Physical Sciences and Mathematics Commons^™

Soil Organic Carbon Depth Profiles And Centennial And Millennial Decay Rates In Tidal Marsh, Mangrove And Seagrass Blue Carbon Ecosystems, Nerea Piñeiro-Juncal, Miguel Ángel Mateo, Carmen Leiva-Dueñas, Eduard Serrano, Karina Inostroza, Montserrat Soler, Eugenia T. Apostolaki, Paul Lavery, Carlos M. Duarte, Anna Lafratta, Oscar Serrano

Research outputs 2022 to 2026

The management of coastal blue carbon ecosystems can contribute to mitigate anthropogenic greenhouse gas emissions. However, limited information on soil organic carbon (OC) decay rates in tidal marsh, mangrove, and seagrass soils hinders their inclusion in climate strategies and carbon-crediting schemes. Here, we analyzed downcore OC trends in 3761 soil cores from blue carbon ecosystems worldwide. A decrease in OC content with soil depth was measured in 63% of the cores, whereas stable and increasing trends were observed in 22% and 15% of the cores, respectively. Based on 85 profiles where OC decay could be modelled, the OC decay rate …

Zero Day Malware Detection With Alpha: Fast Dbi With Transformer Models For Real World Application, Matthew Gaber, Mohiuddin Ahmed, Helge Janicke

Research outputs 2022 to 2026

The effectiveness of an AI model in accurately classifying novel malware hinges on the quality of the features it is trained on, which in turn depends on the effectiveness of the analysis tool used. Peekaboo, a Dynamic Binary Instrumentation (DBI) tool, defeats malware evasion techniques to capture authentic behavior at the Assembly (ASM) instruction level. This behavior exhibits patterns consistent with Zipf's law, a distribution commonly seen in natural languages, making Transformer models particularly effective for binary classification tasks. We introduce Alpha, a framework for zero-day malware detection that leverages Transformer models, Support Vector Machines (SVMs) and ASM language features. …

Spectroscopic Studies Of Metal Containing Molecules Under Jet-Cooled Conditions Using Laster-Induced Fluoresence (Lif) And Dispersed Fluorescence (Df) Techniques., Md Touhidul Islam

Electronic Theses and Dissertations

This dissertation examines the jet-cooled spectroscopy of the calcium propoxide radical (CaOC₃H₇) to understand how increasing molecular complexity reshapes symmetry, electronic degeneracy, and vibronic coupling. Moving from Ca–OCH₃ to Ca–OC₃H₇ lowers symmetry (C₃v → Cs → C₁) and exposes effects such as spin–orbit splitting and both Jahn–Teller and pseudo–Jahn–Teller distortions. These features remodel the excited-state potential surfaces and are directly observable with laser-induced fluorescence (LIF) and dispersed fluorescence (DF). A central goal is to evaluate whether CaOC₃H₇ supports the near-diagonal vibronic branching needed for efficient optical cycling, while also highlighting implications for catalysis and astrochemistry, where precise spectral fingerprints guide …

Optical, Mechanical, And Transport Characterization Of Two-Dimensional Magnetic Materials., Hiruni Weerahennedige

Electronic Theses and Dissertations

This work investigates the structural, magnetic, thermoelectric, and optoelectronic behavior of layered two-dimensional (2D) materials, with emphasis on Fe₃GeTe₂, Ni-substituted Fe₃GeTe₂ alloys, and GeSe. The study aims to clarify how dimensionality, alloying, and external perturbations influence charge transport, magnetic ordering, and light-matter interactions in van der Waals crystals. Single crystals of Fe₃GeTe₂ and (Ni_xFe_1-x)₃GeTe₂ (x = 0-1) were synthesized by chemical vapor transport and characterized using X-ray diffraction, Raman spectroscopy, and transmission electron microscopy. Angle-resolved polarized Raman spectroscopy resolved symmetry-dependent phonon modes and …

Symmetry, Stability, And Robust Optimization Strategies For Nonorthogonal Multiconfiguration Self-Consistent Field Wavefunctions., Zihui Song

Electronic Theses and Dissertations

The "different orbital different configuration" (DODC) framework is a general formulation of multireference wavefunctions that allows each configuration (determinant) to possess its own set of optimized molecular orbitals, rather than sharing a common orbital basis as in conventional orthogonal configuration interaction (CI) or Complete Active Space Self-Consistent Field (CASSCF) methods. One prominent example of the DODC framework is the Nonorthogonal Configuration Interaction (NOCI) method, which relaxes the orthogonality constraint between the orbitals of different configurations. This relaxation enables a compact yet flexible description of systems exhibiting strong correlation. By employing multiple nonorthogonal reference determinants, NOCI naturally incorporates orbital relaxation and …

By The Numbers: Numeracy, Religion, And The Quantitative Transformation Of Early Modern England (Book Review), Calvin Jongsma

Faculty Work Comprehensive List

Reviewed Title: By the Numbers: Numeracy, Religion, and the Quantitative Transformation of Early Modern England by Jessica Marie Otis. New York, NY: Oxford University Press, 2024. 264 pp. ISBN: 9780197608777.

Spatial–Temporal Evolution Of The Box Springs Plutonic Complex, Riverside, Ca, Mateo Ospino Díaz

Loma Linda University Electronic Theses, Dissertations & Projects

The mechanisms of pluton emplacement into continental crust have long been debated in igneous geology, with early models emphasizing forceful processes such as ballooning, later contrasted by alternative emplacement mechanisms including diapirism, incremental assembly, stoping and, emplacement by sheets and dikes. These contrasting perspectives highlight the complexity of the construction of mid-crustal intrusions and the need for case studies that integrate multiple datasets. The Box Springs Plutonic Complex (BSPC) in the northern Peninsular Ranges Batholith (PRB) preserves structural, textural, and compositional features that record its emplacement and internal construction. Although its lithology, structure, and geochemistry have been described, an integrated …

Computational Expressions Of Void Reactions In Extended Chemical Reaction Network Models, Aiden J. Massie

Theses and Dissertations

Chemical Reaction Networks (CRNs) are a system of abstraction of real-world chemical dynamics. Each CRN system is defined as a pair of molecular species and reaction rules, which consume a set of reactant species and create a new set of product species. In this paper, we investigate the simple class of void reactions, which cannot create new species and are computationally weak with small-enough sizes in basic CRNs. Here, we study their computational expression in more powerful extended CRN models. Specifically, we consider the Step CRN model, in which new species are added into the system through a sequence of …

Copyright Ownership And Duration Of Ai-Authored Works, Cheng Lim Saw

Research Collection Yong Pung How School Of Law

On the assumption that Parliament has endorsed the notion of AI authorship and the prospect that copyright may well subsist in works created autonomously by the AI itself, this essay further explores allied issues surrounding the ownership and duration of copyright in AI-authored works.

When Less Language Is More: Language-Reasoning Disentanglement Makes Llms Better Multilingual Reasoners, Weixiang Zhao, Jiahe Guo, Yang Deng, Tongtong Wu, Wenxuan Zhang, Yulin Hu, Xingyu Sui, Yanyan Zhao, Wanxiang Che, Bing Qin, Tat-Seng Chua, Ting Liu

Research Collection School Of Computing and Information Systems

Multilingual reasoning remains a significant challenge for large language models (LLMs), with performance disproportionately favoring high-resource languages. Drawing inspiration from cognitive neuroscience, which suggests that human reasoning functions largely independently of language processing, we hypothesize that LLMs similarly encode reasoning and language as separable components that can be disentangled to enhance multilingual reasoning. To evaluate this, we perform a causal intervention by ablating language-specific representations at inference time. Experiments on 10 open-weight LLMs spanning 11 typologically diverse languages show that this language-specific ablation consistently boosts multilingual reasoning performance. Layer-wise analyses further confirm that language and reasoning representations can be effectively …

Instance-Level Video Depth In Groups Beyond Occlusions, Yuan Liang, Yang Zhou, Ziming Sun, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

Depth estimation in dynamic, multi-object scenes remains a major challenge, especially under severe occlusions. Existing monocular models, including foundation models, struggle with instance-wise depth consistency due to their reliance on global regression. We tackle this problem from two key aspects: data and methodology. First, we introduce the Group Instance Depth (GID) dataset, the first large-scale video depth dataset with instance-level annotations, featuring 101,500 frames from real-world activity scenes. GID bridges the gap between synthetic and real-world depth data by providing high-fidelity depth supervision for multi-object interactions. Second, we propose InstanceDepth, the first occlusion-aware depth estimation framework for multi-object environments. Our …

Content And Consequences: Impact Of Representation In Stem Higher Education Instructional Content On Marginalized Students, Nichole Ventura

Doctorate in Education

This qualitative study examined representation of historically marginalized students in STEM instructional content at the higher education level and its impact on their learning experiences. Despite growing diversity initiatives in STEM enrollment, curricular materials often fail to reflect the identities of underrepresented students. Using critical theory and interpretivist approaches, this research investigated how representation—or its absence—shapes students' sense of belonging, academic identity formation, and persistence. Through semi-structured interviews with undergraduate students from historically marginalized backgrounds, and purposeful sampling, this study captured the lived experiences of students engaging with STEM instructional materials. Interview protocols explored how students perceive their representation in …

Investigating Programming Behaviors To Understand Student Engagement And Experience In Introductory Programming Courses, Marcus Eugene Gubanyi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Introductory programming courses are foundational to developing students’ problem-solving abilities and shaping their persistence in computing pathways. Engagement with programming tasks plays a central role in student learning and experience. Many research measures, including self-reports and code submissions, offer only a limited view of student engagement with programming tasks. This dissertation leverages programming process data, consisting of keystrokes and compilation events, to capture the programming process as it unfolds and to investigate observable programming behaviors. Guided by educational theories, three studies examine how students’ programming behaviors vary across instructional and assessment contexts, how they relate to motivational profiles, and how …

Making Deep Neural Networks Trustworthy: Intelligibility And Safety Through Symbolic Methods, Eleanor Catherine Quint

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The rapid adoption of deep learning has come at the cost of properties long valued in artificial intelligence: intelligibility and safety. This dissertation develops methods that restore these properties by coupling neural networks with symbolic structure.

First, for supervised classification, I propose a differentiable decision tree integrated with a supervised variational autoencoder. The resulting model maintains competitive accuracy and generative performance while exposing clear macro-features in its latent space, improving interpretability.

Second, for reinforcement learning, I extend constrained Markov decision processes by specifying constraints in formal languages. This formal language constrained MDP enables the use of automata for state augmentation, …

Changepoint Detection As Model Selection: A General Framework, Michael A. Grantham

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation presents a general framework for changepoint detection based on ℓ₀ model selection. The core method, Iteratively Reweighted Fused Lasso (IRFL), improves upon the generalized lasso by adaptively reweighting penalties to enhance support recovery and minimize criteria such as the Bayesian Information Criterion (BIC). The approach allows for flexible modeling of seasonal patterns, linear and quadratic trends, and autoregressive dependence in the presence of changepoints.

Simulation studies demonstrate that IRFL achieves accurate changepoint detection across a wide range of challenging scenarios, including those involving nuisance factors such as trends, seasonal patterns, and serially correlated errors. The framework is …

Two Topics In Survival Analysis: Restricted Distance Covariance Test For Non-Proportional Hazard And A New Estimation For Dropout Rate, Ruizhe Yin

Graduate Theses and Dissertations

When treatment effects change over time, standard statistical methods, such as the log-rank test and the Cox proportional hazards model, may give misleading results. This dissertation presents the restricted distance covariance (rdcov) test, a nonparametric method that compares survival curves between groups within a chosen study period [0, τ] using right censored data. The statistic measures the dependence between pre-specified group labels and survival times using pairwise distances from Kaplan-Meier estimates. Our method does not rely on the proportional hazards assumption, and it equals zero only when survival functions are identical across groups. Thus, this test can be applied to …

Stochastic Functional Data-Driven Models For Real-Time Battery Health Forecasting Under Dynamic Operating Conditions, Joshua Owusu

Electronic Theses and Dissertations

This thesis provides an effective statistical model to predict the real-time state of lithium-ion batteries for reliable Battery Management Systems (BMS). It highlights battery data (voltage, current, temperature) as smooth functional curves. The principal method demonstrates diminishing trends to health outcomes like State of Health (SoH) and Remaining Useful Life (RUL) by employing Functional Principal Component Analysis (FPCA) and Bayesian Functional Linear Models (FLMs). The primary objective is to figure out how uncertain forecasts are. Simulations demonstrate that the highest accuracy (lowest MSE) is achieved through low noise levels along with large sample sizes. The final system provides a highly …

Soil Characterization With Proximal Geophysics, Sophia M. Becker

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

High quality soil data is crucial for addressing numerous threats to human well-being such as water scarcity, food insecurity, and intensified natural disasters. True soil property values are determined by analyzing soil samples in a laboratory, but soil sampling is often expensive and time-consuming. Some in-field point sensors and remote sensing products are available to measure soil properties, but they have inherent limitations in measurement extent and resolution. Geophysical methods can fill the measurement scale gap between point measurements and remote sensing products, but various research questions remain open. This dissertation aims to advance understanding of geophysics-derived soil property measurements …

An Integrated Modeling Framework To Evaluate Circularity Of The Corn–Water–Ethanol–Beef Nexus, Heydi Han

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation examines the transition from conventional linear agricultural and food bioenergy systems toward more circular, resilient, and resource-efficient configurations. Prior research indicates that spatial and temporal variability in soil, weather, animal biological responses, and management decisions strongly influences productivity, nutrient-use efficiency, and profitability. Studies have also shown that a diversified circular system can buffer these sources of variability, improving stability and adaptive capacity. Building on these insights, the central focus of this work is to develop an integrated modeling framework to evaluate circularity within the Corn-Water-Ethanol-Beef (CWEB) nexus and explore how climate variability and management choices shape system-wide performance. …

Investigating Molecular Rotation And Vibration With Ultrafast Electron Diffraction, Haoran Zhao

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Ultrafast electron diffraction (UED) has emerged since the late 20th century as a powerful technique for resolving molecular dynamics. With its high spatial and temporal resolution, UED can now measure rotational motion induced by linearly polarized, nonresonant, nonadiabatic laser pulses—one of the fundamental molecular degrees of freedom with broad applications. By combining laser-induced alignment with UED, new capabilities such as three-dimensional structural retrieval and isotope detection have been demonstrated, as discussed in Chapter 2.

In Chapter 3, three symmetry relations in the coefficients of rotational wave packets are identified and derived, reducing the computational cost of simulating asymmetric-top molecular alignment …

Electrical And Magnetic Properties Of Ferroic Oxide Thin Films And Free-Standing Membranes, Qiuchen Wu

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation presents a comprehensive study of the electrical, magnetic, and transport properties of epitaxial ferroic oxide thin films and free-standing membranes, including ferroelectric PbZr_0.2Ti_0.8O₃ (PZT) and ferrimagnetic NiCo₂O₄ (NCO).

We evaluate the effects of electrostatic and mechanical boundary conditions on the ferroelectric properties of free-standing PZT membranes by transferring them on three types of base layers: the metallic Au, strongly correlated oxide La_0.67Sr_0.33MnO₃ (LSMO), and 2D semiconductor MoS₂. The coercive field and domain wall roughness depend sensitively on the metallicity and surface roughness of …

Evaluating Fall And Spring Planted Cover Crops For Integrated Management Of Herbicide Resistant Palmer Amaranth And Effect On Soil Health, Vipin Kumar

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Herbicide-resistant Palmer amaranth (Amaranthus palmeri S. Watson) pose a severe threat to agronomic crop productivity in the United States, including corn and soybean production in Nebraska. Therefore, there is an urgent need for diversified and sustainable management approaches. Integrating cover crops (CCs) with herbicide programs represents a promising strategy to achieve Palmer amaranth suppression, sustain crop yields, and contribute to long-term soil health in irrigated corn–soybean production systems in Nebraska.

A meta-analysis of 41 studies and 595 paired observations demonstrated that CCs reduced Amaranthus spp. density and biomass by 37–59% depending on the growing season, with grasses and mixtures …

Synthesis And Study Of Stable Organic Radicals For Mri Contrast Agents And New Materials, Sabina Dhakal

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The first part of this dissertation focuses on the design, synthesis, and characterization of a thermally robust S =1/2 phototetrazolinyl monoradical and the development of synthetic methodologies for a high-spin (S = 1) phototetrazolinyl diradical. Electrochemical studies of the phototetrazolium cation (precursor to the monoradical) revealed a remarkably narrow electrochemical band gap (Ecell ≈ 0.82 V), suggesting promising electrical conductivity. Thermal analysis of the monoradical demonstrated excellent stability, with the onset of decomposition at 232 °C. Building on the excellent thermal stability and promising properties for electrical conductivity of the monoradical, we developed two condensation-based synthetic routes that provide viable …

Rainfall-Runoff Modelling In An Indonesian Humid Tropical Area Using Satellite-Based Precipitation Products, Noordiah Helda

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores three rainfall-runoff models in the humid tropical regions of Indonesia using satellite-based precipitation products (SBPPs) and develops integrated machine-learning modeling frameworks. Several ground-based observations from BMKG (Badan Meteorologi, Klimatologi, dan Geofisika (also known as the Indonesian Agency for Meteorology, Climatology, and Geophysics)) stations across Indonesia (133−165 stations) are compared and evaluated against satellite products, indicating that GPM performs well, with R-squared values ranging from 0.54 to 0.76 and correlation coefficients ranging from 0.45 to 0.69, respectively.

In the Martapura Watershed, South Kalimantan, due to a lack of observational discharge data, streamflow was generated using the FJ Mock …

Global, Continental, And Local Scale Paleoenvironmental Reconstruction Methods For Interpreting The History Of Miocene North America And The Great Plains, Willow Hue Nguy

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The Miocene of North America is characterized by dynamic changes in herbivore communities, habitat composition, and global climate. Long-term cooling and drying trends influenced large changes in floral and faunal communities. The Great Plains, North America shifted from closed-canopy biomes to open-canopy biomes with C3-grasses to biomes with C4-grasses. This shift affected the herbivore communities as browsing-adapted ungulates were replaced by grazing-adapted ungulates. Much focus has centered on the Great Plains, so it is not well understood how the changes in biomes compare to other regions of North America. The models used for vegetation density indicate open-canopy biomes since at …

Residential Hvac Installation Faults: Field Prevalence, Drivers, And Energy Impacts, Seyed Ali Rooholghodos

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Faults in residential comfort systems can have detrimental effects on the performance of the system, reducing the energy efficiency, affecting indoor comfort, and shortening equipment lifespan. Many of the faults occur at installation. However, there has not previously been a systematic and nationally representative study to indicate the prevalence of the faults, meaning the distribution of faults by fault type and fault intensity. Understanding true fault prevalence is essential to be able to identify derivers, and to assess the incremental electricity consumption of the new installation systems.

This study presents on-site data from 341 new central cooling systems—air conditioners and …

Large-Scale Experimental Study On The Impact Of Air Cleaning & Ventilation On Indoor Air Quality And Student Illness-Related Absenteeism, Daud Nosham

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This large-scale randomized experimental field study investigated the effect of portable air purifiers (PAPs) on classroom’s air quality and student’s illness related absenteeism. PAPs were installed in 317 classrooms from various school districts located in Eastern Nebraska. The classrooms were randomly assigned into four conditions: three treatment conditions (T1, T2 & T3) and one control condition (device without any filter). T1 was equipped with HEPA filters, T2 added Activated Carbon (AC) layer to HEPA, and T3 further integrated Germicidal Ultraviolet (GUV) alongside HEPA and AC filters. The measured variables were carbon dioxide (CO2), fine particles (PN2.5) and coarse particles (PNcoarse), …

Assessing Crop Rotation Productivity, Soil Health, And Fertility, And Economic Performance, To Enhance Semi-Arid High Plains Cropping Systems Sustainability, Ezequiel Maria Villamil

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Sustainable crop production in the semi-arid High Plains of Nebraska faces challenges from limited precipitation, high interannual variability, and economic risk. This dissertation investigates the long-term productivity, water use, soil health, and economic sustainability of dryland crop rotations, with emphasis on the role of pulses as alternatives to fallow.

Chapter 1 analyzes nearly three decades (1995–2023) of on-farm data from the High Plains Agricultural Laboratory (Sidney, Nebraska) to compare seven crop rotations, including wheat, corn, millet, sunflower, and field peas. Results showed that wheat–corn–fallow (W–C–F) consistently outperformed traditional wheat–fallow (W–F) and more intensified four-year rotations, providing the highest grain yields, …

Detecting Prescribed Fire, Haying And Grazing Events Via Remote Sensing To Create Grassland Disturbance Landcovers For The Ring-Necked Pheasant (Phasianus Colchicus), Megan A. Baldissara

School of Natural Resources: Dissertations, Theses, and Student Research

This dissertation developed disturbance detection models to fulfill the need for remote sensing landcover products describing grassland structure. The use of landcover products derived from remote sensing is increasing over time in pheasant (Phasianus colchicus) research. Such landcover, however, does not provide relevant pheasant structural habitat information (Chapter 1). Pheasants require tall, high-density grassland for nesting, tall grassland with medium density for brood rearing, and tall grassland for wintering. Time since disturbance can serve as a proxy for structure, as it shapes vegetation by removing biomass and resetting succession. Disturbance is easier to detect than structure with current …

On Bayesian Empirical Likelihood-Based Method For Complex Survey Data With Application To Non-Probability Sampling, Md Hasibur Rahman

Department of Statistics: Dissertations, Theses, and Student Research

This thesis develops a Bayesian empirical likelihood (BEL) framework for inference under complex survey designs and extends it to non-probability sampling. Parametric likelihood based methods are difficult to apply to complex survey data because the likelihood is rarely available in closed form. EL provides a flexible alternative by replacing the parametric likelihood with an empirical likelihood constructed from moment conditions. The proposed method first integrates empirical likelihood constraints with survey design features then extends BEL to non-probability sampling through selection models and design consistent restrictions. Posterior inference is carried out using a Metropolis–Hastings MCMC algorithm. A real-data analysis further illustrates …