Digital Commons Network^™

Re: Comment Letter For Bpsou Blacktail Creek Riparian Actions Uniform Federal Policy Quality Assurance Project Plan Addendum (Dated April 24, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: 1st Quarter 2026 – Interim Site-Wide Surface Water Monitoring Data Report Silver Bow Creek Butte Area Npl Site, Butte Priority Soils Operable Unit Consent Decree-Civil Action No. Cv 89-039-Bu-She, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Faith And Technology Resource Hub: Building The Christian Engineer’S Bookshelf, Gayle Ermer, Derek Schuurman

University Faculty Publications and Creative Works

A wealth of material related to the interactions between faith and technology has been generated over time to help Christian engineers reflect on and evaluate their work and technology development more generally. However, there is currently no central location where this large variety of resources can easily be accessed. This paper will describe the process of developing a faith and technology resource hub. The vision for the hub is that it will include a comprehensive searchable directory of resources addressing faith and technology, as well as a browsable, organized, curated, and annotated set of webpages containing links to particularly important …

Silver Bow Creek Conservation Area Approved Final Principles For A Greener Cleanup Report, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

An Ai-Integrated Methodology For Secure Software And System Development, Ian Matthew Campbell Coston

Electronic Theses and Dissertations 2020 - Present

Securing interconnected software systems requires more than layering existing frameworks on top of each other. Most current Secure Software and System Development Lifecycle (S-SDLC) models treat security as a phase rather than a design condition, leaving real gaps in governance, access control, and automated enforcement that become critical failure points in Internet of Things (IoT) environments where devices are resource-constrained, long-lived, and frequently insecure by default.

This dissertation introduces the Automated Zero Trust Risk Management with DevSecOps Integration (AZTRM-D) methodology, a novel approach that unifies DevSecOps automation, the National Institute of Standards and Technology (NIST) Risk Management Framework (RMF), and …

Evaluating Soil Health And Crop Yield In Louisiana Agricultural Systems: Impacts Of Best Management Practices And Prediction Models, Hector J. Mendoza Lagos

LSU Doctoral Dissertations

The adoption of conservation management practices is critical for improving soil health, enhancing nutrient use efficiency, and sustaining crop productivity in row crop systems in Louisiana. This study evaluated the role of conservation agronomic practices, soil biochemical indicators, and machine learning predictive models to improve soil nutrient dynamics, soil health indicators, microbial communities (MC), and crop productivity on a corn (Zea mays L.) research plot scale and in a commercial forty-hectare cotton (Gassypium hirsutum L.)-corn-soybean (Glycine max L.) rotation system in northeast Louisiana. The objectives of the study were to evaluate soil nutrient dynamics and MCs under …

Long Panel Studies Of Small-Scale Rural Societies In The Global South: What Is Their Value, Why Are They Rare, And Suggestions To Make Them Happen, Jonathan Bauchet, Ricardo Godoy, William R. Leonard, Victoria Reyes-Garcia, Asher Y. Rosinger, Susan Tanner, Eduardo A. Undurraga

Department of Agricultural Economics Faculty Publications

Many topics in the behavioral sciences and epidemiology require researchers to directly observe entities (e.g., individuals, households) over a long time to identify lasting effects. Long-term panel data collection is more common in high-income countries than in small-scale rural societies (SSRS) of low-income countries. SSRS are mobile, nature-dependent, linguistic minorities, and highly autarkic. Analyzing such data using a life-course perspective can help uncover patterns that align or upend what we know from high-income countries. This study a) reviews long (>∼10 year) panels in SSRS (n = 9), b) extends the analysis to cover somewhat comparable societies of smallholders (n …

Theorizing Rural Cosmopolitanism: Modern Economic History, Urban Elites, And The Political Economy Of Disaster Recovery, Manuel Montoya

Natural Resources Journal

A heavily understated dimension of cosmopolitanism is the urban rural divide. This is particularly true in the context of modern economics, which emerged at the same time that the notion of cosmopolitanism was gaining renewed political significance. This paper examines how economic thought of the late eighteenth and early nineteenth centuries directly influenced the socio-literary interactions of a “World Republic of Letters” and how writers such as Goethe used terms like “universal spiritual commerce” to valorize the role of the city in the making of a new modern world. The paper also describes how the rural was left behind in …

Front Matter, Natural Resources Journal Nrj

Natural Resources Journal

No abstract provided.

Measuring Stock Market Inefficiency Using A Multilayer Composite Efficiency Index: A Case Of The Egyptian Exchange, Patrick K. Owido, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Financial markets play a critical role in resource allocation. Their performance depends on the decisions of millions of independent investors constantly reacting to one another. Their informational efficiency remains a subject of debate across economic systems. When informational efficiency is present at the weak form, historical price information should not consistently predict future returns. Several empirical tests of this hypothesis often focus on the behavior of aggregate market indices, and use individual efficiency proxies such as autocorrelation, GARCH-type volatility, or entropy-based measures to measure efficiency. This has often yielded mixed results, particularly in emerging markets. Here we show that testing …

Host Range And Characterization Of Phytophthora Species That Cause Plant Diseases In California, Dinh Hieu Pham

Natural Sciences and Mathematics | Biological Sciences Master's Theses

Phytophthora is one of the most destructive genera of plant pathogens in California, posing significant threats to both nursery production and natural ecosystems. Phytophthora ramorum, the causal agent of Sudden Oak Death (SOD), has expanded its host range to include more than 100 plant species. In addition, Phytophthora elongata, previously isolated in Western Australia from Eucalyptus marginata in 2013, has recently been detected for the first time in the United States on Rhododendron species. This naturally raises concern that a new etiological species has entered the country. Therefore, the goal of this thesis study was three-fold:  i) to …

Hepatoprotective Evaluation Of Benzoylated Emodin Derivatives: Integrating Bioinformatics And In Vitro Studies, Firdayani Firdayani, Putri Hawa Syaifie, Siska Andrina Kusumastuti, Muthia Rahayu Iresha, Wirawan Adikusuma, Dhecella Winy Cintya Ningrum, Etik Mardliyati, Ayu Masyita, Ariza Yandwiputra Besari, Fathir Azzaki Iradata, Lucy Arianie

BioMedicine

Background: Emodin exhibits various pharmacological activities, including hepatoprotective effects. However, its clinical application is limited by poor absorption and low oral bioavailability. This study aimed to optimize emodin through benzoylation and to assess the hepatoprotective potential of the resulting derivatives integrating bioinformatics and in vitro methods.

Methods: We conducted network pharmacology, molecular docking and molecular dynamics (MD) simulations to predict potential targets and interactions of benzoylated emodin derivatives. The derivatives were synthesized and evaluated for cytotoxicity using the MTT assay. The hepatoprotective effects were assessed in vitro using a paracetamol-induced HepG2 cell injury model.

Results: Network pharmacology analysis and gene …

Algorithm Development For Vehicle Detection And Counting With Application Of Opencv, Olajide M. Babatunde, Alase A. Daniel, Obi E. Nnamdi, Kuponiyi S. David, Aina O. Adeola

Al-Bahir

Accurate vehicle detection and counting play a crucial role in traffic monitoring, intelligent transportation systems, and urban planning. This study presents an algorithm for vehicle detection and counting using OpenCV, leveraging image processing and computer vision techniques. The proposed method incorporates background subtraction, contour detection, and object tracking to accurately identify and count vehicles in real-time video streams. The algorithm is tested on various traffic scenarios to evaluate its efficiency and accuracy. Experimental results demonstrate the effectiveness of the approach. The developed system provides a cost-effective and scalable solution for automated traffic analysis, offering potential applications in traffic management, congestion …

High-Throughput Robotic Ethanol Inhibition Assays For Engineered Thermophilic Biofuel Strains, Kevin He, Daniel Olson, Marybeth Maloney, Anthony Lanahan

Wetterhahn Science Symposium Posters

Ethanol stress assays are commonly used to evaluate microbial tolerance, metabolic adaptation, and fermentation performance. However, manual liquid handling introduces variability across replicate wells and small-volume pipetting steps, limiting reproducibility and throughput. This study developed an automated OT-2 robotic workflow to generate replicated ethanol concentration gradients for high-throughput inhibition assays in engineered thermophilic biofuel strains. Kinetic plate-reader measurements were used to quantify ethanol-dependent growth responses under anaerobic fermentation conditions. The reasearch question is: How do engineered thermophilic biofuel strains differ in ethanol-dependent growth inhibition under anaerobic fermentation conditions, and can automated robotic assays improve the reproducibility of these measurements? Can …

The Constitutional Dimension Of Ai: A Phenomenology Of Cybernetic Power, Andrea Simoncini

Maryland Law Review Online

No abstract provided.

Ai-Infused Writing-Intensive Problems For Introduction To Programming In C++, Esma Yildirim

Open Educational Resources

This exercise book uses Writing-Intensive (WI) pedagogy in an introductory programming course setting, because I believe WI can help students engage in deeper analysis of programming problems while strengthening their critical and analytical thinking skills. In computer science, a single problem can often be solved using multiple algorithms, designs, and implementation strategies. Exploratory thinking and reflective writing can improve students’ ability not only to read and write computer programs, but also to evaluate the efficiency, readability, and maintainability of algorithms and code. Students must learn not only how to design solutions, but also how to compare alternatives and determine the …

Academic Senate - Minutes, 05/26/2026, Academic Senate

Academic Senate Minutes

No abstract provided.

Short Peptoid Capping Ligands Stabilize Dispersion Of Gold Nanospheres In Aqueous Solutions, Hanna G. Goldberg, Isabella K. Matusich, Jack M. Petersen, Nikhila Raman, Joseph C. Hong, Gabriela Edler, Daniel K. Tanaka, Jwwad M. Javed, Amelia A. Fuller

Chemistry and Biochemistry

Surface functionalization of colloidal gold nanoparticles with capping ligands is critical for controlling their dispersive stability and for introducing application-specific moieties. Peptoids (N-substituted glycine oligomers) are useful candidates for study as capping ligands owing to their straightforward preparation and their biocompatibility. In this work, we have prepared a library of five-residue peptoids and evaluated them as capping ligands for 10 nm gold nanospheres. Our findings revealed important sequence features of peptoids that stabilize nanosphere colloidal dispersions in a range of aqueous conditions that vary in ionic strength and pH. We have also characterized the sizes and surface charges of peptoid-capped …

Rethinking Functional Groupings In Basketball Wings Through Ecological Trait Frameworks, Dhruv Mehrotra

Theses and Dissertations

This paper starts with a review about Plant Functional Types and then goes deeper into the conceptual foundations of Plant Functional Types (PFT's) with detailed discussion of global trait spectra such as the leaf economics spectrum and the fast-slow continuum. Using concepts like response and effect traits, the review then talks about how a trait based ecological framework can provide a more robust guideline to classify plants. The review then talks about how players in basketball have been classified in the past along with some of the newer typologies. The review starts to draw some parallels between the ecological framework …

Cross-Scale Feature Learning For Alzheimer's Disease Detection Via Hybrid Deep Networks, Essam Haidar Majeed, Fallah H. Najjar, Safaa M. Kareem, Munaf H. Kareem, Duha Amer Mahdi

Baghdad Science Journal

Alzheimer's disease (AD) is a chronic neurodegenerative disorder that is the leading causeof dementia. Early diagnosis is essential for interepting the progressionof cognitive decline and favoring the clinical outcome, although conventional diagnostic means may not be able to identify early symptomatic forms. In this manuscript, we propose a residual attention-based hybrid deep learning model withthe EfficientNetB1 backbone for improving the classification of AD based on structural MRI data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and ADNI1 datasets. The network structure integrates two-dimensional (2D) convolutional feature extraction, multi-head self-attention for building the global context information, and residual learning. The …

Predicting Future Stock Closing Prices: A Five-Stage Approach Utilizing Historical Data And Enhanced Deep Learning Techniques With Multi-Strategies Improved Beluga Whale Optimization, D. Murahari Reddy, R. Balamanigandan

Baghdad Science Journal

Predicting stock market movements is a complex and challenging task due to many factors that can influence stock prices. While there are various approaches and techniques that researchers and analysts have explored, it's crucial to note that accurately forecasting stock prices consistently is complicated. Financial data can be noisy and subject to errors. Minor inaccuracies in data can lead to inaccurate predictions. In this research, we propose a new deep learning technique with an optimization algorithm to overcome the limitations in stock market prediction. This research has five stages to predict closing prices using historical data. The input data is …

Enhanced Population Mean Estimation Using An Exponential Estimator With Known Medians Of Dual Auxiliary Variables Within A Neutrosophic Approach: Applications In Agricultural Yield Prediction, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistical theory, estimation of population parameters is generally carried out under the assumption that all observed data are precise, complete, and free from ambiguity. However, in many practical and real-world situations, data often deviate from these ideal conditions and instead appear in vague, uncertain, or interval-valued forms. Such imperfections reduce the effectiveness of traditional estimation techniques and motivate the development of more flexible and robust methodologies. To address these challenges, several improved estimators, particularly neutrosophic ratio-type estimators and their advanced extensions, have been proposed in recent literature. In this study, a new estimator known as the two auxiliary …

Bottem Realty, Llc V. Yaa

All Decisions

The Civil Court denied the tenant's motion for discovery in a nonpayment proceeding where the tenant raised a rent overcharge defense. The tenancy commenced in 1992 and rent history included multiple unexplained increases exceeding legally permitted amounts. The court distinguished Harvey and Syllman, holding that reliance on those post-HSTPA cases was misplaced because the tenancy predated HSTPA, and declined to extend the fraud exemption to pre-HSTPA tenancies absent a fraud claim.

Oregon State Rank Assessment For Straggling Gilia (Allophyllum Gilioides), Lindsey K. Wise

Institute for Natural Resources Publications

Oregon state conservation status assessment for Straggling gilia (Allophyllum gilioides) using NatureServe methodology, 2026.

Wake-On-Anomaly Federated Architecture For Privacy-Preserving Poultry Health Early Warning, Mahmoud Aziz Louati

Masters Theses

Highly pathogenic avian influenza outbreaks, respiratory disease, heat stress, and silent equipment failures share one operational reality: they are detected too late because today’s poultry-health workflow is reactive, manual, and dependent on producers volunteering commercially sensitive data. This thesis presents a wake-on-anomaly federated architecture that addresses both the detection-latency problem and the privacy–adoption deadlock that has so far prevented cross-farm collaboration. The architecture is organized in two tiers. Tier 1 is a lightweight LSTM autoencoder that continuously screens four routine telemetry channels (water, feed, house temperature, activity proxy) and emits a per-window reconstruction-error score. A debounced k-of-m trigger with cooldown …

Academic Senate - Agenda, 05/26/2026, Academic Senate

Academic Senate Agendas

No abstract provided.

As-1013-26 Resolution On Revised Academic Assessment Council Membership, Academic Assessment Council

Academic Senate Resolutions

Resolves that the Academic Senate of Cal Poly endorses the attached proposal to adjust the membership of the Academic Assessment Council; and further resolves that this revised AAC membership be put into effect beginning with the 2026-27 academic year.

A Govsecops-Oriented Governance, Risk, And Compliance Platform For Continuous Authorization In Dod Il4/Il5 Environments, Anand Janjal

Journal of Cybersecurity Education, Research and Practice

Department of Defense (DoD) Impact Level 4 and Impact Level 5 (IL4/IL5) systems require continuous assurance of cybersecurity posture under stringent operational and regulatory constraints. While the NIST Risk Management Framework (RMF) and DoD DevSecOps guidance emphasize continuous authorization supported by real-time evidence, many existing Governance, Risk, and Compliance (GRC) platforms remain documentation-centric and insufficiently integrated with operational telemetry. This paper presents a GovSecOps-oriented GRC architecture that integrates vulnerability ingestion, automated Plan of Action and Milestones (POA&M) lifecycle management, dynamic risk scoring, and continuous authorization dashboards within IL4/IL5 environments. Using a Design Science Research methodology, the study develops and evaluates …

Reinforcement Threshold Controlled Modernn Tuned With J* And QMax Bilingual Spatiotemporal Attention Fusion For Inclusive Real-Time Sign Language Interpretation, Harapriya Kar, P Viswanathan

Baghdad Science Journal

Deaf communities still struggle with communication, partly due to the inefficiency of current sign language recognition systems, their poor generalization, and their inability to manage regional and linguistictions. This work suggests a novel architecture that blends attention-based spatiotemporal processing (RTC-ModeRNN-BSF) with a reinforcement threshold–controlled ModeRNN to solve these problems. The model adapts its computation based on the complexity of the input gesture, using between 2 and 8 attention slots, while gradually reducing exploration during training ($\varepsilon$: 0.9→ 0.1). Dual-stream memory pathways are optimized using joint log-likelihood maximization (J-Star) and computational pruning (Q-Max) to capture both immediate sequential patterns (C_{t …}

A Novel Ffueat Technique Enhancing The Performance Of Multiple Url Classification And Cybersecurity Using Rnn And Transformer-Based Models, Zafar Ali, Siti Sophiayati Yuhaniz, Noureen Noureen, Ghulam Mujtaba, Husham M. Ahmed

Baghdad Science Journal

Thousands of new websites are published every day, which pose significant challenges for web classification and cybersecurity. URL classification datasets, including general and cybersecurity-specific ones, face challenges such as class imbalance, noise, and ambiguous data, which can significantly affect model performance. This study proposes a novel Fine-Tuned FastText Unsupervised Embedding Augmentation Technique (FFUEAT). Datasets (DMOZ and Phishing) were used to evaluate the performance of the proposed technique, achieving F1-scores of 0.8639 with DistilBERT and 0.8891 with BERT. The performance of sparse minority classes, achieving accuracy increases of 20.88% for 'home', 58.04% for 'news', and 11.18% for the 'kids' categories of …