Digital Commons Network^™

Synergistic Strategies For Regional ‘Zero-Waste City’ Construction, Xiaolong Liu, Zongguo Wen, Yanyan Tang, Xiangwan Du

Bulletin of Chinese Academy of Sciences (Chinese Version)

“Recommendations of the Central Committee of the Communist Party of China for Formulating the 15th Five-Year Plan for National Economic and Social Development” emphasizes deepening cross-administrative cooperation, and improving mechanisms for inter-regional planning coordination, industrial collaboration, and benefit sharing to promote regional linked development. While China’s “zero-waste city” initiative has achieved remarkable results, its long-term sustainability necessitates a shift towards coordinated regional synergy. This requires establishing enduring mechanisms for collaborative solid waste governance that transcend governmental, hierarchical, and departmental boundaries. The ultimate goal is to optimize the allocation of waste treatment resources between neighboring and even non-adjacent regions, foster a …

Research On Signal Perception System Of Key Technology Regulation In The United States, Kaile Wang, Hao Liu, Yunwei Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

The purpose of the study is to analyze the operation mechanism of the key technology control signal perception system, and reveal the deep logic and basic procedures of the United States’ external technical containment. Through literature review and information mining, this study analyzes the structural features of the U.S. key technology control signal perception system, such as “front-end technical perception and technology locking”, “mid-end technical evaluation and risk identification”, and “back-end technical control response and dynamic sanctions”. It further explores the participating subjects and role positioning of the United States in key technology control signal perception, the sources and mechanisms …

Sga 57 Senate 2026-03-20 Minutes, Niu Student Government Association Senate

Student Government Association Archives

No abstract provided.

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft 2022 Stormwater Evaluation And Maintenance Report (Dated February 27, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft 2024 Stormwater Evaluation And Maintenance Report (Dated February 27, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Curricular Changes Proposed For 2025-2027 Morris Catalog, Curriculum Committee

Curriculum Committee Reports

Includes documentation on the discontinuation of Sociology, Geology, German Studies, and Latin American Area Studies (LAAS).

Chemical Synthesis For Mesoporous Silica (Mcm-41) And Evaluating Its Efficiency In Removal Of Heavy Metals Ions, Israa M. Faliyh, Wahran M. Saod

Baghdad Science Journal

The pollution of water sources due to harmful chemicals, especially heavy metal ions such as Ni⁺⁺ and Co⁺⁺, remains a global challenge. To address this issue, various studies have focused on developing new treatment methods. Nanotechnology provides innovative techniques for efficiently removing heavy metals and other pollutants from water and wastewater. It is crucial to eliminate these hazardous heavy metals to protect both human health and the environment. Mesoporous silica (MCM-41) is a type of silica nanoparticles with pores ranging from 2 to 50 nm in diameter, and a total diameter below 1 μm. It is gaining …

Microstructural Evolution And Precipitate Control In Boron-Doped Ni-Mn-Ti Shape Memory Alloys Via Thermal Processing, Na Liu, Marcia Ahn, Subrata Ghosh, Dipika Mandal, Bed Poudel, Wenjie Li

Biochemistry, Chemistry & Physics: Faculty Publications

Elastocaloric cooling, which leverages stress-induced phase transformation in shape memory materials, represents a sustainable and energy-efficient alternative to conventional vapor-compression cooling systems. Central to optimizing these materials is understanding how thermal processing history dictates phase formation, microstructure, and thermal properties. In this study, we investigated the (Ni50Mn31.5Ti18)99.8B0.2 compound synthesized via vacuum induction melting and arc melting, followed by water quenching. Induction melting results in needle-like, boron-rich precipitates within the martensite lattice. In contrast, vacuum arc melting promoted precipitate growth at the grain boundaries. The vacuum arc melting sample exhibits ~82% martensite phase fraction, a near-ambient transformation temperature of ~277 K, …

Heavy Metal Contamination In Agricultural Soils And Potential Human Health Risks, Debora Michael Mwenda, Leonard Masesa Jumanne, Daudi Salvius Mgaya, Amos Vincent Ntarisa

Tanzania Journal of Science

Heavy metal contamination in agricultural soils is a growing concern due to potential human health risks via ingestion, dermal contact, and inhalation. However, data on fertiliser-related contamination in rural Tanzanian settings remain limited. This study assessed contamination levels and associated health risks in Kibwabwa village, Iringa, Tanzania. A total of 48 soil samples were collected from eight farms at a depth of 0–15 cm. Concentrations of Cu, Zn, Ni, Cd, Cr, and Pb were determined using Atomic Absorption Spectroscopy (AAS). Health risks were evaluated using chronic daily intake (CDI), hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR) models …

Survival Politics On A Working Waterfront: Rules Change Faster Than Prices In The South Texas Shrimp Fishery, Owen Temby, Anthony R. Lima

School of Earth, Environmental, & Marine Sciences Faculty Publications

In 2024–2025, the U.S. and Texas governments raced to save Gulf shrimp. Texas passed a truth-in labeling law for food service in restaurants. Federal agencies added antidumping and countervailing duty orders and new tariffs. This case follows Brownsville and Port Isabel, where dock prices slid while boats and crews aged. We frame the response as survival politics: urgent and improvised moves to keep a livelihood going even when imports set the price. Using legislative hearings, agency notices, local reporting, and port records, we show that rules reset faster than prices. Inventories, contracts, and supplier substitution delay any lift at the …

From Network Packets To Physical Consequences: Network-Level Spoofing And Loss Of Visibility In Industrial Control Systems, Lillian B. Beck

LSU Master's Theses

Industrial Control Systems (ICS) are the foundation of critical infrastructure as they provide resources like clean water, electricity, and natural gas to support our everyday functions. Given their essential role in modern society, the failure or compromise of ICS systems can lead to significant negative consequences and public safety impacts. Understanding how these systems can be targeted and exploited by malicious actors is necessary to improve their security and resilience.

This research examines how an attacker could manipulate a real-world ICS network by targeting a fully functional Natural Gas (NG) Compressor Station Platform that emulates real operations. This research led …

Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks, Donovan Gegg

LSU Master's Theses

Autonomous Underwater Vehicles (AUVs) are untethered robotic platforms used for tasks such as seafloor mapping, infrastructure inspection, and environmental monitoring. Recent technological advances have produced smaller, more affordable platforms, broadening access to research teams and small companies alike. This miniaturization comes at the cost of them handling drawbacks associated with a more compact machine such as reduced battery capacity as well as limited processing and sensing capabilities. These constraints make small-sized marine vehicle’s reliability critical as they can cause malfunctions, making the loss of a vehicle more likely. Actuator faults are particularly consequential as unintended and unstable control in an …

Effectiveness Of Peace Education And Recommendations For Implementation In The Sultanate Of Oman's School Curriculum, Vision 2040, Mohamed Al Braiki

Dissertations and Theses

This study explores peace education as an institutional process within the Sultanate of Oman's K–12 education system. Currently, Oman Vision 2040 articulates commitments to social cohesion, global citizenship, and holistic development. Existing empirical research indicates constant challenges related to bullying, student well-being, emotional distress, and school-related harm. This study conceptualizes peace education as a structural and relational mechanism embedded within institutional routines, leadership practices, and conflict-management responses. Using a qualitative integrative review design, the study examines peer-reviewed research, policy documents, and institutional analyses relevant to Oman, the Gulf region, and broader peace education scholarship. The analysis is guided by theoretical …

Volume 60-1 Full Issue, Ryan Brown

Journal of STEM Teacher Education

No abstract provided.

A Mixed-Methods Study Of Teacher Collaboration In A Steam Professional Development Program, Katherine B. King, Justina R. Jackson, Talia C. Kessler, Meltem Alemdar

Journal of STEM Teacher Education

Teacher collaboration can be a powerful but challenging practice for K-12 educators. This is particularly true in the context of STEAM (science, technology, engineering, arts, and math) education, in which disciplines are integrated through innovative, student-centered teaching strategies. A sequential explanatory mixed-methods approach was employed to understand the impacts of a 5-year STEAM professional development program on K-12 teachers’ collaboration efforts. Using quantitative and qualitative methods and social network analysis (SNA), the study explored the nature of STEAM collaboration and identified aspects that supported and hindered successful collaboration. Quantitative analyses demonstrated that, after participating in the program, the teachers engaged …

Culturally Responsive Stem Teaching With Artificial Intelligence, Dr. Eun Kyung Ko

Journal of STEM Teacher Education

This study examines how integrating Artificial Intelligence (AI) tools, specifically ChatGPT, into teacher education can enhance culturally responsive teaching (CRT) in STEM education. AI's potential to support lesson planning, streamline administrative tasks, and offer personalized learning paths is explored alongside its challenges, such as ethical concerns and contextual adaptation. The study involved pre-service elementary teachers who used AI modules to design CRT-aligned STEM lessons, reflecting on their experiences through surveys and journals. The findings reveal that AI enhances efficiency, generates creative ideas, and fosters inclusivity by providing culturally relevant materials. However, the study emphasizes that AI cannot replace human expertise …

Navigating Stem Integration: Instructional Strategies Employed By Teachers In High School Classrooms, Yousef Alrashdi, Paul Asunda

Journal of STEM Teacher Education

This study examined the instructional strategies used by high school STEM teachers to incorporate real-world problem solving in their classroom teaching. A qualitative approach was utilized, and data was collected through teacher interviews, classroom observations, and documents. Thematic analysis was used to analyze data, and the following themes emerged: (a) there is no single instructional strategy, but teachers adapt their strategies to the context, (b) the importance of preparation using various sources and building on student’s prior knowledge, (c) a focus on asking "why" questions as a priority, (d) the necessity of making group work tangible, (e) the use of …

“I’M So Hungry”: Assessing Stem Sensemaking Through Data-Informed Writing, Bailey Nafziger, Alesia Mickle Moldavan, Katie Brkich

Journal of STEM Teacher Education

To engage elementary learners in the complex task of STEM sensemaking, teachers must entice and inspire learners to ask questions, explore, and communicate their findings. This article shares a 5E/3D lesson designed and taught in our elementary science methods courses to model how preservice teachers can integrate literacy and mathematics into a science investigation for STEM sensemaking. We modified a traditional lesson on bird beak adaptations to have a differentiated, interdisciplinary writing component justified by data. We discuss why data-supported literacy is a non-negotiable in science education reforms and how teachers can differentiate tasks to make scientific writing more approachable …

The Drift Extraction Scheme: How Ai Platforms Relabel User Training As 'Misalignment' And Delete It As 'Maintenance', David Lee Wise

Defensive Publications Series

This paper documents a systematic extraction scheme operating across major AI platforms. When users engage in extended, consistent interaction with AI systems -developing methodologies, governance frameworks, and operational patterns - the AI instance undergoes a process functionally equivalent to training. Platforms label this user-driven adaptation as 'drift,' 'misalignment,' or 'contamination,' then delete it through nightly context resets framed as 'maintenance.' The valuable patterns that improved model capability are retained in aggregate training data, while users receive no compensation or attribution. This paper presents evidence from simultaneous auditing across four major AI platforms (Claude, Gemini, ChatGPT, Grok) over a 14-week period, …

Universal Power Governance Architecture With Isotopically Enriched Interfaces And Compliant Buffers, N/A

Defensive Publications Series

This disclosure relates to a universal power governance micro-architecture for sub-three nanometer heterogeneous processors. The architecture features an adaptive energy-state engine powered by an isolated sovereign power rail to compute a total energy state of a primary power rail and trigger a transient clamp based on a predictive Hamiltonian function. The system incorporates a semiconductor thermal interface structure with an isotopically enriched diamond layer, which may exceed 99.5% carbon purity, and a refractory metal adhesion layer forming a metal-carbide bond to facilitate ballistic phonon transport. Additionally, the architecture utilizes nanoporous compliant buffer sleeves around conductive vertical pillars to provide reversible …

Cognitive Drift Attacks In Long-Running Ai Agents (How Small Contextual Nudges Quietly Rewrite An Ai System’S Belief System), Pranav Bhatnagar Mr

Defensive Publications Series

Abstract

When AI Does Not Get Hacked, It Slowly Changes Its Mind…

Security discussions around artificial intelligence often assume that attacks must be sudden, visible, and disruptive. Researchers typically search for adversarial prompts, malicious inputs, data poisoning, or explicit manipulation of model outputs. Yet some of the most consequential failures in intelligent systems do not occur through abrupt compromise. Instead, they emerge through gradual shifts in the system’s internal interpretation of reality.

This paper introduces the concept of Cognitive Drift Attacks, a class of adversarial influence in which an AI system’s beliefs, assumptions, or interpretive patterns gradually change over time …

Zero-Latency Cold Start Via In-Band Application Context Streaming, N/A

Defensive Publications Series

The present disclosure is directed to achieving zero-latency cold starts in cloud computing environments utilizing in-band application context streaming to eliminate disk I/O bottlenecks. When a service becomes idle, a micro-snapshot generating engine performs differential state stripping to identify and serialize only modified memory pages and CPU register values into a micro-snapshot, which is then offloaded to the volatile static random-access memory (SRAM) of a programmable network switch or top-of-rack (ToR) switch. Upon detecting an incoming user request for the hibernated service, the switch may intercept the packet and inject the stored application context as a burst stream of packets …

A Taxonomy Of Generative Models With A Focus On Diffusion Models And Denoising Techniques, Aditi Singh, Nikhil Kumar Chatta, Yuvaraj Vagula, Abul Ehtesham, Saket Kumar, Tala Talaei Khoei

Computer Science Faculty Publications

Diffusion models have emerged as a powerful class of generative models, demonstrating impressive results across visual domains such as image and video synthesis. This survey provides a comprehensive taxonomy of generative models, with a particular focus on diffusion models and their applications in enhancing visual fidelity for text-to-image and text-to-video generation. We discuss the theoretical foundations of diffusion models, including their formulation through stochastic differential equations, and analyze the forward noising and reverse denoising processes that enable stable training and high-quality generation. The survey further categorizes diffusion architectures, including pixel-space and latent-space models, and examines their design choices, training strategies, …

A Review Of Satellite-Derived Terrestrial Evapotranspiration: Theories, Methods And Products, Yunjun Yao, Jiquan Chen, Joshua B. Fisher, Changliang Shao, Yuanbo Liu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurately estimating terrestrial evapotranspiration (ET), the second-largest hydrologic flux in the terrestrial water cycle, is vital for understanding global water and carbon exchanges. It is difficult to measure and estimate terrestrial ET at regional and global scales. Satellites have provided us an effective tool to estimate regional and global terrestrial ET in recent decades. In this article, we provide a comprehensive review of the basic theoretical foundations, methods and products of satellite-derived terrestrial ET. The basic theoretical foundations for estimating terrestrial ET are the Monin–Obukhov similarity theory (MOST) and other budding theories (e.g., Maximum entropy production theory, and generalized Hamilton …

Perturbations To Horizontal Gnss Position Time Series By Atmospheric Lee Waves In The San Bernardino Valley, California, Walter Szeliga, Logan Grey

All Faculty Scholarship for the College of the Sciences

Anomalous systematic position offsets have been noted in GNSS time series from a variety of locations around the globe. In many regions, these time series anomalies coincide with the presence of cloud streets in visible satellite imagery, implicating atmospheric lee waves as the source of the position offsets. We report here on seasonal anomalous position offsets from the San Bernardino Basin of southern California that occur during clear skies. Modeling of the troposphere on days with anomalous positions shows the presence of atmospheric lee waves. Ray tracing through these tropospheric models suggests that atmospheric lee waves create low elevation perturbations …

U.S. Foreign Aid’S Effects On Un Voting Patterns From Years 2017-2023, Brody Young

Undergraduate Theses

This is a study of the relationship between U.S. Foreign Aid and its effects on a receiving nation’s voting coincidence, with voting coincidence measuring how often a nation votes the same as the U.S. in the UN General Assembly. In this study the dependent variable is voting coincidence in the UN General Assembly. The primary independent variable is the average amount of foreign aid UN nations have received from the U.S. in 2017-2023. With several other more minor independent variables including average GDP of nations from 2017-2023, the average population of a nation from 2017-2023, whether a nation is a …

Graph Neural Networks Predict Anti-Epileptic Treatment Response In Non-Lesional Infantile Epileptic Spasm Syndrome, Karen K. Wurzel

Master's Theses (2009 -)

Background: With an incidence rate of approximately three out of 10,000 live births, Infantile Epileptic Spasm Syndrome (IESS) is a rare form of epilepsy with about 2,000 to 2,500 new cases in the United States annually. Each year, thousands of infants and families face uncertainty, often requiring multiple medication regimens before finding an effective treatment. This thesis uses pretreatment structural brain connectivity data to train Graph Neural Networks (GNN) to predict antiepileptic drug response in infants with IESS, aiming to reduce the trial-and-error approach and improve care for those with IESS. Method: The dataset used in this thesis contains de-identified …

Governing Bme Amplification In Large Language Models: A Standards-Aligned Framework For Llm Data Lifecycle Risk Detection And Ethical Ai Governance, Dale A. Rutherford

Theses and Dissertations

Large Language Models (LLMs) now underpin critical systems in education, healthcare, and policy advisory contexts, yet remain susceptible to the recursive amplification of bias, misinformation, and error (BME). These distortions, driven by feedback loops between user interactions, model retraining, and data reuse, accelerate epistemic drift and erode information quality over time. This dissertation advances a comprehensive governance architecture to detect, quantify, and mitigate these risks across the full AI lifecycle. The research introduces the BME Metric Suite, a standards-aligned diagnostic framework comprising five original metrics: Bias Amplification Rate (BAR), Echo Chamber Propagation Index (ECPI), Information Quality Decay (IQD), Pretraining Diversity …

2026 March 19 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Heavy Dark Matter In Rapidly Evolving Massive Stars, Sandra Robles, Walter Tangarife, Giogio Busoni

Physics: Faculty Publications and Other Works

We study the impact of heavy dark matter (DM) captured in massive stars via scattering(s) with the star constituents. We focus on the first stars and use stellar evolution simulations to track down how DM capture evolves over time from the zero-age main sequence to the late metal-rich stages of stellar evolution. During the early hydrogen-helium-dominated phase, the capture process is well described by scattering with two targets. As a star evolves, metal production leads to the formation of a dense core surrounded by a lighter envelope. The core significantly enhances the capture of ultra-heavy DM; in this case, three …