Digital Commons Network^™

Gust-Induced Aerodynamic Performance In Insects' Forward Flapping Flight, Arash Farsani, Ori Stearns, Gal Ribak, Roi Gurka

Physics and Engineering Science

Flapping-wing flight is inherently unsteady, where atmospheric gusts can substantially degrade the aerodynamic performance when their characteristic time scales are comparable to the wingbeat period. This study presents a numerical investigation and time–frequency characterization of gust-induced aerodynamic response of flapping wings of varying size, inspired by the flight of a longhorn beetle, Batocera rufomaculata. Geometrically similar wings spanning the biological range were simulated in forward flight under identical prescribed kinematics and a transient frontal gust with a smoothly ramped profile. Three-dimensional unsteady Reynolds-averaged Navier–Stokes simulations using the shear stress transport k–ω turbulence model were performed to resolve the instantaneous pressure …

Upar-Guided Dendrimer Gel Nanoparticles Reprogram Inflammation To Stabilize Atherosclerotic Plaques, Hsin Yin Chuang, Huari Kou, Yue-Wern Huang, Hu Yang

Biological Sciences Faculty Research & Creative Works

Atherosclerosis is characterized by lipid deposition, chronic inflammation, and apoptosis within the arterial wall, leading to plaque progression and instability. Current lipid-lowering therapies fail to fully address residual cardiovascular risk driven by local inflammation and cell death. Here, we report the development of uPA-functionalized, rapamycin-encapsulated dendrimer nanoparticles (G5PM-uPA/RA) that preferentially accumulate in urokinase plasminogen activator receptor (uPAR)-enriched atherosclerotic plaque, including macrophage- and apoptosis-rich lesion microenvironments. G5PM-uPA/RA was constructed by cross-linking reaction-enabled flash nanoprecipitation in a custom-made multi-inlet vortex mixer, followed by thiol-maleimide conjugation of uPA for uPAR-guided targeting. The nanoparticles demonstrated uniform morphology, favorable stability, and efficient rapamycin loading. In …

Electrospinning Of Covalent Organic Frameworks (Cofs) For Adsorption Of Heavy Metal Ions, Samar A. Salim

Nanotechnology Research Centre

This study reported the synthesis, electrospinning, and heavy metal adsorption of covalent organic frameworks (COFs) integrated into poly(methyl methacrylate) (PMMA) nanofibers. COF-1 and COF-2 were synthesized by solvothermal and reflux techniques, respectively, and subsequently incorporated into PMMA via electrospinning with different loadings (0.1%, 0.5%, and 1.0%). The synthesized PMMA_COF nanofibers were analyzed utilizing X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and diffuse reflectance spectroscopy (DRS). PMMA_COF nanofibers with fiber diameters of 350-450 nm were obtained. The structural and morphological investigations validated the effective integration of COFs into the PMMA matrix, with COF-1 demonstrating superior dispersion …

Coherent Two-Photon Backscattering And Induced Angular Quantum Correlations In Multiple-Scattered Two-Photon States Of The Light, Nooshin M. Estakhri, Theodore B. Norris

Engineering Faculty Articles and Research

We present the emergence of coherent two-photon backscattering, a manifestation of weak localization, in multiple scattering of maximally entangled pure and fully mixed two-photon states and examine the effect of entanglement and classical correlations. Quantum correlations in backscattering are investigated for finite three-dimensional disordered structures in the weak localization regime, as well as systems of a small number of scatterers with specified spatial arrangements. No assumptions are made about the statistical behavior of the scattering matrix elements. Furthermore, we study the interplay between quantum correlations induced by multiple scattering and the correlations that may be present in the illumination fields, …

Enhanced Intrusion Detection Using Recurrent Neural Networks With Amino Acid Codon Features, Omar Fitian Rashid, Mohammed Ahmed Subhi, Safa Ahmed Abdulsahib, Mohammed Khaleel Hussein, Marwan Ali Albahar

Iraqi Journal for Computer Science and Mathematics

Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which …

Explainable Ai In Agriculture: Bridging The Gap Between Technology And Farmer, Jayarekha P, Anitha H M, Sowmya K S, Nalina V, Audithan Sivaraman, Madhu Narasimha

Iraqi Journal for Computer Science and Mathematics

An intelligent and explainable, as well as user-friendly, crop recommendation and yield prediction system is developed to facilitate agricultural decision-making under various tillage methods with the help of Explainable AI. The system utilizes Machine Learning algorithms and calculates yield changes as a relative term with respect to various inputs such as location, month of sowing, years of NT adoption, and soil type using real-time environmental data; accordingly, it recommends crops. The prediction framework, which is based on various regression algorithms, including Linear Regression, Decision Tree, Random Forest, and Gradient Boosting, was trained on the dataset of agronomic and climatic variables. …

Effect Of Recycled Water As Mixing And Curing Water, On Concrete Properties, Nagah Mousalem, Sayed Abdelbaky, Hesham Ali Ezz-Eldeen, Ahmed Abdel Hafiz Mahmoud

HBRC Journal

This research aims to study the effect of secondary treated wastewater (STWW) and tertiary treated wastewater (TTWW) in concrete mixing and curing as a complete alternative to fresh water to address the water crisis. The treated wastewater used in the study was collected from two wastewater treatment plants in Orasqualia for STWW and El Shorouk for TTWW, Egypt. Chemical analysis was performed on the collected water samples to verify their compliance with the recommendations of the relevant standards used in concrete production. Physical and mechanical tests were performed on cement paste, mortar and concrete specimens. Some durability characteristic of concrete …

Mental Health Self-Perceptions And Resource Utilization In Undergraduate Students At Binghamton University, Nicole J. Dreznin, Sarah Marcus

Binghamton University Undergraduate Journal

Undergraduate students face increasing rates of mental health challenges, however discrepancies in mental health literacy and utilization of resources may exist across student populations. This study examined the perceptions of mental health in undergraduate students at Binghamton University and if they differed among STEM vs non-STEM, man vs. women, and first-generation vs. continuing generation undergraduate students. A 20-question survey, containing 5 demographic questions and 15 mental health related questions was distributed through Qualtrics to 9 undergraduate classes. The available response choices were based on the Likert scale. A total of 1266 students participated.  Chi square tests of independence were done …

Purification And Concentration Of Model Viruses Using Single-Pass Tangential Flow Filtration, Luis Alberto Mejía-Manzano, Lynn M. Manchester, Grace Wallis, Kan Wang, Bruce Lee, Michael Betenbaugh, Caryn Heldt

Michigan Tech Publications

The vaccine and viral vector industry is growing at an accelerated rate. To improve harvest and purification processes, the development of continuous membrane-based operations, such as normal flow filtration (NFF) and single pass tangential flow filtration (SPTFF) for concentration were explored. This work was conducted using two model viruses, non-enveloped porcine parvovirus (PPV) and enveloped Suid herpesvirus (SuHV). The viruses are in the same family as the gene therapy vectors adeno associated virus and herpes simplex virus, respectively. SPTFF design started with batch TFF for membrane selection. Hollow fiber membranes with a 100 and 300 kDa molecular weight cut off …

Influence Of Peristalsis On The Hemodynamic Analysis Of Magnetohydrodynamic Jeffrey Fluid In A Two-Layered Narrow Channel, N. Lavanya, G. Ravi Kiran, M. Varun Kumar, K. Rajyalakshmi

Mansoura Engineering Journal

In this paper, an analytical study of MHD-influenced hemodynamic of Jeffrey fluid during peristaltic transport in a two layered narrow channel is presented, a phenomenon that has substantial ramifications for microcirculatory dynamics in the cardiovascular system. The model assumes a Jeffery fluid in the core area to encapsulate microstructural phenomena, including viscosity fluctuations, whereas the periphery area is treated as a Newtonian fluid. The governing equations for both regions are simplified and analytically solved under the long wavelength approximation. Using MATHEMATICA, a numerical investigation is carried out to examine the influence of various parameters, such as the magnetic parameters, amplitude, …

Design And Fpga Deployment Of Quantized Convolutional Spiking Neural Networks For Ecg Arrhythmia Classification, Olamilekan Banjo

Electronic Theses and Dissertations

Wearable ECG monitors enable continuous cardiac surveillance, yet most remain limited to basic heart rate metrics or coarse atrial fibrillation detection, relying on cloud-based analysis that introduces latency, connectivity dependence, and battery drain. Deploying advanced multi-class arrhythmia classification directly on-device is constrained by the tight memory, power, and computational budgets of wearable hardware. This dissertation presents a Quantized Convolutional Spiking Neural Network (QCSNN) for real-time ECG arrhythmia detection on edge hardware, developed across three progressive phases.

Phase 1 introduces a separately trained two-stage QCSNN architecture — a binary classifier cascaded with a four-class classifier — trained directly via surrogate gradient …

Human Cancer Genomes Harbor The Mutational Signature Of Tobacco-Specific Nitrosamines Nnn And Nnk, Michael Korenjak, Nuri Alpay Temiz, Stéphane Keita, Bérénice Chavanel, Claire Renard, Cécilia Sirand, Jiehong Guo, Et Al.

Michigan Tech Publications

BACKGROUND: Tobacco use is linked to multiple cancer types and a quarter of cancer deaths. Tobacco smoke contains numerous mutagenic chemicals such as polycyclic aromatic hydrocarbons (PAH), however, the mutagenicity of many chemicals in tobacco products remains underexplored. The tobacco-specific nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N'-nitrosonornicotine (NNN), both International Agency for Research on Cancer (IARC) Group 1 carcinogens, form pre-mutagenic pyridyloxobutyl (POB) DNA adducts, yet little is known about the associated genomic mutation landscape(s) in humans. METHODS: We applied bulk and error-corrected next-generation sequencing to a battery of experimental systems comprising mammalian cell lines and animals exposed to NNK or NNN, …

Artificial Intelligence Based Predictive Simulation And Decision-Support Framework For Full Scale Wastewater Treatment Systems, Muhammad Hassnain, Cameron Veal, Sarada M.W. Lee, Muhammad Rizwan Azhar

Research outputs 2022 to 2026

Full scale wastewater treatment plants (WWTPs) generate extensive sensor and laboratory datasets that remain challenging to translate into real-time operational insight, while increasing hydraulic variability, energy constraints, tightening effluent regulations, and events such as sensor faults, hydraulic shocks, and effluent-quality excursions require predictive decision-support tools beyond conventional mechanistic modelling. This study presents a full-scale, industry-deployed artificial intelligence (AI) framework integrating machine learning (ML), simulation, and operational boundary definition across a nitrogen-removal WWTP in Australia. Up to nine years of high-frequency online instrumentation data (≤419,000 records per target; 5–30 min resolution) and ~3000 laboratory samples were used to train and evaluate …

Perspectives Of Scholars, Families, And Advisors On 360-Degree Video Technology In Graduate Education, Oluwatobi A. Mogbojuri, Bridget A. Walsh, Matthew Aguirre

Journal of Human Sciences and Extension

This study explored the experiences of scholars in creating and sharing 360-degree videos, as well as the perspectives of families and advisors who viewed the videos. Focus groups and individual interviews were conducted online using a videoconferencing platform. Perspectives from 20 participants (15 scholars, three advisors, and two family members) were analyzed using thematic analysis. Three primary themes were identified: (1) barriers to 360-degree video use, (2) perspective shifts and limited change, and (3) storytelling and scholar visibility. Findings suggest that 360-degree video technology may be an innovative tool for enhancing recruitment and retention, especially for historically marginalized groups, through …

Analysis Of Construction Safety Costs In Girder Erection Work On Toll Road Projects To Reduce Risks And Construction Accident Costs, Aditya Daniar Wicaksono, Rossy Armyn Machfudiyanto

CSID Journal of Infrastructure Development

The construction of toll roads, as part of Indonesia’s National Strategic Projects, plays a crucial role in enhancing mobility and economic competitiveness. Girder erection work constitutes one of the most critical phases in toll road bridge construction, characterized by high safety risks due to confined workspaces, technical complexity, and suboptimal risk management practices. This study aims to analyze construction safety costs in girder erection work to reduce risks and construction accident costs. The research process includes hazard identification, effective risk control analysis, risk impact valuation, and cost-benefit analysis of safety investments. The methods employed consist of secondary data analysis, risk …

Nebraska And The Midwest Agtech Ecosystem: Benchmarking Innovation Investment And Translation Gaps, Ankit Chandra, Ishani Lal, Brennan Costello

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural innovation is central to the sustainable transformation of food systems, yet the capital that finances it is unevenly distributed relative to where food is produced. This paper develops a diagnostic framework for measuring this mismatch and applies it across the U.S. Midwest from 2021 to 2025, with particular emphasis on Nebraska's structural position within this landscape. Drawing on venture capital deal-flow data, 17 stakeholder interviews, and a novel strength-weakness-opportunity-gap (SWOG) ecosystem mapping methodology, we document $736 million in tracked Midwest AgTech funding across eight states (Nebraska, Iowa, Missouri, Illinois, Indiana, Kansas, North Dakota, and South Dakota). We introduce three …

Interpretable Machine Learning Of Plasma Proteomics Reveals Stage-Specific Signatures Across The Alzheimer's Disease Continuum, Hemshankar Laugi

2026 Spring Honors Capstones Projects

Alzheimer’s pathology begins years before clinical symptoms, starting early with amyloid-β accumulation, followed by tau deposition and neurodegeneration. Although existing tools, such as cerebrospinal fluid (CSF) screening and PET/MRI imaging, can accurately track disease progression, they are invasive, expensive, and not scalable for population-level screening. So, there is a growing interest in using blood-based plasma biomarkers as a scalable alternative. While recent studies demonstrate strong predictive performance with plasma biomarkers, most rely on a small set of canonical blood-based protein biomarkers such as amyloid-β, p-tau, and neurofilament light. These biomarkers primarily reflect downstream brain pathology and may fail to capture …

Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers

Electrical and Computer Engineering Faculty Research & Creative Works

Background/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated …

Chi Meta-Project Ecosystem Overview - Spring 2026, David B. Smith

Publications and Research

This paper offers a high-level account of the Center for Holistic Integration’s (CHI) meta-project ecosystem as visualized in the included system map. CHI provides an organizational structure framed around persistent meta-projects that support and extend individual initiatives across curriculum, scholarly and applied research, infrastructure, artistic production, AI development, cultural inquiry, and external partnerships. Rather than presenting the map as a static inventory of projects, the paper examines how its core domains function as living systems through which knowledge, tools, documentation, participants, and collaborations can accumulate over time. It also considers how CHI-mediated connectivity, institutional integration, and external funding allow the …

How Do Different Food Influents Affect Biogas Production, Process And Operational Stability, And System Performance In The Armfield W8, A Bench-Scale Anaerobic Digester, Jarko Rumbaoa, Anahita Adhikari

Rose-Hulman Undergraduate Research Publications

No abstract provided.

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas

Computer Science Faculty Research & Creative Works

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, …

Thiol-Based Neuroprotective Copolymers Acutely Restore Redox Metabolism And Mediate Vasogenic Edema In A Mouse Model Of Traumatic Brain Injury, Evan T. Curtis, Brandon Z. Mcdonald, Aria W. Tarudji, Aaron M. Priester, Anthony J. Convertine, Forrest M. Kievit

Materials Science and Engineering Faculty Research & Creative Works

Effective pharmaceutical interventions for treating the secondary damage associated with traumatic brain injury (TBI) are limited due to poor delivery into the brain, insufficient target engagement, and an incomplete understanding of the pathophysiological changes that occur post-impact. Thus, nanoparticles (NP), which have an enhanced permeation and retention-like effect within the perturbed blood-brain barrier, have grown as a potential candidate for treating TBI. We have investigated the antioxidant capacity of thiol-based NP, termed neuroprotective copolymers (NPC3), and their ability to neutralize reactive oxygen species (ROS) and lipid peroxidation products (LPOx). Here, we assessed the efficacy of NPC3 for alleviating the secondary …

The Open Wiki Of Electrochemical Methods (Owem): A Community-Driven Educational Resource, Anderson Fuller, Devin Rappleye

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

The traditional resources for learning electrochemical methods—textbooks, academic literature, and university coursework—remain essential but are limited in accessibility, update frequency, and practical usability. This paper introduces the Open Wiki of Electrochemical Methods (OWEM), an open-access, community-driven platform designed to complement these resources. OWEM organizes content into equations, definitions, methods, tutorials, and supplementary articles, with a heavy emphasis on experimental relevance. A case study on cyclic voltammetry demonstrates how OWEM consolidates foundational theory, lesser-known results, and practical guidance within a continuously maintainable framework to benefit the broader electrochemistry community.

Aspirational Mirrors: A Conceptual Model Of Alumni-Led Near-Peer Outreach For Precollege Engagement In Ocean Engineering, Habibi Palippui, Juswan Sade

Journal of Pre-College Engineering Education Research (J-PEER)

Precollege students in Indonesia, especially in rural and coastal regions, often lack exposure to engineering disciplines due to social, geographic, and informational barriers. This essay proposes a conceptual model of alumni-led near-peer outreach as an affective and culturally grounded mechanism to engage high school students in ocean engineering. Drawing from theories of social similarity, possible selves, and engineering identity, the model conceptualizes alumni as “aspirational mirrors” who influence students not merely through information but also through identification. The model outlines four primary mechanisms—social connection, narrative engagement, aspirational mirroring, and early identity activation—and also accounts for contextual variables such as school …

Ai-Enhanced Heat Transfer Optimization In Magnetic Bio-Nanofluids, Hasan Attyah Shaboot

Al-Esraa University College Journal for Engineering Sciences

This study presents a hybrid Artificial Intelligence–Computational Fluid Dynamics (AI-CFD) framework for optimizing heat transfer in magnetic bio-nanofluids subjected to external magnetic fields. Magnetic bio-nanofluids, composed of biocompatible base fluids containing superparamagnetic nanoparticles, exhibit tunable thermal and flow behavior, making them promising for biomedical and micro-cooling applications. Conventional optimization methods based on experiments or brute-force CFD are computationally expensive and limited in exploring the full design space. To overcome these challenges, an Artificial Neural Network (ANN) surrogate model was developed to predict two key performance indicators, the Nusselt number and the friction factor, with high accuracy (R² > 0.997). The …

Numerical Method For Strongly Variable-Density Flows At Low Mach Number: Flame-Sheet Regularisation And A Mass-Flux Immersed Boundary Method, Matheus P. Severino, Fernando F. Fachini, Elmer M. Gennaro, Daniel Rodríguez, Leandro F. Souza

Mathematical Modelling and Numerical Simulation with Applications

A low-Mach-number flow, in the laminar regime, has intrinsically two characteristic spatial scales for a given time scale, or two characteristic temporal scales for a given spatial scale, and these dual scales are very different due to the disparity between the flow and acoustic speed. Therefore, low-Mach-number flows impose mathematical and computational challenges in their description. Standard numerical methods for compressible flows, which are typically designed for problems with a single dominant spatial and temporal scale, require alternative approaches, such as preconditioning techniques or solvers tailored for low-Mach-number equations. The present work introduces a simplified fluid dynamics model for flows …

Evaluation Of A Vortex Flow Device On A Center Pivot Irrigation System, Ankit Chandra, Derek M. Heeren, Tyler Smith

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

This study presents the first independent field evaluation of a passive vortex flow device designed to reduce hydraulic friction in pressurized irrigation systems. Experiments were conducted on a full-scale, groundwater-fed center pivot irrigation system at the Eastern Nebraska Research, Extension, and Education Center (ENREEC). A paired comparison approach was used to quantify differences in flow rate, energy consumption, and pressure distribution along the pivot lateral under baseline (no device) and treatment (device installed) conditions. Results showed negligible change in system flow rate (621 vs. 618 gpm) and energy consumption (~1.2% difference), consistent with expectations for pressure-regulated irrigation systems. However, the …

Management Of Multi-Agent Robotic Systems Using Artificial Intelligence Technologies, A.T. Hamiyev

Chemical Technology, Control and Management

This article addresses the problem of managing multi-agent robotic systems using artificial intelligence technologies. A hybrid model combining the Vision-Language-Action (VLA) architecture with the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is proposed for the synergetic control of a group of robots. The model is built on the Centralized Training with Decentralized Execution (CTDE) principle, with a Social-Force component incorporated into the reward function to automatically maintain a safe distance between agents. Experiments were conducted in the NVIDIA Isaac Sim environment using a dataset of over 10,000 trajectories and scenarios involving 4 to 16 agents. The results show a 90% …