This study examines the impact of audit committee gender diversity (ACGD) and women audit ‎partners (WAP) on fraud risk (FR) in Chinese A-share listed companies. It also explores the ‎moderating effect of WAP on the ACGD-FR relationship within China’s dual-signature audit ‎system. Using a quantitative approach, the study analyzes 21,760 firm-year observations from ‎‎2019 to 2023 and employs logistic regression to assess the effects of ACGD, WAP, and their ‎interaction on FR. The results indicate that both ACGD and WAP are significantly and ‎negatively associated with FR, with their interaction further reducing fraud risk. These findings ‎provide important academic implications by extending the audit governance literature through a ‎dual focus on ACGD and WAP, while also offering practical insights for policymakers and ‎corporate managers seeking to enhance governance effectiveness through gender diversity ‎initiatives. The novelty of this study lies in its systematic analysis of the synergistic role of ‎ACGD and WAP in mitigating fraud risk, an area largely overlooked in prior research‎.

The increasing complexity of tax systems and the limitations of traditional rule-based audits have highlighted the need for adaptive, transparent, and efficient auditing solutions. This paper presents the design and evaluation of a Secure AI-Driven Adaptive Audit Transparency Engine (AI-AATE), a novel framework integrating machine learning, explainable AI (XAI), and human-in-the-loop oversight to enhance tax compliance, reduce administrative inefficiencies, and strengthen economic outcomes. The architecture combines supervised and unsupervised models for risk detection, continuous feedback incorporation for adaptive learning, and comprehensive audit logging to ensure transparency, fairness, and traceability. A rigorous evaluation framework employing operational Key Performance Indicators (KPIs), counterfactual simulations, and economic modeling quantifies performance across audit yield, coverage, processing efficiency, revenue recovery, and equity. Governance and trust metrics assess explainability, human oversight, and bias mitigation, linking design principles to measurable institutional outcomes. Simulation results demonstrate that AI-AATE can significantly improve detection of non-compliance, optimize resource allocation, and support equitable and accountable audit selection compared to traditional approaches. By bridging technical design, performance evaluation, and economic impact assessment, this study contributes a holistic methodology for AI-enabled audit systems, offering actionable insights for policymakers, tax authorities, and researchers. The findings underscore the potential of AI-AATE to transform public-sector auditing while maintaining fairness, legitimacy, and public trust, addressing a critical gap in the literature on adaptive, transparent, and secure AI applications in taxation.

The scale and complexity of U.S. federal financial management is growing to a level that is increasingly testing the conventional oversight, audit, and accountability mechanisms. Even though artificial intelligence and sophisticated business analytics have become an appealing tool to deal with fraud, improper payments, and performance monitoring, their implementation in federal programs exceeded the creation of governance frameworks to guarantee transparency, auditability, and democratic accountability. The current literature on AI in government finance is disconnected, as technical literature focuses on analytical performance and policy literature on governance principles, but with limited integration between public finance accounting and audit systems. This study addresses this gap through an integrative review of peer-reviewed research, federal oversight reports, and policy frameworks published between 2020 and 2025. The review integrates insights from public finance, audit practice, and AI governance to examine how AI-driven business analytics are currently applied in U.S. federal financial management and where accountability failures persist. The literature indicates that AI initiatives strengthen oversight only when embedded within existing financial control systems and supported by robust data governance, explainability mechanisms, auditable model outputs, and clearly defined human oversight. Analytics deployed as standalone technical solutions frequently increase opacity and weaken audit assurance. Based on these insights, the paper proposes a multi-layered AI-driven business analytics framework that integrates technical capability with federal accounting standards, audit requirements, and governance structures, repositioning AI as a governance instrument rather than a purely technological tool. Keywords: Artificial Intelligence, Public Financial Management, Federal Audit, Accountability, Transparency, Governance

Purpose This study aims to examine the impact of audit partners’ quality on stock price crash risk in Iran, with particular focus on how agency costs, state ownership and audit firm size moderate this relationship. Iran’s unique dual-signature audit system and the absence of Big 4 firms provide an exceptional setting to explore the role of individual audit partners in an emerging market. The authors hypothesize that higher audit partner quality reduces crash risk, with lead partners having a stronger influence than review partners due to their primary role in decision-making. Design/methodology/approach Using 2,898 firm-year observations from Tehran Stock Exchange-listed companies (2011–2024), audit partner quality is proxied by audit failure rates for lead and review partners. Panel regressions with fixed effects and interaction terms assess the association between partner quality and crash risk, accounting for unobserved heterogeneity. Findings Results show that higher-quality partners significantly reduce crash risk, with lead partners exerting stronger influence than review partners. The effect is more pronounced in firms with higher agency costs, lower state ownership concentration and audits conducted by larger domestic firms. The findings remain consistent when alternative proxies of audit quality – discretionary accruals and audit report modifications – are used. In addition, endogeneity controlled by firm fixed effects and two-stage least squares supports the main findings. Originality/value To the best of the authors’ knowledge, this study is the first to provide evidence from Iran regarding the role of individual audit partner quality in mitigating stock price crash risk. The dual-signature audit system and the absence of Big 4 firms make Iran a unique setting for studying partner-level audit quality. The study contributes to the global discussion on individual auditor accountability and financial market stability, particularly in emerging economies where institutional contexts differ significantly from those in developed markets.

The 2016 United States presidential election was marked by the abuse of targeted advertising on Facebook. Concerned with the risk of the same kind of abuse to happen in the 2018 Brazilian elections, we designed and deployed an independent auditing system to monitor political ads on Meta in Brazil. To do that we first adapted a browser plugin to gather ads from the timeline of volunteers using Facebook. We managed to convince more than 2,000 volunteers to help our project and install our tool. Then, we use a Convolution Neural Network (CNN) to detect political Meta ads using word embeddings. To evaluate our approach, we manually label a data collection of 10k ads as political or non-political and then we provide an in-depth evaluation of proposed approach for identifying political ads by comparing it with classic supervised machine learning methods. Finally, we deployed a real system that shows the ads identified as related to politics during the 2018 National Brazilian elections. We also investigated early electoral advertisement before the 2020 local Brazilian elections using our model on unsponsored content (regular posts in groups and pages). We noticed that not all political ads we detected were present in the Meta Ad Library for political ads on 2018. Additionally, we found possible early electoral advertisements in 2020, which is forbidden in Brazil. Our results emphasize the importance of enforcement mechanisms for declaring political ads and the need for independent auditing platforms.

ABSTRACT This bibliometric review is developed over 267 publications in the Web of Science and draws the indispensable cross-connection of legal coverage, information systems governance (ISG) and audit accountability. It uses co-citation and keyword mapping to identify major works, key intellectual groups or clusters, and innovative clusters, e.g. AI governance or algorithmic auditing. Results show an impressive rise of the research output after 2010, in developed economies. It emphasizes the crucial role in responsible technology systems that is played by law, governance and auditing and reinforces calls for greater international cooperation. It offers a rich source of advices for researchers, practitioners, and policy-makers in the journey of digital transformation.

The main purpose of this thesis is to study the importance of integration between financial sustainability and digital governance and its principles for the sustainability of the comprehensive health insurance system. A survey on an intentional sample consisting of (325) individuals from (workers in the General Authority for Comprehensive Health Insurance / workers in the Ministry of Finance and related to the Authority / workers in the health sector and related to the Authority) and collecting and analyzing the relationships using the statistical software package SPSS as well as various statistical methods, considering that the independent variable It is digital governance and the dependent variable is the sustainability of the comprehensive health insurance system. The most important governance mechanisms, including (internal audit systems / reward systems / transparent information system / system Information characterized by the disclosure of reports) in the comprehensive health insurance system, and between indicators of financial sustainability in general, with the need to enhance the use of governance in the digital business environment.

A comparison of sensitivity and specificity of dosimetry audits for intensity modulated radiation therapy used internationally for clinical trial credentialing.

The article addresses the issue of applying artificial intelligence (AI) technologies in the activities of university libraries as a foundation for sustainable development. Artificial intelligence is transforming library practice at all levels—from the automation of routine cataloguing processes, analysis of user queries, and management of electronic resources to the development of personalized information services and decision-support systems. Technologies such as machine learning, natural language processing (NLP), chatbots, and intelligent recommendation systems expand the functional capabilities of libraries, increase the efficiency of user services, facilitate deeper analysis of information flows, and contribute to the formation of a new quality of library services. At the same time, the relevance of integrating AI into library activities is determined by the need to maintain a balance between technological modernization and the humanistic essence of libraries. The implementation of intelligent systems requires a rethinking of librarians’ professional competencies, the development of digital and information literacy, and the establishment of ethical standards for AI use that ensure algorithmic transparency, protection of personal data, and the prevention of cognitive or social biases. In practical terms, these ethical principles are operationalized through internal governance frameworks, such as institutional AI policies that regulate data collection and processing, mandatory human oversight of algorithmic decision-making in reference and recommendation services, and regular audits of AI systems to identify and mitigate potential biases. Additionally, libraries increasingly adopt internal protocols for staff training and ethical review committees to ensure that AI applications align with professional values, user rights, and institutional accountability. From the perspective of sustainable development, the application of AI technologies in university libraries contributes to more efficient resource management, optimization of energy consumption, rational use of human potential, and the creation of a knowledge ecosystem oriented toward long-term stability and social responsibility. Libraries that implement intelligent technologies are able to provide more inclusive access to educational and research resources, support the principles of Open Science and digital equity, which are fundamental pillars of the sustainable development of the knowledge society. Keywords: artificial intelligence, university libraries, library digitalization, digital culture, sustainable development, digital technologies, digital library services

The effectiveness of public financial control depends not only on the quality of audit inspections and tax procedures but also on their coordination, transparency, digitalization, and analytical coherence. Under current conditions, audit should perform strategic, preventive, and analytical functions, while tax control should focus on ensuring the completeness of tax revenues, minimizing tax evasion risks, and strengthening public trust in the state’s fiscal policy. The article considers an integral approach to assessing the efficiency of interaction between audit and tax control based on the use of a multi-factor indicator system. This approach makes it possible to account not only for the quantitative results of inspections but also for qualitative aspects such as the level of implementation of audit recommendations, the degree of elimination of violations, the timeliness of tax revenues, and the influence of external factors, including the transparency of public finances, macroeconomic stability, and the scale of the shadow economy. According to the calculations conducted, the Integrated Efficiency Indicator of supervisory (IEC) amounted to 0.49 in 2023, which indicates a medium-low level of system effectiveness and highlights the need for deep structural reforms. The priority areas of reform include: establishing a unified information and analytical space for the exchange of inspection results among the State Services of Ukraine; strengthening the institutional independence of audit bodies; introducing risk-oriented approaches to inspection planning; enhancing the professional capacity of auditors and tax inspectors; and improving the regulatory framework in accordance with INTOSAI and IIA standards. This research contributes to the UN Sustainable Development Goals by confirming that the synergy between audit and tax control forms a stable foundation for fiscal policy, enhances the efficiency of public administration, reinforces macroeconomic balance, and ensures the economic resilience of the state under wartime and post-crisis challenges. Keywords: audit; digitalization; economic security; fiscal resilience; financial stability; integral control efficiency index; public financial transparency; risk-oriented approach; state financial control; tax control

Feasibility and limitations of a postal dosimetry audit system using RPLGD for high-dose-rate brachytherapy

Chronic respiratory diseases, including chronic obstructive pulmonary disease and asthma, pose substantial challenges to healthcare systems worldwide, which are projected to grow in coming years. Variations in care represent a threat to health equity and must be identified and remedied. Robust auditing systems can improve healthcare effectiveness and efficiency by identifying strengths and weaknesses in existing service models. The Australia New Zealand Respiratory Audit Programme (ANZRAP) is a new funded research and quality improvement programme commencing in 2025 aiming to improve quality of care, clinical outcomes and health service provision for people with respiratory illness across Australia and New Zealand. This paper describes the development, plans for implementation and likely outcomes of the ANZRAP.

Acute respiratory distress syndrome, associated with mortality rates as high as 30%, consumes substantial healthcare resources. Prone positioning has been proven to effectively improve patient oxygenation and reduce mortality. A recent analysis in our unit found the incidence of adverse events related to prone positioning care had increased by 20.4% over the previous year and that all of these events were associated with care provided by postgraduate-year-two (PGY2) nurses. A program was initiated to enhance knowledge and practical skills related to prone positioning care among PGY2 nurses in our unit with the goal of improving the average accuracy rates of both knowledge and skills to at least 85%. Program components included: prone care education combined with small-group teaching, producing instructional videos on prone positioning care, designing a prone care competency checklist, developing innovative simulation dolls for skill practice, establishing a regular auditing system for prone care, and organizing periodic in-person skill workshops. After program implementation, the average accuracy of prone care knowledge increased from 44.7% to 93.1% in PGY2 nurses and the average accuracy rate of related practical skills improved from 77.6% to 93.7% in the unit. Future prone positioning care education and skill assessments should be conducted regularly and incorporated into training programs provided to newly employed nurses. These measures should effectively strengthen the professional competency of intensive care nurses and improve overall patient care quality.

With tax socialization acting as a moderator, this study attempts to investigate the impact of a contemporary tax administration system and tax audits on taxpayer compliance (A Study on Corporate Taxpayers Registered at the Cibinong Pratama Tax Office in 2023). This work employs a quantitative methodology using SmartPLS 4.0 for structural equation modeling (SEM). Corporate taxpayers serve as the analytical unit. Purposive sampling was used to choose 99 corporate taxpayers from the population of 10,524 corporate taxpayers. A questionnaire was used to collect data. The study's findings show that taxpayer compliance is positively and significantly impacted by a contemporary tax administration system, tax audits, and tax socialization. Additionally, the impact of a contemporary tax administration system and tax audits on corporate taxpayer compliance reported with the Cibinong Pratama Tax Office in 2023 is positively and significantly moderated by tax socialization.

The study provides a comprehensive review of cybersecurity detection methods within Industry 4.0, focusing on enhancing system resilience and user trust. The research uses a qualitative approach to analyze nine case studies from Africa, Asia, and the West to identify key challenges, detection strategies,and region-specific insights.The findings emphasize the critical role of AI-driven and hybrid detection systems, which have proven effective in mitigating advanced cyber threats such as ransomware, distributed denial of service (DDoS), and false data injection attacks. Comparative analysis highlights common global challenges,including resource limitations,human-related vulnerabilities, and compliance issues, while addressing unique regional factors such as infrastructure gaps and evolving threat sophistication.The study proposes a cybersecurity taxonomy integrating machine learning, real-time anomaly detection, and adaptive threat response mechanisms for Industry 4.0 environments. Recommendations for practitioners include adopting AI-enhanced intrusion detection systems (IDS), implementing energy-efficient IoT security solutions, and conducting regular system audits. Policymakers are encouraged to mandate adherence to global cybersecurity standards, foster international collaboration, and invest in workforce capacity building initiatives. The review, therefore, strengthens global cybersecurity frameworks,improves organizational resilience, and fosters public trust in the secure integration of Industry 4.0 technologies.

This study investigates green industrial palm oil project cost performance determinants through Artificial Intelligence (AI)-based Architecture, Engineering, and Construction (AEC) systems. The study employed a Structural Equation Modeling Partial Least Squares (SEM-PLS) approach to analyze significant data collected from 115 respondents through 166 validated indicators. Ten primary drivers were identified, and alternative water sources topped the list, followed by indoor air quality auditing, green material, and smart metering systems, all of which were identified as primary cost-effectiveness drivers. Simulations of Green Mark certification levels (Gold, Gold Plus, and Platinum) indicated potential cost savings of 7.01% to 7.05%. The model continued to have very good predictive capability with an R² value of 0.791, testifying to the robustness of the methodology presented. The results validate the engineering value of AI-aided AEC in cost performance maximization and enhancement in eco-friendly industrial building. The findings also offer practical suggestions for design, planning, and execution of cost-saving, eco-friendly palm oil mills.

The rapid evolution of technology and the food industry has raised concerns about the accurate labelling of Halal food and meat authentication. The Halal authentication system maintains a zero-tolerance policy regarding the halal status of food products from farm to fork. As a result, innovative technologies such as recombinase polymerase amplification are necessary to address the growing issues of food fraud and enhance the current species identification method. Recombinase amplification method is an isothermal amplification process that operates at 37-42°C without the need for specialized equipment or technicians. A systematic review was conducted to analyse research on the application of Recombinase Amplification method in meat and Halal authentication, covering literature published from 2018 to 2024. Relevant studies were identified through a comprehensive search of established databases in which 25 studies met the inclusion criteria, focusing specifically on meat and Halal authentication, while studies related to clinical diagnostics and microbiological testing were excluded. This paper aims to analyse the various detection technologies integrated with Recombinase Polymerase Amplification (RPA) and to provide a comprehensive review of the application of RPA in meat and Halal authentication. The review will summarise current trends and evaluate the potential future developments and implications of RPA-based methods for establishing a reliable and rapid on-site auditing system.

HighlightsWhat are the main findings?A low-cost multimodal intervention was associated with increased composite hand hygiene compliance in a resource-limited ICU, from 63.1% to 82.0% over a four-week observation period.Sensitivity analysis excluding non-applicable moments demonstrated that pure adherence improved from 54.2% to 82.5%, confirming a genuine behavioral change rather than a measurement artifact.The largest gains occurred in awareness-dependent WHO moments targeted by the intervention (before touching the patient: +27.0 pp; after touching the patient’s surroundings: +40.0 pp), with smaller changes in non-targeted moments.Baseline pure adherence for high-risk moments involving body fluid exposure was substantially lower (12.2%) than that suggested by the primary compliance metric (80.0%), revealing how “compliant by default” scoring can mask poor performance in frequently non-applicable moments.What are the implications of the main findings?Pragmatic, workflow-embedded interventions utilizing education, visual cues, feedback, and leadership engagement can achieve measurable short-term compliance improvements without electronic monitoring or additional resources in resource-limited ICU settings.Episode-based audits with fixed denominators provide operationally feasible tools for directional process monitoring but should be complemented with sensitivity analyses reporting pure adherence to distinguish true behavioral changes from measurement artifacts.Long-term sustainability beyond the four-week observation period remains unknown; extended follow-up at 6–12 months is required to assess the persistence of improvements and the need for ongoing reinforcement.Background/Objective: Hand hygiene is a cornerstone of infection prevention; however, compliance is inconsistent in intensive care units (ICUs), particularly in resource-constrained settings. This study evaluated whether a low-cost, multimodal quality improvement intervention could improve process-level hand hygiene compliance using routine, episode-based audits embedded in the ICU practice. Methods: We conducted a single-cycle Plan-Do-Study-Act quality improvement project in a 12-bed mixed medical–surgical ICU in Pakistan (December 2023–January 2024). Hand hygiene performance was assessed using the unit’s routine weekly episode-based audit protocol, aligned with the WHO Five Moments framework. A targeted multimodal intervention comprising education, point-of-care visual reminders, audit feedback, and leadership engagement was implemented between the pre- and post-intervention phases (four weeks each). Non-applicable moments were scored as “compliant by default” according to the institutional protocol. A sensitivity analysis was performed excluding these moments to calculate pure adherence. Compliance proportions were summarized using exact 95% Clopper–Pearson confidence intervals without inferential testing. Results: A total of 942 audit episodes (471 per phase) generated 4710 moment-level assessments were generated. Composite hand hygiene compliance increased from 63.1% pre-intervention to 82.0% post-intervention [absolute increase: 18.9 percentage points (pp)]. Sensitivity analysis excluding non-applicable moments demonstrated pure adherence improvement from 54.2% to 82.5% (+28.3 pp), confirming a genuine behavioral change rather than a measurement artifact. Compliance improved across all five WHO moments, with the largest gains in awareness-dependent moments targeted by the intervention: before touching the patient (+27.0 pp) and after touching patient surroundings (+40.0 pp). Week-by-week compliance remained stable within both phases, without immediate post-intervention decay. Conclusions: A pragmatic, low-cost multimodal intervention embedded in routine ICU workflows was associated with substantial short-term improvements in hand hygiene compliance over a four-week observation period, particularly for awareness-dependent behaviors. Episode-based audit systems can support directional process monitoring in resource-limited critical care settings without the need for electronic surveillance. However, its long-term sustainability beyond one month and generalizability to other settings remain unknown. Sensitivity analyses are essential when using “compliant by default” scoring to distinguish adherence patterns from measurement artifacts.

This study aims to explain the influence of auditor competence, data trusworthinesst, and technology anxiety on audit judgment performance, with fraud risk assessment as an intervening variable. This study was conducted on internal auditors in Indonesian higher education institutions. This study uses Behavioral Decision Theory (BDT) and Technology-to-Performance Chain (TPC) model to explore how behavioral and technological factors interact to shape the cognitive process in assessing fraud risk and producing high-quality audit judgments. This study uses a questionnaire-based survey approach administered to internal auditors across Indonesian higher education institutions, resulting in 158 respondents. The proposed hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the relationships between constructs. The findings indicate that auditor competence and data trust have a positive influence on audit judgment performance, both directly and indirectly through an effective incident risk assessment process. This indicates the importance of professional skills and reliable digital audit data in supporting appropriate audit decisions. In contrast, technology anxiety does not influence fraud risk assessment, indicating that internal auditors have largely adapted to the use of digital audit systems. This study contributes to the audit literature by integrating the BDT and TPC models in the context of higher education internal audit and provides practical insights for governance and policymakers in strengthening internal audit performance in the digital transformation process.

This study investigates the clinical application and safety of Toosendan Fructus to provide evidence for its rational use in practice. A total of 3,925 outpatient prescriptions containing Toosendan Fructus were collected from January to December 2023 at Guangzhou Hospital of Integrated Chinese and Western Medicine. Data on patient demographics, diagnosis, department distribution, dosage, and herb combinations were analyzed. Among 2,951 patients, 1,697 were female (1.35 times that of male). Most patients (52.18%) were aged 19–44 years. The Liver disease department prescribed the most Toosendan Fructus (28.87%), primarily for liver stagnacy (22.52%). Stir-fried Toosendan Fructus was used in 95.18% of prescriptions, with 64.84% exceeding the Chinese Pharmacopoeia limit (>10 g). Common combinations included Paeoniae Radix Alba, Bupleuri Radix, and vinegar-processed Rhizoma Corydalis. Stir-frying and compatible use of Chinese materia medica can reduce the toxicity of Toosendan Fructus. However, an audit system for off-label use and enhanced medication monitoring are recommended to ensure clinical safety.