainable with a saliency map. To fill this research gap, we first propose a VGG-16-architecture-based deep learning approach in combination with image enhancement, segmentation-based region …

Cumulative Distribution Function And Spatially Resolved Surface-Enhanced Raman Spectroscopy For The Quantitative Analysis Of Emtricitabine, Jana Hrncirova, Marguerite R. Butler, Sucharita Dutta, Meredith R. Clark, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) has exceptional analytical sensitivity and selectivity. However, SERS irreproducibility presents an obstacle when using it for precise quantitative measurements. In this study, colloidal nanoparticles evaporated to dryness are used as a SERS active surface for the detection of the HIV drug emtricitabine (FTC; trade name Emtriva). Despite the irreproducibility of the SERS resulting from the stochastic process of evaporation, using a SERS scanning instrument, the SERS enhancement factors of spatially resolved spectra have a well-defined distribution of signals for a given analyte concentration. This distribution follows a power law function ranging from weak (very abundant signals) …

Role Of Nitrogenous Functional Group Identity In Accelerating 1,2,3- Trichloropropane Degradation By Pyrogenic Carbonaceous Matter (Pcm) And Sulfide Using Pcm-Like Polymers, Han Cao, Jingdong Mao, Paul G. Tratnyek, Wenqing Xu

Chemistry & Biochemistry Faculty Publications

Groundwater contamination by 1,2,3-trichloropropane (TCP) poses a unique challenge due to its human toxicity and recalcitrance to degradation. Previous work suggests that nitrogenous functional groups of pyrogenic carbonaceous matter (PCM), such as biochar, are important in accelerating contaminant dechlorination by sulfide. However, the reaction mechanism is unclear due, in part, to PCM's structural complexity. Herein, PCM-like polymers (PLPs) with controlled placement of nitrogenous functional groups [i.e., quaternary ammonium (QA), pyridine, and pyridinium cations (py⁺)] were employed as model systems to investigate PCM-enhanced TCP degradation by sulfide. Our results suggest that both PLP-QA and PLP-py⁺ were highly effective …

Evaluating The Influence Of Trypanosomiasis On Murine Model Using Corchorus Olitorius Leaf Extract As A Trypanocidal Agent, Fatima M. Madaki, Adamu Y. Kabiru, Ogunrombi D. Clinton, Sakariyau A. Waheed, Yunusa O. Ibrahim

Chemistry & Biochemistry Faculty Publications

Trypanosomiasis, a parasitic disease caused by trypanosomes, which are flagellate protozoa transmitted through the bite of the tsetse fly, manifests with symptoms including substantial weight loss, anemia, fever, edema, adenitis, dermatitis, and nervous disorders. This research investigated the impact of trypanosomiasis on a murine model while utilizing Corchorus olitorius leaf extract as a potential trypanocidal agent. An acute toxicity analysis was conducted following Lorke's method, and the antitrypanosomal efficacy was assessed in rats at doses of 100, 200, and 400 mg/kg over three weeks, monitoring changes in parasitemia count, body weight, and hematological parameters. Additionally, lipid profile, electrolyte concentration, and …

Type-B Energetic Processes: Their Identification And Implications, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

We have now identified two thermodynamically distinct types (A and B) of energetic processes naturally occurring on Earth. Type-A energy processes, such as classical heat engines, apparently well follow the second law of thermodynamics; Type-B energy processes, such as the newly discovered thermotrophic function that isothermally utilizes environmental heat energy to perform useful work in driving ATP synthesis, follow the first law of thermodynamics (conservation of mass and energy) but do not have to be constrained by the second law, owing to their special asymmetric functions. Several Type-B energy processes such as asymmetric function-gated isothermal electricity production and epicatalysis have …

Examining The Effectiveness Of Oiled Ballast Water Treatment Processes: Insights Into Hydrocarbon Oxidation Product Formation And Environmental Implications, Maxwell L. Harsha, Danielle E. Verna, Yanila Salas-Ortiz, Eduardo Osborn, Eduardo Turcios Valle, Aleksandar I. Goranov, Patrick G. Hatcher, Ana M. Aguilar-Islas, Patrick L. Tomco, David C. Podgorski

Chemistry & Biochemistry Faculty Publications

Ballast water released from ships into coastal environments has been identified as a mechanism that introduces contaminants of concern into coastal ecosystems. This study investigates the treatment processes employed at a ballast water treatment facility in Valdez, Alaska, that remove hydrocarbons from unsegregated ballast water. Specifically, the aim is to quantify and characterize hydrocarbons of emerging concern, known as dissolved hydrocarbon oxidation products (HOPs) and heavy metals (HMs), throughout the treatment process. Specialized analytical techniques were employed, such as non-volatile dissolved organic carbon analysis, fluorescence spectroscopy, Fourier transform-ion cyclotron resonance-mass spectrometry, and inductively coupled plasma triple quadrupole mass spectrometry. Results …

The Ownership Of Potato Boy: A Discussion On Ai And Copyright, James Thibeault

Library Publications

Surprisingly, the copyright status of generative AI works is pretty straight forward in the US: no one owns the copyright. According to the United States Copyright Office (2023), “copyright can protect only material that is the product of human creativity. Most fundamentally, the term ‘author,’ which is used in both the Constitution and the Copyright Act, excludes non-humans.” This concept is not new as previous court cases had already established this ruling. In the 1884 court case Burrow-Giles Lithographic Company v. Sarony, the defendant made copies of a photograph and claimed the author held no copyright since a machine, a …

Sdgs And Circularity In Fashion Industry: Bruneian Perspective Based On Basic Values, Izzah Mohd Noor, Shahid Anjum

ASEAN Journal on Science and Technology for Development

The fashion industry is facing significant textile waste, with millions of textiles ending up in landfills annually. Overconsumption of textiles and clothes due to fast fashion trends has negative environmental impacts. Transitioning to a circular economy is crucial for minimizing environmental impact and addressing the Sustainable Development Goals (SDGs) in the United Nations' 2030 Agenda. This study investigates the adoption of Circular Economy practices and SDGs awareness in second-hand clothing. Using IBM SPSS Statistics Software and Ordinary Least Squares (OLS) regression, the study models consumer behaviors, and attitudes by investigating the influence of four key components from Schwartz's theory of …

Factors Influencing Consumers' Intention To Use Over-The-Top (Ott) Services: A Study In Brunei Darussalam, Hjh Faralisa Hj Zulfikri, Heru Susanto

ASEAN Journal on Science and Technology for Development

The market for over-the-top (OTT) services has witnessed significant growth and transformation, presenting new opportunities and challenges to service providers. This study aims to explore the factors that influence consumers' intention to use OTT services, focusing on the context of Brunei Darussalam. Drawing on the Technology Acceptance Model (TAM) as a theoretical framework, this study investigates the impact of perceived ease of use, perceived usefulness, innovativeness, service quality, information seeking, and entertainment on consumers' intention to use OTT services. A quantitative research approach was adopted and data were collected through an online survey conducted among the general public in Brunei …

The Effects Of Seaweed Farming On Local Ecosystems In The United States, Reid Cohen

Pitzer Senior Theses

In my thesis, I explore how seaweed farming contributes to the regeneration of marine ecosystems, supports biodiversity, and assists in harmful nutrient removal. Seaweed farming is a relatively unexplored industry in the United States with huge carbon capturing potential. Seaweed farming poses a significant opportunity for a project that has the potential to sequester carbon, increase biodiversity, protect coastal ecosystems, naturally clean water, provide biofuel capabilities, substitute as livestock fodder which then decreases methane emissions, along with many more benefits. Kelp supports biodiversity in marine ecosystems and provides essential habitats for various species. The seaweed farming industry holds profound potential …

Numerical Solution Of Hybrid Nanofluid And Its Stability Over Permeable Wedge Sheet With Heat Transfer Analysis, Aisha M. Alqahtani, Zeeshan, Waris Khan, Florentin Smarandache, Nidhal Becheikh, Roobaea Alroobaea, Taseer Muhammad

Branch Mathematics and Statistics Faculty and Staff Publications

The inclusion of nanoparticles has the potential to improve the thermal efficiency of the base fluid. The field of nanofluid (NF) dynamics has attracted important attention due to its extensive range of practical uses like fuel cells, solar energy, medication administration, heat transfer, microfabrication, coolant applications, and other related domains. The aim of this study is to scrutinize the impact of Lorentz force, thermal energy, joule heating, heat source and injection parameters, and Brownian and thermoporetic diffusions on the hybrid nanofluid over the moving wedge. The stability inquiry is reported for the existing work in order to confirm the stable …

Water Quality Contaminants Long-Term Spatial Analysis Along The Upper Clark Fork River Superfund Site Between Warm Springs And Garrison, Montana, Raegan Michele Osentowski

Undergraduate Theses, Professional Papers, and Capstone Artifacts

Long-term data of heavy metal contaminants, cadmium, copper, lead, arsenic, and zinc were compiled from the Montana Department of Environmental Quality, DEQ, and the United States Geological Survey, USGS, to investigate the effects of remediation on water quality along the upper Clark Fork River superfund site. Long-term data sets were analyzed at CFR-03A, CFR-27H, CFR-34, and SS-25 along the upper Clark Fork River and Silver Bow Creek. CFR-03A and CFR-27H had full remediation in the immediate vicinity, SS-25 had on-going remediation in the immediate vicinity, and CFR-34 had no remediation in the immediate vicinity. Analysis of heavy metal contaminants is …

A Data-Driven Machine Learning Approach For Electron-Molecule Ionization Cross Sections, Allison Harris, Josh Nepomuceno

Faculty publications – Physics

Despite their importance in a wide variety of applications, the estimation of ionization cross sections for large molecules continues to present challenges for both experiment and theory. Machine learning (ML) algorithms have been shown to be an effective mechanism for estimating cross section data for atomic targets and a select number of molecular targets. We present an efficient ML model for predicting ionization cross sections for a broad array of molecular targets. Our model is a 3-layer neural network that is trained using published experimental datasets. There is minimal input to the network, making it widely applicable. We show that …

121, Scott Brande

All 3D Rock Models

Model 121 - granite - igneous rock

SketchFab link: https://sketchfab.com/3d-models/121-e1e6025763a1493085ee2d9f63c641dd

163, Scott Brande

All 3D Rock Models

Model 163 - bituminous coal - sedimentary rock

SketchFab link: https://sketchfab.com/3d-models/163-c2903dfb82bc4f05bf7b3556edf8d4ef