Digital Commons Network^™

Exploring Coping Mechanisms For Colorism Among African American Women: A Focus On Social Support And Resilience, Zelina Marie Chinwoh

Walden Dissertations and Doctoral Studies

No abstract provided.

Exploring The Impact Of Mental Health On Childhood Obesity In Southern African American Youth Ages 12-18, Shari Scott Robinson

Walden Dissertations and Doctoral Studies

No abstract provided.

Experiences Of Recent High School Graduates In Missouri Regarding Stress Management And Coping Skills Within Their Health Education Curriculum, Courtney Faye Thomas

Walden Dissertations and Doctoral Studies

No abstract provided.

University Counselors' Experiences With Providing Services To Students Of Color, Kim Ridley

Walden Dissertations and Doctoral Studies

No abstract provided.

Standardized Pediatric Obesity Screening Guideline For Children Ages 5–17 Years, Jennifer Nacius

Walden Dissertations and Doctoral Studies

No abstract provided.

Evidence-Based Approaches To Managing Adolescent Aggression, April Dade

Walden Dissertations and Doctoral Studies

No abstract provided.

Beyond A Corrective Experience: Reimagining Liberation In Special Education, Erin Elise Macnabb

Doctoral Dissertations

This qualitative study establishes a critical bridge between special education and liberatory pedagogy, positioning these historically siloed fields as interdependent for systemic justice. While Special Education Teachers (SETs) daily work involves resisting systemic oppression, special education has been historically excluded from liberatory pedagogy and instead focused on medicalized models and deficit based assumptions. The separation of liberatory pedagogy and special education contributes to professional siloing and a culture of compliance that prioritizes bureaucratic processes over the meaningful and radical work of SETs.

The research utilizes a qualitative design rooted in Collaborative Critical Inquiry (CCI) where an intentional sample of veteran, …

Electronic Research Notebooks And Partnership Checklists: Fostering Cultured Collaboration In Evidence Synthesis Projects Using Labarchives And Swirl-Sr, Gary Kaplan, Mslis, Ahip, Abby Adamczyk, Mlis, Ahip, Emmett Booth, Mlis, Ahip, Stephanie Roth, Mlis, Ahip

Academic Commons and Scott Memorial Library Staff Papers and Presentations

Background

Librarians providing evidence synthesis services often face project management challenges, from tracking progress on search strategy development to clarifying team roles. Librarians have a variety of tools to address these challenges.¹ We propose using electronic lab notebooks (ELNs), which standardize how scientists record research progress. Institutions have adapted ELNs to protect intellectual property and improve rigor and reproducibility.

Although many published systematic reviews report following guidelines such as PRISMA, they still lack rigor and reproducibility.² Therefore, one of the authors developed the Standards for Working with Research Librarians-on Systematic Reviews (SWiRL-SR) checklist to facilitate collaboration and improve …

The Status Of The 2025 U.S.-Ukraine Minerals Agreement Under International Law And Why It Is Unsustainable

Washington International Law Journal

No abstract provided.

Automatic Speed Guidance Method And Simulation Evaluation For Trams At Intersections, Jing Teng, Wencong Tong, Zhongjie Zhang, Xing Yao, Junxian Li

Journal of System Simulation

To address the lack of speed regulation mechanism and the high dispersion of operational time in the current manual driving mode, this paper proposes an automatic speed guidance method for trams at intersections. Considering the speed disturbances caused by potential traffic conflicts at intersections, an initial decision point for safe passage speed at an intersection is established, dividing the operational curve into deterministic segments and disturbance-response segments.To verify the effectiveness of the method, a case study of Songjiang Tram Line 1 is conducted.Driving simulation experiments are performed to obtain manual driving trajectories, and a dynamic trajectory simulation model …

This Body Held Others, Mia I. Pons

LSU Master's Theses

The exhibition this body held others examines the body's invisible depths, the unseen, and its interpersonal memories. These ideas are explored through printmaking, book arts, and papermaking, with a focus on their connection and response to the materiality and nature of the body. Through the examination of my personal archive this work explores the collection, reconstruction, and recycling of imagery. The exhibition explores an unfolding story that examines how the ephemeral and corporeal survival and legacy of self and maternal lineage. These ideas are explored through the exhibitions three sections; emergence, body merger / departure, and the return. The attention …

Improving Graft-Versus-Host Disease Documentation Through Provider Education On An Epic-Based Gvhd Documentation Flowsheet, Emily Shearon

Doctoral Projects

Graft-versus-host disease (GvHD) is a common and serious complication following allogeneic hematopoietic stem cell transplantation (HSCT). Accurate documentation of GvHD severity and management is essential for clinical decision-making, interdisciplinary communication, and regulatory reporting to organizations such as the Foundation for the Accreditation of Cellular Therapy (FACT) and the Center for International Blood and Marrow Transplant Research (CIBMTR). Despite the availability of structured documentation tools within the electronic health record (EHR), their utilization is often inconsistent. The purpose of this quality improvement project was to evaluate whether a targeted provider-focused intervention could improve completion rates of a standardized GvHD documentation flowsheet …

Improving Early Detection Of Dementia In Primary Care, Terry E. Smith

Group: Northern Arizona University School of Nursing, DNP Doctoral Papers

Dementia remains under-detected in primary care despite recommendations to assess cognitive health during Medicare’s Annual Wellness Visit (AWV). Persistent gaps in clinician knowledge and workflow standardization contribute to delayed diagnosis and missed opportunities for early intervention. Strengthening early detection practices is essential to improving outcomes for individuals with dementia. This project aimed to improve early detection of dementia by implementing a brief clinician education program and evaluating its impact on dementia knowledge, mild cognitive impairment (MCI) diagnostic coding, and utilization of the Cognitive Assessment and Care Planning Visit (CACPV). The DNP (Doctor of Nursing Practice) project was conducted in two …

Volume 35, Issue 2: Contents

Washington International Law Journal

No abstract provided.

Titanium Dioxide: An Inquiry Into The Mechanisms And Implications Of Exposure In Gut Dysbiosis And Metabolic Disorders, Meghan Gardiner

Senior Honors Theses

Titanium dioxide (TiO₂) is one of the most prevalent food additives utilized in commercial products in the United States. While TiO₂ was originally hailed as a nontoxic and cost-effective additive, studies are beginning to reveal that TiO₂ is not as safe as it once seemed. TiO₂ may contribute to the development of insulin resistance and metabolic disorders through direct and indirect mechanisms. The compound induces gut dysbiosis, leading to alterations in bacterial metabolites and pro-inflammatory cytokines, which results in the selective resistance of glucocorticoid receptors. Additionally, TiO₂ itself can translocate from the gut to …

Capacity Market Trading Strategies Of Generators Based On Per-Maddpg Algorithm, Yanbin Li, Zhaolun Pan, Xinyue Ma, Minghao Song, Yujie Hu, Xiaoda Xue

Journal of System Simulation

Considering the issue of how power generators trade off their quantity and price bidding strategies to maximize profits in different capacity market environments, a capacity market bidding equilibrium model is constructed. Recognizing the limitations of traditional solution methods, which rely on the assumption of complete information and have low utilization of historical trading strategy information, a capacity market trading simulation method based on prioritized experience replay multi- agent deep deterministic policy gradient (PER-MADDPG) is proposed. The action space is constructed using quantity bidding strategy and price bidding strategy, and the state space is constructed using historical transaction strategies and winning …

Vol 6. May '26 Cover, Publishing, And Table Of Contents, Donna L. Williams

Journal of the Louisiana Public Health Association

No abstract provided.

An Automated Generation Method For Combat Simulation Scenarios Based On Large Language Models, Zhiming Dong, Zhongqi Hu, Haoran Dai, Jiancheng Gao

Journal of System Simulation

To address the issue of low efficiency in generating traditional army tactical combat simulation scenarios, an automated generation method based on large language models is proposed. The large language model invokes a semantic segmentation algorithm to parse and restructure the combat scenario, forming semantic modules. Utilizing a multi-agent collaborative framework based on the model contextual protocol, the large language model drives each agent to extract simulation elements from the corresponding semantic modules, constructing a knowledge graph of scenario elements. Using this knowledge graph as a retrieval medium, the method employs a dense retrieval algorithm to achieve precise matching between simulation …

Robust Identification Of Black-Box Nonlinear Ssm Using Expectation-Maximization, Xiaonan Li, Tao Chao, Ping Ma, Ming Yang, Yuxuan Wang

Journal of System Simulation

To address the robust identification problem of nonlinear state space models (SSM) with outliers, missing observations, and unknown state equations, this paper proposes a modeling method based on eigenfunction expansion, Gaussian-process state-space models (GP-SSM), and Student-t distribution. The proposed approach consists of: modeling the state transition function using eigenfunctions and pre-encoding the priors of basis function coefficients via GP-SSM to enhance flexibility; modeling observations as a Student-t distribution with unknown parameters to enhance robustness against outliers; proposing the enhanced particle Gibbs with ancestor sampling (EPGAS) algorithm to adapt to state estimation in scenarios with missing observations; and deriving unknown model …

Multi-Agent Cbs Path Planning Algorithm Based On Minimum Planning Margin First, Longxiao Liang, Jianlin Mao, Niya Wang, Chengyuan Fang, Wenna Zhou

Journal of System Simulation

To address the problems of chain effect and insufficient solving efficiency in the conflict tree (CT) expansion of the traditional conflict-based search (CBS) framework, a minimum-margin-first CBS algorithm based on planning margin was proposed. The calculation of planning margin was introduced into the underlying A* search, and the robots with the minimum margin were prioritized in the high-level conflict resolution, to suppress the chain expansion of the CT while ensuring path optimality.Simulation experiments show that the proposed algorithm significantly reduces the amount of CT node expansion and the number of root node conflicts and effectively improves the solving efficiency, …

Topology Identification Of Complex Dynamical Networks Under Dynamical Saturation Inputs, Haoyu Wang, Yayong Wu, Guoping Jiang, Ying Zheng, Xuanxin Zhou

Journal of System Simulation

In view of the problem that the controller inputs in actual engineering systems are vulnerable to the constraints of dynamical saturation and delayed dynamical saturation, which makes it difficult for the topology identification of complex dynamical networks to adapt to real physical scenarios, a topology identification method based on the drive-response mechanism was proposed. A response network with the same dynamical characteristics and node scale as the original network was constructed, and the dynamical equation of synchronization error between the drive-response networks was established. A controller with dynamical saturation and delayed dynamical saturation and a topology identifier were designed, and …

Robust Two-Stage Mimo-Ofdm Channel Estimation Method Against Sensing Errors, Yi Peng, Jun Wang, Qingqing Yang, Jianming Wang, Hui Li

Journal of System Simulation

To address the challenges of performance degradation, high pilot overhead, and high computational complexity in traditi onal channel estimation methods for integrated sensing and communication (ISAC) assisted MIMO-OFDM systems when radar sensing information contains errors, this paper proposes a robust two-stage sparse channel estimation framework designed to be tolerant of sensing errors. In the first stage, a residual energy weighted simultaneous orthogonal matching pursuit (REW-SOMP) algorithm is designed. Leveraging locally adaptive dictionary expansion and a residual- weighted path selection mechanism, it accurately captures communication-associated paths even under sensing errors. The second stage introduces an adaptive penalty factor alternating direction method …

Dynamic Task Planning For Wargaming Based On Large Language Models, Yingang Liu, Ming Ma, Ronghua Zhang

Journal of System Simulation

To address the problems of great difficulty in intelligent decision-making and insufficient dynamism in task planning caused by the complex adversarial environment and strong uncertainty in wargaming tasks, this paper proposed a hierarchical Agent collaborative decision-making framework based on large and small model synergy.Through a multi-level structure, the hierarchical decoupling and dynamic coordination of battlefield tasks were achieved. A memory management module was constructed, and a query optimization mechanism driven by large language models was introduced to dynamically perceive the decision-making process and query intent, completing the semantic reconstruction and context completion of raw queries. A time-driven two-stage task …

Ultra-Short-Term Photovoltaic Power Prediction Based On Improved Patchtst Considering Data Drift, Huawei Mei, Penghui Yang, Yang Yu

Journal of System Simulation

Existing PV power prediction methods often suffer from limited accuracy and robustness due to three key shortcomings: relying on single-point mapping that cannot fully extract local temporal patterns; inadequate exploration of the global temporal dependencies in PV output, and failure to account for prevalent data drift phenomena. To overcome these limitations,an improved patch time series transformer (PatchTST) based approach is proposed for ultra-short-term PV power prediction. The methodology applies rough set theory for feature dimensionality reduction, effectively preserving critical decision information by analyzing both feature-label relationships and inter-feature correlations. An enhanced PatchTST model with a modified channel-independent mechanism extracts …

Sos Effectiveness Evaluation Method Based On Fuzzy Functional Dependency Network Analysis, Hongjia Su, Cheng Zhang, Fei Liu

Journal of System Simulation

Functional dependency network analysis (FDNA) enables modeling functional dependencies among equipment in a system of systems (SoS) and then computing the whole SoS effectiveness based on the effectiveness of each equipment, thus overcoming the deficiency of traditional SoS effectiveness evaluation based on tree-like index systems. However, critical parameters such as strength/criticality of dependency in this methodology currently rely on subjective empirical assignments, where the deviations resulting from subjectivity may compromise the accuracy of effectiveness evaluation. To address this limitation, this paper proposes a fuzzy FDNA (FFDNA)-based SoS effectiveness evaluation method. This method constructs a functional dependency network (FDN) model …

Multi-Agent Reinforcement Learning Method For Wargame Simulation Based On Suboptimal Demonstration Guidance, Zicong Zhou, Junjie Zeng, Yue Hu, Zhengqiu Zhu, Quanjun Yin

Journal of System Simulation

To address issues such as fixed behavior patterns and insufficient adaptability in complex adversarial environments exhibited by traditional wargame agent decision-making models, this paper proposes a multi-agent reinforcement learning method based on suboptimal demonstrations (MARLSD). The proposed method integrates reward relabeling with a self-imitation learning mechanism, effectively improving the training efficiency of multi-agent reinforcement learning algorithms in environments with large state-action spaces and sparse rewards, even when only a small number of suboptimal demonstrations are available, while encouraging agents to explore better strategies. Experimental results show that, compared with baselines such as QMIX and MAGAIL, MARLSD significantly improves performance and …

Research On Calculation Model Of Excavation Resistance Under Heterogeneous Soil Conditions, Xin Zhang, Ping Zhang, Chen Zhang, Wei Liu, Boyang Han

Journal of System Simulation

To address the problem of insufficient prediction accuracy of excavation resistance in heterogeneous cohesive soil, a spatial calculation model of excavation resistance at each excavation stage under heterogeneous soil conditions was proposedbased on the cutting wedge model, comprehensively considering multi-dimensional factors such as bucket geometry, side plate effect, lateral force, and inertia. By taking a small crawler hydraulic excavator as the research object, a coupled simulation model of boom multi-body dynamics and soil-rock particle discrete element was established, and the theoretical model was validated through the co-simulation of excavation operations. The simulation results indicate that under the working …

Research On Completion Method For Trajectory Based On Image Representation And Collaborative Feature Perception, Ye Tao, Jinhui Tang, Chen Zhou, Chong Wang

Journal of System Simulation

To address the constraints imposed by missing trajectory data in surveillance systems on the efficacy of civil aviation safety monitoring, as well as the limitations on the development and application of advanced technologies within trajectory-based operational frameworks, a completion method for trajectory based on image representation and collaborative feature perception was proposed. A conversion strategy for trajectory image representation was designed to reformulate the trajectory completion task as a deterministic image completion problem, effectively circumventing the cumulative error problem of traditional time-series data caused by the limitation of recurrent neural network inference mechanisms.A regression model fusing a multi-kernel hybrid …

Robot Trajectory Planning And Adjustment Method For Abnormal Pose Of Actuator, Lang Qin, Jiacheng Xie, Xiaojun Qiao, Xuewen Wang, Zhijie Xiao

Journal of System Simulation

To address the influence of the abnormal pose of the robot actuator on the robot trajectory, an adaptive planning and adjustment method of trajectory based on virtual-real fusion was proposed. AR technology was introduced to couple with the robot kinematics model, and the hardware dependence on multiple sensors was replaced by synchronous comparison of three-dimensional virtual and real poses; AR gestures and voice interaction were combined to simplify the operation process; based on the actual pose of the actuator, the trajectory of the robot terminal axis was dynamically adjusted. The experimental results show that this method breaks through the technical …

Hyperspectral Anomaly Detection Algorithm Based On Window Reconstruction And Collaborative Representation, Shuanghao Fan, Fang He, Jianwei Zhao, Haojie Hu, Fengchao Zhu, Xiangyang Li

Journal of System Simulation

Hyperspectral anomaly detection refers to identifying ground objects that deviate from normal background distributions and have low probability and small scales from scenes involving mixed multi- class ground objects, spectral feature overlaps, and noise interference. This technology has received extensive attention in recent years. Although collaborative representation-based anomaly detection algorithms demonstrate excellent performance in hyperspectral image anomaly detection, their time costs are too high to enable widespread application.To address this issue, this paper proposes a hyperspectral image anomaly detection algorithm based on window reconstruction and collaborative representation, which consists of two stages. Window reconstruction is performed on hyperspectral background …