Digital Commons Network^™

Understanding Statutory Corporate Tax Rates And Corporate Tax Revenue: Evidence From Oecd Countries, 2015–2023, Carter Johnson

Celebrating Scholarship and Creativity Day (2018-)

This paper analyzes the relationship between statutory corporate tax rates and corporate tax revenues among the OECD countries from 2015-2023. Since the 1980’s, statutory corporate tax rates have been gradually declining, however, the relationship between rate and revenue remains unclear. The Laffer Curve helps motivate the relationship between rate and revenue within the theoretical model. Foreign Direct Investment (FDI) and Real GDP are included as control variables, along with incorporating inflation and per capita measurements. The fixed effects panel regression findings conclude there is no direct relationship between corporate tax rate and revenue. However, FDI and Real GDP were found …

Minutes From The April 30, 2026 Meeting Of The University Of Montana Faculty, University Of Montana--Missoula. Faculty

University of Montana Faculty Senate Meeting Minutes

Meeting minutes from the April 30, 2026 meeting of the University of Montana faculty.

Apparent Hack’S Law In River Deltas, Tian Y. Dong, Lawrence Vulis, Hongbo Ma, Alejandro Tejedor, Timothy A. Goudge

School of Earth, Environmental, & Marine Sciences Faculty Publications

River deltas are densely populated, ecologically vital landscapes threatened by rising sea levels. Distributary channel networks disperse sediment to build deltaic land, yet the relationship between the network organization and land building remains elusive. Inspired by Hack’s law, which shows that watershed drainage area scales with channel length in tributary networks, we analyzed a global dataset of distributary networks and found a nearly identical scaling relationship between distributary channel length and nourishment area, the land-building counterpart to drainage area. Despite this apparent global scaling, we further identified two distinct local land-building patterns: uniform delta networks consistently follow Hack’s law, whereas …

A Comparative Study Of Traditional Training And Xr-Based Simulation In Healthcare Professional Education, Fazal Qudus Khan, Gohar Khan, Ibrar Ahmad, Owais Khan, Suleman Shah

All Works

Immersive Virtual Reality or VR/VX stands poised to revolutionize healthcare education through interactive learning modules, overcoming current deficiencies in existing methodologies for instruction. This research compared the effectiveness of VR/VX-based training to traditional CT scanner operator training using a within-subjects design, involving 30 subjects, and concluded the effectiveness of using VR/VX in enhancing knowledge retention, task accomplishment, and engagement, and proved it by showing significant enhancement in immediate knowledge acquisition scores (Δ = 8.87, t(29) = 6.71, p < .0001), relative to delayed knowledge retention scores (Δ = 11.03, t(29) = 6.85, p < .0001), procedural achievement scores (Δ = 5.40, t(29) = 4.45, p = .0001), reduced overall task completion time using VR/VX for increased speed of execution (t(29) = 10.74, p < .0001), as well as reduced task errors for lower error rates using VR/VX in comparison to existing methodologies, as testified by the results, t(29) = 8.14, p < .0001, respectively, while showing no significant difference in usability, although assessed superior in terms of engagement and relative usefulness by the involved subjects.

Research Remix: Teams, Tech, And Texts, Jaime Carbajal

UNLV Best Teaching Practices Expo

The pedagogical innovation that enhanced student learning in the Research Methodologies in Health Sciences course is described as Integrated Digital Collaborative Inquiry-Based Learning (IDCIBL). The IDCIBL approach leveraged digital tools (lecture videos, podcasts, recorded poster presentations, and Artificial Intelligence (AI) platforms), integrated journal article analysis, utilized research-informed active learning, and included team-based learning activities. The combination of multiple innovative strategies into the IDCIBL model intentionally transforms the educational environment and optimizes the student learning experience, relating to the TLC priority area of teaching and assessments in the age of Gen AI.

Ai Literacy: An Annotated Oer Bibliography, Houy Yvonne

UNLV Best Teaching Practices Expo

"Scalable, discipline-agnostic AI literacy instruction can be implemented incrementally without requiring full course redesign in higher education, supporting both technical understanding and critical engagement with the social and ethical dimensions of AI: The curated list of open educational resources (OER) on this poster enable a flexible, modular approach to teaching foundational AI literacy. The annotated list includes self-paced, hands-on projects with complementary educator-guided activities and discussion to support conceptual understanding of machine learning, training data, and algorithmic bias, drawing on OER such as Code.org’s AI curriculum, MIT RAISE’s Day of AI, and the multi-lingual Elements of AI course. Many resources …

Artificial Intelligence In Primary School Writing Instruction: A Bibliometric Analysis Of Global Research Trends (2016–2026), Nurul Umrotullatifah, Rina Heryani, Angga Hadiapurwa

Jurnal Pendidikan dan Pembelajaran

Background: The rapid integration of artificial intelligence (AI) into primary education has generated substantial scholarly interest, yet no comprehensive bibliometric study has systematically mapped the intersection of AI and writing instruction at the primary school level. Objective: This study aims to analyze global research trends, identify key contributors and collaboration patterns, and uncover dominant thematic clusters within this domain over the period 2016–2026. Method: A bibliometric research design was employed, drawing on a corpus of 2,277 documents retrieved from the Scopus database in April 2026, filtered to include only English-language journal articles. Data visualization and network mapping were conducted using …

Artificial Intelligence In Education: Readiness, Perceptions, And Implementation In An Early Childhood Teacher Education Program At Universitas Mataram, Fahruddin Fahruddin, Mansur Hakim, Hasanuddin Chaer, Lale Dewi Nurlita Safitri

Jurnal Pendidikan dan Pembelajaran

Background: Early Childhood Teacher Education Program (PGPAUD) requires complex pedagogical translation of content into concrete learning experiences. In this context, Artificial Intelligence (AI) has the potential to support prospective teachers in developing personalized learning media, generating age-appropriate instructional content, and simulating interactive environments aligned with children’s cognitive and socio-emotional development. Objective: This study aims to examine the readiness, perceptions, and implementation of AI in learning activities within the PGPAUD program, Faculty of Teacher Training and Education, Universitas Mataram. Method: This research employed a descriptive qualitative approach. The participants consisted of lecturers and students of the PGPAUD program. Data were collected …

Research Evolution Of Artificial Intelligence In Mathematics Learning: A Bibliometric Review From 2015 To 2026, Nadya Syifa Utami, Hafsah Adha Diana, Verra Budhi Lestari, Sani Sahara

Jurnal Pendidikan dan Pembelajaran

Background: The recent growth of Artificial Intelligence (AI) has attracted increasing attention in mathematics learning research, yet a comprehensive understanding of its development remains limited. Objective: This study aims to explore the research evolution of AI in mathematics learning from 2015 to 2026 using a bibliometric approach. Method: Data were collected from the Scopus database, yielding 169 publications comprising journal articles and conference papers. Analysis was conducted using Bibliometrix and VOSviewer to examine publication trends, leading sources, contributing countries, influential references, keyword cooccurrence, and thematic evolution. Results: The findings reveal a significant growth in publications, particularly after 2021, reflecting expanding …

An Improved Logarithmic Ratio-Product Type Estimator For Mean Modeling And Estimation Under Neutrosophic Uncertainty, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistics, population mean estimation generally assumes precise and determinate data along with known auxiliary information. However, in real-world situations where observations are imprecise or expressed in interval form, such as temperature variations or financial market data, classical approaches become less effective. To address this limitation, neutrosophic statistics provide a more flexible framework for handling uncertainty and indeterminacy. This study proposes a neutrosophic logarithmic ratio-product type estimator for estimating the finite population mean using auxiliary information. The bias and mean squared error (MSE) of the proposed estimator are derived using a first-order approximation. Furthermore, performance evaluation is carried out …

Warming Climate Amplifies Vapor Pressure Deficit Limits On Gross Primary Productivity, Shiqin Xu, Nate G. Mcdowell, Tim R. Mcvicar, Diego G. Miralles, Stephen Sitch, Pablo Sanchez-Martinez, Joshua B. Fisher, Pierre Friedlingstein, Hylke E. Beck, Matthew F. Mccabe

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ongoing climate warming may profoundly impact terrestrial gross primary productivity (GPP), a key component of the global carbon cycle. However, uncertainty in the relative roles of atmospheric water demand (vapor pressure deficit, VPD) and root-zone soil moisture (SM) limits predictions of drought impacts on GPP. Here, we show that growing-season GPP was more strongly constrained by VPD than SM globally, based on observation-constrained model estimates, satellite retrievals and Dynamic Global Vegetation Model simulations. The importance of VPD increased with higher temperatures and more severe and prolonged droughts. This pattern reflects VPD’s critical role in regulating stomatal conductance and plant hydraulic …

Learning With Ai: A Structured Approach To Student-Ai Collaboration, April Ursula Fox

UNLV Best Teaching Practices Expo

The rapid integration of generative artificial intelligence (AI) into higher education has created an urgent need for instructional models that move beyond tool use toward intentional, pedagogically grounded practice. This study presents a structured assignment design that positions AI as a scaffolded collaborator within undergraduate educational psychology courses. Across a multi-part, semester-long sequence, students engage in concept explanation, self-directed inquiry, AI-supported knowledge construction, and reflective documentation of their learning process. Findings from recurring student artifacts indicate progressive gains in conceptual understanding, integration of research sources, and transfer of knowledge to personally meaningful contexts. Students demonstrate increased capacity for self-regulated learning …

Arts Integration: Teaching Through The Senses Just Makes Sense!, Isabella Shenouda, Noah Karnafel, Hongming Xu

UNLV Best Teaching Practices Expo

Arts Integration is a high-impact teaching practice for both higher education and K-12 settings. Because students bring diverse backgrounds, learning preferences, and ways of making meaning, the arts offer flexible, multi-sensory pathways to content comprehension that traditional lecture-based and text-based instruction often cannot. Drawing on classroom evidence from an Honors First-Year Seminar at UNLV in which students identified an arts-based workshop as their favorite lesson, we argue that creative, hands-on activities deepen knowledge retention and foster genuine intellectual engagement. Arts Integration is inherently an asset-based and inclusive practice, as it encourages students to connect through various sensory learning experiences, whether …

The Prep‑Check Routine: How Students Prepare With Ai, Homa Soroudi-Terzian

UNLV Best Teaching Practices Expo

This poster presents a simple, repeatable Attempt & Audit routine that supports students in using AI as a learning partner rather than a shortcut. The Prep_Check structure guides students to attempt a problem on their own, ask AI for help on only one part, compare their work with the AI’s reasoning, and reflect on differences. This routine promotes metacognition, reduces anxiety, and helps students build confidence and independence in gateway math courses.

The Importance Of Relational Teaching In Introductory Statistics, Nathan Matthew Slife

UNLV Best Teaching Practices Expo

This poster presents relational teaching strategies for introductory statistics courses.

Redefining Certainty: Non-Euclidean Geometry And Theology Transformation Throughout The Intellectual Unrest Of The Early 1800s, Luke Bensinger

Honors Theses

To bridge the gap between mathematics and theology, it is necessary to explore their intersection and challenge the notion that these fields are incompatible. This study focuses on the 19th century, a period when non-Euclidean geometries emerged and disrupted mathematical certainty, while Protestant theologians such as Barton W. Stone and Alexander Campbell grappled with Calvinism and shifting theological perspectives. By analyzing mathematicians studying geometry, such as Gauss, Lobachevsky, and Riemann, this research examines how both disciplines balance change with enduring truths.

Analysis Of The Flavonoid Composition Of Honey Using High-Performance Liquid Chromatography, Bryce Phillips

Honors Theses

Honey is a naturally occurring substance that has a complex composition including compounds such as flavonoids, that contribute to potential health benefits. Quantitative analysis of flavonoids in honey can be challenging due to their similar structural characteristics, matrix effects, and chromatographic peak separation issues. This study aimed to establish calibration curves for five flavonoids–kaempferol, luteolin, chrysin, myricetin, and quercetin– to estimate their concentrations in five honey samples from varying geographic origins. Liquid-liquid extraction was used to isolate the flavonoids from honey. High Performance Liquid Chromatography was utilized to establish calibration curves and analyze honey samples. The calibration curves assembled demonstrated …

Reinforcement Learning Improves Llm Accuracy And Reasoning In Disease Classification From Radiology Reports, Yishu Wei, Yi Lin, Adam Flanders, George Shih, Yifan Peng

Department of Radiology Faculty Papers

Accurate disease classification from radiology reports is essential for many applications. While supervised fine-tuning (SFT) of lightweight LLMs improves accuracy, it can degrade reasoning. We propose a two-stage approach: SFT on disease labels followed by Group Relative Policy Optimization (GRPO) to refine predictions by optimizing accuracy and format without reasoning supervision. Across three radiologist-annotated datasets, SFT outperformed baselines and GRPO further improved classification and enhanced reasoning recall and comprehensiveness.

Comparison Of Chatgpt, Claude Ai, And Dental Students In The Detection Of Artifacts On Panoramic Radiography, Elif Çeçen Erol, Ceren Aktuna Belgin, Gözde Serindere, Kaan Gunduz

Journal of Dentistry Indonesia

Background: Accurate radiographic diagnosis requires images obtained with proper technique. Artifacts are unwanted irregularities or densities not produced by the primary X-ray beam and may obscure anatomical details in radiographic images. This retrospective study aimed to evaluate the performance of ChatGPT, Claude AI, and intern dental students in detecting artifacts in panoramic radiographs (PRs).

Methods: Between January and December 2024, panoramic radiographs of 40 patients containing 74 artifacts (motion, mispositioning, airway/soft tissue, and foreign body/metal artifacts) were retrospectively evaluated. The artifact detection performance of ChatGPT-4.0, Claude AI 3.5 Sonnet, and intern dental students was subsequently evaluated and compared …

2026 April 30 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Re: Comment Letter For The Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Bres No. 30 – Atlantic 1 Remedial Action Work Plan (Rawp) (Dated March 24, 2026), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Comment Letter For Draft Final 2026 Interim Site-Wide Groundwater Monitoring Quality Assurance Project Plan (Dated April 17, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final Unreclaimed Sites Field Sampling Plan (Fsp) Package #7: Ur-01, Ur-12, Ur-03, Ur-04, Ur-15, And Ur-17 Amendment (Dated April 28, 2026), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Hussein Mu’Nis’S Perceptions Of Historical Knowledge In Light Of Developments In The Foundations And Logic Of Modern Science, Kawa Azeez Brahim

Journal of Arts and Social Sciences

During the modern era, humanity witnessed major developments and transformations of the foundations and concepts upon which the logic of science was built, up to the present time in which we live, especially since these changes were in the essence and foundations of science, including, for example, what can be called the exact, mathematical, and experimental sciences, in which major and influential developments occurred that affected the sciences. The nature of man’s understanding of life and existence changed to the point that humanity was able, by employing these transformations, to control and control the external environment in which it lives …

Bibliography Of Religious Faith And The Mathematical Sciences, Calvin Jongsma

Faculty Work Comprehensive List

This Bibliography is offered as a helpful resource for anyone who wishes to thoughtfully explore the connections between religious faith and the mathematical sciences. Searching the database for a topic of interest will bring up items with that focus. An entry’s attached PDF (when publicly available) can be opened and read while in the database. Alternatively, each item contains a URL/web link to a location where one can either read the item or retrieve information about how to obtain a copy of it.

Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov

Chemical Technology, Control and Management

This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …

Data-Driven Neuro-Fuzzy Modeling And Rule Optimization For Intelligent Prediction Of Bioreactor Dynamics, Kamala Najaf Mammadzada

Chemical Technology, Control and Management

Modeling wastewater bioreactors is a challenging problem in environmental engineering because the processes are constantly changing and the microorganisms do not behave in a linear or predictable way. This makes it difficult to predict and control the system behavior. This research investigates three artificial intelligence approaches for modeling wastewater bioreactors: the Mamdani Fuzzy Inference System (FIS), the Adaptive Neuro-Fuzzy Inference System (ANFIS), and clustering-based fuzzy models. These models help us predict what is happening in the bioreactors. For instance they help us predict how the amount of substances in the water is changing over time like dS₀/dt dSs/dt …

Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

The computation of eigenvalues and eigenvectors under uncertainty is a fundamental problem in fuzzy linear algebra and decision analysis. When matrix elements are represented by fuzzy numbers, classical spectral methods cannot be directly applied due to nonlinearity, ambiguity in ordering, and the propagation of uncertainty. Moreover, in many practical applications, particularly those involving pairwise comparison matrices, the reliability of eigenvalue-based results strongly depends on the consistency of the underlying data. This paper proposes a consistency-based framework for computing fuzzy eigenvalues and fuzzy eigenvectors that explicitly integrates consistency analysis into the spectral derivation process. The proposed method preserves the fuzzy structure …

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …

Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …