Digital Commons Network^™

Teachers’ Perceptions Of The Effectiveness Of Tier 3 Academic Interventions, Dana Esposito

Theses and Dissertations

This applied dissertation was designed to discover teachers’ perceptions about the overall effectiveness of Tier 3 RTI services for resolving academic problems and teachers’ perceptions about transitioning students out of RTI. Students receiving services in Tier 3 of the RTI process often spend a considerable amount of time attempting to meet their goals. A search for answers to this problem, combined with a gap in the existing literature regarding time spent in Tier 3, led to the development of this study.

Data collection was acquired through a qualitative collective-case method focused on semi-structured interviews. Participants consisted of general and special …

Walk This Way: Effects Of Eyewitness Identification Factors And The Featural Justification Effect On Mock-Juror Decision-Making, Lauren Nicole Stornelli

Theses and Dissertations

Surveillance cameras serve many purposes, including security, monitoring, and investigating crimes. The presence of surveillance cameras allows for a new form of witness: a non-eyewitness, where crimes are captured by surveillance cameras without a physical witness present (Pezdek & Lerer, 2023a). As such, police officers are acting as eyewitnesses by identifying the perpetrator from the surveillance evidence and testifying about their identification at trial (Rumschik et al., 2020). Previous studies have examined participants’ ability to accurately match previously viewed faces with faces on surveillance evidence, with results suggesting accuracy rates around chance (e.g., Bruce et al., 2001; White et al., …

Mindfulness And Modification Therapy (Mmt) Group Feasibility And Acceptability Among Prison Residents With Dysregulated Behaviors, Leslie Unger

Theses and Dissertations

Mindfulness and Modification Therapy (MMT; Wupperman, 2019) is a transdiagnostic therapy that systematically integrates aspects of six empirically supported treatments for impulsive and dysregulated behavior. As such, MMT may offer an efficient approach to addressing a variety of dysregulated behaviors, thereby supporting increased safety within carceral settings and enhancing goals of rehabilitation. To date, MMT has demonstrated positive results in community settings when treating substance misuse and anger/aggression, but it has not yet been examined in a prison setting. The present research examines the feasibility and acceptability of using a 14-session version of group MMT as a voluntary treatment option …

High-Speed Aircraft Stability And Control Metrics, Timothy T. Takahashi, Jack A. Griffin, Ramana Grandhi

Faculty Publications

This review paper identifies key stability and control screening parameters needed to design low-risk, general-purpose high-speed aircraft. These derive from MIL-STD-8785C, MIL-STD-1797, and older AGARD reports, and are suitable for assessing conceptual high-speed vehicles. We demonstrate their applicability using published ground test, computation, and flight test data from the Bell X-2, North American X-15, Martin X-24A, Northrop HL-10, Lockheed Blackbird (YF-12/SR-71), and North American XB-70 as well as the Rockwell Space Shuttle Orbiter. The relative success of the X-15 and Blackbird and the performance limitations of the others indicate the need to scrutinize lateral-directional stability at the preliminary design phase. …

The Space Rescue Professional: Operationalizing Guardians For The Future, Benjamin Johnis, Robert Bettinger, James Dean

Faculty Publications

The escalating competition in space exploration demands a dedicated space rescue capability. This article argues for the establishment of a space rescue professional (SRP) career field within the Department of Defense and the US Space Force. By harnessing existing US Air Force combat rescue expertise and partnering with the National Aeronautics and Space Administration, the Space Force can rapidly develop a robust SRP program with the warrant officer corps as its backbone. This article addresses a critical gap in national space policy to outline a cost-effective dual-service training pipeline and SRP operational roles. Such an investment safeguards astronauts, bolsters US …

2025-2026 Usf Libraries Annual Report, Usf Libraries

Library Annual Reports

No abstract provided.

The Pre-Polarization And Concentration Of Cells Near Micro-Electrodes Using Ac Electric Fields Enhances The Electrical Cell Lysis In A Sessile Drop, Kishor Kaphle, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell lysis is the starting step of many biomedical assays. Electric field-based cell lysis is widely used in many applications, including point-of-care (POC) applications, because it provides an easy one-step solution. Many electric field-based lysis methods utilize micro-electrodes to apply short electric pulses across cells. Unfortunately, these cell lysis devices produce relatively low cell lysis efficiency as electric fields do not reach a significant portion of cells in the sample. Additionally, the utility of syringe pumps for flow cells in and out of the microfluidics channel causes cell loss and low throughput cell lysis. To address these critical issues, we …

Epicardial Cryoablation During Cardiopulmonary Bypass In A Pig Survival Model, Federica Serra, Jonathan M. Philpott, Anna Bulysheva, Christian W. Zemlin

Electrical & Computer Engineering Faculty Publications

Objective

Atrial cryolesions are usually created from the endocardium with the heart arrested. Some cardiac surgeons have used cryoablation epicardially during cardiopulmonary bypass, which is convenient because it does not require an incision into the atrial wall. Here, we analyzed the transmurality of epicardial cryoablations created during cardiopulmonary bypass in an arrested heart 30 days after ablation.

Methods

In Yucatan minipigs (n=5), hearts were exposed via sternotomy. Both caval veins were cannulated to collect blood for the cardiopulmonary bypass. Cryolesions were created applying a cryoprobe for 4 minutes per lesion. Hearts were harvested 30 days after the surgery. The transmurality …

Automating The Amino Acid Identification In Elliptical Dichroism Spectrometer With Machine Learning, Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

Electrical & Computer Engineering Faculty Publications

Amino acid identification is crucial across various scientific disciplines, including biochemistry, pharmaceutical research, and medical diagnostics. However, traditional methods such as mass spectrometry require extensive sample preparation and are time-consuming, complex and costly. Therefore, this study presents a pioneering Machine Learning (ML) approach for automatic amino acid identification by utilizing the unique absorption profiles from an Elliptical Dichroism (ED) spectrometer. Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. The results show that ML can potentially revolutionize the amino acid analysis …

Mxenes In Biosensing: Enhancing Sensitivity And Flexibility - A Review Of Properties, Applications, And Future Directions, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Alireza Jahanbin, Milad Abbasi, Ahmed Vaez, Hesam Kamyab, Lalitha Gnanasekaran, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are a novel type of nanostructured material that has received a lot of attention for their potential applications in bioanalysis owing to their unique features. These materials, made from transition metal nitrides, carbides, or carbonitrides, have a number of advantages, including high hydrophilicity, a large surface area, strong metallic conductivity, superior ion transport capabilities, biocompatibility, and low diffusion barriers. Their surfaces are easily manipulated, making them more adaptable for a variety of applications, including biosensing. The outstanding properties of MXenes have attracted researchers of different fields, including renewable energy, fuel cells, supercapacitors, electronics, and catalysis. In the context of …

Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman

Electrical & Computer Engineering Faculty Publications

This paper presents a comparative analysis of OpenAI's GPT-4 and its optimized variant, GPT-4o, focusing on their architectural differences, performance, and real-world applications. GPT-4, built upon the Transformer architecture, has set new standards in natural language processing (NLP) with its capacity to generate coherent and contextually relevant text across a wide range of tasks. However, its computational demands, requiring substantial hardware resources, make it less accessible for smaller organizations and real-time applications. In contrast, GPT-4o addresses these challenges by incorporating optimizations such as model compression, parameter pruning, and memory-efficient computation, allowing it to deliver similar performance with significantly lower computational …

T3-Ciders: Fostering A Community Of Practice In Ci-And Data Enabled Cybersecurity Research Through A Train-The-Trainer Program, Wirawan Purwanto, Mohan Yang, Peng Jiang, Masha Sosonkina

Electrical & Computer Engineering Faculty Publications

We present a training program named T³-CIDERS, the Train- The-Trainer approach to fostering cyberinfrastructure (CI)- and Data-Enabled Research in CyberSecurity. T³-CIDERS is a train-the-trainer program for advanced cyberinfrastructure (CI) skills that is designed to be synergistic with research, teaching, and learning activities in cybersecurity and cyber-related disciplines. The participants, termed 'future trainers' (FTs), are trained in effective instructional design and CI hands-on materials from DeapSECURE, developed in a previous CyberTraining program. T³-CIDERS aims to enhance cybersecurity research and education through broader adoption of advanced CI techniques such as artificial intelligence, big data, parallel programming, and platforms like high-performance computing (HPC) …

Detecting Anomalous Srf Cavity Behavior With Unsupervised Learning, Hal Ferguson, Jiang Li, Adam Carpenter, Chris Tennant, Dillon Thomas, Dennis Turner

Electrical & Computer Engineering Faculty Publications

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a …

Personalized Prediction Of Tumor Recurrence With Image-Guided Physics-Informed Computational Model In High-Grade Gliomas, Walia Farzana, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

High grade gliomas are infiltrating tumors characterized by their diffusive invasion and proliferative growth. Across and within patients heterogeneity of tumors makes it challenging to determine tumor spatial extent after surgical resection. Traditionally, tumor growth predictions after surgical resections rely on generalized models and population-based observations, which do not account for individual patient differences. To address this gap, we propose a personalized approach with image-guided computational model (digital twin) that incorporates physics-based modeling to predict tumor recurrence. Our digital twin involves an inverse modeling step, followed by a recurrence model that accounts for varying surgical effects. The physics-guided inverse model …

Key Brain Region Identification In Obesity Prediction With Structural Mri And Probabilistic Uncertainty Aware Model, Walia Farzana, Megan A. Witherow, Ahmed Temtam, Liangsuo Ma, Melanie Bean, F. Gerry Moeller, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: Predictive performance alone may not determine a model’s clinical utility. Neurobiological changes in obesity alter brain structures, but traditional voxel-based morphometry is limited to group-level analysis. We propose a probabilistic model with uncertainty heatmaps to improve interpretability and personalized prediction. Methods/Study Population: The data for this study are sourced from the Human Connectome Project (HCP), with approval from the Washington University in St. Louis Institutional Review Board. We preprocessed raw T1-weighted structural MRI scans from 525 patients using an automated pipeline. The dataset is divided into training (357 cases), calibration (63 cases), and testing (105 cases). Our probabilistic model …

Effect Of Bioactive Glass On Pxdda / Pxdda-Co-Pla Nanocomposite For Hard Tissue Reconstruction: Synthesis And Characterization, Ehsan Vafa, Lobat Tayebi, Fatemeh Azizli, Somayeh Parham, Katayoon Rezaeeparto, Sedigheh Azadi, Ali Mohammad Amani, Mohammad Javad Azizli, Hesam Kamyab, Shreeshivadasan Chelliapan, Saravanan Rajendran

Electrical & Computer Engineering Faculty Publications

Newer bone graft materials face various challenges in achieving optimal mechanical strength, bioactivity, and antibacterial action simultaneously, which can result in suboptimal regeneration outcomes and increased infection risks In the present study, we developed a novel nanocomposite of poly (xylitol-co-dodecanedioic acid) (PXDDA) and poly (lactic acid) (PLA) with 1-10 wt% incorporation of bioactive glass (BG), utilizing a a PXDDAco-PLA compatibilizer for maintaining homogeneity. Extensive characterization techniques including, Fourier infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauere Emmette Teller (BET), Proton Nuclear Magnetic Resonance (¹H NMR) and contact angle measurements, revealed that the addition …

A Fast Framework For Generating Radioactive Mixture Spectra And Its Application To Remote High-Performance Mixture Identification, Chiman Kwan, Bulent Ayhan, Adam Stavola, Kazi Aminul Islam, Hongfang Zhang, Jiang Li

Electrical & Computer Engineering Faculty Publications

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework.

A Potentially Fruitful Path Toward A Cleaner And Safer Environment: Mxenes Uses In Environmental Remediation, Ali Mohammad Amani, Milad Abbasi, Atena Najdian, Farzaneh Mohamadpour, Seyed Reza Kasaee, Hesam Kamyab, Shreeshivadasan Chelliapan, Hanieh Ardeshiri, Lobat Tayebi, Ehsan Vafa, Sarah Mosleh-Shirazi, Alireza Jahanbin, Saravanan Rajendran, Daniel Simancas-Racines

Electrical & Computer Engineering Faculty Publications

The rapid industrialization of the world has resulted in severe environmental pollution, necessitating the development of new materials such as pollution remediation. Two-dimensional (2D) MXenes have emerged as a promising family of materials due to their unique physicochemical properties, making them ideal for environmental remediation. The article sheds light on the new opportunities of MXenes in the removal of organic and inorganic contaminants, including organic dyes, pharmaceuticals, heavy metals, radionuclides, and gas pollutants. MXenes also show excellent performance in photocatalytic degradation, adsorption, and microbial inactivation with environmental safety. Moreover, their application in recovering valuable elements from waste streams is also …

Data-Driven Gradient Optimization For Field Emission Management In A Superconducting Radio-Frequency Linac, S. Goldenberg, K. Ahammed, A. Carpenter, J. Li, R. Suleiman, C. Tennant

Electrical & Computer Engineering Faculty Publications

Field emission can cause significant problems in superconducting radio-frequency linear accelerators (linacs). When cavity gradients are pushed higher, radiation levels within the linacs may rise exponentially, causing degradation of many nearby systems. This research aims to utilize machine learning with uncertainty quantification to predict radiation levels at multiple locations throughout the linacs and ultimately optimize cavity gradients to reduce field emission-induced radiation while maintaining the total linac energy gain necessary for the experimental physics program. The optimized solutions show over 40% reductions for both neutron and gamma radiation from the standard operational settings.

Targeting Bone In Cancer Therapy: Advances And Challenges Of Bisphosphonate-Based Drug Delivery Systems, Fariba Ganji, Mohammadmahdi Eshaghi, Hossein Shaki, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: Bisphosphonates (BPs) are well-known for their strong affinity toward bone mineral matrices and are widely used to inhibit excessive osteoclast activity associated with various bone disorders. Beyond their clinical use, their unique bone-targeting capability has positioned them as promising ligands for drug delivery systems aimed at treating bone-related cancers. Approach: The review analyses published studies on BP-functionalized drug delivery systems, including direct drug conjugates, calcium-based nanomaterials, carbon-based nanostructures, and self-assembling systems such as micelles and liposomes. In vitro assays (e.g. hydroxyapatite binding, cell viability) and in vivo biodistribution studies are discussed to evaluate targeting efficiency and …

Biomedical Mxene-Polymer Nanocomposites: Advancing Photothermal Therapy, Antibacterial Action, And Smart Drug Delivery: A Review, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Mohammad Javad Azizli, Milad Abbasi, Ahmad Vaez, Hesam Kamyab, Daniel Simancas-Racines, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are hydrophilic, conductive, tunable, and biocompatible two-dimensional ceramic materials prepared by etching the 'A' layer from their precursor MAX phases. Although MXenes show exceptional promise in photothermal therapy, biosensing, and regenerative medicine, they face challenges such as oxidative instability in physiological environments, limited drug-loading capacity, and unpredictable immune responses. To address these limitations, MXene/polymer nanocomposites incorporating both synthetic polymers (e.g., polyethylene glycol (PEG), polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP), and polylactic-co-glycolic acid (PLGA)) and natural biopolymers (e.g., cellulose nanofiber, gelatin, chitosan, hyaluronic acid, and soybean phospholipids) have been developed. These composites enhance functionality for biomedical applications such as photothermal cancer …

Optimizing Superconducting Nb Film Cavities By Mitigating Medium-Field Q-Slope Through Annealing, B. Abdisatarov, G. Eremeev, H. E. Elsayed-Ali, D. Bafia, A. Murthy, Z. Sung, A. Netepenko, A. Romanenko, C. P.A. Carlos, G. J. Rosaz, S. Calatroni, S. Leith, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are of interest in applications in various superconducting devices, such as superconducting radiofrequency cavities for particle accelerators and superconducting qubits for quantum computing. In this study, we address the persistent medium-field Q-slope issue in Nb film cavities, which, despite their high-quality factor at low RF fields, exhibit a significant Q-slope at medium RF fields compared to bulk Nb cavities. Traditional heat treatments, effective in reducing surface resistance and mitigating the Q-slope in bulk Nb cavities, are challenging for Nb-coated copper cavities. To overcome this challenge, we employed DC bias high-power impulse magnetron sputtering to deposit …

Land Target Detection Algorithm In Remote Sensing Images Based On Deep Learning, Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

Electrical & Computer Engineering Faculty Publications

Remote sensing technology plays a crucial role across various sectors, such as meteorological monitoring, city planning, and natural resource exploration. A critical aspect of remote sensing image analysis is land target detection, which involves identifying and classifying land-based objects within satellite or aerial imagery. However, despite advancements in both traditional detection methods and deep-learning-based approaches, detecting land targets remains challenging, especially when dealing with small and rotated objects that are difficult to distinguish. To address these challenges, this study introduces an enhanced model, YOLOv5s-CACSD, which builds upon the YOLOv5s framework. Our model integrates the channel attention (CA) mechanism, CARAFE, and …

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …

Polarized Photocathode R&D At Bnl And Spin Consideration For The Eic Preinjector, Jyoti Biswas, Erdong Wang, Omer Rahman, John Skaritka, Adam Masters, Sylvain Marsillac, Tai-De Li

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes are vital for producing polarized electron beams for the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. The electron pre-injector at the EIC requires a 7 nC bunch with at least 85% spin polarization from a GaAs-based superlattice cathode. The doping density of the very surface layer of the cathode needs to be optimized to extract a high bunch charge beam from the high-voltage DC gun. The polarization axis of the emitted beam is longitudinal, and it will be rotated to transverse direction using two Wien filters, each rotating the spin by 45 degrees. In this paper, we …

The Impact Of Chromium Ion Implantation On Ald Lead Chalcogenide Thin Films, Haifeng Cong, Charlotte Poterie, Jean Francois Barbot, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

Inherently the synthesis of semiconducting materials by Atomic Layer Deposition ALD produces only intrinsic undoped films which require the introduction of small amounts of impurities for doping to change them into extrinsic semiconductors. Apart from various in-situ diffusion doping techniques like delta doping during the ALD process, post deposition doping by ion implantation affords the best control of dose and doping profile. The present study investigates the impact of 180 keV Cr⁺ ion implantation on the properties of semiconducting ALD lead chalcogenide thin films to improve their thermoelectric figure of merit. The implantation was accomplished with 180 keV Chromium …

Potential Of Lidar And Hyperspectral Sensing For Overcoming Challenges In Current Maritime Ballast Tank Corrosion Inspection, Sergio Pallas Enguita, Jiajun Jiang, Chung-Hao Chen, Samuel Kovacic, Richard Lebel

Electrical & Computer Engineering Faculty Publications

Corrosion in maritime ballast tanks is a major driver of maintenance costs and operational risks for maritime assets. Inspections are hampered by complex geometries, hazardous conditions, and the limitations of conventional methods, particularly visual assessment, which struggles with subjectivity, accessibility, and early detection, especially under coatings. This paper critically examines these challenges and explores the potential of Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) to form the basis of improved inspection approaches. We discuss LiDAR’s utility for accurate 3D mapping and providing a spatial framework and HSI’s potential for objective material identification and surface characterization based on spectral …

High-Fidelity Soh Prediction In Lithium-Ion Batteries Using Hybrid Ml Networks, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Accurate and efficient prediction of lithium-ion battery state of health (SOH) is critical for ensuring reliability in electric vehicles, grid storage, and aerospace systems. Traditional SOH estimation methods often struggle with nonlinear degradation behaviors and lack sensitivity to subtle electrochemical signals, limiting their real-world deployment. To address these challenges, this study examines hybrid deep learning models that integrate differential capacity (dQ/dV) analysis to enhance predictive accuracy. Four hybrid architectures - hybrid CNN-LSTM multihead, CNN extractor for LSTM, DNN-LSTM, and DNN Bi-LSTM - were developed and evaluated using the NASA randomized battery usage dataset, offering a realistic benchmark under diverse operational …

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …

Enhancing Bone Regeneration Using Kaempferol As An Osteoprotective Compound: Signaling Mechanisms, Delivery Strategies, And Potential Applications, Mojdeh Salehi Namini, Sanam Mohandesnezhad, Sadaf Mohandesnezhad, Vahid Mansouri, Lobat Tayebi, Nima Beheshtizadeh

Electrical & Computer Engineering Faculty Publications

Various plants, including fruits, vegetables, and spices, contain kaempferol, a bioflavonoid compound with diverse medicinal effects, such as antioxidant, antibacterial, and anti-inflammatory characteristics. Furthermore, this compound exhibits multiple health-promoting properties, including osteoprotection and osteogenesis, primarily by modulating various cell-signaling pathways. This review aims to illustrate the medical advantages of kaempferol and its role in regulating bone metabolism through cell signaling mechanisms. Numerous studies have demonstrated the bone-protective properties of kaempferol and its encapsulated form. Further research is needed to clarify the optimal dosages, toxicity, safety, and other potential mechanisms of action. This review demonstrates that several signaling pathways, including nuclear …