Digital Commons Network^™

Legal Ethics Of Ai Snake Oil: Navigating The Hype, Harm, And Hope Of Legal Ai, Drew Simshaw

Michigan Law Review

A review of AI Snake Oil.By Arvind Narayanan and Sayash Kapoor.

Supramolecular Assembly In Short Peptide Systems For Selective Metabolite Recognition And Drug Nanoencapsulation, Maithreyi Ramakrishnan

Dissertations, Theses, and Capstone Projects

Short peptides can form adaptive supramolecular assemblies, and understanding how minimal sequences organize around neurometabolites or hydrophobic cancer drugs enables the rational design of functional materials. This thesis combines molecular dynamics with experimental validation to establish design rules linking peptide sequence to emergent structure and function. Chapter 1 outlines the molecular determinants governing peptide assembly. Chapter 2 reviews computational workflows that reveal sequence-dependent conformations and supramolecular organization. Chapter 3 applies these principles to Dynamic Peptide Libraries which identify tetrapeptides that selectively interact with neurometabolites. Chapter 4 extends the same interaction-driven framework to design tryptophan-rich pentapeptides that co-assemble with kinase inhibitors …

Saag: Structured Agent Assessment And Grounding, Ritvik Garimella, Vedant Khandelwal, Anvi Kohli, Amit Sheth

Publications

Exact-match evaluation of agent-calling obscures qualitatively different failure modes: a model may select the right function yet hallucinate argument values, or satisfy a schema while choosing a agent for the wrong reason. Existing benchmarks collapse these distinctions into a single binary score, leaving practitioners unable to diagnose where agent calls fail. We propose SAAG a cascaded diagnostic framework that decomposes agent-calling evaluation into three sequential stages: registry conformance, structural completeness, and argument grounding, each producing interpretable stage-specific diagnostics. These diagnostics additionally enable iterative self-repair: on prediction failure, the stage-specific signal guides targeted correction without leaking ground-truth values. We evaluate this …

Scaling Up Multi-Agent Reinforcement Learning For Large Agent Teams And Long-Horizon Tasks: A Survey, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Multi-agent reinforcement learning (MARL) empowers multiple autonomous agents to acquire effective policies for collaborative problem-solving. Over the last decade, MARL has seen significant advancements, with numerous algorithms achieving impressive performance across various benchmarks and real-world applications. Nevertheless, the scalability of multi-agent systems, in terms of the number of agents and the length of the task horizon, remains a critical consideration for applying MARL methods to complex problem-solving. Given that a dedicated review of the existing approaches and challenges in scaling up multi-agent systems remains largely absent, this survey aims to bridge this gap by delivering a comprehensive review of MARL …

Frozen Lvlms For Micro-Video Recommendation: A Systematic Study Of Feature Extraction And Fusion, Huatuan Sun, Yunshan Ma, Changguang Wu, Yanxin Zhang, Pengfei Wang, Xiaoyu Du

Research Collection School Of Computing and Information Systems

Frozen Large Video Language Models (LVLMs) are increasingly employed in micro-video recommendation (MVR) due to their strong multimodal understanding. However, existing apporches typically deploy LVLMs as fixed black-box feature extractors without systematically comparing alternative representation strategies. To address this gap, we present the first systematic empirical study on various feature extraction paradigms and integration strategies, along with hierarchical representations from frozen LVLMs for MVR. Extensive experiments on representative LVLMs reveal that hidden states from multiple decoder layers provide richer and more effective representations for MVR. Guided by this insight, we propose the Dual Feature Fusion (DFF) Framework, a lightweight approach …

Context Matters: Auditing Gender Bias In T2i Generation Through Risk-Tiered Use-Case Profiles, Jose Luis Luna Campoverde, Yankun Wu, Xiaofei Xie, Noa Garcia

Research Collection School Of Computing and Information Systems

Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting to be integrated into higher-impact pipelines. Since generated images tend to reinforce stereotypes, producing representational erasure via “default” depictions and shaping perceptions of who belongs in certain roles, a growing body of work has proposed metrics to quantify gender bias in T2I outputs. Yet existing evaluations remain fragmented. Metrics are often reported without a shared view of what they measure, what assumptions they entail, or how their results should be interpreted under different deployment contexts. This limits the usefulness of gender …

Anatomical Domain Shifts: Test-Time Heterogeneous Adaptation For 3d Human Pose Prediction, Qiongjie Cui, Pan Zhou, Jingjing Chen, Na Zhao

Research Collection School Of Computing and Information Systems

The research frontier in human pose prediction (HPP) is advancing toward continual test-time adaptation (TTA), where models must self-adapt to dynamic test distributions. To date, the homeostatic continual TTA remains the sole viable solution, which isolates the model parameters and update domain-sensitive ones. Despite mitigating full-body domain gaps, human anatomical heterogeneity (domain shifts often localize to specific regions) is ignored. This anatomical-agnostic approach forces uniform parameter adaptation across kinematically distinct segments, causing: over-adaptation of stable regions and under-adaptation of shift-prone articulations. To address it, we introduce TT-HA, a novel Test-Time Heterogeneous Adaptation that implicitly estimates domain changes for anatomical segments, …

Municipality Of Bayamón V. Exxon Mobil Corp. (2025): Bringing Racketeering Charges For Climate Justice, Ilinca C. Johnson

Pace Environmental Law Review

Environmental justice communities should have their climate change damages heard in the courtroom. One means to increase environmental justice claims is through claims under the federal Racketeer Influence and Corrupt Organizations (RICO) Act. Using Municipality of Bayamón v. Exxon Mobil Corp. (2025) as a model, this Article suggests a novel RICO case strategy to pursue climate damages for marginalized communities. Fundamentally, environmental justice RICO claims involve careful case design based on the climate-related damages a marginalized community has faced because of the long-term deception by fossil fuel actors upon those communities. Pursuing such claims forwards the intersectional issues faced by …

Intervention Levers For Stunting Reduction In Indonesia: Evidence From The 2023 Indonesian Health Survey Data, Iwan Ariawan, Hafizah Jusril, Zahra Izza Afifa, Azka Fitri, Elmarizha Sekar Utami, Mikail Hasan, Dwi Puspasari

Kesmas

Stunting remains the largest public health challenge among macro-nutrition problems in Indonesia, affecting almost a quarter of children under five in 2023. The prevalence is considered high according to the World Health Organization standard. This study analyzed 15 aggregated provincial variables from the 2023 Indonesian Health Survey using Structural Equation Modeling (SEM), focusing on determinants of stunting among children under two to identify primary intervention levers. Findings indicated that intervention urgency should focus on the first 1,000 days, particularly the steep increase in stunting prevalence observed in the 12–24-month age range. While the highest prevalence is in Eastern provinces (e.g., …

Mechanics And Physical Attributes Of Nature-Based Alterations: Rock Reinforcement And Urban Heat Island Assessment, Mary Chikondi Ngoma

Dissertations

Ground improvement is critical to geotechnical and geo-engineering systems, where modification of the properties of geomaterials (rocks and soils) is required to maintain stability and prevent failure of infrastructure installed within and around them. This need has become increasingly important with rapid urbanization and population growth, which intensify demands on surface and subsurface systems and further challenge the performance of supporting geomaterials. As a result, there is growing interest in nature-based solutions, particularly biologically mediated processes such as biocementation, which can enhance the physical, hydraulic, and mechanical properties of geomaterials while offering environmentally sustainable alternatives to conventional ground improvement techniques. …

Holistic Dram Enhancements: From Intrinsic In-Memory Operations To Robust Security Mechanisms, Ranyang Zhou

Dissertations

Dynamic Random-Access Memory (DRAM) is both the performance bottleneck and a critical security boundary of modern computing systems. Its physical properties make it an attractive substrate for near-data computation—yet those same properties expose it to disturbance-based hardware attacks. This dissertation argues that these two dimensions are not independent: the architectural choices that make DRAM efficient also reshape its threat landscape. Addressing both requires a unified approach to memory architecture and security co-design.

The first part of this dissertation attacks the memory wall through four processing-in-DRAM (PIM) frameworks. ReD-LUT and LT-PIM unify lookup-table arithmetic with charge-sharing logic, achieving up to 37.8x …

A Generative Ai-Driven Computational Framework For Industry-Scale Discovery Of Novel Battery Materials, Joy Datta

Dissertations

The growing demand for sustainable, high-energy-density electrochemical storage has motivated the exploration of multivalent-ion batteries based on earth-abundant elements such as aluminum, calcium, magnesium, and zinc. While multivalent charge carriers offer higher theoretical energy density than lithium, their practical deployment is hindered by sluggish ion transport, strong ion-host interactions, and structural degradation of electrode materials. Identifying host materials that can reversibly accommodate multivalent ions while maintaining structural integrity remains a fundamental challenge. The dissertation develops a scalable, end-to-end computational framework that integrates density functional theory (DFT), machine learning (ML), and generative artificial intelligence (GenAI) to accelerate the discovery of next-generation …

Toward Learning-Based Reconstruction And Part Decomposition Of Man-Made 3d Geometry: Neural Implicit Representations And Scalable Supervision, Shen Fan

Dissertations

Digital three-dimensional (3D) models are central to engineering design, analysis, and manufacturing, but learning pipelines for man-made geometry often operate on sampled carriers that do not preserve all of the structure present in exact CAD representations. This dissertation studies learning-based reconstruction and part decomposition for structured man-made 3D geometry, from general object benchmarks to CAD-derived datasets, with a focus on neural implicit representations trained from signed-distance samples, point clouds, and tessellated meshes. The goal is to make these models more accurate, more part-aware, and more consistently supervised.

First, signed distance function (SDF) reconstruction with implicit neural representations is improved through …

Grassland Development In Japan And Other Asian Countries, I Nikki

IGC Proceedings (1977-2023)

Only since World War II has attention been directed to grassland injapan. Forage crops were introduced on dairy farms for feeding cattle . Acreages have increased and now equal 15 % of the total field area. Forage crops are second to :rice as a major crop . The New Grassland Law, approved in 1950, has led to "grassland improvement" and development of established pastures. J apa:n, situated in the most northern part of the Asian Monsoon Area, is warm as a rule and has much rainfall. Miscanthus sinen­sis Steud. and Zoysiajaponica Steud. are the dominant representative species of natural grassland. …

Collections Of Western Wheatgrass And Blue Grama And Associated Nematode Genera In The Western Dakotas, R E. Barker, J D. Berdahl, J M. Krupinsky, E T. Jacobson

IGC Proceedings (1977-2023)

Western wheatgrass (Agropyron smithii Rydb.) and blue grama (Bouteloua gracilis[Willd. ex H.B.K.J Lag. ex Griffiths) are widely distributed throughout the U.S.A. They arc two of the predominant native grasses in rangelands in the northern Great Plains. Because suitable cultivars are not always available for reseeding disturbed areas, we collected plants of the two species and evaluated phenotypic variability to determine potential for breeding improvement. We also sampled the nematode popula­tion associated with the collections. Sampling sites were systematically chosen by establishing a grid pattern 19 .3 km apart in the western halves of North Dakota and South Dakota. …

Classical-Correlation-Enhanced Weak-Value Amplification Resilient To Persistent Noises, Xu-Song Hong, Gong-Chu Li, Lei Chen, Si-Qi Zhang, Hua-Qin Xu, Yuancheng Liu, Shengshi Pang, Andrew N. Jordan, Geng Chen, Chuan-Feng Li, Guang-Can Guo

Mathematics, Physics, and Computer Science Faculty Articles and Research

Weak measurement (WM) offers the advantage of amplifying small signals at the cost of postselecting a small portion of the probes. This so-called weak-value amplification effect makes it compare favorably with conventional techniques (without postselection) to overcome various technical noises. However, certain types of technical noise, such as jitter and pixelation, present insurmountable limitations for both WM and conventional techniques. In this work, we propose an advanced variant of WM that incorporates time-momentum correlation (TMC) into biased weak measurement (BWM). By employing the Fisher information metric, we theoretically show that TMC-BWM can overcome jitter and pixelation, and meanwhile extract significantly …

Sealing Performance Evaluation Criteria And Profile Optimization Of The Volumetric Cavities Of Positive Displacement Motors For Directional Drilling, Kuang Yuchun, Hu Xin, Zhou Jingpei, Luo Jinwu, Liu Yihui, Han Yiwei

Coal Geology & Exploration

Objective Constrained by complex stratigraphic conditions in underground coal mines, directional drilling faces challenges such as low efficiency when encountering medium-hard and hard formations. Positive displacement motors (PDMs) with a diameter of 89 mm are commonly used for directional drilling. Their efficiency is primarily influenced by the sealing performance of their volumetric cavities, which further significantly affects the drilling efficiency. Methods Based on the structural characteristics of the three-dimensional (3D) volumetric cavities of PDMs and the simulation method of two-way fluid-structure interactions, this study proposed the criteria for quantitatively evaluating the efficiency and volumetric cavity performance of PDMs, followed by …

Stoker-Fired Laboratory Boiler As A Tool For Optimising The Solid Fuel Combustion Process, Przemysław Rompalski, Justyna Guzy-Proc, Mariusz Kieczek

Journal of Sustainable Mining

This paper presents the results of quality testing performed on a stoker-fired laboratory boiler to present the technical potential of the boiler as a tool for optimising the combustion process of prepared solid fuels (granulate, energy blend) in the context of current demands related to the decarbonisation policy. The comprehensive testing of such fuels at a laboratory scale makes it possible to gain deep insights into the quality parameters of the fuel, flue gas and combustion waste, as well as to determine the combustion process parameters before the fuel is introduced for combustion in broader power engineering and household boilers. …

How Fe(Ii)/2-Oxoglutarate Oxygenase Chooses Chlorination Over Hydroxylation: Electric Field-Driven Ligand Exchange Governs C-Cl Formation, Simahudeen Bathir Jaber Sathik Rifayee, Midhun George Thomas, Anandhu Krishnan, Kritika Gupta, Carter Davis, Tatyana Karabencheva-Christova, Christo Z. Christov

Michigan Tech Publications

Non-heme Fe(II)/2-oxoglutarate (2OG)-dependent halogenases catalyze highly selective C-H halogenation. BesD is a non-heme Fe(II)/2OG halogenase that performs regio- and stereoselective chlorination of the l-lysine (l-Lys) substrate. Understanding the mechanism by which halogenation is favored over canonical hydroxylation is essential for guiding enzyme engineering efforts aimed at converting hydroxylases into halogenases. Here, we combine molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations to elucidate the origin of chlorination selectivity in BesD and variants derived from a homologous hydroxylase. Our results indicate that, although the initial inline Cl-Fe(III)-OH intermediate is inherently predisposed toward hydroxylation, it undergoes a two-step isomerization in …

Linking Fishery Productivity To Child Health In The Coastal Tropics, Francisco Flores-Mejia

Master's Theses

Fish are a primary source of calories, macronutrients, and income for coastal communities around the world, but overfishing and environmental changes have dramatically reduced productivity in the majority of small-scale fisheries. The social costs of these losses are believed to be large, particularly in poorer communities, but most estimates of fishery productivity effects on households are contextual and difficult to generalize. We combine a remote sensing measure of pelagic fishery productivity with geolocated child health and growth data from 34 countries in the coastal tropics. We estimate that the difference between sustainedly good versus bad fishing conditions corresponds up to …

Comparative Analysis Of Transportation Emissions And Policy In Lahore And Los Angeles, Laiba Rehman

Master's Projects and Capstones

In 2023, exposure to air pollution killed 7.9 million people globally, becoming the second leading cause of death worldwide. Transportation emissions are among the primary drivers of this burden especially in rapidly urbanizing cities where vehicle fleets are growing faster than regulatory frameworks respond. This study examines the contribution of transportation emissions to urban air quality, public health and climate change in Lahore, Pakistan and Los Angeles, California. First, it employs a secondary data analysis of PM_2.5 and ozone concentrations and vehicle fleet composition in each city, followed by an analysis of emission inventories. Second, it evaluates the regulatory …

Decision Making At Triage Classification Using Svm With Smote Technique, Mehanas Shahul, Pushpalatha Kp

Northeast Journal of Complex Systems (NEJCS)

The efficient functioning of triage gates in overcrowded emergency departments (EDs) occurs in the context of the complex adaptive system (CAS) framework, where diverse system elements – patients, medical personnel, resources, patients’ inflow patterns, and patients themselves – simultaneously and dynamically influence the decision process. This study addresses the automated incorporation of machine learning triage algorithms as part of the system triage process to support automated classified risk-level recognition based on a limited set of vital signs. Patients are dynamically subsumed under high and low-risk categories enhanced by sensitivity, which enables optimal diagnosis and triage response to the critical clinician …

Material Costs, Karima Weinman

Masters Theses

This thesis investigates how migration fatality and disappearance data can be reinterpreted through material craft to create a more reflective encounter with information. Working with the Missing Migrants Project's dataset, this project asks how design can communicate dimensions of human loss that conventional data visualization cannot reach.

The work situates contemporary border violence within a longer colonial history, arguing that the logics of surveillance and quantification that structured European imperial expansion persist in the databases that govern mobility in the Mediterranean today.

Terrazzo is a 15th-century Venetian flooring technique built from discarded fragments bound together into a unified surface. This …

Computational-Experimental Synergy As A Predictive And Interpretive Tool Through Metal-Organic Framework Investigations, Cristian Sayers

Graduate Student Theses and Dissertations

In the search for tunable materials platforms capable of addressing both clean energy conversion and viable post-combustion carbon capture, metal-organic frameworks (MOFs) have emerged as a uniquely versatile class of porous solids offering high specific surface area, structural tunability, and chemically addressable metal nodes and organic linkers. Realizing their potential requires understanding behavior that spans atomic-scale electronic structure and bulk-scale property response, a regime in which neither computation nor experiment alone is sufficient. This work attempts to develop a tighter integration between density functional theory (DFT) and laboratory investigation, treating the two modalities as mutually informing probes of the same …

Conditional Product Sampling For Gaussian Process Implicit Surfaces, Song Shi

Dartmouth College Master’s Theses

Gaussian Process Implicit Surfaces (GPISes) provide a powerful and unified stochastic geometry representation for rendering surfaces, volumes, and the rich continuum between them. Recent work has shown that GPISes can model a broad space of visual appearances under a unified light transport framework. However, practical rendering with GPISes remains challenging: existing estimators can become inefficient for particular correlation structures, and highly anisotropic or heightfield-like GPISes require specialized treatment to obtain robust variance reduction.

This thesis extends recent work on GPIS rendering by introducing a new next-event estimation (NEE) technique for anisotropic GPISes.We show that standard NEE provides diminishing benefits as …

Beyond Stabilization: Biological Healing, Structural Exclusion, And The Recovery Gap After Border-Fall Trauma At The U.S.-Mexico Border, Julia Robinson

Undergraduate Honors Theses

This honors thesis examines the biochemical, ethical, and public health consequences of insufficient post-operative follow-up care for undocumented immigrants injured in border falls. Discussing pathways of inflammation resolution, wound healing, and bone remodeling, this thesis argues that recovery depends on tightly regulated molecular and cellular processes that are highly vulnerable to disruption without continued monitoring and rehabilitation (Loi et al., 2016; Maruyama et al., 2020). When follow-up care is absent, these processes can be predicted to derail, leading to infection, impaired healing, and permanent disability (Chung & Sohn, 2025; Howard et al., 2020; Kruidenier et al., 2018). Framed through principles …

Arylation Of Nitrogen, Oxygen And Carbon Nucleophiles By Aryl(Tmp)Iodonium Salts, Joseph Jordan Hatton

Dissertations and Theses

Substituted aromatic rings are present in industry in a plethora of organic molecules such as pharmaceuticals, agrochemicals, materials and beyond. Therefore, methods for broadly installing aryl rings into other compounds to create substituted aromatic rings are valuable to many organic chemists. Historically these transformations are achieved through methods such as nucleophilic aromatic substitution and metal catalyzed cross-coupling. Nucleophilic aromatic substitution is a user-friendly method in this space but is limited by reliance on specific electronics. Metal catalyzed cross-coupling reduced the dependence on electronics in this space, but metals are generally unattractive reagents due to high costs, toxicity and challenges with …

Innovation Strategies For Small And Medium-Sized Construction Companies In Nigeria, Olabode Akinkunmi Akindele

Walden Dissertations and Doctoral Studies

No abstract provided.

Exploring Resource-Efficient Deep Learning For Medical Image Segmentation, Pallabi Dutta

Doctoral Theses

Automated medical image segmentation improves diagnostic accuracy by au tomating the precise delineation of target anatomical structures in the input images. Artificial Intelligence (AI), and specifically, Deep Learning (DL), has emerged as a state-of-the-art approach for this task. However, the significant computational demands of DL approaches often hinders their deployment. Ad vanced models, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), require substantial processing power and a large memory footprint, limiting their use in resource-constrained settings. This thesis aims to address this challenge by developing a series of novel, resource-efficient DL models that achieve high segmentation accuracy with reduced …

3d Puzzle Generation Beyond Voxelized Parts, Iris Xia

Computer Science Theses

Burr puzzles are interlocking assemblies whose pieces must be inserted and removed through tightly constrained motions. Designing them is difficult because geometric fit, interlocking behavior, and disassembly order are tightly coupled, while existing computational methods remain largely limited to voxelized or template-based constructions.

This work presents a framework for 3D puzzle generation beyond voxelized parts. The method replaces local mobility heuristics with a certified search over geometry edits. Starting from a topological contact specification, it constructs signed distance fields for individual parts, applies complementary local edits, and validates each candidate using exact geometric checks and a kernel disassembly graph. The …