Digital Commons Network^™

Simulation Strategies For Safer Student Medication Administration: A Quality Improvement Project, Rochelle D. Beaver

Doctor of Nursing Practice Projects

Medication administration is an essential skill for nurses, but there are few opportunities for students to practice this skill to prepare for clinical practice. Literature shows that best practice to bridge the gap is simulation. The purpose of this quality improvement project is to implement an evidence-based simulation activity for students. The problem is that not all faculty are trained to teach via simulation. The aim of the project is to increase the nursing faculty’s competence in facilitating a medication administration simulation activity focusing on pre-briefing and debriefing utilizing evidence-based standards from International Nursing Association for Clinical Simulation and Learning. …

Beyond The Numbers: How Elementary Principals’ Beliefs, Experiences, And Contexts Shape Their Descriptions And Perceptions Of Effective Data Use As Instructional Leaders, Brett Lobben

Doctorate in Education

Effective data use informs next steps in student learning and drives school improvement and systemic change, making it a critical factor in school success. Principals play a critical role in creating the conditions necessary for data use to thrive (Park & Datnow, 2009; Keuning et al., 2017; Schildkamp et al., 2019; DuFour et al., 2016; Albiladi et al., 2020). This study explored how elementary school principals describe and perceive effective data use within the context of their instructional leadership, and how these perceptions are shaped by personal beliefs, past experiences, and the educational contexts in which they lead.

This qualitative …

Profiting From Disaster: How Rising Climate Risk Is Reducing Insurance Coverage And Paving The Way For Predatory Lending, Samuel Tunnell

St. Mary's Law Journal

No abstract provided.

Comparative Analysis Of The Complete Chloroplast Genome Of The Rare Endemic Palm Pinanga Arinasae Witono From Bali, Indonesia, Ni Putu Sri Asih, Risha Amilia Pratiwi, Istiana Prihatini, Paramita Cahyaningrum Kuswandi, Evy Yulianti, Arief Priyadi

Turkish Journal of Botany

Pinanga arinasae is an endangered species endemic to Bali, Indonesia. Our study aims to characterize its chloroplast genome, compare it with other chloroplast genomes, including its phylogenetic position within the Arecoideae subfamily, and identify potential molecular markers. P. arinasae chloroplast genomes characterization involves Illumina-based sequencing, de novo genome assembly, gene annotation, amino acid frequency, codon usage pattern analysis, and Simple Sequence Marker (SSR) identification. Comparative analysis include phylogenetic tree reconstruction, comparison of amino acid frequency, codon usage pattern, SSR number, inverted repeat junction arrangement, genome length, GC content, and gene number. Nucleotide diversity is calculated to identify substitution markers. The …

Exploring Students' Perceptions Of Genai Tools In Higher Education: A Case Study, Dina Mansour Tbaishat, Maha Waleed Elfadel

All Works

As artificial intelligence transforms the educational landscape, generative artificial intelligence (GenAI) tools have become influential in enhancing learning experiences. Despite their growing presence in higher education, limited research explores how university students, especially learners in non-Western contexts, perceive these tools. This study investigates students' perceptions at a university in the UAE, focusing on five dimensions: perceived benefits, institutional support, technological self-efficacy, ethical considerations and user satisfaction. The findings reveal that students generally expressed strong agreement regarding the benefits of GenAI, demonstrated a clear sense of ethical awareness and felt confident in their technological abilities. While satisfaction levels were generally high, …

Financial Inducements In Gambling Marketing: An Information Disclosure Proposal To Inform Gamblers Of Their True Economic Value, Philip Newall, Dominic Cortis, Jamie Torrance

UNLV Gaming Research & Review Journal

Financial inducements such as free bets are frequently-used gambling marketing offers which temporarily improve a gambler’s usual pattern of risk and potential return. Previous research has shown that there are up to 15 distinct types of financial inducements in common use, and that gamblers frequently misunderstand inducements’ play-through requirements and other complex terms and conditions. The Australian government has therefore recently banned play-through requirements for inducements shown to new customers, and the Great British regulator the Gambling Commission has recently announced a maximum play-through requirement of 10 times. The present work describes an alternative and yet potentially complementary approach based …

Ground-Based Modeling Of Deep-Space Risks To The Spleen And Intestine In Mice, Edith Nathalie Pineda Sotomayor

Theses and Dissertations

Deep-space missions, such as those planned for the cis-lunar space and Mars, pose unique challenges to astronaut health due to prolonged microgravity (MG) exposure and low-dose chronic irradiation (CIR). Understanding the impact of these stressors on secondary lymphoid tissues, such as the spleen and intestine, is crucial for ensuring crewmembers' well-being, given the impracticality of conducting this research with human samples. Using a ground-based facility, we exposed C57BL/6 female and male mice to CIR (1.74 Gy at a dose rate of 0.0029 Gy/h) and/or simulated MG (SMG) via hind limb unloading (HLU) for one month. Spleen and intestinal tissues were …

The Scarlet - Volume Civ, No. 2 (September 19, 2025), Scarlet Staff

The Scarlet (Student Newspaper) (2011-present)

The September 19, 2025 edition of The Scarlet (est. 1939), Clark University's student-run newspaper. The Scarlet is intellectually and editorially independent of the University.

Advanced Microstructured Batio3-Embedded Pvdf–Hfp/Peo Film For Enhanced Triboelectric Interface In Self-Sufficient Energy Generation And Sensing, Rigobert Ybarra, Diego De Leon, Michael Moreno, Cesar Sanchez, Fernando Viesca, Kevin Alejandro, Shishir Timilsena, Nicholas Dimakis, Joseph H. Dumont, Tommy Rockward, Tarik J. Dickens, Md. Wasikur Rahman, Mohammed Jasim Uddin

Mechanical Engineering Faculty Publications

The global reliance on fossil fuels and natural gas has largely dominated the energy production field, but due to finite resource depletion and escalating greenhouse gas emissions, the immediate exploration of sustainable energy alternatives to mitigate climate change and ensure resource security has been a major concern. There has been extensive research into other more renewable methods of energy production, such as wind and hydropower. Of these current energy generation types, there are many areas of untapped potential from the mechanical movements generated ambiently not only in the large scale of power generation but also on a smaller scale. The …

Identification Of Critical Brain Regions For Autism Diagnosis From Fmri Data Using Explainable Ai: An Observational Analysis Of The Abide Dataset, Suryansh Vidya, Kush Gupta, Amir Aly, Andy Wills, Emmanuel Ifeachor, Rohit Shankar

School of Engineering, Computing and Mathematics

BACKGROUND: Diagnosis of autism spectrum disorder (ASD) significantly improves quality of life, yet current diagnostic practices rely on subjective behavioural assessments. While machine learning models using functional Magnetic Resonance Imaging (fMRI) show promise for objective diagnosis, existing approaches have critical limitations. High-accuracy models often neglect interpretability, increasing clinical distrust, while interpretable approaches frequently suffer from low accuracy and lack neuroscientific validation of identified biomarkers. Furthermore, no studies have systematically benchmarked which interpretability methods are most effective for fMRI data, hindering the translation of Artificial intelligence (AI) findings into clinical practice.

METHODS: In this observational study, we used the Autism Brain …

Fort Hays State University Tiger Weekly, September 19, 2025, University Relations

Tiger Weekly Newsletters

No abstract provided.

Synoptic-Scale Meteorological Patterns Associated With Extreme Precipitation Over The Contiguous United States And Concomitant Seasonal And Regional Variability, Amy M. Johnson

Dissertations and Theses

Seasonal and spatial variations of synoptic-scale weather patterns concurrent to extreme precipitation days, defined as days above the seasonal 95th percentile of the daily precipitation distribution, are characterized over a 44-year period (1980-2023) for the Contiguous United States (CONUS). Using atmospheric reanalysis data and a grid-cell centered approach, we construct seasonal anomaly composite patterns for sea level-pressure (SLP), integrated water vapor transport, 500 hPa geopotential height (Z500), and 300 hPa wind speed. Atmospheric variables known to be important for extreme precipitation. By interpolating composites for each grid cell onto the same polar coordinate grid relative to the grid cell we …

A Computational Framework For Multi-Scale Analysis Of Mouse Cerebral Blood Flow Regulation, Hadi Esfandi

Electronic Theses and Dissertations 2020 - Present

Cerebral hemodynamic imaging is increasingly used as a non-invasive technique to study brain function and dysfunction in both research and clinical settings. Recent advances in imaging technologies have enabled high-speed, high-resolution, whole-brain measurements of blood flow and oxygenation. Improving the interpretation of these cerebral hemodynamic signals through a mechanistic understanding of their cellular drivers would enable more accurate characterization of brain function and pathology. However, no existing biophysical model fully captures the fine-grained dynamics observed in these signals. This dissertation introduces a biophysically grounded computational framework for multi-scale analysis of the mouse cerebral blood flow regulatory system, which captures mechanistic …

Pollen Loads Of Insects Caught In Cultivated Fields Of Oilseed Pennycress, Frank Forcella, Ellinor Sheik, Michael Zavada, Mark Bernards

The Great Lakes Entomologist

Although many insects are known to be associated with the floral canopies of oilseed pennycress (Thlaspi arvense), those that carry the crop’s pollen are unknown. During early spring of 2024 insects associated with pennycress flowers in Illinois and Minnesota were captured in sweep nets, frozen, sorted by species, and sonicated to remove pollen. Pollen grains were counted, and pollen loads per individual insect were calculated. Members of the orders Diptera, Hemiptera, and Hymenoptera accounted for 66%, 16%, and 14% of the 850 insects examined, but these same orders were responsible, respectively, for 18%, 3%, and 78% of the …

The Association Between Pre-Existing Medical Conditions And Trigger Finger Release In A Medically Underserved Region, Blake C. Martin, Manoj Peiris, Michael D. Sander

Research Colloquium

Background: Trigger finger is a relatively common condition that may affect daily activities. The Rio Grande Valley (RGV) is a health professional shortage area with a unique patient population. Our primary objective in this study was to analyze patients with various pre-existing medical conditions and determine if there was an association with the risk of trigger finger release surgery.

Methods: We conducted a retrospective chart review using the University of Texas Rio Grande Valley (UTRGV) UTHealth electronic database utilizing medical charts from January 1, 2018, to January 1, 2025. We collected and analyzed medical charts of patients who were diagnosed …

Chronic Conditions And Osteoporosis Risk: Insights From Penalized Logistic Modeling, Blake C. Martin, Juan Lopez Alvarenga

Research Colloquium

Background: The Rio Grande Valley (RGV) is a rural area with underserved, unique communities that may influence the health of the population. The primary objective of this study was to analyze factors associated with osteoporosis in individuals in the RGV to determine if the number of pre-existing medical conditions had an association with the frequency of osteoporosis. We hypothesized that individuals with more pre-existing medical conditions would be associated with an increased frequency of osteoporosis.

Methods: This study was a retrospective chart review from January 1, 2018, to January 1, 2025, using the University of Texas Rio Grande Valley (UTRGV) …

Unified Study Of The Classical Hall Effect, Carter J. Reed, Javier E. Hasbun, Wyatt E. Ackerman, L Ajith Desilva

Georgia Journal of Science

Germanium (Ge) samples with different doping types, acceptors (p-type) and donors (n-type), were studied to investigate charge carrier behavior. Carrier concentrations were found to be 1.16×10^21 m^(-3) for the p-type sample and 7.337×10^20 m^(-3) for the n-type sample. These experiments were conducted for the standard Hall effect (Hall voltage versus low magnetic field (B) values) as well as conductivity and Hall voltage versus temperature for different B-fields. The measurements versus temperature at zero-field allow us to obtain band gap ( Eg). While we investigate the conductivities for n-type and p-type doped samples, we also study the conductivity of an undoped …

Enhancing Fault Tolerance In Distributed Systems Using Shared Checkpoint Replica Mechanisms, Ameer A. Mousa, Mahdi S. Almhanna

Journal of Intelligent Informatics, Networking, and Cybersecurity

Fault tolerance is a critical requirement in distributed systems, as node and network failures can cause significant data loss, service disruption, and performance degradation. Traditional fault-tolerance methods often provide partial solutions, relying on separate recovery models for errors and delayed responses, while also incurring high resource costs. This paper aims to design and implement a more robust and efficient fault-tolerant architecture based on the concept of a shared checkpoint replica. In the proposed system, a master server and multiple slave servers collaboratively process client requests, share checkpoint replicas, and ensure seamless recovery in case of failures. To evaluate the approach, …

Optimization Of Multi-Target Interception Scheme Based On Performance Simulation Modeling, Hanwen Liu, Zhimin Zhuo, Xue Yang

Journal of System Simulation

Abstract: The air attack scenarios faced by air defense weapons and equipment show the trend of saturation, diversification and intelligence. It is very important to establish multi-target interception efficiency model and optimize interception scheme according to simulation. The current intercepting efficiency index mainly considers the whole operation process, and can not guide the optimization of the intercepting scheme of specific intercepting rounds. The generation of interception schemes mainly relies on experience and simple mathematical model, which is difficult to cope with the increasingly complex and changeable battlefield environment. Therefore, an interception scheme advantage index that comprehensively considers interception probability and …

September 2025 Cafe Newsletter, Elizabeth Reardon

CAFE Faculty Newsletters

Center for Advancing Faculty Excellence (CAFE) newsletter Sept. 2025.

A Case Study Of Long-Term Disease Burden In A Rural Community Near An Open Burn Facility, Arundhati Bakshi, Liana Baconguis, Md Abdullah Al-Mamun, Qingzhao Yu, Jennifer Richmond-Bryant, Stephania A. Cormier

School of Public Health Faculty Publications

Open burning and open detonation (OB/OD) of explosive and hazardous wastes creates various toxic waste products, including particulate matter, that is released into the atmosphere and capable of generating significant health impacts upon exposure. The last commercially run OB/OD thermal treatment facility in operation in the United States is located near the rural community of Colfax in central Louisiana. To evaluate the community’s concerns about the potential health impacts from air pollution due to the facility’s regular open burning of explosive and hazardous wastes, we examined the disease burden in Colfax compared to the surrounding parish and state. In a …

Allosteric Control Overcomes Steric Limitations For Neutralizing Antibodies Targeting Conserved Binding Epitopes Of The Sars-Cov-2 Spike Protein: Exploring The Intersection Of Binding, Allostery, And Immune Escape With A Multimodal Computational Approach, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Understanding the atomistic basis of multi-layer mechanisms employed by broadly reactive neutralizing antibodies of the SARS-CoV-2 spike protein without directly blocking receptor engagement remains an important challenge in coronavirus immunology. Class 4 antibodies represent an intriguing case: they target a deeply conserved, cryptic epitope on the receptor-binding domain yet exhibit variable neutralization potency across subgroups F1 (CR3022, EY6A, COVA1-16), F2 (DH1047), and F3 (S2X259). The molecular basis for this variability is not fully understood. Here, we employed a multi-modal computational approach integrating atomistic and coarse-grained molecular dynamics simulations, binding free energy calculations, mutational scanning, and dynamic network analysis to elucidate …

Framework For Assessing Sustainability In Industry 4.0: Supply Chain Optimization, Manufacturing Processes, And Energy Consumption Reduction, Mohamed Abouhawwash, Nebojsa Bacanin

Sustainable Machine Intelligence Journal

Decision making has uncertainty problems in evaluation process, so to overcome uncertainty existing fuzzy decision-making approaches, the neutrosophic set is used to solve incomplete data. Interval valued neutrosophic numbers (IVNNs) are used in this study to solve uncertainty problems. The IVNNs are used with the multi-criteria decision making (MCDM) methods. MCDM method is used to deal with different criteria and alternatives. This study proposes an MCDM methodology for assessment sustainability in industry 4.0. Twenty cases and ten alternatives are used in this study. The criteria weights are computed using the average method. The alternatives are ranked using the ARAS method. …

Design And Prediction Of Deep Fuzzy Neural Network, Chengbiao Wei, Taoyan Zhao, Jiangtao Cao, Ping Li

Journal of System Simulation

Abstract: A deep fuzzy neural network (DFNN) is proposed to solve the problem that the deep neural network has poor interpretability and the correction of the model is not targeted when dealing with the big data regression prediction problem. The proposed deep fuzzy neural network adopts an adaptive fuzzy Cmeans (AFCM) clustering algorithm in structural learning. The structure of the model, namely the number of rules and the antecedent parameters of the rules, is determined by calculating the introduced validity function. The identification of consequent parameters uses an improved grey wolf optimization (IGWO) algorithm. By replacing the linear decreasing strategy …

Kill Chain Efficiency Evaluation Model Based On Gray Dematel-Anp, Zejing Zhao, Junliang Shang, Yanpei Qin

Journal of System Simulation

Abstract: In modern conflict scenarios, the kill chain is integral to the comprehensive understanding, orchestration, and execution of military operations. Accurately appraising the efficiency of the kill chain is imperative for gaining insights into battle dynamics and strategically distributing military assets. However, traditional assessments of kill chain efficacy have been hampered by fragmented and isolated indicators that frequently overlook the interplay and influence among various segments of the kill chain. To address these limitations, based on the characteristics of each phase of the kill chain and the OODA loop theory, a new set of performance evaluation indices has been proposed. …

Optimization Method For Multi Agricultural Machinery Collaborative Operation Based On Genetic Algorithm And A* Algorithm, Yiran Yu, Huicheng Lai, Guxue Gao, Guo Zhang, Wangyinan Peng, Longfei Yang, Junhao Huang

Journal of System Simulation

Abstract: To address the uneven task distribution among multiple agricultural machines (referred to as farm machinery) and the high time cost due to numerous turning points at intersections, this paper proposes a task planning method that combines a pre-heat multi grouped genetic algorithm (PHMGA) with the turn A* algorithm (tA*). PHMGA allocates tasks to each piece of farm machinery based on the known environment, ensuring balanced workload through a cost objective function that considers travel, operation, and turning distances. It also designs various operators and strategies to search for nearoptimal solutions. The tA* algorithm is used to select paths …

Research On The Truth, Function And Common Principles Of Simulation, Haohua Xu, Bin Xiao, Yunhao Cui

Journal of System Simulation

Abstract: Simulation applications are becoming increasingly widespread and have a greater impact, while the theoretical foundation of simulation is relatively weak. This article provides a new definition of simulation by analyzing the common activities of simulation, which can include both virtual and real simulation forms; referring to Popper's three worlds theory, this paper discusses the objective authenticity of simulation from a philosophical perspective; From a methodological perspective, this paper elaborates on the methodological characteristics of simulation as an indirect cognitive object, revealing its significance in integrating human-machine intelligence and promoting knowledge evolution. It also discusses the common principles of simulation, …

A Model Combining Self-Attention And Weight Sharing For Human Activity Recognition, Lun Ma, Yue Yang, Daihe Wang, Guisheng Liao, Xing Li

Journal of System Simulation

Abstract: With the prevalence of wearable devices, human activity recognition based on wearable sensor data has garnered significant attention. The central issue in this field is how to extract effective behavioral information from raw sensor data to form corresponding feature vectors. Currently, convolutional neural networks and recurrent neural networks have been widely utilized for feature extraction from multisensory data. However, these networks struggle to globally capture the crucial temporal features inherent of human activity over time. To address this, a multi-CNN-BiLSTM-self attention (Multi-CBSA) model based on self-attention and weight sharing has been proposed, taking into consideration the logical correlations among …

Wingtip Docking Control Of Composite Aircraft Based On Adrc Theory, Chunlei Xie, Hongxia Hu, Weibo Han

Journal of System Simulation

Abstract: The process of wingtip docking in composite aircraft is challenged by significant unsteady vortex aerodynamic disturbances arising from the close-range coupling of wingtips, thereby posing considerable constraints on docking precision and flight safety. This study endeavors to address the intricate task of airborne wingtip docking control amidst wingtip vortex disturbances through a comprehensive investigation of airborne wingtip docking control technology, grounded in the tenets of active disturbance rejection control (ADRC) theory. Initially, a mathematical model encapsulating the dynamics of three-channel attitude/displacement during the docking operation, incorporating both the wingtip docking mechanism and the wingtip vortex model, is established. …

Solving The Vehicle Routing Problem Based On Deep Reinforcement Learning, Ming Jiang, Tao He

Journal of System Simulation

Abstract: The capacitated vehicle routing problem (CVRP) is a well-known combinatorial optimization challenge recognized as NP-hard due to its significant complexity. Building upon existing research, this paper introduces a novel end-to-end deep reinforcement learning approach based on a multi-pointer Transformer to tackle the CVRP. The proposed algorithm employs an invertible residual network in the encoder to encode input features, effectively reducing memory consumption. In the decoder, a multipointer network determines the probability distribution of solutions. To further enhance the performance of CVRP solutions, the algorithm leverages the symmetry in combinatorial optimization by implementing multi-trajectory parallel processing during both training …