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Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee Aug 2026

Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee

Computer Science Faculty Research & Creative Works

It is well-known that classical random walks on regular graphs converge to the uniform distribution. Quantum walks, in their various forms, are quantization's of their corresponding classical random walk processes. Gerhardt and Watrous (2003) demonstrated that continuous-time quantum walks do not converge to the uniform distribution on certain Cayley graphs of the Symmetric group, which by definition are all regular. In this paper, we demonstrate that discrete-time quantum walks, in the sense of quantized Markov chains as introduced by Szegedy (2004), also do not converge to the uniform distribution. We analyze the spectra of the Szegedy walk operators using the …

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Underground Mine Tunnel Fire Dynamics: Experimental Investigation And Ai-Driven Characterization Of Flame Behavior, Jingmin Xu, Rui Tian, Ashish Kakoria, Aamir Iqbal, Tao Yang, Lina Zheng, Guang Xu Aug 2026

Underground Mine Tunnel Fire Dynamics: Experimental Investigation And Ai-Driven Characterization Of Flame Behavior, Jingmin Xu, Rui Tian, Ashish Kakoria, Aamir Iqbal, Tao Yang, Lina Zheng, Guang Xu

Mining Engineering Faculty Research & Creative Works

Underground mine tunnel fires pose serious threats to personnel safety and infrastructure integrity, yet their detection and characterization remain challenging due to complex ventilation environments and limited visibility. This study combines full-scale fire experiments with advanced computer vision analysis to investigate the influence of fire size and ventilation on thermal, chemical, and visual signatures of mine fires. Six full-scall controlled experiments were conducted using two fire pan sizes under three ventilation conditions. Fuel mass loss, temperature distribution, and gas concentrations were systematically recorded using thermocouples, gas sensors, and visual/thermal imaging. Results show that mass loss rate is primarily governed by …

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Synthesis Of Bea Zeolite From Coal Fly Ash Nano-Silica Extract: Application In Co2 Adsorption, Alechine E. Ameh, Shabnam Feyziyeva, Jean Luc Mukaba, Keagan Pokpas, Baylar Zarbaliyev, Ojo O. Fatoba, Benoit Louis, Leslie F. Petrik, Oluwaseun O. Oyekola Aug 2026

Synthesis Of Bea Zeolite From Coal Fly Ash Nano-Silica Extract: Application In Co2 Adsorption, Alechine E. Ameh, Shabnam Feyziyeva, Jean Luc Mukaba, Keagan Pokpas, Baylar Zarbaliyev, Ojo O. Fatoba, Benoit Louis, Leslie F. Petrik, Oluwaseun O. Oyekola

Mining Engineering Faculty Research & Creative Works

This study demonstrates a circular economy approach to carbon dioxide sorption by re-purposing coal fly ash (CFA) into BEA zeolite using CFA-derived nano-silica and aluminum precursors via hydrothermal synthesis. The XRD patterns, with characteristic peaks at 15° and 37° 2θ, and SEM images both confirmed the complete transformation of the spherical-shaped CFA particles into amorphous nano-silica materials with particle sizes less than 100 nm. The absence of amorphous phases and the formation of high-intensity peaks at 7.8° and 22.8° 2θ further indicated the production of a highly crystalline BEA zeolite, obtained after hydrothermal synthesis durations between 10 and 72 h. …

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Five-State Seismic Damage Classification Of Steel-Girder Bridges On Soft Soil Using Directional Intensity Measures And Multi-Parameter Damage Indices, Ibrahim Alomari, Woubishet Zewdu Taffese, Mohammad Hossein Afsharmovahed, Genda Chen Aug 2026

Five-State Seismic Damage Classification Of Steel-Girder Bridges On Soft Soil Using Directional Intensity Measures And Multi-Parameter Damage Indices, Ibrahim Alomari, Woubishet Zewdu Taffese, Mohammad Hossein Afsharmovahed, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Rapid yet accurate post-earthquake damage assessment of highway bridges is essential to ensure transportation network resilience. Traditional inspection, fragility analysis, and finite element modeling are time-consuming or inaccurate for real-time decision-making. This study compares ten machine-learning classifiers for the seismic damage states of highway steel-girder bridges that incorporate directional intensity measures to represent the variance of ground motions. Based on the nonlinear time-history analyses of two Missouri bridges, one Michigan bridge, and one Wisconsin bridge, multi-parameter structural damage indices were proposed and mapped to five damage states from none to collapse. Among ten supervised algorithms studied, the artificial neural network …

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Field Calibration Of Flow Over Tilting Weirs In Canals, Joseph E. Pugh, Timothy K. Gates, S. Karan Venayagamoorthy, Caner Kutlu Aug 2026

Field Calibration Of Flow Over Tilting Weirs In Canals, Joseph E. Pugh, Timothy K. Gates, S. Karan Venayagamoorthy, Caner Kutlu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Tilting weirs are widely used to regulate water levels in open channel irrigation systems and can also provide flow measurement capability that helps optimize irrigation efficiency and ensure equitable water distribution. This case study demonstrates adaptation of lab-based tilting weir ratings to field settings, where flow behavior is more complex. We compile and analyze an extensive data set derived from independent studies of five structures within three canal systems, featuring both lined and unlined channels with discharge ranging from 0.35 to 15 m3/s (12 to 530 ft3/s). Results indicate that lab-based rating equations can be calibrated to account for site-specific …

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Barrier-Drainage Performance Of A Wicking Geotextile In Controlling Capillary Rise In Silt: Experimental Evaluation, Dahao Zou, Yipeng Guo, Jiejin Chen, Yafeng Li, Xiong Zhang, Yongjie Zhang, Luqiang Ding Aug 2026

Barrier-Drainage Performance Of A Wicking Geotextile In Controlling Capillary Rise In Silt: Experimental Evaluation, Dahao Zou, Yipeng Guo, Jiejin Chen, Yafeng Li, Xiong Zhang, Yongjie Zhang, Luqiang Ding

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Capillary rise in silt significantly degrades its strength and durability, yet the hydraulic mechanisms governing moisture control using wicking geotextile in silt remain insufficiently understood. This study investigates the barrier-drainage performance of a wicking geotextile in silt through one-dimensional column experiments, supported by preliminary trials. Three configurations were examined: a control specimen without geotextile (CS), an embedded configuration (ES), and a surface-exposed configuration (SES). Volumetric moisture content and matric suction were monitored, capillary responses at the soil-geotextile interface and water storage behavior were evaluated. The results show that the wicking geotextile initially acts as a temporary capillary barrier due to …

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Impact Of Climate Change On Extreme Windstorms And Implications For Structural Design In The United States, Teng Wu, Reda Snaiki, Frank Lombardo, Sihan Li, Michele Barbato, Guirong Yan, Robert J. Trapp Aug 2026

Impact Of Climate Change On Extreme Windstorms And Implications For Structural Design In The United States, Teng Wu, Reda Snaiki, Frank Lombardo, Sihan Li, Michele Barbato, Guirong Yan, Robert J. Trapp

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Climate change impacts various extreme windstorms associated with specific meteorological phenomena in different ways. Because various windstorms contribute to the design wind speeds, this study systematically reviewed the state-of-the-art understanding of climate change effects on wind events that collectively contribute to structural wind design in North America, particularly the US, including extratropical cyclones (as well as nor'easters), tropical cyclones, thunderstorms, and tornadoes. For each windstorm type, the general evidence of climate change impacts on storm activities (e.g., occurrence frequency and intensity) are summarized, followed by the introduction of existing simulation frameworks for yearly (or subyearly) maximum storm winds under changing …

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A Transfer-Learning And Continuous Optimization-Based Framework For Predicting Heat Treatment-Dependent Mechanical Properties Of Ded-Processed Low-Alloy Steels, Atiqur Rahman, Sung Heng Wu, Ranjit Joy, Frank Liou Aug 2026

A Transfer-Learning And Continuous Optimization-Based Framework For Predicting Heat Treatment-Dependent Mechanical Properties Of Ded-Processed Low-Alloy Steels, Atiqur Rahman, Sung Heng Wu, Ranjit Joy, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Directed energy deposition (DED) of low-alloy steels involves strongly coupled effects among alloy composition, solidification behavior, and post-deposition heat treatment, making mechanical property prediction difficult when target-domain data are limited. This study develops a transfer-learning and continuous optimization framework for predicting heat treatment-dependent yield strength (YS), ultimate tensile strength (UTS), hardness (HV), and as-solidified phase fractions of martensite, ferrite, and austenite in DED-processed low-alloy steels. A CALPHAD-based dataset was generated for 125 low-alloy steel compositions. A multilayer perceptron (MLP) surrogate was first trained as a baseline model, then fine-tuned through transfer learning and progressively updated as staged continuous optimization; the …

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Where Do Ai Coding Agents Fail? An Empirical Study Of Failed Agentic Pull Requests In Github, Ramtin Ehsani, Sakshi Pathak, Shriya Rawal, Abdullah Al Mujahid, Mia Mohammad Imran, Preetha Chatterjee Jul 2026

Where Do Ai Coding Agents Fail? An Empirical Study Of Failed Agentic Pull Requests In Github, Ramtin Ehsani, Sakshi Pathak, Shriya Rawal, Abdullah Al Mujahid, Mia Mohammad Imran, Preetha Chatterjee

Computer Science Faculty Research & Creative Works

AI coding agents are now submitting pull requests (PRs) to software projects, acting not just as assistants but as autonomous contributors. As these agentic contributions are rapidly increasing across real repositories, little is known about how they behave in practice and why many of them fail to be merged. In this paper, we conduct a large-scale study of 33k agent-authored PRs made by five coding agents across GitHub. (RQ1) We first quantitatively characterize merged and not-merged PRs along four broad dimensions: 1) merge outcomes across task types, 2) code changes, 3) CI build results, and 4) review dynamics. We observe …

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Hybrid Microbial-Enzymatic Electrosynthesis For De Novo Decanoic Acid Production From Co2, Yongze Wang, Wenjin Dong, Meijing Wei, Su Song, Zhiqing Huang, Yaojie Liu, Shelley D. Minteer, Hui Chen Jul 2026

Hybrid Microbial-Enzymatic Electrosynthesis For De Novo Decanoic Acid Production From Co2, Yongze Wang, Wenjin Dong, Meijing Wei, Su Song, Zhiqing Huang, Yaojie Liu, Shelley D. Minteer, Hui Chen

Chemistry Faculty Research & Creative Works

The steady increase in atmospheric CO2 levels is a key driver of anthropogenic climate change, prompting widespread global concern. In this context, the sustainable conversion of CO2 into value-added chemicals represents an attractive route toward carbon-neutral manufacturing and green chemistry. Here, we developed a proof-of-concept hybrid microbial-enzymatic electrosynthesis system that combines microbial electrosynthesis (MES) and enzymatic electrosynthesis (EES) to convert CO2 into decanoic acid under ambient conditions, using electrical energy. In the MES module, CO2 was converted to acetate via the Wood–Ljungdahl pathway of Clostridium ljungdahlii, using H2 produced by electrochemical water splitting as the electron …

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Entity Labels Are Not Entity Signals: A Framework For Observable Relevance In Document Re-Ranking, Utshab Kumar Ghosh, Shubham Chatterjee Jul 2026

Entity Labels Are Not Entity Signals: A Framework For Observable Relevance In Document Re-Ranking, Utshab Kumar Ghosh, Shubham Chatterjee

Computer Science Faculty Research & Creative Works

Entity-aware document retrieval uses query-associated entities as ranking signals, assuming that semantically relevant entities are also useful retrieval signals. We show this assumption is insufficient - and explain why. Unlike terms, which are ground-truth observations, entity links are hypotheses produced by an imperfect linker: an entity can be topically central yet provide no discriminative signal if the linker fires indiscriminately across relevant and non-relevant documents. We formalize this as a distinction between Conceptual Entity Relevance (CER) - whether an entity is topically related to a query - and Observable Entity Relevance (OER) - whether its observed presence in a collection …

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Reproduction Beyond Benchmarks: Constbert And Colbert-V2 Across Backends And Query Distributions, Utshab Kumar Ghosh, Ashish David, Shubham Chatterjee Jul 2026

Reproduction Beyond Benchmarks: Constbert And Colbert-V2 Across Backends And Query Distributions, Utshab Kumar Ghosh, Ashish David, Shubham Chatterjee

Computer Science Faculty Research & Creative Works

Reproducibility must validate architectural robustness, not just numerical accuracy. We evaluate ColBERT-v2 and ConstBERT across five dimensions, finding that while ConstBERT reproduces within 0.05% MRR@10 on MS-MARCO, both models show a drop of 86-97% on long, narrative queries (TREC ToT 2025). Ablations prove this failure is architectural: performance plateaus at 20 words because the MaxSim operator's uniform token weighting cannot distinguish signal from filler noise. Furthermore, undocumented backend parameters create an 8-point gap due to ConstBERT's sparse centroid coverage, and fine-tuning with 3x more data actually degrades performance by up to 29%. We conclude that architectural constraints in multi-vector retrieval …

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Fundamental Surface Chemistry And Mechanistic Insights Into The Flotation Of Tellurium-Bearing Pyrite From Sulfide Tailings, Mulenga Chibesa, Fardis Nakhaei, Lana Alagha Jul 2026

Fundamental Surface Chemistry And Mechanistic Insights Into The Flotation Of Tellurium-Bearing Pyrite From Sulfide Tailings, Mulenga Chibesa, Fardis Nakhaei, Lana Alagha

Mining Engineering Faculty Research & Creative Works

Tellurium (Te), a critical element for photovoltaic technologies, commonly occurs as a trace constituent in pyrite, which is typically depressed during copper porphyry flotation process and discarded to tailings. Selective flotation of pyrite offers a promising route to enhance Te production within the copper supply chain, although its recovery is often limited by surface oxidation and hydrophilic passivation. This study establishes a mechanistic framework to improve flotation of Te-bearing pyrite from copper sulfide tailings. Micro flotation tests designed using Box–Behnken response surface methodology revealed significant nonlinear and synergistic effects of pH, potassium amyl xanthate (PAX), methyl isobutyl carbinol (MIBC), and …

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Depro: Understanding The Role Of Llms In Debugging Competitive Programming Code, Nabiha Parvez, Md Tanvin Sarkar Pallab, Mia Mohammad Imran, Tarannum Shaila Zaman Jul 2026

Depro: Understanding The Role Of Llms In Debugging Competitive Programming Code, Nabiha Parvez, Md Tanvin Sarkar Pallab, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Debugging consumes a substantial portion of the software development lifecycle, yet researchers do not yet understand well the effectiveness of Large Language Models (LLMs) in this task. Competitive programming offers a rich benchmark for such evaluation, given its diverse problem domains and strict efficiency requirements. We present an empirical study of LLM-based debugging on competitive programming problems and introduce DePro, a test-case-driven approach that assists programmers by correcting existing code rather than generating new solutions. DePro combines brute-force reference generation, stress testing, and iterative LLM-guided refinement to efficiently identify and resolve errors. Experiments on 13 faulty user submissions from Codeforces …

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Llm-Enabled Open-Source Systems In The Wild: An Empirical Study Of Vulnerabilities In Github Security Advisories, Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou, Jaydeb Sarker, Mia Mohammad Imran Jul 2026

Llm-Enabled Open-Source Systems In The Wild: An Empirical Study Of Vulnerabilities In Github Security Advisories, Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou, Jaydeb Sarker, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Large language models (LLMs) are increasingly embedded in open-source software (OSS) ecosystems, creating complex interactions among natural language prompts, probabilistic model outputs, and execution-capable components. However, it remains unclear whether traditional vulnerability disclosure frameworks adequately capture these model-mediated risks. To investigate this, we analyze 295 GitHub Security Advisories published between January 2025 and January 2026 that reference LLM-related components, and we manually annotate a sample of 100 advisories using the OWASP Top 10 for LLM Applications 2025.We find no evidence of new implementation-level weakness classes specific to LLM systems. Most advisories map to established CWEs, particularly injection and deserialization weaknesses. …

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“Innocent” Electrolytes Can Influence Organic Electrosynthetic Selectivity, Zachary A. Nguyen, Nhu H. Quach, Mayank Tanwar, Joshua A. Beeler, Kevin Mcfadden, Dylan G. Boucher, Matthew Neurock, Shelley D. Minteer Jul 2026

“Innocent” Electrolytes Can Influence Organic Electrosynthetic Selectivity, Zachary A. Nguyen, Nhu H. Quach, Mayank Tanwar, Joshua A. Beeler, Kevin Mcfadden, Dylan G. Boucher, Matthew Neurock, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Organic electrosynthesis has emerged as a powerful strategy for leveraging electricity in organic synthesis. Despite its growing popularity, the fundamental molecular interactions governing electrochemical systems remain poorly understood. Many electrosynthetic reactions show strong dependence on the identity of the allegedly inert supporting electrolyte, which can significantly impact yields and selectivity, yet the physical origins of these effects are largely unexplored. A mechanistic understanding of electrolyte effects would enable more rational reaction design for applications. Here, we use cyclic voltammetry to investigate cobalt-based metal–carbon bond homolysis and elucidate how common supporting electrolytes influence reaction rates. Bulk electrolysis experiments further reveal how …

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"Todo: Fix The Mess Gemini Created": Towards Understanding Genai-Induced Self-Admitted Technical Debt, Abdullah Al Mujahid, Mia Mohammad Imran Jul 2026

"Todo: Fix The Mess Gemini Created": Towards Understanding Genai-Induced Self-Admitted Technical Debt, Abdullah Al Mujahid, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

As large language models (LLMs) such as ChatGPT, Copilot, Claude, and Gemini become integrated into software development workflows, developers increasingly leave traces of AI involvement in their code comments. Among these, some comments explicitly acknowledge both the use of generative AI and the presence of technical shortcomings. Analyzing 6,540 LLM-referencing code comments from public Python and JavaScript-based GitHub repositories (November 2022-July 2025), we identified 81 that also self-admit technical debt (SATD). Developers most often describe postponed testing, incomplete adaptation, and limited understanding of AI-generated code, suggesting that AI assistance affects both when and why technical debt emerges. We term GenAI-Induced …

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Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang Jul 2026

Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Challenges In Scaling R-Tree Spatial Search On Processing-In-Memory, Tasmia Jannat, Michael Gowanlock, Satish Puri Jul 2026

Challenges In Scaling R-Tree Spatial Search On Processing-In-Memory, Tasmia Jannat, Michael Gowanlock, Satish Puri

Computer Science Faculty Research & Creative Works

Spatial query processing is important in scientific, geospatial, and data-intensive applications. R-trees are widely used to index spatial objects, but their query-dependent traversal creates irregular work across different regions. This poster studies the challenges of scaling R-tree spatial search on a commercial Processing-in-Memory (PIM) system. Although PIM reduces CPU to memory data movement by executing search near memory, it does not remove full-pipeline overheads: the host still manages data placement, query batching, kernel launches, result retrieval, and aggregation. Our results show strong DPU-side search acceleration, with PIM kernel speedup ranging from about 20 x to 73 x, but end-to-end speedup …

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Learning Programming In Informal Spaces: Using Emotion As A Lens To Understand Novice Struggles On R/Learnprogramming, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran Jul 2026

Learning Programming In Informal Spaces: Using Emotion As A Lens To Understand Novice Struggles On R/Learnprogramming, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Novice programmers experience emotional difficulties in informal online learning environments, where Confusion and Frustration can hinder motivation and learning outcomes. This study investigates novice programmers' emotional experiences in informal settings, identifies causes of emotional struggle, and explores design opportunities for affect-aware support systems. We manually annotated 1,500 posts from r/learnprogramming using the Learning-Centered Emotions framework, applying clustering, and axial coding. Confusion, Curiosity, and Frustration dominated emotional experiences, sometimes co-occurring and linked to early learning stages. Positive emotions were infrequent. The primary emotional triggers included ambiguous errors, unclear learning pathways, and misaligned resources. We identify five key areas where novice programmers …

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Performance Evaluation Of Approximate Nearest Neighbor Search On Nvidia Bluefield-3 Dpu, Sophia Bhoria, Nathan Tibbetts, Arjun Kirubakaran, Alima Subedi, Satish Puri Jul 2026

Performance Evaluation Of Approximate Nearest Neighbor Search On Nvidia Bluefield-3 Dpu, Sophia Bhoria, Nathan Tibbetts, Arjun Kirubakaran, Alima Subedi, Satish Puri

Computer Science Faculty Research & Creative Works

Advanced SmartNICs known as Data Processing Units (DPU) enable in-network data analytics, being equipped with standard processors and accelerators capable of doing custom computation on-NIC. These SmartNICs are advantageous because the host CPU can delegate simpler data analytics tasks, like filtering, to the NIC where the data first arrives. Only data needing further refinement must be passed on to the host CPU. Our benchmarks focus on NVIDIA's commercially available Bluefield-3 DPU. Similarity search, particularly Approximate Nearest Neighbor (ANN) search, is an important domain with wide usage across numerous applications. We explore ANN search on SmartNICs, providing insight into the performance …

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Upar-Guided Dendrimer Gel Nanoparticles Reprogram Inflammation To Stabilize Atherosclerotic Plaques, Hsin Yin Chuang, Huari Kou, Yue-Wern Huang, Hu Yang Jul 2026

Upar-Guided Dendrimer Gel Nanoparticles Reprogram Inflammation To Stabilize Atherosclerotic Plaques, Hsin Yin Chuang, Huari Kou, Yue-Wern Huang, Hu Yang

Biological Sciences Faculty Research & Creative Works

Atherosclerosis is characterized by lipid deposition, chronic inflammation, and apoptosis within the arterial wall, leading to plaque progression and instability. Current lipid-lowering therapies fail to fully address residual cardiovascular risk driven by local inflammation and cell death. Here, we report the development of uPA-functionalized, rapamycin-encapsulated dendrimer nanoparticles (G5PM-uPA/RA) that preferentially accumulate in urokinase plasminogen activator receptor (uPAR)-enriched atherosclerotic plaque, including macrophage- and apoptosis-rich lesion microenvironments. G5PM-uPA/RA was constructed by cross-linking reaction-enabled flash nanoprecipitation in a custom-made multi-inlet vortex mixer, followed by thiol-maleimide conjugation of uPA for uPAR-guided targeting. The nanoparticles demonstrated uniform morphology, favorable stability, and efficient rapamycin loading. In …

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Comparative Lca Of Germanium Production From Coal Fly Ash Using Chlorinated Distillation And Solvent Extraction, Dennis Dadzie, Kwame Awuah-Offei, Michael Moats, Nasib Al Habib, Weston Hartzell Jul 2026

Comparative Lca Of Germanium Production From Coal Fly Ash Using Chlorinated Distillation And Solvent Extraction, Dennis Dadzie, Kwame Awuah-Offei, Michael Moats, Nasib Al Habib, Weston Hartzell

Mining Engineering Faculty Research & Creative Works

Germanium is increasingly important for high-tech applications, yet its supply chain is vulnerable, with production limited to a few countries. Although prior research has explored alternative techniques for extracting and recovering germanium, the literature lacks comparative life-cycle evidence that quantifies their environmental burdens and translates findings into actionable (policy) recommendations. This paper presents a cradle-to-gate life-cycle assessment that compares the environmental burdens of producing 1 kg of single-crystal germanium from coal fly ash via chlorinated distillation (CD) and solvent extraction (SX). Under the study's assumptions, CD has lower potential impacts in 15 of 19 impact categories, while both routes show …

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Dynlp: Parallel Dynamic Batch Update For Label Propagation In Graph-Based Semi-Supervised Learning, S. M. Shovan, Arindam Khanda, S. M. Ferdous, Sajal K. Das, Mahantesh Halappanavar Jul 2026

Dynlp: Parallel Dynamic Batch Update For Label Propagation In Graph-Based Semi-Supervised Learning, S. M. Shovan, Arindam Khanda, S. M. Ferdous, Sajal K. Das, Mahantesh Halappanavar

Computer Science Faculty Research & Creative Works

Semi-supervised learning aims to infer class labels using only a small fraction of labeled data. In graph-based semi-supervised learning, this is typically achieved through label propagation to predict labels of unlabeled nodes. However, in real-world applications, new data often arrives in batches, and stale data often becomes irrelevant. Each time a new batch appears, reapplying the traditional label propagation algorithm to recompute all labels is redundant, computationally intensive, and inefficient. To address the absence of an efficient label propagation update method, we propose DynLP, a novel GPU-centric Dynamic Batched Parallel Label Propagation algorithm that performs only the necessary updates, propagating …

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3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing, Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire Jul 2026

3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing, Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In additive manufacturing (AM), stress field drives distortion and warping and promotes delamination and cracking. Fast, accurate stress prediction is therefore essential for AM process planning and control, including real-time adaptive control, AM digital twins, data-driven and physics-driven workflows. However, spot-wise thermo-elasto-plastic finite element method (FEM) are often too slow for design iteration or real time use. Existing semi-analytical thermo-elasto-plastic approaches achieve high speed but are largely limited to 2D. In this paper, a full 3D semi-analytical thermo-elasto-plastic model for AM is built. The method uses a spot-wise analytical thermal field as the load and computes displacements and stresses via …

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An Automated Electrochemistry Platform For Accelerating The Characterization Of Enzymatic Electrochemistry, Michael A. Pence, Zachary A. Nguyen, Luke G. Kays, Dylan G. Boucher, Joaquín Rodríguez-López, Shelley D. Minteer Jul 2026

An Automated Electrochemistry Platform For Accelerating The Characterization Of Enzymatic Electrochemistry, Michael A. Pence, Zachary A. Nguyen, Luke G. Kays, Dylan G. Boucher, Joaquín Rodríguez-López, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Enzymatic electrochemistry harnesses the selectivity of enzymes to enable electrochemical applications spanning sensing, synthesis, and energy conversion. However, the sequential nature of electroanalytical experiments limits throughput, restricting the scale at which enzyme-electrode systems can be screened. Here we demonstrate the capabilities of an automated electrochemistry platform, eLab, to increase the throughput of enzymatic electrochemistry investigations. We used the eLab to collect over 10,000 cyclic voltammograms across a large parameter space consisting of two enzyme variants (promiscuous and wild-type glucose oxidase), 20 saccharide substrates, 21 concentrations, and four scan rates, with measurements being made all in triplicate. The expansive dataset enabled …

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Existence And Uniqueness Of Positive Solutions For Hilfer–Hadamard-Type Fractional Differential Equations With Γ-Concave And Sub-Homogeneous Operators, Hasan Rasouli, Hojjat Afshari, Martin Bohner Jul 2026

Existence And Uniqueness Of Positive Solutions For Hilfer–Hadamard-Type Fractional Differential Equations With Γ-Concave And Sub-Homogeneous Operators, Hasan Rasouli, Hojjat Afshari, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

In this research, we present necessary and sufficient conditions for the existence and uniqueness of positive solutions for a class of Hilfer–Hadamard-type fractional differential equations with boundary value problems, including those with integral boundary conditions. The obtained results are conditional on a specific set of strong assumptions, which substantially narrow the class of admissible nonlinearities, coefficients, and boundary data. Thus, the present work extends the Hadamard-type framework to the Hilfer–Hadamard setting only within this restrictive regime, rather than providing a full extension to all Hilfer–Hadamard systems. We utilize the properties of (Formula presented.) -concave and sub-homogeneous operators along with two …

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A System Dynamics Model For Analyzing Customer Satisfaction Drivers In A Manufacturing Context, Mahnaz Asgari Sooran, Venkat Allada, Adewole Adegbola Jul 2026

A System Dynamics Model For Analyzing Customer Satisfaction Drivers In A Manufacturing Context, Mahnaz Asgari Sooran, Venkat Allada, Adewole Adegbola

Engineering Management and Systems Engineering Faculty Research & Creative Works

Customer satisfaction offers economic benefits and competitive advantage to manufacturing enterprises. However, a gap exists in understanding how to achieve customer satisfaction due to the complexities involved in coordinating various subsystems of an enterprise in an efficient manner. In this paper, we identified four internal and external-to-the-firm customer satisfaction drivers which include: government policies, supply chain reliability, knowledge management, and manufacturing performance criteria such as on-time delivery, quality and cost. We then developed a conceptual framework to define the non-linear mathematical relationships between drivers using system dynamics modeling. We conducted "what-if "scenario analyses for a base case, optimistic case and …

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Digital Twin-Assisted Optimization Of 6g Wireless Networks: Ensuring Deterministic Communication, Yingpu Nian, Bo Yi, Xingwei Wang, Sajal K. Das Jul 2026

Digital Twin-Assisted Optimization Of 6g Wireless Networks: Ensuring Deterministic Communication, Yingpu Nian, Bo Yi, Xingwei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

With the rapid advancement of 6G technology and the increasing use of smart devices, Deterministic 6G Wireless Networks (D6WN) have emerged to meet the growing network transmission demands. In particular, applications such as autonomous vehicles, remote surgery, and industrial automation require extremely low transmission latency to function effectively, highlighting the critical need for D6WN in supporting these time-sensitive use cases. Yet, the conventional TCP/IP framework lacks effective unified traffic and congestion control scheduling, aggravating latency and uncertainty, posing a challenge to ensuring reliable real-time critical applications. To address the challenges of deterministic transmission in D6WN, this paper integrates Digital Twin …

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Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas Jul 2026

Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas

Computer Science Faculty Research & Creative Works

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, …

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