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Full-Text Articles in Physical Sciences and Mathematics

Optimal Ordering To Maximize Mev Arbitrage, Granton Michael White Jun 2023

Optimal Ordering To Maximize Mev Arbitrage, Granton Michael White

Theses and Dissertations

The rise of cryptocurrencies has brought with it new math problems with new sets of constraints. The MEV problem entails solving for the ordering of pending trades that maximizes a block creator's profit. In decentralized finance, time is a big constraint, so an exhaustive search of all possible orderings is impossible. I propose a solution to the MEV problem that gives a near optimal result that can be solved in a reasonable amount of time. I layout the method and the formulas required for my solution. Additionally, I test my solution on synthesized data to show that it works as …

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Hamiltonian Monte Carlo For Reconstructing Historical Earthquake-Induced Tsunamis, Jacob Paul Callahan Jun 2023

Hamiltonian Monte Carlo For Reconstructing Historical Earthquake-Induced Tsunamis, Jacob Paul Callahan

Theses and Dissertations

In many areas of the world, seismic hazards pose a great risk to both human and natural populations. In particular, earthquake-induced tsunamis are especially dangerous to many areas in the Pacific. The study and quantification of these seismic events can both help scientists better understand how these natural hazards occur and help at-risk populations make better preparations for these events. However, many events of interest occurred too long ago to be recorded by modern instruments, so data on these earthquakes are sparse and unreliable. To remedy this, a Bayesian method for reconstructing the source earthquakes for these historical tsunamis based …

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A Structural Analysis Of The Simpson Mountains, Hyrum A. Briscoe Jun 2023

A Structural Analysis Of The Simpson Mountains, Hyrum A. Briscoe

Theses and Dissertations

The Simpson Mountains have long been of economic interest and have renewed interest in their potential value. Field mapping of the project area redefined structural relationships between stratigraphic units. Geometric and kinematic analysis of structures in the Simpson Mountains show the range is deformed by the three most recent tectonic events: the Sevier Orogeny, the Laramide Orogeny, and Basin and Range Extension. Laramide structures define the range with a significant E-W normal fault and an E-W thrust fault, which are both likely related to Eocene-age igneous intrusions. Principal component analysis (PCA) of regional quartzite X-ray Fluorescence (XRF) data resulted in …

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Non-Tuberculous Mycobacterium Correlation With Geochemical Characteristics Of Soil And Basalt In Hawaii, Leeza Marie Wells Jun 2023

Non-Tuberculous Mycobacterium Correlation With Geochemical Characteristics Of Soil And Basalt In Hawaii, Leeza Marie Wells

Theses and Dissertations

Non-tuberculous mycobacteria (NTM) cause opportunistic lung disease though environmental exposure pathways. Among the United States, Hawaii has a significantly higher infection rate. Preliminary studies have shown certain environmental factors, such as phosphorus and other select soil geochemical characteristics, to be statistically significant to NTM occurrence. However, a model to predict NTM occurrence based on soil geochemistry had yet to be attempted. A selection of 40 NTM positive and 40 NTM negative soils from Oahu were selected for a geochemical analysis to search for possible correlations to mineralogy and elemental abundances that may promote, or inhibit, NTM growth in the environment. …

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Dd Slug Migration: Mathematical Model And Numerical Results, Joy Song May 2023

Dd Slug Migration: Mathematical Model And Numerical Results, Joy Song

Theses and Dissertations

Amoebae are commonly studied to understand embryogenesis, and the best-characterized amoebozoan species is Dictyostelium discoideum (Dd). Dd has a very simple life cycle with a range of developmental stages, among which we are most interested in the stage of a migrating slug. It has been observed that different sizes of Dd slugs maintain a proportional distribution of prestalk cells and prespore cells: prestalk cells occupy the anterior 20% of the slug, while prespore cells occupy the posterior 80%. However, it remains unknown how the migrating slug forms and preserves this anterior-posterior proportional pattern under so many different dynamics including cell …

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Recommending Answers To Math Questions Using Kl-Divergence And The Approximate Xml Tree Matching Approach, Siqi Gao May 2023

Recommending Answers To Math Questions Using Kl-Divergence And The Approximate Xml Tree Matching Approach, Siqi Gao

Theses and Dissertations

Mathematics is the science and study of quality, structure, space, and change. It seeks out patterns, formulates new conjectures, and establishes the truth by rigorous deduction from appropriately chosen axioms and definitions. The study of mathematics makes a person better at solving problems. It gives someone skills that (s)he can use across other subjects and apply in many different job roles. In the modern world, builders use mathematics every day to do their work, since construction workers add, subtract, divide, multiply, and work with fractions. It is obvious that mathematics is a major contributor to many areas of study. For …

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A Method Of Reconstructing Historical Destructive Landslides Using Bayesian Inference, Raelynn Wonnacott May 2023

A Method Of Reconstructing Historical Destructive Landslides Using Bayesian Inference, Raelynn Wonnacott

Theses and Dissertations

Along with being one of the most populated regions of the world, Indonesia has one of the highest natural disaster rates worldwide. One such natural disaster that Indonesia is particularly prone to are tsunamis. Tsunamis are primarily caused by earthquakes, volcanoes, landslides and debris flows. To effectively allocate resources and create emergency plans we need an understanding of the risk factors of the region. Understanding the source events of destructive tsunamis of the past are critical to understanding the these risk factors. We expand upon previous work focusing on earthquake-generated tsunamis to consider landslide-generated tsunamis. Using Bayesian inference and modern …

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"I Think They're Poisoning My Mind": Understanding The Motivations Of People Who Have Voluntarily Adopted Secure Email, Warda Usman May 2023

"I Think They're Poisoning My Mind": Understanding The Motivations Of People Who Have Voluntarily Adopted Secure Email, Warda Usman

Theses and Dissertations

Secure email systems that use end-to-end encryption are the best method we have for ensuring user privacy and security in email communication. However, the adoption of secure email remains low, with previous studies suggesting mainly that secure email is too complex or inconvenient to use. However, the perspectives of those who have, in fact, chosen to use an encrypted email system are largely overlooked. To understand these perspectives, we conducted a semi-structured interview study that aims to provide a comprehensive understanding of the mindsets underlying adoption and use of secure email services. Our participants come from a variety of countries …

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Selection-Based Convolution For Irregular Images And Graph Data, David Marvin Hart May 2023

Selection-Based Convolution For Irregular Images And Graph Data, David Marvin Hart

Theses and Dissertations

The field of Computer Vision continues to be revolutionized by advances in Convolutional Neural Networks. These networks are well suited for the regular grid structure of image data. However, there are many irregular image types that do not fit within such a framework, such as multi-view images, spherical images, superpixel representations, and texture maps for 3D meshes. These kinds of representations usually have specially designed networks that only operate and train on that unique form of data, thus requiring large datasets for each data domain. This dissertation aims to bridge the gap between standard convolutional networks and specialized ones. It …

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Algorithmic Fidelity And The Use Of Large Language Models In Social Science Research, Christopher Michael Rytting May 2023

Algorithmic Fidelity And The Use Of Large Language Models In Social Science Research, Christopher Michael Rytting

Theses and Dissertations

In this dissertation, we argue that large language models (LLMs) exhibit a considerable amount of \textit{algorithmic fidelity}, a property where they have modeled ideas, behaviors, and attitudes of the population who generated their training data. This has important implications for social science, as this fidelity theoretically allows for the use of LLMs as effective proxies for human beings in experiments and research. We demonstrate this empirically in various social science domains (political partisanship, demographic surveying, voting behavior, hot-button policy issues, news media, populism, congressional summaries), in various applications (replicating social science survey findings, assisting in coding of text datasets, inferring …

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Developing Genotypic And Phenotypic Systems For Early Analysis Of Drug-Resistant Bacteria, Yesman Akuoko May 2023

Developing Genotypic And Phenotypic Systems For Early Analysis Of Drug-Resistant Bacteria, Yesman Akuoko

Theses and Dissertations

Antimicrobial resistance in bacteria is a global health challenge with a projected fallout of 10 million deaths annually and cumulative costs of over 1 trillion dollars by 2050. The currently available tools exploited in the detection of bacteria or their DNA can be expensive, time inefficient, or lack multiplex capabilities among others. The research work highlighted in this dissertation advances techniques employed in the phenotypic or genotypic detection of bacteria and their DNA. In this dissertation, I present polymethyl methacrylate-pressure sensitive adhesive microfluidic platforms developed using a time-efficient, inexpensive fabrication technique. Microfluidic devices were then equipped with functionalized monoliths and …

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Popr: Probabilistic Offline Policy Ranking With Expert Data, Trevor F. Schwantes Apr 2023

Popr: Probabilistic Offline Policy Ranking With Expert Data, Trevor F. Schwantes

Theses and Dissertations

While existing off-policy evaluation (OPE) methods typically estimate the value of a policy, in real-world applications, OPE is often used to compare and rank policies before deploying them in the real world. This is also known as the offline policy ranking problem. While one can rank the policies based on point estimates from OPE, it is beneficial to estimate the full distribution of outcomes for policy ranking and selection. This paper introduces Probabilistic Offline Policy Ranking that works with expert trajectories. It introduces rigorous statistical inference capabilities to offline evaluation, which facilitates probabilistic comparisons of candidate policies before they are …

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Introducing Stochastic Time Delays In Gradient Optimization As A Method For Complex Loss Surface Navigation In High-Dimensional Settings, Eric Benson Manner Apr 2023

Introducing Stochastic Time Delays In Gradient Optimization As A Method For Complex Loss Surface Navigation In High-Dimensional Settings, Eric Benson Manner

Theses and Dissertations

Time delays are an inherent part of real-world systems. Besides the apparent slowing of the system, these time delays often cause destabilization in otherwise stable systems, and perhaps even more unexpectedly, can stabilize an unstable system. Here, we propose the Stochastic Time-Delayed Adaptation as a method for improving optimization on certain high-dimensional surfaces, which simply wraps a known optimizer --such as the Adam optimizer-- and is able to add a variety of time-delays. We begin by exploring time delays on certain gradient-based optimization methods and their affect on the optimizer's convergence properties. These optimizers include the standard gradient descent method …

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Zero And Few-Shot Concept Learning With Pre-Trained Embeddings, Jamison M. Moody Apr 2023

Zero And Few-Shot Concept Learning With Pre-Trained Embeddings, Jamison M. Moody

Theses and Dissertations

Neural networks typically struggle with reasoning tasks on out of domain data, something that humans can more easily adapt to. Humans come with prior knowledge of concepts and can segment their environment into building blocks (such as objects) that allow them to reason effectively in unfamiliar situations. Using this intuition, we train a network that utilizes fixed embeddings from the CLIP (Contrastive Language--Image Pre-training) model to do a simple task that the original CLIP model struggles with. The network learns concepts (such as "collide" and "avoid") in a supervised source domain in such a way that the network can adapt …

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Rigorous Computation Of The Evans Function, Devin Mcghie Apr 2023

Rigorous Computation Of The Evans Function, Devin Mcghie

Theses and Dissertations

We develop computer-assisted methods of proof for rigorous computation of the Evans function in order to prove stability of traveling waves. We use the parameterization method, series solutions, and the Newton-Kantorovich Theorem to obtain precise, rigorous error bounds for the numerical solution of the ODE used in the construction of the Evans function. We demonstrate these methods on a scalar reaction-diffusion model and on the Gray-Scott model.

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A Game Theoretical Approach To Optimal Pitch Sequencing, William Melville Apr 2023

A Game Theoretical Approach To Optimal Pitch Sequencing, William Melville

Theses and Dissertations

This paper presents a game theoretical solution to the difficult challenge of optimal pitch sequencing. We model the batter/pitcher matchup as a zero-sum game and determine the equilibrium strategy for both the pitcher and batter. We conclude that the Stackelberg equilibrium and our newly defined decision point equilibrium serve as effective pitch sequencing strategies.

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A Large-Scale Survey Of Brown Dwarf Atmospheres, Savanah Kay Turner Apr 2023

A Large-Scale Survey Of Brown Dwarf Atmospheres, Savanah Kay Turner

Theses and Dissertations

Brown dwarfs are substellar objects that fall in-between the smallest stars and largest planets in size and temperature. Due to their relatively cool temperatures, the atmospheres of these 'failed stars' have been shown to exhibit interesting properties such as iron, silicate, and salt clouds. Theoretical atmospheric models based on known physics and chemistry can be used as tools to interpret and understand our observations of brown dwarfs. I have fit archival and new infrared spectra of over 300 brown dwarfs with atmospheric models. Using the parameters of the best-fit models as estimates for the physical properties of the brown dwarfs …

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Use And Misuse Of X-Ray Photoelectron Spectroscopy (Xps): Reproducibility, Gross Errors, Data Reporting, And Peak Fitting, George Hobbs Major Apr 2023

Use And Misuse Of X-Ray Photoelectron Spectroscopy (Xps): Reproducibility, Gross Errors, Data Reporting, And Peak Fitting, George Hobbs Major

Theses and Dissertations

X-ray photoelectron spectroscopy (XPS) is the most widely used surface analysis technique for chemically probing surfaces. Its popularity stems from the large amount of information that can be gathered about the electronic states of the atoms it probes, including core shell information and valence electron information. Simple qualitative analysis (peak identification) can often be performed, but quantitative analysis is a much more complicated process. Although XPS usage has increased dramatically, so has the amount of erroneous analysis observed in the literature. In my thesis, I first present a perspective on how to improve the quality of surface and material data …

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Comparative Gpr Analysis Of Carbonate Strandline Deposits, Sydney Adelaide Richards Apr 2023

Comparative Gpr Analysis Of Carbonate Strandline Deposits, Sydney Adelaide Richards

Theses and Dissertations

The Bahamas Island archipelago grows by the precipitation and secretion of calcium carbonate. A majority of this growth is by lateral accretion of shoreline sedimentary deposits. Previous research is not clear on whether the growth is largely due to eustasy, sediment input from catastrophic events, or a combination of both. The Bahamas is an ideal location for studying Holocene carbonate generation and deposition, but there is limited research on the analysis of strandlines in relation to lateral accretion. Carbonate strandline deposits are commonly classified as low-energy beach ridge deposits. Previous researchers have primarily focused on ooid shoals and subtidal regions. …

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Bézout Domains And Elementary Divisor Domains: Are They The Same?, Michael D. Walton Apr 2023

Bézout Domains And Elementary Divisor Domains: Are They The Same?, Michael D. Walton

Theses and Dissertations

This thesis examines the connections between Bézout domains and elementary divisor domains. I establish what both of these domains are, and I provide some clarifying examples of each. I state and prove some key results that have been established already in the literature. I describe a process by which I tried to show a distinction between Bézout domains and elementary divisor domains, and then provide an explicit example which shows that this process as formulated would not lead to an example of a Bézout domain which is not an elementary divisor domain. Throughout the thesis, I also state open questions …

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A Survey Of Graph Neural Networks On Synthetic Data, Brigham Stone Carson Apr 2023

A Survey Of Graph Neural Networks On Synthetic Data, Brigham Stone Carson

Theses and Dissertations

We relate properties of attributed random graph models to the performance of GNN architectures. We identify regimes where GNNs outperform feedforward neural networks and non-attributed graph clustering methods. We compare GNN performance on our synthetic benchmark to performance on popular real-world datasets. We analyze the theoretical foundations for weak recovery in GNNs for popular one- and two-layer architectures. We obtain an explicit formula for the performance of a 1-layer GNN, and we obtain useful insights on how to proceed in the 2-layer case. Finally, we improve the bound for a notable result on the GNN size generalization problem by 1.

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Skew Relative Hadamard Difference Set Groups, Andrew Haviland Apr 2023

Skew Relative Hadamard Difference Set Groups, Andrew Haviland

Theses and Dissertations

We study finite groups $G$ having a nontrivial subgroup $H$ and $D \subset G \setminus H$ such that (i) the multiset $\{ xy^{-1}:x,y \in D\}$ has every element that is not in $H$ occur the same number of times (such a $D$ is called a {\it relative difference set}); (ii) $G=D\cup D^{(-1)} \cup H$; (iii) $D \cap D^{(-1)} =\emptyset$. We show that $|H|=2$, that $H$ has to be normal, and that $G$ is a group with a single involution. We also show that $G$ cannot be abelian. We give examples of such groups, including certain dicyclic groups, by using results …

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Designing Resilient Agents Using Grammatical Evolution, Behavior Trees, And Finite Linear Temporal Logic, Aadesh Neupane Apr 2023

Designing Resilient Agents Using Grammatical Evolution, Behavior Trees, And Finite Linear Temporal Logic, Aadesh Neupane

Theses and Dissertations

Resilience is essential for long-term autonomous agents. Swarm behaviors seen in bees, ants, birds, fish, and others are interesting because they resiliently perform complex coordinated tasks like foraging, nest-selection, flocking and escaping predators without centralized control or coordination. Conventionally, mimicking swarm behaviors with robots requires researchers to study actual behaviors, derive mathematical models, and implement these models as state machines. Since the conventional approach is time-consuming and cumbersome, this dissertation uses a grammatical evolution algorithm with Behavior Trees (BTs) to evolve behaviors that are resilient to different perturbations for foraging and nest maintenance tasks. The modular, reactive, and readable properties …

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A Language-Model-Based Chatbot That Considers The User's Personality Profile And Emotions To Support Caregivers Of People With Dementia, Yeganeh Nasiri Apr 2023

A Language-Model-Based Chatbot That Considers The User's Personality Profile And Emotions To Support Caregivers Of People With Dementia, Yeganeh Nasiri

Theses and Dissertations

Chatbots are programs that mimic human conversation using Artificial Intelligence (AI). Recent advances in natural language pro- cessing pave the way for chatbots to generate more human-like responses. Therefore, chatbots are finding more complex tasks to perform, such as emotional support which requires both understanding emotions and the ability to properly respond to them. This work presents a chatbot capable of identifying the user's personality and creating responses based on that. During this process, emotion detection is being used to detect and react to users' emotions. The chatbot uses a dynamic knowledge graph to save information as the conversation goes …

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Unsupervised Categorical Clustering On Labor Markets, Matthew James Steffen Apr 2023

Unsupervised Categorical Clustering On Labor Markets, Matthew James Steffen

Theses and Dissertations

During this "white collar recession,'' there is a flooded labor market of workers. For employers seeking to hire, there is a need to identify potential qualified candidates for each job. The current state of the art is LinkedIn Recruiting or elastic search on Resumes. The current state of the art lacks efficiency and scalability along with an intuitive ranking of candidates. We believe this can be fixed with multi-layer categorical clustering via modularity maximization. To test this, we gathered a dataset that is extensive and representative of the job market. Our data comes from PeopleDataLabs and LinkedIn and is sampled …

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Characterizing The Informativity Of Level Ii Book Data For High Frequency Trading, Logan B. Nielsen Apr 2023

Characterizing The Informativity Of Level Ii Book Data For High Frequency Trading, Logan B. Nielsen

Theses and Dissertations

High Frequency Trading (HFT) algorithms are automated feedback systems interacting with markets to maximize returns on investments. These systems have the potential to read different resolutions of market information at any given time, where Level I information is the minimal information about an equity--essentially its price--and Level II information is the full order book at that time for that equity. This paper presents a study of using Recurrent Neural Network (RNN) models to predict the spread of the DOW Industrial 30 index traded on NASDAQ, using Level I and Level II data as inputs. The results show that Level II …

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Language Modeling Using Image Representations Of Natural Language, Seong Eun Cho Apr 2023

Language Modeling Using Image Representations Of Natural Language, Seong Eun Cho

Theses and Dissertations

This thesis presents training of an end-to-end autoencoder model using the transformer, with an encoder that can encode sentences into fixed-length latent vectors and a decoder that can reconstruct the sentences using image representations. Encoding and decoding sentences to and from these image representations are central to the model design. This method allows new sentences to be generated by traversing the Euclidean space, which makes vector arithmetic possible using sentences. Machines excel in dealing with concrete numbers and calculations, but do not possess an innate infrastructure designed to help them understand abstract concepts like natural language. In order for a …

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The Topology And Dynamics Of Surface Diffeomorphisms And Solenoid Embeddings, Xueming Hui Apr 2023

The Topology And Dynamics Of Surface Diffeomorphisms And Solenoid Embeddings, Xueming Hui

Theses and Dissertations

We study two topics on surface diffeomorphisms, their mapping classes and dynamics. For the mapping classes of a punctured disc, we study the $\ZxZ$ subgroups of the fundamental groups of the corresponding mapping tori. An application is the proof of the fact that a satellite knot with braid pattern is prime. For the mapping classes of the disc minus a Cantor set, we study a special type of reducible mapping class. This has direct application on the embeddings of solenoids in $\mathbb{S}^3$. We also give some examples of other types of mapping classes of the disc minus a Cantor set. …

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Network Representation Theory In Materials Science And Global Value Chain Analysis, Mats C. Haneberg Apr 2023

Network Representation Theory In Materials Science And Global Value Chain Analysis, Mats C. Haneberg

Theses and Dissertations

This thesis is divided into two distinct chapters. In the first chapter, we apply network representation learning to the field of materials science in order to predict aluminum grain boundaries' properties and locate the most influential atoms and subgraphs within each grain boundary. We create fixed-length representations of the aluminum grain boundaries that successfully capture grain boundary structure and allow us to accurately predict grain boundary energy. We do this through two distinct methods. The first method we use is a graph convolutional neural network, a semi-supervised deep learning algorithm, and the second method is graph2vec, an unsupervised representation learning …

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Impact Of Applying Visual Design Principles To Boardwork In A Mathematics Classroom, Jennifer Rose Canizales Mar 2023

Impact Of Applying Visual Design Principles To Boardwork In A Mathematics Classroom, Jennifer Rose Canizales

Theses and Dissertations

Though black boards and white boards have been a fundamental tool in the classroom for over a century, little research has been done on how to best design and present information using these boards. My study takes visual design principles and applies them to boardwork in a mathematics classroom to better organize and clarify the content. This research shows that students notice boardwork, have strong opinions on what makes boardwork good, and that the application of design principles on boards has a significant impact on students and the teacher. Students felt their cognitive load was lightened and that they were …

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