Digital Commons Network^™

Beta Lactams Anticancer Effect On Human Breast Cancer, Mcf-7 Cell Line, Ailis A. Abalos

Theses and Dissertations

Cancer is a disease where abnormal cells replicate uncontrollably in that same region and/or other parts of the body. One in eight women are diagnosed with breast cancer, thus making it the second leading cause of cancer-related deaths in the U.S. Chemotherapy, is the utilization of medicinal compounds (drugs) to treat cancer. While most are nonspecific and target both cancer and healthy cells, more emphasis is on developing drugs with specificity (only target tumor cells) and low toxicity. Interestingly, Beta Lactams (β-lactams) have emerged as a class of compounds that are effective in the treatment of various cancers. The benefits …

Modulating Covalency In A Ni-H-Al Subunit: Synthesis And Characterization Of A Series Of Electronically Differentiating Ni-Al Heterometallics, Aleida Guadalupe Gonzalez

Theses and Dissertations

Metal hydrides are moieties that are present in a variety of applications as intermediates in catalysis. Despite the vast utilization of metal hydrides, monometallic metal hydride complexes bear limitations in inert-bond activation and functionalization. A strategy to overcome these limitations and access more challenging reactivity is utilizing metal-metal cooperativity on a single platform to further activate hydride moieties. Although incorporating multiple metal centers on a single ligand scaffold has been realized, access to heterometallic hydride-bearing complexes is a greater synthetic challenge. Given the limitations in accessing such systems, the reactivity and electronic structure of heterometallic hydrides are seldom studied. Recently, …

A Deep Dive Into The Conformations Of Fluorine-Substituted Benzoic Acids And Ethanesulfonic Acid And Spectroscopic Characterizations Of Their Hydrogen-Bonded Complexes, Alitza Gianina Gracia

Theses and Dissertations

Microwave spectroscopy is a technique used to study the molecular structures of a wide range of systems. The first part of the thesis focuses on fluorinated benzoic acids and complexes they form through hydrogen bonding to explore the fluorination effect, while the last part shifts to ethanesulfonic acid and its interaction with water. The study of 3,4,5-triflurorbenzoic acid with formic acid offers insight on the proton tunneling process, which is a process that occurs in many chemical and biological processes. Microwave spectroscopy can help provide dynamic information for the better understanding of this fundamental process. Solvation is another topic that …

The Effects Of Using Dynamic Geometry Software While Exploring The Properties Of Quadrilaterals, Jose J. Jaramillo

Theses and Dissertations

The purpose of my study was to determine the effectiveness of using dynamic geometry software while exploring the properties of quadrilaterals. Dynamic geometry software can be effective if used properly in the exploration process as students construct their own knowledge through constructivism. Students were given the Van Hiele Test as a pretest to determine their van Hiele level prior to taking a high school geometry course. The results determined that the majority of the students were not at the level needed for the course, which is typically taught at a van Hiele level 3. Students in the treatment group used …

Conditional Optimal Sets And The Quantization Coefficients For Some Uniform Distributions, Evans Nyanney

Theses and Dissertations

Bucklew and Wise (1982) established that the quantization dimension of an absolutely continuous probability measure on a Euclidean space equals the Euclidean dimension of the space, and that the quantization coefficient is finite and positive. This thesis explores the variability of quantization coefficients for uniform distributions on various geometric structures, including line segments, circles, and regular polygons. We derive the conditional optimal sets of n-points and calculate the n-th conditional quantization errors for uniform distributions under different conditions. On line segments, we identify optimal point distributions as either equally spaced or geometrically spaced towards fixed end-points. For circles, we analyze …

Application And Analysis Of Machine Learning And Deep Learning Algorithms In Detection Of Ddos Cyberattacks, Dipok Deb

Theses and Dissertations

A Distributed Denial-of-Service (DDoS) attack involves overwhelming a target system's data bandwidth or computational resources, often using multiple attack systems, aiming to slow down or disable the targeted system. Detecting and mitigating DDoS attacks effectively remains challenging due to their varying characteristics. One of the promising approaches involves developing an AI based Intrusion Detection System (IDS) against cyberattacks. In this study, we aim to develop an AI based Intrusion Detection System (IDS) for DDoS threat detection using Machine Learning, Deep Learning, or hybrid techniques. Different Machine Learning (ML) and Deep Learning (DL) algorithms like Random Forest (RF), Naïve Bayes (NB), …

On The Development Of A Software Pipeline For Automatic Detection Of Transients With The Transient Optical Robotic Observatory Of The South, Alejandro Reyes

Theses and Dissertations

The Transient Optical Robotic Observatory of the South (TOROS) telescope has the mission to follow up transient events in the southern hemisphere by surveying the visible sky and responding to detection alerts from space and ground based observatories, such as the Fermi Gamma-Ray Telescope, the Swift X-ray Telescope, and the LIGO VIRGO Kagra gravitational wave detectors. In this work we study the automation of various data analysis pipelines and instrumentation control under development for implementation at the TOROS observatory. I present the design of libraries and routines for data organization, archival, and data reduction, as well as a tool to …

Ecological Effects On Greenhouse Gas Emissions In Vegetated Estuarine Soils Of The Lower Laguna Madre, David R. De La Garza

Theses and Dissertations

Coastal wetlands are important ecosystems that provide numerous ecosystem services including erosion control, habitat for fauna, and carbon sequestration. Notably, coastal wetlands are producers of greenhouse gases (GHGs) but are able to store significant amounts of carbon relative to their surface area. Mangrove forests are amongst the most effective ecosystems for carbon sequestration. Soil emits (GHGs) containing carbon (such as carbon dioxide (CO2) and methane (CH4)), which are produced by organic matter decomposition and soil organic carbon mineralization, and both are an important component of the global carbon cycle. Soil emissions may be affected by a variety of factors including …

Contribution Of Dentoalveolar Heights On Facial Heights In Class I And Class Ii Untreated Subjects, Mira Bharat Suvagia

Master's Theses (2009 -)

Objective: This research aims to investigate the impact of dentoalveolar heights on craniofacial growth and the development of Class I and Class II malocclusions in untreated subjects aged 6-18 years. The study seeks to establish relationships between dentoalveolar heights and anterior and posterior facial heights. The findings contribute to understanding the dynamic interplay between dentoalveolar growth, mandibular rotation, and facial height establishment, shedding light on critical aspects of craniofacial development. Materials and Methods: The study draws upon cephalograms from the University of Michigan Growth Study, encompassing untreated Class I and Class II subjects aged 6-18 years. A subsample of 408 …

July 2024 News, Office Of Sustainability

Office of Sustainability Newsletter

No abstract provided.

Diffuse Reflectance Spectroscopy For Optical Characterizations Of Orthotopic Head And Neck Cancer Models In Vivo, Pranto Soumik Saha, Jing Yan, Caigang Zhu

Markey Cancer Center Faculty Publications

We demonstrated an easy-to-build, portable diffuse reflectance spectroscopy device along with a Monte Carlo inverse model to quantify tissue absorption and scattering-based parameters of orthotopic head and neck cancer models in vivo. Both tissue-mimicking phantom studies and animal studies were conducted to verify the optical spectroscopy system and Monte Carlo inverse model for the accurate extraction of tissue optical properties. For the first time, we reported the tissue absorption and scattering coefficients of mouse normal tongue tissues and tongue tumor tissues. Our in vivo animal studies showed reduced total hemoglobin concentration, lower tissue vascular oxygen saturation, and increased tissue scattering …

A Probabilistic Approach To Estimate The Temporal Order Of Pathway Mutations Accounting For Intra-Tumor Heterogeneity, Menghan Wang, Yanqi Xie, Jinpeng Liu, Austin Li, Li Chen, Arnold Stromberg, Susanne Arnold, Chunming Liu, Chi Wang

Markey Cancer Center Faculty Publications

The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumori- genesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this …

Response To Replication Stress And Maintenance Of Genome Stability By Wrn, The Werner Syndrome Protein, David K. Orren, Amrita Machwe

Markey Cancer Center Faculty Publications

Werner syndrome (WS) is an autosomal recessive disease caused by loss of function of WRN. WS is a segmental progeroid disease and shows early onset or increased frequency of many characteristics of normal aging. WRN possesses helicase, annealing, strand exchange, and exonuclease activities and acts on a variety of DNA substrates, even complex replication and re- combination intermediates. Here, we review the genetics, biochemistry, and probably physiological functions of the WRN protein. Although its precise role is unclear, evidence suggests WRN plays a role in pathways that respond to replication stress and maintain genome stability particularly in telomeric regions.

Kaleidoscopic Federalism, Roger Karapin

Publications and Research

This chapter focuses on state-level climate policies in the United States in the context of its federalist system. The empirical focus is on policies that have been adopted by many states and that have been most effective in reducing greenhouse gas (GHG) emissions, which include target setting, emissions trading, and sectoral policies on renewable energy, motor vehicles, appliances, and power plants (Karapin 2016; Karapin/Vogel 2024: ch. 1). It addresses five questions: First, what are the most important policies that state governments have adopted over the last few decades? Second, how have those efforts tied in with federal policies in the …

Assessing Soil Properties For Optimized Irrigation Development In Sudan, Northern Africa, Suhib Hamid, Derek M. Heeren, Aaron R. Mittelstet, Saleh Taghvaeian, Randall S. Ritzema

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Sustainable irrigation methods maximize agricultural productivity in Northern African countries like Sudan. This project evaluates soil properties to develop optimized irrigation strategies for Sudan's arid and semi-arid climate. Assessing soil characteristics such as texture, infiltration rates, and nutrient content informs the selection of modern irrigation systems. Data from 3,192 locations, collected using GPS and ring infiltrometers for infiltration rates, alongside laboratory analyses for soil properties, were employed. A ranking system determined suitable irrigation systems for specific soil classes, considering factors like slope, wind, crop tolerance, available water capacity (AWC), drainage, germination, capital cost, labor cost, maintenance, and evapotranspiration (ET). The …

Incorporating Intrinsic Structures Into Entity Matching And Representation Learning, Ween Jiann Lee

Dissertations and Theses Collection (Open Access)

The proliferation of internet-connected devices and online services has generated vast amounts of user-generated content in various formats, such as text, visual, and spatial information. Despite the potential of advanced deep learning techniques, challenges such as fragmentation, lack of cohesive structure, and the inability to capture intrinsic data structures persist, affecting data amalgamation and quality. Our research addresses these challenges by enhancing entity matching and representation learning across graph, semi-ordered, and spatial data. These advancements have significant implications for applications in transportation, recommendation systems, and urban planning.

In entity matching, we introduce Robust BiPoly-Matching and Semi-Ordered Bidirectional Poly-Matching. Matching records …

Creating And Delivering Audio Descriptions For Videos, Rosiana Natalie

Dissertations and Theses Collection (Open Access)

Despite anti-discrimination regulations mandating the provision of audio descriptions (ADs), the majority of online video content remains inaccessible to blind and low-vision (BLV) individuals. This is because these ADs are either absent or fail to adequately address the diverse and unique needs of the audience. Traditionally, content creators have relied on professionals to author ADs. However, this gold standard may not be accessible for some content creators because this method is still costly and has a long turnaround time. Moreover, when ADs are available, they tend to be static and unalterable, failing to cater to the unique preferences of BLV …

Essays On Artificial Intelligence (Ai) In Management, Bowen Zhou

Dissertations and Theses Collection (Open Access)

This dissertation comprises three essays that investigate the transformative potential of Artificial Intelligence (AI) in business.

Chapter 1 investigates the fundamental issue of how integrating AI within R&D activities influences a firm’s market value. We developed an "AI Index" using patent data and textual analysis. Interestingly, empirical results indicate a negative correlation between AI integration and market value. However, this does not suggest that AI is an unviable avenue for exploration. Further analysis of the boundary conditions reveals that complementary assets are crucial for successful commercialisation, highlighting that while AI adoption is costly, these assets significantly enhance its market value. …

Decentralized Consensus And Governance For Collaborative Intelligence, Huiwen Liu

Dissertations and Theses Collection (Open Access)

The data economy today is becoming increasingly collaborative in nature. Take business intelligence, for example. To unleash the full potential of big data, it is essential to integrate multi-source data depicting entities from a multi-faceted and multi-modal perspective, which, not surprisingly, is not achievable by any company alone. In collaborative intelligence, there are two core issues, namely "trust" and "incentive". The core mechanisms to solve these two problems are consensus and tokenization separately.

To solve the trust problem more effectively, we propose a systematic consensus evaluation framework to investigate whether existing consensus algorithms can do so. After a lot of …

The Impact Of Organizational Dynamic Capability On Collaborative Innovation: A Supply Chain Perspective, Xiangdong Wang

Dissertations and Theses Collection (Open Access)

Innovation capability is one of the most important competitive advantages of the firms, and fully collaborating with partners in the supply chain to form an innovation alliance has been proven can effectively promote the firm’s innovation performance. This research apply case study on China sportswear supply chain with a mixed method, aims to disclose the innovation Black-box and reveal the influencing factors and its mechanism. The study consists of two parts, Study 1 is semi-structured interviews with 32 industry experts, through the analysis of the interview records, we figured out what factors the industry experts believe it can improve the …

Empowering Interprofessional Teams: Exploring Genai With The Health Sciences Library, Jess King, Teresa L. Hartman

Posters and Presentations: Leon S. McGoogan Health Sciences Library

The Leon S. McGoogan Health Sciences Library at the University of Nebraska Medical Center (UNMC) organized workshops to delve into Generative Artificial Intelligence (GenAI) applications in academic medical centers. These sessions, tailored for all skill levels, provided a safe forum for faculty and staff to engage with GenAI, increasing their digital literacy skills. Participants benefited from introductory sessions, hands-on activities, and reflective discussions, gaining practical insights into ethical GenAI use. These workshops form a vibrant GenAI community at UNMC, fostering collaboration and knowledge exchange among healthcare professionals and paving the way for continued technological integration in academic and clinical settings

Functional Multivariable Logistic Regression With An Application To Hiv Viral Suppression Prediction, Siyuan Guo, Jiajia Zhang Ph.D., Yichao Wu, Alexander C. Mclain Ph.D., James W. Hardin, Bankole Olatosi Ph.D., Xiaoming Li Ph.D.

Faculty Publications

Motivated by improving the prediction of the human immunodeficiency virus (HIV) suppression status using electronic health records (EHR) data, we propose a functional multivariable logistic regression model, which accounts for the longitudinal binary process and continuous process simultaneously. Specifically, the longitudinal measurements for either binary or continuous variables are modeled by functional principal components analysis, and their corresponding functional principal component scores are used to build a logistic regression model for prediction. The longitudinal binary data are linked to underlying Gaussian processes. The estimation is done using penalized spline for the longitudinal continuous and binary data. Group-lasso is used to …

Exchange Rates And Fundamentals In Developed And Emerging Markets, Rocky K. Laurel

DLSU Business & Economics Review

This paper investigates the relationship between exchange rates on the one hand and money supply and real output on the other, then compares the relationship in developed and emerging markets. It tests the validity of the flexible price monetary model using in-sample analysis to determine if there are long-term relationships among the variables and out-of-sample analysis to compare the predictive performance of the model against a random walk. It finds evidence for a relationship as predicted by the model, contrary to long-standing findings of no relationship. It also finds some evidence that foreign exchange rates of emerging markets are more …

Review Of Agricultural Biomass Burning And Its Impact On Air Quality In The Continental United States Of America, Sai Deepak Pinakana, Amit U. Raysoni, Alqamah Sayeed, Juan L. Gonzalez, Owen Temby, Dawid K. Wladyka, Katarzyna Sepielak

School of Earth, Environmental, & Marine Sciences Faculty Publications

Burning is a common method to dispose agricultural biomass residue. This practice is widely used by farmers during pre- and post-harvest seasons for crops such as wheat, rice, grass seed, soy, cotton, sugarcane, and corn. Farmers choose this method because it is cost and time effective. These burning activities emit several types of pollutants into the atmosphere, including CH4, SOx, NOx, CO, CO2, and particulate matter of different sizes (i.e., PM1, PM2.5 and PM10). Globally, the United States of America ranks third, preceded by China and India, in greenhouse gas emissions due to agricultural burning activities. According to the 2020 …

Exploring The Effects Of An Alfalfa Leaf-Derived Adsorbent On Microbial Community, Ileal Morphology, Barrier Function, And Immunity In Turkey Poults During Chronic Aflatoxin B1 Exposure, Maria De Jesus Nava-Ramirez, Jing Liu, Juan Omar Hernandez-Ramirez, Xochitl Hernandez-Velasco, Juan D. Latorre, Alma Vazquez-Duran, Guolong Zhang, Roberto Señas-Cuesta, Sergio Gomez-Rosales, Andressa Stein, Billy M. Hargis, Guillermo Tellez-Isaias, Abraham Mendez-Albores, Jesus A. Maguey-Gonzalez

Poultry Science Faculty Publications and Presentations

This article follows-up on our recently published work, which evaluated the impact of the addition of an alfalfa leaf-derived adsorbent in the aflatoxin B₁ (AFB₁)-contaminated diet in regard to the production parameters, blood cell count, serum biochemistry, liver enzymes, and liver histology of turkey poults. This paper presents complementary results on microbial community, ileal morphology, barrier function, and immunity. For this purpose, 350 1-day-old female turkey poults were randomly distributed into five groups: (1) Control, AFB₁-free diet; (2) AF, AFB₁-contaminated diet at 250 ng/g; (3) alfalfa, AFB₁-free diet + 0.5% ( …

Deciphering Water Quality And Algal Dynamics In Clear Lake Through Hyperspectral Analysis Using Emit Data, Wenzhao Li, Shahryar Fazli, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

This study evaluates the potential application of hyperspectral Earth Surface Mineral Dust Source Investigation (EMIT) remote sensing for monitoring harmful algal blooms (HABs) and water quality in Clear Lake, California. The research focuses on correlating the chlorophyll-a (Chl-a) concentrations with EMIT spectral signatures, using waterbody-wide statistical analysis of Chl-a and EMIT data sampling at various lake locations. Results demonstrate distinct spectral signatures associated with varying Chl-a levels, highlighting the potential of hyperspectral imaging in differentiating algae levels and assessing water quality variables. It also indicates the EMIT’s utility in filling data gaps and offering high-resolution monitoring. This study underscores the …

Assessing Rice Phenological Features With Hyperspectral Imaging Insights From Earth Surface Mineral Dust Source Investigation (Emit), Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

In California's Central Valley, water management and crop health, particularly in rice cultivation, are critical. This paper details the application of Earth surface Mineral dust source InvesTigation (EMIT) hyperspectral imaging, specifically employing Spectral Correlation Mapper (SCM) and Spectral Information Divergence (SID), for precise phenological analysis. By aligning EMIT data with Hyperion satellite references, we address spectral and geographical discrepancies. Our methodology includes seasonal sampling of spectral curves to capture the phenological stages of rice. Results show a strong correlation (R ² = 0.86) between August EMIT and Reference dataset, emphasizing EMIT's utility in enhancing agricultural practices and water efficiency in …

Linkages Of The 2022 Unprecedented Global Heatwave Events To Triple-Dip La Niña, Sachi Perera, Joshua B. Fisher, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Heatwaves are influenced significantly by El Niño-Southern Oscillation (ENSO), which alters temperature and precipitation patterns throughout the world. Since 2020, we have witnessed a "triple dip" La Niña conditions persisting for three consecutive years resulting in severe weather and climate driven events globally. In this study, we identified the dominant frequency of Niño 3.4 Sea Surface Temperature (SST) signals and correlated them with regions experiencing unprecedented heat waves in 2022, namely, the Indian Ocean, the North Atlantic around England and Spain, and the Mediterranean Sea. The signal's power spectrum and its three highest power components are determined based on the …

Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Hani Sewilam, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 …

Derivative Propagation Through Vortex Particle Method Simulation, Eric Green, Andrew Ning

Faculty Publications

Automatic differentiation (AD) is a powerful tool for evaluating numerical derivatives. In particular, reverse-mode AD provides numerical gradients in a way that is insensitive to the number of input variables. This makes reverse-mode AD well-suited for solving large optimization problems. However, reverse-mode AD has a particularly large associated memory cost because most intermediate values in operations need to be cached. This is problematic for large problems such as aerodynamics simulations, though, since the memory requirements can quickly become impractical. The solution implemented in this work is to provide analytic pullback expressions for functions for which many of the intermediate values …