Digital Commons Network^™

Parametric Characteristics Of The B6omsi-Re, Sarahelizabeth Janemarie Baguhn

Dissertations

Orientation and mobility specialists for young children who are blind or visually impaired have relied on informal assessments or commercially available tools designed for sighted children to track developmental progress. When Bradley-Johnson (1994) literally wrote the book on assessment in blindness, the sharing and refinement of common tools led to professionals working in teams to sift and winnow the checklists, and move the best available tools into wider circulation. This has led to the evolution of the practitioner made tools becoming the published tools, although they have not yet had statistical evidence to support their efficacy. This three-paper dissertation aims …

Advanced Risk Models To Predict Surgical Site Infections Using Machine Learning Approaches And Risk-Adjusted Control Charts, Rabia Emhamed Al Mamlook

Dissertations

Even though most infections are treatable with antibiotics, Surgical Site Infections (SSIs) remain a significant healthcare problem as they increase hospital stays, require additional treatments, reduce a patient’s quality of life, and increase morbidity and mortality. To reduce the risks and to encourage the highest quality healthcare, it is important to measure, predict, and monitor the risk of SSIs. Preoperative prediction of SSIs is essential to facilitate the implementation of preventative strategies for high-risk patients. The overarching goal of this dissertation is to investigate new opportunities of using machine-learning (ML) to improve the accuracy and use of pre-operative prediction models …

Conditional Wasserstein Generative Adversarial Networks Applied To Acoustic Metamaterial Design, Peter Lai, Feruza Amirkulova, Peter Gerstoft

Faculty Research, Scholarly, and Creative Activity

This work presents a method for the reduction of the total scattering cross section (TSCS) for a planar configuration of cylinders by means of generative modeling and deep learning. Currently, the minimization of TSCS requires repeated forward modelling at considerable computer resources, whereas deep learning can do this more efficiently. The conditional Wasserstein generative adversarial networks (cWGANs) model is proposed for minimization of TSCS in two dimensions by combining Wasserstein generative adversarial networks with convolutional neural networks to simulate TSCS of configuration of rigid scatterers. The proposed cWGAN model is enhanced by adding to it a coordinate convolution (CoordConv) layer. …

The Future Is Big - And Small: Remote Sensing Enables Cross- Scale Comparisons Of Microbiome Dynamics And Ecological Consequences, Deanna S. Beatty, Lillian R. Aoki, Olivia J. Graham, Bo Yang

Faculty Research, Scholarly, and Creative Activity

Coupling remote sensing with microbial omics-based approaches provides a promising new frontier for scientists to scale microbial interactions across space and time. These data-rich, interdisciplinary methods allow us to better understand interactions between microbial communities and their environments and, in turn, their impact on ecosystem structure and function. Here, we highlight current and novel examples of applying remote sensing, machine learning, spatial statistics, and omics data approaches to marine, aquatic, and terrestrial systems. We emphasize the importance of integrating biochemical and spatiotemporal environmental data to move toward a predictive framework of microbiome interactions and their ecosystemlevel effects. Finally, we emphasize …

The Human Right To Water And Sanitation: Using Natural Language Processing To Uncover Patterns In Academic Publishing, Christopher Michael Faulkner, Joshua Earl Lambert, Bruce M. Wilson, Matthew Steven Faulkner

Faculty Research, Scholarly, and Creative Activity

After years of advocacy and international negotiation, the General Assembly of the United Nations voted to officially recognize a stand-alone human right to water and sanitation on 28 July 2010. Since, academic scholarship has continued to grow in an effort to understand the implications of the codification of this human right. Yet, with this growth, it has become impractical if not impossible for scholars to keep up with the advancement of academic knowledge or to make sense of it in a systematic way. In short, to date, we know very little about the trends in the literature as they have …

Supervision Of A Self-Driving Vehicle Unmasks Latent Sleepiness Relative To Manually Controlled Driving, Erin E. Flynn-Evans, Lily R. Wong, Yukiyo Kuriyagawa, Nikhil Gowda, Patrick F. Cravalho, Sean Pradhan, Nathan H. Feick, Nicholas G. Bathurst, Zachary L. Glaros, Theerawit Wilaiprasitporn, Kanika Bansal, Javier O. Garcia, Cassie J. Hilditch

Faculty Research, Scholarly, and Creative Activity

Human error has been implicated as a causal factor in a large proportion of road accidents. Automated driving systems purport to mitigate this risk, but self-driving systems that allow a driver to entirely disengage from the driving task also require the driver to monitor the environment and take control when necessary. Given that sleep loss impairs monitoring performance and there is a high prevalence of sleep deficiency in modern society, we hypothesized that supervising a self-driving vehicle would unmask latent sleepiness compared to manually controlled driving among individuals following their typical sleep schedules. We found that participants felt sleepier, had …

Drivers Of Understory Plant Communities In Sierra Nevada Mixed Conifer Forests With Pyrodiversity, Kate Wilkin, Lauren Ponisio, Danny L. Fry, Brandon M. Collins, Tadashi Moody, Scott L. Stephens

Faculty Research, Scholarly, and Creative Activity

Background: Fire suppression in western North America increased and homogenized overstory cover in conifer forests, which likely affected understory plant communities. We sought to characterize understory plant communities and their drivers using plot-based observations from two contemporary reference sites in the Sierra Nevada, USA. These sites had long-established natural fire programs, which have resulted in restored natural fire regimes. In this study, we investigated how pyrodiversity—the diversity of fire size, severity, season, and frequency—and other environment factors influenced species composition and cover of forest understory plant communities. Results: Understory plant communities were influenced by a combination of environmental, plot-scale recent …

Community Norms Of The Muscle Dysmorphic Disorder Inventory (Mddi) Among Gender Minority Populations, Jason M. Nagata, Emilio J. Compte, F. Hunter Mcguire, Jason M. Lavender, Tiffany A. Brown, Stuart B. Murray, Annesa Flentje, Matthew R. Capriotti, Micah E. Lubensky, Juno Obedin-Maliver, Mitchell R. Lunn

Faculty Research, Scholarly, and Creative Activity

Purpose: Representing the pathological extreme pursuit of muscularity, muscle dysmorphia (MD) is characterized by a pervasive belief or fear around insufficient muscularity and an elevated drive for muscularity. Despite evidence of heightened body image-related concerns among gender minority populations, little is known about the degree of MD symptoms among gender minorities, particularly based on Muscle Dysmorphic Disorder Inventory (MDDI) scores. The objective of this study was to assess community norms of the MDDI in gender-expansive people, transgender men, and transgender women. Method: Data from participants in The PRIDE Study, an existing study of health outcomes in sexual and gender minority …

Head-Mounted Accelerometry Accurately Detects Prey Capture In California Sea Lions, Mason R. Cole, Jenifer A. Zeligs, Stefani Skrovan, Birgitte I. Mcdonald

Faculty Research, Scholarly, and Creative Activity

Detecting when and where animals feed is key to understanding their ecophysiology, but our ability to collect these data in marine mammals remains limited. Here, we test a tag-based accelerometry method to detect prey capture in California sea lions. From synchronized underwater video and acceleration data of two trained sea lions, we isolated a combined acceleration and Jerk pattern that reliably indicated prey capture in training datasets. We observed a stereotyped feeding motion in underwater video that included (1) mouth opening while approaching prey; (2) head deceleration to allow initial suction or prey engulfment, and (3) jaw closure. This motion …

Immunological And Hematological Outcomes Following Protracted Low Dose/Low Dose Rate Ionizing Radiation And Simulated Microgravity, Amber M. Paul, Eliah G. Overbey, Willian A. Da Silveira, Nathaniel Szewczyk, Nina C. Nishiyama, Michael J. Pecaut, Sulekha Anand, Jonathan M. Galazka, Xiao Wen Mao

Faculty Research, Scholarly, and Creative Activity

Using a ground-based model to simulate spaceflight [21-days of single-housed, hindlimb unloading (HLU) combined with continuous low-dose gamma irradiation (LDR, total dose of 0.04 Gy)], an in-depth survey of the immune and hematological systems of mice at 7-days post-exposure was performed. Collected blood was profiled with a hematology analyzer and spleens were analyzed by whole transcriptome shotgun sequencing (RNA-sequencing). The results revealed negligible differences in immune differentials. However, hematological system analyses of whole blood indicated large disparities in red blood cell differentials and morphology, suggestive of anemia. Murine Reactome networks indicated majority of spleen cells displayed differentially expressed genes (DEG) …

Adaptive Laboratory Evolution Of Β-Caryophyllene Producing Saccharomyces Cerevisiae, Avinash Godara, Katy C. Kao

Faculty Research, Scholarly, and Creative Activity

Background: β-Caryophyllene is a plant terpenoid with therapeutic and biofuel properties. Production of terpenoids through microbial cells is a potentially sustainable alternative for production. Adaptive laboratory evolution is a complementary technique to metabolic engineering for strain improvement, if the product-of-interest is coupled with growth. Here we use a combination of pathway engineering and adaptive laboratory evolution to improve the production of β-caryophyllene, an extracellular product, by leveraging the antioxidant potential of the compound. Results: Using oxidative stress as selective pressure, we developed an adaptive laboratory evolution that worked to evolve an engineered β-caryophyllene producing yeast strain for improved production within …

Neural Upscaling From Residue-Level Protein Structure Networks To Atomistic Structures, Vy T. Duong, Elizabeth M. Diessner, Gianmarc Grazioli, Rachel W. Martin, Carter T. Butts

Faculty Research, Scholarly, and Creative Activity

Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and other biological macromolecules. Topological coarse-graining, in which biomolecules or sets thereof are represented via graph structures, is a particularly useful way of obtaining highly com-pressed representations of molecular structures, and simulations operating via such representations can achieve substantial computational savings. A drawback of coarse-graining, however, is the loss of atomistic detail—an effect that is especially acute for topological representations such as protein structure networks (PSNs). Here, we introduce an approach based on a combination of machine learning and physically-guided refinement for inferring atomic coordinates from …

Fuel Load, Stand Structure, And Understory Species Composition Following Prescribed Fire In An Old-Growth Coast Redwood (Sequoia Sempervirens) Forest, David Cowman, Will Russell

Faculty Research, Scholarly, and Creative Activity

Background: With the prevalence of catastrophic wildfire increasing in response to widespread fire suppression and climate change, land managers have sought methods to increase the resiliency of landscapes to fire. The application of prescribed burning in ecosystems adapted to fire can reduce fuel load and fire potential while minimizing impacts to the ecosystem as a whole. Coast redwood forests have historically experienced fire from both natural and anthropogenic sources, and are likely to respond favorably to its reintroduction. Results: Random sampling was conducted in three burned sites and in three unburned sites, in an old-growth coast redwood (Sequoia sempervirens [D. …

Comparative Egg Attendance Patterns Of Incubating Polar Petrels, Scott A. Shaffer, Pierre Blévin, Christophe Barbraud, Olivier Chastel, Henri Weimerskirch

Faculty Research, Scholarly, and Creative Activity

Background: The internal environment of eggs in most birds is regulated by transferring heat energy through contact incubation, maintaining nest microclimate, and frequent egg turning by the incubating parent on its nest. However, we lack information about egg attendance patterns in birds that breed in polar environments where variations in life history are expected to influence incubation behavior. Moreover, crevice/burrow nesting petrels in high-latitude regions are known for periodically leaving their egg unattended (hereafter ‘egg neglect’), but there is little reporting on the internal condition of unattended eggs. At Dumont d’Urville Station, Antarctica, we studied the incubation behavior of 24 …

The Extracellular Contractile Injection System Is Enriched In Environmental Microbes And Associates With Numerous Toxins, Alexander Martin Geller, Inbal Pollin, David Zlotkin, Aleks Danov, Nimrod Nachmias, William B. Andreopoulos, Keren Shemesh, Asaf Levy

Faculty Research, Scholarly, and Creative Activity

The extracellular Contractile Injection System (eCIS) is a toxin-delivery particle that evolved from a bacteriophage tail. Four eCISs have previously been shown to mediate interactions between bacteria and their invertebrate hosts. Here, we identify eCIS loci in 1,249 bacterial and archaeal genomes and reveal an enrichment of these loci in environmental microbes and their apparent absence from mammalian pathogens. We show that 13 eCIS-associated toxin genes from diverse microbes can inhibit the growth of bacteria and/or yeast. We identify immunity genes that protect bacteria from self-intoxication, further supporting an antibacterial role for some eCISs. We also identify previously undescribed eCIS …

Potential Health And Economic Impacts Of Dexamethasone Treatment For Patients With Covid-19, Ricardo Águas, Adam Mahdi, Rima Shretta, Peter Horby, Martin Landray, Lisa White, Fatima Arifi, Chynar Zhumalieva, Inke N.D. Lubis, Antoninho Benjamin Monteiro, Ainura Moldokmatova, Siyu Chen, Aida Estebesova, Mofakhar Hussain, Dipti Lata, Emmanuel A. Bakare, Michael Klein, For Full Author List, See Comments Below

Faculty Research, Scholarly, and Creative Activity

Dexamethasone can reduce mortality in hospitalised COVID-19 patients needing oxygen and ventilation by 18% and 36%, respectively. Here, we estimate the potential number of lives saved and life years gained if this treatment were to be rolled out in the UK and globally, as well as the cost-effectiveness of implementing this intervention. Assuming SARS-CoV-2 exposure levels of 5% to 15%, we estimate that, for the UK, approximately 12,000 (4,250 - 27,000) lives could be saved between July and December 2020. Assuming that dexamethasone has a similar effect size in settings where access to oxygen therapies is limited, this would translate …

Canita: Faster Rates For Distributed Convex Optimization With Communication Compression, Zhize Li, Peter Richtarik

Research Collection School Of Computing and Information Systems

Due to the high communication cost in distributed and federated learning, methods relying on compressed communication are becoming increasingly popular. Besides, the best theoretically and practically performing gradient-type methods invariably rely on some form of acceleration/momentum to reduce the number of communications (faster convergence), e.g., Nesterov's accelerated gradient descent (Nesterov, 1983, 2004) and Adam (Kingma and Ba, 2014). In order to combine the benefits of communication compression and convergence acceleration, we propose a \emph{compressed and accelerated} gradient method based on ANITA (Li, 2021) for distributed optimization, which we call CANITA. Our CANITA achieves the \emph{first accelerated rate} $O\bigg(\sqrt{\Big(1+\sqrt{\frac{\omega^3}{n}}\Big)\frac{L}{\epsilon}} + \omega\big(\frac{1}{\epsilon}\big)^{\frac{1}{3}}\bigg)$, …

Linear Algebra For Computer Science, M. Thulasidas

Research Collection School Of Computing and Information Systems

This textbook introduces the essential concepts and practice of Linear Algebra to the undergraduate student of computer science. The focus of this book is on the elegance and beauty of the numerical techniques and algorithms originating from Linear Algebra. As a practical handbook for computer and data scientists, LA4CS restricts itself mostly to real fields and tractable discourses, rather than deep and theoretical mathematics.

Self-Supervised Learning Disentangled Group Representation As Feature, Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang

Research Collection School Of Computing and Information Systems

A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics). In this paper, we formulate the notion of “good” representation from a group-theoretic view using Higgins’ definition of disentangled representation [38], and show that existing Self-Supervised Learning (SSL) only disentangles simple augmentation features such as rotation and colorization, thus unable to modularize the remaining semantics. To break the limitation, we propose an iterative SSL algorithm: Iterative Partition-based Invariant Risk Minimization (IP-IRM), which successfully grounds the abstract semantics and the group acting on them into concrete contrastive learning. …

Hierarchical Control Of Multi-Agent Reinforcement Learning Team In Real-Time Strategy (Rts) Games, Weigui Jair Zhou, Budhitama Subagdja, Ah-Hwee Tan, Darren Wee Sze Ong

Research Collection School Of Computing and Information Systems

Coordinated control of multi-agent teams is an important task in many real-time strategy (RTS) games. In most prior work, micromanagement is the commonly used strategy whereby individual agents operate independently and make their own combat decisions. On the other extreme, some employ a macromanagement strategy whereby all agents are controlled by a single decision model. In this paper, we propose a hierarchical command and control architecture, consisting of a single high-level and multiple low-level reinforcement learning agents operating in a dynamic environment. This hierarchical model enables the low-level unit agents to make individual decisions while taking commands from the high-level …

Automated Doubt Identification From Informal Reflections Through Hybrid Sentic Patterns And Machine Learning Approach, Siaw Ling Lo, Kar Way Tan, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

Do my students understand? The question that lingers in every instructor’s mind after each lesson. With the focus on learner-centered pedagogy, is it feasible to provide timely and relevant guidance to individual learners according to their levels of understanding? One of the options available is to collect reflections from learners after each lesson to extract relevant feedback so that doubts or questions can be addressed in a timely manner. In this paper, we derived a hybrid approach that leverages a novel Doubt Sentic Pattern Detection (SPD) algorithm and a machine learning model to automate the identification of doubts from students’ …

Shhh-Tereotypes: A Conversation Among Librarians With Hearing Loss, Jill Cirasella, Lee Ann Fullington, Monica Berger, William Gargan

Publications and Research

We are four hard of hearing librarians dependent on hearing aids. Our hearing loss complicates our work, often in ways that are not apparent to colleagues and patrons. In this article, based on our panel at the 2021 LACUNY Institute, we share our experiences, challenges, and self-accommodations, and offer suggestions for supporting and effectively communicating with hard of hearing colleagues.

A Closer Look At The Aha's Antibiotic Prophylaxis Guidelines, Dora-Ann Oddo

Publications and Research

In May 2021, the American Heart Association (AHA) updated its antibiotic prophylaxis guidelines for the prevention of infective endocarditis (IE). As some dental and dental hygiene procedures may increase the risk of this potentially life-threatening infection in at-risk patients, oral health professionals must have a thorough understanding of this serious, albeit rare infection of the heart and understand appropriate precautions for treatment. This article focuses on the AHA's guidelines; however, oral health professionals should also consider the IE guidelines from the American Academy of Orthopedics Surgeons.

Investigation Of Optical And Structural Properties Of Gesn Heterostructures, Oluwatobi Gabriel Olorunsola

Graduate Theses and Dissertations

Silicon (Si)-based optoelectronics have gained traction due to its primed versatility at developing light-based technologies. Si, however, features indirect bandgap characteristics and suffers relegated optical properties compared to its III-V counterparts. III-Vs have also been hybridized to Si platforms but the resulting technologies are expensive and incompatible with standard complementary-metal-oxide-semiconductor processes. Germanium (Ge), on the other hand, have been engineered to behave like direct bandgap material through tensile strain interventions but are well short of attaining extensive wavelength coverage. To create a competitive material that evades these challenges, transitional amounts of Sn can be incorporated into Ge matrix to form …

The Flavoprotein Rcla Is A Hypothiocyanous Acid Reductase, Irina Chapman

Masters Theses

Reactive chlorine species (RCS) - hypochlorous acid (HOCl), hypothiocyanous acid (HOSCN), and chloramines - are powerful antimicrobial oxidants generated by the innate immune system. Bacteria developed defense mechanisms against RCS, which are highly toxic for invading pathogens. One such defense system involves RclA, an enzyme from the flavin disulfide reductase family, which is massively upregulated upon exposure of Escherichia coli to RCS. Recent research suggests that RclA functions as a Cu(II) reductase to provide resistance against RCS. However, the exact mechanism used by RclA was subject to debate. In this study, we demonstrate that RclA is unlikely to function as …

Using Sedimentary Mercury Geochemistry To Evaluate The Niagara-Salina Transition, Silurian Michigan Basin, Usa, Sara Hayes

Masters Theses

The Niagara-Salina boundary in the Michigan Basin is marked by an abrupt transition from carbonates to evaporites. Though the cause is uncertain, previous work suggests the onset of Salina evaporites was driven by basin restriction, but the presence of several global carbon isotope excursions (CIE) suggest a global driver. This study builds on this discussion using two relatively new geochemical proxies - elemental mercury concentrations [Hg] and Hg isotopes.

Mercury concentrations [Hg] were measured in 88 samples from the State Kalkaska #2-15 core from 6604.03 ft to 6797.42 ft. [Hg] ranges from 0.11 to 0.62 mg/kg and [Hg]/TOC from 0.038 …

An Investigation Of Principals’ Social Justice Leadership And Black Male Academic Achievement, Brain L. Gibson

All Dissertations

Black males in K-12 school systems across the nation continue to face formidable challenges such as low graduation rates, overrepresentation in special education, high out-of-school suspension rates, and underperformance in the classroom (Bryan, 2020; Grace & Nelson, 2019; Johnson & Bryan, 2017; Powell, 2018). Despite decades of research devoted to addressing the educational and social injustices Black males face, many scholars contend that such attention has resulted in minimal change, and a revised narrative for managing the state of Black males is needed (Adedoyin et al., 2019; Carter, 2019; Johnson & Bryan, 2017).

Some scholars have insisted that the academic …

Joint Linear And Nonlinear Computation With Data Encryption For Efficient Privacy-Preserving Deep Learning, Qiao Zhang

Electrical & Computer Engineering Theses & Dissertations

Deep Learning (DL) has shown unrivalled performance in many applications such as image classification, speech recognition, anomalous detection, and business analytics. While end users and enterprises own enormous data, DL talents and computing power are mostly gathered in technology giants having cloud servers. Thus, data owners, i.e., the clients, are motivated to outsource their data, along with computationally-intensive tasks, to the server in order to leverage the server’s abundant computation resources and DL talents for developing cost-effective DL solutions. However, trust is required between the server and the client to finish the computation tasks (e.g., conducting inference for the newly-input …

New Titanate Bioceramic Nanomaterials For Drug Delivery And Controlled Release, Seaab Imad Sahib

Graduate Theses and Dissertations

Nanomaterials have attracted much attention for biomedical applications due to their unique characteristics that are proven to be potential in cell sensing, drug delivery, biological membrane penetration, biocompatibility, and tissue adhesion. The outcomes of this dissertation presented in chapter III-V mainly discuss new approaches in drug delivery, cellular uptake improvement, and neuronal regeneration and protection using a well-optimized titanium-based nanomaterial. In particular, Chapter III summarizes the impact of two different versions of the titanate nanowires on ameliorating the delivery of the antimicrobial and anticancer drug in vitro. Those drugs were loaded on the surface of the fabricated nanowires and characterized …

Academic Resilience, Student Engagement, And Academic Achievement Among Black Male Undergraduates At Predominantly White Institutions, Henry C. Mccain Iii

Dissertations

The proportion of Black men enrolled in college is representative of the Black male population in the U.S. (Toldson, 2019). However, an investigation of the 2010 college entry cohort of Black men showed that only 34% graduate within six years (National Center for Education Statistics; NCES, 2019). The disparity in Black male graduation rate is clearer when compared to other races such as White men (61%), Hispanic men (50%), and Asian men (70%) (NCES, 2019). Within-group disparities also exist in that Black women graduate at a rate of 44% (NCES, 2019). Much of the literature on Black undergraduates has been …