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Spectroscopic And Structural Characterization Of Unexpected Porphyrinoid Byproducts Resulting From The Reaction Of A Cyclopentadiene Trialdehyde With N-Alkyltripyrranes, Kimberly Le, Gregory M. Ferrence, Timothy D. Lash

Faculty Publications – Chemistry

Acid-catalyzed condensation of N-alkyltripyrranes with a cyclopentadiene trialdehyde, followed by oxidation with aqueous ferric chloride solutions, gave unusual tripyrrolic byproducts in addition to previously reported carbaporphyrins and oxycarbaporphyrins. These stable nonaromatic structures incorporate aldehyde substituents, macrocyclic ketones, two conjugated pyrrole units, and a pyrrolo[1,2-a]pyrrole moiety. The NMR and UV-vis data were consistent with a nonaromatic system, and single-crystal X-ray diffraction confirmed that these structures are highly distorted. Structural characterization of a related aromatic carbaporphyrin triketone was also accomplished.

Modern Research Tools Supporting Science At Andrews University, Peter Lyons, Henry Navarro

Faculty Publications

No abstract provided.

A Note On The Novel Passive Sampling In Environmental Dna (Edna) Collection Technique To Detect Yellow Mud Turtle (Kinosternon Flavescens): Field And Laboratory Approaches In Turtle Edna, Sakib Tahmid Rishan, Richard J. Kline, Md. Saydur Rahman

School of Integrative Biological & Chemical Sciences Faculty Publications

Environmental DNA (eDNA) is a powerful and sensitive method for monitoring aquatic and terrestrial organisms, offering insights into their distribution. Usually, eDNA is collected using a filter membrane through water filtration. However, the passive eDNA method can simplify sampling and broaden its scope, offering new insights for ecological surveillance. This study examined the efficacy of six different membrane filters in detecting the yellow mud turtle (Kinosternon flavescens) through a novel passive eDNA method. After being immersed in water for 12 h, only the mixed cellulose ester (MCE) membrane filter consistently demonstrated specific polymerase chain reaction (PCR) amplification using …

The Periodical 2025-2026, Southern Adventist University

the Periodical – Chemistry Department Newsletter

Vol. 13, Issue 1 of the Periodical features an article on new faculty member, Sarah Pak, chemistry graduates, and several Meet the Faculty highlights.

Stem Identities Of Iowa State University's Biological And Biomanufacturing Systems Technology Students, Levi Nettleton

Dissertations and Theses @ UNI

STEM identity plays a crucial role in students' pursuit and persistence into the STEM field. Iowa State University's Biological and Biomanufacturing Systems Technology (BBST) undergraduate program, developed in alignment with the goals of Chemurgy 2.0, prepares students for careers in the growing STEM workforce. The purpose of this study is to examine how participation in the Biological and Biomanufacturing Systems Technology program influences undergraduate students' STEM identity and how students within the program perceive themselves within the scope of STEM. Specifically, the study investigates students' perceptions of their STEM identity across the four components of STEM identity: recognition, performance and …

The Impact Of Synchronous And Asynchronous Preference On The Performance Of Distance Learning Students, Christopher A. Wilson

Electronic Theses and Dissertations

Distance learning is a growing part of education. The transition to distance learning was underway at higher education institutions, but the COVID-19 pandemic forced institutions of all types to rapidly transition to distance learning. The technology that was adapted during this emergency distance learning remained in the classroom once normal instruction resumed. This quantitative study examined two aspects of distance learning technology in education. The study examined student preference for either synchronous or asynchronous instruction through the framework of expectancy theory. Students who were more familiar with the course material were hypothesized to have a higher expectation of success and …

Assistant Principals’ Perspectives And Experiences Concerning Their Influence As Instructional Leaders On Student Achievement In Title I Schools, Courtney J. Charles

Electronic Theses and Dissertations

Abstract

This qualitative descriptive study explored the perspectives and experiences of assistant principals in Title I schools in the context of their instructional leadership responsibilities. The study examined the relationship between assistant principals as instructional leaders in Title I schools and student achievement by addressing research questions related to curriculum implementation, data-driven decisions, school culture, instructional support, and professional development. Moreover, this study used purposeful sampling to select 13 assistant principals from Title I schools, and data were collected through semistructured interviews and analyzed using thematic analysis. Marzano’s focused school leader evaluation model served as the framework for interview questions. …

Preoperative Patient Sentiment Is Associated With Postoperative Outcomes In Adult Spinal Deformity Surgery, Ross J. Gore, David Mazur-Hart, Mohan K. Sunkara, Aaqib Ali, Qizar Ali, Christopher J. Lynch, Christopher Ames

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Study Design: Prospective observational pilot study of adult spinal deformity surgery patients.

Objective: To determine whether preoperative patient sentiment, quantified using a 21-class valence scale extending the CARP paradigm implemented through an offline Large Language Model, predicts postoperative outcomes.

Summary of Background Data: Predicting adult spinal deformity surgery outcomes remains challenging with traditional clinical and radiographic parameters alone. Although patient psychological factors and expectations significantly influence postoperative satisfaction and quality of life, systematic approaches to capture these factors are underdeveloped. Offline Large Language Models offer scalable, privacy-preserving psychological risk stratification.

Materials and Methods: We prospectively enrolled 18 patients undergoing adult …

Adaptive Boundary-Aware Fact-Checker Placement For Misinformation Suppression In Social Networks, Mostafa Taghizade Firouzjaee, Ghazal Naderi, Ross Gore, Neda Moghim

School of Cybersecurity Faculty Publications

The spread of fake news on online social networks is driven by imitation-based user behavior and network topology, often leading to persistent misinformation clusters and echo chambers. In this study, we develop a spatial evolutionary game-theoretic framework in which agents update their latent opinions through payoff-biased imitation, while external fact-checkers act as non-imitative intervention nodes. Building on this formulation, we propose an adaptive, boundary-aware intervention mechanism that dynamically regulates both the density and spatial allocation of fact-checkers according to real-time system conditions. Competing information clusters are identified through local neighborhood composition, enabling boundary nodes, i.e., interfaces between fake-news and non-fake-news …

Enlem: Ensemble Learning-Based Model To Detect Phishing Websites, Most Nilufa Yeasmin, Md Abu Rumman Refat, Bikash Chandra Singh, Zulfikar Alom, Zeyar Aung, Mohammad Azim

School of Cybersecurity Faculty Publications

Phishing involves manipulating individuals into revealing private data, e.g., user IDs, bank details, and passwords. The observed surge in fraud is related to increased deception, impersonation, and advanced online attacks. Thus, effective phishing detection methods are required to mitigate escalating global phishing threats. Existing methods (e.g., heuristics-based, signature-based, and visual similarity-based methods) attempt to detect phishing sites, and machine learning (ML) and deep learning (DL) methods are effective in the cybersecurity context in terms of learning from data, offering insights, and forecasting. However, independent ML algorithms are limited when handling complex data, and DL techniques surpass traditional ML methods in …

Toward Secure And Practical Machine Learning-Based Access Control: A Framework With Real-World Constraints And Adversarial Analysis, Olusesi Balogun, Mohammad Ghasemigol, Zhipeng Cai, Daniel Takabi

School of Cybersecurity Faculty Publications

Attribute-Based Access Control (ABAC) frameworks coordinate access requests based on subject, object, and environment attributes, as well as policy rules, and are widely used in corporate security systems. Recently, machine learning has been applied to ABAC to address policy-generation imbalances, misassigned privileges, and attribute leakages. However, existing MLBAC techniques do not consider the structural constraints and attribute interdependencies present in traditional ABAC systems. Moreover, these frameworks have not been extensively evaluated under black-box attack scenarios. To address these gaps, we propose extensions to MLBAC that integrate structural constraints, attribute dynamism, and attribute weighting into the MLBAC objective function. Additionally, we …

Preoperative Patient Sentiment Is Associated With Postoperative Outcomes In Adult Spinal Deformity Surgery, Ross J. Gore, David Mazur-Hart, Mohan K. Sunkara, Aaqib Ali, Qizar Ali, Christopher J. Lynch

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Study Design:

Prospective observational pilot study of adult spinal deformity surgery patients.

Objective:

To determine whether preoperative patient sentiment, quantified using a 21-class valence scale extending the CARP paradigm implemented through an offline Large Language Model, predicts postoperative outcomes.

Summary of Background Data:

Predicting adult spinal deformity surgery outcomes remains challenging with traditional clinical and radiographic parameters alone. Although patient psychological factors and expectations significantly influence postoperative satisfaction and quality of life, systematic approaches to capture these factors are underdeveloped. Offline Large Language Models offer scalable, privacy-preserving psychological risk stratification.

Materials and Methods:

We prospectively enrolled 18 patients undergoing adult …

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

Framework For Task Offloading In O-Ran Architecture For Heterogeneous Computing Applications, Samira Taheri, Neda Moghim, Naser Movahhedinia, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Computational offloading transfers tasks from resource-constrained devices to more capable servers or cloud platforms, improving processing speed and user experience. Open radio access networks (O-RAN's) disaggregated architecture and open interfaces make it suitable for offloading delay-sensitive tasks, enhancing real-time application performance. This study focuses on task offloading in O-RAN, a reference network architecture. Although research on O-RAN is limited, existing work lacks a comprehensive approach to offloading, including offloading layer determination, node selection, and resource allocation based on task types and their latency needs. We propose a delay-aware task offloading framework within O-RAN to support diverse delay requirements, improving offloading …