Search Results (459)

Purpose: Meningo-ophthalmic and orbitomeningeal arterial communications comprise route-specific relationships between the middle meningeal artery (MMA) and the ophthalmic or orbital arterial system. Their recognition is relevant to middle meningeal artery embolization because orbital or ophthalmic collateral pathways may create routes for non-target embolization. This systematic review aimed to synthesize the prevalence and anatomical patterns of these communications, using quantitative pooling only where the anatomical definition and denominator were sufficiently coherent. Methods: This systematic review and meta-analysis were conducted according to PRISMA 2020 principles and registered in PROSPERO (CRD420261361050). Eligible studies were original human cadaveric anatomical, angiographic, or radiological investigations reporting MMA-ophthalmic or MMA-orbital arterial relationships. After the closure of the full-text retrieval audit, studies and extracted rows were audited by anatomical family, unit of analysis, numerator, denominator, and independence. No global pooled prevalence was calculated across anatomical families. When family-specific pooling was methodologically defensible, proportions were synthesized using logit transformation, restricted maximum likelihood random-effects models, and Hartung-Knapp confidence intervals. Results: Database searches identified 558 records. After removal of 228 duplicates, 330 records were screened, and 285 were excluded by title and abstract. Forty-five reports were sought for retrieval; 10 were not retrieved or were not available as assessable full-text reports after retrieval auditing. Thirty-five full-text reports were assessed; thirteen were excluded for reasons, and three were duplicate reports at the full-text stage. Nineteen studies were included in the qualitative synthesis, and 12 contributed independent data to the final R-ready matrix. MMA arising from the ophthalmic artery was uncommon, with a pooled prevalence of 0.03 (95% CI 0.01 to 0.13; I² = 75.9%). After excluding the clinically selected chronic subdural hematoma subgroup, the estimate was 0.02 (95% CI 0.01 to 0.06; I² = 7.7%). The meningolacrimal/lacrimal-MMA route yielded an exploratory pooled proportion of 0.45 (95% CI 0.09 to 0.86; I² = 95.9%), with substantial anatomical and methodological heterogeneity. Conclusions: The available evidence supports route-specific synthesis rather than a single global prevalence estimate. MMA arising from the ophthalmic artery appears uncommon but procedurally important; however, this estimate should be interpreted as a route-specific estimate across eligible angiographic/anatomical series rather than as a universal anatomical prevalence. Meningolacrimal and lacrimal-MMA routes are frequently described, but their prevalence remains difficult to generalize because detection methods, populations, and denominators differ across studies. Future anatomical and angiographic reports should standardize route definitions, laterality, unit of analysis, and denominator reporting to improve prevalence estimation and procedural safety interpretation. Full article

Background/Objectives: Gastrointestinal (GI) symptoms, including abdominal pain, bloating, altered stool pattern, dyschezia, and nausea, are frequent in women with endometriosis and may persist despite conventional gynecological treatment. The low fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (low-FODMAP) diet is an established dietary intervention for irritable bowel syndrome. Its endometriosis-specific evidence base remains limited. This systematic review evaluated clinical evidence on the low-FODMAP diet or structured FODMAP restriction for GI symptoms in women with endometriosis. Methods: This systematic review was prospectively registered in PROSPERO (CRD420261388786) and conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. PubMed/MEDLINE, EBSCOhost, and BASE were searched from inception to 30 April 2026. Eligible reports were clinical studies investigating low-FODMAP diet or structured FODMAP restriction in women with confirmed, clinically diagnosed, imaging-based, or medically reported endometriosis and extractable GI or related clinical outcomes. Risk of bias was assessed with design-specific tools. Due to substantial heterogeneity across studies in design, comparators, and outcome measures, a narrative synthesis was performed. Results: Five clinical reports met the inclusion criteria: one randomized controlled crossover feeding trial, two prospective non-randomized studies, one retrospective audit of prospectively collected clinic data, and one case report. The randomized trial showed greater GI response during a 28-day low-FODMAP feeding period than during a nutritionally matched control diet. Prospective studies reported improvements in selected GI symptoms, constipation, pain, and quality-of-life domains, but interpretation was limited by non-randomized allocation, attrition, and mixed or pooled diet comparisons. The retrospective audit and case report supported clinical plausibility but were hypothesis-generating. Conclusions: The five available studies, though limited in number and design, indicate that a low-FODMAP diet can reduce GI symptoms in women with endometriosis, particularly those with abdominal pain, bloating, constipation, or IBS-like symptoms. Currently, the low-FODMAP diet should be viewed as a potentially useful, dietitian-guided GI symptom intervention for selected patients. Future trials should define responder profiles, assess long-term tolerability and nutritional safety, and determine the added value of reintroduction and personalization beyond short-term restriction. Full article

This study investigates whether the March 2023 failure of Silicon Valley Bank (SVB) coincided with changes in market-risk exposure, abnormal returns, and return connectedness among five major Chinese financial institutions. Using daily data from January 2022 to December 2023, we apply CAPM and market-model regressions, structural-break tests, event-study methods, and generalized forecast-error variance decompositions. The revised design distinguishes 10 March from the first subsequent Chinese trading day, 13 March, and adds symmetric event windows, placebo tests, an alternative risk-free rate, return-series audits, significance tests, and VAR diagnostics. Full-sample Chow tests identify breaks for ICBC and CITIC Securities, but only ICBC remains significant within the ±60-day window, and none are significant within ±30 days. Only ICBC records a significant positive CAR over [−3, +3]. Overall connectedness falls from 55.53% to 47.98%, while CITIC Securities becomes the largest post-event net transmitter. The evidence therefore indicates selective repricing and reconfigured linkages rather than a system-wide effect, and does not support unique causal attribution to SVB. Full article

The application of Internet of Things (IoT) technology to Digital Twin (DT) in smart manufacturing has opened significant opportunities for real-time monitoring, predictive maintenance, and closed-loop control; however, the inherent latency that exists in these architectures (the temporal gap between a physical event and its reflection in a digital model) remains one of the most significant and least systematically understood barriers to fulfill its full potential. This paper aims to propose a formal four-layer taxonomy of latency sources in IoT-based Digital Twin systems for smart manufacturing and to review the current approaches and tools that are available for their measurement. The PRISMA protocol has been used to perform a systematic literature review, where 58 primary survey studies published between 2020 and 2026 were extracted from IEEE Xplore, Elsevier Scopus, Google Scholar and arXiv, with all the studies being coded along six dimensions (architectural layer, application domain, latency metrics reported, evaluation methodology, quantitative impact, and enabling technologies). The proposed taxonomy presents 28 different types of latencies under four layers: (L1) network, (L2) compute, (L3) data, and (L4) end-to-end (E2E), whose magnitudes vary from 0.1 ms for local network propagation to tail latencies above 500 ms in production (P99). Three categories and three cross-layer interaction patterns are formalized here and are absent from prior partial taxonomies. Among the most promising results is the finding that several high-impact interventions require no infrastructure investment: a protocol migration from Modbus to WebSocket reduces telemetry latency by 32%, while Age of Information-aware synchronization and clock drift correction deliver substantial data layer gains through software updates alone, yet remain underutilized. The review identifies a systematic under-reporting of tail-latency percentiles across the corpus, the lack of a cross-protocol jitter benchmark, and a predominance of simulation-based evaluation over real-hardware measurement. The systematic review contributions of this paper (the formal four-layer taxonomy, the proportional metric audit across the 58 papers, and the formalization of three cross-layer interaction patterns) are derived from cross-corpus analysis. The investigation also identifies three open research directions (a standardized manufacturing IoT-DT benchmark, cross-layer joint optimization frameworks, and wireless TSN validation on real manufacturing testing grounds) that together form a well-organized and practical basis to advance both the science and the application of ultra-low-latency Digital Twin technology in the industrial field. Full article

In recent years, artificial intelligence (AI) has been increasingly used in criminal justice systems across the world. To achieve objectives set out through Sustainable Development Goals (SDGs), adoption of technology is inevitable and undeniable. The press release dated 25 February 2025 from India’s Ministry of Law and Justice, quoting Prime Minister of India Narendra Modi to make a “justice system that will be fully future-ready”, confirmed that the Indian law enforcement agencies are integrating AI into policing and law enforcement to enhance crime detection, criminal investigation, etc. It is intended to enhance their capabilities in solving criminal cases and delivering justice speedily and more efficiently. However, the usage of AI tools in such contexts presents a double-edged sword, as evidenced by their application in a number of cases across the world like Christopher Gatlin, Nijeer Parks, the Harm Assessment Risk Tool (HART), and in India during the 2020 Delhi riots cases. As reported by the Washington Post, in Christopher Gatlin’s case it was found that the police arrested him on the basis of the facial recognition programme matching his face with the captured video footage. He spent 17 months in jail before his release by the court, observing that the police failed to conduct fair investigation. A similar incident was reported by NJ.com and CNN Business. In the investigations following the 2020 Delhi riots, Delhi Police effected over 1900 arrests in 758 riot-related cases, relying predominantly on AI-driven facial recognition matches. Subsequent court scrutiny in decided cases raised questions about reliability, leading to widespread acquittals and discharges of the accused in 82% of decided cases as of early 2025. In certain cases, AI-driven solutions have failed, leading to criminal prosecutions of innocent people based on AI-generated evidence. This study examines the reliability, validity, and ethics of AI technology in the criminal justice system in India’s unique socio-legal and political environment. The researchers analyse three interrelated axes. First, a comprehensive review of the international algorithmic policing literature to identify successes and failures. In addition, cases of AI-assisted investigations during the Delhi riots show how facial recognition systems and other AI techniques were used for inquiry. Finally, stakeholders’ perspectives, including a preliminary survey of 27 legal experts showing strong consensus on classifying AI-FRT outputs strictly as corroborative evidence and highlighting BSA insufficiencies for addressing opacity and explainability, help identify practical, procedural, and normative fault lines. Researchers noted that while AI has the potential to revolutionise resource-constrained investigative agencies, its unquestioning and uncritical adoption risks amplify pre-existing biases, undermine presumptions of innocence, and shift the burden of refuting algorithmic inference onto the accused. Independent algorithmic audits, transparent documentation of error rates and confidence thresholds, statutory guidelines on AI tool use and admissibility, and sustained capacity-building throughout the justice delivery chain are needed to integrate it into the Indian criminal justice system. Without such measures, the very tools designed and introduced to enhance accuracy threaten to undermine the fundamental norms of the criminal justice system such as fairness and due process. This fills a gap in doctrinal analysis of AI-specific evidentiary admissibility in non-Western contexts like India. This study aims to propose policy reforms, enhance judicial discourse, and promote a more circumspect trajectory for AI adoption in Indian law enforcement by mapping the potential and risks of algorithmic evidence in a non-Western legal order. Full article

This research aims to assess the degree of risk disclosure practices in the Jordanian corporate sector and to examine the influence of critical audit quality dimensions—specifically audit opinion, audit fees, and auditor type—on the amount of corporate risk disclosure (CRD). The research examines 90 annual reports from Jordanian non-financial publicly traded companies from 2014 to 2023, resulting in 900 firm-year observations. A manual content analysis method was used to quantitatively assess the degree of risk disclosure, supplemented by logistic regression to analyze the influence of audit quality indicators. The empirical data indicate that the quantity of risk disclosure statements differs across businesses, spanning from 2 to 10 words, with a mean of 24 sentences. Furthermore, the findings indicate that characteristics influencing audit quality—specifically unqualified audit opinions, elevated audit fees, and Big Four auditors—exhibit a positive and substantial correlation with increased levels of risk disclosure. This indicates that enhanced audit quality elevates the legitimacy and openness of company reporting, thus reducing information asymmetry between management and stakeholders. Previous research on risk disclosure in Jordan has mostly neglected the influence of audit quality as a factor in transparency. This study is among the few that thoroughly investigate the impact of audit opinion, audit fees, and auditor type on company risk disclosure within the non-financial sector. The results underscore the essential importance of audit quality in improving monitoring and disclosure processes, thereby enriching the existing literature on corporate governance and risk reporting in developing economies. Full article

Background: Timely admission to a specialised burn unit is considered crucial for optimising outcomes in burn patients. However, the impact of delayed admission on hospital length of stay and clinical outcomes remains unclear, particularly in resource-constrained settings such as South Africa. This retrospective study aimed to determine whether admission to a burn unit more than 24 h after injury was associated with increased length of stay, sepsis, or mortality. Methods: A retrospective case-audit study was conducted at the Chris Hani Baragwanath Academic Hospital Adult Burn Unit, Johannesburg, from January 2018 to December 2022. Patients were categorised into early (≤24 h) and delayed (>24 h) admission groups. The primary outcome was length of stay; secondary outcomes included sepsis incidence and in-hospital mortality. Results: A total of 123 files were analysed; 71 (58%) were admitted within 24 h. The median length of stay was 14 days, with no statistical difference between the two groups (p = 0.7). The overall mortality rate was 13%, with 68% occurring in the early admission group. Sepsis occurred in 27% of patients. Multivariate analysis revealed that early admission was independently associated with longer length of stay. Conclusions: In this single-centre retrospective case note audit with a limited sample size and significant risk of selection bias, delayed admission to a burn unit was not associated with increased length of stay, mortality, or sepsis. However, these findings should be considered preliminary and require confirmation in larger, prospective studies. The higher rate of surgical intervention in the delayed admission group warrants further investigation. Full article

Enterprise Resource Planning (ERP) systems have long served as the primary infrastructure for internal control in financial governance, functioning as deterministic, auditable systems of record. The emergence of Zero-Trust Architecture (ZTA) and artificial intelligence (AI) progressively challenges this model, transforming enterprise systems from passive ledgers into autonomous systems of judgment capable of influencing decisions with direct financial and regulatory consequences. This study investigates how trust mediates this transformation. Drawing on a longitudinal dataset of 968 survey responses collected across five measurement waves during a ZTA deployment in a multinational telecommunications organization, we apply an extended Technology Acceptance Model (TAM) to examine changes in perceived usefulness, ease of use, and trust. The findings reveal an Audit Paradox: ZTA simultaneously strengthens formal compliance controls while eroding user trust and perceived productivity, with only partial recovery following structured governance interventions. Building on these findings, we introduce a trust-contingent framework for ERP evolution and develop the concept of the Agency Gap, a structural misalignment between algorithmic decision-making authority and institutional accountability. This study extends accounting and auditing theory into AI-driven control environments and offers practical guidance for auditors, CFOs, and technology leaders navigating the governance of increasingly autonomous digital systems. This study contributes by empirically demonstrating the trust-mediated dynamics of advanced control architectures, introducing the Agency Gap as a theoretical construct addressing algorithmic accountability in AI-driven governance, and extending Sarbanes–Oxley (SOX) oriented control theory into probabilistic, algorithmic environments. Full article

Following the global financial crisis, the transition to IFRS 9’s forward-looking Expected Credit Loss (ECL) model has introduced significant implementation complexity, particularly in emerging markets facing data limitations. This study investigates the heterogeneous ECL compliance strategies adopted within the Cambodian banking sector during a period of heightened credit stress, marked by a system-wide non-performing loan ratio of 8.6%. Utilizing a multiple-case study design and replication logic, a qualitative content analysis was conducted on the 2024 audited financial statements of 13 representative institutions, ranging from market leaders to international subsidiaries. The findings reveal a pronounced technical divide: market leaders utilize advanced internal statistical methods, such as cohort analysis, whereas international subsidiaries rely on top-down parent-group proxy models to bridge local data gaps. A “macro-correlation paradox” was identified, where certain institutions prioritize faithful representation by excluding macroeconomic variables when statistical links to historical defaults remain weak. Furthermore, a significant transparency gap exists, where granular disclosures are consistent with a signaling interpretation regarding institutional safety. These results suggest that ECL compliance in data-limited environments may be interpreted as a strategic management choice rather than a standardized technical exercise, highlighting the need for regulatory standardization of modeling assumptions to improve inter-bank comparability. Full article

As global markets navigate the dual transition of digitalization and sustainability, the risk of “digital greenwashing” has emerged as a critical corporate governance challenge. Utilizing a comprehensive dataset of Chinese A-share listed firms from 2018 to 2024—an ideal laboratory characterized by rapid regulatory shifts and unique state-market dynamics that provide highly generalizable insights for other emerging economies—this study empirically investigates whether corporate digital transformation acts as a genuine driver for Environmental, Social, and Governance (ESG) enhancement or merely serves as a symbolic disclosure tool. Fortified by rigorous identification strategies, including Propensity Score Matching and Lewbel heteroskedasticity-based instrumental variable estimations, the results confirm that digitalization serves as an incremental yet statistically significant driver for corporate sustainability. Crucially, mechanism analyses reveal a “full moderation” effect: the positive impact of digitalization on ESG performance is completely activated only in the presence of premium external assurance (e.g., Big 4 audits). Without high-quality IT auditing to act as a credibility enforcer and verify the substance of digital signals, technological adoption alone fails to yield significant ESG improvements. Furthermore, a nuanced structural asymmetry is identified: foundational data infrastructures (Cloud Computing and Big Data) directly enhance quantifiable Environmental and Governance metrics, whereas premium audits are strictly required to activate the “soft,” qualitative Social dimension. Finally, the synergy exhibits distinct boundary conditions. It is heavily concentrated within high-pollution industries where digital transition acts as a regulatory survival imperative rather than mere market expansion, and its reliance on external assurance is fundamentally driven by the market-signaling needs of non-State-Owned Enterprises (non-SOEs) rather than the policy-distorted mandates of SOEs. These findings offer critical theoretical extensions and policy implications for standardizing digital-audit infrastructures globally. Full article

This study investigates product abuse, reconciliation challenges, and cybersecurity risks in warehouse management systems (WMS) within increasingly digitized supply chain environments. As warehouses evolve into data-driven operational hubs, vulnerabilities such as data manipulation, insider threats, and fraudulent activities pose significant risks to financial accountability and system integrity. To address these challenges, this research proposes a security-centric WMS framework that integrates blockchain-based immutable logging, Internet of Things (IoT)-enabled tracking, and artificial intelligence (AI)-driven anomaly detection. The methodology follows a hybrid iterative–incremental development approach, supported by real-world deployment of a prototype WMS implemented using a scalable microservices architecture. Over a five-year operational period, the system processed more than 10 million transactions with no recorded successful cybersecurity incidents leading to data breaches, operational compromise, or unauthorized system access, while achieving improvements in reconciliation accuracy, operational efficiency, and fraud detection capabilities. Results demonstrate reductions in manual reconciliation efforts, mispricing incidents, and operational losses, while maintaining high system availability and low latency. In addition, the reported 18–22% improvement associated with AI-assisted anomaly detection is presented as a simulation-based projection rather than a production-validated measurement. The findings indicate that combining secure software engineering practices with automation, auditability, and advanced analytics can significantly enhance transparency and resilience in warehouse operations. The study concludes that integrating decentralized and intelligent technologies provides a viable pathway toward secure, privacy-preserving, and abuse-resistant warehouse ecosystems. Full article

This study investigates the interplay of internal audit system, cultural complexity and corruption control in Ghana’s state-owned enterprises (SOEs), examining how these factors influence anti-corruption efforts. Employing a quantitative and cross-sectional survey design, we gather data from 1150 internal auditors and use EFA, descriptive statistics and macro-process modeling for analysis. The results show that internal audit effectiveness, quality, independence, and resources are all positively related to corruption control (prevention, detection and response), with internal audit independence having the greatest effect on corruption control. Power distance culture (PDC) moderates these relationships, but the direction and significance of the moderation vary across the different aspects of corruption control. This study highlights the importance of strengthening internal audit system and addressing cultural barriers to enhance corruption control in SOEs, informing governance strategies in emerging economies. It has demonstrated that PDC plays a complex role in shaping the effectiveness of internal audit system in controlling corruption. Thus, this research contributes to the limited literature on the intersection of internal audit, PDC and corruption control in a developing country context, offering insights for policymakers and practitioners. Full article

This study aims to investigate the greenhouse gas (GHG) emissions and environmental footprint of BOCOM Petroleum, a mid-sized downstream oil company operating in Douala, Cameroon. In response to the critical need for empirical data on industrial emissions in Sub-Saharan Africa, a mixed-methods approach combining Life Cycle Assessment (LCA), carbon accounting, and stakeholder interviews was adopted. Emissions were categorised following the GHG Protocol into Scope 1 (direct), Scope 2 (energy-related), and Scope 3 (value chain). Results reveal total annual emissions of 51,734 CO₂, kg/year, with Scope 3 accounting for 38%, Scope 2 for 33%, and Scope 1 for 29%. Major emission sources include stationary combustion, laboratory processes, and the use of electricity-intensive heat-generating machines. An Environmental Management Plan (EMP) was developed, proposing actionable measures such as process optimisation, adoption of energy-efficient equipment, electrification of vehicle fleets, and improved waste management. Findings underscore the need for systemic decarbonisation strategies among mid-sized oil firms and highlight the alignment of corporate initiatives with Cameroon’s climate commitments. This study contributes a replicable methodological framework for emission auditing in industrial enterprises across the region and calls for further integration of environmental and financial planning in corporate sustainability strategies. Full article

Environmental, Social, and Governance (ESG) performance has become critical for businesses seeking transparency, sustainability, and stakeholder confidence. However, the extant evidence is equivocal regarding its influence on company performance. Corporate governance may play an important role in determining the efficacy of ESG efforts. Hence, this research investigates the relationship between corporate governance and firm performance, focusing on the moderating role of ESG performance, using unbalanced panel data from 370 Malaysian firms for the period from 2012 to 2023. For analysis of the data, fixed effects estimation, Driscoll–Kraay robust standard errors, and a subsample analysis were used. The results reveal that board expertise and independence enhance firm performance, whereas board gender diversity negatively affects market valuation (Tobin’s Q). Similarly, audit committee expertise shows a negative effect. Further, the results reveal that ESG strengthens the role of board expertise but weakens the influence of audit committee independence. This study offers practical and theoretical insights for policymakers, scholars, and stakeholders seeking to balance sustainability with financial performance, bridging a notable gap in the literature by thoroughly examining the relationship between board gender diversity and ESG performance, and how it affects company performance. This reveals new insights into the strategic significance of diverse leadership in promoting both financial and non-financial results by bridging the gap between corporate governance and sustainability. Full article

Earnings management undermines financial transparency and threatens long-term corporate sustainability, particularly in emerging markets where principal–agent conflicts remain pronounced. In China’s capital market, performance-based incentives may motivate managers to manipulate reported earnings, thereby impairing investor protection and governance quality. Despite growing interest in enterprise risk management (ERM) as a holistic governance mechanism, empirical evidence on its effectiveness in constraining earnings manipulation remains limited. This paper investigates the governance role of ERM in mitigating both accrual-based earnings management (AEM) and real earnings management (REM) among Chinese listed firms over the period 2019–2024. Using panel regression models, this study examines whether higher ERM engagement is associated with lower levels of earnings manipulation. The results indicate that ERM is significantly and negatively related to both AEM and REM. These findings remain robust to alternative variable definitions, different sample period specifications, interaction analyses between accrual-based and real earnings management, alternative constructions of ERM (including PCA-based measures and exclusion of reporting-related components), and endogeneity tests using industry–year average ERM as a proxy. Further heterogeneity analyses reveal that the constraining effect of ERM on REM is more pronounced in firms audited by non-Big Four auditors, while the effect is weaker in Big Four audited firms. Overall, the evidence suggests that ERM functions as an effective internal governance mechanism that enhances financial reporting quality and supports sustainable corporate performance. This paper contributes to the sustainability and corporate governance literature by providing empirical evidence from an emerging market context and offers practical implications for regulators and corporate decision-makers seeking to strengthen risk governance frameworks. Full article