Digital Commons Network^™

Asymmetric Positioning Errors In Gnss Time-Series: A Study From Different World Regions, Francesca Silverii, Emilie Klein, Roberto Devoti, Walter Szeliga, Sylvain Michel, Adriano Gualandi, Elisa Trastatti

All Faculty Scholarship for the College of the Sciences

Global Navigation Satellite System (GNSS) plays a fundamental role in monitoring time-dependent ground displacement. However, GNSS daily position time-series can often contain significant outliers, reaching up to several centimetres. These are likely of non-tectonic origin, and, if not properly accounted for, they can significantly impact the accuracy and dependability of the estimation of key parameters for geophysical analyses, such as long-term velocities and transient deformations. Characterizing these outliers can provide information about their possible sources and help us implement mitigation strategies. Asymmetric outliers, that is, those characterized by a primary direction, therefore occurring on one side of the mean time-series, …

Novel R Shiny Tool For Survival Analysis With Time-Varying Covariate In Oncology Studies: Overcoming Biases And Enhancing Collaboration, Yimei Li, Yang Qiao, Fei Gao, Jordan Gauthier, Qiang Ed Zhang, Jenna Voutsinas, Wendy Leisenring, Ted Gooley, Corinne Summers, Alexandre Hirayama, Cameron Turtle, Rebecca Gardner, Jarcy Zee, Qian Vicky Wu

Wills Eye Hospital Papers

PURPOSE: Our study is motivated by evaluating the role of hematopoietic cell transplantation (HCT) after chimeric antigen receptor T-cell (CAR-T) therapy for ALL, a debated topic. Because patients may receive HCT at different times after CAR-T infusion or never, HCT post-CAR-T should be considered as a time-varying covariate (TVC).

METHODS: Standard Cox models and Kaplan-Meier (KM) curves (naïve method) assume that TVC status is known and fixed at baseline, which can yield biased estimates. Landmark analysis is a popular alternative but depends on a chosen landmark time. Time-dependent (TD) Cox model is better suited for TVC although visualizing survival curves …

A Systematic Literature Review On The Influence Of The El Niño Southern Oscillation On Rainfall Variability In Central Java, Indonesia, Sri Endah Ardhi Ningrum Abdullah, Trinah Wati, Wahyu Hardyanto

Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi

The El Niño-Southern Oscillation (ENSO) phenomenon greatly influences rainfall variability in tropical regions, including Central Java, Indonesia. This study employs a Systematic Literature Review (SLR) approach in accordance with the PRISMA guidelines. This study examines 50 articles from 2010 to 2025, as well as conducting a bibliometric analysis using VOSviewer, to identify trends and the evolution of themes. The results of the study indicate that El Niño generally reduces rainfall and increases the risk of drought, while La Niña tends to increase rainfall, potentially causing flooding. The impacts of ENSO extend to agriculture, food security, and water management, and are …

A High-Resolution Daily Precipitation Fusion Framework Integrating Radar, Satellite, And Nwp Data Using Machine Learning Over South Korea, Hyoju Park, Hiroyuki Miyazaki, Menas Kafatos, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) daily precipitation fusion framework that integrates Korea Meteorological Administration (KMA) radar, Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), and Local Data Assimilation and Prediction System (LDAPS) data. The framework employs a Random Forest model augmented with a monthly Empirical Cumulative Distribution Function (ECDF) correction. Auxiliary predictors are incorporated to enhance physical interpretability and stability, including terrain attributes to represent orographic effects, land-cover …

Artificial Intelligence In Higher Education, Opportunities, And Challenges: A Review, Sharifa Alblooshi

All Works

Artificial intelligence (AI) is a growing force of change in higher education, providing assistance to students, teachers, and administrators in teaching, learning, and administration. As AI technologies advance rapidly, they present a combination of significant opportunities and complex challenges. In this study, we examine the role of AI in higher education, highlighting both its positive and negative impacts, as well as current policy gaps and issues arising from its deployment. The literature on the topic was reviewed to determine how AI decisively impacts teaching and learning, the role of AI in assessments and academic integrity, as well as ethics, psychological …

Interpretable Linear Models For Heart Disease Prediction: A Comparative Study, Dipok Deb, Emran Hossain

Data Science and Data Mining

Heart disease remains a leading cause of mortality worldwide, underscoring the importance of accurate and transparent methods for early diagnosis. While many machine learning and artificial intelligence models have demonstrated strong predictive performance, their limited interpretability poses challenges for clinical adoption. In this study, we evaluate three interpretable linear classification models—Generalized Linear Model (GLM) logistic regression, L1-regularized (Lasso) logistic regression, and Linear Discriminant Analysis (LDA)—for heart disease prediction using the Cleveland Heart Disease dataset. Following comprehensive data preprocessing, the models are assessed on a held-out test set using standard evaluation metrics, including accuracy, precision, recall, F1-score, and the area under …

Leveraging Blockchain Technology In Mining Supply Chain Management: Vietnam Coal Mining Case Study, Thu Hang Nguyen, Nguyen Trung Tuan, Hong Anh Le

Journal of Sustainable Mining

The global economy heavily relies on the mining industry for essential resources such as coal, oil, gas, and metal ores. However, the intricate nature of mining operations poses significant challenges in supply chain management (SCM). This research investigates how blockchain technology can address these challenges within mining supply chain management (MSCM). Through a systematic review of existing research and projects, a conceptual blockchain model is proposed to improve mining supply chains’ transparency, traceability, efficiency, and sustainability, specifically focusing on coal supply chain management in Vietnam. The model integrates distributed ledgers, smart contracts, IoT devices, identity management, and consensus mechanisms to …

Patient-Specific Lumped-Parameter Model For Quantifying Vessel-Specific Remodeling And Predicting Right Ventricular Function In Pulmonary Hypertension, Christopher G. Lechuga, Amirreza Kachabi, Mitchel J. Colebank, Claudia E. Korcarz, Farhan Raza

Faculty Publications

Purpose: Pulmonary hypertension (PH) is a heterogeneous disease with patient-specific variability and vessel-specific remodeling, which eventually lead to right ventricular (RV) failure. The gold standard for RV assessment—pressure–volume (PV) loop acquisition—is invasive and limited to specialized settings. This study aims to develop a patient-specific lumped-parameter model that quantifies vessel-specific remodeling and simulates RV PV loops across PH phenotypes using routine clinical data.

Methods: A lumped-parameter model was calibrated using right heart catheterization and echocardiography data. Model agreement was assessed by R2 values for pressure and flow goodness-of-fit, and model-derived hemodynamic metrics were comparedwith clinical values. A dimensionality reduction approach was …

Adaptive Multi-Agent Intelligence: A Dynamic Data Management System For Enhanced Data Quality And Reconciliation, Anthony Taeyang Vigil

USF Tampa Graduate Theses and Dissertations

Organizations struggle with data quality problems that cost them millions of dollars annually. Manual data cleanup and standardizing, also known as reconciliation, can take skilled analysts days to complete and can still contain human errors. This dissertation addresses this challenge by developing and validating the Origin Data Management System, which automates processes that traditionally require days of manual work. The system achieved up to 100% accuracy in standardizing vendor names and identifying CEO information across real-world test datasets from Jefferson County Public Schools, Forbes, and Fortune Magazines. Processing time dropped from days to minutes—a 96-fold improvement over manual methods. These …

Development Status And Existing Problems Of Ion-Solvation Membranes For Electrolysis Of Water, Zheng-Yuan Zhou, Yu-Tao Sun, Zheng-Bang Liu, Chuan-Zheng Wang, Yong-Nan Zhou, Xi Luo, Tian-Chi Zhou, Jin-Li Qiao

Journal of Electrochemistry

Ion-solvaing membranes (ISMs) have received extensive attention in recent years as a key component in electrochemical energy conversion and storage devices. This article provides an overview of structural composition, performance advantages, research progress, ion conduction mechanism and existing issues of ISMs, primarily classifying them according to the matrix structure. A detailed analysis of performance enhancement methods, key performance indicators of ISMs and performance influencing factors is also presented. The article contributes to further optimizing the design and application of ion-solvation membranes, providing theoretical support for the development of fields such as hydrogen production through electrolysis of water and electrochemical energy …

Iron-Involved Orr Electrocatalysts Under The Lens Of In-Situ/Operando Mössbauer Spectroscopy, Sumbal Farid, Jun-Hu Wang

Journal of Electrochemistry

Exploring cost-effective and efficient catalysts for oxygen reduction reaction (ORR) poses a significant challenge, especially in the pursuit of alternatives to precious metals like platinum. Significant advancements have driven electrochemists to develop efficient ORR catalysts using abundant materials, particularly iron (Fe)-based, known for their exceptional performance in ORR. While the crucial function of Fe in boosting ORR catalytic activity is recognized, the connection between material attributes and catalytic performance remains enigmatic. Understanding the dynamic processes involved in oxygen electrocatalysis is paramount for designing precious-metals-free ORR electrocatalysts. Mössbauer spectroscopy stands out as a powerful technique for deciphering the structural characteristics of …

Observation-Based Reconstruction Of High-Resolution Daily Temperature Field Using Lapse-Rate-Constrained Kriging In Complex Terrain: A Nationwide Dataset For South Korea, Youjeong Youn, Menas Kafatos, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

High-resolution air-temperature fields are essential for climate, hydrologic, and ecological applications in complex terrain, yet operational products often lack the spatial detail to resolve topographic effects. We develop an observation-driven reconstruction of daily air temperature fields for South Korea (2024) using ordinary kriging with lapse-rate correction (OKLR), integrating a dense network of over 500 stations from the Automatic Mountain Meteorology Observation System (AMOS) and the Automated Surface Observing System (ASOS). The OKLR framework systematically removes elevation-driven trends using a physically based fixed lapse rate (–6.5 °C km−1), performs kriging on detrended residuals, and reapplies Digital Elevation Model (DEM)-based corrections to …

The Ntp Anode For Aqueous Sodium Ion Batteries: Recent Advances And Future Perspectives, Ming-Li Wang, Xue-Ying Su, Zheng-Xiang Shan, Shu-Zhe Yang, Heng-Rui Guo, Hao Luo, Dong-Liang Chao

Journal of Electrochemistry

Aqueous sodium-ion batteries (ASIBs) have attracted great attention in aqueous batteries due to their merit of high safety. However, the constrained work potential and insufficient chemical stability of anode materials in aqueous electrolytes hinder the large-scale application of ASIBs. Sodium titanium phosphate, NaTi₂(PO₄)₃ (NTP), is considered one of the most promising anode materials for ASIBs due to its excellent electrochemical performance and tunable structure. Recently, great achievements have been made in the development of NTP, however, a comprehensive review of existing studies is still lacking. This article firstly introduces the basic properties of NTP and …

Land Use And Sovereignty Along The Catawba River, Thomas C. Brugh, Lucile C. Rencher

Student Scholarship

This document-based case study explains how land-use change along the Catawba River Corridor (Lancaster and York Counties, South Carolina) has been produced through the interaction of property rights (dominium) and rule-setting authority (imperium), showing why sovereignty continues to shape development even after land disputes appear “settled.” Through analyzing legal records (Treaty of Nation Ford, the 1959 Catawba Division of Assets Act, the 1986 Supreme Court timing decision, and the 1993 Settlement Act), planning documents, parcel records, and field observations, we trace how shifting jurisdiction and title certainty structured what kinds of land uses were possible and when. We argue that …

Handling Missing Data In Copd Research, Chia-Ying Chiu

ETDs from 2020-2029

Chronic Obstructive Pulmonary Disease (COPD) remains a major global health concern and one of the leading causes of death in the United States, affecting approximately 4.6% of adults and reaching a prevalence of 9.4% in Alabama according to 2024 National Health Interview Survey. The disease imposes a substantial burden on quality of life and healthcare costs and contributes to increased disability-adjusted life years and years of life lost, as highlighted by the 2022 Lancet Commission report. Despite its im-pact, COPD is frequently diagnosed only after irreversible lung damage has occurred, largely due to under-recognized symptoms and limited diagnostic tools. Early …

Development Of Salinomycin Analogs As Potential Anti-Cancer Agents, Pavan Goud Juluri

Theses and Dissertations

Salinomycin, a poly-ionophore antibiotic originally isolated from Streptomyces albus, exhibits antimicrobial activity against Gram-positive bacteria. Over the years Salinomycin has been studied in the effects it has on cancer, specifically cancer stem cells. Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. Inhibiting PARP has been explored as a strategy in cancer treatment, particularly in cancers with defective DNA repair mechanisms, such as those with BRCA mutations. The benzo-thiazoles, and -imidazoles are identified as inhibitor scaffolds, which compete with nicotinamide in the binding pocket of human poly- and mono-ADP-ribosylating enzymes. Benzothiazole, and benzimidazole based compounds particularly with modification at …

Investigation Of The Phase Space Of Tungsten Oxides Nanostructures Via Resistive Hot Wire Oxidation For Efficient Electrochemical Energy Storage And Conversion Applications., Krishna Kc

Theses and Dissertations

The synthesis of tungsten oxide (WO3−δ, 0 ≤ δ ≤ 1) nanostructures with controlled phase and morphology remains a significant challenge, particularly for applications in energy conversion and storage. This dissertation presents an eco-friendly and time-efficient method for synthesizing tungsten oxide nanostructures with tailored stoichiometry and crystal phases through the Resistive Hot Wire Oxidation (RHWO) technique. In this method, a tungsten wire is heated via resistive heating in an oxygen environment, and by precisely controlling the growth conditions, we successfully synthesized WO2.72, WO2.76, WO2.80, WO2.83, WO2.90, and WO2.98 phases with controlled morphologies using simple instrumentation. This approach eliminates the need …

Mapping Post-Rainfall Recovery In Arid Regions Using A Hierarchical U-Net, Xin Hong

All Works

The United Arab Emirates (UAE) experienced an extreme rainfall event between April 15 and 17, 2024, and that resulted in severe flooding in its coastal regions. Dubai was among the most affected regions. This study applies a hierarchical deep learning model on PlanetScope imagery to detect flood inundation, quantify flood extent by land cover, and examine short-term recovery dynamics. While earlier work detailed the methodological development of a hierarchical U-Net model (Hong et al., in press), here we emphasize its application for monitoring resilience trajectories in an arid urban environment. Results show that approximately 22 km² of land was …

Mapping Urban Vegetation Changes Using Planetscope Imagery And Gis: A Case Study Of The 2024 Dubai Flood, Sumayya Almansoori, Xin Hong

All Works

In April 2024, unexpected heavy rainfall triggered one of the most severe flooding events in Dubai’s recent history, causing widespread concern for urban infrastructure and green spaces. This study evaluates the flood’s impact on urban vegetation in South Dubai using high-resolution PlanetScope satellite imagery and the Normalized Difference Vegetation Index (NDVI). Vegetation conditions before and after the flood (April 14 and April 18–19, 2024) were quantified and compared using NDVI analysis within QGIS to assess changes in vegetation health and coverage. Results indicate significant declines in vegetation health in areas dominated by intensive turf management, such as Damac Hills and …

Generative Ai Use And Self-Learning In Higher Education: The Role Of Learning Difficulties, Dana Saleh, Areej Elsayary

All Works

The rapid development of GenAI tools and their adoption in education have shown promising potential to personalize learning experiences. However, their effectiveness is influenced by factors such as familiarity, frequency of use, and the impact on self-learning. This study investigates the undergraduate students' familiarity with Generative AI (GenAI) tools, their frequency of use, and the perceived impact of GenAI on self-learning, with particular consideration of differences between students with and without learning difficulties. Prompt engineering is also included as a secondary aspect of students' GenAI experience. The research employed a quantitative survey design, utilizing validated scales to measure familiarity, usage …

Assessing Urban Flooding And Vegetation Impact In Dubai Creek Following The April 2024 Extreme Rainfall, Dana Alhammadi, Xin Hong

All Works

During April 2024, the United Arab Emirates experienced an unusual phenomenon of an intense rainfall episode between April 14 and 18 that resulted in massive flooding in urban environments, particularly low-lying areas such as Dubai Creek. As a tidal waterway with dense urban development and environmentally sensitive zones surrounding it, Dubai Creek is an ideal site for assessing environmental changes caused by to floods. The study employed pre-flood (14 April) and post-flood (18 April) high-resolution PlanetScope satellite images, in combination with QGIS analysis, to evaluate vegetation health and surface water changes. Quantification of affected areas from flooding was achieved through …

Recurrence Of Locally Perturbed Random Walks With Long Jumps, Tamer Oraby, András Telcs

School of Mathematical & Statistical Sciences Faculty Publications

We study the effect of local perturbations on the recurrence of random walks with long jumps. Such walks serve as discrete models for infinite-horizon Lorentz processes, in which a particle can take arbitrarily long steps in specific directions. Motivated by a question of Sinai in the finite-horizon case and its extension by Szász to the infinite-horizon setting, we give recurrence and transience criteria for long-jump walks on Z2 and certain classes of graphs, and we prove that local perturbations in a bounded region do not change the recurrence property. Our proofs combine the Markov chain approach with the electrical network …

Predictions Of Masses For Light Hybrid Baryons, Qi-Nan Wang, Ding-Kun Lian, Wei Chen, Hui-Min Yang, Hua-Xing Chen, Jason N.E. Ho, T. G. Steele

Faculty Work Comprehensive List

Within the method of parity-projected QCD sum rules, we study the mass spectra of light hybrid baryons with 𝐼⁡(𝐽𝑃) =1/2⁢(1/2±),3/2⁢(1/2±),1/2⁢(3/2±),3/2⁢(3/2±) by constructing the local 𝑞⁢𝑞⁢𝑞⁢𝑔 interpolating currents. We calculate the correlation functions up to dimension eight condensates at the leading order of 𝛼𝑠. The stable QCD Lapalce sum rules can be established for the positive-parity 𝑁1/2+,Δ3/2+,Δ1/2+ and negative-parity 𝑁1/2−,𝑁3/2−,Δ1/2− channels to extract their mass spectra. The lowest-lying hybrid baryons are predicted to be the positive-parity 𝑁1/2+ state around 2.01 GeV. These hybrid baryons mainly decay into conventional baryon plus meson final states. We propose to search for the light hybrid …

A Cross-System Analysis Of Structural Commensurability Between Axiomatic Foundations Of Set Theory (Zfc) And The Principles Of Transcendent Wisdom, Mohammadjavad Maarefvand

Comparative Philosophy

Building on observed similarities in uniqueness proofs for the empty set and the Necessary Existent (Wājib al-Wujūd), this study engages the meta-methodological issue of cross-system commensurability. It identifies four instances of structural commensurability between Zermelo-Fraenkel set theory with Choice (ZFC) and Mulla Sadra's Transcendent Wisdom (Ḥikmat al-Muta'āliyah). First, identity principles: the Axiom of Extensionality provides a formal operational criterion analogous to the philosophical principle of identity through absence of distinguishing features. Second, multiplicity mechanisms: ZFC's constructor axioms (bottom-up construction) and emanation principles (top-down explanation) address analogous problems with inverse orientations. Third, transcending limitation: the Axiom of Infinity ensuring quantitative extensional …

Pitfalls Of Multiplied 3d Landforms Projection: Mapping Deep Multilevel Cave Systems In The Alps (Gamssteig Cave System, Göll Massif), Mateusz Golicz, Jacek Szczygieł

International Journal of Speleology

Cave mapping represents one of the most complex challenges in geomorphological cartography, as it must convey the true three-dimensional geometry of subterranean spaces such as overlapping passages, irregular cross-sections, and variable ceiling and floor morphologies, within a two-dimensional framework. This study examines the methodological and interpretive challenges of cave mapping, utilizing the Gamssteighöhle cave in the Austrian Alps as a case study. During the 11 years of exploration, over 10 km of passages were surveyed using the DistoX vector survey method. Yet, the complex morphological forms necessitated deviations from the standard symbology recommended by the International Union of Speleology. Several …

Correlation Analysis Of Factors Associated With Students’ Numeracy Skills Using Decision Tree Algorithms, Yenita Roza, Arisman Adnan, Zul Indra, Tuti Alawiyah

Numeracy

Numeracy is a critical competency for academic and everyday functioning. This study investigates the key factors associated with students’ numeracy skills by employing decision tree algorithms as a data mining technique. The dataset used in this study is educational assessment data from Indonesia. Utilizing a dataset comprising 6,953 entries and 60 variables from Education Report, the research adopts an exploratory approach involving data preprocessing, exploratory data analysis, and decision tree model construction. The findings reveal that students’ literacy skills serve as the most dominant predictor of numeracy proficiency, emerging as the root node in the decision tree structure. Additional associated …

Sparc Grade 2 Integrated Coding-Math Lessons, Spatial Activities And Robot Coding (Sparc)

Spatial Activities and Robot Coding (SPARC)

SPARC-Math Grade 2 Integrated Coding-Math Lessons with related Utah Core Standards and lessons for Spatial and Programming Language and Geometry.

Integrating Adversarial Scenarios Into Llm Security Labs: An Experience Report On A Hands-On Approach, Dominic A. Wilson

Journal of Cybersecurity Education, Research and Practice

This paper presents an exploratory case study detailed as a pedagogical experience report on integrating adversarial Large Language Model (LLM) scenarios into a graduate cybersecurity curriculum. In addition to prompt injection, sophisticated techniques such as jailbreaking and model inversion pose emerging threats that traditional computer security curricula often lack. We present the design and implementation of a structured, hands-on module addressing this gap, utilizing a custom Retrieval-Augmented Generation (RAG) platform with local open-source LLMs. A cohort of 16 graduate students participated in this two-week pilot module, engaging in "red team" activities to actively exploit model alignment and privacy vulnerabilities. The …

Fairmaterials: Ontology Tools With Data Fairification In Development, Alexander Harding Bradley, Jonathan E. Gordon, Balashanmuga Priyan Rajamohan, Van D. Tran, Nathaniel Hahn, Kiefer Lin, Hayden W. Caldwell, Arafath Nihar, Quynh D. Tran, Yinghui Wu, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

The bilingual FAIRmaterials package simplifies the creation and visualization of materials and data science ontologies. FAIRmaterials, available in the Python and R languages, addresses the complexities associated with traditional ontology editors based on manual user input such as Protege (Musen, 2015) with an intuitive workflow and easy-to-use templates, making it accessible to users both experienced and inexperienced with ontologies. The FAIRmaterials package is its ability to programatically convert simple and structured CSV inputs into rich, well-defined ontologies. This capability is designed to support the findability, accessibility, interoperability, and reusability (FAIR) (Wilkinson et al., 2016) of research data and serve as …

Revealing The Fuel Of A Quantum Continuous Measurement-Based Refrigerator, Cyril Elouard, Sreenath K. Manikandan, Andrew N. Jordan, Géraldine Haack

Mathematics, Physics, and Computer Science Faculty Articles and Research

While quantum measurements have been shown to constitute a resource for operating quantum thermal machines, the nature of the energy exchanges involved in the interaction between system and measuring apparatus is still under debate. In this work, we show that a microscopic model of the apparatus is necessary to unambiguously determine whether quantum measurements provide energy in the form of heat or work. We illustrate this result by considering a measurement-based refrigerator, made of a double quantum dot embedded in a two-terminal device, with the charge of one of the dots being continuously monitored. Tuning the parameters of the measurement …