Compliance Challenges Research Articles

Caregiver’s experiences with a mobile-based educational program and its impact on dietary treatment compliance of children with methylmalonic acidemia: an online survey

BackgroundCompliance to highly restrictive diets is critical for children with Methylmalonic Acidemia (MMA), and their caregivers play a prominent role in children’s dietary treatment from early childhood through to adulthood. Despite lots of efforts by the multidisciplinary medical team to ensure the smooth implementation of dietary treatment, restricting dietary protein remains particularly challenging for children with MMA. This study aimed to assess dietary treatment compliance in children with MMA and evaluate the impact of WeChat-based parent education on compliance.MethodsA sample of 151 caregiver-child dyads was obtained through online recruitment using convenience sampling from February to March 2023. At least one month following the enrollment of MMA caregivers in the WeChat public account “Methylmalonic Acidemia Diet Manager”, structured questionnaires were distributed to them through the electronic platform “Questionnaire Star” in collaboration with the Chinese National Alliance of Rare Diseases. Subsequently, the collected data was analyzed using quantitative methods.ResultsChildren with MMA aged over 5 years were more likely to present a lower level of dietary treatment compliance compared to those under 1 year old. Besides, the levels of children’s dietary treatment compliance were higher when their caregivers had higher levels of satisfaction and benefit from using the public account.ConclusionOur findings highlighted the significance of age-related challenges in dietary treatment compliance among children with MMA and the promising impact of utilizing WeChat public accounts as a supportive education tool.

Strengthening Compliance with Data Privacy Regulations in U.S. Healthcare Cybersecurity

This study evaluates the state of data privacy and cybersecurity compliance within the U.S. healthcare sector, leveraging data from the U.S. Department of Health & Human Services Breach Portal, Verizon Data Breach Investigations Report, and the Health IT Dashboard. A quantitative methodology comprising descriptive statistical analysis, K-means clustering, and multivariate regression was employed to examine healthcare data breaches, categorize cybersecurity threats, and identify compliance challenges. Findings revealed a persistent increase in breaches, with hacking/IT incidents comprising over 80% of breaches in 2020 and a peak of 135 incidents in 2021. Budget allocation emerged as the most significant predictor of compliance (p = 0.0178), affirming resource constraints. Malware and ransomware were identified as dominant threats, while insider threats emerged as high-impact vulnerabilities. The study recommends increasing cybersecurity budgets, implementing continuous staff training, harmonizing regulations, and adopting Cybersecurity Maturity Models to systematically enhance security postures. The study provides critical insights into the challenges faced by healthcare organizations in achieving compliance with evolving data privacy regulations such as HIPAA and HITECH. The findings highlight the economic and operational implications of non-compliance, including financial penalties, reputational harm, and patient trust erosion. The study further affirms the importance of strategic investments in advanced cybersecurity tools, policy harmonization, and employee education. Hence, policymakers and healthcare administrators can utilize these insights to foster a robust culture of compliance, ensuring the protection of sensitive patient information and the resilience of healthcare operations against cyber threats. The study suggests that future research explores integrating artificial intelligence, zero-trust architectures, and adaptive risk management frameworks to further enhance cybersecurity strategies and regulatory compliance.

Survey of Artificial Intelligence Model Marketplace

The rapid advancement and widespread adoption of artificial intelligence (AI) across diverse industries, including healthcare, finance, manufacturing, and retail, underscore the transformative potential of AI technologies. This necessitates the development of viable AI model marketplaces that facilitate the development, trading, and sharing of AI models across the pervasive industrial domains to harness and streamline their daily activities. These marketplaces act as centralized hubs, enabling stakeholders such as developers, data owners, brokers, and buyers to collaborate and exchange resources seamlessly. However, existing AI marketplaces often fail to address the demands of modern and next-generation application domains. Limitations in pricing models, standardization, and transparency hinder their efficiency, leading to a lack of scalability and user adoption. This paper aims to target researchers, industry professionals, and policymakers involved in AI development and deployment, providing actionable insights for designing robust, secure, and transparent AI marketplaces. By examining the evolving landscape of AI marketplaces, this paper identifies critical gaps in current practices, such as inadequate pricing schemes, insufficient standardization, and fragmented policy enforcement mechanisms. It further explores the AI model life-cycle, highlighting pricing, trading, tracking, security, and compliance challenges. This detailed analysis is intended for an audience with a foundational understanding of AI systems, marketplaces, and their operational ecosystems. The findings aim to inform stakeholders about the pressing need for innovation and customization in AI marketplaces while emphasizing the importance of balancing efficiency, security, and trust. This paper serves as a blueprint for the development of next-generation AI marketplaces that meet the demands of both current and future application domains, ensuring sustainable growth and widespread adoption.

From money laundering to illicit finance? The evolving ‘AML’ regulatory regimes for legal professionals in the UK and Australia

ABSTRACT Since the introduction of the global anti-money laundering (AML) regime, the focus of (inter)national concern has broadened, from the laundering of the proceeds of drug trafficking and other organised crimes to a range of crime and security issues captured by the term ‘illicit finance’. These include money laundering, terrorism financing, proliferation financing, tax evasion, corruption, kleptocracy and sanctions evasion. This article considers how this shift from ‘money laundering’ to ‘illicit finance’ has changed the nature of the ‘AML’ regime for legal professionals in the UK, and what lessons this holds for Australia amidst ongoing regulatory reform. It argues that legislation enacted in the UK since 2017, encompassing key themes of transparency and financial sanctions, has expanded the ‘gatekeeper’ role of legal professionals, creating further opportunities to prevent or enable illicit finance and further regulatory obligations (and potential exposure to criminal sanctions). A reformed Australian AML/CTF regime should aim to address all relevant crime and security threats and the various ways that individual actors, systemic factors and regulatory gaps within professional service provision can enable illicit finance. However, it must also recognise and manage the implications of ever-expanding regulatory obligations, and the compliance challenges these obligations can create.

Advising Estates of Non-Resident Non-Citizen Decedents: Historical Context and Compliance Challenges

Advising Estates of Non-Resident Non-Citizen Decedents: Historical Context and Compliance Challenges

Designing AI driven compliance frameworks to expand digital banking access in underserved US Communities

Expanding digital banking access in underserved communities is vital to financial inclusion in the United States. However, regulatory compliance challenges and a lack of tailored banking solutions hinder progress. This paper explores the integration of Artificial Intelligence (AI) to create dynamic compliance frameworks that facilitate broader access to digital banking. AI can not only streamline regulatory adherence but also personalize banking services, fostering trust and reducing barriers for underserved populations. By combining AI capabilities with robust compliance measures, financial institutions can ensure equitable banking access while maintaining regulatory integrity.

Enhancing ZIS management through marketplace platforms: Opportunities and sharia compliance challenges

Zakat Institutions and marketplace platforms have established a collaboration to adapt to the growing shift toward digital transaction patterns in managing Zakat, Infaq, and Shadaqah (ZIS). Marketplaces offer convenience in ZIS collection, while LAZ ensures Sharia compliance in fund management. This study highlights how such collaboration significantly expands the reach of ZIS collection, presenting immense potential, but also identifies challenges in ensuring Sharia compliance and accountability. The research employs a qualitative methodology to explore the dynamics of the collaboration between Zakat Institutions and marketplace platforms. Thematic analysis was applied to identify key themes related to the opportunities and challenges of the collaboration. The research contributes to the understanding of digital platforms' role in faith-based financial management, offering practical insights for enhancing cooperation between LAZ and marketplaces. It emphasizes the need for dialogue, public education about ZIS and qurban, and system adjustments to ensure Sharia compliance. The findings have practical implications for improving digital ZIS management through enhanced accountability and regulatory frameworks, making this collaboration a model for leveraging technology in religious fund management

Navigating Credit Risk in Islamic banks: A Multidimensional Analysis of Non-Performing Loans

Purpose ‒ This study examines the determinants of non-performing loans (NPLs) in Islamic banks. The research aims to identify bank-specific and macroeconomic factors that influence NPLs and explores the effects of the institutional environment, product development, and credit concentration on credit risk. Design/Methodology/Approach ‒ The study employs panel data analysis, utilising secondary data from 2008- 2022 from the World Bank, Refinitiv Eikon, FitchConnect and the AAOIFI website. Multiple regression models are used to isolate the impact of specific variables on NPLs in Islamic banks. Findings ‒ The results indicate that return on assets (ROA), liquidity ratio (LIQ), net interest margin (NIM), and net charge-off ratio (NCOFF) are significant bank-specific determinants of NPLs. Higher ROA and LIQ reduce credit risk, while higher NIM and NCOFF increase it. Macroeconomic factors like GDP growth and inflation significantly affect NPLs, with economic downturns and high inflation intensifying credit risk. Political stability mitigates risk, while credit concentration in sectors such as real estate increases NPLs. A positive relationship between AAOIFI membership and NPL suggests compliance challenges. Originality/Value ‒ This study comprehensively analyses NPL determinants in Islamic banks across 30 countries, emphasising the role of institutional stability and prudent product development in credit risk management. Research Limitations/Implications ‒ The unavailability of NPL data from earlier years results in an unbalanced sample. Future research should explore the impact of Fintech and ESG (environmental, social, and governance) factors on credit risk management in Islamic banks. Practical Implications ‒ The findings offer valuable insights for policymakers and banking practitioners aiming to enhance credit risk management in Islamic banking. Integrating fintech and ESG principles can improve risk profiles and foster sustainable banking practices.

Methodology for Safe and Secure AI in Diabetes Management.

The use of artificial intelligence (AI) in diabetes management is emerging as a promising solution to improve the monitoring and personalization of therapies. However, the integration of such technologies in the clinical setting poses significant challenges related to safety, security, and compliance with sensitive patient data, as well as the potential direct consequences on patient health. This article provides guidance for developers and researchers on identifying and addressing these safety, security, and compliance challenges in AI systems for diabetes management. We emphasize the role of explainable AI (xAI) systems as the foundational strategy for ensuring security and compliance, fostering user trust, and informed clinical decision-making which is paramount in diabetes care solutions. The article examines both the technical and regulatory dimensions essential for developing explainable applications in this field. Technically, we demonstrate how understanding the lifecycle phases of AI systems aids in constructing xAI frameworks while addressing security concerns and implementing risk mitigation strategies at each stage. In addition, from a regulatory perspective, we analyze key Governance, Risk, and Compliance (GRC) standards established by entities, such as the Food and Drug Administration (FDA), providing specific guidelines to ensure safety, efficacy, and ethical integrity in AI-enabled diabetes care applications. By addressing these interconnected aspects, this article aims to deliver actionable insights and methodologies for developing trustworthy AI-enabled diabetes care solutions while ensuring safety, efficacy, and compliance with ethical standards to enhance patient engagement and improve clinical outcomes.

Elastic Search AI in Enterprise Systems: Revolutionizing Universities and Health Institutions

This article explores the revolutionary impact of ElasticSearch AI in transforming data management and operational efficiency within universities and healthcare institutions. The article examines how this technology addresses critical challenges in data volume management, regulatory compliance, and operational effectiveness across these sectors. Through comprehensive article analysis, the research demonstrates how Elastic Search AI's advanced search, analytics, and security capabilities have fundamentally altered how institutions handle information and make decisions. The article covers the technology's implementation across various domains, from administrative functions to research capabilities, highlighting its role in enhancing user experiences and institutional effectiveness. By examining specific applications in both educational and healthcare settings, the study reveals how ElasticSearch AI enables personalized learning environments, streamlined administrative processes, and improved healthcare delivery systems. The article also provides detailed implementation guidelines, emphasizing the importance of strategic planning, security measures, and system maintenance in achieving optimal results. This article contributes to understanding how artificial intelligence and search technologies can be effectively deployed to address complex institutional challenges while maintaining security and efficiency.

Cyber Security Threats and its Analysis

The rapid evolution and adoption of cloud computing have revolutionized the way organizations store, manage, and access data. However, this transition has introduced a wide array of cybersecurity threats, posing significant challenges to data integrity, confidentiality, and availability. This review paper provides a comprehensive analysis of cybersecurity threats in cloud environments, with a focus on understanding their implications and exploring effective mitigation strategies. The study categorizes cloud security threats into several key areas, including data breaches, account hijacking, insecure interfaces, and denial of service (DoS) attacks IEEE Xplore MDPI. It highlights how shared technology vulnerabilities and malicious insider threats exacerbate these risks, especially in multi-tenant cloud architectures IEEE Xplore. These issues are further compounded by regulatory and compliance challenges, requiring organizations to navigate complex legal landscapes while maintaining robust security protocols MDPI. To counter these threats, various technical and organizational measures are examined. Technical solutions such as encryption, intrusion detection systems, and blockchain technologies offer promising avenues for securing data and preventing unauthorized access IEEE Xplore IEEE Xplore . Additionally, adopting zero-trust architectures and leveraging artificial intelligence for real-time threat detection are identified as emerging trends that could significantly enhance cloud security MDPI. The paper also discusses the role of policy frameworks and regular security audits in fostering a culture of security awareness. Emphasis is placed on the need for a collaborative approach involving governments, academia, and industry stakeholders to develop innovative, scalable, and resilient security solutions. In conclusion, while cloud computing offers unparalleled benefits in terms of scalability and efficiency, its security challenges require a multifaceted approach. This review underscores the importance of continuous innovation in cybersecurity measures to safeguard against evolving threats, ensuring that cloud environments remain a reliable and secure platform for organizations worldwide..

Enhancing Buccal Drug Delivery: The Impact of Glycerol in Slot-Die-Coated Pectin Films.

Buccal delivery offers a promising alternative to e.g., oral or parenteral drug administrations by leveraging the mucosal membranes of the mouth to enhance drug absorption and enhance patient compliance. Buccal films offer a promising approach for enhancing drug delivery by utilizing the mucoadhesive properties of the biopolymer pectin and glycerol's plasticizing effects. Designed to provide fast drug release, these films address the challenges of patient compliance, particularly among the elderly, children, and individuals with dysphagia. This study characterized the physicochemical properties of slot-die-coated films with pectin containing varying amounts of glycerol, including swelling behavior, disintegration rate, mechanical properties, mucoadhesion, and drug release profiles, using paracetamol as a model drug. Different methods such as quartz crystal microbalance with dissipation and open-source force analyzer were employed for the characterization. The results demonstrated that a high glycerol content in the films led to slower drug release with 95% paracetamol released for film without glycerol (GLY0) compared to only 74% released for film with 20% w/v glycerol (GLY20) after 60 min Additionally, higher glycerol levels resulted in enhanced mucoadhesive properties. Films containing 20% glycerol also showed superior permeability of paracetamol through ex vivo porcine buccal mucosa, with double the amount of paracetamol permeating in the first 120 min from GLY20 films compared to GLY0 films. These findings suggest that the pectin-glycerol buccal films, fabricated with slot-die coating as a novel technique, are user-friendly, exhibit interaction with the mucosa, and can be adjusted for specific disintegration and drug release rates, presenting a promising option for efficient, targeted drug delivery.

Nexus of Tax Law and Non-Profit Organizations: Incentives and challenges in compliance with tax laws by Public Benefit Organizations in South Africa: a scoping review

This study examines the tax incentives and challenges faced by Non-Profit Organisations (NPOs) in South Africa, with a focus on those registered as Public Benefit Organisations (PBOs). NPOs play a vital role in addressing socio-economic issues, and serving vulnerable communities. While these organizations operate for non-profit purposes, the tax incentives provided by the government are crucial for their financial sustainability. Therefore, establishing a supportive tax framework is essential to promote their growth and operational capacity. A scoping review methodology was employed, analyzing literature on tax incentives and compliance challenges faced by South African NPOs from 2010 to 2023. Key provisions include income tax exemptions under Section 10(1)(cN), capital gains tax exclusions, and Section 18A tax-deductible donations. The study also explored the legal framework governing tax-exempt status and trading activities. Findings show that while tax incentives provide significant benefits, NPOs face challenges in maintaining compliance, such as complex regulations, limited financial resources, and a lack of expertise. Many struggle with differentiating between exempt and taxable activities. Strategies to address these issues include simplifying tax processes, enhancing financial management education, and improving communication between SARS and NPOs. Introducing user-friendly tax reporting systems and tailored support could further boost compliance and ensure NPOs maximize available benefits. These insights are valuable for policymakers and tax authorities seeking to strengthen the regulatory framework and support the growth of NPOs in South Africa.

EXAMINING THE EU POLICIES AND CORPORATE RELATIONS THROUGH A CYBERSECURITY LENS

The present paper integrates a broad analysis of European Union policies and their synergy with private corporations through a cybersecurity filter. As the digital landscape evolved, the EU has implemented a series of regulations and directives aimed at sustaining cybersecurity across member states. Various EU regulations establish strict requirements for cyber resilience and data protection. The analysis explores how these policies affect private corporations, emphasizing the impact on operational practices and compliance challenges. The paper examines the joint frameworks established between the EU and private sector entities, such as information-sharing initiatives and public-private partnerships. A bibliometric analysis was conducted to highlight the connections between the key terms used in the study. This analysis allows understanding of the interferences between the cybersecurity-related EU framework and private companies operating in the EU.

EXAMINING THE EU POLICIES AND CORPORATE RELATIONS THROUGH A CYBERSECURITY LENS

The present paper integrates a broad analysis of European Union policies and their synergy with private corporations through a cybersecurity filter. As the digital landscape evolved, the EU has implemented a series of regulations and directives aimed at sustaining cybersecurity across member states. Various EU regulations establish strict requirements for cyber resilience and data protection. The analysis explores how these policies affect private corporations, emphasizing the impact on operational practices and compliance challenges. The paper examines the joint frameworks established between the EU and private sector entities, such as information-sharing initiatives and public-private partnerships. A bibliometric analysis was conducted to highlight the connections between the key terms used in the study. This analysis allows understanding of the interferences between the cybersecurity-related EU framework and private companies operating in the EU.

Automated cybersecurity compliance and threat response using AI, blockchain and smart contracts

AbstractTo address the challenges of internal security policy compliance and dynamic threat response in organizations, we present a novel framework that integrates artificial intelligence (AI), blockchain, and smart contracts. We propose a system that automates the enforcement of security policies, reducing manual effort and potential human error. Utilizing AI, we can analyse cyber threat intelligence rapidly, identify non-compliances and automatically adjust cyber defence mechanisms. Blockchain technology provides an immutable ledger for transparent logging of compliance actions, while smart contracts ensure uniform application of security measures. The framework’s effectiveness is demonstrated through simulations, showing improvements in compliance enforcement rates and response times compared to traditional methods. Ultimately, our approach provides for a scalable solution for managing complex security policies, reducing costs and enhancing the efficiency while achieving compliance. Finally, we discuss practical implications and propose future research directions to further refine the system and address implementation challenges.

Innovative Orthodontic-Restorative Treatment With Customized CAD/CAM Smartwires.

The demand for discreet and low-compliance appliances has driven innovation in orthodontics, particularly with technological advances in artificial intelligence, robotics, and CAD/CAM technology. The evolution of Programmed Non-Sliding Mechanics for precise, automated tooth movement is the latest innovation. In this article, we aimed to demonstrate the application of a novel orthodontic lingual appliance, The Gen 2 InBrace system (InBrace, Irvine, CA), in the orthodontic-restorative treatment of an adult patient with anterior tooth-size discrepancies, anterior openbite, and incisor proclination. The Gen 2 InBrace system uses a new generation of CAD/CAM Smartwires, including pre-programmed customized multiloop nickel-titanium lingual archwires, which enable light, continuous, and frictionless tooth movements. The Gen 2 InBrace system can enhance esthetic and occlusal outcomes in patients requiring combined orthodontic-restorative treatment via automatic space management with maximum esthetic and minimal compliance. Precision dentistry and orthodontics using esthetic custom appliances have become a reality. The Gen 2 InBrace system, a new generation custom lingual appliance, offers effective treatment solutions for adults who have previously avoided preprosthetic orthodontics due to the esthetic concerns of wearing traditional labial braces or the compliance challenges associated with clear aligners.

Multi-Material 3D Printing and Computational Design in Pharmaceutical Tablet Manufacturing

Multi-material 3D printing has revolutionized pharmaceutical tablet manufacturing by enabling unprecedented control over the spatial arrangement of active pharmaceutical ingredients (APIs) and excipients. This systematic review analyzes the significant advances in computational methods and 3D printing technologies for pharmaceutical applications from 2005 to 2024. The review explores the integration of artificial intelligence and evolutionary algorithms in solving complex inverse problems of tablet design, where computational methods achieve better accuracy in predicting drug release profiles. Recent developments in material science, including novel thermoresponsive polymers and stimuli-responsive materials, have enhanced manufacturing capabilities while maintaining drug stability. Clinical trials and real-world implementations demonstrate improvements in therapeutic outcomes, with personalized 3D printed medications showing enhanced treatment efficacy and better safety profiles compared to conventional formulations. The review also addresses critical challenges in regulatory compliance, quality control, and scale-up processes, providing a framework for future developments in personalized medicine manufacturing. This work synthesizes current knowledge and identifies emerging trends, offering insights into the future direction of pharmaceutical 3D printing technology and its implications for personalized medicine.

Research on an Elderly Indoor Fall Detection System Based on IoT and Computer Vision Technology: Integration and Performance Analysis of YOLOv5 and OpenPose

The rapid growth of the global elderly population has led to an increased need for efficient and reliable fall detection systems to ensure timely medical assistance. Traditional monitoring methods, such as wearable devices and environmental sensors, often face challenges in accuracy, reliability, and user compliance. This study proposes an indoor fall detection system for the elderly, integrating Internet of Things (IoT) and computer vision technologies, specifically utilizing YOLOv5 and OpenPose algorithms. YOLOv5 is employed for rapid and accurate human body detection, providing position information by computing the center of objects in frames or videos. OpenPose is then used for detailed real-time pose estimation, detecting 135 key points on the human body—including hands, face, and feet—to assess whether a fall has occurred based on posture analysis. The system was tested using two datasets, GMDCSA and URFD, achieving sensitivity values of 0.9412 and 0.9583, respectively, indicating high accuracy in fall detection. The false positive rates were 0.0588 and 0.2857, while the false negative rates were 0.0588 and 0.0417, demonstrating the system's reliability in minimizing detection errors. The integration of YOLOv5 and OpenPose leverages their combined strengths in object detection and pose estimation, resulting in a robust solution suitable for real-time applications.

AI-Driven Diagnostics and Imaging: Transforming Early Detection and Precision in Healthcare

Artificial intelligence is revolutionizing medical imaging and diagnostics, marking a transformative era in healthcare delivery. This comprehensive article explores the evolution from early computer-aided diagnosis systems to sophisticated deep-learning architectures, examining their impact across radiology, pathology, and clinical workflows. The article covers breakthrough technologies, including vision transformers, multi-modal integration, and explainable AI frameworks, highlighting their contributions to improved diagnostic accuracy and efficiency. The article encompasses the clinical benefits of early disease detection, workflow optimization, and cost reduction while addressing crucial challenges in regulatory compliance, ethical considerations, and data privacy. Looking ahead, the review examines emerging trends in federated learning, infrastructure requirements, and the economic implications of AI implementation in healthcare settings, providing insights into the future landscape of AI-driven medical imaging.