Digital Commons Network^™

Neutrosophic Optimal Transport Of Rural Cultural Development Quality Under Rural Revolutionary Topological Constraints: A Strategic Evaluation Model, Yongjun Zhang

Neutrosophic Sets and Systems

No abstract provided.

The Applications Of Definite 2-Refined Neutrosophic Integrals, Yaser Ahmad Alhasan, Asma Mohammed Alshallali, Qusay Alhassan, Ashraf Alnassan

Neutrosophic Sets and Systems

No abstract provided.

Refined N-Valued Neutrosophic Markov Decision Processes For Quality Evaluation Of Talent Cultivation In Vocational Education Under Emerging Productive Forces, Wei Zhao

Neutrosophic Sets and Systems

No abstract provided.

The N-Hyperspherical Neutrosophic Sets Defined On Some Algebraic Structures, Marimuthu Dharmalingam, G. S. Mahapatra, I. Silambarasan, R. Vijaykrishnaraj, P. Ra Jakumari, R. Selvakumar

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Network Flow With Truth, Indeterminacy, And Falsity Capacities: An Innovative Mathematical Framework For Efficiency Evaluation Of Achievement Transformation Of College Student Innovation And Entrepreneurship Training Programs, Yingchun Gan

Neutrosophic Sets and Systems

No abstract provided.

Mr-Metric Spaces: Theory And Applications In Fractional Calculus And Fixed-Point Theorems, Abed Al-Rahman M.Malkawi, Ayat M. Rabaiah

Neutrosophic Sets and Systems

No abstract provided.

N-Edu: An Innovative Neutrosophic Logic Construction For Digital Transformation Effectiveness Of College Ideological And Political Education With Mathematical Foundations And Applied Learning Dynamics, Ye Chen

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Triplet Growth Model For Moral-Linguistic Competence In College English Teaching Reform Under Moral Education And Talent Cultivation, Jianguo Liu, Ruohan Liu

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Aesthetic Attainment Index With Αm-Continuity And Ngsr-Closed Classification For Robust Assessment In Dance Aesthetic Education Classes, Xiaoli Liu

Neutrosophic Sets and Systems

No abstract provided.

A Blockchain-Enabled Neutrosophic Framework For Secure, Verifiable, And Adaptive Configuration Management Effectiveness And Computer Network Telemetry, Xiaojian Hong

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Truncated Normal Distribution For Renewable Energy Forecasting And Optimization, Afrah Al Bossly, Zahid Khan

Neutrosophic Sets and Systems

No abstract provided.

Modeling Entangled Indeterminacy Flows: A Neutrosophic Multi Module Simulation Framework For Cross-Border E-Commerce Digital Marketing Effectiveness, Ying Zhu, Lingling Li

Neutrosophic Sets and Systems

No abstract provided.

Existence And Uniqueness Of Best Proximity Point In Non-Archimedean Neutrosophic Complete Metric Space, A. Sreelakshmi Unni, V. Pragadeeswarar

Neutrosophic Sets and Systems

No abstract provided.

Quaternion Algebra And Neutrosophic Integers For Generating An Efficient Mathematical Encryption System, Majida H. Majeed, Mohammed Hassan Hamza, Abdullah Mhmood Jasim, Hassan Yassein

Neutrosophic Sets and Systems

No abstract provided.

Correlation Coefficient Under Rough Neutrosophic Set For Effectiveness Assessment Of Students' Mental Health Education In Higher Education Institutions, Shuang Cui

Neutrosophic Sets and Systems

No abstract provided.

Pythagorean Language Neutrosophic Number For Teaching Quality Analysis Of Dance Education And Performing Arts Programs Based On Multimedia Technology, Shifei He, Lizhu Fang

Neutrosophic Sets and Systems

No abstract provided.

Probabilistic Single-Valued Neutrosophic Set For A Multidimensional Evaluation Of College Students’ Mental Health And Academic Success, Xue Wang, Lu Yang

Neutrosophic Sets and Systems

No abstract provided.

Comprehensive Drought Analysis: Machine Learning-Based Meterological Drought Forecasting And Pca-Driven Agricultural Drought Monitoring., Bishal Poudel

Theses

Drought is a long-term natural disaster that affects many aspects of human life from health, water supply to ecosystems and agriculture. Drought’s occurrence and intensity has increased in recent years because of global warming, which urges for proper and accurate monitoring and forecasting of drought. For better understanding of droughts, this study uses two approaches. In first part, the study uses the historical temperature and precipitation data from period of 1960 to 2021 as input features for three different machine learning models – Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest (RF). The research focuses on calculating …

Prediction Of Geometric Deviation In Additively Manufactured Tpms Lattice Structures Using Non-Destructive Evaluation And Conditional Generative Adversarial Networks, Prateek Neupane

Theses

Metal 3D printing has emerged as a widely used additive manufacturing method, finding applications across numerous industries and research areas. However, its application is often hindered by geometric inaccuracies and surface quality issues resulting from the complex interplay of laser power, melt pool behavior, and cooling characteristics. These inconsistencies have a significant impact on the design and functionality of printed parts, affecting structural integrity and dimensional accuracy. Thus, an effective data-driven approach is crucial to predict these deviations before manufacturing. This study proposes a methodology that incorporates Non-destructive evaluation techniques, like in-situ monitoring and X-ray CT scan, with Conditional Generative …

Studies On Curcumin-Glucoside In The Prevention Of Alpha-Synuclein Aggregation, Lakshmi Sowmya Emani, Jayanth K. Rao, Jagadeesha Kumar Dasappa, Marisín Pecchio, Johant Lakey-Beitia, Hansapani Rodrigo, Jessica Cruz-Mora, Priya Narayan, Nikhilesh Anand, Bharathi Gadad

School of Medicine Publications

Background: α-synuclein (α-syn) deposition in the mid-brain region is one of the hallmark pathologies of Parkinson's disease (PD). The key steps involve the transformation of α-synuclein into a toxic oligomer and insoluble fibrillar aggregates.

Objective: To understand the role of curcumin-glucoside in the prevention of α-syn aggregation, a mechanistic approach.

Methods: In the present study, we synthesized a novel molecule, curcumin-glucoside (Curc-gluc), to improve the water solubility and partition coefficient, making the molecule with high bioavailability. The present study is focused on understanding the α-syn aggregation kinetics in the presence and absence of Curc-gluc, curcumin (Cur), copper (Cu), and iron …

Neutrosophic Sets And Systems, Vol. 91,2025, Florentin Smarandache, Mohamed Abdel-Basset, Maikel. Leyva Vazquez

Neutrosophic Sets and Systems

No abstract provided.

Roadmap To Success: Perspectives Of Black Females Overcoming Barriers In Doctoral Programs At Predominantly White Institutions (Pwis) And Historically Black Colleges And Universities (Hbcus) In Southeast Texas, Jenta’ Monique Young

All Dissertations

This study employed a qualitative research design to explore the experiences of 10 Black female doctoral students as they matriculated and successfully graduated from doctoral programs at Predominantly White Institutions (PWIs) and a Historically Black Colleges and Universities (HBCUs) in Southeast Texas. A descriptive phenomenological research methodology was employed in this study to illustrate the struggles and barriers Black females face during matriculation and their persistence in achieving success in a doctoral program. The participants were women who self-identified as Black or African American. Participants were previously enrolled full-time in a cohort-oriented doctoral program with face-to-face, online, or hybrid instruction …

Early Conceptual Sketches Of Blended Reality And The Precursor To The Bbs Quad (2022), David Smith

Publications and Research

This document contains two original hand-drawn conceptual sketches created in early 2022, representing the earliest visual formulations of what would later evolve into the Balanced Blended Space (BBS) framework. The drawings predate my first conversations with ChatGPT and were produced as part of my independent sabbatical research into blended environments, mediated performance, and human–machine interaction.

The first drawing examines human–computational mediation, perception, and internal mapping. The second sketch—later referred to informally as the “BBS Quad”—extends this idea by reconciling cognition–computation symmetry with physical–virtual spatial relationships. Published together, these images document the conceptual foundations of the BBS framework prior to its …

Greenhouse Gas Accounting For Western Australian Agriculture 2023, Johnny Machon, Christophe D'Abbadie

Climate Science Published Reports

This report presents new modelling of the greenhouse gas emissions attributable to Western Australia’s agricultural industries and provides an overview of sequestration at the state level. The report updates the estimates from previous technical reports by the Department of Primary Industries and Regional Development (DPIRD). It presents not only emissions from agricultural activities in Western Australia (WA) but also from the production of agricultural inputs and energy use. This broader picture of emissions aligns with frameworks for emissions reporting at the business and product level.

Total on-farm and pre-farm emissions are estimated to have been about 12.6–13.3 million tonnes of …

Instance-Adaptive Gated Fusion Of Multi-Transform Image Representations, Prince Appiah

Open Access Theses & Dissertations

This dissertation proposes the Instance-Adaptive Gated Fusion (IAGF) framework, a novel deep learning architecture for adaptive and interpretable fusion of multiple time–series image transformations. While existing methods rely on static concatenation or dataset-level optimization, IAGF introduces a learnable gating mechanism that dynamically assigns per-instance weights to Recurrence Plots (RP), Gramian Angular Summation Fields (GASF), and Gramian Angular Difference Fields (GADF). The gating layer performs a convex fusion of transformation-specific embeddings under a softmax constraint, ensuring mathematical stability and interpretability. An entropy-regularized objective prevents dominance collapse and promotes balanced exploration of transformations during training. Comprehensive experiments across eighteen benchmark datasets, spanning …

Simulation, Modeling, And Economical Optimization Of Small Modular Reactors For Flexible Power System Operations, Javier Bejarano

Open Access Theses & Dissertations

The transition toward a low-carbon and increasingly renewable electric grid has heightened the need for generation technologies that can deliver both stability and operational flexibility. Small Modular Reactors (SMRs), with their modularity, reduced geographical footprint, and capacity for flexible operation, have emerged as promising resources for supporting modern power systems. However, a comprehensive evaluation of their technical performance across steady-state conditions, fault-induced disturbances, and economically optimized dispatch is necessary to understand their role in future grid architectures. This thesis provides an assessment of SMR capabilities using benchmark test systems, data-driven forecasting, dynamic simulation, and unit commitment modeling to evaluate how …

Hydrological Responses To Rainfall Pulses In Desert Vadose Zones: A Multi-Scale Approach Integrating Geophysical, Isotopic, And Eddy-Covariance Measurements, Alfredo Dagda-Torres

Open Access Theses & Dissertations

Drylands are shaped by natural episodic precipitation, where short, intense rainfall pulses interrupt prolonged drought and drive most hydrological and ecological activity. Yet the mechanisms that determine how pulse water infiltrates, is redistributed, stored, evaporated, and ultimately used by desert vegetation remain under quantified in landscapes underlain by shallow petrocalcic horizons. This dissertation integrates three complementary approaches 1) three-dimensional electrical resistivity tomography, 2) eddy-covariance evapotranspiration partitioning, and 3) stable-isotope tracing to improve a mechanistic understanding of pulse-driven water movement and plant water use in a caliche-rich piedmont at the Jornada Experimental Range. The first component characterizes how infiltration pulses interact …

Intelligent Predictive Frameworks Under Data Scarcity And Uncertainty, Solayman Hossain Emon

Open Access Theses & Dissertations

Modern predictive systems frequently operate under conditions of limited annotated data, high uncertainty, and the need for reliable decision-making. When the predictive models expand across heterogeneous data types (e.g., spatial, temporal streams), the challenge lies not only in accurate prediction but also in adapting in data distributions shifts or label scarcity. To address these issues, this thesis explores an Intelligent Predictive Framework that operates robustly under data scarcity and uncertainty across two distinct domains: medical imaging (spatial) and time-series forecasting (temporal). In the first part of this work, a semi-supervised mean teacher (MT) paradigm is tailored for medical image segmentation …

Development Of Oxide And Oxynitride Thin Films For Advanced Optical Applications, Nathan Christopher Episcopo

Open Access Theses & Dissertations

To develop Ga2O3 and TiOₓNᵧ thin films for optical applications, the process–structure–properties relationship was investigated using a comprehensive set of characterization techniques to establish the atomic structure and composition of the films in relation to the deposition conditions. The results provide critical insights into how deposition parameters influence the atomic structure and composition during magnetron sputtering. Furthermore, the correlation between atomic structure and composition with the optical and electrical properties of the films was examined to determine how variations in these factors affect functional performance. Collectively, these findings offer the necessary information to target desirable optical properties for Ga2O3 and …

From Morphology To Machine Learning And Genomics: Understanding Phenotypic Variation In Wild Ducks, Sara Gonzalez

Open Access Theses & Dissertations

Understanding the genetic underpinning and distribution of phenotypic variation within and between divergent groups is core towards shedding light into how populations diverge and adapt, as well as how hybridization breaks or builds on these scenarios; and thus, central to evolutionary biology. In wild organisms, however, quantifying and linking phenotypic traits to underlying genetic processes, like mutation, gene expression, epigenetics and allele interactions, remains challenging. This difficulty arises from the complex interplay between morphology, environment, and gene regulation, as well as the logistical barriers of collecting and standardizing large-scale data across individuals and populations. As a result, researchers are increasingly …