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Of Rollercoasters And Resilience: The Role Of Ceos’ Biases And Heuristics For Large Firms’ Technological Innovation, Cristina O. Vlas, Radu E. Vlas

International Journal of Applied Management and Technology

How do CEOs’ personality biases and motivational heuristics influence innovation in large firms? Because large-firm innovation is more common and less risky, overlooked factors—such as narcissism, self-monitoring, and promotion or prevention foci—become pivotal. Drawing on these traits, we found that narcissistic CEOs differ from self-monitoring CEOs in driving innovation. Moreover, the effect of self-monitoring CEOs depends on whether their regulatory focus is oriented toward promotion or prevention. However, this interplay between personality and motivation does not apply to narcissistic CEOs, suggesting that certain characteristics remain relatively fixed. These findings advance the understanding of how CEO traits shape large-firm innovation and …

Nursing Students As Advocates: Addressing Social Determinants Of Health Through Service-Learning, Rebekah Mullins

Nursing Theses and Dissertations

Advocacy is at the heart of nursing practice, and advocating for the social determinants of health (SDOH) is crucial when providing care to patients from vulnerable populations. Service-learning is a strategy that can be used to teach students advocacy skills. Chapter 2 of this dissertation portfolio presents a concept analysis that explores the definition of advocacy using the Walker and Avant method (2019). The concept analysis informed the development of the case study presented in Chapter 3 and the research study presented in Chapter 4. The portfolio includes original, qualitative research that was guided by the interpretive descriptive method. The …

Decreasing Symptoms Of Burnout In Nurses Through Mindfulness Training, Mckenzie Posey

Biennial Convention (CONV)

Background: An important initiative in many healthcare systems is aiming to reduce stress, not only because of the psychological effects, but because of the effect it has on the safety of our patients and their outcomes. Nurses’ stress levels have increased over the years and have an impact on healthcare outcomes, staff satisfaction and retention, and patient safety.

Problem: Patient safety and quality of care are the most important pieces of healthcare, but taking care of our healthcare providers should also be at the top of the list to address this global, national, and local nursing issue. Mindfulness-Based Stress Reduction …

Implementation Of A Dementia-Specific Advance Care Planning Tool: A Quality Improvement Pilot, Stephanie Nichole Johnson

Biennial Convention (CONV)

Purpose: There are 55 million cases of dementia worldwide and the cost of care for these individuals is estimated to rise to $2 trillion by 2030. Dementia-specific Advance Care Planning (ACP) can help to reduce the burdens of providing care to those diagnosed with dementia. This study sought to determine if the implementation of a dementia-specific ACP tool increases knowledge and decision-maker confidence, as well as decrease inappropriate healthcare utilization rates.

Method: At a Program for All-Inclusive Care for the Elderly (PACE), individuals diagnosed with a cognitive deficit (CD) and their surrogate decision-maker (SDM) were recruited as dyads to participate …

Nursing Education And Practice In The Afp: Responding To The Vucad National Security Threats, Darlene Dialogo Flores

Biennial Convention (CONV)

INTRODUCTION: The COVID-19 pandemic has underscored the critical importance of healthcare, revealing both the system's strengths and vulnerabilities. This study focuses on the preparedness of the Philippine healthcare workforce, particularly among military and civilian nurses in the AFP, to handle national security threats in a VUCAD environment. It evaluates whether current nursing education equips nurses with the skills needed to face complex challenges. This study emphasizes the need for holistic national security strategies and proposes enhancing nursing education to prepare for 21st-century security challenges, focusing on CBRNE, climate change, cyberattacks, and emerging viruses.

OBJECTIVES: Determine the responsiveness and relevance of …

Developing Interventions To Improve Future Age And Situation Specific Mask Wearing, John Knight, Barbara R. Medvec, Patrick Hammett

Biennial Convention (CONV)

Background: Outcomes from the COVID-19 pandemic indicate that masks lower a person’s exposure to respiratory infections. The Centers for Disease Control and Prevention (CDC) continues to recommend situation-specific mask-wearing to protect oneself from COVID-19 variants and other viruses. Yet, the clinical community continues to struggle with targeting interventions to increase the likelihood of mask-wearing when the risk of virus exposure is higher in the post-pandemic environment. In this study, we applied the Health Belief Model (HBM) to identify the attitudes and beliefs influencing mask-wearing and recommend targeted interventions for low-frequency mask wearers in CDC recommended situations.

Methods: We administered a …

A Multi-Patient Sim To Increase Exposure To Diversity And Evaluate Clinical Judgement, Elizabeth Holtel, Gina Herron, Megan Stuffle, Jennifer Remick

Biennial Convention (CONV)

Lack of readiness for practice in newly licensed Registered Nurses (RN) is not a new problem in nursing education. Existing literature demonstrates a preparation-practice gap, lack of practice readiness, and a crisis of competency in newly licensed RN. A large-scale study by Kavanagh and Szweda¹ found that only 20-24% of newly licensed nurses demonstrated acceptable levels of practice readiness. With over 10,000 assessments collected to date, the researchers note a continued decline in practice readiness with 2020 data showing only 9% of newly licensed nurses demonstrating acceptable levels². To address this gap, a multi-patient simulation-based experience (SBE) …

“They Are Having Sex!” Hbcu Students Awareness Of Sexual Risk Associated With Hiv Prevention, Tyesha Karume

Biennial Convention (CONV)

In 2020, 20% of new HIV diagnoses in the U.S. were among individuals aged 13-24 transitional age youth (TAY), with 85% being male and 54% Black/African American (CDC, 2022a). Black/African American TAY acquire HIV at disproportionately higher rates than other ethnic groups (CDC, 2023e). A study of students at Historically Black Colleges/Universities (HBCUs) revealed that women reported 2-5 sexual partners, while men reported six or more, with up to 55.5% being inconsistent in condom use (Marshall et al., 2020). Despite this, 89% of students believed their sexual behaviors posed little to no HIV risk (Okeke et al., 2021).

This project …

Faculty Advisors Perspectives Of Baccalaureate Nursing Students' Attrition: A Qualitative Study, Danielle E. Shaver, Jennifer Dunbar Viveiros, Susan Hunter Revell, Christine Ann Devine

Biennial Convention (CONV)

Background: Exploring faculty advisors' perspectives on voluntary attrition is essential to optimize resources and increase the number of nursing graduates. This qualitative study aimed to uncover nursing faculty advisors' perceptions of the extrinsic factors, intrinsic factors, and mediators that influence four-year baccalaureate students' decisions to voluntarily leave nursing programs.

Method: A qualitative descriptive design utilized Rubin and Rubin’s (2012) interviewing methodology to solicit narrative accounts from 12 experienced nursing faculty advisors in four-year baccalaureate nursing degree programs.

Results: The semi-structured interviews revealed four intrinsic themes: preparedness, fear, maturity, and personal crisis. Four extrinsic themes emerged: external motivations, interpersonal relationships, program …

Love At A Distance: Exploring Perceptions Of Long-Distance Relationships Through Q Methodology, Ljubica Ivanovic Klobcic

Theses and Dissertations

With technology advancing and making it easier for individuals to connect and keep in touch, long-distance romantic relationships (LDRRs) have become increasingly common. While some people thrive in these relationships despite physical separation, others find the experience stressful and unsatisfying. This study explores how individuals perceive and navigate LDRRs and what their experiences are. Using Q methodology, participants sorted and ranked statements related to their experiences. Factor analysis revealed three unique groups: Traditional Romantics, who see their relationships in traditional terms despite technology use; Debbie Downers, who perceive distance as a burden and do not feel that technology improves their …

East Greenland Ice Sheet Retreat History From Scoresby Sund And Storstrømmen Glacier During The Last Deglaciation, Jacob T.H. Anderson, Nicolás E. Young, Allie Balter-Kennedy, Karlee K. Prince, Caleb K. Walcott-George, Brandon L. Graham, Joanna Charton, Jason P. Briner, Joerg M. Schaefer

Earth and Environmental Sciences Faculty Publications

The lack of geological constraints on past ice-sheet change in marine-based sectors of the Greenland Ice Sheet (GrIS) following the Last Glacial Maximum limits our ability to assess (1) the drivers of ice-sheet change, and (2) the performance of ice-sheet models that are benchmarked against the paleo-record of GrIS change. Here, we provide new in situ¹⁰Be surface exposure chronologies of ice-sheet margin retreat from the outer Scoresby Sund and Storstrømmen Glacier regions in eastern and northeastern Greenland, respectively. Ice retreated from Rathbone Island, east of Scoresby Sund, by ∼ 14.1 ka, recording some of the earliest documentations of …

Improvement Of Slam Localization Accuracy In Ar By Enhancing Yolov8, Jia Liu, Zengwei Zhang, Dapeng Chen, Nanxuan Huang, Bin Wang, Hong Song

Journal of System Simulation

Abstract: In the presence of dynamic interference in the environment, traditional simultaneous localization and mapping (SLAM) methods often experience reduced precision and stability in the registration of virtual objects during three-dimensional registration in augmented reality (AR). To address these issues, an improved method for dynamic scenes based on semantic segmentation and optical flow tracking was proposed. The convolutional block attention module (CBAM) attention mechanism was incorporated into YOLOv8 to enhance its focus on dynamic objects in the environment, thereby improving detection performance and accuracy. The semantic segmentation functionality of the improved YOLOv8 was integrated into the front-end of ORB-SLAM3 to …

Parking Space Reasoning Model For Complex Scenarios, Congling Zhou, Chunpeng Wang, Qiwei Xie, Yongqiang Wang, Lijun Shen

Journal of System Simulation

Abstract: In the industrialization process of the combined driving assistance system, complex parking environments bring many challenges, such as occlusion of parking spaces, uneven lighting, and missed and false detections. To address these issues, a parking space reasoning model named PIPS-Net was proposed through PINet optimization. In terms of network architecture design, the model deeply integrated the stacked hourglass network with the recurrent feature-shift aggregator (RESA) to construct a context feature extraction architecture, which enhanced the feature reasoning ability in complex scenarios. Meanwhile, it reconstructed the output to meet the requirements of parking space detection tasks, thereby jointly improving the …

Research On Vehicle Path Optimization Algorithms For Urban Logistics And Distribution, Zhenpeng Ma, Hanyang Jiao, Zhe Zhang, Cheng Liu, Bo Jiang, Lin Wang

Journal of System Simulation

Abstract: Existing optimization algorithms for solving the vehicle routing problem with time windows (VRPTW) are prone to fall into local optimal solutions and have slow convergence speed. To address this issue, a K-means clustering algorithm and improved large neighborhood search algorithm (K-means-ILNSA) was proposed. A strategy of clustering before optimization was adopted, and the K-means algorithm was adopted to group the customers to be delivered, so as to improve the optimization efficiency. The genetic algorithm was adopted to optimize each group of customers generated by clustering separately to initially plan the distribution routes. The large neighborhood search (LNS) algorithm was …

Auv Path Planning Based On Behavior Cloning And Improved Dqn In Partially Unknown Environments, Lijing Xing, Min Li, Xiangguang Zeng, Ping Zhang, Bei Peng

Journal of System Simulation

Abstract: To address the problems of large randomness and slow convergence of the DQN dynamic path planning algorithm for a single autonomous underwater vehicle (AUV) in a partially unknown environment, a path planning method combining behavior cloning with A* algorithm and DQN (BA_DQN) was proposed. Based on the known environmental information, an improved A* algorithm incorporating ocean current resistance was proposed to guide DQN, thereby reducing the randomness of the DQN algorithm. By considering the complexity of the marine environment, the sampling probability was improved again after expanding the positive experience pool to enhance the training success rate. To address …

Bayesian Network Parameter Learning Based On Ahp-Dst Fusion Of Expert Prior Knowledge, Haiyang Chen, Hongkai Lin, Zhifang Ren, Jing Liu, Jing Zhang

Journal of System Simulation

Abstract: Aiming at the problem of low accuracy of BN parameter learning due to the uncertainty of a single expert prior knowledge under the condition of small sample data set, a BN parameter learning method based on AHP-DST fusion expert prior knowledge was designed. The synthetic prior knowledge of experts was calculated by using the thought of analytic hierarchy process combined with the rules of evidence theory synthesis. The expert comprehensive prior knowledge was added to the normal distribution and combined with the monotonicity constraint to obtain the virtual sample information. The virtual sample information was added to the Bayesian …

Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang

Journal of System Simulation

Abstract: A finite-time fault-tolerant control scheme based on backstepping was proposed for the attitude tracking control problem of quadrotor UAVs. A finite-time neural network disturbance observer was designed, which could quickly compensate for the impacts of actuator failures and external disturbances, thereby enhancing the system's robustness. A first-order command filter and a compensation mechanism were introduced, which could avoid the computational complexity caused by differentiating the virtual control law and eliminate the influence of filtering errors. The hyperbolic tangent function was selected as the constraint function for the input torque, which restricted the input signal to prevent excessive magnitude …

Research On Path Smoothing Processing Of Mobile Robot Based On Improved A* Algorithm, Mengyuan Chen, Guifang Qiao, Xu Zou, Jiayu Cao, Lei Tian

Journal of System Simulation

Abstract: Traditional bidirectional A* algorithm has many path inflection points, undergoes smoothness, and faces diagonal obstacles in path traversing. Therefore, an improved bidirectional A* algorithm was proposed. Local path constraint search was added to the forward search and backward search, respectively to solve the problem of planning paths traversing diagonal obstacles, and the effectiveness of the improved bidirectional A* algorithm to avoid traversing diagonal obstacles was verified through simulations. The path inflection points were optimized by introducing the cubic B-spline curve, and the paths before and after smoothing were tracked and controlled, respectively by using the differential-driven mobile robot. The …

Boolean Network Model Optimization Based On Neural Network And Genetic Programming, Jinlin Tang, Yan Wang, Xiang Liu, Tuanjie Wang, Zhicheng Ji

Journal of System Simulation

Abstract: To address the issues of complex node relationships and low accuracy in large-scale Boolean network inference, a new optimization algorithm integrated with long short-term memory (LSTM) networks and genetic programming was proposed. An enhanced LSTM network combined with a self-attention mechanism was designed to extract potential regulatory nodes from time-series data. These nodes were utilized as terminals of the syntax tree for the design of the genetic programming algorithm, and new operators were introduced to optimize Boolean function search. Experimental results have demonstrated that the proposed method significantly outperforms the most advanced existing algorithms in inference accuracy. The Boolean …

Twin Modeling Of Gearbox Fault Early Warning System Based On Spatio-Temporal Characteristics, Yuanxing Tian, Zeyin Han, Ning Wang, Baoding Su, Weilin Xiang

Journal of System Simulation

Abstract: The wind turbine gearbox cannot effectively collect vibration signals under complex faults, which leads to the decline of fault early warning accuracy of wind turbine gearbox. To address this issue, this study investigated the twin modeling of gearbox fault early warning system based on spatio-temporal characteristics. Through the information acquisition subsystem and optical fiber sensing technology, the time sequence and spatial position data of the wind turbine gearbox during operation were collected in real time to obtain spatio-temporal characteristic data. By using the twin space, the collected spatiotemporal characteristic data of the gearbox were transmitted to the virtual space. …

Image Feature Point Matching Algorithm Based On Attention And Hierarchical Features, Na Chen, Jiajia Bai, Qiyin Zhou, Jialin Li

Journal of System Simulation

Abstract: Feature point detection and matching is one of the core technologies in the field of intelligent driving. Aiming at the lack of consistency and continuity of feature points extracted by the existing algorithms, as well as the problem of easily ignoring the contextual semantic information when matching, this paper proposes an image feature point matching algorithm based on attention and hierarchical features (AHMF). In the feature point detection stage, differential interaction attention module (DIAM) is proposed to enhance the model's attention to the salient regions so as to improve the robustness of the feature points; further introduction of hierarchical …

Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang

Journal of System Simulation

Abstract: Evolutionary reinforcement learning currently suffers from low sample efficiency, a single coupling method, and poor convergence, which can affect its performance and scaling. To address this issue, an improved algorithm based on elite gradient instruction and double random search was proposed. The direction of the reinforcement strategy gradient update was corrected by introducing elite strategy gradient guidance carrying evolutionary information during reinforcement strategy training. Double stochastic search was used to replace the original evolutionary component, reducing the complexity of the algorithm while making the policy search meaningful and controllable in the parameter space. The introduction of complete replacement information …

Research On Temperature Compensation Technology Of Fiber Optic Gyroscope Based On Iscso-Bp Neural Network Model, Zhili Zhang, Jin Liu, Zhaofa Zhou, Zhe Liang, Yunhao Zhang

Journal of System Simulation

Abstract: To address the issue that changes in ambient temperature significantly affect the output accuracy of the fiber optic gyro (FOG), which causes zero bias drift, increases measurement errors, and limits their application accuracy in complex environments, a temperature compensation model based on BP neural networks was proposed. To improve the performance of neural networks, the sand cat swarm optimization (SCSO) was improved, and the improved SCSO (ISCSO) was used to optimize the weights and thresholds of BP neural networks. Experimental results show that using the ISCSO-BPNN temperature compensation model to compensate for the gyro's temperature errors significantly improves the …

Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu

Journal of System Simulation

Abstract: Due to the difficulty in reflecting the various information activities and interactions within the command information system using general modeling methods for complex system structure, the advantages of supernetwork in characterizing node heterogeneity and link multiplicity of the system were utilized. Based on the research on the mapping mechanism of the command information system across three domains, the dynamic and multifunctional properties of the functional network structure were analyzed. A dynamic supernetwork model based on task timing was constructed considering task requirements, providing model support for further research on complex interaction relationships in the command information system. The dynamic …

Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang

Journal of System Simulation

Abstract: To solve the problem of misidentification of star maps due to time sequence mismatch in the hardware-in-the-loop simulation system of star navigation, where star trackers with different shutter types (global shutter and rolling shutter) and star simulators with varying refresh display methods (whole frame refresh and line sweep refresh) operated without synchronization, a time sequence design method of the dynamic simulation scene for starlight navigation without the need of external synchronization signals was proposed. The method could design the refresh frequency and duty cycle of the corresponding star simulators according to the detector integration time of the tested star …

Robot Path Planning Optimization Based On Fusion Of Improved Ant Colony Algorithm And A* Algorithm, Lanying Yang, Chao Li, Haifeng Zou, Jiangtao Wan, Renqiang Zhang, Hui Liu, Hong Lu

Journal of System Simulation

Abstract: To improve slow search efficiency and achieve real-time obstacle avoidance in traditional ant colony algorithms, an adaptive ant colony algorithm was proposed. A guidance direction mechanism was introduced to shorten the time of node selection. The A* algorithm's path-finding mechanism was introduced into the heuristic function to reduce the length and number of circles of the optimal path solution. The route planned by the traditional A* algorithm was used as the initial iteration data of the ant colony algorithm in global path planning, so as to solve the problem of slow initial convergence of the ant colony algorithm. The …

Fy26 Dcag Committee 11.18.2025, Julia Lovett

HELIN Board of Directors reports

Minutes from the DCAG Affinity Group 11.18.2025

Development Of A Low-Barrier, Reimbursable Take-Home Naloxone Program At A Regional Health System, Kory S. London, Sejal Patel, Drew Lockstein, Jamal Rashid, Dennis Goodstein, Richard Pacitti, Tareva Warrick-Stone, Frederick Randolph, Alan Cherney, Karen Alexander, Megan Reed

Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers

INTRODUCTION: Take-home naloxone (THN) programs in emergency departments (ED) can reduce opioid overdose deaths by providing naloxone directly to at-risk patients before discharge. However, sustainable models that integrate reimbursement and workflow alignment remain limited.

METHODS: A reimbursable ED-led THN program was developed across a large regional health system. The program used electronic health record (EHR)-integrated ordering, on-site kit dispensing, and third-party insurance billing when available. Kits were stocked in automated medication dispensing systems and supplemented by city-provided stock for uninsured patients. Pilot outcomes included kits dispensed and reimbursement rates across eight participating EDs.

RESULTS: A total of 2,520 naloxone kits …

Optimization Of Service Caching And Computation Offloading In Digital Twin Cloud-Edge Networks, Jiayu Zheng, Zhuxue Mai, Zheyi Chen

Journal of System Simulation

Abstract: In mobile edge computing (MEC), to satisfy diverse user demands by jointly optimizing service caching and computation offloading and address low-efficiency resource utilization caused by irrational resource allocation, this paper proposed a novel joint optimization of service caching and computation offloading with a convex-optimization-enabled deep reinforcement learning (JCO-CR) method. Additionally, a new model for digital twin cloud-edge networks (DTCEN) was constructed. The joint optimization of service caching and computation offloading was decoupled into two sub-problems, which were solved by an improved deep reinforcement learning method and convex optimization theory, respectively. Simulation experiments demonstrate that the proposed JCO-CR method …

Research On Cgf-Oriented Natural Language Interaction Framework, Xinmeng Li, Kai Xu, Yue Hu, Hesong Huang, Quanjun Yin

Journal of System Simulation

Abstract: To address the mismatch between existing natural language interaction frameworks and training tasks in simulation-based military training, which limits smooth interaction between trainees and Computer Generated Forces (CGF), this paper proposes a Natural Language Interaction framework for Computer Generated Forces (NLI4CGF). The framework analyzes the logic and functional requirements of natural language interaction between trainees and CGF, and establishes an interaction architecture tailored for military simulation training scenarios. It supports semantic parsing and knowledge query tasks within a prototype system developed for infantry squad simulation training. Experimental results demonstrate that the proposed model performs effectively, meets the requirements of …