Digital Commons Network^™

The Lumberjack, March 11, 2026

Cal Poly Humboldt's Student Newspaper

The student newspaper of Humboldt State University.

Efficient Energy-Stable Discontinuous Galerkin Schemefor The Non-Isothermal Cahn–Hilliard–Navier–Stokestwo-Phase Fluid Flow System, Guang-An Zou, Meiting Wang, Kejia Pan, Yin Yang, Xiaofeng Yang

Faculty Publications

In this article, we propose a novel numerical framework for the non-isothermal Cahn–Hilliard–Navier–Stokes two-phase flow system, which couples the incompressible Navier–Stokes equations, the Cahn–Hilliard phase-field equation, and the heat transport equation to capture temperature-dependent two-phase flow dynamics. The pro-posed scheme achieves three major advances: (i) unconditional energy stability through a combined scalar auxiliary variable (SAV) and zero-energy-contribution (ZEC) approach, (ii) linearity and full decoupling of all variables while using a second-order temporal discretization, and (iii) efficient implementation via discontinuous Galerkin (DG) spa-tial discretization together with a second-order projection method for the Navier–Stokes equations. We rigorously prove the unconditional energy stability …

100 Years In The Making: The Drive Initiative And A Reorganization Of The Department Of Energy And Natural Resources, Blake Canfield, Tyler Gray, Clay Parker

LSU Journal of Energy Law and Resources

No abstract provided.

Drilling Into Louisiana's Mineral Industry: The Significance Of The Fifth Circuit's Recent Decision Expanding The Application Of The Louisiana Oilfield Anti-Indemnity Act, Katherine Reese Kelso

LSU Journal of Energy Law and Resources

No abstract provided.

It's Getting Hot In Here: The Heated Debate On The Censorhip Of Climate Change Education And Its Violation Of State Constitutions, Lilyan Jarreau

LSU Journal of Energy Law and Resources

No abstract provided.

Ahoy, Matey! I'Ve Harnessed The Wind: Turning Ocean Air Into Renewable Wind Energy, Amber Ferguson

LSU Journal of Energy Law and Resources

No abstract provided.

Defining A Multi-Omic, Ai-Enabled Stool Screening Paradigm For Colorectal Cancer: A Consensus Framework For Clinical Translation, Arturo Loaiza-Bonilla, Yan Leyfman, Viviana Cortiana, Rhys Crawford, Shivani Modi

Einstein Health Papers

Colorectal cancer (CRC) develops through both conventional adenoma-carcinoma and serrated neoplasia pathways, yet noninvasive screening still under-detects the advanced precursor lesions that enable true cancer prevention. Stool-based screening reduces CRC mortality, but its preventive impact remains constrained by limited detection of advanced precancerous lesions (APLs), including advanced adenomas and sessile serrated lesions. Next-generation multitarget stool DNA assays (mt-sDNA; e.g., Cologuard Plus) have established high sensitivity for CRC and specificity approaching 94%, leaving improved APL detection as the principal opportunity for innovation. This review presents a consensus framework for a multi-omic stool screening paradigm that integrates host epigenetic markers (DNA methylation) …

Guido Bussinelli V. Township Of Mahwah

2026 Decisions

USDC for the District of New Jersey

Michael Kaplon V. Morris Township Police Department

2026 Decisions

USDC for the District of New Jersey

Spartan Daily, March 11, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 21

Ulk4 And Cdkn2a Polymorphisms Influence The Risk Of Developing Monoclonal Gammopathy Of Undetermined Significance, José Manuuel Sánchez-Maldonado, Angelica Macauda, Antonio José Cabrera-Serrano, Hauke Thomsen, Murat Güler, Rob Ter Horst, Bethany Van Guelpen, Pavel Vodicka, Stefano Landi, Subhayan Chattopadhyay, Pelin Ünal, Lucía Ruiz-Durán, Delphine Casabonne, Hartmut Goldschmidt, Istemi Serin, María Carretero-Fernández, Elena Cabezudo, Fernando Reyes-Zurita, Alyssa I. Clay-Gilmour, Et. Al.

Faculty Publications

Monoclonal gammopathy of undetermined significance (MGUS) is a necessary precursor condition to multiple myeloma (MM). Given the role of autophagy in modulating MM risk, we investigated whether genetic variation in autophagy-related genes influences susceptibility to MGUS. We analyzed the association of 34,042 common autophagy-related single nucleotide polymorphisms (SNPs) with MGUS across six independent cohorts, five from Europe and one from North America, comprising 2317 MGUS cases and 282,358 controls. We also assessed their impact on immune parameters, including absolute counts of 91 blood-derived immune cell subsets and 103 circulating immunological proteins. Meta-analysis revealed a genome-wide significant association between the ULK4 …

Meeting 2026-03-11, Civil Service Senate

Civil Service Senate Minutes

Minutes of the Civil Service Senate meeting.

Interlibrary Loan: From Basics To Current Issues, Jennifer K. Lloyd

Library Faculty Publications

While interlibrary loan has been a core service for health science libraries for decades, changes in policies, software, and workflow are accelerating. This webinar will explain some basics of ILL and its platforms while also focusing on current issues and changes that are confronting libraries.

Ocean Observing System Design: Transatlantic Acoustic Propagation For Acoustic Thermometry, Brian D. Dushaw, Dimitris Menemenlis, John A. Colosi

Faculty Research, Scholarly, and Creative Activity

Ocean acoustic thermometry is simulated in the North Atlantic using two global ocean state estimates to assess its potential contributions to the Global Ocean Observing System. Acoustic data were simulated for transatlantic acoustic propagation from Cabo Verde to Bermuda, a 4183-km archetypal path across the Mid-Atlantic Ridge. Acoustic scattering by internal waves was simulated using a range-dependent, stochastic model added to the ocean state estimates. While the Ridge blocks acoustic propagation traveling deeper than about 3000 m, and internal-wave sound speed scintillations cause prohibitive scattering of later-arriving rays, it is apparent that O(10) acoustic ray arrivals on this path are …

Perspectives On Choice Of Law Challenges In Multistate Precision Medicine Research, Laura M. Beskow, Catherine Hammack-Aviran, James W. Hazel, Leslie E. Wolf

Law Faculty Scholarship

This empirical legal study investigates challenges related to determining applicable law in multistate precision medicine research. Through interviews with experts in law, research ethics, and human subjects protections, the authors examine how differences in state laws governing research, genetic privacy, and data protection may affect participant rights and research practices. Interviewees reported varying levels of awareness regarding state law variation and expressed differing views on its significance. The findings suggest that uncertainty surrounding applicable legal frameworks can complicate research design, informed consent processes, and institutional oversight. The study calls for further legal and policy analysis to address these challenges and …

Rethinking Textbook Reading Checks: Designing Reflective Assignments With Ai, Sue A. Bauer, Ezekiel Walker Dr.

Teaching Online Pedagogical Repository

This strategy uses AI as a planning partner to help instructors design reading-based assignments that move beyond traditional quizzes by emphasizing analysis, interpretation, and reflection on textbook chapters. By providing AI with key themes and learning objectives, instructors can quickly generate structured prompts and rubrics that assess insight, use of evidence, and clarity of reasoning. The approach encourages deeper student engagement with readings while allowing instructors to customize and maintain oversight of the assignment and evaluation process.

Interfacial Chemistry Involved In Selective Separation Of Nmc/Lmo And Lco/Lmo Binary Cathode Materials By Froth Flotation Using Oleic Acid, Richard Kofi Oboh, Kaiwu Huang, Seoung Bum Son, Lei Pan

Michigan Tech Publications

The variability in cathode compositions within recycled lithium-ion battery (LIB) feedstocks poses a significant challenge to efficient downstream refining processes. This study demonstrates the feasibility of using froth flotation with oleic acid as a collector to selectively separate lithium nickel-manganese-cobalt oxide (NMC) and lithium cobalt oxide (LCO) from lithium manganese oxide (LMO) materials. Laboratory-scale flotation tests achieved an 80% separation efficiency in a single stage, producing a froth product with >90% purity of NMC/LCO at approximately 90% yield. Concurrently, the LMO materials were enriched in the sink product with ∼90% purity and ∼90% yield. This approach was further validated using …

Chv 690-738 Albany Avenue Lp. V. Kandil, Ali-Abdelqader

All Decisions

The undertenant, claiming domestic violence victim status and an informal marriage to the primary tenant in a Section 8 rent-stabilized unit, moved to dismiss a holdover proceeding, citing improper VAWA and CARES Act notices. The court denied the motion, ruling the undertenant lacked standing to assert VAWA defenses due to failure to establish a colorable claim to succession rights. The court further held that VAWA protections apply only to applicants and tenants, not occupants, and the CARES Act’s 30-day notice provision is for nonpayment, not holdover, proceedings. The undertenant was granted leave to file an answer.

Understanding Math-Anxious Teachers' Stories Of Comfort, Competence, And Confidence With Learning And Teaching Mathematics, Deborah Peart Crayton

USF Tampa Graduate Theses and Dissertations

Math anxiety is a complex issue that affects students and teachers. It has been researched for decades, but the focus has often been on addressing math anxiety in students, while finding solutions to support elementary teachers experiencing math anxiety has been overlooked. This study fills a gap in existing research by shedding light on math anxiety in elementary education and highlighting ways to address it by leveraging existing structures that support professional development. This qualitative narrative inquiry explores the experiences of four elementary educators who identify as math-anxious and how they report that math anxiety impacts their confidence in teaching …

Analysis Of The Yeast Surface Display Platform As A Tool For Tyrosine Kinase Phosphorylation Assays, Alexandra Maritza Tang

USF Tampa Graduate Theses and Dissertations

Developing and optimizing platforms to study complex protein-protein interactions is important to maintain fidelity of the modeled activity. Yeast surface display has been used as a high-throughput platform to model substrate phosphorylation by tyrosine kinases, a key enzymatic process that is essential for most cell signaling pathways. However, existing characteristics of the yeast surface display platform limit the ease-of-use, reproducibility, and feasibility of screening enzymatic modification processes like tyrosine phosphorylation. The cytoplasmic domain of T cell costimulatory receptor CD28 and lymphocyte kinase (LCK) were used as a model enzyme-substrate pair to showcase molecular cloning issues that can hinder reproducibility and …

Interview No. 1840, Norma Flores

Combined Interviews

This interview with El Pasoan Norma Flores reflects on her childhood growing up in Segundo Barrio and the strong family and community ties that shaped her life. Born in 1949 at Newark Methodist Maternity Hospital in South El Paso, she described growing up primarily with her grandmother on Grama St while her parents and siblings lived nearby on Frutas St. Norma shared vivid memories of her neighborhood life, including children playing outside together, helping with household chores and walking to school at Guardian Angel Catholic School. She recalled both joyful and difficult moments, such as spending summers outdoors with family …

Molecular Quantum Particle Algorithm (Mqpa): Hybrid Quantum-Classical Learning For Molecular Property Prediction, Jessica Mcphaul, Bivin Sadler Ph.D.

SMU Data Science Review

Classical machine learning models and quantum kernel methods often struggle to capture quantum-coherent molecular features under the constraints of noisy intermediate-scale quantum (NISQ) hardware, limiting both predictive accuracy and scalability.

This paper introduces the Molecular Quantum Particle Algorithm (MQPA), a hybrid quantum–classical framework designed to achieve chemically accurate property prediction by integrating handcrafted molecular descriptors with parameterized quantum circuits. Molecular inputs, expressed as SMILES strings, are processed via RDKit and encoded through angle-based quantum gates with entangling layers in Qiskit [1]. Quantum parameters are optimized using simultaneous perturbation stochastic approximation (SPSA) [2], while classical regression layers leverage Adam [3] …

Predicting House Prices Using Machine Learning, Pejal Rath, Robert Slater

SMU Data Science Review

This study explores the use of Machine Learning methods to predict housing prices, a problem of significant interest in real estate economics, and data science. Traditional hedonic pricing models have long been used to evaluate the impact of housing attributes on property values, but they often lack the flexibility to capture nonlinear relationships and complex feature interactions. Recent advancements in regression based and Machine Learning approaches provide promising alternatives that may improve prediction of accuracy and market insights. This research will investigate how models such as linear regression, random forest, and gradient boosting can be applied to publicly available housing …

Ai-Powered Reporting For Improved Hospital Efficiency, Joel C. Laskow, Chris Papesh, Srishti Awasthi, Jacquelyn Cheun

SMU Data Science Review

This study explores the feasibility of an AI-powered chatbot for HIPAA-aligned intake of emergency room patients seeking treatment for overdose and violence. The system utilizes AWS Amplify, an encrypted EC2 instance, and a secure S3 Bucket house on Amazon Web Services. Chat functionality is powered by a multi-agentic framework operating on Anthropic’s Claude Sonnet 4. Manual evaluation and exact match testing reveal the system reliably obtains and records relevant information during intake. Future work will focus on expanding accessibility by integrating voice functionality, obtaining HIPAA compliance certifications, and incorporating the chat system into existing healthcare networks.

Bias Evaluation Of Healthcare Data With The Use Of Vbqa - A Vaers Inspired Bias Question Answer Dataset, Nolan Dulude, Renu Karthikeyan, Bivin Sadler, Faizan Javed

SMU Data Science Review

Abstract. Large Language Models (LLMs) are being used increasingly within the healthcare industry to summarize complex clinical information, but their outputs can often reflect biases inherited from their training data. In healthcare, these biases are not just technical flaws, but they can lead to distorted and false information about vaccine safety, compromise patient trust, and lead to potential harmful outcomes. This study investigates bias found in LLM-generated outputs to question-answer pairs inspired by adverse vaccine reactions using COVID-19 data from the Vaccine Adverse Event Reporting System (VAERS) from 2020–2024. We examined whether training the LLMs on a known Bias Benchmark …

Nlp Bias And African American English, Kenya Roy, Faizan Javed

SMU Data Science Review

African American English (AAE), also referred to as African American Vernacular English (AAVE), is widely used on social media, but most sentiment analysis tools are trained only on Standard American English (SAE). This mismatch can cause models to misclassify dialectal expressions—especially by labeling neutral or positive AAE as negative or toxic. These errors matter, since Natural Language Processing (NLP) systems are now central to content moderation and brand monitoring. This research will evaluate the VADER, RoBERTa, GPT-OSS, and Gemma’s handling of AAE in comparison to SAE using the TwitterAAE corpus, a public dataset of tweets with estimated AAVE usage. The …

Automating Cardiff Model Data Capture In Emergency Departments: Ambient Nlp Integration With Oracle-Cerner Fhir Systems, Simi Augustine, Marco A. Lopez, Jacquelyn Cheun, Chris Papesh

SMU Data Science Review

Violence and overdose events in Las Vegas occur at rates above the national average, with fewer than half of violent injuries reported to law enforcement [2,7]. The Cardiff Model offers a proven framework for standardized data collection and sharing between hospitals and public safety partners, yet many implementations still rely on manual entry. We propose an ambient triage pipeline integrated with Oracle-Cerner electronic health record systems to listen to nurse–patient dialogue, convert speech to text, extract Cardiff fields, and write standards-based FHIR Bundles for analytics. Using SMART on FHIR standards and Cerner Millennium APIs, the study evaluates whether ambient capture …

Virtual Ai Lifestyle Assistant, Solomon T. Mathew, Babu T. Mathew

SMU Data Science Review

Patients struggle with adhering to prescribed medication and leading a healthy lifestyle outside of clinical visits. A mechanism needs to be developed and deployed to constantly remind them about the need to take medication and to lead a healthy lifestyle in a non-intrusive way while watching for changes in vitals that can be collected using wearable devices. With these considerations, a Virtual Healthcare Assistant is proposed, built with a multi-agent system that is easily integrated with wearable devices such as Apple Watches, Fitbits, and Oura Rings. a LangGraph-based multi-agent workflow to mimic real-world continuous monitoring. The resulting system enables agent-to-agent …

Anomaly Detection For Multi-System Bug Triage, Gibran Miguel Zavala Gamero, Hayoung Cheon, Mustafa Iqbal

SMU Data Science Review

Large-scale software systems produce vast volumes of logs and telemetry, making manual incident triage slow and error prone. This study presents an unsupervised anomaly detection pipeline that fuses logs, metrics, and traces through late fusion. Using Hybrid Ensemble modeling with Isolation Forest, and Long Short-Term Memory (LSTM) Deep Learning model, the system detects cross-service anomalies producing and assigning a composite triage score reflecting severity and impact. Ranked alerts are categorized into Critical, High, or Medium priorities for review. A retrieval-augmented generation (RAG) layer enriches results with contextual summaries for explainable triage. Evaluated on synthetic multi-service datasets, the pipeline …

A Modular Framework For Cost-Efficient Aspect-Based Sentiment Analysis Using Small Language Models, Senthil Kumar, Nibhrat Lohia

SMU Data Science Review

Aspect-based sentiment analysis (ABSA) links opinions in text to specific product attributes (for example, battery life, screen quality, or delivery speed) rather than only assigning an overall star rating. This level of detail is important in domains such as e-commerce, where teams need to know which features customers praised and which they criticized. Traditional ABSA pipelines have relied on large language models (LLMs), which achieved high quality but were expensive to run and difficult to scale. This study evaluated whether small language models (SLMs) in the 1–3 billion parameter range could serve as a lower-cost alternative. We implemented a modular …