Digital Commons Network^™

The Study Of Hybrid Nanostructures For Optoelectronics, Alex Davis, Khaoula Dehhou

Publications and Research

Hybrid nanostructures that combine zero-dimensional (0D) quantum dots (QDs) with two-dimensional (2D) transition-metal dichalcogenides (TMDs) are promising building blocks for next-generation optoelectronic devices, such as highly sensitive photodetectors, light-emitting diodes, and tunable light sources. These hybrid systems take advantage of the strong, size-dependent emission of colloidal QDs and the high carrier mobility and tunable band structure of 2D materials. In this research, we investigate hybrid structures composed of colloidal CdSe/ZnS, CuInS/ZnS, and PbS QDs integrated with indium selenide (InSe), a TMD known for its exceptional electron mobility and robust photoluminescence in few-layer form. The goal is to understand how interfacial …

Facility Usage On The International Space Station, Justin St. P. Walsh, Rao Hamza Ali, Ryan Shihabi, Erik Linstead

Art Faculty Articles and Research

Science experiments on the International Space Station (ISS) and in future space habitats require “facilities,” as they are known to space agencies, as the core building blocks of the research capabilities they provide. Facilities are experimental apparatus that enable research, often (but not always) used for more than one experiment, such as centrifuges, furnaces, gloveboxes, freezers, and more. The US Orbital Segment of the ISS has been home to 191 such facilities, belonging to four of the five ISS international partner agencies as well as private companies, in its 25 years of continuous operation. Until now, there has been no …

Gets: Greenhouse Environment Time Series, Scott Grimshaw, Natalie J. Blades, Grant R. Mcqueen

ScholarsArchive Data

This dataset contains high-frequency environmental measurements from a single greenhouse used to study multivariate statistical process control under strong autocorrelation. The data consist of a continuous Phase 1 monitoring period of approximately four weeks, during which environmental sensors recorded conditions inside the greenhouse once per minute.

The primary variables included in the archived dataset are:

• date – Date-time stamp at one-minute resolution (local greenhouse time).

• co2_ppm – Carbon dioxide concentration in parts per million (ppm).

• humidity_pct – Relative humidity (%).

• soil_temp_F – Soil temperature in degrees Fahrenheit.

Experience From A Distance: Improving Transparency For The Multnomah Athletic Club, Matthew Penner

University Honors Theses

Portland is home to the largest and one of the most prestigious athletic clubs in the world: Multnomah Athletic Club. In many ways, it is the pinnacle of luxury and innovation, and over time, it finds any way to entice prospective members to pay the expensive upfront fee of $6000 and monthly membership fees exceeding $300. Due to the previous technological barrier, which was not being able to see the full extent of what amenities the club had to offer, the club faced major challenges in recruitment and marketing. Over two academic terms, a team of six computer science capstone …

Understanding Medical Information And Emotional Support Needs In Mental Health Questions With Large Language Models, Chen Liu, William Yu Chung Wang, Gohar Khan

All Works

Purpose – This study seeks to bridge the gap between users’ multidimensional needs and the single-task capabilities of existing Mental Health Question Answering (MHQA) systems by tackling the underexplored challenge of jointly understanding medical informational needs and emotional support needs within complex consumer mental health inquiries. Design/methodology/approach – Grounded in Rhetorical Structure Theory (RST), the proposed Multi-Needs and Context Recognition (MNCR) framework decomposes mental health question understanding task into four interrelated subtasks: Medical Needs Recognition (MNR), Medical Needs-related Context Extraction (MNCE), Emotional Needs Recognition (ENR) and Emotional Needs-related Context Extraction (ENCE). A new benchmark dataset, MHQ-MedEmo, was constructed through multi-layered …

The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Dre Boyd-Weatherly, Sean Curry, Krish Sharma, Kristian Thymianos, William E. Brown Jr.

Economic Development & Workforce

This fact sheet reports on the artificial intelligence (AI) readiness of five Mountain West metropolitan statistical areas (MSAs): Phoenix-Mesa-Chandler, AZ; Salt Lake City-Murray, UT; Denver-Aurora-Centennial, CO; Las Vegas-Henderson-North Las Vegas, NV; and Albuquerque, NM. Using data from the Brookings Institution's “Mapping the AI Economy” report, the MSAs are benchmarked based on their overall population, employment, talent, adoption, and innovation.

Unsaturated Fatty Acid Oil-Based Microdroplets: A Promising Novel Class Of Microdroplets, Ramiz S. Alejilat

Seton Hall University Dissertations and Theses (ETDs)

Droplet-based microfluidics has rapidly advanced numerous fields, including chemistry, biology, materials science, medicine, food science, and cosmetics. In these systems, fluorocarbon oil combined with fluorinated surfactants is the preferred medium for fluid encapsulation, offering exceptional stability and biocompatibility essential for sensitive biological and chemical processes. However, growing concerns about the environmental and biological risks associated with fluorinated chemicals have prompted a search for alternatives.

This study is the first to explore the use of unsaturated fatty acids derived from emu oil for microdroplet formation. We characterized droplet formation based on flow rates and the presence non-fluorinated surfactant at a certain …

Bridging Machine Learning And Islamic Scholarship: A Study In Hadith Translation And Similarity Analysis, Asiyah R. Speight

Student Scholar Symposium Abstracts and Posters

Translation of Islamic religious texts poses unique challenges requiring both linguistic and theological expertise. This study explores the application of neural machine translation (NMT) models to Arabic-English hadith translation while analyzing semantic similarity patterns across different human translations. Using the complete Sahih Bukhari corpus (7,550 hadiths) as the primary dataset, we adopt a dual approach combining transfer learning and comprehensive neural network analysis to demonstrate the critical impact of corpus size on model performance.

First, we fine-tune a pre-trained MarianMT Arabic-English translation model on the full Sahih Bukhari corpus, comparing models trained on 40 hadiths versus 7,550 hadiths. Performance is …

Lead Sources Detected In Manila's Air After The Phase-Out Of Leaded Gasoline, Grace Betito, Paola Angela Bañaga, Maria Obiminda L. Cambaliza, Melliza Templonuevo Cruz, James Bernard Simpas, Mengli Chen, Jariya Kayee, Armin Sorooshian, Rachel A. Braun, Alexander B. Macdonald

Ateneo Atmospheric Physics Laboratory

Abstract

The global phase-out of leaded gasoline marked a major milestone in pollution control, yet modern uses of lead (Pb) continue to pose significant health risks, especially in low- and middle-income countries. In the Philippines, significant data gaps still exist despite increasing exposure. This study presents to the best of our knowledge, the first Pb isotopic fingerprinting of atmospheric aerosols in Metro Manila, Philippines, covering fine (0.56–1 μm) and coarse (5.6–10 μm) fractions, collected in 2018–2019. Results show that local sources, mainly industrial activities (45–62 %) and fossil fuel combustion (30–45 %), are now the dominant contributors to airborne Pb, …

Extensions Of Weighted Integral Inequalities For Ga-Convex Functions In Connection With Fejér’S Result, Muhammad Amer Latif

Publications and Research

No abstract provided.

Evaluating Defi Vulnerabilities: The Role Of Bug Bounty Programs On Defi Software Supply Chain, Ping Fan Ke, Yi Meng Lau, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Decentralized finance (DeFi), powered by blockchain technology, enables peer-to-peer financial transactions without intermediaries. Despite rapid adoption, DeFi attracts malicious actors exploiting vulnerabilities. To mitigate risks, we propose a framework assessing entry points in the DeFi software supply chain: smart contracts, oracles/third-party feeds, user interfaces, off-chain storage, and crypto wallets. Applying this framework, we evaluate whether industry solutions—particularly bug bounty programs—adequately address these gaps. Our preliminary analysis indicates that most programs cover smart contract vulnerabilities (85.7%), followed by user interface issues (21.3%) and crypto wallet loopholes (11.9%). However, third-party risks, such as oracle feeds, are frequently deemed out of scope. This …

A Socio-Technical Analysis Of Market Reactions On Meme Coins: Trump’S Presidential Effect, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Meme coins are a unique type of cryptocurrency whose value is shaped by internet culture and viral trends. This study introduces a socio-technical research model to examine key factors influencing meme coin dynamics and applies it to analyze market reactions to Donald Trump’s 2024 U.S. presidential election victory and inauguration, focusing on the $TRUMP meme coin and other politics-related meme coins, known as PolitiFi. Using a mixed-methods approach, we analyze publicly available news, social media activity, and marketplace data to investigate the interaction between social engagement and technical infrastructure. Econometric analysis shows that Trump-related events triggered short-term price surges, increased …

Registration Is A Powerful Rotation-Invariance Learner For 3d Anomaly Detection, Yuyang Yu, Zhengwei Chen, Xuemiao Xu, Lei Zhang, Haoxin Yang, Yongwei Nie, Shengfeng He

Research Collection School Of Computing and Information Systems

3D anomaly detection in point-cloud data is critical for industrial quality control, aiming to identify structural defects with high reliability. However, current memory bank-based methods often suffer from inconsistent feature transformations and limited discriminative capacity, particularly in capturing local geometric details and achieving rotation invariance. These limitations become more pronounced when registration fails, leading to unreliable detection results. We argue that point-cloud registration plays an essential role not only in aligning geometric structures but also in guiding feature extraction toward rotation-invariant and locally discriminative representations. To this end, we propose a registration-induced, rotation-invariant feature extraction framework that integrates the objectives …

Safe-Sora: Safe Text-To-Video Generation Via Graphical Watermarking, Zihan Su, Xuerui Qiu, Hongbin Xu, Tangyu Jiang, Jun-Hao Zhuang, Chun Yuan, Ming Li, Shengfeng He, Fei Yu

Research Collection School Of Computing and Information Systems

The explosive growth of generative video models has amplified the demand for reliable copyright preservation of AI-generated content. Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further …

Jury-And-Judge Chain-Of-Thought For Uncovering Toxic Data In 3d Visual Grounding, Kaixiang Huang, Qifeng Zhang, Jin Wang, Jingru Yang, Yang Zhou, Huan Yu, Guodong Lu, Shengfeng He

Research Collection School Of Computing and Information Systems

3D Visual Grounding (3DVG) faces persistent challenges due to coarse scene-level observations and logically inconsistent annotations, which introduce ambiguities that compromise data quality and hinder effective model supervision. To address these challenges, we introduce Refer-Judge, a novel framework that harnesses the reasoning capabilities of Multimodal Large Language Models (MLLMs) to identify and mitigate toxic data. At the core of Refer-Judge is a Jury-and-Judge Chain-of-Thought paradigm, inspired by the deliberative process of the judicial system. This framework targets the root causes of annotation noise: jurors collaboratively assess 3DVG samples from diverse perspectives, providing structured, multi-faceted evaluations. Judges then consolidate these insights …

Misodice: Multi-Agent Imitation From Mixed-Quality Demonstrations, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

We study offline imitation learning (IL) in cooperative multi-agent settings, where demonstrations have unlabeled mixed quality - containing both expert and suboptimal trajectories. Our proposed solution is structured in two stages: trajectory labeling and multi-agent imitation learning, designed jointly to enable effective learning from heterogeneous, unlabeled data. In the first stage, we combine advances in large language models and preference-based reinforcement learning to construct a progressive labeling pipeline that distinguishes expert-quality trajectories. In the second stage, we introduce MisoDICE, a novel multi-agent IL algorithm that leverages these labels to learn robust policies while addressing the computational complexity of large joint …

Cssa-Fusion: Channel Selective And Spatial Alignment Infrared-Visible Image Fusion, Zhen Li, Zhi Zeng, Zhongrui Xiao, Ming Wen, Zhiyuan Zhang, Yibin Tian

Research Collection School Of Computing and Information Systems

Infrared-visible image fusion aims to integrate complementary information from two modalities to generate images with enriched semantic content. However, existing methods often neglect two critical aspects: the design of a local–global feature enhancement architecture and spatial alignment. To address these challenges, we propose Channel Selective and Spatial Alignment Fusion (CSSA-Fusion), a novel framework composed of two synergistic modules. The first is a selective channel and redundancy suppression module, which introduces a dual-branch selective channel attention mechanism to jointly capture local saliency and global channel importance for enhanced feature representation, and an informativeness–redundancy separation strategy to suppress redundant information while preserving …

The Rise Of Parameter Specialization For Knowledge Storage In Large Language Models, Yihuai Hong, Yiran Zhao, Wei Tang, Yang Deng, Yu Rong, Wenxuan Zhang

Research Collection School Of Computing and Information Systems

Over time, a growing wave of large language models from various series has been introduced to the community. Researchers are striving to maximize the performance of language models with constrained parameter sizes. However, from a microscopic perspective, there has been limited research on how to better store knowledge in model parameters, particularly within MLPs, to enable more effective utilization of this knowledge by the model. In this work, we analyze twenty publicly available open-source large language models to investigate the relationship between their strong performance and the way knowledge is stored in their corresponding MLP parameters. Our findings reveal that …

A Partition Cover Approach To Tokenization, Jia Peng Lim, Shawn Tan, Davin Choo, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Tokenization is the process of encoding strings into tokens of a fixed vocabulary size, and is widely utilized in Natural Language Processing applications. The leading tokenization algorithm today is Byte Pair Encoding (BPE), which formulates the tokenization problem as a compression problem and tackles it by performing sequences of merges. In this work, we formulate tokenization as an optimization objective, show that it is NP-hard via a simple reduction from vertex cover, and propose a polynomial-time greedy algorithm GreedTok. Our formulation naturally relaxes to the well-studied weighted maximum coverage problem which has a simple -approximation algorithm GreedWMC. Through empirical evaluations …

Sheetpedia: A 300k-Spreadsheet Corpus For Spreadsheet Intelligence And Llm Fine-Tuning, Zailong Tian, Zhuoheng Han, Houfeng Wang, Lizi Liao

Research Collection School Of Computing and Information Systems

Spreadsheets are widely used for data analysis and reporting, yet their complex structure and formula logic pose significant challenges for AI systems. We introduce Sheetpedia, a large-scale corpus of over 290,000 diverse spreadsheets (from 324,000+ workbooks) compiled from enterprise email archives and online forums. We detail a rigorous collection and preprocessing pipeline (integrating the Enron email spreadsheet archive and the Fuse web corpus, plus a new crawl of Excel forums) to standardize formats, filter languages, and remove duplicates. Sheetpedia provides extensive coverage of real formulas and annotations – addressing a gap left by prior table datasets (e.g. web tables used …

Cropcapsnet: Enhanced Capsule Network For Crop Disease Classification, Juan Qin, Linfan Deng, Cong Li, Junjie He, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

The prevention and treatment of crop diseases are crucial for the development of smart agriculture. The classification of crop diseases based on deep learning for early disease monitoring and control has become the mainstream direction of research. This paper proposes a novel deep learning model called ”CropCapsNet”, which combines Squeeze-and-Excitation Inception (SE-Inception) module and has improved capsule structure for crop disease classification. The network first extracts shallow features of input samples through double-layer convolution, then uses SE-Inception to achieve deep multi-scale feature acquisition, and finally outputs classification results through an improved capsule structure. SE-Inception adds Squeeze-and-Excitation(SE) attention after each multi-scale …

El Poder Del Bilingüismo Y La Ciencia, Isabella Winslow

World Languages and Cultures

This project is an explanation of the importance of bilingualism, science, and our responsibility as humans within this environment. As living beings on this planet, we have a responsibility to respect and protect it. Over the course of the last several hundred years, we humans have made countless advancements. We have created unimaginable technology and discovered incredible resources produced by the land. However, in the process of doing so, we have damaged and continue to damage our environment. Reefs in the ocean have been bleached by increases in acidity, thousand year old glaciers have melted, forests have been destroyed by …

Wacsaw: An Adaptive, Statistical Method To Classify Movement Into Sleep And Wakefulness States, Austin Vandegriffe, V. A. Samaranayake, Matthew S. Thimgan

Mathematics and Statistics Faculty Research & Creative Works

Wearable actimeters can improve our understanding of sleep in the natural environments. Current algorithms may produce inaccuracies in specific individuals and circumstances, such as quiet wakefulness. New hardware allows data collection at higher frequencies enabling sophisticated analytical methods. We have developed a novel statistical algorithm, the Wasserstein Algorithm for Classifying Sleep and Wakefulness (WACSAW), to identify behavioral states from recordings of everyday movement. WACSAW employs optimal transport techniques to identify segments with differing activity variability. Functions characterizing the segments' movement distributions were clustered into two groups using a k-nearest neighbors and labeled as sleep or wake based on their proximity …

(R2125) Impact Of Convective Condition And Inclined Magnetic Field On Casson Nanofluid With Bioconvection In Porous Medium, Touseef Fayaz, O. Otegbeye, Md. Sharifuddin Ansari

Applications and Applied Mathematics: An International Journal (AAM)

This paper presents an analysis on steady magnetohydrodynamic boundary layer flow of Casson nanofluid with microorganisms near an expandable boundary in a porous medium. The flow behaviour is analysed by incorporating impacts of magnetic field applied in a direction which makes an angle α∗ with the boundary and convective conditions in temperature, nanoparticle concentration and microorganism density at boundary. Non-dimensionalised nonlinear and coupled system of ordinary differential equations are solved by exercising a numerical algorithm termed as spectral local-linearization method. The considered numerical algorithm is found to be convergent and capable of yielding accurate results. Graphical sketches of solutions obtained …

Flood Resilience Through Working-Land Conservation: Assessment Of Wetland Inundation Dynamics Across Wrp, Wma, Wpa, Padus And Crp Lands In Nebraska (2018–2024), Pranjay Joshi

Community and Regional Planning Program: Theses

This study first confirms whether Nebraska’s wetlands are still functioning hydrologically in ways that reduce flood impacts. Wetlands are known to lessen flood damage by storing water, slowing runoff, and moderating peak flows, but these benefits depend on the wetlands’ ability to maintain inundation and saturation through time. Many wetlands across the state have undergone drainage, hydrologic alteration, or isolation from surrounding watersheds, raising uncertainty about their present-day functioning. Using seven years of Sentinel-2 imagery processed in Google Earth Engine, this research establishes a clear, long-term record of inundation patterns across thousands of wetland parcels. This analysis verifies which wetlands …

Detection Of Phase-Binning And Interpolation Artifacts In 4-Dimensional Computed Tomography Imaging Using Deep Learning And Rule-Based Approaches, Jorge Cisneros, Nathan H. Feldt, Yevgeniy Vinogradskiy, Richard Castillo, Edward Castillo

Department of Radiation Oncology Faculty Papers

BACKGROUND: Four-dimensional computed tomography (4DCT) imaging is a crucial component to lung cancer radiotherapy planning and enables CT-ventilation-based functional avoidance planning to mitigate radiation toxicity. However, 4DCT scans are frequently impaired by acquisition artifacts that corrupt downstream analyses that depend on lung segmentation and deformable image registration, such as CT-ventilation and dose accumulation.

PURPOSE: This study develops 3D deep learning models to identify phase-binning artifacts at the voxel level and a heuristic, rule-based method to identify interpolation slices within 4DCT images.

METHODS: We introduce a generator that systematically inserts synthetic phase-binning and interpolation artifacts into any artifact-free breathing phase obtained …

Tuning A Magnetic Energy Scale With Pressure And Field In Ute2, Hyunsoo Kim, I. Lin Liu, Wen Chen Lin, Yun Suk Eo, Sheng Ran, Nicholas P. Butch, Johnpierre Paglione

Physics Faculty Research & Creative Works

When a fragile ordered state is suppressed to zero temperature, a quantum phase transition occurs, which is often marked by the appearance of unconventional superconductivity. While the quantum critical point can be hidden, the influence of the quantum criticality extends to fairly high temperatures, manifesting non-Fermi liquid behavior in a wide range of the field-temperature-pressure phase space. Here, we report the tuning of a magnetic energy scale in the heavy-fermion superconductor UTe₂, previously identified with a peak in the c-axis electrical transport temperature dependence, using applied hydrostatic pressures and a-axis-oriented magnetic fields as complementary (and opposing) tuning parameters: …

Investigating The Efficiency Of Ingan P-N-P-N Homojunction Solar Cells, Moath Alhejji, Mohammad Alavijeh, Jacob Kupernik, Mirsaeid Sarollahi, Abbas Jammali, Seyed Taghavi, Reem Alhelais, Md Hel Uddin Maruf, Morgan Ware

Electrical Engineering and Computer Science Faculty Publications and Presentations

This research investigates the development of a novel p-n-p-n homostructure solar cell, through semiconductor simulations using the Nextnano software. InGaN was used as a model system in order to achieve a bandgap with optimized efficiency for a p-n homojunction solar cell. By increasing the uniform doping concentration from 1.5*10(16) cm(-3) to 1.5*10(17) cm(-3), the open circuit voltage (V-oc) increased while the short-circuit current density (J(sc)) decreased, as expected in simple p-n junctions. The p-n-p-n structure achieved a peak efficiency of 32.91% at a doping level of 6.5*10(16) cm(-3), a similar to 7% improvement over a conventional p-n junction's 25.31% efficiency …

Flux Crystal Growth Of A Series Of Calcium Rare Earth Silicate Chlorides Calnsio4Cl (Ln = Pr, Nd, Sm, Eu, Gd, And Tb): Mixed Anion Materials With A Spodiosite-Type Structure, Maria Goncalves, Mark D. Smith, Hans Conrad Zur Loye

Faculty Publications

A series of calcium rare earth silicate chlorides, CaLnSiO4Cl (Ln = Pr, Nd, Sm, Eu, Gd, and Tb), was obtained as single crystals from flux crystal growth. The structures were determined by single crystal X-ray diffraction and were found to be related to the spodiosite/Wagnerite mineral structure, Ca2PO4F. The obtained compositions are variations of the spodiosite structure that result from two simultaneous elemental substitutions. Replacing one calcium for one rare earth element and the simultaneous replacement of one VO4³⁻ or PO4³⁻ with one SiO4⁴⁻. CaEuSiO4Cl was found to luminesce, and its photoluminescence spectrum is reported.

Water Circulation Beneath A Hovering Suas For Water Quality Monitoring Applications, Erin E. Hackett, Boone Fleenor, Jensine C. Coggin, Duvall Dickerson-Evans, Nikolaos Vitzilaios, Whitney E. Schuler, Paige K. Williams, Michael L. Myrick

Faculty Publications

Water quality has traditionally been measured via in situ sensors and satellites. The latter has limited applicability for smaller inland water bodies, while the former requires significant logistics, labor, and expense for routine sampling, and reactive/spurious sampling is often not feasible as a result (e.g., sampling pre-/post-storm). Consequently, small uncrewed aircraft system-based (sUAS-based) sampling has emerged as a potential solution to bridge these sampling gaps and challenges. But sampling from an sUAS is complicated by the need to pump water from depth, rather than suspending a sensor from the sUAS, due to concern over sampling sUAS-impacted waters. Here, we measure …