Digital Commons Network^™

Best Proximity Point Results In Neutrosophic Fuzzy Metric Space For Ciric Type Α-Ψ Proximal Contractive Mappings, Samriddhi Ghosh, Ramakant Bhardwaj, Purvee Bhardwaj, Sneha Khandait, Satyendra Narayan

Neutrosophic Sets and Systems

No abstract provided.

Decision-Making Under Deep Uncertainty: A Generalized Neutrosophic Fuzzy Assignment Model With Multi-Criteria Multi-Expert Evaluation, Priyanka U, Dr. V. Kamal Nasir

Neutrosophic Sets and Systems

No abstract provided.

Application Of New Neutrosophic Open Set Via Neutrosophic Topological Spaces, S.R. Yaseen, Qays Hatem Imran, Giorgio Nordo

Neutrosophic Sets and Systems

No abstract provided.

New Classes Of Δ − Β∗-Continuous Mappings In M-Polar Neutrosophic Topological Spaces, Shadia M. Noori, Asmaa G. Raoof, S.R. Yaseen, Qays Hatem Imran, Giorgio Nordo, Lorenzo Aff´E

Neutrosophic Sets and Systems

No abstract provided.

Bibliometric Study Of Neutrosophy As An Emerging Discipline, Miguel Cruz Ramírez, Osvaldo Jesús Rojas Velázquez, Elio H. Cables

Neutrosophic Sets and Systems

No abstract provided.

Δβ-Open Sets In Pythagorean Neutrosophic Nano Topological Spaces And Their Application Via Machine Learning, Mohanarao Navuluri, Shantha Lakshmi K

Neutrosophic Sets and Systems

No abstract provided.

Dealing With Missingness In Uncertain Data Via Neutrosophic Exponential Imputation: Climate Data Insights, Anoop Kumar, Vishal Kumar, Vrijesh Tripathi

Neutrosophic Sets and Systems

No abstract provided.

Breaking The Chains Of Probability: Neutrosophic Logic As A New Framework For Epistemic Uncertainty In Large Language Models, Maikel Yelandi Leyva-Vázquez, Florentin Smarandache

Neutrosophic Sets and Systems

No abstract provided.

Analysis Of (1,2,3,4)-Type Inverses In Neutrosophic Hyper Soft Rough Fuzzy Matrices, G. Punithavalli, K. Ramany

Neutrosophic Sets and Systems

No abstract provided.

Applied Neutrosophic Triplets In Ai Decision Systems: Introduction To An Ongoing Case Study Across Agentic, Swarm, Rag, And Pipeline Architectures, Jean-Sebastien Beaulieu

Neutrosophic Sets and Systems

No abstract provided.

Probabilistic And Neutrosophic Coefficient Conditions In Geometric Function Theory With Applications To Sound Denoising Associated With Mersenne Polynomials, Ibrahim Tunji Awolere, Abimbola Adeniyi Ayeni, Abiodun Tinuoye Oladipo

Neutrosophic Sets and Systems

No abstract provided.

Mathematics Education And Its Contributions To Attention Deficit Hyperactivity Disorder, Randy Zabaleta, Osvaldo Rojas, Beatriz Villarraga, Miguel Cruz, Diana Pérez

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophication As A General Framework For Regret Theory, Grey System Theory, And Three-Way Decision Models, Florentin Smarandache

Neutrosophic Sets and Systems

No abstract provided.

Real-World Implementation Of A Neutrosophic Logarithmic Estimator For Population Mean Estimation Under Stratified Random Sampling, Deep Shikha, Shakti Prasad, Deepak Majhi, Housila P. Singh

Neutrosophic Sets and Systems

No abstract provided.

Foundations Of Type-1 Neutrosophic Topological Modules, Hussain Wahish, Adel Al-Odhari, Abdulwahed Mhdi, Basheer Al-Refaei, Khaled Alhamadi

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Logic As A Framework For Managing Uncertainty In Artificial Intelligence, Conf. Univ. Dr. N. Grigorie Lăcrița, Craiova Craiova, Romania Romania

Neutrosophic Sets and Systems

No abstract provided.

On Operations Of Indetermsoft Sets, Savita Rathee, Diksha Goyal, Meenakshi Hooda, Ridam Girdhar, Savita Ahlawat

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Sets And Systems, Vol. 99,2026, Florentin Smarandache, Mohamed Abdel-Basset, Maikel. Leyva Vazquez

Neutrosophic Sets and Systems

No abstract provided.

A Quantum Phase Space Description Of Local Noise In Atomic Ensembles, Andrew Kolmer Forbes

Physics & Astronomy ETDs

Nonclassicality in quantum sensors can improve sensitivity, but often increases susceptibility to noise. Thus, modeling physically relevant noise sources and analyzing their effect on quantum metrology are both of importance to the field of quantum sensing. In this dissertation, I demonstrate that local noise sources, which are present in almost all many-spin systems, can be tractably modeled when assuming permutation symmetry of the noise, and we show that many common local noise sources can be mapped to a Fokker-Planck equation on quantum phase space. We apply this description of noise to study quantum sensing using noisy probe states and establish …

Optical Nuclear Spin Detection In Diamond And Varifocal Metasurface Optics, Maxwell D. Aiello

Physics & Astronomy ETDs

This dissertation presents two experimental investigations at the intersection of quantum sensing and precision optical instrumentation. The primary project demonstrates optically detected nuclear magnetic resonance (NMR) of ¹³C nuclear spins in diamond, using state-selective Landau-Zener transitions under microwave frequency sweeping to bidirectionally transfer spin polarization between nitrogen-vacancy (NV) electron spins and remote ¹³C nuclear spins. This enables optical polarization and readout of large ensembles of polarized nuclear spins at low magnetic fields and room temperature, with spin dephasing times limited by longitudinal relaxation of nearby NV electron spins. The secondary project reports the design, fabrication, and characterization of …

Quantifying Co2 And Ch4 Fluxes In A Semi-Arid Floodplain: Assessing Spatial And Temporal Drivers, Miles E. Kelsey

Earth and Planetary Sciences ETDs

Rivers transport sediment and carbon across Earth’s surface, and their floodplains can store carbon over decades to millennia, making them important to terrestrial carbon management. While soil carbon can persist long term, it may be released as greenhouse gases through processes like methanogenesis and heterotrophic respiration. Environmental controls on these fluxes remain poorly constrained across floodplains in different climate and geomorphic setting, but especially in semi-arid systems where measurements are limited. To address this gap, we quantified CO₂ and CH₄ fluxes along the Middle Rio Grande (New Mexico, USA) using 227 chamber measurements collected May to November 2025 at three …

Continuous Polygenic Trait Evolution Under Brownian Motion With Gaussian Mixture Models, Mary S. Hopkins

Mathematics & Statistics ETDs

Gaussian mixed-models (GMMs) show promise as a tool for modeling polygenic trait evolution for multiple taxa with established phylogenetic comparative methods (PCMs). When phenotypic traits are influenced by more than one gene, neither a gene tree nor a species tree may be completely adequate to model specific cross-taxa dependencies. In such cases common solutions include using trees inferred from concatenated DNA sequences [35, 95] and consensus gene trees [35]. The GMM-based model, first proposed by Jiang in 2017 [55] allows traits to evolve on more than one tree with distinct topologies. This approach provides a framework for trait evolutionary modeling …

Bayesian Designs For Two-Arm Clinical Trials With Time-To-Event Endpoints: Incorporating Historical Data Through Power Priors, Sara Hajraf H. Almutiri

Mathematics & Statistics ETDs

Bayesian methods provide a flexible framework for time-to-event analysis by incorporating prior information. The power prior offers a systematic way to borrow information from historical data. This approach is especially valuable in clinical research, where historical data can enhance inference in early-phase trials with limited sample sizes. This dissertation develops Bayesian approaches for two-arm survival studies using both closed-form and simulation-based methods. The closed-form inference is derived under exponential and Weibull survival models. Under the proportional hazards framework, the posterior is derived through a normal approximation to the log hazard ratio, allowing inference on the treatment effect when the variance …

Marine Geophysical Studies Of Coupled Tectonic And Sedimentary Processes At Active Plate Boundaries, Sarah R. Rysanek

Earth and Planetary Sciences ETDs

Deep-sea and convergent margin sedimentary systems preserve critical records of tectonic and climatic processes that shape Earth’s surface. This dissertation investigates source-to-sink sediment routing and forearc deformation to better constrain the interplay between sedimentary and tectonic processes, through investigations of a deep-sea fan system, and the forearc geomorphology offshore Nicaragua. In the Gulf of Alaska, we integrate ultra-long-offset and regional multi-channel seismic reflection data, multi-resolution bathymetry, and plate reconstructions to remap the Baranof Fan system. Results show that the fan is larger than previously recognized and constructed by two primary depocenters linked to distinct glacial sediment pathways, with accommodation space …

Quantum Control Protocols For Robust Quantum Computing, Leeseok Kim

Electrical and Computer Engineering ETDs

The fundamental goal of quantum computing is to precisely control quantum systems to perform meaningful tasks, including implementing high-fidelity quantum gates for reliable quantum computation and accurately simulating complex quantum many- body dynamics. In this dissertation, we develop improved quantum control protocols for three distinct objectives, quantum error suppression, quantum optimal control, and analog quantum algorithms, achieving performance beyond standard approaches. First, we introduce new dynamical decoupling protocols, including both determin- istic and randomized constructions, that can substantially outperform conventional deterministic sequences. We then extend the randomized approach to dynamically corrected gates. Second, we propose a randomized quantum optimal control …

Constraining Magmatic Processes In The Central American Arc Using Melt Inclusion Vapor Bubble Analysis And Triple Oxygen Isotope Modeling And Exploration Of Volatile Contributions To The Production Of Continual Radio Frequency (Crf) Lightning Events, John M. Hamilton

Earth and Planetary Sciences ETDs

Magmatic volatiles are key to determining the processes happening in the subsurface that we cannot directly sample. Advances in measuring volatile and isotope contents from erupted volcanic samples have given us the ability to understand magmatic processes, mixing components that produce the bulk magma composition and potentially precursors to eruptive hazards, such as lightning.

Through analysis of melt inclusions that sample the melt at depth and triple oxygen isotope quantification of olivine crystals from multiple volcanic edifices, the three following studies display how I have utilized these analytical techniques to help unravel processes happening in the subsurface that lead volcanic …

Computational Design Of Peptides And Proteins Through Machine Learning Approaches, Emily J. Hendrix

Chemistry and Chemical Biology ETDs

Advancements in machine learning have emerged as a pivotal tool in computational biochemistry, offering new advancements to address challenges in protein structure and function. However, current machine-learning approaches offer limited insight in understanding protein dynamics. The purpose of this work is to combine traditional physics-based computational tools, such as molecular dynamics and coarse-grained simulations, with recently developed AI-driven computational tools to bridge gaps and advance the understanding of proteins in both structural and dynamic aspects. I investigated several approaches such as (i) traditional physics-based methods to study protein conformation and ensembles; (ii) identifying a peptide inhibitor for the PICK1 PDZ …

Nanoscale Structure And Spontaneous Self-Assembly Of Hydrothermal Organic Products, Glorianne P. Dorce

Chemistry and Chemical Biology ETDs

Carbon nanomaterials derived from citric acid and urea exhibit behaviors that challenge conventional structure–property models based on static bulk descriptions. This study examines how precursor pairing and reaction duration, post‑synthetic thermal history, and time‑dependent aging govern nanoscale organization and optical response. Through controlled synthesis and processing, distinct nanostructures with tunable structural and spectroscopic profiles are generated.

A multiscale framework integrating nano‑FTIR, atomic force microscopy, and thermal analysis reveals chemical heterogeneity and continuous structural reorganization across length scales. By correlating local chemical environments with optical behavior, we show that fluorescence efficiency and photostability depend on specific nanoscale architectures rather than average …

Computing Certificates Of Members In Archimedean Quadratic Modules In A[X] And Certifying The Emptiness In Inconsistent Monogenic Archimedean Quadratic Modules In A[X_1, ..., X_N], Jose A. Castellanos Joo

Computer Science ETDs

Polynomials have been found to be a powerful tool over hundreds of years for modeling problems in numerous applications in science, engineering, medicine, and other domains. In the context of formal methods, polynomials arise in modeling in aerospace software and robotics, cyber-physical and hybrid systems, autonomous vehicles and controllers based on neural networks.

A quadratic module is a linear combination of polynomials in a set of generators (including the constant 1) with sum of squares polynomials as multipliers. The membership problem for a finitely generated quadratic module can be decided; however, computing a certificate exhibiting why it is nonnegative under …

Design, Fabrication, And Characterization Of Silicon Nitride Microresonator Optical Frequency Combs, Lala Rukh

Optical Science and Engineering ETDs

Optical frequency combs consist of equidistant optical frequencies and have numerous applications ranging from optical metrology to medical diagnostics. Initially, frequency combs were based on bulky mode-locked lasers, but advancements in integrated photonics enabled the generation of frequency combs in chip-scale resonators (microcombs) using Kerr nonlinearity. These miniaturized systems present various challenges, including increased propagation losses, enhanced thermal effects, and the extension of microcombs to visible wavelengths. In this dissertation, I will focus on addressing these challenges in silicon nitride (SiN) resonators. First, this thesis focuses on the fabrication of high-Q SiN resonators and the impact of fabrication parameters on …