Digital Commons Network^™

The Role Of External Factors In Shaping Carbohydrate Conformational Landscapes, Murat Yaman

Dissertations, Theses, and Capstone Projects

Carbohydrates (glycans) are among the most structurally diverse biomolecules and participate in a wide range of biological processes, including molecular recognition, cell adhesion, immune response, host-pathogen interactions, and cellular signaling. Their biological functions are governed by a complex interplay between sequence, stereochemistry, conformational flexibility, and environmental factors. However, the structural heterogeneity and dynamic nature of glycans present significant challenges for both experimental characterization and theoretical modeling. In particular, the relationships between glycan structure, conformational dynamics, and the resulting potential energy surfaces remain incomplete.

This dissertation investigates how external factors modulate the potential energy surfaces of carbohydrates through a combination of …

Ultrafast Spectroscopy Of Organic Materials In Strong Light–Matter Interaction And Terahertz Optics, Kamyar Rashidi

Dissertations, Theses, and Capstone Projects

Ultrafast spectroscopy is a powerful tool for investigating phenomena that occur on extremely short timescales and for probing ultrabroadband spectral responses enabled by its ultrashort laser pulses. These capabilities are essential for advancing both the fundamental understanding of light–matter interactions and the development of next-generation optoelectronic technologies. The first part of this thesis investigates the ultrafast dynamics of organic exciton–polaritons and their application to controlling molecular excited-state processes using momentum-resolved pump–probe spectroscopy. A major challenge in these systems is the dark-state problem, where photoexcitation predominantly populates long-lived excitonic reservoir states that obscure the in trinsic dynamics of the hybrid light–matter …

Generalized Logit Adjustment: Improved Fine-Tuning By Mitigating Label Bias In Zero-Shot Vision Models, Beier Zhu, Qianru Sun, Xun Yang, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Foundation models like CLIP allow zero-shot transfer on various tasks without additional training data. Yet, the zero-shot performance is less competitive than a fully supervised one. Thus, fine-tuning and ensembling are also commonly adopted to better fit the downstream tasks. However, we argue that such prior work has overlooked the inherent biases in foundation models. Due to the highly imbalanced Web-scale training set, foundation models are inevitably skewed toward frequent semantics, and thus the subsequent fine-tuning or ensembling is still biased. In this study, we systematically examine the biases in foundation models and demonstrate the efficacy of our proposed Generalized …

Restoring Linguistic Grounding In Vla Models Via Train-Free Attention Recalibration, Ninghao Zhang, Bin Zhu, Shijie Zhou, Jingjing Chen

Research Collection School Of Computing and Information Systems

Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasingly viewed as a foundation for generalist robotic policies. However, their reliability under Out-Of-Distribution (OOD) instructions remains underexplored. In this paper, we reveal a critical failure mode in which VLA policies continue executing visually plausible actions even when the language instruction contradicts the scene. We refer to this phenomenon as linguistic blindness, where VLA policies prioritize visual priors over instruction semantics during action generation. To systematically analyze this issue, we introduce ICBench, a diagnostic benchmark constructed from the LIBERO dataset that probes language–action coupling …

Facevalue: Exploring Real-Time Self-View Overlays To Prompt Meaning-Oriented Self-Awareness In Remote Meetings, Gun Woo (Warren) Park, Anthony Tang, Fanny Chevalier

Research Collection School Of Computing and Information Systems

In remote video meetings, visual non-verbal cues, such as facial expressions or head movements, are seen continuously but often only partially. This increases ambiguity compared to in-person settings and can cause misinterpretation or misalignment between intended and perceived meaning. Motivated by communication theories, we designed FaceValue, a technology probe that augments the self-view with private, real-time overlays. These overlays are subtle, suggestive prompts intended to help attendees reflect on how their cues might be interpreted by others. To invite personal interpretation, FaceValue avoids behavioral labeling and instead aims to support meaning-oriented self-awareness: recognizing when visible cues may unintentionally (mis)communicate intent. …

From Green Presence To Perceived Greenery: Everyday Mobility And Perceptual Availability In Singapore, Ziheng Zeng, Sonny Rosenthal, Orlando Woods

Research Collection College of Integrative Studies

Urban greenery may be abundant in transit-oriented cities, yet green presence does not necessarily become perceptually available to people moving through it. This paper distinguishes green supply, perceived greenery, and green experience, and examines the step at which greenery enters awareness during travel. The study combined 21 days of ecological momentary assessment from 68 participants in Singapore, yielding 6,794 in-trip moments, and 25 route-reconstruction interviews. A satellite normalized difference vegetation index (NDVI) provided a top-down baseline of green supply, and a street-level green view index (GVI) from Google Street View (GSV), matched to 5,824 moments, provided a co-located eye-level baseline. …

Towards More Inclusive Ai Systems In Cities, Siew Ying Shee, Orlando Woods

Research Collection School of Social Sciences

Artificial Intelligence (AI) is increasingly embedded in urban infrastructures and governance, shaping how people, spaces, and futures are classified, prioritised, and managed. Yet, most AI systems are developed within a narrow set of linguistic and geopolitical contexts and exported globally, embedding particular epistemic assumptions into diverse urban environments. Even where formal inclusion metrics are met, such asymmetries can render certain populations and realities less legible within algorithmic systems. Prevailing approaches in digital inclusion—centred on fairness metrics, representation, or access—presume technologies as politically inert and bounded. Yet, the adaptive and probabilistic behaviour of contemporary AI disrupts this premise, challenging the idea …

Generalizations Of The Dirichlet Problem For Bianalytic Functions, William L. Blair

Math Faculty Publications and Presentations

We prove the Dirichlet problem for second-order iterated Vekua equations, a natural generalization of the Bitsadze equation, is well-posed when the boundary condition is defined as a product of an exponential function and a polynomial on a non-degenerate conic that is not a circumference. Also, we extend this result, as well as other related results for the Dirichlet problem for polyanalytic and generalized analytic functions from the literature, to their analogues for bicomplex differential equations.

Investigating The Impact Of Outreach Programmes On Second Level Students In Formal And Informal Computer Science Education In Ireland, Karen Nolan

Doctoral

Computer Science (CS) education at second-level in Ireland has undergone significant development, including the introduction of the Leaving Certificate Computer Science (LCCS). However, the existing literature examined demonstrated that access to and participation in CS education is uneven, resulting in many students having limited exposure CS at second-level before making educational choices. At the same time, students who elect to study LCCS require appropriate support as they engage with programming and other aspects of a relatively new formal curriculum. This thesis investigates the function of school-based CS outreach in helping students at these various phases of their second-level CS education …

Learning 1-Bit Lidar-Based Localization With Auxiliary Objective, Kaijie Yin, Zhiyuan Zhang, Tian Gao, Wentao Zhu, Cheng-Zhong Xu, Hui Kong

Research Collection School Of Computing and Information Systems

6-DoF LiDAR-based localization is a fundamental capability for autonomous systems operating in large-scale outdoor environments. Many deep-learning-based localization methods have achieved promising performance so far. However, as one of the always-on modules competing for limited on-board computational resources, the localization module is expected to consume only a small portion of the overall compute budget. Most existing learning-based methods are still too heavy for this purpose. In contrast, binary neural networks (BNNs) offer an appealing solution, but the 1-bit compression causes severe information loss and performance drop. In this paper, we address this challenge by proposing Binarized LiDAR-based Localization (BiLoc), the …

Editorial For The Special Issue “Advances And Applications Of Polymer Gels For Subsurface Energy And Storage”, Baojun Bai, Jingyang Pu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer gels are essential functional materials for subsurface energy operations, playing a critical role in conformance control, fluid diversion, hydraulic fracturing, and leakage mitigation. As reservoirs become increasingly complex and the demand for sustainable energy grows, continued innovation in gel technologies is crucial. This editorial introduces a Special Issue titled "Advances and Applications of Polymer Gels for Subsurface Energy and Storage," which compiles seven original research articles exploring recent developments in gel synthesis, characterization, and applications. The featured studies highlight the versatility of polymer gels, including nanoparticle-reinforced composites, foam–gel hybrids, recrosslinkable preformed particle gels, and advanced fracturing fluids. The contributions …

Analysis Of The Throttle Settings Under Uncertain Information, Latafat Gardashova, Nihad Afandi

Chemical Technology, Control and Management

Although classical fuzzy logic controllers are capable of modelling non-linear control systems, they fail to consider the reliability of linguistic information, sensor measurements, and expert knowledge. In this paper, an intelligent controller based on the use of Z-numbers is developed for steam-turbine throttle control. Linguistic information and its confidence degree are considered simultaneously in such a controller. The temperature and pressure values are taken as input variables, while the throttle rotation is selected as the controller output variable. At first, the Z-number representation system is constructed to include the credibility of linguistic measurements and control rules. Then, a Mamdani Type-1 …

Guardians Of The Record (Cs2 Edition): Heaps, Queues, And A Scarce Oracle, Ilan Goodman

Generative AI Teaching Activities

Students defend Wikipedia from vandals with data structures instead of infrastructure: a sliding-window edit-velocity tracker (hash map of queues), a hand-built binary min-heap, and a budget-bounded top-K selection decide which few suspicious edits earn a question to an expensive, rate-limited Oracle — a stand-in for a real LLM.

Validation Of A Home-Based Tool For Preschool Children Fall Prevention: A Rasch Analysis, Devie Fitri Octaviani, Fatma Lestari, Indang Trihandini, Dadan Erwandi

Kesmas

Unintentional falls are a leading cause of injury among preschool children, primarily occurring in home environments, yet validated tools to assess household fall prevention capacity in low- and middle-income countries remain limited. This study aimed to develop and psychometrically validate the Home-Based Preschool Fall Prevention Instrument using the Rasch Measurement Model. A cross-sectional validation study was conducted in Depok City, Indonesia, involving 167 primary caregivers of preschool children enrolled in kindergartens selected through multistage cluster random sampling. The instrument was developed based on an etiological injury model, socio-ecological perspectives, and risk management principles, and comprised four main factors: child, home, …

Nonlinear System Identification Based On Fuzzy Radial Basis Neural Network With Multi-Connected Weight Connections, Kabul Khudaybergenov

Chemical Technology, Control and Management

This paper builds on our earlier radial basis function network with multiple connections (RBFMC) by placing it within a fuzzy inference framework for nonlinear system identification. The idea is inspired by the diversity of neurotransmitters found in biological neurons: instead of a single hidden-to-output weight, RBFMC gives each hidden unit a multi-dimensional connection whose components act as independent filters. Once fuzzy logic is added, each hidden neuron becomes a fuzzy rule, and its antecedent is built from several Gaussian membership functions, one per connection. The resulting Fuzzy RBFMC produces an interpretable, multi-filter description of local regions of the input space …

Guardians Of The Record: A Two-Tiered Streaming Cascade With Kafka, Flink, And A Real Llm, Ilan Goodman

Generative AI Teaching Activities

Students build a streaming vandalism detector for live Wikipedia edits in which a fast rule-based tier decides which few of ~1,500 edits per minute are worth escalating to a slow, rate-limited real LLM (Gemini) — confronting the cost, latency, and failure modes of putting AI inside a production data pipeline.

Motor Imagery Eeg Decoding For Brain-Computer Interfaces: Structured Representation, Transfer, And Drift, Yiming Shen

Graduate Doctoral Dissertations

Motor imagery EEG decoding is often summarized by the accuracy of a final classifier, but the classifier is only the last stage of the pipeline. Before classification, the signal has already been shaped by preprocessing, feature extraction, source-session organization, and adaptation. This dissertation studies how feature representation, source-session transfer, and drift shape reliable MI-EEG decoding for brain-computer interfaces.

It first studies within-session decoding on public MI-EEG datasets using nested validation that keeps preprocessing, feature fitting, and model selection inside the training folds. This analysis separates gains from feature representation from gains due to nonlinear classification, and relates both comparisons to …

Artificial Intelligence And Social Equities: Navigating The Intersectionalities In A Digital Age (Editorial), Daisuke Akiba, Julie Albright

Publications and Research

This editorial article introduces and synthesizes the Special Issue, “Artificial intelligence and social equities: navigating the intersectionalities in a digital age,” which examines how AI systems intersect with race, ethnicity, and interconnected identity dimensions across global contexts. The eight contributions span healthcare, digital media, higher education, organizational communication, and speculative futures, addressing anti-racist psychiatric algorithms, AI-generated visual disinformation, epistemic injustice between the Global North and South, algorithmically mediated rural–urban divides, culturally untranslated technology transfer, accessibility auditing across the AI lifecycle, and the tension between mechanical objectivity and empathic understanding. Read together, they show that AI is neither inherently …

Modeling Of Supersonic Wave And Shock Propagation Using The Lattice Boltzmann Method, Timothy P. Schroeder

Beyond: Undergraduate Research Journal

The lattice Boltzmann method (LBM) has emerged as a mesoscopic alternative to traditional Navier-Stokes solvers for modeling fluid dynamics offering advantages in computational efficiency, parallelization, and handling of complex boundaries. Despite these strengths, accurately reproducing compressible, shock-driven phenomena remains challenging. This study investigates the performance of LBM in simulating the Sod shock tube problem, a classical benchmark for compressible flow-using both single and double distribution function formulations across one- and two-dimensional lattice stencils. A MATLAB-based solver was developed to model the flow under isothermal conditions and compared to the analytical solution using the L2 norm error. The one-dimensional models achieved …

3d Geological Modeling And Its Application For Steeply Dipping Coal Seams In The Miquan Area, Xinjiang, Wu Luofei, Li Yong, Zhang Weiqi, Han Yiyang, Zhang Jie, Cao Mingliang, Li Qiang

Coal Geology & Exploration

Background Influenced by multi-stage compression from the North Tianshan and Bogda mountains, the southern margin of the Junggar Basin in Xinjiang exhibits the widespread development of steeply dipping coal seams. The extreme stratigraphic occurrence, combined with complex structural superimposition styles, poses significant challenges to the fine-scale characterization of these coal seams. Correspondingly, the planar and regional distribution patterns of gas content in these coal seams remain poorly understood, rendering it difficult to effectively determine the sweet spots of coalbed methane (CBM). Methods Focusing on the Miquan area, Xinjiang, this study investigated the methodology for 3D geological modeling of representative steeply …

Machine Learning-Based Diagnosis Of Fracture-Induced Lost Circulation And Intelligent Selection Of Lost Circulation Control Fluids, Sun Huan, Zhu Mingming, Wang Jinshu, Yao Lu, Zhou Fangfang, Tan Xuebin, Sun Yan, Qu Yanping, Chen Ning

Coal Geology & Exploration

Objective and Method Drilling operations in the Changqing area face several challenges in lost circulation, including complex types, significantly different characteristics, and difficulty in designing plugging formulations. To address these issues, this study proposes a DSX-Hybrid coupled intelligent decision-making framework, which serves as an integrated scheme to identify lost circulation channels, perform intelligent selection of plugging formulations, and offer recommendations on construction process. In this framework, given the scarcity of labeled log data, the density-based spatial clustering of applications with noise (DBSCAN) is employed to mine latent geological characteristics of unlabeled data. Then, the self-attention convolutional neural network (SACNN) is …

An Analysis Of The Effects And Implementations Of The Early Literacy Grant In Arizona, Alicia Severiano Perez

Mathematics, Statistics, and Computer Science Honors Projects

Over the years, states have implemented Science of Reading (SoR) frameworks to address low literacy levels. The Early Literacy Grant (ELG) in Arizona funds and supports such frameworks for schools serving low-income students. This paper is the first to explore the grant through interrupted time series modeling to evaluate effectiveness and text analysis to understand its implementation. We do not find clear evidence of positive effects caused by the grant, other than some cases, such as Yuma County. Schools typically allocate funds toward salaries and hiring instructors. These findings raise questions about whether its allocations should be closely monitored.

Temperature Predictions With Zncuins/Zns Quantum Dots, Reu/Fri Program Physics And Astronomy, Amber Banks

Student Works

For hundreds of years, humans have built thermometers based on the principles of thermal expansion and contraction. In the modern world, there is a need to scale down our thermometers to monitor cellular reactions, both within the human body and within artificial organ chips. Lewis et al. (2020) introduces a nanoscale thermometer based on the thermal expansion of CdTe quantum dots. When ex panded, these dots exhibit systematic changes in photoluminescence (PL) which are recognized by a neural network as an increase in temperature. Our research builds upon the framework of Lewis et al. (2020), testing its feasibility with ZnCuInS/ZnS …

Machine Learning For Functional Outcome Prediction After Vestibular Schwannoma Surgery: A Systematic Review And Diagnostic Test Accuracy Meta-Analysis, Shiva Nischal, Shaan Patel, Musa China, Kush Kale, Yi Hein Chai, Santosh Guru, William Muirhead, Patrick Grover

Department of Neurosurgery Faculty Papers

PURPOSE: Machine learning (ML) models have been increasingly applied to predict postoperative facial nerve dysfunction and hearing preservation after vestibular schwannoma (VS) surgery. However, reported performance varies substantially, and the overall diagnostic accuracy and clinical reliability of these models remain uncertain. We conducted a systematic review and diagnostic test accuracy meta-analysis to characterise the current state and methodological readiness of ML-based prediction of these outcomes.

METHODS: PubMed, Embase, and CENTRAL were searched from inception to February 2026. Studies evaluating ML-based prediction of facial nerve function or hearing preservation following VS surgery were included. Diagnostic performance metrics were pooled using random-effects …

Synthesis, Thermal Stability, And Ionic Conductivity Of Phenyl-Extended Viologen Ditriflate Salts: Tailoring Properties Via Oxyethylene Chain Length, Seonghyeok L. Cox, Emily Moon, Si L. Chen, David King, Haesook Han, Pradip K. Bhowmik, Calvin Ng Yi Bin, Thamil Selvi Velayutham, Alfonso Martinez-Felipe

Chemistry and Biochemistry Faculty Research

Six new phenyl-extended viologen salts with oxyethylene groups paired with triflate anions (OTF) have been synthesized using anionic ring-opening and ring-closing reactions (ANRORC) and metathesis reactions with LiOTf salts. The salts, which contain terminal oxyethylene chains of varying lengths ((CH₂CH₂O)_n, n = 1, 2, 3, 4, 5, and 7), are named PEOn-OTF. These materials exhibit a fluorescence response and possess high thermal stability, with processing windows up to approximately 300 °C, as confirmed by thermogravimetric analysis. While samples with short chain lengths (n = 1, 2, and 3) undergo crystallization observed …

Molecular Interactions Of The Gas–Solid Interface: Svocs On Swelling Clays And San Joaquin Soil Surfaces, Liesl T. Jensen

Electronic Theses and Dissertations

Soil-derived mineral dust plays an important role in atmospheric chemistry by acting as a reactive interface for gas–particle interactions that influence the fate and transport of organic contaminants. Among soil components, clay minerals dominate surface reactivity due to their high surface area, structural complexity, and the presence of chemically active sites arising from cation exchange capacity and surface acidity. Environmental conditions, particularly relative humidity, further regulate these interactions by altering surface accessibility and competitive adsorption processes.

Despite the recognized importance of mineral dust, gas-phase interactions between organic compounds and clay minerals remain insufficiently understood, particularly under atmospherically relevant conditions. This …

Compact 1 Ghz Electron Paramagnetic Resonance Spectrometers For Preclinical Imaging Studies, Tanden A. Hovey

Electronic Theses and Dissertations

Magnetic resonance is one of the most generally useful scientific techniques. New horizons of understanding are revealed as technological advances make possible explorations of nuclear spins and electron spins at higher and lower magnetic fields and electromagnetic frequencies. While the greatest current effort is on ever higher magnetic fields and microwave frequencies, both in nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR), the Eaton lab focusses on developing high signal-to-noise performance EPR at low microwave frequencies. EPR provides information about O2, pH, viscosity, glutathione concentrations, and reactive oxygen species in living organisms that MRI cannot. To yield clinically or …

Three-Dimensional Cell And Nuclear Geometries Inform Tissue Level Fluid Mechanics During Epithelial Remodeling, Liam Joseph Russell

Electronic Theses and Dissertations

During epithelial remodeling, mechanical and molecular programs must coordinate to drive the cell shape changes that enable new tissue topologies. Dynamic morphogenesis requires epithelia to preferentially exhibit solid- or fluidlike properties depending on developmental and biophysical constraints. Convergent extension in the Drosophila germband epithelium is one such remodeling event, during which the lateral ectoderm lengthens by two-fold along the primary body axis while concomitantly shortening orthogonally. This process is an incredibly dynamic and attractable system for studying tissue morphogenesis mechanics in vivo.

Germband extension is driven by oriented cell intercalation through T1 transitions, where cells directionally interdigitate with one another …

Ngram Data Social Media, William Zywiak

Data and Datasets

Data set for a NSF STEM grant.

Lag Correlation Variance, William Zywiak

Data and Datasets

Data set for a NSF STEM grant.