Digital Commons Network^™

Conservative Non-Surgical Endodontic Management Of A Large Cyst-Like Periapical Tunnel Lesion With 22-Month Cbct Follow-Up: A Case Report, Smriti Rohilla, Sameer Makkar, Sandeep Gupta

International Arab Journal of Dentistry

The present case report epitomises the successful non-surgical management of a large cyst-like periapical tunnel lesion of endodontic origin due to trauma using Lesion Sterilization and Tissue Repair technique. Endodontic orthograde treatment (and re-treatment) was performed in association with triple antibiotic paste as an intra-canal medication in a sixteen-year boy. Preoperative CBCT as well as at the 22 months CBCT followup were used to compare the evolution of the healing of the lesion. Accurate diagnosis in combination with non-surgical orthograde endodontic treatment can lead to can lead to complete healing of large lesions without any need of surgical intervention.

Patient-Related And Tooth-Related Factors As Predictors For Tooth Loss In Periodontitis Patients: A Systematic Review, Cleane Daraze, Carole Chakar, Abdelrahman Kassir, Charbel Anka, Jean-Marie Megarbane

International Arab Journal of Dentistry

Introduction: The treatment of periodontitis aims to prevent further disease progression, to minimize symptoms and perception of the disease, possibly to restore lost tissues and to support patients in maintaining a healthy periodontium. Management of chronic periodontal disease requires a combination of therapeutic modalities and a lifelong commitment to periodontal self-care.

Objectives: The aim of this study is to evaluate predictors for tooth loss in patients previously diagnosed with periodontitis. This systematic review covers studies of over 10 years of follow up.

Methods: Electronic literature search was conducted on 19/02/2024 by one author across several databases, including …

Comparative Evaluation Of Marginal And Internal Fit Of Zirconia Crown Designed Using Artificial Intelligence And Cad-Cam Software: A Systematic Review, Pritesh Gangde, Sweta Kale Pisulkar, Arushi Beri, Pritam Das

International Arab Journal of Dentistry

Introduction: The long-term performance of dental restorations depends on their internal and marginal fits. Improvements in the fit of restorations, especially zirconia crowns, have been investigated through the use of diverse materials, manufacturing processes, and impression techniques.

Objectives: The purpose of this review was to examine the internal and marginal fit of zirconia crowns made with CAD/CAM software with artificial intelligence (AI) software.

Methods: Using a combination of keywords and MeSH terms, the literature search was carried out across seven databases: PubMed, Scopus, Web of Science, Cochrane Library, Embase, ProQuest, and ScienceDirect from inception till 1st of …

2025 Digital Commons And Experts Annual Report, Amanda Steinvall

Publications 2026-present

No abstract provided.

The Massachusetts Proactive Coastal Relocation Workshop: Summary Report & Proceedings, Kristin Uiterwyk, Kimberly Starbuck, Emma Gildsgame, Andrew Laquerre, Melissa Ocana, Elisa Rivero

Urban Harbors Institute Publications

On June 3rd, the project team held the “Massachusetts Coastal Relocation Workshop” which provided the first opportunity for the Coastal Relocation Network members to come together in-person. More than 70 people attended and, among other things, (1) made new connections through activities designed to encourage engagement; (2) learned about new and forthcoming plans, tools, and resources; and (3) were encouraged to think deeply about planning for retreat, engaging communities, and using data to inform decisions

Enhancing Intrusion Detection Systems With Adaptive Neuro-Fuzzy Inference Systems, Jitender Sharma, Sonia ., Karan Kumar, Pankaj Jain, Pankaj Jain, Hussein Alkattan

Mesopotamian Journal of CyberSecurity

Network security has become increasingly critical in recent years. Among the various aspects of network security and considering several approaches to network security, intrusion detection systems (IDSs) have gained considerable attention. The prominence of this factor, among other factors of network security, is due to its ability to address the complex and uncertain nature of security breaches. Whenever data flow over the network, precise categorization of normal and malicious data is necessary. Past IDS systems lack precise categorization. Thus, the present study focuses on the use of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier to categorize network instances …

Improvement Of Internet Of Things (Iot) Interference Based On Pre-Coding Techniques Over 5g Networks, Inas F. Jaleel, Rasha S. Ali, Ghassan A. Abed

Mesopotamian Journal of CyberSecurity

The advent of 5G technology has revolutionized wireless communication, offering unprecedented data rates, reduced latency, and enhanced connectivity. A critical component driving these advancements is Multiple-Input Multiple-Output (MIMO) technology. MIMO utilizes multiple antennas at both the transmitter and receiver ends to improve communication performance. In the context of the Internet of Things (IoT), MIMO plays a pivotal role in enhancing network efficiency, reliability, and capacity and can improve system capacity and reduce interference between different users. By leveraging MIMO, IoT devices can achieve higher data throughput and better signal quality, even in challenging environments. This is particularly important for IoT …

Hybrid Cooperative Spectrum Structured (Hcss) Approach For Adaptive Routing In Cognitive Radio Ad Hoc Networks, Sadeem Dheyaa Shamsi, Ameer Sameer Hamood Mohammed Ali, Wameed Deyah Shamsi

Mesopotamian Journal of CyberSecurity

Cognitive radio networks provide an important function in the efficient use of the radio spectrum. Therefore, dedicated cognitive radio ad hoc networks (CRAHNs) are expected to improve communication performance in a multihop network that requires a dedicated routing protocol that considers the dynamic mobility of secondary user nodes on the basis of the random availability of primary node channels. To enhance routing in the CRAHNs environment, in this paper, a novel Hybrid Cooperative Spectrum Structured (HCSS) approach that combines cooperative spectrum sensing and spectrum-aware routing protocols can be effective in appropriate decision making for routing packets in such a network. …

Data Mining And Machine Learning-Based Healthcare Monitoring In Cloud-Iot, Sarah Amer, Rania Hazim, Wassan Kader

Mesopotamian Journal of CyberSecurity

Healthcare monitoring Cloud-IoT systems use data mining and machine learning methods to analyse patient data in real-time from linked devices. By offering insights for the early diagnosis of anomalies and individualized treatment suggestions, this strategy improves healthcare management. In this research first the Collect and Load the Clevant Heart Disease Dataset for Data Collection Process. Next, preprocess the loaded data using the Synthetic Minority Oversampling Technique (SMOTE), and then the feature extraction process is done using the Principal Component Analysis (PCA) Method. In this case, the characteristic must be extracted by feeding a specific column. The classification procedure is then …

Department Of Computer Engineering, University Of Diyala, 32001 Diyala, Iraq., Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel

Mesopotamian Journal of CyberSecurity

Android devices are rapidly being used, which makes it easy for the malware threat to rise to higher levels. This ever-growing problem has prompted the need to enhance detection systems as far as these devices are concerned. Standard techniques of machine learning (ML) are sufficient from the point of view of their speed for searching patterns and behaviors of contemporary malware; however, it is more important to have effectively enhanced methods. The purpose of this paper is to expand the utilization of Android malware identification via artificial neural networks (ANNs) and compare its efficiency with that of other ML methods. …

Exploring The Impact Of Blockchain Revolution On The Healthcare Ecosystem: A Critical Review, Maad M. Mijwil, Mohammad Aljanabi, Mostafa Abotaleb, Ban Salman Shukur, Ban Salman Shukur, Indu Bala, Kamal Kant Hiran, Ruchi Doshi, Klodian Dhoska

Mesopotamian Journal of CyberSecurity

Blockchain technology is a type of distributed ledger that provides secure and efficient storage, management, and transmission of data over a decentralized network. With its ability to ensure transparency and immutability, blockchain is increasingly adopted across various sectors ranging from finance, healthcare, and logistics to education. In healthcare, blockchain technology is attracting attention because of its potential to fundamentally transform health ecosystems. The healthcare sector has significantly benefited from blockchain technology by enhancing data security and interoperability and reducing medical errors. In this context, a set of studies highlighted the importance of blockchain in the field of healthcare, enhancing trust …

Antdroidnet Cybersecurity Model: A Hybrid Integration Of Ant Colony Optimization And Deep Neural Networks For Android Malware Detection, Riyadh Rahef Nuiaa Al Ogaili, Osamah Adil Raheem, Mohamed H Ghaleb Abdkhaleq, Zaid Abdi Alkareem Alyasseri, Zaid Abdi Alkareem Alyasseri, Ali Hakem Alsaeedi, Yousif Raad Muhsen, Selvakumar Manickam

Mesopotamian Journal of CyberSecurity

Malware detection is a vital problem, and efficient methods that can efficiently detect malware are needed. The increasing use of mobile computers makes malware detection a vital part of security in an era where smartphones have come to play a key role in many of our daily lives. Earlier approaches, however, suffer from high false positive rates; they are not scalable for larger databases, or they are not amenable to adapt well to novel zero-day malware. For these reasons, the demand for more sensitive and flexible detection models is high. In this study, we develop a hybrid mobile malware detection …

Enhancing Crime Detection In Video Surveillance Via A Lightweight Blockchain And Homomorphic Encryption-Based Computer Vision System, Tanya Abdulsattar Jaber

Mesopotamian Journal of CyberSecurity

Blockchain technology consists of distributed ledgers or database systems, regarded as immutable, secure, and innovative, characterized by unsupervised internal maintenance with a special security protocol used to prevent inference from malicious or third parties. The widespread use of this technology has led to deep research into the problems posed by this technology, which can be summarized in terms of computational cost and latency time. The crime detection process in video surveillance has made great progress with the use of technologies such as the Internet of Things and blockchain technologies. However, to reach high levels of security in the physical crime …

Improved Blockchain Technique Based On Modified Slim Algorithm For Cyber Security, Sarah Mohammed Shareef, Rehab Flaih Hassan

Mesopotamian Journal of CyberSecurity

The number of cybersecurity incidents is increasing, and the cost of a security breach has a catastrophic financial effect. The existing real estate information systems require more robust and resilient cybersecurity solutions to secure hardware, software, and databases. Cybersecurity often relies on user behavior. Phishing attacks and social engineering can bypass blockchain security, highlighting the need for robust user education and awareness. Many blockchain networks face challenges in handling a high volume of transactions. Solutions that work well on a small scale may not perform efficiently as the network grows, leading to delays and increased costs. A secure system is …

Smartphone Authentication Based On 3d Touch Sensor And Finger Locations On Touchscreens Via Decision-Making Techniques, Moceheb Lazam Shuwandy, Rawan Adel Fawzi Alsharida, Maytham M. Hammood

Mesopotamian Journal of CyberSecurity

Smartphone authentication systems must balance security and user convenience, which is a persistent challenge in the digital realm. Traditional biometrics, such as fingerprints and facial recognition, face vulnerabilities to spoofing and environmental conditions, limiting reliability. This study introduces a novel approach by integrating three-dimensional (3D) touch sensors with finger location data for authentication. The goal is to develop a system that improves accuracy while minimizing false positives and negatives, leveraging touch pressure and spatial interaction as unique biometric identifiers. Data from 20 participants, including pressure levels, spatial coordinates, and timestamps, were analysed using Random Forest (RF) and Extreme Gradient Boosting …

Enhanced Audio Encryption Scheme: Integrating Blowfish, Hmac-Sha256, And Md5 For Secure Communication, Jenan Ayad, Noor Qaddoori, Hasanain Maytham

Mesopotamian Journal of CyberSecurity

In today's communications, it is vital to protect audio data privacy before and after transfer. This work therefore introduces the enhanced audio encryption scheme (EAES), which employs the most effective techniques of cryptography and processes them to make it impossible for unauthorized persons or programs to access or change the contents of audio files. This method uses RSA to encrypt the Blowfish key, which is used for data encryption, the HMAC-SHA256 algorithm for integrity checks, and the Message-Digest algorithm (MD5) for the checking phase. The performance of the EAES is measured statistically via the MSE, PSNR, and correlation coefficient. For …

Enhancing Cybersecurity With Machine Learning: A Hybrid Approach For Anomaly Detection And Threat Prediction, Adil M. Salman, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Hussein Alkattan, Hussein Alkattan

Mesopotamian Journal of CyberSecurity

In today's digital era, cybersecurity has become a principal concern because of the increasing frequency and advancement of cyber threats. This study explores machine learning models for detecting and predicting anomalies in cybersecurity datasets. The research evaluates models such as linear regression, decision tree, RF, gradient boosting, KNN, SVR, LSTM, and neural networks utilizing performance metrics such as accuracy, MAE and MSE. A hybrid model that integrates different learning strategies is additionally proposed to improve the predictive accuracy and strength. The results highlight the superiority of ensemble approaches, especially the hybrid model, in improving peculiarity detection capabilities. The comparative analysis …

Secured Multi-Objective Optimisation-Based Protocol For Reliable Data Transmission In Underwater Wireless Sensor Networks, Mostfa Albdair, Zainab Rustum Mohsin, Ahmed Saihood, Aqeel M. Hamad, Aqeel M. Hamad

Mesopotamian Journal of CyberSecurity

Underwater wireless sensor network (UWSN) requirements have increased beyond applications in environmental monitoring and underwater exploration to military surveillance. The complex underwater environment raises many challenges due to high propagation delays, limited bandwidth, high error rates, and dynamic underwater currents. Most traditional clustering algorithms do not consider the multifaceted requirements of UWSNs. In most cases, a single objective is optimised at the cost of other essential factors, such as energy consumption, network robustness, and data transmission reliability. This paper proposes a new UWSN protocol based on the tiger beetle optimisation (TBO) algorithm for multiobjective K-means clustering (TBO-MOK). The protocol comprises …

Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie

Mesopotamian Journal of CyberSecurity

Securing big data in power plants is an important and fundamental step in the infrastructure of smart cities. In addition, it becomes a barrier if it is not controlled from the beginning. Security must be a combination of fast and robust properties. This research presents a traffic security system (TSS) in a smart city (SC). It is a novel paradigm meant to improve data security and integrity by means of a multilayered method. Advanced fault analysis, dual-stage pseudonymizing, quantum key distribution via the BB84 protocol, and Falcon signatures (FS) are combined in the proposed system. TSS enhances data security by …

Learning Techniques-Based Malware Detection: A Comprehensive Review, Sarah Fouad Ali, Musaab Riyadh Abdulrazzaq, Methaq Talib Gaata

Mesopotamian Journal of CyberSecurity

The rapid proliferation of Internet of Things (IoT) devices has significantly increased the threat landscape, with malwares arising as a critical concern. Advanced learning methods such as machine learning (ML), deep learning (DL), and federated learning (FL) are essential for handling complex IoT data. ML provides tools for pattern identification and detecting anomalies. DL boosts malware detection by automatically extracting features and identifying patterns. FL enables collaborative model training across decentralized devices, ensuring data privacy, which is crucial for diverse IoT systems. This comprehensive review specifically synthesizes ML, DL and FL for malware detection in the IoT environment, highlighting key …

Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi

Mesopotamian Journal of CyberSecurity

In the current digital landscape, information security has become a critical necessity given the escalating frequency and sophistication of cyberattacks across global computing networks. Cryptography is the science and practice of securing information by transforming it into a format that is unreadable or inaccessible to unauthorized parties. The strength of the cryptography algorithm lies in the strength of used encryption key. Recently, the nonlinear behavior of chaotic maps has been utilized as a random source to generate robust key stream bits for cryptographic purposes. The aim of this paper is to introduce an efficient and robust system for generating strong …

Regulation Of Ocean Alkalinity Enhancement In Washington State, Ashwin Murthy, Korey Silverman-Roati, Romany M. Webb

Sabin Center for Climate Change Law

This paper focuses on one commonly-discussed ocean carbon dioxide removal approach, ocean alkalinity enhancement (“OAE”), which involves adding alkaline substances to ocean waters in order to increase their ability to uptake carbon dioxide from the atmosphere. OAE also has the potential to mitigate ocean acidification, which has been worsening globally due to climate change, and has threatened marine life and industries in places like Washington State.

There is significant interest in pursuing OAE off the coast of Washington state. This paper examines the legal framework for OAE projects in Washington State. As we explain, OAE projects conducted in near-shore areas …

Evidence-Based Strategies For Novice Teachers: Increasing The Participation Of Students With Autism Spectrum Disorder In Integrated Physical Education, Kristina K. Vargo, Jihyun Lee

Faculty Research, Scholarly, and Creative Activity

Autism spectrum disorder (ASD) is a pervasive developmental disorder that impacts approximately 1 in 36 students. Because of its high prevalence, it is likely that all physical education teachers will serve students with ASD during their careers. Although physical education leads to many improvements in students’ physical and social skills, students with ASD may experience challenges in the integrated physical education setting due to various factors, including motivation, skill proficiency, challenging behaviors, and sensory stimulation. The purpose of this article is to describe the challenges faced by some students with ASD in integrated physical education and to provide novice teachers …

Symp25s: Cactas-Ai: Automatic Segmentaion Of Calcified Plaque In Carotid Arteries, Jiehyun Kim, Kevin Wang, Yu Sakai, Youxiang Zhu, Andrew C. Hu, Huy Q. Phi, Nathan Arnett, Grace J. Wang, Brett L. Cucchiara, Jae W. Song, Daniel Haehn

Paul English Applied Artificial Intelligence (AI) Institute Publications

Manual segmentation of calcified plaque, essential for assessing stroke risk, is time-consuming, and conventional methods like 2D and 3D UNet often struggle with the small size. We developed CACTAS-AI, a two-step segmentation process. This approach outperforms baseline methods in plaque segmentation.

Exploration Of The Effects Of Tai Chi Practice On Lower Limb Corticomuscular Coherence During Balance-Demanding Virtual Reality Conditions In Older Adults, Yang Hu, Elizabeth T. Hsiao-Wecksler, Manuel E. Hernandez

Faculty Research, Scholarly, and Creative Activity

Tai Chi practice has been widely adopted to improve balance and prevent falls in older adults. However, the neural mechanisms underlying the benefits of Tai Chi are difficult to evaluate during traditional balance assessments. The goal of this study was to evaluate the effects of Tai Chi and healthy aging on corticomuscular coherence (CMC) while standing in virtual balance-demanding environments. We recorded neural, muscular, and behavioral data in an immersive virtual reality environment while implementing sensory and mechanical perturbations to introduce high postural threats. Through the acquisition of electroencephalography and electromyography signals, we examined β and γ CMC changes in …

The Hon Ip Kwok-Him, Gbm, Gbs, Jp 葉國謙先生, Gbm, Gbs, Jp

Honorary Fellowship 榮譽院士

No abstract provided.

Mr Ng Leung-Sing, Sbs, Jp 吳亮星先生, Sbs, Jp

Honorary Fellowship 榮譽院士

No abstract provided.

A Review Of The Summer Treatment Program (Stp) For Youth With Callous-Unemotional (Cu) Traits: Moving Past The “Untreatable” Hypothesis, Daniel A. Waschbusch, Pevitr S. Bansal, Michael T. Willoughby

Department of Psychology Faculty Scholarship and Creative Works

Youth with both callous-unemotional (CU) traits and conduct problems (CP) present a significant challenge for treatment due to their disruptive and aggressive behaviors. While traditional interventions often show significant but insufficiently positive effects, the Summer Treatment Program (STP), an intensive behavior therapy program, has shown promise in addressing these challenges. This review examines the existing research on the STP’s effectiveness for youth with CP and CU (CPCU), highlighting its potential to improve behavioral outcomes and treatment response. However, limitations such as small sample sizes, lack of long-term follow-up, and potential iatrogenic effects are also acknowledged. The review then proposes several …

Disentangling The Association Between Cognitive Flexibility And Anxiety In Autistic Youth: Real-World Flexibility Versus Performance-Based Task Switching, Farah Mahmud, Erin Kang, Rachel G. Mcdonald, Drew Wallace, Carrie Masia Warner

Department of Psychology Faculty Scholarship and Creative Works

Introduction: Anxiety symptoms are highly prevalent among autistic youth yet remain under-recognized and undertreated, in part, due to a limited conceptual understanding of autistic cognition. Emerging evidence suggests that autistic differences in cognitive flexibility (CF) may be associated with a greater likelihood of developing and maintaining anxiety symptoms, relative to non-autistic youth. However, further work is needed to elucidate mechanisms of anxiety vulnerability that could inform potential targets for anxiety treatment in autistic youth. The current study aims to examine the associations between CF and anxiety in this population. Given the complexity of CF as a multifaceted construct, we used …

Impact Of Computer-Mediated Versus Face-To-Face Motivational-Type Interviews On Participants’ Language And Subsequent Cannabis Use: Randomized Controlled Trial, Karla D. Llanes, Jon Amastae, Paul C. Amrhein, Nadra Lisha, Katherina Arteaga, Eugene Lopez, Roberto A. Moran, Lawrence D. Cohn

Department of Psychology Faculty Scholarship and Creative Works

Background: Motivational interviewing (MI) is frequently used to facilitate behavior change. The use of change talk during motivational interviews can predict subsequent behavior change. However, no studies have compared the information obtained from traditional face-to-face motivational interviews and computer-mediated motivational interviews or resulted in the same amount of behavior change. Objective: This study aimed to investigate if face-to-face motivational-type interviews (MTIs) and computer-mediated MTIs elicit the same amount of “change talk” and behavior change when young adults discuss their ambivalence about using marijuana. Methods: A total of 150 users, including frequent marijuana users, occasional marijuana users, and non–marijuana users, participated …