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Full-Text Articles in Physical Sciences and Mathematics

Informative Hypothesis For Group Means Comparison, Dr. Teck Kiang Tan Jan 2023

Informative Hypothesis For Group Means Comparison, Dr. Teck Kiang Tan

Practical Assessment, Research, and Evaluation

Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons if the null hypothesis is rejected. As this approach is not able to incorporate order, inequality, and direction into hypothesis testing, and neither does it able to specify multiple hypotheses, this paper introduces the informative hypothesis that allows more flexibility in stating hypothesis testing and is …


Source Data For Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, Malleable Double Diamond Twin", Xueyan Feng, Michael S. Dimitriyev, Edwin L. Thomas Jan 2023

Source Data For Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, Malleable Double Diamond Twin", Xueyan Feng, Michael S. Dimitriyev, Edwin L. Thomas

Data and Datasets

Source data and code for Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, malleable double diamond twin"


In The Face Of The Robot, David J. Gunkel Oct 2022

In The Face Of The Robot, David J. Gunkel

communication +1

“Robot” designates something that does not quite fit the standard way of organizing beings into the mutually exclusive categories of “person” or “thing.” The figure of the robot interrupts this fundamental organizing schema, resisting efforts at both reification and personification. Consequently, what is seen reflected in the face or faceplate of the robot is the fact that the existing moral and legal ontology—the way that we make sense of and organize our world—is already broken or at least straining against its own limitations. What is needed in response to this robot uprising is a significantly reformulated moral and legal ontology …


Manganese Bioavailability Drives Organic Matter Transformations Across Oxic-Anoxic Interfaces Via Biotic And Abiotic Pathways, Nathan A. Chin Oct 2022

Manganese Bioavailability Drives Organic Matter Transformations Across Oxic-Anoxic Interfaces Via Biotic And Abiotic Pathways, Nathan A. Chin

Masters Theses

Soil organic matter decomposition is a critical process that affects nutrient cycling, CO2 emissions, and carbon storage in terrestrial environments. Recent evidence suggests reactive manganese (Mn) phases, potent oxidants that depolymerize compounds like lignocellulose in soil organic matter, act as critical drivers of organic matter decomposition in soil and sediment environments. Furthermore, oxic-anoxic interfaces (OAIs) have been shown to be crucial hotspots for the formation of reactive Mn(III) species and associated organic matter degradation. However, the extent to which microbially mediated Mn(III) formation and subsequently Mn(III)-driven organic matter oxidation depends on Mn availability remains largely unknown. Additionally, the relative …


Identifying New Invasives In The Face Of Climate Change: A Focus On Sleeper Populations, Ayodelé C. O'Uhuru Oct 2022

Identifying New Invasives In The Face Of Climate Change: A Focus On Sleeper Populations, Ayodelé C. O'Uhuru

Masters Theses

Sleeper populations are established populations of a non-native species whose population growth is limited by one or more abiotic or biotic conditions, such as climate change. While the northeastern US is predicted to be a hotspot for future invasions, identifying potential sleeper populations before they become invasive can inform proactive, climate-smart invasive species management. I focused on 169 introduced species that are established in one or more northeastern states. I used the Environmental Impact Classification for Alien Taxa (EICAT) framework to systematically identify and review the peer-reviewed literature for these candidate species to quantify their negative ecological and socioeconomic impacts. …


Symmetry Breaking Effects In Low-Dimensional Quantum Systems, Ke Wang Oct 2022

Symmetry Breaking Effects In Low-Dimensional Quantum Systems, Ke Wang

Doctoral Dissertations

Quantum criticality in low-dimensional quantum systems is known to host exotic behaviors. In quantum one-dimension (1D), the emerging conformal group contains infinite generators, and conformal techniques, e.g., operator product expansion, give accurate and universal descriptions of underlying systems. In quantum two-dimension (2D), the electronic interaction causes singular corrections to Fermi-liquids characteristics. Meanwhile, the Dirac fermions in topological 2D materials can greatly enrich emerging phenomena. In this thesis, we study the symmetry-breaking effects of low-dimensional quantum criticality. In 1D, we consider two cases: time-reversal symmetry (TRS) breaking in the Majorana conformal field theory (CFT) and the absence of conformal symmetry in …


Answer Similarity Grouping And Diversification In Question Answering Systems, Lakshmi Nair Vikraman Oct 2022

Answer Similarity Grouping And Diversification In Question Answering Systems, Lakshmi Nair Vikraman

Doctoral Dissertations

The rise in popularity of mobile and voice search has led to a shift in IR from document to passage retrieval for non-factoid questions. Various datasets such as MSMarco, as well as efficient retrieval models have been developed to identify single best answer passages for this task. However, such models do not specifically address questions which could have multiple or alternative answers. In this dissertation, we focus on this new research area that involves studying answer passage relationships and how this could be applied to passage retrieval tasks.

We first create a high quality dataset for the answer passage similarity …


Approximate Bayesian Deep Learning For Resource-Constrained Environments, Meet Prakash Vadera Oct 2022

Approximate Bayesian Deep Learning For Resource-Constrained Environments, Meet Prakash Vadera

Doctoral Dissertations

Deep learning models have shown promising results in areas including computer vision, natural language processing, speech recognition, and more. However, existing point estimation-based training methods for these models may result in predictive uncertainties that are not well calibrated, including the occurrence of confident errors. Approximate Bayesian inference methods can help address these issues in a principled way by accounting for uncertainty in model parameters. However, these methods are computationally expensive both when computing approximations to the parameter posterior and when using an approximate parameter posterior to make predictions. They can also require significantly more storage than point-estimated models.

In this …


How Do Galaxies Form Their Stars Over Cosmic Time?, Jed H. Mckinney Oct 2022

How Do Galaxies Form Their Stars Over Cosmic Time?, Jed H. Mckinney

Doctoral Dissertations

Galaxies in the past were forming more stars than those today, but the driving force behind this increase in activity remains uncertain. In this thesis I explore the origin of high star-formation rates today and in the past by studying the properties of gas and dust in the cold interstellar medium (ISM) of dusty galaxies over cosmic time. Critically, we do not yet understand how these galaxies could form so many stars. This work began with my discovery of unusual infrared (IR) emission line ratios in the class of dusty galaxies where most of the Universe’s stars were formed. To …


Bayesian Hierarchical Temporal Modeling And Targeted Learning With Application To Reproductive Health, Herbert P. Susmann Oct 2022

Bayesian Hierarchical Temporal Modeling And Targeted Learning With Application To Reproductive Health, Herbert P. Susmann

Doctoral Dissertations

The international community via the United Nations Sustainable Development Goals has set the target of universal access to reproductive health-care services, including family planning, by 2030. Progress towards reaching this goal is assessed by tracking appropriate demographic and health indicators at national and subnational levels. This task is challenging, however, in populations where relevant data are limited or of low quality. Statistical models are then needed to estimate and project demographic and health indicators in populations based on the available data. Our first contribution, in Chapter 1, is to unify many existing demographic and health indicator models by proposing an …


Intracellular Delivery Of Therapeutic Biomolecules Through Versatile Polymer Nanotechnology, David C. Luther Oct 2022

Intracellular Delivery Of Therapeutic Biomolecules Through Versatile Polymer Nanotechnology, David C. Luther

Doctoral Dissertations

Advancing pharmaceutical technology has made it possible to treat diseases once considered ‘undruggable.’ Access to these new pharmaceutical targets is possible thanks to the advent of protein and nucleic acid therapeutics. Responses to the COVID-19 pandemic, as well as cutting-edge treatments for cancer and multiple sclerosis have centered on these biologic therapies, promising even greater value in the future. However, their utility is limited at a cellular level by inability to cross the plasma membrane. Nanocarrier technologies encapsulate therapeutics and facilitate uptake into the cell but are often trapped and degraded in endosomes. Arginine-functionalized gold nanoparticles (Arg-NPs) provide efficient, direct …


Controllable Neural Synthesis For Natural Images And Vector Art, Difan Liu Oct 2022

Controllable Neural Synthesis For Natural Images And Vector Art, Difan Liu

Doctoral Dissertations

Neural image synthesis approaches have become increasingly popular over the last years due to their ability to generate photorealistic images useful for several applications, such as digital entertainment, mixed reality, synthetic dataset creation, computer art, to name a few. Despite the progress over the last years, current approaches lack two important aspects: (a) they often fail to capture long-range interactions in the image, and as a result, they fail to generate scenes with complex dependencies between their different objects or parts. (b) they often ignore the underlying 3D geometry of the shape/scene in the image, and as a result, they …


Probabilistic Commonsense Knowledge, Xiang Li Oct 2022

Probabilistic Commonsense Knowledge, Xiang Li

Doctoral Dissertations

Commonsense knowledge is critical to achieving artificial general intelligence. This shared common background knowledge is implicit in all human communication, facilitating efficient information exchange and understanding. But commonsense research is hampered by its immense quantity of knowledge because an explicit categorization is impossible. Furthermore, a plumber could repair a sink in a kitchen or a bathroom, indicating that common sense reveals a probable assumption rather than a definitive answer. To align with these properties of commonsense fundamentally, we want to not only model but also evaluate such knowledge human-like using abstractions and probabilistic principles. Traditional combinatorial probabilistic models, e.g., probabilistic …


Languages And Compilers For Writing Efficient High-Performance Computing Applications, Abhinav Jangda Oct 2022

Languages And Compilers For Writing Efficient High-Performance Computing Applications, Abhinav Jangda

Doctoral Dissertations

Many everyday applications, such as web search, speech recognition, and weather prediction, are executed on high-performance systems containing thousands of Central Processing Units (CPUs) and Graphics Processing Units (GPUs). These applications can be written in either low-level programming languages, such as NVIDIA CUDA, or domain specific languages, like Halide for image processing and PyTorch for machine learning programs. Despite the popularity of these languages, there are several challenges that programmers face when developing efficient high-performance computing applications. First, since every hardware support a different low-level programming model, to utilize new hardware programmers need to rewrite their applications in another programming …


Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh Oct 2022

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale.

Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …


Statistical Methods To Study Transposon Sequencing Data: Nonparametric Bayesian Models With Sampling Algorithms, Shai He Oct 2022

Statistical Methods To Study Transposon Sequencing Data: Nonparametric Bayesian Models With Sampling Algorithms, Shai He

Doctoral Dissertations

As the development of Next Generation Sequencing(NGS) technology, researchers can easily obtain data from millions of cells( bulk samples) or just collecting data from a single cell. However, while bulk samples can capture broad changes, it may risk providing an average measurement that is not representative of the genetic state of any individual cell. While single-cell experiments can capture the genetic state of the individual cell, a single cell sample can increase uncertainty, sampling enough cells to gain a representative sample of population is expensive. Therefore, there is a need to integrate information from both bulk and single-cell data to …


Modeling The Multi-Mode Distribution In Self-Supervised Language Models, Haw-Shiuan Chang Oct 2022

Modeling The Multi-Mode Distribution In Self-Supervised Language Models, Haw-Shiuan Chang

Doctoral Dissertations

Self-supervised large language models (LMs) have become a highly-influential and foundational tool for many NLP models. For this reason, their expressivity is an important topic of study. In near-universal practice, given the language context, the model predicts a word from the vocabulary using a single embedded vector representation of both context and dictionary entries. Note that the context sometimes implies that the distribution over predicted words should be multi-modal in embedded space. However, the context’s single-vector representation provably fails to capture such a distribution. To address this limitation, we propose to represent context with multiple vector embeddings, which we term …


Communicative Information Visualizations: How To Make Data More Understandable By The General Public, Alyxander Burns Oct 2022

Communicative Information Visualizations: How To Make Data More Understandable By The General Public, Alyxander Burns

Doctoral Dissertations

Although data visualizations have been around for centuries and are encountered frequently by the general public, existing evidence suggests that a significant portion of people have difficulty understanding and interpreting them. It might not seem like a big problem when a reader misreads a weather map and finds themselves without an umbrella in a rainstorm, but for those who lack the means, experience, or ability to make sense of data, misreading a data visualization concerning public health and safety could be a matter of life and death. However, figuring out how to make visualizations truly usable for a diverse audience …


Expanding The Polymer Zwitterion Library – Novel Phosphonium-Based Polymer Zwitterions And Analogous Structures, Marcel U. Brown Oct 2022

Expanding The Polymer Zwitterion Library – Novel Phosphonium-Based Polymer Zwitterions And Analogous Structures, Marcel U. Brown

Doctoral Dissertations

This dissertation encompasses the synthesis, characterization and application of novel polymer zwitterions that significantly expand the library of available zwitterionic polymers. Their facile synthesis is facilitated by the preparation of a novel functional sultone precursor molecule, which can be ring-opened by commercially available phosphine, amine and sulfide nucleophiles, affording phosphonium, ammonium or sulfonium sulfonate monomers, respectively. Most notably, this work describes the invention of phosphonium-based polymer zwitterions, establishing a new class of zwitterionic polymer structures with unique solution and interfacial properties. Furthermore, the incorporation of these phosphonium sulfonates into block copolymer architectures with conventional polymer zwitterions, and the resulting switchable …


Anomalous Transport, Quasiperiodicity, And Measurement Induced Phase Transitions, Utkarsh Agrawal Oct 2022

Anomalous Transport, Quasiperiodicity, And Measurement Induced Phase Transitions, Utkarsh Agrawal

Doctoral Dissertations

With the advent of the noisy-intermediate scale quantum (NISQ) era quantum computers are increasingly becoming a reality of the near future. Though universal computation still seems daunting, a great part of the excitement is about using quantum simulators to solve fundamental problems in fields ranging from quantum gravity to quantum many-body systems. This so-called second quantum revolution rests on two pillars. First, the ability to have precise control over experimental degrees of freedom is crucial for the realization of NISQ devices. Significant progress in the control and manipulation of qubits, atoms, and ions, as well as their interactions, has not …


Combinatorial Algorithms For Graph Discovery And Experimental Design, Raghavendra K. Addanki Oct 2022

Combinatorial Algorithms For Graph Discovery And Experimental Design, Raghavendra K. Addanki

Doctoral Dissertations

In this thesis, we study the design and analysis of algorithms for discovering the structure and properties of an unknown graph, with applications in two different domains: causal inference and sublinear graph algorithms. In both these domains, graph discovery is possible using restricted forms of experiments, and our objective is to design low-cost experiments.

First, we describe efficient experimental approaches to the causal discovery problem, which in its simplest form, asks us to identify the causal relations (edges of the unknown graph) between variables (vertices of the unknown graph) of a given system. For causal discovery, we study algorithms …


Building Intrapersonal Competencies In The First-Year Experience: Utilizing Random Forest, Cluster Analysis, And Linear Regression To Identify Students’ Strengths And Opportunities For Institutional Improvement, Marilee Bresciani Ludvik, Shiming Zhang, Sandra Kahn, Nina Potter, Lisa Richardson-Gates, Stephen Schellenberg, Robyn Saiki, Nasima Subedi, Rebecca Harmata, Rey Monzon, Randy Timm, Jeanne Stronach, Anna Jost Aug 2022

Building Intrapersonal Competencies In The First-Year Experience: Utilizing Random Forest, Cluster Analysis, And Linear Regression To Identify Students’ Strengths And Opportunities For Institutional Improvement, Marilee Bresciani Ludvik, Shiming Zhang, Sandra Kahn, Nina Potter, Lisa Richardson-Gates, Stephen Schellenberg, Robyn Saiki, Nasima Subedi, Rebecca Harmata, Rey Monzon, Randy Timm, Jeanne Stronach, Anna Jost

Practical Assessment, Research, and Evaluation

Leveraging research that illustrates the importance of intrapersonal competency cultivation and its correlation with institutional performance indicators of student success such as end-of-term cumulative GPA, persistence, and academic probation, our team set out to conduct an analysis on the effectiveness of a 1-unit credit/no-credit first-semester, first-year student seminar course. The course was designed to cultivate specific intrapersonal competency gains using a pre- and post-assessment design. Using a supervised Random Forest method and cluster analysis, the team expected to find unique differences in intrapersonal competency pre-, matched pre- and post-, and post-assessment inventory scores in a way where course design improvements …


Practical T-Test Power Analysis With R, Teck Kiang Tan Aug 2022

Practical T-Test Power Analysis With R, Teck Kiang Tan

Practical Assessment, Research, and Evaluation

Power analysis based on the analytical t-test is an important aspect of a research study to determine the sample size required to detect the effect for the comparison of two means. The current paper presents a reader-friendly procedure for carrying out the t-test power analysis using the various R add-on packages. While there is a growing of R users in the academic that uses R as the base for carrying out research, there is a lack of reference that discusses both frequentist and Bayesian approaches and point out their distinct features for t-test power analysis. The practical aspects of the …


Chromatographic Dynamic Chemisorption, Shreya Thakkar Jun 2022

Chromatographic Dynamic Chemisorption, Shreya Thakkar

Masters Theses

Reaction rates of catalytic cycles over supported metal catalysts are normalized by the exposed metal atoms on the catalyst surface, reported as site time yields which provide a rigorous standard to compare distinct metal surfaces. Defined as the fraction of exposed metal surface atoms to the total number of metal atoms, it is important to measure the dispersion of supported metal catalysts to report standardized rates for kinetic investigations. Multiple characterization techniques such as electron microscopy, spectroscopy and chemisorption are exploited for catalyst dispersion measurements. While effective, electron microscopy and spectroscopy are not readily accessible due to cost and maintenance …


Pre-Agricultural Soil Erosion Rates In The Midwestern U.S., Caroline Lauth Quarrier Jun 2022

Pre-Agricultural Soil Erosion Rates In The Midwestern U.S., Caroline Lauth Quarrier

Masters Theses

Soil erosion undermines agricultural productivity, limiting the lifespan of civilizations. For agriculture to be sustainable, soil erosion rates must be low enough to maintain fertile soil, as was present in many agricultural landscapes prior to the initiation of farming. However, there have been few measurements of long-term pre-agricultural erosion rates in major agricultural landscapes. We quantified geological erosion rates in the Midwestern U.S., one of the world’s most productive agricultural areas. We sampled soil profiles from 14 native prairies and measured concentrations of the cosmogenic nuclide 10Be and chemically immobile elements to calculate physical erosion rates. We used the erosion …


Three Dimensional Spatio-Temporal Cluster Analysis Of Sars-Cov-2 Infections, Keith W. Allison Jun 2022

Three Dimensional Spatio-Temporal Cluster Analysis Of Sars-Cov-2 Infections, Keith W. Allison

Masters Theses

The COVID-19 pandemic has heightened the need for fine-scale analysis of the clustering of cases of infectious disease in order to better understand and prevent the localized spread of infection. The students living on the University of Massachusetts, Amherst campus provided a unique opportunity to do so, due to frequent mandatory testing during the 2020-2021 academic year, and dense living conditions. The South-West dormitory area is of particular interest due to its extremely high population density, housing around half of students living on campus during normal conditions. Using data gathered by the Public Health Promotion Center (PHPC), we analyzed the …


Scalable Data Analytics For Relational Databases, Graphs And Videos, Fubao Wu Jun 2022

Scalable Data Analytics For Relational Databases, Graphs And Videos, Fubao Wu

Doctoral Dissertations

Data analytics is to analyze raw data and mine insights, trends, and patterns from them. Due to the dramatic increase in data volume and size in recent years with the development of big data and cloud storage, big data analytics algorithms and techniques have been faced with more challenges. Moreover, there are various types of data formats, such as relational databases, text data, audio data, and image/video data. It is challenging to generate a unified framework or algorithm for data analytics on various data formats. Different data formats still need refined and scalable algorithms. In this dissertation, we explore three …


Collective Motion And Phase Diagram Of Self-Propelled Vibrated Hard Squares, Zhejun Shen Jun 2022

Collective Motion And Phase Diagram Of Self-Propelled Vibrated Hard Squares, Zhejun Shen

Doctoral Dissertations

In equilibrium, matter condenses into ordered phases due to the combined effects of inter-particle interactions and entropy. In this dissertation, we explore the self-propulsion of particles as an additional nonequilibrium consideration in the mechanisms for ordering. Our experiments employ square-shaped hard particles; in equilibrium, when particle motions are randomly directed, squares form entropically-stabilized phases in which first their orientations, and then their positions, get locked in relative to each other, depending on the density of coverage. When the square tiles are modified to have small propulsion along some body-fixed axis we find that their tendency to order is profoundly altered. …


Measurement Of The Fiducial Cross Section For Vector-Boson-Fusion Production Of The Higgs Boson In The Ww Decay Channel With The Atlas Detector, Guy Rosin Jun 2022

Measurement Of The Fiducial Cross Section For Vector-Boson-Fusion Production Of The Higgs Boson In The Ww Decay Channel With The Atlas Detector, Guy Rosin

Doctoral Dissertations

This doctoral thesis presents a measurement of the fiducial and differential cross section of vector boson fusion produced Higgs boson.The measurement is taken in the H → WW∗ → lνlν channel with 139 fb−1 of data. Proton-proton collisions from the Large Hadron Collider at √s = 13 TeV were recorded by the ATLAS detector. New analysis techniques using boosted decision trees with a statistical fit are introduced to accurately estimate backgrounds in the signal region. The fiducial cross section is measured to be 1.7 ± 0.42fb. The differential cross section was measured for 13 kinematic variables. No significant deviations …


Calibration Of The Lux-Zeplin Dual-Phase Xenon Time Projection Chamber With Internally Injected Radioisotopes, Christopher D. Nedlik Jun 2022

Calibration Of The Lux-Zeplin Dual-Phase Xenon Time Projection Chamber With Internally Injected Radioisotopes, Christopher D. Nedlik

Doctoral Dissertations

Self-shielding in ton-scale liquid xenon (LXe) detectors presents a unique challenge for calibrating detector response to interactions in the detector's innermost volume. Calibration radioisotopes must be injected directly into the LXe to reach the central volume, where they must either decay away with a short half life or be purified out. We present an overview of, and results from, the prototype source injection system (SIS) developed at the University of Massachusetts Amherst for the LUX-ZEPLIN experiment (LZ). The SIS is designed to refine techniques for the injection and removal of precise activities of various calibration radioisotopes that are useful in …