Digital Commons Network^™

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …

Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …

Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The continuous increase of UAVs, particularly in swarms, creates significant challenges for security and airspace regulation. Traditional RF fingerprinting methods struggle to detect and classify UAV swarms due to overlapping signals and interference. This study introduces RF-AttenNet, a hybrid deep learning model designed to classify mixed UAV signals by analyzing composite RF spectrograms. RF-AttenNet uses dual attention mechanisms, channel and spatial attention to focus on critical spectral features, enabling the model to effectively separate and identify overlapping UAV signals. We have developed custom composite UAV datasets that simulate real-world swarm interference, incorporating both single and mixed UAV classes. RF-AttenNet achieves …

Fixed-Time Consensus Tracking For Nonlinear Multi-Agent Systems Under Aperiodically Intermittent Control, Lei Xue, Tong Wu, Wenwen Jia, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article explores the problem of fixed-time consensus tracking (FT-CT) for nonlinear multi-agent systems utilizing the a periodically intermittent control (AIC) strategy. In contrast to existing control algorithms, the proposed algorithm utilizes the AIC strategy instead of the conventional continuous-time control strategy, effectively reducing the consumption of communication resources. Moreover, the problem of intermittent FT-CT is well handled by proposing the average control rate of the AIC strategy. Two theorems based on the cases of directed and undirected graphs are proposed, respectively. Finally, the validity of these results is confirmed through numerical simulations on a general nonlinear system and a …

Effect Of Process Parameters On Thermal Response Of An Oxy-Fuel Burner/Injector Panel In An Electric Arc Furnace Via Fiber Optic Sensors, Mobashir Ahmed, Rony Kumer Saha, Koustav Dey, Todd Sander, Jie Huang, Ronald J. O'Malley

Electrical and Computer Engineering Faculty Research & Creative Works

Modern oxy-fuel burner/injectors in electric arc furnaces (EAFs) play a critical role in scrap melting, liquid steel refining, and slag foaming. However, varying operational modes, combined with dynamic process conditions, such as arcing and slag behavior, can expose the injector panel surface to intense thermal conditions that can compromise efficiency and safety. Conventional monitoring techniques, including cooling water temperature measurements and thermocouples, fail to capture localized thermal anomalies due to their limited spatial resolution and susceptibility to electromagnetic interference. In this study, four high-resolution Rayleigh backscattering-based fiber optic sensors, interrogated via optical frequency domain reflectometry, were embedded in top and …

Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Sapphire fiber Bragg gratings (SFBGs) have attracted growing interest for high temperature sensing in harsh environments, yet their interrogation typically relies on optical spectrum measurements, demanding a high-resolution optical spectrum analyzer (OSA) that is bulky, expensive, and constrained in acquisition speed. Moreover, the inherently multimode nature of sapphire fiber further complicates spectrum-based demodulation, thereby limiting the achievable sensing resolution. In this paper, we propose and experimentally demonstrate a microwave-photonic interrogation approach for SFBG sensors. Instead of measuring the optical reflection spectrum, the complex frequency response in the microwave domain of an SFBG is acquired using a vector network analyzer (VNA) …

Honey-Cnt Memristive Artificial Synaptic Device For Sustainable Neuromorphic Computing System, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru, Jinhui Wang, Kuan Yew Cheong, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, with the advantages of sustainability, environmentally friendliness, and low-cost manufacturing. In this study, carbon nanotubes (CNTs) are added in honey to fabricate honey-CNT memristive artificial synaptic devices. Honey-CNT film is characterized by micro-Raman spectroscopy and the distribution of CNT bundles embedded in the honey-CNT composite layer by cross-sectional scanning electron microscopy for the first time. Critical synaptic functions of the honey-CNT memristor, including spike-rate-dependent plasticity, spike voltage dependent plasticity, learn-forget-relearn, and supralinear spatial summation are revealed, …

Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes and experimentally demonstrates a corrugated-tube-based fiber-optic sensor capable of measuring pressure, vibration, or both simultaneously. To address the limited sensitivity of conventional diaphragm-based designs, the sensor incorporates an optimized corrugated tube that balances the conflicting stiffness requirements for pressure and vibration measurements. The corrugated tube, acting as a mechanical transducer, is integrated with an extrinsic fiber-optic Fabry–Perot interferometer (EFPI). The EFPI cavity is formed between a reflective surface at the sealed end of the corrugated tube and the cleaved end face of an optical fiber fixed within a mounting assembly. In this configuration, displacement of the corrugated …

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …

Real-Time Multiregional Market-To-Market Congestion Management Through Exchange Of Relief Cost Curve, Haotian Chen, Yonghong Chen, Jose Daniel Lara, Jarrad Wright, Matthew Bossart, Sebastian De Jesus Machado, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a novel method for multiregional market-to-market (M2M) coordinated congestion management. It identifies shortcomings in existing M2M approaches, where Regional Transmission Organizations (RTOs) exchange shadow prices and relief requests to optimize congestion relief allocations across interconnected regions. Two methods are proposed to enhance flow and price convergence. The first method proposes that both Regional Transmission Organizations (RTOs) use state-estimator flows directly to determine relief requirements, eliminating delays and potential oscillations caused by using market flows calculated from the prior period under existing M2M approach. The second method involves exchanging transmission relief cost curves, enabling each RTOs to integrate …

Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Accurately identifying the connectivity between transformers and downstream three-phase customers in low-voltage distribution networks is challenging, because voltage curves of different phases and nearby nodes can be weakly distinguishable, especially when adjacent transformers on the same feeder serve geographically close customers with highly similar voltage curves. This paper proposes a novel method based on load-switching fluctuation characteristics recorded by smart meters. By extracting localized current and voltage fluctuations and establishing correlation matching, the method overcomes the limited discriminability using steady-state measurements. The method operates in two stages: first, switching-induced fluctuation characteristics are extracted and matched to cluster customers by the …

Corrections To: Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems (Ieee Transactions On Instrumentation And Measurement (2026) 75 (1–12) Doi: 10.1109/Tim.2026.3676091), Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In the above article [1], a wording ambiguity appears in Proposition 4 regarding the description of the missing at random (MAR) mechanism. The published sentence states that the probability of observing the kth sample depends on the realized measurement value. This wording may be interpreted as dependence on the current unobserved value y[tk], which could suggest a missing not at random (MNAR) mechanism. The intended MAR mechanism is that the observation probability for the kth sample depends only on previously observed measurement information, such as y[tk-1], and not on the current unobserved value y[tk]. Therefore, the corrected wording clarifies that …

Multi-Agent Reinforcement Learning Driven Package Pdn Design Automation, Haran Manoharan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The design of package-level power delivery networks (PDNs) has become increasingly challenging as modern high-performance systems demand higher currents. Existing PDN design flows treat ball map assignment, stackup selection, and power plane routing as separate, largely manual steps, leading to long iteration times and limited scalability. This work proposes a unified and automated package PDN design framework based on multi-agent reinforcement learning (MARL). Each power domain is modeled as an agent, with specialized agents responsible for ball map assignment, routing layer selection, and power plane synthesis. A central controller coordinates agent decisions using a global reward that captures electrical and …

Enhancing Explainable Ai For Medical Imaging: Improved Lime Interpretation With Influence Mapping, Abiha Tahsin Chowdhury, Dhanush Bavisetti, Daniel B. Hier, Rahul Dubey, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

The integration of artificial intelligence (AI) into medical imaging is progressing rapidly. It is essential for these AI tools to be transparent, interpretable, and explainable to gain the trust of clinicians and regulators. Current state-of-the-art explainable AI (XAI) techniques in imaging includes Local Interpretable Model-Agnostic Explanations (LIME), Shapley Additive Explanations (SHAP), and Gradient-weighted Class Activation Mapping (Grad-CAM). Recent studies have shown that LIME often suffers from inconsistency and unreliability which limits their utility in sensitive fields like medical imaging. This paper proposes Influence Map based Explanation (IME), an enhanced variant of the original LIME framework, that aggregates multiple runs to …

Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the development of Human Activity Recognition (HAR) systems capable of identifying suspicious activities to enhance security in public spaces. We propose an innovative solution that integrates LiDAR sensors with deep learning technologies. Our method employs advanced models operating on LiDAR point cloud, PV-RCNN for human detection, and LidarGait++ for classifying activities into categories such as standing or walking (non-suspicious) and sneaking or fighting (suspicious). Due to the scarcity of suitable real-world datasets for training such systems, we utilize a 3D simulation tool, Blender, to create realistic environments and generate labeled point cloud data. This synthetic dataset allows …

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …

Femtosecond-Laser-Inscribed Cladding Fiber Bragg Gratings: Architectures, Design Trade-Offs And Future Sensing Opportunities, Koustav Dey, Rex E. Gerald, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Femtosecond (fs) laser inscription enables fiber Bragg gratings (FBGs) to be positioned beyond the fiber core, including within the cladding, thereby expanding control over modal interactions and directional sensing. These cladding fiber Bragg gratings (CLFBGs) extend FBG functionality through interactions with core, cladding, and evanescent fields. Their operation does not involve fundamentally different grating physics; rather, core-mode, cladding-mode, and coupled-mode responses depend on power distribution, modal overlap with the laser-inscribed refractive-index modulation (RIM), grating position, fiber geometry, modal excitation, and interrogation configuration. This Perspective reviews advances in CLFBG fabrication, optical characteristics, sensing mechanisms, and applications. Cladding-waveguide-assisted, evanescent-field-coupled, and direct cladding-mode-excitation …

Ai Bots As Law Teachers: What Is Left For Human Professors To Do?, Harold I. Abramson

Scholarly Works

This article considers what bots can do as AI law teachers, how students are already using bots for learning, how to integrate the use of AI into law courses, and what faculty can do to stay ahead of the bots in their classrooms. During this discussion, the article confronts the existential question of what is left for human law professors to do in an AI world. It concludes that there is a future for humans for now, and one that might make us better teachers.

Native Gifts In An Electric Universe: Exploring Tribal Sovereignty Through Digital Data, Spectrum, And Technological Imaginings, Michael Johnson

American Indian Law Review

No abstract provided.

In Pursuit Of Federal Recognition: A Legal And Historical Analysis Of The Duwamish Tribe’S Fight For Federal Tribal Recognition, Gabrielle Gollihar

American Indian Law Review

No abstract provided.

Rapid Electrochemical Biosensor With Enhanced Accuracy And Repeatability Using Pyrene Nhs Ester Modified 3d Graphene Electrodes, S. Nazir, D. Jenkins, G. Pan

School of Engineering, Computing and Mathematics

A consistent and reproducible chemical modification of the transducer interface is essential to ensure effectiveimmobilization of bioreceptors, thereby improving the sensitivity and reproducibility of biosensors. Althoughnotable progress has been made in fabricating graphene-based biosensors, the effects of surface biofunctionalization on sensing performance remain not fully understood. This study shows that combining threedimensional (3D) graphene foam electrodes with a straightforward, single-step surface biofunctionalizationmethod is key to enhancing the performance of graphene-based biosensors. Specifically, it presents a single-stepapproach to functionalize the 3D graphene foam (Gii-Sens) with 1-pyrenebutyric acid N-hydroxysuccinimideester (Pyrene-NHS ester). Electrochemical techniques, including cyclic voltammetry (CV) and differential pulsevoltammetry (DPV), confirmed …

Runt-Related Transcription Factor 2 Transcriptionally Represses Sirtuin 1 To Regulate Osteoclastogenesis And Tooth Eruption, Jie Li, Changqing Yan, Xinyi Sun, Chenying Zhang, Xiaozhe Wang, Yang Liu, Shuguo Zheng

Journal of Dental Sciences

Background/purpose: Cleidocranial dysplasia (CCD), caused by Runt-related transcription factor 2 (RUNX2) haploinsufficiency, features delayed tooth eruption. Although impaired osteoclastogenesis contributes to eruption failure, the direct molecular mechanisms linking RUNX2 deficiency to osteoclast dysfunction remain elusive. Sirtuin 1 (SIRT1) is a critical regulator of osteoclastogenesis; however, whether it serves as a downstream effector of RUNX2 remains unexplored. This study aimed to elucidate the mechanistic link between RUNX2 and SIRT1 in regulating osteoclast differentiation and tooth eruption.

Materials and methods: Tooth eruption and osteoclast differentiation were assessed by micro-computed tomography and histological analysis in Runx2^+/- mice. Chromatin immunoprecipitation quantitative polymerase chain …

Ansys Discovery And Fluent Files For Modeling A Hydrocyclone With Scco2 And Coal Fly Ash, Isaiah Morones, Catherine Brewer

Chemical & Materials Engineering: Datasets

No abstract provided.

The Trademark Bargain: Registration As Disclosure, Dustin Marlan

Faculty Publications

This Article highlights the central—and under-theorized—role that disclosure plays within trademark law. By loose analogy, the patent disclosure requirement is a cornerstone of patent law, embodying the “patent bargain” where an inventor must disclose their invention in exchange for a twenty-year monopoly. This quid pro quo is believed to stimulate the progress of science and technology, making patent disclosure the very pulse of the patent regime. However, the fundamental importance of disclosure in trademark law remains underexplored. Like patents, trademark law imposes a rigorous bargain—to obtain the enhanced rights granted by federal registration, trademark owners must first make significant disclosures …

Epigallocatechin Gallate In Dentistry: Therapeutic Applications, Biomaterial Integration, And Translational Challenges, Chloe Jui-Yun Chang, Fang-Yu Fan, Yung-Li Wang, Thi Thuy Tien Vo, Yang-Che Wu, Yu-Chia Chang, I-Ta Lee

Journal of Dental Sciences

Epigallocatechin gallate (EGCG), a major bioactive catechin in green tea, has attracted increasing attention in dentistry because of its antioxidant, anti-inflammatory, antimicrobial, matrix-modulating, and regenerative properties. This narrative review summarizes current evidence on the biological mechanisms, dental applications, and translational challenges of EGCG in oral healthcare. EGCG can modulate oxidative stress and inflammatory signaling pathways, including nuclear factor-kB (NF-kB), mitogen-activated protein kinase (MAPK), nuclear factor erythroid 2-related factor 2/heme oxygenase-1 (Nrf2/HO-1), and NOD-like receptor family pyrin domain containing 3 (NLRP3)-related responses, and has activity against oral disease-associated microorganisms and biofilms. In periodontal therapy, EGCG has been investigated as an adjunct …

Isoliquiritigenin Represses The Pro-Fibrotic Tgf-Β/Smad2 Signaling And Nuclear Enriched Abundant Transcript 1 (Neat1) In Oral Submucous Fibrosis, Chi-Shan Tseng, Shih-Min Wang, Yi-Wen Liao, Her-Hsiung Huang, Cheng-Chia Yu, Yicyuan Chen

Journal of Dental Sciences

Background/purpose: Isoliquiritigenin (ISL) has shown anti-fibrotic potential in several organ systems, but its effects on oral submucous fibrosis (OSF) remain unclear. This study investigated whether ISL attenuates myofibroblast activities in buccal mucosal fibroblasts (BMFs) from OSF patients by modulating TGF-β/Smad2 signaling and the long non-coding RNA NEAT1.

Materials and methods: Primary normal BMFs and fibrotic BMFs (fBMFs) were isolated from human buccal mucosa, and cell viability, collagen gel contraction, migration, and wound closure were examined after ISL treatment with or without arecoline. TGF-β1 secretion was quantified, while protein expression of phosphorylated Smad2, COL1A1, and α-SMA was analyzed, and …

Dual-Layer Biphasic Calcium Phosphates/Tantalum Pentoxide Coating On Titanium For Concurrent Biocorrosion Resistance And Enhanced Biocompatibility, Ying-Sui Sun, Kai-Yi Lin, Wei-Cheng Chen, Her-Hsiung Huang

Journal of Dental Sciences

Background/purpose: Titanium (Ti) dental implants must resist biocorrosion while maintaining biocompatibility. This study developed a dual-layer biphasic calcium phosphates/tantalum pentoxide (BCPs/Ta₂O₅) coating on Ti to improve both biocorrosion resistance and biological performance.

Materials and methods: A dense Ta₂O₅ inner layer was fabricated via a hydrolysis–condensation process to act as a corrosion barrier. Subsequently, a porous BCPs outer layer was deposited by electrochemical cathodic deposition to provide a bioactive interface. Surface morphology, functional groups, crystalline structure, wettability, surface free energy, coating thickness and nanostructure, protein adsorption, and in vitro bioactivity were characterized. Biocorrosion behavior was evaluated using polarization curve measurements in …

Developing Anti-Inflammatory Mineral Trioxide Aggregate As Dental Implant Crown Cement To Reduce Peri-Implantitis Incidence, Yung-Fu Hsu, Sea-Fue Wang, Yi-Le Liao, Chih-Sheng Lin, Ssu-Chi Chen, Sheng-Yang Lee, Wei-Chun Lin

Journal of Dental Sciences

背景/目的：牙周組織周圍的牙科樹脂黏固劑殘留是植體周圍炎的原因之一。嚴重病例可能導致植體鬆動或脫落。因此，本研究旨在對礦物三氧化物聚集體（MTA）進行改性，使其成為一種抗發炎的牙科植體冠黏固劑（ICC）。

材料與方法：本研究評估了去離子水溶液（Daq）、羥基磷灰石溶液（Haq）和氯化鈣溶液（Caq）對ICC凝固時間、抗壓強度、黏結強度和生物相容性的影響。以單因子變異數分析（ANOVA）檢定各實驗組間的差異（ P < 0.05）。

結果：表面微觀結構分析表明，添加Haq和Caq有助於ICC顆粒間的結合。表面元素分析表明，添加Haq增加了Ca離子含量。凝固時間結果表明，與Daq相比，Caq和Haq分別使最終凝固時間縮短了46.5%和34.7%（ P < 0.05）。 Caq的抗壓強度分別比Daq和Haq高35.1%和13.4%（ P < 0.05）。三種ICC組的黏接強度結果表明，樹脂黏接劑的效果相同（ P > 0.05）。生物相容性和清除活性測試表明，ICC優於樹脂黏接劑。

結論： ICC與Caq合併使用可縮短凝固時間、提高抗壓強度、增強生物相容性並降低發炎發生的可能性。因此，ICC與Caq聯合使用可作為牙科樹脂黏固劑的替代方案。